Miracle-dz/UniFAR-FTUs huggingface dataset:
PART OF SPEECH TAGGER FOR MALAY LANGUAGE BASED ON WORDS MORPHOLOGY

: Part of Speech (POS) tagging is an essential task in pre-processing for text processing performance. A POS tagger assigns a tag to each token which is consigned as word classes of noun, verb, adjective and adverb because all the four word classes is the basic and important structure in Malay sentences. Rules for tagging are developed to facilitate the process of new information extraction from unstructured text. This paper presents the evaluation of a POS tagger for Malay texts. It evaluates the accuracy of tagging on each word in a police report corpus from which 50 sentences and 643 words are selected from five different police reports. The results show that tagging accuracy varies between 85.7 percent and 91.8 percent overall. Accuracy is the main factor in evaluating any POS tagger.
Hormonal anticonception anno 2013: a clinician’s view

Hormonal contraception has recently drawn the attention of both national and international Health Organizations mainly because of new data on the risk of venous and arterial thrombosis. This has, fortunately, not led to a ‘pill scare’ as happened in 1996 when controversy arose with respect to the thrombotic risk of third versus second generation pills. This time, evidence on the thrombotic risk of pills with the newer progestogens is gathering, leading to a re-evaluation of guidelines. In this paper, we summarize this evidence and try to present a clinician’s view of the indications and contraindications of hormonal contraception and situate them in the perspective of the numerous non-contraceptive health benefits of hormonal contraception.
Probabilistic Multiagent Reasoning over Annotated Amalgamated F-Logic Ontologies

In a multiagent system (MAS), agents can have different opinions about a given problem. In order to solve the problem collectively they have to reach consensus about the ontology of the problem. A solution to probabilistic reasoning in such an environment by using a social network of trust is given. It is shown that frame logic can be annotated and amalgamated by using this approach which gives a foundation for collective ontology development in MAS. Consider the following problem: a set of agents in a multiagent system (MAS) model a certain domain in order to collectively solve a problem. Their opinions about the domain differ in various ways. The agents are connected into a social network defined by trust relations. The problem to be solved is how to obtain consensus about the domain.
Obstacle detection by direct estimation of multiple motion and scene structure from a moving stereo rig

In the context of real-time collision-obstacle avoidance this paper investigates a direct method of estimating dense scene structure and image motion. Our proposed method combines both stereo vision (involving geometric constraints) and optical flow (involving photometric constraints). It is applied to multiple motion images (i.e., images with vehicle ego-motion plus obstacle motion). Modifications to the direct method were introduced to improve the reliability of the motion estimation. The multiple-motion-estimation scheme comprises local motion estimations followed by a classification of these estimates in a simplified motion parameter space through cluster analysis. The classification enables segmentation of the different motions that are used to estimate more accurately the dense structure and motion of objects in a scene. Experimental results on both synthetic and real image sequences demonstrate the potential of the method.
Exploiting Integrity Constraints for Cleaning Trajectories of RFID-Monitored Objects

A probabilistic framework for cleaning the data collected by Radio-Frequency IDentification (RFID) tracking systems is introduced. What has to be cleaned is the set of trajectories that are the possible interpretations of the readings: a trajectory in this set is a sequence whose generic element is a location covered by the reader(s) that made the detection at the corresponding time point. The cleaning is guided by integrity constraints and consists of discarding the inconsistent trajectories and assigning to the others a suitable probability of being the actual one. The probabilities are evaluated by adopting probabilistic conditioning that logically consists of the following steps. First, the trajectories are assigned a priori probabilities that rely on the independence assumption between the time points. Then, these probabilities are revised according to the spatio-temporal correlations encoded by the constraints. This is done by conditioning the a priori probability of each trajectory to the event that the constraints are satisfied: this means taking the ratio of this a priori probability to the sum of the a priori probabilities of all the consistent trajectories. Instead of performing these steps by materializing all the trajectories and their a priori probabilities (which is infeasible, owing to the typically huge number of trajectories), our approach exploits a data structure called conditioned trajectory graph (ct-graph) that compactly represents the trajectories and their conditioned probabilities, and an algorithm for efficiently constructing the ct-graph, which progressively builds it while avoiding the construction of components encoding inconsistent trajectories.
ROUTING MANAGEMENT APPLICATION BASED ON MOBILE AGENTS ON THE INTERNET2

TIC1998-0495-C02-01 ABSTRACT In this work, the design and development of a routing management application based on mobile agents in an Internet 2 (I2) environment is proposed. The objective of the application is to provide a routing based on the quality of service defined on a Service Level Agreement (SLA). For this purpose, the application obtains in each moment the best route according to a traffic and congestion control. As a consequence of the distributed operation scenario and the requirement of real time functionality, the application uses CORBA and intelligent mobile agent technologies.
CRUDE OIL FORECASTING WITH AN IMPROVED MODEL BASED ON WAVELET TRANSFORM AND SUPPORT VECTOR MACHINES

