bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary supplementation with N-acetylcysteine confers a protective effect on muscle and liver in lipopolysaccharide-challenged piglets
Authors: Li Peng , Zhou Hancong , Yang Yuzhu , Wu Mengjun , Zhao Di , Wang Lei , Yi Dan , Hou Yongqing
Published: September 2024

N-acetylcysteine (NAC) is a well-established antioxidant that offers exciting opportunities for intestinal health in weaned piglets, while the effects of NAC on muscle and liver has not been fully characterized. Therefore, the present study was performed to investigate the effects of dietary supplementation with NAC on muscle and liver in weaned piglets challenged with lipopolysaccharide (LPS). Twenty-four piglets (24-day-old) were randomly assigned to three treatment groups, the piglets in the control (CTR) and LPS- challenged (LPS) groups were fed the basal diet and those in the LPS+ NAC group was fed the basal diet supplemented with 500 mg/kg NAC. The animal trial lasted for 21 days. At the end of the trial, piglets in the LPS and LPS+ NAC groups were injected intraperitoneally with LPS (100 μg/kg body weight) and piglets in the CTR group were administrated with an equal volume of normal saline. 3 h later, the blood was collected and tissue samples were obtained after 6 h of LPS or normal saline treatment. The results showed that the level of IL-1β, and the mRNA levels of C-X-C motif chemokine receptor 3 (CXCR3) and interferon-γ (IFN-γ) in the liver were up-regulated, and the mRNA levels of insulin-like growth factor 1 (IGF-1), total glutathione (T-GSH), and the ratio of total protein to DNA in the liver were decreased under LPS challenge (P < 0.05). At the same time, LPS increased the level of H2O2 and decreased the content of T-GSH and DNA in the longissimus dorsi and gastrocnemius muscles (P < 0.05). In addition, the percentage of monocytes and the level of epidermal growth factor (EGF) were down-regulated in the LPS treatment (P < 0.05). Interestingly, dietary NAC supplementation reversed the above changes induced by LPS (P < 0.05). Furthermore, NAC might alleviate the muscle and liver injury in LPS-challenged piglets by regulating the expression of genes related to the type I interferon signaling pathway, as well as hypoxia inducible factor 1 (HIF1) and nuclear factor erythroid-2 related factor 2 (Nrf-2). Our findings suggested that dietary supplementation with NAC could benefit the health of muscle and liver in LPS-challenged weaned piglets.
Lipid profiling of RON and DEK-dependent signaling in breast cancer guides discovery of gene networks predictive of poor outcomes
Authors: Vicente-Muñoz Sara , Davis James C. , Lane Adam , Lane Andrew N. , Waltz Susan E. , Wells Susanne I.
Published: September 2024

Recurrent and metastatic breast cancer is frequently treatment resistant. A wealth of evidence suggests that reprogrammed lipid metabolism supports cancer recurrence. Overexpression of the RON and DEK oncoproteins in breast cancer is associated with poor outcome. Both proteins promote cancer metastasis in laboratory models, but their influence on lipid metabolite levels remain unknown. To measure RON- and DEK-dependent steady-state lipid metabolite levels, a nuclear magnetic resonance (NMR)-based approach was utilized. The observed differences identified a lipid metabolism-related gene expression signature that is prognostic of overall survival (OS), distant metastasis-free survival (DMFS), post-progression survival (PPS), and recurrence-free survival (RFS) in patients with breast cancer. RON loss led to decreased cholesterol and sphingomyelin levels, whereas DEK loss increased total fatty acid levels and decreased free glycerol levels. Lipid-related genes were then queried to define a signature that predicts poor outcomes for patients with breast cancer patients. Taken together, RON and DEK differentially regulate lipid metabolism in a manner that predicts and may promote breast cancer metastasis and recurrence.
Repeated CT scans on 12,984 Asians to diagnose lung cancer once it is suspected
Authors: Vy Vu Pham Thao , Chien Li-Nien , Chen Wan-Ting , Lin Wan-Ying , Chang Yeun-Chung , Hsu Hsian-He , Chan Wing P.
Published: September 2024

In Taiwan, lung cancer remains the leading cause of cancer-related fatalities, resulting in substantial healthcare expenses. This research aims to evaluate both the frequency and the costs of low-dose computed tomography (LDCT) in individuals suspected of having lung cancer until their diagnosis of cancer. LDCT screening was not conducted on a population-wide scale, and asymptomatic participants had to cover the expenses for the screening personally or reimburse from other sources. If the screening results were positive or suspicious, National Health Insurance (NHI) could be utilized for subsequent follow-up examinations. This cohort study utilized the NHI Database and focused on individuals with suspected cases of lung cancer identified between 2010 and 2014. A total of 17,572 suspected new lung cancer cases were initially identified and assigned to the relevant International Classification of Diseases codes. Individuals with suspected lung cancer received a diagnosis following an average follow-up period of 2.24 (95%CI, 2.11-2.37) years, and required the use of 2.36 (95%CI, 2.20-2.51) repeated CT scans. The NHI expenditures incurred by the use of CT scans for monitoring suspected lung cancer cases were relatively modest.
Case report: Cardiac neuroendocrine carcinoma and squamous cell carcinoma treated with MR-guided adaptive stereotactic radiation therapy
Authors: Chen Xinru , Weng Julius K. , Sobremonte Angela , Lee Belinda M. , Hughes Neil W. , Mohammedsaid Mustefa , Zhao Yao , Wang Xiaochun , Zhang Xiaodong , Niedzielski Joshua S. , Shete Sanjay S. , Court Laurence E. , Liao Zhongxing , Lee Percy P. , Yang Jinzhong
Published: September 2024

