bluuebunny/crossref_metadata_2025 huggingface dataset:
A Robust Chronic Kidney Disease Classifier Using Machine Learning
Authors: Swain Debabrata , Mehta Utsav , Bhatt Ayush , Patel Hardeep , Patel Kevin , Mehta Devanshu , Acharya Biswaranjan , Gerogiannis Vassilis C. , Kanavos Andreas , Manika Stella
Published: January 2023

Clinical support systems are affected by the issue of high variance in terms of chronic disorder prognosis. This uncertainty is one of the principal causes for the demise of large populations around the world suffering from some fatal diseases such as chronic kidney disease (CKD). Due to this reason, the diagnosis of this disease is of great concern for healthcare systems. In such a case, machine learning can be used as an effective tool to reduce the randomness in clinical decision making. Conventional methods for the detection of chronic kidney disease are not always accurate because of their high degree of dependency on several sets of biological attributes. Machine learning is the process of training a machine using a vast collection of historical data for the purpose of intelligent classification. This work aims at developing a machine-learning model that can use a publicly available data to forecast the occurrence of chronic kidney disease. A set of data preprocessing steps were performed on this dataset in order to construct a generic model. This set of steps includes the appropriate imputation of missing data points, along with the balancing of data using the SMOTE algorithm and the scaling of the features. A statistical technique, namely, the chi-squared test, is used for the extraction of the least-required set of adequate and highly correlated features to the output. For the model training, a stack of supervised-learning techniques is used for the development of a robust machine-learning model. Out of all the applied learning techniques, support vector machine (SVM) and random forest (RF) achieved the lowest false-negative rates and test accuracy, equal to 99.33% and 98.67%, respectively. However, SVM achieved better results than RF did when validated with 10-fold cross-validation.
Multi-Micro-Grid Main Body Electric Heating Double-Layer Sharing Strategy Based on Nash Game
Authors: Wang Hui , Wang Chenglin , Zhao Liang , Ji Xiu , Yang Chengdong , Wang Jiarui
Published: January 2023

In order to promote energy mutual aid among microgrids, expand the types of energy interaction, and improve the utilization of renewable energy, a two-layer sharing strategy for multi-microgrids (MMGs) based on the Nash game is proposed. Firstly, the low-carbon transformation of the micro-grid model is carried out, and the source side is transformed into a comprehensive and flexible operation mode for carbon capture thermal power plants. Then, the multi-microgrid subject electro-thermal double-layer sharing model based on the Nash game is constructed, which is decomposed into a revenue maximization sub-problem and a revenue redistribution sub-problem. In the sub-problem of revenue maximization, considering the lowest operation cost of carbon allowances and stepped carbon trading as the goal, the alternating direction multiplier method is used for a distributed solution. In the revenue redistribution sub-problem, the reasonable redistribution of income is realized by constructing the asymmetric energy mapping contribution function for different periods and energy types. Finally, the simulation results have verified the effectiveness of the proposed method. The results showed that the strategy of this paper can achieve the optimization of the economic objectives of the multi-microgrid (MMG) alliance and has the advantages of reasonable redistribution of benefits, promotion of wind and solar consumption, and reduction of carbon emissions.
Crop Disease Detection against Complex Background Based on Improved Atrous Spatial Pyramid Pooling
Authors: Ma Wei , Yu Helong , Fang Wenbo , Guan Fachun , Ma Dianrong , Guo Yonggang , Zhang Zhengchao , Wang Chao
Published: January 2023

Timely crop disease detection, pathogen identification, and infestation severity assessments can aid disease prevention and control efforts to mitigate crop-yield decline. However, improved disease monitoring methods are needed that can extract high-resolution, accurate, and rich color and spatial features from leaf disease spots in the field to achieve precise fine-grained disease-severity classification and sensitive disease-recognition accuracy. Here, we propose a neural-network-based method incorporating an improved Rouse spatial pyramid pooling strategy to achieve crop disease detection against a complex background. For neural network construction, first, a dual-attention module was introduced into the cross-stage partial network backbone to enable extraction of multi-dimensional disease information from the channel and space perspectives. Next, a dilated convolution-based spatial pyramid pooling module was integrated within the network to broaden the scope of the collection of crop-disease-related information from images of crops in the field. The neural network was tested using a set of sample data constructed from images collected at a rate of 40 frames per second that occupied only 17.12 MB of storage space. Field data analysis conducted using the miniaturized model revealed an average precision rate approaching 90.15% that exceeded the corresponding rates obtained using comparable conventional methods. Collectively, these results indicate that the proposed neural network model simplified disease-recognition tasks and suppressed noise transmission to achieve a greater accuracy rate than is obtainable using similar conventional methods, thus demonstrating that the proposed method should be suitable for use in practical applications related to crop disease recognition.
Cognitive Adaptive Systems for Industrial Internet of Things Using Reinforcement Algorithm
Authors: Rajawat Anand Singh , Goyal S. B. , Chauhan Chetan , Bedi Pradeep , Prasad Mukesh , Jan Tony
Published: January 2023

