Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspectivas actuales en el tratamiento del trastorno de estrés postraumático en la población infantil: Análisis bibliométrico Current approaches to post-traumatic stress disorder among children: A biblimetric analysis

Very little attention has been paid by researchers to post-traumatic stress disorder (PTSD)in the paediatric population. Not until 1987 the fact that child reaction to trauma may differ from adult reaction is reflected in diagnostic criteria. Bearing these differences in mind with regard to the PTSD semiology, we may think that planning of assessment and intervention must differ in the case of children. Therefore, the aim of this paper is to follow the evolution of literature during the last 10 years, and to establish the current state of the art of PTSD in children. Deficiencies and needs will be remarked in order to develop future research lines.
Design and analysis of printed dipole slot antenna for WLAN and RFID applications

A printed dipole slot antenna for 2.4GHz RFID band and 5.2GHz WLAN band application is designed fabricated on FR4 substrate and measured using Agilent network analyzer. This antenna effectively covers both 2.4GHz and 5.2GHz bands. The return losses of the measured results are in agreement with simulated results, the measured S parameters and radiation pattern showed that the proposed design is suitable for RFID and WLAN frequency regions. The measured return loss (S parameter) of is -14.8 dB at 2.4GHz and simulated return loss is 31.61dB at 5.2GHz which is most suitable for RFID and wireless LAN applications.
Clinical Features according to the Frequency of Acute Exacerbation in COPD

Background Chronic obstructive pulmonary disease (COPD) is now regarded as a heterogenous disease, with variable phenotypes. Acute exacerbation of COPD is a major event that alters the natural course of disease. The frequency of COPD exacerbation is variable among patients. We analyzed clinical features, according to the frequency of acute exacerbation in COPD. Methods Sixty patients, who visited Gyeongsang National University Hospital from March 2010 to October 2010, were enrolled. Patients were divided into two groups, according to their frequency of acute exacerbation. Frequent exacerbator is defined as the patient who has two or more exacerbation per one year. We reviewed patients' medical records and investigated modified Medical Research Council (MMRC) dyspnea scale, smoking history and frequency of acute exacerbation. We also conducted pulmonary function test and 6-minute walking test, calculated body mass index, degree of airway obstruction and dyspnea and exercise capacity (BODE) index and measured CD146 cells in the peripheral blood. Results The number of frequent exacerbators and infrequent exacerbators was 20 and 40, respectively. The frequent exacerbator group had more severe airway obstruction (forced expiratory volume in one second [FEV1], 45% vs. 65.3%, p=0.001; FEV1/forced vital capacity, 44.3% vs. 50.5%, p=0.046). MMRC dyspnea scale and BODE index were significantly higher in the frequent exacerbator group (1.8 vs. 1.1, p=0.016; 3.9 vs. 2.1, p=0.014, respectively). The fraction of CD146 cells significantly increased in the frequent exacerbator group (2.0 vs. 1.0, p<0.001). Conclusion Frequent exacerbator had more severe airway obstruction and higher symptom score and BODE index. However, circulating endothelial cells measured by CD146 needed to be confirmed in the future.
Development of a behavioral test battery for the assessment of pharmacologic and non-pharmacologic environmental factors on the developing brain.

Preterm infants are at a high risk of suffering from alterations in brain development with subsequent neurocognitive sequelae. Beside histochemical and biochemical methods, it is of utmost importance to evaluate the effect of environmental factors and interventions on functional outcome. In the present work a neurobehavioral test battery with several routines and procedures including testing, data processing and statistical analyses were successfully established, implement and tested on two animal models of preterm brain injury.
Detecting JavaScript races that matter

