bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutritional Monitoring of Rhodena Lettuce via Neural Networks and Point Cloud Analysis
Authors: Ramírez-Pedraza Alfonso , Salazar-Colores Sebastián , Terven Juan , Romero-González Julio-Alejandro , González-Barbosa José-Joel , Córdova-Esparza Diana-Margarita
Published: September 2024

In traditional farming, fertilizers are often used without precision, resulting in unnecessary expenses and potential damage to the environment. This study introduces a new method for accurately identifying macronutrient deficiencies in Rhodena lettuce crops. We have developed a four-stage process. First, we gathered two sets of data for lettuce seedlings: one is composed of color images and the other of point clouds. In the second stage, we employed the interactive closest point (ICP) method to align the point clouds and extract 3D morphology features for detecting nitrogen deficiencies using machine learning techniques. Next, we trained and compared multiple detection models to identify potassium deficiencies. Finally, we compared the outcomes with traditional lab tests and expert analysis. Our results show that the decision tree classifier achieved 90.87% accuracy in detecting nitrogen deficiencies, while YOLOv9c attained an mAP of 0.79 for identifying potassium deficiencies. This innovative approach has the potential to transform how we monitor and manage crop nutrition in agriculture.
Automated Windrow Profiling System in Mechanized Peanut Harvesting
Authors: Senni Alexandre Padilha , Tronco Mario Luiz , Pedrino Emerson Carlos , Silva Rouverson Pereira da
Published: September 2024

In peanut cultivation, the fact that the fruits develop underground presents significant challenges for mechanized harvesting, leading to high loss rates, with values that can exceed 30% of the total production. Since the harvest is conducted indirectly in two stages, losses are higher during the digging/inverter stage than the collection stage. During the digging process, losses account for about 60% to 70% of total losses, and this operation directly influences the losses during the collection stage. Experimental studies in production fields indicate a strong correlation between losses and the height of the windrow formed after the digging/inversion process, with a positive correlation coefficient of 98.4%. In response to this high correlation, this article presents a system for estimating the windrow profile during mechanized peanut harvesting, allowing for the measurement of crucial characteristics such as the height, width and shape of the windrow, among others. The device uses an infrared laser beam projected onto the ground. The laser projection is captured by a camera strategically positioned above the analyzed area, and through advanced image processing techniques using triangulation, it is possible to measure the windrow profile at sampled points during a real experiment under direct sunlight. The technical literature does not mention any system with these specific characteristics utilizing the techniques described in this article. A comparison between the results obtained with the proposed system and those obtained with a manual profilometer showed a root mean square error of only 28 mm. The proposed system demonstrates significantly greater precision and operates without direct contact with the soil, making it suitable for dynamic implementation in a control mesh for a digging/inversion device in mechanized peanut harvesting and, with minimal adaptations, in other crops, such as beans and potatoes.
Characterization of Maize, Common Bean, and Avocado Crops under Abiotic Stress Factors Using Spectral Signatures on the Visible to Near-Infrared Spectrum
Authors: Goez Manuel , Torres-Madronero Maria C. , Rondon Tatiana , Guzman Manuel A. , Casamitjana Maria , Gonzalez Juan Manuel
Published: September 2024

Abiotic stress factors can be detected using visible and near-infrared spectral signatures. Previous work demonstrated the potential of this technology in crop monitoring, although a large majority used vegetation indices, which did not consider the complete spectral information. This work explored the capabilities of spectral information for abiotic stress detection using supervised machine learning techniques such as support vector machine (SVM), random forest (RF), and neural network (NN). This study used avocados grown under various water treatments, maize submitted to nitrogen deficiency, and common beans under phosphorous restriction. The spectral characterization of the crops subjected to abiotic stress was studied on the visible to near-infrared (450 to 900 nm) spectrum, identifying discriminative bands and spectral ranges. Then, the advantages of using an integrated approach based on machine learning to detect abiotic stress in crops were demonstrated. Instead of relying on vegetation indices, the proposed approach used several spectral features obtained by analyzing the discriminative signature shape, applying a spectral subset band selection algorithm based on similarity, and using the minimum redundancy maximum relevance (MRMR), F-test and chi-square test ranks for feature selection. The results showed that supervised classifiers applied to the spectral features outperform the accuracies obtained from vegetation indices. The best common bean results were obtained using SVM with accuracies up to 91%; for maize and avocado, NN obtained 90% and 82%, respectively. It is noted that detection accuracy depends on various factors, such as crop type, genotype, and level of stress.
Multivariate Adaptive Regression Splines Enhance Genomic Prediction of Non-Additive Traits
Authors: de Oliveira Celeri Maurício , da Costa Weverton Gomes , Nascimento Ana Carolina Campana , Azevedo Camila Ferreira , Cruz Cosme Damião , Sagae Vitor Seiti , Nascimento Moysés
Published: September 2024

