Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of the Genus of Surfaces from the Spectrum of Schr\"odinger Operators attached to height functions. (An inverse spectral problem for surfaces)

Using results on inverse spectral problems, in particular the so-called new wave invariants attached to a classical equilibrium, we show that it is possible to determine the Morse index of height functions. For compact Riemannian surfaces $M\subset \mathbb{R}^3$ this imply that we can retrieve the topology (via the genus). Our results are independent from the choice of a metric on $M$ and can be obtained from the choice of a 'generic' height-function. For surfaces of genus zero, diffeomorphic to a 2-sphere, the method allows to detect the convexity, or the local convexity of the surface. Keywords : Micro-local analysis; Schr\"odinger operators; Inverse spectral problems.
Knot surgery and Scharlemann manifolds

Abstract. We discuss the relation between Fintushel–Stern knot surgery operation on 4-manifolds and “Scharlemann manifolds”, and as a corollary show that they all are standard. Along the way we show the fishtail can exotically knot in S4 infinitely many ways.
Design of Cylindrical Surrounding Double-Gate MOSFET With Fabrication Steps Using a Layer-by-Layer Approach

The semiconductors with nanometer-scale are subjected to various patterns and scaling using the latest technology. The most widely used methods are top-down approaches in the design of complex heterostructures. The top-down approach involves the photolithography to ion sequentially beaming of the materials. In this context, the alternative layer-by-layer approach with cylindrical structures has been discussed and supported by the subsequent results to make Cylindrical Surrounding Double-Gate (CSDG) MOSFETs in this research work. This method involves the making of cylindrical structures with high-resolution morphological structures of CSDG MOSFETs. The process has been described in detail to design the CSDG MOSFETs with high-ƙ dielectric materials to make them suitable for low-frequency RF applications. The fast modulation of the Single Nano Wire (SNW) has been adopted for complex heterostructure modeling. The high-ƙ dielectric materials are placed in between the spacer and the gate material to overcome the Short Channel Effects (SCEs). This method produces symmetrical and concentric cylindrical structures of the CSDG MOSFETs with suitable layers. The minimum layer thickness achieved is about 10 nm axial length along with the core of the SNW. This gives enough insight for the proposed cylindrical structure to fabricate over the core of 2DEG. In this type of structure development, many cylindrical structures with various properties can be designed. The parameters focused on the cylindrical structure will be periodic, non-periodic, symmetric, asymmetric structures, and gaps/dots of nanometer scale. This innovative method introduces the method of designing the symmetric CSDG MOSFET concerning the center core. In this work, the authors focus on the suitable novel technique of designing cylindrical structures with unique dimensions and physical properties using various semiconductor materials.
Reconstruction of constitutive parameters in isotropic linear elasticity from noisy full-field measurements

Within the framework of linear elasticity we assume the availability of internal full-field measurements of the continuum deformations of a non-homogeneous isotropic solid. The aim is the quantitative reconstruction of the associated moduli. A simple gradient system for the sought constitutive parameters is derived algebraically from the momentum equation, whose coefficients are expressed in terms of the measured displacement fields and their spatial derivatives. Direct integration of this system is discussed to finally demonstrate the inexpediency of such an approach when dealing with noisy data. Upon using polluted measurements, an alternative variational formulation is deployed to invert for the physical parameters. Analysis of this latter inversion procedure provides existence and uniqueness results while the reconstruction stability with respect to the measurements is investigated. As the inversion procedure requires differentiating the measurements twice, a numerical differentiation scheme based on an ad hoc regularization then allows an optimally stable reconstruction of the sought moduli. Numerical results are included to illustrate and assess the performance of the overall approach.
ALGORITHM FOR PLANNING FASTER ROUTES IN URBAN NETWORKS WITH TIME-DEPENDENT ARCS AND THE POSSIBILITY OF INTRODUCING WAITING PERIODS AT NODES

Navigation systems implemented in mobile devices allow users to search for the shortest routes between pairs of points. Many of the existing commercial products assume in a simplified way that the travel time to cross each arc of a road network is fixed, once a starting time has been established. However, the real travel time along a road section within cities depends on many factors that are related to traffic congestion, weather conditions, possible incidents, etc., and consequently, it depends on the time. As can easily be shown, determining the shortest itineraries in a network whose arcs are time-dependent can result in a diversity of optimal routes for a same origin–destination pair based on different departure times. Assuming the availability of the estimated data of the time required to travel along each section of the street network, once the departure time has been previously set, we propose in this work an efficient algorithm for obtaining faster routes on time-dependent arcs, in such a way that the sum of driving times is minimized, which in parallel allows improving fuel consumption and reducing associated polluting emissions. The possibility of introducing waiting periods in the nodes to optimize the total time spent on the trip has also been considered in the design of the proposed procedure. An experimental evaluation is carried out to show the effectiveness of the provided algorithm.
Modified Adaptive Filter Based UPQC for Battery Supported Hydro Driven PMSG System

