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Objectives The objective of this study was to explore the relationship between seat armrest height and human neck comfort when using a smartphone while sitting on a passenger seat during the flight. Material and Methods The authors used a wireless angle-measuring instrument and subjective comfort scale to evaluate the changes of head flexion angle and neck comfort level of 24 young smartphone users in an aircraft simulated cabin. Results The study results indicated that using a smartphone while sitting on a passenger seat during the flight would pose a larger discomfort to the neck, and the discomfort would be higher for gaming than reading tasks. Seat armrest height is related to the comfort level of the neck when using a smartphone, increasing the height of the armrest can effectively alleviate discomfort in this state. Conclusions Considering the prevalence of passengers using smartphones in aircraft, a seat armrest that can be properly adjusted in height, which can effectively reduce the risk of passenger head flexion angle and neck discomfort. Int J Occup Med Environ Health. 2022;35(2):199–208

Objectives The purpose of this paper is to investigate the effects of the seat cushion contour and the sitting posture on the seat pan interface pressure distribution and subjective comfort perception. Material and Methods Overall, 16 volunteers typed a text passage on a laptop while seated, by assuming 3 kinds of common sitting postures (forward, relaxed and upright) in 4 seat cushion configurations: chair only, and chair with 1 of 3 supplementary cushions. Pressure data and cushion comfort ratings were collected in the experiment. Results It was found that the sitting posture and the seat cushion contour had different impacts on surface pressure. The seat cushion contour had an impact on pressure parameters and pressure distribution on the seat pan, while the sitting posture affected the location of peak pressure on the seat pan. The correlation analysis revealed that the subjective comfort rating was significantly correlated with average pressure (AP) and mean peak pressure (MPP). Conclusions The conclusion was that the cushion contour had a greater effect on seat pan interface pressure parameters than the sitting posture. Notably, AP and MPP can be indicators for assessing seat cushion comfort in a short-term perspective. Int J Occup Med Environ Health. 2020;33(5):675–89

The assessment of indoor thermal environments is crucial to achieving thermal comfort and energy efficiency. However, the inaccurate evaluation and strong nonlinear variations of thermal comfort parameters limit engineering designs. Therefore, a coupled heat-transfer model was developed in this study, and large eddy simulations were performed to verify the influence of inertia and buoyancy—which are mutually exclusive forces but coexist in large-space building environments—on inhomogeneous thermal environments. Furthermore, an artificial neural network (ANN) model was designed to overcome the limitations of the nonlinear relationships between thermal parameters and predicted mean vote (PMV) values. PMV indexes can be predicted using the ANN model when thermal parameters are used as input data. Subsequently, a genetic algorithm, harmony search algorithm, gravitational search algorithm, and whale optimization algorithm were adopted to optimize the neural network structure to prevent its confinement in a local optimum. Finally, with 5000 data sets, the minimum-error neural network structure 6-22-23-1 of the ANN-GA neural network model had high prediction accuracy, mean relative error < 1.38, root mean square error < 1.34, and a regression coefficient of ~1. The proposed ANN model can help improve the assessment of the thermal environment and thermal comfort of buildings.

Objectives The objective of this study was to assess the postures that were commonly used in automobile chassis repair operations, and to evaluate shoulder girdle muscle fatigue for different combinations of the weight of hand-tools. Material and Methods Two right muscles, including upper trapezius (UT) and middle deltoid (MD), were selected. Surface electromyography (SEMG) and a perceived level of discomfort (PLD) were used to assess the degree of shoulder girdle fatigue. Fifteen healthy young male subjects from the Northwestern Polytechnical University participated in the test. The test consisted of assuming 4 different postures and maintaining each of them for 60 s. The 4 postures varied in terms of dumbbell weights, standing for the hand-tools weight: W1 was 0.48 kg and W2 was 0.75 kg; the 4 shoulder postures were shoulder flexions of 150°, 120°, 90°, and 60°, combined with an included elbow angle of 180°, 150°, 120° and 90°, respectively. The experimental sequences were randomly selected. The signals of SEMG and the values of PLD in the shoulder girdle were recorded in 60 s. All subjects completed the whole test. The repeated measure analysis of variance (ANOVA) was performed to ascertain differences between dumbbell weight (0.48 kg and 0.75 kg) and shoulder postures (150°/180°, 120°/150°, 90°/120° and 60°/90°). The Friedman test was utilized to determine the significant differences for UT(PLD) and MD(PLD) on shoulder postures. Spearman’s correlation was used to analyze the relationship between the subjective and objective measurements. Results Significant correlational relationships existed between the UT percentage of the maximal voluntary electrical activation (%MVE) and UT(PLD) (r = 0.459, p < 0.01), between MD(%MVE) and MD(PLD) (r = 0.821, p < 0.01). The results showed that SEMG and PLD of the 4 postures under analysis differed significantly (p < 0.05). Conclusions It was indicated that posture T4 (shoulder forward flexion 60° and included elbow angle 90°) resulted in the lowest fatigue, both in terms of the objective measure and the subjective perception, which meant that this posture was more ergonomic. Int J Occup Med Environ Health. 2019;32(4):537–52

