bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Analysis of Mechanical In-Field Corn Residue Shredding Methods: Evaluating Particle Size Distribution and Rating of Structural Integrity of Corn Stalk Segments
Authors: Ramm Sebastian , Voßhenrich Hans Heinrich , Hasler Mario , Reckleben Yves , Hartung Eberhard
Published: February 2024

The European corn borer is a major pest of corn that overwinters in corn stubble and stalks. Shredding these residues disrupts the larvae’s habitat or directly harms them. A corn header has been engineered with a new type of cutting tool on its horizontal choppers, featuring sharp edges and dulled flails, to shred corn stubble near the soil surface. This study investigated the effect of the dulled flails on the shredding intensity of corn stover. Field trials compared flail knives with standard knives for particle size distribution of corn stover and structural integrity of corn stalk segments. Additionally, a common two-step method, which involved a standard knives-equipped corn header followed by tractor-driven flail mowers, was tested. The flail knives reduced the mean particle size by 3.6 mm compared to the standard knives. Subsequent processing with tractor-driven flail mowers, following the corn header using standard knives, led to a reduction in mean particle size by 11.8 mm. It also further reduced the number of incompletely destroyed stalk segments. However, completely intact internodes were scarce in all methods. Given that flail knives enhance shredding intensity without a second processing step, this concept is concluded to be effective for corn stover shredding.
Increased Mass-Rearing of Queens in High Royal-Jelly-Producing Honey Bee Colonies (Apis mellifera ligustica) Generates Smaller Queens with Comparable Fecundity
Authors: Ahmat Buajiram , Yang Ting , Ma Chuan , Zong Cheng
Published: February 2024

The mass rearing of high-quality queen bees is an essential beekeeping practice for producing new queens to maintain colony productivity. A strain of high royal-jelly-producing bees (RJBs; Apis mellifera ligustica) in China exhibits high potential for the rapid mass rearing of queens. To explore the potential changes in the quality of mass-reared queens, a set of morphometric traits and the sealed brood area were compared between the queens reared from 64 and 320 queen cells in RJB colonies. The increase in the queen cell number was found to induce a slightly but significantly reduced body weight and smaller wing length and thorax width in the reared queens at emergence. However, the ovariole number and sealed brood area, an indicator of the queen fecundity, were not observed to be significantly influenced. With respect to body weight and ovariole number, all the reared queens satisfied the current criteria for high-quality queens. Our findings provide evidence for the efficient mass production of high-quality queens using RJB colonies.
Diversity of Unusual Ribosomal Genes and Ecological Origin of Rice (Oryza spp.)
Authors: Tan Xiyu , Peng Guixiang , Muhammad Sajid , Kaleem Sidra , Jan Mehmood , Munir Raheel , Chen Xiaoyuan , Khattak Arif Ali , Abbas Abid Ali , Chen Yihang , Wang Xiaolin , Afzal Muhammad , Tan Zhiyuan
Published: February 2024

Tandemly organized rRNA genes are a typical example of a multigene family, where individual members evolve co-ordinately within—but independently between—species due to gene conversion and unequal crossing over. More frequently, in eukaryotic species with an interspecies hybrid origin, expression of unhomogenized rRNA genes from one progenitor is epigenetically silenced because of nucleolus dominance, and distinct rRNA genes may lose functionality and evolve faster. Interestingly, we obtained unusual ribosomal gene sequences from Oryza species that showed great diversity and did not appear in the present rice genomic sequence. The diversity of rDNA sequences indicated that the homogenization in rice is incomplete and explains the introgression of distinct rRNA gene families into ancestral rice genomes before speciation and continent separation. The divergent large subunit (LSU) ribosomal genes are expressed, some of them differentially, depending on the N fertilization of plants. Detection of differential transcripts of the rRNA genes suggested that rRNA gene families are not functionally equivalent. Phylogenetic analysis assigned Oryza species branching order to monocots, and monocot lineages probably have the same ecological origin by molecular clock calculation. Therefore, our results suggested that the geographical distances of continent-separation cause barriers to the gene flow and homogenization among Oryza species which requires further explanation.
Identifications of Seed Vigor-Related QTLs and Candidate Genes Combined Cultivated Soybean with Wild Soybean
Authors: Ma Shengnan , Feng Haojie , Sun Yiran , Yu Lin , Tang Chunshuang , Zhao Yanqiang , Xue Liansong , Wang Jinhui , Liu Chunyan , Xin Dawei , Chen Qingshan , Yang Mingliang
Published: February 2024