Agile product development cycles and re-configurable Industrial Internet of Things (IIoT) allow more flexible and resilient industrial production systems that can handle a broader range of challenges and improve their productivity. Reinforcement Learning (RL) was shown to be able to support industrial production systems to be flexible and resilient to respond to changes in real time. This study examines the use of RL in a wide range of adaptive cognitive systems with IIoT-edges in manufacturing processes. We propose a cognitive adaptive system using IIoT with RL (CAS-IIoT-RL) and our experimental analysis showed that the proposed model showed improvements with adaptive and dynamic decision controls in challenging industrial environments.
Blockchain-Based Anonymous Authentication in Edge Computing Environment
Authors: Liu Song , Chai Yuxiang , Hui Longshuo , Wu Weiguo
Published: January 2023

Authentication is an important requirement for the security of edge computing applications. The existing authentication schemes either frequently rely on third-party trusted authorities, leading to the security risk of user information disclosure, or have high authentication overhead, causing certain pressure on the computation and communication of lightweight terminal equipment in the edge environment. In this paper, we proposed a blockchain-based anonymous authentication scheme for edge computing environments. We first designed a blockchain-based authentication architecture to store a small number of authentication elements in the blockchain network, and provide a decentralized and trusted authentication environment to ensure device anonymity and improve the security of authentication processes. Then, an elliptic cryptographic curve-based authentication scheme is proposed. It uses the chameleon hash function to dynamically generate the authentication data according to the elements stored in the blockchain and negotiate the session key, which effectively reduces the computational overhead in the authentication process. The experimental results show that the proposed scheme achieves a secure authentication process and effectively reduces the authentication overhead by up to 43.16% compared to three state-of-the-art schemes.
An Agent-Based Bidding Simulation Framework to Recognize Monopoly Behavior in Power Markets
Authors: He Ye , Guo Siming , Wang Yu , Zhao Yujia , Zhu Weidong , Xu Fangyuan , Lai Chun Sing , Zobaa Ahmed F.
Published: January 2023

Although many countries prefer deregulated power markets as a means of containing power costs, a monopoly may still exist. In this study, an agent-based bidding simulation framework is proposed to detect whether there will be a monopoly in the power market. A security-constrained unit commitment (SCUC) is conducted to clear the power market. Using the characteristics that the agent can fully explore in a certain environment and the Q-learning algorithm, each power producer in the power market is modeled as an agent, and the agent selects a quotation strategy that can improve profits based on historical bidding information. The numerical results show that in a power market with monopoly potential among the power producers, the profits of the power producers will not converge, and the locational marginal price will eventually become unacceptable. Whereas, in a power market without monopoly potential, power producers will maintain competition and the market remains active and healthy.
Solving Power Outages in Healthcare Facilities: Algorithmisation and Assessment of Preparedness
Authors: Vichova Katerina , Hromada Martin , Dzermansky Martin , Snopek Lukas , Pekaj Robert
Published: January 2023

Power outages present a significant threat to all of humanity. However, elements of critical infrastructure are most affected by this event. Among other things, healthcare facilities can be considered critical infrastructure. They are the backbone for saving lives. However, even these medical facilities can be endangered. The primary aim of this paper is to design an algorithm to assess healthcare facilities to solve power outages. Several inputs are considered for the evaluation of healthcare facilities. Based on these inputs, we could gain several outputs, such as object priority, preparedness of the healthcare facility, missing aggregate capacity and fuel stocks. Calculations to obtain this information are available in this article. This algorithm follows up the methodology for the categorisation and prioritisation of objects necessary for the resumption of electricity supply after a blackout. We conclude that only 15% of the surveyed healthcare facilities are prepared for a power outage.
Research on Air Distribution Control Strategy of Supercritical Boiler
Authors: Jin Yingai , Sun Yanwei , Zhang Yuanbo , Jiang Zhipeng
Published: January 2023

Supercritical boilers have become a major development trend in coal-fired power plants, and the air distribution strategy is a key factor in the design and operation of making it fully combustible. In this paper, the mathematical and physical models of a 350 MW supercritical boiler is established, and the optimal air distribution mode of the boiler at different load is determined based on the furnace outlet temperature, NOx concentration, and O2 content. The air distribution control strategies were derived and the corresponding procedures were established. 160 MW and 280 MW were selected for positive pagoda and 180 MW and 230 MW for waist reduced. At 290–350 MW load, the effect of adjusting the combustion damper opening on the outlet oxygen is weak, so preferentially adjusting the SOFA damper opening can achieve better results. The results show good thermal efficiency and emission performance and are applicable to adjust the air distribution mode to achieve fuller combustion of supercritical boilers.
A New Power System Source-End Low Carbonization Evaluation System Considering Carbon Control Model
Authors: Gong Gangjun , Qiang Ren , Yang Jiaxuan , Hou Rui , Lv Zeming , Xu Mingfeng , Liu Xuesong , Yang Haixia
Published: January 2023

