bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bradyrhizobium ontarionense sp. nov. isolated from Aeschynomene indica (Indian jointvetch) harbours photosynthesis, nitrogen fixation and nitrous oxide reductase genes.
Authors: Bromfield Eden S. P. , Cloutier Sylvie 
Published: November 2023

Abstract

Bacterial strain A19T was previously isolated from a root-nodule of Aeschynomene indica (Indian jointvetch) and assigned to a new lineage in the genus Bradyrhizobium.
Here data are presented for the detailed phylogenomic and taxonomic characterisation of strain A19T.
Phylogenetic analysis of whole genome sequences as well as 51 concatenated core gene sequences placed strain A19T in a highly supported lineage that was distinct from described Bradyrhizobium species; B. oligotrophicum, a symbiont of A. indica, was the most closely related species. The digital DNA-DNA hybridization and average nucleotide identity values for strain A19T in pair-wise comparisons with close relatives were far lower than the respective threshold values of 70% and ~96% for definition of species boundaries.
The complete genome of strain A19T consists of a single 8.44 Mbp chromosome (DNA G+C content, 64.9 mol%) and contains a photosynthesis gene cluster, nitrogen-fixation genes and genes encoding a complete denitrifying enzyme system including nitrous oxide reductase. Nodulation and type III secretion system genes, needed for nodulation by most rhizobia, were not detected in the genome of A19T.
Data for multiple phenotypic tests complemented the sequence-based analyses. Strain A19T elicits nitrogen-fixing nodules on stems and roots of A. indica plants but not on soybeans or Macroptilium atropurpureum. Based on the data presented, a new species named Bradyrhizobium ontarionense sp. nov. is proposed with strain A19T (= LMG 32638T = HAMBI 3761T ) as the type strain.
Mycobacterium avium subspecies paratuberculosis (MAP) infection, and its impact on gut microbiome of individuals with Multiple Sclerosis
Authors: Ashraf Hajra , Dikarlo Plamena , Masia Aurora , Zarbo Ignazio R. , Solla Paolo , Ijaz Umer Zeeshan , Sechi Leonardo A. 
Published: November 2023

Abstract
Background
There is a growing body of evidence suggesting the role of gut microbiome in the aetiology of Multiple sclerosis (MS) with the development and progression of the disease as a multifactorial interaction between the gut, the brain, and the immune system. At the same time there is also existing evidence to link Mycobacterium avium subspecies paratuberculosis infections (MAP) and the development of MS. Whilst perturbations of the gut microbiome in patients with MS are well described in the literature, nothing is known about the gut microbiome perturbations in MAP infected MS patients. In the present study, using 16S rRNA amplification, we characterize the compositional and functional differences of the gut microbiome between MS patients with MAP (MAP+) and without (MAP-) infection and compare the results with a healthy cohort to understand the gut microbiome dynamics.
Results
Based on diversity analyses, there were notable differences between HC, MAP-, and MAP + profiles. Fitting neutral modelling on core microbiome, we have found taxa selected by the hosts, and those that were based on dispersal limitation. Core phyla shared between MAP + and MAP- belonged to Actinobacteria, Bacteroidata, Verrucomicrobiota, Firmicutes, with additional Desulfobacterota, and Proteobacteria observed in MAP + only. Using a Quasi Conditional Association Test, Archaea were over represented in MS samples, particularly in MAP+. Using contingency analyses, we are able to identify discriminatory patterns between MAP statuses in the context of anthropometric and sociodemographic patterns. Finally, an advanced mediation analysis then consolidates confounders, treatment groups, microbiome, and the outcome parameters (including disease duration). This highlighted certain species i.e., Sutterella, Akkermmansia, Bacteriodes, Gastranaerophilales, Alistipes, Balutia, Faecalibacterium, Lachnospiraceae, Anaerostipes, Ruminococcaceae, Eggerthellaceae and Clostridia-UCG-014 having mediatory effect considering disease duration as an outcome and MAP as a treatment group.
Conclusions
Overall, we found that there were profound differences in the composition and function of the gut microbiome between MAP + and MAP- MS patients, with the difference in taxonomic structure being greater than the functional difference. Our analysis indicates that the gut microbiome may be an important target for dietary and lifestyle intervention in MS patients with and without MAP infection.
Individual fungal taxa drive community structure change and necromass accumulation increment
Authors: Meng Xiangtian , Zhang Xuechen , Fan Lichao , Wang Jiangyuzhuo , Yu Haiyang , Jiang Yuhan , Shi Jianglan , Tian Xiaohong , Kuzyakov Yakov 
Published: November 2023

