Enhancement Of Production Research Articles

Constitutive Overexpression of CRZ1 in Trichoderma reesei Reveals Its Ability to Enhance Recombinant Lipase Production.

The filamentous fungus Trichoderma reesei is extensively utilized in the realm of recombinant protein expression owing to its well-established protein production systems. However, the potential for efficient and convenient protein production in T. reesei has not been fully harnessed. To further increase the production of recombinant lipase Candida antarctica lipase B (CalB), we overexpressed seven transcription activators and found that overexpression of the calcineurin CRZ1 could significantly enhance CalB production by 2.08-fold, and then through employing a synthetic strong promoter Pcbh7IR and knocking out ace1, a competitor of crz1, CalB production was further increased 4.2-fold. Furthermore, we found that increasing the Ca2+ concentration enabled the enhancement of CalB production in the CRZ1-overexpressing strains. Additionally, transcription analysis revealed a significant upregulation of calcium-related pathway genes and ER chaperone genes in T. reesei, revealing that overexpression of CRZ1 can increase the production of the recombinant protein by activation of the calcium signaling pathway. In this study, by systematically manipulating the recombinant protein expression module and its regulatory transcription activators, we found a positive effect of crz1-mediated calcium channels in boosting the expression of the recombinant protein.

Does Common Agricultural Policy Influence Regional Disparities and Environmental Sustainability in European Union Countries?

This study examines the impact of the European Union’s Common Agricultural Policy (CAP) funds, specifically the European Agricultural Fund for Rural Development (FEADR) and the European Agricultural Guarantee Fund (FEGA), on a range of economic, social, and environmental outcomes across European regions. Utilizing Fully Modified Ordinary Least Squares (FMOLS) estimators, this research analyses 13 equations corresponding to various dependent variables, including employment rates, poverty levels, agricultural productivity, and environmental indicators such as greenhouse gas emissions and renewable energy production from agriculture. This analysis covers the period from 2010 to 2021, and draws upon a balanced sample of 301 observations to ensure robust estimations. Results indicate that both FEADR and FEGA payments significantly influence these regional outcomes, though the effects vary depending on the specific economic or environmental indicator examined. The findings reveal that while FEADR payments positively impact rural employment, agricultural income, and renewable energy production, they are less effective in addressing poverty reduction and productivity enhancement. Conversely, FEGA payments exhibit a stronger influence on agricultural productivity and income, but have mixed effects on environmental sustainability. This study highlights significant regional disparities, suggesting that the allocation of CAP funds is uneven in its impact across regions. The implications for policymakers are clear: a more tailored approach is required to enhance the effectiveness of CAP funds in meeting diverse regional needs, particularly in promoting economic development while minimizing environmental harm. This study also emphasizes the need for further research to explore alternative policy mechanisms and innovative agricultural practices that can bridge the gaps identified in the current CAP framework. Limitations of this study include data availability and the inherent complexity of agricultural systems, which may affect the generalizability of the results across different EU member states.

Enhancement of medium-chain fatty acids production from sewage sludge fermentation by zero-valent iron.

The effect of zero-valent iron (ZVI) dosage on medium-chain fatty acids (MCFAs) production from sewage sludge fermentation was explored. ZVI within a dosage of 2-20 g/L favored MCFAs production. Adding 20 g/L ZVI (ZVI20) increased the MCFAs and long-chain alcohols (LCAs) production to 4079.0 mg/L and 93.1 mg/L, the electron transfer efficiency of MCFAs and MCFAs selectivity were also increased by over 40% and 25% than the control. This may be due to the enriched MCFAs-producing genera, like Romboutsia and Paraclostridium. 2 g/L ZVI favorably strengthened the RBO pathway and facilitated intracellular electron generation. Moreover, ZVI facilitated the extracellular electron transfer, and cytochrome C was most enriched by ZVI20. The low MCFAs production in the ZVI50 group might be due to the inhibition of acetyl-CoA and ATP synthesis. These results provided a deep insight into the effects of ZVI dosage on MCFAs production and the specific mechanisms.

