Miracle-dz/UniFAR-FTUs huggingface dataset:
A Theory of Strategic Uncertainty and Cultural Diversity

This paper presents a novel mechanism through which culture can affect behavior. Cultural diversity matters because it influences the degree of strategic uncertainty that players face. We model this by building on research in psychology on perspective taking. The model delivers comparative statics that are broadly consistent with experimental evidence and that are difficult to obtain with existing methods. In addition, it can account for a variety of disparate evidence, including why inefficient social customs persist in some societies but not in others and why exclusively targeting incentives may not help with resolving collective action problems. ∗A version of this paper has been circulated under the title “Challenging Conformity: A Case for Diversity. ” Part of the material incorporated here was previously in a paper entitled “A belief-based theory of homophily” by the same authors (Kets and Sandroni, 2015). We are grateful to the Associate Editor and three anonymous referees for excellent suggestions. We thank Larbi Alaoui, Vincent Crawford, Yan Chen, Vessela Daskalova, Wouter Dessein, Matthew Jackson, Wouter Kager, Rachel Kranton, Bart Lipman, George Mailath, Niko Matouschek, Rosemarie Nagel, Santiago Oliveros, Scott Page, Antonio Penta, Nicola Persico, Debraj Ray, Nick Robalino, Yuval Salant, Larry Samuelson, Paul Seabright, Rajiv Sethi, Eran Shmaya, Andy Skrzypacz, Jakub Steiner, Colin Stewart, Jeroen Swinkels, Tymon Tatur, Yiqing Xing, and numerous seminar audiences and conference participants for helpful comments and stimulating discussions. †Department of Economics, University of Oxford. E-mail: willemien.kets@economics.ox. ac.uk. ‡Kellogg School of Management, Northwestern University. E-mail: sandroni@kellogg.northwestern. edu
A Two-Step Disentanglement Method

We address the problem of disentanglement of factors that generate a given data into those that are correlated with the labeling and those that are not. Our solution is simpler than previous solutions and employs adversarial training. First, the part of the data that is correlated with the labels is extracted by training a classifier. Then, the other part is extracted such that it enables the reconstruction of the original data but does not contain label information. The utility of the new method is demonstrated on visual datasets as well as on financial data. Our code is available at https://github.com/naamahadad/A-Two-Step-Disentanglement-Method.
Looking South

Mobile and social technologies are providing new opportunities to document, characterize, and gather impressions of urban environments. In this article, we present a study that examines urban perceptions of three cities in central Mexico; the study integrates a mobile crowdsourcing framework to collect geo-localized images of urban environments by a local youth community, an online crowdsourcing platform to gather impressions of urban environments along 12 physical and psychological dimensions, and a deep learning framework to automatically infer human impressions of outdoor urban scenes. Our study resulted in a collection of 7,000 geo-localized images containing outdoor scenes and views of each city’s built environment, including touristic, historical, and residential neighborhoods, and 144,000 individual judgments from Amazon Mechanical Turk. Statistical analyses show that outdoor environments can be assessed in terms of interrater agreement for most of the urban dimensions by the observers of crowdsourced images. Furthermore, we proposed a methodology to automatically infer human perceptions of outdoor scenes using a variety of low-level image features and generic deep learning (CNN) features. We found that CNN features consistently outperformed all the individual low-level image features for all the studied urban dimensions. We obtained a maximum R2 of 0.49 using CNN features; for 9 out of 12 labels, the obtained R2 values exceeded 0.44.
Breast Cyst Fluid Free Amino Acid Profile Meme Kist

Objective: Gross cystic breast disease (GCBD) is the most common benign breast disease. There are two types of breast cyst; lined by apocrine epithelium (Na/ K<3) or flattened epithelium (Na/K>3). Several studies have shown that women with palpable breast cysts may have 1.7-7.5 times higher risk of developing breast cancer. Patients with malignant disease usually show abnormal amino acid profiles in the peripheral circulation. Changes in amino acid profile diagnostically correlate with organ sites of malignancy. The aim of this study was to investigate the levels of amino acids in two cyst groups and possible mechanisms involved in the development of breast cancer.
A Rank Correlation Coefficient Resistant to Outliers

