Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Admission SOFA Score and 48-hour Delta Sofa on Clinical Outcomes of Critically Ill Patients

Background: Multiple organ dysfunction syndrome (MODS) is an important cause of morbidity and mortality in the Intensive Care Unit (ICU). Sequential Organ Failure Assessment (SOFA) scores, determined upon ICU admission, can identify patients at risk of unfavorable outcomes and trigger assessment and application of interventional approaches, of which effectiveness can be evaluated by determining the SOFA score trend after 48 hours. Herein, we evaluated the impact of an admission SOFA score ≥ 2 and the 48-hour delta SOFA, on critically ill patients’ outcomes.Methods: This retrospective, observational cohort study included 1101 patients admitted to three ICUs of a tertiary hospital, from January 01 to December 31, 2020. SOFA scores—determined upon ICU admission and 48 hours thereafter—denoted three patient groups: those with admission SOFA scores below 2 (Group 1, n = 348), those with admission SOFA scores ≥ 2 whose 48-hour delta SOFA reflected improvement (SOFA after 48 hours < admission SOFA) (Group 2, n = 415), and those with admission SOFA scores ≥ 2 that had increased or remained unchanged after 48 hours (SOFA after 48 hours ≥ admission SOFA) (Group 3, n = 338). Statistical tests included the Shapiro-Wilk, Tukey's post hoc, and Kruskal-Wallis tests, among others.Results: Group 1 patients were significantly younger and less severely ill (based on SAPS 3 score and admission SOFA) than those in Groups 2 and 3, and their length of ICU stay was shorter. Furthermore, both their ICU (3.4%) and hospital (8.6%) mortality was significantly lower, compared to that of Group 2 and 3 patients. Among these, patients in Group 3 were older and had significantly higher mortality, both in the ICU (27.3% versus 10.1%, p < 0.001) and hospital (53.8% versus 14.9%, p < 0.001), compared to Group 2 patients. We discovered an independent association between age ≥ 66 years, the Charlson Comorbidity Index, prolonged vasopressor use, and hospital mortality.Conclusion: We demonstrated that the admission SOFA score and 48-hour delta SOFA are predictors of prognosis in a non-selective cohort of critically ill patients.Trial registration: The study protocol was retrospectively registered at ClinicalTrials.gov (NCT04980274, July 27, 2021.)
Expansion planning of transmission network with large wind farm in deregulated electricity market environment

The heuristic algorithm of conventional TNEP(Transmission Network Expansion Planning) is improved to meet the needs of grid-connected large-scale wind farm and deregulated electricity market.Monte Carlo simulation method is applied to deduce the PDF(Probability Density Function) of wind farm power output and the PDF of unit power outputs is determined according to electricity market swapping mechanism.The direct power flow model is adopted to analyze the PDF of line active power and the line overload probability.An effectiveness index considering both cost and profit prospect is put forward to evaluate the importance of line,based on which the TNEP is carried out.Simulative results for Garver 6-bus test system demonstrate the feasibility of the improved algorithm and the obvious effect of both deregulated electricity market and irregular wind power output on TNEP,probably resulting in the investment increase.
Re-orienting transdisciplinary research and community-based participatory research for health equity

Abstract Introduction: Transdisciplinary (TD) research and community-based participatory research (CBPR) represent promising investigative approaches to ameliorate health disparities. Public investments in team-based TD research to address multifactorial public health problems have increased over the last two decades. Similarly, recognition that community participation in research and social action is essential to promoting health equity is reflected in increased prioritization of community engagement in research and practice. Yet, models that describe and guide the combined TD and CBPR approach are lacking. Methods: We utilized a qualitative, convergent parallel case study design that included document reviews and one-on-one interviews to assess how investigators from the Centers for Population Health and Health Disparities (CPHHD) initiative integrated TD team science and CBPR in their work, and what they perceived as the impact of that work on health equity. Results: Twenty-five CPHHD investigators and National Institutes of Health program staff participated in a one-on-one interview. Document and interview data informed the development of an iterative conceptual model of TD CBPR comprising five domains: problem focus, contexts, collaboration and partnership, outcomes, and societal impact of TD CBPR. Conclusions: TD team science and CBPR are integrally related; combining principles of both can facilitate more efficient, equitable progress toward team outcomes, improved population health, and increased health equity. This model could assist researchers and public health practitioners in designing community-relevant, scientifically rigorous research with practical implications for improving health and quality of life among marginalized populations.
Changes in chromatin accessibility are not concordant with transcriptional changes for single‐factor perturbations

