This study examines farmers' intentions towards pro-environmental behavior in a famous tourist village in China called Guanshan, whose ecological environment is polluted. By adopting the empirically ...validated norm activation model (NAM) of Schwartz and merging it with Vroom's expectancy theory, the current research aims to develop a refined framework for understanding the formation of and predicting changes in pro-environmental intention. Field surveys were conducted in Guanshan, which resulted in sample data consisting of 275 valid responses collected by the research team. We develop a refined model, including six latent variables and 24 observational items. The structural equation modeling results show that the final model enjoys a better predictive accuracy of pro-environmental intention than does the original NAM. The study also discovers that the motivational force of expectancy theory significantly influences pro-environmental intention, whose motivational force comes from the impact of valence and expectancy. The pro-environmental intentions of farmers are mainly affected by the environmental personal norm and by a certain degree of personal expectancy. The improvement of farmers' pro-environmental intention needs be promoted in two approaches: the cultivation of personal environmental protection norms and the guidance of producing a desired expectation for pro-environmental intention.
•The presence of increased loudness and roughness in the soundscape of nursing homes may lead to elevated heart rate and an increased risk of cardiovascular health issues among the elderly ...population.•The moderate elevation of LAeq levels in the outdoor dynamic scenes within nursing homes may have a positively stimulating effect on the physiological function of older individuals.•Preference for different sound source types may have a significant effect on physiological indicators in older adults.
This research explores the impact of outdoor soundscapes at nursing homes on the physiological health of older adults. Using virtual reality, the study recreated the outdoor environments at nursing homes for 57 seniors in a lab setting, continuously monitoring physiological indicators such as skin conductance level, heart rate, low to high-frequency heart rate variability ratio, respiratory frequency, blink frequency, and pupil diameter. The comparison of these indicators with corresponding soundscapes revealed the diverse effects of different nursing home outdoor scenarios on the physiological health of older adults. Furthermore, analysis of the temporal marginal effects of these indicators highlighted the significant influence of time on the physiological responses of seniors in various soundscapes, showing fluctuations in each indicator at different times. Finally, to understand the channels of impact, the study examined how acoustic features at nursing homes affect seniors' physiological indicators. The findings suggest that increased loudness and roughness in soundscapes elevate seniors' heart rates and cardiovascular risks, while a moderate increase in LAeq and fluctuation strength in dynamic scenarios might have positive stimulative effects on the physiological functions of the older adults.
This study explores the physiological and psychological recovery effects of outdoor soundscapes on the elderly in urban nursing homes. In this study, virtual reality technology was used to reproduce ...the outdoor audio-visual environment of a nursing home for 29 older adults in a laboratory environment. The experiment used a within-group design to measure the participants' physical and psychological responses. The physiological indicators included skin conductance level (SCL), heart rate (HR), heart rate variability (HRV), respiratory rate (RF), and blink frequency (BF), and the psychological indicators included emotional level and attention. This study confirmed that the outdoor soundscape in nursing homes has inductive and restorative physiological and psychological effects on elderly people by comparing the data from the audio-visual experiment and the pure video experiment. Additionally, it was found that an environment that is too quiet has the potential to impair the mental state of elderly people. We also found that in addition to SCL and HR, many physiological indicators showed noticeable changes after 1 min. Time trends in changes in SCL and positive mood indicators were statistically significant. The data and findings of this study can be widely used in future in-depth research on aged care settings.
•Confirmed the physiological and psychological effects of outdoor soundscape in nursing homes on inducing recovery of the elderly.•The overly quiet environment can potentially impair the mental state of the elderly.•The time trends in changes in physiological and psychological indexes of the elderly under different acoustics environmental Settings.•Scales, measurements, and testing methods suitable for VR experiments with elderly participants.
•Proposed two Responsibility-Sensitive Safety (RSS) based longitudinal driving capability indicators.•Utilized Bayesian Tobit quantile regression (BTQR) models to quantify driving capability with ...trip level characteristics•Presented case studies for longitudinal driving capability assessment.•Discussed model applications for fleet safety management and autonomous vehicle (AV) performance evaluations.
