Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of early versus deferred antiretroviral therapy for HIV on survival.

BACKGROUND The optimal time for the initiation of antiretroviral therapy for asymptomatic patients with human immunodeficiency virus (HIV) infection is uncertain. METHODS We conducted two parallel analyses involving a total of 17,517 asymptomatic patients with HIV infection in the United States and Canada who received medical care during the period from 1996 through 2005. None of the patients had undergone previous antiretroviral therapy. In each group, we stratified the patients according to the CD4+ count (351 to 500 cells per cubic millimeter or >500 cells per cubic millimeter) at the initiation of antiretroviral therapy. In each group, we compared the relative risk of death for patients who initiated therapy when the CD4+ count was above each of the two thresholds of interest (early-therapy group) with that of patients who deferred therapy until the CD4+ count fell below these thresholds (deferred-therapy group). RESULTS In the first analysis, which involved 8362 patients, 2084 (25%) initiated therapy at a CD4+ count of 351 to 500 cells per cubic millimeter, and 6278 (75%) deferred therapy. After adjustment for calendar year, cohort of patients, and demographic and clinical characteristics, among patients in the deferred-therapy group there was an increase in the risk of death of 69%, as compared with that in the early-therapy group (relative risk in the deferred-therapy group, 1.69; 95% confidence interval [CI], 1.26 to 2.26; P<0.001). In the second analysis involving 9155 patients, 2220 (24%) initiated therapy at a CD4+ count of more than 500 cells per cubic millimeter and 6935 (76%) deferred therapy. Among patients in the deferred-therapy group, there was an increase in the risk of death of 94% (relative risk, 1.94; 95% CI, 1.37 to 2.79; P<0.001). CONCLUSIONS The early initiation of antiretroviral therapy before the CD4+ count fell below two prespecified thresholds significantly improved survival, as compared with deferred therapy.
AGENT-BASED DISPATCHING ENABLES AUTONOMOUS GROUPAGE TRAFFIC 1

The complexity and dynamics in groupage traffic require flexible, efficient, and adaptive planning and control processes. The general problem of allocating orders to vehicles can be mapped into the Vehicle Routing Problem (VRP). However, in practical applications additional requirements complicate the dispatching processes and require a proactive and reactive system behavior. To enable automated dispatching processes, this article presents a multiagent system where the decision making is shifted to autonomous, interacting, intelligent agents. Beside the communication protocols and the agent architecture, the focus is on the individual decision making of the agents which meets the specific requirements in groupage traffic. To evaluate the approach we apply multiagent-based simulation and model several scenarios of real world infrastructures with orders provided by our industrial partner. Moreover, a case study is conducted which covers the autonomous groupage traffic in the current processes of our industrial parter. The results reveal that agent-based dispatching meets the sophisticated requirements of groupage traffic. Furthermore, the decision making supports the combination of pickup and delivery tours efficiently while satisfying logistic request priorities, time windows, and capacity constraints.
Investigating the heterodimerization process among receptors by Monte Carlo cellular automaton simulation

It has become well known that simulation can be used to investigate complex biomedical systems in situations where traditional methodologies are difficult or too costly to be used. In this paper, Monte Carlo cellular automaton simulation is employed to study heterodimerization of receptor proteins. A computer program, based on a simple random walk of receptor molecules over a fixed lattice, has been written to simulate the diffusion and association of receptors over a two-dimensional membrane. The interaction and dynamics of these particles is in the form of the lattice Hamiltonian. The formation of two-dimensional clusters of receptors in a defined area of surface membrane is investigated. In particular, we measure the number of dimers throughout the dynamics and try to define the power law that governs the process. Keywords—Monte Carlo simulation, heterodimerization, membrane receptors, signal transduction.
Analgesic activity of Leea indica (Burm. f.) Merr