Under the global goal of “carbon peaking and carbon neutrality”, new power system is facing a new energy development trend of increasing the capacity of new energy and reducing the capacity and quantity of coal power. Furthermore, new power systems are also moving towards new models such as the Energy Internet and energy storage diversification. This paper combines the needs of new power systems’ “source-load interaction” and a differentiated analysis of the specific carbon emission characteristics of each subject of the Energy Internet “source-network-load-storage”. This paper analyzes the energy efficiency coefficient and carbon emission factors of each link of “source-grid-load-storage”. Therefore, the paper proposes a carbon control model for the Energy Internet. This paper focuses on the characteristics of coal power with the largest carbon reduction. Therefore, this article constructs a multi-dimensional low-carbonization evaluation index system for coal-fired power plants. In addition, this article designs a fusion weight calculation method for subjective and objective indicators based on CRITIC-G1. Additionally, this paper uses the ideal solution–gray relational method to evaluate the specified samples. Finally, this article verifies the effectiveness and feasibility of the implementation of the low-carbonization evaluation index system for coal-fired power plants.
Households’ Energy Transformation in the Face of the Energy Crisis
Authors: Szymańska Elżbieta Jadwiga , Kubacka Maria , Polaszczyk Jan
Published: January 2023

The purpose of conducted research was to recognize factors determining households’ Energy transition and barriers that slow that process. Energy transition itself, understood as a shift in the structure of fuels used in energy production and technological changes related to its use, are key elements of shaping the economy. It was determined to what extent existing household renewable energy installations meet the energy needs of their residents and what factors encourage their installation. In addition, barriers limiting energy transition as perceived by household members were identified. The research used data from the EUROSTAT and the results of surveys conducted using the CAWI (Computer-Assisted Web Interview) and PAPI (Paper and Pencil Interview) techniques among households in Poland. The methods of descriptive statistics, the chi-square test of independence, the Kruskal–Wallis ANOVA test, the Mann–Whitney U test and logistic regression were used to analyze the research results. The analyses show that fossil fuels dominate in energy production in Poland. The share of renewable energy sources in the gross final energy consumption in 2020 was 16.1%. Their structure is dominated by photovoltaic installations with a share of 52%. Further increase in energy prices and fears of interruptions in energy supplies will favor the further increase in the number of installations for renewable energy sources. According to the respondents, the energy efficiency has a significant impact on the quality of life and environment, but the main barriers to its development include financial constraints of households.
Multi-Criteria Analysis of the Influence of Lignocellulosic Biomass Pretreatment Techniques on Methane Production
Authors: Zdeb Magdalena , Bis Marta , Przywara Artur
Published: January 2023

Methane from environmentally friendly anaerobic digestion may be an alternative non-renewable source that is depleting. One of the substrates for that process may be lignocellulose-based materials. The article concerns comparing the environmental impact as well as technical and energy indicators of alternative ways of producing methane from the anaerobic digestion of Pennisetum hybrid. Five scenarios were analyzed: methane production from the anaerobic digestion of the raw grass, the grass subjected to alkaline pretreatment (with 2% NaOH solution at two temperatures), and the grass subjected to mechanical pretreatment (ground to obtain particle sizes <0.18 mm and 0.25–0.38 mm). Multi-criteria decision (MCA) analysis was carried out with the use of five indicators, including life cycle assessment results as well as methane production parameters, in order to optimize this sustainable way of bioenergy production. The purpose of this study was to identify the most cost-effective and environmentally friendly method of Pennisetum hybrid pretreatment in order to optimize the methane production process in terms of environmental, technical, and economic aspects. According to the obtained results, it was stated that the most advantageous solution for the majority of the analyzed indicators turned out to be the mechanical pretreatment with grinding the lignocellulosic biomass into a particle size <0.18 mm.
Modern Use of Prosumer Energy Regulation Capabilities for the Provision of Microgrid Flexibility Services
Authors: Ostrowska Anna , Sikorski Tomasz , Burgio Alessandro , Jasiński Michał
Published: January 2023

Due to the prospect of climate change and the challenges posed by the European Union to the modern power grid, a decentralized system based on distributed energy sources is being created from a centralized system based on utility power. It also involves new ideas on the operation and management of power grids, especially at the level of low-voltage distribution networks, where prosumers play a special role. In addition to the transformation of sources to renewables, the aim is to increase the flexibility of power grids by exploiting the regulatory potential of flexible grid components. The issue of grid flexibility assumes particular importance in the case of microgrids and local grids covered by the energy communities. Many posts describe the realization of the task of flexibility through energy storage, e.g., storing storage resources in electric vehicles or the use of energy transformation through conversion to heat, air compression air, or process cooling. However, there seems to be a lack of exploration of the topic, where the photovoltaic inverter could provide a flexible energy source while maintaining the rigor of power quality. This article presents current developments in low-voltage grids and the prospect of using prosumer installations to provide grid flexibility and stability.
Comparison of Algorithms for the AI-Based Fault Diagnostic of Cable Joints in MV Networks
Authors: Negri Virginia , Mingotti Alessandro , Tinarelli Roberto , Peretto Lorenzo
Published: January 2023

