Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Spatial-based Targeted Disease Containment Strategies using Mobile Phone Data

Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment processes during epidemics. Using a real-world dataset from Ivory Coast, this work presents an attempt to unveil the socio-geographical heterogeneity of disease transmission dynamics. By employing a spatially explicit meta-population epidemic model derived from mobile phone Call Detail Records (CDRs), we investigate how the differences in mobility patterns may affect the course of a realistic infectious disease outbreak. We consider different existing measures of the spatial dimension of human mobility and interactions, and we analyse their relevance in identifying the highest risk sub-population of individuals, as the best candidates for isolation countermeasures. The approaches presented in this paper provide further evidence that mobile phone data can be effectively exploited to facilitate our understanding of individuals' spatial behaviour and its relationship with the risk of infectious diseases' contagion. In particular, we show that CDRs-based indicators of individuals' spatial activities and interactions hold promise for gaining insight of contagion heterogeneity and thus for developing containment strategies to support decision-making during country-level pandemics.
Disease genes and intracellular protein networks.

By a computational approach we reconstructed genomic transcriptional profiles of 19 different adult human tissues, based on information on activity of 27,924 genes obtained from unbiased UniGene cDNA libraries. In each considered tissue, a small number of genes resulted highly expressed or "tissue specific. " Distribution of gene expression levels in a tissue appears to follow a power law, thus suggesting a correspondence between transcriptional profile and "scale-free" topology of protein networks. The expression of 737 genes involved in Mendelian diseases was analyzed, compared with a large reference set of known human genes. Disease genes resulted significantly more expressed than expected. The possible correspondence of their products to important nodes of intracellular protein network is suggested. Auto-organization of the protein network, its stability in time in the differentiated state, and relationships with the degree of genetic variability at genome level are discussed.
Mesh Decimation Using VTK

This paper describes general mesh decimation methods which operate on triangle meshes. The goal of the mesh decimation is the reduction of triangles in a mesh while preserving the shape and topology as good as possible. Further the usage of mesh decimation with the Visualization Tool Kit (VTK) is explained. Currently VTK (version 4.0, June 2002) contains four mesh decimation classes: vtkDecimate, vtkDecimatePro, vtkQuadricDecimation and vtkQuadricClustering. The paper describes also the differences between those classes.
Simulating awareness in global software engineering: A comparative analysis of Scrum and Agile Service Networks

Global software engineering (GSE) is a business strategy to realize a business idea (i.e. the development project) faster, through round-the-clock productivity. However, GSE creates a volatile and unstable process in which many actors interact together against unpredictable premises (e.g. cultural or time differences), often producing unexpected outcomes (e.g. compacting effects of distance and time). So far, Scrum has been used extensively for embarking in global software engineering, but many of the problems in Scrum-based GSE could still benefit from the usage of ad-hoc supporting tools (e.g. information continuity between timezones, cultural differences, developers awareness, etc.). Agile Service Networks (ASNs) are networks of service oriented applications (nodes) that collaborate adaptively towards a common goal. ASNs offer a way to represent GSE professionals through service-oriented “social” nodes in a “small-world” network (much like a Facebook for a specific GSE project). This paper presents a comparison between the two approaches, namely Scrum and ASNs, to determine ASN's potentials as mechanisms to maintain awareness in GSE.
Pulmonary Hypertension an Independent Risk Factor for Death in Intensive Care Unit: Correlation of Hemodynamic Factors with Mortality

Objective Critically ill patients with pulmonary hypertension (PH) pose additional challenges due to the existence of right ventricular (RV) dysfunction. The purpose of this study was to assess the impact of hemodynamic factors on the outcome. Methods We reviewed the records of patients with a diagnosis of PH admitted to the intensive care unit. In addition to evaluating traditional hemodynamic parameters, we defined severe PH as right atrial pressure >20 mmHg, mean pulmonary artery pressure >55 mmHg, or cardiac index (CI) <2 L/min/m2. We also defined the RV functional index (RFI) as pulmonary artery systolic pressure (PASP) adjusted for CI as PASP/CI; increasing values reflect RV dysfunction. Results Fifty-three patients (mean age 60 years, 72% women, 79% Blacks), were included in the study. Severe PH was present in 68% of patients who had higher Sequential Organ Failure Assessment (SOFA) score (6.8 ± 3.3 vs 3.8 ± 1.6; P = 0.001) and overall in-hospital mortality (36% vs 6%; P = 0.02) compared to nonsevere patients, although Acute Physiology and Chronic Health Evaluation (APACHE) II scores (19.9 ± 7.5 vs 18.5 ± 6.04; P = 0.52) were similar and sepsis was more frequent among nonsevere PH patients (31 vs 64%; P = 0.02). Severe PH (P = 0.04), lower mean arterial pressure (P = 0.04), and CI (P = 0.01); need for invasive ventilation (P = 0.02) and vasopressors (P = 0.03); and higher SOFA (P = 0.001), APACHE II (P = 0.03), pulmonary vascular resistance index (PVRI) (P = 0.01), and RFI (P = 0.004) were associated with increased mortality. In a multivariate model, SOFA [OR = 1.45, 95% confidence interval (C.I.) = 1.09-1.93; P = 0.01], PVRI (OR = 1.12, 95% C.I. = 1.02-1.24; P = 0.02), and increasing RFI (OR = 1.06, 95% C.I. = 1.01-1.11; P = 0.01) were independently associated with mortality. Conclusion PH is an independent risk factor for mortality in critically ill patients. Composite factors rather than individual hemodynamic parameters are better predictors of outcome. Monitoring of RV function using composite hemodynamic factors resulting in specific interventions is likely to improve survival and needs to be studied further.
C OMPARISON OF C APILLARY AND V ENOUS G LUCOSE M EASUREMENTS IN H EALTHY V OLUNTEERS

