Miracle-dz/UniFAR-FTUs huggingface dataset:
Induced Toxicity and Oxidative Stress in Liver of Male Rats : Protection by Melatonin

Aluminum is a ubiquitous element with known toxicity for both human and experimental animals. It has been implicated in the pathogenesis of several diseases. The present study investigates the possible hepatoprotective role of melatonin in modulating the toxicity and the oxidative stress induced by chronic exposure to aluminum chloride (AlCl3) in the liver of male rats. 40 male rats were divided into four groups (10 rats each): vehicle control group treated with alcoholic saline, AlCl3 group treated with 20 mg/kg of AlCl3, melatonin group treated with 5 mg/kg of melatonin, and melatonin+AlCl3 group treated with the previous doses of both AlCl3 and melatonin. Rats were treated orally once daily for 30 consecutive days. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin, total lipids, total cholesterol, triglycerides, glucose and total proteins were measured in the plasma to assess the liver functioning. Liver specimens were also collected for histopathological examination and also for assessment of hepatic level of malondialdehyde (MDA), reduced glutathione (GSH) in addition to the activity of glutathione peroxidase (GPx), superoxide dismutase (SOD) and catalase (CAT). The results showed that the oral administration of AlCl3 caused significant (p<0.05) increases in the plasma level of the ALT, AST, ALP, total bilirubin, total lipids, total cholesterol, triglycerides and glucose while the level of total proteins was found to be decreased. Moreover, AlCl3 induced oxidative stress as indicated by a significant increase in the level of MDA with a concomitant decrease in the GSH content as well as in the activity of GPx, SOD and CAT in the liver tissue. Histological examination for liver sections revealed marked necrosis and degeneration of hepatocytes, centrilobular necrosis, congestion of the central vein, vacuolization of cytoplasm, infiltration of inflammatory cells, dilatation and congestion of the blood sinusoids. Pretreatment with melatonin in AlCl3-treated rats alleviated the previously mentioned alterations in the biochemical and oxidative stress parameters and restored their values toward the normal value of the control group. Moreover, it improved to a large extent the histological changes induced by AlCl3 in such a way that more or less normal architecture of the liver was observed. Therefore, the data obtained in the present study confirmed the deleterious effects of AlCl3 in the liver. Moreover, it can be concluded that these effects could be overcome or, at least, significantly minimized by the administration of melatonin. [Wessam M. Abdel-Wahab . AlCl3-Induced Toxicity and Oxidative Stress in Liver of Male Rats: Protection by Melatonin. Life Sci J 2012; 9(4): 1173-1182] (ISSN: 1097-8135). http://www.lifesciencesite. com. 174
Is it true that Indian gold price influenced by Indian stock market reaction

The present study investigates the reaction of Indian stock market index (Sensex and Nifty) on Indian gold price or the relationship between Indian gold price and Indian stock market index (Sensex and Nifty) for the period of study between 2nd January 1991 and 10th August 2012 using daily time series data with the application of bivariate and multivariate cointegration test. In times of national crisis, bank failures, rupee depreciation, and in case of negative real interest rate, people consider gold as a solid asset and safe haven and like to invest in such yellow precious metal because there is a little chance of getting better returns in the stock investment due to a fragile economic and financial position. Bivariate cointegration test results specify that there is no cointegration relationship between gold price and the two stock market indices. But multivariate cointegration test results show that there is a presence of steady cointegration relationship between the gold price and two stock market indices in India. So, gold price in India was increased during the study period because of stock market reaction in India along with other macro-economic factors.
Multilingual Aspects of Multiword Lexical Units

As most of the machine-readable dictionaries contain clearly insufficient information about multiword lexical units, there is a constant need to extend and tune specialized lexical databases to account for new expressions. In this paper, we present a system exclusively based on statistics that massively extracts from unrestricted text corpora contiguous and noncontiguous rigid multiword lexical units. For that purpose, a new association measure called the Mutual Expectation is conjugated with a new acquisition process based on an algorithm of local maxima. The system has been applied to a Portuguese, French, English and Italian parallel corpus and has evidenced that multiword lexical units embody a great deal of cross-language regularities.
Modularizing Web Services Management with AOP

Web services (WS) are modular applications that are described, published, localised and invoked over a network. Web services technologies accelerate application development by allowing the selection and integration of third-party web services, achieving high modularity, flexibility and configurability. However, current approaches only allow this integration by hard wiring the references to concrete web services into the client applications. As stated in [1], this leads to unmanageable applications that cannot adapt to changes in the business environment (e.g. a service that is abandoned or changed, a new service that becomes available on the market, etc). Moreover these approaches do not provide any management support, which is fundamental for achieving robustness. To deal with these issues , code has to be written manually and repeated for each service, resulting scattered in the application. We observe the need for the application to be independent of specific services.
Flexible and practical flow analysis for higher-order programming languages