The present work used Multivariate Adaptive Regression Splines (MARS) for genomic prediction and to study the non-additive fraction present in a trait. To this end, 12 scenarios for an F2 population were simulated by combining three levels of broad-sense heritability (h2 = 0.3, 0.5, and 0.8) and four amounts of QTLs controlling the trait (8, 40, 80, and 120). All scenarios included non-additive effects due to dominance and additive–additive epistasis. The individuals’ genomic estimated breeding values (GEBV) were predicted via MARS and compared against the GBLUP method, whose models were additive, additive–dominant, and additive–epistatic. In addition, a linkage disequilibrium study between markers and QTL was performed. Linkage maps highlighted the QTL and molecular markers identified by the methodologies under study. MARS showed superior results to the GBLUP models regarding predictive ability for traits controlled by 8 loci, and results were similar for traits controlled by more than 40 loci. Moreover, the use of MARS, together with a linkage disequilibrium study of the trait, can help to elucidate the traits’ genetic architecture. Therefore, MARS showed potential to improve genomic prediction, especially for oligogenic traits or traits controlled by approximately 40 QTLs, while enabling the elucidation of the genetic architecture of traits.
Spatiotemporal Graph Autoencoder Network for Skeleton-Based Human Action Recognition
Authors: Abduljalil Hosam , Elhayek Ahmed , Marish Ali Abdullah , Alsolami Fawaz
Published: September 2024

Human action recognition (HAR) based on skeleton data is a challenging yet crucial task due to its wide-ranging applications, including patient monitoring, security surveillance, and human- machine interaction. Although numerous algorithms have been proposed to distinguish between various activities, most practical applications require highly accurate detection of specific actions. In this study, we propose a novel, highly accurate spatiotemporal graph autoencoder network for HAR, designated as GA-GCN. Furthermore, an extensive investigation was conducted employing diverse modalities. To this end, a spatiotemporal graph autoencoder was constructed to automatically learn both spatial and temporal patterns from skeleton data. The proposed method achieved accuracies of 92.3% and 96.8% on the NTU RGB+D dataset for cross-subject and cross-view evaluations, respectively. On the more challenging NTU RGB+D 120 dataset, GA-GCN attained accuracies of 88.8% and 90.4% for cross-subject and cross-set evaluations. Overall, our model outperforms the majority of the existing state-of-the-art methods on these common benchmark datasets.
Hypervolume-Based Multi-Objective Optimization Method Applying Deep Reinforcement Learning to the Optimization of Turbine Blade Shape
Authors: Yonekura Kazuo , Yamada Ryusei , Ogawa Shun , Suzuki Katsuyuki
Published: September 2024

A multi-objective turbine shape optimization method based on deep reinforcement learning (DRL) is proposed. DRL-based optimization methods are useful for repeating optimization tasks that arise in applications such as the design of turbines and automotive parts. In conventional research, DRL is applied only to single-optimization tasks. In this study, a multi-objective optimization method using improvements in hypervolume is proposed. The proposed method is applied to a benchmark problem and a turbine optimization problem. It succeeded in efficiently solving the problems, and Pareto optimal solutions are obtained.
Evaluation of the Effect of a New Skin Fixation Technique to Avoid Shrinkage of Skin Samples Obtained from Canine Cadavers
Authors: Zorgevica-Pockevica Ligita , Kuzhel Nataliia , Kerziene Sigita , Vincenti Simona
Published: September 2024

Skin shrinkage begins immediately after surgical incision and is an artefact associated with the excision and fixation of a specimen. Skin shrinkage results in important changes in histologic tissue dimensions and can affect the correct quantification of the histologic tumour-free margin (HTFM). Bilateral and symmetrical circular skin samples with a diameter of 60 mm were taken from the lateral thoracic, flank and femoral regions of dog cadavers, with the samples from one side belonging to the study group and the samples from the same animal from the other side belonging to the control group. The radius and diameter of the specimen were measured immediately after the excision and 10 min later for each sample. The measurements of the study group were taken again after manual re-extension and fixation on a cork plate before formalin fixation and 48 h after formalin fixation. A total of 66 (33 study and 33 control group) samples were collected from 11 canine cadavers. The mean diameter shrinkage after formalin fixation was 18.24% for the control group and 0.64% for the study group. A statistically significant difference between the study and the control group was found (p < 0.001). This method of specimen fixation in the study group avoided skin shrinkage and deformation of the specimen in formalin, which we believe improves the diagnostic accuracy of surgical margins and, thus, reduces the number of false-positive or false-negative HTFM.
Trends in Antimicrobial Resistance of Uropathogens Isolated from Urinary Tract Infections in a Tertiary Care Hospital in Dhaka, Bangladesh
Authors: Chowdhury Sara Sadia , Tahsin Promi , Xu Yun , Mosaddek Abu Syed Md. , Muhamadali Howbeer , Goodacre Royston
Published: September 2024

