bluuebunny/crossref_metadata_2025 huggingface dataset:
Post-Fire Soil Nutrient Dynamics in Seriphium plumosum L. Encroached Semi-Arid Grassland of Gauteng Province, South Africa
Authors: Pule Hosia T. , Tjelele Julius T. , Tedder Michelle J.
Published: October 2023

Seriphium plumosum L. is an indigenous unpalatable shrub that occurs in fire-prone semi-arid South African grassland areas, yet research proposes the use of fire to control its encroachment of rangelands. This study investigated the interaction effects of burning and soil depth on components of soil fertility. Soil samples were collected from the surface (<10 cm) and subsurface (>10 ≤ 20 cm) soil, before and after burning in randomly selected paired subplots (25 m × 25 m), with six replicates. Data was analysed as a randomised complete block design, with repeated measures (before and after burning) in a 2 × 2 factorial analysis of variance (ANOVA) using generalised linear model (GLM) procedures. Components of soil fertility measured (K, Ca, Mg, Org C, P, pH and TN) showed a significant decrease with increasing soil depth both before and after burning, except for K and P, which were significantly higher in surface soils after burning. The results showed that the response of soil nutrients to fire depends on the temperature tolerance threshold of individual soil nutrient elements. Increasing surface soil available K and P concentrations after burning may improve the conditions for S. plumosum encroachment, with implications for similar environments and species worldwide.
Evaluating the Impacts of Waterlogging Disasters on Wheat and Maize Yields in the Middle and Lower Yangtze River Region, China, by an Agrometeorological Index
Authors: Wang Xinhui , Qian Long , Dong Chunyu , Tang Rong
Published: October 2023

Waterlogging disasters severely restrict crop production. The middle and lower Yangtze River region (MLYRR) is an important grain-producing region in China but suffers from severe waterlogging disasters. In this study, an agriculture-specific index called the accumulative humidity index was introduced to analyze the spatiotemporal characteristics of waterlogging during different wheat and maize growth stages in the MLYRR from 1960 to 2020. Additionally, the relationships between waterlogging intensities and crop yield fluctuations were revealed. The results showed that over the past 60 years, the intensity of wheat and maize waterlogging in the central and eastern MLYRR have increased; crop waterlogging was more intense in the 1990s–2010s than during the 1960s–1980s, and waterlogging intensity peaked in the 1990s. For both crops, waterlogging was more intense during the early growth stages, but its yield-reducing impacts were more significant during middle and late growth stages. The southern MLYRR (especially southern Anhui) was the region where both crops were most prone to waterlogging, but yields in this region were not severely affected by waterlogging. Compared with wheat, maize was more prone to waterlogging, and its yield was more significantly reduced by waterlogging. In conclusion, this study provides guidance for agricultural waterlogging risk reduction in the MLYRR.
The Microbiomes of Various Types of Abandoned Fallow Soils of South Taiga (Novgorod Region, Russian North-West)
Authors: Abakumov Evgeny V. , Gladkov Grigory V. , Kimeklis Anastasiia K. , Andronov Evgeny E.
Published: October 2023

More than 30 years have passed after the collapse of the Soviet Union, and huge areas of soil were left in a fallow state. The study of the microbiological status of fallow soils is an extremely urgent task because fallow soils represent the “hidden” food basket of Eurasia. In this context, we studied the influence of land use type (pasture, vegetable garden, hayfield, or secondary afforestation) on key agrochemical parameters and parameters of soil microbial biodiversity. All anthropogenically transformed soils included in the analysis showed increased humus content and pH shift to a more neutral side compared to the mature soil; the same seemed to be the case for all nutrient elements. It was established that the key factor regulating soil microbiome composition shift was the duration and degree of irreversibility of an agrogenic impact. The key phyla of soil microorganisms were Pseudomonadota, Acidobacteriota, Verrucomicrobiota, Bacteroidota, and Actinobacteriota. The proportion of other phyla was quite variative in soils of different land use. At the same time, all the 30-year-old abandoned soils were more similar to each other than to mature reference soil and 130-year-old soils of monoculture vegetable gardens. Thus, the first factor, regulating soil microbiome composition, is a continuation of soil agrogenic transformation. The second factor is the type of land use if the soil age was equal for fallow territory in the case of one initial podzol soil and one type of landscape. Thus, 30-year-old abandoned soils are intermediate in terms of microbial biodiversity between pristine natural podzols and plaggic podzol. It could be suggested that in the case of secondary involvement of soils in agriculture, the composition of the microbiome may turn to mature soil or to plaggic soil under intensive amelioration.
Improved Faster Region-Based Convolutional Neural Networks (R-CNN) Model Based on Split Attention for the Detection of Safflower Filaments in Natural Environments
Authors: Zhang Zhenguo , Shi Ruimeng , Xing Zhenyu , Guo Quanfeng , Zeng Chao
Published: October 2023

