bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolomics Analysis of Rabbit Plasma after Ocular Exposure to Vapors of Sulfur Mustard
Authors: Bouhlel Jihéne , Caffin Fanny , Gros-Désormeaux Fanny , Douki Thierry , Benoist Jean-François , Castelli Florence A. , Chu-Van Emeline , Piérard Christophe , Junot Christophe , Fenaille François
Published: June 2024

Sulfur mustard (SM) is a highly potent alkylating vesicant agent and remains a relevant threat to both civilians and military personnel. The eyes are the most sensitive organ after airborne SM exposure, causing ocular injuries with no antidote or specific therapeutics available. In order to identify relevant biomarkers and to obtain a deeper understanding of the underlying biochemical events, we performed an untargeted metabolomics analysis using liquid chromatography coupled to high-resolution mass spectrometry of plasma samples from New Zealand white rabbits ocularly exposed to vapors of SM. Metabolic profiles (332 unique metabolites) from SM-exposed (n = 16) and unexposed rabbits (n = 8) were compared at different time intervals from 1 to 28 days. The observed time-dependent changes in metabolic profiles highlighted the profound dysregulation of the sulfur amino acids, the phenylalanine, the tyrosine and tryptophan pathway, and the polyamine and purine biosynthesis, which could reflect antioxidant and anti-inflammatory activities. Taurine and 3,4-dihydroxy-phenylalanine (Dopa) seem to be specifically related to SM exposure and correspond well with the different phases of ocular damage, while the dysregulation of adenosine, polyamines, and acylcarnitines might be related to ocular neovascularization. Additionally, neither cysteine, N-acetylcysteine, or guanine SM adducts were detected in the plasma of exposed rabbits at any time point. Overall, our study provides an unprecedented view of the plasma metabolic changes post-SM ocular exposure, which may open up the development of potential new treatment strategies.
Experiments on High-Resolution Digitizer Accuracy in Measuring Voltage Ratio and Phase Difference of Distorted Harmonic Waveforms above 2 kHz
Authors: Dewayalage Imanka , Robinson Duane A. , Elphick Sean , Perera Sarath
Published: June 2024

High-resolution multi-channel digitizers are used extensively for precision low voltage measurements in numerous applications and allow the simultaneous measurement of voltage magnitude ratio and phase difference between two different waveforms in power system applications. Delta–sigma-based analog-to-digital conversion enables the use of sampling frequencies in the range of megahertz, which provides accurate measurement bandwidths for transformed high-frequency, high-voltage signals. With the increased use of power electronic converters contributing to high-frequency harmonic emissions in power systems, there is a growing interest in developing calibration systems to measure voltage ratio and phase difference of distorted fundamental frequency waveforms consisting of superimposed, high-frequency harmonics. However, information regarding the accuracy of the high-resolution digitizers in the measurement of distorted voltage waveforms is limited as characterization is typically performed under sinusoidal voltage waveform conditions. This paper presents the details of the accuracy characterization of a 24-bit resolution digitizer under both sinusoidal and distorted waveform conditions for measuring complex voltage ratio and phase error for frequencies up to 10 kHz. The detailed experimental results and the measurement uncertainty evaluations show that increased voltage ratio and phase difference errors should be allocated when these high-resolution digitizers are used to measure distorted voltage waveforms. The estimated expanded uncertainties of complex voltage ratio measurement and phase error measurement for harmonic frequencies up to 10 kHz are ±260 ppm and ±100 µrad, respectively.
Fabrication of Bulk Tungsten Microstructure Arrays for Hydrophobic Metallic Surfaces Using Inductively Coupled Plasma Deep Etching
Authors: Wang Zetian , Xia Yanming , Song Lu , Chen Jing , Wang Wei
Published: June 2024

Hydrophobic surfaces have attracted great attention due to their ability to repel water, and metallic surfaces are particularly significant as they have several benefits, for example they self-clean and do not corrode in marine environments, but also have several applications in the aircraft, building and automobile industries. Tungsten is an ideal material for metallic surfaces due to its remarkable mechanical properties. However, conventional micromachining methods of micro- or nanostructures, including mechanical fabrication and laser and wet etching are incapable of balancing functionality, consistency and cost. Inspired by the etching process of silicon, deep etching of bulk tungsten has been developed to achieve versatile microstructures with the advantages of high efficiency, large scale and low cost. In this article, fabrication methods of tungsten-based hydrophobic surfaces using an ICP deep etching process were proposed. Micro- or hierarchical structure arrays with controllable sidewall profiles were fabricated by optimizing etching parameters, which then exhibited hydrophobicity with contact angles of up to 131.8°.
Leaf Health Status Regulates Endophytic Microbial Community Structure, Network Complexity, and Assembly Processes in the Leaves of the Rare and Endangered Plant Species Abies fanjingshanensis
Authors: Li Long , Zheng Rong , Wang Zuhua , Li Haibo , Shi Yongjia , Pan Zhongjie , Liu Min
Published: June 2024

