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Uniblue SpeedUpMyPC 2015 6.0.9.0 15.07.27

1 post in this topic

Uniblue SpeedUpMyPC 2015 6.0.9.0 15.07.27
[center]
Uniblue SpeedUpMyPC 2015 6.0.9.0 | 18.78 MB
SpeedUpMyPC - the program is a handy tuner to your operating system and provides for her a more stable and faster work . The program allows you to free memory and other system resources, prevent crashes, reduce download time and make more effective communication with the Internet. The utility also allows you to monitor the system and makes recommendations to accelerate the startup programs to monitor and control all your PC resources with one simple click.
System settings, internet usage, disk clutter , RAM and CPU are all automatically scanned , cleaned and optimized for peak performance . You can also pause or delete the background and startup processes, to produce high-quality multi-pass disk defragmentation and mop up, to respect privacy, completely remove sensitive data and much more.
SpeedUpMyPC lets you monitor and control all your PC resources with one simple click. System settings, internet usage, disk clutter , RAM and CPU are all automatically scanned , cleaned and optimized for peak performance . You can also pause or delete the background and startup processes, to produce high-quality disk defragmentation and multipass grinding , for compliance with privacy , completely remove sensitive data and much more.
Features
- Automatic scanning system
- Overview of CPU
- Improved functionality of the processor
- Review the use of RAM
- Optimize RAM
- Review the use of disk space
- Analyzing and defragmenting hard drives
- Analysis and Optimization speed internet connection
- Startup Manager
- Task Manager
- Review of and recommendations for increasing its productivity
- Crawling on unnecessary or unwanted data
- Complete destruction of confidential data (optional )
- Manager to uninstall
- Nice and easy interface yuzersky
- Run programs at system startup ( optional)
- Automatic start scanning the system at boot program ( optional)
- Start, the program icon in the system tray
Updates: official site does not provide any info about changes in this version
[b]Buy a premium to download file with fast speed[/b]
[b]Rapidgator.net[/b]
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SC notice to Goa on plea challenging renewal of mining leases

New Delhi: Renewal of 89 mining leases by Goa government has come under scanner with the Supreme Court today seeking response from the state and several mining companies on petitions challenging their renewal.

A bench of Justices J S Khehar and R Banumathi issued notices to the state government and 89 mining firms while directing them to file response on the pleas by December 1. It also directed the Goa government to produce all records and files related to the mining lease before it.

The bench was hearing pleas by NGO Goa Foundation and others who had approached the apex court challenging the Bombay High Court judgement directing Goa government to renew the leases in favour of mining companies that had paid the stamp duty in accordance with the Goa Mineral Policy, 2013.

The high court had also held the government could not retract its promise as it is stopped by the doctrine of "promissory estoppel" after promising execution of mining leases under Section 8(3) of the Mines and Minerals (Development and Regulation) Act.

Advocate Prashant Bhushan, appearing for the NGO, contended that the apex court had last year ordered that all mining licences granted for 50 years which had expired in 2007 shall not be given automatic renewal.

"The mining leases could not have been renewed in light of law declared by this court in the allocation of spectrum (2G scam) and Presidential Reference. Directly or indirectly you have to maximise the revenue of the state. Second renewal beyond 20 years is exceptional and state government has not recorded appropriate reasons for the same," he said seeking quashing of the mining leases.

The mining firms should stand in queue for competitive bidding along with other applicants and apply to get environment clearance afresh. The Goa government, however, violated the order and allowed the miners to operate without auction or competitive bid, he said.

Bhushan said that by flouting the court order and environment regulations, the state government, which holds natural resources like minerals, has only benefited profit- maximising companies, ignoring public welfare and social good. The matter is listed for final hearing on December 9.


Tardoire

The Tardoire is a river in southwestern France, left tributary to the river Bonnieure. Its source is in Châlus, in the Haute-Vienne département. It flows into the Bonnieure near Saint-Ciers-sur-Bonnieure. Over much of its length, the Tardoire flows underground.

It flows through the following départements and towns:

Haute-Vienne: Châlus, Cussac
Charente: Montbron, La Rochefoucauld

References
http://www.geoportail.fr
The Tardoire at the Sandre database

Category:Rivers of France
Category:Rivers of Nouvelle-Aquitaine
Category:Rivers of Haute-Vienne
Category:Rivers of Charente


Q:

Question on preventing SQL with magic_quotes off and XSS with htmlentities

On my server I have magic_quotes turned off.
When a user save content as article in my DB from a form, I use
$text = mysql_real_escape_string($_POST['text']); to prevent SQL Injecion.
This is my input   and this is what it is saved in the DB
When I echo htmlentities($row['text']); i get  printed on screen, on view source I get <img src="image.png"></img>.
My questions are

Isn't supposed to be saved in DB like  to prevent SQL Injections ?
Is htmlentities is a good candidate to prevent XSS attacks?
Should I turn on magic_quotes?

A:

Isn't supposed to be saved in DB like  to prevent SQL Injections ?

No, SQL injections are widely misunderstood, mainly because they actually have nothing to do with SQL as they are just string manipulation. You don't need to alter the data you insert into the database, you only have to alter the string you send to the database server as query (unless you do the wise choice and use prepared statements instead of escaping the query string). The data, once stored, should be in its original state.

Is htmlentities is a good candidate to prevent XSS attacks?

Yes but htmlentities() is good for sending data as output to the browser, not for storing it into the database (as the data from the DB might be used for something other than a web page).

Should I turn on magic_quotes?

No, you should use prepared statements.


Isolated extramedullary relapse in the breast of a patient with acute myeloid leukemia following allogeneic stem cell transplantation: case report and review of the literature.
We report an unsual case of a woman with acute myeloid leukemia who showed an isolated extramedullary relapse (IEMR) in the breast following allogeneic stem cell transplantation and review the related literature. Eighty cases of IEMR following allogeneic stem cell transplantation, including our case, were identified. The review suggests that an M2 or M4 phenotype in the French-American-British classification and a favorable cytogenetic risk group are more frequently associated with the occurrence of IEMR. Combined treatment with radiation and high-dose chemotherapy may be effective.


FROM node:8.6

WORKDIR /usr/src
COPY app/ /usr/src/
RUN npm install --production
EXPOSE 2222
ENTRYPOINT [ "/usr/local/bin/node", "index.js" ]


---
abstract: 'It is well known that behavioral changes in contact patterns may significantly affect the spread of an epidemic outbreak. Here we focus on simple endemic models for recurrent epidemics, by modelling the social contact rate as a function of the available information on the present and past disease prevalence. We show that social behaviour change alone may trigger sustained oscillations. This indicates that human behavior might be a critical explaining factor of oscillations in time-series of endemic diseases. Finally, we briefly show how the inclusion of seasonal variations in contacts may imply chaos.'
author:
- |
    Alberto d’Onofrio[^1]\
    Division of Epidemiology and Biostatistics,\
    European Institute of Oncology\
    Via Ripamonti 435, 20141 Milano, Italy\
    e-mail: alberto.donofrio@ieo.it, phone:+390257489819
- |
    Piero Manfredi\
    Dipartimento di Statistica e Matematica Applicata all’Economia,\
    Università di Pisa,\
    Via Ridolfi 10, 5612 Pisa, Italy
title: ' Information-related changes in contact patterns may trigger oscillations in the endemic prevalence of infectious diseases. '
---

*Key words*: Behavior, Hopf Bifurcations, force of infection, SIR models.

Introduction
============

The prevailing wisdom suggests that besides major factors, such as the sanitary revolution, or the discovery of vaccines, the role of men in affecting the disease’s dynamics has always been a minor one. This is mirrored by the amazing simplicity of the role paid to humans in models of diseases. However, the threat posed by the possibility of a pandemic of avian flu, and the related need to develop predictive and control tools, has clearly indicated that while we dispose of richer and richer models, we are still poor in the understanding of human behavior [@ferguson1]. Though serious progresses have been recently made, for instance for the first time we dispose of a body of standardised international data on social contact patterns [@mossong], yet these data give a static picture of the contacts an individual has in one average day. This fact - human behavior as static - is postulated in most models of both endemic and epidemic diseases, but is clearly a coarse abstraction. Individuals are neither static nor passive: they elaborate the available information and can change their social behavior to respond to changes in their perceived risk. Symptoms of behavioral change were evident during the pandemic of Spanish flu  [cummings]{}. A recent, well documented instance of individual’s behavior change in response to an epidemic outbreak is given by the dramatic decline in travels and social contacts during the 2003 SARS epidemics in Hong Kong and Singapore [@ferguson1]. Large behavioral changes were observed in the S. Francisco homosexual community as a response to the spread of HIV  [@mckusick]. Similarly the control of HIV/AIDS in some low resources settings, for instance the Uganda ’success story’  [@green], has mainly been achieved thanks to dramatic changes in sexual beviour, which are now documented in other Sub-Saharan Africa contexts as well [@gregson].

