Service Resources Research Articles

EFFICIENCY OF URBAN PASSENGER TRANSPORT BY BUS: AN APPLICATION TO THE CASE OF CUENCA-ECUADOR

Objective: The study aims to analyze the technical and scale efficiency of public transportation in Cuenca, Ecuador, using Data Envelopment Analysis (DEA). It evaluates both supply and demand aspects. Theoretical Framework: DEA measures the efficiency of decision-making units (DMUs) in using inputs to produce outputs. It's widely used to assess public transportation efficiency by comparing resource usage and service outcomes. Method: The study analyzes 37 DMUs, considering kilometers traveled, number of frequencies, and total fleet as inputs, and operating costs and passenger demand as outputs. Results and Discussion: DEA_Demand showed a 90% technical efficiency and 45% scale efficiency. DEA_Offer showed 94% and 96% efficiency, respectively, highlighting the potential for adjustments in both approaches. Research Implications: The findings help policymakers optimize resource allocation and improve public transport services. Originality/Value: The study uniquely combines supply and demand analysis using DEA in a mid-sized city like Cuenca, offering actionable insights.

Delay-aware resource allocation for partial computation offloading in mobile edge cloud computing

Mobile Edge Cloud Computing (MECC), as a promising partial computing offloading solution, has provided new possibilities for compute-intensive and delay-sensitive mobile applications, which can simultaneously leverage edge computing and cloud services. However, designing resource allocation strategies for MECC faces an extremely challenging problem of simultaneously satisfying the end-to-end latency requirements and minimum resource allocation of multiple mobile applications. To address this issue, we comprehensively consider the randomness of computing request arrivals, service time, and dynamic computing resources. We model the MECC network as a two-level tandem queue consisting of two sequential computing processing queues, each with multiple servers. We apply a deep reinforcement learning algorithm called Deep Deterministic Policy Gradient (DDPG) to learn the computing speed adjustment strategy for the tandem queue. This strategy ensures the end-to-end latency requirements of multiple mobile applications while preventing overuse of the total computing resources of edge servers and cloud servers. Numerous simulation experiments demonstrate that our approach is significantly superior to other methods in dynamic network environments.

Streaming and Elastic Traffic Service in 5G-Sliced Wireless Networks and Mutual Utilization of Guaranteed Resource Units

Researchers of 5G-sliced Wireless Networks are faced with the task of achieving, at the same time, (i) mandatory isolation among network slices and (ii) the effective utilization of resource at Fifth Generation Base Station (gNB). This article proposes the second version of the Preemption-based service Prioritization (PP2) scheme that merges the capabilities of the classical Resource Reservation (RR) and Service Prioritization (SP) schemes and realizes the coexistence of non-TCP streaming and TCP elastic traffic at gNB. Analytical methods are given for Dynamic Resource Sharing (DRS) and Dynamic Resource Reallocation (DRR) with data rate reduction and service preemption. As main results, under some baseline scenario, the PP2 scheme, in comparison with RR, does increase the admission probability up to 99.999% at the system while ensuring 100% in system capacity utilization.

Epidemiology of obesity during pregnancy in Europe: a systematic review

Abstract Background Obesity during pregnancy poses inter-generational health risks and places added burden on healthcare systems. Characterising levels of obesity during pregnancy is necessary to guide future research, policy and practice. Methods The systematic review was performed according to PRISMA guidelines. PubMed, Embase and Web of Science were searched. Studies published between 2009 and 2023 that report the prevalence of obesity during pregnancy in countries in the World Health Organization (WHO) European region were eligible. The Joanna Briggs Institute Prevalence Critical Appraisal tool was used. Two reviewers screened studies independently. A single reviewer completed data extraction and quality assessments, a second checked 20% of extractions and a third resolved disagreements. Narrative synthesis was completed. Results 100 studies reporting the prevalence of obesity during pregnancy in the WHO European region were identified. 59% from Western Europe, 36% Northern, 4% Southern and 1% Eastern. Data within the studies was collected between 1950 and 2019. 35% of studies reported national estimates, 65% regional. 39% studies had measured height and weight, 34% did not report how either were ascertained, 6% used self-report for both, 17% had self-reported height but measured weight, 4% a mixture of self-report and measurement. The smallest sample was 157 while the largest was 1,891,097. Estimated prevalence of obesity during pregnancy ranged from 2.3% (Sweden, data collected 1982-1989) to 28.3% (England, 2007). Conclusions This review identifies variation in the prevalence of obesity during pregnancy in the WHO European region. This may reflect diverse sociocultural contexts, different methodological approaches and temporal trends. There was limited evidence available for Southern and Eastern Europe. Key messages • There are high levels of obesity during pregnancy within the WHO European region. • Enhanced primary prevention and resourcing of obstetric services is needed.

