Miracle-dz/UniFAR-FTUs huggingface dataset:
Falls among Middle-Aged Women in the Women's Interagency HIV Study

Background To determine the frequency and risk factors for falls among middle-aged HIV+ and HIV- women in the Women's Interagency HIV Study (WIHS). Methods We quantified self-report of any and multiple (≥2) falls in the prior 6 months among 1,412 HIV+ and 650 HIV- women with mean age 48 years. Logistic regression was used to evaluate associations of demographics, behavioural factors, comorbid conditions and medications with odds of any fall (versus none) and multiple falls (versus ≤1 fall). Results At least one fall was reported in 263 HIV+ (19%) versus 119 HIV- (18%) women, and ≥2 falls reported in 133 HIV+ (9%) versus 65 HIV- (10%) women. HIV infection was not associated with falls in multivariate analyses. Factors independently associated with any fall included age (adjusted odds ratio [aOR] 1.71, 95% CI 1.17, 2.49 age 50-59 versus <39 years; aOR 2.26, 95% CI 1.38, 3.71 age ≥60 versus <39), current marijuana use (aOR 2.19, 95% CI 1.53, 3.13) depressive symptoms (aOR 1.57, 95% CI 1.21, 2.05 for Center for Epidemiology Studies Depression score ≥16), subjective cognitive complaints (aOR 2.19, 95% CI 1.56, 3.08), neuropathy (aOR 1.59, 95% CI 1.19, 2.13), obesity (aOR 1.39, 95% CI 1.08, 1.80), number of central nervous system active agents (aOR 2.98, 95% CI 1.90, 4.68 for ≥3 agents versus 0) and WIHS site. Factors associated with ≥2 falls included age, marijuana use, number of central nervous system active agents, subjective cognitive complaints, depressive symptoms, neuropathy and study site. Conclusions Falls were associated with factors affecting cognition, but not HIV status in this large cohort of women. Longitudinal studies are needed to determine the incidence and consequences of falls by HIV status as women age.
Subspace Clustering on Static Datasets and Dynamic Data Streams Using Bio­-Inspired Algorithms. (Subspace Clustering sur Jeux de Données Statiques et sur Streams Dynamiques à l'Aide d'Algorithmes Bio-Inspirés)

Une tache importante qui a ete etudiee dans le contexte de donnees a forte dimensionnalite est la tache connue sous le nom de subspace clustering. Le subspace clustering est generalement reconnu comme etant plus complique que le clustering standard, etant donne que cette tache vise a detecter des groupes d’objets similaires entre eux (clusters), et qu’en meme temps elle vise a trouver les sous-espaces ou apparaissent ces similitudes. Le subspace clustering, ainsi que le clustering traditionnel ont ete recemment etendus au traitement de flux de donnees en mettant a jour les modeles de clustering de facon incrementale. Les differents algorithmes qui ont ete proposes dans la litterature, reposent sur des bases algorithmiques tres differentes. Parmi ces approches, les algorithmes evolutifs ont ete sous-explores, meme si ces techniques se sont averees tres utiles pour traiter d’autres problemes NP-difficiles. L’objectif de cette these a ete de tirer parti des nouvelles connaissances issues de l’evolution afin de concevoir des algorithmes evolutifs qui traitent le probleme du subspace clustering sur des jeux de donnees statiques ainsi que sur des flux de donnees dynamiques. Chameleoclust, le premier algorithme developpe au cours de ce projet, tire partie du grand degre de liberte fourni par des elements bio-inspires tels qu’un genome de longueur variable, l’existence d’elements fonctionnels et non fonctionnels et des operateurs de mutation incluant des rearrangements chromosomiques. KymeroClust, le deuxieme algorithme concu dans cette these, est un algorithme de k-medianes qui repose sur un mecanisme evolutif important: la duplication et la divergence des genes. SubMorphoStream, le dernier algorithme developpe ici, aborde le probleme du subspace clustering sur des flux de donnees dynamiques. Cet algorithme repose sur deux mecanismes qui jouent un role clef dans l’adaptation rapide des bacteries a des environnements changeants: l’amplification de genes et l’absorption de materiel genetique externe. Ces algorithmes ont ete compares aux principales techniques de l’etat de l’art, et ont obtenu des resultats competitifs. En outre, deux applications appelees EvoWave et EvoMove ont ete developpes pour evaluer la capacite de ces algorithmes a resoudre des problemes reels. EvoWave est une application d’analyse de signaux Wi-Fi pour detecter des contextes differents. EvoMove est un compagnon musical artificiel qui produit des sons bases sur le clustering des mouvements d’un danseur, decrits par des donnees provenant de capteurs de deplacements.
Expression of Inducible Nitric Oxide Synthase Is Increased in Acute Myeloid Leukaemia