The analgesic potential of Leea indica (Burm. f.) Merr. , a Bangladeshi tribal medicinal plant was studied for the first time. Despite the progress that has occured in recent years in the development of therapy, there is still a need for effective and potent analgesics, especially for the treatment of chronic pain. One of the most important analgesic drugs employed in clinical practice today continues to be the alkaloid morphine. Analgesic potential of L. indica was evaluated for centrally acting analgesic property using formalin induced licking response model and peripheral pharmacological actions using acetic acid-induced writhing test. In acetic acid-induced writhing test, ethanolic extracts at 200 mg/kg dose exhibited significant (p<0.05) reduction of writhing response in a dose dependent manner; in formalin induced licking response model a significant (p < 0.05 0.001) result was comparable to the standard drug diclofenac sodium. From the results it was concluded that both extracts exhibited anti-nociceptive activity by central and peripheral mechanism(s). Plant-derived substances have, and will certainly continue to have, a relevant place in the process of drug discovery, particularly in the development of new analgesic drugs.
Arbitrage Pricing Theory Modelling of Microfinance Institutions Financial Performance in Kenya

Microfinance is the provision of a broad range of financial services such as deposits, loans, payment services, money transfers and insurance to the poor and low-income households and their micro enterprises. The sector reaches out to 832,794 active borrowers with a loan book amounting to Kshs.28. 6 billion and reporting 26.4 % annual growth in Kenya. However, owing to the fact that there is limited literature on the determinants of financial performance, various studies conducted indicate divergent views on the effect of financial indicators on financial performance. For this reasons it is not clear whether or not financial indicators affect financial performance of microfinance institutions (MFIs) in Kenya. The study was modeled on the Arbitrage pricing Theory and correlation research design adopted. Target population comprised 12 registered MFIs. Sample size consisted a panel data set of 12 MFIs selected using purposing sampling method for the period from 2009 to 2013 and secondary data was collected. Fixed effect model was the preferred model based on the Hausman specification but the study used random effect model since fixed effect model gave insignificant results. Breusch pagan LM test of heteroscedasticity in random effects was conducted to test if the variance of the residual term will be constant over different values of the explanatory variables. Random effect model results revealed that debt to equity ratio had a negative but insignificant relationship with return on assets ratio. Portfolio to assets ratio had a positive relationship with financial performance but the relationship was not significant. Operating expense ratio had negative and significant relationship with return to assets ratio. The coefficient for lagged return to assets ratio was 0.4733, debt to equity ratio was -0.0026, portfolio to assets ratio was 0.0090 and coefficient for operating expense ratio was -0.1857. Pvalues for DER was 0.878 , PAR, 0.686 and OER, 0.000. The results for lagged ROA the coefficient was positive and was statistically significant. Autoregressive distributed lag model on debt to equity ratio preferred model random effect model findings postulated that debt to equity ratio had positive and significant relationship with return to assets ratio. Lagged DER had positive and significant relationship with return to assets ratio. ARDL model on portfolio to assets ratio preferred model random effect findings revealed that PAR had positive and insignificant relationship with return to assets ratio. Lagged PAR had positive and significant relationship with return to assets ratio. ARDL model on operating expense ratio and preferred model fixed effect model showed that OER had negative and significant relationship with return to assets ratio. The lagged OER had positive and insignificant relationship with return to assets ratio.
Fetale Anämie – Diagnostik, Therapie und Management

Das perinatale Outcome von anämischen Feten hat sich in den letzten Jahren erheblich verbessert. Mittels Titerkontrollen, Abschätzen des fetalen Anämiegrads durch DopplerSonografie und Messung der Spitzenflussgeschwindigkeit der A. cerebri media als nicht invasivem und damit risikolosem Verfahren, sowie der Möglichkeit der intrauterinen Behandlung durch Nabelschnurbluttransfusion können letale Verläufe heute in den meisten Fällen vermieden werden. Anämische Feten können so noch vor dem Auftreten eines Hydrops, was mit einer signifikant schlechteren Prognose vergesellschaftet ist, rechtzeitig erkannt und im weiteren Schwangerschaftsverlauf engmaschig überwacht und gegebenenfalls therapiert werden. In dieser Arbeit wird ein Überblick über die Ursachen der fetalen Anämie, die Diagnostik und Überwachung dieser Risikoschwangerschaft sowie über die therapeutischen Möglichkeiten und das fetale Outcome gegeben.
PII: S0191-8869(99)00123-3

