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In this paper, we derive a novel Schwarzschild-like black hole (BH) solution describing a static and asymptotically flat BH surrounded by a dark matter (DM) halo with a Dehnen-type density distribution in the surrounding environment. We investigate the properties of the obtained BH by studying the curvature properties and energy conditions in Einstein gravity. Furthermore, we explore the features of a novel Schwarzschild-like BH embedded in a DM halo with Dehnen-type density profile by analyzing the timelike geodesics of particles along with BH observable properties., Comment: 20 pages, 7 captioned figures

This work proposes a fairness monitoring approach for machine learning models that predict patient mortality in the ICU. We investigate how well models perform for patient groups with different race, sex and medical diagnoses. We investigate Documentation bias in clinical measurement, showing how fairness analysis provides a more detailed and insightful comparison of model performance than traditional accuracy metrics alone., Comment: 8 pages

The notion that collaborative machine learning can ensure privacy by just withholding the raw data is widely acknowledged to be flawed. Over the past seven years, the literature has revealed several privacy attacks that enable adversaries to extract information about a model's training dataset by exploiting access to model parameters during or after training. In this work, we study privacy attacks in the gray-box setting, where the attacker has only limited access - in terms of view and actions - to the model. The findings of our investigation provide new insights for the development of privacy-preserving collaborative learning solutions. We deploy SmartCryptNN, a framework that tailors homomorphic encryption to protect the portions of the model posing higher privacy risks. Our solution offers a trade-off between privacy and efficiency, which varies based on the extent and selection of the model components we choose to protect. We explore it on dense neural networks, where through extensive evaluation of diverse datasets and architectures, we uncover instances where a favorable sweet spot in the trade-off can be achieved by safeguarding only a single layer of the network. In one of such instances, our approach trains ~4 times faster compared to fully encrypted solutions, while reducing membership leakage by 17.8 times compared to plaintext solutions., Comment: 19 pages, 7 figures, in submission

This article investigates the geodesic structure and deflection angle of charged black holes in the presence of a nonzero vacuum expectation value background of the Kalb-Ramond field. Topics explored include null and timelike geodesics, energy extraction by collisions, and the motion of charged particles. The photon sphere radius is calculated and plotted to examine the effects of both the black hole charge ($Q$) and the Lorentz-violating parameter ($b$) on null geodesics. The effective potential for timelike geodesics is analyzed, and second-order analytical orbits are derived. We further show that the combined effects of Lorentz-violating parameter and electric charge can mimic a Kerr black hole spin parameter up to its maximum values, i.e., $a/M \sim 1$ thus suggesting that the current precision of measurements of highly spinning black hole candidates may not rule out the effect of Lorentz-violating parameter. The center of mass energy of colliding particles is also considered, demonstrating a decrease with increasing Lorentz-violating parameter. Circular orbiting particles of charged particles are discovered, with the minimum radius for a stable circular orbit decreasing as both $b$ and $Q$ increase. Results show that this circular orbit is particularly sensitive to changes in the Lorentz-violating parameter. Additionally, a timelike particle trajectory is demonstrated as a consequence of the combined effects of parameters $b$ and $Q$. Finally, the light deflection angle is analyzed using the weak field limit approach to determine the Lorentz-breaking effect, employing the Gauss-Bonnet theorem for computation. Findings are visualized with appropriate plots and thoroughly discussed.

Simulating Darcy flows in porous media is fundamental to understand the future flow behavior of fluids in hydrocarbon and carbon storage reservoirs. Geological models of reservoirs are often associated with high uncertainly leading to many numerical simulations for history matching and production optimization. Machine learning models trained with simulation data can provide a faster alternative to traditional simulators. In this paper we present a single Fourier Neural Operator (FNO) surrogate that outperforms traditional reservoir simulators by the ability to predict pressures and saturations on varying permeability fields, well locations, well controls, and number of wells. The maximum-mean relative error of 95\% of pressure and saturation predictions is less than 5\%. This is achieved by employing a simple yet very effective data augmentation technique that reduces the dataset size by 75\% and reduces overfitting. Also, constructing the input tensor in a binary fashion enables predictions on unseen well locations, well controls, and number of wells. Such model can accelerate history matching and reservoir characterization procedures by several orders of magnitude. The ability to predict on new well locations, well controls, and number of wells enables highly efficient reservoir management and optimization.

