Production Output Research Articles

Research Output, Key Topics, and Trends in Productivity, Visibility, and Collaboration in Social Sciences Research on COVID-19: A Scientometric Analysis and Visualization

COVID-19 has caused a surge in scientific publications, with increased collaboration. This study aims to elucidate scientific output, focal topics, emerging themes, and trends and patterns of productivity, visibility, and collaboration within social sciences research (SSR) on COVID-19. A scientometric analysis was conducted utilizing Biblioshiny and VOSviewer software. About 65,742 records published on WOS between 2020 and 2022 were analyzed. Topics such as “telehealth,”“well-being,” and “inequalities,” were among the key topics while “interventions” and “mental well-being” were among emerging key topics. Collaboration patterns were regional. Harvard Medical School, the University of Toronto, and the University of Oxford emerge as leaders in collaboration, productivity, and influence. The USA, Italy, India, Spain, and Brazil serve as regional hubs for facilitating collaboration. The USA, England, and China exhibit leadership and influence, playing pivotal roles In shaping the global research. These findings are important for policymakers, funding agencies, and researchers in cultivating future research topics and collaborative efforts. The findings can inform strategic decision-making, resource allocation, and policy development to address present and future health crises. Additionally, these efforts contribute to advancing global sustainability initiatives and promoting human well-being. Encouraging international collaboration is essential, particularly for tackling the regional challenges encountered by countries with limited domestic research capabilities. Future research can improve the methodology used by di-versifying data sources beyond WOS.

Measuring environmental inefficiency through machine learning: An approach based on efficiency analysis trees and by-production technology

The main objective of this study is to introduce machine learning-type extensions for the measurement of environmental inefficiency based on regression trees under shape constraints. The new methods developed are implemented using a by-production approach that distinguishes two technologies, one related to the generation of pollution and the other to the production of good outputs. In particular, we define two alternative approaches to measuring environmental inefficiency: by-production Efficiency Analysis Trees (by-production EAT) and by-production Convexified Efficiency Analysis Trees (by-production CEAT). The main advantage of the methods developed is that they do not suffer from the typical statistical problem of overfitting connected to Free Disposal Hull (FDH) and Data Envelopment Analysis (DEA). The performance of the new models is evaluated through a simulation study which shows that the new approaches outperform FDH and DEA in terms of mean squared error and bias. We also illustrate the practical usefulness of the new techniques through empirical application to 43 developing and developed countries over a fifteen-year period - from 2000 to 2014. Our empirical findings using real data clearly indicate the higher discriminating power of the by-production EAT and CEAT models as compared respectively to FDH and DEA.

Global Research Trends on Colorectal Cancer (2014-2023): A Scientometric and Visualized Study

Background: Colorectal cancer (CRC) ranks as the third most common cancer worldwide, significantly contributing to cancer-related deaths and increasingly affecting younger populations. Although its impact on patients’ quality of life is profound, scientometric studies on CRC remain underexplored. The objective of this study was to evaluate the scientific literature on CRC from 2014 to 2023, employing a range of scientometric and statistical approaches. Methods: This study obtained CRC-related publications from the Scopus database. The analyses of the collaboration and co-occurrence among countries/regions, institutions, journals, references, authors, and keywords were conducted utilizing VOSviewer, facilitating the identification of key research trends and emergent subjects. Results: A review of Scopus entries yielded 200,385 papers on CRC in the last decade, noting a yearly increase in publications from 2014 to 2023. China emerged as the most prolific contributor with 46,674 documents. A positive correlation was identified between a country’s CRC research output and gross domestic product (GDP; r=0.961, P<0.001). The journal "Cancers" led to 3006 articles, and H. Brenner stood out as the foremost author with 452 publications. However, the Ministry of Education of the People’s Republic of China led institutional contributions to 3094 papers. Conclusion: With a leading count of 46674 articles, China dominated CRC research, particularly highlighted by the Ministry of Education of the People’s Republic of China. The primarily obtained keywords were CRC, cancer, prognosis, rectal cancer, and colon cancer. Despite the presence of global collaborations, there is a pressing need for increased research funding and support in the CRC, especially within developing nations. This study is a navigational tool for medical professionals, researchers, and surgical assistants to grasp the international progress and directions in CRC research.

