Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems

A long-term goal of machine learning is to build intelligent conversational agents. One recent popular approach is to train end-to-end models on a large amount of real dialog transcripts between humans (Sordoni et al., 2015; Vinyals & Le, 2015; Shang et al., 2015). However, this approach leaves many questions unanswered as an understanding of the precise successes and shortcomings of each model is hard to assess. A contrasting recent proposal are the bAbI tasks (Weston et al., 2015b) which are synthetic data that measure the ability of learning machines at various reasoning tasks over toy language. Unfortunately, those tests are very small and hence may encourage methods that do not scale. In this work, we propose a suite of new tasks of a much larger scale that attempt to bridge the gap between the two regimes. Choosing the domain of movies, we provide tasks that test the ability of models to answer factual questions (utilizing OMDB), provide personalization (utilizing MovieLens), carry short conversations about the two, and finally to perform on natural dialogs from Reddit. We provide a dataset covering 75k movie entities and with 3.5M training examples. We present results of various models on these tasks, and evaluate their performance.
Contribution of a Streptococcus mutans Antigen Expressed by a Salmonella Vector Vaccine in Dendritic Cell Activation

ABSTRACT A Salmonella vector vaccine expressing the saliva-binding region (SBR) of the adhesin AgI/II of Streptococcus mutans has been shown to induce a mixed Th1/Th2 anti-SBR immune response in mice and to require Toll-like receptor 2 (TLR2), TLR4, and MyD88 signaling for the induction of mucosal anti-SBR antibody responses. Since dendritic cells (DC) are critical in innate and adaptive immunity, the present study assessed the role of SBR expression by the vector vaccine in DC activation. Bone marrow-derived DC from wild-type and TLR2, TLR4, and MyD88 knockout mice were stimulated with Salmonella vector BRD509, the SBR-expressing Salmonella vector vaccine BRD509(pSBRT7), or SBR protein, and the DC responses to different stimuli were compared by assessing costimulatory molecule expression, cytokine production, and signaling pathways. The DC response to both BRD509(pSBRT7) and BRD509 was dependent mainly on TLR4. BRD509(pSBRT7) and BRD509 induced upregulation of CD80, CD86, CD40, and major histocompatibility complex class II (MHC II) expression. Lower levels of interleukin-10 (IL-10) and IL-12p40 were produced by BRD509(pSBRT7)-stimulated DC than by BRD509-stimulated DC. Furthermore, BRD509(pSBRT7)-stimulated DC showed decreased p38 phosphorylation compared to that induced by DC stimulated with BRD509. However, BRD509(pSBRT7)-treated DC produced a higher level of IL-6 than BRD509-stimulated cells. The low IL-12p40 and high IL-6 cytokine profile expressed by BRD509(pSBRT7)-stimulated DC may represent a shift toward a Th2 response, as suggested by the increased expression in Jagged-1. These results provide novel evidence that a heterologous protein expressed by a Salmonella vector vaccine can differentially affect DC activation.
Automatic Detection of Bone Contours in X-Ray Images

Detection of bone contours in x-ray images is an important step in the computer analysis of medical images. Analog X-ray images are characterized by low contrast ratio value and high variability of their optical properties. Therefore classical segmentation algorithms based on homogeneity criteria are not applicable. In this paper we propose an approach for automatic bone contours detection which does not require homogeneity of regions. This method is based on accurate edge fragments detection and elimination of discontinuities between them. We have dened the criteria for calculating numerical characteristics of the quality of image contours detection. The obtained results are used for diagnosis of abnormalities and diseases of the detected object.
An Intelligent Hybrid Approach for Improving Recall in Electronic Discovery

