Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Facade Details on Radio Propagation at 28 GHz

Channel modeling tools, such as ray-tracers, require geometrical information of the environment. Usually, this geometrical information consists of smooth 3D models. These models are obtained by extruding building footprints from commercially available digital maps. However, with the evolution of mobile networks and the use of higher frequencies, small-scale geometric details are becoming increasingly important. This contribution investigates if the typically used Lambertian diffuse scattering model is sufficient to mimic these small-scale geometric variations or if more detailed geometrical models are needed. A raytracing tool is used to simulate the channel with a 3D model of various levels of details. Comparison between simulations and corresponding measurements indicate that typically used diffuse scattering models mimic scattering from facades not well enough. More details, such as windows, should be included in the 3D models or an improved facade scattering model is required to more realistically model the scattering observed from a facade.
Distinguishing Human-Written and ChatGPT-Generated Text Using Machine Learning

The use of sophisticated Artificial Intelligence (AI) language models, including ChatGPT, has led to growing concerns regarding the ability to distinguish between human-written and AI-generated text in academic and scholarly settings. This study seeks to evaluate the effectiveness of machine learning algorithms in differentiating between human-written and AI-generated text. To accomplish this, we collected responses from Computer Science students for both essay and programming assignments. We then trained and evaluated several machine learning models, including Logistic Regression (LR), Decision Trees (DT), Support Vector Machines (SVM), Neural Networks (NN), and Random Forests (RF), based on accuracy, computational efficiency, and confusion matrices. By comparing the performance of these models, we identified the most suitable one for the task at hand. The use of machine learning algorithms for detecting text generated by AI has significant potential for applications in content moderation, plagiarism detection, and quality control for text generation systems, thereby contributing to the preservation of academic integrity in the face of rapidly advancing AI-driven content generation.
Filter-Integrated LCC Compensation for Wireless Charging System

In this paper, filter-integrated LCC compensation is proposed. Since electromagnetic interference (EMI) is one of the issuses of wireless power transfer (WPT) system for electric vehicles (EVs), EMI filters are required for the inverter, which is the source of noise. In this work, a filter-based design of the conventional LCC compensation circuit is first proposed. The compensation circuit of the WPT system operates as a differential mode filter after the cutoff frequency. Second, a method of integrating the EMI filter into the compensation circuit is proposed. The effect of the filter-based LCC compensation circuit was experimentally verified by applying it to the 22kW WPT system.
Customized CNN with Adam and Nadam Optimizers for Emotion Recognition using Facial Expressions

People communicate using one of the communication types of facial expressions to express their emotions. Human feelings are detected through facial expressions to interpret their present state of mood. It stimulates researchers to work in the field of emotion recognition. The design of deep learning models is essential to interpret the human current mind state by capturing the pattern of the facial gesture through their facial expressions. This study proposed a customized Convolutional Neural Network (CNN) with various optimizers Adaptive Moment Estimation (Adam) and Nesterov-accelerated Adaptive Moment Estimation (Nadam) to improve emotion recognition using the dataset FER-2013. The customized proposed model is designed by varying the number of convolution layers, filters, filter sizes, and optimizers. The emotions are recognized using softmax activation in the output layer. The experimental results have proved that the proposed model classified the facial expressions with accuracy of 0.841, 0.826 using Nadam and Adam optimizers respectively.
Ultra-Wideband Air-Filled SIW Cavity-Backed Slot Antenna with Multipolarization Reconfiguration

