Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiogram of Extended Spectrum Beta-lactamase (ESBL) producing Escherichia coli and Klebsiella pneumoniae isolated from Hospital Samples

Extended spectrum beta-lactmase (ESBL) producing organisms create a major problem for clinical therapeutics. The frequency of ESBL producing strains among clinical isolates has been steadily increasing over the past few years resulting in limitation of the therapeutic options. These resistant bacteria are emerging world wide as a threat to human health in both the community and hospital settings. -lactamase production by several organisms is the most important mechanism of resistance to beta-lactam antibiotics, such as penicillins and cephalosporins. This study was done to determine the susceptibility of different antimicrobials to ESBL producing Escherichia coli and Klebsiella pneumoniae isolated from wound swabs, blood, urine, fluid, tracheal aspirates and sputum in Shahid Bahonar Hospital of Tehran from July, 2007 to June, 2008. A total of 115 ESBLproducing isolates were obtained from outdoor and indoor patients. Out of 115 isolates, 60% were E. coli and 40% were K. pneumoniae. All ESBL-producing isolates were confirmed using the Clinical and Laboratory Standards Institute (CLSI)-approved double-disk diffusion method. 29.6% of these isolates were collected from medical wards and 24.3% were collected from outdoor. Urine (70.4%) was the main source of ESBL-producing isolates from all patients, followed by blood (16.5%). All isolates were susceptible to both imipenem and meropenem. Of all isolates, 93.9% were susceptible to amikacin. The cephalosporins (1-4 generations) were almost 100% resistant. For Nitrofurantoin, 57.4% were sensitive. High rate resistance (74.8%) was observed to all quinolones tested. Aztreonam, Ampicillin, Co-amoxyclav and Ampicillin/Sulbactam were 100% resistant. This study shows that the frequency of ESBL producing strains of E. coli and K. pneumoniae is high in both hospital and community levels and it has a significant implication for patients’ management. Advance drug resistance surveillance and molecular characteristics of ESBL isolates is necessary to guide the appropriate and judicious antibiotic use. Key words: Extended spectrum beta-lactamase (ESBL), Drug sensitivity, Escherichia coli, Klebseilla pneumoniae DOI: http://dx.doi. org/10.3329/bjmm.v4i1. 8467 BJMM 2011; 4(1): 32-36
Checking treebank consistency to find annotation errors

This report describes a tool which helps checking the consistency of syntactic annotation in treebanks. Such annotation usually groups words in a sentence into phrases (e.g. NP, VP, etc), often also specifying the syntactic functions (e.g. subject, object etc) of the words in the phrases. Most of the annotation work is done manually, the number of different annotators can be large, their familiarity with the underlying linguistic theory can be different, and the theory itself is likely to be modified as new texts (of different nature and unpredicted challenges) are introduced. Therefore, the treebank can come out erroneous. Errors in the annotation can be signalled by the inconsistency of the annotation. E.g. if the same sequence of words is annotated differently in different sentences, then it might mean that the annotator has made a mistake. Our intention here is not to provide one single mechanism for treebank consistency checking. Instead, we describe a tool that can be used in many different ways which could reveal inconsistencies in the treebank. The exact usage has to be determined by the linguist in charge of checking the treebank. Note that the approach presented here is likely to be a bit specific to checking the NEGRA corpus, as this corpus has been our main test suite.
Learning to Transfer PrivilegedRanking Attribute for Object Classification

Learning Using Privileged Information (LUPI) provides an efiective framework to solve the learning problem under situation of the asymmetric distribution of information between training and test time. It has been successfully applied in the category recognition, e.g., protein classiflcation, hand-writing recognition, animal categorization, etc. However, in the existing methods, various semantic attributes, with the help of experts, were only simply translated into the feature vectors and considered as the privileged data, which restricts the LUPI to the simple applications since it is di‐cult to guarantee that the privileged data is similarly informative about the problem at hand as the original data. Therefore, this paper presents a novel approach based on an attribute-ranking learning algorithm to construct the example-oriented privileged data. The main idea is to provide an efiective means to transfer the midlevel semantic attributes to the original training data. Namely, we flrst obtain a real-valued rank per attribute for each example indicating the relative strength of the attribute presence in all examples, and then the resulting attribute ranking results are used to generate the privileged data. The experimental results show that the proposed approach provides a promising means to apply the privileged ranking attributes, and further demonstrate signiflcant improvements in classiflcation accuracy on three typical databases: PubFig, OSR and AwA.
Genera of the Asian Catfish Families Sisoridae and Erethistidae (Teleostei: Siluriformes)

