bluuebunny/crossref_metadata_2025 huggingface dataset:
Hematopoietic stem cell a reservoir of innate immune memory
Authors: Ruffinatto Lucas , Groult Yann , Iacono Johanna , Sarrazin Sandrine , de Laval Bérengère
Published: December 2024

Hematopoietic stem cells (HSCs) are a rare, long-lived and multipotent population that give rise to majority of blood cells and some tissue-resident immune cells. There is growing evidence that inflammatory stimuli can trigger persistent reprogramming in HSCs that enhances or inhibits the cellular functions of these HSCs and their progeny in response to subsequent infections. This newly discovered property makes HSCs a reservoir for innate immune memory. The molecular mechanisms underlying innate immune memory in HSCs are similar to those observed in innate immune cells, although their full elucidation is still pending. In this review, we examine the current state of knowledge on how an inflammatory response leads to reprogramming of HSCs. Understanding the full spectrum of consequences of reshaping early hematopoiesis is critical for assessing the potential benefits and risks under physiological and pathological conditions.
Case report: Identification of a novel TOR1AIP2::ETV6 transcript with FLT3-ITD mutation in acute myeloid leukemia progressed from myelodysplastic syndrome
Authors: Xia Jun , Yang Guanqun , Yu Qingling , Zhang Ruiyi , Li Ge , Wang Man , Sun Hongli , Chen Heng , Wang Lingling , Chen Ping , Gu Kai-Li , Sun Chao
Published: December 2024

Acute myeloid leukemia (AML), which is most common in adults, is a challenging hematological malignancy. The occurrence and the progression of AML are often accompanied by various gene fusions and/or mutations. Herein, we report the first case of a TOR1AIP2::ETV6 fusion transcript with a translocation of t(1;12)(q25;p13) in AML progressed from myelodysplastic syndrome (MDS) combined with an FLT3-ITD (internal tandem duplication) mutation. Further studies should focus on the biological functions of these novel chimeric products in disease onset and progression, as well as their potential as monitoring markers in disease regression.
The fruit fly Drosophila melanogaster as a screening model for antiseizure medications
Authors: Fischer Florian P. , Karge Robin A. , Koch Henner , Voigt Aaron , Weber Yvonne G. , Wolking Stefan
Published: December 2024

Objective

Resistance to antiseizure medications (ASMs) is a major challenge in the treatment of patients with epilepsy. Despite numerous newly marketed ASMs, the proportion of drug-resistant people with epilepsy has not significantly decreased over the years. Therefore, novel and innovative seizure models for preclinical drug screening are highly desirable. Here, we explore the efficacy of a broad spectrum of ASMs in suppressing seizure activity in two established Drosophila melanogaster bang-sensitive mutants. These mutants respond with seizures to mechanical stimulation, providing a promising platform for screening novel ASMs.

Methods

Seven frequently used ASMs (brivaracetam, cenobamate, lacosamide, lamotrigine, levetiracetam, phenytoin, and valproate) were administered to the bang-sensitive mutants easily shocked2F (eas2F) and paralyticbss1 (parabss1). After 48 h of treatment, the flies were vortexed to induce mechanical stimulation. The seizure probability (i.e., ratio of seizing and non-seizing flies) as well as the seizure duration were analyzed.

Results

In case of eas2F mutants, treatment with the sodium channel blockers phenytoin and lamotrigine resulted in a robust reduction of seizure probability, whereas flies treated with lacosamide showed a decrease in seizure duration. Treatment with valproate resulted in both a reduction in seizure probability and in seizure duration. In contrast, levetiracetam, brivaracetam and cenobamate had no effect on the bang-sensitive phenotype of eas2F flies. In case of parabss1 flies, none of the tested medications significantly reduced seizure activity, supporting its role as a model of intractable epilepsy.

Significance

Our results show that particularly sodium channel blockers as well as valproate are effective in suppressing seizure activity in the bang-sensitive mutant eas2F. These findings demonstrate the usability of Drosophila for screening drugs with antiseizure properties. Due to fewer ethical concerns, the short life cycle, and low maintenance costs, Drosophila might provide an attractive and innovative high-throughput model for the discovery of novel antiseizure compounds.
A novel network with enhanced edge information for left atrium segmentation from LGE-MRI
Authors: Zhang Ze , Wang Zhen , Wang Xiqian , Wang Kuanquan , Yuan Yongfeng , Li Qince
Published: December 2024

Introduction

Automatic segmentation of the left atrium (LA) constitutes a crucial pre-processing step in evaluating heart structure and function during clinical interventions, such as image-guided radiofrequency ablation of atrial fibrillation. Despite prior research on LA segmentation, the low contrast in medical images exacerbates the challenge of distinguishing various tissues, rendering accurate boundary delineation of the target area formidable. Moreover, class imbalance due to the small target size further complicates segmentation.

