bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative protein profiling of two soybean genotypes with different stress tolerance reveals major components in drought tolerance
Authors: Dong Shoukun , Zhou Qi , Yan Chao , Song Shuang , Wang Xin , Wu Zihao , Wang Xiyue , Ma Chunmei
Published: August 2023

Introduction

Drought stress has gradually become a limiting factor for plant growth. Soybean, a crop with a higher water demand than other plants, is particularly sensitive to water deficits.

Method

To explore the effect of drought stress on soybean protein expression, we used drought-tolerant soybean genotype HeiNong44 (HN44) and sensitive soybean genotype HeiNong65 (HN65) as experimental materials, PEG-6000 as an osmotic regulator, and tandem mass tag (TMT) technology to identify the differential expression of soybean proteins.

Results

We identified that 48 upregulated and 38 downregulated proteins in HN44 and 55 upregulated and 13 downregulated proteins in HN65.

Discussion

KEGG analysis showed that these differentially expressed proteins were involved in carbohydrate metabolism, signal transduction, amino acid metabolism, lipid metabolism, and programmed cell death. Drought stress usually caused an increase in the activity of plant antioxidant enzymes, the obstruction of photosynthetic synthesis, and a significant change in the content of plant hormones. We found that HN44 responds to drought stress mainly through sugar decomposition, increased antioxidant enzyme activity and lipid metabolism. HN65 responds to drought stress mainly through ABA synthesis, increased antioxidant enzyme activity and amino acid metabolism. Our study also found that differential proteins in the starch and sucrose metabolic pathway play a key role in supplying energy and regulating osmotic potential.
Feasibility study of computed tomography texture analysis for evaluation of canine primary adrenal gland tumors
Authors: Lee Kyungsoo , Goh Jinhyong , Jang Jaeyoung , Hwang Jeongyeon , Kwak Jungmin , Kim Jaehwan , Eom Kidong
Published: August 2023

Objective

This study aimed to investigate the feasibility of computed tomography (CT) texture analysis for distinguishing canine adrenal gland tumors and its usefulness in clinical decision-making.

Materials and methods

The medical records of 25 dogs with primary adrenal masses who underwent contrast CT and a histopathological examination were retrospectively reviewed, of which 12 had adenomas (AAs), 7 had adenocarcinomas (ACCs), and 6 had pheochromocytomas (PHEOs). Conventional CT evaluation of each adrenal gland tumor included the mean, maximum, and minimum attenuation values in Hounsfield units (HU), heterogeneity of the tumor parenchyma, and contrast enhancement (type, pattern, and degree), respectively, in each phase. In CT texture analysis, precontrast and delayed-phase images of 18 adrenal gland tumors, which could be applied for ComBat harmonization were used, and 93 radiomic features (18 first-order and 75 second-order statistics) were extracted. Then, ComBat harmonization was applied to compensate for the batch effect created by the different CT protocols. The area under the receiver operating characteristic curve (AUC) for each significant feature was used to evaluate the diagnostic performance of CT texture analysis.

Results

Among the conventional features, PHEO showed significantly higher mean and maximum precontrast HU values than ACC (p < 0.05). Eight second-order features on the precontrast images showed significant differences between the adrenal gland tumors (p < 0.05). However, none of them were significantly different between AA and PHEO, or between precontrast images and delayed-phase images. This result indicates that ACC exhibited more heterogeneous and complex textures and more variable intensities with lower gray-level values than AA and PHEO. The correlation, maximal correlation coefficient, and gray level non-uniformity normalized were significantly different between AA and ACC, and between ACC and PHEO. These features showed high AUCs in discriminating ACC and PHEO, which were comparable or higher than the precontrast mean and maximum HU (AUC = 0.865 and 0.860, respectively).

Conclusion

Canine primary adrenal gland tumor differentiation can be achieved with CT texture analysis on precontrast images and may have a potential role in clinical decision-making. Further prospective studies with larger populations and cross-validation are warranted.
Clinical success of guided tissue regeneration for treating vertical bone and furcation defects in dogs
Authors: Lee Bonnie L. , Soukup Jason , Rendahl Aaron , Goldschmidt Stephanie
Published: August 2023

This study evaluated the clinical success rate of guided tissue regeneration (GTR) for treating advanced periodontal disease in a large canine cohort. A total of 112 GTR procedures performed from 2003–2021 were retrospectively evaluated, including pre- and post-treatment (3–12 months) periodontal probing depths of 104 treated teeth, dental radiographs of 73 treated teeth, and both diagnostic modalities in 64 treated teeth. Probing depth, radiographically apparent bone height, bone graft material, barrier membrane material, and tooth extraction adjacent to the GTR site were investigated as factors affecting success. Vertical bone defects were evaluated separately from furcation defects. GTR was clinically successful, defined as objective improvement in probing depth, objective decrease in radiographic vertical bone defect, and subjective radiographic gain in bone height in 90.3% of vertical bone defects. Success was significantly associated with the magnitude of initial probing depth and the type of barrier membrane used. GTR was clinically successful, defined as objective improvement in furcation probing and subjective radiographic improvement of the bone in the furcation in 22.2% of furcation defects. When F3 lesions were excluded, GTR was successful in 64.3% of furcation defects. GTR is an appropriate treatment to maintain teeth in the oral cavity of dogs with proper client counseling and patient selection, but it is most likely to be successful in vertical defects.
Investigation of biofilm formation and the associated genes in multidrug-resistant Salmonella pullorum in China (2018–2022)
Authors: Chen Wenyan , Xu Ziheng , Li Changcheng , Wang Can , Wang Min , Liang Jingzhen , Wei Ping
Published: August 2023

