bluuebunny/crossref_metadata_2025 huggingface dataset:
Exogenous Salicylic Acid Alleviates Water Deficit Stress by Protecting Photosynthetic System in Maize Seedlings
Authors: Xin Longfei , Wang Jiajia , Yang Qinghua
Published: September 2023

Water deficit is a significant abiotic stress affecting crop growth and production. While many studies have indicated that salicylic acid (SA) plays a crucial role in mitigating the detrimental effects of environmental stress on plants, its mechanism regulating the photosynthetic adaptability of maize seedlings under water deficit is still unclear. This study aimed to investigate the impact of exogenous SA on maize seedling performance under polyethylene glycol (PEG)-induced water deficit. The results showed that PEG treatment destroyed the integrity of chloroplast and reduced chlorophyll content and photosynthesis rate (Pn), leading to growth retardation of maize seedlings with lower biomass accumulation and leaf relative water content (RWC). Moreover, chlorophyll fluorescence index, including potential photochemical activity (Fv/Fo), maximum Photosystem II (PSII) quantum yield (Fv/Fm), and energy captured by PSII reaction center for electron transfer (Eto/RC), were decreased, but energy dissipated by unit reaction center (DIo/RC) was enhanced in maize seedlings under water deficit. In addition, PEG treatment also significantly declined the activity of Rubisco and Rubisco activase (RCA) in maize seedlings. In contrast, SA treatment enhanced the content of chlorophyll, as well as the transcription level of psbA, and RCA and Rubisco small subunit (rbcS) reduced the damaging effects of PEG treatment by protecting the integrity of chloroplast and repairing the damaged PSII reaction center, thus positively regulating photosynthetic reaction and water-deficit tolerance in maize seedlings. Our data implied that SA played an important regulatory role in plant resistance to water-deficit stress, and the result will further supply the regulatory network of SA-mediated photosynthetic adaptability.
Nitrogen-Driven Genotypic Diversity of Wheat (Triticum aestivum L.) Genotypes
Authors: Gawdiya Sandeep , Kumar Dinesh , Shivay Yashbir Singh , Radheshyam  , Nayak Somanath , Ahmed Bulbul , Kour Babanpreet , Singh Sahadeva , Sadhukhan Rahul , Malik Sintu , Saini Ravi , Kumawat Anita , Malik Naveen , Dewidar Ahmed Z. , Mattar Mohamed A.
Published: September 2023

Imbalanced use (form, quantity, and ratio) of nitrogen fertilization can result in decreased grain yields and increased nitrogen loss, leading to adverse effects on overall environmental quality. Globally, limited empirical research has been conducted on the comprehensive effects of different levels of N that can significantly influence wheat agronomic and genotypic traits. Therefore, this study aimed to evaluate wheat genotypes for two consecutive years (2020–2021 and 2021–2022) under different N fertilization treatments: N0 (native N, without external application of N), N75 (½ of the recommended dose of N), and N150 (recommended dose of N). The study findings revealed that ‘HD 3249’ and ‘HD 3117’ were the top-performing genotypes in terms of grain yield (5.3 t ha−1; 5.0 t ha−1), straw yield (6.9 t ha−1; 6.7 t ha−1), biological yield (12.2 t ha−1; 11.8 t ha−1), and harvest index (42.9%; 42.4%). In particular, the application of N75 and N150 increased grain yields by 142.6% and 61.3%, respectively; straw yields by 72.3%; and by 110.6% over N0. Furthermore, N levels (N75 and 150) significantly increased the higher concentration of N in grain (23.1% and 33%) and straw (21.1% and 29.8%); N uptake in grain (70.2 and 104.2) and straw (64.8 and 41.5); and total N uptake (68.8% and 101.4%) than N0, respectively. Additionally, correlation analysis revealed that there were positive correlations between yields, harvest index as well as N concentration and uptake. This study identified the two elite genotypes, ‘HD 3249’ and ‘HD 3117’, with N150 splits giving a better response, which can be used as selection criteria for developing wheat varieties that are more efficient in using nitrogen, leading to high yields and N uptake.
Multi-Traits Selection of Maize Hybrids under Sole-Crop and Multiple-Crops with Soybean
Authors: Ruswandi Dedi , Maulana Haris , Karuniawan Agung , Mansyur  , Ismail Ade , Maxiselly Yudithia , Fauzan Mochamad Rafi , Abdullah Muhammad Ali , Yuwariah Yuyun
Published: September 2023

