Estimation of temporal gait parameters using Bayesian models on acceleration signals

The purpose of this study is to develop a system capable of performing calculation of temporal gait parameters using two low-cost wireless accelerometers and artificial intelligence-based techniques as part of a larger research project for conducting human gait analysis. Ten healthy subjects of different ages participated in this study and performed controlled walking tests. Two wireless accelerometers were placed on their ankles. Raw acceleration signals were processed in order to obtain gait patterns from characteristic peaks related to steps. A Bayesian model was implemented to classify the characteristic peaks into steps or nonsteps. The acceleration signals were segmented based on gait events, such as heel strike and toe-off, of actual steps. Temporal gait parameters, such as cadence, ambulation time, step time, gait cycle time, stance and swing phase time, simple and double support time, were estimated from segmented acceleration signals. Gait data-sets were divided into two groups of ages to test Bayesian models in order to classify the characteristic peaks. The mean error obtained from calculating the temporal gait parameters was 4.6%. Bayesian models are useful techniques that can be applied to classification of gait data of subjects at different ages with promising results     

琥珀酸索利那新片治疗膀胱过度活动症的效果分析

目的:观察琥珀酸索利那新片治疗膀胱过度活动症的临床效果。方法:回顾性分析我科收治的膀胱过度活动症患者共90例,所有患者均符合由中华医学会泌尿外科分会尿控学组制定的《膀胱过度活动症临床指导原则》。其中43例患者采用酒石酸托特罗定片治疗并设为对照组,47例患者采用琥珀酸索利那新片治疗并设为观察组,对比两组患者用药前后排尿症状和尿动力学参数变化、膀胱过度活动症症状评分表(OABSS评分)和前列腺症状评分(IPSS评分)变化以及不良反应发生率对比情况。结果:观察组患者用药后平均24 h尿急次数、平均24 h排尿次数均明显低于对照组,最大尿流率(Qmax)、初始尿意容量(FDV)、最大膀胱压容量(MCBC)均明显高于对照组,两组患者以上指标相比较,差异均有显著性(P0.05);两组患者用药后OABSS评分和IPSS评分均有所下降,但是两组相比,差异不具有显著性(P0.05);3两组患者用药后均有不同程度的不良反应,其中口干症状患者比例具有差异性(P0.05)。结论:琥珀酸索利那新片治疗膀胱过度活动症疗效确切,安全性高。     

钙素对彩叶玉簪光合作用和保护酶活性的影响

该文以彩叶玉簪为材料,研究了不同钙素水平对玉簪叶片光合作用和保护酶活性的影响。结果表明:随着钙素水平的提高,彩叶玉簪叶片的净光合速率(Pn)、气孔导度(Gs)、胞间CO_2浓度(Ci)、蒸腾速率(Tr)和最大光化学效率(F_v/F_m)均呈单峰曲线,最高峰值出现在Ca~(2+)90 mg·L~(-1)时;电子传递速率(ETR)的变化也呈单峰曲线,峰值出现在Ca~(2+)50 mg·L~(-1)时;初始荧光(F_0)和最大荧光(F_m)值在0~360 mg·L~(-1)钙素水平下呈先升高后下降再升高的趋势,最大值均出现在90 mg·L~(-1)时;Pn和Gs值的变化与Ci值成正相关。同时叶片中过氧化物酶(POD)、过氧化氢酶(CAT)的活性及丙二醛(MDA)、可溶性蛋白质(SP)含量均表现为单谷曲线,在Ca~(2+)90 mg·L~(-1)时达最小值。超氧化物歧化酶(SOD)活性呈现持续下降趋势。综上所述,彩叶玉簪Pn下降主要由气孔引起,叶面喷施90 mg·L~(-1)的Ca~(2+)可增强彩叶玉簪光合作用,降低保护酶活性。     

