Geographic Placement Research Articles

Commercial and industrial centers of the Samara region in the second half of the XIX – early XX century

The article considers the formation process of the commercial and industrial centers of the Samara region in the post-reform era. Despite there are scientific works that cover the topic of the formation and development of commercial and industrial entrepreneurship in the Samara province, the issue presented in the article can be considered as one of the unstudied. The scientific literature is not yet clearly defined the main factors that influenced this process. These factors include natural and climatic conditions, pace of establishment and development of agricultural production and other branches of farming industry, modernization of transport and financial infrastructure. The source base of the article is presented by administrative documentation, guidance and statistical materials, sources of personal nature, and fiction. The most significant sources include the documentary publications that contain a large amount of historical information, for example, «Lists of populated areas» for 1859, 1889, 1900, 1910. They contain valuable information about the geographical location of trade and industry facilities. On the basis of these and other materials, comparative-historical, analytical, methods of periodization and systematization, conclusions were formulated about the stages of the formation and development of shopping and industrial centers, their geographical placement, as well as that the modernization of transport and financial infrastructure gave a powerful impetus to the development of trading -Industrial activities of both the provincial capital and county centers, as well as a number of settlements, which at the end of the XIX-early XX centuries were shopping and industrial centers.

Refined 70-cm earth-based lunar radar maps and a new interpretation of the Cruger-Sirsalis cryptomare

We present a new processing approach for Earth-based, 70-cm wavelength, dual-polarization radar data collected using the Arecibo and Green Bank Telescopes. Earth-based data represent the only view of the Moon at this wavelength. This methodology greatly improves the synthetic aperture focusing of the images to their best possible spatial resolution, with a concurrent improvement in signal-to-noise ratio and multi-look summing. Image coverage is also expanded to the full illuminated beam area. Registration to a visible image basemap reduces RMS geographic placement errors to less than ∼2 km. Images collected after the first Planetary Data System archive delivery are also included. Analysis of the circular polarization ratio (CPR) suggests an uncertainty of ∼20 %, based on the likely ∼1 dB error in estimating the background noise in a radar look. We use the new 70-cm maps with topography and 12.6-cm radar images to revisit an initial study of cryptomare units in the Cruger-Sirsalis region, and find that mare contamination of the Orientale ejecta must be well-mixed with highland material, as opposed to the earlier hypothesis of a highland-dominated blanket over mare-rich regolith. This result shows that the two radar wavelengths provide a more complete view of the cryptomare regolith cross section, and that radar signatures can delineate ilmenite contamination of highlands areas where multi-spectral methods are limited by other factors.

The Impact of the COVID-19 Pandemic on Geographic Placement of Applicants to General Surgery Residency Programs

COVID-19 greatly influenced medical education and the residency match. As new guidelines were established to promote safety, travel was restricted, visiting rotations discontinued, and residency interviews turned virtual. The purpose of this study is to assess the geographic trends in distribution of successfully matched General Surgery applicants prior to and after the implementation of pandemic guidelines, and what we can learn from them as we move forward. This was a retrospective review of 129 Accreditation Council for Graduate Medical Education (ACGME) accredited, academic General Surgery Residency Programs across 46 states and the District of Columbia. Categorically matched residents' medical schools (i.e., home institutions), medical school states, and medical school regions as defined per the Association of American Medical Colleges (AAMC), were compared to the same geographic datapoints as their residency program. Preliminary residents were excluded. Residents in the 2018, 2019, and 2020 cycles were sub-categorized into the "pre-COVID" group and residents in the 2021 and 2022 applications cycles were sub-categorized into the "post-COVID" group. The percentages of residents who matched at their home institution, in-state, and in-region were examined. Multiple ACGME-accredited, university-affiliated General Surgery Residency Programs across the United States of America. A total of 4033 categorical General Surgery residents were included. Of 4033 categorical residents who matched between 2018 and 2022, 56.1% (n = 2,263) were in the pre-COVID group and 43.9% (n = 1770) were in the post-COVID group. In the pre-COVID group 14.4% (n = 325) of residents remained in-home (IH), 24.4% (n = 553) in-state (IS), and 37.0% (n = 837) in- region (IR), compared to 18.8% IH (n = 333), 27.8% IS (n = 492), and 39.9% IR (n = 706) in the post-COVID group, respectively. Significant increases for IH and IS resident matching at 4.5% and 3.4%, respectively, were noted in the post-COVID period (p < 0.05). The COVID-19 pandemic, and the ensuing changes adopted to promote safety, significantly impacted medical student opportunities and the General Surgery residency application process. General Surgery match data over the last 5 years reveals a statistically significant increase in the percentage of applicants matching at in-home and in-state institutions after the pandemic.

