基于智能手机传感器的人体活动识别

人体活动识别是上下文感知系统及其应用中一个具有挑战性的研究问题。目前,关于人体活动识别的研究主要使用一些基于监督学习或半监督学习的统计方法来构建识别模型。然而,考虑到识别活动类型本身具有的复杂性和多样性,当前的人体活动识别系统不能取得较好的识别效果。针对这一问题,通过智能手机的三维加速度和陀螺仪传感器信息来提取人体活动的特征向量,选择四种典型的统计学习方法（分别是K-近邻算法、支持向量机、朴素贝叶斯网络以及基于朴素贝叶斯网络的AdaBoost算法）分别创建人体活动的识别模型,最后通过模型决策得到最优的人体活动识别模型。实验结果表明,通过模型决策选择的识别模型对人体活动识别准确率达到92%,取得很好的识别效果。     

Physical activity classification in free-living conditions using smartphone accelerometer data and exploration of predicted results

In recent decades, decreasing physical activity has emerged as one of the major issues affecting human health since people increasingly engaged in sedentary behavior in their homes and workplaces. In physical activity research, using GPS trajectories and advanced GIS methods has a potential for greatly enhancing our understanding of the association between objectively measured moderate and vigorous physical activity and physical and social environments. Relying only on objectively measured physical activity intensity, however, ignores the role of different places and types of physical activity on people's health outcomes. The aim of this study is to propose an approach to classifying physical activity in free-living conditions for physical activity research using published smartphone accelerometer data. Random forest and gradient boosting are used to predict jogging, walking, sitting, and standing. Generated training models based on the two classifiers are tested on accelerometer data collected from the smartphones of two subjects in free-living conditions. GPS trajectories with predicted physical activity labels are visually explored on a map to offer new insight on the assessment of the predicted results of daily activities and the identification of any difference in the results between random forest and gradient boosting. The findings of this study indicate that random forest and gradient boosting enable accurate physical activity classification in free-living conditions. GPS trajectories linked with predicted labels on a map assist the visual exploration of the erroneous prediction in daily activities including in-vehicle activities.     

A systematic review – physical activity in dementia: The influence of the nursing home environment

Most older persons with dementia living in nursing homes spend their days without engaging in much physical activity. This study therefore looked at the influence that the environment has on their level of physical activity, by reviewing empirical studies that measured the effects of environmental stimuli on the physical activity of nursing home residents suffering from dementia. The electronic databases PubMed, PsycINFO, EMBASE, CINAHL and the Cochrane Library were used for the search. The search covered studies published between January 1993 and December 2012, and revealed 3187 abstracts. 326 studies were selected as potentially relevant; of these, 24 met all the inclusion criteria. Positive results on the residents' levels of physical activity were found for music, a homelike environment and functional modifications. Predominantly positive results were also found for the small-scale group living concepts. Mixed results were found for bright or timed light, the multisensory environment and differences in the building footprint.     

磁场处理对土壤磷酸酶活性的影响

本文研究了磁场处理后棕壤、黑土及白浆土中磷酸酶活性的变化。研究结果表明，磁处理对土壤的3种磷酸酶都有一定的激活作用，但以碱性磷酸酶的活性变化最明显。3种磷酸酶活性提高的大小顺序是：黑土中碱性磷酸酶＞酸性磷酸酶＞中性磷酸酶；棕壤和白浆土中碱性磷酸酶＞中性磷酸酶＞酸性磷酸酶。土壤水分对磷酸酶的磁处理效果影响不大。对于磷酸酶活性影响以＜100mT的低场强以及lrnin或10min的短时间处理效果较好。     

电子书包支持的体验学习活动设计与应用研究

旨在研究电子书包支持的体验学习的活动模型和应用效果。首先通过理论分析提出了电子书包支持的体验学习活动模型,并设计了《校园植物知多少》等3个教学专题,之后在某小学进行了试点实验研究。研究结果表明,电子书包支持的体验学习模型确实有助于提高学生的认知体验、行为体验和情感体验的参与度。     

气功外气传感器的研制与外气成分的初步分析

本文报道了一种用于气功外气测定的光敏生物传感器。这种传感器是由能催化鲁米诺一过氧化氢化学发光反应的酶的固相化膜与光敏三极管装配而成。当外气作用于固相化酶膜时,光强度随酶活性的改变而变化,从而可以用来确定气功外气的强弱。用这种传感器对6位有名的气功师进行了外气测定,结果表明：外气能明显地影响固相化酶的活性;对同一气功师而言,光强度的改变与气功师同固相化酶膜之间的距离以及外气发放的时间有关。用金属网屏蔽罩隔离能明显地使显示减少,由此可知外气中存在有电磁波成分。     

Synchronous Digital Hierarchy statistical simulation of pointer activity

Pointer activity in Synchronous Transport Module 1 (STM1) networks is presented based on simulated models of various STM1 network payload configurations. A statistical clock model is used to simulate the effects of clocking instabilities. The clock model used is based upon an RMS Time Interval Error (RMSTIE) metric and conforms to the RMSTIE mask as defined by CCITT and other standards committees. Traditional pointer activity studies have been done on a behavioural basis, minimizing byte by byte calculations to reduce simulation time and resolution of results. Additionally, previous studies have examined the effects of constant clock frequency offsets on pointer activity. This study approaches the problem by using byte by byte calculations coupled with a statistical clock model and constant frequency offsets to determine pointer generation and interactions at a level of detail not presented previously. The results of this study are the expected nature of pointer activity in Synchronous Digital Hierarchy (SDH) networks for clock instabilities within the CCITT clock stability specifications.     

