Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of biomass burning smoke influence on environmental conditions for multiyear tornado outbreaks by combining aerosol‐aware microphysics and fire emission constraints

We use the Weather Research and Forecasting (WRF) system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the U.S. during spring. The model is configured with an aerosol‐aware microphysics parameterization capable of resolving aerosol‐cloud‐radiation interactions in a cost‐efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included, and smoke emissions are constrained using an inverse modeling technique and satellite‐based aerosol optical depth observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low‐level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low‐level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud‐level tending to burn‐off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF‐Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics, and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near‐storm environments. This provides reliability on the aerosol‐aware microphysics scheme as a less computationally expensive alternative to WRF‐Chem for its use in applications such as NWP and cloud‐resolving simulations.
Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks

Interstitial lung diseases (ILD) involve several abnormal imaging patterns observed in computed tomography (CT) images. Accurate classification of these patterns plays a significant role in precise clinical decision making of the extent and nature of the diseases. Therefore, it is important for developing automated pulmonary computer-aided detection systems. Conventionally, this task relies on experts’ manual identification of regions of interest (ROIs) as a prerequisite to diagnose potential diseases. This protocol is time consuming and inhibits fully automatic assessment. In this paper, we present a new method to classify ILD imaging patterns on CT images. The main difference is that the proposed algorithm uses the entire image as a holistic input. By circumventing the prerequisite of manual input ROIs, our problem set-up is significantly more difficult than previous work but can better address the clinical workflow. Qualitative and quantitative results using a publicly available ILD database demonstrate state-of-the-art classification accuracy under the patch-based classification and shows the potential of predicting the ILD type using holistic image.
Australian bat lyssavirus

BACKGROUND Australian bat lyssavirus (ABLV) causes human illness that is indistinguishable from classical rabies. All Australian bats have the potential to carry and transmit ABLV, and potentially risky human exposures to bats are common. ABLV infection has resulted in three human deaths in Australia since 1996. OBJECTIVE The aim of this article is to equip general practitioners (GPs) to assist in the prevention and management of potential ABLV exposures in Australia, including complex clinical scenarios that are not fully addressed in current national guidelines. DISCUSSION Potential ABLV exposures are frequently encountered in general practice. GPs play a critical role in risk mitigation for groups such as veterinarians and wildlife carers, and in triggering urgent multidisciplinary responses to potential exposures. Timely notification of the public health unit following a potential exposure is crucial to ensure appropriate assessment and access to correct treatment. Complex exposure scenarios require careful consideration.
Monte Carlo Bayesian inference on a statistical model of sub‐gridcolumn moisture variability using high‐resolution cloud observations. Part 2: Sensitivity tests and results

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub‐gridcolumn moisture variability using high‐resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large‐scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud‐top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non‐assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non‐gradient‐based jumps into regions of non‐zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost‐effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive‐radiometer‐retrieved cloud observables on cloud vertical structure, beyond cloud‐top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow‐dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.
Scene Text Detection with Novel Superpixel Based Character Candidate Extraction

Maximally stable extremal region (MSER) is popularly used for candidate character candidate extraction in scene text detection. Its requirement of maximum stability hinders high performance on images of high variability. In this paper, we propose a novel character candidate extraction method based on superpixel segmentation and hierarchical clustering. The proposed superpixel segmentation algorithm for scene text image takes advantage of the color consistency of characters and fuses color and edge information. Based on superpixel segmentation, character candidates are extracted by single-link clustering. To improve the accuracy of non-text candidate filtering, we use a deep convolutional neural networks (DCNN) classifier and double threshold strategy for classification. Experimental results on public datasets demonstrate that the proposed superpixel based method performs better than MSER in character candidate extraction, and the proposed system achieves competitive performance compared to state-of-the-art methods.
Heart rate and the risk of adverse outcomes in patients with heart failure with preserved ejection fraction

