bluuebunny/crossref_metadata_2025 huggingface dataset:
How three-dimensional forest structure regulates the amount and timing of snowmelt across a climatic gradient of snow persistence
Authors: Dwivedi Ravindra , Biederman Joel A. , Broxton Patrick D. , Pearl Jessie K. , Lee Kangsan , Svoma Bohumil M. , van Leeuwen Willem J. D. , Robles Marcos D.
Published: May 2024

Across the western United States, forests are changing rapidly, with uncertain impacts on snowmelt water resources. Snow partitioning is controlled by forest effects on interception, radiation, and sublimation. Yet, models often lack snow measurements with sufficiently high spatial and temporal resolution across gradients of forest structure to accurately represent these fine-scale processes. Here, we utilize four Snowtography stations in Arizona, in the lower Colorado River Basin, with daily measurements over 3–5 years at ~110 positions distributed across gradients of forest structure resulting from wildfires and mechanical thinning. We combine Snowtography with lidar snapshots of forest and snow to train a high-resolution snow model and run it for 6 years to quantify how forest structure regulates snowpack and snowmelt. These study sites represent a climate gradient from lower/warmer ephemeral snowpack (~2,100 m asl) to higher/colder seasonal snowpack (~2,800 m asl). Forest cover reduced snowpack and snowmelt through canopy sublimation. Forest advanced snowmelt timing at lower/warmer sites but delayed it at higher/colder sites. Within canopy gaps, shaded cool edges had the greatest peak snow water equivalent (SWE). Surprisingly, sunny/warm gap edges produced more snowmelt than cool edges, because high radiation melted snow quickly, reducing exposure to sublimation. Therefore, peak SWE is not an ideal proxy for snowmelt volume from ephemeral snowpacks, which are becoming more prevalent due to warming. The results imply that forest management can influence the amount and timing of snowmelt, and that there may be decision trade-offs between enhancing forest resilience through delayed snowmelt and maximizing snowmelt volumes for downstream water resources.
Optimization Design of Straw-Crushing Residual Film Recycling Machine Frame Based on Sensitivity and Grey Correlation Degree
Authors: Zhao Pengda , Lyu Hailiang , Wang Lei , Zhang Hongwen , Li Zhantao , Li Kunyu , Xing Chao , Guoyao Bocheng
Published: May 2024

This paper takes the frame as the research object and explores the vibration characteristics of the frame to address the vibration problem of a 1-MSD straw-crushing and residual film recycling machine in the field operation process, and an accurate identification of the modal parameters of the frame is carried out to solve the resonance problem of the machine, which can achieve cost reduction and increase income to a certain extent. The first six natural frequencies of the frame are extracted by finite element modal identification and modal tests, respectively. The rationality of the modal test results is verified using the comprehensive modal and frequency response confidences. The maximum frequency error of modal frequency results of the two methods is only 6.61%, which provides a theoretical basis for the optimal design of the frame. In order to further analyze the resonance problem of the machine, the external excitation frequency of the machine during normal operation in the field is solved and compared with the first six natural frequencies of the frame. The results show that the first natural frequency of the frame (18.89 Hz) is close to the external excitation generated by the stripping roller (16.67 Hz). The first natural frequency and the volume of the frame are set as the optimization objectives, and the optimal optimization scheme is obtained by using the Optistruct solver, sensitivity method, and grey correlation method. The results indicate the first-order natural frequency of the optimized frame is 21.89 Hz, an increase of 15.882%, which is much higher than the excitation frequency of 16.67 Hz, and resonance can be avoided. The corresponding frame volume is 9.975 × 107 mm3, and the volume reduction is 3.46%; the optimized frame has good dynamic performance, which avoids the resonance of the machine and conforms to the lightweight design criteria of agricultural machinery structures. The research results can provide some theoretical reference for this kind of machine in solving the resonance problem and carrying out related vibration characteristics research.
Effects of Soil Quality Decline on Soil-Dwelling Mesofaunal Communities in Agricultural Lands of the Mollisols Region, China
Authors: Ma Chen , Yao Xin , Du Guoming
Published: May 2024

Soil quality decline can adversely affect ecosystem health and land productivity, with soil-dwelling mesofauna considered to potentially fulfill vital functions in accurately predicting these outcomes. However, the current state of research reveals a gap concerning the relationships between soil quality decline and soil-dwelling mesofauna in the Mollisols Region. For a more profound understanding of this issue, we conducted a comprehensive investigation of soil-dwelling mesofaunal communities in the different agricultural lands of the Mollisols Region. In this study, soil-dwelling mesofauna were collected, and 11 soil properties were determined following standard procedures, with soil quality levels quantified by utilizing soil quality index (SQI). Our results revealed that there was a gradient of soil quality across the different agricultural lands, which were divided into five levels, including very strong, strong, medium, weak, and very weak. Subsequently, this investigation provided empirical evidence that the decline in soil quality had implications for soil-dwelling mesofaunal communities in agricultural lands of the Mollisols region. A consistent decrease in the density of soil-dwelling mesofauna was observed with the decline of soil quality. In contrast, a greater richness was observed in areas with relatively weaker soil quality, suggesting that the consequences of soil quality decline on soil-dwelling mesofauna were not exclusively negative. Various taxa of soil-dwelling mesofauna exhibited varying degrees of response to the decline in soil quality. Oribatida was overwhelmingly dominant in the sampling fields with medium soil quality, and most Entomobryidae were found in agricultural lands with very weak soil quality. During soil quality decline, soil nutrients were observed to correlate positively with the density of soil-dwelling mesofauna. Overall, the outcomes of this investigation carry significance for comprehending how soil quality decline relates to soil-dwelling mesofauna, and can provide valuable ecological insights for formulating biodiversity guidelines targeted at preserving soil resources in the Mollisols region.
The Effect of Combined Application of Biocontrol Microorganisms and Arbuscular Mycorrhizal Fungi on Plant Growth and Yield of Tomato (Solanum lycopersicum L.)
Authors: Almuslimawi Alaa Abdulkadhim A. , Kuchár Borbála , Navas Susana Estefania Araujo , Turóczi György , Posta Katalin
Published: May 2024