Multi-trait selection is very helpful in plant breeding programs. This technique can select genotypes for specific traits. Yield performance of maize hybrids is influenced by genotype-by-environment interactions (GEIs). This requires multi-environmental testing to identify superior hybrids. The aims of this study were to: (1) select maize hybrids within favorable traits such as grain yield and yield attributes; (2) identify genotype and environment interactions (GEIs) within maize yield; (3) evaluate maize hybrids adaptability to four different locations in West Java; and (4) identify a representative environment for testing and developing new maize hybrids. Twenty-two maize hybrids were evaluated using a randomized block design repeated three times in each environment. The genotype by traits (GT) biplot showed that G3 maize hybrid was superior to ear weight (EW), ear weight without corn husk (EwoH), ear weight per plot (EWP), plant height (PH), ear diameter (ED), and 1000 seed weight (OSW) traits. The G22 maize hybrid was superior to ear weight without corn husk per plot (EwoP), ratio seed weight and ear weight without corn husk (RSEW), grain yield per ha (Y), seed weight (SW), and seed weight per plot (SWP) traits. Combined analysis of variance showed that genotype (G), environment (E), and their interactions (GEIs) had a significant effect on yield (p < 0.01) with contributions of 85.63%, 2.24%, and 12.13%, respectively. The combined stability measurement results and the GGE biplot reveal that G2 is a stable high-yield hybrid, while G4 and G16 are unstable high-yield hybrids. The most representative environment is Arjasari, with the sole-cropping system (ARJ M). This study reveals that the resulting maize hybrid can be useful as a substitute for commercial hybrids currently used. The stable high yield of maize hybrids can be recommended as new varieties with wide adaptation, while unstable high-yield hybrids can be recommended as varieties adapted to specific environments.
Evaluation of Agricultural Water Resources Allocation Efficiency and Its Influencing Factors in the Yellow River Basin
Authors: Zhang Yan , Gao Chao , Liu Chengjian , Li Ping , Chen Xinchi , Liang Zhijie
Published: September 2023

Improving the agricultural water resources allocation efficiency (AWRAE) and promoting the efficient and intensive utilization of agricultural water resources and high-quality development is an effective path to alleviate the water scarcity in one basin. In this study, the AWRAE and its influencing factors were measured and evaluated by constructing the evaluation system of the AWRAE in nine provinces (autonomous regions) of the Yellow River Basin, which consists of the super-efficiency slacks-based model (SBM), standard deviation ellipse (SDE), spatial autocorrelation analysis, Malmquist index and Tobit regression model. The results show that the value of AWRAE is 0.768 and it is at the medium level in the whole Yellow River Basin. The AWRAE values in the nine provinces (autonomous regions) ranking from large to small are Sichuan > Shaanxi > Ningxia > Henan > Inner Mongolia > Shanxi > Qinghai > Shandong > Gansu, and the AWRAE values show a significant increasing trend in Shanxi, Henan, Inner Mongolia and Shandong. The gravity center of the AWRAE keeps wandering along the provincial boundaries of Gansu and Shaanxi, which presents a counterclockwise rotation trend; the AWRAE of Shaanxi exhibits significant H-H aggregation in 2000, 2005, 2010, and 2015 (p < 0.05) while the agglomeration is not significant in 2020. The AWRAE has been continuously improved in which the technological progress change (Techch) and technical efficiency change (Effch) play an important positive role while the pure technical efficiency change (Pech) acts as the negative role in the Yellow River Basin. Moreover, the key influencing factors on the AWRAE in different provinces and autonomous regions are significantly different; for example, the total power of agricultural machinery (AMTP) has a significant positive effect on AWRAE in most provinces, but the annual average precipitation (AAP), agricultural water (AW), water saving irrigated area (WIA) and water saving irrigation machinery (WIM) have significant negative effects on the efficiency of AWRAE in Qinghai. The research results can provide quantitative support for agricultural water-saving and stable grain yield increase in the Yellow River Basin.
Image Segmentation of the Sudd Wetlands in South Sudan for Environmental Analytics by GRASS GIS Scripts
Authors: Lemenkova Polina
Published: September 2023

This paper presents the object detection algorithms GRASS GIS applied for Landsat 8-9 OLI/TIRS data. The study area includes the Sudd wetlands located in South Sudan. This study describes a programming method for the automated processing of satellite images for environmental analytics, applying the scripting algorithms of GRASS GIS. This study documents how the land cover changed and developed over time in South Sudan with varying climate and environmental settings, indicating the variations in landscape patterns. A set of modules was used to process satellite images by scripting language. It streamlines the geospatial processing tasks. The functionality of the modules of GRASS GIS to image processing is called within scripts as subprocesses which automate operations. The cutting-edge tools of GRASS GIS present a cost-effective solution to remote sensing data modelling and analysis. This is based on the discrimination of the spectral reflectance of pixels on the raster scenes. Scripting algorithms of remote sensing data processing based on the GRASS GIS syntax are run from the terminal, enabling to pass commands to the module. This ensures the automation and high speed of image processing. The algorithm challenge is that landscape patterns differ substantially, and there are nonlinear dynamics in land cover types due to environmental factors and climate effects. Time series analysis of several multispectral images demonstrated changes in land cover types over the study area of the Sudd, South Sudan affected by environmental degradation of landscapes. The map is generated for each Landsat image from 2015 to 2023 using 481 maximum-likelihood discriminant analysis approaches of classification. The methodology includes image segmentation by ‘i.segment’ module, image clustering and classification by ‘i.cluster’ and ‘i.maxlike’ modules, accuracy assessment by ‘r.kappa’ module, and computing NDVI and cartographic mapping implemented using GRASS GIS. The benefits of object detection techniques for image analysis are demonstrated with the reported effects of various threshold levels of segmentation. The segmentation was performed 371 times with 90% of the threshold and minsize = 5; the process was converged in 37 to 41 iterations. The following segments are defined for images: 4515 for 2015, 4813 for 2016, 4114 for 2017, 5090 for 2018, 6021 for 2019, 3187 for 2020, 2445 for 2022, and 5181 for 2023. The percent convergence is 98% for the processed images. Detecting variations in land cover patterns is possible using spaceborne datasets and advanced applications of scripting algorithms. The implications of cartographic approach for environmental landscape analysis are discussed. The algorithm for image processing is based on a set of GRASS GIS wrapper functions for automated image classification.
Nest Box Bacterial Loads Are Affected by Cavity Use by Secondary Hole Nesters
Authors: Zabłotni Agnieszka , Kaliński Adam , Glądalski Michał , Markowski Marcin , Skwarska Joanna , Wawrzyniak Jarosław , Bańbura Jerzy
Published: September 2023

