Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Lattice and Process-Stress Responses in the Sub-7 nm Germanium-Based Three-Dimensional Transistor Architecture of FinFET and Nanowire GAAFET

The comprehensive layout-dependence lattice and process-stress variations and induced mobility gain in sub-7 nm germanium (Ge)-based Fin-type field-effect transistors (FinFETs) and gate-all-around (GAA) nanowire (NW)-type FETs are investigated through process-oriented stress simulation with lattice generated from strain-relaxed buffer (SRB) and source-drain (S-D) region. Analysis results reveal that the local lattice stressors mentioned above are the dominant stress resources in sub-7 nm FinFET and GAA transistor architectures. For FinFET architecture, the mobility performance is highly linearly proportional to the S-D length, and 49.01% and 105.96% gains are observed when S-D lengths of 5 and 50 nm are designed, respectively. To achieve simultaneous maximum integration density and effective performance enhancement of the three-dimensional transistor of concern, the design roles of narrow stacked pitch and channel length are explored. The maximum mobility enhancements are determined to be 231.89% and 288.90% for the Ge n- and p-type GAAFET analyzed herein, respectively.
Energy-Efficient Power Control for Simultaneous Wireless Information and Power Transfer—Nonorthogonal Multiple Access in Distributed Antenna Systems

A simultaneous wireless information and power transfer (SWIPT)-enabled nonorthogonal multiple access (NOMA) system has been recognized as a promising technology for enabling the Industrial Internet of Things (IIoT), as it extends the lifetime of small battery-driven sensors. However, its energy efficiency significantly decreases with distance from the central controller. This article proposes a framework for applying SWIPT-aided NOMA system to a distributed antenna system (DAS) to improve the spectral efficiency and energy efficiency of the IIoT. Moreover, we jointly optimize the power allocation for the NOMA signaling and power splitting for SWIPT in the DAS to maximize energy efficiency while reaching the minimum harvested energy and data rate requirements. Owing to the nonconvexity of the joint optimization problem, we divide the optimization problem into subproblems and present an iterative algorithm for finding the optimal solution. To verify the effectiveness of the proposed method, extensive simulation results are presented, and we show improvements in energy efficiency relative to conventional schemes. Particularly, the proposed SWIPT-NOMA-DAS system provides energy efficiency of more than five times that of SWIPT-NOMA without DAS, and more than 10% improvement compared with SWIPT-OMA-DAS.
Vector-valued Eisenstein series of small weight

We study the (mock) Eisenstein series [Formula: see text] of weight [Formula: see text] for the Weil representation on an even lattice, defined as the result of Bruinier and Kuss’s coefficient formula for the Eisenstein series naively evaluated at [Formula: see text]. We describe the transformation law of [Formula: see text] in general. Most of this paper is dedicated to collecting examples where the coefficients of [Formula: see text] contain interesting arithmetic information. Finally, we make a few remarks about the case [Formula: see text].
OCT Meets micro-CT: A Subject-Specific Correlative Multimodal Imaging Workflow for Early Chick Heart Development Modeling

Structural and Doppler velocity data collected from optical coherence tomography have already provided crucial insights into cardiac morphogenesis. X-ray microtomography and other ex vivo methods have elucidated structural details of developing hearts. However, by itself, no single imaging modality can provide comprehensive information allowing to fully decipher the inner workings of an entire developing organ. Hence, we introduce a specimen-specific correlative multimodal imaging workflow combining OCT and micro-CT imaging which is applicable for modeling of early chick heart development—a valuable model organism in cardiovascular development research. The image acquisition and processing employ common reagents, lab-based micro-CT imaging, and software that is free for academic use. Our goal is to provide a step-by-step guide on how to implement this workflow and to demonstrate why those two modalities together have the potential to provide new insight into normal cardiac development and heart malformations leading to congenital heart disease.
GIANT GALAXIES, DWARFS, AND DEBRIS SURVEY. I. DWARF GALAXIES AND TIDAL FEATURES AROUND NGC 7331