Background/Objectives: Urinary tract infection (UTI) is a prevalent microbial infection in medical practise, leading to significant patient morbidity and increased treatment costs, particularly in developing countries. This retrospective study, conducted at a tertiary care hospital in Dhaka, Bangladesh, aims to examine the antimicrobial resistance (AMR) patterns of uropathogens and evaluate whether these patterns are influenced by demographic factors such as gender, age, or patient status. Methods: Standard microbiological techniques were used to identify uropathogens, and AMR patterns were determined using the Kirby–Bauer disc diffusion method. Results: Out of 6549 urine samples, 1001 cultures were positive. The infection was more prevalent in females compared to males. The incidence of UTIs in children aged 0–10 years accounted for 12.59% of the total cases, with this age group also exhibiting the highest rate of polymicrobial infections. Among the bacterial uropathogens, 71.19% of isolates were multidrug resistant (MDR) and 84.27% were resistant to at least one antibiotic. Escherichia coli (n = 544, 73.90% MDR) and Klebsiella species (n = 143, 48.95% MDR) were the most common Gram-negative uropathogens, while Enterococcus species (n = 78, 94.87% MDR) was the predominant Gram-positive isolate in this study. Our results indicate that most uropathogens showed resistance against ceftazidime, followed by cefuroxime, trimethoprim-sulfamethoxazole, amoxicillin-clavulanate, and netilmicin. Moderate levels of resistance were observed against ciprofloxacin, levofloxacin, aztreonam, and cefpodoxime. Conclusions: Amikacin was observed to be effective against Gram-negative uropathogens, whereas cefixime was more active against Gram-positive microorganisms, such as Enterococcus species. Moreover, a principal coordinate analysis (PCoA) depicted no significant influence of gender, patient status, or age on AMR patterns. For the continued usefulness of most antibiotics, periodic analysis of the AMR patterns of uropathogens can help assess the rise of MDR bacteria, and therefore guide the selection of appropriate antibiotic treatment strategies.
Mycobacteriophages and Their Applications
Authors: Bonacorsi Andrea , Ferretti Caterina , Di Luca Mariagrazia , Rindi Laura
Published: September 2024

Mycobacterial infections caused by tuberculous and non-tuberculous strains pose significant treatment challenges, especially among immunocompromised patients. Conventional antibiotic therapies often fail due to bacterial resistance, highlighting the need for alternative therapeutic strategies. Mycobacteriophages are emerging as promising candidates for the treatment of mycobacteria. This review comprehensively explores phage isolation, characterization, and clinical applications. Despite the need for more extensive in vitro and in vivo studies, existing evidence shows their efficacy against both sensitive and antibiotic-resistant mycobacterial strains, even under disease-mimicking conditions, particularly when used in cocktails to minimize resistance development. Mycobacteriophages can be engineered and evolved to overcome limitations associated with lysogeny and narrow host range. Furthermore, they exhibit activity in ex vivo and in vivo infection models, successfully targeting mycobacteria residing within macrophages. Delivery methods such as bacterial and liposomal vectors facilitate their entry into human cells. Considering the potential for phage-treatment-induced bacterial resistance, as described in this review, the combination of mycobacteriophages with antibiotics shows efficacy in countering mycobacterial growth, both in the laboratory setting and in animal models. Interestingly, phage-encoded products can potentiate the activity of relevant antibiotics. Finally, the application of phages in different compassionate cases is reported. The positive outcomes indicate that phage therapy represents a promising solution for the treatment of antibiotic-resistant mycobacteria.
The Influence of Processing on the Bioactive Compounds of Small Berries
Authors: Dumitrașcu Loredana , Banu Iuliana , Patraşcu Livia , Vasilean Ina , Aprodu Iuliana
Published: September 2024

Small berries are rich sources of bioactive compounds, acknowledged for a wide variety of biological activities. The health benefits of these berries are primarily attributed to phenolic compounds, such as phenolic acids, flavonoids, and tannins, owing to their good antioxidant capacity, anti-inflammatory, anticancer, and neuro- and cardioprotective properties. In order to compensate for the lack of fresh fruit availability throughout the year, berries are usually processed to obtain various final products. Depending on the processing condition, the nutritional and functional profile of the berries might be affected. The present review focuses on the bioactive compounds with antioxidant activity that contribute to the health-related properties of berries and on the effects of the conventional and alternative thermal and non-thermal techniques employed for processing berries into final products. The literature suggests that, regardless of the processing method, incorporating berries into the daily diet offers protective and preventive benefits against various diseases.
Synthesis of Si-Fe Chondrule-like Dust Analogues in RF Discharge Plasmas
Authors: Baikaliyev Akdaulet , Abdirakhmanov Assan , Orazbayev Sagi , Ussenov Yerbolat , Brodsky Alexander , Aitzhanov Madi , Akhanova Nazym , Dosbolayev Merlan , Gabdullin Maratbek , Ramazanov Tlekkabul , Batryshev Didar
Published: September 2024