Background. Out-of-hospital (OOH) emergency personnel measure serum glucose in order to determine the need for dextrose therapy. Most devices that measure serum glucose are designed to use capillary blood obtained from a finger puncture. However, OOH emergency personnel often use venous blood obtained during intravenous line (IV) placement to determine serum glucose. Objective. To compare capillary and venous glucose measurements. Methods. This prospective study used healthy, non-fasting volunteers. Simultaneous venous and capillary blood samples were obtained from each subject. Glucose levels were measured using a glucometer designed for capillary samples. The capillary and venous measurements were compared using a Pearson correlation coefficient. Power analysis revealed that the study had the ability to detect a difference of 15 mg/dL. Results. Ninety-seven volunteers (56 males, 41 females) with a mean age of 37 ± 11.9 years were enrolled. The mean capillary and venous glucose values were 104.5 ± 20.7 mg/dL and 109.7 ± 22.4 mg/dL, respectively. The Pearson correlation coefficient was 0.24. Conclusions. The correlation between venous and capillary blood glucose measurements is relatively poor in this group of healthy volunteers. Further research must be conducted on patients at risk for abnormal blood glucose.
Demonstration of the Static Magnetic Fields Inability to Improve the Bone Mineral Density in an Osteoporotic Rat Model

Objectives: Osteoporosis is a raising public health issue. There are several medications in the treatment of osteoporosis and osteoporotic-related fractures involving either enhancement of the osteogenesis or inhibition of the osteoclastogenestis. However, each medication has side effect. Therefore, we try to look for an alternative therapy for the treatment of osteoporosis, which increases bone mineral density without accompanying side effects. Methods: In the current study, we used a Static Magnetic Field (SMF) to evaluate the hypothesis of improvement of the bone mineral density after an SMF exposure. In-vitro, we tested the capacities of osteogenesis and osteoclastogenesis on Mesenchymal Stem Cells (MSCs). In-vivo, we implanted a permanent magnet adjacent to the vertebrae in an osteoporotic rat model to examine the effects on the treatment of osteoporosis Results: In cell culture studies, a positive osteogenesis effect of Mesenchymal Stem Cells (MSCs) was observed under an SMF exposure; this osteogenesis effect was correlated to the SMF intensity. However, there was no effect on the osteoclastogenesis of MSCs under the same condition. In an osteoporotic rat model, there was no positive effect on alteration of the bone mineral density after a persistent 6-week exposure by an implanted SMF. Conclusion: An in-vitro study showed that an SMF exposure of MSCs had a positive osteogenesis effect. However, there was no effect in terms of improvement of the bone mineral density when the SMF was applied on the osteoporotic rat model.
A Study on Efficient Data Mining Approach on Compressed Transaction

Data mining can be viewed as a result of the natural evolution of information technology. The spread of computing has led to an explosion in the volume of data to be stored on hard disks and sent over the Internet. This growth has led to a need for data compression, that is, the ability to reduce the amount of storage or Internet bandwidth required to handle the data. This paper analysis the various data mining approaches which is used to compress the original database into a smaller one and perform the data mining process for compressed transaction such as MTQT,PINCER-SEARCH algorithm, APRIORI & ID3 algorithm, TM algorithm, AIS & SETM, CT-Apriori algorithm, CBMine, CT-ITL algorithm, FIUTTree. Among the various techniques MTQT uses the relationship of transactions to merge related transactions and builds a quantification table to prune the candidate item sets which are impossible to become frequent in order to improve the performance of mining association rules. Thus MTQT is observed to perform better than existing approaches.
High-rank coded aperture projection for extended depth of field

