Production Output Research Articles

Influence Home Industry Kampoeng Batik Laweyan To Community Economy in the Laweyan Region of Surakarta

Surakarta is a city that is famous for its culture, industry, etc. Surakarta is also one of the districts in Central Java which has superior potential and functions in various sectors which can be utilized to improve welfare and increase people's income. One of them is in the industrial sector. A small and medium home industry that can increase people's income is the batik home industry. In Laweyan Batik Village, Laweyan District, Surakarta City, there are several batik home industries that can increase the income of the local community. The aim of this research is to analyze the influence of the batik home industry on increasing the income of the people of Kampung Batik Laweyan, Laweyan District, Surakarta City. This type of research is descriptive with a qualitative approach. Data collection techniques used include: 1). Informant observations, 2). Field survey, 3). In-depth interviews, 4). Documentation. The results of the research show that the batik home industry has an influence in increasing the income of the surrounding community. The efforts made by the owner of the batik home industry to increase the income of the surrounding community are by taking batik home industry workers from the surrounding community and increasing the batik production output and expanding the market and promoting it through the media. social services so that it will increase workers' income

Enhancing energy hub efficiency through advanced modelling and optimization techniques: A case study on micro-refinery output products and parking lot integration

A new model of energy carriers (micro-refinery output products) in the concept of an energy hub is presented. In addition, in the presented model, the effect of different models of parking lot in an energy hub is analyzed. In this study, the uncertainty of the number of electric vehicles was modeled using the Monte Carlo method, and then considering the same conditions, the uncertainty of the number of electric vehicles was calculated using the Probability-Possibility hybrid method. In addition, the study uses a scenario-based approach to address uncertainties related to multi-carrier energy demand and multi-carrier energy prices. In the present paper, ensuring water demand is of great importance, which is why the proposed energy hub structure of a sea desalination unit and sour water treatment that is extracted from the micro refinery output was analyzed. The optimization model presented in this paper for the energy hub is a complex integer linear programming (MILP) that is solved using a CPLEX solver in the GAMS environment. The results show that the use of the Probability-Possibility method resulted in an 8 % reduction in the final energy supply cost in the energy hub compared to the Monte Carlo method.

Acetylation of PGK1 at lysine 323 promotes glycolysis, cell proliferation, and metastasis in luminal A breast cancer cells

BackgroundIn prior research employing iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) technology, we identified a range of proteins in breast cancer tissues exhibiting high levels of acetylation. Despite this advancement, the specific functions and implications of these acetylated proteins in the context of cancer biology have yet to be elucidated. This study aims to systematically investigate the functional roles of these acetylated proteins with the objective of identifying potential therapeutic targets within breast cancer pathophysiology.MethodsAcetylated targets were identified through bioinformatics, with their expression and acetylation subsequently confirmed. Proteomic analysis and validation studies identified potential acetyltransferases and deacetylases. We evaluated metabolic functions via assays for catalytic activity, glucose consumption, ATP levels, and lactate production. Cell proliferation and metastasis were assessed through viability, cycle analysis, clonogenic assays, PCNA uptake, wound healing, Transwell assays, and MMP/EMT marker detection.ResultsAcetylated proteins in breast cancer were primarily involved in metabolism, significantly impacting glycolysis and the tricarboxylic acid cycle. Notably, PGK1 showed the highest acetylation at lysine 323 and exhibited increased expression and acetylation across breast cancer tissues, particularly in T47D and MCF-7 cells. Notably, 18 varieties acetyltransferases or deacetylases were identified in T47D cells, among which p300 and Sirtuin3 were validated for their interaction with PGK1. Acetylation at 323 K enhanced PGK1's metabolic role by boosting its activity, glucose uptake, ATP production, and lactate output. This modification also promoted cell proliferation, as evidenced by increased viability, S phase ratio, clonality, and PCNA levels. Furthermore, PGK1-323 K acetylation facilitated metastasis, improving wound healing, cell invasion, and upregulating MMP2, MMP9, N-cadherin, and Vimentin while downregulating E-cadherin.ConclusionPGK1-323 K acetylation was significantly elevated in T47D and MCF-7 luminal A breast cancer cells and this acetylation could be regulated by p300 and Sirtuin3. PGK1-323 K acetylation promoted cell glycolysis, proliferation, and metastasis, highlighting novel epigenetic targets for breast cancer therapy.

