Search Results (4,239)

Phosphorus (P) is critical for maximizing agricultural production and represents an appreciable input cost. Geologic sources of P that are most easily mined are a finite resource, while P transported from agricultural land to surface waters contributes to water quality degradation. Improved knowledge of P timing needs by corn (maize) can help inform management decisions that increase P use efficiency, which is beneficial to productivity, economics, and environmental quality. The objective of this study was to evaluate P application timing on the growth and yield components of corn. Corn was grown in a sand-culture hydroponics system that eliminated confounding plant–soil interactions and allowed for precise control of nutrient availability and timing. All nutrients were applied via drip irrigation and were therefore 100% bioavailable. Eight P timing treatments were tested using “low” (L) and “sufficient” (S) P concentrations. In each of the three growth phases, solution P application levels were changed or maintained, resulting in eight possible combinations, LLL, LLS, LSL, LSS, SLL, SSL, SLS, and SSS, where the first, second, and third letters indicate P solution application levels from planting to V6, V6 to R1, and R1 to R6, respectively. All other nutrients were applied at sufficient levels. Sacrificial samples were harvested at V6, R1, and R6 and evaluated for various yield parameters. Plants that received sufficient P between V6 and R1 produced a significantly higher grain yield than plants that received low P between V6 and R1 regardless of the level of P supply before V6 or after R1. The grain yield of plants that received sufficient P only between V6 and R1 did not differ significantly from plants that received only sufficient P (SSS), due to (1) a greater ear P concentration at R1; (2) an efficient remobilization of assimilates from the stem and leaf to grains between R1 and R6 (source–sink relationship); (3) a higher kernel/grain weight; and (4) less investment into root biomass. Full article

Conventional oil-based emulsions used in hard-turning processes present significant environmental and economic challenges, including high waste generation and hazardous disposal requirements. In response, cryogenic CO₂ cooling has gained attention as a sustainable alternative, offering improved productivity, reduced tool wear and a diminished environmental footprint. While technical advances have been reported, the industrial adoption of cryogenic cooling is still limited due to the lack of clear data on its actual viability. This paper moves beyond the analysis of the technical performance of cryogenic CO₂ cooling analyzed in previous works to conduct a detailed evaluation of its environmental and economic performance when machining roller bearing components with pCBN tools on a hard-turning installation. Utilizing Life Cycle Assessment (LCA) and Return-on-Investment (ROI) methodologies, this study compares cryogenic CO₂ with traditional cooling methods, quantitatively assessing the environmental impact and economic viability across different manufacturing scenarios. The findings reveal that cryogenic cooling can outperform conventional cooling regarding both environmental impact and cost-effectiveness thanks to the tool life improvements provided by cryogenic cooling, specifically in cases where high tool consumption is generated during hard-turning operations. These results provide critical insights for selecting cooling strategies during the design phase of industrial turnkey projects, highlighting the potential of cryogenic CO₂ as a superior solution for sustainable and efficient hard-turning operations. Full article

This paper establishes a theoretical framework for understanding the connotations of industrial basic capacity. It employs models from economic growth theory to derive indices for assessing industrial basic capacity and exploring the economic correlations among its influencing factors. Additionally, it measures the industrial basic capacity indices of 17 subsectors across 9 major industrial countries from 2000 to 2020 using OECD data. The findings reveal that from 2000 to 2020, the Chinese manufacturing industry has surpassed the United States, becoming the global leader. Specifically, within the 17 subsectors, 9 are globally ranked first, with 7 nearing advanced levels, and only 1 facing relative backwardness. Chinese manufacturing industry’s enhanced basic capacity is attributed to advantages in cost competitiveness and scale. However, significant disparities persist in technological input and industrial linkages with advanced nations. The decline in basic capacity among developed countries stems primarily from diminished value chain profitability due to inadequate investment. Sustainable improvement in industry basic capacity necessitates concurrent advancements in value chain profitability, fixed asset investment, technological levels, industrial linkages, and market scale. Overreliance on cost advantages or advanced technology poses substitution risks. Moreover, this paper underscores the limitations of exclusively relying on current data to assess global industrial basic capacity, advocating for a greater historical perspective. To strengthen the Chinese manufacturing industrial basic capacity within the global value chain, the Chinese manufacturing industry must enhance technological inputs, reduce the operational costs of enterprises, and elevate the degree of openness. Full article