Given the severe traffic safety issue, tremendous efforts have been devoted to identify the crash contributing factors for developing and implementing safety improvement countermeasures. According to the study findings, driving behaviors have attributed to the majority crash occurrence, among which inadequate driving capability is a key factor. Therefore, a number of studies have been conducted for developing techniques associated with the driving capability assessment and its various improvement. However, the conventional assessment approaches, such as driving license exams and vehicle insurance quotes, have only focused on basic driving skill evaluations or aggregated driving style classifications, which failed to quantify driving capability from the safety perspective with respect to the complex driving scenarios. In this study, a novel longitudinal driving capacity assessment and ranking approach was developed with naturalistic driving data. Two Responsibility-Sensitive Safety (RSS) based driving capability indicators from the perspectives of risk exposure and severity were first proposed. Then, Bayesian Tobit quantile regression (BTQR) models were introduced to explore the relationships between driving capability indicators with trip level characteristics from the aspects of travel features, operational conditions, and roadway characteristics. The modeling results concluded that nighttime driving and higher average speed would lead to higher longitudinal collision risk and its severity. Besides, the BTQR models have provided varying factors significances among different quantile levels, for instance, driving duration is only significant at high quantiles for the driving capability indicators, implying that duration only affects drivers with large longitudinal risk exposures and strong close following tendencies. Furthermore, the case studies provided how to deploy the developed model to obtain the relative longitudinal driving capability rankings. Finally, the model applications from the aspects of commercial fleet safety management and comparing the autonomous vehicles’ longitudinal driving behaviors with human drivers have been discussed.
Car-sharing is a representative of the sharing economy in the field of transportation, which provides drivers with more economical and flexible approaches for car ownership and usage. Currently the ...car-sharing users are mainly young and novice drivers with frequent risky driving behaviors and traffic crashes. The risky driving behaviors have led to a sharp increase in the cost of maintenance and insurance for car-sharing enterprises, and the crashes have also increased the operational risks of roadway traffic. Therefore, it is urgent to conduct analyses for driving style classifications in order to identify potential high-risk drivers. In this study, we conducted a driving style analysis based on the operation data of a car-sharing project located in Shanghai. Rather than the high resolution driving behavior data that adopted in the majority driving style studies, low-frequency trajectory data were utilized here. Relative speeding time ratios of freeway, urban expressway and urban road were used as analysis variables and K-Means clustering technique was used to classify the drivers' driving styles. A total of three categories were concluded, which are aggressive, calm and novice with the percentages of 28.33%, 66.67%, and 5.00% correspondingly. Then, for the purpose of understanding the different driving styles, comparison analyses were further conducted from the aspects of vehicle operation features and personal information. The results suggested that drivers have substantial differences in their vehicle operation characteristics. The aggressive drivers tend to drive faster, have higher speeding tendency, better speed stability and higher skills; while the novice drivers reported highest speeding tendency on freeway, lowest operating speed and speed stability. Besides, no statistically significant differences in age, gender or violation between driving styles were identified.
OBJECTIVE： To investigate the effects of Yindanxinnaotong capsule（YDXNTC） and main components compatibility and ratios on myocardium against ischemia/reperfusion injury and the effect＇s underlying ...mechanism.METHODS： Myocardial ischemia/reperfusion injury（MIRI） was induced by ischemia for 30 min and reperfusion for 30 min. Electrocardiogram data and coronary flow were recorded, and superoxide dismutase（SOD）, malondialdehyde（MDA）, lactate dehydrogenase, creatine kinase-MB, cardiac troponin T and I（cT nT, cT n I） and interleukin-1β, interleukin-8,interleukin-18（IL-1β, IL-8, IL-18） in myocardium were measured. Hypoxia/reoxygenation and hydrogen peroxide（H2O2） injury were induced by hypoxia for 3 h/reoxygenation for 2 h, and 100 μM H2O2 for 1 h, respectively, in vitro rat myocardial cells（H9c2）. Cell viability, SOD, MDA, cT nT and inflamma-tory factors（IL-1β, IL-8 and IL-18） were determined,and Toll-like receptor 4（TLR-4） expression was measured by western blotting.RESULTS： In the isolated heart experiment, elevated heart function, coronary flow and SOD levels,and decreased MDA levels and inflammatory factors were noted in the YDXNTC, main components and main components compatibility groups. Ventricular tachycardia/ventricular fibrillation occurrence decreased in the ginkgo biloba extract（GBE）,and GBE and salvia miltiorrhiza ethanol extract compatibility（SM-E, GSEC） groups. Lactic dehydrogenase levels decreased in the YDXNTC and aqueous extract of salvia miltiorrhiza（SM-H） groups. Creatine kinase-MB decreased with GBE, SM-E, SM-H and GSEC treatment, and cT n I and cT nT levels decreased with GSEC. In the in vitro cell study,YDXNTC and main components ratios improved cell viability and SOD levels, and suppressed MDA,cT nT and inflammatory factors. TLR-4 expression was down-regulated.CONCLUSION： YDXNTC and main components compatibility showed protective effects on MIRI in this rat model and in vitro study. Regulating the Toll-like receptor signaling pathway may affect the mechanism.
Based on learning theory, we adopt a stochastic learning updating rule to investigate the evolution of cooperation in the Prisoner's Dilemma game on Newman-Watts small-world networks with different ...payoff aspiration levels. Interestingly, simulation results show that the mechanism of intermediate aspiration promoting cooperation resembles a resonancelike behavior, and there exists a ping-pong vibration of cooperation for large payoff aspiration. To explain the nontrivial dependence of the cooperation level on the aspiration level, we investigate the fractions of links, provide analytical results of the cooperation level, and find that the simulation results are in close agreement with analytical ones. Our work may be helpful in understanding the cooperative behavior induced by the aspiration level in society.