In this work, we propose a hybrid method for improving recall in electronic discovery proceedings. This approach takes ideas from Natural Language Processing (Word sense disambiguation) and Information Retrieval in enhancing retrieval of responsive documents using the semantics of query terms instead of direct text matching. Preliminary results from disambiguation of user queries show that this approach is promising to improve recall at the same time maintaining high degree of precision in the retrieval of relevant documents to help lawyers and their clients during litigations.
Structure–activity relationship study of trifluoromethylketone inhibitors of insect juvenile hormone esterase: Comparison of several classification methods

Juvenile hormone esterase (JHE) plays a key role in the development and metamorphosis of holometabolous insects. Its inhibitors could possibly be targeted for insect control. Conversely, JHE may also be involved in endocrine disruption by xenobiotics, resulting in detrimental effects in beneficial insects. There is therefore a need to know the structural characteristics of the molecules able to monitor JHE activity, and to develop SAR and QSAR studies to estimate their effectiveness. For a large diverse population of 181 trifluoromethylketones (TFKs) – the most potent JHE inhibitors known to date – we recently proposed a binary classification (active/inactive) using a support vector machine and Codessa structural descriptors. We have now examined, using the same data set and with the same descriptors, the applicability and performance of five other machine learning approaches. These have been shown able to handle high dimensional data (with descriptors possibly irrelevant or redundant) and to cope with complex mechanisms, but without delivering explicit directly exploitable models. Splitting the data into five batches (training set 80%, test set 20%) and carrying out leave-one-out cross-validation, led to good results of comparable performance, consistent with our previous support vector classifier (SVC) results. Accuracy was greater than 0.80 for all approaches. A reduced set of 15 descriptors common to all the investigated approaches showed good predictive ability (confirmed using a three-layer perceptron) and gives some clues regarding a mechanistic interpretation.
Survey of County-Level Heat Preparedness and Response to the 2011 Summer Heat in 30 U.S. States

Background: Adapting to extreme heat is becoming more critical as our climate changes. Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather. Objective: Our goal was to examine county-level local heat preparedness and response in 30 U.S. states following the unusually hot summer of 2011. Methods: Using a multimodal survey approach, we invited local health and emergency response departments from 586 counties to participate in the largest survey to date of heat preparedness and response in the United States. County-level responses were pooled into national and regional-level summaries. Logistic regressions modeled associations between heat planning/response and county characteristics, including population, poverty rates, typical summer weather, and 2011 summer weather. Results: Of 586 counties, 190 (32%) responded to the survey. Only 40% of these counties had existing heat plans. The most common heat responses were communication about heat, outreach, and collaborations with other organizations. Both heat preparedness and heat response were, on average, more extensive in counties with higher populations, lower poverty rates, and lower percentages of older people. Heat response was generally more extensive in counties with heat plans. Conclusions: Most responding counties were underprepared for extreme heat in 2011 and lacked a formal response plan. Because counties with heat plans were more likely to act to prevent adverse heat impacts to residents, local health departments should consider adopting such plans, especially because increased extreme heat is anticipated with further climate change. Citation: White-Newsome JL, Ekwurzel B, Baer-Schultz M, Ebi KL, O’Neill MS, Anderson GB. 2014. Survey of county-level heat preparedness and response to the 2011 summer heat in 30 U.S. States. Environ Health Perspect 122:573–579; http://dx.doi. org/10.1289/ehp.1306693
Exploring Distributional Representations and Machine Translation for Aspect-based Cross-lingual Sentiment Classification.

Cross-lingual sentiment classification (CLSC) seeks to use resources from a source language in order to detect sentiment and classify text in a target language. Almost all research into CLSC has been carried out at sentence and document level, although this level of granularity is often less useful. This paper explores methods for performing aspect-based cross-lingual sentiment classification (aspect-based CLSC) for under-resourced languages. Given the limited nature of parallel data for many languages, we would like to make the most of this resource for our task. We compare zero-shot learning, bilingual word embeddings, stacked denoising autoencoder representations and machine translation techniques for aspect-based CLSC. Each of these approaches requires differing amounts of parallel data. We show that models based on distributed semantics can achieve comparable results to machine translation on aspect-based CLSC and give an analysis of the errors found for each method.
Origin of the sequence‐dependent polyproline II structure in unfolded peptides