Mô hình lựa chọn nhà cung cấp: Ứng dụng phương pháp phân tích thứ bậc mờ

It has been argued that supplier selection is of paramount importance for production companies. In particular, selecting appropriate suppliers may improve production outputs’ quality for firms. Until date, some methods have been developed to select suppliers; yet, some weaknesses still exist. To fill the literature gap, this paper aims to set up a model for judging and selecting potential suppliers from manufactures’ perspectives by the fuzzy Analytic Hierarchy Process (fuzzy AHP). It is posulated that fuzzy AHP is not only applicable for supplier selection, but also helpful in assessing staff’s operational efficiency, evaluating product quality, and appraising the types of technologies to use in the production line.

Large loss of reactive nitrogen and the associated environmental damages from tea production in China

Tea (Camellia sinensis L.), the most popular beverage worldwide and an important cash crop in China, plays a crucial role in the socio-economic landscape. Reactive nitrogen (Nr) loss from tea cultivation in China has become a major environmental problem due to the high input of N fertilizers. However, the scale of the Nr loss and its environmental impact on tea production in China remains unknown. Hence, we conducted a comprehensive meta-analysis of ammonia volatilization (NH3), nitrogen oxide (NOx), nitrous oxide (N2O) emissions, N leaching (total nitrogen, TN), and N runoff (TN) losses in tea plantations in China. The total Nr loss in Chinese tea plantations was 376 Gg yr−1 (149 kg N ha−1 yr−1) in 2014, with N leaching, NH3 volatilization, N2O emissions, NOx emissions, and N runoff losses accounting for 52.2 %, 33.2 %, 7.5 %, 5.4 %, and 1.7 %, respectively. The total Nr loss-related environmental damage cost of tea cultivation reached 9.53 billion CNY yr−1 in 2014, which was 7.7 % of the total tea production output value. The bulk of the environmental damage cost was attributed to NH3 volatilization (49.1 %), N2O emissions (24.9 %), and N leaching (19.2 %). Large Nr losses occurred during tea production in Sichuan, Hubei, Guizhou, Yunnan, Zhejiang, and Hunan provinces, accounting for 17.7 %, 17.0 %, 13.4 %, 10.7 %, 7.6 %, and 7.0 % of the total Nr losses in China, respectively. Our analysis showed that the adoption of integrated nutrient management reduced N fertilizer inputs to 300 kg N ha−1, lowered Nr loss from 376 Gg to 172 Gg yr−1, and reduced the environmental damage cost of N loss by 45.4 %. These findings, along with detailed data on the N balance of tea cultivation, provides critical information needed to develop effective region-specific N nutrient management practices and policies for sustainable and profitable tea crop production in China, and possibly in other similar geographies.

Social Capital in the Patron-Client Dimension towards the Sustainability of Seaweed Cultivation Businesses in Rural Areas, South Sulawesi, Indonesia