The Giant GAlaxies, Dwarfs, and Debris Survey (GGADDS) concentrates on the nearby universe to study how galaxies have interacted in groups of different morphology, density, and richness. In these groups, we select the dominant spiral galaxy and search its surroundings for dwarf galaxies and tidal interactions. This paper presents the first results from deep wide-field imaging of NGC 7331, where we detect only four low-luminosity candidate dwarf companions and a stellar stream that may be evidence of a past tidal interaction. The dwarf galaxy candidates have surface brightnesses of μr ≈ 23–25 mag arcsec−2 with (g − r)0 colors of 0.57–0.75 mag in the Sloan Digital Sky Survey filter system, consistent with their being dwarf spheroidal (dSph) galaxies. A faint stellar stream structure on the western edge of NGC 7331 has μg ≈ 27 mag arcsec−2 and a relatively blue color of (g − r)0 = 0.15 mag. If it is tidal debris, then this stream could have formed from a rare type of interaction between NGC 7331 and a dwarf irregular or transition-type dwarf galaxy. We compare the structure and local environments of NGC 7331 to those of other nearby giant spirals in small galaxy groups. NGC 7331 has a much lower (∼2%) stellar mass in the form of early-type satellites than found for M31 and lacks the presence of nearby companions like luminous dwarf elliptical galaxies or the Magellanic Clouds. However, our detection of a few dSph candidates suggests that it is not deficient in low-luminosity satellites.
Performance Analysis of Anode-Supported Solid Oxide Fuel Cells: A Machine Learning Approach

Prior to the long-term utilization of solid oxide fuel cell (SOFC), one of the most remarkable electrochemical energy conversion devices, a variety of difficult experimental validation procedures is required, so it would be time-consuming and steep to predict the applicability of these devices in the future. For numerous years, extensive efforts have been made to develop mathematical models to predict the effects of various characteristics of solid oxide fuel cells (SOFCs) components on their performance (e.g., voltage). Taking advantage of the machine learning (ML) method, however, some issues caused by assumptions and calculation costs in mathematical modeling could be alleviated. This paper presents a machine learning approach to predict the anode-supported SOFCs performance as one of the most promising types of SOFCs based on architectural and operational variables. Accordingly, a dataset was collected from a study about the effects of cell parameters on the output voltage of a Ni-YSZ anode-supported cell. Convolutional machine learning models and multilayer perceptron neural networks were implemented to predict the current-voltage dependency. The resulting neural network model could properly predict, with more than 0.998 R2 score, a mean squared error of 9.6 × 10−5, and mean absolute error of 6 × 10−3 (V). Conventional models such as the Gaussian process as one of the most powerful models exhibits a prediction accuracy of 0.996 R2 score, 10−4 mean squared, and 6 × 10−3 (V) absolute error. The results showed that the built neural network could predict the effect of cell parameters on current-voltage dependency more accurately than previous mathematical and artificial neural network models. It is noteworthy that this procedure used in this study is general and can be easily applied to other materials datasets.
Black hole horizons from within loop quantum gravity

In general relativity, the fields on a black hole horizon are obtained from those in the bulk by pullback and restriction. Similarly, in quantum gravity, the quantized horizon degrees of freedom should result from restricting, or pulling-back, the quantized bulk degrees of freedom. This is not yet fully realized in the - otherwise very successful - quantization of isolated horizons in loop quantum gravity. In this work we outline a setting in which the quantum horizon degrees of freedom are simply components of the quantized bulk degrees of freedom. There is no need to quantize them separately. We present evidence that for a horizon of sphere topology, the resulting horizon theory is remarkably similar to what has been found before.
Transcriptome Analysis Revealed Genes Related to γ-Irradiation Induced Emergence Failure in Third-Instar Larvae of Bactrocera dorsalis