Sustainable plant production requires less use of synthetic chemicals in plant nutrition and protection. Microbial products are among the most promising substitutes for chemicals. With the increasing popularity and availability of such products, it has become obligatory to use different microbes together. The effect of this has been tested in several studies, but their results have sometimes been contradictory depending on the microbial strains tested and the mode of application. We tested the effect of two commercially available antagonists and Funneliformis mosseae alone and in combination on tomato. Mycorrhizal treatment increased plant growth and yield, both alone and combined with the antagonists; however, mycorrhizal root colonization was not influenced by the antagonist. This treatment also led to a slight decrease in the occurrence of Trichoderma spp. on tomato roots but did not impede the colonization of roots by the applied Trichoderma strain. Our result confirmed that Trichoderma asperellum (T34) and Streptomyces griseoviridis (K61) can be safely combined with arbuscular mycorrhizal fungi (AMF), namely with F. mosseae.
Genome-Wide Identification and Expression Analysis of the Broad-Complex, Tramtrack, and Bric-à-Brac Domain-Containing Protein Gene Family in Potato
Authors: Aiana  , Katwal Anita , Chauhan Hanny , Upadhyay Santosh Kumar , Singh Kashmir
Published: May 2024

The BTB (broad-complex, tramtrack, and bric-à-brac) domain, also known as the POZ (POX virus and zinc finger) domain, is a conserved protein–protein interaction domain present in various organisms. In this study, we conducted a genome-wide search to identify and characterize BTB genes in Solanum tuberosum. A total of 57 StBTBs were identified and analyzed for their physicochemical properties, chromosomal distribution, gene structure, conserved motifs, phylogenetic relationships, tissue-specific expression patterns, and responses to hormonal and stress treatments. We found that StBTBs were unevenly distributed across potato chromosomes and exhibited diverse gene structures and conserved motifs. Tissue-specific expression analysis revealed differential expression patterns across various potato tissues, implying their roles in plant growth and development. Furthermore, differential expression analysis under hormonal and stress treatments indicated the involvement of StBTBs in abiotic and biotic stress responses and hormone signaling pathways. Protein–protein interaction analysis identified potential interactions with ribosomal proteins, suggesting roles in translational regulation. Additionally, microRNA target site analysis revealed regulatory relationships between StBTBs and miRNAs. Our study provides a comprehensive understanding of the StBTB gene family in potato, laying the groundwork for further functional characterization and manipulation of these genes to improve stress tolerance and agricultural productivity in potato and related plant species.
A Simple Method for Estimating Stomatal Aperture from Temperature Measurements on Intact Leaves and Wet and Dry Artificial Reference Leaves
Authors: Kitaya Yoshiaki , Ikeda Noboru , Endo Ryosuke , Shibuya Toshio
Published: May 2024

Environmental control in greenhouse horticulture is essential for providing optimal conditions for plant growth and achieving greater productivity and quality. To develop appropriate environmental management practices for greenhouse horticulture through sensing technologies for monitoring the environmental stress responses of plants in real time, we evaluated the relative value of the stomatal opening to develop a technology that continuously monitors stomatal aperture to determine the moisture status of plants. When plants suffer from water stress, the stomatal conductance of leaves decreases, and transpiration and photosynthesis are suppressed. Therefore, monitoring stomatal behavior is important for controlling plant growth. In this study, a method for simply monitoring stomatal conductance was developed based on the heat balance method. The stomatal opening index (SOI) was derived from heat balance equations on intact tomato leaves, wet reference leaves, and dry reference leaves by measuring their temperatures in a growth chamber and a greenhouse. The SOI can be approximated as the ratio of the conductance of the intact leaf to the conductance of the wet reference leaf, which varies from 0 to 1. Leaf temperatures were measured with infrared thermometry. The theoretically and experimentally established SOI was verified with tomato plants grown hydroponically in a greenhouse. The SOI derived by this method was consistent with the leaf conductance measured via the porometer method, which is a standard method for evaluating actual leaf conductance that mainly consists of stomatal conductance. In conclusion, the SOI for the continuous monitoring of stomatal behavior will be useful not only for studies on interactions between plants and the environment but also for environmental management, such as watering at plant production sites.
Leaf Spot Disease of Red Clover Caused by Leptosphaeria weimeri (=Longiseptatispora meliloti) in China
Authors: Zheng Rongchun , Nan Zhibiao , Duan Tingyu
Published: May 2024

