bluuebunny/crossref_metadata_2025 huggingface dataset:
Activating/Mobilizing Intersectional Assets: Racial Justice-Focused School Leadership Systems That Center Students of Color and Privilege Their Interests
Authors: Lee Ung-Sang Albert
Published: December 2024

Integrating Students of Color in school leadership offers ways to remediate the historical exclusion of Students of Color from schooling, develop asset-based educational practices for Students of Color, and offer rich developmental pathways for the students. Efforts to build more participatory leadership systems must consider how the unique assets that Students of Color bring to bear are positioned and leveraged within such leadership systems, the kinds of structures and practices that facilitate the meaningful participation of Students of Color in school leadership, and how the interests of Students of Color are privileged through their participation in school leadership. This paper examines three student cases that analyze the students’ participation in efforts aimed at centering students in conceptualizing, designing, and implementing digital media-integrated school practices. The analysis will show that a diverse set of student assets, such as their families’ political activism, career aspirations shaped by experiences with literature across borders, and experiences with navigating tensions across multiple axes of exclusion, helped the students navigate their emergent roles in school leadership. Such asset-based participation led to the activation/mobilization of such assets towards the students’ broader life and educational goals. Together, their experiences can help inform the ways we build asset-based, racial justice-focused school leadership systems that facilitate the meaningful participation of Students of Color.
Empowering Non-Specialist English Teachers: Self-Efficacy Enhancement Through Classroom English Proficiency and Collaborative Support
Authors: Matsumura Shoichi , Hinoki Yushi
Published: December 2024

The increase in the provision of English language teaching programs in primary school contexts in Asia has resulted in a concomitant increase in non-specialist teachers, often generalist homeroom teachers, to address the shortage. However, non-specialist teachers often lack the pedagogical training necessary for effective English instruction, which often negatively impacts their self-efficacy. This study was designed to examine the effects of a professional development workshop, aimed at improving “classroom English” proficiency, on these teachers’ self-efficacy. It also explored sources influencing self-efficacy during the in-class implementation of what they learned in the workshop. Quantitative results revealed that the immediate impact of the training was substantial, leading to a rapid increase in self-efficacy. However, this effect appeared to diminish after three months of teaching. Qualitative findings indicated that non-specialist teachers’ perceptions of capability were significantly influenced by collegial assurances and support from individuals who evaluated their progress and achievements. Notably, support from specialist teachers emerged as a critical factor in sustaining or diminishing the enhanced self-efficacy of non-specialist teachers. These findings highlight the importance of providing needs-based, continuous professional development opportunities and establishing robust peer-support systems within schools to ensure the effective translation of training outcomes into classroom practices.
S3D Approach: Incremental Professional Development for Fostering Small-Group Discourse
Authors: Quebec Fuentes Sarah
Published: December 2024

The value of discourse in the mathematics classroom is evident across standards, policy documents, and research. The quality of discourse is associated with students’ mathematical understanding and achievement. Productive mathematical discourse includes students providing explanations and critically listening to and evaluating the ideas of others. Such high-level discourse takes time to develop and is impacted by how teachers structure lessons and interact with students (e.g., talk moves). The present case study reports on an incremental professional development, S3D Approach, that guides teachers through a two-phase process to enhance small-group, student-to-student discourse. One middle school mathematics teacher implemented the incremental stages of the S3D Approach with support from a mathematics teacher educator, who conducted weekly observations and debrief meetings. Qualitative analyses revealed that, despite initial challenges, the S3D Approach became integrated into the teacher’s practice, enabling the teacher to identify and build upon incremental improvements in the small-group discourse. Overall, the findings demonstrate how through a reframing of starting points and the definition of success, incremental PD supports sustainable changes in a teacher’s practice and student engagement in productive mathematical discourse.
Calibration-Enhanced Multi-Awareness Network for Joint Classification of Hyperspectral and LiDAR Data
Authors: Zhang Quan , Cui Zheyuan , Wang Tianhang , Li Zhaoxin , Xia Yifan
Published: December 2024

Hyperspectral image (HSI) and light detection and ranging (LiDAR) data joint classification has been applied in the field of ground category recognition. However, existing methods still perform poorly in extracting high-dimensional features and elevation information, resulting in insufficient data classification accuracy. To address this challenge, we propose a novel and efficient Calibration-Enhanced Multi-Awareness Network (CEMA-Net), which exploits the joint spectral–spatial–elevation features in depth to realize the accurate identification of land cover categories. Specifically, we propose a novel multi-way feature retention (MFR) module that explores deep spectral–spatial–elevation semantic information in the data through multiple paths. In addition, we propose spectral–spatial-aware enhancement (SAE) and elevation-aware enhancement (EAE) modules, which effectively enhance the awareness of ground objects that are sensitive to spectral and elevation information. Furthermore, to address the significant representation disparities and spatial misalignments between multi-source features, we propose a spectral–spatial–elevation feature calibration fusion (SFCF) module to efficiently integrate complementary characteristics from heterogeneous features. It incorporates two key advantages: (1) efficient learning of discriminative features from multi-source data, and (2) adaptive calibration of spatial differences. Comparative experimental results on the MUUFL, Trento, and Augsburg datasets demonstrate that CEMA-Net outperforms existing state-of-the-art methods, achieving superior classification accuracy with better feature map precision and minimal noise.
Low-Complexity Model Predictive Control for Series-Winding PMSM with Extended Voltage Vectors
Authors: Hu Jinde , Fu Zhaoyang , Xu Rongwei , Jin Tian , Feng Zhengyang , Wang Sheng
Published: December 2024

