Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Algorithms via Linear Algebra: A Primer

This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of all the relevant material from linear algebra. By emphasizing computation and algorithms rather than physics, this primer makes quantum algorithms accessible to students and researchers in computer science without the complications of quantum mechanical notation, physical concepts, and philosophical issues. After explaining the development of quantum operations and computations based on linear algebra, the book presents the major quantum algorithms, from seminal algorithms by Deutsch, Jozsa, and Simon through Shor's and Grover's algorithms to recent quantum walks. It covers quantum gates, computational complexity, and some graph theory. Mathematical proofs are generally short and straightforward; quantum circuits and gates are used to illuminate linear algebra; and the discussion of complexity is anchored in computational problems rather than machine models. Quantum Algorithms via Linear Algebra is suitable for classroom use or as a reference for computer scientists and mathematicians.
The Color Glass Condensate and the Glasma: Two Lectures.

These two lectures concern the Color Glass Condensate and the Glasma. These are forms of matter which might be studied in high energy hadronic collisions. The Color Glass Condensate is high energy density gluonic matter. It constitutes the part of a hadron wave function important for high energy processes. The Glasma is matter produced from the Color Glass Condensate in the first instants after a collision of two high energy hadrons. Both types of matter are associated with coherent fields. The Color Glass Condensate is static and related to a hadron wavefunction, where the Glasma is transient and evolves quickly after a collision. I present the properties of such matter, and some aspects of what is known of their properties.
A new spectral theory of turbulent flows with stable stratification

Vertical-horizontal anisotropy and turbulence-internal waves interaction are among the most fundamental problems one encounters in modeling of turbulent flows with stable stratification. Governed by strong nonlinearity, these two phenomena have been beyond reach for analytical theories. Here, we present an attempt to develop a self-consistent theory capable of dealing with host of complicated factors introduced by nonlinearity and stable stratification within a framework of a second-moment spectral closure. This theory is based upon a mapping of the actual velocity field to a quasi-Gaussian field whose modes are governed by the Langevin equation. The parameters of the mapping are calculated using a systematic process of successive averaging over small shells of velocity and temperature modes that eliminates them from the equations of motion. This procedure does not differentiate between turbulence and internal waves and accounts for their combined effect. This approach offers a powerful mathematical tool that allows tackling problems that have been nearly intractable; among them are the threshold criterion for generation of internal waves and the modification of their dispersion relation by turbulence. The process of successive small scales elimination results in a model describing the largest scales of a flow. Partial scale elimination gives sub-grid-scale viscosities and diffusivities that can be used in large eddy simulations. The elimination of all fluctuating scales results in RANS models. The model predicts various important characteristics of stably stratified flows, such as the dependence of the vertical turbulent Prandtl number on Froude and Richardson numbers, anisotropization of the flow filed, and decay of vertical diffusivity under strong stratification in good agreement with computational and observational data. The model’s results are suitable for immediate use in practical applications. Here we present tests of the model as applied to atmospheric boundary layer with strong stable stratification.
Impact of nuclear effects on the determination of the nucleon axial mass

We analyze the influence of nuclear effects on the determination of the nucleon axial mass from nuclear cross sections. Our work is based on a formalism widely applied to describe electron-nucleus scattering data in the impulse approximation regime. The results of numerical calculations show that correlation effects, not taken into account by the relativistic Fermi gas model, sizably affect the Q{sup 2} dependence of the cross section. However, their inclusion does not appear to explain the large values of the axial mass recently reported by the K2K and MiniBooNE Collaborations.
Inelastic Confinement-Induced Resonances in Quantum Dots

Recently, it was shown that the coupling of center-of-mass and relative motion in atomic systems leads to inelastic confinement-induced resonances (ICIRs) [Phys. Rev. Lett. 109, 073201 (2012)]. In the present work, the possible occurrence of ICIRs in quantum dots is investigated. Particularly, electron-hole and electron-electron two-body systems with long-range Coulomb interaction are considered using the material parameters of GaAs. ICIRs are identified for the electron-hole system verifying the universal nature of the ICIR and, additionally, resonances due to the coupling of center-of-mass and relative motion are found also for the electron-electron system. In analogy to the coherent molecule formation appearing at ICIR in atomic systems a significant change in the mean distance between electrons and holes at the resonance is observed. By using the redistribution of the particle densities at the resonance position in modern quantum-dot experiments, the ICIR can provide a new technique for the control of the electron distribution in quantum dots and for the generation of single photons on demand.
STUDIES ON BIO AND CHEMICAL FERTILIZATION ON SWEET POTATO (Ipomea batatas, L) 1-EFFECT OF SOME CHEMICAL NITROGEN SOURCES, RATES AND BIOFERTILIZER (NITROBIEN) ON PLANT GROWTH, YIELD AND QUALITY OF TUBER ROOTS