Significant activity of inducible nitric oxide synthase (iNOS) has been reported in tumour cells, including chronic lymphoid leukaemic cells. In this study, we analysed the expression of iNOS in 15 untreated patients with acute myeloid leukaemia (AML) and in 7 normal controls. Using flow cytometry and immunocytochemistry, we demonstrated that patients with AML had a high expression of iNOS when compared to controls. There was no correlation between the expression of iNOS and the expression of p53 and K, H, and N-ras mutation and expression, suggesting that the high expression of iNOS is independent of these proteins and could be the result of transcription factors expressed in AML.
3D prompt gamma imaging for proton beam range verification

We tested the ability of a single Compton camera (CC) to produce 3-dimensional (3D) images of prompt gammas (PGs) emitted during the irradiation of a tissue-equivalent plastic phantom with proton pencil beams for clinical doses delivered at clinical dose rates. PG measurements were made with a small prototype CC placed at three different locations along the proton beam path. We evaluated the ability of the CC to produce images at each location for two clinical scenarios: (1) the delivery of a single 2 Gy pencil beam from a hypo-fractionated treatment (~9 × 108 protons), and (2) a single pencil beam from a standard treatment (~1 × 108 protons). Additionally, the data measured at each location were combined to simulate measurements with a larger scale, clinical CC and its ability to image shifts in the Bragg peak (BP) range for both clinical scenarios. With our prototype CC, the location of the distal end of the BP could be seen with the CC placed up to 4 cm proximal or distal to the BP distal falloff. Using the data from the simulated full scale clinical CC, 3D images of the PG emission were produced with the delivery of as few as 1 × 108 protons, and shifts in the proton beam range as small as 2 mm could be detected for delivery of a 2 Gy spot. From these results we conclude that 3D PG imaging for proton range verification under clinical beam delivery conditions is possible with a single CC.
Nonmuscle myosin IIB regulates epicardial integrity and epicardium-derived mesenchymal cell maturation

ABSTRACT Nonmuscle myosin IIB (NMIIB; heavy chain encoded by MYH10) is essential for cardiac myocyte cytokinesis. The role of NMIIB in other cardiac cells is not known. Here, we show that NMIIB is required in epicardial formation and functions to support myocardial proliferation and coronary vessel development. Ablation of NMIIB in epicardial cells results in disruption of epicardial integrity with a loss of E-cadherin at cell–cell junctions and a focal detachment of epicardial cells from the myocardium. NMIIB-knockout and blebbistatin-treated epicardial explants demonstrate impaired mesenchymal cell maturation during epicardial epithelial–mesenchymal transition. This is manifested by an impaired invasion of collagen gels by the epicardium-derived mesenchymal cells and the reorganization of the cytoskeletal structure. Although there is a marked decrease in the expression of mesenchymal genes, there is no change in Snail (also known as Snai1) or E-cadherin expression. Studies from epicardium-specific NMIIB-knockout mice confirm the importance of NMIIB for epicardial integrity and epicardial functions in promoting cardiac myocyte proliferation and coronary vessel formation during heart development. Our findings provide a novel mechanism linking epicardial formation and epicardial function to the activity of the cytoplasmic motor protein NMIIB. Highlighted Article: The cytoplasmic motor protein nonmuscle myosin IIB is essential for epicardial development. This function of nonmuscle myosin IIB is critical in the regulation of myocardial proliferation and coronary vessel formation.
Drought-induced shoot dieback starts with massive root xylem embolism and variable depletion of nonstructural carbohydrates in seedlings of two tree species.