Employer-provided parking: Departure time choice, investment decision, and welfare effects

Employer-provided parking (EP) has become a prevalent way to reduce employees’ parking delays and late arrivals through offering them free or low-price parking spaces at the workplace. This paper explores the EP effects on employees’ trip scheduling, employer’s EP investment decision, and commercial parking operator’s pricing decision. An analytical trip scheduling equilibrium model is first presented to model the interaction between EP provision and employees’ departure time choices during morning commute. A profit maximization model incorporating the employee productivity is then developed to determine the employer’s optimal EP investment decision. A competitive game between employer’s investment decision and commercial parking operator’s parking pricing decision is analytically investigated, together with the effects of EP investment on social welfare. The results show that the EP investment can lead to a win-win situation with decreased employee commuting cost and increased firm production output; and the employer would like to provide only part of the employees with EP services. The competitive game solutions depend very much on the marginal costs of EP and commercial parking spaces. The EP investment with an excessively high commercial parking fee may hurt the society due to decreased social welfare.

Application of Fuzzy Mamdani Method to Predict the Number of Blood Bags Based on Demand and Supply Data Using Matlab

Fuzzy logic is a control system technique in solving problems and is applied to systems, from basic systems to difficult or complex systems. Fuzzy logic is the proper method to plan an input space into an output space using MATLAB's mathematical theory of fuzzy sets. The reason for using fuzzy logic is because it is related to uncertainty. The unstable demand for blood bags in hospitals makes the supply of blood bags excessive or lacking from demand. The lack of blood supply results in the unfulfilled demand for blood needed by the hospital, while the excess blood supply worsens the quality of blood. In this study, we will predict the number of bags produced using the Mamdani Fuzzy Inference System (FIS) method based on the minimum demand and maximum demand values and the minimum supply and maximum supply that produce output from the defuzzification process. Applying the Mamdani Fuzzy Inference System (FIS) method based on demand and supply data obtains optimal output with MATLAB in predicting the number of blood bags produced. The results of the study showed that the Mean Absolute Percentage Error (MAPE) fuzzy logic Mamdani error value was 24%, the accuracy value of the Fuzzy Inference System (FIS) Mamdani in determining the number of blood bag production was 76%, and the production output generated through the Fuzzy Inference System (FIS) Mamdani was 4,774 blood bags. The number of blood requests at the hospital is 4,443 blood bags, so the amount of blood that must be produced to meet the hospital's demand is 4,774 bags.

Study on the effect of particles in oilfield produced water on the deposition process of CaCO3

In crude oil production, scale deposition significantly reduces production output and elevates operational costs, posing a severe threat to production safety. While chemical methods have been extensively explored for the scaling and inhibition of inorganic salts, the inorganic scaling triggered by solid particle scaling in complex oilfield water has largely been overlooked. This study involves the introduction of particles into a supersaturated CaCO3 solution, utilizing static scale inhibition and conductivity techniques to examine their influence on the scaling process and crystallization rate. It is evident that solid particles expedite the deposition process of CaCO3. Moreover, the deposition rate of CaCO3 is influenced by factors such as the solid particle content, particle size, and stirring speed. It is noteworthy that the presence of solid particles solely impacts the formation rate of CaCO3 crystals, without altering the total deposition. Specifically, under conditions of 70°C, 250/min stirring speed, and 0.08% SiO2 addition, the deposition rate of CaCO3 is enhanced by 13.5%. The nucleus growth rate constant increases from 11.10 × 10-3min-1 to 14.52 × 10-3min-1 and the crystal growth rate constant increases from 3.02 × 10-3min-1 to 3.36 × 10-3min-1 at most. Observations made through scanning electron microscopy (SEM) and polarized light microscopy reveal that scaling occurs predominantly on the added solid particles in later stages, indicating that solid particles in supersaturated solutions serve as crystal nuclei, inducing the growth of CaCO3 crystals and thus accelerating scaling. This research provides valuable insights for the study of scaling in complex water environments.

