bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular role of non-exonic variants in CALPAIN 10 gene in polycystic ovarian syndrome in Saudi women
Authors: Alageel Arwa A. , Alshammary Amal F. , Ali Khan Imran
Published: December 2023

Introduction

Non-diabetic women with polycystic ovarian syndrome (PCOS) often have abnormal insulin regulation. Calpain 10 (CALP10) is a biomarker of type 2 diabetes mellitus, with some of its single-nucleotide polymorphisms (SNPs) influencing PCOS development.

Methods

In this case-control study on 90 women each with and without PCOS, we explored the molecular role of five CALP10 SNPs using biochemical parameters and Sanger sequencing analyses.

Results

Different genetic models, genotypes, and allele frequencies were significantly associated with UCSNP-19 (rs3842570; p=0.01), UCSNP-44 (rs2975760; p=0.009), UCSNP-56 (rs2975762; p<0.0001), and UCSNP-63 (rs5030952; p=0.0003) in women with PCOS. The multiple logistic regression model showed a strong association of CALP10 SNPs with fasting blood glucose (p<0.001). ANOVA showed significant associations with various biochemical parameters such as FSH (p=0.0001) in UCSNP-19 (rs3842570), FI (p=0.002), TG (p=0.01) in UCSNP-56 (rs2975762) and FBG (p=0.001), FI (p=0.004), FSH (p=0.02) & LDLc (p=0.04) in UCSNP-63 (rs5030952) SNPs. Haplotype analysis also revealed significant associations between different combinations of alleles in the studied 5 SNPs in women with PCOS (p<0.05). Generalized multifactor dimensionality reduction analysis showed the best gene–gene interactions among the five SNPs in CALP10I (p<0.05). However, dendrogram and graphical depletion models found no strong association in women with PCOS.

Conclusion

In conclusion, this study confirms rs3842570, rs2975760, rs2975767, and rs5030952 SNPs in CALP10 gene is associated in diagnosed PCOS women in the Saudi Arabia.
Effect of regional block technique on postoperative high-grade complications according to Clavien-Dindo classification in elderly patients with thoracic and abdominal cancer: a retrospective propensity score matching analysis
Authors: Ding Weisi , Zhang Yunpeng , Liu Huixin , Zhou Tianxin , Zhao Wanlu , Feng Yi , An Haiyan
Published: December 2023

Background

Postoperative complications have an influence on postoperative rehabilitation, length of hospital stay and hospitalization expenses in elderly patients, especially those with higher Clavien-Dindo (C-D) classification. Patients with cancers often experience more serious postoperative complications after surgery. Different anesthesia methods can affect the postoperative outcomes of cancer patients. Regional block techniques have been recommended in guidelines for enhanced recovery after surgery. However, the relationship between regional blocks and high-grade postoperative complications remains unclear, thus, the study explored the relationship between regional block techniques and high-grade postoperative complications graded by C-D classification in elderly patients with thoracic and abdominal cancer.

Method

Retrospective enrollment of eligible elderly patients admitted to Peking University People’s Hospital between January 2018 and March 2022 was conducted. Propensity score matching (PSM) and univariate and multivariate regression analyses were used to analyze the potential benefits of regional blocks for elderly patients in real world practice.

Results

A total of 2769 patients were enrolled in this study, including 568 who underwent colorectal resection, 2201 who underwent video-assisted thoracoscopic pneumonectomy. Among them, 2033 patients received regional block, while 736 patients did not. Statistical analysis indicated that regional blocks could reduce the incidence of postoperative complications of C-D classification Grade II or higher, with an Odds ratio (OR) of 0.742, 95% Confidence interval (CI) (0.552 to 0.996) (P = 0.047).

Conclusion

Regional block is associated with a reduction in the occurrence of postoperative complications graded by C-D classification in elderly patients with thoracic and abdominal cancer. The application of regional blocks can lower the risk of high-risk complications and mortality.
Effect of asking questions and providing knowledge on attitudes toward organic foods among Japanese consumers
Authors: Iwatani Shuma , Honda Hidehito , Otaki Yurina , Ueda Kazuhiro
Published: December 2023

Some people overestimate the benefits of certain kinds of foods, such as organic foods, while others underestimate it. Previous studies have found that reducing people’s self-assessed knowledge successfully moderated these extreme attitudes. In this study, we investigated interventions to reduce people’s self-assessed knowledge and to moderate attitude extremity. We examined extreme attitudes toward organic foods and investigated the effects of implementing two intervention methods to moderate their attitude: (1) providing knowledge on organic food after asking them some questions and (2) simply providing them with knowledge. We conducted a two-factor mixed-design experiment with 653 college-educated Japanese women. In the first condition, before knowledge provision, participants were asked to answer questions about organic foods and were then informed of the correct answer and whether their answer was correct (Q&A Intervention). This step was based on an intervention conducted in a previous study to reduce their self-assessed factual knowledge. In the second condition, participants were simply provided with knowledge without being asked to answer any questions (Simple Intervention). The results showed that both intervention methods, on average, decreased the participants’ self-assessed knowledge and attitude extremity. Therefore, simply providing knowledge may be effective in reducing their self-assessed factual knowledge and moderating their extreme attitudes toward organic foods.
Evaluating the sensitivity of droplet digital PCR for the quantification of SARS-CoV-2 in wastewater
Authors: de la Cruz Barron Magali , Kneis David , Geissler Michael , Dumke Roger , Dalpke Alexander , Berendonk Thomas U.
Published: December 2023