The standalone three phase system for power quality (PQ) improvement of both the load side voltages as well as the currents of the machine terminal is presented in this article. This standalone system consists of a three-phase permanent magnet synchronous generator (PMSG) driven by governor-less hydro turbine as a three-phase source feeding the sensitive/nonlinear/linear loads, connected via a unified power quality conditioner (UPQC). The UPQC consists of a back-to-back connected voltage source converters (VSCs) sharing a common dc bus. The series compensator of the UPQC is used to eliminate voltage PQ and to maintain the sinusoidal, balanced, and constant amplitude voltages at load terminals irrespective of any variation in the system. Moreover, the current quality, such as reactive power compensation, and harmonics elimination, are provided by the shunt compensator of the UPQC, simultaneously while improving voltage quality issues. In addition, the efficiency of the overall system is significantly improved by running the generator below its rated voltage and reduces the losses by operating at unity pf. The system frequency and the generated voltage magnitudes are maintained during any load fluctuation or imbalance loading. The model of the UPQC-based hydro turbine driven PMSG system is developed in the Simulink-MATLAB environment, and its results are presented for analysis. The validation of the system is also done on the hardware prototype, and it performs effectively for the voltage and current PQ enhancement simultaneously. It significantly improves the PQs at the generator terminals and ensures to adhere the IEC-61727 and the IEEE-519 standards even with either balanced or unbalanced loads.
Higher Quantum Theory

We propose a 2-categorical formalism for describing classical information, quantum systems, and their interactions, based on the principle that classical information can be encoded as correlations between quantum systems. Applying this in the 2-category of 2-Hilbert spaces recovers ordinary quantum theory. The formalism gives a simple, graphical way to describe the specification and implementation of certain quantum procedures, which we use to investigate quantum teleportation, dense coding, complementarity and quantum erasure, verifying our results computationally using a software package.
COOH-TERMINALLY ADDED CYSTEINE VARLANT OF THE BETA INTERFERON

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Countable dense homogeneity and the Cantor set

It is shown that CH implies the existence of a compact Hausdorff space that is countable dense homogeneous, crowded and does not contain topological copies of the Cantor set. This contrasts with a previous result by the author which says that for any crowded Hausdorff space $X$ of countable $\pi$-weight, if ${}^\omega{X}$ is countable dense homogeneous, then $X$ must contain a topological copy of the Cantor set.
Existence results and numerical solution for the Dirichlet problem for fully fourth order nonlinear equation

In this paper we study the existence and uniqueness of a solution and propose an iterative method for solving a beam problem which is described by the fully fourth order equation $$u^{(4)}(x)=f(x,u(x),u'(x),u'''(x),u'''(x)), \quad 0 < x < 1$$ associated with the Dirichlet boundary conditions. This problem was studied by several authors. Here we propose a novel approach by the reduction of the problem to an operator equation for the triplet of the nonlinear term $\varphi (x)=f(x,u(x),u'(x),u''(x),u'''(x))$ and the unknown values $u''(0), u''(1). $ Under some easily verified conditions on the function $f$ in a specified bounded domain, we prove the contraction of the operator. This guarantees the existence and uniqueness of a solution and the convergence of an iterative method for finding it. Many examples demonstrate the applicability of the theoretical results and the efficiency of the iterative method. The advantages of the obtained results over those of Agarwal are shown on some examples.
An Intelligent and Social-Oriented Sentiment Analytical Model for Stock Market Prediction using Machine Learning and Big Data Analysis

In an era of machine learning, many fields outside of computer science have implemented machine learning as a tool [5]. In the financial world, a variety of machine learning models are used to predict the future prices of a stock in order to optimize profit. This paper preposes a stock prediction algorithm that focuses on the correlation between the price of a stock and its public sentiments shown on social media [6]. We trained different machine learning algorithms to find the best model at predicting stock prices given its sentiment. And for the public to access this model, a web-based server and a mobile application is created. We used Thunkable, a powerful no code platform, to produce our mobile application [7]. It allows anyone to check the predictions of stocks, helping people with their investment decisions.
Diagnosing Autism Spectrum Disorder Using Ensemble 3D-CNN: A Preliminary Study