Implementing the concept of Dark Fluid with a Chaplygin-like equation of state within General Relativity, we construct a new higher-dimensional, static, and spherically symmetric anti-de Sitter (AdS) black hole solution. Energy conditions are explored alongside curvature singularity tools. The inspection at the level of the phase structure and $P-v$ critical behavior is carried out in the context of the extended phase space, where the cosmological constant appears as pressure. Our findings disclose non-trivial similarities between the small/large phase transition of AdS black holes surrounded by Chaplygin dark fluid and van der Waals systems' liquid/gas phase transition. This analysis offers insights into the physical interpretation of the $P-v$ diagram and identifies critical exponents that reveal the scaling behavior of thermodynamic quantities close to criticality in a universal manner. We finally deepen our understanding of the thermodynamic properties and microstructure of AdS black holes by leveraging the geometrothermodynamic formalism. Specifically, we employ tools, including Weinhold, Ruppeiner, Hendi-Panahiyan-Eslam-Momennia (HPEM) and Quevedo classes I and II. We show that each class of metrics predicts either the physical limitation point and/or the phase-transition critical points, with HPEM and Quevedo formulations providing richer information about the phase transitions. Altogether, this study contributes to advancing our knowledge of the role of Chaplygin gas in General Relativity and thoroughly examining the thermodynamic phase structure of high-dimensional AdS black holes under extreme conditions., Comment: 26 pages, 11 labeled figure, accepted for publication in Phys. Dark. Univ

We investigate shadows, deflection angle, quasinormal modes (QNMs), and sparsity of Hawking radiation of the Schwarzschild string cloud black hole's solution after applying quantum corrections required by the Generalised Uncertainty Principle (GUP). First, we explore the shadow's behaviour in the presence of a string cloud using three alternative GUP frameworks: linear quadratic GUP (LQGUP), quadratic GUP (QGUP), and linear GUP. We then used the weak field limit approach to determine the effect of the string cloud and GUP parameters on the light deflection angle, with computation based on the Gauss-Bonnet theorem. Next, to compute the quasinormal modes of Schwarzschild string clouds incorporating quantum correction with GUP, we determine the effective potentials generated by perturbing scalar, electromagnetic and fermionic fields, using the sixth-order WKB approach in conjunction with the appropriate numerical analysis. Our investigation indicates that string and linear GUP parameters have distinct and different effects on QNMs. We find that the greybody factor increases due to the presence of string cloud while the linear GUP parameter shows the opposite. We then examine the radiation spectrum and sparsity in the GUP corrected black hole with the cloud of string framework, which provides additional information about the thermal radiation released by black holes. Finally, our inquiries reveal that the influence of the string parameter and the quadratic GUP parameter on various astrophysical observables is comparable, however the impact of the linear GUP parameter is opposite., Comment: 32 pages, 7 tables, 14 captioned figures. Accepted for publication in Eur. Phys. J. C

In this paper, different techniques of few-shot, zero-shot, and regular object detection have been investigated. The need for few-shot learning and zero-shot learning techniques is crucial and arises from the limitations and challenges in traditional machine learning, deep learning, and computer vision methods where they require large amounts of data, plus the poor generalization of those traditional methods. Those techniques can give us prominent results by using only a few training sets reducing the required amounts of data and improving the generalization. This survey will highlight the recent papers of the last three years that introduce the usage of few-shot learning and zero-shot learning techniques in addressing the challenges mentioned earlier. In this paper we reviewed the Zero-shot, few-shot and regular object detection methods and categorized them in an understandable manner. Based on the comparison made within each category. It been found that the approaches are quite impressive. This integrated review of diverse papers on few-shot, zero-shot, and regular object detection reveals a shared focus on advancing the field through novel frameworks and techniques. A noteworthy observation is the scarcity of detailed discussions regarding the difficulties encountered during the development phase. Contributions include the introduction of innovative models, such as ZSD-YOLO and GTNet, often showcasing improvements with various metrics such as mean average precision (mAP),Recall@100 (RE@100), the area under the receiver operating characteristic curve (AUROC) and precision. These findings underscore a collective move towards leveraging vision-language models for versatile applications, with potential areas for future research including a more thorough exploration of limitations and domain-specific adaptations.

