Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of congenital syphilis in Fortaleza, Brazil: A retrospective case-control study

Congenital syphilis (CS) is a significant public health problem in Brazil. Despite efforts to increase syphilis testing and treatment among pregnant women, rates of CS in the country remain high. We conducted a retrospective case-control study to identify potential associations between the mothers’ sociodemographic characteristics, clinical factors related to the current and previous pregnancies, and the occurrence of CS among newborns in Fortaleza, a populous city with one of the highest incidences of CS in Brazil. Data from newborns diagnosed with CS between 2017 and 2020 were extracted from SINAN, the national database for notifiable diseases. Data from women who had delivered an infant with CS were extracted from SINASC, the national database for registration of live births, and linked with their infant’s data. CS cases and non-CS controls were matched by year of birth at a ratio of 1:3 respectively. Potential associations were estimated using a multivariate regression model accounting for sociodemographic, obstetric, and antenatal care-related factors. Epidemiological data from 8,744 live births were included in the analysis, including 2,186 cases and 6,588 controls. The final multivariate regression model identified increased odds of delivering an infant with CS among pregnant women and girls aged below 20 years (OR 1.29), single women (OR 1.48), women who had less than 8 years of formal education (OR 2.42), women who delivered in a public hospital (OR 6.92), women who had more than 4 previous pregnancies (OR 1.60), and women who had one or more prior fetal loss (OR 1.19). The odds of delivering an infant with CS also increased as the number of antenatal visits decreased. Women who did not attend any antenatal visits had 3.94 times the odds of delivering an infant with CS compared to women who attended 7 or more visits. Our study found that increased odds of delivering an infant with CS were highly associated with factors related to socioeconomic vulnerability. These determinants not only affect the access to essential antenatal care services, but also the continuity and quality of such preventive measures. Future policies aimed at reducing the incidence of CS should not only target those pregnant women and adolescents with identifiable risk factors for testing, but also assure high quality care, treatment and follow-up for this group.
Enhancing Cryptocurrency Price Forecasting: a Comparative Analysis of Feature Quantity and Forecasting Models

Cryptocurrencies such as Bitcoin have become a popular digital currency in recent years, attracting investors and traders worldwide. However, the volatile nature of Bitcoin prices poses a challenge for predicting future prices accurately. To this end, this articles examines how different forecasting models for Bitcoin prices are affected by the number of features and which models are more effective at forecasting. We apply different ARIMA, SVM, LSTM, models on the Bitcoin historical dataset from Kaggle to predict the prices. With one-minute intervals, the dataset spans from 2012-01-01 to 2021-03-31. The data is separated into subsets for training (70%) and testing (30%) to get performance results of the models. The results show that the LSTM model performs better only when the appropriate features are selected. The study emphasizes the importance of selecting appropriate features to improve forecasting accuracy, as it can significantly impact the prediction of Bitcoin prices.
PixelMRF A Deep Markov Random Field for Image Generation

In this work we introduce a new graphical model for generative image modeling. The popular PixelCNN has utilized deep graphical models to represent images as directed, acyclic Markov chains. The limitations enforced by the directed, acyclic nature of Pix-elCNN have restricted the model to conceptualize an image as a sequence of directional dependencies, where each pixel is conditionally dependent on the pixels before it in row-major order. We instead propose PixelMRF, a deep graphical model that fully captures the conditional distributions for each pixel of an image. PixelMRF achieves this goal by representing the pixels in an image as a undirected Markov random ﬁeld, and so allows the dependencies that PixelCNN lacks.
MicroRNAs are deeply linked to the emergence of the complex octopus brain

Soft-bodied cephalopods such as the octopus are exceptionally intelligent invertebrates with a highly complex nervous system that evolved independently from vertebrates. Because of elevated RNA editing in their nervous tissues, we hypothesized that RNA regulation may play a major role in the cognitive success of this group. We thus profiled mRNAs and small RNAs in 18 tissues of the common octopus. We show that the major RNA innovation of soft-bodied cephalopods is a massive expansion of the miRNA gene repertoire. These novel miRNAs were primarily expressed in neuronal tissues, during development, and had conserved and thus likely functional target sites. The only comparable miRNA expansions happened, strikingly, in vertebrates. Thus, we propose that miRNAs are intimately linked to the evolution of complex animal brains. One-Sentence Summary miRNAs are deeply linked to the emergence of complex brains.
Advances in Clinical Medical Research and Healthcare Delivery Advances in Clinical Medical Research and Healthcare Delivery