塔里木河下游多枝柽柳幼苗生长和光合生理指标对输水漫溢的响应特征

以塔里木河下游天然漫溢区多枝柽柳幼苗为研究对象,分析连续漫溢干扰下多枝柽柳幼苗生长和种群变化特征,以及不同漫溢强度下幼苗的光合特性。结果表明：（1）在连续2次较强输水漫溢的干扰下,多枝柽柳幼苗种群密度从2013年3月到2014年7月呈先增后降再增的趋势,而其冠面积、株高和基径则呈先降后增再降的趋势。（2）在第2次输水漫溢较弱的Ⅲ监测区,多枝柽柳幼苗种群密度呈先增加后逐渐降低的趋势,而其冠面积、株高和基径则呈先降低后逐渐增加的趋势。（3）随第2次输水漫溢量逐渐减弱,多枝柽柳幼苗叶片相对含水量呈先降后增的趋势,叶绿素含量、实际光化学量子产量（Φ_PSⅡ）、光化学猝灭系数（q_p）均呈逐渐降低的趋势,而非光化学猝灭系数（NPQ）呈逐渐增加的趋势,但潜在最大光化学量子效率（F_v/F_m）总体处于相对适宜的状态。研究认为,连续2次较强的输水漫溢条件虽能够使生长季期间漫溢区多枝柽柳幼苗种群得到更新,但同时也导致大量幼苗受淹死亡,从而使漫溢区的多枝柽柳幼苗种群不能形成一定的规模;建议采取强弱交替的方式进行生态输水,既能提高新发生幼苗的存活率,又能使幼苗稳定的生长。     

24-表油菜素内酯和盐度对浒苔生长和生理活性的影响

为探讨低温条件下外源植物激素和盐度变化对浒苔光合生理的影响,本文选取浒苔为供试材料,研究24-表油菜素内酯和盐度对其生长、光合色素、叶绿素荧光参数、抗氧化活性和可溶性蛋白含量的影响.结果表明: 与正常盐度(近岸海水盐度为25)相比,浒苔的生长在盐度10处理下显著增加,增幅为45.9%,但在盐度5处理下显著降低.盐度5处理的浒苔比其他盐度处理具有较高的Chl a和可溶性蛋白.24-表油菜素内酯(0.2 mg·L^-1)的加入显著抑制了浒苔的生长,尤其在盐度25处理下,浒苔呈现负增长的趋势,并大量释放孢子(配子),有效光化学效率、超氧化物歧化酶酶活性和可溶性糖含量明显降低,但可溶性蛋白含量显著增加.即在温度15 ℃条件下,可通过适当降低盐度促进浒苔的生长;在盐度25条件下,可通过添加24-表油菜素内酯促进孢子(配子)释放,为浒苔的大规模养殖提供原材料.     

滨海盐土土壤水分的高光谱参数及估测模型

基于滨海盐土5个试验点的土壤含水量和室内土壤表面高光谱反射率,综合分析了350～2500 nm波段范围内土壤含水量与土壤光谱之间的关系,并基于比值光谱指数(RSI)、归一化光谱指数(NDSI)和差值光谱指数(DI)确定了光谱参数,进而构建土壤含水量估测定量模型.结果表明： 滨海盐土原始光谱反射率与土壤含水量呈显著负相关关系,且最大负相关出现在1930 nm(r=0.86)附近.对RSI、NDSI和DI的直线回归方程、幂函数回归方程进行对比,以RSI(R₁₄₀₇,R₁₄₅₉)为自变量构建的土壤含水量指数函数线性回归方程决定系数最大(0.780),标准误较小(0.016),拟合方程为y=0.00001e^9.72053x.估测模型能够更好地监测滨海盐土土壤水分状况.基于RSI(R₁₄₀₇,R₁₄₅₉)构建的模型可实现对江苏省滨海盐土土壤水分的精确监测.     

Genetic variability of functional longevity in five rabbit lines

The objectives of this study were to analyse the differences in the genetic determination of functional longevity in five Spanish lines of rabbits and to check how different systematic factors might affect this genetic determination. Four of the lines were maternal (lines A, V, H and LP), these lines were established selecting base generation animals according to different criteria, but in the subsequent generations all of them were selected for litter size at weaning. The other is the paternal line R, this line was constituted by selecting animals with an outstanding daily growth rate. The trait analysed, length of productive life, was the time in days between the date of the first positive pregnancy test and the date of culling or death of a doe. Four models extended from the Cox proportional hazard model were used to analyse data of each line separately and jointly. The complete model (Model 1) included the fixed effect of year-season (YS) combination, positive palpation order (OPP), that is, reproductive cycle, physiological status of the doe (PS) at service and number of kits born alive (NBA) in each kindling as time-dependent factors. The inbreeding coefficient was fitted as a continuous covariate and the animal’s additive genetic effect was also fitted to the model (Model 1). The other models were identical to Model 1 but excluding OPP (Model 2) or PS (Model 3) or NBA (Model 4), which were explored to assess the consequence on additive variance estimates of not correcting for these animal-dependent factors. Estimated effective heritabilities of longevity were 0.07 ± 0.03, 0.03 ± 0.02, 0.14 ± 0.09, 0.05 ± 0.04, 0.02 ± 0.01 and 0.04 ± 0.01 for lines A, V, H, LP, R and for the merged data set, respectively. Removing the PS from the model led to an increase in the estimated additive genetic variance in all lines (0.17 ± 0.05, 0.05 ± 0.03, 0.29 ± 0.19, 0.29 ± 0.20, 0.07 ± 0.04 and 0.05 ± 0.02 for lines A, V, H, LP, R and the merged data set, respectively). The highest hazard of death and/or culling was observed during the first two parities and decreased as the order of parity progressed. Does non-pregnant-non-lactating had the highest risk of death or culling. The does that had zero kits born alive incurred the highest risk, and this risk decreased as the NBA increased. In conclusion, the consideration of longevity as selection criterion for the studied rabbit lines is not recommended.     

