bluuebunny/crossref_metadata_2025 huggingface dataset:
An improved U-net and attention mechanism-based model for sugar beet and weed segmentation
Authors: Li Yadong , Guo Ruinan , Li Rujia , Ji Rongbiao , Wu Mengyao , Chen Dinghao , Han Cong , Han Ruilin , Liu Yongxiu , Ruan Yuwen , Yang Jianping
Published: January 2025

Introduction

Weeds are a major factor affecting crop yield and quality. Accurate identification and localization of crops and weeds are essential for achieving automated weed management in precision agriculture, especially given the challenges in recognition accuracy and real-time processing in complex field environments. To address this issue, this paper proposes an efficient crop-weed segmentation model based on an improved UNet architecture and attention mechanisms to enhance both recognition accuracy and processing speed.

Methods

The model adopts the encoder-decoder structure of UNet, utilizing MaxViT (Multi-Axis Vision Transformer) as the encoder to capture both global and local features within images. Additionally, CBAM (Convolutional Block Attention Module) is incorporated into the decoder as a multi-scale feature fusion module, adaptively adjusting feature map weights to enable the model to focus more accurately on the edges and textures of crops and weeds.

Results and discussion

Experimental results show that the proposed model achieved 84.28% mIoU and 88.59% mPA on the sugar beet dataset, representing improvements of 3.08% and 3.15% over the baseline UNet model, respectively, and outperforming mainstream models such as FCN, PSPNet, SegFormer, DeepLabv3+, and HRNet. Moreover, the model’s inference time is only 0.0559 seconds, reducing computational overhead while maintaining high accuracy. Its performance on a sunflower dataset further verifies the model’s generalizability and robustness. This study, therefore, provides an efficient and accurate solution for crop-weed segmentation, laying a foundation for future research on automated crop and weed identification.
Improving panicle blast resistance and fragrance in a high-quality japonica rice variety through breeding
Authors: Ye Junhua , Wang Kai , Wang Yi , Zhao Zhipeng , Yan Ying , Yang Hang , Zhang Lixia , Hu Zejun , Shi Zhenying , Sun Dapeng , Bai Jianjiang , Cao Liming , Wu Shujun
Published: January 2025

Introduction

Huruan1212 (HR1212) is well-regarded for its superior eating and cooking quality in the lower reaches of the Yangtze River in China. Still, its high susceptibility to rice panicle blast and lack of fragrance have limited its further spread and utilization. Pigm and Pi-ta are two dominant genes known for their stable broad-spectrum resistance against rice blast fungus Magnaporthe oryzae, while badh2 is the crucial gene that regulates rice aroma.

Methods

In this study, we utilized a molecular marker-assisted selection backcrossing strategy to introduce Pigm, Pi-ta, and badh2 into introgressed lines employing re-sequencing for precise genetic background selection.

Results

Finally, we selected three introgressed lines, including two that carry Pigm with the highest background recovery rates, showing eating and cooking qualities similar to those of HR1212, and one line that pyramids Pigm, Pi-ta, and badh2, which features a strong aroma. They all displayed significantly enhanced resistance to panicle blast and improved yield compared to HR1212.

Discussion

In conclusion, this study expanded the germplasm resources of japonica, providing a material foundation for enhancing breeding programs aimed at developing rice blast-resistant and high-quality fragrant japonica varieties. Additionally, the study demonstrated that integrating molecular markers and re-sequencing can inform breeders’ decision-making more precisely and efficiently.
Long-term nitrogen fertilization alters the partitioning of amino acids between citrus leaves and fruits
Authors: Zhao Yuanlai , Xiong Huaye , Luo Yayin , Hu Bin , Wang Jie , Tang Xiaodong , Wang Yuehong , Shi Xiaojun , Zhang Yueqiang , Rennenberg Heinz
Published: January 2025

Introduction

The growth of evergreen fruit trees is influenced by the interaction of soil nitrogen (N) and leaf amino acid contents. However, information on free amino acid contents in leaves of fruiting and non-fruiting branches during long-term N fertilizer application remains scarce.

Methods

Here, a four-year field experiment (2018-2021) in a citrus orchard revealed consistently lower total N and amino acid contents in leaves of fruiting compared to non-fruiting branches.

Results and discussion

Appropriate N fertilizer application increased free amino acid and total N contents in leaves of both types of branches and fruits, but excessive amounts led to decreases. Correlation analysis showed that, in the early stage of fruit development, leaves on both types of branches can meet the N requirements of the fruit (R²=0.77 for fruiting, R²=0.82 for non-fruiting). As fruits entered the swelling stage, a significant positive correlation emerged between fruiting branch leaves and fruit total N content (R²=0.68), while the R² for leaves on non-fruiting branches dropped to 0.47, indicating a shift in N supply towards leaves on fruiting branches. Proline and arginine are the most abundant amino acids in these leaves. At fruit maturity, these amino acids account for more than half of the total amino acids in the fruit (29.0% for proline and 22.2% for arginine), highlighting their crucial role in fruit development. Further research is needed to investigate amino acid transport and distribution mechanisms between citrus leaves and fruits.
Improved plant biomass production under low nitrogen conditions through conditional accumulation of the second messenger, guanosine tetraphosphate, in chloroplasts and mitochondria
Authors: Goto Mina , Nemoto Takanari , Sakoda Kazuma , Sakurai Atsushi , Imamura Sousuke , Masuda Shinji
Published: January 2025