A flow analysis is a procedure for computing static information about programs. Such an analysis can infer information about a program even if the program does not terminate when executed. This is done by abstracting over the values computed and the primitives used to manipulate those values. The information inferred is necessarily approximate but can still be used to justify the correctness of program transformations like partial evaluation, type check elimination, and register allocation. Work on flow analyses for higher-order languages has identified several important aspects of the flow analysis problem. To date, however, no single flow analysis has been used for the practical flow analysis of mostly-functional languages. To be practical, an analysis must be able to analyze the full language, be accurate enough to justify program transformations such as compiler optimizations, and be acceptably fast for even large programs. In this dissertation we develop a new flow analysis framework that unifies and extends previous work to yield an analysis that is indeed practical. The analysis framework can express a wide variety of analyses that vary in accuracy, speed, and the information they collect. The framework is proved correct using a novel application of a proof technique developed for proving the correctness of compilers. The analysis is fully implemented in a production-quality Scheme compiler. The analysis is used by the compiler to justify optimizations such as loop recognition, procedure call optimization, and closure elimination. Benchmarks demonstrate that the analysis is able to analyze large programs quickly yet retain enough accuracy to justify optimizations.
On the use the ID Boolean Model for the Description of Binary Textures

In this paper we investigate the use of the Poisson model in the creation and the description of binary textures, in conjunction with two forms of image scanning, namely raster and Hilbert scan. We apply our model to some binary random textures for which we estimate the Poisson parameters using Maximum Likelihood Estimation and nd that the values we obtain are suuciently distinct and suuciently constant over the same texture, to allow the use of this model in texture identiication.
Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model

A minimum mathematical model of the marine pelagic microbial food web has previously shown to be able to reproduce central aspects of observed system response to different bottom‐up manipulations in a mesocosm experiment Microbial Ecosystem Dynamics (MEDEA) in Danish waters. In this study, we apply this model to two mesocosm experiments (Polar Aquatic Microbial Ecology (PAME)‐I and PAME‐II) conducted at the Arctic location Kongsfjorden, Svalbard. The different responses of the microbial community to similar nutrient manipulation in the three mesocosm experiments may be described as diatom‐dominated (MEDEA), bacteria‐dominated (PAME‐I), and flagellated‐dominated (PAME‐II). When allowing ciliates to be able to feed on small diatoms, the model describing the diatom‐dominated MEDEA experiment give a bacteria‐dominated response as observed in PAME I in which the diatom community comprised almost exclusively small‐sized cells. Introducing a high initial mesozooplankton stock as observed in PAME‐II, the model gives a flagellate‐dominated response in accordance with the observed response also of this experiment. The ability of the model originally developed for temperate waters to reproduce population dynamics in a 10°C colder Arctic fjord, does not support the existence of important shifts in population balances over this temperature range. Rather, it suggests a quite resilient microbial food web when adapted to in situ temperature. The sensitivity of the model response to its mesozooplankton component suggests, however, that the seasonal vertical migration of Arctic copepods may be a strong forcing factor on Arctic microbial food webs.
Comparison of Unimodal Analytical Expressions for the Soil-Water Retention Curve

This study was conducted to evaluate ten closed-form unimodal analytical expressions to describe the soil-water retention curve, in terms of their accuracy, linearity, Akaike Information Criterion (AIC), and prediction potential. The latter was evaluated by correlating the model parameters to basic soil properties. Soil samples were taken in duplicate from 48 horizons of 24 soil series in Flanders, Belgium. All sample locations were under forest and hence the samples had, besides their difference in texture, a high variety in bulk density (ρ b ) and organic matter content (OM). The van Genuchten model with m as a free parameter showed the highest overall performance in terms of goodness-of-fit. It had the highest accuracy, the highest degree of linearity, and the lowest AIC value. However, it had a low prediction potential. Imposing the constraint m = 1 - 1/n and hence reducing the number of model parameters by one, increased the prediction potential of the model significantly, without loosing much of the model's accuracy and linearity. A high degree of accuracy and linearity was also observed for the two Kosugi models tested. Restricting the bubbling pressure to be equal to zero resulted in a rather high prediction potential, which was not the case when keeping the bubbling pressure as a free parameter. A major drawback of van Genuchten and Kosugi type models is that they do not define the soil-water retention curve beyond the residual water content. We further demonstrated that the performance of all but one model in terms of their match to the data Increased with increasing clay content and decreasing sand content, which is contradictory to the deterministic character of these models. Bulk density and OM did not have a significant effect on the accuracy of most models.
Social learning in large online audiences of health professionals: Improving dialogue with automated tools