The study explored the biofilm (BF) formation capacity, BF-related gene profiles, and the trends in antimicrobial resistance (AMR) of Salmonella pullorum (SP) strains over several years. A total of 627 SP strains were isolated from 4,540 samples collected from chicken farms in Guangxi, China during 2018–2022. The BF-forming capacity of these isolates was assessed using crystal violet staining, and the presence of eight BF-related genes (csgA, csgB, csgD, ompR, bapA, pfs, luxS, and rpoS) in BF formation-positive strains was determined through Polymerase Chain Reaction (PCR) analysis. Antimicrobial susceptibility test was conducted to investigate the AMR of the isolates. Minimum Inhibitory Concentration (MIC) and Minimal Biofilm Eradication Concentration (MBEC) of nine SP-BF strains were determined using the broth microdilution method to assess the impact of BF formation on AMR. Additionally, the Optimal Biofilm Formation Conditions (OBFC) were investigated. The results indicated that 36.8% (231/627) of the strains exhibited a positive BF-formation capacity. Among these, 24.7% (57/231) were strong BF producers, 23.4% (54/231) were moderate BF producers, and 51.9% (120/231) were weak BF producers. Analysis of the eight BF-related genes in SP-BF strains revealed that over 90% of them were positive for all the genes. Antimicrobial susceptibility test conducted on the isolates showed that 100% (231/231) of them exhibited resistance to at least one antibiotic, with 98.3% (227/231) demonstrating multidrug resistance (MDR). Both MIC and MBEC measurements indicated varying degrees of increased AMR after BF formation of the bacteria. The optimal conditions for BF formation were observed at 37°C after 48 h of incubation, with an initial bacterial concentration of 1.2 × 106 CFU/mL. Notably, NaCl had a significant inhibitory effect on BF formation, while glucose and Trypticase Soy Broth (TSB) positively influenced BF formation. The results of the study emphasized the need for effective preventive and control strategies to address the challenges posed by the BF formation and MDR of SP in the field.
Surveying North American Specialty Crop Growers’ Current Use of Soilless Substrates and Future Research and Education Needs
Authors: Fields Jeb S. , Owen James S. , Lamm Alexa , Altland James , Jackson Brian , Oki Lorence , Samtani Jayesh B. , Zheng Youbin , Criscione Kristopher S.
Published: August 2023

Many specialty crop growers are transitioning high-value crops from in-ground production to soilless culture due to the diminishing availability of fumigants, increasing pest pressure, extreme weather, and the need for flexible production practices. The objective of this study was to determine the research and educational needs of specialty crop growers who are transitioning to soilless substrates. North American growers were surveyed using an online instrument that incorporated Likert-type statement matrices, open-ended questions, and demographic questions. Additionally, two virtually led focus groups were conducted to further expand upon the quantitative findings with descriptive data. Respondents indicated the most important factors in considering whether to adopt soilless substrates were improving, managing, and reducing overall plant quality, disease management, and crop loss, respectively. The most important research needs were understanding the effects of substrates on crop quality and uniformity, fertilizer management, and economic costs and benefits/return on investment. In both the grower survey and focus groups, crop quality and uniformity were among the highest-scored responses. Food safety, disease and pest management, consumer perception, substrate disposal-related issues, transportation, and return-on-investment were also identified as important factors when considering soilless substrates.
Method of Attention-Based CNN for Weighing Pleurotus eryngii
Authors: Jia Junmin , Hu Fei , Zhang Xubo , Ben Zongyou , Wang Yifan , Chen Kunjie
Published: August 2023

Automatic weight detection is an essential step in the factory production of Pleurotus eryngii. In this study, a data set containing 1154 Pleurotus eryngii images was created, and then machine vision technology was used to extract eight two-dimensional features from the images. Because the fruiting bodies of Pleurotus eryngii have different shapes, these features were less correlated with weight. This paper proposed a multidimensional feature derivation method and an Attention-Based CNN model to solve this problem. This study aimed to realize the traditional feature screening task by deep learning algorithms and built an estimation model. Compared with different regression algorithms, the R2, RMSE, MAE, and MAPE of the Attention-Based CNN were 0.971, 7.77, 5.69, and 5.87%, respectively, and showed the best performance. Therefore, it can be used as an accurate, objective, and effective method for automatic weight measurements of Pleurotus eryngii.
Determinants of Simultaneous Use of Soil Fertility Information Sources among Smallholder Farmers in the Central Highlands of Kenya
Authors: Asule Pamellah A. , Musafiri Collins , Nyabuga George , Kiai Wambui , Ngetich Felix K. , Spurk Christoph
Published: August 2023

