Miracle-dz/UniFAR-FTUs huggingface dataset:
The Shape of Things to Come: COVID's Organizational Impact

It’s no great secret that epidemics have an impact on society. In addition to their immediate toll of death and suffering, history records multiple examples of their ability to alter our patterns of behavior, to affect local and national economies, to influence the laws that we pass, and to bring about changes in the way that organizations operate, among other effects. The ongoing epidemic of SARS-CoV-2 is no exception to this observation. And while COVID-19’s immense death toll may be its most obvious and immediately relevant impact, public health managers and practitioners should also pay close attention to the pandemic’s influence on organizations within our public health system and the ways in which it has and will continue to influence the delivery of public health services. Recognizing the variety of organizations that constitute America’s public health system, and understanding how these organizations function and interact with one another, is critical to achieving many of the stated core competencies of public health professionals. And this understanding must encompass much more than an awareness of lines of authority or a detailing of who performs what function and when. Why? Because increasingly, theories explaining how organizations are structured and the contextual factors that influence their performance and interactions with one another are being used to better understand the factors that can affect the successful delivery of clinical and community health services. Traditional models of health care delivery, including the delivery of population health services, envision a linear “pipeline” extending from the researchers who develop and test new methods and technologies through to the practitioners who implement these new interventions in clinical or public
Neutron star solutions with curvature induced scalarization in the extended Gauss-Bonnet scalar-tensor theories

In the present paper we study models of neutron stars in a class of extended scalar-tensor Gauss-Bonnet (ESTGB) theories for which the scalar degree of freedom is exited only in the strong curvature regime. We show that in the framework of the ESTGB theories under consideration there exist new neutron star solutions which are formed via spontaneous scalarization of the general relativistic neutron stars. In contrast to the spontaneous scalarization in the standard scalar-tensor theories which is induced by the presence of matter, in our case the scalarization is induced by the spacetime curvature.
Robust two parameter ridge M-estimator for linear regression

The problem of multicollinearity and outliers in the data set produce undesirable effects on the ordinary least squares estimator. Therefore, robust two parameter ridge estimation based on M-estimator (ME) is introduced to deal with multicollinearity and outliers in the y-direction. The proposed estimator outperforms ME, two parameter ridge estimator and robust ridge M-estimator according to mean square error criterion. Moreover, a numerical example and a Monte Carlo simulation experiment are presented.
Prediction of circRNA-MiRNA Association Using Singular Value Decomposition and Graph Neural Networks

A large number of experimental studies have shown that circRNAs can act as molecular sponges of microRNAs, interacting with miRNAs to regulate gene expression levels, thereby affecting the development of human diseases. Exploring the potential associations between circRNAs and miRNAs can help understand complex disease mechanisms. Considering that biological experiments are time-consuming and labor-intensive, this study proposes a computational model using a graph neural network and singular value decomposition (CMASG) for circRNA-miRNA association prediction. Specifically, graph neural networks are used to learn nonlinear feature representations of nodes, followed by matrix factorization algorithms to learn linear feature representations of nodes, and then combined feature representations learned from different perspectives. Finally, the lightGBM algorithm was used for circRNA-miRNA association prediction. The proposed CMASG model achieved an AUC value of 0.8804. The experimental results demonstrate the superiority and effectiveness of the CMASG model in predicting circRNA-miRNA association tasks.
First-principles calculations of phonon dispersion and lattice dynamics in La 2 CuO 4