Red clover (Trifolium pretense) is widely cultivated as an excellent forage and green manure crop. In 2021, a leaf spot disease was discovered in a red clover field in Min County, Gansu Province, China. Symptoms on T. pratense manifested as small white spots that gradually expanded into nearly oval or irregularly shaped gray-white lesions. The causal agent of this new disease was identified as Leptosphaeria weimeri (=Longiseptatispora meliloti) based on morphological identification, pathogenicity tests, and the phylogenetic identification of ITS, LSU, and SSU sequence. The optimal growth temperature was found to be 20 °C under different culture conditions, while the optimal spore-producing temperature was 25 °C. The pH for optimal growth and spore production was seven. The fungus grew and produced spores successfully on both PDA and PSA media. Additionally, the pathogen was efficiently inhibited using 450 g/L of prochloraz fungicide in vitro. To our knowledge, this is the first report of leaf spot disease on red clover caused by L. meliloti in China.
Study on Water and Salt Transport Characteristics of Sunflowers under Different Irrigation Amounts in the Yellow River Irrigation Area
Authors: Tong Changfu , He Rui , Wang Jun , Zheng Hexiang
Published: May 2024

The control of irrigation volume is of significant importance in arid regions of northwest China. Particularly, it has a crucial impact on the salinization of shallow groundwater areas. In 2022 and 2023, field experiments were conducted to test three distinct under-membrane irrigation treatments. These treatments were assigned water quotas of HW (27 mm), MW (22.5 mm), and LW (18 mm). The HYDRUS-2D model was integrated with a field experiment to accurately simulate the dynamic fluctuations of soil water and salt in the sunflower root zone. The model’s performance was assessed and verified using real-field data from 2022 and 2023, and the simulation results closely matched the measured values. This research also used stable hydroxide isotopes to assess the water supply from various soil layers at different time intervals in sunflower plants. The results indicated that the three different levels of irrigation applied under the membrane had a significant impact on soil water content. Specifically, there was a significant difference in soil water content at a depth of 0–40 cm (p < 0.05), while there was little effect on the water content at a depth of 40–60 cm (p > 0.05). After irrigation, the average salt content in the top 0–20 cm of soil decreased by 7.0% compared to the medium and low irrigation levels, and by 10.8% compared to the medium irrigation level. Additionally, the medium irrigation level resulted in a 10.8% decrease in salt content compared to the low irrigation level, and a 4.1% decrease compared to the medium irrigation level. During the same period, the soil salinity levels at depths of 0–20 cm, 20–40 cm, 40–60 cm, and 60–100 cm in the area outside the membrane were measured to be 2.7~4.8 g·kg−1, 2.8~4.0 g·kg−1, 2.7~3.4 g·kg−1, and 1.7~2.6 g·kg−1, respectively. These levels decreased by 13.1~55.5%, 0.7~42.8%, −0.4~16.2%, and −72.7~7.5%, respectively. Following irrigation, the HW treatment mostly absorbed water in the 0–40 cm soil layer, while the MW and LW treatments absorbed water in both the 0–40 cm and 60–80 cm soil levels. The results indicated that the most optimal drip irrigation method beneath the membrane in this location was achieved when the amount of water applied was between 25–30 mm. This method demonstrated a combination of water conservation, high crop yield, and effective salt suppression.
Navigating the Cyber Threat Landscape: An In-Depth Analysis of Attack Detection within IoT Ecosystems
Authors: AboulEla Samar , Ibrahim Nourhan , Shehmir Sarama , Yadav Aman , Kashef Rasha
Published: May 2024

The Internet of Things (IoT) is seeing significant growth, as the quantity of interconnected devices in communication networks is on the rise. The increased connectivity of devices has heightened their susceptibility to hackers, underscoring the need to safeguard IoT devices. This research investigates cybersecurity in the context of the Internet of Medical Things (IoMT), which encompasses the cybersecurity mechanisms used for various healthcare devices connected to the system. This study seeks to provide a concise overview of several artificial intelligence (AI)-based methodologies and techniques, as well as examining the associated solution approaches used in cybersecurity for healthcare systems. The analyzed methodologies are further categorized into four groups: machine learning (ML) techniques, deep learning (DL) techniques, a combination of ML and DL techniques, Transformer-based techniques, and other state-of-the-art techniques, including graph-based methods and blockchain methods. In addition, this article presents a detailed description of the benchmark datasets that are recommended for use in intrusion detection systems (IDS) for both IoT and IoMT networks. Moreover, a detailed description of the primary evaluation metrics used in the analysis of the discussed models is provided. Ultimately, this study thoroughly examines and analyzes the features and practicality of several cybersecurity models, while also emphasizing recent research directions.
Analysis of Genetic Diversity and Population Structure of Endemic Endangered Goose (Anser cygnoides) Breeds Based on Mitochondrial CYTB
Authors: Qi Shangzong , Fan Suyu , Li Haoyu , He Yufan , Zhang Yang , Zhao Wenming , Xu Qi , Chen Guohong
Published: May 2024