The rare and endangered plant species Abies fanjingshanensis, which has a limited habitat, a limited distribution area, and a small population, is under severe threat, particularly due to poor leaf health. The plant endophytic microbiome is an integral part of the host, and increasing evidence indicates that the interplay between plants and endophytic microbes is a key determinant for sustaining plant fitness. However, little attention has been given to the differences in the endophytic microbial community structure, network complexity, and assembly processes in leaves with different leaf health statuses. Here, we investigated the endophytic bacterial and fungal communities in healthy leaves (HLs) and non-healthy leaves (NLs) of A. fanjingshanensis using 16S rRNA gene and internal transcribed spacer sequencing and evaluated how leaf health status affects the co-occurrence patterns and assembly processes of leaf endophytic microbial communities based on the co-occurrence networks, the niche breadth index, a neutral community model, and C-score metrics. HLs had significantly greater endophytic bacterial and fungal abundance and diversity than NLs, and there were significant differences in the endophytic microbial communities between HLs and NLs. Leaf-health-sensitive endophytic microbes were taxonomically diverse and were mainly grouped into four ecological clusters according to leaf health status. Poor leaf health reduced the complexity of the endophytic bacterial and fungal community networks, as reflected by a decrease in network nodes and edges and an increase in degrees of betweenness and assortativity. The stochastic processes of endophytic bacterial and fungal community assembly were weakened, and the deterministic processes became more important with declining leaf health. These results have important implications for understanding the ecological patterns and interactions of endophytic microbial communities in response to changing leaf health status and provide opportunities for further studies on exploiting plant endophytic microbes to conserve this endangered Abies species.
Green Roof Substrate Microbes Compose a Core Community of Stress-Tolerant Taxa
Authors: Van Dijck Thomas , Stevens Vincent , Steenaerts Laure , Thijs Sofie , Van Mechelen Carmen , Artois Tom , Rineau François
Published: June 2024

Extensive green roofs provide for many ecosystem services in urban environments. The efficacy of these services is influenced by the vegetation structure. Despite their key role in plant performance and productivity, but also their contribution to nitrogen fixation or carbon sequestration, green roof microbial communities have received little attention so far. No study included a spatiotemporal aspect to investigate the core microbiota residing in the substrates of extensive green roofs, although these key taxa are hypothesized to be amongst the most ecologically important taxa. Here, we identified the core microbiota residing in extensive green roof substrates and investigated whether microbial community composition is affected by the vegetation that is planted on extensive green roofs. Eleven green roofs from three different cities in Flanders (Belgium), planted either with a mixture of grasses, wildflowers and succulents (Sedum spp.; Sedum–herbs–grasses roofs) or solely species of Sedum (Sedum–moss roofs), were seasonally sampled to investigate prokaryotic and fungal communities via metabarcoding. Identifying the key microbial taxa revealed that most taxa are dominant phylotypes in soils worldwide. Many bacterial core taxa are capable of nitrogen fixation, and most fungal key taxa are stress-tolerant saprotrophs, endophytes, or both. Considering that soil microbes adapted to the local edaphic conditions have been found to improve plant fitness, further investigation of the core microbiome is warranted to determine the extent to which these stress-tolerant microbes are beneficial for the vegetational layer. Although Sedum–herbs–grasses roofs contained more plant species than Sedum–moss roofs, we observed no discriminant microbial communities between both roof types, likely due to sharing the same substrate textures and the vegetational layers that became more similar throughout time. Future studies are recommended to comprehensively characterize the vegetational layer and composition to examine the primary drivers of microbial community assembly processes.
Identifying Minerals from Image Using Out-of-Distribution Artificial Intelligence-Based Model
Authors: Ji Xiaohui , Liang Kaiwen , Yang Yang , Yang Mei , He Mingyue , Zhang Zhaochong , Zeng Shan , Wang Yuzhu
Published: June 2024

Deep learning has increasingly been used to identify minerals. However, deep learning can only be used to identify minerals within the distribution of the training set, while any mineral outside the spectrum of the training set is inevitably categorized erroneously within a predetermined class from the training set. To solve this problem, this study introduces the approach that combines a One-Class Support Vector Machine (OCSVM) with the ResNet architecture for out-of-distribution mineral detection. Initially, ResNet undergoes training using a training set comprising well-defined minerals. Subsequently, the first two layers obtained from the trained ResNet are employed to extract the discriminative features of the mineral under consideration. These extracted mineral features then become the input for OCSVM. When OCSVM discerns the mineral in the training set’s distribution, it triggers the subsequent layers within the trained ResNet, facilitating the accurate classification of the mineral into one of the predefined categories encompassing the known minerals. In the event that OCSVM identifies a mineral outside of the training set’s distribution, it is categorized as an unclassified or ‘unknown’ mineral. Empirical results substantiate the method’s capability to identify out-of-distribution minerals while concurrently maintaining a commendably high accuracy rate for the classification of the 36 in-distribution minerals.
Paleoredox Conditions, Paleoproductivity, and Terrigenous Sediment Influx of the Lower-Middle Cenomanian Strata in the Abu Gharadig Basin, Northern Egypt
Authors: Mansour Ahmed , Wagreich Michael , Tahoun Sameh S. , Ahmed Mohamed S. , Gentzis Thomas
Published: June 2024

