Are there attentional demands associated with haptic modalities while walking in young,healthy adults?

Study designA prospective, observational study.ObjectivesTo assess the attentional demands of using haptic modalities during walking using a multi-task paradigm in young, healthy adults.SettingBiomechanics of Balance and Movement (BBAM) Lab, University of Saskatchewan.MethodsTwenty-two (12 male) young, healthy adults performed walking trials with and without a verbal reaction time (VRT) task, as well as with and without the use of haptic anchors and light touch on a railing. Walking performance was evaluated using normalized stride velocity and step width, and dynamic stability was evaluated using step width variability and medial-lateral margin of stability (ML MOS) and its variability.ResultsThere were no significant differences in VRT when walking with and without added haptic input and no interactions between the added VRT task and added haptic input. Step width increased and variability of the ML MOS increased during trials with the VRT task compared to trials without the VRT task. The ML MOS decreased when using both haptic tools with a greater decrease when using light touch on the railing compared to when using the haptic anchors. Normalized stride velocity and step width decreased when using light touch on the railing only.ConclusionBoth haptic tools affected stability during walking. Using the railing to add haptic input had a greater effect on walking stability and was the only haptic tool to affect walking performance. Attentional demands should be considered in future research and applications of adding haptic input during walking.     

Nonlinear approach to study the acute effects of static and dynamic stretching on local dynamic stability in lower extremity joint kinematics and muscular activity during pedalling

Researchers have reported contradictory results on the effect of static and dynamic stretching on subsequent performance. Due to the importance of performance through static and dynamic stretching, the aim of this study is to investigate the acute effects of static and dynamic stretching protocols on local dynamic stability in lower extremity joint kinematics and muscular activities during pedalling using a nonlinear dynamics approach. Using a randomised crossover trial design, fifteen active males participated voluntarily in this research (mass: 69.02 ± 10.52 kg, height: 174.00 ± 6.74 cm, and age: 21.20 ± 1.47 years) and completed a pedalling trial in situations of without stretching (WS), after static (SS), and dynamic stretching (DS) of lower extremity. The lower extremity joint angles in the sagittal plane and the electrical activity of soleus, gastrocnemius medialis, tibialis anterior, vastus medialis, biceps femoris, and rectus femoris muscles were collected during 30 pedalling cycles at 70 rates per minute. The results of the repeated measure ANOVA indicated that the knee and ankle angle largest LyE was significantly lower in DS compared to WS and SS. The largest LyE in muscle activity is also significantly lower for all the muscles after DS compared to WS and SS (P ≤ 0.05). Regarding the positive effects of DS on the joints and the muscle activity local dynamic stability, it is suggested to use DS than SS in the warm-up program before repetitive activities like pedalling.     

Subadditive versus hyperbolic discounting: A comparison of choice and matching

Impulsive and myopic choices are often explained as due to hyperbolic discounting, meaning that people are impatient for outcomes available immediately, and become increasingly more patient the more the outcome is delayed. Recent research, however, has suggested that much experimental evidence for increasing patience is actually due to subadditive discounting: people are less patient (per-time-unit) over shorter intervals regardless of when they occur. Because previous research into subadditive discounting has used a choice elicitation procedure, the present paper tests whether it generalises to matching. We find strong evidence that it does, but also find weak evidence of increasing patience for matching. We suggest, however, that subadditive discounting alone may be sufficient to account for all of our results. We conclude by questioning the contribution that hyperbolic discounting makes to our understanding of time preference.     

Developing networks in disempowered communities: Experiencing hardships while focusing on opportunities

This study aims to present an evaluation and the process steps of a community‐based initiative (CBI) consisting of a group of organizations that work to enhance the lives of boys and men of colour. Using a participatory research model, the researchers collaborated with 14 community stakeholders to develop the questions during two data collection periods and reviewed the reports for accuracy. The findings were separated into two broad categories. The perceived challenges included a lack of clear goals and measurements of success, an absence of leadership and direction, and a shortage of resources. The successes included passion of partners, increased collaboration, and increasing and maintaining social capital within the community. The lessons learned from both data collection periods helped this CBI broaden its reach and collaboration efforts. Overall, this study provides suggestions to other CBIs as they embark on making changes in their own communities.     

