Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study on the Effects of Different Sources of Carboxymethyl Poria Polysaccharides on the Repair of DSS-Induced Colitis in Mice

Carboxymethyl poria polysaccharide plays important anti-tumor, antioxidant, and anti-inflammatory roles. Therefore, this study aimed to compare the healing impacts of two different sources of carboxymethyl poria polysaccharides [Carboxymethylat Poria Polysaccharides I (CMP I) and Carboxymethylat Poria Polysaccharides II (CMP II)] on ulcerative colitis in mice caused by dextran sulfate sodium (DSS). All the mice were arbitrarily split into five groups (n = 6): (a) control (CTRL), (b) DSS, (c) SAZ (sulfasalazine), (d) CMP I, and (e) CMP II. The experiment lasted for 21 days, and the body weight and final colon length were monitored. A histological analysis of the mouse colon tissue was carried out using H&E staining to assess the degree of inflammatory infiltration. The levels of inflammatory cytokines [interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and interleukin-4 (IL-4)] and enzymes [superoxide dismutase (SOD) and myeloperoxidase (MPO)] in the serum were examined using ELISA. Additionally, 16S ribosomal RNA sequencing was used to analyze the microorganisms in the colon. The results indicated that both CMP I and CMP II alleviated weight loss, colonic shortening, and inflammatory factor infestation in colonic tissues caused by DSS (p < 0.05). Furthermore, the ELISA results revealed that both CMP I and CMP II reduced the expression of IL-1β, IL-6, TNF-α, and MPO, and elevated the expression of IL-4 and SOD in the sera of the mice (p < 0.05). Moreover, 16S rRNA sequencing showed that CMP I and CMP II increased the plenitude of microorganisms in the mouse colon relative to that in the DSS group. The results also indicated that the therapeutic effect of CMP I on DSS-induced colitis in the mice was superior to that of CMP II. This study demonstrated that carboxymethyl poria polysaccharide from Poria cocos had therapeutic effects on DSS-induced colitis in mice, with CMP I being more effective than CMP II.
V2PNet: Voxel-to-Point Feature Propagation and Fusion That Improves Feature Representation for Point Cloud Registration

Point-based and voxel-based methods can learn the local features of point clouds. However, although point-based methods are geometrically precise, the discrete nature of point clouds negatively affects feature learning performance. Moreover, although voxel-based methods can exploit the learning power of convolutional neural networks, their resolution and detail extraction may be inadequate. Therefore, in this study, point-based and voxel-based methods are combined to enhance localization precision and matching distinctiveness. The core procedure is embodied in V2PNet, an innovative fused neural network that we design to perform voxel-to-pixel propagation and fusion, which seamlessly integrates the two encoder–decoder branches. Experiments are conducted on indoor and outdoor benchmark datasets with different platforms and sensors, i.e., the 3DMatch and Karlsruhe Institute of Technology and Toyota Technological Institute datasets, with the registration recall of 89.4% and the success rate of 99.86%, respectively. Qualitative and quantitative evaluations demonstrate that V2PNet has shown improvements in semantic awareness, geometric structure discernment, and other performance metrics.
Dissipative Control for Linear Time-Delay Systems

This paper focuses on a class of linear time delay systems. We are concerned with the design of dissipative static state feedback and dynamic output feedback controllers such that the closed loop system is quadratically stable and strictly (Q,S,R) dissipative. Sufficient conditions for the existence of the quadratic dissipative controllers are obtained by using a linear matrix inequality (LMI) approach. Furthermore, we provide a procedure of constructing such controllers from the solutions of LMIs. It is shown that the solvability of dissipative controller design problem is implied by the feasibility of LMIs. The main result of this paper unify the existing results on H ∞ control and passive control for linear time delay systems.
Interference-enhanced Raman scattering of F16CuPc thin films

Interference-enhanced Raman scattering (IERS) was observed for thin films of copper(II) hexadecafluorophthalocyanine (F16CuPc) deposited on SiO2 layers on a Si substrate. The enhancement of the Raman scattering originates from the interference of the light in the transparent SiO2 layer. Stripes of SiO2/Si with gradually varying oxide layer thickness were used as IERS substrates for a systematic study of the enhancement parameters. Raman measurements were carried out using three laser lines (325, 514.7, and 632.8 nm) in order to probe the F16CuPc thin films at non-resonant and resonant Raman conditions. Spectroscopic ellipsometry was used to determine both the SiO2 layer and thin film thicknesses. The intensity enhancement of the F16CuPc Raman peaks occurs periodically, corresponding to the alternating interference conditions for the Raman scattered light with increasing SiO2 layer thickness. The enhancement factors were calculated using the optical constants of the layers involved and the geometric parameters. This allows a straightforward application of IERS for optical studies of thin films and interfaces by calculating the dielectric thickness where maximum Raman enhancement is expected.
Music Genre Classification Using Convolutional Neural Network

