Maria Kozlovska, Ivana Halaszova, Daniela Kaposztasova
et al.
IntroductionUniversity campuses in Central Europe, like elsewhere, are under increasing pressure to adopt flexible, climate-responsive, and ecological infrastructure that improves both environmental performance and student experience. In this study, we introduce a hexagonal modular unit (HEXA unit) designed to revitalize underused campus spaces through green infrastructure.MethodsWe combined a survey of 190 campus users, statistical tests for reliability and associations, and a Life Cycle Assessment.ResultsThe survey revealed that students strongly prefer natural materials like wood and vegetation and favor multifunctional module configurations that enhance social interaction and collaborative learning. Reliability (Cronbach's Alpha) supported consistency in our attitudinal measures; Chi-square tests revealed significant differences in material preferences. Our LCA shows that HEXA units built with natural materials can reduce carbon footprint by up to ~30% compared to traditional synthetic designs.DiscussionBeyond environmental gains, the findings suggest that modular design choices can also enhance student engagement and support more resilient campus ecosystems. Overall, HEXA represents a scalable model for green infrastructure that can be adapted by universities and potentially extended to other urban contexts in support of sustainability goals.
Abstract In coal mines, dynamic disasters such as rock bursts seriously threaten the safety of mining activities. Exploring the dynamic behaviors and disaster characteristics in the impact failure process of coal serves as the basis and prerequisite for monitoring and warning rock bursts. In this context, impact failure tests of coal were carried out under different axial static loads and impact velocities to analyze the dynamic behaviors and acoustic emission (AE) response characteristics of coal. The results show that the dynamic behaviors of coal under combined dynamic and static loads are significantly different from those under static loads, and the stress‐strain curve displays double peaks without an obvious compaction stage. As the axial static load grows, the dynamic strength and peak strain both have a quadratic function with the axial static load. When the coal damage intensifies instantaneously, the AE count and energy parameters both witness pulse‐like increases and reach their peak values. The damage effect of axial static loads on coal, though limited, has an extreme point. In contrast, the impact velocity can strengthen the response of AE signals and has linear function relationships with the peak values of AE count and energy. This plays a leading role in the damage to samples and sets a critical point for coal failure and fracture. Compared with the analysis results of stress and strain, the responses of AE signals are more accurate and reliable. Based on AE response characteristics, the damage evolution process of coal under the combined dynamic and static loads can be identified more accurately to reveal the moment corresponding to coal damage and the characteristics of coal failure. The research results are conducive to the further application of AE monitoring methods to early warning of rock burst disasters in coal mining sites.
Engineering geology. Rock mechanics. Soil mechanics. Underground construction
Meilita Tryana Sembiring, Novika Zuya, Muhammad Riezky Anindhitya Laksmana
et al.
Logistics efficiency is critical to operational success in manufacturing, especially for corrugated carton manufacturers. The challenges of this type of manufacturing include optimizing truck utilization, without which high costs, resource waste, and customer dissatisfaction can occur. Transportation consolidation can reduce trips, increase vehicle capacity, and lower carbon emissions. This study proposes a delivery optimization model using genetic algorithms within the Multi-Objective Evolutionary Algorithm (MOEA) framework. The results show that the model significantly improves fleet utilization from 75% to 100% and reduces delivery delays by adhering to predefined time windows, thereby improving cost efficiency and customer satisfaction.