The system of livelihoods in seaweed cultivation becomes the subject of study because of the factor of production, and the distribution of the output of production requires a strategy of merging between something material and non-material that involves interaction with various actors in society. The social capital awakened by the actors in the seaweed cultivation business through the patron-client dimension is an effort to ensure the sustainability of the business. The study aims to characterize the components of social capital that bind, bridge, and connect in the context of the relationship between actors in seaweed cultivation, including the important role of the combination of these three types of social capital in the sustainability of the seaweed cultivation business. The Research methods use qualitative descriptive approaches. Data is collected through semi-structured interviews and analyzed with open, axial, and selective encoding. The results show that actors in seaweed cultivation enterprises combine the social capital components of bonding, bridging, and linking selectively, depending on the interests behind each interaction with different actors. Social bonding capital is owned by seaweed farmers in their interactions to gain access to financial capital (in the form of cash and loans). The patron-client relationship pattern is the most prominent of the reciprocity relationships, where the patron is the provider of corporate capital and the guarantor of subsistence is the cultivator. The social bridging and linking capital is owned in its interaction to gain access to social assistance and political support as well as networking. Mechanisms of sale of seaweed production are dominated by marketing networks using intermediary services (middlemen) through the concept of personalized exchange. In such market trading, the symptoms of “boro” (guarantees) are detected through subscription relationships between sellers and buyers characterized by regular personality contacts and through credit mechanisms known as “take now, pay later”. Therefore, social capital plays an important role in the sustainability of seaweed farming in the countryside. In a situation of economic or environmental change, social capital can help the farmer adapt and survive in his business and household life. We found that social capital plays an important role in the rural habitat system, where access to livelihoods depends on social relationships. Thus, support is needed to strengthen the capacity of social capital in societies because the configuration of the social capital elements can inherit the cognitive social capital, the social structural capital and the social relational capital necessary for the improved social, economic and cultural development of societies.

Recursive identification of kernel-based hammerstein model for online energy efficiency estimation of large-scale chemical plants

Accurate energy efficiency prediction is crucial for decision-making in large-scale chemical production, especially considering energy management and environmental concerns. The complexity of chemical processes, characterized by strong nonlinearities, dynamics, and uncertainties, challenges traditional prediction methods. This paper introduces KHSM (Kernel-based Hammerstein Subspace Model), which models nonlinear static and linear dynamic processes in series by embedding kernel function-based nonlinear mapping into subspace modeling for energy efficiency estimation. KHSM identifies nonlinear process models without explicit nonlinear mapping functions, constructing dynamic models that encompass both energy input and product output variables. An adaptive KHSM variant dynamically updates the energy efficiency model, improving accuracy by iteratively selecting and excluding samples. Comparative analysis shows KHSM outperforms existing methods, achieving a coefficient of determination (R2) closest to 1 and reducing the root-mean-square error (RMSE) by up to an order of magnitude, with the smallest mean and standard deviation. Additionally, modeling efficiency increases by an order of magnitude. The developed model enables ongoing energy efficiency estimation and proactive identification of efficiency trends. Validation through mathematical and real-world ethylene process cases demonstrates KHSM's efficacy and applicability. These estimates facilitate informed adjustments to energy management strategies and optimization of production approaches in energy-intensive chemical processes.

UK Reproducibility Network open and transparent research practices survey dataset

Openness and transparency in the research process are a prerequisite to the production of high quality research outputs. Efforts to maximise these features have substantially accelerated in recent years, placing open and transparent research practices at the forefront of funding and related priorities, and encouraging investment in resources and infrastructure to enable such practices. Despite these efforts, there has been no systematic documentation of current practices, infrastructure, or training and resources that support open and transparent research in the UK. To address this gap, we developed and conducted the Open and Transparent Research Practices survey, a large-scale audit study completed by research-active staff in UK research institutions to better understand existing practices, needs, support, and barriers faced when implementing open and transparent research. The data presented here capture responses from over 2,500 research-active staff based at 15 institutions affiliated with the UK Reproducibility Network. The data provide a snapshot of open research practices that can be used to identify barriers, training needs, and areas that require greater investments.