Autism spectrum disorder (ASD) is a neuro-developmental disorder that results in behavioural retardation in verbal communications and social interactions. Traditional ASD detection methods involve assessing patients’ behavioural patterns by medical practitioners, which often lack credibility and precision. The contribution of the current study involves a 3D-CNN (convolutional neural network) model to diagnose ASD patients from healthy individuals using functional magnetic resonance imaging (fMRI) of the brain. We utilised a publicly available dataset, Autism Brain Imaging Data Exchange (ABIDE I), and tested different CNN-based models in individual and combined brain parcellations. Our model showed a better outcome (74.53% accuracy, 69.98% sensitivity, and 76.00% specificity) for combined parcellations than individuals. Further, we compared our model with several state-of-the-art models and discussed the suitability of our model for future prospects. The current model would be a predecessor of future prognosis models or behavioural patterns-based multi-modal models for early detection of ASD.
Evolution to a singular measure and two sums of Lyapunov exponents

We consider dissipative dynamical systems represented by a smooth compressible flow in a finite domain. The density evolves according to the continuity (Liouville) equation. For a general, non-degenerate flow the result of the infinite time evolution of an initially smooth density is a singular measure. We give a condition for the non-degeneracy which allows us to decide for a given flow whether the infinite time limit is singular. The condition uses a Green–Kubo-type formula for the space-averaged sum of forward- and backward-in-time Lyapunov exponents. We discuss how the sums determine the fluctuations of the entropy production rate in the SRB state and give examples of computation of the sums for certain velocity fields.
The outburst of the eruptive young star OO Serpentis between 1995 and 2006

Aims. OO Serpentis is a deeply embedded pre-main sequence star in the Serpens NW star-forming region. The star went into outburst in 1995 and gradually faded afterwards. In many respects its eruption resembled the well-known FU Orionis-type (FUor) or EX Lupi-type (EXor) outbursts. Since very few such events have ever been documented at infrared wavelengths, our aim is to study the temporal evolution of 00 Ser in the infrared. Methods. OOSer was monitored with the Infrared Space Observatory in the 3.6-100μm wavelength range, starting 4 months after peak brightness and covering a period of 20 months. Eight years later, in 2004-2006 we again observed OO Ser at 2.2 and 12 μm from the ground and complemented this dataset with archival Spitzer observations also from 2004. We analysed these data with special attention to source confusion and constructed light curves at 10 different wavelengths as well as spectral energy distributions. Results. The outburst caused brightening in the whole infrared regime. According to the infrared light curves, OOSer started a wavelength-independent fading after the peak brightness. Later the flux decay became slower but stayed practically wavelength-independent. The fading is still ongoing, and current fading rates indicate that 00 Ser will not return to quiescent state before 2011. The outburst timescale of OO Ser seems to be shorter than that of FUors, but longer than that of EXors. Conclusions. The outburst timescale and the moderate luminosity suggest that OO Ser is different from both FUors and EXors, and shows some similarities to the recently erupted young star V 1647 Ori. Based on its SED and bolometric temperature, OO Ser seems to be an early class I object, with an age of <10 5 yr. As proposed by outburst models, the object is probably surrounded by an accretion disc and a dense envelope. This picture is also supported by the wavelength-independence of the fading. Due to the shorter outburst timescales, models developed for FUors can only work for OO Ser if the viscosity parameter in the circumstellar disc, α, is set to an order of magnitude higher value than usual for FUors.
Relativistic corrections to the Moyal-Weyl spacetime

We use the framework of quantum field theory to obtain by deformation the Moyal-Weyl spacetime. This idea is extracted from recent progress in deformation theory concerning the emergence of the quantum plane of the Landau-quantization. The quantum field theoretical emerging spacetime is not equal to the standard Moyal-Weyl plane, but terms resembling relativistic corrections occur.
Deep Active Learning for Pornography Recognition Using ResNet