This article considers a static and spherical black hole (BH) in f(Q) gravity. f(Q) gravity is the extension of symmetric teleparallel general relativity, where both curvature and torsion are vanishing, and gravity is described by nonmetricity. In this study, we investigate the possible implications of quasinormal modes (QNM) modified Hawking spectra, and deflection angles generated by the model. The WKB method is used to solve the equations of motion for massless Dirac perturbation fields and explore the impact of the nonmetricity parameter ($Q_{0}$). Based on the QNMs computation, we can ensure that the BH is stable against massless Dirac perturbations and as $Q_{0}$ increases the the oscillatory frequency of the mode decrease. We then discuss the weak deflection angle in the weak field limit approximation. We compute the deflection angle up to the fourth order of approximation and show how the nonmetricity parameter affects it. We find that the $Q_{0}$ parameter reduces the deflection angle.

Standard Patlak plot is widely used to describe FDG kinetics for dynamic PET imaging. Whole-body Patlak parametric imaging remains constrained due to the need for a full-time input function. Here, we demonstrate the Relative Patlak (RP) plot, which eliminates the need for the early-time input function, for total-body parametric imaging and its application to clinical 20-min scan acquired in list-mode. We demonstrated that the RP intercept b' is equivalent to a ratio of standardized uptake value relative to the blood, while the RP slope Ki' is equal to the standard Patlak Ki multiplied by a global scaling factor for each subject. One challenge in applying RP to a short scan duration (20 min) is the high noise in parametric images. We applied a deep kernel method for noise reduction. Using the standard Patlak plot as the reference, the RP method was evaluated for lesion quantification, lesion-to-background contrast, and myocardial visualization in total-body parametric imaging with uEXPLORER in 22 human subjects who underwent a 1-h dynamic 18F-FDG scan. The RP method was also applied to the dynamic data regenerated from a clinical standard 20-min scan either at 1-h or 2-h post-injection for two cancer patients. We demonstrated that it is feasible to obtain high-quality parametric images from 20-min dynamic scans using the RP plot with a self-supervised deep-kernel noise reduction strategy. The RP Ki' highly correlated with Ki in lesions and major organs, demonstrating its quantitative potential across subjects. Compared to conventional SUVs, the Ki' images significantly improved lesion contrast and enabled visualization of the myocardium for potential cardiac assessment. The application of RP parametric imaging to two clinical scans also showed similar benefits. Total-body PET with the RP plot is feasible to generate parametric images from the dynamic data of a 20-min clinical scan.

The purpose of this study is to investigate the quasinormal modes (QNMs), greybody factors (GFs) and shadows in a plasma of a black hole (BH) surrounded by an exotic fluid of quintessence type in a scalar-vector-tensor modified gravity. The effects of a quintessence scalar field and the modified gravity (MOG) field on the QNM, GF, and shadow are examined. Using the sixth-order WKB approach, we investigate the QNMs of massless scalar and electromagnetic perturbations. Our findings show that as the quintessence and the MOG parameter ($\epsilon$ and $\alpha$) increase, the oscillation frequencies decrease significantly. Gravitational wave damping, on the other hand, decreases with increasing $\epsilon$ and $\alpha$. In addition, we obtain an analytical solution for the transmission coefficients (GF) and demonstrate that more thermal radiation reaches the observer at spatial infinity as both the $\epsilon$ and $\alpha$ parameters increase. We also investigate the effect of the plasma background on the BH shadow and show that as the plasma background parameter increases, the shadow radius slightly shrinks. Nevertheless, the shadow radius increases as $\alpha$ and $\epsilon$ increase. Particularly intriguing is the fact that increasing $\epsilon$ has a greater impact on the shadow radius than increasing $\alpha$, indicating that the quintessence parameter has a greater impact than the MOG parameter.

Reducing scan times, radiation dose, and enhancing image quality, especially for lower-performance scanners, are critical in low-count/low-dose PET imaging. Deep learning (DL) techniques have been investigated for PET image denoising. However, existing models have often resulted in compromised image quality when achieving low-dose PET and have limited generalizability to different image noise-levels, acquisition protocols, and patient populations. Recently, diffusion models have emerged as the new state-of-the-art generative model to generate high-quality samples and have demonstrated strong potential for medical imaging tasks. However, for low-dose PET imaging, existing diffusion models failed to generate consistent 3D reconstructions, unable to generalize across varying noise-levels, often produced visually-appealing but distorted image details, and produced images with biased tracer uptake. Here, we develop DDPET-3D, a dose-aware diffusion model for 3D low-dose PET imaging to address these challenges. Collected from 4 medical centers globally with different scanners and clinical protocols, we extensively evaluated the proposed model using a total of 9,783 18F-FDG studies (1,596 patients) with low-dose/low-count levels ranging from 1% to 50%. With a cross-center, cross-scanner validation, the proposed DDPET-3D demonstrated its potential to generalize to different low-dose levels, different scanners, and different clinical protocols. As confirmed with reader studies performed by nuclear medicine physicians, experienced readers judged the images to be similar to or superior to the full-dose images and previous DL baselines based on qualitative visual impression. The presented results show the potential of achieving low-dose PET while maintaining image quality. Lastly, a group of real low-dose scans was also included for evaluation to demonstrate the clinical potential of DDPET-3D., Comment: 15 Pages, 15 Figures, 5 Tables. Paper under review. First-place Freek J. Beekman Young Investigator Award at SNMMI 2024. arXiv admin note: substantial text overlap with arXiv:2311.04248

