Miracle-dz/UniFAR-FTUs huggingface dataset:
Stress Intensity of Debonding for A Rigid Inclusion Near An Angle Dislocation

The study of debonding is of importance in providing a good understanding of the bonded interfaces of dissimi- lar materials. The problem of debonding of an arbitrarily shaped rigid inclusion in an infinite plate with a point dislocation of thin plate bending is investigated in this paper. Herein, the point dislocation is defined with respect to the difference of the plate deflection angle. An analytical solution is obtained by using the complex stress function approach and the rational mapping function technique. In the derivation, the fundamental solutions of the stress boundary value problem are taken as the principal parts of the corresponding stress functions, and through analytical continuation, the problem of obtaining the complementary stress function is reduced to a Riemann-Hilbert problem. Without loss of generality, numerical results are calculated for a square rigid inclusion with a debonding. It is noted that the stress components are singular at the dislocation point, and a stress concentration can be found in the vicinity of the inclusion corner. We also obtain the stress intensity of a debonding in terms of the stress functions. It can be found that when a debonding starts from a corner of the inclusion and extends to another corner progressively, the stress intensity of the debonding increases monotonously; once the debonding extends over the corner points, the value of the stress intensity of the debonding gradually decreases. The relationships between the stress intensity of the debonding and the direction and position of the dislocation are also presented in this paper.
Membrane Fusion Involved in Neurotransmission: Glimpse from Electron Microscope and Molecular Simulation

Membrane fusion is one of the most fundamental physiological processes in eukaryotes for triggering the fusion of lipid and content, as well as the neurotransmission. However, the architecture features of neurotransmitter release machinery and interdependent mechanism of synaptic membrane fusion have not been extensively studied. This review article expounds the neuronal membrane fusion processes, discusses the fundamental steps in all fusion reactions (membrane aggregation, membrane association, lipid rearrangement and lipid and content mixing) and the probable mechanism coupling to the delivery of neurotransmitters. Subsequently, this work summarizes the research on the fusion process in synaptic transmission, using electron microscopy (EM) and molecular simulation approaches. Finally, we propose the future outlook for more exciting applications of membrane fusion involved in synaptic transmission, with the aid of stochastic optical reconstruction microscopy (STORM), cryo-EM (cryo-EM), and molecular simulations.
Characterization of the Mode of Action of a Potent Dengue Virus Capsid Inhibitor

ABSTRACT Dengue viruses (DV) represent a significant global health burden, with up to 400 million infections every year and around 500,000 infected individuals developing life-threatening disease. In spite of attempts to develop vaccine candidates and antiviral drugs, there is a lack of approved therapeutics for the treatment of DV infection. We have previously reported the identification of ST-148, a small-molecule inhibitor exhibiting broad and potent antiviral activity against DV in vitro and in vivo (C. M. Byrd et al., Antimicrob. Agents Chemother. 57:15–25, 2013, doi:10 .1128/AAC.01429-12). In the present study, we investigated the mode of action of this promising compound by using a combination of biochemical, virological, and imaging-based techniques. We confirmed that ST-148 targets the capsid protein and obtained evidence of bimodal antiviral activity affecting both assembly/release and entry of infectious DV particles. Importantly, by using a robust bioluminescence resonance energy transfer-based assay, we observed an ST-148-dependent increase of capsid self-interaction. These results were corroborated by molecular modeling studies that also revealed a plausible model for compound binding to capsid protein and inhibition by a distinct resistance mutation. These results suggest that ST-148-enhanced capsid protein self-interaction perturbs assembly and disassembly of DV nucleocapsids, probably by inducing structural rigidity. Thus, as previously reported for other enveloped viruses, stabilization of capsid protein structure is an attractive therapeutic concept that also is applicable to flaviviruses. IMPORTANCE Dengue viruses are arthropod-borne viruses representing a significant global health burden. They infect up to 400 million people and are endemic to subtropical and tropical areas of the world. Currently, there are neither vaccines nor approved therapeutics for the prophylaxis or treatment of DV infections, respectively. This study reports the characterization of the mode of action of ST-148, a small-molecule capsid inhibitor with potent antiviral activity against all DV serotypes. Our results demonstrate that ST-148 stabilizes capsid protein self-interaction, thereby likely perturbing assembly and disassembly of viral nucleocapsids by inducing structural rigidity. This, in turn, might interfere with the release of viral RNA from incoming nucleocapsids (uncoating) as well as assembly of progeny virus particles. As previously reported for other enveloped viruses, we propose the capsid as a novel tractable target for flavivirus inhibitors.
A Toxicogenomic Approach for the Prediction of Murine Hepatocarcinogenesis Using Ensemble Feature Selection