Electrical utilities and system operators (SOs) are constantly looking for solutions to problems in the management and control of the power network. For this purpose, SOs are exploring new research fields, which might bring contributions to the power system environment. A clear example is the field of computer science, within which artificial intelligence (AI) has been developed and is being applied to many fields. In power systems, AI could support the fault prediction of cable joints. Despite the availability of many legacy methods described in the literature, fault prediction is still critical, and it needs new solutions. For this purpose, in this paper, the authors made a further step in the evaluation of machine learning methods (ML) for cable joint health assessment. Six ML algorithms have been compared and assessed on a consolidated test scenario. It simulates a distributed measurement system which collects measurements from medium-voltage (MV) cable joints. Typical metrics have been applied to compare the performance of the algorithms. The analysis is then completed considering the actual in-field conditions and the SOs’ requirements. The results demonstrate: (i) the pros and cons of each algorithm; (ii) the best-performing algorithm; (iii) the possible benefits from the implementation of ML algorithms.
A State-of-the-Art Review of Smart Energy Systems and Their Management in a Smart Grid Environment
Authors: Muqeet Hafiz Abdul , Liaqat Rehan , Jamil Mohsin , Khan Asharf Ali
Published: January 2023

A smart grid (SG), considered as a future electricity grid, utilizes bidirectional electricity and information flow to establish automated and widely distributed power generation. The SG provides a delivery network that has distributed energy sources, real-time asset monitoring, increased power quality, increased stability and reliability, and two-way information sharing. Furthermore, SG provides many advantages, such as demand response, distribution automation, optimized use of electricity, economical energy, real-time grid status monitoring, voltage regulation or VAR control, and electricity storage. In this survey, we explore the literature on smart Grid enabling technologies until 2022. We dig out four major systems: (1) the smart grid’s prominent features and challenges; (2) the smart grid standard system and legislations; (3) smart grid energy subsystem; and (4) the smart grid management system and protection system for new researchers for their future projects. The research challenges and future recommendations are also presented in the conclusion section to explore the new paradigm.
Numerical Study on Flow-Melt Characteristics of Ice Slurry in Horizontal Straight Pipe with a Local Large Heat Flux Segment
Authors: Xie Fushou , Guo Wan , Zhu Yuhao
Published: January 2023

Ice slurry is a high energy density coolant with excellent flow, phase change, and thermophysical properties. In order to investigate the recovery of ice slurry flowing through a local large heat flux segment, a 3D Eulerian-Eulerian model based on the granular kinetic theory considering the flow and melting phase change of ice slurry is developed. Sensitivity analysis of interphase forces is carried out. A comparison of the pressure drop, solid phase velocity, and heat transfer coefficient with empirical data is carried out, respectively. The calculated results are in good agreement with the experimental results, indicating that the numerical model could accurately describe the flow and melting characteristics. Thermophysical field distributions, the axial variation of ice volume fraction (IVF), recovery curve, the average heat transfer coefficient, as well as the re-uniformization length are obtained. After passing through local large heat flux segment, due to shear stress action, the IVF and the particle uniformity of the cross section have recovery characteristics. The gradient of the recovery curve decreases with increasing inlet IVF as well as with increasing Reynolds number. After the local large heat flux increases to a certain value, its effect on the recovery curve of the ice slurry is small. The re-uniformization length increases as the local large heat flux increases. The average heat transfer coefficient of local large heat flux segment increases due to damage of the boundary layer. These results can provide a theoretical basis for the design of ice slurry systems in practical application.
Barriers and Drivers for Changes in Circular Business Models in a Textile Recycling Sector: Results of Qualitative Empirical Research
Authors: Wójcik-Karpacz Anna , Karpacz Jarosław , Brzeziński Piotr , Pietruszka-Ortyl Anna , Ziębicki Bernard
Published: January 2023

The growing environmental problems associated with the dumping of large amounts of textile waste and the demand for circular products are prompting textile waste recycling enterprises to develop circular business models (CBMs). This implies a radical change in the way some enterprises operate to obtain growth. Considering the importance of the drivers of and barriers for the adoption and implementation of CBMs in the textile recycling sector, it is claimed that the comprehension of these factors to CBMs is limited and deserves more attention in empirical research. Therefore, our research investigates the antecedents of circular business models in the textile recycling sector by highlighting influencing factors. The aim of the article is to explore the main enhancing and inhibiting factors in the development of circular business models on the example of a large enterprise operating for 30 years in the textile recycling sector. In this study, a case study design of mixed methods, including semi-structured interviews with a business practitioner and the data presented on the websites of the surveyed enterprise, is used. The results suggest that main enhancing factors are relevant regulations at the European level, appropriate technologies and digitisation, and increasing social and environmental awareness of consumers and managerial capabilities. However, inhibiting factors are supply chain complexity and supply chain collaboration in connection with a large scale of business in crisis situations, a large scope and range of geographic diversification of outlets in the perspective of the consequences of the information gap, and readiness to take the so-called “being the first in the market” risk. In practice, this means that general drivers of the CBMs may facilitate the reuse of second-hand clothing and recycling of textiles for other new products as the primary CE action. On the other hand, enterprises have to overcome a number of technological barriers, and in the case of the textile recycling sector, it is necessary to understand which barriers they face to take appropriate actions. Research findings indicate factors that may be the subject of intervention or support of managers or policymakers. This study has practical implications and suggests future study paths.
Technical Analysis of a Large-Scale Solar Updraft Tower Power Plant
Authors: Singh Varun Pratap , Dwivedi Gaurav
Published: January 2023