Methods

This study aims to devise an architecture that augments edge information for LA segmentation from late gadolinium enhancement magnetic resonance imaging. To intensify edge information within image features, this study introduces an Edge Information Enhancement Module (EIEM) to the foundational network. The design of EIEM is grounded in exploring edge details within target region features learned from images. Additionally, it incorporates a Spatially Weighted Cross-Entropy loss function tailored for EIEM, introducing constraints on different regions based on the importance of pixels to edge segmentation, while also mitigating class imbalance through weighted treatment of positive and negative samples.

Results

The proposed method is validated on the 2018 Atrial Segmentation Challenge dataset. Compared with other state-of-the-art algorithms, the proposed algorithm demonstrated a significant improvement with an average symmetric surface distance of 0.684 mm and achieved a commendable Dice coefficient of 0.924, implicating the effectiveness of enhancing edge information.

Discussion

The method offers a practical framework for precise LA localization and segmentation, particularly strengthening the algorithm’s effectiveness in improving segmentation outcomes for irregular protrusions and discrete multiple targets. Additionally, the generalizability of our model was evaluated on the heart dataset from the Medical Segmentation Decathlon (MSD) challenge, confirming its robustness across different clinical scenarios involving LA segmentation.
Using the Pearson’s correlation coefficient as the sole metric to measure the accuracy of quantitative trait prediction: is it sufficient?
Authors: Pan Shouhui , Liu Zhongqiang , Han Yanyun , Zhang Dongfeng , Zhao Xiangyu , Li Jinlong , Wang Kaiyi
Published: December 2024

How to evaluate the accuracy of quantitative trait prediction is crucial to choose the best model among several possible choices in plant breeding. Pearson’s correlation coefficient (PCC), serving as a metric for quantifying the strength of the linear association between two variables, is widely used to evaluate the accuracy of the quantitative trait prediction models, and generally performs well in most circumstances. However, PCC may not always offer a comprehensive view of predictive accuracy, especially in cases involving nonlinear relationships or complex dependencies in machine learning-based methods. It has been found that many papers on quantitative trait prediction solely use PCC as a single metric to evaluate the accuracy of their models, which is insufficient and limited from a formal perspective. This study addresses this crucial issue by presenting a typical example and conducting a comparative analysis of PCC and nine other evaluation metrics using four traditional methods and four machine learning-based methods, thereby contributing to the improvement of practical applicability and reliability of plant quantitative trait prediction models. It is recommended to employ PCC in conjunction with other evaluation metrics in a targeted manner based on specific application scenarios to reduce the likelihood of drawing misleading conclusions.
Evolution and comparative transcriptome analysis of glucosinolate pathway genes in Brassica napus L.
Authors: Liu Shiying , Wu Zexuan , Chen Xingying , Chen Zhuo , Shen Yibing , Qadir Salman , Wan Huafang , Zhao Huiyan , Yin Nengwen , Li Jiana , Qu Cunmin , Du Hai
Published: December 2024

Glucosinolates (GSLs) are important secondary metabolites abundantly distributed in Brassicaceae plants, whose degradation products benefit plant resistance but are regarded as disadvantageous factors for human health. Thus, reducing GSL content is an important goal in the breeding program in crops, such as Brassica napus. In this study, 1280 genes in the GSL pathway were identified from 14 land plant genomes, which are specifically distributed in Brassicaceae and are extensively expanded in B. napus. Most GSL pathway genes had many positive selection sites, especially the encoding genes of transcription factors (TFs) and structural genes involved in the GSL breakdown process. There are 344 genes in the GSL pathway in the B. napus genome, which are unequally distributed on the 19 chromosomes. Whole-genome duplication mainly contributed to the gene expansion of the GSL pathway in B. napus. The genes in GSL biosynthesis were regulated by various TFs and cis-elements in B. napus and mainly response to abiotic stress and hormone induction. A comparative transcriptome atlas of the roots, stems, leaves, flowers, siliques, and seeds of a high- (ZY821), and a low-GSL-content (ZS11) cultivar was constructed. The features of the two cultivars may be attributed to diverse expression differences in each organ at different stages, especially in seeds. In all, 65 differential expressed genes (DEGs) concentrated on the core structure pathway were inferred to mainly influence the GSL contents between ZY821 and ZS11. This study provides an important RNA-seq dataset and diverse gene resources for future manipulating GSLs biosynthesis and distribution in B. napus using molecular breeding methods.
Avoiding the elephant in the room: echo chambers and the (de-)politicization of COVID-19 during the 2021 German federal election on Twitter
Authors: Riedl Jasmin , Drews Wiebke , Richter Friederike
Published: December 2024

