Response Programs Research Articles

Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach

The mining industry is a key contributor to Western Australia’s economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportunities of integrating renewable energy sources into isolated power systems, particularly under uncertainties associated with renewable energy generation and demand. A robust optimization approach is developed to model a multi-source hybrid energy system that considers risk-averse, risk-neutral, and risk-seeking strategies. These strategies address power demand and renewable energy supply uncertainties, ensuring system reliability under various risk scenarios. The optimization framework, formulated as a mixed integer linear programming problem and implemented in Python using the Gurobi Optimizer, integrates renewable energy sources such as wind turbines, photovoltaic arrays, and demand response programs alongside traditional diesel generators, boilers, combined heat and power units, and water desalination. The model ensures reliable access to electricity, heat, and water while minimizing operational costs and reducing reliance on fossil fuels. A comprehensive sensitivity analysis further examines the impact of uncertainty margins and the value of a lost load on the total system cost, providing insights into how different risk strategies affect system performance and cost-efficiency. The results are validated through three case studies demonstrating the effectiveness of the proposed approach in enhancing the resilience and sustainability of isolated power systems in the mining sector. Significant improvements in reliability, scalability, and economic performance are observed, with the sensitivity analysis highlighting the critical trade-offs between cost and reliability under varying uncertainty conditions.

Firearm Injury Prevention and Survivor Interventions: A Scoping Review.

To examine components of firearm injury prevention and survivor response programs, their outcomes, and gaps in this body of research. A total of 100 publications were identified across four databases: PubMed/Medline, PsycInfo, CINAHL, and Scopus. Articles were screened for inclusion in the scoping review and details were extracted into an electronic table for synthesis. A total of 27 articles were included. Education on firearm injury prevention was shown to be feasible and acceptable in health care settings, including emergency departments. Firearm survivor interventions to reduce violent injury recidivism may include peer or mentored support along with case management for coordination of mental health services, vocational training, and other services to address social determinants of health. Other community initiatives to clean up abandoned lots and engage community members in creating safe neighborhoods have been shown to reduce overall gun violence. Multi-level interventions that encompass education on reducing firearm injuries, strategies to improve psychosocial conditions and access to mental health services, as well as meeting the needs of firearm injury survivors, their families, and communities, are needed. Health sector and community partnerships can lead to integrated and sustainable programs to achieve safer neighborhoods and improve psychosocial outcomes for individuals affected by gun violence and impacted communities. [Journal of Psychosocial Nursing and Mental Health Services, xx(xx), xx-xx.].

Innovative Microgrid Services and Applications in Electric Grids: Enhancing Energy Management and Grid Integration

Currently, microgrids are a reliable solution for integrating distributed energy resources and managing demand on electricity grids, serving as a pathway towards a responsible energy transition. However, the evolving needs of the sector require specialized approaches to enhance grid flexibility and support the increasing penetration of renewable energy sources and their rising demand. This article explores and characterizes various advanced and innovative services offered by microgrids to improve the resilience, security, and reliability of electricity grids. It analyzes technical advances and novel control methodologies that demonstrate the potential for microgrids beyond mere energy provision. These include ancillary services, services aligned with demand response programs, and advanced asset management and energy resource optimization services. A global case study is conducted to provide a framework for the services that microgrids can provide. The case study validates the efficiency and reliability of electric grids with microgrids and addresses challenges related to their stability and resilience. This research provides a comprehensive perspective on the benefits of implementing microgrids and proposes new guidelines for the deployment of these systems in both urban and rural areas within the framework of energy communities in the Colombian electricity system, emphasizing the need for collaboration among stakeholders to ensure sustainable energy solutions.

