Miracle-dz/UniFAR-FTUs huggingface dataset:
The Mobile Phone Affinity Scale: Enhancement and Refinement

Background Existing instruments that assess individuals’ relationships with mobile phones tend to focus on negative constructs such as addiction or dependence, and appear to assume that high mobile phone use reflects pathology. Mobile phones can be beneficial for health behavior change, disease management, work productivity, and social connections, so there is a need for an instrument that provides a more balanced assessment of the various aspects of individuals’ relationships with mobile phones. Objective The purpose of this research was to develop, revise, and validate the Mobile Phone Affinity Scale, a multi-scale instrument designed to assess key factors associated with mobile phone use. Methods Participants (N=1058, mean age 33) were recruited from Amazon Mechanical Turk between March and April of 2016 to complete a survey that assessed participants’ mobile phone attitudes and use, anxious and depressive symptoms, and resilience. Results Confirmatory factor analysis supported a 6-factor model. The final measure consisted of 24 items, with 4 items on each of 6 factors: Connectedness, Productivity, Empowerment, Anxious Attachment, Addiction, and Continuous Use. The subscales demonstrated strong internal consistency (Cronbach alpha range=0.76-0.88, mean 0.83), and high item factor loadings (range=0.57-0.87, mean 0.75). Tests for validity further demonstrated support for the individual subscales. Conclusions Mobile phone affinity may have an important impact in the development and effectiveness of mobile health interventions, and continued research is needed to assess its predictive ability in health behavior change interventions delivered via mobile phones.
IMPLEMENTATION AND CONTROL OF INTEGRAL CYCLE CONTROLLER FOR RESISTANCE SPOT WELDING

The Resistance Spot Welding (RSW) process requires simultaneous application of high electrical current and appropriate pressure over short periods in order to keep the molten material inside the weld zone. Values of these parameters vary in function of the characteristics of the materials to be welded. The application of the electrical current is by means of two copper electrodes brought in contact with the welded parts while the required pressure is applied by means of pneumatic or hydraulic systems. This paper presents the simulation, design, and control of resistance welding system which is used for performing a welding process. The paper is discussed about two aspects. First, simulation of the concept of ICC used for the specific application of RSW. Secondly, the critical factor and method employed for the implementation of the controller. This paper also discuss about the implementation methodology of the RSW. The simulation for the RSW is carried out in PROTEUS software. Index Word: Constant Current Feedback, Integral Cycle Control (ICC), Resistance Spot Welding, Sequential Timer. --------------------------------------------------------------------***---------------------------------------------------------------------
A Real-Time Video Abstraction Technique for AR Content Synthesis on Android Platform

In this paper, we offer an efficient real-time video abstraction technique that enables interaction with the real-world environment using a smart device for combining augmented reality (AR) and virtual content. The conventional video abstraction technique is inappropriate for the real-time processing of AR content. Therefore, real-time video abstraction through the GPU approach is necessary to minimize the CPU processing of AR content. The methods other than the abstraction technique using the Open GL-ES shader have constraints regarding hardware and the dependency of AR content data. Consequently, this paper proposes a real-time video abstraction technique using the Open GL-ES shader. The proposed real-time video abstraction technique is a method for minimizing the disharmony between virtual and real-world content occurring on AR performing in the limited computing resources of a smart device. To do this, we performed research on video abstraction and applied three filtering algorithms (Sobel operator, Striped pattern-based toon, Non-boundary-based color quantization). In addition, we considered the applicability of AR content through real-time video abstraction experiments using adjusted and monitoring parameters.
Survival analysis of weekend emergency medical admissions

Background We previously reported weekend emergency admissions to have a higher mortality; we have now examined the time profile of deaths, by weekday or weekend admission, in all emergency medical patients admitted between 2002 and 2014. Methods We divided admissions by a weekday or weekend (After 17.00 Friday-Sunday) hospital arrival. We examined survival following an admission using Cox proportional hazard models and Kaplan-Meier time to event analysis. Results In total 82 368 admissions were recorded in 44, 628 patients. Weekend admissions had an increased mortality of 5.0% (95% CI 4.7, 5.4) compared with weekday admissions of 4.5% (95% CI 4.3, 4.7) ( P = 0.007). The univariate adjusted Odds Ratio (OR) of death for a weekend admission was significantly increased OR = 1.15 (95% CI 1.05, 1.24) ( P = 0.001). Mortality following an admission declined exponentially over time with a long tail, ∼25% of deaths occurred after day 28. Only 11.4% of deaths occurred on the weekend of the admission. Survival curves showed no mortality difference at 28 days ( P = 0.21) but a difference at 90 days ( P = 0.05). The higher mortality for a weekend admission was attributable to late deaths in the cohort with an extended stay; compared with weekday, these weekend admissions were more likely to be older and have greater co-morbidity. Conclusion Survival rates following a weekend or weekday admission were similar out to 28 days. The higher overall mortality for weekend admissions is due to divergence in survival between 28 and 90 days. Most deaths in weekend admissions occurred when the hospital was fully staffed.
Evaluation of Entropy-based Edge Detector Methods for Human Object