This paper presents a hybrid wavelet support vector machines (WSVM) model that combines both wavelet technique and the SVM model for crude oil forecasting. Based on the purpose, the main time series was decomposed to some multi-frequently time series by wavelet theory and these time series were imposed as input data to the SVM for forecasting of crude oil series. To assess the effectiveness of this model, daily crude oil market-West Texas Intermediate (WTI) has been used as the case study. Time series prediction capability performance of the WSVM model is compared with the single SVM model using various statistics measures. As seen in comparison, WSVM yielded more accurate than of any individual model and offered a practical solution to the problem in crude oil forecasting.
Inductive and non-inductive methods of clustering

This paper aims to overview a variety of methods of clustering by introducing the concepts of inductive and non-inductive clustering. These concepts are in parallel with the concepts of inductive and transductive learning in the studies of semi-supervised classification. When the result of clustering naturally induces functions for classification on the whole space of interest, the method is called that of inductive clustering. In contrast, a method is called non-inductive, if it does not induce such a function. Typical examples in the inductive class are crisp and fuzzy c-means, while one of the non-inductive class is agglomerative hierarchical clustering. We show how differences of the two classes of methods of clustering occur in the theoretical consideration of clustering algorithms, in particular two concepts are clearly contrasted when positive-definite kernel functions are employed. Moreover semi-supervised classification is considered for the two classes.
Embryonic development of the rat cerebellum. III. Regional differences in the time of origin, migration, and settling of Purkinje cells

The time of origin, site of origin, migratory path and settling pattern of the Purkinje cells of the cerebellar hemispheres, anterior vermis, and posterior vermis were investigated in thymidine radiograms and plastic‐embedded materials from rat embryos ranging in age from 15 to 22 days. In the hemispheres there is a rostral‐to‐caudal cytogenetic gradient: the Purkinje cells of lobulus simplex, crus I, and crus II are produced earlier than the Purkinje cells of the paramedian lobule and paraflocculus, followed by the Purkinje cells of the flocculus. The Purkinje cells of the vermis, in general, are generated later than those of the hemispheres, and with a reverse gradient from caudal to rostral: the Purkinje cells of the posterior vermis (lobules X–VI) being produced ahead of the Purkinje cells of the anterior posteriorly directed wedge of early‐produced Purkinje cells through the vermis.
New heating system using resonant cavity applicator with electrical shield for rheumatoid arthritis

This paper discusses the improvement of the reentrant resonant cavity applicator with an electromagnetic shield for concentrating heating energy in deep regions inside a human knee. Thermotherapy is widely used for musculoskeletal disorders as a physical therapy in clinical settings. Hot packs, paraffin baths, ultra-short waves and microwaves are generally used as well as therapeutic exercises for joint diseases such as osteoarthritis (OA) and rheumatoid arthritis. However, all of them have advantages and disadvantages, and a successful heating method for deep tissue has not yet been realized. In this paper, first, the heating method with the resonant cavity applicator is presented. Second, the proposed method of reconstructing the 3-D anatomical human FEM model to calculate temperature distributions is described. Third, the results of temperature distributions are discussed. Finally, the results of the temperature distributions for the resonant cavity applicator is compared with the temperature distribution for microwave diathermy. As the penetration depth of microwave diathermy used in the clinic is less than approximately 20 mm, it is not easy to heat the joint cavity. However, the proposed heating method with the resonant cavity applicator can be expected to heat the joint cavity.
The Neural Extracellular Matrix, Cell Adhesion Molecules and Proteolysis in Glioma Invasion and Tumorigenicity

