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A Dynamic Adaptational Process Theory of Resilience (ADAPTOR) incorporates a synchronistic interplay of reserve capacity, adaptation, and consequences in the context of the larger exposome. This conceptualization of resilience centers on the argument that individuals can "build" resilience by drawing upon their various reserve capacities to effectively adapt to challenging contextual factors, and that this process has long-term consequences for health and wellness trajectories. These theoretical arguments were tested using the Notre Dame Study of Health & Well-Being–COVID Study, which is a multitimescale, longitudinal study of data collected from September 2020 through February 2022. We included 444 participants (age range = 26–90, M = 62.23, SD = 14.26), and used hierarchical linear modeling to assess the effects of global perceptions of stress reactivity (reserve capacity), daily affective reactivity (adaptation), as well as negative pandemic exposure (exposome) on trajectories of depression and anxiety (consequences) across the COVID-19 pandemic. Most pertinent to ADAPTOR, an interactive effect indicated that reserve capacity and adaptation may serve compensatory roles for one another in the context of a more stressful exposome, whereas the synchrony between reserve capacity and adaptation may be important in the context of a less stressful exposome. These findings support the ADAPTOR framework, such that reserve capacity, adaptation, the exposome, and their confluence differentially impact various consequences. This ultimately highlights the importance of taking a dynamic, process-oriented, and multifaceted approach to studying resilience. Public Significance Statement: This article details "A Dynamic Adaptational Processes Theory of Resilience (ADAPTOR)," a novel metatheory that incorporates several resilience conceptualizations into a developmental framework. The key argument of ADAPTOR is that individuals can "build" resilience by utilizing their reserve capacities to adapt to challenging contextual factors, and that this process has long-term health consequences. An empirical example supported ADAPTOR, indicating that reserve capacity, adaptation, and contextual factors, together, predict mental health. [ABSTRACT FROM AUTHOR]

Introduction: Frailty is significantly correlated with a higher incidence of medical complications during hospitalization after esophagectomy. As frailty is thought to be a reversible condition, improving the reserve capacity through preoperative physical therapy is expected to reduce the risk of postoperative pulmonary complications (PPCs). Herein, we report our experience with preoperative physical therapy in a patient with esophageal cancer who was considered to have inadequate fitness for surgery owing to poor physical performance. Case Presentation: A 72‐year‐old man (height: 169.5 cm, weight: 54.7 kg, body mass index: 18.9 kg/m2) with esophagogastric junction tumors (cStage IIIA) was hospitalized and scheduled to undergo surgery based on preoperative screening. He was categorized as frail according to the revised Japanese version of the Cardiovascular Health Study criteria and the Mini Nutritional Assessment Short‐Form indicated severe malnutrition. We focused on physical therapy to improve exercise tolerance and prevent PPCs and devised a short‐term intensive physical therapy program comprising minimal exercises that the patient could perform efficiently. The program consisted of only inspiratory muscle training and aerobic exercises. His maximal inspiratory pressure (MIP) and 6‐min walking distance improved by 30 cm H2O and 145 m, respectively, on the day before surgery compared with those on day 8. The percentage predicted value of the MIP improved from 56.6% at the start of physical therapy to 102.9% on the day before surgery. On day 43, the patient underwent subtotal esophagectomy and was able to ambulate on postoperative day 5 without respiratory complications. Conclusion: We conducted a short‐term, intensive, and minimal preoperative physical therapy program for a patient with esophageal cancer who had physical frailty. Preoperative physical therapy to increase the reserve capacity may result in a favorable postoperative course even in patients with physical frailty. [ABSTRACT FROM AUTHOR]

Ride-sharing is one of the effective method to reduce car ownership, thus it may have a profound impact on the reserve capacity of road network. However, it’s unclear the relationships among users’ ridesharing behaviors, travel demand pattern and the reserve capacity of road network. To this end, this paper builds a ridesharing trip-assignment model which considers users’ ridesharing choice, destination choice and path choice, and further proposes a bi-level programming for reserve capacity of road network with ride-sharing. The bi-level programming is then converted into an equivalent single-layer optimization problem by a conventional relaxation scheme. Finally, numerical experiments are conducted to provide valuable insights and examine the effectiveness of the proposed model. The results show that subsidizing ridesharing drivers can improve almost as much reserve capacity of road network as expanding link capacity without ridesharing. However, retrofitting High-Occupancy Toll (HOT) lane has limited impact on improving reserve capacity of road network.

