Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Effective Elastic Parameters of Nodular Cast Iron from Micro-Tomographic Imaging and Multiscale Finite Elements: Comparison between Numerical and Experimental Results

Herein, we describe in detail a methodology to estimate the effective elastic parameters of nodular cast iron, using micro-tomography in conjunction with multiscale finite elements. We discuss the adjustment of the image acquisition parameters, address the issue of the representative-volume choice, and present a brief discussion on image segmentation. In addition, the finite-element computational implementation developed to estimate the effective elastic parameters from segmented microstructural images is described, indicating the corresponding computational costs. We applied the proposed methodology to a nodular cast iron, and estimated the graphite elastic parameters through a comparison between the numerical and experimental results.
and other research outputs Evaluation datasets for Twitter sentiment analysis : a survey and a new dataset , the STS-Gold Conference Item How to

Sentiment analysis over Twitter offers organisations and individuals a fast and effective way to monitor the publics’ feelings towards them and their competitors. To assess the performance of sentiment analysis methods over Twitter a small set of evaluation datasets have been released in the last few years. In this paper we present an overview of eight publicly available and manually annotated evaluation datasets for Twitter sentiment analysis. Based on this review, we show that a common limitation of most of these datasets, when assessing sentiment analysis at target (entity) level, is the lack of distinctive sentiment annotations among the tweets and the entities contained in them. For example, the tweet “I love iPhone, but I hate iPad” can be annotated with a mixed sentiment label, but the entity iPhone within this tweet should be annotated with a positive sentiment label. Aiming to overcome this limitation, and to complement current evaluation datasets, we present STS-Gold, a new evaluation dataset where tweets and targets (entities) are annotated individually and therefore may present different sentiment labels. This paper also provides a comparative study of the various datasets along several dimensions including: total number of tweets, vocabulary size and sparsity. We also investigate the pair-wise correlation among these dimensions as well as their correlations to the sentiment classification performance on different datasets.
Investigating Mitochondrial Metabolism in Contracting HL-1 Cardiomyocytes Following Hypoxia and Pharmacological HIF Activation Identifies HIF-Dependent and Independent Mechanisms of Regulation

Hypoxia is a consequence of cardiac disease and downregulates mitochondrial metabolism, yet the molecular mechanisms through which this occurs in the heart are incompletely characterized. Therefore, we aimed to use a contracting HL-1 cardiomyocyte model to investigate the effects of hypoxia on mitochondrial metabolism. Cells were exposed to hypoxia (2% O2) for 6, 12, 24, and 48 hours to characterize the metabolic response. Cells were subsequently treated with the hypoxia inducible factor (HIF)-activating compound, dimethyloxalylglycine (DMOG), to determine whether hypoxia-induced mitochondrial changes were HIF dependent or independent, and to assess the suitability of this cultured cardiac cell line for cardiovascular pharmacological studies. Hypoxic cells had increased glycolysis after 24 hours, with glucose transporter 1 and lactate levels increased 5-fold and 15-fold, respectively. After 24 hours of hypoxia, mitochondrial networks were more fragmented but there was no change in citrate synthase activity, indicating that mitochondrial content was unchanged. Cellular oxygen consumption was 30% lower, accompanied by decreases in the enzymatic activities of electron transport chain (ETC) complexes I and IV, and aconitase by 81%, 96%, and 72%, relative to controls. Pharmacological HIF activation with DMOG decreased cellular oxygen consumption by 43%, coincident with decreases in the activities of aconitase and complex I by 26% and 30%, indicating that these adaptations were HIF mediated. In contrast, the hypoxia-mediated decrease in complex IV activity was not replicated by DMOG treatment, suggesting HIF-independent regulation of this complex. In conclusion, 24 hours of hypoxia increased anaerobic glycolysis and decreased mitochondrial respiration, which was associated with changes in ETC and tricarboxylic acid cycle enzyme activities in contracting HL-1 cells. Pharmacological HIF activation in this cardiac cell line allowed both HIF-dependent and independent mitochondrial metabolic changes to be identified.
Spectral Efficiency Optimization for an Interfering Cognitive Radio with Adaptive Modulation and Coding