Soil fertility decline is a significant drawback to food and nutritional security in sub-Saharan Africa. However, information and knowledge barriers seriously impede the adoption, effective use, and scaling up of soil fertility management innovations, especially by smallholder farmers who produce the bulk of the region’s food needs. Apart from the knowledge that smallholder farmers seek soil fertility information from diverse sources, which they apply simultaneously, there is limited knowledge of farmers’ information-seeking behaviour regarding which sources are used simultaneously and the factors influencing these choices. We employed a cross-sectional survey study design to determine the simultaneous use of soil fertility information sources of 400 smallholder farming households in the Central Highlands of Kenya. We analysed the data using descriptive statistics, principal component analysis (PCA), and a multivariate probit model. The PCA distinguished seven categories of information sources farmers use: local interpersonal, cosmopolite interpersonal, aggregative, print/demonstration, broadcast media, community-based, and progressive learning sources. The intensity of use revealed that most of the smallholders used soil fertility information sources simultaneously and primarily as complements. The determinants of simultaneous use of soil fertility information sources were farmer location, marital status, main occupation, age, farming experience, exposure to agricultural training, group membership, arable land and livestock units owned, soil fertility status, soil fertility change, and soil testing. This study’s findings have implications for information dissemination strategies involving using multiple complementary sources of knowledge for improved soil health and productivity.
Calibration and Modeling of Parameters for Kale Root Stubble Simulation Based on the Discrete Unit Method
Authors: Chen Jun , Jiang Pin , Liu Jianfei , Zhang Xiaocong , Shi Yixin
Published: August 2023

Today, the post-harvest root stubble treatment of kale in Hunan mostly uses manual pulling and centralized treatments, which are inefficient and labor-intensive. In this study, to realize the direct mechanical crushing of kale root stubble and return it to the field after harvesting, we established an accurate simulation model of kale root stubble by creating a model of the root stubble of kale and calibrating the parameters of the simulation. This study took Jingfeng No. 1 kale stubble as the research object and used EDEM2021.2 simulation software to study the parameters of the kale stubble-crushing simulation model. The peak shear force of the sheared kale root stubble was used as the test data, and the most significant factors affecting the shear force were screened out through the Plackett–Burman test for the Design-Expert design. In addition, the steepest climb test and Box–Behnken test were used to accurately assess the factor data to obtain the best simulation value, which was 861.02 N. The relative error between the simulated and measured values was 0.61%. Finally, an accurate simulation stubble model was established by combining the best simulation parameters with the measured stubble length and diameter. This model provides a theoretical basis and technical support for more in-depth research on stubble simulation and mechanized stubble return.
Tracing the Element: The Molecular Bases of Molybdenum Homeostasis in Legumes
Authors: Bursakov Sergey A. , Kroupin Pavel Yu. , Karlov Gennady I. , Divashuk Mikhail G.
Published: August 2023

The optimization of all constituent conditions to obtain high and even maximum yields is a recent trend in agriculture. Legumes play a special role in this process, as they have unique characteristics with respect to storing protein and many other important components in their seeds that are useful for human and animal nutrition as well as industry and agriculture. A great advantage of legumes is the nitrogen fixation activity of their symbiotic nodule bacteria. This nitrogen self-sufficiency contributes directly to the challenging issue of feeding the world’s growing population. Molybdenum is one of the most sought-after nutrients because it provides optimal conditions for the maximum efficiency of the enzymes involved in nitrogen assimilation as well as other molybdenum-containing enzymes in the host plant and symbiotic nodule bacteria. In this review, we consider the most optimal way of providing legume plants with molybdenum, its distribution in ontogeny throughout the plant, and its accumulation at the end of the growing season in the seeds. Overall, molybdenum supply improves seed quality and allows for the efficient use of the micronutrient by molybdenum-containing enzymes in the plant and subsequently the nodules at the initial stages of growth after germination. A sufficient supply of molybdenum avoids competition for this trace element between nitrogenase and nodule nitrate reductase, which enhances the supply of nitrogen to the plant. Finally, we also consider the possibility of regulating molybdenum homeostasis using modern genetic approaches.
The Impact of Greenhouse and Field Growth Conditions on Chenopodium quinoa Willd Accessions’ Response to Salt Stress: A Comparative Approach
Authors: Slimani Narmine , Arraouadi Soumaya , Hajlaoui Hafedh , Borgi Mohamed Ali , Boughattas Nour El Houda , De Feo Vincenzo , Snoussi Mejdi
Published: August 2023

Quinoa’s exceptional capacity to tolerate high salt levels presents a promising solution to the agricultural challenges posed by salt stress. This study aimed to explore salt stress effects on three quinoa accessions (18 GR, R-132, and DE-1) and to compare the influence of greenhouse and field growing conditions on their salinity tolerance. The plants were irrigated by 50, 100, 150, and 200 mM NaCl concentrations. The results showed that quinoa plants’ response to morphological, physiological, biochemical, and enzymatic parameters was influenced by NaCl concentration, accession, growing conditions, and their interactions. As salinity irrigation increased, aerial part length and leaf area decreased significantly (p < 0.05) for all studied accessions, correlating with plant photosynthetic parameters. Greenhouse conditions promote faster and more vigorous growth with a larger leaf area compared to field cultivation. Furthermore, at 200 mM concentration, the DE-1 accession displayed greater photosynthetic activity, recording values of 195.66 ± 3.56 and 120 ± 1.13 µmol·m−2·s−1 for greenhouse and open field conditions, respectively. NaCl stimulated MDA and H2O2 in both conditions for all accessions, and the DE-1 accession displayed the lowest levels. Proteins, sugars, proline, peroxidase, ascorbate peroxidase, and catalase were stimulated by salt stress, except in the R-132 accession. Field cultivation resulted in a more severe salinity response. Greenhouse conditions may enhance quinoa’s salt tolerance due to the less demanding growth conditions. DE-1 exhibited the highest salt tolerance, while R-132 showed the lowest. This study sets the stage for further research into the genetic basis of salt tolerance in various quinoa accessions, optimizing growth in salty regions through farming practices, and confirming the obtained results in real-world conditions for sustainable agriculture.
Impact of Inbreeding and Ancestral Inbreeding on Longevity Traits in German Brown Cows
Authors: Wirth Anna , Duda Jürgen , Distl Ottmar
Published: August 2023

