nils-herrmann/clean_scirepeval huggingface dataset:
Natural Products as Anti HIV Agents and Role in HIV Associated Neurocognitive Disorders (HAND) A Brief Overview
Venue: Front. Microbiol.

As the threat of Human Immunodeficiency Virus (HIV)/Acquired Immunodeficiency Syndrome (AIDS) persists to rise, effective drug treatments are required to treat the infected people. Even though combination antiretroviral therapy (cART) provides stable viral suppression, it is not devoid of undesirable side effects, especially in persons undergoing long term treatment. The present therapy finds its limitations in the emergence of multidrug resistance and accordingly finding new drugs and novel targets is the need of the hour to treat the infected persons and further to attack HIV reservoirs in the body like brain, lymph nodes to achieve the ultimate goal of complete eradication of HIV and AIDS. Natural products such as plant originated compounds and plant extracts have enormous potential to become drug leads with anti HIV and neuroprotective activity. Accordingly, many research groups are exploring the biodiversity of the plant kingdom to find new and better anti HIV drugs with novel mechanisms of action and for HIV associated neurocognitive disorders (HAND) The basic challenge that still persists is to develop viral replication targeted therapy using novel anti HIV compounds with new mode of action, accepted toxicity and less resistance profile. Against this backdrop, the World Health Organization (WHO) suggested the need to evaluate ethno medicines for the management of HIV/AIDS. Consequently, there is need to evaluate traditional medicine, particularly medicinal plants and other natural products that may yield effective and affordable therapeutic agents. Although there are a good number of reports on traditional uses of plants to treat various diseases, knowledge of herbal remedies used to manage HIV/AIDS and HAND are scanty, vague and not well documented. In this review, plant substances showing a promising action that is anti HIV and HAND will be explored along with what they interact. Since some plant substances are also known to modulate several cellular factors which are also involved in the replication of HIV and hence their role as potential candidates will be discussed. HIV/AIDS being an exceptional epidemic, demands an exceptional approach and that forms very much focus for the current review.
Natural product modulators of transient receptor potential (TRP) channels as potential anti cancer agents.
Venue: Chemical Society reviews

Treatment of cancer is a significant challenge in clinical medicine, and its research is a top priority in chemical biology and drug discovery. Consequently, there is an urgent need for identifying innovative chemotypes capable of modulating unexploited drug targets. The transient receptor potential (TRPs) channels persist scarcely explored as targets, despite intervening in a plethora of pathophysiological events in numerous diseases, including cancer. Both agonists and antagonists have proven capable of evoking phenotype changes leading to either cell death or reduced cell migration. Among these, natural products entail biologically pre validated and privileged architectures for TRP recognition. Furthermore, several natural products have significantly contributed to our current knowledge on TRP biology. In this Tutorial Review we focus on selected natural products, e.g. capsaicinoids, cannabinoids and terpenes, by highlighting challenges and opportunities in their use as starting points for designing natural product inspired TRP channel modulators. Importantly, the de orphanization of natural products as TRP channel ligands may leverage their exploration as viable strategy for developing anticancer therapies. Finally, we foresee that TRP channels may be explored for the selective pharmacodelivery of cytotoxic payloads to diseased tissues, providing an innovative platform in chemical biology and molecular medicine.
Making Choices For Multicultural Education Five Approaches To Race Class And Gender

Thank you very much for downloading making choices for multicultural education five approaches to race class and gender. Maybe you have knowledge that, people have look numerous times for their chosen novels like this making choices for multicultural education five approaches to race class and gender, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some harmful virus inside their laptop.
Multicultural Education: Teachers' Perceptions and Preparation.

This paper focuses on theory and practice in multicultural education as it pertains to the preparation of preservice teachers. The literature reviews the history and definition of multiculturalism and investigates multiple theoretical frameworks around the ongoing debate and issues of multicultural education. Teachers' perceptions of multicultural education and various approaches to multicultural pedagogy and curriculum are explored. The finding indicates that thorough and balanced courses preparing preservice teachers to teach culturally diverse students are essential to supporting teachers' awareness, knowledge, and skill in providing equal education for all students.
Architecture of the Hyperledger Blockchain Fabric

Overview. A blockchain is best understood in the model of state machine replication  where a service maintains some state and clients invoke operations that transform the state and generate outputs. A blockchain emulates a "trusted" computing service through a distributed protocol, run by nodes connected over the Internet. The service represents or creates an asset, in which all nodes have some stake. The nodes share the common goal of running the service but do not necessarily trust each other for more. In a "permissionless" blockchain such as the one underlying the Bitcoin cryptocurrency, anyone can operate a node and participate through spending CPU cycles and demonstrating a "proof of work." On the other hand, blockchains in the "permissioned" model control who participates in validation and in the protocol; these nodes typically have established identities and form a consortium. A report of Swanson compares the two models
Semantic Text Classification for Supporting Automated Compliance Checking in Construction

