Pruning waste (PW) and agricultural timber residue are barely treated, creating environmental pollution issues. A lack of regulations and environmental control criteria leads to poor ecosystems. Here we propose transforming PW from a nuisance into a valuable energy and environmental resource. Reuse and recycling options include turning the waste into a food source, or using it to generate energy, compost, soil fertilizer amendment and other products. A linear programming model with Boolean variables and a management model were defined and run for the reuse of PW. The management model defined the diverse options of PW reuse for resource recovery. These options depend to a considerable extent on the country’s production capacity and the preferred applied alternatives. The area of Israel was split into separate regions, which were classified according to preferred alternatives for PW treatment and reuse. These alternatives included factors such as annual amounts of trash generated, transportation expense, energy demand, and requirements based on annual and daily needs. An optimization model was defined and solved, subject to a series of constraints. The results showed that a net profit of approximately 3.5 million USD/year for a total community of close to 10x106 residents could be derived from the amounts of waste and improved environmental control, in addition to the additional energy source. This work raises the urgent need to regulate the recycling policies for PW in various environmental regions worldwide.
Abstract The rapid growth of population and construction activities has exacerbated environmental issues, necessitating the adoption of Circular Economy (CE) principles in the construction industry. Despite their benefits, CE implementation remains limited in developing countries, including Indonesia. This study aims to analyze CE practices within Architecture, Engineering, and Construction (AEC) firms with large qualifications in East Java, Indonesia to address the knowledge gap. A quantitative approach, utilizing a questionnaire survey targeting 18 CE-related items, was used and analyzed with descriptive statistics. The results show a partial implementation of CE practices, with mean values ranging from 2.5 to 3.5. However, the five most common implementations of CE principles in East Java’s construction industries include using modern construction methods such as prefabricated and modular products, ecological materials in design, Building Information Modeling (BIM) technology, waste prevention planning, and designing with non-toxic, durable, and reusable materials. The study suggests that there is still plenty of potential for improving and enhancing the integration of CE principles in East Java’s construction industries. This study contributes to revealing the current state of CE adoption among large-scale firms in East Java. It offers practical insights into which CE strategies are emerging and where implementation remains weak. These findings are intended to inform both academic understanding and policymaking, as well as support AEC companies’ efforts to enhance CE integration in similar regional contexts.
Asif Raihan, Syed Masiur Rahman, Mohammad Ridwan
et al.
This article analyzed the effect of various energy sources, energy efficiency, technological innovation, population size, and GDP on greenhouse gas (GHG) emissions in the United Kingdom. The annual data spanning from 1990 to 2021 is examined utilizing the Autoregressive Distributed Lag (ARDL) model. Results reveal that a 1 % rise in GDP, population, and fossil fuel consumption led to a 0.11 %, 0.16 %, and 0.60 % increase in GHG emissions in the short-run while 0.28 %, 0.23 %, and 0.74 % in the long-run. Besides, a 1 % improvement in renewable energy, nuclear power, energy efficiency, and technological innovation cut GHG emissions by 0.25 %, 0.13 %, 0.21 %, and 0.29 % in the short-term and 0.39 %, 0.28 %, 38 %, and 48 % in the long-run. The robustness analysis through the Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) demonstrates the consistency of the long-term effects obtained from the ARDL technique. The investigation provides novel insights essential for designing and implementing policies that advance the UK power industry's net-zero goals through cleaner energy, efficiency, and green technology investments.
Swathi Mukundan, Lennie Foster, Sharon Henson
et al.
This study examines the role of postdoctoral researchers, an often-overlooked segment of the UK workforce, in addressing high-level skill shortages in industries pursuing net-zero targets. A series of qualitative focus groups with industry stakeholders captures their perceptions of the suitability of postdoctoral researchers to enter the workforce, particularly regarding the technical, interdisciplinary, leadership, and communication capabilities essential for sustainable innovation. While our findings reveal a broad willingness, driven by demand, among industry stakeholders to employ postdoctoral researchers, they highlight persistent misalignments between academic training pathways and the broader skill sets required by industry as the primary barrier to implementation. The study provides practical insights into strengthening academic-industry collaboration, advancing work-integrated learning, and reconfiguring postdoctoral development to meet sectoral needs. By situating postdoctoral talent within a broader workforce strategy, this research contributes to ongoing debates on aligning research careers with net-zero transitions and building a future-ready, high-skill green economy.
