Miracle-dz/UniFAR-FTUs huggingface dataset:
LARGE-EDDY SIMULATION OF THE THREE-DIMENSIONAL UNSTABLE FLOW IN A LID-DRIVEN CAVITY

Transitional and turbulent flows in a three-dimensional lid-driven cavity has been performed employing a large-eddy simulation methodology with dynamical and Smagorinsky subgrid-scale modes. The finite volume method in cartesian coordinates is applied on staggered grids, considering second order temporal and spatial schemes. The tree-dimensional structures as spanwise inward and outward currents, the end-wall corner vortices and the Taylor- Gortler-like vortices were observed. As Reynolds number is increased the instabilities appear in the lower part of the cavity and, for the high Reynolds number the unstable flow becomes fully turbulent. The Taylor-Gortler-like vortices were distorted due to onset of turbulence regime. The qualitative and quantitative results showed a good agreement with experimental and numerical dates of other authors, also, the comparative analyze between the sub-grid scale models is presented.
Frequency and Intensity of Landfalling Tropical Cyclones in East Asia: Past Variations and Future Projections

This paper presents the latest analyses and integrates results of many past studies on the spatial and temporal variations of the annual frequency and intensity of tropical cyclones (TCs) making landfall along different areas of the East Asian (EA) coast. Future projections of such variations based on the past investigations are also presented. No statistically significant trend in the number of landfalling TCs could be identified in most of the EA coastal regions, except for an increasing one in Vietnam and a decreasing one in South China. Multi-decadal as well as interannual variations in the frequency of landfalling TCs are prevalent in almost all the EA coastal regions. Only TCs making landfall in Vietnam and the Korean Peninsula showed an increase in landfall intensity, with no trend in the other regions. Nevertheless, more intense landfalling TCs were evident in most regions during the past two decades. Multidecadal variations were not observed in some regions although interannual variations remained large. Various oscillations in the atmospheric circulation and the ocean conditions can largely explain the observed changes in the frequency and intensity of landfalling TCs in different regions of the EA coast. In the future, most climate models project a decrease in the number of TCs making landfall but an increase in the intensity of these TCs in all the EA coastal regions, especially for the most intense ones.
Up-Regulation of microRNA-424 Causes an Imbalance in AKT Phosphorylation and Impairs Enteric Neural Crest Cell Migration in Hirschsprung Disease

Insights into the role of microRNAs (miRNAs) in disease pathogenesis have made them attractive therapeutic targets, and numerous miRNAs have been functionally linked to Hirschsprung disease (HSCR), a life-threatening genetic disorder due to defective migration, proliferation, and colonization of enteric neural crest cells (ENCCs) in the gut. Recent studies have demonstrated that miR-424 strongly inhibits migration in a variety of cell types and its potential target RICTOR is essential for neural crest cell development. We therefore sought to interrogate how miR-424 and RICTOR contribute to the pathogenesis of HSCR. We utilized HSCR cases and human neural cells to evaluate the miR-424-mediated regulation of RICTOR and the downstream AKT phosphorylation. We further developed an ex vivo model to assess the effects of miR-424 on ENCC migration and proliferation. Then, single-cell atlases of gene expression in both human and mouse fetal intestines were used to determine the characteristics of RICTOR and AKT expression in the developing gut. Our findings demonstrate that miR-424 levels are markedly increased in the colonic tissues of patients with HSCR and that it regulates human neural cell migration by directly targeting RICTOR. Up-regulation of miR-424 leads to decreased AKT phosphorylation levels in a RICTOR-dependent manner, and this, in turn, impairs ENCC proliferation and migration in the developing gut. Interestingly, we further identified prominent RICTOR and AKT expressions in the enteric neurons and other types of enteric neural cells in human and mouse fetal intestines. Our present study reveals the role of the miR-424/RICTOR axis in HSCR pathogenesis and indicates that miR-424 is a promising candidate for the development of targeted therapies against HSCR.
Aerosol Impacts on Storm Electrification and Lightning Discharges Under Different Thermodynamic Environments