Accurate classification of electrocardiogram (ECG) signals is vital for reliable arrhythmia diagnosis and informed clinical decision-making, yet real-world datasets often suffer severe class imbalance that degrades recall and F1-score. To address these limitations, we introduce MAK-Net, a hybrid deep learning framework that combines: (1) a four-branch multiscale convolutional module for comprehensive feature extraction across diverse waveform morphologies; (2) an efficient channel attention mechanism for adaptive weighting of clinically salient segments; (3) bidirectional gated recurrent units (BiGRU) to capture long-range temporal dependencies; and (4) Kolmogorov–Arnold Network (KAN) layers with learnable spline activations for enhanced nonlinear representation and interpretability. We further mitigate imbalance by synergistically applying focal loss and the Synthetic Minority Oversampling Technique (SMOTE). On the MIT-BIH arrhythmia database, MAK-Net attains state-of-the-art performance—0.9980 accuracy, 0.9888 F1-score, 0.9871 recall, 0.9905 precision, and 0.9991 specificity—demonstrating superior robustness to imbalanced classes compared with existing methods. These findings validate the efficacy of multiscale feature fusion, attention-guided learning, and KAN-based nonlinear mapping for automated, clinically reliable arrhythmia detection.
The circular economy offers a vital avenue for sustainable development by optimizing resource utilization through reusing and recycling materials. This study focuses on the lifecycle assessment (LCA) of a 5 MW alkaline water electrolysis (AWE) system, emphasizing end-of-life (EoL) strategies, material recovery, and their environmental implications. Focusing on the recycling and reuse of critical materials—including stainless steel and nickel—we argue that enhancing material efficiency in AWE systems can lead to significant reductions in global warming potential (GWP). Our LCA reveals that manufacturing an AWE system from recycled materials results in a 50% decrease in GWP compared to virgin materials. Despite the operational focus of previous studies, our research uniquely incorporates comprehensive EoL considerations, assessing realistic recycling scenarios that highlight potential material recovery and component reuse after the system’s 20-year lifespan. Notably, 77% of materials in the AWE system can be recycled or reused, though the substantial environmental impacts of certain components, particularly the inverter and nickel, necessitate ongoing research and improved recycling technologies. This study underscores the critical role of systematic recycling and the strategic selection of materials to enhance the sustainability profile of hydrogen production technologies. By bridging the gap between operational efficiency and EoL management in AWE systems, our findings contribute to the broader aim of advancing circular economy principles in clean energy transitions. Ultimately, the research emphasizes the need for integrating innovative recycling methods and material reuse strategies to lower carbon footprints and enhance resource security, aligning with sustainable industrial practices and future energy demands.
Ajinath Dukare, Rahul Yadav, Sheshrao Kautkar
et al.
Cotton-based textile industries sustain millions of people’s livelihoods and are significant sources of revenue for the nation’s economy. The enormous amount of biomass, processing wastes, and byproducts generated during cotton processing are usually landfilled or incinerated, which is the cause of environmental pollution and health hazards. Cotton biomass, mainly comprised of cellulose, hemicellulose, and lignin, represents a sustainable feedstock for the fermentative production of value-added bioproducts using microorganisms. Advances in microbial biotechnology have led to the effective valorization of cotton biomass and processing waste into valuable products. To date, cotton-based waste biomaterial has been utilized for microbial production of biofuel, hydrogen, biomethane, enzymes, organic acids, bio-enriched compost, and as a substrate for mushroom cultivation. Furthermore, the use of cotton biomass for developing fungal mycelial-based composite and eco-friendly packaging material is documented. Cotton seed meal, an essential byproduct of the cottonseed industry, is converted into more proteinous products and bioactive peptides via microbial-mediated degossypolization and fermentation. The potential of modern metabolic engineering tools such as gene sequencing and assembly, genome editing, clustered regularly interspaced short palindromic repeats (CRISPR), and cell surface engineering for microbial strain development is summarized. This is the first comprehensive review highlighting the aspects of cotton biomasses and byproducts, their structural composition, pretreatment strategies, and microbial approaches for bioconversion into valuable compounds. This document presents the cotton processing industry with an innovative pathway towards a waste-to-wealth solution via microbial-based biorefineries.
A methodic approach to the Lorenz curve application in the efficiency analysis of the Oil-Gas Production Department (OGPD) main production well stocks usage is developed. The scientific-researchwork consists of two stages: preliminary and main. In the preliminary stage, gathering and systematizationof major technical-economic, accounting, geological and other indexes are conducted, the basic chart forthe OGPD well survey is developed. In main stage, considering well division by quintile, the followingaction are carried out: 1) the factorial application of the Lorenz curve (calculation); 2) calculation of return on assets by all wells, as well as necessary calculations on determinant factors influencing return onassets. They are followed by the Lorenz curve plotting on determinant factors. Then, based on well division by quintile, the graphs on return of assets and determinant factors are developed.