The accurate acquisition of safflower filament information is the prerequisite for robotic picking operations. To detect safflower filaments accurately in different illumination, branch and leaf occlusion, and weather conditions, an improved Faster R-CNN model for filaments was proposed. Due to the characteristics of safflower filaments being dense and small in the safflower images, the model selected ResNeSt-101 with residual network structure as the backbone feature extraction network to enhance the expressive power of extracted features. Then, using Region of Interest (ROI) Align improved ROI Pooling to reduce the feature errors caused by double quantization. In addition, employing the partitioning around medoids (PAM) clustering was chosen to optimize the scale and number of initial anchors of the network to improve the detection accuracy of small-sized safflower filaments. The test results showed that the mean Average Precision (mAP) of the improved Faster R-CNN reached 91.49%. Comparing with Faster R-CNN, YOLOv3, YOLOv4, YOLOv5, and YOLOv6, the improved Faster R-CNN increased the mAP by 9.52%, 2.49%, 5.95%, 3.56%, and 1.47%, respectively. The mAP of safflower filaments detection was higher than 91% on a sunny, cloudy, and overcast day, in sunlight, backlight, branch and leaf occlusion, and dense occlusion. The improved Faster R-CNN can accurately realize the detection of safflower filaments in natural environments. It can provide technical support for the recognition of small-sized crops.
Emotional Contagion and Social Support in Pigs with the Negative Stimulus
Authors: Zhang Ye , Yu Jiaqi , Zhang Yu , Zhang Yaqian , Sun Fang , Yao Yuhan , Bai Ziyu , Sun Hanqing , Zhao Qian , Li Xiang
Published: October 2023

This study expects to confirm the existence of emotional transmission in pigs from multiple perspectives and to provide theoretical references for improving animal welfare in livestock farming. A group that could directly observe (DO) and a group that could not directly observe (NO) were created based on whether or not their peers observed the treatment process, as the treated pig (TP) was treated with electrical shock and the companion pig (CP) either witnessed the treatment inflicted upon TP or not, and a third group was a control group, in which neither pig was stimulated. The behavioral responses of both the TPs and CPs were recorded to evaluate the emotional reaction. The results found that in both the DO and NO groups, the frequency of TP freezing was significantly higher than that of CP, and CP was significantly higher than that of the control group. Interestingly, although the social interaction responses of the CPs were not similar in the DO and NO groups, there were no significant differences between the behaviors of TPs in the DO and NO groups, except for nose–nose contact and a single approach to the partition, which allowed us to conclude that, whether or not the pigs directly observed the negative treatment, they were able to respond accordingly to fear and provide similar social support to their companions who were treated negatively.
Novel Heredity Basis of the Four-Horn Phenotype in Sheep Using Genome-Wide Sequence Data
Authors: Zhang Haoyuan , Yang Pu , Liu Chengli , Ma Yuehui , Han Yanguo , Zeng Yan , Huang Yongfu , Zhao Yongju , Zhao Zhongquan , He Xiaohong , E Guangxin
Published: October 2023

Horns are an important breeding trait for sheep. However, no widely recognized viewpoint on the regulatory genes and mechanisms of horns is available, and the genetic basis of the four-horn phenotype (FHP) is unclear. This work conducted a genome-wide association study with 100 sheep genomes from multiple breeds to investigate the genetic basis of the FHP. The results revealed three significant associations (corrected as p < 1.64 × 10−8) of the InDels (CHR2: g.133,742,709delA, g.133,743,215insC, and g.133,743,940delT) for FHP in the intergenic sequence (IGS) between the MTX2 and the LOC105609047 of CHR2. Moreover, 14 significant associations (corrected as p < 1.42 × 10−9) of SNPs with the FHP phenotype were identified in CHR2 and CHR16, including five (e.g., CHR16: g.40,351,378G > A and g.40,352,577G > A) located in the intron of the ADAMTS12 gene, eight (e.g., CHR2: g.133,727,513C > T and g.133,732,145T > G) in the IGS between MTX2 and LOC105609047, and only one (CHR2: g.133,930,761A > G) in the IGS between HOXD1 and MTX2. Obvious divergence was also observed in genotype patterns between the FHP and others (two horns and hornless) in the HOXD1 and ADAMTS12 gene regions. An extremely significant linkage also occurred between Loci I and Loci II within 100 individuals (LD = −156.02186, p < 0.00001). In summary, our study indicated that the genomic sequences from CHR2 and CHR16 contributed to the FHP in sheep, specifically the key candidate genes HOXD1 and ADAMTS12. These results improved our understanding of the Mendelian genetic basis of the FHP in sheep.
Intestinal Microbiome in Dogs with Chronic Hepatobiliary Disease: Can We Talk about the Gut–Liver Axis?
Authors: Habermaass Verena , Olivero Daniela , Gori Eleonora , Mariti Chiara , Longhi Erika , Marchetti Veronica
Published: October 2023

