Miracle-dz/UniFAR-FTUs huggingface dataset:
Neighborhood-Level Stress and Circadian Cortisol: A Systematic Review and Meta-Analysis

Abstract The main objective was to find association between basal cortisol and neighborhood-level stress. Systematic searches, including electronic and hand searches, were conducted. The most recent date of the search was July 26, 2013. Primary observational studies included if they considered stress related outcomes in the neighborhood context. Using the EndNote X7 advanced search option; the authors examined the abstracts and titles of the 18,092 articles to exclude obviously irrelevant studies, gray literature, discussion papers, reviews and, studies with no complete data. Two authors independently extracted data from the original reports into pre-designed data extraction forms based on the Data Extraction Template of the Cochrane Consumer and Communication Review Group (CCCRG). Ten studies with a total of 2,134 participants were synthesized and analyzed. Two studies out of ten received expanded meta-analysis. The overall effect size (95% CI) for cortisol level for residents in neighborhoods with lower stress compared to inhabitants from higher was 0.12 (0.01, 0.23). This review is demonstrating a link between psychosocial or physical stress and cortisol obtained from saliva. However, living in high disorder neighborhoods results in higher level of cortisol. This represents a biological indicator of psychosocial/physical stress exposure (i.e., neighborhood disorder) that reflects variances in stress exposure levels.
Scalar multiplet dark matter

We perform a systematic study of the phenomenology associated to models where the dark matter consists in the neutral component of a scalar SU(2)L n-uplet, up to n = 7. If one includes only the pure gauge induced annihilation cross-sections it is known that such particles provide good dark matter candidates, leading to the observed dark matter relic abundance for a particular value of their mass around the TeV scale. We show that these values actually become ranges of values - which we determine - if one takes into account the annihilations induced by the various scalar couplings appearing in these models. This leads to predictions for both direct and indirect detection signatures as a function of the dark matter mass within these ranges. Both can be largely enhanced by the quartic coupling contributions. We also explain how, if one adds right-handed neutrinos to the scalar doublet case, the results of this analysis allow to have altogether a viable dark matter candidate, successful generation of neutrino masses, and leptogenesis in a particularly minimal way with all new physics at the TeV scale.
Who matters most? Social support, social strain, and emotions

This research investigates the way in which social support and social strain stemming from spouses, children, and friends have different impacts on emotional states. While previous studies have compared the relative impact of different sources, our research builds upon these studies by (1) comparing various close network ties and (2) leveraging longitudinal data to investigate the causal links between support and strain from different sources and emotional states over time. We analyze individuals who have a spouse, a child, and friends across three waves of the Americans’ Changing Lives data. Although we find that social support and strain from all three sources are associated with emotional states, this relationship is not always causal. In the majority of cases, the same people who experience support or strain in their relationships are also more likely to experience more positive or negative emotional states, respectively. Only spousal interactions and child-based strain have a direct causal effect on emotional states.
Construction and characterisation of a complete reverse genetics system of dengue virus type 3

Dengue virulence and fitness are important factors that determine disease outcome. However, dengue virus (DENV) molecular biology and pathogenesis are not completely elucidated. New insights on those mechanisms have been facilitated by the development of reverse genetic systems in the past decades. Unfortunately, instability of flavivirus genomes cloned in Escherichia coli has been a major problem in these systems. Here, we describe the development of a complete reverse genetics system, based on the construction of an infectious clone and replicon for a low passage DENV-3 genotype III of a clinical isolate. Both constructs were assembled into a newly designed yeast- E. coli shuttle vector by homologous recombination technique and propagated in yeast to prevent any possible genome instability in E. coli . RNA transcripts derived from the infectious clone are infectious upon transfection into BHK-21 cells even after repeated passages of the plasmid in yeast. Transcript-derived DENV-3 exhibited growth kinetics, focus formation size comparable to original DENV-3 in mosquito C6/36 cell culture. In vitro characterisation of DENV-3 replicon confirmed its identity and ability to replicate transiently in BHK-21 cells. The reverse genetics system reported here is a valuable tool that will facilitate further molecular studies in DENV replication, virus attenuation and pathogenesis.
Mobility Prediction Algorithm with Differential Accuracy Requirements in Target Tracking Sensor Network

In object tracking wireless sensor networks, communication overheads affect the accuracy of tracking localization seriously. Existing seminar works suffer from lacking of adaptively on various accuracy requirements, which lead to large amount of network traf¿c. In this paper, we propose a coordination mechanism based on joint mobility prediction method between sink node and sensor node, as to meet different level of accuracy requirements. A optimize model is made according to the analysis on vehicular mobility. Employing the trace generate base on kinematic model and the data collected in real deployment with a commercial simulation platform Qualnet, we set up a simulation environment in evaluating our protocol. Simulation results show that, the proposed algorithm can effectively improve network efficiency and successfully meet different level of accuracy requirements.
Searching ISP Router Networks for Footprints of Engineering Design Consideration