Small and micro-businesses often struggle with poor data accuracy due to a lack of dedicated labor force for non-core business functions. The required efforts and costs associated with improving data accuracy, such as setting up and operating an adequate inventory management system, are unpredictable for these businesses. Despite the data-intensive nature of operating specialized software like MES and WMS, the decision to invest in excessive data manipulation can be challenging for micro-entities, even with the potential benefits. This study aims to empirically determine the challenges, risks, and other non-financial decision factors micro-enterprises face when establishing effective data management and utilization practices. A data model was developed based on interviews with 17 small business manufacturers and service companies to support the essential data entry requirements of micro-businesses. The findings support the concept of a SAAS (Software as a Service) product tailored to the needs of these businesses. Furthermore, this research highlights the under-researched areas of logistics processes and data management in small businesses. Full article

The selection of the optimal 35 kV network structure is crucial for modern distribution networks. To address the problem of balancing investment costs and reliability benefits, as well as to establish the target network structure, firstly, the investment cost of the distribution network is calculated based on the determined number of network structure units. Secondly, reliability benefits are measured by combining the comprehensive function of user outage losses with the System Average Interruption Duration Index (SAIDI). Then, a multi-objective planning model of the network structure is established, and the weighted coefficient transformation method is used to convert reliability benefits and investment costs into the total cost of power supply per unit load. Finally, by using the influencing factors of the network structure as the initial population and setting the minimum total cost of the unit load as the fitness function, the DE algorithm is employed to obtain the optimal grid structure under continuous load density intervals. Case studies demonstrate that different load densities correspond to different optimal network structures. For load densities ranging from 0 to 30, the selected optimal network structures from low to high are as follows: overhead single radial, overhead three-section with two ties, cable single ring network, and cable dual ring network. Full article

Pandemics of infectious disease and growing anti-microbial resistance (AMR) pose major threats to global health, trade, and security. Conflict and climate change compound and accelerate these threats. The One Health approach recognizes the interconnectedness of human, animal, and environmental health, but is grounded in the biomedical model, which reduces health to the absence of disease. Biomedical responses are insufficient to meet the challenges. The COVID-19 pandemic is the most recent example of the failure of this biomedical model to address global threats, the limitations of laboratory-based surveillance, and the exclusive focus on vaccination for disease control. This paper examines the current paradigm through the lens of polio and the global campaign to eradicate it, as well as other infectious threats including mpox and drug-resistant tuberculosis, particularly in the context of armed conflict. Decades before vaccines became widely available, public health measures—ventilation, chlorination, nutrition and sanitation— led to longer, healthier, and even taller lives. Chlorine, our primary tool of public health, conquered cholera and transformed infection control in hospitals. The World Health Organization (WHO), part of the One Health alliance, focuses mainly on antibiotics and vaccines to reduce deaths due to superbugs and largely ignores the critical role of chlorine to control water-borne diseases (including polio) and other infections. Moreover, the One Health approach ignores armed conflict. Contemporary wars are characterized by indiscriminate bombing of civilians, attacks targeting healthcare, mass displacement and lack of humanitarian access, conditions which drive polio outbreaks and incubate superbugs. We discuss the growing trend of attacks on healthcare and differentiate between types: community-driven attacks targeting vaccinators in regions like Pakistan, and state-sponsored attacks by governments such as those of Syria and Russia that weaponize healthcare to deliberately harm whole populations. Both fuel outbreaks of disease. These distinct motivations necessitate tailored responses, yet the WHO aggregates these attacks in a manner that hampers effective intervention. While antimicrobial resistance is predictable, the escalating pandemic is the consequence of our reliance on antibiotics and commitment to a biomedical model that now borders on pathological. Our analysis reveals the international indenture to the biomedical model as the basis of disease control is the root driver of AMR and vaccine-derived polio. The unique power of vaccines is reduced by vaccination-only strategy, and in fact breeds vaccine-derived polio. The non-specific effects of vaccines must be leveraged, and universal vaccination must be supplement by international investment in water chlorination will reduce health costs and strengthen global health security. While vaccines are an important weapon to combat pandemics and AMR,, they must be accompanied by the entire arsenal of public health interventions. Full article

