Miracle-dz/UniFAR-FTUs huggingface dataset:
Lattice instability and magnetic phase transitions in strongly correlated MnAs

Using variable temperature x-ray total scattering in magnetic field, we study the interaction between lattice and magnetic degrees of freedom in MnAs, which loses its ferromagnetic order and hexagonal (‘H’) lattice symmetry at 318 K to recover the latter and become a true paramagnet when the temperature is increased to 400 K. Our results show that the 318 K transition is accompanied by highly anisotropic displacements of Mn atoms that appear as a lattice degree of freedom bridging the ‘H’ and orthorhombic phases of MnAs. This is a rare example of a lowering of an average crystal symmetry due to an increased displacive disorder emerging on heating. Our results also show that magnetic and lattice degrees of freedom appear coupled but not necessarily equivalent control variables for triggering phase transitions in strongly correlated systems in general and in particular in MnAs.
Response of phytoplankton to coastal upwelling: The importance of temporal and spatial scales

The Western Iberian Coast (WIC) is characterized by a dynamic coastal upwelling system with interactions between oceanographic features and continental river run‐off. The present study investigates the spatio‐temporal variability in the concentrations of Chlorophyll a (Chl a) and turbidity, and their relationships with physical and other biogeochemical properties along the entire coast of Portugal, as well as the response of phytoplankton to coastal upwelling pulses. In situ data were obtained during four oceanographic campaigns conducted in spring (April–May 2019), autumn (October 2018 and 2019), and early spring (February–March 2020). Upwelling conditions were evaluated through an upwelling index and auxiliary data such as sea surface temperature and height. In the WIC, the in situ surface temperature and salinity have a clear spatial pattern, both increasing from North to South. In autumn 2018 the highest temperatures coincided with the weakening of spring–summer upwelling conditions. Overall, high Chl a was associated with lower temperatures and higher dissolved oxygen concentrations (e.g., spring 2019). During spring 2019, an increase in Chl a, especially in the northern area, was associated with previous upwelling conditions. In early spring 2020, ongoing upwelling conditions in the northern area were associated with high turbidity and nutrients close to the shoreline with no immediate biological responses. An increase in Chl a was visible in satellite imagery a few days later. These results highlight the importance of understanding the complexity of coastal processes in the WIC.
Convergence Property of Response Matrix Method for Various Finite-Difference Formulations Used in the Nonlinear Acceleration Method

Abstract Convergence properties were investigated for the response matrix method with various finite-difference formulations that can be utilized in the nonlinear acceleration method. The nonlinear acceleration method is commonly used for the diffusion calculation with the advanced nodal method or the transport calculation with the method of characteristics. Efficiency of the nonlinear acceleration method depends on convergences on two different levels, i.e., those of the finite-difference calculation and the correction factor. This paper focuses on the former topic, i.e., the convergence property of finite-difference calculations using the response matrix method. Though various finite-difference formulations can be used in the nonlinear acceleration method, systematic analysis of the convergence property for the finite-difference calculation has not been carried out so far. The spectral radius of iteration matrixes was estimated for the various finite-difference calculations assuming the response matrix method with the red-black sweep. From the calculation results, numerical stability of the various finite-difference formulations was clarified, and a favorable form of the finite-difference formulation for the nonlinear iteration was recommended. The result of this paper will be useful for implementation of the nonlinear acceleration scheme with the response matrix method.
RESULTS ON N-TUPLED COINCIDENCE AND FIXED POINTS IN PARTIALLY ORDERED G-METRIC SPACES VIA SYMMETRIC (φ, ψ)-CONTRACTIONS

Recently, n -tupled fixed point theorems have been intensively studied by some authors in the framework of partially ordered G -metric spaces. In the present paper, some n -tupled coincidence as well as n -tupled fixed point results for a pair of symmetric ( φ , ψ )-contractive mappings having mixed g -monotone property are established in the context of partially ordered complete G - metric spaces. Furthermore uniqueness of n -tupled common fixed points is presented. Our results improve the results of Karpinar et al. [8], Jain and Tas [7] and Mustafa [16]. In light of the comment given in Jain and Tas [7], our results also generalize the results of Choudhary and Maity [5], Nashine [18] and Mohiuddin et al. [15]. To substantiate the validity of our hypothesis, some examples are also presented herein.
ENHANCING PRIMARY PUPILS' GEOMETRIC THINKING THROUGH PHASE-BASED INSTRUCTION USING THE GEOMETER'S SKETCHPAD

