Indoor pollutants can have short- and long-term health effects, especially if exposure occurs during prenatal life or early childhood. read more This study describe the perceptions, knowledge, and practices of adults concerning indoor environmental pollution. Adults of 18 to 45 years of age were recruited in the department of Ille-et-Vilaine (Brittany-France) in 2019 through a stratified random draw in the waiting rooms of general practitioners (GPs) (n = 554) who completed a self-questionnaire. The 71% who had already heard of this type of pollution were older (p = 0.001), predominantly women (p = 0.007), not expecting a baby (p = 0.005), and had a higher knowledge score (p 80% of participants) (aeration during renovation) whereas others were insufficiently practiced ( less then 60% of participants) (paying attention to the composition of cosmetic products). Factors associated differed depending on the frequency of integration living in a couple and having a child for well implemented practices and educational level, knowledge level, and perception for those under implemented. Knowledge must be improved to modify perceptions and certain practices, making sure not to increase social inequalities in health. To solve the problem of dwell time management for multiple target tracking in Low Probability of Intercept (LPI) radar network, a Nash bargaining solution (NBS) dwell time allocation algorithm based on cooperative game theory is proposed. This algorithm can achieve the desired low interception performance by optimizing the allocation of the dwell time of each radar under the constraints of the given target detection performance, minimizing the total dwell time of radar network. By introducing two variables, dwell time and target allocation indicators, we decompose the dwell time and target allocation into two subproblems. Firstly, combining the Lagrange relaxation algorithm with the Newton iteration method, we derive the iterative formula for the dwell time of each radar. The dwell time allocation of the radars corresponding to each target is obtained. Secondly, we use the fixed Hungarian algorithm to determine the target allocation scheme based on the dwell time allocation results. Simulation results show that the proposed algorithm can effectively reduce the total dwell time of the radar network, and hence, improve the LPI performance.Neurorehabilitation for stroke is important for upper limb motor recovery. Conventional rehabilitation such as occupational therapy has been used, but novel technologies are expected to open new opportunities for better recovery. Virtual reality (VR) is a technology with a set of informatics that provides interactive environments to patients. VR can enhance neuroplasticity and recovery after a stroke by providing more intensive, repetitive, and engaging training due to several advantages, including (1) tasks with various difficulty levels for rehabilitation, (2) augmented real-time feedback, (3) more immersive and engaging experiences, (4) more standardized rehabilitation, and (5) safe simulation of real-world activities of daily living. In this comprehensive narrative review of the application of VR in motor rehabilitation after stroke, mainly for the upper limbs, we cover (1) the technologies used in VR rehabilitation, including sensors; (2) the clinical application of and evidence for VR in stroke rehabilitation; and (3) considerations for VR application in stroke rehabilitation. Meta-analyses for upper limb VR rehabilitation after stroke were identified by an online search of Ovid-MEDLINE, Ovid-EMBASE, the Cochrane Library, and KoreaMed. We expect that this review will provide insights into successful clinical applications or trials of VR for motor rehabilitation after stroke.Parkinson’s disease (PD) is a neurodegenerative disease and a multidisciplinary approach to rehabilitation has been suggested as the best clinical practice. However, very few studies have investigated the long-term effects of a multidisciplinary rehabilitation approach, particularly regarding whether this can slow the progression of PD. The purpose was to investigate the short- and long-term effect of a 2-week multidisciplinary rehabilitation regimen on the PD-related decline in health-related quality of life (HRQOL), mobility, and muscle function. Individuals with PD (IPD) participated in a 2-week inpatient multidisciplinary rehabilitation regimen that focused on improving HRQOL, mobility, and muscle function. Data from the primary outcome HRQOL (Parkinson’s Disease Questionnaire 39, PDQ-39), secondary outcomes handgrip strength, Timed-up and Go (TUG), Hospital Anxiety and Depression Scale (HADS), and Falls Efficacy Scale-International (FES-I) were compared at pre-visitation, before and after the 2-week regimen, and again at 4 and 10 months follow-up. In total, 224 patients with PD were included. There were short-term improvements in all outcomes. PDQ-39 was maintained at the same level as pre-visitation after 10 months follow-up. A 2-week multidisciplinary rehabilitation regimen improved short-term mobility, muscle function, and HRQOL in individuals with Parkinson’s disease. HRQOL was maintained after 10 months demonstrating long-term effects.This study aimed to investigate possible associations of the susceptibility to congenital heart defects (CHDs) with AXIN1 rs1805105, rs12921862 and rs370681 gene variants and haplotypes, and AXIN2 rs2240308 gene variant. Significant associations were identified for AXIN1 rs370681 and AXIN2 rs2240308 variants. AXIN1 rs370681 variant was significantly associated with decreased odds of CHDs (adjusted OR varying from 0.13 to 0.28 in codominant, dominant and recessive gene models), while the AXIN2 rs2240308 variant was associated with increased odds of CHD in the dominant model. The haplotype-based generalized linear model regression of AXIN1 rs1805105, rs12921862 and rs370681 variants revealed that C-C-C and C-C-T haplotypes significantly increased the risk of CHDs (p less then 0.05). No significant second order epistatic interactions were found between investigated variants (AXIN1 rs1805105, rs12921862, rs370681, and AXIN2 rs2240308). Our conclusion is that AXIN1 rs1805105, rs12921862, and rs370681 (C-C-C and C-C-T) haplotypes and AXIN2 rs2240308 contribute to CHDs susceptibility.