The onset of the bioterrorism scare and of SARS have given great impulse to improve our understanding of the possible effects of the responses by the public to epidemic threats in the globalisation era  [@fe; @cho; @de]. The increased risk of a H5N1 pandemics flu has definitively put better modelling of human behavior, particularly the individuals’ response to an epidemic threat, at the top of the current research agenda  [@ferguson1]. A variety of epidemic models including ’thinking agents’ who elaborate the available information, and consequently strategically adapt their social behaviour not only to changing epidemiological conditions but also to changes in other agents’ behaviour, have been proposed, e.g. [@fBauch; @Vardavas; @fBreban; @cummings]. This is a long way from the first epidemiological model dealing with behavioral changes during an epidemic, the SIR epidemic model by Capasso and Serio in seventies [capasso,capassobook]{}. Capasso and Serio allowed the contact rate $\beta$, until then taken as constant, to be a decreasing function of the disease prevalence (i.e. the infective fraction in the total population) $I$. This implies that the Force of Infection (FoI), i.e. the per-capita rate at which susceptible individuals acquire the infection per unit of time, takes the following non-linear form  [@capassobook]:$$FoI(I)=\beta (I)I  \label{capassoFoI}$$with: $\beta ^{\prime }(I)<0$. Capasso and Serio pointed out that, differently from standard mass action formulations, this could make the FoI to become a non-monotone function of the prevalence (e.g. if $\beta (I)=\beta
_{0}(1+hI^{2})^{\text{-}1}$). Capasso and Serio motivated their formulation with behavioral changes: in epochs of high prevalence the perceived risk of infection might become very large yielding dramatic changes in individuals’ behavior, therefore also reducing the actual risk of getting the disease. Since that seminal paper, several other works have been devoted to epidemic models with a non-linear FoI [@liu; @mo; @del; @li; @wa; @zxl], in order to mirror the existence of some degree of change in contact patterns. However, in some works [@liu; @li; @wa; @zxl] (and references therein) it is assumed that contact rate is an increasing function of $I$ in all $\le I \le 1$ [@liu; @li], or that it is increasing in an initial interval $0 \le I \le \bar{I} < 1 $ and then decreasing [@wa; @zxl]. It is worth of note that in these cases multiple equilibria and oscillations, through Hopf bifurcations of endemic states, may arise. We stress, however, that local and global increases of the contact rate (for their biological roots, see [@liu] ) can hardly be related to social phenomena, such as behavioural change, which is the focus of our paper. Indeed it would not be epidemiologically realistic to assume that susceptible subjects do intensify their contacts patterns as the prevalence of the disease increases.\
Most investigations of human behavior in relation to diseases dynamics have however been carried out in relation to STDs, particularly HIV, motivated by the need to understand the possible impact of information campaigns on sexual behavior, and as a consequence on infection trends. In particular, the long time scales of HIV/AIDS have motivated the study of the role of behavioral changes not only in relation to epidemic control but also under endemic conditions. Most such papers have incorporated behavioral changes extending in various ways the phenomenological approach à la Capasso-Serio (e.g., among the first papers appeared on the subject, [@velasco]), but there have also been some works including the individual’s behavioral choice within HIV diffusion models  [@kremer].

On the other hand no investigation has been carried out on the impact of behavioral changes on the dynamics of common endemic close-contacts diseases, such as measles. This is surprising given that, despite the anecdotic importance paid to pandemics (e.g. of plague), the history, and growth, of mankind has largely been regulated by devastating recurrent epidemics of essentially endemic diseases such as smallpox, typhoid fever, or measles. In the absence of any knowledge on the diseases’ etiology and of therapies, measures of social distancing and behavioral changes were the only walls against the fatal impact of these diseases. Though most available documentation regards especially social distancing, as for the plague, there is evidence that behavioral changes also played a role, as documented in historical, anthropological and social medicine studies [@fa; @hal].

Now actual forms and extent of such behavioral changes, i.e. the relative importance of quarantine vs absenteism (to assist sick people) vs reduced contact rates vs more hygienic practices - are probably largely dependent on the social, say developed vs developing countries or urban vs rural areas, and historical context considered. Nonetheless we speculate that, differently from big but largely spaced epidemics, where knowledge of the disease impact could only be anecdotic, already in historical times the adopted mechanisms of behavioral changes for endemic periodic diseases could have been based on the available information on the state of the disease, filtered though the knowledge about it, acquired through the social and family history during past epidemics.

Consistently with this idea in this paper we study a new simple model for the dynamics of recurrent endemic diseases with behavioral changes, where the contact rate is a function of some information index $M$ summarising the current and past history of the disease prevalence:$$FoI(M)=\beta (M)I,  \label{ourFoI}$$where $\beta ^{\prime }(M)<0$, and where $M$ is related to past prevalence through a suitable function $g(.)$ as follows:$$M(t)=\int_{0}^{+\infty }{g(I(t-\tau ))\varrho (\tau )d\tau }.  \label{eqM}$$where $\varrho (t)$ is a delaying kernel  [@delbook1; @delbook2] i.e. a positive function such that: $\int_{0}^{+\infty}\varrho(\tau)d\tau = 1$. The chosen approach, based on a phenomenological modelling of behaviour change, is a first step toward more involved modelling of social behaviour change that has the advantage of providing simpler and clearcut mathematical results.A similar approach has been recently used to model a different behavior-related phenomenon: the social acceptance of vaccination programmes and rational exemption [@rebaga; @n; @o; @i]. In this case the vaccination coverage has been represented as an increasing function of $M$.The fact to relate current contact patterns to the delayed information on the disease, is realistic also in today’s world since for most diseases information is made available after articulated routine procedures (e.g. laboratory confirmations), but it was central in historical times due to the low speed of information spread on the geographic scale.

The model
=========

Consistently with our aims, we investigate the implications of our information-dependent FoI on a basic Susceptible-Infectious-Removed (SIR) model with vital dynamics [@capasso]:$$\begin{aligned}
S^{\prime } &=&\mu (1-S)-\beta (M)IS  \label{SIR-M} \\
I^{\prime } &=&\beta (M)IS-(\mu +\nu )I  \label{SIR-S}\end{aligned}$$completed by eq. (\[eqM\]), governing the dynamics of $M$, and by the balance equation of the removed fraction $R(t)$: $R(t)=1-S(t)-I(t)$. The parameters $\mu $ and $\nu $ denote the general mortality rate and the removal rate from the disease, respectively.As for $g(I)$, one might take any function such that $g(0)=0$ and $g^{\prime
}(I)>0$. The simplest example is $g(I)=kI$ where $k\in (0,1)$ which could represent for instance the actually reported incidence of serious case of the disease. Another example could be [@n; @o; @i]; $M=wI/(1+qI)
$ where M is a non-linear increasing function of the disease prevalence which can be taken as a measure of the perceived, rather than actual, risk of infection  [@rebaga; @n; @o; @i].As for the delay kernel $\varrho (\tau )$, some noteworthy cases are the following ($\delta $ is the Dirac’s delta function): *i)* the no-delay case: $\varrho (\tau )=\delta (\tau )$; *ii)* the fixed delay: $\varrho (\tau )=\delta (\tau -T)$, with $T>0;$ *iii)* the Erlang distribution of order $n$:$$\varrho (\tau ;a)=\frac{a^{n}}{(n-1)!}\tau ^{n}e^{-a\tau },  \label{Erlang}$$where the mean delay is given by $T=n/a$ and the standard deviation is $\sigma =T/\sqrt{n}$. This model has been largely used in literature  [delbook1,delbook2,aw,gr,ll,kg,ad]{} since it is more realistic than the case of constant delay, and it allows a finite dimensional reduction of the integral equation (\[eqM\]) to the following $n$ ODEs: $$\begin{aligned}
M_{1}^{\prime } &=&a\left( g(I)-M_{1}\right)   \notag \\
M_{j}^{\prime } &=&a\left( M_{j-1}-M_{j}\right) \text{, }j=1,\dots ,n-1,
  \label{nODEs}\end{aligned}$$where $M=M_{n}$. The case $n=1$ corresponds to the exponentially fading kernel, the case $n=2$ to the so called strong kernel [delbook1,delbook2]{}, and the case $n\rightarrow +\infty $ implies $\rho
(\tau ,n/T)\rightarrow \delta (t-T)$.

The Basic Reproduction Number
-----------------------------

It is possible to define a basic reproduction number (BRN)  [@capassobook] for our model:$$\Re _{0}=\frac{\beta (0)}{\mu +\nu },  \label{brn}$$which may be interpreted as the average number of secondary cases caused by a single infectious individual entering a fully susceptible population that has no information on the disease.\
In this section we shall show how this parameter influences the behavior of the model in case of generic delay kernel. In fact, it is easy to verify that if $\Re
_{0}\leq 1$ then: $$\lim_{t\rightarrow +\infty }\left( S\left( t\right) ,I\left( t\right)
\right) =(1,0),  \label{LAS_DFE_1}$$i.e. the disease-free state (DFS) is Globally Asymptotically Stable (GAS). This result immediately follows from the differential inequality: $$I^{\prime }\leq I\left( \beta (0)(1-I)-(\mu +\nu )\right).$$ Moreover, since the linearized equation for $I$ is: $$i^{\prime }=i\left( \beta (0)-(\mu +\nu )\right),$$ it is easy to show that if $\Re _{0}>1$ then the DFS is unstable and it exists a unique endemic state $EE=(S_{e},I_{e})$ where $S_{e}=(\mu +\nu )/\beta \left( g\left( I_{e}\right) \right) $ and $I_{e}>0$ is the unique solution of:$$\mu \left( 1-\frac{\mu +\nu }{\beta \left( g\left( I\right) \right) }\right)
-(\mu +\nu )I=0.  \label{Ie}$$Moreover, in case of Erlang kernel, we demonstrate in the appendix that if $\Re _{0}>1$ then the disease is strongly persistent.\
Summing up, $\Re _{0}$ indicates that the capability of the disease to invade the host population or to go extinct is governed by the baseline behavior in absence of information on the disease spreading, independently on the structure of the memory kernel.

Oscillations around the Endemic Equilibrium
===========================================

As we showed in the previous section, the existence and stability of DFS is independent of the delay properties, as well as the existence and location of the endemic equilibrium. On the contrary, the stability properties of the EE critically depend on $\varrho (\tau )$.

Analytical results
------------------

We notice first that in the no-delay case, i.e. when the information index M is related to the current prevalence, $M=g(I)$, if $\Re
_{0}>1$ then the endemic state is GAS, as it was previously obtained by [@wa], although without modelling the information. In fact EE is LAS and since: $$div\left(  \frac{S^{\prime }}{I},\frac{I^{\prime }}{I}\right)=-\frac{\mu}{I} - \beta\left(g\left(I\right)\right) + g^{\prime}\left(I\right)\beta^{\prime}\left(g\left(I\right)\right) <0$$ the Dulac’s criterion (see the appendix of [@capassobook]) rules out the possibility of closed orbits. Second, in the case of the exponentially fading kernel, which leads to the following three-dimensional family of models: $$\begin{aligned}
S^{\prime } &=&\mu (1-S)-\beta (M)IS  \label{SIRexpS} \\
I^{\prime } &=&\beta (M)IS-(\mu +\nu )I  \label{SIexpI} \\
M^{\prime } &=&a\left( g(I)-M\right)   \label{SIRexpM} \end{aligned}$$for which some lengthish algebra shows (see appendix) that independently of the specific functional forms of $g$ and $\beta $ the endemic state is (at least) locally asymptotically stable (LAS).\
However, we note that the exponentially fading Kernel gives maximum weight to the current, i.e. at the time $\tau =0$, rather than past, disease history. This might be un-realistic in many cases. Therefore, in the following we consider the Erlang strong kernel $\varrho (\tau )=a\tau
e^{-a\tau }$, so that the integral equation (\[eqM\]) can be replaced by a pair of ODE given by(\[nODEs\]) with $n=2$, leading to the following family of models: $$\begin{aligned}
S^{\prime } &=&\mu (1-S)-\beta (M)IS  \label{SIRERLS} \\
I^{\prime } &=&\beta (M)IS-(\mu +\nu )I  \label{SIRERLI} \\
M_{1}^{\prime } &=&a\left( g(I)-M_{1}\right)   \label{SIRERLM1} \\
M^{\prime } &=&a\left( M_{1}-M\right)  \label{SIRERLM2}.\end{aligned}$$Thus, in principle, it is possible to analytically characterise the local stability of the endemic state for the above four-dimensional system. However, also for very simple $g(I)$ and $\beta (M)$, the problem becomes analytically cumbersome. Some partial results on the local stability of the endemic state are thus reported in the appendix for generic $\beta$ and $g$. Though partial these results indicate some biologically meaningful facts: *i)* for very small delay the endemic state is locally stable. This makes sense since in this case the system approaches the undelayed case (therefore the system is also GAS in this case); *ii)* likewise for large delays the system is LAS; *iii)* the LAS of the endemics state continues to prevail for arbitrary delays if at equilibrium $\beta (g(.))$ is sufficiently large and $\beta
^{\prime }$ sufficiently small. The latter point means that stability always prevails if contact patterns at equilibrium are not dramatically altered by behaviour change as a response to small changes in the endemic prevalence.