The analysis of the genetic diversity and historical dynamics of endemic endangered goose breeds structure has attracted great interest. Although various aspects of the goose breed structure have been elucidated, there is still insufficient research on the genetic basis of endemic endangered Chinese goose breeds. In this study, we collected blood samples from Lingxiang White (LX), Yan (YE), Yangjiang (YJ), Wuzong (WZ), Xupu (XP), and Baizi (BZ) geese (Anser cygnoides) and used Sanger sequencing to determine the partial sequence of the cytochrome b (CYTB) gene in a total of 180 geese. A total of 117 polymorphic sites were detected in the 707 bp sequence of the mtDNA CYTB gene after shearing and correction, accounting for approximately 16.55% of the entire sequence. The AT content (51.03%) of the processed sequence was slightly higher than the GC content (48.97%), indicating a preference for purine bases. The YJ, YE, and WZ breeds had the highest population genetic diversity, with a haplotype diversity greater than 0.9 (Hd > 0.9) and average population nucleotide difference of 8.01 (K > 8.01). A total of 81 haplotypes were detected and divided into six major branches. Among the six goose breeds, there were frequent genetic exchanges among LX, YJ, YE, and WZ geese (Nm > 15.00). We analyzed the distribution of base-mismatch differences in goose breeds and tested their historical dynamics for neutrality in Tajima’s D and Fu’s Fs. For YJ and WZ geese, Tajima’s D > 0, but the difference was not significant (p > 0.05). The actual values for the two breeds exhibited multimodal Poisson distributions. The population patterns of the WZ and YJ geese are purportedly relatively stable, and the breeds have not experienced population expansions or bottleneck effects, which is consistent with the neutrality test results. This study provides new insights into the diverse genetic origins and historical dynamics that sustain endemic endangered goose breeds.
Effects of Transport Duration and Pre-Transport Fasting on Blood Biochemistry in Dorper × Mongolian Sheep
Authors: Xiao Jin , Han Zhipeng , Li Xintong , Phillips Clive J. C. , Shi Binlin
Published: May 2024

Transport is a high-risk time for sheep, especially if the distances are long and sheep are fasted for a long time beforehand. Two experiments were conducted to compare transport durations of 1 hour (1 h) and 3 hours (3 h) and the effects of feeding before transport using Dorper × Mongolian sheep, which are typical of the region and may be tolerant of the high temperatures in the Inner Mongolian summer. Thirty 4-month-old male sheep were randomly divided into two treatment groups, with 15 sheep/treatment in each experiment, to evaluate the effects on blood biochemical indicators, stress hormone levels, rectal temperatures, and antioxidant status of lambs in summer. In Experiment 1, the levels of triglycerides and free fatty acids after 3 h transport were significantly lower than after 1 h transport (p < 0.05). The levels of thyroxine and malondialdehyde in blood were greater after 3 h transport than 1 h transport (p < 0.05). Creatine kinase levels after 3 h transport tended to be lower than after 1 h transport (p = 0.051). In Experiment 2, the levels of urea and superoxide dismutase in the group fasted pre-transport was significantly lower than those of the group fed pre-transport (p < 0.05). The serum cortisol level in the pre-transport fed group was higher compared to the group fed pre-transport (p = 0.04). Total antioxidant capacity in the pre-transport fasted group tended to be lower compared to that in the pre-transport fed group (p < 0.0001). We conclude that the reduction in nutritional status of sheep transported for longer and without feed pre-transport suggests that transporting sheep in hot conditions in northern China after fasting for a long period should be restricted. However, a decrease in the stress induced by transport following fasting is worthy of further study.
Genomic Characterization of Carbapenemase-Producing Enterobacter hormaechei, Serratia marcescens, Citrobacter freundii, Providencia stuartii, and Morganella morganii Clinical Isolates from Bulgaria
Authors: Sabtcheva Stefana , Stoikov Ivan , Ivanov Ivan N. , Donchev Deyan , Lesseva Magdalena , Georgieva Sylvia , Teneva Deana , Dobreva Elina , Christova Iva
Published: May 2024

Carbapenemase-producing Enterobacter spp. Serratia marcescens, Citrobacter freundii, Providencia spp., and Morganella morganii (CP-ESCPM) are increasingly identified as causative agents of nosocomial infections but are still not under systematic genomic surveillance. In this study, using a combination of whole-genome sequencing and conjugation experiments, we sought to elucidate the genomic characteristics and transferability of resistance genes in clinical CP-ESCPM isolates from Bulgaria. Among the 36 sequenced isolates, NDM-1 (12/36), VIM-4 (11/36), VIM-86 (8/36), and OXA-48 (7/36) carbapenemases were identified; two isolates carried both NDM-1 and VIM-86. The majority of carbapenemase genes were found on self-conjugative plasmids. IncL plasmids were responsible for the spread of OXA-48 among E. hormaechei, C. freundii, and S. marcescens. IncM2 plasmids were generally associated with the spread of NDM-1 in C. freundii and S. marcescens, and also of VIM-4 in C. freundii. IncC plasmids were involved in the spread of the recently described VIM-86 in P. stuartii isolates. IncC plasmids carrying blaNDM-1 and blaVIM-86 were observed too. blaNDM-1 was also detected on IncX3 in S. marcescens and on IncT plasmid in M. morganii. The significant resistance transfer rates we observed highlight the role of the ESCPM group as a reservoir of resistance determinants and stress the need for strengthening infection control measures.
Dissemination of Ceftriaxone-Resistant Salmonella Enteritidis Harboring Plasmids Encoding blaCTX-M-55 or blaCTX-M-14 Gene in China
Authors: Yang Siyuan , Fan Jianzhong , Yu Lifei , He Jintao , Zhang Linghong , Yu Yunsong , Hua Xiaoting
Published: May 2024

