Miracle-dz/UniFAR-FTUs huggingface dataset:
Young Malawians on the interaction between mental health and HIV/AIDS

Previous research has identified high levels of mental health problems among people affected by HIV. This study surveys specifically adolescents in southern Malawi on their experience of the impacts of living with HIV or AIDS on one's mental health. At the same time, the study explores the link between mental health problems and subsequent HIV-risk behaviour. Short texts relating everyday scenarios that depicted symptoms of three mental health problems (i.e.depression, anxiety and HIV-related brain impairment) formed the basis of in-depth discussions in 12 existing groups of secondary school students, orphans and vulnerable children, teenage mothers, and out-of-school youths, in both rural and urban settings. The responses show that these young people recognised the mental health sequelae of HIV/AIDS as impacting upon many aspects of one's life. The young people traced these 'interruptions' and 'disruptions' through deteriorating psychological and socio-economic conditions. They showed awareness of a two-way interaction between HIV/AIDS and mental illness, indicating that the latter can increase thoughts of suicide and HIV risk-taking behaviour. More importantly, they identified a number of locally derived community interventions, which if supported by statutory health and education services, can significantly ameliorate their situations. The findings provide avenues for practical integration of mental health provision within HIV prevention, education and care initiatives.
Normative beliefs, attitudes, and social norms: People reduce waste as an index of social relationships when spending leisure time

This study has adopted and refined Ajzen’s theory of planned behavior, theory of reasoned action, and the value–belief–norm theory by Stern et al. to investigate the effects of normative beliefs, attitudes, and social norms on pro-environmental behavioral intentions. A total of 391 valid responses were collected from visitors to a theme park in Taiwan. A structure equation analysis indicated that the overall fit of the proposed model was supported. It was also found that both attitudes and social norms had positive and significant influence on waste reduction. While the results did not reveal any direct relation between normative beliefs and behavioral intentions, normative beliefs had positive direct influence on social norms and attitudes, which in turn had an impact on behavioral intentions. The findings provided further insights about pro-environmental behavioral intentions from an Asia perspective and highlighted important implications for environmental policies and education to reduce waste.
A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis*

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSn proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) “SmallGlyPep,” a minimal linear representation of glycopeptides for MSn data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the “Ensemble Score (ES),” a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSn spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.
EXPERIMENTAL FINANCE

1 CHAPTER 6 EXPERIMENTAL FINANCE ROBERT BLOOMFIELD Nicholas H. Noyes Professor of Management and Professor of Accounting, Cornell University, ALYSSA ANDERSON Ph.D. Student in Finance, Cornell University October 9, 2009. Forthcoming in Behavioral Finance, Kent Baker and John Nofsinger, Eds. Wiley (NY), © 2010 by John Wiley and Sons. ABSTRACT This chapter provides a guide for those interested in experimental research in finance. The chapter emphasizes the role experiments play in a field governed largely by modeling and archival data analysis; discusses the basic methods and challenges of experimental finance; explores the close connection between experiments and behavioral finance; and comments on how to think about experimental design. First, the chapter begins by discussing the relationship between experiments and archival data analysis. Experiments are useful because they allow researchers to circumvent common econometric issues such as omitted variables, unobserved variables and self-selection. Next, the chapter examines the contributions that experiments can make beyond theoretical models, either by relaxing certain assumptions or by addressing settings that are too complex to be modeled analytically. Lastly, the chapter discusses the difference between experiments and demonstrations, and emphasizes the critical role of controlled manipulation.
A Theory of Capital Structure, Price Impact, and Long-Run Stock Returns under Heterogeneous Beliefs

We study an environment with short-sale constraints and heterogeneous beliefs among outsiders and between insiders and outsiders. Firm insiders choose between equity, debt, and convertible debt to raise external financing. We analyze two settings: one in which heterogeneous beliefs is the only market imperfection and another in which there are significant security issue and financial distress costs. Our model generates a pecking order of external financing different from asymmetric information models, and new predictions for capital structure, sequential tranching of securities, the price impact of security issues, and long-run stock returns. We also provide a new rationale for convertible debt issuance.
Nursing students' stereotypes of married and unmarried pregnant clients.

