bluuebunny/crossref_metadata_2025 huggingface dataset:
Decentralized Identity Management for Metaverse-Enhanced Education: A Literature Review
Authors: Polychronaki Maria , Xevgenis Michael G. , Kogias Dimitrios G. , Leligou Hellen C.
Published: September 2024

As we transition into the era of Web 3.0, where decentralized information and user privacy are paramount, emerging technologies are reshaping the way in which personal data are managed. This paper focuses on decentralized identity management (DID) in the metaverse, particularly within the education sector, which has rapidly embraced digital tools for e-learning, especially since the COVID-19 pandemic. Technologies such as blockchain, artificial intelligence (AI), and virtual and augmented reality (VR/AR) are increasingly integrated into educational platforms, raising questions about privacy, security, and interoperability. This literature review examines the current landscape of DID in metaverse-based educational applications. Through a systematic methodology, relevant academic papers were identified, filtered, and analyzed based on four key criteria: standardization, interoperability, application scalability, and security/privacy considerations. The paper provides a comparative analysis of these papers to assess the maturity of DID implementations, highlight existing challenges, and suggest future research directions in the intersection of decentralized identity and educational metaverse applications.
Reliability Enhancement of a Double-Switch Single-Ended Primary Inductance–Buck Regulator in a Wind-Driven Permanent Magnet Synchronous Generator Using a Double-Band Hysteresis Current Controller
Authors: Emar Walid , Alzgool Mais , Mansour Ibrahim
Published: September 2024

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of (D (1+D)/(1−D). where D is the regulator transistor’s on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance.
An Experimental and Kinetic Modeling Study of the Laminar Burning Velocities of Ammonia/n-Heptane Blends
Authors: Liang Jinhu , Wang Anwen , Feng Yujia , Li Xiaojie , Hu Yi , Dong Shijun , Zhang Yang , Zhao Fengqi
Published: September 2024

Ammonia is carbon-free and is a very promising renewable fuel. The ammonia/diesel dual-fuel combustion strategy is an important combustion strategy for ammonia internal combustion engines. To achieve clean and efficient combustion with a high ammonia blending ratio in ammonia engines, it is important to thoroughly investigate the combustion characteristics and chemical reaction mechanisms of ammonia/diesel fuel blends. Based on the constant volume combustion vessel experiments, the laminar burning velocities (LBVs) of ammonia/n-heptane blends were measured at the conditions of an ammonia–energy ratio of 60–100%, at initial pressures of 0.1–0.5 MPa and initial temperatures of 338–408 K, and under an equivalence ratio regime of 0.8–1.3. The experimental results indicate that the laminar burning velocities of ammonia/n-heptane fuel blends increase with a decreasing ammonia–energy ratio. Specifically, with an ammonia–energy ratio of 60%, an initial temperature of 373 K, an initial pressure of 0.1 MPa, and an equivalence ratio of 1.1, the measured LBV is approximately 20 cm/s, which is about 61% faster than that of pure ammonia flames under the same conditions. A previously developed chemical kinetic mechanism is employed to simulate the new experimental data, and the model exhibits overall good performance. The sensitivity analyses have been conducted to highlight the important reaction pathways. The elementary reaction O2 + Ḣ<=>Ö + ȮH demonstrates the most significant promotional effect on the laminar burning velocities, while the interaction reaction pathways of via H-abstraction from n-heptane by ṄH2 radicals are not showing obvious effects on the simulation results under the studied conditions.
Multi-Objective Optimization and Reconstruction of Distribution Networks with Distributed Power Sources Based on an Improved BPSO Algorithm
Authors: Lu Dan , Li Wenfeng , Zhang Linjuan , Fu Qiang , Jiao Qingtao , Wang Kai
Published: September 2024

The continuous integration of distributed power into the distribution network has increased the complexity of the distribution network and created challenges in distribution-network reconfiguration. In order to make the distribution network operate in the optimal mode, this paper establishes a multi-objective reconfiguration-optimization model that takes into account active network loss, voltage offset, number of switching actions and distributed power output. For a distribution network with a distributed power supply, it is easy for the traditional binary particle swarm optimization algorithm to fall into a local optimum. In order to improve the convergence speed of the algorithm and avoid premature convergence, this paper adopts an improved binary particle swarm optimization algorithm to solve the problem. The IEEE33 node system is used as an example for simulation verification. The experimental results show that the algorithm improves the convergence speed and global search ability, effectively reduces the system network loss, and greatly improves the voltage level of each node. It improves the stability and economy of distribution-network operation and can effectively solve the problem of multi-objective reconfiguration.
The Operation Strategy of a Multi-Microgrid Considering the Interaction of Different Subjects’ Interests
Authors: Wang Siwen , Chen Hui , Gong Chunyang , Shang Yanfei , Wang Zhixin
Published: September 2024

