bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomass Resources and Biofuel Technologies: A Focus on Indian Development
Authors: Shweta  , Capareda Sergio C. , Kamboj Baldev Raj , Malik Kamla , Singh Karmal , Bhisnoi Dalip Kumar , Arya Sandeep
Published: January 2024

As a result of the depletion of fossil resources, ongoing population growth, and the industrialized economy, energy demand has been rising quickly throughout the world. India is now the world’s third-largest oil consumer, surpassing Japan and Russia. Today, biofuel research is conducted worldwide because surrounding two essential characteristics: sustainability and renewability. Biofuels have gained considerable significance as a result of dwindling oil sources, worries about energy security, and the escalating environmental issues associated with climate change and greenhouse gas emissions. In most cases, biofuels are produced by subjecting materials that have been densified to the process of heat conversion. In the disciplines of research and development, alternative energy development is a top focus. Due to the depletion of fossil fuel resources, it has become important to find innovative replacements for fossil fuels, such as biofuels, to generate heat and power. Biofuels may be generated using several methodologies, encompassing biological, chemical, and physical approaches. The three steps of densification systems’ pre-, during-, and post-pelletization procedures convert biomass into pellets. Several agricultural wastes, such as grain dust, crop leftovers, and fruit tree residues, are available as sources of agricultural energy. Bioenergy from biomass, such as leftovers and energy crops, can be used to produce contemporary energy carriers. This article focuses on an overview of sustainable and renewable biofuel resources and their commercialization.
Experimental Study on Carbon Dioxide Flooding Technology in the Lunnan Oilfield, Tarim Basin
Authors: Wu Zangyuan , Feng Qihong , Tang Yongliang , Zhou Daiyu , Lian Liming
Published: January 2024

The Lunnan Oilfield in the Tarim Basin is known for its abundant oil and gas resources. However, the marine clastic reservoir in this oilfield poses challenges due to its tightness and difficulty in development using conventional water drive methods. To improve the recovery rate, this study focuses on the application of carbon dioxide flooding after a water drive. Indoor experiments were conducted on the formation fluids of the Lunnan Oil Formation, specifically investigating gas injection expansion, thin tube, long core displacement, oil and gas phase permeability, and solubility. By injecting carbon dioxide under the current formation pressure, the study explores the impact of varying amounts of carbon dioxide on crude oil extraction capacity, high-pressure physical parameters of crude oil, and phase characteristics of formation fluids. Additionally, the maximum dissolution capacity of carbon dioxide in formation water is analyzed under different formation temperatures and pressures. The research findings indicate that the crude oil extracted from the Lunnan Oilfield exhibits specific characteristics such as low viscosity, low freezing point, low-medium sulfur content, high wax content, and medium colloid asphaltene. The measured density of carbon dioxide under the conditions of the oil group is 0.74 g/cm3, which closely matches the density of crude oil. Additionally, the viscosity of carbon dioxide is 0.0681 mPa·s, making it well-suited for carbon dioxide flooding. With an increase in the amount of injected carbon dioxide, the saturation pressure and gas-oil ratio of the crude oil also increase. As the pressure rises, carbon dioxide dissolves rapidly into the crude oil, resulting in a gradual increase in the gas-oil ratio, expansion coefficient, and saturation pressure. As the displacement pressure decreases, the degree of carbon dioxide displacement initially decreases slowly, followed by a rapid decrease. Moreover, an increase in the injection rate of carbon dioxide pore volume leads to a rapid initial improvement in oil-displacement efficiency, followed by a slower increase. Simultaneously, the gas-oil ratio exhibits a slow increase initially, followed by a rapid rise. Furthermore, as the displacement pressure increases, the solubility of carbon dioxide in water demonstrates a linear increase. These research findings provide valuable theoretical data to support the use of carbon dioxide flooding techniques for enhancing oil recovery.
Underground Hydrogen Storage Safety: Experimental Study of Hydrogen Diffusion through Caprocks
Authors: Salina Borello Eloisa , Bocchini Sergio , Chiodoni Angelica , Coti Christian , Fontana Marco , Panini Filippo , Peter Costanzo , Pirri Candido Fabrizio , Tawil Michel , Mantegazzi Andrea , Marzano Francesco , Pozzovivo Vincenzo , Verga Francesca , Viberti Dario
Published: January 2024

