bluuebunny/crossref_metadata_2025 huggingface dataset:
A Lightweight Neural Network-Based Method for Detecting Estrus Behavior in Ewes
Authors: Yu Longhui , Pu Yuhai , Cen Honglei , Li Jingbin , Liu Shuangyin , Nie Jing , Ge Jianbing , Lv Linze , Li Yali , Xu Yalei , Guo Jianjun , Zhao Hangxing , Wang Kang
Published: August 2022

We propose a lightweight neural network-based method to detect the estrus behavior of ewes. Our suggested method is mainly proposed to solve the problem of not being able to detect ewe estrus behavior in a timely and accurate manner in large-scale meat sheep farms. The three main steps of our proposed methodology include constructing the dataset, improving the network structure, and detecting the ewe estrus behavior based on the lightweight network. First, the dataset was constructed by capturing images from videos with estrus crawling behavior, and the data enhancement was performed to improve the generalization ability of the model at first. Second, the original Darknet-53 was replaced with the EfficientNet-B0 for feature extraction in YOLO V3 neural network to make the model lightweight and the deployment easier, thus shortening the detection time. In order to further obtain a higher accuracy of detecting the ewe estrus behavior, we joined the feature layers to the SENet attention module. Finally, the comparative results demonstrated that the proposed method had higher detection accuracy and FPS, as well as a smaller model size than the YOLO V3. The precision of the proposed scheme was 99.44%, recall was 95.54%, F1 value was 97%, AP was 99.78%, FPS was 48.39 f/s, and Model Size was 40.6 MB. This study thus provides an accurate, efficient, and lightweight detection method for the ewe estrus behavior in large-scale mutton sheep breeding.
Design and Test of the Clearing and Covering of a Minimum-Tillage Planter for Corn Stubble
Authors: Hou Shouyin , Wang Shengzhe , Ji Zhangchi , Zhu Xiaoxin
Published: August 2022

Conservation tillage technology can reduce wind erosion and soil erosion, improve soil fertility, avoid straw burning and relieve ecological pressure. It is an important measure to achieve sustainable agricultural development. In northeast China, there is a large amount of straw covering the ground after the corn machine harvest, which can easily lead to the blockage of the soil-touching parts during no-tillage seeding, affecting sowing quality and crop yield. In order to solve the above problems, the clearing and covering of a minimum-tillage planter for corn stubble was developed. The machine can complete multiple processes, such as seedbed preparation, seeding, fertilization, covering and suppression, straw covering, etc., in a single entity. This paper focuses on the design of the straw cleaning device and uses discrete element method software (EDEM 2018, Altair Engineering, Troy, MI, USA) to establish the straw cleaning device–straw–soil discrete element simulation model. The quadratic-regression orthogonal center-of-rotation combination test method is used to optimize the parameter combination of the machine, using the operating speed, the speed of the knife roller and the penetration depth of the knife as the test factors and using the rate of cleaning straw and the equivalent power consumption as the evaluation index. The results show that each factor has a significant influence on the performance evaluation indices, and the order of influence of each factor on the rate of cleaning straw is operation speed > penetration depth of knife > speed of knife roller, and the order of influence of each factor on the equivalent power consumption is penetration depth of knife > speed of knife roller > operation speed. The optimal combination of parameters is a 5.5–6.2 km/h operation speed, a 500 rpm speed of the knife roller, a 40 mm penetration depth of the knife, a straw-cleaning rate of more than 90% and an equivalent power consumption of less than 8 kW. This study provides technical and equipment support for the promotion of conservation tillage technology in Northeast China.
Experimental Study on the Particle Size and Weight Distribution of the Threshed Mixture in Corn Combine Harvester
Authors: Zhang Ning , Fu Jun , Wang Ruixue , Chen Zhi , Fu Qiankun , Chen Xuegeng
Published: August 2022

The distribution of the threshed mixture is the link between the threshing and cleaning process during corn harvesting. Uneven distribution leads to a local accumulation of the mixture in the cleaning, resulting in high impurity and loss rate. Existing studies rarely concern the distribution of the corn threshed mixture. To address this problem, the distribution experiment was conducted in a self-made corn longitudinal axial threshing system to explore the distribution pattern, and both the particle size distribution and weight distribution of components (corn kernel, corn cob, and corn husk) were analyzed in this study. The results showed that the drum speed and concave clearance has a significant effect on particle size. Moreover, the impurities (corn cob, corn husk) increase with the drum speed. The weight distribution has an obvious uneven trend. In the axial weight distribution, corn kernels increased initially and decreased afterwards, while corn cobs and corn husks constantly increased. In the radial weight distribution, corn kernels and corn cobs were greater on both sides and less in the middle; corn husks had a clear left posterior accumulation. The increase in drum speed and feed rate and the decrease in concave clearance aggravated the inhomogeneity of the weight distribution. By analyzing the distribution characteristics, the drum speed of 400 r/min, concave clearance of 40 mm, and feed rate of 7 kg/s were confirmed to be optimal operating parameters. Under these conditions, the accumulation of the threshed mixture was weakened, which provided a satisfactory base for the subsequent cleaning. This study could provide a data support for the improvement of the threshing system. Additionally, this study is believed to have the potential to be used for the structural design of the cleaning system to reduce mixture accumulation and improve the cleaning performance.
Design and Optimization of a Soil-Covering Device for a Corn No-Till Planter
Authors: Geng Yuanle , Wang Xianliang , Zhong Xiaokang , Zhang Xiangcai , Chen Kun , Wei Zhongcai , Lu Qingxin , Cheng Xiupei , Wei Mingtao
Published: August 2022