4 Introduction . 4 Methods . 6 Erethistidae Bleeker, 1862 . 7 Ayarnangra Roberts, 2001 . 8 Caelatoglanis Ng & Kottelat, 2005 . 10 Conta Hora, 1950 . 12 Erethistes Müller & Troschel, 1849 . 13 Erethistoides Hora, 1950 . 17 Pseudolaguvia Misra, 1976 . 20 Species incertae sedis . 23 Sisoridae Bleeker, 1858 . 23 A. Sisorinae Bleeker, 1858 . 26 Bagarius Bleeker, 1853 . 26 Gagata Bleeker, 1858 . 29 Gogangra Roberts, 2001 . 33 Nangra Day, 1877 . 34 Sisor Hamilton, 1822 . 37 B. Glyptosterninae Gill, 1872; Glyptothoracini de Pinna, 1996 . 39 Glyptothorax Blyth, 1860 . 40 C. Glyptosterninae Gill, 1872; Pseudecheneidina de Pinna, 1996 . 58 Pseudecheneis Blyth, 1860 . 58 D. Glyptosterninae Gill, 1872; Glyptosternina Gill, 1872 . 61 Euchiloglanis Regan, 1907 . 63 Exostoma Blyth, 1860 . 65 Glaridoglanis Norman, 1925 . 67
Complete sequence analysis of human norovirus GII.17 detected in South Korea

Abstract Norovirus, a major cause of gastroenteritis in people of all ages worldwide, was first reported in South Korea in 1999. The most common causal agents of pediatric acute gastroenteritis are norovirus and rotavirus. While vaccination has reduced the pediatric rotavirus infection rate, norovirus vaccines have not been developed. Therefore, prediction and prevention of norovirus are very important. Norovirus is divided into genogroups GI–GVII, with GII.4 being the most prevalent. However, in 2012–2013, GII.17 showed a higher incidence than GII.4 and a novel variant, GII.P17-GII.17, appeared. In this study, 204 stool samples collected in 2013–2014 were screened by reverse transcriptase-polymerase chain reaction; 11 GI (5.39%) and 45 GII (22.06%) noroviruses were identified. GI.4, GI.5, GII.4, GII.6 and GII.17 were detected. The whole genomes of the three norovirus GII.17 were sequenced. The whole genome of GII.17 consists of three open reading frames of 5109, 1623 and 780 bp. Compared with 20 GII.17 strains isolated in other countries, we observed numerous changes in the protruding P2 domain of VP1 in the Korean GII.17 viruses. Our study provided genome information that might aid in epidemic prevention, epidemiology studies and vaccine development.
GIP: A Gene network-based integrative approach for Inferring disease-associated signaling Pathways

Dysregulation or crosstalk of signal transduction pathways contributes to disease development. Despite the initial success of identifying causal links between source and target proteins in simple or well-studied biological systems, it remains challenging to investigate alternative pathways specifically associated with a disease. We develop a Gene network-based integrative approach for Inferring disease-associated signaling Pathways (GIP). Specifically, we identify alternative pathways given source and target proteins. GIP was applied to human breast cancer data. Experimental results showed that GIP identified biologically meaningful pathway modules associated with antiestrogen resistance.
Parallel accumulation – serial fragmentation combined with data-independent acquisition (diaPASEF): Bottom-up proteomics with near optimal ion usage

