Miracle-dz/UniFAR-FTUs huggingface dataset:
Cascading Bandits for Large-Scale Recommendation Problems

Most recommender systems recommend a list of items. The user examines the list, from the first item to the last, and often chooses the first attractive item and does not examine the rest. This type of user behavior can be modeled by the cascade model. In this work, we study cascading bandits, an online learning variant of the cascade model where the goal is to recommend $K$ most attractive items from a large set of $L$ candidate items. We propose two algorithms for solving this problem, which are based on the idea of linear generalization. The key idea in our solutions is that we learn a predictor of the attraction probabilities of items from their features, as opposing to learning the attraction probability of each item independently as in the existing work. This results in practical learning algorithms whose regret does not depend on the number of items $L$. We bound the regret of one algorithm and comprehensively evaluate the other on a range of recommendation problems. The algorithm performs well and outperforms all baselines.
The Dynamics of Glutathione Species and Ophthalmate Concentrations in Plasma from the VX2 Rabbit Model of Secondary Liver Tumors

Purpose. Available tumor markers have low sensitivity/specificity for the diagnosis of liver tumors. The present study was designed to evaluate the oxidoreductive status of the liver as surrogates of tumor subsistence and growth. Methods. Glutathione species (GSH:GSSG), ophthalmate (OA) concentrations, and their turnover were measured in plasma of rabbits (n = 6) in their healthy state and in the state of tumor growth after implantation of the VX2 carcinoma in their liver. Tumors were allowed to grow for a period of 14 days when rabbits were sacrificed. Livers were removed and cysteine concentration was measured in liver tissue. Results. Tumor growth was found in 100% of the rabbits. Concentration and labeling of GSH/GSSG were similar in experimental animals before and after tumor implantation and to sham animals. In contrast, OA concentration increased significantly in experimental animals after tumor implantation when compared to same animals prior to tumor implantation and to sham animals (P < .05). The concentration of cysteine, a precursor of GSH, was found to be significantly lower in the liver tissue adjacent to the tumor (P < .05). Conclusion. Disturbances in the oxidoreductive state of livers appear to be a surrogate of early tumor growth.
Bmc Medical Genetics Resequencing of Genes for Transforming Growth Factor Β1 (tgfb1) Type 1 and 2 Receptors (tgfbr1, Tgfbr2), and Association Analysis of Variants with Diabetic Nephropathy

Background: Diabetic nephropathy is the leading cause of end stage renal failure in the western world. There is substantial epidemiological evidence supporting a genetic predisposition to diabetic nephropathy, however the exact molecular mechanisms remain unknown. Transforming growth factor (TGFβ1) is a crucial mediator in the pathogenesis of diabetic nephropathy.
Knowledge, Attitude, Behavior, and Practices Regarding HIV, Viral Hepatitis, and Sexually Transmitted Infections Among Migrants From Sub-Saharan Africa Living in Germany: A Multicenter Survey Protocol

Background Migration has an impact on the epidemiology of viral hepatitis B and C (HEP) and HIV in Germany; migrants from sub-Saharan Africa (MisSA) in Germany are disproportionally affected by HIV. In the last 10 years, a total of 10%-15% of all newly diagnosed HIV cases were among MisSA; 20%-30% of them acquired HIV in Germany. Prevalence of HEP among MisSA in Germany is unknown, but Western Africa, from where most MisSA in Germany originate, reports the highest prevalence of hepatitis B worldwide. There is limited information on knowledge, attitudes, behaviors, and practices (KABP) regarding HIV, HEP, and sexually transmitted infections (STIs), as MisSA are not reached with surveys targeting the general population. Objective Our objective was to determine the HIV, HEP, and STI information and prevention needs of MisSA in Germany. Methods We conducted a multicenter, cross-sectional, KABP survey regarding HIV, HEP, and STIs among MisSA living in Germany using convenience sampling. The study design was developed as a community-based participatory health research (CBPHR) project; HIV/STI-prevention specialists, key persons from MisSA communities, and HIV/STI researchers were involved in all steps of the research process. Trained peer researchers recruited participants in six study cities. Potential modes of survey administration were interview or self-completion, and the questionnaire was available in English, French, and German. Questions on knowledge about HIV, HEP, and STIs were presented as true statements; participants were asked if they had known the information before. Focus groups with MisSA were conducted to interpret results. Data collection took place from October 2014 to November 2016. Results Recruitment by peer researchers concluded with 3040 eligible participants. Data collection was completed in November 2016. We are currently analyzing the quantitative data and qualitative data from focus groups. We are conducting working group meetings to discuss the results in the respective study cities and to evaluate the application of participatory health research in epidemiological studies. First results are expected by the end of 2017. Conclusions Working with peer researchers to collect data allowed accessibility to a diverse sample of MisSA and, particularly, allowed us to reach vulnerable subgroups, such as MisSA without legal status. The ability to access hard-to-reach groups is one of the big advantages of CBPHR. The active inclusion of the persons under study in the design of the study resulted in higher acceptance and ownership of the research project in the target community; this ultimately lead to better quality of collected data. Furthermore, the participation of MisSA in the development of study design and data collection assures a better understanding of the interests, needs, and living conditions of this group.
Two-Phase Flow-Induced Vibration: An Overview (Survey Paper)