Numerical results
-----------------

To get further insight in the system behaviour, in particular as regards the possibility of instability triggered by social behaviour change, we shall investigate numerically the ’benchmark’ case $g(I)=kI$ and$$\beta (M)=\frac{\beta _{0}}{1+\alpha \frac{M}{I_{\ast }}},  \label{anstaz}$$where the parameter $I_{\ast }$ is simply a reference value, which we introduce to keep $\alpha$ small. This choice of $\beta(M)$ allows to analytically calculate $I_{e}$:$$I_{e}(\alpha ,k)=I_{SIR}\frac{I_{\ast }\Re_{0}}{\frac{k\alpha \mu }{\mu +\nu }+I_{\ast }\Re_{0}}  \label{I_ee}$$where $I_{SIR}=\mu(1-(\mu+\nu)/\beta_0)/(\mu+\nu)$ denotes the equilibrium in the classical mass-action SIR model with contact rate $\beta _{0}$ [@capassobook], and $S_{e}(\alpha ,k)=1-(1+\nu /\mu
)I_{e}(\alpha ,k)$. Note that the presence of behavioral changes affects the location of the endemic state, compared to the standard SIR model, by lowering the endemic prevalence $I_{e}$ and increasing the susceptible fraction $S_{e}$. As bifurcation parameters we choose $\alpha $ and $a$ that are the new parameters introduced by our model. The former tunes unambiguously the degree of change of contact patterns: given the level of the prevalence $I$, the greater $\alpha $ is, the smaller the contact rate as a function of $I$. In particular: $\alpha $ represents the relative rate of decline of the contact rate for an infinitesimal increase of the infective prevalence; $a$ tunes, as already pointed out, the delaying kernel.In our simulations, we consider the following measles-like parameter constellation: $\mu =(75\cdot 365)$days$^{-1}$, (implying a life expectancy $A=1/\mu =75$ years), $\nu =1/7$ days$^{-1}$, implying an average duration of the infectious period of one week, and $k=1$. As for the contact rate, we set $\beta _{0}=20(\mu +\nu )$, which implies $\Re _{0}=20$. Finally we set $I_{\ast }=0.9\mu /(\mu +\nu )$ which is the endemic prevalence in the classical SIR model with a BRN equal to 10, implying $I_{e}=I_{\ast }$. Note that at the steady state the value of the contact rate is one half of the value at $M=0$. This choice of parameters is sufficiently realistic and it allows a straightforward comparison with the the behavior of the classical SIR model.Figure \[bifu\] reports the the Hopf stability boundary in the $(\alpha ,a)
$ space and the related stability/instability regions. The figure shows that for low $\alpha $ ($\alpha <\alpha _{min}\approx 0.0386$) the endemic state is LAS independently of the delay, whereas for $\alpha >\alpha _{min}$ the equilibrium is unstable for low or high values of the mean delay, and it is unstable for intermediate delays. For example for $\alpha =0.5$ instability prevails for an average memory lenght $T=2/a$ between $76$ days and $3.36$ years, whereas for $\alpha =1$ it prevails for $T$ between $55.4$ days and $10.4$ years. Finally, at Hopf curve there are supercritical Hopf bifurcations.In figure \[figata\] we show, for $\alpha =1$, the off-transient behavior of the ratio $I(t)/I_{e}$ for an average memory length of two months ($a=1/30
$ days$^{-1}$). As it is easy to see, there are sustained oscillations such that the maximum peak is about $2.4$ times the value that would have been reached in case of instantaneous reaction to the disease prevalence. Quite interestingly, the minimum value is roughly equal to one quarter of $I_{e}$. This detail is of some interest, since the values of the minima reported in literature for regimes of sustained oscillations are usually very small. In this circumstance low populations stochastic effects should be taken into account. Furthermore, increasing the average delay both reduces the minimum of $I(t)$ and increases the period of the oscillations. For example, for $T=6
$ months and $\alpha =0.50$ to $1$, the oscillation becomes biennial. Thus, seemingly plausible values of the average delay $T$ and of the rate of decline of the contact rate $\alpha $ have the potential to generate the classical biennial inter-epidemic period of measles. Finally, as in the classical SIR model [@ly; @arsc; @ea], nonlinear resonance and chaos may be triggered by seasonal variations of the contact patterns [@grfr; @kg; @bac; @waz], modelled by one-year periodically modulating the FoI: $$FoI(M,t)=\varphi (t)\beta (M)I.$$For example, by assuming the simple seasonal law: $$\varphi (t)=1+\varphi _{1}cos\left( \omega t\right)$$where $\omega =2\pi /$(1 year)), one has that for $T=6$ months and $\alpha =1$ the behavior of the system for $\varphi _{1}=0.3$ is chaotic and the Maximum Liapunov Exponent  [@mle] of the associated Poincare’s map is equal to $3.067$ (value calculated by using the software NDT by Dr. Joshua Reiss [jr]{}).

Concluding Remarks
==================

The results of this paper show facts that, at the best of our knowledge, were never pointed out in the literature on endemic diseases. The main one regards the issue of oscillations, a central one in theoretical epidemiology. As well documented, a variety of diseases, first of all pre-vaccination measles in developed countries, exhibit steady oscillations in large communities, with a period around two years for the measles. Nonetheless, the classical SIR (and SEIR) model has a unique GAS endemic state where oscillations are only a transient, non sustained, phenomenon [@capassobook]. A huge work has therefore been devoted to the explanation of regular and chaotic oscillations in time-series of infectious diseases  [@kg; @ly; @arsc; @ea; @grfr] as the ’output’ of external periodic forcing due to periodic changes in contacts rates, plus further concurring factors such as time heterogeneity in susceptible recruitment. The present paper indicates that oscillations of endemic disease could have been triggered by a further, largely neglected, factor, i.e. changing human social behavior as a response to the recurrent disease threat. More precisely it shows that the existence of some degree of behavioral changes in response to the disease threat, coupled with some information delay as a memory of the past disease history may be a source of oscillations of common SIR diseases. Comparing this result to the oscillations triggered by changing vaccination behavior [@rebaga; @n; @o; @i], where an exponentially fading memory is sufficient to destabilize the endemic state and trigger sustained oscillations, here it happens that memories more focused in the disease past history, as exemplified by the Erlangian strong kernel, are needed. Moreover, here sustained oscillations occur even under moderate values of the parameter $\alpha $ tuning the individuals’ reaction to changing prevalence of the disease. In particular, in the oscillatory regime, seemingly plausible values of the average delay $T$ and of the rate of decline of the contact rate $\alpha $ have the potential to generate a large range of values of the inter-epidemic period of the sustained oscillation, including annual and biennial oscillations, as commonly observed for pre-vaccination measles. In the end, although empirical work is needed to better support our results, all this suggests the interesting possibility that behavioral changes could have been important factors in shaping endemic profiles of diseases in history, as recently suggested by  [@ferguson1].

Aknowledgements
===============

We thank very much two anonymous referees and an anonymous associated editor whose suggestions were very helpful.

Appendix
========

*If the referees should think it appropriate, this appendix might be put online.*

Persistence of the disease
--------------------------

As we mentioned in the main text, its hold that:

If $\Re_0 >1$ then the disease is strongly persistent, i.e. it exists a $\epsilon_0>0$ such that if $I(0)>0$, $S(0)>0$ and $M(0)>0$ then: $$MinLim_{t \rightarrow + \infty}I(t)\ge \epsilon_0>0\textrm{, }MinLim_{t \rightarrow + \infty}S(t)\ge \epsilon_0>0\textrm{, }MinLim_{t \rightarrow + \infty}M(t)\ge \epsilon_0>0 .$$

For the sake of the notation simplicity, we proof this lemma in the case of weak Erlang kernel, but the proof substantially holds for all Erlang delay kernels.We start noticing that the set: $$\label{pi}
\Omega = \left\{(S,I,M)| S\ge 0\textrm{, }I\ge 0\textrm{, }S+I \le 1\textrm{, }0\le M \le g(1)\right\}$$ is positively invariant for our model. Moreover, the disease free state $DFS=(1,0,0)$ is on $\partial \Omega$, as well as its stable manifold which is the set $\left\{(S,I,M)\in \Omega | I=0\right\}$. Thus, in virtue of the Freedman-Ruan-Tang theorem [@frt], if $DFS$ is unstable (i.e. if $\Re_0>1$) and, of course, the initial point is in the interior of $\Omega$, then the state variables are strongly persistent.

