Reallocation Of Resources Research Articles

Critical Care Nursing Response to the Maui Wildfire Disaster: Narrative Review and Case Study.

Climate change has increased the frequency and severity of natural disasters, including the 2023 wildfires in Maui, Hawai'i. The no-notice disaster affected hospital operations at the sole acute care hospital that serves the community, requiring immediate interventions and reallocation of resources. The purpose of this article is to explore the role that critical care nurses play in responding to wildfires. Literature related to the nursing role in managing wildfire injuries and the events on Maui are explored and a case study presented. Results are organized into themes: environmental limitations, disaster response and code triage activation, no-notice preparation for critical care nurses, preparation to increase patient capacity and maintain patient safety standards, hospital staffing and staff affected by the disaster, management of patient care and hospital system operations, and disaster medical tent. Preparation for no-notice events requires critical care nurse involvement to effectively facilitate care for patients affected by disasters.

Impact of Macroeconomic Shocks on Financial Performance and Risk Management: A Case Study of LPP SA During the COVID-19 Pandemic and the Ukraine War

This study analyses the impact of two major macroeconomic shocks—the COVID-19 pandemic and the Ukraine war—on the financial stability of LPP SA, a leading apparel company in Poland and Central and Eastern Europe. This research uses the coefficient of variation to assess changes in financial volatility and evaluates the effectiveness of LPP SA’s risk management strategies. The findings reveal that, while the COVID-19 pandemic had a more destabilising effect on the company’s performance, the Ukraine war’s impact was mitigated by strategic diversification and resource reallocation. The study’s implications are relevant for risk management practices in the apparel industry and other consumer-driven sectors.

Impact of the COVID-19 pandemic on direct medical costs of acute coronary syndrome admissions in Yogyakarta, Indonesia

The number of admissions, therapeutic management, and clinical results of acute coronary syndrome (ACS) have been extensively reported. However, the economic impact of ACS therapy has been ignored. This study examined the effect of the COVID-19 pandemic on direct medical costs for ACS hospitalizations in Yogyakarta, Indonesia. A retrospective study of patients with ACS admitted to one of three hospitals during March to August in 2019, 2020, and 2021 was conducted. Direct medical costs from a provider’s perspective were estimated using the charges. All costs were reported in Indonesian Rupiah (IDR) at a 2021 value. Multiple linear regression analysis was used to evaluate the impact of the pandemic on total direct medical costs. The total direct medical costs associated with ACS admission per patient during the pandemic period was approximately 40% higher than that during the pre-COVID period (28.41 vs. 20.33 million IDR or 1976.90 vs. 1414.65 USD). A substantial impact of the COVID-19 pandemic on total direct medical costs still remained after adjusting the ACS types, hospital types, length of stay, percutaneous coronary intervention, in-hospital mortality, and delay time of onset to first medical contact. Given the limited health budget, reallocation of health care resources must be prioritized to maintain the provision of essential health care for those who timely treatment is crucial.

Structural Change, Growth and the Increasing Service Trade in Low and Middle Income Countries

This paper explains the increasing service export in low and middle-income countries of the world and tries to relate it with structural change and pattern of growth. The authors have constructed a theoretical model to derive hypotheses and estimated empirical results from panel regressions based on data from 34 low and middle-income countries. The theoretical results show that productivity differences caused by endogenous technological innovations and human capital formation lead to a reallocation of resources and structural change. As a result, the relative prices of the goods change. This paper shows that the growing service export is the reflection of industrial backwardness due to lack of capital, technological innovation and infrastructure. The results of panel regression also reveal that service sector-led growth and investment in human capital formation have a significant effect on service export while expenditure on R & D is so low in such countries that it has no effect on per capita income, industrial growth and service export. As investment in human capital formation is high and R&D expenditure is low, the developing countries experience unbalanced growth with an increasing share of services in GDP and export.