In large samples of American armed forces veterans, those below the ®rst percentile and above the 99th percentile in serum testosterone level show signi®cantly and considerably lower g factor scores derived from a battery of 19 diverse psychometric variables. Between these extremes of testosterone level, however, there is little relationship between testosterone and psychometric g. Factors orthogonal to g were also aected only at the extremes of testosterone level. # 2000 Elsevier Science Ltd. All rights reserved.
Bayes-optimal Classification Model Classification Prediction :   Class 0 Attacks Prediction :   Class

{ethanf, jjacobs,wgrathwohl, zemel}@cs.toronto. edu Class-conditional generative models hold promise to overcome the shortcomings of their discriminative counterparts. They are a natural choice to solve discriminative tasks in a robust manner as they jointly optimize for predictive performance and accurate modeling of the input distribution. In this work, we investigate robust classification with likelihood-based generative models from a theoretical and practical perspective to investigate if they can deliver on their promises. Our analysis focuses on a spectrum of robustness properties: (1) Detection of worst-case outliers in the form of adversarial examples; (2) Detection of average-case outliers in the form of ambiguous inputs and (3) Detection of incorrectly labeled in-distribution inputs. Our theoretical result reveals that it is impossible to guarantee detectability of adversarially-perturbed inputs even for near-optimal generative classifiers. Experimentally, we find that while we are able to train robust models for MNIST, robustness completely breaks down on CIFAR10. We relate this failure to various undesirable model properties that can be traced to the maximum likelihood training objective. Despite being a common choice in the literature, our results indicate that likelihood-based conditional generative models may are surprisingly ineffective for robust classification.
Redacted for privacy

approved:_ ________ ary . Taghon In September of 1989, the site of an active seafloor methane vent was confirmed approximately 20 km off the coast of Oregon in shelf waters 135 m deep. The location of the vent had been described to Oregon State University oceanographers by a local commercial fisherman. Preliminary observations in 1989 suggested that biological activity near the vent was high. In analogy to other known venting phenomena, it was proposed that the methane served as an energy source fueling enhanced biological productivity. This thesis addresses this hypothesis as a portion of a larger project which investigates the biology, geology and chemistry of shallow-water methane vents on the Oregon shelf. The data presented within are the results of a second oceanographic cruise to the site in September, 1990. Samples of benthic and pelagic organisms were collected near the vent and compared to collections from background sites in terms of quantitative abundance of organisms, qualitative community composition and ratios of the stable isotopes of C, N, and S. The stable isotope analyses indicate that a significant fraction of vent methane-derived carbon is present in most samples collected near the vent. Despite this, there does not appear to be a major impact on the abundance of any organisms sampled. Several hypotheses are put Redacted for privacy forward which might explain these results. The findings at this site are compared to what is known about other types of seafloor vents and seeps.
Adversarially learned anomaly detection for time series data

Anomaly detection in time series data is an important topic in many domains. However, time series are known to be particularly hard to analyze. Based on the recent developments in adversarially learned models, we propose a new approach for anomaly detection in time series data. We build upon the idea to use a combination of a reconstruction error and the output of a Critic network. To this end we propose a cycle-consistent GAN architecture for sequential data and a new way of measuring the reconstruction error. We then show in a detailed evaluation how the different parts of our model contribute to the final anomaly score and demonstrate how the method improves the results on several data sets. We also compare our model to other baseline anomaly detection methods to verify its performance.
An Approach for Personalized Social Inter- actions Between a Therapeutic Robot and Children with Autism Spectrum Disorder