Advancing Industries with AI: The applications being transformational include: Healthcare, powering the Petroleum industry, Handling fraud, Cybersecurity, and Conversational AI

Today, AI is becoming integrated into more and more sectors of human activity, providing new approaches to a number of traditional problems, and improving multiple aspects of business and industrial processes, decision-making, and customer interactions. This paper explores the applications of AI across five key sectors: health care, petroleum, fraud detection, cybersecurity, and conversational designing. Using AI in healthcare, diagnostics and treatment have been transformed together with improvement of patients’ care, early disease identification and better clinical outcomes. AI is applied in enhancement of exploration, production and refinery of petroleum products in the industry while enhancing sustainability. In fraud detection, AI systems thus offer capability to analyze large datasets in real time to reduce and prevent frauds in banking and insurance industries as well as e-commerce businesses. AI in cybersecurity strengthens threat identification, supports automatic management of preventive measures, and offers risk prognosis, with improved protection measures against cyber threats. And, lastly, conversational AI is emerging in the shape of technologies such as Chatgpt that help enhance customer experience and generate content. However, the increasing number of users of artificial intelligence technologies has a number of problems related to advisor ethics, data protection, system openness, and the dynamic nature of threats. While AI technologies mature, their adoption in these industries raises important questions about ethics, security and legal requirements with a view of mainstream proper and democratic development of these technologies. Raising the question of how to advance AI in the face of its problems, the future of AI remains in the effectiveness of using it as a tool for improving technology’s capabilities and for providing solutions which will make the technology more effective, secure, and more accessible in a number of years.

The low enoyl-acyl carrier protein reductase activity of FabI2 is responsible for the high unsaturated fatty acid composition in Sinorhizobium meliloti

BackgroundSinorhizobium meliloti is noted for its exceptional capacity to produce unsaturated fatty acids (UFAs). Earlier studies have indicated that S. meliloti primarily employs the FabA-FabB pathway for UFA synthesis, however, the mechanisms remain elusive. This study was conducted to elucidate these mechanisms responsible for the significant UFA production in S. meliloti.MethodsThe genes encoding enoyl-acyl carrier protein (ACP) reductase (ENR) were disrupted using the suicide plasmid pK18mobsacB, followed by the creation of single-crossover and double-crossover mutants. The ENR proteins were expressed in Escherichia coli BL21(DE3) strains and subsequently purified. Their enzymatic activities were assessed through gel electrophoresis and NADH oxidation assays. Additionally, the fatty acid composition was determined using gas chromatography-mass spectrometry (GC-MS) and thin-layer chromatography.ResultsOur findings demonstrate that the heterologous expression of fabI2 in a temperature-sensitive E. coli fabI mutant results in a significant enhancement of UFA production. Genetic analyses confirmed that fabI2 is an indispensable gene in the S. meliloti genome, as it cannot be disrupted. Interestingly, we observed that fabI2 could only be functionally replaced by the Enterococcus faecalis fabI gene and not by the homologous fabI1 from S. meliloti, E. coli fabI, or Pseudomonas aeruginosa fabV. Furthermore, we validated that the deletion of fabI1 in S. meliloti triggered an increase in UFA production compared to the wild-type strain Rm1021.ConclusionsIn this study, we identified the ENR, encoded by the S. meliloti SMc00326 gene (fabI2), as playing a pivotal role in the biosynthesis of UFAs. Additionally, the FabI1 enzyme, encoded by SMc00005, was found to modulate the fatty acid composition within S. meliloti. Together, these discoveries establish a foundation for the development of a model that explains the significant contribution of FabI2 to the robust synthesis of UFAs in S. meliloti.

Strategies for Enhancing Rural Vitality from the Perspective of Comprehensive Land Consolidation: Integrating Production, Living, Ecology, and Efficiency Enhancement

