bluuebunny/crossref_metadata_2025 huggingface dataset:
The improvement of agronomic performances in the cold weather conditions for perennial wheatgrass by crossing Thinopyrum intermedium with wheat-Th. intermedium partial amphiploids
Authors: Liu Yizhuo , Song Weiwei , Song Anning , Wu Chunfei , Ding Jiarui , Yu Xiaoning , Song Jia , Liu Miaomiao , Yang Xinyuan , Jiang Changtong , Zhao Haibin , Song Weifu , Liu Dongjun , Yang Xuefeng , Song Qingjie , Li Xinling , Cui Lei , Li Hongjie , Zhang Yanming
Published: October 2023

Thinopyrum intermedium (2n=6x=42, StStJrJrJvsJvs) is resistant or tolerant to biotic and abiotic stresses, making it suitable for developing perennial crops and forage. Through five cycles of selection, we developed 24 perennial wheatgrass lines, designated 19HSC-Q and 20HSC-Z, by crossing wheat-Th. intermedium partial amphiploids with Th. intermedium. The cold resistance, morphological performance, chromosome composition, and yield components of these perennial lines were investigated from 2019 to 2022. Six lines of 19HSC-Q had higher 1,000-kernel weight, grains per spike, and tiller number than Th. intermedium, as well as surviving -30°C in winter. Lines 19HSC-Q14, 19HSC-Q18, and 19HSC-Q20 had the best performances for grain number per spike and 1,000-kernel weight. The 20HSC-Z lines, 20HSC-Z1, 20HSC-Z2, and 20HSC-Z3, were able to survive in the cold winter in Harbin and had been grown for two years. Sequential multicolor GISH analysis revealed that the Jvs subgenome of Th. intermedium were divided into two karyotypes, three pairs of type-I Jvs chromosomes and four pairs of type-II Jvs chromosomes. Both Th. intermedium and the 24 advanced perennial wheatgrass lines had similar chromosome compositions, but the translocations among subgenome chromosomes were detected in some lines with prominent agronomic traits, such as 19HSC-Q11, 19HSC-Q14, 19HSC-Q18, 19HSC-Q20, and the three 20HSC-Z lines. The chromosome aberrations were distinguished into two types: the large fragment translocation with St-Jr, Jvs-St, Jr-IIJvs, and Jvs-Jr and the small fragment introgression of Jr-St, St-IJvs, and Jvs-Jr. These chromosomal variations can be used to further analyze the relationship between the subgenomes and phenotypes of Th. intermedium. The results of this study provide valuable materials for the next selection cycle of cold-resistant perennial wheatgrass.
How do plants maintain pH and ion homeostasis under saline-alkali stress?
Authors: Li Jing , Yang Yongqing
Published: October 2023

Salt and alkaline stresses often occur together, severely threatening plant growth and crop yields. Salt stress induces osmotic stress, ionic stress, and secondary stresses, such as oxidative stress. Plants under saline-alkali stress must develop suitable mechanisms for adapting to the combined stress. Sustained plant growth requires maintenance of ion and pH homeostasis. In this review, we focus on the mechanisms of ion and pH homeostasis in plant cells under saline-alkali stress, including regulation of ion sensing, ion uptake, ion exclusion, ion sequestration, and ion redistribution among organs by long-distance transport. We also discuss outstanding questions in this field.
Navigation path extraction for inter-row robots in Panax notoginseng shade house based on Im-YOLOv5s
Authors: Tan Yu , Su Wei , Zhao Lijun , Lai Qinghui , Wang Chenglin , Jiang Jin , Wang Yongjie , Li Peihang
Published: October 2023

Introduction

The accurate extraction of navigation paths is crucial for the automated navigation of agricultural robots. Navigation line extraction in complex environments such as Panax notoginseng shade house can be challenging due to factors including similar colors between the fork rows and soil, and the shadows cast by shade nets.

Methods

In this paper, we propose a new method for navigation line extraction based on deep learning and least squares (DL-LS) algorithms. We improve the YOLOv5s algorithm by introducing MobileNetv3 and ECANet. The trained model detects the seven-fork roots in the effective area between rows and uses the root point substitution method to determine the coordinates of the localization base points of the seven-fork root points. The seven-fork column lines on both sides of the plant monopoly are fitted using the least squares method.

Results

The experimental results indicate that Im-YOLOv5s achieves higher detection performance than other detection models. Through these improvements, Im-YOLOv5s achieves a mAP (mean Average Precision) of 94.9%. Compared to YOLOv5s, Im-YOLOv5s improves the average accuracy and frame rate by 1.9% and 27.7%, respectively, and the weight size is reduced by 47.9%. The results also reveal the ability of DL-LS to accurately extract seven-fork row lines, with a maximum deviation of the navigation baseline row direction of 1.64°, meeting the requirements of robot navigation line extraction.