The impacts of aerosol and thermodynamics on electrification and lightning activities have been investigated in detail using the Weather Research and Forecasting Model coupled with a double‐moment microphysics parameterization and an explicit electrification lightning scheme. To obtain a varied combination of convective available potential energy (CAPE) values and aerosol concentrations, a sounding was modified consistently and initiated with five sets of aerosol concentrations that served as cloud condensation nuclei. The simulated electric processes respond to the varying dynamical and microphysical characteristics associated with the different CAPE and aerosol conditions. Under high CAPE circumstances, the augmentation of ice‐phase particle leads to the enhancement of non‐inductive charging primarily through the dynamic processes. Increased aerosol content further invigorates the electrification through microphysical processes. Elevated aerosol loading under low CAPE conditions increases cloud droplet and ice crystal numbers. Larger graupel particle size further leads to the enhanced electric intensity and lightning discharges.
Integrodifferential equations for systems of leaky aquifers and applications: 2. Error analysis of approximate theories

This paper is the second of a series devoted to developing a method of analysis based on the integrodifferential equations of leaky aquifer systems. In part 1 [Herrera and Rodarte, 1973a] the integrodifferential equations were derived, and an interpretation for some of the approximate theories was given in terms of the memory functions occurring in the equations. The same equations are quite suitable for a systematic analysis of the errors involved, and therefore in this paper they are used to carry it out.
A Critique of a Formalist-Mechanist Version of the Justification of Arguments in Mathematicians' Proof Practices

In a recent article, Azzouni has argued in favor of a version of formalism according to which ordinary mathematical proofs indicate mechanically checkable derivations. This is taken to account for the quasi-universal agreement among mathematicians on the validity of their proofs. Here, the author subjects these claims to a critical examination, recalls the technical details about formalization and mechanical checking of proofs, and illustrates the main argument with aanalysis of examples. In the author's view, much of mathematical reasoning presents genuine meaning-dependent mathematical characteristics that cannot be captured by formal calculi. ‘…there is a conflict between mathematical practice and the formalist doctrine. ’ [Kreisel, 1969, p. 39]
Understanding Dataset Design Choices for Multi-hop Reasoning

Learning multi-hop reasoning has been a key challenge for reading comprehension models, leading to the design of datasets that explicitly focus on it. Ideally, a model should not be able to perform well on a multi-hop question answering task without doing multi-hop reasoning. In this paper, we investigate two recently proposed datasets, WikiHop and HotpotQA. First, we explore sentence-factored models for these tasks; by design, these models cannot do multi-hop reasoning, but they are still able to solve a large number of examples in both datasets. Furthermore, we find spurious correlations in the unmasked version of WikiHop, which make it easy to achieve high performance considering only the questions and answers. Finally, we investigate one key difference between these datasets, namely span-based vs. multiple-choice formulations of the QA task. Multiple-choice versions of both datasets can be easily gamed, and two models we examine only marginally exceed a baseline in this setting. Overall, while these datasets are useful testbeds, high-performing models may not be learning as much multi-hop reasoning as previously thought.
The Efficacy of Tumor Mutation Burden as a Biomarker of Response to Immune Checkpoint Inhibitors

Cancer is one of the leading causes of death in the world; therefore, extensive research has been dedicated to exploring potential therapeutics, including immune checkpoint inhibitors (ICIs). Initially, programmed-death ligand-1 was the biomarker utilized to predict the efficacy of ICIs. However, its heterogeneous expression in the tumor microenvironment, which is critical to cancer progression, promoted the exploration of the tumor mutation burden (TMB). Research in various cancers, such as melanoma and lung cancer, has shown an association between high TMB and response to ICIs, increasing its predictive value. However, the TMB has failed to predict ICI response in numerous other cancers. Therefore, future research is needed to analyze the variations between cancer types and establish TMB cutoffs in order to create a more standardized methodology for using the TMB clinically. In this review, we aim to explore current research on the efficacy of the TMB as a biomarker, discuss current approaches to overcoming immunoresistance to ICIs, and highlight new trends in the field such as liquid biopsies, next generation sequencing, chimeric antigen receptor T-cell therapy, and personalized tumor vaccines.
Robust - Filtering for Uncertain Systems with Multiple Time-Varying State Delays