For high-variability populations, such as individuals with Autism Spectrum Disorders (ASD), the importance of personalization and adaptation mechanisms in Human-Robot Interaction becomes crucial. This technical report presents an algorithmic method for personalization of robotic behavior in structured social interactions with ASD children, based on state-of-the-art diagnostic models. In a first step, we leverage the structure of the diagnostic procedure to build robotic behaviors on a NAO humanoid robot, aimed at eliciting target behaviors from the child. Through appropriate sequencing of possible actions, the robot is able to assess a child’s behavioral profile and use it to personalize the interaction. To test our method, we developed a semi-autonomous robotic scenario where a humanoid robot interacts with a child with ASD through interactive storytelling, focusing on social prompts related to deficits in attention, one of the core impairments of ASD. We present the design and methodology of an evaluation study run with 11 young ASD children in a child development center in Portugal.
Prediction of overwash in alongshore variable barrier islands Previsão da ocorrência de galgamentos em ilhas barreira com variabilidade longilitoral

Overwash prediction is very important for coastal zone management. This work intends to identify alongshore variations in storm impact and evaluate the role of sub-aerial and submerged morphologies in overwash occurrence. For this study, 24 cross-shore topo-bathymetric profiles were set on Barreta Island (Ria Formosa barrier island system, Portugal). Preand post-overwash surveys were made between August 2012 and April 2013. During overwash events, tidal levels and wave parameters at breaking were obtained. Overwash occurred under storm and non-storm conditions, the latter coincident with spring high-tide. Beach morphology was spatially variable, and changeable from one overwash episode to the next. Predictions of overwash occurrence were made using the Overwash Potential, defined as the difference between runup and barrier elevation. Several runup equations were tested, and the results compared to the actual observations. The selected predictor provided an accuracy of 88% for the identification of the locations where overwash occurred. This study proves that nearshore and foreshore morphologies have a major impact on the longshore distribution of overwash.
ALGORITHM FORMULATION OF MODIFIED IWD MODEL FOR MEB PROBLEM

In this paper, Algorithm formulation of modified IWD model for MEB problem in WSN. The proposed methodology incorporates a heuristic method in it for solving the MEB problem. the potential technique considers the highly qualified nodes to participate in the cluster head formation. Participation of such potential nodes in the population the problem can be solved in the given time.The second phase imposes the diversification factor in the proposed Modified IWD. The primary objective for proposing a diversification factor is because without the diversification factor the algorithm converges towards any local optimal solution. In such cases the Modified IWD algorithm in turn returns the local optimal values even after n number of iterations and over many cycles. In order to solve the exploration issues a new diversification factor has been incorporated.
Antimicrobial Resistance Factors of Extended-Spectrum Beta-Lactamases Producing Escherichia coli and Klebsiella pneumoniae Isolated from Cattle Farms and Raw Beef in North-West Province, South Africa

Background Extended spectrum beta-lactamases (ESBLs) producing Enterobacteriaceae cause severe infections in humans which leads to complicated diseases. There is increasing evidence that cattle contribute to the development and spread of multidrug resistant pathogens and this raises public health concern. Despite this, data on the concurrence of ESBL producing pathogens in cattle, especially in the North-West province are rare. Therefore, the aim of the present study was to isolate, identify and characterise ESBL producing E. coli and K. pneumoniae species from cattle faeces and raw beef samples. Results A total of 151 samples comprising 55 faeces samples and 96 raw beef samples were collected and 259 nonreplicative potential isolates of Enterobacteriaceae were obtained. One hundred and ninety-six isolates were confirmed as E. coli (114; 44%) and K. pneumoniae (82; 32%) species through amplification of uspA and uidA and ntrA gene fragments, respectively. Antimicrobial susceptibility test revealed that large proportions (66.7–100%) of the isolates were resistant to Amoxicillin, Aztreonam, Ceftazidime, Cefotaxime, and Piperacillin and were multidrug resistant isolates. Cluster analysis of antibiotic inhibition zone diameter data revealed close similarities between isolates from different sources or species thus suggested a link in antibiotic exposures. The isolates showing phenotypic resistance against ESBL antimicrobial susceptibility tests were screened for the presence of ESBL gene determinants. It was observed that 53.1% of the isolates harboured ESBL gene determinants. The blaTEM, blaSHV and blaCTX-M genes were detected in E. coli isolates (85.5%, 69.6%, and 58%, respectively) while blaCTX-M and blaOXA were detected in K. pneumoniae (40% and 42.9%, respectively). All the genetically confirmed ESBL producing E. coli and K. pneumoniae isolates were subjected to Enterobacterial Repetitive Intergenic Consensus (ERIC) PCR analysis. Fingerprinting data revealed great similarities between isolates from different areas and sources which indicates cross-contamination between cattle and beef. Conclusion This study revealed that cattle and its associated food products, beef in particular, harbour ESBL producing pathogens. And this warrants a need to enforce hygiene measures and to develop other mitigation strategies to minimise the spread of antibiotic resistant pathogens from animals to human.
Effective Leadership Theory Cases and Applications 1st Edition Humphrey Test Bank

