Station Distance Research Articles

Multiscale Spatial and Temporal Patterns of Distribution of Marine Fish Larvae—Patchiness and Predator–Prey Overlap

ABSTRACTThe distribution of fish larvae and other planktonic organisms is highly heterogenous and influenced by a complex interplay of physical, behavioural and ecological processes operating across different scales. Information on patterns and scale of resulting patchiness in plankton distributions is pivotal for understanding the bio‐physical linkages, trophodynamics and ecological strategies in the marine pelagic environment. In this study, we examine the distribution and degree of patchiness of four fish larvae species and their copepod prey, placing specific emphasis on the scale of patterns in both horizontal and vertical dimensions. Our sampling effort encompassed a 120 km long transect of stations covering a frontal area in the southern North Sea, employing depth‐stratified net sampling at varying station distances. Our results show distinct distributional patterns and migratory behaviours among different taxa of both larvae and their copepod prey, yet some commonalities were apparent. Across all species, we observed increased patchiness at larger spatial scales, significantly influenced by day/night fluctuations and hydrography. The overall findings highlight the dynamic nature of patch distributions and underscore the strong impact of hydrographic interfaces, whether vertically oriented pycnoclines or horizontally structured hydrographic fronts. These insights into bio‐physical linkages deepen our understanding of the mechanisms driving larval survival, prey availability and overall ecosystem dynamics.

Bear baiting risks and mitigations: An assessment using expert opinion analyses.

Bear baiting is authorized in 12 states, 2 territories, and 8 provinces across North America. In Alaska, more than 70% of lands managed by the National Park Service (NPS) are open to some form of hunting including National Preserves where non-conflicting state wildlife hunting regulations apply. Alaska state regulations authorize bear baiting with few restrictions on the type or amount of bait that can be used to attract bears; although, restrictions related to bait station distance from roads and trails (¼ mile) and cabins/dwellings (1 mile) apply. However, National Preserves host diverse recreational activities in addition to hunting (e.g., hiking, camping, fishing). Because road and trail access to and within Alaska National Park and Preserve lands is limited, hunting and non-hunting-related activities often occur in the same areas-increasing potential for conflict between potentially non-compatible activities. We developed questionnaires about potential impacts on NPS lands, which were distributed to 14 NPS and 27 non-NPS bear research and management experts. We collated respondents' opinions regarding consistency of bear baiting practices with state and federal mandates for wildlife management. While minor differences in expert opinions were noted, findings from this study are unequivocal. Bear baiting is functionally equivalent to feeding bears, bears may defend a bait station similar to how they would defend a carcass, and bear baiting can lead to human food-conditioning in bears. Bear baiting also increases the likelihood bears will be killed in defense of life and property, and alters natural bear behaviors and ecological processes. Further, current mitigation strategies to minimize public safety risks and potential property damage are inadequate. For example, because bears are known to defend food resources, avoiding food conditioning of bears is central to the educational messaging of all entities that manage bears. In short, bear baiting is a harvest practice that challenges harmony between State mandates, which emphasize hunter opportunity, and NPS mandates that include public safety and natural processes.

A quantitative assessment of GeoNet earthquake location quality in Aotearoa New Zealand

ABSTRACT Tens of thousands of earthquakes are located by GeoNet across Aotearoa every year. However, spatial variability – both in station coverage and earthquake distributions – produce heterogeneity in earthquake location quality throughout the GeoNet catalogue. Here we consider simple, established criteria (including station azimuthal coverage, minimum station distance, phase arrival coverage and fixed location criteria) to score earthquakes on a network location Quality Score (QS) scale of QS0 (unconstrained) to QS6 (best constrained). Significant variation in QS exists nationwide; 48% and 20% of earthquakes score QS6 for the North and South Islands respectively. The Hawkes Bay region scores highest (68% QS6) closely followed by other Hikurangi regions. However, several regions score extremely poorly, with Fiordland, West Coast, Nelson, Otago-Southland and Auckland-Northland regions having ≤5% QS6 events and >75% of events scoring QS3 or lower. Low QS mostly arises from the failure of minimum distance criteria, whereby the closest station is too far from the earthquake to provide sufficient depth control. Our analysis quantitatively assesses the impact of network heterogeneity on GeoNet earthquake catalogue location quality to inform end users. This work also provides motivation for the expansion of the weak-motion network in critically under-instrumented regions, especially those with high seismic hazard.