This paper proposes a low-complexity model predictive current control (MPCC) strategy based on extended voltage vectors to enhance the computational efficiency and steady-state performance of three-phase series-winding permanent magnet synchronous motors (TPSW-PMSMs). Compared to conventional MPCC methods, this approach increases the number of candidate voltage vectors in the alpha–beta plane from 8 to 38, thereby achieving better steady-state performance. Specifically, the proposed method reduces the total harmonic distortion (THD) by 59%. To improve computational efficiency, a two-stage filtering strategy is employed, significantly reducing the computational burden. The number of voltage vectors traversed in one control period is reduced from 38 to a maximum of 4, achieving an 89% reduction in traversals. Additionally, to mitigate the impact of zero-sequence currents, zero-sequence current suppression is implemented within the control system for effective compensation. By combining low computational complexity, reliable steady-state performance, and real-time control capabilities, this strategy provides an efficient solution for TPSW-PMSM systems. Simulation results validate the effectiveness of the proposed method.
Energy Efficiency of Polish Farms Following EU Accession (2004–2021)
Authors: Wąs Adam , Tsybulska Julia , Sulewski Piotr , Krupin Vitaliy , Rawa Grzegorz , Skorokhod Iryna
Published: December 2024

Modern agriculture requires substantial energy inputs, a significant portion of which are derived from fossil fuels. In the interests of addressing global challenges, such as sustainable resource management and reducing greenhouse gas emissions, this study examines changes in energy efficiency within Polish agriculture following the country’s accession to the European Union. It emphasizes the impact of dynamic structural transformations on energy consumption patterns in the agricultural sector. The research, based on data from Statistics Poland and FADN (Farm Accountancy Data Network) covering the period 2004–2021, analyzes various farm types and their economic sizes. Key indicators include energy intensity in agricultural production, expressed as the ratio of energy consumption to production value, and the share of different energy carriers in total energy inputs. The results demonstrate an overall improvement in energy efficiency during the analyzed period, with energy intensity decreasing by an average of 40%. The most significant improvements were observed in large-scale farms. Additionally, there was a notable decline in the use of solid fuels, offset by increased reliance on diesel fuel and electricity. Despite these positive trends, challenges persist. Energy costs per unit of production value in Poland remain relatively high compared to other EU countries, driven by rapidly rising energy prices and the structure of Polish agriculture, which predominantly produces goods with relatively low added value. Furthermore, variations in energy consumption structures across production types highlight the importance of specialization in enhancing energy efficiency at the farm level.
Advanced Genetic Algorithms for Optimal Battery Siting: A Practical Methodology for Distribution System Operators
Authors: Ortiz Edward Alejandro , Tello-Maita Josimar , Celeita David , Marulanda Guerra Agustin
Published: December 2024

The growing integration of renewable energy sources and the electrification of multiple sectors have heightened the need for optimized planning and operation of modern electrical distribution systems. A critical challenge for distribution network operators is enhancing the resilience and reliability of their grids by identifying effective solutions. One promising approach to achieving this is through the deployment of battery energy storage systems, which can rapidly inject power to mitigate the impacts of network disturbances or outages. This study investigates the use of advanced genetic algorithms as a practical methodology for the optimal siting of batteries in modern distribution networks. By incorporating historical data on demand and network failures, the algorithm generates statistical models that inform the optimization process. The model integrates both the technical and economic aspects of battery systems to identify locations that minimize reliability indices such as SAIDI and SAIFI, while also reducing investment costs. Tested on a real distribution system comprising 1837 nodes, the proposed approach demonstrates the ability of genetic optimization to deliver efficient solutions compared with traditional methods, providing a high likelihood of identifying strategic battery locations that respond to variable demand, system failures, and technical constraints.
Heterojunction Technology vs. Passivated Emitter and Rear Contact Photovoltaic Panels: Evaluating Efficiency and Profitability Under Challenging Summer Conditions in Lisbon Using Extensive Field Data
Authors: Sapina André , Branco Paulo
Published: December 2024

Renewable energy is essential for reducing fossil fuel dependence and achieving carbon neutrality by 2050. This study compares the widely used passivated emitter and rear contact (PERC) cells with advanced heterojunction technology (HJT) cells. Conducted in Lisbon during August 2022, this research evaluates the energy yield of PV installations over 400 W under challenging summer conditions. HJT cells, which combine monocrystalline silicon and amorphous layers, showed a 1.88% higher efficiency and a 3% to 6% increase in energy yield compared to PERC cells. This study also examines the effects of irradiance and temperature on performance using experiment field data. HJT modules are ideal for limited space or power constraints, offering long-term profitability, while PERC modules are more cost-effective for budget-limited projects.
Enhanced Three-Phase Shunt Active Power Filter Utilizing an Adaptive Frequency Proportional-Integral–Resonant Controller and a Sensorless Voltage Method
Authors: Ghanayem Haneen , Alathamneh Mohammad , Yang Xingyu , Seo Sangwon , Nelms R. M.
Published: December 2024

