Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns of Fungal Colonization in Preterm Infants Weighing Less Than 1000 Grams at Birth

Background: Colonization with Candida spp. is an important risk factor for systemic infection in very low birth weight (VLBW; <1500 g) and extremely low birth weight (ELBW, <1000 g) infants. ELBW infants are at a higher risk than VLBW infants for fungal sepsis and its associated mortality, but few studies have examined fungal colonization exclusively in ELBW infants. Methods: Fungal colonization data were analyzed retrospectively in 50 high risk ELBW infants. Weekly surveillance fungal cultures of the skin, gastrointestinal tract, respiratory tract and umbilicus had been performed from birth through the first 6 weeks of life. Colonization was analyzed for time of initial colonization, site, species and spread of Candida from one site to another. Results: Candida was isolated from surveillance cultures in 31 of 50 (62%) infants. Colonization was inversely proportional to gestational age. Initial week of both the fungal colonization of the skin [1 (0–6) week, median (range)] and gastrointestinal tract [2 (0–6)] preceded colonization of the respiratory tract [3 (1–6)] (P = 0.0001). Among infants colonized by only 1 of the species, colonization at 2 or more sites occurred similarly with Candida albicans (77%) and Candida parapsilosis (85%), whereas colonization at 3 or more sites occurred more frequently with C. albicans (69%) compared with C. parapsilosis (23%) (P = 0.047). Conclusions: Fungal colonization occurs on the skin and gastrointestinal tract before the respiratory tract. In addition, C. albicans is more likely than C. parapsilosis to colonize multiple sites.
Students’ loyalty in higher education: The mediating effect of satisfaction, trust, commitment on student loyalty to Alma Mater

Article history: Received: March 14, 2019 Received in revised format: April 19 2019 Accepted: April 29, 2019 Available online: April 30, 2019 Students’ loyalty enhances sustainability and survival rate of higher education institutions. Successful university managers and higher education thrive to improve service quality and to build loyalty among local and international students to sustain under the globalization. The aim of this research was to investigate the mediation effect of some key long-term relationship antecedent variables such as trust, satisfaction, and commitment between the perceived service quality and student loyalty latent variables. The relationship between the constructs in the instrument was tested through Partial Least squares (PLS) structural equations methodology using SmartPLS 3 program. The results of this research show that perceived service quality impacts loyalty specifically through commitment. Students’ loyalty is significantly influenced by commitment. However, student satisfaction has no significant direct effects on loyalty. Student trust has a negative effect on student loyalty so the results indicate that commitment fully mediates the effects of perceived service quality on student loyalty. Hence, university managers revitalize and sustain students’ loyalty if along with high quality services they also stimulate bonds and students identification with the university by reinforcing emotional force such as commitment. © 2019 by the authors; licensee Growing Science, Canada
Therapeutics , Targets , and Chemical Biology ARecombinant Reporter System forMonitoring Reactivation of an Endogenously DNA Hypermethylated Gene

Reversing abnormal gene silencing in cancer cells due to DNA hypermethylation of promoter CpG islands may offer new cancer prevention or therapeutic approaches. Moreover, such approachesmay be broadly applicable to enhance the efficacy of radiotherapy, chemotherapy, or immunotherapy. Here, we demonstrate the powerful utility of a novel gene reporter system to permit studies of the dynamics, mechanisms, and translational relevance of candidate therapies of this type in human colon cancer cells. The reporter system is based on in situ modification of the endogenous locus of the tumor-suppressor gene SFRP1, a pivotal regulator of theWnt pathway that is silenced by DNA hypermethylation in many colon cancers. The modified SFRP1-GFP reporter allele used remained basally silent, like the unaltered allele, and it was activated only by drug treatments that derepress gene silencing by reversingDNAhypermethylation.Weused the establishedDNAmethyltransferase inhibitor (DNMTi) 5-aza-deoxycitidine (DAC) to show how this system can be used to address key questions in the clinical development of epigenetic cancer therapies. First, we defined conditions forwhich clinically relevant dosing could induce sustained induction of RNA and protein. Second, we found that, in vivo, a more prolonged drug exposure than anticipated was essential to derepress gene silencing in significant cell numbers, and this has implications for generating effective anticancer responses in patients with hematopoietic or solid tumors. Finally, we discovered how histone deacetylase inhibitors (HDACi) alone, when administered to cells actively replicating DNA, can robustly reexpress the silenced gene with no change in promoter methylation status. Taken together, ourfindings offer a new tool and insights for devising optimal clinical experiments to evaluateDNMTi andHDACi, alone or in combination, and with other cancer treatments, as agents for the epigenetic management and prevention of cancer. Cancer Res; 74(14); 3834–43. 2014 AACR.
Practical indoor localization using ambient RF

