bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Regeneration from Leaf Explants of Helianthus verticillatus, a Critically Endangered Sunflower
Authors: Nowakowska Marzena , Pavlovic Zaklina , Nowicki Marcin , Boggess Sarah L. , Trigiano Robert N.
Published: January 2024

Helianthus verticillatus (Asteraceae), a whorled sunflower, is a perennial species restricted to a few locations in the southeastern United States and is now considered endangered. Therefore, restoring and protecting H. verticillatus as a species is a priority. This study introduces a highly efficient in vitro adventitious plant regeneration system from leaf explants, utilizing five diverse specimens of H. verticillatus, each representing distinct genotypes with phenotypic variations in leaf and stem morphology. Key factors influencing in vitro morphogenesis, including genetic constitution, explant source, and plant growth regulators (PGRs), were identified. The study revealed a remarkably strong genotype-dependent impact on the regeneration efficiency of the investigated H. verticillatus genotypes, ranging from a lack of regeneration to highly effective regeneration. The selection of two genotypes with varying regeneration abilities provides valuable models for genetic analyses, offering insights into factors influencing the regeneration potential of this endangered species. Optimum adventitious shoot regeneration results were achieved using Murashige and Skoog basal media (MS) supplemented with 8.8 µM N6-benzyladenine (BA) and 1.08 µM α-naphthalene acetic acid (NAA). This combination yielded the highest adventitious shoot production. Subsequent successful rooting on ½ MS medium without PGRs further solidified the efficiency of the developed protocol. Regenerated plantlets, demonstrating robust shoots and roots, were successfully acclimatized to greenhouse conditions with a 95% survival rate. The protocol developed in this study is the first such report for this endangered species and is expected to contribute to future genetic manipulation and modification studies.
Quality Characteristics of Twelve Advanced Lines of Avena magna ssp. domestica Grown in Three Contrasting Locations in Morocco
Authors: Thiam El hadji , Dunn Michael , Jackson Eric W. , Jellen Eric N. , Nelson Mark , Rogers Will , Wallace Carol , Ahlborn Gene , Mounir Majid , Yakovac Teresa , Morris Shane , Benlhabib Ouafae
Published: January 2024

The popularity of oats (Avena sativa) continues to increase in the cereal market due to their health benefits. The recent domestication of Avena magna, a Moroccan oat, presents an opportunity to enhance these benefits due to their higher nutritional composition. As the impact of microclimates on A. magna grain composition has not been explored, this study evaluates twelve A. magna ssp. domestica lines across three Moroccan locations, providing new data into microclimate effects on key grain characteristics. Significant variability is observed among lines and sites for nutrients, with mean protein, fat, and dietary fiber contents at 23.1%, 8.38%, and 7.23%, respectively. High protein levels, reaching 27.1% in Alnif and 26.5% in El Kbab, surpass the ‘Avery’ control (21.7% and 24.2%) in these environments. Groats from Bouchane exhibited elevated fat and fiber contents (10.2% and 9.94%) compared to the control (8.83% and 7.36%). While β-glucan levels remain consistent at 2.53%, a negative correlation between protein content, fat, and starch was observed. A. magna lines exhibited higher levels of iron (7.50 × 10−3 g/100 g DM) and zinc (3.40 × 10−3 g/100 g DM) compared to other cereals. Environmental conditions significantly influence grain quality, with El Kbab yielding higher protein and ash contents, as well as Bouchane having increased fat, fiber, and starch. Stability analysis indicates that fat content was more influenced by the environment, while 25% of protein variability is influenced by genetics. Lines AT3, AT5, AT6, AT13, and AT15 consistently exceeds both the mean for protein and fiber across all sites, emphasizing their potential nutritional value. This study highlights the potential of A. magna ssp. domestica to address nutritional insecurity, particularly for protein, iron, and zinc in domestic settings.
A Novel and Green Method for Preparing Highly Conductive PEDOT:PSS Films for Thermoelectric Energy Harvesting
Authors: Liu Fuwei , Gao Luyao , Duan Jiajia , Li Fuqun , Li Jingxian , Ge Hongbing , Cai Zhiwei , Li Huiying , Wang Mengke , Lv Ruotong , Li Minrui
Published: January 2024

As a π-conjugated conductive polymer, poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is recognized as a promising environmentally friendly thermoelectric material. However, its low conductivity has limited applications in the thermoelectric field. Although thermoelectric efficiency can be significantly enhanced through post-treatment doping, these processes often involve environmentally harmful organic solvents or reagents. In this study, a novel and environmentally benign method using purified water (including room temperature water and subsequent warm water) to treat PEDOT:PSS film has been developed, resulting in improved thermoelectric performance. The morphology data, chemical composition, molecular structure, and thermoelectric performance of the films before and after treatment were characterized and analyzed using a scanning electron microscope (SEM), Raman spectrum, XRD pattern, X-ray photoelectron spectroscopy (XPS), and a thin film thermoelectric measurement system. The results demonstrate that the water treatment effectively removes nonconductive PSS from PEDOT:PSS composites, significantly enhancing their conductivity. Treated films exhibit improved thermoelectric properties, particularly those treated only 15 times with room temperature water, achieving a high electrical conductivity of 62.91 S/cm, a Seebeck coefficient of 14.53 μV K−1, and an optimal power factor of 1.3282 µW·m–1·K–2. In addition, the subsequent warm water treatment can further enhance the thermoelectric properties of the film sample. The underlying mechanism of these improvements is also discussed.
Research on an Intelligent Identification Method for Wind Turbine Blade Damage Based on CBAM-BiFPN-YOLOV8
Authors: Yu Hang , Wang Jianguo , Han Yaxiong , Fan Bin , Zhang Chao
Published: January 2024

