50716 research outputs found
Sort by
Prudent Electricity Procurement by a Load Serving Entity
No full textMotivated by the projected solar and wind capacity additions around the world, we model the energy procurement decision of a load serving entity (LSE) faced with alternatives of solar power purchase agreements (PPAs), wind PPAs, non-renewable energy forward contracts, and spot energy purchases in a wholesale electricity market with uncertain prices. Using a pseudo-data sample of over one million observations, we estimate a translog cost function to find that the LSE’s own-price elasticity estimates range from −1.87 for nighttime spot MWh demands to −13.1 for forward MWh demands. MWh demands are influenced by solar and wind capacity factors, daytime and nighttime retail sales, and spot energy price forecasts. The LSE’s optimal procurement of solar capacity is roughly twice the wind capacity, corroborating the ratios of projected solar and wind capacity additions in regions around the world. If the LSE’s existing energy mix is nearly all renewable, it becomes carbon-free when solar and wind power purchase agreements have declining energy prices or when forward energy price and spot energy price forecasts increase over time. These results imply that piecemeal policy measures can have conflicting outcomes, calling for integrated resource planning under wholesale market competition and price uncertainty
Providing social support in technology-based service encounters: Activating intrinsic motivations to create better outcomes
No full textThis study explores how customers’ attitudes and preferences influence their interactions with virtual agents and human support across varying task complexities. Customers with a Positive Attitude towards Technology (PAT) demonstrate a clear preference for virtual agents that prioritize efficiency and minimal intrusion, aligning with their technological affinity and expectations for streamlined service. Conversely, individuals with a high Need for Human Interaction (NHI) derive significant benefits from social support, particularly in the context of simple tasks. Interestingly, for such straightforward interactions, the source of support—whether human or virtual—is less critical to satisfaction, provided the interaction meets the social needs of the customer. However, the dynamic shifts when tasks become more complex. In these scenarios, human support becomes indispensable for NHI customers, as virtual agents frequently fall short of delivering the interactional depth and nuanced understanding required for more challenging service exchanges. These findings highlight the importance of tailoring support systems to the affective and interactional preferences of customers. Businesses and designers of support systems should consider these distinctions when implementing virtual agent solutions, ensuring that such systems can accommodate the diverse needs of their users. By doing so, organizations can enhance user satisfaction, optimize support effectiveness, and foster stronger relationships with their customers. This research contributes to the broader understanding of human-technology interaction, offering practical insights for improving customer support strategies in an increasingly digital world
Sleep characteristics and brain structure:A systematic review with meta-analysis
Get PDFBackground: As the global population ages, the prevalence of associated conditions, including neurodegeneration and dementia, will increase. Thus, reducing risk factors is crucial to prevention. Sleep contributes to brain homeostasis and repair, which, if impaired, could lead to neurodegeneration. However, the relationship between sleep characteristics, disorders, and brain morphology is poorly understood in healthy adults. Therefore, we aimed to systematically analyse the literature and clarify how sleep characteristics are associated with brain structures. Methods: We systematically searched PUBMED, MEDLINE, ProQuest, Web of Science, and Scopus for empirical studies of healthy adults examining the associations between sleep characteristics or disorders and brain structure, adjusting for age, gender, and head size. We conducted a meta-analysis with random effects models for volumetric studies and a seed-based spatial analysis for voxel-based morphometry (VBM) studies. Results: One hundred and five articles (60 volumetric, 45 VBM) with 106 studies reporting 108,364 participants were included. Most studies (73.1%) found sleep characteristics and disorders to be associated with predominantly lower brain volumes (cross-sectional: 51.9% of all cross-sectional; longitudinal: 45.5% of longitudinal). In VBM studies, REM sleep behaviour disorder was linked to lower grey matter volume in the right frontal gyrus (z-score = −3.617, 68 voxels, p-value = <0 0.001). Conclusion: Sleep characteristics - poor quality, short or long sleep - and sleep disorders are predominantly associated with lower brain volumes, suggesting that inadequate sleep (short, long or poor quality) might contribute to neurodegeneration. This insight highlights the importance of monitoring, managing, and enforcing sleep health to prevent or mitigate potential neurodegenerative processes.</p