As the share of renewable energy generation continues to increase, the new-type power system exhibits the characteristics of coordinated operation between the main grid, distribution networks, and microgrids. The microgrid is primarily concerned with achieving self-balancing between power sources, the network, loads, and storage. In decentralized multi-microgrid (MMG) access scenarios, the aggregation of distributed energy within a region enables the unified optimization of scheduling, which improves regional energy self-sufficiency while mitigating the impact and risks of distributed energy on grid operations. However, the cooperative operation of MMGs involves interactions among various stakeholders, and the absence of a reasonable operational mechanism can result in low energy utilization, uneven resource allocation, and other issues. Thus, designing an effective MMG operation strategy that balances the interests of all stakeholders has become a key area of focus in the industry. This paper examines the definition and structure of MMGs, analyzes their current operational challenges, compiles existing research methods and practical experiences, explores synergistic operational mechanisms and strategies for MMGs under different transaction models, and puts forward prospects for future research directions.
An Integrated Frequency Regulation Method Based on System Frequency Security Posture
Authors: Zhang Qiang , Wang Chao , Song Wenting , Chao Pupu , Jin Yonglin , Zeng Hui , Li Ping , Liu Wansong
Published: September 2024

As the share of renewable energy in a grid increases, the grid’s frequency support capability weakens, and the spatial distribution of grid frequency becomes more pronounced. As a result, control strategies based on system frequency consistency and traditional frequency regulation dominated by synchronous machines are becoming increasingly inadequate for meeting the frequency regulation requirements of new-type power systems. To enhance the system’s frequency support capability, it is imperative to fully utilize the frequency regulation resources within the power system. To address this issue, this paper first introduces a system frequency security posture assessment method that accounts for the spatial distribution characteristics of the grid. Subsequently, a parameter optimization method for diverse frequency regulation resources is proposed in conjunction with the proposed comprehensive evaluation method for frequency regulation. Next, using a renewable energy feeder regional grid as an example, an integrated frequency regulation method based on the system frequency security posture is presented. Finally, the frequency regulation performance and economic costs of different frequency regulation methods are analyzed under various operating scenarios and disturbances using a model based on actual data from the renewable energy feeder regional grid. The simulation and index calculation results demonstrate that the method proposed in this paper effectively enhances the system’s frequency support capability, reduces the frequency disparity between different nodes within the grid, and maintains high economic performance.
Review of Reservoir Damage Mechanisms Induced by Working Fluids and the Design Principles of Reservoir Protection Fluids: From Oil–Gas Reservoirs to Geothermal Reservoirs
Authors: Jiang Ou , Cao Ling , Zhu Wenxi , Zheng Xiuhua
Published: September 2024

Various working fluids are applied during geothermal reservoir development, and geothermal reservoir damage induced by contacts between working fluids and reservoir formations are inevitable. Reservoir damage mechanisms, including solid and colloidal plugging, fluid sensitivity, stress sensitivity, and water locking, provide guidance for designing reservoir protection working fluids. In this paper, based on the design principles of reservoir protection working fluids applied in oil–gas reservoirs, four design principles of reservoir protection working fluids are proposed to eliminate potential geothermal reservoir damage for geothermal reservoirs, containing solid-free, facilitated flowback, temporary plugging, and inhibition. Solid-free is achieved by replacing solids with polymers in working fluids. Surfactant and materials with low affinity towards rock surfaces are applied for the facilitated flowback of working fluids from reservoir formations. Temporary plugging is achieved by using temporary plugging materials, some of which are polymers that also apply to solid-free working fluids. Besides, some of the temporary plugging materials, such as surfactant, are applicable for both the facilitated flowback and inhibition of working fluids. The inhibition of working fluids include the inhibition of clay minerals, which can be attributed to clay mineral inhibitors or activity regulators in working fluids, as well as the inhibition of mineral precipitations. This review aims to provide insights for geothermal reservoir protection working fluids, contributing to achieving an efficient development of geothermal resources.
Design of Flow Fields for High-Temperature PEM Fuel Cells Using Computational Fluid Dynamics
Authors: Chowdhury Prantik Roy , Gladen Adam C.
Published: September 2024

