title:
High-frequency measurements of aeolian saltation flux: Field-based
  methodology and applications

abstract:
  Aeolian transport of sand and dust is driven by turbulent winds that
fluctuate over a broad range of temporal and spatial scales. However, commonly
used aeolian transport models do not explicitly account for such fluctuations,
likely contributing to substantial discrepancies between models and
measurements. Underlying this problem is the absence of accurate sand flux
measurements at the short time scales at which wind speed fluctuates. Here, we
draw on extensive field measurements of aeolian saltation to develop a
methodology for generating high-frequency (25 Hz) time series of total
(vertically-integrated) saltation flux, namely by calibrating high-frequency
(HF) particle counts to low-frequency (LF) flux measurements. The methodology
follows four steps: (1) fit exponential curves to vertical profiles of
saltation flux from LF saltation traps, (2) determine empirical calibration
factors through comparison of LF exponential fits to HF number counts over
concurrent time intervals, (3) apply these calibration factors to subsamples of
the saltation count time series to obtain HF height-specific saltation fluxes,
and (4) aggregate the calibrated HF height-specific saltation fluxes into
estimates of total saltation fluxes. When coupled to high-frequency
measurements of wind velocity, this methodology offers new opportunities for
understanding how aeolian saltation dynamics respond to variability in driving
winds over time scales from tens of milliseconds to days.


title:
How do future expectations affect the financial sector? Expectations
  modeling, infinite horizon (controlled) random FBSDEs and stochastic
  viscosity solutions

abstract:
  In this paper we study a class of infinite horizon fully coupled
forward-backward stochastic differential equations (FBSDEs), that are
stimulated by various continuous time future expectations models with random
coefficients. Under standard Lipschitz and monotonicity conditions, and by
means of the contraction mapping principle, we establish existence, uniqueness,
a comparison property and dependence on a parameter of adapted solutions.
Making further the connection with infinite horizon quasilinear backward
stochastic partial differential equations (BSPDEs) via a generalization of the
well known four-step-scheme, we are led to the notion of stationary stochastic
viscosity solutions. A stochastic maximum principle for the optimal control
problem of such FBSDEs is also provided as an application to this framework.


title: Invariance of certain plurigenera for surfaces in mixed characteristics

abstract:
  We prove the deformation invariance of Kodaira dimension and of certain
plurigenera for log surfaces which are smooth over a DVR.


title:
Limit theorems for local and occupation times of random walks and
  Brownian motion on a spider

abstract:
  A simple random walk and a Brownian motion are considered on a spider that is
a collection of half lines (we call them legs) joined in the origin. We give a
strong approximation of these two objects and their local times. For fixed
number of legs we establish limit theorems on local and occupation times in n
steps.


title: Highly variable young massive stars in ATLASGAL clumps

abstract:
  High-amplitude variability in Young Stellar Objects (YSOs) is usually
associated with episodic accretion events. It has not been observed so far in
massive YSOs. Here, the high-amplitude variable star sample of
ContrerasPe\~{n}a et al.(2016) has been used to search for
highly-variable($\Delta$K$\ge$1\,mag) sources coinciding with dense clumps
mapped using the 850\mum continuum emission by the ATLASGAL survey. 18 variable
sources are centred on the sub-mm clump peaks, and coincide ($<$1") with a
24$\mu$m point or compact ($<$10") source. 13 of these 18 sources can be fit by
YSO models. The 13 variable YSOs(VYSO) have luminosities of $\sim$10$^3$
L$_{\odot}$, an average mass of 8 M$_{\odot}$ and a range of ages up to 10$^6$
yr. 11 of these 13 VYSOs are located in the midst of infrared dark clouds. 9 of
the 13 sources have $\Delta$K$>$2 mag, significantly higher compared to the
mean variability of the entire VVV sample. The light curves of these objects
sampled between 2010-2015 display rising, declining, or quasi-periodic
behaviour but no clear periodicity. Light-curve analysis using Plavchan method
show that the most prominent phased signals have periods of a few hundred days.
The nature and time-scale of variations found in 6.7 Ghz methanol maser
emission (MME) in massive stars are similar to that of the VYSO light curves.
We argue that the origin of the observed variability is episodic accretion. We
suggest that the timescale of a few hundred days may represent the frequency at
which a spiralling disk feeds dense gas to the young massive star.


title:
Some results on counting roots of polynomials and the Sylvester
  resultant

abstract:
  We present two results, the first on the distribution of the roots of a
polynomial over the ring of integers modulo $n$ and the second on the
distribution of the roots of the Sylvester resultant of two multivariate
polynomials. The second result has application to polynomial GCD computation
and solving polynomial diophantine equations.


title:
Multi-physics simulations of lithiation-induced stress in Li$_{\rm
  1+x}$Ti$_2$O$_4$ electrode particles

abstract:
  Cubic spinel Li$_{\rm 1+x}$Ti$_2$O$_4$ is a promising electrode material as
it exhibits a high lithium diffusivity and undergoes minimal changes in lattice
parameters during lithiation and delithiation, thereby ensuring favorable
cycleability. The present work is a multi-physics and multi-scale study of
Li$_{\rm 1+x}$Ti$_2$O$_4$ that combines first principles computations of
thermodynamic and kinetic properties with continuum scale modeling of
lithiation-delithiation kinetics. Density functional theory calculations and
statistical mechanics methods are used to calculate lattice parameters, elastic
coefficients, thermodynamic potentials, migration barriers and Li diffusion
coefficients. These quantities then inform a phase field framework to model the
coupled chemo-mechanical evolution of electrode particles. Several case studies
accounting for either homogeneous or heterogeneous nucleation are considered to
explore the temporal evolution of maximum principle stress values, which serve
to indicate stress localization and the potential for crack initiation, during
lithiation and delithiation.


title: Nonlinear damping and dephasing in nanomechanical systems

abstract:
  We present a microscopic theory of nonlinear damping and dephasing of
low-frequency eigenmodes in nano- and micro-mechanical systems. The mechanism
of the both effects is scattering of thermally excited vibrational modes off
the considered eigenmode. The scattering is accompanied by energy transfer of
$2\hbar\omega_0$ for nonlinear damping and is quasieleastic for dephasing. We
develop a formalism that allows studying both spatially uniform systems and
systems with a strong nonuniformity, which is smooth on the typical wavelength
of thermal modes but not their mean free path. The formalism accounts for the
decay of thermal modes, which plays a major role in the nonlinear damping and
dephasing. We identify the nonlinear analogs of the Landau-Rumer,
thermoelastic, and Akhiezer mechanisms and find the dependence of the
relaxation parameters on the temperature and the geometry of a system.


title: Transforming how water is managed in the West

abstract:
  California is challenged by its worst drought in 600 years and faces future
water uncertainty. Pioneering new data infrastructure to integrate water use
data across California's more than a thousand water providers will support
water managers in ensuring water reliability. The California Data Collaborative
is a coalition of municipal water utilities serving ten percent of California's
population who are delivering on that promise by centralizing customer water
use data in a recently completed pilot project. This project overview describes
tools that have shown promising early results in improving water efficiency
programs and optimizing system operations. Longer term, these tools will help
navigate future uncertainty and support water managers in ensuring water
reliability no matter what the future holds. The uniquely publicly-owned data
infrastructure deployed in this project is envisioned to enable the world's
first "marketplace of civic analytics" to power the volume of water efficiency
measurements water managers require at a radically more cost effective price.
More broadly, this data-utility approach is adaptable to domains other than
water and shows specific potential for the broader universe of natural
resources.


title:
Access to Taxicabs for Unbanked Households: An Exploratory Analysis in
  New York City

abstract:
  Taxicabs are a critical aspect of the public transit system in New York City.
The yellow cabs that are ubiquitous in Manhattan are as iconic as the city's
subway system, and in recent years green taxicabs were introduced by the city
to improve taxi service in areas outside of the central business districts and
airports. Approximately 500,000 taxi trips are taken daily, carrying about
800,000 passengers, and not including other livery firms such as Uber, Lyft or
Carmel. Since 2008 yellow taxis have been able to process fare payments with
credit cards, and credits cards are a growing share of total fare payments.
However, the use of credit cards to pay for taxi fares varies widely across
neighborhoods, and there are strong correlations between cash payments for taxi
fares and the presence of unbanked or underbanked populations. These issues are
of concern for policymakers as approximately ten percent of households in the
city are unbanked, and in some neighborhoods the share of unbanked households
is over 50 percent. In this paper we use multiple datasets to explore taxicab
fare payments by neighborhood and examine how access to taxicab services is
associated with use of conventional banking services. There is a clear spatial
dimension to the propensity of riders to pay cash, and we find that both
immigrant status and being 'unbanked' are strong predictors of cash
transactions for taxicabs. These results have implications for local
regulations of the for-hire vehicle industry, particularly in the context of
the rapid growth of services that require credit cards. Without some type of
cash-based payment option taxi services will isolate certain neighborhoods. At
the very least, existing and new providers of transit services must consider
access to mainstream financial products as part of their equity analyses.


title:
Modeling quantum cascade lasers: Coupled electron and phonon transport
  far from equilibrium and across disparate spatial scales

abstract:
  Quantum cascade lasers (QCLs) are high-power coherent light sources in the
midinfrared and terahertz parts of the electromagnetic spectrum. They are
devices in which the electronic and lattice systems are far from equilibrium,
strongly coupled to one another, and the problem bridges disparate spatial
scales. We present our ongoing work on the multiphysics and multiscale
simulation of far-from-equilibrium transport of charge and heat in midinfrared
QCLs.


title: No Conclusive Evidence for Transits of Proxima b in MOST photometry

abstract:
  The analysis of Proxima Centauri's radial velocities recently led
Anglada-Escud\'e et al. (2016) to claim the presence of a low mass planet
orbiting the Sun's nearest star once every 11.2 days. Although the a-priori
probability that Proxima b transits its parent star is just 1.5%, the potential
impact of such a discovery would be considerable. Independent of recent radial
velocity efforts, we observed Proxima Centauri for 12.5 days in 2014 and 31
days in 2015 with the MOST space telescope. We report here that we cannot make
a compelling case that Proxima b transits in our precise photometric time
series. Imposing an informative prior on the period and phase, we do detect a
candidate signal with the expected depth. However, perturbing the phase prior
across 100 evenly spaced intervals reveals one strong false-positive and one
weaker instance. We estimate a false-positive rate of at least a few percent
and a much higher false-negative rate of 20-40%, likely caused by the very high
flare rate of Proxima Centauri. Comparing our candidate signal to HATSouth
ground-based photometry reveals that the signal is somewhat, but not
conclusively, disfavored (1-2 sigmas) leading us to argue that the signal is
most likely spurious. We expect that infrared photometric follow-up could more
conclusively test the existence of this candidate signal, owing to the
suppression of flare activity and the impressive infrared brightness of the
parent star.