Simple Summary Bactrocera dorsalis (Diptera: Tephritidae) is a severe insect pest of numerous fruits and crops worldwide. Using the Illumina Hiseq 2000 platform, we generated a comprehensive transcriptome of B. dorsalis in response to radiation. The adult of B. dorsalis could not emerge when third-instar larvae were irradiated with 60Co-γ at 116Gy. Most differentially expressed genes (DEGs) in gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEEG) in enrichment studies were involved in hemolymph coagulation and digestive processes, such as protein digestion and absorption, while pancreatic secretion may be linked to the response to irradiation. Furthermore, the differential expressions of up/down regulated unigenes were confirmed by quantitative reverse transcription-PCR (qRT-PCR). The downregulation of sqd may contribute to the failure of emergence in irradiated samples, while the up-regulation of ENPEP and Ugt are involved in metabolic pathways, and their up-regulation may be considered the results of the irradiation stress reaction. Overall, the current study is a useful resource for the identification of potentially useful biochemical markers that can be used in quarantine. Abstract The oriental fruit fly is a polyphagous and highly invasive economically important pest in the world. We proposed the hypothesis that radiation treatment influence RNA expression in the larvae and leads to emergence failure. Therefore, transcriptome analyses of third-instar larvae of B. dorsalis ionizing, irradiated with 60Co-γ at 116Gy, were conducted and compared with the controls; a total of 608 DEGs were identified, including 348 up-regulated genes and 260 down-regulated ones. In addition, 130 SNPs in 125 unigenes were identified. For the DEGs, the most significantly enriched GO item was hemolymph coagulation, and some of the enriched pathways were involved in digestive processes. The subsequent validation experiment confirmed the differential expression of six genes, including sqd, ENPEP, Jhe, mth, Notch, and Ugt. Additionally, the 3401:G->A SNP in the Notch gene was also successfully validated. According to previous research, this was the first comparative transcriptome study to discover the candidate genes involved in insect molt to pupae. These results not only deepen our understanding of the emerging mechanism of B. dorsalis but also provide new insights into the research of biomarkers for quarantine insect treatment with the appropriate dose of radiation.
IoT-Based Federated Learning Model for Hypertensive Retinopathy Lesions Classification

Traditional classification algorithms struggle to categorize hypertensive retinopathy (HR) lesions correctly because they lack obvious characteristics. A regional IoT-enabled federated learning-based HR categorization approach (IoT-FHR) incorporating global and local attributes is suggested as a solution to this issue. The local feature arterial and venous nicking (AVN) classification model is fused with the overall IoT-FHR classification model to enhance the effect of the classification of IoT-FHR. The AVN classification model’s local lesion characteristics and the IoT-FHR classification model’s global lesion characteristics were combined using feature mean. After that, the results of the global IoT-FHR classification model are averaged with the results of the local AVN classification model. An easy neural network receives its input from the final outcome. The probability value of IoT-FHR in the fundus image is output by the sigmoid classifier after the neural network’s two fully connected and one dropout layer. The AVN classification makes a new kind of intersection detection algorithm suggestion. To determine the intersection points, the algorithm applies a logical AND operation to the classified arteries and veins. It takes HR fundus pictures and extracts AVN image blocks using the region of interest extraction approach. The accuracy, sensitivity, and specificity of the suggested fusion model are 93.50%, 69.83%, and 98.33%, respectively, when tested on a private dataset. It is clear from the experiments and results that the suggested model leads the currently used methods when the single-stage classification model is compared with them.
The Relation Between Helicopter Parenting and Satisfaction with Life in Emerging Adults Living with Their Parents: The Moderating Role of Gender and Age Group