An adaptation of Random Forest to estimate convex non‐parametric production technologies: an empirical illustration of efficiency measurement in education

AbstractThis paper presents a novel approach to conduct non‐parametric estimations of production technologies that adhere to the basic assumptions of production theory axioms, including free disposability in inputs and outputs and convexity. The methodology is rooted in adapting the highly effective machine learning techniques associated with Random Forest and the use of splines. The new method features a piecewise linear estimator analogous to data envelopment analysis (DEA); however, it distinguishes itself by addressing DEA's overfitting and lack of robustness via randomization of data and input variables in the construction of the models. In this paper, the virtues of employing machine learning techniques for assessing the efficiency of public services, particularly in the realm of educational institutions, are underscored. The new approach has the capability to predict outputs based on inputs, even for units not included in the observed sample. Furthermore, it enables the identification of the most relevant inputs in relation to output production. To demonstrate the advantages of our method, an estimation of the educational production function is conducted for Spanish regions utilizing data sourced from the Program for International Student Assessment.

FORECASTING AND OPTIMIZATION OF CATALYTIC CRACKING UNIT OPERATION UNDER CONDITIONS OF FUZZY INFORMATION

This paper discusses the application of nonlinear regression to forecast and optimize the operation of catalytic cracking units under conditions of fuzzy information. Catalytic cracking is a crucial process in oil refining that produces high-quality gasoline and other light hydrocarbon products. However, the complexity of the process and the uncertainty of initial data complicate the modeling and optimization of plant operations. To address this issue, a nonlinear regression method is proposed that accommodates the fuzziness of input and output parameters described by linguistic variables. The methodology includes the collection and formalization of expert knowledge, the construction of fuzzy models, and their integration into the process control system. Forecasting is performed by creating regression models that describe the relationships between operational parameters and product quality characteristics. The paper presents a procedure for developing and applying nonlinear regression models, describes algorithms for synthesizing linguistic models, and provides examples of their use to optimize the operation of catalytic cracking units. The modeling results demonstrate the high adequacy and accuracy of the proposed method, as well as its advantages over traditional approaches in conditions of uncertainty and data scarcity. The scientific novelty of the research lies in the development and testing of advanced nonlinear regression models adapted for analyzing and optimizing catalytic cracking processes based on fuzzy data. These methods take into account the specificity and uncertainty of process data, improving the accuracy and reliability of forecasts, which facilitates more effective management of production processes in the petrochemical industry. The main reason for conducting this study is the need to improve the control of oil refining processes, particularly catalytic cracking, which plays an important role in producing high-quality gasoline. The complexity of this process and the presence of fuzzy information caused by fuzzy initial data require the development of new modeling and optimization methods. Existing traditional models based on deterministic methods are often insufficient under uncertainty. This leads to a decrease in the accuracy of process control, which can negatively affect the quality of the final product and production efficiency. The use of nonlinear regression in combination with fuzzy logic is a more flexible and adaptive approach that allows you to take into account the fuzziness and uncertainty of data and use expert knowledge to build models that match the actual operating conditions of the units. Thus, this study aims to solve the key problems associated with data uncertainty and the complexity of the catalytic cracking process, which will improve the accuracy of forecasting and optimization of the units. The main contribution is creating a model that uses nonlinear regression methods in combination with fuzzy logic. This allows uncertainty in input data (such as reactor temperature or pressure) to be effectively considered and processed to improve gasoline and other product yield forecasts. It is shown that using nonlinear regression combined with fuzzy logic significantly improves the management of technological processes, increases the output and quality of products, and reduces production costs. The conclusion of the paper discusses the prospects for further development of the methodology and its application to solve similar tasks in other areas of chemical technology.