Let $R$ be a commutative ring with $1 \neq 0$. A proper ideal $I$ of $R$ is a {\it square-difference factor absorbing ideal} (sdf-absorbing ideal) of $R$ if whenever $a^2 - b^2 \in I$ for $0 \neq a, b \in R$, then $a + b \in I$ or $a - b \in I$. In this paper, we introduce and investigate sdf-absorbing ideals., Comment: 18 pages

A hairy black hole (HBH) emerges due to matter surrounding the Schwarzschild metric when using the Extended Gravitational Decoupling (GD) approach. The fermionic greybody factors (GFs) and quasinormal modes (QNMs) as well as Hawking spectra and sparsity of HBH solutions are investigated. We consider massive and massless spin- 1/2 fermions, along with massless spin- 3/2 fermions. The equations of the effective potential for fermions with different spins are derived in HBH spacetime. Then, the rigorous bound method is used to calculate the fermionic spin- 1/2 and spin- 3/2 GFs. With the time domain integration method at our disposal, we illustrate the impact of additional parameters on the ringdown waveform of the massless fermionic spin -1/2 and spin -3/2 fields and, in turn, on their quasinormal modes. We then delve into investigating the Hawking spectra and sparsity of the radiation emitted by an HBH. Hairy parameters significantly affect the sparsity of Hawking radiation as well. We observe that the total power emitted by the BH increases both with $\alpha$ and $Q$ but decreases with $l_{0}$. Our study conclusively shows the significant impact of the additional parameters on important astrophysical phenomena such as quasinormal modes, Hawking spectra, and sparsity.

X-ray computed tomography (CT) in PET/CT is commonly operated with a single energy, resulting in a limitation of lacking tissue composition information. Dual-energy (DE) spectral CT enables material decomposition by using two different x-ray energies and may be combined with PET for improved multimodality imaging, but would either require hardware upgrade or increase radiation dose due to the added second x-ray CT scan. Recently proposed PET-enabled DECT method allows dual-energy spectral imaging using a conventional PET/CT scanner without the need for a second x-ray CT scan. A gamma-ray CT (gCT) image at 511 keV can be generated from the existing time-of-flight PET data with the maximum-likelihood attenuation and activity (MLAA) approach and is then combined with the low-energy x-ray CT image to form dual-energy spectral imaging. To improve the image quality of gCT, a kernel MLAA method was further proposed by incorporating x-ray CT as a priori information. The concept of this PET-enabled DECT has been validated using simulation studies, but not yet with 3D real data. In this work, we developed a general open-source implementation for gCT reconstruction from PET data and use this implementation for the first real data validation with both a physical phantom study and a human subject study on a uEXPLORER total-body PET/CT system. These results have demonstrated the feasibility of this method for spectral imaging and material decomposition., Comment: 8 pages, 11 figures

In this paper, we study the dynamics of a test particle around a regular black hole (BH) in a non-minimal Einstein Yang Mills (EYM) theory and examine the BH shadow. The EYM theory is a non-minimally coupled theory in which curvature couples to non-Abelian gauge fields. We investigate particle motion with parameters in EYM BH for massless and massive particles. This work provides the horizon structure, photon radius and inner stable circular orbit (ISCO) of a mass particle with EYM BH parameters. An analysis is provided of the effective potential as well as the possible orbits for test particles under various EYM BH parameters values. In timelike radial geodesics, we find that for smaller values of magnetic charge, particles following a timelike radial geodesic are hastier in EYM BH, and hence arrive at the center faster than those traveling a Schwarzschild BH geodesic. However, at larger values of the magnetic charge, the inverse effect is observed. The effect of model parameters is investigated in order to study the ISCO, photon radius, orbit stability (Lyapunov exponent), and effective force on particles for the BH in the EYM theory. Finally, we investigate the BH shadow. We find that higher magnetic charge values and non-minimal coupling parameters result in smaller shadow radius values.