With the wide application of the gas-power system, gas-power coupling equipment such as gas turbines are gradually becoming widely used, and the problem of insufficient system reserve capacity needs to be solved. In order to improve the operational flexibility of the gas-power system, this paper combines the source side, the load side, and the energy storage side to propose a multi-type backup system, and constructs the source-load-storage multiple reserve capacity system of the gas-power system. Through the participation of gas turbine, steam turbine, interruptible load, and energy storage battery to provide reserve capacity, it can fully cope with the output fluctuation of the load side and source side and realize the coordinated operation of multiple resources to provide reserve capacity. In addition, the coordination of gas turbines and steam turbines can further improve the operation flexibility of the gas-power system. Through the example analysis, it was found that the proposed method reduced the total operating cost of the system by 10.6%. [ABSTRACT FROM AUTHOR]

Geroscience offers a counterpoint to the challenged pursuit of curing diseases of aging, by focusing on slowing the biological aging process for extended healthspan earlier in life. Remarkable progress has led this field toward animal trials and the next challenge lies with translation to humans. There is an emerging number of small human trials that can take advantage of new models integrating behavioral and social factors. Understanding dynamic aging mechanisms, given the powerful social determinants of aging (Crimmins, 2020) and human variability and environmental contexts (Moffitt, 2020), will be critical. Behavioral and social factors are intrinsic to aging. Toxic stressors broadly defined can lead to stress-acceleration of aging, either directly impacting aging processes or by shaping poor behavioral health, and underlie the socioeconomic disparities of aging. In contrast, hormetic stressors, acute intermittent stressors of moderate intensity, can produce stress resilience, the ability for quick recovery and possibly rejuvenation of cells and tissues. Although health research usually examines static biomarkers, aging is reflected in dynamic ability to recover from challenges pointing to new interventions and targets for examining mechanisms. A fuller model incorporating stress resilience provides innovative biobehavioral interventions, both for bolstering response to challenges, such as COVID-19, and for improving healthspan.

Existing studies estimate the economic value (EcV) of network reliability and robustness separately. In this study, a model is proposed for estimating the EcV of reserve capacity in a rail transit network (RTN), which consists of: (1) the reduction of passengers’ total generalized travel cost (GTC) in normal operations, (2) the EcVof reliability enhancement in normal operations, and (3) the EcVof robustness enhancement when disturbances occur. The standard deviation of travel time (SDT) is used to measure travel time reliability (TTR). The reserve capacity helps to reduce passengers’ total GTC and the SDT during normal operations. The EcV of reliability enhancement equals the EcV converted from the reduction in SDT when the RTN operates normally. The EcV of robustness enhancement is the difference of passengers’ total GTC with and without reserve capacity when disturbances occur. To optimize reserve capacity, a model is developed to maximize its net benefit, equaling its EcV minus its cost, which is then solved with a quantum genetic algorithm. A case study of Chengdu’s RTN shows the effectiveness of the model with promising numerical results. The research findings show that the value of reserve capacity is severely underestimated without considering the EcV of reliability and robustness. The study can guide policymakers and operators in quantifying the EcV of reliability and robustness enhancement when expanding an RTN’s capacity. [ABSTRACT FROM AUTHOR]

A primary goal of research in cognitive impairment and dementia is to understand how some individuals retain sufficient cognitive function for a fulfilling life while many others are robbed of their independence, sometimes their essence, in the last years and decades of life. In this commentary, we propose operational definitions of the types of factors that may help individuals retain cognitive function with aging. We propose operational definitions of resistance, resilience, reserve, with an eye toward how these may be measured and interpreted, and how they may enable research aimed at prevention. With operational definitions and quantification of resistance, resilience, and reserve, a focused analytic search for their determinants and correlates can be undertaken. This approach, essentially a search to identify protective risk factors and their mechanisms, represents a relatively unexplored pathway toward the identification of candidate preventive interventions.

Mitochondrial DNA (mtDNA) haplotype regulates mitochondrial structure/function and reactive oxygen species in aortocaval fistula (ACF) in mice. Here, we unravel the mitochondrial haplotype effects on cardiomyocyte mitochondrial ultrastructure and transcriptome response to ACF in vivo. Phenotypic responses and quantitative transmission electron microscopy (TEM) and RNA sequence at 3 days were determined after sham surgery or ACF in vivo in cardiomyocytes from wild-type (WT) C57BL/6J (C57n:C57mt) and C3H/HeN (C3Hn:C3Hmt) and mitochondrial nuclear exchange mice (C57n:C3Hmt or C3Hn:C57mt). Quantitative TEM of cardiomyocyte mitochondria C3HWT hearts have more electron-dense compact mitochondrial cristae compared with C57WT. In response to ACF, mitochondrial area and cristae integrity are normal in C3HWT; however, there is mitochondrial swelling, cristae lysis, and disorganization in both C57WT and MNX hearts. Tissue analysis shows that C3HWT hearts have increased autophagy, antioxidant, and glucose fatty acid oxidation-related genes compared with C57WT. Comparative transcriptomic analysis of cardiomyocytes from ACF was dependent upon mtDNA haplotype. C57mtDNA haplotype was associated with increased inflammatory/protein synthesis pathways and downregulation of bioenergetic pathways, whereas C3HmtDNA showed upregulation of autophagy genes. In conclusion, ACF in vivo shows a protective response of C3Hmt haplotype that is in large part driven by mitochondrial nuclear genome interaction. [ABSTRACT FROM AUTHOR]