Renewable energy sources, Environmental engineering
The underwater Internet of Things (UIoT) and remote sensing are significant for biodiversity preservation, environmental protection, national security, disaster assistance, and technological innovation. Assigning tasks to autonomous underwater vehicles (AUVs) is a fundamental challenge in underwater technology and exploration. Remote sensing and AUVs are vital for pollution detection, disaster prevention, marine observation, and ocean monitoring. This work presents an optimized network connectivity using a multi-attribute decision-making approach for underwater IoT deployment. A feature engineering approach highlights the significant characteristics of underwater things, incorporating remote sensing data, and a multi-objective optimization method is used to select optimal UIoT for effective task allocation in deep-sea environments. A balance between data transmission, energy economy, and operational performance is necessary for efficient task distribution. Effective communication algorithms and protocols are needed to maintain environmental sustainability, protect marine ecosystems, and improve underwater monitoring enhanced by remote sensing technologies. Multi-criteria decision-making (MCDM) is beneficial for addressing various challenges in underwater technology, considering factors such as mission objectives, energy efficiency, environmental conditions, vehicle performance, safety, and much more. The proposed criteria importance through intercriteria correlation (CRITIC) methodology will assess technical competencies like communication, resilience, navigation, and safety in an underwater environment, leveraging remote sensing and aiding decision-makers in selecting appropriate undersea devices and vehicles for enhancing communication and transportation. This method prioritizes characteristics and aligns them with specific objectives, improving decision-making quality in the marine environment.
Science, General. Including nature conservation, geographical distribution
The increasing demand for sustainable energy has brought biobutanol as a potential substitute for fossil fuels. The Clostridium genus is deemed essential for biobutanol synthesis due to its capability to utilize various substrates. However, challenges in maintaining fermentation continuity and achieving commercialization persist due to existing barriers, including butanol toxicity to Clostridium, low substrate utilization rates, and high production costs. Proper substrate selection significantly impacts fermentation efficiency, final product quality, and economic feasibility in Clostridium biobutanol production. This review examines underutilized substrates for biobutanol production by Clostridium, which offer opportunities for environmental sustainability and a green economy. Extensive research on Clostridium, focusing on strain development and genetic engineering, is essential to enhance biobutanol production. Additionally, critical suggestions for optimizing substrate selection to enhance Clostridium biobutanol production efficiency are also provided in this review. In the future, cost reduction and advancements in biotechnology may make biobutanol a viable alternative to fossil fuels.
Maryna Ivanova, Svitlana Sannikova, Olena Varyanichenko
et al.
The article examines the topical issue of risk management in foreign economic and logistics activities, which is closely related to the enterprise’s chosen strategy and ensures its sustainable development. The study considers the issue of developing a hedging strategy using statistical methods since adequate forecasting allows predicting the impact of external environment factors on the exchange rate, which will allow the enterprise to timely predict and mitigate the risks in foreign economic and logistics activities. The authors have used general scientific and special methods of systemic and structural analysis to clarify the directions of sustainable performance and risk management tools; formulate the goals and steps in choosing a strategy of hedging; compare the methods of foreign exchange rate risk hedging and perform correlation and regression analysis of factors that impact exchange rate under crisis conditions. The purpose of the paper is to study the specifics of ensuring the sustainable performance of an enterprise using statistical methods in risk management for planning foreign economic and logistics activities. The authors have proposed a definition of a hedging strategy based on the concepts, approaches, and ideas of asset and/or investment management with the aim of reducing loss through hedging instruments, whose feasibility can be substantiated by statistical methods. It has been found that the formation and successful implementation of a hedging strategy requires the use of statistical analysis in order to timely predict fluctuations in exchange rates. The findings of the research were tested based on the performance of PrJSC "Linde Gas Ukraine". In the strategy of hedging the exchange rate risks, it has been proposed to simultaneously open a foreign currency deposit and take a loan in the national currency to replenish the company's working capital. The perspective of further research is the implementation of the proposed hedging strategy and assessment of its effectiveness.