This article introduces a frequency-adaptive control strategy for a three-phase shunt active power filter, aimed at improving energy efficiency and ensuring high power quality in consumer-oriented power systems. The proposed control system utilizes real-time frequency estimation to dynamically adjust the gain of a proportional-integral–resonant (PIR) controller, facilitating precise harmonic compensation under challenging unbalanced grid conditions, such as unbalanced three-phase loads, grid impedance variations, and diverse nonlinear loads like three-phase rectifiers and induction motors. These scenarios often increase total harmonic distortion (THD) at the point of common coupling (PCC), degrading the performance of connected loads and reducing the efficiency of induction motors. The PIR controller integrates both proportional-integral (PI) and proportional-resonant (PR) control features, achieving improved stability and reduced overshoot. A novel voltage sensorless control method is proposed, requiring only current measurements to determine reference currents for the inverter, thereby simplifying the implementation. Validation of the frequency adaptive control scheme through MATLAB/Simulink simulations and real-time experiments on a dSPACE (DS1202) platform demonstrates significant improvements in harmonic compensation, energy efficiency, and system stability across varying grid frequencies. This approach offers a robust consumer-oriented solution for managing power quality, positioning the SAPF as a key technology for advancing sustainable energy management in smart applications.
Comparison of the Heat Transfer Efficiency of Selected Counterflow Air-to-Air Heat Exchangers Under Unbalanced Flow Conditions
Authors: Kaminski Kazimierz , Znaczko Pawel , Kardas-Cinal Ewa , Chamier-Gliszczynski Norbert , Koscielny Krzysztof , Cur Krzysztof
Published: December 2024

This study investigates the thermal performance of various counterflow air-to-air heat exchangers under unbalanced flow conditions, aiming to enhance the efficiency of heat recovery systems. Mechanical ventilation with heat recovery is critical in energy-efficient buildings to reduce heat loss, which can reach up to 60% in air exchange processes. This research focuses on the effects of flow imbalance on the heat transfer efficiency of three specific heat exchangers: two commercially available models (Recair Sensitive RS160 and Core ERV366) and a custom 3D-printed prototype (GV PROTO). Experimental tests measured temperature efficiency under both balanced and unbalanced flow conditions, with results indicating that flow imbalance significantly impacts thermal efficiency. Among the exchangers, the RS160 displayed the highest temperature efficiency, maintaining performance better than the others as flow rates increased. The results of the study show that even small differences in the thermal efficiency of different heat exchangers under balanced airflow conditions transform into significant differences under unbalanced conditions. These findings contribute to a better understanding of how real-world ventilation imbalances affect heat exchanger performance, offering insights to optimize energy efficiency in ventilation systems.
A High-Precision Curvature Compensation Reference Circuit for a Cable Accessory Image Acquisition Device
Authors: Xiao Ning , Tian Yuewei , Peng Xiaosong , Wang Weijun , Zou Wenqiang , Yuan Chao , Zhou Qian
Published: December 2024

High-voltage cables are widely used in power transmission and distribution systems, and their accessories (such as connectors, terminals, and insulators) are key parts to ensure the safe and reliable operation of power systems. These accessories may be affected by factors such as temperature, humidity, and mechanical stress during long-term operation, resulting in performance degradation or failure. In high-voltage environments, performance monitoring of cable accessories is crucial. The reference voltage circuit can withstand the influence of temperature changes and power supply fluctuations, support accurate current and voltage measurement, and thus detect potential faults in time to ensure the safe and stable operation of the power system. However, the traditional reference voltage circuit has a low-temperature curvature loss, which results in an inaccurate reference voltage, resulting in equipment damage. Therefore, in order to solve the problem of curvature loss in this part, this paper proposes a curvature compensation circuit, which realizes a high-precision reference voltage circuit through a high-temperature curvature compensation circuit, thereby meeting the current reference voltage requirements for cable accessory monitoring.
Three-Dimensional Finite Element Method Modeling for the Improvement of the Design of an Electromechanical Device to Drive a Fan Shaft Balancing System
Authors: Lefik Marcin , Krygier Michał , Podsędkowski Leszek
Published: December 2024

This paper describes a solution to the problem of improving the design of an electromechanical device with two perpendicular axes of rotation. This device is part of the fan shaft balancing system’s drive system. The aim of this improvement was to obtain the highest possible value for the electromagnetic torque. A simplified three-dimensional model and the finite element method were used to solve the problem. The analysis showed that structures with better torque characteristics as a function of speed, especially for the fan rotational speed, were obtained. Measurements verified the results of these analyses.
Performance Analysis of a Compressor Rotor Dedicated to Low-Power Drive Systems
Authors: Kapela Natalia , Wyżkiewicz Karolina , Frąckowiak Andrzej
Published: December 2024

