bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Interconnected MRAS Parameter Identification for Speed Sensorless Control of Linear Induction Motor
Authors: Hu Hailin , Yu Shiyan , Ren Liangjie , Zhai Mingda , Chen Yuhui
Published: December 2024

After eliminating the speed sensor in the linear induction motor (LIM) high-performance closed-loop control system, the speed feedback information is missing in the speed closed loop. The accuracy of speed observation results is affected by changes in magnetizing inductance and primary resistance. This effect can cause significant oscillations in the results of the speed sensorless control system, preventing them from converging. An enhanced model reference adaptive system (MRAS) multi-parameter parallel identification methodology based on the interconnected second-order super-twisting algorithm (SOSTA) is proposed. To enhance the system’s dynamic performance, we designed an improvement to the MRAS observer based on the SOSTA, with a focus on the LIM state-space equation that considers dynamic edge-end effects. The impact of parameter alterations on the LIM system is examined. To improve speed observation accuracy and system stability, a two-parameter MRAS identification model was created. The Popov hyperstability principle was used to formulate control laws for these two parameters, ultimately enabling the identification of these two parameters. The identified values were fed back to the speed observation and control system, which reduces the coupling of these two parameters and speed. Simulation and hardware-in-the-loop experiments demonstrate that the observation system estimates speed accurately when these two parameters undergo abrupt changes within the rated speed range, enhancing the precision and robustness of the speed sensorless control system.
Ground Motion Modeling and Adaptive Joint Control for Large-Scale UAVs
Authors: Wang Bo , Wang Wensheng , Cui Xiaodan , Liu Xiaoxiong
Published: December 2024

Aiming at the problem of lateral deviation of large-scale long-endurance solar-powered UAVs relative to the runway during takeoff or landing, a UAV ground motion control structure based on the combination of engine differential and rudder was proposed. According to the structural characteristics of large-scale long-endurance solar-powered UAVs, a ground motion model of a three-point layout UAV including landing gear was established, and the ground rolling dynamics and modal characteristics were analyzed. In order to accurately correct the trajectory error, the outer loop designs a trajectory correction control law and gives the inner loop desired control instructions. In order to solve the problem of environmental disturbance and small heading damping, the inner loop adopts the adaptive back-stepping control method. The disturbance signal is estimated through the adaptive law and compensated into the control system to achieve balanced control of speed and rolling correction. Finally, medium-speed and high-speed sliding tests were designed to verify the rationality of the proposed control scheme and control structure, as well as the efficiency of the control law design method adopted.
A Bibliometric Analysis on the Impact of Internal Communication in Post-Pandemic Corporate Environments: A Transversal Survey of Trends and Developments in the Scientific Literature
Authors: Puigvert-Santoro Alba , Arimany-Serrat Nuria , Tarrats-Pons Elisenda
Published: December 2024

The emergence of COVID-19 has boosted internal communication as a central axis in the corporate environment, establishing itself as a key trend in 2024. This article examines the evolution and impact of internal communication in the business world since the appearance of the mentioned virus, with an analysis of selected publications in the months following the pandemic until the present in Scopus and the Web of Science. Through this study, the importance of internal communication in promoting well-being and effective leadership is highlighted, as well as its impact on transforming work practices and corporate culture, offering a detailed understanding of its benefits and added value for both organizations and employees.
Coffee Rust Severity Analysis in Agroforestry Systems Using Deep Learning in Peruvian Tropical Ecosystems
Authors: Ocaña-Zuñiga Candy , Quiñones-Huatangari Lenin , Barboza Elgar , Peña Naili Cieza , Zamora Sherson Herrera , Ojeda Jose Manuel Palomino
Published: December 2024

Agroforestry systems can influence the occurrence and abundance of pests and diseases because integrating crops with trees or other vegetation can create diverse microclimates that may either enhance or inhibit their development. This study analyzes the severity of coffee rust in two agroforestry systems in the provinces of Jaén and San Ignacio in the department of Cajamarca (Peru). This research used a quantitative descriptive approach, and 319 photographs were collected with a professional camera during field trips. The photographs were segmented, classified and analyzed using the deep learning MobileNet and VGG16 transfer learning models with two methods for measuring rust severity from SENASA Peru and SENASICA Mexico. The results reported that grade 1 is the most prevalent rust severity according to the SENASA methodology (1 to 5% of the leaf affected) and SENASICA Mexico (0 to 2% of the leaf affected). Moreover, the proposed MobileNet model presented the best classification accuracy rate of 94% over 50 epochs. This research demonstrates the capacity of machine learning algorithms in disease diagnosis, which could be an alternative to help experts quantify the severity of coffee rust in coffee trees and broadens the field of research for future low-cost computational tools for disease recognition and classification
Assessment Activity Concentrations of Rice Components (Root, Stem, Leaf, and Grain) and Transfer Factors (TF) from Paddy Soil to Rice Grain of Radionuclides 40K, 226Ra, 232Th, and 137Cs Investigation in Taiwan
Authors: Huang Wei-Hsiang , Chen Ting-Chien , Lin Sheng-Chi , Chen Zhi-Mou , Yeh Yi-Lung
Published: December 2024