This study proposes novel and modified conventional flow fields for a high-temperature PEM fuel cell, and predicts the fluid dynamic behavior with a 3D, computational fluid dynamics model. Five base flow field patterns (FFPs) are selected: a 4-channel serpentine, a hybrid design, a 2-channel spiral, a dual-triangle sandwich, and a parallel pin-type flow field. For each base FFP, sub-patterns are developed through modification of the channels and ribs. The 4-channel serpentine is taken as the state-of-the-art reference flow field. Simulations are carried out at two different mass flow rates. The result shows that the incorporation of a dead end in flow channels or the merging of channels into a single channel before connecting to the outlet enhances the average and maximum GDL mass flux, but it also increases the pressure drop. The parallel pin-type design-3 and dual-triangle sandwich design-1 exhibit a more even distribution but yield a lower average GDL mass flux than the 4-channel serpentine, which could be beneficial for reducing MEA degradation and thus used at low load conditions where a high mass flux is not needed. In contrast, the uniform hybrid design and 2-channel spiral design-2 provide a higher average and maximum mass flux with a more non-uniform distribution and greater pressure drop. The high average GDL mass flux would be beneficial during high load conditions to ensure enough reactants reach the catalyst.
Transforming Wastewater into Biofuel: Nutrient Removal and Biomass Generation with Chlorella vulgaris
Authors: Salgueiro Jose Luis , Perez-Rial Leticia , Maceiras Rocio , Sanchez Angel , Cancela Angeles
Published: September 2024

This study investigates the potential of Chlorella vulgaris for nutrient removal and biomass production in synthetic wastewater. The experiments were conducted in 2 L photobioreactors under controlled aeration, agitation, and lighting conditions for 19 days. Despite a moderate growth rate (0.137 d−1), C. vulgaris achieved efficient pollutant removal, with 97% of nitrate, 90% of nitrite, and 90.6% of COD eliminated. Additionally, the biomass was processed to extract fatty acids, yielding a 20% extraction rate, indicating its potential as a biofuel feedstock. These results demonstrate C. vulgaris’s dual function in wastewater remediation and biofuel production, presenting a sustainable and economically viable approach to addressing environmental challenges.
A Data-Driven Predictive Control Method for Modeling Doubly-Fed Variable-Speed Pumped Storage Units
Authors: Zhao Peiyu , Nan Haipeng , Cai Qingsen , Gao Chunyang , Wu Luochang
Published: September 2024

In this study, a data-driven model predictive control (MPC) method is proposed for the optimal control of a doubly-fed variable-speed pumped storage unit. This method combines modern control theory with the dynamic characteristics of the pumped storage unit to establish an accurate dynamic model based on actual operating data. In each control cycle, the MPC uses the system model to predict future system behavior and determines the optimal control input sequence by solving the constrained optimization problem, thereby effectively dealing with the nonlinearity, time-varying characteristics, and multivariable coupling problems of the system. When compared with a traditional PID control, this method significantly improves control accuracy, response speed, and system stability. The simulation results show that the proposed MPC method exhibits better steady-state error, overshoot, adjustment time, and control energy under various operating conditions, demonstrating its advantages in complex multivariable systems. This study provides an innovative solution for the efficient control of doubly-fed variable-speed pumped storage units and lays a solid foundation for the efficient utilization of new energy sources.
Probabilistic Estimation of Parameters for Lubrication Application with Neural Networks
Authors: Paschek Stefan , Förster Frederic , Kipfmüller Martin , Heizmann Michael
Published: September 2024

This paper investigates the use of neural networks to predict characteristic parameters of the grease application process pressure curve. A combination of two feed-forward neural networks was used to estimate both the value and the standard deviation of selected features. Several neuron configurations were tested and evaluated in their capability to make a probabilistic estimation of the lubricant’s parameters. The value network was trained with a dataset containing the full set of features and with a dataset containing its average values. As expected, the full network was able to predict noisy features well, while the average network made smoother predictions. This is also represented by the networks’ R2 values which are 0.781 for the full network and 0.737 for the mean network. Several further neuron configurations were tested to find the smallest possible configuration. The analysis showed that three or more neurons deliver the best fit over all features, while one or two neurons are not sufficient for prediction. The results showed that the grease application process pressure curve via pressure valves can be estimated by using neural networks.
Metal Bioaccumulation and Biochemical Responses in Loggerhead Turtles (Caretta caretta) from the Gulf of Gabès (Tunisia)
Authors: Hrizi Marwa , Jribi Imed , Baracchini Clément , Leignel Vincent
Published: September 2024

Caretta caretta (Cheloniidae, Cryptodira) is a species of turtle considered a ‘flagship species’ in the Mediterranean Sea. Unfortunately, the circular marine currents and semi-enclosed configuration of the Mediterranean Sea encourage the accumulation of pollutants (metals, pesticides, etc.) emitted by human activities. Tunisia suffers particularly from coastal urbanisation and industrial development. Metal concentrations (Ag, Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn) were measured in distinct tissues (heart, kidney, liver, lung, muscle) of loggerhead turtles stranded in the Gulf of Gabès (Tunisia) to estimate the pollution levels in this emblematic species. High concentrations of arsenic and cadmium were found in marine turtles. Therefore, the differential accumulation of metals was measured in the tissues. For example, the liver appears to be a preferential organ for the accumulation of copper, iron, silver and zinc. In contrast, cobalt and cadmium were more concentrated in the kidneys, while arsenic, chromium and nickel were mainly found in the muscles. Antioxidant enzyme responses (catalase, GPx and SOD) and lipid peroxidation were more expressed in the liver and kidneys than in the muscles.
Adaptive Operation Strategy of a District Cooling System with Chilled Water Storage and Its Validations by OpenModelica Modeling and Simulations
Authors: Liu Yang , Wang Songcen , Chen Hongyin , Zhong Ming
Published: September 2024