Soybean (Glycine max) is an economically important cash crop and food source that serves as a key source of high-quality plant-derived protein and oil. Seed vigor is an important trait that influences the growth and development of soybean plants in an agricultural setting, underscoring a need for research focused on identifying seed vigor-related genetic loci and candidate genes. In this study, a population consisting of 207 chromosome segment substitution lines (CSSLs) derived from the crossing and continuous backcrossing of the Suinong14 (improved cultivar, recurrent parent) and ZYD00006 (wild soybean, donor parent) soybean varieties was leveraged to identify quantitative trait loci (QTLs) related to seed vigor. The candidate genes detected using this approach were then validated through RNA-seq, whole-genome resequencing, and qPCR approaches, while the relationship between specific haplotypes and seed vigor was evaluated through haplotype analyses of candidate genes. Phenotypic characterization revealed that the seed vigor of Suinong14 was superior to that of ZYD00006, and 20 total QTLs were identified using the selected CSSLs. Glyma.03G256700 was also established as a seed vigor-related gene that was upregulated in high-vigor seeds during germination, with haplotypes for this candidate gene also remaining consistent with observed soybean seed vigor. The QTLs identified herein can serve as a foundation for future marker-assisted and convergent breeding efforts aimed at improving seed vigor. In addition, future molecular and functional research focused on Glyma.03G256700 has the potential to elucidate the signaling network and key regulatory mechanisms that govern seed germination in soybean plants.
Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes
Authors: Farid Muh , Anshori Muhammad Fuad , Rossi Riccardo , Haring Feranita , Mantja Katriani , Dirpan Andi , Larekeng Siti Halimah , Mustafa Marlina , Adnan Adnan , Tahara Siti Antara Maedhani , Amier Nirwansyah , Amal M. Alfan Ikhlasul , Sakinah Andi Isti
Published: February 2024

The fruit weight is an important guideline for breeders and farmers to increase marketable productions, although conventionally it requires destructive measurements. The combination of image-based phenotyping (IBP) approaches with multivariate analysis has the potential to further improve the line selection based on economical trait, like fruit weight. Therefore, this study aimed to evaluate the potential of image-derived phenotypic traits as proxies for individual fruits weight estimation using multivariate analysis. To this end, an IBP experimentation was carried out on five populations of low-land tomato. Specifically, the Mawar (M; 10 plants), Karina (K; 10 plants), and F2 generation cross (100 lines) samples were used to extract training data for the proposed estimation model, while data derived from M/K//K backcross population (35 lines) and F5 population (50 lines) plants were used for destructive and non-destructive validation, respectively. Several phenotypic traits were extracted from each imaged tomato fruit, including the slice and whole fruit area (FA), round (FR), width (FW), height (FH), and red (RI), green (GI) and blue index (BI), and used as inputs of a genetic- and multivariate-based method for non-destructively predicting its fresh weight (FFW). Based on this research, the whole FA has the greatest potential in predicting tomato FFW regardless to the analyzed cultivar. The relevant model exhibited high power in predicting FFW, as explained by R2-adjusted, R2-deviation and RMSE statistics obtained for calibration (81.30%, 0.20%, 3.14 g, respectively), destructive (69.80%, 0.90%, 4.46 g, respectively) and non-destructive validation (80.20%, 0.50%, 2.12 g, respectively). These results suggest the potential applicability of the proposed IBP approach in guiding field robots or machines for precision harvesting based on non-destructive estimations of fruit weight from image-derived area, thereby enhancing agricultural practices in lowland tomato cultivation.
High Exposure to Livestock Pathogens in Southern Pudu (Pudu puda) from Chile
Authors: Hidalgo-Hermoso Ezequiel , Verasay Caviedes Sebastián , Pizarro-Lucero Jose , Cabello Javier , Vicencio Rocio , Celis Sebastián , Ortiz Carolina , Kemec Ignacio , Abuhadba-Mediano Nour , Asencio Ronie , Vera Frank , Valencia Carola , Lagos Rocio , Moreira-Arce Dario , Salinas Fernanda , Ramirez-Toloza Galia , Muñoz-Quijano Raul , Neira Victor , Salgado Rodrigo , Abalos Pedro , Parra Barbara , Cárdenas-Cáceres Simone , Muena Nicolás A. , Tischler Nicole D. , Del Pozo Itziar , Aduriz Gorka , Esperon Fernando , Muñoz-Leal Sebastián , Aravena Paula , Alegría-Morán Raúl , Cuadrado-Matías Raul , Ruiz-Fons Francisco
Published: February 2024

A significant gap in exposure data for most livestock and zoonotic pathogens is common for several Latin America deer species. This study examined the seroprevalence against 13 pathogens in 164 wild and captive southern pudu from Chile between 2011 and 2023. Livestock and zoonotic pathogen antibodies were detected in 22 of 109 wild pudus (20.18%; 95% CI: 13.34–29.18) and 17 of 55 captive pudus (30.91%; 95% CI: 19.52–44.96), including five Leptospira interrogans serovars (15.38% and 10.71%), Toxoplasma gondii (8.57% and 37.50%), Chlamydia abortus (3.03% and 12.82%), Neospora caninum (0.00% and 9.52%), and Pestivirus (8.00% and 6.67%). Risk factors were detected for Leptospira spp., showing that fawn pudu have statistically significantly higher risk of positivity than adults. In the case of T. gondii, pudu living in “free-range” have a lower risk of being positive for this parasite. In under-human-care pudu, a Pestivirus outbreak is the most strongly suspected as the cause of abortions in a zoo in the past. This study presents the first evidence of Chlamydia abortus in wildlife in South America and exposure to T. gondii, L. interrogans, and N. caninum in wild ungulate species in Chile. High seroprevalence of livestock pathogens such as Pestivirus and Leptospira Hardjo in wild animals suggests a livestock transmission in Chilean template forest.
Contribution of elovl5a to Docosahexaenoic Acid (DHA) Synthesis at the Transcriptional Regulation Level in Common Carp, Cyprinus carpio
Authors: Zhang Hanyuan , Li Peizhen , Zhu Youxiu , Jiang Yanliang , Feng Jianxin , Zhao Zixia , Xu Jian
Published: February 2024