The current strategy for identifying the carcinogenicity of drugs involves the 2-year bioassay in male and female rats and mice. As this assay is cost-intensive and time-consuming there is a high interest in developing approaches for the screening and prioritization of drug candidates in preclinical safety evaluations. Predictive models based on toxicogenomics investigations after short-term exposure have shown their potential for assessing the carcinogenic risk. In this study, we investigated a novel method for the evaluation of toxicogenomics data based on ensemble feature selection in conjunction with bootstrapping for the purpose to derive reproducible and characteristic multi-gene signatures. This method was evaluated on a microarray dataset containing global gene expression data from liver samples of both male and female mice. The dataset was generated by the IMI MARCAR consortium and included gene expression profiles of genotoxic and nongenotoxic hepatocarcinogens obtained after treatment of CD-1 mice for 3 or 14 days. We developed predictive models based on gene expression data of both sexes and the models were employed for predicting the carcinogenic class of diverse compounds. Comparing the predictivity of our multi-gene signatures against signatures from literature, we demonstrated that by incorporating our gene sets as features slightly higher accuracy is on average achieved by a representative set of state-of-the art supervised learning methods. The constructed models were also used for the classification of Cyproterone acetate (CPA), Wy-14643 (WY) and Thioacetamid (TAA), whose primary mechanism of carcinogenicity is controversially discussed. Based on the extracted mouse liver gene expression patterns, CPA would be predicted as a nongenotoxic compound. In contrast, both WY and TAA would be classified as genotoxic mouse hepatocarcinogens.
Zero-mean Convolutional Network with Data Augmentation for Sound Level Invariant Singing Voice Separation

We address an issue of separating singing voices from polyphonic music signals regardless of sound level variance of the mixture input. Using a standard separation quality assessment tool BSS Eval 4.0, we found that the separation quality of a singing voice separation (SVS) system based on a dilatable Convolutional Neural Network (CNN) decreases under different sound levels. Even if this SVS system is comparable to state-of-the-art SVS systems, it is vulnerable to the issue of sound level variance. We therefore investigate four methods of making the CNN-based SVS system invariant to different sound levels — two types of data augmentation, frame normalization, and zero-mean convolution. By testing all 15 combinations of the four methods, we found that all combinations can improve the sound level invariance and analyzed the best combinations. To the best of our knowledge, this is the first SVS work systematically investigating sound level variance.
Silver nanoparticles induce pro‐inflammatory gene expression and inflammasome activation in human monocytes

A complete cytotoxic profile of exposure to silver (AgNP) nanoparticles investigating their biological effects on the innate immune response of circulating white blood cells is required to form a complete understanding of the risk posed. This was explored by measuring AgNP‐stimulated gene expression of the pro‐inflammatory cytokines interleukin‐1 (IL‐1), interleukin‐6 (IL‐6) and tumour necrosis factor‐alpha (TNF‐α) in THP‐1 monocytes. A further study, on human monocytes extracted from a cohort of blood samples, was carried out to compare with the AgNP immune response in THP‐1 cells along with the detection of pro‐IL‐1β which is a key mediator of the inflammasome complex.
Abstract machines, optimal reduction, and streams