title: An experimental investigation of Neumann's conjecture

abstract:
  We use a large census of hyperbolic 3-manifolds to experimentally investigate
a conjecture of Neumann regarding the Bloch Group. We present an augmented
census including, for feasible invariant trace fields, explicit manifolds
(associated to that field) that appear to generate the Bloch group of that
field. We also make use of Ptolemy coordinates to compute "exotic volumes" of
representations, and attempt to realize these volumes as linear combinations of
generator volumes. We thus present a large body of empirical support for
Neumann's conjecture.


title:
Slicing the stars: counting algebraic numbers, integers, and units by
  degree and height

abstract:
  Masser and Vaaler have given an asymptotic formula for the number of
algebraic numbers of given degree $d$ and increasing height. This problem was
solved by counting lattice points (which correspond to minimal polynomials over
$\mathbb{Z}$) in a homogeneously expanding star body in $\mathbb{R}^{d+1}$. The
volume of this star body was computed by Chern and Vaaler, who also computed
the volume of the codimension-one "slice" corresponding to monic polynomials --
this led to results of Barroero on counting algebraic integers. We show how to
estimate the volume of higher-codimension slices, which allows us to count
units, algebraic integers of given norm, trace, norm and trace, and more. We
also refine the lattice point-counting arguments of Chern-Vaaler to obtain
explicit error terms with better power savings, which lead to explicit versions
of some results of Masser-Vaaler and Barroero.


title: Chow rings of versal complete flag varieties

abstract:
  In this paper, we compute Chow rings of generically twisted (versal) complete
flag varieties corresponding to simple Lie groups


title: Solving polynomial systems via homotopy continuation and monodromy

abstract:
  We study methods for finding the solution set of a generic system in a family
of polynomial systems with parametric coefficients. We present a framework for
describing monodromy based solvers in terms of decorated graphs. Under the
theoretical assumption that monodromy actions are generated uniformly, we show
that the expected number of homotopy paths tracked by an algorithm following
this framework is linear in the number of solutions. We demonstrate that our
software implementation is competitive with the existing state-of-the-art
methods implemented in other software packages.


title: Cut Tree Construction from Massive Graphs

abstract:
  The construction of cut trees (also known as Gomory-Hu trees) for a given
graph enables the minimum-cut size of the original graph to be obtained for any
pair of vertices. Cut trees are a powerful back-end for graph management and
mining, as they support various procedures related to the minimum cut, maximum
flow, and connectivity. However, the crucial drawback with cut trees is the
computational cost of their construction. In theory, a cut tree is built by
applying a maximum flow algorithm for $n$ times, where $n$ is the number of
vertices. Therefore, naive implementations of this approach result in cubic
time complexity, which is obviously too slow for today's large-scale graphs. To
address this issue, in the present study, we propose a new cut-tree
construction algorithm tailored to real-world networks. Using a series of
experiments, we demonstrate that the proposed algorithm is several orders of
magnitude faster than previous algorithms and it can construct cut trees for
billion-scale graphs.


title: Hausdorff dimension of the set approximated by irrational rotations

abstract:
  Let $\theta$ be an irrational number and $\varphi: {\mathbb N} \to {\mathbb
R}^{+}$ be a monotone decreasing function tending to zero. Let
$$E_\varphi(\theta) =\Big\{y \in \mathbb R: \|n\theta- y\|<\varphi(n), \
{\text{for infinitely many}}\ n\in {\mathbb N} \Big\}, $$ i.e. the set of
points which are approximated by the irrational rotation with respect to the
error function $\varphi(n)$. In this article, we give a complete description of
the Hausdorff dimension of $E_\varphi(\theta)$ for any monotone function
$\varphi$ and any irrational $\theta$.


title: An adaptable generalization of Hotelling's $T^2$ test in high dimension

abstract:
  We propose a two-sample test for detecting the difference between mean
vectors in a high-dimensional regime based on a ridge-regularized Hotelling's
$T^2$. To choose the regularization parameter, a method is derived that aims at
maximizing power within a class of local alternatives. We also propose a
composite test that combines the optimal tests corresponding to a specific
collection of local alternatives. Weak convergence of the stochastic process
corresponding to the ridge-regularized Hotelling's $T^2$ is established and
used to derive the cut-off values of the proposed test. Large sample properties
are verified for a class of sub-Gaussian distributions. Through an extensive
simulation study, the composite test is shown to compare favorably against a
host of existing two-sample test procedure in a wide range of settings. The
performance of the proposed test procedure is illustrated through an
application to a breast cancer data set where the goal is to detect the
pathways with different DNA copy number alterations across breast cancer
subtypes.


title:
The link between solenoidal turbulence and slow star formation in
  G0.253+0.016

abstract:
  Star formation in the Galactic disc is primarily controlled by gravity,
turbulence, and magnetic fields. It is not clear that this also applies to star
formation near the Galactic Centre. Here we determine the turbulence and star
formation in the CMZ cloud G0.253+0.016. Using maps of 3mm dust emission and
HNCO intensity-weighted velocity obtained with ALMA, we measure the
volume-density variance $\sigma_{\rho/\rho_0} = 1.3 \pm 0.5$ and turbulent Mach
number $\mathcal{M} = 11 \pm 3$. Combining these with turbulence simulations to
constrain the plasma $\beta = 0.34 \pm 0.35$, we reconstruct the turbulence
driving parameter $b = 0.22 \pm 0.12$ in G0.253+0.016. This low value of $b$
indicates solenoidal (divergence-free) driving of the turbulence in
G0.253+0.016. By contrast, typical clouds in the Milky Way disc and spiral arms
have a significant compressive (curl-free) driving component ($b > 0.4$). We
speculate that shear causes the solenoidal driving in G0.253+0.016 and show
that this may reduce the star formation rate by a factor of 7 compared to
nearby clouds.


title: The $\mathrm{GL}_n$-Connes-Marcolli Systems

abstract:
  In this paper, we generalize the results of Laca, Larsen, and Neshveyev on
the $\mathrm{GL}_2$-Connes-Marcolli system to the $\mathrm{GL}_n$ systems. We
introduce the $\mathrm{GL}_n$-Connes-Marcolli systems and discuss the question
of the existence and the classification of KMS equilibrium states at different
inverse temperatures $\beta$. In particular, using an ergodicity argument, we
prove that in the range $n-1 <\beta\leq n$, there is only one KMS state. We
show that there are no KMS states for $\beta<n-1$ and not an integer, while we
construct KMS states for integer values of $\beta$ in the range $1\leq\beta\leq
n-1$, and we classify extremal KMS states for $\beta>n$.


title:
Properties of long-term optical variability of active galactic nuclei
  with double-peaked broad low-ionization emission lines

abstract:
  In this manuscript, we study properties of long-term optical variability of a
large sample of 106 SDSS spectroscopically confirmed AGN with double-peaked
broad low-ionization emission lines (double-peaked emitters). The long-term
optical light curves over 8 years are collected from the Catalina Sky Surveys
Data Release 2. And, the Damped Random Walk (DRW) process is applied to
describe the long-term variability of the double-peaked emitters. Meanwhile,
the same DRW process is applied to long-term optical light curves of more than
7000 spectroscopically confirmed normal quasars in the SDSS Stripe82 Database.
Then, we can find that the DRW process determined rest-frame intrinsic
variability timescales $\ln(\tau/{\rm days})$ are about 5.8 and about 4.8 for
the double-peaked emitters and for the normal quasars, respectively. The
statistically longer intrinsic variability timescales can be confirmed in the
double-peaked emitters, after considerations of necessary effects, such as the
effects from different distributions of redshift, BH mass and accretion rate
between the double-peaked emitters and the normal quasars. Moreover, a radial
dependence of accretion rate $\dot{m}_{\rm R}~\propto~R^\beta$ with larger
values of $\beta$ could be an acceptable interpretation of the longer intrinsic
variability timescales in the double-peaked emitters. Therefore, there are
different intrinsic properties of emission regions between the double-peaked
emitters and the normal quasars. The double-peaked emitters can be well treated
as an unique subclass of AGN.


title: Adaptive 360 VR Video Streaming: Divide and Conquer!

abstract:
  While traditional multimedia applications such as games and videos are still
popular, there has been a significant interest in the recent years towards new
3D media such as 3D immersion and Virtual Reality (VR) applications, especially
360 VR videos. 360 VR video is an immersive spherical video where the user can
look around during playback. Unfortunately, 360 VR videos are extremely
bandwidth intensive, and therefore are difficult to stream at acceptable
quality levels. In this paper, we propose an adaptive bandwidth-efficient 360
VR video streaming system using a divide and conquer approach. In our approach,
we propose a dynamic view-aware adaptation technique to tackle the huge
streaming bandwidth demands of 360 VR videos. We spatially divide the videos
into multiple tiles while encoding and packaging, use MPEG-DASH SRD to describe
the spatial relationship of tiles in the 360-degree space, and prioritize the
tiles in the Field of View (FoV). In order to describe such tiled
representations, we extend MPEG-DASH SRD to the 3D space of 360 VR videos. We
spatially partition the underlying 3D mesh, and construct an efficient 3D
geometry mesh called hexaface sphere to optimally represent a tiled 360 VR
video in the 3D space. Our initial evaluation results report up to 72%
bandwidth savings on 360 VR video streaming with minor negative quality impacts
compared to the baseline scenario when no adaptations is applied.


title: Spanning trails with maximum degree at most 4 in $2K_2$-free graphs

abstract:
  A graph is called $2K_2$-free if it does not contain two independent edges as
an induced subgraph. Mou and Pasechnik conjectured that every
$\frac{3}{2}$-tough $2K_2$-free graph with at least three vertices has a
spanning trail with maximum degree at most $4$. In this paper, we confirm this
conjecture. We also provide examples for all $t < \frac{5}{4}$ of $t$-tough
graphs that do not have a spanning trail with maximum degree at most $4$.


title:
Synchronization of coupled noisy oscillators: Coarse-graining from
  continuous to discrete phases

abstract:
  The theoretical description of synchronization phenomena often relies on
coupled units of continuous time noisy Markov chains with a small number of
states in each unit. It is frequently assumed, either explicitly or implicitly,
that coupled discrete-state noisy Markov units can be used to model
mathematically more complex coupled noisy continuous phase oscillators. In this
work we explore conditions that justify this assumption by coarse-graining
continuous phase units. In particular, we determine the minimum number of
states necessary to justify this correspondence for Kuramoto-like oscillators.


