bluuebunny/crossref_metadata_2025 huggingface dataset:
Stress responses, social support and death care experience among spouse caregivers of young and middle-aged patients with terminal cancer: a mixed-methods analysis
Authors: Xu Shaoyuan , Weng Guizhen , Chen Xiaoyan , Liu Lina , Chen Huan
Published: November 2024

Background

Faced with cancer patients in the near-death stage, spousal caregivers may experience a series of stress reactions and have a high risk of suffering from physical and psychological problems. Good social support can help alleviate stressful reactions.

Objectives

To investigate stress responses and social support among spouse caregivers of young and middle-aged patients with terminal cancer in the near-death stage, and to explore the death care experience of spouse caregivers.

Methods

A prospective mixed-methods study was conducted. Questionnaires of stress response questionnaire and social support rating scale were used to investigate stress responses and social support of spouse caregivers. And semi-structured interviews were conducted to explore the death care experience of spouse caregivers in at a university-affiliated hospital in China.

Results

Spouse caregivers with higher social support scores were significantly more likely to have poor stress response. Meanwhile, whether the spouses had alternative care for other dependents, the number of venous pathways and instruments in/on the patient’s body significantly affected the spousal stress response. Among them, spousal social support was the best influencing factor to predict spousal stress response. Four qualitative themes of the death care experience were identified. Theme 1: Psychological feelings of spouses caregivers when they care for the patients’ physical function. Theme 2: Psychological feelings of spouse caregivers when they communicated with the patients. Theme 3: Psychological feelings of spouses caregivers when they will being widowed soon. Theme 4: The focus of life shift, and life concept change.

Conclusion

Overall, spousal stress response was statistically affected by alternative caregivers for spouses, spousal social support, and the number of venous pathways and instruments in/on the patient’s body. Among that, social support was the best influencing factor to predict the stress response. Meanwhile, spousal caregivers was distressed and felt deeply fear, wronged and helpless deep and when facing the patients’ dying symptoms and communicating with patient, and reflected on the essence of life, and changing the concept of life.

Implications for practice

Medical staff should pay special attention to spousal caregivers’ physical discomfort and improve spousal social support, and provide targeted information and assistance to decrease spousal stress response in the near-death stage of cancer patients.
Organic fertilizer increases pumpkin production by improving soil fertility
Authors: Ren Fangfang , Zhang Jinxia , Ding Lin , Zhang Rui , Li Fuqiang , Li Xuan , Zhong Tao , Yin Meng , Yang Runheng , Tian Pengliang , Du Liangliang , Gan Kaiyuan , Yong Tian , Li Qirun , Liu Xingrong
Published: November 2024

Compared with long-term and continuous application of large amounts of chemical fertilizers, fertilizers with microbial organic nutrient sources can improve soil environment, increase soil fertility and increase crop yield. In view of the current low soil fertility and poor soil environment leading to low crop yield and instability in the arid regions of northwest China, the effects of organic fertilizer with microbial nutrient sources on soil nutrients and pumpkin yield were studied in 2022 and 2023 in this region. The fertilizer application level was used as control factor, with four treatments of low level (L), medium level (M), high level (H), and a conventional fertilizer control (CK). The results showed that the high application level of organic fertilizer was more beneficial to the growth of pumpkin, and the stem diameter, vine length, and leaf area of pumpkin under H treatment were the highest from 2022 to 2023. Compared to CK, the average soil bulk density was significantly decreased by 8.27–18.51% (P< 0.05); the soil organic carbon, available phosphorus, available potassium, and nitrate nitrogen under H treatment were increased by an average of 32.37%, 21.85%, 18.70%, and 36.97%, respectively. Under different organic fertilizer treatments, the pumpkin yield under M treatment was the highest, reaching 30926.18 kg·ha-1, followed by H treatment. compared to CK, M and H treatments increased the yield by 25.26% and 7.01%, respectively, and improved water use efficiency by 14.18% and 2.21%, respectively. Redundancy analysis (RDA) of soil nutrients, pumpkin growth dynamics and yield in 2022 and 2023 showed that soil organic carbon, available phosphorus, available potassium, nitrate nitrogen, and water use efficiency were significantly positively correlated with pumpkin yield (P<0.01). In conclusion, H and M treatments can improve soil fertility promote pumpkin growth and development, and ultimately increase pumpkin yield. In summary, medium organic fertilizer level (M=5700 kg·ha-1) is recommended as the fertilization scheme for local pumpkin cultivation.
Electroencephalography: electrode arrays in dogs
Authors: Everest Stephen , Gaitero Luis , Dony Robert , Linden Alexander Zur , Cortez Miguel A. , James Fiona M. K.
Published: November 2024