This study analyzed the activity concentrations of various radionuclides in irrigation water, rice components, and corresponding soil samples from eleven paddy fields, revealing significant findings with potential environmental and health implications. The soil exhibited high levels of activity concentrations ranging from 350 to 829, 12.4 to 41.2, and 18.5 to 60.3 Bq/kg, with mean values of 609, 31.1, and 45.0 Bq/kg for 40K, 226Ra, and 232Th respectively. Additionally, 12 soil samples from two paddy fields showed 137Cs activity concentrations of 5.6 ± 1.3 Bq/kg. The rice plant roots accumulated the highest percentages of total activity concentrations for 226Ra, 232Th, and 137Cs, ranging from 76–86%, while only 1.1–10.0% were found in the un-hulled grain. For 40K, activity concentrations were distributed among the root (23%), stem (32%), leaf (35%), and un-hulled grain (10%). The mean activity concentrations were 99 ± 12, 0.49 ± 0.09, 0.43 ± 0.12, and 0.10–0.31 Bq/kg for 40K, 226Ra, 232Th, and 137Cs for un-hulled rice grain, respectively. Transfer factors (TFs) from soil to un-hulled rice grain were calculated as (1.21–2.86) × 10−1 for 40K, (0.07–0.11) × 10−1 for 232Th, (0.11–0.29) × 10−1 for 226Ra, and (0.16–0.61) × 10−1 for 137Cs. Notably, significant negative correlations were observed between TFs and soil concentrations for 40K (r = 0.92, p < 0.001, n = 11) and 226Ra (r = 0.98, p = 0.026, n = 4), suggesting that macronutrients in soil solutions may inhibit the linear transfer of natural nuclides from the soil solution to rice plants.
Design and Experimental Research on Staggered Straw Cleaning Device for No-Till Seeding in Drip Irrigation Area
Authors: Yuan Panpan , Zhu Xingliang , Zhang Xuejun , You Jia , Yan Jinshan , Qiu Shilong
Published: December 2024

To solve the problem of straw cleaning and drip irrigation belt restoration for no-till seeding in drip irrigation areas, a staggered straw cleaning device was developed for no-till seeding, which is mainly composed of a front two-sided tine discs group, a drip irrigation belt laying mechanism, a middle single inner tine discs group, a rear single outer tine discs group. Different tine disc groups are set in longitudinal, transverse, and radial directions to move and throw the straw on the surface of the seeding strip. The critical parameters of the tine disc were designed and calculated, and the radius was determined to be 160 mm, the number of teeth was 12, and the theoretical working width was obtained. The movement and straw scattering process were analyzed, and the main influencing factors and the maximum straw scattering distances in the horizontal and vertical directions were determined. The interaction model of staggered tine discs group–straw–soil is established using the discrete element method (DEM). The forwarding speed, rotating speed, disc rake angle, and lateral distance of the middle tine discs were used as influencing factors, and the straw cleaning rate and the mass of straw returned in the drip irrigation coverage area were selected as the text indexes to carry out quadratic orthogonal rotation experiments. The quadratic regression model of the three sensitive parameters on the cleaning rate and the mass of straw returned in the drip irrigation coverage area was constructed and optimized. The optimal solutions were obtained: the forwarding speed was 9 km/h, the disc rake angle was 33.7°, and the lateral distance of the middle tine discs was 529 mm. The field validation test was carried out, and the results showed that the straw cleaning was 89.13%, the straw cleaning width of the seed strip was 527.2 mm, and the straw coverage rate of the drip irrigation area was 80.74%. This achievement can provide a reference for straw cleaning of no-till seeding under drip irrigation.
Screening and Identification of Cold-Tolerant Phosphorus and Potassium Solubilizing Bacteria and Their Growth-Promoting Effects on Soybean in Cold Regions
Authors: Yan Hao , Wang Tianyi , Wang Haocheng , Sun Nan , Wang Xuebing , Zhao Xingbo , Yao Zhongbao , Tian Hao , Chen Shengjie , Tang Songyan , Li Chenyang
Published: December 2024