LAS of the EE under the exponentially fading memory
---------------------------------------------------

In case of exponentially fading kernel, linearizing the system at the endemic equilibrium $(S_{e},I_{e},g(I_{e}))$, the characteristic polynomial is: $$\lambda ^{3}+(a+\mu +I_{E}\beta (g(I_{E})))\lambda ^{2}+$$$$+\lambda \left( I_{E}(\mu +\nu )\beta (g(I_{E}))+a\left( \mu +I_{E}\beta
(g(I_{E}))-\frac{aI_{E}(\mu +\nu )g^{\prime }(I_{E})\beta ^{\prime
}(g(I_{E}))}{\beta (g(I_{E}))}\right) \right) +$$$$a\left( I_{E}(\mu +\nu )\beta (g(I_{E}))-\frac{I_{E}\mu (\mu +\nu )g^{\prime
}(I_{E})\beta ^{\prime }(g(I_{E}))}{\beta (g(I_{E}))}\right) ,$$whose coefficients are all positive.\
Thus the Routh-Hurwitz condition for the local stability of the endemic state is: $$\left( \mu +I_{E}\beta (g(I_{E}))-\frac{I_{E}(\mu +\nu )g^{\prime
}(I_{E})\beta ^{\prime }(g(I_{E}))}{\beta (g(I_{E}))}\right) a^{2}+\left(
(\mu +I_{E}\beta (g(I_{E})))^{2}-I_{E}^{2}(\mu +\nu )g^{\prime }(I_{E})\beta
^{\prime }(g(I_{E}))\right) a+$$$$+I_{E}^{2}(\mu +\nu )\beta (g(I_{E}))^{2}+I_{E}\mu (\mu +\nu )\beta
(g(I_{E}))>0,$$which is fulfilled in all cases since the coefficients of the above second order polynomial in $a$ are positive for all positive increasing $g(I)$ and positive decreasing $\beta (M)$. As a consequence, EE is locally asymptotically stable.

LAS of the EE under the strong Erlangian kernel
-----------------------------------------------

In this case one may show that the Routh-Hurwitz condition takes the form: $$RH= \sum_{h=1}^{5}q_{h}a^{h}>0$$where the rhs is a 5-th order polynomial in $a$ with null zero degree coefficient and: $$q_{1}=2I_E^{2}(\mu +\nu )^{2}\beta (g(I_E))^{2}(\mu +I_E\beta (g(I_E)))>0$$$$q_{5}=2\mu +2I_E\beta (g(I_E))-\frac{2I_E(\mu +\nu )g^{\prime }(I_E)\beta ^{\prime
}(g(I_E))}{\beta (g(I_E))}>0$$since $\beta ^{\prime }(M)<0$ and $g^{\prime }(I)>0$. The positivity of $q_{1}$ implies that for sufficiently small $a$ (i.e. for large average delays) the EE is LAS. The positivity of $q_{5}$ implies, on the contrary, that for sufficiently large $a$ (i.e. for very small average delays) the EE is LAS. Moreover, for large $a$ it also holds that: $$a^{-1}M_{1}^{\prime }\approx 0\Rightarrow M_{1}=g(I)$$$$a^{-1}M^{\prime }\approx 0\Rightarrow M=M_{1}\Rightarrow M=g(I),$$Therefore by singular perturbation approximation the system reduces to the undelayed one, which is not only LAS but also GAS. As far as the other coefficients are concerned, they have variable sign: $$q_{2}=4I_E(\mu +\nu )\beta (g(I_E))(\mu +I_E\beta (g(I_E)))^{2}+\frac{I_E(\mu +\nu
)\left( \mu ^{2}-I_E\nu \beta (g(I_E))\right) g^{\prime }(I_E)\beta ^{\prime
}(g(I_E))(\mu +I_E\beta (g(I_E)))}{\beta (g(I_E))}$$$$q_{3}=2(\mu +I_E\beta (g(I_E)))\left( \mu ^{2}+I_E\beta (g(I_E))(4\mu +2\nu +I_E\beta
(g(I_E)))\right) +$$$$+\frac{2I_E(\mu +\nu )\left( \mu ^{2}+I_E\beta (g(I_E))(\mu +\nu
-I_E\beta (g(I_E)))\right) g^{\prime }(I_E)\beta ^{\prime }(g(I_E))}{\beta (g(I_E))}$$ $$q_{4}=4(\mu +I_E\beta (g(I_E)))^{2}-\frac{I_E^{2}(\mu +\nu )^{2}g^{\prime
}(I_E)^{2}\beta ^{\prime }(g(I_E))^{2}}{\beta (g(I_E))^{2}}+\frac{I_E(\mu +\nu )(\mu
-3I_E\beta (g(I_E)))g^{\prime }(I_E)\beta ^{\prime }(g(I_E))}{\beta (g(I_E))}$$However, a sufficient condition to have $q_{2}>0$ is: $$\mu ^{2}-I_E\nu \beta (g(I_E))<0  \label{cq2p}$$Similarly we have the following a sufficient condition guaranteeing that $q_{3}>0$: $$\mu ^{2}+I_E\beta (g(I_E))(\mu +\nu -I_E\beta (g(I_E)))<0  \label{cq3p}$$and $q_{4}>0$: $$\frac{\beta (g(I_E))\left( \mu -3I_E\beta (g(I_E))-\sqrt{17\mu ^{2}+I_E\beta
(g(I_E))(26\mu +25I_E\beta (g(I_E)))}\right) }{2I_E(\mu +\nu )g^{\prime }(I_E)}<\beta
^{\prime }(g(I_E))<0.  \label{cq4p}$$As a consequence, if at the EE all the conditions (\[cq2p\]), (\[cq3p\]) and (\[cq4p\]) are met then the EE is LAS. These conditions are quite general, since they are not linked a priori to particular forms of the contact rate or of $g(I)$. Although, they are complex and of difficult reading, a simple biological interpretation is given in the text.

[9]{}

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![Strong Erlangian kernel. Local stability boundary, and corresponding regions of Local Asymptotic stability and instability in the parameter space $(\alpha,a)$), where $\alpha$ is the relative rate of decline of the contact rate for an infinitesimal increase of the infective prevalence, and $a$ is inversely related to the average information delay $T$ ($a=2/T$).[]{data-label="bifu"}](cpall.eps){width="0.95\linewidth"}

![After-transient sustained oscillations of infectious fraction (scaled to the equilibrium value $I_{e}(\protect\alpha)$) that are induced by information-dependent FoI. Here $\protect\alpha=1$ and $a=30^{-1}$ days$^{-1}
$ corresponding to an average memory of two months: $T=60$ days[]{data-label="figata"}](I30.eps){width="0.95\linewidth"}

[^1]: corresponding author


Q:

Testing/mocking an orientation change in Chrome?

We're writing a mobile app using jQuery mobile and do most of the javascript debugging in Chrome.  One thing I can't test however is an orientation change, from portrait to landscape and vice versa.  I have to use a phone to fire that event, and am unable to debug the javascript window.orientationchange event without Chrome.
Or so it would seem.  Is there a way to mock this event in Chrome somehow?

A:

Since a desktop device doesn't have any real orientation changes, like mobile devices does have, it's no use to listen to orientationchange. You could simulate orientation by resizing the browser window though.
David Walsh wrote an article about this: http://davidwalsh.name/orientation-change


Q:

Why does the x axis disappear when the graph very big

I am trying to load large graphs using JFreeChart. However, I have a problem with the X axis when the buffered image is above a certain size. The values disappear on the X axis. This can be seen in the third graph on the image.

I would appreciate any help in fixing the problem
import java.awt.Color;
import java.awt.image.BufferedImage;
import java.util.ArrayList;

import org.jfree.chart.ChartFactory;
import org.jfree.chart.JFreeChart;
import org.jfree.chart.axis.ValueAxis;
import org.jfree.chart.plot.PlotOrientation;
import org.jfree.chart.plot.XYPlot;
import org.jfree.data.xy.XYSeries;
import org.jfree.data.xy.XYSeriesCollection;

import javafx.application.Application;
import javafx.concurrent.Task;
import javafx.embed.swing.SwingFXUtils;
import javafx.geometry.Pos;
import javafx.scene.Scene;
import javafx.scene.control.Label;
import javafx.scene.control.ScrollPane;
import javafx.scene.image.Image;
import javafx.scene.image.ImageView;
import javafx.scene.layout.StackPane;
import javafx.scene.layout.VBox;
import javafx.stage.Stage;

public class Program2 extends Application {
    public static void main(String[] args) {
        launch(args);
    }

    @Override
    public void start(Stage primaryStage) {
        try {
            StackPane p = new StackPane();
            primaryStage.setTitle("Chart Application");
            Label loader = new Label("Loading...");
            loader.setGraphic(new ImageView(new Image("https://media.giphy.com/media/FmcNeI0PnsAKs/giphy.gif")));
            loader.setFont(new javafx.scene.text.Font(35));
            p.setStyle("-fx-background: #FFFFFF;");
            p.getChildren().add(loader);
            StackPane.setAlignment(loader, Pos.CENTER);

            Scene scene = new Scene(p, 600, 600);
            primaryStage.setScene(scene);
            primaryStage.setMaximized(true);

            Task<ArrayList<ImageView>> loadInitial = new Task<ArrayList<ImageView>>() {
                @Override
                public ArrayList<ImageView> call() {
                    ArrayList<ImageView> images = new ArrayList<ImageView>();
                    XYSeries data = new XYSeries(1);

                    for(int j = 0; j <= 100; j += 2) {
                        data.add(j, -0.2);
                        data.add(j, 1);
                        data.add(j + 1, 1);
                        data.add(j + 1, -0.2);
                    }

                    XYSeriesCollection dataset = new XYSeriesCollection(data);

                    JFreeChart chart = ChartFactory.createXYAreaChart("", "", "", dataset, PlotOrientation.VERTICAL, false, false, false);
                    chart.setBackgroundPaint(Color.WHITE);
                    chart.setBorderVisible(false);
                    chart.setAntiAlias(true);

                    XYPlot plot = (XYPlot) chart.getPlot();

                    ValueAxis range = plot.getRangeAxis();
                    range.setLowerMargin(0);
                    range.setUpperMargin(0);
                    range.setVisible(false);

                    ValueAxis domainAxis = plot.getDomainAxis();
                    domainAxis.setLowerMargin(0);
                    domainAxis.setUpperMargin(0);

                    BufferedImage capture = chart.createBufferedImage(1000, 50);
                    ImageView imageView = new ImageView();
                    Image chartImg = SwingFXUtils.toFXImage(capture, null);
                    imageView.setImage(chartImg);

                    images.add(imageView);

                    BufferedImage capture2 = chart.createBufferedImage(10000, 50);
                    ImageView imageView2 = new ImageView();
                    Image chartImg2 = SwingFXUtils.toFXImage(capture2, null);
                    imageView2.setImage(chartImg2);

                    images.add(imageView2);