To enhance plant biomass production under low nitrogen conditions, we employed a method to artificially and temporarily accumulate the bacterial second messenger, guanosine tetraphosphate (ppGpp), to modify plastidial or mitochondrial metabolism. Specifically, we fused a chloroplast or mitochondrial transit-peptide to the N-terminus of the bacterial ppGpp synthase YjbM, which was conditionally expressed by an estrogen-inducible promoter in Arabidopsis. The resulting recombinant Arabidopsis plants exhibited estrogen-dependent ppGpp accumulation in chloroplasts or mitochondria and showed reduced fresh weight compared to wild type (WT) plants when grown on agar-solidified plates containing a certain amount of estrogen. This finding aligns with the previous study indicating that plastidial ppGpp levels can influence plant biomass production. When the recombinant plants were grown in the soil with estrogen and low nitrogen-containing water at specific time intervals, they exhibited greater fresh weight than WT plants. These results suggest that the conditional accumulation of ppGpp in not only chloroplasts, but also in mitochondria can lead to improved plant biomass production in soil with low nitrogen applications.
Designing community-based strategies to reach non-household contacts of people with tuberculosis in Lusaka, Zambia: a rapid qualitative study among key stakeholders
Authors: Kerkhoff Andrew D. , Foloko Marksman , Kundu-Ng’andu Evelyn , Nyirenda Herbert , Jabbie Zainab , Syulikwa Mainza , Mwamba Chanda , Kagujje Mary , Muyoyeta Monde , Sharma Anjali
Published: January 2025

Background

In high-burden settings, most tuberculosis (TB) transmission likely occurs outside the home. Our qualitative study in Zambia explored the acceptability and preferences for designing TB active case finding (ACF) strategies to reach non-household contacts of people with TB.

Methods

We conducted 56 in-depth interviews with persons with TB (n = 12), TB healthcare workers (HCWs) (n = 10), TB lay HCWs (n = 10), and leaders/owners (n = 12) and attendees (n = 12) of community venue types identified as potential TB transmission locations. Interviews explored TB attitudes and beliefs, and perceptions toward two ACF strategies targeting non-household contacts: (1) “social-network strategy”—persons with newly diagnosed TB reach out to their close non-household contacts and (2) “venue-based strategy”—HCWs conduct screening at community venues frequented by persons with newly diagnosed TB. We used the Consolidated Framework for Implementation Research (CFIR) framework to develop interview topic guides and analyze data using a rapid deductive approach.

Results

All participants felt that TB was an important issue in their community and that new detection strategies were needed. A “social-network strategy” was perceived as acceptable and feasible, where participants noted it was a caring act and could facilitate early diagnosis. For a “venue-based strategy,” most participants suspected TB transmission occurred at bars/taverns due to heavy alcohol use and prolonged time spent in crowded spaces; churches and betting halls were also commonly mentioned locations. Nearly all owners/leaders and patrons/attendees of bars, churches, and betting halls expressed acceptance of a venue-based strategy. They also indicated an interest in participating, citing many benefits, including increased TB knowledge/awareness, early diagnosis, convenience, and possibly reduced transmission, and recommended that the strategy incorporate sensitization, consent, volunteerism, and respectful, confidential, private services. For both strategies, most participants preferred the use of and being approached by trained peer TB survivors to facilitate ACF, given their prior TB patient experience and trust among community members.

Conclusion

Stakeholders found social-network and venue-based TB-ACF strategies highly acceptable, recognizing their potential benefits for individuals and the broader community. Future research should evaluate the feasibility and effectiveness of TB ACF strategies for reaching non-household contacts.
Spatial, temporal, and spatiotemporal cluster detection of malaria incidence in Southwest Ethiopia
Authors: Demoze Lidetu , Gubena Fetlework , Akalewold Eyob , Brhan Helen , Kifle Tigist , Yitageasu Gelila
Published: January 2025

Background

Malaria is a major global health hazard, particularly in developing countries such as Ethiopia, where it contributes to high morbidity and mortality rates. According to reports from the South Omo Zone Health Bureau, despite various interventions such as insecticide-treated bed nets and indoor residual spraying, the incidence of malaria has increased in recent years. Therefore, this study aimed to assess the spatial, temporal, and spatiotemporal variation in malaria incidence in the South Omo Zone, Southwest Ethiopia.

Methods

A retrospective study was conducted using 4 years of malaria data from the South Omo Zone District Health Information Software (DHIS). The incidence rate of malaria per 1,000 people was calculated using Microsoft Excel software. Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant spatial, temporal, and spatiotemporal malaria clusters. Graduated color maps depicting the incidence of malaria were generated using ArcGIS 10.7 software.

