Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Survival Recommender

The ability to predict future user activity is invaluable when it comes to content recommendation and personalization. For instance, knowing when users will return to an online music service and what they will listen to increases user satisfaction and therefore user retention. We present a model based on Long-Short Term Memory to estimate when a user will return to a site and what their future listening behavior will be. In doing so, we aim to solve the problem of Just-In-Time recommendation, that is, to recommend the right items at the right time. We use tools from survival analysis for return time prediction and exponential families for future activity analysis. We show that the resulting multitask problem can be solved accurately, when applied to two real-world datasets.
Molecular Characterization of Enteric Picornaviruses in Archived Turkey and Chicken Samples from the United States

SUMMARY Recent metagenomic analyses of the enteric viromes in turkeys and chickens have revealed complex viral communities comprised of multiple viral families. Of particular significance are the novel avian picobirnaviruses (family Picobirnaviridae), multiple genera of tailed phages (family Siphoviridae), and undescribed avian enteric picornaviruses (family Picornaviridae). In addition to these largely undescribed—and therefore relatively poorly understood—poultry enteric viral families, these metagenomic analyses have also revealed the presence of well-known groups of enteric viruses such as the chicken and turkey astroviruses (family Astroviridae) and the avian rotaviruses and reoviruses (family Reoviridae). The order Picornavirales is a group of viruses in flux, particularly among the avian picornaviruses, since several new genera have been described recently based upon community analysis of enteric viromes from poultry and other avian species worldwide. Our previous investigation of the turkey enteric picornaviruses suggests the avian enteric picornaviruses may contribute to the enteric disease syndromes and performance problems often observed in turkeys in the Southeastern United States. This report describes our recent phylogenetic analysis of turkey and chicken enteric samples archived at the Southeast Poultry Research Laboratory from 2004 to present and is a first step in placing these novel avian picornaviruses within the larger Picornaviridae family.
A six‐country European survey on consumer attitudes to the metabolic syndrome, genetics in nutrition and potential agro‐food technologies: questionnaire design methodology

Summary The prevalence of overweight, obesity and type 2 diabetes is increasing all over Europe. In order to address this major public health problem and to reverse the situation, effective measures are urgently needed. LIPGENE (http://www.lipgene.tcd.ie; http://www.nutrition.org.uk), an EU Sixth Framework Integrated Project (2004–2009), entitled ‘Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis’, focuses on those strategies. This paper presents the methodology used to develop a questionnaire to provide data on the general population's attitudes towards genetics in nutrition, the metabolic syndrome and potential agro-food technologies in a geographically representative sample of six European countries within LIPGENE. In total, 5967 subjects aged 15 years and above in six European countries (France, Germany, Great Britain, Italy, Poland and Portugal) completed the survey. Their demographic characteristics are also presented.
The Akaike Likelihood Ratio Index

In 1983, Horowitz proposed the use of an adjusted likelihood ratio index to select between alternative models. We define an alternative index based on the Akaike Information Criterion. The two indices incorporate different degrees-of-freedom corrections to the same measure of goodness-of-fit. The Akaike index favors more parsimonious models. We argue that the Akaike measure is the appropriate criterion for model selection. We utilize Horowitz's results on non-nested hypothesis testing for the new index.
The Fastest Path through a Network with Random Time-Dependent Travel Times

This paper introduces the problem of finding the least expected travel time path between two nodes in a network with travel times that are both random and time-dependent (e.g., a truck, rail, air or bus network). It first shows that standard shortest path algorithms (such as the Dijkstra algorithm) do not find the minimum expected travel time path on such a network, then proposes a method which does find the minimum path. Next, this paper shows that the optimal “route choice” is not a simple path but an adaptive decision rule. The best route from any given node to the final destination depends on the arrival time at that node. Because the arrival time is not known before departing the origin, a better route can be selected by deferring the final choice until later nodes are reached. A method for finding the optimal adaptive decision rule is proposed.
Software Engineering Aspects of Green and Sustainable Software: A Systematic Mapping Study

Green and sustainable software engineering is an emerging research field which aims at creating, using, and disposing the energy-efficient software in an environment friendly manner with less negative impacts. The research community strongly believes that the energy efficiency and sustainability of the software can be improved by modifying the existing software engineering methods. This systematic mapping study identifies and map such methods for green and sustainable software development. Especially, this study identifies the research types, research goals, software engineering research topics, accepted validation methods and publication fora that are used in the field of green and sustainable software engineering. This study was conducted with 7 research questions and analyzed 82 relevant studies. We have used snowballing reading to find out the relevant studies that were published from 2010 to May, 2016. One of the important finding of this study is, there are less number of contributions on software design and construction. In future, sufficient research works and tools support must be provided to make this research field more matured. The main contribution of this study is to summarize the body of knowledge in the field of green and sustainable software engineering and provides a platform to conduct future research.
Using Structured Text Source Code Metrics and Artificial Neural Networks to Predict Change Proneness at Code Tab and Program Organization Level