Combining hydraulic- and carbon-related measurements helps to understand drought-induced plant mortality. Here, we investigated the role that plant respiration (R) plays in determining carbon budgets under drought. We measured the hydraulic conductivity of stems and roots, and gas exchange and nonstructural carbohydrate (NSC) concentrations of leaves, stems and roots of seedlings of two resprouting species exposed to drought or well-watered conditions: Ulmus minor (riparian tree) and Quercus ilex (dryland tree). With increasing water stress (occurring more rapidly in larger U. minor), declines in leaf, stem and root R were less pronounced than that in leaf net photosynthetic CO2 uptake (Pn ). Daytime whole-plant carbon gain was negative below -4 and -6 MPa midday xylem water potential in U. minor and Q. ilex, respectively. Relative to controls, seedlings exhibiting shoot dieback suffered c. 80% loss of hydraulic conductivity in both species, and reductions in NSC concentrations in U. minor. Higher drought-induced depletion of NSC reserves in U. minor was related to higher plant R, faster stomatal closure, and premature leaf-shedding. Differences in drought resistance relied on the ability to maintain hydraulic conductivity during drought, rather than tolerating conductivity loss. Root hydraulic failure elicited shoot dieback and precluded resprouting without root NSC reserves being apparently limiting for R.
IP mobility management using software defined networking: A review

Several smart IoT services are stalled with the absence of an efficient IP mobility framework to interconnect moving terminals in globe, extend indoor smart services, and provide session continuity for instant data transfer in real time cogitative and multimedia applications with negligible latency, efficient bandwidth utilization, improved reliability, and least power consumption. Despite the efforts exhausted by vendors, institutes, and researchers to improve existing standards, still efficient real time interactions and data transfer across moving objects are not achievable with existing standard hierarchical routing principles. This paper reviews the evolution of IP mobility and the severe challenges hindering global mobility in real 4G LTE deployments. Software Defined Networking (SDN) with its logical centralized control plane attracts the focus of the researchers to directly influence decision during real time motion. Some SDN researchers propose attractive ideas to enhance mobility performance in real deployments with seamless expansion cross providers. Preservative researchers fear performance degradation as the controller represents a single point of failure. Other researchers over simplify challenges in mobility and provide non-feasible solutions. This paper analyzes these efforts and complimentary solutions to provides a realistic conclusion on how SDN can participate in IoT global mobility.
Sympathetic arousal as a marker of chronicity in childhood stuttering

ABSTRACT Purpose: This study investigated whether sympathetic activity during a stressful speaking task was an early marker for stuttering chronicity. Method: Participants were 9 children with persisting stuttering, 23 children who recovered, and 17 children who do not stutter. Participants performed a stress-inducing picture-naming task and skin conductance was measured across three time points. Results: Findings indicated that at the initial time point, children with persisting stuttering exhibited higher sympathetic arousal during the stressful speaking task than children whose stuttering recovered. Conclusions: Findings are taken to suggest that sympathetic activity may be an early marker of heightened risk for chronic stuttering.
IFN Regulatory Factor 3 Balances Th1 and T Follicular Helper Immunity during Nonlethal Blood-Stage Plasmodium Infection