In this paper, we consider a primary and a cognitive user transmitting over a wireless fading interference channel. The primary user transmits with a constant power and utilizes an adaptive modulation and coding (AMC) scheme satisfying a bit error rate requirement. We propose a link adaptation scheme to maximize the average spectral efficiency of the cognitive radio, while a minimum required spectral efficiency for the primary user is provisioned. The resulting problem is constrained to also satisfy a bit error rate requirement and a power constraint for the cognitive link. The AMC mode selection and power control at the cognitive transmitter is optimized based on the modified signal to noise plus interference ratio feedback of both links. The problem is then cast as a nonlinear discrete optimization problem for which a fast and efficient suboptimum solution is presented. We also present a scheme with rate adaptive and constant power cognitive radio. An important characteristic of the proposed schemes is that no computation or coordination overhead is imposed on the primary radio due to the cognitive radio activity. Numerical results and comparison with the interweave approach to cognitive radio demonstrate the efficiency of the proposed solutions.
Mechanisms for Vascular Cell Adhesion Molecule-1 Activation of ERK1/2 during Leukocyte Transendothelial Migration

Background During inflammation, adhesion molecules regulate recruitment of leukocytes to inflamed tissues. It is reported that vascular cell adhesion molecule-1 (VCAM-1) activates extracellular regulated kinases 1 and 2 (ERK1/2), but the mechanism for this activation is not known. Pharmacological inhibitors of ERK1/2 partially inhibit leukocyte transendothelial migration in a multi-receptor system but it is not known whether VCAM-1 activation of ERK1/2 is required for leukocyte transendothelial migration (TEM) on VCAM-1. Methodology/Principal Findings In this study, we identified a mechanism for VCAM-1 activation of ERK1/2 in human and mouse endothelial cells. VCAM-1 signaling, which occurs through endothelial cell NADPH oxidase, protein kinase Cα (PKCα), and protein tyrosine phosphatase 1B (PTP1B), activates endothelial cell ERK1/2. Inhibition of these signals blocked VCAM-1 activation of ERK1/2, indicating that ERK1/2 is activated downstream of PTP1B during VCAM-1 signaling. Furthermore, VCAM-1-specific leukocyte migration under physiological laminar flow of 2 dynes/cm2 was blocked by pretreatment of endothelial cells with dominant-negative ERK2 K52R or the MEK/ERK inhibitors, PD98059 and U0126, indicating for the first time that ERK regulates VCAM-1-dependent leukocyte transendothelial migration. Conclusions/Significance VCAM-1 activation of endothelial cell NADPH oxidase/PKCα/PTP1B induces transient ERK1/2 activation that is necessary for VCAM-1-dependent leukocyte TEM.
Effects of low dose quercetin: Cancer cell‐specific inhibition of cell cycle progression

Quercetin is a flavonoid present in many vegetables, fruits, and beverages. Due to its anti‐oxidant, anti‐tumor, and anti‐inflammatory activity, quercetin has been studied extensively as a chemoprevention agent in several cancer models. Since most of these studies used higher doses of quercetin than clinically achievable, we focused on the effectiveness of physiologically relevant doses of quercetin. A low dose of quercetin exerted cancer cell‐specific inhibition of proliferation and this inhibition resulted from cell cycle arrest at the G1 phase. Quercetin induced p21 CDK inhibitor with a concomitant decrease of phosphorylation of pRb, which inhibits the G1/S cell cycle progression by trapping E2F1. A low dose of quercetin induced mild DNA damage and Chk2 activation, which is the main regulator of p21 expression by quercetin. In addition, quercetin down‐regulated the cyclin B1 and CDK1, essential components of G2/M cell cycle progression. Inhibition of the recruitment of key transcription factor NF‐Y to cyclin B1 gene promoter by quercetin led to transcriptional inhibition. This study proved that the chemo‐preventive efficacy of a physiologically relevant dose of quercetin can be achievable through the inhibition of cell cycle progression. J. Cell. Biochem. 106: 73–82, 2009. © 2008 Wiley‐Liss, Inc.
Symptom propagation and transformation analysis: A pragmatic model for system-level diagnosis of large automation systems

In automation systems, the diagnostic task is to efficiently deduce candidates for replacement or repair from centrally available observations. Often, classic model-based diagnosis cannot provide a practical solution as it requires in-depth knowledge of system components and their functions and interactions. Such detailed data is seldom readily available. Our approach to system-level diagnosis adopts a purely non-functional view of the system, similar to field-tested safety assessment techniques, e.g. fault trees or FMEA, but goes beyond that to support core diagnostic analyses (runtime diagnosis and diagnosability). We propose a new component-based model that is solely focused on faults and causal propagation and the transformation of symptoms. Modeling is now an iterative process that supports refinement as new data becomes available. We evaluate our approach on a small-scale rail automation example.
Ecological multiplex interactions determine the role of species for parasite spread amplification