Recent studies have indicated that the unfolded states of polypeptides contain a substantial amount of polyproline type II (PII) structure. This energetically and structurally preorganized state may contribute to the reduction of the folding search, as well as to the recognition of intrinsically unstructured proteins and polyproline ligands. Using Monte Carlo simulations of natively unfolded peptides in the presence of explicit aqueous solvation, we observe that residue‐specific PII conformational propensity is the result of the modulation of polypeptide backbone hydration by a proximal side‐chain. Such a mechanism may be unique among those that contribute to the modulation of secondary structures in proteins. The calculated conformational propensities should prove useful for the development of a configurational PII scale necessary for the prediction and design of natural‐like polypeptides. Proteins 2005. © 2005 Wiley‐Liss, Inc.
Analysis and design of L-probe proximity fed patch antennas

In this paper, the L-probe patch antenna is studied using the finite-difference time-domain (FDTD) method because of its flexibility and efficiency in solving complex heterogeneous geometries. The Berenger's perfectly matched layer (PML) is used as the absorbing boundary condition (ABC). Extensive numerical results of the parametric study are presented. Characteristics including input impedance, and far-field radiation patterns are considered. The simulation results confirm the broadband characteristic of the antenna. In order to provide some design information, the variation of input impedance at resonance with different parameters is plotted on a Smith chart.
Expert Systems in Clinical Microbiology

SUMMARY This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the “big three”: Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.
Software Companion: The Mexar2 Support to Space Mission Planners

This paper describes a fielded AI system in daily use at the European Space Agency (ESA-ESOC) since February 2005. The tool, named MEXAR2, provides continuous support to human mission planners in synthesizing plans for downlinking on-board memory data from the MARS EXPRESS spacecraft to Earth. The introduction of the tool in the mission planning workflow significantly decreased the time spent in producing plans. Moreover MEXAR2 improves the quality of the produced plans thus guaranteeing a strong reliability in data return enabling a more intensive science activity on board. The introduction of MEXAR2 has modified the role of the human mission planners who can now evaluate and compare different solutions rather than dedicating their time exclusively to computing single solutions (a tedious and repetitive task which does not capitalize on the mission planners' decision-making expertise). These characteristics have effectively made MEXAR2 a fundamental work companion for the human mission planners.
Co-reference Resolution of Definite Descriptions

The paper presents an implemented model of definite description processing that is based on extensive empirical studies of definite description use and whose performance is quantitatively measured. In almost all approaches to discourse processing and discourse representation, definite descriptions have been regarded as anaphoric; and the models of definite description processing proposed in the literature tend to emphasise the role of common-sense inference mechanisms. The corpus study we developed are evidence that definite descriptions are not primarily anaphoric; they are often used to introduce a new entity in the discourse. Therefore, in the model of definite description processing that we propose recognising discourse new descriptions plays a role as important as identifying the antecedent of those used anaphorically.
Frequency and antimicrobial resistance of bacteria isolated from oral and topical medicaments from Hilla, Iraq.