Electroencephalography (EEG) is the gold standard for confirming epileptic seizures in both human and veterinary patients. Despite idiopathic epilepsy being one of the most common neurological conditions in dogs, our understanding of it in veterinary medicine lags that in human medicine. The relative underuse of EEG in dogs with seizures has potential causes including practical issues, financial concerns, lack of training/equipment, and questions of clinical value. This technological underuse may lead to, or result from, major gaps in our understanding of EEG in veterinary patients. This underutilization of EEG is of significant clinical relevance because the diagnosis of specific epilepsy syndromes in humans guides the treatment, namely pharmacological, dietary, or surgical. These epilepsy syndromes are diagnosed based on several factors, one of which is the characteristic electrical brain activity on EEG. The aim of this narrative literature review was to highlight the study of cortical brain activity to improve our understanding of EEG in veterinary medicine. Specifically, the utility of EEG with focus on the existing proposed electrode arrays and their current supporting evidence. A recent survey study confirmed that a variety of canine EEG protocols are concurrently in use, including diverse electrode arrays. By comparison, in humans there is a standardized 10–20 electrode array, with average localization error of 13–17 mm depending on the number of placed electrodes on the scalp. We offer a review of the factors that would contribute to the ideal canine EEG electrode array highlighting areas for improvement and future validation. This proposed level of understanding will facilitate the identification of cortical seizure foci with a known degree of error, paving the way for non-pharmaceutical interventions like epilepsy surgeries.
Human-computer interactions with farm animals—enhancing welfare through precision livestock farming and artificial intelligence
Authors: Neethirajan Suresh , Scott Stacey , Mancini Clara , Boivin Xavier , Strand Elizabeth
Published: November 2024

While user-centered design approaches stemming from the human-computer interaction (HCI) field have notably improved the welfare of companion, service, and zoo animals, their application in farm animal settings remains limited. This shortfall has catalyzed the emergence of animal-computer interaction (ACI), a discipline extending technology’s reach to a multispecies user base involving both animals and humans. Despite significant strides in other sectors, the adaptation of HCI and ACI (collectively HACI) to farm animal welfare—particularly for dairy cows, swine, and poultry—lags behind. Our paper explores the potential of HACI within precision livestock farming (PLF) and artificial intelligence (AI) to enhance individual animal welfare and address the unique challenges within these settings. It underscores the necessity of transitioning from productivity-focused to animal-centered farming methods, advocating for a paradigm shift that emphasizes welfare as integral to sustainable farming practices. Emphasizing the ‘One Welfare’ approach, this discussion highlights how integrating animal-centered technologies not only benefits farm animal health, productivity, and overall well-being but also aligns with broader societal, environmental, and economic benefits, considering the pressures farmers face. This perspective is based on insights from a one-day workshop held on June 24, 2024, which focused on advancing HACI technologies for farm animal welfare.
Analysis and Optimization of Low-Resistance Animal Bionic Subsoiling Shovel Based on EDEM
Authors: Zhang Lei , Wang Xiaowei , Chen Jianneng , Wang Haiyang , Cao Yonggan
Published: November 2024

Considering the problems of high tillage resistance and high energy consumption in existing subsoiling shovels, the contour-fitting curve characteristics of the front paw toes of mole crickets were applied to the structural design of subsoiling shovels using bionic principles. Combined with the structure of an existing subsoiling shovel, three types of bionic subsoiling shovels were designed using bionic principles, aiming to reduce tillage resistance and energy consumption. In order to investigate their tillage effect, the microparameters of the red soil in South China were calibrated using EDEM 2020, and a corresponding discrete element soil model was established. The simulation conducted on the subsoiling process using both common and bionic subsoiling shovels, and the disturbance of the red soil by common and bionic subsoiling shovels, as well as the tillage resistance and kinetic energy experienced by subsoiling shovels, were studied. The results demonstrated that, compared with the common subsoiling shovel, the bionic subsoiling shovel 1 experienced a 5.31% reduction in tillage force, with a 4.01% reduction in tillage force at the shovel tip, a 7.15% reduction in tillage force at the shovel handle, and a 6.33% reduction in energy consumption. The bionic subsoiling shovel 2 experienced a 9.25% reduction in tillage force, with an 11.43% reduction in tillage force at the tip, a 5.49% reduction in tillage force at the handle, and a 10.58% reduction in energy consumption. The bionic subsoiling shovel 3 experienced a 6.55% reduction in tillage force, with a 5.87% reduction in tillage force at the tip and a 7.72% reduction in tillage force at the handle. Further verification has shown that the bionic subsoiling shovel has better resistance reduction and energy reduction effects.
Potential Role of WIP Family Genes in Drought Stress Response in Rubus idaeus
Authors: Gao Xiangqian , Yang Guiyan , Li Dapei , Xie Muhong , Mei Yujie , Hu Lan , Zheng Yongqi , Avramidou Evangelia V.
Published: November 2024

Rubus idaeus is one of the primary cultivated species of raspberries, renowned for its appealing color, distinctive flavor and numerous health benefits. WIP proteins, which contain three conserved amino acids (W: Tryptophan, I: Isoleucine, P: Proline) and four zinc finger motifs in a highly conserved C-terminal region, are members of the A1d subgroup of C2H2 zinc finger proteins. Drought is one of the main limiting factors of plant growth and development, which restricts the cultivation and utilization of raspberry in northwest China. In this study, to obtain candidate genes for drought resistance, we identified key related genes, RiWIPs, from R. idaeus and analyzed their bioinformation and tissue stress response expression to drought. We found that there are three RiWIPs in R. idaeus and they are located on chromosomes 3, 4 and 6 of R. idaeus, respectively. The open reading frames (ORFs) of the RiWIPs ranged from 870 to 1056 bp in length, encoding 289 to 372 amino acid residues. The proteins were highly conserved and feature diverse conserved motifs. The promoters of the RiWIPs contained abundant cis-elements related to growth, development and stress response. Tissue-specific expression analysis revealed that the RiWIPs were expressed in the leaves, stems and roots of both drought-susceptible and drought-tolerant cultivars, except for RiWIP2, which was only expressed in the roots of the drought-tolerant one. Under drought stress, the transcriptional activity of the RiWIPs was increased to different degrees with specificity in the leaves, stems and roots. Our study demonstrated the role of WIP genes in raspberry drought response and provided a marker gene, RiWIP2, for drought resistance and candidate genes for subsequent drought-resistant breeding of R. idaeus.
The More the Better? Reconsidering the Welfare Effect of Crop Insurance Premium Subsidy
Authors: Hu Mingyu , Yi Fujin , Zhou Hong , Yan Feier
Published: November 2024

