bluuebunny/crossref_metadata_2025 huggingface dataset:
Kazakhstan tulips: comparative analysis of complete chloroplast genomes of four local and endangered species of the genus Tulipa L.
Authors: Tussipkan Dilnur , Shevtsov Vladislav , Ramazanova Malika , Rakhimzhanova Aizhan , Shevtsov Alexandr , Manabayeva Shuga
Published: November 2024

Species of Tulipa are important ornamental plants used for horticultural purposes in various countries, across Asia, Europe, and North Africa. The present study is the first report on typical features of the complete chloroplast genome sequence of four local and endangered species including T. alberti, T. kaufmanniana, T. greigii, and T. dubia from Kazakhstan using Illumina sequencing technology. The comparative analyses revealed that the complete genomes of four species were highly conserved in terms of total genome size (152. 006 bp - 152. 382 bp), including a pair of inverted repeat regions (26. 330 bp - 26. 371 bp), separated by a large single copy region (82.169 bp - 82,378 bp) and a small copy region (17.172 bp -17.260 bp). Total GC content (36.58-36.62 %), gene number (131), and intron length (540 bp - 2620 bp) of 28 genes. The complete genomes of four species showed nucleotide diversity (π =0,003257). The total number of SSR loci was 159 in T. alberti, 158 in T. kaufmanniana, 174 in T. greigii, and 163 in T. dubia. The result indicated that ten CDS genes, namely rpoC2, cemA, rbcL, rpl36, psbH, rps3, rpl22, ndhF, ycf1, and matK, with effective polymorphic simple sequence repeats (SSRs), high sequence variability (SV) ranging from 2.581 to 6.102, and high nucleotide diversity (Pi) of these loci ranging from 0,004 to 0,010. For all intergenic regions longer than 150 bp, twenty one most variable regions were found with high sequence variability (SV) ranging from 4,848 to 11,862 and high nucleotide diversity (Pi) ranging from 0,01599 to 0,01839. Relative synonymous codon usage (RSCU) analysis was used to identify overrepresented and underrepresented codons for each amino acid. Based on the phylogenic analysis, the sequences clustered into four major groups, reflecting distinct evolutionary lineages corresponding to the subgenera Eriostemons, Tulipa, and Orithyia. Notably, T. greigii was distinctively grouped with species from Orithyia and Eriostemons rather than with other Tulipa species, suggesting a unique evolutionary history potentially shaped by geographical isolation or specific ecological pressures. The complete chloroplast genome of the four Tulipa species provides fundamental information for future research studies, even for designing the high number of available molecular markers.
Low-cost nano biochar: a sustainable approach for drought stress mitigation in faba bean (Vicia faba L.)
Authors: Abd El-Moaty Heba Ibrahim , El-Dissouky Ali , Elhusseiny Amel F. , Farag Kareem M. , Abu-Khudir Rasha , Alkuwayti Mayyadah Abdullah , Al Abdulsalam Najla K. , Abdel Rahman Salwa M.
Published: November 2024

This study tends to reach some objectives of the sustainable development goals, which call for responsible consumption and production and climate action. Long-term global food security is affected by drought and the optimal use of water in agricultural areas under climate change scenarios. Our approach aims to amend soil for cultivation under drought stress and improve plant growth to contribute to food security. In this context, a biochar was prepared from peanut shell and thoroughly examined as a soil enhancer for broad bean cultivation during drought stress. The produced biochar exhibited 0.307 g cm−3 bulk density, 9.6 cmol kg−1 cation exchange capacity, −15.5 mV zeta potential, and an average diameter of 21.86 nm. Surprisingly, the application of biochar increased soil water holding capacity and organic matter by 66% and 220%, respectively. Moreover, its application under drought improved plant growth as indicated by stem height, leaf area index, pod number/plant, pod weight, protein level, chlorophyll content, nutrient levels in leaves, and reduced lipid peroxidation and electrolyte leakage. The principal component and factorial analysis of the current study demonstrated correlations between the physiological response of faba bean plants and soil physiochemical parameters after the application of peanut shell-derived biochar. This study presents promising nano biochar that could be an effective sustainable practice for disposing residual materials.
Molecular mechanisms underlying floral fragrance in Camellia japonica ‘High Fragrance’: a time-course assessment
Authors: Chen Xuemei , Zhang Xueping , Li Yongquan , Tian Xueqin , Tian Xueyi , Zhao Hongjie , Xuan Zuying , Xue Kena , Li Yongjuan , Lin Wei
Published: November 2024