Prakash Saravanan, Antara Chatterjee, Gourav Dhar Bhowmick
The imperative to replace fossil fuels with renewable fuels, such as marine ecosystem-derived fuel and food, has spurred the development of a blue carbon economic model. Seaweed emerges as a pivotal element in this framework, demonstrating potential as a substantial carbon sink. Seaweed serves multiple purposes, encompassing climate change adaptation and mitigation and contributing to advancing a bioeconomy by reducing dependence on fossil fuels. Seaweed also holds promise as a source of human food, cattle feed, biofuels, renewable feedstocks, and other versatile applications. Numerous contemporary scientific publications, reputable organizations, and business resources offer illuminating insights and fresh perspectives on how seaweed can effectively contribute to the growing blue carbon economy, providing innovative tools for combating long-term climate change. This comprehensive review delves into the multifaceted potential of seaweed, concentrating on its contributions to carbon sequestration, its role as a blue carbon precursor, and the carbon-neutralization capabilities of both wild seaweeds and seaweed farming. Moreover, it explores the specific role of seaweed in the blue carbon economy, mainly as cattle feed in ruminant diets. In addition, seaweed cultivation has the potential to mitigate global climate change, promote economic development, and support sustainable livelihoods, offering a versatile solution to address pressing environmental and socioeconomic challenges. Received: 13 September 2023 | Revised: 5 November 2023 | Accepted: 2 December 2023 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Prakash Saravanan: Conceptualization, Methodology, Resources, Data curation, Writing - original draft, Visualization. Antara Chatterjee: Conceptualization, Methodology, Resources, Data curation, Writing - review & editing, Visualization. Gourav Dhar Bhowmick: Conceptualization, Data curation, Writing - review & editing, Supervision, Project administration, Funding acquisition.
Laura B. Vedovato, Lidiany C. S. Carvalho, Luiz E. O. C. Aragão
et al.
Drought and fire reduce productivity and increase tree mortality in tropical forests. Fires also produce pyrogenic carbon (PyC), which persists in situ for centuries to millennia, and represents a legacy of past fires, potentially improving soil fertility and water holding capacity and selecting for the survival and recruitment of certain tree life-history (or successional) strategies. We investigated whether PyC is correlated with physicochemical soil properties, wood density, aboveground carbon (AGC) dynamics and forest resistance to severe drought. To achieve our aim, we used an Amazon-wide, long-term plot network, in forests without known recent fires, integrating site-specific measures of forest dynamics, soil properties and a unique soil PyC concentration database. We found that forests with higher concentrations of soil PyC had both higher soil fertility and lower wood density. Soil PyC was not associated with AGC dynamics in non-drought years. However, during extreme drought events (10% driest years), forests with higher concentrations of soil PyC experienced lower reductions in AGC gains (woody growth and recruitment), with this drought-immunizing effect increasing with drought severity. Forests with a legacy of ancient fires are therefore more likely to continue to grow and recruit under increased drought severity. Forests with high soil PyC concentrations (third quartile) had 3.8% greater AGC gains under mean drought, but 33.7% greater under the most extreme drought than forests with low soil PyC concentrations (first quartile), offsetting losses of up to 0.68 Mg C ha–1yr–1 of AGC under extreme drought events. This suggests that ancient fires have legacy effects on current forest dynamics, by altering soil fertility and favoring tree species capable of continued growth and recruitment during droughts. Therefore, mature forest that experienced fires centuries or millennia ago may have greater resistance to current short-term droughts.
