Maximum Cost Research Articles

Influence of Sulphur and Zinc on Yield, Yield Attributes and Economics of Baby Corn (Zea mays L.)

A Field experiment was conducted during Zaid season of 2023 at Crop Research Farm Department of Agronomy. The objective of this study is to asses the influence of sulphur and zinc on yield attritibutes of baby corn and to evaluate the economics of different treatment combinations taken. The treatments consisted of 3 levels of Sulphur viz., (15, 30 and 45 kg/ha) and 3 levels of Zinc viz., (10, 20 and 30 kg/ha) along with recommended doses of nitrogen, phosphorus and potash as control (60- 60-40 kg N-P-K/ha). The experiment was laid out in a Randomized Block Design with 10 treatments and replication thrice. Application of Sulphur 45 kg/ha along with Zinc 30 kg/ha (Treatment 9) recorded maximum cob yield with husk (10.6 t/ha), cob yield without husk (3.91 t/ha), green fodder yield (28.43 t/ha). The aforesaid treatment also recorded maximum gross returns (1,43,144.00 INR/ha), net returns (955,19.00 INR/ha) and Benefit cost ratio (2.01).

Economic burden of chronic obstructive pulmonary disease and post-tuberculosis sequelae in low- and middle-income countries: a database compiled from a systematic review and meta-analysis

BackgroundChronic obstructive pulmonary disease (COPD) and tuberculosis (TB) impose a substantial economic burden globally. This systematic review summarised the evidence on the costs of COPD, including post-TB diseases in low-...

Intelligent decision modeling for optimizing railway cold chain service networks under uncertainty

Railway cold chain service network design (RCC-SND) aims to optimize the utilization of stations and lines as well as train allocations in a manner that minimizes costs while satisfying the service requirements of shippers. Furthermore, the uncertainties associated with freight demand, transportation costs, quality loss, station handling capacity, and arc capacity make the RCC-SND a complex decision-making problem. To tackle this challenge, we first formulate a Mixed-Integer Nonlinear Programming (MINLP) model to determine hub locations, freight wagon flows, and service frequency. To cope with uncertain parameters with varying degrees of uncertainty incorporated in the model, we extend the problem using fuzzy programming and further convert it to its crisp counterpart. A real-world cases study in Southwest China is performed to validate the proposed model, whose results provide different strategies for decision-makers with varying preferences. There are some main findings: As the number of hubs increases from 5 to 6, a maximum total cost savings of 1.99% can be achieved. Railway operators may opt for different decision preferences, for decisions prioritizing economic efficiency, the cost can decrease by 2.69% compared to deterministic optimization.

Measuring homoplasy I: comprehensive measures of maximum and minimum cost under parsimony across discrete cost matrix character types.

Here, we propose, prove mathematically and discuss maximum and minimum measures of maximum parsimony evolution across 12 discrete phylogenetic character types, classified across 4467 morphological and molecular datasets. Covered character types are: constant, binary symmetric, multistate unordered (non-additive) symmetric, multistate linear ordered symmetric, multistate non-linear ordered symmetric, binary irreversible, multistate irreversible, binary Dollo, multistate Dollo, multistate custom symmetric, binary custom asymmetric and multistate custom asymmetric characters. We summarize published solutions and provide and prove a range of new formulae for the algebraic calculation of minimum (m), maximum (g) and maximum possible (gmax) character cost for applicable character types. Algorithms for exhaustive calculation of m, g and gmax applicable to all classified character types (within computational limits on the numbers of taxa and states) are also provided. The general algorithmic solution for minimum steps (m) is identical to a minimum spanning tree on the state graph or minimum weight spanning arborescence on the state digraph. Algorithmic solutions for character g and gmax are based on matrix mathematics equivalent to optimization on the star tree, respectively for given state frequencies and all possible state frequencies meeting specified numbers of taxa and states. We show that maximizing possible cost (gmax) with given transition costs can be equivalent to maximizing, across all possible state frequency combinations, the lowest implied cost of state transitions if any one state is ancestral on the star tree, via the solution of systems of linear equations. The methods we present, implemented in the Claddis R package, extend to a comprehensive range, the fundamental character types for which homoplasy may be measured under parsimony using m, g and gmax, including extra cost (h), consistency index (ci), retention index (ri) or indices based thereon.