Underground Hydrogen Storage (UHS) provides a large-scale and safe solution to balance the fluctuations in energy production from renewable sources and energy consumption but requires a proper and detailed characterization of the candidate reservoirs. The scope of this study was to estimate the hydrogen diffusion coefficient for real caprock samples from two natural gas storage reservoirs that are candidates for underground hydrogen storage. A significant number of adsorption/desorption tests were carried out using a Dynamic Gravimetric Vapor/Gas Sorption System. A total of 15 samples were tested at the reservoir temperature of 45 °C and using both hydrogen and methane. For each sample, two tests were performed with the same gas. Each test included four partial pressure steps of sorption alternated with desorption. After applying overshooting and buoyancy corrections, the data were then interpreted using the early time approximation of the solution to the diffusion equation. Each interpretable partial pressure step provided a value of the diffusion coefficient. In total, more than 90 estimations of the diffusion coefficient out of 120 partial pressure steps were available, allowing a thorough comparison between the diffusion of hydrogen and methane: hydrogen in the range of 1 × 10−10 m2/s to 6 × 10−8 m2/s and methane in the range of 9 × 10−10 m2/s to 2 × 10−8 m2/s. The diffusion coefficients measured on wet samples are 2 times lower compared to those measured on dry samples. Hysteresis in hydrogen adsorption/desorption was also observed.
Three-Dimensional Spatial Microscopic Characteristics and Developmental Influencing Factors of Tight Gas Layers in Hangjinqi Prospect Area, Ordos Basin, China
Authors: Gu Nanling , Hu Wangshui , Gao Lingyu , Liu Guowen
Published: January 2024

The unconventional tight oil and gas resources in the Xinzhao East belt of the Hangjinqi Prospect area in the Ordos Basin of China are abundant. However, the reservoir’s internal storage space is complex, and the microscopic pore throat structural features are not well recognized, which has led to some trouble in the deployment of oil and gas exploration. To reveal the microscopic characteristics of the dense sandstone gas layer in the first member of the Lower Stone Box Formation of the D-well Zone in the Xinzhao East belt of the Hangjinqi Prospect area, a three-dimensional space digital core was built, and the stored set spatial data were extracted, based on rock sheet and coring data and X-CT scanning technology. Quartz grain size was segmented and analyzed based on an adaptive approach. The microscopic characteristics of the gas layer in the studied section and the factors influencing its development were studied, combining the use of a field emission scanning electron microscope, helium porosimeter, and gas permeability meter. We found that in the studied section, the porosity is relatively high, the pore throat size is large, and the pore permeability correlation is good. The reservoir space, which consists of intergranular pores, intragranular pores, and microcracks at the grain edges in the study area, is characterized by a complex distribution pattern. Within the gas layer, isolated pores are connected by microcracks to form a network of reservoir spaces, which increases the pore throat size, enhances the connectivity of the pore throat, and makes the microscopic characteristics of the reservoir space better. The first member of the Lower Stone Box Formation could be an advantageous reservoir. Hole–throat connectivity is poor because of the gas layer having underdeveloped primary pores, the blockage of pores by unstable minerals (kaolinite, etc.), and poorly connected pore throats based on insoluble mud cementation. The high content of quartz brittle minerals and the development of natural microcracks within the gas formation are favorable conditions for fracking development. The quartz grain size within the gas layer is positively correlated with the pore throat size, which suggests that the quartz grain size somewhat influences the microscopic characteristics of the reservoir space. This comprehensive study shows that the methodology of the study is more advantageous than traditional methods in the fine and three-dimensional spatial characterization of the microstructure of dense sandstone reservoirs. The research results of this paper have certain guiding significance for further reservoir evaluation and advantageous reservoir prediction in the Hangjinqi Prospect area in the Ordos Basin. We also provide the basis for the subsequent efficient development of the gas reservoir.
Magnesium–Air Battery with Increased Power Using Commercial Alloy Anodes
Authors: Zhuk Andrey , Belyaev Grigory , Borodina Tatiana , Kiseleva Elena , Shkolnikov Eugeny , Tuganov Viktor , Valiano Georgy , Zakharov Viktor
Published: January 2024

Mg–air batteries have high theoretical energy density and cell voltage. Their use of environmentally friendly salt electrolyte and commercially available magnesium materials determines their acceptable technical and economic efficiency, safety, and ease of operation. However, the practical applicationsof Mg–air batteries arevery limited due to the polarization of magnesium anodes and the batteries’ low Faraday efficiency. In this study, we considered the possibility of designingan Mg–air battery withincreased power by adapting engineering solutions developed for an Al–air battery with alkaline electrolytes. To increase the specific power of the battery, it was proposed that the internal resistance of the battery maybe reduced using a concentrated salt electrolyte. We investigated the discharge performance of a commercial alloy of AZ31 type in 15 wt.% NaCl electrolyte at current densities of 40–120 mA/cm2. The influence of a small addition of sulfosalicylic acid into the electrolyte on the discharge performance of the anode alloy was studied as well. The estimated values of the energy characteristics of the 0.5 kW Mg–air battery were compared with those of an Al–air battery with an alkaline electrolyte.
Energy Generation Intensity (EGI) of Solar Updraft Tower (SUT) Power Plants Relative to CSP Plants and PV Power Plants Using the New Energy Simulator “Aladdin”
Authors: Marzouk Osama A.
Published: January 2024

