Miracle-dz/UniFAR-FTUs huggingface dataset:
How Important Are Parental Age and Educational Level in Nonurgent Admissions to the Pediatric Emergency Department?

OBJECTIVE The aims of the present study were to investigate the reasons parents prefer the pediatric emergency department for nonurgent admissions and to evaluate the effect of parental age and educational level on nonurgent admissions and the relationship between the reasons for nonurgent admissions and child age. METHODS We conducted a cross-sectional survey at an emergency department of a tertiary care pediatric referral center. A questionnaire that was prepared to understand the reasons underlying nonurgent admissions was administered to the parents of 1033 children who were classified as nonurgent cases using the Pediatric Canadian Triage and Acuity Scale (4-5). RESULTS The most common reasons for nonurgent admissions were the concern for progression in child's complaints, the complaints with an onset outside working hours, and the parental perception that more cautious and better care is provided in the emergency department. The most urgent complaints from the parental perspective included fever (23.1%), vomiting (11.0%), and diarrhea (10.5%), respectively. The mean age of the mothers was 31.1 ± 5.9 years (17-51 years), and the mean age of the fathers was 34.94 ± 6.1 years (20-60 years). Parents younger than 30 years were more likely to prefer the emergency department due to convenience and economic reasons. Nonurgent admissions due to confidence in the emergency department were more frequent among parents who were primary school graduate. CONCLUSIONS It is critically important to examine why parents prefer the emergency department for nonurgent conditions of their children and to develop solution offers in this regard. The improvements to be made in the emergency department would both prioritize patients requiring urgent care and increase the productivity of emergency department staff.
Shallow Syntax in Deep Water

Shallow syntax provides an approximation of phrase-syntactic structure of sentences; it can be produced with high accuracy, and is computationally cheap to obtain. We investigate the role of shallow syntax-aware representations for NLP tasks using two techniques. First, we enhance the ELMo architecture to allow pretraining on predicted shallow syntactic parses, instead of just raw text, so that contextual embeddings make use of shallow syntactic context. Our second method involves shallow syntactic features obtained automatically on downstream task data. Neither approach leads to a significant gain on any of the four downstream tasks we considered relative to ELMo-only baselines. Further analysis using black-box probes confirms that our shallow-syntax-aware contextual embeddings do not transfer to linguistic tasks any more easily than ELMo's embeddings. We take these findings as evidence that ELMo-style pretraining discovers representations which make additional awareness of shallow syntax redundant.
Years of life lost due to diseases of the digestive system in Poland according to socioeconomic factors: a cross-sectional study

Objectives To analyse years of life lost (YLLs) due to digestive diseases in Poland according to: marital status, education, working status and place of residence. Design A cross-sectional study. Setting The study was based on a dataset containing information from death certificates of Poles who died in 2002 and in 2011. Participants The analysis covered records with codes K00–K93 according to the International Classification of Diseases and Related Health Problems, 10th Revision. Outcome measures YLL values were calculated using the Standard Expected Years of Life Lost measure. For each socioeconomic variable, the rate ratio (RR) was calculated as the quotient of YLLs in the less privileged group to the more privileged group. Results Among the categories of marital status, the smallest YLL values (per 10 000) were recorded among singles (men: 100.63 years in 2002, 121.10 years in 2011; women: 26.99, 33.33, respectively), and the most among divorced men (657.87, 689.32) and widowed women (173.97, 169.46). YLL analysis according to education level revealed the lowest values in people with higher education (men: 54.20, 57.66; women: 17.31, 18.31) and the highest in people with lower than secondary education (men: 178.85, 198.32; women: 104.95, 125.76). Being economically active was associated with a smaller YLL score (men: 39.93, 59.51; women: 10.31, 14.96) than being inactive (men: 340.54, 219.93; women: 126.86, 96.80). Urban residents had higher YLL score (men: 159.46, 174.18, women: 73.03, 78.12) than rural ones (men: 126.83, 137.11, women: 57.32, 57.56). In both sexes, RR according to education level and place of residence increased, and those according to marital status and working status decreased with time. Conclusions Activities aimed at reducing health inequalities in terms of YLL due to digestive diseases should be primarily addressed to inhabitants with lower than secondary education, divorced and widowed people, urban residents and those who are economically inactive.
Mysterious Coherence in Several-megaparsec Scales between Galaxy Rotation and Neighbor Motion