A recent study on the population structure of the German Brown population found increasing levels of classical and ancestral inbreeding coefficients. Thus, the aim of this study was to determine the effects of inbreeding depression and purging on longevity traits using classical and ancestral inbreeding coefficients according to Kalinowski (2002) (Fa_Kal, FNew), Ballou (1997) (Fa_Bal), and Baumung (2015) (Ahc). For this purpose, uncensored data of 480,440 cows born between 1990 and 2001 were available. We analyzed 17 longevity traits, including herd life, length of productive life, number of calvings, lifetime and effective lifetime production for milk, fat, and protein yield, the survival to the 2nd, 4th, 6th, 8th, and 10th lactation number, and the culling frequencies due to infertility, or udder and foot and leg problems. Inbreeding depression was significant and negative for all traits but for culling due to udder and to foot and leg problems. When expressed in percentages of genetic standard deviations, inbreeding depression per 1% increase in inbreeding was −3.61 to −10.98%, −2.42 to −2.99%, −2.21 to −4.58%, and 5.13% for lifetime production traits, lifetime traits, survival rates, and culling due to infertility, respectively. Heterosis and recombination effects due to US Brown Swiss genes were positive and counteracted inbreeding depression. The effects of FNew were not significantly different from zero, while Fa_Kal had negative effects on lifetime and lifetime production traits. Similarly, the interaction of F with Fa_Bal was significantly negative. Thus, purging effects could not be shown for longevity traits in German Brown. A possible explanation may be seen in the breed history of the German Brown, that through the introgression of US Brown Swiss bulls ancestral inbreeding increased and longevity decreased. Our results show, that reducing a further increase in inbreeding in mating plans is advisable to prevent a further decline in longevity due to inbreeding depression, as purging effects were very unlikely in this population.
Effect of Slow-Release Urea Partial Replacement of Soybean Meal on Lactation Performance, Heat Shock Signal Molecules, and Rumen Fermentation in Heat-Stressed Mid-Lactation Dairy Cows
Authors: Jiang Maocheng , Zhang Xuelei , Wang Kexin , Datsomor Osmond , Li Xue , Lin Miao , Feng Chunyan , Zhao Guoqi , Zhan Kang
Published: August 2023

This study aimed to assess the effects of partially substituting soybean meal in the diet with slow-release urea (SRU) on the lactation performance, heat shock signal molecules, and environmental sustainability of heat-stressed lactating cows in the middle stage of lactation. In this study, 30 healthy Holstein lactating dairy cattle with a similar milk yield of 22.8 ± 3.3 kg, days in milk of 191.14 ± 27.24 days, and 2.2 ± 1.5 parity were selected and randomly allocated into two groups. The constituents of the two treatments were (1) basic diet plus 500 g soybean meal (SM) for the SM group and (2) basic diet plus 100 g slow-release urea and 400 g corn silage for the SRU group. The average temperature humidity index (THI) during the experiment was 84.47, with an average THI of >78 from day 1 to day 28, indicating the cow experienced moderate heat stress conditions. Compared with the SM group, the SRU group showed decreasing body temperature and respiratory rate trends at 20:00 (p < 0.1). The substitution of SM with SRU resulted in an increasing trend in milk yield, with a significant increase of 7.36% compared to the SM group (p < 0.1). Compared to the SM group, AST, ALT, and γ-GT content levels were significantly increased (p < 0.05). Notably, the levels of HSP-70 and HSP-90α were significantly reduced (p < 0.05). The SRU group showed significantly increased acetate and isovalerate concentrations compared with the SM group (p < 0.05). The prediction results indicate that the SRU group exhibits a significant decrease in methane (CH4) emissions when producing 1 L of milk compared to the SM group (p < 0.05). In summary, dietary supplementation with SRU tended to increase the milk yield and rumen fermentation and reduce plasma heat shock molecules in mid-lactation, heat-stressed dairy cows. In the hot summer, using SRU instead of some soybean meal in the diet alleviates the heat stress of dairy cows and reduces the production of CH4.
Application of Machine Learning Algorithms to Describe the Characteristics of Dairy Sheep Lactation Curves
Authors: Guevara Lilian , Castro-Espinoza Félix , Fernandes Alberto Magno , Benaouda Mohammed , Muñoz-Benítez Alfonso Longinos , del Razo-Rodríguez Oscar Enrique , Peláez-Acero Armando , Angeles-Hernandez Juan Carlos
Published: August 2023