Among the environmental factors that affect bird nesting in nest boxes, the influence of microbial communities is relatively poorly understood. In this study, nest boxes used for breeding by secondary cavity nesters were sampled before the start of the breeding season to assess the bacterial loads of the nest box in relation to their previous year status. Different parts of the wooden nest box offer variable conditions for the development of bacteria. During the breeding season, the nest box entrance hole is wiped out by birds, delivering bacteria to their bodies, but during winter, it is exposed to unfavourable external conditions. The interior of the nest box, in turn, is also wiped by birds, but the conditions during winter are more stable there. Therefore, samples from the entrance hole and the interior of the nest box were taken at two different study sites: an urban parkland and a natural forest. We predicted that both the occupancy of the nest boxes during the previous breeding season by birds and the nesting sites would influence the bacterial load of the nest box. To verify this prediction, two categories of nest boxes were sampled at both study sites: nest boxes occupied by any of the two tit species (Great Tit or Blue Tit) in the previous season for breeding and nest boxes that had remained empty that year. The interior bacterial load of the nest box was higher in the nest boxes occupied in the previous breeding season, but only in the forest area. Furthermore, the bacterial load of both the entrance hole of the nest box and the interior was significantly higher in the forest study area in both occupied and unoccupied nest boxes. Our results show that the bacterial load of the nest box is positively related to the presence of nests in the previous breeding season and can vary between different sites.
Differences in Donor Animal Production Stage Affect Repeatability of In Vitro Rumen Fermentation Kinetics
Authors: Jantzen Britt , Hansen Hanne Helene
Published: September 2023

In vitro gas production techniques (IVGPT) are widely used to screen feeds and feed additives to reduce the number of animals needed for experiments, which in turn, reduces costs and increases animal welfare. However, information about repeatability is scarce. The objective of this study was to evaluate the variation from in vitro gas production fermentations in the same laboratory using the same feed substrate. The source of rumen fluid used in the fermentations was from two different farms with either cannulated lactating dairy cows or cannulated fasting heifers, representing two distinct stages of production (donor types). Seventeen 24 h fermentations, undertaken during a year, were used to evaluate the variation between the following parameters: gas curve parameters, baseline-corrected total gas production (TGP (mL at Standard Temperature and Pressure (STP))/g incubated dry matter (DM)), methane concentration (%) and yield (mL gas at STP/g DM), pH and degraded dry matter (dDM). Significant differences between donor types were found for the pH of the rumen fluid from individual animals and pH of fermented fluid. However, no significant differences were observed within donor type. The means for methane concentration and yield, after 24 h of fermentation, were not significantly different between or within donor types. Rate of early gas production was significantly different between donor types, but baseline-corrected TGP was not significantly different at 24 h. No dDM differences after 24 h of fermentation between or within donor types were detected. Gas production curves were different between donor types, being either a monophasic version of the sigmoidal model or an exponential curve for the heifers and the production animals, respectively. No differences were observed within type. Repeatability of rumen fluid (CVRF), calculated as the coefficient of variation, and the associated parameters, which were investigated, was best for methane yield (CVRFALL = 0.3%) and least for TGP at 3 h (CVRFALL = 3%). Repeatability was dependent on donor type.
Overview of Direct and Indirect Effects of Antibiotics on Terrestrial Organisms
Authors: Narciso Alessandra , Barra Caracciolo Anna , De Carolis Chiara
Published: September 2023

Antibiotics (ABs) have made it possible to treat bacterial infections, which were in the past untreatable and consequently fatal. Regrettably, their use and abuse among humans and livestock led to antibiotic resistance, which has made them ineffective in many cases. The spread of antibiotic resistance genes (ARGs) and bacteria is not limited to nosocomial environments, but also involves water and soil ecosystems. The environmental presence of ABs and ARGs is a hot topic, and their direct and indirect effects, are still not well known or clarified. A particular concern is the presence of antibiotics in agroecosystems due to the application of agro-zootechnical waste (e.g., manure and biosolids), which can introduce antibiotic residues and ARGs to soils. This review provides an insight of recent findings of AB direct and indirect effects on terrestrial organisms, focusing on plant and invertebrates. Possible changing in viability and organism growth, AB bioaccumulation, and shifts in associated microbiome composition are reported. Oxidative stress responses of plants (such as reactive oxygen species production) to antibiotics are also described.
Mechanism of Action of Streptococcus downii, a New Bacterial Species with Probiotic Potential
Authors: Martínez-Lamas Lucía , García-Mato Eliane , Rincón-Quintero Anniris , Rivas-Mundiña Berta , Diz-Dios Pedro , Álvarez-Fernández Maximiliano
Published: September 2023