In our recent report, observational evidence supports that the rotational direction of a galaxy tends to be coherent with the average motion of its nearby neighbors within 1 Mpc. We extend the investigation to neighbors at farther distances in order to examine if such dynamical coherence is found even in large scales. The Calar Alto Legacy Integral Field Area (CALIFA) survey data and the NASA-Sloan Atlas (NSA) catalog are used. From the composite map of velocity distribution of “neighbor” galaxies within 15 Mpc from the CALIFA galaxies, the composite radial profiles of the luminosity-weighted mean velocity of neighbors are derived. These profiles show unexpectedly strong evidence of the dynamical coherence between the rotation of the CALIFA galaxies and the average line-of-sight motion of their neighbors within several-megaparsec distances. Such a signal is particularly strong when the neighbors are limited to red ones: the luminosity-weighted mean velocity at 1 < D ≤ 6 Mpc is as large as 30.6 ± 10.9 km s−1 (2.8σ significance to random spin-axis uncertainty) for central rotation (R ≤ Re). In the comparison of several subsamples, the dynamical coherence tends to be marginally stronger for the diffuse or kinematically well-aligned CALIFA galaxies. For this mysterious coherence in large scales, we cautiously suggest a scenario in which it results from a possible relationship between the long-term motion of a large-scale structure and the rotations of galaxies in it.
A Comparison of methods for computing the added resistance of ships using a high-order BEM

The validation of added resistan e is of importan e for both sin e it a(cid:27)e ts both e onomi al performan e and range. In order to provide guidan e to the designer at an early stage, it is important to have a reliable omputational tool. One su h tool is AEGIR. Full details of AEGIR an be found in [3℄. AEGIR is a time domain, three-dimensional, high-order Boundary Element Method (BEM). In this abstra t, we will present the theory for predi ting added resistan e using both Neumann-Kelvin and double-body (cid:29)ow linearizations. Both near-(cid:28)eld and far-(cid:28)eld approa hes are onsidered. Results are ompared with experimental data for three hull forms. The aim of this work is to determine whi h linearization and method is most reliable for general ship hulls. a body at steady forward speed. referen e frames employed:
The Translator's Amanuensis 2020

This paper is an exercise of imagination. Based on Kay’s (1980) inspiring idea of a translator’s amanuensis, we attempt to describe a post-editing tool that enables ubiquitous translation (Cronin 2010). We argue that a parallelism exists between media remediation (Bolter and Grusin 1999) and the shifting phase translation is undergoing, with machine translation post-editing having an impact on the global workflow of translated content. We take the hybridisation of traditional and machine translation processes as a starting point to envisage the features of forthcoming translation technologies. Results of previous surveys helped us to select features expected to play a central role: versatile devices to which we broadly refer as displayers would enable ubiquity; a relevant knowledge feature would provide human translators with a well-assorted repertoire of reliable sources; and an effort prediction feature would provide post-editors with reliable estimates of how much work lay ahead. Interacting with the Translator’s Amanuensis 2020 would not always be straightforward, however. Translators will have to adapt to richer ways of reading and visualising information. Ultimately, we argue that the Translator’s Amanuensis 2020 could benefit from existing Translation Studies concepts: the study of translation problems, translation competence models, and the ethics and sociology of translation.
Successive Point-of-Interest Recommendation With Local Differential Privacy