Music genres are categories that classify music based on its common traditions and customs. These genres can enhance the enjoyment of music by providing listeners with a way to categorize and understand the music. When used constructively, it helps to better understand the art form, to recognize innovation and, above all, to improve the ability to judge quality. The main goal of this work is to study the different behaviors of musical genres based on their spectral representations and create an automated system for classification. Collecting the properly classified music dataset (i.e., GTZAN Music Genre) the feature-map of the data that is extracted is fed to the neural network model for evaluation. Accuracy of training, testing and validation is acquired. Along with that validation losses are reduced to an extent. The evaluation matrix is also computed. After the model is trained, it is deployed to the server along with a Flask-based REST API for easy access and use of the trained model for classification.
Direct Synthesis of Mn3[Fe(CN)6]2·nH2O Nanosheets as Novel 2D Analog of Prussian Blue and Material for High-Performance Metal-Ion Batteries

Rechargeable metal-ion batteries (RMIBs) are prospective highly effective and low-cost devices for energy storage. Prussian blue analogues (PBAs) have become a subject of significant interest for commercial applications owing to their exceptional specific capacity and broad operational potential window as cathode materials for rechargeable metal-ion batteries. However, the limiting factors for its widespread use are its poor electrical conductivity and stability. The present study describes the direct and simple synthesis of 2D nanosheets of MnFCN (Mn3[Fe(CN)6]2·nH2O) on nickel foam (NF) via a successive ionic layer deposition (SILD) method, which provided more ion diffusion and electrochemical conductivity. MnFCN/NF exhibited exceptional cathode performance for RMIBs, delivering a high specific capacity of 1032 F/g at 1 A/g in an aqueous 1M NaOH electrolyte. Additionally, the specific capacitance reached the remarkable levels of 327.5 F/g at 1 A/g and 230 F/g at 0.1 A/g in 1M Na2SO4 and 1M ZnSO4 aqueous solutions, respectively.
Augmented Reality Surgical Navigation System Integrated with Deep Learning

Most current surgical navigation methods rely on optical navigators with images displayed on an external screen. However, minimizing distractions during surgery is critical and the spatial information displayed in this arrangement is non-intuitive. Previous studies have proposed combining optical navigation systems with augmented reality (AR) to provide surgeons with intuitive imaging during surgery, through the use of planar and three-dimensional imagery. However, these studies have mainly focused on visual aids and have paid relatively little attention to real surgical guidance aids. Moreover, the use of augmented reality reduces system stability and accuracy, and optical navigation systems are costly. Therefore, this paper proposed an augmented reality surgical navigation system based on image positioning that achieves the desired system advantages with low cost, high stability, and high accuracy. This system also provides intuitive guidance for the surgical target point, entry point, and trajectory. Once the surgeon uses the navigation stick to indicate the position of the surgical entry point, the connection between the surgical target and the surgical entry point is immediately displayed on the AR device (tablet or HoloLens glasses), and a dynamic auxiliary line is shown to assist with incision angle and depth. Clinical trials were conducted for EVD (extra-ventricular drainage) surgery, and surgeons confirmed the system’s overall benefit. A “virtual object automatic scanning” method is proposed to achieve a high accuracy of 1 ± 0.1 mm for the AR-based system. Furthermore, a deep learning-based U-Net segmentation network is incorporated to enable automatic identification of the hydrocephalus location by the system. The system achieves improved recognition accuracy, sensitivity, and specificity of 99.93%, 93.85%, and 95.73%, respectively, representing a significant improvement from previous studies.
Extracting Spatial Muscle Activation Patterns in Facial and Neck Muscles for Silent Speech Recognition Using High-Density sEMG

Human is capable of producing versatile and precise speech owing to the complex neuromuscular systems that control the movement of facial and neck muscle groups. Silent speech recognition (SSR) based on surface electromyography (sEMG) has been widely researched, which enables speech communication in the absence of an audible acoustic signal. However, the differences in the activities of facial and neck muscle groups under different phoneme pronunciation conditions have not been well investigated. The present work aims to quantify the macroscopic spatial patterns of the muscle activations at the phoneme level during the movement of facial and neck speech articulator muscle groups (SAMGs) using 320-channel high-density (HD) electrode arrays. Ten subjects performed 14 vowel speech tasks and 15 consonant speech tasks in audible speech (AS) and silent speech (SS) modes, respectively. Specifically, the root-mean-square heat maps of sEMG signals were used to characterize the SAMGs activation patterns. The results show that the muscle activation regions are overlapped under different phoneme pronunciation conditions and are symmetric between the left and right sides of the face and neck with an average correlation coefficient $>0.9$ . In addition, the best result can achieve a classification accuracy of 85.78% for consonants and 79.42% for vowels in SS mode. The overall results can provide a reference to the hardware or electrode design of portable devices for practical use in future work.
Semidefinite programming for graph partitioning with preferences in data distribution