Air-filled substrate integrated waveguide (AFSIW) cavity-backed slot antenna topologies are promising candidates to address the specific design challenges posed by the Internet of Things (IoT). In this contribution, we demonstrate a new single-feed ultrawideband cavity-backed slot antenna with multipolarization reconfiguration by leveraging four quartets of PIN diodes in substrate-independent AFSIW technology for operation in the [5.15-5.85] GHz frequency band. To achieve ultra-wideband performance, two concentric annular slots are created on the top of the circular cavity. By electrically shorting these annular slots at well-defined positions by the aforementioned PIN diodes, dynamic polarization reconfiguration is achieved by switching their DC bias current. Moreover, a systematic investigation of the different loss contributions and power consumption is performed. A physical explanation of the different effects is also provided. Finally, a fabricated prototype exhibits a measured impedance bandwidth of 1.6 GHz (or 29%), a total efficiency higher than 74%, and a gain higher than 5.2 dBi for all four states in free-space conditions.
On the Comparison between Local and Optimized Approach for the Design of a Beam-Tilting Metasurface

A numerically efficient tool based on the optimization of surface field harmonics for the design of three-layer beam-tilting metasurfaces is compared with a design approach based on a local approximation. In the first approach, a certain number of evanescent Floquet modes are introduced through an optimization procedure aiming at minimizing the real part of the sheets surface impedance. In the second one, the sheet impedance profiles are derived analytically based on the uniform problem that locally matches the structure. The two techniques have been applied to design three different beam-tilting metasurfaces, and the resulting structures have been analyzed with a full-wave code in order to assess and compare their accuracy. Numerical results show the superior performance of the optimization approach with respect to the local approach in terms of capability to design highly-efficient reflectionless wide-angle anomalous beam-tilting metasurfaces.
COVARIANT INTEGRAL QUANTIZATIONS AND THEIR APPLICATIONS TO QUANTUM COSMOLOGY

We present a general formalism for giving a measure space paired with a separable Hilbert space a quantum version based on a normalized positive operator-valued measure. The latter are built from families of density operators labeled by points of the measure space. We especially focus on group representation and probabilistic aspects of these constructions. Simple phase space examples illustrate the procedure: plane (Weyl-Heisenberg symmetry), half-plane (affine symmetry). Interesting applications to quantum cosmology (“smooth bouncing”) for Friedmann-Robertson-Walker metric are presented and those for Bianchi I and IX models are mentioned.
A Miniatured Fully Integrated High Resolution and Accuracy Capacitive Angle Encoder

In this article, a capacitive angle encoder monitored and sensed by application specific integrated circuit (ASIC) with a sensitive structure fabricated by MEMS technology is proposed. The sensitive structure with a 27.5 mm outer diameter is designed and optimized in a limited footprint to realize higher accuracy. After being fabricated by MEMS technology, it is integrated with an ASIC, realizing high fabrication accuracy and a small footprint at the same time. The ASIC is designed in an analog–digital hybrid architecture to achieve low power consumption and a small footprint. The analog part of the ASIC consists of a charge to voltage converter with capacitance cancellation array and a sigma-delta modulator (SDM) with a 3-bit quantizer. In the digital part of ASIC, the processor based on Cortex-M3 core is designed to perform angle calculation. The measurement result of the proposed angle sensor reveals that the power consumption is 250 mW from a single 5-V supply, the bandwidth is over 130 Hz, the resolution is 0.002°, and the accuracy over the full range is 0.024°, indicating that the encoder has considerable potential for use in high-precision applications.
Direct Calculations of One-, Two-, and Three-Dimensional Detonations by the CESE Method

The present paper reports one-, two-, and threedimensional numerical simulation of propagating detonations. We solve the Euler equations for chemically reacting flows with the space-time CESE method. The stiff source terms in the species equations are treated by a volumetric integration over a space-time region as an integral part of the space-time flux conservation. The classical ZND solution is used for code validation as well as the initial condition in the simulations. One-dimensional results include a piston problem and an instability problem. Two-dimensional cases include planar detonation waves and an oblique detonation over a ramp. Three-dimensional results include planar detonations in square ducts of various sizes. For H2/air mixtures at various equivalence ratios, the cell size of the calculated soot trace compares well with experimental data. For the same flow conditions, the cell sizes of two-dimensional calculations are generally 30 to 40% less than that in three-dimensional ones. Moreover, both the amplitude and the frequency of the peak pressures in the calculated three-dimensional detonations are much higher than that in the twodimensional results. Similarly, the frequency and amplitudes of the calculated two-dimensional pressure peaks are higher than that of the galloping one-dimensional detonations. While oneand two-dimensional simulations provide qualitative features of propagating detonations, one has to resort to three-dimensional simulations to obtain realistic flow structures of a detonation wave.
Coordinate System Invariant Formulation of Fractional‐Dimensional Child‐Langmuir Law for a Rough Cathode