Re-conceptualising the Theory of Justice and the Needs of Victims of Sexual Violence in Nigeria: an Appraisal of a Victim Centered Approach

Abstract Background In the 21st century, the recognition of the rights and needs of victims of sexual violence has emerged as a fundamental discourse within international, regional, and local policy agendas. This has been influenced by the lasting psychological, emotional, and physical effects of sexual violence on the victims. These commentaries and agitation have spurred the need for alternative ways in which the Nigerian criminal justice system can be strengthened by incorporating criminal justice mechanisms and interventions that would enhance the needs and interests of victims in accessing justice despite its adversarial system of justice. Methods This study aims to appraise the different mechanisms of justice, needs, and interests of victims of sexual violence through a theoretical lens and drawing lessons from South Africa and Australia. To achieve this work, a doctrinal research methodology that utilized existing literature and secondary sources such as textbooks and online websites was adopted. Results The study found that there is a need for accountability for the protection of victims, implementation of legislation, and scaling up of resources for effective support services. In addition, the absence of resources, effective monitoring and compliance institutions, monitoring reports, specialized courts, and special regulations hampers the implementation of a victim-centered approach. Among others, the study recommends an all-inclusive criminal justice mechanism that would further incorporate a victim-centered approach towards advancing the rights and quality of justice for victims of Sexual Violence and the need for a victim impact statement to our criminal justice system for cases of sexual violence. Conclusion The study concludes that there is a need to make provisions for more effective alternative responses to incorporate the justice interests and needs of victims of sexual violence.

Rancangan Sistem Pendukung Keputusan Pemilihan Calon Pegawai Honorer Pemerintah Kabupaten Lamandau Menggunakan Metode Profile Matching

This study aims to design a Decision Support System (DSS) that implements the Profile Matchingmethod for the selection of honorary employees in the Lamandau District Government. The oftennon-systematic selection process results in less objective decisions, necessitating a system that canenhance effectiveness and transparency in decision-making. The Profile Matching method is usedto compare the profiles of candidates with predetermined criteria, leading to a fairer and moreaccurate selection process. Data were collected through interviews with relevant stakeholders inthe Lamandau District Government, which were then analyzed to identify appropriate selectioncriteria. The findings indicate that the application of DSS can reduce subjectivity and improveclarity in the evaluation process. Additionally, the designed computer-based system facilitatesfaster data processing and presents information in a more comprehensible manner. Thus, thisresearch is expected to make a significant contribution to the development of employee selectionsystems in local government and enhance the quality of human resources in public service. Theimplementation of information technology in DSS is anticipated to serve as a reference for futureresearch in decision-making and human resource management.

Implementation Strategy Analysis of Network Security using dalo RADIUS and Pi-hole DNS Server to enhance Computer Network Security, Case Study: XYZ as a Fintech Company

According to the annual report by the National Encryption Agency in 2023, Indonesia had the highest number of cyber-attack sources, with over 1 million attacks, which has increased quite rapidly compared to the last 3 years. Several online media platforms have reported incidents of this nature over the past three years. Among the 10 institutions implicated in the present incident, it has been confirmed that 6 of them are Fintech institutions. The incident's factors are various, including the user's lack of awareness who accessed an unofficial website outside the company's production website. This act ultimately proved to be detrimental to the company. Therefore, this study highlights the importance of RADIUS (Remote Authentication Dial-In User Service) as a comprehensive security tool that contributes to mitigating unauthorized access and strengthening network defenses against emerging threats. This research focuses on XYZ, a Fintech Company, using it as a case study. The main discussion in this paper focuses on utilizing the daloRADIUS server to resolve authorization concerns regarding network security. Pi-hole DNS Server is also used in this research to block access to illegal sites such as pornography and online gambling. The results of this research are proof of the success of a combination of daloRADIUS server components, RADIUS router, and Pi-hole DNS Server in blocking users who are detected accessing illegal sites and are also observed regarding the use of daloRADIUS Server resources in a usage range ranging from 10 active users to 300 active users.

