Production Resources Research Articles

A 30-m annual grassland dataset from 1991 to 2020 for Inner Mongolia, China

Grassland is a widely distributed land use type that provides essential resources for livestock production and serves as a crucial ecosystem component. Over the past decades, grassland has significantly degraded and shrunk due to climate change and human activities, with ongoing changes in its area. This study utilized the Google Earth Engine (GEE) and the Res-UNet++ model to analyze the phenological and spectral characteristics of grasslands in Landsat images for long-term annual monitoring. Additionally, the LandTrendr algorithm was utilized to correct long-term time series data for grasslands, yielding a map of grassland distribution in Inner Mongolia from 1991 to 2020. The results indicate that the overall spatial accuracy from 1991 to 2020 exceeded 96%, with a Kappa coefficient over 0.92, demonstrating high monitoring accuracy. In particular, the 2019 grassland monitoring area showed high consistency with data from the Third National Land Survey (TNLS), with a coefficient of determination (R^2) reaching 0.97, reflecting the high accuracy and reliability.

Sustainable Energy Solutions in Sub-Saharan Africa: Integrating Indigenous Knowledge and Climate Resilience for Lower Carbon Emissions

Promoting sustainable energy solutions in sub-Saharan countries is crucial for addressing energy poverty, reducing carbon emissions, and fostering long-term environmental and economic sustainability. This study explored using indigenous knowledge and emerging technologies to reduce carbon footprints and GHG emissions in Africa's climate hotspots in sub-Saharan countries. The study revealed that operating institutions utilize various applications to ensure that energy management resources can mitigate the effects of carbon emissions. The study revealed that the most efficient use of natural resources for energy production requires collaboration among governments, private sectors, NGOs, and local communities. By adopting a holistic and inclusive approach, one can work toward a more sustainable and low-carbon energy future. This paper focuses on carbon footprint analysis and proposes solutions to address environmental issues in implementing sustainable energy solutions in sub-Saharan countries. A multifaceted approach involving effective strategies is needed to lower the carbon footprint. The contribution of this study is to improve energy consumption in communities in Africa by integrating climate resilience considerations into sustainable energy projects to ensure long-term viability. This will involve planning for changing climate conditions, such as extreme weather events, and designing infrastructure that can withstand and adapt to these challenges. It has been concluded that carbon footprint analysis is useful for determining the impacts of carbon particles in the world’s atmosphere. The role of energy management operations seeks to improve the assessment and analysis of carbon footprints by allowing atmospheric measurements of carbon.

Cu/N-doped carbon spheres derived from soybean flour as an active green nanocomposite for the synthesis of 1,4-disubstituted 1H-1,2,3-triazole derivatives

Cu immobilized onto N-doped carbon spheres (Cu/N-doped CS) derived from soybean flour was synthesized via the hydrothermal method and certified as a green high-efficiency catalyst for the regioselective synthesis of 1,4-disubstituted 1H-1,2,3-triazoles. The obtained N-doped carbon spheres from a combination of glucose and soy flour have a larger size and suitable affinity for load copper species. The morphology and structure of the as-prepared catalyst have been confirmed based on FT-IR, XRD, FE-SEM, EDX, BET, and ICP-OES characterizations. The catalytic performance of the Cu/N-doped carbon spheroids was investigated experimentally. It was found that the Cu/N-doped CS nanocomposite has a high efficiency and recyclability for 5 cycles without any appreciable loss in its catalytic activity in the synthesis of 1,4-disubstituted 1H-1,2,3-triazoles via the three-component condensation reaction of various epoxide/alkyl or aryl halides, sodium azide, and phenylacetylene in a water medium. Furthermore, significant advantages such as stability, ease of preparation, low cost of the carbon resource, high regioselectivity, and good product yield have been achieved in the heterogeneous catalyst system attractive for large-scale in many industrial products.

