bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging multi-omics data to infer regulators of mRNA 3’ end processing in glioblastoma
Authors: Mironov Aleksei , Franchitti Lorenzo , Ghosh Shreemoyee , Ritz Marie-Francoise , Hutter Gregor , De Bortoli Michele , Zavolan Mihaela
Published: August 2024

Alterations in mRNA 3’ end processing and polyadenylation are widely implicated in the biology of many cancer types, including glioblastoma (GBM), one the most aggressive tumor types. Although several RNA-binding proteins (RBPs) responsible for alternative polyadenylation (APA) were identified from functional studies in cell lines, their contribution to the APA landscape in tumors in vivo was not thoroughly addressed. In this study we analyzed a large RNA-seq data set of glioblastoma (GBM) samples from The Cancer Genome Atlas (TCGA) to identify APA patterns differentiating the main molecular subtypes of GBM. We superimposed these to RBP footprinting data and to APA events occurring upon depletion of individual RBPs from a large panel tested by the ENCODE Consortium. Our analysis revealed 22 highly concordant and statistically significant RBP-APA associations, whereby changes in RBP expression were accompanied by APA in both TCGA and ENCODE datasets. Among these, we found a previously unknown PTBP1-regulated APA event in the PRRC2B gene and an HNRNPU-regulated event in the SC5D gene. Both of these were further supported by RNA-sequencing data of paired tumor center-periphery GBM samples obtained at the University Hospital of Basel. In addition, we validated the regulation of APA in PRRC2B by PTBP1 in siRNA-knockdown and overexpression experiments followed by RNA-sequencing in two glioblastoma cell lines. The transcriptome analysis workflow that we present here enables the identification of concordant RBP-APA associations in cancers.
A novel approach to cytoarchitectonics: developing an objective framework for the morphological analysis of the cerebral cortex
Authors: Prkačin Matija Vid , Petanjek Zdravko , Banovac Ivan
Published: August 2024

Introduction

The cytoarchitectonic boundaries between cortical regions and layers are usually defined by the presence or absence of certain cell types. However, these cell types are often not clearly defined and determining the exact boundaries of regions and layers can be challenging. Therefore, in our research, we attempted to define cortical regions and layers based on clear quantitative criteria.

Methods

We performed immunofluorescent anti-NeuN labelling on five adult human brains in three cortical regions—Brodmann areas (BA) 9, 14r, and 24. We reconstructed the cell bodies of 90,723 NeuN-positive cells and analyzed their morphometric characteristics by cortical region and layer. We used a supervised neural network prediction algorithm to classify the reconstructions into morphological cell types. We used the results of the prediction algorithm to determine the proportions of different cell types in BA9, BA14r and BA24.

Results

Our analysis revealed that the cytoarchitectonic descriptions of BA9, BA14r and BA24 were reflected in the morphometric measures and cell classifications obtained by the prediction algorithm. BA9 was characterized by the abundance of large pyramidal cells in layer III, BA14r was characterized by relatively smaller and more elongated cells compared to BA9, and BA24 was characterized by the presence of extremely elongated cells in layer V as well as relatively higher proportions of irregularly shaped cells.

Discussion

The results of the prediction model agreed well with the qualitative expected cytoarchitectonic descriptions. This suggests that supervised machine learning could aid in defining the morphological characteristics of the cerebral cortex.
Potential role of endothelial progenitor cells in the pathogenesis and treatment of cerebral aneurysm
Authors: Yu Jin , Du Qian , Li Xiang , Wei Wei , Fan Yuncun , Zhang Jianjian , Chen Jincao
Published: August 2024

Cerebral aneurysm (CA) is a significant health concern that results from pathological dilations of blood vessels in the brain and can lead to severe and potentially life-threatening conditions. While the pathogenesis of CA is complex, emerging studies suggest that endothelial progenitor cells (EPCs) play a crucial role. In this paper, we conducted a comprehensive literature review to investigate the potential role of EPCs in the pathogenesis and treatment of CA. Current research indicates that a decreased count and dysfunction of EPCs disrupt the balance between endothelial dysfunction and repair, thus increasing the risk of CA formation. Reversing these EPCs abnormalities may reduce the progression of vascular degeneration after aneurysm induction, indicating EPCs as a promising target for developing new therapeutic strategies to facilitate CA repair. This has motivated researchers to develop novel treatment options, including drug applications, endovascular-combined and tissue engineering therapies. Although preclinical studies have shown promising results, there is still a considerable way to go before clinical translation and eventual benefits for patients. Nonetheless, these findings offer hope for improving the treatment and management of this condition.
Genetic associations between ULK3 and epilepsy: a two-sample Mendelian randomization study
Authors: Liu Baolai , Fan Keyi , Zheng Xinyi , Zhang Yaochen , Bai Shangkai , Liu Zhentong , Xu Shuhan , Su Zhihao , Cao Huiting , Zhang Heyi , Zhang Shengxiao
Published: August 2024

Background and objectives

Observational studies have suggested that a multitude of pathological processes and biomolecules are involved in the initiation and development of epilepsy, and ULK3 is linked to the nervous system. However, it remains uncertain whether this association between ULK3 and epilepsy is causal and the direction of any causal relationship. This study employs a two-sample Mendelian randomization (MR) method to investigate the relationship between ULK3 and the risk of epilepsy.