China has invested substantial financial subsidies to promote the development of crop insurance; however, the insurance demand among farmers remains notably low, resulting in significant welfare loss. Based on a field survey conducted in 2021 in seven major grain-producing counties in Jiangsu Province, this study analyses the relationship between premium subsidy rates and the welfare effects of subsidies through theoretical model derivation and explores the impact of farmer heterogeneity on the results. This study innovatively introduces a power law distribution model to elucidate the distributional characteristics of farmers’ crop insurance demand, demonstrates the significant limitations of the linear demand model in welfare research, and effectively analyzes the welfare effects of China’s current crop insurance premium subsidy policy. The results indicate that: (1) the actual crop insurance demand of farmers aligns more closely with a power law distribution, and its long-tailed characteristics refute the assumption of linear distribution; (2) there exists an inverted “U”-shaped relationship between the subsidy ratio and the welfare effect, and an excessively high subsidy ratio produces substantial unnecessary losses; (3) variations in welfare effects exist among farmers in different regions, risk attitudes, and cultivation scales, but the range of differences between groups is limited.
Point-to-Interval Prediction Method for Key Soil Property Contents Utilizing Multi-Source Spectral Data
Authors: Liu Shuyan , Huang Dongyan , Fu Lili , Wu Shengxian , Xu Yanlei , Chen Yibing , Zhao Qinglai
Published: November 2024

Key soil properties play pivotal roles in shaping crop growth and yield outcomes. Accurate point prediction and interval prediction of soil properties serve as crucial references for making informed decisions regarding fertilizer applications. Traditional soil testing methods often entail laborious and resource-intensive chemical analyses. To address this challenge, this study introduced a novel approach leveraging spectral data fusion techniques to forecast key soil properties. The initial datasets were derived from UV–visible–near-infrared (UV-Vis-NIR) spectral data and mid-infrared (MIR) spectral data, which underwent preprocessing stages involving smoothing denoising and fractional-order derivative[s] (FOD) transform techniques. After extracting the characteristic bands from both types of spectral data, three fusion strategies were developed, which were further enhanced using machine learning techniques. Among these strategies, the outer-product analysis fusion algorithm proved particularly effective in improving prediction accuracy. For point predictions, metrics such as the coefficient of determination (R2) and error metrics demonstrated significant enhancements compared to predictions based solely on single-source spectral data. Specifically, R2 values increased by 0.06 to 0.41, underscoring the efficacy of the fusion approach combined with partial least squares regression (PLSR). In addition, based on the coverage width criterion to establish reliable prediction intervals for key soil properties, including soil organic matter (SOM), total nitrogen (TN), hydrolyzed nitrogen (HN), and available potassium (AK). These intervals were developed within the framework of the kernel density estimation (KDE) interval prediction model, which facilitates the quantification of uncertainty in property estimates. For available phosphorus (AP), a preliminary assessment of its concentration was also provided. By integrating advanced spectral data fusion with machine learning, this study paves the way for more informed agricultural decision making and sustainable soil management strategies.
Analysis of Growth Variation in Maize Leaf Area Index Based on Time-Series Multispectral Images and Random Forest Models
Authors: Wang Xuyang , Ren Jiaojiao , Wu Penghao
Published: November 2024

The leaf area index (LAI) is a direct indicator of crop canopy growth and serves as an indirect measure of crop yield. Unmanned aerial vehicles (UAVs) offer rapid collection of crop phenotypic data across multiple time points, providing crucial insights into the evolving dynamics of the LAI essential for crop breeding. In this study, the variation process of the maize LAI was investigated across two locations (XD and KZ) using a multispectral sensor mounted on a UAV. During a field trial involving 399 maize inbred lines, LAI measurements were obtained at both locations using a random forest model based on 28 variables extracted from multispectral imagery. These findings indicate that the vegetation index computed by the near-infrared band and red edge significantly influences the accuracy of the LAI prediction. However, a prediction model relying solely on data from a single observation period exhibits instability (R2 = 0.34–0.94, RMSE = 0.02–0.25). When applied to the entire growth period, the models trained using all data achieved a robust prediction of the LAI (R2 = 0.79–0.86, RMSE = 0.12–0.18). Although the primary variation patterns of the maize LAI were similar across the two fields, environmental disparities changed the variation categories of the maize LAI. The primary factor contributing to the difference in the LAI between KZ and XD lies in soil nutrients associated with carbon and nitrogen in the upper soil. Overall, this study demonstrated that UAV-based time-series phenotypic data offers valuable insight into phenotypic variation, thereby enhancing the application of UAVs in crop breeding.
Comparative Analysis of Acute-Phase Protein Profiles in Cats Undergoing Ovariectomy: Laparoscopic vs. Conventional Surgery in Short Time After Procedure
Authors: Cuervo Belén , Satué Katy , Velasco-Martínez María Gemma , Sopena Joaquín Jesús , Carrillo José María , Damiá Elena , Chicharro Deborah , Peláez Pau , Martins Emma , García-Martínez Juan Diego , Rubio Mónica
Published: November 2024

