Miracle-dz/UniFAR-FTUs huggingface dataset:
CogniCrypt: Supporting developers in using cryptography

Previous research suggests that developers often struggle using low-level cryptographic APIs and, as a result, produce insecure code. When asked, developers desire, among other things, more tool support to help them use such APIs. In this paper, we present CogniCrypt, a tool that supports developers with the use of cryptographic APIs. CogniCrypt assists the developer in two ways. First, for a number of common cryptographic tasks, CogniCrypt generates code that implements the respective task in a secure manner. Currently, CogniCrypt supports tasks such as data encryption, communication over secure channels, and long-term archiving. Second, CogniCrypt continuously runs static analyses in the background to ensure a secure integration of the generated code into the developer's workspace. This video demo showcases the main features of CogniCrypt: youtube.com/watch? v=JUq5mRHfAWY.
Evolutionary Model Discovery of Factors for Farm Selection by the Artificial Anasazi

Agent-based modeling has been criticized for its apparent lack of establishing causality of social phenomena. However, we demonstrate that when coupled with evolutionary computation techniques, agent-based models can be used to evolve plausible agent behaviors that are able to recreate patterns observed in real-world data, from which valuable insights into candidate explanations of the macro-phenomenon can be drawn. Existing methodologies have suggested the manual assembly and comparison or automated selection of pre-built models on their ability to fit patterns in data. We discuss the cons of existing manual approaches and how evolutionary model discovery, an evolutionary approach to explore the space of agent behaviors for plausible rule-sets, can overcome these issues. We couple evolutionary model discovery with concepts from the Agent\_Zero framework, ensuring social connectivity, emotional theory components and rational mechanisms. In this study, we revisit the farm-seeking strategy of the Artificial Anasazi model, originally designed to simply select the closest potential farm plot as their next farming location. We use evolutionary model discovery to explore plausible farm seeking strategies, extending our previous study by testing four social connectivity strategies, four emotional theory components and five rational mechanisms for a more complex human-like approach towards farm plot selection. Our results confirm that, plot quality, dryness and community presence were more important in the farm selection process of the Anasazi than distance, and discover farm selection strategies that generate simulations that produce a closer fit to the archaeological data.
Cross‐Species Transcriptome Profiling Identifies New Alveolar Epithelial Type I Cell‐Specific Genes

&NA; Diseases involving the distal lung alveolar epithelium include chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung adenocarcinoma. Accurate labeling of specific cell types is critical for determining the contribution of each to the pathogenesis of these diseases. The distal lung alveolar epithelium is composed of two cell types, alveolar epithelial type 1 (AT1) and type 2 (AT2) cells. Although cell type‐specific markers, most prominently surfactant protein C, have allowed detailed lineage tracing studies of AT2 cell differentiation and the cells' roles in disease, studies of AT1 cells have been hampered by a lack of genes with expression unique to AT1 cells. In this study, we performed genome‐wide expression profiling of multiple rat organs together with purified rat AT2, AT1, and in vitro differentiated AT1‐like cells, resulting in the identification of 54 candidate AT1 cell markers. Cross‐referencing with genes up‐regulated in human in vitro differentiated AT1‐like cells narrowed the potential list to 18 candidate genes. Testing the top four candidate genes at RNA and protein levels revealed GRAM domain 2 (GRAMD2), a protein of unknown function, as highly specific to AT1 cells. RNA sequencing (RNAseq) confirmed that GRAMD2 is transcriptionally silent in human AT2 cells. Immunofluorescence verified that GRAMD2 expression is restricted to the plasma membrane of AT1 cells and is not expressed in bronchial epithelial cells, whereas reverse transcription‐polymerase chain reaction confirmed that it is not expressed in endothelial cells. Using GRAMD2 as a new AT1 cell‐specific gene will enhance AT1 cell isolation, the investigation of alveolar epithelial cell differentiation potential, and the contribution of AT1 cells to distal lung diseases.
Learning Parametric Closed-Loop Policies for Markov Potential Games

