Accelerated Parameter Optimization of Granular Models of Battery Manufacturing

From Rio to Iragua--sustainability versus efficiency and equity for preventive health interventions.

Resource use efficiency (RUE) is an ecological concept that measures the proportion of supplied resources, which is converted into new biomass, i.e. it relates realized to potential productivity. It is also commonly perceived as one of the main mechanisms linking biodiversity to ecosystem functioning based on the assumption that higher species numbers lead to more complementary and consequently more efficient use of the available resources. While there exists a large body of literature lending theoretical and experimental support to this hypothesis, there are a number of inconsistencies regarding its application: First, empirical tests use highly divergent approaches to calculate RUE. Second, the quantification of RUE is commonly based on measures of standing stock instead of productivity rates and total pools of nutrients instead of their bioavailable fractions, which both vary across systems and therefore can introduce considerable bias. Third, conceptual studies suggest that the relationship between biodiversity, productivity and RUE involves many more mechanisms than complementary resource use, resulting in variable magnitude and direction of biodiversity effects on productivity. Moreover, RUE has mainly been applied to single elements, ignoring stoichiometric or metabolic constraints that lead to co-limitation by multiple resources. In this review we illustrate and discuss the use of RUE within and across systems and highlight how the various drivers of RUE affect the diversity-productivity relationship with increasing temporal and spatial scales as well as under anthropogenic global change. We illustrate how resource supply, resource uptake and RUE interactively determine ecosystem productivity. In addition, we illustrate how in the context of biodiversity and ecosystem functioning, the addition of a species will only result in more efficient resource use and consequently higher community productivity if the species’ traits related to resource uptake and RUE are positively correlated.

Introduction. Under the crisis circumstances in the economy an important task for enterprises is to consolidate and sometimes expand their position in the market. In this context, it is important to analyze the indicators of resource use, that allow to assess their use level and identify areas to help improve their efficiency.Methods. The theoretical basis of the study is the scientific publications of domestic and foreign scholars to assess the effectiveness of the enterprise resources usage. The results are obtained through the methods: analysis – in the study of basic theoretical, methodological approaches to assessing the efficiency of resource use; abstraction – to determine the essential characteristics of the key indicators of resource efficiency; generalization – to systematize indicators for the efficiency assessment of enterprise resources use. The purpose is to search the directions to increase the efficiency of resources use in the conditions of an enterprise economic activity on the basis of the recent methodical achievements.Results. A thorough analysis of indicators for assessing the enterprise resources effectiveness on the basis of domestic and foreign scientists study is realized. It is proposed to systematize the most common indicators in order to assess the enterprise resources efficiency in quantitative terms into three groups: relative indicators of business activity (turnover ratios), indicators of resource management efficiency (turnover duration) and indicators of company assets efficiency for profit generation (profitability). An improved system of indicators has been applied to assess the resource use efficiency in the conditions of a real enterprise. Perspectives. Prospects for further research are to establish the degree of efficiency influence of enterprise resources use on the profit level with the mathematical models.

Cloud computing has grown due to internet advancements in recent years. The Internet, Cloud of Things (IoT, CoT), edge, and fog computing are integrated in modern cloud architecture. These devices generated a lot of client-requested data that must be handled quickly. Mobile Edge Computing (MEC) devices offloaded smartphone tasks to nearby edge servers to speed up execution. Task offloading has become increasingly crucial for accelerating execution, minimizing latency, and conserving energy. Task execution and efficient resource use enhance the Quality of Service (QoS). So, researchers have proposed heuristic and rule-based dynamic offloading policies. However, they typically fail to balance exploring multiple solution spaces and using high-quality solutions, resulting in imbalanced task allocation convergence. In this paper, a machine learningbased method is proposed that uses the Random Forest (RF) classifier to choose Differential Evolution (DE) and Particle Swarm Optimization (PSO). The classifier was trained using several metrics derived from different job sizes. It used the best possible metaheuristic method for the incoming job size. The proposed methodology yielded promising results when compared to several current strategies.

Statistical entropy analysis to evaluate resource efficiency: Phosphorus use in Austria

General Background: Efficient resource utilization is a critical determinant of competitiveness and sustainability in industrial enterprises facing economic uncertainty and rising costs. Specific Background: In resource-intensive industries, particularly textile enterprises, traditional management approaches are insufficient to control material, labor, energy, and financial resources under dynamic market conditions. Knowledge Gap: Existing studies provide limited integrated frameworks that empirically link strategic, operational, and digital management mechanisms to measurable improvements in resource efficiency and financial performance. Aims: This study aims to analyze management mechanisms that enhance the efficiency of resource use in industrial enterprises through integrated strategic, operational, and digital tools. Results: The findings demonstrate that integrated management mechanisms improve material utilization, labor productivity, and energy efficiency, while reducing unit production costs, operational risks, and cost volatility, leading to stronger financial performance. Novelty: The study proposes a structured, block-based management mechanism that systematically connects resource planning, digital support, monitoring, and financial management. Implications: The results provide practical guidance for managers and policymakers to strengthen resource efficiency, cost optimization, and long-term competitiveness in industrial enterprises, particularly within the textile sector.Keywords : Resource Efficiency, Industrial Enterprise Management, Integrated Management Mechanisms, Digital Resource Management, Operational and Cost OptimizationHighlight : Integrated managerial systems significantly reduce material waste and stabilize input–output ratios across textile production stages. Digital tools enhance decision accuracy, real-time oversight, and operational consistency, strengthening productivity and risk control. Coordinated planning and monitoring improve cost structures, profitability, and financial resilience under volatile market conditions.

Resource efficiency has always been a hot topic for the steel industry, due to the large amounts of primary raw materials, by products and water, which are handled in the steelmaking cycle as well as the considerable energy consumptions. The ever more stringent environmental regulations also contribute to pressurize the iron and steel industry to strengthen further its research activities fostering an optimal management and exploitation of resources. Thus important research efforts are spent in order to find the best way to recover wastes and wastewater also involving the implementation of retrofit actions and major plant modifications allowing also the reduction of primary raw material consumption and of waste disposal. In order to achieve such ambitious objective, which implies both environmental benefits and cost savings, process integration is a powerful tool. The assessment of the viability of process integration solution necessarily include a final experimental stage to be performed at plant level, which can be expensive or unsafe. To this aim process simulation can be a useful alternative to accomplish preliminary feasibility studies allowing a deep analysis of all the aspect of a particular technology or retrofit actions, which also allows testing conditions that are very difficult to replicate within practical experiments. Different levels of detail can be achieved and a comprehensive analysis can be carried out. The present paper provides an overview of the simulation techniques exploited during the project entitled Efficient Use of Resources in Steel Plants through Process Integration to the aim of optimizing the use of resources in an Italian integrated steelmaking plant. In particular, different case studies are proposed and the obtained meaningful and practical results are presented and discussed.

The study determined resource use efficiency in maize crop production by small-scale farmers in the Central Agricultural Zone of Cross River State Nigeria. It specifically examined the allocative efficiency of resources used by small-scale farmers in rainfed maize production in the area. Primary data were used to conduct the study. Statistical tools employed were multiple regression analysis and allocative efficiency index (AEI). The results of the multiple regression analysis revealed that the variables of farm size (x1), farm capital (x3), fertilizer (x4), farm credit (x6), extension service (x7), seeds planted (x8) had a positive relationship with the output of maize. The allocative efficiency index (AEI) of the various productive resources showed that farm size (x1), fertilizer (x3), and herbicides (x5) were found to be underutilized since their allocative efficiency index (AEI) was greater than one (1) and their marginal value product (MVP) were greater than their marginal factor cost (MFC) while Labour(x2) was over-utilized as the allocative efficiency index (AEI) was less than one (1). Based on these findings, the following recommendations were made; maize farmers should improve their use of productive resources such as land, capital, fertilizers, herbicide and seeds. Labour factor should be maximally utilized to create a favourable return to a unit of man day employed in maize production in the area.