Wastewater surveillance for SARS-CoV-2 has been demonstrated to be a valuable tool in monitoring community-level virus circulation and assessing new outbreaks. It may become a useful tool in the early detection and response to future pandemics, enabling public health authorities to implement timely interventions and mitigate the spread of infectious diseases with the fecal excretion of their agents. It also offers a chance for cost-effective surveillance. Reverse transcription-quantitative polymerase chain reaction (RTqPCR) is the most commonly used method for viral RNA detection in wastewater due to its sensitivity, reliability, and widespread availability. However, recent studies have indicated that reverse transcription droplet digital PCR (RTddPCR) has the potential to offer improved sensitivity and accuracy for quantifying SARS-CoV-2 RNA in wastewater samples. In this study, we compared the performance of RTqPCR and RTddPCR approaches for SARS-CoV-2 detection and quantification on wastewater samples collected during the third epidemic wave in Saxony, Germany, characterized by low-incidence infection periods. The determined limits of detection (LOD) and quantification (LOQ) were within the same order of magnitude, and no significant differences were observed between the PCR approaches with respect to the number of positive or quantifiable samples. Our results indicate that both RTqPCR and RTddPCR are highly sensitive methods for detecting SARS-CoV-2. Consequently, the actual gain in sensitivity associated with ddPCR lags behind theoretical expectations. Hence, the choice between the two PCR methods in further environmental surveillance programs is rather a matter of available resources and throughput requirements.
National cross-sectional survey on psychological impact on French nursing homes of the first lockdown during the COVID-19 pandemic as observed by psychologists, psychomotor, and occupational therapists
Authors: Vaillant-Ciszewicz Anne-Julie , Couturier Bérengère , Segaux Lauriane , Canouï-Poitrine Florence , Guérin Olivier , Bonin-Guillaume Sylvie
Published: December 2023

Objectives

The main objective was to explore the psychological impact of the French lockdown during the first wave of the COVID-19 pandemic on nursing home residents, their relatives, and healthcare teams, as observed by mental health professionals.

Design

A national online cross-sectional survey was conducted from May 11 to June 9, 2020.

Setting and participants

Respondents were psychologists, psychomotor therapists, and occupational therapists (mental health professionals).

Results

A total of 1,062 participants responded to the survey, encompassing 59.8% psychologists, 29.2% occupational therapists, and 11% psychomotor therapists. All mental health professionals felt fear (76.1%), fatigue and exhaustion (84.5%), and inability to manage the emotional burden (78.4%). In nursing homes with COVID-19 cases, residents felt significantly sadder (83.2%), more anxious (65.0%), experienced more anorexia (53.6%), resurgence of traumatic war memories (40.2%), and were more often disoriented (75.7%). The suffering of relatives did not vary between nursing homes with and without COVID-19 cases. The nursing staff was heavily impacted emotionally and was in need of psychological support particularly when working in nursing homes in a low COVID-19 spread zone with COVID-19 cases (41.8 vs. 34.6%).

Conclusion and implications

Primary prevention must be implemented to limit the psychological consequences in the event of a new crisis and to prevent the risk of psychological decompensation of residents and teams in nursing homes.
Effectiveness of Four Synthetic Fungicides in the Control of Post-Harvest Gray Mold of Strawberry and Analyses of Residues on Fruit
Authors: Vischetti Costantino , Feliziani Erica , Landi Lucia , De Bernardi Arianna , Marini Enrica , Romanazzi Gianfranco
Published: December 2023

Fungicides are usually applied on strawberries to manage gray mold, induced by the fungal pathogen Botrytis cinerea. In this study, four reduced-risk fungicides (formulations of pyrimethanil, PYR, 175 mL/hL; boscalid, BOS, 80 g/hL; combination fludioxonil, FLU, +cyprodinil, CYP, 110 g/hL) were applied before harvest for the management of post-harvest diseases of strawberries. The resulting fungicide residues on the strawberry fruit were also quantified. Strawberry fruits were harvested at 0, 4, 8, and 12 days following treatment (dft) and kept at 20 ± 1 °C for 4 days or cold-stored for 7 days at 0.5 ± 1 °C, followed by a 4-day shelf life at 20 ± 1 °C. All fungicides significantly reduced gray mold, according to the McKinney Index. At 0 dft and 4 days of shelf life, the FLU + CYP completely prevented post-harvest strawberry gray mold, while PYR and BOS reduced the disease by 88% and 42%, respectively, in comparison to the untreated control. For the duration of experiment, fungicide residues were always below the maximum residue levels, and FLU was the most degraded, thanks to the enzymatic pool of the strawberries. Monitoring fungicide residues in strawberries is essential to provide the consumer information on the safety of this widely consumed fruit. The present study points out the safety of strawberry fruits for consumers, even if the treatment strategy implies the use of fungicide mixtures before the consumption, with fungicide levels always being below the MRL.
Development and Optimization of a Chamber System Applied to Maize Net Ecosystem Carbon Exchange Measurements
Authors: Pan Chenxin , Hu Junguo , Cai Hanghang , Jiang Junjie , Gu Kechen , Zhu Chao , Mao Guodong
Published: December 2023