Camellia japonica ‘High Fragrance’ is a camellia hybrid known for its unique and intense floral scent. The current understanding of the dynamic changes in its fragrance and the underlying mechanisms are still limited. This study employed a combination of metabolomic and transcriptomic approaches to reveal the characteristics of the metabolites involved in the remarkable fragrance of this camellia and their biosynthetic mechanisms along three flower developmental stages (flower bud, initial bloom, and full bloom). Among the 349 detected volatile organic compounds (VOCs), the majority were terpenes (57, 16.33%) and esters (53, 15.19%). Of these, 136 VOCs exhibited differential accumulation over time. Transcriptomic data from floral organs at different flowering stages identified 56,303 genes, with 13,793 showing significant differential expression. KEGG enrichment analysis revealed 57, 91, and 33 candidate differential genes related to the biosynthesis of terpenes, phenylpropanoids, and fatty acid derivatives, respectively. This indicates that terpenes, esters, and their related synthetic genes might play a crucial role in the formation of ‘High Fragrance’ characteristics. During the entire flowering process, the majority of genes exhibited an elevated expression pattern, which correlated with the progressive accumulation of VOCs. Interestingly, the expression patterns of the differentially expressed genes in the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, associated with terpene synthesis, showed opposite trends. A transcriptional-metabolic regulatory network linking terpenoid compounds, related synthetic enzymes, and potential transcription factors could be outlined for ‘High Fragrance’ camellia, thus providing a theoretical basis for further exploring these events and breeding more fragrant camellias.
Describing and characterizing the WAK/WAKL gene family across plant species: a systematic review
Authors: Harvey Aaron , van den Berg Noëlani , Swart Velushka
Published: November 2024

Wall-associated kinases (WAKs) and WAK-likes (WAKLs) are transmembrane pectin receptors which have seen rising interest in recent years due to their roles in stress responses and developmental pathways. Consequently, the genes encoding these proteins are continuously identified, described and characterised across a wide variety of plant species. The primary goal of characterizing these genes is to classify, describe and infer cellular function, mostly through in silico methods. However, inconsistencies across characterizations have led to discrepancies in WAK/WAKL definitions resulting in sequences being classified as a WAK in one study but as a WAKL or not identified in another. The methods of characterization range widely with different combinations of analyses being conducted, to similar analyses but with varying inputs and parameters which are impacting the outputs. This review collates current knowledge about WAK/WAKL genes and the recent characterizations of this family and suggests a more robust strategy for increased consistency among the different gene members, as well as the characterizations thereof.
Biochar co-compost increases the productivity of Brassica napus by improving antioxidant activities and soil health and reducing lead uptake
Authors: Jiang Wenjie , Liu Ying , Zhou Jing , Tang Haiying , Meng Guiyuan , Tang Xianrui , Ma Yulong , Yi Tuyue , Gad Elsaid Fahmy
Published: November 2024

Lead (Pb) is a serious toxic metal without any beneficial role in the biological system. Biochar (BC) has emerged as an excellent soil amendment to mitigate Pb toxicity. The impact of BC co-compost (BCC) in mitigating the toxic impacts of Pb has not been studied yet. Therefore, this study aimed to evaluate the potential of BC and BCC in improving the growth, physiological, and biochemical traits of Brassica napus and soil properties and reducing health risks (HR). The study was comprised of different Pb concentrations (control and 100 mg kg-1) and organic amendments (control, BC, compost, and BCC). The results indicated that Pb stress reduced the growth, photosynthetic pigments, seed yield, and oil contents by increasing hydrogen peroxide (H2O2) production and Pb uptake and accumulation in plant tissues and decreasing photosynthetic pigment and nutrient availability. The application of BCC alleviated the adverse impacts of Pb and improved seed production (40.24%) and oil yield (11.06%) by increasing chlorophyll a (43.18%) and chlorophyll b (25.58%) synthesis, relative water content (23.89%), total soluble protein (TSP: 23.14%), free amino acids (FAA: 26.47%), proline (30.98%), APX (40.90%), CAT (32.79%), POD (24.93%), and SOD (33.30%) activity. Biochar co-compost-mediated increase in seed and oil yield was also linked with a reduced accumulation of Pb in plant parts and soil Pb availability and improved the soil-available phosphorus, potassium, total nitrogen, soil organic carbon (SOC), and microbial biomass carbon (MBC). Furthermore, BCC also reduced the bioaccumulation concentration, daily metal intake, hazard index, and target hazard quotient. In conclusion, application of BCC can increase the growth, yield, and oil contents of Brassica napus by improving the physiological and biochemical traits and soil properties and reducing the Pb uptake.
Effects of football training on cognitive performance in children and adolescents: a meta-analytic review
Authors: Mao Fan , Yin An , Zhao Shan , Fang Qun
Published: November 2024

Background

The cognitive development of children and adolescents is crucial for their academic success and overall well-being. Physical activity has been linked to improved cognitive performance, but the specific effects of football training on cognitive function in this population remain unclear. This meta-analytic review aimed to comprehensively evaluate the impact of football training on cognitive performance in children and adolescents.

Methods

Literature was searched through PubMed, PsycINFO, SPORTDiscus, Embase, and Web of Science. Eligible studies were randomized controlled trials (RCTs) or crossover designs assessing cognitive performance following football training interventions. Outcome measures included attention, inhibitory control, and working memory. Data synthesis and meta-analysis were performed to determine the overall effect sizes.

Results

Twelve studies were included in the meta-analysis, comprising 1,574 children and 94 adolescents. Football training demonstrated moderate, statistically significant effects on attention (Hedges’ g = −0.77, p = 0.01), inhibitory control (Hedges’ g = −0.67, p = 0.02), and working memory (Hedges’ g = −0.44, p = 0.03). The findings suggest that football training positively influences cognitive performance in children and adolescents.

