Access Time Research Articles

Determining the Optimal Fire Station Locations in Baghdad Al-Rusafa Using GIS Models and Data

The study of sitology has a long historical background and has recently attracted the attention of many researchers. One of its most important branches is the location of fire stations, which are of great importance in major cities. One of the most important features of an appropriate location is increasing coverage and reducing access time. In this research, geographic information systems were used to choose the most appropriate sites on the Al-Rasafa side in the city of Baghdad/Iraq to facilitate access to the scene of the accident as soon as possible from the fire stations and through the use of the geographical database of the city of Baghdad. GIS analysis was used to build the mathematical model that was adopted based on a number of criteria, including land use, distance to commercial malls, government and educational institutions, hospitals, and distance from existing fire stations. A weight was given to each of these criteria using the Overlay Weighted tool from spatial analysis in geographic information systems to determine the most appropriate areas. Then the road network was added to the criteria used, and then the selection was made on the areas close to the main roads, so the search results were to determine the best sites in Al-Karrada, Al-Sadr City, and Al-Adhamiya.

Tutorial on Molecular Latent Space Simulators (LSSs): Spatially and Temporally Continuous Data-Driven Surrogate Dynamical Models of Molecular Systems.

The inherently serial nature and requirement for short integration time steps in the numerical integration of molecular dynamics (MD) calculations place strong limitations on the accessible simulation time scales and statistical uncertainties in sampling slowly relaxing dynamical modes and rare events. Molecular latent space simulators (LSSs) are a data-driven approach to learning a surrogate dynamical model of the molecular system from modest MD training trajectories that can generate synthetic trajectories at a fraction of the computational cost. The training data may comprise single long trajectories or multiple short, discontinuous trajectories collected over, for example, distributed computing resources. Provided the training data provide sufficient sampling of the relevant thermodynamic states and dynamical transitions to robustly learn the underlying microscopic propagator, an LSS furnishes a global model of the dynamics capable of producing temporally and spatially continuous molecular trajectories. Trained LSS models have produced simulation trajectories at up to 6 orders of magnitude lower cost than standard MD to enable dense sampling of molecular phase space and large reduction of the statistical errors in structural, thermodynamic, and kinetic observables. The LSS employs three deep learning architectures to solve three independent learning problems over the training data: (i) an encoding of the high-dimensional MD into a low-dimensional slow latent space using state-free reversible VAMPnets (SRVs), (ii) a propagator of the microscopic dynamics within the low-dimensional latent space using mixture density networks (MDNs), and (iii) a generative decoding of the low-dimensional latent coordinates back to the original high-dimensional molecular configuration space using conditional Wasserstein generative adversarial networks (cWGANs) or denoising diffusion probability models (DDPMs). In this software tutorial, we introduce the mathematical and numerical background and theory of LSS and present example applications of a user-friendly Python package software implementation to alanine dipeptide and a 28-residue beta-beta-alpha (BBA) protein within simple Google Colab notebooks.

Factors affecting treatment delays among malaria patients presenting at health facilities in Guinea, 2022–2023

BackgroundEarly identification and management of cases are key for controlling and eliminating malaria. This study aimed to assess the factors associated with the delay malaria treatment in Guinea.MethodsCross-sectional study was conducted at 60 health facilities in eight administrative regions from December 2022 to March 2023. Patients with a diagnosis of malaria through either microscopy or a rapid diagnostic test (RDT), were interviewed using a standardized questionnaire. Treatment delays were defined as seeking care 48 hours after the onset of symptoms. Logistic regression was performed to assess factors associated with treatment delay. Adjusted odds ratio (OR) and confidence interval (CI) were used to explain the associated factors.Results3,300 malaria patients were included and the findings showed a median time of symptoms onset and access of malaria treatment was 3.04 days. Alarmingly, only 800 (24.24%) of all cases sought and received treatment within 48 hours of symptom onset. The multivariate logistic regression indicated that children under 5 years of age who attempted self-medication for fever were 4.32 times more likely to experience a delay in treatment than those who sought immediate medical care in health facilities (OR:4.32, 95% CI: 2.96–6.36). Children whose parents had no formal education were 3.05 times more likely to experience a delay in treatment (OR:3.05, 95% CI: 1.66–5.60). Moreover, when the disease was considered non-severe the first time by caregivers, OR = 1.71 (95% CI: 1.26–2.33). For those 5 years old and above, using university hospital OR = 4.01, (95% CI: 2.01–8.44), living in Forest Guinea OR = 3.14, (95% CI 1.93–5.10) and Middle Guinea OR = 1.46 (95% CI: 1.09–1.95) were more likely to experience delay treatment.ConclusionsThe proportion of malaria patients with treatment within 48 is low, significantly falling short of the national targets. This substantial delay in treatment was attributed to factors such the lack of formal education, self-medication practices, and failure to recognize the illness severity. These findings underscore the urgent need for NMCP to enhance awareness regarding the importance of early presentation at health facilities, with targeted interventions.