Acute-phase proteins (APPs) are biomarkers of systemic inflammation, which allow monitoring the response to surgery and post-operative complications. Ovariectomy (OVE) can be a useful model to evaluate surgical trauma and inflammation in feline species. The objective of this study was to evaluate and compare the acute-phase response (APR) after applying two different OVE techniques by measuring serum levels of serum amyloid A (SAA), haptoglobin (Hp), total serum proteins (TSPs), albumin (ALB), and paraoxonase-1 (PON-1) during the first 48 h post-surgery (hospital stay). Forty-two female cats were selected for elective spaying. The animals were randomly distributed into two groups: laparoscopic OVE (L-OVE) and midline OVE (M-OVE). Serum SAA, Hp, TSPs, ALB, and PON-1 were measured before surgery and 1, 6, 12, 24, and 48 h post-surgery. Unlike negative APPs such as PON-1 and ALB, SAA is the most sensitive positive APP for monitoring the inflammatory response in cats undergoing OVE following laparoscopic and conventional surgery. OVE performed in cats via both laparoscopic and midline techniques results in a significative increase in SAA levels, with early recovery, minor variations in serum total protein, and no significant changes in albumin, haptoglobin, or PON-1 over a 48-h period post-procedure. Based on SAA concentrations, the response to surgical trauma does not differ between surgical techniques.
Energy Expenditure and Maintenance Requirements in Non-Pregnant First-Parity Sows
Authors: Samuel Ryan S. , Moehn Soenke , Ball Ronald O.
Published: November 2024

Five sows, non-pregnant after the first parity (body weight: 174 ± 11 kg), were used to determine energy expenditure (EE) measured as heat production (HP). Sows were fed first 1.0, then 2.0, times the recommended maintenance energy requirement (MEm) for one week each. Sows received half their daily ration in 16 half-hourly meals, then the remaining half in a large meal followed by an overnight fast in respiration chambers. Sows fed 1.0 MEm consumed 473 kJ ME/kg0.75 (22.8 MJ/d) and lost weight (−198 g/d) because HP (24.0 MJ/d) was greater than intake. Sows fed 2.0 MEm consumed 925 kJ ME/kg0.75 (44.9 MJ/d) and gained 1292 g/d and HP was 32.3 MJ/d. The respiratory quotient (RQ) of sows fed 2.0 MEm was greater than one, indicating body fat deposition. The HP when sows were eating repeated small meals (33.6 MJ/d) or a single large meal (29.8 MJ/d) was greater (p < 0.05) than the HP in the following 2 h (25.2 MJ/d). Based upon the recalculation of MEm using the present data, 506 kJ ME/kg0.75 is proposed as the MEm for non-pregnant modern sows.
Monitoring Multiple Behaviors in Beef Calves Raised in Cow–Calf Contact Systems Using a Machine Learning Approach
Authors: Kim Seong-Jin , Jin Xue-Cheng , Bharanidharan Rajaraman , Kim Na-Yeon
Published: November 2024

The monitoring of pre-weaned calf behavior is crucial for ensuring health, welfare, and optimal growth. This study aimed to develop and validate a machine learning-based technique for the simultaneous monitoring of multiple behaviors in pre-weaned beef calves within a cow–calf contact (CCC) system using collar-mounted sensors integrating accelerometers and gyroscopes. Three complementary models were developed to classify feeding-related behaviors (natural suckling, feeding, rumination, and others), postural states (lying and standing), and coughing events. Sensor data, including tri-axial acceleration and tri-axial angular velocity, along with video recordings, were collected from 78 beef calves across two farms. The LightGBM algorithm was employed for behavior classification, and model performance was evaluated using a confusion matrix, the area under the receiver operating characteristic curve (AUC-ROC), and Pearson’s correlation coefficient (r). Model 1 achieved a high performance in recognizing natural suckling (accuracy: 99.10%; F1 score: 96.88%; AUC-ROC: 0.999; r: 0.997), rumination (accuracy: 97.36%; F1 score: 95.07%; AUC-ROC: 0.995; r: 0.990), and feeding (accuracy: 95.76%; F1 score: 91.89%; AUC-ROC: 0.990; r: 0.987). Model 2 exhibited an excellent classification of lying (accuracy: 97.98%; F1 score: 98.45%; AUC-ROC: 0.989; r: 0.982) and standing (accuracy: 97.98%; F1 score: 97.11%; AUC-ROC: 0.989; r: 0.983). Model 3 achieved a reasonable performance in recognizing coughing events (accuracy: 88.88%; F1 score: 78.61%; AUC-ROC: 0.942; r: 0.969). This study demonstrates the potential of machine learning and collar-mounted sensors for monitoring multiple behaviors in calves, providing a valuable tool for optimizing production management and early disease detection in the CCC system
First Detection of Lactococcus petauri in Domestic Dogs in Italy
Authors: Sciuto Simona , Esposito Giuseppe , Pastorino Paolo , Shahin Khalid , Varello Katia , Trabunella Eliana , Milanese Giulia , Scala Sonia , Prearo Marino , Acutis Pier Luigi , Salerno Angelo , Zoppi Simona , Colussi Silvia
Published: November 2024

