bluuebunny/crossref_metadata_2025 huggingface dataset:
GFS-YOLO11: A Maturity Detection Model for Multi-Variety Tomato
Authors: Wei Jinfan , Ni Lingyun , Luo Lan , Chen Mengchao , You Minghui , Sun Yu , Hu Tianli
Published: November 2024

In order to solve the problems that existing tomato maturity detection methods struggle to take into account both common tomato and cherry tomato varieties in complex field environments (such as light change, occlusion, and fruit overlap) and the model size being too large, this paper proposes a lightweight tomato maturity detection model based on improved YOLO11, named GFS-YOLO11. In order to achieve a lightweight network, we propose the C3k2_Ghost module to replace the C3K2 module in the original network, which can ensure a feature extraction capability and reduce model computation. In order to compensate for the potential feature loss caused by the light weight, this paper proposes a feature-refining module (FRM). After embedding each feature extraction module in the trunk network, it improves the feature expression ability of common tomato and cherry tomato in complex field environments by means of depth-separable convolution, multi-scale pooling, and channel attention and spatial attention mechanisms. In addition, in order to further improve the detection ability of the model for tomatoes of different sizes, the SPPFELAN module is also proposed in this paper. In combining the advantages of SPPF and ELAN, multiple parallel SPPF branches are used to extract features of different levels and perform splicing and fusion. To verify the validity of the method, this study constructed a dataset of 1061 images of common and cherry tomatoes, covering tomatoes in six ripened categories. The experimental results show that the performance of the GFS-YOLO11 model is significantly improved compared with the original model; the P, R, mAP50, and MAP50-95 increased by 5.8%, 4.9%, 6.2%, and 5.5%, respectively, and the number of parameters and calculation amount were reduced by 35.9% and 22.5%, respectively. The GFS-YOLO11 model is lightweight while maintaining high precision, can effectively cope with complex field environments, and more conveniently meet the needs of real-time maturity detection of common tomatoes and cherry tomatoes.
Early Sweet Potato Plant Detection Method Based on YOLOv8s (ESPPD-YOLO): A Model for Early Sweet Potato Plant Detection in a Complex Field Environment
Authors: Xu Kang , Sun Wenbin , Chen Dongquan , Qing Yiren , Xing Jiejie , Yang Ranbing
Published: November 2024

Traditional methods of pest control for sweet potatoes cause the waste of pesticides and land pollution, but the target detection algorithm based on deep learning can control the precise spraying of pesticides on sweet potato plants and prevent most pesticides from entering the land. Aiming at the problems of low detection accuracy of sweet potato plants and the complex of target detection models in natural environments, an improved algorithm based on YOLOv8s is proposed, which can accurately identify early sweet potato plants. First, this method uses an efficient network model to enhance the information flow in the channel, obtain more effective global features in the high-level semantic structure, and reduce model parameters and computational complexity. Then, cross-scale feature fusion and the general efficient aggregation architecture are used to further enhance the network feature extraction capability. Finally, the loss function is replaced with InnerFocaler-IoU (IFIoU) to improve the convergence speed and robustness of the model. Experimental results showed that the mAP0.5 and model size of the improved network reached 96.3% and 7.6 MB. Compared with the YOLOv8s baseline network, the number of parameters was reduced by 67.8%, the amount of computation was reduced by 53.1%, and the mAP0.5:0.95 increased by 3.5%. The improved algorithm has higher detection accuracy and a lower parameter and calculation amount. This method realizes the accurate detection of sweet potato plants in the natural environment and provides technical support and guidance for reducing pesticide waste and pesticide pollution.
Detection of Candidate Genes and Development of KASP Markers for Pod Length and Pod Width by Combining Genome-Wide Association and Transcriptome Sequencing in Vegetable Soybean
Authors: Dai Dongqing , Huang Lu , Zhang Xiaoyan , Liu Jinyang , Zhang Shiqi , Yuan Xingxing , Chen Xin , Xue Chenchen
Published: November 2024

Vegetable soybeans are one of the most important vegetable types in East Asia. The yield of vegetable soybeans is considerably influenced by the size of their pods. To facilitate the understanding of the genetic basis of the pod length and width in vegetable soybeans, we conducted a genome-wide association study (GWAS) and transcriptome sequencing. Four quantitative trait loci, namely, qGPoL1, qGPoL2, qGPoW1, and qGPoW2, were mapped via GWAS analysis. Through the integration of gene function annotation, transcriptome sequencing, and expression pattern analysis, we identified Glyma.06G255000 and Glyma.13G007000 as the key determinants of the pod length and width in vegetable soybeans, respectively. Furthermore, two kompetitive allele-specific polymerase chain reaction (KASP) markers, namely, S06-42138365 (A/T) and S13_628331 (A/T), were developed and effectively validated in 27 vegetable soybean accessions. Overall, our research identified genes that regulate the pod length and width and determined KASP markers for molecular marker-assisted selection breeding. These findings have crucial implications for the improvement of soybean crops and can contribute to the development of efficient breeding strategies.
Effects of Exercise on Urinary Parameters and Proteins in Well-Trained Canicross Dogs: A Preliminary Study
Authors: Spinella Giuseppe , Valentini Simona , Dalmonte Thomas , Isani Gloria , Andreani Giulia
Published: November 2024

