Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Rapid Detection Method of Dry Matter Content in Raw Milk Based on Mid-infrared Spectrum

This paper takes raw milk as research object, and using mid-infrared spectrum analysis method rapidly tests dry matter in raw milk through establishing quantitative analysis model. First of all, researchers collect 84 kinds of raw milk which is different areas and varieties in Heilongjiang province, and classify 84 samples into calibration sets and validation sets by standard chemical testing and spectral scanning on raw milk, and calibration sets contain 64 samples, and validation sets contain 20 samples. Then, respectively selecting SPA and GA characteristic wavelength after treating by smoothing denoising method which window size is 11 points, and establishing PLS model and model demonstration. Eventually, researchers draw the conclusion that SPA wavelength selection method which value of m_max is 10 and GA wavelength selection method which value of Evaluat is 10d can effectively improve validation set model precision, but precision of the latter is higher and characteristic wavelength point reduces from 352 to 10, The calibrating determination coefficient R2 of model is 0.8092155, root mean square error (RMSEC ) is 0.1206172. Validation set determination coefficient R2 is 0.8620867, the root mean square error (RMSEC) is 0.0950656, and relative standard deviation RSD<3%. These prove that the method for rapid testing of raw milk components is feasible.
Towards a robust and fully reversible image watermarking framework based on number theoretic transform

This paper presents a new watermarking approach in the spectral domain based on the number theoretic transform (NTT) to ensure sharing and transferring medical images in a secure way. Through this approach we ensure also the robustness of the embedded watermarks within the medical image to prove ownership. The NTT's effectiveness has been proven in the images lossless transmission and in convolution fast calculation. In this new approach, the watermark is embedded into the NTT image based on linear interpolation with a specific factor controlling the visibility/invisibility of the watermark. The extraction process will be performed on the attacked watermarked image in order to extract the attacked watermark. We are particularly interested in the NTT since it is considered as a fully reversible transform without any loss when choosing the suitable parameters. We measured the robustness of the proposed approach by the commonly used metrics against several scenarios of attacks (geometric and non-geometric) such as JPEG compression, adding noise, rotation, median filtering, etc. The tests are performed on several types of medical images. The obtained results are very encouraging and represent a remarkable robustness which will be detailed in this paper.
Exploring the Dark Universe with Cosmic Microwave Background and Optical Data

of the Dissertation Exploring the Dark Universe with Cosmic Microwave Background and Optical Data by Mathew Syriac Madhavacheril Doctor of Philosophy in Physics Stony Brook University 2016 Over the past two decades, a standard cosmological model has emerged that supports the picture of an expanding Universe dominated by dark matter and dark energy. Understanding the nature of the dark Universe is a major open problem in cosmology. The work described in this dissertation advances our understanding of the dark Universe by first constraining the properties of dark matter through the effect of annihilations on the cosmic microwave background (CMB), and then by mapping dark matter via gravitational lensing as a way of constraining dark energy. By making the first measurement of gravitational lensing of the CMB by dark matter halos and the first measurement of the ratio of this signal to the lensing signal from optical data, this dissertation develops new techniques to map dark matter and constrain the properties of dark energy. We first investigate the particle properties of dark matter by examining its effect on fluctuations in the CMB, thereby setting the tightest constraints on the annihi-
Positive absorption constraint based ptychographical algorithm with fast convergence rate

Ptychography can reconstruct the complex amplitude distribution of the transmission object from the overlapped diffraction patterns. The extended ptychographical iterative engine (ePIE) algorithm is considered as one of the most popular phase retrieval algorithms of present time which has strong robustness and high image quality. However, no constraint is added in the iteration process, which results in slow convergence and makes the real-time imaging difficult. To overcome this problem, an efficient phase retrieval algorithm is proposed based on the constraint of positive absorption in the object plane where the absorption coefficient and phase distribution of the object are constrained by the positive absorption of the object. The simulation demonstrated that the proposed algorithm has greatly improve the convergence rate and imaging quality of traditional ePIE algorithm and is expected to be applied in real-time imaging.
Excitation Magnetohydrodynamic Wave by Gravitational Wave Produced by Binary of Neutron Stars