In the field of image processing, edges of an image are important as they characterize boundaries. To reduce the volume of data and refine insignificant information without damaging the structural properties of an image, a process called Image Edge Detection may be performed. Understanding algorithms of edge detection is therefore imperative because it is essential in image processing, particularly in object detection. This paper aimed to recognize this importance to detect human object in particular by conducting an experiment , with emphasis on entropy. Similarly, a comparison of the entropy-based edge detector was done based on the different edge detection techniques such as Prewitt, Robert, Sobel, Canny, and LOG operators. Result show that Canny edge detector exhibits a better performance as compared to the other edge detectors to detect the human object in the image. This is derived from the detectors’ characteristics including their adaptive nature, sharp edge detection, and performance as applied in noisy image.
Grey matter volume and thickness abnormalities in young people with a history of childhood abuse

Background Childhood abuse is associated with abnormalities in brain structure and function. Few studies have investigated abuse-related brain abnormalities in medication-naïve, drug-free youth that also controlled for psychiatric comorbidities by inclusion of a psychiatric control group, which is crucial to disentangle the effects of abuse from those associated with the psychiatric conditions. Methods Cortical volume (CV), cortical thickness (CT) and surface area (SA) were measured in 22 age- and gender-matched medication-naïve youth (aged 13–20) exposed to childhood abuse, 19 psychiatric controls matched for psychiatric diagnoses and 27 healthy controls. Both region-of-interest (ROI) and whole-brain analyses were conducted. Results For the ROI analysis, the childhood abuse group compared with healthy controls only, had significantly reduced CV in bilateral cerebellum and reduced CT in left insula and right lateral orbitofrontal cortex (OFC). At the whole-brain level, relative to healthy controls, the childhood abuse group showed significantly reduced CV in left lingual, pericalcarine, precuneus and superior parietal gyri, and reduced CT in left pre-/postcentral and paracentral regions, which furthermore correlated with greater abuse severity. They also had increased CV in left inferior and middle temporal gyri relative to healthy controls. Abnormalities in the precuneus, temporal and precentral regions were abuse-specific relative to psychiatric controls, albeit at a more lenient level. Groups did not differ in SA. Conclusions Childhood abuse is associated with widespread structural abnormalities in OFC–insular, cerebellar, occipital, parietal and temporal regions, which likely underlie the abnormal affective, motivational and cognitive functions typically observed in this population.
From the Experience of Interactivity and Entertainment to Lower Intention to Smoke: A Randomized Controlled Trial and Path Analysis of a Web-Based Smoking Prevention Program for Adolescents

Background Web-based programs for smoking prevention are being increasingly used with some success among adolescents. However, little is known about the mechanisms that link the experience of such programs to intended nicotine or tobacco control outcomes. Objective Based on the experiential learning theory and extended elaboration likelihood model, this study aimed to evaluate the impact of a Web-based intervention, A Smoking Prevention Interactive Experience (ASPIRE), on adolescents’ intention to smoke, while considering the experience of interactivity and entertainment as predictors of reduced intention to smoke, under a transitional user experience model. Methods A total of 101 adolescents were recruited from after-school programs, provided consent, screened, and randomized in a single-blinded format to 1 of 2 conditions: the full ASPIRE program as the experimental condition (n=50) or an online , text-based version of ASPIRE as the control condition (n=51). Data were collected at baseline and immediate follow-up. Repeated-measures mixed-effects models and path analyses were conducted. Results A total of 82 participants completed the study and were included in the analysis. Participants in the experimental condition were more likely to show a decrease in their intention to smoke than those in the control condition (beta=−0.18, P=.008). Perceived interactivity (beta=−0.27, P=.004) and entertainment (beta=−0.20, P=.04) were each associated with a decrease in intention to smoke independently. Results of path analyses indicated that perceived interactivity and perceived entertainment mediated the relationship between ASPIRE use and emotional involvement. Furthermore, perceived presence mediated the relationship between perceived interactivity and emotional involvement. There was a direct relationship between perceived entertainment and emotional involvement. Emotional involvement predicted a decrease in intention to smoke (beta=−0.16, P=.04). Conclusions Adolescents’ experience of interactivity and entertainment contributed to the expected outcome of lower intention to smoke. Also, emphasis needs to be placed on the emotional experience during Web-based interventions in order to maximize reductions in smoking intentions. Going beyond mere evaluation of the effectiveness of a Web-based smoking prevention program, this study contributes to the understanding of adolescents’ psychological experience and its effect on their intention to smoke. With the results of this study, researchers can work to (1) enhance the experience of interactivity and entertainment and (2) amplify concepts of media effects (eg, presence and emotional involvement) in order to better reach health behavior outcomes. Trial Registration Clinicaltrials.gov NCT02469779; https://clinicaltrials.gov/ct2/show/NCT02469779 (Archived by WebCite at http://www.webcitation.org/6nxyZVOf0)
Destabilizing Terrorist Networks