The aim of the present study was to investigate the effects of exercise during canicross competition on urinary biochemical parameters and urinary proteins. Our results showed that, among the parameters analysed in routine urinalysis, pH was affected by exercise and albuminuria also showed changes immediately after physical exercise with a return to baseline within 2 h after the physical activity. In particular, SDS-PAGE electrophoresis allowed the separation of the urinary proteins on the basis of their molecular mass allowing a qualitative evaluation of the urinary proteome and a quantitative analysis of urine albumin and uromodulin, with a significant increase in urinary albumin and a decrease in uromodulin after exercise. In this study, urine was collected by spontaneous voiding and the use of this non-invasive sampling method proved useful in obtaining information on the health of the animals in the immediate moments before and after the competition without increasing the stress of the animals involved in the competition by any visits or invasive manipulations by veterinarians.
Exploring Factors That Influence Public Engagement of Adoptable Pets on Facebook
Authors: Morrison Rachel , Maust-Mohl Maria , Ferry Tracy
Published: November 2024

Recent statistics suggest that the percentage of animals adopted from shelters or rescue organizations is lower than expected, especially given the number of animals available for adoption. To help increase adoption rates, animal shelters often advertise adoptable animals on webpages and social media. However, little research has examined what information may be more successful in increasing engagement and interest in the animals to ultimately lead to adoption. This exploratory study examined posts of adoptable animals on Facebook pages of 13 different animal shelters in the US to better understand how post content, such as pictures or videos, type/sex of animal, and the environment the animals are depicted in, may influence public engagement. We also sought to examine if there was a difference between posts in 2019 (pre-pandemic) compared to 2020 (pandemic). The findings suggest that posts on social media can successfully promote animals available for adoption, but the type of animal (dog vs. cat) and environment (e.g., home vs. other) can influence the likes and shares of the posts. In addition, the COVID-19 pandemic and a shift to more online activity may have influenced engagement; posts from Fall 2019 had more likes, while posts in Fall 2020 had more shares. Future research should continue to look for trends in the content of posts, as well as content shared on other social media outlets, to provide further clarification about how these posts influence adoptions.
Dosing of Bacterial Phytase (EC 3.1.3.26) in Laying Hens’ Diets
Authors: Lima Guilherme Souza , Cavalcante Danilo Teixeira , Guerra Ricardo Romão , Vilar da Silva José Humberto , de Brito Alexandre Barbosa , Gomes Gilson Alexandre , Ramalho Lima Matheus , Assunção Marcos Aurélio Victor de , do Nascimento Carlos Henrique , de Lima Adiel Vieira , Lopes de Souza Paloma Eduarda , Perazzo Costa Fernando
Published: November 2024

Despite the acknowledged advancements in the utilization of phytase dosing, limited research has been conducted on commercial laying hens. To assess the effectiveness of doses of exogenous phytase, a total of 320 laying hens aged between 44 and 64 weeks were utilized. These hens were divided into five treatments, which were then distributed using a completely randomized design with eight replicates, each containing eight birds. The treatments consisted of phytase supplementation levels of 0, 500, 1000, 1500, and 3000 FTU/kg. Quadratic regression equations were utilized to determine the maximum and minimum values for the levels of phytase supplementation. A significant difference was observed in the levels of phytase supplementation, where a quadratic model was fitted to various variables including egg weight (g), egg mass (g/bird/day), feed conversion per egg mass (g/g), yolk concentration (%), albumen concentration (%), shell thickness (μm), shell strength (kgf), specific gravity, and yolk color. Further, an increased supplementation improved the digestive tract of the hens, thereby providing a better villus–crypt ratio. Considering the advantageous effects of phytase dosing, it is recommended to supplement corn and soybean meal-based diets with 1500 FTU/kg of bacterial phytase for laying hens during the 44- to 64-week production period.
Study on the Swimming Behavior of Black Carp (Mylopharyngodon piceus) and Silver Carp (Hypophthalmichthys molitrix) in Early Developmental Stage
Authors: Tan Junjun , Zhu Xueqin , Sun Junjian , Wang Yuanyang , Zhang Hongqing , Ke Senfan , Kattel Giri Raj , Shi Xiaotao
Published: November 2024

Fish need to make different responses to different water flow conditions, as a variety of fish utilize or overcome the water flow while fish are in the water. This study aims to analyze the response of two types of carp (black carp and silver carp) to water flow in different body lengths (2.0–10.0 cm) in early developmental stages in an open channel. By analyzing the water velocity and fish swimming behavior, swimming against the water flow was the most frequent swimming behavior, and the frequencies of this behavior increased with the increased body length of fish. The results demonstrated that the detectable water velocity of two carp species of different body lengths remained in a certain range (0.020–0.060 m/s). Black carp and silver carp can swim against the water flow of 0.295–0.790 m/s and 0.245–0.825 m/s, respectively. The results of this study can provide invaluable data for engineers and biologists to protect fish in the early developmental stage and restore the ecological habitats in the regulated river systems.
Use of CLEANED to Assess the Productive, Environmental, and Economic Impact of Dairy Farms in the Peruvian Amazon
Authors: Oré Linda , Romero Gelver , Souza de Abreu Maria H. , Velarde-Guillén José , Arango Jacobo , Ku-Vera Juan Carlos , Gómez Carlos
Published: November 2024