Abstract In this paper, we propose and explore a new approach to abstract machines and optimal reduction via streams, infinite sequences of elements. We first define a sequential abstract machine capable of performing directed virtual reduction (DVR) and then we extend it to its parallel version, whose equivalence is explained through the properties of DVR itself. The result is a formal definition of the λ-calculus interpreter called Parallel Environment for Lambda Calculus Reduction (PELCR), a software for λ-calculus reduction based on the Geometry of Interaction. In particular, we describe PELCR as a stream-processing abstract machine, which in principle can also be applied to infinite streams.
Analysis of high density expression microarrays with signed-rank call algorithms

MOTIVATION We consider the detection of expressed genes and the comparison of them in different experiments with the high-density oligonucleotide microarrays. The results are summarized as the detection calls and comparison calls, and they should be robust against data outliers over a wide target concentration range. It is also helpful to provide parameters that can be adjusted by the user to balance specificity and sensitivity under various experimental conditions. RESULTS We present rank-based algorithms for making detection and comparison calls on expression microarrays. The detection call algorithm utilizes the discrimination scores. The comparison call algorithm utilizes intensity differences. Both algorithms are based on Wilcoxon's signed-rank test. Several parameters in the algorithms can be adjusted by the user to alter levels of specificity and sensitivity. The algorithms were developed and analyzed using spiked-in genes arrayed in a Latin square format. In the call process, p-values are calculated to give a confidence level for the pertinent hypotheses. For comparison calls made between two arrays, two primary normalization factors are defined. To overcome the difficulty that constant normalization factors do not fit all probe sets, we perturb these primary normalization factors and make increasing or decreasing calls only if all resulting p-values fall within a defined critical region. Our algorithms also automatically handle scanner saturation.
Input Dataset Survey of In-Silico Tools for Inference and Visualization of Gene Regulatory Networks (GRN)

Understanding Gene Regulatory Network (GRN) is considered to be the fundamental approach to many biological questions, and the input dataset performs a crucial role in investigating and visualizing the gene regulatory network [5, 14, 17, 23, 34, 37, 40, 41, 44, 45]. Several software tools [2, 5, 7, 10, 11, 14, 21, 22, 25, 31-33, 37, 38, 40, 41, 44] have recently been developed for GRN inference, where some are designed for a particular dataset, an organism or a particular diseased cell. The questions that prompted this review are; what is (are) the kind of omic data needed to construct a GRN? Is there any peculiar property attached to a GRN of a particular data? And, could there be an integration of data from various omic experiments in form of a knowledge base? The input dataset for GRN are transcriptome information which is analyzed comprehensively including the two major technologies (sources) that produce them. We consider four omic datasets and two of their sources for the purpose of this review. The biological data source technologies are hybridization-based, and sequence-based. Dataset from microarray and ChIP-Chip experiments are hybridization-based while RNA-seq and ChIP-seq are sequence-based. Software tools published on Omic Tool website (http://omictools.com/gene-regulatory-networks-c435-p1.html) are analyzed for this review. However, the major disparity is whether the dataset is ChIP-X (ChIP-Chip and ChIP-seq) or expression (Microarray and RNA-seq) dataset not whether the source is from hybridization-based or sequence-based. Moreover, ChIP-X dataset gives more opportunity to investigate more biological problems. The importance of gene regulatory network suggests a GRN software template, which contains all the additional data from ChIP-X experiment and a knowledge base of biological prior knowledge, including integration of data from different omic datasets as a single knowledge base.
Vitamin D Receptor TaqI Gene Variant in Exon 9 and Polycystic Ovary Syndrome Risk

