Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Expression Profiling of Human Vaginal Cells In Vitro Discriminates Compounds with Pro-Inflammatory and Mucosa-Altering Properties: Novel Biomarkers for Preclinical Testing of HIV Microbicide Candidates

Background Inflammation and immune activation of the cervicovaginal mucosa are considered factors that increase susceptibility to HIV infection. Therefore, it is essential to screen candidate anti-HIV microbicides for potential mucosal immunomodulatory/inflammatory effects prior to further clinical development. The goal of this study was to develop an in vitro method for preclinical evaluation of the inflammatory potential of new candidate microbicides using a microarray gene expression profiling strategy. Methods To this end, we compared transcriptomes of human vaginal cells (Vk2/E6E7) treated with well-characterized pro-inflammatory (PIC) and non-inflammatory (NIC) compounds. PICs included compounds with different mechanisms of action. Gene expression was analyzed using Affymetrix U133 Plus 2 arrays. Data processing was performed using GeneSpring 11.5 (Agilent Technologies, Santa Clara, CA). Results Microarraray comparative analysis allowed us to generate a panel of 20 genes that were consistently deregulated by PICs compared to NICs, thus distinguishing between these two groups. Functional analysis mapped 14 of these genes to immune and inflammatory responses. This was confirmed by the fact that PICs induced NFkB pathway activation in Vk2 cells. By testing microbicide candidates previously characterized in clinical trials we demonstrated that the selected PIC-associated genes properly identified compounds with mucosa-altering effects. The discriminatory power of these genes was further demonstrated after culturing vaginal cells with vaginal bacteria. Prevotella bivia, prevalent bacteria in the disturbed microbiota of bacterial vaginosis, induced strong upregulation of seven selected PIC-associated genes, while a commensal Lactobacillus gasseri associated to vaginal health did not cause any changes. Conclusions In vitro evaluation of the immunoinflammatory potential of microbicides using the PIC-associated genes defined in this study could help in the initial screening of candidates prior to entering clinical trials. Additional characterization of these genes can provide further insight into the cervicovaginal immunoinflammatory and mucosal-altering processes that facilitate or limit HIV transmission with implications for the design of prevention strategies.
Measurement of the density of states in a Si nanowall exhibiting the quantum size effect

We developed a slimming process of Si nanowall aiming at the Si nanowall solar cell whose band gap is tuned by the quantum size effect. The width of Si nanowall was successfully reduced to 3 nm by using thermal oxidation. The density of states (DOS) in Si nanowall was measured by ultraviolet photoelectron spectroscopy. The 3-nm width Si nanowall showed DOS with stepwise shape which is completely different from that of bulk Si. This change in the DOS is probably due to the quantum size effect.
Robot Learning : Some Recent Examples

This paper provides a brief overview of three recent contributions to robot learning developed by researchers at the University of Massachusetts Amherst. The first is the use of policy search algorithms that exploit new techniques in nonparameteric heteroscedastic regression to directly model policy-dependent distribution of cost [12]. Experiments demonstrate dynamic stabilization of a mobile manipulator through learning flexible, risk-sensitive policies in very few trials. The second contribution is a novel method for robot learning from unstructured demonstrations [19] that permits intelligent sequencing of primitives to create novel, adaptive behavior. This is demonstrated on a furniture assembly task using the PR2 mobile manipulator. The third contribution is a robot system that autonomously acquires skills through interaction with its environment [6]. Material in this paper has been published previously in refs. [8, 10, 11, 13, 14, 15, 19, 20] from which additional details are available.
Optical mammography: improved sensitivity by combined absorption and fluorescence analysis

We present a method to enhance tumor detectability in breasts imaged with our optical fluorescence mammography system. During a measurement, transmission data at 4 wavelengths and fluorescence data for excitation at 1 wavelength are collected after injection of an optical contrast agent. The data are reconstructed into 3D images of the absorption and fluorescence distributions. Combining those images enables the identification of various breast tissue compounds. Here, we investigate the relevance of our method in phantom experiments.
Review of the Hough Transform Method, With an Implementation of the Fast Hough Variant for Line Detection

This report explains the basic principles of the Hough Transform method for detection of geometric shapes, and reviews some of its variants and generalizations. The report further describes an implementation of the Fast Hough variant of the transform, for the detection of lines and circles in the framework of an image-processing application. Considerations of speed and efficiency of the Fast Hough algorithm are discussed in detail, with a view toward an ASIC implementation.
EXTRACTS AND KAVALACTONES OF PIPER METHYSTICUM G. FORST (KAVA-KAVA) INHIBIT P-GLYCOPROTEIN IN VITRO