Results

Spatial clusters were identified in the districts of Dasenech (RR = 2.06, p < 0.0001), Hamer (RR = 1.90, p < 0.0001), Salamago (RR = 2.00, p < 0.0001), Bena Tsemay (RR = 1.71, p < 0.0001), Malie (RR = 1.50, p < 0.0001), Nyngatom (RR = 1.91, p < 0.0001) and North Ari (RR = 1.05, p < 0.0001) during the period from 08th July 2019 to 07th July 2023. A temporal cluster was identified as the risk period across all districts between 08th July 2022 and 07th July 2023 (RR = 1.59, p = 0.001). Spatiotemporal clusters were detected in Dasenech (RR = 2.26, p < 0.001) Salamago, (RR = 2.97, p < 0.001) Hamer (RR = 1.95, p < 0.001), Malie (RR = 2.03, p < 0.001), Bena Tsemay (RR = 1.80, p < 0.001), Nyngatom (RR = 2.65, p < 0.001), North Ari (RR = 1.50, p < 0.001), and Jinka town (RR = 1.19, p < 0.001).

Conclusion

Significant spatial, temporal, and spatiotemporal clusters in malaria incidence were identified in the South Omo Zone. To better understand the factors contributing to these high-risk areas, further research is needed to explore individual, household, geographical, and climatic factors. Targeted interventions based on these findings could help reduce malaria incidence and associated risks in the region.
An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling
Authors: Zuo Qiuxia , Liu Di , Dong Baoji , Zhou Yuan , Zhao Kexin , Tian Ping
Published: January 2025

Introduction

Surgical site infection (SSI) represents a significant postoperative complication, resulting in extended hospital stays and substantial economic burdens. Previous research on the direct economic impact of SSIs using recursive systems modeling is limited. This study aims to quantify the direct economic losses attributable to SSIs and to dissect the various factors to these losses.

Methods

A retrospective 1:1 matched case–control study was conducted from January 2023 to March 2024 in three tertiary hospitals in Xinjiang, China. Patients with SSIs were matched on a 1:1 basis by hospital, department, age (±5 years), sex, primary diagnosis, and procedure with controls to form case and control groups. Wilcoxon Signed Ranks Test was utilized to quantify the direct economic loss from SSIs. Influencing factors were analyzed using a recursive system model.

Results

Among the 74,258 patients surveyed, 226 developed SSIs, resulting in an infection rate of 0.3%. The total direct economic loss from SSIs at three hospitals was $467,867, with an average loss of $1,364.37 per SSI patient. SSI patients experienced hospital stays 11 days longer than uninfected patients. Multivariate linear regression identified the duration of hospital stay, catheter and ventilator usage, age, number of surgeries, and duration of antibiotic treatment as influencing factors. Recursive system modeling revealed the indirect contributions of the number of surgeries (indirect effect: 0.074), antibiotic use for 17–36 days (indirect effect: 0.063) and ≥ 37 days (indirect effect: 0.045), and debridement procedures (indirect effect: 0.054), as well as the direct contributions of hospital days (direct effect: 0.276), indwelling catheter days (direct effect: 0.260), ventilator days (direct effect: 0.221), and age (direct effect: 0.182).

Conclusion

Recursive system modeling helped identify the key factors influencing the economic losses from SSIs. These findings provide a theoretical basis for healthcare departments to develop targeted policies.
Evaluating the effectiveness of prompt engineering for knowledge graph question answering
Authors: Kosten Catherine , Nooralahzadeh Farhad , Stockinger Kurt
Published: January 2025

Many different methods for prompting large language models have been developed since the emergence of OpenAI's ChatGPT in November 2022. In this work, we evaluate six different few-shot prompting methods. The first set of experiments evaluates three frameworks that focus on the quantity or type of shots in a prompt: a baseline method with a simple prompt and a small number of shots, random few-shot prompting with 10, 20, and 30 shots, and similarity-based few-shot prompting. The second set of experiments target optimizing the prompt or enhancing shots through Large Language Model (LLM)-generated explanations, using three prompting frameworks: Explain then Translate, Question Decomposition Meaning Representation, and Optimization by Prompting. We evaluate these six prompting methods on the newly created Spider4SPARQL benchmark, as it is the most complex SPARQL-based Knowledge Graph Question Answering (KGQA) benchmark to date. Across the various prompting frameworks used, the commercial model is unable to achieve a score over 51%, indicating that KGQA, especially for complex queries, with multiple hops, set operations and filters remains a challenging task for LLMs. Our experiments find that the most successful prompting framework for KGQA is a simple prompt combined with an ontology and five random shots.
Embedding-based pair generation for contrastive representation learning in audio-visual surveillance data
Authors: Wang Wei-Cheng , De Coninck Sander , Leroux Sam , Simoens Pieter
Published: January 2025