title:
How Similar are the Properties of Quasars with Nearly Identical
  Ultraviolet Spectra?

abstract:
  The spectrum of a quasar contains important information about its properties.
Thus, it can be expected that two quasars with similar spectra will have
similar properties, but just how similar has not before been quantified. Here
we compare the ultraviolet spectra of a sample of 5553 quasars from Data
Release 7 of the Sloan Digital Sky Survey, focusing on the $1350$ \AA \ $\leq
\lambda \leq 2900$ \AA \ rest-frame region which contains prominent emission
lines from \SiIV, O IV], \CIV, \CIII, and \MgII\ species. We use principal
component analysis to determine the dominant components of spectral variation,
as well as to quantitatively measure spectral similarity. As suggested by both
the Baldwin effect and modified Baldwin effect, quasars with similar spectra
have similar properties: bolometric luminosity, Eddington fraction, and black
hole mass. The latter two quantities are calculated from the luminosity in
conjunction with spectral features, and the variation between quasars with
virtually identical spectra (which we call doppelg\"angers) is driven by the
variance in the luminosity plus measurement uncertainties. In the doppelgangers
the luminosity differences show 1$\sigma$ uncertainties of 57\% (or 0.63
magnitudes) and $\sim$70\% 1$\sigma$ uncertainties for mass and Eddington
fraction. Much of the difference in luminosities may be attributable to time
lags between the spectral lines and the continuum. Furthermore, we find that
suggestions that the mostly highly accreting quasars should be better standard
candles than other quasars are not bourne out for doppelgangers. Finally, we
discuss the implications for using quasars as cosmological probes and the
nature of the first two spectral principal components.


title: Growing Controllable Networks via Whiskering and Submodular Optimization

abstract:
  The topology of a network directly influences the behaviour and
controllability of dynamical processes on that network. Therefore, the design
of network topologies is an important area of research when examining the
control of distributed systems. We discuss a method for growing networks known
as whiskering, as well as generalizations of this process, and prove that they
preserve controllability. We then use techniques from submodular optimization
to analyze optimization algorithms for adding new nodes to a network to
optimize certain objectives, such as graph connectivity.


title:
Interprocedural Semantic Change-Impact Analysis using Equivalence
  Relations

abstract:
  Change-impact analysis (CIA) is the task of determining the set of program
elements impacted by a program change. Precise CIA has great potential to avoid
expensive testing and code reviews for (parts of) changes that are refactorings
(semantics-preserving). Existing CIA is imprecise because it is coarse-grained,
deals with only few refactoring patterns, or is unaware of the change
semantics.
  We formalize the notion of change impact in terms of the trace semantics of
two program versions. We show how to leverage equivalence relations to make
dataflow-based CIA aware of the change semantics, thereby improving precision
in the presence of semantics-preserving changes. We propose an anytime
algorithm that allows applying costly equivalence relation inference
incrementally to refine the set of impacted statements. We have implemented a
prototype in SymDiff, and evaluated it on 322 real-world changes from
open-source projects and benchmark programs used by prior research. The
evaluation results show an average 35% improvement in the size of the set of
impacted statements compared to standard dataflow-based techniques.


title:
Renormalization of trace distance and multipartite entanglement close to
  the quantum phase transitions of one- and two-dimensional spin-chain systems

abstract:
  We investigate the quantum phase transitions of spin systems in one and two
dimensions by employing trace distance and multipartite entanglement along with
real-space quantum renormalization group method. As illustration examples, a
one-dimensional and a two-dimensional $XY$ models are considered. It is shown
that the quantum phase transitions of these spin-chain systems can be revealed
by the singular behaviors of the first derivatives of renormalized trace
distance and multipartite entanglement in the thermodynamics limit. Moreover,
we find the renormalized trace distance and multipartite entanglement obey
certain universal exponential-type scaling laws in the vicinity of the quantum
critical points.


title:
Analysis of ground penetrating radar data from the tunnel beneath the
  Temple of the Feathered Serpent in Teotihuacan, Mexico, using new multi-cross
  algorithms

abstract:
  As multichannel equipment is increasingly used, we developed two algorithms
for multivariable wavelet analysis of GPR signals (multi-cross wavelet MCW and
Fourier multi-cross function FMC) and applied them to analyze raw GPR traces of
archeological subsurface strata. The traces were from the tunnel located
beneath the Temple of the Feathered Serpent (The Citadel, Teotihuacan, Mexico).
The MCW and FMC algorithms determined the periods of subsurface strata of the
tunnel. GPR traces inside-and-outside the tunnel/chamber, outside the
tunnel/chamber and inside the tunnel/chamber analyzed with the MCW and filtered
FMC algorithms determined the periods of the tunnel and chamber fillings, clay
and matrix (limestone-clay compound). The tunnel filling period obtained by MCW
analysis (14.37 ns) reflects the mixed limestone-clay compound of this stratum
since its value is close to that of the period of the matrix (15.22 ns);
periods of the chamber filling (11.40 ns) and the matrix (11.40 ns) were almost
identical. FMC analysis of the tunnel obtained a period (5.08 ns) close to that
of the chamber (4.27 ns), suggesting the tunnel and chamber are filled with
similar materials. The use of both algorithms allows a deeper analysis since
the similarities of the tunnel and chamber filling periods could not have been
determined with the MCW algorithm alone. The successful application of the new
multi-cross algorithms to archeological GPR data suggests they may also be used
to search water and other resources in celestial bodies.


title:
A Bayesian Interval Dose-Finding Design Addressing Ockham's Razor:
  mTPI-2

abstract:
  There has been an increasing interest in using interval-based Bayesian
designs for dose finding, one of which is the modified toxicity probability
interval (mTPI) method. We show that the decision rules in mTPI correspond to
an optimal rule under a formal Bayesian decision theoretic framework. However,
the probability models in mTPI are overly sharpened by the Ockham's razor,
which, while in general helps with parsimonious statistical inference, leads to
suboptimal decisions in small-sample inference such as dose finding. We propose
a new framework that blunts the Ockham's razor, and demonstrate the superior
performance of the new method, called mTPI-2. An online web tool is provided
for users who can generate the design, conduct clinical trials, and examine
operating characteristics of the designs through big data and crowd sourcing.


title: Frogs on trees?

abstract:
  We study a system of simple random walks on $\mathcal{T}_{d,n} =
\mathcal{V}_{d,n}, \mathcal{E}_{d,n})$, the $d$-ary tree of depth $n$, known as
the frog model. Initially there are Pois($\lambda$) particles at each site,
independently, with one additional particle planted at some vertex
$\mathbf{o}$. Initially all particles are inactive, except for the ones which
are placed at $\mathbf{o}$. Active particles perform (independent) $ t \in
\mathbb{N} \cup \{\infty \} $ steps of simple random walk on the tree. When an
active particle hits an inactive particle, the latter becomes active. The model
is often interpreted as a model for a spread of an epidemic. As such, it is
natural to investigate whether the entire population is eventually infected,
and if so, how quickly does this happen. Let $\mathcal{R}_t$ be the set of
vertices which are visited by the process. Let $\mathcal{S}(\mathcal{T}_{d,n})
:= \inf \{t:\mathcal{R}_t = \mathcal{V}_{d,n} \} $. Let the cover time
$\mathrm{CT}(\mathcal{T}_{d,n})$ be the first time by which every vertex was
visited at least once, when we take $t=\infty$. We show that there exist
absolute constants, $c,C>0$ such that for all $d \ge 2$ and all $\lambda =
\lambda_n $ which does not diverge nor vanish too rapidly, with high
probability $c \le \lambda \mathcal{S}(\mathcal{T}_{d,n}) /n \log (n/\lambda)
\le C$ and $\mathrm{CT}(\mathcal{T}_{d,n}) \le 3^{4 \sqrt{ \log
|\mathcal{V}_{d,n}| }}$.


title: Approximate Sparse Linear Regression

abstract:
  In the Sparse Linear Regression (SLR) problem, given a $d \times n$ matrix
$M$ and a $d$-dimensional query $q$, the goal is to compute a $k$-sparse
$n$-dimensional vector $\tau$ such that the error $||M \tau-q||$ is minimized.
This problem is equivalent to the following geometric problem: given a set $P$
of $n$ points and a query point $q$ in $d$ dimensions, find the closest
$k$-dimensional subspace to $q$, that is spanned by a subset of $k$ points in
$P$. In this paper, we present data-structures/algorithms and conditional lower
bounds for several variants of this problem (such as finding the closest
induced $k$ dimensional flat/simplex instead of a subspace).
  In particular, we present approximation algorithms for the online variants of
the above problems with query time $\tilde O(n^{k-1})$, which are of interest
in the "low sparsity regime" where $k$ is small, e.g., $2$ or $3$. For $k=d$,
this matches, up to polylogarithmic factors, the lower bound that relies on the
affinely degenerate conjecture (i.e., deciding if $n$ points in $\mathbb{R}^d$
contains $d+1$ points contained in a hyperplane takes $\Omega(n^d)$ time).
Moreover, our algorithms involve formulating and solving several geometric
subproblems, which we believe to be of independent interest.


title:
Scalable Discrete Supervised Hash Learning with Asymmetric Matrix
  Factorization

abstract:
  Hashing method maps similar data to binary hashcodes with smaller hamming
distance, and it has received a broad attention due to its low storage cost and
fast retrieval speed. However, the existing limitations make the present
algorithms difficult to deal with large-scale datasets: (1) discrete
constraints are involved in the learning of the hash function; (2) pairwise or
triplet similarity is adopted to generate efficient hashcodes, resulting both
time and space complexity are greater than O(n^2). To address these issues, we
propose a novel discrete supervised hash learning framework which can be
scalable to large-scale datasets. First, the discrete learning procedure is
decomposed into a binary classifier learning scheme and binary codes learning
scheme, which makes the learning procedure more efficient. Second, we adopt the
Asymmetric Low-rank Matrix Factorization and propose the Fast Clustering-based
Batch Coordinate Descent method, such that the time and space complexity is
reduced to O(n). The proposed framework also provides a flexible paradigm to
incorporate with arbitrary hash function, including deep neural networks and
kernel methods. Experiments on large-scale datasets demonstrate that the
proposed method is superior or comparable with state-of-the-art hashing
algorithms.