The gut–liver axis represents a current topic in human medicine. Extensive research investigates the gut microbiome (GM) modifications in relation to various kinds of chronic hepatobiliary diseases (CHD), with many mechanisms and therapeutical implications recognized. Those aspects in veterinary medicine are still quite unexplored. The aim of the present study was to evaluate GM in dogs diagnosed with CD. Comparison among CHD dogs were made considering some clinical and biochemical variables (lipemia and alanine–aminotransferase activities), presence of cholestasis or endocrine disorders, diet). Sixty-five dogs were prospectively enrolled with clinical and hematobiochemical evaluation and 16S-RNA GM sequencing assessed. Dogs that received antibiotics and/or pre/pro/symbiotics administration were excluded. Deeper GM alteration was observed between dogs with or without ultrasonographic and biochemical cholestatic CHD. Cholestasis was associated with a decrease in several bacterial taxa, including Clostridium hiranonis, Fusobacterium, Megamonas, Ruminococcus faecis, Turicibacter, and higher levels of Escherichia/Shigella and Serratia. Thus, the alteration in bile flow and composition, typical of cholestasis, may directly affect the local intestinal microbial environment. For the management of dogs with CHD and especially cholestatic CHD, clinicians should be aware that gut–liver interaction may lead to dysbiosis.
Genomic Insights into Methicillin-Resistant Staphylococci and Mammaliicocci from Bulk Tank Milk of Dairy Farms in Serbia
Authors: Kos Andrea , Papić Bojan , Golob Majda , Avberšek Jana , Kušar Darja , Ledina Tijana , Đorđević Jasna , Bulajić Snežana
Published: October 2023

The potential risk to human and animal health provides a rationale for research on methicillin-resistant staphylococci (MRS) and mammaliicocci (MRM) in dairy herds. Here, we aimed to estimate their occurrence in the bulk tank milk (BTM) samples collected in 2019–2021 from 283 bovine dairy farms in the Belgrade district. We used whole-genome sequencing to characterize the obtained isolates and assess their genetic relatedness. A total of 70 MRS/MRM were recovered, most frequently Staphylococcus haemolyticus and Mammaliicoccus sciuri. Five clusters of 2–4 genetically related isolates were identified and epidemiological data indicated transmission through, e.g., farm visits by personnel or milk collection trucks. Most MRSA isolates belonged to the typical livestock-associated lineage ST398-t034. One MRSA isolate (ST152-t355) harbored the PVL-encoding genes. Since MRS/MRM isolates obtained in this study frequently harbored genes conferring multidrug resistance (MDR), this argues for their role as reservoirs for the spread of antimicrobial resistance genes. The pipeline milking system and total bacterial count >100,000 CFU/mL were significantly associated with higher occurrences of MRS/MRM. Our study confirms that BTM can be a zoonotic source of MRS, including MDR strains. This highlights the urgent need for good agricultural practices and the continuous monitoring of MRS/MRM in dairy farms.
Streptococcus pyogenes Lineage ST62/emm87: The International Spread of This Potentially Invasive Lineage
Authors: Martini Caroline Lopes , Silva Deborah Nascimento Santos , Viana Alice Slotfeldt , Planet Paul Joseph , Figueiredo Agnes Marie Sá , Ferreira-Carvalho Bernadete Teixeira
Published: October 2023

Streptococcus pyogenes is known to be associated with a variety of infections, from pharyngitis to necrotizing fasciitis (flesh-eating disease). S. pyogenes of the ST62/emm87 lineage is recognized as one of the most frequently isolated lineages of invasive infections caused by this bacterium, which may be involved in hospital outbreaks and cluster infections. Despite this, comparative genomic and phylogenomic studies have not yet been carried out for this lineage. Thus, its virulence and antimicrobial susceptibility profiles are mostly unknown, as are the genetic relationships and evolutionary traits involving this lineage. Previously, a strain of S. pyogenes ST62/emm87 (37–97) was characterized in our lab for its ability to generate antibiotic-persistent cells, and therapeutic failure in severe invasive infections caused by this bacterial species is well-reported in the scientific literature. In this work, we analyzed genomic and phylogenomic characteristics and evaluated the virulence and resistance profiles of ST62/emm87 S. pyogenes from Brazil and international sources. Here we show that strains that form this lineage (ST62/emm87) are internationally spread, involved in invasive outbreaks, and share important virulence profiles with the most common emm types of S. pyogenes, such as emm1, emm3, emm12, and emm69, which are associated with most invasive infections caused by this bacterial species in the USA and Europe. Accordingly, the continued increase of ST62/emm87 in severe S. pyogenes diseases should not be underestimated.
Rational Drug and Antibiotic Use Status, E-Health Literacy in Syrian Immigrants and Related Factors: A Cross-Sectional Study
Authors: Değer Mehmet Sait , Sezerol Mehmet Akif , Atak Muhammed
Published: October 2023

Rational drug use is a pivotal concept linked with morbidity and mortality. Immigration plays a significant role as a determinant affecting individuals’ health-related attitudes, behaviors, and the pursuit of health services. Within this context, the study was initiated to assess the factors influencing health literacy and rational drug use among Syrian immigrants in Istanbul. A cross-sectional study was undertaken on 542 Syrian adults utilizing a three-part questionnaire encompassing sociodemographics, rational drug use, and the e-health literacy scale (eHEALS). With an average age of 39.19 ± 13.10 years, a majority of participants believed medications should solely be doctor-prescribed (97%) and opposed keeping antibiotics at home (93.7%). Yet, 62.5% thought excessive herbal medicine use was harmless. The mean eHEALS score stood at 20.57 ± 7.26, and factors like age, marital status, income, and duration of stay in Turkey influenced e-health literacy. Associations were seen between low e-health literacy and being female, being older, having a lower education level, and regular medication use. Syrian immigrants displayed proper knowledge concerning antibiotics yet exhibited gaps in their understanding of general drug usage, treatment adherence, and herbal medicines. Approximately 80.3% had limited health literacy, pointing to the need for targeted interventions for enhanced health and societal assimilation.
Thylakoid Rhodanese-like Protein–Ferredoxin:NADP+ Oxidoreductase Interaction Is Integrated into Plant Redox Homeostasis System
Authors: Vojta Lea , Rac-Justament Anja , Zechmann Bernd , Fulgosi Hrvoje
Published: October 2023