This article was migrated. The article was marked as recommended. Massive open online courses (MOOCs) bring about the opportunity to reach large international audiences of health professionals. However, change in clinical practice eventually needs social interaction, to validate the new knowledge with trusted peers, in the agreement and adoption phases of change. How can meaningful dialogue take place without scaling up expert tutoring? The extensive experience from social network applications such as Facebook or Twitter provides an opportunity to improve dialogue among peers and with experts automatically and seamlessly, as part of what is called social learning analytics (SLA). Large amounts of data about prior relationships among participants in a course - similar to Facebook and other social applications-, among participants and course materials - similar to Netflix or Amazon -, as well as natural language processing, could be obtained, and then analyzed and used to improve the educational processes and outcomes. In this paper, a series of examples with pilot uses of SLA in the context of massive online courses for physicians and other health care professionals are described. They include: 1) Forecasting of academic accomplishment. 2) Team-based face-to-face learning as part of massive online courses. 3) Analysis of existing connections, to ensure the most connected discussion groups of course participants. 4) Facebook-like dialogue with other course participants who are previously related, as well as with the Course Faculty. 5) Crowdsourcing and friendsourcing, for recommending useful study materials or future courses. 6) Natural language processing, to classify posts in online discussions. It should be noted that the article does not address the use of Facebook or Twitter in continuing medical education (CME), but instead, the use of their approaches in CME. The intent of this manuscript is to create awareness in the medical education community that this type of analysis is possible and potentially useful, to receive feedback on the possible functionalities as well as critique these developments, and to create a space for collaboration in research and innovation projects with other interested parties.
On the Progression of Knowledge in the Situation Calculus

In a seminal paper, Lin and Reiter introduced the notion of progression for basic action theories in the situation calculus. Earlier works by Moore, Scherl and Levesque extended the situation calculus to account for knowledge. In this paper, we study progression of knowledge in the situation calculus. We first adapt the concept of bisimulation from modal logic and extend Lin and Reiter's notion of progression to accommodate knowledge. We show that for physical actions, progression of knowledge reduces to forgetting predicates in first-order modal logic. We identify a class of first-order modal formulas for which forgetting an atom is definable in first-order modal logic. This class of formulas goes beyond formulas without quantifyingin. We also identify a simple case where forgetting a predicate reduces to forgetting a finite number of atoms. Thus we are able to show that for local-effect physical actions, when the initial KB is a formula in this class, progression of knowledge is definable in first-order modal logic. Finally, we extend our results to the multi-agent case.
Genome-wide Analysis of Chlamydophila pneumoniae Gene Expression at the Late Stage of Infection

Chlamydophila pneumoniae, an obligate intracellular eubacterium, changes its form from a vegetative reticulate body into an infectious elementary body during the late stage of its infection cycle. Comprehension of the molecular events in the morphological change is important to understand the switching mechanism between acute and chronic infection, which is deemed to relate to the pathogenesis of atherosclerosis. Herein, we have attempted to screen genes expressed in the late stage with a genome-wide DNA microarray, resulting in nomination of 17 genes as the late-stage genes. Fourteen of the 17 genes and six other genes predicted as late-stage genes were confirmed to be up-regulated in the late stage with a quantitative reverse transcriptase–polymerase chain reaction. These 20 late-stage genes were classified into two groups by clustering analysis: ‘drastically induced’ and ‘moderately induced’ genes. Out of eight drastically induced genes, four contain σ28 promoter-like sequences and the other four contain an upstream common sequence. It suggests that besides σ28, there are certain up-regulatory mechanisms at the late stage, which may be involved in the chlamydial morphological change and thus pathogenesis.
An Unsupervised Speaker Clustering Technique based on SOM and I-vectors for Speech Recognition Systems

In this paper, we introduce an enhancement for speech recognition systems using an unsupervised speaker clustering technique. The proposed technique is mainly based on I-vectors and Self-Organizing Map Neural Network(SOM). The input to the proposed algorithm is a set of speech utterances. For each utterance, we extract 100-dimensional I-vector and then SOM is used to group the utterances to different speakers. In our experiments, we compared our technique with Normalized Cross Likelihood ratio Clustering (NCLR). Results show that the proposed technique reduces the speaker error rate in comparison with NCLR. Finally, we have experimented the effect of speaker clustering on Speaker Adaptive Training (SAT) in a speech recognition system implemented to test the performance of the proposed technique. It was noted that the proposed technique reduced the WER over clustering speakers with NCLR.
Pitch accent detection and prediction with DCT features and CRF model

