bluuebunny/crossref_metadata_2025 huggingface dataset:
Expert goalkeepers’ and coaches’ views on anticipation and cue utilisation facing backcourt throws in handball goalkeeping
Authors: Huesmann Kim , Schorer Jörg , Büsch Dirk , Witt Jelto , Loffing Florian
Published: October 2023

Introduction

Handball goalkeepers have to act under severe spatio-temporal pressure in both standardised (e.g., 7 m penalty) and non-standardised situations (e.g., backcourt throws) which require them to predict action outcome before ball flight is visible. So far, research on goalkeepers’ cue utilisation for anticipation of an opponent’s action has mainly focused on 7 m throw situations whereas little attention has been paid to the latter, more complex and far more frequently occurring backcourt throw situations.

Methods

To address this gap, we conducted semi-structured interviews with N = 6 expert handball goalkeepers and goalkeeper coaches [all of whom were (former) expert handball goalkeepers] on anticipation and cue utilisation when facing backcourt throws. The interviews were subsequently transcribed, coded and results were inductively as well as deductively categorised by means of a thematic analysis.

Results

Results reveal a variety of kinematic and contextual cues relevant for action anticipation that become available before the game and before or during the throw. Participants reported to use information from the offence (e.g., thrower’s jump; opposing team’s task distribution) and the defence (e.g., defensive players’ strategies, block position) for anticipation in backcourt throw situations. Additionally, we identified several factors that influence cue availability and utilisation.

Discussion

Our findings provide a thorough basis to (a) guide future research that yields questions on kinematic and contextual cue integration and in-situ cue usage as well as (b) inform the development of training programs to foster goalkeepers’ anticipatory skill.
Brucellae as resilient intracellular pathogens: epidemiology, host–pathogen interaction, recent genomics and proteomics approaches, and future perspectives
Authors: Dawood Ali Sobhy , Elrashedy Alyaa , Nayel Mohamed , Salama Akram , Guo Aizhen , Zhao Gang , Algharib Samah Attia , Zaghawa Ahmed , Zubair Muhammed , Elsify Ahmed , Mousa Walid , Luo Wanhe
Published: October 2023

Brucellosis is considered one of the most hazardous zoonotic diseases all over the world. It causes formidable economic losses in developed and developing countries. Despite the significant attempts to get rid of Brucella pathogens in many parts of the world, the disease continues to spread widely. Recently, many attempts proved to be effective for the prevention and control of highly contagious bovine brucellosis, which could be followed by others to achieve a prosperous future without rampant Brucella pathogens. In this study, the updated view for worldwide Brucella distribution, possible predisposing factors for emerging Brucella pathogens, immune response and different types of Brucella vaccines, genomics and proteomics approaches incorporated recently in the field of brucellosis, and future perspectives for prevention and control of bovine brucellosis have been discussed comprehensively. So, the current study will be used as a guide for researchers in planning their future work, which will pave the way for a new world without these highly contagious pathogens that have been infecting and threatening the health of humans and terrestrial animals.
Desorption and Sorption Isotherms of Different Varieties of Hemp Seeds with Different Percentages of Dockage under Different Temperatures and Different Relative Humidities
Authors: Tiwari Abhinav , Jian Fuji
Published: October 2023

Hemp cultivation faces challenges due to the adoption of dioecious cultivars, which suffer from biomass loss and fibre heterogeneity. In contrast, monoecious cultivars offer simultaneous fibre and seed production, albeit with lower fibre quality. Understanding the drying characteristics and storage requirements of hemp seeds is crucial for effective post-harvest management. This study explored the moisture sorption and desorption isotherms of two common Canadian hemp seed varieties, Altair (dioecious) and CanMa (monoecious), by using both saturated salt solution (SSS) and thin-layer drying methods. Their isotherms were also compared with the published isotherm of Finola—a common dioecious variety in Europe. The thin-layer drying method yielded higher EMC values than the SSS method due to incomplete equilibrium attainment. Larger EMC differences existed between different seed types (dioecious vs. monoecious), and this difference was small between the same seed types (dioecious vs. dioecious). The GAB equation provided the most accurate prediction of equilibrium moisture contents for both varieties.
Yield Adaptability and Stability in Field Pea Genotypes Using AMMI, GGE, and GYT Biplot Analyses
Authors: Yang Xin , Soliman Alaa A. , Hu Chaoqin , Yang Feng , Lv Meiyuan , Yu Haitian , Wang Yubao , Zheng Aiqing , Dai Zhengming , Li Qiong , Tang Yongsheng , Yang Jiangu , Zhang Yurong , Niu Wenwu , Wang Liping , He Yuhua
Published: October 2023