Maternal and perinatal death surveillance and response in Bangladesh: A case study on measuring impact through health information systems

The health sector in Bangladesh is thriving, and the Maternal and Perinatal Death Surveillance and Response (MPDSR) program has been in place to investigate the causes of maternal and perinatal death. This study aimed to investigate the availability of information systems for measuring the status of an MPDSR program and the planning process and actions developed based on real-time information. This study delved into innovative information systems that can be used to monitor and measure the impact of health programs. The study included both the primary and secondary data. A total of six key informant interviews were conducted to explore the enablers and strengths of information systems. Secondary data were collected from government websites and MPDSR action plans. This study highlights the potential and challenges of governmental health information systems in notifying maternal and neonatal deaths. While the current notification rates are not up to national standards, it is encouraging to see health managers develop action plans and address this issue. The MPDSR information system is a valuable tool to help health managers measure changes in maternal and perinatal mortality rates and design locally targeted interventions. However, several obstacles must be addressed, such as insufficient data, lack of monitoring, and irregularities in MPDSR review meetings. By finding ways to overcome these challenges, we can unlock the full potential of MPDSR and improve maternal and neonatal health outcomes. The success of an MPDSR program relies on how the information is utilized to take action and measure the outcome. Advanced information systems, such as health dashboards, scorecards, and administrative data, can play a vital role in measuring the progress and impact of a program. The primary challenge lies in capturing all deaths, including their causes, and having the capacity to analyze the data effectively to develop action plans for health managers.

Dynamic Energy Management and Control of Networked Microgrids based on Load to Grid Services and Incentive-Based Demand Response Programs: A Multi-Agent Deep Reinforcement Learning Approach

This study has presented the energy management paradigm in a networked microgrid structure based on L2G services and considering incentive-based load response (IBDR) programs and energy market requirements to reduce operating costs, control and restore voltage and frequency index, providing the benefits of subscribers and distribution system operators. In this study, multi-objective functions such as optimal operation based on IBDR structure and energy market requirements, risk assessment, and L2G service approach are configured in the framework of central and local controllers. Optimal operation and risk assessment are analyzed by a multi-task learning algorithm based on multi-objective function and L2G service policies are evaluated based on multi-agent deep reinforcement learning. Control policies are sent by the communication system to the components affecting the optimal power distribution as well as the voltage and frequency controllers. L2G services have been evaluated in different scenarios such as plug-and-play operating conditions, load fluctuations, and operating in island mode. The results of optimal operation based on L2G services show that the IBDR program implementation reduces the total operation cost by 21%. Also, the total operating cost of the proposed framework is 13.97% less than the RL method and 27.8% less than the ANN method.

Individual differences in acceptance of direct load control

Consumer acceptance of direct load control is becoming increasingly important as energy systems transition towards greater reliance on intermittent renewable energy sources. The objective of this paper is to better understand the attitudinal and socio-economic determinants of direct load control acceptance. To do so, we collect survey data from participants in 31 European countries (N = 5,970). Regression analyses testing a comprehensive model of attitudinal and socio-economic determinants of direct load control acceptance reveal that attitudes and beliefs specific to direct load control acceptance (social and personal norms, anticipated emotions, and outcome efficacy beliefs) predict acceptance, whereas more general attitudinal variables and socio-economic characteristics play no or only a secondary role. These findings substantially improve our understanding of direct load control acceptance. While European policy documents recognize the importance of individual attitudes for the success of demand response programs, reference to specific factors or processes is often missing due to lack of evidence. The present research helps fill this gap, and can inform the design of novel soft policy measures – highlighting the usefulness of facilitating positive peer influence, of reinforcing perceptions that engaging in demand response is effective, is the responsible thing to do, and also something to be proud of

Association between cardiac consultation and outcomes in patients with perioperative myocardial infarction/injury