Modeling router-level networks is a challenging task, for it is unclear today as how to represent such networks by a simple and accurate model of modest size and complexity. To provide more insights into router-level network modeling, this paper studies some topological features of several Internet service provider (ISP) networks. The main concern is on the relationships amongst bandwidth constraints, topological features, and engineering design consideration. Computer experiments show some highly unlikely topological structures to network congestion, which are common amongst several geographically independent ISP networks. It suggests that engineering design consideration paves a feasible way to model router-level networks. The findings in this paper may provide some new information toward developing a more realistic model for the router-level Internet.
Component-Based Robotic Engineering (Part II)

This article discusses the role of software components as architectural units of large, possibly distributed, software-intensive robotic systems. The focus is on technologies to manage the heterogeneity of hardware, computational, and communication resources and on design techniques to assemble components into systems . A component-based system is a composition of components, and the way components interact with other components and with the computational environment greatly affects the flexibility of the entire system and the reusability of individual functionality.
Interactive Virtual Materials

In this paper we present a fast and robust approach for simulating elasto-plastic materials and fracture in real time. Our method extends the warped stiffness finite element approach for linear elasticity and combines it with a strain-state-based plasticity model. The internal principal stress components provided by the finite element computation are used to determine fracture locations and orientations. We also present a method to consistently animate and fracture a detailed surface mesh along with the underlying volumetric tetrahedral mesh. This multi-resolution strategy produces realistic animations of a wide spectrum of materials at interactive rates that have typically been simulated off-line thus far.
Automatically Detecting SSL Error-Handling Vulnerabilities in Hybrid Mobile Web Apps

Today, there are many hybrid apps in which both native Android app UI and WebView UI are used. To protect the security and privacy of the communications, these hybrid apps all use HTTPS by WebView, a key component in modern web browser. In this paper, we show there is another type of SSL vulnerability that stems from the error-handling code in the hybrid mobile web apps. At a high level, this error-handling code should have stopped the communication but it still proceeds regardless of certificate errors, thereby leading to the MITM attacks. To automatically identify these vulnerable apps, we present a hybrid approach that combines both static analysis and dynamic analysis. We have implemented our approach and evaluated with 13,820 real world mobile web apps from a third party market, of which 645 are confirmed truly vulnerable, with an average overhead of 60.8 seconds per app.
Statistical Analysis on Social Support toward Migrant Women in Jiangsu Province

This paper studied current condition of social support toward migrant women in Jiangsu province. It was based on a poll of 1187 randomly sampled migrant people (729 females and 458 males) and was conducted by means of Social Support Review Scale (SSRS) and self-compiled questionnaire on general situation. By descriptive statistics, variance analysis and regression analysis, the results indicate that differences of various degrees among people surveyed lie in two aspects: sociology of population factors and migrant experiences and characteristics. Concrete items contained are gender, age, education, marital status, stay duration, daily working hours, frequency of returning hometowns, stability of employment, satisfaction toward one’s living condition and whether working and living in the same city with one’s families.
Games on Graphs The Complexity of Pure Nash Equilibria

In this thesis, we analyze the problem of computing pure Nash equilibria in succinctly representable games, with a focus on graphical and action-graph games. While the problem is NP-Complete for both models, it is known to be polynomial time computable when restricted to games of bounded treewidth. We propose a dynamic programming approach for computing pure Nash equilibria of graphical games. Our algorithm attacks the combinatorics of the problem directly, in contrast to previous algorithms that use mappings to other problems. The analysis yields substantial improvements over the known bounds on the time complexity of the problem. From the viewpoint of parameterized complexity, we prove that computing pure Nash equilibria for graphical games is W [1]-Hard when parameterized by treewidth. On the other hand, our algorithm becomes Fixed-Parameter-Tractable for games with bounded cardinality strategy sets. Moreover, we discuss the implication of our algorithm for solving games with O(log n) bounded treewidth. Finally, it is possible to construct a sample, and the maximum payoff, pure Nash equilibrium without additional computational effort.
A Post-Stroke Rehabilitation System Integrating Robotics, VR and High-Resolution EEG Imaging