Developing operation strategies for district cooling systems with chilled water storage is challenging due to uncertain fluctuations of cooling demand in actual operations. To address this issue, this paper developed an adaptive operation strategy and performed its validations by modeling and simulating a commercial cooling system in Shanghai using OpenModelica. Firstly, the originally designed operation strategy of the cooling system was evaluated by simulation but was found unable to meet the statistically averaged ideal cooling requirements due to the early exhaustion of stored chilled water at about 5:30 PM. Then, to build foundations for adaptive operation strategy development, a newly designed operation strategy was established by increasing the operation time of base load chillers in the valley and flat electricity price periods. The new strategy proved numerically sustainable in satisfying the ideal cooling demand. Moreover, to realize the strategy’s adaptability to actual cooling load fluctuations, an adaptive operation strategy was developed by tracking the target stored chilled water mass curve that was calculated by implementing the newly designed strategy. The simulation results verify that the adaptive operation strategy enables good adaptability to representative cooling load fluctuation cases by automatically and periodically adjusting the operation status of base load chillers. The adaptive operation strategy was then further widely numerically tested in hundreds of simulation cases with different cooling load variations. The time-lagging problem resulting in strategy failures was found in numerical tests and was addressed by slightly modifying the adaptive strategy. Results indicate that the adaptive operation strategy enables adaptability to deal with cooling demand fluctuations as well as allowing low cooling supply economic costs and power grid-friendly characteristics. This study provides theoretical support to strategy design and validations for district cooling system operations.
Taxonomic Studies on Five Species of Sect. Tuberculata (Camellia L.) Based on Morphology, Pollen Morphology, and Molecular Evidence
Authors: Xiao Xu , Li Zhi , Ran Zhaohui , Yan Chao , Tang Ming , Huang Lang
Published: September 2024

Sect. Tuberculata Chang in the genus Camellia (Theaceae Mirb.) is named after the “tubercle-like projections on the surface of the capsule and ovary”. Due to complex morphological variations in these taxon and insufficient field investigations, the interspecies relationships are unclear, the species’ definitions are vague, and the names are confusing. This is not conducive to the conservation and study of these species. Therefore, herein, we systematically explore the taxonomic status of five sect. Tuberculata species using morphological, pollen morphological, and molecular phylogenetic methods. The results showed that (1) the morphological characteristics of the flower, fruit, and leaves of C. anlungensis and C. leyeensis are similar. Furthermore, the pollen characteristics and pollen wall ornamentation show that there is no significant difference between the two species; (2) there are significant differences between C. acutiperulata and C. anlungensis in terms of leaf shape (elliptic vs. obovate), calyx characteristics (sepal apex pointed vs. sepal oblong), and fruit shape (subglobose folds with shallow verruculose vs. flat folds and verruculose protuberances with pronounced internal cleavage); (3) C. pyxidiacea and C. rubituberculata differ in flower color (white or light color vs. red) and fruit verrucae (obviously deeply cleft vs. shallowly uncracked); (4) a phylogenetic tree based on the chloroplast genome shows that C. anlungensis and C. leyeensis form a single clade (BS = 100%, PP = 1.0) and are on a different branch, with C. acutiperulata on clade II (BS = 100%, PP = 1.0), and C. pyxidiacea and C. rubituberculata clustered on different branches of clade I (BS = 99%, PP = 1.00). Considering the above results together, we propose that C. leyeensis should be treated as a homonym of C. anlungensis, and C. acutiperulata, C. pyxidiacea, and C. rubituberculata should be considered as separate species. Clarifying the taxonomic status of these five species not only advances our understanding of the significance and complexity of the systematic classification of the genus Camellia but also has important implications for diversity conservation and population genetics.
Enhanced Estimation of Crown-Level Leaf Dry Biomass of Ginkgo Saplings Based on Multi-Height UAV Imagery and Digital Aerial Photogrammetry Point Cloud Data
Authors: Qiu Saiting , Zhu Xingzhou , Zhang Qilin , Tao Xinyu , Zhou Kai
Published: September 2024