Discussion

The results shows that compared to existing models, this model is more effective in detecting the seven-fork roots in images, and the computational complexity of the model is smaller. Our proposed method provides a basis for the intelligent mechanization of Panax notoginseng planting.
Global metabolic profile and multiple phytometabolites in the different varieties of Gastrodia elata Blume
Authors: Zeng Xu , Li Jiaxue , Chen Tongyao , Li Yuanyuan , Guo Shunxing
Published: October 2023

Gastrodia elata Blume (Tianma in Chinese), a myco-heterotrophic orchid, is widely distributed in China. Tubers derived from this orchid are traditionally used as both medicinal and edible materials. At present, five primary varieties of G. elata are recorded in the “Flora of China.” Among them, the three main varieties currently in artificial cultivation are G. elata f. elata (GR, red stem), G. elata f. glauca (GB, black stem), and G. elata f. viridis (GG, green stem). In our study, the metabolic profiles and chemical composition of these three varieties were determined via UPLC-MS/MS and HPLC-UV. In total, 11,132 metabolites were detected, from which multiple phytometabolites were identified as aromatic compounds, heteroatomic compounds, furans, carbohydrates, organic acids, and their derivatives. A number of differentially expressed metabolites (DEMs) were annotated as bioactive ingredients. Overall, parishins, vanilloloside, and gastrodin A/B in the GB group were markedly higher, whereas gastrodin, gastrol, and syringic acid were more enriched in the GG or GR groups. Moreover, HPLC fingerprint analysis also found six metabolites used as markers for the identification of Gastrodiae Rhizoma in the Chinese Pharmacopoeia, which were also typical DEMs in metabolomics. Of these, gastrodin, 4-hydroxybenzyl alcohol, citric acid, and adenosine were quantitatively detected, showing a similar result with the metabolomic data. In summary, our findings provide novel insights into the phytochemical ingredients of different G. elata varieties, highlighting diverse biological activities and healthcare value.
Responses of Persian walnut on foliar applications of different biostimulants
Authors: Simon Gergely , Bujdosó Géza , Cvetkovic Miljan , Tevfik Alp Ozan , Kithi Laurine , Oláh Richárd , Ficzek Gitta , Végvári György
Published: October 2023

Biostimulants have different effects on plants. The aim of this paper is to determine responses of the ‘Alsószentiváni 117’ walnut cultivar on foliar applications of different biostimulants (Wuxal Ascofol, Kondisol, Alga K Plus). The nut traits (nut length, nut diameter, nut weight, kernel weight) and some phenolic compounds of the kernel were measured and detected. In 2020, during warmer early spring weather conditions under pistillate flowering receptivity, chlorogenic acid and quercetin content of kernels treated with Kondisol were higher than in control. All biostimulants influenced positive effects on catechin and rutin content, as well as treatments made with Wuxal Ascofol and Kondisol increased the juglon content of the kernel. In 2021, when the spring weather was typical for that period, only the Kondisol treatments had increasing effects on the catechin and chlorogenic acid content, than the control. The rutin and quercetin concentrations reached the highest value in this trial by Alga K Plus applications. The juglon content decreased in this year compared to the control. The pirocathecin, cinnamic acid, and gallic acid (except Wuxal Ascofol treatment in 2021) content decreased in all treatments in both observed years. Responses of woody fruit species on biostimulants applications depend on the weather conditions. Biostimulants had positive effects on the nut size characteristics in both observed years.
Adding scent: exploring improvements in pan trapping to monitor pollinators
Authors: Dunlap Madison M. , Casey Christina R. , VanOverbeke Dustin R.
Published: October 2023

Our project assessed whether adding floral scents to pan traps would increase the abundance and/or diversity of Hymenoptera sampled or decrease bycatch. We sampled insects using white pan traps containing 0.5 mL of floral scent (linalool, phenylacetaldehyde, limonene, geraniol, benzaldehyde, no scent control) per liter of trapping solution in an interior southern California natural space. Scented traps shared between 53.0% and 79.7% similarity in Hymenoptera assemblage and 59.5% and 72.2% similarity when using presence/absence data as compared with the control. Phenylacetaldehyde and geraniol increased the capture rate of new Hymenoptera, while phenylacetaldehyde also increased overall Hymenoptera and bycatch capture rate. Additionally, we noted that phenylacetaldehyde traps increased small parasitoid wasp capture 10-fold, potentially indicating an alternative use for the addition of phenylacetaldehyde to pan traps. We found no evidence that the addition of scent decreased the abundance or diversity of Hymenoptera caught. Those seeking to exhaustively record the species richness in an area may benefit the most from this method with potential to increase capture of large-bodied, rare, or specialist pollinating Hymenoptera with scent preference, though further research is needed. Based on the data presented here, scent should be explored further for its effect on pan trap catch.
Gender diversity and syphilis: something's going on?
Authors: de Dios-Aguado Mercedes , Cunha-Oliveira Aliete , Cotto-Andino Maylene , Gama de Sousa Aperibense Pacita Geovana , de Almeida Peres Maria Angélica , Gómez-Cantarino Sagrario
Published: October 2023

Introduction

This study aims to analyze the influence of syphilis among people with sexual and gender diversity, different from the binary dimension.

Materials and methods

A systematic review was conducted as a method to address the objective of the study, based on the Dialectical Structural Model of Care (DSM), to obtain the phenomenon from the perspective of cultural history.

Results

In this review the analysis of 129 documents, of which 22 texts were used. The construction of sex and gender in Western civilization is based on the Judeo-Christian tradition, which permitted many people throughout history to be persecuted and mistreated for living a lifestyle different from that dictated by religious and traditional canons. Therefore, throughout history, gender-diverse people, sexual minorities, and prostitutes have suffered segregation, mockery, aggression, and health problems, including syphilis.

