Effects of Walking in Bamboo Forest and City Environments on Brainwave Activity in Young Adults

Background. In Japan, “Shinrin-yoku” or forest bathing (spending time in forests) is a major practice used for relaxation. However, its effects on promoting human mental health are still under consideration. The objective of this study was to investigate the physiological and psychological relaxation effects of forest walking on adults. Sixty participants (50% males; 50% females) were trained to walk 15-minute predetermined courses in a bamboo forest and a city area (control). The length of the courses was the same to allow comparison of the effects of both environments. Blood pressure and EEG results were measured to assess the physiological responses and the semantic differential method (SDM) and STAI were used to study the psychological responses. Blood pressure was significantly decreased and variation in brain activity was observed in both environments. The results of the two questionnaires indicated that walking in the bamboo forest improves mood and reduces anxiety. Moreover, the mean meditation and attention scores were significantly increased after walking in a bamboo forest. The results of the physiological and psychological measurements indicate the relaxing effects of walking in a bamboo forest on adults

Primary adenomyoepithelioma of tonsil

We present a case of adenomyoepithlioma (AME) arising from the tonsil. AME is an uncommon tumor that typically arises in breast, but rarely found in salivary glands, lung, and skin. Its biological features have not been thoroughly characterized. Here we describe a primary AME originating from the tonsil. The pathologic changes were characterized by hypercellularity, the dominance of both epithelial and myoepithelial cells. Malignancy was evidenced by the presence of a high mitotic rate and invasive growth. The epithelial cells express high levels of cytokeratin and epithelial membrane antigen (EMA). The myoepithelial cells show positive staining for calponin, p63, vimentin, and S-100. A thorough review of the literature indicates that this is likely the first reported case of AME from the tonsil. Following descriptions of the diagnosis, treatment, and prognosis of this specific case, pathologic and clinical characteristics of AME from other tissues are also compiled and discussed

Effect of sarcopenia on survival of patients with cirrhosis: A meta-analysis

The association between sarcopenia and prognosis in patients with cirrhosis remains to be determined. In this study, we aimed to quantify the association between sarcopenia and the risk of mortality in patients with cirrhosis, by sex, underlying liver disease etiology, and severity of hepatic dysfunction.PubMed, Web of Science, EMBASE, and major scientific conference sessions were searched without language restriction through 13 January 2021 with additional manual search of bibliographies of relevant articles. Cohort studies of ?100 patients with cirrhosis and ?12 months of follow-up that evaluated the association between sarcopenia, muscle mass and the risk of mortality were included.22 studies with 6965 patients with cirrhosis were included. The pooled prevalence of sarcopenia in patients with cirrhosis was 37.5% overall (95% CI 32.4%-42.8%), higher in male patients, patients with alcohol associated liver disease (ALD), patients with CTP grade C, and when sarcopenia was defined in patients by lumbar 3- skeletal muscle index (L3-SMI). Sarcopenia was associated with the increased risk of mortality in patients with cirrhosis (adjusted-hazard ratio [aHR] 2.30, 95% CI 2.01-2.63), with similar findings in sensitivity analysis of cirrhosis patients without HCC (aHR 2.35, 95% CI 1.95-2.83) and in subgroup analysis by sex, liver disease etiology, and severity of hepatic dysfunction. The association between quantitative muscle mass index and mortality further supports the poor prognosis for patients with sarcopenia (aHR 0.95, 95% CI 0.93-0.98). There was no significant heterogeneity in all analyses.Sarcopenia was highly and independently associated with higher risk of mortality in patients with cirrhosis.The prevalence of sarcopenia and its association with death in patients with cirrhosis remain unclear. This meta-analysis indicated that sarcopenia affected about one-third of patients with cirrhosis and up to 50% in patients with ALD or Child's class C cirrhosis. Sarcopenia was independently associated with about 2-fold higher risk of mortality in patients with cirrhosis. The mortality rate increased with greater severity or longer period of having sarcopenia. Increasing awareness about the importance of sarcopenia in patients with cirrhosis among stakeholders must be prioritized

An Approach of Path Optimization Algorithm for 3D Concrete Printing Based on Graph Theory