Docosahexaenoic acid (DHA) is an essential nutrient for humans and plays a critical role in human development and health. Freshwater fish, such as the common carp (Cyprinus carpio), have a certain degree of DHA biosynthesis ability and could be a supplemental source of human DHA needs. The elongase of very-long-chain fatty acid 5 (Elovl5) is an important enzyme affecting polyunsaturated fatty acid (PUFA) biosynthesis. However, the function and regulatory mechanism of the elovl5 gene related to DHA synthesis in freshwater fish is not clear yet. Previous studies have found that there are two copies of the elovl5 gene, elovl5a and elovl5b, which have different functions. Our research group found significant DHA content differences among individuals in Yellow River carp (Cyprinus carpio var.), and four candidate genes were found to be related to DHA synthesis through screening. In this study, the expression level of elovl5a is decreased in the high-DHA group compared to the low-DHA group, which indicated the down-regulation of elovl5a in the DHA synthesis pathways of Yellow River carp. In addition, using a dual-luciferase reporter gene assay, we found that by targeting the 3’UTR region of elovl5a, miR-26a-5p could regulate DHA synthesis in common carp. After CRISPR/Cas9 disruption of elovl5a, the DHA content in the disrupted group was significantly higher than in the wildtype group; meanwhile, the expression level of elovl5a in the disrupted group was significantly reduced compared with the wildtype group. These results suggest that elovl5a may be down-regulating DHA synthesis in Yellow River carp. This study could provide useful information for future research on the genes and pathways that affect DHA synthesis.
A Five-Year Analysis of Antibiotic Resistance Trends among Bacteria Identified in Positive Urine Samples in a Tertiary Care Hospital from Bucharest, Romania
Authors: Borcan Alina Maria , Radu Georgiana , Simoiu Mădălina , Costea Elena Liliana , Rafila Alexandru
Published: February 2024

The rise of multidrug-resistant bacteria (MDR) has resulted in limited treatment options and poorer outcomes for patients. The objective of this study was to analyze the overall antibiotic resistance trends and distribution for pathogens identified in urine samples at the National Institute of Infectious Diseases “Prof. Dr. Matei Balș” from Bucharest, Romania, over a 5-year period. Antibiotic susceptibility testing was performed using automatic systems and the disk diffusion method. ESBL- and carbapenemases-producing strains were identified using immunochromatography tests, and ROSCO Diagnostica kits were used for definitive confirmation. All results were interpreted according to EUCAST clinical breakpoints. Gram-negative rods (GNR) had overall resistance rates higher than 50% for penicillin and 40% for 3rd- and 4th-generation cephalosporins. Escherichia coli resistance to fosfomycin (3%) and nitrofurantoin (2%) remains low, and 33.30% of E. coli, 48% of Klebsiella spp., and 37% of Pseudomonas aeruginosa isolates were multidrug-resistant (MDR). All Acinetobacter baumannii isolates were MDR by the last year of the study. For Gram-positive cocci (GPC), 37% of all Enterococcus faecium strains and 2% of Enterococcus faecalis were vancomycin-resistant (VRE). E. coli’s incidence in UTIs’ etiology is on a downward trend. The incidence of Klebsiella spp. and GPCs is rising. Antibiotic stewardship strategies should be implemented after carefully considering regional variations in etiology and resistance trends.
Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in Resource-Constrained Environments
Authors: Doniec Rafał , Berepiki Eva Odima , Piaseczna Natalia , Sieciński Szymon , Piet Artur , Irshad Muhammad Tausif , Tkacz Ewaryst , Grzegorzek Marcin , Glinkowski Wojciech
Published: February 2024

Cardiovascular diseases (CVDs) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appropriate counseling and medication, which can effectively manage the condition and improve patient outcomes. This study introduces an innovative ontology-based model for the diagnosis of CVD, aimed at improving decision support systems in healthcare. We developed a database model inspired by ontology principles, tailored for the efficient processing and analysis of CVD-related data. Our model’s effectiveness is demonstrated through its integration into a web application, showcasing significant improvements in diagnostic accuracy and utility in resource-limited settings. Our findings indicate a promising direction for the application of artificial intelligence (AI) in early CVD detection and management, offering a scalable solution to healthcare challenges in diverse environments.
Analysis of Characteristics of the Electric Field Induced by an Angularly Rotating and Oscillating Magnetic Object
Authors: Zhang Jiawei , Xiao Dawei , Xie Taotao , Ji Qing
Published: February 2024

