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BACKGROUND Hypertension has gained global significance and risk of cardiovascular disease, and adiposity is the most important of the conditions associated with and considered responsible for hypertension in children. Therefore, the present study aimed to determine whether indices of adiposity independently predicted blood pressure at multiple points in gender-specific groups. METHODS This was a cross-sectional study involving 10 randomly selected primary schools within the Ellisras Longitudinal Study, and involved 1816 adolescents (876 girls and 940 boys) aged 8 to 17 years. All the anthropometric indices and blood pressures (BP) were examined according to the International Society for the Advancement of Kinanthropometry protocol. RESULTS In an adjusted linear quantile regression analysis of boys, waist circumference (WC) was associated with BP across all multiple points of systolic blood pressure (SBP). Furthermore, the triceps skinfold site was associated with high SBP. click here In girls, body mass index (BMI) was significantly associated with SBP after adjustment for potential confounders. Other anthropometric indices of adiposity, including WC, biceps, and triceps skinfold sites were not associated with SBP. CONCLUSIONS The results of the present study suggest that in black South African children, variables such as WC and triceps skinfold site may provide stronger explanatory capacity to SBP variance and systolic hypertension risk in boys than other adiposity indices; whereas in girls, only WC and BMI predict diastolic blood pressure (DBP) and SBP, respectively.This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully parallel strategy associated with a hybrid bit format scheme (fixed-point and floating-point). Two hardware designs are proposed; the first one uses a single clock cycle processing architecture, and the other uses a pipeline scheme. The bit accuracy was tested by simulation with a nonlinear control system of a robotic manipulator. The area, throughput, and dynamic power consumption of the implemented hardware are used to validate and compare the results of this proposal. The results achieved allow the use of the proposed hardware in applications with high-throughput, low-power and ultra-low-latency requirements such as teleoperation of robot manipulators, tactile internet, or industry 4.0 automation, among others.Knee acoustic emissions provide information about joint health and loading in motion. As the reproducibility of knee acoustic emissions by vibroarthrography is yet unknown, we evaluated the intrasession and interday reliability of knee joint sounds. In 19 volunteers (25.6 ± 2.0 years, 11 female), knee joint sounds were recorded by two acoustic sensors (16,000 Hz; medial tibial plateau, patella). All participants performed four sets standing up/sitting down (five repetitions each). For measuring intrasession reliability, we used a washout phase of 30 min between the first three sets, and for interday reliability we used a washout phase of one week between sets 3 and 4. The mean amplitude (dB) and median power frequency (Hz, MPF) were analyzed for each set. Intraclass correlation coefficients (ICCs (2,1)), standard errors of measurement (SEMs), and coefficients of variability (CVs) were calculated. The intrasession ICCs ranged from 0.85 to 0.95 (tibia) and from 0.73 to 0.87 (patella). The corresponding SEMs for the amplitude were ≤1.44 dB (tibia) and ≤2.38 dB (patella); for the MPF, SEMs were ≤13.78 Hz (tibia) and ≤14.47 Hz (patella). The intrasession CVs were ≤0.06 (tibia) and ≤0.07 (patella) (p less then 0.05). The interday ICCs ranged from 0.24 to 0.33 (tibia) and from 0 to 0.82 (patella) for both the MPF and amplitude. The interday SEMs were ≤4.39 dB (tibia) and ≤6.85 dB (patella) for the amplitude and ≤35.39 Hz (tibia) and ≤15.64 Hz (patella) for the MPF. The CVs were ≤0.14 (tibia) and ≤0.08 (patella). Knee joint sounds were highly repeatable within a single session but yielded inconsistent results for the interday reliability.Duchenne muscular dystrophy (DMD) is a fatal X-linked muscle wasting disorder arising from mutations in the ~2.4 Mb dystrophin-encoding DMD gene. RNA-guided CRISPR-Cas9 nucleases (RGNs) are opening new DMD therapeutic routes whose bottlenecks include delivering sizable RGN complexes for assessing their effects on human genomes and testing ex vivo and in vivo DMD-correcting strategies. Here, high-capacity adenoviral vectors (HC-AdVs) encoding single or dual high-specificity RGNs with optimized components were investigated for permanently repairing defective DMD alleles either through exon 51-targeted indel formation or major mutational hotspot excision (>500 kb), respectively. Firstly, we establish that, at high doses, third-generation HC-AdVs lacking all viral genes are significantly less cytotoxic than second-generation adenoviral vectors deleted in E1 and E2A. Secondly, we demonstrate that genetically retargeted HC-AdVs can correct up to 42% ± 13% of defective DMD alleles in muscle cell populations through targeted removal of the major mutational hotspot, in which over 60% of frame-shifting large deletions locate. Both DMD gene repair strategies tested readily led to the detection of Becker-like dystrophins in unselected muscle cell populations, leading to the restoration of β-dystroglycan at the plasmalemma of differentiated muscle cells. Hence, HC-AdVs permit the effective assessment of DMD gene-editing tools and strategies in dystrophin-defective human cells while broadening the gamut of DMD-correcting agents.To satisfy an increasing demand to reconstruct an athlete’s motion for performance analysis, this paper proposes a new method for reconstructing the position and velocity in the context of ski jumping trajectories. Therefore, state-of-the-art wearable sensors, including an inertial measurement unit, a magnetometer, and a GPS logger are used. The method employs an extended Rauch-Tung-Striebel smoother with state constraints to estimate state information offline from recorded raw measurements. In comparison to the classic inertial navigation system and GPS integration solution, the proposed method includes additional geometric shape information of the ski jumping hill, which are modeled as soft constraints and embedded into the estimation framework to improve the position and velocity estimation accuracy. Results for both simulated measurement data and real measurement data demonstrate the effectiveness of the proposed method. Moreover, a comparison between jump lengths obtained from the proposed method and video recordings shows the relative root-mean-square error of the reconstructed jump length is below 1.