Objective. Over the last couple of decades, a trend of emerging adults living with parents has been rising. However, little is known about the developmental specificities and impact of parenting practices in this context. The objectives of this study were: to compare the levels of helicopter parenting and the levels of life satisfaction by gender (men versus women) and by age group (late adolescents versus young adults); to analyze the relationship between helicopter parenting, life satisfaction levels and age; and to investigate the moderating role of gender and age group in the relationship between helicopter parenting and life satisfaction.Materials and Methods. Self-report questionnaires were administered to a sample of 173 emerging adults (aged 18-29) living with their parents in Portugal. In order to examine differences in helicopter parenting and levels of life satisfaction, Student’s ttest was performed for independent samples. To analyze the association between helicopter parenting, life satisfaction and age, Pearson’s correlation coefficients were calculated. To detect possible interaction effects, regression-based analyses were performed; the SPSS macro PROCESS was used to optimize this procedure.Results. Life satisfaction levels differed according to age group, with late adolescents reporting higher levels of life satisfaction than young adults. Helicopter parenting was negatively correlated with life satisfaction, and life satisfaction was negatively correlated with age. The developmental variables of gender and age group moderated the association between helicopter parenting and life satisfaction.Conclusions. Interventions with emerging adults that aim to prevent the negative effects of helicopter parenting and increase life satisfaction must account for the developmental specificities associated with gender roles and different age groups.Key Words: Emerging Adulthood ■ Cohabitation ■ Helicopter Parenting ■ Life Satisfaction
Stability and Hermitian-Einstein metrics for vector bundles on framed manifolds

We adapt the notions of stability of holomorphic vector bundles in the sense of Mumford-Takemoto and Hermitian-Einstein metrics in holomorphic vector bundles for canonically polarized framed manifolds, i.e. compact complex manifolds X together with a smooth divisor D such that K_X \otimes [D] is ample. It turns out that the degree of a torsion-free coherent sheaf on X with respect to the polarization K_X \otimes [D] coincides with the degree with respect to the complete K\"ahler-Einstein metric g_{X \setminus D} on X \setminus D. For stable holomorphic vector bundles, we prove the existence of a Hermitian-Einstein metric with respect to g_{X \setminus D} and also the uniqueness in an adapted sense.
Efficient Biometric Identification on the Cloud With Privacy Preservation Guarantee

Benefited from its reliability and convenience, biometric identification has become one of the most popular authentication technologies. Due to the sensitivity of biometric data, various privacy-preserving biometric identification protocols have been proposed. However, the low computational efficiency or the security vulnerabilities of these protocols limit their wide deployment in practice. To further improve the efficiency and enhance the security, in this paper, we propose two new privacy-preserving biometric identification outsourcing protocols. One mainly utilizes the efficient Householder transformation and permutation technique to realize the high-efficiency intention under the known candidate attack model. The other initializes a novel random split technique and combines it with the invertible linear transformation to achieve a higher security requirement under the known-plaintext attack model. Also, we argue the security of our proposed two protocols with a strict theoretical analysis and, by comparing them with the prior existing works, comprehensively evaluate their efficiency.
A geometric entropy detecting the Erdös-Rényi phase transition

We propose a method to associate a differentiable Riemannian manifold to a generic many-degrees-of-freedom discrete system which is not described by a Hamiltonian function. Then, in analogy with classical statistical mechanics, we introduce an entropy as the logarithm of the volume of the manifold. The geometric entropy so defined is able to detect a paradigmatic phase transition occurring in random graphs theory: the appearance of the “giant component” according to the Erdös-Rényi theorem.
Cohomology jump loci of differential graded Lie algebras

To study infinitesimal deformation problems with cohomology constraints, we introduce and study cohomology jump functors for differential graded Lie algebra (DGLA) pairs. We apply this to local systems, vector bundles, Higgs bundles, and representations of fundamental groups. The results obtained describe the analytic germs of the cohomology jump loci inside the corresponding moduli space, extending previous results of Goldman–Millson, Green–Lazarsfeld, Nadel, Simpson, Dimca–Papadima, and of the second author.
Maximal regularity in exponentially weighted Lebesgue spaces of the Stokes operator in unbounded cylinders

Abstract We study resolvent estimates and maximal regularity of the Stokes operator in Lq-spaces with exponential weights in the axial directions of unbounded cylinders of ℝn, n ≥ 3. For a straight cylinder we use exponential weights in the axial direction and Muckenhoupt weights in the cross-section. Next, for cylinders with several exits to infinity we prove that the Stokes operator in Lq-spaces with exponential weights generates an exponentially decaying analytic semigroup and has maximal regularity. The proof for straight cylinders uses an operator-valued Fourier multiplier theorem and unconditional Schauder decompositions based on the ℛ-boundedness of the family of solution operators for a system in the cross-section of the cylinder parametrized by the phase variable of the one-dimensional partial Fourier transform. For general cylinders we use cut-off techniques based on the result for straight cylinders and the case without exponential weight.
Detecting asymptotic non-regular values by polar curves