The purpose of this study was to enhance primary pupils' geometric thinking through phase-based instruction using The Geometer's Sketchpad (GSP) based on the van Hiele theory of geometric thinking. Specifically, it sought to examine Year Four pupils' van Hiele levels of geometric thinking about equilateral triangle, square, regular pentagon and regular hexagon before and after phase-based instruction using GSP, and whether there was any significant difference in the pupils' van Hiele levels of geometric thinking about the regular polygons after the intervention. The researchers employed an exploratory case study research design and purposeful sampling to select a class of 26 mixed-ability Year Four pupils from a primary school in Selangor. A van Hiele level test based on Mayberry's (1981) test and scoring criteria was devised and administered to the pupils before and after the intervention to assess their van Hiele levels of geometric thinking about the regular polygons. The results of the pre-test showed that the pupils' initial van Hiele levels were predominantly at Level 0 (Pre-recognition) for regular pentagon and regular hexagon but at Level 1 (Recognition) for equilateral triangle and square. However, the results of the post-test revealed that the pupils' van Hiele levels after the intervention were predominantly at Level 2 (Analysis) for all the regular polygons. In addition, the results of the Wilcoxon test showed that there was a significant difference in the pupils' van Hiele levels of geometric thinking for all the regular polygons after phase- based instruction using GSP. The median van Hiele level in the post-test was higher than the median van Hiele level in the pre-test for all the regular polygons, indicating that the intervention had significantly enhanced the pupils' geometric thinking about the regular polygons.
Deregulation of the miR-19b/PPP2R5E Signaling Axis Shows High Functional Impact in Colorectal Cancer Cells

MicroRNA (miR)-19b is deregulated in colorectal cancer (CRC) and locally advanced rectal cancer (LARC), predicting worse outcome and disease progression in CRC patients, and acting as a promising prognostic marker of patient recurrence and pathological response to 5-fluorouracil (5-FU)-based neoadjuvant chemoradiotherapy in LARC. Moreover, there is a strong inverse correlation between miR-19b and PPP2R5E in LARC, and both predict the response to neoadjuvant therapy in LARC patients. However, the functional role of the miR-19b/PPP2R5E axis in CRC cells remains to be experimentally evaluated. Here, we confirm with luciferase assays that miR-19b is a direct negative regulator of PPP2R5E in CRC, which is concordant with the observed decreased PP2A activity levels after miR-19b overexpression. Furthermore, PPP2R5E downregulation plays a key role mediating miR-19b-induced oncogenic effects, increasing cell viability, colonosphere formation ability, and the migration of CRC cells. Lastly, we also confirm the role of miR-19b mediating 5-FU sensitivity of CRC cells through negative PPP2R5E regulation. Altogether, our findings demonstrate the functional relevance of the miR-19b/PPP2R5E signaling pathway in disease progression, and its potential therapeutic value determining the 5-FU response of CRC cells.
Task-Oriented Compact Representation of 3D Point Clouds via A Matrix Optimization-Driven Network

This paper explores the task-oriented compact representation of 3D point clouds, which should maintain the performance of subsequent applications applied to such compact point clouds as much as possible. Designing from the perspective of matrix optimization, we propose MOPS-Net, a novel deep learning-based method that is distinguishable from existing approaches due to its interpretability and flexibility. The matrix optimization problem is challenging due to the discrete and combinatorial nature of the sampling matrix. Therefore, we tackle the challenges by relaxing the binary constraint of the sampling matrix and formulating a constrained and differentiable optimization problem. We then design a deep neural network to mimic the matrix optimization by exploring both the local and global structures of the input data. MOPS-Net can be end-to-end trained with a task network and is permutation-invariant, making it robust to the input. We also extend MOPS-Net such that a single network after one-time training is capable of handling arbitrary downsampling ratios. Extensive experimental results show that MOPS-Net can achieve favorable performance against state-of-the-art deep learning-based methods over various tasks, including classification, reconstruction, and registration. Besides, we validate the robustness of MOPS-Net on noisy data.
High-dimensional variable selection via penalized credible regions with global-local shrinkage priors

The method of Bayesian variable selection via penalized credible regions separates model fitting and variable selection. The idea is to search for the sparsest solution within the joint posterior credible regions. Although the approach was successful, it depended on the use of conjugate normal priors. More recently, improvements in the use of global-local shrinkage priors have been made for high-dimensional Bayesian variable selection. In this paper, we incorporate global-local priors into the credible region selection framework. The Dirichlet-Laplace (DL) prior is adapted to linear regression. Posterior consistency for the normal and DL priors are shown, along with variable selection consistency. We further introduce a new method to tune hyperparameters in prior distributions for linear regression. We propose to choose the hyperparameters to minimize a discrepancy between the induced distribution on R-square and a prespecified target distribution. Prior elicitation on R-square is more natural, particularly when there are a large number of predictor variables in which elicitation on that scale is not feasible. For a normal prior, these hyperparameters are available in closed form to minimize the Kullback-Leibler divergence between the distributions.
Buoyant convection from a discrete source in a leaky porous medium