An improved energy saving clustering method for IWSN based on Gaussian mutation adaptive artificial fish swarm algorithm

The current industrial wireless sensor network (IWSN) cluster routing methods suffer from energy inefficiency. Designing efficient cluster-based routing protocols is crucial for improving network performance and energy efficiency. Therefore, this paper first designs a new clustering model to achieve efficient cluster head (CH) selection and data transmission performance by comprehensively considering multiple key factors such as CH energy, base station (BS) distance, packet loss rate, and data delay. Based on this clustering model, a novel cluster routing protocol based on Gaussian mutation adaptive artificial fish swarm algorithm (GAAFSA) is proposed. At the same time, a new Gaussian mutation strategy and an adaptive strategy were introduced to effectively promote the protocol to avoid local optima and prevent premature convergence. The GAAFSA based cluster routing protocol was experimentally compared with five popular schemes, namely CMSTR, D2CRP, EEHCHR, ESCVAD and BAFSA. The results showed that the proposed protocol outperformed the other four schemes in terms of network energy consumption, system lifetime, data transmission reliability, and latency. Specifically, GAAFSA has improved network lifespan by at least 15.68%, BS received packets by at least 7.46%, and reduced packet loss rate by at least 15.28%. Therefore, GAAFSA effectively optimizes network performance and extends network lifespan, greatly reducing energy loss within the network and significantly improving network quality of service (QoS).

Empirical Evaluation and Simulation of the Impact of Global Navigation Satellite System Solutions on Uncrewed Aircraft System–Structure from Motion for Shoreline Mapping and Charting

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

Capturing the Value of Walkability

Capturing the value infrastructure investments add to the residential market is a longstanding policy to defray their expense. Unfortunately, estimates of the added value of infrastructure, generally, and estimates of the added value of walkability, specifically, are scarce. Novel, multiscale models free independent variables to manifest simultaneously at different scales of analysis to greatly improve specifications to precisely estimate walkability valuation. Results from analysis of years of transactions within walking distance of heavy rail stations suggest that walkability adds value available for capture locally, not systemically. Stakeholders confront myriad problems to replicate the accessibility characteristics shown to add value given the distinct cluster where walkability adds value available for capture in a heavy rail system.

Investigating Subsurface Properties of the Shallow Lunar Crust Using Seismic Interferometry on Synthetic and Recorded Data

AbstractIn the past few years, the remarkable progress of commercially operated spacecrafts, the success with reusable rocket engines, as well as the international competition to explore space, has led to a substantial acceleration of activities in the design and preparation of ambitious future lunar missions. In the search for ice and/or cavities imaging the shallow subsurface structure is of vital importance. Hereby, previous studies have shown that seismic interferometry is a promising method to investigate the subsurface properties from passive lunar data. In this study, we want to evaluate the potential of this method further by examining the required duration of seismic measurements and the influence of scattering on the Green's function retrieval. Therefore, we applied seismic interferometry to both measured Apollo 17 data and synthetic data. Our findings indicate that, under optimal conditions, a few hours of data are sufficient when using the method of time‐scaled phase‐weighted stack (ts‐PWS). However, this strongly depends on the inter‐station distance, the orientation toward the principal noise sources, and the timing of the measurement during the lunar cycle. Additionally, we were able to reproduce the measured data using numerical simulations in 2D. The synthetic results show that scattering effects clearly influence the Green's function extraction, especially for larger station distances.

Energy efficient cluster-based routing protocol for WSN using multi-strategy fusion snake optimizer and minimum spanning tree

In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the internet of things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the multi-strategy fusion snake optimizer (MSSO) and employs the minimum spanning tree algorithm for inter-cluster routing planning, thereby extending the system’s lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space. Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy c-means (FCM) algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%.