title: Digital spiral object identification using random light

abstract:
  Photons that are entangled or correlated in orbital angular momentum have
been extensively used for remote sensing, object identification and imaging. It
has recently been demonstrated that intensity fluctuations give rise to the
formation of correlations in the orbital angular momentum components and
angular positions of random light. Here, we demonstrate that the spatial
signatures and phase information of an object, with rotational symmetries, can
be identified using classical orbital angular momentum correlations in random
light. The Fourier components imprinted in the digital spiral spectrum of the
object, measured through intensity correlations, unveil its spatial and phase
information. Sharing similarities with conventional compressive sensing
protocols that exploit sparsity to reduce the number of measurements required
to reconstruct a signal, our technique allows sensing of an object with fewer
measurements than other schemes that use pixel-by-pixel imaging. One remarkable
advantage of our technique is the fact that it does not require the preparation
of fragile quantum states of light and works at both low- and high-light
levels. In addition, our technique is robust against environmental noise, a
fundamental feature of any realistic scheme for remote sensing.


title: A Note on Spectral Analysis for ${\rm GL}_2$: I

abstract:
  We establish the Fourier inversion for the smooth vectors in ${\rm L}^2({\rm
GL}_2, \omega)$ over a number field $\mathbf{F}$, using minimal knowledge from
automorphic representation theory. We point out a possible way to establish
Fourier inversion for larger classes of functions. We also point out the
incompleteness of some commonly believed "proof" of Fourier inversion in the
literature. Moreover, the explicit computation of the intertwining operator has
independent interests.


title: Inequalities for Zero-Balanced Gaussian hypergeometric function

abstract:
  In this paper, we consider the monotonicity of certain combinations of the
Gaussian hypergeometric functions $F(a-1,b;a+b;1-x^c)$ and
$F(a-1-\delta,b+\delta;a+b;1-x^d)$ on $(0,1)$ for $\delta\in(a-1,0)$, and study
the problem of comparing these two functions, thus get the largest value
$\delta_1=\delta_1(a,c,d)$ such that the inequality
$F(a-1,b;a+b;1-x^c)<F(a-1-\delta,b+\delta;a+b;1-x^d)$ holds for all $x\in
(0,1)$.


title:
Strong Convergence Rate of Finite Difference Approximations for
  Stochastic Cubic Schr\"odinger Equations

abstract:
  In this paper, we derive a strong convergence rate of spatial finite
difference approximations for both focusing and defocusing stochastic cubic
Schr\"odinger equations driven by a multiplicative $Q$-Wiener process. Beyond
the uniform boundedness of moments for high order derivatives of the exact
solution, the key requirement of our approach is the exponential integrability
of both the exact and numerical solutions. By constructing and analyzing a
Lyapunov functional and its discrete correspondence, we derive the uniform
boundedness of moments for high order derivatives of the exact solution and the
first order derivative of the numerical solution, which immediately yields the
well-posedness of both the continuous and discrete problems. The latter
exponential integrability is obtained through a variant of a criterion given by
[Cox, Hutzenthaler and Jentzen, arXiv:1309.5595]. As a by-product of this
exponential integrability, we prove that the exact and numerical solutions
depend continuously on the initial data and obtain a large deviation-type
result on the dependence of the noise with first order strong convergence rate.


title: A note on Diophantine approximation with Gaussian primes

abstract:
  We investigate the distribution of $p\theta$ modulo 1, where $\theta$ is a
complex number which is not contained in $\mathbb{Q}(i)$, and $p$ runs over the
Gaussian primes.


title:
When Big Data Fails! Relative success of adaptive agents using
  coarse-grained information to compete for limited resources

abstract:
  The recent trend for acquiring big data assumes that possessing
quantitatively more and qualitatively finer data necessarily provides an
advantage that may be critical in competitive situations. Using a model complex
adaptive system where agents compete for a limited resource using information
coarse-grained to different levels, we show that agents having access to more
and better data can perform worse than others in certain situations. The
relation between information asymmetry and individual payoffs is seen to be
complex, depending on the composition of the population of competing agents.


title: Telecom data for efficient malaria interventions

abstract:
  Telecom data is rich on mobility information and as such can be used to
identify mobility patterns of people in near real time, enabling to build
epidemiological models for understanding where epidemics might spread over
time. Based on previous research, we have built an operational tool fed with
telecom data which shows malaria risk flows in Zambia in near real time. It
provides insights on which areas should eradicate malaria first in order to
have a maximum impact on the overall country malaria flows, and it highlights
regions that should coordinate their eradication efforts together. Such
information is particularly relevant for countries like Zambia, which are
getting close to malaria elimination and need to prevent its re-introduction
into areas that are already malaria-free.


title: Measuring the speed of light with ultra-compact radio quasars

abstract:
  In this paper, based on a 2.29 GHz VLBI all-sky survey of 613 milliarcsecond
ultra-compact radio sources with $0.0035<z<3.787$, we describe a method of
identifying the sub-sample which can serve as individual standard rulers in
cosmology. If the linear size of the compact structure is assumed to depend on
source luminosity and redshift as $l_m=l L^\beta (1+z)^n$, only
intermediate-luminosity quasars ($10^{27}$ W/Hz$<L<$ $10^{28}$ W/Hz) show
negligible dependence ($|n|\simeq 10^{-3}$, $|\beta|\simeq 10^{-4}$), and thus
represent a population of such rulers with fixed characteristic length
$l=11.42$ pc. With a sample of 120 such sources covering the redshift range
$0.46<z<2.80$, we confirm the existence of dark energy in the Universe with
high significance under the assumption of a flat universe, and obtain stringent
constraints on both the matter density $\Omega_m=0.323^{+0.245}_{-0.145}$ and
the Hubble constant $H_0=66.30^{+7.00}_{-8.50}$ km sec$^{-1}$ Mpc$^{-1}$.
Finally, with the angular diameter distances $D_A$ measured for quasars
extending to high redshifts ($z\sim 3.0$), we reconstruct the $D_A(z)$ function
using the technique of Gaussian processes. This allows us to identify the
redshift corresponding to the maximum of the $D_A(z)$ function: $z_m=1.70$ and
the corresponding angular diameter distance $D_A(z_m)=1719.01\pm43.46$ Mpc.
Similar reconstruction of the expansion rate function $H(z)$ based on the data
from cosmic chronometers and BAO gives us $H(z_m)=176.77\pm6.11$ km sec$^{-1}$
Mpc$^{-1}$. These measurements are used to estimate the speed of light:
$c=3.039(\pm0.180)\times 10^5$ km/s. This is the first measurement of the speed
of light in a cosmological setting referring to the distant past.


title:
Study of Two-Body $e^+e^- \to B_s^{(*)}\bar{B}_s^{(*)}$ Production in
  the Energy Range from 10.77 to 11.02 GeV

abstract:
  We report results on the studies of the $e^+e^-\to B_s^{(*)}\bar{B}_s^{(*)}$
processes. The results are based on a $121.4$ fb$^{-1}$ data sample collected
with the Belle detector at the center-of-mass energy near the $\Upsilon(10860)$
peak and $16.4$ fb$^{-1}$ of data collected at 19 energy points in the range
from 10.77 to 11.02 GeV. We observe a clear $e^+e^-\to\Upsilon(10860)\to
B_s^{(*)}\bar{B}_s^{(*)}$ signal, with no statistically significant signal of
$e^+e^-\to \Upsilon(11020)\to B_s^{(*)}\bar{B}_s^{(*)}$. The relative
production ratio of $B_s^*\bar{B}_s^*$, $B_s\bar{B}_s^{*}$, and $B_s\bar{B}_s$
final states at $\sqrt{s}=10.866$ GeV is measured to be $7:$
$0.856\pm0.106(stat.)\pm0.053(syst.):$
$0.645\pm0.094(stat.)^{+0.030}_{-0.033}(syst.)$. An angular analysis of the
$B_s^*\bar{B}_s^*$ final state produced at the $\Upsilon(10860)$ peak is also
performed.


title:
Magmatic sulfides in the porphyritic chondrules of EH enstatite
  chondrites

abstract:
  The nature and distribution of sulfides within 17 porphyritic chondrules of
the Sahara 97096 EH3 enstatite chondrite have been studied by backscattered
electron microscopy and electron microprobe in order to investigate the role of
gas-melt interactions in the chondrule sulfide formation. Troilite (FeS) is
systematically present and is the most abundant sulfide within the EH3
chondrite chondrules. It is found either poikilitically enclosed in low-Ca
pyroxenes or scattered within the glassy mesostasis. Oldhamite (CaS) and
niningerite [(Mg,Fe,Mn)S] are present in about 60% of the chondrules studied.
While oldhamite is preferentially present in the mesostasis, niningerite
associated with silica is generally observed in contact with troilite and
low-Ca pyroxene. The chondrule mesostases contain high abundances of alkali and
volatile elements as well as silica. Our data suggest that most of the sulfides
found in EH3 chondrite chondrules are magmatic minerals that formed after the
dissolution of S from a volatile-rich gaseous environment into the molten
chondrules. Troilite formation occurred via sulfur solubility within Fe-poor
chondrule melts followed by sulfide saturation, which causes an immiscible iron
sulfide liquid to separate from the silicate melt. The FeS saturation started
at the same time as or prior to the crystallization of low-Ca pyroxene during
the high temperature chondrule forming event(s). Protracted gas-melt
interactions under high partial pressures of S and SiO led to the formation of
niningerite-silica associations via destabilization of the previously formed
FeS and low-Ca pyroxene. We also propose that formation of the oldhamite
occurred via the sulfide saturation of Fe-poor chondrule melts at moderate S
concentration due to the high degree of polymerization and the high Na-content
of the chondrule melts, which allowed the activity of CaO in the melt to be
enhanced.


title:
A remark on the convergence of the Douglas-Rachford iteration in a
  non-convex setting

abstract:
  Using the construction of a Lyapunov function, it is shown that the
Douglas-Rachford iteration with respect to a sphere and a line in $\mathbb R^d$
is robustly $\mathcal{KL}$-stable. This implies a convergence which is stronger
than uniform convergence on compact sets.


title: Stabilizing Linear Prediction Models using Autoencoder

abstract:
  To date, the instability of prognostic predictors in a sparse high
dimensional model, which hinders their clinical adoption, has received little
attention. Stable prediction is often overlooked in favour of performance. Yet,
stability prevails as key when adopting models in critical areas as healthcare.
Our study proposes a stabilization scheme by detecting higher order feature
correlations. Using a linear model as basis for prediction, we achieve feature
stability by regularising latent correlation in features. Latent higher order
correlation among features is modelled using an autoencoder network. Stability
is enhanced by combining a recent technique that uses a feature graph, and
augmenting external unlabelled data for training the autoencoder network. Our
experiments are conducted on a heart failure cohort from an Australian
hospital. Stability was measured using Consistency index for feature subsets
and signal-to-noise ratio for model parameters. Our methods demonstrated
significant improvement in feature stability and model estimation stability
when compared to baselines.


