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The IDS Project was formed in 2003 to improve resource sharing among the State University of New York colleges. Over the years it grew from the original 12 to over 120 libraries. While the focus has always been on community, there has also been a strong developmental desire and innovative push from its members. IDS Project has developed many systems and tools over the years and continues to support resource sharing among all libraries and not just its members. [ABSTRACT FROM AUTHOR]

The metaverse represents a transformative landscape for human interaction, promising an immersive digital ecosystem where users can create, share, and experience resources in novel ways. Within this context, the establishment of Beidou Navigation Satellite System (BDS) commons in the metaverse is an exciting prospect that could revolutionize knowledge sharing, governance, and sustainability. This paper explores the potential of the metaverse as a platform for building BDS commons, focusing on three key dimensions: resource sharing, collaborative governance, and sustainable development. We examine the current state of research, identify existing gaps, and propose directions for future inquiries to fully harness the potential of the metaverse for global resource sharing and collective action. [ABSTRACT FROM AUTHOR]

Summary: Mobile networks have advanced in many fields to share information with others. But finding the required resources for each user to share the data is a complex task because of the moving environment. So, the present research article has introduced a novel Chimp‐based Random Forest Peer Identification Framework (CbRFPIF) in the mobile environment. Initially, the required nodes were designed dynamically in the moving background. Hence, the designed wireless moving environment has included sender, peer, and receiver nodes. Moreover, the Chimp fitness model predicted the users' requested resources in the primary stage, then the nearest peer and the user locations were predicted. Consequently, the requested resource by users was distributed to the particular closest peers, and the peer forwarded the data to the specific users. Finally, the planned model is simulated in the NS2 environment, and the communication parameters were calculated and compared with other associated models, which gained the highest throughput and search rate. [ABSTRACT FROM AUTHOR]

Academic libraries are entering a new reality for collections and resource sharing due to the increased acquisition of electronic books, or ebooks, during the last decade. The need to interlibrary loan (ILL) ebooks will likely increase based on current purchasing trends, but how well are we prepared for this future? Important advancements are underway, but ILL for ebooks is hampered by restrictive licensing models, resource sharing systems, and current practices. This study provides an environmental scan of the current acquisitions and ILL practices of academic libraries. This paper guides academic libraries through these conversations so that they can support the borrowing and lending of ebooks into the future. [ABSTRACT FROM AUTHOR]

This research investigated the role of agricultural cooperatives (ACs) in promoting sustainable agriculture and agrifood security, with a particular emphasis on Greece. A cross-sectional survey technique was employed, and data were collected from 400 farmers and professionals either employed by or associated with Greek agricultural cooperatives by administering an online questionnaire. A response rate of 96.5% was achieved. The study findings show that cooperative techniques bring about a positive shift in agrifood security and sustainable agriculture. Particularly, participants concurred that resource sharing among cooperative members increases farm productiveness and sustainability by 94.2% while improving access to credit and financial support by 91.5%. Moreover, 84.3% agreed that access to up-to-date information enhances the practice of sustainable agriculture, and 95.1% agreed that collective bargaining through cooperatives increases the prices of agricultural commodities. Regarding the application of advanced technologies in cooperative practices, 96.7% of the participants acknowledged that it improved farm efficiency. The cooperative model demonstrates how agricultural expansion may be achieved by collective bargaining, information sharing, resource sharing, and technological integration, while also considerably improving agrifood security and sustainability. These findings highlight the crucial importance of cooperatives in increasing the level of agricultural production, ensuring sustainability, and improving agrifood security in Greece. [ABSTRACT FROM AUTHOR]