Optimal spatial distribution of seismic stations to detect magma migration using the seismic amplitude ratio analysis

Magma migrations frequently trigger seismic swarms, resulting in seismic events that overlap in time and hinder real-time phase picking commonly used for hypocenter location. Addressing this challenge, seismic amplitude ratio analysis (SARA) allows identification of seismic migrations in real-time by simply tracking the relative seismic amplitude between a pair of seismic stations.This paper aims to identify key statistical features of the seismic network array locations that improve their ability to detect seismic migrations using SARA. We evaluated the capability to detect the most frequently oriented magma migrations in over 100 volcanoes, using a criterion previously proposed to study vertical magma migrations in Piton de la Fournaise. Additionally, we investigate the influence of vent-station proximity on magma conduit coverage and identify the distance ratio that yields improved detection.Furthermore, we estimate the seismic network efficiency by calculating the detection capability volume per station. We then use the random forest regression algorithm to identify which statistical features of the seismic network location contribute more to the efficiency disparity among different volcanoes. Notably, our findings reveal that optimizing seismic network coverage entails maximizing the standard deviation of relative pair station distances, while maintaining a prescribed minimum separation distance between station pairs. Our results reveal important criteria that can be used to optimize seismic network location design.

Exploring Factors Influencing Family's Enrollment in Community-Based Health Insurance in the City of Gondar Peri-Urban Community, Northwest Ethiopia: A Health Belief Model Approach.

A research gap exists in finding practical solutions to provide affordable and accessible health insurance coverage to improve CBHI enrollment and sustainability to people in resource-poor settings and contribute to achieving universal health coverage (UHC) in Ethiopia. This research was initiated to analyze the role of community trust in scheme management and health choice to identify significant factors based on the health belief model (HBM). This psychological framework explains and predicts health behavior by considering individual perceptions. Cross-sectional information was gathered from 358 families, and original facts were utilized. Descriptive data and the Binary logistics in the econometric model were applied for data analysis. The descriptive findings demonstrated that other variables were established to possess a significant consequence except for job and occupation variables. The results of the logistic regression model showed that the distance of the nearest health station from the family's home in a minute [AOR (95% CI) =0.177 (0.015, -0.399)], being a member of the families having an official position in local government or cultural structure [AOR (95% CI) =0.574 (0.355, 0.793)], having an experience of visiting health facilities [AOR (95% CI) =0.281 (0.166, 0.396)], and perceiving the local CBHI scheme management as trustworthy [AOR (95% CI) =0.404 (0.233, 0.575)] were positively associated with family enrollment in the CBHI scheme. On the other hand, being a member of the "rotating saving and credit association" (ROSCA) [AOR (95% CI) =-.299 (-.478, -0.120)] was negatively associated with the family's enrollment in the CBHI scheme. Trust in CBHI scheme management, family's experience of visiting health facilities, and distance from the nearest health station were essential factors influencing enrollment in CBHI schemes. "Rotating saving and credit association" (ROSCA) ° negatively and statistically significantly impacted the family's CBHI enrolment status. Income level was not associated with enrollment.

A risk‐based evaluation of safe distance for a hydrogen refueling station

AbstractTo ensure the safety of hydrogen refueling stations (HRSs) and protective targets in the surrounding area, this paper has introduced a risk‐based safe distance assessment method for a 35MP HRSs, emphasizing the impact of the station's surrounding area. The findings indicate that the safe distance is determined by vapor cloud explosion (VCE) accident scenarios arising from pipeline leaks (compressor‐hydrogen storage tanks) at 125 m. Therefore, a crucial focus should be placed on safeguarding and maintaining hydrogen pipelines. Furthermore, based on societal risk, the requirement of a 358‐m safe distance specifies that the population gathering within this range should be <500 people, virtually eliminating the possibility of constructing hydrogen stations in urban residential areas. Only in scenarios where VCE risks are not considered, less‐populated surrounding environments might reduce the safe distance of hydrogen stations. Eliminating the risk scenarios of VCE is a crucial approach to lowering the safe distance of HRSs, making establishing such stations in urban centers feasible. Therefore, factors such as open spaces, well‐ventilated facilities, and blast walls become critical elements in reducing the safe distance of HRSs.

