New York City Fire Department

Introduction: First aid is multifaceted, with one scenario involving mass casualty incidents where multiple patients are injured simultaneously. In such situations, triage must first be conducted, followed by the allocation of appropriate medical resources according to the severity of injuries and the available resources. However, emergency care education in Taiwan rarely addresses this topic, often focusing solely on one-on-one scenarios, leading to a disconnect between education and real-world practice. This study surveys perceptions of mass casualty incidents to explore the importance of community people learning to triage, and then provides scientific suggestions on the design of resilience education for Taiwanese people to jointly build a resilient urban and rural area. Methods: According to the medical treatment process of injured and injured patients, it can be divided into three stages: first aid/first response, ambulance transfer, and medical treatment in the hospital. Therefore, this study focuses on “Community people”, “Civilian rescuer”, “Emergency medical practitioners (including fire department)”, and “Hospital medical staff” are the research objects for which questionnaires are distributed. Then use Standard deviation, One-way ANOVA, Scheffe’s method/Tukey’s range test to analyze and obtain key information. Results: The study found that all four groups agreed that courses on “first aid education under 39 hours” and “disaster preparedness education” should include triage training. Additionally, the study found that hospital-based medical personnel and emergency medical practitioners believe that community members with basic first aid training, volunteers of disaster response teams, and community leaders should learn triage, rather than requiring everyone to learn it. Conclusion: This study suggests that triage training should be included as an extension/supplementary course in disaster resilience education or as part of continuing/in-service education. Give priority to those who already have first aid knowledge and disaster prevention teaming skills to improve their survival rate and resilience in emergencies.

This paper presents the research, design, and implementation of a low phase-noise dielectric resonator oscillator (DRO) operating at 9.4 GHz for X-band radar applications. A high-quality-factor dielectric resonator operating in the mode was employed to enhance frequency stability and suppress phase noise. The oscillator was realized using a microstrip coupling structure, with a GaAs FET transistor serving as the active element in the feedback network. Comprehensive electromagnetic and circuit-level simulations were conducted in CST and ADS to optimize the resonator coupling and feedback configuration, ensuring stable oscillation and effectively mitigating spurious modes. Compared with conventional oscillator designs, the proposed DRO demonstrates superior frequency stability and reduced phase noise, while maintaining a compact form factor. These characteristics render the proposed design highly suitable for modern X-band radar front-ends as well as other advanced microwave communication systems requiring low-noise and high-stability local oscillators.

The California Prescribed Fire Monitoring Program dataset (2019–2024) provides comprehensive ecological monitoring data from prescribed fire treatments across California’s diverse forest ecosystems. This dataset encompasses forest structure and cover, fuel loads, and post-fire recovery metrics, collected using a standardized protocol, from over 36 disparate sites (114 burn units, 972 plots, and 1,838 total surveys). Data collected during pre-fire, immediate, and multi-year post-fire sampling episodes allow for robust analysis of prescribed fire effects across variable environmental conditions. The monitoring framework captures key ecological indicators, including tree mortality, fuel consumption, understory vegetation response, species composition, and regeneration. This dataset can address critical knowledge gaps regarding prescribed fire effectiveness for ecological restoration, hazardous fuel reduction, and ecosystem resilience objectives. These data can support evidence-based fire management decisions, validate fire effects models, and establish baseline reference conditions for future prescribed fire implementation throughout California’s fire-prone landscapes.

This analysis examines the alignment of the Public Health Accreditation Board (PHAB) standards, the Mobilizing for Action through Planning and Partnerships (MAPP) model, and the Pennel evaluation tool. Despite the growing use of Community Health Assessments (CHAs) and Community Health Improvement Plans (CHIPs), variation in quality and evaluation persists. The analysis identifies convergence, divergence, and integration opportunities to inform more cohesive and sustainable public health improvement strategies. An alignment analysis was conducted through a document review of the PHAB Standards (v2022, initial accreditation), the MAPP model, and the 17-item Pennel evaluation tool. A structured matrix categorized alignment as full, partial, or absent, supported by thematic coding and expert validation for consistency and reliability. The present analysis focuses on the approaches used by US local health departments conducting CHA/CHIP development and accreditation activities. The unit of analysis was not individuals but rather the core components of each approach as articulated in public documentation, handbooks, and peer-reviewed sources. Alignment was evaluated across three themes: Community Engagement & Governance, Data and Health Equity, and Strategy Development & Implementation. The analysis revealed strong alignment across the approaches in stakeholder engagement, data-informed decision-making, and goal setting. Divergence was observed in implementation specificity and sustainability planning. PHAB emphasized compliance documentation; MAPP prioritized participatory planning; and the Pennel tool provided guidance on evaluation and accountability. A complementary approach that integrates the evaluative rigor of the Pennel tool, the procedural depth of MAPP, and the accountability of PHAB could foster a more equitable, responsive, and sustainable public health improvement. Findings underscore the need for public health agencies to support this integration by developing implementation guidance, training, and resources for evaluation. This integration has the potential to bridge accreditation compliance and meaningful health outcomes, advancing toward Public Health 3.0.