Ginkgo is a multi-purpose economic tree species that plays a significant role in human production and daily life. The dry biomass of leaves serves as an accurate key indicator of the growth status of Ginkgo saplings and represents a direct source of economic yield. Given the characteristics of flexibility and high operational efficiency, affordable unmanned aerial vehicles (UAVs) have been utilized for estimating aboveground biomass in plantations, but not specifically for estimating leaf biomass at the individual sapling level. Furthermore, previous studies have primarily focused on image metrics while neglecting the potential of digital aerial photogrammetry (DAP) point cloud metrics. This study aims to investigate the estimation of crown-level leaf biomass in 3-year-old Ginkgo saplings subjected to different nitrogen treatments, using a synergistic approach that combines both image metrics and DAP metrics derived from UAV RGB images captured at varying flight heights (30 m, 60 m, and 90 m). In this study, image metrics (including the color and texture feature parameters) and DAP point cloud metrics (encompassing crown-level structural parameters, height-related and density-related metrics) were extracted and evaluated for modeling leaf biomass. The results indicated that models that utilized both image metrics and point cloud metrics generally outperformed those relying solely on image metrics. Notably, the combination of image metrics obtained from the 60 m flight height with DAP metrics derived from the 30 m height significantly enhanced the overall modeling performance, especially when optimal metrics were selected through a backward elimination approach. Among the regression methods employed, Gaussian process regression (GPR) models exhibited superior performance (CV-R2 = 0.79, rRMSE = 25.22% for the best model), compared to Partial Least Squares Regression (PLSR) models. The common critical image metrics for both GPR and PLSR models were found to be related to chlorophyll (including G, B, and their normalized indices such as NGI and NBI), while key common structural parameters from the DAP metrics included height-related and crown-related features (specifically, tree height and crown width). This approach of integrating optimal image metrics with DAP metrics derived from multi-height UAV imagery shows great promise for estimating crown-level leaf biomass in Ginkgo saplings and potentially other tree crops.
Two Infectious Diseases: “COVID-19” and “Pine Wilt Disease”
Authors: Futai Kazuyoshi
Published: September 2024

Two epidemics, a new coronavirus disease (hereafter COVID-19) and pine wilt disease (hereafter PWD) whose causal agent is the pine wood nematode Bursaphelenchus xylophilus, are similar in terms of disease spread, particularly in an important role of the latent carrier in the spread of the disease. In Japan, damage caused by PWD has gradually decreased over the past 40 years, not because of successful control of PWD, but because pine forests susceptible to pine wilt have been drastically reduced by the disease. Meanwhile, COVID-19, which was first identified in China in 2019, became a pandemic in 2020 and caused long-term disruptions to people’s lives worldwide. Even after the declaration of the end of the emergency by the WHO in May 2023, the coronavirus continues to produce new variants and maintains the potential for new waves of infection. In this paper, I would like to discuss the issues of control measures for the forest disease PWD, especially for the measures against asymptomatic carrier trees, with reference to the efforts implemented for COVID-19, which is more closely related to human society. This is because an asymptomatic carrier has been a blind spot in conventional PWD control measures, and I believe that a fundamental review of control measures considering this aspect is essential, and understanding the similarities between COVID-19 management and PWD control can provide guidance on how to effectively deal with both human and plant epidemics.
Timber Harvest Planning Using Reinforcement Learning: A Feasibility Study
Authors: Ji Hyo-Vin , Han Sang-Kyun , Park Jin-Woo
Published: September 2024

This study developed a forest management plan model using reinforcement learning (Q-learning) to optimize both the economic and ecological functions of forests. Management objectives for national forests were established, and forest conditions were analyzed using GIS spatial data and administrative records. A 60-year forest management plan was formulated to predict timber production and management performance across different regions and time periods. Our analysis revealed that Scenario 3 (Carbon Storage Priority) demonstrated the highest economic value, starting at approximately KRW 576.2 billion in the initial period and escalating to KRW 775.7 billion over six 10-year periods, totaling 60 years. In addition to its economic performance, Scenario 3 effectively improved forest age class structure and ensured a stable timber supply, making it the most balanced approach for sustainable forest management. By focusing on carbon storage as a key management goal, this approach highlights the potential for achieving both economic and environmental benefits concurrently. These results suggest that reinforcement learning is a powerful tool for developing long-term forest management strategies that address multiple objectives, including economic viability, ecological sustainability, and resource optimization.
Evaluating Multi-Criteria Decision-Making Methods for Sustainable Management of Forest Ecosystems: A Systematic Review
Authors: Kpadé Cokou Patrice , Tamini Lota D. , Pepin Steeve , Khasa Damase P. , Abbas Younes , Lamhamedi Mohammed S.
Published: September 2024

