Miracle-dz/UniFAR-FTUs huggingface dataset:
Depleting plasmacytoid dendritic cells reduces local type I interferon responses and disease activity in patients with cutaneous lupus

VIB7734 depletes plasmacytoid dendritic cells and demonstrates clinical benefit in patients with cutaneous lupus. Depleting plasmacytoid dendritic cells Plasmacytoid dendritic cells (pDCs) are immune cells that secrete large amounts of proinflammatory molecules, an essential function that is known to promote clearance of viral infections. However, persistent activation of pDCs is associated with autoimmune diseases, including cutaneous lupus. In this study, Karnell et al. developed and tested a monoclonal antibody to target pDCs, finding that the antibody, VIB7734, depleted pDCs both in nonhuman primates and in patients with autoimmune disease. VIB7734 treatment reduced symptom severity in individuals with cutaneous lupus, suggesting that depleting pDCs is a feasible and effective strategy for treating patients with autoimmunity. Plasmacytoid dendritic cells (pDCs) not only are specialized in their capacity to secrete large amounts of type I interferon (IFN) but also serve to enable both innate and adaptive immune responses through expression of additional proinflammatory cytokines, chemokines, and costimulatory molecules. Persistent activation of pDCs has been demonstrated in a number of autoimmune diseases. To evaluate the potential benefit of depleting pDCs in autoimmunity, a monoclonal antibody targeting the pDC-specific marker immunoglobulin-like transcript 7 was generated. This antibody, known as VIB7734, which was engineered for enhanced effector function, mediated rapid and potent depletion of pDCs through antibody-dependent cellular cytotoxicity. In cynomolgus monkeys, treatment with VIB7734 reduced pDCs in blood below the lower limit of normal by day 1 after the first dose. In two phase 1 studies in patients with autoimmune diseases, VIB7734 demonstrated an acceptable safety profile, comparable to that of placebo. In individuals with cutaneous lupus, VIB7734 profoundly reduced both circulating and tissue-resident pDCs, with a 97.6% median reduction in skin pDCs at study day 85 in VIB7734-treated participants. Reductions in pDCs in the skin correlated with a decrease in local type I IFN activity as well as improvements in clinical disease activity. Biomarker analysis suggests that responsiveness to pDC depletion therapy may be greater among individuals with high baseline type I IFN activity, supporting a central role for pDCs in type I IFN production in autoimmunity and further development of VIB7734 in IFN-associated diseases.
Three-dimensional structural characteristics of flow separation induced by a forward-facing step in a turbulent channel flow

Abstract Separating and reattaching turbulent flows induced by a forward-facing step subjected to an incoming fully developed turbulent channel flow are studied using direct numerical simulation. The step height is one quarter of the channel height, and the Reynolds number based on friction velocity and half-channel height at the inlet is 180. The three-dimensional spatio-temporal characteristics of separation bubbles upstream and downstream of the step are analysed with particular attention to the effects of impinging hairpin structures and the topology of principal stretching. Immediately upstream of the step, the fluctuating vorticity parallel to the mean streamlines is significant. On the frontal surface of the step, strong spanwise skin friction appears in the form of alternating positive and negative values in vertical strips. Over the step, the principal stretching switches orientation along a curve emanating from the leading edge, which is termed the principal stretching line (PSL). The reverse flows upstream and downstream of the step possess dominant and harmonic frequencies that mirror those of the incoming flow. As a hairpin structure leans over the step, the associated vorticity is deformed by the principal stretching. Specifically, PSL marks the lower bound of the deformed hairpin legs, and an opposite-signed pair of counter-rotating quasi-streamwise vortices are induced near the top surface of the step. Consequently, the separation bubbles upstream of and over the step are enlarged and suppressed, respectively. For a sufficiently strong hairpin structure interacting with the step, an open-type separation occurs upstream of the step, while dual separation bubbles appear over the step.
Vortical–acoustic resonance in an acoustic resonator: Strouhal number variation, destabilization and stabilization