First-principles density-functional linearized augmented plane-wave linear-response calculations are presented of the lattice dynamics of tetragonal ${\mathrm{La}}_{2}{\mathrm{CuO}}_{4}. $ Phonon frequencies and eigenvectors are obtained throughout the Brillouin zone. Generally good agreement is achieved with experiment, but frequencies of the lowest-lying branches, which involve anharmonic motion of the apical oxygen atoms parallel to the ${\mathrm{CuO}}_{2}$ planes, are underestimated. The octahedral tilt mode at the X point is found to be the most unstable mode throughout the Brillouin zone, consistent with the observed phase transition to the orthorhombic structure at low temperature. The calculated dispersion of the highest frequency ${\ensuremath{\Sigma}}_{3}$ branch is in good agreement with experiment, showing that a proposed large renormalization of the phonon spectrum by a Jahn-Teller electron-phonon interaction is unlikely.
The Struggle Between Protecting Children From and Preparing Them for the Death of Their Parent: A Qualitative Study

Objectives The aim of this study was to gain a greater understanding of communicating with children about parental terminal illness from the perspective of the surviving parents. Methods A qualitative descriptive study was conducted using semi structured interviews with eligible participants. Data was analyzed using thematic analysis. Results The results highlight the pressures experienced by surviving parents, grappling with trying to support their children’s needs on a practical and emotional level, while coping with the emotional upheaval of the impending death of their partner. The issue of communication with the children starts long before the terminal phase of illness and the results confirm that this is an ongoing process that continues after the death of the parent. The need for services to be more responsive to the diverse needs of families was also apparent as a key factor in supporting families during this time. Conclusions This research provides valuable insights into the complexity of communicating with children about terminal illness from the perspective of the surviving parents. It reveals diverse views and experiences in terms of approaching communication with children and illustrates the need for services to be acutely attuned to the unique needs of parents and children throughout the disease trajectory.
The formation of close binary systems

A viable solution to the origin of close binary systems, unaccounted for in recent theories, is presented. Fragmentation, occurring at the end of the secondary collapse phase (during which molecular hydrogen is dissociating), can form binary systems with separations less than 1 au. Two fragmentation modes are found to occur after the collapse is halted. The first consists of the fragmentation of a protostellar disc due to rotational instabilities in a protostellar core, involving both an $m=1$ and an $m=2$ mode. This fragmentation mechanism is found to be insensitive to the initial density distribution: it can occur in both centrally condensed and uniform initial conditions. The second fragmentation mode involves the formation of a rapidly rotating core at the end of the collapse phase which is unstable to the axisymmetric perturbations. This core bounces into a ring which quickly fragments into several components. The binary systems thus formed contain less than 1 per cent of a solar mass and therefore will need to accrete most of their final mass if they are to form a binary star system. Their orbital properties will thus be determined by the properties of the accreted matter.
Insight into synergetic effects of serum albumin and glucose on the biodegradation behavior of WE43 alloy in simulated body fluid

The biodegradation rate of Mg alloy medical devices, such as screws and plates for temporary bone fracture fixation or coronary angioplasty stents, is an increasingly important area of study. In vitro models of the corrosion behavior of these devices use revised simulated body fluid (m-SBF) based on a healthy individual’s blood chemistry. Therefore, model outputs have limited application to patients with altered blood plasma glucose or protein concentrations. This work studies the biodegradation behavior of Mg alloy WE43 in m-SBF modified with varying concentrations of glucose and bovine serum albumin (BSA) to (1) mimic a range of disease states and (2) determine the contributions of each biomolecule to corrosion. Measurements include the Mg ion release rate, electrolyte pH, the extent of hydrogen evolution (as a proxy for corrosion rate), surface morphology, and corrosion product composition and effects. BSA (0.1 g l–1) suppresses the rate of hydrogen evolution (about 30%) after 24 h and—to a lesser degree—Mg2+ release in both the presence and absence of glucose. This effect gets more pronounced with time, possibly due to BSA adsorption on the Mg surface. Electrochemical studies confirm that adding glucose (2 g l–1) to the solution containing BSA (0.1 g l–1) caused a decrease in corrosion resistance (by around 40%), and concomitant increase in the hydrogen evolution rate (from 10.32 to 11.04 mg cm–2 d–1) to levels far beyond the tolerance limits of live tissues.
Use of Machine Learning and Lay Care Coaches to Increase Advance Care Planning Conversations for Patients With Metastatic Cancer

