Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyponatraemia and death or permanent brain damage in healthy children.

OBJECTIVE--To determine if hyponatraemia causes permanent brain damage in healthy children and, if so, if the disorder is primarily limited to females, as occurs in adults. DESIGN--Prospective clinical case study of 16 affected children and a review of 24,412 consecutive surgical admissions at one medical centre. PATIENTS--16 children (nine male, seven female; age 7 (SD 5) years) with generally minor illness were electively hospitalised for primary care. Consultation was obtained for the combination of respiratory arrest with symptomatic hyponatraemia (serum sodium concentration less than or equal to 128 mmol/l). MAIN OUTCOME MEASURES--Presence, gender distribution, and classification of permanent brain damage in children with symptomatic hyponatraemia in both prospective and retrospective studies. RESULTS--By retrospective evaluation the incidence of postoperative hyponatraemia among 24,412 patients was 0.34% (83 cases) and mortality of those afflicted was 8.4% (seven deaths). In the prospective population the serum sodium concentration on admission was 138 (SD 2) mmol/l. From three to 120 inpatient hours after hypotonic fluid administration patients developed progressive lethargy, headache, nausea, and emesis with an explosive onset of respiratory arrest. At the time serum sodium concentration was 115 (7) mmol/l and arterial oxygen tension 6 (1.5) kPa. The hyponatraemia was primarily caused by extrarenal loss of electrolytes with replacement by hypotonic fluids. All 16 patients had cerebral oedema detected at either radiological or postmortem examination. All 15 patients not treated for their hyponatraemia in a timely manner either died or were permanently incapacitated by brain damage. The only patient treated in a timely manner was alive but mentally retarded. CONCLUSIONS--Symptomatic hyponatraemia can result in high morbidity in children of both genders, which is due in large part to inadequate brain adaptation and lack of timely treatment.
Quantifying the Effectiveness of Mobile Phone Virus Response Mechanisms

Viruses that infect smartphones are emerging as a new front in the fight against computer viruses. In this paper, we model the propagation of mobile phone viruses in order to study their impact on the dependability of mobile phones. We propose response mechanisms and use the models to obtain insight on the effectiveness of these virus mitigation techniques. In particular, we consider the effects of multimedia messaging system (MMS) viruses that spread by sending infected messages to other phones. The virus model is implemented using the Mobius software tool and is highly parameterized, enabling representation of a wide range of potential MMS virus behavior. Using the model, we present the results of four illustrative MMS virus scenarios simulated with and without response mechanisms. By measuring the propagation rate and the extent of virus penetration in the simulation phone population, we quantitatively compare the effectiveness of mobile phone virus response mechanisms.
Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces

The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery–based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)–based MI-BCI. Tangent space mapping is a powerful method of feature extraction and strongly depends on the selection of a reference covariance matrix. In general, the observed signals may include outliers; therefore, taking the geometric mean of SCMs as the reference matrix may not be the best choice. In order to deal with the effects of outliers, robust estimators have to be used. In particular, we discuss and test the use of geometric medians and trimmed averages (defined on the basis of several metrics) as robust estimators. The main idea behind trimmed averages is to eliminate data that exhibit the largest distance from the average covariance calculated on the basis of all available data. The results of the experiments show that while the geometric medians show little differences from conventional methods in terms of classification accuracy in the classification of electroencephalographic recordings, the trimmed averages show significant improvement for all subjects.
Automatic design of multi-objective local search algorithms: case study on a bi-objective permutation flowshop scheduling problem

Multi-objective local search (MOLS) algorithms are efficient meta-heuristics, which improve a set of solutions by using their neighbourhood to iteratively find better and better solutions. MOLS algorithms are versatile algorithms with many available strategies, first to select the solutions to explore, then to explore them, and finally to update the archive using some of the visited neighbours. In this paper, we propose a new generalisation of MOLS algorithms incorporating new recent ideas and algorithms. To be able to instantiate the many MOLS algorithms of the literature, our generalisation exposes numerous numerical and categorical parameters, raising the possibility of being automatically designed by an automatic algorithm configuration (AAC) mechanism. We investigate the worth of such an automatic design of MOLS algorithms using MO-ParamlLS, a multi-objective AAC configurator, on the permutation flowshop scheduling problem, and demonstrate its worth against a traditional manual design.
Band structure computation of one-dimensional photonic crystal