Aiming to solve the problems of easy generation of clods, poor soil fluidity and poor soil-covering effect in the no-tillage seeding operation mode, this study has designed a soil-covering device with a soil-closing function for the chisel-type furrow opener of a corn no-tillage planter. Theoretical analysis and design of the soil dividing plate and the soil-covering disc were carried out, and the key parameters were determined. Then, the soil-covering device with soil-closing function and the soil movement model was constructed in Altair EDEM, and the spatial soil particle mobility was analyzed. The numerical simulation method was combined with the center plane composite response test scheme to carry out the simulation test, and the optimal working parameter combination was obtained. The operating speed was 6.35 km·h−1, the inclination angle of the soil-covering disc was 60°, the opening angle of the soil-covering disc was 70°, and the inclination angle of the soil dividing plate was 40°. A comparative test of the soil-covering effect and performance was carried out, and the results showed that the designed device was better than the traditional soil-covering device in terms of the consistency of soil-covering thickness and the stability of seed position deviation. The relative errors of the soil bin experiment results and the simulation optimization results for the cover soil thickness and seed position deviation were 5.7% and 11.1%, respectively. The operation effect of the designed soil-covering device with soil-closing function meets the requirements of soil covering under no-tillage conditions and provides a basis for the research and development of soil-covering suppression technology and devices under no-tillage seeding mode.
Effect of Regulated Deficit Irrigation on the Quality of ‘Arbequina’ Extra Virgin Olive Oil Produced on a Super-High-Intensive Orchard
Authors: García-Garví José Miguel , Sánchez-Bravo Paola , Hernández Francisca , Sendra Esther , Corell Mireia , Moriana Alfonso , Burgos-Hernández Armando , Carbonell-Barrachina Ángel A.
Published: August 2022

The expansion of the super-high-intensive cultivation of olive groves requires irrigation techniques that are compatible with the increasing scarcity of water due to climate change and olive oil demand. For this, the effect of two regulated deficit irrigation treatments (RDI) and a sustained deficit irrigation (SDI) treatment was studied. The treatments consisted of: (i) control treatment, which supplied 100% of the water lost by evapotranspiration (ET0); (ii) the “optimal RDI” treatment, which only reduced irrigation water (~37–54% reduction) during the pit hardening stage; (iii) the “confederation RDI” which limited water restriction to the donation of the Guadalquivir hydrographic confederation (~72% reduction); and, (iv) the “confederation SDI”, similar water restriction (~72%) but dying the whole tree cycle. In general, the reduction in the irrigation water caused no negative effects on the studied parameters. However, the total phenolic content (TPC) was increased when the deficit irrigation was applied. Fatty acid profile showed changes with respect to the control, increasing oleic acid and the total content of monounsaturated fatty acids (MUFA). For the volatile compound profile, reducing water intake caused changes in mayor volatile compound (trans-2-hexenal), related with green flavors. The application of deficit irrigation treatments increased the value obtained in the fruity parameter with respect to the control. On the other hand, irrigation deficit treatments did not generate changes in the olive oil yield.
Bridging Ecology and Agronomy to Foster Diverse Pastures and Healthy Soils
Authors: Reed Kinsey , Morrissey Ember M.
Published: August 2022

Renovating pastures to increase forage species diversity is a burgeoning practice among producers. Over a century of grassland and small-plot research suggests that increasing plant diversity can lead to improved pasture productivity, resilience, and soil health. However, it remains hard to decipher how these benefits translate to grazed production systems given the limited experimentation in realistic grazing systems. There is a disconnect between ecological and agronomic research regarding what qualifies as a “diverse” grassland or pasture. This review aims to examine the current state of research regarding plant diversity and its potential benefits for soil health in pasture systems, and outlines how we can improve our understanding and implementation of this practice in production systems.
Transcriptome-Based Weighted Correlation Network Analysis of Maize Leaf Angle Regulation by Exogenous Brassinosteroid
Authors: Ji Xiangzhuo , Gao Qiaohong , Zhuang Zelong , Wang Yinxia , Zhang Yunfang , Peng Yunling
Published: August 2022

Maize (Zea mays L.) leaf angle is an important characteristic affecting high-density planting, and it is also a central indicator for maize plant type selection to improve yield. Brassinosteroids (BRs) are a class of phytohormones that could modulate the growth and development of plant leaf angles. However, its functional mechanism remains unclear in maize. In this study, we used maize self-line B73 as material to analyze the transcriptome of leaf cushion after BR treatment at the seedling stage. Using seven concentrations of exogenous BR-treated maize B73 plants, the results show that the leaf angle and the cell length near the leaf pillow increased and then decreased with BR concentration increasing, and the 50 μM level was the best treatment. Analysis of 11,487 differences expressed genes (DEGs) found that genes related to cell volume were up-regulated, and the expression of genes related to the cell division was down-regulated. It is speculated that exogenous BR regulates the size of the maize leaf angle by regulating cell volume and cell division, and so we constructed a molecular mechanism model of maize response to exogenous BR. The molecular mechanism model of exogenous BR through weighted gene co-expression network analysis (WGCNA) DEGs, and two gene modules related to changes in maize leaf angle were identified. The results can provide a theoretical basis for determining the mechanism of exogenous BR-regulated maize.
Multi-Risk Assessment to Evaluate the Environmental Impact of Outdoor Pig Production Areas: A Case Study
Authors: Horta Carmo , Roque Natália , Batista Marta , Duarte António Canatário
Published: August 2022