Digital Competences and Years of Access to Technologies Among Chilean University Students: An Analysis Based on the DIGCOMP Framework

This study investigates the relationship between access time to digital technologies and the devel-opment of digital competences among Chilean university students, using the DIGCOMP-PED in-strument based on the DIGCOMP framework. Methods: The instrument was applied to 4360 first-year students at a Chilean public university, and an expert validation process was carried out to identify relevant competences for academic training. Results: The findings indicate a positive but non-linear relationship between years of experience using technologies and performance in certain areas of the DIGCOMP framework. Although the study was conducted between 2021 and 2022, with the follow-up analysis completed in 2024, access alone does not guarantee the acquisition of ad-vanced skills across all competences. Conclusions: The study emphasizes the complexity of the re-lationship between access to technology and the development of digital competences, highlighting the importance of pairing access with quality education and structured guidance in digital literacy to prepare students for the challenges of the digital world.

A Novel Approach for Improving XML Querying over Wireless Broadcast Channels

The querying of large XML data over wireless broadcast channels can reduce bandwidth utilization, cause significant latency, and produce inefficient energy usage. This paper proposes a scheme to improve XML querying over wireless broadcast channels in order to address the issues mentioned above. Various techniques, including partitioning, load balancing, and query routing, have been combined into one approach. The proposed scheme partitions the XML data stream into several partitions based on criteria like document size, type, or content. Each partition is routed to a separate channel to balance the load on each wireless broadcast channel. A query routing mechanism that directs queries to the right channel or combination of channels that hold the relevant XML data partition was implemented. This study simulates, evaluates, and compares the proposed scheme’s performance. The results from the comparison study with existing schemes demonstrate a considerable reduction in the access time for XML querying via wireless broadcast channels.

Abortion access barriers shared in “r/abortion” after Roe: a qualitative analysis of Reddit community post-Dobbs decision leak in 2022

With drastic changes to abortion policy, the months following the Dobbs leak and subsequent decision in 2022 were a uniquely uncertain and difficult time for abortion access in the US. To understand experiences of challenges to abortion access during that time, we used a hybrid inductive and deductive thematic coding approach to analyse descriptions of barriers and their impacts shared in an abortion subreddit (r/abortion). A simple random sample of 10% of posts was obtained from those shared from 02 May 2022 through 23 December 2022; comments were purposively sampled during the coding process. In this sample of submissions (n = 523 posts, 88 comments), people described structural barriers identified in past research, including state abortion bans and gestational limits, high costs, limited appointment availability, and long travel required. Posters also commonly described known social barriers, including limited social support and abortion stigma. Several impactful barriers not well-described in past research emerged inductively, including wait time for receiving mail-ordered abortion medication, low credibility of online ordering platforms, and concerns about legal risks of accessing abortion or related medical care. The most common consequences of experiencing barriers were adverse mental health outcomes, delayed access to care, and being compelled to self-manage their abortion because of access barriers. This analysis provides timely insights into the experiences and impacts of abortion access barriers in a group of people with a range of engagement with clinical abortion care, lived experiences, and points in their abortion processes, with public health implications for mental health and abortion access.

Delivery room dextrose gel for preterm hypoglycaemia (the GEHPPI study): a randomised placebo-controlled trial

ObjectiveEarly hypoglycaemia at the time of neonatal intensive care unit (NICU) admission is common in very/extreme preterm infants. This study aimed to determine whether buccal dextrose gel in the delivery...

Utilisation of New Zealand Rugby's concussion management pathway: A mixed methods investigation.