Smart cities deploy various sensors such as microphones and RGB cameras to collect data to improve the safety and comfort of the citizens. As data annotation is expensive, self-supervised methods such as contrastive learning are used to learn audio-visual representations for downstream tasks. Focusing on surveillance data, we investigate two common limitations of audio-visual contrastive learning: false negatives and the minimal sufficient information bottleneck. Irregular, yet frequently recurring events can lead to a considerable number of false-negative pairs and disrupt the model’s training. To tackle this challenge, we propose a novel method for generating contrastive pairs based on the distance between embeddings of different modalities, rather than relying solely on temporal cues. The semantically synchronized pairs can then be used to ease the minimal sufficient information bottleneck along with the new loss function for multiple positives. We experimentally validate our approach on real-world data and show how the learnt representations can be used for different downstream tasks, including audio-visual event localization, anomaly detection, and event search. Our approach reaches similar performance as state-of-the-art modality- and task-specific approaches.
Motivation and experiences of dentists of primary care dental clusters in Hungary: a qualitative inquiry
Authors: Sztrilich András , Túri Gergő , Kaposvári Csilla , Teller Rita , Vingender István
Published: January 2025

Background

In recent years, dental clusters and networks have been established in primary care in many countries to improve access to services for the population and develop cooperation between providers. In Hungary, the first dental clusters were established in 2021, and currently, one-third of dental practices have already joined a cluster. The study aimed to gather and analyze early experiences regarding the motivation of participation in primary care dental clusters and experiences of implementation.

Methods

Qualitative in-depth individual interviews with primary care dentists (n = 21). The study was designed to meet the COREQ criteria for reporting qualitative research. The research team members defined a purposive sample of interviewees. All interviews were conducted from March to April 2024. A qualitative content analysis method was used to analyze the interview transcripts. The WHO health system framework was chosen for the theoretical framework of the analysis.

Results

The motivations for joining a dental cluster were financial reasons, professional development and knowledge exchange. Lack of information and distrust were barriers to joining the dental clusters. Different professional management practices have developed within the clusters. In the interviewees' opinion, the population's access to preventive dental services has not yet changed substantially under the new operational model. The portfolio of services offered by dental clusters could be expanded to include a range of types of care. Digital health technologies and innovative solutions should be developed and widely adopted.

Conclusions

In designing policy measures to promote the broader adoption of the dental cluster model, it is helpful to consider the different factors influencing dentists' decisions during implementation. Dental clusters can benefit the public and dentists, but further development of the model and improvement of the primary conditions for the operation of practices are essential.
Green norms in the workplace to promote environmental sustainability: the positive effect on green innovative work behaviors and person-environment relationship
Authors: Dibattista Ilaria , Berdicchia Domenico , Mazzardo Elena , Masino Giovanni
Published: January 2025

Introduction

This study explores the relevance of behavioral and psychological factors in contributing to organizational environmental sustainability in the workplace.

Methods

Data were obtained from 271 workers in 5 organizations operating in the manufacturing sector in Italy and analyzed through a regression methodology. We tested two models, in which the employees’ perception of the work climate is derived from different sets of norms. In one model, we explored the influence of organizational policies and practices (injunctive norms). In another model, we explored the influence of peers’ behavior (social, descriptive norms).

Results

The results show a positive impact of the employees’ perception of their work climate on both their propensity to engage in innovative green behaviors and their sense of personal connection with the environment, via environmental commitment. Moreover, we found that the employee’s organizational identification positively moderates the effect on green innovative behavior.

Discussion

This study underscores the relevance of creating and maintaining a pro-environment work climate in order to foster pro-environment innovative behavioral changes. Also, the results indirectly suggest that the influence on the sense of personal connection with the environment may generate a positive spill-over effect into the private life of workers.
Applying intervention mapping to develop a program for promoting short physical activity breaks during class time in upper secondary schools: the MOVE12 protocol study
Authors: Barene Svein , Johansen Patrick Foss , Tjomsland Hege Eikeland , Ølberg Rolf Inge , Thurston Miranda
Published: January 2025

Introduction

Physical inactivity is a global health challenge, exacerbated by increased screen time and sedentary behaviors. Enhancing physical activity levels at schools offers a promising approach to promote lifelong healthy habits.

Methods

This protocol paper outlines the MOVE12 pilot study, a 12-week intervention study designed to increase physical activity among Norwegian upper secondary school students through 6–7-min daily MOVE-breaks integrated into lessons. Developed using the six-phase Intervention Mapping (IM) protocol, grounded in the social-ecological model and self-determination theory, the intervention focuses on fostering motivation and creating a supportive environment. Key steps include needs assessment, performance objectives, theoretical methods, and program structuring for sustainability.

Results

Linear mixed models, t-tests, and regression analyses will evaluate quantitative outcomes, while qualitative focus groups will explore engagement and behavior change.