In this study, we collected soybean inter-root soil (clay soil) from the cold region of Heilongjiang Province, China, screening for cold-tolerant phosphorus- and potassium-solubilizing bacteria by the gradient-cooling-directed screening and design of mixed bacterial agents. This study screened cold-tolerant phosphorus-solubilizing and potassium-solubilizing bacteria by gradient-cooling-directed screening and constructed mixed bacterial agents. We analyzed the strain’s phosphorus/potassium solubilizing capacity, as well as its organic acid secretion ability, to reveal its mechanism of detoxification of phosphorus and potassium. Clay soil from the cold region of Heilongjiang, China, was collected for soybean potting trials. The soybean pot experiment was used to investigate the growth-promoting effects of cold-tolerant strains applied to soybeans and to analyze the effects of changes in soil bacterial activity on soybean growth. A dominant phosphorus-solubilizing bacteria strain P-5 (Pantoea ananatis) was screened, and the amount of phosphorus-solubilizing bacteria was 34.94 mg/L with a PSI (Phosphorus Solubilization Index) of 1.80 for 7 days of incubation at 15 °C. The OD600 value (optical density of 600 nm) on the 10th day was 0.61. The dominant potassium-solubilizing bacteria, K-1 (Rahnella aquatilis), solubilized 23.02 mg/L of potassium under the same culture conditions, with a KSI (Potassium Solubilization) of 1.51 and an OD600 value of 0.59 on day 10. The dominant mixed bacterial agents H-5 (25% P-5 and 75% K-1), designed with the above two, detoxified phosphorus at 62.58 mg/L and potassium at 37.59 mg/L under the same culture conditions. It was shown that P-2 secretes gluconic acid and P-5 secretes lactic acid to degrade insoluble phosphorus at low temperatures and that K-1 secretes citric acid to degrade insoluble potassium. The soybean pot experiment study showed that the application of phosphorus-solubilizing bacteria (PSB), potassium-solubilizing bacteria (KSB), and mixed bacterial agents (MSB) alone could enhance the relative abundance of Pseudomonas, Rhizobium, and other bacterial genera in the soybean planting soil, compared with the control treatment without bacterial agents (BLK). Indirectly, they can enhance the accumulation of phosphorus and potassium in various organs of soybean, promote the development of soybean leaves and stems, and achieve the effect of promoting production and increasing income. This study has important theoretical value for the replacement of chemical fertilizer application by microbial agents in the cold region of China, and it has important practical and strategic significance for the promotion of income green safety in China’s main grain-producing areas.
Animal as the Solution II: Phenotyping for Low Milk Urea Nitrogen A1PF Dairy Cows
Authors: Pereira Fabiellen C. , Kumara Sagara , Fleming Anita , Lai Shu Zhan , Wilson Ella , Gregorini Pablo
Published: December 2024

The societal pressure on intensive pastoral dairying demands the search for strategies to reduce the amount of N flowing through and excreted by dairy cows. One of the strategies that is being currently explored focuses on the animal as a solution, as there are differences in N metabolism between cows even within the same herd. This work was conducted to explore such an approach in A1PF herds in New Zealand and the possibility of identifying A1PF cows that are divergent for milk urea nitrogen (MUN) concentration through phenotyping as a potential viable strategy to reduce N leaching and emissions from temperate dairy systems. Three herd tests were conducted to select a population sample of 200 cows (exhibiting the lowest 100 and highest 100 MUN concentrations). Milk samples were collected from the 200 cows during mid and late lactation to test for milk solids content and MUN. From the 200 cows, urine for urinary N concentration (UN), blood for plasma urea N, total antioxidants (TAS), and glutathione peroxidase (GPx) were collected from the 20 extremes (the lowest 10 and highest 10 MUN concentrations). Milk urea N was greater in cows selected as high-MUN cows (16.2 vs. 14.32 ± 0.23 mg/dL) and greater during late lactation (16.9 vs. 13.0 ± 0.19 mg/dL). Milk solids and fat content were 38% and 20% greater in cows selected as low-MUN cows than in high-MUN cows during mid lactation (p < 0.001). Low-MUN cows had lower UN than high-MUN cows during mid lactation (0.64 vs. 0.88 ± 0.11%). The N concentration in the plasma (p = 0.01) and Tas (p = 0.06) were greater during late lactation. There was a positive relationship between the MUN concentration phenotype used for selection and the MUN concentration for the trial period and MUN concentration and UN concentration during mid and late lactation (p < 0.001). Our results suggest that A1PF cows within a commercial herd can be phenotyped and selected for low-MUN, which may be potentially a viable strategy to reduce N losses to the environment and create healthier systems. Following genetic tracking, those cows can be bred to further promote low-MUN A1PF herds.
Rumen-Degradable Starch Improves Rumen Fermentation, Function, and Growth Performance by Altering Bacteria and Its Metabolome in Sheep Fed Alfalfa Hay or Silage
Authors: Guo Wenliang , Na Meila , Liu Shuwei , Li Kenan , Du Haidong , Zhang Jing , Na Renhua
Published: December 2024