We present two cases of cardiac metastases adjacent to the right ventricle in a 55-year-old male and a 61-year-old female, both treated with magnetic resonance (MR)-guided adaptive stereotactic radiation therapy (SBRT). The prescribed regimen was 30Gy delivered in 3 fractions using a 1.5 Tesla magnetic resonance linear accelerator (MR-linac). Patients exhibited favorable tolerance to the treatment, with no observed acute toxicity.
Testing home-based exercise strategies in underserved minority cancer patients undergoing chemotherapy (THRIVE) trial: a study protocol
Authors: Yan Huimin , Gonzalo-Encabo Paola , Wilson Rebekah L. , Christopher Cami N. , Cannon James D. , Kang Dong-Woo , Gardiner John , Perez Michelle , Norris Mary K. , Gundersen Daniel , Hayman Laura L. , Freedman Rachel A. , Rebbeck Timothy R. , Shi Ling , Dieli-Conwright Christina M.
Published: September 2024

Background

Higher rates of physical inactivity and comorbid conditions are reported in Hispanic/Latinx and Black cancer patients receiving chemotherapy compared to their White counterparts. Despite the beneficial effect of exercise training for cancer patients, rates of participation in exercise oncology clinical trials are low among disadvantaged and racial and ethnic minority groups. Here, we will examine the effect of an exercise intervention using a novel, accessible, and cost-effective home-based exercise approach among Hispanic/Latinx and Black cancer patients receiving chemotherapy on exercise participation and cardiovascular disease risk.

Methods

The THRIVE trial is an 8-month prospective, three-arm study of 45 patients who are randomized in a 1:1:1 fashion to a supervised exercise intervention (SUP), unsupervised exercise (UNSUP), or an attention control (AC) group. Eligible patients include those with breast, colorectal, or prostate cancer, who are sedentary, overweight or obese, self-identify as Hispanic/Latinx or Black, and plan to receive chemotherapy. Patients randomized to the SUP group participate in a home-based 16-week periodized aerobic and resistance exercise program performed three days per week, supervised through video conference technology. Patients randomized to the UNSUP group participate in an unsupervised 16-week, telehealth-based, periodized aerobic and resistance exercise program performed three days per week using the same exercise prescription parameters as the SUP group. Patients randomized to the AC group receive a 16-week home-based stretching program. The primary outcome is changes in minutes of physical activity assessed by 7-day accelerometry at post-intervention. Secondary outcomes include cardiovascular risk factors, patient-reported outcomes, and physical function. Outcome measures are tested at baseline, post-intervention at month 4, and after a non-intervention follow-up period at month 8.

Discussion

The THRIVE trial is the first study to employ a novel and potentially achievable exercise intervention for a minority population receiving chemotherapy. In addition, this study utilizes an intervention approach to investigate the biological and behavioral mechanisms underlying exercise participation in these cancer patients. Results will guide and inform large randomized controlled trials to test the effect of home-based exercise on treatment outcomes and comorbid disease risk in minority patients with cancer undergoing chemotherapy.

Clinical trial registration

https://classic.clinicaltrials.gov/ct2/show/NCT05327452, identifier (NCT#05327452).
Case report: Report of a case of female adnexal malignant tumor of Wolffian origin
Authors: Ji Shujun , Yu Xiao , Xia Yufang , Yin Yifan , Ge Tingting , Cheng Lihua , Tian Cui , Lou Yanhui
Published: September 2024

A 33-year-old young woman with a rare female appendage tumor of suspected Wolffian origin was initially diagnosed with a benign lesion after the resection of a tubal lesion due to the benign cytomorphology of the tumor tissue. However, 1 year after surgery, she was diagnosed with stage IV fallopian tube cancer due to a recurrence, which presented with substantial ascites and invasion of multiple organs, including the bilateral ovaries, intestines, pelvic peritoneum, greater omentum, and appendix. After tumor cytoreduction, the patient responded well to treatment, which included a regimen of platinum-based drugs combined with docetaxel, aromatase inhibitors such as letrozole, antihormonal therapy, and targeted therapy with bevacizumab.
HMAE: a high-fidelity multi-agent simulator for economic phenomenon emergence
Authors: Wang Chao , Ma Xitong , Jin Xing , Zeng Honghai , Wang Zhen
Published: September 2024