Methods

We analyzed genome-wide association study (GWAS) summary statistics for ULK3 (sample size = 3,301), focal epilepsy (sample size = 39,348), and generalized epilepsy (sample size = 33,446). Bidirectional MR analyses were conducted to explore these relationships. We selected a set of single nucleotide polymorphisms (SNPs) with an association threshold of less than 1 × 10−5 as instrumental variables for further analysis. Various MR methods, including Inverse Variance Weighted, Weighted Median, MR-Egger Regression, Simple Model, Weighted Model, and Robust Adjustment Profile Score were used. Sensitivity analyses were performed to ensure the robustness of the results.

Results

Our MR analyses revealed a causal relationship where an increased level of ULK3 was associated with a decreased risk of focal epilepsy (odds ratio = 0.92, 95% confidence interval: 0.86–1.00, p = 0.041). No significant heterogeneity (Q = 7.85, p = 0.165) or horizontal pleiotropy (Egger regression intercept = 0.0191, p = 0.415) was detected. However, in the reverse analysis, we found no significant causal effect of focal epilepsy on ULK3 (p > 0.05). Furthermore, no significant causation was identified between ULK3 and generalized epilepsy (p > 0.05).

Conclusion

This study suggests a causal relationship between ULK3 and the risk of focal epilepsy from a genetic perspective. Nevertheless, further investigation is needed to understand the role of ULK3 in epilepsy fully.
A canonical polyadic tensor basis for fast Bayesian estimation of multi-subject brain activation patterns
Authors: Miranda Michelle F.
Published: August 2024

Task-evoked functional magnetic resonance imaging studies, such as the Human Connectome Project (HCP), are a powerful tool for exploring how brain activity is influenced by cognitive tasks like memory retention, decision-making, and language processing. A fast Bayesian function-on-scalar model is proposed for estimating population-level activation maps linked to the working memory task. The model is based on the canonical polyadic (CP) tensor decomposition of coefficient maps obtained for each subject. This decomposition effectively yields a tensor basis capable of extracting both common features and subject-specific features from the coefficient maps. These subject-specific features, in turn, are modeled as a function of covariates of interest using a Bayesian model that accounts for the correlation of the CP-extracted features. The dimensionality reduction achieved with the tensor basis allows for a fast MCMC estimation of population-level activation maps. This model is applied to one hundred unrelated subjects from the HCP dataset, yielding significant insights into brain signatures associated with working memory.
Chronic sleep restriction during juvenility alters hedonic and anxiety-like behaviours in a sex-dependent fashion in adolescent Wistar rats
Authors: Barreto Anna Carolina Muniz , Oliveira Julia Naomi Sakamoto , Suchecki Deborah
Published: August 2024

Chronic reduction of sleep time in children and adolescents has been related to increased incidence of anxiety and depression. In rats, protocols of protracted sleep deprivation or chronic sleep restriction (CSR) are considered a stressor. In previous studies we showed that post-weaning CSR in male rats induces anxiety-like behaviour and changes in neurotransmission in emotion-related brain areas. In the present study we examined whether the effects of this adversity are sex-dependent. Twenty-two litters, containing four males and four females were distributed into control (CTL) and CSR groups. CSR began on postnatal day (PND) 21 and lasted for 21 days; each day the animals were placed onto small platforms immersed in water for 18 h and were allowed to sleep freely in their home-cages for the remaining 6 h. Throughout the CSR, all animals underwent the sucrose splash test once/week to assess their self-care and hedonic behaviours. Body weight was measured on PNDs 21 and 42. At the end of CSR period, the adolescents were allowed to sleep freely for 2 days, after which, behavioural tests began. Within each litter, one male and one female (pair) were not tested and provided blood and brain for determination of basal corticosterone (CORT) levels and hippocampal BDNF. One pair was tested in the sucrose preference test (SPT), one pair on the elevated plus maze (EPM) and one pair in the forced swim test (FST). CORT was measured after all conditions. CSR impaired self-care behaviour and body weight gain in males and females and increased relative adrenal weight only in males. There were no changes in sucrose intake in the SPT; CSR females displayed less immobility in the FST and CSR males displayed more anxiety-like behaviour in the EPM. CORT levels were similar between CTL and CSR males, whilst lower in CSR females than CTL ones in all experimental conditions. No changes in BDNF levels were detected in the dorsal hippocampus of CSR rats. The results indicate that CSR impaired self-care behaviour in both sexes, but only males displayed anxiety-like behaviour, whilst sleep recovery in females appeared to normalise their behaviour.
Extraction of phenolic compounds from Moringa oleifera Lam. leaves with ultrasonic-assisted deep eutectic solvents
Authors: Wang Zilin , Tian Yang , Yang Min , Yang Junyan , Wang Yifan , Tao Liang , Sheng Jun , Shi Chongying
Published: August 2024

Background

In this study, deep eutectic solvents (DESs) combined with ultrasound-assisted extraction (UAE) were used to extract bioactive compounds from the leaves of Moringa oleifera Lam.