During the 2021 German federal election campaign, COVID-19 emerged as a highly salient issue in public discourse. Despite its significance, most political parties adopted a strategy of depoliticization, likely as a means to mitigate potential electoral losses. Against this backdrop, our paper examines whether and to what extent COVID-19 was discussed on Twitter in the run-up to the election. Our analysis draws on two original datasets collected in the four weeks preceding the election on September 26, 2021: one comprising 7,374,166 German-language posts mentioning the federal election and another with 3,195,198 German-language posts commenting on the COVID-19 pandemic. Using these datasets, we calculated echo chamber scores (ECS) based on ideological leanings within retweet-based networks and examined the politicization of COVID-19 in the digital election campaign. Our findings reveal that the online discourse polarized into two distinct echo chambers: a “safety-first” community advocating for strict COVID-19 measures, and a “freedom-first” community opposing such measures. While most political figures sought to depoliticize the issue online, key political actors – due to their leadership roles in the upcoming election-could neither avoid addressing the pandemic nor being publicly addressed on the matter. In particular, users within the echo chambers focused attention on two key health policy leaders from opposing political camps: Jens Spahn, the then-incumbent Health Minister from the Christian Democratic Unio/Christian Social Union (CDU/CSU), and Karl Lauterbach from the Social Democratic Party (SPD), who would later become health minister. Our results underscore that, despite efforts to minimize the salience of COVID-19 in the lead-up to the election, certain leaders were compelled to confront the “elephant in the room” due to the demands of their roles during the health crisis.
CARE Model of Treatment for stuttering: Theory, assumptions, and preliminary findings
Authors: Byrd Courtney T. , Coalson Geoffrey A. , Conture Edward G.
Published: December 2024

The purpose of this article is to present a theory of therapy for stuttering, its related assumptions, and findings from associated empirical studies. Specifically, we propose the Blank Center CARE™ Model of Treatment (CT) for stuttering, which differs from the current, widely employed fluency model of treatment (FT). The CT reflects the authors’ belief in the need to move away from fluency-focused or seemingly ableist treatments (i.e., any approach that attempts to correct, cure, or fix a disabling condition) for stuttering. The authors propose a shift toward a theory of treatment that addresses whole-person wellness and considers the treatment of stuttering from outside the framework of fluency shaping and stuttering modification. In support of such considerations, this article provides preliminary findings from both non-clinical and clinical studies of using the CT for children and adults. Although preliminary, these findings appear to lend empirical support to the authors’ belief that the treatment of stuttering needs to change. In essence, a change in the zeitgeist regarding the treatment of stuttering may contribute to an associated paradigm shift from FT to CT in the management of stuttering in children and adults.
The cerebral metabolic mechanism of group computer magnanimous therapy based on magnetic resonance spectroscopy: effects on improving magnanimous-enterprising levels of lung cancer patients
Authors: Liu Qianyu , Ma Qihui , Sun Qingfeng , Huang Xuewei
Published: December 2024

Introduction

This study aims to evaluate the effects of group computer magnanimous therapy (GCMT) on magnanimous-enterprising levels and brain metabolic changes in patients with advanced lung cancer.

Methods

In this multicenter, randomized controlled trial, 47 participants diagnosed with advanced stage (III or IV) lung cancer were randomly assigned to either the GCMT group (GCMTG, n = 31) or the control group (CTRLG, n = 16). The GCMTG received routine oncotherapy and care along with eight sessions of GCMT over 2 weeks, while the CTRLG received only oncotherapy and routine care. Psychological and brain metabolic changes were assessed using the Enterprising and Magnanimous Questionnaire (EMQ) and proton magnetic resonance spectroscopy (1H-MRS).

Results

After 2 weeks, the GCMTG showed significant improvements in the EMQ “total score” and “enterprising” dimensions compared to baseline (p < 0.05), while the CTRLG showed no significant changes. Significant increases in NAA/Cr levels were observed in the right amygdala, and significant decreases in mI/Cr levels were observed in the right cingulate gyrus in the GCMTG. Pearson correlation analysis indicated that changes in Cho/Cr levels in the left amygdala and Glx/Cr levels in the left hippocampus were significantly correlated with improvements in the enterprising dimension.

Conclusions

GCMT significantly enhanced enterprising attitudes and induced beneficial changes in brain metabolites among patients with advanced lung cancer. Further research with larger sample sizes is warranted to confirm these results and explore the long-term effects of GCMT.

Clinical trial registration

https://www.chictr.org.cn/showproj.html?proj=129557, identifier ChiCTR2100053015.
Evaluation of the outcomes of equity-deserving individuals receiving services and support from integrated substance use health and mental health services: a pilot study protocol
Authors: Edalati Hanie , Katan Christina , Taha Sheena
Published: December 2024

Background

Given the close relationship that can exist between substance use health and mental health (SUHMH) concerns, the need for more integrated services and support has been identified. However, research on the effective integration of SUHMH services and their impact on outcomes of individuals accessing them remains limited. In particular, the unique outcomes of individuals facing significant structural inequities in the health care system, i.e., Indigenous Peoples in Canada, including First Nations, Inuit and Métis (FNIM), and equity-deserving (ED) groups, have not been evaluated while receiving integrated SUHMH services. This paper describes the protocol for a pilot research project, which will evaluate the change in clinical and social outcomes of individuals receiving integrated SUHMH services in relation to their intersectionality status, a linear score ranging from identifying with no FNIM and ED groups to identifying with one or multiple groups.