A mathematical model for an electric field induced by an angularly oscillating magnetic dipole was proposed with magnetic vector potential to analyze the characteristics of the electric field induced by a rotating and angularly oscillating magnetic object. This mathematical model was constructed for the electric field induced by a magnetic object oscillating at a certain angle. On this basis, the phase relationship among the three components of the induced electric field was analyzed (defining the right-hand Cartesian coordinate system). Evidently, a phase difference of π/2 always existed between the horizontal components of the electric field induced by a magnetic dipole rotating around the z-axis. The phase difference between the vertical and transverse components in the x–z plane was also π/2. A phase difference of π was observed in the y–z plane. The above theoretical analysis was verified through simulation and experiment. The results showed that the frequency of the induced electric field was related to the angular velocity and angle of rotation. The amplitude was associated with the magnetic moment and the angular velocity and angle of oscillation. The maximum amplitude did not exceed the amplitude of the electric field induced by a magnetic object angularly oscillating at the same velocity. With regard to the amplitude and phase relationship, the three components of the induced electric field measured in the experiment were consistent with the results of the theoretical analysis.
Alfalfa Stalk Crushing Simulation Test and Parameter Optimization Method
Authors: Ma Xueting , You Yong , Yang Deqiu , Wang Decheng , Hui Yunting , Li Daoyi , Wu Haihua , Feng Bowen
Published: February 2024

To investigate the impact of different cutter structures on the crushing effect of forage stalks at various rotational speeds, this study designed five types of crushing cutters. The effects of cutter structure and rotational speed on the crushing effect of the forage crusher were examined using the discrete element method, a single-factor test. An orthogonal test was conducted, with the percentage of bond breakage as the evaluation index, and tool type and tool speed as influencing factors. The results of the orthogonal test were analyzed using range analysis. The findings revealed that the quality of alfalfa stalk crushing varied depending on the crushing structure and rotational speed. Within a certain rotational speed range, the crushing effect improved as the rotational speed increased. However, beyond a certain value, the improvement in the crushing effect became slower. Notably, the hob-type crushing structure exhibited the best crushing effect at 2400 r/min.
Enhancing Emotion Recognition through Federated Learning: A Multimodal Approach with Convolutional Neural Networks
Authors: Simić Nikola , Suzić Siniša , Milošević Nemanja , Stanojev Vuk , Nosek Tijana , Popović Branislav , Bajović Dragana
Published: February 2024

Human–machine interaction covers a range of applications in which machines should understand humans’ commands and predict their behavior. Humans commonly change their mood over time, which affects the way we interact, particularly by changing speech style and facial expressions. As interaction requires quick decisions, low latency is critical for real-time processing. Edge devices, strategically placed near the data source, minimize processing time, enabling real-time decision-making. Edge computing allows us to process data locally, thus reducing the need to send sensitive information further through the network. Despite the wide adoption of audio-only, video-only, and multimodal emotion recognition systems, there is a research gap in terms of analyzing lightweight models and solving privacy challenges to improve model performance. This motivated us to develop a privacy-preserving, lightweight, CNN-based (CNNs are frequently used for processing audio and video modalities) audiovisual emotion recognition model, deployable on constrained edge devices. The model is further paired with a federated learning protocol to preserve the privacy of local clients on edge devices and improve detection accuracy. The results show that the adoption of federated learning improved classification accuracy by ~2%, as well as that the proposed federated learning-based model provides competitive performance compared to other baseline audiovisual emotion recognition models.
Comparison of Modern Deep Learning Models for Speaker Verification
Authors: Brydinskyi Vitalii , Khoma Yuriy , Sabodashko Dmytro , Podpora Michal , Khoma Volodymyr , Konovalov Alexander , Kostiak Maryna
Published: February 2024

This research presents an extensive comparative analysis of a selection of popular deep speaker embedding models, namely WavLM, TitaNet, ECAPA, and PyAnnote, applied in speaker verification tasks. The study employs a specially curated dataset, specifically designed to mirror the real-world operating conditions of voice models as accurately as possible. This dataset includes short, non-English statements gathered from interviews on a popular online video platform. The dataset features a wide range of speakers, with 33 males and 17 females, making a total of 50 unique voices. These speakers vary in age from 20 to 70 years old. This variety helps in thoroughly testing speaker verification models. This dataset is especially useful for research on speaker verification with short recordings. It consists of 10 clips for each person, each clip being no longer than 10 s, adding up to 500 recordings in total. The total length of all recordings is about 1 h and 30 min, which averages to roughly 100 s for each speaker. This dataset is a valuable tool for research in speaker verification, particularly for studies involving short audio clips. The performance of these models is evaluated using common biometric metrics such as false acceptance rate (FAR), false rejection rate (FRR), equal error rate (EER) and detection cost function (DCF). The results reveal that the TitaNet and ECAPA models stand out by presenting the lowest EER (1.91% and 1.71%, respectively) and thus exhibiting higher discriminative features, ensuring, on the one hand, a reduction in intra-class distance (the same speaker), and, on the other hand, maximizing the distance between different speaker embeddings. This analysis also highlights the ECAPA model’s advantageous balance of performance and efficiency, achieving an inference time of 69.43 milliseconds, slightly longer than the PyAnnote models. This study not only compares the performance of models but also provides a comparative analysis of respective model embeddings, offering insights into their strengths and weaknesses. The presented findings serve as a foundation for guiding future research in speaker verification, especially in the context of short audio samples or limited data. This may be particularly relevant for applications requiring quick and accurate speaker identification from short voice clips.
Bilateral Activity of Spine Extensors and Rotators during Asymmetric Lumbar Stabilization Exercises Executed in Prone, Quadruped, and Standing-Prone Positions
Authors: Biscarini Andrea , Losavio Raffaele , Bartoli Stefano , Calandra Andrea , Dieni Cristina Vittoria , Contemori Samuele , Panichi Roberto
Published: February 2024

