Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Orthogonal Matching Pursuit and Sparse Solution

The Algorithm for finding sparse solution of under-determined linear system is a hot topic in sparse representation and compressive sensing.It covers methods of minimizing L0 quasi-norm,L1 norm and iterative thresholding.A class of algorithm for minimizing L0 quasi-norm,namely iterative orthogonal matching pursuit(OMP) is introduced and its framework for iteratively updating base coordinates are analyzed and proved.Three iterative method are presented,including hermitian inverse update,cholesky and QR decomposition update.Iterative method avoid direct computing of matrix inverse at each step therefore improve the speed.Property of fast recovering sparse solution by OMP are introduced.Experiments on compressive sensing demonstrated that iterative OMP is stable and fast on finding sparse solution of under-determined linear system.
The Impact of Preoperative Hemoglobin Concentration and Erythropoietin Administration on Renal Tumors Patients with Inferior Vena Cava Tumor Thrombus Underwent Robot-Assisted Laparoscopic Inferior Vena Cava Thrombectomy

Introduction: The impact of preoperative hemoglobin (Hb) concentration and recombinant human erythropoietin (rh-EPO) treatment on renal tumors (RTs) patients with inferior vena cava (IVC) tumor thrombus who underwent robot-assisted laparoscopic inferior vena cava thrombectomy (RAL-IVCTE) were not well studied.
Progress of 3D Bioprinting for Neural Tissue

Abstract: 3D bioprinting technology has made great progress in cell engineering and can be used to construct complex geometries with the help of computer set-up programs. This paper introduces the background and concepts of 3D bioprinting technology, describes in detail the main techniques of 3D bioprinting, the biomaterials used for 3D bioprinting technology and the advances in 3D bioprinting technology in terms of neural cells and its applications, providing information for better cell formation and modelling.
3D radiation hydrodynamics: Interacting photo-evaporating clumps

We present the results of a new radiation hydrodynamics code called Maartje. This code describes the evolution of a flow in three spatial dimensions using an adaptive mesh, and contains a combination of a ray tracer and an atomic physics module to describe the effects of ionizing radiation. The code is parallelized using a custom threadpool library. We present an application in which we follow the ionization of two dense spherical clumps which are exposed to an ionizing radiation field from a 50 000 K black body. We study various configurations in which one of the clumps shields the other from the ionizing photons. We find that relatively long-lived filamentary structures with narrow tails are formed. This raises the possibility that cometary knots (such as are found in the Helix Nebula) may be the result of the interaction of an ionizing radiation field with an ensemble of clumps, as opposed to the identification of a single knot with a single clump.
Vibration Detection for Mobile Phone Based on Digital Image Correlation Method

: To solve the problem of vibration test of mobile phone, a non-contact testing method is proposed based on binocular stereo vision. The method determines the internal parameters of the lens and the external parameters of two industrial cameras by camera calibration. After obtaining the corresponding region between the two cameras by digital image correlation matching, the point coordinates of three-dimensional space are reconstructed based on laser triangulation method, and the vibration of a point with the same name is calculated by tracking its three-dimensional position in adjacent frames. The method has the advantages of non-contact and full-field measurement. The experimental results show that the proposed method has high accuracy. Compared with the measurement results of the vibrometer, the maximum deviation of the proposed method is 0.04 mm and the average deviation is 0.021mm. The proposed method can measure the vibration direction and amplitude of the designated area on the mobile phone, which provides a test method for the verification and optimization of mobile phone vibration technology.
AN EFFICIENT DIMENSIONAL REDUCTION METHOD FOR DATA CLUSTERING

The current data tends to be more complex than conventional data and need dimension reduction. Dimension reduction is important in cluster analysis and creates a smaller data in volume and has the same analytical results as the original representation. A clustering process needs data reduction to obtain an efficient processing time while clustering and mitigate curse of dimensionality. This paper proposes a model for extracting multidimensional data clustering of health database. We implemented four dimension reduction techniques such as Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Self Organizing Map (SOM) and FastICA. The results show that dimension reductions significantly reduce dimension and shorten processing time and also increased performance of cluster in several health datasets.
Textual space and its importance to school ethos and cultural pedagogy

ABSTRACT This paper theoretically demonstrates the potential of textual space in making an important contribution to school ethos and cultural pedagogy. It demonstrates how culturally-inclusive (representational) textual space can be expanded throughout the school and could contribute to social justice and decolonisation efforts beyond the English Literature classroom. This is increasingly important in an age of culturally and politically securitised schooling, where government control exercised at the macro-level (colonial/neoliberal education policy) and micro-level (teaching and learning; the enactment of the formal curriculum) reproduces cultural inequality. This paper therefore argues for textual space in the English Literature classroom to be appropriated as a representational, dialogical, historical and connected space (in opposition to neoliberalism’s decontextualising and atomising agenda) for real-world political action and the democratisation of cultural production within the wider school environment.
Coexistence Analysis of Civil Unmanned Aircraft Systems at Low Altitudes

