Miracle-dz/UniFAR-FTUs huggingface dataset:
CCR2+ migratory macrophages with M1 status are the early-responders in the cornea of HSV-1 infected mice

Complex interactions between HSV-1 and infiltrating immune cells play important roles in establishing localized, acute virus replication as well as chronic latent infection. The extent and duration of initial virus replication are the key determinants of subsequent pathologic inflammatory responses and therefore, the accumulation of immune cell populations at this time point is a key target for prevention. Therefore, we evaluated the role of various immune cell infiltrates between 1 h and 28 days post-infection (PI) using mice infected with virulent HSV-1 strain McKrae without corneal scarification. The effect of corneal scarification on immune cell infiltrates was also determined. We first determined the activation status and origin of macrophage infiltrates as early as 1 h PI. We found a sharp increase in the total macrophage population after 12 h PI, that was primarily due to infiltration of CCR2+ migratory macrophages, mostly in M1 status (MHC II+). The number of CCR2- resident macrophages, mostly unpolarized (M0), increased gradually over time and peaked at 48 h PI. Interestingly, some of the resident macrophages gained an M2-like phenotype (CD206Low), which peaked at 12 h PI, concurrent with M1 macrophage infiltration. From 1–7 days PI, infiltration of various immune cells correlated strongly with HSV-1 replication, with neutrophils showing the biggest increase, and NKT cells the biggest decrease, after infection. The presence of geographical ulcer did not correlate with increased infiltration, while mice with corneal scarring had significantly more immune cell infiltration than those without corneal scarring. Overall, we showed time-dependent infiltration of various immune cells in the eye of HSV-1 infected mice. Initial infiltration of macrophages followed by infiltration of T cells at later times PI demonstrates the importance of targeting macrophages rather than other immune cells type, for therapeutic treatment of HSV-1.
Biasing and Distribution Functions for Different Galaxy Types in Optical and IRAS Catalogs

We describe a simple general objective method for determining the distribution functions (counts in cells) of biased subsamples. This method does not depend on any specific definition of a "cluster. " Applying this to morphological subsets of the UGC and ESO catalogs, and to the IRAS catalog, quantifies the excess clustering of early-type E + SO galaxies relative to Sa + Sb spirals. Spirals are distributed nearly randomly, while the average probability of finding an elliptical in a region containing M galaxies is p(M) approximately M0.3. If the present galaxy distribution is similar to the distribution when stripping and merging occurred, then these processes do not account for the observed morphology-density relation of ellipticals and spirals. Models in which stripping or merging occurred at high redshifts are constrained by the requirement that they evolve into the presently observed distribution functions of ellipticals and spirals, which are consistent with simple gravitational clustering. These morphology-density relations may be consistent with gravitational segregation if the average masses associated with ellipticals are several times greater than those of spirals. It may also reflect the initial density threshold for different galaxy types.
Protecting my turf: The moderating role of generational differences on the relationships between self-direction and hedonism values and reactions to generational diversity

ABSTRACT Drawing from basic human values theory and generational identity theory, we hypothesize that two self-focused values, self-direction and hedonism, will be negatively associated with reactions to generational diversity initiatives, and that this relationship will differ between millennials and non-millennials. As expected, our findings illustrate that self-direction and hedonism are negatively related to reactions to generational diversity initiatives. Additionally, self-direction’s influence on reactions to diversity initiatives is significantly higher for non-millennials than millennials. These findings suggest that generational differences affect cognitive processes surrounding reactions to generational diversity initiatives.
Interaction of magnetic reconnection and Kelvin‐Helmholtz modes for large magnetic shear: 2. Reconnection trigger

