title:
Naturalness of Light Neutralino Dark Matter in pMSSM after LHC, XENON100
  and Planck Data

abstract:
  We examine the possibility of a light (below 46 GeV) neutralino dark matter
(DM) candidate within the 19-parameter phenomenological Minimal Supersymmetric
Standard Model (pMSSM) in the light of various recent experimental results,
especially from the LHC, XENON100, and Planck. We also study the extent of
electroweak fine-tuning for such a light neutralino scenario in view of the
null results from the searches for supersymmetry so far. Using a Markov Chain
Monte Carlo likelihood analysis of the full pMSSM parameter space, we find that
a neutralino DM with mass > 10 GeV can in principle still satisfy all the
existing constraints. Our light neutralino solutions can be broadly divided
into two regions: (i) The solutions in the 10 - 30 GeV neutralino mass range
are highly fine-tuned and require the existence of light selectrons (below 100
GeV) in order to satisfy the observed DM relic density. We note that these are
not yet conclusively ruled out by the existing LEP/LHC results, and a dedicated
analysis valid for a non-unified gaugino mass spectrum is required to exclude
this possibility. (ii) The solutions with low fine-tuning are mainly in the 30
- 46 GeV neutralino mass range. However, a major portion of it is already ruled
out by the latest XENON100 upper limits on its spin-independent direct
detection cross section, and the rest of the allowed points are within the
XENON1T projected limit. Thus, we show that the allowed MSSM parameter space
for a light neutralino DM below the LEP limit of 46 GeV, possible in
supersymmetric models without gaugino mass unification, could be completely
accessible in near future. This might be useful in view of the recent claims
for positive hints of a DM signal in some direct detection experiments.


title:
Adaptive High Order Sliding Mode Observer Based Fault Reconstruction for
  a Class of Nonlinear Uncertain Systems: Application to PEM Fuel Cell System

abstract:
  This paper focuses on observer based fault reconstruction for a class of
nonlinear uncertain systems with Lipschitz nonlinearities. An adaptive-gain
Super-Twisting (STW) observer is developed for observing the system states,
where the adaptive law compensates the uncertainty in parameters. The inherent
equivalent output error injection feature of STW algorithm is then used to
reconstruct the fault signal. The performance of the proposed observer is
validated through a Hardware-In-Loop (HIL) simulator which consists of a
commercial twin screw compressor and a real time Polymer Electrolyte Membrane
fuel cell emulation system. The simulation results illustrate the feasibility
and effectiveness of the proposed approach for application to fuel cell
systems.


title: Lower bounds for k-distance approximation

abstract:
  Consider a set P of N random points on the unit sphere of dimension $d-1$,
and the symmetrized set S = P union (-P). The halving polyhedron of S is
defined as the convex hull of the set of centroids of N distinct points in S.
We prove that after appropriate rescaling this halving polyhedron is Hausdorff
close to the unit ball with high probability, as soon as the number of points
grows like $Omega(d log(d))$. From this result, we deduce probabilistic lower
bounds on the complexity of approximations of the distance to the empirical
measure on the point set by distance-like functions.


title:
Lipschitz stability estimate in the inverse Robin problem for the Stokes
  system

abstract:
  We are interested in the inverse problem of recovering a Robin coefficient
defined on some non accessible part of the boundary from available data on
another part of the boundary in the nonstationary Stokes system. We prove a
Lipschitz stability estimate under the \textit{a priori} assumption that the
Robin coefficient lives in some compact and convex subset of a finite
dimensional vectorial subspace of the set of continuous functions. To do so, we
use a theorem proved by L. Bourgeois which establishes Lipschitz stability
estimates for a class of inverse problems in an abstract framework.


title: Riemannian Geometry

abstract:
  These notes on Riemannian geometry use the bases bundle and frame bundle, as
in Geometry of Manifolds, to express the geometric structures. It has more
problems and omits the background material. It starts with the definition of
Riemannian and semi-Riemannian structures on manifolds. Affine connections,
geodesics, torsion and curvature, the exponential map, and the Riemannian
connection follow quickly. The Taylor series for of the metric in normal
coordinates is an unusual feature. The last third covers, first and second
variation of energy, completeness, cut points, the Hadamard-Cartan theorem, and
finishes with the use of matrix Riccati equations to prove the volume
comparison theorem. There is a comprehensive index.


title: RES - a Relative Method for Evidential Reasoning

abstract:
  In this paper we describe a novel method for evidential reasoning [1]. It
involves modelling the process of evidential reasoning in three steps, namely,
evidence structure construction, evidence accumulation, and decision making.
The proposed method, called RES, is novel in that evidence strength is
associated with an evidential support relationship (an argument) between a pair
of statements and such strength is carried by comparison between arguments.
This is in contrast to the onventional approaches, where evidence strength is
represented numerically and is associated with a statement.


title: Optimizing Causal Orderings for Generating DAGs from Data

abstract:
  An algorithm for generating the structure of a directed acyclic graph from
data using the notion of causal input lists is presented. The algorithm
manipulates the ordering of the variables with operations which very much
resemble arc reversal. Operations are only applied if the DAG after the
operation represents at least the independencies represented by the DAG before
the operation until no more arcs can be removed from the DAG. The resulting DAG
is a minimal l-map.


title: Modal Logics for Qualitative Possibility and Beliefs

abstract:
  Possibilistic logic has been proposed as a numerical formalism for reasoning
with uncertainty. There has been interest in developing qualitative accounts of
possibility, as well as an explanation of the relationship between possibility
and modal logics. We present two modal logics that can be used to represent and
reason with qualitative statements of possibility and necessity. Within this
modal framework, we are able to identify interesting relationships between
possibilistic logic, beliefs and conditionals. In particular, the most natural
conditional definable via possibilistic means for default reasoning is
identical to Pearl's conditional for e-semantics.


title: Structural Controllability and Observability in Influence Diagrams

abstract:
  Influence diagram is a graphical representation of belief networks with
uncertainty. This article studies the structural properties of a probabilistic
model in an influence diagram. In particular, structural controllability
theorems and structural observability theorems are developed and algorithms are
formulated. Controllability and observability are fundamental concepts in
dynamic systems (Luenberger 1979). Controllability corresponds to the ability
to control a system while observability analyzes the inferability of its
variables. Both properties can be determined by the ranks of the system
matrices. Structural controllability and observability, on the other hand,
analyze the property of a system with its structure only, without the specific
knowledge of the values of its elements (tin 1974, Shields and Pearson 1976).
The structural analysis explores the connection between the structure of a
model and the functional dependence among its elements. It is useful in
comprehending problem and formulating solution by challenging the underlying
intuitions and detecting inconsistency in a model. This type of qualitative
reasoning can sometimes provide insight even when there is insufficient
numerical information in a model.


title: Lattice-Based Graded Logic: a Multimodal Approach

abstract:
  Experts do not always feel very, comfortable when they have to give precise
numerical estimations of certainty degrees. In this paper we present a
qualitative approach which allows for attaching partially ordered symbolic
grades to logical formulas. Uncertain information is expressed by means of
parameterized modal operators. We propose a semantics for this multimodal logic
and give a sound and complete axiomatization. We study the links with related
approaches and suggest how this framework might be used to manage both
uncertain and incomplere knowledge.


title: Dynamic Network Models for Forecasting

abstract:
  We have developed a probabilistic forecasting methodology through a synthesis
of belief network models and classical time-series analysis. We present the
dynamic network model (DNM) and describe methods for constructing, refining,
and performing inference with this representation of temporal probabilistic
knowledge. The DNM representation extends static belief-network models to more
general dynamic forecasting models by integrating and iteratively refining
contemporaneous and time-lagged dependencies. We discuss key concepts in terms
of a model for forecasting U.S. car sales in Japan.


title: Reformulating Inference Problems Through Selective Conditioning

abstract:
  We describe how we selectively reformulate portions of a belief network that
pose difficulties for solution with a stochastic-simulation algorithm. With
employ the selective conditioning approach to target specific nodes in a belief
network for decomposition, based on the contribution the nodes make to the
tractability of stochastic simulation. We review previous work on BNRAS
algorithms- randomized approximation algorithms for probabilistic inference. We
show how selective conditioning can be employed to reformulate a single BNRAS
problem into multiple tractable BNRAS simulation problems. We discuss how we
can use another simulation algorithm-logic sampling-to solve a component of the
inference problem that provides a means for knitting the solutions of
individual subproblems into a final result. Finally, we analyze tradeoffs among
the computational subtasks associated with the selective conditioning approach
to reformulation.


title: Entropy and Belief Networks

abstract:
  The product expansion of conditional probabilities for belief nets is not
maximum entropy. This appears to deny a desirable kind of assurance for the
model. However, a kind of guarantee that is almost as strong as maximum entropy
can be derived. Surprisingly, a variant model also exhibits the guarantee, and
for many cases obtains a higher performance score than the product expansion.


title: Parallelizing Probabilistic Inference: Some Early Explorations

abstract:
  We report on an experimental investigation into opportunities for parallelism
in beliefnet inference. Specifically, we report on a study performed of the
available parallelism, on hypercube style machines, of a set of randomly
generated belief nets, using factoring (SPI) style inference algorithms. Our
results indicate that substantial speedup is available, but that it is
available only through parallelization of individual conformal product
operations, and depends critically on finding an appropriate factoring. We find
negligible opportunity for parallelism at the topological, or clustering tree,
level.


title: Objection-Based Causal Networks

abstract:
  This paper introduces the notion of objection-based causal networks which
resemble probabilistic causal networks except that they are quantified using
objections. An objection is a logical sentence and denotes a condition under
which a, causal dependency does not exist. Objection-based causal networks
enjoy almost all the properties that make probabilistic causal networks
popular, with the added advantage that objections are, arguably more intuitive
than probabilities.


title: A Symbolic Approach to Reasoning with Linguistic Quantifiers

abstract:
  This paper investigates the possibility of performing automated reasoning in
probabilistic logic when probabilities are expressed by means of linguistic
quantifiers. Each linguistic term is expressed as a prescribed interval of
proportions. Then instead of propagating numbers, qualitative terms are
propagated in accordance with the numerical interpretation of these terms. The
quantified syllogism, modelling the chaining of probabilistic rules, is studied
in this context. It is shown that a qualitative counterpart of this syllogism
makes sense, and is relatively independent of the threshold defining the
linguistically meaningful intervals, provided that these threshold values
remain in accordance with the intuition. The inference power is less than that
of a full-fledged probabilistic con-quaint propagation device but better
corresponds to what could be thought of as commonsense probabilistic reasoning.