Background: The UK Bangladeshi community is socially disadvantaged, and many adults suffer from obesity, diabetes, and other chronic illnesses. Rapid aging has been noted. Objectives: Analyse biosocial trade-offs in growth, adult body composition, and reproduction, which are risk factors for age-related decline in physical performance, more rapid aging, frailty, and death. Methods: Sample: 40 Bangladeshi mothers (40-70 years old), one of their adult daughters (N=37, 18-36 years old) in the United Kingdom (UK), and 22 mother-daughter pairs of the same age range in Bangladesh (BD). Measurements: anthropometry, including knee height, migration, demographic history, education level, current menstruation (yes/no), and a 7-component lower body physical function score (PFS). Analysis: ridge regression and St Nikolas House Analysis (SNHA). Results: All the women are of short stature (x̄=150cm), with especially low knee height. Daughters who migrated to the UK have shorter knee height than daughters born in the UK. Marriage age was 16-18 years and total pregnancies of ~6 per mother, ~3 per daughter. UK mothers have higher fatness and lower PFS than BD women. Greater knee height predicts greater PFS, and that greater waist circumference and older age predict a lower PFS. SNHA finds that knee height is the most direct predictor of PFS. Conclusion: Adult knee height may serve as a sensitive indicator of early life physical and emotional well-being and predict physical performance, a risk factor for frailty and death. International migration of daughters is associated with poorer health status and physical performance at later ages.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Virtual power plants (VPPs) contribute to the flexibility and economy of distributed system by leveraging integrated distributed renewable resources, optimizing energy production and consumption patterns, and facilitating dynamic grid management. However, challenges arise when multi-VPPs coordinated operate, including complex spatial and temporal correlation characteristics and conflicting interests in multi-agent decision-making. Shared energy storage (SES), as a product of the sharing economy, can be more flexible to help VPPs consume power generation from distributed renewable resources. Hence, focusing on the complementary problems and conflicts of interest between VPPs and improving the utilization of distributed renewable resources, this paper proposes an energy-reserve coordinated optimization model led by the distribution system operator (DSO) and involves the participation of both multi-VPPs and SES. Firstly, a Stackelberg-cooperative mixed game (SC-mixed game) framework is proposed for the DSO-VPP system, which leverages the DSO as the leader. The transactional electricity price between DSO and VPPs is optimized via the Stackelberg game, and the operation strategies for multi-VPPs can be calculated by the Cooperative game. Besides, an energy-reserve model is proposed for SES, which considers six reserve modes for further exploring the reserve potential of SES and guarantee the reserve provision ability. Additionally, a tailored alternating direction method of multipliers (ADMM), integrating a bisection method, is proposed to solve the SC-mixed game model efficiently. Finally, several case studies are conducted to validate the effectiveness of the proposed model. • Mixed game method combining Stackelberg game and Cooperative game is built. • Energy and reserve characteristic of SES is considered. • Operation method of multi-VPPs, DSO and SES is designed. • VPPs' internal privacy is protected by using tailored ADMM algorithm. [ABSTRACT FROM AUTHOR]

Due to the considerable number of electric vehicles and the characteristics of energy storage, it is possible for these new energy factors to participate in the operation and regulation of the power system and provide reserve service. In view of this, a multi-objective optimal scheduling model is established, aiming at the economic benefits of electricity collectors, the microgrid power fluctuations, and user satisfaction. Among them, the expression paradigm of user satisfaction is proposed. At the same time, an improved adaptive non-dominated sorting genetic algorithm (NSGA-III-W) was proposed to solve the problem of large-scale and high-dimensional multi-objective in the model. First, an adaptive T-crossover operator is proposed to increase the search and optimization capability of NSGA-III. Second, an adaptive crossover mutation mechanism is proposed to improve the convergence performance of the algorithm. In addition, a compromise solution is selected from the obtained Pareto-dominated solutions through the distance ranking method of superior and inferior solutions (TOPSIS). The improved NSGA-III algorithm, namely the NSGA-III-W algorithm, is compared with the mainstream intelligent optimization algorithms non-dominated sorting genetic algorithm II (NSGA-II) and decomposition-based multi-objective evolutionary algorithm (MOEA\D), and the simulation results demonstrate the feasibility of the proposed model and the effectiveness of the proposed algorithm.

With the advancement of China’s carbon policy, the proportion of renewable energy, mainly wind and solar, has increased, which brings greater challenges to the reservation of power systems. Due to the complexity of China’s power systems, adopting the method of the zonal reserve to ensure stable system operation is very difficult. Among the existing clearing results for calculating reservation, the unit reservation will be restricted by the network security constraints, leading to system operation risks. To obtain the unit reservations efficiently without breaking the security constraints, this paper proposes an effective reserve calculation method for engineering implementation. A box robust optimization is further utilized for Security Constrained Unit Commitment in the method to ensure the consumption of renewable energy, and the stability and clearing efficiency of the power system. Furthermore, a data-driven robust random optimization is employed for Security Constrained Economic Dispatch optimizing the economy of power systems. This multi-stage robust optimization model, which has good extensibility, is in line with China’s clearing process. The simulation analysis based on the actual operation data of a province in China and the IEEE 300-bus system verifies the correctness and feasibility of the proposed model and theory.

