bluuebunny/crossref_metadata_2025 huggingface dataset:
Glove versus controller: the effect of VR gloves and controllers on presence, embodiment, and cognitive absorption
Authors: Palombo Raphael , Weber Sebastian , Wyszynski Marc , Niehaves Björn
Published: March 2024

Introduction: Using our own hands allows humans to interact with the real world, as we learn from an early age. Virtual reality (VR) gloves allow a similar interaction in VR by transferring hand movements through natural mapping. Research outside the VR domain has already shown that this process creates a high level of presence and perceived naturalness. Research in the VR context, on the other hand, is still in an early stage and lacks explorative qualitative research following a human-centered approach and including the direct perceptions of users on mapped controls in system design. Against that background, this research investigates natural mapping in the VR context qualitatively. The study examines how participants experience VR input devices with different degrees of natural mapping (VR gloves, a Valve index controller, and an HTC Vive controller) on perceived naturalness, spatial presence, embodiment, and cognitive absorption.

Methods: A focus group (N = 20 aged 22–36) did the VR experience with the devices and was asked about their experience in semi-structured interviews. Questions focused on perceived naturalness, spatial presence, cognitive absorption, and embodiment with the three devices. Data were analyzed using qualitative content analysis.

Results: Feedback on spatial presence was widely positive for the VR glove due to the highly natural perceived movement capabilities. Mapping with the partly mapped index controller was also seen as natural and immersing if the movement matched the operated actions in the system. Participants mainly perceived the highest degree of cognitive absorption and embodiment while doing the task with the VR glove.

Discussion: The findings indicate that the natural mapping capabilities of VR input devices strongly influence spatial presence. The VR glove stands out while being able to induce a feeling of embodiment in most cases. Furthermore, participants reported a connection between natural mapping and perceived cognitive absorption in the task.
Efficacy of physical activity shared between parents and children to improve sports initiation in the M.A.M.I.deporte® program
Authors: Cueto-Martín Belén , De la Cruz-Márquez Juan Carlos , Burgueño-Menjíbar Rafael , García-Mármol Eduardo
Published: March 2024

Objective

To determine if the active methodology for improving sports initiation (M.A.M.I.deporte®) shared between children and parents successfully promotes children in sports activities, maintains their activity and improves long-term adherence.

Participants

The study involved 118 participants aged between 2 and 11 years (6.3 ± 2.3). In the first season, 34 participated (16 girls; 18 boys); in the second season, 46 participated (22 girls; 24 boys) and in the third season, 38 participated (19 girls; 19 boys).

Methodology

It was carried out from October to June over three academic years for two hours a week. Every 4 sessions a different sporting activity was carried out, planned so that parents and children could practise them, simultaneously.

Analysis

At the beginning and end of each period, a survey was carried out on the sports activities in which the participants had started. If participants remained in the activity, the survey was face-to-face and if participants no longer attended the activity, they were contacted by telephone. Descriptive values were obtained for the variables in absolute and percentage form and a repeated measures anova was performed.

Results

Vigorous physical activity performed was 3.82 ± 1.16 h/week in the first year, 3.38 ± 1.59 in the second year and 2.99 ± 1.46 in the third year with no significant differences between any of the years. 32.20% joined other sporting activities and only 6.78% gave up vigorous physical activity.

Conclusion

Joint activity of parents and children contributed to maintaining vigorous physical activity at the recommended levels in the child population with only 6.78% (n = 8) of the participants dropping out.
Exploring popular information sources and determinants of farmers’ access to agricultural extension services in the Indo-Gangetic plains
Authors: Sahu Subhashree , Bishnoi Sitaram , Sharma Ph. Romen , Satyapriya  , Mahra Girijesh Singh , Burman Rajarshi Roy , Barua Sukanya , Misha Madhavan M. , Sangeetha V. , Sinha Sanjeev Kumar , Singh Rahul , Wason Monika , Joshi Pratibha , Sharma Shailendra
Published: March 2024

A study was undertaken to analyse farmers’ access to various agricultural extension service sources, their preferences and to delineate underlying determinants for their access. The study used NSSO 77th survey dataset of 14,782 households of IGP states (Bihar, Haryana, Punjab, Uttar Pradesh, West Bengal). Farmers’ preferences varied, with private agencies—particularly input dealers—emerging as the top choice, followed by traditional mass media channels and the public extension system. Utility of Cooperative model, and farmer-based organizations have not yet been fully explored for information needs. The inputs (seeds, fertilizers, plant protection) were the most sought-after information. However, in an era of changing needs, farmers should strive to acquire additional information on aspects such as marketing, climate change, and post-harvest functions. The type of information sought by the farmers, influences their preferred sources of extension services. Irrespective of the source, the degree of access diminishes with the decreasing landholding. Among the five IGP states, Haryana emerged as the champion of information access for farmers, while Bihar lagged. Multivariate probit analysis reported that the likelihood of access to agricultural information sources was positively influenced by age, gender, education, size of operational landholding, irrigated area, and sale of produce at MSP. The study suggests making the extension services for small and socio-economically marginalized farmers more inclusive. Inclusiveness of extension services is essential for sustainability because it ensures that all farmers, regardless of their landholding, gender, age, caste, etc., have access to knowledge and resources they need to adopt improved agricultural practices and thus, secure prosperous livelihoods.
Brucellosis in camel, small ruminants, and Somali pastoralists in Eastern Ethiopia: a One Health approach
Authors: Ahad Abdullahi Adan , Megersa Bekele , Edao Bedaso Mammo
Published: March 2024

