bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antarctic snow algae: unraveling the processes underlying microbial community assembly during blooms formation
Authors: Soto Daniela F. , Gómez Iván , Huovinen Pirjo 
Published: September 2023

Abstract
Background and aims
At the West Antarctic Peninsula, snow algae blooms are composed of complex microbial communities dominated by green microalgae and bacteria. During their progression, the assembly of these microbial communities occurs under harsh environmental conditions and variable nutrient content due to fast snow melting. To date, it is still unclear what are the ecological mechanisms governing the composition and abundance of microorganisms during the formation of snow algae blooms. In this study, we aim to examine the main ecological mechanisms governing the assembly of snow algae blooms from early stages to colorful stages blooms.

Methods
The composition of the microbial communities within snow algae blooms was recorded in the West Antarctic Peninsula (Isabel Riquelme Islet) during a 35-day period using 16S rRNA and 18S rRNA metabarcoding. In addition, the contribution of different ecological processes to the assembly of the microbial community was quantified using phylogenetic bin-based null model analysis.

Results
Our results showed that alpha diversity indices of the eukaryotic communities displayed a higher variation during the formation of the algae bloom compared with the bacterial community. Additionally, in a macronutrients rich environment, the content of nitrate, ammonium, phosphate, and organic carbon did not play a major role in structuring the community. The quantification of ecological processes showed that the bacterial community assembly was governed by selective processes such as homogenous selection. In contrast, stochastic processes such as dispersal limitation and drift, and to a lesser extent, homogenous selection, regulate the eukaryotic community.

Conclusions
Overall, our study highlights the differences in the microbial assembly between bacteria and eukaryotes in snow algae blooms and proposes a model to integrate both assembly processes.
Effect of age and gender on dietary patterns, mindful eating, body image and confidence
Authors: Jacob Jinsa Sara , Panwar Neeraj 
Published: September 2023

AbstractThe emergence of ‘Diet Culture’ came into existence with the era of pop culture, which emphasized the idea of body improvement by embracing the portrayal of unrealistic beauty standards set by the thin-ideal media. This growing and trending culture gained its popularity in India with the COVID pandemic and the imposed lockdown, wherein the prevalence of obesity and binge eating resulted from counter-regulatory eating behaviors and restrictive food intake to a greater extent of skipping meals to achieve the desired body type. The present empirical investigation focuses on understanding the gender and age-based differences (between the ages 18 to 55) among Indian population on dietary patterns, body image, mindful eating and physical appearance confidence using 2 × 3 factorial design. The tools used were Eating Behavior Pattern Questionnaire (EBPQ) [43], Body Self- image Questionnaire (BSIQ) [40], Mindful Eating Questionnaire (MEQ) [18] and Personal Evaluation Inventory (PEI) [44] were administered on a sample size of 120, selected using convenience sampling technique. The collected data was analyzed using SPSS Version 20.0. Results of the study reveal non-significant age and gender differences for mindful eating and appearance confidence. Significant age- differences were observed for Snacking and convenience F(2,114) = 6.22, p < .05; social dependence F(2,114) = 3.87, p < .05 and height dissatisfaction F(2,114) = 8.79, p < .05. And, significant gender differences were observed for Meal Skipping F(1,114) = 6.46, P < .05; snacking and convenience F(1,114) = 4.19, p < .05; fatness evaluation F(1,114) = 5.94, p < .05 and fitness evaluation F(1,114) = 5.33, p < .05. The only significant interaction effect observed was for social dependence dimension F(2, 114) = 3.96, p < .05. Thus, high exposure to social media and diet-related content contributed significantly to changing dietary patterns, and how they look, feel or perceive their body.
Development of a resilience-enhancing intervention during and after pregnancy: a systematic process informed by the behaviour change wheel framework
Authors: Van Haeken Sarah , Braeken Marijke A.K.A. , Horsch Antje , Oosterman Mirjam , Bogaerts Annick 
Published: September 2023

Abstract
Background
Pregnancy and the transition to parenthood are accompanied by multiple changes and stress exposure. Resilience has the potential to counteract the negative impact of stress and can be a protective factor against mental health problems. To date, the use of a theoretical framework in the development or application of resilience interventions during pregnancy up to one year postpartum is missing. The aim of this study is to develop an intervention to enhance resilience for pregnant women up to one year postpartum.

Methods
A systematic and theory-based approach informed by the Behaviour Change Wheel framework and the theoretical model of perinatal resilience was applied. The development took place in three phases and during the process, the target group, researchers and clinicians were involved.

Results
A combination of resilience-enhancing exercises, group sessions and an online support platform, including follow-up at six and twelve months after delivery, was designed to enhance resilience during pregnancy and up to one year postpartum. This intervention incorporates 5 intervention functions delivered by 18 behaviour change techniques.