As user-generated data diversifies, an increasing number of big data tasks now encompass unstructured data forms, including audio, imagery, and video content. The processing of these data often requires the support of GPU devices in the cluster. However, most of the existing cluster resource management frameworks lack effective decoupling of CPU resources and GPU resources, and the management granularity of GPU resources is too coarse, resulting in poor GPU sharing and low resource utilization. Given, for the inadequacy of the existing cluster resource management framework that cannot support batch stream integration and CPU-GPU resource scheduling, we design and implement a Hybrid Heterogeneous Resource Management (H-HRM) for CPU-GPU heterogeneous clusters. The resource queue binding mechanism on computing nodes provides flexible binding of CPU resources to GPU resources, which solves the problem that CPU resources and GPU resources in the cluster are difficult to decouple. According to the different uses of CPU or GPU as the main resource, a Hybrid Domain Resource Fairness (HDRF) model is proposed to realize the reasonable allocation of CPU resources and GPU resources. Through the queue stacking technology and the mechanism that multiple executors can run simultaneously on the queue, fine-grained sharing of GPU resources is realized and the utilization rate of GPU resources is improved. Finally, this paper realizes the docking of H-HRM and Spark programming framework and conducts real load tests, and after comparing with the performance of Mesos, it is proved that H-HRM can handle the mixed scenarios of batch jobs and stream processing jobs in the cluster, and the HDRF algorithm also greatly improves the utilization of the GPU. [ABSTRACT FROM AUTHOR]

This research models a medical resource-sharing problem with three powerful techniques in analytics: mixed-integer linear programming (MILP), deep q-learning (DQL), and double deep q-learning (DDQL). These models can be utilized by a group of collaborating entities in emergency situations to decide how they share resources and mitigate adverse effects on human lives. Due to the sudden spikes in demand, the allocation of healthcare resources becomes dynamic in nature. Medical resource management underwent an unprecedented level of difficulty in the modern history of our healthcare system because of the Coronavirus pandemic. At the beginning of the pandemic, we witnessed a severe shortage of ventilators in several countries including in the U.S. Followed by that, there was a severe shortage of Oxygen supply in treating patients who tested positive for the virus in India. Many lives were unnecessarily lost because of the lack of a resource-sharing framework to use in an adverse situation. When a hospital or region experiences sudden spikes in demand for resources, the key decision involves sending resources from other places. Especially, a swift optimal decision has to be made regarding who will send the resources and when will it be sent to the places of need. To tackle this problem, we developed three analytics models—MILP, DQL, and DDQL—based on the Institute for Health Metrics and Evaluation (IHME)'s public data of ventilator allocation. To the best of our knowledge, DQL and DDQL are introduced in this context for the first time. Our models can be used either to share critical resources between collaborators or transfer patients between the locations of the collaborators. We devise two policies for DQL and DDQL models while optimizing the parameters in them. We call these policies the normal policy and the just ship policy. The just ship policy promptly ships healthcare resources to save patients in other locations even at the risk of not meeting its own demand in the future. The normal policy allows saving resources at a location so that future demands are met at the location rather than satisfying the current demand at other locations. To demonstrate the performance of our models, we applied our models to the IHME's ventilator data and present the results for all fifty states in the U.S. We show how these models optimize ventilator allocations assuming that all the fifty states collaborate as a task force and implement the solution that emerges from the analytics. The experimental results show that the proposed models are effective in handling the resource sharing problem presented by Covid-19. This research provides a decision-making framework for resource allocation during any disease outbreak, such as, new variants of coronavirus and other outbreaks like monkey-pox. [ABSTRACT FROM AUTHOR]

Copyright of Cyber Security & Data Governance is the property of Editorial Office of Information Technology & Network Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The metaverse represents a transformative landscape for human interaction, promising an immersive digital ecosystem where users can create, share, and experience resources in novel ways. Within this context, the establishment of Beidou Navigation Satellite System (BDS) commons in the metaverse is an exciting prospect that could revolutionize knowledge sharing, governance, and sustainability. This paper explores the potential of the metaverse as a platform for building BDS commons, focusing on three key dimensions: resource sharing, collaborative governance, and sustainable development. We examine the current state of research, identify existing gaps, and propose directions for future inquiries to fully harness the potential of the metaverse for global resource sharing and collective action.