A major goal in the field of transcriptional regulation is the mapping of changes in the binding of transcription factors to the resultant changes in gene expression. Recently, methods for measuring chromatin accessibility have enabled us to measure changes in accessibility across the genome, which are thought to correspond to transcription factor binding events. In concert with RNA-sequencing, these data in principle enable such mappings; however, few studies have looked at their concordance over short duration treatments with specific perturbations. Here, we used tandem, bulk ATAC-seq and RNA-seq measurements from MCF-7 breast carcinoma cells to systematically evaluate the concordance between changes in accessibility and changes in expression in response to retinoic acid and TGF-β. We found two classes of genes whose expression showed a significant change: those that showed some change in accessibility of nearby chromatin, and those that showed virtually no change despite strong changes in expression. The peaks associated with genes in the former group had a lower baseline accessibility prior to exposure to signal. Focusing the analysis specifically on peaks with motifs for transcription factors associated with retinoic acid and TGF-β signaling did not reduce the lack of correspondence. Analysis of paired chromatin accessibility and gene expression data from distinct paths along the hematopoietic differentiation trajectory showed a much stronger correspondence, suggesting that the multifactorial biological processes associated with differentiation may lead to changes in chromatin accessibility that reflect rather than drive altered transcriptional status. Together, these results show many gene expression changes can happen independent of changes in accessibility of local chromatin in the context of a single-factor perturbation and suggest that some changes to accessibility changes may occur after changes to expression, rather than before.
Epigenetic cell memory: The gene’s inner chromatin modification circuit

Epigenetic cell memory allows distinct gene expression patterns to persist in different cell types despite a common genotype. Although different patterns can be maintained by the concerted action of transcription factors (TFs), it was proposed that long-term persistence hinges on chromatin state. Here, we study how the dynamics of chromatin state affect memory, and focus on a biologically motivated circuit motif, among histones and DNA modifications, that mediates the action of TFs on gene expression. Memory arises from time-scale separation among three circuit’s constituent processes: basal erasure, auto and cross-catalysis, and recruited erasure of modifications. When the two latter processes are sufficiently faster than the former, the circuit exhibits bistability and hysteresis, allowing active and repressed gene states to coexist and persist after TF stimulus removal. The duration of memory is stochastic with a mean value that increases as time-scale separation increases, but more so for the repressed state. This asymmetry stems from the cross-catalysis between repressive histone modifications and DNA methylation and is enhanced by the relatively slower decay rate of the latter. Nevertheless, TF-mediated positive autoregulation can rebalance this asymmetry and even confers robustness of active states to repressive stimuli. More generally, by wiring positively autoregulated chromatin modification circuits under time scale separation, long-term distinct gene expression patterns arise, which are also robust to failure in the regulatory links.
COVID‐19 Disclosures and Market Uncertainty: Evidence from 10‐Q Filings

Abstract We examine whether the quarterly filing COVID‐19 disclosures reduce uncertainty for investors and analysts. We find a negative relationship between COVID‐19 disclosure and return volatility, suggesting COVID‐19 disclosure reduces investor uncertainty. This reduction effect concentrates mainly during the short window following 10‐Q releases and phases out over time. We then detect that industry‐wide COVID‐19 disclosure dispersion is positively associated with return volatility, suggesting high variation of industry‐wide COVID‐19 disclosures reduces information comparability across firms, resulting in increased investor uncertainty. Moreover, we find that COVID‐19 disclosures are positively associated with analysts’ downward earnings forecast revisions and negatively associated with analyst forecast dispersion after 10‐Q releases, suggesting the disclosures reduce information risk even for sophisticated market participants. Further analyses show that COVID‐19 disclosures are negatively associated with future financial and operational performances (i.e., sales, operating cash flow, operating income and ROA). Lastly, we find that the low readability of COVID‐19 disclosure attenuates the negative relation between COVID‐19 disclosure and market volatility. Collectively, our findings suggest that 10‐Q COVID‐19 disclosures contain value‐relevant information that temporarily assists market participants in evaluating the changes in firms’ values in the time of a crisis.
A Model of C4 Photosynthetic Acclimation Based on Least‐Cost Optimality Theory Suitable for Earth System Model Incorporation

Empirical studies have shown that plant photosynthetic responses to environmental change can vary over time due to acclimation, but acclimation responses are often not included in Earth System Models. Photosynthetic least cost theory can be used to develop models of photosynthetic acclimation that are simple and testable. The theory is based on the idea that plants will acclimate to minimize the ratio of carbon costs to photosynthetic assimilation rate (Prentice et al., 2014, https://doi.org/10.1111/ele.12211). Formulations of this theory have been developed for C3 plants, but not C4 plants, which account for over 20% of global photosynthesis and are over‐represented among widely grown crops. Here, we use photosynthetic least cost theory to derive a model for C4 photosynthetic acclimation to above‐ground abiotic conditions. We then compare our model's responses to a similar model of C3 photosynthetic acclimation and find that C4 photosynthesis has the highest simulated advantage over C3 photosynthesis in hot, dry, and low CO2 environments. We find that this advantage predicts C4 abundance globally, but that the shallower CO2 response of C4 as compared to C3 photosynthesis will reduce C4 plant competitiveness under future conditions, despite higher temperatures. We also show that an acclimated model predicts similar or faster rates of C4 under all conditions than a model that does not consider acclimation, suggesting that Earth System Models (ESMs) are underestimating future C4 carbon uptake by not including acclimation. Our model is designed for easy incorporation into such ESMs.
Evaluating Basic Two-Dimensional Echocardiography For Screening In Coronary Artery Disease