Methods

The FT-IR method was used to analyze the structural characteristics of the DESs, and the extraction efficiencies of the DESs for total phenolic content (TPC) and total flavonoid content (TFC) were evaluated. The stability of the extracts under high temperature and UV radiation was assessed, and their antioxidant activity was investigated after undergoing in vitro simulated digestion.

Results

The results show that the seven DESs extracted more TPC and TFC than did the 70% ethanol (36.27 ± 1.58 mg GAE/g, 23.09 ± 1.47 mg RT/g), and the extraction process of UAE-DES was optimized by selecting choline chloride: citric acid as the DES solvent, which has the highest extraction of TPC (86.92 ± 1.34 mg GAE/g) and TFC (49.73 ± 0.85 mg RT/g). The stability results indicated that the DES phenolic extracts were less stable when exposed to high temperature and UV radiation, indicating that DES extracts have better bioactivity. Moreover, after in vitro simulated digestion, the DES extract shows a higher DPPH free radical scavenging capacity (12.79 ± 3.88 mmol Trolox/g of DES extracts, 6.99 ± 4.02 mmol Trolox/g of ethanol extracts) and ferric ion reducing antioxidant power (62.61 ± 1.71 mmol Trolox/g of DES extracts, 55.07 ± 1.66 mmol Trolox/g of ethanol extracts) than ethanol extracts.

Conclusion

This study confirmed that DESs are a new and environmentally friendly solvent that can be used for the extraction of phenolic compounds.
Comparing qSMI and qCEUS for assessing vascularization in uterine cervical cancer: operable versus non-operable group
Authors: Zhu Yi , Li Yanjie , Tang Yixin , Zhang Jie , Jia Shijun , Jiang Zhuolin , Luo Xinyi , Ishikawa Mitsuya , Kato Tomoyasu
Published: August 2024

Objective

The present study aimed to compare the effectiveness and reliability of quantified superb microvascular imaging (qSMI) and quantified contrast-enhanced ultrasonography (qCEUS) in assessing vascularization in both operable and non-operable uterine cervical cancer.

Methods

A case-control study included 64 patients with pathology-proven and untreated cervical cancer, who underwent transvaginal ultrasonography combined with qSMI and qCEUS between January 2022 and June 2023. SMI results were quantified as the vascular index (VI), which were compared to 12 quantitative parameters of CEUS calculated with time-intensity curves (TIC).

Results

According to FIGO staging and different treatment regimens, 64 patients with cervical cancer were divided into operable group (IA ~ IIA, n = 19) and non-operable group (IIB ~ IV, n = 45). In comparison to the operable group, the non-operable group showed significantly higher values in VI, peak intensity (PI), area under the curve (AUC), wash-in area (iAUC), wash-out area (oAUC), wash-in rate (WiR), mean intensity (Mean Int), and standard deviation (STD) (all P < 0.05). VI demonstrated strong correlations with CEUS parameters, notably PI (r = 0.854, P < 0.001) and AUC (r = 0.635, P < 0.001). Furthermore, VI showed a better predictive performance for treatment-group assignment than qCEUS parameters, with an 80.7% accuracy, 64.4% sensitivity and 89.5% specificity.

Conclusion

Both qSMI and qCEUS exhibit significant and comparable utility in detecting microvascular hyperplasia and predicting treatment-group assignments in cervical cancer. Furthermore, qSMI may offer added convenience in implementation.
Case report: Drug reaction with eosinophilia and systemic symptoms (DRESS) induced by ceftazidime in a connective tissue disease (CTD) patient
Authors: Dai Rui , Niu Ziran , Yang Yang , Liu Xin , Zhang Bo
Published: August 2024

Drug reaction with eosinophilia and systemic symptoms (DRESS) is a rare and severe cutaneous adverse drug reactions (SCARs) with high mortality. Antibiotics are the most frequent causative agents related to DRESS. However, it is rarely reported in cephalosporins, especially for ceftazidime. Here, we reported a case of ceftazidime-induced DRESS with HLA genotypic polymorphism as a risk factor. A 58-year-old woman with connective tissue disease was intravenously infused with ceftazidime for the treatment of pneumonia and intestinal infection, followed by the presence of fever, rash, and hematologic and hepatic laboratory abnormalities. DRESS was diagnosed and the positive polymorphism in HLA-B*15:02 was found. Our case illustrated the necessity to clarify the patho-mechanism and the use of pretreatment HLA analysis to prevent ceftazidime-related DRESS may be a valuable option soon.
Non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and hypertension in American adults: a NHANES cross-sectional study
Authors: Wu Jiabei , Guo Jinli
Published: August 2024

Objectives

The relationship between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and hypertension remains uncertain, warranting further investigation. This study aims to elucidate the association between NHHR and hypertension.