Understanding drivers of effort and catch is important for sustainable management of recreational fisheries. For the Pipi (Latona deltoides) fishery in South Australia as a case study, publicly available datasets on fisher demography, market forces and internet connectivity improved understanding of fisher motivations and capabilities, identified different historical periods in the fishery and addressed temporal gaps in effort and catch estimates from on‐site surveys. Most variables were correlated with recreational effort and catch estimates from on‐site surveys and principal component analysis identified 2013–2014, 2015–2018 and 2019–2022 as distinct periods in the Pipi fishery. Results corroborated studies and anecdotal information that suggested declining availability and higher prices of local, commercially caught Pipi, and reduced imports of bivalves from Asia that previously supplied the South Australian bait market. Reduced availability and higher prices of Pipi likely motivated recreational fishers to gather their own bait to increase catch over the years. Similarly, increased internet and smartphone access and increased numbers of utility vehicles aided recreational catch efficiency of Pipi. Effective management of recreationally harvested resources requires understanding of external processes that drive fisher motivations and capabilities, particularly for stocks that are shared among fisheries. The need for improved data on fisher behaviour for management of recreational fisheries can be addressed by leveraging external information from available datasets. We recommend that the temporal gap between surveys should be less than 5 years, supplemented by analysing behavioural information collected from fishers during interviews. [ABSTRACT FROM AUTHOR]

Thin-lipped mullet (Chelon ramada) is an important resource in the Mediterranean Sea and a candidate species for aquaculture. As microsatellite loci remain the markers of choice for the evaluation of breeding programmes or stock assessment, we hereby provide and share a resource of 3,883 species-specific microsatellite loci for this species, where they are currently lacking. This resource includes primer pairs useful for polymerase chain reaction (PCR) amplification. A subset of nine loci including di-, tri- and tetranucleotide loci with correct amplification success rates have been specifically tested under identical PCR conditions, opening up new avenues for research. [ABSTRACT FROM AUTHOR]

This article provides a short note on the lifecycle of the Yucca Giant-Skipper butterfly, which is a relatively understudied species. The researchers conducted a survey in Roosevelt County, New Mexico, to locate populations of this butterfly. They found that the adults were commonly found in two prairie habitats with an abundance of their hostplant, Yucca glauca. The caterpillars of this species bore into the plant crown and feed within the root, constructing a silken "tent" or "chimney" at the opening of the burrow. The researchers also observed signs of parasitism by dipteran pupae, indicating the presence of parasitoid species. The study raises questions about the life history of the Giant-Skippers and the potential impact of inbreeding depression. [Extracted from the article]

With resource sharing staff staying an average of 3-5 years, capturing policies and procedures to facilitate onboarding and strengthen institutional memory is key in building consistent workflows. Creating documentation was a multi-stage process executed over several years. Initially, the staff supervisor wrote office policies and assigned staff to write step-by-step guides for common workflows. These were kept in shared storage and evaluated and updated periodically. During pandemic closures, mind-mapping in MindManager aided gap analysis to prioritize areas of the workflow not yet documented. Most recently, this documentation moved into Microsoft Teams which both limits inadvertent alteration and facilitates searchability. [ABSTRACT FROM AUTHOR]

This study explores the experiences of academic developers engaged in creating a cross-institutional community, the Academic Development Collective (ADC). The ADC was formed to address inequities in resources for educational development across institutions in one U.S. state. Semi-structured interviews with 7 participants were used in a case study approach to examining how the ADC emerged from reacting to crises into a more proactive role addressing inequities in academic development. Findings revealed that participation in the ADC provided members with empathetic support and critical friends, and that cross-institutional collaboration enabled collective action. Members described how distributing expertise through initiatives drove systemic change, particularly in increasing equitable access to faculty development opportunities through resource-sharing. Engagement with the ADC enabled members to expand their capacities, share resources, and provide enhanced development opportunities for local faculty/staff. Recommendations include prioritizing diverse strengths, fostering collaborations beyond resource-sharing, balancing ameliorative and transformative strategies, and institutional investment in leadership and facilitation of collectives. This research illuminates how academic developers can build supportive professional communities to mitigate institutional inequities and transform existing structures through collective action. [ABSTRACT FROM AUTHOR]

