nils-herrmann/clean_scirepeval huggingface dataset:
Health related quality of life and its association with medication adherence in active pulmonary tuberculosis a systematic review of global literature with focus on South Africa
Venue: Health and Quality of Life Outcomes

IntroductionTuberculosis (TB) is a leading cause of morbidity and mortality in South Africa. Clinical parameters are important objective outcomes in TB; however they often are not directly correlated with subjective well being of the patient, but can be assessed using patient reported outcome (PRO) measures. Health related quality of life (HRQOL) is a specific PRO generally multi dimensional in nature and includes physical, mental and social health domains. The inclusion of HRQOL PROs in trials and clinical practice can provide additional information beyondclinical and microbiological parameters. Furthermore, HRQOL may be associated with medication adherence. This review focuses on patient reported HRQOL and its association with medication adherence in TB patients in South Africa.MethodsA comprehensive search strategy was developed focusing on the impact of TB on patient reported HRQOL,the existence of a conceptual framework of TB specific HRQOL, determinants of medication adherence and the association of HRQOL with medication adherence. Data were extracted from all identified articles and additionaldata extraction was performed by two independent reviewers with special focus on longitudinal studies in order to understand changes of HRQOL and adherence over time. Research gaps were identified with regard to patient reported HRQOL and medication adherence. total of 66 articles met the eligibility criteria. Ten HRQOL studies and one adherence study used a longitudinal design, none of these in South Africa. A variety of different generic and disease specific HRQOL measures were identified in the articles. In South Africa four HRQOL and five adherence studies (non longitudinal) were published. Similar factors (socio demographic, socio economic, disease related, therapy related and psycho social aspects) affect HRQOL and adherence. Although standard TB treatment improved all health domains, psychological well being and social functioning remained impaired in microbiologically cured patients after treatment.ConclusionWhile evidence of TB impact on HRQOL and medication adherence and their association exists, it is verylimited for the South African situation. No valid and reliable TB specific HRQOL measures were identified in this systematicreview. An assessment of HRQOL in TB patients in South Africa is required as this may assist with improving current disease management programmes, medication adherence and national treatment guidelines.
Machines Learning Justice: A New Approach to the Problems of Inconsistency and Bias in Adjudication

We offer a two step algorithmic approach to the problems of inconsistency and bias in legal decision making. First, we propose a new tool for reducing inconsistency: Judgmental Bootstrapping Models "JBMs" built with machine learning methods. JBMs, by providing judges with recommendations generated from statistical models of themselves, can help those judges make better and more consistent decisions. To illustrate these advantages, we build a JBM of release decisions for the California Board of Parole Hearings. Second, we describe a means to address systematic biases that are embedded in an algorithm (e.g. disparate racial treatment) We argue for making direct changes to algorithmic output based on explicit estimates of bias. Most commentators concerned with embedded biases have focused on constructing algorithms without the use of bias inducing variables. Given the complex ways that variables may correlate and interact, that approach is both practically difficult and harmful to predictive power. In contrast, our two step approach can address bias without sacrificing performance.
Synthetic Crowdsourcing: A Machine Learning Approach to Inconsistency in Adjudication

This paper presents a novel algorithmic approach to the problems of inconsistency and bias in legal decision making. First, we propose a new tool for reducing inconsistency: "Synthetic Crowdsourcing Models" "SCMs" built with machine learning methods. By providing judges with recommendations generated from statistical models of themselves, such models can help those judges make better and more consistent decisions. To illustrate these advantages, we build an SCM of release decisions for the California Board of Parole Hearings. Second, we describe a means to address systematic biases that are embedded in an algorithm (e.g. disparate racial treatment) We argue for making direct changes to algorithmic output based on explicit estimates of bias. Most commentators concerned with embedded biases have focused on constructing algorithms without the use of bias inducing variables. Given the complex ways that variables may correlate and interact, that approach is both practically difficult and harmful to predictive power. In contrast, our two step approach can address bias with minimal sacrifice of predictive performance.
The Impacts of Droughts in Tropical Forests.
Venue: Trends in plant science

Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other vegetation type and, thus, form a crucial component of the global carbon cycle. However, the impacts of anthropogenic climate change on drought occurrence and intensity could weaken the tropical forest carbon sink, with resulting feedback to future climates. We urgently need a better understanding of the mechanisms and processes involved to predict future responses of tropical forest carbon sequestration to climate change. Recent progress has been made in the study of drought responses at the molecular, cellular, organ, individual, species, community, and landscape levels. Although understanding of the mechanisms is incomplete, the models used to predict drought impacts could be significantly improved by incorporating existing knowledge.
Set valued and interval valued stationary time series
Venue: J. Multivar. Anal.