Dairy farms in developing countries are key to fighting hunger and poverty. However, their environmental and economic impact in the tropical region of Peru has been scarcely studied. The CLEANED tool, developed by the Alliance of Bioversity International and the International Center for Tropical Agriculture, allows us to assess the productive situation and the environmental and economic impact of different dairy systems. The objective of the study was to use the CLEANED tool to evaluate the production, environmental, and economic impacts of extensive and semi-intensive dairy systems in the tropical region of Peru. Data from twelve dairy farms (six extensive and six semi-intensive systems), in two seasons (rainy and dry) were recorded using semi-structured surveys. The required area (ha/year), production (L milk/ha/year), environmental impact (water use in m3/product), and methane (CH4) and nitrous oxide (N2O) emissions in kg CO2eq/kg fat- and protein-corrected milk (FPCM) were estimated, and the economic analysis was performed for each livestock system. Results showed that the required area was of 28.9 and 32.6 ha, milk yield was 382 and 1254 L/ha/year, water use was 0.59 and 0.29 m3/kg FPCM, CH4 emissions were 1.7 and 1.0 kg CO2eq/kg FPCM, and N2O emissions were 0.22 and 0.17 kg CO2eq/kg FPCM, for the extensive and semi-intensive systems, respectively. The study revealed significant positive differences in semi-intensive livestock systems, including increased productivity, the reduced intensity of CH4 and N2O emissions, and greater profitability.
Development of Germ Cell Isolation and Optimal Cryopreservation Method for Lissachatina fulica (L. fulica)
Authors: Jeong Jukyeong , Lee Seungki , Choi Jung Kyu
Published: November 2024

This study aims to develop an optimized method for cryopreserving the germ cells of Lissachatina fulica (L. fulica) using vitrification, as an alternative approach for conserving endangered snail species. First, we isolated several key reproductive organs, including the sperm oviduct, albumen gland, hermaphrodite gland (ovotestis), and hermaphrodite duct from L. fulica. When the ovotestis was finely chopped, numerous sperm with long tails and distinct heads were observed. The staining of sperm nuclei was confirmed using Hoechst 33342 dye. Since the hermaphrodite gland, referred to as the ovotestis, contains both male and female germ cells, we performed tissue staining on the ovotestis using hematoxylin and eosin (H&E) dye. H&E staining of the ovotestis revealed numerous oval-shaped acini containing sperm and early germ cells. Spermatocytes and spermatids were observed within distinct boundaries, with mature sperm appearing following spermatogenesis. To preserve the species of the L. fulica, we introduced vitrification technology to cryopreserve its reproductive organs. The non-vitrification group showed an average cell viability of 96.6%, while the vitrification group had 86.8% after thawing. This study presents a reliable cryopreservation protocol for L. fulica, with potential applications for other endangered snails, supporting conservation efforts to preserve genetic resources and biodiversity.
A Point Prevalence Survey of Antimicrobial Use in Second-Level Mexican Hospitals: A Multicenter Study
Authors: Venegas-Esquivel German Alberto , Berumen-Lechuga María Guadalupe , Molina-Pérez Carlos José , Jimenez-Juarez Rodolfo Norberto , Villanueva-Cabrera Enna Guadalupe , Vargas-González David , Santos-González Gonzalo , Velázquez Pérez Rebeca Pamela , Hernández Navarrete Mariana , Corral-Rico Celene , Robles-Ordoñez Natali , Lara-Hernández Juan Manuel , Sánchez Mendoza Helen’s Irais
Published: November 2024

In 2018, the WHO published a methodology for conducting a point prevalence survey (PPS) of antibiotic use in hospitals. The aim of this study is to report the use of antibiotics in six second-level hospitals in Mexico using this methodology. Methods: A multicenter cross-sectional study based on the 2021–2023 adaptation for Latin American hospitals was conducted in internal medicine, surgery, intensive care unit (ICU), obstetrics and gynecology and pediatrics departments of the IMSS in the western region of the state of Mexico. Results: The overall prevalence of antibiotic use was 61%; the services with the highest prevalence of prescription were general surgery (79%) and the ICU (78%). A total of 846 patients were surveyed; there were no differences in antibiotic use or non-use in terms of gender, surgical procedure and invasive devices, but there were differences in median age and comorbidities. Adherence to guidelines was 53.9%. The three main antibiotics used were third-generation cephalosporins (28%), carbapenems (13%) and glycopeptides (9%); for the type of indication, for CAI and prophylaxis, the rates of use of third-generation cephalosporins were 29.2% and 44.5%, respectively, while for healthcare-associated infections, carbapenems were used (23.9%). By AWaRe group, the watch group was predominant for all types (63.9%), for prophylaxis it was the access group (39.3%), and for HAIs it was the reserve group (4.9%).
Hatching Egg Sanitizers Based on Essential Oils: Microbiological Parameters, Hatchability, and Poultry Health
Authors: Oliveira Gabriel da Silva , McManus Concepta , Santos Pedro Henrique Gomes de Sá , de Sousa Davi Emanuel Ribeiro , Jivago José Luiz de Paula Rôlo , de Castro Márcio Botelho , dos Santos Vinícius Machado
Published: November 2024