Graph partitioning with preferences is one of the data distribution models for parallel computer, where partitioning and mapping are generated together. It improves the overall throughput of message traffic by having communication restricted to processors which are near each other, whenever possible. This model is obtained by associating to each vertex a value which reflects its net preference for being in one partition or another of the recursive bisection process. We have formulated a semidefinite programming relaxation for graph partitioning with preferences and implemented efficient subspace algorithm for this model. We numerically compared our new algorithm with a standard semidefinite programming algorithm and show that our subspace algorithm performs better.
A Simple Approach to Pricing Options with Jumps

It is well known that certain classes of Levy processes (which have inter-period transition densities belonging to a class of exponential family) are appropriate for modelling cumulative returns of stock prices and other risky assets. A Radon-Nikodym derivative can be defined in terms of the cumulant transform of the Levy process and an appropriate choice of parameter. In the case of a complete market, the Gerber-Shiu method involves solving an identity for the unique correct parameter. The Radon-Nikodym derivative with the appropriate parameter induces the change of measure from market measure to the risk-neutral measure, from which European options can be priced. We extend the Gerber-Shiu method to also include processes with jumps (which generally have inter-period transition densities belonging to a class of mixtures of exponential families), where there may be more than one choice of a risk-neutral measure. Examples of our extension include a jump process with exponentially distributed jump size and Merton's jump-diffusion model. In the case of Merton's jump-diffusion model, the option price is obtained without the need for solving an integro-partial differential equation nor the need to apply Fourier transforms.
A Sharp Upper Bound for the Largest Eigenvalue of the Laplacian Matrix of a Tree

This paper contains results in the field of algebraic graph theory and specifically concerns the spectral radius of the Laplacian matrix of a tree. Let A(G) denote the adjacency matrix of a simple graph G. Then, the Laplacian matrix of G is given by L(G) = D(G) − A(G) where D is the diagonal matrix whose diagonal entries are the vertex degrees. The main result provides an upper bound for the spectral radius of any tree with n vertices and k pendant vertices.
Abundance and Distribution of Microplastics in Invertebrate and Fish Species and Sediment Samples along the German Wadden Sea Coastline

Simple Summary In order to reliably record pollution from microplastics within animals, indicators for a monitoring program must be found. For this purpose, we collected invertebrates, fish, and sediment cores at 10 sites along the Wadden Sea coast of Lower Saxony, Germany; determined the amount of microplastics; and made recommendations for potential bioindicator species, based on the sampling conditions and results. The species studied included lugworm (Arenicola marina), common periwinkle (Littorina littorea), blue mussel (Mytilus edulis), and European flounder (Platichthys flesus). In total, microplastics were detected in 88% of the specimens and in each sediment core sample. Regarding the polymer composition, eight different types of microplastic were identified. Based on the results, the species blue mussel and European flounder are recommended for microplastic monitoring in biota. Abstract Monitoring strategies are becoming increasingly important as microplastic contamination increases. To find potentially suitable organisms and sites for biota monitoring in the German Wadden Sea, we collected invertebrates (n = 1585), fish (n = 310), and sediment cores (n = 12) at 10 sites along the coast of Lower Saxony between 2018 and 2020. For sample processing of biota, the soft tissue was digested and the sediment samples additionally underwent a subsequent density separation step. Microplastic particles were identified using Nile red and fluorescence microscopy, followed by polymer composition analysis of a subset of particles via µRaman spectroscopy. All investigated species, sediment cores, and sites contained microplastics, predominantly in the morphology class of fragments. Microplastics were found in 92% of Arenicola marina, 94% of Littorina littorea, 85% of Mytilus edulis, and 79% of Platichthys flesus, ranging from 0 to 248.1 items/g. Sediment core samples contained MPs ranging from 0 to 8128 part/kg dry weight of sediment. In total, eight polymers were identified, predominantly consisting of polyethylene, polyvinylchloride, and polyethylene terephthalate. Considering the sampling, processing, and results, the species Mytilus edulis and Platichthys flesus are suitable species for future microplastic monitoring in biota.
Structural controllability

The new concepts of "structure" and "structural controllability" for a linear time-invariant control system (described by a pair ( A,b )) are defined and studied. The physical justification of these concepts and examples are also given. The graph of a pair ( A,b ) is also defined. This gives another way of describing the structure of this pair. The property of structural controllability is reduced to a property of the graph of the pair ( A,b ). To do this, the basic concept of a "cactus" and the related concept of a "precactus" are introduced. The main result of this paper states that the pair ( A,b ) is structurally controllable if an only if the graph of ( A,b ) is "spanned by a cactus. " The result is also expressed in a more conventional way, in terms of some properties of the pair ( A,b ).
Performance and Attrition in Information Technology Studies; A Survey of Students' Viewpoints

