bluuebunny/crossref_metadata_2025 huggingface dataset:
Pochonia chlamydosporia synergistically supports systemic plant defense response in Phacelia tanacetifolia against Meloidogyne hapla
Authors: Könker Jana , Zenker Sanja , Meierhenrich Anja , Patel Anant , Dietz Karl-Josef
Published: January 2025

The network of antagonistic, neutral, and synergistic interactions between (micro)organisms has moved into the focus of current research, since in agriculture, this knowledge can help to develop efficient biocontrol strategies. Applying the nematophagous fungus Pochonia chlamydosporia as biocontrol agent to manage the root-knot nematode Meloidogyne hapla is a highly promising strategy. To gain new insight into the systemic response of plants to a plant-parasitic nematode and a nematophagous fungus, Phacelia was inoculated with M. hapla and/or P. chlamydosporia and subjected to transcriptome and metabolome analysis of leaves. While the metabolome proved quite stable except for the early time point of 48 h, comparison of the single P. chlamydosporia with the combined treatment revealed even larger effects after 6 d compared to 48 h, aligning with the later root infestation by P. chlamydosporia compared to M. hapla. Simultaneous exposure to both microorganisms showed a stronger overlap with the single M. hapla treatment than P. chlamydosporia. Changes of transcripts and metabolites were higher in the combined treatment compared to the individual inoculations. The results support the conclusion that P. chlamydosporia induces plant defense in a distinct and beneficial manner if combined with M. hapla although plant defense is partly suppressed by the endophytic growth. The results tentatively suggested that the application of P. chlamydosporia as a biocontrol agent against M. hapla can be more effective by supporting these tritrophic interactions with specific additives, such as phytohormones or amino acids in the formulation.
Effects of coupled application of magnetoelectric activated water and amendments on photosynthetic physiological characteristics and yield of maize in arid regions
Authors: Lei Qingyuan , Tao Wanghai , Yang Fan , Liu Jianqi , Xi Zixuan , Wang Quanjiu , Deng Mingjiang
Published: January 2025

Seeking effective improvement agent control measures to enhance the photosynthetic physiological traits and yield levels of spring maize is crucial for efficient green agriculture in arid regions. Therefore, this study was conducted to clarify the effects of coupling improvement agents under magnetoelectric activated water irrigation conditions on the photosynthetic physiological traits, grain nutrients, and yield of spring maize in the arid region of northwest China. Field experiments were set up with three concentrations of growth regulators: 400 times (G1), 500 times (G2), and 600 times (G3), and three amounts of Bacillus subtilis: 15 kg/ha (R1), 45 kg/ha (R2), and 75 kg/ha (R3), along with a control group CK, making a total of 10 treatments applied in the field experiment. The results indicate that under magnetoelectric activated water irrigation, coupling improvement agents significantly enhance the photosynthetic traits, grain nutrients, and yield of spring maize in arid areas. With the coupling of improvement agents, the rectangular hyperbola correction model showed a good fit for the light response curve (R2>0.992). Pnmax was significantly increased (7.37%~37.46%) and was highly correlated with yield (P<0.01). The entropy-weight TOPSIS comprehensive evaluation analysis found that the G2R2 treatment is the optimal improvement agent coupling measure for efficient production of spring maize in arid regions. This treatment yielded 12.68 t/ha and increased 100-kernel weight, grains per spike, and soluble sugar content by 21.3%, 8.22%, and 63.81%, respectively, representing the best balance of quality and high yield. The results of this study provide theoretical references and technical support for the high-quality and efficient production of spring maize in China’s arid regions.
Crimean-Congo haemorrhagic fever virus in ticks, domestic, and wild animals
Authors: Celina Seyma S. , Italiya Jignesh , Tekkara Allan Obonyom , Černý Jiří
Published: January 2025

Crimean-Congo haemorrhagic fever virus (CCHFV) poses a significant public health threat due to its potential for causing severe disease in humans and its wide geographic distribution. The virus, primarily transmitted by Hyalomma ticks, is prevalent across Africa, Asia, Europe, and the Middle East. Understanding the virus’s spread among tick populations is crucial for assessing its transmission dynamics. Vertebrates play a key role in CCHF epidemiology by supporting tick populations and acting as virus carriers during viremia. Livestock, such as cattle, sheep, and goats, amplify the virus and increase tick numbers, posing zoonotic risks. Wildlife, while asymptomatic, can serve as reservoirs. Birds generally do not show signs of the virus but can introduce infected ticks to new regions. This review compiles information on CCHFV’s tick vectors and vertebrate hosts, emphasizing their roles in the virus’s transmission dynamics. Understanding these dynamics is essential for developing effective control and prevention strategies.
RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme
Authors: Zhang Kun , Han Kezhen , Zhao Nanbin
Published: January 2025