Technological Limit of Solar Concentration Technique Applied to Hybrid Photovoltaic-Thermal Solar Collector Equipped with Thermoelectric Generator Incorporating Ternary Nanofluid

Abstract This paper aims to explore the technological limits of the synergy between the solar concentration technique, facilitated by a parabolic concentrator, and the thermoelectric effect induced by a thermoelectric generator (TEG) within a PV/T, incorporating a ternary nanofluid (Cu-Al2O3-MWCNT/Water). Each component of the CPV/T-TEG is subject to energy balance equations, and the Runge Kutta fourth-order method is employed to solve the resultant mathematical model. The effects of the concentration ratio CR, the mass flow rate ṁ, and the nature of the heat transfer fluid (HTF) on the performance of the system are scrutinized. The simulations are carried out under the meteorological conditions of Ain Salah city in southern Algeria for a moderate wind velocity. The results show better performance when operating ternary nanofluid compared to other HTFs. Moreover, the outcomes indicate that by using a 2% volume fraction of nanoparticles of ternary nanofluid, the thermal output, electrical yield, and thermoelectric production reach enhancements of 14.55%, 11.18%, and 22.64%, respectively. Incorporating the solar concentrator resulted in 3.54 and 5.88 times increase in electrical and thermal powers, respectively. With the growths in ṁ, the temperature of the PV decreases by 53°, and the electrical efficiency improved by 34.52%. Correlations encompassing the concentration ratio and mass flow rate for various types of heat transfer fluids are established to predict the technological limits of CPV/T-TEG systems under the meteorological conditions specific to Ain Salah.

Automatically Generated Texts for Fauna and Flora from Structured Data Based on a Controlled Vocabulary

Information systems like Xper3 and Fulgoromorpha Lists On the Web (FLOW) play a crucial role in managing and using biological data. These platforms store extensive collections of normalized data and structured taxonomic descriptions. By using controlled terminologies, they standardize the vocabulary, significantly enhancing the processes of identification, description, and comparison of various taxa. The massive assemblages of data hosted in these repositories could be reused to generate texts in natural languages automatically. The most immediate goal is to produce, from these information systems, more accessible and user-friendly displays in the form of taxon summary pages. This automated production of textual outputs is a great addition that can be continuously updated as the databases evolve. Can structured data be reused to provide better species pages and to ensure updating if the data evolves? Will AI assist in this process, or will specific computing be needed? To address these questions, multiple possible approaches have been identified. The most basic level of this process involves converting a single line from a taxon-by-character matrix into text that resembles natural language, similar to the descriptions found in botanical or zoological guides. The primary goal is to move beyond the rigid format of matrix lines or lists of characteristics (such as characters and states) of a species, and instead generate a coherent, easy-to-read paragraph intended for human eyes. To achieve this objective, a first solution is given by Descrxp, a tool currently developed in conjunction with Xper. The user specifies the desired key outline for the output, and Descrxp fills this canvas using the database contents. While this approach is highly reliable and adaptable to various contexts, its drawback is being labor-intensive, and requiring significant human input and oversight (Fig. 1). The second solution uses AI. Data on well-known taxa, and on more obscure taxa have been tested with ChatGPT 3.5 or 4.0. ChatGPT succeeds well at generating natural language descriptions for well-known taxa (Fig. 2), providing text that appears accurate and coherent due to the extensive information available online for these groups. However, when it comes to more obscure taxa, less represented on the internet, the results can be more inconsistent and unpredictable (Fig. 3). This variability can be explained by the quality of the data the model has been trained on, which is significantly richer for well-known species. Consequently, for lesser-known groups, the generated descriptions may lack the precision and reliability seen with more familiar taxa. However, if more careful attention is given to the output of chatGPT (Fig. 4), it is possible to notice that the AI filled part of the description with inaccurate characters. Due to its inability to recognize specific scientific terminology, and to process hierarchical information, chatGPT ends up producing an over-generalized and redundant description. To go further, it would be possible to use a comparison between taxa to produce a text that highlights the remarkable features of a taxon. Moreover, it could be interesting to try and synthesize several lines of the initial matrix to extract generalized descriptions of groups of taxa, such as the description of a genus based on its included species. Using data from FLOW, Fishbase, and Xper3, the French ACDC (Counterfactual Learning for Controlled Data-to-text) project is creating a variety of text outputs. These range from "fill-in-the-blank" canvas to fully AI-generated content, utilizing data matrices derived from these pilot databases.