                    BufferedImage capture3 = chart.createBufferedImage(100000, 50);
                    ImageView imageView3 = new ImageView();
                    Image chartImg3 = SwingFXUtils.toFXImage(capture3, null);
                    imageView3.setImage(chartImg3);

                    images.add(imageView3);

                    return images;
                }
            };

            loadInitial.setOnSucceeded(e -> {
                VBox images = new VBox();
                ArrayList<ImageView> result = loadInitial.getValue();
                for(ImageView image : result) {
                    images.getChildren().add(image);
                }

                ScrollPane scrollPane = new ScrollPane(images);
                scrollPane.setStyle("-fx-background: #FFFFFF;");

                scene.setRoot(scrollPane);
            });

            new Thread(loadInitial).start();

            primaryStage.show();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Note I also posted here

A:

This problem is caused because the number of ticks (markers on the axis) exceeds the ValueAxis.MAXIMUM_TICK_COUNT when a graph is that large.
In order to fix this problem, you can rebuild the package with an increased value for ValueAxis.MAXIMUM_TICK_COUNT or you could write a method that will allow you to set the maximum tick count and then rebuild the pack. This will allow you to set the amount of ticks in a different java file. This could be a method such as ValueAxis.setMaximumTickCount(int ticks)
Taken from here
Edit
In order to achieve this, I edited two files from org.jfree.chart.axis; ValueAxis.java and NumberAxis.java.
Changes to ValueAxis.java. I added the following to the bottom of the class.
private int maxTicks = MAXIMUM_TICK_COUNT;

public void setMaxTicks(int max) {
    maxTicks = max;
}

public int getMaxTicks() {
    return maxTicks;
}

Changes to NumberAxis.java.
On the line 957 and line 1052 I changed an if statement from
if (count <= ValueAxis.MAXIMUM_TICK_COUNT) {

to
if (count <= getMaxTicks()) {

Finally I rebuilt it using Apache Ant


We study the distortions to industrial organization caused by entry regulation. We take advantage of heterogeneity across industries in their natural barriers and growth opportunities to examine whether some industries are differentially affected by country-level entry regulation. In industries with high natural entry barriers, entry regulation has little impact on the quantity and average size of firms in an industry. By contrast, in industries with low natural entry barriers, countries with high entry regulation have relatively few, large firms. We find no relation between natural entry barriers and overall industry share of manufacturing, as a function of entry regulation. Utilizing firm-level data, we show that operating margins are relatively high in low barrier industries in high entry regulation countries. Finally, we analyze the ability of industries to take advantage of shocks to growth opportunities. In countries with high entry regulation, industries respond to growth opportunities through the expansion of existing firms, while in countries with low entry regulation, the response is through the creation of new firms; the total sectoral response is invariant to the level of regulation. Our results suggest that regulation distorts the structure of industry, promoting industry concentration, but does not have measurable effects on intersectoral allocations.