Abstract Introduction Perioperative cardiac complications are a frequent occurrence and can lead to high short- and long-term mortality rates after major noncardiac surgery. No single intervention has yet demonstrated its effectiveness in treating perioperative myocardial infarction/injury (PMI). In this large prospective multicentre study, we aimed to evaluate the association between postoperative cardiac consultation and major adverse cardiac event (MACE) and all-cause death within 365 days in patients with PMI after undergoing major noncardiac surgery. Methods We prospectively included consecutive patients undergoing major inpatient noncardiac surgery at two hospitals who were eligible for the institutional active PMI surveillance and response programme. For this analysis, only patients with PMI who were directly transferred to the regular ward following surgery were included. In the case of a PMI, the standardised structured institutional response included assessing the patient for possible symptoms, recording a 12-lead ECG and a cardiac consultation. The specific scope of the PMI workup and management was determined by the attending clinical cardiologist following an institutional flowchart. Our primary endpoint was the occurrence of MACE (defined as a composite of cardiovascular death, MI, AHF, and life-threatening arrhythmia) within 365 days, excluding the initial PMI. All-cause death after 365 days was the secondary endpoint. Multivariable Cox proportional hazard models were used to evaluate the association of cardiac consultation with MACE and all-cause death after 365 days. Results During the period between October 2014 and September 2019, the BASEL-PMI study programme enrolled 14294 patients. After the exclusion of patients without PMI, with a postoperative ICU stay, multiple inclusion, or palliative setting 1048 patients remained. Among those, 434 patients received postoperative cardiac consultation (41.4%). Patients had a median age of 77 years and 44.8% were female. After adjustment, patients who received a postoperative cardiac consultation had a lower risk of having MACE after 365 days (adjusted hazard ratio [aHR] = 0.54, 95% confidence interval [CI] 0.37 - 0.79, p-value = 0.001) and a lower risk of death of any cause after 365 days (aHR = 0.66, 95%CI 0.44 - 1.00, p-value = 0.048). Conclusion In a large multicentre prospective cohort study, postoperative cardiac consultation in patients with PMI was associated with a reduced risk of MACE and all-cause death after 365 days.Kaplan-Meier curve for MACE

A Comparative Analysis of Policy Responses to Development Gaps in ASEAN: Examining the Effectiveness of Macroeconomic and Regional Integration Strategies

Abstract: Association of Southeast Asian Nations (ASEAN) integration was originally developed to respond more effectively to political and economic pressures from outside and collective bargaining power with a unified regional organisation. However, the significant disparity in development levels among ASEAN member States posed a challenge to that goal and to the sustainable economic development of ASEAN. This paper will analyse all aspects of the existing disparity in the level of development of ASEAN member countries and the reasons behind it. It will also present and analyse existing policies and mechanisms in ASEAN that address the imbalance in the level of development. To analyse the challenges for ASEAN to address the issue of imbalance in the level of development in the light of the effectiveness of the current ASEAN response to the imbalance in the level of development and the objective and realistic context of the ASEAN member States in terms of the comparison between the countries with high level of development and the countries with low level of development. ASEAN's macro-control policies, influenced by the system, do pay attention to the key factors affecting high and low levels of development, but ASEAN lacks targeted response programmes for countries and regions with complex political contexts.

Preventing and responding to violence against women: A case study from Vietnam

Violence against women (VAW) has significant detrimental effects on the daily lives of women and the overall development of society. Addressing VAW poses a considerable challenge for nations striving to achieve sustainable development goals (SDGs). Vietnamese society, deeply influenced by Confucianism and Buddhism, continues to perpetuate male preferences. The persistence of gender stereotypes and discrimination shaped by societal norms serves as an underlying cause of VAW in Vietnam. Despite the Vietnamese government’s efforts since 2010 to implement prevention and response programs for gender-based violence, the alarming reality is that nearly 63% of women report experiencing at least one form of violence in their lives. However, various obstacles prevent many of these women from seeking legal protection. These obstacles include inadequate support services, burdensome proof requirements, and fear of re-victimization. Thus, the crucial question of how to effectively eliminate VAW in Vietnam remains a major concern, influencing the nation’s progress toward achieving the SDGs and upholding its commitment as a member country of the Convention on the Elimination of All Forms of Discrimination against Women. This paper analyzes the obstacles Vietnam faces in its efforts to prevent and respond to VAW, aiming to safeguard women’s rights and advance gender equality.

SLAMF7 (CD319) on activated CD8+ T cells transduces environmental cues to initiate cytotoxic effector cell responses.