Emergency department frequent users in the paediatric population: a retrospective analysis in Rome

Abstract Background Recent studies have reported the increasing utilisation of the Emergency Departments (EDs) for non-urgent attendances by people aged <18 years. The aim of this study is to describe the characteristic of the paediatric frequent user (FU) population, highlighting the differences between FUs and non-FUs, and to identify factors linked to appropriate ED attendance, comparing the level of variability attributed to the geographical and family physician components. Methods A retrospective cohort study was carried out of the ED attendances in 2022 in the 8 EDs of the Local Health Authority Roma 1 geographical area, in Rome. The cohort was enrolled from the regional Healthcare Emergency Information System. Records included information on number of attendance, age and gender, usage of emergency medical service (EMS), triage code, appropriateness of attendance. Multivariable nested logistic regression was performed to identify the characteristics of FU and non-FU attendances and the predictors for appropriateness of attendances. Results In 2022, the total number of children with at least 1 ED attendance is 24.824 and a total of 35.691 attendances were recorded. The regression analysis highlights that the appropriateness of attendances is associated to the female gender (OR male: 0.84), age <1 year (OR: 2.06), the usage of EMS (OR: 2.00), high triage code and being a FU (OR FU: 1.53). The family physician group have a greater influence of District group but lower influence of single patient characteristics group to determine the appropriateness of paediatric ED attendances (MOR District: 1.73; MOR PCP: 1.84; MOR single patient characteristics: 2.75). Conclusions Frequent use of the ED is partially associated with an inappropriate use of EDs, mostly due to the specific patients’ characteristics. It is therefore necessary to adopt strategies to improve the appropriate use of health service resources in order to provide quality health solutions to real health needs. Key messages • This is the first study that defines an ED paediatric FU profile in Italy. • It compares the level of variability attributed to the geographical component and family physician components.

Cloud IaaS Optimization Using Machine Vision at the IoT Edge and the Grid Sensing Algorithm

Security grids consisting of High-Definition (HD) Internet of Things (IoT) cameras are gaining popularity for organizational perimeter surveillance and security monitoring. Transmitting HD video data to cloud infrastructure requires high bandwidth and more storage space than text, audio, and image data. It becomes more challenging for large-scale organizations with massive security grids to minimize cloud network bandwidth and storage costs. This paper presents an application of Machine Vision at the IoT Edge (Mez) technology in association with a novel Grid Sensing (GRS) algorithm to optimize cloud Infrastructure as a Service (IaaS) resource allocation, leading to cost minimization. Experimental results demonstrated a 31.29% reduction in bandwidth and a 22.43% reduction in storage requirements. The Mez technology offers a network latency feedback module with knobs for transforming video frames to adjust to the latency sensitivity. The association of the GRS algorithm introduces its compatibility in the IoT camera-driven security grid by automatically ranking the existing bandwidth requirements by different IoT nodes. As a result, the proposed system minimizes the entire grid’s throughput, contributing to significant cloud resource optimization.

Request Deadline Split and Interference‐Aware Request Migration in Edge Cloud

ABSTRACTEdge computing extends computing resources from the data center to the edge of the network to better handle latency‐sensitive tasks. However, with the rise of the Internet of Things, edge devices with limited processing capabilities face difficulties in executing requests with fluctuating request peaks. In order to meet the deadline constraints of latency‐sensitive tasks, a feasible solution is to offload some latency‐sensitive tasks to other nearby edge devices. This article studies the problem of request migration in edge computing systems and minimizes the request deadline violation rate based on actual online arrival patterns, performance interference phenomena, and deadline constraints. Since a request contains multiple services and request migration will lead to changes in server resource competition pressure, we split the problem into three sub‐problems, dividing the request deadline to determine the maximum response time of the service, determining the performance of the service under different resource pressures and the request migration strategies. To this end, we propose two deadline splitting methods, a performance interference model under multi‐resource pressure, and two heuristic request migration strategies. Since this article considers online edge scenarios, the number and type of requests are black boxes. We conduct simulation experiments and find that our method has only one‐third the number of request violations of other methods.