Electric vehicle battery swapping stations (BSS) have significant potential in power system frequency regulation. However, uncertainties of swapping demand and regulation signals introduce risks to operational benefits and regulation performances. Aming to enhance overall profitability, this study proposes day-ahead bidding and real-time scheduling strategies for BSS to participate in frequency regulation. In the day-ahead stage, the BSS scheduling model is established. Then, the information-gap decision theory (IGDT) is employed to determine the optimal reserve capacities. The randomness of regulation signals is captured by designing a new uncertainty set based on statistical analysis. Additionally, a boundary autonomous selection (BAS) method is developed to solve the IGDT model, making the selected scenarios more consistent with real-world situations. In the intra-day stage, a real-time response strategy is proposed to track the regulation signals considering the BSS operation economy. Simulations are conducted using historical data from Pennsylvania, Jersey, and Maryland (PJM). The results demonstrate that the reserve capacities and response ratios obtained by the proposed strategies yield higher profits for BSS while ensuring regulation performance. • Modeling for the battery swapping station providing frequency regulation services. • A new uncertainty set of the regulation signal based on statistics. • IGDT based day-ahead bidding strategy and BAS solving method. • A real-time response strategy that can selectively track regulation signals. [ABSTRACT FROM AUTHOR]

In order to study the influence of brace failure on the seismic response of concentrically braced frames and the improvement of the residual structure's resistance to collapse due to reserve capacity, a series of concentrically braced frame prototypes with different story numbers is designed. A matrix of six finite-element concentrically braced-frame (CBF) models is established, which is varied by the number of stories and the level of reserve capacities. Accuracy of the numerical model is verified by comparing the responses of the shaking-table test of the concentrically braced frames, under 10 different working conditions. Then, a nonlinear time-history analysis, considering brace failure in one specified story, is carried out. The results show that the story-drift angle of the failure story as well as its adjacent stories increases greatly in the ideal pinned model. The above phenomenon is particularly serious, when the failure occurs at the top or bottom of the structure. With the reserve capacity brought by column continuity, and the semi-rigid rotation capacity of the beam-to-column and column-to-base connections are taken into consideration, the increase in story-drift angle caused by the brace failure is effectively reduced. However, the inherent reserve capacity has little influence on the dynamic characteristics of concentrically braced frames in the elastic stage. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The intermittency and unpredictability are the obstacles to absorb all wind power. The combined heat and power (CHP) system has been widely utilized as a heat and electricity source, and the heating load limits the regulatory capacity of CHP to reduce curtailed wind power. This study proposes an optimization model of an integrated power and heating network system to fully utilize curtailed wind power. The thermal inertia in the primary heating network, thermal comfort of end-users, and electric boiler in the secondary heating network are included in multiple scenarios to analyze different operation strategies. The simulation results show that considering the heating network, the inertia and thermal comfort of end-users could reduce the curtailed wind power ratio from 15% to 9%. Adding a peak-shaving electric boiler on the user side can increase the system electric load and reduce the curtailed wind power, while reducing the heat output of the CHP unit during the peak and low periods of the heat load at night. Moreover, there is less than 1% of the curtailed wind power ratio if the peak-shaving capacity ratio is higher than 10%, which means the application recommendations of installed electric boiler capacity are obtained to increase enough flexibility of the power and heating network system.

Control strategies with pre and main signal have been increasingly researched and practiced. With the transformative effect of connected and automated vehicles (CAVs), more possibilities have been created, and the long-time mix of CAVs with manual vehicles (MVs) has inspired radical change to the unconventional intersection with double stop lines. Specifically, the study is oriented with CAV controllability to facilitate vehicle passage throughout the intersection, by allowing CAVs to make use of yellow light at the presignal under in-vehicle control. To avoid spill-over and better clear vehicles on the approach, the distance from pre to main signal is constrained so that vehicles can queue upstream and pass the main stop line in time, under the objective of maximizing intersection reserve capacity. The proposedmodel is solved with iteration, and is found to reduce signal cycle, avoid spill-over, and enhance reserve capacity by larger margin as CAV penetration rate increases. This study provides insights to the design and control of intersections with double stop lines under mixed traffic flow, laying foundation to traffic conversion from MV to CAV. [ABSTRACT FROM AUTHOR]

In view of the effect of the volatility and randomness of wind power on the dispatching of the power grid, a neural network-based wind power reserve capacity estimation model is proposed. In this model, the weights of each link layer in BP neural network are optimized by particle swarm optimization algorithm to improve the prediction of wind power value in the future. The Pearson correlation coefficient is used to extract the influence factors which are positively correlated with the prediction error, and then the multiple linear regression method is used to associate the extracted influencing factors to calculate the reserve capacity of wind power. The simulation results show that 80% of the prediction error is within the estimation range of the model, further verifying the effectiveness of the model. [ABSTRACT FROM AUTHOR]