Pea (Pisum sativum L.) is a vital leguminous crop farmed worldwide. Pea plays an essential role in China’s crop rotation system, but the major restrictions to its cultivation are stability and low yield. Breeding for promising cultivars with a significantly high yield will impact the sustainability of pea production. Additionally, diverse environment trials are crucial in determining the best genotype. The new cultivar “Yunwan 52” was developed by hybridization and subsequently evaluated through yield trials among six pea genotypes across 14 environments during the 2016–2018 growing seasons. The results showed that the average yield of “Yunwan 52” for all tested environments was 2.64 t ha−1 compared to the control cultivar (Yunwan 18, 1.83 t ha−1). Analysis of AMMI variance showed significant differences (p < 0.01) between genotypes, environments, and their interaction. Based on the GGE biplot, some genotypes possessed wide and narrow adaptability to environments, such as Yunwan 52 was considered the most stable and ideal gen-otype across all tested environments. GYT biplot analysis also revealed that this realized cultivar was a superior and stable genotype that can be identified visually by combining all characters in breeding programs. Yunwan 52 distinguishes with purple blossoms and seed coat peas. It is possible to infer that the newly released cultivar “Yunwan 52” has outstanding yield performance and wide adaptability to multiple environmental conditions (resilience to abiotic stress). It will contribute to developing nutritional pea genotypes and increase pea production in irrigated areas.
Litter Decomposition of Two Kiwifruit Cultivars (‘Jinkui’ and ‘Hort-16A’) with Different Litter Qualities in the Orchard Ecosystem
Authors: Lu Yupeng , Gao Zhu , Mao Jipeng , Lin Mengfei , Gong Xuchen , Wang Xiaoling
Published: October 2023

The aim of this study was to reveal the decomposition differences of kiwifruit litters with different qualities and verify the “Initial Litter Quality Hypothesis”. This study took litters of ‘Jinkui’ and ‘Hort-16A’ kiwifruit as the research objects, and carried out in situ decomposition experiments. The decomposition rate, nutrients release process, and soil enzyme activities were analyzed. In this study, the litter of ‘Hort-16A’ kiwifruit decomposed faster than the litter of ‘Jinkui’ kiwifruit. The decomposition time was positively correlated with the initial concentration of C of the litters, but negatively correlated with the concentrations of N and P. Except for P and Mn, the dynamic trends of the nutrient concentrations were similar during the litter decomposition of ‘Jinkui’ and ‘Hort-16A’ kiwifruit. After 180 days of decomposition, about 85%~95% of the initial concentrations of the macro-elements of the ‘Hort-16A’ kiwifruit litter were released. The dynamic trends of protease activities were similar, but that of sucrase, β-1,4-glucosidase, polyphenol oxidase, and phosphatase were different. In conclusion, the litter quality of kiwifruit affects the decomposition rate, and the difference in decomposition rate in turn affects the dynamic processes of nutrient release and soil enzyme activity. This study provides evidence for the “Initial Litter Quality Hypothesis” in the orchard ecosystem.
Optimization Model and Application for Agricultural Machinery Systems Based on Timeliness Losses of Multiple Operations
Authors: Sun Jian , Zhang Yiming , Chen Haitao , Qiao Jinyou
Published: October 2023

Present agricultural practices confront issues such as mismatches between tractors and implements, imprecise machinery allocation, and excessive machinery investment. Optimization of agricultural machinery systems was a potent remedy for these concerns. To address inaccuracies in calculating objective functions and the incompleteness of constraints in existing models for agricultural machinery system optimization, a comprehensive mixed integer nonlinear programming (MINP) model for agricultural machinery system optimization was established. The model introduced timeliness loss costs for multiple key operations across various crops into the objective function, and constraints were enhanced by including operation sequence constraints and boundary constraints on initiation and completion dates of those key operations. Taking corn and soybeans as examples, timeliness loss functions of sowing and harvesting operations were derived through experiments. Solving the MINP model by Lingo (V.14.0) software, improvements in total power, workload per unit power, and total operational costs were shown when comparing the optimized machinery system through the MINP model against current systems. When the model omitted considerations for timeliness loss functions and operation sequence constraints, issues arose including an increase in total operational costs and an inversion of operation sequence. The model’s application in devising machinery allocation plans for production units of various operational scales revealed a gradual decrease in total power and costs per unit area with expanding scale, approaching stability when scale exceeded 1600 hm2. This study enriches theory and methodology for optimizing agricultural machinery systems, provides theoretical and technological underpinnings for rational machinery acquisition, and promotes the high-quality progression of comprehensive agricultural mechanization.
An Effect and Less Spraying Control Method Successfully Controls Botrytis cinerea on Grapes in China
Authors: Wang Hui , Liu Mei , Zhang Wei , Yan Jiye , Tang Xingmin , Sanchez-Molina Jorge Antonio , Li Xinghong
Published: October 2023