Concerns around concussion highlight the need for strategies to improve the implementation and translation of concussion guidelines in community sports. This study assessed players' utilisation and compliance with New Zealand Rugby's Concussion Management Pathway (CMP). This pragmatic, mixed methods study comprised of concussion injury surveillance and mapping of players' healthcare touchpoints through the CMP. Semi-structured interviews were conducted to understand stakeholders' experiences. Over the season, 27 different healthcare pathways were identified with 28% of players progressing through all phases of the CMP (ideal pathway). Of the 206 suspected concussions reported over the season, 70% were logged in the CMP phone App, and 89% of these had an associated valid baseline concussion assessment. Prior to returning to contact training, 64% of players obtained a medical clearance. One theme, 'belief in the value of pathway' was identified as a facilitator across all CMP components. Themes such as 'concussion knowledge and the nature of concussion'; 'communication between stakeholders and sufficient information on the process'; and 'strong relationships and clarity around responsibilities' were identified as facilitators across several pathway components. Other facilitators included 'ease and timing of general practitioner access'; 'the phone App as facilitator to logging'; and 'spotting for concussion as a team'. Additionally, the findings signify baseline testing as a potential pre-cursor to overall CMP compliance. Strategies that support the facilitators identified in this study may further enhance compliance.

A High Scalability Memory NoC with Shared-Inside Hierarchical-Groupings for Triplet-Based Many-Core Architecture

Innovative processor architecture designs are shifting towards Many-Core Architectures (MCAs) to meet the future demands of high-performance computing as the limits of Moore’s Law have almost been reached. Many-core processors utilize shared memory hierarchies to achieve high-speed memory systems, improving memory access efficiency. However, as the number of cores multiplies, the scalability of this system is significantly constrained by the increased proportion of long-distance and Non-Uniform Memory Access (NUMA). Improving the scalability of MCAs is crucial for achieving large/super-scale general-purpose many-core processors. This work proposes a high scalability memory Network-on-Chip (NoC) for Triplet-Based Many-Core Architecture (TriBA), named TriBA-mNoC. TriBA-mNoC maintains a consistent core-to-core spacing as the network scale increases, effectively preventing increased long-distance memory access latency. Moreover, it leverages an inherent advantage of shared-inside hierarchical-groupings, alleviating common NUMA issues in the NoC design. Evaluations of static network characteristics show that TriBA-mNoC outperforms most classical NoCs in network diameter, average distance, and cost. TriBA-mNoC can be integrated with TriBA in the same silicon die with a tile-like floorplan, forming a novel NoC called TriBA-NoC, which can combine the strengths of both networks to maximize the architecture performance. We evaluated the memory access performance and scalability of TriBA-NoC using the mathematical evaluation models and actual simulations with real traffic (PARSEC 3.0 and SPLASH-2) at different network scales. The mathematical evaluation results indicate that TriBA-NoC achieves an aggregate speedup of approximately 3x compared with 2D-Mesh for a similar number of cores. Furthermore, TriBA-NoC’s single-core speedup efficiency remains stable as the number of cores increases under the same cache hit ratio, while 2D-Mesh experiences a rapid decline, highlighting TriBA-NoC’s exceptional scalability. Finally, the actual traffic simulation results show that TriBA-NoC achieves an average memory access latency and time reduction of 25.90% − 40.50% and 5.61% − 31.69% respectively, compared with 2D-Mesh.

Improving access to domestic innovative medicines: characteristics and trends of approved drugs in China 2010-2024.

China has initiated drug regulatory reforms since 2015. Here, we analyze the characteristics and trends of domestic innovative drugs approved for marketing in China from January 2010 to May 2024 to explore the effectiveness of drug regulatory reform. Overall, 219 drugs were approved, with growth in chemicals and therapeutic biologics post-reform. Single-arm trials as an important option for clinical trial design of antineoplastic agents increased. The time for each link from investigational new drug (IND) to new drug application (NDA) has been shortened post-reform. Moreover, the time for access to medical insurance for approved drugs has been shortened and price reductions have been increased. China's drug regulatory reforms have made progress in improving the accessibility of domestic innovative drugs.

A hybrid CNN-transformer network: Accurate and efficient semantic segmentation of crops and weeds on resource-constrained embedded devices