Chondrules are tiny particles that occur in stony meteorites and are considered as the building blocks of early asteroids and planets. It is believed that they were formed by the fast heating of the dust in the solar nebula. To date, there is no lab-scale experimental study of the formation of chondrules from the initial gas phase precursors following fast heating and crystallisation. The motivation of this work is a pre-trial study of the formation of chnodrule-like particles. The formation of meteorites in the space environment is associated with the aggregation of small particles or molecular clouds under the influence of shock waves or high-energy gas discharges in the solar nebula. In this work, the properties of product formation at the nanoscale-level were investigated using different feedstock materials which are the dominant elements in the meteorite. The structural and morphological properties of the synthesised Si-Fe nanomaterials were analysed by scanning/transmission electron microscopy (SEM/TEM), and chemical composition was analysed by X-ray energy-dispersive spectroscopy (EDS). The identification of crystalline phases was carried out by X-ray diffraction (XRD), whereas the presence of an Fe-Si system in the synthesised particles was demonstrated by Mössbauer spectroscopy. The obtained materials were exposed to the relatively high-energy pulsed plasma beam on the substrate with the aim to emulate the possible fast heating and melting of the formed nanoparticles. The formation steps of growing synthetic (engineered) chondro-like particles and nanostructures in laboratory conditions is discussed.
A Dual-Template Prompted Mutual Learning Generative Model for Implicit Aspect-Based Sentiment Analysis
Authors: Lei Zhou , Zhang Yawei , Chen Shengbo
Published: September 2024

Generative models have shown excellent results in aspect-based sentiment analysis tasks by predicting quadruples by setting specific template formats. The existing research predicts sentiment elements and enhances the dependency between elements using the multi-template prompting method, but it does not realize the information interaction in the generation process, and it ignores the dependency between the prompt template and the aspect terms and opinion terms in the input sequence. In this paper, we propose a Dual-template Prompted Mutual Learning (DPML) generative model to enhance the information interaction between generation modules. Specifically, this paper designs a dual template based on prompt learning and, at the same time, develops a mutual learning information enhancement module to guide each generated training process to interact with iterative information. Secondly, in the decoding stage, a label marking the interactive learning module is added to share the explicit emotional expression in the sequence, which can enhance the ability of the model to capture implicit emotion. On two public datasets, our model achieves an average improvement of 5.3% and 3.4% in F1 score compared with the previous state-of-the-art model. In the implicit sentiment analysis experiment, the F1 score of the proposed model in the data subset containing implicit words is increased by 2.75% and 3.42%, respectively.
Equivalent Fatigue Constitutive Model Based on Fatigue Damage Evolution of Concrete
Authors: Chen Huating , Sun Zhenyu , Zhang Xianwei , Zhang Wenxue
Published: September 2024

Concrete structures such as bridge decks and road pavements are subjected to repetitive loading and are susceptible to fatigue failure. A simplified stress–strain analysis method that can simulate concrete behavior with a sound physical basis, acceptable prediction precision, and reasonable computation cost is urgently needed to address the critical issue of high-cycle fatigue in structural engineering. An equivalent fatigue constitutive model at discrete loading cycles incorporated into the concrete damaged plasticity model (CDPM) in Abaqus is proposed based on fatigue damage evolution. A damage variable is constructed from maximum fatigue strains, and fatigue damage evolution is described by a general equation whose parameters’ physical meaning and value range are identified. With the descending branch of the monotonic stress–strain curve as the envelope of fatigue residual strength and fatigue damage evolution equation as shape function, fatigue residual strength, residual stiffness, and residual strain are calculated. The equivalent fatigue constitutive model is validated through comparison with experimental data, where satisfactory simulation results were obtained for axial compression and flexural tension fatigue. The model’s novelty lies in integrating the fatigue damage evolution equation with CDPM, explicitly explaining performance degradation caused by fatigue damage. The proposed model could accommodate various forms of concrete constitution and fatigue stress states and has a broad application prospect for fatigue analysis of concrete structures.
Thermography, Temperature, Pressure Force Distribution and Physical Activity in Diabetic Foot: A Systematic Review
Authors: Rosell-Diago Maria P. , Izquierdo-Renau Marta , Julian-Rochina Iván , Arrébola Manel , Miralles Manuel
Published: September 2024

One of the most significant complications of diabetes mellitus is diabetic sensory neuropathy. A reduction in pain perception increases the risk of diabetic patients developing foot ulcers and requiring amputation, which in turn results in impaired mobility and a diminished quality of life. Despite recent advances in our understanding of the aetiology of diabetic foot ulcers (DFUs), there remains a significant gap in the clinical prevention and management of these ulcers. Given that inflammation represents the initial stage in the formation of skin wounds, the utilisation of infrared thermography for the early detection of inflammatory tissue, the analysis of plantar pressures and the monitoring of controlled physical activity (PA) may facilitate the close observation of plantar skin alterations that are susceptible to the development of DFUs, thereby enabling the implementation of timely interventions such as personalised PA for these patients. It is recommended that an integrated approach be adopted which encompasses the utilisation of all emerging technologies in order to enhance outcomes in the prevention and management of DFUs. The aim of this study is to examine the existing literature on the relationship between temperature, pressure and physical activity in the diabetic foot. To this end, a systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format across the PubMed, Scopus and Web of Science databases, with no temporal restriction. A total of 14 studies were included in the review. The use of infrared thermography for the early detection of inflammatory tissue, plantar pressures and the monitoring of controlled PA can facilitate the close monitoring of changes that may pose a risk for the formation of UFDs and provide timely intervention, thereby personalising the PA of the diabetic patient.
Comprehensive Analysis of Teran Red Wine Aroma and Sensory Profiles: Impacts of Maceration Duration, Pre-Fermentation Heating Treatment, and Barrel Aging
Authors: Rossi Sara , Bestulić Ena , Orbanić Fumica , Horvat Ivana , Lukić Igor , Ilak Peršurić Anita Silvana , Bubola Marijan , Plavša Tomislav , Radeka Sanja
Published: September 2024