Assessing the risks associated with indoor and outdoor air quality in relation to the geographic placement of nursing home

Indoor air quality significantly impacts the well-being and health of elderly residents in nursing homes. This study was conducted to explore the connection between indoor and outdoor PM (Particulate Matter) concentrations in nursing homes and their association with the facilities' location and construction characteristics. The findings revealed that indoor PM2.5 and PM10 concentrations ranged from 0.2 to 124 μg/m3 and 2–188.4 μg/m3, respectively, which were approximately 12.67 and 1.25 times higher than their outdoor counterparts. A strong correlation (P < 0.05) was identified between indoor PM levels and various factors, including proximity to parks, passenger terminals, and gas stations, as well as building attributes such as single-glazed windows, ceramic floor coverings, and the use of radiators. The risk assessment indicated that carcinogenic risk factors were well within acceptable limits for all nursing homes. However, it's important to note that certain PM components, particularly polycyclic aromatic hydrocarbons (PAH), may have long-term adverse effects on the health of nursing home residents. Even though indoor PM levels met the standards established by the U.S. Environmental Protection Agency (USEPA) for particulate matter risk assessments, the study emphasized that even low levels of indoor air pollutants can affect the health and well-being of older adults, particularly considering the increased vulnerability associated with aging. Consequently, the study underscores the importance of nursing home location selection and the regular monitoring of particulate matter concentrations. These measures are essential for enhancing air quality within nursing homes, ultimately contributing to the improved well-being and health of their residents.

Geographic clustering of cannabis stores in Canadian cities: A spatial analysis of the legal cannabis market 4 years post-legalisation.

Following the legalisation of non-medical cannabis in 2018, the number of cannabis stores in Canada has rapidly expanded with limited regulation on their geographic placement. This study characterised the clustering of cannabis stores in Canadian cities and evaluated the association of clustering with provincial policy and sociodemographic variables. Cross-sectional spatial analysis of cannabis store density in dissemination areas ('neighbourhoods', n = 39,226) in Canadian cities in September 2022. Cannabis store density was defined as the count of stores within 1000 m of a neighbourhood centre. Clusters of high-density cannabis retail were identified using Local Indicators of Spatial Autocorrelation. Associations between provincial policy (privatised vs. public market), sociodemographic variables and cannabis store density were evaluated using multivariable regression. Clusters of high-density cannabis retail were identified in 86% of Canadian cities, and neighbourhoods in clusters had a median of 5 stores within 1000 m. Toronto, Canada's most populous city, had the most extreme clustering where neighbourhoods in clusters had a median of 10 stores (and a maximum of 25 stores) within 1000 m. Neighbourhoods in private versus public retail markets had a significantly higher neighbourhood-level density of cannabis stores (adjusted rate ratio [aRR] 63.37, 95% confidence interval [CI] 25.66-156.33). Lower neighbourhood income quintile was also associated with a higher neighbourhood-level density of cannabis stores (Q5 vs. Q1, aRR 1.28, 95% CI 1.17-1.40). Since cannabis was legalised, clusters of high-density cannabis retail have emerged in most Canadian cities and were more likely to form lower income neighbourhoods and in private retail markets.

An MPI-based parallel genetic algorithm for multiple geographical feature label placement based on the hybrid of fixed-sliding models

ABSTRACT Multiple Geographical Feature Label Placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. Moreover, the nature of label positioning has proven to be an Nondeterministic polynomial-time hard (NP-hard) problem. Although advances in computer technology and robust approaches have addressed the problem of label positioning, the lengthy running time of MGFLP has not been a major focus of recent studies. Based on a hybrid of the fixed-position and sliding models, a Message Passing Interface (MPI) parallel genetic algorithm is proposed in the present study for MGFLP to label mixed types of geographical features. To evaluate the quality of label placement, a quality function is defined based on four quality metrics: label-feature conflict; label-label conflict; label association with the corresponding feature; label position priority for all three types of features. The experimental results show that the proposed algorithm outperforms the DDEGA, DDEGA-NM, and Parallel-MS in both label placement quality and computation time efficiency. Across three datasets, compared to Parallel-MS, running times decreased from 118.45 to 8.34, 45.98 to 3.51, and 20.01 to 0.43 min, with further reductions in label-label and label-feature conflicts.