Oil and fat industry of the Eastern region of the Republic of Kazakhstan: growth reserves, economic potential

The aim is to study the trends and problems of development of the oil and fat industry of the East Kazakhstan region. Methods - statistical-economic in the study of phenomena and processes occurring in the oil-fat segment, calculative-constructive - to identify possible alternative directions of increasing the volume of production of the oil-fat subcomplex in the future, abstractlogical - to analyze the current situation in the oil-fat sector of the region, comparative - to compare the indicators of economic activity of this food industry by different criteria depending on the final objectives. Results - on the basis of statistical information and other official sources the questions concerning the produced agricultural products, their processing and the sphere of trade in finished goods were considered, at that, the final main product is edible and technical vegetable oils. Conclusions - detailed monitoring allowed to reveal the reasons restraining the expansion of the oil and fat industry in the region, in particular, limited provision of necessary raw materials, low percentage of utilization of production capacities of oil refineries, insufficient supply of high quality seeds. Measures to stabilize the output of oil and fat products have been proposed. These are, first of all, the use of innovative technologies in the production cycle, the formation and functioning of various integrated structures in the agro-industrial complex, which will increase the efficiency of enterprises and solve the issues of food security of the country. High-technology and equipment of advanced brands will significantly reduce the cost of processed products, and cooperation of producers with the support of service centers will make it possible to increase the sown areas of this oilseed crop. It is necessary to use innovative technologies, the implementation of which will contribute to the production of high-quality environmentally friendly food products that are in demand in domestic and foreign markets.

The Role of Exercise in Lymphedema Management: A Bibliometric Analysis

Lymphedema is a lifelong chronic health issue, and exercise approaches are considered one of the gold standards in lymphedema treatment. Numerous articles have been published on exercise approaches in lymphedema. In this study, we aimed to conduct a bibliometric analysis of studies related to exercise in lymphedema. For this purpose, a search was conducted in the Scopus database on October 24, 2023, using the keywords “lymphedema and exercise’’ and 869 documents were examined. Data were downloaded from the relevant search engine. These data were analyzed using the Vosviewer and Biblioshiny package programs. Publication dates ranged from 1957 to 2023. According to the analysis results, while the United States is the leading contributor in terms of article publications (n=979), Austria leads in terms of international collaboration (n=401). The most cited publication using the keywords lymphedema and exercise is the article by Campbell et al. (2019) titled “Exercise Guidelines for Cancer Survivors: Consensus Statement from International Multidisciplinary Roundtable,’’ published in the “Medicine and Science in Sports and Exercise’’ journal with 1101 citations. “Lymphatic Research and Biology”, “Lymphology”, and “Supportive Care in Cancer” are the top three journals with the most citations in this field. Particularly, the University of Pennsylvania stands out as the most prolific institution contributing to this area with productive research output. The most prolific author with 29 articles is Kathryn H. Schmitz. The most frequently used keywords include “lymphedema”, “breast cancer”, and “lymphedema, quality of life”. The findings of this study are valuable not only for researchers and practitioners interested in lymphedema and exercise but also for anyone interested in practical applications and potential future developments. Ultimately, this comprehensive information guide could serve as an important resource and roadmap for future studies.

Trend in agricultural growth and cassava productivity in Nigeria (1961 – 2020)