COVID-19 Modified mRNA “Vaccines”: Lessons Learned from Clinical Trials, Mass Vaccination, and the Bio-Pharmaceutical Complex, Part 2

The COVID-19 modified mRNA (modmRNA) lipid nanoparticle-based “vaccines” are not classical antigen-based vaccines but instead prodrugs informed by gene therapy technology. Of considerable note, these products have been linked to atypical adverse and serious adverse event profiles. As discussed in Part 1, health-related risks and drawbacks were drastically misreported and underreported in the Pfizer and Moderna trial evaluations of these genetic products. Now in Part 2, we examine the main structural and functional aspects of these injectables. The COVID-19 modmRNA injectable products introduce a unique set of biological challenges to the human body with the potential to induce an extensive range of adverse, crippling, and life-threatening effects. Based on the fact that there is no current method to quantify host (cell-based) spike protein production in vivo following injection with these prodrugs, there is no standard “dose”. This is in part due to differences in spike protein production output, which depends on cell metabolism and transfection efficiency. It is therefore difficult to predict adverse event profiles on an individual basis, but considering that millions of adults across the world have reported severe and serious adverse events in the context of these modmRNA COVID-19 products, valid concerns are raised regarding injection of infants and younger age groups for whom COVID-19 poses only minimal risks. We address the process-related genetic impurities inherent in mass production of these products, and the potential risks posed by these contaminants. We then categorize the principal adverse events associated with the modmRNA products with a brief systems-based synopsis of each of the six domains of potential harms: (1) cardiovascular, (2) neurological, (3) hematologic; (4) immunological, (5) oncological, and (6) reproductive. We conclude with a discussion of the primary public health and regulatory issues arising from this evidence-informed synthesis of the literature and reiterate the urgency of imposing a global moratorium on the modmRNA-LNP-based platform.

Returns to scale, technical and efficiency changes in the Spanish hotel industry using technological heterogeneity models

This paper analyses returns to scale, productivity growth and its decomposition in the Spanish hotel industry (period 1997–2019). To do so, we consider that hotels can have technological heterogeneity and, therefore, parameters in their production function can differ between them. Also, we use a multiple input and output production function based on an output distance stochastic frontier approach with random parameters in a Bayesian framework. Results indicate that the percentage of hotels working under increasing returns to scale decreased during the period considered. Furthermore, productivity growth was low, indicating signs of stagnation. Efficiency change appears to be the main driving force behind productivity growth, although technical change had a positive effect on productivity after the start of the global financial crisis. Several practical implications are proposed based on these results.

Design Maintenance System on Mixer Machine to Prevent the Breakdown Using Reliability Centered Maintenance

Equipment, machinery, and labor are fundamental assets of an organization. Therefore, companies must have an appropriate and scheduled maintenance system. However, many manufacturing companies neglect maintenance, leading to frequent machine breakdowns that can result in machine downtime and financial losses. This research aims to determine the machine maintenance interval and the types of actions to be taken. The method employed is Reliability Centered Maintenance with the Failure Mode and Effect Analysis approach to identify failure patterns in a system and formulate the best strategies for designing a maintenance system. The results indicate that the CS-20 Type B mixer is the most critical machine, which can significantly reduce the company's production output due to machine downtime during the repair process. Based on the Reliability Maintenance method, the maintenance interval for components with potential failures is 273.17 hours for the bearing component, experiencing breakdowns three times with the highest damage occurrence within one year.