This study examines the relationship between the space vitality of rural production, living, and ecology (SVRPLE) and comprehensive land consolidation (CLC), establishing a theoretical foundation for improving SVRPLE in rural areas. Building on this theoretical framework, we employed double-constraint spatial clustering and the three-dimensional magic cube method to zone the study area at the village level, facilitating the determination of CLC objectives and scheduling. We then applied an obstacle diagnosis model to identify key challenges within each zone for enhancing rural space vitality. The results indicate the following: (1) Theoretical analysis reveals the mutually reinforcing relationship between CLC and rural vitality. Efficiency-driven CLC enhances the vitality of rural spaces by optimizing the synergistic interactions between production, living, and ecological spaces. Rural vitality is both the core objective of and the guiding principle for the implementation of CLC. (2) The case study validates the proposed framework—”Vitality Status Evaluation—Vitality Enhancement Zoning—Land Consolidation Guidelines”—as a feasible approach for CLC strategy development based on SVRPLE. The zoning outcomes accurately reflect the unique conditions of different rural villages within the study area, providing a scientific and logical methodology for constructing a context-specific CLC strategy. (3) The zoning results, which incorporate CLC objectives and scheduling, yield differentiated CLC sub-strategies aimed at enhancing SVRPLE, offering both theoretical and practical support for CLC implementation in China, particularly in the ecologically fragile Qinghai Plateau. Overall, our research deepens the understanding of rural vitality enhancement pathways, supplements existing studies on rural vitality, and provides practical guidance for CLC.

Application of green synthetic iron oxide nanocatalyst in biohydrogen production from domestic wastewater.

Hydrogen (H2) is considered to be an energy carrier with high yields in future. Using green nanoparticles as the catalyst to produce H2 from organic wastes is an environmentally friendly and cost-effective approach. This study specifically addresses H2 production biologically from domestic wastewater using dark fermentation process with green nanoparticles in anaerobic condition. In this investigation, acid, alkaline, and heat pre-treated wastewater were utilized as the feedstock and identified that the alkaline pre-treated wastewater was an efficient feedstock for H2 production. The reaction conditions such as pH, time, and nanocatalyst dosage were optimized for the enhancement of H2 production. In addition, the green iron oxide nanoparticles (Fe3O4-NPs) were prepared by sustainable way using Murraya koenigii (curry leaves) with FeSO4 and characterized it using Fourier-transform infrared spectroscopy (FT-IR), ultraviolet-visible spectrophotometer (UV-vis), power X-ray diffraction (pXRD), and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM/EDX), further tested for their 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging performance via in vitro antioxidant activities. This study demonstrates that a maximum production of bio-H2 was obtained (72.8mL/L) with 20mg of nanocatalyst load at alkaline condition (pH 9). The correlation coefficient value was highly significant for biohydrogen production with increasing pH (r = 0.9026) and catalyst dosage (r = 0.9962). The characterization studies confirmed the existence of iron oxide nanoparticles in the green synthesized nanoparticles. The in vitro antioxidant assay showed that Fe3O4-NPs effectively reduces the DPPH radical by significantly releasing H-atoms, thereby confirming that the plant extract functions as reducing/oxidizing agents. The high yield under the dark fermentation method has clearly been attributed to the enhancement in bio-H2 production by using the green Fe3O4-NPs based on M. koenigii.

Impact of silicon fertilization on crop growth, productivity and nutrients enhancement in rice: A review

Silicon (Si), constituting around 27.7 % of the Earth's crust by weight, is the second most abundant element after oxygen (47 %). While not considered essential, silicon is beneficial for crop growth, especially for Poaceae family crops. Intensive cultivation or continuous mono-cropping of cereals like rice depletes soil silicon levels, which may lead to decreased rice yields. Rice can absorb and accumulate silicon metabolically, a trait not common in many upland crops. Beyond boosting rice yields, silicon offers multiple benefits, such as enhancing nutrient availability (N, P, K, Ca, Mg, S, Zn), reducing nutrient toxicity (Fe, Mn, P, Al) and mitigating biotic and abiotic stress in rice. Sufficient silicon also stabilizes rice plant culms, reducing lodging risks. Thus, silicon is crucial for plant growth and improving rice productivity at the agronomic level. This review focuses on the relationship between silicon and rice crops, their interactions with other elements and strategies for managing silicon in soils and plants to sustain rice productivity.