Influence of Entrepreneur Social Network on New Product Development Performance of Enterprises Under Intelligent Big Data

In the complex market environment, it is difficult for enterprises to innovate only by their own internal product resources. In order to improve the performance level of new product development, this paper puts forward the influence of entrepreneur social network on the performance of new product development under smart big data. The process of new product development is modeled, and the influence of entrepreneur social network on enterprise new product development performance is analyzed from two aspects: vertical network quality and horizontal network quality. According to the analysis results, build an intelligent big data platform, and use this platform to realize the mining and analysis of enterprise-related data; On this basis, EM algorithm is used to mine the performance data of enterprise new product development, DEA/AHP model is used to evaluate the performance level of enterprise new product development, and the evaluation results are combined with the influence model of entrepreneur social network on enterprise new product development performance to realize the influence analysis of entrepreneur social network on enterprise new product development performance. The experimental results show that the method is highly recognized by experts, which shows that the analysis results are reliable, and the correlation between entrepreneur social network and enterprise new product development performance can be obtained, which provides reference for enterprise new product development.

Digital transformation and resilience in family business: an exploratory study of generational dynamics

PurposeThe paper aims to contribute to the advancement of the debate on digital innovation and entrepreneurship from a cross-generational perspective in the context of family businesses. Specifically, the paper explores the contribution provided by the young generations of entrepreneurs to the digital transformation and resilience of family businesses during the pandemic emergence of COVID-19. Focusing on the need for a major understanding of digital resilience in the context of family businesses and small and medium-sized enterprises, the paper aims to provide theoretical and empirical contributions in replying to the following research question: How did young entrepreneurs contribute to the resilience and the digital transformation of their family businesses during COVID-19?Design/methodology/approachThe methodology consisted of a two-stage qualitative investigation including a focus group managed in presence with the involvement of 24 young entrepreneurs and a self-administered online survey involving the family businesses belonging to the Association of Young Entrepreneurs of Confindustria Puglia (South Italy) that has allowed to collect 47 replies, with a 32% response rate.FindingsThe paper presents evidence about the resilience of family businesses during the COVID-19 supported by the disruptive role of emerging digital technologies. Our analysis demonstrates that young entrepreneurs adopted different patterns of digital transformations, depending on the firm’s industry and the family firm’s digital maturity. Digital resilience in the context of the observed family businesses produced different benefits in terms of competitiveness, effectiveness of decision-making, visibility and communication and new opportunities for value creation; it occurred in several business areas, including production, logistics, sales and human resources management.Practical implicationsThe study highlights the relevant role that younger generations can play in exploring innovation opportunities associated with digitalisation as well as in contributing to reinforce innovation and resilience capability of their family businesses through collaboration with external stakeholders and ecosystems.Originality/valueThe value of the research consists in the attempt to analyse the meaning and implication of digital innovation in the context of family business as a driver for their resilience capability. The Family Businesses Digital Readiness and Young Entrepreneurs Contributions Matrix presented into the study as an original contribution of synthesis of the evidence collected.

An elucidation on productivity, energetics, and carbon footprint of different forage land-use systems in semi-arid tropics of Karnataka, India

Forages are rapid biomass-generating crops that often demand intensive management. They necessitate a clear understanding of energy flow and carbon (C) footprinting which in turn helps in optimization of production resources and environmental impact assessment. Therefore, a field experiment was conducted for five consecutive years (2019–2023) to ascertain eight forage crops’ productivity, energetics, and C footprint. The crops under the annual monoculture system were maize and cowpea. While, Napier, Guinea, Rhodes, Green panic, Anjan grass, and Signal grasses were under perennial monoculture system. The results revealed that, the Napier grass was superior in biological productivity by recording 28%–50% higher green fodder yield over other forages. The energy analysis indicated that the Guinea grass consumed the highest energy (61,719 MJ ha−1 Year−1) during production, while Napier grass showed the highest energy output (32,5991 MJ ha−1 Year−1). Further, Napier grass outperformed the rest in terms of energy use efficiency (5.49), energy productivity (2.39 kg MJ−1), net energy gain (266,641 MJ ha−1 Year−1), energy profitability (4.49), nutrient energy ratio (14.7), and human energy profitability (558). Similar to energy input, Guinea grass production showed the highest C input (970 kg-CE ha−1 Year−1). Whereas, highest C output was observed with Napier grass (56,694 kg-CE ha−1 Year−1) due to its substantial C gain (55,805 kg-CE ha−1), C-efficiency ratio (63.79), and C-stability index (0.98). Consequently, Napier grass can be adopted as a productive, energy profitable, and C-efficient forage crop in semi-arid tropical conditions.