A JSM intelligent system for toxicity. Analysis of functional cumulation of chemical compounds

Here we present the structure of a JSM intelligent system for toxicology. We report the results of data analysis regarding the functional cumulative activity of chemical compounds, based on which the degree of activity is predicted for unstudied compounds.     

磁场对棕壤脲酶活性的影响

通过对棕壤风干土样和相对含水量70%的湿土样进行磁场处理研究发现,对棕壤风干土脲酶活性抑制作用最大的处理为500mT5分钟,对棕壤湿土脲酶活性抑制作用最大的处理为100mT10分钟。土壤湿度对棕壤脲酶活性的磁致效应大小有一定影响;无论是对于风干土或是湿土,500mT场强10分钟处理对棕壤脲酶活性的抑制作用时间最长,磁处理42天后抑制效果仍然显著。     

Effect of canopy shape on physical load when holding an umbrella

The aim of the current study was to investigate the effect of the canopy shape of an umbrella on physical load when holding the umbrella in different circumstances. For this purpose, thirteen subjects participated in this study and muscle activity of seven muscles of the upper limb (including the forearm) was measured for 5 wind speeds (4, 5, 6, 7, 8?Bft) and two wind directions (front and side). From the results, it was seen that for the p50 value of the muscle activity, the umbrella with the asymmetric canopy required 62% and for the p90 value of the muscle activity 74% of the muscle activity, on average, over all wind speeds - compared to the traditional umbrella. Based on these results, we can conclude that the physical load of holding the traditional umbrella is significantly higher than holding the umbrella with the asymmetric canopy shape in windy conditions.     

On the use of ensemble of classifiers for accelerometer-based activity recognition

Activity recognition aims to detect the physical activities such as walking, sitting, and jogging performed by humans. With the widespread adoption and usage of mobile devices in daily life, several advanced applications of activity recognition were implemented and distributed all over the world. In this study, we explored the power of ensemble of classifiers approach for accelerometer-based activity recognition and built a novel activity prediction model based on machine learning classifiers. Our approach utilizes from J48 decision tree, Multi-Layer Perceptrons (MLP) and Logistic Regression techniques and combines these classifiers with the average of probabilities combination rule. Publicly available activity recognition dataset known as WISDM (Wireless Sensor Data Mining) which includes information from thirty six users was used during the experiments. According to the experimental results, our model provides better performance than MLP-based recognition approach suggested in previous study. These results strongly suggest researchers applying ensemble of classifiers approach for activity recognition problem.     

沼泽土施硒对黑麦草生长、品质及生理活性的影响

用土培试验方法研究了若尔盖高原沼泽土施硒对黑麦草(L.mu ltiflorum Lam aubada)生长、品质、谷胱甘肽过氧化物酶(GSH-Px)活性及根系活力的影响。结果表明,适量施硒能促进黑麦草的生物量、GSH-Px活性和根系活力的增加;当施硒高于20 mg kg-1时黑麦草的生长受到抑制,GSH-Px活性与根系活力均随之降低。施硒量在0~20 mg kg-1范围时,黑麦草的粗蛋白、粗脂肪、磷和钙的含量随施硒量的增加而提高,粗纤维与硅的含量下降。适量施硒能促进黑麦草的品质改善。     

Network stability from activity-dependent regulation of neuronal conductances.

Activity-dependent plasticity appears to play an important role in the modification of neurons and neural circuits that occurs during development and learning. Plasticity is also essential for the maintenance of stable patterns of activity in the face of variable environmental and internal conditions. Previous theoretical and experimental results suggest that neurons stabilize their activity by altering the number or characteristics of ion channels to regulate their intrinsic electrical properties. We present both experimental and modeling evidence to show that activity-dependent regulation of conductances, operating at the level of individual neurons, can also stabilize network activity. These results indicate that the stomatogastric ganglion of the crab can generate a characteristic rhythmic pattern of activity in two fundamentally different modes of operation. In one mode, the rhythm is strictly conditional on the presence of neuromodulatory afferents from adjacent ganglia. In the other, it is independent of neuromodulatory input but relies on newly developed intrinsic properties of the component neurons.     