Economic models based on multi-agents are increasingly attracting attention and can provide a new perspective for exploring the causes behind social phenomena at the individual level. Existing research usually adopts society-level learning methods, and more research on micro-level heterogeneity among individuals is needed. For this, we propose a high-fidelity multi-agent economy (HMAE) model based on evolutionary game theory, including three types of agents: workers, firms, and the government. In particular, we characterize worker heterogeneity regarding laziness factors, work endowments, and commuting distances. These agents continuously and iteratively update their strategies by randomly exploring and imitating their neighbors to maximize their utility value. We simulated the evolution process of agent behavioral decisions through experiments and found that individual heterogeneity can significantly affect the decisions of workers and firms. These phenomena are consistent with some economic evolution trends in real life, and our research can provide an analytical tool for analyzing the causes of emerging economic phenomena.
Clinical characteristics of adults with alcohol dependence syndrome comorbid with antisocial personality disorder: a cross-sectional study
Authors: Jarcuskova Dominika , Pallayova Maria , Carnakovic Simona , Frajka Maria , Fidmik Jan , Bednarova Aneta
Published: September 2024

Introduction

Antisocial Personality Disorder (ASPD) is characterized by a pervasive pattern of disregard for and violation of the rights of others, typically emerging by age 15 years and involving behaviors such as deceitfulness, impulsivity, and aggressiveness. The present study sought to examine the prevalence of the comorbid ASPD in adult people with Alcohol Dependence Syndrome (ADS) and identify clinical characteristics associated with ASPD.

Methods

A cross-sectional study of 100 consecutive subjects diagnosed with ADS was conducted. Subjects were examined between August 2023 and September 2023. Various assessments and questionnaires were employed, including the Montreal Cognitive Assessment (MoCA), Alcohol Use Disorders Identification Test (AUDIT), and Structured Clinical Interview for DSM-IV (SCID-II). A computed tomography (CT) scan of the brain was performed on 47.5% participants.

Results

Out of the 100 individuals screened for the study, 20 were excluded. The study found that 35% of the examined study participants had a comorbid ASPD. Individuals with both ADS and ASPD were more likely to be younger, started drinking at an earlier age, had higher hospitalization rates, and scored higher on the AUDIT test (all P < 0.05%). Also, they had lower education levels, higher rates of unemployment, and lower marriage rates (all P < 0.05%). In addition, they reported more family members with ADS, incarceration, or mental illness and a higher frequency of traumatic experiences (all P < 0.05%). Depression, anxiety, stress (all P < 0.05%), and sleep problems (P = 0.058) were correlated with ASPD. Participants with the comorbid ASPD had lower MoCA scores (P = 0.046) and struggled with attention and linguistic subtests compared to subjects with ADS only.

Conclusion

The study highlights the high prevalence of comorbid ASPD in participants with ADS, shedding light on their demographic and psychometric characteristics. Individuals with the comorbid ASPD are more likely to face cognitive deficits, especially in linguistic and attention-related tasks. The findings underline the importance of considering the comorbidity of ASPD in ADS subjects. The study implies that the understanding of the associated risk factors can aid in developing more targeted treatment interventions.
Economic evaluation of the prevention of falls resulting from missed care in polish hospitals
Authors: Wieczorek-Wójcik Beata , Gaworska-Krzemińska Aleksandra , Owczarek Aleksander Jerzy , Kilańska Dorota
Published: September 2024

Objectives

Falls are associated with increased morbidity, mortality, prolonged hospitalization and an increase in the cost of treatment in hospitals. They contribute to the deterioration of fitness and quality of life, especially among older patients, thus posing a serious social and economic problem. They increase the risk of premature death. Falls are adverse, costly, and potentially preventable. The aim of the study was to analyze the cost-effectiveness of avoiding one fall by nurse care provided by the nurses with higher education, from the perspective of the health service provider.

Methods

The economic analysis included and compared only the cost of nurse intervention measured by the hours of care provided with higher education in non-surgical departments (40.5%) with higher time spend by nurses with higher education level an increase in the number of hours by 10% (50.5%) to avoid one fall. The time horizon for the study is 1 year (2021). Cost-effectiveness and Cost–benefit analysis were performed. All registered falls of all hospitalized patients were included in the study.

Results

In the analyzed was based on the case control study where, 7,305 patients were hospitalized, which amounted to 41,762 patient care days. Care was provided by 100 nurses, including 40 nurses with bachelor’s degrees and nurses with Master of Science in Nursing. Increasing the hours number of high-educated nurses care by 10% in non-surgical departments decreased the chance for falls by 9%; however, this dependence was statistically insignificant (OR = 1.09; 95% CI: 0.72–1.65; p = 0.65). After the intervention (a 10% increase in Bachelor’s Degrees/Master of Science in Nursing hours), the number of additional Bachelor’s Degrees/Master of Science hours was 6100.5, and the cost was USD 7630.4. The intervention eliminated four falls. The cost of preventing one fall is CER = USD 1697.1.