Most people have at least an intuitive understanding of hierarchies, how they work, and how to affect their behavior. However, covert organizations, such as terrorist organizations, have network structures that are distinct from those in typical hierarchical organizations. Their structure is distinct from the organizations that most people in western culture are used to dealing with. In particular, they tend to be more cellular and distributed. As such, most people do not have an intuitive understanding of how they work and instead seek to think of them as hierarchies. However, analysis reveals that trying to destabilize a cellular distributed network using tactics designed for hierarchies is likely to be ineffective. A secondary problem is that despite the vast quantities of information on the size, shape and structure of these networks, such, information is incomplete and possible erroneous. What is needed is a set of tools and an approach to assessing destabilization strategies in a decision context that takes these difficulties in to account and provides analysts with guidance in assessing alternative destabilization tactics. Such an approach is forwarded in this paper. In addition, initial lessons learned are discussed. The particular approach is extensible and scales well to groups composed of 1000’s of members.
Unconjugated Bilirubin Exposure Impairs Hippocampal Long-Term Synaptic Plasticity

Background Jaundice is one of the most common problems encountered in newborn infants, due to immaturity of hepatic conjugation and transport processes for bilirubin. Although the majority of neonatal jaundice is benign, some neonates with severe hyperbilirubinemia develop bilirubin encephalopathy or kernicterus. Accumulation of unconjugated bilirubin (UCB) in selected brain regions may result in temporary or permanent impairments of auditory, motor, or cognitive function; however, the molecular mechanisms by which UCB elicits such neurotoxicity are still poorly understood. The present study is undertaken to investigate whether prolonged exposure of rat organotypic hippocampal slice cultures to UCB alters the induction of long-term synaptic plasticity. Methodology/Principal Findings Using electrophysiological recording techniques, we find that exposure of hippocampal slice cultures to clinically relevant concentrations of UCB for 24 or 48 h results in an impairment of CA1 long-term potentiation (LTP) and long-term depression (LTD) induction in a time- and concentration-dependent manner. Hippocampal slice cultures stimulated with UCB show no changes in the secretion profiles of the pro-inflammatory cytokines, interleukin-1β and tumor necrosis factor-α, or the propidium ioide uptake. UCB treatment produced a significant decrease in the levels of NR1, NR2A and NR2B subunits of N-methyl-D-aspartate (NMDA) receptors through a calpain-mediated proteolytic cleavage mechanism. Pretreatment of the hippocampal slice cultures with NMDA receptor antagonist or calpain inhibitors effectively prevented the UCB-induced impairment of LTP and LTD. Conclusion/Significance Our results indicate that the proteolytic cleavage of NMDA receptor subunits by calpain may play a critical role in mediating the UCB-induced impairment of long-term synaptic plasticity in the hippocampus. These observations provide new insights into the molecular mechanisms underlying UCB-induced impairment of hippocampal synaptic plasticity which, in turn, might provide opportunities for the development of novel therapeutic strategies that targets these pathways for treatment.
Exploring validation of a graphic symbol questionnaire to measure participation experiences of youth in activity settings