Multiagent systems where the agents interact among themselves and with an stochastic environment can be formalized as stochastic games. We study a subclass, named Markov potential games (MPGs), that appear often in economic and engineering applications when the agents share some common resource. We consider MPGs with continuous state-action variables, coupled constraints and nonconvex rewards. Previous analysis are only valid for very simple cases (convex rewards, invertible dynamics, and no coupled constraints); or considered deterministic dynamics and provided open-loop (OL) analysis, studying strategies that consist in predefined action sequences. We present a closed-loop (CL) analysis for MPGs and consider parametric policies that depend on the current state and where agents adapt to stochastic transitions. We provide verifiable, sufficient and necessary conditions for a stochastic game to be an MPG, even for complex parametric functions (e.g., deep neural networks); and show that a CL Nash equilibrium (NE) can be found (or at least approximated) by solving a related optimal control problem (OCP). This is useful since solving an OCP---a single-objective problem---is usually much simpler than solving the original set of coupled OCPs that form the game---a multiobjective control problem. This is a considerable improvement over previously standard approach. We illustrate the theoretical contributions with an example by applying our approach to a noncooperative communications engineering game. We then solve the game with a deep reinforcement learning algorithm that learns policies that closely approximates an exact variational NE of the game.
Effectiveness of red blood cell exchange, partial manual exchange, and simple transfusion concurrently with iron chelation therapy in reducing iron overload in chronically transfused sickle cell anemia patients

Chronic transfusion therapy (CTT) is indicated for stroke prevention in children with sickle cell anemia (SCA) and is complicated by iron overload and alloimmunization. CTT is performed by simple transfusion (ST), partial manual exchange (PME), or erythrocytapheresis (RCE). Although small case series have demonstrated RCE in combination with iron chelation therapy stabilizes and/or decreases ferritin, there are no reports comparing the effect of ST, PME, and RCE on liver iron concentration (LIC). CTT modality effect on serum ferritin and LIC were compared in SCA patients on iron chelation, with hemoglobin (Hb)S goal of 30%.
Socioeconomic Outcomes of Women Who Receive and Women Who Are Denied Wanted Abortions in the United States

Objectives To determine the socioeconomic consequences of receipt versus denial of abortion. Methods Women who presented for abortion just before or after the gestational age limit of 30 abortion facilities across the United States between 2008 and 2010 were recruited and followed for 5 years via semiannual telephone interviews. Using mixed effects models, we evaluated socioeconomic outcomes for 813 women by receipt or denial of abortion care. Results In analyses that adjusted for the few baseline differences, women denied abortions who gave birth had higher odds of poverty 6 months after denial (adjusted odds ratio [AOR] = 3.77; P < .001) than did women who received abortions; women denied abortions were also more likely to be in poverty for 4 years after denial of abortion. Six months after denial of abortion, women were less likely to be employed full time (AOR = 0.37; P = .001) and were more likely to receive public assistance (AOR = 6.26; P < .001) than were women who obtained abortions, differences that remained significant for 4 years. Conclusions Women denied an abortion were more likely than were women who received an abortion to experience economic hardship and insecurity lasting years. Laws that restrict access to abortion may result in worsened economic outcomes for women.
How to tell a patient’s story? Influence of the case narrative design on the clinical reasoning process in virtual patients

Abstract Background: Virtual patients (VPs) are narrative-based educational activities to train clinical reasoning in a safe environment. Our aim was to explore the influence of the design of the narrative and level of difficulty on the clinical reasoning process, diagnostic accuracy and time-on-task. Methods: In a randomized controlled trial, we analyzed the clinical reasoning process of 46 medical students with six VPs in three different variations: (1) patients showing a friendly behavior, (2) patients showing a disruptive behavior and (3) a version without a patient story. Results: For easy VPs, we did not see a significant difference in diagnostic accuracy. For difficult VPs, the diagnostic accuracy was significantly higher for participants who worked on the friendly VPs compared to the other two groups. Independent from VP difficulty, participants identified significantly more problems and tests for disruptive than for friendly VPs; time on task was comparable for these two groups. The extrinsic motivation of participants working on the VPs without a patient story was significantly lower than for the students working on the friendly VPs. Conclusions: Our results indicate that the measured VP difficulty has a higher influence on the clinical reasoning process and diagnostic accuracy than the variations in the narratives.
The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders.