Pascal Otto, Mozhdeh Alipoursarbani, Daniel Torrent
et al.
A demonstrator plant of a recently patented process for improved sludge degradation has been implemented on a municipal scale. In a 1500 m<sup>3</sup> sewage sludge digester, an intermediary stage with aerobic sewage sludge reactivation was implemented. This oxic activation increased the biogas yield by up to 55% with a 25% reduction of the remaining fermentation residue volume. Furthermore, this process allowed an NH<sub>4</sub>-N removal of over 90%. Additionally, 16S rRNA gene amplicon high-throughput sequencing of the reactivated digestate showed a reduced number of methane-forming archaea compared to the main digester. Multiple ammonium-oxidizing bacteria were detected. This includes multiple genera belonging to the family Chitinophagaceae (the highest values reached 18.8% of the DNA sequences) as well as a small amount of the genus <i>Candidatus nitrosoglobus</i> (<0.3%). In summary, the process described here provides an economically viable method to eliminate nitrogen from sewage sludge while achieving higher biogas yields and fewer potential pathogens in the residuals.
Abstract Integrating nanoparticles in waste oil-derived biodiesel can revolutionize its performance in internal combustion engines, making it a promising fuel for the future. Nanoparticles act as combustion catalysts, enhancing combustion efficiency, reducing emissions, and improving fuel economy. This study employed a comprehensive approach, incorporating both quantitative and qualitative analyses, to investigate the influence of selected input parameters on the performance and exhaust characteristics of biodiesel engines. The focus of this study is on the potential of using oils extracted from food waste that ended up in landfills. The study's results are analysed and compared with models created using intelligent hybrid prediction approaches including adaptive neuro-fuzzy inference system, Response surface methodology-Genetic algorithm, and Non sorting genetic algorithm. The analysis takes into account engine load, blend percentage, nano-additive concentration, and injection pressure, and the desired responses are the thermal efficiency and specific energy consumption of the brakes, as well as the concentrations of carbon monoxide, unburned hydrocarbon, and oxides of nitrogen. Root-mean-square error and the coefficient of determination were used to assess the predictive power of the model. Comparatively to Artificial Intelligence and the Response Surface Methodology-Genetic Algorithm model, the results provided by NSGA-II are superior. This is because it achieved a pareto optimum front of 24.45 kW, 2.76, 159.54 ppm, 4.68 ppm, and 0.020243% for Brake Thermal Efficiency, Brake Specific Energy Consumption, Oxides of nitrogen, Unburnt Hydro Carbon, and Carbon monoxide. Combining the precision of ANFIS's prediction with the efficiency of NSGA-optimization II's gives a reliable and thorough evaluation of the engine's settings. The qualitative assessment considered practical aspects and engineering constraints, ensuring the feasibility of applying the parameters in real-world engine applications.
