bluuebunny/crossref_metadata_2025 huggingface dataset:
Underwater-Yolo: Underwater Object Detection Network with Dilated Deformable Convolutions and Dual-Branch Occlusion Attention Mechanism
Authors: Li Zhenming , Zheng Bing , Chao Dong , Zhu Wenbo , Li Haibing , Duan Jin , Zhang Xinming , Zhang Zhongbo , Fu Weijie , Zhang Yunzhi
Published: December 2024

Underwater object detection is critical for marine ecological monitoring and biodiversity research, yet existing algorithms struggle in detecting densely packed objects of varying sizes, particularly in occluded and complex underwater environments. This study introduces Underwater-Yolo, a novel detection network that enhances performance in these challenging scenarios by integrating a dual-branch occlusion-handling attention mechanism (GLOAM) and a Cross-Stage Partial Dilated Deformable Convolution (CSP-DDC) backbone. The dilated deformable convolutions (DDCs) in the backbone and neck expand the receptive field, thereby improving the detection of small objects, while the deformable convolutions enhance the model’s adaptive feature extraction capabilities for unstructured objects. Additionally, the CARAFE up-sampling operator in the neck aggregates contextual information across a broader spatial domain. The GLOAM, consisting of a global branch (using a Vision Transformer to capture global features and object–background relationships) and a local branch (enhancing the detection of occluded objects through depthwise–pointwise convolutions), further optimizes performance. By incorporating these innovations, the model effectively addresses the challenges of detecting small and occluded objects in dense underwater environments. The evaluation on the CLfish-V1 dataset shows significant improvements over state-of-the-art algorithms, with an AP50 of 93.8%, an AP75 of 88.9%, and an AP-small of 76.4%, marking gains of 4.7%, 16.7%, and 6%, respectively. These results demonstrate the model’s effectiveness in complex underwater scenarios.
How to Consider Human Footprints to Assess Human Disturbance: Evidence from Urban Agglomeration in the Yellow River Basin
Authors: Luo Sirui , Li Xiangxue , Yang Jie , Li Xingwei
Published: December 2024

Natural processes are substantially impacted by human activity, and assessing human activity has significant ramifications for regional ecological conservation. The study developed an extended human footprint (HF) assessment model based on the theory of ecological effects and human pressures to evaluate human disturbances in the urban agglomerations of the Yellow River Basin using data from 2005 to 2020, revealing the spatiotemporal pattern in the region. The conclusions show that the HF value of urban agglomeration in the Yellow River Basin has steadily increased from 2005 to 2020, primarily driven by mining intensity and road construction. High HF areas are primarily concentrated in urban areas in the south-central of the region, with a tendency to spread outward. Medium HF areas are mainly distributed in the eastern part of the study area, and the spatial distribution increases year by year, extending outward from the center area. The moderately low and HF areas are mostly found in the mountainous areas of the northwest. Among the urban agglomerations in the Yellow River Basin, the Central Plains UA and Shandong Peninsula UA are the areas most heavily affected by human disturbance. The conclusions are instructive for the high-quality development of urban agglomerations in the Yellow River Basin.
Quaternary Ammonium Silica Nanoparticles for Antimicrobial Implantable Medical Devices: An In Vitro Study
Authors: Weiss Eitam , Berl Ariel , Shir-az Ofir , Bilal Biader Samih , Weiss Ervin I. , Paitan Yossi , Zaltsman Natan , Golberg Alexander , Shalom Avshalom
Published: December 2024

Biofilm formation on prostheses and implanted devices can lead to serious complications and increased healthcare expenditures. Once formed, biofilm management is difficult and may involve a long course of antibiotics, additional surgery, and, occasionally, implant removal. This study evaluated the antibacterial properties of medical-grade silicone samples integrated with novel, non-leaching, antibacterial, quaternary ammonium silica (QASi) particles. Our collaborators (Nobio, Israel) prepared silicone sheets integrated with antibacterial QASi nanoparticles. Samples containing 0.5%, 0.75%, and 1%, QASi particles were evaluated for antibacterial properties against S. epidermidis, S. aureus, methicillin-resistant S. aureus (MRSA), E. faecalis, and P. aeruginosa using the direct contact test. The tested silicone samples integrated with QASi particles showed no bacterial growth, while growth was observed in control silicone samples without QASi. In addition, the agar diffusion test, used to evaluate the leaching of antibacterial components, exhibited no inhibition zone around the samples indicating that the QASi particles do not leach into surrounding milieu. The QASi nanoparticles exhibited very potent antibacterial surface properties, killing all viable bacteria placed on their surface. Incorporating QASi nanoparticle technology into medical products during production has the potential to create an antimicrobial surface that prevents microbial colonization and biofilm formation.
Study on High-Temperature Constitutive Model and Plasticity of the Novel Cr-Mo-V Hot-Work Die Steel Forging
Authors: Yuan Yasha , Lin Yichou , Wang Wenyan , Zhang Bo , Shi Ruxing , Zhang Yudong , Xie Jingpei , Wu Chuan , Mao Feng
Published: December 2024