Outdoor pig production (OPP) can be considered an intensive system in many areas of the Mediterranean region. The concentration of the rainfall in the winter season, the OPP’s topographic and soil properties, together with the continuous input of food and pigs’ excreta, contribute to a profound increase in the nutrients leaching and soil erosion. This work aimed to evaluate the accuracy of the DRASTIC-LU index and the Revised Universal Soil Loss Equation (RUSLE) to provide early information to improve the planning of this type of pig production through more adequate location and sustainable management practices. The two models were applied to an OPP with 2.24 ha, with a heavy animal charge (one adult per 1.120 m2). The results showed that 85% of the OPP area has a moderate risk to the vulnerability index to groundwater pollution and 15% high risk. The risk of soil erosion ranged from very severe to extremely severe in 96% of the area. The DRASTIC-LU indexes and the RUSLE model produce a multi-risk assessment that agreed with the observed field data. These two models showed accuracy to be used for early assessment when choosing the best location and improving management practices for OPP systems.
Prediction of Maize Seed Vigor Based on First-Order Difference Characteristics of Hyperspectral Data
Authors: Cui Huawei , Bing Yang , Zhang Xiaodi , Wang Zilin , Li Longwei , Miao Aimin
Published: August 2022

The identification of seed vigor is of great significance to improve the seed germination rate, increase crop yield, and ensure product quality. In this study, based on a hyperspectral data acquisition system and an improved feature extraction algorithm, an identification model of the germination characteristics for corn seeds was constructed. In this research, hyperspectral data acquisition and the standard corn seed germination test for Zhengdan 958 were carried out. By integrating the hyperspectral data in the spectral range of 386.7–1016.7 nm and the first derivative information of the spectral data, the root length prediction for corn seeds was successfully completed. The data regression model and prediction relationship between the spectral characteristics and seedling root length were established by principal component regression, partial least squares, and support vector regression. The first derivative information of the hyperspectral data was obtained by comparing the prediction model results with the original spectral data, which was preprocessed by Savitzky–Golay smoothing, multiplicative scatter correction, standard normal variate, and curve fitting. The results showed that the prediction model based on the first-order differential spectral data showed better performance than the one based on the spectral data obtained by other processing algorithms. By comparing the prediction results using different data characteristics and regression models, it was found that the hyperspectral method can effectively predict the root length of the seed, with the coefficient of determination reaching 0.8319.
Using Visible and Thermal Images by an Unmanned Aerial Vehicle to Monitor the Plant Water Status, Canopy Growth and Yield of Olive Trees (cvs. Frantoio and Leccino) under Different Irrigation Regimes
Authors: Caruso Giovanni , Palai Giacomo , Tozzini Letizia , Gucci Riccardo
Published: August 2022

An efficient management of water relies on the correct estimation of tree water requirements and the accurate monitoring of tree water status and canopy growth. This study aims to test the suitability of visible and thermal images acquired by an unmanned aerial vehicle (UAV) for monitoring tree water status and canopy growth in an irrigation experiment. We used mature olive trees of two cultivars subjected to full irrigation, deficit irrigation (41–44% of full irrigation), or rainfed conditions. Deficit irrigation had limited or no effect on fruit and oil yield. There was a significant relationship between the remotely sensed crop water stress index derived from thermal images and the stem water potential (R2 = 0.83). The RGB images by UAV allowed to estimate tree canopy volume and were able to detect differences in canopy growth across irrigation regimes. A significant relationship between canopy volume and LAI was found for both cultivars (R2 of 0.84 and 0.88 for Frantoio and Leccino, respectively). Our results confirm the positive effects of deficit irrigation strategies to save relevant volumes of water and show that aerial images from UAV can be used to monitor both tree water stress and its effects on canopy growth and yield.
Driving Factor Identification for the Spatial Distribution of Soil Salinity in the Irrigation Area of the Syr Darya River, Kazakhstan
Authors: Duan Yongjian , Ma Long , Abuduwaili Jilili , Liu Wen , Saparov Galymzhan , Smanov Zhassulan
Published: August 2022