Methods

This study recruits 100 individuals who receive SUHMH services and support from a community health center in Ottawa, Canada and assessed their FNIM and ED status and clinical and social outcomes at baseline and three-month follow-up. At the time of writing this manuscript, the baseline data collection was completed. Follow up assessment occurs three months after baseline data was collected. A smaller group of these participants will be purposefully selected match the proportion of FNIM and ED groups from the two-time assessment. They will be invited to participate in a post-data analysis validation consultation session to ensure that the findings are reflective of the experiences of individuals receiving SUHMH services, alternative interpretations are brought forward, and implications are driven by those who will be most impacted. This consultation may also inform knowledge mobilization activities and future studies. This study also recruited staff in different roles from the providing center to rate the implementation of key dimensions of equity-oriented care into their practices and their level and capability to provide integrated services and support to individuals with cooccurring substance use disorders and mental illnesses.

Discussion

The results of this study will inform integrated SUHMH services by emphasizing equity and inclusive approaches, and engagement with the community. Substance use health; Mental health; Integrated services and support; Equity-deserving populations; Equity-oriented care.
Student perspectives on interdisciplinary learning in public health education: insights from a mixed-methods study
Authors: Lim Raymond Boon Tar , Tan Claire Gek Ling , Voo Kelly , Lee Yock Leng , Teng Cecilia Woon Chien
Published: December 2024

Interdisciplinary learning is essential for equipping future health professionals to tackle the complexities of contemporary public health. This mixed-methods study investigates the experiences and perspectives of undergraduate public health students in Singapore on interdisciplinary learning in higher education and employed a convergent parallel design by combining a cross-sectional survey with in-depth interviews. Quantitative data were used to assess the relationship between students’ exposure to interdisciplinary learning and its perceived value, while qualitative analysis explored key themes related to facilitators and barriers. Among 52 survey respondents and 11 interview participants, nearly half regularly engaged in interdisciplinary learning. Students with greater exposure to interdisciplinary experiences demonstrated more positive perceptions. Facilitators identified included career development opportunities, faculty engagement, and diverse learning experiences. Barriers such as disciplinary disconnects and the challenge of managing varied skill sets were also highlighted. This study provides valuable insights into interdisciplinary learning in higher education pertaining to public health, particularly within the context of health professions training. The findings suggest that enhancing curricular design, integrating interdisciplinary approaches more effectively, and increasing faculty support can address identified barriers and better prepare students for the demands of their future public health careers.
Building trusting relationships in teams to support evidence use and implementation in human services: feasibility and acceptability of a training and coaching approach
Authors: Metz Allison , Jensen Todd M. , Dicharry Lacy , Farley Amanda B.
Published: December 2024

Background

Professionals who provide implementation support in human service systems describe relationships as being critical to support evidence use; however, developing trusting relationships are not strongly featured in implementation science literature. The aims of this study were to (a) assess the feasibility and acceptability of a theory-driven training and coaching approach for building trusting relationships among members of an implementation team who were supporting the implementation of an evidence-informed program in a public child welfare system in the United States and (b) gauge the initial efficacy of the approach in terms of the development of trusting relationships and subsequent implementation outcomes.

Methods

Consistent with a convergent mixed-methods approach, we collected both quantitative and qualitative data to address our research questions. Quantitative methods included an adapted version of the Trusting Relationship Questionnaire, a seven-item measure of psychological safety, and items designed to measure acceptability of the training. Qualitative data were collected through semi-structured interviews with participants.

Results

Sixteen individuals participated in the program, consisting of a kick-off training event, five monthly training modules, and five monthly coaching sessions with implementation team leads. Session attendance rates and self-reported satisfaction highlight the general feasibility and acceptability of the training and coaching approach. On average, participants also reported significant increases over time in their perceptions that they were trusted by their team. Results from in-depth interviews further indicated the efficacy of the program in terms of cultivating trust among team members and promoting several elements that were theorized to link trusting relationships to implementation outcomes.

Discussion

Findings suggest the training and coaching approach for trust building was acceptable and feasible. Additionally, results indicate the value of the approach in building trust among implementation partners to increase commitment to implementation efforts, promote a culture of learning and psychological safety, and increase participants' sense of capability and motivation for supporting implementation.
Understanding sprint phase-specific training stimuli: a cluster analysis approach to overload conditions
Authors: Jiménez-Reyes Pedro , van den Tillaar Roland , Castaño-Zambudio Adrián , Gleadhill Sam , Nagahara Ryu
Published: December 2024

Introduction

This study analyzed the impact of various overload conditions on sprint performance compared to free sprinting, aiming to identify the loading scenarios that most closely replicate the mechanics of unresisted sprints across the full acceleration spectrum. While velocity-based training methods have gained popularity, their applicability is limited to the plateau phase of sprinting.

Methods

To address this limitation, we employed cluster analysis to identify scenarios that best replicate the mechanical characteristics of free sprinting across various overload conditions. Sixteen experienced male sprinters performed sprints under six conditions: unresisted, overspeed (OS) and four overloaded conditions inducing a velocity loss (VL) of 10%, 25%, 50% and 65% using a resistance training device with intelligent drag technology. Ground reaction forces and spatiotemporal parameters were recorded for all steps using a 52-meter force plate system for all sprint conditions.