Factors influencing the use of e-library resources by postgraduate engineering students at Kyambogo University in Uganda

The aim of this study was to investigate the factors influencing the use of e-library resources among postgraduate engineering students at Kyambogo University in Uganda to make suggestions on how to improve access to and use of e-library resources. The study adopted a survey research design to collect data from postgraduate engineering students. Following a census sampling strategy, data was obtained from 58 out of 80 registered postgraduate engineering students using online self-administered questionnaires. The findings revealed that the use of e-library resources by postgraduate engineering students was influenced by ease of use, convenience, level of awareness, and information search skills. However, access restrictions and high internet costs negatively affected e-library resources usage. It is the conclusion of the study that the use of e-library resources was largely influenced by personal factors. This study has implications on e-library resources collection development, policy development, and service delivery in academic libraries. The study bridges the knowledge gap in the use of e-library resources among postgraduate engineering students.

FedNIC: enhancing privacy-preserving federated learning via homomorphic encryption offload on SmartNIC

Federated learning (FL) has emerged as a promising paradigm for secure distributed machine learning model training across multiple clients or devices, enabling model training without having to share data across the clients. However, recent studies revealed that FL could be vulnerable to data leakage and reconstruction attacks even if the data itself are never shared with another client. Thus, to resolve such vulnerability and improve the privacy of all clients, a class of techniques, called privacy-preserving FL, incorporates encryption techniques, such as homomorphic encryption (HE), to encrypt and fully protect model information from being exposed to other parties. A downside to this approach is that encryption schemes like HE are very compute-intensive, often causing inefficient and excessive use of client CPU resources that can be used for other uses. To alleviate this issue, this study introduces a novel approach by leveraging smart network interface cards (SmartNICs) to offload compute-intensive HE operations of privacy-preserving FL. By employing SmartNICs as hardware accelerators, we enable efficient computation of HE while saving CPU cycles and other server resources for more critical tasks. In addition, by offloading encryption from the host to another device, the details of encryption remain secure even if the host is compromised, ultimately improving the security of the entire FL system. Given such benefits, this paper presents an FL system named FedNIC that implements the above approach, with an in-depth description of the architecture, implementation, and performance evaluations. Our experimental results demonstrate a more secure FL system with no loss in model accuracy and up to 25% in reduced host CPU cycle, but with a roughly 46% increase in total training time, showing the feasibility and tradeoffs of utilizing SmartNICs as an encryption offload device in federated learning scenarios. Finally, we illustrate promising future study and potential optimizations for a more secure and privacy-preserving federated learning system.

Analysis of the Application and Prospects of Intelligent Technology in Sustainable Railway Operations

With the rapid development of technology, intelligent technology plays an increasingly important role in the sustainable operation of railways. This paper explores the application and prospects of intelligent technology in sustainable railway operations, emphasizing its key roles in enhancing operational efficiency, strengthening safety assurance, optimizing passenger experience, and promoting environmental protection and energy conservation. Through intelligent dispatching, real-time monitoring, big data prediction, personalized services, and mobile ticketing technologies, the railway system achieves efficient resource allocation and service innovation. The intelligent transformation of railways demonstrates significant economic and social benefits, contributing to emission reduction targets and sustainable development. Future efforts should focus on strengthening top-level design, technological innovation, standard construction, and network security to advance the intelligent railway process and co-create a new era of smart, green, and efficient railway transportation.

Reduction in mutualistic ant aggressive behavior upon sugar supplementation

AbstractMutualistic interactions between species are widespread and important for community structure and ecosystem function. In a changing environment, the proximate mechanisms that maintain mutualisms affect their stability and susceptibility to perturbation. In ant‐plant mutualisms, ants defend their host plants against herbivores or competing plants in exchange for housing or food. While the phenomenon of species exchanging services for resources is well documented, how such arrangements are maintained is not. There are at least four hypothesized mechanisms through which plants use sugar to induce ant defense against herbivores. Three such hypotheses (“deficit”, “fuel for foraging”, “predictable rewards”) predict that the appearance of a new sugar source near the host plant would increase the rate of ant attacks against herbivores, but the fourth hypothesis (“attract and distract”) predicts the opposite. To examine how the mutualism between Triplaris americana and Pseudomyrmex dendroicus would be affected, we simulated the appearance of a novel sugar source at a random half of 34 T. americana trees with P. dendroicus colonies. Compared to control colonies, those with access to the sugar source were less likely to attack herbivorous insects (Nasutitermes sp. termites). Thus, our findings support the “attract and distract” hypothesis. We infer that this ant‐plant mutualism could be destabilized by the appearance of an alternative sugar source, such as a nectar‐producing plant or honeydew‐excreting insect. More broadly, we conclude that the mechanisms responsible for maintaining mutualistic relationships are relevant for understanding how ecological communities are affected by environmental change.Abstract in Spanish is available with online material.