In this paper, the band structure for 1-D photonic crystal structure, which is composed of two different dielectric layers in a one-dimensional pattern, obtained by transfer matrix method, is reported. It has been observed that the bandgap depends on the contrast of dielectric constant and thickness of dielectric layers. Further, it is found that the enhanced bandgap can be obtained by changing the dielectric contrast and thickness of the layers. Primary & Secondary bandgaps are also estimated and the bandgaps have been engineered with reference to their dependence on spacing between layers and dielectric contrasts. Further, we also report the band gap calculation of three different dielectric layers stacked in 1-D periodic structure. Such structure might find its application in the design & development of asymmetric planar photonic crystals
COMPARATIVE STUDY OF BROWSER BASED OPEN SOURCE TESTING TOOLS WATIR AND WET

Abstract-Recently, web browser based applications have become very popular in many domains. As an important method to ensure the quality of Web applications, Web testing attracts more and more attentions in the academic community and industrial world. Testing Web applications raises new problems and faces very high challenges. Recently web applications have grown rapidly and have become more and more complex. As web applications become more complex, there is a growing concern about their quality. Web application testing is a challenging work owing to its dynamic behaviors and complex dependencies. As in case what if the end user uses different types of browsers to access the application. So, to deal with Browser compatibility issue this work proposes Browser based testing tools named as Watir (Web Application Testing in Ruby) and WET for the scenario of web-based applications. Starting with the preliminary architectural design, this paper includes the testing scenario for both the tools along with the comparative analysis based on well defined parameters.
A new algorithm for global fault collapsing into equivalence and dominance sets

Nodes in a dominance graph represent faults of a circuit. A directed edge from node f/sub i/ to node f/sub j/ means that fault f/sub j/ dominates f/sub i/. The equivalence of faults f/sub i/ and f/sub j/ is indicated by the presence of simultaneous edges f/sub i/ /spl rarr/ f/sub j/ and f/sub j/ /spl rarr/ f/sub i/. When local dominance and equivalence relations are included in this graph, its transitive closure provides the collapsed fault sets. Pre-collapsed fault sets of standard cells and other logic blocks can be stored in a graph library for hierarchical fault collapsing. Examples show how more compact fault sets are obtained by using functional equivalences that can be found by analysis of small cells. Benchmark circuits c432 and c499 are used to illustrate the use of functional fault collapsing within their exclusive-OR cells.
Electrospun MWCNTs/Poly(lactic-co-glycolic acid) Composite Nanofibrous Drug Delivery System

In this study, nanotubular materials multi-walled carbon nanotubes (MWCNTs) were used to encapsulate a model drug, doxorubicine hydrochloride (DOX). Then, the drug-loaded nanotubes (DOX/CNTs) with an optimized drug encapsulation percentage were mixed with poly (lactide-co-glycolide) (PLGA) polymer solution for subsequent electrospinning to form drug-loaded composite nanofibrous mats. The morphology was characterized using scanning electron microscopy (SEM). The proliferation of mouse fibroblast cells cultured on both PLGA and CNTs-doped PLGA fibrous scaffolds were compared through 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyl tetrazolium bromide (MTT) assay of cell viability and SEM observation of cell morphology. In vitro drug release behavior was examined using UV-vis spectroscopy. We show that the incorporation of CNTs and DOX/CNTs within the nanofibrous mats does not significantly change the morphology of the mats. In addition, our results indicate that this double-container drug delivery system (both PLGA polymer and CNTs are drug carriers) is beneficial to avoid the burst release of the drug. The drug loaded elctrospinning composite nanofibrous mats developed in this study may find various applications in tissues engineering and pharmaceutical sciences.
Explicit predictive control of a hybrid system: A case study: Control of the longitudinal dynamics of a comercial vehicle at very low speed