Gray mold caused by Botrytis cinerea is a destructive disease in grapes. Although the preharvest use of pesticides can control it, fungicide resistance in B. cinerea is now common. We used an Effect and Less Spraying Control (ELSC) method for applying fungicides effective against B. cinerea on grapes. The spraying schedule was determined by exploring the key stages of B. cinerea invasion using field and in vitro inoculation tests. The results indicated that the stage most vulnerable to pathogen invasion is the full-bloom stage. The disease incidence/severity in this stage is highest compared with the pre-bloom, 10-days-after-full-bloom, bunch-closure and veraison stages. Given the inoculation results and the threat of residual infected petals, the ELSC method established an optimum spray schedule at full bloom and 10 days after full bloom. To evaluate the ELSC method, four kinds of fungicides were used in an experimental trial in Beijing in 2015 and 2017; Shanghai in 2016; and Hebei in 2019 and 2021. Fludioxonil was the most effective fungicide, followed by Pythium oligandrum (bio-fungicide), difenoconazole + azoxystrobin and pyraclostrobin. ELSC was more effective against B. cinerea than the traditional control schedule, when comparing the disease severity (i.e., 0.07 ± 0.10% in ELSC and 0.49 ± 0.014% in the traditional practice when using fludioxonil). The average yield per hectare in ELSC confirmed that spraying during flowering does not have a deleterious effect on grape yield. It produced a 1224.37 00 kg/ha greater yield than the control group when fludioxonil was applied.
Canopy Laser Interception Compensation Mechanism—UAV LiDAR Precise Monitoring Method for Cotton Height
Authors: Xu Weicheng , Yang Weiguang , Wu Jinhao , Chen Pengchao , Lan Yubin , Zhang Lei
Published: October 2023

Plant height is a crucial phenotypic trait that plays a vital role in predicting cotton growth and yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy height from single-flight LiDAR data remains a formidable challenge in current high-density cotton cultivation patterns, where dense foliage obstructs the collection of bare soil terrain, particularly after flowering. The existing LiDAR-based methods for cotton height estimation suffer from significant errors. In this study, a new method is proposed to compensate for the canopy height estimation by using the canopy laser interception rate. The ground points are extracted by the ground filtering algorithm, and the interception rate of the laser per unit volume of the canopy is calculated to represent the canopy density and compensate for the cotton height estimation. The appropriate segmented height compensation function is determined by grouping and step-by-step analysis of the canopy laser interception rate. Verified by 440 groups of height data measured manually in the field, the results show that the canopy laser interception compensation mechanism is of great help in improving the estimation accuracy of LiDAR. R2 and RMSE reach 0.90 and 6.18 cm, respectively. Compared with the estimation method before compensation, R2 is increased by 13.92%, and RMSE is reduced by 49.31%. And when the canopy interception rate is greater than 99%, the compensation effect is more obvious, and the RMSE is reduced by 62.49%. This research result can significantly improve the height estimation accuracy of UAV-borne for high planting density cotton areas, which is helpful to improve the efficiency of cotton quality breeding and match genomics data.
Metapopulation Structure of Two Species of Pikeworm (Triaenophorus, Cestoda) Parasitizing the Postglacial Fish Community in an Oligotrophic Lake
Authors: Kashinskaya Elena N. , Vlasenko Pavel G. , Kolmogorova Tatyana V. , Izotova Gelena V. , Shokurova Anastasiya V. , Romanenko Georgy A. , Markevich Grigorii N. , Andree Karl B. , Solovyev Mikhail M.
Published: October 2023

In the present study, we estimated the levels of infestation of the main fish species that are hosts for two Triaenophorus species: T. crassus and T. nodulosus. The prevalence of T. crassus and T. nodulosus infestations in the intestine of their definitive host–pike Esox lucius was similar (71.0% and 77.4%, respectively). At the same time, the prevalence of T. crassus infestation in muscle tissue was significantly different between the second intermediate hosts, Coregonus lavaretus pidschian (31.4%) and Cor. l. pravdinellus (91.2%), due to considerable differences in their diets. For T. nodulosus, we found significant variations in the levels of prevalence among the second intermediate hosts—100% for Lota lota, 81.8% for Cottus sibiricus 31.9% for Thymallus arcticus, and 24.5% for Perca fluviatilis—that we also explained using different diets. Moreover, analysis of the symmetry of parasite infestations did not reveal any asymmetry between the number of cysts in the left and right body surfaces of the “planktivorous” form/species of whitefish, whereas in the ‘‘benthivorous”, an asymmetry of parasite infestations was found.
Polioencephalomalacia in Buffaloes in the Amazon Biome
Authors: Barbosa José Diomedes , Martins Fernanda Monik Silva , Ferreira Filho Carlos Eduardo da Silva , Barbosa Camila Cordeiro , Vieira Eliel Valentim , Silva Ruama Paixão de Lima , Lopes Cinthia Távora de Albuquerque , Silveira Natália da Silva e Silva , Oliveira Carlos Magno Chaves , Brito Marilene Farias , Salvarani Felipe Masiero
Published: October 2023

The epidemiological and clinical pathological aspects of polioencephalomalacia (PEM) in five buffaloes in the Amazon biome are described. Epidemiological data were obtained during the clinical visit in which buffalos were submitted to an examination of the nervous system. The diagnosis of PEM was based on epidemiological, clinical–pathological, and histopathological findings, similar to findings in other ruminants. In the clinical examination, all buffaloes had a body score between 2.5 and 3 (scale from 1 to 5), with decreased alertness, postural changes, marked hypermetria when stimulated to move, total or partial blindness demonstrated by colliding with the corral structures, head pressing and circumduction of the hindquarters when supported on the thoracic limbs, opisthotonos, muscle tremors, convulsions, paddling movements, sialorrhea, decrease in palpebral and pupillary reflexes, and eyeball rotation placing the pupillary slit in a vertical position. At necropsy, mild lesions characterized by edema and flattening of the cerebral convolutions were observed. A histopathological examination showed laminar necrosis of the cerebral cortex. The cause of PEM in the studied buffaloes was not established, which indicates the need for further studies to elucidate this disease in the species, particularly in the Amazon region.
Detecting Forest Musk Deer Abscess Disease Pathogens Using 16S rRNA High-Throughput Sequencing Technology
Authors: Lu Guanjie , Wang Zhe , Zhang Baofeng , Zhou Zhichao , Hu Defu , Zhang Dong
Published: October 2023