The current investigation provides information about solar updraft tower power plants, SUTPPs (also called solar chimney power plants, SCPPs), which form a unique method of solar-powered electricity production through a ducted wind turbine driven by induced airflow as a result of solar heating. The investigation is conducted using numerical modeling via the system-level simulation tool Aladdin (developed and released freely by the Institute for Future Intelligence, IFI) for solar energy systems, wind energy systems, or the built environment. The Aladdin energy simulator is first evaluated here by comparison with published experimental and numerical results corresponding to the historical 50 kW prototype SUTPP that was successfully tested in Manzanares (Spain) between 1982 and 1989. This prototype has a height of about 195 m for the chimney (the updraft tower) and a radius of about 122 m for the solar heat absorber (the solar air collector or the greenhouse). Next, various climate and performance characteristics are investigated and contrasted for nine different locations around the world with a similar latitude of 24°, which is within the sunbelt, assuming that the same Manzanares SUTPP prototype geometry is employed in these locations. These nine locations are Muscat (Oman), Al Jawf (Libya), Riyadh (Saudi Arabia), Karachi (Pakistan), Ahmedabad (India), Havana (Cuba), Culiacán (Mexico), Dhaka (Bangladesh), and Baise (China). The energy generation intensity (EGI) for the Manzanares-type solar updraft tower power plant in these nine examined locations was between 0.93 kWh/m2 per year (in Baise) and 2.28 kWh/m2 per year (in Muscat). Also, Muscat had the smallest seasonality index (maximum-to-minimum monthly electric output) of 1.90, while Baise had the largest seasonality index of 4.48. It was found that the main limitation of the overall SUTPP energy conversion efficiency is the chimney efficiency (the process of accelerating the air after entering the chimney). This study concludes that solar updraft towers (SUTs) cannot compete with existing mature and modular renewable energy alternatives, particularly photovoltaic (PV) panels, if the aimed use is commercial utility-scale electricity generation. Instead, SUTs may become attractive and achievable if viewed as hybrid-use projects by serving primarily as a large-scale greenhouse area for agricultural applications while secondarily allowing energy harvesting by generating clean (emissions-free) electricity from the incoming solar radiation heat.
Catalytic Upgrading of Rice Straw Bio-Oil via Esterification in Supercritical Ethanol over Bimetallic Catalyst Supported on Rice Straw Biochar
Authors: Ibrahim Alhassan , Elsayed Islam , Hassan El Barbary
Published: January 2024

This research explores the enhancement of bio-oil quality through upgrading with the magnetic bimetallic oxide (CuO-Fe3O4) catalysts supported on activated rice straw biochar (AcB). These catalysts were employed in a supercritical ethanol-based upgrading process. Various characterization techniques, including elemental analysis, Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, thermogravimetric analysis (TGA), and scanning electron microscopy (SEM), were utilized to characterize the prepared catalysts. This study revealed significant improvements in the physical characteristics and chemical composition of the bio-oil, with an increase in the heating value (HHV) from 21.3 to 32.1 MJ/kg. Esterification and transesterification were identified as key reactions contributing to this improvement. Notably, the pH of bio-oil increased from 4.3 (raw bio-oil) to 5.63 (after upgrading), signifying reduced acidity. The analysis of the bio-oil’s chemical composition highlighted a decrease in oxygen content and an increase in carbon and hydrogen content. At the optimum conditions, the application of supercritical ethanol proved to be an efficient method for enhancing the bio-oil’s properties. A crucial transformation occurred during the upgrading process and more than 90% of carboxylic acids were converted into esters, primarily ethyl acetate at the optimal conditions. This study has demonstrated the effective enhancement of raw bio-oil from rice straw through the utilization of carbon-based bimetallic oxide catalysts in a supercritical upgrading procedure.
Cyanobacteria as a Biocatalyst for Sustainable Production of Biofuels and Chemicals
Authors: Singh Varsha K. , Jha Sapana , Rana Palak , Soni Renu , Lalnunpuii Rowland , Singh Prashant K. , Sinha Rajeshwar P. , Singh Garvita
Published: January 2024

The combustion of fossil fuels constitutes a significant catalyst for climate change, resulting in the annual release of about two billion tonnes of carbon dioxide (CO2). The increase in CO2 emission is directly linked to a heightened occurrence of natural calamities and health-related issues. The substitution of fossil fuels with renewable energy sources is a fundamental approach to reduce the negative impacts caused by consumption of these nonrenewable energy resources. The utilisation of biological methodologies to produce environmentally friendly energy from renewable sources holds significant potential for the sustainable production of fuel. However, the cultivation of first- and second-generation biofuel crops presents a challenge, since they compete for limited cropland, hence constraining their overall viability. In contrast, photosynthetic microorganisms such as algae and cyanobacteria exhibit significant potential as third-generation biofuel catalysts, devoid of the limitations associated with contemporary biofuels. Cyanobacteria, a type of photosynthetic prokaryotes, exhibit significant potential for the direct conversion of carbon dioxide (CO2) into biofuels, chemicals, and various other valuable compounds. There has been a growing interest in the concept of utilising biological processes to convert carbon dioxide into fuels and chemicals. The introduction of a limited number of heterologous genes has the potential to confer upon cyanobacteria the capability to convert particular central metabolites into a diverse range of end products. The progress in the field of synthetic biology and genetic manipulation has enabled the manipulation of cyanobacteria to synthesise compounds that are not generally produced by these organisms in their natural environment. This study focuses on recent papers that employ various methodologies to engineer cyanobacteria for the purpose of producing high-value compounds, such as biofuels.
Challenges Ahead for Sustainable Cities: An Urban Form and Transport System Review
Authors: Monteiro João , Sousa Nuno , Coutinho-Rodrigues João , Natividade-Jesus Eduardo
Published: January 2024

