763 research outputs found

    Analysing the Global and Local Spatial Associations of Medical Resources Across Wuhan City Using POI Data

    Get PDF
    Background: There is a sharp contradiction between the supply and demand of medical resources in the provincial capitals of China. Understanding the spatial patterns of medical resources and identifying their spatial association and heterogeneity is a prerequisite to ensuring that limited resources are allocated fairly and optimally, which, along with improvements to urban residents’ quality of life, is a key aim of healthy city planning. However, the existing studies on medical resources pattern mainly focus on their spatial distribution and evolution characteristics, and lack the analyses of the spatial co-location between medical resources from the global and local perspectives. It is worth noting that the research on the spatial relationship between medical resources is an important way to realize the spatial equity and operation efficiency of urban medical resources. Methods: Localized colocation quotient (LCLQ) analysis has been used successfully to measure directional spatial associations and heterogeneity between categorical point data. Using point of interest (POI) data and the LCLQ method, this paper presents the first analysis of spatial patterns and directional spatial associations between six medical resources across Wuhan city. Results: (1) Pharmacies, clinics and community hospitals show “multicentre + multicircle”, “centre + axis + dot” and “banded” distribution characteristics, respectively, but specialized hospitals and general hospitals present “single core” and “double core” modes. (2) Overall, medical resources show agglomeration characteristics. The degrees of spatial agglomeration of the five medical resources, are ranked from high to low as follows: pharmacy, clinic, community hospital, special hospital, general hospital and 3A hospital. (3) Although pharmacies, clinics, and community hospitals of basic medical resources are interdependent, specialized hospitals, general hospitals and 3A hospitals of professional medical resources are also interdependent; furthermore, basic medical resources and professional medical resources are mutually exclusive. Conclusions: Government and urban planners should pay great attention to the spatial distribution characteristics and association intensity of medical resources when formulating relevant policies. The findings of this study contribute to health equity and health policy discussions around basic medical services and professional medical services

    Evaluating the sustainability and resiliency of local food systems

    Get PDF
    With an ever-rising global population and looming environmental challenges such as climate change and soil degradation, it is imperative to increase the sustainability of food production. The drastic rise in food insecurity during the COVID-19 pandemic has further shown a pressing need to increase the resiliency of food systems. One strategy to reduce the dependence on complex, vulnerable global supply chains is to strengthen local food systems, such as by producing more food in cities. This thesis uses an interdisciplinary, food systems approach to explore aspects of sustainability and resiliency within local food systems. Lifecycle assessment (LCA) was used to evaluate how farm scale, distance to consumer, and management practices influence environmental impacts for different local agriculture models in two case study locations: Georgia, USA and England, UK. Farms were grouped based on urbanisation level and management practices, including: urban organic, peri-urban organic, rural organic, and rural conventional. A total of 25 farms and 40 crop lifecycles were evaluated, focusing on two crops (kale and tomatoes) and including impacts from seedling production through final distribution to the point of sale. Results were extremely sensitive to the allocation of composting burdens (decomposition emissions), with impact variation between organic farms driven mainly by levels of compost use. When composting burdens were attributed to compost inputs, the rural conventional category in the U.S. and the rural organic category in the UK had the lowest average impacts per kg sellable crop produced, including the lowest global warming potential (GWP). However, when subtracting avoided burdens from the municipal waste stream from compost inputs, trends reversed entirely, with urban or peri-urban farm categories having the lowest impacts (often negative) for GWP and marine eutrophication. Overall, farm management practices were the most important factor driving environmental impacts from local food supply chains. A soil health assessment was then performed on a subset of the UK farms to provide insight to ecosystem services that are not captured within LCA frameworks. Better soil health was observed in organically-farmed and uncultivated soils compared to conventionally farmed soils, suggesting higher ecosystem service provisioning as related to improved soil structure, flood mitigation, erosion control, and carbon storage. However, relatively high heavy metal concentrations were seen on urban and peri-urban farms, as well as those located in areas with previous mining activity. This implies that there are important services and disservices on farms that are not captured by LCAs. Zooming out from a focus on food production, a qualitative methodology was used to explore experiences of food insecurity and related health and social challenges during the COVID-19 pandemic. Fourteen individuals receiving emergency food parcels from a community food project in Sheffield, UK were interviewed. Results showed that maintaining food security in times of crisis requires a diverse set of individual, household, social, and place-based resources, which were largely diminished or strained during the pandemic. Drawing upon social capital and community support was essential to cope with a multiplicity of hardship, highlighting a need to develop community food infrastructure that supports ideals of mutual aid and builds connections throughout the food supply chain. Overall, this thesis shows that a range of context-specific solutions are required to build sustainable and resilient food systems. This can be supported by increasing local control of food systems and designing strategies to meet specific community needs, whilst still acknowledging a shared global responsibility to protect ecosystem, human, and planetary health