Abstract The impact of acoustic resonance on vortical–acoustic resonance and flow instability is studied by a combined travelling–global mode analysis about a low-speed inviscid parallel shear flow in two-dimensional symmetric duct–cavity configurations. First, in a shallow-cavity case, we show that the difference between incompressible and compressible models in describing the compact feedback loop, consisting of the Kelvin–Helmholtz (KH) instability wave and the Rayleigh–Powell–Rossiter (RPR) feedback, is small and the global mode frequency follows the Strouhal law. Using the compact case as a baseline for comparison, the influence of an acoustic resonator (AR) on the $\textrm {KH}+\textrm {RPR}$ feedback loop is then examined. In this deep-cavity case, phenomena such as frequency deviation from the Strouhal law, global mode switching, global mode destabilization and stabilization, caused by a trapped or a heavily damped acoustic resonant mode, are observed. We show that those phenomena can be explained by the local–global relation of the feedback loop and the dual-feedback view: the coexistence of RPR and AR feedbacks. The Strouhal number variation is due to the phase difference of the unstable vortical wave between the upstream and downstream cavity edges being changed by the additional AR feedback. It is found that the switching is not a vortical but an acoustic effect. The destabilization and stabilization, near and far from an acoustic resonance, are respectively understood as the result of the total feedback at the upstream edge being strengthened and weakened by the AR feedback.
Thermodynamics of Fe oxides: Part I. Entropy at standard temperature and pressure and heat capacity of goethite (α-FeOOH), lepidocrocite (γ-FeOOH), and maghemite (γ-Fe2O3)

Abstract The heat capacities (CP) of goethite (goe, α-FeOOH), lepidocrocite (lep, γ-FeOOH), and maghemite (mag, γ-Fe2O3) were measured from below liquid helium temperature up to their decomposition temperatures by a combination of adiabatic, semi-adiabatic, and differential scanning calorimetry. All three phases were synthetic, with <160 ppm of Al. Chlorine content in goe (32 ppm) and lep (202 ppm) is too low to affect the calorimetric results of this study. Phase purity was verified by Rietveld refinement of the powder X-ray diffraction (XRD) patterns; we determined lattice parameters, atomic positions, crystallite size, and microstrain for all three samples. The Brunauer-Emmet-Teller (BET) surface area is 21 (goe), 23 (lep), and 18 (mag) m2/g. No amorphous impurity was found in the goethite sample by extraction of the oxalate soluble fraction. The excess water, determined from weight loss after firing at 1200 K overnight, is 0.083 ± 0.010 (goe), 0.087 ± 0.005 (lep), 0.042 ± 0.003 (mag) moles of water per mole of FeOOH or Fe2O3. The entropy at standard temperature and pressure (STP) was calculated from subambient CP data and corrected for the excess water content using a Debye-Einstein representation of the CP of hexagonal ice. The entropy at STP is 59.7 ± 0.2 (goe), 65.1 ± 0.2 (lep), and 93.0 ± 0.2 (mag) J/(K·mol). The XRD pattern of maghemite lacks superstructure peaks, and complete disorder of the vacancies leads to configurational entropy Sconf = 2.0 J/K·mol. Because very weak superstructure peaks can be overlooked, or the vacancies may be short-range ordered, this calculated Sconf represents only an upper limit. The heat capacity above 273 K was fitted to a Maier-Kelley polynomial CP [J/(K·mol), T in K] = a + bT + cT-2. The CP polynomial coefficients are a = 1.246, b = 0.2332, c = 313900 (goe, valid in temperature range 273-375 K), a = 59.76, b = 0.06052, c = -772900 (lep, 273-390 K), and a = 106.8, b = 0.06509, c = -1886000 (mag, 273-760 K).
Microbial community structure in rice, crops, and pastures rotation systems with different intensification levels in the temperate region of Uruguay