Abstract The requirement of unmanned aircraft systems in civil areas is growing. However, provisioning of flight efficiency and safety of unmanned aircraft has critical requirements on wireless communication spectrum resources. Current researches mainly focus on spectrum availability. In this paper, the unmanned aircraft system communication models, including the coverage model and data rate model, and two coexistence analysis procedures, i. e. the interference and noise ratio criterion and frequency-distance-direction criterion, are proposed to analyze spectrum requirements and interference results of the civil unmanned aircraft systems at low altitudes. In addition, explicit explanations are provided. The proposed coexistence analysis criteria are applied to assess unmanned aircraft systems’ uplink and downlink interference performances and to support corresponding spectrum planning. Numerical results demonstrate that the proposed assessments and analysis procedures satisfy requirements of flexible spectrum accessing and safe coexistence among multiple unmanned aircraft systems.
Substructure and Maximal Common Substructure Searching

There are three important and closely related methods for the manipulation and searching of chemical structures: structure isomorphism identification, substructure searching (SSS), and maximal common substructure (MCSS) perception [1]. To understand the internal relationships of these three concepts, it is useful to define several terms before further proceeding with the discussion of SSS and MCSS problems. Because the structure of a chemical molecule can be treated as a mathematical graph with atoms corresponding to vertices and bonds to edges, it is convenient to introduce the following definitions [2] according to graph theory. Definition 1: A graph G= (V, E ) is a finite set of vertices (V ) and a finite set of edges (E ). Each edge (vi, vj) consists of an unordered pair of distinct vertices. Two vertices vi and vj of a graph are said to be adjacent if (vi, vj) is an edge of the graph [3]. If vertices and edges of a graph possess colors, we say it is a colored graph. The colors of vertices and edges of a colored graph separately correspond to the properties of atoms and bonds of a chemical structure. Definition 2: Two graphs G1 = (V1, E1) and G2 = (V2, E2) are said to be isomorphic if their vertices can be identified in a one-to-one fashion so that, if v1i and v1j are vertices inG1, and v2i and v2j are the corresponding vertices inG2, then (v1i, v1j) is an edge ofG1 if and only if (v2i, v2j) is an edge ofG2 [3]. For two colored graphs, the vertex pairs ‘‘v1i, v2i’’ and ‘‘v1j, v2j,’’ and edge pairs (v1i, v1j) and (v2i, v2j) must have the same kind of colors, respectively. Definition 3: Given two graphs G1 = (V1, E1) and G2 = (V2, E2), we say G1 is a subgraph of G2 if V1 is a subset of V2 and E1 is a subset of E2 [3].
Compact Dual-Layer Bandpass Filter Using Novel Stepped-Impedance Resonators

ABSTRACT In this article, a compact third-order bandpass filter with high-frequency selectivity using novel dual-band stepped-impedance resonators is presented. In the proposed novel dual-band stepped-impedance resonator, the conventional low-impedance stub of the stepped-impedance resonator is replaced by a closed rectangular loop. The high-impedance stub is embedded in the closed loop for more compact structure. Multiple transmission zeros are introduced near the passband to improve the frequency selectivity and stopband performance. The proposed filter was designed, simulated, and fabricated to verify the validity of the proposed method. The measured results show that the center frequency is 2.83 GHz with a fractional bandwidth of 9.32%, and five transmission zeros were introduced near the passband, which are located at 1.76 GHz with 70.2-dB rejection, 2.53 GHz with 30.7-dB rejection, 3.95 GHz with 67.2-dB rejection, 8.85 GHz with 45.5-dB rejection, and 12.3 GHz with 34.5-dB rejection, respectively. The circuit only occupies 0. 11λg × 0. 08λg.
Biomass estimation of World rice (Oryza sativa L.) core collection based on the convolutional neural network and digital images of canopy