    Analytics and optimization for emergency healthcare processes

    Get PDF
    This thesis deals with the analysis and management of emergency healthcare processes through the use of advanced analytics and optimization approaches. Emergency processes are among the most complex within healthcare. This is due to their non-elective nature and their high variability. This thesis is divided into two topics. The first one concerns the core of emergency healthcare processes, the emergency department (ED). In the second chapter, we describe the ED that is the case study. This is a real case study with data derived from a large ED located in northern Italy. In the next two chapters, we introduce two tools for supporting ED activities. The first one is a new type of analytics model. Its aim is to overcome the traditional methods of analyzing the activities provided in the ED by means of an algorithm that analyses the ED pathway (organized as event log) as a whole. The second tool is a decision-support system, which integrates a deep neural network for the prediction of patient pathways, and an online simulator to evaluate the evolution of the ED over time. Its purpose is to provide a set of solutions to prevent and solve the problem of the ED overcrowding. The second part of the thesis focuses on the COVID-19 pandemic emergency. In the fifth chapter, we describe a tool that was used by the Bologna local health authority in the first part of the pandemic. Its purpose is to analyze the clinical pathway of a patient and from this automatically assign them a state. Physicians used the state for routing the patients to the correct clinical pathways. The last chapter is dedicated to the description of a MIP model, which was used for the organization of the COVID-19 vaccination campaign in the city of Bologna, Italy

    Reshaping Higher Education for a Post-COVID-19 World: Lessons Learned and Moving Forward

    Get PDF
    No abstract available

    Seeing Ordinary Objects: The Minimal Condition, Amodal Completion, and Mental Files

    Full text link
    This thesis seeks to explain the way in which we see ordinary objects like books, tables, and apples. Specifically, it is an attempt to explain the way that we are connected to the ordinary objects that populate our world despite the fact that we usually only receive sensory stimulation from small parts of them: their surfaces. I will suggest some conditions that must obtain for ordinary objects to be seen and present a conceptual schema based on the notion of ‘mental files’ that can be used to explain this phenomenon. Mental files, I argue, can not only be used to explain our perceptual connection to ordinary objects but can also dissolve some of the epistemic worries raised by amodal completion and the problem of incomplete sensory information

    ML-based data-entry automation and data anomaly detection to support data quality assurance

    Get PDF
    Data playsacentralroleinmodernsoftwaresystems,whichare very oftenpoweredbymachinelearning(ML)andusedincriticaldo- mains ofourdailylives,suchasfinance,health,andtransportation. However,theeffectivenessofML-intensivesoftwareapplicationshighly depends onthequalityofthedata.Dataqualityisaffectedbydata anomalies; dataentryerrorsareoneofthemainsourcesofanomalies. The goalofthisthesisistodevelopapproachestoensuredataquality by preventingdataentryerrorsduringtheform-fillingprocessandby checking theofflinedatasavedindatabases. The maincontributionsofthisthesisare: 1. LAFF, anapproachtoautomaticallysuggestpossiblevaluesofcat- egorical fieldsindataentryforms. 2. LACQUER, anapproachtoautomaticallyrelaxthecompleteness requirementofdataentryformsbydecidingwhenafieldshould be optionalbasedonthefilledfieldsandhistoricalinputinstances. 3. LAFF-AD, anapproachtoautomaticallydetectdataanomaliesin categorical columnsinofflinedatasets. LAFF andLACQUERfocusmainlyonpreventingdataentryerrors during theform-fillingprocess.Bothapproachescanbeintegratedinto data entryapplicationsasefficientandeffectivestrategiestoassistthe user duringtheform-fillingprocess.LAFF-ADcanbeusedofflineon existing suspiciousdatatoeffectivelydetectanomaliesincategorical data. In addition,weperformedanextensiveevaluationofthethreeap- proaches,assessingtheireffectivenessandefficiency,usingreal-world datasets

    The Impact of Additive Manufacturing on Supply Chains and Business Models: Qualitative Analyses of Supply Chain Design, Governance Structure, and Business Model Change