Abstract The application of turbulent plume theory in describing the dynamics of emptying filling boxes, control volumes connected to an infinite exterior through a series of openings along the upper and lower boundaries, has yielded novel strategies for the natural ventilation of buildings. Making the plume laminar and having it fall through a porous medium yields a problem of fundamental significance in its own right, insights from which may be applied, for example, in minimizing the contamination of drinking water by geologically sequestered $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}{\mathrm{CO}}_2$ or the chemicals leached from waste piles. After reviewing the theory appropriate to rectilinear and axisymmetric plumes in porous media, we demonstrate how the model equations may be adapted to the case of an emptying filling box. In this circumstance, the long-time solution consists of two ambient layers, each of which has a uniform density. The lower and upper layers comprise fluid that is respectively discharged by the plume and advected into the box through the upper opening. Our theory provides an estimate for both the height and thickness of the associated interface in terms of, for example, the source volume and buoyancy fluxes, the outlet area and permeability, and the depth-average solute dispersion coefficient, which is itself a function of the far-field horizontal flow speed. Complementary laboratory experiments are provided for the case of a line source plume and show very good agreement with model predictions. Our measurements also indicate that the permeability, $k_f$ , of the lower opening (or fissure) decreases with the density of the fluid being discharged, a fact that has been overlooked in some previous studies, wherein $k_f$ is assumed to depend only on the fissure geometry.
Cross-Graph Embedding With Trainable Proximity for Graph Alignment

Graph alignment, also known as network alignment, has many applications in data mining tasks. It aims to find the node correspondence across disjoint graphs. With recent representation learning advancements, embedding-based graph alignment has become a hot topic. Existing embedding-based methods focus either on structural proximity across graphs or on the positional proximity within a single graph. However, only considering the structural similarity will make the position relation of nodes not clear enough, which makes it easy to misalign the nodes close in distance, while only considering the position proximity of a single graph will make the node embeddings from different graphs in different subspaces. To mitigate this issue, we propose a novel model CEGA for Cross-graph Embedding-based Graph Alignment, which can generate node embeddings to reflect structural proximity and positional proximity simultaneously. Meanwhile, we make the proximity trainable thus it can be learned to best suit the alignment task at hand automatically. We show that CEGA outperforms existing graph alignment methods in accuracy under unsupervised scenarios through extensive experiments on public benchmarks.
Thermal expansivity of polymer nanocomposites and applications

ABSTRACT Nowadays, the quest for fabricating polymeric nanocomposites with enhanced thermomechanical properties has tremendously escalated as a result of their multifunctional applications in advanced engineering areas sensitive to thermal expansion. Thermal expansion and coefficient of thermal expansion (CTE) of polymers as well as polymeric nanocomposites are critical properties due to the relatively elevated CTE of polymeric matrices in comparison with other materials. Polymer matrices are embedded with low-CTE or negative-CTE fillers in order to minimize the CTE mismatch which occurs in components where polymeric matrices are used in synergy with other materials. This facilitates their usage as system adhesives, electronical flip-clip underfills, metallic component replacement, coatings, electronic packaging, and so on. Thermal Mechanical Analysis (TMA) is a technique used in measuring thermal expansivity and contractivity of polymeric nanocomposites. Therefore, this paper presents in depth insight into thermal expansivity and coefficient of thermal expansivity of polymeric nanocomposites (PNC) and applications. GRAPHICAL ABSTRACT
The relationship between morphological characters and body weight of Ctenopharyngodon idellus

To study the effects of morphological attributes on body weight of grass carp,287 2-year-old individuals were sampled for measuring seven metric traits,including the total length,standard length,head length,body width,body height,interorbital width,length before anus,The relationship between morphological attributes and body weight was quantified by correlation analysis,path analysis and multiple regression analysis to determine the major morphological attributes.The results showed that the correlation coefficients of each morphological trait to body weight were all very significant(P0.01). Head length,body height were eliminated from the variable data,because of no significance in multiple regression analysis.Total length was also kicked out from variable data because it was co-linear with standard length.The regression equation was obtained as Y=-3048.127+220. 925X_4+262. 367X_6+33. 776X_7+10. 648X_2,in which body weight(Y) was used as the dependent variables and body width(X_4),interorbital width(X_6),length before anus(X_7),standard length(X_2) were as independent variables.Judged from the results of high correlation index(R2 =0.900) it suggests that the main variables have been selected,among them the body width weighted the most(P=0.430)to the body weight,and it was key effective factor on body weight.In the selection process,four main morphological traits were considered as a whole,which provided essential theoretical basis and ideal measure for selective breeding of grass carp.
Transverse jet mixing characteristics