This study investigates the possibility of applying a large-scale solar updraft tower power plant in India with local ground conditions as an environmentally friendly and economically viable energy source. A reference model Solar Updraft Tower Power Plant (SUTPP) is constructed to examine the influence of the most prominent plant dimensional parameters, including collector radius (RCollector), tower height (HTower), and tower radius (RTower) with dimensional limits and intervals on the power output of the SUTPP. Udat, Rajasthan, India, is used as a reference location for meteorological conditions to evaluate SUTPP power output equations for a ranging power output, with position coordinates of 27°35′ and 72°43′. Multiple simulations for the objective function are carried out, and the outcomes are compared to the optimized dimensions of each set of plants. The model examines the effect of variation in ambient, plant geometry, and material conditions on power output and analyzes efficiency and power output for optimizing configuration. There exists no definitive approach to determining the proper correlation between the geometrical parameters of a SUTPP with optimized power output. For a fixed power output, the tower radius (RTower) serves as the most influencing dimensional parameter in SUTPP performance. A change in tower height (HTower) has a detrimental impact on SUTPP output and performance. An initial increase in collector radius (RCollector) has a positive influence on SUTPP performance; however, this effect reduces as collector radius (RCollector) increases.
Numerical Investigation of the Effect of Supersonic Air Temperature on the Mixing Characteristics of Liquid Fuel
Authors: Hwang Byeong-Jo , Min Seongki
Published: January 2023

The effect of supersonic air temperature on the mixing characteristics of liquid hydrocarbon fuel injected into three different supersonic airflows elevated in three steps from 373 K to 673 K was investigated numerically. Compressible Reynolds-averaged Navier–Stokes (RANS) equations were solved together with species conservation equation using ANSYS Fluent for two-phase flow simulations including fuel droplet breakup and evaporation. The turbulence model needed to close the RANS equations used the Shear Stress Transport (SST) k-ω model. The Eulerian–Lagrangian model was employed to track fuel droplets in mainstream air, and the Kelvin–Helmholtz and Rayleigh–Taylor (KH-RT) models were used to simulate the droplet breakup process. Numerical solutions were validated using experimental data. The higher the air temperature, the stronger the streamwise vortices downstream of the pylon. When the air temperature was 373 K, the liquid fuel hardly evaporated, but as the air temperature increased, and the mass fraction of the vaporized fuel and the mixing efficiency increased linearly downstream of the pylon. At air temperatures of 523 K and 673 K, the mixing efficiencies were 10% and 51% at the combustor outlet, respectively. The total pressure loss decreased slightly due to droplet evaporation as the temperature increased from 373 K to 673 K.
Demand Response with Electrical Heating in Detached Houses in Finland and Comparison with BESS for Increasing PV Self-Consumption
Authors: Koskela Juha , Järventausta Pertti
Published: January 2023

Distributed electric power production by small-scale customers is increasing continuously. Photovoltaic production is a popular method of producing self-energy for customers. Additionally, power systems require more flexibility when weather-dependent renewable energy production increases. Small-scale customers can increase the self-consumption of self-produced energy by using batteries or a demand response operation. However, batteries require high investment, and demand response operations induce a loss of comfort. Customers who heat their buildings using electric heaters are a good target for demand response operations because their heating can be controlled with limited changes in the indoor temperature. The demand response potential of a building can be defined by simply using customer load profiles and knowledge of the outdoor temperature. Any other information is not required in the proposed novel method. A tolerable variation in indoor temperature corresponds to considerably smaller battery capacity, though it is still a significant amount. With an optimally sized photovoltaic system, it is possible to use both methods simultaneously to increase self-consumption. Maximal benefits can be attained from both methods if the battery system is used as a primary control and the demand response is used as a secondary control. The defined novel method for determining the demand response potential of small-scale customers can also be used when estimating the flexibility of a large customer group. Small-scale customers together can provide significant flexible capacity when their electrical heating is centrally controlled.
Impacts of Prefabrication in the Building Construction Industry
Authors: Rocha Patrícia Fernandes , Ferreira Nuno Oliveira , Pimenta Fernando , Pereira Nelson Bento
Published: January 2023

