Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous Support Promotes Obstetric Labor Progress and Vaginal Delivery in Primiparous Women – A Randomized Controlled Study

Background: Obstetric labor and childbirth are mostly regarded as a physiological process, whereas social, cultural, psychological and transcendental aspects have received less attention. Labor support has been suggested to promote labor progress. The aim of this study was to investigate whether continuous labor support by a midwife promotes labor progress and vaginal delivery. Material and Methods: A randomized controlled study at a university hospital in Sweden in 2015–17. Primiparous women with singleton pregnancy and spontaneous labor onset were randomized to continuous support (n = 30) or standard care (n = 29) during delivery. The primary outcome was the duration of active labor. Secondary outcomes were delivery mode, women's need of labor analgesia and satisfaction with delivery, maternal cortisol levels, and neonatal morbidity. Results: Continuous support was followed by shorter active labor 11.0 ± 5.7 h compared to 13.7 ± 3.9 h with standard care (p = 0.001). Women in the continuous support group tended to have lower cortisol levels and low cortisol during the first (p = 0.02) and second (p = 0.04) stages of labor were correlated with shorter active labor. Continuous support was followed by spontaneous delivery in 73%, instrumental delivery in 24% and emergency cesarean section in 3% in contrast to standard care which was followed by spontaneous delivery in 62%, instrumental delivery in 24% and cesarean in 14% (p = 0.19). The continuous support group received combined analgesic methods more often (p = 0.04). Women's satisfaction with delivery and neonatal morbidity were comparable. Conclusion: Continuous labor support was followed by shorter active labor compared to standard care. Women with continuous support had a high rate of vaginal delivery and tended to have lower cortisol levels during all stages of active labor reflecting a lower stress level. Low cortisol was correlated to shorter active labor. Based on these results, we recommend continuous labor support for all primiparous women during active labor.
Early Diffusion of SARS-CoV-2 Infection in the Inner Area of the Italian Sardinia Island

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for the coronavirus disease 2019 (COVID-19) pandemic, which started as a severe pneumonia outbreak in Wuhan, China, in December 2019. Italy has been the first European country affected by the pandemic, registering a total of 300,363 cases and 35,741 deaths until September 24, 2020. The geographical distribution of SARS-CoV-2 in Italy during early 2020 has not been homogeneous, including regions severely affected as well as administrative areas being only slightly interested by the infection. Among the latter, Sardinia represents one of the lowest incidence areas likely due to its insular nature. Methods Next-generation sequencing of a small number of complete viral genomes from clinical samples and their virologic and phylogenetic characterization was performed. Results We provide a first overview of the SARS-CoV-2 genomic diversity in Sardinia in the early phase of the March–May 2020 pandemic based on viral genomes isolated in the most inner regional hospital of the island. Our analysis revealed a remarkable genetic diversity in local SARS-CoV-2 viral genomes, showing the presence of at least four different clusters that can be distinguished by specific amino acid substitutions. Based on epidemiological information, these sequences can be linked to at least eight different clusters of infection, four of which likely originates from imported cases. In addition, the presence of amino acid substitutions that were not previously reported in Italian patients has been observed, asking for further investigations in a wider population to assess their prevalence and dynamics of emergence during the pandemic. Conclusion The present study provides a snapshot of the initial phases of the SARS-CoV-2 infection in inner area of the Sardinia Island, showing an unexpected genomic diversity.
Intercropping With Aromatic Plants Increased the Soil Organic Matter Content and Changed the Microbial Community in a Pear Orchard

Intercropping influences the soil microbiota via litter and root exudate inputs, but the mechanisms by which root exudates mediate the soil microbial community and soil organic matter (SOM) are still unclear. In this study, we selected three aromatic plants (Ocimum basilicum, Tr1; Satureja hortensis, Tr2; Ageratum houstonianum, Tr3) as intercrops that separately grew between rows of pear trees, and no plants were grown as the control in a pear orchard during the spring–summer season for 3 years. The soil from each plot was collected using a stainless-steel corer by five-point sampling between rows of pear trees. The bacterial and fungal communities of the different aromatic intercrops were analyzed by 16S and ITS rRNA gene amplicon sequencing; their functional profiles were predicted by PICRUSt and FUNGuild analyses. The root exudates of the aromatic plants were analyzed by a liquid chromatography-tandem mass spectrometry (LC-MS) system. Compared with the control treatment, all intercropping treatments with aromatic plants significantly increased SOM and soil water content and decreased pH values. The contents of total nitrogen and alkali-hydrolyzable nitrogen in Tr1 and Tr2 were higher than those in Tr3. In Tr3 soil, the relative content of saccharides increased little, whereas the changes in amine (increases) and alcohols (decreases) were rapid. Ageratum houstonianum intercropping decreased the microbial community diversity and significantly influenced the relative abundances of the dominant microbiota (Actinobacteria, Verrucomicrobia, Gemmatimonadetes, Cyanobacteria, Ascomycota, and Basidiomycota) at the phylum, class, and order levels, which increased the assemblage of functional groups (nitrite ammonification, nitrate ammonification, and ureolysis groups). Our study suggested that the main root exudates from aromatic plants shaped the microbial diversity, structure, and functional groups related to the N cycle during SOM mineralization and that intercropping with aromatic plants (especially basil and summer savory) increased N release in the orchard soil.
Natural convection and solid phase combustion