This study investigates the effect of prolonged maceration, pre-fermentation heating, and barrel aging on the volatile aroma profile and sensory characteristics of Teran wine. The vinification processes included a control treatment (7-day maceration, TM7-Y; Y—young wine), 10-day maceration (TM10-Y), 21-day post-fermentation maceration (TM21-Y), and 48-h pre-fermentation heating at 45 °C followed by 8-day maceration (TPHT-Y). All wines were then aged in oak barrels for six months, resulting in TM7-A, TM10-A, TM21-A, and TPHT-A wines (A—aged wine). Volatile compounds were extracted using headspace solid-phase microextraction (HS-SPME) and analyzed by gas chromatography/mass spectrometry (GC/MS), while sensory profiles were evaluated using quantitative descriptive analysis (QDA). TPHT-Y and TM21-Y treatments reduced several groups of free volatile compounds while enhancing sensory properties, with TM21-Y wines notably exhibiting pronounced dried fruit notes, likely due to high β-damascenone concentrations. Conversely, TM10-Y and TM7-Y treatments resulted in significantly higher concentrations of the most volatile aroma compounds. Aging in oak barrels significantly increased the levels of particular free volatile compounds like C13-norisoprenoids, volatile phenols, furans, and lactones. It also enhanced sensory quality, with fruity aromas prominent across all treatments, and TM21-A and TPHT-A wines showing strong dried fruit, jam, and liqueur notes. This study offers valuable insights into tailoring wine aromas and sensory attributes through specific vinification techniques, contributing to a more refined approach to optimizing wine production. In conclusion, the findings highlight the importance of maceration and aging techniques in developing complex and desirable wine profiles, offering practical guidance for improving Teran wine quality.
TAWC: Text Augmentation with Word Contributions for Imbalance Aspect-Based Sentiment Classification
Authors: Santoso Noviyanti , Mendonça Israel , Aritsugi Masayoshi
Published: September 2024

Text augmentation plays an important role in enhancing the generalizability of language models. However, traditional methods often overlook the unique roles that individual words play in conveying meaning in text and imbalance class distribution, thereby risking suboptimal performance and compromising the model’s generalizability. This limitation motivated us to develop a novel technique called Text Augmentation with Word Contributions (TAWC). Our approach tackles this problem in two core steps: Firstly, it employs analytical correlation and semantic similarity metrics to discern the relationships between words and their associated aspect polarities. Secondly, it tailors distinct augmentation strategies to individual words based on their identified functional contributions in the text. Extensive experiments on two aspect-based sentiment analysis datasets demonstrate that the proposed TAWC model significantly improves the classification performances of popular language models, achieving gains of up to 4% compared with the case of data without augmentation, thereby setting a new standard in the field of text augmentation.
Application of Advanced Process Control to a Continuous Flow Ohmic Heater: A Case Study with Tomato Basil Sauce
Authors: Javed Tasmiyah , Oluwole-ojo Oluwaloba , Howarth Martin , Xu Xu , Rashvand Mahdi , Zhang Hongwei
Published: September 2024

Improving the efficiency and performance of control systems in food processing remains a significant challenge for engineers and researchers. In this paper, Proportional, Integral, and Derivative (PID) control; Model Predictive Control (MPC); and Adaptive Model Predictive Control (AMPC) were implemented on a Continuous Flow Ohmic Heater (CFOH) pilot plant to process tomato basil sauce. The sauce, composed of tomato puree, basil, spices, and other ingredients, was used to assess the effectiveness of these advanced control strategies. This research presents a case study on the pilot-scale heating of tomato basil sauce, with applications in the broader food industry. The performances and energy efficiencies of the different control techniques were compared, demonstrating significant improvements in controlling the CFOH process. The results highlight the industrial practicality of using CFOH technology with advanced process controls for food processing.
YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens
Authors: Li Hongxu , Yuan Wenxia , Xia Yuxin , Wang Zejun , He Junjie , Wang Qiaomei , Zhang Shihao , Li Limei , Yang Fang , Wang Baijuan
Published: September 2024

China’s Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. In external validation, the mAP of the model outperforms other deep learning networks such as Faster-RCNN, SSD, and the original YOLOv8n, with improvements of 14.34%, 8.85%, and 2.18%, respectively. In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science.
Bioactive Peptides from Corn (Zea mays L.) with the Potential to Decrease the Risk of Developing Non-Communicable Chronic Diseases: In Silico Evaluation
Authors: Cagnin Caroline , Garcia Bianca de Fátima , Rocha Thais de Souza , Prudencio Sandra Helena
Published: September 2024