In vascular plants, the final photosynthetic electron transfer from ferredoxin (Fd) to NADP+ is catalyzed by the flavoenzyme ferredoxin:NADP+ oxidoreductase (FNR). FNR is recruited to thylakoid membranes via an integral membrane protein TROL (thylakoid rhodanese-like protein) and the membrane associated protein Tic62. We have previously demonstrated that the absence of TROL triggers a very efficient superoxide (O2•−) removal mechanism. The dynamic TROL–FNR interaction has been shown to be an apparently overlooked mechanism that maintains linear electron flow before alternative pathway(s) is(are) activated. In this work, we aimed to further test our hypothesis that the FNR–TROL pair could be the source element that triggers various downstream networks of chloroplast ROS scavenging. Tandem affinity purification followed by the MS analysis confirmed the TROL–FNR interaction and revealed possible interaction of TROL with the thylakoid form of the enzyme ascorbate peroxidase (tAPX), which catalyzes the H2O2-dependent oxidation of ascorbate and is, therefore, the crucial component of the redox homeostasis system in plants. Further, EPR analyses using superoxide spin trap DMPO showed that, in comparison with the wild type, plants overexpressing TROL (TROL OX) propagate more O2•− when exposed to high light stress. This indicates an increased sensitivity to oxidative stress in conditions when there is an excess of membrane-bound FNR and less free FNR is found in the stroma. Finally, immunohistochemical analyses of glutathione in different Arabidopsis leaf cell compartments showed highly elevated glutathione levels in TROL OX, indicating an increased demand for this ROS scavenger in these plants, likely needed to prevent the damage of important cellular components caused by reactive oxygen species.
Comprehensive Energy Analysis of Vehicle-to-Grid (V2G) Integration with the Power Grid: A Systemic Approach Incorporating Integrated Resource Planning Methodology
Authors: Bortotti Marcos Frederico , Rigolin Pascoal , Udaeta Miguel Edgar Morales , Grimoni José Aquiles Baesso
Published: October 2023

This work aims at a comprehensive assessment of the impact of vehicle-to-grid (V2G) technology on both demand and supply sides, considering integrated resource planning for sustainable energy. By using a computational tool and evaluating the complete potentials, we divide the analysis into four dimensions: environmental, social, technical, economic, and political. Each dimension is further subdivided, allowing for a detailed characterization of the impacts across these various aspects. Our approach employs a simple yet effective algebraic method using matrices to evaluate all the elements involved in the V2G system. This case study focuses on the environmental and technical–economic aspects of integrating V2G technology into a city with industrial parameters. Our findings reveal improvements and future challenges to all four dimensions, including direct and indirect reductions in CO2 emissions. However, the limited availability of specific data in the social and political scopes highlight the need for further research in these areas. This study lays the groundwork for future investigations to explore the social and political implications of V2G technology, offering significant potential for future studies.
Polymer-Stabilized Silver (Gold)–Zinc Oxide Nanoheterodimer Structures as Antimicrobials
Authors: Samoilova Nadezhda A. , Krayukhina Maria A. , Naumkin Alexander V. , Korlyukov Alexander A. , Anuchina Nelya M. , Popov Dmitry A.
Published: October 2023

A simple one-pot method is proposed for obtaining the colloidal nanohybrid structures of silver (gold) and zinc oxide as well as nanostructures doped with zinc ions. The copolymers of maleic acid were used for the stabilization of nanoheterostructures. To characterize the preparation, UV–Vis spectroscopy, TEM, FTIR, XPS, and XRD were used. The bactericidal properties of the nanoheterostructures were studied in relation to the fungus C. albicans and the bacteria E. coli and S. aureus, used in planktonic form. In general, the samples containing nanosilver were the most active, and the preparations containing gold nanoparticles were the least active. The minimum inhibitory concentrations (MICs) of the Ag/ZnO samples, based on all copolymers, were in the ranges of 1.4–1.7 μg/mL for C. albicans, 2.9–6.8 μg/mL for E. coli, and 23–27 μg/mL for S. aureus; the MIC values of Au/ZnO samples were 472 μg/mL for S. aureus and 945 μg/mL for C. albicans and E. coli. The additional introduction of zinc cations into heterodimers had practically no effect on the antimicrobial properties of the composites. For all prepared composites and all tested microorganisms, the fractional inhibitory concentration indexes were in the range of 0.5–2.2, which indicates a close-to-additive contribution of the bioactive components in the samples used in the bactericidal process.
A Model for Probiotic Fermented Food Production
Authors: Savo Sardaro Maria Luisa , Zaini Silvia , Amato Katherine Ryan
Published: October 2023