Conclusion

Football training holds promise for enhancing cognitive function in children and adolescents, particularly in attention, inhibitory control, and working memory. Theoretical frameworks emphasizing environmental enrichment, cardiovascular fitness, and cognitive component skills help elucidate the underlying mechanisms. Future research should explore how football training compares to other sports and assess whether integrative drills that combine cognitive elements with skill practice offer greater cognitive benefits than skill training alone. These insights support the inclusion of football in educational programs to foster cognitive development.
Personality traits and physical activity in patients with gambling disorder attending a rehabilitation center. An observational study
Authors: Fierro Inmaculada , Fernández-Prieto Raúl , Fernández-Parra Alicia , Herrero-Martín Miriam , Herrero Azael J.
Published: November 2024

Objective

Problem gambling is associated with various negative health behaviors, such as physical inactivity. However, physical activity may also be used as a coping mechanism to manage stress and anxiety. This study aimed to investigate whether personality traits are associated with physical activity levels in individuals attending a rehabilitation center for gambling disorder (GD).

Methods

An observational study was conducted in 71 patients belonging to a Gamblers’ Recovery Association. All of them completed a socio-demographic questionnaire, the Exploratory Personality Questionnaire-III (CEPER-III) and the International Physical Activity Questionnaire (IPAQ). Comparisons with general population and association between personality traits and physical activity were analyzed.

Results

The study sample predominantly consisted of male participants (91.5%), with the majority having an educational attainment of compulsory schooling or less (70.4%). Additionally, a substantial proportion of participants exhibited school-related problems (43.7%) and had a history of mental health issues (33.8%). Compared to the general population, individuals in the CEPER-III cohort demonstrated significantly lower scores in the following personality traits: paranoid (p < 0.05), histrionic (p < 0.001), narcissistic (p < 0.001), passive-aggressive (p < 0.05), and sadistic (p < 0.01). Multivariate logistic regression analysis indicated that the antisocial, borderline, obsessive-compulsive, and self-destructive personality traits were significantly associated (p < 0.05) with the level of physical activity.

Conclusion

This study found a link between personality traits and physical activity levels in patients with GD. Gamblers with higher scores on obsessive-compulsive and self-destructive personality traits were more likely to fall into the moderate-high physical activity group. In contrast, those with higher scores on antisocial and borderline personality traits were more likely to be classified in the low physical activity group.
Prevalence of mental disorders and related risk factors in refugees and asylum seekers in Campania
Authors: Giuliani Luigi , Bucci Paola , Bracalenti Raffaele , Giordano Giulia Maria , Conenna Matteo , Corrivetti Giulio , Palumbo Davide , Dell’Acqua Andrea , Piras Federica , Storti Giovanna , Abitudine Verdiana , Di Lieto Roberta , Sandolo Letizia , Schiavitelli Chiara , Mulè Alice , D’Arista Pierpaola , Mucci Armida , Galderisi Silvana
Published: November 2024

Introduction

In recent years, the increasing presence of refugees and asylum seekers displaced from their country of origin, determined significant social, economic, humanitarian and public health implications in host countries, including Italy. These populations are exposed to several potential stressful experiences which make them vulnerable to psychological distress. In fact, the majority of studies addressing the topic found a higher prevalence of mental disorders, especially post-traumatic stress disorder and major depressive disorder, in refugees and asylum seekers with respect to the general population. However, heterogeneous prevalence rates have been reported among studies, due to methodological factor as well as to the impact of a variety of risk factors related to stressful experiences lived in the country of origin, during the migration journey and in the host country.

Objectives

The aim of the present study was to assess the prevalence of the main psychiatric diagnoses in a large group of adult refugees and asylum seekers (N=303) in the reception centers of two provinces of the Campania region, as well as to investigate the impact of potential risk factors on the occurrence of psychiatric disorders.

Methods

The diagnosis of psychiatric disorders and the identification of subjects at high risk to develop psychosis were carried out by means of structured diagnostic interviews. The following variables were explored as potential risk/protective factors to the occurrence of psychiatric disorders: socio-demographic variables, migration status (refugees/asylum seekers) and characteristics of the reception center,assessed by means of an ad hoc questionnaire; cognitive indices assessed by using standardized neuropsychological tests; traumatic experiences and level of political terror in the country of origin, assessed by means of reliable and valid self-report questionnaires.

Results

At least one mental disorder was found in 29.7% of the sample. Most prevalent diagnoses were depressive disorders, anxiety disorders and PTSD. Women showed, with respect to men, a higher prevalence of anxiety disorders, higher trauma levels, and came from more at-risk countries. Higher trauma levels, better cognitive abilities and unemployment and refugee status were associated to the presence of a current psychiatric disorder in the whole sample.