Magneettikouluja vai eliittikouluja?

The connection between urban and school segregation has been identified as a major question in Finnish educational policy. Families’ school choices in basic education are strongly connected to socio-spatial segregation, families’ socio-economic status, and the provision of selective tracks and streams in schools. As a result, the provision of selective schools and selective classes is a major factor shaping the landscape of urban school segregation. We have analyzed whether the geographical placement of selective education in the City of Helsinki can be identified to either ameliorate school segregation through a “magnet school” effect or exacerbate segregation through “elite school” placement. Our results demonstrate that the provision of selective schools and classes in public schools is in general geographically very equally distributed, and as such does not construct a magnet school effect. However, as the placement of private schools has a distinct “elite” pattern, the educational landscape of the city leans towards a slight “elite effect”.

GIS-based land suitability analysis for the optimal location of integrated multi-trophic aquaponic systems

Aquaponics has witnessed global proliferation and a notable enhancement in sustainability in recent years. Consequently, it assumes paramount importance to delineate optimal locations for its implementation, in fact, the success of an aquaponic facility also depends on its geographical placement, necessitating consideration of many variables encompassing natural resources, socioeconomic factors, infrastructural availability and environmental constraints, whether natural or artificial. This paper focuses on the definition and test in the Emilia-Romagna region (Italy) of a GIS-based multi-criteria land suitability assessment model aimed at allowing the diffusion and environmental integration of innovative integrated multi-trophic aquaponic systems. The process has been implemented with a Weighted Linear Combination (WLC) model, where decisions and criteria were selected via a participatory mechanism involving experts in various fields. The region has been subdivided into 50 × 50 m grid cells, with each grid cell being associated with a value ranging from 0 to 8. In this context, a rating of 0 means unsuitability, while a rating of 1 denotes minimal suitability, and the highest rating of 8 designates maximal suitability. Notably, a substantial portion of the surveyed territory has been found to be completely unsuitable for the establishment of aquaponic facilities. More than 86.4% of the remaining suitable areas were rated 6, 7, or 8, affirming the overall favourability of the Emilia-Romagna region for aquaponic installations. Finally, the veracity and robustness of the results have been tested through a one-at-a-time sensitivity analysis, that has proven the appropriateness of the proposed model.

A Novel Approach to Solve K-Center Problems with Geographical Placement

A Novel Approach to Solve K-Center Problems with Geographical Placement

Optimizing a Drone Network to Respond to Opioid Overdoses.

Introduction:Effective out-of-hospital administration of naloxone in opioid overdoses is dependent on timely arrival of naloxone. Delays in emergency medical services (EMS) response time could potentially be overcome with drones to deliver naloxone efficiently to the scene for bystander use. Our objective was to evaluate a mathematical optimization simulation for geographical placement of drone bases in reducing response time to opioid overdose. Methods: Using retrospective data from a single EMS system from January 2016-February 2019, we created a geospatial drone-network model based on current technological specifications and potential base locations. Genetic optimization was then used to maximize county coverage by drones and the number of overdoses covered per drone base. From this model, we identified base locations that minimize response time and the number of drone bases required. Results: In a drone network model with 2,327 opioid overdoses, as the number of modeled drone bases increased the calculated response time decreased. In a geospatially optimized drone network with four drone bases, response time compared to ambulance arrival was reduced by 4 minutes 38 seconds and covered 64.2% of the county. Conclusion: In our analysis we found that in a mathematical model for geospatial optimization, implementing four drone bases could reduce response time of 9-1-1 calls for opioid overdoses. Therefore, drones could theoretically improve time to naloxone delivery.