Salmonella Enteritidis was the primary foodborne pathogen responsible for acute gastroenteritis. The growing ceftriaxone resistance poses a significant threat to public health. Infection with S. Enteritidis has emerged as a major public health concern, particularly in developing countries. However, research on ceftriaxone-resistant S. Enteritidis (CRO-RSE) remains limited, particularly concerning its resistance mechanism, plasmid structure, and transmission characteristics. This study aims to address these gaps comprehensively. We collected 235 S. Enteritidis isolates from Hangzhou First People’s Hospital between 2010 and 2020. Among these, 8.51% (20/235) exhibited resistance to ceftriaxone. Whole-genome analysis revealed that 20 CRO-RSE isolates harbored blaCTX-M-55 or blaCTX-M-14 on the plasmid. Moreover, the dissemination of the blaCTX-M-type gene was associated with IS26 and ISEcp1. Plasmid fusion entailing the integration of the p1 plasmid with antibiotic resistance genes and the p2 (pSEV) virulence plasmid was observed in certain CRO-RSE. Additionally, the structural analysis of the plasmids unveiled two types carrying the blaCTX-M-type gene: type A with multiple replicons and type B with IncI1 (Alpha) replicon. Type B plasmids exhibited superior adaptability and stability compared to type A plasmids within Enterobacteriaceae. Interestingly, although the type B (S808-p1) plasmid displayed the potential to spread to Acinetobacter baumannii, it failed to maintain stability in this species.
Detection of Salmonella Pathogenicity Islands and Antimicrobial-Resistant Genes in Salmonella enterica Serovars Enteritidis and Typhimurium Isolated from Broiler Chickens
Authors: Ramatla Tsepo , Khasapane Ntelekwane G. , Mlangeni Lungile N. , Mokgokong Prudent , Ramaili Taole , Ndou Rendani , Nkhebenyane Jane S. , Lekota Kgaugelo , Thekisoe Oriel
Published: May 2024

Rapid growth in commercial poultry production is one of the major sources of Salmonella infections that leads to human salmonellosis. The two main Salmonella enterica serovars associated with human salmonellosis are enteritidis and typhimurium. The aim of this study was to determine the prevalence of S. enterica serovars Enteritidis and S. Typhimurium as well as their Salmonella pathogenicity islands (SPI) and antibiotic resistance profiles in broiler chicken feces from slaughterhouses. A total of 480 fecal samples from broiler chickens that were grouped into 96 pooled samples were identified to have Salmonella spp. using the invA gene, whilst the Spy and sdfI genes were used to screen for the presence of S. Enteritidis and S. Typhimurium serovars, respectively, by polymerase chain reaction (PCR) assays. The isolates were also screened for the presence of Salmonella pathogenicity islands (SPIs) using PCR. The disc diffusion assay was performed to determine the antibiotic resistance profiles of the isolates. A total of 36 isolates were confirmed as Salmonella spp. through amplification of the invA gene. Out of 36 confirmed Salmonella spp. a total of 22 isolates were classified as S. Enteritidis (n = 8) and were S. Typhimurium (n = 14) serovars. All (n = 22) S. Enteritidis and S. Typhimurium isolates possessed the hilA (SPI-1), ssrB (SPI-2) and pagC (SPI-11) pathogenicity islands genes. Amongst these serovars, 50% of the isolates (n = 11/22) were resistant to tetracycline and nalidixic acid. Only 22% of the isolates, S. Typhimurium (13.6%) and S. Enteritidis (9.1%) demonstrated resistance against three or more antibiotic classes. The most detected antibiotic resistance genes were tet(K), mcr-1, sulI and strA with 13 (59.1%), 9 (40.9%), 9 (40.9%) and 7 (31.8%), respectively. The findings of this study revealed that S. Typhimurium is the most prevalent serotype detected in chicken feces. To reduce the risk to human health posed by salmonellosis, a stringent public health and food safety policy is required.
Review on Mercury Control during Co-Firing Coal and Biomass under O2/CO2 Atmosphere
Authors: Lyu Qiang , Xin Fei
Published: May 2024