Abstract In this article, a nonparametric correlation coefficient is defined that is based on the principle of maximum deviations. This new correlation coefficient, Rg , is easy to compute by hand for small to medium sample sizes. In comparing it with existing correlation coefficients, it was found to be superior in a sampling situation that we call “biased outliers,” and hence appears to be more resistant to outliers than the Pearson, Spearman, and Kendall correlation coefficients. In a correlational study not included in this article of some social data consisting of five variables for each of 51 observations, Rg was compared with the other three correlation coefficients. There was agreement on 8 of the 10 possible correlations, but in one case, Rg was significant when the others were not, and in yet another case, Rg was not significant when the others were. A further analysis of this data set indicated that there were three to six data points that were anomalies and had a severe effect on the other cor.
Disentangling Structure and Aesthetics for Style-Aware Image Completion

Content-aware image completion or in-painting is a fundamental tool for the correction of defects or removal of objects in images. We propose a non-parametric in-painting algorithm that enforces both structural and aesthetic (style) consistency within the resulting image. Our contributions are two-fold: 1) we explicitly disentangle image structure and style during patch search and selection to ensure a visually consistent look and feel within the target image. 2) we perform adaptive stylization of patches to conform the aesthetics of selected patches to the target image, so harmonizing the integration of selected patches into the final composition. We show that explicit consideration of visual style during in-painting delivers excellent qualitative and quantitative results across the varied image styles and content, over the Places2 scene photographic dataset and a challenging new in-painting dataset of artwork derived from BAM!
Reinforcement Cutting-Agent Learning for Video Object Segmentation

Video object segmentation is a fundamental yet challenging task in computer vision community. In this paper, we formulate this problem as a Markov Decision Process, where agents are learned to segment object regions under a deep reinforcement learning framework. Essentially, learning agents for segmentation is nontrivial as segmentation is a nearly continuous decision-making process, where the number of the involved agents (pixels or superpixels) and action steps from the seed (super)pixels to the whole object mask might be incredibly huge. To overcome this difficulty, this paper simplifies the learning of segmentation agents to the learning of a cutting-agent, which only has a limited number of action units and can converge in just a few action steps. The basic assumption is that object segmentation mainly relies on the interaction between object regions and their context. Thus, with an optimal object (box) region and context (box) region, we can obtain the desirable segmentation mask through further inference. Based on this assumption, we establish a novel reinforcement cutting-agent learning framework, where the cutting-agent consists of a cutting-policy network and a cutting-execution network. The former learns policies for deciding optimal object-context box pair, while the latter executes the cutting function based on the inferred object-context box pair. With the collaborative interaction between the two networks, our method can achieve the outperforming VOS performance on two public benchmarks, which demonstrates the rationality of our assumption as well as the effectiveness of the proposed learning framework.
Testable Implications of Some Classic Assignment Methods

We study the testable implications of serial dictatorship, stable many-to-one matchings, and the core of housing markets. We show that serial dictatorship is easy to test, and explain how elements of the power ranking between agents can be identified. Stability is also easy to test for an interesting class of many-to-one matching problems, and is tightly related to serial dictatorship. We provide an insightful characterization of the core of Shapley and Scarf (1974)’s housing markets using revealed top-trading cycles. This characterization proves useful in many examples, but is also used to prove that testing the core is generally NP-hard. ∗Department of Economics. Email address: declippel@brown.edu. †Department of Economics. Email address: kareen rozen@brown.edu.
Factors Affecting the Quality of Life in Climacteric Women in Manisa Region Manisa