This study investigates the efficiency evaluation of a compressor rotor designed for drive units requiring compressors with a power demand of less than 30 kW. The primary aim of the research presented in this article is to assess the feasibility of utilizing axial compressors to maintain high efficiency across a broad range of rotor speeds. A critical challenge in the considered power range is the occurrence of low Reynolds numbers, specifically those below 250,000. This research seeks to identify the underlying causes of efficiency degradation at low Reynolds numbers and determine the rotor’s geometric parameters which most significantly influence the localized efficiency drop. Compressor efficiency was evaluated through numerical simulations. The numerical model was validated using experimental data and subjected to a grid independence study. Simulations were conducted for nine geometric configurations of the axial compressor rotor, with modifications to parameters such as the blade angle, blade thickness, blade solidity, and hub-to-tip ratio. For each configuration, a series of simulations was performed at rotor speeds ranging from 400 RPM to 2400 RPM. The simulation results indicated that the blade angle solidity was the most influential parameter affecting efficiency. A reduction in the blade angle led to approximately a 20% decrease in efficiency, primarily due to localized flow separation near the blade tip. Additionally, altering the number of blades caused a 20% efficiency reduction attributed to hub corner separation. The findings enabled the identification of optimal parameters, which will serve as a foundation for efficiency testing in the multistage configuration.
Machine-Learning-Driven Identification of Electrical Phases in Low-Sampling-Rate Consumer Data
Authors: Hangawatta Dilan C. , Gargoom Ameen , Kouzani Abbas Z.
Published: December 2024

Accurate electrical phase identification (PI) is essential for efficient grid management, yet existing research predominantly focuses on high-frequency smart meter data, not adequately addressing phase identification with low sampling rates using energy consumption data. This study addresses this gap by proposing a novel method that employs a fully connected neural network (FCNN) to predict household phases from energy consumption data. The research utilizes the IEEE European Low Voltage Testing Feeder dataset, which includes one-minute energy consumption readings for 55 households over a full day. The methodology involves data cleaning, preprocessing, and feature extraction through recursive feature elimination (RFE), along with splitting the data into training and testing sets. To enhance performance, training data are augmented using a generative adversarial network (GAN), achieving an accuracy of 91.81% via 10-fold cross-validation. Additional experiments assess the model’s performance across extended sampling intervals of 5, 10, 15, and 30 min. The proposed model demonstrates superior performance compared to existing classification, clustering, and AI methods, highlighting its robustness and adaptability to varying sampling durations and providing valuable insights for improving grid management strategies.
Deep Learning-Based Home Energy Management Incorporating Vehicle-to-Home and Home-to-Vehicle Technologies for Renewable Integration
Authors: Mahmoud Marwan , Ben Slama Sami
Published: December 2024

Smart cities embody a transformative approach to modernizing urban infrastructure and harness the power of deep learning (DL) and Vehicle-to-Home (V2H) technology to redefine home energy management. Neural network-based Q-learning algorithms optimize the scheduling of household appliances and the management of energy storage systems, including batteries, to maximize energy efficiency. Data preprocessing techniques, such as normalization, standardization, and missing value imputation, are applied to ensure that the data used for decision making are accurate and reliable. V2H technology allows for efficient energy exchange between electric vehicles (EVs) and homes, enabling EVs to act as both energy storage and supply sources, thus improving overall energy consumption and reducing reliance on the grid. Real-time data from photovoltaic (PV) systems are integrated, providing valuable inputs that further refine energy management decisions and align them with current solar energy availability. The system also incorporates battery storage (BS), which is critical in optimizing energy usage during peak demand periods and providing backup power during grid outages, enhancing energy reliability and sustainability. By utilizing data from a Tunisian weather database, smart cities significantly reduce electricity costs compared to traditional energy management methods, such as Dynamic Programming (DP), Rule-Based Systems, and Genetic Algorithms. The system’s performance is validated through robust AI models, performance metrics, and simulation scenarios, which test the system’s effectiveness under various energy demand patterns and changing weather conditions. These simulations demonstrate the system’s ability to adapt to different operational environments.
Implications of Large-Scale PV Integration on Grid Operation, Costs, and Emissions: Challenges and Proposed Solutions
Authors: Zubi Ghassan , Parag Yael , Wald Shlomo
Published: December 2024

This study examines integrating large-scale photovoltaic (PV) systems into the power grid to achieve a 30% PV share, addressing operational and economic challenges such as backup generation, storage, and grid stability. Applying an electricity dispatch model to the test case of Israel, it highlights significant impacts on fuel consumption, cost, and carbon emissions. Key findings include an 8% drop in the capacity factor of natural gas combined cycle (NGCC) plants, leading to increased starts, stops, and higher fuel consumption. Annual power generation will grow from 81 to 104 TWh, with PV generation increasing from 8.1 to 31.1 TWh. Open cycle gas turbine (OCGT) output will grow from 2.4 to 10.2 TWh, increasing OCGT’s market share from 3% to 10%. NGCC operations’ intermittency will double annual starts from 3721 to 7793, causing a 1.1% efficiency drop and a 2% rise in natural gas consumption. 3.45 GWh of Li-ion battery capacity will be needed. The LCoE is expected to increase from 6.6 to 7.0 c$/kWh without a carbon tax and from 8.7 to 8.8 c$/kWh with a $40/t carbon tax. Annual emissions will rise from 41.8 to 46.5 Mt. This study provides insights for sunny Mediterranean countries with similar renewable energy goals.
Longitudinal Anatomical Variation of Wood in Stem and Branch of Six Forest Species from the Amazon Region and Its Relationship with Wood Specific Gravity
Authors: Martínez-Guevara Carolina , Pulido-Rodríguez Nancy , Giraldo Benavides Bernardo , Barrera García Jaime
Published: December 2024