Conclusions

Our findings showed a higher prevalence of depressive disorders and PTSD in the sample of refugees and asylum seekers with respect to the general population and highlighted the role of potential risk factors whose identification may guide the implementation of preventive strategies and early treatments in these people.
Are we doing enough to control infection risk in Australian small animal veterinary practice? Findings from a mixed methods study
Authors: Willemsen Angela , Cobbold Rowland , Gibson Justine , Wilks Kathryn , Reid Simon
Published: November 2024

Background

Managing risk effectively within small animal veterinary practice is integral for staff, patient and client safety. Veterinary personnel are exposed to many risks, including bites, scratches, sharps injuries and exposure to zoonotic diseases and multi-resistant organisms. Patients may also be exposed to healthcare-associated infections, including multi-resistant organisms. While veterinary owners/managers have a duty of care under legislated Workplace Health and Safety requirements, all staff have a responsibility to contribute to assessing and minimizing risk. The application of standard and transmission precautions will help with risk minimization. This study aimed to determine how small animal veterinary staff understand and perceive infection prevention and control risk and to provide recommendations to assist with risk mitigation.

Methods

A mixed methods design was used. A digital questionnaire was administered to small animal veterinary staff in Australia to identify knowledge, attitudes and practices of risk related behaviors. Follow up focus groups were conducted with small animal practitioners to explore factors supporting and preventing veterinary staff from implementing recommended practices identified in the questionnaire.

Results

Small animal veterinary staff acknowledged they participated in many high-risk activities, including recapping needles and eating and drinking in patient care areas. Injuries were common, with 77% of staff receiving a bite or scratch, and 22% receiving a sharps injury in the preceding six months. Less than one in five of these incidents was reported. Staff agreed effective infection prevention and control was the responsibility of all staff, but a designated staff member should take responsibility for managing it. The practice owner/manager was integral to supporting and promoting recommended strategies, contributing to a positive workplace culture and improving safety for staff and patients.

Conclusion

Small animal veterinary staff have some understanding of how to identify, report, manage and mitigate risk but were limited by their knowledge of infection prevention and control principles.
Haematological parameters and biochemical indices of African catfish (Clarias gariepinus) exposed to glyphosate-based herbicide (Force up®) for 96 hours
Authors: Alarape Selim Adewale , Adeoye Deborah Damilola , Amusa Azeezat Oluwakemi , Adeyemo Olanike Kudirat
Published: November 2024

Introduction

Geometric aquaculture growth has resulted in exponentially increasing use of agrochemicals as either parasiticides or herbicides in the aquaculture environment. This study determines some of the toxicological (haematological and biochemical) effects of glyphosate-based herbicides on non-target aquatic animals using Clarias gariepinus as the animal model.

Method

Seventy-five apparently healthy adult C. gariepinus (300 g) were sourced from a local farmer and acclimatised for 2 weeks; of these, sixty subjects were divided into four treatment groups (fifteen fish per group and five replicates per unit) by simple randomisation and labelled as T0 (control), T1 (first treatment), T2 (second treatment), and T3 (third treatment). The treatments were replicated thrice. Four concentrations of Force up® [0 mL, 0.15 mL (0.003 mL/L or 5.1 mg/L), 0.225 mL (0.0045 mL/L or 7.65 mg/L), and 0.3 mL (0.006 mL/L or 10.2 mg/L) were added to a 50-L tank of water for T0, T1, T2, and T3, respectively. Approximately 5 mL of blood was collected from the fish in each treatment group 96 h post-exposure for measurement of the blood parameters and biochemical indices using standard analytical methods as well as calculation of the mean values.

Result

The mean values of the packed cell volume, haemoglobin concentration, red blood cell count, and white blood cell count compared to the control group showed an initial increase at T1 but decreased as the glyphosate concentrations increased at T2 (0.0045 mL/L) and T3 (0.006 mL/L). The platelet mean values decreased at T1, increased at T2, and decreased at T3, while the mean values of the corpuscular volume, corpuscular haemoglobin, and corpuscular haemoglobin concentration increased with glyphosate concentration, with the mean corpuscular haemoglobin concentration decreasing at T2. Only the platelet value was statistically significant at a p-value of <0.05 using ANOVA and post hoc Tukey test. The biochemical indices showed decreases in the mean values of aspartate transaminase, blood urea nitrogen, creatinine, and triglycerides at T1, increases at T2, and decreases at T3, while the total protein (g/dL), cholesterol, alanine transaminase, and alkaline phosphatase values showed increases at T1 and decreases at T2 and T3. All these values were not statistically significant based on ANOVA and had p-values >0.05.

Discussion

Based on the results of this study, it is deduced that glyphosate-based herbicide (Force up®) has genotoxic, hepatotoxic, and nephrotoxic effects on C. gariepinus even at sublethal doses, with more adverse effects at increasing concentrations.
Enhanced pathogenicity and synergistic effects of co-infection with bovine viral diarrhea virus 1 and HoBi-like virus in cattle and guinea pigs
Authors: Cui Hongliang , Ren Baoru , Wang Linglong , Chen Jian , Li Jie , Hu Wei , Yang Yang
Published: November 2024

Introduction

The Bovine Viral Diarrhea Virus 1 (BVDV1) and HoBi-like virus (BVDV3), both within the same genus, share genomic homology and exhibit low antigenic cross-reactivity despite presenting similar clinical manifestations. In 2021, a bovine respiratory disease complex (BRDC) outbreak on two cattle farms in the Inner Mongolia Autonomous Region of China resulted in ten fatalities.

