Supply Capacity Research Articles

Towards contextualized complex systems approaches to scaling-up hepatitis B birth-dose vaccination in the African region: a qualitative systematic review.

Despite the longstanding implementation of universal hepatitis B infant vaccination programs, the World Health Organization African region (WHO AFRO) maintains the highest prevalence (2.5%) of chronic hepatitis B virus (HBV) infection among children ≤5 years of age. Scaling-up hepatitis B birth-dose (HepB BD) vaccination could avert mother-to-child transmission of HBV infection and advance regional progress towards eliminating viral hepatitis. To describe whether - and how - complexities within the health system or intervention influence the performance of HepB BD vaccination programs in the WHO AFRO. Using a complexity perspective, we conducted a qualitative systematic review of literature published between 2009-2022. A Boolean search strategy retrieved relevant literature indexed in PubMed, EBSCOhost databases, Scopus, and Web of Science, with supplementary searches conducted to identify any missed articles. No language restrictions were applied. Data extraction, synthesis and analysis were guided by a systems-based logic model tailored to systematic reviews of complex interventions. Our search yielded 672 published records. Of these, 28 (26 English, 2 French) were eligible for inclusion. Among the 12 WHO AFRO member states represented, the origin of evidence weighted highest in Nigeria (n = 12) and Senegal (n = 5). The performance of HepB BD vaccination programs across member states are influenced by underlying complexities across eight cross-cutting themes: (i) availability and interpretation of HepB BD vaccination policies, (ii) capacity of vaccine supply and cold chain systems, (iii) availability of equitable and sustainable financing, (iv) capacity and capability of health care workers (HCWs), (v) immunization monitoring systems and impaired feedback loops, (vi) influence of context vs system design on the timeliness of vaccination, (vii) maternal knowledge and socio-economic factors, and (viii) wider contextual factors (geography, climate, cultural practices). Countries looking to introduce, or scale-up HepB BD vaccination programs will benefit from careful consideration of components of the intervention design that are dependent on the end-user's context and capabilities in accessing the vaccine; the adherence and interpretation of essential components of the policy; the provision of adequate support of stakeholders specifically HCWs and government ministries; and the need for innovative approaches to underlying complexities. Lessons offered by these African experiences provide pragmatic approaches to successfully implementing HepB BD vaccination programs in the region.

Solving a multi-choice solid fractional multi objective transportation problem: involving the Newton divided difference interpolation approach

<abstract> <p>Multi-objective transportation problems (MOTPs) are mathematical optimization problems that involve simultaneously considering multiple, often conflicting objectives in transportation planning. Unlike traditional transportation problems, which typically focus on minimizing a single objective such as cost or distance, MOTPs aim to balance multiple objectives to find the optimal solution. These problems appear in various real-world applications such as logistics, supply chain management, and transportation, where decision-makers need to consider multiple criteria when designing transportation networks, routing vehicles, or scheduling deliveries. The primary challenge lies in the uncertainty in real-world transportation scenarios, where logistics involve factors beyond cost and distance. We investigated a multi-choice solid fractional multi-objective transportation problem (MCSF-MOTP) based on supply, demand, and conveyance capacity, where the coefficients of the objective functions were of the multi-choice type due to uncertainty. To address this uncertainty, the proposed model employed the Newton divided difference interpolation polynomial method, and the suitability of this model was validated through a numerical illustration employing a ranking approach.</p> </abstract>

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Two-Stage Planning of Distributed Power Supply and Energy Storage Capacity Considering Hierarchical Partition Control of Distribution Network with Source-Load-Storage

Quantification of International Trade Network Performance Under Disruptions to Supply, Transportation, and Demand Capacity, and Exchange Rates in Disasters

Quantification of International Trade Network Performance Under Disruptions to Supply, Transportation, and Demand Capacity, and Exchange Rates in Disasters