High-grade gliomas are the most prevalent and lethal form of primary intracranial tumors. Despite significant progress in surgical and adjuvant therapeutic treatments for gliomas, patient prognosis still remains dismal. The ability of gliomas to invade the normal surrounding brain tissue contributes to their capacity to evade therapeutic interventions, ultimately leading to tumor recurrence and subsequent disease progression (Rich & Bigner, 2004). Another major therapeutic obstacle comes from the high degree of intratumoral cellular heterogeneity. The tumor mass is comprised of both terminally differentiated cells, cells that exhibit finite capabilities of self-renewal and multipotency, and a smaller subpopulation of cells that exhibit stem cell-like qualities. These stem-like cells, termed Glioma Initiating Cells (GICs), exihibit pluripotency, self-renewal and, importantly, are capable of repopulating the original parental tumor. Therefore, more effective therapies may be derived from targeting both the infiltrative nature of gliomas and GICs (Louis, 2006; Park & Rich, 2009). The ability of glioma tumor cells to infiltrate the normal surrounding brain tissue is a property that is restricted to intracranial tumors that are phenotypically glial within the central nervous system (CNS). As metastatic tumor cells that are highly invasive in the periphery fail to invade surrounding brain tissue once within the confines of the CNS, and invasive glioma tumors that originate in the brain rarely metastasize outside of the CNS. These findings suggest that the unique interaction between glioma tumor cells and the neural extracellular environment mediate glioma invasion (Bellail et al., 2004; Nutt et al., 2001a). A defining attribute of the neural extracellular environment is the unique composition of the neural extracellular matrix (ECM), which unlike other peripheral matrices has low levels of fibrilliar proteins like collagens, fibronectin, and laminin (Ruoslahti, 1996). In both neural development and pathogenesis, the neural ECM regulates key biological processes including cellular migration, maturation, synapse formation, and plasticity. In the adult brain the composition of the neural ECM is largely inhibitory to cellular reorganization (Galtrey & Fawcett, 2007; Zimmermann & Dours-Zimmermann, 2008). Therefore, glioma tumor cell invasion into the normal surrounding brain tissue is derived from their ability to overcome this normally inhibitory extracellular environment. Decades of research has
Promoting and supporting credibility in neuroscience

(http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). https://doi.org/10.1177/2398212819844167 Brain and Neuroscience Advances Volume 3: 1 –4 © The Author(s) 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/2398212819844167 journals.sagepub.com/home/bna
Country Portfolios

How do countries hold their financial wealth? We construct a new database of countries' claims on capital located at home and abroad, and international borrowing and lending, covering 68 countries from 1966 to 1997. We find that a small amount of capital flows from rich countries to poor countries. Countries' foreign asset positions are remarkably persistent, and mostly take the form of foreign loans rather than foreign equity. To interpret these facts, we build a simple model of international capital flows that highlights the interplay between diminishing returns, production risk and sovereign risk. We show that in the presence of reasonable diminishing returns and production risk, the probability that international crises occur twice a century is enough to generate a set of country portfolios that are roughly consistent with the data.
Predicting the rate of cigarette smoking based on resilience and cognitive emotion regulation in the non-clinical population of Shiraz, Iran, 2016

Article Info Background: Cigarette smoking is considered a public health problem. Much research has been conducted on smoking and respective factors, but little research has addressed the prediction of the smoking rate based on various psychological variables. The present study was conducted aimed at predicting the smoking rate in the non-clinical population of Shiraz, Iran, in 2016, based on resilience and cognitive emotion regulation. Materials and methods: In the present descriptive study, 250 female and male smokers of the non-clinical population of Shiraz, Iran, in 2016, were selected through random sampling. The research instruments included a demographic scale and smoking patterns, the Connor-Davidson Resilience Scale (CD-RISC), and the Cognitive Emotion Regulation Scale. The obtained data were analyzed by the Pearson correlation and linear regression, using SPSS (Version 20(. Results: The results showed a negative correlation between the subscales of resilience and cognitive emotion regulation, age, and education with the cigarette smoking rate (P<0.01). In addition, the values of R and R2 were 0.39 and 0.15, respectively. The daily smoking rates can be predictable with resiliency, cognitive-emotional regulation subscales, age, and education variables (0/015). Conclusion: Some psychological variables, such as resilience and cognitive emotion regulation probably affect the tendency to cigarette smoking, so considering these variables could be efficient in the interventions for preventing and stopping cigarette
Air Trapping on Chest CT Is Associated with Worse Ventilation Distribution in Infants with Cystic Fibrosis Diagnosed following Newborn Screening

Background In school-aged children with cystic fibrosis (CF) structural lung damage assessed using chest CT is associated with abnormal ventilation distribution. The primary objective of this analysis was to determine the relationships between ventilation distribution outcomes and the presence and extent of structural damage as assessed by chest CT in infants and young children with CF. Methods Data of infants and young children with CF diagnosed following newborn screening consecutively reviewed between August 2005 and December 2009 were analysed. Ventilation distribution (lung clearance index and the first and second moment ratios [LCI, M1/M0 and M2/M0, respectively]), chest CT and airway pathology from bronchoalveolar lavage were determined at diagnosis and then annually. The chest CT scans were evaluated for the presence or absence of bronchiectasis and air trapping. Results Matched lung function, chest CT and pathology outcomes were available in 49 infants (31 male) with bronchiectasis and air trapping present in 13 (27%) and 24 (49%) infants, respectively. The presence of bronchiectasis or air trapping was associated with increased M2/M0 but not LCI or M1/M0. There was a weak, but statistically significant association between the extent of air trapping and all ventilation distribution outcomes. Conclusion These findings suggest that in early CF lung disease there are weak associations between ventilation distribution and lung damage from chest CT. These finding are in contrast to those reported in older children. These findings suggest that assessments of LCI could not be used to replace a chest CT scan for the assessment of structural lung disease in the first two years of life. Further research in which both MBW and chest CT outcomes are obtained is required to assess the role of ventilation distribution in tracking the progression of lung damage in infants with CF.
Nonapnea Sleep Disorders and Incident Chronic Kidney Disease