Effect of Extremely Low Power Time-Varying Electromagnetic Field on Germination and Other Characteristics in Foxtail Millet (Setaria italica) Seeds

The ability of extremely low, time-varying electromagnetic field (EMF) to improve germination efficacy was studied in Foxtail millet (Setaria italica) seeds using response surface methodology. An optimal factorial central composite design was chosen to optimize the EMF with three critical factors, viz. frequency, intensity, and duration. The adequacy of the model and fitness was evaluated by analysis of variance and regression coefficients. This model suggested that the factors, frequency, and intensity had a significant impact on germination. Optimal conditions for germination were observed to be 10 Hz frequency, 30,007 nT intensity, and 30-min duration with an observed germination percentage of 93.0, and a predicted germination percentage of 92.92. Magneto-priming was found to increase the germination efficacy (15.66%), shoot length (27.78%), total seedling length (20.30%), seedling dry mass (26.49%), and water uptake (34.48% at 80 min) showing significant output when compared with the control and positive controls. Remarkable improvements were observed in germination parameters such as vigor index-1 (39.14%), vigor index-2 (46.28%), speed of germination (27.52%), and emergence index (12.50%). Magneto-priming was found to reduce the levels of germination-specific enzymes, viz. α-amylase, protease, and dehydrogenase, while it enhanced the levels of antioxidant enzymes, viz. catalase (114.63%) and superoxide dismutase (19.62%), triggering fast germination and early vigor of seedlings. This study clearly showed that EMF priming significantly improved the germination effect and other characteristics of Foxtail millet seeds. Bioelectromagnetics. © 2020 Bioelectromagnetics Society     

Synthesis of Optically Active Cyanohydrins Using R-Oxynitrilase in a Liquid-Liquid Biphasic System: Part 1: An Industrially useful Procedure

An improved method is presented for preparing optically active cyanohydrins in high yield and high enantioselectivity, using R-oxynitrilase from almonds as the catalyst in a biphasic water-organic solvent system. Reaction conditions for two representative substates have been studied with respect to conversion, optical purity and enzyme stability.

The suitability of the procedure for industrial use was substantiated by the possibility of reusing the enzyme-containing aqueous phase for the synthesis of R-mandelonitrile.     

Predictive regression modeling of body segment parameters using individual-based anthropometric measurements

Body segment parameters such as segment mass, center of mass, and radius of gyration are used as inputs in static and dynamic ergonomic and biomechanical models used to predict joint and muscle forces, and to assess risks of musculoskeletal injury. Previous work has predicted body segment parameters (BSPs) in the general population using age and obesity levels as statistical predictors (Merrill et al., 2017). Estimated errors in the prediction of BSPs can be as large as 40%, depending on age, and the prediction method employed (Durkin and Dowling, 2003). Thus, more accurate and representative segment parameter inputs are required for attempting to predict modeling outputs such as joint contact forces, muscle forces, and injury risk in individuals. This study aims to provide statistical models for predicting torso, thigh, shank, upper arm, and forearm segment parameters in working adults using whole body dual energy x-ray absorptiometry (DXA) scan data along with a set of anthropometric measurements. The statistical models were developed on a training data set, and independently validated on a separate test data set. The predicted BSPs in validation data were, on average, within 5% of the actual in vivo DXA-based BSPs, while previously developed predictions (de Leva, 1996) had average errors of up to 60%, indicating that the new models greatly increase the accuracy in predicting segment parameters. These final developed models can be used for calculating representative BSPs in individuals for use in modeling applications dependent on these parameters.