title:
TMI! How Knowledge Platforms Tame the Information Overload and Advance
  Global Development Through Technology

abstract:
  Finding reliable data to inform decisions about technology for global
development remains a challenge. Easily accessible "Knowledge platforms" are a
way to curate and standardize information about technology for development.
Three collaborators, Engineering for Change, the Global Alliance for Clean
Cookstoves and the Center for Affordable Water and Sanitation Technology
(CAWST) are working together to create platforms to serve the global
development sector. Such platforms could be the first step in making decisions
about how to solve a problem that needs a technology-based solution. They could
motivate manufacturers to demonstrate compliance with quality standards, and
they could encourage independent research into each product's impact. Years of
development experience worldwide have yielded a set of best practices to
increase the life of a project. These platforms clarify those practices to
improve quality and reduce waste. As the platforms mature, mining them for data
could identify trends that influence the entire technology ecosystem. Those
could include decisions about performance targets, future innovation, pricing,
compliance with regulations, and funding priorities.


title: Moving the Needle: What Works Cities and the use of data and evidence

abstract:
  Bloomberg Philanthropies launched What Works Cities (WWC) in 2015 to help
cities better leverage data and evidence to drive decision-making and improve
residents' lives. Over three years, WWC will work with 100 American cities with
populations between 100,000 and 1,000,000 to measure their state of practice
and provide targeted technical assistance. This paper uses the data obtained
through the WWC discovery process to understand how 67 cities are currently
using data to deliver city services. Our analysis confirms that while cities
possess a strong desire to use data and evidence, government leaders are
constrained in their ability to apply these practices. We find that a city's
stated commitment to using data is the strongest predictor of overall
performance and that strong practice in almost any one specific technical area
of using data to inform decisions is an indicator of strong practices in other
areas. The exception is open data; we find larger cities are more adept at
adopting open data policies and programs, independent of their performance
using data overall. This paper seeks to develop a deeper understanding of the
issues underlying these findings and to continue the conversation on how to
best support cities' efforts in this work.


title:
A Case in Kenya: Unlocking bottlenecks in public health supply chains
  through data dashboards and enhanced governance structures

abstract:
  The link between data and governance are key to making public health supply
chains more integrated and responsive in order to get life-saving commodities
to those in need. In particular, considering its significant health challenges,
poor maternal and child health indicators, and major recent devolution in
political authority, Kenya represents a country in need of an innovative revamp
of their data management and governance. John Snow, Inc. (JSI) adapted various
elements of proven interventions to build a customized structure to support
routine data collection in order to drive decision making around supply chain
improvement.


title:
Global Fishing Watch: Bringing Transparency to Global Commercial
  Fisheries

abstract:
  Across all major industrial fishing sectors, overfishing due to overcapacity
and lack of compliance in fishery governance has led to a decline in biomass of
many global fish stocks. Overfishing threatens ocean biodiversity, global food
security, and the livelihoods of law abiding fishermen. To address this issue,
Global Fishing Watch (GFW) was created to bring transparency to global
fisheries using computer science and big data analytics. A product of a
partnership between Oceana, SkyTruth and Google, GFW uses the Automatic
Identification System, or AIS, to analyze the movement of vessels at sea. AIS
provides vessel location data, and GFW uses this information to track global
vessel movement and apply algorithms to classify vessel behavior as "fishing"
or "non-fishing" activity. Now publicly available, anyone with an internet
connection can monitor when and where trackable commercial fishing appears to
be occurring around the world. Hundreds of millions of people around the world
depend on our ocean for their livelihoods, and many more rely on it for food.
Collectively, the various applications of GFW will help reduce overfishing and
illegal fishing, restore the ocean's abundance, and ensure sustainability
through better monitoring and governance of our marine resources.


title:
A Functioning Beta Solution to the Challenge of Opening Transit Payment
  System Transaction Data

abstract:
  The deployment of smart-card-based public transit fare payment systems
provides government the opportunity to create a valuable derivative data
product. Companies such as Urban Engines have demonstrated an ability to add
value to the data derived from transit fare transactions. The challenge for the
public sector is to, for the societal good, leverage private sector interest by
giving access to useful fare transaction data in a manner that protects
customer privacy. This challenge is particularly acute in California, where
privacy laws make sharing data in a manner that supports the public interest
difficult. This paper presents the Metropolitan Transportation Commission's
(MTC's) proposed solution to the problem. MTC operates the Clipper(r) transit
fare payment system for the San Francisco Bay Area. In an effort to share
usable data that protects customer privacy, MTC developed an anonymizing scheme
that is the subject of the present paper. We seek feedback on our approach from
the Data for Good Exchange community, asking: in seeking a balance between
customer privacy and usability, does the scheme go too far in either direction?
And, should we take a different anonymizing approach?


title: Video Summarization using Deep Semantic Features

abstract:
  This paper presents a video summarization technique for an Internet video to
provide a quick way to overview its content. This is a challenging problem
because finding important or informative parts of the original video requires
to understand its content. Furthermore the content of Internet videos is very
diverse, ranging from home videos to documentaries, which makes video
summarization much more tough as prior knowledge is almost not available. To
tackle this problem, we propose to use deep video features that can encode
various levels of content semantics, including objects, actions, and scenes,
improving the efficiency of standard video summarization techniques. For this,
we design a deep neural network that maps videos as well as descriptions to a
common semantic space and jointly trained it with associated pairs of videos
and descriptions. To generate a video summary, we extract the deep features
from each segment of the original video and apply a clustering-based
summarization technique to them. We evaluate our video summaries using the
SumMe dataset as well as baseline approaches. The results demonstrated the
advantages of incorporating our deep semantic features in a video summarization
technique.


title:
Quantum coherence quantifiers based on the R\'{e}nyi $\alpha$-relative
  entropy

abstract:
  The resource theories of quantum coherence attract a lot of attention in
recent years. Especially, the monotonicity property plays a crucial role here.
In this paper we investigate the monotonicity property for the coherence
measures induced by the R\'{e}nyi $\alpha$-relative entropy which present in
[Phys. Rev. A 94, 052336, 2016]. We show that the R\'{e}nyi $\alpha$-relative
entropy of coherence does not in general satisfy the monotonicity requirement
under the subselection of measurements condition and it also does not satisfy
the extension of monotonicity requirement which presents in [Phys. Rev. A 93,
032136, 2016]. Due to the R\'{e}nyi $\alpha$-relative entropy of coherence can
act as a coherence monotone quantifier, we examine the trade-off relations
between coherence and mixedness. Finally, some properties for the single qubit
of R\'{e}nyi $2$-relative entropy of coherence are derived.


title: Generalized supersymmetry and L\'evy-Leblond equation

abstract:
  The symmetries of the L\'evy-Leblond equation are investigated beyond the
standard Lie framework. It is shown that the equation has two remarkable
symmetries. One is given by the super Schr\"odinger algebra and the other one
by a $\ZZ$ graded Lie algebra. The $\ZZ$ graded Lie algebra is achieved by
transforming bosonic into fermionic operators in the super Schr\"odinger
algebra and introducing second order differential operators as generators of
symmetry.


title: Electron Plasmas Cooled by Cyclotron-Cavity Resonance

abstract:
  We observe that high-Q electromagnetic cavity resonances increase the
cyclotron cooling rate of pure electron plasmas held in a Penning-Malmberg trap
when the electron cyclotron frequency, controlled by tuning the magnetic field,
matches the frequency of standing wave modes in the cavity. For certain modes
and trapping configurations, this can increase the cooling rate by factors of
ten or more. In this paper, we investigate the variation of the cooling rate
and equilibrium plasma temperatures over a wide range of parameters, including
the plasma density, plasma position, electron number, and magnetic field.


title: Public Intervention Strategies for Distressed Communities

abstract:
  This research presents a methodology to comprehensively define Distressed
Communities. We further identify if there is a significant difference in public
investment between Distressed communities and Wealthy communities. One of the
key tools in sustainability planning is the use of sustainability indicators
(Sis). A considerable amount of scholarship has contributed to define and
develop SI programs for local level application (Elgert and Krueger, 2012).
Much of the focus of SI research is on developing the ideal indicator based on
defined criteria for each indicator (Hart, 1999; Innes and Booher 2000; Holman,
2009). Here we suggest a methodology beyond defining the ideal indicators to
demonstrating how indicators can be used for more in-depth analysis of complex
urban problems. In this analysis we reduce 34 development metrics to a smaller
number of factors that represent how the data can be classified into groups
based on similarities among 88 communities. Using the factor (group) that
contained measures identifying Distressed Communities, the communities were
alloted an index score and ranked. The top 10 communities were then compared to
the bottom 10 communities according to 14 place based variables related to
opportunities for local government led improvement.


title: Uniformization of Cantor sets with bounded geometry

abstract:
  In this note we provide a quasisymmetric taming of uniformly perfect and
uniformly disconnected sets that generalizes a result of MacManus from 2 to
higher dimensions. In particular, we show that a compact subset of
$\mathbb{R}^n$ is uniformly perfect and uniformly disconnected if and only if
it is ambiently quasiconformal to the standard Cantor set $\mathcal{C}$ in
$\mathbb{R}^{n+1}$.


title: Understanding data augmentation for classification: when to warp?

abstract:
  In this paper we investigate the benefit of augmenting data with
synthetically created samples when training a machine learning classifier. Two
approaches for creating additional training samples are data warping, which
generates additional samples through transformations applied in the data-space,
and synthetic over-sampling, which creates additional samples in feature-space.
We experimentally evaluate the benefits of data augmentation for a
convolutional backpropagation-trained neural network, a convolutional support
vector machine and a convolutional extreme learning machine classifier, using
the standard MNIST handwritten digit dataset. We found that while it is
possible to perform generic augmentation in feature-space, if plausible
transforms for the data are known then augmentation in data-space provides a
greater benefit for improving performance and reducing overfitting.


