Dependence of grip strength on shoulder position and its implications for ergonomics practice

Grip strength (GS) variability due to positional changes in the upper extremity joints is of importance while designing workstations and work methods. This study was conducted to analyze the GS variations due to positional changes at shoulder joint when some important variables were under control. The GSs of dominant and nondominant hands were measured in eight shoulder (0°, 45°, 90°, and 135° of flexion and abduction) and standard test positions (STP). One hundred and thirteen subjects 20–30 years old completed the study. At the dominant side, no significant difference was observed in the pairwise comparisons between STP and the others. Maximum and minimum GSs were obtained in 0° abduction and 45° flexion and abduction, respectively. At the nondominant side, GSs were significantly lower (p < 0.001) in the corresponding test positions and demonstrated more variability. The findings of this study can contribute to the available knowledge to guide occupational ergonomists in their practices.     

Computational personality recognition from Facebook text: psycholinguistic features,words and facets

ABSTRACT

Advances in the Natural Language Processing (NLP) and machine learning fields have led to the development of automated methods for the recognition of personality traits from text available from social media and similar sources. Systems of this kind exploit the close relation between lexical knowledge and personality models – such as the well-known Big Five model – to provide information about the author of an input text in a non-intrusive fashion, and at a low cost. Although now a well-established research topic in the field, the computational recognition of personality traits from text still leaves a number of research questions worth further exploration. In particular, this paper attempts to shed light on three main issues: (i) whether we may develop psycholinguistics-motivated models of personality recognition when such knowledge sources are not available for the target language under consideration; (ii) whether the use of psycholinguistic knowledge may be still superior to contemporary word vector representations; and (iii) whether we may infer certain personality facets from a corpus that does not explicitly convey this information. In this paper these issues are dealt with in a series of individual experiments of personality recognition from Facebook text, whose initial results should aid the future development of more robust systems of this kind.     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

基于堆叠深度卷积沙漏网络的步态识别

提出了一种基于堆叠深度卷积沙漏网络的步态识别方法。为了解决人体建模中关节点准确定位的问题，采用基于深度卷积的沙漏网络来提取步态图上的关节点坐标，并计算肘关节与膝关节的角度作为运动特征。为了解决行走速度变化带来的影响，采用动态时间规整（Dynamic Time Warping）对特征序列进行距离计算。通过最近邻分类器对结果进行准确分类。该方法在公共CASIA-B数据集与TUM-GAID数据集上进行了验证并与其他方法进行比较，结果表明该方法有较高的识别率。     

基于CNN的人体姿态识别

姿态识别是人机交互中重要的研究课题之一，随着机器学习与神经网络的发展，研究的方式和成果趋于多样化，姿态识别的应用价值也日趋广泛。本文通过构建卷积神经网络模型，该模型共有11层，在对采样的数据集中5种人体姿态进行卷积与池化操作，最后进入全连接层进行分类，从而完成对数据集的训练和识别。结果显示，相较于机器学习方法，该模型的识别性能更加优秀，且免去了复杂的特征提取方式设计，让网络自身提取特征进行识别分类，效果更好。     

Recent trends for the employment of jumbo squid (Dosidicus gigas) by-products as a source of bioactive compounds with nutritional,functional and preservative applications: a review

Only 50%–60% of total seafood catch is used for human consumption, seafood processing being considered as one of the main sources of by-products. Among marine species, jumbo squid (JS; Dosidicus gigas) represents the most important squid fishery, showing an increasing economic interest in many countries. As for any other marine species, the regular cleaning, dressing and processing produce high quantities of by-products (skin, head, fins, viscera, tentacles, unclaimed mantle, etc.) that are rich in many nutrients (proteins, lipids, minerals, vitamins, enzymes, biopolymers, etc.). This review compiles information about extraction and employment of JS by-products with the aim of enhancing their economic value and reduce environmental drawbacks. A special emphasis is given to the relevance in developing methods susceptible to transform by-products into useful and profitable products susceptible to be applied in several industries such as food, medicine, agrochemical or pharmaceutical. Future possible trends for widening this profitable use are mentioned.     

新人体(火用)分析模型在建筑热舒适评价中的应用

为探究人体■分析法在评估室内热环境状态中的应用,严格根据新陈代谢■的定义,在已有的两种■分析模型基础上,首先提出了更合理的新陈代谢■计算方法,建立了新的两节点■分析模型.然后利用ASHRAE数据库中的实验数据验证了所建立模型的可靠性.最后,揭示了人体■交换速率、■损失速率随室内、外环境参数的变化规律.研究结果表明:新的新陈代谢■计算方法能更准确地进行人体■分析;■损失速率比■交换速率占新陈代谢■率的比例大;操作温度25℃时,■交换速率主要包含辐射■率和对流■率;操作温度32℃时,蒸发■率和呼吸■率则是■交换速率的主要组成部分;人体■损失速率在操作温度较低或较高条件下均出现极值,将其单独用于人体热舒适评价不妥,结合■损失速率和■交换速率两者可更好地评价室内热环境状态;最小■损失速率和最小■交换速率在给定室内条件下,均在室外高温低湿工况下出现;室外温度比室外相对湿度更强烈地影响人体■损失速率和人体■交换速率.     

Expression of Main Toll-Like Receptors in Patients with Different Types of Colorectal Polyps and Their Relationship with Gut Microbiota

Abnormal activation of Toll-like receptor (TLRs) signaling can result in colon cancer development. The aim of this study was to investigate the expression of important TLRs in different histological types of colorectal polyps and evaluate their relationship with intestinal microbiota. The expression levels of TLR2, 3, 4, and 5 were analyzed in intestinal biopsy specimens of 21 hyperplastic polyp (HP), 16 sessile serrated adenoma (SSA), 29 tubular adenoma (TA), 21 villous/tubulovillous (VP/TVP) cases, and 31 normal controls. In addition, selected gut bacteria including Streptococcus bovis, Enterococcus faecalis, Enterotoxigenic Bacteroides fragilis (ETBF), Fusobacterium nucleatum, Porphyromonas spp., Lactobacillus spp., Roseburia spp., and Bifidobacterium spp. were quantified in fecal samples using absolute qRT PCR, and, finally, the association between TLRs and these gut microbiota- was evaluated by Spearman’s correlation coefficient. Higher expression of TLR2 and TLR4 in VP/TVP and TA, and lower expression levels of TLR3 and TLR5 in all type of polyps were observed. The differences in TLR expression patterns was not only dependent on the histology, location, size, and dysplasia grade of polyps but also related to the intestinal microbiota patterns. TLR2 and TLR4 expression was directly associated with the F. nucleatum, E. faecalis, S. bovis, Porphyromonas, and inversely to Bifidobacterium, Lactobacillus, and Roseburia quantity. Furthermore, TLR3 and TLR5 expression was directly associated with Bifidobacterium, Roseburia, and Lactobacillus quantity. Our results suggest a possible critical role of TLRs during colorectal polyp progression. An abnormal regulation of TLRs in relation to gut microbial quantity may contribute to carcinogenesis.