Results

Cluster analysis revealed four distinct groups aligning with established sprint phases: initial contact, early-acceleration, mid-acceleration, and late-acceleration. Results showed that heavier loads prolonged the mechanical conditions typical of early-acceleration and mid-acceleration phases, potentially enhancing training stimuli for these crucial sprint components of sprint performance. Specifically, VL50 and VL65 loads extended the early-acceleration phase mechanics to steps 7–8, compared to steps 2–4 for lighter loads. Conversely, lighter loads more effectively replicated late-acceleration mechanics, but only after covering substantial distances, typically from the 11- to 29-meter mark onwards.

Discussion

These findings suggest that tailoring overload conditions to specific sprint phases can optimize sprint-specific training and provide coaches with precise strategies for load prescription. These insights offer a more nuanced approach to resistance-based sprint training by accounting for every step across all acceleration phases, rather than focusing solely on the plateau phase, which accounts for only 20–30% of the steps collected during initial contact to peak velocity depending on the analyzed overload condition.
Virtual Prototyping-Based Development of Stepper Motor Design
Authors: Kamberov Konstantin , Todorov Georgi , Zlatev Blagovest
Published: December 2024

This study presents a methodology used in the design development of stepper motors. The methodology unites virtual and physical techniques to assess the structure under development at its various design stages. Virtual prototyping is used twice, at the concept and early design stages. Concept check aims to give more general directions for further design development. In contrast, the simulations at the detailed design stage allow for assessing various design parameters at a high level of confidence. The testing of a physical prototype is used to validate simulation results. It is also used to check the design just before it is finished. The presented methodology is demonstrated in an industrial use case for stepper motor development for hydraulic valve application. The main contribution of this study is related to the way the combination of virtual and physical prototyping and testing at different product development stages applies to the development of stepper motors and other similar products.
Advancing Industrial Object Detection Through Domain Adaptation: A Solution for Industry 5.0
Authors: Fatima Zainab , Zardari Shehnila , Tanveer Muhammad Hassan
Published: December 2024

Domain adaptation (DA) is essential for developing robust machine learning models capable of operating across different domains with minimal retraining. This study explores the application of domain adaptation techniques to 3D datasets for industrial object detection, with a focus on short-range and long-range scenarios. While 3D data provide superior spatial information for detecting industrial parts, challenges arise due to domain shifts between training data (often clean or synthetic) and real-world conditions (noisy and occluded environments). Using the MVTec ITODD dataset, we propose a multi-level adaptation approach that leverages local and global feature alignment through PointNet-based architectures. We address sensor variability by aligning data from high-precision, long-range sensors with noisier short-range alternatives. Our results demonstrate an 85% accuracy with a minimal 0.02% performance drop, highlighting the resilience of the proposed methods. This work contributes to the emerging needs of Industry 5.0 by ensuring adaptable and scalable automation in manufacturing processes, empowering robotic systems to perform precise, reliable object detection and manipulation under challenging, real-world conditions, and supporting seamless human–robot collaboration.
Accuracy Analysis of a Multi-Closed-Loop Truss Antenna with Clearance
Authors: Wu Di , Zhao Jiang , Ma Xiaofei , Chen Jinbao , Chen Chuanzhi
Published: December 2024

Surface accuracy is one of the most crucial indicators for evaluating the performance of a large deployable antenna. It depends on the accuracy of the truss structure of the truss antenna. This paper presents a novel method for accurate analysis of a large deployable truss antenna with 3D joint clearances. The proposed method does not depend on the structure’s style, which is suitable for general multi-closed-loop structures. Firstly, the clearance model of the truss structure is established using a vector description. Then, an error transfer path analysis method is proposed for the multi-closed-loop structure. The distribution probability of the truss antenna’s surface accuracy is also obtained. The efficiency of the method is validated through a numerical example of a planar mechanism with a multi-closed loop. The proposed method is also applied to analyze the surface accuracy of the large deployable antenna with a parabolic cylindrical truss.
Accuracy Assessment of Tomato Harvest Working Time Predictions from Panoramic Cultivation Images
Authors: Naito Hiroki , Ota Tomohiko , Shimomoto Kota , Hosoi Fumiki , Fukatsu Tokihiro
Published: December 2024

The scale of horticultural facilities in Japan is expanding, making the efficient management of labor costs essential, particularly in large-scale tomato production. This study developed a consistent and practical system for predicting harvest working time and estimating the quantity and weight of harvested fruit using panoramic images of cultivation rows. The system integrates a deep learning model, the Mask ResNet-50 convolutional neural network, to count harvestable fruits from images and a predictive algorithm to estimate working time based on the fruit count. The results indicated that the average for all workers could be predicted with an error margin of 30.1% when predicted three days before the harvest date and 15.6% when predicted on the harvest date. The trial also revealed that the accuracy of the predictions varied based on workers’ experience and cultivation methods. This study highlights the system’s potential to optimize harvesting plans and labor allocation, providing a novel tool for reducing labor costs while maintaining efficiency in large-scale tomato greenhouse production.
Winter Wheat SPAD Prediction Based on Multiple Preprocessing, Sequential Module Fusion, and Feature Mining Methods
Authors: Nian Ying , Su Xiangxiang , Yue Hu , Anwar Sumera , Li Jun , Wang Weiqiang , Sheng Yali , Ma Qiang , Liu Jikai , Li Xinwei
Published: December 2024