A typical property of magnetopause reconnection is a significant perpendicular shear flow due to the fast streaming magnetosheath plasma. Therefore, the magnetopause represents a large magnetic and flow shear boundary during periods of southward interplanetary magnetic field, which can be unstable to Kelvin‐Helmholtz (KH) modes and to magnetic reconnection. A series of local three‐dimensional MHD and Hall MHD simulations is carried out to investigate the interaction of reconnection and nonlinear KH waves considering magnetic reconnection as the primary process. It is demonstrated that the onset reconnection causes a thinning of the shear flow layer, thereby generating small wavelength KH modes. In turn, the growing KH modes modify the current layer width, which modulate the diffusion regions, increase the local reconnection rates, and generate field‐aligned currents. The simulation results imply a limitation of total amount of open flux likely caused by nonlinear saturation of KH growth and the associated diffusion. It is also demonstrated that the reconnection rate maximizes for conditions that allow a strong nonlinear evolution of KH waves, i.e., fast shear flow and limited guide magnetic field. The presence of Hall physics increases the reconnection rate in the early stage; however, the maximum reconnection rate and the total amount of open flux at saturation are the same as in the MHD case.
X-ray archaeology in the coma cluster

We present images of X-ray emission from hot gas within the Coma cluster of galaxies. These maps, made with the ROSAT satellite, have much higher SNR than any previous X-ray image of a galaxy cluster, and allow cluster structure to be analyzed in unprecedented detail. They show greater structural irregularity than might have been anticipated from earlier observations of Coma. Emission is detected from a number of bright cluster galaxies in addition to the two known previously. In four cases, there is evidence that these galaxies lie at the center of an extended subconcentration within the cluster, possibly the remnant of their associated groups. For at least two galaxies, the images show direct evidence for ongoing disruption of their gaseous atmosphere. The luminosity associated with these galaxies is comparable to that detected around similar ellipticals in much poorer environments. Emission is easily detected to the limit of our field, about 1 deg from the cluster center, and appears to become more regular at large radii. The data show clearly that this archetype of a rich and regular galaxy cluster was, in fact, formed by the merging of several distinct subunits which are not yet fully destroyed.
Low-Light Image Enhancement via a Deep Hybrid Network

Camera sensors often fail to capture clear images or videos in a poorly lit environment. In this paper, we propose a trainable hybrid network to enhance the visibility of such degraded images. The proposed network consists of two distinct streams to simultaneously learn the global content and the salient structures of the clear image in a unified network. More specifically, the content stream estimates the global content of the low-light input through an encoder–decoder network. However, the encoder in the content stream tends to lose some structure details. To remedy this, we propose a novel spatially variant recurrent neural network (RNN) as an edge stream to model edge details, with the guidance of another auto-encoder. The experimental results show that the proposed network favorably performs against the state-of-the-art low-light image enhancement algorithms.
A laboratory model of an atmospheric mesofront

Consideration is given to the leading edge of a well-defined flow of dense air without significant condensation, such as occurs at a thunderstorm outflow or a sea-breeze front. Explanation of the front is proposed in terms of a gravity (density) current formed by the denser air. Observations of such flows are related both to laboratory gravity current heads in which head, tail and calm wind conditions are simulated and to a simple, theoretical gravity current model based primarily on a momentum balance. Good agreement is found between the atmosphere, laboratory and analytical results. The mean flow in the gravity current behind the head is greater than the velocity of the head, a result of mixing between the two fluids. This mixing nearly all occurs at the leading edge of the current. The excess height of the head of the gravity current is interpreted as the mixing region at the leading edge, and this mixed fluid lays down a stable layer above the following gravity current. In the laboratory the effect of a headwind is to flatten the profile of the raised head at the front and to reduce its rate of advance by about three-fifths of the value of the opposing flow.
Assessment of heat flux turbulence models for flows dominated by buoyancy effects

Abstract Improved prediction of complex transport processes usually requires an application of advanced turbulence models. In some particular cases, such as environmental flows, where a variety of physical and thermodynamical processes may occur simultaneously, it is not an easy task to apply a consistent approach for all modelled variables of interest. Consequently, this suggests the use of simple model formulations. In seeking an acceptable turbulence model for the computation of buoyancy dominated turbulent flows, two variants of the modelled turbulent heat flux vector are presented and their performance in the simulation of the lifting of an atmospheric inversion is discussed. By these variants the turbulent heat flux is expressed in both algebraic and differential forms. In applying the algebraic heat flux turbulence model, it was necessary to solve the transport equation for temperature variance and retain its explicit influence in the derived algebraic heat flux model in order to obtain results of similar accuracy to those of the full differential heat flux model.
Improved ENSO prediction by singular vector analysis in a hybrid coupled model.