The gravitational wave, through the strongly magnetized plasma surrounding the neutron stars, in the z-direction, deforms plasma particle rings in ellipses, alternating axes periodically along the direction of the magnetic field (x-axis) and of the y-axis. The uniform field leads to a modulation of the magnetic field, which results in magnetic pressure gradients (magneto-acoustic mode) or in the shear of the magnetic field lines (Alfven mode). The gravitational wave drives MHD modes and transfers energy to the plasma, can become an important alternative process for the acceleration of baryons to high Lorentz factors observed in short GRBs. The total amount of energy that is transferred from the gravitational wave to the plasma is estimated ( ≃ 1040J - 1041 J), with γ ≃ 102. We compare our results with previously obtained results by other works.
Effect of Rectangular Winglet Pair in Common Flow Down Configuration on Heat Transfer from an Isothermally Heated Plate

ABSTRACT Present three-dimensional numerical study aims to investigate the effect of mounting rectangular winglet pair (RWP) on heat transfer enhancement in flow over a flat plate. Computations for incompressible flow of air have been carried out using commercial software ANSYS Fluent. Flow of air has been considered over the surface of an isothermally heated horizontal plate in presence of RWP in the range of Reynolds number from 400 to 2000. Common flow down configuration of RWP has been considered to study the effect of various geometric parameters, such as length of RWP, spacing between leading edges of the winglets and angle of attack of RWP, on flow characteristics and enhancement in heat transfer. Flow and temperature field characteristics have been presented using streamlines and temperature contours near the plate surface and streamlines in cross-stream planes. Enhancement in heat transfer in presence of RWP has been quantified using cross-stream variation of local Nusselt number, streamwise variation of span-averaged Nusselt number and surface-averaged overall Nusselt number.
Numerical radiative transfer using an immerse volume method

For heating and quenching operations occurring during material forming processes, thermal radiation is the the predominant physical phenomenon. Hence, when one tries to simulate such processes, it is important to have at disposal powerful tools for the numerical modelling of thermal radiation.The numerical simulation of these processes often rises numerous problems and questions, as the representation of a complex environment, involving several components ( ingots, burners, nozzles, walls), to deal with different coupled physical phenomena ( flow, heat transfer, boiling, thermal radiation). In this regard, some “immersed” numerical methods, allows a generalist treatment of these different problems, have gained popularity and drag interest of the scientific community in the recent years.The Thost project, aiming to produce a software for heat transfer during material forming processes, fits in the framework, and this PhD is part of this project. The goal is therefore to design tools for numerical modelling of thermal radiation within the immersed volume method of the Thost software. Two approaches are presented: one consisting in the adaptation of an existing method to the context of the immersed volume method, another concerning the development of a formulation for a specific model of radiation. These methods are then tested on industrial applications provided by our partners.
Alternative framework of the Gaussian filter for non-linear systems with randomly delayed measurements and correlated noises

Compared with the normal Gaussian filter that measurements are acquired in real-time and process and measurement noises are independent, the authors study a class of non-linear state estimation problems with one-step randomly delayed measurements and correlated noises. Using a novel alternative framework, where the process and measurement noises are as the augment of the state vector, the author can deduce the related formula and get a novel filtering algorithm. In order to explain the feasibility of the proposed algorithm, this study demonstrates that the relevant recursive formula satisfies the Gaussian distribution. In order to explain the rationality of the proposed algorithm, the relevant union estimation form is given in Section 1. For the sake of facilitating computer simulation, the sub-optimal realisation of the proposed algorithm on the basis of the spherical-radial rule is given, which is alternative framework Gaussian filter with the correlated noise and delayed measurements. The superiority of the algorithm presented, compared with the other algorithm, is shown in the end of this study.
Fuzzy Feature Visualization of 3D Vector Field by Information-Entropy-Based Texture Adaptation