In response to the increasingly strict performance requirements of large molds, a novel Cr-Mo-V hot-work die steel has been developed. In order to study the high-temperature hot deformation behavior and plasticity of the novel steel, hot compression tests were conducted on the Gleeble-1500D thermal simulation testing machine at a deformation temperature of 950~1200 °C and a strain rate of 0.001~5 s−1. Based on the Arrhenius constitutive model, a novel Cr-Mo-V steel high-temperature constitutive model considering strain was established. The reliability and applicability of this modified model, which includes strain compensation, were assessed using the phase relationship coefficient (R) and the average absolute relative error (AARE). The values of R and AARE for comparing predicted outcomes with experimental data were 0.98902 and 3.21%, respectively, indicating that the model demonstrated high precision and reliability. Based on the Prasad criterion, a 3D hot processing map of the novel Cr-Mo-V steel was established, and the instability zone of the material was determined through the hot processing map: the deformation temperature (950~1050 °C) and strain rate (0.001~0.01 s−1) were prone to adiabatic shear and crystal mixing. The suitable processing range was determined based on the hot processing map: The first suitable processing area was the strain range of 0.05~0.35, the temperature range was 1100~1175 °C, and the strain rate was 0.001~0.009 s−1. The second suitable processing area was a strain of 0.45~0.65, a temperature of 1100~1200 °C, and a strain rate of 0.0024~0.33 s−1. Finally, the forging process of hundred-ton die steel forging was developed by combining 3D hot processing maps with finite element simulation, and the forging trial production of 183 t forging was carried out. The good forging quality indicated that the established hot processing map had a good guiding effect on the production of 100-ton test steel forging.
A Novel Method for Identifying Tool–Holder Interface Dynamics Based on Receptance Coupling
Authors: Zhao Dingtang , Li Xiaohu , Wan Shaoke , Zhao Qiangqiang , Hong Jun
Published: December 2024

The structural dynamics of a machine tool play a significant role in chatter occurrence, which significantly deteriorates the metal-cutting performance. The receptance coupling substructure analysis (RCSA) is known for eliminating the experimental dependency on repetitive impact hammer testing. However, the identified contact parameters between the holder and tool, which are necessary for RCSA, usually lose accuracy in predicting tool point dynamics when applied to other tool clamping lengths or to combinations with other tools. To this end, a new method based on conventional impact hammer testing and RCSA technique to identify these parameters is proposed. Two descriptions of the proposed method are presented for different tool combinations and different clamping lengths, respectively. This new method eliminates the need for specialized experimental setups. The predicted tool point dynamics, using the identified contact parameters from the proposed method, show deviations below 3% with one exception, indicating that the identifications are accurate for various clamping lengths. The new approach yields significant advancements in the predicted tool point dynamics and stability boundaries compared to a traditional identification method reported in the literature.
The Influence of Fine Distribution and Compensation on Cooperation in Public Goods Game
Authors: Shen Yong , Guo Jin , Kang Hongwei
Published: December 2024

In spatial public goods games, groups consisting solely of defectors do not benefit. Consequently, intelligent defectors are inclined to incur the cost of punishing other defectors to enable cooperators to flourish within the group, thereby safeguarding their own advantages. Drawing from real-world observations where early preparation often dictates future success, we integrated probabilistic punishment into the public goods game and analyzed two scenarios. In the first scenario, a probabilistic punishment mechanism was established, wherein the higher the cost was of monitoring and enforcement, the greater was the probability of punishment. In the second scenario, a compensation and fine distribution mechanism was introduced alongside probabilistic punishment, where the outcome of the punishment determined whether the smart defector recovered part of the fine or rewarded cooperators with additional benefits. This incentivized smart defectors to judiciously assess the punishment cost required to effectively protect their interests. The study demonstrated that both mechanisms significantly enhanced cooperation, with the probabilistic punishment model involving fine distribution and compensation proving more effective than simple probabilistic punishment alone. These results offer novel insights into the dynamics of probabilistic punishment and the role of fine distribution in fostering cooperation.
Optimizing a Machine Learning Algorithm by a Novel Metaheuristic Approach: A Case Study in Forecasting
Authors: Gülsün Bahadır , Aydin Muhammed Resul
Published: December 2024

Accurate sales forecasting is essential for optimizing resource allocation, managing inventory, and maximizing profit in competitive markets. Machine learning models are being increasingly used to develop reliable sales-forecasting systems due to their advanced capabilities in handling complex data patterns. This study introduces a novel hybrid approach that combines the artificial bee colony (ABC) and fire hawk optimizer (FHO) algorithms, specifically designed to enhance hyperparameter optimization in machine learning-based forecasting models. By leveraging the strengths of these two metaheuristic algorithms, the hybrid method enhances the predictive accuracy and robustness of models, with a focus on optimizing the hyperparameters of XGBoost for forecasting tasks. Evaluations across three distinct datasets demonstrated that the hybrid model consistently outperformed standalone algorithms, including the genetic algorithm (GA), artificial rabbits optimization (ARO), the white shark optimizer (WSO), the ABC algorithm, and the FHO, with the latter being applied for the first time to hyperparameter optimization. The superior performance of the hybrid model was confirmed through the RMSE, the MAPE, and statistical tests, marking a significant advancement in sales forecasting and providing a reliable, effective solution for refining predictive models to support business decision-making.
Acetylation-Mediated Post-Translational Modification of Pyruvate Dehydrogenase Plays a Critical Role in the Regulation of the Cellular Acetylome During Metabolic Stress
Authors: Rajakumar Aishwarya , Nguyen Sarah , Ford Nicole , Ogundipe Gbenga , Lopez-Nowak Ethan , Kondrachuk Olena , Gupta Manish K
Published: December 2024