This work was conducted on sweet potato cv. 93 to evaluate the effect of Ca (NO 3 ) 2 and (NH 4 ) 2 SO 4 fertilizers as chemical N-sources in different rates either single or with biofertilizer (nitrobien) on the plant growth, yield and its components . The obtained results could be summarized as follows:
On the Dirichlet Problem for First Order Linear Hyperbolic PDEs on Bounded Domains with Mere Inflow Boundary

Here we study the Dirichlet problem for first order linear and quasi-linear hyperbolic PDEs on a simply connected bounded domain of $\R^2$, where the domain has an interior outflow set and a mere inflow boundary. By means of a Lyapunov function we show the existence of a unique solution in the space of functions of bounded variation and its continuous dependence on all the data of the linear problem. Finally, we conclude the existence of a solution to the quasi-linear case by utilizing the Schauder fixed point theorem. This type of problems considered here appears in applications such as transport based image inpainting.
Optimal registration of deformed images

Motivated by the need to locate and identify objects in three dimensional CT images, an optimal registration method for matching two and three dimensional deformed images has been developed. This method was used to find optimal mappings between CT images and an atlas image of the same anatomy. Using these mappings, object boundaries from the atlas was superimposed on the CT images. A cost function of the form DEFORMATION-SIMILARITY is associated with each mapping between the two images. The mapping obtained by our registration process is optimal with respect to this cost function. The registration process simulates a model in which one of the images made from an elastic material is deformed until it matches the other image. The cross correlation function which measures the similarity between the two images serves as a potential function from which the forces required to deform the image are derived. The deformation part of the cost function is measured by the strain energy of the deformed image. Therefore, the cost function of a mapping is given in this model by the total energy of the elastic image. The optimal mapping is obtained by finding the equilibrium state of the elastic image, which by definition corresponds to a local minimum of the total energy. The equilibrium state is obtained by solving a set of partial differential equations taken from the linear theory of elasticity. These equations are solved iteratively using the finite differences approximation on a grid which describes the mapping. The image function in a spherical region around each grid point is described by its projections on a set of orthogonal functions. The cross correlation function between the image functions in two regions is computed from these projections which, serve as the components of a feature vector associated with the grid points. In each iteration step of the process, the values of the projections are modified according to the currently approximated deformation. The method was tested by registering several two and three dimensional image pairs. It can also be used to obtain the optimal mapping between two regions from a set of corresponding points (with and without error estimates) in these regions.
Effect of Dietary Garden Cress Seeds on Growth Performance, Feed Utilization, Carcass Characteristics and some Physiological Responses of Growing Rabbits

A total number of 72 growing rabbits (V-Line) with an average initial weight of 605 ± 8.79 g live body. Rabbits at the age of 6 weeks were used to investigate the effect of increasing levels of garden cress, Lepidium sativum, seeds (0, 3, 4.5, 6%) on growth performance, feed utilization, digestibility, carcass characters and physiological performance. The growing rabbits were fed the experimental diets for 7 weeks. The results revealed that garden cress seeds contain considerable levels of crude proteins and crude lipids levels. The dietary garden cress significantly improved final weight, weight gain, and total relative growth rate compared to the control. The maximum growth response was recorded between 3- 4.5% garden cress seeds levels according to the high significant quadratic regression. The feed conversion ratio significantly improved with 3 and 4.5% dietary garden cress seeds levels. The digestibility of crude protein 70.37, 72.46, 73.30 and 79.04%, lipids 77.76, 81.36, 85.20 and 76.94% and nitrogen balance 1.64, 2.22, 2.02 and 2.18 for 0,3,4.5 and 6% garden cress seeds improved with increasing dietary garden cress seeds. The carcass treats did not affect with different treatments, except a significant reduction in the Kidney fat with dietary garden cress seeds. The serum lipid profile did not affect by garden cress seeds supplementation. Finally, the dietary garden cress seeds at levels of 3-4.5% could be hematological serum
CENPO is Associated with Immune Cell Infiltration and is a Potential Diagnostic and Prognostic Marker for Hepatocellular Carcinoma