Combinatorial algorithms for restricted inverse optimal value problems on minimum spanning tree under weighted [formula omitted] norm

We study the restricted inverse optimal value problem on minimum spanning tree under weighted l1 norm. In a connected edge-weighted network G(V,E,w), we are given a spanning tree T0, a cost vector c and a value K. We aim to obtain a new weight vector w̄ satisfying the bounded constraint such that T0 is a minimum spanning tree under w̄ whose weight is just K. We focus on minimizing the modification cost under weighted l1 norm. We first convert its mathematical model into a linear programming problem (P). Then we solve its dual problem (D) by a sub-problem (Dz∗) corresponding to the critical value z∗ which can be calculated by a binary search method. Impressively the sub-problem Dz for z∈R can be transformed into a minimum cost flow problem on an auxiliary network. Finally, we propose an O(|E|2|V|2log|V|log(|V|cmax)) algorithm, where cmax is the maximum cost of the vector c.

The Impact of Cost of Living on the Quality of Life of Cystic Fibrosis Patients: A Study in Greece.

Introduction Cystic fibrosis (CF) leads to the impairment of multiple essential organs and systems in the human body. The objective of this study was to analyze the financial consequences of having cystic fibrosis (CF) on patients, evaluate their general state of health, and specifically investigate the impact of living expenses on their quality of life. Methods The data were collected using three tools and a form for personal information entry. The first questionnaire wasemployed to quantify fluctuations in patients' cost of living. The Greek variant of the Short Form Questionnaire-36 (SF-36)and the Greek version of the Cystic Fibrosis Quality of Life (CFQoL)were implemented to assess quality of life.Statistical significance was set at p < 0.05, and analyses were conducted using SPSS statistical software. Results The study obtained a response rate of 93.2%, with 105 participants consenting to and effectively finishing the questionnaire. The mean age of the patients was 32.1 years, with 46.7% being female and 53.3% being male. Medication was being administered to 46.7% of the patients. The condition incurred an average cost of 767€ in the preceding semester. The maximum cost was 1007€. Patients with a higher monthly family income and those who were taking medication exhibited superior physical performance and functional capacity. Conclusion The research emphasizes that implementing causative treatment and minimizing hospitalizations can potentially enhance life satisfaction. The findings suggest possible approaches to enhance the quality of life in people with cystic fibrosis, in conjunction with the implementation of novel or enhanced treatment modalities.

Relative distances approach for multi-traveling salesmen problem

In this paper, we present a novel approach to addressing the Multi-Traveling Salesman Problem (MTSP), a complex optimization challenge involving the simultaneous fulfillment of multiple tasks such as cargo delivery and warehouse placement by multiple autonomous agents. In general there are two primary objectives to be achieved: minimizing the total path cost and minimizing the maximum cost incurred by agents, also known as makespan. While our primary focus centers on cost minimization, prioritizing this aspect alone often amplifies makespan. Our approach strikes a balance by ensuring that makespan remains within a reasonable threshold. Given the problem’s combinatorial nature, attaining cost-optimal solutions proves infeasible under current constraints. Hence, our emphasis shifts towards swift solution discovery to align with practical applicability. Consequently, we posit that the third pivotal objective is to curtail complexity and expedite solution acquisition, thereby enhancing the problem’s real-world viability. The Multi-Traveling Salesman Problem (MTSP) is typically approached in two distinct phases. In the initial phase, tasks are allocated to salesmen using various methods (such as K-Means or DBSCAN). The second phase involves determining the optimal routes for each salesman, a problem identical to the classic Traveling Salesman Problem (TSP). Our novel heuristic approach integrates these phases into a single method through our relative distance model. This model facilitates the easy addition and removal of tasks within the problem space and enables real-time scheduling.