Implementation of High Availability Based on Load Balancing and Failover Method in E-commerce Using MySQL Database

The rapid growth of e-commerce has brought about challenges in managing traffic loads and ensuring the availability of database servers. One critical issue is what happens when the main database server fails, potentially leading to downtime or data loss. This research aims to address these problems by optimizing server resource distribution and implementing data replication across multiple database servers. The goal is to enhance system efficiency, prevent server overloads, ensure data availability, and minimize downtime or data loss when server failures occur.This research utilizes a multi-stage methodology. First, data collection was conducted to gather relevant information. In the second stage, a needs analysis was performed to identify system requirements. The third stage involved designing the system architecture, including the creation of entity-relationship diagrams (ERD), flowcharts, and network topologies. In the final stage, the system was implemented through database replication and the application of failover methods.The results demonstrate that the failover mechanism operates effectively, ensuring that data is successfully replicated across all database servers. This confirms that the system achieves high availability and minimizes the risk of data loss or service downtime. The implications of this research provide a reliable solution for improving the resilience and performance of e-commerce systems, particularly in managing database server failures.

Navigating the Modern Libraryscape: The Changing Roles, Labor, and Education of Public Librarians

Public libraries and their staff have recently faced a wide array of challenges. Some of these challenges include supporting services for incarcerated individuals, unhoused patrons, and others experiencing crises (American Library Association, 2023; Gross et al., 2024; Knox, 2023; Wahler and Johnson, 2024). These recent challenges give us, as scholars and educators, an opportunity to take a step back and trace the dynamic work of public library professionals. In response, public library workers take on a variety of tasks. These may involve connecting patrons to social service resources, partnering with community organizations, or creating programs to support specific community needs and interests. Some of this work undertaken by public library staff involves routine, everyday tasks. Other labor is in response to community crises. Understanding this work is central to our ability to consider how the realities of public library work impact LIS scholarship and education. This panel provides a space for open conversation among panelists and the ALISE community to address the following overarching questions: What does the work of public librarianship look like, in terms of roles and labor? How can a better understanding of these roles and the reality of public library work inform how we approach LIS scholarship and teaching? Our panel will consider several aspects of public library work, with a view toward connecting theory, research, and practical workforce preparation.

Burden of Non-Protocolized Patient Transport Outside of Response Area on a Rural Emergency Medical Services System

Objectives Transport destination decisions by prehospital personnel depend on a combination of protocols, judgment, patient acuity, and patient preference. Non-protocolized transport outside the service area may result in unnecessary time out of service and inappropriate resource utilization. Scant research exists regarding clinician rationale for destination decisions. Methods We retrospectively reviewed one year of scene transports by a single rural, hospital-based emergency medical services (EMS) system. We collected dispatch, patient demographic, primary impression, and transport data from prehospital records and matched them to emergency department (ED) data. We characterized rationale for transport decisions and compared rates of hospital admission and specialist consultation in the ED as surrogates for decision appropriateness. Results We reviewed 2,223 patient transports, 281 of which were transported out of the service area. The most common reasons for out-of-area transport were patient preference NOT related to prior medical care (40%) and clinician judgment (24%). Admit rates were highest for per protocol (85%) and patient preference related to prior medical care (67%) groups and lowest for no explanation (41%) and clinician judgment (47%) groups. Rates of in person specialist consultation in the ED were highest in per protocol (69%) and clinician judgment (47%) groups and lowest in no explanation (23%) and patient preference NOT related to prior medical care (30%) groups. Clinician judgment was less predictive of admission and specialist consultation for non-trauma and pediatric patients than for all patients. Median time out of service was more than twice as long for out-of-area transports (140 min) compared to patients transported to the nearest facility (62 min). For out-of-area transports discharged from the ED without specialty consultation (n = 104), ambulances traveled an additional 52 miles/patient compared to theoretical transport to nearest facility. Conclusions Unit out of service time more than doubled for non-protocolized transports outside of the service area and rationale for destination decisions variably predicted admission and specialist consultation rates. Patient preference NOT related to prior medical care and, in pediatric and non-trauma populations, clinician judgment, were less predictive of admission and specialist consultation. Transport guidelines should balance rationale for transport destination and patient characteristics with resource preservation, especially in low-resource systems.