Texture adaptation is a challenging issue in tex-ture-based feature visualization. In order to visualize as more information as we can, this paper presents a texture adaptation technique for fuzzy feature visualization of 3D vector field, taking into account information quantity carried by vector field and texture based on extended information entropy. Two definitions of information measurement for 3D vector field and noise texture, MIE and RNIE, are proposed to quantitatively represent the information carried by them. A noise generation algorithm based on three principles derived from minimal differentia of MIE and RNIE is designed to obtain an approximately optimal distribution of noise fragments which shows more details than those used before. A discussion of results is included to demonstrate our algorithm which leads to a more reasonable visualization results based on fuzzy feature measurement and information quantity.
Decomposing Worldwide Complete Spherical Bouguer Gravity Anomaly Using 2-D Empirical Method

Currently available worldwide gravity anomaly data provides a high-resolution (2’×2’) of Complete Spherical Bouguer Anomaly (CSBA) based on the available information of the Earth gravity field from surface and satellite measurements. The data has not only been provided and processed thoroughly but it also has been claimed to be appropriate for various geophysical applications. Therefore, the analysis of gravity anomaly is becoming increasingly significant for the earth sciences as a whole and assisting both shallow and deep geological problems. Earth gravity anomaly has to be analyzed carefully as it has very complex data due to anomaly mixing of the density masses spread over the Earth horizontally and vertically. The bigger the spatial coverage of data (e.g. global scale data), the more severe the data from anomaly mixing due to various wavelength. BEMD is an empirical method supposedly suitable with highly oscillation-mixing data. It can effectively isolate each local anomaly in details and is analogized as successively reverse moving average with local windowing. BEMD is designed to reduce multi-component, non-linear gravity field data to a series of single local anomaly contributions. Anomaly from a single body was assumed as a mono-component signal. The main advantage of BEMD processing techniques is to present the subtle details in the data which are not clearly identified in anomaly maps, without specifying any prior information about the nature of the source bodies. As the result, we have identified regional anomalies due to the drift of continental and oceanic masses considered as crust-regional anomaly (CRA). We remove the CRA from the CBA to provide surface-residual anomaly (SRA) where shallow geologic bodies reveal. Meanwhile, the CRA itself can be used as reference to reduce this high magnitude anomaly from any measurement data to exhibit only shallow body anomaly. Further analysis can be carried out to build a general understanding of the details and parameters of the shallower or deeper causative body distributions.
A New Mathematical Method for Solving Cuttings Transport Problem of Horizontal Wells: Ant Colony Algorithm

Cuttings transport problem has long been recognized as one of the key difficulties in drilling horizontal wells, and the models in cuttings transport research are usually formulated with highly nonlinear equations set. When using Newton methods to solve real engineering problems with nonlinear equations set, the problems of result dependence on initial values, Jacobian matrix singularity, and variable outflow of its definition domain in iterations are three of the often-encountered difficulties. In this paper, the ant colony algorithm is applied to solve the two-layer cuttings transport model with highly nonlinear equations set. The solution-searching process of solving nonlinear equations set is transformed into an optimization process of searching the minimum value of an objective function by applying ant colony algorithm. Analyzing the results of the example, it can be concluded that ant colony algorithm can be used to solve the highly nonlinear cuttings transport model with good solution accuracy; transforming the solution-searching process of solving nonlinear equations set into an optimization process of searching the minimum value of the objective function is necessary; the real engineering problem should be simplified as much as possible to decrease the number of unknown variables and facilitate the use of ant colony algorithm.
Evaluating Binary Splits on Nominal Inputs