Abstract BackgroundBackground: Human leukocyte antigen (HLA) class II has shown potential in determining prognosis, understanding medication reactions, and predicting onset of Graves’ disease. The aim of this study is to further investigate the association between Graves’ disease and HLA class II, specifically HLA-DQ and HLA-DR, via meta-analysis to find HLAs that can be further examined for prognostic reasons. MethodsMethods: Statistical analysis was performed to determine if variants of HLA-DQA1, HLA-DQB1, or HLA-DRB1 were associated with significantly altered odds of Graves’ disease. A minimum of three studies pertaining to a particular HLA was required for inclusion. Studies were excluded if they lacked inclusion criteria. ResultsResults: 27 studies were included. Odds of associated HLAs in Graves’ disease patients versus controls were increased for HLA-DQA1*03:01 (OR = 1.30 [1.03, 1.63], I² =0%, p DiscussionDiscussion: These findings offer new connections between HLAs and Graves’ disease that may be applied to prognosis, treatment, and autoimmune mechanistic understanding for MHC class II in Graves’ disease.
Scholarly Commons @ Baptist Health South Florida Scholarly Commons @ Baptist Health South Florida

Periprosthetic joint infections remain challenging for orthopaedic surgeons. These are typically treated with 2-stage revision with an antibiotic spacer and arthroplasty reimplantation after infection eradication. We report a novel technique to create an antibiotic cement spacer construct in the setting of signi ﬁ cant acetabular medial wall destruction due to osteolysis and infection. The medial wall of the acetabulum was reconstructed using antibiotic cement with 2 screws acting as a rebar. An acetabular liner was then cemented into place forming a cement construct similar to a reconstruction cage in function. This technique created a ﬁ rm acetabular construct that allowed for the placement of a stable articulating spacer. The spacer allowed for infection eradication and was successfully converted into a revision total hip arthroplasty. © 2018 The Authors. Published by Elsevier Inc. on behalf of The American Association of Hip and Knee Surgeons. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
The Aquila Digital Community The Aquila Digital Community

Although incorporating detailed reproductive data into all stock assessments is not a practical goal, the need to understand how reproductive biology affects population productivity is being increasingly recognized. More research focused on reproductive biology—coupled with a shift towards a resilience perspective in ﬁsheries science—is resulting in challenges to many long-held assumptions; the emergence of important new issues; and identiﬁcation of the need to improve data and methods used in reproductive studies. Typically, data for reproductive studies are based on an assessment of gonadal development, which is most accurately evaluated with histology. This special section of Marine and Coastal Fisheries contains contributions from a workshop on the gonadal histology of ﬁshes that was held in Cadiz, Spain, during June 2009. These papers cover a wide range of species and reproductive topics while introducing improved and new histological techniques. In this introduction, we address the following needs: (1) to employ standardization, thereby improving our ability to conduct comparative studies; (2) to better understand patterns of gonadal development and spawning events over time; and (3) to move beyond the spawning stock biomass paradigm. We identify the contributions of special section papers to these topics and conclude by suggesting needs
Mg 2+ -free ATP Regulates Native Cytoplasmic Dynein’s Processivity

Cytoplasmic dynein, a microtubule-based motor protein is responsible for many cellular functions ranging from cargo transport to cell division. The various functions are carried out by a single isoform of cytoplasmic dynein, thus requiring different forms of motor regulation. A possible pathway to regulate motor function was revealed in optical trap experiments. Switching motor function from single steps to processive runs could be achieved by changing Mg 2+ and ATP concentrations. Here we confirm by single molecule TIRF microscopy that a native cytoplasmic dynein dimer is able to switch to processive runs of more than 680 consecutive steps or 5.5 micrometres. We also identified the ratio of Mg 2+ -free ATP to Mg.ATP as the regulating factor and propose a model for dynein processive stepping.
Digital Commons @ New Haven Digital Commons @ New Haven

The Fragile X-related disorders (FXDs) are members of the Repeat Expansion Diseases, a group of human genetic conditions resulting from expansion of a specific tandem repeat. The FXDs result from expansion of a CGG/CCG repeat tract in the 5 ’ UTR of the FMR1 gene. While expansion in a FXD mouse model is known to require some mismatch repair (MMR) proteins, our previous work and work in mouse models of another Repeat Expansion Disease show that early events in the base excision repair (BER) pathway play a role in the expansion process. One model for repeat expansion proposes that a non-canonical MMR process makes use of the nicks generated early in BER to load the MMR machinery that then generates expansions. However, we show here that heterozygosity for a Y265C mutation in Pol β , a key polymerase in the BER pathway, is enough to significantly reduce both the number of expansions seen in paternal gametes and the extent of somatic expansion in some tissues of the FXD mouse. These data suggest that events in the BER pathway downstream of the generation of nicks are also important for repeat expansion. Somewhat surprisingly, while the number of expansions is smaller, the average size of the residual expansions is larger than that seen in WT animals. This may have interesting implications for the mechanism by which BER generates expansions.
Characterization of type 2 diabetes-related immune response heterogeneity to COVID-19 vaccines via single-cell landscape analyses