This study analyzed the trend in agricultural growth and cassava productivity in Nigeria (1961 – 2020). Time series on variables of interest were sourced from the Central Bank of Nigeria (CBN) statistical bulletin, the National Bureau of Statistics (NBS), and FAOSTAT. The secondary data obtained were analysed using trend analysis, instability index, compound growth rate model, and the Granger causality test. The results showed that Nigeria’s agricultural output generally experienced an upward trend from 1960-2020. The findings also revealed a general increase in the output of cassava produced in an area in the country within the study period. The yield however experienced some relatively stable trend with mild fluctuations and a noticeable decline in 2013. Across the major policy line considered in this study, the pre-SAP era (1961 – 1985) had the lowest mean output, while the SAP and post-SAP era had the highest mean output of 24772.15 and 45181.94 respectively. The values of instability of production and land put under cassava cultivation are more pronounced in Period II [1986–1998] and Period III [1999–2020]. During period I, (Pre – SAP; 1961 – 1985), the compound growth rate (CGR) for production accelerated while yield stagnated with a CGR of 0.2%. In period II, (CGR for production (6.2%) and area (6.3%) for cassava accelerated; both CGR and instantaneous growth rate for yield experienced stagnation. For period III, there was an acceleration in output and area. There was unidirectional causality between production (output) and area under cultivation, agricultural growth and cassava production, agricultural growth and area under cassava cultivation at a 5% level of significance; while area under cassava cultivation and cassava productivity, productivity and area under cultivation exhibited a bi-directional causality at 5% significant level. The findings are compelling reasons for encouraging cassava production for sustainable food production in Nigeria as it is a versatile staple to address food security.

Impact of metaverse and corporate social responsibility on agriculture production and accounting firm performance output of nigerian firms

The study objective is to examine the impact of the metaverse and corporate social responsibility (CSR) on agriculture production and accounting firm performance output of Nigerian firms. The study ascertained that metaverse is described as a communal virtual shared environment that is produced when physically persistent virtual reality (VR) and virtually augmented physical reality collide while CSR assists firms in becoming socially responsible to the public, their stakeholders, and themselves. the study findings recognized that firms that effectively use technology to showcase their dedication to ethical CSR practices will likely draw investors who support the Sustainable Development Goals (SDGs). Thus, the production of agricultural products and the performance of accounting businesses within Nigerian firms are significantly impacted by both the metaverse and CSR. Their integration improves community ties, stimulates creativity, increases productivity, supports sustainability, and eventually results in a stronger economic framework within Nigeria's crucial agriculture industry. It was concluded in the study that the synergistic impact that improves the performance of accounting firms and agricultural production is produced when CSR initiatives are combined with metaverse technologies. Businesses can create creative solutions to address social concerns that farmers confront, including market access or teaching about sustainable practices, by utilizing the metaverse technology included in CSR frameworks

The Role of Liquid Crystal Elastomers in Pioneering Biological Applications

Liquid crystal elastomers have shown an attractive potential for various biological applications due to their unique combination of mechanical flexibility and responsiveness to external stimuli. In this review, we will focus on a few examples of LCEs used with specific applications for biological/biomedical/environmental systems. So far, areas of innovation have been concentrating on the integration of LCEs to enhance stability under physiological conditions, ensure precise integration with biological systems, and address challenges related to optical properties and spatial control of deformation. However, several challenges and limitations must still be addressed to fully realize their potential in biomedical and environmental fields, and future research should focus on continuing to improve biocompatibility, response to the environment and chemical cues, mechanical properties, ensuring long-term stability, and establishing cost-effective production processes. So far, 3D/4D printing appears as a great promise to develop materials of high complexity, almost any shape, and high production output. However, researchers need to find ways to reduce synthesis costs to ensure that LCEs are developed using cost-effective production methods at a scale necessary for their specific applications’ needs.