Abstract
Background
Conversion of accessible organic compounds to fungal biomass and subsequent necromass is a crucial process for soil organic matter accrual. The contribution of fungal community structure and biomass to necromass accumulation in croplands remain unclear.
Results
We assessed the fungal necromass increment by amino sugar content in soil of a long-term field experiment after straw return and nitrogen (N) fertilization. The fungal absolute copy number and community structure were assessed by absolute quantitative sequencing technology. Straw input and N-fertilization-induced wheat growth was the main factor in increasing fungal absolute copy number, altering community structure, and consequently boosting necromass accumulation. N fertilization additionally shifted the fungal community structure by alleviating N limitation and balancing the C:N ratio of added material. The fungal community structure, rather than the total absolute copy number, was the best predictor of necromass increment. Specifically, necromass increment were primarily attributed to the rapid growth of individual fungal taxa rather than the keystones in dominant modules. Specifically, the community structure changed towards the aggregation of pathogenic fungi represented by Pyrenochaetopsis and Dokmaia under high straw return and low or no N fertilization scenarios, while in the scenario of co-existence of straw and N fertilization increased the abundance of saprophytic fungi, represented by Ascobolus and Botryotrichum, replaced pathogenic fungi and dominated the community structure change and raised the fungal necromass accumulation.
Conclusions
In conclusion, individual fungal taxa drive community structure changes and necromass increment.
Bacteriological quality and antimicrobial resistance patterns of isolates from raw milk in dairy farms in Ethiopia
Authors: Sebsibe Kaleab Awoke , Mulugeta Yimer , Legesse Tesfaye , F/silassie Getinet , Gonbena Waktole , Abera Frehiwot , Girma Samsone , Alemu Amare , Behailu Getamesay , Yohannes Tigist , Kefale Tesfaddis , Beyene Degefu , Abdela Sintayehu , Akililu Mesfin , Birhanu Endalkachew , Tefera Nardos , Araya Shambel , Abera Dessie , Desta Kassu 
Published: November 2023

Abstract
Background
Food-borne illness has a significant impact on public health and the economy, affecting nearly 30% of the population in developing countries annually. Infections transmitted through milk can lead to acute and severe diseases. However, there is inadequate information available regarding the bacteriological profile and antimicrobial resistance of organisms present in raw milk. This study aimed to assess the bacteriological quality and antimicrobial resistance patterns of isolates from raw milk at different dairy farms found in Ethiopia.
Methods
A cross-sectional study was conducted, selecting 176 raw milk samples through a multi-stage sampling technique from August 2022- April 2023. Bacteriological tests, including Aerobic colony count, total coliform count, thermotolerant coliform count, Salmonella and Shigella detection, as well as Staphylococcus enumerations, were performed. Further bacterial identification was carried out using VITEK-2 compact, while the antimicrobial susceptibility test was determined by the Kirby-Bauer disc-diffusion technique. Data analysis was conducted using SPSS V.27, employing descriptive statistics and appropriate statistical tests.
Resut
The mean aerobic colony count, total coliform, thermo-tolerant coliform, E. coli, and Staphylococcus count was,3.2, 2.70, 2.69, 2.9, and 3.1 log10 cfu/ml respectively. E. coli (77%), Klebsiella spp. (5%), Salmonella spp. (1.4%), S. aureus (13.6%), S. saprophyticus (9.8%) were also isolated. Gram-negative isolates showed sensitivity for Meropenem (96.8%) and Ciprofloxacin (89.9%) but resistant against Tetracycline (62.2%) and Streptomycin (62.2%). Staphylococcus isolates showed 95.1% Sensitivity for Levofloxacin and Gentamycin but 92.6% of isolates were resistant against Oxacillin. Extended-spectrum beta-lactamase production was detected in 16.6% of gram-negative isolates, and Methicillin resistance were observed in 30% of S. aureus isolates.
Conclusion
The results indicate that the overall quality of raw milk is poor, containing pathogenic and antibiotic-resistant organisms. This highlights the necessity for effective control measures to enhance production, storage, and processing practices.
Assessment of Fuzzy Logic to Enhance Species Distribution Modelling
Authors: LI XINGYU , Emery Robert N. , Coupland Grey T. , Ren Yonglin , McKirdy Simon J. 
Published: November 2023