Abstract Participation has a subjective and private dimension, and so it is important to hear directly from youth about their experiences in various activity settings, the places where they “do things” and interact with others. To meet this need, our team developed the Self-Reported Experiences of Activity Settings (SEAS) measure, which demonstrated good-to-excellent measurement properties. To address the needs of youth who could benefit from graphic symbol support, the SEAS-PCSTM,1 was created. The purpose of this paper is to describe the development of SEAS-PCS and the preliminary study that explores the equivalency of the SEAS and SEAS-PCS. The SEAS and SEAS-PCS were compared in terms of the equivalency of meaning of stimulus items by 11 professionals and five adults who used augmentative and alternative communication, were familiar with PCS, and were fluent readers. Out of 22 items, 68% were rated as highly similar on a 5-point scale (M = 4.14; SD = .70; mdn = 4; range: 2.81–5.00). Subsequently, the 32% of the SEAS-PCS items that were rated below 4 were modified based on the participants’ specific comments. Further work is required to validate the SEAS-PCS. The next step could involve exploring the views of youth who use AAC.
Impact of Marijuana on Response Inhibition: An fMRI Study in Young Adults

Rationale: Marijuana use in adolescence is prevalent and increasing. Understanding the neural correlates of the impact of this use is critical for policy making and for youth awareness. Objectives The effects of marijuana use on response inhibition were investigated in 19–21-year-olds using functional magnetic resonance imaging (fMRI). Methods: Participants were members of the Ottawa Prenatal Prospective Study, a longitudinal study that collected a unique body of information on participants from infancy to young adulthood including: prenatal drug history, detailed cognitive/behavioral performance, and current and past drug use. This information allowed for the control of an unparalleled number of potentially confounding variables including: prenatal marijuana, nicotine, alcohol, and caffeine exposure and offspring alcohol, marijuana, and nicotine use. Ten marijuana users and 14 nonusers that served as controls performed a Go/No-Go task while fMRI blood oxygen level-dependent response was examined. Results: Despite similar task performance, there was a positive relationship between amount of marijuana smoked and activation in right thalamus, premotor cortex and middle frontal gyrus. These regions form part of the neural network responsible for inhibition control. There was also a positive dose dependent relationship with marijuana and activation in inferior parietal lobe and precuneus, also parts of response inhibition pathways. Conclusions: These results suggest a dose dependent alteration in neural functioning during response inhibition after controlling for other prenatal and current drug use. These alterations may be necessary in order to compensate for neural changes in response inhibition circuits caused by long term marijuana use that began during adolescence/young adulthood.
Xrn2 accelerates termination by RNA polymerase II, which is underpinned by CPSF73 activity

In this study, Eaton et al. use a new gene-editing approach to delineate the mechanism by which RNA polymerase II terminates. They generated human cell lines from which the 5′-to-3′ exoribonuclease Xrn2 or the poly(A) signal endoribonuclease CPSF73 can be rapidly controlled and show that efficient termination on most protein-coding genes involves CPSF73-mediated RNA cleavage and cotranscriptional degradation of polymerase-associated RNA by Xrn2.
A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology

Background Design processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry. Objective We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk. Methods We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes. Results We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems. Conclusions We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly.
A deep convolutional neural network for recognizing foods

Controlling the food intake is an efficient way that each person can undertake to tackle the obesity problem in countries worldwide. This is achievable by developing a smartphone application that is able to recognize foods and compute their calories. State-of-art methods are chiefly based on hand-crafted feature extraction methods such as HOG and Gabor. Recent advances in large-scale object recognition datasets such as ImageNet have revealed that deep Convolutional Neural Networks (CNN) possess more representation power than the hand-crafted features. The main challenge with CNNs is to find the appropriate architecture for each problem. In this paper, we propose a deep CNN which consists of 769; 988 parameters. Our experiments show that the proposed CNN outperforms the state-of-art methods and improves the best result of traditional methods 17%. Moreover, using an ensemble of two CNNs that have been trained two different times, we are able to improve the classification performance 21:5%.
Moving cast shadow resistant for foreground segmentation based on shadow properties analysis

Moving object detection is the fundamental task in machine vision applications. However, moving cast shadows detection is one of the major concerns for accurate video segmentation. Since detected moving object areas are often contain shadow points, errors in measurements, localization, segmentation, classification and tracking may arise from this. A novel shadow elimination algorithm is proposed in this paper. A set of suspected moving object area are detected by the adaptive Gaussian approach. A model is established based on shadow optical properties analysis. And shadow regions are discriminated from the set of moving pixels by using the properties of brightness, chromaticity and texture in sequence.