Background: Cardiac diseases remain one of the leading causes of death globally, often linked to ischemic conditions that can affect cellular homeostasis and metabolism, which can lead to the development of cardiovascular dysfunction. Considering the effect of ischemic cardiomyopathy on the global population, it is vital to understand the impact of ischemia on cardiac cells and how ischemic conditions change different cellular functions through post-translational modification of cellular proteins. Methods: To understand the cellular function and fine-tuning during stress, we established an ischemia model using neonatal rat ventricular cardiomyocytes. Further, the level of cellular acetylation was determined by Western blotting and affinity chromatography coupled with liquid chromatography–mass spectroscopy. Results: Our study found that the level of cellular acetylation significantly reduced during ischemic conditions compared to normoxic conditions. Further, in mass spectroscopy data, 179 acetylation sites were identified in the proteins in ischemic cardiomyocytes. Among them, acetylation at 121 proteins was downregulated, and 26 proteins were upregulated compared to the control groups. Differentially, acetylated proteins are mainly involved in cellular metabolism, sarcomere structure, and motor activity. Additionally, a protein enrichment study identified that the ischemic condition impacted two major biological pathways: the acetyl-CoA biosynthesis process from pyruvate and the tricarboxylic acid cycle by deacetylation of the associated proteins. Moreover, most differential acetylation was found in the protein pyruvate dehydrogenase complex. Conclusions: Understanding the differential acetylation of cellular protein during ischemia may help to protect against the harmful effect of ischemia on cellular metabolism and cytoskeleton organization. Additionally, our study can help to understand the fine-tuning of proteins at different sites during ischemia.
Role of the Foliar Endophyte Colletotrichum in the Resistance of Invasive Ageratina adenophora to Disease and Abiotic Stress
Authors: Yang Ailing , Li Yuxuan , Zeng Zhaoying , Zhang Hanbo
Published: December 2024

Plant-associated fungi often drive plant invasion success by increasing host growth, disease resistance, and tolerance to environmental stress. A high abundance of Colletotrichum asymptomatically accumulated in the leaves of Ageratina adenophora. In this study, we aimed to clarify whether three genetically distinct endophytic Colletotrichum isolates (AX39, AX115, and AX198) activate invasive plant defenses against disease and environmental stress. We observed that, in the absence of pathogen attack and environmental stress, the foliar endophyte Colletotrichum reduced photosynthesis-related physiological indicators (i.e., chlorophyll content and soluble sugar content), increased resistance-related indicators (i.e., total phenolic (TP) and peroxidase (POD) activity), and decreased the biomass of A. adenophora. However, endophytic Colletotrichum strains exhibit positive effects on resistance to certain foliar pathogen attacks. Strains AX39 and AX115 promoted but AX198 attenuated the pathogenic effects of pathogen strains G56 and Y122 (members of Mesophoma ageratinae). In contrast, AX39 and AX115 weakened, but AX198 had no effect on, the pathogenic effect of the pathogen strain S188 (Mesophoma speciosa; Didymellaceae family). We also found that endophytes increase the biomass of A. adenophora under drought or nutrient stress. Strain AX198 significantly increased stem length and chlorophyll content under drought stress. Strain AX198 significantly increased the aboveground dry weight, AX115 increased the stem length, and AX39 significantly increased the chlorophyll content under nutrient stress. Our results revealed that there are certain positive effects of foliar Colletotrichum endophytes on A. adenophora in response to biotic and abiotic stresses, which may be beneficial for its invasion.
What Do We Know About the Energy Status and Diets of Pre-Professional and Professional Dancers: A Scoping Review
Authors: Rigoli Alessandra , Dang Emily , Michael Victoria , Gifford Janelle , Davies Alyse
Published: December 2024

Background/Objectives: Dancers require adequate nutrition support for growth and development during the pre-professional stage, as well as to fuel classes and rehearsals and to enhance performance for both pre-professional and professional dancers. The aim of this study is to understand the energy status and diet of pre-professional and professional dancers in the genres of ballet, contemporary, musical theatre, and opera. Methods: Electronic databases (n = 9) and grey literature were searched for primary studies with no time limit. Screening and data extraction were completed by two reviewers. Results: Twelve studies were included for pre-professional (n = 7) and professional (n = 5) dancers. The genres identified were ballet (n = 11) and contemporary (n = 1), with no studies on musical theatre or opera. Studies on pre-professional ballet and contemporary dancers indicated a negative energy balance and low energy availability. Pre-professional ballet dancers had lower energy intakes than professional dancers. Professional dancers had lower BMI and body fat percentages. Macronutrients were mostly reported using the acceptable macronutrient distribution range for carbohydrates (38–56%E), protein (12–17%E), and total fat (26–42%E). Iron and calcium were the main micronutrients of concern. Conclusions: Accredited sports dietitians are recommended to support pre-professional and professional dancers to optimize their diet for health and performance. Further investigation is needed to quantify and assess dancers’ dietary intake using sports nutrition guidelines for reference.
Caralluma fimbriata Extract Improves Vascular Dysfunction in Obese Mice Fed a High-Fat Diet
Authors: Thunuguntla Venkata Bala Sai Chaitanya , Gadanec Laura Kate , McGrath Catherine , Griggs Joanne Louise , Sinnayah Puspha , Apostolopoulos Vasso , Zulli Anthony , Mathai Michael L.
Published: December 2024