BACKGROUND Various studies find relationships among anxiety and depressive disorders of adolescence and adulthood. This study prospectively examines the magnitude of longitudinal associations between adolescent and adult anxiety or depressive disorders. METHODS An epidemiologically selected sample of 776 young people living in upstate New York received DSM-based psychiatric assessments in 1983, 1985, and 1992 using structured interviews. The magnitude of the association between adolescent and adult anxiety or depressive disorders was quantified using odds ratios generated from logistic regression analyses and from a set of latent Markov analyses. We focus on longitudinal associations among narrowly defined DSM anxiety or depressive disorders. RESULTS In simple logistic models, adolescent anxiety or depressive disorders predicted an approximate 2- to 3-fold increased risk for adulthood anxiety or depressive disorders. There was evidence of specificity in the course of simple and social phobia but less specificity in the course of other disorders. Results from the analyses using latent variables suggested that while most adolescent disorders were no longer present in young adulthood, most adult disorders were preceded by adolescent disorders. CONCLUSIONS An anxiety or depressive disorder during adolescence confers a strong risk for recurrent anxiety or depressive disorders during early adulthood. Most anxiety and depressive disorders in young adults may be preceded by anxiety or depression in adolescence.
Competitive Price Targeting with Smartphone Coupons

We conduct a large-scale field experiment to study competitive price discrimination in a duopoly market with two rival movie theaters. The firms use mobile targeting to offer different prices based on location and past consumer activity. A novel feature of our experiment is that we test a range of relative ticket prices from both firms to trace out their respective best-response functions and to assess equilibrium outcomes. We use our experimentally-generated data to estimate a demand model that can be used to predict the consumer choices and corresponding firm best-responses at price levels not included in the test. We find an empirically large return on investment when a single firm unilaterally targets its prices based on the geographic location or historical visit behavior of a mobile customer. However, these returns can be mitigated by competitive interactions whereby both firms simultaneously engage in targeting. In practice, firms typically test only their own prices and do not consider the competitive response of a rival. In our study of movie theaters, competition enhances the returns to behavioral targeting but reduces the returns to geo-targeting. Under geographic targeting, each theater offers a discount in the other rival's local market, toughening price competition. In contrast, under behavioral targeting, the strategic complementarity of prices coupled with the symmetric incentives of the two theaters to raise prices charged to high-recency customers softens price competition. Thus, managers need to consider how competition moderates the profitability of price targeting. Moreover, field experiments that hold the competitor's actions fixed may generate misleading conclusions if the permanent implementation of a tested action would likely elicit a competitive response.
Personality and problem gambling: a prospective study of a birth cohort of young adults.

CONTEXT Individual differences in dimensions of personality may play an important role in explaining risk for disordered gambling behavior as well as the comorbidity between disordered gambling behavior and other substance-related addictive disorders. OBJECTIVES To identify the personality correlates of problem gambling in a representative non-treatment-seeking sample, as well as to determine whether these are similar to the personality correlates of other substance-related addictive disorders and whether individual differences in personality might account for the comorbidity between disordered gambling behavior and other substance-related addictive disorders. DESIGN Longitudinal population-based study. PARTICIPANTS A complete birth cohort of young adults born in Dunedin, New Zealand, between April 1, 1972, and March 31, 1973 (N = 939; 475 men, 464 women). MAIN OUTCOME MEASURES Multidimensional Personality Questionnaire assessments of personality were obtained at age 18 years; structured interview-based diagnoses of past-year problem gambling and alcohol, cannabis, and nicotine dependence were obtained at age 21 years. RESULTS Problem gambling at age 21 years was associated with higher scores on the higher-order personality dimension of negative emotionality (d = 0.90) and with lower scores on the personality dimension of constraint (d = -0.72) measured at age 18 years compared with control subjects who did not have a past-year addictive disorder at age 21 years. Problem gambling was also associated with Multidimensional Personality Questionnaire indicators of risk-taking (d = 0.50) and impulsivity (d = 0.56). The personality profile associated with problem gambling was similar to the profiles associated with alcohol, cannabis, and nicotine dependence. The relations between problem gambling and the substance-related addictive disorders (odds ratios = 3.32-3.61) were reduced after controlling for individual differences in personality (odds ratios = 1.90-2.32). CONCLUSIONS From the perspective of personality, problem gambling has much in common with the addictive disorders, as well as with the larger class of "externalizing" or "disinhibitory" disorders. Knowledge gained from the study of common personality underpinnings may be helpful in determining where disordered gambling behavior should reside in our diagnostic classification system.
The Making of the Modern Metropolis: Evidence from London