AbstractAutomated regulatory and contractual compliance checking requires automated rule extraction from regulatory and contractual textual documents (e.g. contract specifications) Automated rule extraction is a challenging task that requires complex processing of text. In the proposed automated compliance checking (ACC) approach, the first step in automating the rule extraction process is automatically classifying the different documents and parts of documents (e.g. contract clauses) into predefined categories (environmental, safety, health, etc. for preparing it for further text analysis and rule extraction. These categories are defined in a semantic model for normative reasoning. This paper presents a semantic, machine learning based text classification algorithm for classifying clauses and subclauses of general conditions for supporting ACC in construction. The multilabel classification problem was transformed into a set of binary classification problems. Different machine learning algorithms, tex.
Domain Specific Hierarchical Text Classification for Supporting Automated Environmental Compliance Checking

AbstractAutomated environmental compliance checking requires automated extraction of rules from environmental regulatory textual documents such as energy conservation codes and EPA regulations. Automated rule extraction requires complex text processing and analysis for information extraction and subsequent formalization of the extracted information into computer processable rules. In the proposed automated compliance checking (ACC) approach, the text is first classified into predefined categories before information extraction (IE) The advantages are that irrelevant text will be filtered out during text classification (TC) and text with similar semantic meaning will be grouped, thereby improving the efficiency and accuracy of further IE and compliance reasoning (CR) The categories used for TC are predefined in a semantic TC topic hierarchy, and the classified text is subsequently used in semantic IE and semantic CR. This paper presents the proposed machine learning (ML) based TC algorithm for classifying.
State Action Immunity and Section 5 of the FTC Act

The state action immunity doctrine of Parker v. Brown immunizes anticompetitive state regulations from preemption by federal antitrust law so long as the state takes conspicuous ownership of its anticompetitive policy. In its 1943 Parker decision, the Supreme Court justified this doctrine on the observation that no evidence of a Congressional will to preempt state law appears in the Sherman Act's legislative history or context. In addition, commentators generally assume that the New Deal Court was anxious to avoid re entangling the federal judiciary in Lochner style substantive due process analysis. The Supreme Court has observed, without deciding, that the Federal Trade Commission might not be bound by the Parker doctrine but instead enjoys "superior preemption" authority under Section 5 of the FTC Act. Drawing on the FTC Act's legislative history and its institutional distinctiveness from Sherman Act enforcement, this Article makes an affirmative case for FTC superior preemption power over anticompetitive state laws.
Does the EQ 5D capture the effects of physical and mental health status on life satisfaction among older people? A path analysis approach
Venue: Quality of Life Research

PurposeTo examine the extent to which EQ 5D utility scores capture the effect of mental and physical health status on life satisfaction (LS) in older adults.MethodsRetrospective cohort study of 884 patients aged =70 years from 15 general practices in Ireland, including medical records, pharmacy claims, and self completion questionnaire. Path analysis was used to evaluate the direct and indirect effects of: (1) chronic disease burden (based on medications data) (2) activity limitation (basic and instrumental activities of daily living) (3) anxiety symptoms and; (4) depressive symptoms (Hospital Anxiety and Depression Scale) on LS (Life Satisfaction Index Z) via a utility score based on responses to the EQ 5D scale. Utility scores were calculated using UK time trade off utility weights. Covariates included age and socioeconomic status.ResultsThe final path model fitted the data well (goodness of fit kh2 7.5, df (7) p 0.37) The direct effects of chronic disease burden and disability on LS were not statistically significant and were excluded from the final model, indicating that EQ 5D score mediated 100% of the total effect on LS. The direct and indirect effects of anxiety and depression on LS were statistically significant, but the size of the indirect effect was small (4% of the total effect for anxiety and 6% of the total effect for depression).ConclusionThe EQ 5D does not adequately capture the effects of anxiety and depression on LS among older adults, suggesting that it may lead to inaccurate assessments of the effectiveness of interventions in this cohort.
Toll like receptor mediated immune response inhibits prion propagation
Venue: Glia