*a. the right candidates—leaders whose personalities and attitudes make them a good fit for Southwest Airlines’ fun, team-based culture b. average people, yet he made these average people stars by treating them right c. people rejected by the other airlines (who could afford to pay higher salaries), yet by good training he was able to bring these below average performers up to par d. his friends and the friends of the people who already worked at Southwest, thus creating a friendly atmosphere
Automated Speech Recognition Technology to Support in Flight Weather-Related Communication for GA Pilots

Weather information latency during flight in general aviation (GA) has resulted in numerous incidents. Hands-free automated speech recognition (ASR) systems have the potential to help overcome this challenge and facilitate rapid weatherrelated information exchange. However, it is unclear to what extent ASR systems can support pilot communication in such noisy environments. The goals of this study were to (1) evaluate the performance of 7 commercially-available ASR systems to recognize weather phrases during GA operations and (2) determine whether speech-to-noise (S/N) ratio, flight phase, and accent type modulate system performance. Overall, the highest accuracy percentage achieved by any system was 72%, when the S/N ratio was at least 3/2. This research can help to inform the selection and development of next-generation technologies to be used in safety-critical, information-rich domains.
Climatological Analysis of Aerosols Optical Properties by Airborne Sensors and in Situ Measurements in West Africa: Case of the Sahelian Zone

This paper deals with the climatology of aerosols in West Africa based on satellite and in situ measurements between 2001 and 2016 and covers four sites in the Sahelian zone. There are indeed Banizoumbou (13.541°N, 02.665°E), Cinzana (13.278°N, 05.934°W), Dakar (14.394°N, 16.959°W) and Ouagadougou (12.20°N, 1.40°W) located respectively in Niger, Mali, Senegal and Burkina Faso. Thus, an intercomparison between the satellite observations and the in situ measurements shows a good correlation between MODIS and AERONET with a correlation coefficient R = 0.86 at Cinzana, R = 0.85 at Banizounbou, R = 0.84 at Ouagadougou and a low correlation coefficient R = 0.66 calculated on the Dakar site. Like MODIS, SeaWiFS shows a very good correspondence with measurements of the ground photometer especially for Banizoumbou (R = 0.89), Cinzana (R = 0.88) and Dakar (R = 0.75) followed by a low correlation coefficient calculated on the Ouagadougou site (R = 0.64). The performance of these airborne sensors is also corroborated by the calculation of root mean square error (RMSE) and the mean absolute error (MAE). Following this validation, a climatological analysis based on aerosol optical depth (AOD) shows the seasonality of aerosols in West Africa strongly influenced by the climate dynamics illustrated by the MERRA model reanalysis. This seasonal spatial distribution of aerosols justifies the temporal variability of the particles observed at the different sites in the Sahel. In addition, a combined analysis of AOD and Angstrom coefficient indicates the aerosol period in the Sahel in spring (March-April-May) and summer (June-July-August). However, these aerosols are strongly dominated by desert dust whose main sources are located north in the Sahara and Sahel.
OTT_A_209937 9685..9696

1Department of Blood Transfusion, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 2Department of Cardiology, Heilongjiang Red Cross Hospital, Harbin, People’s Republic of China; 3Department of Laboratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 4Department of Hematology, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China; 5Ethics Committee, The Tumor Hospital Affiliated to Harbin Medical University, Harbin, People’s Republic of China