Soil salinization has become a worldwide issue affecting agricultural development. Statistical methods and spatial analysis were used to analyze the degree and type of saline soils and their spatial distribution. The driving factors of soil salinity were explored using Geodetetcor models. In this study, 84 soil samples were collected from a 0–20 cm soil layer, and the total salt concentration and salt ion composition were measured. The results of statistical analysis and cluster analysis showed that SO42− and Ca2+ had the highest concentrations of salt ions in terms of anion and cation contents, respectively. The interpolation results indicated that the study area was dominated by mild saline soils, with sulfate-type saline soils and chloride-sulfate-type soils dominating. Results of the factor detector suggested that the distance to the irrigation system (0.425), and distance to the drainage system (0.42), explained salinity more strongly in the Shardara district, and elevation (0.326) was the most important influencing factor for salinity in the Mahtaaral district. Results of the interaction detector indicate that human factors (distance to irrigation canals ∩ distance to drainage canals) had a stronger explanation both in the Shardara and Mahtaaral districts. This research provides a scientific basis for soil salinity regulation and management, which is crucial for sustainable agricultural development.
Bibliometric Analysis of Literature in Snake Venom-Related Research Worldwide (1933–2022)
Authors: Sofyantoro Fajar , Yudha Donan Satria , Lischer Kenny , Nuringtyas Tri Rini , Putri Wahyu Aristyaning , Kusuma Wisnu Ananta , Purwestri Yekti Asih , Swasono Respati Tri
Published: August 2022

Snake envenomation is a severe economic and health concern affecting countries worldwide. Snake venom carries a wide variety of small peptides and proteins with various immunological and pharmacological properties. A few key research areas related to snake venom, including its applications in treating cancer and eradicating antibiotic-resistant bacteria, have been gaining significant attention in recent years. The goal of the current study was to analyze the global profile of literature in snake venom research. This study presents a bibliometric review of snake venom-related research documents indexed in the Scopus database between 1933 and 2022. The overall number of documents published on a global scale was 2999, with an average annual production of 34 documents. Brazil produced the highest number of documents (n = 729), followed by the United States (n = 548), Australia (n = 240), and Costa Rica (n = 235). Since 1963, the number of publications has been steadily increasing globally. At a worldwide level, antivenom, proteomics, and transcriptomics are growing hot issues for research in this field. The current research provides a unique overview of snake venom research at global level from 1933 through 2022, and it may be beneficial in guiding future research.
Transcriptomic and Behavioral Studies of Small Yellow Croaker (Larimichthys polyactis) in Response to Noise Exposure
Authors: Zhang Xuguang , Zhou Jun , Xu Wengang , Zhan Wei , Zou Huafeng , Lin Jun
Published: August 2022

Noise has the potential to induce physiological stress in marine fishes, which may lead to all sorts of ecological consequences. In the current study, we used the RNA-sequencing (RNA-seq) method to sequence the whole transcriptome of the brain in small yellow croaker (Larimichthys polyactis). The animals were exposed to a mix of noises produced by different types of boat played back in a tank, then the brain tissues were collected after the fish had been exposed to a 120 dB noise for 0.5 h. In total, 762 differently expressed genes (DEGs) between the two groups were identified, including 157 up regulated and 605 down regulated genes in the noise exposure group compared with the control group. Gene ontology (GO) enrichment analysis indicated that the most up regulated gene categories included synaptic membranes, receptor-mediated endocytosis and the neurotransmitter secretion process. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways found that endocytosis, cell adhesion molecules and the extracellular matrix (ECM) receptor interaction pathway were over-represented. Specifically, ECM-related genes, including lamin2, lamin3, lamin4, coll1a2, coll5a1 and col4a5 were down regulated in the noise exposure group, implying the impaired composition of the ECM. In addition, the behavioral experiment revealed that L. polyactis exhibited avoidance behaviors to run away from the noise source at the beginning of the noise exposure period. At the end of the noise exposure period, L. polyactis kept motionless on the surface of the water and lost the ability to keep their balance. Taken together, our results indicate that exposure to noise stress contributes to neurological dysfunction in the brain and impaired locomotor ability in L. polyactis.
Pedigree-Based Description of Three Traditional Hungarian Horse Breeds
Authors: Klein Renáta , Oláh János , Mihók Sándor , Posta János
Published: August 2022

The Mezőhegyes Stud was founded in 1784 where three different horse breeds were developed: the Furioso-North Star, the Gidran, and the Nonius. These breeds were based on the same mare population, but each breed had different utilization purposes. Our aim was to analyze the pedigree information of these three indigenous breeds. The genealogical information was traced back from the actual breeding population back to the founder animals, and the final database contained more than 47,000 horses. The reference populations were defined as the registered breeding animals in 2019. The complete generation equivalent was 16.45 for the Gidran breed, 15.18 for Furioso-North Star, and 12.64 for Nonius, respectively. Due to the utilization of English Thoroughbred during the breeding history, the average maximum generations were close to 36 generations for each breed. The average relatedness was approximately 4%. The average Wright’s inbreeding coefficient was the highest for the Nonius breed (5.59%). Kalinowski’s decomposition of inbreeding showed that inbreeding is originated mainly from the past; the current fixation of alleles was higher for the Nonius horse breed. There was a reasonable bottleneck effect for each breed. The estimated effective population sizes suggest that there is no problem with the maintaining of Mezőhegyes horse breeds.
Genetic Parameters for Methane Emissions Using Indirect Prediction of Methane and Its Association with Milk and Milk Composition Traits
Authors: Ghiasi Heydar , Sitkowska Beata , Piwczyński Dariusz , Kolenda Magdalena
Published: August 2022