Discussion

MOVE12 provides insights into scalable school-based interventions addressing physical inactivity, highlighting the potential of the IM framework to establish sustainable health promotion strategies.
Venlafaxine-induced serotonin syndrome causing bilateral cerebral strokes: a case report
Authors: Mein Nils , Mammadli Khadija , Luessi Felix , Uphaus Timo
Published: January 2025

A 21-year-old Caucasian woman was admitted to our neurologic intermediate care unit after attempting suicide by ingesting an estimated 15 g venlafaxine (Trevilor retard®), adding up to a serum concentration of approximately 17,943 μg/l. Brain magnetic resonance imaging (MRI) revealed bilateral cortical restricted-diffusion patterns, indicating ischemic lesions. We report a case of venlafaxine-induced serotonin syndrome most likely cumulating in diffuse artery vasospasm due to an autonomic effect mediated by the serotonergic and adrenergic systems, causing myocardial and cerebral injuries. The serotonin syndrome was treated symptomatically by administering fluids and benzodiazepines and managing the hyperthermia using paracetamol; also, medication with venlafaxine was stopped, and the hypoglycemia was treated. After 6 days, our patient was discharged to the psychiatric facility with no remaining neurologic deficit. The case report provides evidence of ischemic stroke as a rare adverse event of venlafaxine intoxication. Furthermore, we aim to increase awareness of hypoglycemia and epileptic seizures as complications of venlafaxine intoxication. In addition, we demonstrate important pitfalls in the diagnostic procedure and propose a treatment regimen for the underlying serotonin syndrome.
Spatial distribution and influencing factors of China’s overseas farmland investment projects under the background of food security
Authors: Wang Yameng , Zou Fan , Wang Luning , Jin Huawang , Ma Linyan
Published: January 2025

Since the 21st century, overseas farmland investment has gradually become the focus of research in the field of transnational agricultural investment. Under the background of China’s “going out” strategy, exploring the spatial distribution pattern and influencing factors of China’s overseas farmland investment activities in different regions of the world and reducing domestic food supply pressure through effective use of overseas farmland resources has become an important path for China to ensure food security. Based on the case data of China’s overseas cultivated Land investment in the Land Matrix database, this paper sorted out the utilization status of China’s global cultivated land resources, and analyzed the spatial distribution and influencing factors by using spatial analysis method and grey correlation analysis method. The results show that: (1) At present, the host countries of China’s overseas cultivated land investment have obvious spatial aggregation, showing the spatial characteristics of “small agglomeration and large dispersion,” and have the characteristics of distribution along the border and river; (2) China’s overseas farmland investment is affected by geo-economy, resource base, geo-culture and geopolitics, and the degree of impact is weakened in turn. Among them, the average annual import and export value, total water resources and other indicators have a significant impact on the investment choice of Chinese enterprises. Based on this, on the basis of identifying the spatial distribution pattern of China’s global overseas farmland investment and development and analyzing its key driving factors, this study proposed the path that overseas farmland investment and development can help improve the resilience of food system with the goal of ensuring the food security of sustainable agricultural system. It provides a theoretical basis for the country to formulate food security strategy based on overseas farmland investment and guide enterprises to invest overseas farmland.
Analysis of artery injury types and clinical characteristics of patients with transcatheter angioembolization after percutaneous nephrolithotomy
Authors: Meng Xianghu , Cong Rong , Hua Yibo , Wang Zengjun , Song Ninghong , Yang Wei , Song Rijin
Published: January 2025

Background

There is no systematic classification of renal vascular injuries conducted for severe post-percutaneous nephrolithotomy (PCNL) bleeding.

Aim

The aim of the present study was to explore the various types of artery injury and clinical characteristics of patients who underwent transcatheter angioembolization (TAE) after PCNL.

Methods

A retrospective analysis was performed on 52 patients who underwent renal arteriography (RA) because of severe bleeding after PCNL between April 2009 and December 2023. Among the patients, 38 underwent TAE due to positive RA results. Clinical data on the TAE patients, such as gender, age, body mass index, TAE interval, hemoglobin (Hb) decrease, operation time, stone size, the number and size of tracts, and clinical bleeding type, were summarized. The types of artery injury in TAE patients and their relationships with clinical characteristics were analyzed.

Results

Retrospective analysis revealed that, among the 38 TAE patients (32 males and 6 females), the mean TAE interval, average Hb decrease, mean tract number, and mean tract size reached 5.00 (6.25) days, 44.50 (24.50) g/L, 1 (0.25), and F20(6), respectively. Among the TAE patients, four kinds of vascular injury were observed, namely, 18 cases of pseudoaneurysm (PA), 12 cases of arteriocaliceal fistula (ACF), 7 cases of arteriovenous fistula (AVF), and 1 case of arterioperirenal fistula (APF). Analysis of the clinical characteristics of the three types of vascular injury (PA, ACF, and AVF) revealed that the number of tracts was the only factor that differed.