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"[energeticbrassmusic]" "♪♪" "I was going for a younger, sexier, Vincent Price." "Okay, shut it." "As much as I'd love to talk about our wonderful show tonight... [sighs] Whoopi Goldberg, Denis Leary, the amazing ventriloquist, Jonathan Geffner," "I actually have something very serious and pressing and somewhat urgent to discuss." " You finally got laid?" " [laughter]" " [laughs mockingly]" " There's been an outbreak." "How serious of an outbreak?" "'Cause if it gets bad, I do have cyanide pills in my desk drawer." "They are chewable," "Very hard to find on the deep web." "Absolutely it sounds extreme, but it is the cleanest" " and easiest way to die." " Okay." "Everybody can kill themselves during hiatus." "The reason I look a little glum is because we have a lice outbreak." "[all groaning] All right, all right!" "It's not Ebola!" "[exhales] But you all need to be treated." "Well, you might want to start off with Marcus because his children had lice all week." " You bitch!" " Dude!" " What?" " That was a secret." " Marcus, patient zero!" " How dare you!" "Don't worry, the Lice Fairy is here." "Excuse me?" "What did you call me?" "The Jamaican ladies to treat all of our scalps!" "Oh, gotcha." "Um, I've had two very bad experiences with Jamaican ladies touching me." "This place is disgusting." "I'd always knew I'd end up getting something working here." "Which is why we all need to be treated." "All right, I have a time schedule of when everyone is going to visit the Lice Fairy, so please see me after." "Yeah, I think I see one." "What?" "Get it." "Kill him." "Kill him!" " Get it!" " [whimpers] [grunting, screaming]" "I got it." "From Studio 9B in the heart of New York City, it's "Nightcap with Jimmy."" "Tonight, we're "Makin' Whoopee"" "with Whoopi Goldberg." "Lovable Masshole Denis Leary." "Renowned Jewish ventriloquist" "Jonathan Geffner." "And now, the man who's number five in the ratings, but number one in our hearts, here's Jimmy!" "We are in this small, cramped room [whispers] Because we have lice and nobody can find out about it." "We need to be quiet." "Like Anne Frank quiet." "Yeah, yeah, you got it bad." " I knew it." " You know, if she has it," "I probably have it 'cause I fell asleep in her lap last night watching "Cupcake Wars."" " [all aww]" " Boy, that is sweet." "And how long you all been together for?" "2 years, 1 month, 13 days." " Oh. [chuckles]" " Oh, but... we're not.. we're not a couple." " We don't..." " Oh." "Hey, you know, when I was a kid, um, every time I had lice, my dad would soak my head in kerosene." "I think it may have killed more than just the lice." "In your medical opinion, uh, that treatment, does it also... treat down here?" "My pubes?" "[lively music]" "Oh, my God." "It's even worse than I thought." "I actually think I look kind of hot." "I've never felt so tough." "You all look hideous." " This is all your fault." " Allegedly." "You guys don't get it." "We are the fifth-rated late night talk show." "People find out we have lice, that's it." "We're done." "We're cancelled." "You're screwed." "It kind of looks like we just got back from the Caribbean." "That's it." "That's what we're gonna say." "We just got back from the Caribbean." "Don't tell Whoopi we have lice." "I can't wait to get my cornrows." "I have the perfect facial structure for it." "Sorry, Randy." "And Penny." " And Staci." " I'm good." " Ehh..." " I'm cute." " [high-pitch] Ehh..." " Pretty." "[higher-pitched] Ehh... ♪♪" "No, you can't." "Because you can't cancel the day of." " Because people don't..." " Hey, Staci." "I don't care!" "He has to be on the sh..." "Staci!" "Maggie, hold on a second." "What, Todd?" "Oh, uh, do you know where Jimmy's peanut butter is?" "No, I don't know where Jimmy's peanut butter is." "Well, okay, well, he told me to ask you 'cause you know where everything is." "Maggie, listen to me." "I understand that he's sick, but you cannot cancel..." "Maggie!" "[shouts] Maggie!" " Oh!" " Is Denis Leary sick?" "Well, his manager says he is." "No!" "God!" "Jimmy loves Denis!" "We got to get Denis Leary on the show!" " I know!" " All right, well," "Jimmy didn't prepare anything, 'cause, you know he can always wing it with Denis, so..." "That's implying he usually does prepare" " for his interviews?" " No, he doesn't. [laughs]" "So you don't know where the peanut butter is?" "Oh!" "Check his bottom drawer!" "Bottom drawer." "God, yes!" "Oh, my God, I can feel them hatching." "Oh, God, the Lice Fairy is still here." "Ugh!" "Hey, um, you... you know where the ventriloquist put the puppet thing?" "Oh, you mean Ezra?" "He's not technically a puppet, he's a dummy and he's in dressing room number 3." " Did you want to meet him?" " No!" "Nope." "Nope." "Nope." "Nope." "Nope." "He doesn't have access to the whole building, right?" "Oh, well, he is a guest, but he's not a person, but he lives in a suitcase." "The suitcase has locks on it, right?" " So he... he can't get out." " I don't think so." "Why?" "[scoffs] No reason." "It's just, you know, I don't want... to surprise him." "I don't want him... to surprise me." "You know, it's just one of th..." "Just one of those things." "You know what I mean?" "♪♪" "Oh, Whoopi." "Big fan." "Thanks." "I think." "Oh, Whoopi Goldberg, we are so excited to have you on the show." "Okay, so is this some sort of... diversity thing?" "To make me feel more comfortable being black and everything?" "No, no, no, no, no." "Hashtag BlackLivesMatter." "Um, no, we were on a company cruise." "You know that doesn't make this any less racist?" "Right?" "Can I offer you guys some freshly-sliced watermelon?" "Don't mind if I do." "Fresh watermelon, Ms. Whoopi?" "Sure. 'Cause who doesn't like watermelon?" "Mm-hmm." "You know, I gotta tell you, this is really making me a little uncomfortable." "I just feel like maybe "Nightcap"" "is not the place I should be." "No, no, no, no, no, Whoopi." " Please don't walk out." " I gotta think about this." "Do you think we could take the watermelon to my room?" " Yes!" " A safer environment." " Absolutely." " Yeah." "Yeah." "Let's go." "I've always felt this show was racist." " [strained] Grady!" " I know." "[exhales sharply]" "Well, this is a pickle." "Listen to me, if we lose Whoopi... we've already lost Denis Leary because he's sick, we're gonna have 40 minutes of a ventriloquist." "But the ventriloquist is so good." " Not for 40 minutes." "  [phone dings]" "What?" "Did you see your reflection?" "Whoa." "No, no, no." "So my friend who works on Denis' show said that Denis is at work today and looks fine." " You have a friend?" " She's an online friend." "She says that he also baked banana bread for the crew." "Asshole!" "You know what?" "I'm gonna go down to Denis Leary's set and I'm gonna grab his flat, pale, potato eating, Irish ass and I'm gonna bring it back to our show." "And I'm not talking like this 'cause I got cornrows." "♪♪  [energetic brass music]" "♪♪" "Jesus. [panting]" "Let me guess, you're scared of Ezra." "I've seen it before." "[stammers] Is he drinking coffee?" "Oh, it's better for our relationship if I treat him like a person." " Oh." " Nothing to be scared of." "He's a nice guy." "Want to touch him?" "Nah, I don't want to touch him." "Hey, it's okay." "You can touch me." "I don't mind at all." " What?" " Hey, where you going?" "♪♪" "[retching]" "Staci!" "Are you okay?" "Oh, my God, Penny, what are you doing here?" "I thought you might need emotional support." "You just ran out of there so quickly and my natural instinct was to follow you." " Is that wrong?" " No." "Well, yes and no." "Look, I know Denis Leary's trailer is around here somewhere." "I'm trying to find it." "Oh, I know where he is!" "My friend told me he's around the corner." "Go get him, tiger!" "Copy that." "You tell them that the situation's changed." "Oh, fuck." "God damn it." " What?" " Oh, fucking Leary." " What?" " Oh, my God, look at your hair." "I can't believe you came down here." "Look at your hair." "What are you talking about?" "This is for a part." "What's that for?" " I came down here..." " I'm acting." " I'm an actor." " You cancelled on me the day of the shoot!" "Okay, well... well... because I'm sick." " So, that's..." " Denis, we go way back, man." "You've done the show a million times." "Don't be such a Hollywood guy, be honest with me." " Come on, we're..." " Listen, I'm sick, okay?" "I'm fuckin' sick and I..." "I shouldn't even be on my own set, but I'm doing it because" "I have to be here to... you know, 'cause it's a budget thing." "So, like I said, if I were you," " I'd back off." " What, sweetheart?" "I just have your tickets for tonight's hockey game." "Are you kidding me?" "The Bruins-Rangers game?" "Tonight at 7:00?" " Can I explain something?" " You mother..." "Let me explain something to you, this... this is..." "I'm not sick." "I don't..." "I don't like to brag about my charity stuff." "So what I'm doing is I'm taking a couple of sick kids to the..." "I am." "I'm taking sick kids to the..." "they're not gonna die, but they're very sick and... and they're... you know, their house..." "they have lupus." "They can't..." "They can't have ice cream, they can't eat hotdogs, it's like... you know what I mean?" "It's a big thing." "You can't eat pork if you have lupus?" "I don't think you can eat..." "there's certain things you can't eat." "Yeah." "I mean, I don't know everything about it, I'm just..." "Listen," "I don't like to brag about it, so I said I was sick," "I didn't want to mention sick kids." "All right, so it's at 7:00, okay?" "You can still..." "You can still do our show" " and make it there by 7:00." " Yes, but... there's a... pre-game skate." " Which is..." " You're gonna skate" " with the lupus kids?" " It's a lupus, uh..." " related skate." " Okay, you know what, Denis?" " And that's at 6:00." " You're a grown man." "So why don't we just say, you do the show, you'll be there by 7:00." "You can bring all the sick kids with you to the show." "Okay?" "I..." "I'm not sure the sick kids will want to come to the show." " [stammers]" " All right, well, you can meet them at the rink." "Please." " All right, I'll do it." " You will?" " I'll do it." "Yeah." " Oh, my God." " All right." " Oh, my God, you're the best." " Okay." " Oh, my God." " If you weren't married..." " All right, if..." "Well, I'm very married, so..." "Yeah." "All right." ""Nightcap" fuckin' piece of shit that show is." " I got him." " Yay, that's such good news." "And I have some good news too." "I got us a ride back to the studio." "[gasps] Oh, my gosh, Penny!" "This is so fun." " Oh!" " And I also got us an Edible Arrangement to nibble on." "I feel like I'm in a Nora Ephron movie." "[jazzy music]" "All set." "You are mic'd." " Thank you." " Yeah." " Oh, and I'm not a racist." " Okay." "Hey, Whoopi!" "[laughs]" "It's Todd." "We met on, uh..." "I'm Jimmy's friend." "Yeah, and producer." "That's sort of accurate." " Is she all mic'd up?" " Yeah, she's mic'd." "Dude, nice." "Okay, good luck, Whoop." " Touch that tail." " Do not touch my nipples." "I always think he's gonna hit me." "Oh, he never does." "Uh, hey, Whoops, would you mind... could you sign my copy of "Jumpin' Jack Flash"?" "It's me and Jimmy's favorite." "We watch it all the time." " Sure." " Ah, thank you so much." " This a bootleg?" " Yeah, I got it from a Chinese guy down on Canal Street." " Nice." " Nice." "Yeah, no offense." " I just..." " No, no, it's cool." " They don't pay me." " Yeah, right." " Cool." " Ah, cool!" " [sighs]" " So, Todd..." " Yeah?" " What's up with your hair?" " I think we may have lice." " [chuckles]" " Yeah." " You're serious?" "Yeah, who knows, you know?" "[grumbles]" " They're all over the place." " So right now, while we're talking, lice could be jumpin'..." " from you to me?" " No!" "No, no!" "I work upstairs with Jimmy." "No, upstairs is totally clean." "Yeah, I'm all good, but down here is probably infested with them, so I'm getting the hell outta here." "[energetic brass music]" "♪♪" "Oh, my God, look at you guys." "What?" "Listen, you go deal with the ventriloquist," " I'll deal with Whoopi." " I'm on it." " Should we high-five?" " No." "Okay." "♪♪" " Oh, hey, Todd." " Hey." "I just met Ezra." "He's wonderful." " Have you met him?" " Yeah, he drinks coffee!" " Can I tell you a secret?" " Yes!" "You tell me one, then I'll tell you one." "Nah, that's okay, I just want to tell you mine." " Oh." " I'm afraid of puppets." " Why?" " You ever see that movie" ""Magic" with Anthony Hopkins?" "It's one of Jimmy's favorite movies." "He brings me over all the time to watch it." " Does he know you're afraid?" " Yes!" " Do you cry?" " Yes!" "Wait, Jimmy thinks it's funny when you cry?" "Yeah, I make him laugh, you know?" "I am to him what he is to America." "You know, Todd, I used to have a debilitating fear of goats all throughout my childhood." "It was bad." "So I finally tried immersion therapy." "My mom locked me in a pen with goats overnight." "You know, just me and the goats?" "It worked." "I woke up the next day and I wasn't afraid of goats, and I finally saw them for what they are." " Goats?" " Yeah." "Not evil, horned monster creatures." "Just goats." "[giggles]" "Hey, have you seen Jimmy's peanut butter?" "Um... no, I haven't." "[clicks tongue]" "♪♪" "That's fine." "I'll call Kerry Washington" "I don't give a shit." "What are you doing here?" "Hmm, well, I was meditating, but I also figured that you'd like an update on Whoopi." "What is she doing?" "Is she still here?" "Oh, well, she's asking questions, but I did my best to keep her here" " and, uh..." " All right, guys, listen to me, this is... this is probably the biggest thing" "I've had to face thus far in my career." "Do we want to be known as a racist show or a show that's gonna be know for having a lice infestation?" "Okay, but we deal with celebrities and celebrities are whores..." "we all know that, and we all know, very well, that when it comes to self-promotion, people can look beyond racism in a heartbeat." "Okay, on the count of three, you say which you think is worse." "Racism or lice infestation." "Are you ready?" "One, two, three." " Lice." " Strep throat." "Strep throat?" "Um, I think I'm getting it." "It's also contagious." " That's a tough call." " Uh, excuse me, white devils." "What is this I hear about the "Nightcap" staff" " being racist now?" " Jesus, word travels fast." "I'm a publicist." "I'm the one that word travels to;" "and, yes, it travels fast because I'm good." "I'm also black." "Did you know I was black, Staci?" "I knew you were a publicist." "Don't get cute with me now." "Is that what these ridiculous cornrows are about?" "No, no, no." "We went on a vacation in the Caribbean and we..." "When did you go on a vacation to the Caribbean?" "You look whiter than ever." "Do you ever want another black person on this show?" "Lupita Nyong'o, Jamie Foxx, Al Roker." " I don't want Al Roker." " Nobody wants Al Roker." "Malik, why are you here?" "You don't even have a client on the show." "I heard that Whoopi was on the show tonight and she needs a new publicist." "So you need to take me over there." "I will take you over to Whoopi right now, but you have to promise that you won't tell anybody this is a racist show... or that we have lice." "You have lice?" "No." " Deal." " Deal." "♪♪" "Sup, bro?" "I'm Todd." "Ezra, right?" "Just gonna chill real quick." "Is that cool?" "You like coffee, right?" "Yeah, I can get you some coffee there." "[chuckles]" "I'll have some too." "There we go." "Coffee actually does make it feel more normal here." "Whoa-ho-ho." "Oh." "Okay." "Oh, look at these guns." "Ho-ho-ho!" "Look at the guns." "Oh, my God." "Oh, Jesus." "Oh, I sp..." "Oh." "Oh, boy." "Oh, jeez." "I'll get that off for you." "I'll get you off." "Hey, what are you doing?" "Oh, yeah, I'm sorry, man." "Wait, wait, hold it." "I told you you could touch him, but not like that." "This dummy is only 12 years old." "What?" "Oh, what?" "No, no, no." "I wasn't touching his dick." "Yeah, yeah, yeah." "Just get out of here." " People like you disgust me." " What?" "People like..." "I was trying to be social." " Your dummy's antisocial." " "Social."" "Nice euphemism." "I'm a good man." "♪♪" " [knocking on door]" " Yeah?" "Whoopi?" "Ms. Goldberg?" "Hi." "Hi." "I just wanted to come in and brief you on your interview, but before I do that, I want to introduce you..." "Is this to prove to me you know black people and have black friends?" "Oh, no, no, no, no." "We're not friends." "I'm Malik Walker, publicist." "We met at the Met Ball." "Six years ago." "Okay, I only want to talk to you." " Me?" " You." "Okay, well, I'm just going to leave my card right here." "We'll be in touch." "[clears throat] [sighs] Look..." "I don't know how to even begin this conversation." "When I came in, everybody had those, you know, cornrows in their hair and I was feeling really uncomfortable and, you know, looking around and thinking," ""What, are you making fun of me?"" "'Cause you couldn't get it together with the dreads so you got cornrows?" "You got me the watermelon." "It's a whole thing." "But then this guy comes in and tells me that you have a lice infestation." "A lice infestation." "What the hell?" "That is the most disgust... it's the nastiest." "It's like..." "It's like coochie juice on the chair." "Tell me honestly." "I just..." "I just... want somebody to talk to me honestly." "Are you racist, or do you have a lice infestation here?" "I can't say it any clearer." "Oh, okay." "We..." "We're... we're..." "Rrr..." "Racist." "[gasps]" " Yes!" " Oh!" "Oh, my God." "I can't believe you were so honest with me." "You know, I work in television, and no one ever tells you the truth." "You know, you get these big networks and they know what they are, and they pretend they're not, but you know." "I just love that you're honest." "As matter of fact, it's blowing my mind." "And I think I would like to make "Nightcap"" "someplace I come, you know, whenever I have something I need to do." "I got to tell you something." "I like being racist." "♪♪" " Penny." " [gasps] Staci." "I have been looking everywhere for you." "Listen, the lice story didn't break." "Whoopi thinks we're racist, which is so cool, so it's going to be a great show." "Um, no, it's not." "I just got off the phone with Dennis Leary's manager, and he's not coming tonight." "What?" "He says you gave him lice." "Well, that is on us." "All right, tell the ventriloquist and that dummy they have two segments on the show tonight." "Ezra's going to be so excited." " He's gonna get a woody." " What?" "A puppet erection."