In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting and modeling complex data. Therefore, the aim of this study was to evaluate the prediction ability of different ML algorithms and a traditional empirical model to estimate the parameters of lactation curves. A total of 1186 monthly records from 156 sheep lactations were used. The model development process involved training and testing models using ML algorithms. In addition to these algorithms, lactation curves were also fitted using the Wood model. The goodness of fit was assessed using correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and relative root mean square error (RRSE). SMOreg was the algorithm with the best estimates of the characteristics of the sheep lactation curve, with higher values of r compared to the Wood model (0.96 vs. 0.68) for the total milk yield. The results of the current study showed that ML algorithms are able to adequately predict the characteristics of the lactation curve, using a relatively small number of input data. Some ML algorithms provide an interpretable architecture, which is useful for decision-making at the farm level to maximize the use of available information.
Genomic Characterization and Initial Insight into Mastitis-Associated SNP Profiles of Local Latvian Bos taurus Breeds
Authors: Gudra Dita , Valdovska Anda , Jonkus Daina , Galina Daiga , Kairisa Daina , Ustinova Maija , Viksne Kristine , Fridmanis Davids , Kalnina Ineta
Published: August 2023

Latvia has two local Bos taurus breeds—Latvian Brown (LBG) and Latvian Blue (LZG)—characterized by a good adaptation to the local climate, longevity, and high fat and protein contents in milk. Since these are desired traits in the dairy industry, this study investigated the genetic background of the LBG and LZG breeds and identified the genetic factors associated with mastitis. Blood and semen samples were acquired, and whole genome sequencing was then performed to acquire a genomic sequence with at least 35× or 10× coverage. The heterozygosity, nucleotide diversity, and LD analysis indicated that LBG and LZG cows have similar levels of genetic diversity compared to those of other breeds. An analysis of the population structure revealed that each breed clustered together, but the overall differentiation between the breeds was small. The highest genetic variance was observed in the LZG breed compared with the LBG breed. Our results show that SNP rs721295390 is associated with mastitis in the LBG breed, and SNPs rs383806754, chr29:43998719CG>C, and rs462030680 are associated with mastitis in the LZG breed. This study shows that local Latvian LBG and LZG breeds have a pronounced genetic differentiation, with each one suggesting its own mastitis-associated SNP profile.
First Isolation and Identification of Aeromonas veronii in a Captive Giant Panda (Ailuropoda melanoleuca)
Authors: Su Xiaoyan , Yang Mei , Li Yunli , Yan Xia , Hou Rong , Ayala James Edward , Li Lin , Yue Chanjuan , Zhang Dongsheng , Liu Songrui
Published: August 2023

The objective of this study was to understand biological characteristics of one bacteria strain named as VPG which was isolated from multiple organs of a dead captive giant panda cub. Here, we use biochemical tests, 16S rRNA and gyrB genes for bacterial identification, the disk diffusion method for antibiotic resistance phenotype, smart chip real-time PCR for the antibiotic resistance genotype, multiplex PCR for determination of virulence genes, and the acute toxicity test in mice for testing the pathogenicity of isolates. The isolate was identified as A. veronii strain based on the biochemical properties and genetic analysis. We found that the strain carried 31 antibiotic resistance genes, revealed antimicrobial resistance phenotypically to several antibiotics including penicillin, ampicillin, oxacillin, amoxicillin, imipenem, and vancomycin, and carried virulence genes including aer, act, lip, exu, ser, luxs, and tapA. The main pathological changes in giant panda were congestion, necrotic lesions and a large number of bacteria in multiple organs. In addition, the LD50 in Kunming mice infected with strain VGP was 5.14 × 107 CFU/mL by intraperitoneal injection. Infection with strain VGP led to considerable histological lesions such as hemorrhage of internal organs, necrosis of lymphocytes and neurons in Kunming mice. Taken together, these results suggest that infection with strain VGP would be an important causes of death in this giant panda cub.
Inferring on Speleomantes Foraging Behavior from Gut Contents Examination
Authors: Cianferoni Fabio , Lunghi Enrico
Published: August 2023

We here provide the first comprehensive analysis and discussion on prey consumed by the European cave salamanders of the genus Speleomantes. Our study stems from the need to shed light on the still unknown foraging behavior adopted by Speleomantes cave salamanders. Starting from the published datasets on gut contents from all Speleomantes species (including hybrids), we here discuss additional information (i.e., species ecology, lower taxonomic level), which were systematically omitted from those data sets. We analyzed a data set consisting of 17,630 records from 49 categories of consumed prey recognized from gut contents of 2060 adults and juveniles Speleomantes. Flying prey accounted for more than 58% of the prey items, while elongated crawling prey accounted for no more than 16% of the diet within a single population. Among the total recognized prey items, only three can be surely ascribed to the group of strictly-cave species (i.e., troglobites), meaning that European cave salamanders mostly forage in surface environment, and therefore represent one of the major drivers of allochthonous organic matter in subterranean environments. Some of the consumed prey seemed to be aquatic, allowing us to hypothesize whether Speleomantes are able to catch prey from a shallow body water. Furthermore, European cave salamanders possess the ability to prey upon taxa characterized by particular anti-predator defenses, while morphological constraints seem to be the most important limit to prey consumption. For each specific case, we provide insights and propose hypotheses concerning the foraging behavior that need to be tested to properly understand the foraging behavior of this cryptic salamanders.
Editorial for the Special Issue “Antibiotic Prescribing and Antimicrobial Resistance Patterns in Pediatric Patients”
Authors: Vicentini Costanza , Zotti Carla Maria
Published: August 2023