The study covers milk yield and composition data for 17,468 Polish Holstein-Friesian cows. Methane production (g/lactation per cow, MP) for dairy cow were predicted using three methane production equations (MPE) that took into account: milk yield (MPE1), energy corrected milk (MPE2) and both milk protein concentration (%), and energy-corrected milk (MPE3). The average amounts of methane produced for each cow per lactation were 31,089 g, 46,487 g, and 51,768 g for MPE1, MPE2, and MPE3, respectively. Repeatability models were used to estimate genetic parameters for MP. The estimated heritabilities for MPE1, MPE2, and MPE3 were 0.30, 0.24, and 0.24, respectively, with a standard error of 0.01. High genetic correlations (>0.76) were obtained between methane and milk yield, protein, fat, lactose and dry matter contents in milk for MPE1, MPE2 and MPE3. Still, a moderate genetic correlation (0.34) was obtained between methane and fat content (MPE1); the standard error of the estimated genetic correlation was less than 0.05. The results of the current study indicate that genetic selection aimed to reduce MP in dairy cows is possible. However, such direct genetic selection could cause a negative genetic response in milk yield and composition due to negative genetic correlations between MP and milk yield and composition.
Frequency of β-Casein Gene Polymorphisms in Jersey Cows in Western Japan
Authors: Nuomin  , Nguyen Qui Dang , Aodaohu  , Nishino Naoki
Published: August 2022

This study aimed to investigate β-casein gene polymorphisms in Jersey cows in Japan. Blood samples were collected from 590 cows from eight Jersey farms in Okayama Prefecture, western Japan. Sequence analysis of exon 7 regions in chromosome 6 of the CSN2 gene revealed the genotype and allele frequencies of the β-casein variants. Considering that variant B belongs to the A1 group and variant I to the A2 group, plasma metabolite concentrations were compared among the A1A1, A1A2, and A2A2 group-based genotypes. The most frequent genotype was A2A2 (0.558), followed by A2B (0.190) and A2I (0.103). No variants of A3, F, G, H1, or H2 were found. The frequencies of group-based genotypes were A1A1 (0.032), A1A2 (0.303), and A2A2 (0.665). Although farm-to-farm differences were observed in the plasma concentrations of urea nitrogen, calcium, and phosphorus, no differences were found between the A1A1, A1A2, and A2A2 group-based genotypes; hence, the β-casein genotypes did not affect the metabolism of major nutrients. Owing to the high frequency of the A2 variant, Jersey cows can be considered an attractive breed for marker-assisted selection to create A2A2 herds.
New Pyrazolo-Benzimidazole Mannich Bases with Antimicrobial and Antibiofilm Activities
Authors: Zalaru Christina , Dumitrascu Florea , Draghici Constantin , Tarcomnicu Isabela , Marinescu Maria , Nitulescu George Mihai , Tatia Rodica , Moldovan Lucia , Popa Marcela , Chifiriuc Mariana Carmen
Published: August 2022

A new series of pyrazolo-benzimidazole hybrid Mannich bases were synthesized, characterized by 1H-NMR, 13C-NMR, IR, UV-Vis, MS, and elemental analysis. In vitro cytotoxicity of the new compounds studied on fibroblast cells showed that the newly synthesized pyrazolo-benzimidazole hybrid derivatives were noncytotoxic until the concentration of 1 μM and two compounds presented a high degree of biocompatibility. The antibacterial and antibiofilm activity of the newly synthesized compounds was assayed on Gram-positive Staphylococcus aureus ATCC25923, Enterococcus faecalis ATCC29212, and Gram-negative Pseudomonas aeruginosa ATCC27853, Escherichia coli ATCC25922 strains. All synthesized compounds 5a–g are more active against all three tested bacterial strains Staphylococcus aureus ATCC25923, Enterococcus faecalis ATCC29212, and Escherichia coli ATCC25922 than reference drugs (Metronidazole, Nitrofurantoin), with the exception of compounds 5d and 5g, which are less active compared to Nitrofurantoin, and all synthesized compounds 5a–g are more active against Pseudomonas aeruginosa ATCC27853 compared to reference drugs (Metronidazole, Nitrofurantoin). Compound 5f showed the best activity against Staphylococcus aureus ATCC 25923, with a MIC of 150 μg/mL and has also inhibited the biofilm formed by all the bacterial strains, having an MBIC of 310 µg/mL compared to the reference drugs (Metronidazole, Nitrofurantoin).
Cefonicid Benzathine Salt: A Convenient, Lean, and High-Performance Protocol to Make an Old Cephalosporin Shine
Authors: Comito Marziale , Monguzzi Riccardo , Tagliapietra Silvia , Palmisano Giovanni , Cravotto Giancarlo
Published: August 2022

Cefonicid is a second-generation cephalosporin sold under the brand name Sintocef™. It is an injectable drug obtained via a freeze-drying process and is also available for oral preparations. The high-quality standard required is very challenging to satisfy, and current production protocols are characterized by steps that are lengthy and cumbersome, making the product unattractive for the international market. Industrial R&D is constantly working on the process optimization for API synthesis, with the aim of increasing productivity and decreasing production costs and waste. We herein report a new and efficient method for the synthesis of the cefonicid benzathine salt that provides a good yield and high product stability. The double-nucleophilic and lipophilic nature of N′,N″-dibenzylethylene diacetate enables the deformylation of the OH-protected group on the mandelic moiety and also enables product crystallization to occur. We demonstrate that the formyl group in the peculiar position has high reactivity, promoting an amidation reaction that deprotects a hydroxy group and generates a new C-N bond in the reaction by-product. Several amines and OH-protected groups have been studied, but none were able to replicate the excellent results of benzathine diacetate.
Antioxidant and Anti-Inflammatory Activity of Five Medicinal Mushrooms of the Genus Pleurotus
Authors: Stastny Jan , Marsik Petr , Tauchen Jan , Bozik Matej , Mascellani Anna , Havlik Jaroslav , Landa Premysl , Jablonsky Ivan , Treml Jakub , Herczogova Petra , Bleha Roman , Synytsya Andriy , Kloucek Pavel
Published: August 2022