Application of ERT, IP and VLF-EM Methods to Investigate Landslide-Prone Structures at Archaeological Sites in Lamreh, Aceh Besar, Indonesia

Since the 21st century, Lamreh, Aceh Besar Regency, Indonesia played an important role during the maritime silk route at the gate of the Malacca strait. This article investigates the subsurface structure of landslide-prone areas in cultural heritage based on 2D resistivity, chargeability and current density models of ERT, IP and VLF-EM methods, respectively. Field data measurements were carried out on 2 crossing profiles along the cliff suspected of experiencing landslides. The length of each profile is 220 with 4 m distance between stations. The 2D models reveal that the subsurface geological structure of Lamreh is composed of a mixed layer of clastic sediment and volcanic material at the top, followed by a layer of calcareous sandstone, and volcanic breccia at the bottom. The 3 layers are most easily distinguished in the resistivity model. The topmost layer is permeable but dry, i.e., characterized by a more resistive layer in the models. While the second layer is characterized by an intermediate conductivity and the bottom layer is highly conductive. The conductivity in these 2 layers is influenced by the degree of water content within the rocks. The chargeability models derived from IP data can distinguish between the dry layer on the surface and the saturated layer below. Meanwhile, the current density models obtained from VLF-EM data have proven the presence of fractures and faults along the profiles due to weathering as also seen in the resistivity models. HIGHLIGHTS Investigation of subsurface structure in landslide-prone area of Lamreh, Aceh Besar Regency, Indonesia, a cultural heritage site with historical significance in the maritime silk route. Utilization of 2D resistivity, chargeability and current density models (ERT, IP and VLF-EM) to analyze the subsurface structure. Field data measurements conducted on 2 crossing profiles along the suspected landslide cliff, with a profile length of 220 and 4 m station distance. Subsurface geological structure of Lamreh identified as a mixed layer of clastic sediment and volcanic material at the top, followed by calcareous sandstone and volcanic breccia at the bottom. Resistivity models most effectively distinguish the 3 layers, highlighting permeable but dry top layer, intermediate conductivity in the second layer, and high conductivity in the bottom layer influenced by water content. Chargeability and current density models confirm surface dryness and presence of fractures and faults due to weathering GRAPHICAL ABSTRACT

Electric Vehicle Battery State of Charge and Charging Station Distance Estimation Using IoT

Background: The global transition to green energy and the rapid development of Electric Vehicle (EV) technology, along with falling component costs, have fueled the growing popularity of electric vehicles. To support the widespread adoption of EVs, an efficient and userfriendly charging infrastructure is crucial. Objective: This work aims to propose a comprehensive EV charging system that addresses the rising demand for charging stations, streamlines the charging process, and empowers EV drivers with essential information. The primary focus is on an economical and effective booking system, enabling users to locate nearby charging stations and make informed choices about their charging preferences. Method: We suggest developing a EVs Charging Finder App, serving as a central platform for EV users to find nearby charging stations. The app will provide vital details, including ratings, reviews, available time slots, charging duration estimates, and more. Users can also contribute new charging station data, fostering app growth. Additionally, an alert system will notify users when nearby charging slots become available, enhancing convenience for EV drivers. Results: The EVs Charging Finder App is anticipated to significantly enhance the accessibility and convenience of EV charging. Users can effortlessly locate charging stations, assess quality through reviews and ratings, and plan charging sessions based on real-time availability. The battery voltage of 45.2 V is a critical parameter for monitoring the health and performance of the battery, influencing the accuracy of state of charge (SoC) estimations and potentially impacting the efficiency of the electric vehicle. The 47.7 km driven is a key factor in assessing energy consumption and vehicle efficiency, which can affect the remaining state of charge in the battery. The battery's state of charge (SOC) is at 85%, indicating a relatively high charge level. Knowing that the charging station is available is crucial for planning charging activities, allowing users to proceed without concerns about station availability. The booking time at 10:00 AM is essential for efficiently managing charging infrastructure, especially in scenarios with high demand for charging services. These data points collectively contribute to optimizing the charging experience and ensuring the effective utilization of electric vehicle resources. Conclusion: The proposed EVs Charging Finder App offers a practical and efficient solution to address the surging demand for charging stations. By providing comprehensive information and real-time alerts, this system aims to make EV charging more accessible, user-friendly, and environmentally sustainable.