Background Although high resting heart rates are associated with adverse outcomes in heart failure with reduced ejection, the reports for heart failure with preserved ejection fraction (HFpEF) are conflicting. Design A secondary analysis was conducted in order to examine the relationship between resting heart rate and adverse outcomes in 2705 patients (mean age = 68 ± 10 years; 47% men; 88% white) with HFpEF who were in sinus rhythm from the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial (TOPCAT). Methods Baseline heart rate was obtained from baseline electrocardiogram data. Outcomes were adjudicated by a clinical end-point committee and included the following factors: hospitalisation, hospitalisation for heart failure, death and cardiovascular death. Results Over a median follow-up of 3.4 years (25th–75th percentiles = 2.0–4.9 years), a total of 1157 hospitalisations, 311 hospitalizations for heart failure, 369 deaths and 233 cardiovascular deaths occurred. An increased risk (per 5-beats per minute [bpm] increase) for hospitalisation (hazard ratio [HR] = 1.03, 95% confidence interval [CI] = 1.004–1.060), hospitalisation for heart failure (HR = 1.10, 95% CI = 1.05–1.15), death (HR = 1.10, 95% CI = 1.06–1.16) and cardiovascular death (HR = 1.13, 95% CI = 1.07–1.19) was observed. When the analysis was limited to those who did not report the use of β-blockers, the magnitude of the association for each outcome (per 5-bpm increase) was not materially altered (hospitalisation: HR = 1.03, 95% CI = 0.97–1.09; hospitalisation for heart failure: HR = 1.12, 95% CI = 0.98–1.27; death: HR = 1.16, 95% CI = 1.05–1.28; cardiovascular death: HR = 1.12, 95% CI = 0.99–1.27). Conclusion High resting heart rate is a risk factor for adverse outcomes in patients with HFpEF, and future studies are needed in order to determine whether reducing heart rate improves outcomes in HFpEF.
Clonality disguises the vulnerability of a threatened arid zone Acacia

Abstract Long‐lived, widespread plant species are expected to be genetically diverse, reflecting the interaction between large population sizes, overlapping generations, and gene flow. Such species are thought to be resilient to disturbance, but may carry an extinction debt due to reproductive failure. Genetic studies of Australian arid zone plant species suggest an unusually high frequency of asexuality, polyploidy, or both. A preliminary AFLP genetic study implied that the naturally fragmented arid zone tree, Acacia carneorum, is almost entirely dependent on asexual reproduction through suckering, and stands may have lacked genetic diversity and interconnection even prior to the onset of European pastoralism. Here we surveyed microsatellite genetic variation in 20 stands to test for variation in life histories and further assessed the conservation status of the species by comparing genetic diversity within protected stands in National Parks and disturbed range lands. Using herbarium records, we estimate that 219 stands are extant, all of which occur in the arid zone, west of the Darling River in southeastern Australia. With two exceptions, all surveyed stands comprised only one multilocus genet and at least eight were putatively polyploid. Although some stands comprise thousands of stems, our findings imply that the species as a whole may represent ~240 distinct genetic individuals, many of which are polyploid, and most are separated by >10 km of unsuitable habitat. With only 34% of stands (and therefore genets) occurring within conservation reserves, A. carneorum may be at much greater risk of extinction than inferred from on‐ground census data. Land managers should prioritize on‐ground preservation of the genotypes within existing reserves, protecting both vegetative suckers and seedlings from herbivory. Importantly, three stands are known to set viable seed and should be used to generate genetically diverse germ‐plasm for ex situ conservation, population augmentation, or translocation.
Synergistic effects of hybrid conductive fillers on the electrical properties of carbon fiber pultruded polypropylene/polycarbonate composites prepared by injection molding

In this study, the effects of filler characteristics and composite preparation methods on the morphology, mechanical property, electrical conductivity, and electromagnetic interference shielding effectiveness of the polypropylene/polycarbonate (70/30, wt%)/hybrid conductive filler composites were investigated. Nickel-coated carbon fiber (NCCF) was used as main filler and TiO2, multi-walled carbon nanotube, and graphite were used as second fillers in the composites. The pultruded NCCF/polypropylene composite was used in the preparation of the polypropylene/polycarbonate/NCCF/second filler composites. The electrical conductivity and electromagnetic interference shielding effectiveness of the polypropylene/polycarbonate/NCCF/second filler composites were compared with the type of second filler. The superior value of electromagnetic interference shielding effectiveness was observed to be 51.6 dB (decibel) when the hybrid fillers such as NCCF (5.2 vol% or 20 wt%) and TiO2 (1.2 vol% or 5 wt%) were added in the polypropylene/polycarbonate (70/30) composite. The electrical properties of the polypropylene/polycarbonate (70/30)/NCCF/TiO2 composites was compared with the composite preparation methods, which were injection molding and screw extrusion. The results suggested that fiber length of the NCCF affected significantly to the electrical conductivity and electromagnetic interference shielding effectiveness of the polypropylene/polycarbonate (70/30)/NCCF/TiO2 composites.
Group cohesion and homework adherence in multi-family group therapy for schizophrenia