INTRODUCTION The presence of microorganisms in pharmaceuticals is undesirable because they may cause spoilage of the product and may present an infection hazard to the consumers or patients. METHODOLOGY A total of 102 samples of oral and topical non-sterile pharmaceutical products were collected at random from different drug houses and pharmacies in Iraq, to investigate the microbial contamination of these products. Bacterial isolates recovered from these medicaments were subjected to susceptibility testing against various antibiotics by disk diffusion method according to Clinical and Laboratory Standards (CLSI) guidelines. RESULTS The results revealed that the occurrence of gram-positive bacteria was in oral and topical medicaments while gram-negative bacteria were only detected in topical medicaments. More than 58% of Bacillus isolates were resistant to lincomycin and Bacillus mycoides isolates were resistant to beta-lactam antibiotics and trimethoprim-sulfamethoxazole. Staphylococcus spp. showed a relatively high resistance to ampicillin, amoxicillin, penicillin, tetracycline, and trimethoprim-sulfamethoxazole. S. epidermidis had the highest number of multi-resistant isolates. Furthermore, 87.5% of isolated gram-negative rods showed high resistance to beta-lactam antibiotics and 75% of them were highly resistant to erythromycin. One isolate of Pseudomonas aeruginosa was the most resistant among all gram-negative rod isolates. CONCLUSION The high rate of resistance to antimicrobial agents of bacterial isolates recovered from oral and topical medicaments in this study may indicate a widespread antibiotic resistance among bacteria isolated from different sources, including those of anthropological and environmental origin.
Recovering Non-Local Dependencies for Chinese

To date, work on Non-Local Dependencies (NLDs) has focused almost exclusively on English and it is an open research question how well these approaches migrate to other languages. This paper surveys non-local dependency constructions in Chinese as represented in the Penn Chinese Treebank (CTB) and provides an approach for generating proper predicate-argument-modifier structures including NLDs from surface contextfree phrase structure trees. Our approach recovers non-local dependencies at the level of Lexical-Functional Grammar f-structures, using automatically acquired subcategorisation frames and f-structure paths linking antecedents and traces in NLDs. Currently our algorithm achieves 92.2% f-score for trace insertion and 84.3% for antecedent recovery evaluating on gold-standard CTB trees, and 64.7% and 54.7%, respectively, on CTBtrained state-of-the-art parser output trees.
Virtual Laboratories and Scenes to Support Chemistry Instruction : Lessons Learned

Goals and Education Materials The project began by considering ways in which technology could improve learning in introductory chemistry courses. Chemistry concepts are abstract and initially are difficult to attach to real-world experience. For this reason, high school and college chemistry courses have evolved a standard set of paper-and-pencil manipulations (dimensional analysis, balancing equations, stoichiometry, Lewis dot structure, etc.) that are canonized in textbooks and standard exams. Traditional chemistry courses emphasize development of these notational tools as a basis from which the “real stuff” can be approached. However, these tools are taught in the absence of activities that show their underlying utility. While these tools might be considered the underlying procedural knowledge base, they become inert bits of knowledge that are difficult for students to access. The difficulty in applying these procedures occurs at two levels. One is within the formal chemical domain, where it is often difficult to connect a paper-and-pencil procedure to an actual chemical process (use in chemistry). The other level is the application of a procedure to complex real settings (transfer to the real world). More fundamentally, the traditional educational approach strips out the very essence of science and leaves behind a confusing bag of tricks. Our goal is to use technology to complement traditional instruction with manipulatives that allow student problemsolving to be more authentic, i.e., more similar to that engaged in by practicing chemists (Bodner and Heron, 2002). The following two sections discuss the interventions we are developing.
An Empirical Evaluation of Optimization Strategies for ABox Reasoning in Expressive Description Logics

This paper presents an evaluation of a new description logic reasoner called RACE which implements TBox and ABox reasoning for the description logic ALCNHR+ supporting number restrictions, role hierarchies, and transitively closed roles. Tests on benchmark ABoxes indicate a speedup of several orders of magnitude compared to previous systems.
Covalent Immobilization of β-Galactosidase onto Amino-Functionalized Polyvinyl Chloride Microspheres: Enzyme Immobilization and Characterization