The past few decades have demonstrated how important the human gut microbiota is for human health. Because of this, the use of microbiota-modulating dietary interventions such as probiotics and prebiotics is growing in popularity amongst consumers, food manufacturers, healthcare professionals, and regulators. In particular, there is interest in making a wider variety of foods with probiotic properties. However, as a solution for food manufacturers to produce fermented foods compatible with the “probiotic foods” label definition, we used an impedometric analysis to identify the survival and growth capacity of microbial strains in specific environmental contexts. Using this approach, manufacturers can more effectively select the strains with the highest growth rate for use in probiotic fermented food production trials. To provide a proof of concept, we tested three Lacticaseibacillus rhamnosus probiotic strains growing in milk at different temperatures. We quantified the probiotic’s growth using species-specific primers and quantitative real-time PCR. Overall, our results demonstrate the feasibility of this type of model in facilitating the production of probiotic fermented foods by allowing manufacturers to select strains able to grow under specific conditions. Our model can be used to develop, increase, and target the beneficial health properties of a multitude of fermented foods produced worldwide.
Assessment of Parent–Child Interaction Quality from Dyadic Dialogue
Authors: Lin Chaohao , Bai Ou , Piscitello Jennifer , Robertson Emily L. , Merrill Brittany , Lupas Kellina , Pelham William E.
Published: October 2023

The quality of parent–child interaction is critical for child cognitive development. The Dyadic Parent–Child Interaction Coding System (DPICS) is commonly used to assess parent and child behaviors. However, manual annotation of DPICS codes by parent–child interaction therapists is a time-consuming task. To assist therapists in the coding task, researchers have begun to explore the use of artificial intelligence in natural language processing to classify DPICS codes automatically. In this study, we utilized datasets from the DPICS book manual, five families, and an open-source PCIT dataset. To train DPICS code classifiers, we employed the pre-trained fine-tuned model RoBERTa as our learning algorithm. Our study shows that fine-tuning the pre-trained RoBERTa model achieves the highest results compared to other methods in sentence-based DPICS code classification assignments. For the DPICS manual dataset, the overall accuracy was 72.3% (72.2% macro-precision, 70.5% macro-recall, and 69.6% macro-F-score). Meanwhile, for the PCIT dataset, the overall accuracy was 79.8% (80.4% macro-precision, 79.7% macro-recall, and 79.8% macro-F-score), surpassing the previous highest results of 78.3% accuracy (79% precision, 77% recall) averaged over the eight DPICS classes. These results show that fine-tuning the pre-trained RoBERTa model could provide valuable assistance to experts in the labeling process.
Numerical Study on the Effect and Mechanism of Supporting Pile Equivalent Calculation Methods in Pile–Anchor Support System
Authors: Liu Xiaoyang , Wang Changming , Liu Hailiang , Wu Di
Published: October 2023

In numerical analysis, the pile equivalent calculation method plays a key role in foundation pit calculation results. However, the effect and mechanism of different pile equivalent calculation methods in the foundation pit has remained unclear. To solve this question, based on FLAC3D, four pile equivalent calculation methods were introduced into a typical pile–anchor pit. This research was carried out from the perspective of soil displacement and stress, special points’ stress paths, and the plastic zone. The results revealed that there was a remarkable influence on the calculation results for different pile equivalent calculation methods. Specifically, compared with structural pile elements, displacements near the pile were smaller in solid pile element mode. Moreover, with the increase in excavation depth, stress concentration appeared in the solid pile element mode. The solid support pile with the interface, compared to that without the interface, had less displacement but more stress concentration around the pile, which led the special points’ stress paths around the solid pile to become irregular. Regarding the structural pile elements, it is suggested that both modeling approaches had a similar effect. These findings could help to provide a deeper insight into pile–anchor foundation pit numerical analysis.
A Hybrid Genetic Algorithm-Based Random Forest Model for Intrusion Detection Approach in Internet of Medical Things
Authors: Norouzi Monire , Gürkaş-Aydın Zeynep , Turna Özgür Can , Yağci Mehmet Yavuz , Aydin Muhammed Ali , Souri Alireza
Published: October 2023

The Internet of Medical Things (IoMT) is a bio-network of associated medical devices, which is slowly improving the healthcare industry by focusing its abilities on enhancing personal healthcare benefits with medical data. Moreover, the IoMT tries to deliver sufficient and more suitable medical services at a low cost. With the rapid growth of technology, medical instruments that are widely used anywhere are likely to increase security issues and create safe data transmission issues through resource limitations and available connectivity. Moreover, the patients probably face the risk of different forms of physical harm because of IoMT device attacks. In this paper, we present a secure environment for IoMT devices against cyber-attacks for patient medical data using a new IoMT framework with a hybrid genetic algorithm-based random forest (GA-RF) model. The proposed algorithm achieved better results in terms of accuracy (99.999%), precision, and recall (100%, respectively) to detect cyber-attacks based on two NSL-KDD and UNSW_2018_IoT_Botnet data sets than the other machine learning algorithms.
A Comprehensive Review and Analysis of Nanosensors for Structural Health Monitoring in Bridge Maintenance: Innovations, Challenges, and Future Perspectives
Authors: Han Daguang , Hosamo Haidar , Ying Chunli , Nie Ruimin
Published: October 2023