Impact of residential heat pumps and photovoltaics on low-voltage grid reinforcements under varying insulation levels

The European Union’s 2050 climate-neutrality goal necessitates extensive deployment of low-carbon technologies (LCTs) like heat pumps and rooftop photovoltaic systems in dwellings. However, integrating these into low-voltage (LV) grids can cause grid issues (e.g., voltage deviation, feeder overloading), often requiring grid reinforcements. This study uses a techno-economic approach to calculate the grid reinforcement costs under various residential LCT integration and insulation scenarios in representative rural and urban grids in Germany and Italy. Two cost calculation methods (maximum and average) are compared. Results indicate that, compared to the average cost calculation method, the maximum cost calculation method generally gives a higher cost under the same LCTs integration rate. Increasing LCT integration raises costs while improving residential dwelling insulation reduces them. The estimated reinforcement cost for rural and urban zones in Germany and Italy is significant and can be up to more than a billion euros. Improving residential insulation levels can reduce costs significantly for both German and Italian grids. The results and methodology presented can help grid operators and policymakers deploy LCTs in LV grids resiliently and cost-effectively.

Cost Variation Analysis of Hypolipidemic Drugs Currently Available in Indian Pharmaceutical Market

42% of all fatalities worldwide resulting from non-communicable diseases (NCD) are attributable to cardiovascular illnesses. The availability of several brands and generic medications causes a wide range in the pricing at which they are sold. This study was conducted to raise awareness among health care workers and patients about the cost difference between different brands of the same hypolipidemic drug, so that, if possible, a cheaper effective brand can be prescribed to ensure better patient adherence. Maximum retail price (MRP) of various hypolipidemic drugs of same strength and dosage forms manufactured by different pharmaceutical companies were obtained from various online and offline sources. The maximum and minimum cost of 10 tablets/capsules were noted. The cost ratio and percentage cost variation were calculated for single drug and fixed dose combinations. The ceiling price (as per DPCO) of hypolipidemics (as per national list of essential medicines) was compared with their maximum cost. Maximum cost variation observed in case of single drug was Atorvastatin 10mg (3043.9393%), and in case of FDC was seen in Rosuvastatin 10mg + Aspirin75mg (561.341%). This study led us to the conclusion that the majority of hypolipidemic medications should be governed by DPCO in order to lessen the economic load of healthcare services on the Indian population. Keywords: Pharmacoeconomic, Cost variation, Hypolipidemic, Statins

Cost Analysis of DPP4 and SGLT2 Inhibitors - “Dilemma of the Prescribing Physician - Which Brand to Choose?”

Diabetes mellitus (DM) is a complex and heterogeneous group of chronic metabolic diseases causing dreaded complications increasing human sufferings, and a costly disease to manage in low/middle-income countries, which is burdensome for the most vulnerable populations, cause financial strain on individuals and family members. The purpose of the study was to analyze the price variability of different brands of sodium glucose co-transporter 2 inhibitors (SGLT2i) and dipeptidyl peptidase 4 inhibitors (DPP4i) and their combinations. The present study was an observational analytical one. The highest and lowest price of each SGLT2i and DPP4i in the same strength marketed by different pharmaceutical companies, were collected from Current Index of Medical Specialties (Jan–April 2023), Indian Drug Review (IDR 2023), Drug Today (April – July 2023) drug manuals. Calculations were done in Indian Rupees per 10 tablets/capsules. For each drug, the cost ratio and percentage of price variation (PPV) were calculated. Among DPP4i, sitagliptin 50 mg has a maximum cost ratio (5.30) and PPV (1083.66%), while sexagliptin 2.5 mg has minimal cost ratio (1.55) and PPV (55.08%). Among SGLT2i, dapagliflozin 5 mg had the highest cost ratio (10.79) and PPV (978.79%) and remogliflozin100 mg had the lowest cost ratio (1.57) and PPV (56.94%) and among combinations dapagliflozin 10 mg+ metformin 500 mg has the highest cost ratio (6.66) and PPV (565.75%), while empagliflozin 12.5 mg + metformin 500 mg has the lowest cost ratio (1.04) and PPV (4.00%). Current study shows large differences in cost ratio as well as PPV between brands. To reduce the financial burden and treatment adherence, physicians must prescribe less expensive drugs. Keywords: Cost analysis, Cost ratio, Percentage of price variation, Diabetes mellitus