Brucellosis is a neglected bacterial zoonotic disease with economic and public health importance in pastoral communities of sub-Saharan Africa. A cross-sectional study was conducted from December 2021 to April 2022, to estimate the prevalence and identify the associated risk factors causing brucellosis in animals and associated with occupational diseases in humans from three selected districts of “the Somali Pastoral region,” Eastern Ethiopia. In this study, 1,000 serum samples were screened for anti-Brucella spp. antibodies using Rose Bengal Plate Test (RBPT) and further confirmed using a competitive enzyme-linked immunosorbent assay (cELISA). A structured questionnaire was used to collect the biodata of tested animals and animal attendants to test the association between explanatory and outcome variables. The overall animal level prevalence was 5% (95% CI, 6.1–7.2.0) in small ruminants, 2.9% (95% CI, 1.5–4.9) in camels, and 2.0% (95% CI, 0.2–3.7) in occupationally linked humans. Herd size and herd history of retained fetal membranes were risk factors associated with Brucella spp. seropositivity in animals (p < 0.05). Disposing of retained fetal membranes was significantly associated (p < 0.05) with Brucella spp. seropositivity in humans. Evidence of brucellosis in various livestock species and associated seropositivity in humans indicates the need for a coordinated One Health approach, considering sociocultural dynamics of pastoral communities in controlling brucellosis to safe guard public health and increase livestock productivity.
Long-term effects of motivational interviewing vs. traditional counseling on dog owners’ adherence to veterinary dental home care: a three-year follow-up study
Authors: Enlund Karolina Brunius , Jönsson Birgitta , Abrahamsson Kajsa H. , Pettersson Ann
Published: March 2024

Introduction

Periodontal disease is one of the most common health issues in dogs. However, disease is largely preventable by eliminating dental plaque, best achieved by daily tooth brushing. Unfortunately, owner adherence is low to the recommendation of daily tooth brushing in dogs.

Objective

This study aimed to evaluate the impact of various communication strategies, traditional advice (TA) versus motivational interviewing (MI), and compare them to a control group receiving no additional communication (CG), on dog owners’ performance of dental home care and the oral health of their dogs.

Methods

The study was conducted as a longitudinal clinical intervention study spanning 3 years, and involved 75 dog owners with young dogs who were randomly assigned to one of three groups: TA, MI, or CG. Intervention groups received annual telephone consultations based on their assigned methodology. A questionnaire was administered twice to all groups, and the dental health of the dogs was assessed at the study’s conclusion.

Result

Tooth brushing frequency demonstrated a significant increase in the MI group compared to the CG group (p < 0.01), albeit with a relatively low occurrence of daily brushing among owners. Dental health assessment revealed a significantly lower plaque index in the MI group compared to the CG group (p < 0.05), and a lower calculus index in the TA group compared to the CG group (p < 0.01). No statistically significant differences were observed between the MI and TA groups in terms of dental health.

Conclusion

Regular veterinary communication appears to have a positive influence on dog owner adherence to veterinary recommendations concerning dental care in dogs. Communication with veterinarians (MI and traditional advice) improved owner knowledge, attitude, and decreased frequency of not brushing. Although dental health parameters improved, the effect size was small, suggesting the complexity of adherence. Personalized calls to dog owners offer potential for dental health improvement, warranting further comparison of MI with traditional advice.
Intraarticular treatment with integrin α10β1-selected mesenchymal stem cells affects microRNA expression in experimental post-traumatic osteoarthritis in horses
Authors: Andersen Camilla , Walters Marie , Bundgaard Louise , Berg Lise Charlotte , Vonk Lucienne Angela , Lundgren-Åkerlund Evy , Henriksen Betina Lyngfeldt , Lindegaard Casper , Skovgaard Kerstin , Jacobsen Stine
Published: March 2024