Antibiotic overuse is among the most important factors contributing to the growing problem of antimicrobial resistance (AMR) [...]
Pitfalls of Mitochondrial Redox Signaling Research
Authors: Ježek Petr
Published: August 2023

Redox signaling from mitochondria (mt) to the cytosol and plasma membrane (PM) has been scarcely reported, such as in the case of hypoxic cell adaptation or (2-oxo-) 2-keto-isocaproate (KIC) β-like-oxidation stimulating insulin secretion in pancreatic β-cells. Mutual redox state influence between mitochondrial major compartments, the matrix and the intracristal space, and the cytosol is therefore derived theoretically in this article to predict possible conditions, when mt-to-cytosol and mt-to-PM signals may occur, as well as conditions in which the cytosolic redox signaling is not overwhelmed by the mitochondrial antioxidant capacity. Possible peroxiredoxin 3 participation in mt-to-cytosol redox signaling is discussed, as well as another specific case, whereby mitochondrial superoxide release is diminished, whereas the matrix MnSOD is activated. As a result, the enhanced conversion to H2O2 allows H2O2 diffusion into the cytosol, where it could be a predominant component of the H2O2 release. In both of these ways, mt-to-cytosol and mt-to-PM signals may be realized. Finally, the use of redox-sensitive probes is discussed, which disturb redox equilibria, and hence add a surplus redox-buffering to the compartment, where they are localized. Specifically, when attempts to quantify net H2O2 fluxes are to be made, this should be taken into account.
Protein Kinase A Controls the Melanization of Candida auris through the Alteration of Cell Wall Components
Authors: Kim Ji-Seok , Bahn Yong-Sun
Published: August 2023

Candida auris, a multidrug-resistant fungal pathogen, significantly threatens global public health. Recent studies have identified melanin production, a key virulence factor in many pathogenic fungi that protects against external threats like reactive oxygen species, in C. auris. However, the melanin regulation mechanism remains elusive. This study explores the role of the Ras/cAMP/PKA signaling pathway in C. auris melanization. It reveals that the catalytic subunits Tpk1 and Tpk2 of protein kinase A (PKA) are essential, whereas Ras1, Gpr1, Gpa2, and Cyr1 are not. Under melanin-promoting conditions, the tpk1Δ tpk2Δ strain formed melanin granules in the supernatant akin to the wild-type strain but failed to adhere them properly to the cell wall. This discrepancy is likely due to a decreased expression of chitin-synthesis-related genes. Our findings also show that Tpk1 primarily drives melanization, with Tpk2 having a lesser impact. To corroborate this, we found that C. auris must deploy Tpk1-dependent melanin deposition as a defensive mechanism against antioxidant exposure. Moreover, we confirmed that deletion mutants of multicopper oxidase and ferroxidase genes, previously assumed to influence C. auris melanization, do not directly contribute to the process. Overall, this study sheds light on the role of PKA in C. auris melanization and enhances our understanding of the pathogenicity mechanisms of this emerging fungal pathogen.
Analysis of Vibration Characteristics of Cross-Type Hydraulic Pipeline Based on Finite Element Method
Authors: Liu Zhe , Li Huiping , Li Baichun , Chen Jiaxin , Liu Yong
Published: August 2023

Branched hydraulic lines are prone to leakage and break under complex working conditions. The coupling vibration problem caused by the fluid pressure beat and external mechanical excitation of the pump at the junction of the branch of the cross-type hydraulic pipeline is very common. So a method combining finite element simulation and fluid-structure interaction vibration experiments is proposed for research. First, the possibility of the finite element method in solving the pipeline vibration problem is verified, and then the modal analysis and harmonious response analysis of the cross-type pipe are carried out to discuss the influence of fluid pressure and solid elastic modulus on pipeline vibration. The results show that as the fluid pressure and pipeline elastic modulus change, different modes of different orders will be affected. Under external excitation, only a portion of the order is sensitive to external excitation.
Graph Database and Matrix-Based Intelligent Generation of the Assembly Sequence of Prefabricated Building Components
Authors: Yang Bin , Jiang Shanshan , Dong Miaosi , Zhu Dayu , Han Yilong
Published: August 2023