Net ecosystem carbon exchange (NEE) in agricultural land represents a significant source of global greenhouse gas (GHG) emissions. While there are various tools for measuring NEE in agricultural fields, the chamber method remains the sole tool at the plot scale. In this research, we evaluated the NEE of maize plants at the nodulation stage using the flow-through chamber method. Many existing flow-through chamber systems directly introduce gases, leading to collisions with plants and subsequent turbulence inside the chamber. Turbulence can extend the time required to achieve a steady state. We modified the traditional flow-through chamber design to minimize turbulence in the measurement zone. Our modifications were validated by modeling the chamber and maize plants and by conducting fluid simulation experiments. In the analysis of our comparative field measurements between the two chamber designs, the use of the improved system notably shortened the time required to reach the steady state, increased the measurement frequency, and reduced the influence of changing environmental factors on the readings. Enhancing the measurement frequency is crucial for ensuring long-term accuracy. By reducing turbulence in the chamber, we anticipate improvements in the precision of NEE measurements in agricultural research, which could significantly contribute to an accurate assessment of the global carbon cycle.
A Cucumber Leaf Disease Severity Grading Method in Natural Environment Based on the Fusion of TRNet and U-Net
Authors: Yao Hui , Wang Chunshan , Zhang Lijie , Li Jiuxi , Liu Bo , Liang Fangfang
Published: December 2023

Disease severity grading is the primary decision-making basis for the amount of pesticide usage in vegetable disease prevention and control. Based on deep learning, this paper proposed an integrated framework, which automatically segments the target leaf and disease spots in cucumber images using different semantic segmentation networks and then calculates the area of disease spots and the target leaf for disease severity grading. Two independent datasets of leaves and lesions were constructed, which served as the training set for the first-stage diseased leaf segmentation and the second-stage lesion segmentation models. The leaf dataset contains 1140 images, and the lesion data set contains 405 images. The proposed TRNet was composed of a convolutional network and a Transformer network and achieved an accuracy of 93.94% by fusing local features and global features for leaf segmentation. In the second stage, U-Net (Resnet50 as the feature network) was used for lesion segmentation, and a Dice coefficient of 68.14% was obtained. After integrating TRNet and U-Net, a Dice coefficient of 68.83% was obtained. Overall, the two-stage segmentation network achieved an average accuracy of 94.49% and 94.43% in the severity grading of cucumber downy mildew and cucumber anthracnose, respectively. Compared with DUNet and BLSNet, the average accuracy of TUNet in cucumber downy mildew and cucumber anthracnose severity classification increased by 4.71% and 8.08%, respectively. The proposed model showed a strong capability in segmenting cucumber leaves and disease spots at the pixel level, providing a feasible method for evaluating the severity of cucumber downy mildew and anthracnose.
Effect of Foliar Fertilization on the Physiological Parameters, Yield and Quality Indices of the Winter Wheat
Authors: Bărdaş Marius , Rusu Teodor , Popa Alin , Russu Florin , Șimon Alina , Chețan Felicia , Racz Ionuț , Popescu Sorina , Topan Călin
Published: December 2023

The main purpose of the paper is to highlight the impact of foliar fertilization during the various growth stages of winter wheat and its role in achieving high-quality and superior production. Foliar fertilizers play a crucial role in calibrating and forming active growth intervals correlated with productivity factors. The research was conducted over a two-year period using the Andrada winter wheat variety. It involved the application of four different foliar fertilizers: basic mineral fertilization, FoliMAX Orange (two treatments and three treatments), FoliMAX CerealsMIX (two treatments and three treatments), and Microfert U (three treatments). Depending on the treatment, two or three applications of foliar with foliar fertilizers were carried out at various stages of winter wheat development, including pre-flowering and grain formation. The research method used to record physiological parameters was non-destructive (the leaves were not detached from the plant) and was based on the use of the CIRAS-3 foliar gas analyzer, which simultaneously determines several physiological and environmental indicators. As an indicator read by the device, photosynthesis was chosen for leaf temperature and leaf transpiration, correlated with production and quality indices. By applying the foliar fertilizer treatments to the wheat culture, we managed to increase production and improve the quality. After using different foliar fertilizers, the assimilation and physiological parameters had higher values of over 30 μmolm−2·s−1. Foliar fertilization applied to the winter wheat variety resulted in an average production increase between 450 and 765 kg·ha−1 and quality indices with a protein percentage between 11.5 and 12.6%, gluten content between 21.5 to 24.0% and the Zeleny index between 29.0 and 39.0%, and the mass of one thousand grains was between 48.0 and 50.5 g.
Corona- and Paramyxoviruses in Bats from Brazil: A Matter of Concern?
Authors: Weber Matheus Nunes , da Silva Mariana Soares
Published: December 2023