Clinical decision-making:Cognitive biases and heuristics in triage decisions in the emergency department
Get PDFBackground: In emergency medicine, triage decisions are critical for ensuring patient safety and optimizing resource usage. Such decisions involve a complex interplay of rational and analytical thinking, combined with an intuitive and humanistic approach. However, the influence of cognitive biases on triage decisions remains poorly understood. Methods: Between February 20 and June 27, 2023, we conducted an online scenario-based survey with 78 triage-competent Registered Nurses in the emergency department at Princess Alexandra Hospital in Australia. Co-designed with nurse educators and nursing academics, the survey included domains covering demographic information, tailored diagnostic tests to capture the presence of cognitive biases and risk-taking behavior, and six vignettes requiring triage using the Australasian Triage Scale. Logistic mixed-effects and multivariate Poisson regression models were performed to identify the influence of cognitive biases and risk-taking behavior on triage decision accuracy. Results: We identified negative framing bias (82.5 %), anchoring bias (82 %), and availability bias (62.8 %) as the most prevalent cognitive biases among triage nurses. After adjusting for age, sex, education, and triage work experience, no statistically significant associations were observed between cognitive biases or risk-taking behavior and triage accuracy. This indicates that cognitive biases may have a limited influence on well-trained nurses. However, age, sex, and triage work experience were found to be significant predictors of inaccurate triaged decisions. Conclusion: Our study provides preliminary evidence that cognitive biases and risk-taking behavior are not associated with triage accuracy among well-experienced and trained emergency triage nurses. Further research is required to fully understand the impact of cognitive biases on emergency triage decisions.</p
Evidence of pathogens associated with travelers' diarrhea in Thailand:a systematic review
No full textBACKGROUND: Thailand, a major tourist destination, exhibits variations in sanitation and food safety practices that can lead to cases of travelers' diarrhea (TD) caused by a plethora of pathogens. This systematic review synthesizes data on the pathogens associated with TD in Thailand, providing valuable insights into pathogen diversity and distribution, traveler profiles, and geographical regions of concern.METHODS: This systematic review followed the PRISMA guidelines and was registered in PROSPERO (CRD42022346014). A comprehensive search was conducted across PubMed, Embase, Scopus, MEDLINE, and Journals@Ovid databases. The search included terms related to "diarrhea," "travelers," and "Thailand," without restrictions on publication date. Eligible studies focused on travelers to Thailand who developed diarrhea with identified specific pathogens. Data was extracted and synthesized using a narrative approach. The risk of bias was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist.RESULTS: A total of 15 studies met the eligibility criteria, identifying that pathogens related to TD in Thailand were bacteria, particularly enterotoxigenic Escherichia coli (ETEC) (80%), followed by Campylobacter jejuni (33.3%) and Salmonella spp. (40%). Viral pathogens such as rotavirus and norovirus were also notable, with Giardia spp. being the most identified parasite. Pathogen distribution varied across different regions of Thailand, with tourism hubs such as Bangkok, Chiang Mai, Phuket, and Krabi reporting a broader range of infections.CONCLUSIONS: This systematic review highlights the diverse range of pathogens associated with TD in Thailand, with bacterial pathogens, specifically ETEC, being the predominant cause in most studies. The findings underscore the importance of preventive measures, such as improved hygiene practices and food safety awareness, especially in high-risk tourist areas. Further research is needed to understand better the risk factors contributing to TD and to develop targeted interventions for prevention.</p
Independent and joint associations of sedentary behaviour and physical activity with risk of recurrent cardiovascular events in 40,156 Australian adults with coronary heart disease
No full textObjective: Explore the independent and joint associations between sedentary behaviour and physical activity with cardiovascular events, among individuals with coronary heart disease (CHD). Methods: Cohort study including Australians ≥45 years with CHD (2006–2020). Time in sedentary behaviour, walking, moderate-, and vigorous- physical activity were self-reported. Cardiovascular events were identified using health registers (2006–2022). Cox proportional hazard regressions explored the association. Restricted cubic splines explored the shape of the association. Results: There were 40,156 individuals included, with a mean age of 70 (SD=10) years old, 62 % men. During a median of 8.3 (IQR = 10.03) years, 3260 non-fatal-, 5161 total cardiac events, and 14,383 major adverse cardiovascular events (MACE) were recorded. Sedentary