Background: Obesity is a risk factor for developing cardiovascular diseases (CVDs) by impairing normal vascular function. Natural products are gaining momentum in the clinical setting due to their high efficacy and low toxicity. Caralluma fimbriata extract (CFE) has been shown to control appetite and promote weight loss; however, its effect on vascular function remains poorly understood. This study aimed to determine the effect that CFE had on weight loss and vascular function in mice fed a high-fat diet (HFD) to induce obesity, comparing this effect to that of lorcaserin (LOR) (an anti-obesity pharmaceutical) treatment. Methods: C57BL/6J male mice (n = 80) were fed a 16-week HFD to induce obesity prior to being treated with CFE and LOR as standalone treatments or in conjunction. Body composition data, such as weight gain and fat mass content were measured, isometric tension analyses were performed on isolated abdominal aortic rings to determine relaxation responses to acetylcholine, and immunohistochemistry studies were utilized to determine the expression profiles on endothelial nitric oxide synthase (eNOS) and cell stress markers (nitrotyrosine (NT) and 78 kDa glucose-regulated protein (GRP78)) in the endothelial, medial and adventitial layers of aortic rings. Results: The results demonstrated that CFE and CFE + LOR treatments significantly reduced weight gain (17%; 24%) and fat mass deposition (14%; 16%). A HFD markedly reduced acetylcholine-mediated relaxation (p < 0.05, p < 0.0001) and eNOS expression (p < 0.0001, p < 0.01) and significantly increased NT (p < 0.05, p < 0.0001) and GRP78 (p < 0.05, p < 0.01, p < 0.001). Obese mice treated with CFE exhibited significantly improved ACh-induced relaxation responses, increased eNOS (p < 0.05, p < 0.01) and reduced NT (p < 0.01) and GRP78 (p < 0.05, p < 0.01) expression. Conclusions: Thus, CFE alone or in combination with LOR could serve as an alternative strategy for preventing obesity-related cardiovascular diseases.
Thyroid Autoimmunity During Universal Salt Iodisation—Possible Short-Term Modulation with Longer-Term Stability
Authors: Atapattu Navoda , Jayatissa Renuka , de Silva Harendra , Adlan Mohamed A. , Obuobie Emmanuel K. , Premawardhana Lakdasa D.
Published: December 2024

Universal salt iodisation (USI) plays an essential role in the provision of iodine (I) to populations worldwide. Countries adopting USI programmes, adhering to strict criteria laid down by expert organisations such as the Iodine Global Network, are estimated to have reduced the prevalence of I deficiency by 75% (protecting 720 million individuals worldwide). Despite this success, doubts have been raised as to the desirability of continuing such programmes because of (a) the need to reduce salt intake for cardiovascular prevention and (b) the induction of thyroid autoimmunity. We present current evidence from cross-sectional studies in several disparate populations of the possible short-term modulation of thyroid autoimmune markers, thyroid peroxidase (TPOAb) and thyroglobulin antibodies (TgAb), with minimal disruption of biochemical thyroid function. We also present evidence from longer term, mainly cross-sectional studies, that indicate a reduction in the prevalence of TPOAb and TgAb, and the persistence of normal biochemical thyroid function over as long as two decades of USI. We believe these studies indicate that USI is safe, and that long-term salt iodisation does not cause an increase in autoimmune thyroid disease in the populations studied and should not be a safety concern based on current evidence. More long-term and better-designed studies are required.
Scientific Validation of Using Active Constituent as Research Focus in Traditional Chinese Medicine: Case Study of Pueraria lobata Intervention in Type 2 Diabetes
Authors: Chen Yaping , Wen Qiuqi , Lin Meng , Yang Bing , Feng Liang , Jia Xiaobin
Published: December 2024

Objectives: Traditional Chinese Medicine (TCM) is recognized for its complex composition and multiple therapeutic targets. However, current pharmacological research often concentrates on extracts or individual components. The former approach faces numerous challenges, whereas the latter oversimplifies and disregards the synergistic effects among TCM components. This study aims to investigate the scientific validity of focusing on the active constituent in TCM efficacy research, using Pueraria lobata (P. lobata) as a case study. Methods: Through spectrum-effect correlation analysis, network pharmacology, and molecular docking, five active ingredients of P. lobata were identified: puerarin, formononetin, tuberosin, 4′,7-dihdroxy-3′-methoxyisoflavone, and Daidzein-4,7-diglucoside. These ingredients were combined to form an active constituent, which was subsequently tested in vitro and in vivo. Results: In in vitro, the active constituent exhibited superior effects in enhancing glucose consumption and glycogen synthesis compared to both the P. lobata extract and individual components. In vivo experiments demonstrated that medium and high doses of the active constituent were significantly more effective than P. lobata extract, with effects comparable to those of metformin in reducing blood sugar levels. Conclusions: The active constituent effectively improves T2DM by lowering blood glucose levels, promoting glycogen synthesis, and modulating glycolipid metabolism. Both in vitro and in vivo studies indicate that it outperformed the P. lobata extract and individual components. This study establishes the scientific validity and feasibility of utilizing the active constituent as the focus for investigating the efficacy of TCM, thereby offering novel insights and a new research paradigm for future TCM investigations.
The Application of the Design of Experiments and Artificial Neural Networks in the Development of a Fast and Straightforward HPLC-UV Method for Fluconazole Determination in Hemato-Oncologic Pediatric Patients and Its Adaptation to Therapeutic Drug Monitoring
Authors: Adamiszak Arkadiusz , Czyrski Andrzej , Sznek Bartosz , Grześkowiak Edmund , Bienert Agnieszka
Published: December 2024