Background: Eggshell contamination threatens the viability of hatching eggs. This contamination can be caused by harmless, opportunistic, or pathogenic bacteria. Although necessary, the use of synthetic antibiotics to treat eggshells can present several significant problems: They can be toxic and damage the shell, and, most worryingly, they can lead to bacterial resistance. Faced with these challenges, the objective of this research was to create and test a sanitizing plan for hatching eggs using essential oils derived from Citrus aurantifolia (CAEO), Ocimum basilicum (OBEO), or Allium sativum (ASEO). Methods: Sanitizing solutions containing specific concentrations of these essential oils were prepared, and their antimicrobial properties and contributions to poultry safety and hatching parameters were investigated. Results: The bacterial load was reduced in eggshells sanitized with essential oils, and the degree of bacterial inhibition, along with their safety profile, may be directly related to optimal hatchability rates, lower incidences of contaminated dead embryos, and the hatching of healthy chicks. Conclusions: Together, these results reinforce the importance of essential oils in the development of effective and safe treatments for managing hatching eggs.
Understanding the Determinants Influencing Self-Medication with Antibiotics Among Malaysian Residents: A Qualitative Study to Inform Preventive Public Health Strategies
Authors: Aslam Adeel , Jamshed Shazia , Zin Che Suraya , Rahman Norny Syafinaz Ab , Ahmed Syed Imran , Szabó Zita Lívia , Gajdács Márió
Published: November 2024

Introduction: Self-medication with antibiotics (SMA)—the use of these drugs without a physician’s diagnosis, supervision, or a medical prescription—has emerged as a significant crisis in many societies, being a particular concern in low- and middle-income countries. SMA practices hinder global efforts to reduce antibiotic consumption in the human health sector and to control antimicrobial resistance (AMR). The aims of the study were to explore the motivations, perspectives, and personal experiences of the Malaysian population related to SMA, analyzing their subjective viewpoints, attitudes, and behaviors. Methods: The present qualitative study applied an interpretivism paradigm to explore the complex topic of SMA; the interview questions were developed and confirmed by experts in AMR and pharmacy practice. Qualitative data analysis was carried out through a thematic approach. Results: Out of twenty-seven (n = 27) eligible individuals, eleven (n = 11) agreed to participate in in-depth interviews. Three main themes and seven subthemes were identified. Participants revealed directly purchasing antibiotics from pharmacies, due to doctors prescribing similar medications for comparable illnesses in the past. Trust issues related to physicians prescribing unnecessary additional medications and suspected personal motives were revealed. Budgetary constraints, timesaving, and aspects of self-care were identified as some of the key drivers for SMA. Conclusions: The current study’s findings contribute to the understanding of the complexities surrounding SMA and provides insights into the public perceptions and behaviors regarding unregulated antibiotic use in Malaysia. Understanding these dynamics may inform targeted public health interventions to address SMA to mitigate the development of AMR.
Comprehensive Study of Antibiotic Resistance in Enterococcus spp.: Comparison of Influents and Effluents of Wastewater Treatment Plants
Authors: Park Ji-Hyun , Bae Kyung-Seon , Kang Jihyun , Park Eung-Roh , Yoon Jeong-Ki
Published: November 2024

Background/Objectives: The spread of antibiotic resistance, particularly through Enterococcus spp., in wastewater treatment plants (WWTPs) poses significant public health risks. Given that research on antibiotic-resistant enterococci and their antibiotic-resistance genes in aquatic environments is limited, we evaluated the role of Enterococcus spp. in WWTPs by comparing the antibiotic resistance rates, gene prevalence, biofilm formation, and residual antibiotics in the influent and effluent using culture-based methods. Methods: In 2022, influent and effluent samples were collected from 11 WWTPs in South Korea. Overall, 804 Enterococcus strains were isolated, and their resistance to 16 antibiotics was assessed using the microdilution method. Results: High resistance to tetracycline, ciprofloxacin, kanamycin, and erythromycin was observed. However, no significant differences in the overall resistance rates and biofilm formation were observed between the influent and effluent. Rates of resistance to ampicillin, ciprofloxacin, and gentamicin, as well as the prevalence of the tetM and qnrS genes, increased in the effluent, whereas resistance rates to chloramphenicol, florfenicol, erythromycin, and tylosin tartrate, along with the prevalence of the optrA gene, decreased. E. faecium, E. hirae, and E. faecalis were the dominant species, with E. faecalis exhibiting the highest resistance. Conclusions: Our results suggest that WWTPs do not effectively reduce the rates of resistant Enterococcus spp., indicating the need for continuous monitoring and improvement of the treatment process to mitigate the environmental release of antibiotic-resistant bacteria.
Placental Extracts, Proteins, and Hydrolyzed Proteins as Active Ingredients in Cosmetic Preparations for Hair Loss: A Systematic Review of Available Clinical Evidence
Authors: Szendzielorz Ewelina , Spiewak Radoslaw
Published: November 2024