Narrative congruence between populist President Duterte and the Filipino public: Shifting global alliances from the United States to China

This research examines what happened when the populist Philippine President Rodrigo Duterte reversed his country's global alliance, switching loyalties away from the United States towards China. We use the lens of narrative congruence, to see if political storylines of a populist president are accompanied by similar shifts in storylines among his followers. Our data corpus consists of text from Duterte's speeches and from comments on partisan Facebook pages, representing supporters and opponents of the president. We time‐bound our data corpus to text produced around the time President Duterte announced his realignment towards China. We use text mining and network analysis to identify overlaps among words used by the different social actors. Our findings show that when Duterte switched alliances, Facebookers—regardless of partisanship—accepted this alliance shift. However, our results likewise reveal an imperfect congruence. Duterte's followers move on to a story criticizing Duterte's domestic political enemies, whereas anti‐Duterte Facebookers talk about monetary deals and drug issues in the Philippines' newfound friendship with China. We discuss our findings in the light of a psychology of populism, the use of a discursive social networks approach to study macropsychological phenomena, and discursive resistance in a populist state.     

An accurate and efficient multi-category edge detection method

Edge detection plays an important role in image processing. With the development of deep learning, the accuracy of edge detection has been greatly improved, and people have more requirements for edge detection tasks. Most edge detection algorithms are binary edge detection methods, but there are usually multiple categories of edges in an image. In this paper, we present an accurate multi-category edge detection network, the richer category-aware semantic edge detection network (R-CASENet). In order to make full use of convolutional neural network’s powerful feature expression capabilities, we attempt to use more information from feature maps for edge feature extraction and classification. Using the ResNet101 network as the backbone, firstly we merge the building blocks in different composite blocks and down-sample to obtain the feature maps. Then we fuse the feature maps in different composite blocks to obtain the final fused classifier. Experimental results show that R-CASENet can achieve state-of-the-art performance on the large SBD dataset. Furthermore, to get precise one-pixel width edges, we also propose an edge refinement network (ERN) structure. The proposed scheme is an end-to-end method and the proposed ERN can reduce redundant points and improve computational efficiency, especially for further image processing.     

压力性生活事件与青少年自尊：被动性社交网站使用和人生意义感的中介作用

采用青少年生活事件量表、被动性社交网站使用量表、生命意义感量表以及自尊量表对605名青少年施测,旨在探讨压力性生活事件对自尊的效应以及被动性社交网站使用和人生意义感的中介作用。结果发现：被动性社交网站使用和拥有人生意义感在压力性生活事件与自尊之间起中介作用,压力性生活事件分别通过被动性社交网站使用、拥有人生意义感的中介作用和被动性社交网站使用与拥有人生意义感的序列中介作用对自尊产生效应。     

成人在语境中的母语词汇意义学习

语境学习是成人获得词汇意义的主要方式, 大量研究者使用语境学习范式考察成人母语词汇意义学习的问题。已有研究将词汇意义学习分为两大阶段：习得词汇的对应概念阶段和将新词的意义整合到已有的语义网络中的阶段。基于词汇意义学习两大加工阶段中语境学习的相关研究, 梳理了词汇、语境、被试因素对成人词汇意义学习的影响, 指出未来研究需要进一步关注新概念学习、隐喻意义学习等问题。     

失眠患者静息态脑网络的改变：网络内与网络间的功能连接异常

失眠已成为现代人群中的一种高发健康问题。静息态功能磁共振以其数据采集便利性和无创性, 成为失眠研究的主要成像手段之一。基于近年来静息态功能磁共振的发现, 失眠患者存在前额叶、颞叶、前扣带回、脑岛等认知-情绪神经环路的异常。大尺度脑网络是涵盖多个脑区、功能相对单一的大脑结构。失眠患者存在默认网络、突显网络、认知控制网络和负性情绪网络内部活动与连接异常, 而且呈现出以默认网络为核心, 包含认知控制网络、突显网络、负性情绪网络的网络间连接异常模式。此外, 结合症状、治疗和大尺度脑网络的视角, 可为失眠的“精准治疗”提供神经理论依据。未来研究可结合大数据和多模态分析技术, 验证静息态功能磁共振已有发现。而失眠的纵向追踪和队列研究会有利于进一步阐释失眠的神经机制。     

组织公民行为研究的新视角

对2000年以后组织公民行为领域出现的最新研究动态进行讨论和分析,主要包括基于社会资本和社会网络的组织公民行为研究、社会规范对组织公民行为的影响、群体层次的组织公民行为研究以及对组织公民行为的负面作用的探讨。作者分别讨论了上述4个最近研究方向在我国研究的理论和实践意义,并提出了一些具体的研究建议。最后,作者对这4个研究方向的相互关系和整合提出了自己的观点