Chlorophyll is a crucial indicator for monitoring crop growth and assessing nutritional status. Hyperspectral remote sensing plays an important role in precision agriculture, offering a non-destructive approach to predicting leaf chlorophyll. However, crop canopy spectra often face background noise and data redundancy challenges. To tackle these issues, this study develops an integrated processing strategy incorporating multiple preprocessing techniques, sequential module fusion, and feature mining methods. Initially, the original spectrum (OS) from 2021, 2022, and the fusion year underwent preprocessing through Fast Fourier Transform (FFT) smoothing, multiple scattering correction (MSC), the first derivative (FD), and the second derivative (SD). Secondly, feature mining was conducted using Competitive Adaptive Reweighted Sampling (CARS), Iterative Retention of Information Variables (IRIV), and Principal Component Analysis (PCA) based on the optimal preprocessing order module fusion data. Finally, Partial Least Squares Regression (PLSR) was used to construct a prediction model for winter wheat SPAD to compare the prediction effects in different years and growth stages. The findings show that the preprocessing sequential module fusion of FFT-MSC (firstly pre-processing using FFT, and secondly secondary processing of FFT spectral data using MSC) effectively reduced issues such as noisy signals and baseline drift. The FFT-MSC-IRIV-PLSR model (based on the combined FFT-MSC preprocessed spectral data, feature screening using IRIV, and then combining with PLSR to construct a prediction model) predicts SPAD with the highest overall accuracy, with an R2 of 0.79–0.89, RMSE of 4.51–5.61, and MAE of 4.01–4.43. The model performed best in 2022, with an R2 of 0.84–0.89 and RMSE of 4.51–6.74. The best prediction during different growth stages occurred in the early filling stage, with an R2 of 0.75 and RMSE of 0.58. On the basis of this research, future work will focus on optimizing the data processing process and incorporating richer environmental data, so as to further enhance the predictive capability and applicability of the model.
Investigation of the Kinetic Dynamics in the Intermittent Microwave–Hot-Air Combined Drying of Peanut Pods
Authors: An Jiyou , Yan Jianchun , Wei Hai , Liao Xuan , Liu Tao , Xie Huanxiong
Published: December 2024

The drying process is crucial for maintaining the quality of peanut pods and mitigating the risk of mold proliferation. The aim of this study was to investigate the kinetic characteristics of a synergistic intermittent microwave and a hot-air-drying technique, with an emphasis on enhancing efficiency and reducing energy consumption. A comprehensive analysis was performed on key parameters—including moisture content, moisture ratio, drying rate, and effective moisture diffusion coefficient—to elucidate moisture migration during the drying process. The findings indicated that higher microwave power significantly accelerates the drying rate while substantially shortening the drying time for peanut pods. The effective moisture diffusion coefficient was found to range from 0.987 × 10−9 to 1.227 × 10−9 m2/s, with the Verma model demonstrating superior accuracy in predicting drying behavior. The experiment achieved a minimum specific energy consumption of 12,535 kJ/kg and a maximum thermal efficiency of 18.1% at a microwave power density of 0.8 W/g combined with a temperature of 40 °C. However, the observed thermal efficiency was lower than that in previous studies, mainly due to the suboptimal regulation of experimental parameters. Future research should focus on optimizing these parameters and further exploring the impact of this drying method on energy consumption to achieve more efficient and sustainable peanut drying.
Management of Hickory Forest Understory Vegetation Increases Ecosystem Carbon Sequestration, But It Also Increases Soil Greenhouse Gas Emissions in the Short Term
Authors: Shi Haitao , Chen Yangen , Huang Sha , Cheng Xuekun , Chen Huiying , Xu Ruizhi , Zhou Yufeng , Shi Yongjun
Published: December 2024