Two-phase flow exists in many industrial components. To avoid costly vibration problems, sound technology in the area of two-phase flow-induced vibration is required. This paper is an overview of the principal mechanisms governing vibration in two-phase flow. Dynamic parameters such as hydrodynamic mass and damping are discussed. Vibration excitation mechanisms in axial flow are outlined. These include fluidelastic instability, phase-change noise, and random excitation. Vibration excitation mechanisms in cross-flow, such as fluidelastic instability, periodic wake shedding, and random excitation, are reviewed.
Joint Prediction of the Effective Population Size and the Rate of Fixation of Deleterious Mutations

Mutation, genetic drift, and selection are considered the main factors shaping genetic variation in nature. There is a lack, however, of general predictions accounting for the mutual interrelation between these factors. In the context of the background selection model, we provide a set of equations for the joint prediction of the effective population size and the rate of fixation of deleterious mutations, which are applicable both to sexual and asexual species. For a population of N haploid individuals and a model of deleterious mutations with effect s appearing with rate U in a genome L Morgans long, the asymptotic effective population size (Ne) and the average number of generations (T) between consecutive fixations can be approximated by Ne≈N exp [−2U/(2s +L) (1−1/UT)3] and T≈[exp(2sNe) −1]/[2UsNe]. The solution is applicable to Muller’s ratchet, providing satisfactory approximations to the rate of accumulation of mutations for a wide range of parameters. We also obtain predictions of the effective size accounting for the expected nucleotide diversity. Predictions for sexual populations allow for outlining the general conditions where mutational meltdown occurs. The equations can be extended to any distribution of mutational effects and the consideration of hotspots of recombination, showing that Ne is rather insensitive and not proportional to changes in N for many combinations of parameters. This could contribute to explain the observed small differences in levels of polymorphism between species with very different census sizes.
Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder

View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth) as well as their magnitude, which we call “variation level. ” We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group) on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier). This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.
Reliability and validity of the Danish version of the disabilities of arm, shoulder, and hand questionnaire in patients with fractured wrists

Abstract The disabilities of arm, shoulder, and hand (DASH) questionnaire is a 30-item region-specific questionnaire that is used to measure the effect of treatment of the upper extremity. The purpose of this study was to assess the reliability of, and validate, the Danish version of the DASH score in patients with fractured wrists. Sixty patients were studied. We investigated internal consistency and test-retest reliability, convergent validity, content validity and responsiveness. Time to complete questionnaire was 11 minutes and two questionnaires were not usable. The internal consistency was sufficient (Cronbach's alpha 0.96 and intraclass correlation coefficient 0.89). The difference in the mean was 4.6 (CI: 0.48 to 8.72, p = 0.03). Convergent validity at first and last control was high for both pain, 0.46 and 0.40 respectively, and for physical mobility, 0.64 and 0.65 respectively, indicating that results confirmed other similar scores. We conclude that the Danish version of the 30-item DASH questionnaire is valid and practical for patients with fractured wrists.
Engineered antibody Fc variant with selectively enhanced FcγRIIb binding over both FcγRIIaR131 and FcγRIIaH131

Engaging inhibitory FcγRIIb by Fc region has been recently reported to be an attractive approach for improving the efficacy of antibody therapeutics. However, the previously reported S267E/L328F variant with enhanced binding affinity to FcγRIIb, also enhances binding affinity to FcγRIIaR131 allotype to a similar degree because FcγRIIb and FcγRIIaR131 are structurally similar. In this study, we applied comprehensive mutagenesis and structure-guided design based on the crystal structure of the Fc/FcγRIIb complex to identify a novel Fc variant with selectively enhanced FcγRIIb binding over both FcγRIIaR131 and FcγRIIaH131. This novel variant has more than 200-fold stronger binding affinity to FcγRIIb than wild-type IgG1, while binding affinity to FcγRIIaR131 and FcγRIIaH131 is comparable with or lower than wild-type IgG1. This selectivity was achieved by conformational change of the CH2 domain by mutating Pro to Asp at position 238. Fc variant with increased binding to both FcγRIIb and FcγRIIa induced platelet aggregation and activation in an immune complex form in vitro while our novel variant did not. When applied to agonistic anti-CD137 IgG1 antibody, our variant greatly enhanced the agonistic activity. Thus, the selective enhancement of FcγRIIb binding achieved by our Fc variant provides a novel tool for improving the efficacy of antibody therapeutics.
On Business Process Model Reviews