During the Late Cretaceous (Cenomanian), significant disruptions in the carbon cycle, global warming, and episodes of oceanic anoxia occurred, leading to the deposition of organic carbon-rich sediments. In well BED2-3, located in the BED2 gas field within the Abu Gharadig Basin (north Western Desert, Egypt), the lower-to-middle Cenomanian Bahariya Formation displays thick alternating layers of sandstones, siltstones, and shales. Detailed geochemical analyses were conducted on thirty-three cutting samples from the Bahariya Formation, focusing on total organic carbon (TOC), whole-rock elemental geochemistry, and carbonate content. These geochemical measurements provided valuable information regarding paleoredox conditions, marine biological productivity, terrigenous sediment influx, weathering and paleoclimate conditions, and mechanisms influencing organic matter accumulation. The enrichment factors (EF) of redox-sensitive trace elements were utilized to infer oxygenation conditions and marine biological productivity during the deposition of the Bahariya Formation. The stratigraphic distribution of redox-sensitive elements allowed for the Bahariya Formation to be categorized into lower and middle-upper intervals. The results revealed that the lower interval exhibited strong-to-enriched EF values of redox-sensitive elements and fair-to-rich TOC content, indicating a prevalent anoxic setting during deposition. In contrast, the middle-upper interval displayed weakly-to-slightly enriched EF values with poor-to-fair TOC content, suggesting deposition under oxic-suboxic redox conditions. By examining Al-normalized redox-sensitive ratios and their correlations with TOC content, significant relationships were observed in the lower interval, indicating a coupling between the enrichment of redox-sensitive elements and organic matter. This suggests enhanced biological productivity during deposition of the lower interval compared to the relatively low productivity during deposition of the middle-upper interval of the formation. These conditions controlled the production and preservation of organic matter in the lower interval, while the middle-upper interval suffered from organic matter dilution and destruction due to an increased influx of terrigenous material and lower biological productivity. Geochemical proxies related to detrital materials provided evidence of alternating terrigenous sediment flux, consistent with shifts between coarse- and fine-grained fractions and related facies of sandstones, siltstones, and shales. These findings align with active continental weathering in the source terrane and deposition under enhanced warm-humid climatic conditions, with intermittent arid-to-semi-arid phases. These conclusions are further supported by the palynomorph assemblages and clay mineralogy within the Bahariya Formation.
Unveiling the Unusual Mn(CO)3 Migration in a Manganese Cyclohexenyl Complex by DFT Computations
Authors: Liang Guangchao , Zhang Min
Published: June 2024

Homogeneous catalysis involving a transition metal agostic interaction (TM…H…C) is an attractive strategy for C–H bond activation, in which the transition metal agostic intermediates serve as the critical component. To investigate the roles of manganese agostic intermediates in the unusual migration of the Mn(CO)3 fragment in the (exo-phenyl)(η3-cyclohexenyl)manganese tricarbonyl [(Ph)(η3-C6H8)Mn(CO)3] (complex 1) under the protonation of tetrafluoroboric acid–diethyl ether (HBF4.Et2O), a comprehensive density functional theory (DFT) theoretical study was performed. The computational results showed that formation of the [(cyclohex-3-enyl)-η6-benzene]manganese tricarbonyl complex [(C6H9)(η6-Ph)Mn(CO)3+][BF4] (complex 2) was achieved via a series of mono-agostic and di-agostic intermediates. The overall rate-limiting step for this unusual migration of the Mn(CO)3 fragment is the formation of the di-agostic (η2-phenyl)manganese complex 8 (4 → 5 → 8) with a Gibbs barrier of 15.4 kcal mol−1. The agostic intermediates with TM…H…C agostic interactions were well-characterized by geometry parameters, Atoms-In-Molecules (AIM) analyses, and the Natural Adaptive Orbitals (NAdOs). The located pathways in the current study successfully explained the experimental observations, and the findings on the TM…H…C agostic interaction provided a new aspect of the catalytic reaction with the manganese complex.
Comprehensive Quality Assessment of Brassica napus L. Seeds via HPTLC, LC-QToF, and Anatomical Investigation
Authors: Tileuberdi Nazym , Katragunta Kumar , Adams Sebastian John , Aldana-Mejía Jennyfer A. , Omarbekova Ardak , Avula Bharathi , Khan Ikhlas A. , Turgumbayeva Aknur , Ross Samir A.
Published: June 2024

The Brassicaceae family, commonly referred to as cruciferous plants, is globally cultivated and consumed, with the Brassica genus being particularly renowned for its functional components. These vegetables are rich sources of nutrients and health-promoting phytochemicals, garnering increased attention in recent years. This study presents a comprehensive microscopic, chromatographic, and spectroscopic characterization of Brassica napus L. seeds from Kazakhstan aimed at elucidating their morphological features and chemical composition. Microscopic analysis revealed distinct localization of flavonoids, total lipids, and alkaloids. High-performance thin-layer chromatography (HPTLC) analysis of seed extracts demonstrated a complex chemical profile with significant quantities of non-polar compounds in the hexane extracts. Additionally, methanolic extracts revealed the presence of diverse chemical compounds, including alkaloids, flavonoids, and glucosinolates. The chemical composition exhibited varietal differences across different Brassica species, with B. napus L. seeds showing higher concentrations of bioactive compounds. Furthermore, liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QToF-MS) analysis provided insights into the chemical composition, with sinapine isomers, feruloyl, and sinapoyl choline derivatives as major compounds in the seeds. This study contributes to a better understanding of the chemical diversity and quality control methods’ approximations of B. napus L. seeds, highlighting their importance in functional food and nutraceutical applications.
Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning
Authors: Zhang Pengjie , Xu Jiwei , Du Bin , Yang Qianyu , Liu Bing , Xu Jianjie , Tong Zhaoyang
Published: June 2024