title:
Possibilistic Assumption based Truth Maintenance System, Validation in a
  Data Fusion Application

abstract:
  Data fusion allows the elaboration and the evaluation of a situation
synthesized from low level informations provided by different kinds of sensors.
The fusion of the collected data will result in fewer and higher level
informations more easily assessed by a human operator and that will assist him
effectively in his decision process. In this paper we present the suitability
and the advantages of using a Possibilistic Assumption based Truth Maintenance
System (n-ATMS) in a data fusion military application. We first describe the
problem, the needed knowledge representation formalisms and problem solving
paradigms. Then we remind the reader of the basic concepts of ATMSs,
Possibilistic Logic and 11-ATMSs. Finally we detail the solution to the given
data fusion problem and conclude with the results and comparison with a
non-possibilistic solution.


title: An Entropy-based Learning Algorithm of Bayesian Conditional Trees

abstract:
  This article offers a modification of Chow and Liu's learning algorithm in
the context of handwritten digit recognition. The modified algorithm directs
the user to group digits into several classes consisting of digits that are
hard to distinguish and then constructing an optimal conditional tree
representation for each class of digits instead of for each single digit as
done by Chow and Liu (1968). Advantages and extensions of the new method are
discussed. Related works of Wong and Wang (1977) and Wong and Poon (1989) which
offer a different entropy-based learning algorithm are shown to rest on
inappropriate assumptions.


title: Knowledge Integration for Conditional Probability Assessments

abstract:
  In the probabilistic approach to uncertainty management the input knowledge
is usually represented by means of some probability distributions. In this
paper we assume that the input knowledge is given by two discrete conditional
probability distributions, represented by two stochastic matrices P and Q. The
consistency of the knowledge base is analyzed. Coherence conditions and
explicit formulas for the extension to marginal distributions are obtained in
some special cases.


title: Integrating Model Construction and Evaluation

abstract:
  To date, most probabilistic reasoning systems have relied on a fixed belief
network constructed at design time. The network is used by an application
program as a representation of (in)dependencies in the domain. Probabilistic
inference algorithms operate over the network to answer queries. Recognizing
the inflexibility of fixed models has led researchers to develop automated
network construction procedures that use an expressive knowledge base to
generate a network that can answer a query. Although more flexible than fixed
model approaches, these construction procedures separate construction and
evaluation into distinct phases. In this paper we develop an approach to
combining incremental construction and evaluation of a partial probability
model. The combined method holds promise for improved methods for control of
model construction based on a trade-off between fidelity of results and cost of
construction.


title: Reasoning With Qualitative Probabilities Can Be Tractable

abstract:
  We recently described a formalism for reasoning with if-then rules that re
expressed with different levels of firmness [18]. The formalism interprets
these rules as extreme conditional probability statements, specifying orders of
magnitude of disbelief, which impose constraints over possible rankings of
worlds. It was shown that, once we compute a priority function Z+ on the rules,
the degree to which a given query is confirmed or denied can be computed in
O(log n`) propositional satisfiability tests, where n is the number of rules in
the knowledge base. In this paper, we show that computing Z+ requires O(n2 X
log n) satisfiability tests, not an exponential number as was conjectured in
[18], which reduces to polynomial complexity in the case of Horn expressions.
We also show how reasoning with imprecise observations can be incorporated in
our formalism and how the popular notions of belief revision and epistemic
entrenchment are embodied naturally and tractably.


title: A computational scheme for Reasoning in Dynamic Probabilistic Networks

abstract:
  A computational scheme for reasoning about dynamic systems using (causal)
probabilistic networks is presented. The scheme is based on the framework of
Lauritzen and Spiegelhalter (1988), and may be viewed as a generalization of
the inference methods of classical time-series analysis in the sense that it
allows description of non-linear, multivariate dynamic systems with complex
conditional independence structures. Further, the scheme provides a method for
efficient backward smoothing and possibilities for efficient, approximate
forecasting methods. The scheme has been implemented on top of the HUGIN shell.


title:
The Dynamic of Belief in the Transferable Belief Model and
  Specialization-Generalization Matrices

abstract:
  The fundamental updating process in the transferable belief model is related
to the concept of specialization and can be described by a specialization
matrix. The degree of belief in the truth of a proposition is a degree of
justified support. The Principle of Minimal Commitment implies that one should
never give more support to the truth of a proposition than justified. We show
that Dempster's rule of conditioning corresponds essentially to the least
committed specialization, and that Dempster's rule of combination results
essentially from commutativity requirements. The concept of generalization,
dual to thc concept of specialization, is described.


title: A Note on the Measure of Discord

abstract:
  A new entropy-like measure as well as a new measure of total uncertainty
pertaining to the Dempster-Shafer theory are introduced. It is argued that
these measures are better justified than any of the previously proposed
candidates.


title: Semantics for Probabilistic Inference

abstract:
  A number of writers(Joseph Halpern and Fahiem Bacchus among them) have
offered semantics for formal languages in which inferences concerning
probabilities can be made. Our concern is different. This paper provides a
formalization of nonmonotonic inferences in which the conclusion is supported
only to a certain degree. Such inferences are clearly 'invalid' since they must
allow the falsity of a conclusion even when the premises are true.
Nevertheless, such inferences can be characterized both syntactically and
semantically. The 'premises' of probabilistic arguments are sets of statements
(as in a database or knowledge base), the conclusions categorical statements in
the language. We provide standards for both this form of inference, for which
high probability is required, and for an inference in which the conclusion is
qualified by an intermediate interval of support.


title: Some Problems for Convex Bayesians

abstract:
  We discuss problems for convex Bayesian decision making and uncertainty
representation. These include the inability to accommodate various natural and
useful constraints and the possibility of an analog of the classical Dutch Book
being made against an agent behaving in accordance with convex Bayesian
prescriptions. A more general set-based Bayesianism may be as tractable and
would avoid the difficulties we raise.


title:
Bayesian Meta-Reasoning: Determining Model Adequacy from Within a Small
  World

abstract:
  This paper presents a Bayesian framework for assessing the adequacy of a
model without the necessity of explicitly enumerating a specific alternate
model. A test statistic is developed for tracking the performance of the model
across repeated problem instances. Asymptotic methods are used to derive an
approximate distribution for the test statistic. When the model is rejected,
the individual components of the test statistic can be used to guide search for
an alternate model.


title: The Bounded Bayesian

abstract:
  The ideal Bayesian agent reasons from a global probability model, but real
agents are restricted to simplified models which they know to be adequate only
in restricted circumstances. Very little formal theory has been developed to
help fallibly rational agents manage the process of constructing and revising
small world models. The goal of this paper is to present a theoretical
framework for analyzing model management approaches. For a probability
forecasting problem, a search process over small world models is analyzed as an
approximation to a larger-world model which the agent cannot explicitly
enumerate or compute. Conditions are given under which the sequence of
small-world models converges to the larger-world probabilities.


title:
Representing Context-Sensitive Knowledge in a Network Formalism: A
  Preliminary Report

abstract:
  Automated decision making is often complicated by the complexity of the
knowledge involved. Much of this complexity arises from the context sensitive
variations of the underlying phenomena. We propose a framework for representing
descriptive, context-sensitive knowledge. Our approach attempts to integrate
categorical and uncertain knowledge in a network formalism. This paper outlines
the basic representation constructs, examines their expressiveness and
efficiency, and discusses the potential applications of the framework.


title: A Probabilistic Network of Predicates

abstract:
  Bayesian networks are directed acyclic graphs representing independence
relationships among a set of random variables. A random variable can be
regarded as a set of exhaustive and mutually exclusive propositions. We argue
that there are several drawbacks resulting from the propositional nature and
acyclic structure of Bayesian networks. To remedy these shortcomings, we
propose a probabilistic network where nodes represent unary predicates and
which may contain directed cycles. The proposed representation allows us to
represent domain knowledge in a single static network even though we cannot
determine the instantiations of the predicates before hand. The ability to deal
with cycles also enables us to handle cyclic causal tendencies and to recognize
recursive plans.


title: Representing Heuristic Knowledge in D-S Theory

abstract:
  The Dempster-Shafer theory of evidence has been used intensively to deal with
uncertainty in knowledge-based systems. However the representation of uncertain
relationships between evidence and hypothesis groups (heuristic knowledge) is
still a major research problem. This paper presents an approach to representing
such heuristic knowledge by evidential mappings which are defined on the basis
of mass functions. The relationships between evidential mappings and multi
valued mappings, as well as between evidential mappings and Bayesian multi-
valued causal link models in Bayesian theory are discussed. Following this the
detailed procedures for constructing evidential mappings for any set of
heuristic rules are introduced. Several situations of belief propagation are
discussed.


title: The Topological Fusion of Bayes Nets

abstract:
  Bayes nets are relatively recent innovations. As a result, most of their
theoretical development has focused on the simplest class of single-author
models. The introduction of more sophisticated multiple-author settings raises
a variety of interesting questions. One such question involves the nature of
compromise and consensus. Posterior compromises let each model process all data
to arrive at an independent response, and then split the difference. Prior
compromises, on the other hand, force compromise to be reached on all points
before data is observed. This paper introduces prior compromises in a Bayes net
setting. It outlines the problem and develops an efficient algorithm for fusing
two directed acyclic graphs into a single, consensus structure, which may then
be used as the basis of a prior compromise.


title:
Calculating Uncertainty Intervals From Conditional Convex Sets of
  Probabilities

abstract:
  In Moral, Campos (1991) and Cano, Moral, Verdegay-Lopez (1991) a new method
of conditioning convex sets of probabilities has been proposed. The result of
it is a convex set of non-necessarily normalized probability distributions. The
normalizing factor of each probability distribution is interpreted as the
possibility assigned to it by the conditioning information. From this, it is
deduced that the natural value for the conditional probability of an event is a
possibility distribution. The aim of this paper is to study methods of
transforming this possibility distribution into a probability (or uncertainty)
interval. These methods will be based on the use of Sugeno and Choquet
integrals. Their behaviour will be compared in basis to some selected examples.


