Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining for Biomedical Text Data : Feature Space Design and Feature Selection

Unstructured text (e.g., journal articles) remains as the primary means for publishing biomedical research results. To extract and integrate knowledge from such data, text mining has been routinely applied. One important task is extracting relationships between bio-entities such as foods and diseases. Most existing studies however stop short of further analyzing the extracted relationships such as the polarity and the level of certainty at which the authors reported on a given relationship. The latter is termed as the relationship strength and marked at three levels— weak, medium and strong. We have previously reported a preliminary study on this issue [22], and here we detail our studies on constructing a novel feature space towards effectively predicting the polarity and strength of a relationship. Unlike previous work, four types of polarity instead of three are considered, namely, positive, negative, neutral and norelationship. Another contribution is that in addition to the commonly accepted lexicon-based features, we have identified a set of novel features that capture both the semantic and structural aspects of a relationship. Our intensive evaluations demonstrate that combining these new features with the lexicon-based ones can achieve the best accuracy for polarity prediction (~0.91). This however is not the case for strength prediction, where lexiconbased features alone are sufficient (~0.96).
Social Assistance Reform During A Period of Fiscal Stress

This paper reflects on the current state and likely future of the South African social assistance system, focusing specifically on its fiscal sustainability, its effectiveness as an instrument to combat poverty in a longer-term developmental sense, and its impact on the allocation of resources. Despite showing that the grants system is an effective intervention which markedly reduces poverty and apparently does not have severe undesirable behavioural effects, the paper argues that the scope for strengthening anti-poverty policy in South Africa by further expanding the social grants system nonetheless has become very limited. The main policy conclusions of the paper are that sustainable poverty reduction in South Africa requires inclusive job-creating economic growth, and that anti-poverty policy should remain focused on achieving his objective.
Gap Junction Blockers: An Overview of their Effects on Induced Seizures in Animal Models

Abstract: Background Gap junctions are clusters of intercellular channels allowing the bidirectional pass of ions directly into the cytoplasm of adjacent cells. Electrical coupling mediated by gap junctions plays a role in the generation of highly synchronized electrical activity. The hypersynchronous neuronal activity is a distinctive characteristic of convulsive events. Therefore, it has been postulated that enhanced gap junctional communication is an underlying mechanism involved in the generation and maintenance of seizures. There are some chemical compounds characterized as gap junction blockers because of their ability to disrupt the gap junctional intercellular communication. Objective Hence, the aim of this review is to analyze the available data concerning the effects of gap junction blockers specifically in seizure models. Results Carbenoxolone, quinine, mefloquine, quinidine, anandamide, oleamide, heptanol, octanol, meclofenamic acid, niflumic acid, flufenamic acid, glycyrrhetinic acid and retinoic acid have all been evaluated on animal seizure models. In vitro, these compounds share anticonvulsant effects typically characterized by the reduction of both amplitude and frequency of the epileptiform activity induced in brain slices. In vivo, gap junction blockers modify the behavioral parameters related to seizures induced by 4-aminopyridine, pentylenetetrazole, pilocarpine, penicillin and maximal electroshock. Conclusion Although more studies are still required, these molecules could be a promising avenue in the search for new pharmaceutical alternatives for the treatment of epilepsy.
An improved multi-label classification method and its application to functional genomics

In this paper, a multi-label classification method based on label ranking and delicate boundary Support Vector Machine (SVM) is proposed for solving the functional genomics applications. Firstly, an improved probabilistic SVM with delicate decision boundary is used as scoring approach to obtain a proper label rank. Secondly, an instance-dependent thresholding strategy is proposed to decide classification results. A d-folds validation approach is utilised to determine a set of target thresholds for all training samples as teachers, then an appropriate instance-dependent threshold for each testing instance is obtained by applying k-Nearest Neighbours (KNN) strategy on this teacher threshold set.
Network-on-chip with guaranteed-bandwidth data communication service

A network-on-chip (NoC), having guaranteed-throughput (GT) or guaranteed bandwidth service by using a flexible method to establish a connection-oriented data communication at runtime, is presented in this paper. The GT packets can share communication link with a flexible manner, where flits belonging to the same packet will have the same local identity-tag (ID-tag). The ID-tags of each packet will vary locally along communication links, and are organized with an ID-tag mapping management unit, which is implemented at each output part of the on-chip routers. There is no need for a specific algorithm for finding a conflict-free scheduling as commonly used in the TDM-based methods that use time slots allocation technique. The contention problem is solved with the hardware solution based on the locally organized message identity (ID). This guaranteed bandwidth/throughput service will provide a good interconnect platform for many core processor systems running computer vision and multimedia applications with better performance.
Changes of the liver volume and the Child-Pugh score after high dose hypofractionated radiotherapy in patients with small hepatocellular carcinoma

