Atomically Precise Manufacturing (APM) refers to the assembly of materials with atomic precision, representing a highly advanced technology with significant potential. However, the development of APM remains in its early stages, with applications largely confined to specialized fields and lacking cohesion within a unified discipline. The current literature on APM is often dominated by older, speculative papers that discuss its immense potential risks and benefits without sufficient grounding in the latest advancements or practical limitations that exist today. This paper aims to bridge this gap by providing a comprehensive assessment of current APM and near-APM technologies, as well as using the barriers to further progress to predict future developments. Through this analysis, we seek to establish a clearer understanding of the present state of the technology and then use these insights to predict the future trajectory of APM. By doing so, we aim to create a more grounded discourse on APM and its potential risks and benefits, while also guiding future research on the necessary regulations and safety considerations for this emerging field.
{"title":"A Comprehensive Analysis of the Future of Atomically Precise Manufacturing","authors":"Vadym Shvydun, Justin Sato, Gabriel Bristot","doi":"arxiv-2409.00955","DOIUrl":"https://doi.org/arxiv-2409.00955","url":null,"abstract":"Atomically Precise Manufacturing (APM) refers to the assembly of materials\u0000with atomic precision, representing a highly advanced technology with\u0000significant potential. However, the development of APM remains in its early\u0000stages, with applications largely confined to specialized fields and lacking\u0000cohesion within a unified discipline. The current literature on APM is often\u0000dominated by older, speculative papers that discuss its immense potential risks\u0000and benefits without sufficient grounding in the latest advancements or\u0000practical limitations that exist today. This paper aims to bridge this gap by\u0000providing a comprehensive assessment of current APM and near-APM technologies,\u0000as well as using the barriers to further progress to predict future\u0000developments. Through this analysis, we seek to establish a clearer\u0000understanding of the present state of the technology and then use these\u0000insights to predict the future trajectory of APM. By doing so, we aim to create\u0000a more grounded discourse on APM and its potential risks and benefits, while\u0000also guiding future research on the necessary regulations and safety\u0000considerations for this emerging field.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding healthcare system resilience has become paramount, particularly in the wake of the COVID-19 pandemic, which imposed unprecedented burdens on healthcare services and severely impacted public health. Resilience is defined as the system's ability to absorb, recover from, and adapt to disruptions; however, despite extensive studies on this subject, we still lack empirical evidence and mathematical tools to quantify its adaptability (the ability of the system to adjust to and learn from disruptions). By analyzing millions of patients' electronic medical records across US states, we find that the COVID-19 pandemic caused two successive waves of disruptions within the healthcare systems, enabling natural experiment analysis of the adaptive capacity for each system to adapt to past disruptions. We generalize the quantification framework and find that the US healthcare systems exhibit substantial adaptability but only a moderate level of resilience. When considering system responses across racial groups, Black and Hispanic groups were more severely impacted by pandemic disruptions than White and Asian groups. Physician abundance is the key characteristic for determining healthcare system resilience. Our results offer vital guidance in designing resilient and sustainable healthcare systems to prepare for future waves of disruptions akin to COVID-19 pandemics.