Methods

A comprehensive cross-sectional stratified survey involving 30,602 participants aged 20 years and older was conducted using the National Health and Nutrition Examination Survey (NHANES) dataset from 2001 to 2018. NHHR was calculated as [total cholesterol (TC) - high-density lipoprotein cholesterol (HDL-C)]/HDL-C. The relationship between NHHR and hypertension was examined using weighted multiple linear regression, smooth curve fitting, hierarchical analysis, and interaction testing.

Results

The mean age of participants was 49.82 ± 17.64 years, with 15,266 women included. The average NHHR was 2.94 ± 0.56. A positive correlation between NHHR and hypertension was observed. Stratification of NHHR into quartiles, in the fully adjusted Model 3, revealed that individuals in the highest NHHR quartile had a 60% increased risk of hypertension for each unit increase in NHHR compared to those in the lowest quartile. Interaction tests indicated that the relationship between NHHR and hypertension remained consistent across subgroups, except for gender, age, education, and smoking status, which influenced this association.

Conclusion

Analysis of NHANES data from 2001 to 2018 demonstrated a consistent positive association between NHHR and hypertension. NHHR may provide potential assistance in hypertension prevention and diagnosis.
Harnessing the power of machine learning for crop improvement and sustainable production
Authors: Khatibi Seyed Mahdi Hosseiniyan , Ali Jauhar
Published: August 2024

Crop improvement and production domains encounter large amounts of expanding data with multi-layer complexity that forces researchers to use machine-learning approaches to establish predictive and informative models to understand the sophisticated mechanisms underlying these processes. All machine-learning approaches aim to fit models to target data; nevertheless, it should be noted that a wide range of specialized methods might initially appear confusing. The principal objective of this study is to offer researchers an explicit introduction to some of the essential machine-learning approaches and their applications, comprising the most modern and utilized methods that have gained widespread adoption in crop improvement or similar domains. This article explicitly explains how different machine-learning methods could be applied for given agricultural data, highlights newly emerging techniques for machine-learning users, and lays out technical strategies for agri/crop research practitioners and researchers.
Becoming an Open Dialogue practitioner: a qualitative study of practitioners’ training experiences and transitioning to practice
Authors: Anestis Eleftherios , Weaver Timothy , Melia Claire , Clarke Katherine , Pilling Steve
Published: August 2024

Introduction

In the context of transforming mental healthcare towards more personalised and recovery-oriented models, Open Dialogue has attracted significant international interest. Open Dialogue proposes a way of organising services and delivering care that supports an immediate response to crisis, relational continuity of care, a social network approach and the empowerment of networks through shared decision-making and a flattened hierarchy. The ODDESSI trial currently being conducted in the UK is assessing the model’s clinical and cost-effectiveness. Practitioners who delivered the approach within the trial undertook a one-year Open Dialogue foundation training programme, however little is known about their training experiences. This study aimed to explore practitioners’ experiences of receiving the training and transitioning to dialogic practice.

Methods

Individual, joint and focus group interviews with 32 Open Dialogue practitioners were conducted. Thematic analysis was used to analyse the transcripts and transformational learning theory informed the interpretation of the findings.

Results

Two themes further divided in subthemes were generated from the data: (1) experiences and impact of formal training and (2) becoming an Open Dialogue practitioner as an ongoing learning process beyond formal training: barriers and facilitators.

Discussion

The one-year Open Dialogue foundation training was a transformative experience for participants due to its emphasis on self-work and its impact on a personal level. Practitioners felt adequately prepared by their training for dialogic practice, yet becoming an OD practitioner was seen as a continual process extending beyond formal training, necessitating ongoing engagement with the approach and organisational support. However, the commitment of participants to deliver optimal dialogic care was occasionally impeded by organisational constraints, resource limitations, and often having to concurrently deliver conventional care alongside Open Dialogue.
Cost-effectiveness of portable-automated ABR for universal neonatal hearing screening in India
Authors: Sahoo Krushna Chandra , Dwivedi Rinshu , Athe Ramesh , Chauhan Akshay , Jain Shalu , Sahoo Rakesh Kumar , Bhattacharya Debdutta , Rajsekhar Kavitha , Pati Sanghamitra
Published: August 2024

The World Health Organization considers Universal Neonatal Hearing Screening (UNHS) essential to global public health. Rashtriya Bal Swasthya Karyakram has included newborn hearing screening in India since 2013. The program faces human, infrastructure, and equipment shortages. First-line hearing screening with improved diagnostic accuracy is needed. The Portable Automated Auditory Brainstem Responses (P-AABR) can be used in remote areas for UNHS due to its low infrastructure needs and diagnostic accuracy. This study evaluated the cost-effectiveness of P-AABR in UNHS. We employed an analytical model based on decision trees to assess the cost-effectiveness of Otoacoustic Emission (OAE) and P-AABR. The total cost to the health system for P-AABR, regardless of true positive cases, is INR 10,535,915, while OAE costs INR 7,256,198. P-AABR detects 262 cases, whereas OAE detects 26 cases. Portable Automated ABR costs INR 97 per case detection, while OAE costs INR 67. The final ICER was 97407.69. The P-AABR device is cost-effective, safe and feasible for UNHS Rashtriya Bal Swasthya Karyakram (RBSK) programs. Beyond reducing false referrals and parent indirect costs, it detects more hearing-impaired infants. Even in shortages of skilled workers, existing staff can be trained. Thus, this study suggests integrating this device into community and primary health centers to expand UNHS coverage.
Proposal of a modified technique of Nikolsky's sign in oral autoimmune vesiculobullous diseases
Authors: Petruzzi Massimo
Published: August 2024