Vaccines provide the most ideal protection against COVID-19, but variants of concern are highly transmissible and less sensitive to vaccine-elicited antibodies. It is unknown whether patients with type 2 diabetes (T2D) can develop vaccine-elicited immune responses equal to those in healthy individuals. Impaired neutralizing antibodies and spike speci�c antibodies against SARS-CoV-2 have been identi�ed in T2D patients vaccinated with inactivated vaccine. We therefore investigated changes in the peripheral immune systems of vaccinated T2D patients using single-cell RNA-sequencing. The immune cell phenotypes comprised antigen-presenting (APC), T, and plasma cell recon�gurations. Humoral immune damage to plasma cells exhibited impaired protein synthesis, processing, and transport. APCs were characterized by in�ammation following human leukocyte antigen downregulation, neutrophil recruitment, and type I interferon pathway defects. Oxidative stress yielded abnormal hyper-inammation comprising hyper-cytotoxic CD4 + and CD8 + T cells. There was also a decreased subset of SARS-CoV-2-specic B and T cell receptors. These results provide mechanistic insights into the COVID-19 vaccine-elicited immune responses of T2D patients.
Heritage corridor and a primary theoretic framework on study of integ rated conservation of the great canal

As a mixture of the trend of regionalization in cultural heritage conservation and thoughts on greenway, heritage corridors emp hasize not only cultural significance but also ecological and economical value. Though possessing many cultural heritages with a linear form, China has not any regional conservation framework in its heritage system, which give a great impac t on the conservation of those heritages, including The Great Canal. It is point ed out in the article that the construction of heritage corridor in China is not only the need of conservation ,but also the need of constructing foreseeing an efficient ecological infrastructure and the need of further development of cultu ral tourism. It is also discussed briefly in the article how to plan heritage co rridor in China with the case of The Great Canal in the context of rapid urbaniz ation and the project of South Water to North Transfer.
Revisiting the cosmic string origin of GW190521

For the first time we analyse gravitational-wave strain data using waveforms constructed from strong gravity simulations of cosmic string loops collapsing to Schwarzschild black holes; a previously unconsidered source. Since the expected signal is dominated by a black-hole ringdown, it can mimic the observed gravitational waves from high-mass binary black hole mergers. To illustrate this, we consider GW190521, a short duration gravitational-wave event observed in the third LIGO--Virgo--KAGRA observing run. We show that describing this event as a collapsing cosmic string loop is favoured over previous cosmic string analyses by an approximate log Bayes factor of $22$. The binary black hole hypothesis is still preferred, mostly because the cosmic string remnant is non-spinning. It remains an open question whether a spinning remnant could form from loops with angular momentum, but if possible, it would likely bring into contention the binary black hole preference. Finally, we suggest that searches for ringdown-only waveforms would be a viable approach for identifying collapsing cosmic string events. This work opens up an important new direction for the cosmic-string and gravitational-wave communities.
Investigation Related to Influence of Multi-GPUs on Parallel Algorithms Based on PyTorch Distributed

This paper designs experiments to investigate the impact of different GPU counts on occupancy, accuracy, loss values and time of the PyTorch distributed data parallel and model parallel module in LeNet VGG16 and ResNet models respectively. PyTorch is a powerful deep learning framework but due to the expansion of the database size, it cannot load it all into memory at once. So, it divides large-scale data into small chunks, which are then processed simultaneously on multiple processors or computers, and finally the results are combined. But this leads to a change in the model results. Therefore, it brings out the experiment as follow, n LeNet and VGG16 models, model parallel experiments with different numbers of GPUs were conducted on these both models, and about ResNet model in this paper, performed data parallelism experiments with different number of GPUs. The findings revealed that, in the model parallel experiments, the number of GPUs employed did not have a significant impact on the floating accuracy of the results. However, a slight variation in the accuracy of the output answers was observed among the LeNet models, with an overall average accuracy of 26.2%. In the data parallel experiment, it was observed that the running time increased with an increasing number of GPUs. Specifically, the running time using one GPU was measured at 265.173 seconds, while using five GPUs resulted in a running time of 347.273 seconds. These results suggest that the utilization of multiple GPUs in data parallelism leads to an increase in operating time.
Positive and negative plant-plant interactions in�uence seedling establishment at both high and low elevations