This paper presents a thorough review and detailed analysis of nanosensors for structural health monitoring (SHM) in the context of bridge maintenance. With rapid advancements in nanotechnology, nanosensors have emerged as promising tools for detecting and assessing the structural integrity of bridges. The objective of this review is to provide a comprehensive understanding of the various types of nanosensors utilized in bridge maintenance, their operating principles, fabrication techniques, and integration strategies. Furthermore, this paper explores the challenges associated with nanosensor deployment, such as signal processing, power supply, and data interpretation. Finally, the review concludes with an outlook on future developments in the field of nanosensors for SHM in bridge maintenance.
Land Subsidence Prediction Model Based on the Long Short-Term Memory Neural Network Optimized Using the Sparrow Search Algorithm
Authors: Qiu Peicheng , Liu Fei , Zhang Jiaming
Published: October 2023

Land subsidence is a prevalent geological issue that poses significant challenges to construction projects. Consequently, the accurate prediction of land subsidence has emerged as a focal point of research among scholars and experts. Traditional mathematical models exhibited certain limitations in forecasting the extent of land subsidence. To address this issue, the sparrow search algorithm (SSA) was introduced to optimize the efficacy of the long short-term memory (LSTM) neural network in land subsidence prediction. This prediction model has been successfully applied to the Huanglong Commercial City project in the Guanghua unit of Wenzhou city, Zhejiang province, China, and has been compared with the predictions of other models. Using monitoring location 1 as a reference, the MAE, MSE, and RMSE of the test samples for the LSTM neural network optimized using the SSA are 0.0184, 0.0004, and 0.0207, respectively, demonstrating a commendable predictive performance. This new model provides a fresh strategy for the land subsidence prediction of the project and offers new insights for further research on combined models.
Sentiment Analysis on Algerian Dialect with Transformers
Authors: Benmounah Zakaria , Boulesnane Abdennour , Fadheli Abdeladim , Khial Mustapha
Published: October 2023

The task of extracting sentiment from text has been widely studied in the field of natural language processing. However, little work has been conducted specifically on the Arabic language with the Algerian dialect. In this research, we aim to make a significant contribution to the field of sentiment analysis on the Algerian dialect by creating a custom and relatively large dataset with a tailored deep learning model. The dataset was extracted from Algerian YouTube channels and manually annotated by the research team. We then utilize this dataset to train a state-of-the-art deep learning model for natural language processing called BERT, which is a type of Transformer model. Using this model, we were able to achieve an F1-score of 78.38% and an accuracy of 81.74% on the testing set. This demonstrates the effectiveness of our approach and the potential of using BERT for sentiment analysis on the Algerian dialect. Our model can be used to infer sentiment from any Algerian text, thus providing a valuable tool for understanding the opinions and emotions of the population. This research highlights the importance of studying the Algerian dialect and the potential of using state-of-the-art deep learning models for natural language processing in this area.
Predicting Swell in Clay-Sand Mixtures Used in Liners
Authors: Dafalla Muawia
Published: October 2023

A method to predict the swellability of clay-sand mixtures is proposed. This model is a modified form of the Studds (1997) prediction model for clay-sand mixtures. The new proposed model uses the laboratory fall cone penetration technique to produce a characterization chart. This chart presents slope levels that can be used to obtain an equation for the final clay void ratio versus the vertical effective stress for clays. The porosity of the clay-sand mixtures was worked out based on a correction factor obtained from compression and porosity measurements in the laboratory. The porosity of the mixture was merged into the clay profile equation to compute the final clay void ratio at a specified stress level, which made it possible to predict the swelling behavior for different and variable stress levels. The swellability slope was obtained using fall cone tests conducted on the fine portion. Mixtures of kaolinite and bentonite were introduced to represent soils with different swell potentials. The fall cone measurements of a few points can be used to establish the swellability relationships for natural clay. Merging fall cone points with the swellability slope chart can define the profile of the vertical effective stress versus the clay void ratio.
Data-Driven Agricultural Innovation Technology for Digital Agriculture
Authors: Kim Wan-Soo
Published: October 2023

Food security issues are emerging worldwide due to rapid climate change and war [...]
Dietary Behavior of Spanish Schoolchildren in Relation to the Polygenic Risk of Obesity
Authors: Calderón García Andrea , Pedrero Tomé Roberto , Alaminos-Torres Ana , Prado Martínez Consuelo , Martínez Álvarez Jesús Román , López Ejeda Noemí , Cabañas Armesilla María Dolores , Marrodán Serrano María Dolores
Published: October 2023