Conclusions

Despite having a treatment and cure, syphilis has stood the test of time and has remained a secret pathology that is obscure and difficult to detect disease, which is still very much present in people of all social classes. It is necessary to review history to understand the reasons why syphilis is still prevalent in different societies today.
Stray Currents in Livestock Farming: Electrical Diagnosis in Farms
Authors: Lagarde Quentin , Beillard Bruno , Marcuzzi Daan , Mazen Serge , Leylavergne Julien
Published: October 2023

For several years, farmers have been questioning the effects of electromagnetic fields and stray electrical currents on the health of their animals. Observing changes in behavior or a decline in livestock productivity, farmers suspect that electrical installations on or near the farm may be responsible. Indeed, these systems can generate fault currents or stray currents, some of which may pass through the animals, affecting their well-being and productivity. To identify the origin and address this issue, an electrical diagnosis can be performed. In this study, diagnostics were carried out in eleven bovine farms considered “healthy”. These measurements included earth resistance equipment insulation resistance, continuity, leakage currents, as well as contact and step voltages, with some farms presenting non-conformities. This study will better understand the potential links between electrical installations and animal well-being, correlate the results of this study with those obtained in diagnostics conducted on farms experiencing such concerns and implement appropriate preventative and corrective measures.
Metabolic Characterization of Four Members of the Genus Stachys L. (Lamiaceae)
Authors: Tomou Ekaterina-Michaela , Karioti Anastasia , Tsirogiannidis Giorgos , Krigas Nikos , Skaltsa Helen
Published: October 2023

Several members of Stachys L. (among the largest Lamiaceae genera) have been traditionally used as medicinal plants. With 54 Stachys taxa (species and subspecies) occurring in mainland and/or insular Greece, the present study aimed to investigate the metabolic profiling of four range-restricted local Stachys members: Stachys candida and S. chrysantha (protected and endangered local Greek endemics), S. leucoglossa subsp. leucoglossa (local Balkan endemic), and S. spinulosa (local Balkan subendemic). In this investigation, the infusions of their above-ground parts were characterized using NMR and HPLC-PDA-MS techniques. Thus, 1D- and 2D-NMR spectra were obtained to compare the chemical fingerprints of these plants. Furthermore, previously isolated compounds from Stachys spp. were used to identify specific constituents. NMR screening revealed the presence of: (i) phenylethanoid glycosides, mainly acteoside in S. candida and S. chrysantha (section Candida, Swainsoniana phyloclade), and (ii) flavone 7-O-allosylglucoside (isoscutellarein 7-O-[6‴-O-acetyl-β-D-allopyranosyl]-(1→2)-β-D-glucopyranoside) and iridoids (monomelittoside or/and melittoside) in S. leucoglossa subsp. leucoglossa (section Olisia, Swainsoniana/Olisia phyloclade, Swainsoniana phyloclade) and caffeoylquinic acid (chlorogenic acid) in S. spinulosa (section Campanistrum, Stachys phyloclade). In total, 26 compounds were detected by HPLC-PDA-MS belonging to flavonoids, phenylethanoid glycosides, and phenolic acids. Among them, chlorogenic acid was identified in all samples as one of their main metabolites. The present study complements previous studies with first reports of constituents detected in the studied taxa, reports for the first time on the metabolic characterization of S. spinulosa, and discusses the chemotaxonomic significance of such findings.
Agrivoltaic Farming Insights: A Case Study on the Cultivation and Quality of Kimchi Cabbage and Garlic
Authors: Ko Da-Yeong , Chae Seung-Hun , Moon Hyeon-Woo , Kim Hye , Seong Joon , Lee Moon-Sub , Ku Kang-Mo
Published: October 2023

Agrivoltaic systems, which combine the cultivation of crops with solar panel installations, offer a novel solution to the dual challenges of energy production and agricultural productivity. This research verifies the impact of agrivoltaic (APV) conditions on the growth and quality of garlic and kimchi cabbage over two consecutive years in Naju-si, Jeollanam Province, Republic of Korea. In the 2019–2020 cultivation season, both kimchi cabbage and garlic grown under APV conditions experienced weight reductions of 18% and 15%, respectively, when compared to those grown in conventional settings. Intriguingly, despite the altered light conditions of APV leading to microenvironmental changes (mainly 41% light reduction), the quality of these crops, particularly in terms of their sulfur compound concentrations, remained consistent. This suggests that there was no discernible difference in the sensory quality of APV-grown kimchi cabbage and garlic compared to their traditionally grown counterparts. These findings highlight the potential of APV systems in promoting sustainable agriculture by balancing both crop yield and quality. Based on these results, the study suggests three innovative cultivation techniques to enhance crop growth in APV environments.
Effect of Incorporation Techniques and Soil Properties on NH3 and N2O Emissions after Urea Application
Authors: Götze Hannah , Saul Melanie , Jiang Yanyan , Pacholski Andreas
Published: October 2023