Comparison of homology models and X-ray structures of the nuclear receptor CAR: assessing the structural basis of constitutive activity

The constitutive androstane receptor (CAR) possesses an intrinsic basal activity whose structural basis has been analysed during the last decade. Recently, we published a homology model of the CAR ligand binding domain (LBD) based on the X-ray structures of the closely related pregnane X (PXR) and vitamin D (VDR) receptor. A detailed analysis of the homology model and molecular dynamics (MD) simulations afforded us to propose a potential mechanism underlying the constitutive activity of CAR. Almost simultaneously, X-ray structures of human and mouse CAR LBD were released. In the present study, a detailed analysis and comparison of homology model and X-ray structures is carried out in order to evaluate the quality and reliability of our homology modelling procedure. The hypothesis of the constitutive activity which we proposed on the basis of our modelling results was tested for consistency with the crystal structures. In addition, the features stated to be essential for the basal activity based on the X-ray data were investigated by means of molecular dynamics simulations. Our results show that the homology modelling procedure was able to predict the CAR LBD structure with high accuracy. Structural features that have been revealed as critical for constitutive activity in the model are also observed in the X-ray structures. Furthermore, the MD simulations of the CAR X-ray structures and a detailed analysis of other NRs clarify the role of distinct structural features that have been assigned an important role for the constitutive activity.     

Long-term reward prediction in TD models of the dopamine system

This article addresses the relationship between long-term reward predictions and slow-timescale neural activity in temporal difference (TD) models of the dopamine system. Such models attempt to explain how the activity of dopamine (DA) neurons relates to errors in the prediction of future rewards. Previous models have been mostly restricted to short-term predictions of rewards expected during a single, somewhat artificially defined trial. Also, the models focused exclusively on the phasic pause-and-burst activity of primate DA neurons; the neurons' slower, tonic background activity was assumed to be constant. This has led to difficulty in explaining the results of neurochemical experiments that measure indications of DA release on a slow timescale, results that seem at first glance inconsistent with a reward prediction model. In this article, we investigate a TD model of DA activity modified so as to enable it to make longer-term predictions about rewards expected far in the future. We show that these predictions manifest themselves as slow changes in the baseline error signal, which we associate with tonic DA activity. Using this model, we make new predictions about the behavior of the DA system in a number of experimental situations. Some of these predictions suggest new computational explanations for previously puzzling data, such as indications from microdialysis studies of elevated DA activity triggered by aversive events.     

Independent shape component-based human activity recognition via Hidden Markov Model

In proactive computing, human activity recognition from image sequences is an active research area. In this paper, a novel human activity recognition method is proposed, which utilizes Independent Component Analysis (ICA) for activity shape information extraction from image sequences and Hidden Markov Model (HMM) for recognition. Various human activities are represented by shape feature vectors from the sequence of activity shape images via ICA. Based on these features, each HMM is trained and activity recognition is achieved by the trained HMMs of different activities. Our recognition performance has been compared to the conventional method where Principal Component Analysis (PCA) is typically used to derive activity shape features. Our results show that superior recognition is achieved with the proposed method especially for activities (e.g., skipping) that cannot be easily recognized by the conventional method. Furthermore, by employing Linear Discriminant Analysis (LDA) on IC features, the recognition results further improved significantly in the recognition performance.     

聚醚类海生毒素的构效关系与分子设计研究

在对聚醚类海生毒素构效关系研究的基础上，设计了5个结构简化的高活性化合物，对它们的电子结构和空间结构进行了计算和研究，并同CTX、BTX类化合物进行了比较，讨论了新化合物和已知化合物在电子结构与空间结构上的一致性，依据相关关系对新化合物进行了活性预测。     

Effect of sleep loss on core temperature when movement is controlled

Nine subjects were studied for 16 days in an isolation unit where they lived on normal time, working at a decision-making, computer-driven task during the daytime. Interspersed among these control days were three occasions when sleep was curtailed. Rectal temperature and activity (non-dominant wrist) were measured throughout. Any effects of sleep loss on core temperature and activity were assessed by comparing these variables on control days with values during the daytime immediately following sleep loss, and during the next (recovery) day. During the daytime following sleep loss, activity showed no significant changes. By contrast, core temperature was significantly lower, particularly after the night of complete sleep loss. On recovery days also, activity was not significantly changed from control days but core temperatures during work were significantly lower than on control days if there had been no sleep the previous night. These results indicate that the effects of sleep loss on core temperature can persist for at least 24 h, and that they occur in the absence of parallel changes in activity.     

A Neural Chaos Model of Multistable Perception

We present a perception model of ambiguous patterns based on the chaotic neural network and investigate the characteristics through computer simulations. The results induced by the chaotic activity are similar to those of psychophysical experiments and it is difficult for the stochastic activity to reproduce them in the same simple framework. Our demonstration suggests functional usefulness of the chaotic activity in perceptual systems even at higher cognitive levels. The perceptual alternation may be an inherent feature built in the chaotic neuron assembly.