Conclusion

The RA results indicate that the types of postoperative renal artery injury mainly include PA, ACF, AVF, and APF, and the number of tracts may be related to the type of vascular injury.
Zoonotic diseases awareness and food safety practices among livestock farmers in Nepal
Authors: Subedi Deepak , Dhakal Alok , Jyoti Sumit , Paudel Sanjay , Ranabhat Ganesh , Tiwari Ananda , Al-Mustapha Ahmad I.
Published: January 2025

Interactions between humans and livestock could increase the risk of zoonotic disease transmission. In addition, limited knowledge of zoonoses and foodborne diseases among livestock farmers could heighten the risks of foodborne illness and outbreaks of zoonotic diseases. This study evaluated the awareness of zoonotic diseases and preventive practices for zoonotic and foodborne diseases among livestock farmers of the Chitwan, Rupandehi, and Tanahun districts of Nepal by conducting a cross-sectional survey of 280 livestock farmers. They were recruited using the purposive sampling method from October to December 2022. Descriptive statistics revealed that most (72.1%; n = 202/280) livestock farmers were aware of zoonosis. None of the farmers knew about the zoonotic nature of leptospirosis. Two-thirds of pig farmers (67%; n = 12/18) were aware of zoonotic transmission of swine flu, and more than half of the poultry (58%; 50/86) farmers knew about zoonotic avian influenza. The majority of the farmers who had dogs (83%) and cats (89.4%) in their homes or farms knew that rabies can be transmitted to humans from dogs or cats. The multivariable logistic regression analysis revealed that farmers from the Rupandehi district (aOR: 5.56; 95% CI: 2.18–14.22) and Chitwan (aOR: 6.52; 95% CI: 2.46–17.25) had a higher odds of having good preventive practices than those from Tanahun. Also, farmers who had no sickness in the past 6 months after consumption of animal products were three times (aOR: 2.98; 95% CI: 1.48–6.01) more likely to have better practices. Furthermore, secondary education (aOR: 3.64; 95% CI: 1.41–9.44) was a significant positive predictor of good zoonotic diseases and food safety preventive practices. Our study underscores the necessity to enhance Nepalese livestock farmers’ awareness and practices regarding zoonotic and foodborne diseases. It emphasizes the importance of understanding risks, effective behavioral change strategies, and engaging farmers in developing zoonotic disease and foodborne illness prevention programs.
On Assessing the Performance of LLMs for Target-Level Sentiment Analysis in Financial News Headlines
Authors: Muhammad Iftikhar , Rospocher Marco
Published: January 2025

The importance of sentiment analysis in the rapidly evolving financial markets is widely recognized for its ability to interpret market trends and inform investment decisions. This study delves into the target-level financial sentiment analysis (TLFSA) of news headlines related to stock. The study compares the performance in the TLFSA task of various sentiment analysis techniques, including rule-based models (VADER), fine-tuned transformer-based models (DistilFinRoBERTa and Deberta-v3-base-absa-v1.1) as well as zero-shot large language models (ChatGPT and Gemini). The dataset utilized for this analysis, a novel contribution of this research, comprises 1476 manually annotated Bloomberg headlines and is made publicly available (due to copyright restrictions, only the URLs of Bloomberg headlines with the manual annotations are provided; however, these URLs can be used with a Bloomberg terminal to reconstruct the complete dataset) to encourage future research on this subject. The results indicate that the fine-tuned Deberta-v3-base-absa-v1.1 model performs better across all evaluation metrics than other evaluated models in TLFSA. However, LLMs such as ChatGPT-4, ChatGPT-4o, and Gemini 1.5 Pro provide similar performance levels without the need for task-specific fine-tuning or additional training. The study contributes to assessing the performance of LLMs for financial sentiment analysis, providing useful insights into their possible application in the financial domain.
Event-Triggered Bipartite Formation Control for Switched Nonlinear Multi-Agent Systems with Function Constraints on States
Authors: Hou Yingxue , Li Shu
Published: January 2025

A distributed adaptive fuzzy event-triggered bipartite formation tracking control scheme is proposed for switched nonlinear multi-agent systems (MASs) with function constraints on states. Fuzzy logic systems (FLSs) are used to identify uncertain items. To improve the transient performance of the system, a fixed-time prescribed performance function (FTPPF) is introduced to make the formation error converge to a prescribed boundary range within a fixed time. Considering that the state constraint boundary is restricted by multiple pieces of information (historical state, topological relationship, neighbor agent output, leader signal and time), a tan-type barrier Lyapunov function (BLF) is constructed to address the challenges brought by the state function constraint. The shortcoming of the “explosion of complexity” is compensated by fusing the backstepping control and command filter. To mitigate the communication burden while ensuring a steady-state performance, a distributed event-triggered fixed-time bipartite formation control scheme is proposed. Finally, the performance of the proposed control method is verified by an MAS consisting of four followers and one leader.
Robust Onboard Orbit Determination Through Error Kalman Filtering
Authors: Ceresoli Michele , Colagrossi Andrea , Silvestrini Stefano , Lavagna Michèle
Published: January 2025