Structured Text (ST) is a high-level text-based programming language which is part of the IEC 61131-3 standard. ST is widely used in the domain of industrial automation engineering to create Programmable Logic Controller (PLC) programs. ST is a Domain Specific Language (DSL) which is specialized to the Automation Engineering (AE) application domain. ST has specialized features and programming constructs which are different than general purpose programming languages. We define, develop a tool and compute 10 source code metrics and their correlation with each-other at the Code Tab (CT) and Program Organization Unit (POU) level for two real-world industrial projects at a leading automation engineering company. We study the correlation between the 10 ST source code metrics and their relationship with change proneness at the CT and POU level by creating experimental dataset consisting of different versions of the system. We build predictive models using Artificial Neural Network (ANN) based techniques to predict change proneness of the software. We conduct a series of experiments using various training algorithms and measure the performance of our approach using accuracy and F-measure metrics. We also apply two feature selection techniques to select optimal features aiming to improve the overall accuracy of the classifier.
Presence of Epstein- Barr Virus in Oral Lichen Planus and Normal Oral Mucosa

Oral lichen planus (OLP) is a chronic immunologic disease. The etiology of OLP is unknown, viral antigens (for example Epstein-Bar virus) have been proposed as etiologic agents. OLP may get transformation to malignancy so re- search on the presence of EBV in OLP lesions seems to be necessary. The aim of this study was to ascertain if EBV acted as etiologic factor in pathogenesis of OLP. Methods: Tissue specimens of 22 patients with clinical diagnosis and histopathological confirmation of OLP were used as case group. And that of 22 persons without OLP served as control group. Polymerase Chain Reaction (PCR) method was used. Each sample was tested twice. Results: All biopsy specimens from patients and controls were negative for EBV presence. Conclusions: In spite of the fact that the presence of EBV in OLP in these two small groups of Iranian population was not confirmed with PCR method, but due to different ideas and reports in this field, proving or disproving of presence or etio- logical role of EBV in OLP is continuously a question and needs to be examined in further studies.
A Decision Support Framework for Airline Flight Cancellations and Delays

Aircraft shortages occasionally occur during day-to-day airline operation due to factors such as unfavorable weather conditions, mechanical problems, and delays in the schedule of incoming flights. Flight controllers need to respond to such shortages on a real-time basis by delaying or cancelling flights, swapping aircraft among scheduled flights, or requesting the usage of surplus aircraft. The choices undertaken aim at minimizing the losses incurred while retaining an operable flight schedule. In this paper, we represent two network models for aiding flight controllers in this complex decision environment. The models represent an attempt at conceptualizing this important and relatively unstudied problem, and form the basis for an evolving decision support system at United Airlines.
Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts

This paper proposes different “dynamic” estimators using time-varying traffic counts to obtain (discrete) time-varying OD flows or average OD flows. All the estimators can combine counts with other available information, e.g., out-dated matrices and surveys, on a general network and can be formulated as optimization problems. In the case of time-varying OD flows, two types of estimators are proposed. Simultaneous estimators produce joint estimates of the whole set of OD matrices, one for each time slice, whereas sequential estimators produce a sequence of OD estimates for successive time slices. A particular type of simultaneous and sequential estimator (namely Generalized Least Squares) was tested on the Italian Brescia–Padua motorway for which “true” OD flows over a whole day were available. Results were generally satisfactory, showing that also in the “no a priori information” case significant estimates could be obtained.
An Exact Algorithm for the Vehicle Routing Problem with Stochastic Demands and Customers

In this article, the following stochastic vehicle routing problem is considered. Each customer has a known probability of presence and a random demand. This problem arises in several contexts, e.g., in the design of less-than-truckload collection routes. Because of uncertainty, it may not be possible to follow vehicle routes as planned. Using a stochastic programming framework, the problem is solved in two stages. In a first stage, planned collection routes are designed. In a second stage, when the set of present customers is known, these routes are followed as planned by skipping the absent customers. Whenever the vehicle capacity is attained or exceeded, the vehicle returns to the depot and resumes its collections along the planned route. This generates a penalty. The problem is to design a first stage solution in order to minimize the expected total cost of the second state solution. This is formulated as a stochastic integer program, and solved for the first time to optimality by means of an integer L-shaped method.
RANAVIRUS EPIZOOTIC IN CAPTIVE EASTERN BOX TURTLES (TERRAPENE CAROLINA CAROLINA) WITH CONCURRENT HERPESVIRUS AND MYCOPLASMA INFECTION: MANAGEMENT AND MONITORING