In complex real-world traffic environments, the task of automatic lane changing becomes extremely challenging for vehicle control systems. Traditional control methods often lack the flexibility and intelligence to accurately capture and respond to dynamic changes in traffic flow. Therefore, developing intelligent control strategies that can accurately predict the behavior of surrounding vehicles and make corresponding adjustments is crucial. This paper presents an intelligent driving control scheme for autonomous vehicles (AVs) based on a responsibility-sensitive safety (RSS) tracking control mechanism within a Bayesian network intelligent learning framework. Initially, the Bayesian evidence construction method for vehicle lane changing scenarios is studied. Using this method, prior probability tables for lane-hanging vehicles are constructed, and the Bayesian formula is applied to predict the lane changing probabilities of surrounding vehicles. Subsequently, an optimal control method is employed to integrate Bayesian lane changing probabilities into the design of performance indices and auxiliary systems, transforming tracking and safety avoidance tasks into an optimization control problem. Additionally, a critic learning optimal control algorithm is developed to determine the control law. Finally, the proposed tracking control scheme is validated through simulations, demonstrating its reliability and effectiveness.
Neural Network-Based Parameter Estimation and Compensation Control for Time-Delay Servo System of Aeroengine
Authors: Chen Hongyi , Li Qiuhong , Ye Zhifeng , Pang Shuwei
Published: January 2025

Servo systems are important actuators of aeroengines. The repetitive, reciprocating motion of the servo system leads to significant changes in its time delay and gain characteristics, and degradation increases the uncertainty of these changes. These characteristic variations may have an adverse effect on the dynamic performance of the aeroengine. Therefore, a neural network-based parameter estimation and a multi-loop neural network-based predictive control (ML-NNPC) method for aeroengine inlet guide vane (IGV) servo systems (SVS) were proposed. In this study, the time delay estimation of the servo system was treated as a classification problem, and an SE (squeeze-and-excitation)-GRU (gated recurrent unit) network was proposed to estimate the time delay by using the selected dynamic data of the servo system. The estimated delay was embedded into an online sequential extreme learning machine, and a nonlinear model predictive controller was designed to obtain an optimal control sequence. The compensation control loop was designed to reduce the impact of the model and delay mismatch problems of the control system. The proposed method was applied to the IGV SVS control of a turboshaft engine. The simulation results demonstrate that the time delay is estimated accurately and compensated effectively. Compared to the existing PI and PI with Smith predictor methods, the ML-NNPC method achieves better control performance in the control of both the SVS and the engine rotor speed system. The stability and robustness of the ML-NNPC also show superiority. The results verify the effectiveness of the proposed time delay estimation method and the ML-NNPC method.
Adaptive Controller Design for Improving Helicopter Flying Qualities
Authors: Wu Wei
Published: January 2025

A comprehensive flight control law design method based on adaptive control is presented in this paper. The proposed method consists of three basic modules—model decoupling, online system identification and adaptive pole placement. The model decoupling module decouples the helicopter flight dynamics model based on dynamic inversion technique. This procedure helps to reduce the difficulties in online system identification and adaptive controller design. In online system identification module, a recursive extended least squares algorithm is established to identify the augmented linear flight dynamics model which is composed of helicopter model and unideal noise model. The helicopter model parameters and the noise parameters are identified simultaneously which improves the identification accuracy as well as robustness. Pole placement is implemented in the last module, and an optimization method is developed to help selecting ideal poles. The adaptive rule in this step is designed based on eigenvalue analysis of the model to remove all unnecessary oscillations of the control parameters. An adaptive controller is designed according to the developed method for the UH-60A helicopter based on a nonlinear simulation program. Typical response types are also implemented. The simulation results show that the designed adaptive controller has high performance as well as robustness in both hover and forward flight.
Bacillus velezensis TCS001 Enhances the Resistance of Hickory to Phytophthora cinnamomi and Reshapes the Rhizosphere Microbial Community
Authors: Xie Chenshun , Wu Yuntian , Wu Zhonghao , Cao Hao , Huang Xiaohui , Cui Feng , Meng Shuai , Chen Jie
Published: January 2025

Phytophthora cinnamomi causes significant root rot in hickory, leading to substantial yield losses. While Bacillus spp. are recognized as beneficial rhizosphere microorganisms, their application against hickory root rot and their impact on rhizosphere microbial communities remain under-investigated. This study demonstrated that Bacillus velezensis TCS001 significantly inhibited P. cinnamomi ST402 growth in vitro, and achieved 71% efficacy in root rot disease management. Scanning electron microscopy (SEM) revealed that TCS001 fermentation filtrate induced mycelial deformities in P. cinnamomi. An analysis of α and β diversity indicated a significant impact of TCS001 on rhizosphere bacterial community richness and diversity, with minimal effects on the fungal community. Moreover, TCS001 altered the hickory rhizosphere microbiome co-occurrence network. The differential abundance analysis suggests that TCS001 promotes the recruitment of beneficial microbes associated with disease resistance, thereby suppressing disease development. These findings underscore the influence of TCS001 on the hickory rhizosphere microbiome in the presence of pathogens, providing valuable data for future research and the development of effective biocontrol strategies for hickory root rot.
Foliar Application and Translocation of Radiolabeled Zinc Oxide Suspension vs. Zinc Sulfate Solution by Soybean Plants
Authors: Beltrame Anita , Rodrigues Marques João Paulo , Ayres Rodrigues Mariana , de Almeida Eduardo , Arruda Bacchi Márcio , De Nadai Fernandes Elisabete Aparecida , Otto Rafael , Pereira de Carvalho Hudson Wallace
Published: January 2025