Lactococcus garvieae has been considered for a long time the only causal agent of lactococcosis. In recent years, different papers reported the involvement of other two bacterial species: Lactococcus petauri and Lactococcus formosensis. A different host tropism has been described for these species where L. garvieae and L. petauri are predominant species in fish and humans’ infections, while L. formosensis in bovine. L. garvieae has been reported as rare infectious agent in dog. This paper represents the first isolation of L. petauri in two domesticated dog cases from urine and skin samples, respectively. The recovered L. petauri has been identified using PCR and sequencing based on Internal Transcribe Spacer (ITS) and phylogenetic analysis showed that it belongs to the L. petauri cluster with a 100% of identity with sequences previously reported from fish isolates while there were differences with L. petauri isolated from urinary tract infection from humans. L. petauri in human infection has been considered not necessarily deriving from the ingestion of contaminated food but rather as an opportunistic pathogen colonization intestinal tract. Differences among virulotypes have been reported for humans and dogs, and a comparison was also made between the virulotyping of L. petauri and L. garvieae in dogs. The antimicrobial pattern showed susceptibility for the election treatment molecules. These data contribute to our understanding of the host trophism of this species which was misclassified for long time and provide new data on its virulence factors and antimicrobial resistance.
Effects of Genetic Polymorphism in the IFI27 Gene on Milk Fat Traits and Relevance to Lipid Metabolism in Bovine Mammary Epithelial Cells
Authors: Jiang Xinyi , Zhao Zhihui , Chen Xuanxu , Miao Fengshuai , Li Jing , Yu Haibin , Jiang Ping , Lin Ziwei
Published: November 2024

Milk fat is an important indicator for evaluating milk quality and a symbol of the core competitiveness of the dairy industry. It can be improved through genetic and feed management factors. Interferon alpha-inducible protein 27 (IFI27) was found to be differentially expressed when comparing the transcriptome in high- and low-fat bovine mammary epithelial cells (bMECs) in our previous research. Therefore, this study aimed to investigate whether the IFI27 gene had a regulatory effect on lipid metabolism.We detected six SNPs in the IFI27 gene (UTR-(-127) C>A, UTR-(-105) T>A, UTR-(-87) G>A, I1-763 G>T, E2-77 G>A, E2-127 G>T) in a Chinese Holstein cow population. Association analysis of the polymorphism of IFI27 and milk quality traits showed that the AG and GG genotype of E2-77 G>A, and the GG and TT genotypes of E2-127 G>T were connected to milk fat (p < 0.05). Haplotype frequency analysis showed that H5H5 was associated with lower milk fat content (p < 0.05), while milk from H5H6 animals had a higher fat content (p < 0.05). Subsequently, IFI27 overexpression vectors (PBI-CMV3-IFI27) and interference vectors (Pb7sk-GFP-shRNA) were constructed. Overexpression of the IFI27 gene in bMECs caused a significant increase in triglycerides (TGs) content (p < 0.05) and decreases in cholesterol (CHOL) and nonestesterified fatty acid (NEFA) content (p < 0.05), while interference with IFI27 expression produced opposing changes (p < 0.05). In summary, IFI27 E2-77 G>A and IFI27 E2-127 G>T may be useful as molecular markers in dairy cattle to measure milk fat, and the IFI27 gene may play an important role in milk lipid metabolism.
Molecular Detection and Genotyping of Chlamydia psittaci in Birds in Buenos Aires City, Argentina
Authors: Madariaga María Julia , Caraballo Diego Alfredo , Teijeiro María Luisa , Boeri Eduardo Jorge , Cadario María Estela
Published: November 2024

Chlamydia psittaci is a bacterium that infects several species of birds and mammals. It is the causal agent of avian chlamydiosis and psittacosis in humans and it is globally distributed. Chlamydia psittaci is one of the main zoonotic pathogens transmitted by birds. In Argentina, there has been limited research on the prevalence and genetic variability of C. psittaci. The aim of this study was to detect and genotype C. psittaci using molecular techniques in birds living in Buenos Aires City, Argentina, during the period 2012–2015. A descriptive, observational, retrospective and cross-sectional study was carried out. A total of 983 bird samples submitted for diagnosis of avian chlamydiosis were analyzed. The frequency of C. psittaci was 12.54% and 7.89% in Psittaciformes and Columbiformes, respectively. A 348 bp region of the ompA gene was sequenced in positive samples. Molecular genotyping was performed through a Bayesian phylogenetic analysis. Of the 983 bird samples, 83 were positive for C. psittaci and 44 could be sequenced. The genotypes found were A, B, and E. Despite the high levels of host specificity, we found six psittacids with genotype B and one pigeon with genotype A, reflecting the affiliative interaction between Psittaciformes and Columbiformes. This study represents the first survey reporting the presence of C. psittaci in birds within the largest and most populous city in Argentina.
Efficacy of Copper Ion Treatment on Bacteria and Antibiotic Residues Contained in Bovine Waste Milk
Authors: Ulloa Fernando , Penati Martina , Naegel Constanza , Tejeda Carlos , Hernández-Agudelo Miguel , Steuer Pamela , Salgado Miguel
Published: November 2024