Objectives: This study aimed to develop an optimized and wide concentration range HPLC-UV method for fluconazole (FLU) determination and its adaptation for pharmacokinetics (PK) studies in the pediatric population. Methods: The following parameters of chromatographic separation were optimized: retention time, tailing factor, peak height, and the sample preconditioning parameter, such as recovery. The optimization process involved the use of a central composite design (CCD) and Box–Behnken design (BBD) in the design of experiments (DoE) approach and a multilayer perceptron (MLP) for artificial neural network (ANN) application. Statistical and PK analyses were performed using Statistica and PKanalix. Results: The acetonitrile (ACN) concentration revealed the most significant factor influencing the retention time, tailing factor, and peak height of FLU and the internal standard. For recovery, the extracting agent’s volume was the most significant factor. In most cases, the analysis conducted with the DoE and ANN indicated the same factors in a similar order regarding their impact on the analyzed variables. The optimization process allowed for achieving a wide range of determined concentrations (0.5–100 mg/L) and ~100% recovery. The developed method enabled PK analysis of 12 samples from three pediatric patients, proving its clinical usability. The estimated median clearance (CL) and volume of distribution (Vd) were 1.01 L/h and 18.64 L, respectively. Conclusions: DoE and ANNs are promising and useful tools in the optimization of sample preconditioning as well as the HPLC separation procedure. The investigated fluconazole determination method meets the European Medicines Agency (EMA) validation objectives and might be used in pediatric and adult PK studies.
Super Broad Non-Hermitian Line Shape from Out-of-Phase and In-Phase Photon-Phonon Dressing in Eu3+: NaYF4 and Eu3+: BiPO4
Authors: Majeed Muhammad Kashif , Usman Muhammad , Hussain Iqbal , Javed Usman , Khan Muhammad Qasim , Nadeem Faisal , Munir Faisal , Fan Huanrong , Cai Yin , Zhang Yanpeng
Published: December 2024

We report super broad non-Hermitian line shape from out-of-phase and in-phase photon-phonon dressing (quantization) in Eu3+: NaYF4 and Eu3+: BiPO4 nanocrystals. The line shape is controlled by changing time gate position, time gate width, power, temperature, sample, photomultiplier tubes, and laser. We observed that the fluorescence (FL) line-shape contrasts are 69.23% for Eu3+: BiPO4 and 43.75% for Eu3+: NaYF4, owing to the stronger out-of-phase photon-phonon dressing (destructive quantization). Moreover, we observed that the spontaneous four-wave mixing (SFWM) line shape was approximately three times wider at 300 K than at 77 K for the [(12:1)-phase] Eu3+: NaYF4 due to more high-frequency in-phase phonon dressing (strong constructive quantization). Furthermore, we showed that the noise line-shape width remains unchanged for Eu3+: BiPO4 (16 nm) and Eu3+: NaYF4 (12 nm) due to out-of-phase and in-phase photon-phonon dressing balance. Such results have potential applications in multi-channel band stop filter.
Different Impacts of Long-Term Tillage and Manure on Yield and N Use Efficiency, Soil Fertility, and Fungal Community in Rainfed Wheat in Loess Plateau
Authors: Chen Mengni , Yang Hailiang , Yang Qingshan , Li Yongshan , Wang Hui , Wang Juanling , Fan Qiaolan , Yang Na , Wang Ke , Zhang Jiancheng , Yuan Jiawei , Dong Peng , Wang Lu
Published: December 2024