The present study employed a 65Zn radioactive isotope as a tracer to investigate the foliar uptake and distribution patterns of ZnO concentrated suspension- and ZnSO4 solution-sprayed on soybean plant leaves. The radiolabeled foliar treatments were sprayed on the leaves at V4 and V8 phenological stages. The radioactivity of 65Zn in the leaves, roots, stems, and pods was determined using γ-ray spectrometry. After the first foliar spray, V4, the partition of radiolabeled Zn in plants treated with ZnO and ZnSO4 was 99.22% and 98.12% in treated leaves, 0.15% and 0.39% in stems, 0.16% and 0.29% in roots, and 0.47% and 1.19% in newly expanded non-treated leaves, respectively. After two sprayings, V4 and V8, the partition of radiolabeled Zn in plants treated with ZnO and ZnSO4 was 92.56% and 92.18% in treated leaves, 0.92% and 0.70% in stems, 0.52% and 0.39% in roots, 5.60% and 6.15% in newly expanded non-treated leaves, and 0.43% and 0.61% in grains, respectively. The total fraction translocated from the application tissue was 0.79% and 1.91% for ZnO and ZnSO4, respectively, after 12 days and 8.03% and 8.48% for ZnO and ZnSO4, respectively, after 72 days. An anatomical analysis revealed that plants cultivated in a nutrition solution with 10% ionic strength had 63% fewer stomata, and the xylem vessels were 63% smaller compared to plants grown in a solution with 100% Zn ionic. One can conclude that after a short period, 12 days, the absorption and translocation of ZnSO4 was higher and faster than ZnO, and after the long period, 72 days, their performance was similar.
Instance Segmentation and 3D Pose Estimation of Tea Bud Leaves for Autonomous Harvesting Robots
Authors: Li Haoxin , Chen Tianci , Chen Yingmei , Han Chongyang , Lv Jinhong , Zhou Zhiheng , Wu Weibin
Published: January 2025

In unstructured tea garden environments, accurate recognition and pose estimation of tea bud leaves are critical for autonomous harvesting robots. Due to variations in imaging distance, tea bud leaves exhibit diverse scale and pose characteristics in camera views, which significantly complicates the recognition and pose estimation process. This study proposes a method using an RGB-D camera for precise recognition and pose estimation of tea bud leaves. The approach first constructs an for tea bud leaves, followed by a dynamic weight estimation strategy to achieve adaptive pose estimation. Quantitative experiments demonstrate that the instance segmentation model achieves an mAP@50 of 92.0% for box detection and 91.9% for mask detection, improving by 3.2% and 3.4%, respectively, compared to the YOLOv8s-seg instance segmentation model. The pose estimation results indicate a maximum angular error of 7.76°, a mean angular error of 3.41°, a median angular error of 3.69°, and a median absolute deviation of 1.42°. The corresponding distance errors are 8.60 mm, 2.83 mm, 2.57 mm, and 0.81 mm, further confirming the accuracy and robustness of the proposed method. These results indicate that the proposed method can be applied in unstructured tea garden environments for non-destructive and precise harvesting with autonomous tea bud-leave harvesting robots.
Molecular Genetic Assessment Aids in Clarifying Phylogenetic Status of Iranian Kerman Wild Sheep
Authors: Dotsev Arsen V. , Moradi Mohammad Hossein , Deniskova Tatiana E. , Esmailizadeh Ali , Bakoev Neckruz F. , Koshkina Olga A. , Griffin Darren K. , Romanov Michael N. , Zinovieva Natalia A.
Published: January 2025

Two species of wild sheep inhabit Iran: Asiatic mouflon (Ovis gmelini) and urial (O. vignei). Phylogenetic relationships between populations distributed in this country are complex and still remain unclear. This study aimed to clarify, by genetic assessment, the phylogenetic status of Kerman wild sheep, considered to be a hybrid of the two species. For this purpose, we created a dataset that included specimens of O. gmelini, O. vignei, and Kerman sheep. We applied genome-wide SNP genotyping technology to analyze population structure and genetic diversity of these groups. Using Neighbor-Net and PCA plots, it was demonstrated that Kerman sheep were differentiated from other groups and occupy an intermediate position between O. gmelini and O. vignei. Using Admixture analysis, two ancestral components were identified in this population; however, admixed ancestry was not confirmed by f3 statistics. Genetic diversity in Kerman wild sheep was significantly higher than in any group of O. vignei, but lower than in O. gmelini. Additionally, we examined complete mitochondrial genomes and it was demonstrated that the matrilineal ancestor of Kerman sheep belonged to O. vignei. Our results lead to the conclusion that Kerman wild sheep can be recognized as a separate subspecies of O. vignei.
Heat Stress in Dairy Cows: Impacts, Identification, and Mitigation Strategies—A Review
Authors: Oliveira Charles Paranhos , Sousa Fernanda Campos de , Silva Alex Lopes da , Schultz Érica Beatriz , Valderrama Londoño Roger Iván , Souza Pedro Antônio Reinoso de
Published: January 2025