An epidemic and economic growth. A medium-term perspective

The described model of economic growth under conditions of an epidemic does not directly refer to the social and economic situation in the years 2020 and 2021, i.e. to the COVID-19 pandemic. It is aimed to identify the consequences of any epidemic leading to severe social losses (high percentages of the infected and dead, limited interpersonal contacts as a result of lockdown, a lowered level of general individual and social well-being) and economic losses (a fall in production as a result of the collapse of aggregate demand and a reduction in the supply capacity of the economy, and consequently a decreased rate of capital accumulation). The described epidemiological-economic model combines the SIR epidemiological model from 1927 (with its modification proposed in 2020 by Bärwolff) and the neoclassical growth model proposed by Solow in 1956. The authors expanded the concept by lockdown restrictions with various levels of their severity, considering specific rules for their implementation, and by guidelines for scenario analyses of changes in the value of social and economic activity index, in the value of aggregate production, in the capital stock accumulated in the economy and in social utility. The effect of an epidemic on medium-term economic growth was also considered, for various levels of economic development (measured by the distance of input capital stock from that formed in a long-term equilibrium in the Solow model). The principal conclusions drawn from the discussion are listed below. First, the introduction of the same restrictions imposed on social and economic activity throughout the territory of a country poses a considerable risk of error in assuming a uniform spread of the epidemic. Second, a rapid introduction of lockdown measures has a stronger effect on accumulated social and economic activity than a continual process of gradual imposing and lifting restrictions on that activity. Third, a scenario of a rapidly imposed severe lockdown has the most drastic consequences for the economy, causing both the sharpest drop in production, the longest time of remaining on the path of relatively lowest growth, and the most dramatic expected accumulated decrease in production. Similar conclusions are drawn as to the changes in social utility.

A Study on the Impact of IoT Technology on the Operation Management of the Wastewater Management Sector

The research aims to analyze the impact of the Internet of Things (IoT) technology on the operation of the wastewater management (WWM) sector. The study results show that IoT technology could enhance operational process innovation in WWM. It is mainly reflected in wastewater pipeline network management, water quality monitoring, risk monitoring, and equipment maintenance. Through field data collection, transmission, fault detection, and decision-making support, it replaces the conventional manual operation, simplifies the workflow, and improves efficiency. In addition, IoT technology not only improves operation quality, and dependability, and reduces costs, but also improves the environment and water hygiene from the social level. In terms of risk management, IoT technology improves the accuracy and timeliness in hazardous sources monitoring, handling, and potential hazards prediction, to improve the risk management capability. Finally, IoT technology can enhance “demand” management by WWM authorities and provide accurate decision support for base capacity setting, also can solve the constraints of WWM system capacity to improve supply capacity.

Research on optimization of e-commerce supply chain logistics service model based on multi-source data fusion

Abstract Inefficiencies in supply chain logistics management, particularly in certain regions, often result in “broken chain” incidents that significantly impact the efficiency of e-commerce operations and degrade consumer experiences. This paper addresses the necessity of optimizing the logistics service model by integrating 12 heterogeneous data sources related to warehousing, transportation, processing, and sorting. We propose a site selection-inventory-path e-commerce logistics optimization model. For the first time, the model incorporates the Dempster-Shafer (D-S) evidence algorithm to quantitatively evaluate the support relationships among various pieces of evidence by adjusting the weight coefficients accordingly. This adjustment is further refined through the application of the Nash equilibrium in the evidence combination process. The optimized logistics model is then solved using a fusion of the model and an intuitive fuzzy set approach. A case study demonstrates that the optimized logistic supply capacity consistently outperformed the non-optimized scenarios, with statistical increases of 1.64%, 1.72%, 2.15%, 3.73%, 2.71%, 2.46%, 3.59%, 2.17%, and 3.98%. Furthermore, by refining the logistics model, the gap in logistics performance was narrowed by at least 5.13% and by as much as 12.9% across successive evaluations, significantly alleviating issues related to enterprise capacity constraints. This study offers novel insights and methodologies for enhancing the efficiency of regional e-commerce supply chain logistics, boosting the competitiveness of logistics enterprises, and elevating the consumer experience in e-commerce settings.