Weed control plays a crucial role in agricultural production. The utilization of advanced vision algorithms on intelligent weeding robots enables the autonomous and efficient resolution of weed-related issues. Vision transformers are highly sensitive to plant texture and shape, but their computational cost is too high. Consequently, we propose a novel hybrid CNN-transformer network for the semantic segmentation of crops and weeds on Resource-Constrained Embedded Devices. Our network follows an encoder–decoder structure, incorporating the proposed concat extended downsampling block in the encoder, which increases inference speed by reducing memory access time and improves the accuracy of feature extraction. For global semantic extraction, we introduce the proposed Parallel input transformer semantic enhancement module, which employs a shared transformer block to increase the computation rate. Additionally, Global-Local semantic fusion block mitigates the semantic gap problem well. To fully utilize the transformer’s ability to process plant texture and shape, we employ the fusion enhancement block in the decoder, thus minimizing the loss of feature information. Segmentation results on three publicly benchmark datasets show that our network outperforms the commonly used CNN-based, transformer-based, and hybrid CNN-transformer-based methods in terms of segmentation accuracy. Moreover, our network comprises only 0.1887M parameters and 0.2145G floating-point operations. We also evaluate the inference speed on an NVIDIA Jetson Orin NX embedded system, which result for inference single image 28.28 msec, and achieving a detection speed of 35.36 FPS. The experimental results highlight that our network maintains the best inference speed and exhibits the strongest segmentation performance on resource-constrained embedded systems.

The Relationship of Emergency Contraception Knowledge of Young Individuals with Family Planning, Sexual and Reproductive Health Attitudes: A Cross-Sectional Study

Aim: To investigate the relationship between emergency contraception (EC) knowledge and attitudes towards family planning and sexual and reproductive health (SRH) among men and women aged 18-25 years living in Turkey and studying at university. Methods: The cross-sectional study was conducted between August-October 2023 with 492 participants Turkey. The data of the study were obtained through "Data Collection Form" and "Reproductive Health and Family Planning Attitude Scale (RHFPAS)". Results: In women, there was a significant difference between those who had heard of EC, knew the time of use, access, and side effects and RHFPAS. In men, there was a statistically significant difference between those who had heard of EC, time of use, access and side effects and infertility and assisted reproductive treatments. There was a weak moderate positive correlation between SRH knowledge level and RHFPAS total mean score in women and men(p

Dual-energy computed tomography: pediatric considerations.

Multidetector computed tomography (CT) has revolutionized medicine and is now a fundamental aspect of modern radiology. Hardware and software advancements have significantly improved CT accessibility, image quality, and acquisition times. While considerable attention has been directed towards the potential risks of ionizing radiation from CT scans in children, recent concerns regarding the possible short- and long-term risks related to magnetic resonance imaging (MRI) conducted under general anesthesia have generated fresh interest in novel pediatric CT applications and techniques that allow imaging of awake patients at low radiation doses. Among these novel techniques, dual-energy CT (DECT) stands out for its ability to provide enhanced diagnostic information, reduce radiation doses further, and facilitate faster scans, making it a highly promising tool in pediatric radiology. This manuscript explores the current role of DECT in pediatric imaging, emphasizing its technical foundations, hardware configurations, and various reconstruction techniques. We discuss advanced post-processing techniques, such as material decomposition algorithms and virtual monoenergetic imaging, highlighting their clinical advantages in improving diagnostic accuracy and patient outcomes. Furthermore, the paper reviews the clinical applications of DECT in evaluating pulmonary perfusion, cardiovascular assessments, and oncologic imaging in pediatric patients.

Sentiment classification for insider threat identification using metaheuristic optimized machine learning classifiers

This study examines the formidable and complex challenge of insider threats to organizational security, addressing risks such as ransomware incidents, data breaches, and extortion attempts. The research involves six experiments utilizing email, HTTP, and file content data. To combat insider threats, emerging Natural Language Processing techniques are employed in conjunction with powerful Machine Learning classifiers, specifically XGBoost and AdaBoost. The focus is on recognizing the sentiment and context of malicious actions, which are considered less prone to change compared to commonly tracked metrics like location and time of access. To enhance detection, a term frequency-inverse document frequency-based approach is introduced, providing a more robust, adaptable, and maintainable method. Moreover, the study acknowledges the significant impact of hyperparameter selection on classifier performance and employs various contemporary optimizers, including a modified version of the red fox optimization algorithm. The proposed approach undergoes testing in three simulated scenarios using a public dataset, showcasing commendable outcomes.