This study presents an optimization framework for residential energy management that integrates photovoltaic (PV) systems, battery storage, and demand response strategies. The primary objective is to minimize electricity costs while ensuring efficient use of renewable energy resources. The proposed method utilizes the Meerkat Optimization Algorithm (MOA), which is compared against other optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching-Learning-Based Optimization (TLBO). The results show that the proposed MOA achieves significant cost reductions. For example, under Time-of-Use (TOU) tariffs, the total electricity cost is reduced by 14% compared to the base case, while under Real-Time Pricing (RTP), the reduction is 16%. The optimized system also yields a 5 kW PV system and a 10 kWh battery, compared to 3 kW PV and 6 kWh battery in the GA and PSO cases. Additionally, the MOA provides a more computationally efficient solution, with a calculation time of 73 s, compared to 91 s for GA and 102 s for PSO. This study demonstrates the effectiveness of the MOA in optimizing residential energy systems, providing a robust solution for reducing electricity costs while integrating renewable energy sources. The approach is generalizable to other energy management applications and can be adapted for various regions and household configurations.

High Altitude Platforms (HAPs) is the name of a new technology to provide wireless narrowband and broadband services. A unique property of HAPs is the ability of preparing emergency telecommunication facilities once the catastrophic events occur. In these situations efficient use of limited spectrum resources would be of great importance. This paper presented a fuzzy channel allocation scheme in HAPs for emergency mobile communications. The suggested scheme is based on guard channel policy. It dynamically adjusts optimum number of reserved channels according to important quality of service (QoS) parameters to make an efficient use of resources, while prioritizes on-going calls over new calls. Simulation compares the proposed fuzzy scheme with fixed guard channel scheme and complete sharing scheme. Results show that, the fuzzy scheme is able to achieve a better grade of service (GoS), while can keep handoff failures low as network traffic load changes.

The global economic impact of basketball is measured in tens of billions of dollars and requires the efficient use of resources to maximize success on and off the court. Today, coaches, players, investors, and owners need to take full advantage of modern analytical methods and digital video software capabilities to make the most efficient use of a teams resources. This research is the first in a series that makes full use of modern analytic methods and begins to define new defensive and offensive criteria to supplement the decades old game box score performance information. Data envelopment analysis and statistical methods are used to evaluate two new defensive performance metrics on defensive efficiency. The two new defensive metrics are contested and uncontested passes that are fully defined in the articles appendix. Future research will expand the sample size and allow for more comprehensive models of basketball team defensive efficiency.

There is general agreement among the major stakeholders—providers, consumers, payors, and managed behavioral health companies—that managed care poses significant challenges for behavioral health professionals, particularly those whose primary work has been in independent practice rather than organized care settings. In traditional independent practice, clinicians were free to employ relatively unstructured, goal-free approaches to care with an emphasis on patient insight and self-knowledge. Formal written treatment plans were a rarity and there was little external pressure on clinicians to complete treatment within any specified period of time. Often, little attention was paid to the efficient use of financial and service resources, and decisions to begin and end treatment were the purview of the therapist and the patient. Patients were generally seen as financially responsible for their treatment regardless of employment based benefits. Indeed, such an approach to practice was consistent with the ways in which most behavioral health professionals were trained. In contrast, clinicians practicing in today's managed care environment are typically required to develop written, goal-focused, time limited treatment plans emphasizing the return of the patient to an adequate level of day-to-day functioning while making efficient use of resources (Austad & Berman, 1991). Decisions to begin and end treatment, at least the part to be paid for through the benefit plan, are made by the therapist and patient together with a third party—the managed care entity. In order to work effectively within this context, clinicians must be both willing and able to change their practice patterns, to at least accommodate