The object of the study is the processes of building groups of symmetric double-operand operations of cryptographic coding of information. The subject of the study are features of the implementation of a generalized method of synthesis groups of symmetric two-operand operations of cryptographic coding information for "lightweight cryptography". The purpose of this work is to investigate the process of building and implementing a method of synthesis of groups of symmetric multibit double-operand operations of information cryptographic coding to provide automation for finding ways to increase the variability, and stability of lightweight cryptoalgorithms. The following tasks are solved in the article: to determine the mathematical group of single-operand operations, on the basis of which the realization of the method of synthesis of groups of symmetric double-operand operations of cryptographic coding will be presented; to offer the search technology of symmetric double-operand operations; to evaluate power of synthesized groups of operations, and their influence on variability and stability of " lightweight cryptography" algorithms. The following results were obtained: the technology for determining symmetric double-operand operations, which will be the basis for the synthesis of a group of symmetric double-operand operations, was proposed. A method for synthesizing groups of symmetric double-operand cryptographic information coding operations for block encryption systems was proposed and implemented. On the example of module-two addition with correction and the use of three-digit single-operand operations, the practical implementation of this method was shown. Based on the synthesized operations and the given quantitative characteristics of the set of single-operand operations, the power of synthesized groups of operations and their influence on the variability and stability of "lightweight cryptography" algorithms were evaluated. Conclusions: the proposed and implemented method of synthesis of groups of symmetric double-operand operations of cryptographic coding information allows to provide the possibility of increasing the variability of lightweight crypto-algorithms. Synthesis of symmetric cryptographic coding operations belonging to different mathematical groups provides increase of algorithm's crypto stability. Application of synthesized cryptographic coding operations leads to significant increase of variability of cryptoalgorithms and their complexity.
Scientific and technological progress amid the process of global digitalisation has prompted the demand for professions in relevant fields such as logistics, analytics, agriculture, industrial manufacturing, transport, and primarily for engineering and technical workers. Russian railways require not only physical infrastructure, but also digital skills of its operation by engineering and technical workers in order to integrate into the digital economy. The aim of the article is to study modern requirements for the professional competencies of railway engineers, primarily their digital literacy and the ability to work with special software. The authors mention the need for an engineer to have softskills and hardskills. The article provides a list of the main software complexes that are included in the special digital competencies of a railway engineer.The authors of the article through the example of railway transport, describe the directions of digitalisation of railway transport, which is a link between the branches of the national and partly global economy. The emphasise the advanced development of scientific and technological progress in the transport industry – the “Digital Railway” project, which generates related tasks, one of which is the modern training of engineering personnel and the consolidation of digital competencies and metaskills in professional standards.
CPUs are widely used in many industries. These components require electrical energy for processing and generating heat due to their electrical resistance. On the other hand, they have a very high heat flux due to their small size and high energy consumption. Therefore, their cooling with new methods helps their performance a lot. In this study, water flow with Nano-encapsulated phase change material (NPCM) was simulated to cool an embedded CPU inside a mini channel. These NPCMs have a significant effect on heat transfer parameters due to their ability to phase change in their core. On the other hand, examining the exert economy broadens our horizons to choose an appropriate system in practical problem engineering. Numerical simulation by the FVM method was utilized to study the effects of Reynolds numbers, heat flux of CPU's surface, and volume fraction on the temperature distribution, the maximum temperature of CPU's surface, and economic efficiency. Evidence showed that increasing Reynolds number from 50 to 100 at zero volume fraction reduces the maximum temperature of the CPU's surface from 98.4to82.5°C. Also, mixing a 3% volume fraction of NPCM with pure water can decrease the maximum temperature of the CPU's surface by 2.27°C relative to pure water. Moreover, rising Reynolds number from 50 to 100 enhanced the net profit per unit transferred heat load (ηp) by 100 times.
Air India, the prestige of Tatas has the history dates to 1930s. The Air India was founded about 90 years ago as Tata Airlines and first ride was taken by the founder himself, J. R. D. Tata from Karachi to Bombay. The journey of Air India is an emotional rather than commercial. The Air India was nationalized by Government of India decades ago, but its progress under national entity is limited only for few decades. When the private carriers came into the field, and because of maintenance with respect to operations and human resource, the Air India was treated to be not only a company with loss, but also as a burdened national entity. In the process of disinvestment by Government of India, the Air India has arrived back at the Tata’s group. In this paper, a case study of Air India was presented covering all major milestones and inferences are presented.