Sulfur redirects carbon metabolism to optimize nitrogen utilization and promote andrographolide biosynthesis in Andrographis paniculata seedlings

Sulfur (S) is an important mineral nutrient element that improves plant growth and secondary metabolism. S affects the biosynthesis of andrographolide in medicinal plant Androgaphis paniculata by regulating nitrogen (N) metabolism. However, its specific role in N utilization and the connection with andrographolide biosynthesis have not yet been thoroughly understood. Here, a soilless cultivation experiment with low S (LS, 0.1 mM) and high S (HS, 2.4 mM) was conducted to investigate how S influences carbon (C) metabolism and N utilization to promote andographolide biosynthesis in Andrographis paniculata. The results showed that HS significantly increased plant biomass and N use efficiency (NUE), accompanying with remarkable enhanced andrographolide content. HS promoted the expression of photosynthetic genes, and redirected C metabolism towards to sugars accumulation by enhancing the activities of NAD-dependent glutamate dehydrogenase (NAD-GDH), malic enzyme (ME) and phosphoenolpyruvate carboxykinase (PEPCK) (P < 0.05). On the other hand, HS reduced N and S assimilation, and stimulated a greater N allocation in photosynthesis. Accordingly, NUE was increased and andrographolided biosynthesis could profit from the shift of C resource reallocation. Additionally, the significantly increased activities of ME, glucose 6-phosphate dehydrogenase (G6PDH) and isocitrate dehydrogenase (ICDH) provided reductants for secondary metabolism. HS also considerably upregulated the expression of genes in andrographolide biosynthetic pathway, including ApDXS, ApDXR, ApHDS and ApHDR in the MEP pathway, and ApGGPS. Transcription factors in the families of MYB, WRKY, ERF and bHLH, and plant hormones ABA and JA were in response to HS. Our results revealed that S synergistically promotes NUE and andrographolide biosynthesis via remodeling of C metabolism in A. paniculata.

Scaling and Dynamic Resource Reallocation in NFV

Network Function Virtualization (NFV) has brought incredible experiences for Internet users and network operators. NFV enables the implementation of Virtualized Network Functions (VNFs) as software running in High Volume Servers (HVSs) to execute a Service Function Chain (SFC) to satisfy service demands of Internet users. During the execution of SFCs, VNFs and Virtual Links (VLs) tend to change their resource requirements due to the dynamic nature of the end user's demands. In this paper, we focus on dynamic resource allocation to the elements of SFC throughout the SFC process to adapt to the elasticity in demand from users by providing an overall picture of NFV and the scaling problem of SFC. We then review and analyze related studies on dynamic resource allocation of NFV systems during SFC operation and analyze the results of these projects. The most recent works are also classified based on several criteria to highlight their approaches, achievements, and also shortcomings. Finally, we introduce some research directions to deal with the scaling problem during SFC operation that needs more attention from researchers to inspire future work in the elastic operation of NFV-enabled systems.

Impact of the US-China Trade War on Bystander Countries

Abstract: This paper evaluates the impact of US-China trade war on bystander countries (untargeted by additional tariffs) by analysis of changes in import value of 9 taxed products from China and other 11 bystanders in the US from 2018 to 2019. The paper reveal incomplete substitution of Chinese imports on average after adoption of tariffs targeting China. The difference in value between decline of imports from China and aggregated growth of imports from other 11 countries are termed the gaps. The gaps are explained in four aspects: a) supply elasticity; b) heterogeneity across countries; c) global value chain; d) increased use of domestic products. In beneficiary-level, bystanders are divided into large beneficiaries, small beneficiaries and losers. This paper provides suggestions in firm-level, product-level and country-level to help bystanders take advantage of the trade war, which involve efficient reallocation of resources and transformations. Improved positions of countries except for the US and China contribute to both global economic growth and development and multi-polarization in the world.