Many complex systems of theoretical and practical interest can be modeled as hybrid systems, i.e., systems that exhibit both continuous and discrete dynamics. This work focuses on the explicit predictive control of hybrid systems using two free Matlab/Simulink toolboxes designed specifically to synthesize and simulate controllers for this kind of systems. A case study is considered. The system is modeled, from experimental results, after the longitudinal dynamics of a commercial car at low speed. Simulation results are analyzed and a comparative study of both toolboxes is carried out.
Gender-Specific Influence of NO Synthase Gene on Blood Pressure Since Childhood: The Bogalusa Heart Study

Impaired endothelial function caused by decreased NO production plays a pathophysiologic role in essential hypertension. Although cross-sectional data are available on the association between endothelial NO synthase gene polymorphisms and hypertension, whether the gene variants and their haplotypes affect the long-term cumulative burden and trend of blood pressure since childhood is not known. This aspect was examined using 4 polymorphisms and a community-based longitudinal cohort of 347 blacks and 801 whites aged 18 to 45 years who have been examined serially 4 to 13 times (7705 observations) over an on average of 23.4 years. The area under the curve calculated using a growth curve of serial measurements of mean arterial pressure was used as a long-term cumulative burden. Blacks compared with whites displayed significantly lower frequencies of the rare alleles for G894T (0.112 versus 0.325), G10T (0.209 versus 0.323), T-786C (0.147 versus 0.372), and A-922G (0.131 versus 0.355). In addition, T-786C and A-922G polymorphisms were in complete linkage disequilibrium in both races. After adjusting for age and body mass index, the 894T and 10T alleles were significantly associated with lower long-term burden of blood pressure since childhood in black females and white females, respectively. With respect to haplotypes, the G894-10T carriers compared with (G894-G10)/(G894-G10) showed significantly lower long-term burden and trend of blood pressure in white females. In conclusion, the endothelial NO synthase gene influences the long-term burden and trend of blood pressure since childhood in females and may contribute to their predisposition to hypertension.
Biological Relevance Detection via Network Dynamic Analysis

Most existing approaches for gene selection are based on evaluating the statistical relevance. However, there are remarkable discrepancies between statistical relevance and biological relevance. It is important to consider biological relevance for crucial genes identification. The task of detecting biological relevance presents two major challenges: first, how to define different types of measures to evaluate the biological relevance from multiple perspectives; and second, how to effectively integrate these measures to achieve better estimations. In this work, we propose to detect biological relevance by applying dynamics analysis using both biological networks and gene expression profiles from different phenotypes, and develop an effective probabilistic model to integrate various types of relevance measures in a unified form. Experimental results show the efficacy and potential of the proposed approach with promising findings.
1 C . elegans Egg-laying Detection and Behavior Study Using Image Analysis

2 Egg-laying is an important phase of the life cycle of the nematode Caenorhabditis elegans (C. elegans). Previous studies examined egg-laying events manually. This paper presents a method for automatic detection of egg-laying onset using deformable template matching and other morphological image analysis techniques. Some behavioral changes surrounding egg-laying events are also studied. The results demonstrate that the computer vision tools and algorithm developed here can be effectively used to study C. elegans egg-laying behaviors. The algorithm developed is an essential part of a machine vision system for C. elegans tracking and behavioral analysis.
Increased Energy Expenditure in Gastric Bypass Rats Is Not Caused by Activated Brown Adipose Tissue