This paper is concerned with the robust - filtering problem for uncertain systems with multiple time-varying state delays. The uncertain parameters are supposed to reside in a polytope and the attention is focused on the design of robust full-order and reduced-order filters guaranteeing a prescribed energy-to-peak noise-attenuation level for all admissible uncertainties and time delays. The admissible filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities, which can be solved via efficient interior-point algorithms. Both delay-independent and dependent approaches are pre- sented, with an example illustrating the validity of the proposed designs. Index Terms—Energy-to-peak ( - ) performance, linear-matrix inequality (LMI), robust filtering.
Up-Regulation of PSMA Expression In Vitro as Potential Application in Prostate Cancer Therapy

Possibilities to improve the therapeutic efficacy of Lu-177–PSMA-617 radionuclide therapy by modulation of target expression are being investigated. Knowledge on regulatory factors that promote prostate cancer (PCa) progression may contribute to targeting prostate cancer more effectively. We aimed at the stimulation of PCa cell lines using the substances 5-aza-2′-deoxycitidine (5-aza-dC) and valproic acid (VPA) to achieve increased prostate-specific membrane antigen (PSMA) expression. PC3, PC3-PSMA, and LNCaP cells were incubated with varying concentrations of 5-aza-dC and VPA to investigate the cell-bound activity of Lu-177–PSMA-617. Stimulation effects on both the genetically modified cell line PC3-PSMA and the endogenously PSMA-expressing LNCaP cells were demonstrated by increased cellular uptake of the radioligand. For PC3-PSMA cells, the fraction of cell-bound radioactivity was enhanced by about 20-fold compared to that of the unstimulated cells. Our study reveals an increased radioligand uptake mediated by stimulation for both PC3-PSMA and LNCaP cell lines. In perspective of an enhanced PSMA expression, the present study might contribute to advanced radionuclide therapy approaches that improve the therapeutic efficacy, as well as combined treatment options.
Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network

In the field of tunnel lining crack identification, the semantic segmentation algorithms based on convolution neural network (CNN) are extensively used. Owing to the inherent locality of CNN, these algorithms cannot make full use of context semantic information, resulting in difficulty in capturing the global features of crack. Transformer‐based networks can capture global semantic information, but this method also has the deficiencies of strong data dependence and easy loss of local features. In this paper, a hybrid semantic segmentation algorithm for tunnel lining crack, named SCDeepLab, is proposed by fusing Swin Transformer and CNN in the encoding and decoding framework of DeepLabv3+ to address the above issues. In SCDeepLab, a joint backbone network is introduced with CNN‐based Inverse Residual Block and Swin Transformer Block. The former is used to extract the local detailed information of the crack to generate the shallow feature layer, whereas the latter is used to extract the global semantic information to obtain the deep feature layer. In addition, Efficient Channel Attention enhanced Feature Fusion Module is proposed to fuse the shallow and deep features to combine the advantages of the two types of features. Furthermore, the strategy of transfer learning is adopted to solve the data dependency of Swin Transformer. The results show that the mean intersection over union (mIoU) and mean pixel accuracy (mPA) of SCDeepLab on the data sets constructed in this paper are 77.41% and 84.42%, respectively, which have higher segmentation accuracy than previous CNN‐based and transformer‐based semantic segmentation algorithms.
Plasma-Assisted Nitrogen Doping of Langmuir–Blodgett Self-Assembled Graphene Films