Предмет дослідження – процеси побудови та поповнення баз знань, повторного використання знань, і створення програмних систем на основі баз знань, інтерпретація знань як один із підходів до повторного їх застосування, що полягає у виведенні нових знань на основі наявних фактів у базі знань. Мета дослідження – розроблення методу повторного використання знань за допомогою вирішення логічних рівнянь скінченних предикатів для певної предметної галузі. Для досягнення поставленої мети визначено такі завдання: дослідити дескриптивні підходи до логічного моделювання предметної галузі, що дають змогу повторного використання знань, заданих системою логічних рівнянь у межах алгебри скінченних предикатів; розробити метод поповнення бази знань у формі предикатних рівнянь за допомогою вилучення змінних із логічних систем, де рівняння є складними логічними зв’язками між дискретними ознаками об’єктів або процесів. Використано такі методи: алгебра скінченних предикатів, кванторні операції з предикатами для інтерпретації знань. Здобуто такі результати: проаналізовано дескриптивні методи повторного використання знань; запропоновано метод поповнення бази знань у формі логічних рівнянь з метою спрощення подальшого використання неявних зв’язків між дискретними ознаками; розглянуто приклад поповнення бази знань медичної галузі, що дає змогу повторного використання знань, заданих неявно. Висновки. Запропонований метод дає змогу поповнювати базу знань у формі логічних рівнянь способом додавання предикатних рівнянь, що пов’язують окремі набори дискретних змінних, які цікавлять ученого або практика. Метод поповнення бази знань оснований на додаванні нових спрощених рівнянь; спрощені предикатні рівняння моделюють логічні закономірності, що неявно містяться в основній базі знань; проведено експериментальне дослідження.
This research explores the integration of biometric payment systems with power system engineering within the Indian financial sector. It aims to understand and optimize this convergence by examining the current state, assessing power consumption patterns, evaluating regulatory compliance, and providing holistic insights. Utilizing a mixed-method approach including qualitative interviews, focus group discussions, and quantitative surveys, the study uncovers variations in biometric adoption rates among financial institutions, highlighting the correlation with power consumption and the necessity for standardized frameworks. The findings underscore the importance of balancing technology adoption, energy efficiency, and data protection. Practical implications include informed decision-making for financial institutions and refined policies for regulatory authorities to foster a secure, efficient, and sustainable payment ecosystem. This research contributes to existing knowledge by offering comprehensive insights and emphasizes the need for energy-efficient strategies and robust regulatory standards. Overall, it advances our understanding of this convergence, paving the way for a more secure and sustainable financial technology landscape in India.
Abdulqader M. Almars, Malik Almaliki, Talal H. Noor
et al.
In the age of social media, the spread of rumors is becoming easier due to the proliferation of communication and information dissemination platforms. Detecting rumors is a major problem with significant consequences for the economy, democracy, and public safety. Deep learning approaches were used to classify rumors and have yielded state-of-the-art results. Nevertheless, the majority of techniques do not attempt to explain why or how decisions are made. This paper introduces a hybrid attention neural network (HANN) to identify rumors from social media. The advantage of HANN is that it will allow the main user to capture the relative and important features between different classes as well as provide an explanation of the model’s decisions. Two deep neural networks are included in the proposal: CNNs and Bidirectional Long Short Term Memory (Bi-LSTM) networks with attention modules. In this paper, the model is trained using a benchmark dataset containing 3612 distinct tweets crawled from Twitter including several types of rumors related to COVID-19. Each subset of data has a balanced label distribution with 1480 rumors tweets (46.87%) and 1677 non-rumors tweets (53.12%). The experimental results demonstrate that the new approach (HANN model) performs better results in terms of performance and accuracy (about 0.915%) than many contemporary models (AraBERT, MARBEART, PCNN, LSTM, LSTM-PCNN and Attention LSTM). Moreover, a number of software engineering features such as followers, friends, and registration age are used to enhance the model’s accuracy.
The industrial sector is the most important in the structure of the economy of the Russian Federation. Industry has a significant impact on the economic development of the country, on the entire course of expanded reproduction in the country. Mechanical engineering, metallurgy, chemical production, the production and processing of hydrocarbons, and transport vehicles are the most developed in the regions of Russia. Industrially developed regions differ by industry and level of technological development. After conducting research on the indicators and dynamics of industrial production, it is possible to identify the most successful industrially developed regions. The introduction of new technologies requires significant financial resources, and many enterprises have problems with investments. The production of those regions that actively introduce new technologies is effective.
It is shown that the industrial revolution led to the creation of digital production facilities, the automation and robotization of which accelerated production processes and significantly increased quality indicators. Digital transformation is the leading direction of technological development of the industry. The study reveals the role of new technologies, points to the need for their intensive implementation in the industrial sphere, analyzes the state of industry in the regions, reveals the role of digital platforms. It is emphasized that Industry 4.0 requires leading production managers to review their strategic priorities. Digital technologies provide for the creation of communication networks, digital platforms for working with various data, as well as a research base in the country.