Programming is a relatively difficult skill to acquire; the mean worldwide pass rate of CS1 courses is 68%. Programming performance is also difficult to predict. Despite plentiful studies on the topic, there is no consensus of factors predicting performance. The problem escalates from academic institutions to the whole society, as IT industry craves more IT professionals and IT faculties suffer from numerous dropouts. The aim of this study is to consider performance and attrition in higher education IT studies from the perspective of IT majors. Students are regarded as experts by experience in the study. In developing administrative and pedagogical practices, their voices should be heard. The online survey utilised a novel three-phase question methodology combining open and closed questions to elicit initial, informed and prioritised opinions of the students. The survey was replicated to consolidate the results. Students' informed and prioritised opinions on factors contributing to success in computing studies emphasised will to learn, interest in IT, problem-solving, logical reasoning, self-directed information seeking, diligence and perseverance. Main reasons to consider discontinuing IT studies were experiences of difficulty, lack of motivation and lack of time. The top factors contributing to success in computing studies can be categorised into motivational factors, cognitive skill factors and self-directional engagement factors. Scarcities in the very same factor categories were also identified as causes of attrition. Students are expected to take responsibility for their studies, but young brains may not be mature for sufficient self-direction and engagement. The developed three-phase question strategy proved to be informative.
Low-Profile Planar Ultrawideband Modular Antenna Array Loaded With Parasitic Metal Strips

A low-profile dual-polarized planar ultrawideband modular antenna (PUMA) array is proposed in this article. The overall profile is as small as 11.4 mm (<inline-formula> <tex-math notation="LaTeX">$0.228\lambda _{high}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$\lambda _{high}$ </tex-math></inline-formula> is the free-space wavelength at the highest operating frequency) based on element sizes <inline-formula> <tex-math notation="LaTeX">$25\times25$ </tex-math></inline-formula> mm<sup>2</sup> (<inline-formula> <tex-math notation="LaTeX">$0.5\times 0.5\lambda _{high}^{2}$ </tex-math></inline-formula>) and a large operating frequency bandwidth achieved by loading lossless parasitic metal strips between the dipole patches and the ground plane. The loop-mode resonance that causes deterioration of the port isolation around the lowest operating frequency is comprehensively analyzed and suppression methods are proposed. To further reduce the overall profile, a metasurface-based wide-angle impedance matching (MS-WAIM) layer is introduced. The surface waves guided by the MS-WAIM layer during wide-angle scanning in H-plane are suppressed by cutting properly-sized square holes at critical positions. The calculated results show that the proposed infinite array can scan up to ±60° in E-/H-planes with active voltage standing wave ratios (VSWRs) below 2.9 within 2-6 GHz and orthogonal port isolations beyond 20 dB. A <inline-formula> <tex-math notation="LaTeX">$12\times11$ </tex-math></inline-formula> array prototype is fabricated and reasonable agreement is achieved between the calculated and measured results.
Ellipse Detection Using Randomized Hough Transform

This paper discusses the Randomized Hough Transform used to find ellipses in images. The equations to find ellipses and their implementation in the algorithm are explained. The algorithm performed well, finding ellipses of orientation 0 o and 9O o from the x-axis in various images. Ellipses were also found in a real-world image after preprocessing.
Singularities of two-point functions in Quantum Field Theory

The main topic of the present thesis is the study of singularities of two-point functions of spin-0 and spin-1/2 quantum fields, possibly set on curved spacetime or in the presence of smooth, external electromagnetic potentials. The first part reviews the results necessary for the construction of neutral and charged non-interacting quantum fields on globally hyperbolic spacetimes, and supplements the arguments needed in the case when no charge symmetry exists. In this general situation, the Hadamard condition, which refers to the singularities of the two-point functions, is discussed, and its relation to the theory of distinguished parametrices of Duistermaat and Hoermander is explained. Additionally, similarities between the spin-0 and spin-1/2 case are exhibited by considering a two-component form of the Klein-Gordon equation. It is then used in the static case to reformulate the classical dynamics as an evolution equation whose generator is self-adjoint in the sense of Krein spaces. By methods of spectral theory in Krein space, we construct Hadamard two-point functions in the spin-0 case for a class of strong electric potentials which possess no ground state. The second part is concerned with renormalisation of interacting fields in the approach of Epstein and Glaser. We focus on the problem of recovering symmetries, possibly lost in the process of extending singular distributions on R^n\{0} to R^n. In our approach, this is done by imposing that the extended distributions are in the kernel of a given set of (differential) operators. The symmetries are then recovered using a map, which in typical applications turns out to be linear. The same method is applied to derive the relation between off-shell and on-shell time-ordered products for a scalar theory on Minkowski space.