Deterring the Influence of Organized Crime in Sistan and Baluchistan Province on the National Security of Islamic Republic of Iran

Domestic challenges have continuously gone alongside the international interventions in Iran. Out of the domestic security challenges of the country, organized crime and physical security instability and proposing possible propositions to address these challenges have been of vital significance. The diverse population, geographic placement, varied believes, potential marginalization, governance centralism, isolated borders and lack of cross-border control are considered significant factors of the subject. This organized crime has a direct and indirect influence on the national security of the country. This research studies the political facts and factors that can deter the influence of organized crime on the national security of the country and propose feasible and attainable recommendations to deter this influence.

ANALYSIS OF HUNTERS' RETURN IN THREE MAJOR BUSHMEAT DEPOTS, IN SOUTH-WEST NIGERIA

Submissions of game harvested by hunters per expedition to bushmeat landing depots in Southwestern Nigeria were studied for one year. Three established bushmeat landing depots were purposively selected for the study. Olomore and Kila in Ogun State and Odo Ona in Oyo State. The three were so selected because of their distribution along almost the same line of geographical placement on a line with Kila falling in between the other two on a line. Hunters’ return of harvested game after overnight hunting to the three locations on weekly basis was identified and counted for a year. Twenty-one (21) species of Vertebrates in the class Mammalia, reptiles and birds were returned to the three bushmeat depots by hunters during the study. Location-wise, Olomore had the highest return (1,457) and the least was returned to Kila (987) both in Ogun State. Species-wise, Thryonomys swinderianus (Grasscutter) had the highest population of 2,383 animals with a mean value of 794.3 ± 180.58, followed by Cephalophus maxwelli (duiker) with a mean value of 184.0 ± 32.51. The least hunters’ returns were Bitis gabonica (Black cobra) and Perodicticus potto (Bosmans potto) with a mean value of 0.33 ± 0.58 and 0.67 ± 1.15 respectively.

Day and Night: Locating the General Practitioner’s Panel after Hours

Location science is used to determine the optimal geographical placement of primary care resources with operations research models. In determining the optimal placement, we account for the objectives of both patients and physicians. These objectives and the methods used to address them differ between daytime and after-hours settings. These time settings are treated separately since primary care services are typically limited during after-hours operations. Three solution approaches are considered to address both time settings: independent, sequential, and simultaneous. The independent approach is based on the p-Median problem, and the other two approaches use modified forms of the p-Median. Three case studies are examined by applying these models to census data from Nova Scotia. Solving the daytime and after-hours problem simultaneously consistently yields the best results while considering facility-sharing constraints.

A Comparative Model Analysis of Predictors of Community Pharmacists’ Collaborative Practices in Two Southwestern States in Nigeria

Background: In community pharmacy practice, pharmacists are expected to engage in collaborative activities to deliver quality service to clients. However, due to the hybrid nature (social and commercial dimensions) of the practice, certain subjective behavioral norms-competitive and information-sharing behavior may have potential influence on the collaborative behaviors of community pharmacists&#x0D; Objectives: Based on the theory of planned behavior framework, the study tests the influence of subjective norms-competitive behavior and information-sharing practices on the collaborative behavior of community pharmacists; and, investigated possible differences in the perception of respondents in two southwestern states in Nigeria&#x0D; Methods: A cross-sectional quantitative study with randomly administered questionnaires to 421 community pharmacists from two purposively selected states- Lagos (230) and Ogun (191) in southwest Nigeria. A structural equation model was developed using Analysis of Moment Structures software (AMOS). Group differences were evaluated using the chi-square difference test.&#x0D; Results: Competitive behavior and information-sharing behavior are substantial predictors of collaborative behaviors among community pharmacists (R2=0.97, p&lt;0.001). Multigroup analysis revealed differences in perception between respondents in the densely populated and less densely populated settings. Model comparisons revealed insignificant group differences.&#x0D; Conclusion: The study confirmed that information-sharing and competitive behavior have a positive and significant influence on collaborative behavior. The findings of the study imply that no link exists between the geographical placement of community pharmacists and differences in their practice behavior. Professional associations and regulatory bodies should provide training and engage in participatory workshops to strengthen the right collaborative attitudes among community pharmacists. The study provides a theoretical framework for further studies in inter- and intra-professional relations among healthcare professionals.