Abstract Consolidating and translating knowledge about complex environmental processes for decision makers and the public is a multifaceted challenge. Landscape fire, for instance, impacts a wide range of ecological and social values, and communication takes place in a crowded and contested information environment. Evidence briefs are a tool for clearly communicating current knowledge and are commonly used in the health sector and public policy. This raises the questions of whether, and how, evidence briefs could support the management of landscape fire and other environmental issues. Drawing on findings from existing interdisciplinary fire research, we develop four principles to support effective use of evidence briefs for landscape fire applications: (1) Actively engage with complexity and uncertainty whilst highlighting areas of agreement, (2) Recognise diverse ways of knowing, (3) Continually refer back to the problem and goal at the centre of the brief and (4) Embed evidence briefs within a larger process of relationship building and decision‐making. Synthesis and applications. For evidence briefs to provide value to the ecological management and natural hazards community and to the broader public, researchers and practitioners need clear guidance on how briefs must be developed to address a broad spectrum of issues. We propose that principles relating to complexity, diverse forms of knowledge, clear objectives and relationship building will support the delivery of effective and timely evidence briefs.

The rising importance of cryptocurrencies as financial assets pushed their applicability from an object of speculation closer to standard financial instruments such as loans. In this work, we initiate the study of secure protocols that enable fiat-denominated loans collateralized by cryptocurrencies such as Bitcoin. We provide limited-custodial protocols for such loans relying only on trusted arbitration and provide their game-theoretical analysis. We also highlight various interesting directions for future research.

IntroductionAbout 20% of police calls involve a person experiencing a behavioral health crisis. To better address these community member’s needs and reduce risk of harm, jurisdictions are developing programs that shift calls for crises related to homelessness, addiction, and mental health to non-law enforcement alternatives. In responding to these calls, first responders working in these alternative response programs are exposed to a different set of moral dilemmas and pressures, increasing their risk of developing moral injury.MethodsThe Alternative Response Program Moral Injury and Burnout Model highlights causes of exposure to potentially morally injurious events and the interplay between moral distress, moral injury, and burnout among first responders working in alternative response programs. The conceptual model was developed through a multi-year participatory action research (PAR) study with members of a large urban alternative response program. The article draws on a highly diverse set of data sources that contributed to the development and refinement of the model, including focus group discussions, analysis of call logs, assessment of moral injury, and reflective conversations with members and leaders of the alternative response program. Through our collaboration, we identified contributory factors that can produce moral injury and opportunities for interventions to mitigate moral injury. We piloted several interventions collaboratively developed with team members and hypothesized to reduce moral distress and injury based on this model.ResultsOur model explains sources of moral dilemmas and how these can lead to moral distress, moral injury, and burnout. The model also points to intervention pathways to reduce or prevent these outcomes. We provide illustrations of how moral injury arises, using data from the program members, describe six pathways, and share examples for how moral injury may be mitigated.DiscussionDespite scarce research in first responders, moral injury and burnout are growing concerns in alternative response programs. Our goal was to amplify participants’ voices to highlight both their struggles as well as proposed interventions fostering resilience. Through close collaboration, we developed a moral injury model that resonates for these first responders and can guide a better understanding of issues and pathways for interventions among high-risk occupational groups.

This study proposes a novel distributed Model Predictive Control (MPC) framework incorporating virtual tube constraints to address the dual challenges of safe navigation and efficient target attainment for Unmanned Aerial Vehicle (UAV) swarms in complex low-altitude traffic environments. An adaptive neighbor interaction mechanism is proposed that dynamically adjusts based on real-time perception and communication capabilities, enabling effective swarm coordination regardless of communication availability. Then, a multi-objective optimization formulation is constructed integrating maximum velocity pursuit, trajectory tracking precision and lateral deviation minimization within virtual tube boundaries. To ensure the stability of terminal velocity, an adaptive speed weight adjustment mechanism was specifically designed. Thus, a computationally efficient distributed MPC is designed utilizing dynamic local state information on switching topology. Through rigorous Lyapunov-based stability analysis and constraint satisfaction proofs, we establish the theoretical guarantees for both asymptotic stability and recursive feasibility of the proposed algorithm. Extensive numerical simulations demonstrate superior performance in complex traffic scenarios, showing faster target convergence while maintaining safe inter-agent distances and lateral deviation margins across various communication-restricted conditions.