The article presents a simple, practical approach for indoor localization using Received Signal Strength fingerprints from the GSM network, including an analysis of the relationship between signal strength and location, and the evolution of localization performance over time. Support Vector Machine regression applied to very high dimensional fingerprints does not reveal any smooth functional relationship between fingerprints and position. Classification using Support Vector Machines however provides very good results on discriminating different rooms in an indoor environment, albeit with performance that degrades over time. Transductive inference, introduced as a means of updating models to overcome degradation over time, provides hints that accurate indoor localization can be achieved by applying classification methods to cellular Received Signal Strength fingerprints, performance robustness being maintained via model updating and refining.
Degenerate perturbation theory corrections for the vibrational self-consistent field approximation: Method and applications

A new algorithm for computing anharmonic vibrational states for polyatomic molecules is proposed. The algorithm starts with the vibrational self-consistent field (VSCF) method and uses degenerate perturbation theory to correct for effects of correlation between different vibrational modes. The algorithm is developed in a version that computes the anharmonic vibrational spectroscopy directly from potential energy surface points calculated by using ab initio codes. The method is applied to several molecules where near degeneracies occur for excited vibrational states, including HOOH, HSSH, and HOOOH. The method yields results in very good accordance with experiments and generally provides improvements over nondegenerate perturbation corrections for VSCF.
Point Cloud Segmentation and Recognition Deep Learning Dataset for Ornamental trees and Shrubs Environment

The rapid collection and real-time detection of forest resources information is the key to improving the efficiency of forestry survey and realizing the intelligent cultivation and harvesting of under-forest resources. In recent years, tremendous amount of progress is being made in the field of 3D Machine Learning, which is an interdisciplinary field that fuses computer vision, computer graphics and machine learning. Few prior works study deep learning on point sets. The 3D point cloud classification in urban scenes has been widely applied in the fields of automatic driving, map updating, change detection, etc. Accurate and effective classification of mobile laser scanning (MLS) point clouds remains a big challenge for these applications. The existing point cloud processing algorithms have poor generalization ability, weak robustness, low precision, and poor real-time performance, which are urgent scientific problems to be solved. PointNet is a pioneer in this direction. In this paper a dataset produced by FARO 3D laser scanner was generated to test its ability to recognize fine-grained patterns like artificial pruning Ornamental trees and shrubs. As the result, the typical spherical bush segmentation in a big scene could be precisely acquire throughout the Pointnet method. It shows a great potential in identify and segment complex forest environment point clouds in the future.
X-ray coherent scattering form factors of tissues, water and plastics using energy dispersion

A key requirement for the development of the field of medical x-ray scatter imaging is accurate characterization of the differential scattering cross sections of tissues and phantom materials. The coherent x-ray scattering form factors of five tissues (fat, muscle, liver, kidney, and bone) obtained from butcher shops, four plastics (polyethylene, polystyrene, lexan (polycarbonate), nylon), and water have been measured using an energy-dispersive technique. The energy-dispersive technique has several improvements over traditional diffractometer measurements. Most notably, the form factor is measured on an absolute scale with no need for scaling factors. Form factors are reported in terms of the quantity x = λ−1sin (θ/2) over the range 0.363–9.25 nm−1. The coherent form factors of muscle, liver, and kidney resemble those of water, while fat has a narrower peak at lower x, and bone is more structured. The linear attenuation coefficients of the ten materials have also been measured over the range 30–110 keV and parameterized using the dual-material approach with the basis functions being the linear attenuation coefficients of polymethylmethacrylate and aluminum.
Speeding Up GPU Graph Processing Using Structural Graph Properties