Impact of Virtual Interviewing on Geographic Placement for Cardiology Fellowship Recruitment

Background Virtual interviewing for cardiology fellowship was instituted in the 2021 fellowship application cycle because of the COVID-19 pandemic and restricted travel. The impact on geographic patterns of fellow-training program matching is unknown. This study sought to determine if there was a difference in geographic placement of matched fellows for cardiology fellowship match after initiation of virtual interviews compared with in-person interviewing. Methods and Results All US-based accredited cardiovascular disease fellowship programs that participated in the 2019 to 2021 fellowship match cycles and had publicly available data with fellowship and residency training locations and training year were included. Each fellow was categorized based on whether their fellowship and residency programs were in the same institution, same state, same US census region, or different census region. Categories were mutually exclusive. Of 236 eligible programs, 118 (50%) programs were identified, composed of 1787 matched fellows. Compared with the previrtual cohort (n=1178 matched fellows), there was no difference in the geographic placement during the 2021 virtual cycle (n=609 matched fellows) (P=0.19), including the proportion matched at the same program (30.6% versus 31.5%), same state but different program (13% versus 13.8%), same region but different state (24.2% versus 19.7%), or different region (35% versus 33.1%). There was also no difference when stratified by program size or geographic region. Conclusions The use of virtual interviewing in the 2021 cardiology fellowship application cycle showed no significant difference in the geographic placement of matched fellows compared with in-person interviewing. Further study is needed to evaluate the impact of virtual interviewing and optimize its use in fellowship recruitment.

Evaluation of potential sites in Iran to localize solar farms using a GIS-based Fermatean Fuzzy TOPSIS

Iran's energy consumption is constantly and rapidly increasing. Due to the country's geographical placement on the Sun Belt of the Earth, there is a great potential for photovoltaic (PV) energy to be used; however, it necessitates an evidence-based selection of appropriate locations to develop solar farms. In this paper, we used a new approach to prioritize potential PV plant sites employing geographical information system (GIS)-based Fermatean Fuzzy (FF) TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). We considered economic, geographic, climatic, infrastructures, and demographic criteria in GIS-based FF-TOPSIS and compared outputs with earlier versions of the TOPSIS method (crisp and triangular fuzzy numbers (TFN)). Although all three versions indicated high correlations of >0.89, 20.88% of pixels' priority differed depending on the chosen method's logic. Regarding the sensitivity analysis, the GIS-based FF-TOPSIS in terms of criteria's weight was substantially more resistant to uncertainty than the TNF-TOPSIS. Besides, the GIS-based FF-TOPSIS has rational sensitivity (i.e., tolerance) to the accuracy of input data. The GIS-based FF-TOPSIS method demonstrated sensitivity or robustness depending on the degree of uncertainty in the numbers, which can be altered depending on the expertise and mastery of experts. Our findings indicated that approximately 13.81% of the entire country has the potential for solar power plants. According to the results of the GIS-based FF-TOPSIS approach, the provinces of Sistan and Baluchestan, Hormozgan, Fars, and Khuzestan have the largest potential for solar power farms in Iran.

Drone exploration of bat echolocation: A UAV-borne multimicrophone array to study bat echolocation.

Multimicrophone array techniques offer crucial insight into bat echolocation, yet they severely undersample the environments bats operate in as they are limited in geographic placement and mobility. UAVs are excellent candidates to greatly increase the environments in which such arrays can be deployed, but the impact of UAV noise on recording quality and the UAV's behavioral impact on the bats may affect usability. We developed a UAV-borne multimicrophone setup capable of recording bat echolocation across diverse environments. We quantify and mitigate the impact of UAV noise on the recording setup and test the recording capability of the array by recording four common Danish bat species: Pipistrellus pygmaeus, Myotis daubentonii, Eptesicus serotinus, and Nyctalus noctula. The UAV produces substantial noise at ultrasonic frequencies relevant to many bat species. However, suspending the array 30m below the UAV attenuates the noise to levels below the self-noise of our recording system at 20 kHz and above, and we successfully record and acoustically localize all four bat species. The behavioral impact of the UAV is minimal as all four species approached the array to within 1m and all emitted recordable feeding buzzes. UAV-borne multimicrophone arrays will allow us to quantify bat echolocation in hitherto unexplored habitats and provide crucial insight into how bats operate their sonar across their entire natural habitat.

