Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of switching from oral administration to intravenous injection of l-carnitine on lipid metabolism in hemodialysis patients

Background Carnitine deficiency may contribute to cardiovascular disease (CVD) in patients with hemodialysis (HD). Dyslipidemia plays a role in CVD and its prevalence is also high in HD patients. We examined here the effects of switching from oral administration (PO) to intravenous (IV) injection of l-carnitine on lipid metabolism in patients with HD. Methods Nine HD patients who had received l-carnitine orally (900 mg/day) for 1 year were enrolled in this study. We examined whether lipid parameters were improved by switching to IV injection therapy of 1000 mg l-carnitine. Results IV injection of l-carnitine for 1 week significantly increased total, free and acyl carnitine levels both before and after HD. Switching to IV injection therapy for 1 and 4 weeks decreased serum free fatty acid (FFA) (322 ± 104 versus 261 ± 124 µmol/L) and increased high-density lipoprotein-cholesterol levels (1.46 ± 0.49 versus 1.63 ± 0.62 mmol/L), respectively. Change in FFA values from the baseline (ΔFFA) was positively correlated with the Δacyl/free carnitine ratio (r2 = 0.553, P = 0.022). Conclusion This study demonstrated that switching to IV l-carnitine therapy from oral supplementation improved lipid profiles, thus supporting the clinical utility of IV administration of l-carnitine for the treatment of patients on HD.
Implementation of Algorithm for Satellite-Derived Bathymetry using Open Source GIS and Evaluation for Tsunami Simulation

Accurate and high resolution bathymetric data is a necessity for a wide range of coastal oceanographic research topics. Active sensing methods, such as ship-based soundings and Light Detection and Ranging (LiDAR), are expensive and time consuming solutions. Therefore, the significance of Satellite-Derived Bathymetry (SDB) has increased in the last ten years due to the availability of multi-constellation, multi-temporal, and multi-resolution remote sensing data as Open Data. Effective SDB algorithms have been proposed by many authors, but there is no ready-to-use software module available in the Geographical Information System (GIS) environment as yet. Hence, this study implements a Geographically Weighted Regression (GWR) based SDB workflow as a Geographic Resources Analysis Support System (GRASS) GIS module (i.image.bathymetry). Several case studies were carried out to examine the performance of the module in multi-constellation and multi-resolution satellite imageries for different study areas. The results indicate a strong correlation between SDB and reference depth. For instance, case study 1 (Puerto Rico, Northeastern Caribbean Sea) has shown an coefficient of determination (R2) of 0.98 and an Root Mean Square Error (RMSE) of 0.61 m, case study 2 (Iwate, Japan) has shown an R2 of 0.94 and an RMSE of 1.50 m, and case study 3 (Miyagi, Japan) has shown an R2 of 0.93 and an RMSE of 1.65 m. The reference depths were acquired by using LiDAR for case study 1 and an echo-sounder for case studies 2 and 3. Further, the estimated SDB has been used as one of the inputs for the Australian National University and Geoscience Australia (ANUGA) tsunami simulation model. The tsunami simulation results also show close agreement with post-tsunami survey data. The i.mage. bathymetry module developed as a part of this study is made available as an extension for the Open Source GRASS GIS to facilitate wide use and future improvements.
IN-KILN MOISTURE CONTENT MEASUREMENT OF TIMBER USING A WAVEGUIDE APERTURE ARRAY

A microwave technique for the measurement of average moisture content of stacked timber during kiln drying has been developed. This technique based upon a linear array of slots in a waveguide has been modelled and experimentally verified. The experimental trials using standard kiln drying schedules have shown the technique to be accurate to within 1%.
The Complexity of the Nucleolus in Compact Games

The nucleolus is a well-known solution concept for coalitional games to fairly distribute the total available worth among the players. The nucleolus is known to be NP-hard to compute over compact coalitional games, that is, over games whose functions specifying the worth associated with each coalition are encoded in terms of polynomially computable functions over combinatorial structures. In particular, hardness results have been exhibited over minimum spanning tree games, threshold games, and flow games. However, due to its intricate definition involving reasoning over exponentially many coalitions, a nontrivial upper bound on its complexity was missing in the literature and looked for. This article faces this question and precisely characterizes the complexity of the nucleolus, by exhibiting an upper bound that holds on any class of compact games, and by showing that this bound is tight even on the (structurally simple) class of graph games. The upper bound is established by proposing a variant of the standard linear-programming based algorithm for nucleolus computation and by studying a framework for reasoning about succinctly specified linear programs, which are contributions of interest in their own. The hardness result is based on an elaborate combinatorial reduction, which is conceptually relevant for it provides a “measure” of the computational cost to be paid for guaranteeing voluntary participation to the distribution process. In fact, the pre-nucleolus is known to be efficiently computable over graph games, with this solution concept being defined as the nucleolus but without guaranteeing that each player is granted with it at least the worth she can get alone, that is, without collaborating with the other players. Finally, this article identifies relevant tractable classes of coalitional games, based on the notion of type of a player. Indeed, in most applications where many players are involved, it is often the case that such players do belong in fact to a limited number of classes, which is known in advance and may be exploited for computing the nucleolus in a fast way.
Decolonizing Global Mental Health: The psychiatrization of the majority world