Ammonia (NH3) emissions affect the environment, the climate, and human health and originate mainly from agricultural sources like urea fertilizers. Such losses from urea fertilizer can be avoided by different application techniques like incorporation. However, the knowledge of the effect of these techniques on NH3 emissions is very limited and ambiguous since incorporation can also promote nitrous oxide (N2O) emissions. Three different principles of fertilizer incorporation methods were compared in three different soils (sandy, loamy, and clayey) at two moisture levels of 70% and 30% water-holding capacity (WHC), shallow mixing at 2 cm, injection with the slit technique at 5 cm, and deep complete incorporation at 5 cm simulating plow incorporation. The laboratory study was conducted with open dynamic incubation chambers where NH3 emissions were monitored with washing bottles while N2O emissions were studied with gas chromatographic (GC) measurements. The highest cumulative NH3 emissions occurred at low soil moisture levels in sandy soil (34% of the N applied). A maximum reduction in emissions by 87% was achieved with slit injection and 82% with deep injection compared to standard surface application. The reduction effect was positively related to increasing clay content. N2O emissions were delayed and highest from sandy soil. Overall, all urea incorporation techniques showed great potential for mitigating NH3 emissions on the clayey soil; for sandy and drier soils, only deeper or closed slot injection were consistently effective. However, connected to the surface incorporation at the higher moisture level, a relevant increase in N2O emissions compared to surface application was observed. Therefore, an increase in N2O emissions by urea incorporation may rule out specific incorporation techniques for NH3 emissions reduction from field-applied urea. In agricultural practice, a lower reduction in NH3 by fertilizer incorporation can be assumed in sandy soils or under dry soil conditions, as well as a more challenging technical implementation.
Three-Dimensional Volume Rendering in Computed Tomography for Evaluation of the Temporomandibular Joint in Dogs
Authors: Novales Manuel , Lucena Rosario , Hernández Eduardo M. , Ginel Pedro J. , Fernández Jesús M. , Blanco Beatriz
Published: October 2023

Based on computed tomography (CT) images, volume rendering was used to obtain a three-dimensional representation of data (3DVR). The aims of this study included: describing the bone anatomy of the temporomandibular joint (TMJ) of dogs; comparing the TMJs of each dog by skull type and age; comparing 3DVR images with three-standard-plane CTs; assessing soft tissues adjacent to the TMJ and assessing pathological cases. Multidetector computed tomography scans of bilateral TMJs of 410 dogs were observed. From a ventral view, slight displacements in the positions of the skulls were seen, whereas from a caudal view, differences in amplitude of the articular space were observed. Dolichocephalic and mesaticephalic dogs showed more similar TMJ features than brachycephalic dogs. The shape of the TMJ bones were irregular in dogs under 1 year old. The 3DVR images related to the three-standard-plane CT improved the overall comprehension of the changes in the articular space amplitude and condylar process morphology. The fovea pterygoidea, mandibular fossa and retroarticular process were perfectly shown. A better spatial situation of adjacent soft tissues was obtained. The 3DVR represents an ancillary method to the standard-plane CT that could help in the understanding of the anatomy and diagnoses of different pathologies of the TMJ in dogs.
Association between Prepartum Alerts Generated Using a Commercial Monitoring System and Health and Production Outcomes in Multiparous Dairy Cows in Five UK Herds
Authors: Cook John
Published: October 2023

Identifying cows that are at greater risk for disease prior to calving would be a valuable addition to transition management. Prior to the commercial release of software features in an automated behavioral monitoring system, designed to identify cows in the dry period at greater risk of disease postpartum, a retrospective analysis was carried out in five dairy herds to evaluate whether the software could identify prepartum cows that subsequently received health treatments postpartum and whether prepartum alerts (transition alerts) are associated with a reduction in milk production in the subsequent lactation. Herd management and production records were analyzed for cows receiving treatment in the first 21 d of lactation (days in milk, DIM) for clinical mastitis, reproductive tract disease (metritis, retained fetal membranes), metabolic disease (hypocalcemia, ketosis and displaced abomasum) and for cows exiting the herd by 60 DIM. Data was gathered for 986 cows, 382 (38.7%) of which received a transition alert and 604 (61.3%) that did not. During the first 21 DIM 312 (31.6%) cows went on to receive a disease treatment, of these 51.9% (n = 162/312) were transition alert cows and 48.1% (n = 150/312) non-transition alert cows, while 8.6% (n = 33/382) alert cows exited the herd by 60 DIM compared to 4.8% (n = 29/604) of cows that did not receive an alert. A cow receiving a transition alert (OR = 1.76, 95% confidence interval (CI) = 1.27–2.44) and increasing parity (OR = 2.03, 95% CI = 1.44–2.86) were both associated with increased risk of receiving a disease treatment in the first 21 DIM. The occurrence of a transition alert was negatively associated with both week 4 milk yield (daily average yield in fourth week of lactation) and predicted 305 d yield. Transition alerts correctly predicted 62.5% (95% CI: 59.3–65.5) of treatments with a sensitivity of 42.4% (95% CI: 37.4–45.5) and a specificity of 75.2% (95% CI: 71.5–78.6). Associations were identified between postpartum health and production outcomes and prepartum behavioral measures from an automated activity monitoring system.
A Description of Echinochasmus pseudobeleocephalus n. sp. (Echinochasmidae) Based on Morphological and Molecular Data
Authors: Kalinina Kristina Andreevna , Besprozvannykh Vladimir Vladimirovich , Tatonova Yulia Viktorovna , Shchelkanov Mikhail Yurievich
Published: October 2023