Osteoarthritis (OA) remains a major cause of lameness in horses, which leads to lost days of training and early retirement. Still, the underlying pathological processes are poorly understood. MicroRNAs (miRNAs) are small non-coding RNAs that serve as regulators of many biological processes including OA. Analysis of miRNA expression in diseased joint tissues such as cartilage and synovial membrane may help to elucidate OA pathology. Since integrin α10β1-selected mesenchymal stem cell (integrin α10-MSC) have shown mitigating effect on equine OA we here investigated the effect of integrin α10-MSCs on miRNA expression. Cartilage and synovial membrane was harvested from the middle carpal joint of horses with experimentally induced, untreated OA, horses with experimentally induced OA treated with allogeneic adipose-derived MSCs selected for the marker integrin α10-MSCs, and from healthy control joints. miRNA expression in cartilage and synovial membrane was established by quantifying 70 pre-determined miRNAs by qPCR. Differential expression of the miRNAs was evaluated by comparing untreated OA and control, untreated OA and MSC-treated OA, and joints with high and low pathology score. A total of 60 miRNAs were successfully quantified in the cartilage samples and 55 miRNAs were quantified in the synovial membrane samples. In cartilage, miR-146a, miR-150 and miR-409 had significantly higher expression in untreated OA joints than in control joints. Expression of miR-125a-3p, miR-150, miR-200c, and miR-499-5p was significantly reduced in cartilage from MSC-treated OA joints compared to the untreated OA joints. Expression of miR-139-5p, miR-150, miR-182-5p, miR-200a, miR-378, miR-409-3p, and miR-7177b in articular cartilage reflected pathology score. Several of these miRNAs are known from research in human patients with OA and from murine OA models. Our study shows that these miRNAs are also differentially expressed in experimental equine OA, and that expression depends on OA severity. Moreover, MSC treatment, which resulted in less severe OA, also affected miRNA expression in cartilage.
Acid-base properties of non-protein nitrogen affect nutrients intake, rumen fermentation and antioxidant capacity of fattening Hu sheep
Authors: Zheng Wenjin , Duan Hongwei , Cao Liwen , Mao Shengyong , Shen Junshi
Published: March 2024

This study conducted a comparison of the effects of non-protein nitrogen with different acid-base properties on feed intake, rumen fermentation, nutrient digestion and antioxidant capacity in fattening Hu sheep. Sixteen fattening male sheep (31.43 ± 2.41 kg) with permanent rumen cannulas were randomly assigned to two dietary treatments: 1% urea and 1.78% ammonium chloride (NH4Cl, AC). A 42 days experimental period was conducted, with 14 days for adaptation and 28 days for treatment. Daily feed intake was recorded and various samples including feed, feces, rumen fluid, and blood were collected at different time points during the final week. The results indicated that the urea group had significantly higher dry matter intake, average daily gain, and gain efficiency in comparison to the AC group (p < 0.01). There was no difference in rumen pH and concentration of ammonia nitrogen between different groups (p > 0.05), but the rumen pH of urea group was higher than that of the AC group at 1 and 3 h after feeding (p < 0.05). The urea group exhibited higher concentrations of total volatile fatty acids (VFA) and individual VFAs compared to the AC group at all-time points (p < 0.01). Compared to the urea group, the intake of all nutrients decreased in the AC group (p < 0.01), but the digestibility of dry matter and organic matter increased significantly (p < 0.01), and the digestibility of CP had an increasing trend (p = 0.06) in the AC group. Additionally, the urea group had lower levels of serum glucagon-like peptide-1, peptide YY, Cl, total protein and globulin than the AC group (p < 0.05). The overall levels of HCO3−, superoxide dismutase, glutathione peroxidase, catalase, albumin/globulin, blood urea nitrogen and total cholesterol in the urea group increased significantly compared to the AC group (p < 0.05). It was concluded that adding urea to the high-concentrate diet resulted in increased rumen pH and improved rumen fermentation and growth performance in fattening sheep compared to NH4Cl addition. Furthermore, urea addition improved sheep’s antioxidant capacity and maintained their acid-base balance more effectively as compared to NH4Cl.
Smart Blade Count Selection to Align Modal Propagation Angle with Stator Stagger Angle for Low-Noise Ducted Fan Designs
Authors: Schade Stephen , Jaron Robert , Klähn Lukas , Moreau Antoine
Published: March 2024

The rotor–stator interaction noise is a major source of fan noise. Especially for low-speed fan stages, the tonal component is typically a dominant noise source. A challenge is to reduce this tonal noise, as it is typically perceived as unpleasant. Therefore, in this paper, we analytically, numerically and experimentally investigate an acoustic effect to lower the tonal noise excitation. Our study on an existing low-speed fan indicates a reduction in tonal interaction noise of more than 9 dB at the source if the excited acoustic modes propagate parallel to the stator leading edge angle. Moreover, a design-to-low-noise approach is demonstrated in order to apply this effect to two new fan stages with fewer stator than rotor blades. The acoustic design of both fans is determined by an appropriate choice of the rotor and stator blade numbers in order to align the modal propagation angle with the stator stagger angle. The blade geometries are obtained from aerodynamic optimization. Both fans provide similar aerodynamic but opposing acoustic radiation characteristics compared to the baseline fan and a significant tonal noise reduction resulting from the impact of the modal propagation angle on noise excitation. To ensure that this effect can also be applied to other low-speed fans, a design rule is derived and validated.
Analysis of Dynamic Evolution and Driving Factors of Low-Carbon Utilization Efficiency of Cultivated Land in China
Authors: Tian Yuan , Shi Xiuyi
Published: March 2024