Abstract

Fuzzy logic presents a promising approach for Species Distribution Modelling by generating a commensurable value termed ‘favourability’. Departing from conventional value ‘probability’, ‘favourability’ remains robust regardless of species prevalence, enabling across species comparisons despite varying prevalence. Such comparisons facilitate the interpretation of cryptic species, which have intricate distribution data to assign. This study generated environmental favourability values for two borers within a cryptic beetle species complex: Euwallacea fornicatus and Euwallacea perbrevis in Australia. This research delved into biogeographic relationship analyses fuzzy intersection and potential biotic interaction of these closely related borers, highlighting a notably favourable distribution pattern for Euwallacea fornicatus in Queensland. To evaluate the model’s performance, this paper utilized commonly employed evaluation metrics (Area under the receiver operating characteristic curve, True statistical skill, Correct classification rate), alongside fuzzy entropy value and the Hosmer-Lemeshow test to assess the model reliability. This study validates the efficacy of fuzzy logic in species distribution modelling and showcases its utility in assessing habitat suitability for closely related species through the utilization of a more informative value – favourability. This value emerges as a valuable refinement to Species distribution models, enabling the assessment of differences and similarities among species’ distribution areas alongside the species’ environmental correlates.
Conceptualization of Community (Advice)-based Health eCoach Recommendation Generation for Physical Activity Level Monitoring using an Explainable and Ethical Approach
Authors: Chatterjee Ayan , Riegler Michael A. , Halvorsen Pål 
Published: November 2023

Abstract
Utilizing a digital platform for self-monitoring offers advantages for remote activity tracking and generating recommendations. An automatic coaching system, known as eCoach, can be a valuable tool. It consistently gathers individual health and wellness data for the purpose of creating lifestyle recommendations, either tailored to an individual or based on community input. While personal recommendations in eCoaching are well-received, there is a lack of research on community-based recommendations. This study introduces an effective community-based eCoach recommendation system for assessing daily activity levels and offering physical activity suggestions. The approach involves collecting data from remote participants using wearable activity sensors and categorizing the data into sedentary (0) and active (1) classes for binary classification. The dataset used for physical activity levels exhibits an imbalance in class distribution and unequal misclassification costs, making imbalanced classification challenging. To address this issue and improve the performance of traditional machine-learning models, the study employs various oversampling techniques, including the Synthetic Minority Oversampling Technique (SMOTE), to create balanced datasets by generating synthetic samples from the minority class. Third, we explain the model classifications with Shapley Additive Explanations (SHAP). Fourth, we use hyperparameter tuning methods to obtain the best classification performance. Fifth, we consider a preference, activity patterns, and demographic attributes, such as age, gender, height, and weight, for advice and community-based recommendations to meet activity goals. For experimentation, we collected activity data from 16 participants (Male: 12; Female: 4) using a wearable MOX2-5 activity sensor (CE-certified) and combined the dataset with the public Fibit-based PMData activity dataset of 15 participants (Male: 12; Female: 3) to avoid bias, and for verification and advice-based recommendation planning, we considered last week’s participant data. The system’s performance has been evaluated using metrics such as accuracy, precision, recall, F1-score, brier-score, and Mathew’s coefficient (MCC) and achieves 99.8% accuracy (F1 = 99.8%, Precision = 99.8%, Recall = 99.8%, and MCC = 99.8%) with DecisionTree Classifier on the imbalanced dataset and 99.8% accuracy (F1 = 99.8%, Precision = 99.8%, Recall = 99.8%, and MCC = 99.8%) with DecisionTree Classifier on the balanced dataset. Ethical AI involves more than just coding; it entails ethical considerations and decision-making throughout development. In this study, we evaluated our models for bias and fairness, concentrating on the recommendation generation within an eCoach system. Future research will focus on efficacy evaluation in controlled trials, extending beyond this theoretical investigation.
A Deep Learning Approach for Automatic 3D Segmentation of Hip Cartilage and Labrum from Direct Hip MR Arthrography
Authors: Meier Malin Kristin , Helfenstein Ramon , Boschung Adam , Nanavati Andreas , Ruckli Adrian C. , Lerch Till D. , Gerber Nicolas , Jung Bernd , Afacan Onur , Tannast Moritz , Siebenrock Klaus A. , Steppacher Simon Damian , Schmaranzer Florian 
Published: November 2023