Parametric multi-level modeling of Lean Six Sigma

Lean Six Sigma is a methodology that combines Lean manufacturing and Six Sigma into a single framework for process improvement. This combination merges their tools and techniques to overcome their deficiencies while achieving bottom-line improvement. However, existing literature emphasizes general LSS implementation with very little work on modeling the interaction between Leanness and Six Sigma. This work developed a multi-level model containing leanness and Six Sigma levels to generalize LSS implementation. Three hierarchical levels—Six Sigma (level 3), leanness (level 2), and a fattening level (level 1—Sigma quality level) are defined for two models (parametrized and non-parametrized). Aggregate measures (process efficiency, asset intensity, production time, etc.) are considered at levels 2 and 3 to achieve the desired optimization goal at that level. For testing, three process measures [asset intensity (AI), planned stoppages (PS), wastes and rework (WR)] from the manufacturing data of a global brand spanning 18 months were analyzed. The maximum log-likelihood method was used to estimate the model parameters and they converged to 85.2%, 11.2%, and 8.87% for AI, PS, and WR respectively, with a strong correlation between AI and PS. A metaheuristic algorithm was extended to solve both models. The obtained process yield (0.111111 and 0.4132471), defects per million opportunities (DPMO) (12,426 and 18,046), and sigma level (3.6 and 3.74) for the parametrized and non-parametrized models respectively indicated optimal model performance and a need for the strategic use of LSS tools in improving the production output. Also, further reduction in wastes, stoppages, and downtime was observed upon tuning the parametric variables. This model provides a mathematical approach to analyzing LSS implementation and provides a basis for future adaptation to any organization.

Let's innovate! but for what value(s)? Towards an economic geography of valuation in markets and society

In an endeavor to comprehend the socio-economic origins of the value added created within and between territories, economic geography has tended to overlook how value is itself socio-economically constructed in space. I claim, in line with economic sociology and pragmatist market theories, that the socio-economic construction of value should be at the core of our contemporary understanding of innovation to address not merely the economic issues of globalization, but also the grand societal challenges we face today. Value creation should not be regarded as a consequential output of production and innovation organized across space, but as an ongoing process of social, economic and technical co-construction that is contingent on both time and space. This is not to say that one should abandon research on innovation in economic geography, but rather that it should be approached as a question of valuation. In this approach, value creation is not the consequence of innovation, but the process and the result of socially undertaken changes that are co-existential with innovation around two interdependent issues: innovation as relational and transactional valuation in markets and as institutional and political valuation in society. This research should also be future-oriented and should reposition materiality at its center.

On the empirical nexus of agricultural credit facility scheme and agricultural output dynamics in Uganda

The role of the agricultural sector in economic growth cannot be overemphasized. Agriculture is basically one of the key sub-sectors that enhance economic growth in all economies of the world. Since no sector of the economy can grow without enough capital, agricultural credit is considered as imperative for improved agricultural output. To contribute to knowledge in this regard, this study examined the impact of agricultural credit fund (ACF) on agricultural output in Uganda using quarterly data from 2009 to 2021. By employing the Autoregressive Distributed Lag (ARDL) framework, the results revealed that ACF has no significant effect on agricultural output in Uganda in the short run, but it significantly has positive effect on the sector in the long run. We control for economic growth, proxied by gross domestic product (GDP), interest, inflation, and exchange rates and find that exiting level of GDP, spurred agricultural output, while the rate of interest and inflation retard agricultural productivity (output), especially in the long run in Uganda. We recommend that the government of Uganda needs to increase agricultural financing through the credit facility scheme for further productivity of the sector.

Logical and Situational Analysis of the Possibilities of Innovative Development of the Agroindustrial Sector

The author has identified a low level of innovative development of the agroindustrial complex and the reasons for the delay in its growth in comparison with other industries and types of economic activity in Russia. The consequence is a noticeable trend of changes in the positive dynamics of economic efficiency indicators of agricultural production in the recent past. This trend indicates weakening Russia’s food security. The article considers one of the possible options for import substitution of innovative means of production used in the agroindustrial sector in the conditions of external economic isolation of the country. It implies the participation of the state in supporting the development and assimilation of knowledge embodied in the real economy as well as in the financing of national innovative solutions. The option under consideration has the following features: selection on a competitive basis and priority financing of means of production with a high technological potential, which are most in demand among agroindustrial enterprises; reimbursement of payment for information on the state of the markets for technology, means of production, resources, food, raw materials provided by IT specialists, as well as for making calculations to optimize the structure and volumes of production, product exports and technological training to enterprises. This kind of financial support is provided in addition to the current practice of state compensation for losses to low-profit agricultural businesses. An experimental scheme for making decisions on priority financing of innovations is examined. The creators of these innovations are economic entities with the highest indicators of production activities and a high probability of fulfilling an order for the output of innovative products. The list of indicators includes many quantitative and qualitative characteristics. This means that the problem is classified as one that can be solved by using algorithms of multiple criteria modeling.