Heat stress in animals affects productivity, health, and reproduction, with particularly pronounced effects in dairy cows. Identifying heat stress requires understanding both physiological and environmental indicators, such as increased heart rate, respiratory rate, and rectal temperature, which reflect the animal’s thermal condition within its environment. Thermoregulation in cows involves behavioral and physiological adjustments to maintain homeothermy, aiming to stabilize their internal thermal state. To assess the thermal condition of animals, machine learning models have been developed, leveraging both environmental and physiological indicators for more accurate stress detection. Among the various indices of thermal environment, the Temperature and Humidity Index (THI) is the most widely used. Cooling strategies for animals and their environments are essential to mitigate the effects of heat stress. One effective approach involves the use of evaporative adiabatic cooling combined with forced ventilation systems in feeding alleys and pre-milking holding areas. This method enhances evaporative exchanges and facilitates heat dissipation between the animal and its surroundings, thereby alleviating heat stress and improving both the welfare and productivity of dairy cows.
Short- But Not Long-Term Effects of Creep Feeding Provided to Suckling Piglets
Authors: Romero María , Heras-Molina Ana , Muñoz María , Calvo Luis , Morales José Ignacio , Rodríguez Ana Isabel , Escudero Rosa , López-Bote Clemente , Óvilo Cristina , Olivares Álvaro
Published: January 2025

Fifty-eight litters (16 from primiparous gilts and 42 from multiparous sows) were used, with a total number of 750 piglets involved in the study. Birth weight was stratified into three groups: low (<1.02 kg; LBW), normal (1.02–1.62 kg; NBW), and high (>1.62 kg; HBW). A creep feeding diet was offered to piglets in a creep feeder in 29 litters from day 7 until their weaning. Piglet mortality was recorded daily. Traceability was ensured up to the point of carcass splitting and subsequent meat analysis. Each carcass was eviscerated and weighed individually. Sixty-nine piglets were selected for the microbiome analysis (35 from the control group and 34 from the creep feeding group). Feces samples from the rectum were obtained at three time points (three days prior weaning, a week after weaning, and before the slaughtering of the pigs). Mortality during lactation was influenced by birth weight, with LBW piglets exhibiting a six-fold higher mortality rate than HBW. Creep feeding did not impact piglet mortality. Heavier piglets demonstrated greater weight gain when subjected to creep feeding, while the growth potential of lighter piglets was reduced. Variation in creep feeding consumption based on birth weight also affected microbiome composition, with high-birth-weight piglets displaying higher alpha diversity than low- and normal-birth-weight piglets seven days after lactation. Alpha diversity is indicative of gut health, with higher values suggesting greater stability and adaptability to different feed sources. In conclusion, the immediate impacts of creep feeding appear to be most prominent during lactation and potentially early postweaning. These short-term effects are modulated by birth weight, with HBW piglets demonstrating the greatest benefits from the implementation of creep-feeding practices.
Amur Softshell Turtle (Pelodiscus maackii) Population Size, Structure, and Spatial Distribution
Authors: Hou Xiaochen , Shi Haitao
Published: January 2025

Freshwater turtle species preservation relies on understanding their population dynamics and geographical distribution. Amur softshell turtles (ASTs [Pelodiscus maackii]) are poorly protected due to insufficient awareness and the population in Northeastern China has experienced a steep decline compared to previous years. This study aims to investigate the population density and structure of ASTs in the Jewellery Island area of the Ussuri River in Northeast China using continuous-time capture–recapture methods in closed populations. A three-month mark–recapture study was conducted in 2022, resulting in 35 juvenile captures, including 12 recaptures from 23 marked individuals. The estimated population size in the study area was 40.79 ± 9.75 (95% confidence interval, 95% CI = 27–65), translating to 0.663 ± 0.158 turtles/ha (95% CI = 0.44–1.06 individuals/ha). Approximately 35.4–85.2% of the estimated population was marked. Additionally, we explored the influence of environmental variables on turtle distribution by dividing the surveyed sites into seven sections based on their natural characteristics. The ASTs distribution inferred from trapping successes was considerably different among sections, with most turtles (91%) captured at the vegetated shoreline and in water channel 2. This research offers essential baseline data to support future assessments of ASTs population on a larger scale and to inform the development of conservation strategies.
Lipid Metabolism Alterations in Hyperlipidemic Dogs with Biliary Tract or Endocrine Diseases
Authors: Kim Tae-Woo , Kang Min-Hee , Park Hee-Myung
Published: January 2025

Fasting hyperlipidemia results from lipid metabolism defects associated with alterations in specific lipoprotein classes. These changes may originate from genetic predispositions or underlying metabolic disorders, including cholestasis and endocrine diseases. This retrospective study aimed to analyze variations in lipoprotein electrophoresis (LPE) profiles in hyperlipidemic dogs and investigate the associations between biliary tract diseases, endocrine disorders, and lipid metabolism. Sixty-five dogs that underwent LPE were classified into non-hyperlipidemic (NHL) and hyperlipidemic (HL) groups, with further subdivisions based on the presence of biliary tract disease, endocrine disorders, or breed predisposition (Miniature Schnauzers). Dogs in the HL group with biliary tract disease and those with underlying metabolic disorders exhibited significantly higher pre-beta fractions and cholesterol concentrations compared to the NHL group. Additionally, significant linear relationships were observed between serum gamma-glutamyl transpeptidase (GGT) levels and both pre-beta fractions and cholesterol concentrations. The Schnauzer group showed lower alpha fractions and higher triglyceride and cholesterol levels than the NHL group. These findings suggest that LPE is a valuable and useful tool for detecting lipid metabolism abnormalities. Clinicians should consider the potential for altered lipid metabolism when evaluating patients with biliary tract or endocrine diseases in small animal practice.
On the Stability of Graphene-Based Aqueous Dispersions and Their Performance in Cement Mortar
Authors: Gerace Teresa , Candamano Sebastiano , Bartucci Simone , Poselle Bonaventura Carlo , Policicchio Alfonso , Agostino Raffaele Giuseppe , Marroccoli Milena , Telesca Antonio , Davoli Mariano , Scarcello Andrea , Caputi Lorenzo S. , Pacilè Daniela
Published: January 2025