Background/Objectives: Waste milk harbors many bacteria and antibiotic residues. Calves fed with untreated waste milk have a higher incidence of scours and an increased risk of developing antimicrobial-resistant bacteria. This study aimed to evaluate the efficacy of treatment with copper ions on bacteria and antibiotics contained in bovine waste milk. Methods: Waste milk samples were collected from a dairy farm for seven weeks and were subjected to treatment with copper ions. Total bacterial counts, coliforms, Streptococcus, and Staphylococcus were assessed before and after treatment. Additionally, metagenomic analysis was performed to determine microbial diversity. Results: Before treatment, the total bacterial count average was 4.0 × 106 CFU/mL, 1.7 × 104 CFU/mL for coliforms, 2.6 × 106 CFU/mL for Streptococcus, and 5.4 × 102 CFU/mL for Staphylococcus Copper treatment significantly reduced bacterial counts within 15 min. Total bacteria decreased from 4.0 × 106 CFU/mL to 1.1 × 102 CFU/mL after 30 min; meanwhile, other groups were not detected. The most abundant groups were Lactococcus (29.94%), Pseudomonas (28.89%), and Enterobacteriaceae (21.19%). Beta-lactams were detected in five-sevenths samples, and in one sample they were detected before and at 15 min of treatment but not after 30 min. Conclusions: The effect of treatment with copper ions on the different bacterial groups was significantly effective but showed limited effect on the detection of antibiotics.
Quantitative and Qualitative Analysis of Main Parameters and Their Interactions in Thermoacoustic Refrigerators Performance
Authors: Peredo Fuentes Humberto , Escalante Velázquez Carlos Amir
Published: November 2024

Efforts to optimize the design and enhance the efficiency of standing-wave thermoacoustic refrigerators (SWTARs), particularly those with parallel plate stacks, are crucial for achieving rapid and straightforward engineering estimates. This study primarily focused on optimizing the coefficient of performance (COP) by combining linear thermoacoustic theory (LTT) with the design of experiments (DOE) approach. The investigation centered around five key parameters affecting the COP once the working gas had been selected. Then, based on LTT, the COP was estimated numerically over defined intervals of those five parameters. Moreover, through quantitative and qualitative effect analyses, these five parameters and their interactions were determined. Utilizing a transfer function, the study aimed to delineate the best COP value (1.76) over a defined interval of the parameters as well as the contribution of the thermoacoustic main parameters (55.69%) and their interactions (two-way interactions = 33.30%, three-way interactions = 7.36%, and four-way interactions = 3.35%). Furthermore, a comparison between contour and surface responses and several statistical decision approaches applying the full factorial design verified the robustness of the study’s findings. Ultimately, the COP results obtained aligned with the existing literature, underscoring the validity and relevance of the study’s methodologies and conclusions.
A Case Study Exploring the Effects of a Novel Intra-Abdominal Pressure Belt on Fastball and Change-Up Velocity, Command, and Deception Among Collegiate Baseball Pitchers
Authors: Crotin Ryan L. , Conforti Christian
Published: November 2024

Baseball pitchers must reduce batters’ decision-making ability, locating pitches in zones where batters make weak contact. The purpose of this case study was to investigate potential pitching performance improvements when wearing a specialized intra-abdominal pressure (IAP) belt. Thirteen collegiate pitchers were randomly assigned to three bullpens of 40 pitches with visual encouragement from an integrated LED screen and a portable radar. Pitchers wore their typical belt, an IAP belt at regular length, and the IAP belt with a two-inch cinch for separate bullpen conditions. Fastball and change-up velocities, their average differences in velocity, and strike-throwing percentages were indexed and analyzed. A repeated measures ANOVA with an a priori of 0.05 and Tukey’s post hoc analyses evaluated significant differences amongst the case study population across pitch velocity, command, and deception, which was measured as the average velocity difference between fastballs and change-ups. Given the small sample size, subject-specific data were presented and showed the majority of pitchers threw faster, had greater accuracy, and displayed greater velocity ranges between fastballs and change-ups. The subject-specific results in this case study indicated that most pitchers improved performance across velocity, command, and deception metrics with the use of an intra-abdominal pressure belt designed to be worn in competition.
Investigation on the Compressive Behavior of Waste Rock Backfill Materials with Different Specimen Sizes for Roof Control
Authors: Li Meng , Xing Shihao , Huang Peng , Luo Xiaobao , Guo Qiang
Published: November 2024

Waste rock backfilled into a goaf can function as the main load-bearing carrier to support the overlying strata, so the compressive behavior of backfill materials plays a critical role in the effectiveness of strata control. However, in the laboratory, the specimen size also significantly influences on the accurate prediction of compressive deformation in waste rock backfill materials. To assess the influence of the specimen size on compressive behavior in waste rock backfill materials, a WAW-1000D (Changchun Xinte Testing Machine Co., Ltd., Changchun, Jilin Province, China) electric servo-motor testing machine and self-made compressors of different sizes were used to characterize the compressive deformation of waste rock backfill materials with different specimen sizes. The stress–strain relationships and changes in the void ratio of specimens were analyzed, revealing the influence of the specimen size on the compressive behavior. The research found that when the ratio of the inner diameter of compressors to the maximum particle size of specimens is 15:1 and above, the inner diameter of compressors only has a slight influence. Taking a backfill panel in Xinjulong Coal Mine as the engineering context, waste rock with particle sizes in the range of 0~20 mm was backfilled. The measured roof subsidence was 568 mm, matching the measured experimental value. The results provide data to support roof subsidence predictions following waste rock backfill mining.
A Construction Method for the Random Factor-Based G Function
Authors: Feng Yongxin , Su Jiankai , Qian Bo
Published: November 2024