The impact of covid-19 pandemic on syphilis notifications in northeast Brazil

This study aims to evaluate the impact of the COVID-19 pandemic on the number of syphilis notifications (acquired, during pregnancy and congenital) in northeastern Brazil. An ecological study was carried out using the database provided by the Ministry of Health through the Department of Informatics of the SUS (DATASUS). The monthly numbers of notifications of acquired, gestational and congenital syphilis were organized on the Google Sheets online platform and the data were statistically analyzed, using the Wilcoxon test, for the pandemic (Jan/2020-Jun/2021) and pre pandemic periods (Jan/2018-Dec/2019), with a statistical significance of 5%. There was a reduction in the number of notifications of total cases of syphilis in the Northeast in 2020 and in 2021 when compared to the pre-pandemic period (p &lt; 0.001 and p = 0.031, respectively). This reduction represents a drop of 32.38% in 2020 and 28.84% in 2021. Regarding the states, there was no statistical significance in the number of notifications for Sergipe in 2020 (p = 0.638), Ceará in 2021 (p = 0.156) and Rio Grande do Norte in 2021 (p = 0.219) compared to 2018 and 2019. In addition, it was observed that in Sergipe there was an increase of 53.96% in notifications in 2021 compared to the same period (p = 0.031). These variations may be a consequence of social distancing, the reallocation of resources during the pandemic and socioeconomic issues, or even all of these factors combined.

Heuristic Optimal Scheduling for Road Traffic Incident Detection Under Computational Constraints.

The intelligent monitoring of road surveillance videos is a crucial tool for detecting and predicting traffic anomalies, swiftly identifying road safety risks, rapidly addressing potential hazards, and preventing accidents or secondary incidents. With the vast number of surveillance cameras in operation, conducting traditional real-time video analysis across all cameras at once requires substantial computational resources. Alternatively, methods that employ periodic camera patrol analysis frequently overlook a significant number of anomalous traffic events, thereby hindering the effectiveness of traffic event detection. To overcome these challenges, this paper introduces a heuristic optimal scheduling approach designed to enhance traffic event detection efficiency while operating within limited computational resources. This method leverages historical data and prior knowledge to compute a weighted event feature value for each camera, providing a quantitative measure of its detection efficiency. To optimize resource allocation, a cyclic elimination mechanism is implemented to exclude low-performing cameras, enabling the dynamic reallocation of resources to higher-performing cameras, thereby enhancing overall detection performance. Finally, the effectiveness of the proposed method is validated through a case study conducted in a representative region of a major metropolitan city in China. The results revealed a substantial improvement in traffic event detection efficiency, with increases of 40%, 28%, 17%, and 28% across different time periods when compared to the pre-optimized state. Furthermore, the proposed method outperformed existing resource scheduling algorithms in terms of average load degree, load balance degree, and higher computational resource utilization. By avoiding the common issues of resource wastage and insufficiency often found in static allocation models, this approach offers greater flexibility and adaptability in computational resource scheduling, thereby effectively addressing the practical demands of traffic anomaly detection and early warning systems.

AI-Driven Scaling of Sustainable Startups: Business Models and Environmental Impact

With fast growth in sustainable startups at variance with profitability, the likelihood of high profitability contrasted with minimal environmental impact becomes a great challenge and opportunity. In this article, the role of AI in scaling through innovative business models to meet sustainability goals is investigated. The latest development in optimized operating efficiency, lesser resource consumption, and improved scalability has seen AI use go unexplored in business models designed particularly for environmental sustainability goals. This paper addresses how AI-enabled business model innovation can facilitate scaling up of sustainable start-ups in renewable energy, waste management, and circular economy practices. In addition, resource reallocation under such a scenario comes with a double dividend: it brings better economic growth alongside lower ecological damage, while reduction in AI's adverse environmental impact arises as a by-product. Case studies are expected to summarize the complexity in practice and limitations of AI for sustainable business growth. This study, therefore, provides an answer that contributes to understanding how startups may leverage AI to drive not only economic value but also create environmental value, thus providing the much-needed roadmap for future research in a rapidly changing field.