Studies have shown that corn (Zea mays L.) proteins, mainly α-zein, have the potential to act on therapeutic targets related to non-communicable chronic diseases, such as high blood pressure and type 2 diabetes. Enzymatic hydrolysis of proteins present in foods can result in a great diversity of peptides with different structures and possible bioactivities. A review of recent scientific research papers was performed to show evidence of the bioactive properties of corn peptides by in vitro assays. The α-zein amino acid sequences were identified in the UniProtKB protein database and then analyzed in the BIOPEP database to simulate enzymatic digestion and verify the potential biological action of the resulting peptides. The peptides found in the BIOPEP database were categorized according to the probability of presenting biological action using the PeptideRanker database. The aim was to use existing data to identify in silico the potential for obtaining biologically active peptides from α-zein, the main storage protein of corn. The analysis showed that the majority of peptide fragments were related to the inhibition of angiotensin-converting enzyme, followed by the inhibition of dipeptidyl peptidase IV and dipeptidyl peptidase III. Many drugs used to treat high blood pressure and type 2 diabetes work by inhibiting these enzymes, suggesting that corn peptides could be potential alternative agents. In vitro studies found that the primary bioactivity observed was antioxidative action. Both in vitro and in silico approaches are valuable for evaluating the bioactive properties resulting from protein hydrolysis, such as those found in α-zein. However, conducting in vitro studies based on prior in silico evaluation can be more efficient and cost-effective.
PMSFF: Improved Protein Binding Residues Prediction through Multi-Scale Sequence-Based Feature Fusion Strategy
Authors: Li Yuguang , Nan Xiaofei , Zhang Shoutao , Zhou Qinglei , Lu Shuai , Tian Zhen
Published: September 2024

Proteins perform different biological functions through binding with various molecules which are mediated by a few key residues and accurate prediction of such protein binding residues (PBRs) is crucial for understanding cellular processes and for designing new drugs. Many computational prediction approaches have been proposed to identify PBRs with sequence-based features. However, these approaches face two main challenges: (1) these methods only concatenate residue feature vectors with a simple sliding window strategy, and (2) it is challenging to find a uniform sliding window size suitable for learning embeddings across different types of PBRs. In this study, we propose one novel framework that could apply multiple types of PBRs Prediciton task through Multi-scale Sequence-based Feature Fusion (PMSFF) strategy. Firstly, PMSFF employs a pre-trained language model named ProtT5, to encode amino acid residues in protein sequences. Then, it generates multi-scale residue embeddings by applying multi-size windows to capture effective neighboring residues and multi-size kernels to learn information across different scales. Additionally, the proposed model treats protein sequences as sentences, employing a bidirectional GRU to learn global context. We also collect benchmark datasets encompassing various PBRs types and evaluate our PMSFF approach to these datasets. Compared with state-of-the-art methods, PMSFF demonstrates superior performance on most PBRs prediction tasks.
Advancement in Soft Hydrogel Grippers: Comprehensive Insights into Materials, Fabrication Strategies, Grasping Mechanism, and Applications
Authors: Dong Xiaoxiao , Wang Chen , Song Haoxin , Shao Jinqiang , Lan Guiyao , Zhang Jiaming , Li Xiangkun , Li Ming
Published: September 2024

Soft hydrogel grippers have attracted considerable attention due to their flexible/elastic bodies, stimuli-responsive grasping and releasing capacity, and novel applications in specific task fields. To create soft hydrogel grippers with robust grasping of various types of objects, high load capability, fast grab response, and long-time service life, researchers delve deeper into hydrogel materials, fabrication strategies, and underlying actuation mechanisms. This article provides a systematic overview of hydrogel materials used in soft grippers, focusing on materials composition, chemical functional groups, and characteristics and the strategies for integrating these responsive hydrogel materials into soft grippers, including one-step polymerization, additive manufacturing, and structural modification are reviewed in detail. Moreover, ongoing research about actuating mechanisms (e.g., thermal/electrical/magnetic/chemical) and grasping applications of soft hydrogel grippers is summarized. Some remaining challenges and future perspectives in soft hydrogel grippers are also provided. This work highlights the recent advances of soft hydrogel grippers, which provides useful insights into the development of the new generation of functional soft hydrogel grippers.
Reactive Astrocytosis—A Potential Contributor to Increased Suicide in Long COVID-19 Patients?
Authors: Costanza Alessandra , Amerio Andrea , Aguglia Andrea , Rossi Martina , Parise Alberto , Magnani Luca , Serafini Gianluca , Amore Mario , Martins Daniel , Nguyen Khoa D.
Published: September 2024