Conclusions
This study responds to the need for theory-based intervention programs aiming to enhance resilience to improve the psychological health of pregnant women. We developed a multicomponent resilience-enhancing intervention for pregnant women up to one year postpartum.
MAFSIDS: a reinforcement learning-based intrusion detection model for multi-agent feature selection networks
Authors: Ren Kezhou , Zeng Yifan , Zhong Yuanfu , Sheng Biao , Zhang Yingchao 
Published: September 2023

AbstractLarge unbalanced datasets pose challenges for machine learning models, as redundant and irrelevant features can hinder their effectiveness. Furthermore, the performance of intrusion detection systems (IDS) can be further degraded by the emergence of new network attack types. To address these issues, we propose MAFSIDS (Multi-Agent Feature Selection Intrusion Detection System), a DQL (Deep Q-Learning) based IDS.MAFSIDS comprises a feature self-selection algorithm and a DRL (Deep Reinforcement Learning) attack detection module. The feature self-selection algorithm leverages a multi-agent reinforcement learning framework, which redefines the feature selection problem by converting the traditional$${2}^{N}$$2Nfeature selection space into$$N$$Nagent representations. This approach reduces model complexity and enhances the search strategy for feature selection. To ensure accurate feature representation and expedite the feature selection process, we have also developed a GCN (Graph Convolutional Network) method that extracts deeper features from the data. The DRL attack detection module utilizes the Mini-Batchs technique to encode the data, allowing reinforcement learning to be applied in a supervised learning context. This integration improves accuracy. Additionally, the policy network in this module is designed to be minimalist, enhancing model efficiency. To evaluate the performance of our model, we conducted comprehensive simulation experiments using Python. We tested the model using the CSE-CIC-IDS2018 and NSL-KDD datasets, achieving impressive accuracy rates of 96.8% and 99.1%, as well as F1-Scores of 96.3% and 99.1%, respectively. The selected feature subset successfully eliminates approximately 80% of redundant features compared to the original feature set. Furthermore, we compared our proposed model with other popular machine-learning models.
Non-canonical two-step biosynthesis of anti-oomycete indole alkaloids in Kickxellales
Authors: Rassbach Johannes , Hilsberg Nathalie , Haensch Veit G. , Dörner Sebastian , Gressler Julia , Sonnabend Robin , Semm Caroline , Voigt Kerstin , Hertweck Christian , Gressler Markus 
Published: September 2023

Abstract
Background
Fungi are prolific producers of bioactive small molecules of pharmaceutical or agricultural interest. The secondary metabolism of higher fungi (Dikarya) has been well-investigated which led to > 39,000 described compounds. However, natural product researchers scarcely drew attention to early-diverging fungi (Mucoro- and Zoopagomycota) as they are considered to rarely produce secondary metabolites. Indeed, only 15 compounds have as yet been isolated from the entire phylum of the Zoopagomycota.

Results
Here, we showcase eight species of the order Kickxellales (phylum Zoopagomycota) as potent producers of the indole-3-acetic acid (IAA)-derived compounds lindolins A and B. The compounds are produced both under laboratory conditions and in the natural soil habitat suggesting a specialized ecological function. Indeed, lindolin A is a selective agent against plant-pathogenic oomycetes such as Phytophthora sp. Lindolin biosynthesis was reconstituted in vitro and relies on the activity of two enzymes of dissimilar evolutionary origin: Whilst the IAA–CoA ligase LinA has evolved from fungal 4-coumaryl-CoA synthetases, the subsequently acting IAA-CoA:anthranilate N-indole-3-acetyltransferase LinB is a unique enzyme across all kingdoms of life.

Conclusions
This is the first report on bioactive secondary metabolites in the subphylum Kickxellomycotina and the first evidence for a non-clustered, two-step biosynthetic route of secondary metabolites in early-diverging fungi. Thus, the generally accepted “gene cluster hypothesis” for natural products needs to be reconsidered for early diverging fungi.
Discrete element modelling of granular materials incorporating realistic particle shapes
Authors: Kodicherla Shiva Prashanth Kumar 
Published: September 2023

AbstractThis paper proposes an approach to generate realistic particle shapes considering the major plane of orientation of particles in discrete element modelling (DEM). The particle generation framework includes capturing high-quality scanning electron microscope (SEM) images, followed by image processing and generation of clumps using a commonly used multi-sphere (MS) approach in particle flow code (PFC3D). A set of experimental direct shear tests (DST) and subsequent DEM simulations were performed by incorporating realistic particle shapes. The simulation results show a good agreement with those obtained in the laboratory. In addition, the normal stress showed a significant effect on the structural anisotropy of the granular materials.
Infectious disease control: from health security strengthening to health systems improvement at global level
Authors: Zhang Xiao-Xi , Jin Yin-Zi , Lu Yi-Han , Huang Lu-Lu , Wu Chuang-Xin , Lv Shan , Chen Zhuo , Xiang Hao , Zhou Xiao-Nong 
Published: September 2023