(1) Background: Most daily activities and sport gestures involve asymmetric movement patterns of the upper and lower extremities, transferring asymmetric mechanical loadings to the spine. Therefore, asymmetric lumbar stabilization exercises are frequently prescribed in athletic programs and preventive/rehabilitation interventions. This study analyzed the bilateral activity of the thoracic erector spinae (ES), lumbar multifidus (MF), external oblique (EO), and internal oblique (IO) during asymmetric lumbar stabilization exercises executed in prone, quadruped, and standing-prone positions, rising an upper and/or lower limb in all possible combinations. A limited subset of these data has been previously published in earlier studies. (2) Methods: Surface EMG signals were bilaterally recorded from the selected muscles using wireless EMG sensors. (3) Results: ES, MF, and oblique muscles’ activity was significantly higher in prone, standing-prone, and quadruped positions, respectively, and was maximized by specific limb rise combinations (up to 69%, 64%, 34%, and 24% maximum-voluntary-isometric-contraction for ES, MF, EO, and IO). The bilateral difference in muscle activation was significantly higher in the quadruped position and revealed different strategies used to stabilize the body in response to the different exercise conditions. (4) Conclusions: The study results can provide deeper insights into the stabilizing function of the lumbar and oblique muscles and aid in designing optimal progressions for lumbar stabilization exercises.
The Microstructural Investigation and the Temperature-Changing Separation of Brine with a High Mg/Li Ratio
Authors: Cheng Danxu , An Dong , Cheng Huaigang , Cui Xiangmei
Published: February 2024

The difficult separation of magnesium–lithium has always been a problem that impedes the comprehensive utilization of salt lake brine resources. In this paper, a method for the separation of magnesium and lithium based on the crystallization of magnesium sulfate at high-temperature supersaturation and a low viscosity was investigated. The microstructure of soluble solutions was analyzed, and the results showed that, in a single-salt solution, controlling the temperature can change the contact ion pair structure of MgSO4 solution, and the arrangement of SO42− and H2O in the second hydration layer changes. In the Li2SO4 solution, the hydrogen bonds between SO42− and H2O break, and the surrounding water structure changes, breaking the similarity of the microstructure of magnesium–lithium and enhancing the separation effect. In a multi-ion system, the change in water structure in the solution decreases with the increase in Cl− concentration. Controlling the temperature of salt lake brine with different magnesium–lithium mass ratios, it was found that the magnesium–lithium mass ratio in the brine could be reduced by one-third; when the magnesium–lithium mass ratio was 10:1~160:1, the loss of lithium could be controlled within 5%, but when the magnesium–lithium mass ratio was 5:1, the loss of lithium was 25.06%. The main reason for lithium loss is that Li2SO4 in the liquid phase enters the solid phase as a cluster and is entrapped during the MgSO4 crystallization process. The entire experiment shows that controlling the temperature process is more suitable for salt lake brine with a high magnesium–lithium ratio.
Synthesis of High-Precision Sub-Micron CaCO3 Anticancer Drug Carriers from Coral Remains
Authors: Chen Pin-Han , Chen Wei-Sheng , Chen Szu-An , Chen Wei-Chung
Published: February 2024

Calcium carbonate (CaCO3) particles have attracted increasing attention as a promising material for drug delivery systems. In this study, coral remains were utilized as a raw material for a novel drug carrier. A series of pre-treatment and parameter experiments were conducted to synthesize sub-micron spherical CaCO3 particles. The CaCO3 particles exhibited uniform size distribution, with the minimum mean size being only 344 nm. The effects on the CaCO3 crystal phases and particle sizes were also discussed in this study. Drug loading experiments were also conducted to assess the feasibility of the CaCO3 drug carrier. We loaded TRITC-Dextran into CaCO3 particles for the simulation experiments. The loading capacity reached up to 9.6 wt.%, which was as high as common drug carriers such as liposomes. In this study, we aimed not only to tackle the local environmental issues caused by coral remains, but also to synthesize a suitable drug carrier for cancer therapy using the outstanding properties and low cost of CaCO3.
Personalization of Affective Models Using Classical Machine Learning: A Feasibility Study
Authors: Kargarandehkordi Ali , Kaisti Matti , Washington Peter
Published: February 2024