Chiroptera are one of the most diverse mammal orders. They are considered reservoirs of main human pathogens, where coronaviruses (CoVs) and paramyxoviruses (PMVs) may be highlighted. Moreover, the growing number of publications on CoVs and PMVs in wildlife reinforces the scientific community’s interest in eco-vigilance, especially because of the emergence of important human pathogens such as the SARS-CoV-2 and Nipha viruses. Considering that Brazil presents continental dimensions, is biologically rich containing one of the most diverse continental biotas and presents a rich biodiversity of animals classified in the order Chiroptera, the mapping of CoV and PMV genetics related to human pathogens is important and the aim of the present work. CoVs can be classified into four genera: Alphacoronavirus, Betacoronavirus, Deltacoronavirus and Gammacoronavirus. Delta- and gammacoronaviruses infect mainly birds, while alpha- and betacoronaviruses contain important animal and human pathogens. Almost 60% of alpha- and betacoronaviruses are related to bats, which are considered natural hosts of these viral genera members. The studies on CoV presence in bats from Brazil have mainly assayed phyllostomid, molossid and vespertilionid bats in the South, Southeast and North territories. Despite Brazil not hosting rhinophilid or pteropodid bats, which are natural reservoirs of SARS-related CoVs and henipaviruses, respectively, CoVs and PMVs reported in Brazilian bats are genetically closely related to some human pathogens. Most works performed with Brazilian bats reported alpha-CoVs that were closely related to other bat-CoVs, despite a few reports of beta-CoVs grouped in the Merbecovirus and Embecovirus subgenera. The family Paramyxoviridae includes four subfamilies (Avulavirinae, Metaparamyxovirinae, Orthoparamyxovirinae and Rubulavirinae), and bats are significant drivers of PMV cross-species viral transmission. Additionally, the studies that have evaluated PMV presence in Brazilian bats have mainly found sequences classified in the Jeilongvirus and Morbillivirus genera that belong to the Orthoparamyxovirinae subfamily. Despite the increasing amount of research on Brazilian bats, studies analyzing these samples are still scarce. When surveying the representativeness of the CoVs and PMVs found and the available genomic sequences, it can be perceived that there may be gaps in the knowledge. The continuous monitoring of viral sequences that are closely related to human pathogens may be helpful in mapping and predicting future hotspots in the emergence of zoonotic agents.
Self-Administration of a Boar Priming Pheromone Stimulates Puberty in Gilts without Boar Exposure
Authors: McGlone John J. , Duke Lauren , Sanchez Maya , Garcia Arlene
Published: December 2023

Labor is in short supply in animal agriculture. One time-consuming task is estrus detection in gilts. Stimulation with a live boar causes the onset of puberty in young gilts. Typically, a live boar is used to stimulate and identify estrus in the gilts by exposing the gilts to him. Recently, a boar pheromone (BB) was developed to replace the use of a live boar for sows. Additionally, a novel automatic sprayer used as environmental enrichment (EE) by gilts for the self-administration of BB has been developed by this laboratory. A commercial study was conducted to determine whether the use of a live boar could be replaced with a simple EE sprayer, allowing gilts to self-administer BB. Our objective was to determine whether the number and percentage of gilts in estrus obtained using live boars was comparable to self-administration using an EE sprayer containing BB. A total of 242 gilts were randomly assigned to either a live boar (BOAR) or BB self-administration using the environmental enrichment (EE) sprayer. Gilts began simultaneous exposure to either the BOAR or the BB when they were about 4–5 months of age and this continued until they were found in estrus or were injured, died, or never cycled about 2 months later. A total of 83.3% of gilts with exposure to BOAR were identified in estrus and bred, while exposure to BB resulted in 92.9% of gilts reaching puberty and being bred (p < 0.05). The days to reach estrus were 11 days longer for gilts exposed to BB than BOAR. Eight percent more gilts were injured by the BOAR than by using BB (and no boar). The use of BB as a priming pheromone could prevent gilt injuries, save labor, and reduce costs for pig farmers while not inhibiting reproductive output.
Evaluation of Non-Contact Device to Measure Body Temperature in Sheep
Authors: Ibáñez Carla , Moreno-Manrique María , Villagrá Aránzazu , Bueso-Ródenas Joel , Mínguez Carlos
Published: December 2023

Non-contact devices have been used in the measurement of body temperature in livestock production as a tool for testing disease in different species. However, there are few studies about the variation and correlations in body temperature between rectal temperature (RT) and non-contact devices such as non-contact infrared thermometers (NCIT) and thermal imaging/infrared thermography (IRT). The objective of this work was to evaluate the accuracy of non-contact devices to measure the body temperature in sheep, considering six body regions and the possibility of implementing these systems in herd management. The experiment was carried out at the experimental farm of the Catholic University of Valencia, located in the municipality of Massanassa in July of 2021, with 72 dry manchega ewes, and we compared the rectal temperature with two types of non-contact infrared devices for the assessment of body temperature in healthy sheep. Except for the temperature taken by NCIT at the muzzle, the correlation between RT vs. NCIT or IRT showed a low significance or was difficult to use for practical flock management purposes. In addition, the variability between devices was high, which implies that measurements should be interpreted with caution in warm climates and open pens, such as most sheep farms in the Spanish Mediterranean area. The use of infrared cameras devices to assess body temperature may have a promising future, but in order to be widely applied as a routine management method on farms, the system needs to become cheaper, simpler in terms of measurements and quicker in terms of analyzing results.
Effects of Protease in Soybean Meal-Reduced Diets on Growth Performance, Nutrient Digestibility, and Intestinal Health of Weaned Piglets
Authors: Zhang Junhong , Zhou Chunxiang , Zou Honglei , Li Bin , Yu Bing , He Jun , Zheng Ping , Mao Xiangbing , Yan Hui , Luo Junqiu , Luo Yuheng , Chen Jinyong , Yu Jie
Published: December 2023