Cement composites containing different carbon nanomaterials, namely graphene technical grade, graphene super grade, and graphene oxide, up to 1.0% by weight of cement, were prepared. Ultrasonic, chemical, and thermochemical treatments were applied to improve the stability of the dispersions containing the graphene-based nanomaterials. Their exfoliation was analyzed using Raman spectroscopy, and the stability of the dispersions was quantitatively investigated by means of the static multiple light scattering (SMLS) technique. The sonication process enhanced the intensity of the 2D band of graphene technical grade, suggesting a partial degree of exfoliation, while the hydrothermal treatment with sodium cholate significantly promoted the stability of its dispersion. The effect of the addition of selected graphene-based nanomaterials in mortars was evaluated in terms of fresh state properties, mechanical strength, capillary water absorption, and pore size distribution. Workability decreased with the increase in the amount of carbon nanomaterials. Field emission scanning electron microscopy (FESEM) was also employed to characterize the microstructure of pristine graphene-based nanomaterials and their inclusion within the cement matrix. Our results suggest that mechanical properties are only moderately affected by the inclusion of all additives, whereas the introduction of graphene significantly influences the coefficient of capillary water absorption. Specifically, a reduction of about 20% in the capillary water absorption coefficient was observed at the concentration of 1.0 wt% of graphene technical grade, which is ascribed to a refinement of the porosity.
Leveraging Advanced NLP Techniques and Data Augmentation to Enhance Online Misogyny Detection
Authors: Mohasseb Alaa , Amer Eslam , Chiroma Fatima , Tranchese Alessia
Published: January 2025

Online misogyny is a significant societal challenge that reinforces gender inequalities and discourages women from engaging fully in digital spaces. Traditional moderation methods often fail to address the dynamic and context-dependent nature of misogynistic language, making adaptive solutions essential. This study presents a framework that integrates advanced natural-language processing techniques with strategic data augmentation to improve the detection of misogynistic content. Key contributions include emoji decoding to interpret symbolic communication, contextual expansion using Sentence-Transformer models, and LDA-based topic modeling to enhance data richness and contextual understanding. The framework incorporates machine-learning, deep-learning, and Transformer-based models to handle complex and nuanced language. Performance analysis highlights the effectiveness of the selected models, and comparative results emphasize the transformative role of data augmentation. This augmentation significantly enhanced model robustness, improved generalization, and strengthened the detection of misogynistic content.
On the Performance of Portable NiMH Batteries of General Use
Authors: Quintero Pulido Diego F. , Covrig Catalin Felix , Bruchhausen Matthias
Published: January 2025

NiMH batteries are the most used technology of rechargeable batteries sold directly to consumers. Herein, we study the performance of the most common sizes of portable NiMH batteries (AA, AAA, D, C, and 9V). The performance and durability parameters—capacity, charge retention, charge recovery, and endurance in cycles—are measured for these types of batteries, according to the standard IEC 61951-2:2017 NiMH batteries. The purpose of this study is to create a basis for setting minimum performance requirements for the parameters in the European Regulation concerning batteries and waste batteries, EU 2023/1542, Annex III, Part B. Results show that the charging time of 16 h could be reduced to 8 h for verifying the rated capacity. The performance of commercial batteries with regard to charge retention, charge recovery, and endurance in cycles is often found to be 25–30% better than required in the relevant IEC standard. Furthermore, we present a short comparative analysis of an application test (IEC 60086-2:2021 “toy”) for portable NiMH batteries with primary batteries. Such data allow comparing the performance of portable NiMH batteries compared to primary batteries in the application test “toy”.
Battery Health Monitoring and Remaining Useful Life Prediction Techniques: A Review of Technologies
Authors: Ahwiadi Mohamed , Wang Wilson
Published: January 2025

Lithium-ion (Li-ion) batteries have become essential in modern industries and domestic applications due to their high energy density and efficiency. However, they experience gradual degradation over time, which presents significant challenges in maintaining optimal battery performance and increases the risk of unexpected system failures. To ensure the reliability and longevity of Li-ion batteries in applications, various methods have been proposed for battery health monitoring and remaining useful life (RUL) prediction. This paper provides a comprehensive review and analysis of the primary approaches employed for battery health monitoring and RUL estimation under the categories of model-based, data-driven, and hybrid methods. Generally speaking, model-based methods use physical or electrochemical models to simulate battery behaviour, which offers valuable insights into the principles that govern battery degradation. Data-driven techniques leverage historical data, AI, and machine learning algorithms to identify degradation trends and predict RUL, which can provide flexible and adaptive solutions. Hybrid approaches integrate multiple methods to enhance predictive accuracy by combining the physical insights of model-based methods with the statistical and analytical strengths of data-driven techniques. This paper thoroughly evaluates these methodologies, focusing on recent advancements along with their respective strengths and limitations. By consolidating current findings and highlighting potential pathways for advancement, this review paper serves as a foundational resource for researchers and practitioners working to advance battery health monitoring and RUL prediction methods across both academic and industrial fields.
Preservation of Bilateral Corticospinal Projections from Injured Hemisphere After Perinatal Stroke
Authors: Casey Cameron P. , Sutter Ellen N. , Grimaldo Alina , Collins Kellie M. , Guerrero-Gonzalez Jose , McAdams Ryan M. , Dean Douglas C. , Gillick Bernadette T.
Published: January 2025