This article reviews the critical issues surrounding the development of sustainable urban environments, focusing on the impact of transport and urban form on energy consumption and greenhouse gas emissions. The aim is to provide an overview of the state-of-the-art on the subject and to unravel what directions the literature suggests for sustainable urban planning. Current research and practices are synthesized, highlighting the interdependence of urban design and transportation systems in achieving sustainability goals. Important dimensions and practices of city planning and transport policies are explored, including urban form, urban sprawl, mixed land use, densification and infill, and urban public spaces, and how these directly influence transport dynamics, including modal choices and energy consumption. Innovative approaches in urban planning, such as transit-oriented development, and technological advancements, such as electric mobility, are also examined and their potential roles in sustainable urban transport. The conclusion underscores the urgency of adopting holistic and adaptable strategies to foster sustainable urban environments, calling for concerted efforts from policymakers, urban planners, and communities. Awareness of the conclusions can help municipal decision-makers in planning their cities for a sustainable future. Finally, the authors analyze important directions for future research and practical applications towards developing cities that are environmentally sound, socially equitable, and economically viable.
Effect of Tributyl Citrate as a Cosolvent on the Phase Behavior of Crude Oil during CO2 Injection Process
Authors: Xue Fangfang , Yang Li’an , Li Jianshan , Yan Ruoqin , Zhao Mingwei
Published: January 2024

The current research on CO2 cosolvent primarily focuses on reducing the minimum miscibility pressure and improving oil recovery. However, investigations into the impact of additive agents on the phase behavior of crude oil during the CO2 injection process are relatively limited. In this study, we introduced tributyl citrate as a cosolvent to the CO2 injection process. By comparing the phase parameters of crude oil and changes in component composition in the residual oil before and after the addition of tributyl citrate, we explored the influence patterns of this cosolvent during CO2 injection. The experiments show that the optimum concentration of tributyl citrate is 0.3%. After the addition of tributyl citrate, the bubble point pressure of crude oil is reduced from 14.28 MPa to 13.36 MPa, and the density is decreased from 1.00 g/cm3 to 0.95 g/cm3. These alterations of bubble point pressure and density indicate an enhanced solubility of CO2 and improved miscibility with the oil, coinciding with an increased volume expansion coefficient rising from 1.12 to 1.18 under 20 MPa and a decrease in viscosity from 0.73 mPa·s to 0.64 mPa·s. Tributyl citrate primarily affects the properties of crude oil by reducing interfacial tension and the content of heavy components in the dissolution system. The addition of tributyl citrate stabilizes the deposition trend of heavy components in crude oil and promotes the transformation of heavy components into light components, thereby enhancing the efficiency of CO2 extraction. This study provides valuable insights into a novel and simple method to further increase oil recovery in the CO2 injection process.
A Novel Approach for Evaluating Power Quality in Distributed Power Distribution Networks Using AHP and S-Transform
Authors: Chen Yin , Tang Zhenli , Weng Xiaofeng , He Min , Zhang Guanghong , Yuan Ding , Jin Tao
Published: January 2024

As the penetration rate of new energy generation in distributed distribution networks continues to increase, the integration of numerous new energy power plants and associated power electronic devices presents challenges to the power quality of traditional power systems. Therefore, conducting power quality-related research in distribution networks is of significant importance for maintaining power system stability, safeguarding electrical equipment, and enhancing electrical safety. A framework for evaluating the overall power quality of new energy-penetrated distribution network systems based on the analytic hierarchy process (AHP) is proposed. This framework aggregates and calculates the global power quality index (GPQI) through averaging, thereby completing the assessment of power quality situations. By enhancing the computation speed of evaluation metrics through an improved S-transform and considering various disturbances such as diminished illumination, wind power disconnection, and high-current grounding, the GPQI values are used to assess power quality under diverse scenarios. Simulation and experimental results confirm the framework’s close alignment with real scenarios and its effectiveness in evaluating power quality within distribution networks. This method is crucial for maintaining power system stability, protecting electrical equipment, and enhancing overall electrical safety within distribution networks.
Controlling Factors of Vertical Geochemical Variations in Hydrate-Rich Sediments at the Site GMGS5-W08 in the Qiongdongnan Basin, Northern South China Sea
Authors: Liu Huaxin , Li Meijun , Lai Hongfei , Fu Ying , Kuang Zenggui , Fang Yunxin
Published: January 2024