Safety and efficacy of brachial approach for coronary angiography and percutaneous coronary intervention

Abstract Background There are many feasible ways to reach the coronary arteries through a percutaneous technique. Till now, the most commonly used approach is the radial artery approach because it has the lowest risk of known vascular adverse events. However, it could not be an option in some situations as congenital radial artery hypoplasia and radial artery spasm. In these cases, the second most common access is the femoral artery access. The current literature over the brachial artery access is controversial. Our study's objective is to verify the brachial artery approach's effectiveness and safety. Methods We studied 300 patients who underwent elective coronary angiography and percutaneous angioplasty in our institution with failed radial access between August 2022 and February 2023. They were classified into two groups; 150 patients in a group with brachial access and 150 in a group with femoral access. Baseline clinical and demographic traits of all enrolled patients were obtained from hospital records and the cardiovascular risk factors were identified. Venous blood samples, resting 12-lead electrocardiogram and transthoracic echocardiography were done before the coronary angiography. Access, procedural and fluoroscopy times were recorded. Doppler evaluations of both brachial and femoral arteries were done the day after the procedure. All patients were examined carefully immediately after the procedure and before discharge to assess any complications. Results Our data showed that no statistically significant difference between the studied groups regarding the cardiovascular risk factors, demographic, clinical and laboratory characteristics. Left brachial access was used more frequently than left femoral access (32.7% vs. 22.7%, p= 0.05), but no significant difference regarding right sided or bilateral access. Procedure time, fluoroscopy time, and contrast volume did not differ significantly (p=0.19, 0.06 and 0.1 respectively). However, brachial group had shorter access time (2.6 ±1.1 vs. 3.4 ± 0.7 minutes, p=0.05) and shorter hospital stay (3.5 ± 1.1 vs. 5.9 ± 1.3 days, p<0.001). Regarding complications, both major and minor complications were significantly lower in the brachial arm (p=0.04 and 0.05, respectively). Conclusion Brachial artery access is a safe, efficient alternative and non-inferior to the femoral route for coronary intervention whenever radial access is not an option.

Patient characteristics and clinical outcome in acute myocardial infarction related cardiogenic shock according to vascular access site for PCI

Abstract Background / Introduction The optimal vascular access site for percutaneous coronary interventions (PCI) in patients with acute myocardial infarction (AMI) complicated by cardiogenic shock (CS) remains uncertain. While observational data favor trans-radial access (TRA) due to lower complication rates and mortality, trans-femoral (TFA) PCI offers advantages such as shorter access and procedure times, along with quicker escalation to mechanical circulatory support (MCS). Purpose In this study, we aimed to investigate factors associated with a transfemoral approach and compare mortality rates between TRA and TFA in AMI-CS patients undergoing PCI. Methods Data from a nationwide registry of AMI-CS patients undergoing PCI (2017-2021) were analyzed. We compared patient demographics, procedural details, and outcomes between TRA and TFA groups. Logistic regression identified access site factors and radial-to-femoral cross-over predictors. Propensity score matched (PSM) analysis examined the impact of access site on mortality. Results Of 1562 patients, 45% underwent TRA PCI, with an increasing trend over time. TFA patients were more often female, had a history of coronary artery bypass grafting (CABG), lower blood pressure, higher resuscitation and intubation rates, and elevated lactate levels. After PSM, 30-day mortality was lower in TRA (33% vs. 46%, p <0.001). Predictors for cross-over included left coronary artery interventions, multivessel PCI, and MCS initiation. Conclusion Significant differences exist between TRA and TFA PCI in AMI-CS. TFA was more common in patients with worse hemodynamics and was associated with higher 30-day mortality compared to TRA. TRA should be the default access, given its feasibility and favorable outcomes in many patients.Baseline characteristicsPredictors for femoral access

Ultrasound-guided versus fluoroscopy-guided axillary vein puncture for cardiac implantable electronic device implantation: a meta-analysis enrolling 1257 patients.

Ultrasound-guided (Echo-AVP) and Fluoroscopy-guided Axillary Vein Puncture (Fluoro-AVP) are both acknowledged as safe and effective techniques for transvenous implantation of leads for cardiac implantable electronic devices (CIEDs). Nonetheless, it is still debated which of the two techniques has a better safety and efficacy profile. Therefore, we performed a meta-analysis to evaluate the efficacy and safety of Echo-AVP versus Fluoro-AVP for CIEDs implantation. We systematically searched Medline, Embase and Cochrane electronic databases up to May 15th, 2024, for studies that evaluated the efficacy and safety of Echo-AVP and Fluoro-AVP reporting at least one clinical outcome of interest. The primary efficacy endpoint was acute procedural success and the primary safety endpoint was a composite endpoint of pneumothorax, pocket hematoma/bleeding, pocket infection and inadvertent arterial puncture. The effect size was estimated using a random-effect model as Odds Ratio (OR) and Mean Difference (MD) with relative 95% Confidence Interval (CI). Overall, 4 studies were included, which enrolled 1257 patients (Echo-AVP: 373 patients; Fluoro-AVP: 884 patients). Echo-AVP led to a significant reduction in the primary safety endpoint (OR: 0.41; p = 0.0009), risk of inadvertent arterial puncture (OR: 0.29; p = 0.003) and fluoroscopy time ( MD: -105.02; p = 0.008). No differences were found between Echo-AVP and Fluoro-AVP for acute procedural success (OR: 0.77; p = 0.27), pneumothorax (OR: 0.66; p = 0.60), pocket hematoma/bleeding (OR: 0.68; p = 0.30), pocket infection (OR: 0.66; p = 0.60), procedural time (MD: 1.99; p = 0.65), success rate at first attempt (OR: 1.25; p = 0.34) and venous access time (MD: -0. 25; p = 0.99). Echo-AVP proved to reduce significantly the primary safety endpoint, inadvertent arterial puncture and fluoroscopy time compared to Fluoro-AVP.