1 PROBLEM STATEMENT Due to its flexibility and wide applicability, graph processing is an important part of data science. With the prevalence of “big data”, scaling increasingly complex analytics to increasingly large datasets is one of the fundamental problems in graph processing. At the same time, hardware platforms are becoming increasingly parallel and heterogeneous. Distributed systems and acceleratorbased architectures (e.g., based on Graphical Processing Units — GPUs, or Xeon Phi) are frequently cited as solutions for handling large compute workloads, even for graph processing [1, 11]. Both partitioning the data and efficient execution of graph operations on parallel and distributed systems remain hard problems. The heterogeneity of the available platforms makes matters worse, because different types of platforms require different approaches to perform in their “comfort zone”. I focus on the performance of graph operations on GPUs, seen as representative massively parallel HPC architectures. In this context, I start from the following observations:
Chronic Exposure to Proline Causes Aminoacidotoxicity and Impaired Beta-Cell Function: Studies In Vitro.

BACKGROUND Pancreatic islet-cell dysfunction is a hallmark in the development of diabetes, but the reasons for the primary β-cell defect are still elusive. Elevated circulating proline levels have been found in subjects with insulin resistance, obesity, and type 2 diabetes. Therefore, we assessed β-cell function, gene expressions, and cell death after long-term exposure of pancreatic β-cells to excess proline in vitro. METHODS Isolated mouse islets and INS-1E cells were incubated with and without excess proline. After 72 h, we examined: (1) β-cell function, including basal insulin secretion (BIS) and glucose-stimulated insulin secretion (GSIS), (2) transcription factors related to insulin gene expression and enzymes involved in the tricarboxylic acid cycle and cholesterol biogenesis, (3) cellular triglycerides (TG) and cholesterol content, (4) the death of INS-1E cells and 3H thymidine incorporation, and (5) protein expression of INS-1E cells in response to proline by proteomics. RESULTS We found that high doses of proline increased BIS and decreased GSIS in both isolated mouse islets and INS-1E cells. MafA, insulin 1, and the cytochrome c oxidase subunit VIa polypeptide 2 mRNA expressions were all downregulated, indicating that proline impaired insulin gene transcription and mitochondrial oxidative phosphorylation. In contrast, mevalonate decarboxylase gene expression was upregulated, and simultaneously, cholesterol content in INS-1E cells was enhanced. Protein profiling of INS-1E cells revealed that cytosolic non-specific dipeptidase and α enolase were differentially expressed. CONCLUSIONS Our results indicate that proline-induced insulin transcription and mitochondrial oxidative phosphorylation impairment may contribute to the β-cell dysfunction observed in type 2 diabetes. Caution should be applied in interpreting the pathophysiological role of proline since very high proline concentrations were used in the experiments.
Fenugreek and other lesser known legume galactomannan-polysaccharides: Scope for developments

Among useful plants, legumes stand next only to grasses, yet the variety of products produced from legumes are more numerous than those from grasses, which mainly contain glucans (starches & cellulose), hemicelluloses andsugars as carbohydrates. Some legume seeds additionally have galactomannans and amyloid as endosperm reserve polysaccharides, while many legume trees exude variety of gums. Because of unique industrial applications, legume galactomannans have acquired commercial value. There are many unutilized tropical legume galactomannans that could be exploited. This review presents galactomannans of some less common legumes.
Innate resistance to experimental Trypanosoma congolense infection: differences in IL‐10 synthesis by macrophage cell lines from resistant and susceptible inbred mice