In order to cope with global climate warming, measurement of the low-carbon utilization efficiency (LCUE) of cultivated land, considering carbon sink and carbon emission effects, is proposed. To address this, based on the data of 30 provinces in China, this study conducts a LCUE evaluation system by the MinDS-U-M productivity index model in order to analyze the spatiotemporal patterns and driving factors of LCUE with the geographic detector model and GTWR model. The results show the following: (1) Over the past 20 years, the average LCUE value exhibits a slow increasing trend from 2001 to 2021, which ranges from 0.9864 to 1.0272. Provinces with mid-level LCUE ranging from 1.0000 to 1.0990 account for the highest proportion in each period. (2) The annual growth rate of LCUE in the central region is the highest, where the promotion of green technology and farmland protection policies have played important roles. (3) According to the Geodetector analysis, urbanization rate (UR), irrigation index (IR), grain output value (GOV), precipitation (PR), arable land area (ALA), and environmental pollution control (EPC) are important drivers of the spatial difference of LCUE. (4) The GTWR model shows that the positive effects of ALA and SRT have always been concentrated in the main grain-producing areas over time. UR and PR have strong explanatory power for the space/time differentiation of LCUE, especially in eastern coastal regions. IR has an increasing effect on LCUE in the Western region, and the positive effect of EPC on the LCUE is concentrated in the central region. In order to coordinate regional LCUE contradictions, it is suggested to be wary of land resource damage caused by economic development, warn about the impacts of climate change, and strengthen the supervision of land remediation projects in order to achieve sustainable land management.
Soil Microorganisms in Agricultural Fields and Agronomic Regulation Pathways
Authors: Wang Qiming , Chai Qiang , Dou Xuecheng , Zhao Cai , Yin Wen , Li Hanting , Wei Jingui
Published: March 2024

Agricultural soil microorganisms play a crucial role in farmland ecosystems and are integral to the material cycle in these environments. The composition and abundance of soil microorganisms are influenced by agronomic measures that alter the soil microenvironment. These changes are pivotal to enhancing crop resistance, maximizing yield, and facilitating nutrient cycling in farmlands. Drawing on prior research advancements, this study systematically examined the functions of soil microorganisms, the effects of various agronomic measures on their populations, and the ways in which agronomic measures regulate soil microorganisms, and this article offers a comprehensive study of agricultural influences on microorganisms. Additionally, it outlines key areas for future research on soil microorganisms in farmlands, aiming to provide valuable insights for the sustainable development of farmland ecosystems.
Application of UAV Multispectral Imaging to Monitor Soybean Growth with Yield Prediction through Machine Learning
Authors: Shammi Sadia Alam , Huang Yanbo , Feng Gary , Tewolde Haile , Zhang Xin , Jenkins Johnie , Shankle Mark
Published: March 2024

The application of remote sensing, which is non-destructive and cost-efficient, has been widely used in crop monitoring and management. This study used a built-in multispectral imager on a small unmanned aerial vehicle (UAV) to capture multispectral images in five different spectral bands (blue, green, red, red edge, and near-infrared), instead of satellite-captured data, to monitor soybean growth in a field. The field experiment was conducted in a soybean field at the Mississippi State University Experiment Station near Pontotoc, MS, USA. The experiment consisted of five cover crops (Cereal Rye, Vetch, Wheat, Mustard plus Cereal Rye, and native vegetation) planted in the winter and three fertilizer treatments (Fertilizer, Poultry Liter, and None) applied before planting the soybean. During the soybean growing season in 2022, eight UAV imaging flyovers were conducted, spread across the growth season. UAV image-derived vegetation indices (VIs) coupled with machine learning (ML) models were computed for characterizing soybean growth at different stages across the season. The aim of this study focuses on monitoring soybean growth to predict yield, using 14 VIs including CC (Canopy Cover), NDVI (Normalized Difference Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), EVI2 (Enhanced Vegetation Index 2), and others. Different machine learning algorithms including Linear Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) are used for this purpose. The stage of the initial pod development was shown as having the best predictability for earliest soybean yield prediction. CC, NDVI, and NAVI (Normalized area vegetation index) were shown as the best VIs for yield prediction. The RMSE was found to be about 134.5 to 511.11 kg ha−1 in the different yield models, whereas it was 605.26 to 685.96 kg ha−1 in the cross-validated models. Due to the limited number of training and testing samples in the K-fold cross-validation, the models’ results changed to some extent. Nevertheless, the results of this study will be useful for the application of UAV remote sensing to provide information for soybean production and management. This study demonstrates that VIs coupled with ML models can be used in multistage soybean yield prediction at a farm scale, even with a limited number of training samples.
A Phenotypic Extraction and Deep Learning-Based Method for Grading the Seedling Quality of Maize in a Cold Region
Authors: Zhang Yifei , Lu Yuxin , Guan Haiou , Yang Jiao , Zhang Chunyu , Yu Song , Li Yingchao , Guo Wei , Yu Lihe
Published: March 2024