Streptococcus downii is a recently reported bacterial species of oral origin, with inhibitory capacity against Streptococcus mutans, Actinomyces naeslundii, Veillonella parvula and Aggregatibacter actinomycetemcomitans, which confers upon it the potential of being an oral probiotic. The aim of the present study was to identify the potential mechanisms by which S. downii exerts its inhibitory effect on S. mutans. To this end, the study assessed the consumption of glucose and proteins available in the culture medium, the modification of the pH, the production of short-chain fatty acids, the changes in the protein panel of the inhibition halo, the production of hydrogen peroxide and the effect of proteinase K. There were no differences in the glucose values or in the protein content of the medium, but there was a reduction in pH (with no effect on the growth of S. mutans). Significant increases were detected in the levels of lactic and formic acid (with no effect on the growth of S. mutans), as well as changes in the peptide panel (with no effect on the growth of S. mutans). The inhibitory effect was maintained in the presence of peroxidase but disappeared after adding proteinase K. Based on these results, it is suggested that the main mechanism of inhibition of S. downii against S. mutans is the production of bacteriocins.
Insight on Incorporation of Essential Oils as Antimicrobial Substances in Biopolymer-Based Active Packaging
Authors: Tomić Ana , Šovljanski Olja , Erceg Tamara
Published: September 2023

The increasing interest in microbiological food safety requires the development of sensitive and reliable analyses and technologies for preserving food products’ freshness and quality. Different types of packaging systems are one of the solutions for controlling microbiological activity in foods. During the last decades, the development of biopolymer-based active packaging with essential oil incorporation systems has resulted in technologies with exceptional application potential, primarily in the food industry. There is no doubt that this principle can facilitate food status monitoring, reduce food waste, extend the shelf life, improve the overall quality of food, or indicate a larger problem during the storage, production, and distribution of foodstuffs. On the other hand, most antimicrobial packaging systems are in the development phase, while the sensitivity, selectivity, complexity, and, above all, safety of these materials are just some of the essential questions that need to be answered before they can be widely used. The incorporation of essential oils as antimicrobial substances in biopolymer-based active packaging holds significant promise for enhancing food safety, extending shelf life, and offering more sustainable packaging solutions. While challenges exist, ongoing research and innovation in this field are likely to lead to the development of effective and environmentally friendly packaging systems with enhanced antimicrobial properties.
Unraveling the Role of Metals and Organic Acids in Bacterial Antimicrobial Resistance in the Food Chain
Authors: Rebelo Andreia , Almeida Agostinho , Peixe Luísa , Antunes Patrícia , Novais Carla
Published: September 2023

Antimicrobial resistance (AMR) has a significant impact on human, animal, and environmental health, being spread in diverse settings. Antibiotic misuse and overuse in the food chain are widely recognized as primary drivers of antibiotic-resistant bacteria. However, other antimicrobials, such as metals and organic acids, commonly present in agri-food environments (e.g., in feed, biocides, or as long-term pollutants), may also contribute to this global public health problem, although this remains a debatable topic owing to limited data. This review aims to provide insights into the current role of metals (i.e., copper, arsenic, and mercury) and organic acids in the emergence and spread of AMR in the food chain. Based on a thorough literature review, this study adopts a unique integrative approach, analyzing in detail the known antimicrobial mechanisms of metals and organic acids, as well as the molecular adaptive tolerance strategies developed by diverse bacteria to overcome their action. Additionally, the interplay between the tolerance to metals or organic acids and AMR is explored, with particular focus on co-selection events. Through a comprehensive analysis, this review highlights potential silent drivers of AMR within the food chain and the need for further research at molecular and epidemiological levels across different food contexts worldwide.
Antibiotics in Chronic Liver Disease and Their Effects on Gut Microbiota
Authors: Mendez-Sanchez Nahum , Coronel-Castillo Carlos Esteban , Cordova-Gallardo Jacqueline , Qi Xingshun
Published: September 2023

Impairments in liver function lead to different complications. As chronic liver disease progresses (CLD), hypoalbuminemia and alterations in bile acid compositions lead to changes in gut microbiota and, therefore, in the host–microbiome interaction, leading to a proinflammatory state. Alterations in gut microbiota composition and permeability, known as gut dysbiosis, have important implications in CLD; alterations in the gut–liver axis are a consequence of liver disease, but also a cause of CLD. Furthermore, gut dysbiosis plays an important role in the progression of liver cirrhosis and decompensation, particularly with complications such as hepatic encephalopathy and spontaneous bacterial peritonitis. In relation to this, antibiotics play an important role in treating CLD. While certain antibiotics have specific indications, others have been subjected to continued study to determine whether or not they have a modulatory effect on gut microbiota. In contrast, the rational use of antibiotics is important, not only because of their disrupting effects on gut microbiota, but also in the context of multidrug-resistant organisms. The aim of this review is to illustrate the role of gut microbiota alterations in CLD, the use and impact of antibiotics in liver cirrhosis, and their harmful and beneficial effects.
Insights from a Cross-Sectional Study on Knowledge, Attitudes and Behaviors Concerning Antibiotic Use in a Large Metropolitan Area: Implications for Public Health and Policy Interventions
Authors: Pennino Francesca , Maccauro Maria Luisa , Sorrentino Michele , Gioia Mariagiovanna , Riello Simonetta , Messineo Giuseppe , Di Rosa Carmela , Montuori Paolo , Triassi Maria , Nardone Antonio
Published: September 2023