Large amounts of natural gas hydrates have been discovered in the Qiongdongnan Basin (QDNB), South China Sea. The chemical and stable carbon isotopic composition shows that the hydrate-bound gas was a mixture of thermogenic and microbial gases. It is estimated that microbial gas accounts for 40.96% to 60.58%, showing a trend of decrease with the increase in burial depth. A significant amount of gas hydrates is thought to be stored in the mass transport deposits (MTDs), exhibiting vertical superposition characteristics. The stable carbon isotopic values of methane (δ13C1) in the MTD1, located near the seabed, are less than −55‰, while those of the methane below the bottom boundary of MTD3 are all higher than −55‰. The pure structure I (sI) and structure II (sII) gas hydrates were discovered at the depths of 8 mbsf and 145.65 mbsf, respectively, with mixed sI and sII gas hydrates occurring in the depth range 58–144 mbsf. In addition, a series of indigenous organic matters and allochthonous hydrocarbons were extracted from the hydrate-bearing sediments, which were characterized by the origin of immature terrigenous organic matter and low-moderate mature marine algal/bacterial materials, respectively. More allochthonous (migrated) hydrocarbons were also discovered in the sediments below the bottom boundary of MTD3. The gas hydrated is “wet gas” characterized by a low C1/(C2 + C3) ratio, from 2.55 to 43.33, which was mainly derived from a deeply buried source kitchen at a mature stage. There is change in the heterogeneity between the compositions of gas and biomarkers at the site GMGS5-W08 along the depth and there is generally a higher proportion of thermogenic hydrocarbons at the bottom boundary of each MTDs, which indicates a varying contribution of deeply buried thermogenic hydrocarbons. Our results indicate that the MTDs played a blocking role in regulating the vertical transportation of hydrate-related gases and affect the distribution of gas hydrate accumulation in the QDNB.
Energy Efficiency in Wireless Networks
Authors: Maheswar Rajagopal , Kathirvelu Murugan , Mohanasundaram Kuppusamy
Published: January 2024

The pervasive integration of wireless devices across diverse sectors has experienced an unprecedented surge in recent years [...]
Site Selection and Capacity Determination of Electric Hydrogen Charging Integrated Station Based on Voronoi Diagram and Particle Swarm Algorithm
Authors: Tian Xueqin , Yang Heng , Ge Yangyang , Yuan Tiejiang
Published: January 2024

In response to challenges in constructing charging and hydrogen refueling facilities during the transition from conventional fuel vehicles to electric and hydrogen fuel cell vehicles, this paper introduces an innovative method for siting and capacity determination of Electric Hydrogen Charging Integrated Stations (EHCIS). In emphasizing the calculation of vehicle charging and hydrogen refueling demands, the proposed approach employs the Voronoi diagram and the particle swarm algorithm. Initially, Origin–Destination (OD) pairs represent car starting and endpoints, portraying travel demands. Utilizing the traffic network model, Dijkstra’s algorithm determines the shortest path for new energy vehicles, with the Monte Carlo simulation obtaining electric hydrogen energy demands. Subsequently, the Voronoi diagram categorizes the service scope of EHCIS, determining the equipment capacity while considering charging and refueling capabilities. Furthermore, the Voronoi diagram is employed to delineate the EHCIS service scope, determine the equipment capacity, and consider distance constraints, enhancing the rationality of site and service scope divisions. Finally, a dynamic optimal current model framework based on second-order cone relaxation is established for distribution networks. This framework plans each element of the active distribution network, ensuring safe and stable operation upon connection to EHCIS. To minimize the total social cost of EHCIS and address the constraints related to charging equipment and hydrogen production, a siting and capacity model is developed and solved using a particle swarm algorithm. Simulation planning in Sioux Falls city and the IEEE33 network validates the effectiveness and feasibility of the proposed method, ensuring stable power grid operation while meeting automotive energy demands.
Advanced Single-Phase PLL-Based Transfer Delay Operators: A Comprehensive Review and Optimal Loop Filter Design
Authors: Bany Fawaz Bayan H. , Smadi Issam A. , Albatran Saher A. , Atawi Ibrahem E.
Published: January 2024

In recent years, several research works have addressed and developed the phase-locked loop (PLL) in single-phase grid-connected converters with different structures and properties. Each has merits and demerits, such as a complex structure, high computational burden, and slow transient response. This paper aims to comprehensively review advanced single-phase PLLs based on transport delay operators to realize signal orthogonality. A deep insight into the PLLs’ small-signal modeling, main characteristics, stability analysis, and loop filter design are provided in this paper. The main advantages and drawbacks are explained for each type of PLL in terms of different performance indexes, such as settling time, estimation error, and ripples in the estimated grid information. This paper also aims to provide optimal tuning and design of the loop filter gains from the large-signal model point of view, including all the nonlinearities, adopting the stochastic optimization method. All simulations are implemented using the MATLAB/Simulink 2018b environment to validate all theoretical analyses of this paper. The sampling and nominal frequencies are set to be 100 kHz and 50 Hz throughout all the simulation studies.
Particle Swarm Optimization for an Optimal Hybrid Renewable Energy Microgrid System under Uncertainty
Authors: Mquqwana Manduleli Alfred , Krishnamurthy Senthil
Published: January 2024