The participation of the state in the implementation of regional strategies and the formation of high-tech industries is an important mechanism for the implementation of economic policy. The article considers the regions of Russia where the industrial production potential is high and Industry 4.0 technologies are being successfully implemented. It analyzes the extent to which the Russian industry has mastered advanced digital technologies, the scope of application of digital automated lines and modern software products. The role of digital technologies in production management, in the dissemination of knowledge and the promotion of new developments on world markets is revealed. Knowledge, intellectual resources, information technologies, automated systems, the developed infrastructure of the national innovation system, a modern technological platform, and high technologies play an important role in the activation of the innovation process.
Effective investment in industry contributes to increasing the competition of manufactured products, updating the technological base. Digital transformation of manufacturing industries is carried out on the basis of the latest equipment, new machines. It is shown that the key factor for the successful functioning of the economy is the high level of development of science, the creation and application of innovative technologies, standardization in the field of high technologies. The main objectives of the established development centers are the activation of innovation activities in the regions, the concentration of resources and factors of production in a limited area
Sylwester Kaczmarzewski, Piotr Olczak, Maciej Sołtysik
In Poland, a dynamic increase in the share of renewable energy sources in the national energy mix has been observed in recent years. Until now, these were mainly installations used for the needs of single-family houses and large-scale installations used on the RES auction market. However, due to the fact that the carbon footprint of the offered products is taken into account, this aspect is becoming more and more important. The carbon footprint can be offset by, among others, by covering the energy needs of the industrial plant by its own renewable energy sources. The article analyzes four sample electricity demand profiles of production plants operating in the mining industry, mainly located in Upper Silesia. Using statistical methods, the fitting of potential photovoltaic sources production profiles to the electricity consumption profiles in the analyzed case studies was checked. The analysis was carried out for each hour of the day and for the profiles weighted by the electricity price from the Polish Power Exchange on the Day-Ahead Market, because matching profiles at different hours has a different monetary value and, as a result, a different impact on operation costs. The highest correlation coefficient between electricity consumption and insolation on an annual basis was −0.29 in the Spearman rho-statistic for the case of M1 enterprise. On the other hand, the highest value at the level of 0.48 was achieved by the Pearson r-correlation coefficient determined on a monthly basis between the monetary value of electricity consumed and insolation in June for the M2 enterprise.
Christiana Ada Paul, Douglas Omoregie Aghimien, Ahmed Doko Ibrahim
et al.
Unethical practices have been a reoccurring menace in the construction industry globally, with its negative impact reported in existing studies. While several studies have explored issues touching on ethics, ethics compliance and unethical practices within the construction industry, the problems persist especially in developing countries. It is based on this notion that this study assessed the possible measures that could help curb unethical practices in the construction industry with specific reference to Quantity Surveyors (QS). The study adopted a quantitative approach with structured questionnaires used to garner information from registered QS in Nigeria. Data analysis was done using relevant descriptive and multivariate analysis. The reliability of the instrument used was also tested using Cronbach alpha test. The findings revealed that while QS are no strangers to unethical practices, most cases are not reported to the appropriate authorities. The most prevalent of these practices are payment-related and contract-related. To curb these practices, random inspections and development of ethical compliance, ensuring a good reporting and punishment system, and increase ethical awareness through QS organised programmes are needed. The findings of this study would assist the professional bodies and organisations within the industry to effectively enforce ethical conduct among their members and staff.
Introduction. In the conditions of dependence on the imported energy resources there is a problem of ensuring stability of the energy industry with counteraction to changes of the ambient and a possibility of reacting to actions for providing competitive positions and advantages of the state. A number of problems in energy industry need a support of necessary level of the energy security on the basis of providing own extraction with volume reduction of imported energy resources, increasing of the national products’ competitiveness in the world markets, development of innovations and investments into energy efficient technologies. In such conditions, it’s important to apply actions for ensuring economic security of the energy sector through the creating of an efficient program for the protection of the national interests in the energy sector, which will contribute to the national economy development.
Aim and tasks. The purpose of article is a researching of energy security and developing actions for state regulation of energy security.