Multi-criteria decision-making (MCDM) methods provide a framework for addressing sustainable forest management challenges, especially under climate change. This study offers a systematic review of MCDM applications in forest management from January 2010 to March 2024. Descriptive statistics were employed to analyze trends in MCDM use and geographic distribution. Thematic content analysis investigated the appearance of MCDM indicators supplemented by Natural Language Processing (NLP). Factorial Correspondence Analysis (FCA) explored correlations between models and publication outlets. We systematically searched Web of Science (WoS), Scopus, Google Scholar, Semantic Scholar, CrossRef, and OpenAlex using terms such as ‘MCDM’, ‘forest management’, and ‘decision support’. We found that the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the most commonly used methods, followed by the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), the Analytic Network Process (ANP), GIS, and Goal Programming (GP). Adoption varied across regions, with advanced models such as AHP and GIS less frequently used in developing countries due to technological constraints. These findings highlight emerging trends and gaps in MCDM application, particularly for argan forests, emphasizing the need for context-specific frameworks to support sustainable management in the face of climate change.
Assessing Drought Impacts on Gross Primary Productivity of Rubber Plantations Using Flux Observations and Remote Sensing in China and Thailand
Authors: Li Weiguang , Hou Meiting , Liu Shaojun , Zhang Jinghong , Zou Haiping , Chen Xiaomin , Bai Rui , Lv Run , Hou Wei
Published: September 2024

Rubber (Hevea brasiliensis Muell.) plantations are vital agricultural ecosystems in tropical regions. These plantations provide key industrial raw materials and sequester large amounts of carbon dioxide, playing a vital role in the global carbon cycle. Climate change has intensified droughts in Southeast Asia, negatively affecting rubber plantation growth. Limited in situ observations and short monitoring periods hinder accurate assessment of drought impacts on the gross primary productivity (GPP) of rubber plantations. This study used GPP data from flux observations at four rubber plantation sites in China and Thailand, along with solar-induced chlorophyll fluorescence (SIF), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), near-infrared reflectance of vegetation (NIRv), and photosynthetically active radiation (PAR) indices, to develop a robust GPP estimation model. The model reconstructed eight-day interval GPP data from 2001 to 2020 for the four sites. Finally, the study analyzed the seasonal drought impacts on GPP in these four regions. The results indicate that the GPP prediction model developed using SIF, EVI, NDVI, NIRv, and PAR has high accuracy and robustness. The model’s predictions have a relative root mean square error (rRMSE) of 0.22 compared to flux-observed GPP, with smaller errors in annual GPP predictions than the MOD17A3HGF model, thereby better reflecting the interannual variability in the GPP of rubber plantations. Drought significantly affects rubber plantation GPP, with impacts varying by region and season. In China and northern Thailand (NR site), short-term (3 months) and long-term (12 months) droughts during cool and warm dry seasons cause GPP declines of 4% to 29%. Other influencing factors may alleviate or offset GPP reductions caused by drought. During the rainy season across all four regions and the cool dry season with adequate rainfall in southern Thailand (SR site), mild droughts have negligible effects on GPP and may even slightly increase GPP values due to enhanced PAR. Overall, the study shows that drought significantly impacts rubber the GPP of rubber plantations, with effects varying by region and season. When assessing drought’s impact on rubber plantation GPP or carbon sequestration, it is essential to consider differences in drought thresholds within the climatic context.
From Traditional to Exceptional: Impact of the Use of Dried Chicken Meat Powder on Sensory and Nutritional Quality of Tarhana
Authors: Cetin Ramazan Ulku , Kilci Zeynep , Ates Kivilcim , Kaya Dogan , Akpinar-Bayizit Arzu
Published: September 2024

Tarhana is a popular Turkish fermented food, made of a mixture of cereal and yoghurt, generally consumed as soup. Both lactic acid bacteria and yeasts are responsible for the fermentation. The selection and proportions of ingredients integrated along with the production process specify the nutritional value and sensory properties of the final product. Therefore, the first objective of the present study was to process a dried “chicken meat powder (CMP)” that could be used in food formulations. The second objective was to determine the impact of CMP addition on the nutritional and sensorial properties of Uşak tarhana recipe with geographical indication. In order to fulfill these challenges dried chicken meat powder (CMP) at levels of 20, 25, 30, and 35% were included in tarhana recipes for the very first time. Within the scope of the study, organoleptic properties of tarhana soups (control and CMP added) were determined, and the formulation with 30% CMP (TCMP30) achieved the highest sensory evaluation scores. This sample was analyzed further, and its physicochemical properties were compared to a control sample strictly following the traditional Uşak tarhana recipe. In the tarhana samples, the moisture, protein, and total fat content increased with higher CMP additions, while the ash, crude cellulose, carbohydrates, energy, salt, and dietary fiber decreased significantly (p < 0.05). The calcium and sodium contents decreased, however, potassium, phosphorus, and zinc contents increased. The fatty acid composition analysis revealed that Uşak tarhana contained more saturated fatty acids than either CMP or TCMP30; adding 30% CMP reduced the total saturated fatty acids while increasing the monounsaturated fatty acids. The main fatty acids in traditional samples were linoleic, palmitic, and oleic acids, comprising 83.82% of the total fat. In TCMP30, the order changed to oleic > linoleic > palmitic with 83.89% of total fat. Over time, the total phenolic content and antioxidant capacity decreased in the control sample but increased in TCMP30. These results suggest that a formulation including 30% CMP effectively enhances the sensory, functional, and nutritional aspects in tarhana.
Production of Carotenoids by Microorganisms
Authors: Saubenova Margarita , Rapoport Alexander , Venkatachalam Mekala , Dufossé Laurent , Yermekbay Zhanerke , Oleinikova Yelena
Published: September 2024

