Miracle-dz/UniFAR-FTUs huggingface dataset:
SMTCoq Proof witness Certi fi cate Formula Coq goal Legend : Coq checker + Soundess Preprocessor SMT solver

This paper describes SMTCoq, a plug-in for the integration of external solvers into the Coq proof assistant. Based on a checker for generic first-order proof certificates fully implemented and proved correct in Coq, SMTCoq offers facilities to check answers from external SAT and SMT solvers and to increase Coq’s automation using such solvers, all in a safe way. The current version supports proof certificates produced by the SAT solver ZChaff, for propositional logic, and the SMT solvers veriT and CVC4, for the quantifier-free fragment of the combined theory of fixed-size bit vectors, functional arrays with extensionality, linear integer arithmetic, and uninterpreted function symbols.
Therapeutic Response Monitoring of anti-HER 1 therapy with PET imaging biomarkers in Esophageal Squamous Cell Carcinoma Model

Esophageal cancer is the eighth most common cancer worldwide and the sixth most common cause of death from cancer [1]. Two major histologic types of esophageal cancer have been defined: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma. Most patients with esophageal cancer in Asia such as Japan and China have squamous cell carcinoma (SCC) [2]. There have been recent advances in surgical techniques, chemotherapy and radiotherapy, but outcome for patients with esophageal cancer remains poor. Therefore, novel therapeutical strategies such as molecular-targeted therapy, including small molecule inhibitors of tyrosine kinases (TKIs) and monoclonal antibodies (mAbs) are needed [3]. Epidermal growth factor receptor (EGFR, HER-1) overexpression is common in ESCC. Earlier immunohistochemical studies showed that 40-50% of ESCC tumors express EGFR which is associated with disease progression and prognosis. These results indicate that the signaling pathway involving EGFR may is related in biological roles of ESCC tumor and suggests that EGFR could be a proper molecular target. High levels of EGFR expression may be considered to be a pre-treatment predictor of anti-HER-1 therapeutic efficacy. Cetuximab, a human-mouse chimerized IgG1 antibody with a high affinity for the EGFR, blocks the binding of ligand and induces the internalization and downregulation of EGFR. Anti-tumour activity of cetuximab has been reported in pre-clinical studies and clinical trials of esophageal cancer [4]. Imaging biomarker could be used for the screening of pertinent targets or patients and the monitoring therapeutic efficacy. In vivo imaging of immunopositron emission tomography (Immuno-PET) might provide a valuable strategy for evaluating EGFR expression level in tumor and predicting tumor response to anti-EGFR targeted therapy. Cu labeled cetuximab as an Immuno-PET imaging agent has been evaluated in several tumor-bearing mouse models. In molecular targeted therapy, noninvasive imaging biomarker could provide valuable informations for screening patient population and assessing early response to targeted therapy, thereby such information may improve therapeutic outcomes. We provide that both Culabeled cetuximab and FDG as PET imaging biomarkers may be useful for monitoring patient response to cetuximab therapy. 2. Materials and Methods
Breakdown Detection using Hierarchical Bi-Directional LSTMs

In this paper, we present a hierarchical Bi-Directional LSTMs neural network designed for the dialogue breakdown detection challenge 3 (DBDC3). The task of DBDC3 is to detect inappropriate utterances that lead to dialogue breakdowns in dialogue systems. By making use of the hierarchical structure of dialogue systems, our model is context-aware and can be trained directly from word sequences to breakdown labels in an endto-end manner. Thus our model is generic and requires no feature engineering, making it applicable to different dialogue systems. We evaluate our model on 4 dialogue systems provided by the DBDC3 datasets. Experiment results show that our proposed model achieves high accuracy, and outperforms the CRF baseline in terms of both classification-related and distributionrelated metrics without careful fine-tuning.
utachlor induced dissipation of mitochondrial membrane potential , oxidative NA damage and necrosis in human peripheral blood mononuclear cells