In this study, β-galactosidase (Aspergillus oryzae) was covalently immobilized onto aminated polyvinyl chloride (PVC) via glutaraldehyde coupling. Effect of immobilization conditions was investigated. The maximum obtained immobilization yield is 27 units g−1 while the maximum expressed activity is 12 µmol min−1 g−1. The optimum pH of the free enzyme was observed at 5.2, whereas the optimum pH of the immobilized one was schiffed to 4.4. The optimum temperature for both the free and immobilized forms was recognized at 60°C. A change in the temperature profile of the immobilized enzyme below 60°C was observed when response to the elevation temperature was less than that to the free counterpart. The Km and Vmax values of the free and immobilized β-galactosidase were found to be 52.03 and 123.1 mM, and 6.12 and 9.98 µ mol/min, respectively. Lactose hydrolysis, 500 mL of 100 mM concentration, was studied using 400 units of either free or immobilized enzymes at pH 6.0 and 60°C. Almost 80% hydrolysis percentage has been obtained after 6 h hydrolysis time with immobilized enzyme compared with 63% hydrolysis percentage obtained after 2 h for the free counterpart. Investigation of the operational stability at 40°C shows that the immobilized enzyme kept its activity for 5 h over 10 successive lactose hydrolysis cycles, which provides potentials for practical application in milk and whey hydrolysis. © 2013 Wiley Periodicals, Inc. Adv Polym Technol 2014, 33, 21379; View this article online at wileyonlinelibrary.com. DOI 10.1002/adv.21379
Mitochondrial Nitric Oxide Aspects , mechanism , and biological relevance of mitochondrial protein nitration sustained by mitochondrial nitric oxide synthase

Elfering, S. L. , V. L. Haynes, N. J. Traaseth, A. Ettl, and Cecilia Giulivi. Aspects, mechanism, and biological relevance of mitochondrial protein nitration sustained by mitochondrial nitric oxide synthase. Am J Physiol Heart Circ Physiol 286: H22–H29, 2004; 10.1152/ajpheart.00766. 2003. —The goal of this study was to explore the occurrence of nitrated proteins in mitochondria given that these organelles are endowed with a mitochondrial nitric oxide (NO ) synthase and considering the important role that mitochondria have in energy metabolism. Our hypothesis is that nitration of proteins constitutes a posttranslational modification by which NO exhibits long-term effects above and beyond those bioregulatory ones mediated through the interaction with cytochrome c oxidase. Our studies are aimed at understanding the mechanisms underlying the nitration of proteins in mitochondria and the biological significance of such a process in the cellular milieu. On promoting a sustained NO production by mitochondria, we investigated various aspects of protein nitration. Among them, the localization of nitrated proteins in mitochondrial subfractions, the identification of nitrated proteins through proteomic approaches, the characterization of affected pathways, and depiction of a target sequence. The biological relevance was analyzed by considering the turnover of native and nitrated proteins. In this regard, mitochondrial dysfunction, ensuing nitrative stress, may be envisioned as the result of accumulation of nitrated proteins, resulting from an overproduction of endogenous NO (this study), a failure in the proteolytic system to catabolize modified proteins, or a combination of both. Finally, this study allows one to gain understanding on the mechanism and nitrating species underlying mitochondrial protein nitration.
Effects of Haloperidol and Atypical Neuroleptics on Psychomotor Performance and Driving Ability in Schizophrenic Patients

The influence of antipsychotic treatment on the neuropsychological and psychomotor performance of schizophrenic patients is still a subject of investigation. The present study was designed to evaluate the effects of atypical neuroleptics in comparison with a conventional dopamine antagonist neuroleptic (haloperidol) on several dimensions of psychomotor performance (visual perception, attention, reaction time, and sensorimotor performance) considered to be of relevance in evaluating driving fitness. Psychomotor performance was assessed by means of the ART 90, a computerized Act and React Test which is generally used in diagnosis of psychomotor performance. The 49 participating patients were examined at discharge following psychopathological stabilisation; 20 received haloperidol, 29 received an atypical neuroleptic. Our findings demonstrate a remarkably reduced psychomotor performance in the haloperidol-treated group of schizophrenic patients compared with patients treated with atypical neuroleptics. Only 1 (5%) subject passed all subtests without major failures and could be regarded as competent to drive. Among patients with atypical neuroleptics, 7 patients (24%) passed all test parameters without major failures.