In this study, a method based on singular vector analysis is proposed to improve El Nino-Southern Os- cillation (ENSO) predictions. Its essential idea is that the initial errors are projected onto their optimal growth patterns, which are propagated by the tangent linear model (TLM) of the original prediction model. The forecast errors at a given lead time of predictions are obtained, and then removed from the raw pre- dictions. This method is applied to a realistic ENSO prediction model for improving prediction skill for the period from 1980 to 1999. This correction method considerably improves the ENSO prediction skill, com- pared with the original predictions without the correction.
A family of residual‐based stabilized finite element methods for Stokes flows

We present a collection of stabilized finite element (FE) methods derived via first‐ and second‐order finite calculus (FIC) procedures. It is shown that several well known existing stabilized FE methods such as the penalty technique, the Galerkin Least Square (GLS) method, the Pressure Gradient Projection (PGP) method and the orthogonal sub‐scales (OSS) method are recovered from the general residual‐based FIC stabilized form. A new family of stabilized Pressure Laplacian Stabilization (PLS) FE methods with consistent nonlinear forms of the stabilization parameters are derived. The distinct feature of the family of PLS methods is that they are residual‐based, i.e. the stabilization terms depend on the discrete residuals of the momentum and/or the incompressibility equations. The advantages and disadvantages of the different stabilization techniques are discussed and several examples of application are presented. Copyright © 2010 John Wiley & Sons, Ltd.
Spatial Variability of Groundwater Arsenic Concentration as Controlled by Hydrogeology: Conceptual Analysis Using 2‐D Reactive Transport Modeling

Combined geological, hydrogeological, and geochemical controls on the arsenic concentration of contaminated aquifers in SE Asia were explored by two‐dimensional (2‐D) reactive transport modeling of data sets from Bangladesh, Cambodia, and Vietnam. For each site, the field data are summarized and used to create a conceptual 2‐D reactive transport model that elucidates characteristic features influencing the groundwater arsenic concentration. Comparison of models for Bangladesh and Vietnam indicates that fine‐grained layers overlying young sandy aquifers generate shallow high arsenic groundwater because low vertical groundwater velocities allow sufficient time for kinetic As release from the sediment. The low vertical groundwater velocity below major river channels, predicted by the model, also creates long groundwater residence times, leading to high arsenic groundwater. Young aquifer sediments release more arsenic than older sediments, and alternating young and older sediments create complex patterns of high and low arsenic groundwater. Over time, floodplain basins will subside, and river channels migrate, causing sedimentation and erosion on the floodplain while creating local environments with evolving hydrogeology and groundwater geochemistry. We have developed a three‐step model for the evolution of the Red River floodplain with sedimentation and shifting channels over the last 6000 years. The results show comparable timescales between the dynamics of arsenic release and of river migration, causing complex groundwater As distributions, comprising geochemical palinopsia of long vanished rivers.
Evaluation of Piperacillin/Sulbactam, Piperacillin/Tazobactam and Cefoperazone/Sulbactam Dosages in Gram-Negative Bacterial Bloodstream Infections by Monte Carlo Simulation