Alfalfa silage due to its high protein can lead to easier feeding management, but its high proportion of rumen-degradable protein can reduce rumen nitrogen utilization. Nevertheless, increasing dietary energy can enhance ruminal microbial protein synthesis. Thirty-two Suffolk female sheep were used in this study, with a 2 × 2 factorial arrangement of treatment. The four treatments were a combination of two forage types (alfalfa hay; AH vs. alfalfa silage; AS) and two rumen-degradable starch levels (low RDS; LR vs. high RDS; HR) with a 15 d adaptation and 60 d experimental period. The rumen content and rumen epithelium samples were collected after slaughter. Feeding AS increased the rumen isobutyrate, valerate, ammonia-N (NH3-N) concentration, urase activity, and papillae height (p < 0.05) and reduced the feed to gain (F:G), rumen bacterial protein (BCP), rumen lactic acid concentration, and papillae width (p < 0.05) of sheep. Increased RDS in the diet improved the daily matter intake, average daily gain, and rumen weight, reduced the F:G, and enhanced the rumen nitrogen capture rate by decreasing total amino acids and the NH3-N concentration to increase BCP, aquaporins 3 gene, and protein expression. The rumen microbiota also changed as the HR diet reduced the Chao index (p < 0.05). The metabolomics analysis showed that feeding AS upregulated the rumen tryptophan metabolism and steroid hormone biosynthesis, while the purine metabolism, linoleic acid metabolism, and amino acid biosynthesis were downregulated. Furthermore, increased RDS in the diet upregulated rumen lysine degradation and sphingolipid metabolism, while aromatic amino acid biosynthesis was downregulated. Additionally, the correlation analysis results showed that ADG was positively correlated with 5-aminopentanoic acid, and three microorganisms (unclassified_f__Selenomonadaceae, Quinella, Christensenellaceae_R-7_group) were positively correlated with the rumen isobutyrate, valerate, NH3-N concentration, urase activity, tryptophan metabolism, and steroid hormone biosynthesis and negatively correlated with linoleic acid metabolism and amino acid biosynthesis in sheep. In summary, increased RDS in the diet improved the growth performance and rumen N utilization and reduced bacterial diversity in sheep. The alfalfa silage diet only increased feed efficiency; it did not affect growth performance. Additionally, it decreased rumen nitrogen utilization, linoleic acid, and amino acid biosynthesis. Nevertheless, there were limited interactions between forage and RDS; increased RDS in the AS diet enhanced the nitrogen capture rate of rumen microorganisms for alfalfa silage, with only slight improvements in the purine metabolism, linoleic acid, and amino acid synthesis.
Whole-Genome Resequencing to Identify Selection Signatures Associated with High Fertility in Lüliang Black Goat
Authors: Wang Xu , Zhou Zhenqi , Chai Xinrui , Li Jie , Wang Wannian , Pang Zhixu , Cheng Lifen , Cheng Caihong , Qiao Liying , Pan Yangyang , Yang Kaijie , Liu Wenzhong , Liu Jianhua
Published: December 2024

Lüliang black goat (LBG) is a unique livestock genetic resource of great significance for the local agriculture and economic development of Shanxi, China. However, the kidding rate of LBG is relatively low, which limits efforts to improve the reproductive performance and economic benefits of this breed. Therefore, improving the kidding characteristics of LBG is crucial for increasing its economic benefits. In this study, 20 LBG does were selected for whole-genome resequencing and divided into two groups: 10 in the T group (does with three consecutive kiddings of twin kids) and 10 in the S group (does with three consecutive kiddings of single kids). Based on whole-genome resequencing data, this study comprehensively assessed the population structure and genetic diversity of LBG and explored the related genes that affect reproductive performance. Three selection signal analysis methods—Fst (Fixation Index), π (nucleotide diversity), and XP-CLR (Cross Population Composite Likelihood Ratio)—were applied to screen a total of 838 genes, and enrichment analysis was performed to identify genes closely related to the reproductive performance of LBG, including ENPP3, APC, and GLI2. A generalized linear model was used to conduct a correlation analysis between non-synonymous mutations in the three genes and the number of kids produced. Two loci that were significantly correlated with kidding number were identified (p < 0.05): GLI2 g.63400363 C>T and GLI2 g.63417538 C>T. In general, the LBG population has high genetic diversity and good prospects for genetic improvement. The findings revealed that mining high-fecundity selection characteristics provides a basis for research on goat reproductive mechanisms.
Links Between Variation in Movement-Based Visual Signals and Social Communication Complexity in an Asian Agamid Lizard Phrynocephalus vlangalii
Authors: Liu Jian , Hu Qiaohan , Qi Yin
Published: December 2024

The social complexity hypothesis suggests that complex social interactions drive the evolution of sophisticated communicative signals. While the relationship between social communication and the complexity of sound and color signals has been extensively studied, the correlation between social communication and movement-based visual signal complexity remains underexplored. In this study, we selected the Asian agamid lizard, Phrynocephalus vlangalii, as our model system. Through a combination of controlled experiments, behavioral observations, and signal quantification, we examined the relationship between social communications and variation in movement-based visual signals and tested our social complexity hypothesis. Our experiments revealed that males significantly decreased the tail coil duration during the mating season to deal with high social interaction. Conversely, females significantly increased the tail display duration and variation in mean tail coil amplitude in line with the intensity of parental care, and tail display duration showed a significant and positive correlation with female reproductive investment. These findings suggest that social communication plays an important role in shaping the changes in movement-based visual signals, providing new evidence for the social complexity hypothesis.
Identification and Functional Analysis of miRNAs in Extracellular Vesicles of Semen Plasma from High- and Low-Fertility Boars
Authors: Chen Weidong , Xie Yanshe , Xu Zhiqian , Shang Yijun , Yang Wenzheng , Wang Pengyao , Wu Zhenfang , Cai Gengyuan , Hong Linjun
Published: December 2024