Conclusion

The results of these studies broaden the understanding of the relationship among nursing education, falls, and the economic outcomes of hospital care. According to the authors, the proposed intervention has an economic justification.
Research protocol for bridging research, accurate information and dialogue (BRAID)—clinical trials: a mixed-methods study of a community-based intervention to improve trust and diversify participation in clinical trials
Authors: Gutnick Damara N. , Lozano Patricia , Rodriguez Martinez Smeily , Wang Katherine W. , Williams Debra A. , Rapkin Bruce D. , Gonzalez-Lepage Nelly
Published: September 2024

Cultural beliefs, personal experiences, and historic abuses within the healthcare system—rooted in structural racism—all contribute to community distrust in science and medicine. This lack of trust, particularly within underserved communities, contributes to decreased participation in clinical trials and a lack of representation in the data. Open dialogue about community concerns and experiences related to research participation and medical care processes can help build trust and change attitudes and behaviors that affect community health. This protocol outlines an approach to increase trust in science and clinical trials among communities in the Bronx, New York that are typically underrepresented in research data. Bridging Research, Accurate Information and Dialogue (BRAID) is a two-phased, evidence-based community engagement model that creates safe spaces for bilateral dialogues between trusted community messengers, and clinicians and scientists. The team will conduct a series of BRAID Conversation Circles on the topic of clinical trials with local trusted community messengers. Participants will be members of the community who are perceived as “trusted messengers” and can represent the community’s voice because they have insight into “what matters” locally. Conversation Circles will be audiotaped, transcribed, and analyzed to identify emergent challenges and opportunities surrounding clinical trial participation. These key themes will subsequently inform the codesign and co-creation of tailored messages and outreach efforts that community participants can disseminate downstream to their social networks. Surveys will be administered to all participants before and after each Conversation Circle to understand participants experience and evaluate changes in knowledge and attitudes about clinical trials, including protections for research participants the advantages of having diverse representation. Changes in motivation and readiness to share accurate clinical trial information downstream will also be assessed. Lastly, we will measure participants dissemination of codesigned science messages through their social networks by tracking participant specific resource URLs of materials and videos posted on a BRAID website. This protocol will assess the effectiveness and adoptability of an innovative CBPR model that can be applied to a wide range of public health issues and has the potential to navigate the ever-changing needs of the communities that surround health systems.
A Machine Learning Framework for Condition-Based Maintenance of Marine Diesel Engines: A Case Study
Authors: Maione Francesco , Lino Paolo , Maione Guido , Giannino Giuseppe
Published: September 2024

The development of artificial intelligence-based tools is having a big impact on industry. In this context, the maintenance operations of important assets and industrial resources are changing, both from a theoretical and a practical perspective. Namely, conventional maintenance reacts to faults and breakdowns as they occur or schedules the necessary inspections of systems and their parts at fixed times by using statistics on component failures, but this can be improved by a predictive maintenance based on the real component’s health status, which is inspected by appropriate sensors. In this way, maintenance time and costs are saved. Improvements can be achieved even in the marine industry, in which complex ship propulsion systems are produced for operation in many different scenarios. In more detail, data-driven models, through machine learning (ML) algorithms, generate the expected values of monitored variables for comparison with real measurements on the asset, for a diagnosis based on the difference between expectations and observations. The first step towards realization of predictive maintenance is choosing the ML algorithm. This selection is often not the consequence of an in-depth analysis of the different algorithms available in the literature. For that reason, here the authors propose a framework to support an initial implementation stage of predictive maintenance based on a benchmarking of the most suitable ML algorithms. The comparison is tested to predict failures of the oil circuit in a diesel marine engine as a case study. The algorithms are compared by considering not only the mean squared error between the algorithm predictions and the data, but also the response time, which is a crucial variable for maintenance. The results clearly indicate the framework well supports predictive maintenance and the prediction error and running time are appropriate variables to choose the most suitable ML algorithm for prediction. Moreover, the proposed framework can be used to test different algorithms, on the basis of more performance indexes, and to apply predictive maintenance to other engine components.
Understanding and Mitigating Leadership Fear-Based Behaviors on Employee and Organizational Success
Authors: Hubbart Jason A.
Published: September 2024

Leadership behavior profoundly influences organizational culture, serving as a cornerstone for environments that foster safety, innovation, and employee satisfaction. This article utilizes research from the primary literature to demonstrate how leaders’ actions and underlying fears influence organizational dynamics and employee outcomes, highlighting the importance of respect, transparency, and trust. Studies have shown that leadership styles shape the work environment, driving innovation and performance. However, concerns over productivity, evaluation, and control can lead to poor communication, low transparency, reduced innovation, and diminished performance, creating a culture of mistrust and anxiety. Authoritarian control or neglect of employees’ needs exacerbates these issues, stifling creativity. The Pygmalion and Golem effects demonstrate how positive reinforcement enhances morale, productivity, and retention, while negative reinforcement is detrimental. Leaders operating under fears of failure or loss of control or political capital inadvertently create a culture of fear and increasingly severe feedback loops of reduced employee trust, satisfaction, and commitment. Addressing these fears fosters open communication, psychological safety, transparency, and mutual respect. Strategies for transforming leadership fears into positive change include promoting open communication, decentralizing decision-making, and implementing positive reinforcement mechanisms. Constructive feedback mechanisms encourage bidirectional communication and help mitigate the negative impacts of leadership fears. Leaders who address their fears can strengthen team trust, enhancing collaboration and engagement. Ultimately, managing leadership fears proactively catalyzes organizational learning and development, promoting a mindset where challenges are seen as opportunities for growth. This approach enhances adaptability and resilience while fostering continuous improvement. Addressing leadership fears and fostering a supportive culture is essential for sustainable productivity and success, serving as a starting point for exploring strategies that support employee performance and development, ultimately contributing to organizational success.
Research on a Honeycomb Structure for Pyroshock Isolation at the Spacecraft–Rocket Interface
Authors: Wang Xixiong , Gao Zhibo , Cheng Dong , Deng Xuchen , Yu Tao , Qin Zhaoye , Chu Fulei
Published: September 2024