Modern metropolitan areas involve large concentrations of economic activity and the transport of millions of people each day between their residence and workplace. We use the revolution in transport technology from the invention of steam railways, newly-constructed spatially-disaggregated data for London from 1801-1921, and a quantitative urban model to provide evidence on the role of these commuting flows in supporting such concentrations of economic activity. Steam railways dramatically reduced travel times and permitted the first large scale separation of workplace and residence. We show that our model is able to account for the observed changes in the organization of economic activity, both qualitatively and quantitatively. In counterfactuals, we find that removing the entire railway network reduces the population and the value of land and buildings in Greater London by 20 percent or more, and brings down commuting into the City of London from more than 370,000 to less than 60,000 workers.
Midterm Clinical Results in Rugby Players Treated With the Bristow Procedure

Background: Although surgical shoulder stabilization by coracoid transfer is effective for collision athletes and has a low reinjury rate, no reports have described the midterm results of this procedure in specific patient cohorts of sufficient number or provided subjective assessments of these patients. Purpose: To evaluate midterm results after treatment of shoulder instability with the Bristow procedure in a large cohort of rugby players. Study Design: Case series; Level of evidence, 4. Methods: This study included 176 shoulders of 152 competitive rugby players who underwent shoulder stabilization surgery (Bristow procedure with Bankart repair) with a mean follow-up of 4 years (minimum of 2 years) in our institute. The primary outcome measure was the difference in the presurgical and postsurgical functional Rowe score and Western Ontario Shoulder Instability index (WOSI) score and factors affecting these scores. Complication rates and associated factors were also investigated. Results: In total, 176 shoulders of 152 patients underwent the Bristow procedure with Bankart repair, and 93.2% of the players returned to their preinjury competition level at a mean of 6.3 months postoperatively. All Rowe and WOSI scores were significantly improved after surgery. The numbers of shoulders with functional failure as indicated by the Rowe score, WOSI score, and inability to return to the previous level of play were 28 (15.9%), 54 (30.7%), and 12 (6.8%), respectively. Multiple logistic regression analyses demonstrated that reinjury after surgery (odds ratio [OR] = 35.1) and the number of shoulder dislocations (OR = 11.2-11.4) negatively affected the competition level after return to play, while reinjury (OR = 11.1-17.8), the number of shoulder subluxations (OR = 1.1-2.9), injury in the dominant shoulder (OR = 1.2-2.2), and large bone defects (OR = 1.1-11.5) negatively affected functional scores. Reinjury after shoulder stabilization occurred in 6 of 176 shoulders (3.4%). Multiple logistic regression analysis demonstrated that reinjury after surgery occurred more frequently in players at lower versus higher grade levels of competition (OR = 21.0). Although differences were not significant, a trend was noted toward higher postoperative reinjury rates in forward players, those in the upper categories (professional and college), and those with injury in the nondominant shoulder. Conclusion: The Bristow procedure provides good midterm outcomes for competitive collision athletes, while postsurgical reinjury, the number of preoperative dislocations and subluxations, and large bone defects negatively affect postsurgical shoulder function. This information may be useful for treatment of shoulder dislocations in collision athletes.
Incremental Classifier Learning with Generative Adversarial Networks

In this paper, we address the incremental classifier learning problem, which suffers from catastrophic forgetting. The main reason for catastrophic forgetting is that the past data are not available during learning. Typical approaches keep some exemplars for the past classes and use distillation regularization to retain the classification capability on the past classes and balance the past and new classes. However, there are four main problems with these approaches. First, the loss function is not efficient for classification. Second, there is unbalance problem between the past and new classes. Third, the size of pre-decided exemplars is usually limited and they might not be distinguishable from unseen new classes. Forth, the exemplars may not be allowed to be kept for a long time due to privacy regulations. To address these problems, we propose (a) a new loss function to combine the cross-entropy loss and distillation loss, (b) a simple way to estimate and remove the unbalance between the old and new classes , and (c) using Generative Adversarial Networks (GANs) to generate historical data and select representative exemplars during generation. We believe that the data generated by GANs have much less privacy issues than real images because GANs do not directly copy any real image patches. We evaluate the proposed method on CIFAR-100, Flower-102, and MS-Celeb-1M-Base datasets and extensive experiments demonstrate the effectiveness of our method.
Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes

Given the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions.