Supply Costs Research Articles

A Mathematical Model for Green Leaves Diet Using Ranking of Tridecagonal Fuzzy Numbers

This study presents a new way of ranking transportation options using tridecagonal fuzzy numbers. This approach takes into account factors such as demand, supply, and transportation costs, and aims to provide a more optimized solution for these fuzzy environments. With the rising importance of healthy eating habits, particularly emphasizing green leafy vegetables, devising an effective dietary plan becomes imperative. Traditional approaches often overlook the inherent uncertainty and fuzziness in dietary preferences and nutritional requirements. In this context, tridecagonal fuzzy numbers offer a robust framework to represent and analyze uncertain dietary preferences. Our ultimate goal is to promote a green leaf diet that is both affordable and widely available, while also improving the overall health and well-being of the general public. This research contributes to the advancement of mathematical modelling in nutrition science, offering a valuable tool for promoting healthier dietary choices and lifestyle habits.

Evaluation of Tilapia (Oreochromis niloticus) Survival and Growth in Aquaculture Systems with Different Feed Types

Proper feeding is crucial for promoting fast and healthy growth in fish, contributing to increased overall production. However, access to high-nutritional feed is not always feasible. Utilizing locally available ingredients presents a potential solution to this challenge. Consequently, this research aims to assess the impact of locally available feed ingredients on the growth and production of tilapia (O. niloticus) in Liberia. Three types of fish feed were prepared, namely Africa Rice fish feed (diet 1), soybeans fish feed (diet 2), and Gbarnga fish feed (control), each with distinct compositions. These feeds were evaluated to determine their effects on the growth and production performance of tilapia fish for the duration of 31 weeks. Fifty fish with an initial body weight of 12 g each were stocked in each hapa net. Data on survival rate (%), feed conversion ratio (FCR), and growth (g) were collected and compared. The growth results revealed a statistically significant difference (P < 0.001) among the three selected fish feed types. Diet 1 exhibited a higher average mean weight of 1521.67 g per 92 fish followed by the control with an average mean weight of 1315.56 g per 88 fish, while diet 2 demonstrated comparatively lower growth, 1164.44 g per 96 fish. Survival rate and FCR, however, exhibited no significant differences. Notably, the cost of food supplies, particularly proteins, may constrain farmers' access to feed processing and formulation technology. Consequently, the findings of this study are expected to address challenges related to feed formulation and processing, providing valuable insights for the enhancement of fish farming practices.

Mixed-integer disciplined convex programming approach applied to the optimal energy supply of near-zero energy buildings

Energy needs in the buildings sector accounts for 40 % of global energy demand. Therefore, the implementation of several renewable energy sources is necessary to reduce this demand. The design stage of a decentralized generation project requires quantifying the power to be installed and the energy forecast for each source throughout the useful life of the building. This study develops a novel optimization algorithm for a long-term economic function based on mixed-integer disciplined convex programming (MIDCP) which guarantees the sustainability of the building and its energy systems. The robust algorithm integrates risk management of intermittent sources, technical and economic parameters of selected technologies, and life cycle analysis (LCA) of different energy systems, including storage. Furthermore, the penetration of green hydrogen into the distributed generation mix is evaluated as an important contribution. Meteorological and energy demand variables of two antagonistic scenarios were also used as inputs to the algorithm. As a result, the optimal energy supply sizing for tertiary buildings in the two defined locations was obtained. The results of the simulations have achieved an optimal convergence of 100 % in the proposed scenarios, with a resolution time of 14 s and using a memory of about 183 MB. The simulations suggest a higher penetration of green hydrogen in scenarios where supply and investment costs decrease to gray hydrogen supply levels, reaching up to 81 % coverage of the thermal demand of the building. Hybrid energy systems under favorable conditions show a penetration of about 92 % within the distributed generation mix. The developed tool could enable decision-makers to optimally plan distributed generation projects in buildings based on economic, policy, and geographic conditions.

An economic demand-based framework for prioritization strategies in response to transient amino acid limitations

Cells contain disparate amounts of distinct amino acids, each of which has different metabolic and chemical origins, but the supply cost vs demand requirements of each is unclear. Here, using yeast we quantify the restoration-responses after disrupting amino acid supply, and uncover a hierarchically prioritized restoration strategy for distinct amino acids. We comprehensively calculate individual amino acid biosynthetic supply costs, quantify total demand for an amino acid, and estimate cumulative supply/demand requirements for each amino acid. Through this, we discover that the restoration priority is driven by the gross demand for an amino acid, which is itself coupled to low supply costs for that amino acid. Demand from metabolic requirements dominate the demand-pulls for an amino acid, as exemplified by the largest restoration response upon disrupting arginine supply. Collectively, this demand-driven framework that drives the amino acid economy can identify novel amino acid responses, and help design metabolic engineering applications.

Analysis of Efficient Drug Supply Control at Muhammadiyah Siti Aminah Bumiayu Hospital Using the MMSL Method (Minimum-Maximum Stock Level) Period March – May 2023

Medicine supplies that are too large or small will make hospitals sick loss. These losses can be in the form of drug supply costs enlarges and becomes disturbed smooth running of health services in hospitals. Objective study This For know influence method MMSL to supply drug in a way efficient in Installation Pharmacy RSU Muhammadiyah Siti Aminah Bumiayu. This research design uses quasi-experimental without control, by applying the method studied, namely minimum-maximum stock levels. Sampling using technique which can be obtained from Retrospective data for October 2022 – December 2022 and method application prospectively, namely March 2023 - May 2023 and carry out strategies repair use method Hanlon. All data drug results analysis A B C became the sample for this research. Analysis of inventory value data was carried out, stock value out, dea d stock and ITOR before and after application of the method using test statistics Wilcoxon Signed Rank Test. The inventory value before applying the MMSL method was IDR 289,756,421, and after applying control using the MMSL method it was IDR 184,725,126 , with a value of p=0.002<0.05. The implementation of drug control using the MMSL method shows that there is an influence on the value of drug supplies in the pharmaceutical installation of RSU Muhammadiyah Siti Aminah Bumiayu.

Abstract 2: Reduction of Laboratory Supply Costs and Streamlining of Ordering Process

Abstract 2: Reduction of Laboratory Supply Costs and Streamlining of Ordering Process

Using Advanced Metering Infrastructure Data from MV/LV Substations to Minimize Reactive Energy Supply Cost to Final Consumers

This article presents an original methodology to determine the optimal level of reactive energy transmission to low-voltage consumers supplied from MV/LV substations that guarantees the lowest total costs of reactive energy transmission through the DSO network and its generation in receiving installations within the reactive power compensation process. The average value of the optimal factor tgφ to be maintained by customers depends on the efficiency of the network, the characteristics of the load, and the market costs of energy losses due to the transmission of reactive energy through the network that are covered by the DSO and the costs of reactive energy generation in receiving installations. The results presented for real MV/LV substations operating in the Polish distribution network demonstrate the application of annual measurements of active and reactive energy consumed and generated registered by AMI systems to calculate the optimal reactive power compensation level. They can be applied to verify the permissible levels of reactive energy compensation applied by the DSOs until now within the yearly tariffs for customers.

Health Outcome Changes in Individuals With Type 1 Diabetes After a State-Level Insulin Copayment Cap

Many insulin users ration doses due to high out-of-pocket costs. Starting January 2020 with Colorado, 25 states and the District of Columbia enacted laws that cap insulin copayments. To estimate the association of Colorado's $100 copayment cap with out-of-pocket spending, medication adherence, and health care services utilization for diabetes-related complications. In this cohort study using Colorado's All-Payer Claims Database, nonelderly insulin users with type 1 diabetes were analyzed from January 2019 to December 2020. Outcome changes were compared in the prepolicy and postpolicy period among individuals continuously enrolled in state-regulated and non-state-regulated plans using difference-in-differences regressions. Subgroup analyses were conducted based on individuals' prepolicy spending (low: never ≥$100 out-of-pocket vs high: ≥$100 out-of-pocket cost at least once). Data were analyzed from June 2023 to May 2024. Enrollment in state-regulated health insurance plans subject to the copayment cap legislation. Adherence to basal and bolus insulin treatment was evaluated using the proportion of days covered measure, out-of-pocket spending reflected prescription cost for a 30-day supply, and health care utilization for diabetes-related complications was identified using primary diagnosis codes from medical claims data. The panel included 1629 individuals with type 1 diabetes (39 096 person-months), of which 924 were male (56.7%), 540 (33.1%) had 1 or more comorbidities, and the mean (SD) age was 40.6 (15.9) years. Overall, the copayment cap was associated with out-of-pocket spending declines of $17.3 (95% CI, -$27.3 to -$7.3) for basal and $11.5 (95% CI, -$24.7 to $1.7) for bolus insulins and increases in adherence of 3.2 (95% CI, 0.0 to 6.5) percentage points for basal and 3.3 (95% CI, 0.3 to 6.4) percentage points for bolus insulins. Changes in adherence were associated with increases within the prepolicy high-spending group (basal, 9.9; 95% CI, 2.4 to 17.4 percentage points; bolus, 13.0; 95% CI, 5.1 to 20.9 percentage points). The policy was also associated with a mean reduction of -0.09 (95% CI, -0.16 to -0.02) medical claims for diabetes-related complications per person per month among high spenders, a 30% decrease. In this cohort study of Colorado's insulin copayment cap among individuals with type 1 diabetes, the policy was associated with an overall decline in out-of-pocket spending, an increase in medication adherence, and a decline in claims for diabetes-related complications only among insulin users who spent more than $100 in the prepolicy period at least once.

Supply Chain Management Optimization and Cost Reduction Based on Data Mining Algorithm

Supply Chain Management (SCM) is an evolving industry that constantly evolves, but one constant is the significance of effective inventory control in optimizing profits and customer satisfaction. The primary objective of the research is to identify the most effective method for a business to supply several products while maintaining customer service and keeping inventory costs low. The main aim of this paper's Stochastic Gradient Descent (SGD)-enhanced Support Vector Machine (SVM) approach is to predict ideal order and lack quantities, considering into account historical demand, level of inventory, vendor performance, and cost data. The key goal is to reduce the total cost of inventory (which includes holding, placing orders, and supply-chain costs) while maintaining excellent customer service. In order to accomplish this, the proposed system combines SGD's efficiency to enhance predictions and SVM's predictability. A consumer products business chain's real-world dataset was employed to train and test the algorithm. The dataset provides three years' worth of revenue, stock levels, vendors, and costs. Parameters like Mean Absolute Error (MAE), Inventory Turnover Ratio (ITR), and Service Level Achievement (SLA) have been employed to test the methodology, and parameters were optimized using a 5-fold cross-validation. Based on the study findings, the simulation model obtains an average MAE of 1.81 following 100 training epochs, substantially boosting ITR and SLA. As it effectively and accurately balances inventory levels with customer needs, the findings demonstrate that the SVM model with SGD is an excellent match for IMO.

An optimisation method for planning and operating nearshore island power and natural gas energy systems

As the development and use of offshore islands increase, so do the diversity of their energy needs, the cost of utilising the mainland for resource replenishment, and the instability of island energy systems. To address this challenge, this paper introduces an innovative system integrating fossil and renewable energy tailored for these islands, considering seasonal variations and external energy fluctuations. Leveraging a P-graph, an optimisation framework is designed to assess different optimised solutions. A comprehensive analysis is also performed to compare the solutions, while sensitivity assessments evaluate factors including electricity and gas price fluctuations, renewable energy availability, and natural gas demand. Additionally, the carbon emissions resulting from different power generation scenarios are visually represented and thoroughly analysed. The results support two key findings: 1) the cost of combined energy supply is lowest when wind energy accounts for 59 % of the total energy, mainland grid connection accounts for 3 %, fossil fuel energy accounts for 28 %, and natural gas accounts for 10 % of the energy mix; and 2) the price of electricity and natural gas supplied to the islands and the variability in the energy sources of wind and natural gas can significantly affect the cost of the energy system.

Integrated planning for a multiproduct, multisite reforestation value chain: a Canadian case study

This paper addresses integrated supply and distribution planning for a multiproduct, multisite reforestation value chain (RVC) in a make-to-order context. The aim is to develop a tactical planning tool to determine the quantities of seedling species and sizes to order from nurseries to satisfy reforestation site needs while minimizing purchase and distribution costs. A mixed-integer linear programming model was developed and applied to the publicly managed RVC in the province of Quebec, Canada. This tool was also used to analyze scenarios considering the three pillars of sustainability: environmental (climate risk management to bolster resilience), social (fair production allocation), and economic (supply and distribution costs) aspects. This strategic analysis highlights the trade-offs between purely economic and more sustainable scenarios and discusses strategic deployment opportunities to improve the RVC. Ultimately, it serves as a powerful tool for efficiently allocating yearly seedling supply, minimizing costs, and promoting sustainable practices in reforestation planning which provides valuable insights for RVC managers.

Coordinated economic and low‐carbon operation strategy for a multi‐energy greenhouse incorporating carbon capture and emissions trading

AbstractGreenhouses need to supply CO2 to crops while simultaneously emitting CO2. To effectively harness the dual functionality of greenhouses as a carbon source and carbon consumer, this work incorporates carbon capture and emissions trading into a multi‐energy greenhouse (MEG), which is equipped with various power and heat sources such as photovoltaic (PV) panels and a combined heat and power (CHP) unit and proposes that the captured CO2 should be used to feed crops on‐site. A low‐carbon economic operation method is proposed for the coordinated environment‐energy‐carbon management of the MEG, and it considers various factors, including the power purchase/carbon supply costs, carbon emissions trading income, temperature/humidity/light intensity and CO2 concentration requirements for crops, and operational constraints of various energy/environmental regulation equipment. The proposed method is validated using a tomato MEG. The results highlight the significant economic and environmental benefits of introducing carbon capture, emissions trading, and utilisation into MEGs.

Perbandingan Metode EOQ, JIT, Kebijakan Perusahaan dalam Pengendalian Biaya Persediaan Bahan Baku pada Loske Coffeeshop

Coffeshop Loske is a business of the food and beverage industry, the problem with the Loske Coffeeshop is whether its current supply of raw materials is efficient and whether its EOQ method and its effective effective is in the Loske Coffeeshop. The purpose of the study is to analyze the optimum cost of supply of raw materials on the Loske Coffeeshop and to find out if EOQ methods and JIT can optimize the control of supply of raw materials in the Loske Coffeeshop. The data needed is a general picture of Loske Coffeeshop, organization structure, production process, raw materials supply data, raw materials use data, message cost data, and store cost data. A data-collection technique using a documentary method. Based on studies already done, researchers concluded that the EOQ method and JIT method were proven to optimize the cost of controlling the supply of raw materials when applied to the loske coffeeshop. EOQ methods produced a supply charge of Rp 9.998.749, and the JIT method produced a supply cost of Rp 10.203.373, whereas using the company's policy method currently used produces a stock cost of Rp 14.404.302.

Coordinated Multi-Scenario Optimization Strategy for Park Photovoltaic Storage Based on Master-Slave Game.