A point-of-interest (POI) recommendation system performs an important role in location-based services because it can help people to explore new locations and promote advertisers to launch advertisements at appropriate locations. The existing POI recommendation systems require raw check-in history of users, which might cause location privacy violations. Although there have been several matrix factorization (MF) based privacy-preserving recommendation systems, they can only focus on user-POI relationships without considering the human movements in check-in history. To tackle this problem, we design a successive POI recommendation framework with local differential privacy, named SPIREL. SPIREL uses two types of information derived from the check-in history as input for the factorization: a transition pattern between two POIs and the visit counts of POIs. We propose a novel objective function for learning the user-POI and POI-POI relationships simultaneously. We further integrate local differential privacy mechanisms in our proposed framework to prevent potential location privacy breaches. Experiments using four public datasets demonstrate that SPIREL achieves better POI recommendation quality while accomplishing stronger privacy preservation.
Menopausal Status and Physical Activity Are Independently Associated With Cardiovascular Risk Factors of Healthy Middle-Aged Women: Cross-Sectional and Longitudinal Evidence

Cardiovascular disease (CVD) is the primary cause of mortality in women in developed countries. CVD risk rises with age, yet for women there is a rapid increase in CVD risk that occurs after the onset of menopause. This observation suggests the presence of factors in the middle-aged women that accelerate the progression of CVD independent of chronological aging. Leisure time physical activity (LTPA) is a well-established protective factor against CVD. However, its role in attenuating atherogenic lipid profile changes and CVD risk in post-menopausal women has not been well-established. The present study is part of the Estrogenic Regulation of Muscle Apoptosis (ERMA) study, a population-based cohort study in which middle-aged Caucasian women (47–55) were classified into pre-menopausal, peri-menopausal, and post-menopausal groups based on follicle stimulating hormone levels and bleeding patterns. Comprehensive questionnaires, laboratory visits, anthropometric measurements, and physical activity monitoring by accelerometers were used to characterize the menopausal groups and serum lipid profiles were analyzed to quantify CV (cardiovascular) risk factors. Based on our findings, LTPA may attenuate menopause-associated atherogenic changes in the serum CV risk factors of healthy middle-aged women. However, LTPA does not seem to entirely offset the lipid profile changes associated with the menopausal transition.
Integrated Analysis of Multiple Microarray Studies to Identify Novel Gene Signatures in Non-alcoholic Fatty Liver Disease

Background: Non-alcoholic fatty liver disease (NAFLD) is a well-known cause of liver dysfunction and has become a common chronic liver disease in many countries. However, the intrinsic molecular mechanisms underlying the pathogenesis of NAFLD have not yet been fully elucidated. Methods: We obtained the gene expression datasets of NAFLD through the Gene Expression Omnibus (GEO) database. Subsequently, robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between NAFLD patients and controls. Gene functional annotation and PPI network analysis were performed to explore the potential function of the DEGs. Finally, we used a sequencing dataset GSE126848 to validate our results. Results: In this study, GSE48452, GSE66676, GSE72756, GSE63067, GSE89632, and GSE107231 were included, including 125 NAFLD patients and 116 control patients. The RRA integrated analysis determined 96 significant DEGs (50 up-regulated and 46 down-regulated) and the most significant gene aberrantly expressed in NAFLD was ENO3 (P-value = 7.17E-05), followed by CYP7A1 (P-value = 9.04E-05), and P4HA1 (P-value = 1.67E-04). Carboxylic acid metabolic process (GO:0019752; P-value = 1.39E-03) was the most significantly enriched for biological process in GO (gene ontology) analysis. KEGG pathway enrichment analysis showed that steroid hormone biosynthesis (hsa00140; P-value = 6.68E-03) and PPAR signaling pathway (hsa03320; P-value = 9.95E-03) were significantly enriched. Based on the results of the PPI and the results of the RRA, we finally defined the four most critical genes as the hub genes, including ENO3, CYP7A1, P4HA1, and CYP1A1. Conclusions: Our integrated analysis identified novel gene signatures and will contribute to the understanding of comprehensive molecular changes in NAFLD.
The Role of Thyroid Hormones in Hepatocyte Proliferation and Liver Cancer