Information security outsourcing has become an emerging trend in the operations of information security, but the relation between information assets of firms and attack modes of hackers have failed to be considered. Through building a game-theoretic model, this article analyzes security outsourcing of two firms who share their information resource with each other and are confronted with opportunistic attacks and targeted attacks. We find that in the case of security decisions in-house, the firms may obtain a lower expected cost and the hacker may derive a lower expected benefit under targeted attacks than under opportunistic attacks, even though targeted attacks are widely deemed to be more harmful to the firms. When outsourcing security operations to a MSSP (Managed Security Service Provider), we reveal that under targeted attacks the MSSP can reap a higher expected benefit and the hacker can still derive a lower expected benefit. Finally, we examine the effects of key security elements and find some interesting results. In particular, the MSSP may or may not benefit from the degree of resource sharing, and the hacker may suffer from its learning ability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai University / Shanghai Daxue Xuebao is the property of Journal of Shanghai University (Natural Sciences) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The psychological refractory period (PRP) effect occurs when two stimuli that require separate responses are presented sequentially, particularly with a short and variable time interval between them. Fatigue is a suboptimal psycho-physiological state that leads to changes in strategies. In recent years, numerous studies have investigated the effects of transcranial direct current stimulation (tDCS) on motor control. The present study aimed to investigate the effects of two tDCS methods, anodal and cathodal, on PRP in ten different conditions of stimulus-onset asynchronies (SOAs) under non-fatigue and mental fatigue conditions. The participants involved 39 male university students aged 19 to 25 years. In the pre-test, they were assessed using the PRP measurement tool under both non-fatigue and mental fatigue conditions. The mental fatigue was induced by a 30-min Stroop task. The test consisted of two stimuli with different SOAs (50, 75, 100, 150, 300, 400, 600, 900, 1200, and 1500 ms). The first was a visual stimulus with three choices (letters A, B, and C). After a random SOA, the second stimulus, a visual stimulus with three choices (colors red, yellow, and blue), was presented. Subsequently, participants were randomly assigned to the anodal, cathodal, and sham stimulation groups and underwent four consecutive sessions of tDCS stimulation. In the anodal and cathodal stimulation groups, 20 min of tDCS stimulation were applied to the PLPFC area in each session, while in the sham group, the stimulation was artificially applied. All participants were assessed using the same measurement tools as in the pre-test phase, in a post-test phase one day after the last stimulation session, and in a follow-up phase four days after that. Inferential statistics include mixed ANOVA, one-way ANOVA, independent, and dependent t-tests. The findings indicated that the response time to the second stimulus was longer at lower SOAs. However, there was no significant difference between the groups in this regard. Additionally, there was no significant difference in response time to the second stimulus between the fatigue and non-fatigue conditions, or between the groups. Therefore, tDCS had no significant effect. There was a significant difference between mental fatigue and non-fatigue conditions in the psychological refractory period. Moreover, at lower SOAs, the PRP was longer than at higher SOAs. In conditions of fatigue, the active stimulation groups (anodal and cathodal) performed better than the sham stimulation group at higher SOAs. Considering the difference in response to both stimuli at different SOAs, some central aspects of the response can be simultaneously parallel. Fatigue also affects parallel processing. This study supports the response integration phenomenon in PRP, which predicts that there will be an increase in response time to the first stimulus as the interval between the presentation of the two stimuli increases. This finding contradicts the bottleneck model. In this study, the effectiveness of cathodal and anodal tDCS on response time to the second stimulus and PRP was found to be very small. [ABSTRACT FROM AUTHOR]

Participating in megaproject experimental tasks would significantly improve the laboratories' industry influence and future competitiveness. Thus, this paper introduces the long-term reputation effects of the incentive model of an experimental resource-sharing platform for megaprojects, which could motivate them to consider future benefits and improve their current efforts. The aim is to incentivize laboratories' resourcesharing behavior more effectively and to increase the amount of resources shared by these laboratories on the platform, thus guaranteeing the long-term sustainability of the platform. It constructs the incentive model by combining dual implicit and explicit incentive mechanisms. It analyses the incentive mechanism of a reputation effect on laboratories compared with the pure explicit mechanism so that the primary conditions for reputation incentives can be obtained to achieve Pareto improvement. Finally, the proposed method is validated in combination with data simulation. The results show that although dual implicit and explicit incentive mechanisms could reduce the information asymmetry between the two sides and increase the efforts of laboratories and the benefits of the platform, the platform should not blindly increase the intensity of these incentives and need to consider the influence of the subsidies of these laboratories' upfront inputs, the degree of sharing and their informatization capabilities. [ABSTRACT FROM AUTHOR]