Adult individuals of Echinochasmus pseudobeleocephalus n. sp. were obtained during an experimental study on trematodes’ life cycle. An analysis of the morphometric characteristics of the developmental stages and involvement of first intermediate hosts, snails of the genus Boreoelona, in their life cycle, revealed the identity of the obtained trematodes to the European species Echinochasmus beleocephalus previously discovered in the south of the Russian Far East. However, an analysis of molecular data, in particular sequences of the 28S rRNA gene, showed that the Far Eastern trematodes examined do not belong to European E. beleocephalus despite their morphological similarities. An analysis of phylogenetic relationships within the family Echinochasmidae supported the status of E. pseudobeleocephalus n. sp. as an independent species. Our new data confirmed that the individuals attributed to Echinochasmus can be subdivided into two groups on the basis of the number of head-collar spines and the tail length in cercariae on an intergeneric level.
Genome-Wide Association and Pathway Analysis of Carcass and Meat Quality Traits in Karachai Young Goats
Authors: Selionova Marina , Aibazov Magomet , Sermyagin Alexander , Belous Anna , Deniskova Tatiana , Mamontova Tatiana , Zharkova Ekaterina , Zinovieva Natalia
Published: October 2023

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. The work aimed to search for candidate genes related to body measurements and body weight of Karachai goats and develop an experimental PCR-RV test system for genotyping significant SNPs. Comparison of GWAS results for ages 4 and 8 months revealed 58 common SNPs for significant genotypes. 11 common SNPs were identified for body weight, 4 SNPs—for group of traits withers height, rump height, body length, 2 SNPs—for withers height and rump height, 1 SNP—for body length and chest depth. Structural annotation of genomic regions covering a window of ±0.20 Mb showed the presence of 288 genes; 52 of them had the described functions in accordance with gene ontology. The main molecular functions of proteins encoded by these genes are the regulation of transcription, cell proliferation, angiogenesis, body growth, fatty acid and lipid metabolism, nervous system development, and spermatogenesis. SNPs common to body weight and localized within a window of ±200 kb from the structural genes CRADD, HMGA2, MSRB3, FUT8, MAX, and RAB15 were selected to create a test system. The study of meat productivity after slaughter and chemical analysis of muscle tissue in Karachai goats at the age of 8 months of different genotypes according to the identified SNPs revealed that rs268269710 is the most promising for further research and use in breeding. The GG genotype is associated with a larger live weight of animals, a larger carcass yield, the content of the boneless part in it, and the ratio of protein and adipose tissue in meat preferred for dietary nutrition. These results will contribute to the genetic improvement of Karachai goats.
The Chemical Characteristics and In Vitro Degradability of Pineapple By-Products as Potential Feed for Ruminants
Authors: Kiatti Dieu donné , Vastolo Alessandro , Koura Bossima Ivan , Vitaglione Paola , Cutrignelli Monica Isabella , Calabrò Serena
Published: October 2023

Pineapple fruit, which is cultivated in tropical and subtropical areas, is processed by the food industry, generating a large amount of waste. Using pineapple by-products in animal nutrition could reduce feeding costs and contribute to the containment of pollution. The chemical composition and the in vitro fermentation of five pineapple by-products (crown, bud end, peel, core, and pomace) from two West African pineapple varieties (Smooth Cayenne—SC and Sugarloaf—SL) were evaluated. Significant differences were observed between the varieties and by-products. The dry matter (DM) content was low and superimposable between varieties, averaging 17.7%. On a DM basis, pomace showed the highest protein content (SC 8.10% and SL 8.81%, p < 0.001), whereas the crown showed the highest (p < 0.001) NDF content (47.62% and 39.01% for SC and SL, respectively). Due the high sugar content, the core and pomace showed high in vitro organic matter degradability (SC: 85.09% and SL: 83.98%), estimated metabolizable energy (SC: 7.91 KJ/kg and SL: 7.66 KJ/kg), and volatile fatty acid production (96.86 mmol/g and 90.62 mmol/g). Based on chemical composition and in vitro digestibility results, this study suggests that pineapple by-products have the potential to be used in ruminants’ diets, considering the crown, bud end, and peel as fiber sources and the core and pomace as substitutes or supplements to concentrate feedstuffs. Further research should be conducted on the storability of these by-products through in vivo trials evaluating animals’ performances and the quality of their products.
A Simulation Method for Layered Filling of Grain Piles Based on the Discrete Element Method
Authors: Yang Kaimin , Du Xinming , Mao Yudong , Li Xin , Liu Jiying , Wang Yuancheng
Published: October 2023