Nikolsky's sign, originally described for skin lesions, presents challenges when applied to the oral mucosa. To address this, a modified Nikolsky's sign has been proposed specifically for the oral mucosa. In this variant, a gentle breath of air from the air syringe embedded in the dental unit is used to inflate a pre-existing collapsed blister (non-induced technique). Alternatively, in the induced technique, a healthy peri-lesion mucosal site is gently scratched with a blunt dental tool, and after a few minutes, air is blown on the same area to inflate any newly formed blister. The sign is considered positive if a blister is raised from the blown surface. The described modified Nikolsky's sign improves the visualization of oral vesicles and blisters in a cost-effective, easy, and minimally invasive manner. Its elicitation can aid in referring patients to specialized tertiary care units.
Does the short-term learning effect impact vertical jump performance assessment on a portable force plate system?
Authors: Cabarkapa Damjana V. , Cabarkapa Dimitrije , Aleksic Jelena , Ranisavljev Igor , Fry Andrew C.
Published: August 2024

One of the reoccurring questions that arises during the countermovement vertical jump (CVJ) assessment is whether the learning effect has an impact on the accuracy of the results obtained. Thus, the purpose of the present investigation was to examine the impact of the short-term learning effect on the assessment of lower-body neuromuscular performance characteristics when performed on a portable one-dimensional force plate system. Sixteen recreationally active college-age males volunteered to participate in the present study. Each participant completed four sets of three non-consecutive CVJs with no arm swing throughout a single day. Besides strong verbal encouragement, participants were constantly instructed to focus on pushing the ground as explosively as possible. Fourteen force-time metrics were selected for CVJ performance analysis purposes: eccentric and concentric peak and mean force and power, eccentric and concentric duration, contraction time, jump height, reactive strength index-modified, and countermovement depth. Repeated measures multivariate analysis of variance was used to examine statistically significant differences across four testing time points (p < 0.05). The results indicate an absence of any meaningful differences across four testing time points in force-time metrics of interest during both eccentric and concentric phases of the CVJ. Moreover, no differences were observed in CVJ outcome metrics such as countermovement depth, suggesting that the movement strategy tends to remain consistent. Overall, these findings reveal that CVJ test repeatability is not affected by the short-term learning effect and that data are stable at least within the scope of this study and within this population.
The safety of magnetic resonance imaging contrast agents
Authors: Cunningham Amy , Kirk Martin , Hong Emily , Yang Jing , Howard Tamara , Brearley Adrian , Sáenz-Trevizo Angelica , Krawchuck Jacob , Watt John , Henderson Ian , Dokladny Karol , DeAguero Joshua , Escobar G. Patricia , Wagner Brent
Published: August 2024

Gadolinium-based contrast agents are increasingly used in clinical practice. While these pharmaceuticals are verified causal agents in nephrogenic systemic fibrosis, there is a growing body of literature supporting their role as causal agents in symptoms associated with gadolinium exposure after intravenous use and encephalopathy following intrathecal administration. Gadolinium-based contrast agents are multidentate organic ligands that strongly bind the metal ion to reduce the toxicity of the metal. The notion that cationic gadolinium dissociates from these chelates and causes the disease is prevalent among patients and providers. We hypothesize that non-ligand-bound (soluble) gadolinium will be exceedingly low in patients. Soluble, ionic gadolinium is not likely to be the initial step in mediating any disease. The Kidney Institute of New Mexico was the first to identify gadolinium-rich nanoparticles in skin and kidney tissues from magnetic resonance imaging contrast agents in rodents. In 2023, they found similar nanoparticles in the kidney cells of humans with normal renal function, likely from contrast agents. We suspect these nanoparticles are the mediators of chronic toxicity from magnetic resonance imaging contrast agents. This article explores associations between gadolinium contrast and adverse health outcomes supported by clinical reports and rodent models.
Analysis of Bubble Flow in an Inclined Tube and Modeling of Flow Prediction
Authors: Liang Xiaodi , Wang Suofang , Shen Wenjie
Published: August 2024

The lubricating oil system is a significant component of aviation engine lubrication and cooling, and the scavenge pipe is an essential component of the lubricating oil system. Accurately identifying and understanding the flow state of the scavenge pipe is very important. This article establishes a visualization test bench for a 45-degree inclined scavenge pipe, with upward and downward flow directions, respectively. The test temperature is 370 K, and a high-speed camera captures the changes in the two-phase flow inside the pipeline. Based on high-speed photography photos, we develop software for analyzing the flow characteristics of bubbles inside the tube and explore the influence of gas phase conversion velocity and liquid phase conversion velocity on the apparent velocity of bubbles inside the tube. Multiple algorithms were used to develop the model by combining machine learning with speed and accuracy to establish a data regression prediction model for the apparent velocity of bubbles inside the tube. Through calculation and analysis, it was found that the root mean square error of the prediction model using the BP neural network algorithm was the lowest, and the decision coefficient of the prediction model using the support vector machine algorithm was the highest.
An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC
Authors: Chen Danhe , Xu Lingfeng , Wang Chuangge
Published: August 2024