Placentae and their derivatives have been used in both traditional and modern medicine, as well as in cosmetic sciences. Although hair loss is frequently mentioned among problems for which the placenta is supposed to be a remedy, the evidence seems rather scarce. The aim of this study was to highlight the clinical evidence for the efficacy of placenta products against baldness and hair loss. Methods: This systematic review was performed according to PRISMA and PICO guidelines. Database searches were conducted in PubMed, Google Scholar and Scopus. Results: Among the 2922 articles retrieved by the query, only 3 previously published clinical trials on placental products were identified. One study was a randomized controlled trial, in which the efficacy of a bovine placenta hair tonic was found to be comparable to that of minoxidil 2% in women with androgenic alopecia. Another controlled study showed that a porcine placenta extract significantly accelerated the regrowth of shaved hair in healthy people. The third study was an uncontrolled trial of a hair shampoo and tonic containing equine placental growth factor in women with postpartum telogen effluvium with unclear and difficult-to-interpret results. Due to the design and methodology of these studies, the level of evidence as assessed with the GRADE method was low for the first study and very low for the other two. Conclusions: The very limited scientific evidence available to date appears, overall, to indicate the efficacy of placental products in both inhibiting hair loss and stimulating hair growth. Unfortunately, the number of clinical studies published to date is very limited. Further, carefully designed, randomized controlled trials of well-defined placental products are needed to definitively address the question of the value of the placenta and its derivatives in hair loss.
Modeling Borehole Resistivity Logs with Exponentially Graded Multilayered Soil Inversion for Electrical Engineering Applications
Authors: Paramo Ricardo , Faleiro Eduardo , Moreno Jorge , Asensio Gabriel
Published: November 2024

In this paper, we present the application of a special soil resistivity model, the Exponentially Graded Multilayered Soil model, to the interpretation of Borehole Resistivity Logging surveys. The model, which was recently introduced by the authors, offers an alternative to the interpretation provided by constant resistivity layer models. The model is applied to synthetic soil surveys as well as to a real survey that is not satisfactorily interpreted using conventional models. This model aids in the design and calculation of grounding systems in electrical engineering, providing an alternative to calculations performed by traditional layered models.
Evaluation of Hazelnut Cake Flour for Use as a Milk Powder Replacer in Ice Cream
Authors: Lučan Čolić Mirela , Jozinović Antun , Lukinac Jasmina , Jukić Marko , Antunović Martina
Published: November 2024

Hazelnut oil cake, a by-product in the cold-pressing of hazelnut oil, is a rich in valuable nutrients, which makes it a promising option for supplementation or as a raw material in the development of functional products. The aim of this work was to study the influence of partial or complete replacing of skim milk powder (SMP) with hazelnut press cake flour (HPCF) in varying ratios (0%, 25%, 50%, 75%, and 100%) on the physicochemical properties and sensory attributes of milk ice cream. The replacement modified the chemical composition of the ice cream mixture, resulting in a reduction (p < 0.05) of milk solids non-fat (MSNF), protein, and carbohydrates content, while simultaneously elevating the hazelnut content, and total fat content. This modification influenced the rheological characteristics of the ice cream mixtures, leading to an increase in the consistency coefficient from 1.32 to 7.66 Pa sn. Furthermore, a decline in overrun values (from 26.99% to 15.85%), an increase in hardness (from 6881.71 to 23,829.30 g), retarded melting properties, and variations in colour attributes were observed with higher concentrations of HPCF. In the sensory evaluation test, it was found that consumer acceptance was enhanced for the samples with partial substitution of SMP when compared to standard milk ice cream. The findings suggest that a replacement of milk powder with hazelnut cake by up to 75% is achievable, in order to obtain functional ice cream with adequate physicochemical and sensorial qualities.
A Two-Individual-Based Evolutionary Algorithm for Flexible Assembly Job Shop Scheduling Problem with Uncertain Interval Processing Times
Authors: Zheng Peng , Xiao Shichang , Zhang Peng , Lv Youlong
Published: November 2024

The assembly job shop is a prevalent production organization mode in manufacturing enterprises. During the processing and assembly of products, operation processing times are influenced by numerous factors, leading to significant uncertainty. This paper investigates the flexible assembly job shop scheduling problem (FAJSP) with uncertain processing times, where processing times are represented as variable interval numbers. We develop a robust optimization model for the FAJSP, utilizing confidence level estimation to determine the ranges of processing times and reformulating the model based on the chance-constrained method. A two-individual-based master–apprentice evolutionary (MAE) algorithm is proposed. Two effective encoding schemes are designed to prevent the generation of infeasible solutions under assembly sequence constraints. Additionally, a decoding method based on interval scheduling theory is devised to accurately represent interval processing times. Case studies are conducted to validate the effectiveness of the proposed robust optimization model and demonstrate the superiority of the MAE algorithm.
Influence of the Angle of Periodontal Intrabony Defects on Blood Clots: A Confocal Microscopy Study
Authors: Bevilacqua Lorenzo , Patatti Sofia , Macrì Andrea , Del Lupo Veronica , Porrelli Davide , Maglione Michele
Published: November 2024