The maximally selected statistic approach in building tree models is shown to be a cause of variable selection bias. In this study we propose three methods to solve this problem in building regression trees with nominal predictor variables. Out of the three methods proposed we explored only two in detail and defer one for further research. We developed an exact method to compute the p-value corresponding to the maximized splitting statistic in regression trees for nominal predictor variables with at most 10 distinct levels and a method to estimate the best cutoff point as a parameter in a parametric nonlinear mixedeffect model in regression trees for nominal predictor variables with any number of distinct levels. The methods are shown to overcome the variable selection bias in an extensive simulation study and in a real data example.
The answer depends on your lecturer

ABSTRACT This article is concerned with the approaches to the root concept that lecturers in calculus, linear algebra and complex analysis employ in their instruction. Three highly experienced university lecturers participated in the study. In the individual interviews the participants referred to roots of real numbers, roots of complex numbers, roots as real functions and roots as complex functions. However, participants’ approaches to the root concept were mathematically not equivalent and the lecturers resisted to the approaches of their peers. The choices of approach were shaped by different types of pedagogical considerations, such as the mathematical ideas that appear in the courses that lecturers teach, textbook approaches and lecturers’ interpretations of students’ further academic needs. Several cases were indicated where the participants consciously compromised mathematical rigour and limited the scope of their instruction when teaching general mathematics courses.
Variational photoacoustic image reconstruction with spatially resolved projection data

In this work, we explore different reconstruction algorithms for photoacoustic image reconstruction of spatially resolved projection data. While the commonly used back-projected reconstruction is efficient and fast to compute, it cannot deal with noise that arises during measurements. Therefore, we formulate photoacoustic image reconstruction in a variational framework where we add prior knowledge in terms of Total Generalized Variation. Using this prior knowledge, we can reduce measurement noise and improve the visibility of vessel structures.
High Order Well-Balanced Weighted Compact Nonlinear Schemes for Shallow Water Equations

In this study, a numerical framework of the high order well-balanced weighted compact nonlinear (WCN) schemes is proposed for the shallow water equations based on the work in [S. Zhang, S. Jiang, C. -W Shu, J. Comput. Phys. 227 (2008) 7294-7321]. We employ a special splitting technique for the source term proposed in [Y. Xing, C. -W Shu, J. Comput. Phys. 208 (2005) 206-227] to maintain the exact Cproperty, which can be proved theoretically. In the meantime, the genuine high order accuracy of the numerical scheme can be observed successfully, and small perturbation of the stationary state can be resolved and evolved well. In order to capture the strong discontinuities and large gradients, the fifth-order upwind weighted nonlinear interpolations together with the fourth/sixth order cell-centered compact scheme are used to construct different WCN schemes. In addition, the local characteristic projections are considered to further restrain the potential numerical oscillations. A variety of representative oneand two-dimensional examples are tested to demonstrate the good performance of the proposed schemes. AMS subject classifications: 35L65, 35L67
Self-propulsion of bent bimetallic Janus rods

In this paper, the sideways self-propulsion behaviour of straight and bent Janus micro-rods is presented. Janus micro-rods are prepared by consecutively sputter-coating platinum and gold on different sides of aligned polystyrene micro-fibers produced via electrospinning. Self-propulsion is induced via the reaction of hydrogen peroxide at the Janus particle interface, and the effect of the particles shape on their self-propulsion trajectories is studied. We show that the self-propulsion trajectories change from straight to circular when the particle shape is changed from a straight to an ‘L’ shaped rod. In order to understand and quantitatively describe the particle shape effects, we adopted a mathematical model developed by Hagen et al (2011 J. Phys.: Condens. Matter. 23 194119) to predict their trajectories. We show that the trajectory of irregularly shaped micro-rods depends only on the particle shape. The predicted trajectories for various particle shapes are in good agreement with the experimental observations.
Performances of transparent indium zinc oxide thin film transistors using ZrO2 as dielectric processed by solution method