This study examined the relationship between levels of group cohesion, defined as whole group relationships, and between-session therapeutic homework adherence in a multi-family group therapy (MFGT) for people with schizophrenia. Participants from 18 consenting families attending MFGT groups completed weekly homework adherence ratings, group cohesion and spontaneous between-session activity measures. Levels of group cohesion at each session were compared with measures of scheduled and spontaneous homework adherence reported at the next session. It was hypothesised that higher levels of group cohesion would be related to homework adherence and other spontaneous between-session therapeutic activity completed by group members. Results show higher levels of group cohesion were associated with higher rates of spontaneous between-session therapeutic activity. However, contrary to expectations no significant relationship between cohesion and scheduled homework completion was found. The implications of the findings for group processes and homework adherence are discussed.
Mutli-Features Prediction of Protein Translational Modification Sites

Post translational modification plays a significiant role in the biological processing. The potential post translational modification is composed of the center sites and the adjacent amino acid residues which are fundamental protein sequence residues. It can be helpful to perform their biological functions and contribute to understanding the molecular mechanisms that are the foundations of protein design and drug design. The existing algorithms of predicting modified sites often have some shortcomings, such as lower stability and accuracy. In this paper, a combination of physical, chemical, statistical, and biological properties of a protein have been ulitized as the features, and a novel framework is proposed to predict a protein's post translational modification sites. The multi-layer neural network and support vector machine are invoked to predict the potential modified sites with the selected features that include the compositions of amino acid residues, the E-H description of protein segments, and several properties from the AAIndex database. Being aware of the possible redundant information, the feature selection is proposed in the propocessing step in this research. The experimental results show that the proposed method has the ability to improve the accuracy in this classification issue.
Simvastatin induced actin cytoskeleton disassembly in normal and transformed fibroblasts without affecting lipid raft integrity

Statins are the most commonly prescribed agents used to modulate cholesterol levels in course of hypercholesterolemia treatment because of their relative tolerability and LDL‐C lowering effect. Recently, there are emerging interests in the perspectives of statin drugs as anticancer agents based on preclinical evidence of their antiproliferative, proapoptotic, and anti‐invasive properties. Functional impact of statin application on transformed cells still remains obscure that requires systematic study on adequate cellular models to provide correct comparison with their non‐transformed counterparts. Cholesterol is the major lipid component of mammalian cells and it plays a crucial role in organization, lateral heterogeneity, and dynamics of plasma membrane as well as in membrane‐cytoskeleton interrelations. To date, it is uncertain whether cellular effects of statins involve lipid‐dependent alteration of plasma membrane. Here, the effects of simvastatin on lipid rafts, F‐actin network and cellular viability were determined in comparative experiments on transformed fibroblasts and their non‐transformed counterpart. GM1 lipid raft marker staining indicated no change of lipid raft integrity after short‐ or long‐term simvastatin treatments. In the same time, simvastatin induced cytoskeleton rearrangement including partial F‐actin disruption in cholesterol‐ and lipid raft‐independent manner. Simvastatin dose‐dependently affected viability of BALB/3T3 and 3T3B‐SV40 cell lines: transformed fibroblasts were noticeably more sensitive to simvastatin comparing to non‐transformed cells.
Population modeling for pesticide risk assessment of threatened species—A case study of a terrestrial plant, Boltonia decurrens

Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed, individual‐based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species’ population dynamics and were included in the model approach. The authors use the model to compare the population‐level effects of 5 toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism‐level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population‐level risk assessments of listed species. Population‐level effects of herbicides can be assessed in a realistic and species‐specific context, and uncertainties can be addressed explicitly. The authors discuss how their approach can inform the future development and application of modeling for population‐level risk assessments of listed species, and ecological risk assessment in general. Environ Toxicol Chem 2017;36:480–491. © 2016 SETAC
Outcomes in patients treated with ticagrelor or clopidogrel after acute myocardial infarction: experiences from SWEDEHEART registry.