To address challenges in the detection of wind turbine blade damage images, characterized by complex backgrounds and multiscale feature distribution, we propose a method based on an enhanced YOLOV8 model. Our approach focuses on three key aspects: First, we enhance the extraction of small target features by integrating the CBAM attention mechanism into the backbone network. Second, the feature fusion process is refined using the Weighted Bidirectional Feature Pyramid Network (BiFPN) to replace the path aggregation network (PANet). This modification prioritizes small target features within the deep features and facilitates the fusion of multiscale features. Lastly, we improve the loss function from CIoU to EIoU, enhancing sensitivity to small targets and the perturbation resistance of bounding boxes, thereby reducing the gap between computed predictions and real values. Experimental results demonstrate that compared with the YOLOV8 model, the CBAM-BiFPN-YOLOV8 model exhibits improvements of 1.6%, 1.0%, 1.4%, and 1.1% in precision rate, recall rate, mAP@0.5, and mAP@0.5:.95, respectively. This enhanced model achieves substantial performance improvements comprehensively, demonstrating the feasibility and effectiveness of our proposed enhancements at a lower computational cost.
Predictive Quality Analytics of Surface Roughness in Turning Operation Using Polynomial and Artificial Neural Network Models
Authors: Bober Peter , Zgodavová Kristína , Čička Miroslav , Mihaliková Mária , Brindza Jozef
Published: January 2024

The variability of the material properties of steel from different suppliers causes problems in achieving the required surface quality after turning. Therefore, the manufacturer needs to estimate the resulting quality before starting production, especially if it is an expensive, small-batch production from stainless steel. Predictive models will make it possible to estimate the surface roughness from the mechanical properties of steel and thus support decision making about supplier selection or acceptance of a material supply. This research presents a step-by-step decision-making procedure, which enables the trained staff to make quick decisions based on commonly available information in the Mill Test Certificate (MTC). A new multivariate second-order polynomial model and feedforward backpropagation artificial neural network (ANN) models have been developed using input variables from the MTC: Tensile Strength, Yield Strength, Elongation, and Hardness. Models were used to enhance the methodological robustness in formulating the decision if the predicted surface roughness is outside the required range, even before accepting the delivery. Both models can accurately predict surface roughness, while the ANN model is more accurate than the polynomial model; however, the predictive model is sensitive to the accuracy of the input data, and the model’s prediction is valid only under precisely defined conditions.
Model Based Optimization of Energy Consumption in Milk Evaporators
Authors: Tsochatzidi Artemis , Arvanitidis Achilleas L. , Georgiadis Michael C.
Published: January 2024

This work explores five falling film evaporator (FFE) simulation approaches combined with energy consumption minimization strategies, namely Mechanical Vapor Recompression and Thermal Vapor Recompression (MVR and TVR, respectively). Global system analysis and advanced dynamic optimization strategies are then investigated to minimize steam consumption, the cost of steam, and the total annualized cost and to maximize product yield. The results indicate that higher TVR discharge pressures, or MVR compression ratios, along with higher feed temperatures, enhance evaporation but increase operational costs. The most economical option includes three evaporator effects with TVR to achieve 50% product dry mass content. However, for a 35% dry mass content, MVR becomes cost-effective with an 11% reduction in unit electricity prices or a simultaneous 7% drop in electricity prices and a 5% increase in gas-based steam prices. Furthermore, switching from milk powder production to milk concentrates leads to an annual cost reduction ranging from 10.8 to 44%. Additionally, a forecasted 20% (or more) reduction in biomass-based steam cost can lead to lower annual expenditure compared with the nominal NG-based steam case. Regarding the total annualized cost, for a new plant design, optimization strategies lead to a 9–45% reduction in the total cost depending on the case under consideration.
Control Approach of Grid-Connected PV Inverter under Unbalanced Grid Conditions
Authors: Alharbi Mohammed
Published: January 2024