In process reviews, domain experts validate the model against reality. In general, reviews are conducted in an iterative manner. Better reviews can build consensus faster and save iterations, i.e. time and money. In an exploratory study, student clerks were asked to provide feedback to models from their domain. In this paper, we report on the study and the review performance. We explore typical issues raised in reviews and derive implications for practitioners and further studies. We identified education as the most influential factor on review performance in our sample set.
Maternal manifestations of malaria in pregnancy: a review.

Malaria is a major cause of maternal and fetal morbidity and mortality, and this risk is highest in the areas of unstable malaria transmission. In 1990 and 1991 the Department of Obstetrics and Gynecology of Sir Sayajirao General Hospital in central Gujarat, India, has cared for a total of 445 urban as well as rural patients with malaria in pregnancy: 232 were labor ward admissions and 213 were antenatal ward admissions. Plasmodium falciparum infection affected 97.27% of patients, both primigravidae and multigravidae. Heavy parasitemia was observed in 27.14% of primigravidae and 48.57% in secundigravidae, however, this was not statistically significant. Out of the 260 (58.42.) cases who had various degrees of anaemia, 59 (22.69) had severe anaemia with haemoglobin of less than 6.0 gm O/dl. Within this group, 71.16% women were primigravidae or secundigravidae, the rest were multigravidae. Out of the 6 patients in first trimester, the miscarriage rate was 100%. In the second trimester, out of 52 patients 74.99 pregnancies were discontinued, whereas in the third trimester, the miscarriage rate was 18.17%. This observation was statistically significant (p 0.05). 178 patients who were admitted antenatally were discharged, their pregnancy outcome was not known, and accordingly they were excluded. There were 11 patients in the first trimester, 139 in the second trimester, and 295 in the third trimester. The known pregnancy losses were 54.54% in the first trimester. 28.05% in the second trimester, and 12.88% in the third trimester. 75.59% of those with minor parasitemia and 47.36% with heavy parasitemia had a normal pregnancy outcome. The overall fetal loss was 31.08%, which was almost twice that of the miscarriage rates among the general population. Maternal deaths attributed to malaria in pregnancy were 15, with cerebral malaria accounting for 5 deaths. 46.66% of the deaths occurred in primigravidae and secundigravidae. The other causes of mortality were postpartum hemorrhage, acute pulmonary edema, and hypoglycemia.
AVAYA: Sentiment Analysis on Twitter with Self-Training and Polarity Lexicon Expansion

This paper describes the systems submitted by Avaya Labs (AVAYA) to SemEval-2013 Task 2 - Sentiment Analysis in Twitter. For the constrained conditions of both the message polarity classification and contextual polarity disambiguation subtasks, our approach centers on training high-dimensional, linear classifiers with a combination of lexical and syntactic features. The constrained message polarity model is then used to tag nearly half a million unlabeled tweets. These automatically labeled data are used for two purposes: 1) to discover prior polarities of words and 2) to provide additional training examples for self-training. Our systems performed competitively, placing in the top five for all subtasks and data conditions. More importantly, these results show that expanding the polarity lexicon and augmenting the training data with unlabeled tweets can yield improvements in precision and recall in classifying the polarity of non-neutral messages and contexts.
Exit in duopoly under uncertainty

I examine a declining duopoly in which the firms must choose when to exit from the market. The uncertainty is modelled by letting the revenue stream follow a geometric Brownian motion. I consider the Markov-perfect equilibrium in firms' exit strategies. With a low degree of uncertainty there is a unique equilibrium, where one of the firms always exits before the other. When uncertainty is increased, however, another equilibrium with the reversed order of exit may appear, ruining the uniqueness. Whether this happens or not depends on the degree of asymmetry in the firm-specific parameters.
Factors Controlling Anaerobic Ammonium Oxidation with Nitrite in Marine Sediments