Background: Long COVID-19 is an emerging chronic illness of significant public health concern due to a myriad of neuropsychiatric sequelae, including increased suicidal ideation (SI) and behavior (SB). Methods: This review provides a concise synthesis of clinical evidence that points toward the dysfunction of astrocytes, the most abundant glial cell type in the central nervous system, as a potential shared pathology between SI/SB and COVID-19. Results: Depression, a suicide risk factor, and SI/SB were both associated with reduced frequencies of various astrocyte subsets and complex proteomic/transcriptional changes of astrocyte-related markers in a brain-region-specific manner. Astrocyte-related circulating markers were increased in depressed subjects and, to a less consistent extent, in COVID-19 patients. Furthermore, reactive astrocytosis was observed in subjects with SI/SB and those with COVID-19. Conclusions: Astrocyte dysfunctions occurred in depression, SI/SB, and COVID-19. Reactive-astrocyte-mediated loss of the blood–brain barrier (BBB) integrity and subsequent neuroinflammation—a factor previously linked to SI/SB development—might contribute to increased suicide in individuals with long COVID-19. As such, the formulation of new therapeutic strategies to restore astrocyte homeostasis, enhance BBB integrity, and mitigate neuroinflammation may reduce SI/SB-associated neuropsychiatric manifestations among long COVID-19 patients.
Physical Exercise and Mechanism Related to Alzheimer’s Disease: Is Gut–Brain Axis Involved?
Authors: Sanchez-Martinez Javier , Solis-Urra Patricio , Olivares-Arancibia Jorge , Plaza-Diaz Julio
Published: September 2024

Background: Alzheimer’s disease is a progressive neurodegenerative disease characterized by structural changes in the brain, including hippocampal atrophy, cortical thinning, amyloid plaques, and tau tangles. Due to the aging of the global population, the burden of Alzheimer’s disease is expected to increase, making the exploration of non-pharmacological interventions, such as physical exercise, an urgent priority. Results: There is emerging evidence that regular physical exercise may mitigate the structural and functional declines associated with Alzheimer’s disease. The underlying mechanisms, however, remain poorly understood. Gut–brain axis research is a promising area for further investigation. This system involves bidirectional communication between the gut microbiome and the brain. According to recent studies, the gut microbiome may influence brain health through modulating neuroinflammation, producing neuroactive compounds, and altering metabolic processes. Exercise has been shown to alter the composition of the gut microbiome, potentially impacting brain structure and function. In this review, we aim to synthesize current research on the relationship between physical exercise, structural brain changes in Alzheimer’s disease, and the gut–brain axis. Conclusions: In this study, we will investigate whether changes in the gut microbiome induced by physical exercise can mediate its neuroprotective effects, offering new insights into the prevention and treatment of Alzheimer’s disease. By integrating findings from neuroimaging studies, clinical trials, and microbiome research, this review will highlight potential mechanisms. It will also identify key gaps in the literature. This will pave the way for future research directions.
Resveratrol and Exercise Produce Recovered Ankle and Metatarsus Joint Movements after Penetrating Lesion in Hippocampus in Male Rats
Authors: Aguilar-Garcia Irene Guadalupe , Alpirez Jonatan , Castañeda-Arellano Rolando , Dueñas-Jiménez Judith Marcela , Toro Castillo Carmen , León-Moreno Lilia Carolina , Osuna-Carrasco Laura Paulina , Dueñas-Jiménez Sergio Horacio
Published: September 2024

Introduction: This study investigates how traumatic injuries alter joint movements in the ankle and foot. We used a brain injury model in rats, focusing on the hippocampus between the CA1 and dentate gyrus. Materials and Methods: We assessed the dissimilarity factor (DF) and vertical displacement (VD) of the ankle and metatarsus joints before and after the hippocampal lesion. We analyzed joint movements in rats after the injury or in rats treated with resveratrol, exercise, or a combination of both. Results: Resveratrol facilitated the recovery of DF in both legs, showing improvements in the ankle and metatarsus joints on the third and seventh days post-injury. The hippocampal lesion affected VD in both legs, observed on the third or seventh day after the injury. Both exercise and resveratrol partially recovered VD in the ankle and metatarsus joints on these days. These effects may be linked to increased hippocampal neurogenesis and reduced neuroinflammation. Conclusions: The study highlights the benefits of resveratrol and exercise in motor recovery following brain injury, suggesting their potential to enhance the quality of life for patients with neurological disorders affecting motor function and locomotion. These findings also suggest that resveratrol could offer a promising or complementary alternative in managing chronic pain and inflammation associated with orthopedic conditions, thus improving overall patient management.
Perception Matters: The Influence of School Ethnic Racial Context on Ethnic Racial Identity Development for Black Adolescents
Authors: Saafir Amirah , Graham Sandra
Published: September 2024