In grid-connected photovoltaic (PV) systems, power quality and voltage control are necessary, particularly under unbalanced grid conditions. These conditions frequently lead to double-line frequency power oscillations, which worsen Direct Current (DC)-link voltage ripples and stress DC-link capacitors. The well-known dq frame vector control technique, which is effective under normal conditions, struggles with oscillatory component management in unbalanced grid conditions. To address this issue, this paper presents an advanced control approach designed for grid-connected PV inverters. The proposed approach is effective at reducing oscillations in the DC-link voltage at double the grid frequency, thereby enhancing system stability and component longevity. This method introduces a feedback control method designed to regulate oscillatory components that appeared within the dq frame and suppress the DC-link voltage oscillations under imbalance conditions, including single line-to-ground (SLG) faults. Additionally, the control scheme incorporates a maximum power point tracking (MPPT) controller to optimize PV efficiency. Comprehensive simulations demonstrate the effectiveness of this method in maintaining sinusoidal current injections and stabilizing DC-link voltage during unbalanced grid conditions. Simulation results show that the control scheme effectively stabilizes DC-link voltage, maintains balanced grid current, and ensures constant active power under various conditions, including SLG faults and solar irradiance changes.
Numerical Reservoir Simulation of Supercritical Multi-Source and Multi-Component Steam Injection for Offshore Heavy Oil Development
Authors: Fu Qiang , Zhu Zhouyuan , Li Junjian , Jiao Hongmei , Wang Shuoliang , Wen Huiyun , Liu Yongfei
Published: January 2024

We present the workflow for numerical reservoir simulation of supercritical multi-source and multi-component steam injection for offshore heavy oil development. We have developed unique techniques in a commercial reservoir simulator to implement the thermal properties of supercritical multi-source and multi-component steam, the pyrolysis chemical reactions, the temperature-dependent relative permeability, and the process of partially dissolving the sandstone rock to enhance the matrix permeability in a commercial reservoir simulator. Simulations are conducted on the type pattern reservoir model, which represents one of the heavy oil fields in CNOOC’s Bohai Bay oil field. Simulation input parameters are calibrated based on laboratory experiments conducted for supercritical multi-source and multi-component steam injection. Simulation results have shown clear improvements in injecting supercritical multi-source and multi-component steam in offshore heavy oil reservoirs compared to the normal steam injection process using subcritical steam. This serves as a workflow for implementing a numerical simulation of the novel supercritical multi-source and multi-component steam injection recovery process.
Optimization Strategy for Shared Energy Storage Operators-Multiple Microgrids with Hybrid Game-Theoretic Energy Trading
Authors: Chen Yi , He Shan , Wang Weiqing , Yuan Zhi , Cheng Jing , Cheng Zhijiang , Fan Xiaochao
Published: January 2024

To address the issue of low utilization rates, constrained operational modes, and the underutilization of flexible energy storage resources at the end-user level, this research paper introduces a collaborative operational approach for shared energy storage operators in a multiple microgrids (ESO-MGs) system. This approach takes into account the relation of electricity generated by MGs and the integration of diverse energy storage resources managed by ESO. A hybrid game-theoretic energy trading strategy is employed to address the challenges associated with energy trading and revenue distribution in this joint operational mode. Firstly, a multi-objective master–slave game optimization model is developed with the objective of maximizing the revenue earned by shared energy storage operators while simultaneously minimizing the operational costs of multiple microgrids. Secondly, acknowledging the peer-to-peer (P2P) energy sharing dynamics inherent in the multiple microgrid system, a non-co-operative game model is formulated. This model seeks to establish a multi-microgrid Nash equilibrium and equitable income allocation. Finally, leveraging the Karush–Kuhn–Tucker (KKT) conditions and drawing upon the principles of strong duality theory, precise dimensionality reduction is executed on the master–slave game model. The non-co-operative income is iteratively determined using the alternating direction multiplier algorithm. The empirical findings of this study indicate that the integration of electric vehicle clusters contributes to flexible storage resources for shared energy storage operators. Moreover, the proposed hybrid game optimization strategy enhances the overall benefits for shared energy storage operators and multiple microgrids, thereby affirming the economic viability and reliability of this innovative strategy.
Foregrounding African Ontology/Epistemology: A Reading of Deuteronomy 23:3 and Ruth 4:18–22 Considering the Nature of God
Authors: Cezula Ntozakhe Simon
Published: January 2024

Deuteronomy 23:3, says: “No … Moabite may enter the assembly of the Lord”. This verse is motivated by a discriminatory tendency embedded in the ontology of the Deuteronomist. Interestingly, Deuteronomy 23:3 was used by Ezra-Nehemiah to discriminate against the “Moabites” during the Second Temple. Such ontology is countered by the author of Ruth in the narrative of Ruth during the Second Temple. This demonstrates an ontological “war” within the Bible itself. The primary contestation lies in whether God is exclusive or inclusive. This development necessitates a hermeneutics of suspicion. In the course of history, the “theology” of Deuteronomy has been used to grossly violate the human dignity of many God-fearing African people and many other people of the South for colonial purposes. To exacerbate the situation, there were persistent attempts from some quarters to universalise such a discriminatory biblical perspective. This would feed into the centre–periphery arrangement, with the centre feeding the periphery with such hermeneutics. For this reason, African scholars are implored to be very vigilant against ardent pressures put on the biblical texts by ontological, epistemological, and contextual biases of interpretations. Accordingly, Andrew Mbuvi identifies African Biblical Hermeneutics perfectly when he says it seeks to undo “the very construct of the ‘centre-periphery’ binary by allowing the possibility of multiple centres”). Kenneth Ngwa, thus, rightly asserts that African Biblical Hermeneutics considers African epistemologies and conditions “to be invaluable and legitimate contexts and resources in biblical interpretation”), drinking from our own wells). In consequence, this paper intends to set a dialogue between Deuteronomy 23:3 and Ruth 4:18–22. This paper aims to examine the understanding of God behind these verses. This paper will then compare the two theologies with the African philosophical concept of God. Harnessing the African concept of Ubuntu, this paper will de-ideologise the two texts and thus will provide a recommendation concerning the two texts.
Maximum Pseudo-Likelihood Estimation of Copula Models and Moments of Order Statistics
Authors: Dias Alexandra
Published: January 2024