    Get PDF
    Recent global crises like the COVID-19 pandemic challenge traditional global supply chains (SCs). Their disaggregated, “fine-sliced” character comes with a high risk of disruption, and current supply bottlenecks (e.g., the chip shortage in the automotive industry) demonstrate that there is often no quick fix. Firms are increasingly under pressure to react and (re-)design their SCs to increase their resilience. Additive manufacturing (AM) technologies are acclaimed for their potential to foster the shift from global SCs to shorter, decentralized, and more resilient SCs. The key feature of AM technologies lies in their inherently digital and flexible nature. Their specific characteristics are envisioned to enable location-independent manufacturing close to or even at the point of demand and lead to a commoditization of manufacturing infrastructure for flexible outsourcing to local partners. Moreover, AM technologies are expected to revolutionize the way firms do business and put traditional business models at stake. This doctoral thesis is motivated by the outlined potential of AM and the resulting impact on firms’ supply chain design (SCD) and business model choices. The extant literature raises high expectations for AM. However, concrete and real-world insights from specific application domains are still scarce. This thesis seeks to fill the gap between high-level literature-based visions and currently emerging realistic business models and SCDs for AM. Thereby, AM is understood as a potential intervention emanating from outside firms and requiring them to react by realigning their business models and SC structures to maintain a fit. This thesis aims to build an in-depth understanding of these mechanisms and, hence, of the inner causal processes involved in the AM SCD and business model choices. This concentration on the rationales and underlying behavioral patterns is formalized with primarily exploratory (how and why) research questions that are addressed with qualitative research methodologies, mainly case study research and grounded theory. These methodological practices are applied in the industrial AM context, entailing an embedding of this thesis in challenging industries where AM applications have already started to create value (i.e., in the aerospace, rail, automotive, and machinery and equipment industries). The selected research approaches are mostly inductive and, hence, strongly driven by the data collected from this context (e.g., in interviews, by reviewing documents, and by analyzing websites). Additionally, this thesis relies on grand theories, namely transaction cost economics, the resource-based view, and configuration theory, to discuss the findings in their light and to interpret and distill nuances of these theories for their application in the industrial AM context. This thesis is cumulative, consisting of four studies that form its main body. These studies are organized in two parts, part A and part B, since two domains of strategic decisions are targeted jointly, the business model development (part A) and AM SCD choice (part B) for industrial AM. Different perspectives are associated with the two parts. Logistics service providers (LSPs) are in a critical position to develop AM business models. Based on the expected shift to decentralized, shorter SCs, the traditional business models of LSPs are at risk, and their inherent customer orientation puts them under pressure to adjust to their customers’ needs in AM. In part A, study A.1 applies a process-based perspective to build a broad understanding of how LSPs currently respond to AM and consumer-oriented polymer 3D printing with specific AM activities. It proposes six profiles of how LSPs leverage AM, both as users for their in-house operations and as developers of AM-specific services for external customers. A key finding is that the initiated AM activities are oftentimes strongly based on LSPs’ traditional resources. Only a few LSPs are found whose AM activities are detached from their traditional business models to focus on digital platform-based services for AM. In contrast to the process-based perspective and focus on business model dynamics in study A.1, study A.2 takes an output perspective to propose six generic business model configurations for industrial AM. Each configuration emerges from the perspective of LSPs and is reflected by their potential partners/competitors and industrial customers. Study A.2 explores how the six generic configurations fit specific types of LSPs and how they are embedded in a literature-based service SC for industrial AM. In combination, studies A.1 and A.2 provide a comprehensive understanding of how LSPs are currently reacting to AM and an empirically grounded perspective on “finished” AM business models to evaluate and refine literature-based visions. Part B of this thesis is devoted to the mechanism of (re-)designing SCs for AM, which is investigated from the perspective of focal manufacturing firms based on their dominant position in SCs. Two dimensions are used to characterize AM SCDs, their horizontal scope (geographic dispersion) and vertical scope (governance structure). The combination of both dimensions is ideally suited to capture the literature-based vision of shorter, decentralized AM SCs (horizontal scope) with eased outsourcing to local partners (vertical scope). Study B.1 takes a firm-centric perspective to develop an in-depth understanding for AM make-or-buy decisions of manufacturing firms, the outcomes of which determine the SC governance structure. This study elaborates how the specific (digital and emerging) traits of industrial AM technologies modify arguments of grand theories that explain make-or-buy decisions in the “analog” age. In comparison, study B.2 shifts from a firm-centric to a network perspective to rely on both dimensions for investigating cohesive AM SCD configurations. More specifically, study B.2 explores four polar AM SCD configurations and reveals manufacturing firms’ rationales for selecting them. Thereby, it builds an understanding for why manufacturing firms currently have valid reasons to implement industrial AM in-house or distributed in a secure, firm-owned network. As a result, combining both studies provides an understanding of why manufacturing firms currently select specific governance structures for industrial AM and opt for SCDs that differ from the literature-based vision of decentralized, outsourced AM. Overall, this thesis positions itself as theory-oriented research that also aims at supporting managers of manufacturing firms and LSPs in making informed decisions when implementing AM in their SCs and developing AM-based business models. The three studies A.1, A.2, and B.2 contribute to initial theory building on how and why specific AM business models and SCDs emerge. With their focus on developing an understanding for the causal processes (how and why) and by assuming a process-based and output perspective, they can draw a line from firms’ current reactions to sound reflections on future-oriented, high-level expectations for AM. As a result, the studies significantly enrich and refine the current body of knowledge in the AM business model literature on LSPs and the operations and supply chain management literature on AM SCDs, focusing on their geographic dispersion and governance structure. This thesis further contributes with its context-specificity to building domain knowledge for industrial AM, which can serve as one “puzzle piece” for theorizing on how AM and other digitally dominated (manufacturing) technologies will shape the era of digital business models and SCs. In particular, study B.1 stands out by its focus on theory elaboration and the objective of developing contextual middle-range theory. It reveals that emerging digital AM is a setting where the argumentation of grand theories provides contradicting guidance on whether to develop AM in-house or outsource the manufacturing process. Such findings for industrial AM raise multiple opportunities for future research, among them are the comparison with other industry contexts with similar characteristics and the operationalization of the propositions developed in this thesis in follow-up quantitative decision-support models
    corecore