An integrated water resources management model considering carbon source and sink under uncertainty: A case study of agricultural water-dominated basin

The global drive for carbon neutrality promotion through integrated water resource management (IWRM) in the face of burgeoning water demand is of great importance. This study developed an interval fuzzy-credibility chance-constrained multi-objective programming (IFCMP) model for water resources-carbon system (WCS) planning, which not only accounts for multiple uncertainties within system parameters, such as interval, fuzzy, and stochastic, but also effectively balances the conflicting objectives of water scarcity, benefits, emissions, and carbon sinks. The IFCMP-WCS model was applied to an agricultural water-dominated zone in the Tarim River Basin, China. Multiple water-allocation scenarios were examined, encompassing five prefecture-level cities, five departments, and three planning years. The results indicated that: (1) the water deficit was increasing over time, limited by water supply capacity, reaching 0–3.49 × 109 m3 in 2035; (2) as water allocation rises, system benefits and pollutant emissions increase, with the agricultural sector contributing the most economic benefits and pollutant emission; (3) the Tarim River Basin is an important carbon sink area, with the net carbon sink increasing from 8781.7–10,771.1 × 103 to 8851.1–10,937.9 × 103 tonnes during the planning horizon; (4) compared to single-objective models, the IFCMP-WCS model can offer more applicable water resource management options. These findings provide useful information for decision-making regarding IWRM and enhancing the net carbon sink in the Tarim River Basin.

Research on Maximum Energy Supply Capacity of Electric-Gas-Thermal Interconnection Integrated Energy System

Research on Maximum Energy Supply Capacity of Electric-Gas-Thermal Interconnection Integrated Energy System

Forecasting shipbuilding demand using shipping market modeling: A case study of LNGC

Volatile and cyclical shipbuilding demand has consistently been a risk for the shipbuilding industry. This study analyzes the shipping market from a macro perspective and proposes a model capable of long-term shipbuilding demand forecasting. Initially, a system dynamics model representing the shipping market based on maritime economy theory is presented, comprising five main components: external variables, the freight market, shipyards, fleet productivity, and demolition. Based on this system dynamics model, a case study was conducted using LNG carrier market data. The prediction results of the model were compared with seven other time series forecasting models, demonstrating its validity. Finally, scenario analyses evaluated the impact of changes in cargo transport demand, shipyard supply capacity, and carbon regulations. The findings indicated that while increases in transport demand and stricter regulations enhance the amplitude of the shipbuilding demand cycle, increased shipyard supply capacity mitigates these cycles, raising both the period and trough of the cycle.

A study of distribution grid topology and its optimization in planning and operation

Abstract This paper combines the characteristics of a distribution network grid, analyzes the topology and application scenarios of a typical grid, and puts forward the design requirements for the optimization of radial DC distribution network grid structure. Based on the constraints of grid optimization, a Pareto multi-objective planning method is selected, and a multi-objective genetic algorithm is designed to improve the grid reliability index of the distribution network grid planning steps. Analyze the parameters of the example, encode the initial 110kV distribution network frame, carry out the optimal solution of the multi-objective genetic algorithm, compare the iteration number and convergence of different genetic algorithms, and obtain the best economic effect of the optimization of the distribution network frame structure. Analyze the power supply reliability index of distribution networks with different grid switching schemes and explore the degree of reliability influence on grid switching and power supply capacity. The optimal solution is obtained in 10 iterations of the algorithm, that is, the objective function is 65.2421 million yuan, and the optimal solution is reached in the interval of the number of iterations [0,100], and the fitness value is in the range of 2 × 104 million yuan.

Respiratory acidosis and O2 supply capacity do not affect the acute temperature tolerance of rainbow trout (Oncorhynchus mykiss).