A multi-objective optimal control approach to motor strategy changes in older people with mild cognitive impairment during obstacle crossing.

Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI. Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05. Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure. MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains.

Research on Triplex Redundant Flight Control System Based on M1394B Bus

In the modern aviation field, flight control systems’ reliability and safety are paramount. This paper presents a triplex redundant flight control system based on the M1394B bus and designs several key algorithms to enhance system performance. Firstly, a triplex redundant flight control system with a redundant bus structure is constructed based on the characteristics of the M1394B bus. Secondly, a periodic synchronization algorithm with automatic adjustment capabilities is designed to achieve periodic synchronization among the Vehicle Management Computers. An improved voting algorithm based on a sliding window is proposed to enhance the decision-making accuracy and reliability of the control commands output by the flight control system. Additionally, a system reconstruction algorithm is designed to promptly identify and isolate faults, enabling the recovery and reallocation of system resources. Finally, experiments validate the effectiveness of the synchronization algorithm, voting algorithm, and system reconstruction algorithm. The results indicate that the system can effectively address practical engineering challenges and significantly improve reliability and stability. This research provides an essential theoretical foundation and practical reference for the design of future flight control systems for unmanned aerial vehicles and aircraft, holding significant relevance to application.

Plasmid-encoded phosphatase RapP enhances cell growth in non-domesticated Bacillus subtilis strains.

The trade-off between rapid growth and other important physiological traits (e.g., survival and adaptability) poses a fundamental challenge for microbes to achieve fitness maximization. Studies on Bacillus subtilis biology often use strains derived after a process of lab 'domestication' from an ancestral strain known as Marburg strain. The domestication process led to loss of a large plasmid (pBS32) encoding a phosphatase (RapP) that dephosphorylates the Spo0F protein and thus regulates biofilm formation and sporulation. Here, we show that plasmid pBS32, and more specifically rapP, enhance growth rates by preventing premature expression of the Spo0F-Spo0A-mediated adaptive response during exponential phase. This results in reallocation of proteome resources towards biosynthetic, growth-promoting pathways without compromising long-term fitness during stationary phase. Thus, RapP helps B. subtilis to constrain physiological trade-offs and economize cellular resources for fitness improvement.

Fiscal consolidation plans with underground economy

AbstractFiscal consolidation literature often neglects that there are economies characterized by sizable underground sectors, with their mechanisms of response to fiscal policy shocks. Therefore, reliable analyses of fiscal consolidation plans call for the decomposition of Gross Domestic Product in its regular and hidden components. We investigate fiscal consolidation effects in the context of tax evasion for the Italian economy. Results show that a temporary cut in public spending associated with a permanent drop in tax rate yet entails tax evasion reduction. The main underlying mechanism is the strong responsiveness of the underground sector, implying a reallocation of resources toward the regular sector.

From Shock to Adaptation: Evaluating the Mechanisms of Trade Friction on Firms’ Total Factor Productivity Through the Lens of Digital Transformation

Against the backdrop of frequent global trade conflicts and accelerated competition in the digital economy, we investigated how trade friction shocks affect firms’ total factor productivity (TFP), with a focus on the role of digital transformation. We employed a statistical analysis method based on the multi-period difference-in-differences model with anti-dumping and countervailing measures as quasi-natural experiments to analyze firm-level panel data for Chinese exporters from 2003 to 2016. The results indicate that trade frictions compel export firms to enhance their TFP, while digital transformation further promotes this growth. This main conclusion still holds after a series of tests such as parallel trend checks, placebo tests, and variations in primary variables. A mechanism analysis shows that, in response to trade friction shocks, firms aiming to boost productivity have strategically reallocated internal resources by increasing exports of alternative products and expanding into overseas markets rather than solely relying on innovation. Additionally, digital transformation mitigates the negative effects of trade friction on firm innovation and facilitates faster internal resource reallocation during such challenges. A heterogeneity analysis reveals that digital transformation proves more beneficial for firms that are multi-product, non-state-owned, engaged in general trade, and operating in highly competitive industries. This paper contributes to the understanding of trade friction and productivity at the micro level, offering valuable insights into digital transformation strategies for firms navigating these challenges.