The Discrete Element Method (DEM) has been widely employed to investigate the behavior of particle systems at a macroscopic scale. However, effectively simulating the gradual filling of bulk cereal grains within silos using the DEM remains a formidable challenge due to time constraints. Thus, there is a critical need to develop a simplified model capable of substantially reducing the computational time required for simulating cereal grain accumulation. This study introduces a Layered Filling Method (LFM) designed to expedite the computational process for cereal grain piles within silos. By utilizing particle kinetic energy as a specific criterion, this model identifies particles as stable situations when their kinetic energy drops below a designated threshold. Throughout the filling process, lower particles that were judged to satisfy the condition of stability are isolated, forming sub-heaps that are exempt from persistent detection. The whole particle heap is subsequently segregated into multiple sub-piles and a main pile till the process’s culmination, and these divisions are merged back together. In order to validate the model’s feasibility and accuracy, a comparative analysis was performed on the characteristics of the porosity and airflow patterns of grain piles generated using the LFM and the progressive filling method (PFM), respectively. The research results indicate that there is a marginally higher porosity value in the grain pile simulated by the LFM in comparison to the PFM. However, the average relative error remains below 5.00%. Both the LFM and PFM exhibit a similar spiral upward trend in the simulated airflow paths. Notably, the LFM demonstrates a substantial reduction in the time required to construct grain piles.
RMAU-Net: Breast Tumor Segmentation Network Based on Residual Depthwise Separable Convolution and Multiscale Channel Attention Gates
Authors: Yuan Sheng , Qiu Zhao , Li Peipei , Hong Yuqi
Published: October 2023

Breast cancer is one of the most common female diseases, posing a great threat to women’s health, and breast ultrasound imaging is a common method for breast cancer diagnosis. In recent years, U-Net and its variants have dominated the medical image segmentation field with their excellent performance. However, the existing U-type segmentation networks have the following problems: (1) the design of the feature extractor is complicated, and the calculation difficulty is increased; (2) the skip connection operation simply combines the features of the encoder and the decoder, without considering both spatial and channel dimensions; (3) during the downsampling phase, the pooling operation results in the loss of feature information. To address the above deficiencies, this paper proposes a breast tumor segmentation network, RMAU-Net, that combines residual depthwise separable convolution and a multi-scale channel attention gate. Specifically, we designed the RDw block, which has a simple structure and a larger sensory field, to overcome the localization problem of convolutional operations. Meanwhile, the MCAG module is designed to correct the low-level features in both spatial and channel dimensions and assist the high-level features to recover the up-sampling and pinpoint non-regular breast tumor features. In addition, this paper used the Patch Merging operation instead of the pooling method to prevent the loss of breast ultrasound image information. Experiments were conducted on two breast ultrasound datasets, Dataset B and BUSI, and the results show that the method in this paper has superior segmentation performance and better generalization.
An AGCRN Algorithm for Pressure Prediction in an Ultra-Long Mining Face in a Medium–Thick Coal Seam in the Northern Shaanxi Area, China
Authors: Gao Xicai , Hu Yan , Liu Shuai , Yin Jianhui , Fan Kai , Yi Leilei
Published: October 2023

Due to the increase in the length of the mining face, the pressure characteristics and spatial distribution in fully-mechanized mining faces are different from those in typical mining faces, which leads to great challenges in roof management and the intelligent control of ultra-long mining faces. Taking the ultra-long mining face of a medium–thick coal seam in the northern Shaanxi mining area as an example and using field monitoring data for the working resistance of the hydraulic supports, a non-linear prediction method was used to extract the features of the dynamic data sequence of the working resistance of the hydraulic supports, and a deep learning method was used to establish a pressure prediction model for ultra-long mining faces based on the adaptive graph convolutional recurrent network (AGCRN) algorithm. In the proposed model, the supports in the fully mechanized mining face were regarded as the logic nodes of a topological structure, while the time-series resistance data for the supports were regarded as data nodes on a graph. The AGCRN model was used to determine the spatiotemporal relationship between the working resistance data of adjacent hydraulic supports, thereby improving the accuracy of the proposed model. The MAE and MAPE were employed as performance evaluation indices. When the node-embedding dimension was set to 10 and the time window was set to 16, the corresponding MAE and MAPE values of the prediction model were the minimum values. Compared with the reference models (i.e., the BP, GRU, and DCRNN models), the MAE and MAPE of the AGCRN model were 38.75% and 23.49% lower, respectively, indicating that the AGCRN model effectively demonstrates high accuracy in predicting the working resistance of supports. The AGCRN model was applied in the prediction of the working resistance of the supports of the ultra-long fully mechanized mining face. The results revealed that the working resistance of the supports in the lower and upper areas was relatively small along the strike, whereas the working resistance of the supports in the middle area was large, exhibiting a zoning pattern of “low-high-low” in terms of the average working resistance. In conclusion, the proposed model provides data references for the state of the hydraulic supports, pressure identification, and intelligent control of the ultra-long mining faces of the medium–thick coal seams in northern Shaanxi.
Transpiler-Based Architecture Design Model for Back-End Layers in Software Development
Authors: Bastidas Fuertes Andrés , Pérez María , Meza Jaime
Published: October 2023