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Homozygosity Mapping and Genetic Analysis of Autosomal Recessive Retinal Dystrophies in 144 Consanguineous Pakistani Families

Purpose The Pakistan Punjab population has been a rich source for identifying genes causing or contributing to autosomal recessive retinal degenerations (arRD). This study was carried out to delineate the genetic architecture of arRD in the Pakistani population. Methods The genetic origin of arRD in a total of 144 families selected only for having consanguineous marriages and multiple members affected with arRD was examined. Of these, causative mutations had been identified in 62 families while only the locus had been identified for an additional 15. The remaining 67 families were subjected to homozygosity exclusion mapping by screening of closely flanking microsatellite markers at 180 known candidate genes/loci followed by sequencing of the candidate gene for pathogenic changes. Results Of these 67 families subjected to homozygosity mapping, 38 showed homozygosity for at least one of the 180 regions, and sequencing of the corresponding genes showed homozygous cosegregating mutations in 27 families. Overall, mutations were detected in approximately 61.8 % (89/144) of arRD families tested, with another 10.4% (15/144) being mapped to a locus but without a gene identified. Conclusions These results suggest the involvement of unmapped novel genes in the remaining 27.8% (40/144) of families. In addition, this study demonstrates that homozygosity mapping remains a powerful tool for identifying the genetic defect underlying genetically heterogeneous arRD disorders in consanguineous marriages for both research and clinical applications.
Active Information Acquisition

We propose a general framework for sequential and dynamic acquisition of useful information in order to solve a particular task. While our goal could in principle be tackled by general reinforcement learning, our particular setting is constrained enough to allow more efficient algorithms. In this paper, we work under the Learning to Search framework and show how to formulate the goal of finding a dynamic information acquisition policy in that framework. We apply our formulation on two tasks, sentiment analysis and image recognition, and show that the learned policies exhibit good statistical performance. As an emergent byproduct, the learned policies show a tendency to focus on the most prominent parts of each instance and give harder instances more attention without explicitly being trained to do so.
Toward Automatic Character Identification in Unannotated Narrative Text

We present a case-based approach to character identification in natural language text in the context of our Voz system. Voz first extracts entities from the text, and for each one of them, computes a feature-vector using both linguistic information and external knowledge. We propose a new similarity measure called Continuous Jaccard that exploits those feature-vectors to compute the similarity between a given entity and those in the case-base, and thus determine which entities are characters or not. We evaluate our approach by comparing it with different similarity measures and feature sets. Results show an identification accuracy of up to 93.49%, significantly higher than recent related work.
In Vitro Antistaphylococcal Effects of Embelia schimperi Extracts and Their Component Embelin with Oxacillin and Tetracycline

Bacterial infections are in less-developed countries traditionally treated by remedies prepared from medicinal plants. Embelia schimperi (Vatke) is a plant used as a taenicide or disinfectant in Ethiopia, very often taken mixed with another plant species. In the present study, we examined two extracts prepared from seeds and twigs with leaves of E. schimperi and its main present secondary metabolite embelin for their antibacterial combinatory effect with oxacillin and tetracycline against sensitive and resistant Staphylococcus aureus strains. Minimum inhibitory concentrations were determined through the broth microdilution method, whereas the combinatory effect was evaluated through fractional inhibitory concentration sum (ΣFIC) indices. Results show many positive interactions and synergy occurring in embelin and oxacillin combinations against 4 out of 9 strains (ΣFIC 0.203–0.477) and for embelin and tetracycline combination against 3 out of 9 strains (ΣFIC 0.400–0.496). Moreover, the resistance to oxacillin has been overcome in 2 strains and to tetracycline in 3 strains. According to our knowledge, this is the first study showing antimicrobial combinatory effect of E. schimperi as well as of embelin. These findings can be used for the further research targeted on the development of new antistaphylococcal agents.
2016 Ieee International Conference on Big Data (big Data) Semantic Approach to Automating Management of Big Data Privacy Policies