Background: Polycystic ovary syndrome (PCOS) is known as a metabolic disorder. The results of recent studies implied that vitamin D receptor (VDR) genetic variants may impact PCOS and insulin resistance in women with PCOS. The aim of the present study was to determine the VDR TaqI gene variant in exon 9 (T/C) (rs731236) in normal controls and patients with PCOS for the first time in Iranian Azeri women. Materials and Methods: In this case control study between April 2011 and June 2012, a total of 76 women aged 18-40 years (38 patients with PCOS and 38 healthy women as normal controls) participated. Genotypes of VDR TaqI in exon 9 (T/C) (rs731236) were determined using the PCR-RFLP method. Results: The frequencies of VDR TaqI T anc C alleles were 0.605 and 0.395 in cases and 0.697 and 0.303 in controls. Also, the genotypic frequencies of VDR TaqI were 16) (42.11), 14(36.84), and 8(21.05) in cases, and 17(44.74), 19(50), and 2(5.26) in controls for TT, TC and CC genotypes respectively. There was no difference in genotype and allele frequencies between PCOS and controls (p value>0.05) with the exception of the CC genotype (p value=0.04). Conclusion: This report, a first of its own kind in Iranian Azeri patients, suggests that the CC genotype of VDR TaqI in exon 9 (rs731236) is associated with PCOS.
Fostering Resilience Among Urban Youth Exposed to Violence

Most studies to date have examined negative effects of exposure to community violence, in line with the deficit-based perspective. However, given that most youth exposed to community violence demonstrate positive adaptation or resilience over time, we suggest a shift in perspective, practices, and policies across systems toward identifying and building individual, family, and community assets and strengths that may more effectively support youth who have been exposed to community violence and related risks into competent, caring, and thriving adults. In this article, we review how resilience has been conceptualized and operationalized within the context of community violence, highlight gaps in literature, and offer directions for future public health research and practice. We illustrate this review with practice-based examples from public health work in the San Francisco Bay Area. Future multidisciplinary longitudinal studies that identify protective processes and successful trajectories and rigorous evaluations of strength-based policies, programs, and protective processes are needed.
Role of Positive Psychological Strengths and Big five Personality Traits in Coping Mechanism of University Students

Present study aimed to explore the relationship of coping strategies with positive psychological strengths i.e., hope, optimism, self efficacy and resiliency and big-five personality factors among undergraduate university students. Data were collected from 200 students in universities of the Federal Territory Kuala Lumpur, Malaysia. Psychological Capital Questionnaire (Luthans's et al. 2007) [1], Brief Cope Scale (Carver, Scheire & Weintraub, 1989) [2], and Ten-Items Personality Inventory (Swann, Rentfrow, & Gosling, 2003) [3]. were used. Research findings revealed that Positive psychological strengths and Big five personality dimensions were found to be significantly related to coping responses except neuroticism, as persons with high neuroticism were found to be less engage in coping mechanism, while high extraversion, openness and conscientiousness individuals engaged in more problem-focused coping. The results indicate personality factors and PsyCap are emerged as important domains for coping mechanisms.
CONTROL OF PEDESTRIAN-INDUCED BRIDGE VIBRATIONS BY TUNED LIQUID COLUMN DAMPERS

In this paper tuned liquid column dampers (TLCD) are proposed for vibration control of footbridges. TLCD are innovative vibration absorbing devices applicable to the low frequency range (< 3 5 4 0 . . − Hz ) of bridges. Oblique bending and torsional motions of a continuous bridge with several TLCD installed are described mathematically and analyzed numerically. The dynamic behavior due to pedestrian excitation of the original Millennium Bridge in London is considered and it is shown that the installation of three TLCD to the main-span would have been necessary to secure its serviceability. The numerical simulations indicate that the TLCD increase the natural material damping of the bridge, which suppresses the instability phenomenon of synchronization, as discussed by Newland [1]. It is concluded that TLCD are effective and economic damping devices for the control of pedestrian-induced vibrations of footbridges.
Development and verification of cooperative adaptive cruise control via LTE‐V

In this study, the authors present a testbed platform for realising cooperative adaptive cruise control enabled by LTE-V (LTE-vehicle). The platform is developed on a platoon of vehicles, each of which is equipped with a suite of on-board sensing and computing devices for environment perception, as well as an LTE-V transceiver for high-performance vehicle-to-vehicle (V2V) communication. The hardware architecture and software architecture, especially the perception and control methods, of the platform are described. Field experiments in different road conditions are conducted to verify the feasibility of the authors’ platform. The results also show the potential of V2V communications via LTE-V in terms of improving the sensing capability of individual vehicle's on-board sensors.
Document image database retrieval and browsing using texture analysis