Root extracts from kava-kava (Piper methysticum G. Forst) are clinically used for the treatment of anxiety and restlessness. Due to reported cases of liver toxicity, kava-kava extracts were withdrawn from the market in several countries in 2002. Because the efflux transporter P-glycoprotein (P-gp) is involved in the absorption, distribution, and excretion of many drugs and often participates in drug-drug interactions, we studied the effect of a crude kava extract and the main kavalactones kavain, dihydrokavain, methysticin, dihydromethysticin, yangonin, and desmethoxyyangonin on the P-gp-mediated efflux of calcein-acetoxymethylester in the P-gp-overexpressing cell line P388/dx and the corresponding cell line P388. The crude extract and the kavalactones showed a moderate to potent inhibitory activity with f2 (concentration needed to double baseline fluorescence) values of 170 μg/ml and 17 to 90 μM, respectively. The f2 value of yangonin could not be determined due to its higher lipophilicity. In conclusion, our results for the first time demonstrate P-gp-inhibitory activity of kava-kava and its components in vitro.
Cross Low-Dimension Pursuit for Sparse Signal Recovery from Incomplete Measurements Based on Permuted Block Diagonal Matrix

In this paper, a novel algorithm, Cross Low-dimension Pursuit, based on a new structured sparse matrix, Permuted Block Diagonal (PBD) matrix, is proposed in order to recover sparse signals from incomplete linear measurements. The main idea of the proposed method is using the PBD matrix to convert a high-dimension sparse recovery problem into two (or more) groups of highly low-dimension problems and crossly recover the entries of the original signal from them in an iterative way. By sampling a sufficiently sparse signal with a PBD matrix, the proposed algorithm can recover it efficiently. It has the following advantages over conventional algorithms: (1) low complexity, i.e., the algorithm has linear complexity, which is much lower than that of existing algorithms including greedy algorithms such as Orthogonal Matching Pursuit and (2) high recovery ability, i.e., the proposed algorithm can recover much less sparse signals than even l1-norm minimization algorithms. Moreover, we demonstrate both theoretically and empirically that the proposed algorithm can reliably recover a sparse signal from highly incomplete measurements.
Multi-document Summarisation and the PASCAL Textual Entailment Challenge

A fundamental problem for systems that require natural language understanding capabilities is the identification of instances of semantic equivalence and paraphrase in text. The PASCAL Recognising Textual Entailment (RTE) challenge is a recently proposed research initiative that addressed this problem by providing an evaluation framework for the development of generic “semantic engines” that can be used to identify language variability in a variety of applications such as Information Retrieval, Machine Translation and Question Answering. This paper discusses the suitability of the RTE evaluation datasets as a framework for evaluating the problem of redundancy recognition in multi-document summarisation, i.e. the identification of repetitive information across documents. This paper also reports on the development of an additional dataset containing examples of informationally equivalent sentence pairs that are typically found in machine generated summaries. The performance of a competitive entailment recognition system on this dataset is also reported.
Nested and Single Bars in Seyfert and Non-Seyfert Galaxies

We analyze the observed properties of nested and single stellar bar systems in disk galaxies. The 112 galaxies in our sample comprise the largest matched Seyfert versus non-Seyfert galaxy sample of nearby galaxies with complete near-infrared or optical imaging sensitive to length scales ranging from tens of parsecs to tens of kiloparsecs. The presence of bars is deduced by fitting ellipses to isophotes in Hubble Space Telescope (HST) H-band images up to 10'' radius and in ground-based near-infrared and optical images outside the H-band images. This is a conservative approach that is likely to result in an underestimate of the true bar fraction. We find that a significant fraction of the sample galaxies, 17% ± 4%, have more than one bar, and that 28% ± 5% of barred galaxies have nested bars. The bar fractions appear to be stable according to reasonable changes in our adopted bar criteria. For the nested bars, we detect a clear division in length between the large-scale (primary) bars and small-scale (secondary) bars, in both absolute and normalized (to the size of the galaxy) length. We argue that this bimodal distribution can be understood within the framework of disk resonances, specifically the inner Lindblad resonances (ILRs), which are located where the gravitational potential of the innermost galaxy switches effectively from three-dimensional to two-dimensional. This conclusion is further strengthened by the observed distribution of the sizes of nuclear rings which are dynamically associated with the ILRs. While primary bar sizes are found to correlate with the host galaxy sizes, no such correlation is observed for the secondary bars. Moreover, we find that secondary bars differ morphologically from single bars. Our matched Seyfert and non-Seyfert samples show a statistically significant excess of bars among the Seyfert galaxies at practically all length scales. We confirm our previous results that bars are more abundant in Seyfert hosts than in non-Seyfert galaxies and that Seyfert galaxies always show a preponderance of "thick" bars compared to the bars in non-Seyfert galaxies. Finally, no correlation is observed between the presence of a bar and that of companion galaxies, even relatively bright ones. Overall, since star formation and dust extinction can be significant even in the H band, the stellar dynamics of the central kiloparsec cannot always be revealed reliably by the use of near-infrared surface photometry alone.
20 Causal and Probabilistic Reasoning in Plog