•Truncated cube-like NiSe2 single crystals were synthesized using solvothermal method.•A high specific capacitance was achieved under a mass loading of 3.90mgcm−2.•Morphology change and impedance ...increase are responsible for worse cycle performance.•The asymmetric supercapacitors possess high energy density and power density.
Numerous electrode materials have been studied in supercapacitors for next-generation energy storage applications. As a paramagnetic metal with low resistivity, NiSe2 has received much attention and been used extensively in many applications, including energy storage, electrocatalysts, and high temperature superconductors, etc. However, the capacitive properties of NiSe2 are rarely investigated. In the present work, truncated cube-like NiSe2 single crystals are synthesized by a facile hydrothermal approach and further used as electrode material in supercapacitors. The effects of different loading mass of electrode material on electrochemical capacitive behaviors are also investigated. Experimental results demonstrate that under a mass loading of 3.90mgcm−2, the as-prepared NiSe2 electrode exhibits a high specific capacitance of 1044Fg−1 at 3Ag−1 (or an areal capacitance of 4.07Fcm−2), along with an excellent rate capability (601Fg−1 at 30Ag−1). Besides, the morphology change and the impedance increasement are responsible for the worse cycling performance of NiSe2 electrode in the three-electrode system. Meanwhile, the practical electrochemical energy storage behavior of as-synthesized NiSe2 is investigated in an asymmetric supercapacitor. The NiSe2//activated carbon (AC) asymmetric device possesses an outstanding cycle life (87.4% after 20,000 successive cycles), a high energy density of 44.8Whkg−1 at 969.7Wkg−1 and a higher power density of 17.2kWkg−1 at 17.4Whkg−1, showing attractive potential in practical applications. This work opens avenue for utilizing single crystal NiSe2 as electrode material and providing important guidance to the further investigation of nickel selenides for advanced supercapacitors.
Solar radiation, especially ultraviolet (UV) light, is a major hazard for most skin‐related cancers. The growing needs for wearable health monitoring systems call for a high‐performance real‐time UV ...sensor to prevent skin diseases caused by excess UV exposure. To this end, here a novel self‐powered p‐CuZnS/n‐TiO2 UV photodetector (PD) with high performance is successfully developed (responsivity of 2.54 mA W−1 at 0 V toward 300 nm). Moreover, by effectively replacing the Ti foil with a thin Ti wire for the anodization process, the conventional planar rigid device is artfully turned into a fiber‐shaped flexible and wearable one. The fiber‐shaped device shows an outstanding responsivity of 640 A W−1, external quantum efficiency of 2.3 × 105%, and photocurrent of ≈4 mA at 3 V, exceeding those of most current UV PDs. Its ultrahigh photocurrent enables it to be easily integrated with commercial electronics to function as a real‐time monitor system. Thus, the first real‐time wearable UV radiation sensor that reads out ambient UV power density and transmits data to smart phones via wifi is demonstrated. This work not only presents a promising wearable health monitor, but also provides a general strategy for designing and fabricating smart wearable electronic devices.
A real‐time wearable UV sensor for prevention of skin cancers caused by excess UV radiation exposure is demonstrated. The fiber‐shaped device consisting of a novel p‐CuZnS/n‐TiO2 nanotube array structure exhibits an outstanding photocurrent and external quantum efficiency, a fast response speed, and self‐powered property, which make it a promising wearable real‐time health monitor.
The human brain can be regarded as a complex network with interacting connections between brain regions. Complex brain network analyses have been widely applied to functional magnetic resonance ...imaging (fMRI) data and have revealed the existence of community structures in brain networks. The identification of communities may provide insight into understanding the topological functions of brain networks. Among various community detection methods, the modularity maximization (MM) method has the advantages of model conciseness, fast convergence and strong adaptability to large-scale networks and has been extended from single-layer networks to multilayer networks to investigate the community structure changes of brain networks. However, the problems of MM, suffering from instability and failing to detect hierarchical community structure in networks, largely limit the application of MM in the community detection of brain networks. In this study, we proposed the weighted modularity maximization (WMM) method by using the weight matrix to weight the adjacency matrix and improve the performance of MM. Moreover, we further proposed the two-step WMM method to detect the hierarchical community structures of networks by utilizing node attributes. The results of the synthetic networks without node attributes demonstrated that WMM showed better partition accuracy than both MM and robust MM and better stability than MM. The two-step WMM method showed better accuracy of community partitioning than WMM for synthetic networks with node attributes. Moreover, the results of resting state fMRI (rs-fMRI) data showed that two-step WMM had the advantage of detecting the hierarchical communities over WMM and was more insensitive to the density of the rs-fMRI networks than WMM.
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