Background: Perinatal brain injury is a leading cause of developmental disabilities, including cerebral palsy. However, further work is needed to understand early brain development in the presence of brain injury. In this case report, we examine the longitudinal neuromotor development of a term infant following a significant loss of right-hemispheric brain tissue due to a unilateral ischemic stroke. Our analysis focuses on the integrity and development of the corticospinal tract (CST) from the lesioned hemisphere. This case provides a unique opportunity to evaluate CST development after loss of the majority of the motor cortex. Methods: Evaluations were conducted when the infant was 4 (Visit-1), 18 (Visit 2), and 25 (Visit 3) months old. Assessments included magnetic resonance imaging (MRI) to characterize the lesion and quantify CST structural integrity, single-pulse transcranial magnetic stimulation (spTMS) to evaluate CST functional circuitry, and neuromotor assessments. Results: At Visit 1, bilateral CSTs were identified through diffusion-weighted MRI (dMRI) despite an estimated loss of 92.7% (7.3% retained) of age-typical motor cortex from the right hemisphere. Both hemispheres exhibited bilateral motor-evoked potential in response to stimulation with spTMS, which remained when reassessed at Visits 2 and 3. Longitudinal MRI showed distinct developmental trajectories of CST integrity in each hemisphere, with the lesioned hemisphere exhibiting initial increases in integrity between Visits 1 and 2 followed by a decrease in integrity between Visits 2 and 3. The non-lesioned hemisphere showed increased integrity from Visit 1 to Visit 2, which remained stable at Visit 3. Motor assessments at all visits indicated a high risk of cerebral palsy. Conclusions: This report highlights the utility of MRI and spTMS in studying neuromotor development. The findings reveal preserved functional bilateral CST circuitry despite majority loss of the right-hemispheric motor cortex as well as distinct developmental trajectories in CST integrity between hemispheres. These results underscore the potential for neural plasticity after perinatal brain injury. Clinical Trials Registration: NCT05013736.
Binocular Video-Based Automatic Pixel-Level Crack Detection and Quantification Using Deep Convolutional Neural Networks for Concrete Structures
Authors: Liu Liqu , Shen Bo , Huang Shuchen , Liu Runlin , Liao Weizhang , Wang Bin , Diao Shuo
Published: January 2025

Crack detection and quantification play crucial roles in assessing the condition of concrete structures. Herein, a novel real-time crack detection and quantification method that leverages binocular vision and a lightweight deep learning model is proposed. In this methodology, the proposed method based on the following four modules is adopted: a lightweight classification algorithm, a high-precision segmentation algorithm, a semi-global block matching algorithm (SGBM), and a crack quantification technique. Based on the crack segmentation results, a framework is developed for quantitative analysis of the major geometric parameters, including crack length, crack width, and crack angle of orientation at the pixel level. Results indicate that, by incorporating channel attention and spatial attention mechanisms in the MBConv module, the detection accuracy of the improved EfficientNetV2 increased by 1.6% compared with the original EfficientNetV2. Results indicate that using the proposed quantification method can achieve low quantification errors of 2%, 4.5%, and 4% for the crack length, width, and angle of orientation, respectively. The proposed method can contribute to crack detection and quantification in practical use by being deployed on smart devices.
Evaluation of Landscapes and Soundscapes in Traditional Villages in the Hakka Region of Guangdong Province Based on Audio-Visual Interactions
Authors: Zhang Dongxu , Chen Hao , Zhang Xinyi , Tan Lingge
Published: January 2025

Traditional villages in the Hakka region of Guangdong Province have attracted significant attention for their unique cultural heritage and traditional lifestyles. Their favourable audio-visual environments offer immersive and realistic experiences for both residents and visitors. Thus, we selected four representative villages and used semantic segmentation to extract the core visual elements (sky, vegetation, construction, and dynamic) from visual landscape images. Audio-visual interaction experiments and subjective surveys were conducted to investigate the participants’ evaluations of the visual landscape and soundscape to explore the mechanisms of audio-visual interaction. The results revealed that different audio-visual combinations significantly influenced the participants’ visual landscape satisfaction, acoustic comfort, and audio-visual harmony evaluations. Specifically, visual images of natural spaces with a high proportion of sky (24.54%) and vegetation (72.56%), matched with natural sounds (with a sound pressure level of approximately 55 dB) such as birdsong, wind, and flowing water, received excellent ratings for both visual landscape satisfaction and acoustic comfort evaluations. Moreover, the findings further revealed that coordination between visual and audio materials was crucial for enhancing the participants’ perceptions and assessments, highlighting the importance of audio-visual coordination in creating harmonious environments. These findings provide recommendations for spatial planning, landscape design, and soundscape optimisation in traditional villages.
Experimental and Numerical Investigation of Welding Residual Stress of U-Rib Joints in Orthotropic Steel Bridge Decks
Authors: Huang Zhiqiang , Su Wenxue , Shi Jun , Li Tao , Cao Hongyou
Published: January 2025