BALB/c and C57Bl/6 mice differ in resistance to T. congolense infections. We investigated the production of various cytokines (IL‐10, IL‐6, TNF‐α and TGF‐β) by macrophages from these mice. Macrophage cell lines (BALB.BM cells) of BALB/c mice but not (ANA‐1 cells)of C57BL/6 mice constitutively produced IL‐10. Challenge of these cells with trypanosomes induced the production of 50–100 times more IL‐10 in BALB.BM cells than in ANA‐1 cells. Pre‐incubation of the cell lines with IFN‐γ, prior to the trypanosome challenge, further upregulated this IL‐10 production in BALB.BM but not in ANA‐1 cells. Primary cultures of bone marrow‐derived macrophages (BMDM) from BALB/c mice also produced more IL‐10 following challenge with IFN‐γ and opsonized trypanosomes than did the C57Bl/6 BMDM. Similarly after challenge with trypanosomes, BALB.BM and BALB/c BMDM produced significantly more IL‐6 than did the analogous cells from the C57Bl/6 mice following such challenges. Higher steady state levels of TNF‐α mRNA accumulated in ANA‐1 cells than in BALB.BM cells following challenge with IFN‐γ and opsonized trypanosomes. Findings of this study for the first time indicate a differential regulation of cytokines (IL‐10, IL‐6 and TNF‐α) in macrophages of mice that significantly differ in their susceptibility to infections with T. congolense.
Estimating Drivers of Autochthonous Transmission of Chikungunya Virus in its Invasion of the Americas

Background Chikungunya is an emerging arbovirus that has caused explosive outbreaks in Africa and Asia for decades and invaded the Americas just over a year ago. During this ongoing invasion, it has spread to 45 countries where it has been transmitted autochthonously, infecting nearly 1.3 million people in total. Methods Here, we made use of weekly, country-level case reports to infer relationships between transmission and two putative climatic drivers: temperature and precipitation averaged across each country on a monthly basis. To do so, we used a TSIR model that enabled us to infer a parametric relationship between climatic drivers and transmission potential, and we applied a new method for incorporating a probabilistic description of the serial interval distribution into the TSIR framework. Results We found significant relationships between transmission and linear and quadratic terms for temperature and precipitation and a linear term for log incidence during the previous pathogen generation. The lattermost suggests that case numbers three to four weeks ago are largely predictive of current case numbers. This effect is quite nonlinear at the country level, however, due to an estimated mixing parameter of 0.74. Relationships between transmission and the climatic variables that we estimated were biologically plausible and in line with expectations. Conclusions Our analysis suggests that autochthonous transmission of Chikungunya in the Americas can be correlated successfully with putative climatic drivers, even at the coarse scale of countries and using long-term average climate data. Overall, this provides a preliminary suggestion that successfully forecasting the future trajectory of a Chikungunya outbreak and the receptivity of virgin areas may be possible. Our results also provide tentative estimates of timeframes and areas of greatest risk, and our extension of the TSIR model provides a novel tool for modeling vector-borne disease transmission.
Tropical Forests and the Global Carbon Cycle

New data on the three major determinants of the carbon release from tropical forest clearing are used in a computer model that simulates land use change and its effects on the carbon content of vegetation and soil in order to calculate the net flux of carbon dioxide between tropical ecosystems and the atmosphere. The model also permits testing the sensitivity of the calculated flux to uncertainties in these data. The tropics were a net source of at least 0.4 x 1015 grams but not more than 1.6 x 1015 grams of carbon in 1980, considerably less than previous estimates. Decreases in soil organic matter were responsible for 0.1 x 1015 to 0.3 x 1015 grams of the release, while the burning and decay of cleared vegetation accounted for 0.3 x 1015 to 1.3 x 1015 grams. These estimates are lower than many previous ones because lower biomass estimates and slightly lower land clearing rates were used and because ecosystem recovery processes were included. These new estimates of the biotic release allow for the possibility of a balanced global budget given the large remaining uncertainties in the marine, terrestrial, and fossil fuel components of the carbon cycle.
Hba(1c) as a tool for the diagnosis of type 2 diabetes: comparison with fasting glucose.