Abstract

The objective was to use convolutional neural networks (CNNs) for automatic segmentation of hip cartilage and labrum based on 3D MRI. In this retrospective single-center study, CNNs were used to develop a fully automated segmentation model for hip cartilage and labrum from MRI. Direct hip MR arthrographies (01/2020-10/2021) were selected from 100 symptomatic patients. Institutional routine protocol included a 3D T1 mapping sequence, which was used for manual segmentation of hip cartilage and labrum. 80 hips were used for training and the remaining 20 for testing. Model performance was assessed with six evaluation metrics including Dice similarity coefficient (DSC). In addition, model performance was tested on an external dataset (40 patients) with a 3D T2-weighted sequence from a different institution. Inter-rater agreement of manual segmentation served as benchmark for automatic segmentation performance. 100 patients were included (mean age 30 ± 10 years, 64% female patients). Mean DSC for cartilage was 0.92 ± 0.02 (95% confidence interval [CI] 0.92–0.93) and 0.83 ± 0.04 (0.81–0.85) for labrum and comparable (p = 0.232 and 0.297, respectively) to inter-rater agreement of manual segmentation: DSC cartilage 0.93 ± 0.04 (0.92–0.95); DSC labrum 0.82 ± 0.05 (0.80–0.85). When tested on the external dataset, the DSC was 0.89 ± 0.02 (0.88–0.90) and 0.71 ± 0.04 (0.69–0.73) for cartilage and labrum, respectively. The presented deep learning approach accurately segments hip cartilage and labrum from 3D MRI sequences and can potentially be used in clinical practice to provide rapid and accurate 3D MRI models.
Allopatric populations of Drosophila ananassae exhibit different degree of trade-off for evolving immune response against bacterial infection
Authors: Paul Pallab , Mukherjee Goutam , Mandal Sayarneel , Das Debasmita , Dutta Ishita , Ghosh Papiya , Ghosh Sujay 
Published: November 2023

Abstract
We conducted laboratory based selection experiment with two allopatric populations of Drosophila ananassae collected from two isolated geographic regions of India namely, Mysuru and Port Blair and subsequently inbred for several generations at laboratory. The populations were infected enteritically with the bacteria Pseudomonas aeruginosa for fifty-five generations followed by ten generations under relaxed selection. We tested development of immune-competence of the selected flies through the generations and inquired if elicitation of immune responses were needed to pay cost by trading-off with life history and morphological traits. We observed gradual and progressive increase in longevity, reproductive life span, post reproductive life span, developmental time, fecundity rate, fat content and gradual reduction in body length and water content. Under relaxed selection regime there was a reversion of all the traits but not to the basal level. Responses exhibited by the infected-selected flies from Port Blair and Mysuru differed, with the former group exhibited more reduction in body length, more reduction in water content, greater antioxidant enzyme activity, longer post infection period, greater survival than later group. On other side, Mysuru flies showed greater fat deposition, faster developmental time, longer oviposition time than Port Blair flies. Interestingly, Port Blair flies exhibited, increase in post ovipository period in contrast to Mysuru flies that showed decrease for the same. We inferred that two allopatric populations of D. ananassae show different trade-off for evolving immune response with life history traits.
The Contribution of the Social and Solidarity Economy to Sustainable Economic Growth: A Modified Solow Model Approach
Authors: Salustri Andrea , Caria Sara , Sacchetti Silvia , De Pretis Francesco 
Published: November 2023