This research was conducted in a transmigrant settlement in Wasile District, East Halmahera Regency, North Maluku Province, where the initial placement included ethnic groups from Banyuwangi and Banyumas. The study aims to analyze the support of social capital for the adaptability of transmigrants. A post-positivist paradigm was employed in this research. Data were collected through observation, participatory observation, in-depth interviews, focus group discussions, and document reviews. The informants consisted of 6 key informants and 14 supporting informants. The key informants included two representatives each from the Banyuwangi and Banyumas transmigrant groups placed in 1983, a Field Extension Officer (PPL), the Wasile District Head, the Village Head of Bumi Restu, and the Village Head of Mekar Sari. The supporting informants were those recommended by the key informants. The informants were selected purposively, followed by a snowball sampling technique. The data were analyzed qualitatively and descriptively manner. The findings indicate that the social capital support possessed by these two transmigrant groups significantly enhanced their adaptability, enabling them to survive and thrive. Furthermore, the implications of these findings are substantial. Strong social capital among the transmigrants can facilitate knowledge exchange, resource sharing, and collective action, essential for establishing and maintaining effective agribusiness practices. This robust support network enables transmigrants to overcome agricultural production, market access, and economic integration challenges. Consequently, the enhanced adaptability fostered by social capital improves their resilience and contributes to the overall success and sustainability of their agribusiness ventures, promoting community development and economic growth in the region.

Cloud manufacturing (CMfg) aims to realise the sharing of manufacturing resources amongst different stakeholders. Resource-sharing strategies of suppliers are essential in achieving this aim. However, current studies on this topic rarely focus on the sharing of management rights over manufacturing resources. To fill this research gap, this study investigates three resource-sharing strategies: independently, as an alliance and by cooperating with a cloud platform operator. This study explores the effects of these different strategies on meeting client requirements in CMfg. The interactions between the operator and suppliers are modelled as a two-stage Stackelberg game that contains a simultaneous subgame. The equilibrium results indicate that players achieve a lower system profit when suppliers share as an alliance rather than independently, which is why the cloud platform operator strongly opposes it. The extended analysis indicates that considering multiple suppliers complicates the allocation of tasks and profits. Low-cost suppliers have significant advantages in terms of tasks and profits when considering different marginal costs. These findings provide insights for suppliers to select appropriate resource-sharing strategies in CMfg. [ABSTRACT FROM AUTHOR]

The MOBIUS library consortium has been the leading academic library consortium in Missouri for over two decades. Building on earlier collaborative work, seed funding from the state created the consortium in 1998 and MOBIUS became a reality. MOBIUS not only runs a shared integrated library system for most of the academic libraries in Missouri but also implemented a union catalog tying libraries together for resource sharing. Over time MOBIUS has expanded membership out-of-state into Oklahoma, Iowa, Kansas and Texas and as of 2022 MOBIUS has 80 library members with 232 branches. MOBIUS has also been active in licensing of e-resources for libraries, supporting member libraries in their use of open educational resources (OER), training and education, and running open-source software. The MOBIUS Open Source Services (MOSS) program is a service for members hosting software such as ArchivesSpace, Omeka-S, SubjectsPlus, and Evergreen (an open-source ILS). MOBIUS actively works with other consortia around the United States. [ABSTRACT FROM AUTHOR]