Abstract Frog virus 3 (FV3) and FV3-like viruses are members of the genus Ranavirus (family Iridoviridae) and are becoming recognized as significant pathogens of eastern box turtles (Terrapene carolina carolina) in North America. In July 2011, 5 turtles from a group of 27 in Maryland, USA, presented dead or lethargic with what was later diagnosed as fibrinonecrotic stomatitis and cloacitis. The presence of FV3-like virus and herpesvirus was detected by polymerase chain reaction (PCR) in the tested index cases. The remaining 22 animals were isolated, segregated by severity of clinical signs, and treated with nutritional support, fluid therapy, ambient temperature management, antibiotics, and antiviral therapy. Oral swabs were tested serially for FV3-like virus by quantitative real-time PCR (qPCR) and tested at day 0 for herpesvirus and Mycoplasma sp. by conventional PCR. With oral swabs, 77% of the 22 turtles were FV3-like virus positive; however, qPCR on tissues taken during necropsy revealed the true prevalence was 86%. FV3-like virus prevalence and the median number of viral copies being shed significantly declined during the outbreak. The prevalence of herpesvirus and Mycoplasma sp. by PCR of oral swabs at day 0 was 55% and 68%, respectively. The 58% survival rate was higher than previously reported in captive eastern box turtles for a ranavirus epizootic. All surviving turtles brumated normally and emerged the following year with no clinical signs during subsequent monitoring. The immediate initiation of treatment and intensive supportive care were considered the most important contributing factors to the successful outcome in this outbreak.
The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem

We introduce the terms dynamic and static, respectively, to identify the prevailing approaches to the single-leg airline yield-management problem: those allowing customers of different fare classes to book concomitantly (dynamic), and those assuming that the demands for the different fare classes arrive separately in a predetermined order (static). We present a coherent frame-work linking these seemingly disparate models through the underlying dynamic program common to both. We develop a discrete-time Markov decision process formulation mirroring that of Janakiram et al. Transp. Sci. 33, 147Â 167 (1999) to solve the single-leg problem without cancellations, overbooking, or discounting. Borrowing a result from the queueing-control literature, we prove the concavity of the associated optimal value functions and, subsequently, the optimality of a booking limit policy. We then apply this same technique to the more influential papers from the single-leg literature, at once unifying the static and dynamic models and establishing the connection between the yield-management and queueing-control problems. Finally, we propose an omnibus formulation that yields the static and dynamic models as special cases.
EagleSense: Tracking People and Devices in Interactive Spaces using Real-Time Top-View Depth-Sensing

Real-time tracking of people's location, orientation and activities is increasingly important for designing novel ubiquitous computing applications. Top-view camera-based tracking avoids occlusion when tracking people while collaborating, but often requires complex tracking systems and advanced computer vision algorithms. To facilitate the prototyping of ubiquitous computing applications for interactive spaces, we developed EagleSense, a real-time human posture and activity recognition system with a single top-view depth-sensing camera. We contribute our novel algorithm and processing pipeline, including details for calculating silhouette-extremities features and applying gradient tree boosting classifiers for activity recognition optimized for top-view depth sensing. EagleSense provides easy access to the real-time tracking data and includes tools for facilitating the integration into custom applications. We report the results of a technical evaluation with 12 participants and demonstrate the capabilities of EagleSense with application case studies.
JUGULAR CENTRAL VENOUS CATHETER PLACEMENT THROUGH A MODIFIED SELDINGER TECHNIQUE FOR LONG-TERM VENOUS ACCESS IN CHELONIANS

Abstract Long-term or repeated venous access in chelonians is difficult to obtain and manage, but can be critically important for administration of medications and blood sampling in hospitalized patients. Jugular catheterization provides the most rapid and secure route for vascular access, but catheters can be difficult to place, and maintaining catheter patency may be challenging. Long multilumen polyurethane catheters provide flexibility and sampling access, and minimize difficulties, such as catheter displacement, that have been encountered with traditional over-the-needle catheters. We describe placement of 4 Fr. 13-cm polyurethane catheters in three chelonians with the use of a modified Seldinger technique. Venous access was obtained with the use of an over-the-needle catheter, which allowed placement of a 0.018-in. -diameter wire, over which the polyurethane catheter was placed. Indwelling time has ranged between 1 and 4 mo currently. All tortoises were sedated for this procedure. Polyurethane central catheters provide safe, long-term venous access that allows clinicians to perform serial blood sampling as well as intravenous administration of medications, anesthetic agents, and fluids. A jugular catheter can also allow central venous pressure measurement. Utilization of central line catheters was associated with improvements in diagnostic efficiency and therapeutic case management, with minimal risks and complications.
NORMAL VAGINAL BACTERIAL FLORA OF GIANT PANDAS (AILUROPODA MELANOLEUCA) AND THE ANTIMICROBIAL SUSCEPTIBILITY PATTERNS OF THE ISOLATES