Self-propagating high-temperature synthesis (SHS) is a combustion process involving two or more solid reactants. The typical SHS configuration consists of a cylindrical preform of mixed powders, placed in an inert gas chamber, and ignited at one end. In past studies, interaction between the solid phase and the ambient gas phase has been limited to heat losses from the solid; the influence of natural convection on the solid phase has never been considered. In this study, computational fluid dynamics (CFD) is used, and it is shown that intense convection flow develops in the proximity of the combustion front. Gas flows adjacent to reacted solid material, heats up, and when it reaches the unreacted solid heat is transferred from the gas to the solid phase, which aids solid phase thermal conduction in preheating the material. The effect is stronger than expected, and it could stabilize the combustion of structured reactants like roll-ups of foils and wires. Combustion parallel and antiparallel to gravity is investigated for different burning velocities. At low propagation velocities, the natural convection cell forms a torus that is seated above the combustion front. At high propagation velocities, the convection flow cannot track the combustion front, and Tollmien-Schlichting waves form. Constant front propagation and planar oscillations of the combustion front lead to increasingly complex flows. Finally, the heat exchange between the gas and solid for constant front propagation is compared to analytical solutions.
The Impact of Particulate Matter (PM2.5) on Human Retinal Development in hESC-Derived Retinal Organoids

Increasing evidence demonstrated that PM2.5 could cross the placenta and fetal blood–brain barrier, causing neurotoxicity of embryonic development. The retina, an embryologic extension of the central nervous system, is extremely sensitive and vulnerable to environmental insults. The adverse effects of PM2.5 exposure on the retina during embryonic neurodevelopment are still largely unknown. Our goal was to investigate the effect of PM2.5 on human retinal development, which was recapitulated by human embryonic stem cell (hESC)-derived retinal organoids (hEROs). In the present study, using the hEROs as the model, the influences and the mechanisms of PM2.5 on the developing retina were analyzed. It demonstrated that the formation rate of the hERO-derived neural retina (NR) was affected by PM2.5 in a concentration dosage-dependent manner. The areas of hEROs and the thickness of hERO-NRs were significantly reduced after PM2.5 exposure at the concentration of 25, 50, and 100 μg/ml, which was due to the decrease of proliferation and the increase of apoptosis. Although we did not spot significant effects on retinal differentiation, PM2.5 exposure did lead to hERO-NR cell disarranging and structural disorder, especially retinal ganglion cell dislocation. Transcriptome analysis showed that PM2.5 treatment was significantly associated with the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/AKT pathways and reduced the level of the fibroblast growth factors (FGFs), particularly FGF8 and FGF10. These results provided evidence that PM2.5 exposure potentially inhibited proliferation and increased apoptosis at the early development stage of the human NR, probably through the MAPK and PI3K/Akt pathway. Our study suggested that exposure to PM2.5 suppressed cell proliferation and promoted cell apoptosis, thereby contributing to abnormal human retinal development.
Towards Computer-Based Automated Screening of Dementia Through Spontaneous Speech

Dementia, a prevalent disorder of the brain, has negative effects on individuals and society. This paper concerns using Spontaneous Speech (ADReSS) Challenge of Interspeech 2020 to classify Alzheimer's dementia. We used (1) VGGish, a deep, pretrained, Tensorflow model as an audio feature extractor, and Scikit-learn classifiers to detect signs of dementia in speech. Three classifiers (LinearSVM, Perceptron, 1NN) were 59.1% accurate, which was 3% above the best-performing baseline models trained on the acoustic features used in the challenge. We also proposed (2) DemCNN, a new PyTorch raw waveform-based convolutional neural network model that was 63.6% accurate, 7% more accurate then the best-performing baseline linear discriminant analysis model. We discovered that audio transfer learning with a pretrained VGGish feature extractor performs better than the baseline approach using automatically extracted acoustic features. Our DepCNN exhibits good generalization capabilities. Both methods presented in this paper offer progress toward new, innovative, and more effective computer-based screening of dementia through spontaneous speech.
Long Non-coding RNA Expression Patterns in Stomach Adenocarcinoma Serve as an Indicator of Tumor Mutation Burden and Are Associated With Tumor-Infiltrating Lymphocytes and Microsatellite Instability