The purpose of this study was to investigate the effects of information about a pregnant client's marital status on nursing students' initial perceptions of the client, attributions of group stereotypes to the client, predictions of client behavior, data sought, and verbal responses toward the client. Forty-three undergraduate nursing students from a large Midwestern university volunteered to participate. Subjects were randomly assigned to one of two experimental groups, the "married client" or "unmarried client. " Subjects viewed a videotape of a nurse interviewing a pregnant client and were administered a series of questionnaires. Following this, they were asked to respond in writing to five statements made by the videotaped client. Videotapes were identical except that one group was told they were viewing an unmarried woman and the other group was told the client was married. Results indicated that students evaluated the married client more positively than the unmarried client. Students' perceptions were consistent with several cultural stereotypes. In addition, students predicted that, if hospitalized, the unmarried client would have greater difficulty than the married client. There were no differences between groups in the information they would seek from the client or in responses towards the client.
Evaluation of the Left Ventricular Ejection Fraction with Gated IQ-SPECT Myocardial Perfusion Imaging

The aim of this study was to evaluate the assessment of the left ventricular ejection fraction (LVEF) in patients by gated IQ-SPECT. Methods: Twenty-eight patients were examined using gated 99mTc-sestamibi IQ-SPECT. Two different reconstruction datasets were created using the same projection data. The number of iterations, subsets, and gaussian filtering were based on 2 different recommendations from the manufacturer. For each dataset, end diastolic volume, end systolic volume, and LVEF were calculated using 4DMSPECT. A multigated planar equilibrium radionuclide ventriculography (MUGA) study with 99mTc-labeled red blood cells was used as a reference for the LVEF. Results: The values of the different datasets were tested using the Bland–Altman analysis method. The calculated mean and 95% limits of agreement for the LVEF when dataset 1 and 2 were compared were −1.1% and ±15% points; when dataset 1 was compared with MUGA, the mean was calculated to −3.1% points and ±17% points for the 95% limits of agreement. When dataset 2 and MUGA were compared, the mean was −4.2% and 95% limits of agreement of ±18% points. Conclusion: Neither of the gated reconstructed datasets analyzed with 4DMSPECT was comparable to LVEF estimated by MUGA, with a tendency to overestimate LVEF. However, large random variations of the end diastolic volume, end systolic volume, and LVEF between the 2 gated reconstructed datasets were found. The reconstructed datasets were not interchangeable. Thus, these values should only be used with great caution when evaluating the functional state of the heart.
Protein and fat modify the glycaemic and insulinaemic responses to a mashed potato-based meal

Potatoes, especially mashed potatoes, are known to result in high glycaemic and insulinaemic responses. However, in most meals, potatoes are accompanied by other foods. The objective of the present study was to investigate how glycaemic and insulinaemic responses to a mashed potato meal changed when a high-fat food (rapeseed oil), a high-protein food (chicken breast) and/or salad were added to the meal. Healthy subjects (n 11) ingested the test meals once and the reference food (glucose solution) twice in a random order at 1-week intervals. Capillary blood samples were then drawn for 2 h, and glucose and insulin were analysed. The 2 h glycaemic responses to six mashed potato-containing meals varied more than twofold. The glycaemic index (GI) of pure mashed potato was 108, whereas combined with chicken breast, rapeseed oil and salad, it was only 54. The latter GI also differed considerably from its predicted value of 103, which was based on the individual GI of the components of the meal. The insulinaemic indices of the mashed potato-based meals varied between 94 and 148. Chicken breast in the meal increased the insulinaemic response, and rapeseed oil diminished it. However, the insulinaemic response to mashed potato with chicken breast and rapeseed oil was lower than that to mashed potato alone. In conclusion, the protein, fat and salad contents of a meal exert considerable influence on the glycaemic and insulinaemic responses to mashed potatoes. Furthermore, the estimation of the GI of a mixed meal by calculation is imprecise.
A 2.2/2.7fJ/conversion-step 10/12b 40kS/s SAR ADC with Data-Driven Noise Reduction

Low-power sensor applications e.g. for environmental monitoring, bio-potential recording, and wireless autonomous sensor networks require highly power-efficient ADCs, typically with resolutions of at least 10b. SAR ADCs are generally beneficial in terms of power efficiency. However, the most power-efficient designs currently lack the required accuracy for these applications [1, 2], as they are limited to 9b ENOB. Other designs that have sufficient accuracy (10b) are limited to power efficiencies above 10fJ/conv-step [3]. The aim of this work is to increase the accuracy of highly efficient SAR ADCs beyond 10b, while further improving the efficiency to 2.2fJ/conv-step. To do so, this work introduces a Data-Driven Noise-Reduction method to efficiently suppress comparator noise, applies a segmented capacitive DAC with 250aF unit elements for better efficiency and accuracy, and implements a self-oscillating comparator to locally generate the internally required oversampled clock.
High Turnover Stays for Pediatric Asthma in the United States: Analysis of the 2006 Kids' Inpatient Database