The utilization of software architectures and designs is widespread in software development, offering conceptual frameworks to address recurring challenges. A transpiler is a tool that automatically converts source code from one high-level programming language to another, ensuring algorithmic equivalence. This study introduces an innovative software architecture design model that integrates transpilers into the back-end layer, enabling the automatic transformation of business logic and back-end components from a single source code (the coding artifact) into diverse equivalent versions using distinct programming languages (the automatically produced code). This work encompasses both abstract and detailed design aspects, covering the proposal, automated processes, layered design, development environment, nest implementations, and cross-cutting components. In addition, it defines the main target audiences, discusses pros and cons, examines their relationships with prevalent design paradigms, addresses considerations about compatibility and debugging, and emphasizes the pivotal role of the transpiler. An empirical experiment involving the practical application of this model was conducted by implementing a collaborative to-do list application. This paper comprehensively outlines the relevant methodological approach, strategic planning, precise execution, observed outcomes, and insightful reflections while underscoring the the model’s pragmatic viability and highlighting its relevance across various software development contexts. Our contribution aims to enrich the field of software architecture design by introducing a new way of designing multi-programming-language software.
Idiopathic External Cervical Resorption of the Impacted Second Premolar: A Case Report
Authors: Zasčiurinskienė Eglė , Rastokaitė Liveta , Hosseinzadehfard Pedram , Lodienė Greta
Published: October 2023

The tooth impaction of the lower second premolars is an occasional condition but is still seen in clinical practice with a prevalence of 0.6–2.6%. The present case report describes a rare condition of the lower second premolar impaction. An 11-year-old female patient presented with the anteroposterior dental discrepancy, midline shift, and occlusal cant. Intraoral examination revealed the absence of the lower right second premolar with no space available for the eruption. X-ray examination revealed the impaction of tooth #45 in a vertical position, tilting of the adjacent teeth, and two-thirds root length development. The orthodontic treatment plan included space opening using a fixed appliance with a coil spring. The natural eruption of the tooth was expected according to dental age and root development. When the space was opened, no change in the position of tooth #45 was observed. Surgical exposure and active traction were performed. However, the intrusion and tilting of adjacent teeth were observed during the next appointments with no vertical change of tooth #45. Ankylosis was suspected as no tooth movement was recorded. The surgical luxation and osteotomy of the coronal alveolar bone of the impacted tooth were planned for the imminent forced eruption, which was expected due to the young age of the patient. Consequently, the crown of tooth #45 emerged and the bracket was placed. Further traction was planned to use a micro-screw. Following the traction, no vertical displacement of the tooth was observed in the subsequent appointments. Radiographic examination revealed radiolucency in the coronal third of the root. The patient was referred to the endodontist, and CBCT revealed external cervical root resorption in the late reparative stage. ECR in an impacted tooth, mimicking the manifestation of tooth ankylosis, can cause orthodontic treatment failure.
A Fabric Defect Segmentation Model Based on Improved Swin-Unet with Gabor Filter
Authors: Xu Haitao , Liu Chengming , Duan Shuya , Ren Liangpin , Cheng Guozhen , Hao Bing
Published: October 2023

Fabric inspection is critical in fabric manufacturing. Automatic detection of fabric defects in the textile industry has always been an important research field. Previously, manual visual inspection was commonly used; however, there were drawbacks such as high labor costs, slow detection speed, and high error rates. Recently, many defect detection methods based on deep learning have been proposed. However, problems need to be solved in the existing methods, such as detection accuracy and interference of complex background textures. In this paper, we propose an efficient segmentation algorithm that combines traditional operators with deep learning networks to alleviate the existing problems. Specifically, we introduce a Gabor filter into the model, which provides the unique advantage of extracting low-level texture features to solve the problem of texture interference and enable the algorithm to converge quickly in the early stages of training. Furthermore, we design a U-shaped architecture that is not completely symmetrical, making model training easier. Meanwhile, multi-stage result fusion is proposed for precise location of defects. The design of this framework significantly improves the detection accuracy and effectively breaks through the limitations of transformer-based models. Experimental results show that on a dataset with one class, a small amount of data, and complex sample background texture, our method achieved 90.03% and 33.70% in ACC and IoU, respectively, which is almost 10% higher than other previous state of the art models. Experimental results based on three different fabric datasets consistently show that the proposed model has excellent performance and great application potential in the industrial field.
Landslide Susceptibility Evaluation of Bayesian Optimized CNN Gengma Seismic Zone Considering InSAR Deformation
Authors: Deng Yunlong , Zuo Xiaoqing , Li Yongfa , Zhou Xincheng
Published: October 2023

Landslides are one of the most common geological disasters in China, characterized by suddenness and uncertainty. Traditional methods are not sufficient for the accurate identification, early warning, and forecasting of landslide disasters. As high-resolution remote sensing satellites and interferometric synthetic aperture radar (InSAR) surface deformation monitoring technology have been leaping forward, the traditional methods of landslide monitoring data sources are limited, and there have been few effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors, etc. In this study, an area extending 10 km from the VII isobar of the Gengma earthquake was taken as the study area, and 13 evaluation factors were screened out by integrating the factors of InSAR surface deformation, topography, and geological environment. Landslide susceptibility was evaluated through the Bayesian optimized convolutional neural network (BO-CNN), and the Bayesian optimized random forests (BO-RF) and particle swarm optimization support vector machines (PSO-SVM) models were selected for comparative analyses. The accuracy of the model was evaluated by using three indices, including the ROC curve, the AUC value, and the FR value. Specifically, the ROC curves of PSO-SVM, BO-RF, and BO-CNN were close to the upper-left corner, indicating excellent model performance. Moreover, the AUC values were computed as 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslides in the high susceptibility area of BO-CNN reached up to 14.9 and exceeded those of PSO-SVM and BO-RF, respectively. Furthermore, the mentioned values of the SVM and BO-RF models were 4.55 and 3.69 higher. The experimental results indicated that, compared with other models, the BO-CNN model used in this study had a better effect on landslide susceptibility evaluation, and the research results are of great significance to the disaster prevention and mitigation measures of local governments.
Ultrasound-Assisted Extraction as a Technique for Preparing Improved Infusions as Functional Beverage Bases
Authors: Mroczek Karolina , Saletnik Bogdan , Bajcar Marcin , Saletnik Aneta , Puchalski Czesław , Zaguła Grzegorz
Published: October 2023