Optimizing the operation of photovoltaic (PV) storage systems is crucial for meeting the load demands of parks while minimizing curtailment and enhancing economic efficiency. This paper proposes a multi-scenario collaborative optimization strategy for PV storage systems based on a master-slave game model. Three types of energy storage system (ESS) application scenarios are designed to comprehensively stabilize PV fluctuations, compensate for load transfers, and participate in the frequency regulation (FR) market, thereby optimizing the overall operational strategy of PV storage systems in parks. The upper-level objective is to maximize the park operators' profit, while the lower-level objective is to minimize the user's power supply costs. Case studies demonstrate that this strategy can significantly increase the economic benefits for park operators by 25.8%, reduce user electricity expenditures by 5.27%, and lower curtailment through a load response mechanism, thereby promoting the development and construction of PV storage parks.

Параметры, влияющие на стоимость продукции металлургических и трубопрокатных производств в различных регионах РФ

The article considers the market of oil products, the prices of which directly affect the cost of production of the strategically important pipe rolling industry, by years and regions. The geography of metallurgical enterprises location on the territory of the Russian Federation and regional zones are analyzed. Generalized indicators of the Russian steel pipe market are structured by key indicators and federal districts depending on average consumer energy prices in the domestic market. The geographical factor that most strongly influences the final cost of power supply to pipe rolling enterprises-consumers in price zones was identified.

A fast and genotype-independent in planta Agrobacterium-mediated transformation method for soybean

Efficient genotype-independent transformation and genome editing are highly desirable for plant biotechnology research and product development efforts. We have developed a novel approach to enable fast, high-throughput, and genotype-flexible Agrobacterium-mediated transformation using the important crop soybean as a test system. This new method is called GiFT (genotype-independent fast transformation) and involves only a few simple steps. The method uses germinated seeds as explants, and DNA delivery is achieved through Agrobacterium infection of wounded explants as in conventional in vitro-based methods. Following infection, the wounded explants are incubated in liquid medium with a sublethal level of selection and then transplanted directly into soil. The transplanted seedlings are then selected with herbicide spray for 3 weeks. The time required from initiation to fully established healthy T0 transgenic events is about 35 days. The GiFT method requires minimal in vitro manipulation or use of tissue culture media. Because the regeneration occurs in planta, the GiFT method is highly flexible with respect to genotype, which we demonstrate via successful transformation of elite germplasms from diverse genetic backgrounds. We also show that the soybean GiFT method can be applied to both conventional binary vectors and CRISPR-Cas12a vectors for genome editing applications. Analyses of T1 progeny demonstrate that the events have a high inheritance rate and can be used for genome engineering applications. By minimizing the need for tissue culture, the novel approach described here significantly improves operational efficiency while greatly reducing personnel and supply costs. It is the first industry-scale transformation method to utilize in planta selection in a major field crop.

Effects of black soldier fly (Hermetia illucens) larvae meal on production performance, egg quality, and physiological properties in laying hens: A meta-analysis.

The primary components of fat and protein in chicken diets are fishmeal and soybean; however, due to limited supply and high costs, several efforts have been made to utilize alternative feedstuffs. The potential of black soldier fly larvae (BSFL) as a substitute for fat and protein has been extensively studied, but the findings are not consistent. This study used a meta-analysis approach to investigate the integrated efficacy of BSFL supplementation on laying hen production performance, egg quality, and physiological properties. The articles were retrieved from PubMed, Scopus, ScienceDirect, Cochrane Library, and ProQuest. The retrieved references were examined for potential inclusion. The relevant findings of the included studies were then extracted. Fixed-effects, standard mean difference, 95% confidence intervals, and heterogeneity models were analyzed using the Review Manager website version (Cochrane Collaboration, UK). A total of 24 papers from 17 different nations across five continents have been selected for meta-analysis out of the 3621 articles that were reviewed. The current meta-analysis demonstrated that providing BSFL meals significantly favored feed efficiency, haugh units, albumen quality, eggshell quality, serum glucose, and lipid levels. In addition, significant trends in alanine transaminase, alkaline phosphatase, magnesium, phosphorus, chlorine, and iron levels were observed in blood urea nitrogen, uric acid, creatinine, lactate dehydrogenase, creatine kinase, glutathione peroxidase, and malondialdehyde. On the other hand, it was revealed that there was no favorable effect on weight gain, laying, yolk quality, and hematological profile. The meta-analysis confirmed that BSFL meals can be utilized to optimize feed efficiency, haugh units, albumen, eggshell quality, liver, renal, and cellular physiology of laying hens, although they did not significantly increase body weight gain, laying production, and hematological profiles.