This work presents an exact closed‐form analytical model of the space charge limited (SCL) current density for planar, cylindrical, and spherical geometries in fractional dimensional spaces (Fα) where α represents the fractional dimensions having a range 0 < α ⩽ 1. Decreasing value of α shows an increasing degree of surface roughness. This analytical model approaches Langmuir–Blodgett equations for sufficiently close anode (Ra) and cathode (Rc) radii for integer dimensions (α = 1). To calculate SCL current density for any geometry, variational calculus (VC) is used to derive the differential equations in fractional (α) dimensions. The effect of electrode radius ratios on space charge limited current is investigated here considering the surface roughness.
A Modified Trefftz Method for Two-Dimensional Laplace Equation Considering the Domain's Characteristic Length

A newly modified Trefftz method is developed to solve the exterior and interior Dirichlet problems for two-dimensional Laplace equation, which takes the characteristic length of problem domain into account. After introducing a circular artificial boundary which is uniquely determined by the physical problem domain, we can derive a Dirichlet to Dirichlet mapping equa- tion, which is an exact boundary condition. By truncating the Fourier series expansion one can match the physical boundary condition as accu- rate as one desired. Then, we use the colloca- tion method and the Galerkin method to derive linear equations system to determine the Fourier coefficients. Here, the factor of characteristic length ensures that the modified Trefftz method is stable. We use a numerical example to ex- plore why the conventional Trefftz method is fail- ure and the modified onestill survives. Numerical examples with smooth boundaries reveal that the present method can offer very accurate numeri- cal results with absoluteerrors about in the orders from 10 −10 to 10 −16 . The new method is pow- erful even for problems with complex boundary shapes, with discontinuous boundary conditions or with corners on boundary. Keyword: Laplace equation, Artificial bound- ary condition, Modified Trefftz method, Char- acteristic length, Collocation method, Galerkin method, DtD mapping
Cloud-resolving modeling: ARM and the GCSS story

The Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) was created in 1992. As described by Browning et al. (1993, p. 387), ‘‘The focus of GCSS is on cloud systems spanning the mesoscale rather than on individual clouds. Observations from field programs will be used to develop and validate the cloud-resolving models, which in turn will be used as test-beds to develop the parameterizations for the large-scale models. ’’ The most important activities that GCSS promoted were the following:
Sources of stress among Federal Correctional Officers in Canada

Most correctional officers describe their jobs as stressful. The current study advances the scholarship on correctional stress by offering a rare qualitative analysis that identifies, provides meaning, and contextualizes sources of stress in correctional services. This study complements the correctional stress literature, which, until now, has relied primarily on quantitative methodologies to identify and assess stress determinants. Forty-four correctional officers from Canada’s federal prisons were interviewed about their primary source of stress. Findings indicate that staff (i.e., co-workers and managers), not prison residents, represent a primary source of stress in correctional work. In addition, job seniority and gossip were the main stress triggers associated with co-workers, while centralization of decision-making processes and a lack of instrumental communication and support triggered stress coming from managers.
Significance of Cattaneo-Christov Heat Flux on Chemically Reacting Nanofluids Flow Past a Stretching Sheet with Joule Heating Effect