The optimal regimens of piperacillin/sulbactam (PIS 2:1), piperacillin/tazobactam (PTZ 8:1), and cefoperazone/sulbactam (CSL 2:1) are not well defined in patients based on renal function. This study was conducted to identify optimal regimens of BLBLIs in these patients. The antimicrobial sensitivity test was performed by a two-fold agar dilution method. Monte Carlo simulation (MCS) was used to simulate the probability of target attainment (PTA) and the cumulative fraction of response (CFR) for various dosing regimens in patients with different renal functions. For strains with an MIC ≤ 8/4 mg/L, PIS 4.5 g q6h achieved 99.03%PTA in the subset of patients with creatinine clearance (CrCL) > 90 mL/min. For patients with CrCL 60–90 mL/min, PIS 4.5 g q6h achieved 81.2% CFR; for those with CrCL 40–59 mL/min, PIS 4.5 g q8h achieved 80.25% CFR. However, for patients infected by ESBL-producing Enterobacteriaceae, PIS 4.5 g q6h achieved a CFR lower than 80%. For patients infected by A. baumannii with a CrCL of 31–60 mL/min, PIS 6.0 g q8h and 4.5 g q6h achieved 81.24% and 82.42% CFR, respectively. For those infected by P. aeruginosa, PIS 4.5 g q6h reached 90% CFR. PIS and PTZ achieved a similar CFR when piperacillin was at the same dose. The CFRs of CSL were much lower than those of the other two agents in Enterobacteriaceae and P. aeruginosa infections. The antibacterial spectrum of PIS is superior to that of PTZ and CSL. Higher dosages and dosing adjustment according to renal function should be considered to treat Gram-negative bacterial BSIs.
Improving coverage accuracy of nonparametric prediction intervals

Methods are suggested for improving the coverage accuracy of intervals for predicting future values of a random variable drawn from a sampled distribution. It is shown that properties of solutions to such problems may be quite unexpected. For example, the bootstrap and the jackknife perform very poorly when used to calibrate coverage, although the jackknife estimator of the true coverage is virtually unbiased. A version of the smoothed bootstrap can be employed for successful calibration, however. Interpolation among adjacent order statistics can also be an effective way of calibrating, although even there the results are unexpected. In particular, whereas the coverage error can be reduced from O(n‐1) to orders O(n‐2) and O(n‐3) (where n denotes the sample size) by interpolating among two and three order statistics respectively, the next two orders of reduction require interpolation among five and eight order statistics respectively.
The Kolmogorov spectrum and its oceanic cousins: a review

Kolmogorov’s theory of turbulence in an incompressible fluid of constant density at high Reynolds numbers has provided a cornerstone for the interpretation of oceanic spectral measurements of turbulence. The most convincing verification of the theory came from observations by Grant, Stewart and Moilliet under conditions that clearly satisfy the basic premises of the theory, but subsequent measurements have explored the influence of ambient stratification and shear on both the energy and temperature spectra. As the turbulence decays, the larger scales of motion interact more weakly as do internal waves, so that Kolmogorov’s cascade becomes disrupted. It has long been known that the existence of a k-5/3 region in the spectrum does not require local isotropy and it is indicated that the success of Kolmogorov scaling in collapsing measured spectra in the dissipation range, does not require a continuing energy cascade from larger scales. Several questions remain unresolved, particularly the reasons for the shape of temperature spectra that have been measured in turbulence generated by large-scale internal waves in a tidal channel.
Multi-subtype classification model for non-small cell lung cancer based on radiomics: SLS model.

PURPOSE Histological subtypes of non-small cell lung cancer (NSCLC) are crucial for systematic treatment decisions. However, the current studies which used noninvasive radiomic methods to classify NSCLC histology subtypes mainly focused on two main subtypes: squamous cell carcinoma (SCC) and adenocarcinoma (ADC), while multi-subtype classifications that included the other two subtypes of NSCLC: large cell carcinoma (LCC) and not otherwise specified (NOS), were very few in the previous studies. The aim of this work was to establish a multi-subtype classification model for the four main subtypes of NSCLC and improve the classification performance and generalization ability compared with previous studies. METHODS In this work, we extracted 1029 features from regions of interest in computed tomography (CT) images of 349 patients from two different datasets using radiomic methods. Based on "three-in-one" concept, we proposed a model called SLS wrapping three algorithms, synthetic minority oversampling technique, ℓ2,1-norm minimization, and support vector machines, into one hybrid technique to classify the four main subtypes of NSCLC: SCC, ADC, LCC, and NOS, which could cover the whole range of NSCLC. RESULTS We analyzed the 247 features obtained by dimension reduction, and found that the extracted features from three methods: first order statistics, gray level co-occurrence matrix, and gray level size zone matrix, were more conducive to the classification of NSCLC subtypes. The proposed SLS model achieved an average classification accuracy of 0.89 on the training set (95% confidence interval [CI]: 0.846 to 0.912) and a classification accuracy of 0.86 on the test set (95% CI: 0.779 to 0.941). CONCLUSIONS The experiment results showed that the subtypes of NSCLC could be well classified by radiomic method. Our SLS model can accurately classify and diagnose the four subtypes of NSCLC based on CT images, and thus it has the potential to be used in the clinical practice to provide valuable information for lung cancer treatment and further promote the personalized medicine.
Stochastic Modeling of Groundwater Flow by Unconditional and Conditional Probabilities: The Inverse Problem