ABSTRACT Above-ground biomass (AGB) is an important indicator of crop productivity. Destructive measurements of AGB incur huge costs, and most non-destructive estimations cannot be applied to diverse cultivars having different canopy architectures. This insufficient access to AGB data has potentially limited improvements in crop productivity. Recently, a deep learning technique called convolutional neural network (CNN) has been applied to estimate crop AGB due to its high capacity for digital image recognition. However, the versatility of the CNN-based AGB estimation for diverse cultivars is still unclear. We established and evaluated a CNN-based estimation method for rice AGB using digital images with 59 diverse cultivars which were mostly in World Rice Core Collection. Across two years at two locations, we took 12,183 images of 59 cultivars with commercial digital cameras and manually obtained their corresponding AGB. The CNN model was established by using 28 cultivars and showed high accuracy (R2 = 0.95) to the test dataset. We further evaluated the performance of the CNN model by using 31 cultivars, which were not in the model establishment. The CNN model successfully estimated AGB when the observed AGB was lesser than 924 g m−2 (R2 = 0.87), whereas it underestimated AGB when the observed AGB was greater than 924 g m−2 (R2 = 0.02). This underestimation might be improved by adding training data with a greater AGB in further study. The present study indicates that this CNN-based estimation method is highly versatile and could be a practical tool for monitoring crop AGB in diverse cultivars.
Multi-Hop Assisted Offloading Strategy Based on Mobile Awareness in the Internet of Vehicles

: The rapid development of Internet information technology and automobile economy has spawned a large number of computation-intensive and time-delay sensitive vehicle applications. In the face of high amount of computing data and real-time response requirements of applications, how to improve the utilization of network resources and reduce the computing delay of vehicle applications has become an urgent problem to be solved. Most of the existing research focuses on the problem of vehicle task offloading within the coverage of edge servers, and the idle vehicle resources outside the one-hop range are not fully utilized. In this paper, we formulate a multi-hop offloading scheme for tasks with mobility awareness. Based on the high-speed movement characteristics of vehicles, the real-time location of vehicles and the multi-hop-assisted offloading of tasks are modeled as a Markov decision process, and a multi-hop-assisted task offloading and resource allocation algorithm is proposed to ensure the reliability of each hop link and minimize the computation delay of tasks. Simulation results show that the proposed multi-hop assisted offloading scheme can significantly improve the response delay of the task. When the vehicle speed is high, the proposed scheme can reduce the response delay of the task by at least 17.2% compared with other algorithms (such as local and single-hop offloading algorithm and random multi-hop offloading algorithm).
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that thedeveloped ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation alsoshows better prediction over a wide range of operation parameters in RDC columns.
Relative Decrease of Tracer Gas Concentration as a Measure of the Ventilation Effectiveness

An analysis of the ventilation effectiveness measured on a prototype system for local air-conditioning named PERMICS (Personal Microclimate System) was made based on simultaneous measurements of velocity field and of tracer gas concentration using the decay method. A new parameter based on a relative decrease of tracer gas concentration in the first minute of system operation dC(1) was introduced. The newly defined parameter has been verified by simulation results from commercial computational fluid dynamics (CFD) software. The usefulness of the parameter is the possibility to make quick measurements of the local efficiency of personalized ventilation systems.
Robust shape reconstruction from defect-laden data

Over the last two decades, a high number of reliable algorithms for surface reconstruction from point clouds has been developed. However, they often require additional attributes such as normals or visibility, and robustness to defect-laden data is often achieved through strong assumptions and remains a scientific challenge. In this thesis we focus on defect-laden, unoriented point clouds and contribute two new reconstruction methods designed for two specific classes of output surfaces. The first method is noise-adaptive and specialized to smooth, closed shapes. It takes as input a point cloud with variable noise and outliers, and comprises three main steps. First, we compute a novel noise-adaptive distance function to the inferred shape, which relies on the assumption that this shape is a smooth submanifold of known dimension. Second, we estimate the sign and confidence of the function at a set of seed points, through minimizing a quadratic energy expressed on the edges of a uniform random graph. Third, we compute a signed implicit function through a random walker approach with soft constraints chosen as the most confident seed points. The second method generates piecewise-planar surfaces, possibly non-manifold, represented by low complexity triangle surface meshes. Through multiscale region growing of Hausdorff-error-bounded convex planar primitives, we infer both shape and connectivity of the input and generate a simplicial complex that efficiently captures large flat regions as well as small features and boundaries. Imposing convexity of primitives is shown to be crucial to both the robustness and efficacy of our approach.
UV laser ablative figuring of precise optics

The new method of surface shaping for optical plastics have been investigated using UV laser ablation on acrylic resin (PMMA) or ultraviolet (UV)-cured-resin. The surface figuring of optical flat was obtained with direct beam irradiated ablation with ArF laser. The depth of the figuring was determined with the measurement of wave front distortion on the optics using interferogram. The ablated surface had small surface roughness. The miniature size optics such as the collimate lens for a diode laser (LD) was fabricated on flat PMMA at using the focusing beam irradiation. The wave front of LD light through the LD lens was measured with Shach-Hartmann sensor. The wave front control for LD light was carried out with the measured wave front data by the laser ablation on the LD lens surface. The collimated LD light has been obtained.
Financial Globalization and Growth: The Impacts of Financial Development and Governance