Thyroid hormones T3 and T4 (thyroxine) control a wide variety of effects related to development, differentiation, growth and metabolism, through their interaction with nuclear receptors. But thyroid hormones also produce non-genomic effects that typically start at the plasma membrane and are mediated mainly by integrin αvβ3, although other receptors such as TRα and TRβ are also able to elicit non-genomic responses. In the liver, the effects of thyroid hormones appear to be particularly important. The liver is able to regenerate, but it is subject to pathologies that may lead to cancer, such as fibrosis, cirrhosis, and non-alcoholic fatty liver disease. In addition, cancer cells undergo a reprogramming of their metabolism, resulting in drastic changes such as aerobic glycolysis instead of oxidative phosphorylation. As a consequence, the pyruvate kinase isoform M2, the rate-limiting enzyme of glycolysis, is dysregulated, and this is considered an important factor in tumorigenesis. Redox equilibrium is also important, in fact cancer cells give rise to the production of more reactive oxygen species (ROS) than normal cells. This increase may favor the survival and propagation of cancer cells. We evaluate the possible mechanisms involving the plasma membrane receptor integrin αvβ3 that may lead to cancer progression. Studying diseases that affect the liver and their experimental models may help to unravel the cellular pathways mediated by integrin αvβ3 that can lead to liver cancer. Inhibitors of integrin αvβ3 might represent a future therapeutic tool against liver cancer. We also include information on the possible role of exosomes in liver cancer, as well as on recent strategies such as organoids and spheroids, which may provide a new tool for research, drug discovery, and personalized medicine.
Scalable Probabilistic Matrix Factorization with Graph-Based Priors

In matrix factorization, available graph side-information may not be well suited for the matrix completion problem, having edges that disagree with the latent-feature relations learnt from the incomplete data matrix. We show that removing these contested edges improves prediction accuracy and scalability. We identify the contested edges through a highly-efficient graphical lasso approximation. The identification and removal of contested edges adds no computational complexity to state-of-the-art graph-regularized matrix factorization, remaining linear with respect to the number of non-zeros. Computational load even decreases proportional to the number of edges removed. Formulating a probabilistic generative model and using expectation maximization to extend graph-regularised alternating least squares (GRALS) guarantees convergence. Rich simulated experiments illustrate the desired properties of the resulting algorithm. On real data experiments we demonstrate improved prediction accuracy with fewer graph edges (empirical evidence that graph side-information is often inaccurate). A 300 thousand dimensional graph with three million edges (Yahoo music side-information) can be analyzed in under ten minutes on a standard laptop computer demonstrating the efficiency of our graph update.
Effects of Corpus-Based Instruction on Phraseology in Learner English.

This study analyses the effects of data-driven learning (DDL) on the phraseology used by 223 English students at an Italian university. The students studied the genre of opinion survey reports through paper-based and hands-on exploration of a reference corpus. They then wrote their own report and a learner corpus of these texts was compiled. A contrastive interlanguage analysis approach (Granger, 2002) was adopted to compare the phraseology of key items in the learner corpus with that found in the reference corpus. Comparison is also made with a learner corpus of reports produced by a previous cohort of students who had not used the reference corpus. Students who had done DDL tasks used a wider range of genre-appropriate phraseology and produced a lower number of stock phrases than those who had not. The study also finds evidence that students use more phrases encountered in paper-based concordancing tasks than in hands-on tasks. Unlike in previous DDL studies, observations of the learning of a specific text-type through DDL in the present study are based on the comparison with both a control learner corpus and an expert corpus. The study also considers the use of DDL with a large class size.
Phonons in twisted transition-metal dichalcogenide bilayers: Ultrasoft phasons and a transition from a superlubric to a pinned phase