Currently, researchers use bacterial culture and targeted PCR methods to classify, culture, and identify the pathogens causing abscess diseases. However, this method is limited by factors such as the type of culture medium and culture conditions, making it challenging to screen and proliferate many bacteria effectively. Fortunately, with the development of high-throughput sequencing technology, pathogen identification at the genetic level has become possible. Not only can this approach overcome the limitations of bacterial culture, but it can also accurately identify the types and relative abundance of pathogens. In this study, we used high-throughput sequencing of 16S rRNA to identify the pathogens in purulent fluid samples. Our results not only confirmed the presence of the main pathogen reported by previous researchers, Trueperella pyogenes, but also other obligate anaerobes, Fusobacterium necrophorum and Bacteroides fragilis as the dominant pathogens causing abscess diseases for the first time. Therefore, our findings suggest that high-throughput sequencing technology has the potential to replace traditional bacterial culture and targeted PCR methods.
Sublethal Effects of Polystyrene Nanoplastics on the Embryonic Development of Artemia salina (Linnaeus, 1758)
Authors: Contino Martina , Ferruggia Greta , Indelicato Stefania , Pecoraro Roberta , Scalisi Elena Maria , Salvaggio Antonio , Brundo Maria Violetta
Published: October 2023

Currents, wave motion, solar radiation, and abrasion are mechanisms responsible for the degradation of large plastic artifacts and contribute to the dispersion of micro and nanoplastics into aquatic ecosystems, which are, currently, the most dangerous threats due to their invisibility and persistence. The present work evaluated the possible lethal and sublethal effects of amino-modified polystyrene nanoplastics (nPS-NH2) with diameters of 50 nm and 100 nm on Artemia salina (A. salina), an organism at the base of the trophic chain of the aquatic system, using a widely used model for the analysis of embryotoxicity from environmental pollutants. For this purpose, after evaluating the biodistribution of nanoplastics in the body of the tested animals, several endpoints such as anomalies, apoptosis, and ROS production were assessed. In addition, particular attention was dedicated to evaluating the correlation between toxicity and the particle size tested. The results reported that, despite the absence of a lethal impact, several sublethal effects involving gut and body size malformations, as well as the enhancement of apoptosis and oxidative stress in relation to an increase in tested concentration and a decrease in nanoparticle size.
Analysis of Acoustic Flow Field Characteristics of Key Components of High-Speed Train Bogies
Authors: Zhao Xing , Jia Xiaoyang , Li Lin , Wang Hanyu
Published: October 2023

In this paper, we aim to address the challenge of airflow interference during fault detection in high-speed train bogies by introducing a flow field and investigating the characteristics of the sound field distribution of critical components under its influence. This approach overcomes the limitation observed in previous studies that ignored the impact of the flow field. Furthermore, we evaluate and compare various layouts for inter-track acoustic sensor arrays. The study results demonstrate that the axle box and gearbox are primarily affected by frequency bands above 200 Hz, while the motor is mainly influenced by frequencies above 150 Hz. Moreover, the motor is most significantly impacted by vehicle speed, followed by the gear box and finally the shaft box. When altering the vibration frequency of the sound source, there is a decreasing trend in minimum sound pressure level with increasing frequency. Additionally, the gradient of the sound pressure level change at three locations (motor, gear box, and axle box) exceeds that of both vehicle speed variation and vibration intensity of the sound source. By adjusting the vibration intensity of the sound source, similar gradients are observed for both maximum and minimum values of sound pressure level at these three locations. Therefore, vibration intensity has a consistent effect on changes in sound pressure level at these three places but only influences its magnitude. The aforementioned methods can be employed for the analysis of wind noise and structural noise, thereby offering novel insights for future advancements in noise reduction processing.
A Novel Feature Selection Approach to Classify Intrusion Attacks in Network Communications
Authors: Ozkan-Okay Merve , Samet Refik , Aslan Ömer , Kosunalp Selahattin , Iliev Teodor , Stoyanov Ivaylo
Published: October 2023