Background: Low-temperature stress significantly restricts maize germination, seedling growth and development, and yield formation. However, traditional methods of evaluating maize seedling quality are inefficient. This study established a method of grading maize seedling quality based on phenotypic extraction and deep learning. Methods: A pot experiment was conducted using different low-temperature combinations and treatment durations at six different stages between the sowing and seedling phases. Changes in 27 seedling quality indices, including plant morphology and photosynthetic performance, were investigated 35 d after sowing and seedling quality grades were classified based on maize yield at maturity. The 27 quality indices were extracted, and a total of 3623 sample datasets were obtained and grouped into training and test sets in a 3:1 ratio. A convolutional neural network-based grading method was constructed using a deep learning model. Results: The model achieved an average precision of 98.575%, with a recall and F1-Score of 98.7% and 98.625%, respectively. Compared with the traditional partial least squares and back propagation neural network, the model improved recognition accuracy by 8.1% and 4.19%, respectively. Conclusions: This study provided an accurate grading of maize seedling quality as a reference basis for the standardized production management of maize in cold regions.
Study on the Effects of Reducing Nitrogen Fertilizer: Stabilizing Yield and Carbon Sequestration by Synergistic Utilization of Chinese Milk Vetch and Rice Straw in Double-Cropping Rice Area
Authors: Xie Xue , Liao Yulin , Lu Yanhong , Zhang Jianglin , Li Peng , Tang Youyun , Cao Weidong , Gao Yajie , Nie Jun
Published: March 2024

The excessive application of chemical fertilizers in rice fields exacerbates soil degradation and poses a threat to food security. Achieving an increase in rice production and minimizing environmental costs are inevitable requirements for achieving sustainable rice production. The synergistic utilization of rice straw (RS) and Chinese milk vetch (MV) is a sustainable measure to improve soil quality in Southern China. How this management strategy impacts agricultural productivity and soil carbon (C) sequestration under different fertilization conditions is unclear. Several treatments, including only chemical fertilizer (F), F + MV (FM), F + RS (FS), and F + MV + RS (FMS) under a standard rate of nitrogen (N100) and 40% reduced nitrogen (N60) levels were designed to explore changes in rice yields and soil organic carbon (SOC) concentrations, stocks, and soil labile organic C fractions (permanganate oxidizable C) during 2018–2020 in a double-rice-cropping system. The results show that the FMS treatment reduced soil bulk density to alleviate soil compaction and improved the soil carbon management index. The synergistic utilization of MV and RS replacing 40% of the chemical N fertilizer could still maintain the rice yield. Compared to the F treatment, the average annual grain yield was significantly increased by 9.82% and 5.84% in the FMS treatment; SOC concentration was increased by 16.05% and 19.98% on average (p < 0.05), and SOC stock was increased by 1.78 Mg C ha−1 and 2.37 Mg C ha−1 under the N60 and N100 levels, respectively. The random forest regression model and correlation analysis demonstrated that the inputs of chemical N, organic N and C, and appropriate C/N ratio promoted soil C accumulation. Furthermore, the structural equation model analysis exhibited that the C input affects the highly labile organic carbon (HLOC) and total labile organic carbon (LOC); the HLOC had a positive effect on SOC (p < 0.05). N input had a significant effect on LOC and yield. Our results suggest that the synergistic utilization of MV and RS plays an important role in ensuring stable grain production, improving soil C sequestration capacity, and maintaining soil environmental health in Southern China.
Effect of Biochar Types and Rates on SOC and Its Active Fractions in Tropical Farmlands of China
Authors: Chen Mingwan , Liu Daquan , Shao Xujie , Li Shoupeng , Jin Xin , Qi Jincun , Liu Hong , Li Chen , Li Changjiang , Li Changzhen
Published: March 2024

To date, most studies have shown that biochar has great potential in carbon sequestration and reduction, as well as soil quality improvement. However, there is limited knowledge of its effect on soil organic carbon (SOC) fractions in tropical farmland. This study aimed to determine the impact of different types and rates of biochar applied in tropical farmlands on so SOC and its active fractions. The SOC, microbial biomass carbon (MBC), dissolved organic carbon (DOC), and soil mineralizable carbon (SMC) in the 0–30 cm soil layers under rice hull (R) and peanut shell (P) biochar treatments were measured. The results showed that the application of R and P biochar increased the contents, stocks, and cumulative stocks of SOC, MBC, and DOC in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers. The contents, stocks, and cumulative stocks increased with increasing biochar application rates. Compared with CK, the ranges of the increased SOC, MBC, and DOC cumulative stocks were 10.76–46.36%, 30.04–195.65%, and 0.02–17.03%, respectively. However, the R60 and P60 had the lowest cumulative stocks of SMC, decreasing by 14.69% and 8.05%, respectively. The biochar treatment of more than 20 t ha−1 reduced the ratio of SMC:SOC and active fractions:SOC. Therefore, it can be inferred that the application of biochar improved the levels of SOC, MBC, and DOC, and the application of more than 20 t ha−1 biochar could decrease soil carbon mineralization, thus improving the stability of SOC in tropical farmlands.
Design and Synthesis of Novel Amino and Acetamidoaurones with Antimicrobial Activities
Authors: Di Maio Attilio , Olleik Hamza , Courvoisier-Dezord Elise , Guillier Sophie , Neulat-Ripoll Fabienne , Haudecoeur Romain , Bolla Jean-Michel , Casanova Magali , Cavalier Jean-François , Canaan Stéphane , Pique Valérie , Charmasson Yolande , Baydoun Elias , Hijazi Akram , Perrier Josette , Maresca Marc , Robin Maxime
Published: March 2024