Within the group of higher fungi, edible medicinal mushrooms have a long history of being used as food and in folk medicine. These species contain biologically active substances with many potential beneficial effects on human health. The Pleurotus genus is representative of medicinal mushrooms because Pleurotus ostreatus is one of the most commonly cultivated culinary mushrooms. In our study, we focused on lesser-known species in the genus Pleurotus and measured their antioxidant and anti-inflammatory activity. We prepared extracts of the mushrooms and analyzed them using HPLC−HRMS, GC−MS, and 1H-NMR. Significant differences in biological activities were found among the Pleurotus spp. extracts. A MeOH extract of P. flabellatus was the most active as a radical scavenger with the highest ORAC, while a chloroform extract had significant anti-inflammatory COX-2 activity. The 80% MeOH extract of P. flabellatus contained the highest amounts of ergosterol, ergothioneine, and mannitol. The 80% MeOH extract of P. ostreatus Florida was the most active in the NF-κB inhibition assay and had the highest content of β-glucans (43.3% by dry weight). Given the antioxidant and anti-inflammatory properties of P. flabellatus, the potential therapeutic usefulness of this species is worth evaluating through in-depth investigations and confirmation by clinical trials.
ACA-Net: An Adaptive Convolution and Anchor Network for Metallic Surface Defect Detection
Authors: Chen Faquan , Deng Miaolei , Gao Hui , Yang Xiaoya , Zhang Dexian
Published: August 2022

Metallic surface defect detection is critical to ensure the quality of industrial products. Recently, human-advanced surface defect detection algorithms have been proposed. Most of these algorithms rely on convolutional neural networks (CNN) and an anchoring scheme. However, a convolution unit only samples the input feature maps at fixed shapes and locations. Similarly, a set of anchors are uniformly predefined with fixed scales and shapes, which increases the difficulties of bounding box regression. Therefore, we propose an adaptive convolution and anchor network for metallic surface defect detection, named ACA-Net. Specifically, an adaptive convolution and anchor (ACA) module is proposed, which mainly consists of adaptive convolution and an adaptive anchor. Firstly, an adaptive convolution module (ACM) is designed, which adaptively determines the location and shape of each convolution unit. In addition, a multi-scale feature adaptive fusion (MFAF) is proposed, which is used in ACM to extract and integrate multi-scale features. Then, an adaptive anchor module (AAM) is proposed to yield more suitable anchor boxes by adaptively adjusting shapes. Extensive experiments on NEU-DET dataset and GC10 dataset validate the performance of the proposed approach. ACA-Net achieves 1.8% on NEU-DET dataset higher Average Precision (AP) than GA-RetinaNet. Furthermore, the proposed ACA module is also adopted in GA-Faster R-CNN, improving the AP by 1.2% on NEU-DET dataset.
Research on Seeding Performance of Self-Propelled Industrial Hemp Seeder
Authors: Duan Yiping , Xiang Wei , Lv Jiangnan , Yan Bo , Hu Yao , Wu Mingliang
Published: August 2022

In order to solve the problems of high labor intensity and low production efficiency in the cultivation of hemp in hilly areas, the seed arrangement performance of self-propelled hemp seeders was studied. According to the cultivation mode of hemp for the fiber industry in Yunnan, Sichuan, and other hilly areas, the seed metering device for the hemp industry was designed, the seed metering mechanism of hemp was analyzed, and the theoretical value range of design parameters of its key components was determined. The row of kind of wheel speed is obtained by single factor experiment, hole diameter and hole depth and uniformity of the seed, the seed of change rule, on the basis of the quadratic regression orthogonal rotation combination test, two indexes of the regression model, using the regression model of the design parameter optimization, and seeder row of kind of verification test, the results show that: when the rotation speed of the metering wheel was 90.0 r/min, the diameter of the hole was 10.4 mm, and the depth of the hole was 6.4 mm, the coefficient of variation of seeding uniformity of seeding machine was less than 45%, and the coefficient of variation for consistency of seed quantity in each row was less than 8%. The operation of the self-walking industrial hemp seeder met the requirements of fiber industrial hemp planting in hilly areas.
The Irrecoverable Loss in Sleep on Weekdays of Two Distinct Chronotypes Can Be Equalized by Permitting a >2 h Difference in Waking Time
Authors: Putilov Arcady A. , Sveshnikov Dmitry S. , Bakaeva Zarina V. , Yakunina Elena B. , Starshinov Yuri P. , Torshin Vladimir I. , Trutneva Elena A. , Lapkin Michael M. , Lopatskaya Zhanna N. , Budkevich Roman O. , Budkevich Elena V. , Tinkova Elena L. , Dyakovich Marina P. , Cherapkina Larisa P. , Donskaya Olga G. , Puchkova Alexandra N. , Dorokhov Vladimir B.
Published: August 2022