Fused deposition modeling (FDM) is well suited for microfluidic prototyping due to its low investment cost and a wide range of accessible materials. Nevertheless, most commercial FDM materials exhibit low chemical and thermal stability. This reduces the scope of applications and limits their use in research and development, especially for on-chip chemical synthesis. In this paper, we present FDM fabrication of microfluidic chips with polyvinylidene fluoride (PVDF) for applications that require high thermal or chemical resistance. Embedded microchannels with a minimum channel width and heights of ~200 µm × 200 µm were fabricated, and the resistance against common solvents was analyzed. A procedure was developed to increase the optical transmission to result in translucent components by printing on glass. Chips for fluid mixing were printed, as well as microreactors that were packed with a catalytically active phase and used for acetal deprotection with a conversion of more than 99%. By expanding the use of fluorinated polymers to FDM printing, previously challenging microfluidic applications will be conducted with ease at the lab scale. Full article

As nations worldwide strive for carbon neutrality, Saudi Arabia has set ambitious targets to increase its renewable energy capacity, aiming for 50% of its electricity production to come from renewable sources by 2030. To accurately assess the economic viability of these photovoltaic (PV) projects, it is crucial to consider the levelized cost of energy (LCOE). In this study, we developed a comprehensive model incorporating PV panel annual degradation rate, initial system efficiency, and interest rates to provide a more precise LCOE calculation. The results demonstrate that PV panel annual degradation, initial system efficiency, and interest rate all significantly influence LCOE. In the most favorable scenario with a 0.5% degradation rate, 0.95 initial system efficiency, and a 0% interest rate, the LCOE was USD 0.0156/kWh. However, under the least favorable scenario with a 2.5% degradation rate, 0.75 initial system efficiency, and a 4% interest rate, the LCOE increased to USD 0.0317/kWh, representing a 103.2% increase. These findings underscore the importance of considering these factors when evaluating the economic viability of PV projects. By understanding their impact, investors and policymakers can make informed decisions regarding renewable energy investments and policies. Full article

This study models two alternative downstream processes based on magnetic separation with the objective of understanding the economic feasibility of these processes compared to the traditional mAb process. The key focus lies in the economic understanding of the cell harvest and capture steps in the models. Here, the models revealed that integrating cell removal and product capture in a single operation is the main factor driving the unified productivity between USP and the magnetic bead-based processes. This results in significant economic benefits, such as savings in both the cost of goods per gram of mAb and fixed costs, as well as increasing annual facility output. The predicted savings potential approaches 38% for COGs, 17% for capital investment, and 40% for annual facility output. For mammalian cell-based manufacturing, the magnetic separation-based DSP provides a highly valuable option due to its integration of several individual unit operations compared to the traditional process both in reducing process time and cost and accommodating higher demands. Full article