Objectives: To determine the factors affecting the severity of menopausal symptoms and the quality of life among women living in Manisa, a western city of Turkey. Patients and Methods: After statistical estimation of the sample size reflecting the whole population, 268 climacteric women (mean age 50.7±6.6 years; range 40 to 60 years) with menopausal symptoms were investigated by sociodemographic questionnaire, menopause rating scale (MRS), and Quality of Life Scale (WHOQOL-BREF-TR) in Celal Bayar University Hospital. Results: Almost 1/3 of women had no knowledge on menopause. The MRS scores of women were inversely correlated with Physical Health, Psychological well-being, Social Relationship domains of quality of life. Educational level, menopausal knowledge, participation in decision-making in the family and economic status positively affected most domains of quality of life, whereas being married and having high BMI scores had negative effects. Conclusion: In climacteric women, quality of life was negatively affected by the severity of menopausal symptoms, low education level, limited menopausal knowledge, and being overweight.
GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition

3D shape recognition has attracted much attention recently. Its recent advances advocate the usage of deep features and achieve the state-of-the-art performance. However, existing deep features for 3D shape recognition are restricted to a view-to-shape setting, which learns the shape descriptor from the view-level feature directly. Despite the exciting progress on view-based 3D shape description, the intrinsic hierarchical correlation and discriminability among views have not been well exploited, which is important for 3D shape representation. To tackle this issue, in this paper, we propose a group-view convolutional neural network (GVCNN) framework for hierarchical correlation modeling towards discriminative 3D shape description. The proposed GVCNN framework is composed of a hierarchical view-group-shape architecture, i.e., from the view level, the group level and the shape level, which are organized using a grouping strategy. Concretely, we first use an expanded CNN to extract a view level descriptor. Then, a grouping module is introduced to estimate the content discrimination of each view, based on which all views can be splitted into different groups according to their discriminative level. A group level description can be further generated by pooling from view descriptors. Finally, all group level descriptors are combined into the shape level descriptor according to their discriminative weights. Experimental results and comparison with state-of-the-art methods show that our proposed GVCNN method can achieve a significant performance gain on both the 3D shape classification and retrieval tasks.
Behavior of Extended EndPlate Steel Beam to Column Connections

This paper presents the investigations of extended End-Plate connections (EP). A one-model segment is examined under the impact of concentrated load and the exclusive boundary conditions were tested. The analysis of the nonlinear behaviour of the connection is a complicated science and needs to use programs to solve this problem. Experimental works are normally conducted for this type of studies which used more of money, time and effort. Therefore, with the availability of simulation applications, these problems can be addressed.
Validating Rainfall-Runoff Modelling Using Satellite-Based and Reanalysis Precipitation Products in the Sre Pok Catchment, the Mekong River Basin

The limitation in quantity and quality of climate data, in particular rainfall measurements, directly affects the reliability of hydrological models, which negatively impacts on the quality of water resources planning and management. This is obviously true in poorly-gauged or in transboundary river catchments with limited practice of data sharing among the riparian states. Satellite-based and reanalysis rainfall products are increasingly recognised as a promising information source to supplement ground observations. This research aims to study the feasibility of using satellite-based and reanalysis rainfall data for rainfall-runoff modelling in the Sre Pok catchment-a poorly gauged catchment located in Vietnam and Cambodia. First, three selected rainfall products (Tropical Rainfall Measuring Mission-TRMM, CPC MORPHing Technique-CMORPH, and European Reanalysis-ERA-Interim) were compared against ground rainfall data of 13 rain-gauges, located inside and in the vicinity of the study catchment. The validation results show that the studied global datasets have a reasonably good correlation with ground observation at monthly time scale (NSE = 0.3 to 0.8, R2 = 0.4 to 0.8), but relatively poor correlation at daily scale (NSE = −0.4 to 0.3, R2 = 0.1 to 0.4). Next, a semi-distributed rainfall-runoff model based on HBV-Light was developed to validate these datasets in the Krong Ana sub-catchment of the Sre Pok. The results illustrate satisfactory to very good model performances at monthly time scale for the satellite-based and reanalysis rainfall inputs (NSE = 0.58 to 0.77, R2 = 0.59 to 0.78 for the calibration period from 2004 to 2007, while NSE = 0.59 to 0.80, R2 = 0.64 to 0.84 for the validation period from 2008 to 2010). However, only TRMM and ERA-Interim give acceptable results at daily scale with NSE = 0.52 to 0.67, R2 = 0.53 to 0.67 for the calibration period, and NSE = 0.41 to 0.61, R2 = 0.45 to 0.65 for the validation period. The study concludes that the tested satellite-based and reanalysis rainfall products, especially TRMM and ERA-Interim, could mimic reasonably well the monthly rainfall pattern in the study region. It also demonstrates a great opportunity to use satellite-based and reanalysis rainfall for runoff modelling at monthly time scale in the Sre Pok catchment and other poorly-gauged (transboundary) catchments in the region, for example in the Mekong and Red River Basins.
Some Aspects of Turbulent Mixing of Jets in the Marine Environment