Addressing the 2050 demand for terrestrial animal source food

The high emissions intensity of terrestrial animal source food (TASF) and projected increasing demand in low- and middle-income countries (LMIC) have spurred interest in the development of animal-free alternatives and manufactured food items that aim to substitute for meat, milk, and eggs with the promise of reduced environmental impact of producing food. The developing world is the source of 75% of global emissions from ruminants and will house 86% of the world’s human population by 2050. The adoption of cost-effective, genetic, feed and nutrition practices, and improving livestock health in LMIC are seen as the most promising interventions to reduce emissions resulting from projected increased TASF demand though 2050. Genetic improvement is a particularly attractive approach to productivity enhancements, as such improvements are permanent and cumulative. Alternative proteins may play a role in addressing demand for affordable sources of nutrient-dense foods, however, price will be a major factor influencing adoption given 3.1 billion people globally (42%) were currently unable to afford a healthy diet in 2021. Additionally, there is currently a mismatch between the location of alternative protein companies, and both projected increased TASF demand and emissions. To date, the vast majority (>81%) of these companies are based in high-income countries. The sustainability implications of replacing TASF with alternative proteins at scale needs to consider not only environmental metrics but also the wider economic and social sustainability impacts, given the essential role that livestock play in the livelihoods and food security of approximately 1.3 billion people.

Transforming Industrial Supervision Systems: A Comprehensive Approach Integrating Machine Learning Techniques and Fuzzy Logic

Abstract In addressing the mounting challenges of industrial supervision systems grappling with intricate processes, this study pioneers a transformative paradigm centered on the SCIMAT cement factory. By seamlessly integrating Machine Learning and Fuzzy Logic, the primary aim is to revolutionize real-time control systems, with a keen focus on cement production. SVM integration into the supervision system, coupled with connectivity to a Programmable Logic Controller (PLC), is complemented by fuzzy real-time controllers’ regression analysis. Rigorous testing and evaluation validate the proposed approach’s reliability, showcasing its effectiveness in discerning optimal system functioning. The system’s practical application within a PLC environment underscores its prowess in issuing commands to industrial equipment, thereby enhancing operational efficiency. Going beyond conventional methodologies, our approach amalgamates SVM classification, fuzzy controllers, and real-time regression analysis, delivering a multifaceted solution for industrial supervision. The system’s standout achievement is an SVM classification accuracy surpassing 94% compared to other classifiers. The K-Nearest Neighbors (K-NN) model demonstrated an accuracy rate of approximately 93.83%. The decision tree model attained an accuracy of around 83.73%. The logistic regression model achieved an accuracy of 80.25%. These models are not only adept at distinguishing optimal functioning from faults but also adept at preserving the linguistic language used by operators. The study’s novelty lies in the holistic integration of SVM and Fuzzy Logic, offering a practical and adaptable solution that not only advances classification accuracy but also significantly reduces maintenance costs, marking a substantial improvement over the traditional methods. This transformative model, validated through SVM classification and practical application, establishes a new standard for flexibility, cost reduction, and overall productivity enhancement in industrial processes.

The Implementation of Enterprise Resource Planning During the Product Design Process Through the Process of Design Thinking

The implementation of Enterprise Resource Planning (ERP) systems in the product design phase plays a crucial role in modern industries. The product design phase with the design thinking approach produces an innovative product that meets user requirements. The product design process, which begins with capturing user requirements and culminating in a thorough specification of a finished product, requires extensive data and expertise. Iterative product design processes contribute to the complexity of the data that must be managed within an organization. This study involved the implementation of an Enterprise Resource Planning (ERP) software named Odoo within the product design process using a design thinking methodology. By examining the student practicum activities in automotive design, starting from the user survey phase and going all the way to the component design details, a comprehensive ERP system was developed. This system is capable of seamlessly integrating all the data throughout the entire process. Based on the outcomes of testing and assessment, it can be concluded that the modules in Odoo software can be effectively integrated into the product design process. Effective processes in integrating ERP into product design phases can improve production quality and efficiency as well as facilitate greater flexibility and innovation. Implementing ERP throughout the product design phase results in a seamless flow of information, enhanced inventory control, and overall productivity enhancement. This ultimately leads to operational efficiency, competitive advantage, and high user satisfaction in the industry.