Carotenoids are one of the most studied groups of biologically active compounds. They have antioxidant, anti-inflammatory, anti-cancer, and coloring properties and are particularly interesting for the pharmaceutical, nutraceutical, food, feed, cosmetic, and textile industries. Rapidly growing consumer demand for natural products has led to a significant increase in research and development of opportunities for their production from natural sources. Among the sources of carotenoids of natural origin, various microorganisms are of greater interest. This mini-review briefly summarizes the information published mainly during the last decade about carotenoid-producing microorganisms, the physiological importance of carotenoids for microbial cells, and the possibilities to improve their biosynthesis. This review also describes some new approaches/directions to make biotechnological production of microbial carotenoids more efficient.
Assessment of the Biological Activity of a Probiotic Fermented Milk Product with the Addition of Lactobacillus helveticus Cell-Free Supernatant
Authors: Kishilova Svetlana Anatolyevna , Rozhkova Irina Vladimirovna , Kolokolova Anastasia Yurievna , Yurova Elena Anatolyevna , Leonova Victoria Alexandrovna , Mitrova Vera Anatolyevna
Published: September 2024

Products enriched with probiotic microorganisms have proven to possess immunomodulatory, antioxidant, hypo-cholesterolemic, hypotensive, and antimicrobial properties. Biologically active substances, which are by-products of microbial fermentation, have potential applications in various industries. Cell-free supernatants, depending on the microorganisms used and production conditions, can exhibit antimicrobial, antioxidant, bifidogenic, and other biological activities. This paper presents a study on the biological activity of a probiotic fermented milk product, supplemented with 0.01% lyophilized cell-free supernatant from Lactobacillus helveticus. The fermented milk product was developed based on a composition of Lacticaseibacillus rhamnosus F, Lactococcus cremoris CR201, and Propionibacterium shermanii E2. The research evaluated antimicrobial activity, Bifidobacteria growth stimulation, and the content of organic acids, amino acids, and B vitamins. It was found that adding lyophilized cell-free supernatant to the fermented milk product enhanced its biological activity. In particular, the experimental samples showed a threefold increase in vitamin B6 content compared to the control, reaching 22.412 μg/100 g. Additionally, the amino acid content in the experimental samples exhibited a significant increase of more than 100% in the essential amino acid tryptophan compared to the control. Notably, antimicrobial activity increased against several opportunistic strains. The experimental samples also showed a significant increase in lactic and formic acids, which may enhance the product’s inhibitory properties against pathogens. An increase in antioxidant activity was observed, potentially due to the higher content of tryptophan and vitamin B6. The positive effect of adding cell-free supernatant on the growth of Bifidobacteria was also demonstrated. Thus, the findings suggest that this cell-free supernatant can be recommended as an additive in the production of fermented milk products, food additives, dietary supplements, and animal feed.
Simulation of Fire Occurrence Based on Historical Data in Future Climate Scenarios and Its Practical Verification
Authors: Wang Mingyu , Si Liqing , Chen Feng , Shu Lifu , Zhao Fengjun , Li Weike
Published: September 2024

Forest fire is one of the dominant disturbances in the forests of Heilongjiang Province, China, and is one of the most rapid response predictors that indicate the impact of climate change on forests. This study calculated the Canadian FWI (Fire Weather Index) and its components from meteorological record over past years, and a linear model was built from the monthly mean FWI and monthly fire numbers. The significance test showed that fire numbers and FWI had a very pronounced correlation, and monthly mean FWI was suitable for predicting the monthly fire numbers in this region. Then FWI and its components were calculated from the SRES (IPCC Special Report on Emission Scenarios) A2 and B2 climatic scenarios, and the linear model was rebuilt to be suitable for the climatic scenarios. The results indicated that fire numbers would increase by 2.98–129.97% and −2.86–103.30% in the A2 and B2 climatic scenarios during 2020–2090, respectively. The monthly variation tendency of the FWI components is similar in the A2 and B2 climatic scenarios. The increasing fire risk is uneven across months in these two climatic scenarios. The monthly analysis showed that the FFMC (Fine Fuel Moisture Code) would increase dramatically in summer, and the decreasing precipitation in summer would contribute greatly to this tendency. The FWI would increase rapidly from the spring fire season to the autumn fire season, and the FWI would have the most rapid increase in speed in the spring fire season. DMC (Duff Moisture Code) and DC (Drought Code) have relatively balanced rates of increasing from spring to autumn. The change in the FWI in this region is uneven in space as well. In early 21st century, the FWI of the north of Heilongjiang Province would increase more rapidly than the south, whereas the FWI of the middle and south of Heilongjiang Province would gradually catch up with the increasing speed of the north from the middle of 21st century. The changes in the FWI across seasons and space would influence the fire management policy in this region, and the increasing fire numbers and variations in the FWI scross season and space suggest that suitable development of the management of fire sources and forest fuel should be conducted.
Rapid Monitoring of Aquatic Organism Biodiversity Based on Environmental DNA in a Medium-Sized Reservoir
Authors: Jia Hui , Xia Mingxia , Zhang Tao , Zhang Hui
Published: September 2024