It has been shown that, despite being consistent and in some cases efficient, maximum pseudo-likelihood (MPL) estimation for copula models overestimates the level of dependence, especially for small samples with a low level of dependence. This is especially relevant in finance and insurance applications when data are scarce. We show that the canonical MPL method uses the mean of order statistics, and we propose to use the median or the mode instead. We show that the MPL estimators proposed are consistent and asymptotically normal. In a simulation study, we compare the finite sample performance of the proposed estimators with that of the original MPL and the inversion method estimators based on Kendall’s tau and Spearman’s rho. In our results, the modified MPL estimators, especially the one based on the mode of the order statistics, have a better finite sample performance both in terms of bias and mean square error. An application to general insurance data shows that the level of dependence estimated between different products can vary substantially with the estimation method used.
Global Polarimetric Synthetic Aperture Radar Image Segmentation with Data Augmentation and Hybrid Architecture Model
Authors: Wang Zehua , Wang Zezhong , Qiu Xiaolan , Zhang Zhe
Published: January 2024

Machine learning and deep neural networks have shown satisfactory performance in the supervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, the PolSAR image classification task still faces some challenges. First, the current form of model input used for this task inevitably involves tedious preprocessing. In addition, issues such as insufficient labels and the design of the model also affect classification performance. To address these issues, this study proposes an augmentation method to better utilize the labeled data and improve the input format of the model, and an end-to-end PolSAR image global classification is implemented on our proposed hybrid network, PolSARMixer. Experimental results demonstrate that, compared to existing methods, our proposed method reduces the steps for the classification of PolSAR images, thus eliminating repetitive data preprocessing procedures and significantly improving classification performance.
Urban Functional Zone Classification Using Light-Detection-and-Ranging Point Clouds, Aerial Images, and Point-of-Interest Data
Authors: Mo You , Guo Zhaocheng , Zhong Ruofei , Song Wen , Cao Shisong
Published: January 2024

Urban Functional Zones (UFZs) serve as the fundamental units of cities, making the classification and recognition of UFZs of paramount importance for urban planning and development. These differences between UFZs not only encompass geographical landscape disparities but also incorporate socio-economic information. Therefore, it is essential to extract high-precision two-dimensional (2D) and three-dimensional (3D) Urban Morphological Parameters (UMPs) and integrate socio-economic data for UFZ classification. In this study, we conducted UFZ classification using airborne LiDAR point clouds, aerial images, and point-of-interest (POI) data. Initially, we fused LiDAR and image data to obtain high-precision land cover distributions, building height models, and canopy height models, which served as accurate data sources for extracting 2D and 3D UMPs. Subsequently, we segmented city blocks based on road network data and extracted 2D UMPs, 3D UMPs, and POI Kernel Density Features (KDFs) for each city block. We designed six classification experiments based on features from single and multiple data sources. K-Nearest Neighbors (KNNs), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were employed to classify UFZs. Furthermore, to address the potential data redundancy stemming from numerous input features, we implemented a feature optimization experiment. The results indicate that the experiment, which combined POI KDFs and 2D and 3D UMPs, achieved the highest classification accuracy. Three classifiers consistently exhibited superior performance, manifesting a substantial improvement in the best Overall Accuracy (OA) that ranged between 8.31% and 17.1% when compared to experiments that relied on single data sources. Among these, XGBoost outperformed the others with an OA of 84.56% and a kappa coefficient of 0.82. By conducting feature optimization on all 107 input features, the classification accuracy of all three classifiers exceeded 80%. Specifically, the OA for KNN improved by 10.46%. XGBoost maintained its leading performance, achieving an OA of 86.22% and a kappa coefficient of 0.84. An analysis of the variable importance proportion of 24 optimized features revealed the following order: 2D UMPs (46.46%) > 3D UMPs (32.51%) > POI KDFs (21.04%). This suggests that 2D UMPs contributed the most to classification, while a ranking of feature importance positions 3D UMPs in the lead, followed by 2D UMPs and POI KDFs. This highlights the critical role of 3D UMPs in classification, but it also emphasizes that the socio-economic information reflected by POI KDFs was essential for UFZ classification. Our research outcomes provide valuable insights for the rational planning and development of various UFZs in medium-sized cities, contributing to the overall functionality and quality of life for residents.
Cutting the Greenness Index into 12 Monthly Slices: How Intra-Annual NDVI Dynamics Help Decipher Drought Responses in Mixed Forest Tree Species
Authors: Acosta-Hernández Andrea Cecilia , Pompa-García Marín , Martínez-Rivas José Alexis , Vivar-Vivar Eduardo Daniel
Published: January 2024