PURPOSE: Patients with metastatic cancer benefit from advance care planning (ACP) conversations. We aimed to improve ACP using a computer model to select high-risk patients, with shorter predicted survival, for conversations with providers and lay care coaches. Outcomes included ACP documentation frequency and end-of-life quality measures. METHODS: In this study of a quality improvement initiative, providers in four medical oncology clinics received Serious Illness Care Program training. Two clinics (thoracic/genitourinary) participated in an intervention, and two (cutaneous/sarcoma) served as controls. ACP conversations were documented in a centralized form in the electronic medical record. In the intervention, providers and care coaches received weekly e-mails highlighting upcoming clinic patients with < 2 year computer-predicted survival and no prior prognosis documentation. Care coaches contacted these patients for an ACP conversation (excluding prognosis). Providers were asked to discuss and document prognosis. RESULTS: In the four clinics, 4,968 clinic visits by 1,251 patients met inclusion criteria (metastatic cancer with no prognosis previously documented). In their first visit, 28% of patients were high-risk (< 2 year predicted survival). Preintervention, 3% of both intervention and control clinic patients had ACP documentation during a visit. By intervention end (February 2021), 35% of intervention clinic patients had ACP documentation compared with 3% of control clinic patients. Providers' prognosis documentation rate also increased in intervention clinics after the intervention (2%-27% in intervention clinics, P < .0001; 0%-1% in control clinics). End-of-life care intensity was similar in intervention versus control clinics, but patients with ≥ 1 provider ACP edit met fewer high-intensity care measures (P = .04). CONCLUSION: Combining a computer prognosis model with care coaches increased ACP documentation.
Examining the Role for Donor-specific Antibody Testing in Simultaneous Liver-kidney Transplantation: A Single-center Analysis of Outcomes

Background. Simultaneous liver-kidney transplantation (SLKT) is increasingly used for patients with concurrent end-stage liver and renal disease. Emerging evidence suggests that simultaneous liver transplant can provide a tolerogenic benefit to multiorgan transplant recipients. Posttransplant donor-specific antibody (DSA) may be associated with worse outcomes; however, the role for testing DSA in SLKT is unclear. Methods. This study retrospectively assessed the impact of DSA on outcomes following primary SLKT at a large-volume center between 2008 and 2018. Patients were grouped by positive DSA, negative DSA, and DSA not tested, and data were obtained from our institutional database and chart review. Results. The cohort included 138 SLKT recipients with a mean age of 56.1 ± 9.7 y; 61.6% were male, and 55.8% were Hispanic. Overall, 62 patients were tested for DSA posttransplant, and 33 patients (23.9%) had at least 1 DSA detected. A total of 34 patients (24.6%) experienced at least 1 episode of liver rejection, and 23 patients (16.7%) experienced kidney rejection. Over 50% of patients with de novo DSA changed status during their posttransplant course. Rates of both liver and kidney rejection were slightly higher in the DSA+ group, but liver allograft, kidney allograft, and patient survival did not differ when grouped by whether DSA testing was performed or DSA positivity. Conclusions. These data demonstrate that SLKT is associated with excellent long-term patient and allograft survival with a relatively low rate of rejection. In our experience, testing for DSA does not impact SLKT outcomes‚ and further multicenter analyses are needed to establish standard of care.
The status quo of systematic reviews published in high-impact journals in Korea: a study focused on protocol registration and GRADE use

OBJECTIVES This study investigated the status quo of systematic reviews published in major journals in Korea from the perspective of protocol registration and adopting the grading of recommendation, assessment, development and evaluation (GRADE) system. METHODS We examined systematic reviews published in Korea’s top 15 medical journals from 2018 to 2021. Teams of 2 reviewers assessed the studies’ eligibility criteria and extracted data independently and in duplicate. We collected information on study characteristics, protocol registration, and GRADE use of the included reviews, and reviewed the “Instructions for Authors” of the selected journals to assess any guidance related to systematic reviews. RESULTS Out of the 126 identified reviews, 18 (14.3%) reported that they registered or published their protocol. Only 5 (4.0%) rated the certainty of evidence; and all 5 used the GRADE system. Only 6 of 15 journals mentioned systematic reviews in their “Instructions for Authors. ” Six journals endorsed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework for systematic review reporting (2 mandatory, 3 recommended, and 1 unclear). None of the journals included mentioned protocol registration or certainty of evidence in their authors’ guidelines. CONCLUSIONS Overall, the proportion of systematic reviews that had prior protocol registration or used the GRADE approach to rate the certainty of evidence was very low. Our study highlights the need for adherence to systematic review standards in medical journals in Korea, including prior protocol registration and certainty of evidence assessment. Our review will help improve the quality of systematic reviews in Korea.
Neutrino mass and dark energy constraints from redshift-space distortions

Cosmology in the near future promises a measurement of the sum of neutrino masses ∑ mν, a fundamental Standard Model parameter, as well as substantially-improved constraints on the dark energy. We use the shape of the BOSS redshift-space galaxy power spectrum, in combination with CMB and supernova data, to constrain the neutrino masses and the dark energy. Essential to this calculation are several recent advances in non-linear cosmological perturbation theory, including fast Fourier transform methods, redshift space distortions, and scale-dependent growth. Our 95% confidence upper bound ∑ mν < 180 meV degrades substantially to ∑ mν < 540 meV when the dark energy equation of state and its first derivative are also allowed to vary, representing a significant challenge to current constraints. We also study the impact of additional galaxy bias parameters, finding that a greater allowed range of scale-dependent bias only slightly shifts the preferred ∑ mν, weakens its upper bound by ≈ 20%, and has a negligible effect on the other cosmological parameters.
MIGBaseline at ROCLING 2022 Shared Task: Report on Named Entity Recognition Using Chinese Healthcare Datasets

Named Entity Recognition (NER) tools have been in development for years, yet few have been aimed at medical documents. The increasing needs for analyzing medical data makes it crucial to build a sophisticated NER model for this missing area. In this paper, W2NER, the state-of-the-art NER model, which has excelled in English and Chinese tasks, is run through selected inputs, several pretrained language models, and training strategies. The objective was to build an NER model suitable for healthcare corpora in Chinese. The best model managed to achieve an F1 score at 81.93%, which ranked first in the ROCLING 2022 shared task.
Analyzing discourse functions with acoustic features and phone embeddings: non-lexical items in Taiwan Mandarin

Non-lexical items are expressive devices used in conversations that are not words but are nevertheless meaningful. These items play crucial roles, such as signaling turn-taking or marking stances in interactions. However, as the non-lexical items do not stably correspond to written or phonological forms, past studies tend to focus on studying their acoustic properties, such as pitches and durations. In this paper, we investigate the discourse functions of non-lexical items through their acoustic properties and the phone embeddings extracted from a deep learning model. Firstly, we create a non-lexical item dataset based on the interpellation video clips from Taiwan’s Legislative Yuan. Then, we manually identify the non-lexical items and their discourse functions in the videos. Next, we analyze the acoustic properties of those items through statistical modeling and building classifiers based on phone embeddings extracted from a phone recognition model. We show that (1) the discourse functions have significant effects on the acoustic features; and (2) the classifiers built on phone embeddings perform better than the ones on conventional acoustic properties. These results suggest that phone embeddings may reflect the phonetic variations crucial in differentiating the discourse functions of non-lexical items.
Early Speech Production in Infants and Toddlers Later Diagnosed with Cerebral Palsy: A Retrospective Study