Study on the Deployment of Ultra-Wideband Positioning Base Stations in Pig Farms

A novel indoor positioning method for a pigsty based on ultra-wideband (UWB) technology is proposed via reasonably arranging the base stations and positioning tags, which can provide strong support for the accurate positioning of specific pig pens in the pig house. The distribution of Dilution of Precision (DOP) values is analyzed in different deployment schemes which include the amount, the height, the deployment shape, and the distance of the base stations through positioning simulation. Moreover, the positioning effect of dynamic following positioning, the root-mean-square error (RMSE), and the variance of static positioning are measured. It is noteworthy that the Kalman filtering algorithm is adopted to smooth the dynamic following positioning experimental data for reducing the positioning error. The simulated results show that the DOP values decrease with the increase in height and distance, and these results and laws are consistent with the experimental results. However, the DOP values are best reached when the height is from 1.75 m to 2.75 m, and the distance is over 3.00 m. Furthermore, the DOP values of quadrilateral deployment are smaller than the ones of triangular deployment. In addition, the variance of static positioning and dynamic following positioning is decreased by utilizing the Kalman filtering algorithm. Therefore, the excellent positioning system and its solutions in a pigsty can be provided by our proposed indoor positioning method.

COMPARISON OF EARTHQUAKE HYPOCENTER RELOCATION METHODS IN THE JAVA REGION, INDONESIA

Java is a frequent island of earthquakes caused by the subduction of the Indo-Australian plate under the Eurasian plate. The mitigation of earthquake disasters is by relocating the hypocenter. Hypocenter relocation was conducted in order to obtain a more accurate earthquake position, which can be used to interpret the structure under the earth's surface. The Modified Joint Hypocenter Determination (MJHD) and Double Difference (DD) methods are required when applying earthquake hypocenter relocation. The objective of research is comparing the relocation results in the Java region with the Modified Joint Hypocenter Determination (MJHD) and Double Difference (DD) Methods for obtaining the distribution of earthquake hypocenters before and after relocation. The study has obtained arrival time data in the form of BMKG catalog data from the period of January 1, 2022 through May 30, 2022 in the Java area with the coordinates of 6.0 LS - 12.0 LS and 106.0 BT - 114.0 BT. The MJHD method compares the travel time difference of a set of data that occurs simultaneously in order to obtain a more accurate hypocenter position, while the DD method compares the hypocenter distance of the two earthquakes with the station distance, so that Ray Path and Waveform are considered equal. The relocation of the initial earthquake has a depth of 10 km, resulting in a shift of shallow earthquakes clustered in the active fault section, while deep earthquakes are clustered in the subduction zone section. The results of relocation with the MJHD method obtained 637 earthquakes.

Mitigating Hotspot Problem Using Chaotic Salp Swarm Algorithm for Energy Efficient IoT Assisted Wireless Sensor Networks