Butachlor is a systemic herbicide widely applied on rice, tea, wheat, beans and other crops; however, it concurrently exerts toxic effects on beneficial organisms like earthworms, aquatic invertebrates and other non-target animals including humans. Owing to the associated risk to humans, this chloroacetanilide class of herbicide was investigated with the aim to assess its potential for the (i) interaction with DNA, (ii) mitochondria membrane damage and DNA strand breaks and (iii) cell cycle arrest and necrosis in butachlor treated human peripheral blood mononuclear (PBMN) cells. Fluorescence quenching data revealed the binding constant (Ka = 1.2 × 104 M−1) and binding capacity (n = 1.02) of butachlor with ctDNA. The oxidative potential of butachlor was ascertained based on its capacity of inducing reactive oxygen species (ROS) and substantial amounts of promutagenic 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) adducts in DNA. Also, the discernible butachlor dose-dependent reduction in fluorescence intensity of a cationic dye rhodamine (Rh-123) and increased fluorescence intensity of 2′,7′-dichlorodihydro fluorescein diacetate (DCFH-DA) in treated cells signifies decreased mitochondrial membrane potential ( m) due to intracellular ROS generation. The comet data revealed significantly greater Olive tail moment (OTM) values in butachlor treated PBMN cells vs untreated and DMSO controls. Treatment of cultured PBMN cells for 24 h resulted in significantly increased number of binucleated micronucleated (BNMN) cells with a dose dependent reduction in the nuclear division index (NDI). The flow cytometry analysis of annexin V−/7-AAD+ stained cells demonstrated substantial reduction in live population due to complete loss of cell membrane integrity. Overall the data suggested the formation of butachlor–DNA complex, as an initiating event in butachlor-induced DNA damage. The results elucidated the oxidative role of butachlor in intracellular ROS production, and consequent mitochondrial dysfunction, oxidative DNA damage, and chromosomal breakage, which eventually triggers necrosis in human PBMN cells.
Foreign direct investment in Turkey: regional determinants

The uneven regional distribution of foreign direct investment (FDI) in Turkey poses an interesting question from the perspective of multinational firms (MNFs) and policy-makers alike. This paper focuses on the factors governing the location decisions of MNFs within Turkey with specific reference to policy implications. Using a conditional logit model, it is found that agglomeration, depth of local financial markets, human capital, and coastal access dominate location decisions for the aggregate sample of foreign investors in Turkey. This study reveals no evidence that public investment is successful in attracting MNFs to particular regions. Also importantly, the location determinants vary dramatically by broad industrial category, investment composition, and origin-country characteristics, including income category and region.
Polysemy in Compositional Distributional Semantics

Research in distributional semantics has made good progress in capturing individual word meanings using contextual frequencies obtained from a large corpus. While vocabulary of a language is limited, its generative power for combinatorial expressions is nonrestrictive, and so lexical semantic methods cannot be applied directly to phrasal or sentential semantics irrespective of the corpus size. Any distributional model that aims to describe a language adequately needs to address the issue of compositionality. Very recently, a new field called Compositional Distributional Semantics (CDS) emerged, stretching the boundaries of distributional semantics from word level meaning representation to higher levels such phrasal and sentential semantic representations. CDS models deal with the task of composing the meaning of a phrase/sentence from the distributional meaning of its constituents. Polysemy of words have been a major focus in distributional semantics. The challenges posed at lexical level make a transition to phrasal and higher levels, making polysemy a major threat to CDS models. In this thesis, we aim to build better CDS models by performing sense disambiguation. We test our hypothesis, sense disambiguation benefits compositional models, on different compositionality based evaluation tasks. The evaluation of compositional models is an uncertain topic. Since we humans do not know the way we compose semantics of expressions, it is hard to prepare datasets for evaluation, thus making the evaluation of CDS models a challenging topic. In this thesis, we focus on evaluation methods for compositional models and develop a dataset with a novel annotation scheme.
Directed forgetting, event‐related potentials and nicotine