Absorption and diffusion process at the CO[formula omitted]-decane interface considering density fluctuations near the critical CO[formula omitted] point

The injection of CO2 into geological formations for storage and for efficiency enhancement of oil production is considered a promising technology. Fundamental is an understanding of the absorption and diffusion process at the CO2-decane interface and its pressure and temperature dependence when approaching the critical CO2 point (31 °C, 7.38 MPa).Based on a new conceptual model, which considers CO2 density fluctuations in the critical range, we were able to consistently explain the time dependence of the volume increase for the respective thermodynamic state. The experimental results confirm the new conceptual model that volume swelling in the non-critical pressure range (< 6 MPa) is a surface effect with limited penetration depth. In contrast, the volume increase in the critical pressure range (6 - 8 MPa) is caused by mixing of liquid CO2droplets and the oil phase, i.e. to a level increase of the liquid mixed phase. Our experimental contact angles confirm this. The measured minimum miscible pressures (MMP) are 5.6 and 6.5 MPa at 20 °C and 30 °C, respectively.The CO2 absorption process at the CO2-decane interface is studied independently with pressure decay experiments. Our model results show excellent agreement (relative error ≅ 1 %) with the experimental results for both the non-equilibrium and equilibrium model, and the early-time diffusion coefficient is 4.7±1.9×10−7m2/s, confirming a fast CO2 mass transfer process.

Structure-guided engineering of 4-coumarate: CoA ligase for efficient production of rosmarinic acid in Saccharomyces cerevisiae

The utilization of genetically modified microbial cells for rosmarinic acid (RA) production is gaining increased attention as a cost-effective and sustainable approach. However, the substrate promiscuity of 4-coumarate: CoA ligase and RA synthase has been considered as a critical factor for low RA yields. In this study, we rationally engineered the substrate preference of 4-coumarate: CoA ligase (OPc4CL2) from Petroselinum crispum, resulting in a significant enhancement in RA production. Particularly, the introduction of the Y240C mutation led to a remarkable 176% increase in RA yield. Subsequent enzymatic analysis of OPc4CL2 variants revealed diminished activity towards p-coumaric acid, resulting in insufficient time for the transformation of p-coumaric acid to 4-coumaroyl CoA to generate byproduct. Furthermore, to minimize the formation of undesired byproducts, the overexpression of 4-hydroxyphenylacetate 3-monooxygenase (OHpaB) and NADPH-flavin oxidoreductase (HpaC) was carried out to facilitate the conversion of p-coumaric acid to caffeic acid and 4-hydroxyphenyllactate to salvianic acid A, thus achieving a significant increase in RA yield of up to 329.9mg/L (16.5mg/g yield on glucose) in shake-flask cultivation. Finally, the engineered strain YRA113-24BHM achieved a notable RA production of 3.6g/L (about 20.2mg/g yield on glucose) by fed-batch fermentation. This study serves as a foundation for the sustainable biosynthesis of RA and other caffeic acid derivatives.

4E Analysis of Productivity and Efficiency Enhancements in Pyramid Solar Distillation: Innovations in Tray Design, Water Heating, and Forced Condensation Integration

This research enhances the thermal efficiency of a pyramid solar distiller (PSD) through 4E (energy, exergy, economic, and environmental) analysis. The modified distiller (MPSD) features suspended trays on three vertical walls, tested with and without heaters, and various water levels (6.2 to 49.6 L) in the basin. The study also examined MPSD's performance with an external condenser, aided by a fan operating at different speeds (0.25 to 1.5 rpm). Results showed that the MPSD, with a water depth of 1 cm and 12.4 L in the basin, achieved a 33% yield improvement and 50.2% efficiency. Total productivity of MPSD reached 3755 mL/m2 compared to 2820 mL/m2 for the PSD. MPSD with heaters produced 6430 mL/m2, reflecting a 98.5% increase. The best performance occurred at 1.25 rpm, with a 133% productivity increase, 66.5% thermal efficiency, and 4.58% exergy efficiency. The water cost was $0.23/L for the MPSD, lower than the PSD's $0.34/L. CO₂ emissions were 30.93 to 32.23 tons per year for different configurations, and enviroeconomic indicators were 447.46 to 467.33 annually, depending on the setup.