Wireless Sensor Networks (WSN) and Internet of Things (IoT) continued to be pro-active study due to their far reaching applications and also a crucial technology for ubiquitous living. In WSN, energy awareness becomes a significant design problem. Clustering can be defined as a renowned energy-efficient method and renders a lot of benefits like energy competence, less delay, scalability, and lifetime; but it resulted in hot spot problems. To sort out this problem a method called unequal clustering is designed. In unequal clustering, the cluster size differs with the Base Station (BS) distance. In this study, a new Chaotic Salp Swarm Algorithm Based Unequal Clustering Approach (CSSA-UCA) methodology to resolve hot spot issues in IoT-assisted WSN is proposed. The major objective of the CSSA-UCA methodology lies in the effectual identification of CHs and unequal cluster sizes. To accomplish this, the CSSA-UCA technique initially derives the CSSA by the incorporation of chaotic notions into the conventional SSA. At the same time, a fitness function incorporating multiple input parameters was considered for unequal cluster construction. A wide range of experimental result analyses is performed to exhibit the supremacy of the CSSA-UCA technique. The experimental results stated that the CSSA-UCA technique proficiently balances energy accretion and improves the network lifetime.

An Average Speed of Sound Method for Underwater Positioning Based on Time of Arrival

This article uses the distance and sound spread time of each monitoring base station in the underwater positioning system, calculates the effective sound speed of the sound wave to the base station, and proposes a TOA underwater positioning method based on the average speed. The influence of small underwater sound changes the system positioning accuracy, reducing system positioning errors. Simulation experiments show that compared with the traditional fixed sound velocity method, this method has higher positioning accuracy and lower error. The positioning effect in a long baseline underwater positioning system is less dependent on the number of monitoring base stations. The cumulative probability of positioning error within 5 m can reach 70%, and the cumulative probability of error within 10 m can reach over 95%.

The node-place model, accessibility, and station level transit ridership

This paper uses Sydney rail data to examine the relationship between station level ridership and local and regional accessibility. We use net transit accessibility, which is the additional number of opportunities reachable by transit over walking to represent the regional connectivity value provided by transit. We map accessibility at transit stations, and use the number of opportunities within walking distance as an indicator of local access. We find elements of place (or local) access, including access to jobs and to residents within walking distance (local access), and nodal (or regional) access, including transit access to distant jobs and residential locations are both significant indicators of station level ridership. In particular, the number of jobs within walking distance of a transit station is the best single predictor of transit ridership. This paper highlights the importance of high density around station areas for transit ridership.

Quantitative Risk Assessment of Hydrogen Gas Explosion Accidents at Complex Hydrogen Refueling Station

The global automobile market is shifting from vehicles powered by LNG, LPG, diesel, and gasoline toward electric and hydrogen-driven vehicles. To boost the development of a hydrogen economy, the Korean government has been supporting the supply of hydrogen vehicles and permitting the installation of hydrogen refueling stations alongside the existing LNG, LPG, diesel, and gasoline refueling stations. This study entailed an evaluation of the risk of hydrogen gas explosion accidents at a combined hydrogen fueling station that supplies hydrogen, gasoline, and diesel. Numerical analysis was used to examine the extent of damage to the interior and exterior of the hydrogen station caused by the blast wave generated by the vapor cloud explosion resulting from a hydrogen gas leakage inside the station. The results indicate that the severity of the damage to nearby structures and facilities due to the vapor cloud explosion increased with increasing hydrogen gas leakage. The results have applicability in planning the safety separation distance of hydrogen stations and placement of hydrogen facilities.

Spatial heterogeneity in the effects of built environments on walking distance for the elderly living in a mountainous city

Improving the walking distance of elderly people is important for improving their physical and mental health. Most studies to date have considered the global influence of the built environment on the walking distance of the elderly. In contrast, the uneven spatial distribution of slopes in mountainous cities, given the changing terrain, may lead to changes in the walking distance for the elderly. Therefore, in this study, we adopted data from a walking behavior survey of elderly people in Guiyang City, and analyzed the spatial heterogeneity of the influence of the objective built environment on walking distance for older adults using mixed geographically weighted regression models. The results showed that the built environment had significant local spatial differences on the walking distance of the elderly. Slope was significantly and negatively related to walking distance for the elderly; the population density, density of leisure and entertainment venues, and nearest bus station distance had a significant positive influence on walking distance; land use mix and road network density had local positive and negative effects on walking distance in space, respectively. The results of the study have important implications for mountainous city planning and the construction of an age-friendly environment.