Integration of Circular Economy and Urban Metabolism for a Resilient Waste-Based Sustainable Urban Environment

An unsustainable rate of resource production and consumption is evident in urban environments. The absence of innovative approaches in conjunction with the exponential urbanization and expansion of the global population will inevitably result in substantial environmental consequences. There are two emerging alternatives: circular economy (CE) and urban metabolism (UM). The integration of these principles into novel methodology casts doubt on the linear model of contemporary economic and urban systems, which includes extraction, production, utilization, and disposal. In the development of a distinctive urban framework known as circular urban metabolism, the current study has illustrated the application of these principles. We design this study to motivate urban planners and decision-makers to investigate, develop, and supervise ecologically sustainable cities. Scholars from a variety of academic disciplines, intrigued by the intricacies of urban planning, design, and administration, can foster interdisciplinary collaboration in the circular urban metabolism (CUM) region. To address the research question, we implemented a bibliometric analysis, which involved the examination of 627 pertinent research papers, utilizing the R (R 3.6.0+) statistical programming language. The results emphasize the fundamental characteristics and significance of CUM in the management of refuse. In addition, the findings underscore the importance of creating a novel framework that incorporates the principles of urban political ecology, CUM, sustainability, and the novel dimension of waste metabolism. It is the goal of this framework to emphasize the significance of recycling in the informal sector as a waste management strategy in low- and medium-income countries (LMICs).

On ways to reduce the energy supply costs in Russia

Purpose: is to research of ways to reduce the energy supply costs for Russian consumers.Methods: the analysis of the transformation of the electric power industry was carried out using the tools of tectology and system economic theory.Results: the key reason for the constant increase in the cost of energy supply has been identified, which is the transition from a systematic approach to energy development aimed at increasing general economic efficiency to maximizing the economic performance of independent energy companies. The need to adjust the basic principles laid down in the concept of electric power industry development is substantiated.Conclusions and Relevance: the result of the successful completion of the reform of the Russian electric power industry is a steady influx of significant investments into the industry over the course of decades. But despite the increase in power system capacity, which is outstripping the dynamics of electricity demand, the need for the most expensive peak power sources and energy storage systems is growing, which leads to an increase in electricity prices in addition to the investment component. A positive feedback has been identified that reduces the structural stability of the energy sector, namely: between rising electricity prices; reduction of electricity consumption from the network as a result of the installation of their own generation by some consumers; increasing costs of generating and network companies; more intensive growth in electricity prices and increased motivation to install their own generation for that part of consumers who continue to use grid electricity. The ways are proposed and the solutions are considered aimed at forming new connections between participants in the single technological process of production, transmission and consumption of energy resources, with the aim of reducing the energy supply costs and improving the specific performance indicators of the energy system, and in the future reducing the costs of integrating renewable energy sources into it.

Transparency of asset ownership and its importance for the real sector of the economy

Beneficial ownership creates risks for third parties and the beneficiaries themselves, as well as for the international and national economy as a whole. Transparency of asset ownership is of particular importance for the real sector, which contains the most important production and other resources for the interests of the country. The global trend towards transparency as a condition for access to various transactions and legal actions is manifested in domestic legislation and judicial practice through the use of various legal mechanisms (mainly encouraging beneficiaries to disclose the ownership structure of assets). The interdisciplinary significance of the category of “beneficial ownership” requires the development of a uniform approach to determining the legal status of beneficial owners and controlling persons.

Predicting potential biomass production by geospatial modelling: The case study of citrus in a Mediterranean area

Residual biomass from agricultural production and processing, such as citrus pulp and olive pomace, is an important resource for energy production. In particular, this is the case in regions where transformation industries are concentrated.Current biomass estimates often focus on actual production data, that may not fully capture the biomass potential across all suitable cultivation areas. To bridge this gap, the study predicts the overall potential biomass available for energy production, taking into account the total area suitable for citrus cultivation.The research is focused on the study of citrus species in the province of Syracuse, Sicily, Italy. The methodology combines Geographic Information System (GIS) tools, for data interpolation and map overlays, with Software for Assisted Habitat Modelling (SAHM) for local level simulations.The results of the different models showed accurate and spatially coherent predictions, with AUC values ranging from 0.85 to 0.90, and highest potentialities in the northern and eastern regions of the study area. The results highlighted potential citrus cultivation on 47,706 ha and estimated 184,340 t of biomass, 16,461,520.82 Nm3 of biogas, and 8110 t of digestate. The results of the study identified potential areas for both increasing biomass production and optimising the distribution of digestate, thus demonstrating the utility of these thematic maps as a decision support tool for land management. The simulations and the methodology applied in this study indicated potential economic and environmental benefits to be gained from sustainable by-product management. This approach facilitates the optimisation of decision-making processes for land planning, thereby contributing to the broader objective of improving resource efficiency and sustainability in the agricultural production and processing sectors.