Right after water, tea is one of the most popular beverages in the world. The composition of a tea drink is determined by, among other things: the degree of fermentation and the fineness of the tea leaves, as well as the brewing time and temperature. The purpose of this study was to verify the hypothesis that the extraction of selected elements from dried tea during infusion preparation was improved by using ultrasound under laboratory conditions. The effect of increasing the extraction time was also analyzed. The effectiveness of ultrasound was evaluated by measuring the content of selected elements in the extract of teas that were treated with ultrasound compared to a control group. The effectiveness of the application of ultrasound was evaluated by measuring the content of individual elements at intervals of 1 min, 5 min and 10 min comparing the application of ultrasound with the classical technique of tea brewing. In addition, the results were related to measurements of the amounts of overall concentrations of selected ions after the dried tea mineralization procedure. Samples of extracts and mineralizates were analyzed for elemental composition using an ICP-OES iCAP Dual 6500 Thermo® spectrometer. The use of ultrasound was shown to have a positive effect on the extraction process, and the efficiency of the process depended on the tea variety and the extraction time. The percentage of extraction relative to the results of the total amount of extracted ions was also calculated. Analyzing the effect of ultrasound on the leaching of minerals from tea leaves during infusion preparation is another step toward optimizing the tea brewing extraction process and a way to improve the nutritional value of tea infusions as a functional beverage base. The application of ultrasound in the extraction process of tea infusions may be a good solution to support traditional methods of extracting infusions for both research and technological purposes.
Energy Accumulation Law of Different Forms of Coal–Rock Combinations
Authors: Li Zibo , Zhang Guohua , Li Yubo , Zhou Wenjun , Qin Tao , Zeng Li , Liu Gang
Published: October 2023

Coal–rock disasters are becoming more and more severe as the intensity of coal mining increases. Due to its destructive power and resulting extensive area damage, rock burst is among the most critical threats to coal mine safety. It results from the combined action of the coal and the rock when affected by the mining process. To this end, we used a combination of coal and rock to conduct our studies. Combining a uniaxial compression experiment with theoretical analysis, this work investigated how different lithologies and coal–rock height ratios affect the mechanical properties of this combination and the law governing energy accumulation. We determined the following: When the coal–rock height ratios are dissimilar, the peak strength and modulus of elasticity of the combination show a negative correlation with the coal thickness share, and the pre-peak energy accumulation and impact energy index of the combination is positively correlated with the coal thickness percentage. In combination with the same coal–rock height ratio, the peak strength, elastic modulus, pre-peak energy accumulation, and impact energy index all increase with increased rock strength and elastic modulus. The presence of a hard rock layer affects the accumulation of pre-peak energy. Based on the experimental analysis, a theoretical model was established, and the surrounding rock stress negatively correlates with the percentage of coal thickness; the energy stored in the surrounding rock is directly proportional to the coal in the zone. Therefore, we inferred that the stress distribution of the surrounding rock as coal thickness changes is abnormal; substantial energy accumulation can swiftly initiate dynamic disasters, such as rock bursts. This study has important reference significance for preventing and controlling rock bursts in areas where coal thickness changes.
Modelling and Evaluation of the Effect of Pulsed Electric Fields and High Pressure Processing Conditions on the Quality Parameters of Osmotically Dehydrated Tomatoes
Authors: Katsimichas Alexandros , Dimopoulos George , Dermesonlouoglou Efimia , Taoukis Petros
Published: October 2023

This study explores the osmotic dehydration (OD) of fresh-cut cherry tomatoes through the application of Pulsed Electric Fields (PEF) and High-Pressure (HP) pre-treatments. Untreated, PEF-treated (1.8 kV/cm, 0–300 pulses), and HP-treated (0–600 MPa, 5 min) tomatoes were subjected to osmotic dehydration at 35 °C for up to 3 h. The results reveal that a 100-pulse PEF treatment and HP treatment at 600 MPa yielded optimal outcomes in terms of both OD enhancement (with effective moisture diffusion coefficients of 7.91 · 10−10 m2/s for PEF and 7.40 · 10−10 m2/s for HP-treated tomatoes compared to 5.17 · 10−10 m2/s for untreated samples) and product acceptability (achieving overall acceptance scores between 7 and 8). Applying PEF (100 pulses) and HP (600 MPa) pre-treatments reduced the water activity (aw) to 0.887 and 0.760, respectively, after 3 h of OD, compared to aw = 0.923 for untreated OD samples. The selection of these pre-treatment conditions enabled effective dehydration and quality retention, extending the shelf life by up to 40 days under chilled storage.