The paper investigated the extent to which rainfall influences the quality of service delivery at multilane roundabouts using a novel quality of service approach. Quality of service is defined as how well roundabouts operate based on road users and road providers’ perception of service quality. Delay and reserve capacity were used respectively as proxies for road users and road providers’ perception of service quality. The entry and circulating traffic data were recorded continuously for eight weeks under dry, light, moderate, and heavy rainfall weather conditions at each surveyed roundabout, then collated, analysed and compared. Linear regression with dummy variable was used to model the roundabout entry capacity and a corrector factor was added to modify the regression function. The corrector factor considered different entry radii and entry angles of surveyed roundabouts. Multi-criteria quality of service table with travel time as proxy for road users and speed as proxy for road providers’ perception of service delivery was developed from peak traffic data and used to determine the extent of deterioration. The multi-criteria table introduced in the paper is a clear departure from the speed-based criteria used in many studies. The results show a significant increase in time delay and a decrease in reserve capacity relative to rainfall. The paper has concluded that rainfall has an anomalous negative effect on the quality of service at multilane roundabouts. The findings could be used in a variety of ways in traffic management to predict the travel time at roundabouts under rainy conditions and to prescribe speed limits accordingly.

The article presents the main provisions of the model building of the sustainability index on the basis of which it is possible to form the synthetic basic product - the unit of regional currency. The world is ripe the need for changes in financial and currency system. The authors offer a practical approach to a fundamentally new construction of a regional monetary system, based on the methodology of calculation of the new currency unit, secured by the commodities with dual properties.

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We focus on the optimal use of risk mitigation inventory (RMI) and reserve capacity to manage disruption risk in serial multi‐stage supply chains where product transformation occurs at each stage. We find that under reasonable conditions it is better to hold more RMI downstream than upstream even when the upstream holding costs are lower. We also find that it is often optimal to hold more reserve capacity downstream than upstream. While in one‐stage supply chains RMI and reserve capacity always behave as substitutes, it turns out that in multi‐stage serial supply chains the interplay between RMI and reserve capacity is more nuanced. We find that echelon RMI and reserve capacity at each stage are substitutes. In contrast, RMI at a stage complements reserve capacity at the adjacent downstream stage. [ABSTRACT FROM AUTHOR]

In developed countries, structural assessment of existing bridges should not be performed using the same conservative models that are used at the design stage. Field measurements of real behavior provide additional information for the inference of previously unknown reserve capacity. Structural identification helps identify suitable models as well as values for parameters that influence behavior. Since the information gained by the measurement system has a direct impact on structural identification, studies on optimal sensor placement have been extensively carried out. However, information collected during monitoring comes at a cost that may not be justified by its influence on asset manager actions. A metric called value of information measures if the price of collecting information is justified when compared with the potential influence on asset manager decision-making. This paper presents a framework to approximate the value of information of bridge load testing for reserve capacity assessment. Additionally, an approach based on levels of approximation is used to provide a practical strategy for the assessment of the value of information. The framework provides guidance to asset managers to evaluate whether the information from controlled condition monitoring, collected at a cost, may influence their assessment of reserve capacity. Several scenarios of monitoring systems are compared using their respective potential influence on asset-manager decisions and cost of monitoring, using a full-scale case study: the Exeter Bascule Bridge.

Background: Family socioeconomic status (SES) is related to a child’s educational success. Intermediate pathways for this relationship, such as through pubertal timing and reserve capacity, occur in adolescence. Aim: To study whether family SES affects a child’s adult education through a psychosocial and behavioural pathway (reserve capacity) and/or a biological pathway (pubertal timing) or only through school achievement in adolescence. Subjects and methods: Finnish adolescents sampled in five cross-sectional surveys from 1985 to 1995 (n = 37,876) were followed through the Registry of Completed Education and Degrees until 2009, when they were 29–43 years old. Family SES data also came from this registry. Structural equation modelling adjusted for ages at baseline and follow-up was used. Results: Low family SES increased the probability of low adult education, delayed pubertal timing (in boys), weak reserve capacity and low school achievement. Reserve capacity and school achievement directly affected adult education and mediated the relationship of family SES with the outcome. Delayed pubertal timing predicted low adult education, except when school achievement was added to the model. Conclusions: The results show that family SES affects the child’s adult education level through psychosocial and biobehavioural pathways, but the biological pathway is mediated by school achievement.

Family socioeconomic circumstances directly influence adult education level. Adolescent psychosocial resources and health-promoting behaviour collectively termed as ‘reserve capacity’ and school achievement may likely mediate the effect of family socioeconomic circumstances on adult education level. We tested these relationships using 1985–1995 survey data on 12–18-year-old Finns (N = 41,822) linked with three-generation registry data of Statistics Finland until 2009. Results of the multinomial logistic regression models, adjusted for sex and age at end of follow-up, showed that socioeconomic circumstances of parents and grandparents predicted adult education level. School achievement and reserve capacity dimensions of perceived health, health-promoting behaviour and social support in adolescence also positively predicted adult education. Moreover, these tended to decrease the effect of family socioeconomic circumstances on educational level. Our findings suggest that formulating interventions which build reserve capacity and improve school performance, especially among adolescents from disadvantaged socioeconomic backgrounds, could likely reduce educational inequalities.