As JavaScript has become virtually omnipresent as the language for programming large and complex web applications in the last several years, we have seen an increase in interest in finding data races in client-side JavaScript. While JavaScript execution is single-threaded, there is still enough potential for data races, created largely by the non-determinism of the scheduler. Recently, several academic efforts have explored both static and run-time analysis approaches in an effort to find data races. However, despite this, we have not seen these analysis techniques deployed in practice and we have only seen scarce evidence that developers find and fix bugs related to data races in JavaScript. In this paper we argue for a different formulation of what it means to have a data race in a JavaScript application and distinguish between benign and harmful races, affecting persistent browser or server state. We further argue that while benign races — the subject of the majority of prior work — do exist, harmful races are exceedingly rare in practice (19 harmful vs. 621 benign). Our results shed a new light on the issues of data race prevalence and importance. To find races, we also propose a novel lightweight run-time symbolic exploration algorithm for finding races in traces of run-time execution. Our algorithm eschews schedule exploration in favor of smaller run-time overheads and thus can be used by beta testers or in crowd-sourced testing. In our experiments on 26 sites, we demonstrate that benign races are considerably more common than harmful ones.
Prevalence and Prognostic Importance of Pulmonary Hypertension in Dogs with Myxomatous Mitral Valve Disease

Background Pulmonary hypertension (PH) is common in dogs with myxomatous mitral valve disease (MMVD) but its effect on clinical outcome has not been investigated. Hypothesis/objectives The presence of PH worsens the outcome in dogs with MMVD. To compare survival times of dogs with MMVD and PH to those without PH. Animals Two hundred and twelve client‐owned dogs. Methods Case review study. Medical records of dogs diagnosed with ACVIM stage B2 and C MMVD between January 2010 and December 2011 were retrospectively reviewed. Long‐term outcome was determined by telephone interview or from the medical record. End of the observation period was March 2013. PH was identified if tricuspid regurgitation peak velocity was >3 m/s. Results Two hundred and twelve were identified. Eighty‐three dogs (39%) had PH. PH was more commonly identified in stage C compared to B2 (P < .0001). One hundred and five (49.5%) dogs died during the observation period. Median survival time for the entire study population was 567 days (95% CI 512–743). Stage C (P = .003), the presence of PH (P = .009), left atrial to aortic root ratio (LA/Ao) >1.7 (P = .0002), normalized left‐ventricular end‐diastolic diameter (LVEDn) >1.73 (P = .048), and tricuspid regurgitation pressure gradient (TRPG) >55 mmHg (P = .009) were associated with worse outcomes in the univariate analyses. The presence of TRPG >55 mmHg (HR 1.8 95% CI 1–2.9; P = .05) and LA/Ao > 1.7 (HR 2 95% CI 1.2–3.4; P = .01) remained significant predictors of worse outcome in the multivariate analysis. Conclusions and Clinical Importance In dogs with MMVD, moderate to severe PH worsens outcome.
Rule Extraction from Artiicial Neural Networks Trained on Elementary Number Classiication Tasks

Cascade-Correlation and BpTower networks are trained on pattern classiication tasks. The digits of four-digit integer numbers are sparsley coded and neural networks are trained to recognise the digit patterns of numbers divisible by ve, four and three. The performance of the decompositional rule extraction technique LAP is compared with that of the pedagogical technique RuleVI when extracting rules from trained artiicial neural networks. It turns out that the quality of the extracted rules depends on the combination of the neural network and the rule extraction method. The results are compared with results obtained by C4.5. Finally SHRUTI is applied to one of the rule sets.
Genetic risk factors of Alzheimer's disease and cell-to-cell transmission of Tau

