Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Won't Lola Run? An Experiment Examining Stereotype Threat and Political Ambition

Among the most well-documented and long-standing gender gaps in political behavior are those relating to political ambition, as men have consistently been shown to express a significantly higher level of political ambition than women. Although this gap is well established, the reasons for the differences between men and women remain largely unknown. One possible explanation is that negative stereotypes about women's political ability are responsible. Stereotype threat, as it is referred to in the psychology literature, is a phenomenon where individuals of a social group suffer cognitive burdens and anxiety after being exposed to negative stereotypes that relate to their identity. These disruptions have been shown to alter attitudes and behavior. In order to test this possibility, we employed an experimental design whereby we randomly assigned 501 undergraduate students into threat and nonthreat conditions. While men exhibited higher levels of political ambition in both conditions, women in the nonthreat condition expressed significantly higher levels of political ambition than those women who were exposed to negative stereotypes. The results of this study therefore suggest that the gender gap in political ambition may be partly explained by negative stereotypes about women in politics.
Maximum penalized likelihood estimation in semiparametric capture-recapture models

We discuss the semiparametric modeling of mark-recapture-recovery data where the temporal and/or individual variation of model parameters is explained via covariates. Typically, in such analyses a fixed (or mixed) effects parametric model is specified for the relationship between the model parameters and the covariates of interest. In this paper, we discuss the modeling of the relationship via the use of penalized splines, to allow for considerably more flexible functional forms. Corresponding models can be fitted via numerical maximum penalized likelihood estimation, employing cross-validation to choose the smoothing parameters in a data-driven way. Our contribution builds on and extends the existing literature, providing a unified inferential framework for semiparametric mark-recapture-recovery models for open populations, where the interest typically lies in the estimation of survival probabilities. The approach is applied to two real datasets, corresponding to grey herons (Ardea Cinerea), where we model the survival probability as a function of environmental condition (a time-varying global covariate), and Soay sheep (Ovis Aries), where we model the survival probability as a function of individual weight (a time-varying individual-specific covariate). The proposed semiparametric approach is compared to a standard parametric (logistic) regression and new interesting underlying dynamics are observed in both cases.
Information Needs and Utilization among Social Science Undergraduates in Nigerian Universities

Information is a means through which knowledge about a phenomenon derived from observation, study experience or instruction and collection in varying ways. However, failure rates continue to increase in some universities in Nigeria, and information dissemination is not improving. This study, therefore, examines the information needs and utilisation of undergraduates in the Departments of Accountancy and Business Administration within three selected Nigerian Universities based on ownership. The study adopts qualitative research approach using interview method to collect data in the federal, state and privately owned universities. The research adopted snowball sampling method as it was difficult to determine the specific sample frame due to non-availability of intake records. The study therefore recruited ninety respondents for an interview from the three universities covering various disciplines in social sciences including Business Administration, Accounting, Economics and Finance. The study was guided by Wilson’s 1991 information behaviour model using it major variables of information needs, seeking, awareness, utilisation and outcome. Findings revealed that students require relevant information that will assist them to succeed in their academic career. It also found that information needs of students vary depending on their course of study. Students, however, utilise information for various purposes including academic work, social networking, community development and lifelong learning experience.
Asymptotic Models for the Topological Sensitivity Versus the Topological Derivative

An approach, based on the refined method of matched asymptotic expansions, is proposed for the construction of asymptotic models for the topological sensitivity of the energy functional with respect to the creation of a small hole in the geometrical domain. It is shown that the asymptotic model provides more information for calculations than the topo- logical derivative.
High sensitivity cardiac troponin assays in the clinical laboratories

Abstract Immunoassays measuring cardiac troponins I or T have become firmly established as critical tools for diagnosing acute myocardial infarction. While most contemporary assays provide adequate diagnostic performance, the increased sensitivity and precision of the new, high sensitivity assays that have already been introduced into clinical practice, provide the potential to further shorten intervals between blood draws or the time needed to detect the first significant troponin elevation. In addition to the relatively modest benefits at the diagnostic end, the high sensitivity assays and the investigational ultrasensitive cardiac troponin assays offer improvements for predicting major adverse cardiovascular events, development of heart failure or transition to end-stage kidney disease. These novel high sensitivity assays can measure troponin concentrations in 50%–100% of healthy individuals and therefore allow for the distribution of troponin values within a healthy cohort to be measured, patient’s baseline troponin levels to be monitored, and clinicians to be alerted of deteriorating cardiorenal conditions. We envisage that the high sensitivity assays will become important tools for predicting each patient’s risk of future adverse events and for guiding and monitoring corresponding adjustments of preventative therapeutic interventions.
'STOP SPAMMING ME!' - Exploring Information Overload on Facebook