Enhancing the Efficiency of Scientific Activities in a Medical Organization within the Scope of the Process Approach

The article substantiates the principal trends of research optimization in medical organizations with the use of process-oriented management methods (the case of Ya.L.Tsivyan Novosibirsk Research Institute of Traumatology and Orthopedics). The research is based on the principle of the process approach. It is one of the fundamental principles of the total quality management model that is the most effective management concept based on quality. When developing a system for organizing scientific workflows based on the process approach, planning as well as a methodology of academic research play the key role. For all stages of research activities, processes of planning tasks, their fulfilment and reporting with the determination of responsibility for all types of work being performed and with the development of forms of necessary documents used in the organization of scholarly activities have been framed; approaches to the output of scientific products have been standardized and process regulations have been developed for each of its types. The development of processes is carried out on the basis of the requirements of regulatory documentation, taking into account modern approaches to the organization of research activities. Moreover, all documents containing requirements for processes are reviewed and updated at regular intervals, taking into account changes in regulatory guidance. The development and implementation of a system for organizing scientific activities based on the process approach allow a scientific medical institution to achieve compliance with modern requirements for conducting academic research, as well as to improve the quality and efficiency of scientific activities. The accumulated successful experience can be used in organizations that seek to increase the effectiveness of their scientific activities and meet contemporary requirements for their results.

Analysing Market Integration and Causality of Oilseed Crops: Key Insights and Challenges in Major Tamil Nadu Markets and Interstate Regions of India

Oilseed crops like Sesame and Groundnut experience significant price fluctuations due to factors like seasonal production patterns, their perishable nature, and risk involved in production and marketing of output. The farmers are further complicated by a lack of information about market conditions, including the timing of arrivals and prices. Market integration, which helps stabilize prices and improve the efficiency of the marketing system. This study focuses on analysing the market integration of major oilseed crops— Sesame, and Groundnut in India from January 2013 to January 2024. Johansen's cointegration test and Granger Causality test were applied to examine how prices in different markets are influence one another. The stationarity of the prices tested using the Augmented Dickey-Fuller test. The results confirmed that the prices are cointegrated, showing a strong interdependence between them. The analysis also revealed causal relationships between regions, such as bidirectional causality in the case of Sesame and Groundnut. The findings underscore the importance of further research to address production challenges, improve technical methods, and develop informed policies to manage the issues faced by oilseed crop growing farmers. This will help overcome obstacles in production and ensure a more efficient marketing system.

China's carbon neutrality policy facilitates halving industrial water withdrawal

Abstract China concurrently confronts acute water resource challenges and substantial carbon emissions, with its industrial sector being a significant freshwater consumer and a primary carbon emitter. China has committed to achieving carbon neutrality by 2060, yet the exact impact of this goal on industrial water withdrawal (IWW) remains unclear. Here, we project IWW in China considering both scenarios with and without the carbon neutrality target, based on industry-specific water quota standards and projections of industrial product output. Our findings indicate a 53.76% (51.41 km³) reduction of IWW by 2060 under a carbon neutrality scenario, compared to business-as-usual, with the IWW peak advancing from 2035 to 2025. The thermal power industry holds the largest water withdrawal reduction, accounting for 75.74% (38.94 km³) of the total reduction. Additionally, both the East coastal region and the Middle Yangtze River region could reduce 62.08% (31.96 km³) of IWW under the CN scenario, with Jiangsu province emerging as a significant contributor. This study provides a reliable basis for evaluating the potential for future water withdrawal reduction within the industrial sector and suggests that achieving the carbon neutrality target could offer a promising direction for alleviating China's water scarcity challenges.