{"title":"Healthcare system resilience and adaptability to pandemic disruptions in the United States","authors":"Lu Zhong, Dimitri Lopez, Sen Pei, Jianxi Gao","doi":"arxiv-2409.01454","DOIUrl":"https://doi.org/arxiv-2409.01454","url":null,"abstract":"Understanding healthcare system resilience has become paramount, particularly\u0000in the wake of the COVID-19 pandemic, which imposed unprecedented burdens on\u0000healthcare services and severely impacted public health. Resilience is defined\u0000as the system's ability to absorb, recover from, and adapt to disruptions;\u0000however, despite extensive studies on this subject, we still lack empirical\u0000evidence and mathematical tools to quantify its adaptability (the ability of\u0000the system to adjust to and learn from disruptions). By analyzing millions of\u0000patients' electronic medical records across US states, we find that the\u0000COVID-19 pandemic caused two successive waves of disruptions within the\u0000healthcare systems, enabling natural experiment analysis of the adaptive\u0000capacity for each system to adapt to past disruptions. We generalize the\u0000quantification framework and find that the US healthcare systems exhibit\u0000substantial adaptability but only a moderate level of resilience. When\u0000considering system responses across racial groups, Black and Hispanic groups\u0000were more severely impacted by pandemic disruptions than White and Asian\u0000groups. Physician abundance is the key characteristic for determining\u0000healthcare system resilience. Our results offer vital guidance in designing\u0000resilient and sustainable healthcare systems to prepare for future waves of\u0000disruptions akin to COVID-19 pandemics.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pattern recognition constitutes a particularly important task underlying a great deal of scientific and technologica activities. At the same time, pattern recognition involves several challenges, including the choice of features to represent the data elements, as well as possible respective transformations. In the present work, the classification potential of the Euclidean distance and a dissimilarity index based on the coincidence similarity index are compared by using the k-neighbors supervised classification method respectively to features resulting from several types of transformations of one- and two-dimensional symmetric densities. Given two groups characterized by respective densities without or with overlap, different types of respective transformations are obtained and employed to quantitatively evaluate the performance of k-neighbors methodologies based on the Euclidean distance an coincidence similarity index. More specifically, the accuracy of classifying the intersection point between the densities of two adjacent groups is taken into account for the comparison. Several interesting results are described and discussed, including the enhanced potential of the dissimilarity index for classifying datasets with right skewed feature densities, as well as the identification that the sharpness of the comparison between data elements can be independent of the respective supervised classification performance.
{"title":"Supervised Pattern Recognition Involving Skewed Feature Densities","authors":"Alexandre Benatti, Luciano da F. Costa","doi":"arxiv-2409.01213","DOIUrl":"https://doi.org/arxiv-2409.01213","url":null,"abstract":"Pattern recognition constitutes a particularly important task underlying a\u0000great deal of scientific and technologica activities. At the same time, pattern\u0000recognition involves several challenges, including the choice of features to\u0000represent the data elements, as well as possible respective transformations. In\u0000the present work, the classification potential of the Euclidean distance and a\u0000dissimilarity index based on the coincidence similarity index are compared by\u0000using the k-neighbors supervised classification method respectively to features\u0000resulting from several types of transformations of one- and two-dimensional\u0000symmetric densities. Given two groups characterized by respective densities\u0000without or with overlap, different types of respective transformations are\u0000obtained and employed to quantitatively evaluate the performance of k-neighbors\u0000methodologies based on the Euclidean distance an coincidence similarity index.\u0000More specifically, the accuracy of classifying the intersection point between\u0000the densities of two adjacent groups is taken into account for the comparison.\u0000Several interesting results are described and discussed, including the enhanced\u0000potential of the dissimilarity index for classifying datasets with right skewed\u0000feature densities, as well as the identification that the sharpness of the\u0000comparison between data elements can be independent of the respective\u0000supervised classification performance.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bobby Xiong, Davide Fioriti, Fabian Neumann, Iegor Riepin, Tom Brown
This paper provides the background, methodology and validation for constructing a representation of the European high-voltage grid, including and above 200 kV, based on public data provided by OpenStreetMap. The model-independent grid dataset is published under the Open Data Commons Open Database (ODbL 1.0) licence and can be used for large-scale electricity as well as energy system modelling. The dataset and workflow are provided as part of PyPSA-Eur -- an open-source, sector-coupled optimisation model of the European energy system. By integrating with the codebase for initiatives such as PyPSA-Earth, the value of open and maintainable high-voltage grid data extends to the global context. By accessing the latest data through the the Overpass turbo API, the dataset can be easily reconstructed and updated within minutes. To assess the data quality, this paper further compares the dataset with official statistics and representative model runs using PyPSA-Eur based on different electricity grid representations.