Currently, the UK has ambitious plans to reach net zero by 2050, despite other countries such as Russia and India targeting 2060 and 2070, respectively. Assuming that the UK emissions unceasingly decline at a given rate annually towards achieving net zero by 2050, its economy would need to ensure a reduction of 105 MtCO2 per year of its emissions from the current 2021 levels. Given that global greenhouse gas emissions have not peaked and continue to rise, the UK seeks to implement costly and aggressive emission reduction policies towards fulfilling commitments under the 2021 Glasgow Climate Pact. This paper investigates the effect of environmental taxes on environmental degradation in the UK between 2000Q1 and 2019Q4 using novel Fourier approaches. Using the novel Fourier ARDL estimator, the long-run equilibrium estimates indicate that gross domestic product and environmental tax cause a fall in carbon emissions. However, in trade and primary energy use, a unit change caused rising carbon emissions in the UK. Especially, the results indicate that environmental taxes have a negative effect on environmental degradation in the UK, and ecological tax policy could be considered as an effective channel to attain environmental sustainability. The outcome provides the following policy insights: (i) The government of the UK should support international environmental tax coordination mechanisms, especially on carbon pricing, to avoid relocation of carbon-intensive investments. (ii) The UK government must note that imposing more taxes to encourage emissions reductions could bring complexity to the tax system and unnecessarily bring costly ways to deal with climate change. Higher domestic electricity prices could disproportionately hit low-income households and create distributional cost concerns, which require benefit payouts or compensation schemes. (iii) Switching to electric vehicles simultaneously requires investments in charging infrastructure and battery technologies. To avoid this chicken-and-egg problem, the government of the UK could play a coordinating role, including deploying targeted subsidies, regulations, direct government involvement, or setting higher carbon prices in special cases. Full article

Background: The objective was to analyze the budgets invested in prisons by the member states of the Council of Europe (CoE) and the relationships between the global cost, the cost incurred per single inmate, the number of inmates per 100,000 inhabitants (PPR), the gross domestic product (GDP) and per capita GDP. Methods: The data relating to the variables considered for the year 2020 were obtained from the SPACE-I 2021 of the CoE, the World Bank/OECD, and Eurostat. Regression models were used to evaluate the relationships between the PPR and the GDP, the daily cost per prisoner and per capita GDP, and between the PPR and the per capita GDP. A multiple correspondence analysis was performed to evaluate associations between the PPR, EU membership, cost per day, cost rate, geographical area, and inmate gender. Results: The daily expenditure per inmate in northern European countries reaches very high values, respectively: EUR 330.6 (Norway) and EUR 303 (Sweden), while, in the eastern countries, the values drop sharply (EUR 6.50 in Bulgaria and EUR 8.08 in Azerbaijani). The lowest PPR values are found in northern European countries, and the highest in the following countries: Russia, Turkey, Georgia, and Azerbaijan. Conclusions: Countries with a higher GDP per capita tend to have lower prison population rates and to invest larger amounts of funds for prison systems. Full article

In this study, we examine the critical question of whether global equity and bond assets (both green and non-green) offer effective hedging and safe haven properties against stock market risks in South Asia, with a focus on Bangladesh, India, Pakistan, and Sri Lanka. The increasing integration of global financial markets and the volatility experienced during recent economic crises raise important questions regarding the resilience of South Asian markets and the potential protective role of global assets. Drawing on methods like VaR and CVaR tail risk estimators, the DCC-GJR-GARCH time-varying connectedness approach, and cost-effectiveness tools for hedging, we analyze data spanning from 2014 to 2022 to assess these relationships comprehensively. Our findings demonstrate that stock markets in Bangladesh experience lower levels of downside risk in each quantile; however, safe haven properties from the global financial markets are effective for Bangladeshi, Indian, and Pakistani stock markets during the crisis period. Meanwhile, the Sri Lankan stock market neither receives hedging usefulness nor safe haven benefits from the same marketplaces. Additionally, global green assets, specifically green bond assets, are more reliable sources to ensure the safest investment for South Asian investors. Finally, the portfolio implications suggest that while traditional global equity assets offer ideal portfolio weights for South Asian investors, global equity and bond assets (both green and non-green) are the cheapest hedgers for equity investors, particularly in the Bangladeshi, Pakistani, and Sri Lankan stock markets. Moreover, these results hold significant implications for investors seeking to optimize portfolios and manage risk, as well as for policymakers aiming to strengthen regional market resilience. By clarifying the protective capacities of global assets, particularly green ones, our study contributes to a nuanced understanding of portfolio diversification and financial stability strategies within emerging markets in South Asia. Full article