Interest in sustainable construction has been increasing due to recent events. The limitations of natural resources and the scale of global impacts, specifically as a result of the effects of global climate change, have consequences for the construction sector. These changes are giving rise to a need to reassess the way we face the built environment and rethink new solutions for construction systems or methods that contribute to mitigating negative consequences, among which we highlight the prefabrication method. This new scenario, characterised by the need to meet the decarbonisation goals set for 2050, as well as the effects of the spread of the pandemic crisis, emphasizes the importance of understanding the impacts that may occur in the construction industry, which are essentially understood as increases in sustainability, productivity, quality and, consequently, as reductions in deadlines, costs, and dependence on labour. Therefore, this entry seeks to study on the existing literature on prefabrication, seeking to gather relevant information on the new advances, challenges, and opportunities of this construction method whose approach has been mostly focused on partial or specific aspects for case studies, both highlighting the potential and identifying the gaps and opportunities of prefabrication in this new context. The prefabrication method brings benefits compared to the conventional method, and may be an alternative, as it has more positive global impacts on the environment, the economy, and society, and consequently on the sustainable development of construction, despite some limitations that have been reported and that should be looked into in the future.
Study on Dust Migration Law and Spray Dust Suppression Technology in Fully Mechanized Mining Face
Authors: Jing Deji , Jiang Zhuo , Ren Shuaishuai , Meng Xiangxi , Ge Shaocheng , Zhang Tian
Published: January 2023

To effectively solve the problem of high dust concentration during coal cutting and frame shifting in fully mechanized mining faces, based on the theory of gas–solid two-phase flow, a geometric model of a fully mechanized mining face was established by using COMSOL numerical simulation software. Simulations were performed for the movement characteristics of wind flow and the law of dust diffusion. Results show that the air flow at the junction of the working face, the air inlet, the hydraulic support moving area, and the vicinity of the shearer has accelerated movement, and the maximum wind speed zone of about 3 m/s can be formed. Under the influence of wind flow, dust particles above 35 μm settle faster, while dust particles below 35 μm are very vulnerable to the influence of wind flow, and the settling speed is slower. Using a custom experimental platform, the atomization characteristics and wind resistance of a pressure fan nozzle, a supersonic nozzle, and an ultrasonic nozzle were tested, and the nozzle that was suitable for the scheme was selected and applied in the field. Comparing the dust concentration before and after the application of the dust removal scheme at the sampling point, results show that the dust removal efficiency of the proposed scheme exceeds 85%, and the treatment effect is good.
Construction of Rainbow-like Structural Color Coatings on Wood Surfaces Based on Polystyrene Microspheres
Authors: Hu Jing , Liu Yi , Xu Wei , Wu Zhihui , Pang Xiaoren
Published: January 2023

Polystyrene (PSt) microspheres were used to construct rainbow-like, seven-colored structural color coatings on wood surfaces by analyzing how the amount of emulsifier SDBS and emulsion polymerization temperature affected the particle size and monodispersity of the microspheres. The influence of both the amount of self-assembled emulsion coating used and the temperature on the reflected spectrum and the color of the coatings was investigated. It was found that the most monodisperse PSt microspheres were obtained when using 175 mg SDBS and a reaction temperature of 70 °C. By adjusting these two factors, we regulated the particle size of the PSt microspheres. When PSt microspheres were self-assembled on a wood surface to form a structural color coating, the best optical effect was obtained with 40.8 × 10−3 mL/cm2 emulsion amount and 50 °C ambient temperature. Finally, by changing the SDBS amount and reaction temperature, microspheres with different particle sizes and good monodispersity were prepared. The structural color was used to form patterned decorations on the wood surface, providing a technical basis for forming other structural color coatings on wood surfaces.
Impact of Fire Recurrence and Induced Water Stress on Seed Germination and Root Mitotic Cell Cycle of Pinus pinaster Aiton
Authors: Ribeiro Stéphanie , Gaspar Maria João , Lima-Brito José , Fonseca Teresa , Soares Paula , Cerveira Adelaide , Fernandes Paulo M. , Louzada José , Carvalho Ana
Published: January 2023

Climate change will increase the frequency of drought, heat waves, and wildfires. We intended to analyse how fire recurrence and/or induced water stress can affect seed germination and root cell division in Pinus pinaster Aiton. Seeds from stands with no prior fire history and from post-fire regeneration (in areas burnt once, twice, and thrice) in northern Portugal were germinated in distilled water (control) and polyethylene glycol (PEG) to simulate water stress for four weeks, followed by a recovery period. Roots were analysed cytogenetically. The germination index of the Pinus pinaster seeds was not statistically influenced by the induction of osmotic stress, nor by the fire recurrence of the stands. The mean germination time (MGT) was 10–29 days and 1–36 days for the stress and recovery periods, respectively, and increased with PEG concentration. The 20% PEG treatment inhibited root growth after germination. The 10% PEG treatment induced a high frequency of cytogenetic anomalies, mostly in the sites which experienced fire exposure. While fire recurrence did not affect the germination rate, it seemed to reduce the water stress response, negatively impacting cell division and impair root growth.
Comparison of Soundscape Evaluation in Forest-Type and Urban-Type Han Chinese Buddhist Temples
Authors: Zhang Dongxu , Liu Xueliu , Mo Wei
Published: January 2023