The problem of information overload on Facebook is exacerbating as users expand their networks. Growing quantity and increasingly poor quality of information on the Newsfeed may interfere with the hedonic experience of users resulting in frustration and dissatisfaction. In the long run, such developments threaten to undermine sustainability of the platform. To address these issues, our study adopts a grounded theory approach to explore the phenomenon of information overload on Facebook. We investigate main sources of information overload, identify strategies users adopt to deal with it as well as possible consequences. In-depth analysis of the phenomenon allows us to uncover individual peculiarities for identification of relevant information. Based on them we provide valuable recommendations for network providers.
An Agn Identification for 3eg J2006-2321

We present a multiwavelength analysis of the high-energy gamma-ray source 3EG J2006-2321 (l = 1882, b = -2626). The flux of this source above 100 MeV is shown to be variable on timescales of days and months. Optical observations and careful examination of archived radio data indicate that its most probable identification is with PMN J2005-2310, a flat-spectrum radio quasar with a 5 GHz flux density of 260 mJy. Study of the V = 19.3 optical counterpart indicates a redshift of 0.833 and variable linear polarization. No X-ray source has been detected near the position of PMN J2005-2310, but an X-ray upper limit is derived from ROSAT data. This upper limit provides for a spectral energy distribution with global characteristics similar to those of known gamma-ray blazars. Taken together, these data indicate that 3EG J2006-2321, listed as unidentified in the Third EGRET Catalog, is a member of the blazar class of active galactic nuclei (AGNs). The 5 GHz radio flux density of this blazar is the lowest of the 68 EGRET-detected AGNs. The fact that EGRET has detected such a source has implications for unidentified EGRET sources, particularly those at high latitudes (|b| > 30°), many of which may be blazars.
American Journal of Epidemiology Original Contribution Body Mass Index, Height, and Risk of Lymphatic Malignancies: a Prospective Cohort Study

The association among body mass index (BMI), height, and the risk of lymphatic malignancies was investigated in the Netherlands Cohort Study. The participants (n ¼ 120,852), Dutch men and women aged 55–69 years, completed a self-administered questionnaire at baseline in 1986. After 13.3 years of follow-up, data on 1,042 lymphatic malignancy cases (including diffuse large-cell lymphoma, chronic lymphocytic leukemia, multiple mye-loma, and other subtypes) and 4,588 subcohort members were available. Incidence rate ratios were estimated by using Cox regression models. BMI at baseline and BMI change since the age of 20 years were not associated with lymphatic malignancy risk. However, the rate ratio of lymphatic malignancies per 4-unit increase in BMI at 20 years of age was 1.13 (95% confidence interval (CI): 1.01, 1.25). The rate ratio of lymphatic malignancies per 5-cm increase in height was 1.08 (95% CI: 1.02, 1.15). For diffuse large-cell lymphoma, follicular lymphoma, and chronic lymphocytic leukemia, the relative risks were 1. for each 5-cm increase in height. The positive associations among BMI at 20 years of age, height, and the risk of lymphatic malignancies suggest that exposures during early life play a role in the etiology of lymphatic malignancies. The malignancies of the hematopoietic and lymphoid tissues , if taken as 1 group, are the sixth most common malig-nancy worldwide (1). Their occurrence has been rising globally for several decades (2–4). Changes in classification and improvement of cancer reporting, as well as the aging population, the human immunodeficiency virus (HIV) epidemic , and occupational exposures to carcinogens, have been proposed as explanations for the increase, although they do not explain most of the rise that happened over the past 40 years (5). The 2001 World Health Organization (WHO) classification stratifies these malignancies primarily according to lin-eage: myeloid, lymphoid, histiocytic/dendritic cell, and mast cell (6). Neoplasms such as malignant lymphoma, multiple myeloma, and chronic lymphocytic leukemia are all classified as lymphatic malignancies (6). The prevalence of obesity has risen globally (7). Obesity has been associated with several types of cancer, in particular , colorectal, breast in postmenopausal women, kidney, pancreatic, esophageal adenocarcinoma, and gastric cardia (1, 8, 9). A number of studies investigated the association between obesity and lymphatic malignancies, but the results have been inconsistent so far. Several case-control (10–14) and cohort (15–18) studies found positive associations between body mass index (BMI) and lymphatic malignancies, while other studies reported no association (19–23). The possible association …
Surgical resection and radiofrequency ablation initiate cancer in cytokeratin-19+- liver cells deficient for p53 and Rb