Background: Our work/study culture is biased towards the circadian clocks of “morning types”, whereas “evening types” are forced to advance their weekday waking times relative to weekend waking times. Since the experimental research consistently reveals a >2 h difference between these two chronotypes in the positions of their endogenous circadian phases, we hypothesized the necessity to permit a >2 h difference between them in weekday waking times to equalize their irrecoverable loss in sleep on weekdays. Methods: A total of 659 and 1106 participants of online surveys identified themselves as morning and evening types, respectively. The hypothesis was tested by applying a model of sleep–wake regulation for simulating sleep times reported by 245 lecturers of these two types, and by comparison of sleep times of these types among these lecturers and 1520 students. Results: The hypothesis was supported by results showing that, if, on weekdays, an “average” morning type wakes at 6 a.m., the equalization of the weekday sleep loss of the two chronotypes would require the waking time of an “average” evening type to be no earlier than 8 a.m. Conclusions: These results may be implemented in a model-based methodology for the correction of weekday waking times to equalize weekday sleep loss.
Numerical Simulation and Field Measurement Validation of Road Embankment on Soft Ground Improved by Prefabricated Vertical Drains: A Comparative Study
Authors: Mamat Rufaizal Che , Ramli Azuin , Khahro Shabir Hussain , Yusoff Nur Izzi Md
Published: August 2022

This article provides a comparative knowledge of predicted and measured settlements of road embankments with prefabricated vertical drains (PVDs). The emphasis of this study was to investigate and back-analyse the ratio of horizontal permeability in an undisturbed area to a smeared zone, which affects the behaviour of vertical drains. Two models of PVDs in soft ground were developed by utilising a plane strain 2D numerical approach based on the equivalent permeability. Suggestions for the improvement of numerical accuracy of the soft ground beneath road embankments have been made in regards to the obtained results. The employment of the equivalent horizontal permeability in numerical analysis produced significantly similar results to those of the measured values. Furthermore, a smear effect permeability ratio of 300 produced a considerably accurate result with a model based on the equivalent horizontal permeability and measured data. Lastly, the smear effect ratio of 6 using the equivalent horizontal permeability approach was employed in order to predict the behaviour of vertical drains in the soft grounds under road embankments.
Design of a Biomechatronic Device for Upright Mobility in People with SCI Using an Exoskeleton Like a Stabilization System
Authors: Hernández-Rámos Miguel Angel , Flores-Cuautle José de Jesús Agustín , Filippeschi Alessandro , Rodríguez-Jarquin José Pastor , Landeta-Escamilla Ofelia , Jacinto-Villegas Juan Manuel , Sandoval-Gonzalez Oscar Osvaldo
Published: August 2022

This paper presents a novel biomechatronic device that resolves the necessities of mobility for people with spinal cord trauma (SCI) and disability. The proposed device features a safe and reliable mobility mechanism that withstands daily use without premature mechanical wear, facilitating the activities of daily living (ADL) for people affected by SCI, integrating them to a social and workforce environment that allows them, on one hand, to move in a standing upright position in complex situations of the urban architecture, and on the other hand, provides them a mechatronic system to assist them to stand up and sit down.
Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots
Authors: Alothali Eiman , Salih Motamen , Hayawi Kadhim , Alashwal Hany
Published: August 2022

Twitter, as a popular social network, has been targeted by different bot attacks. Detecting social bots is a challenging task, due to their evolving capacity to avoid detection. Extensive research efforts have proposed different techniques and approaches to solving this problem. Due to the scarcity of recently updated labeled data, the performance of detection systems degrades when exposed to a new dataset. Therefore, semi-supervised learning (SSL) techniques can improve performance, using both labeled and unlabeled examples. In this paper, we propose a framework based on the multi-view graph attention mechanism using a transfer learning (TL) approach, to predict social bots. We called the framework ‘Bot-MGAT’, which stands for bot multi-view graph attention network. The framework used both labeled and unlabeled data. We used profile features to reduce the overheads of the feature engineering. We executed our experiments on a recent benchmark dataset that included representative samples of social bots with graph structural information and profile features only. We applied cross-validation to avoid uncertainty in the model’s performance. Bot-MGAT was evaluated using graph SSL techniques: single graph attention networks (GAT), graph convolutional networks (GCN), and relational graph convolutional networks (RGCN). We compared Bot-MGAT to related work in the field of bot detection. The results of Bot-MGAT with TL outperformed, with an accuracy score of 97.8%, an F1 score of 0.9842, and an MCC score of 0.9481.
Environmental Efficiency Indices in the Public Hospital Sector: A Proposal
Authors: Jiménez-Lacarra Vanesa , Martínez-Cámara Eduardo , Santamaría-Peña Jacinto , Jiménez-Macías Emilio , Bruzzone Agostino , Blanco-Fernández Julio
Published: August 2022