Accurate and robust on-board orbit determination is essential for enabling autonomous spacecraft operations, particularly in scenarios where ground control is limited or unavailable. This paper presents a novel method for achieving robust on-board orbit determination by integrating a loosely coupled GNSS/INS architecture with an on-board orbit propagator through error Kalman filtering. This method is designed to continuously estimate and propagate a spacecraft’s orbital state, leveraging real-time sensor measurements from a global navigation satellite system (GNSS) receiver and an inertial navigation system (INS). The key advantage of the proposed approach lies in its ability to maintain orbit determination integrity even during GNSS signal outages or sensor failures. During such events, the on-board orbit propagator seamlessly continues to predict the spacecraft’s trajectory using the last known state information and the error estimates from the Kalman filter, which were adapted here to handle synthetic propagated measurements. The effectiveness and robustness of the method are demonstrated through comprehensive simulation studies under various operational scenarios, including simulated GNSS signal interruptions and sensor anomalies.
Rheology and Stability of Hydrocarbon-Based Gelled Fuels for Airbreathing Applications
Authors: Dell’Acqua Simone , Morando Francesco , Carlotti Stefania , Maggi Filippo
Published: January 2025

Gelled fuels are rheologically complex, non-Newtonian fluids. They combine the benefits of both liquid and solid states, reducing risks of leakage, spilling, and sloshing during storage while maintaining the ability to be sprayed inside a combustion chamber. Additionally, suspending energetic particles, such as metal powders of aluminum and boron, can significantly enhance their energy density compared to conventional liquid fuels. In this study, several kerosene-based and ethanol-based formulations were experimentally investigated, using both organic and inorganic gelling agents. The compositions were optimized in terms of the gellant amount and manufacturing process. Some of the most promising gellants for kerosene include fatty acids, such as Thixcin® R or THIXATROL® ST, and metallic soaps, such as aluminum stearate and zinc stearate. The effects of various co-solvents were assessed, including ketones (methyl isoamyl ketone, methyl ethyl ketone, and acetone) and alcohols (ethanol and octadecanol). Sugar polymers like hydroxypropyl cellulose were tested as gelling agents for ethanol. A preliminary rheological analysis was conducted to characterize their behavior at rest and under shear stress. Finally, a novel approach was introduced to study the stability of the gels under vibration, which was derived from a realistic mission profile of a ramjet. Finally, the ideal gravimetric specific impulse was evaluated through ideal thermochemical computations. The results showed that promising formulations can be found in both kerosene-based and ethanol-based gels. Such compositions are of interest in practical airbreathing applications as they have demonstrated excellent stability under vibration, ideal combustion properties, and pronounced shear-thinning behavior.
The Evolution of Policies for the Resource Utilization of Livestock Manure in China
Authors: Lin Haoyu , Jiao Hongchao , Lin Hai , Xu Xuanguo
Published: January 2025

With the continuous development of animal husbandry, the harmless handling and resource utilization of livestock manure has gradually become a bottleneck problem in sustainable agriculture and livestock production in China. This study evaluates the policies related to manure handling and utilization in different economic development periods in China. The decreased pollutant discharge from livestock manure indicates the effectiveness of the strategy aiming to encourage the construction of manure treatment facilities and resource utilization in cropland and to establish a sound legal system for pollutant discharge. New policies and measures should be introduced to promote the coupling of intensive livestock breeding and crop planting, with the direction of nutrient management planning and the incorporation of a service platform for the resource utilization of manure. Technological innovation in green livestock breeding should be supported by policies to achieve source reduction in pollutants in breeding waste.
Correction: Liu et al. Two-Stage Multimodal Method for Predicting Intramuscular Fat in Pigs. Agriculture 2024, 14, 1843
Authors: Liu Wenzheng , Liu Tonghai , Zhang Jianxun , Wang Fanzhen
Published: January 2025

In the published article [...]
Effects of Irrigation with Treated Slaughterhouse Effluent and Bradyrhizobium spp. Inoculation on Soybean Development and Productivity: Strategies for Sustainable Management
Authors: Murad Lima Ana Carolina , Brichi Lisiane , Trevisan Lucas Renato , Leão de Souza Dominguez André , Nocera Santiago Gustavo , Gomes Tamara Maria , Rossi Fabrício
Published: January 2025

Water scarcity challenges in agriculture are prompting the exploration of alternative irrigation sources, including treated effluents. This study investigates the effects of irrigation with treated slaughterhouse effluent on soybean productivity and development, with and without inoculation, over two cropping cycles. Plant performance was significantly influenced by environmental factors and the interaction between effluent and inoculation. Plant height and leaf area were greater in the second cycle, with effluent enhancing growth and foliar development. Fresh and dry shoot biomass showed significant interactions among cycle, inoculation, and effluent, with higher effluent concentrations combined with inoculation being most effective in the first cycle. Foliar nitrogen concentrations were higher in the first cycle, particularly at elevated effluent doses, while foliar sodium showed a positive correlation with nitrogen and a negative correlation with magnesium. Chlorophyll indices varied across developmental stages, with maximum chlorophyll b estimated at 85.35% effluent irrigation. Soybean yield did not vary significantly with effluent dilutions, suggesting environmental factors had a greater influence. In conclusion, treated effluent irrigation represents a sustainable strategy for soybean production, optimizing water and nutrient use while reducing reliance on chemical fertilizers.
Improvement of Citrus Yield Prediction Using UAV Multispectral Images and the CPSO Algorithm
Authors: Xu Wenhao , Liu Xiaogang , Dong Jianhua , Tan Jiaqiao , Wang Xulei , Wang Xinle , Wu Lifeng
Published: January 2025