Development and Quality Analysis of Pineapple (Ananas comosus L.) Sweetmeat Blend with Bottle Gourd (Lagenaria siceraria)

The present investigation was carried out at Post Harvest Laboratory of Department of Horticulture, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh during the year 2022-2024. The experiment was conducted in Completely Randomized Design (CRD). Under this experiment, overall, 8 treatments were taken and 3 replications of each to evaluate physio-chemical analysis, organoleptic properties and cost of formulation of Pineapple Sweetmeat at different storage days. The sweetmeat samples were stored at ambient temperature (28 ± 5 °C) for 45 days and results were noted after every 15 days intervals. On the basis of results obtained during the present investigation T6 (Pineapple 250gm/kg + Bottle gourd 750gm/kg + Jaggery was found superior in terms of Pineapple Sweetmeat on physio-chemical properties viz TSS, Acidity, Moisture and Ascorbic acid followed by T3 (Pineapple 500gm/kg + Bottle gourd 500gm/kg + Sugar) that was found to be superior in terms of Pineapple sweetmeat on all organoleptic tests viz. Colour and Appearance, Taste and Flavour, Body and Texture and Overall acceptability hence it was found that T6 and T3 were found to be superior in terms of physico-chemical properties and the maximum Benefit cost ratio (1.33) was found for T3 (Pineapple 500gm/kg + Bottle gourd (500gm/kg + Sugar). Hence T3 was found to be more superior followed by T6.

Performance of Different Hybrids of Cucumber (Cucumis sativus L.) in Terms of Growth, Yield and Quality

The present investigation was carried out at the Department of Horticulture, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj, Uttar Pradesh, during the Rabi season 2023, with a view to check the performance of different cucumber hybrids under agro-climatic conditions. The experiment was laid in a randomized block design with eight hybrids and three replicats. The hybrids comprised V1, V2, V3 (LHC 1395); V4, V5, V6 and V7 (CCH-1). From the above experimental finding it was concluded that the hybrid Niyamat performed best in terms of growth parameters like vine length at harvest (182.62 cm), maximum number of leaves (15.93) in earliness in maturity (61.00 days for first fruit harvest). Hybrid CCH-1 performed the best for yield parameters, such as the highest number of fruits per plant (14.59 fruits), maximum fruit length (16.72 cm), fruit diameter (3.60 cm), and fruit yield per vine (2.60 kg/vine). It showed best performance for TSS (3.15 °Brix). The maximum Benefit cost ratio was recorded for Hybrid CCH-1 at 2.13.

Economics of Fieldpea (Pisum sativum L.) as Influenced by Phosphorus Levels and Bio-fertilizers in Central Plains of Uttar Pradesh, India

A field experiment was conducted at the student instructional farm of CSAUA&amp;T, Kanpur, during the Rabi season of 2021-22 and 2022-23. Sandy loam was the texture of the experimental soil. There are twelve treatment involving combinations of phosphorus and biofertilizers with three replication of factorial randomized block design (FRBD). A fieldpea variety IPFD 6-3 was planted according to recommended agronomic practices. The results of these studies indicate that fieldpea cultivation over a two-year period is consistent with T12 (P90 R1 PSB1), the most economically effective treatment and also recorded the highest economics parametric values i.e., maximum cost of cultivation of ₹35850 &amp; ₹36700, gross return of ₹ 106055 &amp; ₹118535, net return of ₹70205 &amp; ₹ 81835 and benefit to cost ratios were 1.96 &amp; 2.23 followed by the treatment T11.

Genetic Variability of Black Cumin (Nigella sativa L.) under Climatic Condition of Prayagraj

An Experiment on Black cumin was conducted during September to March 2023-2024, in horticulture Research field, Department of Horticulture, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, and Technology &amp; Sciences Prayagraj(UP) India. The results of the investigation, regarding the performance of the 7 variety of black cumin i.e. NS-44, NS-32, Ajmer Nigella-1, Ajmer Nigella-20, Azad kalonji, Local variety -1, Local variety- 2 obtained from different sources to find out the best performance in terms of growth and yield in Prayagraj agro-climatic conditions. The experiment was conducted in Randomized Block design, were each variety replicated thrice the results from the present investigation concluded that black cumin genotype Azad kalonji was recorded with maximum number of flowers/plant (78.33), Seed/ capsule (93.67), Seed yield (1.85 t/ha) and with maximum gross return, net return and cost Benefit Ratio of (3.75) which was found to be more productive and economically viable.