Rice is an important crop in Uruguay associated mostly with livestock production in a rice and pasture rotation system since the 1920s. However, in recent years there has been interest in intensifying the production in some of these systems to satisfy market demands and increase income. Intensification occurs by augmenting the rice frequency in the rotation, including new crops like sorghum and soybean, or shortening the pasture phase. A long-term experiment was established in 2012 in the main rice producing area of Uruguay with the objective to study the impact of intensification in rice rotations. After the first cycle of rotation soils from seven rotation phases were sampled and microbial communities were studied by means of high-throughput sequencing of Illumina NovaSeq 6000. Archaeal/bacterial and fungal community composition were studied (16S rRNA and 18S gene regions) detecting 3662 and 807 bacterial and fungal Operational Taxonomic Units (OTUs), respectively. Actinobacteria, Firmicutes and Proteobacteria were the most common bacterial phyla. Among them, only Proteobacteria differed significantly between rotations. Although most fungal OTUs were unidentified, Ascomycota, Basidiomycota and Mucoromycota were the most abundant fungal classes within identified taxa. Bacterial communities differed between rotations forming three groups according to the percentage of rice in the system. Fungal communities clustered in four groups, although not well differentiated, and mostly associated with the antecessor crop. Only P and C:N varied between rotations among soil physicochemical variables after six years, and individual bacterial OTUs appeared weakly influenced by P, pH, Mg and fungal OTUs by P. The results suggest that after six years, bacteria/archaeal communities were influenced by the time with rice in the rotation, and fungal communities were more influenced by the antecessor crop. More studies are needed to associate fungal communities with certain rotational or environmental variables. Some taxa were associated with a particular rotation, and some bacterial taxa were identified as biomarkers. Fungal indicator taxa were not identified at the species level for any rotation.
Describing small-angle scattering profiles by a limited set of intensities

Small angle scattering (SAS) probes the size and shape of particles at low resolution through the analysis of the scattering of X-rays or neutrons passing through a solution of particles. One approach to extracting structural information from SAS data is the indirect Fourier transform (IFT). The IFT approach parameterizes the real space pair distribution function (P(r)) of a particle using a set of basis functions, which simultaneously determines the scattering profile (I(q)) using corresponding reciprocal space basis functions. This article presents an extension of an IFT algorithm proposed by Moore which used a trigonometric series to describe the basis functions, where the real space and reciprocal space basis functions are Fourier mates. An equation is presented relating the Moore coefficients to the intensities of the SAS profile at specific positions as well as a series of new equations that describe the size and shape parameters of a particle from this distinct set of intensity values. An analytical real space regularizer is derived to smooth the P(r) curve and ameliorate systematic deviations caused by series termination, commonly used in IFT methods though not described in Moore’s original approach, which is particularly susceptible to such effects. The algorithm is provided as a script, denss. fit_data. py, as part of the DENSS software package for SAS, which includes both command line and interactive graphical interfaces. Results of the program using experimental data show that it is as accurate, and often more accurate, than existing tools.
Prediction of oil well production based on the time series model of optimized recursive neural network

Abstract The Arps decline model is one of the most commonly used oil field production prediction methods. However, the predictions of Arps decline model are not ideal. In this work, we designed a method that uses long-short term memory (LSTM) network and gate recurrent unit (GRU) to predict oil production. These models use multiple data features for oil well production prediction. The designed method considers the time series and has the ability to deal with nonlinear problems. On the basis of case study of the two numerical models performed on the dataset collected from actual oilfield in China and India, the LSTM and GRU are used to predict the oil production prediction. The final results show that LSTM and GRU have their respective advantages under different input parameters, providing an effective method for dynamic prediction of oil well production. These methods have the ability to be a quick and real-time auxiliary basis for oil well production planning, and have practical value.
A comprehensive review on remote sensing image registration