Stationarity is a key tool in classical time series. In order to analyze the set valued time series, it must be extended to the set valued case. In this paper, stationary set valued time series is defined via D p ?metric of set valued random variables. Then, estimation methods of expectation and auto covariance function of stationary set valued time series are proposed. Unbiasedness and consistency of the expectation estimator and asymptotic unbiasedness of the auto covariance function estimator are justified. After that, a special case of the set valued time series, known as interval valued time series, is considered. Two forecast methods of the stationary interval valued time series are explicitly presented. Furthermore, the interval valued time series is contextualized in the Box Jenkins framework: an interval valued autoregression model, along with its parameter estimation method, is introduced. Finally, experiments on both simulated and real data are presented to justify the efficiency of the parameters estimation method and the availability of the proposed model.
Targeting the stem cell niche with regenerative biomaterials

Regenerative medicine aims to restore form and function to aged, injured, and diseased tissues. One strategy that is gaining traction is in vivo regenerative medicine. Many adult tissues possess stem and progenitor cells that are enlisted to repair minor tissue damage after insult. However, in the setting of disease, aging, or criticalsized injuries, the microenvironment may lack structural elements, physical, and/or chemical cues required to drive repair to completion. Natural and synthetic materials offer an opportunity to facilitate the repair process by restoring the natural reparative capacity of adult tissues. Using design criteria selected based upon an understanding of the inductive niche cues that naturally instruct stem and progenitor cell behavior and fate, it is possible to elicit tissue repair by implementing a cell free approach. This review highlights recent studies that assess biomaterials for in vivo regenerative medicine applications and demonstrate a capacity for controlling stem and progenitor cell behavior to restore tissue form and function.
Genetic diversity in fragmented populations of Populus talassica inferred from microsatellites: implications for conservation.
Venue: Genetics and molecular research GMR

Populus talassica Kom. is an ecologically important species endemic to central Asia. In China, its main distribution is restricted to the Ili region in the Xinjiang Autonomous Region. An understanding of genetic diversity and population structure is crucial for the development of a feasible conservation strategy. Twenty six high level simple sequence repeat (SSR) markers were screened and used to genotype 220 individuals from three native populations. A high level of genetic diversity and low population differentiation were revealed. We identified 163 alleles, with a mean of 6.269 alleles per locus. The observed and expected heterozygosities ranged from 0.472 to 0.485 (with a mean of 0.477) and from 0.548 to 0.591 (mean 0.569) respectively. Analysis of molecular variance revealed 93% variation within populations and 7% among populations. A model based population structure analysis divided P. talassica into two groups (optimal K 2) These genetic data provide crucial insight for conservation management.
European growth models and working class restructuring: An International post Keynesian Political Economy perspective

This paper builds on post Keynesian macroeconomics, the French Regulation Theory and a Neo Gramscian International Political Economy approach to class analysis to propose an International post Keynesian Political Economy approach that is used to offer an empirical analysis of European growth models and working class restructuring in Europe between 2000 and 2008. We will distinguish between the 'East' the 'North' and the 'South' and structure our analysis around industrial upgrading, financialisation and working class coherence. We find an export driven growth model in the North, which came with wage suppression and outsourcing to the East. In the East, the growth model can be characterised as dependent upgrading, which allowed for high real wage growth despite declining working class coherence. The South experienced a debt driven growth model with a real estate bubble and high inflation rates resulting in large current account deficits. Our analysis shows that class restructuring forms an integral part in the economic process that resulted in European imbalances and the Euro crisis.
Underground object characterization based on neural networks for ground penetrating radar data
Venue: SPIE Smart Structures and Materials Nondestructive Evaluation and Health Monitoring

In this paper, an object characterization method based on neural networks is developed for GPR subsurface imaging. Currently, most existing studies demonstrate detecting and imaging objects of cylindrical shapes. While in this paper, no restriction is imposed on the object shape. Three neural network algorithms are exploited to characterize different types of object signatures, including object shape, object material, object size, object depth and subsurface medium's dielectric constant. Feature extraction is performed to characterize the instantaneous amplitude and time delay of the reflection signal from the object. The characterization method is evaluated utilizing the data synthesized with the finite difference timedomain (FDTD) simulator.
Impact of 5 HTTLPR on SSRI serotonin transporter blockade during emotion regulation: A preliminary fMRI study.
Venue: Journal of affective disorders