The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be overlooked. The spectral features of the fourteen class samples were preprocessed and extracted by machine learning algorithms to serve as input data for training purposes. The two types of spectral data were classified using classification models. The partial least squares discriminant analysis (PLS-DA) model achieved classification accuracies of 78.57% and 92.85%, respectively. The Raman spectral data were accurately classified by the support vector machine (SVM) algorithm, with a 100% accuracy rate. The two spectra and their fusion data were correctly classified with 100% accuracy by the random forest (RF) algorithm. The spectral processed algorithms investigated provide an efficient method for eliminating the impact of pollen interference.
Massage It Out: Physiological Responses to a Percussive Therapy Device Used Intra-Resistance Exercise
Authors: Greene Daniel R. , Ruiz-Ramie Jonathan J. , Craig-Jones Andrew
Published: June 2024

Percussive therapy devices have been proven effective at reducing muscle inflammation, soreness, and tension and improving the range of motion before or after exercise. However, there is a notable lack of research on percussive therapy intra-exercise. Purpose: Examine the physiological responses (i.e., sets/reps) to percussive therapy during single-arm biceps curls (BCs) and single-leg quadriceps extensions (LEs). Methods: Participants [N = 26, 10 females] completed an initial 10-repetition maximum (10 RM) for BCs and LEs. Following that, participants completed two testing sessions in which BCs and LEs were completed at their 10 RM until functional failure (i.e., <7 reps completed). Participants completed two testing sessions in which all body parts received percussive therapy at 25 Hz for 60 s between sets and no percussive therapy. Results: Participants completed more sets [p = 0.002; Cohen’s d = 0.54] and reps [p = 0.005; Cohen’s d = 0.51] during the control condition relative to the percussive therapy condition. There were no differences between body parts (i.e., BC vs. LE) or interaction effects. Conclusion: This study provides evidence that low-frequency long-duration percussive therapy used intra-resistance exercise decreases performance parameters.
Degradation and Photocatalytic Properties of Nanocomposites
Authors: Kasak Peter
Published: June 2024

The world is suffering from energy consumption and environmental pollution challenges for the next generation era [...]
Electrospray Ionization—Mass Spectrometry Characterization of Pine Bark Extracts
Authors: Conde Mireia , Solé Maria Mercè , Sorolla Sílvia , Casas Concepció , Bacardit Anna
Published: June 2024

This study explored the potential application of polyphenols from Pinus halepensis bark in leather tanning. The primary objective was to characterize these polyphenols. The extraction and atomization processes proved efficient, reducing moisture content to 7.4%, increasing tannin content from 26.2% to 45.1%, and reducing insoluble substances by 77.5%. High-performance liquid chromatography (HPLC) coupled with mass spectrometry identified and quantified various polyphenolic compounds, including (+)-catechin, (+)-taxifolin, protocatechuic acid, and procyanidin B2. Notably, tannic catechin dimers were detected. Lignin was effectively removed through filtration. Concentrations of protocatechuic acid, (+)-catechin, (+)-taxifolin, (−)-epicatechin, and procyanidin B1 were significantly higher in the extract than in the powder, with the extract showing 1214.3 mg/kg of protocatechuic acid, 2098.0 mg/kg of (+)-catechin, 4017.0 mg/kg of (+)-taxifolin, 2163.0 mg/kg of (−)-epicatechin, and 917.0 mg/kg of procyanidin B1.
The Abundance of Microplastics in the World’s Oceans: A Systematic Review
Authors: Mutuku Judith , Yanotti Maria , Tocock Mark , Hatton MacDonald Darla
Published: June 2024

Microplastics are ubiquitous in marine environments and have been documented across all ocean compartments, especially surface waters, across the world. Even though several studies identify the presence of microplastics in the world’s five oceans, there remains an overt problem of large inconsistencies in their sampling, extraction, and consequent quantification. Despite the complexity of these methodologies, researchers have tried to explore microplastic abundance in ocean surface waters. Using a systematic review approach, a dataset was derived from 73 primary studies undertaken since the year 2010 following the Oslo and Paris Conventions (OSPAR) guidelines to monitor and harmonise marine debris. The results showed differences in the abundance and distribution of microplastics in surface waters across oceans. The overall concentration of microplastics in all five oceans ranged between 0.002 and 62.50 items/m3, with a mean abundance of 2.76 items/m3. The highest mean concentration of microplastics was found in the Atlantic (4.98 items/m3), while the least was observed in the Southern Ocean (0.04 items/m3). While challenging, this paper recommends harmonisation of the sampling, separation, and identification methods across the globe to aid in the design of the appropriate mitigation strategies for reducing marine plastic pollution.
Participation in Elite Sport in Youth and Its Impact on Lifelong Bone Health
Authors: Marriott Amelia , Kirkham-Wilson Fiona , Dennison Elaine
Published: June 2024