CD8+ T-cell responses are meticulously orchestrated processes regulated by intercellular receptor:ligand interactions. These interactions critically control the dynamics of CD8+ T-cell populations that is crucial to overcome threats such as viral infections or cancer. Yet, the mechanisms governing these dynamics remain incompletely elucidated. Here, we identified a hitherto unknown T-cell referred function of the self-ligating surface receptor SLAMF7 (CD319) on CD8+ T cells during initiation of cytotoxic T-cell responses. According to its cytotoxicity related expression on T effector cells, we found that CD8+ T cells could utilize SLAMF7 to transduce environmental cues into cellular interactions and information exchange. Indeed, SLAMF7 facilitated a dose-dependent formation of stable homotypic contacts that ultimately resulted in stable cell-contacts, quorum populations and commitment to expansion and differentiation. Using pull-down assays and network analyses, we identified novel SLAMF7-binding intracellular signaling molecules including the CRK, CRKL, and Nck adaptors, which are involved in T-cell contact formation and may mediate SLAMF7 functions in sensing and adhesion. Hence, providing SLAMF7 signals during antigen recognition of CD8+ T cells enhanced their overall magnitude, particularly in responses towards low-affinity antigens, resulting in a significant boost in their proliferation and cytotoxic capacity. Overall, we have identified and characterized a potent initiator of the cytotoxic T lymphocyte response program and revealed advanced mechanisms to improve CD8+ T-cell response decisions against weak viral or tumor-associated antigens, thereby strengthening our defense against such adversaries.

An overview of the challenges and methods for defining the wildlife-disease interface in the context of disease spread modelling, including concepts of infectious diseases epidemiology

ABSTRACT The wildlife-domestic interface is a key concept helping us to understand how diseases affect both wild and domestic animal populations, yet how to define and measure it remains a challenge. One tool which can contribute to our understanding of the wildlife-domestic interface is disease spread modelling. This can provide insight into how diseases spread within and between populations, and guide decision-making for disease control, response and surveillance programs. Specifically, quantitative estimation of contact rates permits such disease spread models to be developed and used confidently. Here we present a case study of the potential spread of rabies (an exotic disease in Australia) within the wild dog-domestic dog (Canis familiaris) ecosystem of northern Australia to illustrate the concept of the wildlife-domestic interface and disease transmission. We summarise a decade of research conducted to understand one such interface, the wild-domestic dog interface at one site in northern Australia, for the purposes of exploring the impact of one specific disease, rabies. Over a period of 10 years, free-roaming domestic dogs and wild dogs in the Northern Peninsula Area (NPA) of Cape York, Queensland were studied. Key findings included identification of a small but important group of domestic dogs which regularly roam in bushland areas; peri-urban wild dog activity, particularly in the dry season, likely driven by the availability of food sources; and the potential for interaction between hunting dogs and wild dogs in remote areas, particularly during the wet season. These observations can be used to inform disease spread models and identify strategies to mitigate the risks of disease transmission. However, the collection and incorporation of data into such models needs more consideration regarding what information is usable (such as contact rates) and the best ways to collect it. The scarcity of such models incorporating the wildlife-domestic interface suggests that integrated epidemiological-ecological studies are needed to fill this gap.

A Multi-Layer Techno-Economic-Environmental Energy Management Optimization in Cooperative Multi-Microgrids with Demand Response Program and Uncertainties Consideration.