In consideration of the prevailing methodology for constructing G functions, there are certain limitations such as fixed change rules and restricted flexibility when producing frequency-hopping sequences. This paper introduces a novel construction method for the Random Factor-based G function (RFGF). This approach incorporates random factors to dynamically divide the frequency set into equal intervals and randomly selects the frequency hopping frequency within each subset. This effectively reduces the correlation between adjacent frequency-hopping frequencies, enhancing the randomness of the sequence and the system’s anti-interference performance. Furthermore, this method utilizes chaotic sequences to scramble data information, further strengthening the security of the information. The experimental results demonstrate that the frequency-hopping sequence generated by this proposed G function construction method outperforms the sequence generated by the time-varying iterative decomposition in terms of randomness, uniformity, and two-dimensional continuity. Specifically, under the same parameter conditions, the two-dimensional continuity is improved by 36.87%.
A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration
Authors: Agha Kassab Fadi , Rodriguez Rusber , Celik Berk , Locment Fabrice , Sechilariu Manuela
Published: November 2024

This article comprehensively reviews strategies for optimal microgrid planning, focusing on integrating renewable energy sources. The study explores heuristic, mathematical, and hybrid methods for microgrid sizing and optimization-based energy management approaches, addressing the need for detailed energy planning and seamless integration between these stages. Key findings emphasize the importance of optimal sizing to minimize costs and reduce carbon dioxide (CO2) emissions while ensuring system reliability. In a pedagogical manner, this review highlights the integrated methodologies that simultaneously address sizing and energy management and the potential of emerging technologies, such as smart grids and electric vehicles, to enhance energy efficiency and sustainability. This study outlines the importance of accurate load modeling and carefully selecting models for renewable energy sources and energy storage systems, including degradation models, to achieve long-term operational efficiency and sustainability in microgrid design and operation. Future research should focus on developing multi-objective optimization techniques and incorporating cutting-edge technologies for improved microgrid planning and operation.
Optimizing Driver Vigilance Recognition: Examining the Characterization and Cumulative Effect of Physiological Signals Across Manual and Automated Driving and Durations
Authors: Guo Mingyang , Wei Yuning , Zhang Jingyuan , Huang Qingyang , Jin Xiaoping , Ma Jun
Published: November 2024

Identifying changes in driver’s vigilance under combined manual and automated driving conditions, as well as during prolonged driving, is crucial for reducing car crashes. Existing studies have not adequately considered the similarities and differences in physiological signals between different driving modes or the cumulative effects during extended driving periods. To address this gap, our study focuses on enhancing the feature selection method for driver’s vigilance recognition. A long-duration simulated car-following driving experiment was designed and conducted to simultaneously collect EEG, eye movement, EOG, and driving data. Similarities and differences in the physiological signals of vigilance between manual and automated driving are analyzed in terms of correlation and significance. The cumulative effects of physiological signals are investigated using time series analysis. The proposed feature selection method was validated using an LSTM-based driver’s vigilance recognition model. Results showed a recognition accuracy of 86.32% for manual driving, with a fluctuation rate of 1.18% over prolonged periods. For automated driving, the accuracy was 87.12%, with a fluctuation rate of 0.66%. By considering the similarities and differences in physiological signals between manual and automated driving modes and the cumulative effects, our study enhances the applicability and stability of the driver’s vigilance recognition model across different driving conditions. The validation results demonstrate that the proposed method improves the applicability and stability of the driver’s vigilance recognition model across different driving modes during extended driving periods.
Improving Highly Automated Traffic Management Models Using Alternative Graph Structures Simultaneously
Authors: Pauer Gábor , Török Árpád
Published: November 2024

This research focuses on improving the modelling of highly automated centralized traffic management. Authors use a binary integer modelling for traffic flow optimization. One of the main results of the research is the integration of alternative graph structures simultaneously in the investigated traffic optimization model. This allows to take into account different categories of vehicles, especially large vehicles, and specific traffic directions. The study highlights the need for seamless interoperability between graph structures and demonstrates its feasibility through the investigation of advanced safety indicators. In addition, methods are developed and presented that will allow the future integration of non-automated traffic elements and conventional traffic engineering solutions. During our research, we reviewed the automated traffic management models, focusing on the advantages of both continuous and discrete models. Continuous models provide realism but are computationally intensive, while discrete models are simpler but less realistic. Considering this, our paper proposes solutions that offer a trade-off between these approaches, allowing a balance between computational complexity, accuracy, and realism in vehicle modelling.
Experimental and Numerical Simulations on the Mechanical Characteristics of Soil–Rock Mixture in Uniaxial Compression
Authors: Zhang Zhenping , Fu Xiaodong , Sheng Qian , Wang Shuo , Fang Yuwei
Published: November 2024