We propose a system for the neuro-motor rehabilitation of upper limbs in stroke survivors. The system is composed of a passive robotic device (Trackhold) for kinematic tracking and gravity compensation, five dedicated virtual reality (VR) applications for training of distinct movement patterns, and high-resolution EEG for synchronous monitoring of cortical activity. In contrast to active devices, the Trackhold omits actuators for increased patient safety and acceptance levels, and for reduced complexity and costs. VR applications present all relevant information for task execution as easy-to-understand graphics that do not need any written or verbal instructions. High-resolution electroencephalography (HR-EEG) is synchronized with kinematic data acquisition, allowing for the epoching of EEG signals on the basis of movement-related temporal events. Two healthy volunteers participated in a feasibility study and performed a protocol suggested for the rehabilitation of post-stroke patients. Kinematic data were analyzed by means of in-house code. Open source packages (EEGLAB, SPM, and GMAC) and in-house code were used to process the neurological data. Results from kinematic and EEG data analysis are in line with knowledge from currently available literature and theoretical predictions, and demonstrate the feasibility and potential usefulness of the proposed rehabilitation system to monitor neuro-motor recovery.
A high-performance multimedia streaming model on multi-source streaming approach in peer-to-peer networks

A peer-to-peer (P2P) network is composed of large number of peer computers which are cooperating by exchanging messages in networks. In multimedia streaming applications, multimedia data is required to be efficiently and reliably delivered to processes in a real-time manner. In order to support scalable and reliable multimedia streaming service, we newly discuss a multi-source streaming way where multiple source peers transmit packets of multimedia content to each peer. Each of the source peers transmits different packets with some redundancy to the peer in order to be tolerant of some number of faulty peers and packets lost.
Stereo vision via connected-set operators

The use of connected operator morphology, in particular operators that decompose by area, are examined for the problem of determining dense depth maps from stereo images. It is shown that the use of connected operators can augment and improve conventional processing algorithms. This paper describes how the new algorithm works and presents a comparison of its performance.
ECG signal analysis for detection of cardiovascular abnormalities and ischemic episodes

Electrocardiogram (ECG) is generally used for diagnosis of cardiovascular abnormalities and heart disorders. An efficient method for analyzing the ECG signal towards the detection of cardiovascular abnormalities and ischemic episodes follows mainly five stages: pre-processing, feature extraction,cardiac abnormality detection, beat classification and ischemic episode recognition.The detection of cardiovascular abnormalities like bradycardia and tachycardia is based on the calculation of heart rate(HR) from the extracted ECG features.The extracted ST-segment and T-wave features are used for detection of ischemic episodes.The ability of the method was tested on European ST-T database. The performance of ischemic episode detection shows 88.08% sensitivity (Se) and 92.42% positive predictive accuracy (PPA).
Mechanisms Underlying the Reentrant Circuit of Atrioventricular Nodal Reentrant Tachycardia in Isolated Canine Atrioventricular Nodal Preparation Using Optical Mapping

The reentrant pathways underlying different types of atrioventricular (AV) nodal reentrant tachycardia have not yet been elucidated. This study was performed to optically map Koch’s triangle and surrounding atrial tissue in an isolated canine AV nodal preparation. Multiple preferential AV nodal input pathways were observed in all preparations (n=22) with continuous (73%, n=16) and discontinuous (27%, n=6) AV nodal function curves (AVNFCs). AV nodal echo beats (EBs) were induced in 54% (12/22) of preparations. The reentrant circuit of the slow/fast EB (36%, n=8) started as a block in fast pathway (FP) and a delay in slow pathway (SP) conduction to the compact AV node, then exited from the AV node to the FP, and rapidly returned to the SP through the atrial tissue located at the base of Koch’s triangle. The reentrant circuit of the fast/slow EB (9%, n=2) was in an opposite direction. In the slow/slow EB (9%, n=2), anterograde conduction was over the intermediate pathway (IP) and retrograde conduction was over the SP. Unidirectional conduction block occurred at the junction between the AV node and its input pathways. Conduction over the IP smoothed the transition from the FP to the SP, resulting in a continuous AVNFC. A “jump” in AH interval resulted from shifting of anterograde conduction from the FP to the SP (n=4) or abrupt conduction delay within the AV node through the FP (n=2). These findings indicate that (1) multiple AV nodal anterograde pathways exist in all normal hearts; (2) atrial tissue is involved in reentrant circuits; (3) unidirectional block occurs at the interface between the AV node and its input pathways; and (4) the IP can mask the existence of FP and SP, producing continuous AVNFCs.
First report of OXA-48-producing Klebsiella pneumoniae strains in Iran

Carbapenem-resistant Enterobacteriaceae are increasingly reported worldwide and cause therapeutic problem in health care facilities. In this study 28 imipenem-resistant K. pneumoniae were examined for expression of carbapenemases by phenotypic and genotypic methods. Modified Hodge Test (MHT), CarbaNP test were used for phenotypic detection, and PCR using specific primers for the detection of blaOXA-48-, blaKPC-, blaNDM- and blaVIM-type carbapenemases with specific primers were performed. MHT and CarbaNP tests were positive for all of imipenem-resistant K. pneumoniae. The blaOXA-48 gene was detected in 27/28 isolates. One isolate was positive for the presence of the blaVIM-4 gene. According to our results NP test and MHT have high sensitivity and specificity for detection of those carbapenemases. This study reports the first cases of OXA-48-producing K. pneumoniae in Iran.
Effect of elements number of SRR-based BPF to its characteristics