Completion and Stimulation Design Evolution in Tight Chalk Formations in Offshore Norway

Summary Lower completion and acid stimulation designs for low-permeability chalk formations in a series of North Sea fields were modified from historical/legacy approaches to improve well performance for both production and injection purposes. The modifications included (1) a stimulation change from high-rate matrix acidizing to acid fracturing and (2) optimization of ball-activated sliding sleeve designs. The improvement in well performance was validated by actual productivity comparisons to offset wells. Further improvements are being developed for future extended reach wells. A ball-activated sliding sleeve completion was chosen for a new series of improved horizontal well completions. Sleeve spacing, the number of sleeves, and port sizes were subsequently optimized for targeted stimulated lateral lengths by pipe flow modeling and limited-entry design methods. Optimization of acid fracturing designs was achieved after incorporating critical findings from various laboratory tests including rotating disk tests, acid-etched fracture conductivity tests, and gel shear history simulator tests. The new acid fracturing treatment designs were generated with the help of numerical simulations that were continuously fine-tuned based on new observations made during treatments and rigorous analysis of bottomhole injection pressures during the treatment. As a result of the lower completion design optimization process, different-size nozzles were introduced into the sliding sleeves to treat up to five sleeves per stimulation stage with effective, limited-entry, fluid diversion. This allowed (1) use of available pumping weather windows effectively in the often-challenging North Sea offshore environment, (2) reducing or eliminating time-consuming wireline perforation runs, and (3) limiting acid exposure to mitigate ball/seat zonal isolation loss events (i.e., dissolvable balls were not always compatible with acid). The new and improved acid fracturing design enabled a reduction of the number of gel/acid cycles from five to three, which reduced stimulation cost without losing stimulation effectiveness. The new design also resulted in productivity enhancements depending on the well location within the structure. The largest performance improvement was observed in wells that were placed farther downflank, where stronger reservoir rock and lower permeabilities were found. These wells required a more intensive acid fracturing treatment to generate economical and sustainable production rates. Finally, wells that used the new stimulation techniques also tended to require a lower restimulation frequency. This type of analysis work has not been presented previously and it optimizes lower completion for acid fracturing stimulation on a well-by-well basis. Further improvement is expected as stimulation designs and completion technology continue to evolve.

An experimental assessment of five distinct solar distiller designs' thermo-economic performance

This study evaluates five solar still (SS) designs—spherical, cylindrical, pyramid, conventional, and double-slope—to determine the most efficient configuration for freshwater production at a specific test location. In initial testing, the unmodified SS designs were compared to a traditional distiller. Modifications were then made to the spherical SS by adding external reflectors, followed by integrating phase change materials (PCM) with silver nanomaterials. The final configuration tested included the spherical SS with reflectors, fans, and external condensers. Results showed substantial productivity increases over the conventional solar still (CSS), with production enhancements of 115%, 105%, 68%, and 31% for the spherical, cylindrical, pyramid, and double-slope SS designs, respectively. The spherical SS with optimized Nano-PCM and reflectors achieved a 230% increase over CSS (10420 kg/m² vs. 3150 kg/m²). The best-performing configuration, combining a fan, condenser, and reflectors, yielded a 253% improvement, with daily outputs of 11.3 kg/m² compared to 3.2 kg/m² for CSS. Economic analysis revealed that the optimized spherical SS configuration reduced the cost of freshwater production to 0.01 $/kg, significantly lower than the conventional SS cost of 0.024 $/kg.

An Optimization Model for the Offshore Well Intervention Campaign: Literature Review

Abstract In the offshore oil industry, well-intervention barges provide crucial support for the production enhancement of offshore platforms. These specially designed ships contain tools and equipment to perform perforation activities that keep the wells active. However, with the relevance and practical operations, operators meet two principal challenges: 1) limited barge availability to serve a set of platforms and 2) each platform exhibits specific job requirements (different number of wells, duration, production gain, cost, time windows). This short literature review provides an overview of the Well Intervention Campaign Problem (WLICP) adopting the model of Vehicle Routing Problem considering Profits (VRPP). We propose four carefully designed questions to answer. It relates to 1) problem structure 2) modelling approach 3) solution technique and 4) optimization scenario. According to the result, WLICP exhibits a rigorous project management structure. Its structure contains the breakdown of n-sub-project representing VRP nodes. Combinatorial optimization helps barges find routes and schedules to maximize profit.