Soundscapes are one of the main means of creating a religious atmosphere in Han Chinese Buddhist temples, which are the most important religious sites in China. This paper selected several representative forest-type and urban-type Han Chinese Buddhist temples and employed a questionnaire and sound level measurement methods to conduct a comparative analysis of four aspects of acoustic environment evaluation, i.e., quietness, comfort, harmony, and sound preference, to identify and compare the characteristics of respondents’ soundscape evaluation in these two types of temples. The results showed that compared with urban-type temples, respondents found the acoustic environment in forest-type temples to be quieter, more comfortable and more harmonious with the religious atmosphere. The sound level, measured with the questionnaire and respondents’ social characteristics, such as age, occupation, level of education, purpose and frequency of visiting the temples, and attitude towards Buddhist thought, influenced their soundscape evaluation of urban-type and forest-type temples to different degrees. Among the various kinds of sounds in the temple, natural sounds, such as the sounds of flowing water, birds and insects, and rustling leaves, were preferred in forest-type temples, while Buddhism-related human-made sounds, including chanting and background music, were preferred in urban-type temples.
Optimal Management Strategies to Maximize Carbon Capture in Forest Plantations: A Case Study with Pinus radiata D. Don
Authors: Altamirano-Fernández Alex , Rojas-Palma Alejandro , Espinoza-Meza Sergio
Published: January 2023

Plantations with fast-growing species play a crucial role in reducing global warming and have great carbon capture potential. Therefore, determining optimal management strategies is a challenge in the management of forest plantations to achieve the maximum carbon capture rate. The objective of this work is to determine optimal rotation strategies that maximize carbon capture in forest plantations. By evaluating an ecological optimal control problem, this work presents a method that manages forest plantations by planning activities such as reforestation, felling, thinning, and fire prevention. The mathematical model is governed by three ordinary differential equations: live biomass, intrinsic growth, and burned area. The characterization of the optimal control problem using Pontryagin’s maximum principle is analyzed. The model solutions are approximated numerically by the fourth-order Runge–Kutta method. To verify the efficiency of the model, parameters for three scenarios were considered: a realistic one that represents current forestry activities based on previous studies for the exotic species Pinus radiata D. Don, another pessimistic, which considers significant losses in forest productivity; and a more optimistic scenario which assumes the creation of new forest areas that contribute with carbon capture to prevent the increase in global temperature. The model predicts a higher volume of biomass for the optimistic scenario, with the consequent higher carbon capture than in the other two scenarios. The optimal solution for the felling strategy suggests that, to increase carbon capture, the rotation age should be prolonged and the felling rate decreased. The model also confirms that reforestation should be carried out immediately after felling, applying maximum reforestation effort in the optimistic and pessimistic scenarios. On the other hand, the model indicates that the maximum prevention effort should be applied during the life cycle of the plantation, which should be proportional to the biomass volume. Finally, the optimal solution for the thinning strategy indicates that in all three scenarios, the maximum thinning effort should be applied until the time when the fire prevention strategy begins.
Effects of Compression Ratio and Phenolic Resin Concentration on the Properties of Laminated Compreg Inner Oil Palm and Sesenduk Wood Composites
Authors: Ahamad Wan Nabilah , Salim Sabiha , Lee Seng Hua , Abdul Ghani Muhammad Aizat , Mohd Ali Rabiatol Adawiah , Md Tahir Paridah , Fatriasari Widya , Antov Petar , Lubis Muhammad Adly Rahandi
Published: January 2023

Due to its inferior properties, oil palm wood (OPW) extracted from the inner layer of the oil palm (Elaeis guineensis) trunk, referred as inner OPW in this study, is frequently regarded as a waste. Phenolic resin treatment and lamination of inner OPW with other hardwoods may be an excellent way to improve the properties of the inner OPW. In this study, inner OPW were treated with two different concentrations (15% and 20%) of low molecular weight phenol formaldehyde resin (LmwPF) and compressed at different compression ratios (10%, 20%, and 30%). The physical and mechanical properties of the modified inner OPW’s were evaluated according to British Standards (BS) 373: 1957. The results revealed that inner OPW treated with the highest compression ratio (30%) and resin concentration (20%) exhibited the highest weight percent gain, polymer retention and density. In the following phase of the research, the treated inner OPW was used as the core layer in the fabrication of a three-layer laminated compreg hybrid composites, with untreated and treated sesenduk (Endospermum diadenum) wood serving as the face and back layers. The compression ratios of 10% and 20% and resin concentrations of 10% and 20% were used in this phase of study as laminated boards made with 30% compression ratio failed. The findings showed that resin concentration had a significant impact on both the inner OPW and the laminated compreg hybrid panels. Markedly, higher resin concentrations (20%) resulted in improved physical properties, i.e., thickness swelling and water absorption, as well as enhanced mechanical properties (modulus of rupture and modulus of elasticity). Although compression ratios had no significant effect on the properties of the laminated products, those compressed at higher compression ratios (20%) performed slightly better than the panels compressed at lower compression ratios (10%).
Physical and Mechanical Properties of High-Density Fiberboard Bonded with Bio-Based Adhesives
Authors: Gumowska Aneta , Kowaluk Grzegorz
Published: January 2023