title: Sensor Validation Using Dynamic Belief Networks

abstract:
  The trajectory of a robot is monitored in a restricted dynamic environment
using light beam sensor data. We have a Dynamic Belief Network (DBN), based on
a discrete model of the domain, which provides discrete monitoring analogous to
conventional quantitative filter techniques. Sensor observations are added to
the basic DBN in the form of specific evidence. However, sensor data is often
partially or totally incorrect. We show how the basic DBN, which infers only an
impossible combination of evidence, may be modified to handle specific types of
incorrect data which may occur in the domain. We then present an extension to
the DBN, the addition of an invalidating node, which models the status of the
sensor as working or defective. This node provides a qualitative explanation of
inconsistent data: it is caused by a defective sensor. The connection of
successive instances of the invalidating node models the status of a sensor
over time, allowing the DBN to handle both persistent and intermittent faults.


title: Empirical Probabilities in Monadic Deductive Databases

abstract:
  We address the problem of supporting empirical probabilities in monadic logic
databases. Though the semantics of multivalued logic programs has been studied
extensively, the treatment of probabilities as results of statistical findings
has not been studied in logic programming/deductive databases. We develop a
model-theoretic characterization of logic databases that facilitates such a
treatment. We present an algorithm for checking consistency of such databases
and prove its total correctness. We develop a sound and complete query
processing procedure for handling queries to such databases.


title: aHUGIN: A System Creating Adaptive Causal Probabilistic Networks

abstract:
  The paper describes aHUGIN, a tool for creating adaptive systems. aHUGIN is
an extension of the HUGIN shell, and is based on the methods reported by
Spiegelhalter and Lauritzen (1990a). The adaptive systems resulting from aHUGIN
are able to adjust the C011ditional probabilities in the model. A short
analysis of the adaptation task is given and the features of aHUGIN are
described. Finally a session with experiments is reported and the results are
discussed.


title: MESA: Maximum Entropy by Simulated Annealing

abstract:
  Probabilistic reasoning systems combine different probabilistic rules and
probabilistic facts to arrive at the desired probability values of
consequences. In this paper we describe the MESA-algorithm (Maximum Entropy by
Simulated Annealing) that derives a joint distribution of variables or
propositions. It takes into account the reliability of probability values and
can resolve conflicts between contradictory statements. The joint distribution
is represented in terms of marginal distributions and therefore allows to
process large inference networks and to determine desired probability values
with high precision. The procedure derives a maximum entropy distribution
subject to the given constraints. It can be applied to inference networks of
arbitrary topology and may be extended into a number of directions.


title: Decision Methods for Adaptive Task-Sharing in Associate Systems

abstract:
  This paper describes some results of research on associate systems:
knowledge-based systems that flexibly and adaptively support their human users
in carrying out complex, time-dependent problem-solving tasks under
uncertainty. Based on principles derived from decision theory and decision
analysis, a problem-solving approach is presented which can overcome many of
the limitations of traditional expert-systems. This approach implements an
explicit model of the human user's problem-solving capabilities as an integral
element in the overall problem solving architecture. This integrated model,
represented as an influence diagram, is the basis for achieving adaptive task
sharing behavior between the associate system and the human user. This
associate system model has been applied toward ongoing research on a Mars Rover
Manager's Associate (MRMA). MRMA's role would be to manage a small fleet of
robotic rovers on the Martian surface. The paper describes results for a
specific scenario where MRMA examines the benefits and costs of consulting
human experts on Earth to assist a Mars rover with a complex resource
management decision.


title: Modeling Uncertain Temporal Evolutions in Model-Based Diagnosis

abstract:
  Although the notion of diagnostic problem has been extensively investigated
in the context of static systems, in most practical applications the behavior
of the modeled system is significantly variable during time. The goal of the
paper is to propose a novel approach to the modeling of uncertainty about
temporal evolutions of time-varying systems and a characterization of
model-based temporal diagnosis. Since in most real world cases knowledge about
the temporal evolution of the system to be diagnosed is uncertain, we consider
the case when probabilistic temporal knowledge is available for each component
of the system and we choose to model it by means of Markov chains. In fact, we
aim at exploiting the statistical assumptions underlying reliability theory in
the context of the diagnosis of timevarying systems. We finally show how to
exploit Markov chain theory in order to discard, in the diagnostic process,
very unlikely diagnoses.


title:
Guess-And-Verify Heuristics for Reducing Uncertainties in Expert
  Classification Systems

abstract:
  An expert classification system having statistical information about the
prior probabilities of the different classes should be able to use this
knowledge to reduce the amount of additional information that it must collect,
e.g., through questions, in order to make a correct classification. This paper
examines how best to use such prior information and additional
information-collection opportunities to reduce uncertainty about the class to
which a case belongs, thus minimizing the average cost or effort required to
correctly classify new cases.


title:
R&D Analyst: An Interactive Approach to Normative Decision System Model
  Construction

abstract:
  This paper describes the architecture of R&D Analyst, a commercial
intelligent decision system for evaluating corporate research and development
projects and portfolios. In analyzing projects, R&D Analyst interactively
guides a user in constructing an influence diagram model for an individual
research project. The system's interactive approach can be clearly explained
from a blackboard system perspective. The opportunistic reasoning emphasis of
blackboard systems satisfies the flexibility requirements of model
construction, thereby suggesting that a similar architecture would be valuable
for developing normative decision systems in other domains. Current research is
aimed at extending the system architecture to explicitly consider of sequential
decisions involving limited temporal, financial, and physical resources.


title:
Possibilistic Constraint Satisfaction Problems or "How to handle soft
  constraints?"

abstract:
  Many AI synthesis problems such as planning or scheduling may be modelized as
constraint satisfaction problems (CSP). A CSP is typically defined as the
problem of finding any consistent labeling for a fixed set of variables
satisfying all given constraints between these variables. However, for many
real tasks such as job-shop scheduling, time-table scheduling, design?, all
these constraints have not the same significance and have not to be necessarily
satisfied. A first distinction can be made between hard constraints, which
every solution should satisfy and soft constraints, whose satisfaction has not
to be certain. In this paper, we formalize the notion of possibilistic
constraint satisfaction problems that allows the modeling of uncertainly
satisfied constraints. We use a possibility distribution over labelings to
represent respective possibilities of each labeling. Necessity-valued
constraints allow a simple expression of the respective certainty degrees of
each constraint. The main advantage of our approach is its integration in the
CSP technical framework. Most classical techniques, such as Backtracking (BT),
arcconsistency enforcing (AC) or Forward Checking have been extended to handle
possibilistics CSP and are effectively implemented. The utility of our approach
is demonstrated on a simple design problem.


title: Decision Making Using Probabilistic Inference Methods

abstract:
  The analysis of decision making under uncertainty is closely related to the
analysis of probabilistic inference. Indeed, much of the research into
efficient methods for probabilistic inference in expert systems has been
motivated by the fundamental normative arguments of decision theory. In this
paper we show how the developments underlying those efficient methods can be
applied immediately to decision problems. In addition to general approaches
which need know nothing about the actual probabilistic inference method, we
suggest some simple modifications to the clustering family of algorithms in
order to efficiently incorporate decision making capabilities.


title: Conditional Independence in Uncertainty Theories

abstract:
  This paper introduces the notions of independence and conditional
independence in valuation-based systems (VBS). VBS is an axiomatic framework
capable of representing many different uncertainty calculi. We define
independence and conditional independence in terms of factorization of the
joint valuation. The definitions of independence and conditional independence
in VBS generalize the corresponding definitions in probability theory. Our
definitions apply not only to probability theory, but also to Dempster-Shafer's
belief-function theory, Spohn's epistemic-belief theory, and Zadeh's
possibility theory. In fact, they apply to any uncertainty calculi that fit in
the framework of valuation-based systems.


title:
The Nature of the Unnormalized Beliefs Encountered in the Transferable
  Belief Model

abstract:
  Within the transferable belief model, positive basic belief masses can be
allocated to the empty set, leading to unnormalized belief functions. The
nature of these unnormalized beliefs is analyzed.


title: Intuitions about Ordered Beliefs Leading to Probabilistic Models

abstract:
  The general use of subjective probabilities to model belief has been
justified using many axiomatic schemes. For example, ?consistent betting
behavior' arguments are well-known. To those not already convinced of the
unique fitness and generality of probability models, such justifications are
often unconvincing. The present paper explores another rationale for
probability models. ?Qualitative probability,' which is known to provide
stringent constraints on belief representation schemes, is derived from five
simple assumptions about relationships among beliefs. While counterparts of
familiar rationality concepts such as transitivity, dominance, and consistency
are used, the betting context is avoided. The gap between qualitative
probability and probability proper can be bridged by any of several additional
assumptions. The discussion here relies on results common in the recent AI
literature, introducing a sixth simple assumption. The narrative emphasizes
models based on unique complete orderings, but the rationale extends easily to
motivate set-valued representations of partial orderings as well.


title:
Expressing Relational and Temporal Knowledge in Visual Probabilistic
  Networks

abstract:
  Bayesian networks have been used extensively in diagnostic tasks such as
medicine, where they represent the dependency relations between a set of
symptoms and a set of diseases. A criticism of this type of knowledge
representation is that it is restricted to this kind of task, and that it
cannot cope with the knowledge required in other artificial intelligence
applications. For example, in computer vision, we require the ability to model
complex knowledge, including temporal and relational factors. In this paper we
extend Bayesian networks to model relational and temporal knowledge for
high-level vision. These extended networks have a simple structure which
permits us to propagate probability efficiently. We have applied them to the
domain of endoscopy, illustrating how the general modelling principles can be
used in specific cases.


title: A Fuzzy Logic Approach to Target Tracking

abstract:
  This paper discusses a target tracking problem in which no dynamic
mathematical model is explicitly assumed. A nonlinear filter based on the fuzzy
If-then rules is developed. A comparison with a Kalman filter is made, and
empirical results show that the performance of the fuzzy filter is better.
Intensive simulations suggest that theoretical justification of the empirical
results is possible.