Weight-bearing physical activity is considered beneficial to bone health throughout the course of life, with the most marked benefits for bone health often considered to be high levels of activity around the time of peak bone mass (PBM) acquisition. To date, the research focus has been on the benefits of recreational weight-bearing sporting activity. Participation in elite sport is associated with enhanced sporting activity but is often also associated with low body weight, menstrual disturbance in females, and rest periods following injury. The benefit of sporting activity may, therefore, be attenuated in these groups. Here, we undertook a systematic review to consider what evidence is available regarding whether elite sporting activity in young adulthood has lasting benefits for bone health. Studies of retired athletes aged >50 years, who participated in elite sport from 15 to 30 years, were considered for inclusion. Elite sport was defined as participation at the national level or above. Following protocol development, the search strategy was applied to PubMed, Medline, Embase, and Web of Science. The selection was managed with Rayyan software, and the bias was assessed using the Newcastle–Ottawa scale. Two reviewers independently identified papers; a third adjudicated and screened the final selection for consideration. The protocol was registered with PROSPERO (CRD42021293644). Two reviewers screened 951 articles, of which 4 papers met the inclusion criteria. One paper reported findings in women and three in men; no paper included both sexes. The sample sizes varied from 24 to 193 and considered football, endurance running, weightlifting, and swimming. Bone density was measured at the femoral neck, trochanter, and lumbar spine. All studies reported higher density in former athletes than non-elite controls, though the information available regarding confounding lifestyle factors was variable. A meta-analysis was not possible as studies were too heterogenous. In conclusion, from the limited available evidence, our study suggests elite sporting activity in young adulthood may have lasting benefits for bone health. However, given the paucity of available data, we highlight an urgent need for future research, especially in female athletes.
Genetic Complexity of CC5 Staphylococcus aureus Isolates Associated with Sternal Bursitis in Chickens: Antimicrobial Resistance, Virulence, Plasmids, and Biofilm Formation
Authors: Silva Vanessa , Ribeiro Jessica , Teixeira Pedro , Pinto Pedro , Vieira-Pinto Madalena , Poeta Patrícia , Caniça Manuela , Igrejas Gilberto
Published: June 2024

Sternal bursitis, a common inflammatory condition in poultry, poses significant challenges to both animal welfare and public health. This study aimed to investigate the prevalence, antimicrobial resistance, and genetic characteristics of Staphylococcus aureus isolates associated with sternal bursitis in chickens. Ninety-eight samples were collected from affected chickens, and 24 S. aureus isolates were identified. Antimicrobial susceptibility testing revealed resistance to multiple agents, with a notable prevalence of aminoglycoside resistance genes. Whole genome sequencing elucidated the genetic diversity and virulence profiles of the isolates, highlighting the predominance of clonal complex 5 (CC5) strains. Additionally, biofilm formation assays demonstrated moderate biofilm production capacity among the isolates. These findings underscore the importance of vigilant monitoring and targeted interventions to mitigate the impact of sternal bursitis in poultry production systems.
Advances in Laboratory Diagnosis of Coronavirus Infections in Cattle
Authors: van den Hurk Shaun , Regmi Girija , Naikare Hemant K. , Velayudhan Binu T.
Published: June 2024

Coronaviruses cause infections in humans and diverse species of animals and birds with a global distribution. Bovine coronavirus (BCoV) produces predominantly two forms of disease in cattle: a respiratory form and a gastrointestinal form. All age groups of cattle are affected by the respiratory form of coronavirus, whereas the gastroenteric form causes neonatal diarrhea or calf scours in young cattle and winter dysentery in adult cattle. The tremendous impacts of bovine respiratory disease and the associated losses are well-documented and underscore the importance of this pathogen. Beyond this, studies have demonstrated significant impacts on milk production associated with outbreaks of winter dysentery, with up to a 30% decrease in milk yield. In North America, BCoV was identified for the first time in 1972, and it continues to be a significant economic concern for the cattle industry. A number of conventional and molecular diagnostic assays are available for the detection of BCoV from clinical samples. Conventional assays for BCoV detection include virus isolation, which is challenging from clinical samples, electron microscopy, fluorescent antibody assays, and various immunoassays. Molecular tests are mainly based on nucleic acid detection and predominantly include conventional and real-time polymerase chain reaction (PCR) assays. Isothermal amplification assays and genome sequencing have gained increased interest in recent years for the detection, characterization, and identification of BCoV. It is believed that isothermal amplification assays, such as loop-mediated isothermal amplification and recombinase polymerase amplification, among others, could aid the development of barn-side point-of-care tests for BCoV. The present study reviewed the literature on coronavirus infections in cattle from the last three and a half decades and presents information mainly on the current and advancing diagnostics in addition to epidemiology, clinical presentations, and the impact of the disease on the cattle industry.
Distribution and Pathogenicity Differentiation of Physiological Races of Verticillium dahliae from Cotton Stems in Western China
Authors: Zhang Jianwei , Jiamahate Aerguli , Feng Hui , Bozorov Tohir A. , Zhang Dawei , Guo Jianwei , Yang Honglan , Zhang Daoyuan
Published: June 2024