behaviour of 7–10.4 h/day was associated with a 15 % lower risk of total cardiac events and MACE compared to ≥ 10.5 h/day. A higher level of moderate-to-vigorous physical activity was associated with a lower risk of cardiovascular events, with 14–21 % lower risk for 1–149 min/week compared to 0 min/week. A similar pattern was seen for walking and activities at a moderate- or vigorous intensity. The joint association of ≥150 min/week of moderate-to-vigorous physical activity and <7 h/day in sedentary behaviour had the lowest risk (29–48 % lower) for cardiovascular events compared to the reference group. However, moderate-to-vigorous physical activity seems to be of greater importance and partly modifies the risk of sedentary behaviour in the joint association. Sedentary behaviour hours were linearly associated with risks of non-fatal and total cardiac events. Meanwhile time in physical activity had a curvilinear association with cardiovascular events, with the greatest benefits at the beginning of the curve. Conclusion: More time in physical activity and less time in sedentary behaviour are associated with a lower risk of cardiovascular events. This emphasizes the importance of providing recommendations for both physical activity and sedentary behaviour to people with CHD.</p
Demand side management with wireless channel impact in IoT-enabled smart grid system
No full textDemand Side Management (DSM) is a vital issue in smart grids, given the time-varying user demand for electricity and power generation cost over a day. On the other hand, wireless communications with ubiquitous connectivity and low latency have emerged as a suitable option for smart grid. The design of any DSM system using a wireless network must consider the wireless link impairments, which is missing in existing literature. In this paper, we propose a DSM system using a Real-Time Pricing (RTP) mechanism and a wireless Neighborhood Area Network (NAN) with data transfer uncertainty. A Zigbee-based Internet of Things (IoT) model is considered for the communication infrastructure of the NAN. A sample NAN employing XBee and Raspberry Pi modules is also implemented in real-world settings to evaluate its reliability in transferring smart grid data over a wireless link. The proposed DSM system determines the optimal price corresponding to the optimum system welfare based on the two-way wireless communications among users, decision-makers, and energy providers. A novel cost function is adopted to reduce the impact of changes in user numbers on electricity prices. Simulation results indicate that the proposed system benefits users and energy providers. Furthermore, experimental results demonstrate that the success rate of data transfer significantly varies over the implemented wireless NAN, which can substantially impact the performance of the proposed DSM system. Further simulations are then carried out to quantify and analyze the impact of wireless communications on the electricity price, user welfare, and provider welfare.</p
A comparative evaluation of 23 projects on mental health and wellbeing for veterans and first responders
No full textBACKGROUND: Veterans and First Responders (VFR) are at risk of developing a range of mental health disorders because of cumulative exposure to critical incidents at work. Two Philanthropic organisations funded 15 organisations, which collectively implemented 23 highly heterogeneous and international early intervention mental ill-health and suicide prevention Projects. The aim was identify and collaborate with Projects with a multi-project evaluation. The evaluation examined multiple domains including intervention effectiveness but critically the implementation processes impacts for potential replication or scale up. This paper reports on the methods and evaluation results of implementation processes, impact analysis and sustainability.METHOD: The evaluation involved ecosystems and complex systems approaches using novel methods and tools. There was multiple preparatory evaluation steps including developing indices for complexity and context. The Global Impact Analytics Framework (GIAF) toolkit was used to evaluate the implementation processes. Methodological tools included qualitative analysis, descriptive statistics, GIAF ladders/scales and checklists (qualitative and quantitative data).RESULTS: We provide the results on characteristics (organisational, Project and participants), GIAF process components (planning, pre-engagement, pre-readiness/readiness, dissemination/diffusion, usability/sustainability, adoption and uptake). All Project interventions were assessed as usable, adoptable and have capacity to be sustained, with financial resources. Uptake of the intervention was mostly high.CONCLUSION: Complex multi-project evaluation of highly heterogenous Projects implemented in the real world across different countries is possible and provides valuable information and learnings. The evaluation results establish benchmarks including Project pre-engagement with potential end-users, continuous, frequent collaboration between Project and evaluation teams, adequate contract duration for sufficient recruitment and intervention.</p