{"title":"Modelling the High-Voltage Grid Using Open Data for Europe and Beyond","authors":"Bobby Xiong, Davide Fioriti, Fabian Neumann, Iegor Riepin, Tom Brown","doi":"arxiv-2408.17178","DOIUrl":"https://doi.org/arxiv-2408.17178","url":null,"abstract":"This paper provides the background, methodology and validation for\u0000constructing a representation of the European high-voltage grid, including and\u0000above 200 kV, based on public data provided by OpenStreetMap. The\u0000model-independent grid dataset is published under the Open Data Commons Open\u0000Database (ODbL 1.0) licence and can be used for large-scale electricity as well\u0000as energy system modelling. The dataset and workflow are provided as part of\u0000PyPSA-Eur -- an open-source, sector-coupled optimisation model of the European\u0000energy system. By integrating with the codebase for initiatives such as\u0000PyPSA-Earth, the value of open and maintainable high-voltage grid data extends\u0000to the global context. By accessing the latest data through the the Overpass\u0000turbo API, the dataset can be easily reconstructed and updated within minutes.\u0000To assess the data quality, this paper further compares the dataset with\u0000official statistics and representative model runs using PyPSA-Eur based on\u0000different electricity grid representations.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yanmeng Xing, Ye Sun, Tongxin Pan, Xianglong Liang, Giacomo Livan, Yifang Ma
In science, mentees often follow their mentors' career paths, but exceptional mentees frequently break from this routine, sometimes even outperforming their mentors. However, the pathways to independence for these excellent mentees and their interactions with mentors remain unclear. We analyzed the careers of over 500,000 mentees in Chemistry, Neuroscience, and Physics over the past 60 years to examine the strategies mentees employ in selecting research topics relative to their mentors, how these strategies evolve, and their resulting impact. Utilizing co-citation network analysis and a topic-specific impact allocation algorithm, we mapped the topic territory for each mentor-mentee pair and quantified their academic impact accrued within the topic. Our findings reveal mentees tend to engage with their mentors' less-dominated topics and explore new topics at the same time, and through this exaptive process, they begin to progressively establish their own research territories. This trend is particularly pronounced among those who outperform their mentors. Moreover, we identified an inverted U-shaped curve between the extent of topic divergence and the mentees' long-term impact, suggesting a moderate divergence from the mentors' research focus optimizes the mentees' academic impact. Finally, along the path to independence, increased coauthorship with mentors impedes the mentees' impact, whereas extending their collaboration networks with the mentors' former collaborators proves beneficial. These findings fill a crucial gap in understanding how mentees' research topic selection strategies affect academic success and offer valuable guidance for early-career researchers on pursuing independent research paths.
在科学领域，被指导者通常会沿着导师的职业道路前进，但优秀的被指导者往往会打破这种常规，有时甚至会超越导师。然而，这些优秀被指导者实现独立的途径以及他们与指导者之间的互动仍不清楚。我们分析了化学、神经科学和物理学领域过去 60 年里 50 多万名被指导者的职业生涯，研究了被指导者相对于指导者在选择研究课题时所采用的策略、这些策略是如何演变的，以及由此产生的影响。我们的研究结果表明，被指导者倾向于参与指导者不太主导的课题，同时探索新的课题，通过这一适应过程，他们开始逐步建立自己的研究领地。这种趋势在那些表现优于导师的学生中尤为明显。此外，我们还发现，课题分歧程度与被指导者的长期影响力之间存在倒 U 型曲线，这表明，与指导者研究重点的适度分歧能优化被指导者的学术影响力。最后，在通往独立的道路上，与导师增加合作会阻碍被指导者的影响力，而与导师的前合作者扩大合作网络则证明是有益的。这些发现填补了人们在了解被指导者的研究选题策略如何影响学术成功方面的一个重要空白，并为早期研究人员走上独立研究之路提供了宝贵的指导。
{"title":"Exaptation: Academic mentees' career pathway to be independent and impactful","authors":"Yanmeng Xing, Ye Sun, Tongxin Pan, Xianglong Liang, Giacomo Livan, Yifang Ma","doi":"arxiv-2408.16992","DOIUrl":"https://doi.org/arxiv-2408.16992","url":null,"abstract":"In science, mentees often follow their mentors' career paths, but exceptional\u0000mentees frequently break from this routine, sometimes even outperforming their\u0000mentors. However, the pathways to independence for these excellent mentees and\u0000their interactions with mentors remain unclear. We analyzed the careers of over\u0000500,000 mentees in Chemistry, Neuroscience, and Physics over the past 60 years\u0000to examine the strategies mentees employ in selecting research topics relative\u0000to their mentors, how these strategies evolve, and their resulting impact.\u0000Utilizing co-citation network analysis and a topic-specific impact allocation\u0000algorithm, we mapped the topic territory for each mentor-mentee pair and\u0000quantified their academic impact accrued within the topic. Our findings reveal\u0000mentees tend to engage with their mentors' less-dominated topics and explore\u0000new topics at the same time, and through this exaptive process, they begin to\u0000progressively establish their own research territories. This trend is\u0000particularly pronounced among those who outperform their mentors. Moreover, we\u0000identified an inverted U-shaped curve between the extent of topic divergence\u0000and the mentees' long-term impact, suggesting a moderate divergence from the\u0000mentors' research focus optimizes the mentees' academic impact. Finally, along\u0000the path to independence, increased coauthorship with mentors impedes the\u0000mentees' impact, whereas extending their collaboration networks with the\u0000mentors' former collaborators proves beneficial. These findings fill a crucial\u0000gap in understanding how mentees' research topic selection strategies affect\u0000academic success and offer valuable guidance for early-career researchers on\u0000pursuing independent research paths.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ghid KaramLIED, Maïlys ChanialLIED, Maxime ChaumontLIED, Martin HendelLIED, Laurent Royon