Wood functional traits provide information for the management and sustainable use of species. This study evaluated the wood specific gravity (SG) and nine anatomical characteristics of wood in six sections (three levels of stem height and three orders of the branch) in six species of bioeconomic importance for the Colombian Amazon region: Jacaranda copaia, Virola elongata, Virola peruviana, Cedrelinga cateniformis, Erisma uncinatum, and Cabari macrocarpa. The results showed that low- and medium-SG species have branches with equal or greater SG than the stem. In this group, Erisma uncinatum and Virola peruviana showed no differences between their sections. In contrast, for high-SG species such as Cabari macrocarpa, the relationship was inverse. Fiber thickness correlated mainly with SG, with no differences between sections, except in Cabari macrocarpa. Fiber length decreased in all species in the stem-to-branch direction. The other characteristics varied, suggesting an optimization in the effort of water transport along the tree. These findings infer a potential sustainable use of branches of tree species with low biomechanical variation, such as Erisma uncinatum and Virola peruviana. They also demonstrate the hydraulic and mechanical adaptability of these species, which is relevant when facing climate change scenarios.
Evaluating Mechanical Properties and Suitability of Aspen (Populus tremula L.) Load Bearing Replacements in Historical Constructions
Authors: Herdová Barbora , Lagaňa Rastislav , Štefančin Lukáš , Schmidtová Jarmila
Published: December 2024

The replacement of historical load-bearing wooden elements made from not commonly used species such as Populus tremula L. presents significant challenges. As these species are seldomly used in modern construction, a knowledge gap exists regarding their implementation in accordance with current building codes. This study investigates the mechanical properties of European aspen (Populus tremula L.) from central Slovakia as a potential replacement for historical structures. Notably, poplar species, including European aspen, have historically been utilized for construction across various landscapes in Europe. We conducted experimental testing on visually graded aspen timber to determine the dynamic modulus of elasticity (MOEdyn,ultr), modulus of elasticity (MOE), modulus of rupture (MOR), and density. The results were analyzed and compared to established standards for structural timber. Notably, the 5th percentileof the strength distribution (f0.05) was determined to be 28.78 MPa, while the characteristic strength (fk) was 26.23 MPa, and the modulus of elasticity (Eg12) was 13.60 MPa. The correlation between MOR and dynamic MOE facilitated the determination of MOR by non-destructive testing (NDT) using the Sylvatest Duo®. This simple linear model could grade 49% of boards into the higher strength class C30. The additional parameters and their interactions in multiregresssion models improved the predictability of the bending strength of aspen. The advanced model graded 68% of boards into C30. These characteristics, along with aspen’s growth potential, make it a promising candidate for replacing damaged structural elements in historical constructions. Our findings contribute to the understanding of the potential of European aspen as a structural timber, highlighting its viability as a fast-growing hardwood species.
Optimization of Key Stand Structural Factors to Enhance Water-Holding Function, Soil Conservation, and Carbon Sequestration in Schima superba Forests: Insights from Subtropical Dongbai Mountain
Authors: Wang Zhongxu , Han Yini , Yuan Caiyan , Li Xueqin , Qian Penghong , Jin Songheng
Published: December 2024

Revealing the interactions between stand structure factors and ecosystem functions is crucial for enhancing forest soil and water conservation, as well as carbon storage. However, the optimal stand structure configuration for achieving superior ecological functions remains unclear, particularly in complex subtropical evergreen broad-leaved forests. Using Schima superba Gardn. et Champ. forests in Dongbai Mountain as a case study, this study investigated the effects of seven stand structure factors—stand density, canopy density, uniform angle index, and mixing degree—on three key ecosystem functions, water-holding function, soil improvement function, and carbon sequestration. Redundancy analysis (RDA) and structural equation modeling (SEM) were employed to quantify these relationships. The results identified stand density as the most influential factor, directly or indirectly affecting ecosystem functions by regulating other structural attributes. Optimal structural configurations were determined, including stand densities of 1228, 1532, and 1675 plants·hm−2 for maximizing water-holding function, soil improvement function, and carbon sequestration, respectively. Recommendations emphasize adjusting stand density, canopy density, uniform angle index, and mixing degree according to site-specific conditions. Practical strategies, such as replanting, intercropping, and introducing functionally complementary species, should aim to enrich vertical structure, maintain species randomness, and avoid dominance by a single species or excessive density. These findings offer actionable insights for improving the ecological functions of subtropical forests and have broader implications for sustainable forestry management, advancing regional carbon neutrality, and addressing global ecological challenges.
Detection of Emerald Ash Borer (Coleoptera: Buprestidae) in Ash (Fraxinus spp.) Crowns in the Southern United States: Comparing Panel Trap Color, Placement, and Lure
Authors: Walters Benjamin , Bataineh Mohammad , Clarke Stephen , Johnson Wood , Bruce William
Published: December 2024