title: Towards Precision of Probabilistic Bounds Propagation

abstract:
  The DUCK-calculus presented here is a recent approach to cope with
probabilistic uncertainty in a sound and efficient way. Uncertain rules with
bounds for probabilities and explicit conditional independences can be
maintained incrementally. The basic inference mechanism relies on local bounds
propagation, implementable by deductive databases with a bottom-up fixpoint
evaluation. In situations, where no precise bounds are deducible, it can be
combined with simple operations research techniques on a local scope. In
particular, we provide new precise analytical bounds for probabilistic
entailment.


title:
An Algorithm for Deciding if a Set of Observed Independencies Has a
  Causal Explanation

abstract:
  In a previous paper [Pearl and Verma, 1991] we presented an algorithm for
extracting causal influences from independence information, where a causal
influence was defined as the existence of a directed arc in all minimal causal
models consistent with the data. In this paper we address the question of
deciding whether there exists a causal model that explains ALL the observed
dependencies and independencies. Formally, given a list M of conditional
independence statements, it is required to decide whether there exists a
directed acyclic graph (dag) D that is perfectly consistent with M, namely,
every statement in M, and no other, is reflected via dseparation in D. We
present and analyze an effective algorithm that tests for the existence of such
a day, and produces one, if it exists.


title: Generalizing Jeffrey Conditionalization

abstract:
  Jeffrey's rule has been generalized by Wagner to the case in which new
evidence bounds the possible revisions of a prior probability below by a
Dempsterian lower probability. Classical probability kinematics arises within
this generalization as the special case in which the evidentiary focal elements
of the bounding lower probability are pairwise disjoint. We discuss a twofold
extension of this generalization, first allowing the lower bound to be any
two-monotone capacity and then allowing the prior to be a lower envelope.


title: Interval Structure: A Framework for Representing Uncertain Information

abstract:
  In this paper, a unified framework for representing uncertain information
based on the notion of an interval structure is proposed. It is shown that the
lower and upper approximations of the rough-set model, the lower and upper
bounds of incidence calculus, and the belief and plausibility functions all
obey the axioms of an interval structure. An interval structure can be used to
synthesize the decision rules provided by the experts. An efficient algorithm
to find the desirable set of rules is developed from a set of sound and
complete inference axioms.


title: Exploring Localization in Bayesian Networks for Large Expert Systems

abstract:
  Current Bayesian net representations do not consider structure in the domain
and include all variables in a homogeneous network. At any time, a human
reasoner in a large domain may direct his attention to only one of a number of
natural subdomains, i.e., there is ?localization' of queries and evidence. In
such a case, propagating evidence through a homogeneous network is inefficient
since the entire network has to be updated each time. This paper presents
multiply sectioned Bayesian networks that enable a (localization preserving)
representation of natural subdomains by separate Bayesian subnets. The subnets
are transformed into a set of permanent junction trees such that evidential
reasoning takes place at only one of them at a time. Probabilities obtained are
identical to those that would be obtained from the homogeneous network. We
discuss attention shift to a different junction tree and propagation of
previously acquired evidence. Although the overall system can be large,
computational requirements are governed by the size of only one junction tree.


title: A Decision Calculus for Belief Functions in Valuation-Based Systems

abstract:
  Valuation-based system (VBS) provides a general framework for representing
knowledge and drawing inferences under uncertainty. Recent studies have shown
that the semantics of VBS can represent and solve Bayesian decision problems
(Shenoy, 1991a). The purpose of this paper is to propose a decision calculus
for Dempster-Shafer (D-S) theory in the framework of VBS. The proposed calculus
uses a weighting factor whose role is similar to the probabilistic
interpretation of an assumption that disambiguates decision problems
represented with belief functions (Strat 1990). It will be shown that with the
presented calculus, if the decision problems are represented in the valuation
network properly, we can solve the problems by using fusion algorithm (Shenoy
1991a). It will also be shown the presented decision calculus can be reduced to
the calculus for Bayesian probability theory when probabilities, instead of
belief functions, are given.


title: Sidestepping the Triangulation Problem in Bayesian Net Computations

abstract:
  This paper presents a new approach for computing posterior probabilities in
Bayesian nets, which sidesteps the triangulation problem. The current state of
art is the clique tree propagation approach. When the underlying graph of a
Bayesian net is triangulated, this approach arranges its cliques into a tree
and computes posterior probabilities by appropriately passing around messages
in that tree. The computation in each clique is simply direct marginalization.
When the underlying graph is not triangulated, one has to first triangulated it
by adding edges. Referred to as the triangulation problem, the problem of
finding an optimal or even a ?good? triangulation proves to be difficult. In
this paper, we propose to first decompose a Bayesian net into smaller
components by making use of Tarjan's algorithm for decomposing an undirected
graph at all its minimal complete separators. Then, the components are arranged
into a tree and posterior probabilities are computed by appropriately passing
around messages in that tree. The computation in each component is carried out
by repeating the whole procedure from the beginning. Thus the triangulation
problem is sidestepped.


title: Generalized Measures for the Evaluation of Community Detection Methods

abstract:
  Community detection can be considered as a variant of cluster analysis
applied to complex networks. For this reason, all existing studies have been
using tools derived from this field when evaluating community detection
algorithms. However, those are not completely relevant in the context of
network analysis, because they ignore an essential part of the available
information: the network structure. Therefore, they can lead to incorrect
interpretations. In this article, we review these measures, and illustrate this
limitation. We propose a modification to solve this problem, and apply it to
the three most widespread measures: purity, Rand index and normalized mutual
information (NMI). We then perform an experimental evaluation on artificially
generated networks with realistic community structure. We assess the relevance
of the modified measures by comparison with their traditional counterparts, and
also relatively to the topological properties of the community structures. On
these data, the modified NMI turns out to provide the most relevant results.


title: Fractional Order Hybrid Systems and Their Stability

abstract:
  This paper deals with hybrid systems (HS) with fractional order dynamics and
their stability. The stability of two particular types of fractional order
hybrid systems (FOHS), i.e., switching and reset control systems, is studied.
Common Lyapunov method, as well as its frequency domain equivalence, are
generalized for the former systems and, for the latter, H$_{\beta}$-condition
is used --frequency domain equivalence of Lyapunov-like method for reset
control systems. The applicability and efficiency of the proposed methods are
shown by some illustrative examples.


title:
Toward a comprehensive model for feedback by active galactic nuclei: new
  insights from M87 observations by LOFAR, Fermi and H.E.S.S

abstract:
  Feedback by active galactic nuclei (AGNs) appears to be critical in balancing
radiative cooling of the low-entropy gas at the centers of galaxy clusters and
in mitigating the star formation of elliptical galaxies. New observations of
M87 enable us to put forward a comprehensive model for the physical heating
mechanism. Low-frequency radio observations by LOFAR revealed the absence of
fossil cosmic-ray (CR) electrons in the radio halo surrounding M87. This puzzle
can be resolved by accounting for the CR release from the radio cocoons and the
subsequent mixing of CRs with the dense ambient intracluster gas, which
thermalizes the electrons on a timescale similar to the radio halo age of 40
Myr. Hadronic interactions of similarly injected CR protons with the ambient
gas should produce an observable gamma-ray signal in accordance with the steady
emission of the low state of M87 detected by Fermi and H.E.S.S. Hence, we
normalize the CR population to the gamma-ray emission, which shows the same
spectral slope as the CR injection spectrum probed by LOFAR, thereby supporting
a common origin. We show that CRs, which stream at the Alfven velocity with
respect to the plasma rest frame, heat the surrounding thermal plasma at a rate
that balances that of radiative cooling on average at each radius. However, the
resulting global thermal equilibrium is locally unstable and allows for the
formation of the observed cooling multi-phase medium through thermal
instability. Provided that CR heating balances cooling during the emerging
"cooling flow," the collapse of the majority of the gas is halted around 1 keV
- in accordance with X-ray data. We show that both the existence of a
temperature floor and the similar radial scaling of the heating and cooling
rates are generic predictions of the CR heating model.


title:
Breakdown of singlets and triplets in Sr2RuO4 revealed by spin-resolved
  ARPES

abstract:
  Spin-orbit coupling has been conjectured to play a key role in the low-energy
electronic structure of Sr2RuO4. Using circularly polarized light combined with
spin- and angle-resolved photoemission spectroscopy, we directly measure the
value of the effective spin-orbit coupling to be 130 +/- 30 meV. This is even
larger than theoretically predicted and comparable to the energy splitting of
the dxy and dxz,yz orbitals around the Fermi surface, resulting in a strongly
momentum-dependent entanglement of spin and orbital character. As demonstrated
by the spin expectation value obtained for a pair of electrons with zero total
momentum, the classification of the Cooper pairs in terms of pure singlets or
triplets fundamentally breaks down, necessitating a description of the
unconventional superconducting state of Sr2RuO4 in terms of these newly found
spin-orbital entangled eigenstates.


title:
Describing galaxy weak lensing measurements from tenths to tens of Mpc
  and up to z~0.6 with a single model

abstract:
  The clustering of galaxies and the matter distribution around them can be
described using the halo model complemented with a realistic description of the
way galaxies populate dark matter haloes. This has been used successfully to
describe statistical properties of samples of galaxies at z<0.2. Without
adjusting any model parameters, we compare the predicted weak lensing signal
induced by Luminous Red Galaxies to measurements from SDSS DR7 on much larger
scales (up to ~90 h_{70}^{-1} Mpc) and at higher redshift (z~0.4). We find
excellent agreement, suggesting that the model captures the main properties of
the galaxy-dark matter connection. To extend the comparison to lenses at even
higher redshifts we complement the SDSS data with shape measurements from the
deeper RCS2, resulting in precise lensing measurements for lenses up to z~0.6.
These measurements are also well described using the same model. Considering
solely these weak lensing measurements, we robustly assess that, up to z~0.6,
the number of central galaxies as a function of halo mass is well described by
a log-normal distribution with scatter $\sigma_{\log L_{\rm c}}=0.146\pm0.011$,
in agreement with previous independent studies at lower redshift. Our results
demonstrate the value of complementing the information about the properties of
the (lens) galaxies provided by SDSS with deeper, high-quality imaging data.


title:
Beyond Concordance Cosmology with Magnification of Gravitational-Wave
  Standard Sirens

abstract:
  We show how future gravitational-wave detectors would be able of
discriminating between the concordance LCDM cosmological model and up-to-date
competing alternatives, e.g. dynamical dark energy models (DE) or modified
gravity theories (MG). Our method consists in using the weak-lensing
magnification effect that affects a standard-siren signal because of its
travelling trough the Universe's large-scale structure. As a demonstration, we
present constraints on DE and MG from proposed gravitational-wave detectors,
namely ET and DECIGO/BBO.