Several precedents support an association between single nucleotide genetic polymorphisms (SNPs), the obese phenotype, and eating behavior in the infant-juvenile population. This study aims to study this aspect in depth, analyzing the eating behavior of a sample of schoolchildren from Madrid in regard to their genetic predisposition to obesity. A total of 258 schoolchildren, aged 6 to 16 years, were evaluated through the Children’s Eating Behaviour Questionnaire (CEBQ) and the genotyping of 32 SNPs. Associations were observed between the total genetic risk score and eating behaviors related to emotional eating and food responsiveness. Individually, different SNPs were associated with eating behaviors, primarily those related to pro-eating behaviors or increased risk of developing obesity. However, diverse results are obtained, depending on the SNP. These results highlighted the strongest associations between the rs1801725 SNP risk allele (CASR) and increased enjoyment of food by 1846-fold. Likewise, the satiety response was associated with SNP rs11676272 (ADCY3) 2.39 and SNP rs7566605 (INSIG2), increasing this response by 2.39 and 1.63 times, respectively. Emotional anti-ingesting behaviors were inversely associated with SNP rs1421085 (FTO) and SNP rs987237 (TFAP2B). In contrast, SNP rs55915917 (CRHR1) increased the risk of these behaviors. SNPs rs4788099 (SH2B1), rs6857 (NECTIN2), and rs180172 (ADCY3) were associated with slow feeding. In conclusion, associations were found between most of the analyzed SNPs and the CEBQ items. This suggests that feeding behavior exists as a mediator between genotype and obesity phenotype, beginning in childhood.
Nitrogen Metabolism and Antioxidant Capacity of Selected Vegetables from Organic and Conventional Crops
Authors: Chadzinikolau Tamara , Formela-Luboińska Magda
Published: October 2023

The study aimed to determine the level of selected indicators of nitrogen metabolism in vegetables from organic (organic food store) and conventional (supermarket and local market) crops. Nitrates, total chlorophyll content, and the activity of the nitrate biosynthesis pathway enzymes—nitrate reductase (NR) and glutamine synthetase (GS)—were determined in the leaves of selected species from different plant families. The research material consisted of dill, carrot, celery, beet, onion, Chinese and white cabbage, and rocket. The nitrate content was within the permissible limits, except for vegetables bought at a local market. In most cases, no significant differences in the level of nitrates between organic and conventional farming were observed. The analyses revealed the highest nitrate content in dill [2.16 mg × g−1] and the lowest in onions [0.06 mg × g−1] from conventional crops. The enzyme activities were related to the level of nitrates. The analysed species differed in phenolic compounds, ascorbate levels, and total antioxidant capacity (TCA). Positive correlations were found between TCA and antioxidants.
Automated Detection of Social Conflict Drivers in Civil Infrastructure Projects Using Natural Language Processing
Authors: Baek Seungwon , Namgoong Do , Won Jinwoo , Han Seung H.
Published: October 2023

Early detection and mitigation of social conflict in civil infrastructure projects is essential due to its significant impact on project performance and social governance. Nevertheless, there is no scientific system for monitoring conflict drivers in a timely manner in practice. Furthermore, previous studies of social conflict in the civil engineering and management domains have relied on manual literature reviews and case studies. Although these qualitative approaches have provided context-specific insights, they are limited in their generalizability and broad perspectives. Against this backdrop, this study presents an automated process for detecting conflict drivers from news articles using ChatGPT. The authors collected news articles related to civil infrastructure projects implemented in the Republic of Korea using web crawling. Then, ChatGPT was used to extract conflict-related keyphrases from the article collections and classify the keyphrases into predefined conflict drivers. The result showed a notable performance with a micro average F1-score of 85.7%. Moreover, the authors confirmed the validity of the keyphrase extraction and classification results through two illustrative case studies. The proposed process and methods contribute to facilitating data-driven conflict management. Although this study focused on conflict drivers of public infrastructure projects, other types of information extraction tasks can benefit from the presented framework.
A Through-Transmission Ultrasonic Method for the Detection of Ferrite Tile Defects
Authors: Huang Kaiheng , Li Qiaolin , Zhu Kaixiong , Chen Baihan , Qian Xiang , Wang Xiaohao , Li Xinghui
Published: October 2023

A through-transmission ultrasonic method is proposed to address limitations in conventional ultrasonic reflection methods for non-destructive testing of ferrite tiles. The method utilizes a dual-probe configuration on both sides of the test piece to measure ultrasonic transmission signals, overcoming issues related to blind zones and orientation limitations in pulse-echo reflection methods. This method demonstrates excellent capabilities for full inspection of internal and external defects in ferrite tiles. Physical field finite element simulations were conducted to analyze detection capabilities and a transmissive testing system is developed based on the simulation results. Experimental validation was performed on artificially manufactured quantified defect samples in aluminum alloy, and the same testing system was applied to evaluate ferrite tile samples. The results confirmed the effectiveness of the system in distinguishing defective (NG) signals from normal defect-free (OK) signals, with a recall rate of at least 95% on samples of various sizes up to 0.1 mm. This research provides insights for quality control and defect detection technology in ferrite tiles.
CETD: Counterfactual Explanations by Considering Temporal Dependencies in Sequential Recommendation
Authors: He Ming , An Boyang , Wang Jiwen , Wen Hao
Published: October 2023