Despite their potential interplay, multiple routes of many disease transmissions are often investigated separately. As a unifying framework for understanding parasite spread through interdependent transmission paths, we present the ‘ecomultiplex’ model, where the multiple transmission paths among a diverse community of interacting hosts are represented as a spatially explicit multiplex network. We adopt this framework for designing and testing potential control strategies for Trypanosoma cruzi spread in two empirical host communities. We show that the ecomultiplex model is an efficient and low data-demanding method to identify which species enhances parasite spread and should thus be a target for control strategies. We also find that the interplay between predator-prey and host-parasite interactions leads to a phenomenon of parasite amplification, in which top predators facilitate T. cruzi spread, offering a mechanistic interpretation of previous empirical findings. Our approach can provide novel insights in understanding and controlling parasite spreading in real-world complex systems.
On comparison of growth curves: How do we test whether growth rates differ?

Comparisons of growth rates of populations and species are important in fi sheries science for a range of reasons that vary with the context of each study. Most studies of fi sh growth have focused on the practical issues of the most appropriate way of comparing growth rather than on recognizing that there are several methods for making these comparisons and that the conclusions will differ depending on the method chosen. Francis (1996) discussed the problem of how to compare different growth rates or growth curves. He suggested six plausible ways of making a comparison and suggested that the rate at which the asymptotic size is approached was the most natural method of comparing growth (his method 6). He illustrated the differences between the methods by comparing von Bertalanffy growth equations that are based on fi xed growth parameters and that assumed that growth parameters are known and there are no associated uncertainties. However, in practice, the growth parameters are often estimated, and therefore are random variables. Consequently, the corresponding growth curves are also subject to variations. For comparison with Francis’s work, we will assume that growth for a speOn comparison of growth curves: How do we test whether growth rates differ?
Autonomous Portable Solar Ultraviolet Spectroradiometer (APSUS) – a New CCD Spectrometer System for Localized, Real‐Time Solar Ultraviolet (280–400 nm) Radiation Measurement

Terrestrial solar ultraviolet (UV) radiation has significant implications for human health and increasing levels are a key concern regarding the impact of climate change. Monitoring solar UV radiation at the earth's surface is therefore of increasing importance. A new prototype portable CCD (charge‐coupled device) spectrometer‐based system has been developed that monitors UV radiation (280–400 nm) levels at the earth's surface. It has the ability to deliver this information to the public in real time. Since the instrument can operate autonomously, it is called the Autonomous Portable Solar Ultraviolet Spectroradiometer (APSUS). This instrument incorporates an Ocean Optics QE65000 spectrometer which is contained within a robust environmental housing. The APSUS system can gather reliable solar UV spectral data from approximately April to October inclusive (depending on ambient temperature) in the UK. In this study the new APSUS unit and APSUS system are presented. Example solar UV spectra and diurnal UV Index values as measured by the APSUS system in London and Weymouth in the UK in summer 2012 are shown.
Climate and Tick Seasonality Are Predictors of Borrelia burgdorferi Genotype Distribution

ABSTRACT The blacklegged tick, Ixodes scapularis, is of significant public health importance as a vector of Borrelia burgdorferi, the agent of Lyme borreliosis. The timing of seasonal activity of each immature I. scapularis life stage relative to the next is critical for the maintenance of B. burgdorferi because larvae must feed after an infected nymph to efficiently acquire the infection from reservoir hosts. Recent studies have shown that some strains of B. burgdorferi do not persist in the primary reservoir host for more than a few weeks, thereby shortening the window of opportunity between nymphal and larval feeding that sustains their enzootic maintenance. We tested the hypothesis that climate is predictive of geographic variation in the seasonal activity of I. scapularis, which in turn differentially influences the distribution of B. burgdorferi genotypes within the geographic range of I. scapularis. We analyzed the relationships between climate, seasonal activity of I. scapularis, and B. burgdorferi genotype frequency in 30 geographically diverse sites in the northeastern and midwestern United States. We found that the magnitude of the difference between summer and winter daily temperature maximums was positively correlated with the degree of seasonal synchrony of the two immature stages of I. scapularis. Genotyping revealed an enrichment of 16S-23S rRNA intergenic spacer restriction fragment length polymorphism sequence type 1 strains relative to others at sites with lower seasonal synchrony. We conclude that climate-associated variability in the timing of I. scapularis host seeking contributes to geographic heterogeneities in the frequencies of B. burgdorferi genotypes, with potential consequences for Lyme borreliosis morbidity.
Where Are the GaPs? A Rational Approach to Monomer Acquisition and Selection