Circular economy – perception of its essence and comparison of selected indicators in Slovakia and the Czech Republic

The circular economy (CE) is crucial for achieving sustainable development by minimizing waste and optimizing resource use. This study aimed to compare the perception of the CE concept in the Czech Republic and Slovakia through a questionnaire survey and analyze the development of selected CE indicators. The respondents were stakeholders involved in the relevant issue, meeting the condition of operating within the forestry and wood industry sector in the analyzed countries. The results revealed that a majority of respondents in both countries were familiar with the CE concept and recognized its importance for sustainable development. Statistical analysis indicated positive trends in Resource Productivity and Circular Material Use Rate in both countries, highlighting progress towards sustainable economic practices. However, the need for continuous awareness-raising efforts remains evident.

In vitro antimalarial susceptibility profile of Plasmodium falciparum isolates in the BEI Resources repository.

BEI Resources, a National Institute of Allergy and Infectious Diseases-funded program managed by the American Type Culture Collection, serves researchers worldwide through the provision of a centralized repository for the acquisition, production, characterization, preservation, storage, and distribution of standardized biological resources targeting National Institutes of Health priority pathogens including bacteria, viruses, pathogenic fungi, and parasitic protozoa. These reference materials are critical for the development of diagnostics, vaccines, and therapeutics and are available to qualified registered investigators and institutions worldwide. Bioresources within BEI include well-characterized malaria isolates as part of the Malaria Research and Reference Reagent Resource Center (MR4). These isolates are critical for screening antimalarial compounds, conducting drug resistance studies, and for resistance surveillance and management. In our efforts to enhance the characterization of MR4 P. falciparum isolates, we measured antimalarial susceptibility of >100 isolates against a panel of standard antimalarial compounds. Our results provide valuable information to assist current and prospective users of the BEI Resources repository in making data-driven requests of isolates to meet their research needs.

Rock Melon Crop Yield Prediction using Supervised Classification Machine Learning on Cloud Computing

Precision agriculture is a technology-driven approach to farmer to improve their crop yields and reduce costs. One of the major challenges facing farmers today is the lack of precise prediction which leads to decreased production and mismanagement of labour and resource. Precision technology is costly, and they only rely on manual observations which are less precise. Crop yield prediction systems on cloud computing can solve both problems by predicting the harvested fruit at earlier stages of farming and ease farmers to make decisions. In this study, we proposed a crop yield prediction system for farmers that utilizes cloud computing and machine learning techniques. The system uses data on the physical growth of the plant such as plant’s height at 15 and 30 days after transplant, type of pollination treatment, condition of the leaves, and their variety to predict the crop yield at the early stage. Logistic regression, k-nearest neighbour, and random forest classifier were used to compare the accuracy of the model. Our result shows that by using a random forest classifier, it can achieve an accuracy of 91% which is higher than logistic regression which is only 73% of accuracy, and k-nearest neighbour with 82% accuracy. The study highlights the potential of precision agriculture, cloud computing, and machine learning to revolutionize the way farmers manage their crops and increase their efficiency and productivity, even with the limited resources and hardware that many farmers have.

Use of benchmarking as a tool of lean production in the mechanism of cost management in an agricultural organization

The mechanism of cost management, reflecting the peculiarities of its organization at the microand macro-level, with the application of lean production principles (focus on creating value for the customer, continuous improvement, strategic orientation, loss reduction, visualization and transparency, etc.) is presented. Methodological approaches to cost rationing in the production of agricultural products, taking into account the conditions of its production (resource availability of organizations) and the level of efficiency of resource expenditure are substantiated. The novelty of the considered approach consists in the use of the tool of lean production – cost benchmarking. It allowed to calculate the reserves of growth of productive indicators of agricultural producers’ activity taking into account their provision with long-term and short-term assets, labor resources.