title: W and Z bosons in association with two jets using the POWHEG method

abstract:
  In this work we present the implementation of generators for W and Z bosons
in association with two jets interfaced to parton showers using the POWHEG BOX.
We incorporate matrix elements from the parton-level Monte Carlo program MCFM
in the POWHEG BOX, allowing for a considerable improvement in speed compared to
previous implementations. We address certain problems that arise when processes
that are singular at the Born level are implemented in a shower framework using
either a generation cut or a Born suppression factor to yield weighted events.
In such a case, events with very large weights can be generated after the
shower through a number of mechanisms. Events with very small transverse
momentum at the Born level can develop large transverse momentum either after
the hardest emission, after the shower, or after the inclusion of multi-parton
interactions. We present a solution to this problem that can be easily
implemented in the POWHEG BOX. We also show that a full solution to this
problem can only be achieved if the generator maintains physical validity also
when the transverse momentum of the emitted partons becomes unresolved. One
such scheme is the recently-proposed MiNLO method for the choice of scale and
the exponentiation of Sudakov form factors in NLO computations. We present a
validation study of our generators, by comparing their output to available LHC
data.


title: Enhancing the absorption of graphene in the terahertz range

abstract:
  We study graphene on a photonic crystal operating in the terahertz (THz)
spectral range. We show that the absorption of graphene becomes a modulated
function of frequency and can be enhanced by more than three times at specific
frequency values, depending on the parameters of the system. The problem of a
semi-infinite photonic crystal is also solved.


title: Doubly-Fluctuating BPS Solutions in Six Dimensions

abstract:
  We analyze the BPS solutions of minimal supergravity coupled to an
anti-self-dual tensor multiplet in six dimensions and find solutions that
fluctuate non-trivially as a function of two variables. We consider families of
solutions coming from KKM monopoles fibered over Gibbons-Hawking metrics or,
equivalently, non-trivial T^2 fibrations over an R3 base. We find smooth
microstate geometries that depend upon many functions of one variable, but each
such function depends upon a different direction inside the T^2 so that the
complete solution depends non-trivially upon the whole T^2 . We comment on the
implications of our results for the construction of a general superstratum.


title:
On Critical Points for Gaussian Vectors with Infinitely Divisible
  Squares

abstract:
  Investigates the size of the perturbation to the zero mean three dimensional
Gaussian vector with infinitely divisible squares so that the infinite
divisibility is retained.


title:
RadioAstron Early Science Program Space-VLBI AGN survey: strategy and
  first results

abstract:
  RadioAstron is a project to use the 10m antenna on board the dedicated
SPEKTR-R spacecraft, launched on 2011 July 18, to perform Very Long Baseline
Interferometry from space - Space-VLBI. We describe the strategy and highlight
the first results of a 92/18/6/1.35cm fringe survey of some of the brighter
radio-loud Active Galactic Nuclei (AGN) at baselines up to 25 Earth diameters
(D_E). The survey goals include a search for extreme brightness temperatures to
resolve the Doppler factor crisis and to constrain possible mechanisms of AGN
radio emission, studying the observed size distribution of the most compact
features in AGN radio jets (with implications for their intrinsic structure and
the properties of the scattering interstellar medium in our Galaxy) and
selecting promising objects for detailed follow-up observations, including
Space-VLBI imaging. Our survey target selection is based on the results of
correlated visibility measurements at the longest ground-ground baselines from
previous VLBI surveys. The current long-baseline fringe detections with
RadioAstron include OJ 287 at 10 D_E (18cm), BL Lac at 10 D_E (6cm) and
B0748+126 at 4.3 D_E (1.3 cm). The 18 and 6cm-band fringe detections at 10 D_E
imply brightness temperatures of T_b ~ 10^13 K, about two orders of magnitude
above the equipartition inverse Compton limit. These high values of T_b might
indicate that the jet flow speed is often higher than the jet pattern speed.


title:
Fast Computation of the Series Impedance of Power Cables with Inclusion
  of Skin and Proximity Effects

abstract:
  We present an efficient numerical technique for calculating the series
impedance matrix of systems with round conductors. The method is based on a
surface admittance operator in combination with the method of moments and it
accurately predicts both skin and proximity effects. Application to a
three-phase armored cable with wire screens demonstrates a speed-up by a factor
of about 100 compared to a finite elements computation. The inclusion of
proximity effect in combination with the high efficiency makes the new method
very attractive for cable modeling within EMTP-type simulation tools.
Currently, these tools can only take skin effect into account.


title:
The perihelion of Mercury advance and the light bending calculated in
  (enhanced) Newton's theory

abstract:
  We show that results of a simple dynamical gedanken experiment interpreted
according to standard Newton's gravitational theory, may reveal that
three-dimensional space is curved. The experiment may be used to reconstruct
the curved geometry of space, i.e. its non-Euclidean metric. The perihelion of
Mercury advance and the light bending calculated from the Poisson equation and
the equation of motion in the curved geometry have the correct (observed)
values. Independently, we also show that Newtonian gravity theory may be
enhanced to incorporate the curvature of three dimensional space by adding an
extra equation which links the Ricci scalar with the density of matter. Like in
Einstein's general relativity, matter is the source of curvature. In the
spherically symmetric (vacuum) case, the metric of space 3gik that follows from
this extra equation agrees, to the expected accuracy, with the metric measured
by the Newtonian gedanken experiment mentioned above.


title: Multiwavelength modeling the SED of very slow novae PU Vul and V723 Cas

abstract:
  Evolution in the spectrum of very slow novae PU Vul and V723 Cas during their
transition from the optical maximum to the nebular phase is investigated using
the method of disentangling the composite UV/optical spectra. Model SEDs
suggested that a transient decrease in the WD luminosity, during the decline
from the maximum, was caused by a negative beaming effect, when a neutral disk
around the WD was formed. When the disk disappeared, the luminosity increased
again to values from the beginning of the outburst (in the case of V723 Cas,
at/above the Eddington limit). This suggests the presence of a mechanism
maintaining a high energy output for a much longer time than it is predicted by
the current theories. Similarity of light curves, but enormous difference of
the separation between the components of PU Vul and V723 Cas binaries suggest
that the mechanism is basically powered by the accretor.


title:
Flow and streaming potential of an electrolyte in a channel with an
  axial temperature gradient

abstract:
  The effect of an axial temperature gradient on the flow profile and the
induced streaming potential of a pressure-driven symmetric electrolyte in a
slit channel is investigated. Based on the non-isothermal Nernst-Planck
equations as well as the Poisson equation in the lubrication approximation,
expressions for the ion distribution in the electric double layer (EDL) are
derived. It is found that thermophoretic ion motion and a temperature-dependent
electrophoretic ion mobility increase the local EDL thickness with temperature,
whereas a temperature-dependent permittivity shrinks the EDL. Within the
Debye-H\"uckel approximation, the Navier-Stokes equation with the corresponding
electric body force terms is solved. Analytical expressions for the flow
profile and the induced (streaming) field under non-isothermal conditions are
derived. It is shown that for such a situation the induced electric field is
the linear superposition of at least seven individual contributions. For very
wide channels, only the thermoelectric field typically present in bulk
electrolytes when subjected to a temperature gradient (Soret equilibrium) as
well as the conventional pressure-induced streaming field are of importance.
Under extreme confinement, selective thermo-electro-migration driven by the
interplay between the temperature-dependent electrophoretic ion mobility and
the interaction of the ions with the surface wall charge causes a
thermoelectric field of non-advective origin. For wider channels and besides
the well-known thermoosmosis due to the temperature dependence of the
dielectric permittivity, it is demonstrated that a temperature gradient renders
the ion cloud in the EDL out of mechanical equilibrium. This leads to a
thermoosmotic flow, and the ion advection affiliated with it may induce a
thermoelectric field of similar order of magnitude as the one caused by more
conventional thermal effects.


title: Balanced Abelian group valued functions on directed graphs

abstract:
  We discuss functions from the edges and vertices of a directed graph to an
Abelian group. Such functions, when the sum of their values along any cycle is
zero, are called balanced and form an Abelian group. We study this group in two
cases: when we allowed to walk against the direction of an edge taking the
opposite value of the function and when we are not allowed to walk against the
direction.


title:
Explicit solution of a tropical optimization problem with application to
  project scheduling

abstract:
  A new multidimensional optimization problem is considered in the tropical
mathematics setting. The problem is to minimize a nonlinear function defined on
a finite-dimensional semimodule over an idempotent semifield and given by a
conjugate transposition operator. A special case of the problem, which arises
in just-in-time scheduling, serves as a motivation for the study. To solve the
general problem, we derive a sharp lower bound for the objective function and
then find vectors that yield the bound. Under general conditions, an explicit
solution is obtained in a compact vector form. This result is applied to
provide new solutions for scheduling problems under consideration. To
illustrate, numerical examples are also presented.


title: Engineering Nanowire n-MOSFETs at Lg < 8 nm

abstract:
  As metal-oxide-semiconductor field-effect transistors (MOSFET) channel
lengths (Lg) are scaled to lengths shorter than Lg<8 nm source-drain tunneling
starts to become a major performance limiting factor. In this scenario a
heavier transport mass can be used to limit source-drain (S-D) tunneling.
Taking InAs and Si as examples, it is shown that different heavier transport
masses can be engineered using strain and crystal orientation engineering.
Full-band extended device atomistic quantum transport simulations are performed
for nanowire MOSFETs at Lg<8 nm in both ballistic and incoherent scattering
regimes. In conclusion, a heavier transport mass can indeed be advantageous in
improving ON state currents in ultra scaled nanowire MOSFETs.


title:
Exact RG Flow in an Expanding Universe and Screening of the Cosmological
  Constant

abstract:
  We obtain the exact renormalization group (RG) flow equation for a self
interacting real scalar field in an expanding cosmological background. The beta
functional for the potential in the local potential approximation is determined
in terms of the mode functions defining the vacuum of the theory. For a scalar
in an inflating universe, which is released in the Bunch-Davies vacuum, the
flow equation is analyzed in detail using the optimized cutoff function for the
quartically truncated potential. In that case, the constant term in the
potential, which can in fact be viewed as the cosmological constant, decreases
as the IR cutoff is removed, supporting the existence of a quantum mechanical
screening mechanism. On the other hand, the running of the quartic coupling
constant at IR is altered by the expansion, which seems to affect the quantum
triviality of the theory.