Methods

Metagenomic and metatranscriptomic analyses were used to identify viral agents, including a co-infection case. A genetic evolution analysis assessed the relationships with related strains. Experimental infections in guinea pigs and calves evaluated the pathogenicity of the viruses

Results

Phylogenetic analysis of the BVDV3 isolate IM2201 revealed close relatedness to Brazilian strains, with 97.06% nucleotide homology to the highly virulent strain SV478/07. Experimental co-infection in guinea pigs resulted in more severe clinical signs, including fever, cough, diarrhea, and significant pathological changes, and led to a higher mortality rate (40%) compared to no mortality from single-virus infections with BVDV1 or BVDV3. Similarly, co-infected cattle exhibited more severe clinical signs, including bloody diarrhea and rectal temperatures exceeding 40°C, along with persistent viremia and nasal viral shedding from 7 to 21 days post-infection. Blood analysis revealed significant reductions in white blood cell counts, particularly in co-infected cattle.

Discussion

This study highlights the enhanced pathogenicity and synergistic effects of BVDV1 and BVDV3 co-infection, exacerbating disease severity.
Can the Plantar Pressure and Temperature Data Trend Show the Presence of Diabetes? A Comparative Study of a Variety of Machine Learning Techniques
Authors: Gerlein Eduardo A. , Calderón Francisco , Zequera-Díaz Martha , Naemi Roozbeh
Published: November 2024

This study aimed to explore the potential of predicting diabetes by analyzing trends in plantar thermal and plantar pressure data, either individually or in combination, using various machine learning techniques. A total of twenty-six participants, comprising thirteen individuals diagnosed with diabetes and thirteen healthy individuals, walked along a 20 m path. In-shoe plantar pressure data were collected and the plantar temperature was measured both immediately before and after the walk. Each participant completed the trial three times, and the average data between the trials were calculated. The research was divided into three experiments: the first evaluated the correlations between the plantar pressure and temperature data; the second focused on predicting diabetes using each data type independently; and the third combined both data types and assessed the effect of such to enhance the predictive accuracy. For the experiments, 20 regression models and 16 classification algorithms were employed, and the performance was evaluated using a five-fold cross-validation strategy. The outcomes of the initial set of experiments indicated that the machine learning models were significant correlations between the thermal data and pressure estimates. This was consistent with the findings from the prior correlation analysis, which showed weak relationships between these two data modalities. However, a shift in focus towards predicting diabetes by aggregating the temperature and pressure data led to encouraging results, demonstrating the effectiveness of this approach in accurately predicting the presence of diabetes. The analysis revealed that, while several classifiers demonstrated reasonable metrics when using standalone variables, the integration of thermal and pressure data significantly improved the predictive accuracy. Specifically, when only plantar pressure data were used, the Logistic Regression model achieved the highest accuracy at 68.75%. Those predictions based solely on temperature data showed the Naive Bayes model as the lead with an accuracy of 87.5%. Notably, the highest accuracy of 93.75% was observed when both the temperature and pressure data were combined, with the Extra Trees Classifier performing the best. These results suggest that combining temperature and pressure data enhances the model’s predictive accuracy. This can indicate the importance of multimodal data integration and their potentials in diabetes prediction.
Efficient Power Conditioning: Enhancing Electric Supply for Small Satellite Missions
Authors: Khan Shoaib Ahmed , Ali Anwar , Tahir Mustafa , Tao Zou
Published: November 2024

Electric power supply (EPS) is the heart of any aerospace mission and plays an important role in improving the performance and service lifetime of spacecraft. It generates, converts, stores, and distributes power to different voltage levels. The EPS is composed of solar panels, a power conditioning unit (PCU), batteries, and a power distribution unit (PDU). This paper describes the design and analysis of an efficient power conditioning system for a CubeSat standard small satellite. For this purpose, the aim of this paper is to propose a two-input maximum power point tracker (MPPT)-based interleaved boost converter. The design copes with the fact that when a satellite revolves around the Earth, a single panel or at most two panels face solar radiation at different angles. In order to extract maximum power from the panels, the designed converter drives the solar panels at the maximum power point (MPP). A small signal model is drawn for the converter, and the closed-loop gain of the converter is analyzed using a Bode diagram. To improve the phase margin and gain, a PID compensator is designed and added to the closed loop of the converter. Finally, the performance of the proposed converter is validated by the simulation results.
Autonomous UAV Chasing with Monocular Vision: A Learning-Based Approach
Authors: Jin Yuxuan , Song Tiantian , Dai Chengjie , Wang Ke , Song Guanghua
Published: November 2024

In recent years, unmanned aerial vehicles (UAVs) have shown significant potential across diverse applications, drawing attention from both academia and industry. In specific scenarios, UAVs are expected to achieve formation flying without relying on communication or external assistance. In this context, our work focuses on the classic leader-follower formation and presents a learning-based UAV chasing control method that enables a quadrotor UAV to autonomously chase a highly maneuverable fixed-wing UAV. The proposed method utilizes a neural network called Vision Follow Net (VFNet), which integrates monocular visual data with the UAV’s flight state information. Utilizing a multi-head self-attention mechanism, VFNet aggregates data over a time window to predict the waypoints for the chasing flight. The quadrotor’s yaw angle is controlled by calculating the line-of-sight (LOS) angle to the target, ensuring that the target remains within the onboard camera’s field of view during the flight. A simulation flight system is developed and used for neural network training and validation. Experimental results indicate that the quadrotor maintains stable chasing performance through various maneuvers of the fixed-wing UAV and can sustain formation over long durations. Our research explores the use of end-to-end neural networks for UAV formation flying, spanning from perception to control.
Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA
Authors: Guo Changjing , Xu Zhiling , Yang Xiaoyan , Li Hao
Published: November 2024