Projectors require large apertures to maximize light throughput. Unfortunately, this leads to shallow depths of field (DOF), hence blurry images, when projecting on non-planar surfaces, such as cultural heritage sites, curved screens, or when sharing visual information in everyday environments. We introduce high-rank coded aperture projectors - a new computational display technology that combines optical designs with computational processing to overcome depth of field limitations of conventional devices. In particular, we employ high-speed spatial light modulators (SLMs) on the image plane and in the aperture of modified projectors. The patterns displayed on these SLMs are computed with a new mathematical framework that uses high-rank light field factorizations and directly exploits the limited temporal resolution and contrast sensitivity of the human visual system. With an experimental prototype projector, we demonstrate significantly increased DOF as compared to conventional technology.
The Gender Productivity Gap

Using Danish matched employer-employee data, this paper estimates the relative productivity of men and women and finds that the gender “productivity gap” is 12 percent—seventy five percent of the 16 percent residual pay gap can be accounted for by productivity differences between men and women. I measure the productivity gap by estimating the efficiency units lost in a firm-level production function if a worker is female, holding other explanatory covariates such as age, education, experience, and hours worked constant. To study the mechanisms behind the 4 percent gap in pay that is unexplained by productivity, I use data on parenthood and age. Mothers are paid much lower wages than men, but their estimated productivity gap completely explains their pay gap. In contrast, women without children are estimated to be as productive as men but they are not compensated at the same rate as men. The decoupling of pay and productivity for women without children happens during their prime-child bearing years. I provide estimates of the productivity gap in the cross-section and estimates that account for endogenous sorting of women into less productive firms using a control-function approach inspired by Olley-Pakes. This paper also provides estimates of the gender productivity gap across industries and occupations. Though the results do vary across industries and occupations, the overall estimate of the productivity gap is fairly robust to the specification of the production function. JEL Classification: J71, J31, J24
A robust and accurate approach to automatic blood vessel detection and segmentation from angiography x-ray images using multistage random forests

In this paper we propose a novel approach based on multi-stage random forests to address problems faced by traditional vessel segmentation algorithms on account of image artifacts such as stitches organ shadows etc. Our approach consists of collecting a very large number of training data consisting of positive and negative examples of valid seed points. The method makes use of a 14x14 window around a putative seed point. For this window three types of feature vectors are computed viz. vesselness, eigenvalue and a novel effective margin feature. A random forest RF is trained for each of the feature vectors. At run time the three RFs are applied in succession to a putative seed point generated by a naiive vessel detection algorithm based on vesselness. Our approach will prune this set of putative seed points to correctly identify true seed points thereby avoiding false positives. We demonstrate the effectiveness of our algorithm on a large dataset of angio images.
Surface treatments of plant fibers and their effects on mechanical properties of fiber-reinforced composites: A review

The need of natural fiber-reinforced composites is increasing at very fast rate because of their ecofriendly production, decomposition, high specific strength, abundance, good physical and mechanical properties. Available literature reveals that past researchers have done a lot of work for the preparation and characterization of fiber-reinforced composites. While developing natural fiber composites, researchers encountered various problems like hydrophilic nature of natural fibers, incompatibility of natural fibers with matrix materials, thermal instability of natural fibers, and poor interfacial bonding between reinforcing phase and matrix phase. However, some of these problems can be solved to a greater extent by considering surface treatment of natural fibers before they are used in the preparation of fiber-reinforced composites. Thus, there is a need for understanding the effect of several surface treatments on the mechanical properties of fiber-reinforced composites. The aim of this paper is to put forth a comprehensive review on the effects of different surface treatments on the mechanical properties such as tensile strength, flexural strength, and impact strength and also interfacial shear strength of the fiber-reinforced composites.
Empirically-motivated Generalizations of CCG Semantic Parsing Learning Algorithms

Learning algorithms for semantic parsing have improved drastically over the past decade, as steady improvements on benchmark datasets have shown. In this paper we investigate whether they can generalize to a novel biomedical dataset that differs in important respects from the traditional geography and air travel benchmark datasets. Empirical results for two state-of-the-art PCCG semantic parsers indicates that learning algorithms are sensitive to the kinds of semantic and syntactic constructions used in a domain. In response, we develop a novel learning algorithm that can produce an effective semantic parser for geography, as well as a much better semantic parser for the biomedical dataset.
Construction of an Ultrahigh Pressure Liquid Chromatography-Tandem Mass Spectral Library of Plant Natural Products and Comparative Spectral Analyses.