The fast development of communication technologies and computer systems brings several challenges from a security point of view. The increasing number of IoT devices as well as other computing devices make network communications more challenging. The number, sophistication, and severity of network-related attacks are growing rapidly. There are a variety of different attacks including remote-to-user (R2L), user-to-remote (U2R), denial of service (DoS), distributed DDoS, and probing. Firewalls, antivirus scanners, intrusion detection systems (IDSs), and intrusion prevention systems (IPSs) are widely used to prevent and stop cyber-related attacks. Especially, IDPSs are used to stop and prevent intrusions on communication networks. However, traditional IDSs are no longer effective in detecting complicated cyber attacks from normal network traffic. Because of this, new promising techniques, which specifically utilize data mining, machine learning, and deep learning, need to be proposed in order to distinguish intrusions from normal network traffic. To effectively recognize intrusions, the feature generation, feature selection, and learning processes must be performed delicately before the classification stage. In this study, a new feature selection method called FSAP (Feature Selection Approach) is proposed. In addition, a hybrid attack detection model called SABADT (Signature- and Anomaly-Based Attack Detection Technique) is suggested, which utilizes different classification metrics to recognize attacks. The proposed general method FSACM (Feature Selection and Attack Classification Method) is tested on KDD ’99, UNSW-NB15, and CIC-IDS2017 datasets. According to the experiment results, the proposed method outperformed the state-of-the-art methods in the literature in terms of detection, accuracy, and false-alarm rates.
The Thermal Properties and Nutritional Value of Biomass of Oleaginous Yeast Rhodotorula sp. during Glucose Fed-Batch Cultivation in Medium with Waste Nitrogen
Authors: Gientka Iwona , Ostrowska-Ligęza Ewa , Wirkowska-Wojdyła Magdalena , Synowiec Alicja
Published: October 2023

The biotechnological processing of oleaginous yeast biomass should be comprehensively managed using the zero-waste policy. This study focused on the biomass of the red yeast Rhodotorula obtained from a medium containing waste nitrogen. The cells accumulate lipids in intracellular lipid droplets; however, they are also rich in protein. Therefore, the nutritional value of lipid and protein, according to their fatty acid and amino acid composition, is a necessary step for practical application. For the very first time, this study focused on understanding the influence of temperature on powdered red yeast biomass to study components phase transition or chemical reactions by using DSC. Rhodotorula glutinis var. rubescens was cultivated in a glucose fed-batch in a potato wastewater medium, where the biomass yield was powdered, and lipid and fatty acid, protein, and amino acid compositions were determined. The DSC diagrams of red yeast biomass were characterized by two small and mild endothermic peaks, indicating the presence of fat and the presence of low molecular weight carbohydrates and a distinct peak associated with the presence of crystalline sugars. The nutritional quality of the lipid fraction as atherogenicity (0.223), thrombogenicity index (0.438), PUFA/SFA (0.24), and the n-6/n-3 ratio (3.275) was adequate for the recommendation and resulted from the fatty acid composition. The yeast protein was characterized by a high content of glutamic acid (99 mg/1 g of protein), and a value of essential amino acid index of protein suggested a superior amino acid composition compared to the FAO/WHO standard. Despite a high essential amino acid index (>120), yeast protein was characterized by a low content of Lys or Met.
Experimental–Numerical Analysis on the Cable Vibration Behavior of a Long-Span Rail-Cum-Road Cable-Stayed Bridge under the Action of High-Speed Trains
Authors: Yang Fan , Zhao Hanwei , Li Aiqun , Fang Zhao
Published: October 2023

Rail-cum-road cable-stayed bridges are widely used to span rivers, bays, and valleys. It is vital to understand the vibration behavior of the cables, which are the crucial load-bearing components of a cable-stayed bridge, as it is the leading cause of cable fatigue. First, a numerical model of cable vibration under double-end excitation was derived by neglecting the bending stiffness and was verified through a cable’s multi-segment bar finite element model, and a numerical solution program was compiled based on MATLAB R2022a software. Then, a finite element model (FEM) was established according to the design documents of a long-span rail-cum-road cable-stayed bridge. Finally, the dynamic response of the cable under the train loads was analyzed based on the FEM and numerical model. The study shows that the numerical model can accurately simulate the cable with a relative error of less than 1% for its first four frequencies compared with the FEM; the maximum displacement amplitude appears at the longest cable near the middle of the main span; the vibration frequency of the cable is approximate to the cable end excitation frequency within a 1% discrepancy; and the vibration amplitude at the center of the cable is approximately twice that of the excitation amplitude at the end of the cable.
Multi-Scale Flame Situation Detection Based on Pixel-Level Segmentation of Visual Images
Authors: Wang Xinzhi , Li Mengyue , Liu Quanyi , Chang Yudong , Zhang Hui
Published: October 2023

The accurate analysis of multi-scale flame development plays a crucial role in improving firefighting decisions and facilitating smart city establishment. However, flames’ non-rigid nature and blurred edges present challenges in achieving accurate segmentation. Consequently, little attention is paid to extracting further flame situation information through fire segmentation. To address this issue, we propose Flame-SeaFormer, a multi-scale flame situation detection model based on the pixel-level segmentation of visual images. Flame-SeaFormer comprises three key steps. Firstly, in the context branch, squeeze-enhanced axial attention (SEA attention) is applied to squeeze fire feature maps, capturing dependencies among flame pixels while reducing the computational complexity. Secondly, the fusion block in the spatial branch integrates high-level semantic information from the contextual branch with low-level spatial details, ensuring a global representation of flame features. Lastly, the light segmentation head conducts pixel-level segmentation on the flame features. Based on the flame segmentation results, static flame parameters (flame height, width, and area) and dynamic flame parameters (change rates of flame height, width, and area) are gained, thereby enabling the real-time perception of flame evolution behavior. Experimental results on two datasets demonstrate that Flame-SeaFormer achieves the best trade-off between segmentation accuracy and speed, surpassing existing fire segmentation methods. Flame-SeaFormer enables precise flame state acquisition and evolution exploration, supporting intelligent fire protection systems in urban environments.
Potential Synergistic Inhibition of Enterococcus faecalis by Essential Oils and Antibiotics
Authors: John Stanley , Lee Jeung Woon , Lamichhane Purushottam , Dinh Thanhphuong , Nolan Todd , Yoon Thomas
Published: October 2023