Microgrids can assist in managing power supply and demand, increase grid resilience to adverse weather, increase the deployment of zero-emission energy sources, utilise waste heat, and reduce energy wasted through transmission lines. To ensure that the full benefits of microgrid use are realised, hybrid renewable energy-based microgrids must operate at peak efficiency. To offer an optimal solution for managing microgrids with hybrid renewable energy sources (HRESs) while taking microgrid reserve margins into account, the particle swarm optimisation (PSO) method is suggested. The suggested approach demonstrated good performance in terms of charging and discharging BESS and maintaining the necessary reserve margins to supply critical loads if the grid and renewable energy sources are unavailable. On a clear day, the amount of electricity sold to the grid increased by 58%, while on a partially overcast day, it increased by 153%. Microgrids provide a good return on investment for their operators when they are run at peak efficiency. This is because the BESS is largely charged during off-peak hours or with excess renewable energy, and power is only purchased during less expensive off-peak hours.
Chemical Ecology, Detection and Identification of Subterranean Termites Based on Electronic-Nose Volatile Emissions Analysis
Authors: Wilson Alphus Dan , Forse Lisa Beth
Published: January 2024

The effective monitoring and identification of existing subterranean termite populations within coarse woody debris and infested wood in service depend on accurate detection. These insects are often concealed within logs, wooden support structures, walls, and floorboards of buildings. In the absence of external mud tubes, termite infestations normally must be discovered through the destructive exploration of wooden structures to reveal the physical presence of these insect pests. Subterranean termite species are difficult to identify due to similarities in morphological features, but they may be readily distinguished by differences in volatile emissions from which they are divided into chemotaxonomic groups. Consequently, a more effective and nondestructive approach for detection and identification is to take advantage of unique species-specific emissions of volatile organic compounds (VOCs) from termite bodies which easily pass through wooden structures, allowing for detection without physical damage to wood and avoiding expensive DNA analysis. Electronic aroma detection analyses were conducted with an Aromascan A32S electronic-nose (e-nose) instrument, fitted with a 32-sensor conducting polymer (CP) sensor array, for discrimination between four common subterranean termite species based on differences in volatile emissions. Principal component analysis (PCA) of whole-body volatiles effectively distinguished between four termite species with the first two principal components accounting for more than 98% of sample variance (p < 0.01). Unique electronic aroma signature patterns (smellprints) were produced from e-nose sensor array outputs that allowed for the effective identification of termite species based on distinct differences in volatile metabolites released from their bodies. The e-nose methods were determined to be an improved means for rapidly detecting and monitoring termite species in wood. The method is cheaper than conventional detection methods and allows for the timelier discovery of species-specific termite infestations necessary for better management. The e-nose capability of detecting the Formosan termite in indoor living spaces was particularly significant due to the production of naphthalene, a volatile hazardous gas causing many adverse human health effects in enclosed environments.
Early-Stage Pine Wilt Disease Detection via Multi-Feature Fusion in UAV Imagery
Authors: Xie Wanying , Wang Han , Liu Wenping , Zang Hanchen
Published: January 2024

Pine wilt disease (PWD) is a highly contagious and devastating forest disease. The timely detection of pine trees infected with PWD in the early stage is of great significance to effectively control the spread of PWD and protect forest resources. However, in the spatial domain, the features of early-stage PWD are not distinctly evident, leading to numerous missed detections and false positives when directly using spatial-domain images. However, we found that frequency domain information can more clearly express the characteristics of early-stage PWD. In this paper, we propose a detection method based on deep learning for early-stage PWD by comprehensively utilizing the features in the frequency domain and the spatial domain. An attention mechanism is introduced to further enhance the frequency domain features. Employing two deformable convolutions to fuse the features in both domains, we aim to fully capture semantic and spatial information. To substantiate the proposed method, this study employs UAVs to capture images of early-stage pine trees infected with PWD at Dahuofang Experimental Forest in Fushun, Liaoning Province. A dataset of early infected pine trees affected by PWD is curated to facilitate future research on the detection of early-stage infestations in pine trees. The results on the early-stage PWD dataset indicate that, compared to Faster R-CNN, DETR and YOLOv5, the best-performing method improves the average precision (AP) by 17.7%, 6.2% and 6.0%, and the F1 scores by 14.6%, 3.9% and 5.0%, respectively. The study provides technical support for early-stage PWD tree counting and localization in the field in forest areas and lays the foundation for the early control of pine wood nematode disease.
Understanding the Effect of Knots on Mechanical Properties of Chinese Fir under Bending Test by Using X-ray Computed Tomography and Digital Image Correlation
Authors: Zhang Xie , Sun Huibo , Xu Gangbiao , Duan Yanjun , Jan Jan , Joris Joris , Shi Jiangtao
Published: January 2024