Abstract 10670: Impact of Virtual Interviewing on Geographic Placement in the Cardiology Fellowship Match

Introduction: Virtual interviewing for cardiology fellowship was instituted in the 2021 fellowship application cycle due to the COVID-19 pandemic and restricted travel. It is unknown what impact this has had on geographic patterns of fellow-training program matching. Our aim was to determine if there was a significant difference in the geographic placement in the cardiology fellowship match based on virtual interviews compared to prior years with in-person interviewing. Methods: All U.S. based accredited cardiovascular disease fellowship programs that participated in the 2019-2021 fellowship match cycles were identified. Those that had publicly available data regarding fellow residency training and training year were included. Each fellow was categorized based on their fellowship program and residency training as from the same program, from the same state, from the same region or from a different region. These were mutually exclusive categories. Results: Of the 236 eligible programs, 118 programs (50%) had available data for the 2019-2021 application cycles. Cumulatively n=1787 total fellows were identified. Compared to the pre-virtual cohort (n=1178 matched fellows) there was no difference in the geographic placement during the 2021 virtual cycle (n=609 matched fellows) including the proportion that matched at the same program (30.6% vs 31.5%, p=0.738), in the same state (13% vs 13.8%, p=0.719), same region (24.2% vs 19.7%, p=0.164), or different region (35% vs 33.1%, p=0.274). There was also no difference when stratified by small, medium, or large program size or geographic region. Conclusions: The use of virtual interviewing in the 2021 cardiology fellowship application cycle did not result in a significant difference in the geographic placement of fellows. Further study is needed to evaluate the impact of virtual interviewing and optimize its use in fellowship recruitment.

Seismic zoning maps of the National Capital Region (NCR) of India

AbstractWe present seismic zoning maps of the National Capital Region (NCR) of India in terms of uniform hazard spectrum (UHS) amplitudes using three different attenuation equations to model the contributions of local earthquakes around the region and distant earthquakes in northwestern Himalaya (NWH) and Hindu Kush Subduction (HKS) sources. Our results show that the shape of design spectra must depend on the nature of contributing earthquake sources, their relative activity, the potential to create large magnitudes, and their geographical placement relative to the site selected for hazard computation. Our results also show that specifying strong motion amplitudes for use in engineering design by means of peak ground acceleration and a standard spectral shape may result in significant underestimation of intermediate and long‐period ground motions critical for buildings higher than four to five stories and hence should not be used. We present zoning maps for nine possible combinations of three different local geological site conditions (sediments, intermediate sites, and basement rock sites) and three different soil site conditions (“rock,” stiff soil sites, and deep soil sites). One of these maps can be readily used to extract the UHS amplitudes of the pseudo relative velocity spectrum (PSV) at any site in the NCR by specifying the local geological site‐condition parameters from a high‐resolution surface geological map of the region and determining the local soil site conditions by experiments limited to the site alone. The paper also provides a geological map of NCR on a scale of 1:1 million for a rough idea of the local geological parameters for a site of interest.

Emerging Disparities in the Placement of Law Enforcement-Based Treatment Referral and Recovery Programs

Rising rates of opioid use disorder, overdoses, and opioid-related criminal offenses have prompted U.S. law enforcement agencies to adopt alternatives to arrest and formal criminal processing. Police departments frequently implement treatment referral programs and claim an affiliation with the Police Assisted Addiction and Recovery Initiative (PAARI). Although expanding to hundreds of agencies, PAARI efforts may not be equally distributed across communities, raising concerns about access to non-arrest diversion and increasing disparities in the criminal processing of drug-related offenses. This study compares the characteristics and geographic placement of law enforcement agencies with and without PAARI programs in 29 states. Law enforcement agencies situated in communities with lower rates of poverty and smaller Black populations have lower odds of having a PAARI program. Agencies based in counties with more overdose deaths and greater unmet treatment needs have increased odds of deflection programing. This placement of PAARI programs reflects broader inequalities in criminal justice and health. More advantaged, predominantly white communities benefit from diversionary programs while fewer alternatives to formal criminal processing exist for lower-income areas and communities of color. Additional research should explore these growing disparities in the deployment of law enforcement-based treatment referral programs and their consequences on drug law enforcement.