Purpose To investigate the safety of high dose hypofractionated radiotherapy (RT) in patients with small hepatocellular carcinoma (HCC) in terms of liver volumetric changes and clinical liver function. Materials and Methods We retrospectively reviewed 16 patients with small HCC who were treated with high dose hypofractionated RT between 2006 and 2009. The serial changes of the liver volumetric parameter were analyzed from pre-RT and follow-up (FU) computed tomography (CT) scans. We estimated linear time trends of whole liver volume using a linear mixed model. The serial changes of the Child-Pugh (CP) scores were also analyzed in relation to the volumetric changes. Results Mean pre-RT volume of entire liver was 1,192.2 mL (range, 502.6 to 1,310.2 mL) and mean clinical target volume was 14.7 mL (range, 1.56 to 70.07 mL). Fourteen (87.5%) patients had 4 FU CT sets and 2 (12.5%) patients had 3 FU CT sets. Mean interval between FU CT acquisition was 2.5 months. After considering age, gender and the irradiated liver volume as a fixed effects, the mixed model analysis confirmed that the change in liver volume is not significant throughout the time course of FU periods. Majority of patients had a CP score change less than 2 except in 1 patient who had CP score change more than 3. Conclusion The high dose hypofractionated RT for small HCC is relatively safe and feasible in terms of liver volumetric changes and clinical liver function.
Bounding the Integrality Distance of LP Relaxations for Structured Prediction

In structured prediction, a predictor optimizes an objective function over a combinatorial search space, such as the set of all image segmentations, or the set of all part-of-speech taggings. Unfortunately, finding the optimal structured labeling—sometimes referred to as maximum a posteriori (MAP) inference—is, in general, NP-hard [12], due to the combinatorial structure of the problem. Many inference approximations have been proposed, some of which are based on linear programming (LP) relaxations [e.g., 5, 1, 15, 16, 4, 13], which “relax” the combinatorial search space to a convex polytope with a polynomial number of constraints. These LP relaxations can be solved efficiently, but may result in fractional solutions, i.e., non-integral labelings. The approximation quality of an LP relaxation is traditionally measured by a quantity known as the integrality gap, defined as the difference in the objective values obtained at the optima of the relaxed and exact problems. When the integrality gap is zero, the solution is said to be tight.
On the use of intrinsic motivation for visual saliency learning

The use of intrinsic motivation for the task of learning sensori-motor properties has received a lot of attention over the last few years, but only little work has been provided toward using intrinsic motivation for the task of learning visual signals. In this paper, we propose to apply the main ideas of the Intelligent Adaptive Curiosity (IAC) for the task of visual saliency learning. We here present RL-IAC, an adapted version of IAC that uses reinforcement learning to deal with time consuming displacements while actively learning saliency based on local learning progress. We also introduce the use of a backward evaluation to deal with a learner that is shared between several regions. We demonstrate the good performance of RL-IAC compared to other exploration techniques, and we discuss the performance of other intrinsic motivation sources instead of learning progress in our problem.
API for Performance Monitoring in Embedded Multicore Systems

Hardware Performance Counters (HPCs) are special registers available in the most modern processors that can be used to monitor shared hardware resources in multicore processors. Specifically for embedded real-time applications running on a multicore processor, such shared resources can affect their performance and cause deadline misses. This paper presents a hardware performance counter interface designed to embedded systems. The use of the interface is demonstrated through a benchmark that shares data between two threads executing in different cores of a multicore processor. As a result, the operating system can obtain an accurate view of software's behavior.
Are There Trends Towards Efficiency For the Egyptian Stock Market ? ”

The purpose of this paper is to investigate the efficiency of the Egyptian stock market. The paper is concerned with the weak form test of the efficient market hypothesis. If the evidence fails to pass the weak form test, there is no reason to examine strong forms before declaring the market inefficient on such evidence. In order to capture the institutional features of such a growing market (i.e., thin trading, low liquidity, and possibly less informed investors), a non-linear GARCH model is estimated. In addition, by investigating efficiency on a yearly basis we are able to examine impact of the market maturing and regulatory changes on the trading behavior and efficiency of that market. The results show that up to 1996 the market was inefficient, but the inefficiency manifested itself through non-linear behavior However, the results show that in 1997 the market is not characterized by predictability and is therefore informationally efficient.
ANALISIS DERAJAT KEPATUHAN KERJASAMA GENERAL BORDER COMMITTEE MALAYSIA â€“ INDONESIA(Studi Kasus: Perbatasan Darat Di Kalimantan)