title: A waveguide-coupled thermally-isolated radiometric source

abstract:
  The design and validation of a dual polarization source for waveguide-coupled
millimeter and sub-millimeter wave cryogenic sensors is presented. The thermal
source is a waveguide mounted absorbing conical dielectric taper. The absorber
is thermally isolated with a kinematic suspension that allows the guide to be
heat sunk to the lowest bath temperature of the cryogenic system. This approach
enables the thermal emission from the metallic waveguide walls to be
subdominant to that from the source. The use of low thermal conductivity Kevlar
threads for the kinematic mount effectively decouples the absorber from the
sensor cold stage. Hence, the absorber can be heated to significantly higher
temperatures than the sensor with negligible conductive loading. The kinematic
suspension provides high mechanical repeatability and reliability with thermal
cycling. A 33-50 GHz blackbody source demonstrates an emissivity of 0.999 over
the full waveguide band where the dominant deviation from unity arrises from
the waveguide ohmic loss. The observed thermal time constant of the source is
40 s when the absorber temperature is 15 K. The specific heat of the lossy
dielectric MF-117 is well approximated by $C_v(T)=0.12\,T\,^{2.06}$ mJ g$^{-1}$
K$^{-1}$ between 3.5 K and 15 K.


title:
Soliton almost K\"{a}hler structures on 6-dimensional nilmanifolds for
  the symplectic curvature flow

abstract:
  The aim of this paper is to study self-similar solutions to the symplectic
cuvature flow on 6-dimensional nilmanifolds. For this purpose, we focus our
attention in the family of symplectic Two- and Three-step nilpotent Lie
algebras admitting a "minimal compatible metric" and we give a complete
classification of these algebras together with their respective metric. Such
classification is given by using our generalization of Nikolayevsky's nice
basis criterium (arXiv:1301.4949), which will be repeated here in the context
of canonical compatible metrics for geometric structures on nilmanifolds, for
the convenience of the reader.
  By computing the Chern-Ricci operator $P$ in each case, we show that the
above distinguished metrics define a soliton almost K\"{a}hler structure.
  Many illustrative examples are carefully developed.


title:
Theory of warm ionized gases: equation of state and kinetic Schottky
  anomaly

abstract:
  Based on accurate Lennard-Jones type interaction potentials, we derive a
closed set of state equations for the description of warm atomic gases in the
presence of ionization processes. The specific heat is predicted to exhibit
peaks in correspondence to single and multiple ionizations. Such kinetic
analogue in atomic gases of the Schottky anomaly in solids is enhanced at
intermediate and low atomic densities. The case of adiabatic compression of
noble gases is analyzed in detail and the implications on sonoluminescence are
discussed. In particular, the predicted plasma electron density in a
sonoluminescent bubble turns out to be in good agreement with the value
measured in recent experiments.


title:
Chiral phase transition in a planar four-Fermi model in a tilted
  magnetic field

abstract:
  We study a planar four-Fermi Gross-Neveu model in the presence of a tilted
magnetic field, with components parallel and perpendicular to the system's
plane. We determine how this combination of magnetic field components, when
applied simultaneously, affects the phase diagram of the model. It is shown
that each component of the magnetic field causes a competing effect on the
chiral symmetry in these fermionic systems. While the perpendicular component
of the magnetic field tends to make the chiral symmetry breaking stronger, the
effect of the parallel component of the field in these planar systems is to
weaken the chiral symmetry through the enhancement of the Zeeman energy term.
We show that this competing effect, when combined also with temperature and
chemical potential, can lead to a rich phase diagram, with the emergence of
multiple critical points and reentrant phase transitions. We also study how the
presence of these multiple critical points and reentrant phases can manifest in
the quantum Hall effect. Our results provide a possible way to probe
experimentally chiral symmetry breaking and the corresponding emergence of a
gap (i.e., the presence of a nonvanishing chiral vacuum expectation value) in
planar condensed matter systems of current interest.


title:
Connections between the Generalized Marcum Q-Function and a class of
  Hypergeometric Functions

abstract:
  This paper presents a new connection between the generalized Marcum-Q
function and the confluent hypergeometric function of two variables, phi3. This
result is then applied to the closed-form characterization of the bivariate
Nakagami-m distribution and of the distribution of the minimum eigenvalue of
correlated non-central Wishart matrices, both important in communication
theory. New expressions for the corresponding cumulative distributions are
obtained and a number of communication-theoretic problems involving them are
pointed out.


title: Relaxation of Warped Disks: the Case of Pure Hydrodynamics

abstract:
  Orbiting disks may exhibit bends due to a misalignment between the angular
momentum of the inner and outer regions of the disk. We begin a systematic
simulational inquiry into the physics of warped disks with the simplest case:
the relaxation of an unforced warp under pure fluid dynamics, i.e. with no
internal stresses other than Reynolds stress. We focus on the nonlinear regime
in which the bend rate is large compared to the disk aspect ratio. When warps
are nonlinear, strong radial pressure gradients drive transonic radial motions
along the disk's top and bottom surfaces that efficiently mix angular momentum.
The resulting nonlinear decay rate of the warp increases with the warp rate and
the warp width, but, at least in the parameter regime studied here, is
independent of the sound speed. The characteristic magnitude of the associated
angular momentum fluxes likewise increases with both the local warp rate and
the radial range over which the warp extends; it also increases with increasing
sound speed, but more slowly than linearly. The angular momentum fluxes respond
to the warp rate after a delay that scales with the square-root of the time for
sound waves to cross the radial extent of the warp. These behaviors are at
variance with a number of the assumptions commonly used in analytic models to
describe linear warp dynamics.


title: An O(N) Direct Solver for Integral Equations on the Plane

abstract:
  An efficient direct solver for volume integral equations with O(N) complexity
for a broad range of problems is presented. The solver relies on hierarchical
compression of the discretized integral operator, and exploits that
off-diagonal blocks of certain dense matrices have numerically low rank.
Technically, the solver is inspired by previously developed direct solvers for
integral equations based on "recursive skeletonization" and "Hierarchically
Semi-Separable" (HSS) matrices, but it improves on the asymptotic complexity of
existing solvers by incorporating an additional level of compression. The
resulting solver has optimal O(N) complexity for all stages of the computation,
as demonstrated by both theoretical analysis and numerical examples. The
computational examples further display good practical performance in terms of
both speed and memory usage. In particular, it is demonstrated that even
problems involving 10^{7} unknowns can be solved to precision 10^{-10} using a
simple Matlab implementation of the algorithm executed on a single core.


title:
Existence of solutions to path-dependent kinetic equations and related
  forward - backward systems

abstract:
  This paper is devoted to path-dependent kinetics equations arising, in
particular, from the analysis of the coupled backward - forward systems of
equations of mean field games. We present local well-posedness, global
existence and some regularity results for these equations.


title: WASP-8b: Characterization of a Cool and Eccentric Exoplanet with Spitzer

abstract:
  WASP-8b has 2.18 times Jupiter's mass and is on an eccentric ($e=0.31$)
8.16-day orbit. With a time-averaged equilibrium temperature of 948 K, it is
one of the least-irradiated hot Jupiters observed with the Spitzer Space
Telescope. We have analyzed six photometric light curves of WASP-8b during
secondary eclipse observed in the 3.6, 4.5, and 8.0 {\microns} Infrared Array
Camera bands. The eclipse depths are $0.113\pm 0.018$%, $0.069\pm 0.007$%, and
$0.093\pm 0.023$%, respectively, giving respective brightness temperatures of
1552, 1131, and 938 K. We characterized the atmospheric thermal profile and
composition of the planet using a line-by-line radiative transfer code and a
Markov-chain Monte Carlo sampler. The data indicated no thermal inversion,
independently of any assumption about chemical composition. We noted an
anomalously high 3.6-{\microns} brightness temperature (1552 K); by modeling
the eccentricity-caused thermal variation, we found that this temperature is
plausible for radiative time scales less than $\sim 10^{2}$ hours. However, as
no model spectra fit all three data points well, the temperature discrepancy
remains as an open question.


title:
A Bake-Off Between CMFGEN and FASTWIND: Modeling the Physical Properties
  of SMC and LMC O-type Stars

abstract:
  The model atmosphere programs FASTWIND and CMFGEN are both elegantly designed
to perform non-LTE analyses of the spectra of hot massive stars, and include
sphericity and mass-loss. The two codes differ primarily in their approach
towards line blanketing, with CMFGEN treating all of the lines in the co-moving
frame and FASTWIND taking an approximate approach which speeds up execution
times considerably. Although both have been extensively used to model the
spectra of O-type stars, no studies have used the codes to independently model
the same spectra of the same stars and compare the derived physical properties.
We perform this task on ten O-type stars in the Magellanic Clouds. For the
late-type O supergiants, both CMFGEN and FASTWIND have trouble fitting some of
the He I lines, and we discuss causes and cures. We find that there is no
difference in the average effective temperatures found by the two codes for the
stars in our sample, although the dispersion is large, due primarily to the
various difficulties each code has with He I. The surface gravities determined
using FASTWIND are systematically lower by 0.12 dex compared to CMFGEN, a
result we attribute to the better treatment of electron scattering by CMFGEN.
This has implications for the interpretation of the origin of the so-called
mass discrepancy, as the masses derived by FASTWIND are on average lower than
inferred from stellar evolutionary models, while those found by CMFGEN are in
better agreement.


title: Black hole spin-down by truncated disc emission

abstract:
  The influence of disc radiation capture upon black hole rotational evolution
is negligible for radiatively inefficient discs. For the standard thin disc
model it is a slight but potentially important effect leading to the
equilibrium spin parameter value of about 0.998. For optically thin discs, the
fraction of disc radiation captured by the black hole is however about two
times larger. In some disc radiation models, inner parts of the accretion flow
are optically thin, advection-dominated flows, and the thin disc ends at some
transition radius R_{tr}. The thermal energy of the disc stored in trapped
radiation is released at this radius. Angular distribution of the radiation
released at this radial photosphere facilitates its capture by the black hole.
For accretion rates close to critical and disc truncation radius of (2..4)
GM/c^2, radiation capture is most efficient in spinning the black hole down
that may lead to a_{eq} ~ 0.996..0.997 or less depending on the mass accretion
rate. For an accretion flow radiating some constant fraction \epsilon of
dissipated energy, the equilibrium Kerr parameter is shown to obey the relation
1-a_{eq} \propto \epsilon^{3/2} as long as 1-a_{eq} << 1. Deviations from
Keplerian law near the last stable orbit dominate over the radiation capture
effect if they exceed 1..2%.