Harmonization potential of the fragmented farmlands in Finland: The pros and cons for critical parcel characteristics

Agricultural landscapes have been shaped by gradual, partially optimized changes in farms and surrounding areas which have resulted in fragmented agricultural landownership and increased distances on farms. Since Finland joined the EU in 1995, the average farm size has more than doubled which has increased the distances on farms. This may have caused trade-offs with resource use efficiency, productivity, and sustainability. The aim of this study was to evaluate the potential and impacts of land reallocation by integrating regional variability, logistical factors, and emerging satellite imagery, with an emphasis on enhancing resilience in future climates. This study estimated the theoretical potential for land reallocation between farms to reduce farmland fragmentation but also applied fixed land exchange rates (5 % to 40 %) with the primary aim to reduce distances within each farm depending on the farm size and region. The aim was also to identify co-benefits and trade-offs on the number of parcels in a farm, the production capacity of exchanged parcels, diversification potential, and the proximity of parcels to waterways. While keeping the farm size constant, large potential was found to optimize fragmented landscapes and reduce distances within farms especially on large farms. However, only a moderate exchange rate of 5 % almost halved the distances in the best cases of the farms, while exchange rates >20 % provided less additional logistic benefits. Thereby, modest, well targeted measures are not only more acceptable to landowners but may provide the most benefits with fewer trade-offs. In unsatisfactory cases, large parcels were replaced by higher numbers of smaller ones, productivity differences occurred, and closer parcels became more uniform, which may reduce diversification options, which are important for resilience and sustainability. Hence, merging and reshaping nearby parcels after reallocation might be needed to complete rationalization. Estimated changes in the proximity of the parcels to waterways tended to improve the farmers’ readiness to implement irrigation as an adaptation measure to climate change. The variable outcome of parcel reallocation emphasizes the central role of the current customer-driven consolidation system chaired by independent land surveyors to boost the land reallocation also in the future to improve logistics, resource efficiency, and sustainability on farms that today struggle with cost-crises.

Iterative learning robust security predictive tracking control for small delay batch processes: Deception attacks on unreliable network channel

During the batch process, the need for security control is becoming increasingly urgent with the gradual penetration of network control technology. For small time delay batch processes subject to deception attacks, an iterative learning robust security predictive tracking control approach is developed. Reviewing previous studies for iterative learning control, the issue that the repetitive character of the batch process would mask the characteristics of deception attacks was not considered. Moreover, the gains of iterative learning control law are utilized offline, which makes large deviations for the system state as the operating time increases. This will lead to “excessive-input” conditions for control inputs, which means more consumption of energy and production resources. To address these challenges, we introduce robust security invariant sets to improve the robustness of the system by constraining the system state to be in a safe range. Also, the design of the iterative learning controller incorporates deception attack data for historical batches, which is continuously improved and optimized to withstand deception attacks. Meanwhile, by calculating stability conditions online, the real-time control law gain is obtained, which could make the control inputs adjusted online based on the real-time system’s dynamic characteristics, avoiding excessive inputs and improving the efficiency of energy and resource utilization. Additionally, the stability analysis proves that the system is input to state stability. Ultimately, simulation verifies the effectiveness and feasibility of the developed method.

Solids retention time (SRT) control in the co-treatment of leachate with domestic sewage in aerobic granular sludge systems: Impacts on system performance, operational stability, and bioresource production

This study investigates the co-treatment of leachate and domestic sewage in municipal wastewater treatment plants using aerobic granular sludge (AGS) systems, focusing on granule formation, system stability, and resource production in two units (R1 and R2). In R2, solids retention time (SRT) was controlled between 10 and 25 days, while R1 maintained approximately 9 days. The results show that low leachate proportions (5 %) did not affect system performance or stability. However, increasing the leachate to 10 % reduced the structural stability of extracellular polymeric substances (EPS), leading to a significant decrease in alginate-like exopolysaccharides (ALE) production in R1 (216 mgALE/gVSS) and R2 (125 mgALE/gVSS). Principal component analysis revealed that SRT was crucial for optimizing biopolymer synthesis. Furthermore, SRT control in R2 improved filamentous control, biomass retention, and total nitrogen removal. Thus, selective biomass discharge is essential for maintaining granule stability, enhancing treatment efficiency, and supporting resource production.