Prion diseases are progressive neurodegenerative disorders affecting humans and various mammals. The prominent neuropathological change in prion diseases is neuroinflammation characterized by activation of neuroglia surrounding prion deposition. The cause and effect of this cellular response, however, is unclear. We investigated innate immune defenses against prion infection using primary mixed neuronal and glial cultures. Conditional prion propagation occurred in glial cultures depending on their immune status. Preconditioning of the cells with the toll like receptor (TLR) ligand, lipopolysaccharide, resulted in a reduction in prion propagation, whereas suppression of the immune responses with the synthetic glucocorticoid, dexamethasone, increased prion propagation. In response to recombinant prion fibrils, glial cells up regulated TLRs (TLR1 and TLR2) expression and secreted cytokines (tumor necrosis factor a, interleukin 1b, interleukin 6, granulocyte macrophage colony stimulating factor, and interferon b) Preconditioning of neuronal and glial cultures with recombinant prion fibrils inhibited prion replication and altered microglial and astrocytic populations. Our results provide evidence that, in early stages of prion infection, glial cells respond to prion infection through TLR mediated innate immunity. GLIA 2016;64:937 951
Reduced Immune Detection of the Pathogenic Prion Protein in Presenceof Triose Phosphate Isomerase

During performing electrophoresis for detecting the presence of recombinant prion protein (PrPrec) it was punctually planned to examine several expressed protein on the same polyacrylamide gel and the last empty well was used for depositing together the molecular weight marker (triose phosphate isomerase) and the pathogenic bovine prion protein PrPsc. After transfer and immune blotting with specific PrP monoclonal antibodies  no detectable PrPsc bands were observed. So we decided to explore these unexpected results.
A Carbon Cotton Cathode with Ultrahigh Loading Capability for Statically and Dynamically Stable Lithium Sulfur Batteries.
Venue: ACS nano

Sulfur exhibits a high theoretical capacity of 1675 mA h g 1 via a distinct conversion reaction, which is different from the insertion reactions in commercial lithium ion batteries. In consideration of its conversion reaction battery chemistry, a custom design for electrode materials could establish the way for attaining high loading capability while simultaneously maintaining high electrochemical utilization and stability. In this study, this process is undertaken by introducing carbon cotton as an attractive electrode containment material for enhancing the dynamic and static stabilities of lithium sulfur (Li S) batteries. The carbon cotton possessing a hierarchical macro /microporous architecture exhibits a high surface area of 805 m2 g 1 and high microporosity with a micropore area of 557 m2 g 1. The macroporous channels allow the carbon cotton to load and stabilize a high amount of active material. The abundant microporous reaction sites spread throughout the carbon cotton facilitate the redox chemistry of the high loading/content Li S system. As a result, the high loading carbon cotton cathode exhibits (i) enhanced cycle stability with a good dynamic capacity retention of 70% after 100 cycles and (ii) improved cell storage stability with a high static capacity retention of above 93% and a low time dependent self discharge rate of 0.12% per day after storing for a long period of 60 days. These carbon cotton cathodes with the remarkably highest values reported so far of both sulfur loading (61.4 mg cm 2) and sulfur content (80 wt demonstrate enhanced electrochemical utilization with the highest areal, volumetric, and gravimetric capacities simultaneously.
Classification of motor imagery electroencephalography signals using spiking neurons with different input encoding strategies
Venue: Neural Computing and Applications

Motor imagery based brain computer interfaces decode users' intentions from the electroencephalogram; however, poor spatial resolution makes automatic recognition of these intentions a challenging task. New classification approaches with low computational costs and high classification performances need to be developed in order to increase the number of users benefitted by these systems. On the other hand, spiking neuron models, which are mathematical abstractions of real neurons, have shown good performances in several classification tasks, making these models suitable for motor imagery classification. In this work, two different encoding strategies for spiking neuron models, applied to the classification of motor imagery time frequency features of stroke patients and healthy subjects, were evaluated. Classification performances and computational costs of spiking neuron models were compared against those of linear discriminant analysis, support vector machines and artificial neural networks. Results showed that a time varying encoding strategy is more suitable for motor imagery classification, and its implementation computational cost is low. Therefore, a spiking neuron model with a time varying encoding strategy could increase the number of potential users of brain computer interfaces.
Compositional Recurrent Neural Networks for Chinese Short Text Classification
Venue: 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)

Word segmentation is the first step in Chinese natural language processing, and the error caused by word segmentation can be transmitted to the whole system. In order to reduce the impact of word segmentation and improve the overall performance of Chinese short text classification system, we propose a hybrid model of character level and word level features based on recurrent neural network (RNN) with long short term memory (LSTM) By integrating character level feature into word level feature, the missing semantic information by the error of word segmentation will be constructed, meanwhile the wrong semantic relevance will be reduced. The final feature representation is that it suppressed the error of word segmentation in the case of maintaining most of the semantic features of the sentence. The whole model is finally trained end to end with supervised Chinese short text classification task. Results demonstrate that the proposed model in this paper is able to represent Chinese short text effectively, and the performances of 32 class and 5 class categorization outperform some remarkable methods.
Land conflict resolution mechanisms in Kalikiliki Settlement,Lusaka