To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). The NACA4412 airfoil is selected as the research subject, optimizing the original airfoil at three angles of attack (2°, 5° and 10°). The CST (Class Function/Shape Function Transformation) airfoil parametrization method is used to parameterize the original airfoil, and Latin hypercube sampling is employed to perturb the original airfoil within a certain range to generate a sample space. CFD (Computational Fluid Dynamics) software (2024.1) is used to perform aerodynamic analysis on the airfoil shapes within the sample space to construct a sample dataset. Subsequently, the DBO algorithm optimizes the initial weights and thresholds of the BP neural network surrogate model to establish the DBO-BP neural network surrogate model. Finally, the NSWOA algorithm is utilized for multi-objective optimization, and CFD software verifies and analyzes the optimization results. The results show that at the angles of attack of 2°, 5° and 10°, the test accuracy of the lift coefficient is increased by 45.35%, 13.4% and 49.3%, and the test accuracy of the drag coefficient is increased by 12.5%, 39.1% and 13.7%. This significantly enhances the prediction accuracy of the BP neural network surrogate model for aerodynamic analysis results, making the optimization outcomes more reliable. The lift coefficient of the airfoil is increased by 0.04342, 0.01156 and 0.03603, the drag coefficient is reduced by 0.00018, 0.00038 and 0.00027, respectively, and the lift-to-drag ratio is improved by 2.95892, 2.96548 and 2.55199, enhancing the convenience of airfoil aerodynamic optimization and improving the aerodynamic performance of the original airfoil.
Model-Based Sequential Design of Experiments with Machine Learning for Aerospace Systems
Authors: Gerling Tim , Dresia Kai , Deeken Jan , Waxenegger-Wilfing Günther
Published: November 2024

Traditional experimental design methods often face challenges in handling complex aerospace systems due to the high dimensionality and nonlinear behavior of such systems, resulting in nonoptimal experimental designs. To address these challenges, machine learning techniques can be used to further increase the application areas of modern Bayesian Optimal Experimental Design (BOED) approaches, enhancing their efficiency and accuracy. The proposed method leverages neural networks as surrogate models to approximate the underlying physical processes, thereby reducing computational costs and allowing for full differentiability. Additionally, the use of reinforcement learning enables the optimization of sequential designs and essential real-time capability. Our framework is validated by optimizing experimental designs that are used for the efficient characterization of turbopumps for liquid propellant rocket engines. The reinforcement learning approach yields superior results in terms of the expected information gain related to a sequence of 15 experiments, exhibiting mean performance increases of 9.07% compared to random designs and 6.47% compared to state-of-the-art approaches. Therefore, the results demonstrate significant improvements in experimental efficiency and accuracy compared to conventional methods. This work provides a robust framework for the application of advanced BOED methods in aerospace testing, with implications for broader engineering applications.
Machine-Learning Methods Estimating Flights’ Hidden Parameters for the Prediction of KPIs
Authors: Vouros George , Ioannidis Ioannis , Santipantakis Georgios , Tranos Theodore , Blekas Konstantinos , Melgosa Marc , Prats Xavier
Published: November 2024

Complex microscopic simulation models of strategic Air Traffic Management (ATM) performance assessment and decision-making are hindered by several factors. One of the most important is the existence of hidden parameters—such as aircraft take-off weight (TOW) and the selected cost index (CI)—which, if known, would allow for more effective performance modeling methodologies for assessing Key Performance Indicators (KPIs) at various levels of abstraction/detail, e.g., system-wide, or at the level of individual flights. This research proposes a data-driven methodology for the estimation of flights’ hidden parameters combining mechanistic and advanced Artificial Intelligence/Machine Learning (AI/ML) models. Aiming at microsimulation models, our goal is to study the effect of these estimations on the prediction of flights’ KPIs. In so doing, we propose a novel methodology according to which data-driven methods are trained given optimal trajectories (produced by mechanistic models) corresponding to known hidden parameter values, with the aim of predicting hidden parameters’ values of unseen trajectories. The results show that estimations of hidden parameters support the accurate prediction of KPIs regarding the efficiency of flights: fuel consumption, gate-to-gate time and distance flown.
Characteristics and Risk Assessment of Heavy Metal Contamination in Arable Soils Developed from Different Parent Materials
Authors: Wang Junlei , Dong Chunyu , Sun Sijing , Peng Shiqi , Mu Liyuan , Zhang Naiming , Bao Li
Published: November 2024