Background: Basic two-dimensional echocardiography (2D-echocardiography) screens for suspected coronary artery disease (CAD) by detecting impaired left ventricular function (LVF) which declines as atherosclerosis worsens. Aim: To evaluate basic 2D-echocardiography for CAD screening.Methods: CAD screening was performed with 2D-echocardiography. For global screening, left ventricular ejection fraction percentage (LVEF%) was determined and categorised into global systolic LVF. For regional screening, global average echocardiography score (GAES) was quantified, then categorised into functional impairment. After screening, high-risk patients underwent diagnostic coronary angiography. Abnormal angiography had >50% luminal stenosis. Angiography was also quantified with Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) score, then categorised. Statistical Package for Social Science 25.0 analysed data.Results: There were 471 patients screened for CAD; 154/471 (33%) underwent angiography. For angiography selection amongst 471 screened patients, GAES was higher (p<0.001) and positively correlated (Pearson’s coefficient 0.296); LVEF% was lower (p=0.002) and negatively correlated (Pearson’s coefficient -0.187). Amongst 154 patients, SYNTAX score correlated negatively with LVEF% (Pearson’s coefficient -0.276) and positively with GAES (Pearson’s co-efficient 0.180). For categories, angiography had 66/154 (42.9%) normal and 88/154 (57.1%) abnormal results. SYNTAX score had 134/154 (87.0%) low-risk and 20/154 (13.0%) medium-high-risk categories. GAES correlated positively with angiogram results (Spearman’s coefficient 0.298) and SYNTAX categories (Spearman’s coefficient 0.110). LVEF% correlated negatively with angiogram results (Spearman’s coefficient -0.307) and SYNTAX categories (Spearman’s coefficient -0.254). Conclusions: The distribution of underlying atherosclerotic vessels resulted in regional wall abnormalities being more significant than global function on 2D-echocardiography. We conclude that basic 2D-echocardiography remains useful in CAD screening.
Genome-Wide Prediction of Transcription Start Sites in Conifers

The identification of promoters is an essential step in the genome annotation process, providing a framework for gene regulatory networks and their role in transcription regulation. Despite considerable advances in the high-throughput determination of transcription start sites (TSSs) and transcription factor binding sites (TFBSs), experimental methods are still time-consuming and expensive. Instead, several computational approaches have been developed to provide fast and reliable means for predicting the location of TSSs and regulatory motifs on a genome-wide scale. Numerous studies have been carried out on the regulatory elements of mammalian genomes, but plant promoters, especially in gymnosperms, have been left out of the limelight and, therefore, have been poorly investigated. The aim of this study was to enhance and expand the existing genome annotations using computational approaches for genome-wide prediction of TSSs in the four conifer species: loblolly pine, white spruce, Norway spruce, and Siberian larch. Our pipeline will be useful for TSS predictions in other genomes, especially for draft assemblies, where reliable TSS predictions are not usually available. We also explored some of the features of the nucleotide composition of the predicted promoters and compared the GC properties of conifer genes with model monocot and dicot plants. Here, we demonstrate that even incomplete genome assemblies and partial annotations can be a reliable starting point for TSS annotation. The results of the TSS prediction in four conifer species have been deposited in the Persephone genome browser, which allows smooth visualization and is optimized for large data sets. This work provides the initial basis for future experimental validation and the study of the regulatory regions to understand gene regulation in gymnosperms.
Safety Analysis of Medical Implants in the Human Head Exposed to a Wireless Power Transfer System