The overuse and inappropriate use of antibiotics pose a grave threat to public health, contributing significantly to the accelerated development of antimicrobial resistance (AMR) and increased rates of morbidity and mortality, making it a leading cause of death globally. To examine the relationship between demographic variables and knowledge, attitudes, and behaviors concerning antibiotic use, a survey-based cross-sectional study was conducted involving 1158 individuals. The questionnaire included two sections: in the first section, participants’ socio-demographic characteristics were analyzed; the second investigated knowledge, attitudes, and behaviors concerning antibiotics utilization using a total of 36 questions. Descriptive statistics were used, and then a multiple linear regression analysis (MLRA) using three models was carried out. In Model I, knowledge about antibiotics exhibited correlations with smoking habits and educational attainment. In Model II, attitudes were significantly associated with gender, smoking habits, age, education, relationship status, and knowledge. In Model III, behaviors related to antibiotics were correlated with educational attainment, having children, knowledge, and attitudes. Implementing tailored public health programs could be a cost-effective intervention to enhance behaviors associated with antibiotic use in the general population. This study offers valuable insights into the determinants of knowledge, attitudes, and behaviors regarding antibiotics in the general population.
A Cross-Modal Hash Retrieval Method with Fused Triples
Authors: Li Wenxiao , Mei Hongyan , Li Yutian , Yu Jiayao , Zhang Xing , Xue Xiaorong , Wang Jiahao
Published: September 2023

Due to the fast retrieval speed and low storage cost, cross-modal hashing has become the primary method for cross-modal retrieval. Since the emergence of deep cross-modal hashing methods, cross-modal retrieval significantly improved. However, the existing cross-modal hash retrieval methods still need to effectively utilize the dataset’s supervisory information and the lack of similarity expression ability. This means that the label information needs to be maximized, and the potential semantic relationship between two modalities cannot be fully explored, thus affecting the judgment of semantic similarity between two modalities. To address these problems, this paper proposes Tri-CMH, a cross-modal hash retrieval method with fused triples, which is an end-to-end modeling framework consisting of two parts: feature extraction and hash learning. Firstly, the multi-modal data are preprocessing into the form of triple groups. The data supervision matrix is constructed so that the samples with labels and their meanings are aggregated together. In contrast, the samples with labels and their opposite meanings are separated, thus avoiding the problem of the under-utilization of supervisory information in the data set and achieving the effect of efficiently utilizing the global supervisory information. Meanwhile, the loss function of the hash learning part is optimized by considering the Hamming distance loss, single-modality internal loss, cross-modality loss, and quantization loss to explicitly constrain semantically similar hash codes and semantically dissimilar hash codes and to improve the model’s ability to judge cross-modality semantic similarity. The method is trained and tested on the IAPR-TC12, MIRFLICKR-25K, and NUS-WIDE datasets, and the experimental evaluation criteria are mAP and PR curve, and the experimental results show the effectiveness and practicality of the method.
QZRAM: A Transparent Kernel Memory Compression System Design for Memory-Intensive Applications with QAT Accelerator Integration
Authors: Gao Chi , Xu Xiaofei , Yang Zhizou , Lin Liwei , Li Jian
Published: September 2023

In recent decades, memory-intensive applications have experienced a boom, e.g., machine learning, natural language processing (NLP), and big data analytics. Such applications often experience out-of-memory (OOM) errors, which cause unexpected processes to exit without warning, resulting in negative effects on a system’s performance and stability. To mitigate OOM errors, many operating systems implement memory compression (e.g., Linux’s ZRAM) to provide flexible and larger memory space. However, these schemes incur two problems: (1) high-compression algorithms consume significant CPU resources, which inevitably degrades application performance; and (2) compromised compression algorithms with low latency and low compression ratios result in insignificant increases in memory space. In this paper, we propose QZRAM, which achieves a high-compression-ratio algorithm without high computing consumption through the integration of QAT (an ASIC accelerator) into ZRAM. To enhance hardware and software collaboration, a page-based parallel write module is introduced to serve as a more efficient request processing flow. More importantly, a QAT offloading module is introduced to asynchronously offload compression to the QAT accelerator, reducing CPU computing resource consumption and addressing two challenges: long CPU idle time and low usage of the QAT unit. The comprehensive evaluation validates that QZRAM can reduce CPU resources by up to 49.2% for the FIO micro-benchmark, increase memory space (1.66×) compared to ZRAM, and alleviate the memory overflow phenomenon of the Redis benchmark.
Lateral Vibration Control Strategy of High-Speed Elevator Car Based on Sparrow Search Optimization Algorithm
Authors: Su Wanbin , Jiang Yefeng , Yi Cancan , Li Shuhang
Published: September 2023