Objective: To investigate whether gastric bypass induces a higher activity of brown adipose tissue and greater levels of the brown adipose tissue-specific protein uncoupling protein-1 (UCP-1) in rats. Methods: Gastric bypass rats and sham-operated controls (each n = 8) underwent whole body 1H-MR spectroscopy for analysis of body composition and 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography (18F-FDG PET/CT) imaging for measurement of the metabolic activity of brown adipose tissue. Brown adipose tissue was harvested and weighed, and UCP-1 mRNA content was measured by Northern Blot technique. Results: Gastric bypass rats had a significantly lower percentage of whole body adipose tissue mass compared to sham-operated rats (p = 0.001). There was no difference in brown adipose tissue activity between the two groups (standardised uptake value sham 2.81 ± 0.58 vs. bypass 2.56 ± 0.46 ; p = 0.73). Furthermore, there was no difference in the UCP-1 mRNA content of brown adipose tissue between the two groups (sham 49.5 ± 13.2 vs. bypass 43.7 ± 13.1; p = 0.77). Conclusion: Gastric bypass does not increase the activity of brown adipose tissue in rats suggesting that other mechanisms are involved to explain the increased energy expenditure after bypass surgery. Our results cannot justify the radiation dose of 18F-FDG PET/CT studies in humans to determine potential changes in brown adipose tissue after gastric bypass surgery.
Generating ontologies from Intelligent Tutoring System courses . A generic approach

In recent years a great effort has been done in order to create Intelligent Tutoring Systems that get close to the human teaching. Some of the handicaps of the systems already created is the impossibility of sharing the courses between different Intelligent Tutoring Systems and the difficulty to create them. Whereas a great amount of SCORM-compliant learning objects is being created for being imported in educational systems, there is a research current that pleads for ontologies as domain knowledge representation systems. We have created a generic and extensible authoring tool that creates courses for different intelligent tutoring systems. The authoring tool allows the creation of courses for different types of intelligent tutoring systems and saves those courses as ontologies. This allows the reusing of domain models between different Intelligent Tutoring Systems. This paper focuses in the ontology creation and populating process.
A soluble multimeric recombinant CD2 protein identifies CD48 as a low affinity ligand for human CD2: divergence of CD2 ligands during the evolution of humans and mice

To search for possible ligands of CD2 distinct from CD58 (lymphocyte function-associated antigen 3), we have produced a soluble pentameric CD2-immunoglobulin (Ig) fusion protein (spCD2) linking the 182-amino acid human CD2 extracellular segment with CH2-CH3-CH4 domains of human IgM heavy chain, thus enhancing the micromolar affinity of the CD2 monomer through multimeric interaction. Using quantitative immunofluorescence and standard stringency wash conditions, we observed that the binding of spCD2 to human B lymphoblastoid JY cells and red blood cells is virtually inhibited by anti-CD58 TS2/9 monoclonal antibody, even though these cells express levels of CD48 and CD59 comparable to CD58. Consistent with these results, spCD2 did not show any binding to Chinese hamster ovary (CHO) cells transfected with human CD48 or CD59. However, binding studies on CD48-, CD58-, or CD59- transfected CHO cells with spCD2 under low stringency wash conditions revealed that human CD48 is a low affinity ligand of human CD2 compared with CD58 (Kd approximately 10(-4) vs. approximately 10(-6) M, respectively). The findings are noteworthy given that in the murine system CD48 is the major ligand for CD2. No detectable binding was observed to CD59-transfected CHO cells despite a report suggesting that CD59 may bind to the human CD2 adhesion domain. Importantly, in cell- cell adhesion assays between CD2+ Jurkat T cells and CD48- or CD59- transfected CHO cells, there was no conjugate formation, whereas binding of Jurkat T cells to CD58-transfected CHO cells was readily detected. Collectively, our findings provide evidence for a conservation of the CD2-CD48 interaction in the human species that may be of limited, if any, functional significance. Given the importance of the CD2-CD48 interaction in the murine system and CD2-CD58 interaction in humans, it would appear that there has been a divergence of functional CD2 ligands during the evolution of humans and mice.
Preparation of poly(vinyl alcohol)/clay hydrogel through freezing and thawing followed by electron beam irradiation for the treatment of wastewater