ABSTRACT Factors controlling the anaerobic oxidation of ammonium with nitrate and nitrite were explored in a marine sediment from the Skagerrak in the Baltic-North Sea transition. In anoxic incubations with the addition of nitrite, approximately 65% of the nitrogen gas formation was due to anaerobic ammonium oxidation with nitrite, with the remainder being produced by denitrification. Anaerobic ammonium oxidation with nitrite exhibited a biological temperature response, with a rate optimum at 15°C and a maximum temperature of 37°C. The biological nature of the process and a 1:1 stoichiometry for the reaction between nitrite and ammonium indicated that the transformations might be attributed to the anammox process. Attempts to find other anaerobic ammonium-oxidizing processes in this sediment failed. The apparent Km of nitrite consumption was less than 3 μM, and the relative importance of ammonium oxidation with nitrite and denitrification for the production of nitrogen gas was independent of nitrite concentration. Thus, the quantitative importance of ammonium oxidation with nitrite in the jar incubations at elevated nitrite concentrations probably represents the in situ situation. With the addition of nitrate, the production of nitrite from nitrate was four times faster than its consumption and therefore did not limit the rate of ammonium oxidation. Accordingly, the rate of this process was the same whether nitrate or nitrite was added as electron acceptor. The addition of organic matter did not stimulate denitrification, possibly because it was outcompeted by manganese reduction or because transport limitation was removed due to homogenization of the sediment.
Call level performance analysis of 3/sup rd/ generation mobile core networks

We develop a call level model of UMTS core networks where calls belonging to one of the four UMTS service classes arrive randomly. Arriving calls are granted service depending on the call's service class, the required maximum and minimum-bandwidth, and the available network resources at the arrival instance. We use a Markov model of transmission links to derive GoS (blocking probability) and QoS (throughput) measures under two reasonable and technologically feasible bandwidth sharing policies. We conclude that one of these policies is able to provide GoS/QoS guarantees for a wide range of traffic mixes. We argue that the results are applicable to the all IP/MPLS based new UMTS architecture.
Initial assessment of the infant with neonatal cholestasis—Is this biliary atresia?

Introduction Optimizing outcome in biliary atresia (BA) requires timely diagnosis. Cholestasis is a presenting feature of BA, as well as other diagnoses (Non-BA). Identification of clinical features of neonatal cholestasis that would expedite decisions to pursue subsequent invasive testing to correctly diagnose or exclude BA would enhance outcomes. The analytical goal was to develop a predictive model for BA using data available at initial presentation. Methods Infants at presentation with neonatal cholestasis (direct/conjugated bilirubin >2 mg/dl [34.2 μM]) were enrolled prior to surgical exploration in a prospective observational multi-centered study (PROBE–NCT00061828). Clinical features (physical findings, laboratory results, gallbladder sonography) at enrollment were analyzed. Initially, 19 features were selected as candidate predictors. Two approaches were used to build models for diagnosis prediction: a hierarchical classification and regression decision tree (CART) and a logistic regression model using a stepwise selection strategy. Results In PROBE April 2004-February 2014, 401 infants met criteria for BA and 259 for Non-BA. Univariate analysis identified 13 features that were significantly different between BA and Non-BA. Using a CART predictive model of BA versus Non-BA (significant factors: gamma-glutamyl transpeptidase, acholic stools, weight), the receiver operating characteristic area under the curve (ROC AUC) was 0.83. Twelve percent of BA infants were misclassified as Non-BA; 17% of Non-BA infants were misclassified as BA. Stepwise logistic regression identified seven factors in a predictive model (ROC AUC 0.89). Using this model, a predicted probability of >0.8 (n = 357) yielded an 81% true positive rate for BA; <0.2 (n = 120) yielded an 11% false negative rate. Conclusion Despite the relatively good accuracy of our optimized prediction models, the high precision required for differentiating BA from Non-BA was not achieved. Accurate identification of BA in infants with neonatal cholestasis requires further evaluation, and BA should not be excluded based only on presenting clinical features.
A KNIME-Based Analysis of the Zebrafish Photomotor Response Clusters the Phenotypes of 14 Classes of Neuroactive Molecules

Recently, the photomotor response (PMR) of zebrafish embryos was reported as a robust behavior that is useful for high-throughput neuroactive drug discovery and mechanism prediction. Given the complexity of the PMR, there is a need for rapid and easy analysis of the behavioral data. In this study, we developed an automated analysis workflow using the KNIME Analytics Platform and made it freely accessible. This workflow allows us to simultaneously calculate a behavioral fingerprint for all analyzed compounds and to further process the data. Furthermore, to further characterize the potential of PMR for mechanism prediction, we performed PMR analysis of 767 neuroactive compounds covering 14 different receptor classes using the KNIME workflow. We observed a true positive rate of 25% and a false negative rate of 75% in our screening conditions. Among the true positives, all receptor classes were represented, thereby confirming the utility of the PMR assay to identify a broad range of neuroactive molecules. By hierarchical clustering of the behavioral fingerprints, different phenotypical clusters were observed that suggest the utility of PMR for mechanism prediction for adrenergics, dopaminergics, serotonergics, metabotropic glutamatergics, opioids, and ion channel ligands.