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV “Silver Fox”, considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency.
Research on UAV Downwash Airflow and Wind-Induced Response Characteristics of Rapeseed Seedling Stage Based on Computational Fluid Dynamics Simulation
Authors: Wang Qilong , Ren Yilin , Wang Haojie , Wang Jiansong , Zhou Guangsheng , Yang Yang , Xie Zhiwei , Bai Xiaotian
Published: August 2024

Multi-rotor unmanned aerial vehicles (UAVs) are increasingly prevalent due to technological advancements. During rapeseed’s seedling stage, UAV-generated airflow, known as wind-induced response, affects leaf movement, tied to airflow speed and distribution. Understanding wind-induced response aids early rapeseed lodging prediction. Determining airflow distribution at various UAV heights is crucial for wind-induced response study, yet lacks theoretical guidance. In this study, Computational Fluid Dynamics (CFD) was employed to analyze airflow distribution at different UAV heights. Fluid–solid coupling simulation assessed 3D rapeseed model motion and surface pressure distribution in UAV downwash airflow. Validation occurred via wind speed experiments. Optimal uniform airflow distribution was observed at 2 m UAV height, with a wind speed variation coefficient of 0.258. The simulation showed greater vertical than horizontal leaf displacement, with elastic modulus inversely affecting displacement and leaf area directly. Discrepancies within 10.5% in the 0.5–0.8 m height range above the rapeseed canopy validated simulation accuracy. This study guides UAV height selection, leaf point determination, and wind-induced response parameter identification for rapeseed seedling stage wind-induced response research.
Rolling Bearing Fault Diagnosis in Agricultural Machinery Based on Multi-Source Locally Adaptive Graph Convolution
Authors: Xie Fengyun , Sun Enguang , Wang Linglan , Wang Gan , Xiao Qian
Published: August 2024

Maintaining agricultural machinery is crucial for efficient mechanized farming. Specifically, diagnosing faults in rolling bearings, which are essential rotating components, is of significant importance. Domain-adaptive technology often addresses the challenge of limited labeled data from a single source domain. However, information transfer can sometimes fall short in providing adequate relevant details for supporting target diagnosis tasks, leading to poor recognition performance. This paper introduces a novel fault diagnosis model based on a multi-source locally adaptive graph convolution network to diagnose rolling bearing faults in agricultural machinery. The model initially employs an overlapping sampling method to enhance sample data. Recognizing that two-dimensional time–frequency signals possess richer spatial characteristics in neural networks, wavelet transform is used to convert time series samples into time–frequency graph samples before feeding them into the feature network. This approach constructs a sample data pair from both source and target domains. Furthermore, a feature extraction network is developed by integrating the strengths of deep residual networks and graph convolutional networks, enabling the model to better learn invariant features across domains. The locally adaptive method aids the model in more effectively aligning features from the source and target domains. The model incorporates a Softmax layer as the bearing state classifier, which is set up after the graph convolutional network layer, and outputs bearing state recognition results upon reaching a set number of iterations. The proposed method’s effectiveness was validated using a bearing dataset from Jiangnan University. For three different groups of bearing fault diagnosis tasks under varying working conditions, the proposed method achieved recognition accuracies above 99%, with an improvement of 0.30%-4.33% compared to single-source domain diagnosis models. Comparative results indicate that the proposed method can effectively identify bearing states even without target domain labels, showcasing its practical engineering application value.
Fruit Variation in Yellow-Fleshed Actinidia (Actinidia chinensis Planch) Plants Grown in Southern Italy as a Function of Shoot Type
Authors: Dattola Antonio , Accardo Antonella , Zappia Rocco , Gullo Gregorio Antonio Maria
Published: August 2024

One of the goals of modern orcharding is to produce a high volume of fruits with uniform size, organoleptic parameters, and health characteristics. The aim of this work was to study various shoot types and their prevailing positions along the cane and to identify how shoot type can influence the quality of fruit from the Actinidia tree. The experiment was conducted over a two-year period in a commercial orchard of Actinidia chinensis, cv. Gold 3. The shoots along the cane were classified as follows: spur shoots (SPs), terminated shoots (TEs), non-terminated shoots (NTs), and cut non-terminated shoots (CNTs). The data were statistically processed using ANOVA and Principal Component Analysis (ACP). Four different categories of fruit were obtained from the four shoot types, and their various attributes were compared. The prevailing category (comprising 55% of the studied fruits) was TEs, which are characterised by a higher soluble solid content, sweetness, and excellent health characteristics, as well as the reduced hardness of their pulp, which would support the hypothesis that harvesting could be brought forward. The second most common category (comprising 19% of total fruit) with the lowest soluble solid content, but a high antioxidant capacity, was that which was detached from the CNTs, while 13% of the fruit was produced from NTs, which had the lowest health value but good sweetness perception. Finally, the category with the lowest fruit percentage over the total fruit harvested (10%) was SPs, which are characterised by their smaller size. It has yet to be determined what the performance of each category will be post-harvest; whether it is possible to assign the quality categories while harvesting the fruit or to differentiate the harvest time accordingly remains subject to debate.
Evaluating Regional Potentials of Agricultural E-Commerce Development Using a Novel MEREC Heronian-CoCoSo Approach
Authors: Huang Shupeng , Cheng Hong , Tan Manyi , Tang Zhiqing , Teng Chuyi
Published: August 2024