Aiming at the problems of inefficient mitigation of the lateral vibration of high-speed elevator cars, which results in low riding comfort, this paper introduces the electromagnetic active rolling guide shoes and incorporates the sky-hook damping control strategy into the high-speed elevator structure. On this basis, it adopts an optimization algorithm based on Sparrow Search Algorithm (SSA) to adjust the parameters of the lateral vibration controller, thereby reducing the amplitude of the lateral vibration and controlling it within the human comfort range. Specifically, this paper first incorporates electromagnetic active rolling guide shoes into the vibration reduction device of the high-speed elevator car. Based on the motion characteristics of lateral vibration, a mathematical model is established in which the sky-hook damping control strategy is introduced. Then, a simulation model is built, and the damping parameters of the controller are optimized using the SSA, resulting in effective control of the lateral vibration amplitude of the high-speed elevator car. Simulations demonstrate that the lateral vibration control model of the high-speed elevator car, optimized by SSA, achieves lower amplitudes within the frequency range of 1–2 Hz compared to the results obtained by the Genetic Algorithm (GA), demonstrating the effectiveness of SSA in optimizing the damping parameters of the car controller. Finally, the simulation results are compared with the measured data, and the research findings indicate that the proposed method for lateral vibration control of the car can effectively suppress the lateral vibration amplitude.
Skeletal and Dentoalveolar Effects of Maxillary Protraction Using Tooth- and Miniscrew-Anchored Devices in Patients with Class III Malocclusion with Maxillary Deficiency: A Retrospective Follow-Up Study
Authors: Baik Jong-Chan , Choi Youn-Kyung , Jeon Hyeran Helen , Kim Sung-Hun , Kim Seong-Sik , Park Soo-Byung , Kim Yong-Il
Published: September 2023

Introduction: This retrospective study aimed to determine skeletal and dental changes after a growth spurt and shortly after treatment using a facemask in skeletal Class III malocclusion with maxillary deficiency. Methods: We retrospectively studied 50 patients (25 patients per group) with skeletal Class III malocclusion who underwent facemask treatment with tooth-anchored (T-A, mean age 7.92) and miniscrew-anchored (M-A, mean age 9.84) intraoral appliances. In both groups, the facemask applied a traction force of 350–400 g to each side, such that the traction was directed 30° forward and downward. Lateral cephalometric radiographs were obtained from all patients before (T1), immediately after (T2), and at an average of 37.11 months after maxillary protraction (T3). A total of 13 cephalometric measurements were analyzed to determine the skeletal and dental changes. A paired t-test was used to verify the effects before, after, and during follow-up periods in each group. Results: An anteroposterior relationship, the values of SNA and ANB, evident in both groups at T2, was significantly improved in the M-A group (p < 0.05). However, the values of ANB and MP–SN, which indicate the relapse of anteroposterior and vertical relation of maxilla and mandible, were significantly higher in the T-A group compared with the M-A group during follow-up period. The maxillary first molars were significantly more extruded and maxillary incisors were more protruded in the T-A group than the M-A group, and this persisted at T3 (p < 0.05). Conclusions: Miniscrew-anchored maxillary protraction increased the skeletal improvement of anteroposterior relationship and reduced the dental and skeletal relapses compared with tooth-anchored maxillary protraction in growing patients with a hyperdivergent patterns and skeletal Class III malocclusion.
Simulation Study on Fire Product Movement Law and Evacuation in a University High-Rise Teaching Building
Authors: Cui Yan , Wang Hao , You Bo , Cheng Chuan , Li Ming
Published: September 2023

High-rise teaching buildings are complex public buildings that combine the evacuation risks of school buildings and high-rise buildings. In this regard, studying fire product transport patterns and personnel evacuation characteristics of high-rise school buildings is crucial for safe and rapid evacuation. In this paper, we applied Pyrosim2018 software to build a model of a teaching building and performed numerical fire simulation to analyze temperature, CO gas, and visibility to determine the available evacuation time ASET; meanwhile, we performed evacuation simulation by Pathfinder 2019 to determine the required evacuation time and analyze the congestion problem during evacuation. By improving the evacuation route, secondary simulations were conducted and compared with the previous results. The results show that visibility is the main factor affecting evacuation in of the event of a fire in this school building. Based on the visibility analysis, it is recommended that personnel evacuate from floors four and above within 709.2 S when the fire location is at a specific position on the third floor. While the original safety exits of the school building can avoid a large number of casualties, they cannot guarantee the safe evacuation of all people, and planning a reasonable evacuation route can obviously relieve the evacuation pressure in the high-rise corridor.
Susceptibility Modeling of a Rubber Track for Lightweight Mobile Robots
Authors: Szpaczyńska Daniela , Łopatka Marian Janusz , Krogul Piotr
Published: September 2023