In this paper, a method of 3D concrete printing is used to find the optimal path of the nozzle running path. We propose a path optimization algorithm based on graph theory to solve two key problems in 3D concrete printing. The partitioning algorithm based on graph theory was adopted to improve the forming quality of concrete components, and ant colony algorithm was used to reduce printing time. The method was evaluated with 3D concrete printing experiments after introducing the process of implementing the partition algorithm and ant colony algorithm. The experiment results show a significant reduction in the idle strokes and the nozzle head-up times of the running path planned by the method in this paper. This has a direct impact on shortening the printing time and improving the forming quality. Compared with the other three conventional algorithms, the idle strokes of the nozzle planned by the method in this paper are reduced by 18.94%, 37.88%, and 66.67%, and the nozzle head-up times are reduced by 1.59%, 2.15%, and 8.69%. It provides a practical reference for the path optimization of 3D concrete printing

An Approach of Path Optimization Algorithm for 3D Concrete Printing Based on Graph Theory

In this paper, a method of 3D concrete printing is used to find the optimal path of the nozzle running path. We propose a path optimization algorithm based on graph theory to solve two key problems in 3D concrete printing. The partitioning algorithm based on graph theory was adopted to improve the forming quality of concrete components, and ant colony algorithm was used to reduce printing time. The method was evaluated with 3D concrete printing experiments after introducing the process of implementing the partition algorithm and ant colony algorithm. The experiment results show a significant reduction in the idle strokes and the nozzle head-up times of the running path planned by the method in this paper. This has a direct impact on shortening the printing time and improving the forming quality. Compared with the other three conventional algorithms, the idle strokes of the nozzle planned by the method in this paper are reduced by 18.94%, 37.88%, and 66.67%, and the nozzle head-up times are reduced by 1.59%, 2.15%, and 8.69%. It provides a practical reference for the path optimization of 3D concrete printing

A New Belief-based Incomplete Pattern Unsupervised Classification Method

The clustering of incomplete patterns is a very challenging task because the estimations may negatively affect the distribution of real centers and thus cause uncertainty and imprecision in the results. To address this problem, a new belief-based incomplete pattern unsupervised classification method (BPC) is proposed in this paper. Firstly, the complete patterns are grouped into a few clusters by a classical soft method like fuzzy c-means to obtain the corresponding reliable centers and thereby are partitioned into reliable patterns and unreliable ones by an optimization method. Secondly, a basic classifier trained by reliable patterns is employed to classifies unreliable patterns and the incomplete patterns edited by the neighbors. In this way, most of the edited incomplete patterns can be submitted to specific clusters. Finally, some ambiguous patterns will be carefully repartitioned again by a new distance-based rule depending on the obtained reliable centers and belief functions theory. By doing this, a few patterns that are very difficult to classify between different specific clusters will be reasonably submitted to meta-cluster which can characterize the uncertainty and imprecision of the clusters due to missing values. The simulation results show that the BPC has the potential to deal with real datasets

A Survey Of Mobile Crowdsensing Techniques

Mobile crowdsensing serves as a critical building block for emerging Internet of Things (IoT) applications. However, the sensing devices continuously generate a large amount of data, which consumes much resources (e.g., bandwidth, energy, and storage) and may sacrifice the Quality-of-Service (QoS) of applications. Prior work has demonstrated that there is significant redundancy in the content of the sensed data. By judiciously reducing redundant data, data size and load can be significantly reduced, thereby reducing resource cost and facilitating the timely delivery of unique, probably critical information and enhancing QoS. This article presents a survey of existing works on mobile crowdsensing strategies with an emphasis on reducing resource cost and achieving high QoS. We start by introducing the motivation for this survey and present the necessary background of crowdsensing and IoT. We then present various mobile crowdsensing strategies and discuss their strengths and limitations. Finally, we discuss future research directions for mobile crowdsensing for IoT. The survey addresses a broad range of techniques, methods, models, systems, and applications related to mobile crowdsensing and IoT. Our goal is not only to analyze and compare the strategies proposed in prior works, but also to discuss their applicability toward the IoT and provide guidance on future research directions for mobile crowdsensing