The long term prognosis of liver cancer patients remains unsatisfactory because of cancer recurrence after surgical interventions, particularly in patients with viral infections. Since hepatitis B and C viral proteins lead to inactivation of the tumor suppressors p53 and Retinoblastoma (Rb), we hypothesize that surgery in the context of p53/Rb inactivation initiate de novo tumorigenesis. We, therefore, generated transgenic mice with hepatocyte and cholangiocyte/liver progenitor cell (LPC)-specific deletion of p53 and Rb, by interbreeding conditional p53/Rb knockout mice with either Albumin-cre or Cytokeratin-19-cre transgenic mice. We show that liver cancer develops at the necrotic injury site after surgical resection or radiofrequency ablation in p53/Rb deficient livers. Cancer initiation occurs as a result of specific migration, expansion and transformation of cytokeratin-19+-liver (CK-19+) cells. At the injury site migrating CK-19+ cells formed small bile ducts and adjacent cells strongly expressed the transforming growth factor β (TGFβ). Isolated cytokeratin-19+ cells deficient for p53/Rb were resistant against hypoxia and TGFβ-mediated growth inhibition. CK-19+ specific deletion of p53/Rb verified that carcinomas at the injury site originates from cholangiocytes or liver progenitor cells. These findings suggest that human liver patients with hepatitis B and C viral infection or with mutations for p53 and Rb are at high risk to develop tumors at the surgical intervention site.
Static Program Analysis for Performance Modeling

The performance model of an application can provide understanding about its runtime behavior on particular hardware. Such information can be analyzed by developers for performance tuning. However, model building and analyzing is frequently ignored during software development until performance problems arise because they require significant expertise and can involve many time-consuming application runs. In this paper, we propose a faster, accurate, flexible and user-friendly tool, Mira, for generating intuitive performance models by applying static program analysis, targeting scientific applications running on supercomputers. Our tool parses both the source and binary to estimate performance attributes with better accuracy than considering just source or just binary code. Because our analysis is static, the target program does not need to be executed on the target architecture, which enables users to perform analysis on available machines instead of conducting expensive experiments on potentially expensive resources. Moreover, statically generated models enable performance prediction on non-existent or unavailable architectures. In addition to flexibility, because model generation time is significantly reduced compared to dynamic analysis approaches, our method is suitable for rapid application performance analysis and improvement. We present several benchmark validation results to demonstrate the current capabilities of our approach. Keywords-HPC; performance; modeling; static analysis
Influence of Threat and Serotonin Transporter Genotype on Interference Effects

Emotion-cognition interactions are critical in goal-directed behavior and may be disrupted in psychopathology. Growing evidence also suggests that emotion-cognition interactions are modulated by genetic variation, including genetic variation in the serotonin system. The goal of the current study was to examine the impact of threat-related distracters and serotonin transporter promoter polymorphism (5-HTTLPR/rs25531) on cognitive task performance in healthy females. Using a novel threat-distracter version of the Multi-Source Interference Task specifically designed to probe emotion-cognition interactions, we demonstrate a robust and temporally dynamic modulation of cognitive interference effects by threat-related distracters relative to other distracter types and relative to no-distracter condition. We further show that threat-related distracters have dissociable and opposite effects on cognitive task performance in easy and difficult task conditions, operationalized as the level of response interference that has to be surmounted to produce a correct response. Finally, we present evidence that the 5-HTTLPR/rs25531 genotype in females modulates susceptibility to cognitive interference in a global fashion, across all distracter conditions, and irrespective of the emotional salience of distracters, rather than specifically in the presence of threat-related distracters. Taken together, these results add to our understanding of the processes through which threat-related distracters affect cognitive processing, and have implications for our understanding of disorders in which threat signals have a detrimental effect on cognition, including depression and anxiety disorders.
Playing with tagging: A real-time tagging music player

Visualizing audio signals during playback has long been a fundamental function of music players. However, most visual effects are generated by audio signal processing directly and render meaningless or incomprehensible displays to users. In this paper, we present an intelligent music player called the Playing with Tagging (PWT) music player. By integrating a real-time music tagger, the PWT player can display dynamic tag distributions via a set of tag bars that move in sync with the music. To synchronize the tag distributions, the music tagger must be able to online recognize the music tags. We utilize a Gaussian mixture model (GMM) as an auditory feature encoding reference and a mixture of tag-based aspect models (TBAMs) to predict the tag distribution for a short sliding chunk of the music played. To evaluate the real-time tagging function, we simulate tag prediction on short music chunks. The results of experiments on the MajorMiner dataset demonstrate the potential and effectiveness of the proposed music tagging method.
Spontaneous Activity Characteristics of 3D “Optonets”