Conservation tillage and fertilization are widely adopted in agricultural systems to enhance soil fertility and influence fungal communities, thereby improving agroecosystems. However, the effects of no-tillage combined with manure on grain yield, nitrogen use efficiency (NUE), soil fertility, and rhizosphere fungal communities remain poorly understood, particularly in rainfed wheat fields on the Loess Plateau. A 15-year field experiment was conducted at the Niujiawa Experimental Farm of the Cotton Research Institute, Shanxi Agricultural University. Five treatments were assessed: conventional tillage without fertilizer (C), no-tillage with chemical fertilizer (NT), no-tillage with chemical fertilizer and manure (NTM), conventional tillage with chemical fertilizer (T), and conventional tillage with chemical fertilizer and manure (TM). The results demonstrated that the NTM treatment significantly increased grain yield by 124.95%, NT by 65.88%, TM by 68.97%, and T by 41.75%, compared to the C treatment (p < 0.05). NUE in the NTM treatment was improved by 58.73%–200.59%. Compared with the C treatment, NTM significantly enhanced soil nutrients, including organic matter (OM) by 70.68%, total nitrogen (TN) by 8.81%, total phosphorus (TP) by 211.53%, available nitrogen (AN) by 90.00%, available phosphorus (AP) by 769.12%, and available potassium (AK) by 89.01%. Additionally, the NTM treatment altered the rhizosphere fungal community of winter wheat, with Ascomycota (81.36%–90.24%) being the dominant phylum, followed by Mucoromycota (5.40%–12.83%) and Basidiomycota (1.50%–8.53%). At the genus level, NTM significantly increased the abundance of Mortierella and Dendrostilbella. An α-diversity analysis revealed that the richness and diversity of soil fungi were highest under NTM. The unweighted pair-group method with arithmetic mean (UPGMA) and principal coordinates analysis (PCoA) based on Bray-Curtis distances indicated that NTM formed a distinct fungal community with the highest phylogenetic diversity, which differed significantly from other treatments. Redundancy analysis (RDA) demonstrated that soil chemical properties variably influenced fungal community dynamics, with higher abundances of Ascomycota and Zoopagomycota positively correlated with OM, AN, AP, TP, and AK. Correlation analysis showed that wheat yield and NUE were positively correlated with Mortierella and Dendrostilbella, and negatively correlated with Fusarium, Chaetomium, and Alternaria. In conclusion, no-tillage with manure not only enhanced soil fertility but also enhanced soil fungal community structure, leading to greater wheat yield and NUE. These findings provide guidance for agricultural practices in rainfed wheat fields of the Loess Plateau.
Pathways of Oxygen-Dependent Oxidation of the Plastoquinone Pool in the Dark After Illumination
Authors: Naydov Ilya , Kozuleva Marina , Ivanov Boris , Borisova-Mubarakshina Maria , Vilyanen Daria
Published: December 2024

The redox state of the plastoquinone (PQ) pool in thylakoids plays an important role in the regulation of chloroplast metabolism. In the light, the PQ pool is mostly reduced, followed by oxidation after light cessation. It has been believed for a long time that dark oxidation depends on oxygen, although the precise mechanisms of the process are still unknown and debated. In this work, we analyzed PQ pool oxidation kinetics in isolated pea (Pisum sativum) thylakoids by tracking the changes in the area above the OJIP fluorescence curve (Afl) over time intervals from 0.1 s to 10 min in the dark following illumination. Afl served as an indirect measure of the redox state of the PQ pool that enabled quantification of the rate of PQ pool oxidation. The results showed a two-phase increase in Afl. The “fast” phase appeared to be linked to electron flow from the PQ pool to downstream acceptors of the photosynthetic electron transport chain. The “slow” phase involved oxidation of PQH2 through oxygen-dependent mechanisms. Adding octyl gallate, an inhibitor of plastid terminal oxidase (PTOX), to isolated thylakoid suspensions decreased the rate of the “slow” phase of PQ pool oxidation in the dark after illumination. The addition of either H2O2 or catalase, an enzyme that decomposes H2O2, revealed that H2O2 accelerates oxidation of the PQ pool. This indicates that under conditions that favor H2O2 accumulation, H2O2 can contribute substantially to PQ pool oxidation in the dark after illumination. The contribution of PTOX and H2O2 to the modulation of the PQ pool redox state in plants in the dark after illumination is discussed.
Improving the Structural Efficiency of Punched-Metal-Material-Based Composites
Authors: Lisicins Mihails , Serdjuks Dmitrijs , Akishin Pavel , Mironovs Viktors , Goremikins Vadims , Lapkovskis Vjaceslavs
Published: December 2024

This study investigates the potential of reusing punched-steel waste, a significant component of solid inorganic waste, in composite materials for construction applications. Driven by the growing global demand for raw materials (which is projected to quadruple by 2050) and the need for sustainable waste management practices, this research explores the creation of a composite material (PPLK) incorporating punched-steel tape (LPM-4 grade) embedded in a polypropylene matrix. Experimental testing of PPLK specimens (310 × 90 × 6.30 mm) and finite element analysis (FEA) were employed to evaluate the mechanical properties and stress concentration coefficient. The results show that the PPLK composite exhibits a load-carrying capacity of 21.64 kN, exceeding the sum of its individual components by 11.37%, demonstrating a synergistic effect between the steel (average tensile strength 220.65 MPa) and polypropylene. FEA further revealed that increasing the matrix’s modulus of elasticity to 42 MPa significantly reduces the stress concentration coefficient in the steel component, resulting in a 24% enhancement of the elastic force. The findings suggest a viable path toward sustainable waste management and improved material utilisation in the construction industry.
Polyvinyl Butyral Addition Effects on Notched Charpy Impact Strength of Injection-Molded Glass Fiber-Reinforced Polypropylene
Authors: Takayama Tetsuo , Yuasa Yuuki , Jiang Quan
Published: December 2024