The purposes of this review are to summarize the historical progress in the last 60 years of lightweight metal forming, to analyze the state-of-the-art, and to identify future directions in the context of Cyber-physically enabled circular economy. In honoring the 100th anniversary of the establishment of the Manufacturing Engineering Division of ASME, this review paper first provides the impact of the metal forming sector on the economy and historical perspectives of metal forming research work published by the ASME Journal of Manufacturing Science and Engineering, followed by the motivations and trends in lightweighting. To achieve lightweighting, one needs to systematically consider: (1) materials and material characterization; (2) innovative forming processes; and (3) simulation tools for integrated part design and process design. A new approach for process innovation, i.e., the Performance-Constraints-Mechanism-Innovation (PCMI) framework, is proposed to systematically seek new processes. Finally, trends and challenges for the further development in circular economy are presented for future exploration.
Abstract Background Indigo is a color molecule with a long history of being used as a textile dye. The conventional production methods are facing increasing economy, sustainability and environmental challenges. Therefore, developing a green synthesis method converting renewable feedstocks to indigo using engineered microbes is of great research and application interest. However, the efficiency of the indigo microbial biosynthesis is still low and needs to be improved by proper metabolic engineering strategies. Results In the present study, we adopted several metabolic engineering strategies to establish an efficient microbial biosynthesis system for converting renewable carbon substrates to indigo. First, a microbial co-culture was developed using two individually engineered E. coli strains to accommodate the indigo biosynthesis pathway, and the balancing of the overall pathway was achieved by manipulating the ratio of co-culture strains harboring different pathway modules. Through carbon source optimization and application of biosensor-assisted cell selection circuit, the indigo production was improved significantly. In addition, the global transcription machinery engineering (gTME) approach was utilized to establish a high-performance co-culture variant to further enhance the indigo production. Through the step-wise modification of the established system, the indigo bioproduction reached 104.3 mg/L, which was 11.4-fold higher than the parental indigo producing strain. Conclusion This work combines modular co-culture engineering, biosensing, and gTME for addressing the challenges of the indigo biosynthesis, which has not been explored before. The findings of this study confirm the effectiveness of the developed approach and offer a new perspective for efficient indigo bioproduction. More broadly, this innovative approach has the potential for wider application in future studies of other valuable biochemicals’ biosynthesis.
Abstract 2D materials, such as graphene, black phosphorous and transition metal dichalcogenides, have gained persistent attention in the past few years thanks to their unique properties for optoelectronics. More importantly, introducing 2D materials into silicon photonic devices will greatly promote the performance of optoelectronic devices, including improvement of response speed, reduction of energy consumption, and simplification of fabrication process. Moreover, 2D materials meet the requirements of complementary metal‐oxide‐semiconductor compatible silicon photonic manufacturing. A comprehensive overview and evaluation of state‐of‐the‐art 2D photonic integrated devices for telecommunication applications is provided, including light sources, optical modulators, and photodetectors. Optimized by unique structures such as photonic crystal waveguide, slot waveguide, and microring resonator, these 2D material‐based photonic devices can be further improved in light‐matter interactions, providing a powerful design for silicon photonic integrated circuits.
The construction industry has been accused of ineffectiveness and inefficiency because of delays, cost overruns and defects that are partly due to flaws in the design. As professionals responsible for design, architects should achieve optimum performance in the project delivery process. This study aims to investigate the factors that influence the performance of architects in construction projects. This study employs a questionnaire survey for data collection and partial least square structural equation modelling (PLS–SEM) for data analysis. Using a census method, a total of 222 useable responses are gathered from registered architects in Indonesia. Results reveal significant and positive relationships between working condition, organisational support and effective design process and the performance of architects. The strongest effect is found from the influence of effective design process on the performance of architects. Thus, these factors should be applied to enhance the performance of architects, thereby improving the project outcome.
As Chinese economy changes from rapid-speed growth to superior-quality development mods, cultivating the talents for the emerging industries must keep up with The Times to make corresponding adjustments, as well as based on information technology, adopting the multi-paradigm training mode to cultivate amounts of the new engineering talents with cross-knowledge system and innovation.This paper discusses how to take advantage of the creative knowledge map of hourglass to rapidly promote students’ professional ability and the cultivation of their innovation in virtue of online courses, and finally comes to an exploration model.