We studied the correspondence between historical series of tree-ring width (TRW) and the normalized difference vegetation index (NDVI, i.e., greenness index) values acquired monthly over an entire year by unmanned aerial vehicles. Dendrochronological techniques revealed differentiated responses between species and seasonality. Pinus engelmannii Carrière and Juniperus deppeana Steudel were affected by warm temperatures (TMAX) during the winter prior to growth and benefited from precipitation (PP) during the seasons prior to the spring period. The standardized precipitation–evapotranspiration index (SPEI) confirmed the high sensitivity of P. engelmannii to drought (r = 0.7 SPEI). Quercus grisea Liebm. presented a positive association with PP at the beginning and end of its growth season. Monthly NDVI data at the individual tree level in the three species (NDVI ~0.37–0.48) statistically confirmed the temporal differences. Q. grisea showed a drastic decrease during the dry season (NDVI = 0.1) that had no impact on drought sensitivity in the same period, according to the climate-TRW relationship. We conclude that a relationship is plausible between the crown greenness index and radial growth, although more extended temporal windows of the NDVI should be explored. Differences in susceptibility to drought found among the species would presumably have implications for the composition of these forests under drought scenarios.
Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation
Authors: Liu Zenghua
Published: January 2024

During manufacturing, processing, and usage, various types of damage may be caused in structures [...]
Chatter Stability Prediction for Deep-Cavity Turning of a Bent-Blade Cutter
Authors: Wang Xiaojuan , Song Qinghua , Liu Zhanqiang
Published: January 2024

The bent-blade cutter is widely used in machining typical deep-cavity parts such as turbine discs and disc shafts, but few scholars have studied the dynamics of the turning process. The existing mechanism of regenerative chatter in the metal-cutting process does not consider the influence of bending and torsional vibration, the change of tool profile and the complex machining geometry, so it cannot be directly used to reveal the underlying cause of the chatter phenomena in the deep inner cavity part turning process. This paper attempts to investigate the dynamic problem of the bent-blade cutter turning process. The dynamic model of a bent-blade cutter is proposed by considering the regenerative chatter effect. Based on the extended Timoshenko beam element (E-TBM) theory and finite element method (FEM), the coupling between the bending vibrations and the torsional vibrations, as well as the dynamic cutting forces, are modeled along the turning path. The vibration characteristics of the bending–torsion combination of cutter board and cutter bar, together with the dynamical governing equation, were analyzed theoretically. The chatter stability of a bent-blade cutter with a bending and torsion combination effect is predicted in the turning process. A series of turning experiments are carried out to verify the accuracy and efficiency of the presented model. Furthermore, the influence of cutting parameters on the cutting process is analyzed, and the results can be used to optimize the cutting parameters for suppressing machining vibration and improving machining process stability.
Digital-Twin-Driven Intelligent Insulated-Gate Bipolar Transistor Production Lines
Authors: Zhang Xiao , Liu Xun , Song Yifan , Li Xuehan , Huang Wei , Zhou Yang , Liu Sheng
Published: January 2024

With the rapid development of novel energy vehicles, power generation, photovoltaics, and other industries, power electronic devices have gained considerable attention. Insulated-gate bipolar transistors (IGBTs) have been widely used in those fields. With the emergence of intelligent manufacturing concepts such as Germany’s “Industry 4.0” and China’s “Made in China 2025”, conventional manufacturing which needs to be upgraded with higher efficiency and yield is rapidly pivoting toward digitalization and intelligence. The digital twin methodology has been extensively used in various industries for constructing virtual models of physical entities, facilitating real-time data interconnection to reduce costs and improve efficiency. This study proposes a modular intelligent IGBT production line based on the digital twin. Real-time data are transmitted from a physical line to a digital line for storage and analysis. The digital line is visualized, and an intelligent management platform containing multiple functions is developed. Additionally, a process simulation database is established to obtain the optimal process parameters. Numerous quality issues that can arise during each process of IGBT packaging are addressed using a problem-solving approach based on the digital twin methodology. Consequently, this digital-twin-based IGBT intelligent production line effectively enhances yield rates and efficiency. IGBT modules with various packaging forms such as ACF, ACE, and ACD are manufactured.
A Modified Version of RothC to Model the Direct and Indirect Effects of Rice Straw Mulching on Soil Carbon Dynamics, Calibrated in Two Valencian Citrus Orchards
Authors: Pesce Simone , Balugani Enrico , De Paz José Miguel , Marazza Diego , Visconti Fernando
Published: January 2024