Artificial insemination (AI), as an efficient assisted reproduction technology, can help the livestock industry to improve livestock and poultry breeds, optimize production performance and improve reproductive efficiency. AI technology has been widely used in pig production in China, but boar fertility affects the effectiveness of AI, and more and more studies have shown that there are significant differences in the fertility of boars with similar semen quality indicators. Therefore, this study aimed to identify biomarker molecules that indicate the level of boar fertility, which is important for improving the efficiency of AI. In this study, we collected 40 mL of ejaculates per boar used for extracellular vesicle (EV) characterization in 20 boars and identified 53 differentially expressed miRNAs by small RNA sequencing, of which 44 miRNAs were up-regulated in the high-fertility seminal EVs compared with low-fertility seminal EVs, and nine miRNAs were down-regulated. miR-26a was most significantly down-regulated in the high-fertility group compared to the low-fertility group, and it was hypothesized that this miRNA could be used as a biomolecular marker of semen reproductive performance. To further determine the effect of miR-26a on sperm function, we successfully established a miR-26a overexpression model and found that miR-26a reduced sperm viability, motility, acrosome integrity, plasma membrane integrity and ATP levels. Bioinformatics analysis and dual luciferase reporter analysis revealed that miR-26a directly targets High mobility group A1 (HMGA1). In conclusion, miR-26a can be used as a biomarker to identify high and low fertility in boar semen.
Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models
Authors: Ma Weihong , Wang Xingmeng , Yang Simon X. , Song Lepeng , Li Qifeng
Published: December 2024

The stable physiological structure and rich vascular network of pig ears contribute to distinct thermal characteristics, which can reflect temperature variations. While the temperature of the pig ear does not directly represent core body temperature due to the ear’s role in thermoregulation, thermal infrared imaging offers a feasible approach to analyzing individual pig status. Based on this background, a dataset comprising 23,189 thermal infrared images of pig ears (TIRPigEar) was established. The TIRPigEar dataset was obtained through a pig house inspection robot equipped with an infrared thermal imaging device, with post-processing conducted via manual annotation. By labeling pig ears within these images, a total of 69,567 labeled files were generated, which can be directly used for training pig ear detection models and enabling the analysis of pig temperature information by integrating the corresponding thermal imaging data. To validate the dataset’s utility, it was evaluated across various object detection algorithms. Experimental results show that the dataset achieves the highest precision, recall, and mAP50 on the YOLOv9m model, reaching 97.35%, 98.1%, and 98.6%, respectively. Overall, the TIRPigEar dataset demonstrates optimal performance when applied to the YOLOv9m algorithm. Utilizing thermal infrared imaging technology to detect pig ear information provides a non-contact, rapid, and effective method. Establishing the TIRPigEar dataset is highly significant, as it allows for a valuable resource for AI and precision livestock farming researchers to validate and improve their algorithms. This dataset will support many researchers in advancing precision livestock farming by enabling an efficient way for pig ear temperature analysis.
Effects of the Maximum Recommended Levels of Fumonisins in the EU on Oxylipin Profiles in the Liver and Brain of Chickens
Authors: Guerre Philippe , Lassallette Elodie , Guerre Amélie , Tardieu Didier
Published: December 2024

This study aimed to assess the effects of a diet containing 20.8 mg FB1 + FB2/kg over four and nine days on oxylipin (OL) profiles in the liver and brain of chickens. A total of 96 OLs, derived from seven polyunsaturated fatty acids (PUFAs) via the cyclooxygenase (COX), lipoxygenase (LOX), cytochrome P450 (P450), and non-enzymatic pathways, were measured using HPLC-MS/MS. In the liver, a significant increase in epoxide P450-derived OLs was detected by day 4, with smaller but notable increases in COX- and LOX-derived OLs by day 9. These alterations were independent of whether the parent PUFA was ω6 or ω3. However, OLs derived from 18-carbon (C18) PUFAs, such as linoleic acid and alpha-linolenic acid, showed greater increases compared to those derived from C20 or C22 PUFAs. The diol/epoxide ratios in the liver decreased at four and nine days, suggesting that fumonisins did not induce an inflammatory response. In the brain, at four days, the most discriminative OLs were derived from ω3-PUFAs, including docosahexaenoic acid, docosapentaenoic acid, and alpha-linolenic acid, via the LOX pathway. By nine days, several OLs derived from arachidonic acid, spanning all enzymatic pathways, became discriminative. In general, the diol/epoxide ratios in the brain were decreased at 4 days and then returned to the initial levels. Taken together, these results show strong effects of fumonisins on OLs in the liver and brain that are both specific and distinct.
Therapeutic Potential of Herbal Medicines in Combating Particulate Matter (PM)-Induced Health Effects: Insights from Recent Studies
Authors: Intharuksa Aekkhaluck , Arunotayanun Warunya , Takuathung Mingkwan Na , Boongla Yaowatat , Chaichit Siripat , Khamnuan Suthiwat , Prasansuklab Anchalee
Published: December 2024