In this paper we give an overview of the knowledge representation (KR) language Plog [Baral, Gelfond, and Rushton 2009] whose design was greatly influenced by work of Judea Pearl. We introduce the syntax and semantics of P-log, give a number of examples of its use for knowledge representation, and discuss the role Pearl’s ideas played in the design of the language. Most of the technical material presented in the paper is not new. There are however two novel technical contributions which could be of interest. First we expand P-log semantics to allow domains with infinite Herbrand bases. This allows us to represent infinite sequences of random variables and (indirectly) continuous random variables. Second we generalize the logical base of P-log which improves the degree of elaboration tolerance of the language. The goal of the P-log designers was to create a KR-language allowing natural and elaboration tolerant representation of commonsense knowledge involving logic and probabilities. The logical framework of P-log is Answer Set Prolog (ASP) — a language for knowledge representation and reasoning based on the answer set semantics (aka stable model semantics) of logic programs [Gelfond and Lifschitz 1988; Gelfond and Lifschitz 1991]. ASP has roots in declarative programing, the syntax and semantics of standard Prolog, disjunctive databases, and non-monotonic logic. The semantics of ASP captures the notion of possible beliefs of a reasoner who adheres to the rationality principle which says that “One shall not believe anything one is not forced to believe”. The entailment relation of ASP is non-monotonic, which facilitates a high degree of elaboration tolerance in ASP theories. ASP allows natural representation of defaults and their exceptions, causal relations (including effects of actions), agents’ intentions and obligations, and other constructs of natural language. ASP has a number of efficient reasoning systems, a well developed mathematical theory, and a well tested methodology of representing and using knowledge for computational tasks (see, for instance, [Baral 2003]). This, together with the fact that some of the designers of P-log came from the ASP community made the choice of a logical foundation for P-log comparatively easy.
Molecular structure of human fibroblast and leukocyte interferons: probe by lectin and hydrophobic chromatography

Structural differences between human leukocyte virus-induced interferon and human fibroblast polyinosinic-polycytidylic acid (rIn-rCn)-induced interferon have been noted in previous studies. This study reports the behavior of human leukocyte and fibroblast interferon, induced by virus and by rIn-rCn, in several lectin and hydrophobic chromatographic systems. Differences in both glycosylation and in hydrophobicity of human leukocyte and fibroblast interferons are documented. Human fibroblast interferon is a glycoprotein, whereas our evidence suggests that human leukocyte interferon probably is not. Also, fibroblast interferon is more hydrophobic than leukocyte interferon, as probed on several hydrophobic adsorbents. The possible relationships of these differences to each other and to antigenic variations are discussed. Generally, the differences appear to be attributable to the cell type in which the interferon was induced. However, our results suggest that at least subtle differences in the processing of the induction signal (virus or rIn-rCn) within the same cell type may occur, slightly altering some structural features.
EXPLORING PARTICIPATORY DESIGN FOR SNS-BASED AEH SYSTEMS

The rapidly emerging and growing social networking sites (SNS) offer an opportunity to improve adaptive e-learning experience by introducing a social dimension, connecting users within the system. Making connections and providing communication tools can engage students in creating effective learning environment and enriching learning experiences. Researchers have been working on introducing SNS features into adaptive educational hypermedia systems. The next stage research is centered on how to enhance SNS facilities of AEH systems, in order to engage students’ participation in collaborative learning and generating and enriching learning materials. Students are the core participants in the adaptive e-learning process, so it is essential for the system designers to consider students’ opinions. This paper aims at exploring how to apply participatory design methodology in the early stage of the SNS-based AEH system design process.
Identifying Chemicals with Potential Therapy of HIV Based on Protein-Protein and Protein-Chemical Interaction Network

Acquired immune deficiency syndrome (AIDS) is a severe infectious disease that causes a large number of deaths every year. Traditional anti-AIDS drugs directly targeting the HIV-1 encoded enzymes including reverse transcriptase (RT), protease (PR) and integrase (IN) usually suffer from drug resistance after a period of treatment and serious side effects. In recent years, the emergence of numerous useful information of protein-protein interactions (PPI) in the HIV life cycle and related inhibitors makes PPI a new way for antiviral drug intervention. In this study, we identified 26 core human proteins involved in PPI between HIV-1 and host, that have great potential for HIV therapy. In addition, 280 chemicals that interact with three HIV drugs targeting human proteins can also interact with these 26 core proteins. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying novel anti-HIV drugs.
Textual similarities based on a distributional approach