The emerald ash borer (EAB), Agrilus planipennis Fairmaire, is an invasive forest pest that is causing a rapid decline in ash (Fraxinus spp.). As EABs spread across North America to 35 U.S. states and 5 Canadian provinces, detection of the pest has proven difficult, especially at low population density sites. Panel traps have been commonly used in detection and monitoring of EAB populations. Over two sampling periods from 2016 through 2019, adult catches and detection rates were compared among four combinations of panel trap color, lure, and crown placement in southern Arkansas, northern Louisiana, and eastern Texas. The four combinations were as follows: (1) dark purple baited with (Z)-3-hexenol alone in the mid–upper crown; (2) light green with (Z)-3-hexenol plus (3Z)-lactone in the mid–upper crown; (3) dark purple with (Z)-3-hexenol in the lower crown; and (4) dark purple with (Z)-3-hexenol plus (3Z)-lactone in the lower crown. Mid–upper tree crown placement, ~13 m, of panel traps were more effective for EAB detection and adult capture, especially of males. The sex pheromone (3Z)-lactone deterred females but attracted males, while (Z)-3-hexenol attracted females. The green panel trap with both lures and mid–upper crown placement did not drastically increase male catches, contrary to previous studies at low EAB densities. The use of (3Z)-lactone on dark purple traps at low crown placements, such as those used in the National Survey Program, is not recommended for EAB detection due to its repellent effect on EAB females.
A Blockchain-Based Protocol for Fair Delivery for Receipts
Authors: Hinarejos M. Francisca , Ferrer-Gomila Josep-Lluis , Isern-Deyà Andreu-Pere , Chévez-Alvarado Gerardo-Francisco
Published: December 2024

Message exchange for acknowledgment of receipt (e.g., for services that provide recipients with certain documents, such as sanctions, summonses, or requirements, which are often sent by public administrations) has traditionally been provided through protocols based on the use of trusted third parties (TTPs). More recently, solutions have been proposed that totally or partially replace the TTP with a blockchain. However, an analysis of these proposals reveals that they have one or more of the following drawbacks: failure to meet confidentiality requirements, the use of TTPs, and susceptibility to attacks that make them unfair. In this paper, we present a method of providing fair delivery for receipts based on a blockchain that does not suffer from the above disadvantages: it is fair and confidential and does not use a TTP. In addition, we demonstrate the feasibility of the protocol through a cost analysis and a proof-of-concept implementation, showing that our solution is more economical than existing solutions, and can be considered cost-effective even under low time requirements.
Evaluation of Alpaca Yarns Dyed with Buddleja Coriaceous Dye and Metallic Mordants
Authors: Quispe-Quispe Arturo , Lozano Franklin , Pinche-Gonzales Luz María , Vilcanqui-Perez Fulgencio
Published: December 2024

The objective of this research was to evaluate the effect of dye obtained from Buddleja coriacea and metallic mordants on the chromatic properties, textile characteristics, spectral profiles, and color stability in alpaca fibers. The dye extraction technique involved boiling in an aqueous solution, followed by filtration. Subsequently, alpaca yarns were dyed using the resulting extract following a standard protocol. The applied mordants included sodium sulfate (Na2SO4), aluminum sulfate and potassium dodecahydrate (KAl(SO4)2·12H2O), and oxalic acid (C2H2O4). Spectroscopy UV-Vis and FTIR spectrophotometry methods were used for the characterization of the dyed samples and analysis of the dye during the dyeing process. The findings revealed the formation of four distinct color tones. Additionally, it was determined that the mordants influenced the chromatic properties of the fibers dyed with Buddleja coriacea extract without modifying their textile characteristics. The identified spectral bands corresponded to keratin, the structural protein of the fibers. Changes in the intensity of these spectral bands were observed in the dyed samples, attributable to the presence of different mordants. Wet rub fastness was found to be inferior to dry rub fastness, which has implications for textile maintenance. In conclusion, Buddleja coriacea flowers provide an effective yellow dye, and when combined with various mordants, they allow for a variety of shades and hues in alpaca fiber yarns.
Numerical Study on the Combustion and Emissions Characteristics of Liquid Ammonia Spray Ignited by Dimethyl Ether Spray
Authors: Leng Yupeng , Dai Liming , Wang Qian , Lu Jiayu , Yu Ouqing , Simms Nigel John
Published: December 2024