In this work, poly(vinyl alcohol) (PVA)/clay hydrogel based on various ratios of clay (20%, 50%, and 60%) were prepared using freezing and thawing techniques followed by electron beam (EB) irradiation at different irradiation doses (20, 25, and 30 kGy). The physicochemical property of such hydrogel in terms of gel fraction (%) and water uptake (%) was investigated. The structure and property of the hydrogel were investigated by x-ray diffraction (XRD) and scanning electron microscope (SEM). Thermal property was investigated using differential scanning calorimetry and thermogravimetric analysis. The results indicated that the gel fraction (%) increases on increasing the clay content in the hydrogel at all irradiation doses. The results obtained by XRD and SEM show an intercalation and exfoliation between PVA and clay. The occurrence of one T g and T m of the hydrogel indicates the presence of complete miscibility between PVA and clay. Also, the prepared hydrogel exhibit high thermal stability by increasing clay content in the hydrogel. It was found that the prepared PVA/clay hydrogel has a high water uptake, making it acceptable for the use in treatment of wastewater from heavy and toxic metal ions and dye wastes.
Design and Analysis of a Multicolor Quantum Well Infrared Photodetector

Abstract : Recent military applications have demanded photodetectors with high sensitivity, high selectivity and multispectral capability for detection and identification of the target. These characteristics have been found in quantum well infrared photodetectors (QWIP). Driven by these applications, a QWIP photodetector capable of detecting simultaneously infrared emissions within near infrared (NIR), mid wavelength infrared (MWIR) and long wavelength infrared (LWIR) was studied, modeled, designed and characterized. Using the envelope function approximation, the mathematical model of the quantum phenomena in semiconductor heterostructures was derived. A computational tool was developed to solve self-consistently the Schodinger-Poisson equation using the shooting method, allowing the theoretical evaluation of the absorption coefficient. A three-color (NIR, MWIR and LWIR) GaAs-based QWIP sample and a two-color (NIR and MWIR) InP-based QWIP sample were designed, both comprised of stacks of uncoupled wells for each band detection. The 67 layers of the GaAs sample was grown using molecular beam epitaxy (MBE). Intersubband absorption in the sample was measured for the MWIR and LWIR using Fourier transform spectroscopy (FTIR) and the measured peak positions, found at 5.3 m , 8.7 m , and 13.8 m are within 0.3 m of the theoretical values, indicating that the model accurately predicts the absorption wavelengths. A twodimensional ordered grating pattern was selected and optimized separately for both MWIR and LWIR desired peaks. Finally the photodetector device configurations were designed to permit to the measurement of the NIR band through photocurrent spectroscopy and performance analysis. The fabrication and characterization of the prototypes are a matter for future work.
A l1-minimization Based Approach for Hyperspectral Data Classiﬁcation

Most of classiﬁcation methods require model learning procedure or optimal parameters selection using large number of training samples. In this paper, we propose a novel classiﬁcation approach using l1-minimization based sparse representation which does not need any learning procedure or parameters selection. The proposed approach is based on l1minimization because l0-minimization is generally NP-hard and is not a convex optimization problem. Sparse based solutions have been proposed in other areas like signal processing but to the best of our knowledge, this is the ﬁrst time that sparse based classiﬁcation is being proposed for the classiﬁcation of hyperspectral data. l1-minimization based sparse representation is calculated for each of the test samples using few training samples directly. In remote sensing, usually it is extremely difﬁcult and expensive to identify and label the samples due to which we often lack sufﬁcient training samples for classiﬁcation. We tested the proposed approach for difﬁcult classiﬁcation problem i.e high dimensional spaces and few training samples. We also analyzed the cases in which the sparse based classiﬁcation may and may not work. Our extensive experiments on real hyperspectral dataset (AVIRIS 1992 Indiana’s Indian Pines image), prove that the proposed technique offers more classiﬁcation accuracy and more efﬁcient than state-of-the-art SVM and semi-supervised methods as it does not need any model selection.