The assembly of prefabricated components is a critical process in prefabricated building construction, influencing both progress and accuracy. However, the assembly sequence planning and optimization (ASPO) of prefabricated components have yet to receive sufficient attention from researchers, and current research has displayed limited automation and poor generalization capabilities. Therefore, this paper proposes a framework for intelligently generating assembly sequences for prefabricated components based on graph databases and matrices. The framework utilizes an adjacency matrix and interference matrix-based modeling method to comprehensively describe the connections and constraint relationships between components, enabling better evaluation of assembly difficulty during optimization. The graph database serves as the central hub for data exchange, facilitating component information storage, automatic querying, and summarization. The obtained assembly sequence and progress plan are fed back into the graph database. To accomplish assembly sequence optimization, a genetic algorithm based on the double-elite strategy is employed. Furthermore, the effectiveness of the proposed framework is validated through an actual engineering case. The results demonstrate that the framework can effectively find an optimal assembly sequence to mitigate the assembly challenge of a prefabricated building.
Prediction of Blade Tip Timing Sensor Waveforms Based on Radial Basis Function Neural Network
Authors: Zhang Liang , Chen Cong , Xia Yiming , Song Qingxi , Cao Junjun
Published: August 2023

As the existing Blade Tip Timing (BTT) vibration measurement methods have serious under-sampling problems, where the blade resonance frequency is usually higher than the sampling frequency of the data acquisition system of the BTT method, resulting in large errors in the identification of blade vibration parameters, new solutions are needed to extend the capability of BTT to nonlinear and multimodal vibration analysis. Therefore, it is the current research direction to pursue new and more accurate measurement and signal processing methods. By analyzing the waveform data from the BTT sensor and using it for vibration analysis, it significantly extends the BTT database. To avoid the current problems of under-sampling and low recognition accuracy, this paper conducts a study on the recognition of rotating blade vibration parameters based on the Radial Basis Function (RBF) model by establishing a RBF neural network prediction model to analyze the static calibration experimental data and predict the waveform of the BTT sensor, and comparing the prediction curves of various models. As the results show, for the RBF model, the prediction accuracy is closely related to the source data of the sampling point data, when the source data predicted by the RBF model is close to the center of the samples, the prediction accuracy is high, meanwhile, the prediction accuracy decreases as it is far away from the center of these data. At the same time, the number of samples is too small to affect the prediction ability of the RBF model. By using this method, more waveforms under the Blade Tip Clearance (BTC) can be predicted with the available sample point data, and the errors in the experimental measurement process can be corrected.
Unleashing Creative Synergies: A Mixed-Method Case Study in Music Education Classrooms
Authors: Cardoso Mário Anibal , Morgado Elsa Maria Gabriel , Leonido Levi
Published: August 2023

Algorithmic music composition has been gaining prominence and recognition as an innovative approach to music education, providing students with opportunities to explore creativity, computational thinking, and musical knowledge. This study aims to investigate the impact of integrating algorithmic music composition in the classroom, examining its influence on student engagement, musical knowledge, and creative expression, as well as to enhance computational thinking skills. A mixed-method case study was conducted in three Basic Music Education classrooms in the north of Portugal, involving 71 participants (68 students and 3 music teachers). The results reveal: (i) both successes and challenges in integrating computational thinking concepts and practices; (ii) pedagogical benefits of integrating programming platforms, where programming concepts overlapped with music learning outcomes; and (iii) positive impact on participants’ programming self-confidence and recognition of programming’s importance. Integrating algorithmic music composition in the classroom positively influences student engagement, musical knowledge, and creative expression. The use of algorithmic techniques provides a novel and engaging platform for students to explore music composition, fostering their creativity, critical thinking, and collaboration skills. Educators can leverage algorithmic music composition as an effective pedagogical approach to enhance music education, allowing students to develop a deeper understanding of music theory and fostering their artistic expression. Future research should contribute to the successful integration of digital technologies in the Portuguese curriculum by further exploring the long-term effects and potential applications of algorithmic music composition in different educational contexts.
The Production of Marine Iron Objects in Europe Following the First Industrial Revolution: The Akko Tower Shipwreck Test Case
Authors: Iddan Noam , Ashkenazi Dana , Cvikel Deborah
Published: August 2023

Four ferrous objects, a winch, a heart-shaped shackle, a deadeye strap with a futtock plate, and a stud-link chain controller, that were retrieved from the Akko Tower shipwreck were studied by different methods, including conventional metallography, light microscopy, scanning electron microscopy with energy-dispersive spectroscopy, optical emission spectroscopy, microhardness measurements, and the novel field multi-focal metallography (FMM), in order to determine their composition, microstructure, and manufacturing methods. The results of FMM agree well with conventional destructive metallography. The winch drum was made of grey cast iron and its shaft was wrought iron; the heart-shaped shackle and the deadeye strap with a futtock plate were wrought iron; and the stud-link chain controller was grey cast iron similar in composition and microstructure to the winch. All the wrought iron items revealed a similar composition and microstructure. Based on the composition, microstructure, and manufacturing processes of the four items, it is suggested that they were manufactured in the mid-nineteenth century. The high quality of these items indicates that they were produced using controlled processes, probably in the same workshop.
Effects of Freeze–Thaw Cycles on the Mechanical Properties and Microstructure of a Dispersed Soil
Authors: Zhang Shurui , Xu Xin , Dong Xiaoqiang , Lei Haomin , Sun Xun
Published: August 2023