Intrabony defects can be the result of parodontitis. In this study we aimed to examine how clot stability is affected by different infrabony defect angles and superficial treatments in regenerative surgery. Methods: Thirty single-root extracted teeth were cut to obtain a section from each tooth. This section was placed in an artificial model containing an infrabony defect with three walls in order to achieve 10 models at angles of 25°, 37°, and 50°. Five root samples for every angle were not subjected any treatment (NT) and five were subjected to root conditioning with a neutral pH solution of ethylenediaminetetraacetic acid (EDTA) at 24%, applied for 2 min. Venous blood was put into the artificial models containing the root sections, and these were placed in an incubator at a constant temperature of 37 °C for 2 h. Samples were analyzed by laser confocal microscopy. Results: All samples exhibited signs of retraction. The EDTA group exhibited a plateau trend for infrabony defects, while in the NT group, there was a statistically significant difference between clot retraction and the increase in defect amplitude. Conclusion: The greater the angle of the infraosseous defect, the higher the rate of clot retraction. This showed that EDTA could reduce the influence of the angle of the infraosseous defect.
Research on Multi-Objective Evolutionary Algorithms Based on Large-Scale Decision Variable Analysis
Authors: Li Jianing , Xu Sijia , Zheng Jiaming , Jiang Guoqing , Ding Weichao
Published: November 2024

Large-scale high-dimensional many-objective optimization problems (LaMaOPs) are prevalent in fields such as autonomous driving, cloud resource scheduling, and smart grids. LaMaOPs involve a large number of decision variables and multiple conflicting objectives that need to be optimized simultaneously. The challenges posed by the curse of dimensionality due to the vast number of decision variables, and the conflict between convergence and diversity caused by the numerous objective variables, make traditional optimization methods inadequate. To address these issues, this paper proposes a two-population cooperative evolutionary algorithm based on large-scale decision variable analysis (DVA-TPCEA). This algorithm integrates quantitative analysis methods for decision variables to deeply examine their impact on each objective and introduces a contribution-based objective detection method. Additionally, a dual-population cooperative evolution mechanism is employed, with targeted optimization strategies designed for convergence and diversity populations, achieving synergistic and complementary optimization between the two populations. To validate the algorithm’s effectiveness in practical applications, a large-scale container resource scheduling strategy based on the DVA-TPCEA algorithm is also proposed. The experimental results indicate that the proposed algorithm demonstrates significant advantages in both general datasets DTLZ, WFG, and LSMOP, and practical models.
Combined Identification of Vehicle Parameters and Road Surface Roughness Using Vehicle Responses
Authors: Liu Lexuan , Guo Xiurui , Yang Xinyu , Liu Lijun
Published: November 2024

Highways, urban roads, and bridges are the important transportation infrastructures for the economic development of modern society. The evaluation of bridge and road quality is crucial to the maintenance and management of the bridge and road industry. Road roughness is a widely accepted indicator in the evaluation of road quality and safety, which is a major input source for vehicles. The vehicle responses-based method of identifying road roughness is efficient and convenient. However, the dynamic characteristics of the vehicle have an important impact on the interaction between the vehicle and the road. When the vehicle parameters are not yet clear, the coupling of unknown parameters and unknown road roughness results in the need for mutual iteration when the existing methods simultaneously identify vehicle parameters and road roughness. To address this issue, this study proposes an effective method for the combined identification of vehicle parameters and road roughness using vehicle responses. The test vehicle is modeled as a four-degree-of-freedom half-vehicle model. In view of the coupling effect between tire stiffness and road roughness, the unknown vehicle physical parameters, except for tire stiffness, are first included in the extended state vector. Based on the extended Kalman filter for unknown excitation (EKF-UI), unknown vehicle physical parameters and unknown forces on the axle are identified. Subsequently, based on the property that the front and rear axles of the vehicle pass through the same road roughness area at a fixed time lag, the tire stiffness is identified by combining the identified unknown forces on the axle. Finally, the road roughness is obtained using the identified vehicle parameters and unknown forces. Numerical studies with different levels of roughness, different noise levels, and different vehicle speeds have verified the accuracy of this method in identifying vehicle parameters and road roughness.
An Anchor-Free Location Algorithm Based on Transition Coordinates
Authors: Fan Jinzhao , Liu Sanjun
Published: November 2024

In some location scenarios where the location information of nodes cannot be mastered in advance, the anchor-free location technology is particularly important. In order to reduce the complicated calculation and eliminate the accumulated error in the traditional anchor-free location algorithm, a new anchor-free location algorithm based on transition coordinates is proposed in this paper. This algorithm is different from the traditional methods such as minimum cost function or inverse matrix. Instead, N initial coordinates are randomly generated as the starting position of the transition coordinates, and the position increment between the transition coordinates and the real coordinates of the node is constantly modified. After K iterations, the convergent position coordinates are finally infinitely close to the real position coordinates of N nodes, and the computational complexity is less than most existing algorithms. As follows, the factors that affect the performance of the algorithm are investigated in the simulation experiment, including the topology structure, positioning accuracy and the total number of nodes, etc. The results show great advantages compared with the traditional anchor-free positioning algorithm. When the topology structure of the initial coordinates changes from a square to a random graph, the number of iterations increases by 15.79%. When the positioning accuracy increased from 1% to 1‰, the number of iterations increased by 36.84%. When the number of nodes N is reduced from 9 to 4, the number of iterations is reduced by 63.16%. In addition, the algorithm can also be extended to the field of moving coordinates or three-dimensional spatial positioning, which has broad application prospects.
Supervised Contrastive Learning for 3D Cross-Modal Retrieval
Authors: Choo Yeon-Seung , Kim Boeun , Kim Hyun-Sik , Park Yong-Suk
Published: November 2024

