Interrelation of structure and operational states in cascading failure of overloading lines in power grids

As the modern power system is expected to develop to a more intelligent and efficientversion, i.e. the smart grid, or to be the central backbone of energy internet for freeenergyinteractions,securityconcernsrelatedtocascadingfailureshavebeenraisedwithconsideration of catastrophic results. The researches of topological analysis based oncomplex networks have made great contributions in revealing structural vulnerabilitiesof power grids including cascading failure analysis. However, existing literature withinappropriate assumptions in modeling still cannot distinguish the effects between thestructure and operational state to give meaningful guidance for system operation. Thispaper is to reveal the interrelation between network structure and operational statesin cascading failure and give quantitative evaluation by integrating both perspectives.For structure analysis, cascading paths will be identified by extended betweenness andquantitatively described by cascading drop and cascading gradient. Furthermore, theoperational state for cascading paths will be described by loading level. Then, the riskof cascading failure along a specific cascading path can be quantitatively evaluatedconsideringthesetwofactors.Themaximumcascadinggradientofallpossiblecascadingpaths can be used as an overall metric to evaluate the entire power grid for its featuresrelated to cascading failure. The proposed method is tested and verified on IEEE30-bussystem and IEEE118-bus system, simulation evidences presented in this paper suggest

Captopril reverses chronic unpredictable mild stress-induced depression-like behavior in rats via bradykinin-B2r signaling pathway

Purpose: To investigate the effect of captopril on chronic unpredictable mild stress (CUMS)-induced depression-like behavior in mice, and the involvement of the bradykinin-B2r signaling pathway in the process. Methods: Sixty healthy male C57BL/6J mice were assigned to control, model and high-, medium- and low-dose captopril groups and given the drug at doses of 9, 18 and 36 mg/kg, respectively. Open field and elevated cross maze tests were carried out, and escape latency in Morris water maze test was also test. The expressions of bradykinin B2R signal pathway proteins were assayed. Results: Open arm residence time and open arm entry times were significantly higher in captopril-exposed mice than in model mice, while 5-day escape latency values were significantly less in captopril-treated mice than in model group (p < 0.05). Protein expressions of B2R, bpnf and Cdc42 in captopril groups were significantly higher than those in model group (p < 0.05). Conclusion: Captopril mitigates CUMS-mediated depression-like disease in mice by regulating bradykinin B2R signal pathway. Therefore, captopril may play an antidepressant role by activating the expressions of B2R, bpnf and Cdc42

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

Energy-Efficient Train Control with Onboard Energy Storage Systems considering Stochastic Regenerative Braking Energy

With the rapid development of energy storage technology, onboard energy storage systems(OESS) have been applied in modern railway systems to help reduce energy consumption. In addition, regenerative braking energy utilization is becoming increasingly important to avoid energy waste in the railway systems, undermining the sustainability of urban railway transportation. However, the intelligent energy management of the trains equipped with OESSs considering regenerative braking energy utilization is still rare in the field. This paper considers the stochastic characteristics of the regenerative braking power distributed in railway power networks. It concurrently optimizes the train trajectory with OESS and regenerative braking energy utilization. The expected regenerative braking power distribution can be obtained based on the Monte-Carlo simulation of the train timetable. Then, the integrated optimization using mixed integer linear programming (MILP) can be conducted and combined with the expected available regenerative braking energy. A generic four-station railway system powered by one traction substation is modeled and simulated for the study. The results show that by applying the proposed method, 68.8% of the expected regenerative braking energy in the environment will be further utilized. The expected amount of energy from the traction substation is reduced by 22.0% using the proposed train control method to recover more regenerative braking energy from improved energy interactions between trains and OESSs

The influence of different conflict management styles on depressive symptoms in employees: the mediating role of emotional exhaustion

Although some studies have found that conflict management styles impact employees' levels of depression, the expressions of employees' depressive symptoms under various conflict management styles and the underlying mechanisms remain to be elucidated. In this study, a total of 1,312 employees were gathered through an online survey to examine their current depressive status. Drawing on the conservation of resources theory, the mediating role of emotional exhaustion in the association between conflict management style and employee depression was further explored. The findings revealed that the prevalence of moderate to severe depression among the workers was 13.9%. Employees with different conflict management styles displayed distinct depression scores. The high coordination style group exhibited a significantly lower depression score compared to the high concession style group. Emotional exhaustion played a mediating role in the impact of both the coordination style and the concession style on employees' depression. It can be seen that the mental health needs of the workplace are imminent. The intervention measures to improve the mental health of employees in the working environment should take into account the cultivation of the coordination style of employee conflict management, reduce their emotional exhaustion, and stay away from depression through the acquisition of constructive and positive coping styles

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes