bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementation of dietary semen vaccariae extracts to lactating sow diets: effects on the production performance, milk components, and gene expression related to mammogenesis
Authors: Xu Chaohua , Xie Jiajun , Ji Fengjie , Peng Weiqi , Song Yuzhuo , Diao Xinping , Wu Hongzhi
Published: November 2023

This study aimed to investigate the effects of dietary semen vaccariae extracts (SVE) on the production performance, colostrum components, and relative gene expression related to mammogenesis of lactating sows. 48 pregnant sows were selected and randomly allocated into four groups, with six replicates and two sows per replicate. The first group was the control (CON), while the other groups received the same diet further supplemented with 1.5, 3.0 and 4.5 g SVE per kg (SV1, SV2 and SV3, respectively). Compared with the control group, (1) the average daily gain was increased (p < 0.05) in SV1, SV2, and SV3 during the 11–21 days and 1–21 days of lactation; (2) the serum insulin-like growth factor-1, insulin, prolactin, and estrogen contents in SV1, SV2, and SV3 were increased (p < 0.05) on the 1st and 21st day of lactation; (3) The plasma Lysine, Threonine, and Tryptophan concentrations were also higher (p < 0.05) in SV1, SV2, and SV3 on the 1st and 21st day of lactation; (4) The milk Lysine, Methionine, Threonine, and Tryptophan concentrations were higher (p < 0.05) in SV1, SV2, and SV3 on the 1st and 21st day of lactation; (5) The milk lactose ratio and milk protein content were increased (p < 0.05) in the groups treated with semen vaccariae on the 1st day of lactation, while the milkfat ratio and milk protein content were increased (p < 0.05) in SV2 and SV3 on the 21st day of lactation; (6) the immunoglobulin M, A, and G contents were increased (p < 0.05) in the groups treated with the semen vaccariae on the first day of lactation; and (7) the relative PRLR, STAT5a, FcRn, CSN2, and LALBA expressions were higher (p < 0.05) in the groups treated with the semen vaccariae on the 1st and 21st day of lactation. In this study, the optimum dosage was 3.0 g/kg semen vaccariae, which increased the average daily gain of piglets, total lactation yield, and serum hormone levels, improved the amino acid levels in plasma, and facilitated the milk quality, up-regulated the relative gene expressions in the mammogenesis.
Exploring the benefits of in-diet versus repeated oral dosing of saracatinib (AZD0530) in chronic studies: insights into pharmacokinetics and animal welfare
Authors: Vasanthi Suraj S. , Massey Nyzil , Nair Suresh N. , Mochel Jonathan P. , Showman Lucas , Thippeswamy Thimmasettappa
Published: November 2023

Saracatinib/AZD0530 (SAR), a Src tyrosine kinase inhibitor, mitigates seizure-induced brain pathology in epilepsy models upon repeated oral dosing. However, repeated dosing is stressful and can be challenging in some seizing animals. To overcome this issue, we have incorporated SAR-in-Diet and compared serum pharmacokinetics (PK) and brain concentrations with conventional repeated oral dosing. Saracatinib in solution or in-diet was stable at room temperature for >4 weeks (97 ± 1.56%). Adult Sprague Dawley rats on SAR-in-Diet consumed ~1.7 g/day less compared to regular diet (16.82 ± 0.6 vs. 18.50 ± 0.5 g/day), but the weight gain/day was unaffected (2.63 ± 0.5 g/day vs. 2.83 ± 0.2 g/day). Importantly, we achieved the anticipated SAR dose range from 2.5–18.7 mg/kg of rat in response to varying concentrations of SAR-in-Diet from 54 to 260 ppm of feed, respectively. There was a strong and significant correlation between SAR-in-Diet dose (mg/kg) and serum saracatinib concentrations (ng/ml). Serum concentrations also did not vary significantly between SAR-in-Diet and repeated oral dosing. The hippocampal saracatinib concentrations derived from SAR-in-Diet treatment were higher than those derived after repeated oral dosing (day 3, 546.8 ± 219.7 ng/g vs. 238.6 ± 143 ng/g; day 7, 300.7 ± 43.4 ng/g vs. 271.1 ± 62.33 ng/g). Saracatinib stability at room temperature and high serum and hippocampal concentrations in animals fed on SAR-in-Diet are useful to titer the saracatinib dose for future animal disease models. Overall, test drugs in the diet is an experimental approach that addresses issues related to handling stress-induced variables in animal experiments.
Performance and Applicability of Post-Quantum Digital Signature Algorithms in Resource-Constrained Environments
Authors: Vidaković Marin , Miličević Kruno
Published: November 2023

The continuous development of quantum computing necessitates the development of quantum-resistant cryptographic algorithms. In response to this demand, the National Institute of Standards and Technology selected standardized algorithms including Crystals-Dilithium, Falcon, and Sphincs+ for digital signatures. This paper provides a comparative evaluation of these algorithms across key metrics. The results indicate varying strengths and weaknesses for each algorithm, underscoring the importance of context-specific deployments. Our findings indicate that Dilithium offers advantages in low-power scenarios, Falcon excels in signature verification speed, and Sphincs+ provides robust security at the cost of computational efficiency. These results underscore the importance of context-specific deployments in specific and resource-constrained technological applications, like IoT, smart cards, blockchain, and vehicle-to-vehicle communication.
Crushing the Spirit: Unmasking the Impact of Workplace Bullying on Psychological Wellbeing among Portuguese Employees
Authors: Cerdeira José Pedro , Cakirpaloglu Simona Dobešová , Cakirpaloglu Panajotis
Published: November 2023

The research objective of this study was to determine the prevalence of workplace bullying and to find out whether there is a relationship between workplace bullying and psychological wellbeing among employees in Portugal working in different sectors. A cross-sectional study and a survey were conducted with 205 employees to gather the data. The findings indicate that the prevalence of bullying ranges from 28.8% to 9.96% when applying different measurements. The results also revealed that, in the context of the possible influence of different forms of bullying on mental wellbeing, person-related bullying had the strongest effect on mental restlessness, sadness, impulsivity, and anxiety, while it showed the weakest effect on depression. In all cases, the presence of person-related bullying decreased the level of psychological wellbeing. The results of this study hold practical implications for organizations, as they emphasize the crucial role of managers in being aware of and implementing strategies to prevent workplace bullying. By prioritizing mental health among employees, managers may enhance their overall wellbeing and foster positive work relationships, ultimately contributing to a healthier and more productive work environment.
Impact-Angle Constraint Guidance and Control Strategies Based on Deep Reinforcement Learning
Authors: Fan Junfang , Dou Denghui , Ji Yi
Published: November 2023

In this study, two different impact-angle-constrained guidance and control strategies using deep reinforcement learning (DRL) are proposed. The proposed strategies are based on the dual-loop and integrated guidance and control types. To address comprehensive flying object dynamics and the control mechanism, a Markov decision process is used to solve the guidance and control problem, and a real-time impact-angle error in the state vector is used to improve the model applicability. In addition, a reasonable reward mechanism is designed based on the state component which reduces both the miss distance and the impact-angle error and solves the problem of sparse rewards in DRL. Further, to overcome the negative effects of unbounded distributions on bounded action spaces, a Beta distribution is used instead of a Gaussian distribution in the proximal policy optimization algorithm for policy sampling. The state initialization is then realized using a sampling method adjusted to engineering backgrounds, and the control strategy is adapted to a wide range of operational scenarios with different impact angles. Simulation and Monte Carlo experiments in various scenarios show that, compared with other methods mentioned in the experiment in this paper, the proposed DRL strategy has smaller impact-angle errors and miss distance, which demonstrates the method’s effectiveness, applicability, and robustness.
Artificial Intelligence-Based Fault Diagnosis and Prediction for Smart Farm Information and Communication Technology Equipment
Authors: Choe Hyeon O. , Lee Meong-Hun
Published: November 2023

Despite the recent increase in smart farming practices, system uncertainty and difficulties associated with maintaining farming sites hinder their widespread adoption. Agricultural production systems are extremely sensitive to operational downtime caused by malfunctions because it can damage crops. To resolve this problem, the types of abnormal data, the present error determination techniques for each data type, and the accuracy of anomaly data determination based on spatial understanding of the sensed values are classified in this paper. We design and implement a system to detect and predict abnormal data using a recurrent neural network algorithm and diagnose malfunctions using an ontological technique. The proposed system comprises the cloud in charge of the IoT equipment installed in the farm testbed, communication and control, system management, and a common framework based on machine learning and deep learning for fault diagnosis. It exhibits excellent prediction performance, with a root mean square error of 0.073 for the long short-term memory model. Considering the increasing number of agricultural production facilities in recent years, the results of this study are expected to prevent damage to farms due to downtime caused by mistakes, faults, and aging.
Untapped Genetic Resources for Breeding Acidic Soil-Adapted Chickpea (Cicer arietinum L.) Cultivars
Authors: Negusse Hawi , Haileselassie Teklehaimanot , Geleta Mulatu , Tesfaye Kassahun
Published: November 2023

Globally, more than half of potentially arable land is acidic, and aluminum (Al) is the primary factor limiting plant growth and crop productivity on acidic soils worldwide. The development and utilization of Al-tolerant crops is a sustainable approach to enhancing crop production on acidic soils. For this purpose, screening available genetic resources under Al-stressed conditions is a crucial initial step. Hence, the present study aimed to evaluate the Al tolerance of 264 Ethiopian chickpea landraces under hydroponic conditions without Al (control) and with 120 µM Al (Al treatment). Significant (p < 0.001) variations were detected among the genotypes for all studied traits under control (0 µM Al) and 120 µM Al concentration. The relative growth values for the 120 µM Al/0 µM Al ratio was also significant, indicating the presence of a considerable amount of genetic variation in Ethiopian chickpea landraces in terms of Al tolerance. Based on relative root growth (RRG) as an Al-tolerance parameter, the genotypes were grouped into five distinct (p < 0.001) classes. The highest RRG value (1.59) was obtained for genotype ETC_209008, followed by ETC_41184 and ETC_212589, while ETC_208995 had the lowest RRG value of 0.27. Of the total landraces screened, 35% had higher RRG values than the tolerant genotype ETC_WL_1_2016 used as a reference, indicating the presence of adequate genotypes capable of outperforming the reference genotype on acidic soils. The genotypes identified in the present study may serve as sources of novel alleles in genes regulating Al tolerance in chickpea that can be utilized in breeding programs to improve the crop’s adaptation to acidic soils, thus contributing to smallholder farmers’ increased nutritional and food security.
Motion-Control Strategy for a Heavy-Duty Transport Hexapod Robot on Rugged Agricultural Terrains
Authors: Yang Kuo , Liu Xinhui , Liu Changyi , Wang Ziwei
Published: November 2023

Legged agricultural transportation robots are efficient tools that can autonomously transport goods over agricultural terrain, and their introduction helps to improve the efficiency and quality of agricultural production. Their effectiveness depends on their adaptability to different environmental conditions, which is especially true for heavy-duty robots that exert ground forces. Therefore, this study proposes a motion-control strategy for a heavy-duty transport hexapod robot. Two critical tasks were accomplished in this paper: (1) estimating the support surface angle based on the robot’s foot position and body posture, and accordingly determining the motion constraint conditions on this support surface and the body posture based on energy optimization; (2) proposing an adaptive fuzzy impedance algorithm for real-time force–position composite control for adjusting foot position, in order to reduce the steady-state force tracking error caused by terrain stiffness, thus ensuring body stability through tracking of variable foot-end forces. An element of hardware in the loop control platform for a 3.55-ton device was designed and compared with the current popular force-control methods under different external contact terrains. The results show that the proposed control method can effectively reduce force errors, establish support forces faster on less-stiff environments, and reduce the torso tilt during phase switching.
Integrating Agro-Morpho-Physiological Traits and SSR Markers for Detecting the Salt Tolerance of Advanced Spring Wheat Lines under Field Conditions
Authors: Junaid Muhammad Bilawal , El-Hendawy Salah , Al-Ashkar Ibrahim , Al-Suhaibani Nasser , Alotaibi Majed
Published: November 2023

To successfully enhance the salt tolerance of genotypes, it is crucial to conduct field-based trials, establish effective screening criteria and analysis tools, evaluate salt tolerance at various growth stages, and integrate phenotypic assessment-based traits with molecular markers. This study aimed to assess the salt tolerance of 16 F8 recombinant inbred lines (RILs) and eight genotypes by analyzing 13 agro-morpho-physiological traits using various analysis tools and SSR markers under both control and high salinity levels (15 dS m−1) in real field conditions. Analysis of variance (ANOVA), comparison of mean values, calculation of reduction percentage, and multivariate analysis were used to compare the assessed traits among genotypes and identify which traits are the most effective ones in describing the salt tolerance of these genotypes. A heatmap cluster analysis (HMCA) was also employed to categorize the salt tolerance of genotypes into different clusters based on the stress tolerance index (STI) for all traits. The ANOVA results revealed significant statistical differences (p ≤ 0.05) between the genotypes and salinity levels for all assessed traits in each season and their combined data. Moreover, the 150 mM NaCl treatment led to decreases in the assessed traits by 10.2% to 36.9% when compared to the control treatments. Furthermore, the mean values of assessed traits for certain genotypes were approximately one to three times greater than those of other genotypes. Principal component analysis has identified plant dry weight, green leaf area, leaf area index, and grain yield per hectare as effective screening criteria for explaining the substantial variation observed among the genotypes. The HMCA successfully grouped genotypes into three distinct clusters and distinguished the salt-tolerant genotypes from the salt-sensitive and intermediate ones. The 24 genotypes/RILs were classified into three main groups according to the allelic data of 40 SSRs associated with salt-tolerant genes. A weak yet significant correlation was observed between the similarity coefficients of agro-morpho-physiological traits and SSR markers, as determined by the Mantel test (r = 0.13, p < 0.03, and alpha = 0.05). In conclusion, this study has successfully identified several traits, particularly those associated with SSR markers, that greatly contribute to our understanding of the phenotypic and genotypic basis influencing the salt tolerance of wheat genotypes in real field conditions. Consequently, assessing these traits for a large number of wheat plant materials in a rapid and cost-effective manner will be greatly importance in breeding programs aimed at improving salt stress tolerance in this vital food crop. This will be the main focus of our forthcoming research.
Data-Driven Analysis and Machine Learning-Based Crop and Fertilizer Recommendation System for Revolutionizing Farming Practices
Authors: Musanase Christine , Vodacek Anthony , Hanyurwimfura Damien , Uwitonze Alfred , Kabandana Innocent
Published: November 2023

Agriculture plays a key role in global food security. Agriculture is critical to global food security and economic development. Precision farming using machine learning (ML) and the Internet of Things (IoT) is a promising approach to increasing crop productivity and optimizing resource use. This paper presents an integrated crop and fertilizer recommendation system aimed at optimizing agricultural practices in Rwanda. The system is built on two predictive models: a machine learning model for crop recommendations and a rule-based fertilization recommendation model. The crop recommendation system is based on a neural network model trained on a dataset of major Rwandan crops and their key growth parameters such as nitrogen, phosphorus, potassium levels, and soil pH. The fertilizer recommendation system uses a rule-based approach to provide personalized fertilizer recommendations based on pre-compiled tables. The proposed prediction model achieves 97% accuracy. The study makes a significant contribution to the field of precision agriculture by providing decision support tools that combine artificial intelligence and domain knowledge.
Euglena gracilis β-Glucans (1,3): Enriching Colostrum of Sow for Enhanced Piglet Immunity
Authors: de Carvalho Rafael Humberto , Callegari Marco Aurélio , Dias Cleandro Pazinato , Kirwan Susanne , da Costa Mara Cristina Ribeiro , da Silva Caio Abércio
Published: November 2023

The effects of supplementing the diet of sows with βG-(1,3) derived from Euglena gracilis algae were assessed regarding quality and amount of colostrum as well as performance of piglets. A total of 120 sows (first (nulliparous) to sixth parity (multiparous)) from D85 of gestation until weaning were divided into two groups: the control diet group (n = 60) and the βG-(1,3) diet group (n = 60). Sows receiving βG-(1,3) exhibited an average increase of 870 g (24.9%) in colostrum production, leading to a 25.17% higher intake of colostrum by piglets. Furthermore, piglets in the βG-(1,3) group showed significantly superior weight gain of 34 g (50%) compared to the control group 18 h after birth (p < 0.05). Sows fed with βG-(1,3) produced colostrum with significantly higher concentrations of IgG (5.914 mg/mL, 16.16%) and IgM (0.378 mg/mL, 16.29%) than the control group (p < 0.05). Similarly, serum concentrations of IgG (13.86 mg/mL, 51.25%), IgA (17.16 mg/mL, 120.19%), and IgM (13.23 mg/mL, 144.78%) were significantly higher in sows fed with βG-(1,3) than in the control group (p < 0.05). Supplementing sows with βG-(1,3) derived from the Euglena gracilis algae resulted in increased colostrum production and consumption, along with greater weight gain in piglets during the first 18 h after birth. Additionally, both the colostrum produced by the sows and the blood serum of the piglets exhibited higher concentrations of immunoglobulins.
Modeling Spatio-Temporal Variations in the Habitat Utilization of Swordtip Squid (Uroteuthis edulis) in the East China Sea and Southern Yellow Sea
Authors: Gao Xiaodi , Jiang Yazhou , Yuan Xingwei , Yang Linlin , Ling Jianzhong , Li Shengfa
Published: November 2023

Accurately modeling the distribution of keystone species is of utmost importance to gain a comprehensive understanding of their complex ecological dynamics and to develop effective strategies for sustainable scientific management. In the coastal China ecosystem, the swordtip squid (Uroteuthis edulis) stands out as a keystone species with significant commercial and ecological value. Despite its importance, research on the ecological dynamics of this species remains limited and requires further investigation. To investigate the spatial and temporal variability in the distribution of U. edulis and identify the key environmental drivers in the East China Sea (ECS) and southern Yellow Sea across different seasons, we generated ensemble models using oceanographic variables and fishery-independent scientific survey data collected from 2016 to 2018. Our results revealed that U. edulis predominantly inhabited the central and southern regions of the ECS throughout the year. The primary environmental variables driving its distribution varied by season, with the sea surface temperature being the most important in spring, sea surface height in summer and autumn, and depth in winter. During summer and autumn, the suitable habitats of U. edulis were found to be largest and extended northwards towards the coastline. However, they migrated southwards to the waters near the edge of the ECS continental shelf with smaller suitable areas in the spring and winter. These results suggested that U. edulis exhibited season-specific habitat preferences and responded to changing environmental conditions throughout the year. The observed seasonal distribution patterns were likely influenced by the fluctuating mixture of waters (ocean currents) from different sources, with varying physical and chemical characteristics throughout the year. Our study provides baseline data for comprehending the population dynamics of U. edulis and highlights the significance of considering species’ habitat preferences in a dynamic environment.
Effects of Glucose Levels on Inflammation and Amino Acid Utilization in Lipopolysaccharide-Induced Bovine Mammary Epithelial Cells
Authors: Song Han , Lu Zhiqi , Zhan Kang , Datsomor Osmond , Ma Xiaoyu , Yang Tianyu , Chen Yuhang , Jiang Maocheng , Zhao Guoqi
Published: November 2023

Glucose and amino acids are important sources of nutrients in the synthetic milk of dairy cows, and understanding the fate of amino acids is essential to optimize the utilization of amino acids in milk protein synthesis, thereby reducing nutrient inefficiencies during lactation. The purpose of this study was to investigate the effects of LPS and different concentrations of glucose on (1) the expression of inflammatory factors and genes, (2) the glucose metabolism, and (3) amino acid utilization in BMECs. The results showed that there was an interaction (LPS × glucose, p < 0.05) between LPS and glucose content in the inflammatory cytokine genes (IL-6 and TNF-α) and the inflammatory regulatory genes (CXCL2, CXCL8, and CCL5). With the addition of LPS, the HG + LPS group caused downregulated (p < 0.05) expression of IL-6 and TNF-α, compared with the LG + LPS group. Interestingly, compared with the LG + LPS group, the HG + LPS group upregulated (p < 0.05) the expression of CXCL2, CXCL8, and CCL5. LPS supplementation increased (p = 0.056) the consumption of glucose and GLUT1 gene expression (p < 0.05) and tended to increase (p = 0.084) the LDHA gene expression of BMECs under conditions of different concentrations of glucose culture. High glucose content increased (p < 0.001) the consumption of glucose and enhanced (p < 0.05) the GLUT1, HK1, HK2, and LDHA gene expression of BMECs with or without LPS incubation, and there was an interaction (LPS × glucose, p < 0.05) between LPS and glucose concentrations in GLUT1 gene expression. In this study, LPS enhanced (p < 0.05) the consumption of amino acids such as tryptophan, leucine, isoleucine, methionine, valine, histidine, and glutamate, while high levels of glucose decreased (p < 0.01) consumption, except in the case of tyrosine. For histidine, leucine, isoleucine, and valine consumption, there was an interaction (LPS × glucose, p < 0.05) between LPS and glucose levels. Overall, these findings suggest that relatively high glucose concentrations may lessen the LPS-induced BMEC inflammatory response and reduce amino acid consumption, while low glucose concentrations may increase the demand for most amino acids through proinflammatory responses.
RNAseq Analysis of Livers from Pigs Treated with Testosterone and Nandrolone Esters: Selection and Field Validation of Transcriptional Biomarkers
Authors: Benedetto Alessandro , Šťastný Kamil , Giaccio Nunzia , Marturella Marianna , Biasibetti Elena , Arigoni Maddalena , Calogero Raffaele , Gili Marilena , Pezzolato Marzia , Tošnerová Kristína , Hodkovicová Nikola , Faldyna Martin , Puleio Roberto , Bozzo Giancarlo , Bozzetta Elena
Published: November 2023

The use of anabolic–androgenic steroids (AASs) as growth promoters in farm animals is banned in the European Union, representing both an illicit practice and a risk for consumer health. However, these compounds are still illegally administered, often in the form of synthetic esters. This work aimed to characterize significant coding RNA perturbations related to the illicit administration of testosterone and nandrolone esters in fattening pigs. A total of 27 clinically healthy 90-day-old pigs were randomly assigned to test and control groups. Nine animals were treated with testosterone esters (Sustanon®) and other nine with nandrolone esters (Myodine®). At the end of the trial, liver samples were collected and analyzed using RNAseq, allowing the identification of 491 differentially expressed genes (DEGs). The transcriptional signature was further characterized by a smaller sub-cluster of 143 DEGs, from which a selection of 16 genes was made. The qPCR analysis confirmed that the identified cluster could still give good discrimination between untreated gilt and barrows compared to the relative testosterone-treated counterparts. A conclusive field survey on 67 liver samples collected from pigs of different breeds and weight categories confirmed, in agreement with testosterone residue profiles, the specificity of selected transcriptional biomarkers, showing their potential applications for screening purposes when AAS treatment is suspected, allowing to focus further investigations of competent authorities and confirmatory analysis where needed.
Dietary Supplementation with Lysozyme–Cinnamaldehyde Conjugates Enhances Feed Conversion Efficiency by Improving Intestinal Health and Modulating the Gut Microbiota in Weaned Piglets Infected with Enterotoxigenic Escherichia coli
Authors: Tian Zhezhe , Chen Jiaming , Lin Tongbin , Zhu Junhua , Gan Haoyang , Chen Fang , Zhang Shihai , Guan Wutai
Published: November 2023

This study aims to evaluate the efficacy of lysozyme–cinnamaldehyde conjugates (LC) as a potential alternative to antibiotics in treating piglets infected with enterotoxigenic Escherichia coli (ETEC). The results demonstrated that piglets fed with the LC diet exhibited lower rectal temperature and fecal scores at 9 h, 24 h, and 48 h post-ETEC challenge. Furthermore, LC supplementation led to significant improvements in the mechanical and immune barriers of the jejunum and ileum, as indicated by an increased villi-height-to-crypt-depth ratio (VCR) and the expression of tight junction proteins, mucin, and β-defensins. Furthermore, the LC diet lowered the levels of pro-inflammatory cytokines TNF-α and IL-1β in the plasma. Further analyses showed that the LC diet downregulated genes (specifically TLR4 and MyD88) linked to the TLRs/MyD88/NF-κB signaling pathway in the small intestine. Additionally, 16SrDNA sequencing data revealed that LC supplementation increased the α diversity of intestinal microorganisms and the relative abundance of Lactobacillus. In summary, the LC-supplemented diet effectively mitigated the adverse effects of E. coli K88, including intestinal barrier damage and inflammation. Furthermore, it improved the structure of the intestinal flora, ultimately contributing to better growth performance in piglets.
Effect of Miscellaneous Meal Replacements for Soybean Meal on Growth Performance, Serum Biochemical Parameters, and Gut Microbiota of 50–75 kg Growing Pigs
Authors: He Zhentao , Zhan Xianliang , Cao Shuting , Wen Xiaolu , Hou Lei , Liu Shuai , Zheng Huayu , Gao Kaiguo , Yang Xuefen , Jiang Zongyong , Wang Li
Published: November 2023

This study was carried out to investigate the effects of miscellaneous meal (rapeseed meal, cottonseed meal, and sunflower seed meal) as a replacement for soybean meal on growth performance, apparent nutrient digestibility, serum biochemical parameters, serum free amino acid contents, and gut microbiota of 50–75 kg growing pigs. A total of 54 healthy growing pigs (Duroc × Landrace × Yorkshire) with initial body weights (BWs) of 50.64 ± 2.09 kg were randomly divided into three treatment groups, which included the corn–soybean meal group (CON), corn–soybean–miscellaneous meal group (CSM), and corn–miscellaneous meal group (CM). Each treatment included six replicates with three pigs in each replicate. Dietary protein levels were maintained at 15% in all three treatment groups. Additional rapeseed meals, cottonseed meals, and sunflower seed meals were added to the CSM group’s meals to partially replace the 10.99% soybean meal in the CON group in a 1:1:1 ratio. Pigs in the CM group were fed a diet with a mixture of miscellaneous meals (7.69% rapeseed meal, 7.69% cottonseed meal, and 7.68% sunflower seed meal) to totally replace soybean meal. Our findings revealed that there was no significant impact of replacing soybean meal with miscellaneous meal on the ADG (average daily gain), ADFI (average daily feed intake), or F/G (feed-to-gain ratio) (p > 0.05) of growing pigs weighing 50–75 kg, nor on the crude protein, crude fat, or gross energy (p > 0.05) of the diet. On the other hand, compared to the CON group, the CM group exhibited significantly elevated serum alanine aminotransferase (ALT) and triglyceride (TG) levels (p < 0.05), while urea levels were significantly reduced (p < 0.05). No significant effect was observed on the serum free amino acid contents (p > 0.05) following the substitution of soybean meal with miscellaneous meal. A t-test analysis indicated that compared with the CON group, the CM group exhibited a significantly diminished abundance of Euryachaeota at the phylum level and augmented abundance of Desulfobacterota at the genus level. This study demonstrated that the miscellaneous meals (rapeseed meal, cottonseed meal, and sunflower seed meal) as a substitute for soybean meal in the diet had no significant negative effects on the growth performance, apparent nutrient digestibility, serum amino acid content, or diversity of fecal microbiota in 50–75 kg growing pigs. These results can be helpful in developing further miscellaneous meals (rapeseed meal, cottonseed meal, and sunflower seed meal) as functional alternative feed ingredients to soybean meal in pig diets.
Infectious Bovine Rhinotracheitis Post-Eradication Program in the Autonomous Province of Bolzano, Italy: A Retrospective Study on Potential Bovine Herpesvirus Type 2 Cross-Reactivity
Authors: Bettini Astrid , Stella Martina , Precazzini Francesca , Degasperi Marta , Colorio Stefano , Tavella Alexander
Published: November 2023

Bovine alphaherpesviruses, BoAHV, can cause respiratory, genital and neurological disorders. In particular, bovine alphaherpesvirus type 1 (BoAHV1) is one of the most significant ruminant pathogens worldwide and it can heavily damage the livestock industry. BoAHV1 can cause infectious bovine rhinotracheitis (IBR) along with fertility disorders. Bovine alphaherpesvirus type 2 (BoAHV2) can cause two different conditions as well: pseudo-lumpy skin disease (PSLD) and bovine herpetic mammillitis (BHM). The autonomous province of Bolzano (Italy) has adopted several strategies to control and eradicate IBR, and it was declared in 2000 to be IBR-free by the European Commission. Since 2001, a post-eradication monitoring program has overseen the serological analysis of bulk milk and, in the presence of a positive result, a follow-up examination is performed on the individual blood serum of all bovines older than 24 months that belong to bulk milk-positive herds. Despite the detection of positives in both bulk milk and serum samples, South Tyrol has been declared IBR-free, as these positives have never been confirmed through seroneutralization. Between 2014 and 2022, approximately 41,000 bulk milk (averaging 4300 samples/year) and 3229 serum samples were tested for BoAHV1. The aim of this study was to evaluate the post-eradication program for IBR with a particular focus on the potential cross-reactivity with BoAHV2; for this reason, serum samples were also tested for BoAHV2 antibodies. This study could be of great importance for those countries that submit herds to an IBR monitoring and eradication program; performing further analyses to confirm and explain false positive outcomes would increase the reliability of the obtained results.
Antioxidant and Biological Activities of Mahajanaka Mango Pulp Extract in Murine Models
Authors: Paradee Narisara , Janthip Rattanaporn , Taesothikul Tawat , Kanjanapothi Duangta , Settakorn Kornvipa , Srichairatanakool Somdet , Koonyosying Pimpisid
Published: November 2023

Mahajanaka mango, a hybrid cultivar of Mangifera indica Linn., is a highly nutritional fruit that is popularly consumed in Thailand. It has been used in traditional medicine due to its abundance of phytonutrients. The present study aimed to investigate the chemical compositions and antioxidant activity of Mahajanaka mango pulp extract (MPE) in vitro. Additionally, we examined its biological activities, including the analgesic, anti-inflammatory, gastroprotective, and hepatoprotective effects of MPE, in murine models. MPE exhibited high levels of phenolic compounds, mangiferin, β-carotene, and vitamin C, and it potentially showed antioxidant properties in an ABTS scavenging assay. The animal results have revealed that oral administration of MPE (1000 mg/kg body weight (BW)) significantly decreased acetic acid-induced writhing responses in mice. Interestingly, local applications of MPE at 1 mg/ear ameliorated ethyl phenylpropiolate (EPP)-induced ear edema, while gavage of MPE at 1000 mg/kg BW significantly decreased carrageenan-induced hind paw edema in rats. MPE can also protect against gastric ulcers induced by stress, hydrochloric acid/ethanol, and indomethacin in rats. Indeed, MPE (250 mg/kg BW) markedly lowered the level of serum alanine aminotransferase activity and hepatic lipid accumulation in rats with CCl4- and paracetamol-induced hepatotoxicity. Taken together, the findings suggested that MPE exerts potent antioxidant, analgesic, anti-inflammatory, gastroprotective, and hepatoprotective effects.
IFE-Net: An Integrated Feature Extraction Network for Single-Image Dehazing
Authors: Leng Can , Liu Gang
Published: November 2023