Data independent acquisition (DIA) modes isolate and concurrently fragment populations of different precursors by cycling through segments of a predefined precursor m/z range. Although these selection windows collectively cover the entire m/z range, overall only a few percent of all incoming ions are sampled. Making use of the correlation of molecular weight and ion mobility in a trapped ion mobility device (timsTOF Pro), we here devise a novel scan mode that samples up to 100% of the peptide precursor ion current. We extend an established targeted data extraction workflow by including the ion mobility dimension for both signal extraction and scoring, thereby increasing the specificity for precursor identification. Data acquired from whole proteome digests and mixed organism samples demonstrate deep proteome coverage and a very high degree of reproducibility as well as quantitative accuracy, even from 10 ng sample amounts.
Development of a Hardware-in-the-Loop Simulator for the Vehicle-Following System in a Virtual 3D Environment

In order to verify the vehicle tracking and path tracking performances of the vehicle following system,a vehicle dynamic model is presented to perform the longitudinal and lateral position errors with respect to the target vehicle and road.Additionally,a real-time vehicle following experimental platform is developed,which is based on the hardware-in-the-loop and virtual reality technologies.Its hardware and software components,which include the steering wheel,a real-time controller board,a graphics display generator and a 3D virtual reality toolbox,are integrated together to realize the hardware-in-the-loop simulation.This platform is successfully utilized for simulating vehicle following tests in several driving conditions like velocity changing and road curvature changing.The influence of human factors on the vehicle following system is considered too.The experimental results obtained show that the hardware-in-the-loop simulator combined with the virtual reality technology provides an effective and safe method for the verification of the overall performances of the vehicle following system before conducting actual vehicle road tests.
Generalization accuracy of probabilistic neural networks compared with backpropagation networks

The authors demonstrate that probabilistic neural networks (PNN) and backpropagation networks (BPN) generalize comparably for a wide variety of low- and high-dimensional artificial databases. A training time advantage is most important when exploring new databases and preprocessing techniques to determine classification accuracies for potential applications. Since it is demonstrated that classification accuracy can be determined equally well using either PNN and BPN, it is advantageous to use PNN for this stage of a classification project. It is during this phase that most of the effort goes into training a network and a relatively small amount of effort goes into testing and evaluating the accuracy of the network. The PNN is based on the Bayes strategy for decision making and Parzen window estimation, and is asymptotically Bayes-optimal within a given feature space. <<ETX>>
Détection de la présence humaine par vision

Les travaux presentes dans ce manuscrit traitent de la detection de personnes dans des sequences d’images et de l’analyse de leur activite. Ces travaux ont ete menes au sein de l’institut PRISME dans le cadre du projet CAPTHOM du pole de competitivite S2E2. Apres un etat de l’art sur l’analyse de sequences d’images pour l’interpretation automatique de scenes et une etude comparative de modules de video-surveillance, nous presentons la methode de detection de personnes proposee dans le cadre du projet CAPTHOM. Celle-ci s’articule autour de trois etapes : la detection de changement, le suivi d’objets mobiles et la classification. Chacune de ces etapes est decrite dans ce manuscrit. Ce systeme a ete evalue sur une large base de videos correspondant a des scenarios de cas d’usage de CAPTHOM etablis par les partenaires du projet. Ensuite, nous presentons des methodes permettant d’obtenir, a partir du flux video d’une ou deux cameras, d’autres informations de plus haut-niveau sur l’activite des personnes detectees. Nous presentons tout d’abord une mesure permettant de quantifier leur activite. Ensuite, un systeme de stereovision multi-capteurs combinant une camera infrarouge et une camera visible est utilise pour augmenter les performances du systeme de detection mais aussi pour permettre la localisation dans l’espace des personnes et donc acceder a une cartographie de leurs deplacements. Finalement, une methode de detection d’evenements anormaux, basee sur des statistiques de distributions spatiales et temporelles des pixels de l’avant-plan est detaillee. Les methodes proposees offrent un panel de solutions performantes sur l’extraction d’informations haut-niveau a partir de sequences d’images.
EFFECTS OF UNRELIABLE AUTOMATION ON DECISION MAKING IN COMMAND AND CONTROL