Currently, photovoltaic (PV) resources have been widely applied in the agricultural sector. However, due to the unreasonable configuration of multi-energy collaboration, issues such as unstable power supply and high investment costs still persist. Therefore, this study proposes a solution to reasonably determine the area and capacity of PV panels for irrigation machines, addressing the fluctuations in power generation of solar sprinkler PV systems under different regional and meteorological conditions. The aim is to more accurately predict photovoltaic power generation (PVPG) to optimize the configuration of the solar sprinkler power supply system, ensuring reliability while reducing investment costs. This paper first establishes a PVPG prediction model based on four forecasting models and conducts a comparative analysis to identify the optimal model. Next, annual, seasonal, and solar term scale models are developed and further studied in conjunction with the optimal model, using evaluation metrics to assess and compare the models. Finally, a mathematical model is established based on the optimal combination and solved to optimize the configuration of the power supply system in the irrigation machines. The results indicate that among the four PVPG prediction models, the SARIMAX model performs the best, as the R² index reached 0.948, which was 19.4% higher than the others, while the MAE index was 10% lower than the others. The solar term scale model exhibited the highest accuracy among the three time scale models, the RMSE index was 4.8% lower than the others, and the MAE index was 1.1% lower than the others. After optimizing the configuration of the power supply system for the irrigation machine using the SARIMAX model based on the solar term scale, it is verified that the model can ensure both power supply reliability and manage energy overflow effectively. Full article

This study analyzes the thermodynamic and economic viability of modified high-temperature gas-cooled reactor (HTGR) gas-steam combined heat and power (CHP) systems compared to conventional CHP plants. The research addresses the critical need for efficient and sustainable energy production methods. Using comprehensive thermodynamic modeling and economic analysis, the study evaluates system performance under various operating conditions. Key findings reveal that modified CHP plants with HTGR and turboexpanders (TEs) demonstrate significantly higher efficiency and lower heat generation costs compared to conventional gas turbine (GT) CHP plants, despite higher initial capital investments. The modified systems achieve electricity generation efficiencies up to 48%, surpassing traditional nuclear power plants. The absence of CO₂ emissions and lower fuel costs in HTGR systems contribute to their economic advantage. This research provides novel insights into the potential of HTGR technology in CHP applications, offering a promising solution for future energy systems. The study’s originality lies in its comprehensive comparison of conventional and modified CHP systems, considering both thermodynamic and economic aspects, which has not been extensively explored in existing literature. Full article

The rapid expansion of renewable energy sources has led to increased instability in the power grid of Jeju Island, leading to the implementation of the plus demand response (DR) system, which aims to boost electricity consumption during curtailment periods. However, the frequency of curtailment owing to the increased utilization of renewable energy is outpacing the implementation of plus DR, highlighting the need for additional resources, such as energy storage systems (ESS). High initial investment costs have been the primary hindrance to the adoption of ESS by DR-participating companies but have not been fully considered in earlier studies on DR incentive determination. Therefore, this study proposes an algorithm for calculating appropriate incentives for plus DR participation considering the investment costs required for ESS. Based on actual load data, incentives are determined using an iterative mixed-integer programming (MIP) optimization method that progressively adjusts the incentive level to address the overall nonlinearity arising from both the multiplication of variables and the nonlinear characteristics of the internal rate of return (IRR), ensuring that the target IRR is achieved. A case study on the impact of factors such as IRR, ESS costs, and fluctuations in electricity rates on incentive calculations demonstrated that plus DR incentives required to achieve IRR targets of 5%, 10%, and 15% have increased linearly from 142.2 KRW/kWh to 363.0 KRW/kWh, confirming that the appropriate incentive level can be effectively determined based on ESS investment costs and target IRR. This result could help promote ESS adoption among DR companies and plus DR participation, thereby enhancing power grid stability. Full article