In recent years, numerous single-image dehazing algorithms have made significant progress; however, dehazing still presents a challenge, particularly in complex real-world scenarios. In fact, single-image dehazing is an inherently ill-posed problem, as scene transmission relies on unknown and nonhomogeneous depth information. This study proposes a novel end-to-end single-image dehazing method called the Integrated Feature Extraction Network (IFE-Net). Instead of estimating the transmission matrix and atmospheric light separately, IFE-Net directly generates the clean image using a lightweight CNN. During the dehazing process, texture details are often lost. To address this issue, an attention mechanism module is introduced in IFE-Net to handle different information impartially. Additionally, a new nonlinear activation function is proposed in IFE-Net, known as a bilateral constrained rectifier linear unit (BCReLU). Extensive experiments were conducted to evaluate the performance of IFE-Net. The results demonstrate that IFE-Net outperforms other single-image haze removal algorithms in terms of both PSNR and SSIM. In the SOTS dataset, IFE-Net achieves a PSNR value of 24.63 and an SSIM value of 0.905. In the ITS dataset, the PSNR value is 25.62, and the SSIM value reaches 0.925. The quantitative results of the synthesized images are either superior to or comparable with those obtained via other advanced algorithms. Moreover, IFE-Net also exhibits significant subjective visual quality advantages.
Investigation of Wind Power Potential in Mthatha, Eastern Cape Province, South Africa
Authors: Shonhiwa Chipo , Makaka Golden , Mukumba Patrick , Shambira Ngwarai
Published: November 2023

South Africa is currently grappling with a national energy crisis and the high infrastructure costs associated with expanding the national grid to remote areas. Simultaneously, the government has made substantial efforts to harness renewable energy technologies, particularly wind energy. The average wind speed in a specific region significantly influences the energy yield from wind turbines. The vast open inland terrains, mountainous regions, and coastal areas in the Northern Cape, Eastern Cape, and Western Cape provinces of South Africa possess the most substantial wind potential. It is imperative to initiate wind energy projects in these provinces to cater to a significant portion of the local electricity demand, especially in remote areas disconnected from the national grid. Wind energy generation is inherently stochastic, subject to variations in both time and space. Consequently, it is essential to gain a comprehensive understanding of the local wind patterns to assess the feasibility of utilizing wind resources. In the Eastern Cape Province, the Mthatha area still lags in household electrification, presenting an opportunity to electrify some households using wind energy. This study aimed to evaluate the wind resource potential for Mthatha area, utilizing data spanning from 2018 to 2023, provided by the South African Weather Services. Two distribution models, the two-parameter Weibull and three-parameter Weibull, were employed to characterize the provided wind data. To determine the parameters associated with each distribution model, two estimation methods, the Maximum Likelihood Method (MLM) and the Method of Moments (MOM), were utilized. The performance of these distribution models was assessed using the Root Mean Square Error (RMSE) statistical indicator. The results showed that Mthatha area predominantly experiences low wind speeds, with an annual average wind speed of 3.30 m/s and an overall wind power density of approximately 48.48 W/m2. The prevailing winds predominantly originate from the south and east–southeast directions. Consequently, Mthatha is recommended for stand-alone applications, with the added suggestion of augmented wind turbines for the area.
Multivariate Regression and Variance in Concrete Curing Methods: Strength Prediction with Experiments
Authors: Xie Haiyan Sally , Gandla Sai Ram , Shi Owen , Solanki Pranshoo
Published: November 2023

Because concrete strengths and quality are affected by various factors, multivariate regression models are often used to analyze the differences between predicted and target outputs. However, the variableness of a predicted output and how individual input parameters affect prediction reliabilities are still uncertain in practical applications, especially for the prediction of compressive strengths of concrete. This study aims to develop multivariate models for predicting concrete strengths and providing the variance analysis of prediction results by comparisons with experiment outcomes. First, this paper provides an in-depth examination of established variance analysis methods in the context of commonly used multivariate regression models. Then, based on Gaussian process regression, this study melds principal component analysis (PCA), linear discriminant analysis (LDA), and multivariate analysis of variance (MANOVA) to assess the variability in concrete strength prediction using different curing methods. This innovative approach proves effective in evaluating the precision of the correlation and regression models (R-squared values ≥ 0.9049). The comparison between prediction results and experiment outcomes shows that retaining heat in cylinders can make them become too hot and overestimate in-place concrete strength. This study improves the methodologies of regression modeling for variance analysis and improves the reliability of concrete strength prediction. Additionally, the outcomes of this research can help save a substantial amount of financial resources and time that are required to obtain experimental data on the strengths of concrete components.
Noise Source Diagnosis Method Based on Transfer Path Analysis and Neural Network
Authors: Huang Yizhe , Huang Bin , Cao Yuanpeng , Zhan Xin , Huang Qibai , Wang Jiaxuan
Published: November 2023