This paper deals with the investigation of elements number effect of split ring resonator (SRR) based bandpass filter (BPF) to its characteristic. The proposed BPF is intended to operate at around frequency center of 2.4GHz for wireless applications. Three designs of BPFs with 1, 2 and 3 elements of SRR are investigated wherein each design of BPF is deployed on a Rogers RT/Duroid® 6010/6010LM™ dielectric substrate with the thickness of 1.9mm. The characteristics of BPF which are involved in the investigation include return loss, insertion loss, working bandwidth, and physical dimension. The results of investigation show that the shape of frequency response is the most influenced part of BPF in which the higher number of SRR elements produces the sharper selectivity of frequency responses. Meanwhile, the physical dimension of BPF relatively increases for the higher number of elements up to 50% for 3 elements of SRR compared to the BPF with 1 element of SRR.
Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy

Multi-task learning (MTL) is useful for domains in which data originates from multiple sources that are individually under-sampled. MTL methods are able to learn classification models that have higher performance as compared to learning a single model by aggregating all the data together or learning a separate model for each data source. The performance of these methods relies on label accuracy. We address the problem of simultaneously learning multiple classifiers in the MTL framework when the training data has imprecise labels. We assume that there is an additional source of information that provides a score for each instance which reflects the certainty about its label. Modeling this score as being generated by an underlying ranking function, we augment the MTL framework with an added layer of supervision. This results in new MTL methods that are able to learn accurate classifiers while preserving the domain structure provided through the rank information. We apply these methods to the task of detecting abnormal cortical regions in the MRIs of patients suffering from focal epilepsy whose MRI were read as normal by expert neuroradiologists. In addition to the noisy labels provided by the results of surgical resection, we employ the results of an invasive intracranial-EEG exam as an additional source of label information. Our proposed methods are able to successfully detect abnormal regions for all patients in our dataset and achieve a higher performance as compared to baseline methods.
Image enhancement method via blur and noisy image fusion

We present an image enhancement algorithm based on fusing the visual information present in two images of the same scene, captured with different exposure times. The main idea is to exploit the differences between the image degradations that affect the two images. On one hand the short-exposed image is less affected by motion blur, whereas the long-exposed image is less affected by noise. Different fusion rules are designed for the luminance and chrominance components such that to preserve the desirable properties from each input image. We also present a method for estimating the brightness transfer function between the input images for photometric calibration of the short-exposed image with respect to the long-exposed image. As no global blur PSF is assumed, our method can deal with blur from both camera and object motions. We demonstrate the algorithm by a series of experiments and simulations.
Pedestrian detection system based on stereo vision for mobile robot

This paper presents a novel Graphics Processing Unit (GPU)-based system for pedestrian detection with stereo vision in real images on mobile robot. The process of obtaining a dense disparity map on a GPU for real-time applications and the edge property of the scene to extract a region of interest (ROI) is designed. After extracting the histograms of the oriented gradients on the ROIs, a support vector machine (SVM) classifies them as pedestrian and non-pedestrian types. The system employs the recognition by components method, which compensates for the pose and articulation changes of pedestrians. In order to effectively track spatial pedestrian estimates over sequences, sub-windows in distinctive parts of human beings are used as measurements of the Kalman filter.
A Survey of Registered Dietitians’ Concern and Actions Regarding Climate Change in the United States

Dietary choices are a tool to reduce greenhouse gas emissions. While registered dietitians are on the front lines of food and nutrition recommendations, it is unclear how many are concerned with climate change and take action in practice in the United States. We explored concern about climate change among registered dietitians, and identified factors that may influence practice-related behaviors. Our study population included a random sample of all registered dietitians credentialed in the United States. Primary data were gathered using a cross-sectional survey. Of the 570 survey responses, 75% strongly agreed or agreed that climate change is an important issue while 34% strongly agreed or agreed that dietitians should play a major role in climate change mitigation strategies. Thirty-eight percent engaged in activities that promoted diet as a climate change mitigation strategy. Vegetarian (p = 0.002) and vegan dietitians (p = 0.007) were significantly more likely than non-vegetarian and non-vegan dietitians to engage in activities that promoted diet as a climate change mitigation strategy. Overall, concern for climate change among dietitians varied significantly by the region of the country in which the dietitian resided, and awareness that animal products are implicated in climate change. Registered dietitians in the United States are concerned with climate change. However, there is a discrepancy between concern and practice-based actions. These results suggest the need for educational and experiential opportunities connecting climate change mitigation to dietetics practice.