The residual stresses at U-rib joints have a significant adverse impact on the structure. Therefore, it is necessary to conduct research and analysis on their residual stresses. Based on experimental testing and thermal elastic-plastic finite element analysis (FEA), this study investigates the residual stress (RS) of a U-rib joint using gas metal arc welding in an orthotropic steel bridge deck (OSBD). X-ray diffraction (XRD) was adopted to measure the RS of the U-rib welds, and the measurement results were utilized to verify the FEA. The effects of the weld root gap, weld penetration, and weld groove angle on the RS of U-rib welds were investigated by using FEA. The weld root gap had minor effect on the RS of the U-rib welds. With an increase in weld penetration, the peak values of the transverse tensile RS at both the deck plate and the U-rib weld toes increased. Additionally, an enlargement of the groove angle also resulted in a notable increase in the transverse tensile RS peak at the deck plate weld toe.
Deformation and Reinforcement of the Existing Tunnel Affected by New Shield Tunnel Construction with Small Clearance
Authors: Zhang Junchao , Yu Jiacheng , Li Cunjun , Liu Yizhou , Tian Longgang , He Yonglin , Zhang Qi
Published: January 2025

In recent years, the rapid expansion of subway construction has brought increasing challenges related to the crossing of new and existing subway lines. This study focuses on the Nanjing Metro line 11 project, where the new line crosses the existing line 3. A numerical simulation analysis of the tunnel intersection area is conducted using ABAQUS software to investigate the deformation mechanism of shield segments when a new tunnel is constructed at a close distance and oblique angle to an existing tunnel. During the construction of a new tunnel, the existing tunnel segments experience the greatest settlement at the intersection point, with the deformation pattern gradually evolving from a V-shape to a W-shape. The majority of the deformation in the existing tunnel occurs during the close-crossing stage of the new tunnel. An ultra-high-performance grouting (UHPG) material is proposed, and the optimal reinforcement material ratio is determined through tests. The UHPG material is applied to the underside of the existing tunnels in the crossover section for local reinforcement. The results demonstrated the effectiveness of the proposed reinforcement method. Specifically, the deformation of the left line and right line of the existing tunnel is reduced by 35.0% and 33.1%, respectively, the segmental stress decreased by 10.1%, and the ground subsidence was reduced by 13.2%.
The Effect of Steel Reinforcement Diameter on the Behavior of Concrete Beams with Corrosion
Authors: Moreno-Herrera Joel , Vega-Juarez Néstor , Varela-Rivera Jorge , Fernandez-Baqueiro Luis , Castro-Borges Pedro
Published: January 2025

Corrosion is one of the main problems affecting reinforced concrete (RC) structures, yet there remains a lack of studies in which the electrochemical and structural behavior of corroded RC elements are studied together. In this work, four RC beams with and without corrosion were studied to evaluate their electrochemical and structural behavior via the variable of the diameter of the longitudinal tension steel reinforcement (LTR). The beams were initially tested to determine their initial structural behavior and then subjected to sustained loads and wetting and drying cycles by applying a NaCl solution. The beams were tested a second time to determine their final structural behavior. The variations in the corrosion potential and corrosion rate of the LTR with time, together with concrete resistivity, cracking patterns, and load–displacement curves of the RC beam, are presented. It was found that the electrochemical parameters of the beams with corrosion were similar regardless of the steel reinforcement diameter; these parameters indicated a high level of corrosion. The maximum flexural strength loss was observed for beams with an LTR of 10 mm compared to those with a 13 mm diameter. The maximum cross-sectional area loss associated with pitting corrosion was greater for the beam with an LTR of 10 mm.
A Canadian Perspective on Systemic Therapy for Recurrent or Metastatic Nasopharyngeal Carcinoma
Authors: Spreafico Anna , Winquist Eric , Ho Cheryl , O’Sullivan Brian , Bouganim Nathaniel , Chua Neil , Doucette Sarah , Siu Lillian L. , Hao Desiree
Published: January 2025

Although the majority of patients with nasopharyngeal carcinoma (NPC) present with early-stage or locoregional disease that can be treated with definitive radiotherapy, approximately 20% of patients experience disease recurrence, and 15% present with metastatic disease that is not amenable to curative therapy. Management of patients with recurrent or metastatic (r/m) NPC who are not candidates for local salvage therapy is challenging in Canada, as there is uncertainty in extrapolating evidence that is largely generated from Southeast China to non-endemic regions such as Canada. Currently, treatment options in Canada are limited to chemotherapy regimens that can only achieve short-term response and prolongation of survival. The addition of anti-PD-1 monoclonal antibodies to chemotherapy has been shown to extend progression-free survival in recurrent r/m NPC compared to chemotherapy alone; however, approval of PD-1 inhibitors in Canada has lagged behind other jurisdictions where NPC is non-endemic. This paper reviews the current systemic treatment landscape for r/m NPC in Canada, highlights unmet treatment needs for patients who are not candidates for curative therapy, and discusses the challenges and opportunities that lie in emerging therapies.
Genetic Diversity of Diaphorina citri and Its Endosymbiont Across Diffusion Frontier and Epidemic Areas of Citrus Huanglongbing in China
Authors: Yang Jin , Huang Ai-Jun , Zhou Jun , You Ping , Li Xiang , Luo Han , Yi Long
Published: January 2025