The mulching of agricultural soils has been identified as a viable solution to sequester carbon into the soil, increase soil health, and fight desertification. This is why it is a promising solution for carbon farming in Mediterranean areas. Models are used to project the effects of agricultural practices on soil organic carbon in the future for various soil and climatic conditions, and to help policy makers and farmers assess the best way to implement carbon farming strategies. Here, we modified the widely used RothC model to include mulching practices and their direct and indirect effects on soil organic matter input, soil temperature changes, and soil hydraulic balance. We then calibrated and tested our modified RothC (RothC_MM) using the dataset collected in two field mulching experiments, and we used the tested RothC_MM to estimate the expected soil carbon sequestration due to mulching by the year 2050 for the Valencian Community (Spain). Our results show that RothC_MM improved the fit with the experimental data with respect to basic RothC; RothC_MM was able to model the effects of mulch on soil temperature and soil water content and to predict soil organic carbon (SOC) and CO2 observations taken in the field.
The Development and Evaluation of Netball-Specific High-Intensity Interval Training Sessions: The Netball-HIIT Study
Authors: Eather Narelle , Stansfield Katelyn , Babic Mark , Lubans David R.
Published: January 2024

This two-phase study involved the design, development, and evaluation of netball-specific high-intensity interval training sessions (Netball-HIIT) for use with netballers of varied ages and abilities. In Phase 1 (2020), a systematic analysis of netball GPS data from 30 netball players and gameplay video footage (10 h) was conducted, followed by the design and testing of five 8 min Netball-HIIT sessions involving 100 netball players (age 21 ± 8.44 years; Australia). In Phase 2 (2021), the feasibility and preliminary efficacy of delivering one Netball-HIIT session each week for five weeks was assessed using a two-armed, dose-matched, randomized, controlled feasibility study with netball players (born in 2010) (Netball HIIT n = 15; Netball Knee Program: NKP n = 15). Cardiorespiratory and muscular fitness was assessed at baseline and 6 weeks. Data were analyzed using linear mixed models and Cohen’s d effect sizes. Netball-HIIT sessions were highly rated by players, and higher average (139 bpm) and peak heart rates (156 bpm) were detected amongst Netball-HIIT participants (KNP = 127 bpm and 152 bpm). We observed a large effect for cardiorespiratory fitness (+2.4 laps, d = 0.89), and a small to medium effect for muscular fitness (push-ups +1.2, d = 0.49; standing jump +0.8 cm, d = 0.36) in favor of Netball-HIIT, suggesting that coach-led Netball-HIIT may provide a time-efficient and effective training component for use in netball.
A Study on the Mechanical Properties of Glass-Fiber-Reinforced Defective Gypsum Boards
Authors: Wu Di , Jing Laiwang , Peng Shaochi , Jing Wei
Published: January 2024

As a waste derivative, glass fiber has drawn a lot of interest from the engineering community. The purpose of this study was to use glass fiber to improve the performance of defective gypsum boards. Single compression experiments, repeated loading experiments, and scanning electron microscopy (SEM) testing were performed on defective gypsum boards. The results showed that the addition of glass fiber can improve the compressive strength of defective gypsum boards. When the fiber concentration is 1.5%, the strength of single-hole gypsum boards increases by 77.1%. Energy evolution and residual strain evaluation after repeated loading showed the significant reinforcement of the dual-hole gypsum board samples with the addition of glass fiber, improving the stress distribution and elasticity, which was confirmed using damage factor analysis. Glass fibers reduce stress concentrations, improve integrity, and prevent brittle failure, especially at high stress levels. The microstructural analysis showed that the addition of glass fiber improves adhesion and prevents microcracking while acting as a stress transfer bridge, enhancing the behavior of the specimen under cyclic loading. Based on the experimental results and cost, 1.5% glass fiber is the optimal concentration. The research results provide new ideas for the application of glass fiber in defective and brittle materials and contribute toward the sustainable development of the construction industry.
Experimental Study on the Durability Performance of Sustainable Mortar with Partial Replacement of Natural Aggregates by Fiber-Reinforced Agricultural Waste Walnut Shells
Authors: Peng Shiwei , Qiu Kaixin , Yang Bowei , Ai Jifeng , Zhou An
Published: January 2024

Through the recovery and reuse of agricultural waste, the extraction and consumption of natural aggregates can be reduced to realize the sustainable development of the construction industry. Therefore, this paper utilizes the inexpensive, surplus, clean, and environmentally friendly waste agricultural material walnut shell to partially replace the fine aggregates in mortar to prepare environmentally friendly mortar. Considering the decrease in mortar performance after mixing walnut shells, basalt fibers of different lengths (3 mm, 6 mm, and 9 mm) and different dosages (0.1%, 0.2%, and 0.3%) were mixed in the mortar. The reinforcing effect of basalt fibers on walnut shell mortar was investigated by mechanical property tests, impact resistance tests, and freeze–thaw cycle tests. The damage prediction model was established based on the Weibull model and gray model (GM (1,1) model), and the model accuracy was analyzed. The experimental results showed that after adding basalt fibers, the compressive strength, split tensile strength, and flexural strength of the specimens with a length of 6 mm and a doping amount of 0.2% increased by 13.98%, 48.15%, and 43.75%, respectively, and the fibers effectively improved the defects inside the walnut shell mortar. The R²s in the Weibull model were greater than 87.38%, and the average relative error between the predicted life of the impacts and the measured values was greater than 87.38%. The average relative errors in the GM (1,1) model ranged from 0.81% to 2.19%, and the accuracy analyses were all of the first order.
Importing Clothing Made from Recycled Textile Materials? A Study of Retailers’ Sourcing Strategies in Five European Countries
Authors: Marsh Leah , Lu Sheng
Published: January 2024