The design of efficient textual similarities is an important issue in the domain of textual data exploration. Textual similarities are for example central in document collection structuring (e.g. clustering), or in information retrieval (IR) which relies on the computation of textual similarities for measuring the adequacy between a query and documents. The objective of this paper is to present and compare several textual similarity measures in the framework of the distributional semantics (DS) model for IR. This model is an extension of the standard vector space model, which further takes the co-frequencies between the terms in a given reference corpus into account. These co-frequencies are considered to provide a distributional representation of the "semantics" of the terms. The co-occurrence profiles are used to represent the documents as vectors. Practical retrieval experiments using DS-based similarity models have been conducted in the framework of the AMARYLLIS evaluation campaign. The results obtained are presented. They indicate significant improvement of the performance in comparison with the standard approach.
Discrete Simulation of the Infrastructure for Diamond Embedded Metallic Saw Production

Diamond embedded cutting saws (DCSs) are basic tools commonly used in every ornamental stone processing operation from the extraction of the quarry block to the finishing of tiles. Diamond particles are the hard and abrasive essential component that has to be well adhered to the saw matrix, whether metallic, ceramic or polymeric. This work presents a computer simulation analysis and experimental design for an optimized manufacturing process of DCSs. This discrete simulation assesses the basic parameters involved in a possible industrial production in order to maximize the dynamics of the system and operational rules needed for best final products.
Dual Blockade of Cyclic AMP Response Element- (CRE) and AP-1-directed Transcription by CRE-transcription Factor Decoy Oligonucleotide

Alteration of gene transcription by inhibition of specific transcriptional regulatory proteins has important therapeutic potential. Synthetic double-stranded phosphorothioate oligonucleotides with high affinity for a target transcription factor can be introduced into cells as decoy cis-elements to bind the factors and alter gene expression. The CRE (cyclic AMP response element)-transcription factor complex is a pleiotropic activator that participates in the induction of a wide variety of cellular and viral genes. Because the CRE cis-element, TGACGTCA, is palindromic, a synthetic single-stranded oligonucleotide composed of the CRE sequence self-hybridizes to form a duplex/hairpin. Herein we report that the CRE-palindromic oligonucleotide can penetrate into cells, compete with CRE enhancers for binding transcription factors, and specifically interfere with CRE- and AP-1-directed transcriptionin vivo. These oligonucleotides restrained tumor cell proliferation, without affecting the growth of noncancerous cells. This decoy oligonucleotide approach offers great promise as a tool for defining cellular regulatory processes and treating cancer and other diseases.
“Cerebellar Challenge” for Older Adults: Evaluation of a Home-Based Internet Intervention

There is converging evidence that maintenance of function in the multiple connectivity networks involving the cerebellum is a key requirement for healthy aging. The present study evaluated the effectiveness of a home-based, internet-administered “cerebellar challenge” intervention designed to create progressive challenges to vestibular function, multi-tasking, and dynamic coordination. Participants (n = 98, mean age 68.2, SD 6.6) were randomly allocated to either intervention (the cerebellar challenge training for 10 weeks) or no intervention. All participants undertook an initial series of pre-tests, and then an identical set of post-tests following the intervention period. The test battery comprised five suites of tests designed to evaluate cognitive-sensori-motor-affective functions, including Physical Coordination, Memory, Language Dexterity, Fluid Thinking and Affect. The intervention group showed significant pre- to post improvements in 9 of the 18 tests, whereas the controls improved significantly on one only. Furthermore, the intervention group showed significantly greater improvement than the controls on the “Physical Coordination” suite of tests, with evidence also of differential improvement on the Delayed Picture Recall test. Frequency of intervention use correlated significantly with the improvement in balance and in peg-moving speed. It is concluded that an internet-based cerebellar challenge programme for older adults can lead to benefits in balance, coordination and declarative memory. Limitations and directions for further research are outlined.
Using the Hint Factory to Compare Model-Based Tutoring Systems

Model-based tutoring systems are driven by an abstract domain model and solver that is used for solution validation and student guidance. Such models are robust but costly to produce and are not always adaptive to specific students’ needs. Data-driven methods such as the Hint Factory are comparatively cheaper and can be used to generate individualized hints without a complete domain model. In this paper we explore the application of data-driven hint analysis of the type used in the Hint Factory to existing modelbased systems. We present an analysis of two probability tutors Andes and Pyrenees. The former allows for flexible problem-solving while the latter scaffolds students’ solution path. We argue that the state-space analysis can be used to better understand students’ problem-solving strategies and can be used to highlight the impact of different design decisions. We also demonstrate the potential for data-driven hint generation across systems.