Corrected Thermodynamics of Black Holes in f(R) Gravity with Electrodynamic Field and Cosmological Constant.

The thermodynamics of black holes (BHs) and their corrections have become a hot topic in the study of gravitational physics, with significant progress made in recent decades. In this paper, we study the thermodynamics and corrections of spherically symmetric BHs in models f(R)=R+αR2 and f(R)=R+2γR+8Λ under the f(R) theory, which includes the electrodynamic field and the cosmological constant. Considering thermal fluctuations around equilibrium states, we find that, for both f(R) models, the corrected entropy is meaningful in the case of a negative cosmological constant (anti-de Sitter-RN spacetime) with Λ=-1. It is shown that when the BHs' horizon radius is small, thermal fluctuations have a more significant effect on the corrected entropy. Using the corrected entropy, we derive expressions for the relevant corrected thermodynamic quantities (such as Helmholtz free energy, internal energy, Gibbs free energy, and specific heat) and calculate the effects of the correction terms. The results indicate that the corrections to Helmholtz free energy and Gibbs free energy, caused by thermal fluctuations, are remarkable for small BHs. In addition, we explore the stability of BHs using specific heat. The study reveals that the corrected BH thermodynamics exhibit locally stable for both models, and corrected systems undergo a Hawking-Page phase transition. Considering the requirement on the non-negative volume of BHs, we also investigate the constraint on the EH radius of BHs.

Acoustic black hole immersed sonoreactor for high-efficiency cavitation treatment.

Developing innovative sonoreactors to enhance acoustic processing efficiency holds immense importance in the field of sonochemistry. Traditional immersed sonoreactors (TISs) mainly produce cavitation at the probe tip, with a relatively weak cavitation around the probe, resulting in posing challenges for high-efficiency cavitation treatment. Here we propose an acoustic black hole immersed sonoreactor (ABHIS) in longitudinal-flexural coupled vibration, enabling high-efficiency cavitation treatment by unleashing the cavitation potential of the probe. The symmetrical structure of the probe is altered to introduce a coupling of flexural vibration mode, and an acoustic black hole (ABH) profile is integrated to further enhance both flexural wave number and amplitude. In this paper, we present a systematic theoretical design method for ABHIS and compare its performance with TIS using finite element method (FEM). An ABHIS prototype is fabricated and subjected to experimental tests and cavitation observation. The results demonstrate that our theoretical analysis model accurately predicts the frequency characteristics of ABHIS. The proposed ABHIS exhibits satisfactory dynamic characteristics, with significantly increased vibration displacement and acoustic radiation ability compared to TIS. Importantly, the ABH design significantly expands ultrasonic cavitation regions and enhances acoustic radiation intensity of ABHIS, resulting in a substantial improvement in acoustic processing efficiency.

Hypomagnesemia is Associated with the Skull Computed Tomography Black Hole Sign in Patients with Spontaneous Intracerebral Hemorrhage.

OBJECTIVES: The evaluation of hypomagnesemia's significance in predicting the presence of the black hole sign in patients with intracranial hemorrhage is currently under investigation. METHODS: The study included 261 patients with cerebral hemorrhage who underwent initial skull computed tomography within 24 hours of admission. Sixty-nine patients (26.4%) exhibited hypomagnesemia in the initial laboratory examinations. The black hole sign was observed in 123 patients (referred to as the black hole sign group, which includes patients with and without hypomagnesemia), while the remaining 138 patients (nonblack hole sign group) did not exhibit this feature. The values of hypomagnesemia were assessed through multivariable logistic regression analyses. RESULTS: The black hole sign occurred in 45 of the 69 (65.2%) patients with hypomagnesemia, and in 78 of the 192 (40.6%) patients without hypomagnesemia. In the black hole sign group, hypomagnesemia was observed in 45 patients (36.6%). However, only 24 patients (19.5%) from the normal magnesium concentration group exhibited hypomagnesemia. The sensitivity, specificity, and positive and negative predictive values of hypomagnesemia for predicting the black hole sign were 69.9%, 82.5%, 36.6%, and 82.8%, respectively. The odds ratios for hypomagnesemia, smoking history, and hypokalemia in predicting the presence of the black hole sign were 2.74, 1.971, and 1.629, correspondingly. CONCLUSIONS: The presence of hypomagnesemia may serve as a predictive factor for the black hole sign and rebleeding in patients with intracerebral hemorrhage, thereby providing valuable guidance for clinical treatment.

Multipartite Correlations in Parikh-Wilczek Non-Thermal Spectrum.