Fifteen male users of oral snuff performed a directed forgetting task after over‐night abstinence and after administration of oral snuff. Directed forgetting tasks use cues to classify items for differential reporting at test, emphasizing the need for strategic encoding. Recognition was better after nicotine administration, but we found no evidence for greater strategic control, as hypothetically reflected in successful compliance with the directed forgetting instruction. Reaction time decreased after nicotine administration. Performance among 15 controls was unaffected over two sessions. Copyright © 1999 John Wiley & Sons, Ltd.
Versioning Goods and Joint Purchase: Substitution and Complementarity Strategies

We analyze the monopolist’s decision about how to design different versions of a good, i.e. whether to make them substitutes or complements, when consumers can buy them simultaneously. In this context, we find that versioning goods as substitutes or complements may be optimal for the monopolist, and the final result depends on the degree of concavity and convexity of the cost function.
Solution-derived ZnO nanostructures for photoanodes of dye-sensitized solar cells

Solution-phase derived ZnO nanostructures have triggered considerable interest and become the mainstream route to obtain low-cost and large-scale electrode materials for dye-sensitized solar cells (DSSCs). The article reviews recent progress in liquid-phase synthesis methods for preparing ZnO nanostructures as the photoanodes of the DSSCs. A few classic paradigms and new advancements in the ZnO nanostructures made by our group are demonstrated. The effects of ZnO nanostructured films with different morphologies, prepared by solution-phase approaches, on the performance of DSSCs are discussed. Finally, various liquid-phase methods of ZnO nanostructure synthesis are summarized and compared to allow further exploration of the ways to improve the photoelectric conversion efficiency of DSSCs.
School Feeding Programs in Middle Childhood and Adolescence

Almost every country in the world has a national school feeding program to provide daily snacks or meals to school-attending children and adolescents. The interventions reach an estimated 368 million children and adolescents globally. The total investment in the intervention is projected to be as much as US$75 billion annually (WFP 2013), largely from government budgets. School feeding may contribute to multiple objectives, including social safety nets, education, nutrition, health, and local agriculture. Its contribution to education objectives is well recognized and documented, while its role as a social safety net was underscored following the food and fuel crises of 2007 and 2008 (Bundy and others 2009). In terms of health and nutrition, school feeding contributes to the continuum of development by building on investments made earlier in the life course, including maternal and infant health interventions and early child development interventions (see chapter 7 in this volume, Alderman and others 2017). School feeding may also help leverage global efforts to enhance the inclusiveness of education for out-of-school children, adolescent girls, and disabled persons, as called for in the Sustainable Development Goals (see chapter 17 in this volume, Graham and others 2017). Although the Disease Control Priorities series focuses on lowand middle-income countries (LMICs), evidence from high-income countries (HICs) is included because of the near universality of school feeding and the insights that inclusion can provide as economies develop. For example, the design of school feeding in countries undergoing the nutrition transition1 may provide some lessons on how to shift from providing access to sufficient calories to promoting healthful diets and dietary behaviors for children and adolescents (WFP 2013). Agricultural development has increasingly gained attention. It is clear that to enable the transition to sustainable, scalable government-run programs, the inclusion of the agricultural sector is essential (Bundy and others 2009; Drake and others 2016). Accounting for the full benefits of school feeding through costeffectiveness and benefit-cost analysis is challenging, similar to other complex interventions, but undertaking this accounting is critical for assessing the tradeoffs with competing investments. This chapter reviews the evidence about how school feeding meets these objectives and provides some indication of costs in relation to benefits. The costs of the intervention are well established; estimates that encompass all the benefits of school feeding are more challenging. The benefits must be quantified and translated to the same unit to allow for aggregation. Moreover, how school feeding interventions are designed and implemented varies significantly across
Iterative Inference Models