Model-based assembly process planning for flexible aircraft cabin architectures

The configuration and equipment of an aircraft cabin has a significant impact on the passenger’s flight experience. To meet the needs of passengers and improve the flight experience, airlines repeatedly demand customised adaptations to the cabin design. The implementation of these changes requires a high degree of flexibility in production and can lead to difficulties in setting up a fixed final assembly line. In addition, unforeseen events and changes in the OEMs’ supply chain require a rapid response in aircraft production to be able to deliver on time. Digitalisation in product development and production planning makes it possible to overcome these challenges and makes an important contribution to flexibility, time and cost efficiency. This paper presents a digital approach to modelling and flexible planning of assembly processes of the cabin. To this end, aircraft design data is automatically linked to the assembly system to react quickly to design changes in the assembly planning process. The integration is realised in a system architecture model depicted with the systems modelling language (SysML). The architecture model follows the formal process description defined in VDI3682. A planning algorithm then uses the production architecture parameters to optimise the assembly processes, e.g. in terms of time. The approach presented is demonstrated using the example of scheduling the pre-assembly processes of the "crown module". The latter includes all structural and functional components above the window panels, such as overhead bins, electrics and air conditioning. The results show how changes in aircraft and cabin design or in the production plant and resources can be flexibly evaluated. This allows conceptual changes to be evaluated and traded before the cabin design is frozen and transferred to real production. These advantages contribute to the time and cost optimisation of aircraft production. This work thus makes a valuable contribution to the further development of digital solutions in aircraft production.

Energy and fertigation consumption and economic viability of a light blocking film in greenhouse lettuce production

High-technology greenhouses offer a promising avenue for enhancing global food security, yet their high operational energy costs, associated with cooling, remain a significant barrier to extensive utilisation in crop production, particularly in warm regions. This study evaluates the impact of Light Blocking Film (LBF) and different cooling technologies on lettuce production in high-technology greenhouses in Australia. The effect of LBF on cooling energy reduction and crop yield variation was evaluated over three lettuce trials, and the results were used to assess the commercial feasibility. LBF was found to slightly reduce average cooling energy expenditure and the average fertigation use by 24.2%. Despite these savings, LBF led to decreased crop yields of 6.2%–14% across three seasons and three different cultivars, highlighting a trade-off between resource use efficiency and productivity. Economic modelling indicates that integrating LBF with fan-pad systems could achieve a net present value of $1013 per m2, and a benefit-cost ratio of 2.11 through the lifespan. Conversely, the system combining LBF with fan-coil units showed a longer payback period of more than 17 years, emphasizing the importance of system compatibility. The study highlights the necessity for precision in the choice of greenhouse technologies to balance energy and resource sustainability with crop productivity. These findings serve as a guide for optimizing technology deployment in protected cropping systems to maximize agricultural, environmental and economic benefits.

Adoption of Life Cycle Thinking: Impact-driven comparative assessment of Japanese construction corporations’ trends in practices

Although life cycle thinking offers a well-founded set of concepts, methods, and tools for organizational contexts, only little is known about its relevance in the construction sector. In this sector, construction corporations are key players. In this work, a novel impact-driven method to assess the adoption of life cycle thinking by construction corporations is introduced. Japan, as a high-income country with a relatively long history of environmental policies informed by material flow analysis, is chosen as the context. Five Japanese construction corporations and respective reporting are used as case studies. Trends in environmental impacts over time of the case study corporations are assessed using two indicators: resource and carbon productivity. In comparison, an automated text corpus analysis workflow is presented to explore the corporate report’s life cycle thinking-related content in a meaningful way. Comparing the period of 2014–2018 and 2019–2023, an overall relative increase in framework adoptions (77%) and their integration in corporate categories (85%) in corporate reports indicates its increased procedural relevance among Japanese construction contractors. Findings show how the carbon indicator is embedded in various frameworks and, for instance, reveal an increased relevance of Scope 3 emissions as a framework on a low level. However, Scope 3 is also utilized as a performance indicator. To this end, considerable temporal differences in adoption practices are observed. Finally, a potentially effective corporate adoption model is identified through the comparative research design. The proposed method can be applied to other construction corporations and regional contexts.