Clarifying the noise source and the contribution of each path is essential for the system’s noise control. The auxiliary converter cabinet, which is a crucial component of rail transportation, has numerous intricate noise sources. The contribution of each path point must be inverted-solved using known transfer functions and target point test values when identifying noise sources. This article suggests a method for diagnosing noise using transfer path analysis and neural networks (TPA-NN). Firstly, the principle and scheme for analyzing the transmission path of the converter cabinet are proposed. The transfer function of each path is obtained by selecting suitable path points, reference points, and target points for air and structure acoustic vibration experiments. The external target point data are then combined with the neural network’s linear fitting function, and the contribution of each path is used as an output for network training while some path point contributions are rebuilt. The results indicate that the method’s outcomes are most accurate when the converter cabinet’s path point is 13 and the target point is 6. This approach offers an innovative technique for locating noise sources in intricate systems.
A Mathematical Model for the COVID-19 Pandemic in Tokyo through Changing Point Calculus
Authors: Martinez-Vazquez Laura , Fonseca i Casas Pau
Published: November 2023

The great social and economic impact that the COVID-19 pandemic has had on a global level has encouraged the development of new mathematical models that make it possible to better manage this and future pandemics. Here, we propose an extension of the classical epidemiological compartmental model SIR, the SEIAMD model (Susceptible–Exposed–Identified–Asymptomatic–iMmunized–Deceased), which considers the appearance of new virus variants, the use of vaccines, the existence of nonidentified asymptomatic individuals, and the loss of immunity acquired by infection or vaccination. Using an optimization model coded in Python that allows us to determine the change points that represent different behaviors of infected people, the SEIAMD model calculates, from official data, the different effective contact rates that were observed during the first seven waves of the COVID-19 pandemic in Tokyo due to the application of Non-Pharmaceutical Interventions (NPIs) and social habits. The closeness of the results obtained with our model and the real data, as well as the accuracy of predictions and observations, confirm the suitability of our model for studying the evolution of the COVID-19 pandemic in Tokyo.
Study on the Potential Antitumor Activity of Cookies Enriched with Sambucus nigra L., Aronia melanocarpa, Hippophae rhamnoides L., and Crataegus L., on WM793 Melanoma and MCF-7 Breast Cell Lines
Authors: Borczak Barbara , Kapusta-Duch Joanna , Domagała Dominik , Doskočil Ivo
Published: November 2023

The number of deaths due to malignant neoplasms is increasing year by year. For this reason, new ways of preventing them and supporting treatment are being sought. One of them is adding plant extracts to food to increase its antioxidant, anti-inflammatory and anti-cancerogenic activity. The aim of the study was to examine the effect of different wild-grown fruits (chokeberry, elderberry, hawthorn and sea-buckthorn) added to wheat-flour cookies on the proliferation of: (i) normal BJ lines (fibroblasts); (ii) tumor cells of the MCF-7 (breast cancer) and (iii) WM793 (melanoma) lines. Methanol-acetone extracts were prepared from previously baked wheat-flour cookies fortified with fruits in order to use them in the further part of the research to prepare mixtures with concentrations of 0.5 mg/mL; 1 mg/mL; 1.5 mg/mL; 2.5 mg/mL. The viability and cytotoxicity of normal and neoplastic cells was examined. It was observed that the WM793 melanoma tumor line appeared to be more susceptible to the action of the tested extracts with the addition of selected wild-grown fruits compared to MCF7 breast cancer cells. Moreover, the greatest significant effect on the inhibition of WM793 cells among extracts with a concentration of 2.5 mg/mL was proved in the case of sea-buckthorn (p < 0.05). In terms of the inhibition of the MCF7 line, the effect was proved only in the case of sea buckthorn (p < 0.05), while the viability of these neoplastic cells was at most affected by elderberry and chokeberry extracts (p < 0.05).
A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study
Authors: Vidal-Paz José , Rodríguez-Gómez Benigno Antonio , Orosa José A.
Published: November 2023

With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network over a period of 18 years, but the time series data are not complete. In order to estimate missing rainfall data, four imputation methods were evaluated in this study: missForest, MICE, Amelia II, and inverse distance weighting (IDW). Crossvalidation results show that the precipitation is out of phase in the different stations due to their geographical locations, and the imputation can be improved with a displacement of the time series; on the other hand, the missForest method provided better results in the imputation of this meteorological variable than the MICE, Amelia, or IDW.
Sepsis Treatment Recommendation Using Sensitivity to Input Medicine Dosage in Deep Neural Networks
Authors: Baek Eu-Tteum
Published: November 2023

Sepsis is a life-threatening condition that ranks among the foremost global causes of mortality. Its treatment is marked by significant expenses and the incorporation of diverse symptomatology. Consequently, an array of investigative efforts has been dedicated to sepsis, spanning the classification of its stages, early detection, prognosis prediction, and therapeutic recommendations. Notably, the complex and contentious nature of sepsis management underscores the necessity for precision in combination therapies. In this research endeavor, this study proposes an advanced methodology for sepsis treatment recommendations grounded in deep neural networks. The approach entails the construction of an ensemble deep learning model geared towards predicting the subsequent Sequential Organ Failure Assessment (SOFA) score. Employing this trained ensemble model, the study embarks on the task of optimizing sepsis treatment dosages. The empirical results conclusively demonstrate the superior performance of the proposed ensemble model relative to those of the conventional methods, signifying its capacity to offer treatment prescriptions akin to or surpassing those rendered by medical practitioners. The model consistently outperforms the alternative approaches in predicting the SOFA score and aligns the treatment recommendations with those of medical professionals, exhibiting a high degree of similarity. This innovative approach holds promise for advancing personalized medicine and improving patients’ outcomes in sepsis treatment.