Abstract
This paper illustrates the interplay between economic growth and social inclusion, whereas the latter is produced by the organizations of the social and solidarity economy, highlighting its synergies with the pursuit of the Sustainable Development Goals. Assuming that economic growth and social inclusion are not antinomic concepts, but, rather, the two sides of the same coin, technological progress can be restricted to the subset of the eco-efficient innovations, and social inclusion can be added to the arguments of a production function, thus obtaining a macroeconomic model encompassing the three dimensions of sustainable development. By introducing social inclusion in a modified Solow model, the paper illustrates how the former is an important driver of economic growth and can complement input accumulation, reducing the inconsistencies between growth and development. Given the heterogeneity among equilibrium level of output of different countries, this model identifies an alternative pattern of development, compatible with the initial conditions of a low resource economy lacking endogenous technological progress. This research provides a strong case for the integration of socio-economic and environmental concerns into policy planning, building on the specific resources that can be mobilised and the peculiar socio-economic needs expressed by society.
JEL codes: O00; O35; Q01; L30
A marigold corolla detection model based on the improved YOLOv7 lightweight
Authors: Fan Yixuan , Tohti Gulbahar , Geni Mamtimin , Zhang Guohui , Yang Jiayu 
Published: November 2023

Abstract
Marigold, as an important traditional Chinese medicine with the functions of clearing heat and detoxification, protecting the liver, beautifying the face as well as promoting the health of the eyes, etc. Its demand is increasing day by day, and mechanized harvesting has become an inevitable trend in the industrialization of marigold harvesting. Therefore, this study tries to collect a new dataset in the south of Xinjiang, China, which is important for the production of marigold focusing on improving the YOLOv7 model by lightweighting, and proposing a set of detection models suitable for marigold. By deleting the redundant object detection layer of the YOLOv7 model, replacing the ordinary convolution of the backbone network with the DSConv convolution, replacing the SPPCSPC module with Simplified SPPF, and finally pruning and fine-tuning the model, it seeks to solve the trouble of the difficulty in deploying the mobile devices of the marigold picking robot and the inability to realize the high real-time detection. The experimental result shows that the accuracy and average accuracy mAP0.5 of the improved YOLOv7 model in marigold detection reach 93.9% and 97.7%, which are both improved compared with the original YOLOv7 model; the GFLOPs is only 2.3, which is 2.2% of the original model; and the parameter amount is 15.04M, which is 41.2% of the original model; The FPS is 166.7, which is 26.7% higher than the original model. It shows excellent accuracy and speed in detecting marigolds, providing strong technical support for marigold harvesting.
Social exclusion and short video addiction in Chinese college students: The mediating role of boredom and self-control
Authors: Zhang Yali , Bu Ruohan , Zhao Jinxia , Li Xiaoli 
Published: November 2023

Abstract
Background
Short video apps are very popular among Chinese college students, and some students even rely on them. Most of the current research only focuses on Internet addiction, and seldom pays attention to the phenomenon of short video addiction. Its influencing factors and formation mechanism are worth exploring.
Objectives
This study aims to explore the relationship between social exclusion and short video addiction among college students, and the mediating roles of boredom and self-control.
Methods
This study adopted a Multi-stage investigation and investigated 532 college students (39% males; mean age 19.32 ± 1.23 years) with social exclusion scale, boredom proneness scale, self-control scale, and short video addiction scale. The mediating effect was tested with Process 3.1.
Results
The results showed that social exclusion could directly affect short video addiction. Moreover, boredom and self-control can independently mediate the association between social exclusion and short video addiction. Furthermore, boredom and self-control can sequentially mediate the association between social exclusion and short video addiction.
Conclusion
Theoretically, this study modified the I-PACE model, indicating that behavioral addiction, such as short video addiction, should consider personal and distant social factors. Practically, the results suggested that schools should reduce peer rejection and improve students' mental health literacy to reduce boredom and enhance self-control, thus effectively preventing short video addiction.