title:
The Second Law of Thermodynamics under Unitary Evolution and External
  Operations

abstract:
  A microscopic definition of the thermodynamic entropy in an isolated quantum
system must satisfy (i) additivity, (ii) extensivity and (iii) the second law
of thermodynamics. We show that the diagonal entropy, which is the Shannon
entropy in the energy eigenbasis at each instant of time, meets the first two
requirements and that the third requirement is satisfied if an arbitrary
external operation is performed at typical times. In terms of the diagonal
entropy, thermodynamic irreversibility follows from the facts that the
Hamiltonian dynamics restricts quantum trajectories under unitary evolution and
that the external operation is performed without referring to any particular
information about the microscopic state of the system.


title: The Darboux-Bianchi-B\"acklund transformation and soliton surfaces

abstract:
  In the first part of the paper we present the dressing method which generates
multi-soliton solutions to integrable systems of nonlinear partial differential
equations. We compare the approach of Neugebauer with that of Zakharov, Shabat
and Mikhailov. In both cases we discuss the group reductions and reductions
defined by some multilinear constraints on matrices of the linear problem. The
second part of the paper describes the soliton surfaces approach. The so called
Sym-Tafel formula simplifies the explicit reconstruction of the surface from
the knowledge of its fundamental forms, unifies various integrable
nonlinearities and enables one to apply powerful methods of the theory of
solitons to geometrical problems. The Darboux-Bianchi-B\"acklund transformation
(i.e., the dressing method on the level of soliton surfaces) reconstructs
explicitly many classical transformations of XIX century. We present examples
of interesting classes of surfaces obtained from spectral problems. In
particular, we consider spectral problems in Clifford algebras associated with
orthogonal coordinates. Finally, compact formulas for multi-soliton surfaces
are discussed and applied for the Localized Induction Equation with axial flow.


title: On the stretch factor of the Theta-4 graph

abstract:
  In this paper we show that the \theta-graph with 4 cones has constant stretch
factor, i.e., there is a path between any pair of vertices in this graph whose
length is at most a constant times the Euclidean distance between that pair of
vertices. This is the last \theta-graph for which it was not known whether its
stretch factor was bounded.


title: Adiabatic quantum pumping in graphene with magnetic barriers

abstract:
  We study an adiabatic quantum pump effect in a two terminal graphene device
with two oscillating square electric barriers and a stationary magnetic barrier
using the scattering matrix approach. The model employs the low-energy Dirac
approximation and incorporates the possible existence of a finite band gap in
graphene spectrum. We show that in this case valley-polarized and pure valley
currents can be pumped due to the valley symmetry breaking. For a
\delta-function magnetic barrier we present analytical expressions for bilinear
total and valley pumping responses. These results are compared to numerical
ones for a double \delta-function, a square and a triple square magnetic
barriers.


title:
On Some Zarankiewicz Numbers and Bipartite Ramsey Numbers for
  Quadrilateral

abstract:
  The Zarankiewicz number $z(m,n;s,t)$ is the maximum number of edges in a
subgraph of $K_{m,n}$ that does not contain $K_{s,t}$ as a subgraph. The
bipartite Ramsey number $b(n_1, \cdots, n_k)$ is the least positive integer $b$
such that any coloring of the edges of $K_{b,b}$ with $k$ colors will result in
a monochromatic copy of $K_{n_i,n_i}$ in the $i$-th color, for some $i$, $1 \le
i \le k$. If $n_i=m$ for all $i$, then we denote this number by $b_k(m)$. In
this paper we obtain the exact values of some Zarankiewicz numbers for
quadrilateral ($s=t=2$), and we derive new bounds for diagonal multicolor
bipartite Ramsey numbers avoiding quadrilateral. In particular, we prove that
$b_4(2)=19$, and establish new general lower and upper bounds on $b_k(2)$.


title: Realization of Carrier Tunneling from InAlAs Quantum Dots to AlAs

abstract:
  With the aim of improving solar cell efficiency, a structure for realizing
electron tunneling from In0.6Al0.4As quantum dots (QDs) through an Al0.4Ga0.6As
barrier to AlAs has been grown using molecular beam epitaxy. The
photoluminescence decay time decreased from 1.1 ns to 390 ps as the barrier
thickness decreased from 4 to 2 nm, which indicates that the photo-excited
carriers tunneled from the QDs to the AlAs X energy level for a barrier
thickness 2 nm in 0.6 ns, which is significantly longer than the tunneling time
of GaAs and InAlAs quantum wells. We expect that this structure will assist in
developing high-efficiency QD sensitized solar cells.


title: Boundary Effects in the BLG Theory

abstract:
  In this paper we will analyse a system of multiple M2-branes in between two
M5-branes. This will be analysed by studying Bagger-Lambert-Gustavsson (BLG)
theory on a manifold with two boundaries. The original BLG theory will be
modified to make it gauge and supersymmetric invariant in presence of the
boundaries. However, this modified theory will only preserve half the
supersymmetry of the original theory. We will also analyse the deformation of
this theory caused by noncommutativity between Grassman coordinates and
spacetime coordinates. Finally, we will analyse the Higgsing of this theory to
deformed D2-branes with boundaries.


title: Noether's Charge in the Super-Group Field Cosmology

abstract:
  In this paper we will analyse the third quantization of a model of
super-group field cosmology with gauge symmetry. The effect of creation and
annihilation of bosonic and fermionic universes in the multiverse will also be
analysed. We will also construct a third quantized Noether's charge which will
be conserved even when the number of universes is not conserved. Finally, we
will construct both the third quantized BRST and the third quantized anti-BRST
charges for this theory and use them to show that the creation and annihilation
of universes is a unitarity process.


title:
Bottom-k and Priority Sampling, Set Similarity and Subset Sums with
  Minimal Independence

abstract:
  We consider bottom-k sampling for a set X, picking a sample S_k(X) consisting
of the k elements that are smallest according to a given hash function h. With
this sample we can estimate the relative size f=|Y|/|X| of any subset Y as
|S_k(X) intersect Y|/k. A standard application is the estimation of the Jaccard
similarity f=|A intersect B|/|A union B| between sets A and B. Given the
bottom-k samples from A and B, we construct the bottom-k sample of their union
as S_k(A union B)=S_k(S_k(A) union S_k(B)), and then the similarity is
estimated as |S_k(A union B) intersect S_k(A) intersect S_k(B)|/k.
  We show here that even if the hash function is only 2-independent, the
expected relative error is O(1/sqrt(fk)). For fk=Omega(1) this is within a
constant factor of the expected relative error with truly random hashing.
  For comparison, consider the classic approach of kxmin-wise where we use k
hash independent functions h_1,...,h_k, storing the smallest element with each
hash function. For kxmin-wise there is an at least constant bias with constant
independence, and it is not reduced with larger k. Recently Feigenblat et al.
showed that bottom-k circumvents the bias if the hash function is 8-independent
and k is sufficiently large. We get down to 2-independence for any k. Our
result is based on a simply union bound, transferring generic concentration
bounds for the hashing scheme to the bottom-k sample, e.g., getting stronger
probability error bounds with higher independence.
  For weighted sets, we consider priority sampling which adapts efficiently to
the concrete input weights, e.g., benefiting strongly from heavy-tailed input.
This time, the analysis is much more involved, but again we show that generic
concentration bounds can be applied.


title: Derangements in Subspace Actions of Finite Classical Groups

abstract:
  This is the third in a series of papers in which we prove a conjecture of
Boston and Shalev that the proportion of derangements (fixed point free
elements) is bounded away from zero for transitive actions of finite simple
groups on a set of size greater than one. This paper treats the case of
primitive subspace actions. It is also shown that if the dimension and
codimension of the subspace go to infinity, then the proportion of derangements
goes to one. Similar results are proved for elements in finite classical groups
in cosets of the simple group. The results in this paper have applications to
probabilistic generation of finite simple groups and maps between varieties
over finite fields.


title:
Novel O(H(N)+N/H(N)) Algorithmic Techniques for Several Types of Queries
  and Updates on Rooted Trees and Lists

abstract:
  In this paper we present novel algorithmic techniques with a O(H(N)+N/H(N))
time complexity for performing several types of queries and updates on general
rooted trees, binary search trees and lists of size N. For rooted trees we
introduce a new compressed super-node tree representation which can be used for
efficiently addressing a wide range of applications. For binary search trees we
discuss the idea of globally rebuilding the entire tree in a fully balanced
manner whenever the height of the tree exceeds the value of a conveniently
chosen function of the number of tree nodes. In the end of the paper we
introduce the H-list data structure which supports concatenation, split and
several types of queries. Note that when choosing H(N)=sqrt(N) we obtain
O(H(N)+N/H(N))=O(sqrt(N)).


title:
Type IIb Supernova SN 2011dh: Spectra and Photometry from the
  Ultraviolet to the Near-Infrared

abstract:
  We report spectroscopic and photometric observations of the Type IIb SN
2011dh obtained between 4 and 34 days after the estimated date of explosion
(May 31.5 UT). The data cover a wide wavelength range from 2,000 Angstroms in
the UV to 2.4 microns in the NIR. Optical spectra provide line profiles and
velocity measurements of HI, HeI, CaII and FeII that trace the composition and
kinematics of the SN. NIR spectra show that helium is present in the atmosphere
as early as 11 days after the explosion. A UV spectrum obtained with the STIS
reveals that the UV flux for SN 2011dh is low compared to other SN IIb. The HI
and HeI velocities in SN 2011dh are separated by about 4,000 km/s at all
phases. We estimate that the H-shell of SN 2011dh is about 8 times less massive
than the shell of SN 1993J and about 3 times more massive than the shell of SN
2008ax. Light curves (LC) for twelve passbands are presented. The maximum
bolometric luminosity of $1.8 \pm 0.2 \times 10^{42}$ erg s$^{-1}$ occurred
about 22 days after the explosion. NIR emission provides more than 30% of the
total bolometric flux at the beginning of our observations and increases to
nearly 50% of the total by day 34. The UV produces 16% of the total flux on day
4, 5% on day 9 and 1% on day 34. We compare the bolometric light curves of SN
2011dh, SN 2008ax and SN 1993J. The LC are very different for the first twelve
days after the explosions but all three SN IIb display similar peak
luminosities, times of peak, decline rates and colors after maximum. This
suggests that the progenitors of these SN IIb may have had similar compositions
and masses but they exploded inside hydrogen shells that that have a wide range
of masses. The detailed observations presented here will help evaluate
theoretical models for this supernova and lead to a better understanding of SN
IIb.