AbstractSince the twenty first century, the outbreaks of global infectious diseases have caused several public health emergencies of international concern, imposing an enormous impact on population health, the economy, and social development. The COVID-19 pandemic has once again exposed deficiencies in existing global health systems, emergency management, and disease surveillance, and highlighted the importance of developing effective evaluation tools. This article outlines current challenges emerging from infectious disease control from the perspective of global health, elucidated through influenza, malaria, tuberculosis, and neglected tropical diseases. The discordance among government actors and absent data sharing platforms or tools has led to unfulfilled targets in health system resilience and a capacity gap in infectious disease response. The current situation calls for urgent action to tackle these threats of global infectious diseases with joined forces through more in-depth international cooperation and breaking governance barriers from the purview of global health. Overall, a systematic redesign should be considered to enhance the resilience of health systems, which warrants a great need to sustain capacity-building efforts in emergency preparedness and response and raises an emerging concern of data integration in the concept of One Health that aims to address shared health threats at the human-animal-environment interface.
Typology and working mechanism of a hybrid power router based on power-frequency transformer electromagnetic coupling with converters
Authors: Lai Jinmu , Yin Xin , Yin Xianggen , Hu Jiaxuan , Xiao Fan 
Published: September 2023

AbstractThe power router (PR) is a promising piece of equipment for realizing multi-voltage level interconnection and flexible power control in the future distribution power grid. In this paper, a hybrid PR (HPR) topology based on power-frequency transformer electromagnetic coupling with converters is proposed for the medium distribution power grid. The power-frequency transformer is used to undertake power transmission, voltage conversion, and other main tasks, while the power electronic converters are combined to achieve active control. Equivalent magnetic and electrical circuit models are established to help discuss the operating principle of the proposed HPR. Additionally, the power flow and control principle of the HPR in different operating conditions are analyzed, with the control system design scheme presented. The theoretical analysis results are verified by MATLAB/Simulink + Plecs simulation and a controller hardware-in-the-loop study, as well as a down-scale experimental test, indicating that the proposed HPR is flexible in active voltage support and current control.
Health and well-being of the Portuguese citizens: impacts of the COVID-19
Authors: Ferreira Lara N. , Pereira Luís N. , Ferreira Pedro L. 
Published: September 2023

Abstract
Background
COVID-19 pandemic placed unprecedented pressure on societies and healthcare systems around the world. Over the last years, measures imposed in almost all countries dealing with the pandemic sent the entire world into an extensive crisis and thus into a deep global recession. Since the outbreak began, many European countries have faced three/four waves of pandemic. Portugal has mainly dealt with three waves (March/April’2020; October/November’2020; January/February’2021), the third being the deadliest one. The purpose of this article is to provide evidence on the impact of the COVID-19 on health-related quality of life (HRQol) and well-being (W-B) of Portuguese citizens. It aims to (i) characterize these outcomes during the COVID-19 pandemic; (ii) compare them to pre-COVID-19 Portuguese population; and (iii) identify the social determinants that may affect these outcomes during the COVID-19 pandemic.

Methods
This study used data from a survey that collected data on HRQoL, W-B, satisfaction with life, economic and labour impacts, access to healthcare, mental and physical health, amongst others. The survey was implemented by telephone to a representative random sample of 1,255 respondents from the general adult Portuguese population, stratified by sex, age group and region. Data was collected during the end of the second national lockdown. For comparison purposes, we have also used two other representative databases from the general Portuguese population: (i) data from before the pandemic (n = 1,006); and (ii) data from a survey conducted during the first lockdown, (n = 904).

Results
Looking at health and access to healthcare, 4% of citizens had their surgeries postponed or cancelled because of COVID-19, more than a quarter had medical appointments or complementary exams postponed or cancelled, with 7% over 65 years old with surgeries cancelled or postponed and 32% medical appointments. COVID-19 pandemic also impacted negatively on the HRQoL of citizens, especially in the first lockdown. Half of the respondents reported feeling nervous, anxious, or on edge, about 45% of citizens felt sad or depressed. Sleeping problems were reported for almost 39% of citizens, and loneliness is reported by 29% of citizens. For about 70–85% of citizens, these feelings were more so than before the pandemic. Citizens with fair/strong economic stability were the most economically affected by the pandemic.