This paper presents a multi-layer, multi-objective (MLMO) optimization model for techno-economic-environmental energy management in cooperative multi-Microgrids (MMGs) that incorporates a Demand Response Program (DRP). The proposed MLMO approach simultaneously optimizes operating costs, MMG operator benefits, environmental emissions, and MMG dependency. This paper proposed a new hybrid ε-lexicography-weighted-sum that eliminates the need to normalize or scalarize objectives. The first layer of the model schedules MMG resources with DRP to minimize operating costs (local generation and power transactions with the utility grid) and maximize MMG profit. The second layer achieves the environmental operation of the MMG, while the third layer maximizes MMG reliability. This paper also proposed a new application of a recently developed enhanced equilibrium optimizer (EEO) for solving the three-layer EM problem. In addition, the uncertainties of solar power generation, wind power generation, load demand, and energy prices are considered based on the probabilistic 2m + 1 Point estimation method (PEM) approach. Three case studies are presented to verify the proposed MLMO approach on an MMG test system. In Case I, a deterministic EM is solved to simulate the MMG as a single layer to minimize costs and maximize benefits through DRP, while Case II solves the MLMO optimization problem. Simulation results show that the proposed MLMO technique reduces environmental emissions by 2.45% and 3.5% in its optimization layer and at the final layer, respectively. The independence index is also enhanced by 2.49% and 4.8% in its layer only and as a total increase, respectively. Case III is for the probabilistic EM simulation; due to the uncertain variables effect, the mean value in this case is increased by about 2.6% over Case I.

Robust distribution networks reconfiguration considering the improvement of network resilience considering renewable energy resources

The integration of renewable energy sources into smart distribution grids poses substantial challenges in maintaining grid stability, efficiency, and reliability due to their inherent variability and intermittency. This study addresses these challenges by proposing a novel two-level optimization model aimed at enhancing operational efficiency and robustness in smart distribution grids. The model synergistically integrates renewable energy sources, energy storage systems, electric vehicles, and demand-side management through a dynamic reconfiguration approach. It employs a robust optimization framework combined with a two-stage second-order cone optimization model to manage real-time operations and strategic grid reconfiguration. Key findings from simulations on the IEEE 33 and 69-bus networks underscore the model’s effectiveness. In the 33-bus system, implementing the demand response program led to a significant reduction in power losses, from 0.64 MW to 0.52 MW, and improved voltage stability, with the minimum voltage increasing from 0.970 to 0.980 p.u. Similarly, in the 69-bus system, power losses decreased from 0.85 MW to 0.79 MW, and voltage stability improved, with the minimum voltage rising from 0.962 to 0.972 p.u. The model also demonstrated reduced energy procurement needs, showcasing its impact on enhancing grid efficiency and reliability. These results highlight the model’s potential for advancing smart grid management strategies, offering significant improvements in operational performance and stability under varying demand conditions.

Development and implementation of a digital remote symptom monitoring program (RESPONSe) to support patients undergoing IV chemotherapy at a community ambulatory cancer clinic in Richmond, BC, Canada.

406 Background: We identified delays in accessing symptom management during treatment as an existing care gap at the Richmond Cancer Clinic. Patient-reported outcome measures (PROMs) have been demonstrated to communication, quality of life, and reduce symptom burden and acute care utilization. The RESPONSe program was initiated to address this gap by implementing a digital remote symptom monitoring (RSM) system paired with a supporting Symptom Management Nurse (SMN). Methods: We designed a digital RSM system to collect PROMs at specific timepoints during the first 6 months of IV chemotherapy initiation, with automated triaging logic to flag symptoms of concern that would result in a phone call from the SMN. Routine surveys include baseline, health-checks on days 3 and 10 post-chemotherapy, and pre-doctor’s-appointment; with optional health checks available anytime. Through competitive procurement, SeamlessMD was selected as the technology partner. From Aug 2023 to Jan 2024, multiple design cycles with dry run testing were held to incorporate branching logic, COSTARS oncology symptom specific questionnaires, automatic triaging flags, immediate self—management tips and links to educational resources. Concurrent development of SMN clinical workflows included in-person patient enrolment, digital dashboard monitoring and integration with the clinical chart. Results: From Jan 22-Apr 30, 2024, 32 patients have been enrolled with 42% over the age of 70. 90% of patients completed the baseline survey, 79% of patients completed at least 1 post-treatment health check and 45% completed at least 1 pre-doctors’-appointment survey. An average of 22 library resources were accessed per patient. Through the system, 19 severe and 34 moderate symptoms were identified. The dashboard prompted 63 telephone calls from the SMN, with a further 28 follow-up calls required. Early 3-month patient experience surveys (n=8) indicate high satisfaction, with 100% of patients saying they would recommend the program to others undergoing treatment. 87.5% of patients felt the system was very helpful in communicating their issues to the clinical team, with 100% reporting very high/extreme satisfaction with the support provided by the SMN. Additionally, 67% of patients felt very satisfied with the RESPONSe program overall. Conclusions: The RESPONSe program demonstrates the potential of digital RSM systems in improving patient-centered care and assisting with symptom reporting and management. Initial results suggest high engagement and patient satisfaction, showing this is a feasible approach in community oncology settings. We will be reviewing acute care utilization to assess the impact of the RESPONSe program on emergency room visits and hospitalization.