In the current study, latent growth curve modeling is used to explore growth in ethnic–racial identity (ERI) commitment from 9th to 12th grade as a function of two aspects of the school ethnic–racial environment—perceived representation among peers and perceived discrimination from peers. The participants included 237 students that self-identified as African American (Mage = 14.7; 50% female). The results showed that perceiving more Black peers at school buffered the negative impact of racial discrimination from peers on ERI commitment. Further, the positive impact of perceived representation remained significant even after controlling for other markers of school ethnic–racial context including objective representation and school ethnic–racial diversity. The findings have implications for the environmental factors that support ERI development as well as how we study and conceptualize the influence of the school ethnic–racial environment.
Alcohol Abuse and Physical Violence towards a Partner: How Can We Attenuate the Relationship? A Study on Emotional Dysregulation in Adolescents
Authors: Peñacoba Cecilia , Balandin Alejandro , Estévez Ana , Olave Leticia , Momeñe Janire , Chávez-Vera María Dolores , Muñiz José Antonio , Iruarrizaga Itziar
Published: September 2024

Background: The previous literature has revealed the relationship between alcohol abuse and violent behaviours; however, the results are not always conclusive, highlighting the need to explore other variables that allow us to establish risk profiles. Aim: The goal is to examine whether the relation between alcohol abuse and physical violence towards a partner can be influenced (moderate) by difficulties in emotional regulation. Setting: A public high school in Manabí (Ecuador). Participants: A total of 1519 high school students with ages between 14 and 18 years (mean = 15.77, SD = 1.22), with 54% (n = 820) being male. Main Outcome Measures: The measures we observed were alcohol abuse (i.e., frequency of alcohol abuse in the past 30 days), physical violence exercised towards a partner (Violence Received, Exercised and Perceived in Dating Relationships of Young People and Adolescents) and emotional dysregulation (Difficulties in Emotional Regulation Scale; DERS). Results: It is observed that there exists significantly higher alcohol abuse in males, regardless of their age, as well as more physical violence by adolescent males towards their partners. Direct effects of alcohol abuse on physical intimate partner violence are observed in males from the age of 16 and in females from the age of 14. Moreover, the direct effects of different emotional dysregulation strategies on physical violence depend on gender. Conclusion: The moderating effects of emotional dysregulation strategies between alcohol abuse and physical intimate partner violence are observed only in the case of adolescent females (16–17 years). In particular, emotional dysregulation variables such as non-awareness, impulse, nonacceptance, or lack of strategies interfere as moderators in the relationship between excessive alcohol abuse and physical violence towards a partner. In the case of non-awareness, contrary to the other three, when scores are low or moderate, a statistically significant relationship between alcohol abuse and violence is observed.
Substitution of Sand in Concrete Blocks with Coconut Fiber and Cattle Manure: Effects on Compressive Strength and Thermal Conductivity
Authors: González Yahir , Miranda-Cantillo Cesar , Quintero-Torres Jason , Rhenals-Julio Jesús D. , Jaramillo Andrés F. , Cabello-Eras Juan José
Published: September 2024

Improving the energy performance of buildings is critical in the construction sector. This study investigates the effects of incorporating coconut mesocarp fibers (F = Fiber) and bovine manure (M = Manure) on the thermal conductivity and compressive strength of concrete blocks. Bovine manure and coconut fiber replaced the block sand at maximum concentrations of 10 and 1.5%, respectively. Thermal conductivities were measured according to the ASTM C177 (2013) standard, compression tests were performed using the ASTM C140 standard, and characterization assays such as Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were performed to determine the morphological properties of the final material and its constituents. The results showed a 50% reduction in the thermal conductivity coefficient of the blocks when 10 and 1.5% of the sand was replaced with manure and coconut fiber, respectively. Similarly, incorporating coconut fiber at percentages of 0.5, 1, and 1.5% improved compressive strength results. Blocks comprising 0.5, 1, and 1.5% fiber or a mix of 3% manure and 1.5% fiber attained the compressive strength requirements established by the standard. This study demonstrated the feasibility of using coconut fiber mixed with cattle manure as a substitute for up to 2.5% of the sand in non-structural wall elements manufacturing, attaining a decrease in thermal conductibility of around 10%.
A Bibliometric Review of Chinese Traditional Defensive Settlement Heritage
Authors: Lin Xiuhong , Zhang Yukun , Wu Yilin , Yang Yingqian , Yang Wenjing
Published: September 2024

Unlike residential settlements, Chinese traditional defensive settlements (CTDS) are fortress-shaped settlements built by forefathers to resist invasion and defend their homeland. What remains of these settlements today are not only unique defensive entities but also defensive spatial layouts and architectural techniques that reflect military defense strategies and spatial patterns of ancient Chinese society, resulting in a distinct cultural heritage. Using CiteSpace as a research tool and CNKI as a core database, this paper conducts a visual analysis and review of the research related to CTDS, aiming to accurately and intuitively elaborate on the literature distribution characteristics, collaborative characteristics, key issues, research trends, and research hotspots. We found that research on CTDS focuses on three key issues: the composition system and defense mode of northern defensive settlements, the architectural style and cultural characteristics of southern defensive dwellings, and the settlements’ heritage conservation and development planning; and research trends can be divided into three phases. We also propose five future research recommendations. This study helps to fill the gap in the bibliometric review of Chinese traditional defensive settlements, serves as a reference for future priority research directions, and provides a manual for heritage conservation and sustainable development of this special type of settlement.