In this thesis explains about Indonesia-Malaysia Agreement in General Border Committee Regime to handle the problems of border in Kalimantan. This agreement based on Security Agreement in 1972 and 1984. This research tries to answer about compliance of General Border Indonesia-Malaysia participant that havenâ��t gotten the solution yet. The researcher was interested in this topic and wants to explore comprehensively, because the relationship between Indonesia and Malaysia has been established long time ago but the problem about land border in Kalimantan has not been resolved yet. Therefore, this thesis will analyze the factors that affect compliance and noncompliance between the two countries in the General Border Committee Agreement. Explaining about the topic, the researcher needs Theory of International Regime and Compliance Theory. Theory of International Regime in this thesis was intended to explain the dynamics of General Border Committee Agreement, while The Compliance Theory was used to measure the degree of compliance from each country that assigned agreement and to analyze procedure and strategy of agreement. To measure the degree of compliance with Malaysia-Indonesia General Border Committee cooperation, carried out with viewing of agreement was binding or not, one of the way is analyzing the text of treaty was been made to know the degree of cooperation of international agreement that called the degree of legalization (obligation, precision, and delegation). The method of this research is qualitative data analysis techniques. While the techniques of data collection is using primary data and secondary data. The result showed that the regime of General Border Committee agreement Malaysia-Indonesia has failed in creating a compliance mechanism. That failure is caused by several factors, such as some of agreement was priority interest, limited authority, and cost efficiency. The inability of the regime of General Border Committee cooperation in the local level (East Kalimantan and West Kalimantan)in creating a compliance mechanism effected in implementation of cooperation programs that agreed by both parties hampered.
Static power system security assessment via artificial neural network.

Maintaining system security is an important factor in the operation of a power system. The aim of this study is to evaluate the reliability using artificial neural network (ANN) in static security assessment to determine the security status of a power system. Feed Forward Back Propagation Neural Network is implemented to classify the security condition of IEEE 9 bus system. The input data of ANN are derived from offline Newton Raphson load flow analysis. The result obtained from the ANN method is compared with the Newton Raphson load flow analysis in terms of accuracy to predict the security level of IEEE 9 bus system and the computational time required by each method. The average time required by Newton- Raphson load flow analysis to evaluate security level of IEEE 9 bus system is 0.0481 seconds while the average time required by neural network is 0.0119 seconds. The accuracy of 13 hidden neurons feed forward back propagation neural network to predict the security level of IEEE 9 bus system is 98.57%. In conclusion, ANN is found to be reliable to evaluate the security level of IEEE 9 bus system.
Predicting Individual Action Switching in Covert and Continuous Interactive Tasks Using the Fluid Events Model

The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covert event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Thus, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.
Obama's Wars

Drawing on hundreds of interviews with key administration officials, their deputies, and other first-hand sources, Woodward takes listeners deep into the national security state and shows how Obama debates, decides, and balances the enormous pressures facing the modern president. As always, Woodward also bases his work on extensive documentation, including internal memos, letters, detailed chronologies, and meeting notes that reveal the behind-the-scenes realities of the Obama era. Obama has learned that he is not commander-in-chief of the economy. Many of his high-profile domestic reforms - healthcare, education, and energy - were largely turned over to Congress. But the president has realised the weight and reach of his authority as commander-in-chief, a responsibility that may define much of his legacy. Filled with intimate scenes told verbatim, this is an unprecedented look at a young president responding to the dangers and commitments of the 21st century.
Intracranial hemorrhage after stenting and angioplasty of extracranial carotid stenosis.