Background:Pediatric observation units provide an alternative to traditional hospitalization. The extent to which observation units could replace inpatient care for asthmatic children is unknown. Objective:To describe brief inpatient (“high-turnover,” HTO) stays for US children hospitalized with a principal discharge diagnosis of asthma, to characterize cases that may be appropriate for observation. Design:We analyzed the 2006 Kids' Inpatient Database, a nationally representative sample of hospital discharges. HTO stays were defined as hospitalizations of 0 or 1 night in duration. We conducted descriptive statistics and case-mix adjusted, sample-weighted regression analysis of HTO stays, and associated hospital charges. Subjects:Discharges among children aged 2 to 20 years with a principal discharge diagnosis of asthma. Measures:HTO stays and total charges. Results:Overall, 34,592 (34%) pediatric asthma hospitalizations were HTO, accounting for 66,278 hospital days in 2006. HTO stays were associated with younger age, uncomplicated asthma, and private insurance. Freestanding children's hospitals had the highest proportion of HTO stays, 38% (95% CI: 34%–42%) compared with 32% (95% CI: 28%–36%) for children's units and 33% (95% CI: 31%–34%) for general hospitals. In multivariate regression analyses, charges were significantly higher across hospital types when HTO stays begin in the emergency department. Conclusions:The presence of a large number of HTO stays for children hospitalized for asthma suggests the need to explore opportunities to restructure care for this condition, perhaps through the development of physically or operationally distinct observation units.
Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?

Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary sources of dynamic habitat data have been in situ and remotely sensed oceanic variables (both are considered “measured data”), but now ocean models can provide historical estimates and forecast predictions of relevant habitat variables such as temperature, salinity, and mixed layer depth. To assess the performance of modeled ocean data in species distribution models, we present a case study for cetaceans that compares models based on output from a data assimilative implementation of the Regional Ocean Modeling System (ROMS) to those based on measured data. Specifically, we used seven years of cetacean line-transect survey data collected between 1991 and 2009 to develop predictive habitat-based models of cetacean density for 11 species in the California Current Ecosystem. Two different generalized additive models were compared: one built with a full suite of ROMS output and another built with a full suite of measured data. Model performance was assessed using the percentage of explained deviance, root mean squared error (RMSE), observed to predicted density ratios, and visual inspection of predicted and observed distributions. Predicted distribution patterns were similar for models using ROMS output and measured data, and showed good concordance between observed sightings and model predictions. Quantitative measures of predictive ability were also similar between model types, and RMSE values were almost identical. The overall demonstrated success of the ROMS-based models opens new opportunities for dynamic species management and biodiversity monitoring because ROMS output is available in near real time and can be forecast.
An Impossibility Theorem in Matching Problems

This paper studies the possibility of strategy-proof rules yielding satisfactory solutions to matching problems. Alcalde and Barber_ (1994) show that efficient and individually rational matching rules are manipulable in the one-to-one matching model. We pursue the possibility of strategy-proof matching rules by relaxing effciency to the weaker condition of respect for unanimity. Our first result is positive. We prove that a strategy-proof rule exists that is individually rational and respects unanimity. However, this rule is unreasonable in the sense that a pair of agents who are the best for each other are matched on only rare occasions. In order to explore the possibility of better matching rules, we introduce the natural condition of "respect for pairwise unanimity. " Respect for pairwise unanimity states that a pair of agents who are the best for each other should be matched, and an agent wishing to stay single should stay single. Our second result is negative. We prove that no strategy-proof rule exists that respects pairwise unanimity. This result implies Roth (1982) showing that stable rules are manipulable. We then extend this to the many-to-one matching model.
Exploring Correlation of Dependency Relation Paths for Answer Extraction

In this paper, we explore correlation of dependency relation paths to rank candidate answers in answer extraction. Using the correlation measure, we compare dependency relations of a candidate answer and mapped question phrases in sentence with the corresponding relations in question. Different from previous studies, we propose an approximate phrase mapping algorithm and incorporate the mapping score into the correlation measure. The correlations are further incorporated into a Maximum Entropy-based ranking model which estimates path weights from training. Experimental results show that our method significantly outperforms state-of-the-art syntactic relation-based methods by up to 20% in MRR.
A POPULATION OF z > 2 FAR-INFRARED HERSCHEL-Spire-SELECTED STARBURSTS