Discovering dynamics and parameters of nonlinear oscillatory and chaotic systems from partial observations

Despite rapid progress in data acquisition techniques, many complex physical, chemical, and biological systems remain only partially observable, thus posing the challenge to identify valid theoretical models and estimate their parameters from an incomplete set of experimentally accessible time series. Here, we combine sensitivity methods and ranked-choice model selection to construct an automated hidden dynamics inference framework that can discover predictive nonlinear dynamical models for both observable and latent variables from noise-corrupted incomplete data in oscillatory and chaotic systems. After validating the framework for prototypical FitzHugh-Nagumo oscillations, we demonstrate its applicability to experimental data from squid neuron activity measurements and Belousov-Zhabotinsky reactions, as well as to the Lorenz system in the chaotic regime. Published by the American Physical Society 2024

How workable is a 20-minute city in Australia? Re-examining the challenge of change in spatial labour and job relations

ABSTRACT Most x-minute city studies focus on liveability and neighborhood accessibility to local services, but rarely include primary employment. This paper complements these studies by examining the urban employment structure and transport dynamics of an Australian city under the 20-minute city concept framework. To do this, we develop a comprehensive method to model residents’ job access time using census-based journey to work (JTW) data and detailed household activity and travel survey. Analysing JTW time stepping down to diverse industry and employment categories and transport modes allows new insight into the disparity in residents’ job and housing locations and transport choices at local scales. By evaluating the distribution of working residents, types of employment, and transport performance, this paper examines possible policy responses and challenges of change in expanding the 20-minute planning target for employment. The analysis suggests that housing infill development could support reduced JTW time for residents experiencing longer time for work travels. However, this would require active planning of both land-use mix and dwelling design to meet prevalent household expectations about dwelling size and quality.

Measuring post-disaster accessibility to essential goods and services: proximity, availability, adequacy, and acceptability dimensions

Rapid restoration of access to essential goods and services has long been regarded as paramount for community recovery. Yet, there remains ambiguity in how access should be defined, measured, or operationalized. Defining accessibility as the ability to use available goods and services with a reasonable level of effort and cost requires evaluating it across six dimensions (proximity, availability, adequacy, acceptability, affordability, and awareness) while considering the perspective of both users and providers in the evaluation. But common distance-based metrics that focus solely on physical access and travel time often fall short of fully capturing these requirements, overlooking the user's perception. This paper introduces a new spatio-temporal accessibility metric that combines four out of these six dimensions, including proximity, acceptability, adequacy, and availability. The metric considers uncertainty in measuring each dimension and addresses both user and provider perspectives in measuring the acceptability and adequacy dimensions. The variation in the metric across the disaster timeline serves as a proxy for community recovery. The metric aligns with common engineering-oriented functionality-based resilience frameworks as the functionality level of the providers has been incorporated in its development. Operating at the household level, the metric determines the ratio of post-disruption access time to the intended good or service against its pre-disruption access time and yields a unitless ratio between zero and one, with zero expressing a total loss in accessibility and one signifying the same level of accessibility as pre-disruption. The proposed metric, while being scientifically principled, is a practical tool whose output is easily understood even by non-expert individuals. The metric is illustrated for schools and pharmacies using the Lumberton Testbed and data collected following the 2016 flood in Lumberton, North Carolina after Hurricane Matthew. Findings provide new insight into recovery plan prioritization and can be used to trigger protective actions. The paper concludes by discussing issues and barriers related to developing and validating accessibility metrics while highlighting areas for future research.