Dispersed soil is highly sensitive to water and can easily disperse in low-salt water, leading to weakened structures and engineering issues. To investigate the freeze–thaw effects on the mechanical properties and microstructure of dispersed soils in western Jilin Province, we simulated 0, 1, 3, 5, 7, 9, 12, and 15 freeze–thaw cycles. Qualitative and quantitative analyses were performed using numerous methods, including soluble salt determination, density and water content determination, particle size analysis, dispersion identification tests, and scanning electron microscopy (SEM), to investigate the mechanism of deterioration in soil mechanical properties from various perspectives. The research findings indicate that the unconfined compressive strength (UCS) decreased from 156.843 kPa in the unfrozen state to 76.961 kPa and then stabilized. The freeze–thaw action resulted in particle fragmentation, increased soil porosity, and elevated crack content, thereby contributing to soil structure deterioration and strength reduction. Furthermore, the cohesion value (c-value) gradually decreased from 22.196 kPa in the unfrozen state to 7.997 kPa and then stabilized. The angle of internal friction (φ-value) started at 7.514°, peaked at 9.514°, and gradually declined. This comprehensive study provides valuable insights into the variations in soil mechanical properties under freeze–thaw cycles from multiple perspectives.
Integrating Text Classification into Topic Discovery Using Semantic Embedding Models
Authors: Lezama-Sánchez Ana Laura , Tovar Vidal Mireya , Reyes-Ortiz José A.
Published: August 2023

Topic discovery involves identifying the main ideas within large volumes of textual data. It indicates recurring topics in documents, providing an overview of the text. Current topic discovery models receive the text, with or without pre-processing, including stop word removal, text cleaning, and normalization (lowercase conversion). A topic discovery process that receives general domain text with or without processing generates general topics. General topics do not offer detailed overviews of the input text, and manual text categorization is tedious and time-consuming. Extracting topics from text with an automatic classification task is necessary to generate specific topics enriched with top words that maintain semantic relationships among them. Therefore, this paper presents an approach that integrates text classification for topic discovery from large amounts of English textual data, such as 20-Newsgroups and Reuters Corpora. We rely on integrating automatic text classification before the topic discovery process to obtain specific topics for each class with relevant semantic relationships between top words. Text classification performs a word analysis that makes up a document to decide what class or category to identify; then, the proposed integration provides latent and specific topics depicted by top words with high coherence from each obtained class. Text classification accomplishes this with a convolutional neural network (CNN), incorporating an embedding model based on semantic relationships. Topic discovery over categorized text is realized with latent Dirichlet analysis (LDA), probabilistic latent semantic analysis (PLSA), and latent semantic analysis (LSA) algorithms. An evaluation process for topic discovery over categorized text was performed based on the normalized topic coherence metric. The 20-Newsgroups corpus was classified, and twenty topics with the ten top words were identified for each class. The normalized topic coherence obtained was 0.1723 with LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters Corpus was also classified, and twenty and fifty topics were identified. A normalized topic coherence of 0.1441 was achieved when applying the LDA algorithm, obtaining 20 topics for each class; with LSA, the coherence was 0.1360, and with PLSA, it was 0.1436.
Study on the Rate of the Removal of Nano-Crystalline Diamond—Coated Materials by Femtosecond Laser Etching
Authors: Ren Lujun , Ma Yuping , Cao Haisong , Zhang Xingxing , Han Yuan , Wei Chao
Published: August 2023

The rate of the removal of materials coated with nano−crystalline diamonds by femtosecond laser etching was examined by adjusting the repetition rate of the femtosecond laser, the energy−flux density of the concentrated spot, and the scanning speed. The observational results of the white-light interferometer and the numerical fitting approach were used to develop the removal rate function model of the nano-crystalline diamond-covered material etched by the femtosecond laser. The findings demonstrated that the rate of material removal was not greatly affected by the repetition frequency and that the amount of laser energy accumulated over time on the coated surface is steady. The processing outcomes under different laser scanning speeds are different, and the material removal rate tends to increase and then decrease with an increase in scanning speed. The greater the energy−flux density of the focused spot, the greater the etching intensity, and the greater the material removal rate. With an increase in scanning speed, the rate at which the material is removed often rises initially before falling.
A Novel Chaotic Elite Adaptive Genetic Algorithm for Task Allocation of Intelligent Unmanned Wireless Sensor Networks
Authors: Fei Hongmei , Zhang Baitao , Liu Yan , Yan Manli , Lu Yi , Zhou Jie
Published: August 2023

In recent times, the progress of Intelligent Unmanned Wireless Sensor Networks (IUWSNs) has inspired scientists to develop inventive task allocation algorithms. These efficient techniques serve as robust stochastic optimization methods, aimed at maximizing revenue for the network’s objectives. However, with the increase in sensor numbers, the computation time for addressing the challenge grows exponentially. To tackle the task allocation issue in IUWSNs, this paper introduces a novel approach: the Chaotic Elite Adaptive Genetic Algorithm (CEAGA). The optimization problem is formulated as an NP-complete integer programming challenge. Innovative elite and chaotic operators have been devised to expedite convergence and unveil the overall optimal solution. By merging the strengths of genetic algorithms with these new elite and chaotic operators, the CEAGA optimizes task allocation in IUWSNs. Through simulation experiments, we compare the CEAGA with other methods—Hybrid Genetic Algorithm (HGA), Multi-objective Binary Particle Swarm Optimization (MBPSO), and Improved Simulated Annealing (ISA)—in terms of task allocation performance. The results compellingly demonstrate that the CEAGA outperforms the other approaches in network revenue terms.