The mechanisms that determine the temperature tolerances of fish are poorly understood, creating barriers to disentangle how additional environmental challenges-such as CO2-induced aquatic acidification and fluctuating oxygen availability-may exacerbate vulnerability to a warming climate and extreme heat events. Here, we explored whether two acute exposures (~0.5hours or ~72hours) to increased CO2 impact acute temperature tolerance limits in a freshwater fish, rainbow trout (Oncorhynchus mykiss). We separated the potential effects of acute high CO2 exposure on critical thermal maximum (CTmax), caused via either respiratory acidosis (reduced internal pH) or O2 supply capacity (aerobic scope), by exposing rainbow trout to ~1kPa CO2 (~1% or 10 000 μatm) in combination with normoxia or hyperoxia (~21 or 42kPa O2, respectively). In normoxia, acute exposure to high CO2 caused a large acidosis in trout (blood pH decreased by 0.43units), while a combination of hyperoxia and ~1kPa CO2 increased the aerobic scope of trout by 28%. Despite large changes in blood pH and aerobic scope between treatments, we observed no impacts on the CTmax of trout. Our results suggest that the mechanisms that determine the maximum temperature tolerance of trout are independent of blood acid-base balance or the capacity to deliver O2 to tissues.

A lumped parameter model for evaluating coronary artery blood supply capacity.

The coronary artery constitutes a vital vascular system that sustains cardiac function, with its primary role being the conveyance of indispensable nutrients to the myocardial tissue. When coronary artery disease occurs, it will affect the blood supply of the heart and induce myocardial ischemia. Therefore, it is of great significance to numerically simulate the coronary artery and evaluate its blood supply capacity. In this article, the coronary artery lumped parameter model was derived based on the relationship between circuit system parameters and cardiovascular system parameters, and the blood supply capacity of the coronary artery in healthy and stenosis states was studied. The aortic root pressure calculated by the aortic valve fluid-structure interaction (AV FSI) simulator was employed as the inlet boundary condition. To emulate the physiological phenomenon of sudden pressure drops resulting from an abrupt reduction in blood vessel radius, a head loss model was connected at the coronary artery's entrance. For each coronary artery outlet, the symmetric structured tree model was appended to simulate the terminal impedance of the missing downstream coronary arteries. The particle swarm optimization (PSO) algorithm was used to optimize the blood flow viscous resistance, blood flow inertia, and vascular compliance of the coronary artery model. In the stenosis states, the relative flow and fractional flow reserve (FFR) calculated by numerical simulation corresponded to the published literature data. It was anticipated that the proposed model can be readily adapted for clinical application, serving as a valuable reference for diagnosing and treating patients.

Joint Generation and Voyage Scheduling of All-Electric Ships Considering Power Supply Capacity Constraints

Joint Generation and Voyage Scheduling of All-Electric Ships Considering Power Supply Capacity Constraints

Octahedral CoS2 electrocatalysts for efficient nitrate reduction to ammonia

Octahedral CoS2 nanocrystals are highly active to ambiently reduce NO3− to NH3 (NO3RR). DFT calculations reveal that CoS2 (111) with high electron supply capacity is responsible for enhanced NO3RR activity.

KAREKTERISASI OPTIMISASI JARINGAN RANTAI PASOKAN

This study proposes a mathematical solution to optimization problems in supply chains. The supply chain analyzed includes suppliers, manufacturers and distribution centers, bearing in mind that orders come from clients to distribution centers. A mathematical model that solves optimization characterization problems regarding the duration and cost of executing client orders is proposed. Many constraints are supported in this mathematical model such as supplier and producer capacity and balanced supply. The aim of the proposed model is to find optimal characteristic solutions that minimize cost and time criteria throughout the entire supply chain process. Mathematical models are tested on supply chains to determine the characteristics of several models that can be used to obtain optimal supply chain networks. This research produces a mathematical model with the function of the procurement model.