Providing interpretable explanations can notably enhance users’ confidence and satisfaction with regard to recommender systems. Counterfactual explanations demonstrate remarkable performance in the realm of explainable sequential recommendation. However, current counterfactual explanation models designed for sequential recommendation overlook the temporal dependencies in a user’s past behavior sequence. Furthermore, counterfactual histories should be as similar to the real history as possible to avoid conflicting with the user’s genuine behavioral preferences. This paper presents counterfactual explanations by Considering temporal dependencies (CETD), a counterfactual explanation model that utilizes a variational autoencoder (VAE) for sequential recommendation and takes into account temporal dependencies. To improve explainability, CETD employs a recurrent neural network (RNN) when generating counterfactual histories, thereby capturing both the user’s long-term preferences and short-term behavior in their real behavioral history. Meanwhile, CETD fits the distribution of reconstructed data (i.e., the counterfactual sequences generated by VAE perturbation) in a latent space, and leverages learned variance to decrease the proximity of counterfactual histories by minimizing the distance between the counterfactual sequences and the original sequence. Thorough experiments conducted on two real-world datasets demonstrate that the proposed CETD consistently surpasses current state-of-the-art methods.
Decarbonizing the Atmosphere Using Carbon Capture, Utilization, and Sequestration: Challenges, Opportunities, and Policy Implications in India
Authors: Gupta Abhishek , Paul Akshoy Ranjan , Saha Suvash C.
Published: October 2023

The IPCC’s (Intergovernmental Panel on Climate Change) special report highlights the urgent necessity of limiting global warming to 1.5 °C, prompting a vital exploration of decarbonization methods. Carbon capture and sequestration (CCS) play a pivotal role in reducing carbon dioxide emissions from industrial processes and power generation, helping to combat climate change and meet global decarbonization goals. This article focuses on the economic prospects and market potential of carbon capture technologies in India, specifically in utilizing captured CO2 in the power, petrochemicals, and fertilizer sectors. It also emphasizes decarbonization through carbon sequestration involving geological storage to extract carbon dioxide from the environment, ultimately reducing greenhouse gas emissions. This article stresses the need to develop new technologies for carbon capture, utilization, and sequestration to overcome technical and financial barriers. It highlights the importance of improving efficiency, reducing costs, and scaling up these technologies for widespread adoption. Additionally, this study delves into the essential policy and regulatory frameworks for CCUS implementation, emphasizing the need for standards and laws to ensure safety, environmental protection, and effective monitoring in the Indian context. The research findings and recommendations provide valuable insights for future CCUS implementation, advancing sustainable decarbonization efforts in India and globally.
The St. Benedict Facility: Probing Fundamental Symmetries through Mixed Mirror β-Decays
Authors: Porter William S. , Bardayan Daniel W. , Brodeur Maxime , Burdette Daniel P. , Clark Jason A. , Gallant Aaron T. , Houff Alicen M. , Kolata James J. , Liu Biying , O’Malley Patrick D. , Quick Caleb , Rivero Fabio , Savard Guy , Valverde Adrian A. , Zite Regan
Published: October 2023

Precise measurements of nuclear beta decays provide a unique insight into the Standard Model due to their connection to the electroweak interaction. These decays help constrain the unitarity or non-unitarity of the Cabibbo–Kobayashi–Maskawa (CKM) quark mixing matrix, and can uniquely probe the existence of exotic scalar or tensor currents. Of these decays, superallowed mixed mirror transitions have been the least well-studied, in part due to the absence of data on their Fermi to Gamow-Teller mixing ratios (ρ). At the Nuclear Science Laboratory (NSL) at the University of Notre Dame, the Superallowed Transition Beta-Neutrino Decay Ion Coincidence Trap (St. Benedict) is being constructed to determine the ρ for various mirror decays via a measurement of the beta–neutrino angular correlation parameter (aβν) to a relative precision of 0.5%. In this work, we present an overview of the St. Benedict facility and the impact it will have on various Beyond the Standard Model studies, including an expanded sensitivity study of ρ for various mirror nuclei accessible to the facility. A feasibility evaluation is also presented that indicates the measurement goals for many mirror nuclei, which are currently attainable in a week of radioactive beam delivery at the NSL.
Color Image Recovery Using Generalized Matrix Completion over Higher-Order Finite Dimensional Algebra
Authors: Liao Liang , Guo Zhuang , Gao Qi , Wang Yan , Yu Fajun , Zhao Qifeng , Maybank Stephen John , Liu Zhoufeng , Li Chunlei , Li Lun
Published: October 2023

To improve the accuracy of color image completion with missing entries, we present a recovery method based on generalized higher-order scalars. We extend the traditional second-order matrix model to a more comprehensive higher-order matrix equivalent, called the “t-matrix” model, which incorporates a pixel neighborhood expansion strategy to characterize the local pixel constraints. This “t-matrix” model is then used to extend some commonly used matrix and tensor completion algorithms to their higher-order versions. We perform extensive experiments on various algorithms using simulated data and publicly available images. The results show that our generalized matrix completion model and the corresponding algorithm compare favorably with their lower-order tensor and conventional matrix counterparts.
Solutions of Time Fractional (1 + 3)-Dimensional Partial Differential Equations by the Natural Transform Decomposition Method (NTDM)
Authors: Gadallah Musa Rahamh , Eltayeb Hassan
Published: October 2023

The current study employs the natural transform decomposition method (NTDM) to test fractional-order partial differential equations (FPDEs). The present technique is a mixture of the natural transform method and the Adomian decomposition method. For the purpose of checking the precis of our technique, some examples are offered, and the series solutions of these equations are introduced by using NTDM. The outcome shows that the suggested approach is very active and straightforward for obtaining a series solutions of FPDEs and is more accurate if we compare it with existing methods.