This experiment was conducted in weaned piglets to determine the effects of exogenous protease to low soybean meal (SBM) diets on growth performance, diarrhea rate, nutrient digestibility, and intestinal morphology. Seventy-two Duroc × Landrace × Yorkshire weaned barrows (21-day-old, 5.88 ± 0.95 kg) were randomly divided into four treatments with six replicates in each following a 2 × 2 factorial arrangement of SBM levels (0 to 14 d, 9%, 7.5%; 15 to 42 d, 20%, 18.5%) and protease (0 or 150 mg/kg) for a 42-day trial. Fecal samples were collected on days 11 to 14 and 38 to 42 of the experiment, and serum, intestinal tissue, and chyme samples were taken at the end of the experiments. Adding protease in low SBM diets had a significant increase in ADG (p < 0.05) and a decrease in F/G (p < 0.05). Protease significantly reduced the diarrhea rate (p < 0.05). Low SBM level decreased the apparent total tract digestibility (ATTD) of crude protein (CP) and ash (p < 0.05) but increased the ATTD of dry matter (DM), ash, organic matter (OM), and CP after the addition of protease (p < 0.05). The apparent ileal digestibility (AID) of aspartic acid (Asp), threonine (Thr), serine (Ser), alanine (Ala), lysine (Lys), and total amino acids (AAs) were significantly increased by protease supplementation (p < 0.05). Both the SBM-reduced and protease-added diets lead to lower albumin (ALB), albumin/globulin (A/G), and urea nitrogen (UREA) (p < 0.05), but greater globulin (GLOB) with low SBM diets (p < 0.05). The SBM-reduced and protease-added diets decreased the duodenum pH, respectively (p < 0.05). The protease increased the villus:crypt (V:C) in the duodenum and ileum, and ileal villus length (p < 0.05). In conclusion, the dietary supplementation of 150 mg/kg protease improved the intestinal health and performance of the weaned piglets and reversed the negative effect of a 1.5% SBM reduction in nutrient utilization, intestinal pH, and intestinal morphological parameters of weaned piglets.
Seasonal Variations on Testicular Morphology, Boar Taint, and Meat Quality Traits in Traditional Outdoor Pig Farming
Authors: Botelho-Fontela Sofia , Ferreira Sílvia , Paixão Gustavo , Pereira-Pinto Ricardo , Vaz-Velho Manuela , Pires Maria dos Anjos , Payan-Carreira Rita , Patarata Luís , Lorenzo José M. , Silva José A. , Esteves Alexandra
Published: December 2023

Traditional outdoor pig farming is renowned for its emphasis on animal welfare and the production of highly valued, quality meat. While seasonality is known to impact certain animals, particularly those raised outdoors, there is a lack of research on Bísaro boars, a native Portuguese breed. This research study was conducted on a total of 20 male entire Bísaro pigs, reared in outdoor pens from 4 to 13 months old, and subsequently slaughtered. The animals were divided into two groups: one slaughtered in winter (Wi, n = 9), and the other in summer (Su, n = 11). The objective was to evaluate testicular morphometry, boar taint compounds, and meat quality traits, including sensory analysis and fatty acid profile. Testicles from the Su group exhibited reduced volume, indicating diminished functionality during that season. While no significant differences were observed in the boar taint compound analysis, panelists could discern a more intense aroma and flavor of boar taint in the Su meat. Other meat quality traits showed no significant variations, but the fatty acid profile displayed higher values in the Wi group. This study reveals that Bísaro boars experience reproductive seasonality, leading to variations in boar taint compounds across the seasons. This information is crucial for farm planning.
Prevalence and Antimicrobial Resistance of Escherichia coli O157:H7 and Salmonella, and the Prevalence of Staphylococcus aureus in Dairy Cattle and Camels under Pastoral Production System
Authors: Hunduma Diriba , Amenu Kebede , Desta Hiwot , Grace Delia , Agga Getahun E. , Kerro Dego Oudessa
Published: December 2023

Escherichia coli O157:H7, Salmonella and Staphylococcus aureus are common foodborne pathogens. We determined the prevalence of E. coli O157:H7 and Salmonella in feces and milk and the prevalence of S. aureus in milk from dairy cattle and camels in the Borana pastoral community in the Southern Oromia Region of Ethiopia. Paired individual cow composite (pooled from all quarters in equal proportions) milk and fecal samples were collected from cows (n = 154) and camels (n = 158). Samples were cultured on bacterial isolation and identification media. E. coli O157:H7 and Salmonella isolates were further tested for susceptibility against nine antimicrobial drugs. Different risk factors associated with hygienic milking practices were recorded and analyzed for their influence on the prevalence of these bacteria in milk and feces. The prevalence of E. coli O157:H7 and Salmonella in feces were 3.9% and 8.4%, respectively, in cows, and 0.6% and 2.5%, respectively, in camels. E. coli O157:H7 and Salmonella were detected in the composite milk samples of 2.6% and 3.9% of the cows, respectively, and 0% and 1.3% of the camels, respectively. S. aureus was detected in composite milk samples of 33.4% of the cows and 41.7% of the camels. All E. coli O157:H7 (n = 11) and Salmonella (n = 25) isolates from both animal species and sample types were resistant to at least one antimicrobial drug. Multidrug resistance was observed in 70% (7/10) of the E. coli O157:H7 fecal and milk isolates from cows and 33.3% (2/6) of the Salmonella fecal and milk isolates from camels. The prevalence of these bacteria in feces and milk was not affected by risk factors associated with milking practices. Given the very close contact between herders and their animals and the limited availability of water for hand washing and udder cleaning, these bacteria are most likely present in all niches in the community. Improving community awareness of the need to boil milk before consumption is a realistic public health approach to reducing the risk of these bacteria.
An Investigation of Applying Large Language Models to Spoken Language Learning
Authors: Gao Yingming , Nuchged Baorian , Li Ya , Peng Linkai
Published: December 2023