Streamflow responses to forest and climate change in the boreal Da Hinggan Mountains, Northeastern China

AbstractBoreal forests cover vast stretches of land across all continents and represent a principal source area of clean water in the northern hemisphere. Increasingly, studies are conducted on the impact of changes in boreal forest cover on water yield; however, much remains unknown concerning the effects of forest structure changes on stream discharge over the course of multi‐decadal forest harvest cycles. In this study, we analysed long‐term hydrometeorological and forest dynamics data spanning from 1990 to 2016 from a typical boreal forest watershed in the Da Hinggan Mountains in northern China. Our objective was to quantify how changes in forest age and tree species composition affect mean annual streamflow and flow regimes in the context of a changing climate. To distinguish the effects of forest and climate changes on annual streamflow from one another, we employed a combination of a sensitivity‐based method and a temporal trend analysis. Further, we evaluated the impact of forest changes on flow regimes using four indicators: magnitude, duration, frequency, and variability. The results indicated that mean annual streamflow increased by 55.8 mm, with forest changes contributing +61.4 mm compared to −5.6 mm due to climate change (negative effect). This increase occurred when approximately 20% of mature coniferous forests transitioned to mid‐age broad‐leaved forests, accompanied by a 10% increase in total stock volume during the later period. Finally, the effect of changes in forest structure on flow regime were not significant. Our results underscore that variations in forest structure affect streamflow differently depending on stand age and species proportions. Therefore, dynamic forest structure management can benefit not only carbon sequestration but also water supply capacity in boreal forested watersheds.

An optimization model for sustainable multi-product multi-echelon supply chain networks with U-shaped assembly line balancing under uncertainty

This study presents an integrated supply chain network with suppliers, manufacturers, assemblers, and customers. The proposed model considers a U-shaped assembly line with three sustainability objective functions. We consider assumptions considering different types of raw materials, multiple products, location selection of manufacturers, location selection of assemblers, and capacity of suppliers. The problem is formulated non-linear and then linearized as a multi-objective model. Some cost and demand parameters are considered uncertain and are represented by fuzzy sets and theory. The proposed uncertain model is first converted to a multi-objective crisp model by applying the modified robust possibilistic programming approach. Then, the obtained crisp multi-objective model is solved by an interactive-fuzzy optimization approach in the literature. For computational study, some test problems are generated and solved using an original deterministic formulation and the crisp form of the uncertain formulation. The obtained results are analyzed and compared according to the objective function values. Finally, an extensive sensitivity analysis is performed on the parameters of the models.

Evaluating Trade-Offs in Ecosystem Services for Blue–Green–Grey Infrastructure Planning

The effectiveness and feasibility of urban planning are significantly influenced by the supply capacity and net value of ecosystem services offered by blue–green–grey infrastructure. This study used a cost–benefit analysis (CBA) to ascertain and contrast the ecological net present value (NPV) of the blue–green–grey infrastructure in three distinct functional areas (a park, a square, and a residential district) under 12 scenarios during the period characterized by representative summer temperature, which we refer to as “warm periods”. Our findings suggest varied optimal scenarios for the three functional areas. For the park, the most beneficial scenario involved an integrated approach with a 5% increase in grey infrastructure and a 5% replacement of green infrastructure with grey. This scenario yielded an NPV of 7.31 USD/m2 in a short-term life span (25 years) and 11.59 USD/m2 in a long-term life span (150 years). In the case of the square, the introduction of an additional 5% of blue infrastructure led to the highest NPV of ecological benefits, resulting in gains of 1.49 USD/m2 for a short-term life span and 2.18 USD/m2 for a long-term life span. For the residential district, the scenario where 5% of green infrastructure was replaced with blue infrastructure resulted in the highest NPV across all scenarios, with values of 8.02 USD/m2 and 10.65 USD/m2 for a short- and long-term life span, respectively. Generally, the most beneficial scenario yielded greater benefits over the long term compared with short-term projects. By quantifying the ecological benefits of different blue–green–grey infrastructure combinations, our research provides theoretical support for optimizing both the ecological and economic value of urban infrastructures. This study could benefit academics, practitioners, and policymakers in urban planning in optimizing the allocation of the blue–green–grey infrastructure.

Effect of Project Planning Practices on Performance of Improve Capacity for Supply of Quality in Reproductive Health Services Project in Nyamasheke District, Rwanda

Effect of Project Planning Practices on Performance of Improve Capacity for Supply of Quality in Reproductive Health Services Project in Nyamasheke District, Rwanda