In Alzheimer’s disease (AD), loss of neurons and synapses parallels the formation of neurofibrillary tangles, protein aggregates mainly composed of hyperphosphorylated and aggregated Tau protein. Tau is mostly a cytosolic protein but can also be secreted by neurons. Cell-to-cell transfer of misfolded Tau protein plays a key role in the spread of neurofibrillary pathology between brain regions in AD and other tauopathies. Advances in genome-wide technologies have identified a large number of genetic risk factors for late-onset AD (LOAD). Currently, it remains unknown if genetic factors influence disease risk or progression rate by altering cell-to-cell propagation of Tau. Several LOAD risk genes are functionally associated with endocytic trafficking providing a potential link to Tau secretion and uptake. Recently, a LOAD risk gene FRMD4A was shown to regulate Tau secretion via a pathway linked to presynaptic vesicle machinery and polarity signaling. Tau release is linked to neuronal activity, and genetic factors that affect presynaptic vesicle release in the aging brain may also influence disease progression in AD and other tauopathies. In this mini review, we summarize the recent literature with a focus on the role of FRMD4A-cytohesin-Arf6 pathway and presynaptic vesicle machinery in the secretion of Tau.
Computability and Adaptivity in CFD

We present an approach to Computational Fluid Dynamics CFD based on adaptive stabilized Galerkin finite element methods with duality based a posteriori error control for chosen output quantities of interest. We address the basic question of computability in CFD: For a given flow, w hat quantity is computable to what tolerance to what cost? We focus on incompressible Newtonian flow with medium to large Reynolds numbers involving both laminar and turbulent flow features. Our basic tool is a repre sentation formula for the error in the quantity of interest in terms of a space-time integral of the residual of a computed solution multiplied by weights related to derivatives of the solution of an associated dual linearize d problem with data connected to the output. We use the error representation formula to derive an a posterori er ror estimate combining residuals with computed dual weights, which is used for mesh adaptivity in space-time with the objective of satisfying a given error tolerance with minimal computational effort. We show in conrete examples that outputs such as mean values in time of drag and lift of turbulent flow around a bluff body are computable o n a PC with a tolerance of a few percent using a few hundred thousand mesh points in space. We refer to our methodology as Adaptive DNS/LES, where automatically by adaptivity certain features of the flow are resolved in a Direct Numerical Simulation DNS , while certain other small scale turbulent features are left unresolved in a Large Eddy Simulation LES . The stabilization of the Galerkin method giving a weighted least square control of the residual acts as the subgrid model in the LES. The a posteriori error estimate takes into account both the error from discretization and the error from the subgrid model.
Cerebral malaria

Cerebral malaria is the most severe pathology caused by the malaria parasite, Plasmodium falciparum. The pathogenic mechanisms leading to cerebral malaria are still poorly defined as studies have been hampered by limited accessibility to human tissues. Nevertheless, histopathology of post-mortem human tissues and mouse models of cerebral malaria have indicated involvement of the blood-brain barrier in cerebral malaria. In contrast to viruses and bacteria, malaria parasites do not infiltrate and infect the brain parenchyma. Instead, rupture of the blood-brain barrier occurs and may lead to hemorrhages resulting in neurological alterations. Here, we review the most recent findings from human studies and mouse models on the interactions of malaria parasites and the blood-brain barrier, shedding light on the pathogenesis of cerebral malaria, which may provide directions for possible interventions.
Towards the ubiquitous Web

Today, we observe the amalgamation of the Social Web and the Mobile Web, which will ultimately lead to a Ubiquitous Web. The integration and aggregation of the different kinds of available data, and the extraction of useful knowledge and its representation has become an important challenge for researchers from the Semantic Web, Web 2.0, social network analysis and machine learning communities. We discuss the Ubiquitous Web vision, by addressing the challenge of bridging the gap between Web 2.0 and the Semantic Web, before widening the scope to mobile applications.
On Inferring Autonomous System in the Internet