title:
iRescU - Data for Social Good Saving Lives Bridging the Gaps in Sudden
  Cardiac Arrest Survival

abstract:
  Currently every day in the USA 1000 people die of sudden cardiac arrest (SCA)
outside of hospitals or ambulances - before emergency medical help arrives - in
the streets, workplaces, schools and homes of our cities, adults and children.
Brain death commences in 3 minutes, and often the ambulance just can't be there
in time. Citizen cardiopulmonary resuscitation (CPR) and automated external
defibrillator (AED) use can save precious minutes and lives. Using public
access AED's saves lives in SCA- however AEDs are used in <2% of cardiac
arrests, though could save lives in 80% if available, findable, functioning,
and used. The systems problem to solve is that there is no comprehensive or
real time accessible database of the AED locations, and also it is not known
that they are actually being positioned where they are needed. The iRescU
project is designed to bridge this gap in SCA survival, by substantially
augmenting the AED database. Utilizing a combination of AED crowd sourcing and
geolocation integrated with existing 911 services and SCA events and projected
events based on machine learning data information to help make the nearest AED
accessible and available in the setting of a SCA emergency and to identify the
areas of greatest need for AEDs to be positioned in the community. Helping to
save lives and address preventable death with a social good approach and
applied big data.


title:
Data Accessibility as a Pathway to Genuine Equality for Atlanta's
  Westside Communities

abstract:
  Data is a dominant force during the decision-making process. It can help
determine which roads to expand and the optimal location for a grocery store.
Data can also be used to influence which schools to open or to shutter and
"appropriate" city services to continue or discontinue. Considered fact-based,
objective, and impartial, data can trump emotional appeals during the final
evaluation of a project; thus creating a power imbalance between those with the
resources to access data and those without. Most often left behind are
communities already struggling to stay afloat due to years of disinvestment by
market forces and external decision-makers. For long ignored residents in
Atlanta's Westside neighborhoods, the burden of inaccessible data continuously
thwarts their opportunity for mobility. However, with the advent of the
internet and the global push for open data, access to information is no longer
solely in the hands of those with power, influence and money. Online tools,
like the Westside Communities Alliance (WCA) Data Dashboard, quickly
disseminate data to those most impacted by "data driven decision-making," thus
creating the potential of a genuinely equitable society.
  Based out of the Georgia Institute of Technology, the WCA works to build and
sustain relationships among constituencies located in West Atlanta with the
goal to strengthen partnerships around issues of common concern. The creation
of the Data Dashboard stemmed from a recognized community desire for more
localized control and the need for improvements to the communities' overall
prosperity. Development of the site progressed through significant engagement
between the WCA, community groups, and local agencies. The Dashboard takes the
vast abundance of data and synthesizes it into a format that is both visually
and geographically user-friendly. Through different portals, users can access
neighborhood-level data around demographics, housing, education, and history
that is formatting in a way that is easily accessible and understandable. The
site includes qualitative research that goes beyond data and stats to give a
totality of the community. By allowing West Atlanta advocacy groups to easily
retrieve data, the WCA Data Dashboard empowers residents, nonprofits, and
neighborhood associations to be full participants in the decision-making
process.


title: The Subset Assignment Problem for Data Placement in Caches

abstract:
  We introduce the subset assignment problem in which items of varying sizes
are placed in a set of bins with limited capacity. Items can be replicated and
placed in any subset of the bins. Each (item, subset) pair has an associated
cost. Not assigning an item to any of the bins is not free in general and can
potentially be the most expensive option. The goal is to minimize the total
cost of assigning items to subsets without exceeding the bin capacities. This
problem is motivated by the design of caching systems composed of banks of
memory with varying cost/performance specifications. The ability to replicate a
data item in more than one memory bank can benefit the overall performance of
the system with a faster recovery time in the event of a memory failure. For
this setting, the number $n$ of data objects (items) is very large and the
number $d$ of memory banks (bins) is a small constant (on the order of $3$ or
$4$). Therefore, the goal is to determine an optimal assignment in time that
minimizes dependence on $n$. The integral version of this problem is NP-hard
since it is a generalization of the knapsack problem. We focus on an efficient
solution to the LP relaxation as the number of fractionally assigned items will
be at most $d$. If the data objects are small with respect to the size of the
memory banks, the effect of excluding the fractionally assigned data items from
the cache will be small. We give an algorithm that solves the LP relaxation and
runs in time $O({3^d \choose d+1} \text{poly}(d) n \log(n) \log(nC) \log(Z))$,
where $Z$ is the maximum item size and $C$ the maximum storage cost.


title:
Ignoring Extreme Opinions in Complex Networks: The Impact of
  Heterogeneous Thresholds

abstract:
  We consider a class of opinion dynamics on networks where at each time-step,
each node in the network disregards the opinions of a certain number of its
most extreme neighbors and updates its own opinion as a weighted average of the
remaining opinions. When all nodes disregard the same number of extreme
neighbors, previous work has shown that consensus will be reached if and only
if the network satisfies certain topological properties. In this paper, we
consider the implications of allowing each node to have a personal threshold
for the number of extreme neighbors to ignore. We provide graph conditions
under which consensus is guaranteed for such dynamics. We then study random
networks where each node's threshold is drawn from a certain distribution, and
provide conditions on that distribution, together with conditions on the edge
formation probability, that guarantee that consensus will be reached
asymptotically almost surely.


title: A non-local Poisson bracket for Coxeter--Toda lattices

abstract:
  We present a non-local Poisson bracket defined on the phase space $G^{u,v}/H$
of a Coxeter--Toda lattice, where $G^{u,v}$ is a Coxeter double Bruhat cell of
$GL_n$ and $H$ is the subgroup of diagonal matrices. This non-local Poisson
bracket is given in an appropriate set of coordinates of $G^{u,v}/H$ derived
from the so-called {\it factorization parameters}. We prove that the
generalized B\"acklund--Darboux transformations $\sigma_{u,v}^{u',v'}:
G^{u,v}/H\to G^{u',v'}/H$ are Poisson maps. We exploit that fact to show that
the non-local Poisson bracket corresponds to the Atiyah--Hitchin bracket under
the Moser map.


title:
Education Stats Made Visible: Helping School District Managers Write
  Better Three-Year Plans

abstract:
  Problem: School district leaders in California are awash in a sea of data,
but are often unable to find it, query it, or relate it with other data.
Districts are islands, leaving district managers able to see only their own
data. A state education agency gathers and republishes districts' data, but
doesn't clean it. New laws now require them to plan in public, set goals,
assign resources, and project benefits for specific groups of kids. The
evidence base they need remains out of reach.
  Solution: Our team was commissioned by two county offices of education to
design a comparative methodology and data visualization environment to help
district managers write these three-year plans. Ten year of data spanning
finance, staffing, students, discipline, course offerings and assessments were
acquired, QA'd and integrated. A Tableau development team built 50+ pages of
leaderboards and scatterplots. A documentation team wrote training materials.
Each district in this county received a custom workbook which framed its
district's vital signs within a context of 15 districts whose students were
most like their own. This presentation shares the work and our evaluation.


title:
Spatially Resolved HCN Absorption Features in the Circumnuclear Region
  of NGC 1052

abstract:
  We present the first VLBI detection of HCN molecular absorption in the nearby
active galactic nucleus NGC 1052. Utilizing the 1 milliarcsecond resolution
achieved by the Korean VLBI Network, we have spatially resolved the HCN
absorption against a double-sided nuclear jet structure. Two velocity features
of HCN absorption are detected significantly at the radial velocity of 1656 and
1719 km/s, redshifted by 149 and 212 km/s with respect to the systemic velocity
of the galaxy. The column density of the HCN molecule is estimated to be
10^{15}-10^{16} cm^{-2}, assuming the excitation temperature of 100-230 K. The
absorption features show high optical depth localized on the receding jet side,
where the free-free absorption occurred due to the circumnuclear torus. The
size of the foreground absorbing molecular gas is estimated to be on
approximately one-parsec scales, which agrees well with the approximate size of
the circumnuclear torus. HCN absorbing gas is likely to be several clumps
smaller than 0.1 parsec inside the circumnuclear torus. The redshifted
velocities of the HCN absorption features imply that HCN absorbing gas traces
ongoing infall motion inside the circumnuclear torus onto the central engine.


title:
SXDF-ALMA 2-arcmin^2 Deep Survey: Stacking of Rest-Frame Near-Infrared
  Selected Objects

abstract:
  We present stacking analyses on our ALMA deep 1.1 mm imaging in the SXDF
using 1.6 {\mu}m and 3.6 {\mu}m selected galaxies in the CANDELS WFC3 catalog.
We detect a stacked flux of ~0.03-0.05 mJy, corresponding to LIR < 10^11 Lsun
and a star formation rate (SFR) of ~ 15 Msun/yr at z = 2. We find that galaxies
brighter in the rest-frame near-infrared tend to be also brighter at 1.1 mm,
and galaxies fainter than m[3.6um] = 23 do not produce detectable 1.1 mm
emission. This suggests a correlation between stellar mass and SFR, but
outliers to this correlation are also observed, suggesting strongly boosted
star formation or extremely large extinction. We also find tendencies that
redder galaxies and galaxies at higher redshifts are brighter at 1.1 mm. Our
field contains z ~ 2.5 H-alpha emitters and a bright single-dish source.
However, we do not find evidence of bias in our results caused by the bright
source. By combining the fluxes of sources detected by ALMA and fluxes of faint
sources detected with stacking, we recover a 1.1 mm surface brightness of up to
20.3 +/- 1.2 Jy/deg, comparable to the extragalactic background light measured
by COBE. Based on the fractions of optically faint sources in our and previous
ALMA studies and the COBE measurements, we find that approximately half of the
cosmic star formation may be obscured by dust and missed by deep optical
surveys, Much deeper and wider ALMA imaging is therefore needed to better
constrain the obscured cosmic star formation history.


title:
Beyond the effective mass approximation: predictive theory of the
  nonlinear optical response of conduction electrons

abstract:
  We present an experimental and computational study of the nonlinear optical
response of conduction electrons to intense terahertz (THz) electric field. Our
observations (saturable absorption and an amplitude-dependent group refractive
index) can be understood on the qualitative level as the breakdown of the
effective mass approximation. However, a predictive theoretical description of
the nonlinearity has been missing. We propose a model based on the
semiclassical electron dynamics, a realistic band structure, and the free
electron Drude parameters to accurately calculate the experimental observables
in InSb. Our results open a path to predictive modeling of the
conduction-electron optical nonlinearity in semiconductors, metamaterials, as
well as high-field effects in THz plasmonics.