Conclusions
We provided evidence on the impact of COVID-19 on health and W-B of Portuguese citizens. Their health was worse than before the pandemic and the access to healthcare was highly affected.
Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset
Authors: Sharmila B S , Nagapadma Rohini 
Published: September 2023

AbstractIn recent years, many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify attacks. The deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge devices. This study proposes quantized autoencoder (QAE) model for intrusion detection systems to detect anomalies. QAE is an optimization model derived from autoencoders that incorporate pruning, clustering, and integer quantization techniques. Quantized autoencoder uint8 (QAE-u8) and quantized autoencoder float16 (QAE-f16) are two variants of QAE built to deploy computationally expensive AI models into Edge devices. First, we have generated a Real-Time Internet of Things 2022 dataset for normal and attack traffic. The autoencoder model operates on normal traffic during the training phase. The same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error (RE) of the anomaly will be high, which helps to identify the attacks. Furthermore, we study the performance of the autoencoders, QAE-u8, and QAE-f16 using accuracy, precision, recall, and F1 score through an extensive experimental study. We showed that QAE-u8 outperforms all other models with a reduction of 70.01% in average memory utilization, 92.23% in memory size compression, and 27.94% in peak CPU utilization. Thus, the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.
The effect of sulfadiazine in manure on accumulation of sulfonamide resistance genes in freshly consumable plants
Authors: van Overbeek Leo , Berendsen Björn , Aanstoot Stefan , Bossers Alex , Nijhuis Els , Russ Lina , Andreo Jimenez Beatriz 
Published: September 2023

Abstract
Background
Antibiotic resistance genes will spread via soil fertilized with animal manure to food products. Especially plants whose harvested products can be consumed freshly are of concern. The aim of this study was to assess the impact of sulfadiazine (SDZ)-manured soil on the occurrence of sulfonamide (SA) resistance genes in freshly consumable plants.

Methods
Sulfadiazine-containing manure was administered via soil to lettuce and leek plants. At harvest, the rhizosphere soil, roots and leaves were investigated on the presence of SDZ-resistant bacteria and sul1 and sul2 genes via qPCR. Further, the impact of SDZ in manure on bacterial community and antibiotic resistance gene composition via amplicon sequencing and shotgun metagenomics was investigated in rhizosphere soils.

Results
Amendment of SDZ to manure resulted in an increase in sul2 genes in manure. However, abundances of sul genes in rhizosphere soils was strongly determined by plant growth and not by soil treatments with SDZ-manure, which was also the case for the bacterial community composition. Effects of SDZ at low or undetectable levels in leek rhizosphere soil became evident by bacterial association network and resistome analyses, and also in roots and leaves by SDZ-selective bacterial cultivation.

Conclusions
Antibiotic residues present in animal manure can lead to an increase in antibiotic resistances in food products. Plants play an important role in selection of antibiotic resistance genes present in manured soil. Transmission of antibiotic resistances via manure to the soil–plant ecosystem must be placed into the context of soils as vast reservoirs of ARGs.
A yield curvature model considering axial compression ratio
Authors: Zhu Yanyan , Zhong Jian 
Published: September 2023

AbstractThis study proposed a yield curvature prediction model considering axial compression ratio with exponential function which is improved on the basis of the specification effective yield curvature prediction model. Parametric moment–curvature curves approach was used to verify that the yield curvature is greatly affected by the section size, the yield strength of longitudinal steel bar and the axial compression ratio. On the basis, the yield curvature under different levels was obtained by Xtract and parametric moment–curvature curves approach, the result shows that with the increase of axial compression ratio, the yield curvature also increases, which is roughly a linear relationship. Subsequently, combined with the specification and considering the influence of axial compression ratio, a new yield curvature prediction model is proposed based on a massive sample space obtained by parametric moment–curvature curves approach. Moreover, by comparing with the experimental database of PEER, the accuracy of new prediction model is verified, and the result shows that the new prediction model is suitable for estimating yield curvature of square section columns.
Silent subepicardial hematoma due to spontaneous coronary artery rupture in a patient with Graves’ disease
Authors: Matsuzaki Kanji , Mitomi Kisato , Imai Akito , Watanabe Yasunori 
Published: September 2023

Abstract
Background
Subepicardial hematoma due to spontaneous coronary artery rupture (SCAR) is exceedingly rare.

Case presentation
An asymptomatic 68-year-old woman with Graves’ disease was introduced to us because of an abnormal right hilar shadow. Graves’ disease had been treated effectively with thiamazole. Without any chest trauma or disease related to coronary artery rupture, computed tomography revealed a 44-mm mass lesion that occupied the front of the right atrium. Two branches arising from the proximal right coronary artery surrounded the lesion and appeared to be the feeding vessels. We suspected a tumor and performed radical surgery. The lesion was completely removed using an ultrasonic scalpel and revealed as organized subepicardial hematoma.

Conclusion
This is the rare surgical case of organized subepicardial hematoma due to SCAR. A high grade of suspicion is necessary for the correct diagnosis. Graves’ disease is not considered as an underlying disease of SCAR.