The international guidelines for surveillance following the finding of a small tubular adenoma vary between no surveillance or colonoscopy at 5 or 10 years, whereas surveillance after an advanced adenoma is 3 years. Optimization of surveillance reduces the risk of colorectal cancer (CRC) with efficient use of colonoscopy resources. We assessed the risks of advanced colorectal neoplasia following a baseline finding of a small adenoma compared with advanced adenoma. A retrospective audit was undertaken of patients enrolled in a CRC surveillance program, wherein regular colonoscopies and screening with faecal immunochemical test (FIT) were provided. Patients diagnosed with either small or advanced adenoma followed by at least one surveillance colonoscopy were included. Advanced adenoma included adenomas with features of villous change, size of at least 10 mm, high-grade dysplasia, three or more small tubular adenomas and traditional and sessile serrated adenomas. Subdistribution hazard ratios were calculated for advanced neoplasia (CRC or advanced adenoma). Overall, 378 patients (62.6±11.2 years, 57.9% male) were included, with 44.2% diagnosed with small adenoma and 55.5% with advanced adenoma at baseline. The crude cumulative incidence of advanced neoplasia at first surveillance was 13.2 and 18.5% after small and advanced adenoma (P=0.16) (at 45.9 and 35.6 months, respectively), which became significant for advanced adenoma after adjustment (subdistribution hazard ratio=2.55, 95% confidence interval=1.49-4.35, P<001). A positive FIT was the only independent predictor of advanced neoplasia after a small adenoma at baseline colonoscopy (odds ratio=5.05, 95% confidence interval=1.27-20.02, P=0.02). The risk of advanced neoplasia following a small adenoma was lower than that following an advanced adenoma, but was strongly predicted by a positive FIT. Reducing frequency of colonoscopy while providing regular FIT might be a more efficient use of resources for this population.

This article reviews the principles involved in establishing the cost effectiveness of mass drug therapy for the major intestinal nematodes and the intestinal form of schistosomiasis, as well as the extent to which the available studies have provided definitive answers. For governments or agencies that have decided to introduce a control programme, there is considerable evidence about the comparative cost effectiveness of different types of delivery strategies. For example, mass treatment is more cost effective than selective treatment (treatment after individual screening) in high prevalence areas and at observed prices. Mass treatment targeted at known high risk groups, such as schoolchildren, for the major intestinal helminths (apart from hookworm) can be more cost effective than population-based mass treatment. However, this raises the question whether any form of mass anthelmintic chemotherapy is an efficient use of scare health resources in view of the competing demands for scarce public funds, and for the scarce resources of other funders of healthcare including donors, nongovernmental organisations and missions. Some evidence that it is an efficient use of resources is available; this article concludes by outlining the type of information that is required to strengthen the argument for mass therapy.

Of the several mechanisms that can bring about efficient resource use, the most widelyapplicable one is intercropping systems that can make better use of resources. The aim of thisstudy was to evaluate resource capture and resource use efficiency in transgenic cotton-peanutintercropping system and in their respective sole crops with using 25-50% substitution ofrecommended dose of nitrogen (RDN) of cotton through farmyard manure (FYM) along with100 % RDN through urea and control (0N). Apparent crop water productivity, nutrient useefficiency, economic returns and modern intercropping indices (system productivity index,actual yield loss, intercropping advantage index, nitrogen stress factor, etc.) were measured formaking better understanding of resource use efficiency. Comparisons of intercropped peanutwith sole peanut were emphasized because of shrinking area of peanut in the south-east Asianregion represents a threat to agricultural system sustainability. Cotton + peanut intercroppingsystem resulted in improved water productivity (19%), nutrient use efficiency (15-20%) andmonetary advantage index (16,709) as measured with modern tools of intercropping indicescompared with sole crops of cotton and peanut. Peanut cultivated as sole crop attained the leastresource productivity in terms of apparent crop water productivity (0.71 kg m-3), nutrient useefficiency (4.47 kg grain kg N-1) and total factor productivity (0.07). Among fertility levels,substitution of 25% RDN of cotton through FYM maintained higher apparent crop waterproductivity (17%), monetary advantage index (6%), system productivity index (9%) andnutrient use efficiencies (15-17%) over 100% RDN through urea only. This work provides basisfor efficient resource use by peanut intercropping with cotton which simultaneously enhancesdomestic oilseed production and reduce import load of cooking oil without sacrificing theproductivity of main crop of cotton in India and other cotton growing countries of the world.