Emotion recognition, a rapidly evolving domain in digital health, has witnessed significant transformations with the advent of personalized approaches and advanced machine learning (ML) techniques. These advancements have shifted the focus from traditional, generalized models to more individual-centric methodologies, underscoring the importance of understanding and catering to the unique emotional expressions of individuals. Our study delves into the concept of model personalization in emotion recognition, moving away from the one-size-fits-all approach. We conducted a series of experiments using the Emognition dataset, comprising physiological and video data of human subjects expressing various emotions, to investigate this personalized approach to affective computing. For the 10 individuals in the dataset with a sufficient representation of at least two ground truth emotion labels, we trained a personalized version of three classical ML models (k-nearest neighbors, random forests, and a dense neural network) on a set of 51 features extracted from each video frame. We ensured that all the frames used to train the models occurred earlier in the video than the frames used to test the model. We measured the importance of each facial feature for all the personalized models and observed differing ranked lists of the top features across the subjects, highlighting the need for model personalization. We then compared the personalized models against a generalized model trained using data from all 10 subjects. The mean F1 scores for the personalized models, specifically for the k-nearest neighbors, random forest, and dense neural network, were 90.48%, 92.66%, and 86.40%, respectively. In contrast, the mean F1 scores for the generic models, using the same ML techniques, were 88.55%, 91.78% and 80.42%, respectively, when trained on data from various human subjects and evaluated using the same test set. The personalized models outperformed the generalized models for 7 out of the 10 subjects. The PCA analyses on the remaining three subjects revealed relatively little facial configuration differences across the emotion labels within each subject, suggesting that personalized ML will fail when the variation among data points within a subject’s data is too low. This preliminary feasibility study demonstrates the potential as well as the ongoing challenges with implementing personalized models which predict highly subjective outcomes like emotion.
Improving Low-Frequency Panel Absorbers with Two-Dimensional Acoustic Black Hole
Authors: Funk Michael , Özer Mehmet Sait , Altinsoy M. Ercan
Published: February 2024

Many rooms struggle with the absorption of low-frequency sound due to its long wavelengths. The integration of existing solutions into these spaces is often challenging due to their intricate installations and large depths. To address this problem, a new type of resonance absorber has been developed: the Distributed Mode Absorber (DMA). It consists of a thin vibrating front panel and a volume of enclosed air behind it. This straightforward structure can be utilized to create acoustically functional furniture that can be seamlessly incorporated into rooms. This article is devoted to the structural optimization of the DMA front panel, using the Acoustic Black Hole (ABH) effect known within structural dynamics. A numerical model is constructed using a Finite Element Analysis (FEA) and examined numerically. Several geometric parameters of the ABH are studied with regard to their influence on the vibrations of the front panel. Prototypes are developed and manufactured based on these insights. The quality of the numerical model is verified during the subsequent validation. Finally, the sound absorption of the improved DMA is compared with that of the reference DMA.
Research on a Feature Enhancement Extraction Method for Underwater Targets Based on Deep Autoencoder Networks
Authors: Ji Fang , Li Guonan , Lu Shaoqing , Ni Junshuai
Published: February 2024

The low-frequency line spectrum of the radiated noise signals of hydroacoustic targets contains features describing the intrinsic properties of the target that make the target susceptible to exposure. In order to extract the line spectral features of underwater acoustic targets, a method combining image processing and a deep autoencoder network (DAE) is proposed in this paper to enhance the low-frequency weak line spectrum of underwater targets in an extremely low signal-to-noise ratio environment based on the measured data of large underwater vehicles. A Gauss–Bernoulli restricted Boltzmann machine (G–BRBM) for real-value signal processing was designed and programmed by introducing a greedy algorithm. On this basis, the encoding and decoding mechanism of the DAE network was used to eliminate interference from environmental noise. The weak line spectrum features were effectively enhanced and extracted under an extremely low signal-to-noise ratio of 10–300 Hz, after which the reconstruction results of the line spectrum features were obtained. Data from large underwater vehicles detected by far-field sonar arrays were processed and the results show that the method proposed in this paper was able to adaptively enhance the line spectrum in a data-driven manner. The DAE method was able to achieve more than double the extractable line spectral density in the frequency band of 10–300 Hz. Compared with the traditional feature enhancement extraction method, the DAE method has certain advantages for the extraction of weak line spectra.
Effects of Mechanical Vibration during an Incremental Slide Board Skating Test on Physiological and Movement Variability Parameters
Authors: Gisbert-Orozco Jose F. , Moras Gerard , Toro-Román Víctor , Illera-Domínguez Víctor , Pérez-Chirinos Buxadé Carla , Fernández-Valdés Bruno
Published: February 2024

The physiological, kinematic, and performance benefits of slide board (SB) training are well established. However, there is limited research investigating the potential effects offered by combining SB training with whole-body vibration (WBV). This study aimed to evaluate the impact of WBV on movement variability (MV) and physiological parameters during an incremental SB skating test. Ten elite ice hockey players (20.4 ± 2.07 years; 1.79 ± 0.05 m; 75.97 ± 5.44 kg; 23.64 ± 1.64 body mass index) participated in this study. An incremental test was conducted on the SB under two conditions, randomized in order: WBV (30 Hz) and non-WBV (0 Hz). The incremental test rhythms were established at 30, 35, 40, and 45 Hz. Participants performed the exercise on the SB at each rhythm for four minutes, for a total of 16 mins. MV, subjective perception of effort (RPE), heart rate (HR), and ergospirometric parameters were assessed. Differences were observed between rhythms in ergospirometric parameters and HR, increasing directly with rhythm (p < 0.05). Regarding differences between conditions, MV was higher when the incremental test was performed with WBV (p < 0.01). The addition of WBV during SB training resulted in a rise in MV without affecting physiological parameters.
The Effect of a Magnetic Field on the Transport of Functionalized Magnetite Nanoparticles into Yeast Cells
Authors: Dobosz Bernadeta , Gunia Eliza , Kotarska Klaudia , Schroeder Grzegorz , Kurczewska Joanna
Published: February 2024