title:
Nanoscale orbital excitations and the infrared spectrum of a molecular
  Mott insulator: A15-Cs$_{3}$C$_{60}$

abstract:
  The quantum physics of ions and electrons behind low-energy spectra of
strongly correlated {\it molecular} conductors, superconductors and Mott
insulators is poorly known, yet fascinating especially in orbitally degenerate
cases. The fulleride insulator Cs$_{3}$C$_{60}$ (A15), one such system,
exhibits infrared (IR) spectra with low temperature peak features and
splittings suggestive of static Jahn-Teller distortions with breakdown of
orbital symmetry in the molecular site. That is puzzling, for there is no
detectable static distortion, and because the features and splittings disappear
upon modest heating, which they should not. Taking advantage of the
Mott-induced collapse of electronic wavefunctions from lattice-extended to
nanoscale localized inside a caged molecular site, we show that unbroken spin
and orbital symmetry of the ion multiplets explains the IR spectrum without
adjustable parameters. This demonstrates the importance of a fully quantum
treatment of nuclear positions and orbital momenta in the Mott insulator sites,
dynamically but not statically distorted. The observed demise of these features
with temperature is explained by the thermal population of a multiplet term
whose nuclear positions are essentially undistorted, but whose energy is very
low-lying. That term is in facts a scaled-down orbital excitation analogous to
that of other Mott insulators, with the same spin $1/2$ as the ground state,
but with a larger orbital moment of two instead of one.


title:
The supersingular locus of unitary Shimura varieties with exotic good
  reduction

abstract:
  In this paper, we use a group-theoretic approach to give a concrete
description of the geometric structure of the supersingular locus of unitary
Shimura varieties with exotic good reduction. This approach also is a more
uniform way to prove results of this form obtained previously by, for example,
Vollaard-Wedhorn and Rapoport-Terstiege-Wilson.


title:
Connecting Data Science and Qualitative Interview Insights through
  Sentiment Analysis to Assess Migrants' Emotion States Post-Settlement

abstract:
  Large-scale survey research by social scientists offers general
understandings of migrants' challenges and provides assessments of
post-migration benchmarks like employment, obtention of educational
credentials, and home ownership. Minimal research, however, probes the realm of
emotions or "feeling states" in migration and settlement processes, and it is
often approached through closed-ended survey questions that superficially
assess feeling states. The evaluation of emotions in migration and settlement
has been largely left to qualitative researchers using in-depth, interpretive
methods like semi-structured interviewing. This approach also has major
limitations, namely small sample sizes that capture limited geographic
contexts, heavy time burdens analyzing data, and limits to analytic consistency
given the nuances of qualitative data coding. Information about migrant emotion
states, however, would be valuable to governments and NGOs to enable policy and
program development tailored to migrant challenges and frustrations, and would
thereby stimulate economic development through thriving migrant populations. In
this paper, we present an interdisciplinary pilot project that offers a way
through the methodological impasse by subjecting exhaustive qualitative
interviews of migrants to sentiment analysis using the Python NLTK toolkit. We
propose that data scientists can efficiently and accurately produce large-scale
assessments of migrant feeling states through collaboration with social
scientists.


title: Character Sequence Models for ColorfulWords

abstract:
  We present a neural network architecture to predict a point in color space
from the sequence of characters in the color's name. Using large scale
color--name pairs obtained from an online color design forum, we evaluate our
model on a "color Turing test" and find that, given a name, the colors
predicted by our model are preferred by annotators to color names created by
humans. Our datasets and demo system are available online at colorlab.us.


title:
Transforming building industry and health outcomes through social
  data-supported design

abstract:
  A glaring reality of American industrialized society is that people spend a
tremendous amount of their waking life in their workplace and other interior
environments. Despite the amount of time that we spend in them, many of our
constructed environments that we inhabit are not designed for the people and
communities that rely on them. From a health and wellness perspective, there is
a growing body of research on the ways that our interior environments and lack
of exposure to natural elements systematically impacts our health and strains
our healthcare system. In short, the spaces in which we live and work are a
major public health issue and should be considered in this way. In this paper,
we lay out a vision for using the underleveraged social data-available through
social media-to inform the architecture, developer and real estate industries.
The goal is ultimately a public health initiative: to create spaces that are
healthier, more responsive, equitable and human-centric through social
data-supported design.


title:
Using Natural Language Processing and Qualitative Analysis to Intervene
  in Gang Violence: A Collaboration Between Social Work Researchers and Data
  Scientists

abstract:
  The U.S. has the highest rate of firearm-related deaths when compared to
other industrialized countries. Violence particularly affects low-income, urban
neighborhoods in cities like Chicago, which saw a 40% increase in firearm
violence from 2014 to 2015 to more than 3,000 shooting victims. While recent
studies have found that urban, gang-involved individuals curate a unique and
complex communication style within and between social media platforms,
organizations focused on reducing gang violence are struggling to keep up with
the growing complexity of social media platforms and the sheer volume of data
they present. In this paper, describe the Digital Urban Violence Analysis
Approach (DUVVA), a collaborative qualitative analysis method used in a
collaboration between data scientists and social work researchers to develop a
suite of systems for decoding the high- stress language of urban, gang-involved
youth. Our approach leverages principles of grounded theory when analyzing
approximately 800 tweets posted by Chicago gang members and participation of
youth from Chicago neighborhoods to create a language resource for natural
language processing (NLP) methods. In uncovering the unique language and
communication style, we developed automated tools with the potential to detect
aggressive language on social media and aid individuals and groups in
performing violence prevention and interruption.


title:
The Quantified Community at Red Hook: Urban Sensing and Citizen Science
  in Low-Income Neighborhoods

abstract:
  The Quantified Community (QC)--a long-term neighborhood informatics research
initiative--is a network of instrumented urban neighborhoods that collect,
measure, and analyze data on physical and environmental conditions and human
behavior to better understand how neighborhoods and the built environment
affect individual and social well-being. This initiative is intended to create
a data-enabled research environment to rigorously study the complex
interactions in urban neighborhoods. The QC has initially launched in three
very distinct areas in New York City: at Hudson Yards, a ground-up
"city-within-a-city" of approximately 20 million square feet in Manhattan, in
collaboration with the Related Companies; in Lower Manhattan, a mixed-use
neighborhood that attracts residents, workers, and visitors, in collaboration
with the Alliance for Downtown NY; and in Red Hook, Brooklyn, an
economically-distressed community facing significant development and
demographic changes, in partnership with the Red Hook Initiative. This paper
describes our recent pilot project to deploy novel urban sensors in Red Hook to
collect and analyze quality-of-life measurements at high spatial and temporal
resolution. This effort is complemented by a citizen science initiative to
engage local residents in the data collection and problem-solving process to
drive evidenced-based community decision-making and improve local and city
governance.


title:
Quark-gluon discrimination in the search for gluino pair production at
  the LHC

abstract:
  We study the impact of including quark- and gluon-initiated jet
discrimination in the search for strongly interacting supersymmetric particles
at the LHC. Taking the example of gluino pair production, considerable
improvement is observed in the LHC search reach on including the jet
substructure observables to the standard kinematic variables within a
multivariate analysis. In particular, quark and gluon jet separation has higher
impact in the region of intermediate mass-gap between the gluino and the
lightest neutralino, as the difference between the signal and the standard
model background kinematic distributions is reduced in this region. We also
compare the predictions from different Monte Carlo event generators to estimate
the uncertainty originating from the modelling of the parton shower and
hadronization processes.


title:
Surprises from quenches in long-range interacting systems: Temperature
  inversion and cooling

abstract:
  What happens when one of the parameters governing the dynamics of a
long-range interacting system of particles in thermal equilibrium is abruptly
changed (quenched) to a different value? While a short-range system, under the
same conditions, will relax in time to a new thermal equilibrium with a uniform
temperature across the system, a long-range system shows a fast relaxation to a
nonequilibrium {\em quasistationary state} (QSS). The lifetime of such an
off-equilibrium state diverges with the system size, and the temperature is
non-uniform across the system. Quite surprisingly, the density profile in the
QSS obtained after the quench is anticorrelated with the temperature profile in
space, thus exhibiting the phenomenon of {\em temperature inversion}: denser
regions are colder than sparser ones. We illustrate with extensive molecular
dynamics simulations the ubiquity of this scenario in a prototypical long-range
interacting system subject to a variety of quenching protocols, and in a model
that mimics an experimental setup of atoms interacting with light in an optical
cavity. We further demonstrate how a procedure of iterative quenching combined
with filtering out the high-energy particles in the system may be employed to
cool the system. Temperature inversion is observed in nature in some
astrophysical settings; our results imply that such a phenomenon should be
observable, and could even be exploitable to advantage, also in controlled
laboratory experiments.


title:
Quantum Heat Current under Non-perturbative and Non-Markovian
  Conditions: Applications to Heat Machines

abstract:
  We consider a quantum system strongly coupled to multiple heat baths at
different temperatures. Quantum heat transport phenomena in this system are
investigated using two definitions of the heat current, one in terms of the
system energy, and the other in terms of the bath energy. When we consider
correlations among system-bath interactions (CASBI) -- which have a purely
quantum mechanical origin -- the definition in terms of the bath energy becomes
different. We found that CASBI are necessary to maintain the consistency of the
heat current with thermodynamic laws in the case of strong system-bath
coupling. However, within the context of the quantum master equation approach,
both of these definitions are identical. Through a numerical investigation, we
demonstrate this point for a non-equilibrium spin-boson model and a three-level
heat engine model using the reduced hierarchal equations of motion approach
under strongly coupled and non-Markovian conditions. We observe cyclic behavior
of the heat currents and the work performed by the heat engine,and we find that
their phases depend on the system-bath coupling strength. Through consideration
of the bath heat current, we show that the efficiency of the heat engine
decreases as the strength of the system-bath coupling increases, due to the
CASBI contribution. In the case of a large system-bath coupling, the efficiency
increases further if the bath temperature is decreased, with fixed the ratio of
the bath temperatures, due to the discretized nature of energy eigenstates.
This is also considered to be a unique feature of quantum heat engines.


title: Gene networks accelerate evolution by fitness landscape learning

abstract:
  We consider evolution of a large population, where fitness of each organism
is defined by many phenotypical traits. These traits result from expression of
many genes. We propose a new model of gene regulation, where gene expression is
controlled by a gene network with a threshold mechanism and there is a feedback
between that threshold and gene expression. We show that this regulation is
very powerful: depending on parameters we can obtain any functional connection
between thresholds and genes. Under general assumptions on fitness we prove
that such model organisms are capable, to some extent, to recognize the fitness
landscape. That fitness landscape learning sharply reduces the number of
mutations necessary for adaptation and thus accelerates of evolution. Moreover,
this learning increases phenotype robustness with respect to mutations.
However, this acceleration leads to an additional risk since learning procedure
can produce errors. Finally evolution acceleration reminds races on a rugged
highway: when you speed up, you have more chances to crash. These results
explain recent experimental data on anticipation of environment changes by some
organisms.