Honeycomb is a splendid kind of structure for aerospace engineering with the advantages of light weight, good shock absorption, and good structural stability. This article aims to provide methods to isolate Pyroshocks based on a honeycomb structure and guarantee the safety of such equipment against a high-frequency shock response. According to stress wave theory, an equation for stress wave transmittance of the honeycomb structure is derived considering the effect of cell wall length and thickness, where desirable honeycomb parameters are obtained. The complexity of the transfer path of the honeycomb structure is exploited to build the spacecraft–rocket interface, which could increase the impedance of the stress wave dramatically. Both finite element analysis and experiments are carried out to validate the shock isolation strategies. The influence of parameters, such as cell wall length and the thickness of the stainless-steel honeycomb, on the isolation performance is analyzed. It is revealed that the honeycomb structure has a significant effect on Pyroshock isolation performance when the wall length of the honeycomb cell is 8 mm and the thickness of the cell is 0.1 mm.
Preliminary Design of Satellite Systems through the Integration of Model-Based System Engineering and Agile Methodologies: Application to the 3ColStar Mission
Authors: Buitrago-Leiva Jeimmy Nataly , Mejía Juan José , Puerta-Ibarra Juan Francisco , Acero-Niño Ignacio Francisco , Guarnizo-Saavedra Andrés Felipe , Rodriguez-Ferreira Julian , Rojas-Rodriguez Leandro , Hernández-Torres Francisco Luis , Arango-Cotacio Cristian Esteban , Salazar-Morales Jorge Enrique , Herrera-Cruz Miguel Angel , Linares-Vásquez Mario , Jiménez-Vargas Jose Fernando , Espíndola-Díaz Jorge Enríque , Montañez-Sogamoso Óscar Javier , Camps Adriano
Published: September 2024

This paper presents a case study on integrating Agile Systems Engineering methodologies in the preliminary design phase of satellite systems, focusing on the 3ColStar satellite mission. Through Model-Based Systems Engineering (MBSE), technical consistency was rigorously managed across various architectural documents, ensuring coherency and minimizing errors. Furthermore, the preliminary design was developed, with the implementation of the Arcadia Method, supported by the Capella modeling tool. This allowed the digitalization of the system, which was represented by models that contain requirements, architecture, and interfaces between the different parts of the system. At the same time, the preliminary design process was streamlined and completed within an accelerated time frame of 4 months, with weekly sprints driving progress based on the scrum methodology. This case study highlights the effectiveness of Agile Systems Engineering principles to improve the team communication accuracy, communication, and efficiency of satellite systems preliminary design, providing valuable insights for future missions.
Experimental Study on Submerged Nozzle Damping Characteristics of Solid Rocket Motor
Authors: Li Xinyan , Chen Zhenglong , Li Xiaosi , Xu Bo , Wang Shengnan
Published: September 2024

Acoustic instabilities in solid rocket motors (SRMs) can lead to severe performance deterioration and structural damage. Nozzle damping accounts for the main acoustic dissipation source, and it is highly dependent on geometric parameters and operating conditions. This study experimentally investigated the acoustic damping characteristics of submerged nozzles in SRMs, focusing on the effects of submerged cavity dimensions, nozzle convergent angle, throat-to-port area ratio, and mean pressure variations on the longitudinal instability. The steady-state wave decay method was used to quantify the acoustic damping, and a designed rotary valve system was employed to introduce periodic pressure oscillations in the high-pressure combustion chamber. The results revealed that a larger submerged cavity would reduce the nozzle damping efficiency, with the elimination of the submerged cavity enhancing the nozzle decay coefficient magnitude by 41.9%. Furthermore, increasing the nozzle convergent angle was found to amplify acoustic wave reflection, thereby diminishing damping performance. A linear inverse relationship was observed between the throat-to-port area ratio and the decay coefficient, with a 125% increase in the ratio resulting in a 24.3% reduction in the decay coefficient. Interestingly, despite the formation of complex vortices in the submerged cavity, the mean pressure variation presented negligible effects on acoustic damping characteristics, and its damping performance is similar to a simple nozzle without a cavity. These findings provide valuable experimental data for predicting the stability of a solid rocket motor with a submerged nozzle and offer insights into the optimization of submerged nozzle designs for higher acoustic damping in SRMs.
Oxalic Acid Boosts Phosphorus Release from Sewage Sludge Biochar: A Key Mechanism for Biochar-Based Fertilizers
Authors: Santos Marcela Granato Barbosa dos , Costa Camila Rodrigues , Mendes Gilberto de Oliveira , Blasi Paiva Andressa , Peixoto Ludmila Soares , Costa Jéssica da Luz , Marchi Giuliano , Martins Éder de Souza , Figueiredo Cícero Célio de
Published: September 2024