Climate change will result in more frequent, more intense and longer-lasting heat waves by 2050. As part of its Climate Plan and its resilience strategy, the City of Paris is deploying, through its Oasis program, a network of urban cool islands to mitigate the urban heat island phenomena: schoolyards are renovated in order to reduce the heat stress of users. We establish a methodology aiming to quantify the microclimatic impact of the transformation. Mobile measurements are carried out within a case courtyard under hot conditions and coupled with fixed weather station data to evaluate heat stress using UTCI. The heat stress mapping thus obtained allows a first microclimatic diagnosis of the schoolyard.
{"title":"Cartographie du confort thermique au sein d'une cours d'{é}cole parisienne : couplage de mesures microclimatiques fixes et mobiles","authors":"Ghid KaramLIED, Maïlys ChanialLIED, Maxime ChaumontLIED, Martin HendelLIED, Laurent Royon","doi":"arxiv-2409.00148","DOIUrl":"https://doi.org/arxiv-2409.00148","url":null,"abstract":"Climate change will result in more frequent, more intense and longer-lasting\u0000heat waves by 2050. As part of its Climate Plan and its resilience strategy,\u0000the City of Paris is deploying, through its Oasis program, a network of urban\u0000cool islands to mitigate the urban heat island phenomena: schoolyards are\u0000renovated in order to reduce the heat stress of users. We establish a\u0000methodology aiming to quantify the microclimatic impact of the transformation.\u0000Mobile measurements are carried out within a case courtyard under hot\u0000conditions and coupled with fixed weather station data to evaluate heat stress\u0000using UTCI. The heat stress mapping thus obtained allows a first microclimatic\u0000diagnosis of the schoolyard.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study synthetic temporal networks whose evolution is determined by stochastically evolving node variables - synthetic analogues of, e.g., temporal proximity networks of mobile agents. We quantify the long-timescale correlations of these evolving networks by an autocorrelative measure of edge persistence. Several distinct patterns of autocorrelation arise, including power-law decay and exponential decay, depending on the choice of node-variable dynamics and connection probability function. Our methods are also applicable in wider contexts; our temporal network models are tractable mathematically and in simulation, and our long-term memory quantification is analytically tractable and straightforwardly computable from temporal network data.
{"title":"Autocorrelation properties of temporal networks governed by dynamic node variables","authors":"Harrison Hartle, Naoki Masuda","doi":"arxiv-2408.16270","DOIUrl":"https://doi.org/arxiv-2408.16270","url":null,"abstract":"We study synthetic temporal networks whose evolution is determined by\u0000stochastically evolving node variables - synthetic analogues of, e.g., temporal\u0000proximity networks of mobile agents. We quantify the long-timescale\u0000correlations of these evolving networks by an autocorrelative measure of edge\u0000persistence. Several distinct patterns of autocorrelation arise, including\u0000power-law decay and exponential decay, depending on the choice of node-variable\u0000dynamics and connection probability function. Our methods are also applicable\u0000in wider contexts; our temporal network models are tractable mathematically and\u0000in simulation, and our long-term memory quantification is analytically\u0000tractable and straightforwardly computable from temporal network data.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valisoa RakotonirinjanaharyPC2A, Suzanne CrumeyrolleLOA, Mateusz BogdanPC2A, Benjamin HanounePC2A
To enhance the understanding of air quality within underground railway stations (URS), a methodology has been developed to establish a baseline profile of particle concentrations (PM10 and PM2.5). This approach incorporates an extensive data cleaning process based on the identification of URS operation periods, physically inconsistent or mathematically aberrant data, and comparing the profile of each day to an average profile. The versatility of this methodology allows its application to different particle classes within various URS. The results obtained from the three studied URS indicate the possibility of obtaining reliable daily typical profiles even over short measurement periods (up to one or two weeks).