Particulate matter (PM), particularly fine (PM2.5) and ultrafine (PM0.1) particles, originates from both natural and anthropogenic sources, such as biomass burning and vehicle emissions. These particles contain harmful compounds that pose significant health risks. Upon inhalation, ingestion, or dermal contact, PM can penetrate biological systems, inducing oxidative stress, inflammation, and DNA damage, which contribute to a range of health complications. This review comprehensively examines the protective potential of natural products against PM-induced health issues across various physiological systems, including the respiratory, cardiovascular, skin, neurological, gastrointestinal, and ocular systems. It provides valuable insights into the health risks associated with PM exposure and highlights the therapeutic promise of herbal medicines by focusing on the natural products that have demonstrated protective properties in both in vitro and in vivo PM2.5-induced models. Numerous herbal medicines and phytochemicals have shown efficacy in mitigating PM-induced cellular damage through their ability to counteract oxidative stress, suppress pro-inflammatory responses, and enhance cellular defense mechanisms. These combined actions collectively protect tissues from PM-related damage and dysfunction. This review establishes a foundation for future research and the development of effective interventions to combat PM-related health issues. However, further studies, including in vivo and clinical trials, are essential to evaluate the safety, optimal dosages, and long-term effectiveness of herbal treatments for patients under chronic PM exposure.
A Dynamic Measurement System Based on Adaptive Clustering and Multi-Classifier
Authors: Shi Bowen , You Hongjian , Wang Huixian
Published: December 2024

This technology is highly suitable for detecting and tracking multi-skeletal targets in the field of aerial refueling. The paper presents a target feature responder based on K-means clustering, used for categorizing samples and training models. It employs a decision function to optimize the localization region across various classifier detection and tracking algorithms for targets. Additionally, a state judgment module scores the classifiers based on target state and depth information, which allows for adaptive selection of the classifier. To address the issue of missing target information, the method incorporates a stereo-vision-based mechanism to complete the localization region. This approach effectively handles challenges related to target appearance deformation, significant scale variations, motion blur, and occlusions.
Efficient Fine-Tuning of Large Language Models via a Low-Rank Gradient Estimator
Authors: Zhang Luoming , Lou Zhenyu , Ying Yangwei , Yang Cheng , Zhou Hong
Published: December 2024

In this paper, we present a Low-Rank Gradient Estimator (LoGE) to accelerate the finetune-time computation of transformers, especially large language models (LLMs). Unlike Parameter-Efficient Fine-Tuning (PEFT) methods, which primarily aim to minimize the number of fine-tuning parameters, LoGE also significantly reduces the computational load of activation gradient calculations by decomposing pre-trained weights and utilizing low-rank matrices during the backward pass. Our approach includes an effective solution for identifying sensitive and important latent subspaces in large models before training with downstream datasets. As LoGE does not alter the network structure, it can be conveniently integrated into existing models. We validated LoGE’s efficacy through comprehensive experiments across various models on various tasks. For the widely used LLaMA model equipped with LoRA, LoGE achieves up to a 1.3× speedup while maintaining graceful accuracy.
Study on the Influence of Collision Scene on the Energy Dissipation Process for Train Collision
Authors: Guo Lirong , Zhang Jingke , Zhu Tao , Xiao Shoune , Liu Yanwen , Li Benhuai
Published: December 2024

Orderly and controllable dissipation of impact kinetic energy is the key to ensuring train collision safety in different collision scenarios. Therefore, it is necessary to analyze the change rule of collision energy dissipation under different collision scenarios and design the parameters of the energy-absorbing structure to meet the demand for collision energy dissipation. Four representative train collision scenarios are formulated based on train collision accidents, and the concept of energy dissipation rate is proposed to characterize the drastic degree of collision energy change under different collision scenarios. Based on the train longitudinal collision dynamics model verified by the line collision test of the train, the effects of varying collision scenarios on the energy dissipation rate, energy absorption and maximum average acceleration of train collision are studied. The study results show that the longitudinal collision dynamics model of the train established in this paper can better characterize the dynamic response of the vehicle by comparing it with the results of the line collision test. The maximum difference in the speed of each vehicle after the collision is 4.91%. The differences in the energy dissipation process, interface energy absorption and maximum average acceleration are minor in four collision scenarios, including a moving train hitting a stationary train, rear-end train collision and head-on train collision. The maximum difference in energy absorbed at the interface for head-on collision is 1.54%. The initial and residual collision kinetic energy is greater in the train rear-end collision scenario, and the train rear-end collision scenario should be considered when evaluating the train’s lateral instability and vertical climbing behavior.
Evidence for Proximity Effect in Superconductor–Organic Semiconductor–Superconductor Stacked Devices
Authors: Kremen Anna , Aviv Hagit , Tischler Yaakov Raphael , Sharoni Amos
Published: December 2024

Coupling superconducting (SC) contacts to light-emitting layers can lead to remarkable effects, as seen in inorganic quantum-well LEDs with superconducting contacts, where an enhancement in radiative recombination was observed. Additional dramatic effects were theorized if both electrodes are SC, such as correlated emission and 2-photon entanglement. Motivated by this and by the question of whether proximity induced SC is possible in organic light-emitting materials, we studied the electronic properties of stacked SC–organic–SC devices. Our structures consisted of Nb (bottom) and NbN (top) SC electrodes and a spin-coated light-emitting semiconductor polymer, MEH-PPV. Sputtering the SC directly on the polymer causes pinholes, which we prevent by ultra-slow deposition of a 5 nm aluminum film, before depositing the top SC in situ. The Al protects the organic film from damage and pinhole formation, while preserving SC in the top electrodes due to the proximity effect between Al and NbN. Electrical transport measurements of the completed junctions indicate that indeed, the top and bottom contacts are superconducting and the protected MEH-PPV layer is pinhole-free, as supported by HR-TEM and EDS. Most importantly, we find that as the temperature is decreased below the critical temperature of the SCs, the device shows evidence for the proximity effect in the MEH-PPV.
A Rule-Based Parser in Comparison with Statistical Neuronal Approaches in Terms of Grammar Competence
Authors: Strübbe Simon M. , Grünwald Alexander T. D. , Sidorenko Irina , Lampe Renée
Published: December 2024