The development of new and effective antimicrobial compounds is urgent due to the emergence of resistant bacteria. Natural plant flavonoids are known to be effective molecules, but their activity and selectivity have to be increased. Based on previous aurone potency, we designed new aurone derivatives bearing acetamido and amino groups at the position 5 of the A ring and managing various monosubstitutions at the B ring. A series of 31 new aurone derivatives were first evaluated for their antimicrobial activity with five derivatives being the most active (compounds 10, 12, 15, 16, and 20). The evaluation of their cytotoxicity on human cells and of their therapeutic index (TI) showed that compounds 10 and 20 had the highest TI. Finally, screening against a large panel of pathogens confirmed that compounds 10 and 20 possess large spectrum antimicrobial activity, including on bioweapon BSL3 strains, with MIC values as low as 0.78 µM. These results demonstrate that 5-acetamidoaurones are far more active and safer compared with 5-aminoaurones, and that benzyloxy and isopropyl substitutions at the B ring are the most promising strategy in the exploration of new antimicrobial aurones.
Feature-Interaction-Enhanced Sequential Transformer for Click-Through Rate Prediction
Authors: Yuan Quan , Zhu Ming , Li Yushi , Liu Haozhe , Guo Siao
Published: March 2024

Click-through rate (CTR) prediction plays a crucial role in online services and applications, such as online shopping and advertising. The performance of CTR prediction can have a direct impact on user experience and the revenue of the online platforms. For CTR prediction models, self-attention-based methods have been widely applied to this field. Recent works generally adopted the Transformer architecture, where the self-attention mechanism can capture the global dependencies of the user’s historical interactions and predict the next item. Despite the effectiveness of self-attention methods in modeling sequential user behaviors, most sequential recommenders hardly exploit feature interaction techniques to extract high-order feature combinations. In this paper, we propose a Feature-Interaction-Enhanced Sequence Model (FESeq), which integrates feature interaction and the sequential recommendation model in a cascading structure. Specifically, the interacting layer in FESeq is an automatic feature engineering step for the Transformer model. Then, we add a linear time interval embedding layer and a positional embedding layer to the Transformer in the sequence-refiner layer to learn both the time intervals and the position information in the user’s sequence behaviors. We also design an attention-based sequence pooling layer that can model the relevance of the user’s historical behaviors and the target item representation through scaled bilinear attention. Our experiments show that the proposed method beats all the baselines on both public and industrial datasets.
Development of an Indexed Score to Identify the Most Suitable Biological Material to Assess SARS-CoV-2
Authors: Almeida-Silva Marina , Cervantes Renata , Ribeiro Edna , Marques-Ramos Ana
Published: March 2024

Introduction: The rapidly contagious process of respiratory viruses such as SARS-CoV-2 makes it urgent to multiply testing for diagnostics to identify the active viral shedding cases (current infection, carriage state or, residual viral RNA) and decrease the risk of transmission to other patients and healthcare professionals. Although nasopharyngeal swabs (NPSs) are the most common specimen type used for COVID-19 diagnosis, they require supervision by a professional, and concerns have been raised regarding healthcare personnel exposure, difficulty in collection, and patient discomfort. Viral RNA can also be detected in specimens such as saliva, blood, bronchoalveolar lavage fluid, sputum, faeces, and urine. This study aimed to provide updated information about the most suitable biological material to diagnose SARS-CoV-2, considering the risk assessment, specialization needed, test cost, complexity of the collection, and sample treatment associated with the different types of specimens. Methods: An extensive search of scientific review articles was made to collect information about the biological specimens to identify SARS-CoV-2 in the urine, sputum, nasopharyngeal, oropharyngeal, bronchoalveolar (BAL), saliva, faeces, and blood. For this purpose, an index score was developed based on seven categories: Materials and Equipment; Infection Risk for the Health Professional; Infection Risk for the Patient; Collection; Cost; Specialized HR; and RNA Extraction Type. Results and Discussion: Each criterion from the index score was quoted from 1.0 to 5.0, and a sum was made to classify which specimen is the best choice to diagnose SARS-CoV-2, according to the chosen parameters. Data indicated that urine specimens are the most elementary biological sample to access. Regarding RNA extraction, NPSs, OPS, and BAL presented the maximum score. However, BAL has the lowest score regarding associated costs. Concerning sputum and saliva, all the aspects were evaluated with a score of 5.0 except for the RNA Extraction Type in sputum. Regarding the total scores of the multiple specimens, the lowest corresponds to BAL with a score of 1.7, followed by blood with 3.1 and NPSs and OPS with 3.6 and 3.7, respectively. Urine and faeces have the same value, 4.4, sputum has 4.9, and the highest and maximum possible value corresponds to saliva with 5.0, making this last specimen the most suitable for all considered parameters. Conclusion: Although OPS and NPSs are the most used specimens, there are better alternatives. Among all the specimens of the respiratory system, saliva is the most cost-effective specimen for performing SARS-CoV-2 diagnosis. Even though these infections are usually diagnosed clinically based on symptoms and local epidemiology, the identification of the specific pathogen may affect clinical management and be crucial for containing potential outbreaks.
Path Planning Method for Manipulators Based on Improved Twin Delayed Deep Deterministic Policy Gradient and RRT*
Authors: Cai Ronggui , Li Xiao
Published: March 2024