Gridding and partitioning (GaP) is a computational method for the classification and selection of monomers for combinatorial libraries. The molecules are described in terms of the pharmacophoric groups they contain and where those pharmacophoric groups can be located in three-dimensional space. The approach involves a detailed conformational analysis of each molecule. This conformational analysis is done within a common coordinate frame, thus enabling the monomers to be compared. The use of a partitioned space is central to this particular application as it facilitates the identification of regions of space which are not well represented by existing compounds. Several ways to extend the use of partitioned pharmacophore spaces are described. Applications of the approach in monomer acquisition and in library design are outlined.
Profit Sharing and Workplace Productivity: Does Teamwork Play a Role?

The conditions under which profit sharing affects workplace productivity have never been fully understood. Using panel data, this paper examines whether there is any link between adoption of an employee profit sharing plan and subsequent productivity growth in Canadian establishments, and whether this relationship is affected by various contextual factors, particularly use of work teams. In so doing, we use both three and five-year panels. Overall, we find a significant link between adoption of a profit sharing program and subsequent productivity growth in both panels, but only among establishments that utilize employee work teams.
Hermes: A Privacy-Preserving Approximate Search Framework for Big Data

We propose a sampling-based framework for privacy-preserving approximate data search in the context of big data. The framework is designed to bridge multi-target query needs from users and the data platform, including required query accuracy, timeliness, and query privacy constraints. A novel privacy metric, $(\varepsilon,\delta)$ -approximation, is presented to uniformly measure accuracy, efficiency and privacy breach risk. Based on this, we employ bootstrapping to efficiently produce approximate results that meet the preset query requirements. Moreover, we propose a quick response mechanism to deal with homogeneous queries, and discuss the reusage of results when appending data. Theoretical analyses and experimental results demonstrate that the framework is capable of effectively fulfilling multi-target query requirements with high efficiency and accuracy.
Network Robustness and Graph Topology

Two important recent trends in military and civilian communications have been the increasing tendency to base operations around an internal network, and the increasing threats to communications infrastructure. This combination of factors makes it important to study the robustness of network topologies. We use graph-theoretic concepts of connectivity to do this, and argue that node connectivity is the most useful such measure. We examine the relationship between node connectivity and network symmetry, and describe two conditions which robust networks should satisfy. To assist with the process of designing robust networks, we have developed a powerful network design and analysis tool called CAVALIER, which we briefly describe.
Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory

Abstract OBJECTIVE: Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. MATERIALS AND METHODS: This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. RESULTS: For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. CONCLUSION: This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes.
Finite Element Modeling of Welded Joints

This work deals with the simulation of fusion welding by the Finite Element Method. The implemented models include moving heat sources, temperature dependence of thermo-physical properties, elasto-plasticity, non-steady state heat transfer, and mechanical analysis. It is assumed that the thermal problem is not coupled with the mechanical one, being the thermal analysis performed separately and prior to the mechanical analysis. The mechanical problem is based on thermal history. A special treatment is performed on mechanical elements during the liquid/solid and solid/liquid phase changes. The three-dimensional stress state of a butt-welded joint is obtained as an example of application.
An Early Warning System for Islamic Banks Performance

There is increasing demand for predicting the performane of Islamic banks due to the vital importance of any problem that may face these banks before it materializes and negatively affects their performance and their financial status. This will save on the costs of bad performance or failure to depositors, owners and the economy. Thus, a need arises for an early warning system which will identify the possible causes of bad performance, detect potential problem banks, facilitate surveilence of banks as well as reduce its costs and make possible proper timing of examining problem banks as well as scheduling the remedical procedures. This research aims at benefiting from the previous research efforts on the subject to develop a preliminary model for the prediction of the performance level of Islamic banks (i.e. an early warning system), hoping that this will be a cornerstone for further development and improvisation, specially as more information and data become available or accessible. To achieve such objective Discriminant Analysis technique will be utilized, whereby a Discriminant Function will be designed comprising the significant characteristics (financial ratios) as explanatory variables and the profitability rate as dependent variable. Discriminant scores are then extracted and used to distinguish between high performance and low performance groups of banks, thus forming a possible early warning system for the prediction of future performance of the observed banks. The prediction power of such a system is finally tested and conclusions drawn.