A plant natural product tandem mass spectral library has been constructed using authentic standards and purified compounds. Currently, the library contains 1734 tandem mass spectra for 289 compounds, with the majority (76%) of the compounds being plant phenolics such as flavonoids, isoflavonoids, and phenylpropanoids. Tandem mass spectra and chromatographic retention data were acquired on a triple quadrupole mass spectrometer coupled to an ultrahigh pressure liquid chromatograph using six different collision energies (CEs) (10-60 eV). Comparative analyses of the tandem mass spectral data revealed that the loss of ring substituents preceded the C-ring opening during the fragmentation of flavonoids and isoflavonoids. At lower CE (i.e., 10 and 20 eV), the flavonoids and isoflavonoid central ring structures typically remained intact, and fragmentation was characterized by the loss of the substituents (i.e., methyl and glycosyl groups). At higher CE, the flavonoid and isoflavonoid core ring systems underwent C-ring cleavage and/or rearrangement depending on the structure, particularly hydroxylation patterns. In-source electrochemical oxidation was observed for phenolics that had ortho-diphenol moieties (i.e., vicinal hydroxyl groups on the aromatic rings). The ortho-diphenols were oxidized to ortho-quinones, yielding an intensive and, in most cases, a base ion peak corresponding to a [(M - 2H) - H](-) ion in their mass spectra. The library also contains reverse-phase retention times, allowing for the construction, validation, and testing of an artificial neural network retention prediction of other flavonoids and isoflavonoids not contained within the library. The library is freely available for nonprofit, academic use and it can be downloaded at http://www.noble. org/apps/Scientific/WebDownloadManager/DownloadArea.aspx.
GeneMed: An Informatics Hub for the Coordination of Next-Generation Sequencing Studies that Support Precision Oncology Clinical Trials

We have developed an informatics system, GeneMed, for the National Cancer Institute (NCI) molecular profiling-based assignment of cancer therapy (MPACT) clinical trial (NCT01827384) being conducted in the National Institutes of Health (NIH) Clinical Center. This trial is one of the first to use a randomized design to examine whether assigning treatment based on genomic tumor screening can improve the rate and duration of response in patients with advanced solid tumors. An analytically validated next-generation sequencing (NGS) assay is applied to DNA from patients’ tumors to identify mutations in a panel of genes that are thought likely to affect the utility of targeted therapies available for use in the clinical trial. The patients are randomized to a treatment selected to target a somatic mutation in the tumor or with a control treatment. The GeneMed system streamlines the workflow of the clinical trial and serves as a communications hub among the sequencing lab, the treatment selection team, and clinical personnel. It automates the annotation of the genomic variants identified by sequencing, predicts the functional impact of mutations, identifies the actionable mutations, and facilitates quality control by the molecular characterization lab in the review of variants. The GeneMed system collects baseline information about the patients from the clinic team to determine eligibility for the panel of drugs available. The system performs randomized treatment assignments under the oversight of a supervising treatment selection team and generates a patient report containing detected genomic alterations. NCI is planning to expand the MPACT trial to multiple cancer centers soon. In summary, the GeneMed system has been proven to be an efficient and successful informatics hub for coordinating the reliable application of NGS to precision medicine studies.
PTHrP Overexpression Increases Sensitivity of Breast Cancer Cells to Apo2L/TRAIL

Parathyroid hormone-related protein (PTHrP) is a key component in breast development and breast tumour biology. PTHrP has been discovered as a causative agent of hypercalcaemia of malignancy and is also one of the main factors implicated in breast cancer mediated osteolysis. Clinical studies have determined that PTHrP expression by primary breast cancers was an independent predictor of improved prognosis. Furthermore, PTHrP has been demonstrated to cause tumour cell death both in vitro and in vivo. Apo2L/TRAIL is a promising new anti-cancer agent, due to its ability to selectively induce apoptosis in cancer cells whilst sparing most normal cells. However, some cancer cells are resistant to Apo2L/TRAIL-induced apoptosis thus limiting its therapeutic efficacy. The effects of PTHrP on cell death signalling pathways initiated by Apo2L/TRAIL were investigated in breast cancer cells. Expression of PTHrP in Apo2L/TRAIL resistant cell line MCF-7 sensitised these cells to Apo2L/TRAIL-induced apoptosis. The actions of PTHrP resulted from intracellular effects, since exogenous treatment of PTHrP had no effect on Apo2L/TRAIL-induced apoptosis. Apo2L/TRAIL-induced apoptosis in PTHrP expressing cells occurred through the activation of caspase-10 resulting in caspase-9 activation and induction of apoptosis through the effector caspases, caspase-6 and -7. PTHrP increased cell surface expression of Apo2L/TRAIL death receptors, TRAIL-R1 and TRAIL-R2. Antagonistic antibodies against the death receptors demonstrated that Apo2L/TRAIL mediated its apoptotic signals through activation of the TRAIL-R2 in PTHrP expressing breast cancer cells. These studies reveal a novel role for PTHrP with Apo2L/TRAIL that maybe important for future diagnosis and treatment of breast cancer.