Applying life cycle assessment to European high nature value farming systems: Environmental impacts and biodiversity

CONTEXTLife Cycle Assessment (LCA) remains a method of choice for assessing the environmental performance of agricultural systems. However, it is rarely applied to multifunctional extensive production systems, in which livestock use, apart from animal production, maintains a continuous disturbance that sustains the diversity of habitats and species. OBJECTIVEThis study aims to assess the environmental impact and biodiversity of extensive ruminant production on semi-natural grasslands (SNG), that is, High Nature Value (HNV) farming across Europe. We collected data from a total of 41 HNV farms in five countries (Finland, Estonia, Spain, Greece, and France) that produce beef, sheep, and goats, and that incorporate (to a varied degree) semi-natural and permanent pastures into production. METHODSWe used LCA to assess the potential environmental impact of HNV farms according to global warming potential (GWP100), fossil resource scarcity (FRS), water scarcity (WS) and land use (LU), by using the Solagro Carbon Calculator and OpenLCA software. We assessed biodiversity based on the expert scoring system of SALCA-BD. We compared impacts on per area and per product basis across the farms, and related them to the productivity. RESULTS AND CONCLUSIONSResults revealed a considerable variation in all environmental impacts among HNV farms, explained mostly by the type of ruminants, main product (meat or milk) and the production level. GWP100 per unit in beef product in France was almost twice as high as that in boreal and 3 times more than in Spain, while sheep systems in Greece varied 7-fold for meat. Sheep systems consistently had the highest GWP100, while goat systems used the most land, fossil fuel and water. Small ruminant production in Spain had both the highest land occupation and biodiversity values. Biodiversity was at its highest on farms utilising only SNG for production, which, however, related negatively to the farms' production output. Enteric fermentation accounted for 32% of overall emissions. SIGNIFICANCEThis study makes a novel contribution towards a better understanding of the environmental performance and production capacity of HNV farming systems that are often used as examples of multifunctional and sustainable ruminant-based production.

The Fourth Industrial Revolution and Its Impacts on Production Processes and Efficiency Enhancements Through Automation and Data Networking

Industry 4.0, also known as the Fourth Industrial Revolution, recalls a period of change, knocking complex human activities into production lines by implementing innovative technologies in automation, artificial intelligence, and data networking in manufacturing. Its relevance is found in the capacity to cause significant shifts in the characteristics of industries by improving product output, effectiveness, and adaptability. This paper seeks to review the effects of Industry 4.0 on manufacturing, emphasizing enhancing those technologies in production processes. The first research question is whether implementing Industry 4.0 technologies would lead to enhanced productivity and efficiency of production. To this extent, qualitative research tools, such as case studies and interviews, were used alongside quantitative approaches like surveys and statistical analysis. Some of the conclusions highlighted include finding a cause to believe that Industry 4.0 technologies lead to increased productivity, decreased time lost, and flexibility in operations. Based on these findings, Industry 4.0 is becoming an essential factor in current processes of production system renovation and offers valuable information for industries interested in the successful application of such developments

Calcium sulfate scale: A review of state-of-the-art

Precipitation of sparingly soluble salts is a common issue in water treatment processes and oil and gas production systems. Precipitation occurs when incompatible brine mix and operating parameters like pressure, pH, temperature, etc. change. This may lead to decreased production output, equipment failure, and a decline in process efficacy. Of the many different types of scales known to exist, the calcium sulfate scale is particularly challenging to deal with as CaSO4 is practically insoluble in hydrochloric acid, which is used to remove other types of scales, such as carbonate scales. Although numerous initiatives to inhibit calcium sulfate precipitation have been documented in the literature, it remains largely an issue. This review offers a critical analysis of the state-of-the-art regarding calcium sulfate scaling, exposing its mechanisms of precipitation, inhibition, and methods for mitigating its effects. The limits of current technologies and further research areas are also highlighted in this review.

Abiotic stressors in poultry production: A comprehensive review.