Sewage sludge biochar (SSB) exhibits higher phosphorus (P) concentrations than the original sewage sludge (SS) and can be used as a P fertilizer. However, SSB-associated P is strongly retained in chemical compounds, which hinders its release and subsequent plant uptake. The use of organic acids facilitates P solubilization from SSB. Herein, we evaluated the effect of oxalic acid on P release from SSB applied to soil over time. Biochar was produced at 300 °C (SSB300) and 500 °C (SSB500). P release from SSB increased with an increasing concentration of oxalic acid in the SSB incubation solution and in SSB-treated soil. P speciation in SSB showed that P was predominantly inorganic (Pi), which represented 81% and 92% of the total P in SSB300 and SSB500, respectively. Pi in SSB consisted mainly of non-apatite P, accounting for 91% and 96% of all Pi in SSB300 and SSB500, respectively. Because SSB is predominantly insoluble in water, oxalic acid is crucial for the release of P from SSB. Oxalic acid increased P release from SSB300 and SSB500 by 103- and 600-fold, respectively, compared to the control, from which P was extracted with water. Oxalic acid enhancement of P release from SSB increases the possibility of using SSB as a sustainable source of P for agriculture.
Combining Vegetation Indices to Identify the Maize Phenological Information Based on the Shape Model
Authors: Wu Huizhu , Liu Bing , Zhu Bingxue , Zhen Zhijun , Song Kaishan , Ren Jingquan
Published: September 2024

Maize is the world’s largest food crop and plays a critical role in global food security. Accurate phenology information is essential for improving yield estimation and enabling timely field management. Yet, much of the research has concentrated on general crop growth periods rather than on pinpointing key phenological stages. This gap in understanding presents a challenge in determining how different vegetation indices (VIs) might accurately extract phenological information across these stages. To address this, we employed the shape model fitting (SMF) method to assess whether a multi-index approach could enhance the precision of identifying key phenological stages. By analyzing time-series data from various VIs, we identified five phenological stages (emergence, seven-leaf, jointing, flowering, and maturity stages) in maize cultivated in Jilin Province. The findings revealed that each VI had distinct advantages depending on the phenological stage, with the land surface water index (LSWI) being particularly effective for jointing and flowering stages due to its correlation with vegetation water content, achieving a root mean square error (RMSE) of three to four days. In contrast, the normalized difference vegetation index (NDVI) was more effective for identifying the emergence and seven-leaf stages, with an RMSE of four days. Overall, combining multiple VIs significantly improved the accuracy of phenological stage identification. This approach offers a novel perspective for utilizing diverse VIs in crop phenology, thereby enhancing the precision of agricultural monitoring and management practices.
PlLAC15 Facilitates Syringyl Lignin Deposition to Enhance Stem Strength in Herbaceous Peony
Authors: Yin Yuehan , Zuo Shiqi , Zhao Minghao , Tao Jun , Zhao Daqiu , Tang Yuhan
Published: September 2024

Stems are prone to bending or lodging due to inadequate stem strength, which seriously reduces the cut-flower ornamental quality of herbaceous peony (Paeonia lactiflora Pall.). Plant LACCASE (LAC), a copper-containing polyphenol oxidase, has been shown to participate in the polymerization process of monolignols; however, the role of LAC in regulating the stem strength of P. lactiflora remains unclear. Here, the full-length cDNA of PlLAC15, which demonstrated a positive association with stem strength, was isolated. It consisted of 1790 nucleotides, encoding 565 amino acids that had four typical laccase copper ion-binding domains. Moreover, PlLAC15 was highly expressed in the stem, and its expression level gradually significantly increased during stem development. Furthermore, PlLAC15 was found to be localized specifically to the cell wall, and its recombinant protein exhibited laccase activity. Additionally, the role of PlLAC15 in regulating the stem strength of P. lactiflora was confirmed by transgenic studies. When PlLAC15 was overexpressed in tobacco, stem strength increased by more than 50%, S-lignin was significantly deposited, and the lignification degree of stem xylem fiber cells increased. These results suggested that PlLAC15 facilitated S-lignin deposition to enhance stem strength in P. lactiflora, which would provide precious information that benefits future exploration of stem bending or lodging resistance in plants.
Genome-Wide Association Study Reveals Loci and New Candidate Gene Controlling Seed Germination in Rice
Authors: Chen Shaona , Chen Guanlong , Peng Zepeng , Liu Jiping , Zheng Yixiong , Yang Bin
Published: September 2024