—Ensuring privacy of Big Data managed on the cloud is critical to ensure consumer confidence. Cloud providers publish privacy policy documents outlining the steps they take to ensure data and consumer privacy. These documents are available as large text documents that require manual effort and time to track and manage. We have developed a semantically rich ontology to describe the privacy policy documents and built a database of several policy documents as instances of this ontology. We next extracted rules from these policy documents based on deontic logic which can be used to automate management of data privacy. In this paper we describe our ontology in detail along with the results of our analysis of privacy policies of prominent cloud services.
LDA-SVM-Based EGFR Mutation Model for NSCLC Brain Metastases

AbstractEpidermal growth factor receptor (EGFR) activating mutations are a predictor of tyrosine kinase inhibitor effectiveness in the treatment of non–small-cell lung cancer (NSCLC). The objective of this study is to build a model for predicting the EGFR mutation status of brain metastasis in patients with NSCLC.Observation and model set-up.This study was conducted between January 2003 and December 2011 in 6 medical centers in Southwest China.The study included 31 NSCLC patients with brain metastases.Eligibility requirements were histological proof of NSCLC, as well as sufficient quantity of paraffin-embedded lung and brain metastases specimens for EGFR mutation detection. The linear discriminant analysis (LDA) method was used for analyzing the dimensional reduction of clinical features, and a support vector machine (SVM) algorithm was employed to generate an EGFR mutation model for NSCLC brain metastases. Training-testing-validation (3 : 1 : 1) processes were applied to find the best fit in 12 patients (validation test set) with NSCLC and brain metastases treated with a tyrosine kinase inhibitor and whole-brain radiotherapy.Primary and secondary outcome measures: EGFR mutation analysis in patients with NSCLC and brain metastases and the development of a LDA-SVM-based EGFR mutation model for NSCLC brain metastases patients.EGFR mutation discordance between the primary lung tumor and brain metastases was found in 5 patients. Using LDA, 13 clinical features were transformed into 9 characteristics, and 3 were selected as primary vectors. The EGFR mutation model constructed with SVM algorithms had an accuracy, sensitivity, and specificity for determining the mutation status of brain metastases of 0.879, 0.886, and 0.875, respectively. Furthermore, the replicability of our model was confirmed by testing 100 random combinations of input values.The LDA-SVM-based model developed in this study could predict the EGFR status of brain metastases in this small cohort of patients with NSCLC. Further studies with larger cohorts should be carried out to validate our findings in the clinical setting.
A Model of Continuous Sedimentation of Flocculated Suspensions in Clarifier-Thickener Units

The chief purpose of this paper is to formulate and partly analyze a new mathematical model for continuous sedimentation-consolidation processes of flocculated suspensions in clarifier-thickener units. This model appears in two variants for cylindrical and variable cross-sectional area units, respectively (Models 1 and 2). In both cases, the governing equation is a scalar, strongly degenerate parabolic equation in which both the convective and diffusion fluxes depend on parameters that are discontinuous functions of the depth variable. The initial value problem for this equation is analyzed for Model 1. We introduce a simple finite difference scheme and prove its convergence to a weak solution that satisfies an entropy condition. A limited analysis of steady states as desired stationary modes of operation is performed. Numerical examples illustrate that the model realistically describes the dynamics of flocculated suspensions in clarifier-thickeners.
Changes in health status experienced by women with gestational diabetes and pregnancy-induced hypertensive disorders.

OBJECTIVE To examine changes in health status among women with gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH). METHODS We examined perceived health status changes from the prepregnancy, as recalled at 12-20 weeks gestation, to the postpartum period in women with GDM (n = 64) vs. unaffected gravidas (n = 1233) and women diagnosed with PIH (n = 148) vs. unaffected gravidas. We used patient survey and medical record data from a prospective cohort study. Health status measures included the Short Form-36 scales for physical function, vitality, and self-rated health and the Center for Epidemiologic Studies-Depression Scale (CES-D). Multivariate logistic regression models controlled for age, parity, race, education, prepregnancy body mass index (BMI) and exercise levels, food insufficiency, and GDM or PIH during a prior pregnancy. RESULTS Women with PIH more often reported a significant decline in vitality (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.02-2.23) and self-rated health (OR 2.12, 95% CI 1.19- 3.77) and an increase in depressive symptoms from prepregnancy to postpartum compared with unaffected women (OR 1.84, 95% CI 1.11-3.05). Decline in self-rated health was partially mediated by cesarean birth and preterm delivery. Similar proportions of women with GDM and unaffected women reported declines in health status measures. CONCLUSIONS Women with PIH, but not GDM, more often experience significant declines in health status from prepregnancy to postpartum than unaffected women.
Unusual Crystallization Behavior of Organoclay Reinforced Poly(l-lactic acid) Nanocomposites