In the past decades, the use of indices and indicators to report on the environmental performance of organisations has increased exponentially. However, the available studies did not address the topic of obtaining indicators that show the environmental behaviour of the health sector. The main objective of this research, therefore, was aimed at the calculation of environmental efficiency indices in the hospital sector, taking a regional hospital as a case study and considering the environmental aspects identified during the development of its healthcare activity in 2019. The results obtained provided information on the potential environmental impacts triggered by every aspect of the operation of a hospital in the course of its activities that focus on patient care. The results demonstrated that the aspects related to transportation of patients, workers, and materials had the greatest impact on the global environmental indices we calculated. For the environmental efficiency indices of hospital activities, the most significant environmental aspects were materials consumption and waste generation.
Depth and Angle Evaluation of Oblique Surface Cracks Using a Support Vector Machine Based on Seven Parameters
Authors: Li Haiyang , Liu Yihao , Deng Jin , An Zhiwu , Pan Qianghua
Published: August 2022

To intelligently and quickly verify the depths and angles of oblique surface cracks using the laser ultrasound technique, a crack geometry information evaluation method using a support vector machine (SVM) is proposed. The relationships between several parameters—which are based on transmitted waves and reflected waves containing crack geometry information in the time domain, frequency domain and time–frequency domain, and crack size—are presented in detail. To decide which feature parameters are involved in the SVM model, two selection standards are proposed according to the correlations between feature parameters and crack size and between the feature parameters themselves. Finally, a seven-feature-parameter SVM model which has an excellent ability to classify oblique crack depths and angles is built. The results of simulations using the finite element method (FEM) and experimental data show that seven parameters based on the SVM model are available for the oblique surface crack depth and angle evaluation and can be used to nondestructively detect natural cracks.
Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
Authors: David Leo Gertrude , Patra Raj Kumar , Falkowski-Gilski Przemysław , Divakarachari Parameshachari Bidare , Antony Marcilin Lourdusamy Jegan
Published: August 2022

In recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep learning models are extensively used in the existing studies. In this manuscript, a new model is proposed for the effective classification of both serviceable and worn cutting edges. Initially, a dataset is chosen for experimental analysis that includes 254 images of edge profile cutting heads; then, circular Hough transform, canny edge detector, and standard Hough transform are used to segment 577 cutting edge images, where 276 images are disposable and 301 are functional. Furthermore, feature extraction is carried out on the segmented images utilizing Local Binary Pattern (LBPs) and Speeded up Robust Features (SURF), Harris Corner Detection (HCD), Histogram of Oriented Gradients (HOG), and Grey-Level Co-occurrence Matrix (GLCM) feature descriptors for extracting the texture feature vectors. Next, the dimension of the extracted features is reduced by an Improved Dragonfly Optimization Algorithm (IDOA) that lowers the computational complexity and running time of the Deep Belief Network (DBN), while classifying the serviceable and worn cutting edges. The experimental evaluations showed that the IDOA-DBN model attained 98.83% accuracy on the patch configuration of full edge division, which is superior to the existing deep learning models.
Dynamic Single-Electron Transistor Modeling for High-Frequency Capacitance Characterization
Authors: Singh Alka , Nishimura Tomoki , Satoh Hiroaki , Inokawa Hiroshi
Published: August 2022

Based on the time-dependent master equation and taking the dynamic gate current into account, a new single-electron transistor (SET) model is proposed, which can represent intrinsic terminal capacitances and transcapacitances. By using this model, bias, frequency and temperature dependences of these capacitances are evaluated. Since the model is implemented in the SPICE circuit simulator, it can be used to analyze the high-frequency behavior of circuits, including SETs and is applied to the characterization of a SET-based inverting amplifier this time.
Omega Network Pseudorandom Key Generation Based on DNA Cryptography
Authors: Rahman Gohar , Wen Chuah Chai
Published: August 2022

Eliminating the risk of bugs and external decryption in cryptographic keys has always been a challenge for researchers. The current research is based on a new design that uses an Omega network-based pseudorandom DNA key generation method to produce cryptographic keys for symmetric key systems. The designed algorithm initially takes two random binary numbers as inputs to the Omega network design, generating an output of 256 symmetric keys. The Omega network uses the concept of the central dogma of molecular biology (DNA and RNA properties), including DNA replication (for DNA) and the transcription process (for RNA). The NIST test suite is applied to test the security properties of the proposed design. According to the study’s findings, the suggested design is significantly suited to achieve the NIST test security properties and passes all of the NIST recommended tests.
Lateral Load Capacity and p-Multiplier of Group Piles with Asymmetrical Pile Cap under Seismic Load
Authors: Munawir As’ad , Harimurti  , Sumarsono Queen Arista Rosmania Putri
Published: August 2022

Earthquakes are a high-risk natural phenomenon in Indonesia, which is between three tectonic plates: the Eurasian, Pacific, and Indo–Australian plates. This study examines the response of bored piles with asymmetrical pile cap in the Auditorium Building of Brawijaya University to seismic loads, which is still rare to conduct this research. This study assessed based on 3D finite element-numerical approach, where lateral resistance and p-multiplier values compared on the effects of combination lateral loads, pile stiffness, and soil stiffness. The behavior of lateral resistance and deflection group piles with asymmetrical pile cap and single pile with square pile cap gives a good agreement. The side slope of the pile cap can increase the shear zone, increase the lateral resistance, and the most considerable lateral resistance to the lowest occurs in the horizontal direction, opposite the loading direction. In addition, the pile configuration that is not symmetrical gives an increasing p-multiplier value followed by an increasing deflection and the p-multiplier from the 3D finite element method was within the recommended range.