The short 'S' allele of the serotonin transporter (5 HTT) linked polymorphic region (5 HTTLPR) is associated with increased negative emotion processing bias, and this polymorphism moderates acute effects of selective serotonin reuptake inhibitor (SSRI) treatment. In this preliminary study, we explore the moderating effect of 5 HTTLPR on the impact of the SSRI, escitalopram during emotion regulation of negative emotional stimuli.  Thirty six healthy Caucasian, female participants underwent two fMRI scanning sessions following single dose escitalopram and placebo administration separated by a seven day washout period according to a double blind, randomized, placebo controlled crossover design. Functional connectivity analysis was employed with a left (L) amygdala seed and a right interior frontal gyrus (R IFG) target.  Changes in functional connectivity with emotion regulation and treatment were linearly related to 5 HTTLPR 'L' allele load such that negative R IFG L amygdala connectivity was increased with an increasing number of 'L' alleles. Therefore, escitalopram may facilitate the effects of reappraisal by enhancing negative functional connectivity, a finding that is greatest in participants homozygous for the 'L' allele and least in those homozygous for the 'S' allele.  Sub samples of the homozygote 'S/S' and 'L/L' 5 HTTLPR groupings were small. However, the within subjects nature of the experiment and observing changes at the individual subject level increases our confidence in the findings of the present study.  The present study elucidates a potential neural mechanism by which antidepressant treatment produces differential treatment outcomes dependent on the 5 HTTLPR polymorphism, providing new and important leads for models of antidepressant action.
Face and emotion expression processing and the serotonin transporter polymorphism 5 HTTLPR/rs22531
Venue: Genes, brain, and behavior

Face cognition, including face identity and facial expression processing, is a crucial component of socio emotional abilities, characterizing humans as highest developed social beings. However, for these trait domains molecular genetic studies investigating gene behavior associations based on well founded phenotype definitions are still rare. We examined the relationship between 5 HTTLPR/rs25531 polymorphisms related to serotonin reuptake and the ability to perceive and recognize faces and emotional expressions in human faces. For this aim we conducted structural equation modeling on data from 230 young adults, obtained by using a comprehensive, multivariate task battery with maximal effort tasks. By additionally modeling fluid intelligence and immediate and delayed memory factors, we aimed to address the discriminant relationships of the 5 HTTLPR/rs25531 polymorphisms with socio emotional abilities. We found a robust association between the 5 HTTLPR/rs25531 polymorphism and facial emotion perception. Carriers of two long (L) alleles outperformed carriers of one or two S alleles. Weaker associations were present for face identity perception and memory for emotional facial expressions. There was no association between the 5 HTTLPR/rs25531 polymorphism and non social abilities, demonstrating discriminant validity of the relationships. We discuss the implications and possible neural mechanisms underlying these novel findings.
Serotonin Promoter Polymorphism (5 HTTLPR) Predicts Biased Attention for Emotion Stimuli
Venue: Clinical psychological science a journal of the Association for Psychological Science

A number of studies have found an association between attentional bias for negative stimuli and variation in the serotonin transporter promoter region polymorphism (5 HTTLPR) The current project examined whether a positive social environment mitigates this association. More specifically, we examined the relationship among attentional bias on the dot probe task, variation in the 5 HTTLPR, and current social support among a community sample of adults (N 216) Consistent with prior research, the S/LG homozygotes were more likely than the other genotype groups to have a negative attention bias. However, social support moderated the association between 5 HTTLPR variation and attentional bias. The S/LG homozygote group was particularly likely to exhibit greater attentional bias toward negative stimuli at low levels of social support. However, as social support improved, negative attention bias decreased. Findings suggest that supportive environments may attenuate genetic associations with negative attention bias.
Multivariate Trace Inequalities
Venue: ArXiv

We prove several trace inequalities that extend the Golden Thompson and the Araki Lieb Thirring inequality to arbitrarily many matrices. In particular, we strengthen Lieb's triple matrix inequality. As an example application of our four matrix extension of the Golden Thompson inequality, we prove remainder terms for the monotonicity of the quantum relative entropy and strong sub additivity of the von Neumann entropy in terms of recoverability. We find the first explicit remainder terms that are tight in the commutative case. Our proofs rely on complex interpolation theory as well as asymptotic spectral pinching, providing a transparent approach to treat generic multivariate trace inequalities.
The Determinants of Capital Structure Evidence from China

This paper investigates the determinants of capital structure using a cross section sample of 1481 non financial firms listed on the Chinese stock exchanges in 2011.  Employing four leverage measures (total leverage and long term leverage in terms of both book value and market value, respectively) this study examines the effects of factors with proven influences on capital structure in literature, along with industry effect and ownership effect.  We find that large firms favour debt financing while profitable firms rely more on internal capital accumulation. Intangibility and business risk increase the level of debt financing but tax has little impact on capital structure. We also observe strong industrial effect and ownership effect. Real estate firms borrow considerably more and firms from utility and manufacturing industries use more long term debt despite Chinese firms generally employ significantly more short term debt. On the other hand, firms with state ownership tend to borrow more, while firms with foreign ownership choose more equity financing.  These results may provide important implications to investors in making investment decision and to firms in making financing decisions.  this paper uses by far the largest and latest sample from the Chinese stock markets, offering the most complete picture of the financing behaviours in the Chinese firms, with known characters and the impact of ownerships.
Austerity and niche parties: The electoral consequences of fiscal reforms