The Maximum Attainable Flow and Minimal Cost Problem in a Network

This paper, presents an efficient algorithm that solves such a large class of optimization problems. Ford-Fulkerson determines the maximum flow in a network by iteratively augmenting flow paths until no further improvement is possible. On the other hand, Dijkstra&amp;apos;s algorithm excels in finding the shortest path in a weighted graph, making it suitable for minimizing costs in network traversal. However, this paper simultaneously optimizes both objectives (flow and cost) dependently in unique iterations by considering all constraints and objectives holistically. The aim of this work is to develop efficient algorithms that can handle complex optimization problems in transportation, network design, and other fields, ultimately improving resource utilization and minimizing costs as its crucial for enhancing decision-making processes, improving efficiency in resource utilization, and achieving cost savings in diverse applications ranging from transportation networks to production planning. This paper deals about formulating the linear programming for the optimizations problems and finding the maximum amount of flow that can be sent from a source node to a sink node while minimizing the total cost of sending that flow by using simplex method (Two phase method). Through computational experiments and case studies, everybody demonstrate the effectiveness and efficiency of the proposed approach in solving real-world network flow problems. Our method yields efficient algorithms with in smallest numbers of iterations and time that enable the optimal allocation of resources within networks, achieving both maximum flow and minimum cost simultaneously.

Cost-aware quantum-inspired genetic algorithm for workflow scheduling in hybrid clouds

Cloud computing delivers a desirable environment for users to run their different kinds of applications in a cloud. Numerous of these applications (tasks), such as bioinformatics, astronomy, biodiversity, and image analysis, are deadline-sensitive. Such tasks must be properly allocated to virtual machines (VMs) to avoid deadline violations, and they should reduce their execution time and cost. Due to the contradictory environment, minimizing the application task's completion time and execution cost is extremely difficult. Thus, we propose a Cost-aware Quantum-inspired Genetic Algorithm (CQGA) to minimize the execution time and cost by meeting the deadline constraints. CQGA is motivated by quantum computing and genetic algorithm. It combines quantum operators (measure, interference, and rotation) with genetic operators (selection, crossover, and mutation). Quantum operators are used for better population diversity, quick convergence, time-saving, and robustness. Genetic operators help to produce new individuals, have good fitness values for individuals, and play a significant role in preserving the evolution quality of the population. In addition, CQGA used a quantum bit as a probabilistic representation because it has higher population diversity attributes than other representations. The simulation outcome exhibits that the proposed algorithm can obtain outstanding convergence performance and reduced maximum cost than benchmark algorithms.

Topology-aware Parallel Joins

We study the design and analysis of parallel join algorithms in a topology-aware computational model. In this model, the network is modeled as a directed graph, where each edge is associated with a cost function that depends on the data transferred between the two endpoints and the link bandwidth. The computation proceeds in synchronous rounds and the cost of each round is measured as the maximum cost over all the edges in the network. Our main result is an asymptotically optimal join algorithm over symmetric tree topologies. The algorithm generalizes prior topology-aware protocols for set intersection and cartesian product to a binary join over an arbitrary input distribution with possible data skew.