{"title":"Typical daily profiles of PM concentrations in parisian underground railway stations","authors":"Valisoa RakotonirinjanaharyPC2A, Suzanne CrumeyrolleLOA, Mateusz BogdanPC2A, Benjamin HanounePC2A","doi":"arxiv-2409.08291","DOIUrl":"https://doi.org/arxiv-2409.08291","url":null,"abstract":"To enhance the understanding of air quality within underground railway\u0000stations (URS), a methodology has been developed to establish a baseline\u0000profile of particle concentrations (PM10 and PM2.5). This approach incorporates\u0000an extensive data cleaning process based on the identification of URS operation\u0000periods, physically inconsistent or mathematically aberrant data, and comparing\u0000the profile of each day to an average profile. The versatility of this\u0000methodology allows its application to different particle classes within various\u0000URS. The results obtained from the three studied URS indicate the possibility\u0000of obtaining reliable daily typical profiles even over short measurement\u0000periods (up to one or two weeks).","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elma Dervić, Ola Ali, Carola Deischinger, Rafael Prieto-Curiel, Rainer Stütz, Ellenor Mittendorfer-Rutz, Peter Klimek
Equal access to health ensures that all citizens, regardless of socio-economic status, can achieve optimal health, leading to a more productive, equitable, and resilient society. Yet, migrant populations were frequently observed to have lower access to health. The reasons for this are not entirely clear and may include language barriers, a lack of knowledge of the healthcare system, and selective migration (a "healthy migrant" effect). We use extensive medical claims data from Austria (13 million hospital stays of approximately 4 million individuals) to compare the healthcare utilization patterns between Austrians and non-Austrians. We looked at the differences in primary diagnoses and hospital sections of initial hospital admission across different nationalities. We hypothesize that cohorts experiencing the healthy migrant effect show lower readmission rates after hospitalization compared to migrant populations that are in poorer health but show lower hospitalization rates due to barriers in access. We indeed find that all nationalities showed lower hospitalization rates than Austrians, except for Germans, who exhibit a similar healthcare usage to Austrians. Although around 20% of the population has a migration background, non-Austrian citizens account for only 9.4% of the hospital patients and 9.79% of hospital nights. However, results for readmission rates are much more divergent. Nationalities like Hungary, Romania, and Turkey (females) show decreased readmission rates in line with the healthy migrant effect. Patients from Russia, Serbia, and Turkey (males) show increased readmissions, suggesting that their lower hospitalization rates are more likely due to access barriers. Considering the surge in migration, our findings shed light on healthcare access and usage behaviours across patients with different nationalities, offering new insights and perspectives.
{"title":"Healthcare Utilization Patterns Among Migrant Populations: Increased Readmissions Suggest Poorer Access. A Population-Wide Retrospective Cohort Study","authors":"Elma Dervić, Ola Ali, Carola Deischinger, Rafael Prieto-Curiel, Rainer Stütz, Ellenor Mittendorfer-Rutz, Peter Klimek","doi":"arxiv-2408.16317","DOIUrl":"https://doi.org/arxiv-2408.16317","url":null,"abstract":"Equal access to health ensures that all citizens, regardless of\u0000socio-economic status, can achieve optimal health, leading to a more\u0000productive, equitable, and resilient society. Yet, migrant populations were\u0000frequently observed to have lower access to health. The reasons for this are\u0000not entirely clear and may include language barriers, a lack of knowledge of\u0000the healthcare system, and selective migration (a \"healthy migrant\" effect). We\u0000use extensive medical claims data from Austria (13 million hospital stays of\u0000approximately 4 million individuals) to compare the healthcare utilization\u0000patterns between Austrians and non-Austrians. We looked at the differences in\u0000primary diagnoses and hospital sections of initial hospital admission across\u0000different nationalities. We hypothesize that cohorts experiencing the healthy\u0000migrant effect show lower readmission rates after hospitalization compared to\u0000migrant populations that are in poorer health but show lower hospitalization\u0000rates due to barriers in access. We indeed find that all nationalities showed\u0000lower hospitalization rates than Austrians, except for Germans, who exhibit a\u0000similar healthcare usage to Austrians. Although around 20% of the population\u0000has a migration background, non-Austrian citizens account for only 9.4% of the\u0000hospital patients and 9.79% of hospital nights. However, results for\u0000readmission rates are much more divergent. Nationalities like Hungary, Romania,\u0000and Turkey (females) show decreased readmission rates in line with the healthy\u0000migrant effect. Patients from Russia, Serbia, and Turkey (males) show increased\u0000readmissions, suggesting that their lower hospitalization rates are more likely\u0000due to access barriers. Considering the surge in migration, our findings shed\u0000light on healthcare access and usage behaviours across patients with different\u0000nationalities, offering new insights and perspectives.