The tunability of the interlayer coupling by twisting one layer with respect to another layer of two-dimensional materials provides a unique way to manipulate the phonons and related properties. We refer to this engineering of phononic properties as "Twistnonics". We study the effects of twisting on low-frequency shear (SM) and layer breathing (LBM) modes in transition metal dichalcogenide (TMD) bilayer using atomistic classical simulations. We show that these low-frequency modes are extremely sensitive to twist and can be used to infer the twist angle. We find unique "ultra-soft" phason modes (frequency $\lesssim 1\ \mathrm{cm^{-1}}$, comparable to acoustic modes) for any non-zero twist, corresponding to an \textit{effective} translation of the moir{\'e} lattice by relative displacement of the constituent layers in a non-trivial way. Unlike the acoustic modes, the velocity of the phason modes is quite sensitive to twist angle. As twist angle decreases, ($\theta \lesssim 3^{\circ},\ \gtrsim 57^{\circ}$) the ultra-soft modes represent the acoustic modes of the "emergent" soft moir{\'e} scale lattice. Also, new high-frequency SMs appear, identical to those in stable bilayer TMD ($\theta = 0\degree/60\degree$), due to the overwhelming growth of stable stacking regions in relaxed twisted structures. Furthermore, we find remarkably different structural relaxation as $\theta \to 0^{\circ}$, $\to 60^{\circ}$ due to sub-lattice symmetry breaking. Our study reveals the possibility of an intriguing $\theta$ dependent superlubric to pinning behavior and of the existence of ultra-soft modes in \textit{all} two-dimensional (2D) materials.
A cross-sectional study of social inequities in medical crowdfunding campaigns in the United States

Americans are increasingly relying on crowdfunding to pay for the costs of healthcare. In medical crowdfunding (MCF), online platforms allow individuals to appeal to social networks to request donations for health and medical needs. Users are often told that success depends on how they organize and share their campaigns to increase social network engagement. However, experts have cautioned that MCF could exacerbate health and social disparities by amplifying the choices (and biases) of the crowd and leveraging these to determine who has access to financial support for healthcare. To date, research on potential axes of disparity in MCF, and their impacts on fundraising outcomes, has been limited. To answer these questions, this paper presents an exploratory cross-sectional study of a randomized sample of 637 MCF campaigns on the popular platform GoFundMe, for which the race, gender, age, and relationships of campaigners and campaign recipients were categorized alongside campaign characteristics and outcomes. Using both descriptive and inferential statistics, the analysis examines race, gender, and age disparities in MCF use, and tests how these are associated with differential campaign outcomes. The results show systemic disparities in MCF use and outcomes: people of color (and black women in particular) are under-represented; there is significant evidence of an additional digital care labor burden on women organizers of campaigns; and marginalized race and gender groups are associated with poorer fundraising outcomes. Outcomes are only minimally associated with campaign characteristics under users’ control, such as photos, videos, and updates. These results corroborate widespread concerns with how technology fuels health inequities, and how crowdfunding may be creating an unequal and biased marketplace for those seeking financial support to access healthcare. Further research and better data access are needed to explore these dynamics more deeply and inform policy for this largely unregulated industry.
Dust survival rates in clumps passing through the Cas A reverse shock – I. Results for a range of clump densities

The reverse shock in the ejecta of core-collapse supernovae is potentially able to destroy newly formed dust material. In order to determine dust survival rates, we have performed a set of hydrodynamic simulations using the grid-based code astrobear in order to model a shock wave interacting with clumpy supernova ejecta. Dust motions and destruction rates were computed using our newly developed external, post-processing code paperboats, which includes gas drag, grain charging, sputtering, and grain–grain collisions. We have determined dust destruction rates for the oxygen-rich supernova remnant Cassiopeia A as a function of initial grain sizes and clump gas density. We found that up to $30\,\mathrm{{{\ \rm per\ cent}}}$ of the carbon dust mass is able to survive the passage of the reverse shock if the initial grain size distribution is narrow with radii around ∼10–50 nm for high gas densities, or with radii around $\sim 0.5\! -\! 1.5\,\mathrm{\mu m}$ for low and medium gas densities. Silicate grains with initial radii around 10–30 nm show survival rates of up to $40\,\mathrm{{{\ \rm per\ cent}}}$ for medium- and high-density contrasts, while silicate material with micron-sized distributions is mostly destroyed. For both materials, the surviving dust mass is rearranged into a new size distribution that can be approximated by two components: a power-law distribution of small grains and a lognormal distribution of grains having the same size range as the initial distribution. Our results show that grain–grain collisions and sputtering are synergistic and that grain–grain collisions can play a crucial role in determining the surviving dust budget in supernova remnants.