Graphene films prepared from solution and deposited by Langmuir–Blodgett self-assembly technique (LBSA) were treated with radio-frequency (13.56 MHz) nitrogen plasma in order to investigate the influence of the time of nitrogen plasma exposure on the work function, sheet resistance, and surface morphology of LBSA graphene films. Kelvin probe force microscopy and sheet resistance measurements confirm nitrogen functionalization of our films, with the Fermi level shifting in a direction that indicates binding to a pyridinic and/or pyrrolic site. Upon 1 min of nitrogen plasma exposure, the sheet resistance decreases and there is no obvious difference in film morphology. However, plasma exposure longer than 5 min leads to the removal of graphene flakes and degradation of graphene films, in turn, affecting the flake connectivity and increasing film resistance. We show that by changing the exposure time, we can control the work function and decrease sheet resistance, without affecting surface morphology. Controllability of the plasma technique has an advantage for graphene functionalization over conventional doping techniques such as chemical drop-casting. It allows for the controllable tuning of the work function, surface morphology, and sheet resistance of LBSA graphene films, which is substantial for applications in various optoelectronic devices.
A Construction Method of Dynamic Protein Interaction Networks by Using Relevant Features of Gene Expression Data

Essential proteins play an important role in various life activities and are considered to be a vital part of the organism. Gene expression data are an important dataset to construct dynamic protein-protein interaction networks (DPIN). The existing methods for the construction of DPINs generally utilize all features (or the features in a cycle) of the gene expression data. However, the features observed from successive time points tend to be highly correlated, and thus there are some redundant and irrelevant features in the gene expression data, which will influence the quality of the constructed network and the predictive performance of essential proteins. To address this problem, we propose a construction method of DPINs by using selected relevant features rather than continuous and periodic features. We adopt an improved unsupervised feature selection method based on Laplacian algorithm to remove irrelevant and redundant features from gene expression data, then integrate the chosen relevant features into the static protein-protein interaction network (SPIN) to construct a more concise and effective DPIN (FS-DPIN). To evaluate the effectiveness of the FS-DPIN, we apply 15 network-based centrality methods on the FS-DPIN and compare the results with those on the SPIN and the existing DPINs. Then the predictive performance of the 15 centrality methods is validated in terms of sensitivity, specificity, positive predictive value, negative predictive value, F-measure, accuracy, Jackknife and AUPRC. The experimental results show that the FS-DPIN is superior to the existing DPINs in the identification accuracy of essential proteins.
Nonhydrostatic Atmospheric Modeling using az-Coordinate Representation

Abstract A representation of the orography based on approximate finite-volume techniques is applied to a nonhydrostatic atmospheric model. Techniques previously developed by the authors in the context of a semi-implicit, semi-Lagrangian model are applied also to a Eulerian, split-explicit model. Furthermore, an improved formulation of the original approach is introduced, which allows for better orography representation by introducing a simplified version of the most general shaved cells. A two-dimensional numerical test shows that the method developed does not suffer from the problems reported in connection with the η-coordinate.
Wide-Sense and Strict-Sense Nonblocking Operation

Multicast connections are used in broad-band switching networks as well as in parallel processing. We con- sider wide-sense and strict-sense nonblocking conditions for multi- switching networks with multicast connections in this paper. We prove that such networks are wide-sense nonblocking if they are design by vertically stacking at least planes of a networks together, where and defines the size of a blocking window . F or and even, and for the number of planes must be at least and , respectively. In the case of strict-sense nonblocking switching networks, the number of planes is at least . The results obtained in this paper show that in many cases number of planes in wide-sense nonblocking switching networks is less than those for considered in (1). Number of planes given in the paper is the minimum number of planes needed for wide-sense nonblocking operation provided that Algorithm 1 is used for setting up connections. Minimum number of planes for such operation in general is still open issue.
The Role of Good Corporate Governance in Moderating the Effect of Financial Ratio on Financial Distress (Study of Consumer Sector Companies Listed on the Indonesia Stock Exchange Over Period 2018-2020)