Managing forest understory has a significant impact on soil greenhouse gas (GHG) emissions and the ecosystem’s capacity for carbon sequestration. However, its specific impacts and mechanisms within hickory (Carya cathayensis Sarg) forests remain unclear. The objective of this study was to examine the effects of different understory vegetation treatments on hickory stands with similar growth history, site conditions, and slopes: Cinnamomum chekiangense (Cinnamomum chekiangense Nakai) and strip-sown ryegrass (Lolium perenne L.) (CR1), Cinnamomum chekiangense and scattered ryegrass (CR2), Torreya grandis (Torreya grandis’ ‘Merrillii’ Hu) and strip-sown wild rapeseed (Brassica napus L.) (TW1), Torreya grandis and scattered wild rapeseed (TW2), and removal of understory vegetation (CK). Twenty experimental plots were established at the Lin’an Forestry Carbon Sink Pioneer Base, and after 12 months of monitoring, the responses of GHG emissions, vegetation, and soil organic carbon (SOC) sequestration were analyzed, revealing the differences in ecosystem carbon sequestration capacity. Compared to CK, CR1, CR2, TW1, and TW2 increased the global warming potential (GWP) by approximately 26%, 55%, 26%, and 16%, respectively. The SOC increased by approximately 76%, 102%, 51%, and 32%, respectively, while the vegetation carbon sink increased by approximately 30%, 27%, 53%, and 62%, respectively. In summary, ecosystem carbon sequestration increased by approximately 109%, 98%, 95%, and 92%, respectively. The findings indicate that managing understory vegetation in pecan forests significantly enhances ecosystem carbon sequestration but also increases soil GHG emissions. To enhance future research priorities, it is essential to focus on increasing carbon sequestration in hickory forests and managing soil GHG emissions through effective and rational understory vegetation management.
Meta-Analysis of the Impacts of Applying Livestock and Poultry Manure on Cadmium Accumulation in Soil and Crops
Authors: Tang Tao , Zhou Hang , Yang Zhuo , Zeng Peng , Gu Jiao-Feng , Mu Yun-Song , Liu Chen-Feng , Han Zi-Yu
Published: December 2024

The return of livestock and poultry manure (LPM) to fields is necessary for sustainable agricultural development, but it is also a primary source of heavy metal contamination in agricultural land, which potentially threatens soil and crops. Conflicting results have been reported in previous studies on the impacts of returning LPM to fields on cadmium (Cd) accumulation in the soil and crops. Herein, we investigated the impacts of applying such manure on Cd accumulation in the soil and crops through meta-analysis. We also explored the relationships of Cd content in the soil and crops with the soil properties, experimental conditions, and manure properties. Moreover, we evaluated the primary reasons for the differences in the results of different studies and the factors influencing them. Upon applying LPM, the contents of soil total Cd, soil available Cd, and crop grain Cd increased by 30.96%, 86.91%, and 20.43%, respectively, and the crop root Cd content decreased by 16.91%. Random forest analysis and decision tree analysis further quantified the importance of each influencing factor and identified the primary factors influencing soil available Cd and grain Cd contents. From the perspective of safe production, some suggestions were made for returning LPM to fields: (1) applying higher pH LPM or increasing the dosage in soils with low Cd content and pH of <5.7; (2) applying LPM to soils with Cd content of <1.8 mg/kg, pH of >5.7, and soil organic matter content of >19 g/kg, which was associated with a low risk of Cd accumulation in crop grains; and (3) applying LPM while planting low-Cd-accumulating crop varieties. This study provides scientific guidance for the safe use of such manure resources and helps to reduce the risk of cadmium accumulation.
Advancements in Predictive Maintenance: A Bibliometric Review of Diagnostic Models Using Machine Learning Techniques
Authors: Vithi Nontuthuzelo Lindokuhle , Chibaya Colin
Published: December 2024

This bibliometric review investigates the advancements in machine learning techniques for predictive maintenance, focusing on the use of Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) for fault detection in wheelset axle bearings. Using data from Scopus and Web of Science, the review analyses key trends, influential publications, and significant contributions to the field from 2000 to 2024. The findings highlight the performance of ANNs in handling large datasets and modelling complex, non-linear relationships, as well as the high accuracy of SVMs in fault classification tasks, particularly with small-to-medium-sized datasets. However, the study also identifies several limitations, including the dependency on high-quality data, significant computational resource requirements, limited model adaptability, interpretability challenges, and practical implementation complexities. This review provides valuable insights for researchers and engineers, guiding the selection of appropriate diagnostic models and highlighting opportunities for future research. Addressing the identified limitations is crucial for the broader adoption and effectiveness of machine learning-based predictive maintenance strategies across various industrial contexts.
A Quadruplex RT-qPCR for the Detection of African Swine Fever Virus, Classical Swine Fever Virus, Porcine Reproductive and Respiratory Syndrome Virus, and Porcine Pseudorabies Virus
Authors: Feng Zhuo , Shi Kaichuang , Yin Yanwen , Shi Yuwen , Feng Shuping , Long Feng , Wei Zuzhang , Si Hongbin
Published: December 2024