We present spectroscopic observations for a sample of 36 Herschel-Spire 250–500 μm selected galaxies (HSGs) at 2 < z < 5 from the Herschel Multi-tiered Extragalactic Survey. Redshifts are confirmed as part of a large redshift survey of Herschel-Spire-selected sources covering ∼0.93 deg2 in six extragalactic legacy fields. Observations were taken with the Keck I Low Resolution Imaging Spectrometer and the Keck II DEep Imaging Multi-Object Spectrograph. Precise astrometry, needed for spectroscopic follow-up, is determined by identification of counterparts at 24 μm or 1.4 GHz using a cross-identification likelihood matching method. Individual source luminosities range from log (LIR/L☉) = 12.5–13.6 (corresponding to star formation rates (SFRs) 500–9000 M☉ yr−1, assuming a Salpeter initial mass function), constituting some of the most intrinsically luminous, distant infrared galaxies discovered thus far. We present both individual and composite rest-frame ultraviolet spectra and infrared spectral energy distributions. The selection of these HSGs is reproducible and well characterized across large areas of the sky in contrast to most z > 2 HyLIRGs in the literature, which are detected serendipitously or via tailored surveys searching only for high-z HyLIRGs; therefore, we can place lower limits on the contribution of HSGs to the cosmic star formation rate density (SFRD) at (7 ± 2) × 10−3 M☉ yr−1 h3 Mpc−3 at z ∼ 2.5, which is >10% of the estimated total SFRD of the universe from optical surveys. The contribution at z ∼ 4 has a lower limit of 3 × 10−3 M☉ yr−1 h3 Mpc−3, ≳20% of the estimated total SFRD. This highlights the importance of extremely infrared-luminous galaxies with high SFRs to the buildup of stellar mass, even at the earliest epochs.
Inferential modeling of 3D chromatin structure

For eukaryotic cells, the biological processes involving regulatory DNA elements play an important role in cell cycle. Understanding 3D spatial arrangements of chromosomes and revealing long-range chromatin interactions are critical to decipher these biological processes. In recent years, chromosome conformation capture (3C) related techniques have been developed to measure the interaction frequencies between long-range genome loci, which have provided a great opportunity to decode the 3D organization of the genome. In this paper, we develop a new Bayesian framework to derive the 3D architecture of a chromosome from 3C-based data. By modeling each chromosome as a polymer chain, we define the conformational energy based on our current knowledge on polymer physics and use it as prior information in the Bayesian framework. We also propose an expectation-maximization (EM) based algorithm to estimate the unknown parameters of the Bayesian model and infer an ensemble of chromatin structures based on interaction frequency data. We have validated our Bayesian inference approach through cross-validation and verified the computed chromatin conformations using the geometric constraints derived from fluorescence in situ hybridization (FISH) experiments. We have further confirmed the inferred chromatin structures using the known genetic interactions derived from other studies in the literature. Our test results have indicated that our Bayesian framework can compute an accurate ensemble of 3D chromatin conformations that best interpret the distance constraints derived from 3C-based data and also agree with other sources of geometric constraints derived from experimental evidence in the previous studies. The source code of our approach can be found in https://github.com/wangsy11/InfMod3DGen.
Can a Novel Clinical Risk Score Improve Pneumonia Prediction in Acute Stroke Care? A UK Multicenter Cohort Study

Background Pneumonia frequently complicates stroke and has a major impact on outcome. We derived and internally validated a simple clinical risk score for predicting stroke‐associated pneumonia (SAP), and compared the performance with an existing score (A2DS2). Methods and Results We extracted data for patients with ischemic stroke or intracerebral hemorrhage from the Sentinel Stroke National Audit Programme multicenter UK registry. The data were randomly allocated into derivation (n=11 551) and validation (n=11 648) samples. A multivariable logistic regression model was fitted to the derivation data to predict SAP in the first 7 days of admission. The characteristics of the score were evaluated using receiver operating characteristics (discrimination) and by plotting predicted versus observed SAP frequency in deciles of risk (calibration). Prevalence of SAP was 6.7% overall. The final 22‐point score (ISAN: prestroke Independence [modified Rankin scale], Sex, Age, National Institutes of Health Stroke Scale) exhibited good discrimination in the ischemic stroke derivation (C‐statistic 0.79; 95% CI 0.77 to 0.81) and validation (C‐statistic 0.78; 95% CI 0.76 to 0.80) samples. It was well calibrated in ischemic stroke and was further classified into meaningful risk groups (low 0 to 5, medium 6 to 10, high 11 to 14, and very high ≥15) associated with SAP frequencies of 1.6%, 4.9%, 12.6%, and 26.4%, respectively, in the validation sample. Discrimination for both scores was similar, although they performed less well in the intracerebral hemorrhage patients with an apparent ceiling effect. Conclusions The ISAN score is a simple tool for predicting SAP in clinical practice. External validation is required in ischemic and hemorrhagic stroke cohorts.