Q:

SQL FOR XML multilevel from one pivoted table

I've been trying to use FOR XML without success to do the following.
Source table:
Country            | ID      | 1950        | 1955
-----------------------------------------------------
Country 1          | 1       | 2.43        | 2.55
Country 2          | 2       | 4.54        | 42.15

Desired output:
<locations>
  <location>
    <loc name='Country 1' id='1' />
    <dub>
      <data year='1950' value='2.43' />
      <data year='1955' value='2.55' />
    </dub>
  </location>
  <location>
    <loc name='Country 2' id='2' />
    <dub>
      <data year='1950' value='4.54' />
      <data year='1955' value='42.15' />
    </dub>
  </location>
</locations>

Will it be necessary to unpivot for the dub element? I wanted the simplest SQL query possible.
I think FOR XML is too difficult to use. You should be able to specify the hierarchy just using simple XPath on column names but it won't accept, for example, [dub/data/@year=1955/@value] as the name of the column [1950].

A:

SQL Fiddle
MS SQL Server 2012 Schema Setup:
create table YourTable
(
  Country varchar(20),
  ID int,
  [1950] numeric(5,2),
  [1955] numeric(5,2)
)

insert into YourTable values
('Country 1',           1,        2.43,         2.55),
('Country 2',           2,        4.54,         42.15)

Query 1:
select T.Country as 'loc/@name',
       T.ID as 'loc/@id',
       (
         select 1950 as 'data/@year',
                T.[1950] as 'data/@value',
                null,
                1955 as 'data/@year',
                T.[1955] as 'data/@value'
         for xml path(''), type
       ) as dub
from YourTable as T
for xml path('location'), root('locations'), type

Results:
<locations>
  <location>
    <loc name="Country 1" id="1" />
    <dub>
      <data year="1950" value="2.43" />
      <data year="1955" value="2.55" />
    </dub>
  </location>
  <location>
    <loc name="Country 2" id="2" />
    <dub>
      <data year="1950" value="4.54" />
      <data year="1955" value="42.15" />
    </dub>
  </location>
</locations>


Carpets, such as free-lay carpet or backed carpet tile, have been prepared as either a tufted or a fusion-bonded carpet material having a wear face surface.
Tufted carpet tile generally comprises a primary carpet base sheet material having a plurality of tufted yarns through the primary base sheet material to form a wear face surface of loop or cut pile, and usually with a precoat, such as of a latex-type material, like carboxylated styrene-butadiene-styrene precoat, on the back surface to bond the yarn to the primary back. Tufted carpet roll goods usually have a secondary backing of jute, woven polypropylene or foam. Tufted carpet tile includes a backing layer which generally comprises a solid, thermoplastic material, such as atactic polypropylene, bitumen or polyvinyl chloride, preferably with a glass fiber sheet material, such as a mesh or fleece material, embedded therein to impart dimensional stability to the carpet tile. The backing may also include a foam-type backing layer, such as a PVC or urethane foam layer. Non-thermoplastic materials, such as polyurethane, may also be used for the backing. In addition, the tufted carpet tile may include a secondary backing sheet, such as of fiberglass, polypropylene or polyester-type material, or in fact, may be laminated and/or contain a pressure-sensitive, adhesive, strippable layer for application to a substrate.
Fusion-bonded carpet has essentially the same backing except that the fusion-bonded carpet is characterized by a plurality of cut pile yarns, for example, of nylon or other natural or synthetic fibrous-type material, implanted in an adhesive layer, particularly a thermoplastic, like a polyvinyl chloride layer, or a hot-melt adhesive layer. Where a polyvinyl chloride plastisol is used, heating of the layer gels and then fuses the layer into solid form, while with hot-melt adhesive material, a melted layer is applied and subsequently cooled into solid form. The plurality of fibrous yarns are bonded to and extend upright from the adhesive base layer to form a face wear surface. Generally, a fusion-bonded carpet also includes an adjacent backing layer of a glass fiber scrim material having large open areas and a glass fiber fleece which serves as a stabilizing carrier.
Fusion-bonded carpets may be prepared employing a number of well-known, but different techniques and machines in both horizontal and vertical processes known as the I-bond or U-bond processes. The single-end fiber implantation technique, known as the I-bond process, holds the ends of the severed yarns in place by a layer of an adhesive material on a backing material, for example, a fiberglass scrim-type material adjacent to a non-woven, glass fiber fleece layer. Thereafter, the free ends of the fusion-bonded carpet may be embedded in another adhesive layer as before on the same or different backing material, and the resulting sandwich-type carpet then cut, for example, with an oscillating blade in a vertical fusion-bonding method or by a continuing band knife in the horizontal fusion-bonding method, to form two rolls of fusion-bonded carpet having a cut wear face surface for backing into carpet tile or used as roll goods. In another I-bond process, the severed yarn has one end implanted directly into an adhesive layer on a backing sheet, with the other severed end forming the wear face surface of the carpet.
The U-bond process generally includes a corrugated or pleated layer of yarn, wherein each loop end is placed in a layer of adhesive material on backing sheet material, and then the sandwich-formed carpet material cut to form two rolls of fusion-bonded carpet, each roll having cut loops of yarn embedded in the adhesive layer; hence, the name U-bond process.
The fusion-bonded carpet material prepared by these various processes can then be used as free-lay carpet or be converted into carpet or carpet tile with the application of a suitable backing layer and cutting or trimming it into suitable form.
It is desirable to provide for a new and improved fusion-bonded carpet material prepared by a modified I-bond process, including a carpet tile characterized by novel design patterns on the face wear surface and for a method for preparing such carpet material.


.class final Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;
.super Landroid/os/AsyncTask;

# annotations
.annotation system Ldalvik/annotation/Signature;
    value = {
        "Landroid/os/AsyncTask",
        "<",
        "Ljava/lang/Object;",
        "Ljava/lang/Void;",
        "Ljava/lang/Void;",
        ">;"
    }
.end annotation

# instance fields
.field final synthetic this$0:Landroid/support/v7/widget/ActivityChooserModel;

# direct methods
.method constructor <init>(Landroid/support/v7/widget/ActivityChooserModel;)V
    .locals 0

    iput-object p1, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    invoke-direct {p0}, Landroid/os/AsyncTask;-><init>()V

    return-void
.end method

# virtual methods
.method public final bridge synthetic doInBackground([Ljava/lang/Object;)Ljava/lang/Object;
    .locals 1

    invoke-virtual {p0, p1}, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->doInBackground([Ljava/lang/Object;)Ljava/lang/Void;

    move-result-object v0

    return-object v0
.end method

.method public final varargs doInBackground([Ljava/lang/Object;)Ljava/lang/Void;
    .locals 12

    const/4 v2, 0x0

    const/4 v11, 0x1

    const/4 v10, 0x0

    aget-object v0, p1, v2

    check-cast v0, Ljava/util/List;

    aget-object v1, p1, v11

    check-cast v1, Ljava/lang/String;

    :try_start_0
    iget-object v3, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iget-object v3, v3, Landroid/support/v7/widget/ActivityChooserModel;->mContext:Landroid/content/Context;

    const/4 v4, 0x0

    invoke-virtual {v3, v1, v4}, Landroid/content/Context;->openFileOutput(Ljava/lang/String;I)Ljava/io/FileOutputStream;
    :try_end_0
    .catch Ljava/io/FileNotFoundException; {:try_start_0 .. :try_end_0} :catch_0

    move-result-object v3

    invoke-static {}, Landroid/util/Xml;->newSerializer()Lorg/xmlpull/v1/XmlSerializer;

    move-result-object v4

    const/4 v1, 0x0

    :try_start_1
    invoke-interface {v4, v3, v1}, Lorg/xmlpull/v1/XmlSerializer;->setOutput(Ljava/io/OutputStream;Ljava/lang/String;)V

    const-string/jumbo v1, "UTF-8"

    const/4 v5, 0x1

    invoke-static {v5}, Ljava/lang/Boolean;->valueOf(Z)Ljava/lang/Boolean;

    move-result-object v5

    invoke-interface {v4, v1, v5}, Lorg/xmlpull/v1/XmlSerializer;->startDocument(Ljava/lang/String;Ljava/lang/Boolean;)V

    const/4 v1, 0x0

    const-string/jumbo v5, "historical-records"

    invoke-interface {v4, v1, v5}, Lorg/xmlpull/v1/XmlSerializer;->startTag(Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    invoke-interface {v0}, Ljava/util/List;->size()I

    move-result v5

    :goto_0
    if-ge v2, v5, :cond_1

    const/4 v1, 0x0

    invoke-interface {v0, v1}, Ljava/util/List;->remove(I)Ljava/lang/Object;

    move-result-object v1

    check-cast v1, Landroid/support/v7/widget/ActivityChooserModel$HistoricalRecord;

    const/4 v6, 0x0

    const-string/jumbo v7, "historical-record"

    invoke-interface {v4, v6, v7}, Lorg/xmlpull/v1/XmlSerializer;->startTag(Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    const/4 v6, 0x0

    const-string/jumbo v7, "activity"

    iget-object v8, v1, Landroid/support/v7/widget/ActivityChooserModel$HistoricalRecord;->activity:Landroid/content/ComponentName;

    invoke-virtual {v8}, Landroid/content/ComponentName;->flattenToString()Ljava/lang/String;

    move-result-object v8

    invoke-interface {v4, v6, v7, v8}, Lorg/xmlpull/v1/XmlSerializer;->attribute(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    const/4 v6, 0x0

    const-string/jumbo v7, "time"

    iget-wide v8, v1, Landroid/support/v7/widget/ActivityChooserModel$HistoricalRecord;->time:J