Artificial ground reflector size and position effects on energy yield and economics of single‐axis‐tracked bifacial photovoltaics

AbstractArtificial ground reflectors improve bifacial energy yield by increasing both front and rear‐incident irradiance. Studies have demonstrated an increase in energy yield due to the addition of artificial reflectors; however, they have not addressed the effect of varying reflector dimensions and placement on system performance and the impact of these parameters on the reflectors' financial viability. We studied the effect of high albedo (70% reflective) artificial reflectors on single‐axis‐tracked bifacial photovoltaic systems through ray‐trace modeling and field measurements. In the field, we tested a range of reflector configurations by varying reflector size and placement and demonstrated that reflectors increased daily energy yield up to 6.2% relative to natural albedo for PERC modules. To confirm the accuracy of our model, we compared modeled and measured power and found a root mean square error (RMSE) of 5.4% on an hourly basis. We modeled a typical meteorological year in Golden, Colorado, to demonstrate the effects of artificial reflectors under a wide range of operating conditions. Seventy percent reflective material can increase total incident irradiance by 1.9%–8.6% and total energy yield by 0.9%–4.5% annually after clipping is considered with a DC–AC ratio of 1.2. Clipping has a significant effect on reflector impact and must be included when assessing reflector viability because it reduces reflector energy gain. We calculated a maximum viable cost for these improvements of up to $2.50–4.60/m2, including both material and installation, in Golden. We expanded our analysis to cover a latitude range of 32–48°N and demonstrated that higher‐latitude installations with lower energy yield and higher diffuse irradiance content can support higher reflector costs. In both modeling and field tests, and for all locations, the ideal placement of the reflectors was found to be directly underneath the module due to the optimized rear irradiance increase.

Selection and integration of adjustable load in multiple scenarios

In the context of the “carbon peaking and carbon neutrality goals”, the new electricity systems are evolving towards source-load friendly interactions. At the same time, the increasing necessity for adjustable loads to participate in the power balance of the new electricity systems is highlighted. Consequently, a large-scale source-grid-load design scheme is proposed. It employs three independent communication channels to facilitate communication between users and intelligent grid-load terminals. Based on analysis of the individual loads and equipment characteristics of each user, principles for user shunt load access principle and adjustable loads are formulated by combining the maximum duration, frequency constraints, and compliance costs. Furthermore, it proposes construction plans for both the customer side in a single distribution room and the customer side distributed across different locations. According to the experimental analysis of 245 users, the response time of the experimental system is less than 600 ms. These advancements enhance the emergency response speed and responsiveness, contributing to the advancement of precise, real-time, and lean management of the demand side of the power grid.

Comparative Economics of Different Management Tactics by Novel Insecticides against Pest Complex on Capsicum (Capsicum annuum L.) under Protected Conditions

Field experiment was conducted under shade net house at Hi-Tech Horticulture Farm, Rajasthan Agricultural Research Institute, Durgapura (Sri Karan Narendra Agriculture University, Jobner), Jaipur, Rajasthan to work out the economics and cost benefit ratio of different management strategies by three spraying of eleven bio-rationale and newer pesticides against Yellow Mite, Polyphagotarsonemus latus (Banks), thrips, Scirtothrips dorsalis Hood, aphids (Aphis gossypii Glover, Myzus persicae Sulzer), Whitefly, Bemisia tabaci (Gennadius) and Beat army worm, Spodoptera exigua (Hubner) during summer 2014 and 2015 on capsicum (Capsicum annuum L.). The result on the basis of pooled data indicated that maximum net profit of Rs 77185/ha was obtained in the treatment of fipronil 0.005% with the yield of 51.46 q/ha followed by emamectin benzoate 0.002% (Rs 67422/ha) with the yield of 49.77 q/ha. The minimum net profit of Rs 23840/ha was recorded in the treatment of NSKE 5% followed by azadirachtin 0.0003% (Rs 29876). The net profit ranging from Rs 53613/ha to Rs 60263/ha was computed in the treatment of acephate (Rs 53613/ha), spiromesifen (Rs 59971/ha), spinosad (Rs 58262/ha) and indoxacarb (Rs 60263/ha), whereas, Rs 39125/ha to 41476/ha was found in propargite and novaluron. The maximum incremental cost benefit ratio (1:20.23) was found in fipronil (0.005%) followed by 1:17.99 in the treatment of acephate (0.075%). The minimum ICBR (1:4.64) was recorded in the treatments of novaluron followed by spinosad (1:5.96). Study revealed that three spray of fipronil 5 SC @ 1 ml/l or emamectin benzoate 5 SG @ 0.4 g/l can be suggested to the farmers for the management of pest complex on capsicum under shade net house conditions during summer for off season production.