This paper proposes a path planning framework that combines the experience replay mechanism from deep reinforcement learning (DRL) and rapidly exploring random tree star (RRT*), employing the DRL-RRT* as the path planning method for the manipulator. The iteration of the RRT* is conducted independently in path planning, resulting in a tortuous path and making it challenging to find an optimal path. The setting of reward functions in policy learning based on DRL is very complex and has poor universality, making it difficult to complete the task in complex path planning. Aiming at the insufficient exploration of the current deterministic policy gradient DRL algorithm twin delayed deep deterministic policy gradient (TD3), a stochastic policy was combined with TD3, and the performance was verified on the simulation platform. Furthermore, the improved TD3 was integrated with RRT* for performance analysis in two-dimensional (2D) and three-dimensional (3D) path planning environments. Finally, a six-degree-of-freedom manipulator was used to conduct simulation and experimental research on the manipulator.
Natural Language Processing in Knowledge-Based Support for Operator Assistance
Authors: Besharati Moghaddam Fatemeh , Lopez Angel J. , De Vuyst Stijn , Gautama Sidharta
Published: March 2024

Manufacturing industry faces increasing complexity in the performance of assembly tasks due to escalating demand for complex products with a greater number of variations. Operators require robust assistance systems to enhance productivity, efficiency, and safety. However, existing support services often fall short when operators encounter unstructured open questions and incomplete sentences due to primarily relying on procedural digital work instructions. This draws attention to the need for practical application of natural language processing (NLP) techniques. This study addresses these challenges by introducing a domain-specific dataset tailored to assembly tasks, capturing unique language patterns and linguistic characteristics. We explore strategies to process declarative and imperative sentences, including incomplete ones, effectively. Thorough evaluation of three pre-trained NLP libraries—NLTK, SPACY, and Stanford—is performed to assess their effectiveness in handling assembly-related concepts and ability to address the domain’s distinctive challenges. Our findings demonstrate the efficient performance of these open-source NLP libraries in accurately handling assembly-related concepts. By providing valuable insights, our research contributes to developing intelligent operator assistance systems, bridging the gap between NLP techniques and the assembly domain within manufacturing industry.
Parametric Finite Element Study on FREEDAM Beam to Column Joints with Different Details of the Haunch Slotted Holes
Authors: D’Aniello Mario , Montuori Rosario , Nastri Elide , Piluso Vincenzo , Todisco Paolo
Published: March 2024

Parametric Finite Element (FE) simulations were performed to investigate the ultimate flexural of different configurations of friction steel beam-to-column joints equipped with FREEDAM (free from damage) dampers. The main aim of this study was to compare the effectiveness of friction dampers featuring either single or multiple slotted holes, examining how these variations influence the behavior of the joint and the devices under seismic loads. In particular, the ultimate behavior of the connection (i.e., when the device reaches its maximum stroke) was investigated to characterize the involvement of the bolts in shear, the bearing of the plates, and the yielding of the supporting components. The analysis of bolt stress states revealed significant differences influenced by the number of bolts and slots. The FE models were calibrated against the experimental results obtained within the FREEDAM RFCS Project. These insights contribute to the design and performance evaluation of steel beam-to-column joints with FREEDAM connections, in particular the detailing of the haunch slots, laying the groundwork for future research and applications.
Automatic Extraction Method of Landslide Based on Digital Elevation Model and Digital Orthophoto Map Data Combined in Complex Terrain
Authors: Qiu Zhiwei , Li Junfeng , Wang Yuemin , Niu Yuan , Qian Hui
Published: March 2024

This study aims to accurately determine the distribution of landslides in the complex terrain of Jiangdingya, Nanyu Township, Zhouqu County, Gansu Province. The digital orthophoto map (DOM) and digital elevation model (DEM) are used to accurately identify landslide areas and analyze associated data. Based on image-based supervised classification, the influence factor constraint analysis is used to further identify and delineate the landslide area. Three mathematical morphology operations—erosion, dilation, and opening—are then applied to automatically identify and extract landslides. Experimental results demonstrate that achieving an accuracy, precision, and recall of 98.02%, 85.24%, and 84.78% shows that it is possible to better avoid interference caused by complex terrain with rich features. High-resolution DEM and DOM data contain rich spectral and texture information. These data can accurately depict geomorphic features of complex terrain and aid in identifying landslide-prone areas when combined with mathematical morphology processing. This contribution is important for identifying landslides in complex terrain and emergency disaster management.
Numerical Analysis of the Wing Leading Edge Electro-Impulse De-Icing Process Based on Cohesive Zone Model
Authors: Ma Fangping , Zhu Zhengtao , Wang Di , Jin Xiaoming
Published: March 2024