What happens after the funding ends?: A qualitative sustainability investigation of emergency department-based peer support programs implemented as part of Indiana's opioid state targeted response initiative

Introduction: In 2017, funding disseminated through the US Substance Abuse and Mental Health Services Administration's Opioid State Targeted Response (STR) program accelerated the expansion of peer recovery support services across several states to engage emergency department patients presenting with opioid use disorder. While there is some literature on the initial implementation of these programs, little is known about their sustainability after the STR funding's end. Identifying what happened to these programs is a key component of understanding their ultimate impact and can inform future activities to develop, fund, or sustain similar efforts. Methods: We collected qualitative data from six organizations that participated in Indiana's STR-funded Recovery Coaching and Peer Support Initiative (RCPSI). The semi-structured interview guide was designed to gather data related to eight domains of sustainability (i.e., environmental support, funding stability, partnerships, organizational capacity, program evaluation, program adaptation, program evaluation, communications, and strategic planning). The analysts followed a deductive-inductive analysis approach, using the eight domains as an a priori coding structure and developing higher-level inductive themes. Results: A total of ten individuals (roles included 4 Program Supervisors, 2 Nurse Administrators, a Psychiatric Social Worker, a Mobile Treatment Manager, a Grant Coordinator, and a Vice President of Planning) participated in six interviews. Two programs did not sustain services, primarily because they lacked a sufficient volume of eligible patients to justify services. Factors identified as supporting sustainability in the other four programs included (1) identification of alternate funding sources, (2) evolving internal support for ED-based opioid use disorder treatment, and (3) investment in internal and external relationships. Furthermore, these themes operated across multiple sustainability domains. Conclusions: The findings illustrate a dynamic interplay between program context and multiple theorized sustainability domains that impacted the viability of RCPSI programs after the end of STR funding. Results indicate a need for a better understanding of the factors influencing the sustainability of programs supported by federal funding to mitigate the opioid crisis, and such findings will likely apply to a broader range of grant-supported programs.

Day-ahead multi-criteria energy management of a smart home under different electrical rationing scenarios

With the recent global energy crisis, some countries have implemented electrical rationing (ER), making it necessary for smart homes to play a pivotal role in optimizing energy consumption and contributing to sustainable practices. To effectively manage smart home consumption, a stochastic programming approach for a grid-connected smart home energy management system (SHEMS) is proposed in this paper. The system includes PV, battery, diesel, and gas-based heating/cooling systems (HCS). Additionally, a demand response program (DRP) has been employed under time-of-use tariffs in the Syrian energy market. The main objective is to minimize the day-ahead expected cost and consumer discomfort by optimizing the operation of dispatchable units and loads. To manage the risks associated with the expected cost due to potential uncertainties in PV energy generation and electrical rationing programs, the conditional value-at-risk (CVaR) approach is adopted. Two methods are proposed to model the uncertainty in PV energy generation; interval bands and interval-based scenarios. The problem is modeled as a mixed-integer non-linear programming (MINLP) model, and coded in GAMS to test different cases. Based on the results obtained, substantial reductions reached 56.2% in worst-case cost scenarios when employing concurrent DRP-risk management.