Abstract A primary goal of research in cognitive impairment and dementia is to understand how some individuals retain sufficient cognitive function for a fulfilling life while many others are robbed of their independence, sometimes their essence, in the last years and decades of life. In this commentary, we propose operational definitions of the types of factors that may help individuals retain cognitive function with aging. We propose operational definitions of resistance, resilience, reserve, with an eye toward how these may be measured and interpreted, and how they may enable research aimed at prevention. With operational definitions and quantification of resistance, resilience, and reserve, a focused analytic search for their determinants and correlates can be undertaken. This approach, essentially a search to identify protective risk factors and their mechanisms, represents a relatively unexplored pathway toward the identification of candidate preventive interventions.

Due to the increased use of variable renewable energy sources, more capacity for reserves is required. Non-generating resources such as thermostatically controlled loads (TCLs) can arbitrage energy prices and provide reserves due to their thermal energy storage capacity. The quantity of reserves depends not only on the aggregate power capacity, but also on information and communication technology, exogenous parameters, and system operator requirements. Specifically, the practical limitations origin from (i) communication constraints, (ii) ambient temperature, and (iii) the dispatch time of the activation signal. This study explores the impact of these parameters on the amount of reserves that an aggregator of TCLs can provide to the system operator based on centralised control of a TCL population. A decision support tool is proposed that can be used by aggregators to decide on maximum dispatchable reserve bids. The method can accommodate the specific control algorithm and TCL population of an aggregator and is based on offline computation. It constitutes a powerful reserve bid library to be used when optimisation tools become computationally intractable due to the increased number of decentralised flexible loads. [ABSTRACT FROM AUTHOR]

Emerging adulthood has been described as a difficult stage in life and may be particularly stressful for Hispanic emerging adults who are disproportionately exposed to adversity and chronic sociocultural stressors. To better prevent and treat depressive disorders among Hispanic emerging adults, more research is needed to identify and understand modifiable determinants that can help this population enhance their capacity to offset and recover from adversity and sociocultural stressors. As such, this study aimed to (1) examine the association between resilience and depressive symptoms among Hispanic emerging adults, and (2) examine the extent to which intrapersonal resources (e.g., mindfulness, distress tolerance, emotion regulation strategies) and interpersonal resources (e.g., family cohesion, social support) moderate the association between resilience and depressive symptoms. To examine these aims, 200 Hispanic emerging adults (ages 18–25) from Arizona (n = 99) and Florida (n = 101) completed a cross-sectional survey, and data were analyzed using hierarchical multiple regression and moderation analyses. Findings from the hierarchical multiple regression indicate that higher resilience was associated with lower depressive symptoms. Findings from the moderation analyses indicate that family cohesion, social support, and emotion regulation strategies (e.g., cognitive reappraisal and expressive suppression) functioned as moderators; however, mindfulness and distress tolerance were not significant moderators. Findings from this study add to the limited literature on resilience among Hispanics that have used validated measures of resilience. Furthermore, we advance our understanding of who may benefit most from higher resilience based on levels of intrapersonal and interpersonal resources. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Effectively managing the inherent unpredictability and fluctuation attributes of renewable energy sources within scheduling systems has emerged as a critical matter demanding immediate attention. The incorporation of energy storage technology offers notable advantages by mitigating fluctuations in wind power generation and curtailing peak shaving costs in scheduling systems through economical utilization of energy storage. This study employs the adjustment of energy storage's reserve capacity function to modify the economic gains and losses arising from fixed spinning reserve. This approach tailors the reserve capacity function by formulating the uncertainty inherent in wind power generation. The paper presents an enhanced selection method for calculating optimal bandwidth within the framework of least squares approximation probability density function scenarios. The fusion of least squares approximation and optimal bandwidth computation permits precise refinement of bandwidth in non-parametric kernel density estimation approaches. Consequently, the study puts forth a comprehensive model for coordinated scheduling and regulation of a multi-scale energy storage power system. Finally, the stability and economy of the proposed method in the scheduling operation process were verified through simulation, and the research results can provide a theoretical basis for future uncertain wind power scheduling. • Wind power prediction error KDE calculated by optimal bandwidth method. • ESS reserve capacity model for cooperative KDE confidence interval. • Multi-scale security economic regulation model for multiple types of energy. [ABSTRACT FROM AUTHOR]

The pursuit of individual mobilities expedites the development of demand-responsive systems, while the balance between service flexibilities and operational cost is becoming particularly important. This paper proposes a method for operating a novel demand-responsive bus system termed terminal-based zonal bus (TZB). It is a flexible system with vehicles executing a terminal-based zone routing scheme in specified service zones. The terminal-based routing scheme intends to generate TZB lines, and each line is operated by one vehicle that travels along a series of terminal stations arranged in order and serves enroute passenger requests between any two consecutive terminal stations. As instant response is the main trait of demand-responsive systems, TZB is able to address instance response by incorporating reserve capacity, which is employed to indicate the vehicle responsive ability of new real-time requests. Further, a tailored heuristic algorithm is designed to solve the proposed model, which simultaneously incorporates several practical restrictions, including the capability of adopting real-time requests, terminal stations' fleet-size constraints, time window constraints, and vehicle capacity. Computational experiments are conducted based upon the newly developed modern city Xiong An, China which confirm that the proposed method is capable of obtaining high-quality solutions efficiently, and TZB can provide flexible service at a relatively low operational cost. [ABSTRACT FROM AUTHOR]