Glass short fiber-reinforced thermoplastics (GSFRTPs) are a cost-effective alternative to other short fiber-reinforced thermoplastics (SFRTPs). Their excellent mechanical properties make them a suitable material for components that require rigidity and light weight in widely diverse fields, including transportation and office automation equipment. The melt-mixing process is used to shorten glass fibers. The notched impact strength of molded products is strongly affected by the fiber length. An important issue is how to conduct melt-molding processing while keeping the fibers long. In this regard, a survey of cases in which additives were used to increase the fiber length revealed no useful reports. However, a growing trend toward the reuse of plastic material wastes has emerged. When reusing GSFRTP wastes, the objective is to recycle the material as GSFRTPs. This promotion of the reuse of GSFRTPs necessitates the production of molded products with the fiber length maintained to the greatest extent feasible. Moreover, GSFRTPs should be recycled in a manner consistent with the original GSFRTPs. In recent years, there has also been a growing movement to reuse polyvinyl butyral (PVB) in accordance with Sustainable Development Goals (SDGs). It has been established that PVB can be extracted from the laminated glass state with high efficiency using mechanical methods. This study evaluated the mechanical properties of GSFRTPs with a PP matrix when PVB was added. The results show that the incorporation of PVB and maleic anhydride-modified PP in quantities of less than 1 wt% into GSFRTPs leads to sizing effects wherein the fibers are dispersed in bundles. Furthermore, this combination enhances the notched impact strength of the resulting molded product by 0.5 kJ/m2 at the maximum.
A Study on the Preparation and Performance of Ultrafine Powder Made of Industrial Hemp Degumming Residue
Authors: Shamim Sarker Md , Huan Yonghe , Gan Linli , Zhang Shangyong
Published: December 2024

Industrial hemp, one of the most widely available and extensively produced varieties, generates a substantial amount of waste in the form of hemp cellulose. This study uses a recycling method combining crushing and acid treatment to convert leftover hemp fiber into ultrafine powder. A scanning electron microscope (SEM), an atomic force microscope (AFM), Fourier transform infra-red spectroscopy (FTIR), and X-ray diffraction (XRD) were used to examine the morphology of acid-treated hemp fiber heated to 200 °C and crushed into powder. The decrease in intensity, fiber surface crystalline, and grain size was analyzed. It became apparent that fiber strength decreased, and fiber roughness significantly increased after acid treatment. The degree of crystallinity of the broken fibers decreased significantly. The proposed method was a simple and effective method for converting leftover hemp fiber into ultrafine powder. In approximately 3 to 5 min, about 1 kg of dry ultrafine powder with a particle size of 38.68 μm was produced. This production method will significantly enhance future industrial applications of hemp residue.
A CFD-Based Decision Matrix for Evacuation Planning: Minimizing Exposure to Hazardous Chemicals
Authors: Jo Seungbum
Published: December 2024

The extent of casualty and property loss due to chemical accidents depends on how well the emergency action plan was established in advance and how fast the warning notice and evacuation orders are given to the public. Assistant methods for the establishment of protective action plans have been developed for several decades. However, the currently developed decision trees are complicated, so they may require a detailed analysis, and previous decision matrices do not consider the indoor and outdoor concentration directly and hence do not allow a change in evacuation order. In this study, five key parameters, report time, toxic cloud arrival/removal time and indoor/outdoor concentration, are selected for the evacuation decision, and the effectiveness of leakage and wind speed on five parameters is investigated. CFD simulations are performed for the various values of mass flow rate and wind speed. Near the release point of toxic gas, the maximum concentration is unaffected by wind speed, but the mass flow rate significantly influences it at low wind speeds. In the far field, the maximum concentration decreases with increasing wind speed. The termination time for shelter-in-place, suggesting a shift to evacuation, decreases with both higher mass flow rate and wind speed. For smaller mass flow rates (m˙=0.1kg/s), indoor concentration exceeds outdoor levels after 25.9 min, while for larger mass flow rates (m˙=2.0kg/s), this time shortens to 15.2 min. Increasing wind speed from 0.5 m/s to 5.0 m/s decreases the equilibrium concentration from 13.9 ppm to 3.4 ppm and reduces the escape time from 48.9 min to 16.0 min. Overall, higher mass flow rates and wind speeds shorten the equilibrium and escape times, improving toxic cloud removal efficiency. Based on the simulation results, a new evacuation decision matrix is developed which minimizes the total exposure concentration. This study provides the proper evacuation time along distance which eventually prevents traffic congestion because of the simultaneous escape rush.
Fault Diagnosis of Mechanical Rolling Bearings Using a Convolutional Neural Network–Gated Recurrent Unit Method with Envelope Analysis and Adaptive Mean Filtering
Authors: Zhu Huiyi , Sui Zhen , Xu Jianliang , Lan Yeshen
Published: December 2024

Rolling bearings are vital components in rotating machinery, and their reliable operation is crucial for maintaining the stability and efficiency of mechanical systems. However, fault detection in rolling bearings is often hindered by noise interference in complex industrial environments. To overcome this challenge, this paper presents a novel fault diagnosis method for rolling bearings, combining Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRUs), integrated with the envelope analysis and adaptive mean filtering techniques. Initially, envelope analysis and adaptive mean filtering are applied to suppress random noise in the bearing signals, thereby enhancing the visibility of fault features. Subsequently, a deep learning model that combines a CNN and a GRU is developed: the CNN extracts spatial features, while the GRU captures the temporal dependencies between these features. The integration of the CNN and GRU significantly improves the accuracy and robustness of fault diagnosis. The proposed method is validated using the CWRU dataset, with the experimental results achieving an average accuracy of 99.25%. Additionally, the method is compared to four classical fault diagnosis models, demonstrating superior performance in terms of both diagnostic accuracy and generalization ability. The results, supported by various visualization techniques, show that the proposed approach effectively addresses the challenges of fault detection in rolling bearings under complex industrial conditions.
Research on Monitoring Methods for Fluid Flow in Strata
Authors: Zhang Feng
Published: December 2024