Combining biomass co-firing with oxy-fuel combustion is a promising Bioenergy with Carbon Capture and Storage (BECCS) technology. It has the potential to achieve a large-scale reduction in carbon emissions from traditional power plants, making it a powerful tool for addressing global climate change. However, mercury in the fuel can be released into the flue gas during combustion, posing a significant threat to the environment and human health. More importantly, mercury can also cause the fracture of metal equipment via amalgamation, which is a major risk for the system. Therefore, compared to conventional coal-fired power plants, the requirements for the mercury concentration in BECCS systems are much stricter. This article reviews the latest progress in mercury control under oxy-fuel biomass co-firing conditions, clarifies the impact of biomass co-firing on mercury species transformation, reveals the influence mechanisms of various flue gas components on elemental mercury oxidation under oxy-fuel combustion conditions, evaluates the advantages and disadvantages of various mercury removal methods, and finally provides an outlook for mercury control in BECCS systems. Research shows that after biomass co-firing, the concentrations of chlorine and alkali metals in the flue gas increase, which is beneficial for homogeneous and heterogeneous mercury oxidation. The changes in the particulate matter content could affect the transformation of gaseous mercury to particulate mercury. The high concentrations of CO2 and H2O in oxy-fuel flue gas inhibit mercury oxidation, while the effects of NOx and SO2 are dual-sided. Higher concentrations of fly ash in oxy-fuel flue gas are conducive to the removal of Hg0. Additionally, under oxy-fuel conditions, CO2 and metal ions such as Fe2+ can inhibit the re-emission of mercury in WFGD systems. The development of efficient adsorbents and catalysts is the key to achieving deep mercury removal. Fully utilizing the advantages of chlorine, alkali metals, and CO2 in oxy-fuel biomass co-firing flue gas will be the future focus of deep mercury removal from BECCS systems.
Study on Fault Diagnosis Technology for Efficient Swarm Control Operation of Unmanned Surface Vehicles
Authors: Jeong Sang Ki , Kim Min Kyu , Park Hae Yong , Kim Yoon Chil , Ji Dae-Hyeong
Published: May 2024

The purpose of this study is to design a Swarm Control algorithm for the effective mission performance of multiple unmanned surface vehicles (USVs) used for marine research purposes at sea. For this purpose, external force information was utilized for the control of multiple USV swarms using a lead–follow-formation technique. At this time, to efficiently control multiple USVs, the LSTM algorithm was used to learn ocean currents. Then, the predicted ocean currents were used to control USVs, and a study was conducted on behavioral-based control to manage USV formation. In this study, a control system model for several USVs, each equipped with two rear thrusters and a front lateral thruster, was designed. The LSTM algorithm was trained using historical ocean current data to predict the velocity of subsequent ocean currents. These predictions were subsequently utilized as system disturbances to adjust the controller’s thrust. To measure ocean currents at sea as each USV moves, velocity, azimuth, and position data (latitude, longitude) from the GPS units mounted on the USVs were utilized to determine the speed and direction of the hull’s movement. Furthermore, the flow rate was measured using a flow rate sensor on a small USV. The movement and position of the USV were regulated using an Artificial Neural Network-PID (ANN-PID) controller. Subsequently, this study involved a comparative analysis between the results obtained from the designed USV model and those simulated, encompassing the behavioral control rules of the USV swarm and the path traced by the actual USV swarm at sea. The effectiveness of the USV mathematical model and behavior control rules were verified. Through a comparison of the movement paths of the swarm USV with and without the disturbance learning algorithm and the ANN-PID control algorithm applied to the designed simulator, we analyzed the position error and maintenance performance of the swarm formation. Subsequently, we compared the application results.
The Effect of Icon Color Combinations in Information Interfaces on Task Performance under Varying Levels of Cognitive Load
Authors: Yang Liuxinyue , Qi Bo , Guo Qi
Published: May 2024

In human–computer interaction interfaces, icons serve as highly symbolic elements that convey information and significantly influence the performance of visual search and other tasks. Thus, the selection of appropriate colors plays a crucial role in the design of human–computer interfaces. This study aimed to investigate the effects of icon color combinations on human visual search task performance across various cognitive load conditions. The experiment was divided into two parts, involving a cognitive load test experiment and an icon search task, wherein the former required participants to select the target icon from 16 de-colored icons, and the latter involved selecting the target icon from 16 color combinations of 8 colors (background colors: black, red, blue, and purple; foreground colors: white, yellow, green, and turquoise). A total of 20 participants (11 females and 9 males, all aged between 18 and 24 years) were recruited for this experiment to perform both tasks sequentially. Through a comprehensive consideration of factors such as the NASA-TLX scale, retrieval time, etc., the experimental results revealed that cognitive load increased with time pressure, resulting in varying optimal color combinations for different cognitive load levels. Additionally, background colors did not affect task response time under different cognitive loads, whereas white foreground color was superior to turquoise foreground color in a medium cognitive load environment. Meanwhile, our results recommend prioritizing white-on-black as the preferred color combination, given that it demonstrated excellent cognitive performance in all three cognitive load environments. Conversely, white-on-blue is not recommended as a color combination for the design of high cognitive load environments. Concerning medium cognitive load environments, yellow-on-red or white-on-purple color combinations were preferred. Finally, in low cognitive load environments, white-on-purple is recommended as the primary color combination. Overall, this study provides a theoretical reference for the future design of interactive interface icons across various contexts.
A Novel Deep Learning Method for Detecting Strawberry Fruit
Authors: Shen Shuo , Duan Famin , Tian Zhiwei , Han Chunxiao
Published: May 2024

