Miracle-dz/UniFAR-FTUs huggingface dataset:
Stagewise regularized orthogonal matching pursuit algorithm

A novel reconstruction algorithm(stagewise regularized orthogonal matching pursuit)was proposed to reconstruct signals without prior sparsity information.The method constructed the candidate set by designing threshold based on the residual from signal reconstruction.The extracted signal atoms from the candidate set were merged with the previous support set.When the candidate set was a null set,the atom with the greatest correlation was directly added to the support set.Finally,the refinement of signal approximation and residual updating were achieved by solving a least-square algorithm on the support set.The experimental results for Gaussian signal and binary signal with a length of 256show that the probability of exact reconstruction can be reached above 90%on the conditions of signal sparsity of 50and 40,and the reconstructing effects and reconstructing speeds are better thanthose of similar algorithms under the same condition of signal sparsity.This algorithm is proved to be higher processing speeds and more stabile.
The Trajectory Planning of a 6-DOF Manipulator

To make the 6-DOF manipulator to finish some kind of jobs,we need to prepare the instruction sequences to input.Firstly,this paper gives the function which decides the relationship between the pose of the manipulator and the position of the Fingertip.And then in order to solve the three jobs:the problem of arriving at some point,the problem of moving along a special curve,and the problem of avoiding obstacles,we design three methods:pose speculation,discretely arriving,and constrained arriving.The main algorithm is adaptive search,which is highly efficient,highly accurate and it can be used in many situations.When calculating the instructions we use greedy Algorithm.All of this results in very short time searching and very little errors(0.8mm).
Analysis of the Error Result from Single Step of Runge-Kutta for the Euler Equation with Quaternion Method

This paper makes a further study of the large error which appears in solving the Euler equation with single step of Runge-Kutta in Quaternion method. Through the study, it is found that the equation is fine and simultaneously the step used in usual flight simulation can meet the command of step determined by the absolutely stable domain of the equation, and the main source of the error lies in cumulative errors.
Overlapping Community Detection Algorithm Based on High-Quality Subgraph Extension in Local Core Regions of Network

Community structure is an important feature of complex networks. Detecting overlapping communities in complex networks is a hot research topic in data mining and graph theory, aiming at the shortcomings of community detection algorithm based on seed expansion, such as the instability of community detection results caused by randomly selecting seeds, the similarity of selected seeds leading to similar communities after different seed expansion, and the increase of calculation caused by deleting nodes in the process of seed expansion. This paper proposes an overlapping community detection algorithm based on high-quality subgraph extension in local core regions of the network (OLCRE). First, a novel seed community selection method is designed. By analyzing the sum of node degrees of the subgraph formed by a node and its neighbor nodes in the local core region of the network and the tightness of the internal and external connections of the subgraph, a seed community selection function is proposed. According to this function, high-quality subgraphs are selected from all the local core regions of the network as seed communities. Then, taking the definition of community as the guideline, a new community expansion strategy is proposed. Considering the influence of the neighbor node on the inner and outer connection tightness of the seed community comprehensively, it is determined whether the neighbor node can join the seed community. Finally, after the completion of all seed community expansion, overlapping nodes and possible missing nodes should be simplified and redetected to further improve the quality of community detection. The proposed algorithm is tested on the artificial and real-world networks and compared with several overlapping community detection algorithms. The experimental results verify the effectiveness and feasibility of the proposed algorithm.
Propagation of the lower hybrid wave in a density fluctuating scrape-off layer (SOL)

The perturbation of the lower hybrid wave (LH) power spectrum by fluctuations of the plasma in the vicinity of the antenna is investigated by solving the full wave equation in a slab geometry using COMSOL Multiphysics®. The numerical model whose generality allows to study the effect of various types of fluctuations, including those with short characteristic wavelengths is validated against a coupling code in quiescent regimes. When electron density fluctuations along the toroidal direction are incorporated in the dielectric tensor over a thin perturbed layer in front of the grill, the power spectrum may be strongly modified from the antenna mouth to the plasma separatrix as the LH wave propagates. The diffraction effect by density fluctuations leads to the appearance of multiple satellite lobes with randomly varying positions and the averaged perturbation is found to be maximum for the Fourier components of the fluctuating spectrum in the vicinity of the launched LH wavelength. This highlights that fast toroidal inhomogeneities with short characteristics length scales in front of the grill may change significantly the initial LH power spectrum used in coupled ray-tracing and Fokker–Planck calculations.
Study of the diets of two coexisting species – invasive Chinese sleeper (Perccottus glenii Dybowski, 1877) and native European perch (Perca fluviatilis Linnaeus, 1758)