AIMS Ticagrelor reduces ischaemic events and mortality in acute coronary syndrome (ACS) vs. clopidogrel. We wished to study clinical outcomes in a large real-world population post-ACS. METHODS AND RESULTS We performed a prospective cohort study in 45 073 ACS patients enrolled into Swedish Web system for Enhancement and Development of Evidence-based care in Heart Disease Evaluated According to Recommended Therapies who were discharged on ticagrelor (N = 11 954) or clopidogrel (N = 33 119) between 1 January 2010 and 31 December 2013. The primary outcome was a composite of all-cause death, re-admission with myocardial infarction (MI) or stroke, secondary outcomes as the individual components of the primary outcome, and re-admission with bleeding. The risk of the primary outcome with ticagrelor vs. clopidogrel was 11.7 vs. 22.3% (adjusted hazard ratio (HR) 0.85 [95% confidence interval: 0.78-0.93]), risk of death 5.8 vs. 12.9% (adjusted HR 0.83 [0.75-0.92]), and risk of MI 6.1 vs. 10.8% (adjusted HR 0.89 [0.78-1.01]) at 24 months. Re-admission with bleeding with ticagrelor vs. clopidogrel occurred in 5.5 vs. 5.2% (adjusted HR 1.20 [1.04-1.40]). In a subset of patients undergoing percutaneous coronary intervention (PCI) on ticagrelor vs. clopidogrel the PCI-related in-hospital bleeding was 3.7 vs. 2.7% (adjusted odds ratio, OR, 1.57 [1.30-1.90]). CONCLUSION Ticagrelor vs. clopidogrel post-ACS was associated with a lower risk of death, MI, or stroke, as well as death alone. Risk of bleeding was higher with ticagrelor. These real-world outcomes are consistent with randomized trial results.
Distributed Non-Convex First-Order optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms

Consider a distributed non-convex optimization problem, in which a number of agents connected by a network $\mathcal{G}$ collectively optimize a sum of smooth and non-convex local objective functions. We address the following important question: For a class of unconstrained problems, if only local gradient information is available, what is the fastest rate that distributed algorithms can achieve, and how to achieve those rates. We perform a lower bound analysis for a class of first-order distributed methods which only utilizes local gradient information. We show that in the worst-case it takes at least $\mathcal{O}(1/\sqrt{\xi(\mathcal{G})}\times L/\epsilon)$ iterations to achieve certain $\epsilon$-solution, where $\xi(\mathcal{G})$ represents the spectrum gap of the graph Laplacian matrix, and L is some Lipschitz constant. Further, for a general problem class, we propose rate-optimal methods whose rates match the lower bounds (up to a polylog factor). To the best of our knowledge, this is the first time that lower rate bounds and optimal methods have been developed for distributed non-convex optimization problems.
A cross sectional and longitudinal study of endodontic and periapical status in an Australian population

BACKGROUND This study describes the cross sectional and longitudinal data of endodontic and periapical status of new patients presenting to a major dental hospital, and assesses the relationships between tooth-related variables with apical periodontitis. METHODS The records of 695 patients were randomly selected and the orthopantomograms of these patients up to 31 October 2014 were reviewed by two endodontists. The periapical status of teeth was recorded using the periapical index. The presence and quality of root fillings and coronal restorations were recorded. Statistical analysis included Fleiss' kappa, Cohen's kappa and logistic regression set at P < 0.05. RESULTS Of 695 patient records and 16 936 teeth examined, 138 (19.9%) patients or 284 (1.7%) teeth had root fillings and 179 (25.8%) patients or 325 (1.9%) teeth had apical periodontitis. Root fillings and coronal restorations were adequate in 34.6% and 69.4% teeth, respectively. A large proportion (47%) of teeth with apical periodontitis remained unchanged in subsequent orthopantomograms. CONCLUSIONS There was lower prevalence of root filled teeth or apical periodontitis in the present study compared with international studies. The frequency of adequate root fillings must be considered unacceptably low. Teeth with apical periodontitis may remain quiescent in the absence of caries or restorative breakdown.