According to the stress gradient hypothesis (SGH), plant-plant interactions are expected to shift from predominantly negative (i.e. competition) to predominantly positive (i.e. facilitation) along gradients of environmental severity. The SGH has been particularly useful as a framework for understanding how plants interact with each other across elevation gradients, partly as a proxy for future responses to climate change. However, most experiments examine the net effects of interactions by growing plants in either the presence or absence of neighbours, thereby neglecting the interplay of both negative and positive effects acting simultaneously within communities. To partially unravel these effects, we tested how the seedling establishment of 10 montane grassland plants varied in the presence versus absence of plant communities at two sites along an elevation gradient. We created a third experimental treatment that retained the main hypothesised bene�ts of plant neighbours (microsite amelioration), while reducing a key negative effect (competition for soil resources). In contrast to predictions of the SGH, we found evidence for net positive effects of vegetation at the low site, and net negative effects at the high site. Interestingly, the surprisingly negative effects of plant neighbours at high elevation were driven by high establishment rates of low elevation grasses in bare soil plots. At both sites, establishment rates were highest in arti�cial vegetation (after excluding two low elevation grasses at the high site), indicating that positive effects of above-ground vegetation are partially offset by their negative effects. Our results demonstrate that both competition and facilitation act jointly to affect community structure across environmental gradients, while challenging the view that competition is weak at high elevation in temperate mountain regions. Consequently, plant-plant interactions are likely to in�uence the establishment of new, and persistence of resident, species in mountain plant communities as environments change.
Characterisation of crevicular fluid microbiota in primary Sjögren's syndrome.

OBJECTIVES To describe the taxonomy of the microbiota in crevicular fluid of primary Sjögren's syndrome (pSS) patients, and evaluate its association with clinical/serological variables, and oral quality of life. METHODS Observational study that included 48 pSS without diabetes mellitus, no active neoplasia, no antibiotic use in the previous two weeks, and no current active infection. We registered demographics, oral/ocular sicca symptoms, parotid enlargement and anti-Ro/La serology. We assessed the non-stimulated whole salivary flow (NSWSF), the EULAR Sjögren's Syndrome Patient Reported Index (ESSPRI), and the Xerostomia-related Quality of Life Scale (XeQoLS). Two periodontists determined the presence of periodontal disease and collected crevicular fluid from 6 teeth using filter paper. Samples were frozen at -86°C until processing. We included 17 sex- and age-matched control subjects. Bacterial DNA was extracted from the crevicular fluid sample using a commercial kit. 16SrRNA V3-V4 region was sequenced using reversible adaptor technology. Sequences were pre-processed and analysed using QIIME2 and phyloseq software programs. Functionality profiles were predicted using the Tax4Fun2 package. RESULTS PSS patients had more bacteria of the genera Prevotella, Streptococcus, Veillonella, Fusobacterium, and Leptotrichia and fewer bacteria of the genus Selenomonas than controls. The pSS microbiota contained more genes encoding accessory secretory proteins. Microbiota also differed between patients with anti-Ro/La status, parotid gland enlargement, and periodontal disease severity, but did not correlate with NSWSF and XeQoLS. CONCLUSIONS The crevicular fluid microbiota of pSS patients and controls differed significantly, even in SSP patients depending on their serology, parotid gland enlargement, and periodontal disease status.
Public emotional dynamics toward AIGC content generation across social media platform

Given the widespread popularity of interactive AI models like ChatGPT, public opinion on emerging artificial intelligence generated content(AIGC) has been extensively debated. Pessimists believe that AIGC will replace humans in the future, and optimists think that it will further liberate productivity. Public emotions play a crucial role on social media platforms. They can provide valuable insights into the public's opinions, attitudes, and behaviors. There is a lack of research on the analysis of social group emotions triggered by AIGC content, and even more on the cross-platform differences of group emotions. This study fills the research gap by connecting the theory of group dynamics with emotions in social media. Specifically, we develop a scientific group emotion calculation and visualization system based on chains of communication. The system is capable of crawling data in real time and presenting the current state of group emotions in a fine-grained manner. We then analyze which group dynamic factors drive different public emotions towards nine AIGC products on the three most popular social media platforms in China. Finally, we obtain four main findings. First, Douyin is the only platform with negative group emotion on emerging AI technologies. Second, Weibo users prefer extreme emotions more than others. Third, the group emotion varies by education and age. It is negatively correlated with senior high school or lower and 25 or younger, and positively correlated with bachelor's degree or higher and 26-35. Fourth, the group emotion polarization increases with more posts without comments and celebrity publishers. By analyzing the key dynamic factors of group emotions to AIGC on various social media platforms, we can improve our products and services, develop more effective marketing strategies, and create more accurate and effective AI models to solve complex problems.