The interactions of medical implants in the human body with electromagnetic fields from newly introduced high-field technologies such as near-field wireless power transfer (WPT) are of great concern. In this study, the effects of implants on the specific absorption rate (SAR) in a head model were computationally evaluated in the immediate vicinity of a WPT system operating at 6.78 MHz with a transferred power of 50 W. The SAR in the head model located 30 mm above the WPT system was evaluated with a skull plate, bone plates (different shapes), miniplate, fixtures, and a deep brain stimulator. The results indicated that even small implants had notable effects on the SAR distribution and corresponding local peak and mass-averaged SAR values. Apart from the size and shape of the implant, the crucial factor influencing the SAR was the implant’s position with respect to the WPT system. Therefore, various position configurations were simulated for the WPT system to determine the worst case scenario for each specific implant. Although the local peak SAR value was increased by a factor of 600 in the worst-case scenario (for the skull plate), the SAR<inline-formula><tex-math notation="LaTeX">$_{\text{1}g}$</tex-math></inline-formula> and SAR<inline-formula><tex-math notation="LaTeX">$_{\text{10}g}$</tex-math></inline-formula> were only increased by factors of seven and four, respectively. Compliance with international safety limits was studied, followed by computing the maximum allowable transmit power (MATP). It was found that, without the implant, the MATP satisfying SAR<inline-formula><tex-math notation="LaTeX">$_{\text{1}g}$</tex-math></inline-formula> was 43 W for the designed WPT system, and was reduced to 6.9 W in the presence of the skull plate.
Study on Sequence of Cable Replacement for Cable-stayed Bridge Based on Sensitivity Analysis

By analyzing the cable replacement sequence survey of some bridges,the major sequence of cable replacement was summarized according to the different arrangement forms of the cable,and the safety cable replacement sequence was obtained from simulating the cable replacement of a cable-stayed bridge with double towers and double cable planes using the finite element model.The sequence of cable replacement of cable-stayed bridge was analyzed according to the variation of bending strain energy when only one cable was replaced.The variation of cable force in different cable replacing conditions were compared,including replacing one cable of single tower,replacing four cables symmetrically on the same side of double towers and replacing four cables antisymmetrically on the different sides of double towers,and the sequence of cable replacement was studied.The alignment control of bridge girder was analyzed under the conditions of replaceing four cables on the same side of double towers and replacing four cables on the different sides of double towers,and established a finite element model.By summarizing and analysis,the cable replacement of cable-stayed bridge should proceed antisymmetrically from the short cable to the long cable.
Learnable Wavelet Scattering Networks: Applications to Fault Diagnosis of Analog Circuits and Rotating Machinery

Analog circuits are a critical part of industrial electronics and systems. Estimates in the literature show that, even though analog circuits comprise less than 20% of all circuits, they are responsible for more than 80% of faults. Hence, analog circuit fault diagnosis and isolation can be a valuable means of ensuring the reliability of circuits. This paper introduces a novel technique of learning time–frequency representations, using learnable wavelet scattering networks, for the fault diagnosis of circuits and rotating machinery. Wavelet scattering networks, which are fixed time–frequency representations based on existing wavelets, are modified to be learnable so that they can learn features that are optimal for fault diagnosis. The learnable wavelet scattering networks are developed using the genetic algorithm-based optimization of second-generation wavelet transform operators. The simulation and experimental results for the diagnosis of analog circuit faults demonstrates that the developed diagnosis scheme achieves greater fault diagnosis accuracy than other methods in the literature, even while considering a larger number of fault classes. The performance of the diagnosis scheme on benchmark datasets of bearing faults and gear faults shows that the developed method generalizes well to fault diagnosis in multiple domains and has good transfer learning performance, too.
Asymmetric effect of FEARS Sentiment on Stock Returns: Short-sale constraints, limits to arbitrage, and behavioural biases

ABSTRACT This paper examines the implications of short-sale constraints, limits to arbitrage, and behavioral biases on the FEARS sentiment and stock returns asymmetric relationship. Our results indicate a strong negative relationship between FEARS sentiment and stock return. Our findings show that short-sell and arbitrage constraint attenuates the potential impact of sentiment on return behavior. We find that the FEARS sentiment influences behavioral biases and the trading activity of market participants.
Quality of Service Measure for Bike Sharing Systems

Bike sharing systems (BSSs) are becoming an important part of urban mobility in many cities given that they are sustainable and environmentally friendly. BSS operators spend great efforts to ensure bike and dock availability at each station. Measuring the quality of service (QoS) of each station and/or the entire system is critical for efficient system operations. The traditionally-known QoS measure reported in the literature is based on the proportion of problematic stations, which are defined as those with no bikes or docks available to users. This measure neither exposes the spatial dependencies between stations nor does it discriminate between stations in the BSS. Hence, we propose a novel QoS measure, namely the Optimal Occupancy, in which: 1) the temporal variations in arrival and pick up rates at individual stations are considered; 2) the discriminative property of the Optimal Occupancy is demonstrated using Analysis of Variance (ANOVA) procedures; and 3) geo-statistics, which have not been used before, are applied to explore the spatial Optimal Occupancy variations and model variograms for spatial prediction. This study uses an anonymized bike trip dataset from 34 stations in downtown San Francisco to compare the traditionally-known QoS measure and the proposed Optimal Occupancy measure. Results reveal that the Optimal Occupancy is beneficial, outperforms the traditionally-known QoS measure, and produces a better prediction of the QoS at nearby locations. In addition, the Optimal Occupancy can be used to predict candidate locations for the introduction of new stations in an existing BSS.