Knots in wood have a substantial impact on both the physical and mechanical properties of derived products. It is necessary to study their effect on the mechanical properties of wood and understand the mechanisms behind the effect. The modulus of elasticity (MOE) and modulus of rupture (MOR) of specimens without knots and with knots are measured using the three-point bending test. The size and position of knots are recorded. The specimens with knots are analyzed according to failure not at knots and failure at knots. For specimens with failure at knots, they are further divided into two sub-groups, i.e., failure around knots (FK-A) or failure in knots (FK-I).
The Observation of Creep Strain Distribution in Laminated Veneer Lumber Subjected to Different Loading Regimes
Authors: Xu Shuwei , Cao Yizhong , Cao Xiaobing , Yang Pei , Liu Xiaohan , Tang Ruixing , Yan Yutao , Wu Qiang
Published: January 2024

Timber architectures have arisen as sustainable solutions for high-rise and long-span buildings, assisting in implementing a circular economy. The creep strain dissipation of laminated veneer lumber (LVL) was investigated in this work to understand the inherent creep behaviors of LVL derived from natural wood. The results demonstrated a significant loading regime dependency of the creep behaviors of LVL. Coupled creep strain dissipation that transits/is parallel to the wood–adhesive interface was proven in the creep deformation of flat-wise and edge-wise bent LVL. In contrast, the creep strain dissipated considerably along the wood–adhesive interface when the LVL was subjected to axial compression creep. Further investigation into the morphologies of LVL after creep revealed that direct contact between the loading plane and wood–adhesive interface could be a plausible trigger for the accelerated deformation and the resultant plastic deformation of the LVL after creep. We believe that this work provides essential insights into the creep strain dissipation of LVL. It is thus beneficial for improving creep resistance and assisting in the long-term safe application of LVL-based engineered wood products in timber architectures.
Methodological Aspects and Mesh Convergence in Numerical Analysis of Athermal Fiber Network Material Deformation
Authors: Parvez Nishan , Amjad Syed Nabeel , Dey Mithun K. , Picu Catalin R.
Published: January 2024

A balance between model complexity, accuracy, and computational cost is a central concern in numerical simulations. In particular, for stochastic fiber networks, the non-affine deformation of fibers, related non-linear geometric features due to large global deformation, and size effects can significantly affect the accuracy of the computer experiment outputs and increase the computational cost. In this work, we systematically investigate methodological aspects of fiber network simulations with a focus on the output accuracy and computational cost in models with cellular (Voronoi) and fibrous (Mikado) network architecture. We study both p and h-refinement of the discretizations in finite element solution procedure, with uniform and length-based adaptive h-refinement strategies. The analysis is conducted for linear elastic and viscoelastic constitutive behavior of the fibers, as well as for networks with initially straight and crimped fibers. With relative error as the determining criterion, we provide recommendations for mesh refinement, comment on the necessity of multiple realizations, and give an overview of associated computational cost that will serve as guidance toward minimizing the computational cost while maintaining a desired level of solution accuracy.
Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions
Authors: Mara Andrea , Migliorini Matteo , Ciulu Marco , Chignola Roberto , Egido Carla , Núñez Oscar , Sentellas Sònia , Saurina Javier , Caredda Marco , Deroma Mario A. , Deidda Sara , Langasco Ilaria , Pilo Maria I. , Spano Nadia , Sanna Gavino
Published: January 2024

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors.
Methodological Challenges and Confounders in Research on the Effects of Ketogenic Diets: A Literature Review of Meta-Analyses
Authors: Szendi Katalin , Murányi Edit , Hunter Nicole , Németh Balázs
Published: January 2024

Several meta-analyses have found a positive association between a popular type of “fad diet”, ketogenic diets, and their effect on anthropometric and blood parameters. However, the non-specific inclusion criteria for meta-analyses may lead to incorrect conclusions. The aim of this literature review is to highlight the main confounders and methodological pitfalls of meta-analyses on ketogenic diets by inspecting the presence of key inclusion criteria. The PubMed, Embase, and Web of Science databases and the Cochrane Database of Systematic Reviews were searched for meta-analyses. Most meta-analyses did not define the essential parameters of a ketogenic diet (i.e., calories, macronutrient ratio, types of fatty acids, ketone bodies, etc.) as inclusion criteria. Of the 28 included meta-analyses, few addressed collecting real, re-measured nutritional data from the ketogenic diet and control groups in parallel with the pre-designed nutritional data. Most meta-analyses reported positive results in favor of ketogenic diets, which can result in erroneous conclusions considering the numerous methodological pitfalls and confounders. Well-designed clinical trials with comparable results and their meta-analyses are needed. Until then, medical professionals should not recommend ketogenic diets as a form of weight loss when other well-known dietary options have been shown to be healthy and effective.
Evaluation of the Emulsifying Property and Oxidative Stability of Myofibrillar Protein-Diacylglycerol Emulsions Containing Catechin Subjected to Different pH Values
Authors: Li Yuexin , Wang Hui , Zhao Yubo , Chen Qian , Xia Xiufang , Liu Qian , Kong Baohua
Published: January 2024