Prominent among environmental problems is the pollution of the coastal marine zone as a result of anthropogenic activities. On this point, while studies of jets in still water and in crossflows have been developed in many research centres, studies on jets interacting with waves are still rare. The present study analyses turbulent, non-buoyant water jets issued into a wave environment. A comparison of the time-averaged and phase-averaged velocity components has been carried out, in order to highlight the flow patterns in the two configurations. The experimental data have also been compared with others in the literature, such as the relationship between the dimensionless, longitudinal, time-averaged velocities of the jet mean axis and the distance from the source. Such comparisons reveal a good agreement. Furthermore, using the analogy between the equation of the turbulent transport of a solute concentration and the equation of the turbulent kinetic energy, the paper presents also estimates of the turbulence diffusion coefficients and advection terms of jets in a wave environment. The experimental results are compared with jets in still water. With the presence of waves, the turbulence length-scales in the streamwise direction vary, contributing to an increase in streamwise turbulent diffusion, relative to the condition of the same jet in still water. The analysis of the jet streamwise advection term reveals that it increases in the case of jets in a wave environment, as compared to no-wave conditions.
Overcoming Barriers and Increasing Independence – Service Robots for Elderly and Disabled People

The paper discusses the potential of assistive service robots to support disabled and elderly people. It shows that they have considerable untapped potential in this area, but also that inappropriate implementations could increase isolation, reduce independence and lead to users feeling as though they are under surveillance. The main body of the paper presents an overview of existing applications and discusses their benefits and potential problems. This is organized by an extension of the common classification into socially and physically assistive robots by the two categories of sensory assistive and mixed assistance robots. Another more detailed classification is also presented. This discussion is introduced by an overview of many of the technological components of smart mobile robots. It is followed by a discussion of user acceptance. The problems of existing models based on either solely positive or solely negative factors are noted and a model containing both types of factors is proposed. The need for continuing research is noted and various proposals are made.
A Novel Multislope MUSCL Scheme for Solving 2D Shallow Water Equations on Unstructured Grids

Within the framework of the two-dimensional cell-centered Godunov-type finite volume (CCFV) method, this paper presents a novel multislope scheme on the basis of the monotone upstream scheme for conservation law (MUSCL) for numerically solving nonlinear shallow water equations on two-dimensional triangular grids. The Riemann states of the considered edge are calculated by an edge-based reconstructing procedure, where a limited scalar slope is employed to prevent potential numerical oscillations. The novel aspect of the new scheme is that it takes advantage of the geometrical characteristics of triangular grids in the reconstructing and limiting procedures, which effectively reduces the cost of computation and provides higher resolution and accuracy compared with classical MUSCL schemes. Seven tests are adopted to verify the scheme, and the results indicate that this scheme is efficient, accurate, robust, and high-resolution, and can be an ideal alternative for solving shallow water problems over uneven and frictional topography.
The Association of Hypertension and C 825 T Polymorphism of the Gene Encoding the G-protein Beta-3 subunit ( GNB 3 ) in a Group of Turkish Hypertensive Patients