Leveraging single-dose human papillomavirus vaccination dose-efficiency to attain cervical cancer elimination in resource-constrained settings.

In low- and middle-income countries, resource constraints remain a critical factor limiting access to cervical cancer preventive measures. The option of single-dose immunization could help improve access to human papillomavirus vaccination and attain cervical cancer elimination. With simulation models adapted to country-specific data and scenarios for single-dose protection derived from International Agency for Research on Cancer India vaccine trial data, we estimated the expected impact of single-dose vaccination in India, Rwanda, and Brazil, three countries with varying profiles of cervical cancer risk and vaccination timelines. In combination with single-dose vaccination, we explored different resource reallocation strategies based on dose efficiency, elimination attainment, and cervical cancer cases prevented, with the existing 2-dose program as a comparator. Assuming lifelong single-dose protection, switching from 2-dose to 1-dose vaccination and reallocating resources to female catch-up could prevent 467-1336, 94-194, and 15-207 additional cervical cancer cases (per 100 000 women born) in cohorts aged 11-30 years in India, Rwanda, and Brazil, respectively. Resource reallocation to improve the current routine coverage could help eliminate cervical cancer in India and across all Brazilian states but not in Rwanda. For each country, we found a dose-efficient reallocation strategy (or a combination of strategies) together with 1-dose vaccination that could prevent more cervical cancers vs 2-dose vaccination, even in the worst-case scenario of single-dose protection. Adopting single-dose vaccination with resource reallocation is a resource-efficient approach to enhance progress toward cervical cancer elimination. The overall impact of vaccination can be maximized by fine-tuning resource reallocation to a country's needs.

Impact of fleQ Deficiency on Resource Allocation and Heterologous Gene Expression in Pseudomonas putida Across Various Growth Media.

Pseudomonas putida is widely used in industrial applications, including the recombinant proteins production, because of its natural advantageous properties. In this study, the gene encoding FleQ, the primary regulator of flagellar synthesis, was deleted to construct a new non-motile P. putida KT2440-derived strain (ΔfleQ). The non-motile cells showed reduced biofilm formation and enhanced expression of a heterologous gene in nutrient-rich media compared with the wild-type (WT) strain, attributed to the reallocation of cellular resources from flagellar synthesis and cellular motility. Additionally, the ΔfleQ strain exhibited enhanced tolerance to chloramphenicol, indicating higher ribosome production, confirmed by a higher RNA/protein ratio relative to the WT. While the WT strain showed decreased growth and a three-fold increase in reporter gene activity in minimal media, the ΔfleQ strain maintained consistent reporter gene expression and exhibited a relatively higher growth rate. This suggests that the FleQ is involved in modulating proteome allocation based on nutrient quality. The removal of FleQ allows for more flexible resource allocation, creating a chassis strain with nutrient quality-independent gene expression capacity, which could be valuable in industrial applications where consistent output is essential.

Assessing economic resilience in aviation system disruptions based on CGE model

This study employs a Computable General Equilibrium (CGE) model to assess the economic resilience of Shanghai's aviation system disruption caused by Typhoon Lekima. The research integrates advanced modules for disaster shock and economic resilience, providing a comprehensive framework to evaluate economic resilience tactics and their effectiveness. Specially, the disaster shock module is designed to account for perturbations in both commodity flow and passenger flow, and the economic resilience module incorporates both inherent and adaptive resilience tactics. The results show the following. First, Typhoon Lekima significantly impacted Shanghai's aviation system, resulting in substantial GDP losses of 0.52 %, decreased government revenue by 0.29 %, and reduced total investment in the base scenario. Second, the implementation of resilience tactics, both inherent and adaptive, mitigated these losses. Inherent resilience reduced potential GDP losses by 0.29 % in the Shanghai region. Adaptive resilience tactics, such as flight rescheduling, flight diversion, and effective management processes, though initially suppressing GDP due to resource reallocation towards recovery efforts, ultimately enhanced the system's overall resilience. Third, traffic disruptions have a significant hindering effect on regional trade activities, especially in the regional output and value added. The industries most sensitive to traffic disruptions were transportation, storage, and postal service, and wholesale and retail trade. These findings provide valuable insights for policymakers and stakeholders in the aviation industry, highlighting the necessity of resilience tactics to mitigate the economic impacts of future disruptions.