The “Easy Language” standard was created to help individuals with cognitive disabilities understand texts more easily. Typically, text simplification is performed by language experts and is available for limited materials. We introduce a new software tool designed to analyze and simplify any text according to the “Easy Language” rules. This tool uses a rule-based system, conducting a full grammatical analysis of each sentence and then simplifying it into a grammatically correct form. Unlike neuronal approaches, which are based on statistics and are very popular today, our rule-based approach explicitly addresses language ambiguities by examining all possible interpretations and eliminating the incorrect ones. The purpose of the present study is to compare the performance of our rule-base parser with two state-of-the-art statistical parsers, one based on dependencies between words (SpaCy parser) and the other based on linguistic constituents (Stanford parser). Although large language models (LLMs), which are the technical basis of the software ChatGPT, were not designed specifically for grammatical parsing, because of their popularity, users, especially language learners, often ask them grammatical questions as well. Therefore, we use LLMs as supplementary models for comparison. LMMs produce grammatically correct text on any topic; however, their grammar knowledge is implicit within the trained weights. To evaluate how well state-of-the-art methods can perform a grammatical analysis, we parse ten sentences with our tool, the statistical parsers from SpaCy and Stanford, and ask two LLMs equivalent grammar questions. The results show that our rule-based method provides a more informative and reliable grammatical analysis compared to these two parsers and outperforms LLMs in that specific task.
3L-YOLO: A Lightweight Low-Light Object Detection Algorithm
Authors: Han Zhenqi , Yue Zhen , Liu Lizhuang
Published: December 2024

Object detection in low-light conditions presents significant challenges due to issues such as weak contrast, high noise, and blurred boundaries. Existing methods often use image enhancement to improve detection, which results in a large amount of computational resource consumption. To address these challenges, this paper proposes a detection method, 3L-YOLO, based on YOLOv8n, which eliminates the need for image enhancement modules. First, we introduce switchable atrous convolution (SAConv) into the C2f module of YOLOv8n, improving the model’s ability to efficiently capture global contextual information. Second, we present a multi-scale neck module that aggregates shallow features and incorporates a channel attention mechanism to prioritize the most relevant features. Third, we introduce a dynamic detection head, which employs a cascade of spatial, scale, and channel attention mechanisms to enhance detection accuracy and robustness. Finally, we replace the original loss function with MPDIoU loss, improving bounding box regression and overall reliability. Additionally, we create a synthetic low-light dataset to evaluate the performance of the proposed method. Extensive experiments on the ExDark, ExDark+, and DARK FACE datasets demonstrate that 3L-YOLO outperforms YOLOv8n in low-light object detection, with improvements in mAP@0.5 of 2.7%, 4.3%, and 1.4%, respectively, across the three datasets. In comparison to the LOL-YOLO low-light object detection algorithm, 3L-YOLO requires 16.9 GFLOPs, representing a reduction of 4 GFLOPs.
Effects of Active Video Games Combined with Conventional Physical Therapy on Perceived Functionality in Older Adults with Knee or Hip Osteoarthritis: A Randomized Controlled Trial
Authors: Guede-Rojas Francisco , Mendoza Cristhian , Fuentes-Contreras Jorge , Alvarez Cristian , Agurto Tarbes Bárbara , Muñoz-Gutiérrez Javiera Karina , Soto-Martínez Adolfo , Carvajal-Parodi Claudio
Published: December 2024

Background: Osteoarthritis (OA) leads to functional decline in older adults. This study aimed to evaluate the effectiveness of active video games (AVGs) as a complement to conventional physical therapy (CPT) in improving functional disability. Methods: Sixty participants were randomly assigned to an experimental group (EG, n = 30, 68.7 ± 5.4 years), which received CPT combined with AVGs, or to a control group (CG, n = 30, 69.0 ± 5.5 years), which received CPT alone. Sessions were performed three times a week for ten weeks. Functional disability was assessed using the WOMAC index before, during, and after the intervention. Secondary outcomes included the Global Rating of Change (GRoC), the Minimal Clinically Important Difference, and patient trajectories through functional disability strata. Results: The EG showed progressive improvements in all WOMAC scores, with moderate to large increases by the end of the intervention, while the CG only showed significant changes in the later stages. The EG demonstrated greater improvements in WOMAC pain and the GroC scale (p < 0.05), maintaining most of the gains at follow-up, whereas the CG showed regression. Additionally, the EG had a higher proportion of responders, particularly for pain, while the CG had a predominance of non-responders and adverse responders. In the EG, 70% improved their functional disability stratification compared to 50% in the CG. Conclusion: Integration of AVGs with CPT further improves perceived functional disability in older adults with OA. Future research should explore these findings further.
High-Frequency Workpiece Image Recognition Model Based on Hybrid Attention Mechanism
Authors: Deng Jiaqi , Sun Chenglong , Liu Xin , Du Gang , Jiang Liangzhong , Yang Xu
Published: December 2024