-The Internet consists of rapidly increasing number of hosts interconnected by constantly evolving networks of links and routers. Interdomain routing in the Internet is coordinated by the Border Gateway Protocol (BGP). BGP allows each autonomous system (AS) to choose its own administrative policy in selecting routes and propagating reachability information to others. These routing policies are constrained by the contractual commercial agreements between administrative domains. For example, an AS sets its policy so that it does not provide transit services between its providers. Such policies imply that AS relationships are an important aspect of Internet structure. We propose an augmented AS graph representation that classifies AS relationships into customer-provider, peering, and sibling relationships. We classify the types of routes that can appear in BGP routing tables based on the relationships between the ASs in the path and present heuristic algorithms that infer AS relationships from BGP routing tables. The algorithms are tested on publicly available BGP routing tables. We verify our inference results with AT&T internal information on its relationship with neighboring ASs. As much as 99.1% of our inference results are confirmed by the AT&T internal information. We also verify our inferred sibling relationships with the information acquired from the WHOIS lookup service. More "lhan half of our inferred sibling-to-sibling relationships are conf~rmed by the WHOIS lookup service. To the best of our knowledge, there has been no publicly available information about AS relationships and this is the first attempt in understanding and inferring AS relationships in the Internet. We show evidence that some routing table entries stem from router misconfigurations.
Online spectrum auction in cognitive radio networks with uncertain activities of primary users

In this paper, we investigate an online spectrum auction problem in cognitive radio networks with uncertain activities of primary users (PUs). In our framework, a primary base station (PBS), acted as the spectrum auctioneer, leases its under-utilized channels to secondary users (SUs) who request and access spectrum on the fly. Different from most of existing works in online spectrum allocation, we focus on a more practical situation that the auctioneer (or the PBS) has no prior knowledge of PUs' activities so that its channel states are not static. In order to balance the auction profits from granted SUs' spectrum requests and the potential penalties caused by incomplete services to PUs, we introduce the idea of virtual spectrum sellers and formulate the problem as an online double spectrum auction. We then propose a novel online admission and pricing mechanism which also considers the reusability of wireless spectrum. Theoretical analyses are provided to prove that our auction algorithm satisfies all desired economic properties in terms of budget-balance, individual rationality and truthfulness. Simulation results show that our proposed auction algorithm can increase the utility of the PBS, enhance spectrum utilization and achieve better satisfaction for SUs compared to counterparts.
Taming the Uncertainty: Budget Limited Robust Crowdsensing Through Online Learning

Mobile crowdsensing has been intensively explored recently due to its flexible and pervasive sensing ability. Although many crowdsensing platforms have been built for various applications, the general issue of how to manage such systems intelligently remains largely open. While recent investigations mostly focus on incentivizing crowdsensing, the robustness of crowdsensing toward uncontrollable sensing quality, another important issue, has been widely neglected. Due to the non-professional personnel and devices, the quality of crowdsensing data cannot be fully guaranteed, hence the revenue gained from mobile crowdsensing is generally uncertain. Moreover, the need for compensating the sensing costs under a limited budget has exacerbated the situation: one does not enjoy an infinite horizon to learn the sensing ability of the crowd and hence to make decisions based on sufficient statistics. In this paper, we present a novel framework, Budget LImited robuSt crowdSensing (BLISS), to handle this problem through an online learning approach. Our approach aims to minimize the difference on average sense (a.k.a. regret) between the achieved total sensing revenue and the (unknown) optimal one, and we show that our BLISS sensing policies achieve logarithmic regret bounds and Hannan-consistency. Finally, we use extensive simulations to demonstrate the effectiveness of BLISS.
Affective classification using Bayesian classifier and supervised learning

An affective classification technology plays a key role in the affective human and computer interaction. This paper presents an affective classification method based on the Bayes classifier and the supervisory learning. We newly define a weighted-log-posterior function for the Bayes classifier, instead of the posterior function or the likelihood function that is used in the ordinary Bayes classifier. The weighted-log-posterior function is represented as the weighted sum of likelihood function of each feature plus bias factor under the assumption of feature independence. The Bayes classifier finds an affective state with the maximum value of the weighted-log-posterior function. The weights and the bias factors are iteratively computed by using supervisory learning approach. In the implementation, the affective states are divided into two and three classes in valence dimension and arousal dimension, respectively. An open database for emotion analysis using electroencephalogram (DEAP) is used to evaluate the proposed method. The accuracies for valence and arousal classification are 66.6 % and 66.4 % for two classes and 53.4 % and 51.0 % for three classes, respectively.
Independence through social networks: bridging potential among older women and men.