Research results. The article outlines the priority directions of the state policy on ensuring the energy sector development which are identified as a main risks and adverse factors of influence on functioning of energy industry of Ukraine. And the necessity of energy security systems formation at the state level is grounded. The perspective increasing directions of energy security are the establishment of more adapted to transformations system of state regulation with market self-regulation elements. The state regulation of energy security in conditions of high level internationalization of national economy should be aimed at the harmonization of its technological and institutional aspects which influence the development and implementation of energy technologies and projects related to renewable energy sources. The state regulation requires further active development of institutional conditions for use of alternative energy resources and energy saving based on renewable energy.
Conclusion. To provide energy security it is necessary to improve the complex program of its development which will involve wide use of state regulation methods as well as public-private partnership development so the support of the implementation of investment projects will be provided. The important aspect in development of energy engineering is ensuring its economic security which will allow to level possible threats of the industry and to provide requirements of fuel and energy complex and industry for a long term. Energy security should be directed towards increasing energy efficiency which will promote reducing imports and depending on the supply of energy resources by other countries. State regulation of energy security should ensure the rational use of the energy sector potential and stable functioning of the energetic supply system which includes: implementation of energy efficiency and energy saving policies; increase of investment in energy engineering; reduction of environmental impact and emissions.
The purpose of the article is to study the state of the regional industrial complex of the old industrial region of the East of Ukraine, which suffered as a result of the military-political conflict that began in 2014. One of the objectives of the study is to analyse the process of destroying the foundations of the regional economy, as well as to assess the significance of the loss of Donbas industries for the stable socio-economic development of all regions of Ukraine. Methodology. The method of analysis made it possible to study the process of destruction of industrial enterprises in the basic sectors of the regional economy of Donbas since the beginning of the military-political conflict. The author defined the schemes of the operation of a part of enterprises operating in the temporarily occupied territory of the East of Ukraine, who, becoming hostages to the situation, were forced to cooperate with representatives of the illegal authorities of the unrecognized republics to preserve production. Result. The statistical method is used to analyse the financial and economic performance of industrial enterprises, with the purpose of assessing their role in the state economy of the country as a whole. The method of system analysis allowed the author to estimate the damage caused by the loss in the state economy of coal supplies, which was previously mined in the mines of Donbas. Thus, the fact of a decrease in industrial production in the east of the country was argued, which led to a significant drop in Ukraine’s exports in general in such areas as supplies of ferrous metals, engineering products, and non-ferrous metallurgy. Practical implication. The author analysed the facts of loss, as a result of dismantling and export of equipment, strategically important enterprises of the militaryindustrial complex of the country. The article reflects the problem of the growing ecological danger that has arisen as a result of the lack of control over the closed enterprises of the coal mining industry and the chemical industry. In addition, in the course of active hostilities, a number of industrial objects suffered significant damage, which leads to uncontrolled emissions of harmful substances into the atmosphere. The shutdown of mines and concentrators created yet another problem – the discharge of mine waters, their access to the surface, the flooding of significant areas and the entry of toxic waters into rivers that serve as a source of drinking water for residents, both the conflict region and the country as a whole, and neighbouring states. Also, the technogenic threat is represented by the methane gas output to the surface displaced by groundwater. Value/originality. The results of the research made it possible to depict the dynamics of the destruction of the economic complex of the old industrial region as a result of military operations in the territory of the state and illegal export of equipment of enterprises. All these actions led to the launch of negative processes in the Ukrainian economy, provoking a deep social and economic crisis, which accelerated the destruction of the metallurgical, coal and chemical industries in the region. Thus, today it is necessary to conduct an inventory of surviving and continuing enterprises, to quickly identify the risk zone, and develop strategies for minimizing and overcoming them in key sectors of the economy.
Aiming at the nonstationary characteristic of a gear fault vibration signal, a recognition method based on permutation entropy of ensemble local characteristic-scale decomposition (ELCD) and relevance vector machine (RVM) is proposed. First, the vibration signal was decomposed by ELCD; then a series of intrinsic scale components (ISCs) were obtained. Second, according to the kurtosis of ISCs, principal ISCs were selected and then the permutation entropy of principal ISCs was calculated and they were combined into a feature vector. Finally, the feature vectors were input in RVM classifier to train and test and identify the type of rolling bearing faults. Experimental results show that this method can effectively diagnose four kinds of working condition, and the effect is better than local characteristic-scale decomposition (LCD) method.