AbstractNonapnea sleep disorders (NASDs) are associated with an increased risk of stroke, diabetes, and hypertension. No longitudinal study has yet examined the association between NASD and chronic kidney disease (CKD) by using epidemiologic study methods. To test this hypothesis, we examined the effect of NASD on the incidence of CKD in a large population-based retrospective cohort study.Based on a retrospective cohort study of a general population sample of 128 to 436 patients in the Taiwan National Health Insurance Research Database from January 1, 1998 to December 31, 2001, 42 to 812 NASD patients were followed up for 10.2 ± 3.12 years, and additional 85 to 624 individuals had no NASD at baseline. The International Classification of Diseases, Ninth Revision, Clinical Modification was used to identify the diagnosis of disease. Cox proportional hazard regression models were used to assess the association between NASD and subsequent CKD risk.The incidence rate of CKD was significantly higher in the NASD cohort than in the comparison cohort (2.68 vs 1.88 per 1000 person-years, respectively). After we adjusted for age, sex, and comorbidities, the risk of developing CKD was significant for patients with NASD (adjusted hazard ratio [HR] = 1.13; 95% confidence interval [CI] = 1.05–1.22; P < 0.01). Among different types of NASDs, patients with sleep disturbance associated disorders had a 14% increased risk of developing CKD (95% CI = 1.03–1.26; P < 0.01), whereas patients with insomnia had a 13% increased risk of subsequent CKD (95% CI = 1.02–1.25; P < 0.05) compared with the non-NASD cohort. Kaplan–Meier survival analysis indicated that the CKD-free rate was 1% lower in the NASD cohort than in the comparison cohort (log-rank test, P < 0.0001). Our study provides evidence that patients with NASD have an increased risk of developing subsequent CKD compared with patients without NASD; men, elderly people, and patients with concomitant comorbidities are at the greatest risk.
On validation of turbulent mixing simulations for Rayleigh–Taylor instability

The purpose of this paper is to analyze the validation achieved in recent simulations of Rayleigh–Taylor unstable mixing. The simulations are already in agreement with experiment; mesh refinement or insertion of a calibrated subgrid model for mass diffusion will serve to refine this validation and possibly shed light on the role of unobserved long wavelength perturbations in the initial data. In this paper we present evidence to suggest that a subgrid model will have a barely noticeable effect on the simulation. The analysis is of independent interest, as it connects a validated simulation to common studies of mixing properties. The average molecular mixing parameter θ for the ideal and immiscible simulations is zero at a grid block level, as is required by the exact microphysics of these simulations. Averaging of data over volumes of (4Δx)3 to (8Δx)3 yields a conventional value θ∼0.8, suggesting that fluid entrainment in front tracked simulations produces a result similar to numerical mass diffusion in u.
Differentiation of Human Dental Pulp Stem Cells into Dopaminergic Neuron-like Cells in Vitro

We investigated the potential of human dental pulp stem cells (hDPSCs) to differentiate into dopaminergic neurons in vitro as an autologous stem cell source for Parkinson’s disease treatment. The hDPSCs were expanded in knockout-embryonic stem cell (KO-ES) medium containing leukemia inhibitory factor (LIF) on gelatin-coated plates for 3–4 days. Then, the medium was replaced with KO-ES medium without LIF to allow the formation of the neurosphere for 4 days. The neurosphere was transferred into ITS medium, containing ITS (human insulin-transferrin-sodium) and fibronectin, to select for Nestin-positive cells for 6–8 days. The cells were then cultured in N-2 medium containing basic fibroblast growth factor (FGF), FGF-8b, sonic hedgehog-N, and ascorbic acid on poly-l-ornithine/fibronectin-coated plates to expand the Nestin-positive cells for up to 2 weeks. Finally, the cells were transferred into N-2/ascorbic acid medium to allow for their differentiation into dopaminergic neurons for 10–15 days. The differentiation stages were confirmed by morphological, immunocytochemical, flow cytometric, real-time PCR, and ELISA analyses. The expressions of mesenchymal stem cell markers were observed at the early stages. The expressions of early neuronal markers were maintained throughout the differentiation stages. The mature neural markers showed increased expression from stage 3 onwards. The percentage of cells positive for tyrosine hydroxylase was 14.49%, and the amount was 0.526 ± 0.033 ng/mL at the last stage. hDPSCs can differentiate into dopaminergic neural cells under experimental cell differentiation conditions, showing potential as an autologous cell source for the treatment of Parkinson’s disease.