BACKGROUND AND PURPOSE The transluminal angioplasty and stenting procedure has been recently advocated as a potential alternative to surgical endarterectomy for the treatment of severe extracranial carotid stenosis. This study assesses the incidence and significance of intracranial hemorrhage occurring after this procedure. METHODS We retrospectively reviewed 104 carotid arteries (96 internal, two external, and six common) in 90 patients (63 male; mean age, 69.4 years; range, 48-88 years) who underwent primary stenting and angioplasty by use of Wallstents (103/104) at three centers between January 1996 and January 1999. Seventy-five (83%) patients were referred by neurosurgery departments. Seventy-one (68%) arteries were symptomatic; the mean stenosis percentage was 85% (range, 40-99%). RESULTS Four intraparenchymal hemorrhages occurred, representing 4.4% of patients and 3.8% of vessels, after angioplasty and stent placement. The mean preoperative stenosis percentage was 95% (range, 90-99%). One hemorrhage occurred immediately after stent placement, whereas the three other hemorrhages occurred in a delayed fashion (mean, 2.8 days). The mean hematoma size was 4.8 cm (range, 2-8 cm). Three patients had associated subarachnoid or intraventricular bleeding; the fourth had associated subdural hemorrhage. Three hemorrhages were fatal; the fourth experienced two seizures only. No acute neurologic symptoms were present prior to hemorrhages, and there was no postprocedural hypertension in these patients. All had been receiving antiplatelet agents as well as intraprocedural IV heparin. CONCLUSION Intracranial hemorrhage can occur after carotid angioplasty and stenting. We speculate that this represents cerebral hyperperfusion injury. The 3.8% incidence of cerebral hemorrhage observed is approximately sixfold greater than that reported post endarterectomy (0.6%) (95% CI, 0.2-8.7%). This is not statistically significant in this small study group. This trend may reflect patient selection, different anticoagulation protocols, and/or study population size. Additional data are needed to determine the safety and efficiency of carotid stenting as a treatment for carotid stenosis.
A Loss of Parvalbumin-Containing Interneurons Is Associated with Diminished Oscillatory Activity in an Animal Model of Schizophrenia

Decreased GABAergic signaling is among the more robust pathologies observed postmortem in schizophrenia; however, the functional consequences of this deficit are still largely unknown. Here, we demonstrate, in a verified animal model of schizophrenia, that a reduced expression of parvalbumin (PV)-containing interneurons is correlated with a reduction in coordinated neuronal activity during task performance in freely moving rats. More specifically, methylazoxymethanol acetate (MAM)-treated rats display a decreased density of parvalbumin-positive interneurons throughout the medial prefrontal cortex (mPFC) and ventral (but not dorsal) subiculum of the hippocampus. Furthermore, the reduction in interneuron functionality is correlated with a significantly reduced gamma-band response to a conditioned tone during a latent inhibition paradigm. Finally, deficits in mPFC and ventral hippocampal oscillatory activity are associated with an impaired behavioral expression of latent inhibition in MAM-treated rats. Thus, we propose that a decrease in intrinsic GABAergic signaling may be responsible, at least in part, for the prefrontal and hippocampal hypofunctionality observed during task performance, which is consistently observed in animal models as well as in schizophrenia in humans. In addition, a deficit in intrinsic GABAergic signaling may be the origin of the hippocampal hyperactivity purported to underlie the dopamine dysfunction in psychosis. Such information is central to gaining a better understanding of the disease pathophysiology and alternate pharmacotherapeutic approaches.
Fault Diagnosis and control-reconfiguration in Large-Scale Systems: a Plug-and-Play approach

This paper deals with a novel Plug-and-Play (PnP) architecture for the control and monitoring of Large-Scale Systems (LSSs). The proposed approach integrates a distributed Model Predictive Control (MPC) strategy with a distributed Fault Detection (FD) methodology for a class of nonlinear LSS in a PnP framework. The basic concept is to use the FD scheme as an autonomous decision support system: once a fault is detected, the faulty subsystem can be unplugged to avoid the propagation of the fault in the interconnected LSS. Analogously, once the issue has been solved, the disconnected subsystem can be re-plugged-in. PnP design of local controllers and detectors allow these operations to be performed safely, i.e. without spoiling stability and constraint satisfaction for the whole LSS.
Surface deformation analysis of the Napoli bay ( Italy ) area : sixteen years of ERS and ENVISAT DInSAR observations

Differential Synthetic Aperture Radar Interferometry (DInSAR) is a microwave remote sensing technique that allows us to investigate surface deformation phenomena with a centimeter to millimeter accuracy with a large spatial coverage capability. Firstly applied to investigate single deformation events, the DInSAR algorithms have further been developed to analyze the temporal evolution of the detected displacements via the generation of deformation time series.
Rule-based versus training-based extraction of index terms from business documents: how to combine the results

Current systems for automatic extraction of index terms from business documents either take a rule-based or training-based approach. As both approaches have their advantages and disadvantages it seems natural to combine both methods to get the best of both worlds. We present a combination method with the steps selection, normalization, and combination based on comparable scores produced during extraction. Furthermore, novel evaluation metrics are developed to support the assessment of each step in an existing extraction system. Our methods were evaluated on an example extraction system with three individual extractors and a corpus of 12,000 scanned business documents.