Differentiation of CD4+ Th cells is critical for immunity to malaria. Several innate immune signaling pathways have been implicated in the detection of blood-stage Plasmodium parasites, yet their influence over Th cell immunity remains unclear. In this study, we used Plasmodium-reactive TCR transgenic CD4+ T cells, termed PbTII cells, during nonlethal P. chabaudi chabaudi AS and P. yoelii 17XNL infection in mice, to examine Th cell development in vivo. We found no role for caspase1/11, stimulator of IFN genes, or mitochondrial antiviral-signaling protein, and only modest roles for MyD88 and TRIF-dependent signaling in controlling PbTII cell expansion. In contrast, IFN regulatory factor 3 (IRF3) was important for supporting PbTII expansion, promoting Th1 over T follicular helper (Tfh) differentiation, and controlling parasites during the first week of infection. IRF3 was not required for early priming by conventional dendritic cells, but was essential for promoting CXCL9 and MHC class II expression by inflammatory monocytes that supported PbTII responses in the spleen. Thereafter, IRF3-deficiency boosted Tfh responses, germinal center B cell and memory B cell development, parasite-specific Ab production, and resolution of infection. We also noted a B cell–intrinsic role for IRF3 in regulating humoral immune responses. Thus, we revealed roles for IRF3 in balancing Th1- and Tfh-dependent immunity during nonlethal infection with blood-stage Plasmodium parasites.
Effects of a Tablet Computer on Self-care, Quality of Life, and Knowledge: A Randomized Clinical Trial

Background: Conflicting results have been reported for telemonitoring in patients with heart failure (HF). We wanted to evaluate whether patients using a tablet computer aimed at improving self-care behavior could do so and also whether it affects quality of life and health-related quality of life, disease knowledge, and in-hospital days. Methods and Results: Patients with HF (n = 82) were randomized to the intervention group (IG) with a tablet computer (giving information and advice) or the control group (CG) that was subject to standard care. Study was completed by 72 patients, with a mean (SD) age of 75 (8) years, 68% male, and 74% NYHA class III. Self-care behavior measured with the 9-item European Heart Failure Self-Care Behaviour Scale, health related quality of life measured by the Kansas City Cardiomyopathy Questionnaire, quality of life measured by the Swedish version of the Health Survey, knowledge measured by the Dutch Heart Failure Knowledge Scale, days in hospital, and adherence were analyzed. The IG displayed better 9-item European Heart Failure Self-Care Behaviour Scale score (median IG, 16.5 [interquartile range {IQR}, 12–22], vs median CG, 23.5 [IQR, 18.8–30.0]; P < .05) and improved health related quality of life (median IG, 72.7 [IQR, 50.8–87.9], vs median CG, 51.8 [IQR, 40.9–62.8]; P < .05). A significant difference in knowledge was seen, with an 11% increase in IG and a 1% decrease in CG (P < .05), as well as a reduction in hospital days in IG by 2.7 days per patient (relative risk, 0.72; 95% confidence interval, 0.61–0.84; P < .05). Conclusion: The tablet computer significantly improved self-care behavior and health related quality of life, increased HF knowledge, and reduced hospital days.
Multi-view face detection using Normalized Pixel Difference feature

The initial phase in an automatic facial analysis is face detection, which has been concentrated in the course of recent decades. It is very challenging to recognize a face from an image due to illumination, variations in pose, occlusion, scaling and facial expression. In our work, we propose a methodology to detect a face with arbitrary pose variations. First, a Normalized Pixel Difference (NPD) feature is calculated from the face image. Second, the optimal subset of NPD features and their combinations are refined via Deep Quadratic Tree (DQT). In order to learn the NPD feature based deep quadratic trees, Discrete Adaboost classifier is adopted. The experimental results on Labeled Faces in the Wild (LFW) face dataset demonstrate that our framework performs better than the previous methods in detecting multi-view faces.
The moderator effect of commitment on the relations between satisfaction and motivation in Special Employment Centres

BACKGROUND Little is known about the relation between satisfaction, commitment and motivation among employees with mild intellectual disabilities. The present research analyses the moderated effect of commitment on the relation between satisfaction of employees with intellectual disabilities and their motivation. METHOD Employees with legally recognized intellectual disabilities, following the Spanish law, answered a questionnaire. The present authors examined bivariate relations across all variables in the model. Subsequently, a moderator model was tested, using the Johnson-Neyman and the pick-a-point approximation. RESULT There was a direct effect between employees' satisfaction and motivation (b = 2.4621; p < .0001). Commitment had a moderator effect on this relation (b = [-3.36 to -0.30]; p < .001), especially for those employees with lower levels of commitment. CONCLUSIONS Our research focuses on the antecedents of work motivation of employees with mild intellectual disabilities as full employees. So, our results help HR managers to increase employees' motivational levels, as one of the main objectives of healthy organizations.
An Internet of things and cloud-based approach for energy consumption evaluation and analysis for a product