Inference models, which replace an optimization-based inference procedure with a learned model, have been fundamental in advancing Bayesian deep learning, the most notable example being variational auto-encoders (VAEs). We propose iterative inference models, which learn how to optimize a variational lower bound through repeatedly encoding gradients. Our approach generalizes VAEs under certain conditions, and viewing VAEs in the context of iterative inference provides further insight into several recent empirical findings. We demonstrate the inference optimization capabilities of iterative inference models and show that they outperform standard inference models on typical benchmark data sets.
5 Current Knowledge of Microarray Analysis for Gene Expression Profiling in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is characterised by the accumulation of mature CD5/CD19 B-lymphocytes in the blood, bone marrow, lymph nodes and spleen (Caligaris-Cappio & Hamblin, 1999). Although the role of cellular proliferation disorders in CLL may originally have been underestimated, the typical characteristic of the disease is still regarded as a failure of malignant cells to undergo apoptosis (Munk Pedersen & Reed, 2004). CLL is a heterogeneous disease and although it is relatively stable in some patients, it progresses rapidly in others (Caligaris-Cappio & Hamblin, 1999). The mutational status of immunoglobulin heavy chain variable gene segment (IGHV) and the expression of CD38 and/or ZAP70 are important prognostic factors of disease so their detection is very useful for stratification of patients into indolent or aggressive subgroups (Hamblin et al., 1999; Krober et al., 2002; Orchard et al., 2004).
INDC International Nuclear Data Committee Summary Report of the 1 st Research Coordination Meeting of CRP on Primary Radiation Damage Cross Sections

The Nuclear Data Section of IAEA has initiated a new Coordinated Research Project with the main goal of reviewing and recommending primary damage response functions for neutron and ion irradiations of materials. The output of this CRP will be a database of recommended damage response functions for selected materials with corresponding documentation. It will serve the needs of the fission, fusion and accelerator neutron source communities. The first Research Coordination Meeting (RCM) was held 4 to 8 November 2013 at the IAEA. At this meeting, the attendees discussed the objectives of the whole CRP, presented their contributions and elaborated on consolidated recommendations and actions for implementation over the next 1.5 year period. This Summary Report documents the individual contributions and joint decisions made during this meeting. The identified research needs were refined through extensive discussion, and a consensus was developed which defined the CRP objectives in two broad categories. The first addresses the underlying physics-related research relevant to nuclear reactions and ion stopping powers, while the second task will address the development of new materials damage response functions.
A case for corpus stylistics: analysing Ian Fleming’s Casino Royale

In this article we investigate keywords and key semantic domains in Fleming’s Casino Royale. We identify groups of keywords that describe elements of the fictional world such as characters and settings as well as thematic signals. The keyword groups fall into two broad categories that are characterized as text-centred and reader-centred, with the latter providing particular clues for interpretation. We also compare the manually identified keyword groups with key semantic domains that are based on automatic semantic analysis. The comparison shows, for instance, how words that do not seem to fit a semantic domain can be seen as reader-centred keywords fulfilling specific textual functions. By linking our analysis to arguments in literary criticism, we show how quantitative and qualitative approaches can usefully complement one another.
cell tracking automatedsingle proteins using a microfluidic turbidostat and High-throughput gene expression analysis at the level of Supplementary data

Supplementary data ml http://rstb.royalsocietypublishing. org/content/suppl/2012/12/14/rstb.2012. 0025.DC1. ht "Data Supplement" References http://rstb.royalsocietypublishing. org/content/368/1611/20120025.full. html#related-urls Article cited in: http://rstb.royalsocietypublishing. org/content/368/1611/20120025.full. html#ref-list-1 This article cites 15 articles, 7 of which can be accessed free Subject collections (61 articles) systems biology  (132 articles) molecular biology  (25 articles) microbiology  (112 articles) cellular biology  (57 articles) biophysics  Articles on similar topics can be found in the following collections
Identification of key pathways and genes in endometrial cancer using bioinformatics analyses