The effectiveness of automated decision aids used by human operators in command and control systems may depend not only on automation reliability, but also on the type (stage) and level the automated support provides. Automation can be applied to information acquisition, information integration and analysis, decision choice selection, or action implementation (Parasuraman, Sheridan, & Wickens, 2000). The present study examined the effects of variations in the stage of automation support on performance in a “Sensor to Shooter” targeting simulation of command and control. Independent variables included the type and level of automation support (complete listing, priority listing, top choices, and recommendation of decision choice) and the reliability of the automation (60% and 80%). Dependent variables included accuracy and reaction time of target engagement decisions. Compared to manual performance, reliable automation did not affect the accuracy of target engagement decisions but did significantly reduce decision times. When the automation was unreliable, under the higher reliability condition (80%) there was a greater cost in accuracy performance for higher levels of automation aiding (priority listing, top choice, and recommendation) than at a lower level (complete listing). The results support the view that automation unreliability has a greater performance cost for decision automation than for information automation. This performance cost generalizes across a number of different forms of decision-aiding.
Towards an integrated CORBA/RAISE Semantic Interoperable Environment

UNU/IIST UNU/IIST enables developing countries to attain self-reliance in software technology by: (i) their own development of high integrity computing systems, (ii) highest level postgraduate university teaching, (iii) international level research, and, through the above, (iv) use of as sophisticated software as reasonable. UNU/IIST contributes through: (a) advanced, joint industry{university advanced development projects in which rigorous techniques supported by semantics-based tools are applied in case studies to software systems development, (b) own and joint university and academy institute research in which new techniques for (1) application domain and computing platform modelling, (2) requirements capture, and (3) software design & programming are being investigated, (c) advanced, postgraduate and post-doctoral level courses which typically teach Design Calculi oriented software development techniques, (d) events panels, task forces, workshops and symposia], and (e) dissemination. Application-wise, the advanced development projects presently focus on software to support large-scale infrastructure systems such as transport systems (railways, airlines, air traac, etc.), manufacturing industries , public administration, telecommunications, etc., and are thus aligned with UN and International Aid System concerns. UNU/IIST is a leading software technology centre in the area of infrastructure software development. UNU/IIST is also a leading research centre in the area of Duration Calculi, i.e. techniques applicable to real-time, reactive, hybrid & safety critical systems. The research projects parallel and support the advanced development projects. At present, the technical focus of UNU/IIST in all of the above is on applying, teaching, researching , and disseminating Design Calculi oriented techniques and tools for trustworthy software development. UNU/IIST currently emphasises techniques that permit proper development steps and interfaces. UNU/IIST also endeavours to promulgate sound project and product management principles. UNU/IIST's primary dissemination strategy is to act as a clearing house for reports from research and technology centres in industrial countries to industries and academic institutions in developing countries. At present more than 200 institutions worldwide contribute to UNU/IIST's report collection while UNU/IIST at the same time subscribes to more than 125 international scientiic and technical journals. Information on reports received (and produced) and on journal articles is to be disseminated regularly to developing country centres | which are then free to order a reasonable number of report and article copies from UNU/IIST. Abstract The report describes the concept of an integrated CORBA/RAISE environment for addressing problems in the semantic-based reuse of distributed CORBA-compliant software. Such environment could support a highly conndent reasoning about re-usability and consistent composability of …
Evaluation of apical foramen distance in relation to the anatomical apex of mandibular molars by cone-beam computed tomography (CBCT) in a selected Iranian population

Introduction: Knowledge of the internal anatomy and apical foramen of a tooth has always been a fundamental prerequisite for root canal therapy. Aim of the present study was to evaluate the distance of apical foramen in relation to the anatomical apex of mandibular molars by cone beam computed tomography (CBCT) in a selected Iranian population. Material & Methods: In this crosssectional study, 97 CBCT images of 25-50 years old patients were evaluated . the teeth were assessed in coronal plan. Results: Average (±SD) distance from apical foramen to the anatomical apex in the mesio-buccal and mesio-lingual, distal canal were [0.938 (±0.294)mm], [0.964 (±0.315)mm] and [0.982 (±0.322)mm] respectively. No statistical difference was found between right and left quadrant. Conclusion: This study demonstrated that 1mm distance from radiographic apex in mandibular molars could be appropriate for root canal therapy.
Prevalence of Hand-Arm Vibration Syndrome (HAVS) among Tyre Shop Workers in Kota Bharu, Kelantan, Malaysia