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite significant anecdotal evidence regarding the vulnerability of the U.S. power infrastructure, there is a dearth of longitudinal and nation-level characterization of the spatial and temporal patterns in the frequency and extent of power outages. A data-driven national-level characterization of power outage vulnerability is particularly essential for understanding the urgency and formulating policies to promote the resilience of power infrastructure systems. Recognizing this, we retrieved 179,053,397 county-level power outage records with a 15-minute interval across 3,022 US counties during 2014-2023 to capture power outage characteristics. We focus on three dimensions--power outage intensity, frequency, and duration--and develop multiple metrics to quantify each dimension of power outage vulnerability. The results show that in the past ten years, the vulnerability of U.S. power system has consistently been increasing. Counties experienced an average of 999.4 outages over the decade, affecting an average of more than 540,000 customers per county, with disruptions occurring approximately every week. Coastal areas, particularly in California, Florida and New Jersey, faced more frequent and prolonged outages, while inland regions showed higher outage rates. A concerning increase in outage frequency and intensity was noted, especially after 2017, with a sharp rise in prolonged outages since 2019. The research also found positive association between social vulnerability and outage metrics, with the association becoming stronger over the years under study. Areas with higher social vulnerability experienced more severe and frequent outages, exacerbating challenges in these regions. These findings reveal the much-needed empirical evidence for stakeholders to inform policy formulation and program development for enhancing the resilience of the U.S. power infrastructure.
{"title":"Recent Decade's Power Outage Data Reveals the Increasing Vulnerability of U.S. Power Infrastructure","authors":"Bo Li, Junwei Ma, Femi Omitaomu, Ali Mostafavi","doi":"arxiv-2408.15882","DOIUrl":"https://doi.org/arxiv-2408.15882","url":null,"abstract":"Despite significant anecdotal evidence regarding the vulnerability of the\u0000U.S. power infrastructure, there is a dearth of longitudinal and nation-level\u0000characterization of the spatial and temporal patterns in the frequency and\u0000extent of power outages. A data-driven national-level characterization of power\u0000outage vulnerability is particularly essential for understanding the urgency\u0000and formulating policies to promote the resilience of power infrastructure\u0000systems. Recognizing this, we retrieved 179,053,397 county-level power outage\u0000records with a 15-minute interval across 3,022 US counties during 2014-2023 to\u0000capture power outage characteristics. We focus on three dimensions--power\u0000outage intensity, frequency, and duration--and develop multiple metrics to\u0000quantify each dimension of power outage vulnerability. The results show that in\u0000the past ten years, the vulnerability of U.S. power system has consistently\u0000been increasing. Counties experienced an average of 999.4 outages over the\u0000decade, affecting an average of more than 540,000 customers per county, with\u0000disruptions occurring approximately every week. Coastal areas, particularly in\u0000California, Florida and New Jersey, faced more frequent and prolonged outages,\u0000while inland regions showed higher outage rates. A concerning increase in\u0000outage frequency and intensity was noted, especially after 2017, with a sharp\u0000rise in prolonged outages since 2019. The research also found positive\u0000association between social vulnerability and outage metrics, with the\u0000association becoming stronger over the years under study. Areas with higher\u0000social vulnerability experienced more severe and frequent outages, exacerbating\u0000challenges in these regions. These findings reveal the much-needed empirical\u0000evidence for stakeholders to inform policy formulation and program development\u0000for enhancing the resilience of the U.S. power infrastructure.","PeriodicalId":501043,"journal":{"name":"arXiv - PHYS - Physics and Society","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142220968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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