The effect of organically modified montmorillonite clay addition on crystallization of a polymer matrix has been studied. Two types of commercially available organoclays with different extent of miscibility with a polymer matrix were employed, leading to fully exfoliated (high miscibility) and intercalated (low miscibility) nanocomposite morphologies. The nanocomposites were fabricated via the exfoliation−adsorption technique with the biodegradable polyester matrix polymer poly(l-lactic acid) (PLLA). As-cast nanocomposite films were melted and isothermally crystallized at different temperatures. Bulk kinetics studies and radial spherulite growth rates indicate that when a high degree of filler−polymer matrix miscibility is present, nucleation properties of the organoclay are low relative to the less miscible organoclay. Therefore, the overall bulk crystallization rate was increased in the intercalated system and somewhat retarded in the exfoliated system. Surprisingly, spherulite growth rates were signifi.
Attitude determination of LEO satellites using an array of GNSS sensors

The proliferation of Global Navigation Satellite Systems (GNSS) paves the way for an increasing number of applications in positioning, guidance and navigation. GNSS-based attitude determination is one of such an important and promising application. In this contribution we explore the potential of GNSS-based attitude determination for Low Earth orbiting (LEO) formation flying Synthetic Aperture Radar (SAR) satellites. Precise attitude determination using multiple GNSS receivers/antennas relies on a successful resolution of the integer carrier phase ambiguities. For a set of rigidly satellite-mounted GNSS antennas, a number of nonlinear geometrical constraints can be exploited for the purpose of increasing the probability of correct integer ambiguity estimation. In this contribution, we make use of the Multivariate Constrained Least-squares AMBiguity Decorrelation Adjustment (MC-LAMBDA) method. By incorporating the known antenna geometry into its ambiguity objective function, this method is shown to demonstrate reliable and instantaneous single-frequency integer ambiguity resolution. The resulting attitude estimates are further improved using nonlinear filtering. Our hardware-in-the-loop experiment with the University of New Sourth Wales “Namuru” GNSS receivers shows the potential of stand-alone, unaided, single-frequency attitude determination of LEO satellites.
Effect of Tumor Necrosis Factor Inhibitor Therapy on Osteoclasts Precursors in Ankylosing Spondylitis

Introduction Ankylosing Spondylitis (AS) is characterized by excessive local bone formation and concomitant systemic bone loss. Tumor necrosis factor (TNF) plays a central role in the inflammation of axial skeleton and enthesis of AS patients. Despite reduction of inflammation and systemic bone loss, AS patients treated with TNF inhibitors (TNFi) have ongoing local bone formation. The aim of this study was to assess the effect of TNFi in the differentiation and activity of osteoclasts (OC) in AS patients. Methods 13 AS patients treated with TNFi were analyzed at baseline and after a minimum follow-up period of 6 months. 25 healthy donors were recruited as controls. Blood samples were collected to assess receptor activator of nuclear factor kappa-B ligand (RANKL) surface expression on circulating leukocytes and frequency and phenotype of monocyte subpopulations. Quantification of serum levels of bone turnover markers and cytokines, in vitro OC differentiation assay and qRT-PCR for OC specific genes were performed. Results RANKL+ circulating lymphocytes (B and T cells) and IL-17A, IL-23 and TGF-β levels were decreased after TNFi treatment. We found no differences in the frequency of the different monocyte subpopulations, however, we found decreased expression of CCR2 and increased expression of CD62L after TNFi treatment. OC number was reduced in patients at baseline when compared to controls. OC specific gene expression was reduced in circulating OC precursors after TNFi treatment. However, when cultured in OC differentiating conditions, OC precursors from AS TNFi-treated patients showed increased activity as compared to baseline. Conclusion In AS patients, TNFi treatment reduces systemic pro osteoclastogenic stimuli. However, OC precursors from AS patients exposed to TNFi therapy have increased in vitro activity in response to osteoclastogenic stimuli.
The Interrelationship of Autonomy, Motivation, and Academic Performance of Persian L2 Learners in Distance Education Contexts

Among various variables affecting the learning of a language, motivation and autonomy play salient roles. The present study aimed at investigating the possible relationship among autonomy, motivation, and academic performance of Persian L2 learners. To do so, 60 Persian L2 learners from Shahrekord Payam-e-Noor University were randomly selected to see whether or not autonomy, motivation, and academic performance are interrelated. Two questionnaires, one for autonomy and one for motivation, were employed to gather the required data. Analyzing the data through correlation and regression, the results revealed that there is a significant relationship between autonomy and academic performance, and also between motivation and academic performance. On the contrary, no significant relationship was observed between motivation and autonomy. The results of studies like the current one will help L2 teachers and curriculum developers make L2 learners more self-directed, motivated, and successful in conducting their own learning in distance contexts.