Endometrial cancer (EC) is one of the most common gynecological cancer types worldwide. However, to the best of our knowledge, its underlying mechanisms remain unknown. The current study downloaded three mRNA and microRNA (miRNA) datasets of EC and normal tissue samples, GSE17025, GSE63678 and GSE35794, from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) and miRNAs (DEMs) in EC tumor tissues. The DEGs and DEMs were then validated using data from The Cancer Genome Atlas and subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. STRING and Cytoscape were used to construct a protein-protein interaction network and the prognostic effects of the hub genes were analyzed. Finally, miRecords was used to predict DEM targets and an miRNA-gene network was constructed. A total of 160 DEGs were identified, of which 51 genes were highly expressed and 100 DEGs were discovered from the PPI network. Three overlapping genes between the DEGs and the DEM targets, BIRC5, CENPF and HJURP, were associated with significantly worse overall survival of patients with EC. A number of DEGs were enriched in cell cycle, human T-lymphotropic virus infection and cancer-associated pathways. A total of 20 DEMs and 29 miRNA gene pairs were identified. In conclusion, the identified DEGs, DEMs and pathways in EC may provide new insights into understanding the underlying molecular mechanisms that facilitate EC tumorigenesis and progression.
Road side video surveillance in traffic scenes using map-reduce framework for accident analysis

Video surveillance and biomedical research have received a great attention in most of the active application-oriented research areas of computer vision, artificial intelligence, and image processing. Visual analysis of human motion is presently one of the active research areas in video surveillance system. Human motion analysis relates the detection, tracking and recognition of activities of the people, and more generally, the understanding of human behaviours, from image sequences involving humans. The road side traffic video surveillance aims at using several image processing methods to obtain better traffic and road safety, which in turn provides direct solution for to reducing death rate of accident victims. The distributed computing process has an efficient solution for this scalability issues in traffic video surveillance system. In this paper, a road traffic video surveillance system is proposed which can automatically identify road accidents from live video files. The system alerts neighbouring hospitals and highway rescue teams when accidents occur. This paper proposes a methodology to process the video file using map-reduce framework for better network service and better scalability solution in surveillance system. Then, the distributed video files are enhanced with Gaussian filtering. Efficient object classification and detection is carried out using Linear Discriminant Analysis (LDA) with Support Vector Machine (SVM) for traffic monitoring using video files from surveillance camera. Foreground object segmentation is a vital task which is carried out by Markov Random field (MRF) with Bayesian estimation process. This proposed method efficiently track and classify the foreground objects with use of object classification and detection and this will improve traffic monitoring in traffic scenes. The results obtained from the experiments on the proposed research shows the efficiency of traffic monitoring using traffic scenes.
Bacterioplankton biomass and production during destratification in a monomictic eutrophic bay of a tropical lagoon

Vertical profiles of bacterial biomass (AODC method), production of biomass (thymidine method) and total ETS (Electron Transport System) activity were recorded on 14 dates during the destratification process in the monomictic eutrophic Bietri Bay (Ebrie Lagoon, Ivory Coast). Bacterial biomass and production were both very high, indicating the importance of heterotrophic processes in this system. Interpretation of ETS data suggests that bacteria or 'bacteria-associated organisms' are responsible for most of the oxygen consumed in the water column. 'Integrated bacterial production of biomass represented ca 80 % of carbon produced by primary producers, thus showing that autotrophic production does not meet heterotrophic requirements of bacteria. Destratification appears to be of less importance than suggested by the physical and chemical characteristics, resulting in a decrease of bacterial biomass and production by a factor of 2 in the epilimnion. In the hypolimnion, the 'anaerobic community' characterized by low specific incorporation rates (3.4 X mol cell-i h-') and high mean cellular volume (0.203 pm3) during stratification is replaced by an 'aerobic community' with higher specific thymidine incorporation rates (6.6 X lo-" mol cell-' h-') and lower mean cellular volumes (0.151 pm3). Interpretation of bacterial production of biomass in these newly oxygenated layers demonstrates that oxygen requirements in the aphotic zone are roughly equivalent to autotrophic production of oxygen in the euphotic zone, thus showing that oxygenation of the entire water column is necessarily transient and explaining the return to anoxic conditions before the establishment of a new density stratification.