In Poland, the Chinese sleeper Perccottus glenii is one of the alien fish species which, by effectively competing with native species, may contribute to the weakening of their population and a reduction of the biodiversity. The aim of this paper is to study the diets of two coexisting species: the native European perch Perca fluviatilis and the invasive Chinese sleeper. The fish were collected from a watercourse used for draining water from a fishing farm, located in the Nida River water system (Poland), using the electrofishing method. The captured fish were killed, preserved in a 4% formaldehyde solution and the stomachs of the fish were dissected. Then, based on the materials collected from these stomachs, the abundance and taxonomic rankings of the individual diet components (quantity of individuals in the individual taxa) were determined. The overlap of the P. fluviatilis and P. glenii feeding spectra was studied using a principal component analysis (PCA). The analysis of the data collected demonstrated that the diets of these two species overlaps considerably. At the same time, the analysis of the major diet components showed that the niche used by P. fluviatilis is broader than that used by P. glenii. It seems that, due to its high level of plasticity, P. fluviatilis is able to withstand the pressures of P. glenii and is also able to limit its abundance. Both species frequently choose fish as their prey, including juvenile common carp Cyprinus carpio Linnaeus, 1758, which indicates that together with native predators, P. glenii may pose a considerable threat to farmed juvenile Cyprinidae.
Random phase fields and Gaussian fields for image sharpness assessment and fast texture synthesis

This thesis deals with the Fourier phase structure of natural images, and addresses no-reference sharpness assessment and fast texture synthesis by example. In Chapter 2, we present several models of random fields in a unified framework, like the spot noise model and the Gaussian model, with particular attention to the spectral representation of these random fields. In Chapter 3, random phase models are used to perform by-example synthesis of microtextures (textures with no salient features). We show that a microtexture can be summarized by a small image that can be used for fast and flexible synthesis based on the spot noise model. Besides, we address microtexture inpainting through the use of Gaussian conditional simulation. In Chapter 4, we present three measures of the global Fourier phase coherence. Their link with the image sharpness is established based on a theoretical and practical study. We then derive a stochastic optimization scheme for these indices, which leads to a blind deblurring algorithm. Finally, in Chapter 5, after discussing the possibility of direct phase analysis or synthesis, we propose two non random phase texture models which allow for synthesis of more structured textures and still have simple mathematical guarantees.
Local feature size based Delaunay tetrahedral mesh generation from medical volume data

This paper presented a Delaunay algorithm based on local feature size to generate tetrahedral mesh from medical volume data for virtual surgery system.Firstly,preprocessed the medical volume data to create polyhedron representation of the domain,including iso-surface extraction,mesh simplification and internal redundant mesh deletion.Secondly,constructed local feature size based protecting balls for all vertices of the polyhedron.Conforming initial tetrahedral mesh was then generated by revised Delaunay refinement method.Lastly,mesh optimization combining space-disassembling method and random perturbations was applied to place internal points quickly and efficiently.It inserted these points one by one to improve the mesh quality.Allowed arbitrarily small input angles in the presented method and the convergence could be guaranteed by theoretical proof.Experimental results show that the presented algorithm has better boundary consistency than the traditional delaunay algorithm.And the generated meshes are well suited for virtual surgery system.
Beyond the Standard Model through the Higgs portal

In this thesis, we will investigate the collider phenomenology and cosmological consequences of extensions of the Standard Model (SM) with hidden sectors coupled to the SM via a Higgs portal coupling. We will explore how models with classical scale invariance, where all mass scales are dynamically generated, can address the shortcomings of the SM without destabilising the Higgs mass. The matter-antimatter asymmetry in the Universe and the tiny masses of active neutrinos are addressed in a U(1)$_{B-L}$ extension of the SM with GeV scale right-handed neutrinos. We then investigate a range of models with both Abelian and non-Abelian gauge groups in the hidden sector to show how we can stabilise the Higgs potential and at the same time provide phenomenologically viable dark matter candidates where all scales in the theory have a common origin. For non-Abelian gauge groups in the hidden sector, we also show that hidden magnetic monopoles can make up a significant fraction of dark matter. The dark matter in this model, which consists of both magnetic monopoles and gauge bosons, has long-range self-interactions which could explain the too-big-to-fail-problem at small scales in the standard cold dark matter scenario. We then study the collider phenomenology of hidden sector models with dark matter candidates through a simplified model framework both at the LHC and at a future 100 TeV collider. Hidden sector extensions of the SM with a Higgs portal coupling give a rich and predictive model building framework for BSM physics without introducing a large hierarchy of scales.
Reliability of the National Institutes of Health (NIH) Stroke Scale Between Emergency Room and Neurology Physicians for Initial Stroke Severity Scoring