Environmental DNA (eDNA) has emerged as a highly sensitive and efficient tool for the biomonitoring of aquatic ecosystems. In this study, we investigated fish and benthic species communities using eDNA techniques in a medium-sized reservoir (about 3 square kilometers) in Anhui, China. A total of 12 water samples and 11 sediment samples were analyzed by 12S and 18S primers, respectively. We analyzed the composition of species diversity and the effect of seven environmental factors using the Mantel test. A total of 42 fish taxa were present in the water samples, and 188 benthic taxa in the sediment samples. Species composition was different in disparate stations. We found that water temperature and salinity are pivotal factors influencing the composition of fish communities, while chlorophyll-a is a primary environmental determinant for benthic species assembly structures across different zones. Biodiversity information generated by eDNA techniques can be used to reflect the resource status of this reservoir. The relevant results will provide important scientific reference information for the development and exploitation of medium-sized reservoirs.
Improvement in the Number of Velocity Vector Acquisitions Using an In-Picture Tracking Method for 3D3C Rainbow Particle Tracking Velocimetry
Authors: Takeyama Mao , Fujiwara Kota , Hattori Yasuo
Published: September 2024

Particle image velocimetry and particle tracking velocimetry (PTV) have developed from two-dimensional two-component (2D2C) velocity vector measurements to 3D3C measurements. Rainbow particle tracking velocimetry is a low-cost 3D3C measurement technique adopting a single color camera. However, the vector acquisition rate is not so high. To increase the number of acquired vectors, this paper proposes a high probability and long-term tracking method. First, particles are tracked in a raw picture instead of in three-dimensional space. The tracking is aided by the color information. Second, a particle that temporarily cannot be tracked due to particle overlap is compensated for using the positional information at times before and after. The proposed method is demonstrated for flow under a rotating disk with different particle densities and velocities. The use of the proposed method improves the tracking rate, number of continuous tracking steps, and number of acquired velocity vectors. The method can be applied under the difficult conditions of high particle density (0.004 particles per pixel) and large particle movement (maximum of 60 pix).
Modelling the Flow in the Utah FORGE Wells Disrete Fracture Network
Authors: Aghajannezhad Pouria , Sellier Mathieu
Published: September 2024

The focus of this paper is the efficient numerical solution of the fluid flow in the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) reservoir. In this study, the public data available for Discrete Fracture Networks (DFN) around well 58-32 is used to represent the DFN. In this research, a novel computationally efficient method called Hele-Shaw (HS) approximation is used for modeling fluid flow in FORGE well. An analysis of the influence of fracture intensity in a network is carried out using the HS method. The HS method was validated by solving the full Navier–Stokes equations (NSE) for a network of eight fractures. A good agreement was observed between the evaluated results (average deviation of 0.76%).
Mediating Roles of Perceived Quality and Perceived Behaviour Control in Shaping Chinese Consumer’s Purchase Intention for Domestic Infant Milk Formula (IMF)
Authors: Zhang Jing , Waldron Scott , Dong Xiaoxia , Dai Xin
Published: September 2024

The 2008 melamine crisis led to widespread consumer distrust of Chinese domestic infant milk formula (IMF), which was substituted through a surge of imported products. Recent studies, however, suggest a revival in consumer confidence in Chinese domestic products and regulatory supervision. This coincides with a rise in consumer ethnocentrism and increased concern about foreign IMF, which arose during the COVID-19 pandemic. This study aims to investigate the multifaceted factors that influence consumers’ intention to purchase domestic IMF, using a structural equation model based on a survey of 563 online consumers. Our findings challenge conventional thinking that food safety governance, consumer ethnocentrism, and COVID-19 have no significant direct impact on IMF purchase decisions. Instead, consumer purchase intentions are driven more indirectly by mediating factors of perceived product quality and perceived behavioural control. The findings have significant implications for Chinese policymakers and industry stakeholders seeking to rebuild trust and strengthen the market position of domestic IMF in the post-melamine and post-pandemic era. By understanding the nuanced dynamics and consumer preferences in this market, international stakeholders can also develop more effective strategies to navigate and compete in the ever-evolving landscape of the Chinese IMF industry.