iv ACKNOWLEDGEMENTS v LIST OF TABLES viii LIST OF FIGURES viii ABBREVIATIONS AND ACRONYMS ix CHAPTER 1: INTRODUCTION 1 1.1 Problem Statement 3 1.2 Aim of the Study 3 1.3 Research  LITERATURE REVIEW 5 2.1 Land Use 5 2.2 Land Use Conflict 6 2.2.1 Types and Causes of Land use Conflicts 6 2.3 Development of Informal Settlements 8 2.3.1 Development of Informal Settlements in Zambia 10 2.3.1.1 Community Leadership Structures in Informal Settlements 12 2.3.2 Social Economic Characteristics of Informal Settlements 13 2.3.3 Informal Settlement Upgrading and Mechanisms for Land Use Conflict Resolution 16 2.4 Implications for Settlement Upgrading 23 2.5 Theoretical Framework 24 2.5.1 Constructive Conflict Resolution Theory 24 CHAPTER 3: STUDY AREA 27 3.1 Location 27 3.2 History of the Settlement 27
RipMC: RIPPER for Multiclass Classification
Venue: Neurocomputing

A major challenge in extending RIPPER for multiclass classification problems is the order of learning the classes. In this paper, RIPPER for Multiclass Classification (RipMC) is presented, which extends several aspects of RIPPER. In RipMC, all classes are initially given an equal opportunity with a Parallel Rule Learning (PRL) to generate their best rules in a global search, causing the rules in the decision list to be reordered, which improves performance in classifying new instances. Next, the most complex and costly class, which will be set as the default class in the subsequent execution of the algorithm, is identified according to a new measure called MaxDL. Finally, a new rule evaluation measure, namely LogLaplace, is presented for better pruning of the rules. The performance of the proposed algorithm and RIPPER is compared using 18 data sets. Experimental results show that RipMC significantly outperforms the original RIPPER.
RIPPER: a framework for MS1 only metabolomics and proteomics label free relative quantification
Venue: Bioinform.

UNLABELLED RIPPER is a framework for mass spectrometry based label free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity based intensity normalization. RIPPER produces lists of analyte signals with their unnormalized and normalized intensities that can serve as input to statistical and directed mass spectrometry (MS) methods for detecting quantitative differences between biological samples using MS. AVAILABILITY AND IMPLEMENTATION http:/www.z.umn.edu/ripper CONTACT vanr0014@umn.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Portraying an employee performance management system based on multi criteria decision analysis and visual techniques

Performance appraisal is one of the most critical and indispensable human resource practices for organisations. However, it generates dissatisfaction among employees as it is often viewed as complex and ineffective. The purpose of this paper is to present a new performance management system that integrates multi criteria decision analysis (MCDA) methods the analytic network process (ANP) and PROMETHEE with the visual techniques of the GAIA plane and the stacked bar chart. MCDA methods allow a structured and consistent evaluation integrating qualitative and quantitative criteria. The authors developed a structured and transparent performance management system. It is based on the MCDA methods PROMETHEE and ANP. It also incorporates the visual techniques: GAIA and stacked bar chart. Feedback for trainings and developments can precisely be formulated. Visual techniques permit clear identification and quantification, for each employee, of the areas that need improvement through training and development, which contributes to the resource based view of organisations. A real case study has been portrayed to show the added value of the MCDA methods and the visual techniques in employee performance management. The paper describes a new employee performance system adopted in an organisation. The multi criteria analysis transparently combines qualitative and quantitative decision criteria into a holistic and transparent evaluation. The visual techniques permit us to gain a deep insight into the employees' skills profile and capture fine details where individuals perform or underperform.
Small scale integrated agriculture: a tool of poverty alleviation, gender equality promotion and improving food security at household level in coastal region of Bangladesh

The chemical composition of four edible plant foods species, three fish species and one prawn were analyzed in Food Chemistry Laboratory of Behbahan Khatam Alanbia University of Technology, Behbahan, Iran in 2014. The analysis of fatty acid and sugars composition were performed by gas liquid chromatography and high performance liquid chromatography, respectively. Protein and lipid content were founded higher in baked and fried in fish S. commersonnianus (74.29% (20.20% fish Sphyraena helleri (88.12% and (17.77% respectively. Ash content in fish S. commersonnianus varies from 9.80% to 15.34% and in fish S. helleri from 5.83% to 7.68% Based on the proximate analysis, it can be calculated that an edible portion of 100 g of studied edible plant foods provides, on average, around 303.9+ 1.04 kcal. The plant Portulaca neglecta is suitable for high temperature food processes. The macronutrient profile in general revealed that the wild plant foods were with rich sources of protein and carbohydrates, and had low amounts of fat. The highest protein, the lowest fat and energy contents were found in boiled in both fish species; therefore, boiling can be recommended as the best cooking method for healthy diet.  82 85, December, 2015