Sporadic spontaneous network activity emerges during early central nervous system (CNS) development and, as the number of neuronal connections rises, the maturing network displays diverse and complex activity, including various types of synchronized patterns. These activity patterns have major implications on both basic research and the study of neurological disorders, and their interplay with network morphology tightly correlates with developmental events such as neuronal differentiation, migration and establishment of neurotransmitter phenotypes. Although 2D neural cultures models have provided important insights into network activity patterns, these cultures fail to mimic the complex 3D architecture of natural CNS neural networks and its consequences on connectivity and activity. A 3D in-vitro model mimicking early network development while enabling cellular-resolution observations, could thus significantly advance our understanding of the activity characteristics in the developing CNS. Here, we longitudinally studied the spontaneous activity patterns of developing 3D in-vitro neural network “optonets,” an optically-accessible bioengineered CNS model with multiple cortex-like characteristics. Optonet activity was observed using the genetically encodable calcium indicator GCaMP6m and a 3D imaging solution based on a standard epi-fluorescence microscope equipped with a piezo-electric z-stage and image processing-based deconvolution. Our results show that activity patterns become more complex as the network matures, gradually exhibiting longer-duration events. This report characterizes the patterns over time, and discusses how environmental changes affect the activity patterns. The relatively high degree of similarity between the network's spontaneously generated activity patterns and the reported characteristics of in-vivo activity, suggests that this is a compelling model system for brain-in-a chip research.
NEW SECURITY ALGORITHM FOR MOBILE ADHOC NETWORKS USING ZONAL ROUTING PROTOCOL

Mobile adhoc network is a special kind of wireless networks. It is a collection of mobile nodes without having aid of establish infrastructure. In mobile adhoc network, it is much more vulnerable to attacks than a wired network due to its limited physical security, volatile network topologies, power-constrained operations, intrinsic requirement of mutual trust among all nodes in underlying protocol design and lack of centralized monitoring and management point. The main aim of this work is to provide secure data transmission between the source and destination. The simulation is carried out for different number of mobile nodes using network simulator with the help of 1000 mobile nodes. We have compared this model with the existing models such as DSR and AODV. This model has shown the better results in terms of packet delivery, packet drop, and delay. The proposed model has dropped 19% of the packets even if network has five malicious nodes.
Aspect-oriented programming: Introduction

Computer science has experienced an evolution in programming languages and systems from the crude assembly and machine codes of the earliest computers through concepts such as formula translation, procedural programming, structured programming, functional programming, logic programming, and programming with abstract data types. Each of these steps in programming technology has advanced our ability to achieve clear separation of concerns at the source code level. Currently, the dominant programming paradigm is object-oriented programming - the idea that one builds a software system by decomposing a problem into objects and then writing the code of those objects. Such objects abstract together behavior and data into a single conceptual and physical entity. Object-orientation is reflected in the entire spectrum of current software development methodologies and tools - we have OO methodologies, analysis and design tools, and OO programming languages. Writing complex applications such as graphical user interfaces, operating systems, and distributed applications while maintaining comprehensible source code has been made possible with OOP. Success at developing simpler systems leads to aspirations for greater complexity. Object orientation is a clever idea, but has certain limitations. We are now seeing that many requirements do not decompose neatly into behavior centered on a single locus. Object technology has difficulty localizing concerns invoking global constraints and pandemic behaviors, appropriately segregating concerns, and applying domain-specific knowledge. Post-object programming (POP) mechanisms that look to increase the expressiveness of the OO paradigm are a fertile arena for current research. Examples of POP technologies include domain-specific languages, generative programming, generic programming, constraint languages, reflection and metaprogramming, feature-oriented development, views/viewpoints, and asynchronous message brokering. (Czarneclu and Eisenecker s book includes a good survey of many of these technologies).
GUY1 confers complete female lethality and is a strong candidate for a male-determining factor in Anopheles stephensi

Despite their importance in sexual differentiation and reproduction, Y chromosome genes are rarely described because they reside in repeat-rich regions that are difficult to study. Here, we show that Guy1, a unique Y chromosome gene of a major urban malaria mosquito Anopheles stephensi, confers 100% female lethality when placed on the autosomes. We show that the small GUY1 protein (56 amino acids in length) causes female lethality and that males carrying the transgene are reproductively more competitive than their non-transgenic siblings under laboratory conditions. The GUY1 protein is a primary signal from the Y chromosome that affects embryonic development in a sex-specific manner. Our results have demonstrated, for the first time in mosquitoes, the feasibility of stable transgenic manipulation of sex ratios using an endogenous gene from the male-determining chromosome. These results provide insights into the elusive M factor and suggest exciting opportunities to reduce mosquito populations and disease transmission. DOI: http://dx.doi. org/10.7554/eLife.19281. 001