Safety is always acritical focus of exploration of ocean resources, and it is well recognized that human factor is one of the major causes of accidents and breakdowns. Our research developed a dynamic human reliability assessment approach, Predicted Mean Vote-Cognitive Reliability and Error Analysis Method (PMV-CREAM), that is applicable to monitoring the cognitive reliability of oceanauts during deep-sea missions. Taking into account the difficult and variable operating environment of manned submersibles, this paper analyzed the cognitive actions of oceanauts during the various procedures required by deep-sea missions, and calculated the PMV index using human factors and dynamic environmental data. The Cognitive Failure Probabilities (CFP) were calculated using the extended CREAM approach. Finally, the CFP were corrected using the PMV index. This PMV-CREAM hybrid model can be utilized to avoid human error in deep-sea research, thereby preventing injury and loss of life during undersea work. This paper verified the method with “Jiaolong” manned submersible 7,000 m dive test. The“Jiaolong” oceanauts CR(Corrected CFP) is dynamic from 3.0615E-3 to 4.2948E-3, the CR caused by the environment is 1.2333E-3. The result shown the PMV-CREAM method could describe the dynamic human reliability of manned submersible caused by thermal environment. Keywords: Manned submersible, Deep sea exploration, Predicted Mean Vote (PMV), Human Reliability Analysis (HRA), Human factors, Cognitive behavior

Crowdsourcing services and cloud-based design and manufacturing platforms have been combined into an emerging network service model. Due to the diversity and differences of crowdsourcing members in the platform, member optimized selection process is uncertain and discrete, and it is difficult to find the most satisfying solution. In view of this, this article proposed an optimized selection strategy of crowdsourcing members to help users select reasonable crowdsourcing members to form the cooperative team with the most satisfaction. The research steps in this article are as follows. The first step is to analyze the characteristics of crowdsourcing services and crowdsourcing members in the cloud-based design and manufacturing platform. In the second step, according to the characteristics of crowdsourcing members, the evaluation index and target variables of members in the optimized process are proposed, the optimized selection system is established, and the calculation based on each target variable is given. In the third step, the decision-making model is established based on the optimized selection index system. The model decomposes the task-oriented global optimized selection indexes for crowdsourcing members into subtask-oriented local optimized selection indexes, and the gray relational analysis method is used to solve the model. Finally, the effectiveness of the proposed method is verified by taking the crowdsourcing member optimized selection process in the medical product research and development task as an example.

Background: Sit-stand workstations are available for office work purposes but there is a dearth of quantitative evidence to state benefits for lower limb outcomes while using them. And there are no guidelines on what constitutes appropriate sit/stand time duration. The primary aim of this study has been to compare muscle activity and perceived discomfort in the lower extremity during various combinations of sit/stand time duration associated with a sit-stand workstation separately and to evaluate the effects of the sit-stand workstation on the lower extremity during the text entry task. Material and Methods: During the 5 days, all participants completed a 2-h text entry task each day for various sit/stand time duration combinations as follows: 5/25 min, 10/20 min, 15/15 min, 20/10 min, 25/5 min. Lower extremity muscular exposure of 12 male and 13 female participants was collected at 8 sites by surface electromyography and body discomfort was calculated by a questionnaire under those 5 conditions. Results: Results have demonstrated that lower extremity muscle activity has been significantly varied among the 5 sit/stand time duration groups. Perceived level of discomfort (PLD) has not differed significantly for 9 out of 10 body parts. Conclusions: The muscle activity of the thigh region was influenced by sit/stand time duration significantly. Ergonomic exposures of lower extremity when using a sit-stand workstation were increased, particularly during the long time standing posture. Results indicate that body mass index (BMI) and gender were not significant factors in this study. Combination of sit/stand time duration 25/5 min appears to show positive effects on relief of muscle exposure of back of thigh in the shifts of sitting and standing work position. Med Pr 2017;68(3):315–327

Renal fibrosis is the common pathological foundation of many chronic kidney diseases (CKDs). The aim of this study was to investigate whether Hydroxysafflor yellow A (HSYA) can preserve renal function by inhibiting the progression of renal fibrosis and the potential mechanisms.Renal fibrosis was induced by unilateral ureteral obstruction (UUO) performed on 7-week-old C57BL/6 mice. HSYA (10, 50 and 100 mg/kg) were intragastrically administered. Sham group and model group were administered with the same volume of vehicle. Serum and kidney samples were collected 14 days after the UUO surgery. Serum biochemical indicators were measured by automatic biochemical analyzer. Histological changes were evaluated by HE and Masson staining. In vitro, the anti-fibrotic effect of HSYA was tested on human recombinant transforming growth factor-β1 (TGF-β1) stimulated HK-2 cells. The protein levels of α-SMA, collagen-I and fibronectin in kidney tissue and HK-2 cells were measured by immunohistochemistry and immunofluorescence. The protein levels of apoptosis-relative and TGF-β1/Smad3 signaling were detected by western blot.HSYA slowed the development of renal fibrosis both in vivo and in vitro. In UUO rats, renal function index suggested that HSYA treatment decreased the level of serum creatinine (Scr) and blood urea nitrogen (BUN) rose by UUO (P

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design. This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph. Specifically, the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data, and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design. Moreover, the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module, and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module. Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model. The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge. [ABSTRACT FROM AUTHOR]