Verticillium wilt, caused by the pathogenic fungus Verticillium dahliae, has emerged as a severe threat to cotton globally. However, little is known about the genetic diversity of this pathogen in an infected single cotton plant. In this study, we isolated three new V. dahliae strains from the disease stems of Gossypium hirsutum from the cotton field in Western China and assessed their pathogenicity to the cotton cultivar Xinnongmian-1 and its two transgenic lines, as well as two laboratory strains, VD592 and VD991. These three new V. dahliae strains were identified using DNA barcodes of tryptophan synthase (TS), actin (ACT), elongation factor 1-α (EF), and glyceraldehyde-3-phosphate dehydrogenase (GPD). Moreover, the haplotype analysis revealed that the three new races had distinct haplotypes at the TS locus. Furthermore, the results of culture features and genetic diversity of ISSR (inter-simple sequence repeat) revealed that there were separate V. dahliae strains, which were strong defoliating pathotypes belonging to race 2 type, as determined by particular DNA marker recognition. The identified strains demonstrated varied levels of pathogenicity by leaf disc and entire plant inoculation methods. Conservatively, these strains showed some pathogenicity on cotton lines, but were less pathogenic than the reference strains. The findings revealed that several strong defoliating V. dahliae pathotypes coexist on the same cotton plant. It indicats the importance of regular monitoring as an early warning system, as well as the detection and reporting of virulent pathogen strains and their effects on crop response.
Wheat Fusarium Head Blight Automatic Non-Destructive Detection Based on Multi-Scale Imaging: A Technical Perspective
Authors: Feng Guoqing , Gu Ying , Wang Cheng , Zhou Yanan , Huang Shuo , Luo Bin
Published: June 2024

Fusarium head blight (FHB) is a major threat to global wheat production. Recent reviews of wheat FHB focused on pathology or comprehensive prevention and lacked a summary of advanced detection techniques. Unlike traditional detection and management methods, wheat FHB detection based on various imaging technologies has the obvious advantages of a high degree of automation and efficiency. With the rapid development of computer vision and deep learning technology, the number of related research has grown explosively in recent years. This review begins with an overview of wheat FHB epidemic mechanisms and changes in the characteristics of infected wheat. On this basis, the imaging scales are divided into microscopic, medium, submacroscopic, and macroscopic scales. Then, we outline the recent relevant articles, algorithms, and methodologies about wheat FHB from disease detection to qualitative analysis and summarize the potential difficulties in the practicalization of the corresponding technology. This paper could provide researchers with more targeted technical support and breakthrough directions. Additionally, this paper provides an overview of the ideal application mode of the FHB detection technologies based on multi-scale imaging and then examines the development trend of the all-scale detection system, which paved the way for the fusion of non-destructive detection technologies of wheat FHB based on multi-scale imaging.
A Novel Underlying Algorithm for Reducing Uncertainty in Process Industry Risk Assessment
Authors: Zhang Yuanyuan , Zhao Long
Published: June 2024

Normal fuzzy fault tree is a classic model in the field of process industry risk assessment, and it can provide reliable prior knowledge for machine learning. However, it is difficult to adapt the traditional approximate calculation method to highly nonlinear problems, and this may introduce model uncertainty. To solve this problem, this study proposes an accurate calculation algorithm. In the proposed algorithm, first, an exact α-cut set of normal fuzzy fault tree is derived according to the exact calculation formula of normal fuzzy numbers and in combination with the cut-set theorem. Subsequently, the relationship between the membership function and the exact cut set is derived based on the representation theorem. Finally, according to the previous derivation, the coordinates of the point on the exact membership curve are found within the range of x from 0 to 1. Based on this, an accurate membership graph is drawn, the membership curve is evenly divided with the area enclosed by the x-axis, and the fuzzy median is obtained. The results of the two chemical accident cases demonstrate that the proposed algorithm has a strong ability to handle uncertainty and can significantly reduce the uncertainty of the process industry risk assessment results. The results also reveal that the superiority of the accurate calculation algorithms becomes more obvious when the mean failure probability of basic events is larger or the accident tree is more complex. This study provides a high-accuracy underlying algorithm for process industry risk assessment, and it is of great value for improving system security.
Non-Backdrivable Wedge Cam Mechanism for a Semi-Active Two-Axis Prosthetic Ankle
Authors: Greene Michael J. , Fischman Ekman Simões Ivan , Lewis Preston R. , Nichols Kieran M. , Adamczyk Peter G.
Published: June 2024