African swine fever virus (ASFV), classical swine fever virus (CSFV), porcine reproductive and respiratory syndrome virus (PRRSV), and porcine pseudorabies virus (PRV) induce similar clinical signs in infected pigs, including hyperthermia, anorexia, hemorrhage, respiratory distress, neurological symptoms, and/or abortions in pregnant sows. The differential diagnosis of these diseases relies on laboratory examinations. In this study, a quadruplex RT-qPCR was established using four pairs of specific primers and probes aimed at the B646L (p72) gene of ASFV, the 5′ untranslated region (5′UTR) of CSFV, the ORF6 gene of PRRSV, and the gB gene of PRV for the detection and differentiation of ASFV, CSFV, PRRSV, and PRV. The assay exhibited great sensitivity with limits of detection (LODs) of 134.585, 139.831, 147.076, and 142.331 copies/reaction for ASFV, CSFV, PRRSV, and PRV, respectively. The assay exclusively identified ASFV, CSFV, PRRSV, and PRV, yielding negative results for the other control swine viruses used in this study. The intra-assay and inter-assay coefficients of variation (CVs) were not higher than 1.12%, indicating good reproducibility of the assay. The quadruplex RT-qPCR assay was used to analyze 3116 clinical tissue samples from pigs in Guangxi province, China, from April 2023 to September 2024. ASFV, CSFV, PRRSV, and PRV had positivity rates of 10.84% (338/3116), 0.80% (25/3116), 14.92% (465/3116), and 1.38% (43/3116), respectively, demonstrating a coincidence rate of ≥99.45% with the previously described RT-qPCR assays, which were also used to test these same samples. The established assay was rapid, sensitive, and accurate in detecting and differentiating ASFV, CSFV, PRRSV, and PRV.
Genetic Analysis of HSP70 and HSF3 Polymorphisms and Their Associations with the Egg Production Traits of Bangladeshi Hilly Chickens
Authors: Ali Md Yousuf , Faruque Shakila , Ahmadi Sadequllah , Ohkubo Takeshi
Published: December 2024

In warm environments, thermoregulation in poultry is controlled by heat shock protein 70 (HSP70), whose expression is controlled by heat shock factor 3 (HSF3). Although the association between genetic polymorphisms in these genes and thermotolerance as well as reproductive traits has been extensively studied in mammals, the association has not yet been studied in poultry. This study aimed to explore the relationship between single-nucleotide polymorphisms (SNPs) in these genes and the egg production traits of Bangladeshi hilly chickens. Sequencing and allele-specific PCR (AS-PCR) were used to detect new SNPs and perform genotyping. We identified two novel SNPs (G-399A and A-68G) in the 5′-flanking regions of HSP70 that were significantly associated with egg numbers (ENs) at 161–190 days and increased egg weight (EW) at 40 weeks of age. Furthermore, three SNPs in HSP70 (A258G, C276G and C1431A) and one SNP in HSF3 (A-1388G) were associated with EN at different ages. The haplotype and combined genotypic effects of these two genes were found to be associated with age at sexual maturity (ASM), EN, EW, and body weight at ASM. The identified SNPs and their corresponding haplotypes may be useful in selective breeding to enhance the productivity of chickens in warm environments.
Genome-Wide Association Study of Insertions and Deletions Identified Novel Loci Associated with Milk Production Traits in Dairy Cattle
Authors: Zhao Lu , Teng Jun , Ning Chao , Zhang Qin
Published: December 2024

Genome-wide association study (GWAS) have identified a large number of SNPs associated with milk production traits in dairy cattle. Behind SNPs, INDELs are the second most abundant genetic polymorphisms in the genome, which may exhibit an independent association with complex traits in humans and other species. However, there are no reports on GWASs of INDELs for milk production traits in dairy cattle. In this study, using imputed sequence data, we performed INDEL-based and SNP-based GWASs for milk production traits in a Holstein cattle population. We identified 58 unique significant INDELs for one or multiple traits. The majority of these INDELs are in considerable LD with nearby significant SNPs. However, through conditional association analysis, we identified nine INDELs which showed independent associations. Genomic annotations of these INDELs indicated some novel associated genes, i.e., TRNAG-CCC, EPPK1, PPM1K, PTDSS1, and mir-10163, which were not reported in previous SNP-based GWASs. Our findings suggest that INDEL-based GWASs could be valuable complement to SNP-based GWASs for milk production traits.
Assessing the Variability of Energy Metabolisability in Barley, Rye, and Wheat Varieties for Broiler Diets
Authors: Kaikat Ibtissam , Solà-Oriol David , Pérez José Francisco
Published: December 2024

This trial assessed the variability of energy metabolisability in four varieties of barley, rye, and wheat based on changes in energy and nutrient flow estimations in excreta. Twelve diets were created by combining 40% of each cereal variety and 60% of a common mixture, divided into enzyme-supplemented and non-supplemented versions, resulting in 24 experimental diets that included TiO2 and Yb2O3 as indigestible markers. A total of 432 one-day-old broilers were distributed into 72 cages and fed a single diet from day 1 to 15. Experimental runs were conducted from day 16 to 25 using a crossover design. Diets were alternated between enzyme-supplemented and non-supplemented for each cage. Excreta samples were collected on days 20 and 25. Energy metabolisability was highest (p < 0.001) in wheat (83.3%), followed by barley (77.8%) and lowest in rye (70.6%). The variety influenced energy metabolisability in barley and wheat (p < 0.001) at a wider range than predicted by NIR analyses. The variety influenced the increment of energy in response to enzyme supplementation in barley diets (p < 0.05), with varieties having low metabolisability values showing higher responses. TiO2 and Yb2O3 did not differ in estimating nutrient flow. This study quantifies energy variability among and within cereals and identifies potential variation factors.