Financial distress is a condition where management fails to manage company finances. This study aims to determine the effect of leverage, net profit margin, liquidity, and sales growth on financial distress with corporate governance as a moderating variable. This sample used all consumer goods sector companies listed on the Indonesia Stock Exchange for the 2018-2020 period. Sampling was used with the purposive sampling technique and selected 25 companies. Data analysis used multiple linear regression and the absolute difference value test. The results are that the variables of leverage, net profit margin, and liquidity affect predicting financial distress. Meanwhile, sales growth does not affect financial distress. As measured by managerial ownership, corporate governance can moderate the effect of liquidity on financial distress. Still, it cannot moderate the effect of leverage, net profit margin, and sales growth on financial distress. Keywords:leverage, net profit margin, liqudity, sales growth, financial distress, good corporate governance
Application of Liquid Organic Pusri Fertilizer (LOPF) and Inorganic Fertilizer on Ultisols Planted With Red Chili (Capsicum annuum L.)

Red chili is a strategic horticultural commodity that is currently experiencing an increase in demand, especially in the food industry. Chili productivity itself tends to be unstable and often decreases. The things that can be done to increase the plant growth and production are fertilization. Liquid Organic Pusri Fertilizer (LOPF) is a biological fertilizer product developed by Pupuk Sriwidjaja Ltd. As the growth promoter, LOPF contains nitrogen fixing bacteria, P and K solubillizing bacteria with a biostimulant carrier made from seaweed extract. This study was designed in a randomized block design with 9 treatment levels and 3 replications. The treatment levels are P0 (100% inorganic fertilizer); P1 (LOPF application to soil); P2 (LOPF application to soil + 50% inorganic fertilizer); P3 (LOPF application to soil + 75% inorganic fertilizer); P4 (LOPF application to soil + 100% inorganic fertilizer); P5 (LOPF application to seeds and soil); P6 (LOPF application to seeds and soil + 50% inorganic fertilizer); P7 (LOPF application to seeds and soil + 75% inorganic fertilizer); and P8 (LOPF application to seeds and soil + 100% inorganic fertilizer). The recommendation dose of 100% inorganic fertilizer for NPK 16-16-16 is 300 kg ha−1 and urea fertilizer 200 kg ha−1. LOPF applied to seeds with a concentration of 100 ppm and in soil was 12 L ha−1. Application of LOPF on seeds and soil combined with 100% recommendation dose of inorganic fertilizer gave the best results in increasing the production of red chili plants with a production of 9.70 tons ha−1.
Quasi-elastodynamic Processes Involved in the Interaction between Solar Wind and Magnetosphere

The interaction between the solar wind and the magnetosphere is one of the most important research subjects in the fields of astrophysics and space physics. For more than half a century, based on the pressure balance assumption between the solar wind and the magnetosphere and considering other important factors, such as the interplanetary magnetic field and magnetic reconnection process, the dynamic processes at the magnetopause have been extensively analyzed. However, the responses of magnetopause to the solar wind dynamic pressure variations are still complicated to understand. Here, we show that the interaction between the solar wind and the magnetosphere can be regarded as a quasi-elastodynamic process. The driving frequency of the solar wind is determined as a crucial reason for the phase difference between solar wind dynamic pressure variations and magnetopause standoff distance. The low-pass filter effect and oscillation properties of the magnetopause can also be well explained by the forced damped vibrations. Moreover, the quasi-elastodynamic processes predict deformations at the magnetopause, which resemble the magnetopause surface wave. Finally, a three-dimensional time-dependent magnetopause model is constructed and verified by observation. Based on 12,242 magnetopause crossing events, it is found that the new model reveals ∼9.7% better prediction accuracy than the widely used time-independent model. These results can also shed light on our understanding of the solar-wind–magnetopause interaction for other planets.