Myofibrillar protein–diacylglycerol emulsions containing catechin (MP-DAG-C) possess outstanding emulsifying property and oxidative stability. However, the effect of pH on MP-DAG-C emulsions should be revealed to provide possibilities for their application in practical meat products. Therefore, MP-DAG-C emulsions at different pH values were used in this study, in which lard, unpurified glycerolytic lard (UGL), and purified glycerolytic lard (PGL) were used as the oil phases. The results indicated that the emulsifying property of the UGL- and PGL-based emulsions increased compared to those of the lard-based emulsions (p < 0.05). The emulsifying activity and stability indices, absolute value of ζ-potential, and rheological characteristics increased with the increase in pH values (p < 0.05), with the droplets were smallest and distributed most uniformly at a pH of 6.5 compared to the other acidic environment (p < 0.05). The thiobarbituric acid substance and carbonyl content increased (p < 0.05), while the total sulfydryl content decreased (p < 0.05) during storage. However, there was no statistical difference between the oxidative stability of the MP-DAG-C emulsions with different pH values (p > 0.05). The results implied that the emulsifying property of MP-DAG-C emulsions increased with an increase in pH values. The oxidative stability of the MP-DAG-C emulsions at high pH values was improved by catechin.
Fractal-Based Pattern Quantification of Mineral Grains: A Case Study of Yichun Rare-Metal Granite
Authors: Liu Yue , Sun Tao , Wu Kaixing , Zhang Hongwei , Zhang Jingwei , Jiang Xinwen , Lin Quanwei , Feng Mei
Published: January 2024

The quantification of the irregular morphology and distribution pattern of mineral grains is an essential but challenging task in ore-related mineralogical research, allowing for tracing the footprints of pattern-forming geological processes that are crucial to understanding mineralization and/or diagenetic systems. In this study, a large model, namely, the Segmenting Anything Model (SAM), was employed to automatically segment and annotate quartz, lepidolite and albite grains derived from Yichun rare-metal granite (YCRMG), based on which a series of fractal and multifractal methods, including box-counting calculation, perimeter–area analysis and multifractal spectra, were implemented. The results indicate that the mineral grains from YCRMG show great scaling invariance within the range of 1.04~52,300 μm. The automatic annotation of mineral grains from photomicrographs yields accurate fractal dimensions with an error of only 0.6% and thus can be utilized for efficient fractal-based grain quantification. The resultant fractal dimensions display a distinct distribution pattern in the diagram of box-counting fractal dimension (Db) versus perimeter–area fractal dimension (DPA), in which lepidolites are sandwiched between greater-valued quartz and lower-valued albites. Snowball-textured albites, i.e., concentrically arranged albite laths in quartz and K-feldspar, exhibit characteristic Db values ranging from 1.6 to 1.7, which coincide with the fractal indices derived from the fractal growth model. The zonal albites exhibit a strictly increasing trend regarding the values of fractal and multifractal exponents from core to rim, forming a featured “fractal-index banding” in the radar diagram. This pattern suggests that the snowball texture gradually evolved from rim to core, thus leading to greater fractal indices of outer zones, which represent higher complexity and maturity of the evolving system, which supports a metasomatic origin of the snowball texture. Our study demonstrates that fractal analyses with the aid of a large model are effective and efficient in characterizing and understanding complex patterns of mineral grains.
Deep-Learning Estimators for the Hurst Exponent of Two-Dimensional Fractional Brownian Motion
Authors: Chang Yen-Ching
Published: January 2024

The fractal dimension (D) is a very useful indicator for recognizing images. The fractal dimension increases as the pattern of an image becomes rougher. Therefore, images are frequently described as certain models of fractal geometry. Among the models, two-dimensional fractional Brownian motion (2D FBM) is commonly used because it has specific physical meaning and only contains the finite-valued parameter (a real value from 0 to 1) of the Hurst exponent (H). More usefully, H and D possess the relation of D = 3 − H. The accuracy of the maximum likelihood estimator (MLE) is the best among estimators, but its efficiency is appreciably low. Lately, an efficient MLE for the Hurst exponent was produced to greatly improve its efficiency, but it still incurs much higher computational costs. Therefore, in the paper, we put forward a deep-learning estimator through classification models. The trained deep-learning models for images of 2D FBM not only incur smaller computational costs but also provide smaller mean-squared errors than the efficient MLE, except for size 32 × 32 × 1. In particular, the computational times of the efficient MLE are up to 129, 3090, and 156248 times those of our proposed simple model for sizes 32 × 32 × 1, 64 × 64 × 1, and 128 × 128 × 1.