This study analyzes the heavy metal pollution in cultivated soils developed from different parent materials in Yunnan Province and assesses their risk levels. The results show significant regional differences in soil heavy metal pollution, greatly influenced by the type of parent material. Cadmium (Cd) pollution is most severe in multiple parent material soil regions, particularly in areas with carbonate and purple rocks, exhibiting a high pollution risk. Other heavy metals such as zinc (Zn), copper (Cu), and lead (Pb) also show varying degrees of enrichment in different parent material zones, posing potential pollution risks. The soil pollution levels of heavy metals were classified using the geo-accumulation index method. It was found that soils developed from carbonate rocks and purple rocks have the most severe heavy metal pollution, while soils from quartzitic rocks, acidic crystalline rocks, and basalt exhibit relatively lower pollution levels. By analyzing the characteristics of heavy metal pollution in different parent materials, this study provides a scientific basis for regional soil pollution management and sustainable agricultural development.
Variability in Nutrient Content and Biochemical Parameters of Soil Under Rotational Pasture Management of Farmed Fallow Deer
Authors: Futa Barbara , Ukalska-Jaruga Aleksandra , Tajchman Katarzyna , Janiszewski Paweł , Pecio Monika
Published: November 2024

Fallow deer are animals kept on large-scale pastures, which influence soil properties, including the content of nutrients in the soil and the flow of these nutrients in the soil–plant–animal system. Therefore, the aim of this case study was to analyze the variability in the macronutrient content and biochemical properties of soil under rotational grazing conditions of farmed fallow deer. Fallow deer grazed in two summer pens from April to November, and in the winter pen from December to March. The analyses included the determination of several soil parameters to capture sensitive soil changes and assess potential degradation of the soil environment in response to grazing: pHKCl, TOC, TN, N-NO3, N-NH4+, total (P, K, Mg, Ca, and Na) and available (Pav, Kav, Mgav) forms of macronutrients, and selected soil enzymes (dehydrogenase, acid phosphatase and alkaline phosphatase, and urease). The results showed that the pHKCl in the plots used by farm fallow deer was lower than in the soil of the control object. Moreover, the TN and TOC content in the soils of all pastures was statistically significantly lower than in the soil without grazing, while for TOC, the same effect was observed in the winter pasture soil. The content of N-NO3− was several times higher than that of N-NH4+ in the soils of the studied breeding plots. The relationships noted indicate that grazing is important in the transformation of soil organic matter, which is influenced by the relationship between carbon and nitrogen. In addition, the grazing of farmed fallow deer had a negative effect on the content of P in the soils of all pastures and a positive impact on the accumulation of K. Winter grazing had a positive effect on the amount of Pav and Kav in the soil, but a negative effect on the content of Mgav, compared to grazing in the summer quarters. In the plots used for pastures, the activity of soil enzymes was higher than in the control soil. It has been shown that the influence of fallow deer farming on the soil environment of pastures is not unequivocal. Therefore, long-term monitoring of changes in the properties of these soils is necessary.
Integration of Optical and Synthetic Aperture Radar Data with Different Synthetic Aperture Radar Image Processing Techniques and Development Stages to Improve Soybean Yield Prediction
Authors: Cunha Isabella A. , Baptista Gustavo M. M. , Prudente Victor Hugo R. , Melo Derlei D. , Amaral Lucas R.
Published: November 2024

Predicting crop yield throughout its development cycle is crucial for planning storage, processing, and distribution. Optical remote sensing has been used for yield prediction but has limitations, such as cloud interference and only capturing canopy-level data. Synthetic Aperture Radar (SAR) complements optical data by capturing information even in cloudy conditions and providing additional plant insights. This study aimed to explore the correlation of SAR variables with soybean yield at different crop stages, testing if SAR data enhances predictions compared to optical data alone. Data from three growing seasons were collected from an area of 106 hectares, using eight SAR variables (Alpha, Entropy, DPSVI, RFDI, Pol, RVI, VH, and VV) and four speckle noise filters. The Random Forest algorithm was applied, combining SAR variables with the EVI optical index. Although none of the SAR variables showed strong correlations with yield (r < |0.35|), predictions improved when SAR data were included. The best performance was achieved using DPSVI with the Boxcar filter, combined with EVI during the maturation stage (with EVI:RMSE = 0.43, 0.49, and 0.60, respectively, for each season; while EVI + DPSVI:RMSE = 0.39, 0.49, and 0.42). Despite improving predictions, the computational demands of SAR processing must be considered, especially when optical data are limited due to cloud cover.
Detection of the Pigment Distribution of Stacked Matcha During Processing Based on Hyperspectral Imaging Technology
Authors: He Qinghai , Liu Zhiyuan , Li Xiaoli , He Yong , Lin Zhi
Published: November 2024