ABSTRACT Over the last two decades, there has been a significant improvement in the quality and volume of the remote-sensing images. With the extensive availability of the images, these are used in many applications such as change detection, image mosaicing, and image fusion where image registration is very necessary. However, image registration is a challenging task in remote sensing due to the following reasons: geometric differences between images, intensity differences, and noise affect. Over the years, wide variety of algorithms have come into existence to handle these issues. In this paper, a comprehensive review is presented on these remote sensing image registration methods. At first, the general information of remote sensing image registration, its classifications, and application areas are provided. Then, an exhaustive review is given on the existing methods and their merits as well as shortcomings are mentioned. Finally, a comparative analysis is provided for the state-of-the-art methods and current challenges of this research are presented.
Estimation of precipitation intensity based on small wisely network (SW-Net)

ABSTRACT Precipitation estimation with high spatial and temporal resolution is very important for monitoring floods and natural disasters. At present, a couple of quantitative precipitation estimation products and research methods can successfully estimate precipitation at one hourly temporal resolution. In this study, a deep learning model based on Convolutional Neural Network (CNN) was proposed to estimate the precipitation intensity based on the hyperspectral satellite FengYun-4/Advanced Geostationary Radiation Imager (FY-4A), and the temporal resolution is reduced to half an hour. Firstly, the importance of different channels and channel differences for precipitation intensity estimation was determined by ablation experiments. Secondly, compared with the existing model Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks (PERSIANN-CNN) and U-Net. The experimental results show that Small Wisely Network (SW-Net) provides more accurate precipitation intensity estimation, compared with PERSIANN-CNN (U-Net) in the same spatial and temporal resolutions. SW-Net outperformed PERSIANN-CNN (U-Net) by 5.9439% (5.6298%) and 6.3600 (5.8400) percentage points in the loss value and Mean Intersection over Union (MIoU), demonstrating the better feature extraction performance of the model. Furthermore, the False Alarm Ratio (FAR) of precipitation estimation with respect to Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (GPM-IMERG), for SW-Net was lower than that of PERSIANN-CNN (U-Net) by 49.2132% (49.4302%), showing the higher accuracy of proposed model.
Features of the structure formation of PZT thin films by reactive plasma sputtering

Abstract The electrophysical characteristics of the PZT film formed on a silicon by the method of high-frequency reactive plasma sputtering were studied, and their relationship with the structure of the film was established. In particular, the hysteresis in the capacitance-voltage characteristics of the metal - ferroelectric - semiconductor indicates the polarization of the film, which, in turn, indicates the presence of the perovskite phase in the PZT film. However, the crystallite size of this phase is so small that it cannot be detected by X-ray diffraction analysis.
Impact of vertical integration on movie scheduling in Korea

ABSTRACT This study investigates the impact of vertical integration on movie screening decisions using data from the Korean movie industry (Korea in the text refers to the Republic of Korea, also known as South Korea). Previous studies have found that movie exhibitors (i.e. theaters) that own distributors allocated more screens when they release their affiliated movies. The novelty of this study is that it focuses on the impact of vertical integration on showtime scheduling of integrated players that own both distribution services and theaters. Controlling for seasonality, levels of competition, and expected quality of movies, the study found evidence of the dominating power of integrated players in the market that occupied more screens and put their movies in more favorable time slots. However, this power weakened after the opening week and did not appear by the fourth week. Although the integrated exhibitors are likely to screen their affiliated distributors’ movies more in the opening week, they did not block other distributors’ movies over time. Our study suggests that the integrated theaters’ screening decisions favorable to their own movies are better understood as the result of pursuing incentives rather than as the result of blocking competitors’ movies.
Pulse Frequency in Crop Rotations Alters Soil Microbial Community Networks and the Relative Abundance of Fungal Plant Pathogens