Economic influences of agriculture production and import mechanisms through commodity market in the nepalese context

Agriculture production not only manage food and domestic needs rather enhance nation’s economy. Nepalese production is relying from neighbours through import due to insufficiency. This study design to analyse the impact of agricultural cereal production and import scenario in the Nepalese context. A mixed method approach, both Qualitative and Quantitative data utilized for this Doctoral study-based paper, Farmers of all Seven Provinces samples with HHs interview and secondary data of agriculture and Custom data used. The study was conducted from January to June 2023. The findings revealed the major cereal crop production from own like paddy, maize, wheat and millet are limited for some season. In addition, import from India shifting large economy to India through import. The agriculture production meeting domestic needs like seasonal food and market stock. Whereas seeds, input and mechanization dependency largely depending on neighbours due to no manufacturing of own. The study concluded as agriculture production is a major source of income and food for Nepal. Limited month of sufficiency at the local production bounded Nepal depends on import. The cause was found as lack of sufficient input system, low priority of agriculture from all sectors, diversity and low-political priority. Food Diversity and local production enhancement is the ultimately way out to deal with this issue.

How can intelligent manufacturing lead enterprise low-carbon transformation? Based on China's intelligent manufacturing demonstration projects

As global climate change and environmental challenges intensify, low-carbon transformation has become a common goal worldwide. Intelligent manufacturing (IM) is a crucial driver of total factor productivity enhancement and carbon reduction, necessitating an in-depth exploration of its impact on enterprises' low-carbon transformation. This study utilizes data from Chinese A-share listed manufacturing enterprises from 2011 to 2022, taking the intelligent manufacturing demonstration projects (IMDP) policy. A staggered difference-in-differences (DID) model is adopted to analyze the impact and mechanism of IM on the total carbon emissions and carbon emission intensity. The study finds that IM reduces the total carbon emissions and carbon emission intensity of manufacturing enterprises. This effect is more pronounced in non-state-owned enterprises, high-pollution industries, and inland firms. Mechanism analysis indicates that enterprises achieve low-carbon transformation mainly through three pathways: promoting green technological innovation, improving total factor productivity, and alleviating financing constraints. Additionally, the transformation of the energy structure in the region where the enterprise is located contributes to enhancing the carbon reduction effect of IM. Research confirms that IM empowers enterprises in low-carbon transformation and provides insights for achieving green development and optimizing energy structures.

An Efficiency Analysis of Sugarcane Farming in India: An Interstate Comparison of Performance with Data Envelopment Analysis and Malmquist Index

Background: This paper aims to evaluate the agricultural production of sugarcane in major sugarcane-producing states of India. Even though agriculture’s share of India’s GDP is decreasing, it still plays a significant role in the labor force by accounting for a sizable number of jobs. Recognizing the importance of sugarcane farming and the variations in resource availability among the states is crucial. The study highlights the importance of enhancing production management and resource allocation to increase sugarcane production and optimize inputs. Methods: The present research employs sophisticated statistical techniques, including Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI), to investigate the influence of variables such as land area and labor utilization on the efficacy of sugarcane cultivation at the state level spanning from 2017 to 2022. It uses DEA to analyze the connection between various agricultural inputs and the efficiency of food grain production and provides recommendations for improved resource allocation among Indian states. Result: The results of the investigation indicate that the mean efficiency of sugarcane cultivation across India is approximately 84.2%. Notably, states such as Uttar Pradesh, Tamil Nadu and Karnataka have demonstrated the highest levels of efficiency in terms of input utilization in sugarcane farming. Conversely, Bihar and Uttarakhand have emerged as the least efficient states in this regard. Furthermore, an analysis using the Malmquist productivity index indicates that Uttar Pradesh has exhibited the most significant average productivity growth, with Maharashtra and Gujarat following closely behind. Conversely, states such as Andhra Pradesh, Punjab, Haryana and Tamil Nadu have demonstrated only marginal enhancements in productivity. The study’s insights on sustainable sugarcane production and enhanced farmer-level regulatory frameworks have the potential to greatly benefit sugarcane-producing states. By implementing these ideas, we can work towards boosting revenue and reducing poverty in rural areas.