The elastic-damping properties of the rubber track structure can have a significant impact on the running gear performance of lightweight mobile robots. Taking these properties into account is particularly important for modeling obstacle negotiation and estimating the robot’s driving force. The article presents track susceptibility identification using both static and dynamic tests. The experimental results were used to validate the multi-body dynamics model of the rubber track for three modeling methods and for three track link number model variants. The methods and variants were compared by the accuracy of the susceptibility parameters obtained using them. The impact of the modeling methods on the track bending resistance simulations was also checked.
Performance Improvement of Melanoma Detection Using a Multi-Network System Based on Decision Fusion
Authors: El-khatib Hassan , Ștefan Ana-Maria , Popescu Dan
Published: September 2023

The incidence of melanoma cases continues to rise, underscoring the critical need for early detection and treatment. Recent studies highlight the significance of deep learning in melanoma detection, leading to improved accuracy. The field of computer-assisted detection is extensively explored along all lines, especially in the medical industry, as the benefit in this field is to save hu-man lives. In this domain, this direction must be maximally exploited and introduced into routine controls to improve patient prognosis, disease prevention, reduce treatment costs, improve population management, and improve patient empowerment. All these new aspects were taken into consideration to implement an EHR system with an automated melanoma detection system. The first step, as presented in this paper, is to build a system based on the fusion of decisions from multiple neural networks, such as DarkNet-53, DenseNet-201, GoogLeNet, Inception-V3, InceptionResNet-V2, ResNet-50, ResNet-101, and compare this classifier with four other applications: Google Teachable Machine, Microsoft Azure Machine Learning, Google Vertex AI, and SalesForce Einstein Vision based on the F1 score for further integration into an EHR platform. We trained all models on two databases, ISIC 2020 and DermIS, to also test their adaptability to a wide range of images. Comparisons with state-of-the-art research and existing applications confirm the promising performance of the proposed system.
Lane Line Type Recognition Based on Improved YOLOv5
Authors: Liu Boyu , Wang Hao , Wang Yongqiang , Zhou Congling , Cai Lei
Published: September 2023

The recognition of lane line type plays an important role in the perception of advanced driver assistance systems (ADAS). In actual vehicle driving on roads, there are a variety of lane line type and complex road conditions which present significant challenges to ADAS. To address this problem, this paper proposes an improved YOLOv5 method for recognising lane line type. This method can accurately and quickly identify the types of lane lines and can show good recognition results in harsh environments. The main strategy of this method includes the following steps: first, the FasterNet lightweight network is introduced into all the concentrated-comprehensive convolution (C3) modules in the network to accelerate the inference speed and reduce the number of parameters. Then, the efficient channel attention (ECA) mechanism is integrated into the backbone network to extract image feature information and improve the model’s detection accuracy. Finally, the sigmoid intersection over union (SIoU) loss function is used to replace the original generalised intersection over union (GIoU) loss function to further enhance the robustness of the model. Through experiments, the improved YOLOv5s algorithm achieves 95.1% of mAP@0.5 and 95.2 frame·s−1 of FPS, which can satisfy the demand of ADAS for accuracy and real-time performance. And the number of model parameters are only 6M, and the volume is only 11.7 MB, which will be easily embedded into ADAS and does not require huge computing power to support it. Meanwhile, the improved algorithms increase the accuracy and speed of YOLOv5m, YOLOv5l, and YOLOv5x models to different degrees. The appropriate model can be selected according to the actual situation. This plays a practical role in improving the safety of ADAS.
The Change in the Shape Characteristics of the Plastic Zone in the Surrounding Rock of an Auxiliary Retracement Channel and a Reasonable Channel Spacing Determination Method
Authors: Gao Xu , Liu Chenyi , Zhang Hongkai , Yang Kunlin , Hu Yingjie , Guo Xiaofei
Published: September 2023

In underground coal mines, the stability of the retracement channel in the surrounding rock is crucial for the safe and efficient retracement of the equipment and to guarantee the continuity of the retracement work. To reveal the deformation and damage mechanism of the surrounding rock of an auxiliary retracement channel (ARC) and the determination method for the reasonable spacing of two retracement channels during the end of the mining period, the deviatoric stress field in front of the working face and the change in the shape characteristics of the plastic zone in the ARC are investigated in this paper. The formation of ultimate stress equilibrium, high deviatoric stress, decreasing deviatoric stress, and low deviatoric stress environments in front of the working face during the end of mining occur successively, and the different deviatoric stress environments are the main reasons for the different shape characteristics of the plastic zone in the surrounding rock. The changes in the shape characteristics of the plastic zone correspond to the changes in the shape characteristics in the zone with deviatoric stress and exhibit the following order: full plastic deformation zone, butterfly-shaped zone, elliptical zone, and circular plastic zone. A reasonable spacing determination method for the two retracement channels is proposed: the ARC is arranged in the decreasing deviatoric stress environment, where the surrounding rock plastic zone shape is elliptical, and the ARC is relatively stable. Based on this research result, the spacing of the double retracement channels at the Lijiahao 22-116 working face was determined to be 25 m, which achieved a positive application effect and allowed the safe and efficient retracement of the working face equipment.
State of Charge Estimation for Power Battery Using Improved Extended Kalman Filter Method Based on Neural Network
Authors: Liu Xiaoyu , Zhang Xiang
Published: September 2023