Recurrent infections after root canal treatments often involve Enterococcus faecalis, a microorganism closely associated with therapy failures due to its biofilm production, survival in nutrient-deprived conditions, and antibiotic tolerance. Essential oils (EOs), which display antimicrobial and antibacterial properties, exhibit inhibitory effects on the growth of many microorganisms including E. faecalis. This study assessed the in vitro efficacy of combining 5% antibiotics (kanamycin 2.5 mg/mL, streptomycin 2.5 mg/mL, gentamicin 1.5 mg/mL, and ampicillin 5 mg/mL) with cinnamon (1.25% to 5%) or clove (25% and 50%) EOs in inhibiting the growth of E. faecalis, using disk diffusion tests. Disks were treated with EOs-only, antibiotics-only, or EO–antibiotic combinations, placed on BEA agar plates, and incubated for 24 h, and the zones of inhibition were measured. Results showed that EOs (cinnamon and clove) and 5% antibiotics, by themselves, had robust growth inhibition of E. faecalis across all tested concentrations. Moreover, combining 5% aminoglycosides (kanamycin 2.5 mg/mL, streptomycin 2.5 mg/mL, and gentamicin 1.5 mg/mL) with 5% cinnamon EO produced significantly enhanced antimicrobial effect than the corresponding 10% antibiotic solution alone. These findings suggest that combining cinnamon EO with aminoglycoside antibiotics can achieve significant inhibition of E. faecalis at a lower concentration of antibiotics compared to using a higher dose of antibiotics alone. Further in vivo studies should determine the safety, efficacy, and treatment duration, with the potential to reduce antibiotic dosages and associated toxicity while preventing recurrent infections.
Exploring the ViDiDetect Tool for Automated Defect Detection in Manufacturing with Machine Vision
Authors: Dziubek Mateusz , Rysiński Jacek , Jancarczyk Daniel
Published: October 2023

Automated monitoring of cutting tool wear is of paramount importance in the manufacturing industry, as it directly impacts production efficiency and product quality. Traditional manual inspection methods are time-consuming and prone to human error, necessitating the adoption of more advanced techniques. This study explores the application of ViDiDetect, a deep learning-based defect detection solution, in the context of machine vision for assessing cutting tool wear. By capturing high-resolution images of machining tools and analyzing wear patterns, machine vision systems offer a non-contact and non-destructive approach to tool wear assessment, enabling continuous monitoring without disrupting the machining process. In this research, a smart camera and an illuminator were utilized to capture images of a car suspension knuckle’s machined surface, with a focus on detecting burrs, chips, and tool wear. The study also employed a mask to narrow the region of interest and enhance classification accuracy. This investigation demonstrates the potential of machine vision and ViDiDetect in automating cutting tool wear assessment, ultimately enhancing manufacturing processes’ efficiency and product quality. The project is at the implementation stage in one of the automotive production plants located in southern Poland.
Study on Mechanical Properties of Deep Expansive Soil and Coupling Damage Model of Freeze–Thaw Action and Loading
Authors: Zhu Zhuliang , Lin Bin , Chen Shiwei
Published: October 2023

This study is primarily intended to present a damage constitutive equation under the combined action of confining pressures and freeze–thaw cycles by subjecting deep expansive clay to the consolidated undrained triaxial tests. We study the influence of the numbers of freeze–thaw cycles on various mechanical indexes of soil by using the TSZ-2 instrument (fully automatic triaxial instrument). As the number of freeze–thaw cycles increases, the ultimate peak stress of the soil decreases, and then, the effect of the freeze–thaw effect on the shear strength gradually weakened. By combining the expression method of the damage variable under the action of loading alone with the expression method under the action of freeze–thaw cycles alone, we brought in the damage evolution equation to obtain the damage constitutive equation under the combined action of confining pressures and freeze–thaw cycles. The stress values under three confining pressures (100 kPa, 200 kPa, and 300 kPa) can be determined by using the final damage constitutive model. The measured data with a water content of 17% and six freeze–thaw cycles were compared with the theoretical data. The actual strength values were 118.4 kPa, 152.3 kPa, and 184.1 kPa, and the theoretical strength values were 120 kPa, 150 kPa, and 186 kPa. The fitting degree of the strength value was as high as 99%, which verifies the feasibility of this model. This study can serve as an available reference for well wall construction and disaster prediction in deep coal mining.
CIPSO-Based Decision Support Method for Collision Avoidance of Super-Large Vessel in Port Waters
Authors: Xiang Bo , Zhuo Yongqiang
Published: October 2023

Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm optimization (CIPSO). Firstly, the objective function is constructed based on the multi-objective optimization method. Here, a fuzzy comprehensive evaluation (FCE)-based vessel collision hazard model and vessel speed-varying energy-loss model integrating the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) are involved. Furthermore, in response to the limitations of the PSO algorithm, which is prone to falling into local optima in the later stages of iteration, a curve increment strategy is incorporated. To improve the performance of the global optimization, it is optimized using a local followed by global search method. The iterative evolution of CIPSO is used to obtain the optimal decision value in the set domain of feasible solutions. Finally, the effectiveness and feasibility of the proposed method are verified by the numerical simulation and large vessel maneuvering simulator, which can provide collision avoidance decision support for ship pilots.
Study on Mechanical Properties and Erosion Resistance of Self-Compacting Concrete with Different Replacement Rates of Recycled Coarse Aggregates under Dry and Wet Cycles
Authors: Liu Shan , Han Fengxia , Zheng Shiqi , Gao Songpu , Zhang Guoxing
Published: October 2023

Concrete that self-compacts is frequently utilized in engineering construction. Recycled coarse aggregate self-compacting concrete (RCASCC) is made by partially substituting recycled coarse aggregates (RCA) for natural coarse aggregates in order to conserve construction resources. This study examines the impact of linked sulfate erosion, dry and wet cycles, and RCA replacement rates of 0%, 25%, 50%, 75%, and 100% on the mechanical properties and durability of RCASCC. By using the mass loss rate, relative dynamic elastic modulus, corrosion resistance factor, X-ray diffraction (XRD), scanning electron microscope (SEM), and atomic force microscope (AFM) analyses, as well as other macroscopic and microscopic methods, it is possible to examine the deterioration patterns of RCASCC under dry and wet cycles. The results demonstrate that the addition of RCA has a notable impact on concrete’s resistance to sulfate attack during both dry and wet cycles. The erosion products steadily rise, the interfacial transition zone (ITZ) becomes rougher, and the sulfate resistance falls as the replacement rate of RCA rises. According to the findings of SiO2, AFt, and CaCO3, the examination of corrosion products from XRD and microstructure from SEM and EDS is carried out. The old mortar that has adhered to the surface of RCA, as shown by the AFM analysis of ITZ and the SEM analysis of RCA, can significantly affect the roughness of ITZ inside RCASCC.
A Review of Transformer-Based Approaches for Image Captioning
Authors: Ondeng Oscar , Ouma Heywood , Akuon Peter
Published: October 2023

Visual understanding is a research area that bridges the gap between computer vision and natural language processing. Image captioning is a visual understanding task in which natural language descriptions of images are automatically generated using vision-language models. The transformer architecture was initially developed in the context of natural language processing and quickly found application in the domain of computer vision. Its recent application to the task of image captioning has resulted in markedly improved performance. In this paper, we briefly look at the transformer architecture and its genesis in attention mechanisms. We more extensively review a number of transformer-based image captioning models, including those employing vision-language pre-training, which has resulted in several state-of-the-art models. We give a brief presentation of the commonly used datasets for image captioning and also carry out an analysis and comparison of the transformer-based captioning models. We conclude by giving some insights into challenges as well as future directions for research in this area.
Reduction of Satellite Signature Effect in High-Accuracy Satellite Laser Ranging to Etalon
Authors: An Ning , Guan Bowen , Nunez Natalia Edith , Gao Jian , Dong Xue , Zhang Haitao , Podesta Ricardo Cesar
Published: October 2023

Etalon is considered to be one of the most promising satellites for studying crustal motions, Earth rotation, and other scientific applications. Unfortunately, its outsized shape and signature result in a measurement range bias of several millimeters. On the basis of simulations of the echo signals, we analyze the center of mass corrections (CoM) for Etalon due to variations in satellite signature effect at different incidence angles. To minimize range bias caused by satellite signature effects, a center of mass corrections filter has been proposed for the processing of standard SLR data. According to the relationship between RMS of CoM and the upper limits of the rejection criteria, the measurements with the lowest variability of CoM are selected for normal points. Statistics indicate that the center of mass corrections filter can improve the stability of the collected data by 79%, and reduce the mean RMS of normal points from 163.7 × 41.8 ps to 118.2 × 8.94 ps. Additionally, the new algorithm is applicable to Etalon-2. In particular, this paper enriches and provides a useful reference for minimizing the effects of satellite signatures on the production of SLR data by providing a theoretical model that incorporates systematic errors in SLR.
Application of the Ground Penetrating Radar (GPR) and Electromagnetic (EM34-3) Geophysical Tools and Sedimentology for the Evaluation of the Subsurface of Sites Earmarked for Aquaculture Ponds in the Amazon Region of Northern Brazil
Authors: Pena Ramon Wagner Torres , Oliva Pedro Andrés Chira , Abrunhosa Fernando Araújo
Published: October 2023