Abstract In order to study the typical vaginal bacterial flora of giant pandas (Ailuropoda melanoleuca), we took vaginal swabs for the sake of bacterial isolation, from 24 healthy female giant pandas. A total of 203 isolates were identified, representing a total of 17 bacterial species. The most common bacteria isolated were Lactobacillus spp. (54.2%, 13 of 24), followed by Staphylococcus epidermidis (41.7%, 10 of 24) and Escherichia coli (33.3%, 8 of 24). Some opportunistic pathogenic bacteria, such as Peptostreptococcus spp. , Klebsiella pneumoniae, and Proteus mirabilis, were also isolated but showed no pathology. Antimicrobial susceptibility testing of aerobic bacterial isolates was performed with disk diffusion method. Of the 152 isolates, resistance was most frequently observed with chloramphenicol (17.8%), followed by tetracycline (14.5%), ciprofloxacin (12.5%), streptomycin (11.8%), and florfenicol (11.8%), while 7.2% were multidrug resistant. This is the first report of the normal vaginal culturable bacterial flora of giant pandas, followed by the antimicrobial susceptibility patterns of the isolates.
Rerouting Aircraft for Airline Recovery

Disruptions in airline transportation systems can prevent airlines from executing their schedules as planned. Adverse weather conditions, congestion at airports, and mechanical failures often hinder a flight schedule. During such events, decision makers must reschedule flight legs, and reroute aircraft, pilots, and passengers. We present an optimization model that reschedules legs and reroutes aircraft by minimizing an objective function involving rerouting and cancellation costs. We develop a heuristic for selecting which aircraft are rerouted, and we provide proof of concept by evaluating our model using a simulation of airline operations. Finally, we revise the model to minimize crew and passenger disruptions.
DRUG UTILIZATION PATTERN OF ANTIMALARIAL DRUGS AT A TERTIARY CARE HOSPITAL: A RETROSPECTIVE STUDY -

Background of Study: Malaria is the one of most common cause of fever and morbidity in the tropics and a significant source of mortality, especially among infants and young children (2) . So its drug therapy needs to be review. Aim: Evaluate the use of antimalarial agents in treatment of patients admitted to KMC Hospital, Attavar (Mangalore) with a diagnosis of Malaria. Research Methodology: We analyzed the use of antimalarial agents in treatment of patients admitted to KMC Hospital, Attavar (Mangalore) with a diagnosis of Malaria and compared it with the guidelines on Diagnosis and Treatment of Malaria in India which were revised in 2007 by the Ministry of Health of India. A total sample size was 478 and pattern of Uncomplicated and complicated Malarial Parasite Infection was evaluated. Results: 26% of the admitted patients receive a combination of 3 anti-malarial agents, 58% received a combination of 2 antimalarial agents, while only 16% of the patients were managed with monotherapy as part of treatment. Lumefantrine was the most commonly prescribed agent in 86.5% of the patients, followed by Mefloquine 41.1%. Conclusion: There is an increased use of Artemisinin as first line drugs in Mangalore, irrespective of the causative agent for malaria, which is an unhealthy practice. The use of primaquine for all types of malaria
Goodbye Text, Hello Emoji: Mobile Communication on WeChat in China

We present a qualitative study of mobile communication via WeChat in Southern China, focusing on the rapid proliferation of emoji and stickers and the lessening dependence on text. We use interview and observation data from 30 participants to investigate how rural, small town, and urban Chinese adults creatively and innovatively balance the use of emoji, stickers, and text in their mobile communication practices. We also discuss design implications of our research for the field of HCI, offering ways of leveraging the non-textual communication practices that we uncover, in scenarios where purely text-based communication may not suffice.
Feldvalidierung einer real-time PCR zum Nachweis von Mycoplasma hyopneumoniae in Nasentupfermaterial von lebenden Schweinen

Enzootic pneumonia (EP) of pigs, caused by Mycoplasma hyopneumoniae has been a notifiable disease in Switzerland since May 2003. The diagnosis of EP has been based on multiple methods, including clinical, bacteriological and epidemiological findings as well as pathological examination of lungs (mosaic diagnosis). With the recent development of a real-time PCR (rtPCR) assay with 2 target sequences a new detection method for M. hyopneumoniae became available. This assay was tested for its applicability to nasal swab material from live animals. Pigs from 74 herds (average 10 pigs per herd) were tested. Using the mosaic diagnosis, 22 herds were classified as EP positive and 52 as EP negative. From the 730 collected swab samples we were able to demonstrate that the rtPCR test was 100% specific. In cases of cough the sensitivity on herd level of the rtPCR is 100%. On single animal level and in herds without cough the sensitivity was lower. In such cases, only a positive result would be proof for an infection with M. hyopneumoniae. Our study shows that the rtPCR on nasal swabs from live pigs allows a fast and accurate diagnosis in cases of suspected EP.