BACKGROUND Glycated hemoglobin (HbA(1c)) has been proposed for the diagnosis of diabetes. However, several countries have not incorporated its use for this purpose yet and there is no consensus on a suitable cut-off point of HbA(1c) for the diagnosis of diabetes. Thus, the aim of this study was to evaluate the diagnostic characteristics of HbA(1c) and fasting plasma glucose (FPG) for the assessment of type 2 diabetes. METHODS FPG, HbA(1c), and creatinine levels were assessed in 47 patients with type 2 diabetes and 46 healthy controls. RESULTS The areas under the curve for HbA(1c) > or = 6.5% and FPG > or = 7.0 mmol/L were 0.97 and 0.92, respectively. HbA(1c). has a slightly higher ability to discriminate type 2 diabetes compared with FPG. The association between HbA(1c) and type 2 diabetes was independent of gender, age, hypertension, smoking, and body mass index. CONCLUSIONS HbA(1c) was able to be used for the diagnosis of type 2 diabetes.
Some aspects of the composition of buffalo semen.

An earlier report from this laboratory (Banerjee & Ganguli, 1971) was con-cerned with the electrophoretic and gel filtration behaviour of seminal plasma proteins in Zebu and buffalo bull semen. The chemical composition of Zebu semen has been reported by Mann (1964) and that of buffalo semen by Roy, Karnik, Lukuture, Bhattacharya & Bhattacharya (1950) and Roy, Pandey & Rawat (1960). The present work was undertaken in order to evaluate the nature of the composition of semen from Zebu and buffalo bulls maintained in our Institute's herd.
Stochastic geometrical modeling for built-up area understanding from a single SAR intensity image with meter resolution

To investigate the limits and merits of information extraction from a single high-resolution synthetic aperture radar (SAR) backscatter image, we introduce a model-based algorithm for the automatic reconstruction of building areas from single-observation meter-resolution SAR intensity data. The reconstruction is based on the maximum a posteriori estimation by Monte Carlo methods of an optimal scene that is modeled as a set of mutually interacting Poisson-distributed marked points describing parametric building objects. Each of the objects can be hierarchically decomposed into a collection of radiometrically and geometrically specified object facets that in turn get mapped into data features by ground-to-range projection and inverse Gaussian statistics. The detection of the facets is based on a likelihood ratio. Results are presented for airborne data with resolutions in the range of 0.5-2 m on urban scenes covering agglomerations of buildings. To achieve robust results for building reconstruction, the integration with data from other sources is needed.
Journal of Engineering and Technology ( SJET ) ISSN 2321-435 X ( Online )

The current study proposes a verb-based method of relation pattern extraction, which aims to extract entity relations with high accuracy from Chinese website corpus. In this study, entity identifications of human names and island/reef names are carried out by means of ICTCLAS and entity table; accurate sentence examples are generated; and, consequently, verb-based relation patterns are constructed. The experiment results show that the proposed method has good extraction performance.
Analytical Gate Delay Variation Model with Temperature Effects in Near-Threshold Region Based on Log-Skew-Normal Distribution

The near-threshold design is widely employed in the energy-efficient circuits, but it suffers from a high sensitivity to process variation, which leads to 2X delay variation due to temperature effects. Hence, it is not negligible. In this paper, we propose an analytical model for gate delay variation considering temperature effects in the near-threshold region. The delay variation model is constructed based on the log-skew-normal distribution by moment matching. Moreover, to deal with complex gates, a multi-variate threshold voltage approximation approach of stacked transistors is proposed. Also, three delay metrics (delay variability, ± 3 σ percentile points) are quantified and have a comparison with other known works. Experimental results show that the maximum of delay variability is 5% compared with Monte Carlo simulation and improves 5X in stacked gates compared with lognormal distribution. Additionally, it is worth mentioning that, the proposed model exhibits excellent advantages on − 3 σ and stacked gates, which improves 5X–10X in accuracy compared with other works.