Objective : The objectives of this study were to determine the prevalence and severity of HAVS among tyre shop workers in Kota Bharu, Kelantan. Method : A cross-sectional study involving 100 tyre shop workers in Kota Bharu, Kelantan was conducted. Data was collected by interviewing the workers using Malay Translated HAVS questionnaire and measurement of hand-arm vibration using Human Vibration Meter (Larson Davis HVM 100). The next phase measurements involved a set of hand clinical examinations (Purdue pegboard, Semmes-Weinstein Monofilaments and Two-point Discrimination tests). The workers were divided into high (≥5ms -2 ) and low/moderate (<5ms -2 ) exposure group according to their 8 hr time weighted average [A(8)] of vibration exposure. Result: The prevalence of vascular, neurological and musculoskeletal symptoms was 16%, 47% and 51% respectively. This study has identified that the workers exposed to HAV above 5ms -2 have significantly higher risk of developing symptoms on neurological and vascular component. Conclusion : There- fore, there is need for better control of vibration exposure, monitoring and reporting of HAVS among workers exposed to hand-arm vibration in this tyre shop. Keywords: Hand-Arm Vibration, Hand-Arm Vibration Syndrome, Tyre Shop Workers
Speeding-up the Verification Phase of Set Similarity Joins in the GPGPU paradigm

We investigate the problem of exact set similarity joins using a co-process CPU-GPU scheme. The state-of-the-art CPU solutions split the wok in two main phases. First, filtering and index building takes place to reduce the candidate sets to be compared as much as possible; then the pairs are compared to verify whether they should become part of the result. We investigate in-depth solutions for transferring the second, so-called verification phase, to the GPU addressing several challenges regarding the data serialization and layout, the thread management and the techniques to compare sets of tokens. Using real datasets, we provide concrete experimental proofs that our solutions have reached their maximum potential, since they totally overlap verification with CPU tasks, and manage to yield significant speed-ups, up to 2.6X in our cases.
Neural Diffusion Model for Microscopic Cascade Prediction

The prediction of information diffusion or cascade has attracted much attention over the last decade. Most cascade prediction works target on predicting cascade-level macroscopic properties such as the final size of a cascade. Existing microscopic cascade prediction models which focus on user-level modeling either make strong assumptions on how a user gets infected by a cascade or limit themselves to a specific scenario where "who infected whom" information is explicitly labeled. The strong assumptions oversimplify the complex diffusion mechanism and prevent these models from better fitting real-world cascade data. Also, the methods which focus on specific scenarios cannot be generalized to a general setting where the diffusion graph is unobserved. To overcome the drawbacks of previous works, we propose a Neural Diffusion Model (NDM) for general microscopic cascade prediction. NDM makes relaxed assumptions and employs deep learning techniques including attention mechanism and convolutional network for cascade modeling. Both advantages enable our model to go beyond the limitations of previous methods, better fit the diffusion data and generalize to unseen cascades. Experimental results on diffusion prediction task over four realistic cascade datasets show that our model can achieve a relative improvement up to 26% against the best performing baseline in terms of F1 score.
Pan-Cancer Epigenetic Biomarker Selection from Blood Samples Using SAS

A key focus in current cancer research is the discovery of cancer biomarkers that allow earlier detection with high accuracy and lower costs for both patients and hospitals. Blood samples have long been used as a health status indicator, but DNA methylation signatures in blood have not been fully appreciated in cancer research. Historically, analysis of cancer has been conducted directly with the patient's tumor or related tissues. Such analyses allow physicians to diagnose a patient's health and cancer status; however, physicians must observe certain symptoms that prompt them to use biopsies or imaging to verify the diagnosis. This is a post-hoc approach. Our study will focus on epigenetic information for cancer detection, specifically information about DNA methylation in human peripheral blood samples in cancer discordant monozygotic twin-pairs. This information might be able to help us detect cancer much earlier, before the first symptom appears. Several other types of epigenetic data can also be used, but here we demonstrate the potential of blood DNA methylation data as a biomarker for pan-cancer using SAS 9.3 and SAS EM. We report that 55 methylation CpG sites measurable in blood samples can be used as biomarkers for early cancer detection and classification.