Frontal plane ankle motion is important for balance in walking but is seldom controlled in robotic prostheses. This article describes the design, control and performance of a semi-active two-degree-of-freedom robotic prosthetic ankle. The mechanism uses a non-backdrivable wedge cam system based on rotating inclined planes, allowing actuation only during swing phases for low power, light weight and compactness. We present details of the mechanism and its kinematic and mechatronic control, and a benchtop investigation of the system’s speed and accuracy in ankle angle control. The two-axis ankle achieves angular reorientation movements spanning ±10 deg in any direction in less than 0.9 s. It achieves a plantarflexion/dorsiflexion error of 0.35 ± 0.27 deg and an inversion/eversion error of 0.29 ± 0.25 deg. Backdriven motion during walking tests is negligible. Strengths of the design include self-locking behavior for low power and simple kinematic control. Two-axis ankle angle control could enable applications such as balance augmentation, turning assistance, and wearable perturbation training.
Experience in Processing Alternative Crude Oils to Replace Design Oil in the Refinery
Authors: Stratiev Dicho , Shiskova Ivelina , Toteva Vesislava , Georgiev Georgi , Dinkov Rosen , Kolev Iliyan , Petrov Ivan , Argirov Georgi , Bureva Veselina , Ribagin Simeon , Atanassov Krassimir , Nenov Svetoslav , Sotirov Sotir , Nikolova Radoslava , Veli Anife
Published: June 2024

A comprehensive investigation of a highly complex petroleum refinery (Nelson complexity index of 10.7) during the processing of 11 crude oils and an imported atmospheric residue replacing the design Urals crude oil was performed. Various laboratory oil tests were carried out to characterize both crude oils, and their fractions. The results of oil laboratory assays along with intercriteria and regression analyses were employed to find quantitative relations between crude oil mixture quality and refining unit performance. It was found that the acidity of petroleum cannot be judged by its total acid number, and acid crudes with lower than 0.5 mg KOH/g and low sulphur content required repeated caustic treatment enhancement and provoked increased corrosion rate and sodium contamination of the hydrocracking catalyst. Increased fouling in the H-Oil hydrocracker was observed during the transfer of design Urals crude oil to other petroleum crudes. The vacuum residues with higher sulphur, lower nitrogen contents, and a lower colloidal instability index provide a higher conversion rate and lower fouling rate in the H-Oil unit. The regression equations developed in this work allow quantitative assessment of the performance of crucial refining units like the H-Oil, fluid catalytic cracker, naphtha reformer, and gas oil hydrotreatment based on laboratory oil test results.
Potential of Attapulgite/Humic Acid Composites for Remediation of Cd-Contaminated Soil
Authors: Ren Hanru , Ren Jun , Tao Ling , Ren Xuechang , Li Yunmeng , Jiang Yuchen , Lv Mairong
Published: June 2024

Stabilizing materials were prepared by different ratios of attapulgite/humic acid composites, and the optimum proportion for the remediation of Cd-polluted soils was found. The results suggested that the bioavailability of Cd in soil was decreased by the application of material prepared with humic acid and attapulgite in a ratio of 1:5. CaCl2-Cd, diethylenetriaminepentaacetic acid (DTPA-Cd) and the toxicity characteristic leaching procedure (TCLP-Cd) were reduced by 34.03%, 26.62% and 43.66%, and the ecological risk was depressed accordingly. The addition of stabilizing materials could transform the acid-soluble and reducible speciation to residue speciation, with a ratio of 1:5, significantly increasing the residue proportion of Cd in soil. The content of the residue state was increased by 63.13%, and the content of the acid-soluble state was significantly decreased by 34.10% compared with the control. The bioavailability, acid-soluble and reducible speciation of Cd had a highly negative correlation with the growth of corn, and the accumulation of Cd in corn had a significantly negative correlation with the residue speciation. Attapulgite/humic acid composites can reduce the bioavailability and increase the ratio of residue Cd in soil effectively, and they have the potential to remediate the pollution of heavy metals in soil.
Soil Heavy Metal(loid) Pollution Evaluation, Risk Assessment, and Source Analysis of a Mineral Processing Plant
Authors: Luo Wenping , Wei Pingtang , Zhang Yan , Sun Chengshuai
Published: June 2024

Yunnan Province is rich in mineral resources. Early mining, processing, metallurgy, and other mining activities produce three industrial wastes (waste water, waste gas, and waste residue) causing environmental pollution. Considering the legacy site of a mineral processing plant in Yunnan as the research object, 21 sampling points in the study area and 12 control sampling points in the periphery were set up to determine the contents of the heavy metal(loid)s As, Hg, Cd, Cu, Ni, Pb, and Cr in the soil. The spatial distribution of heavy metal(loid)s was interpolated and analyzed using Arcmap10.8, and combined with the single-factor index, Nemero Comprehensive Pollution Index, and the health risk assessment method for the heavy metal(loid) pollution status and health risk of the soil were evaluated. The soil in the study area was acidic, with the largest average value of elemental As and the largest percentages of control and screening values. The results of the single-factor and Nemero composite pollution index showed the following trend: As > Pb > Cd > Cu > Ni > Hg. Cd, Cu, and Pb mainly originate from mining and metallurgy and Hg from the combustion of fossil fuels, while soil-forming substrates are the main sources of Ni. Pollution by As was the most prominent element, whereas pollution by Cd, Cu, and Pb in some areas also cannot be ignored to prevent negative impacts on residents. It is recommended to remediate and treat the soil on site for public events; therefore, this study fills the gap in studying potential ecological risks, human health risk assessments, and sources of exposure (oral ingestion, respiratory ingestion, dermal contact).
Delineating Landscape Features Perception in Tourism-Based Traditional Villages: A Case Study of Xijiang Thousand Households Miao Village, Guizhou
Authors: Wang Ziyang , Zhou Qixuan , Man Tianjiao , He Lai , He Yiwen , Qian Yi
Published: June 2024