Abstract Background Despite robust evidence on the inverse relationship between socioeconomic status (SES) and mortality, deviations from expected results have been observed likely due to school achievement and psychosocial resources, termed as “reserve capacity.” Since adolescence is a critical period in developing sound psychological and behavioural patterns and adolescent markers of SES were seldom used, we determine if family SES in adolescence predicts later mortality. We also study how reserve capacity (perceived health, health-promoting behaviour and social support) and school achievement modify this relationship and reduce the negative effects of low SES. Methods A longitudinal study was designed by linking baseline data on 12 to 18 year-old Finns in 1985–95 (N = 41,833) from the Adolescent Health and Lifestyle Surveys with register data on mortality and SES from Statistics Finland. Average follow-up time was 18.4 years with a total of 770,161 person-years. Cox regression models, stratified by sex, were fitted to determine the effects of variables measured during adolescence: family SES, reserve capacity and school achievement on mortality risk. Results All reserve capacity dimensions significantly predicted mortality in boys. Perceived health and social support predicted that in girls. Adolescents with the lowest school achievement were more than twice at risk of dying compared to those with better school performance. Low SES increased the risk of death in boys (Hazard ratios: 1.6, 95% CI 1.1–2.4) but not in girls. Reserve capacity and school achievement weakened the effects of low SES on boys’ risk of death. Conclusions High reserve capacity and good school achievement in adolescence significantly reduce the risk of mortality. In boys, these also mitigate the negative effect of low SES on mortality. These findings underscore the roles of reserve capacity and school achievement during adolescence as likely causal or modifying factors in SES-health inequalities.

This article discusses issues related to reserve capacity. The author concludes that these issues need be solved above all in the economic context rather than the technical context: Necessary actions include establishing the equal rights of electricity consumers and producers, introducing a multilevel insurance system for electrical power facilities, and harmonizing the reserve capacity categories with international classifications. [ABSTRACT FROM AUTHOR]

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The increasing shares of stochastic renewables bring higher uncertainty in power system operation and underline the need for optimal utilization of flexibility. However, the European market structure that separates energy and reserve capacity trading is prone to inefficient utilization of flexible assets, such as the HVDC interconnections, since their capacity has to be ex-ante allocated between these services. Stochastic programming models that co-optimize day-ahead energy schedules with reserve procurement and dispatch, provide endogenously the optimal transmission allocation in terms of minimum expected system cost. However, this perfect temporal coordination of trading floors cannot be attained in practice under the existing market design. To this end, we propose a decision-support tool that enables an implicit temporal coupling of the different trading floors using as control parameters the inter-regional transmission capacity allocation between energy and reserves and the area reserve requirements. The proposed method is formulated as a stochastic bilevel program and cast as mixed-integer linear programming problem, which can be efficiently solved using a Benders decomposition approach that improves computational tractability. This model bears the anticipativity features of a transmission allocation model based on a pure stochastic programming formulation, while being compatible with the current market structure. Our analysis shows that the proposed mechanism reduces the expected system cost and thus can facilitate the large-scale integration of intermittent renewables. [ABSTRACT FROM AUTHOR]

To cope with the uncertainty and variability of wind power, it is important for the power system to maintain adequate reserve capacity. The energy storage ability of the district heating system (DHS) provides considerable flexibility for the combined heat and power (CHP) units, and hence CHP can also participate in reserve capacity service. However, the CHP operation is restricted not only by its power condition, but also by the DHS heating condition, which brings difficulty in quantifying the CHP reserve flexibility. This paper focuses on properly assessing and utilizing the available reserve capacity of the CHP units as well as addressing the DHS heating constraints. The particularity for CHP reserve assessment is first analyzed and summarized as the component-coupling feature and the heating-dependency feature. Based on this, the regulating region method is proposed to describe the heating-restricted reserve capacity of the CHP units. Furthermore, an integrated power and heat dispatch approach is developed which utilizes the regulating region to formulate the available CHP reserve capacity. Finally, the numerical simulation is performed to demonstrate the necessity of precisely assessing the available reserve capacity of the CHP units and the benefit of utilizing this potential reserve flexibility for wind accommodation. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) as dynamic energy storage systems could provide ancillary services to the grids. The aggregator could coordinate the charging/discharging of EV fleets to attend the electricity market to get profits. However, the aggregator profits are threatened by the uncertainty of the electricity market. In this study, an EV aggregator bidding strategy in the day‐ahead market (DAM) is proposed, both reserve capacity and reserve deployment are considered. The novelty of this study is that: (i) The uncertainty of the reserve developments is addressed in terms of both time and amount. (ii) Scenario‐based stochastic programming method is used to maximise the average aggregator profits based on one‐year data. The proposed method, jointly considers the reserve capacity in the DAM and the reserve deployment requirements in the real‐time market (RTM). (iii) The risk of the deployed reserve shortage is addressed by introducing a penalty factor in the model. (iv) An owner‐aggregator contract is designed, which is used to mitigate the economic inconsistency issue between the EV owners and the aggregator. Results verify the performance of the proposed strategy, that is the average aggregator profits are guaranteed by maximising reserve deployment payments and mitigating the penalties in RTM and thus the reserve deployment requirements uncertainty is well managed. [ABSTRACT FROM AUTHOR]