Aircraft icing has historically been a critical cause of airplane crashes. The electro-impulse de-icing system has a wide range of applications in aircraft de-icing due to its lightweight design, low energy consumption, high efficiency, and other advantages. However, there has been little study into accurate wing electric-impulse de-icing simulation methods and the parameters impacting de-icing efficacy. Based on the damage mechanics principle and considering the influence mechanisms of interface debonding and ice fracture on ice shedding, this paper establishes a more accurate numerical model of wing electric-impulse de-icing using the Cohesive Zone Model (CZM). It simulates the process of electric-impulse de-icing at the leading edge of the NACA 0012 wing. The numerical results are compared to the experimental results, revealing that the constructed wing electro-impulse de-icing numerical model is superior. Lastly, the effects of varying ice–skin interface shear adhesion strengths, doubler loading positions, and impulse sequences on de-icing effectiveness were studied. The de-icing rate is a quantitative description of the electro-impulse’s de-icing action, defined in the numerical model as the ratio of cohesive element deletions to the total elements at the ice–skin interface. The findings reveal that varying shear adhesion strengths at the ice–skin interface significantly impact the de-icing effect. The de-icing rate steadily falls with increasing shear adhesion strength, from 66% to 56%. When two, four, and seven impulses were applied to doubler two, the de-icing rates were 59%, 71%, and 71%, respectively, significantly increasing the de-icing efficiency compared to when impulses were applied to doubler one. Doubler one and two impulse responses are overlaid differently depending on the impulse sequences, resulting in varying de-icing rates. When the impulse sequence is 20 ms, the superposition results are optimal, and the de-icing rate reaches 100%. These studies can guide the development and implementation of a wing electric-impulse de-icing system.
OmniSR-M: A Rock Sheet with a Multi-Branch Structure Image Super-Resolution Lightweight Method
Authors: Liu Tianyong , Xu Chengwu , Tang Lu , Meng Yingjie , Xu Weijia , Wang Jinhuan , Xu Jian
Published: March 2024

With the rapid development of digital core technology, the acquisition of high-resolution rock thin section images has become crucial. Due to the limitation of optical principles, thin section imaging involves a contradiction between resolution and field of view. In order to solve this problem, this paper proposes a lightweight, fully aggregated network with multi-branch structure for super resolution of rock thin section images. The experimental results on the rock thin section dataset demonstrate that the improved method, called OmniSR-M, achieves significant enhancement compared to the original OmniSR method and also surpasses other state-of-the-art methods. OmniSR-M effectively recovers image details while maintaining its lightweight nature. Specifically, OmniSR-M reduces the number of parameters by 26.56% and the computation by 27.66% compared to OmniSR. Moreover, this paper quantitatively analyzes both the facies porosity rate and grain size features in the application scenario. The results show that the images generated by OmniSR-M successfully recover key information about the rock thin section.
Polyp Generalization via Diversifying Style at Feature-Level Space
Authors: Poudel Sahadev , Lee Sang-Woong
Published: March 2024

In polyp segmentation, the latest notable topic revolves around polyp generalization, which aims to develop deep learning-based models capable of learning from single or multiple source domains and applying this knowledge to unseen datasets. A significant challenge in real-world clinical settings is the suboptimal performance of generalized models due to domain shift. Convolutional neural networks (CNNs) are often biased towards low-level features, such as style features, impacting generalization. Despite attempts to mitigate this bias using data augmentation techniques, learning model-agnostic and class-specific feature representations remains complex. Previous methods have employed image-level transformations with styles to supplement training data diversity. However, these approaches face limitations in ensuring style diversity due to restricted style sources, limiting the utilization of the potential style space. To address this, we propose a straightforward yet effective style conversion and generation module integrated into the UNet model. This module transfers diverse yet plausible style features to the original training data at the feature-level space, ensuring that generated styles align closely with the original data. Our method demonstrates superior performance in single-domain generalization tasks across five datasets compared to prior methods.
Diversity of Soil-Borne Fungi Isolated from Places Frequently Visited by People in the City of Wrocław (Poland)
Authors: Spychała Klaudyna , Kłosińska Katarzyna , Salwińska Weronika , Ogórek Rafał
Published: March 2024

In this study, we identified culturable microscopic fungi in soil from areas frequented by people (parks, allotments, and other green areas) in the city of Wrocław (Poland). In addition to general species analysis, attention was focused on keratin-degrading fungi. From 60 soil samples (12 study sites), we obtained 75 isolates of keratinophilic and keratinolytic fungi using the hair bait method, and 54 isolates of fungi were isolated on PDA (Potato Dextrose Agar) medium. Based on morphological and molecular analyses, a total of 37 strains were identified, classified into 2 phyla, 11 families, 17 genera, and 30 filamentous species. The mean values of the Shannon Diversity Index for both experimental variants ranged from 0.074 to 0.117. The most common species was the Penicillium genus, which accounted for 33.33% of all fungal species obtained in these studies. These fungi are common in both indoor and outdoor environments. However, particularly noteworthy in this study are the species belonging to the group of dermatophytes (Arthroderma uncinatum, Keratinophyton wagnerii, Nannizzia gypsea, and Paraphyton cookei), which may pose a real biological threat to humans and animals due to their well-known potential to cause dermatomycosis.