Austerity policies policies of sharp reductions of a government's budget deficint involving spending cuts and tax increases are claimed to boost support for radical political parties. We argue, counter to popular claims, that austerity measures actually reduce support for radical and niche parties. Austerity policies force traditional left right politics to the forefront of political debate with the traditional mainstream parties having a stronger ownership over those issues. We systematically explore the impact of austerity measures on the electoral fortunes of niche parties in 16 developed countries over a 35 year period, while controlling for a number of socio economic variables. We find that austerity policies that rely on tax increases affect radical parties on the left and the right in different ways than fiscal adjustments based on spending cuts.
Use of Archetypal Structures in Urban Dynamics

The paper demonstrates the use of systems archetypes as a practical method to understand the impact of urban policies and programs on urban dynamics. Systems archetypes are generic templates to represent the structural and behavioral insights in dynamic systems. They highlight counterintuitive behavior of social systems and the recursive nature of complex systems. This paper maps systems archetypes pertaining to the failures in urban programs, as described by Prof. J.W. Forrester in his classic book Urban Dynamics. 'Fixes that backfire' is a systems archetype that construes a situation where a fix effective in a short term creates long term behavioral side effects which might need even more fixes. This archetype is mapped onto the failures in urban programs. The insights to the reasons of failures of urban programs through the systems archetypes lens will enable us bring a change in the society and assist policy makers by being cautious of the unintended consequences while devising urban policies. Therefore, an approach has been proposed to deal with urban change by applying archetypal structures to urban problems. The approach illustrated in this paper will enable urban governors and planners, distinguish programs and policies that may or may not lead to desired dynamics.
Effects of different seat cushions on interface pressure distribution: a pilot study
Venue: Journal of physical therapy science

The purpose of this study was to evaluate pressure redistribution on the supporting area of healthy volunteers when using different cushions.  Twenty healthy individuals ranging in age from 19 23 years old and 20 older adults age 60 or above participated in the study. All participants lived in urban communities in South Korea. Group differences according to gender, age, and cushion types were analyzed with one way analysis of variance and post hoc analysis.  Statistically significant differences in peak pressure and mean pressure were identified between age, gender, and cushion types. Peak pressure and mean pressure were higher on firm surfaces and on the air cushion than other cushion types. The pressure ratio was lower when an air cushion was used in the buttock area and was higher when it was used under the thighs compared to that in other conditions.  This study showed that interface pressure can be distributed differently depending on what cushions are used. Therefore, when using seat cushions, individuals should seek advice to help them choose the appropriate cushion for their needs.
School Belonging, Ethnic Identity, and Psychological Adjustment Among Ethnic Minority College Students

This study considers how the psychological adjustment of ethnic minority college students may be linked to a sense of school belonging and ethnic identity, two constructs related to individuals feeling like they belong to a larger group. Using self reports from 311 undergraduates from ethnic minority backgrounds, school belonging was found to be negatively associated with depressive symptoms, and positively associated with perceived self worth, scholastic competence, and social acceptance, while ethnic identity was only found to be positively associated with self worth. Furthermore, the interaction between ethnic identity and school belonging was significantly associated with self worth, suggesting that in the absence of a sense of belonging at school, stronger ethnic identity was linked to higher self worth. College students reported the lowest levels of self worth when they were neither connected to their college nor connected to their ethnic group.
Leakage Abuse Attacks Against Searchable Encryption
Venue: IACR Cryptol. ePrint Arch.

Schemes for secure outsourcing of client data with search capability are being increasingly marketed and deployed. In the literature, schemes for accomplishing this efficiently are called Searchable Encryption (SE) They achieve high efficiency with provable security by means of a quantifiable leakage profile. However, the degree to which SE leakage can be exploited by an adversary is not well understood. To address this, we present a characterization of the leakage profiles of in the wild searchable encryption products and SE schemes in the literature, and present attack models based on an adversarial server's prior knowledge. Then we empirically investigate the security of searchable encryption by providing query recovery and plaintext recovery attacks that exploit these leakage profiles. We term these leakage abuse attacks and demonstrate their effectiveness for varying leakage profiles and levels of server knowledge, for realistic scenarios. Amongst our contributions are realistic active attacks which have not been previously explored.