In this retrospective study, we compared the early speech development between infants with cerebral palsy (CP) and typically developing (TD) infants. The recordings of utterances were collected from two CP infants and two typically-developing (TD) infants at approximately 8 and 24 months old. The data was analyzed by volubility, consonant emergence, canonical babbling ratio (CBR), mean babbling level (MBL). The major findings show that comparing with TD group, CP group has the characteristics of: 1) lower volubility 2) CBRutter below 0.15 at 2 years old 3) MBL score below 2 at the age of 2 with a feature of above 95% in level 1 4) using consonants mainly at two oral places (bilabials and velars) and three manners of articulation (nasal, fricative, and stop) at 2 years old.
Unsupervised Text Summarization of Long Documents using Dependency-based Noun Phrases and Contextual Order Arrangement

Unsupervised extractive summarization has recently gained importance since it does not require labeled data. Among unsupervised methods, graph-based approaches have achieved outstanding results. These methods represent each document by a graph, with sentences as nodes and word-level similarity among sentences as edges. Common words can easily lead to a strong connection between sentence nodes. Thus, sentences with many common words can be misinterpreted as salient sentences for a summary. This work addresses the common word issue with a phrase-level graph that (1) focuses on the noun phrases of a document based on grammar dependencies and (2) initializes edge weights by term-frequency within the target document and inverse document frequency over the entire corpus. The importance scores of noun phrases extracted from the graph are then used to select the most salient sentences. To preserve summary coherence, the order of the selected sentences is re-arranged by a flow-aware orderBERT. The results reveal that our unsupervised framework outperformed other extractive methods on ROUGE as well as two human evaluations for semantic similarity and summary coherence.
RoBERTa-based Traditional Chinese Medicine Named Entity Recognition Model

In this study, a named entity recognition was constructed and applied to the identification of Chinese medicine names and disease names. The results can be further used in a human-machine dialogue system to provide people with correct Chinese medicine medication reminders. First, this study uses web crawlers to sort out web resources into a Chinese medicine named entity corpus, collecting 1097 articles, 1412 disease names and 38714 Chinese medicine names. Then, we annotated each article using TCM name and BIO tagging method. Finally, this study trains and evaluates BERT, ALBERT, RoBERTa, GPT2 with BiLSTM and CRF. The experimental results show that RoBERTa’s NER system combining BiLSTM and CRF achieves the best system performance, with a precision rate of 0.96, a recall rate of 0.96, and an F1-score of 0.96.
Simulations of fully deformed oscillating flux tubes

In recent years, a number of numerical studies have been focusing on the significance of the Kelvin-Helmholtz instability (KHI) in the dynamics of oscillating coronal loops. This process enhances the transfer of energy into smaller scales, and has been connected with heating of coronal loops, when dissipation mechanisms, such as resistivity, are considered. However, the turbulent layer is expected near the outer regions of the loops. Therefore, the effects of wave heating are expected to be confined to the loop's external layers, leaving their denser inner parts without a heating mechanism. In the current work we aim to study the spatial evolution of wave heating effects from a footpoint driven standing kink wave in a coronal loop. Using the MPI-AMRVAC code, we performed ideal, three dimensional magnetohydrodynamic simulations of footpoint driven transverse oscillations of a cold, straight coronal flux tube, embedded in a hotter environment. We have also constructed forward models for our simulation using the FoMo code. The developed Transverse Wave Induced Kelvin-Helmholtz (TWIKH) rolls expand throughout the tube cross-section, and cover it entirely. This turbulence significantly alters the initial density profile, leading to a fully deformed cross section. As a consequence, the resistive and viscous heating rate both increase over the entire loop cross section. The resistive heating rate takes its maximum values near the footpoints, while the viscous heating rate at the apex. We conclude that even a monoperiodic driver can spread wave heating over the whole loop cross section, potentially providing a heating source in the inner loop region. Despite the loop's fully deformed structure, forward modelling still shows the structure appearing as a loop.