Long non-coding RNAs (lncRNAs) are crucial in controlling important aspects of tumor immunity. However, whether the expression pattern of lncRNAs in stomach adenocarcinoma (STAD) reflects tumor immunity is not fully understood. We screened differentially expressed lncRNAs (DElncRNAs) between high and low tumor mutation burden (TMB) STAD samples. Using the least absolute shrinkage and selection operator method, 33 DElncRNAs were chosen to establish a lncRNA-based signature classifier for predicting TMB levels. The accuracy of the 33-lncRNA-based signature classifier was 0.970 in the training set and 0.950 in the test set, suggesting the expression patterns of the 33 lncRNAs may be an indicator of TMB in STAD. Survival analysis showed that a lower classifier index reflected better prognosis for STAD patients, and the index showed correlation with expression of immune checkpoint molecules (PD1, PDL1, and CTLA4), tumor-infiltrating lymphocytes, and microsatellite instability. In conclusion, STAD samples with different tumor mutation burdens have different lncRNA expression patterns. The 33-lncRNA-based signature classifier index may be an indicator of TMB and is associated expression of immune checkpoints, tumor-infiltrating lymphocytes, and microsatellite instability.
Interpersonal Relations Within the Context of Resource Groups for People With Severe Mental Illness: A Narrative Approach

Objective: The resource group method intends to promote patients' agency and self-management and to organize meaningful partnerships between patients and their informal and formal support systems. The aim of this study was to enhance the understanding of interpersonal dynamics that arise within resource groups for people with severe mental illness. Insight into these unfolding processes would enable improved implementation of the resource group method so that it contributes to establishing a positive social environment, which can lead to more enduring recovery. Methodology: We performed a narrative analysis of transcripts and field notes obtained in a longitudinal, qualitative study on the resource group method. The stories of four different resource groups were reconstructed and analyzed in depth. Data included a total of 36 interviews (with patients, significant others, and mental health professionals) and 18 observations of resource group meetings. Results: The degree to which the resource group method actually contributes to recovery was based on the extent to which the existing roles of and patterns between the patient and his/her resource group members were altered. Breaking through old patterns of inequality and the joint search for a new balance in relationships proved to be crucial processes for establishing an empowering resource group. The four cases showed that it takes time, patience, and small steps back and forth to overcome the struggles and fears related to finding new ways of relating to each other. An honest and reflective atmosphere in which all participants are encouraged to participate and be curious about themselves and each other is essential for changes in interpersonal dynamics to emerge. Such changes pave the way for individuals with SMI to find their own voices and pursue their unique recovery journeys. Conclusions: The functioning of the resource group and the ability of the involved members to respond in new ways are important when working toward the patient's recovery goals. The resource group method should therefore not be considered an intervention to organize informal support for the patient, but a platform to expose and adjust the functioning of the patient's social network as a whole.
A Novel Real-Time PCR Assay for the Rapid Detection of Virulent Streptococcus equi Subspecies zooepidemicus—An Emerging Pathogen of Swine

Streptococcus equi subspecies zooepidemicus, a zoonotic bacterial pathogen caused a series of outbreaks with high mortality affecting swine herds in multiple locations of the USA and Canada in 2019. Further genetic analysis revealed that this agent clustered with ATCC 35246, a S. zooepidemicus strain associated with high mortality outbreaks in swine herds of China originally reported in 1977. Rapid and accurate diagnosis is absolutely critical for controlling and limiting further spread of this emerging disease of swine. Currently available diagnostic methods including bacteriological examination and PCR assays do not distinguish between the virulent strains and avirulent commensal strains of S. zooepidemicus, which is critical given that this pathogen is a normal inhabitant of the swine respiratory tract. Based on comparative analyses of whole genome sequences of the virulent isolates and avirulent sequences, we identified a region in the SzM gene that is highly conserved and restricted to virulent S. zooepidemicus strains. We developed and validated a novel probe-based real-time PCR targeting the conserved region of SzM. The assay was highly sensitive and specific to the virulent swine isolates of Streptococcus equi subspecies zooepidemicus. No cross reactivity was observed with avirulent S. zooepidemicus isolates as well as other streptococcal species and a panel of porcine respiratory bacterial and viral pathogens. The PCR efficiency of the assay was 96.64 % and was able to detect as little as 20 fg of the bacterial DNA. We then validated the diagnostic sensitivity and specificity of the new PCR assay using a panel of clinical samples (n = 57) and found that the assay has 100% sensitivity and specificity as compared to bacteriological culture method. In summary, the PCR assay will be an extremely valuable tool for the rapid accurate detection of virulent swine S. zooepidemicus isolates and directly from clinical samples.
Quantifying Signal Quality From Unimodal and Multimodal Sources: Application to EEG With Ocular and Motion Artifacts