We report here the electrical and UV‐photoelectrical performance of transparent indium zinc oxide (IZO) thin film transistors with solution‐processed zirconia (ZrO2) dielectric. The channel layers were deposited by magnetron sputter at room temperature. The ZrO2 dielectric was deposited by solution process under ambient conditions followed by low temperature annealing. The films were structurally characterized by X‐ray diffraction and atomic force microscope. Good device characteristics have been obtained with a field effect mobility of 30.7 cm2 V−1s−1, a current on/off ratio of 105, a threshold voltage of 0.8 V, and a sub‐threshold swing of 30 mV decade−1. A resistor‐load inverter was fabricated and shows reasonable transfer characteristics with a gain of about 5 at supply voltage of 2 V. It was observed that the transistors are sensitive to UV illumination. When exposed to ultraviolet light with an intensity of 120 µW cm−2, the photo‐to‐dark current ratio was more than 104 in the depletion region. All the above features make IZO thin film transistor a promising candidate to be also used as a UV‐photo transistor.
THE COMPOUND DECISION PROBLEM WITH m X n FINITE LOSS MATRIX

0. Summary. Simultaneous consideration of N statistical decision problems having identical generic structure constitutes a compound decision problem. The risk of a compound decision problem is defined as the average risk of the component problems. When the component decisions are between two fully specified distributions P, and P2, P1 $ P2, Hannan and Robbins [5] give a decision function whose risk is uniformly close (for N large) to the, risk of a best "simple" procedure based on knowing the proportion of component problems in which P2 is the governing distribution. This result was motivated by heuristic arguments and an example (component decisions between M(- 1, 1) and K(1, 1)) given by Robbins [8]. In both papers, the decision functions for the component problems depended on data from all N problems. This paper generalizes and strengthens a result of Hannan and Robbins (Theorem 4, [5]) to the case where each component problem consists of making one of n decisions based on an observation from one of m distributions. Specifically, we find upper bounds for the difference in the risks (the regret function) of a certain compound procedure and a best "simple" procedure which is Bayes against the empirical distribution on the component parameter space. Theorem 2 gives sufficient conditions for a uniform (in parameter sequences) bound on the regret function of order N1, while Theorem 3 states sufficient conditions for a uniform bound of order N-1. For m = n = 2, Theorem 2 furnishes a strength
Enhanced thermal transport across multilayer graphene and water by interlayer functionalization

Graphene has attracted enormous attention due to its extraordinary physical properties, which have potential for increasing the thermal conductivity of nanocomposites or nanofluids, and the thermal resistance between graphene and the surrounding matrices arises as an important issue. In this paper, the thermal transport at the graphene-water interface is investigated by molecular dynamics simulations. The interfacial thermal resistance decreases with the graphene layer number. Interlayer functionalization by oxygen atoms is applied to tune the interfacial thermal resistance. A peak thermal resistance reduction of nearly 50% is generated with the oxygen ratio of only 0.5% for two-layer graphene. Based on the analyses of vibrational density of states, it is found that lower thermal resistance is consistent with more vibrational density of states overlaps at the interface. Our results are instructive for improving the interfacial thermal transport in graphene-based nanocomposites and nanofluids.
Adiabatic inner volume selection (IVS) method for high resolution 3D MRI

O. Grohn, J. Poduslo, C. Jack, J. Lin, M. Garwood Center for Magnetic Resonance Research, Minneapolis, MN, United States, Mayo Clinic, Rochester, MN, United States Synopsis A novel inner volume selection (IVS) method using single hyperbolic secant (HS)-pulses for slab selection for 3D imaging is introduced. The feasibility of the method for high-resolution 3D imaging is demonstrated by imaging amyloid-β plaques size of < 100 μm in transgenic mouse brain, ex vivo. The quadratic phase-roll caused by single HS refocusing pulses spreads the signal energy in the time-domain, which normally prevents use of single-HS pulses for refocusing. However, in 3D-imaging the phase variation over each imaging voxel was found to be insignificant, and a 17% improvement in signal-to-noise ratio resulted because receiver gain could be increased to reduce digitization noise.