The field of business management involves a large amount of data and information sources, including market data, customer data, supply chain data, etc. In order to quantify and analyze different resources, help enterprises better plan and allocate resources, and improve resource utilization efficiency, a clustering analysis based digital resource integration algorithm for business management is studied. Build a business management digital resource integration framework, including data layer, integration layer, and storage layer, to integrate and store data from different sources of business management databases, thereby facilitating unified management and utilization of digital resources by enterprises. The data layer collects data from different business management databases and stores it in the database according to different sources; The integration layer preprocesses the collected data, simply fixes errors and missing information in the data, and improves data quality. Adopting a feature extraction method based on the projection direction uncorrelation strategy of the labeled power set conversion method, the useful feature information of digital resources in enterprise management can be effectively extracted; Based on the two-step clustering analysis method, business management digital resources are clustered according to similar characteristics to complete the classification and integration of business management digital resources, and improve the efficiency of resource utilization; The storage layer adopts the Security Information Diffusion Algorithm (IDA) storage model to store integrated and classified digital resources managed by enterprises, ensuring data security and effectively preventing data leakage and illegal access. The experimental results show that the digital resource structure of business management integrated by this algorithm is clear, with a data redundancy of less than 8% and a difference of less than 11%. The time consumption for data integration is less than 2.11 minutes, indicating good resource integration ability. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the pursuit of Universal Health Coverage (UHC), developing countries with limited resources face significant hurdles. Traditional top-down approaches, spearheaded by governments, often entail lengthy planning periods and substantial costs to reach underserved communities. This paper proposes a bottom-up, cost-effective, and preventive approach aimed at empowering local human resources and using advanced technology. We call it the Micro Healthcare Entrepreneurship (MHE) model. The MHE model comprises four primary components: (1) utilization of local human resources, (2) disruptive healthcare technology, (3) continuous training, and (4) available funds. Extensive testing of the digital health and social business elements across diverse contexts underscores their efficacy. Furthermore, the viability of social business funds has been established. To solicit feedback and refine the MHE concept, three workshops, conducted in phases, engaged 60 community healthcare service providers. This paper elucidates both the potential advantages and the challenges inherent in implementing the MHE model. By shifting the paradigm toward grassroots empowerment and leveraging existing community assets, this approach offers promise in advancing healthcare accessibility and sustainability in resource-constrained settings to achieve UHC. [ABSTRACT FROM AUTHOR]

Shared resources are common among supply chain partners and also occur in multiple linked stages of an internal network. The sharing of these resources impacts the organization's profits. This study is focused on the potential benefits of resource sharing on a three-stage network system and on the profit improvement allocation. Previous treatments concentrate on defining optimal proportions to allocate resources and disregard the impacts of allocations to promote cooperation and are limited to static evaluations. Data Envelopment Analysis performs the decision-making units (DMUs) efficiency measurement. Methodological advances have resulted in models that analyze their internal structure and temporal impacts on efficiency. We propose an integrated cooperative game and dynamic network DEA that considers known quantities of resources used in each stage and the time effects to optimize the system's profit. Each DMU stage is a player, and we investigate performance before and after resource sharing. Using Shapley value and Nucleolus, it is possible to allocate the benefits obtained based on the marginal contributions of each stage, providing incentives to motivate and maintain cooperation. A numerical example is used to illustrate the method. The results confirm the identification of inefficient DMUs and that sharing resources allows for profit increase for all of them. [ABSTRACT FROM AUTHOR]

COVID‐19 outbreaks in local communities can result in a drastic surge in demand for scarce resources such as mechanical ventilators. To deal with such demand surges, many hospitals (1) purchased large quantities of mechanical ventilators, and (2) canceled/postponed elective procedures to preserve care capacity for COVID‐19 patients. These measures resulted in a substantial financial burden to the hospitals and poor outcomes for non‐COVID‐19 patients. Given that COVID‐19 transmits at different rates across various regions, there is an opportunity to share portable healthcare resources to mitigate capacity shortages triggered by local outbreaks with fewer total resources. This paper develops a novel data‐driven adaptive robust simulation‐based optimization (DARSO) methodology for optimal allocation and relocation of mechanical ventilators over different states and regions. Our main methodological contributions lie in a new policy‐guided approach and an efficient algorithmic framework that mitigates critical limitations of current robust and stochastic models and make resource‐sharing decisions implementable in real‐time. In collaboration with epidemiologists and infectious disease doctors, we give proof of concept for the DARSO methodology through a case study of sharing ventilators among regions in Ohio and Michigan. The results suggest that our optimal policy could satisfy ventilator demand during the first pandemic's peak in Ohio and Michigan with 14% (limited sharing) to 63% (full sharing) fewer ventilators compared to a no sharing strategy (status quo), thereby allowing hospitals to preserve more elective procedures. Furthermore, we demonstrate that sharing unused ventilators (rather than purchasing new machines) can result in 5% (limited sharing) to 44% (full sharing) lower expenditure, compared to no sharing, considering the transshipment and new ventilator costs. [ABSTRACT FROM AUTHOR]