Magnetic nanoparticles are of great interest to scientists as potential drug carriers. Therefore, it is essential to analyze the processes these nanoparticles undergo at the cellular level. The present paper demonstrates the effect of a constant and rotating magnetic field on penetration of TEMPOL-functionalized magnetite nanoparticles into yeast cells. The interactions between nanoparticles and yeast cells without and with a magnetic field were studied using electron spin resonance spectroscopy (ESR). The results showed that the ESR method can monitor the effect of a magnetic field on the magnetite nanoparticle penetration rate into the cells.
Additive Manufacturing in Underwater Applications
Authors: Korniejenko Kinga , Gądek Szymon , Dynowski Piotr , Tran Doan Hung , Rudziewicz Magdalena , Pose Sebastian , Grab Thomas
Published: February 2024

Additive manufacturing (AM), commonly named 3D printing, is a promising technology for many applications. It is the most viable option for widespread use in automated construction processes, especially for harsh environments such as underwater. Some contemporary applications of this technology have been tested in underwater environments, but there are still a number of problems to be solved. This study focuses on the current development of 3D printing technology for underwater applications, including the required improvements in the technology itself, as well as new materials. Information about underwater applications involving part fabrication via AM is also provided. The article is based on a literature review that is supplemented by case studies of practical applications. The main findings show that the usage of additive manufacturing in underwater applications can bring a number of advantages—for instance, increasing work safety, limiting the environmental burden, and high efficiency. Currently, only a few prototype applications for this technology have been developed. However, underwater additive manufacturing is a promising tool to develop new, effective applications on a larger scale. The technology itself, as well as the materials used, still require development and optimization.
Multi-Layer Fusion 3D Object Detection via Lidar Point Cloud and Camera Image
Authors: Guo Yuhao , Hu Hui
Published: February 2024

Object detection is a key task in automatic driving, and the poor performance of small object detection is a challenge that needs to be overcome. Previously, object detection networks could detect large-scale objects in ideal environments, but detecting small objects was very difficult. To address this problem, we propose a multi-layer fusion 3D object detection network. First, a dense fusion (D-fusion) method is proposed, which is different from the traditional fusion method. By fusing the feature maps of each layer, more semantic information of the fusion network can be preserved. Secondly, in order to preserve small objects at the feature map level, we designed a feature extractor with an adaptive fusion module (AFM), which reduces the impact of the background on small objects by weighting and fusing different feature layers. Finally, an attention mechanism was added to the feature extractor to accelerate the training efficiency and convergence speed of the network by suppressing information that is irrelevant to the task. The experimental results show that our proposed approach greatly improves the baseline and outperforms most state-of-the-art methods on KITTI object detection benchmarks.
Evaluation of Periodontal Status and Oral Health Habits with Continual Dental Support for Young Patients with Hemophilia
Authors: Kametani Mariko , Akitomo Tatsuya , Usuda Momoko , Kusaka Satoru , Asao Yuria , Nakano Masashi , Iwamoto Yuko , Tachikake Meiko , Ogawa Masashi , Kaneki Ami , Nishimura Taku , Niizato Noriko , Mitsuhata Chieko , Kozai Katsuyuki , Nomura Ryota
Published: February 2024

Hemophilia is a congenital disorder associated with impaired blood clotting. Routine dental intervention to prevent oral bleeding in patients with hemophilia is considered important, but its effectiveness remains unknown. In the present study, we evaluated the effect of continual dental support on periodontal status and oral health habits in young patients with hemophilia. Of the 168 young patients with hemophilia who visited our clinic for 5 years, we selected subjects who had visited annually since 2015 and were in the mixed and permanent dentitions. To evaluate the periodontal status of these subjects, Community Periodontal Index (CPI) values in the molars and anterior teeth were measured. In addition, a questionnaire regarding oral health habits, including floss use, frequency of brushing by parents, and attending a family dentist, was administered to the subjects and their parents. In the patients with mixed dentition, the CPI values for the upper right molars and lower left central incisor decreased significantly in later years compared with the first year (p < 0.05). In the patients with permanent dentition, only one year recorded a significant decrease in CPI values compared with the first year (p < 0.05), localized in the upper right molars. The results of the questionnaire revealed that continual dental support improved dental floss use and the frequency of brushing by parents only in the mixed dentition group. Furthermore, these oral health habits significantly affected CPI values only in the mixed dentition group (p < 0.01). These results suggest that continual dental support improves the periodontal condition and oral health habits of hemophilic patients, especially those with mixed dentition.
Synthesis of Thiophene-Fused Siloles through Rhodium-Catalyzed Trans-Bis-Silylation
Authors: Naka Akinobu , Inoue Maho , Kawabe Haruna , Kobayashi Hisayoshi
Published: February 2024