Ammonia has attracted considerable attention as a zero-carbon fuel for decarbonizing energy-intensive industries. However, its low reactivity and narrow flammability limit efficient ignition and efficient combustion. By using CONVERGR software, this study numerically investigates the ignition and combustion characteristics of liquid ammonia spray ignited by dimethyl ether spray in a constant-volume chamber at an ambient temperature of 900 K. Critical parameters, including injection angles (90°–150°), liquid ammonia injection pressures (60–90 MPa), and ambient pressures (2.8–5.8 MPa), were systematically analyzed to evaluate their effects on ignition conditions and emissions. Results indicate that increasing the injection angle improves mixing between liquid ammonia and dimethyl ether sprays, enhancing combustion efficiency and achieving a maximum efficiency of 92.47% at 120°. Excessively large angles cause incomplete combustion or misfire. Higher liquid ammonia injection pressures improve atomization and promote earlier interactions between the sprays but reduce combustion efficiency, decreasing by approximately 2% as injection pressure increases from 60 MPa to 90 MPa. Higher ambient pressures improve combustion stability but decrease ammonia combustion efficiency. Post-combustion NO emissions at 5.8 MPa are reduced by 60.48% compared to 3.8 MPa. The formation of NO is strongly correlated with the combustion efficiency of liquid ammonia. A higher combustion rate of liquid ammonia tends to result in elevated NO. Based on these findings, an injection angle of 120°, an NH3 injection pressure of 75 MPa, and an ambient pressure of 3.8 MPa are recommended to optimize combustion efficiency.
Reduced Numbers of Returning Atlantic Salmon (Salmo salar) and Thiamine Deficiency Are Both Associated with the Consumption of High-Lipid Prey Fish
Authors: Keinänen Marja , Raitaniemi Jari , Pönni Jukka , Ritvanen Tiina , Myllylä Timo , Vuorinen Pekka J.
Published: December 2024

In 2023, exceptionally few salmon (Salmo salar) ascended from the Baltic Sea to spawn in the Rivers Tornionjoki and Simojoki, regardless of the proper number of smolts descending to the sea in preceding years. We investigated how the numbers of age-0 and young herring (Clupea harengus) and sprat (Sprattus sprattus), which are the principal prey species of salmon in the Baltic Proper, the main feeding area of these salmon, as well as the amount of lipid obtained from them and their protein-to-lipid ratio, correlated with the number of returning salmon and the thiamine (vitamin B1) status of spawning salmon. The fewer the 0-year-old herring were and the more abundant were the youngish sprat in the Baltic Proper when the post-smolts arrived there, and the greater the lipid content and lower the protein-to-lipid ratio of the prey fish, the fewer salmon returned to the Rivers Tornionjoki and Simojoki to spawn two years later. The number of returning salmon was lowest with a high ratio of youngish sprat, 1–3 years old, regarding the River Tornionjoki and 1–2 years old regarding the River Simojoki post-smolts, to 0-year-old herring, which were of a suitable size to be the prey for the post-smolts upon their arrival in the Baltic Proper. In 2021, the ratios were lowest due to the record-low number of 0-year-old herring. The poor thiamine status of spawning salmon was also associated with the high lipid content of available prey fish and with the abundance of youngish sprat, which have twice the lipid content of age-0 herring. Our findings parallel the observations in the early 1990s when post-smolt survival declined concurrently with the outbreak of thiamine deficiency, M74. We conclude that consuming high-lipid marine fish reduces the survival of post-smolts and, thus, the number of returning salmon, in addition to causing thiamine deficiency.
Improved Functionality, Quality, and Shelf Life of Merguez-Type Camel Sausage Fortified with Spirulina as a Natural Ingredient
Authors: Djenane Djamel , Khaled Boumediène Méghit , Ben Miri Yamina , Metahri Mohammed Said , Montañés Luis , Aider Mohammed , Ariño Agustín
Published: December 2024

The objective of the present work was to examine the effect of incorporating spirulina powder (SP) in merguez-type sausages made exclusively with camel meat, as well as to evaluate its physicochemical, microbiological, and sensory quality attributes and its prebiotic potential. The final purpose was to offer an innovative meat product to increase camel meat consumption. Several innovative fresh sausage formulations were developed using SP (00, 100, 250, and 500 mg/kg) and stored under vacuum conditions with refrigeration at 1 ± 1 °C for 35 days. A control group of camel sausage without SP was also stored overwrapped (OW) under aerobic conditions, to serve as the negative control. The addition of SP to the vacuum-packed camel sausages extended their shelf life by 20 to 35 days compared to the control group, which was completely spoiled by the fifth day of storage. These results were more pronounced the higher the percentage of SP incorporated into the camel sausage formulation, as indicated by the following parameters: 2-thiobarbituric acid-reactive substances TBARS (1.46 vs. 2.89 mg MDA/kg), CIE a* (14.65 vs. 10.12), total volatile basic nitrogen TVB-N (13.02 vs. 15.09 mg/kg), total psychrotrophic bacteria TPB (5.71 vs. 6.34 log CFU/g), and overall acceptability score (3.17 vs. 2.5). The study of prebiotic potential suggested that the addition of SP to camel sausages promoted the growth of probiotic strains, which in turn were able to inhibit the growth of pathogenic microorganisms such as S. aureus and E. coli O157:H7. In conclusion, this study highlighted how SP, as a clean label ingredient, based on its rich composition and its antioxidant, antibacterial, and prebiotic effects, may represent a source of beneficial substances for human health and offer an alternative approach to producing a new traditional merguez-type sausage with improved acceptance.
Pore Structure and Fractal Characteristics of Inter-Layer Sandstone in Marine–Continental Transitional Shale: A Case Study of the Upper Permian Longtan Formation in Southern Sichuan Basin, South China
Authors: Wang Jianguo , Zhang Jizhen , Xiao Xiao , Chen Ya’na , Han Denglin
Published: December 2024