Ultra‐Lean Silver Screen‐Printing for Sustainable Terawatt‐Scale Photovoltaic

As the photovoltaics industry approaches the terawatt (TW) manufacturing scale, the consumption of silver in screen‐printed contacts must be significantly reduced for all cell architectures to avoid risks of depleting the global silver supply and substantial cost inflations. With alternative metallization techniques (e.g., plating) facing their own challenges for mass production, advancements in the mainstream screen‐printing technology to accelerate the pace of silver reductions are urgently needed. This work presents a silver‐lean screen‐printed contact scheme, providing scope for substantial reductions in silver consumption based on existing industrial screen‐printing capabilities. The initial testing of such a design leads to the fabrication of 24.04% efficient large‐area TOPCon solar cells with 9 mg W−1 silver consumption compatible with existing soldering‐based interconnection technologies, corresponding to a 25%rel reduction in silver usage compared to standard industrial screen‐printed TOPCon solar cells. Upon further optimization in pattern designs and fabrication processes, this silver‐lean design offers a promising pathway toward ultra‐low silver consumption of less than 2 mg W−1 for screen‐printed TOPCon solar cells without sacrificing efficiency.

Enhancing sustainable energy production in the Canary Islands: Valorization of local biomass resources through thermochemical processes

Diverse biomass sources from the Canary Islands (vineyard, tomato plant residues, Canary pine needles and Pennisetum setaceum) were assessed due to their local abundance, availability, and low supply cost. Based on their physico-chemical properties, various thermochemical processes were conducted to assess their thermal degradation behaviour, using simultaneous thermal analysis, and their potential for energy production. The results indicate that while tomato plant biomass is unsuitable for thermochemical processes because of its elevated ash content and limited volatile matter, the other biomass sources show promising potential for pyrolysis and gasification, characterized by high fixed carbon content and reactivity. The yearly production of residual biomass in the Canary Islands was quantified at 87,253 tonnes. This biomass could generate an estimated 88.5 GWh of electricity annually. Considering that electricity consumption in the Canary Islands reached 8750 GWh in 2023, biomass-derived electricity could contribute approximately 1.0 % to the archipelago's energy needs. These findings highlight the significant role of local biomass resources in advancing renewable energy goals and reduce dependence on non-renewable sources, promoting a greener energy landscape for the Canary Islands.

Research and economic evaluation on novel pulse superconducting magnet power supply topology with energy storage for fusion devices

Large capacity fusion devices power supply poses a significant challenge to the stability of power grid, as it can lead to power outages and jeopardize the safety of fusion devices. And traditional distribution methods result in a significant waste of resources. This paper proposes novel topologies with integrated energy storage. In these topologies, high-amplitude pulsed power is supplied by the energy storage devices, while low-amplitude stable power is obtained from the grid. This decouples the pulsed power from power grid, and significantly reducing its impact. Moreover, it can reduce the design capacity of distribution equipment and lowers investment costs. To optimize the deployment of the energy storage device, a hybrid topology is proposed, which further reducing the cost of the novel power supply. Additionally, a cost model for the fusion power supply is developed and validated using simulation data from ITER. Through the case study shows that the HEPS topology saves more than 10 % of the investment cost and about 60 % of the annual operating cost compared to the traditional converter topology.