High-frequency workpieces are specialized items characterized by complex internal textures and minimal variance in properties. Under intricate lighting conditions, existing mainstream image recognition models struggle with low precision when applied to the identification of high-frequency workpiece images. This paper introduces a high-frequency workpiece image recognition model based on a hybrid attention mechanism, HAEN. Initially, the high-frequency workpiece dataset is enhanced through geometric transformations, random noise, and random lighting adjustments to augment the model’s generalization capabilities. Subsequently, lightweight convolution, including one-dimensional and dilated convolutions, is employed to enhance convolutional attention and reduce the model’s parameter count, extracting original image features with robustness to strong lighting and mitigating the impact of lighting conditions on recognition outcomes. Finally, lightweight re-estimation attention modules are integrated at various model levels to reassess spatial information in feature maps and enhance the model’s representation of depth channel features. Experimental results demonstrate that the proposed model effectively extracts features from high-frequency workpiece images under complex lighting, outperforming existing models in image classification tasks with a precision of 97.23%.
Encryption of 3D or Higher-Dimensional Images: A Review
Authors: Nigro Renatta , Ferreira Gabriel , Calazans Maria Alice Andrade , Miguel Geovane , Ferreira Felipe Alberto B. S. , Severo Verusca , Madeiro Francisco
Published: December 2024

This article aims to review encryption techniques for 3D or higher-dimensional images. Precisely, the following classes of images are considered: light field images, point clouds, and 3D medical images. The security and performance aspects of the encryption schemes for images are analyzed. It is observed that the number of papers with encryption in the transform domain exceeds the number of papers with encryption in the spatial domain. Additionally, it is observed that the application of encryption does not predominate in all the dimensions of the images, that is, the encryption does not occur completely in the image but rather through slices or sections. This review article summarizes several issues related to encryption techniques, technical perspectives for the future, and gaps in the literature.
Influence of Low-Temperature Stress-Relieving Treatment in the Fatigue Life of Components Produced by Laser Powder Bed Fusion in AlSi10Mg
Authors: António Malcolm , Fernandes Rui , Jesus Joel de , Borrego Luís , Branco Ricardo , Costa José da , Ferreira José
Published: December 2024

This study investigates the impact of low-temperature stress-relieving treatment on the fatigue life of AlSi10Mg components produced by Laser Powder Bed Fusion (L-PBF). The research focuses on a bicycle crank arm, comparing its performance in as-built and heat-treated conditions. The heat treatment involved stress-relieving at 250 °C for 2 h, followed by water quenching. The study found that the as-built condition exhibited a supersaturated Si cellular-dendritic microstructure, while the heat-treated condition showed coarsening of β-Mg2Si phases and Si precipitates. This morphological change led to a decrease in hardness and an increase in ductility. Fatigue tests demonstrated that the heat-treated crank arms achieved the target of 100,000 cycles without failure, unlike the as-built samples, which failed prematurely. The fractography analysis identified surface porosity as the primary crack initiation site. The findings suggest that low-temperature stress-relieving treatment can enhance the fatigue performance of L-PBF AlSi10Mg components by reducing residual stresses and improving defect tolerance.
Design Limitations of Laboratory Solar Chimney for Engineering Education
Authors: Glavaš Hrvoje , Jukić Dina , Barić Tomislav , Šplajt Luka
Published: December 2024

This paper presents numerical and experimental investigations of a small-scale solar chimney power plant with a tower height of 50 cm. Numerical thermodynamic analysis was carried out in the ANSYS 2022 R1 (22.1) software, and the results were compared with the mathematical model of the Manzanares prototype. The results indicate that there is a geometry limit for which boundary physics overcomes the resultant upward force. Upon obtaining initial parameters in CAD and CFD software, further experimental measurements were conducted on a physical model enhanced with fans to induce the air flow in accordance with the Nyquist criterion. The structure could not withstand the mechanical force needed for continuous turbine rotation.
A Blockchain Network Admission Control Mechanism Using Anonymous Identity-Based Cryptography
Authors: Zhang Haibao , Jiang Wenbao , Ding Jin
Published: December 2024

Permissioned blockchains are increasingly used in areas like supply chain management, financial transactions, and medical data sharing, where ensuring data consistency and security is critical. However, these systems are vulnerable to threats such as DDoS attacks, forged transactions, and certificate authority compromises, primarily due to inadequate network layer admission control. Existing solutions, like static whitelisting, struggle with scalability and adaptability in dynamic environments. This paper proposes a novel admission control mechanism based on identity-based cryptography, utilizing multi-level anonymous identifiers and decentralized private key generation to enhance user authentication and privacy. The mechanism dynamically updates whitelists and selectively filters network traffic, ensuring a balance between security and performance. Experimental results validate its effectiveness in mitigating key threats while maintaining operational efficiency.