Purpose To examine the expression, clinical significance, and potential regulatory mechanism of centromere protein O (CENPO) in hepatocellular carcinoma (HCC). Methods CENPO expression in pan-cancer was studied using the TCGA-GTEx database, in HCC and normal liver tissues using the GEO and TCGA databases, and in clinical HCC samples by RT-qPCR. The diagnostic value of CENPO was assessed using receiver operating characteristic curves. Univariate and multivariate regression analyses of factors associated with HCC prognosis were performed. CENPO function and its mechanism in HCC were explored using GO, KEGG, and GSEA analyses of differentially expressed genes (DEGs). Association of CENPO expression with immune cell infiltration and immune checkpoint-associated molecules was conducted using TCGA data and the TIMER2.0 database. Relationships between CENPO expression and DNA methylation were analyzed using the UALCAN and cBioPortal databases. CENPO expression in HCC cell lines was detected using RT-qPCR. Results CENPO is upregulated in most cancers, including HCC and cell lines, and is a potential biomarker for HCC diagnosis (AUC = 0.936, 95% CI: 0.911–0.960). Higher CENPO expression was associated with poorer outcomes in patients with HCC (OS, p = 0.004; DSS, p = 0.002; PFI, p < 0.001), and CENPO was an independent predictor of factors influencing overall survival in HCC. DEGs between samples with high and low CENPO levels were enriched in various biological processes, including activation of the G2M checkpoint and other signaling pathways, while CENPO expression correlated with HCC immune cell infiltration and immune checkpoint-associated molecules, as well as CENPO promoter methylation (p < 0.001). Conclusion In HCC and cell lines, CENPO is overexpressed, a potential diagnostic marker and an indicator of poor prognosis. CENPO may regulate HCC development by influencing nuclear division and tumor immune infiltration and is regulated by methylation, making it a potential target for HCC immunotherapy.
Observational Constraints on the Completeness of Space near Astrophysical Objects

We consider the observational effects of a deficit angle, $w$, in the topology of the solar system and in the ``double pulsar'' system PSR J0737-3039A/B. Using observations of the perihelion precession of Mercury, and the gravitational deflection of light due to the Sun, we constrain the magnitude of such a deficit angle in the solar system to be $2\ensuremath{\pi}(1\ensuremath{-}w)$, with $0\ensuremath{\le}(1\ensuremath{-}w)l{10}^{\ensuremath{-}9}$ at 95% confidence. We calculate the effects of a deficit angle on the periastron advance, geodetic precession rate and inclination angle of the double pulsar system and use the observational data to obtain the constraint $0\ensuremath{\le}(1\ensuremath{-}w)l2.4\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}8}$ at 95% confidence. Although this result is weaker than the solar system bound, it is in a very different physical environment, where accumulating data is likely to lead to tighter constraints in the future.
Still Deluded by Artifices? The Role of the Common European Framework of Reference in Facilitating Test Score Interpretation

The introduction of the CEFR was welcomed by researchers and practitioners in language education, given its potential for increasing transparency of test results and the meaningfulness of test scores. In this paper, I reflect on Glenn Fulcher’s (2004, 2016) critical take on the use of the CEFR in the context of mapping (linking or aligning) test scores to the CEFR proficiency levels and the implications for score interpretation and use. I argue that although mapping test scores to the CEFR levels can enhance score interpretation, the field of language assessment needs to address misinterpretations of score mapping as sufficient evidence of quality of test design or comparability of scores of different tests.
Intelligent packaging design and research based on big data image processing

Abstract. As people’s living standards become higher and higher, people’s requirements for commodities and packaging also become higher and higher. The traditional single packaging can no longer meet the consumer demand of the public. The traditional packaging not only wastes resources but also has single functions. Therefore, this paper proposes an intelligent packaging design. This paper aims to study how to research intelligent packaging design based on big data (BD) image processing. This paper proposes the relevant theoretical knowledge of BD image processing, intelligent packaging design, and the importance of both. The experimental results of this paper show that the development of traditional packaging has been constrained in recent years, from the usage rate of about 80% at the beginning to the usage rate of about 20% later. The utilization rate of smart packaging has risen from about 16% at the beginning to the highest utilization rate of about 83%. It can be seen that smart packaging meets people’s consumption needs. Smart packaging not only has various styles but also has many more functions than traditional packaging and has become more environmentally friendly, which also greatly reduces environmental pollution. Therefore, it is necessary to analyze the intelligent packaging design based on BD image processing in this paper.
Four-manifolds with positive isotropic curvature

1. Positive Isotropic Curvature 2 (1) The Result 2 (2) The Algebra of Isotropic Curvature 4 2. Curvature Pinching 6 (1) Pinching Estimates which are Preserved 6 (2) Pinching Estimates which Improve 13 (3) Necklike Curvature Pinching 21 3. The Geometry of Necks 27 (1) Harmonic Parametrizations by Spheres 27 (2) Geometric Necks 30 (3) Curvature Necks 35 (4) The Fundamental Group 41 (5) Finding Necks 44 4. Surgery 47 (1) How to do Surgery 47 (2) Curvature Changes under Surgery . 49 (3) Pinching Estimates under Surgery 57 5. Recovering the Manifold from Surgery , 60 Research supported by NSF grant # DMS92-04336
A Method for Estimating a Distance Using the Stereo Zoom Lens Module