100 Amaç: G proteini beta-3 (β3) altbirimini (GNB3) kodlayan genin C825T polimorfizmi G proteinleri yoluyla sinyal iletiminde artışla ve sonuçta artmış Na+/H+ değiştiricisinin aktivitesi ile ilişkilidir. Bu iyon taşıma sistemi proksimal tübülden sodyum geri emilimine aracılık eder. Değişik nüfuslardan hipertansif hastaların hücrelerinde Na+/H+ değiştiricisinin aktivitesinde artış bulunmuştur. Bu çalışmada hipertansiyonlu Türk hasta grubunda bu polimorfizm araştırıldı ve normotansif bireylerle karşılaştırıldı. Hastalar ve Yöntemler: Doksan dokuz hipertansif hasta (57 erkek, 42 kadın) ve 45 normotansif kontrolde (33 erkek, 12 kadın) GNB3 C825T polimorfizmi için genotipleme yapıldı. Bulgular: Hasta ve kontrol gruplarında alel dağılımı sırasıyla CC:35, CT:51, TT:13 ve CC:26, CT:15, TT:4 şeklindeydi. T aleli taşıyıcıları (CT ve TT) hipertansiyonlu grupta anlamlı şekilde daha yüksekti. Hipertansiyon ve C825T aleli arasında istatistiksel bakımdan anlamlı ilişki (Ki-kare testi, p=0.041) bulundu. Sonuç: Bu bulgular Türk hastalarda hipertansiyon ve GNB3 polimorfizminin ilişkili olduğunu ve artmış G proteini aktivitesinin C825T ile hipertansiyon arasındaki patofizyolojik bağlantı olabileceğini düşündürmektedir. Anahtar Sözcükler: Hipertansiyon; polimorfizm; GNB3; G proteini; C825T. The Association of Hypertension and C825T Polymorphism of the Gene Encoding the G-protein Beta-3 subunit (GNB3) in a Group of Turkish Hypertensive Patients[*]
The Recurrence of Cholera in the City of Lubumbashi: Investigation of Risk Factors for an Effective Response and Health Education Perspective

Introduction: Cholera is one of the so-called dirty hand diseases. Its effective response saves lives. The city of Lubumbashi has recorded at least one cholera epidemic for almost ten years, each of which generates significant socio-economic costs. Method: We conducted a case-control study on cholera in the city of Lubumbashi in the Democratic Republic of Congo in 330 individuals, including 110 cases matched to 220 controls. The linear list of the cholera treatment center was used to identify the cases. Results: Half of the respondents were 50, 30% did not treat water before drinking, and the remaining 49.70% used the treatment of drinking water. The risk factors for the cholera outbreak that were found to be statistically significant include: poor food preservation (AOR = 3.32, 95% CI [1.85 - 5.96], and p value = 0.0001), contact with a cholera patient (AOR = 2.88, 95% CI [1.65 - 5.01], and p value = 0.0002) and stay outside Lubumbashi (AOR = 4.18, its 95% CI [1.83 - 9.55]). Conclusion: An urgent need for information on risk factors for cholera and a rapid organization of the response is the key to cope with this recurrent epidemic in the city of Lubumbashi.
The Mediterranean Moisture Contribution to Climatological and Extreme Monthly Continental Precipitation

Moisture transport from its sources to surrounding continents is one of the most relevant topics in hydrology, and its role in extreme events is crucial for understanding several processes such as intense precipitation and flooding. In this study, we considered the Mediterranean Sea as the main water source and estimated its contribution to the monthly climatological and extreme precipitation events over the surrounding continental areas. To assess the effect of the Mediterranean Sea on precipitation, we used the Multi-Source Weighted-Ensemble Precipitation (MSWEP) database to characterize precipitation. The Lagrangian dispersion model known as FLEXPART was used to estimate the moisture contribution of this source. This contribution was estimated by tracking particles that leave the Mediterranean basin monthly and then calculating water loss (E − P < 0) over the continental region, which was modelled by FLEXPART. The analysis was conducted using data from 1980 to 2015 with a spatial resolution of 0.25°. The results showed that, in general, the spatial pattern of the Mediterranean source’s contribution to precipitation, unlike climatology, is similar during extreme precipitation years in the regions under study. However, while the Mediterranean Sea is usually not an important source of climatological precipitation for some European regions, it is a significant source during extreme precipitation years.