This study examined retailers’ sourcing strategies for clothing made from recycled textile materials in the five largest European clothing retail markets (i.e., the UK, Italy, France, Germany, and Spain), given the increasing availability of such products. The multivariate analysis of variance (MANOVA) was conducted based on the detailed country of origin and product assortment information of thousands of such clothing items for sale in these five EU countries from January 2021 to May 2023. The results show that EU retailers sourced clothing using recycled textile materials diversely from over 40 developing and developed countries across Asia, America, Europe, and Africa. The geographic location of supplying countries statistically affects the detailed assortment of recycled clothing that EU retailers import. However, apart from assortment diversity, no statistical evidence indicates that developing countries had advantages over developed ones regarding product sophistication, replenishment frequency, and pricing in the five EU markets. The study’s findings offer new insights into the business aspects of recycled clothing and reveal promising global sourcing opportunities for such products. The results also imply a potentially significant shift in global apparel trade patterns as retailers embrace fashion circularity and expand sourcing clothing made from recycled textile materials.
Does Industrial Symbiosis Improve Carbon Emission Efficiency? Evidence from Chinese National Demonstration Eco-Industrial Parks
Authors: Ji Yingwen , Shao Zhiying , Wang Ruifang
Published: January 2024

Improving carbon emission efficiency (CEE) is a necessary consideration in response to economic downturn and climate change. In this case, industrial symbiosis paves the way for cities to conserve energy, reduce carbon emissions, and upgrade economic development patterns. This paper verifies the influence of industrial symbiosis policies on CEE, represented by National Demonstration Eco-industrial Parks (NDEPs). The difference-in-differences (DID) and spatial DID (SDID) models, as well as panel data of 282 Chinese cities during 2003–2019, were used to complete this argumentation process. The results show that NDEP policy dramatically increases the CEE of pilot cities. Compared with cities without NDEP, pilot cities climb by 3.49% on CEE, mainly due to industrial structure upgrading and green technological innovation. Moreover, eastern, non-resource-based, and multi-NDEP cities experience a noticeable increase in CEE. NDEP increases not only the CEE of pilot cities but also that of their neighboring cities within 450 km through diffusion and demonstration effects. All these findings help promote China’s NDEP construction and offer decision-making guidance for climate governance and low-carbon transition in China and others following a similar pathway.
A Study on Nursing Personnel Operations to Ensure Evacuation Safety during Medical Facility Disasters
Authors: Kim Yongjoo , Kim Junghyeon , Kim Moonsik , Rie Dongho
Published: January 2024

Worldwide, the number of users of medical facilities is increasing due to the pandemic phenomenon and extended life expectancy. In addition, the majority of medical facility occupants are patients, leading to issues of inconvenience in movement and increased vulnerability during evacuations in the event of a fire. Therefore, the availability of nursing personnel, who serve as assistants in tasks such as transporting beds and wheelchairs essential for patient evacuation, is crucial for ensuring evacuation safety. However, a global shortage of nursing personnel has led to ongoing research on optimizing workforce allocation. In this study, the Available Safe Egress Time (ASET) and Required Safe Egress Time (RSET) were quantitatively compared for medical facilities with a combination of intensive care units and general wards, utilizing a Fire Dynamics Simulator (FDS) and Flexsim Healthcare simulations to assess fire risk. The research goal here is to provide sustainable research directions for determining the minimum ratio of nurses to patients required for evacuation in a disaster, ensuring the continuous availability of nursing personnel in medical facilities. To achieve this, the variable was set to five stages based on the total number of patients per nurse. As a result of this study, it was confirmed that when the nurse-to-patient ratio exceeded 1:6, more than 70% of bedridden patients died. Additionally, it was verified that maintaining a patient-to-nurse ratio of less than 1:1 is effective for ensuring evacuation safety.
Can the Carbon Emissions Trading Pilot Policy Improve the Ecological Well-Being Performance of Cities in China?
Authors: Guo Jianfeng , Ou Xiaotong , Li Yan , Liu Kecheng
Published: January 2024