In modern animal husbandry, stress can be viewed as an automatic response triggered by exposure to adverse environmental conditions. This response can range from mild discomfort to severe consequences, including mortality. The poultry industry, which significantly contributes to human nutrition, is not exempt from this issue. Although genetic selection has been employed for several decades to enhance production output, it has also resulted in poor stress resilience. Stress is manifested through a series of physiological reactions, such as the identification of the stressful stimulus, activation of the sympathetic nervous system and the adrenal medulla, and subsequent hormonal cascades. While brief periods of stress can be tolerated, prolonged exposure can have more severe consequences. For instance, extreme fluctuations in environmental temperature can lead to the accumulation of reactive oxygen species, impairment of reproductive performance, and reduced immunity. In addition, excessive noise in poultry slaughterhouses has been linked to altered bird behaviour and decreased production efficiency. Mechanical vibrations have also been shown to negatively impact the meat quality of broilers during transport as well as the egg quality and hatchability in hatcheries. Lastly, egg production is heavily influenced by light intensity and regimens, and inadequate light management can result in deficiencies, including visual anomalies, skeletal deformities, and circulatory problems. Although there is a growing body of evidence demonstrating the impact of environmental stressors on poultry physiology, there is a disproportionate representation of stressors in research. Recent studies have been focused on chronic heat stress, reflecting the current interest of the scientific community in climate change. Therefore, this review aims to highlight the major abiotic stressors in poultry production and elucidate their underlying mechanisms, addressing the need for a more comprehensive understanding of stress in diverse environmental contexts.

The effect of temperature on energy related CO[formula omitted] emissions and economic performance in German industry

This paper represents an addition to the scanty empirical evidence relating to the impact of temperature on the manufacturing sector. To study the effect of temperature on plants’ energy-related CO2 emissions and economic performance, we combine daily temperature information from 11,000 German municipalities with the German census of the manufacturing industry for the period 2004–2017. Based on fixed effects panel regression models, we find that temperature affects industrial emissions significantly. Low temperatures cause a large and robust increase in CO2 emissions as a reflection of heating requirements. For example, one additional day with a mean temperature below −6 °C increases average plant-level emissions by ≈ 0.16% or 4.2t CO2 relative to a day with mean temperatures between 15 °C and 18 °C. Evidence for increased emissions from electricity consumption due to cooling needs is less consistent. Our findings indicate that, on average, plants in the German manufacturing sector experienced a 4–7.5% reduction in their annual CO2 emissions from using fossil fuels in recent years (2004–2017 vs 2018–2022) due to warmer temperatures. We extend our analysis to encompass the effect of temperature on economic performance. While finding consistent evidence for a negative effect of cold days on output, growth, and labor productivity, results for hot days are mixed. Finally, we interpret our estimates against the backdrop of climate projections.

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO2 Reduction Devices

Integrated solar fuels devices for CO2 reduction (CO2R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO2R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO2R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO2R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Agricultural sector circular economy development: Agroecological approach

This study aimed to investigate the feasibility of using agroecological concepts to establish a circular economy in the agricultural industry. The paper examined circular economy as a novel economic development paradigm that seeks to optimise resource utilisation and reduce waste, particularly in the agriculture industry. The main principle of the circular economy is resource conservation, which includes the rational use of land, water and energy, as well as the preservation of biodiversity and the improvement of soil fertility. An analysis was conducted on the economic advantages of adopting a circular economy in the agriculture industry, which include the reduction of production costs, enhancement of productivity, and generation of new employment opportunities. The study also addressed the importance of digitalisation, which can significantly increase the efficiency of agricultural production using modern digital technologies for monitoring soil conditions, managing water resources and optimising processes. This paper examined the effects of the war in Ukraine on the agricultural industry, specifically highlighting a substantial decrease in the output of key crops and livestock products. A comprehensive examination of the destruction of infrastructure, soil, and water contamination exposed severe environmental issues resulting from the attacks. The successful circular concepts implemented by European countries such as the Netherlands, Sweden, Denmark, and France can be applied to the post-war revival of the Ukrainian agriculture industry. The study also addressed the experience of the Ukrainian company Kernel, which successfully implements circular practices such as recycling of production waste, use of biomass and introduction of precision farming, which reduces environmental impact and increases production efficiency. Based on the analysis, recommendations for the post-war reconstruction of Ukraine’s agricultural sector were proposed, including the identification of priority regions for recovery, stimulation of innovation and modern technologies, support for small and medium-sized farms, development of irrigation systems, environmental restoration and protection, international cooperation and support, and education and training