In this paper, a risk-constrained two-stage stochastic model is proposed for optimal scheduling of autonomous microgrids considering the participation of end-use customers in demand response programs. The goal of the proposed scheme is to maximize the profit of the microgrid operator in different conditions of the user's risk taking, so that customers pay the lowest cost for their energy consumption. Based on the proposed model, customers are able to provide part of the system's reserve capacity to deal with uncertainties by using smart and response loads capability. The uncertainties of the problem are due to the predicted error of renewable resources, energy prices and demand loads, modeled on scenario-based methods. In the proposed model, in order to deal with the effects of undesirable scenarios, an index for assessing the value of risk is employed to estimate the level of undesirable profits. In addition, in order to more accurately analyze the frequency and voltage limitations, an AC load flow is used in the problem-solving process that achieves more realistic result to the microgrid operation. Finally, the proposed model is implemented in a typical microgrid and the results are investigated in different cases. [ABSTRACT FROM AUTHOR]

This study proposes a data‐driven distributionally robust framework for unit commitment based on Wasserstein metric considering the wind power generation forecasting errors. The objective of the constructed model is to minimise the expected operating cost, including the generating cost, start‐up and shut‐down costs, and also the reserve cost, which overcomes the shortcomings of the conventional model without optimising the reserve capacity. What is more important, different from the conventional robust optimisation methods, wind power big data is fully utilised in this model to construct the ambiguity set without any presumption about its probability distribution. This is realised by Wasserstein ball with an empirical distribution as the centre. Thus, the proposed robust model is actually data‐driven and can immunise the solutions against the worst‐case distribution in the ambiguity set. In addition, the scale of the historical data is very critical for this method, the larger the scale is, the smaller the ambiguity set is and the less conservative the result is. Numerical results and Monte Carlo simulations on a real 75‐bus system demonstrate the superiority of the proposed model. [ABSTRACT FROM AUTHOR]

Knockdown of the suppression of tumorigenicity 14-encoding type II transmembrane serine protease matriptase (MTP) in neural stem/progenitor (NS/P) cells impairs cell mobility, response to chemo-attractants, and neurovascular niche interaction. In the present study, we showed by Western blot that a portion of MTP can be detected in the mitochondrial fraction of mouse NS/P cells by immunostaining that it is co-stained with the mitochondrial dye MitoTracker (Thermo Fisher Scientific, Waltham, MA, USA) inside the cells. Co-immunoprecipitation showed that MTP is bound to the β subunit of mitochondrial F0F1-ATP synthase complex (ATP-β). Cyto-immunofluorescence staining and an in situ proximity ligation assay further confirmed a physical interaction between MTP and ATP-β. This interaction relied on the presence of both Cls/Clr urchin embryonic growth factor, bone morphogenic protein 1 and low-density lipoprotein receptor motifs of MTP. We found that NS/P cell mitochondrial membrane potential is impaired by MTP knockdown, and ATP synthesis and oxygen consumption rate are significantly reduced in MTP-knockdown NS/P cells. Among the oxidative phosphorylation functions, the greatest effect of MTP knockdown is the reduction by over 50% in the mitochondrial energy reserve capacity. This made MTP-knockdown NS/P cells unable to overcome hydrogen peroxide stress, which leads to cessation of cell growth. This work identifies 2 previously unknown functions for MTP: first as a binding protein in the mitochondrial F1F0-ATP synthase complex and second as a regulatory mechanism of mitochondrial bioenergetics. Mitochondrial MTP may serve a protective function for NS/P cells in response to stress. [ABSTRACT FROM AUTHOR]

Abstract The incorporation of renewable energy sources in isolated power systems is being significantly slower than in well-connected power systems. The intermittency and uncertainty of the power output of most renewable power technologies prevent a greater usage of these technologies in isolated power systems, in which the supply security is the major concern. In this paper we formulate a stochastic unit commitment problem that allows the participation of electric vehicles in energy, reserve capacity and primary frequency response markets in order to increase the flexibility of the power system operation. We explicitly consider the uncertainty in the power demand and renewable power availability, as well as accounting for the possibilities of contingencies of generating units using a N-1 security criterion. The proposed formulation is tested on an actual isolated power system comprising 38 generating units and 8 buses. Highlights • We analyze isolated power systems with a large penetration of electric vehicles. • A stochastic unit commitment is proposed for scheduling this type of power systems. • Electric vehicles participate in energy, reserve and primary response markets. • A pricing mechanism is derived for remunerating electricity market participants. • A realistic case study based on an isolated power system is solved. [ABSTRACT FROM AUTHOR]