The demand for nudity and pornographic content detection is increasing due to the prevalence of media products containing sexually explicit content with Internet being the main source. Recent literature has proved the effectiveness of deep learning techniques for adult image and video detection. However, the requirement for a huge dataset with labeled examples poses a restriction in practical use. Several research has shown that training deep models using an active learning framework could reduce the annotation effort, but this approach has yet to be applied for pornography detection. In this paper, the classification efficiency and annotation requirement of fine-tuned ResNet50V2 model trained using an active learning framework in pornographic image recognition was explored by comparing the method’s performance using three sampling strategies (random sampling, least confidence sampling, and entropy sampling). The baseline for comparison was a fully supervised learning method. The video frames of the public NPDI dataset were utilized to run a 5-fold cross-validation. The results of the experiments demonstrated that similar average test accuracy of five folds could be obtained using the deep active learning method, with only 60% of labeled samples in the training dataset compared to 100% annotated samples in fully supervised learning.
Interpolation inequalities between Sobolev and Morrey-Campanato spaces: A common gateway to concentration-compactness and Gagliardo-Nirenberg interpolation inequalities

We prove interpolation estimates between Morrey-Campanato spaces and Sobolev spaces. These estimates give in particular concentration-compactness inequalities in the translation-invariant and in the translation- and dilation-invariant case. They also give in particular interpolation estimates between Sobolev spaces and functions of bounded mean oscillation. The proofs rely on Sobolev integral representation formulae and maximal function theory. Fractional Sobolev spaces are also covered.
Finitistic test ideals on numerically $\mathbb{Q}$-Gorenstein varieties

We prove that the finitistic test ideal $\tau_{\rm fg}(R, \Delta, \mathfrak{a}^t)$ coincides with the big test ideal $\tau_{\rm b}(R, \Delta, \mathfrak{a}^t)$ if the pair $(R,\Delta)$ is numerically log $\mathbb{Q}$-Gorenstein.
Geometrically simply connected 4–manifolds
and stable cohomotopy Seiberg–Witten invariants

We show that every positive definite closed 4-manifold with $b_2^+>1$ and without 1-handles has a vanishing stable cohomotopy Seiberg-Witten invariant, and thus admits no symplectic structure. We also show that every closed oriented 4-manifold with $b_2^+\not\equiv 1$ and $b_2^-\not\equiv 1\pmod{4}$ and without 1-handles admits no symplectic structure for at least one orientation of the manifold. In fact, relaxing the 1-handle condition, we prove these results under more general conditions which are much easier to verify.
Cell-Free UAV Networks: Asymptotic Analysis and Deployment Optimization

Recently, cell-free (CF) architectures, in which every user can potentially communicate with every base station, have received a lot of attention. This paper considers the uplink of fully and partially centralized CF networks where unmanned aerial vehicles serve as flying base stations (FBSs). A subset of FBSs participates in the reception of each user and a subset of users is received by each FBS. Deterministic equivalent expressions, exact asymptotically in the subset sizes and approximate for finite dimensions thereof, are derived for the spectral efficiency under Rician fading. Capitalizing on these expressions, the FBS deployment problem is investigated for different receiver architectures. The nonconvex deployment problem, tackled through a combination of gradient-based and Gibbs sampling algorithms, results in a superior performance with respect to a square grid deployment; this superiority extends to the minimum and aggregate spectral efficiency for both fully and partially centralized cell-free networks.
Efficient Hardware Implementation of CORDIC-Based Symbol Detector for GSM MIMO Systems: Algorithm and Hardware Architecture

Aiming at providing an efficient hardware architecture for generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems, in this paper a COordinate Rotation DIgital Computer (CORDIC) -based symbol detector is proposed. In the proposed detector, several CORDIC-based Givens rotation modules are conducted in parallel for the transmit antenna combinations (TACs) to facilitate QR-decomposition. After that, the proposed detector uses adders, shifters, and backward substitution mechanisms to currently estimate symbols for the corresponding TAC. At last, the estimated symbols and corresponding TAC index with the smallest distance measurement are chosen as the final solution. In particular, to achieve efficient hardware implementation, the architecture of the proposed detector has several features, including multiplication-free ranking mechanism, parallel CORDIC-based architectures, and shorter-bit-length multipliers. In addition, the overall architecture is pipelined to speed up the processing of the hardware. At last, computer simulations and hardware implementation are conducted under the configuration of four transmit, two active transmit, and four receive antennas. Simulation results reveal the proposed detector performs near to the optimal maximum likelihood (ML), but uses lower computational complexity. Additionally, the VLSI implementation results under the TSMC 90-nm CMOS technology show that the proposed hardware architecture requires 266K gates (KGEs), provides detection throughput 2.008 Gbps, works with pre-processing latency of 47 clock cycles, and has the hardware efficiency 7.54 (Mbps/KGEs) while operating at frequency 200.8 MHz. Moreover, implementation comparisons show the proposed architecture provides high throughput rate as well as hardware efficiency, and works with low pre-processing latency.