Color is a key indicator for evaluating the quality of tea during processing; various processing procedures can significantly affect the content of fat-soluble pigments of tea, which in turn affects the color and quality of finished tea. Therefore, there is an urgent demand for the fast, non-destructive detection of pigments of stacked tea during processing. This paper presents the use of hyperspectral imaging technology (HSI), combined with machine learning algorithms, to detect chlorophyll a, chlorophyll b, and carotenoids in stacked matcha tea during processing. Firstly, a quantitative relationship between HSI data of tea and their pigment contents was developed based on regression analysis, and the results showed that exceptional prediction performance was achieved by the partial least squares regression (PLSR) algorithm combined with the feature band algorithm of competitive adaptive reweighting (CARS), and the Rp2 values of detection models of chlorophyll a, chlorophyll b and carotenoids were 0.90465, 0.92068 and 0.62666, respectively. Then, these quantitative detection models were extended to each pixel in hyperspectral images, achieving point-by-point prediction of pigment components, so the distribution of pigments of stacked tea leaves during processing procedures was successfully visualized on the processing line in situ. By integrating a hyperspectral imaging system into the real-world environment, operators can monitor pigment levels in real time and thus dynamically adjust processing parameters based on real-time data. This study enhances pigment detection efficiency in tea processing, supports process optimization, and aids in quality control.
Fungi Preference of Fungivorous Nematode Aphelenchus avenae (Aphelenchida: Aphelenchidae) and Its Impact on Strawberry (Fragaria ananassa Duch.) Root
Authors: Li Xingyue , Zeng Shuocheng , Yi Jun , Zhang Haiting , Fu Huijuan , Chen Cheng , Liu Qizhi , Cao Aocheng , Yang Wuyun
Published: November 2024

In continuously cropped strawberry soil, a large population of the fungivorous nematode, Aphelenchus avenae, was observed to increase significantly over time. This nematode, which feeds on pathogenic fungi affecting strawberries, has significant potential as a biocontrol agent. The purpose of this article is to discuss the nematode’s preference for fungi associated with strawberries and its impact on the growth of strawberry roots. With the exception of Trichoderma harzianum, most of the pathogenic fungi commonly found in strawberry soil, such as Fusarium oxysporum, Rhizoctonia solani, Verticillium, Phytophthora infestans, and Botrytis cinerea Pers. attracted A. avenae and supported their propagation. All treatments with A. avenae and the non-nematode control showed a consistent trend throughout strawberry development, indicating that a moderate amount of A. avenae does not adversely affect strawberry roots. Moderate and low levels of A. avenae significantly increased the activity of antioxidant enzymes, superoxide dismutase (SOD), and peroxidase (POD) in strawberry roots in all treatments during the entire growth stages. Also, the malondialdehyde (MDA) content of strawberry roots in all nematode treatments was lower than that in the no-nematode control. Despite an overabundance of A. avenae, which negatively affected the redox system balance of strawberry roots, A. avenae can protect the roots from pathogenic fungi by preventing infection and damage. These results lay the foundation for the potential use of A. avenae as a biological agent to control these pathogenic fungi in strawberry soil, in combination with the biological fungi (T. harzianum).
Sustainability and Perspectives of Edible Insect Rearing and Utilization of Their Products and Byproducts
Authors: Errico Simona
Published: November 2024

This Special Issue, titled “Sustainability and Perspectives of Edible Insect Rearing and Utilization of Their Products and Byproducts”, aimed to gather high-quality scientific contributions suggesting innovative solutions for rearing edible insects and new perspectives on the use of rearing products and by-products [...]
The Evaluation of Compost Maturity and Ammonium Toxicity Using Different Plant Species in a Germination Test
Authors: Lončarić Zdenko , Galić Vlatko , Nemet Franjo , Perić Katarina , Galić Lucija , Ragályi Péter , Uzinger Nikolett , Rékási Márk
Published: November 2024

The determination of the maturity of compost and other organic fertilizers is very important because of possible phytotoxic or phytostimulating effects. The maturity of compost can be assessed on the basis of chemical analyses, and a germination test with different test plants is most often used to determine phytotoxicity. In this research, the maturity of compost produced from the plant residues subsequent to the maintenance of green public areas was assessed using the results of chemical analyses. Simultaneously, a germination test was carried out with the four test plant species (cucumber, garden cress, triticale, and barley) to determine the phytotoxicity of compost extract in a ratio of 1:2.5 v/v (1:3.3 w/v) and 1:10 v/v (1:13.3 w/v) and the three ammonium N solutions (in the concentrations of 200, 400, and 600 mg/L NH4-N). According to the chemical properties of compost (primarily the C/N, NH4-N/NO3-N ratios, and the NH4-N concentration) and the germination test with cucumber and garden cress, we may conclude that the tested compost was mature and that we did not expect a phytotoxic effect. The choice of a plant is very significant because the germination test with a compost extract demonstrated an undoubted phytostimulating effect on the garden cress and cucumber, with a more pronounced phytostimulating effect of the 1:10 than that of the 1:2.5 v/v compost extract. No such effect was detected on the monocotyledonous test plants triticale and barley since the 1:10 v/v extract had no significant effect, and the 1:2.5 v/v extract had a phytotoxic effect, moderate on the triticale and high on barley. The conclusion is that garden cress and cucumber are suitable test plants for the determination of compost’s phytostimulative effect, but they are not suitable for the determination of phytotoxicity for monocotyledonous plants, especially if the cause of phytotoxicity is a non-ammonium component. Barley is the most suitable species for the determination of compost’s non-ammonium phytotoxicity and nitrogen’s ammonium-form phytostimulative or phytotoxic effect. It would be very useful to conduct a comparative germination test with the compost extracts in the ratios 1:2.5 and 1:10, whereby the 1:2.5 extract would be used as a test of phytotoxicity, and the 1:10 extract for the test of a phytostimulating effect.