Understanding user motivations for asking and answering a question on brainly, online social learning network

As an emergence of social question-answering (Q&A) services has spurred the growth of social information seeking through question-answering interactions in order to share knowledge and information for users’ need in their learning processes, the current study focuses on conceptualizing and gaining a holistic view of what motivates students to visit social Q&A services and engage in social interactions for sharing and seeking knowledge. The findings show that an immediate help, learning, verification are the top motivations for asking a question, while altruism, learning, and self-enjoyment are the top motivations for answering a question on Brainly, an online social learning Q&A service

Development and Validation of Credit-Scoring Models

Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many .nancial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit decisions. We build credit scoring models for bankcard markets using the Office of the Comptroller of the Currency, Risk Analysis Division (OCC/RAD) consumer credit database (CCDB). This unusu- ally rich data set allows us to evaluate a number of methods in common practice. We introduce, estimate, and validate our models, using both out-of-sample contempora- neous and future validation data sets. Model performance is compared using both separation and accuracy measures. A vendor-developed generic bureau-based score is also included in the model performance comparisons. Our results indicate that current industry practices, when carefully applied, can produce models that robustly rank-order potential borrowers both at the time of development and through the near future. However, these same methodologies are likely to fail when the the objective is to accurately estimate future rates of delinquency or probabilities of default for individual or groups of borrowers.

Beyond questioning and answering: Teen’s learning experiences and benefits of Social Q&A services

https://deepblue.lib.umich.edu/bitstream/2027.42/147349/1/Rieh et al. Beyond Questioning and Answering CSCW17 poster.pd

Perspectives of Dermatology Program Directors on the Impact of Step 1 Pass/Fail.

INTRODUCTION: The shift of Step 1 to Pass/Fail has generated several questions and concerns about obtaining residency positions among allopathic and osteopathic students alike. Determining the perspectives of Dermatology Program Directors in regards to post-Step 1 Pass/Fail is critical for students to better prepare for matching into dermatology. METHODS: After receiving Institutional Review Board (IRB) exemption status, the program directors were chosen from 144 Accreditation Council for Graduate Medical Education (ACGME) and 27 American Osteopathic Association (AOA) Dermatology programs using contact information from their respective online website databases. An eight-item survey was constructed on a three-point Likert scale, one free text response, and four demographic questions. The anonymous survey was sent out over the course of three weeks with weekly individualized reminder requests for participation. RESULTS: A total of 54.54% of responders had Letters of Recommendation in their top 3. Forty-five percent of responders had Completed Audition Rotation at Program in their top 3. And, 38.09% of responders had USMLE Step 2 CK Scores in their top 3. CONCLUSION: Approximately 50% of responders agreed that all medical students will have more difficulty matching dermatology. Based on the survey study, Dermatology program directors want to focus more on letters of recommendation, audition rotations, and Step 2 CK scores. Because each field seems to prioritize different aspects of an application, students should attempt to gain as much exposure to different fields such as through research and shadowing to narrow down their ideal specialties. Consequently, the student will have more time to tailor their applications to what residency admissions are looking for

Molecular determinants of chaperone interactions on MHC-I for folding and antigen repertoire selection.

The interplay between a highly polymorphic set of MHC-I alleles and molecular chaperones shapes the repertoire of peptide antigens displayed on the cell surface for T cell surveillance. Here, we demonstrate that the molecular chaperone TAP-binding protein related (TAPBPR) associates with a broad range of partially folded MHC-I species inside the cell. Bimolecular fluorescence complementation and deep mutational scanning reveal that TAPBPR recognition is polarized toward the α2 domain of the peptide-binding groove, and depends on the formation of a conserved MHC-I disulfide epitope in the α2 domain. Conversely, thermodynamic measurements of TAPBPR binding for a representative set of properly conformed, peptide-loaded molecules suggest a narrower MHC-I specificity range. Using solution NMR, we find that the extent of dynamics at "hotspot" surfaces confers TAPBPR recognition of a sparsely populated MHC-I state attained through a global conformational change. Consistently, restriction of MHC-I groove plasticity through the introduction of a disulfide bond between the α1/α2 helices abrogates TAPBPR binding, both in solution and on a cellular membrane, while intracellular binding is tolerant of many destabilizing MHC-I substitutions. Our data support parallel TAPBPR functions of 1) chaperoning unstable MHC-I molecules with broad allele-specificity at early stages of their folding process, and 2) editing the peptide cargo of properly conformed MHC-I molecules en route to the surface, which demonstrates a narrower specificity. Our results suggest that TAPBPR exploits localized structural adaptations, both near and distant to the peptide-binding groove, to selectively recognize discrete conformational states sampled by MHC-I alleles, toward editing the repertoire of displayed antigens

Computational Relativistic Astrophysics With Adaptive Mesh Refinement: Testbeds

We have carried out numerical simulations of strongly gravitating systems based on the Einstein equations coupled to the relativistic hydrodynamic equations using adaptive mesh refinement (AMR) techniques. We show AMR simulations of NS binary inspiral and coalescence carried out on a workstation having an accuracy equivalent to that of a $1025^3$ regular unigrid simulation, which is, to the best of our knowledge, larger than all previous simulations of similar NS systems on supercomputers. We believe the capability opens new possibilities in general relativistic simulations.Comment: 7 pages, 16 figure

A machine learning-based approach to predicting success of questions on social question-answering

While social question-answering (SQA) services are becoming increasingly popular, there is often an issue of unsatisfactory or missing information for a question posed by an information seeker. This study creates a model to predict question failure, or a question that does not receive an answer, within the social Q&A site Yahoo! Answers. To do so, observed shared characteristics of failed questions were translated into empirical features, both textual and non-textual in nature, and measured using machine extraction methods. A classifier was then trained using these features and tested on a data set of 400 questions – half of them successful, half not – to determine the accuracy of the classifier in identifying failed questions. The results show the substantial ability of the approach to correctly identify the likelihood of success or failure of a question, resulting in a promising tool to automatically identify ill-formed questions and/or questions that are likely to fail and make suggestions on how to revise them.published or submitted for publicationis peer reviewe