Rhodium-catalyzed reactions of 3-ethynyl-2-pentamethyldisilanylthiophene derivatives (1a–1c) have been reported. At 110 °C, compounds 1a–1c reacted in the presence of a rhodium complex catalyst, yielding thiophene-fused siloles (2a–2c) through intramolecular trans-bis-silylation. To understand the production of 2a from 1a, the mechanism was investigated using density functional theory (DFT) calculations.
Climate Driver Influences on Prediction of the Australian Fire Behaviour Index
Authors: Taylor Rachel , Marshall Andrew G. , Crimp Steven , Cary Geoffrey J. , Harris Sarah
Published: February 2024

Fire danger poses a pressing threat to ecosystems and societies worldwide. Adequate preparation and forewarning can help reduce these threats, but these rely on accurate prediction of extreme fire danger. With the knowledge that climatic conditions contribute heavily to overall fire danger, this study evaluates the skill with which episodes of extreme fire danger in Australia can be predicted from the activity of large-scale climate driver patterns. An extremal dependence index for extreme events is used to depict the historical predictive skill of the Australian Bureau of Meteorology’s subseasonal climate prediction system in replicating known relationships between the probability of top-decile fire danger and climate driver states at a lead time of 2–3 weeks. Results demonstrate that the El Niño Southern Oscillation, Southern Annular Mode, persistent modes of atmospheric blocking, Indian Ocean Dipole and Madden-Julian Oscillation are all key for contributing to predictability of fire danger forecasts in different regions during critical fire danger periods. Northwest Australia is found to be particularly predictable, with the highest mean index differences (>0.50) when certain climate drivers are active, compared with the climatological index mean. This integrated approach offers a valuable resource for decision-making in fire-prone regions, providing greater confidence to users relying on fire danger outlooks for key management decisions, such as those involved in the sectors of national park and forest estate management, agriculture, emergency services, health and energy. Furthermore, the results highlight strengths and weaknesses in both the Australian Fire Danger Rating System and the operational climate model, contributing additional information for improving and refining future iterations of these systems.
The Function of Root Exudates in the Root Colonization by Beneficial Soil Rhizobacteria
Authors: Chen Lin , Liu Yunpeng
Published: February 2024

Soil-beneficial microbes in the rhizosphere play important roles in improving plant growth and health. Root exudates play key roles in plant–microbe interactions and rhizobacterial colonization. This review describes the factors influencing the dynamic interactions between root exudates and the soil microbiome in the rhizosphere, including plant genotype, plant development, and environmental abiotic and biotic factors. We also discuss the roles of specific metabolic mechanisms, regulators, and signals of beneficial soil bacteria in terms of colonization ability. We highlight the latest research progress on the roles of root exudates in regulating beneficial rhizobacterial colonization. Organic acids, amino acids, sugars, sugar alcohols, flavonoids, phenolic compounds, volatiles, and other secondary metabolites are discussed in detail. Finally, we propose future research objectives that will help us better understand the role of root exudates in root colonization by rhizobacteria and promote the sustainable development of agriculture and forestry.
Bacterial Endophytes from Legumes Native to Arid Environments Are Promising Tools to Improve Mesorhizobium–Chickpea Symbiosis under Salinity
Authors: Ben Gaied Roukaya , Sbissi Imed , Tarhouni Mohamed , Brígido Clarisse
Published: February 2024

Symbiotic nitrogen fixation is a major contributor of N in agricultural ecosystems, but the establishment of legume–rhizobium symbiosis is highly affected by soil salinity. Our interest is focused on the use of non-rhizobial endophytes to assist the symbiosis between chickpea and its microsymbiont under salinity to avoid loss of production and fertility. Our aims were (1) to investigate the impact of salinity on both symbiotic partners; including on early events of the Mesorhizobium-chickpea symbiosis, and (2) to evaluate the potential of four non-rhizobial endophytes isolated from legumes native to arid regions (Phyllobacterium salinisoli, P. ifriqiyense, Xanthomonas translucens, and Cupriavidus respiraculi) to promote chickpea growth and nodulation under salinity. Our results show a significant reduction in chickpea seed germination rate and in the microsymbiont Mesorhizobium ciceri LMS-1 growth under different levels of salinity. The composition of phenolic compounds in chickpea root exudates significantly changed when the plants were subjected to salinity, which in turn affected the nod genes expression in LMS-1. Furthermore, the LMS-1 response to root exudate stimuli was suppressed by the presence of salinity (250 mM NaCl). On the contrary, a significant upregulation of exoY and otsA genes, which are involved in exopolysaccharide and trehalose biosynthesis, respectively, was registered in salt-stressed LMS-1 cells. In addition, chickpea co-inoculation with LMS-1 along with the consortium containing two non-rhizobial bacterial endophytes, P. salinisoli and X. translucens, resulted in significant improvement of the chickpea growth and the symbiotic performance of LMS-1 under salinity. These results indicate that this non-rhizobial endophytic consortium may be an appropriate ecological and safe tool to improve chickpea growth and its adaptation to salt-degraded soils.