The recognition and localization of strawberries are crucial for automated harvesting and yield prediction. This article proposes a novel RTF-YOLO (RepVgg-Triplet-FocalLoss-YOLO) network model for real-time strawberry detection. First, an efficient convolution module based on structural reparameterization is proposed. This module was integrated into the backbone and neck networks to improve the detection speed. Then, the triplet attention mechanism was embedded into the last two detection heads to enhance the network’s feature extraction for strawberries and improve the detection accuracy. Lastly, the focal loss function was utilized to enhance the model’s recognition capability for challenging strawberry targets, which thereby improves the model’s recall rate. The experimental results demonstrated that the RTF-YOLO model achieved a detection speed of 145 FPS (frames per second), a precision of 91.92%, a recall rate of 81.43%, and an mAP (mean average precision) of 90.24% on the test dataset. Relative to the baseline of YOLOv5s, it showed improvements of 19%, 2.3%, 4.2%, and 3.6%, respectively. The RTF-YOLO model performed better than other mainstream models and addressed the problems of false positives and false negatives in strawberry detection caused by variations in illumination and occlusion. Furthermore, it significantly enhanced the speed of detection. The proposed model can offer technical assistance for strawberry yield estimation and automated harvesting.
Characteristics and Sources of CBM Well-Produced Water in the Shouyang Block, China
Authors: Zhang Bing , Wang Gang , Li Wei , Jiao Xinglong
Published: May 2024

The Shouyang Block was selected as the research subject. Comprehensive analysis was conducted using coalbed methane (CBM) well production data, geochemical test data on water produced from the coalbed methane well, and fundamental geological information. The findings reveal the water dynamics in the Shouyang Block are characterized by weak groundwater runoff or retention in most areas. The groundwater head height exhibits a gradual decrease from the north to south, which is closely associated with the monoclinic structure of the Shouyang Block. Overall, water production is relatively high. As the average water production increases, the average gas production gradually decreases. A concentration of high water production wells is observed in the northern part of the Shouyang Block, which gradually increases towards the southeast direction. A comprehensive analysis was conducted on the factors influencing water production, including total water content of coal seams, coal seam porosity, groundwater stability index, groundwater sealing coefficient, D value of the fracture fractal dimension, fault fractal dimension, and sand–mud ratio. The correlation degree was calculated and ranked in order of magnitude through grey correlation analysis. The order of factors that influence water production, from strongest to weakest, is as follows: sand–mud ratio > porosity > fractal dimension of fault > fracture fractal dimension D value > groundwater sealing coefficient > groundwater stability index > total water content of coal seams. The dissolution amounts of carbonate and sulfate are both small, and the water source may mainly come from the sandstone aquifer. Attention should be paid to the distribution and lithological combination of sandstone aquifers in coal-bearing strata in the future exploration and development process of the Shouyang Block. This will help to avoid the potential influence of fault structures and enable the identification of favorable areas for low water and high gas production.
An Intelligent Multi-Ring Shield Movement Performance Prediction and Control Method
Authors: Zeng Shaoxiang , Yu Mengfei , Chen Shanmin , Shen Mengfen
Published: May 2024

Accurate control of the shield attitude can ensure precise tunnel excavation and minimize impact on the surrounding areas. However, neglecting the total thrust force may cause excessive disturbance to the strata, leading to collapse. This study proposes a Bayesian optimization-based temporal attention long short-term memory model (BOTA-LSTM) for multi-objective prediction and control of shield tunneling, including shield attitude and total thrust. The model can achieve multi-ring predictions of shield attitude and total thrust by allocating larger weights to significant moments through a temporal attention mechanism. The hyperparameters of the proposed model are automatically selected through Bayesian hyperparameter optimization, which can effectively address the issue of complex parameter selection and optimization difficulties in multi-ring, multi-objective tasks. Based on the predictive results of the optimal model, an intelligent control method that considers both shield attitude and total thrust is proposed. Compared to a method that solely predicts and corrects for the next ring, the proposed multi-ring correction method provides the opportunity for further adjustments, if the initial correction falls short of expectations. A shield tunneling project in Hangzhou is used to demonstrate the effectiveness of the proposed model. The results show that the BOTA-LSTM model outperforms the models without the integration of a temporal attention mechanism and Bayesian hyperparameter optimization. The proposed multi-ring intelligent correction method can adjust the shield attitude and total thrust to a reasonable range, providing references for practical engineering applications.
Performance Evaluation of Convolutional Neural Network Models for Classification of Highway Hidden Distresses with GPR B-Scan Images
Authors: Jin Guanglai , Liu Qilin , Cai Wenlong , Li Mingjie , Lu Congde
Published: May 2024