This study is a feature perception study of traditional village landscapes, refines the research method of traditional village landscape features using tourists online comment data, combs the landscape perception features of Xijiang Thousand Households Miao Village from tourists perspectives, digs out the managers’ problems in landscape planning, protection, utilisation, and puts forward the corresponding improvement strategies. In this paper, the Octopus data collector was used to collect online evaluation data from nine target platforms, and ROST CM6 was used to analyse the data for word frequency analysis, semantic network analysis, and sentiment analysis. Finally, using Nvivo12, the data was coded and a multidimensional model of landscape perception was constructed: natural landscapes, cultural and social landscapes, perceived landscapes, seasonal landscapes, and services and infrastructures. The results show that in the landscape perception model, the cultural and social landscape modules are the core factors affecting tourists’ psychological perceptions, with most tourists holding positive emotions towards the scenic spots and a few negative emotions mainly focusing on the relatively weak natural landscape, the unsatisfactory road system and charging system, and the over-commercialised development. In response to these problems, this study proposes corresponding planning recommendations. The results of the study reflect the trend of deep integration of culture and tourism in traditional villages in China, respond to the policy guidance of China’s rural revitalisation policy, and provide useful references and insights for the landscape construction and development of the Xijiang Thousand Households Miao Village and even similar tourist-oriented traditional villages.
Evaluation of Ecological Sensitivity and Spatial Correlation Analysis of Landscape Patterns in Sanjiangyuan National Park
Authors: Liu Tianshu , Peng Xiangbin , Li Junjie
Published: June 2024

The Sanjiangyuan region, situated on the Qinghai–Tibetan Plateau, constitutes an exceptionally delicate ecological environment. Alterations in the region’s ecological landscape stem not only from natural factors but also from significant anthropogenic influences, exerting a notable impact on the sustainable economic and social development of the region’s middle and lower reaches. Consequently, investigating changes in the landscape pattern of Sanjiangyuan National Park holds paramount importance for comprehending the formation mechanism of spatial landscape distribution in the area. This study analyzes the ecological sensitivity and landscape pattern of Sanjiangyuan National Park in Qinghai Province, China, utilizing ArcGIS 10.8 and Fragstats 4.2. Employing the bivariate spatial autocorrelation analysis method, the research uncovers the spatial distribution characteristics between ecological sensitivity and landscape pattern, along with their aggregated change traits. The findings reveal that ecological sensitivity areas within the park encompass varying degrees, ranging from extremely sensitive to insensitive. The area of moderately sensitive zones in the Yellow River source region is 7279.67 km2 (39.17%), whereas the corresponding area in the Yangtze River source region is 32,572.34 km2 (36.30%). The eastern and northern parts of the Sanjiangyuan National Park exhibit significant landscape fragmentation. Ecological sensitivity varies markedly across different regions, with the southern and some northern areas showing higher sensitivity. In the Lancang River source park and the southern part of the Yellow River source park, the Largest Patch Index (LPI) and Ecological Sensitivity Index exhibit a high–high (HH) clustering pattern, indicating strong ecological connectivity in these areas. These regions also feature high Total Edge (TE), Number of Patches (NP), Patch Density (PD), and Edge Density (ED), indicating a complex landscape structure and abundant habitat edge areas. The study recommends restoring ecological connectivity in highly fragmented areas and implementing strict protection measures in sensitive regions to maintain ecosystem health and biodiversity. These findings provide a foundation for developing targeted ecological protection measures to enhance ecosystem health and biodiversity conservation in the area. This research aligns with several Sustainable Development Goals (SDGs), including Climate Action, Life on Land, and Clean Water and Sanitation, by promoting sustainable ecosystem management and biodiversity conservation.
A Novel Approach for the Analysis of Ship Pollution Accidents Using Knowledge Graph
Authors: Hu Junlin , Zhou Weixiang , Zheng Pengjun , Liu Guiyun
Published: June 2024

Ship pollution accidents can cause serious harm to marine ecosystems and economic development. This study proposes a ship pollution accident analysis method based on a knowledge graph to solve the problem that complex accident information is challenging to present clearly. Based on the information of 411 ship pollution accidents along the coast of China, the Word2vec’s word vector models, BERT–BiLSTM–CRF model and BiLSTM–CRF model, were applied to extract entities and relations, and the Neo4j graph database was used for knowledge graph data storage and visualization. Furthermore, the case information retrieval and cause correlation of ship pollution accidents were analyzed by a knowledge graph. This method established 3928 valid entities and 5793 valid relationships, and the extraction accuracy of the entities and relationships was 79.45% and 82.47%, respectively. In addition, through visualization and Cypher language queries, we can clearly understand the logical relationship between accidents and causes and quickly retrieve relevant information. Using the centrality algorithm, we can analyze the degree of influence between accident causes and put forward targeted measures based on the relevant causes, which will help improve accident prevention and emergency response capabilities and strengthen marine environmental protection.