OBJECTIVES Most studies of older adults' social networks focus on their access to dense networks that yield access to social support. This paper documents gender differences in the extent to which older adults maintain a related, but distinct, form of social capital-bridging potential, which involves serving as a tie between two unconnected parties and thus boosts independence and control of everyday social life. METHODS I use egocentric social network data from a national sample of 3,005 older adults--collected in 2005-2006 by the National Social Life, Health, and Aging Project--to compare older men's and women's network bridging potential using multivariate regression analysis. RESULTS Older women are more likely than older men to have bridging potential in their networks-between both kin and non-kin contacts. These gender differences increase with age. Older women are also more likely to have network members who are not connected to or monopolized by their spouse or partner. Some, but not all, of these gender differences are due to the fact that older women have larger social networks and maintain more ties to people outside of the household. DISCUSSION These findings raise important questions about the relational advantages older women have over older men, including greater autonomy, and contradict stereotypes about women having more closely knit, kin-centered networks than men.
FAKTOR YANG BERPENGARUH MENINGKATKAN RISIKO TERJADINYA PREMENSTRUAL SYNDROME (PMS) PADA WANITA USIA SUBUR MAHASISWI ALIH JENIS FAKULTAS KESEHATAN MASYARAKAT UNIVERSITAS AIRLANGGA TAHUN 2013-2014

Premenstrual Syndrome (PMS) is a group of physical symptoms, psychological, and emotions associated with a woman's menstrual cycle. Premenstrual syndrome is one of disorder which emerge approach menstruation. It is a problem for the student because it causes a decrease in the concentrations studied. Factors that increase the risk of premenstrual syndrome are women who have birth, marital status, age, stress, diet, eating and drinking habits, and physical activity. The purpose of this study was to analyze the influence of age, marital status, history of childbirth, stress, eating and drinking habits, and physical activity factors that affect the occurrence of PMS. The research was conducted with cross-sectional design using a quantitative approach. Interviews were conducted in 49 women of childbearing age. Subjects drawn from the population by simple random sampling. Depth interviews were conducted to obtain more detailed information about the variables studied. The independent variables were age, marital status, history of childbirth, stress levels, eating and drinking habits, physical activity. Prevalence of premenstrual syndrome in women of childbearing age in the Class Type Rather School of Public Health, Airlangga University – Surabaya is 46.9%. Results of multiple logistic regression showed that the factors that eating and drinking habits (p = 0.026; OR =5,228) and physical activity (p = 0.007; OR = 10,810). The third variable has a p-value smaller than the significant value = 0.05. The conclusion are women of childbearing age who are experiencing habit of consuming certain foods and drinks and less physical activity have a higher risk of experiencing PMS.
Recognition and coupling of A-to-I edited sites are determined by the tertiary structure of the RNA

Adenosine-to-inosine (A-to-I) editing has been shown to be an important mechanism that increases protein diversity in the brain of organisms from human to fly. The family of ADAR enzymes converts some adenosines of RNA duplexes to inosines through hydrolytic deamination. The adenosine recognition mechanism is still largely unknown. Here, to investigate it, we analyzed a set of selectively edited substrates with a cluster of edited sites. We used a large set of individual transcripts sequenced by the 454 sequencing technique. On average, we analyzed 570 single transcripts per edited region at four different developmental stages from embryogenesis to adulthood. To our knowledge, this is the first time, large-scale sequencing has been used to determine synchronous editing events. We demonstrate that edited sites are only coupled within specific distances from each other. Furthermore, our results show that the coupled sites of editing are positioned on the same side of a helix, indicating that the three-dimensional structure is key in ADAR enzyme substrate recognition. Finally, we propose that editing by the ADAR enzymes is initiated by their attraction to one principal site in the substrate.