Interoperability between different virtual platforms requires the ability to search and transfer digital assets across platforms. Digital assets in virtual platforms are represented in different forms or modalities, such as images, meshes, and point clouds. The cross-modal retrieval of three-dimensional (3D) object representations is challenging due to data representation diversity, making common feature space discovery difficult. Recent studies have been focused on obtaining feature consistency within the same classes and modalities using cross-modal center loss. However, center features are sensitive to hyperparameter variations, making cross-modal center loss susceptible to performance degradation. This paper proposes a new 3D cross-modal retrieval method that uses cross-modal supervised contrastive learning (CSupCon) and the fixed projection head (FPH) strategy. Contrastive learning mitigates the influence of hyperparameters by maximizing feature distinctiveness. The FPH strategy prevents gradient updates in the projection network, enabling the focused training of the backbone networks. The proposed method shows a mean average precision (mAP) increase of 1.17 and 0.14 in 3D cross-modal object retrieval experiments using ModelNet10 and ModelNet40 datasets compared to state-of-the-art (SOTA) methods.
Effect of Geometric Parameters of High-Speed Helical Gears on Friction Flash Temperature and Scuffing Load Capacity in Electric Vehicles
Authors: Bai Bo , Li Xianping , Guo Wenchao , Mao Shimin
Published: November 2024

High-speed reducers in electric vehicles, characterized by high rotation speeds, heavy loads, large helix angles, and high contact ratios, are prone to tooth surface scuffing due to high sliding speeds. This scuffing is caused by adhesion wear from excessive instantaneous friction flash temperatures. The prevailing approach to gear scuffing analysis relies on the standard formula method, which is a relatively rudimentary technique. This method lacks the precision required to accurately assess the intricate distribution of tooth surface flash temperature (TSFT), limiting its efficacy in targeted tooth optimization. This study introduces an enhanced semi-analytical method to calculate TSFT and analyzes its variation under different conditions: increased tooth number and reduced module, altered pressure angle, and varied helix angle. The aim is to understand how these geometric parameters affect TSFT and the scuffing load capacity of high-speed reducer gears. This study calculates load distribution and TSFT under peak operating conditions and shows that increasing the tooth number, pressure angle, and helix angle can reduce maximum TSFT by more than 30%, improving scuffing safety and load capacity. However, these improvements must consider the gear’s allowable bending safety factor and bearing service life. The research concludes that optimizing these geometric parameters can significantly enhance the scuffing load capacity of gearsets.
Towards the Valorization of Elderberry By-Product: Recovery and Use of Natural Ingredients for Sorbet Formulations
Authors: Neves Cláudia M. B. , Fogeiro Élia , Cardoso Susana M. , Gonçalves Fernando , Pinto António , Wessel Dulcineia F.
Published: November 2024

One of the food industry’s greatest challenges is to find natural ingredients capable of conferring antioxidant and color properties. In addition, the agri-food industry generates by-products that are often treated as waste, despite their abundance of phytochemicals that can be recovered and used as food ingredients. This study explores the potential of elderberry pomace, an industrial by-product of juice processing rich in anthocyanins and polyphenols, as a natural food additive in blueberry sorbet. Elderberry pomace was incorporated into the sorbet formulation in powder form or as aqueous extracts at two different concentrations. The analysis of the pomace extract by UHPLC-DAD-MS showed the presence of four anthocyanins: cyanidin-3,5-O-diglucoside, cyanidin-3-O-sambubioside-5-O-glucoside, cyanidin-3-O-sambubioside, and cyanidin-3-O-glucoside. The physicochemical properties of the sorbets such as pH, °Brix, overrun, melting rate, and color were evaluated, as well as their levels of total phenolic compounds, total monomeric anthocyanins, and in vitro antioxidant activity. The potential of sorbets to stimulate the growth of probiotic bacteria was evaluated and a sensory analysis was conducted to assess consumer acceptance. Results indicated that the sorbet containing the more concentrated extract presented higher overrun, faster melting rate, higher contents of phenolic compounds and anthocyanins, and higher antioxidant activity compared to the control. Additionally, this formulation showed a darker hue (lower L* value) and a tendency to stimulate probiotic bacteria. Moreover, the sorbets with pomace in their composition had good consumer acceptability. These findings highlight the potential of elderberry pomace to be used as a natural, sustainable ingredient in the ice cream industry, aligning with growing consumer trends towards healthier and eco-friendly products.
An Efficient LC–HRMS-Based Approach to Evaluate Pesticide Contamination in Water Bodies with Measurement Uncertainty Considerations
Authors: Nannou Christina , Gkountouras Dimitrios , Boti Vasiliki , Albanis Triantafyllos
Published: November 2024