With prevalence of electrophysiological data collected outside of the laboratory from portable, non-invasive modalities growing at a rapid rate, the quality of these recorded data, if not adequate, could affect the effectiveness of medical devices that depend of them. In this work, we propose novel methods to evaluate electrophysiological signal quality to determine how much of the data represents the physiological source of interest. Data driven models are investigated through Bayesian decision and deep learning-based methods to score unimodal (signal and noise recorded on same device) and multimodal (signal and noise each recorded from different devices) data, respectively. We validate these methods and models on three electroencephalography (EEG) data sets (N = 60 subjects) to score EEG quality based on the presence of ocular artifacts with our unimodal method and motion artifacts with our multimodal method. Further, we apply our unimodal source method to compare the performance of two different artifact removal algorithms. Our results show we are able to effectively score EEG data using both methods and apply our method to evaluate the performance of other artifact removal algorithms that target ocular artifacts. Methods developed and validated here can be used to assess data quality and evaluate the effectiveness of certain noise-reduction algorithms.
Climate and Health in Buenos Aires: A Review on Climate Impact on Human Health Studies Between 1995 and 2015

In this review, seven pieces of research on climate variability and its impact on human health in Buenos Aires City between 1995 and 2015 were evaluated. The review highlighted continuities and ruptures in the methodology, variables, and statistics data of the research, considering their similarities and differences in the period of study and the methodology applied. Contributions, pending issues, and public policies on climate change challenges in the city aimed at improving living conditions were considered. Six studies contributed evidence on the relationship between climate and health and its impacts on the population; two studies suggested the development of early warning systems and one study is a preliminary approach.
The Relationship Between the Need to Belong and Nature Relatedness: The Moderating Role of Independent Self-Construal

The perception of the relationship between humans and nature is important for promoting not only pro-environmental behaviors but also psychological well-being. The present research explored how people’s self-construal would moderate the relationship between the need to belong, the desire for social acceptance and connectedness and perceived nature relatedness. Two studies using community samples with diverse demographic characteristics in two different cultures (Study 1: the United States; Study 2: Singapore) obtained consistent findings. The results showed that independent self-construal, which emphasizes separateness from others in the social contexts, moderated the relationship between the need to belong and nature relatedness. Specifically, the need to belong was negatively associated with nature relatedness among people with a stronger independent self-construal, while this pattern was not significant among those with a weaker independent self-construal. No evidence for the moderating role of interdependent self-construal was found in the two studies. These findings highlighted the importance of non-nature experience in understanding people’s perception of human–nature relationships.
The Arabic ontology - an Arabic wordnet with ontologically clean content

We present a formal Arabic wordnet built on the basis of a carefully designed ontology hereby referred to as the Arabic Ontology. The ontology provides a formal representation of the concepts that the Arabic terms convey, and its content was built with ontological analysis in mind, and benchmarked to scientific advances and rigorous knowledge sources as much as this is possible, rather than to only speakers’ beliefs as lexicons typically are. A comprehensive evaluation was conducted thereby demonstrating that the current version of the top-levels of the ontology can top the majority of the Arabic meanings. The ontology consists currently of about 1,800 well-investigated concepts in addition to 16,000 concepts that are partially validated. The ontology is accessible and searchable through a lexicographic search engine (http://ontology.birzeit.edu) that also includes about 150 Arabic-multilingual lexicons, and which are being mapped and enriched using the ontology. The ontology is fully mapped with Princeton WordNet, Wikidata, and other resources.
Edge Computing- and H∞-Switching-Based Networked Control for Frequency Control in Multi-Microgrids with Time Delays

The frequency stability of multi-microgrids is easily affected by random load fluctuations and intermittent renewable resources. Additionally, geographically distributed generation equipment usually cannot adopt the “point-to-point” dedicated communication scheme to realize the information exchange considering the construction and computation costs. Therefore, a H∞-switching frequency control strategy for multi-microgrids based on edge computing framework is proposed in this paper. Firstly, an edge computing device is set up in each microgrid to collect the operation statuses of local participating equipment and generate the control instructions to ensure the real-time local frequency stability. Secondly, the multihop data transmission process in edge computing environment is described as a cascade queuing model. Then, the frequency control system in each microgrid is described as a switching model dependent on the varying time delays. Finally, via constructing a Lyapunov function, the constraints of the controller gains ensuring the H∞-damping performance for external load demands and the renewable outputs are derived at the same time. Simulation results show that compared with the traditional centralized control schemes, the peak value of our proposed edge computing framework is reduced by 32.51% compared with the traditional centralized control scheme. Moreover, under the same edge computing framework, the integral of absolute error (IAE) of frequency with the proposed H∞ control strategy can be reduced by 37.19% at least. Therefore, a better transient performance can be obtained with our proposed method.