Adhering to ecological priorities and promoting environmental regulations is essential for improving ecological well-being performance (EWP); conversely, EWP is a crucial measure of social and economic sustainability. From the perspective of high-quality development, we see China’s cities’ adoption of the carbon emissions trading pilot (CETP) policy as a quasi-natural experiment, and we use the difference-in-differences (DID) approach to analyze how market-based carbon credits affect the urban EWP and its action mechanism. The findings of the empirical study show that: (1) The implementation of CETP can effectively improve the quality of urban development, with an increase of 29.1% in the EWP value, effectively contributing to the realization of the goal of high-quality development; (2) the urban EWP levels in China are higher in the east, lower in the west and lowest in the middle, but they all show a fluctuating upward trend; (3) according to the heterogeneity study, the implementation of CETP has a scale effect and significant urban locational differences, and its impact on EWP of cities is greater in “advanced cities” and central region cities; (4) the implementation of CETP can advance industrial structure upgrading, thereby promoting the EWP level, but the mediating effect of technological innovation is not significant. The possible innovations in this paper are as follows: (1) It broadens the existing research system on the effectiveness of CETP policies. (2) It reconstructs the index system of EWP from the perspective of high-quality development so that its measurement results can reflect the quality of urban development more comprehensively. (3) The research samples of CETP and EWP are enriched by using prefectural-level data.
Research on Land Use Versatility Evaluation, Spatiotemporal Coupling, and Influencing Factors Based on Multimethod Integration
Authors: Zhang Nana , Jiang Gang , Xia Xingsheng , Ge Yuejing
Published: January 2024

Land use multifunctionality research is important for the efficient use of land resources and the resolution of land use conflicts. With the use of methods such as the technique for order of preference by similarity to ideal solution (TOPSIS) model, coupling coordination model, and geographical detector, the land use multifunctionality level, spatiotemporal coupling, and influencing factors in the Sichuan Province of China from 2000 to 2020 were systematically analyzed in this paper. It was revealed that, from 2000 to 2020, the comprehensive land use functionality in Sichuan Province was continuously improved with increasing economic, social, and ecological functionality levels. The comprehensive land use functionality in each city (prefecture) exhibited a positive development trend. The coupling coordination degree of the land use multifunctionality in Sichuan Province has been continuously improved, undergoing an evolutionary process from the brink of disarray to barely coordinated, then to primary coordination, and finally to medium coordination. The spatial differentiation of land use multifunctionality coupling coordination among cities (prefectures) was notable, showing center–periphery spatial distribution characteristics. The average slope and employed population density exhibited the highest explanatory power for the spatial differences in land use multifunctionality coupling coordination. The interaction between any two factors exerted a greater impact than any single factor on the spatial differentiation of land use multifunctionality coupling coordination. Based on the regional development characteristics, region-specific strategies should be adopted to enhance the land use multifunctionality level in Sichuan Province.
Numerical Analysis of the Transfer Dynamics of Heavy Metals from Soil to Plant and Application to Contamination of Honey
Authors: Atanasov Atanas , Georgiev Slavi , Vulkov Lubin
Published: January 2024

We analyze a mathematical model of the effects of soil contamination by heavy metals, which is expressed as systems of nonlinear ordinary differential equations (ODEs). The model is based on the symmetry dynamics of heavy metals soil–plant interactions. We aim to study this symmetric process and its long-term behavior, as well as to discuss the role of two crucial parameters, namely the flux of the hydrogen protons to the soil in rainfall events W(t), and the available water for roots p(t). We study the boundedness and positivity of the solution. Further, a parameter identification analysis of the model is presented. Numerical experiments with synthetic and realistic data of honeybee population are discussed.
Constraints on Phase Transitions in Neutron Star Matter
Authors: Brandes Len , Weise Wolfram
Published: January 2024

Recent inference results of the sound velocity in the cores of neutron stars are summarized. Implications for the equation of state and the phase structure of highly compressed baryonic matter are discussed. In view of the strong constraints imposed by the heaviest known pulsars, the equation of state must be very stiff in order to ensure the stability of these extreme objects. This required stiffness limits the possible appearance of phase transitions in neutron star cores. For example, a Bayes factor analysis quantifies strong evidence for squared sound velocities cs2>0.1 in the cores of 2.1 solar-mass and lighter neutron stars. Only weak first-order phase transitions with a small phase coexistence density range Δρ/ρ<0.2 (at the 68% level) in a Maxwell construction still turn out to be possible within neutron stars. The central baryon densities in even the heaviest neutron stars do not exceed five times the density of normal nuclear matter. In view of these data-based constraints, much discussed issues such as the quest for a phase transition towards restored chiral symmetry and the active degrees of freedom in cold and dense baryonic matter, are reexamined.
Noether Symmetry Analysis of the Klein–Gordon and Wave Equations in Bianchi I Spacetime
Authors: Camci Ugur
Published: January 2024

We investigate the Noether symmetries of the Klein–Gordon Lagrangian for Bianchi I spacetime. This is accomplished using a set of new Noether symmetry relations for the Klein–Gordon Lagrangian of Bianchi I spacetime, which reduces to the wave equation in a special case. A detailed Noether symmetry analysis of the Klein–Gordon and the wave equations for Bianchi I spacetime is presented, and the corresponding conservation laws are derived.