Over recent decades, the global occurrence of pesticide residues in aquatic environments has been a pivotal issue; however, their trace-level concentrations necessitate the establishment of ultra-sensitive and reliable analytical approaches. To this end, the present study describes the optimization and validation of an LC-HRMS-based method for the accurate determination of 18 pesticides in river and sea water, accompanied by a measurement uncertainty estimation. This method was applied to analyze 17 real samples from agriculture and aquaculture-impacted areas in Greece and Albania. Different solid-phase extraction (SPE) protocols were tested. For the analysis, cutting-edge Orbitrap MS technology and MS/MS fragmentation, along with the use of matrix-matched calibration curves, provided unprecedented accuracy (<5 ppm) and sensitivity for the confirmation of positive detections. Regarding method performance, exceptional linearity was obtained; the limits of quantification ranged from 1.7 ng L−1 to 90 ng L−1, recoveries varied from 61% to 96% in river water, while slightly higher recoveries (60–111%) were observed in seawater. In all cases, repeatability and intra-laboratory reproducibility were below 15%. The measurement expanded uncertainty (U′, k = 2) was estimated considering precision and bias. MU% values were lower than 50% in all cases, as recommended in SANTE guidelines and applied to the quantified results. The matrix effect study exhibited negative values (<20%) for all compounds. Application to real samples showed a low pesticide contamination load that should not be underestimated.
RS-DETR: An Improved Remote Sensing Object Detection Model Based on RT-DETR
Authors: Zhang Hao , Ma Zheng , Li Xiang
Published: November 2024

Object detection is a fundamental task in computer vision. Recently, deep-learning-based object detection has made significant progress. However, due to large variations in target scale, the predominance of small targets, and complex backgrounds in remote sensing imagery, remote sensing object detection still faces challenges, including low detection accuracy, poor real-time performance, high missed detection rates, and high false detection rates in practical applications. To enhance remote sensing target detection performance, this study proposes a new model, the remote sensing detection transformer (RS-DETR). First, we incorporate cascaded group attention (CGA) into the attention-driven feature interaction module. By capturing features at different levels, it enhances the interaction between features through cascading and improves computational efficiency. Additionally, we propose an enhanced bidirectional feature pyramid network (EBiFPN) to facilitate multi-scale feature fusion. By integrating features across multiple scales, it improves object detection accuracy and robustness. Finally, we propose a novel bounding box regression loss function, Focaler-GIoU, which makes the model focus more on difficult samples, improving detection performance for small and overlapping targets. Experimental results on the satellite imagery multi-vehicles dataset (SIMD) and the high-resolution remote sensing object detection (TGRS-HRRSD) dataset show that the improved algorithm achieved mean average precision (mAP) of 78.2% and 91.6% at an intersection over union threshold of 0.5, respectively, which is an improvement of 2.0% and 1.5% over the baseline model. This result demonstrates the effectiveness and robustness of our proposed method for remote sensing image object detection.
Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach
Authors: Ullah Saif , Ullah Niamat , Siddique Muhammad Farooq , Ahmad Zahoor , Kim Jong-Myon
Published: November 2024

Pipeline leakage represents a critical challenge in smart cities and various industries, leading to severe economic, environmental, and safety consequences. Early detection of leaks is essential for overcoming these risks and ensuring the safe operation of pipeline systems. In this study, a hybrid convolutional neural network–long short-term memory (CNN-LSTM) model for pipeline leak detection that uses acoustic emission signals was designed. In this model, acoustic emission signals are initially preprocessed using a Savitzky–Golay filter to reduce noise. The filtered signals are input into the hybrid model, where spatial features are extracted using a CNN. The features are then passed to an LSTM network, which extracts temporal features from the signals. Based on these features, the presence or absence of a leakage is determined. The performance of the proposed model was compared with two alternative approaches: a method that employs combined features from the time domain and LSTM and a bidirectional gated recurrent unit model. The proposed approach demonstrated superior performance, as evidenced by lower validation loss, higher validation accuracy, enhanced confusion matrices, and improved t-distributed stochastic neighbor embedding plots compared to the other models when tested on industrial data. The findings indicate that the proposed model is more effective in accurately detecting pipeline leaks, offering a promising solution for enhancing smart cities and industrial safety.
Insights into Machining Techniques for Additively Manufactured Ti6Al4V Alloy: A Comprehensive Review
Authors: Sambo Abdulkadir Mohammed , Younas Muhammad , Njuguna James
Published: November 2024

Investigation into the post-processing machinability of Ti6Al4V alloy is increasingly crucial in the manufacturing industry, particularly in the machining of additively manufactured (AM) Ti6Al4V alloy to ensure effective machining parameters. This review article summarizes various AM techniques and machining processes for Ti6Al4V alloy. It focuses on powder-based fusion AM techniques such as electron beam melting (EBM), selected laser melting (SLM), and direct metal deposition (DMD). The review addresses key aspects of machining Ti6Al4V alloy, including machining parameters, residual stress effects, hardness, microstructural changes, and surface defects introduced during the additive manufacturing (AM) process. Additionally, it covers the qualification process for machined components and the optimization of cutting parameters. It also examines the application of finite element analysis (FEA) in post-processing methods for Ti6Al4V alloy. The review reveals a scarcity of articles addressing the significance of post-processing methods and the qualification process for machined parts of Ti6Al4V alloy fabricated using such AM techniques. Consequently, this article focuses on the AM-based techniques for Ti6Al4V alloy parts to evaluate and understand the performance of the Johnson–Cook (J–C) model in predicting flow stress and cutting forces during machining of the alloy.