People have long desired intelligent conversational systems that can provide assistance in practical scenarios. The latest advancements in large language models (LLMs) are making significant strides toward turning this aspiration into a tangible reality. LLMs are believed to hold the most potential and value in education, especially in the creation of AI-driven virtual teachers that facilitate language learning. This study focuses on assessing the effectiveness of LLMs within the educational domain, specifically in the areas of spoken language learning, which encompass phonetics, phonology, and second language acquisition. To this end, we first introduced a new multiple-choice question dataset to evaluate the effectiveness of LLMs in the aforementioned scenarios, including the understanding and application of spoken language knowledge. Moreover, we investigated the influence of various prompting techniques such as zero- and few-shot methods (prepending the question with question-answer exemplars), chain-of-thought (CoT) prompting, in-domain exemplars, and external tools. We conducted a comprehensive evaluation of popular LLMs (20 distinct models) using these methods. The experimental results showed that the task of extracting conceptual knowledge posed few challenges for these LLMs, whereas the task of application questions was relatively difficult. In addition, some widely proven effective prompting methods combined with domain-specific examples resulted in significant performance improvements compared to the zero-shot baselines. Additionally, some other preliminary experiments also demonstrated the strengths and weaknesses of different LLMs. The findings of this study can shed light on the application of LLMs to spoken language learning.
A Comparative Study of Real and Virtual Environment via Psychological and Physiological Responses
Authors: Llinares Carmen , Higuera-Trujillo Juan Luis , Montañana Antoni
Published: December 2023

Currently, immersive virtual environments (IVE) are widely used in fields such as architecture and environmental psychology. These simulated environments allow for a detailed evaluation of how different designs impact users’ perception and interaction with the built environment, under controlled conditions and without incurring high costs. The validity of these IVEs is related to their capacity to evoke a participant’s response similar to that of the space they are simulating. This paper presents a validation study of a virtual classroom with two phases: the analysis of the sense of presence in the generated IVE and the comparison of the psychological and neurophysiological response of subjects in the two environments (physical vs. IVE). The psychological response captures cognitive processes via the performance of attention and memory tasks. The physiological response records the subject’s activity monitored via electroencephalogram, electrocardiogram, and electrodermal activity. The results showed that the psychological and physiological responses in both environments (physical vs. IVE) were similar. This may be of interest to architecture researchers and professionals as they validate IVE systems as tools to study the effects of the built environment on users’ cognitive responses.
Thermal Management of Diesel Engine Aftertreatment System Based on Ultra-Low Nitrogen Oxides Emission
Authors: Sun Ke , Zhang Gecheng , Wang Zhengyong , Li Da , Li Guoxiang , Bai Shuzhan , Lin Chunjin , Cheng Hao
Published: December 2023

To achieve diesel engine ultra-low nitrogen oxide emission, light-off selective catalyst reduction (LO-SCR) has been suggested for better performance with lower exhaust temperature. An electric heater upstream of the exhaust aftertreatment system was applied to significantly decrease the NOx emission at a low exhaust temperature. With a 7.2 kW electric heater coupled with LO-SCR, the NOx emission during 200~500 s of the world harmonized transient cycle (WHTC) decreased from 282.6 ppm to 61.5 ppm, which is a decrease of 45%. Application of an upstream diesel oxidation catalyst (DOC) decreased the NOx emission by 63% at the same interval at the cost of worse cold-start performance. The urea input was also adjusted to avoid NOx emission during the latter part of the WHTC.
Integrating Lean and Automation for Enhanced Serology Diagnosis Efficiency in Tertiary Healthcare Microbiology Laboratories
Authors: Acero Raquel , Torralba Marta , Valverde Emilio-David , Roc Lourdes , Rezusta Antonio
Published: December 2023

Healthcare services and institutions are focused on providing the most appropriate medical service in terms of patient safety and satisfaction outcomes. According to Lean methodologies, effectiveness and efficiency can be improved by assuring value-added processes. This article presents a joint approach for the development and implementation of Lean techniques combined with Total Laboratory Automation (TLA) for serology diagnosis in a microbiology laboratory in a tertiary-level hospital. The results obtained show an improvement in the process efficiency and its key performance indicators. In particular, for the HIV and COVID tests, the process Turnaround Times (TAT) were decreased by up to 87.3% and 19.3%, having a direct effect in the diagnostic response time. The process added-value for HIV tests increased by 81%. This meant a cost reduction per test, a higher number of diagnostic tests and clinical samples processed and laboratory resource optimisation. The implementation of TLA also enabled the reallocation of skilled labour towards value-added tasks, increased the process quality and reduced sample waiting times. This work opens up new opportunities for their deployment in other laboratory areas and sample types, directly influencing the overall quality of patient diagnosis in the context of tertiary healthcare facilities.
A Seismic Inversion Method Based on Multi-Scale Super-Asymmetric Cycle-JNet Network
Authors: Tang Mingming , Huang Boyang , Xie Rong , Chen Zhenzhen
Published: December 2023