In terms of both economy and sustainability, rural areas can greatly benefit from adopting E-commerce. The Chinese government is currently devoting significant efforts to developing agricultural E-commerce. However, one of the most significant problems is the lack of effective tools for evaluating regional potentials in this regard, possibly leading to inappropriate policymaking, investment allocation, and regional planning. To address this issue, this study proposes a novel and effective method for evaluating regional potentials for agricultural E-commerce development, integrating the method based on the removal effects of criteria (MEREC), Heronian mean operator, and combined compromise solution (CoCoSo) method. The method’s effectiveness is then tested and confirmed in the Chinese city of Yibin through an evaluation of its ten regions. The results suggest that such a method is robust, objective, and able to consider indicator interactions effectively. By applying this method, regional agricultural E-commerce development potentials can be thoroughly evaluated and ranked. This study contributes to the literature by providing new analytical techniques for agricultural studies, as well as by supporting political and investment decision-making for governments and E-commerce practitioners in the agriculture sector.
Estimation of Fiber Fragility and Digestibility of Corn Silages and Cool Season Pastures
Authors: Facco Francine B. , Heller Richander G. , Santos Vitória , Viégas Julio , Takiya Caio S. , Gandra Jefferson R. , Del Valle Tiago A.
Published: August 2024

Fiber fragility is defined as the particle size reduction rate during chewing and can help to explain the effects on feed intake and animal performance of different fiber sources. This study aimed to estimate the fiber fragility of corn silage and cool-season pasture based on their chemical composition. Between June and December 2022, 25 samples of corn silage and 25 samples of cool-season pasture were collected from dairy farms in the state of Rio Grande do Sul. The samples were analyzed for particle size distribution, chemical composition, and fiber fragility. Contents of dry matter (DM), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and fiber fragility were greater in corn silages compared to cool-season pasture. However, the ADF–NDF ratio was similar in forages. Crude protein (CP) content and the in situ degradation of DM and NDF were greater in cool-season pasture than corn silage. Dry matter and NDF in situ degradation were negatively correlated with increased contents of ADF, NDF, and ADL and the ADF–NDF ratio in forages. Fiber fragility was negatively correlated with DM degradation and positively correlated with contents of ADF, NDF, ADL, and DM. Fiber fragility decreased as CP content increased. Thus, greater fiber fragility may jeopardize nutrient degradation, and levels of fiber fragility are directly associated with fiber content.
Replacing Tobacco with Hemp in the Beqaa Is Financially Rewarding for Farmers and Government in Lebanon
Authors: Abboud Mazen , Gemayel Joseph , Khnayzer Rony S.
Published: August 2024

Lebanon has been grappling with severe financial and monetary crisis since 2019. In this context, minimizing losses and finding additional revenue sources to sustain state operations have become imperative. One potential solution is to replace subsidized tobacco farming, which has no economic value, with hemp farming for industrial and medicinal purposes. This shift not only ensures economic efficiency but also provides farmers with a moral and profitable crop. However, until now, there has been no scientific study examining the economic impact of hemp cultivation in Lebanon’s Beqaa area. To address this gap, we conducted a Cost-Benefit Analysis within a Business Plan framework to assess the benefits of replacing tobacco with hemp and to provide decision-makers with data-driven strategies. For this analysis, we obtained accurate data on tobacco farming from the state-owned Tobacco Monopoly (Regie), while data on hemp was sourced from existing literature and adapted to Lebanon. Our findings indicate that tobacco farming currently generates USD 828 per dunam for farmers but results in a net loss of USD 317 per dunam to the economy, a shortfall subsidized by the Regie. In contrast, hemp yields a net profit of USD 2405 per dunam, equating to an overall gain of USD 19,240,000 in the Bekaa Valley area. This stark contrast in profitability underscores the potential of hemp as a more lucrative and sustainable alternative to tobacco.
Prediction and Classification of Phenol Contents in Cnidium officinale Makino Using a Stacking Ensemble Model in Climate Change Scenarios
Authors: Lee Hyunjo , Koo Hyun Jung , Lee Kyeong Cheol , Song Yoojin , Joo Won-Kyun , Chae Cheol-Joo
Published: August 2024

Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of medicinal plants. In the study presented herein, we analyzed feature variables that affect the phenolic content of Korean Cnidium officinale Makino (C. officinale Makino) under different climate change scenarios. We applied different climate change scenarios based on environmental information obtained from Yeongju city, Gyeongsangbuk-do, Republic of Korea, and cultivated C. officinale Makino to collect data. The collected data included 3237, 75, and 45 records, and data augmentation was performed to address this data imbalance. We designed a function based on the DPPH value to set the phenolic content grade in C. officinale Makino and proposed a stacking ensemble model for predicting the total phenol contents and classifying the phenolic content grades. The regression model in the performance evaluation presented an improvement of 6.23–7.72% in terms of the MAPE; in comparison, the classification model demonstrated a 2.48–3.34% better performance in terms of accuracy. The classification accuracy was >0.825 when classifying phenol content grades using the predicted total phenol content values from the regression model, and the area under the curve values of the model indicated high model fitness (0.987–0.981). We plan to identify the key feature variables for the optimal cultivation of C. officinale Makino and explore the relationships among these feature variables.
‘No State, No Masters’: Café Lavandería in Tokyo, Music, and Anticapitalism in a Cultural Environment
Authors: González Dávila María José , Pérez Garrido Federico Fco.
Published: August 2024

This paper is part of a series of research that these authors are conducting to study the linguistic landscape of the Tokyo megacity. In this instance, our focus lies on Shinjuku city. However, our examination does not extend to the linguistic landscape of the city itself; rather, it zeroes in on a café situated at its core, the Café Lavandería. How did Café Lavandería contribute to the development of the Hispanic linguistic, sociolinguistic, and subversive landscape in central Tokyo? The research unfolds in various segments. Initially, contextualization introduces the reader to Tokyo and Shinjuku; subsequently, the significance of Café Lavandería and the subversive social and political movements in Japan are elucidated. Following this, the study’s foundation, including the photographic evidence and corresponding data, is presented. Lastly, an analysis of these data is conducted, culminating in an evaluation of Café Lavandería’s impact in Japan.
Estimation of the Attraction Domain for the Quantum Systems Based on the Schrödinger Equation
Authors: Yang Hongli , Yu Guohui , Ivanov Ivan Ganchev
Published: August 2024

This paper investigates a quantum system described by the Schrödinger equation, utilizing the concept of the quantum Lyapunov function. The Lyapunov function is chosen based on the mean value of a virtual mechanical quantity, where different values of P, the mean value of the virtual mechanical quantity in the Lyapunov function, have an impact on the attractive domain of the quantum system. The selected primary optimization algorithms approximating matrix P are the particle swarm optimization (PSO) algorithm and the simulated annealing (SA) algorithm. This study examines the characteristics of the system’s attraction domain under these two distinct algorithms and establishes stability conditions for the nonlinear quantum system. We introduce a method to estimate the size of the attractive domain using the Lyapunov function approach, converting the attractive domain issue into an optimization challenge. Numerical simulations are conducted in various two-dimensional test systems and spin 1/2 particle systems.
Pathway to Fractional Integrals, Fractional Differential Equations, and Role of the H-Function
Authors: Mathai Arak M. , Haubold Hans J.
Published: August 2024

In this paper, the pathway model for the real scalar variable case is re-explored and its connections to fractional integrals, solutions of fractional differential equations, Tsallis statistics and superstatistics in statistical mechanics, the reaction-rate probability integral, Krätzel transform, pathway transform, etc., are explored. It is shown that the common thread in these connections is their H-function representations. The pathway parameter is shown to be connected to the fractional order in fractional integrals and fractional differential equations.
Effects of Probiotic Supplementation on Body Weight, Growth Performance, Immune Function, Intestinal Microbiota and Metabolites in Fallow Deer
Authors: Wang Meihui , Guo Qingyun , Shan Yunfang , Cheng Zhibin , Zhang Qingxun , Bai Jiade , Dong Yulan , Zhong Zhenyu
Published: August 2024

Intestinal diseases are one of the diseases that affect the growth and immunity of deer. Currently, more lactic acid bacteria (LAB) are available as feed additives to improve the intestinal ecological balance of ruminants in production practices. In this study, Enterococcus faecalis was supplemented in the feed of fallow deer for 170 d, and body weights, blood indices and immune levels of fallow deer were counted at 35, 65 and 170 d. The effects of Enterococcus faecalis on the intestinal microbiota and the metabolism of fallow deer were analysed using 16S rDNA and UPLC-MS/MS methods. The results showed that the addition of Enterococcus faecalis to the diet improved body weight and immune function and increased the aggregation of gut microbiota in fallow deer. The addition of Enterococcus faecalis altered the community structure of intestinal microorganisms in fallow deer and increased the number of beneficial bacteria. In addition, combined with metabolomics analysis, it was found that supplementation with Enterococcus faecalis significantly altered the metabolites of fallow deer, mainly regulating lipid metabolism, carbohydrate metabolism and phospholipid metabolism. In conclusion, this study presents, for the first time, evidence that the LAB strain Enterococcus faecalis can be used as a potential probiotic for deer and points to a new direction for the treatment of intestinal disorders in the deer family.