The present study evaluated the application of Ground Penetrating Radar and Electromagnetic Induction geophysical tools combined with sedimentology for the description of the subsurface of sites destined for the installation of ponds for an extensive freshwater fish farming system. Two areas with similar topographic characteristics (flat land near bodies of water) were investigated in the Amazon region of northern Brazil: Area 1—the future site of an aquaculture research center, and Area 2—an established fish farming operation. These tools performed well in the evaluation of the suitability of the terrain for the installation of aquaculture ponds. The application of these tools can, thus, be recommended for aquaculture projects, given that it provides advanced knowledge on the characteristics of the local soils, which is extremely important to guarantee the sustainability of any aquaculture operation. These data can help minimize the environmental impacts of the process, while maximizing the economic returns to the installation of an aquaculture operation.
Remote Control Device to Drive the Arm Gestures of an Assistant Humanoid Robot
Authors: Rubies Elena , Bitriá Ricard , Clotet Eduard , Palacín Jordi
Published: October 2023

This work presents a remote control device designed to drive the arm gestures of an assistant humanoid mobile robot. The remote control is a master device with two passive arms configured to replicate the four degrees of freedom of each arm of the original assistant humanoid robot and send this information to the robot. This configuration allows the mobile robot to directly replicate the position of the arms on the remote controller. The objective of this proposal is to provide the robot with enhanced non-verbal and pointing communication capabilities during human interaction or assistance. The master device registers the angular position of each joint of its passive arms and transmits this information to the mobile robot, which replicates it. The experimental evaluation of the system has shown that the humanoid robot is able to successfully replicate any gesture on the remote controller. The positions of the arms have been sampled at a frame rate of 20 ms, and the average telecontrol delay obtained in the gesture experiments has been 549 ms, without appreciable jumps or irregularities in the gestures. The conclusion is that the direct manipulation of the passive arms of the remote control device provides the APR-02 humanoid robot with enhanced non-verbal and pointing communication capabilities during human interaction or assistance.
Application of Deep Learning in the Early Detection of Emergency Situations and Security Monitoring in Public Spaces
Authors: Villegas-Ch William , Govea Jaime
Published: October 2023

This article addresses the need for early emergency detection and safety monitoring in public spaces using deep learning techniques. The problem of discerning relevant sound events in urban environments is identified, which is essential to respond quickly to possible incidents. To solve this, a method is proposed based on extracting acoustic features from captured audio signals and using a deep learning model trained with data collected both from the environment and from specialized libraries. The results show performance metrics such as precision, completeness, F1-score, and ROC-AUC curve and discuss detailed confusion matrices and false positive and negative analysis. Comparing this approach with related works highlights its effectiveness and potential in detecting sound events. The article identifies areas for future research, including incorporating real-world data and exploring more advanced neural architectures, and reaffirms the importance of deep learning in public safety.
Hypoxic Extracellular Matrix Preserves Its Competence after Expansion of Human MSCs under Physiological Hypoxia In Vitro
Authors: Matveeva Diana , Buravkov Sergey , Andreeva Elena , Buravkova Ludmila
Published: October 2023

Tissue-relevant O2 levels are considered as an important tool for the preconditioning of multipotent mesenchymal stromal cells (MSCs) for regenerative medicine needs. The present study investigated the quality and functions of the extracellular matrix (ECM) of MSCs under low O2 levels. Human adipose tissue-derived MSCs were continuously expanded under normoxia (20% O2, N) or “physiological” hypoxia (5% O2, Hyp). Decellularized ECM (dcECM) was prepared. The structure of the dcECM was analyzed using confocal laser and scanning electron microscopy. Collagen, dcECM-N, and dcECM-Hyp were recellularized with MSC-N and further cultured at normoxia. The efficacy of adhesion, spreading, growth, osteogenic potential, and paracrine activity of recellularized MSC-N were evaluated. At low O2, the dcECM showed an increased alignment of fibrillar structures and provided accelerated spreading of MSC-N, indicating increased dcECM-Hyp stiffness. We described O2-dependent “ECM-education” of MSC-N when cultured on dcECM-Hyp. This was manifested as attenuated spontaneous osteo-commitment, increased susceptibility to osteo-induction, and a shift in the paracrine profile. It has been suggested that the ECM after physiological hypoxia is able to ensure the maintenance of a low-commitment state of MSCs. DcECM, which preserves the competence of the natural microenvironment of cells and is capable of “educating” others, appears to be a prospective tool for guiding cell modifications for cell therapy and tissue engineering.
Correction: Zhu et al. Gait Analysis with Wearables Is a Potential Progression Marker in Parkinson’s Disease. Brain Sci. 2022, 12, 1213
Authors: Zhu Sha , Wu Zhuang , Wang Yaxi , Jiang Yinyin , Gu Ruxin , Zhong Min , Jiang Xu , Shen Bo , Zhu Jun , Yan Jun , Pan Yang , Zhang Li
Published: October 2023

In the original publication [...]
ARCH Is Bringing Asia Closer to the Rest of the World
Authors: Wijeratne Tissa , Ravishankar Krishnamurthy
Published: October 2023

As the immediate Past President (KR) of Asian Regional Consortium For Headache (ARCH) and the newly appointed President (TW) of ARCH, we are pleased to share our thoughts with the readers of MDPI [...]