Introduction: In patients with acute ischemic stroke (AIS), the National Institutes of Health Stroke Scale (NIHSS) is essential to establishing a patient’s initial stroke severity. While previous research has validated NIHSS scoring reliability between neurologists and other clinicians, it has not specifically evaluated NIHSS scoring reliability between emergency room (ER) and neurology physicians within the same clinical scenario and timeframe in a large cohort of patients. This study specifically addresses the key question: does an ER physician’s NIHSS score agree with the neurologist’s NIHSS score in the same patient at the same time in a real-world context? Methods: Data was retrospectively collected from 1,946 patients being evaluated for AIS at Houston Methodist Hospital from 05/2016 - 04/2018. Triage NIHSS scores assessed by both the ER and neurology providers within one hour of each other under the same clinical context were evaluated for comparison. Ultimately, 129 patients were included in the analysis. All providers in this study were NIHSS rater-certified. Results: The distribution of the NIHSS score differences (ER score - neurology score) had a mean of -0.46 and a standard deviation of 2.11. The score difference between provider teams ranged ±5 points. The intraclass correlation coefficient (ICC) for the NIHSS scores between the ER and neurology teams was 0.95 (95% CI, 0.93 - 0.97) with an F-test of 42.41 and a p-value of 4.43E-69. Overall reliability was excellent between the ER and neurology teams. Conclusion: We evaluated triage NIHSS scores performed by ER and neurology providers under matching time and treatment conditions and found excellent interrater reliability. The excellent score agreement has important implications for treatment decision-making during patient handoff and further in stroke modeling, prediction, and clinical trial registries where missing NIHSS scores may be equivalently substituted from either provider team.
Sensing probation in Canada: Notes on affect and penal aesthetics in risk assessment

Based on 6 years of probation practitioner experience in a metropolis of Canada, I provide an autoethnographic account reflecting on my fieldwork as I now commence doctoral studies. Contributing to discussions of experience in the penal atmosphere, I explore personal ethics and values, looking specifically to LSI-R software, where my experience with risk-based programming indicates a subjugation of both supervisees and supervisors. Studying penal aesthetics within the version of the software I used to assess criminogenic risk thus elucidates why evaluators tend to score their risk ratings upward rather than downward. Implications for a desistance paradigm are juxtaposed to the RNR model of offender management, where sensing visual and haptic stimuli pertains to an algorithmic governance mode limiting human connection. I conclude by reflecting on organisational values and behaviour to indicate where therapeutic alliances with criminalised people intersect criminalisation and desistance.
Application of new general fractional‐order derivative with Rabotnov fractional–exponential kernel to viscous fluid in a porous medium with magnetic field

The main objective is to apply the concept of newly developed idea of the fractional‐order derivative of the Rabotnov fractional–exponential function in fluid dynamics. In this article, a newly developed idea of the fractional‐order derivative of the Rabotnov fractional–exponential function and the nonsingular kernel has been applied to study viscous fluid flow in the presence of an applied magnetic field. The flow is considered over an infinite vertical plate moving with arbitrary velocity. The modeled problem is transformed into a nondimensional form via dimensionless analysis, and then the Laplace transform method is applied for the solution of the problem. Due to the complexity in Laplace inversion, a strong numerical inversion procedure, namely, Zakian's algorithm, has been used, and the results are computed in various plots and tables. The corresponding discussion of results is included in detail. It is concluded that the generalized fractional‐order derivative is accurate and efficient for describing general fractional‐order dynamics in complex and power law phenomena.
Features Image Matching Approach Based on SIFT and RANSAC

In order to improve the ability of anti-interference in the matching of image feature,a new matching method is proposed based on SIFT and RANSAC.Firstly,using SIFT to extract invariant features from images,best bin first research to be performed and computer the Euclidean distance ratio of nearest neighbor feature vector and second nearest neighbor feature vector to achieve the pre-matching.After that,RANSAC robust estimation is performed to eliminate the wrong feature matching.Finally,transformation parameters between matching and template image is computed by reliable matching points.The experimental results indicate that the matching algorithm is invariant to scale and rotation,and a substantial range of affine distortion,addition of noise,and can effectively complete the object matching between images.
Direct observation of condensate and vortex confinement in nanostructured superconductors