A system is presented that uses texture to retrieve and browse images stored in a large document image database. A method of graphically generating a candidate search image is used that shows the visual layout and content of a target document. All images similar to this candidate are returned for the purpose of browsing or further query. The system is accessed using a World Wide Web (Web) browser. Applications include the retrieval and browsing of document images including newspapers, fares and business letters.
A clinically relevant mouse model of cisplatin-induced kidney injury.

v LIST OF TABLES. ix LIST OF FIGURES. x CHAPTER 1: BACKGROUND AND INTRODUCTION. 1 CHAPTER 2: SUB-CLINICAL KIDNEY INJURY INDUCED BY REPEATED CISPLATIN ADMINISTRATION RESULTS IN PROGRESSIVE CHRONIC KIDNEY DISEASE. 21 CHAPTER 3: AGING DOES NOT LEAD TO INCREASED SUSCEPTIBILITY TO CISPLATIN-INDUCED KIDNEY INJURY OR EXACERBATED INJURY WITH REPEATED, LOW DOSE CISPLATIN ADMINISTRATION. 57 CHAPTER 4: TREATMENT WITH REPEATED DOSING OF CISPLATIN CAUSES WORSENED FIBROSIS IN A MOUSE MODEL OF KRAS4BG12D LUNG ADENOCARCINOMA THAT CANNOT BE PREVENTED WITH ERLOTINIB. 86 SUMMARY AND DISCUSSION. 117 STRENGTHS AND LIMITATIONS. 124 FUTURE DIRECTIONS. 127 REFERENCES. 133
Firms' investment under financial constraints: a euro area investigation

In this article we describe a model of optimal investment of various types of financially constrained firms. We show that the resulting relationship between internal funds and investment is nonmonotonic. In particular, the magnitude of Cash Flow (CF) sensitivity of the investment is lower for the firms with credit rationing compared to the firms that are able to obtain short-term external financing. The inverse relationship is driven by the leverage multiplier effect. A positive CF shock increases the short-term borrowing capacity of the firm, which in turn has a positive effect on investment and the firm's growth. Moreover, the leverage multiplier effect is the highest for firms relying on short-term credits and it is lower for firms that are able to obtain long-term financing. Analysing a large euro area data set we find strong empirical support for our theoretical predictions. The results also help to explain some contrasting findings in the financial constraints literature.
Metabolomic Tools for Secondary Metabolite Discovery from Marine Microbial Symbionts

Marine invertebrate-associated symbiotic bacteria produce a plethora of novel secondary metabolites which may be structurally unique with interesting pharmacological properties. Selection of strains usually relies on literature searching, genetic screening and bioactivity results, often without considering the chemical novelty and abundance of secondary metabolites being produced by the microorganism until the time-consuming bioassay-guided isolation stages. To fast track the selection process, metabolomic tools were used to aid strain selection by investigating differences in the chemical profiles of 77 bacterial extracts isolated from cold water marine invertebrates from Orkney, Scotland using liquid chromatography-high resolution mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. Following mass spectrometric analysis and dereplication using an Excel macro developed in-house, principal component analysis (PCA) was employed to differentiate the bacterial strains based on their chemical profiles. NMR 1H and correlation spectroscopy (COSY) were also employed to obtain a chemical fingerprint of each bacterial strain and to confirm the presence of functional groups and spin systems. These results were then combined with taxonomic identification and bioassay screening data to identify three bacterial strains, namely Bacillus sp. 4117, Rhodococcus sp. ZS402 and Vibrio splendidus strain LGP32, to prioritize for scale-up based on their chemically interesting secondary metabolomes, established through dereplication and interesting bioactivities, determined from bioassay screening.