In order to improve the resolution and accuracy of seismic inversion, this study constructs a multi-scale super-asymmetric network (Cycle-JNet). In this model, wavelet analysis is used to capture the multi-scale data characteristics of well-seismic data, thereby improving the machine’s ability to learn details. Using the UNet neural network from Convolutional Neural Network (CNN), we modified the network structure by adding several convolution kernel layers at the output end to expand generated data, solving the problem of mismatched resolutions in well-seismic data, thus improving the resolution of seismic inversion and achieving the purpose of accurately identifying thin sandstone layers. Meanwhile, a cycle structure of Recurrent Neural Network (RNN) was designed for the secondary learning of the seismic data generated by JNet. By comparing the data transformed through inverse wavelet transform with the original data again, the accuracy of machine learning can be improved. After optimization, the Cycle-JNet model significantly outperforms traditional seismic inversion methods in terms of resolution and accuracy. This indicates that this method can provide more precise inversion results in more complex data environments, providing stronger support for seismic analysis.
Classification of Different Winter Wheat Cultivars on Hyperspectral UAV Imagery
Authors: Lyu Xiaoxuan , Du Weibing , Zhang Hebing , Ge Wen , Chen Zhichao , Wang Shuangting
Published: December 2023

Crop phenotype observation techniques via UAV (unmanned aerial vehicle) are necessary to identify different winter wheat cultivars to better realize their future smart productions and satisfy the requirement of smart agriculture. This study proposes a UAV-based hyperspectral remote sensing system for the fine classification of different winter wheat cultivars. Firstly, we set 90% heading overlap and 85% side overlap as the optimal flight parameters, which can meet the requirements of following hyperspectral imagery mosaicking and spectral stitching of different winter wheat cultivars areas. Secondly, the mosaicking algorithm of UAV hyperspectral imagery was developed, and the correlation coefficient of stitched spectral curves before and after mosaicking reached 0.97, which induced this study to extract the resultful spectral curves of six different winter wheat cultivars. Finally, the hyperspectral imagery dimension reduction experiments were compared with principal component analysis (PCA), minimum noise fraction rotation (MNF), and independent component analysis (ICA); the winter wheat cultivars classification experiments were compared with support vector machines (SVM), maximum likelihood estimate (MLE), and U-net neural network ENVINet5 model. Different dimension reduction methods and classification methods were compared to get the best combination for classification of different winter wheat cultivars. The results show that the mosaicked hyperspectral imagery effectively retains the original spectral feature information, and type 4 and type 6 winter wheat cultivars have the best classification results with the classification accuracy above 84%. Meanwhile, there is a 30% improvement in classification accuracy after dimension reduction, the MNF dimension reduction combined with ENVINet5 classification result is the best, its overall accuracy and Kappa coefficients are 83% and 0.81, respectively. The results indicate that the UAV-based hyperspectral remote sensing system can potentially be used for classifying different cultivars of winter wheat, and it provides a reference for the classification of crops with weak intra-class differences.
RAU-Net++: River Channel Extraction Methods for Remote Sensing Images of Cold and Arid Regions
Authors: Tang Yiyu , Zhang Jianjie , Jiang Zhangzhen , Lin Ying , Hou Peng
Published: December 2023

Extracting river channels from remote sensing images is crucial for locating river water bodies and efficiently managing water resources, especially in cold and arid regions. The dynamic nature of river channels in these regions during the flood season necessitates a method that can finely delineate the edges of perennially changing river channels and accurately capture information about variable fine river branches. To address this need, we propose a river channel extraction method designed specifically for detecting fine river branches in remote sensing images within cold and arid regions. The method introduces a novel river attention U-shaped network structure (RAU-Net++), leveraging the rich convolutional features of VGG16 for effective feature extraction. For optimal feature extraction along channel edges and fine river branches, we incorporate a CBAM attention module into the upper sampling area at the end of the encoder. Additionally, a residual attention feature fusion module (RAFF) is embedded at each short jump connection in the dense jump connection. Dense skip connections play a crucial role in extracting detailed texture features from river channel features with varying receptive fields obtained during the downsampling process. The integration of the RAFF module mitigates the loss of river information, optimizing the extraction of lost river detail feature information in the original dense jump connection. This tightens the combination between the detailed texture features of the river and the high-level semantic features. To enhance network performance and reduce pixel-level segmentation errors in medium-resolution remote sensing imagery, we employ a weighted loss function comprising cross-entropy (CE) loss, dice loss, focal loss, and Jaccard loss. The RAU-Net++ demonstrates impressive performance metrics, with precision, IOU, recall, and F1 scores reaching 99.78%, 99.39%, 99.71%, and 99.75%, respectively. Meanwhile, both ED and ED′ of the RAU-Net++ are optimal, with values of 1.411 and 0.003, respectively. Moreover, its effectiveness has been validated on NWPU-RESISC45 datasets. Experimental results conclusively demonstrate the superiority of the proposed network over existing mainstream methods.
How to Find Disruptions in Logistics Processes in the Cold Chain and Avoid Waste of Products?
Authors: Lorenc Augustyn
Published: December 2023