Improving seed germination and seedling development can potentially increase crop yield and improve quality in direct-seeded rice. This study aimed to detect loci or genes associated with rice seed germination. We reported the phenotypic analysis of seed germination in 103 rice accessions across two years, and a genome-wide association study (GWAS) was conducted to identify loci underlying the genetic regulation of seed germination. A total of seven genetic loci were found to be associated with seed germination, including five loci that overlapped with the previously reported loci/genes, and two novel loci. Of these, two loci (qGP2 and qGP4.1) were stable across different environments. GP4 (Germination percentage 4), encoding a 9-cis-epoxycarotenoid dioxygenase, was identified as the candidate gene of the major locus qGP4.1. A sequence analysis of GP4 revealed that four functional polymorphic sites in the coding region were significantly associated with germination percentage. The disruption of GP4 by gene editing resulted in faster seed germination and seedling establishment. Taken together, we have identified GP4 as a novel gene involved in rice seed germination, and we provide a potential target gene for improving rice seed vigor via gene editing or molecular breeding.
A Lightweight Cotton Verticillium Wilt Hazard Level Real-Time Assessment System Based on an Improved YOLOv10n Model
Authors: Liao Juan , He Xinying , Liang Yexiong , Wang Hui , Zeng Haoqiu , Luo Xiwen , Li Xiaomin , Zhang Lei , Xing He , Zang Ying
Published: September 2024

Compared to traditional manual methods for assessing the cotton verticillium wilt (CVW) hazard level, utilizing deep learning models for foliage segmentation can significantly improve the evaluation accuracy. However, instance segmentation methods for images with complex backgrounds often suffer from low accuracy and delayed segmentation. To address this issue, an improved model, YOLO-VW, with high accuracy, high efficiency, and a light weight, was proposed for CVW hazard level assessment based on the YOLOv10n model. (1) It replaced conventional convolutions with the lightweight GhostConv, reducing the computational time. (2) The STC module based on the Swin Transformer enhanced the expression of foliage and disease spot boundary features, further reducing the model size. (3) It integrated a squeeze-and-excitation (SE) attention mechanism to suppress irrelevant background information. (4) It employed the stochastic gradient descent (SGD) optimizer to enhance the performance and shorten the detection time. The improved CVW severity assessment model was then deployed on a server, and a real-time detection application (APP) for CVW severity assessment was developed based on this model. The results indicated the following. (1) The YOLO-VW model achieved a mean average precision (mAP) of 89.2% and a frame per second (FPS) rate of 157.98 f/s in assessing CVW, representing improvements of 2.4% and 21.37 f/s over the original model, respectively. (2) The YOLO-VW model’s parameters and floating point operations per second (FLOPs) were 1.59 M and 7.8 G, respectively, compressed by 44% and 33.9% compared to the original YOLOv10n model. (3) After deploying the YOLO-VW model on a smartphone, the processing time for each image was 2.42 s, and the evaluation accuracy under various environmental conditions reached 85.5%, representing a 15% improvement compared to the original YOLOv10n model. Based on these findings, YOLO-VW meets the requirements for real-time detection, offering greater robustness, efficiency, and portability in practical applications. This model provides technical support for controlling CVW and developing cotton varieties resistant to verticillium wilt.
Research on the Wild Mushroom Recognition Method Based on Transformer and the Multi-Scale Feature Fusion Compact Bilinear Neural Network
Authors: Liu He , Hu Qingran , Huang Dongyan
Published: September 2024

Wild mushrooms are popular for their taste and nutritional value; however, non-experts often struggle to distinguish between toxic and non-toxic species when foraging in the wild, potentially leading to poisoning incidents. To address this issue, this study proposes a compact bilinear neural network method based on Transformer and multi-scale feature fusion. The method utilizes a dual-stream structure that integrates multiple feature extractors, enhancing the comprehensiveness of image information capture. Additionally, bottleneck attention and efficient multi-scale attention modules are embedded to effectively capture multi-scale features while maintaining low computational costs. By employing a compact bilinear pooling module, the model achieves high-order feature interactions, reducing the number of parameters without compromising performance. Experimental results demonstrate that the proposed method achieves an accuracy of 98.03%, outperforming existing comparative methods. This proves the superior recognition performance of the model, making it more reliable in distinguishing wild mushrooms while capturing key information from multiple dimensions, enabling it to better handle complex scenarios. Furthermore, the development of public-facing identification tools based on this method could help reduce the risk of poisoning incidents. Building on these findings, the study suggests strengthening the research and development of digital agricultural technologies, promoting the application of intelligent recognition technologies in agriculture, and providing technical support for agricultural production and resource management through digital platforms. This would provide a theoretical foundation for the innovation of digital agriculture and promote its sustainable development.
Research on SLAM Localization Algorithm for Orchard Dynamic Vision Based on YOLOD-SLAM2
Authors: Ma Zhen , Yang Siyuan , Li Jingbin , Qi Jiangtao
Published: September 2024