Citrus huanglongbing (HLB) is one of the most severe diseases affecting the citrus industry, with Diaphorina citri (Hemiptera: Liviidae) serving as its primary natural vector. To understand the genetic diversity and population structure of D. citri in the context of HLB diffusion, we analyzed 13 populations from the HLB diffusion frontier and 25 populations from epidemic areas in China. The HLB diffusion frontier areas refer to the peripheral regions of HLB distribution in China, including the western Zhejiang, southern Jiangsu, northern Jiangxi, northern Hunan, and eastern Sichuan provinces. In contrast, the HLB epidemic areas represent regions in China where HLB is actively widespread and causing significant impacts. We utilized mitochondrial genes (COI, ND5, and Cytb) of D. citri and housekeeping genes (dnaQ, rpoC, and argH) of its endosymbiont Candidatus Carsonella ruddii (Ca. C. ruddii) for this analysis. Our findings revealed that the D. citri and Ca. C. ruddii in different regions showed low haplotype diversity and nucleotide diversity. While the genetic variation in D. citri populations primarily occurred within populations, the endosymbiont showed contrasting patterns in the HLB epidemic areas. We identified three dispersal paths: (1) migration of the Yunnan population to Sichuan, Guizhou, and Guangxi; (2) movement of the Guangdong population to Fujian, Jiangxi, and Zhejiang; and (3) dispersal of the Guangdong population to Hunan and Guangxi. Our study suggests that D. citri populations at the HLB diffusion frontier are predominantly transmitted from neighboring epidemic areas.
A Comprehensive Parcel-Level Dataset on Farmland Assessment: Addressing Grid-Cell Data Bias Estimation
Authors: Siu Wai Yan , Li Man , Caplan Arthur J.
Published: January 2025

Grid-cell data are increasingly used in research due to the growing availability and accessibility of remote sensing products. However, grid-cell data often fails to represent the actual decision-making unit, leading to biased estimates in socio-economic analysis. To this end, this paper presents a comprehensive parcel-level dataset for Salt Lake County, Utah, spanning from 2008 to 2018. This dataset combines detailed spatial and temporal data on land ownership, land use, and preferential farmland tax assessments under the Greenbelt program. Compiled from multiple geospatial sources, the dataset includes nearly 200,000 parcel-year observations, providing valuable insights into landowner decision-making and the impact of tax abatement incentives at the decision-making level. This resource is beneficial for researchers, educators, and practitioners in sustainable development, environmental studies, and farmland conservation.
Resistance to Radiotherapy in Cancer
Authors: Akhunzianov Almaz A. , Rozhina Elvira V. , Filina Yuliya V. , Rizvanov Albert A. , Miftakhova Regina R.
Published: January 2025

Radiation therapy or radiotherapy is a medical treatment that uses high doses of ionizing radiation to eliminate cancer cells and shrink tumors. It works by targeting the DNA within the tumor cells restricting their proliferation. Radiotherapy has been used for treating cancer for more than 100 years. Along with surgery and chemotherapy, it is one of the three main and most common approaches used in cancer therapy. Nowadays, radiotherapy has become a standard treatment option for a wide range of cancers around the world, including lung, breast, cervical, and colorectal cancers. Around 50% of all patients will require radiotherapy, 60% of whom are treated with curative intent. Moreover, it is commonly used for palliative treatment. Radiotherapy provides 5-year local control and overall survival benefit in 10.4% and 2.4% of all cancer patients, respectively. The highest local control benefit is reported for cervical (33%), head and neck (32%), and prostate (26%) cancers. But no benefit is observed in pancreas, ovary, liver, kidney, and colon cancers. Such relatively low efficiency is related to the development of radiation resistance, which results in cancer recurrence, metastatic dissemination, and poor prognosis. The identification of radioresistance biomarkers allows for improving the treatment outcome. These biomarkers mainly include proteins involved in metabolism and cell signaling pathways.
Creation of a Collaborative “School–University” Environment to Support Research Activities in Schools
Authors: Begaliyeva Saule , Shmakova Elena , Zhunisbayeva Assel
Published: January 2025

This study identifies the issue of insufficient scientific and methodological support for school research projects. To address this, the study proposes the creation of a collaborative “school–university” environment, enabling schoolteachers and students to receive necessary guidance and methodological assistance in preparing and implementing school research projects in the humanities. The study suggests leveraging the Digital Humanities field to incorporate modern digital tools for creating competitive research projects that meet not only the requirements of the Ministry of Education, but also global scientific and economic trends. The assessment of the current situation in the preparation and implementation of school projects involved a survey of more than 600 teachers from the southern region of Kazakhstan. The survey results reveal that over 80% of teachers require scientific and methodological support in preparing school research projects. Based on the survey findings and the expressed demand for methodological assistance, the development of a pilot digital platform is planned. This platform will facilitate collaborative work among schoolteachers, students, university professors, and gifted students to create research projects in Digital Humanities. Such collaborative efforts aim to address the lack of adequate preparation for school research projects.