The high demand for wood-based composites generates a greater use of wood adhesives. The current industrial challenge is to develop modified synthetic adhesives to remove harmful formaldehyde, and to test natural adhesives. The scope of the current research included the manufacturing of high-density fiberboards (HDF) using natural binders such as polylactic acid (PLA), polycaprolactone (PCL), and thermoplastic starch (TPS) with different resination (12%, 15%, 20%). The HDF with biopolymers was compared to a reference HDF, manufactured following the example of industrial technology, with commonly used adhesives such as urea-formaldehyde (UF) resin. Different mechanical and physical properties were determined, namely modulus of rupture (MOR), modulus of elasticity (MOE), internal bonding strength (IB), thickness swelling (TS), water absorption (WA), surface water absorption (SWA), contact angle, as well as density profile; scanning electron microscope (SEM) analysis was also performed. The results showed that increasing the binder content significantly improved the mechanical properties of the panels in the case of starch binder (MOR from 31.35 N mm−2 to 40.10 N mm−2, IB from 0.24 N mm−2 to 0.39 N mm−2 for dry starch), and reduces these in the case of PLA and PCL. The wet method of starch addition improved the mechanical properties of panels; however, it negatively influenced the reaction of the panels to water (WA 90.3% for dry starch and 105.9% for wet starch after 24 h soaking). Due to dynamically evaporating solvents from the PLA and PCL binding mixtures, a development of the fibers’ resination (blending) techniques should be performed, to avoid the uneven spreading of the binder over the resinated material.
Enterococcus faecalis-Induced Biochemical Transformation during Fermentation of Underutilized Solenostemon monostachyus Leaves
Authors: Afolabi Israel Sunmola , Ahuekwe Eze Frank , Garuba Precious Amaneshi , Adigun Aderinsola Jumai , Odutayo Oluwatofunmi E. , Adeyemi Alaba Oladipupo
Published: January 2023

Solenostemon monostachyus is an underutilized plant that is yet to be explored for consumption. This study assessed the biochemical impacts of a probiotic Enterococcus faecalis as an agent of fermentation, promoting the edible properties of the leaves from S. monostachyus using either an unfermented water leaf or S. monostachyus. The results with p < 0.05 were considered statistically significant. The α-amylase activity, proteins, carbohydrates, and ash, iron, and copper contents significantly increased (p < 0.05), while fats, crude fiber, cadmium, and manganese contents of the fermented S. monostachyus leaves were significantly reduced (p < 0.05), compared to the control (unfermented water leaves). The total phenol and saponin contents of the leaves were 1.98 ± 0.03 and 2.77 ± 0.04 mg GAE/mL for the S. monostachyus, 2.20 ± 0.01 and 2.39 ± 0.51 mgGAE/mL for water leaf, respectively on Day 5. Spirostanol (20.7343 mg/10 g) and two possible yet-to-be-identified saponin compounds P-S1 (33.5773 mg/10 g) and P-S2 (23.5718 mg/10 g) were newly synthesized along with one possible novel volatile compound by the fermentation process. Furostanol (19.873–29.420), gallic acid (88.111–98.949 mg/10 g), luteolin (0.954–11.712 mg/10 g) were retained, and aescin (69.510 mg/10 g) was completely consumed by the fermentation process. E. faecalis derived some micronutrients to drive the α-amylase catalyzed biotransformation of phytochemicals to improve the health benefits in the leafy vegetable.
Low-Grade Syngas Biomethanation in Continuous Reactors with Respect to Gas–Liquid Mass Transfer and Reactor Start-Up Strategy
Authors: Jiang Bingyi , Zhang Dongming , Hu Xiao , Söderlind Ulf , Paladino Gabriela , Gamage Shiromini , Hedenström Erik , Zhang Wennan , Arrigoni Juan , Lundgren Anders , Tuvesson Malin , Yu Chunjiang
Published: January 2023

In order to utilize a wider range of low-grade syngas, the syngas biomethanation was studied in this work with respect to the gas–liquid mass transfer and the reactor start-up strategy. Two reactors, a continuous stirred tank (CSTR) and a bubble column with gas recirculation (BCR-C), were used in the experiment by feeding an artificial syngas of 20% H2, 50% CO, and 30% CO2 into the reactors at 55 °C. The results showed that the CH4 productivity was slightly increased by reducing the gas retention time (GRT), but was significantly improved by increasing the stirring speed in the CSTR and the gas circulation rate in the BCR-C. The best syngas biomethanation performance of the CSTR with a CH4 productivity of 22.20 mmol·Lr−1·day−1 and a yield of 49.01% was achieved at a GRT of 0.833 h and a stirring speed of 300 rpm, while for the BCR-C, the best performance with a CH4 productivity of 61.96 mmol·Lr−1·day−1 and a yield of 87.57% was achieved at a GRT of 0.625 h and a gas circulation rate of 40 L·Lr−1·h−1. The gas–liquid mass transfer capability provided by gas circulation is far superior to mechanical stirring, leading to a much better performance of low-grade syngas biomethanation in the BCR-C. Feeding H2/CO2 during the startup stage of the reactor can effectively stimulate the growth and metabolism of microorganisms, and create a better metabolic environment for subsequent low-grade syngas biomethanation. In addition, during the thermophilic biomethanation of syngas, Methanothermobacter is the dominant genus.