In this work we report a scanning tunneling microscopy investigation of lithographically defined superconducting nanosquares. The obtained spectroscopic maps reveal the spatial evolution of both the superconducting condensate and the screening currents as a function of the applied magnetic field. The symmetry of the nanostructure is imposed on the condensate and it controls the distribution of the vortices inside the nanosquare. Our local study allows exploring the impact of small structural defects, omnipresent in these kind of structures, on both the supercurrent and vortex distribution. As a result, direct experimental evidence of vortex pinning and current crowding at the nanoscale has been obtained.
Multivariate Hawkes processes

This thesis addresses theoretical and practical questions arising in connection with multivariate, marked, linear Hawkes processes. On the theoretical side, the following two main topics are discussed: the calculation of moment measures; and the existence and uniqueness of stationary solutions. Two different representations of Hawkes processes are used to answer these problems. First, a Hawkes process is constructed as a recursive Poisson cluster process. This reveals the underlying treelike structure and is used to derive the moment measures. Second, a Hawkes process is defined as the solution to a thinning problem and the associated minimal solution is introduced. Afterwards continuations are defined and their coupling properties are analyzed. These results serve as a basis for answering the questions of existence and uniqueness of the aforementioned thinning problem. The formulation and proof of these statements requires several results from point process theory, some of which have to be extended first. Notable related topics that are discussed are: translation-invariant measures and their corresponding reduced versions; an extended notion of delta-functions and their usefulness in proving decompositions of moment measures; a concise construction of Poisson cluster fields and the proof of associated moment measure formulas; the formulation of the self-similarity structure of Hawkes processes; a general definition of strong solutions; and finally a general notion of hazard rates and its relation to intrinsic intensity functions. On the practical side, issues that come up during the implementation of parameter estimation and simulation algorithms are addressed: the parameterization of a reasonably large family of Hawkes processes which is suitable for numerical calculations; the derivation of algorithms which perform the calculations in a numerically efficient way; concrete examples of Hawkes processes; and an illustrative financial case study.
Finite element analysis of the behaviour of a crack in the orthopedic cement

In this paper, the finite element method is used to analyse the crack behaviour in the orthopedic cement of the total hip replacement by computing the stress intensity factors (SIFs) arround the crack tip. In this work, three cases are studied: crack emanating from a cavity, interaction effect of the crack emanating from a cavity with another cavity and the interaction effect of two cracks emanatingfrom two cavities. The stress intensity factors under mixed mode problems at the crack tip are computed for three zones of prosthesis: proximal, median and distal. The obtained results show that the crack initiated from a micro-cavity in the distal zone of cement can be propagated at the same time by opening and shearing of its lips. It is contrary to that initiated in the proximal zone which cannot be propagated. The mechanical behaviour of cracks in the medial zone depends of the crack initiation position.
UAV target detection based on attention mechanism YOLOv3 network

In recent years, the world's attention has made UAV surveillance a vital tool for combat reconnaissance. Target detection has taken the place of manual interpretation and has grown into a significant factor limiting UAV reconnaissance. Therefore, it is essential for battlefield reconnaissance to figure out how to increase the precision and speed of target detection. The fundamental issue addressed in this work is enhancing target detection accuracy while maintaining speed. YOLOv3 is a popular network structure in the industry because it is quick and precise compared to other network architectures. The attention mechanism, on the other hand, has a better detection impact on small and medium stimuli, whereas it just has a general detection effect on larger targets. The attention mechanism is implemented in YOLOv3 in this study.
Network-inspired design of broadband materials with reduced dimensionality

A network picture has been applied to various physical and biological systems not only to explore their governing mechanisms but also to develop progressive functionalities. Utilizing discretization schemes, both electrical and optical materials can also be interpreted as abstract 'graph' networks composed of couplings (edges) between local elements (vertices), which define the correlation between material structures and wave flows. Nonetheless, the fertile structural degrees of freedom in graph theory have not been fully exploited in physics owing to the suppressed long-range interaction between far-off elements. Here, by exploiting the similarity between Hamiltonians in different dimensions, we propose the design of reduced-dimensional materials that preserve the level statistics of highly complex networks with significant long-range coupling. We show that the disorder-induced removal of the level degeneracy in high-degree networks allows their isospectral projection to one-dimensional structures without any disconnection. This inter-dimensional isospectrality between high- and low-degree graphs enables the ultimate simplification of disorder-based broadband designs from three- to one-dimensional structures.