This article presents a review of the literature related to the topic discussed and then discusses the system enabling the collection of data for analysis, the components of which are described in the paper. Next, a case study containing analyses of the circulation of logistic containers and the quality of deliveries is presented. Finally, a discussion of the results is presented. Background: This research is instrumental in navigating the intricacies of using these insulated containers of disturbances in the cold supply chain is imperative for ensuring the safety of perishable items, pharmaceuticals, and medical provisions, all of which necessitate precise temperature storage. Moreover, it holds significant sway over the efficacy of logistics, curtails losses, and guarantees adherence to regulatory stipulations and quality benchmarks. Research target: The research aimed to analyze the circulation of isothermal containers and indirectly assess the transportation quality for food products using the example of a 3PL company. Method: The article addresses issues encountered in the transportation of products within the cold supply chain. Using a company as an example, the temperature of coolboxes at the beginning of the logistics cycle, temperature distribution during transportation, and the temperature at the end of delivery were analyzed. The circulation of containers, their utilization over time, cycle durations, and the entire container circulation process were also examined. Results: Based on the collected data, recommendations were formulated to enhance product quality and increase container utilization. This research offers valuable insights into improving the efficiency and quality of logistics processes, specifically within the cold chain transportation industry, and provides recommendations for better managing temperature-sensitive product transportation.
Pollution Characteristics of Different Components of PM2.5 in Taiyuan during 2017–2020 Wintertime and Their Toxicity Effects on HepG2 Cells
Authors: Bai Lirong , Zhang Mei , Chen Shanshan , Chen Wenqi , Li Zhiping , Yue Jianwei , Dong Chuan , Li Ruijin
Published: December 2023

Fine particulate matter (PM2.5) is a common pollutant, and its health risk has attracted much attention. Studies have shown that PM2.5 exposure is associated with liver disease. The composition of PM2.5 is complex, and its hepatotoxic effects and lipid metabolism process are not well understood. In this study, we detected the concentrations of PM2.5 and its components (metals and polycyclic aromatic hydrocarbon (PAHs)) in the winter in Taiyuan, Shanxi Province, China, from 2017 to 2020 and then assessed the health risks. We also investigated the effects of different components (whole particles (WP), water-soluble particles (WSP), organic particles (OP)) of PM2.5 on the cytotoxicity and lipid metabolism in human liver cell line (HepG2) after 24 h of treatment. The changes in cytotoxicity indexes (LDH, IL-6, reactive oxygen species (ROS)) and lipids (triglyceride (TG), free fatty acid (FFA)) were measured after 24 h. The mRNA expression of lipid metabolism-related factors (SREBP1, CD36, MTTP) was determined by real-time quantitative RT-qPCR. Finally, the correlation between metals and PAHs with higher PM2.5 content in 4 years and biomarkers was analyzed. The results showed that: (1) The PM2.5 pollution was severe in Taiyuan during winter in 2017 and the subsequent four years. The calculation results of the metal enrichment factor (EF) value and PAHs characteristic ratio of PM2.5 showed that PM2.5 pollution sources differed in different years. (2) Exposure to metals and PAHs in PM2.5 did not cause a non-carcinogenic risk. Metals had no cancer risk, while PAHs inhaled in PM2.5 in 2017 and 2018 had a potential cancer risk. The atmospheric PM2.5 pollution in Taiyuan has had a downward trend, but the PAHs in the PM2.5 of 2017–18, when the pollution is relatively serious, have a potential carcinogenic risk. (3) WP, OP and WSP inhibited cell survival rate from 2017 to 2020, and OP had higher cytotoxicity at the same concentration. (4) WP, OP and WSP increased the levels of LDH, IL-6, TNF-α, ROS, MDA, TG and FFA, and inhibited SOD activity in a dose-effect relationship. The organic components in PM2.5 are more toxic to HepG2 cells and affect the expression of lipid metabolism-related factors at the transcriptional level. (5) The mRNA expressions of factors related to lipid synthesis, uptake, oxidation and output were up-regulated after treatment with PM2.5 and its components, suggesting a lipid metabolism disorder. (6) The biomarkers were associated with certain metals (Zn, Pb, Cu and Cr) and PAHs in PM2.5. These suggested that PM2.5- and PM2.5-bound organic matter caused HepG2 cytotoxicity and affected lipid metabolism.
A Two-Step Estimation Method for a Time-Varying INAR Model
Authors: Pang Yuxin , Wang Dehui , Goh Mark
Published: December 2023

This paper proposes a new time-varying integer-valued autoregressive (TV-INAR) model with a state vector following a logistic regression structure. Since the autoregressive coefficient in the model is time-dependent, the Kalman-smoothed method is applicable. Some statistical properties of the model are established. To estimate the parameters of the model, a two-step estimation method is proposed. In the first step, the Kalman-smoothed estimation method, which is suitable for handling time-dependent systems and nonstationary stochastic processes, is utilized to estimate the time-varying parameters. In the second step, conditional least squares is used to estimate the parameter in the error term. This proposed method allows estimating the parameters in the nonlinear model and deriving the analytical solutions. The performance of the estimation method is evaluated through simulation studies. The model is then validated using actual time series data.