The inverse problem is defined here as follows: determine the transmissivity at varius points, given the shape and boundary of the aquifer and recharge intensity and given a set of measured log-transmissivity Y and head H values at a few points. The log-transmissivity distribution is regarded as a realization of a random function of normal and stationary unconditional probability density function (pdf). The solution of the inverse problem is the conditional normal pdf of Y, conditioned on measured H and Y, which is expressed in terms of the unconditional joint pdf of Y and H. The problem is reduced to determining the unconditional head-log-transmissivity covariance and head variogram for a selected Y covariance which depends on a few unknown parameters. This is achieved by solving a first-order approximation of the flow equations. The method is illustrated for an exponential Y covariance, and the effect of head and transmissivity measurements upon the reduction of uncertainty of Y is investigated systematically. It is shown that measurement of H has a lesser impact than those of Y, but a judicious combination may lead to significant reduction of the predicted variance of Y. Possible applications to real aquifers are outlined.
Adapting Two-Moment Microphysics Schemes across Model Resolutions: Subgrid Cloud and Precipitation Fraction and Microphysical Sub–Time Step

AbstractTwo-moment multiclass microphysics schemes are very promising tools to be used in high-resolution NWP models. However, they must be adapted for coarser resolutions. Here, a twofold solution is proposed—namely, a simple representation of subgrid cloud and precipitation fraction—as well as a microphysical sub-time-stepping method. The scheme is easy to implement, allows supersaturation in ice cloud, and exhibits flexibility for adoption across model grid spacing. It is implemented in the Milbrandt and Yau two-moment microphysics scheme with prognostic precipitation in the context of a simple 1D kinematic model as well as a mesoscale NWP model [the Canadian regional Global Environmental Multiscale model (GEM)]. Sensitivity tests were performed and the results highlighting the advantages and disadvantages of the two-moment multiclass cloud scheme relative to the classical Sundqvist scheme. The respective roles of subgrid cloud fraction, precipitation fraction, and time splitting were also studied. Whe.
The Role of Red Cell Distribution Width as a Prognostic Marker in Chronic Liver Disease: A Literature Review

Liver disease is one of the leading public health problems faced by healthcare practitioners regularly. As such, there has been a search for an inexpensive, readily available, non-invasive marker to aid in monitoring and prognosticating hepatic disorders. Recently, red blood cell distribution width (RDW) has been found to be associated with various inflammatory conditions with implications for its use as a potential marker for assessing disease progression and prognosis in multiple conditions. Multiple factors effect red blood cell production whereby a dysfunction in any process can lead to anisocytosis. Furthermore, a chronic inflammatory state leads to increased oxidative stress and produces inflammatory cytokines causing dysregulation and increased intracellular uptake and use of both iron and vitamin B12, which leads to a reduction in erythropoiesis causing an increase in RDW. This literature review reviews in-depth pathophysiology that may lead to an increase in RDW and its potential correlation with chronic liver diseases, including hepatitis B, hepatitis C, hepatitis E, non-alcoholic fatty liver disease, autoimmune hepatitis, primary biliary cirrhosis, and hepatocellular carcinoma. In our review, we examine the use of RDW as a prognostic and predictive marker for hepatic injury and chronic liver disease.