Soil–rock mixture is a common geo-material found in natural deposit slopes and various constructions, such as tunnels, hydropower stations, and subgrades. The complex mechanical characteristics of soil–rock mixture arise from its multi-phase compositions and cooperative interactions. This paper investigated the mechanical properties of soil–rock mixture, focusing on the influence of rock content, and soil–rock interface strength was discussed. Specimens with varying rock contents were subjected to uniaxial compression tests. The results indicated that rock content, as a key structural parameter, significantly controls the crack propagation trends. As rock content increases, the initial structure of the soil matrix is damaged, leading to the formation of a weak-strength soil–rock interface. The failure mode transitions from longitudinal cracking to multiple shear fractures. To analyze the strength of the soil–rock interface from a mesoscopic perspective, simulations of soil–rock mixture specimens with irregular rock blocks were conducted using the particle discrete element method (PDEM). At the meso-scale, the specimen with 30% rock content exhibited a complex particle displacement distribution, with differences in the direction and magnitude of displacement between soil and rock particles being critical to the failure modes of the specimen. As the soil–rock interface strength increased from 0.1 to 0.9, the distribution of force chains within the specimen shifted from a centralized to a more uniform distribution, and the thickness of force chains became increasingly uniform. The strength responses of the soil–rock mixture under uniaxial compression condition were discussed, revealing that the uniaxial compression strength (UCS) of soil–rock mixture decreases exponentially with increasing rock content. An estimation formula was developed to characterize the UCS of soil–rock mixture in relation to rock content and interface strength. The findings from both the experiments and simulations can provide valuable insights for evaluating the stability of deposit slopes and other constructions involving soil–rock mixture.
Exploring Demand: Challenges and Opportunities for Free-From and Organic Foods in Portuguese Market
Authors: Lemos Teresa , Vasconcelos Marta , Sousa Sérgio , Pinho Simão , Gomes Ana M. , Pinto Elisabete
Published: November 2024

The rising prevalence of food intolerances and increased health and environmental consciousness has driven the demand for free-from (FF) and organic products. This study aims to analyze consumer needs, motivations, and challenges related to these products in Portugal through an online survey with 2268 eligible responses, with a median age of the participants of 41 years. The sample was predominantly female (76.9%), with male participants comprising 23.1% of the sample. The results show that 97.4% of the respondents were aware of FF products, with 60.0% being regular consumers, particularly of lactose-free milk and gluten-free bread and biscuits. Significant market gaps were identified in the variety of FF bread (62.8%), pastries (49.0%), and cookies (38.4%). The consumers identified high prices (84.9%) and excessive sugar/fat content (52.1%) as the main drawbacks of FF products currently on the market. The women showed greater knowledge and purchase levels compared to the men. The trust in organic certification was low (21.4%), with skepticism higher among the lower-income and male participants. Despite this, 78.1% believed in the health benefits of organic products, and 72.2% agreed that increased demand could lower prices. Overall, this study highlights the need for greater product variety, improved transparency, and consumer education to enhance market trust and accessibility.
Bioaccessibility and Stability Studies on Encapsulated Phenolics and Carotenoids from Olive and Tomato Pomace: Development of a Functional Fruit Beverage
Authors: Katsouli Maria , Thanou Ioanna V. , Raftopoulou Evgenia , Ntzimani Athina , Taoukis Petros , Giannakourou Maria C.
Published: November 2024

This study pertains the encapsulation of bioactive compounds, specifically phenolic compounds and lycopene, extracted from olive and tomato by-products via oil-in-water (O/W) nanoemulsions and their potential application in functional beverages. The effect of various edible oils (olive pomace oil (OPO), sunflower oil (SFO), corn oil (CO), fish oil (FO), and canola oil (CLA)) in the lipid phase and antioxidants (ascorbic acid and phenolic extracts) in the aqueous phase on the physicochemical properties of oil-in-water (O/W) nanoemulsions enriched with lycopene was evaluated, along with the bioaccessibility of the encapsulated bioactive compounds using the static INFOGEST in vitro simulation protocol for gastrointestinal food digestion. All examined edible oils led to nanoemulsions with uniform droplet sizes (droplet size < 300 nm, droplet distribution < 0.3) and high stability during storage at 4 °C, with FO being the smallest, at 259.3 ± 9.1 nm, and OPO the largest, at 286.6 ± 10.0 nm. Ascorbic acid increased the droplet size by 5–8%, improved droplet distribution, and led to a lower deterioration rate (−0.014 d−1) when compared to the “control” counterparts (−0.037 d−1). Lycopene bioaccessibility was significantly affected by the lipid phase, with OPO exhibiting the highest percentage (53.8 ± 2.6%) and FO the lowest (40.1 ± 2.1%). The OPO nanoemulsion was selected for the development of a functional beverage, showing excellent long-term stability. The phenolic compound concentration remained consistent during storage, and the lycopene degradation rate was minimal, at −0.0088 d−1, resulting in an estimated shelf life of 165 days at 4 °C, based on a 50% reduction in lycopene content. Similarly, phenolic compounds demonstrated high bioaccessibility, without a significant dependence on the lipid phase, and stability during shelf life, enhancing the beverage’s overall antioxidant profile. These results indicate that O/W nanoemulsions are effective delivery systems for functional beverages, offering improved stability and bioaccessibility of lycopene.