We locate the Malgrange non-regular values of a given polynomial function $f:\bC^n \to \bC$ by using a series of affine polar curves. We moreover show that all non-trivial Malgrange non-regular values of $f$ are indicated by a single "super-polar curve" which we introduce here, providing also an effective algorithm of detection.
Stochastic Metamorphosis in Imaging Science

In the pattern matching approach to imaging science, the process of \emph{metamorphosis} in template matching with dynamical templates was introduced in \cite{ty05b}. In \cite{HoTrYo2009} the metamorphosis equations of \cite{ty05b} were recast into the Euler-Poincar\'e variational framework of \cite{HoMaRa1998} and shown to contain the equations for a perfect complex fluid \cite{Holm2002}. This result related the data structure underlying the process of metamorphosis in image matching to the physical concept of order parameter in the theory of complex fluids \cite{GBHR2013}. In particular, it cast the concept of Lagrangian paths in imaging science as deterministically evolving curves in the space of diffeomorphisms acting on image data structure, expressed in Eulerian space. (In contrast, the landmarks in the standard LDDMM approach are Lagrangian.) For the sake of introducing an Eulerian uncertainty quantification approach in imaging science, we extend the method of metamorphosis to apply to image matching along \emph{stochastically} evolving time dependent curves on the space of diffeomorphisms. The approach will be guided by recent progress in developing stochastic Lie transport models for uncertainty quantification in fluid dynamics in \cite{holm2015variational,CrFlHo2017}.
Boundedness of the solutions to non-linear systems with Morrey data

ABSTRACT We consider non-linear elliptic systems satisfying componentwise coercivity condition. The non-linear terms have controlled growths with respect to the solution and its gradient, while the behaviour in x is governed by functions in Morrey spaces. We firstly prove essential boundedness of the weak solution and then we obtain Morrey regularity of its gradient.
Quadratic interpolation of the Heinz means

The main goal of this article is to present several quadratic refinements and reverses of the well known Heinz inequality, for numbers and matrices, where the refining term is a quadratic function in the mean parameters. The proposed idea introduces a new approach to these inequalities, where polynomial interpolation of the Heinz function plays a major role. As a consequence, we obtain a new proof of the celebrated Heron-Heinz inequality proved by Bhatia, then we study an optimization problem to find the best possible refinement. As applications, we present matrix versions including unitarily invariant norms, trace and determinant versions.
Large fluctuations of radiation in stochastically activated two-level systems

We study large fluctuations of emitted radiation in the system of N non-interacting two-level atoms. Two methods are used to calculate the probability of large fluctuations and the time dependence of excitation and emission. The first method is based on the large deviation principle for Markov processes. The second one uses an analogue of the quantum formalism for classical probability problems. Particularly we prove that in a large fluctuation limit approximately half of the atoms are excited. This fact is independent on the fraction of the excited atoms in equilibrium.
On the width of transitive sets: Bounds on matrix coefficients of finite groups

We say that a finite subset of the unit sphere in $\mathbf{R}^d$ is transitive if there is a group of isometries which acts transitively on it. We show that the width of any transitive set is bounded above by a constant times $(\log d)^{-1/2}$. This is a consequence of the following result: If $G$ is a finite group and $\rho : G \rightarrow \mbox{U}_d(\mathbf{C})$ a unitary representation, and if $v \in \mathbf{C}^d$ is a unit vector, there is another unit vector $w \in \mathbf{C}^d$ such that \[ \sup_{g \in G} |\langle \rho(g) v, w \rangle| \leq (1 + c \log d)^{-1/2}. \] These results answer a question of Yufei Zhao.