In this manuscript, we delve into an analytic and numerical probe of shadow with different accretion models, quasinormal modes, Hawking radiation, and gravitational lensing to study observational impacts of quantum effect introduced throughh linear-quadratic GUP(LQG). Our investigation reveals that the shadows of LQG modified black holes are smaller and brighter than Schwarzschild black holes. To examine the impact of the quantum correction on the quasinormal mode, linear-quadratic GUP modified black holes are explored under scalar and electromagnetic field perturbation. Here, linear-quadratic GUP is used to capture quantum corrections. It is observed that the incorporation of quantum correction by linear-quadratic GUP alters the singularity structure of the black hole. To compute the quasinormal modes of this linear-quadratic GUP-inspired quantum-corrected black holes, we compute the effective potential generated under the perturbation of scalar and electromagnetic field, and then we use the sixth-order WKB approach in conjunction with the appropriate numerical analysis. We find that the greybody factor decreases with the GUP parameter $\alpha$ implying that the probability of transmission decreases with the GUP parameter. The total power emitted by LQG modified black hole is found to be greater than that emitted by Schwarzschild black hole. Finally, we study weak gravitational lensing and make a comparison with quadratic GUP and linear GUP modified black holes.

We investigate the impact of the modified gravity (MOG) field and the quintessence scalar field on horizon evolution, black hole (BH) shadow and the weak gravitational lensing around a static spherically symmetric BH. We first begin to write the BH metric associated with the MOG parameter and quintessence scalar field. We then determine the BH shadow and obtain numerical solutions for the photon sphere and shadow radius. We show that the MOG ($\alpha$) and the quintessence ($c$) parameters have a significant impact on BH shadow and photon sphere. Based on the analysis, we further show that the combined effects of the MOG parameter and quintessential field can increase the values of BH shadow and photon sphere radii. We also obtain constraints on the BH parameters by applying the observational data of Sgr A$^{\star}$ and M87$^{\star}$. Finally, we consider the weak deflection angle of BH within the context of the Gauss-Bonnet theorem (GBT) and show that the combined effects of the MOG and quintessence parameters do make the value of the deflection angle grow, referring to remarkable property being in well agreement with the physical meaning of both parameters that can maintain the strong gravitational field in the surrounding environment of BH., Comment: 14 pages, 2 tables, 9 captioned figures

In this paper, we investigate the optical properties of a charged black hole in Einstein-Maxwell-scalar (EMS) theory. We evaluate the shadow cast by the black hole and obtain analytical solutions for both the radius of the photon sphere and the shadow radius. We observe that the black hole parameters $\gamma$ and $\beta$ both influence the shadow of black hole. It is shown that the photon sphere and the shadow radius increase as a consequence of the presence of parameter $\gamma$. Interestingly, we show that shadow radius decreases first and then remains unchanged due to the impact of parameter $\beta$. Finally, we consider the weak gravitational lensing and the total magnification of lensed images around black hole. We find that the black hole charge and parameter $\beta$ both give rise to a significant effect, reducing the deflection angle. Similarly, the same behavior for the total magnification is observed due to the effect of black hole charge and parameter $\beta$., Comment: 9 pages, one table, 9 captioned figures, Accepted for publication in Chinese Physics C

Physics-Informed machine learning models have recently emerged with some interesting and unique features that can be applied to reservoir engineering. In particular, a physics-informed neural network (PINN) leverages the fact that neural networks are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations. The transient diffusivity equation is a fundamental equation in reservoir engineering and the general solution to this equation forms the basis for Pressure Transient Analysis (PTA). The diffusivity equation is derived by combining three physical principles, the continuity equation, Darcy's equation, and the equation of state for a slightly compressible liquid. Obtaining general solutions to this equation is imperative to understand flow regimes in a porous media. Analytical solutions of the transient diffusivity equation usually are very hard to obtain due to the steep gradients of the pressure near the well. In this work we apply physics-informed neural networks to the one and two dimensional diffusivity equation and demonstrate that decomposing the space domain into very few subdomains can overcome the stiffness problem of the equation. Additionally, we demonstrate that the inverse capabilities of PINNs can estimate missing physics such as permeability and sealing fault similar to buildup tests without shutting in the well., Comment: 19 pages, Paper titled: "Physics-Informed Neural Network for the Transient Diffusivity Equation in Reservoir Engineering"