Case Study on the Inherent Mechanisms Driving Industrial Innovation through Data Empowerment

In the context of the profound integration of big data, artificial intelligence technologies, and industries, both data resources and digital technologies became crucial pillars supporting the development of industrial innovation. They played key roles in enhancing the innovation capabilities of industries. In this regard, the present study employed the specific case of the intelligent brain of the Taizhou Machine Tool Industry. Utilizing grounded theory, the research integrated relevant data through coding analysis and category extraction to construct a comprehensive theoretical model of the intrinsic mechanisms driving industrial innovation through data empowerment. The study revealed that the realization of data-empowered industrial innovation followed a logical path of 'data resource services data capability spillover industrial innovation achievement.' Specifically, data empowerment operated across three dimensions: industrial resources, production, and ecology, effectively propelling the realization of industrial innovation. From a systematic perspective, this research analyzed the intrinsic mechanisms of data-empowered industrial innovation, deepening the theoretical understanding of industrial innovation. In the context of past industrial digitization transformation, these findings provided valuable insights for guiding industrial innovation development.

Location-aware job scheduling for IoT systems using cloud and fog

The rapid growth of Internet of Things (IoT) applications generates vast volumes of high-speed data streams from numerous devices. Cloud computing solutions often handle and manage this data; however, for certain applications, the latency introduced by transmitting data from edge devices to the cloud may be unacceptable. This issue is exacerbated by the bandwidth constraints of public networks, which become significant barriers in large-scale IoT implementations. Consequently, effective resource management, service management, data storage, and power management require more robust infrastructure and complex protocols. An "intelligent gateway" based on fog computing can enhance the efficient utilization of cloud and network resources. Resource planning and management in a fog-cloud environment significantly impact system performance, particularly latency. This problem is known to be NP-hard. This paper addresses the challenge of lifetime optimization for scheduling data-intensive tasks in fog and cloud-based IoT systems. Initially, we propose an Integer Linear Programming (ILP) optimization model to frame the problem. Subsequently, we introduce a heuristic method named Data-Locality Aware Job Scheduling in Fog-Cloud (DLSFC), which is derived from the proposed formulation. The effectiveness of DLSFC is evaluated across various system characteristics, with results demonstrating that DLSFC achieves solutions within 85 % of the ideal outcome provided by the LP solver.

Ambulance Transports from NCAA Division 1 Football Games.

There is significant public health interest towards providing medical care at mass-gathering events. Furthermore, mass gatherings have the potential to have a detrimental impact on the availability of already-limited municipal Emergency Medical Services (EMS) resources. This study presents a cross-sectional descriptive analysis to report broad trends regarding patients who were transported from National Collegiate Athletic Association (NCAA) Division 1 collegiate football games at a major public university in order to better inform emergency preparedness and resource planning for mass gatherings. Patient care reports (PCRs) from ambulance transports originating from varsity collegiate football games at the University of Minnesota across six years were examined. Pertinent information was abstracted from each PCR. Across the six years of data, there were a total of 73 patient transports originating from NCAA collegiate football games: 45.2% (n = 33) were male, and the median age was 22 years. Alcohol-related chief complaints were involved in 50.7% (n = 37) of transports. In total, 31.5% of patients had an initial Glasgow Coma Scale (GCS) of less than 15. The majority (65.8%; n = 48; 0.11 per 10,000 attendees) were transported by Basic Life Support (BLS) ambulances. The remaining patients (34.2%; n = 25; 0.06 per 10,000 attendees) were transported by Advanced Life Support (ALS) ambulances and were more likely to be older, have abnormal vital signs, and have a lower GCS. This analysis of ambulance transports from NCAA Division 1 collegiate football games emphasizes the prevalence of alcohol-related chief complaints, but also underscores the likelihood of more life-threatening conditions at mass gatherings. These results and additional research will help inform emergency preparedness at mass-gathering events.