Energy management of hybrid AC/DC microgrid considering incentive‐based demand response program

AbstractIncreasing the use of renewable energy in microgrids (MGs) offers environmental and economic benefits. However, the unpredictable and intermittent nature of available resources poses challenges for optimal MG scheduling. Hybrid AC–DC microgrids provide a solution, seamlessly integrating renewables while reducing energy losses and improving power grid reliability. Additionally, incentive‐based demand response programs promote flexible energy consumption, further mitigating the variability of renewable generation and enhancing grid stability. This paper investigates the challenges and potential of high renewable penetration in hybrid AC–DC MGs, analysing the role of demand response programs in system optimization. The microgrid's energy management is modelled using MILP, while a Stackelberg game represents the demand response program. These models are integrated to optimize energy management and demand response jointly. Simulations demonstrate the cost‐saving benefits of this integrated framework, achieved through coordinated flexible resource scheduling and incentive‐based demand response programming.

Thermostat standardization, technology trends, future considerations: Expert interviews

Thermostats dictate the majority of energy consumption in households across North America. Despite this, there are minimal requirements for interface configuration or usability. Furthermore, thermostats have developed into highly sophisticated, multi-modal consumer devices, integrating smart technology and complex automated features. A comprehensive understanding of the benefits and challenges for new, complex thermostat features, as well advisement for the way forward, is unclear. This paper addresses this gap and establishes a harmonized expert opinion through a series of semi-structured interviews. Twenty-five interviewees from private/public industries and academia, with an average of 21 years of experience related to heating/cooling engineering, share their expert opinions for thermostat standardization, technology trends, and future considerations. Overall, experts agree that some degree of standardization is required to improve thermostat usability and put forward critical elements for a standard. Experts offer suggestions for the adoption of smart technology, including demand response programs, automated setbacks, and integration with smartphones/smart homes. Results are supplemented by an AI-generated affinity diagramming exercise and contextualized with a characterization of sixty EnergyStar certified smart thermostats.

Cost-effective and optimal pathways to selecting building microgrid components – The resilient, reliable, and flexible energy system under changing climate conditions

Amidst the changing climate conditions, electricity retailers-led demand response programs and the emergency backup power for possible grid outages are often discussed in isolation, although several underlying linkages exist, which are important for how the existing building stock evolves with the energy transition. This study navigates through the linkages while investigating the levelized cost of electricity (LCOE)-based building microgrid components and undertakes a comparative analysis of energy optimisation models with and without emergency diesel generators. It also examines the building energy system’s resilience, reliability, and flexibility by using OpenStudio and HOMER Grid to develop energy simulation and optimisation models and other probabilistic models for a chosen building archetype in Sydney, Australia. This study finds that excluding the emergency diesel generator will require a larger battery storage system, increasing LCOE from A$0.17/kWh to A$0.20/kWh across climate scenarios. However, the larger battery storage system increases the probability of surviving outages (> 4 h) by around 10 % across climate scenarios. The LCOE increases up to 45 % for outages up to 8 h across climate scenarios and up to 85 % for outages up to 12 h. Additionally, for the building archetype, the probability of grid purchase (below the current average) is 0.78 in 2030, which drops to 0.55 in 2050. The probability of grid sales (above the current average) also drops from 0.69 to 0.46. Thus, while the narratives around the building energy system’s flexibility overstate the electricity exchange between the building and the grid, this study finds that increasing the on-site production utilisation rate and larger battery throughput contributes to demand response application and flexibility.

Improving Participation in Depression Risk Screening for Working Populations: Qualitative Results from Interviews with Six EAP Directors

The purpose of this qualitative study was to provide practice-based evidence of ways to implement an effective and successful workplace depression screening program. Six participants from companies who participated in the workplace response program of Screening for Mental Health, Inc. (now MindWise Innovations) were interviewed to identify what they had found helpful in the online confidential depression screening programs developed for their employees. An inductive analysis of the interview responses resulted in the emergence of nine themes: accessibility, employee assistance programs, online screening, company web page, national observances, education about depression, gender differences, anonymous screening, and measurement of effectiveness.