A method of estimating the distance using single zoom camera limits a distance range(only optical axis) in field of view. So, in this paper, we propose a method of estimating the distance information in Stereoscopic display using the stereo zoom lens module for estimating the distance in the wide range. The binocular stereo zoom lens system is composed using a horizontal moving camera module. The left and right images are acquired in polarized stereo monitor for getting the conversion and estimating a distance. The error distance is under 10mm which has difference between optically a traced distance and an estimated distance in left and right range at center. This presents the system using a function of the zoom and conversion has more precise distance information than that of conversion control. Also, a method of estimating a distance from horizontal moving camera is more precise value than that from toe-in camera by comparing the error distance of the two camera methods.
Analysis of Symmetric Two and Four-coil Magnetic Resonant Coupling Wireless Power Transfer

This study examined the efficiency of power transfer for two-coil and four-coil spiral magnetic resonant coupling wireless power transfer (WPT) using distance to coil diameter (D/dm) ratio and reflection coefficient, S21 value. Adding resonators reduced the total resistance in the two-coil WPT system while increasing the S21 values of the whole system. A same-size spiral coil was proposed for the system and simulated using computer simulation technology (CST). A prototype with similar specifications for a four-coil design was implemented for verification. The proposed method yielded an optimal efficiency of 76.3% in the four-coil system, while the two-coil WPT yielded a 23.2% efficiency with a 1.33 D/dm ratio.
Adoption of Technological Change in the Public Sector: Evidence From US States

Our paper explores the broad influences that stimulate technological change in governmental service delivery. Using panel data by state, we examine whether residents are able to apply for Unemployment Insurance (UI) benefits via technology services such as the internet or automated telephone, or are required to apply in person. The reduced form model tests for the relative influence of residential demand, political pressure, and bureaucratic influence. We find that it is the dispersion of the urban population across a state that provides the impetus for government adoption of new technology, in stark contrast to the importance of urban concentration found for the private sector. A unique additional influence we test is the ability of the entrenched bureaucracy to impede technology options. We find that governors of either political party in their term-limited term—when compromise with bureaucrats is less important—save 4% in administrative costs. We find that technology adoption can be delayed but not prevented by bureaucratic interests.
Attention‐based convolutional neural network deep learning approach for robust malware classification

Recently, transforming windows files into images and its analysis using machine learning and deep learning have been considered as a state‐of‐the art works for malware detection and classification. This is mainly due to the fact that image‐based malware detection and classification is platform independent, and the recent surge of success of deep learning model performance in image classification. Literature survey shows that convolutional neural network (CNN) deep learning methods are successfully employed for image‐based windows malware classification. However, the malwares were embedded in a tiny portion in the overall image representation. Identifying and locating these affected tiny portions is important to achieve a good malware classification accuracy. In this work, a multi‐headed attention based approach is integrated to a CNN to locate and identify the tiny infected regions in the overall image. A detailed investigation and analysis of the proposed method was done on a malware image dataset. The performance of the proposed multi‐headed attention‐based CNN approach was compared with various non‐attention‐CNN‐based approaches on various data splits of training and testing malware image benchmark dataset. In all the data‐splits, the attention‐based CNN method outperformed non‐attention‐based CNN methods while ensuring computational efficiency. Most importantly, most of the methods show consistent performance on all the data splits of training and testing and that illuminates multi‐headed attention with CNN model's generalizability to perform on the diverse datasets. With less number of trainable parameters, the proposed method has achieved an accuracy of 99% to classify the 25 malware families and performed better than the existing non‐attention based methods. The proposed method can be applied on any operating system and it has the capability to detect packed malware, metamorphic malware, obfuscated malware, malware family variants, and polymorphic malware. In addition, the proposed method is malware file agnostic and avoids usual methods such as disassembly, de‐compiling, de‐obfuscation, or execution of the malware binary in a virtual environment in detecting malware and classifying malware into their malware family.
Maternal History of Childhood Maltreatment and Brain Responses to Infant Cues Across the Postpartum Period

Adults with histories of childhood maltreatment (CM) are more likely to display problematic parenting behaviors. The goal of this study was to examine changes in maternal brain activation to negative infant cues over the early postpartum period among new mothers with and without histories of CM, as this is a period of immense neuroplasticity in the maternal brain. CM was measured using the Adverse Childhood Experiences Scale. Functional magnetic resonance imaging (fMRI) conducted at approximately 5 and 13 weeks postpartum measured brain responses to own and unfamiliar infant cues in primiparous women. Women with histories of CM displayed increasing activation in the anterior cingulate cortex, and greater increases in anterior cingulate cortex activation was associated with maternal reports of less regulatory capacity in their infants. Preliminary results suggest that new mothers with CM histories display greater brain responses to negative infant cues compared to new mothers without CM histories. Women with CM histories may benefit from additional supports during the transition to parenthood.