With the evolution of unconventional oil and gas exploration concepts from source rocks and reservoirs to carrier beds, the inter-layer sandstone carrier bed within marine–continental transitional shale strata has emerged as a significant target for oil and gas exploration. The inter-layer sandstone is closely associated with the source rock and differs from conventional tight sandstone in terms of sedimentary environment, matrix composition, and the characteristics of reservoir microscopic pore development. Preliminary exploration achievements display that the inter-layer sandstone is plentiful in gas content and holds promising prospects for exploration and development. Consequently, it is essential to investigate the gas-rich accumulation theory specific to the inter-layer sandstone reservoir in transitional facies. Pore development characteristics and heterogeneity are crucial aspects of oil and gas accumulation research, as they influence reservoir seepage performance and capacity. This paper employs total organic carbon analysis, X-ray diffraction, rock thin section examination, field emission scanning electron microscopy, physical analysis, high-pressure mercury intrusion analysis, gas adsorption experiments, and fractal theory to explore the reservoir development characteristics of the sandstone samples from the Upper Permian marine–continental transitional facies Longtan Formation in the southern Sichuan Basin. It also attempts to combine high-pressure mercury intrusion analysis and gas adsorption experiments to describe the structural and fractal characteristics of pores at different scales in a segmented manner. The findings reveal that the sandstone type of the Longtan Formation is mainly lithic sandstone. The pore size distribution of the sandstone primarily falls below 30 nm and above 1000 nm, with the main pore types being inter-granular pores and micro-fractures in clay minerals. The pore volume and specific surface area are largely attributed to the micropores and mesopores of clay minerals. The pore morphology is complex, exhibiting strong heterogeneity, predominantly characterized by slit-like and ink bottle-like features. Notably, there are discernible differences in reservoir structural characteristics and homogeneity between muddy sandstone and non-muddy sandstone. The pore morphology is complex, exhibiting strong heterogeneity, predominantly characterized by slit-like and ink bottle-like features. Notably, there are discernible differences in reservoir structural characteristics and homogeneity between muddy sandstone and non-muddy sandstone.
Analysis of Nanostructures and Wettability of Marine Shale in Southern China, Based on Different Fractal Models
Authors: Wang Yang , Zhong Baoyuan , Zhang Yunsheng , Zhu Yanming , Wang Meng
Published: December 2024

The wetting behavior of shale oil and gas on shale surfaces is determined by the interplay of organic matter (OM), mineral composition, and the intricate pore network structure of the shale. In this paper, the sensitivity responses of the Frenkel–Halsey–Hill (FHH), Neimark (NM), and Wang–Li (WL) fractal models to marine shale with varying material components are analyzed, based on liquid nitrogen adsorption experiments and fractal theory. The wettability evolution model of shale with different maturity stages is established to reveal the heterogeneity characteristics of wettability in shale with complex pore structures. Results show that the NM and WL models offer distinct advantages in evaluating the reservoir structure of shale oil and gas resources. The existence of large-diameter pores is conducive to the homogeneous development of the pore structure. The coupling relationship between pore volume, pore size and pore specific surface affects the fractal characteristics of the pore structure. For highly overmature shale, with an increase in fractal dimension, the wettability of shale changes from neutral-wet to water-wet. For ultramature shale, the higher heterogeneity of the pore structure leads to larger contact angles, causing the wettability to transition gradually from water-wet to oil-wet. In addition, the sensitivity analysis of wettability to fractal structure parameters is examined from the perspective of OM maturation and evolution.
Particle Flow Simulation of the Mechanical Properties and Fracture Behavior of Multi-Mineral Rock Models with Different Fractal Dimensions
Authors: Shi Run , Xiao Huaiguang
Published: December 2024

To study the effects of rock models with different fractal dimensions on their mechanical properties and fracture behavior, three representative numerical rock models, including the digital texture model, the Voronoi polygon model, and the Weibull distribution model, are established in this paper. These models are used to simulate the structure of multi-mineral rocks and to investigate the influence of fractal dimensions on the mechanical properties and fracture behavior of rocks. Uniaxial compression numerical tests are carried out on 2D and 3D intact rocks under different fractal dimensions using the particle flow simulation method. The relationship between fractal dimensions and uniaxial compression strength and fracture behavior was analyzed. The results show that the fractal dimension of the Weibull distribution model is the largest, followed by the digital texture model, and the fractal dimension of the Voronoi polygon model is the smallest. With the increase in fractal dimension, the uniaxial compressive strength of intact rocks increases significantly, and their relationship is approximately linear. The influence of fractal dimension on rock strength shows a similar trend in both the 2D and 3D models. This study provides a new perspective for the application of fractal dimensions in multi-mineral rock models.