The conventional theory suggests that financial globalization encourages growth. The empirical literature, however, does not give convincing support for the theoretical benefits of financial globalization. This paper investigates the relationship between financial globalization and growth in a sample of 33 emerging market economies during the 1995-2019 period by considering both de facto and de jure measures of financial globalization. We first study the direct effect of financial globalization on growth. Then, we focus on whether the growth impact of financial globalization is conditional on the level of financial development and governance. Our two-step system GMM estimation results suggest that both financial globalization measures tend to lower growth, albeit this negative relationship mitigates after the global financial crisis. Our empirical findings also indicate that the negative growth impact of financial globalization diminishes with the high levels of financial development and governance. The results indicate that investing and upgrading the collateral environment cause higher growth and mitigate the negative growth impact of financial globalization.
Line Radiation Events Observed by the DEMETER Spac ecraft

When r epresented in a traditional form of frequency-time spectro- grams, electromagnetic waves observed by low-altitude satellites and ground-based instruments sometimes consist of several clearly defined, nearly parallel and almost equidistant lines. These may drift in frequency and are usually called Line Radia- tion (LR). Although these emissions have been already known for a long time, in most cases their origin is still rather poorly understood. We present a systematic survey of this kind of events as observed by the DEMETER spacecraft (altitude 700 km). We demonstrate that there exist three different types of LR: 1) Power Line Harmonic Radiation (PLHR) generated by electromagnetic radiation from electric power systems on the ground. 2) Magnetospheric Line Radiation (MLR) whose origin is still quite unclear. 3) Electromagnetic harmonic emissions generated probably by instabilities of proton distribution functions. An example of each type of LR is presented and its properties and generation mechanism/region are discussed.
Environmental education at regular schools and in youth and adult education

This study aimed to comparatively investigate the concepts of environmental education (EE) related to elementary school students enrolled in regular schools and in youth and adult education (YAE) in Brazil. A qualitative study was conducted using unstructured interviews. These interviews were carried out with twenty two students of YAE and the regular elementary school with themes formed about relation between human being and nature, conceptions about labor and conceptions of EE. We used the technique of content analysis and Toulmin’s argument pattern to analyze the data. The theoretical basis our study was the relation between the human being and labor. We considered the perspective of the ontological labor’s in the transformation of nature by the human being, and the subsequent transformation of the human being by nature, forming a cyclic process. Our results show that the students’ conceptions are related to a separation of the human being and nature, as well as their ideas about conservation and preservation of nature, recognizing their impacts on the environment. We did not verify any knowledge involving a more complex and critical comprehension about the relation between human beings and nature.This research suggests that the development and application of EE projects, should consider how subjects comprehend the relation between society and nature, leading to interesting outcomes.
Numerical Simulations of a Landfalling Cold Front Observed during COAST: Rapid Evolution and Responsible Mechanisms*

Abstract This paper identifies mechanisms that led to the observed rapid evolution of a landfalling weak cold front along the steep mountainous northern California coast on 1 December 1995. This event was simulated down to 3-km horizontal grid spacing using the Pennsylvania State University–NCAR Mesoscale Model version 5 (MM5). The MM5 simulation reproduced the basic features such as the timing, location, and orientation of the cold front and associated precipitation evolution, as well as the tendency for enhanced precipitation to extend ∼50–100 km upwind of the coastal barrier, with the heaviest amounts occurring over the windward slopes (0–20 km inland); locally, however, the model underestimated the magnitude of the prefrontal terrain-enhanced flow by as much as 30% since the simulated low-level static stability was weaker than observed. The MM5 simulations illustrate the complex thermal, wind, and precipitation structures in the coastal zone. Upstream flow blocking by the steep coastal terrain led to .
How Much Can You Earn in the Stock Market ? Answers from the Algorithmic Graph Theory

This paper proposes a new method for determining the upper bound of any investment strategy's maximum profit, applied in a given time window [0, T]. This upper bound is defined once all the prices are known at time T and therefore represents the ex-post maximum efficiency of any investment strategy determined during the relevant time interval. This approach allows us to gauge in absolute terms those behaviors defined through atomic "buy" and "sell" actions, and can be extended to more complex strategies. We show that, even in the ex-post framework, establishing this upper bound when transaction costs are implemented is extremely complex. We first describe this problem using a linear programming framework. Thereafter, we propose to embed this question in a graph theory framework and to show that determining the best investment behavior is equivalent to identifying an optimal path in an oriented, weighted, bipartite network or a weighted, directed, acyclic graph. We illustrate this method using real world data and introduce a new theory about absolute optimal behavior in the financial world.