Streaming and Elastic Traffic Service in 5G-Sliced Wireless Networks and Mutual Utilization of Guaranteed Resource Units

Researchers of 5G-sliced Wireless Networks are faced with the task of achieving, at the same time, (i) mandatory isolation among network slices and (ii) the effective utilization of resource at Fifth Generation Base Station (gNB). This article proposes the second version of the Preemption-based service Prioritization (PP2) scheme that merges the capabilities of the classical Resource Reservation (RR) and Service Prioritization (SP) schemes and realizes the coexistence of non-TCP streaming and TCP elastic traffic at gNB. Analytical methods are given for Dynamic Resource Sharing (DRS) and Dynamic Resource Reallocation (DRR) with data rate reduction and service preemption. As main results, under some baseline scenario, the PP2 scheme, in comparison with RR, does increase the admission probability up to 99.999% at the system while ensuring 100% in system capacity utilization.

6.Y.1. Defining, measuring, and reducing low-value care in Europe - proposing a new definition and framework

Abstract The EU Expert Group on Health Systems Performance Assessment (HSPA) selected value-based healthcare, with a focus on low-value care, as the work topic for 2023-2024. Against the backdrop of increasing healthcare expenditures and the overall aim to deliver high quality and efficient healthcare, efforts to reduce waste and inefficiencies have long been emerging in health systems worldwide. Value-based healthcare shifts the focus towards improving patient outcomes; the concept of low-value care in particular aims to identify health services that provide little or no health benefits but expose patients to potential harm. The COVID-19 pandemic clearly demonstrated that value-based healthcare is a prerequisite for high-performing health systems and the need to steer resource allocation to those services that maintain or improve health. The reduction in certain elective services observed during the pandemic (e.g. tonsillectomies) indicates that there may be areas for potential dis-investment and reallocation of resources to higher-value care. The pandemic has thereby emphasized the need for identifying and systematizing measurable efforts directed at reducing low-value care. Tackling low-value care can contribute to alleviating health workforce constraints by ensuring that efforts are focused where they are most beneficial, and not on unnecessary services. Engaging and educating the health workforce about low-value care and how to reduce it is a key measure in this direction. What is more, there is increasing awareness about the health sector’s considerable environmental footprint. Reducing low-value care would contribute to less greenhouse gas emissions, energy consumption and air pollution from the delivery of health services. Despite intensified efforts to address waste and inefficiencies in healthcare in the last decade, the ability of health systems in Europe to identify and reduce low-value care varies. Through the Expert Group’s work, a new comprehensive definition was proposed and a framework to distinguish different types of low-value care was developed as a basis for identifying and tackling low-value care in EU Member States. Indicators to measure low-value care as well as measures to reduce it were collected. This workshop aims to present the findings of the Expert Group´s work on low-value care and to discuss them with conference participants to both raise awareness and identify priority elements for future activities. After a brief introduction on the definition, framework, obstacles and solutions, the panelists will share their views and experiences, followed by a facilitated discussion with the audience. Key messages • A comprehensive definition of low-value care and an accompanying framework for categorizing and identifying low-value care is proposed. • Country experiences with indicators to measure low-value care and strategies to reduce it, as well as related methodological obstacles, offer substantial opportunities for cross-country learning.