    invoke-static {v8, v9}, Ljava/lang/String;->valueOf(J)Ljava/lang/String;

    move-result-object v8

    invoke-interface {v4, v6, v7, v8}, Lorg/xmlpull/v1/XmlSerializer;->attribute(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    const/4 v6, 0x0

    const-string/jumbo v7, "weight"

    iget v1, v1, Landroid/support/v7/widget/ActivityChooserModel$HistoricalRecord;->weight:F

    invoke-static {v1}, Ljava/lang/String;->valueOf(F)Ljava/lang/String;

    move-result-object v1

    invoke-interface {v4, v6, v7, v1}, Lorg/xmlpull/v1/XmlSerializer;->attribute(Ljava/lang/String;Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    const/4 v1, 0x0

    const-string/jumbo v6, "historical-record"

    invoke-interface {v4, v1, v6}, Lorg/xmlpull/v1/XmlSerializer;->endTag(Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;
    :try_end_1
    .catch Ljava/lang/IllegalArgumentException; {:try_start_1 .. :try_end_1} :catch_2
    .catch Ljava/lang/IllegalStateException; {:try_start_1 .. :try_end_1} :catch_4
    .catch Ljava/io/IOException; {:try_start_1 .. :try_end_1} :catch_6
    .catchall {:try_start_1 .. :try_end_1} :catchall_0

    add-int/lit8 v1, v2, 0x1

    move v2, v1

    goto :goto_0

    :catch_0
    move-exception v0

    sget-object v0, Landroid/support/v7/widget/ActivityChooserModel;->LOG_TAG:Ljava/lang/String;

    new-instance v0, Ljava/lang/StringBuilder;

    invoke-direct {v0}, Ljava/lang/StringBuilder;-><init>()V

    const-string/jumbo v2, "Error writing historical record file: "

    invoke-virtual {v0, v2}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    invoke-virtual {v0}, Ljava/lang/StringBuilder;->toString()Ljava/lang/String;

    :cond_0
    :goto_1
    return-object v10

    :cond_1
    const/4 v0, 0x0

    :try_start_2
    const-string/jumbo v1, "historical-records"

    invoke-interface {v4, v0, v1}, Lorg/xmlpull/v1/XmlSerializer;->endTag(Ljava/lang/String;Ljava/lang/String;)Lorg/xmlpull/v1/XmlSerializer;

    invoke-interface {v4}, Lorg/xmlpull/v1/XmlSerializer;->endDocument()V
    :try_end_2
    .catch Ljava/lang/IllegalArgumentException; {:try_start_2 .. :try_end_2} :catch_2
    .catch Ljava/lang/IllegalStateException; {:try_start_2 .. :try_end_2} :catch_4
    .catch Ljava/io/IOException; {:try_start_2 .. :try_end_2} :catch_6
    .catchall {:try_start_2 .. :try_end_2} :catchall_0

    iget-object v0, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iput-boolean v11, v0, Landroid/support/v7/widget/ActivityChooserModel;->mCanReadHistoricalData:Z

    if-eqz v3, :cond_0

    :try_start_3
    invoke-virtual {v3}, Ljava/io/FileOutputStream;->close()V
    :try_end_3
    .catch Ljava/io/IOException; {:try_start_3 .. :try_end_3} :catch_1

    goto :goto_1

    :catch_1
    move-exception v0

    goto :goto_1

    :catch_2
    move-exception v0

    :try_start_4
    sget-object v0, Landroid/support/v7/widget/ActivityChooserModel;->LOG_TAG:Ljava/lang/String;

    new-instance v0, Ljava/lang/StringBuilder;

    invoke-direct {v0}, Ljava/lang/StringBuilder;-><init>()V

    const-string/jumbo v1, "Error writing historical record file: "

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    iget-object v1, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iget-object v1, v1, Landroid/support/v7/widget/ActivityChooserModel;->mHistoryFileName:Ljava/lang/String;

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    invoke-virtual {v0}, Ljava/lang/StringBuilder;->toString()Ljava/lang/String;
    :try_end_4
    .catchall {:try_start_4 .. :try_end_4} :catchall_0

    iget-object v0, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iput-boolean v11, v0, Landroid/support/v7/widget/ActivityChooserModel;->mCanReadHistoricalData:Z

    if-eqz v3, :cond_0

    :try_start_5
    invoke-virtual {v3}, Ljava/io/FileOutputStream;->close()V
    :try_end_5
    .catch Ljava/io/IOException; {:try_start_5 .. :try_end_5} :catch_3

    goto :goto_1

    :catch_3
    move-exception v0

    goto :goto_1

    :catch_4
    move-exception v0

    :try_start_6
    sget-object v0, Landroid/support/v7/widget/ActivityChooserModel;->LOG_TAG:Ljava/lang/String;

    new-instance v0, Ljava/lang/StringBuilder;

    invoke-direct {v0}, Ljava/lang/StringBuilder;-><init>()V

    const-string/jumbo v1, "Error writing historical record file: "

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    iget-object v1, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iget-object v1, v1, Landroid/support/v7/widget/ActivityChooserModel;->mHistoryFileName:Ljava/lang/String;

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    invoke-virtual {v0}, Ljava/lang/StringBuilder;->toString()Ljava/lang/String;
    :try_end_6
    .catchall {:try_start_6 .. :try_end_6} :catchall_0

    iget-object v0, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iput-boolean v11, v0, Landroid/support/v7/widget/ActivityChooserModel;->mCanReadHistoricalData:Z

    if-eqz v3, :cond_0

    :try_start_7
    invoke-virtual {v3}, Ljava/io/FileOutputStream;->close()V
    :try_end_7
    .catch Ljava/io/IOException; {:try_start_7 .. :try_end_7} :catch_5

    goto :goto_1

    :catch_5
    move-exception v0

    goto :goto_1

    :catch_6
    move-exception v0

    :try_start_8
    sget-object v0, Landroid/support/v7/widget/ActivityChooserModel;->LOG_TAG:Ljava/lang/String;

    new-instance v0, Ljava/lang/StringBuilder;

    invoke-direct {v0}, Ljava/lang/StringBuilder;-><init>()V

    const-string/jumbo v1, "Error writing historical record file: "

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    iget-object v1, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iget-object v1, v1, Landroid/support/v7/widget/ActivityChooserModel;->mHistoryFileName:Ljava/lang/String;

    invoke-virtual {v0, v1}, Ljava/lang/StringBuilder;->append(Ljava/lang/String;)Ljava/lang/StringBuilder;

    move-result-object v0

    invoke-virtual {v0}, Ljava/lang/StringBuilder;->toString()Ljava/lang/String;
    :try_end_8
    .catchall {:try_start_8 .. :try_end_8} :catchall_0

    iget-object v0, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iput-boolean v11, v0, Landroid/support/v7/widget/ActivityChooserModel;->mCanReadHistoricalData:Z

    if-eqz v3, :cond_0

    :try_start_9
    invoke-virtual {v3}, Ljava/io/FileOutputStream;->close()V
    :try_end_9
    .catch Ljava/io/IOException; {:try_start_9 .. :try_end_9} :catch_7

    goto/16 :goto_1

    :catch_7
    move-exception v0

    goto/16 :goto_1

    :catchall_0
    move-exception v0

    iget-object v1, p0, Landroid/support/v7/widget/ActivityChooserModel$PersistHistoryAsyncTask;->this$0:Landroid/support/v7/widget/ActivityChooserModel;

    iput-boolean v11, v1, Landroid/support/v7/widget/ActivityChooserModel;->mCanReadHistoricalData:Z

    if-eqz v3, :cond_2

    :try_start_a
    invoke-virtual {v3}, Ljava/io/FileOutputStream;->close()V
    :try_end_a
    .catch Ljava/io/IOException; {:try_start_a .. :try_end_a} :catch_8

    :cond_2
    :goto_2
    throw v0

    :catch_8
    move-exception v1

    goto :goto_2
.end method


Q:

Can the minimal index of a subfactor take all values in {4cos^2(pi/n);n=3,4,5,...} u [4,infinity]?

Given a subfactor $N\to M$ and a conditional expectation $E:M\to N$,
there is a numerical invariant $Ind(E)$ associated to to this situation, called the index of $E$.
The possible values of $Ind(E)$ are
restricted to the set {$4\cdot \cos^2(\pi/n);n=3,4,5,...$} $\cup$ $[4,\infty]$.
The minimal conditional expectation is
the one that minimizes the value of $Ind(E)$.
The minimal index of the subfactor is then defined to be the index of its minimal conditional expectation.
Can the minimal index take all values in {$4\cdot \cos^2(\pi/n);n=3,4,5,...$} $\cup$ $[4,\infty]$? In other words, given a real number in the above set, is there a subfactor whose minimal index is that real number?

Remark: If the factors are of type $II_1$, there is another preferred conditional expectation: the one
that is compatible with the traces. The corresponding index is called the Jones index. This is not the index I care about.
Jones' index agrees with the minimal index in the case of irreducible subfactors,
but not in general.
Jones' index is known to take all the above values. But the subfactors used in the construction are not irreducible (and one can also check that their minimal index is different from their Jones index).

A:

There is an irreducible Temperley-Lieb subfactor at every allowed index. For $n\geq 3$, it has index $4\cos^2(\pi/n)$ and principal graph $A_{n-1}$ (in fact all subfactors of index less than $4$ are irreducible), and for every $r\geq 4$, it has index $r$ and principal graph $A_\infty$. Doesn't that do the job by your remark?


Lego: Jurassic World

****

Lego: Jurassic World is the fun we've come to expect from a Lego game. Collecting studs, smashing bricks and playing through stories you already know might sound a bit tedious but the Lego games somehow do it well. You play through the stories of all four Jurassic Park films – it took me about 3 hours to complete the first film – and the game balances referential elements with slightly mocking, tongue-in-cheeks parts.

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Heroes of the Storm

****

Mac, PC (Free-to-play )

Considering League of Legends and Dota borrowed heavily from Warcraft and Starcraft, it's no surprise that Blizzard have produced one of the finest Multiplayer Online Battle Arena (Moba) games yet. Heroes of the Storm pits you and four players against another team of heroes, the main objective being to take down the others' HQ.

Unlike other Moba games, matches are shorter and the interface simpler, meaning players can easily pick it up. Unfortunately, much of the fun is hidden behind a paywall and to get further requires intense grind, enough to put off long-haul players but not those who want quick 20 minute bursts of fantasy action.