Despite the considerable advancements in automated identification methods of highway hidden distress with ground-penetrating radar (GPR) images, there still exist challenges in realizing automated identification of highway hidden distress owing to the quantity, variability, and reliability of the distress samples and diversity of classification models. Firstly, the dataset collected contains 31,640 samples categorized into four categories: interlayer debonding, interlayer loosening, interlayer water seepage, and structural loosening from 1500 km highway, for obtaining larger enough samples and covering the variable range of distress samples. Secondly, the distresses were labeled by experienced experts, and the labels were verified with drilled cores to ensure their reliability. Lastly, 18 exemplary convolutional neural network (CNN) models from 8 different architectures were evaluated using evaluation metrics such as precision, recall, and f1-score. Further, confusion matrix and Grad-CAM techniques were utilized to analyze these models. The experimental results show that VGG13 performed most prominently and stably, while the lightweight network SqueezeNet1_1 performed particularly well with a batch size of 64. Furthermore, this study indicates that models with fewer layers can achieve comparable or better performance than deeper models.
Evaluation of the Effect of Primary and Secondary Closure on the Use of Leukocyte and Platelet-Rich Fibrin in Impacted Lower Third Molar Surgery
Authors: Orhan Zeynep Dilan , Ciğerim Levent , Güzel Mehmet , Doğru İbrahim , Alsmadi Mohammad , Kahraman Nazlı Hilal , Hussein Abdalrahim , Tatar Kader
Published: May 2024

The aim of this study was to compare the effect of using L-PRF in patients undergoing impacted lower third molar surgery with either primary or secondary closure techniques. Methods: This prospective, randomized, double-blind, split-mouth clinical trial was conducted on patients with bilateral impacted lower third molars of a similar position. Primary closure was performed in group 1 and secondary closure in group 2. The group 1 closure technique was applied to one side of the patients, and the group 2 closure technique was applied to the other side at different times. Of the 45 patients evaluated, 9 patients were excluded from the study because of alveolitis and failure to attend regular control visits out. Results: Of the 36 patients included in the study, 23 were female and 13 were male, with a mean age of 22.42 ± 3.36 years. The secondary closure group had lower VAS scores at hour 6 (p < 0.05). Pain decreased more in the primary closure group when comparing changes between the VAS scores at 6 hours and 7 days (p < 0.05). Conclusions: The results of this study, showing that both secondary and primary closure are effective, with similar outcomes in terms of pain, swelling, and trismus, should be supported by future clinical trials.
Assessing the Stress Induced by Novel Packaging in GaN HEMT Devices via Raman Spectroscopy
Authors: Dahrouch Zainab , Malta Giuliana , d’Ambrosio Moreno , Messina Angelo Alberto , Musolino Mattia , Sitta Alessandro , Calabretta Michele , Patanè Salvatore
Published: May 2024

Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium-Nitride-based devices, specifically, AlGaN/GaN high-electron-mobility Transistors (HEMTs) with a novel packaging design provided by STMicroelectronics S.r.l. (Catania, Italy). The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of packaging.
High-Dimensional Data Analysis Using Parameter Free Algorithm Data Point Positioning Analysis
Authors: Mustapha S. M. F. D. Syed
Published: May 2024

Clustering is an effective statistical data analysis technique; it has several applications, including data mining, pattern recognition, image analysis, bioinformatics, and machine learning. Clustering helps to partition data into groups of objects with distinct characteristics. Most of the methods for clustering use manually selected parameters to find the clusters from the dataset. Consequently, it can be very challenging and time-consuming to extract the optimal parameters for clustering a dataset. Moreover, some clustering methods are inadequate for locating clusters in high-dimensional data. To address these concerns systematically, this paper introduces a novel selection-free clustering technique named data point positioning analysis (DPPA). The proposed method is straightforward since it calculates 1-NN and Max-NN by analyzing the data point placements without the requirement of an initial manual parameter assignment. This method is validated using two well-known publicly available datasets used in several clustering algorithms. To compare the performance of the proposed method, this study also investigated four popular clustering algorithms (DBSCAN, affinity propagation, Mean Shift, and K-means), where the proposed method provides higher performance in finding the cluster without using any manually selected parameters. The experimental finding demonstrated that the proposed DPPA algorithm is less time-consuming compared to the existing traditional methods and achieves higher performance without using any manually selected parameters.
Nutritional and Medicinal Properties of Microbial Oil
Authors: Uğur Şuheda , Zieniuk Bartłomiej , Fabiszewska Agata
Published: May 2024

Plant and animal oils and fats currently dominate the edible oil market, but a new sustainable alternative of lipids from single-celled organisms has become advantageous in human nutrition and pharmacy. Single-cell oils (SCOs) are lipids biosynthesized and accumulated in the lipid bodies of oleaginous species of bacteria, yeasts, molds, and algae. The review has investigated SCOs’ composition, with a detailed review of the described beneficial impact in medicine, cosmetics, pharmacy, and nutrition. Although microbial oil has been known for more than 100 years, it was not applied until the 21st century, when commercial SCO production for human use started and administrative regulations governing their use were completed. This article discusses the applications of SCOs, which can be easily found in microorganisms, in the pharmaceutical, cosmetic, and food industries. In addition, some aspects of 15- or 17-carbon-atom-long fatty acids were also pointed out. Furthermore, some challenges for heterotrophic single-cell oil synthesis and improvements in its extraction efficiency have also been concluded, which can further contribute to their broadened use in pharmacy, medicine, cosmetics, and food applications.