title: 2D-Zernike polynomials and coherent state quantization of the unit disc

abstract:
  Using the orthonormality of the 2D-Zernike polynomials, reproducing kernels,
reproducing kernel Hilbert spaces, and ensuring coherent states attained. With
the aid of the so-obtained coherent states, the complex unit disc is quantized.
Associated upper symbols, lower symbols and related generalized Berezin
transforms also obtained. A number of necessary summation formulas for the
2D-Zernike polynomials proved.


title: Discriminating different models of luminosity-redshift distribution

abstract:
  The beginning of the cosmological phase bearing the direct kinematic imprints
of supernovae dimming may significantly vary within different models of
late-time cosmology, even if such models are able to fit present SNe data at a
comparable level of statistical accuracy. This effect -- useful in principle to
discriminate among different physical interpretations of the
luminosity-redshift relation -- is illustrated here with a pedagogical example
based on the LTB geometry.


title: MEtop - a top FCNC event generator

abstract:
  We present a new Monte Carlo generator for Direct top and Single top
production via flavour-changing neutral currents (FCNC). This new tool
calculates the cross section and generates events with Next-to-Leading order
precision for the Direct top process and Leading-Order precision for all other
FCNC single top processes. A set of independent dimension six FCNC operators
has been implemented - including four-fermion operators - where at least one
top-quark is present in the interaction.


title: $PD_4$-complexes and 2-dimensional duality groups

abstract:
  This paper is a synthesis and extension of three earlier papers on
$PD_4$-complexes $X$ with fundamental group $\pi$ such that $c.d.\pi=2$ and
$\pi$ has one end. Our goal is to show that the homotopy types of such
complexes are determined by $\pi$, the Stiefel-Whitney classes and the
equivariant intersection pairing on $\pi_2(X)$. We achieve this under further
conditions on $\pi$.


title: Physical properties of B-type asteroids from WISE data

abstract:
  Aims: Our aim is to obtain more information about the physical nature of
B-type asteroids and extend on the previous work by studying their physical
properties derived from fitting an asteroid thermal model to their NASA's
Wide-field Infrared Survey Explorer (WISE) data. We also examine the Pallas
collisional family, a B-type family with a moderately high albedo in contrast
to the large majority of B-types. Methods: We apply a combination of the NEATM
and a model of the reflected sunlight to WISE asteroid data in order to derive
effective diameter (D), the so-called infrared beaming parameter (\eta), ratio
of infrared to visible albedo (R_p = p_{IR}/p_V) and visible geometric albedo
(p_V). Results: We obtained parameter values for $\ga$ 100 B-types asteroids
and plotted the value distributions of p_V, R_p and \eta (p_V = 0.07 +- 0.03$,
R_p = 1.0 +- 0.2, and \eta = 1.0 +- 0.1). By combining the IR and visible
albedos with 2.5-micron reflectances from the literature we obtained the ratio
of reflectances at 3.4 and 2.5 micron, from which we found statistically
significant indications that the presence of a 3-micron absorption band related
to water may be commonplace among the B-types. Finally, the Pallas collisional
family members studied ($\sim$ 50 objects) present moderately high values of
p_V (p_V = 0.14 +- 0.05), significantly higher than the average albedo of
B-types. In addition, this family presents the lowest and most homogeneously
distributed R_p-values of our whole sample, which shows that this group is
clearly different from the rest, likely because its members are pieces probably
originating from the same region of (2) Pallas, a particularly high-albedo
B-type asteroid.


title: Cosmic rays: interstellar gamma-ray and radio emission

abstract:
  We discuss the relation between cosmic-ray induced interstellar gamma-ray and
radio emission from our Galaxy, and emphasize the importance of their parallel
study. We give an overview of results from Fermi-LAT on the interstellar
gamma-ray emission, and then focus on complementary studies of the radio
emission from the Galaxy.


title: Main Sequence Star Populations in the Virgo Overdensity Region

abstract:
  We present deep CMDs for two Subaru Suprime-Cam fields in the Virgo Stellar
Stream(VSS)/Virgo Overdensity(VOD) and compare them to a field centred on the
highest concentration of Sagittarius (Sgr) Tidal Stream stars in the leading
arm, Branch A of the bifurcation. A prominent population of MS stars is
detected in all three fields and can be traced as faint as g~24 mag. Using
theoretical isochrone fitting we derive an age of 9.1(+1.0;-1.1)Gyr, a median
abundance of [Fe/H]=-0.70 (+0.15; -0.20)dex and d_helio of 30.9+-3.0kpc for the
MS of the Sgr Stream Branch A. The dominant main sequence populations in the
two VSS/VOD fields (Lsun ~265 deg, Bsun ~13 deg) are located at a mean distance
of 23.3+-1.6kpc and have an age ~8.2Gyr and an abundance
[Fe/H]=-0.67(+0.16;-0.12)dex similar to the Sgr Stream stars. These parameters
are also in good agreement with the age of the main population in the
Sagittarius dwarf (8.0+-1.5Gyr). They also agree with the peak in the
metallicity distribution of 2-3Gyr old M-giants, [Fe/H] ~ -0.6dex, in the Sgr
leading arm north. We then compare the results from the VSS/VOD fields with the
Sgr Tidal Stream model by Law & Majewski based on a triaxial Galactic halo that
is calibrated with SDSS Sgr A-branch and 2MASS M-giant stars. We find that the
most prominent feature in the CMDs, the MS population at 23kpc, is not
explained by the model. Instead the model predicts in these directions a low
density filamentary structure of Sgr debris stars at ~9kpc and a slightly
higher concentration of Sgr stars spread from 42-53kpc. At best there is only
marginal evidence for the presence of these populations in our data. Our
findings then suggest that while there are probably some Sgr debris stars
present, the dominant stellar population in the VOD originates from a different
halo structure that has almost identical age and metallicity as some sections
of the Sgr tidal stream.


title:
The Supermassive Black Hole Mass - Spheroid Stellar Mass Relation for
  S\'ersic and Core-S\'ersic Galaxies

abstract:
  We have examined the relationship between supermassive black hole mass
(M$_{BH}$) and the stellar mass of the host spheroid (M$_{sph,*}$) for a sample
of 75 nearby galaxies. To derive the spheroid stellar masses we used improved
2MASS K$_s$-band photometry from the ARCHANGEL photometry pipeline. Dividing
our sample into core-S\'ersic and S\'ersic galaxies, we find that they are
described by very different M$_{BH}$-M$_{sph,*}$ relations. For core-S\'ersic
galaxies - which are typically massive and luminous, with M$_{BH} \gtrsim
2x10^8 M_\odot$ - we find M$_{BH} \propto M_{sph,*}^{(0.97 \pm 0.14)}$,
consistent with other literature relations. However, for the S\'ersic galaxies
- with typically lower masses, M$_{sph,*} \lesssim 3x10^10 M_\odot$ - we find
M$_BH \propto M_{sph,*}^{(2.22 \pm 0.58)}$, a dramatically steeper slope that
differs by more than 2 standard deviations. This relation confirms that, for
S\'ersic galaxies, M$_{BH}$ is not a constant fraction of M$_{sph,*}$. S\'ersic
galaxies can grow via the accretion of gas which fuels both star formation and
the central black hole, as well as through merging. Their black hole grows
significantly more rapidly than their host spheroid, prior to growth by dry
merging events that produce core-S\'ersic galaxies, where the black hole and
spheroid grow in lock step. We have additionally compared our S\'ersic
M$_{BH}$-M$_{sph,*}$ relation with the corresponding relation for nuclear star
clusters, confirming that the two classes of central massive object follow
significantly different scaling relations.


title:
A software package for stellar and solar inverse-Compton emission:
  Stellarics

abstract:
  We present our software to compute gamma-ray emission from inverse-Compton
scattering by cosmic-ray leptons in the heliosphere, as well as in the
photospheres of stars. It includes a formulation of modulation in the
heliosphere, but it can be used for any user-defined modulation model. Profiles
and spectra are output to FITS files in a variety of forms for convenient use.
Also included are general-purpose inverse-Compton routines with other features
like energy loss rates and emissivity for any user-defined target photon and
lepton spectra. The software is publicly available and it is under continuing
development.


title: Sample Distortion for Compressed Imaging

abstract:
  We propose the notion of a sample distortion (SD) function for independent
and identically distributed (i.i.d) compressive distributions to fundamentally
quantify the achievable reconstruction performance of compressed sensing for
certain encoder-decoder pairs at a given sampling ratio. Two lower bounds on
the achievable performance and the intrinsic convexity property is derived. A
zeroing procedure is then introduced to improve non convex SD functions. The SD
framework is then applied to analyse compressed imaging with a multi-resolution
statistical image model using both the generalized Gaussian distribution and
the two-state Gaussian mixture distribution. We subsequently focus on the
Gaussian encoder-Bayesian optimal approximate message passing (AMP) decoder
pair, whose theoretical SD function is provided by the rigorous analysis of the
AMP algorithm. Given the image statistics, analytic bandwise sample allocation
for bandwise independent model is derived as a reverse water-filling scheme.
Som and Schniter's turbo message passing approach is further deployed to
integrate the bandwise sampling with the exploitation of the hidden Markov tree
structure of wavelet coefficients. Natural image simulations confirm that with
oracle image statistics, the SD function associated with the optimized sample
allocation can accurately predict the possible compressed sensing gains.
Finally, a general sample allocation profile based on average image statistics
not only illustrates preferable performance but also makes the scheme
practical.