title:
Well-posedness of the linearized Prandtl equation around a non-monotonic
  shear flow

abstract:
  In this paper, we prove the well-posedness of the linearized Prandtl equation
around a non-monotonic shear flow in Gevrey class $2-\theta$ for any
$\theta>0$. This result is almost optimal by the ill-posedness result proved by
G\'{e}rard-Varet and Dormy, who construct a class of solution with the growth
like $e^{\sqrt{k}t}$ for the linearized Prandtl equation around a non-monotonic
shear flow.


title:
Evolution of Microstructure and Relaxor Ferroelectric Properties in
  (La_zBa_(1-z)(Ti0.80Sn0.20)O3

abstract:
  We report a study on a series of lanthanum doped barium stannate-titanate
(LBTS) ceramics towards correlating their microstructure with ferroelectric
properties. The samples were prepared by solid state reaction technique and the
XRD analysis indicated predominantly single phase microstructure. Scanning
Electron Microscopy revealed that while a low La doping of 1 atomic % yielded
inhibited grain growth in 1LBTS, higher amounts of La doping yield larger leafy
grains. This peculiar grain growth and microstructure evolution could be
attributed to the combination of the following two competing factors: (i)
suppression of O vacancies due to La doping leading to grain growth inhibition
and (ii) enhancement of mechanism leading to nucleation and growth of 2-D
(leafy) grains for La doping higher than 2 atomic % due to eutectic phenomena.
Dielectric permittivity measurements indicate that addition of La enhances
diffused phase transition in BTS, but its frequency dependence is observed only
at 2 atomic % La doping. This signature relaxor behaviour and the increase in
the intensity of a particular Raman peak with La doping, as well as
non-saturated PE hysteresis loops confirm the presence of polar nano-regions
for 2 and 3 atomic % La doped BTS. However significant enhancement in
dielectric permittivity could not be achieved due to reduced grain size.


title:
Mitigating Pilot Contamination Through Location-Aware Pilot Assignment
  in Massive MIMO Networks

abstract:
  We propose a novel location-aware pilot assignment scheme to mitigate pilot
contamination in massive multiple-input multiple-output (MIMO) networks, where
the channels are subjected to Rician fading. Our proposed scheme utilizes the
location information of users as the input to conduct pilot assignment in the
network. Based on the location information, we first determine the line of
sight (LOS) interference between the intended signal and the interfering
signal. Our analysis reveals that the LOS interference converges to zero as the
number of antennas at the base station (BS) goes to infinity, whereas for
finite number of antennas at the BS the LOS interference indeed depends on
specific pilot allocation strategies. Following this revelation, we assign
pilot sequences to all the users in the massive MIMO network such that the LOS
interference is minimized for finite number of antennas at the BS. Our proposed
scheme outperforms the random pilot assignment in terms of achieving a much
higher uplink sum rate for reasonable values of the Rician K-factor. Moreover,
we propose a new performance metric, which measures the strength of the LOS
interference and demonstrate that it is a good metric to analyze the
performance of pilot assignment schemes. Theoretical analysis is provided and
verified through numerical simulations to support the proposed scheme.


title: The distribution of the Carlitz binomial coefficients modulo a prime

abstract:
  For a nonnegative integer $n$, and a prime $\wp$ in $\mathbb{F}_q[T]$, we
prove a result that provides a method for computing the number of integers $m$
with $0 \le m \le n$ for which the Carlitz binomial coefficients
$\binom{n}{m}_C$ fall into each of the residue classes modulo $\wp$. Our main
result can be viewed as a function field analogue of the Garfield-Wilf theorem.


title:
Memory Visualization for Gated Recurrent Neural Networks in Speech
  Recognition

abstract:
  Recurrent neural networks (RNNs) have shown clear superiority in sequence
modeling, particularly the ones with gated units, such as long short-term
memory (LSTM) and gated recurrent unit (GRU). However, the dynamic properties
behind the remarkable performance remain unclear in many applications, e.g.,
automatic speech recognition (ASR). This paper employs visualization techniques
to study the behavior of LSTM and GRU when performing speech recognition tasks.
Our experiments show some interesting patterns in the gated memory, and some of
them have inspired simple yet effective modifications on the network structure.
We report two of such modifications: (1) lazy cell update in LSTM, and (2)
shortcut connections for residual learning. Both modifications lead to more
comprehensible and powerful networks.


title:
Phase-locked array of quantum cascade lasers with an integrated Talbot
  cavity

abstract:
  We show a phase-locked array of three quantum cascade lasers with an
integrated Talbot cavity at one side of the laser array. The coupling scheme is
called diffraction coupling. By controlling the length of Talbot to be a
quarter of Talbot distance (Zt/4), in-phase mode operation can be selected. The
in-phase operation shows great modal stability under different injection
currents, from the threshold current to the full power current. The far-field
radiation pattern of the in-phase operation contains three lobes, one central
maximum lobe and two side lobes. The interval between adjacent lobes is about
10.5{\deg}. The output power is about 1.5 times that of a single-ridge laser.
Further studies should be taken to achieve better beam performance and reduce
optical losses brought by the integrated Talbot cavity.


title:
RZ Leonis Minoris Bridging between ER Ursae Majoris-Type Dwarf Nova and
  Novalike System

abstract:
  We observed RZ LMi, which is renowned for the extremely (~19d) short
supercycle and is a member of a small, unusual class of cataclysmic variables
called ER UMa-type dwarf novae, in 2013 and 2016. In 2016, the supercycles of
this object substantially lengthened in comparison to the previous measurements
to 35, 32, 60d for three consecutive superoutbursts. We consider that the
object virtually experienced a transition to the novalike state (permanent
superhumper). This observed behavior extremely well reproduced the prediction
of the thermal-tidal instability model. We detected a precursor in the 2016
superoutburst and detected growing (stage A) superhumps with a mean period of
0.0602(1)d in 2016 and in 2013. Combined with the period of superhumps
immediately after the superoutburst, the mass ratio is not as small as in WZ
Sge-type dwarf novae, having orbital periods similar to RZ LMi. By using least
absolute shrinkage and selection operator (Lasso) two-dimensional power
spectra, we detected possible negative superhumps with a period of 0.05710(1)d.
We estimated the orbital period of 0.05792d, which suggests a mass ratio of
0.105(5). This relatively large mass ratio is even above ordinary SU UMa-type
dwarf novae, and it is also possible that the exceptionally high mass-transfer
rate in RZ LMi may be a result of a stripped core evolved secondary which are
evolving toward an AM CVn-type object.


title:
Semi-empirical AGN detection threshold in spectral synthesis studies of
  Lyman-continuum-leaking early-type galaxies

abstract:
  Various lines of evidence suggest that the cores of a large portion of
early-type galaxies (ETGs) are virtually evacuated of warm ionised gas. This
implies that the Lyman-continuum (LyC) radiation produced by an assumed active
galactic nucleus (AGN) can escape from the nuclei of these systems without
being locally reprocessed into nebular emission, which would prevent their
reliable spectroscopic classification as Seyfert galaxies with standard
diagnostic emission-line ratios. The spectral energy distribution (SED) of
these ETGs would then lack nebular emission and be essentially composed of an
old stellar component and the featureless power-law (PL) continuum from the
AGN. A question that arises in this context is whether the AGN component can be
detected with current spectral population synthesis in the optical,
specifically, whether these techniques effectively place an AGN detection
threshold in LyC-leaking galaxies. To quantitatively address this question, we
took a combined approach that involves spectral fitting with STARLIGHT of
synthetic SEDs composed of stellar emission that characterises a 10 Gyr old ETG
and an AGN power-law component that contributes a fraction $0\leq
x_{\mathrm{AGN}} < 1$ of the monochromatic luminosity at $\lambda_0=$ 4020 \AA.
In addition to a set of fits for PL distributions $F_{\nu} \propto
\nu^{-\alpha}$ with the canonical $\alpha=1.5$, we used a base of multiple PLs
with $0.5 \leq \alpha \leq 2$ for a grid of synthetic SEDs with a
signal-to-noise ratio of 5-$10^3$. Our analysis indicates an effective AGN
detection threshold at $x_{\mathrm{AGN}}\simeq 0.26$, which suggests that a
considerable fraction of ETGs hosting significant accretion-powered nuclear
activity may be missing in the AGN demographics.


title:
Non-renormalization theorem in a lattice supersymmetric theory and the
  cyclic Leibniz rule

abstract:
  N=4 supersymmetric quantum mechanical model is formulated on the lattice. Two
supercharges, among four, are exactly conserved with the help of the cyclic
Leibniz rule without spoiling the locality. In use of the cohomological
argument, any possible local terms of the effective action are classified into
two categories which we call type-I and type-II, analogous to the D- and
F-terms in the supersymmetric field theories. We prove non-renormalization
theorem on the type-II terms which include mass and interaction terms with
keeping a lattice constant finite, while type-I terms such as the kinetic terms
have nontrivial quantum corrections.


title:
N-body modeling of globular clusters: Masses, mass-to-light ratios and
  intermediate-mass black holes

abstract:
  We have determined the masses and mass-to-light ratios of 50 Galactic
globular clusters by comparing their velocity dispersion and surface brightness
profiles against a large grid of 900 N-body simulations of star clusters of
varying initial concentration, size and central black hole mass fraction. Our
models follow the evolution of the clusters under the combined effects of
stellar evolution and two-body relaxation allowing us to take the effects of
mass segregation and energy equipartition between stars self-consistently into
account. For a subset of 16 well observed clusters we also derive their
kinematic distances. We find an average mass-to-light ratio of Galactic
globular clusters of $<M/L_V>=1.98 \pm 0.03$, which agrees very well with the
expected M/L ratio if the initial mass function of the clusters was a standard
Kroupa or Chabrier mass function. We do not find evidence for a decrease of the
average mass-to-light ratio with metallicity. The surface brightness and
velocity dispersion profiles of most globular clusters are incompatible with
the presence of intermediate-mass black holes (IMBHs) with more than a few
thousand $M_\odot$ in them. The only clear exception is $\omega$ Cen, where the
velocity dispersion profile provides strong evidence for the presence of a
$\sim$40,000 $M_\odot$ IMBH in the centre of the cluster.


title:
On the divisibility of odd perfect numbers, quasiperfect numbers and
  amicable numbers by a high power of a prime

abstract:
  We shall give an explicit upper bound for the smallest prime factor of
multiperfect numbers of the form $N=p_1^{\alpha_1}\cdots p_s^{\alpha_s}
q_1^{\beta_1}\cdots q_t^{\beta_t}$ with $\beta_1, \ldots, \beta_t$ bounded by a
given constant. We shall also give similar results for quasiperfect numbers and
relatively prime amicable pairs of opposite parity.