Including pulse crops in cereal-based cropping systems has become a widely accepted and useful agronomic practice to increase crop diversification and biologically fixed nitrogen in agroecosystems. However, there is a lack of knowledge regarding how the intensification of pulses in crop rotations influence soil microbial communities. In this study, we used an amplicon sequencing approach to examine the bulk and rhizosphere soil bacterial and fungal communities from the wheat (Triticum aestivum L.) phase (final year of 4 years rotations) of a long-term pulse intensification field trial in the semi-arid region of the Canadian Prairies. Our results revealed pulse frequency had a minimal impact on microbial α-diversity, but caused a significant shift in the composition of the fungal (rhizosphere and bulk soil) and bacterial (bulk soil) communities. This effect was the most pronounced in the Ascomycete and Bacteroidete communities. Increasing pulse frequency also promoted a higher proportion of fungal pathotrophs in the bulk soil, particularly those putatively identified as plant pathogens. The network analysis revealed that rotations with higher pulse frequency promoted increased competition within the soil microbial networks in the rhizosphere and bulk soil. However, we also detected more negative interactions among the dominant pathotrophic taxa with increased pulse frequency, suggesting higher soil-borne disease potential. These findings highlight the potential drawbacks and reduced sustainability of increasing pulse frequency in crop rotations in semiarid environments.
Editorial: Understanding the Heterogeneity in Exercise-Induced Changes in Glucose Metabolism to Help Optimize Treatment Outcomes

Regular exercise improves several aspects of glucose metabolism. The evidence to date has culminated in clear public health physical activity guidelines (1). However, for patients with diabetes, physical activity guidelines are no different from those issued for the general population. While many randomized controlled trials (RCTs) have demonstrated the benefits of exercise for the prevention and the treatment of diabetes, some trials have not and several studies now highlight the large variability that exists in the inter-individual changes in blood glucose control following exercise (2–5). A 2018 narrative review (6) speculated that this variability is explained by exercise dose, meal-exercise timing, drug-exercise interactions, and more. But these speculations were largely based on observational and correlative evidence because prospective trials were lacking. Identifying and understanding the causes of this response heterogeneity is critical for maximizing therapeutic outcomes for patients with, or at risk of, diabetes. Optimizing the therapeutic effect of exercise may also reduce diabetes incidence, complications, and health care burdens. Therefore, this Research Topic aimed to publish papers that: (i) advance our understanding of the inter-individual heterogeneity of exercise-induced changes in blood glucose control, (ii) identify factors influencing such heterogeneity, and (iii) test the causality of such factors.
Stochasticity Versus Determinacy in Neurobiology: From Ion Channels to the Question of the “Free Will”

If one accepts that decisions are made by the brain and that neuronal mechanisms obey deterministic physical laws, it is hard to deny what some brain researchers postulate, such as “We do not do what we want, but we want what we do” and “We should stop talking about freedom. Our actions are determined by physical laws. ” This point of view has been substantially supported by spectacular neurophysiological experiments demonstrating action-related brain activity (readiness potentials, blood oxygen level–dependent signals) occurring up to several seconds before an individual becomes aware of his/her decision to perform the action. This report aims to counter the deterministic argument for the absence of free will by using experimental data, supplemented by computer simulations, to demonstrate that biological systems, specifically brain functions, are built on principle randomness, which is introduced already at the lowest level of neuronal information processing, the opening and closing of ion channels. Switching between open and closed states follows physiological laws but also makes use of randomness, which is apparently introduced by Brownian motion – principally unavoidable under all life-compatible conditions. Ion-channel stochasticity, manifested as noise, function is not smoothed out toward higher functional levels but can even be amplified by appropriate adjustment of the system’s non-linearities. Examples shall be given to illustrate how stochasticity can propagate from ion channels to single neuron action potentials to neuronal network dynamics to the interactions between different brain nuclei up to the control of autonomic functions. It is proposed that this intrinsic stochasticity helps to keep the brain in a flexible state to explore diverse alternatives as a prerequisite of free decision-making.