This paper examined the significance of Cattaneo-Christov's theories on the flow of chemically reacting fluid past a stretching surface with thermophysical parameters. The mathematical modelling of the physical problem was represented by partial differential equations. The set of partial differential equations was simplified by employing suitable similarity variables to obtain the system of coupled nonlinear ordinary differential equations. The transformed equations were later solved using the spectral relaxation method. The spectral relaxation method employs the basic concept of the Gauss-Seidel relaxation techniques. The outcome of this method was presented in graphs and tables. The thermal radiation parameter was found to enhance the velocity and temperature distributions. Also, the effect of the magnetic field parameter was found to decline the velocity profile. It was found that the Brownian motion parameter greatly influences the velocity as well as temperature profiles
Attainability Analysis of the DICE Model

The paper is devoted to a development of a method for constructing attainability domains for the DICE model of the economics of global warming. Such domains allow one to observe all possible states of the model, to compare different strategies, and to perform sensitivity and uncertainty analysis. All these make attainability domains an efficient tool for the evaluation of different strategies from the viewpoint of their rationality.
Therapeutic Potential of Dillenia indica L. in Attenuating Hyperglycemia-Induced Oxidative Stress and Apoptosis in Alloxan-Administered Diabetic Mice.

BACKGROUND Hyperglycemia-induced oxidative stress accelerates the process of apoptosis in tissues. Dilleniaindica (DI) is a medicinal plant, and its fruit contains many therapeutic properties. The therapeutic activity of the Methanolic Fruit Extract (MFE) of DI in attenuating oxidative stress and apoptosis in the liver and kidney tissues of alloxan-induced diabetic mice was analyzed in the present study. METHODS High-Performance Thin Layer Chromatography (HPTLC) profiling of MFE was conducted. GLUT4 protein expression analysis and lipid peroxidation assays were conducted to check for MFE effect by administering in diabetic mice. An ultrastructural study was conducted for both the tissues. In apoptotic studies, the TUNEL assay and apoptotic protein expression analysis was conducted. RESULTS High-Performance Thin Layer Chromatography (HPTLC) profiling of MFE showed the presence of two crucial antioxidants, ascorbic acid, and naringenin. In GLUT-4 protein expression analysis, MFE suppresses hyperglycemia by upregulating GLUT4 protein expression. Lipid peroxidation assay showed a decrease in malondialdehyde (MDA) upon MFE administration in diabetic mice. An ultrastructural study was conducted, and MFE was found to restore cellular alterations in diabetic tissues. In apoptotic studies, the TUNEL assay shows that MFE treatment showed fewer apoptotic cells than the diabetic group. The study also observed decreased caspase 3 protein expression and increased Bcl-2 protein expression. CONCLUSIONS Therefore, it is inferred from the study that MFE can exert a protective effect by suppressing hyperglycemia and modulating oxidative stress and apoptosis in alloxan-administered diabetic mice.
Effective Feature Engineering Technique for Heart Disease Prediction With Machine Learning

Heart failure is a chronic disease affecting millions worldwide. An efficient machine learning-based technique is needed to predict heart failure health status early and take necessary actions to overcome this worldwide issue. While medication is the primary treatment, exercise is increasingly recognized as an effective adjunct therapy in managing heart failure. In this study, we developed an approach to enhance heart failure detection based on patient health parameter data involving machine learning. Our study helps improve heart failure detection at its early stages to save patients’ lives. We employed nine machine learning-based algorithms for comparison and proposed a novel Principal Component Heart Failure (PCHF) feature engineering technique to select the most prominent features to enhance performance. We optimized the proposed PCHF mechanism by creating a new feature set as an innovation to achieve the highest accuracy scores. The newly created dataset is based on the eight best-fit features. We conducted extensive experiments to assess the efficiency of several algorithms. The proposed decision tree method outperformed the applied machine learning models and other state-of-the-art studies, achieving a high accuracy score of 100%, which is admirable. All applied methods were successfully validated using the cross-validation technique. Our proposed research study has significant scientific contributions to the medical community.
In vitro photoacoustic sensing of calcium dynamics with arsenazo III