Automatic detection/prediction of pitch accent, which determines the existence of prominent syllable of a word and its corresponding pitch accent pattern, is crucial in making expressive Text-To-Speech (TTS) synthesis. To train a model to detect and predict pitch accent usually requires a large amount of annotated training data to be manually labeled by phonetically trained language experts, which is both time consuming and costly. In this paper, we propose a semi-automatic algorithm to do pitch accent modeling, where the existence of accentuation in the training data is labeled at the word level by native speaker (i.e., not phonetically trained language experts) and the type of a pitch accent is automatically detected with its vector quantized DCT coefficient patterns. A cascaded, two-stage approach, which separates predicting the pitch accent existence and determining corresponding pitch accent type, is proposed to process any unrestricted text input with Conditional Random Field (CRF) trained models. The evaluation results show that the new approach outperforms the conventional, single stage approach.
Lack of Effectiveness of Hyperbaric Oxygen Therapy for the Treatment of Diabetic Foot Ulcer and the Prevention of Amputation

OBJECTIVE Hyperbaric oxygen (HBO) is a device that is used to treat foot ulcers. The study goal was to compare the effectiveness of HBO with other conventional therapies administered in a wound care network for the treatment of a diabetic foot ulcer and prevention of lower-extremity amputation. RESEARCH DESIGN AND METHODS This was a longitudinal observational cohort study. To address treatment selection bias, we used propensity scores to determine the “propensity” that an individual was selected to receive HBO. RESULTS We studied 6,259 individuals with diabetes, adequate lower limb arterial perfusion, and foot ulcer extending through the dermis, representing 767,060 person-days of wound care. In the propensity score–adjusted models, individuals receiving HBO were less likely to have healing of their foot ulcer (hazard ratio 0.68 [95% CI 0.63–0.73]) and more likely to have an amputation (2.37 [1.84–3.04]). Additional analyses, including the use of an instrumental variable, were conducted to assess the robustness of our results to unmeasured confounding. HBO was not found to improve the likelihood that a wound might heal or to decrease the likelihood of amputation in any of these analyses. CONCLUSIONS Use of HBO neither improved the likelihood that a wound would heal nor prevented amputation in a cohort of patients defined by Centers for Medicare and Medicaid Services eligibility criteria. The usefulness of HBO in the treatment of diabetic foot ulcers needs to be reevaluated.
International Conference on Intelligent Control and Information Processing Protein S Econdary S Tructure Prediction Based on Multi-s Vm Ensemble

To improve the performance of secondary structure prediction, a multi-SVM ensemble was applied, bagging was used to resample the training dataset. The SVM ensemble was made of two-layer, one is composed by three SVM network decided by winner-take-all, the other is a ensemble network composed of five classifier decided by majority voting. Seven-fold cross-validation test on RS126 dataset indicated that the multi-SVM ensemble could achieve better performance on secondary structure prediction.
GENDER DIFFERENCES Large-Sample , Single Experiment Estimates of the Size of Gender Differences on Visual Illusions , Maze Learning , and Mirror

Using data from PsychExperiments, a public data archive that has been accumulating data from a set of cognitive and perceptual experiments since 1998, this report provides large-sample evidence of gender differences on three visual illusions (Poggendorff, Mueller-Lyer, and Ponzo), a maze learning task, a dynamic line motion illusion, and a mirror drawing task. For comparison purposes, data from a three-dimensional mental rotation task are included. The large-sample, exhaustive datasets permit estimation of effect size in the absence of meta-analysis, which is subject to the file-drawer problem and which requires pooling data across methodologically different studies. The data show effects that are consistent with the well-established finding that females are slower and less accurate than males in performing a variety of “spatial” tasks. The novel contribution is that the tasks reported—except for mental rotation—are not among those previously known to produce gender effects.
Discrete tomography on the triangular grid: a memetic approach

In this paper we present a memetic algorithm for the reconstruction of binary images represented on a triangular grid. We define the crossover and mutation evolutionary algorithm operators introduced on this grid. We propose a discrete tomography algorithm which uses a switch and compactness operators for the triangular grid to improve the quality of the image in each generation. The algorithm was tested on some images for its effectiveness.
Digitizing archaeological excavations from multiple views

We present a novel approach on digitizing large scale unstructured environments like archaeological excavations using off-the-shelf digital still cameras. The cameras are calibrated with respect to few markers captured by a theodolite system. Having all cameras registered in the same coordinate system enables a volumetric approach. Our new algorithm has as input multiple calibrated images and outputs an occupancy voxel space where occupied pixels have a local orientation and a confidence value. Both, orientation and confidence facilitate an efficient rendering and texture mapping of the resulting point cloud. Our algorithm combines the following new features: Images are back-projected to hypothesized local patches in the world and correlated on these patches yielding the best orientation. Adjacent cameras build tuples which yield a product of pair-wise correlations, called strength. Multiple camera tuples compete each other for the best strength for each voxel. A voxel is regarded as occupied if strength is maximum along the normal. Unlike other multi-camera algorithms using silhouettes, photoconsistency, or global correspondence, our algorithm makes no assumption on camera locations being outside the convex hull of the scene. We present compelling results of outdoors excavation areas.