With the development of agriculture, the complexity and dynamism of orchard environments pose challenges to the perception and positioning of inter-row environments for agricultural vehicles. This paper proposes a method for extracting navigation lines and measuring pedestrian obstacles. The improved YOLOv5 algorithm is used to detect tree trunks between left and right rows in orchards. The experimental results show that the average angle deviation of the extracted navigation lines was less than 5 degrees, verifying its accuracy. Due to the variable posture of pedestrians and ineffective camera depth, a distance measurement algorithm based on a four-zone depth comparison is proposed for pedestrian obstacle distance measurement. Experimental results showed that within a range of 6 m, the average relative error of distance measurement did not exceed 1%, and within a range of 9 m, the maximum relative error was 2.03%. The average distance measurement time was 30 ms, which could accurately and quickly achieve pedestrian distance measurement in orchard environments. On the publicly available TUM RGB-D dynamic dataset, YOLOD-SLAM2 significantly reduced the RMSE index of absolute trajectory error compared to the ORB-SLAM2 algorithm, which was less than 0.05 m/s. In actual orchard environments, YOLOD-SLAM2 had a higher degree of agreement between the estimated trajectory and the true trajectory when the vehicle was traveling in straight and circular directions. The RMSE index of the absolute trajectory error was less than 0.03 m/s, and the average tracking time was 47 ms, indicating that the YOLOD-SLAM2 algorithm proposed in this paper could meet the accuracy and real-time requirements of agricultural vehicle positioning in orchard environments.
Engineering Discrete Element Method-Based Design and Optimization of the Key Components of a Spoon-Wheel Spinach Seed-Metering Device
Authors: Zheng Gang , Qi Bing , Zhang Wenyi , Shao Weixing , Zhang Lei , Wang Yunxia , Ding Youqiang
Published: September 2024

In view of issues affecting manual on-demand sowing of spinach, such as high working intensity, low seeding efficiency, and high cost, a mechanized precision seeding device for spinach seeds is proposed, based on a spoon-wheel including a combined cell with two intersecting surfaces. The key structure was designed, and motion analysis was conducted employing SolidWorks software (2022). Additionally, the seeding process was simulated using EDEM simulation software (2022). The number of spoons, the radius of the spoons, and the speed of the seed wheel were chosen as the influencing factors, while the qualified index, reseeding index, and missing index were utilized as the evaluation indexes. A response surface method test based on the Box–Behnken design was carried out, and the test results were analyzed to obtain the optimal parameter combination for the seed-metering device. The field test results showed that when the rotation speed was 18 rpm, the radius of each seed spoon was 2.5 mm, and the number of seed spoons was 50, the average qualified index was 90.89%, the reseeding index was 8.22%, and the missed seeding index was 0.89%. The test results satisfy the technical production requirements for spinach seed sowing.
EF yolov8s: A Human–Computer Collaborative Sugarcane Disease Detection Model in Complex Environment
Authors: Sun Jihong , Li Zhaowen , Li Fusheng , Shen Yingming , Qian Ye , Li Tong
Published: September 2024

The precise identification of disease traits in the complex sugarcane planting environment not only effectively prevents the spread and outbreak of common diseases but also allows for the real-time monitoring of nutrient deficiency syndrome at the top of sugarcane, facilitating the supplementation of relevant nutrients to ensure sugarcane quality and yield. This paper proposes a human–machine collaborative sugarcane disease detection method in complex environments. Initially, data on five common sugarcane diseases—brown stripe, rust, ring spot, brown spot, and red rot—as well as two nutrient deficiency conditions—sulfur deficiency and phosphorus deficiency—were collected, totaling 11,364 images and 10 high-definition videos captured by a 4K drone. The data sets were augmented threefold using techniques such as flipping and gamma adjustment to construct a disease data set. Building upon the YOLOv8 framework, the EMA attention mechanism and Focal loss function were added to optimize the model, addressing the complex backgrounds and imbalanced positive and negative samples present in the sugarcane data set. Disease detection models EF-yolov8s, EF-yolov8m, EF-yolov8n, EF-yolov7, and EF-yolov5n were constructed and compared. Subsequently, five basic instance segmentation models of YOLOv8 were used for comparative analysis, validated using nutrient deficiency condition videos, and a human–machine integrated detection model for nutrient deficiency symptoms at the top of sugarcane was constructed. The experimental results demonstrate that our improved EF-yolov8s model outperforms other models, achieving mAP_0.5, precision, recall, and F1 scores of 89.70%, 88.70%, 86.00%, and 88.00%, respectively, highlighting the effectiveness of EF-yolov8s for sugarcane disease detection. Additionally, yolov8s-seg achieves an average precision of 80.30% with a smaller number of parameters, outperforming other models by 5.2%, 1.9%, 2.02%, and 0.92% in terms of mAP_0.5, respectively, effectively detecting nutrient deficiency symptoms and addressing the challenges of sugarcane growth monitoring and disease detection in complex environments using computer vision technology.