Energy consumption evaluation and analysis (ECEA) of a product entire life cycle is a key issue for realising green and sustainable manufacturing. In this paper, an Internet-of-things (IoT) and cloud-based novel approach for product ECEA is proposed in which the IoT technologies are employed for real-time and dynamic collection of energy consumption-related data, and various ECEA functions are developed and encapsulated into services which are managed in a cloud. An experimental bench and a cloud-based software system are developed, and a case study is provided to test and illustrate the effectiveness of the approach in a product’s design and manufacturing processes.
The effects of work factors on nurses’ job satisfaction, quality of care and turnover intentions in oncology

AIMS We examined the effects of perceived supervisor support, value congruence and hospital nurse staffing on nurses' job satisfaction through the satisfaction of the three psychological needs for autonomy, competence and relatedness. Then, we examined the links between job satisfaction and quality of care as well as turnover intentions from the workplace. BACKGROUND There is growing interest in the relationships between work factors and nurses' job satisfaction. However, minimal research has investigated the effects of perceived supervisor support, value congruence and staffing on nurses' job satisfaction and the psychological mechanisms by which these factors lead to positive outcomes. DESIGN A cross-sectional questionnaire was distributed in 11 oncology units between September 2015 - February 2016. METHOD Data were collected from a sample of 144 French nurses who completed measures of perceived supervisor support, value congruence, staffing adequacy, psychological need satisfaction, job satisfaction, quality of care and turnover intentions. RESULTS The hypothesized model was tested with path analyses. Results revealed that psychological need satisfaction partially mediated the effects of perceived supervisor support, value congruence and hospital nurse staffing on job satisfaction. Moreover, job satisfaction was positively associated with quality of care and negatively linked to turnover intentions. CONCLUSION Overall, these findings provide insight into the influence of perceived supervisor support, value congruence and staffing on nurses' attitudes and behaviours.
Gasoline-related injuries and fatalities in the United States, 1995-2014

ABSTRACT This descriptive study examines twenty years of gasoline-related fatalities and emergency department treated injuries in the United States, based on data from the US Consumer Product Safety Commission. Thermal burns consistently accounted for the majority (56%) of gasoline-related injuries and for most (82%) gasoline-related deaths, and were commonly (57–71%) associated with the use of gasoline as an accelerant. Poisoning accounted for 13% of injuries and 17% of deaths. The primary poisoning injury pattern was ingestion; the primary fatality pattern was inhalation, with about half of those associated with deliberate abuse. The estimated number of ingestions decreased from 60 to 23% of poisoning-related injuries, while injuries associated with inhalation abuse increased from 6 to 23%. Chemical burns and dermatitis were less represented in the injury data and were primarily associated with gasoline spills or splashes. Gasoline cans reportedly ignited or exploded in about 5% of thermal burn injuries and fatalities. While mandatory requirements for child resistant closures on gasoline cans (a primary intervention) have potentially impacted poisonings, the use of flame mitigation devices to address thermal injuries, if successful, would be a secondary intervention, and could address only a small percentage (about 5%) of injuries and deaths.
Fast vanishing point detection method based on road border region estimation

The vanishing point is the converging point at which the road boundaries extend to the distance. It can be used to estimate the road region in a complicated environment. As the vanishing point detection algorithms for the unstructured road often take long time and they could not adapt to the image with complex environment of the road, in this study, the authors propose a vanishing point estimation method based on road boundaries region estimation. This method uses the boundary direction of the voting points in the border region to estimate the vanishing point by the line-soft-voting based on maximum weight. This method has fast calculation speed, and it can overcome the influence of the shadow and the complex environment on the surface of the road in many cases.