In order to enhance the accuracy of the traditional extended Kalman filter (EKF) algorithm in the estimation of the state of charge (SoC) of power batteries, we first derived the state space equation and measurement equation of lithium power batteries based on the Thevenin battery model and the modified Ampere-Hour integral algorithm. Then, the basic principles of EKF, backpropagation neural networks (BPNNs), and a biogeography-based optimization (BBO) algorithm were analyzed, and the arc curve mobility model was used to improve the global search ability of the BBO algorithm. By combining these three algorithms, this paper proposes a BP neural network method based on the BBO algorithm. This method uses the BBO algorithm to optimize the incipient weight and threshold of the BP neural network and uses this improved neural network to modify the estimated value of the extended Kalman filter algorithm (BBOBP-EKF). Finally, the BBOBP-EKF algorithm, the extended Kalman filter algorithm based on the BP neural network (BP-EKF), and the EKF algorithm are used to estimate the error value of the SOC of a power battery, and according to the experimental data, it was confirmed that the proposed BBOBP-EKF algorithm has been improved compared to other algorithms with respect to each error index term, in which the maximum error is 1% less than that of the BP-EKF algorithm and 2.4% less than that of the EKF algorithm, the minimum error is also the smallest, and the estimation accuracy is improved compared to the traditional algorithms.
Temporal Resolution of Acoustic Process Emissions for Monitoring Joint Gap Formation in Laser Beam Butt Welding
Authors: Kodera Sayako , Schmidt Leander , Römer Florian , Schricker Klaus , Gourishetti Saichand , Böttger David , Krüger Tanja , Kátai András , Straß Benjamin , Wolter Bernd , Bergmann Jean Pierre
Published: September 2023

With the increasing power and speed of laser welding, in-process monitoring has become even more crucial to ensure process stability and weld quality. Due to its low cost and installation flexibility, acoustic process monitoring is a promising method and has demonstrated its effectiveness. Although its feasibility has been the focus of existing studies, the temporal resolution of acoustic emissions (AE) has not yet been addressed despite its utmost importance for realizing real-time systems. Aiming to provide a benchmark for further development, this study investigates the relationship between duration and informativeness of AE signals during high-power (3.5 kW) and high-speed (12 m/min) laser beam butt welding. Specifically, the informativeness of AE signals is evaluated based on the accuracy of detecting and quantifying joint gaps for various time windows of signals, yielding numerical comparison. The obtained results show that signals can be shortened up to a certain point without sacrificing their informativeness, encouraging the optimization of the signal duration. Our results also suggest that large gaps (>0.3mm) induce unique signal characteristics in AE, which are clearly identifiable from 1 ms signal segments, equivalent to 0.2mm weld seam.
Enhancing the Strength of Mine Residue Soil by Bioremediation Combined with Biopolymers
Authors: Correia António A. S. , Caldeira Joana B. , Branco Rita , Morais Paula V.
Published: September 2023

Traditional soil stabilization methods are usually associated with high energy consumption, carbon emissions, and long-term environmental impact. Recent developments have shown the potential use of bio-based techniques as eco-friendly alternatives for soil stabilization. The present work studies the effects of the addition of the biopolymers xanthan gum (XG) or carboxymethyl cellulose (CMC) to a mine residue soil, combined or not with biostimulation and bioaugmentation techniques, in terms of compressive stress–strain behavior. Unconfined compressive strength (UCS) tests were performed on previously disturbed samples (two cycles of percolation, extraction and homogenization) to evaluate if the biostimulation and bioremediation remain active in a real adverse scenario. The results allowed for us to conclude that both biopolymers, when applied individually (with a content of 1%), are effective stabilizers (CMC allows for unconfined compressive strength increases of up to 109%), showing better results for CMC than Portland cement. The biostimulation of the autochthonous community of the mine residue soil was revealed to be a non-effective technique, even when combined with the biopolymers. However, good results were observed when the bioaugmentation was combined with xanthan gum, with unconfined compressive strength improvements of up to 27%. The study revealed that these bio-based techniques are promising soil engineering techniques, offering environmentally friendly alternatives for sustainable soil stabilization and contributing to a greener and more sustainable future.
A Three-Dimensional Mesoscale Computational Simulation Method for Soil–Rock Mixtures Considering Grain Crushing
Authors: Li Zhengsheng , Yi Haiyang , Xu Yiming , Li Gangqiang , Zhuo Zhuang
Published: September 2023

A new 3D mesoscale computational approach to simulate the mechanical behavior of soil–rock mixtures (SRMs) with the consideration of the grain-crushing process is proposed in this study. The proposed approach adopts a random SRM mesostructure generation algorithm to create a random SRM structure. Based on the generated mesostructure, the whole simulation area is divided into discrete cubic numbers, and the mesostructure is transformed into a material distribution matrix as an input for the computational approach. The computational approach is achieved by the coupling calculation of Matlab and COMSOL. Theimulations are presented alongside experimental data to validate the efficiency of the proposed approach. The simulation results indicate that the proposed computational approach can accurately capture the mechanical behavior of SRMs under loadings. This method helps to predict the physical properties of SRMs and has promising applications in engineering.