Achieving timely and non-destructive assessments of crop yields is a key challenge in the agricultural field, as it is important for optimizing field management measures and improving crop productivity. To accurately and quickly predict citrus yield, this study obtained multispectral images of citrus fruit maturity through an unmanned aerial vehicle (UAV) and extracted multispectral vegetation indices (VIs) and texture features (T) from the images as feature variables. Extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), gaussian process regression (GPR), and multiple stepwise regression (MSR) models were used to construct citrus fruit number and quality prediction models. The results show that, for fruit number prediction, the XGB model performed best under the combined input of VIs and T, with an R2 = 0.792 and an RMSE = 462 fruits. However, for fruit quality prediction, the RF model performed best when only the VIs were used, with an R2 = 0.787 and an RMSE = 20.0 kg. Although the model accuracy was acceptable, the number of input feature variables used was large. To further improve the model prediction performance, we explored a method that utilizes a hybrid coding particle swarm optimization algorithm (CPSO) coupled with XGB and SVM models. The coupled models had a significant improvement in predicting the number and quality of citrus fruits, especially the model of CPSO coupled with XGB (CPSO-XGB). The CPSO-XGB model had fewer input features and higher accuracy, with an R2 > 0.85. Finally, the Shapley additive explanations (SHAP) method was used to reveal the importance of the normalized difference chlorophyll index (NDCI) and the red band mean feature (MEA_R) when constructing the prediction model. The results of this study provide an application reference and a theoretical basis for the research on UAV remote sensing in relation to citrus yield.
The Role of European Equestrian Institutions in Training Professionals: Outcomes from a Workshop on Horse Welfare in Equestrian Education
Authors: Torell Palmquist Gabriella , Känsälä Alveheim Nina , Huot-Marchand François , Ashton Lisa , Lewis Victoria
Published: January 2025

This paper highlights and summarizes the experiences and perceptions of European equestrian educational experts from a workshop held at the French National Riding School in Saumur. The workshop, which brought together fifty leading experts, aimed to address challenges in equestrian education, identify common ground, and share best practices. Using ‘The World Café’ method, the participants were divided into groups to discuss four key topics: the relationship between horses and humans, diversity of perspectives versus common ground, training philosophy, and social acceptability. A follow-up online focus group was conducted six months later, and the discussions were transcribed and analyzed using qualitative content analysis. The results revealed the need for a universal cultural shift towards an evidence-based approach to riding and training horses, with equine welfare at its core. Key challenges, such as anthropomorphism, varying standards across disciplines and countries, and the evolving horse–human relationship, pose risks to the social license to operate. The findings suggest that educational institutions, with their shared values, are well-positioned to lead this change, although further research is needed to address pedagogical challenges. The study also emphasizes the importance of communicating ’good news stories’ to promote evidence-based practices in training and competition.
METTL3 and FTO Regulate Heat Stress Response in Hu Sheep Through Lipid Metabolism via m6A Modification
Authors: Chen Bowen , Yuan Chao , Guo Tingting , Liu Jianbin , Lu Zengkui
Published: January 2025

In an established hepatocyte lipid deposition heat stress model, the expression levels of METTL3 and FTO were significantly upregulated (p < 0.05), indicating that METTL3 and FTO play important roles in the process of lipid deposition heat stress in hepatocytes. Transcriptome and metabolome analyses showed that lipid deposition heat stress had significant effects on the linoleic acid, linolenic acid, glycerophospholipid, and arachidonic acid metabolic pathways in hepatocytes. After METTL3 knockdown, the m6A methylation level decreased, but the difference was not significant (p > 0.05), the FABP4 and Accα expression levels increased, and the HSP60, HSP70, and HSP110 expression levels decreased significantly. After METTL3 overexpression, the m6A methylation level increased significantly and the expression levels of FABP4, ATGL, Accα, HSP60, HSP70, HSP90, and HSP110 decreased significantly, indicating that the overexpression of METTL3 reduced the expression of heat shock genes by inhibiting the lipid-deposition-related gene expression in an m6A-dependent manner. The m6A methylation level increased significantly after FTO knockdown, while HSP60, HSP110, FABP4, ATGL, and Accα expression levels were significantly reduced. Following FTO overexpression, the m6A methylation level and HSP60, HSP90, and HSP110 expression levels significantly decreased, while the ATGL and Accα expression levels significantly increased. This indicates that the overexpression of FTO promoted the expression of lipid-deposition-related genes in an m6A-dependent manner to reduce the expression of heat shock genes. Transcriptome and metabolome sequencing screened a large number of differential genes and metabolites, and a KEGG enrichment analysis showed that m6A methylation mainly regulated heat stress by affecting the TNF, cAMP, MAPK, lipolysis, and synthesis pathways in hepatocytes. In the lipid deposition heat stress model of preadipocytes, the regulation of gene expression was similar to that in hepatocytes.