Imaging of cellular electric potential via calcium-ion sensitive contrast agents is a useful tool, but current techniques lack sufficient depth penetration. We explore contrast-enhanced photoacoustic (PA) imaging, using Arsenazo III dye, to visualize cardiac myocyte depolarization in vitro. Phantom results show strong linearity of PA signal with dye concentration (R2 > 0.95), and agree spectrally with extinction measurements with varying calcium concentration. Cell studies indicate a significant (>100-fold) increase in PA signal for dye-treated cells, as well as a 10-fold increase in peak-to-peak variation during a 30 s window. This suggests contrast-enhanced PA imaging may have sufficient sensitivity and specificity for depth-resolved visualization of tissue depolarization in real-time.
An Energy-Efficient Generic Accuracy Configurable Multiplier Based on Block-Level Voltage Overscaling

Voltage Overscaling (VOS) is one of the well-known techniques to increase the energy efficiency of arithmetic units. Also, it can provide significant lifetime improvements, while still meeting the accuracy requirements of inherently error-resilient applications. This paper proposes a generic accuracy-configurable multiplier that employs the VOS at a coarse-grained level (block-level) to reduce the control logic required for applying VOS and its associated overheads, thus enabling a high degree of trade-off between energy consumption and output quality. The proposed configurable Block-Level VOS-based (BL-VOS) multiplier relies on employing VOS in a multiplier composed of smaller blocks, where applying VOS in different blocks results in structures with various output accuracy levels. To evaluate the proposed concept, we implement 8-bit and 16-bit BL-VOS multipliers with various blocks width in a 15-nm FinFET technology. The results show that the proposed multiplier achieves up to 15% lower energy consumption and up to 21% higher output accuracy compared to the state-of-the-art VOS-based multipliers. Also, the effects of Process Variation (PV) and Bias Temperature Instability (BTI) induced delay on the proposed multiplier are investigated. Finally, the effectiveness of the proposed multiplier is studied for two different image processing applications, in terms of quality and energy efficiency.
Relative Kloosterman Integrals for GL(3): II

Abstract Let G′ be a quasi–split reductive group over a local field F, ƒ′ the characteristic function of a maximal compact subgroup K′ of G′, N′ a maximal unipotent subgroup of G′. We consider the orbits of maximal dimension for the action of N′ × N′ on G′ and the weighted orbital integral of f′ on such an orbit, the weight being a generic character. The resulting integral, we call a Kloosterman integral. A relative version of this construction is to consider a symmetric space S associated to a quasi-split group G, a maximal unipotent subgroup N of G, a maximal compact K of G and the orbits of maximal dimension for the action of N on S. The weighted orbital integral of the characteristic function f of K ∩ S on such an orbit is what we call a relative Kloosterman integral; the weight is an appropriate character of N. We conjecture that a relative Kloosterman integral is actually a Kloosterman integral for an appropriate group G′. We prove the conjecture in a simple case: E is an unramified quadratic extension of F, G is GL(3, E), S is the set of 3 × 3 matrices s such that the group G′ is then the quasi-split unitary group in three variables.
SHIMM: a seeing and turbulence monitor for astronomy

Optical turbulence characterisation is crucial to understanding astronomical site and observational limitations. The Differential Image Motion Monitor (DIMM) is a widely used, low cost and portable instrument for measuring the total integrated seeing. We have designed and tested a variation on the DIMM design that utilises a low order Shack-Hartmann (SH) lenslet array instead of the standard two hole aperture mask. This instrument, which is comprised of readily available components, is known as SHIMM. This alternative design utilises more of the telescope aperture, in comparison to the DIMM, and therefore increases the signal to noise ratio, as well as providing a more accurate method of noise estimation. In future the instrument will be developed to provide estimation of the coherence timescale, limited turbulence altitude information, and to correct for scintillation effects on the seeing measurements. We describe the instrument and present measurements from two identical SHIMM seeing monitors, as well as a comparison with simultaneous optical turbulence profiles recorded with Stereo-SCIDAR on the 2.5m Isaac Newton Telescope, La Palma.