This experimental study explores and quantifies mixing characteristics associated with a gaseous round jet injected perpendicularly into cross-flow for a range of flow and injection conditions. The study utilizes acetone planar laser-induced fluorescence imaging to determine mixing metrics in both centreplane and cross-sectional planes of the jet, for a range of jet-to-cross-flow momentum flux ratios ( $2\leqslant J\leqslant 41$ ), density ratios ( $0.35\leqslant S\leqslant 1.0$ ) and injector configurations (flush nozzle, flush pipe and elevated nozzle), all at a fixed jet Reynolds number of 1900. For the majority of conditions explored, there is a direct correspondence between the nature of the jet’s upstream shear layer instabilities and structure, as documented in detail in Getsinger et al. (J. Fluid Mech., vol. 760, 2014, pp. 342–367), and the jet’s mixing characteristics, consistent with diffusion-dominated processes, but with a few notable exceptions. When quantified as a function of distance along the jet trajectory, mixing metrics for jets in cross-flow with an absolutely unstable upstream shear layer and relatively symmetric counter-rotating vortex pair cross-sectional structure tend to show better local molecular mixing than for jets with convectively unstable upstream shear layers and generally asymmetric cross-sectional structures. Yet the spatial evolution of mixing with downstream distance can be greater for a few specific convectively unstable conditions, apparently associated with the initiation and nature of shear layer rollup as a trigger for improved mixing. A notable exception to these trends concerns conditions where the equidensity jet in cross-flow has an upstream shear layer that is already absolutely unstable, and the jet density is then reduced in comparison with that of the cross-flow. Here, density ratios below unity tend to mix less well than for equidensity conditions, demonstrated to result from differences in the nature of higher-density cross-flow entrainment into lower-density shear layer vortices.
CirFix: Automated Hardware Repair and its Real-World Applications

This article presents CirFix, a framework for automatically repairing defects in hardware designs implemented in languages like Verilog. We propose a novel fault localization approach based on assignments to wires and registers, and a fitness function tailored to the hardware domain to bridge the gap between software-level automated program repair and hardware descriptions. We also present a benchmark suite of 32 defect scenarios corresponding to a variety of hardware projects. Overall, CirFix produces plausible repairs for 21/32 and correct repairs for 16/32 of the defect scenarios. Additionally, we evaluate CirFix's fault localization independently through a human study (n = 41), and find that the approach may be a beneficial debugging aid for complex multi-line hardware defects.
Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT): Developing a Data Analysis Pipeline for the Assessment of Developmental Toxicity with an Interlaboratory Study

The embryonic zebrafish is a useful vertebrate model for assessing the effects of substances on growth and development. However, cross-laboratory developmental toxicity outcomes can vary and reported developmental defects in zebrafish may not be directly comparable between laboratories. To address these limitations for gaining broader adoption of the zebrafish model for toxicological screening, we established the Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) program to investigate how experimental protocol differences can influence chemical-mediated effects on developmental toxicity (i.e., mortality and the incidence of altered phenotypes). As part of SEAZIT, three laboratories were provided a common and blinded dataset (42 substances) to evaluate substance-mediated effects on developmental toxicity in the embryonic zebrafish model. To facilitate cross-laboratory comparisons, all the raw experimental data were collected, stored in a relational database, and analyzed with a uniform data analysis pipeline. Due to variances in laboratory-specific terminology for altered phenotypes, we utilized ontology terms available from the Ontology Lookup Service (OLS) for Zebrafish Phenotype to enable additional cross-laboratory comparisons. In this manuscript, we utilized data from the first phase of screening (dose range finding, DRF) to highlight the methodology associated with the development of the database and data analysis pipeline, as well as zebrafish phenotype ontology mapping.
The Epithelial Sodium Channel—An Underestimated Drug Target

Epithelial sodium channels (ENaC) are part of a complex network of interacting biochemical pathways and as such are involved in several disease states. Dependent on site and type of mutation, gain- or loss-of-function generated symptoms occur which span from asymptomatic to life-threatening disorders such as Liddle syndrome, cystic fibrosis or generalized pseudohypoaldosteronism type 1. Variants of ENaC which are implicated in disease assist further understanding of their molecular mechanisms in order to create models for specific pharmacological targeting. Identification and characterization of ENaC modifiers not only furthers our basic understanding of how these regulatory processes interact, but also enables discovery of new therapeutic targets for the disease conditions caused by ENaC dysfunction. Numerous test compounds have revealed encouraging results in vitro and in animal models but less in clinical settings. The EMA- and FDA-designated orphan drug solnatide is currently being tested in phase 2 clinical trials in the setting of acute respiratory distress syndrome, and the NOX1/ NOX4 inhibitor setanaxib is undergoing clinical phase 2 and 3 trials for therapy of primary biliary cholangitis, liver stiffness, and carcinoma. The established ENaC blocker amiloride is mainly used as an add-on drug in the therapy of resistant hypertension and is being studied in ongoing clinical phase 3 and 4 trials for special applications. This review focuses on discussing some recent developments in the search for novel therapeutic agents.