Participating in megaproject experimental tasks would significantly improve the laboratories’ industry influence and future competitiveness. Thus, this paper introduces the long-term reputation effects of the incentive model of an experimental resource-sharing platform for megaprojects, which could motivate them to consider future benefits and improve their current efforts. The aim is to incentivize laboratories’ resource-sharing behavior more effectively and to increase the amount of resources shared by these laboratories on the platform, thus guaranteeing the long-term sustainability of the platform. It constructs the incentive model by combining dual implicit and explicit incentive mechanisms. It analyses the incentive mechanism of a reputation effect on laboratories compared with the pure explicit mechanism so that the primary conditions for reputation incentives can be obtained to achieve Pareto improvement. Finally, the proposed method is validated in combination with data simulation. The results show that although dual implicit and explicit incentive mechanisms could reduce the information asymmetry between the two sides and increase the efforts of laboratories and the benefits of the platform, the platform should not blindly increase the intensity of these incentives and need to consider the influence of the subsidies of these laboratories’ upfront inputs, the degree of sharing and their informatization capabilities.

Virtualization plays a crucial role in successfully integrating multiple real-time applications on a single platform. Through virtualization, different applications can run in independent virtual machines, isolated from each other to prevent mutual interference. This paper considers partitioned fixed priority (P-FP) scheduling for tasks and servers on the multi-core virtualization platform with non-preemptive resource sharing. The solution for P-FP scheduling on multi-core virtualization environments typically uses vMPCP, an extension protocol of the well-known Multiprocessor Priority Ceiling Protocol (MPCP), to address the problem of resource sharing among real-time application tasks. However, the existing analysis of Worst-Case Blocking Time (WCBT) for the P-FP+vMPCP scheduling tends to be overly conservative, resulting in many schedulable task sets being incorrectly classified as unschedulable. Consequently, it leads to wasted system resources and degraded performance. To mitigate this issue and reduce the pessimism of existing analysis, we propose an improved WCBT analysis. This analysis bounds the maximum blocking time that tasks experience when each job from the same task requires to access the same type of non-preemptive global resource multiple times. As a result, it enhances the accuracy over prior work and obtains more precise Worst-Case Response Time (WCRT) for tasks. In our experiments, the WCRT-based schedulability test is adopted to evaluate the schedulability of tasks. Additionally, we do not consider additional scheduling costs, as no online decisions are required. Experimental results demonstrate that our proposed method outperforms the latest advanced methods in terms of the schedulability rate of tasks. Specifically, the schedulable task sets are increased by approximately 47.7% on average.

The shift towards agile microservice architecture has enabled significant benefits for IT companies but has also resulted in increased complexity for Cloud orchestration tools. Traditional tools were designed for centralized data centers and are ineffective for locating microservices in geographically-distributed edge-like infrastructures. This paper presents Phare, a decentralized scheduling algorithm designed to optimize the placement of microservices by satisfying their computing and communication demands while minimizing deployment costs. Phare employs a heuristic-based approach to solve the NP-Hard scheduling problem, prioritizing the microservices with the more stringent requirements and placing them on the most convenient computing facilities, based on the concept of affinity, contributing to the field by providing a more holistic approach to resource scheduling in edge computing. We validate our approach against Firmament, the state-of-the-art workload scheduling algorithm for component-based applications, on simulated edge infrastructures with hundreds of clusters. Phare achieves up to a $10\times $ reduction in terms of deployment costs compared to Firmament while providing a much lower scheduling latency.