In many projects, it is important to monitor the direction of groundwater flow, but conventional methods make it difficult. Through streaming potential detection technology, under the action of external pressure, liquid can be forced to flow through solid pores to generate directional flow, and a flow potential can be generated at both ends of solid pores. The phenomenon of different streaming potentials can help engineers determine the direction of fluid flow. In this study, tests were conducted using a core injection system and a streaming potential tester to carry out injections on sandstone samples of two different structures to study the effects of different injection pressures and different salinities on the variation in the streaming potential in sandstone. Moreover, a small-scale field water injection monitoring experiment was also carried out to observe the actual situation of the streaming potential generated during water injection in the field formation structure. The laboratory test results show that the flow potential is accompanied by the liquid injection process in the sandstone sample, and the flow potential produced by the sandstone with different porosities is obviously different, Therefore, the flow potential associated with the actual rock injection process can be used to infer porosity and permeability. This study provides a new method for monitoring underground fluids and is expected to improve the efficiency of oil extraction and geothermal development.
Upcycling Coffee Waste: Key Industrial Activities for Advancing Circular Economy and Overcoming Commercialization Challenges
Authors: Pongsiriyakul Kanokthip , Wongsurakul Peerawat , Kiatkittipong Worapon , Premashthira Aerwadee , Kuldilok Kulapa , Najdanovic-Visak Vesna , Adhikari Sushil , Cognet Patrick , Kida Tetsuya , Assabumrungrat Suttichai
Published: December 2024

The valorization of coffee waste has gained traction due to its potential to generate valuable products, lessen its impact on the environment, and promote sustainability. This review examines the diverse range of coffee waste, including pulp, husk, mucilage, and parchment from the upstream processing of green beans, as well as silverskin (coffee chaff) and spent coffee grounds (SCGs) generated during roasting and brewing. These materials are identified as valuable raw inputs for biorefineries pursuing a bio-circular economy. Recent research has yielded several viable applications for these by-products, categorized into four main areas: (1) agriculture, (2) biofuels and bioenergy, (3) biochemicals and biomaterials, and (4) food ingredients and nutraceuticals. Despite significant advancements in research, the industrial application of coffee waste remains limited. This review summarizes the global commercialization landscape, highlighting that SCGs are particularly advantageous for large-scale upcycling, with applications spanning agriculture, biofuels, and biochemicals. In contrast, coffee husk is primarily utilized in food ingredients and nutraceuticals. The review also addresses the challenges and constraints that must be overcome to facilitate successful commercialization.
Deep Reinforcement Learning-Based Robotic Puncturing Path Planning of Flexible Needle
Authors: Lin Jun , Huang Zhiqiang , Zhu Tengliang , Leng Jiewu , Huang Kai
Published: December 2024

The path planning of flexible needles in robotic puncturing presents challenges such as limited model accuracy and poor real-time performance, which affect both efficiency and accuracy in complex medical scenarios. To address these issues, this paper proposes a deep reinforcement learning-based path planning method for flexible needles in robotic puncturing. Firstly, we introduce a unicycle model to describe needle motion and design a hierarchical model to simulate layered tissue interactions with the needle. The forces exerted by tissues at different positions on the flexible needle are considered, achieving a combination of kinematic and mechanical models. Secondly, a deep reinforcement learning framework is built, integrating obstacle avoidance and target attraction to optimize path planning. The design of state features, the action space, and the reward function is tailored to enhance the model’s decision-making capabilities. Moreover, we incorporate a retraction mechanism to bolster the system’s adaptability and robustness in the dynamic context of surgical procedures. Finally, laparotomy simulation results validate the proposed method’s effectiveness and generalizability, demonstrating its superiority over current state-of-the-art techniques in robotic puncturing.
The Importance of an Interreligious Quranic Hermeneutics for a Gender-Sensitive Reading of the Quran, Using the Example of the Story of the Queen of Sheba
Authors: El Omari Dina
Published: December 2024

This article explores a novel perspective on the Quran by examining its interreligious and intercultural dimensions, challenging traditional readings that often treat it solely as a religious or historical text. By focusing on the Quran’s engagement with diverse religious traditions, the article highlights how the Quran negotiates and reflects its multicultural context. The analysis centers on the story of the Queen of Sheba, revealing how her portrayal disrupts conventional gender roles and provides a unique lens for understanding the Quran’s treatment of gender and religious diversity. Through a comparative study with Jewish intertexts, the article demonstrates that the Quran not only engages with other religious traditions but also incorporates and positively represents figures from these traditions. This approach offers new insights into how interreligious hermeneutics can enhance our understanding of the Quran’s stance on religious plurality and gender dynamics.