In this study, we systematically investigate the multipartite correlations in the process of black hole radiation via the Parikh-Wilczek tunneling model. We examine not only the correlations among Hawking radiations but also the correlations between the emissions and the remainder of the black hole. Our findings indicate that the total correlation among emitted particles continues to increase as the black hole evaporates. Additionally, we observe that the bipartite correlation between the emissions and the remainder of the black hole initially increases and then decreases, while the total correlation of the entire system monotonically increases. Finally, we extend our analysis to include quantum correction and observe similar phenomena. Through this research, we aim to elucidate the mechanism of information conservation in the black hole information paradox.

Embedded periodically ABHs and distributed DVAs for passive low-frequency broadband vibration attenuation in thin-walled structures.

The acoustic black hole (ABH) structure exhibits remarkable energy focalization above a given cut-on frequency, offering potential for broadband vibration suppression in structures. However, its energy focusing properties diminish significantly below this cut-on frequency. Therefore, it is crucial to enhance the vibration attenuation capabilities of ABH structures within the low frequency range. This study presents a numerical investigation into the impact of thin-walled structures with embedded ABHs and distributed dynamic vibration absorbers (DVAs) on low frequency broadband vibration reduction. Initially, the focusing characteristics of the ABH thin-walled structure is analyzed, aiding in the attached position of DVAs. Furthermore, the influence of the design parameters and attached position of DVA on the broadband damping effect of the structure is explored. The findings indicate that DVAs designed for low frequencies can achieve significant vibration attenuation across the entire frequency spectrum, including low frequencies, when installed at specific focusing positions. When compared to the position with the maximum vibration response, while the attenuation of the low frequency common amplitude value is slightly reduced, greater vibration attenuation across the entire frequency band is achieved. This research offers valuable insights into optimizing the integration of DVAs with ABHs in thin-walled structures for enhanced broadband vibration attenuation.

A Cooperative Intrusion Detection System for the Internet of Things Using Convolutional Neural Networks and Black Hole Optimization.

Maintaining security in communication networks has long been a major concern. This issue has become increasingly crucial due to the emergence of new communication architectures like the Internet of Things (IoT) and the advancement and complexity of infiltration techniques. For usage in networks based on the Internet of Things, previous intrusion detection systems (IDSs), which often use a centralized design to identify threats, are now ineffective. For the resolution of these issues, this study presents a novel and cooperative approach to IoT intrusion detection that may be useful in resolving certain current security issues. The suggested approach chooses the most important attributes that best describe the communication between objects by using Black Hole Optimization (BHO). Additionally, a novel method for describing the network's matrix-based communication properties is put forward. The inputs of the suggested intrusion detection model consist of these two feature sets. The suggested technique splits the network into a number of subnets using the software-defined network (SDN). Monitoring of each subnet is done by a controller node, which uses a parallel combination of convolutional neural networks (PCNN) to determine the presence of security threats in the traffic passing through its subnet. The proposed method also uses the majority voting approach for the cooperation of controller nodes in order to more accurately detect attacks. The findings demonstrate that, in comparison to the prior approaches, the suggested cooperative strategy can detect assaults in the NSLKDD and NSW-NB15 datasets with an accuracy of 99.89 and 97.72 percent, respectively. This is a minimum 0.6 percent improvement.

Acoustic black hole ultrasonic scalpel.

Ultrasonic scalpels (USs), as the preferred energy instruments, are facing a growing need to exhibit enhanced performance with the diversification of modern surgical challenges. Hence, we proposed an acoustic black hole ultrasonic scalpel (ABHUS) in longitudinal-bending coupled vibration for efficient surgical cutting. By incorporating an acoustic black hole profile, the local bending wave velocity is reduced and the amplitude is amplified cumulatively, thus creating a high-energy region near the blade tip to enhance the cutting performance of the ABHUS. The precise physical analysis model is established for systematic design of the ABHUS and quick estimation of its frequency characteristics. The vibration simulation and experiments demonstrate that compared with the conventional ultrasonic scalpel (CUS), the output amplitude of the ABHUS significantly increases, particularly a 425% increase in bending vibration displacement. The in-vitro cutting experiment confirms that ABHUS exhibits superior cutting performance. Our design presents vast possibilities and potential for the development of high-performance ultrasonic surgical instruments, serving as an innovative supplement with extraordinary significance for application of acoustic black holes.

Joule-Thomson expansion in a mimetic black hole.

This paper investigates some implications of mimetic gravity on the black hole thermodynamics. We begin with an analysis of the mimetic action and its relationship to the spacetime curvature, highlighting the field equations and their contributions to the black hole solutions. Then we explore the behavior of various thermodynamic parameters including pressure, temperature and heat capacity, revealing some intriguing features of the system near the event horizon. We analyze also the inversion temperatures, inversion curves and the Joule-Thomson coefficients to enrich our comprehension of thermodynamic phenomena in this context. By extending coordinates close to the event horizon, we study the Joule-Thomson expansion, demonstrating how strong gravitational fields create pressure gradients similar to gas cooling processes. Comparison between mimetic black hole and Schwarzschild black hole in this setup provides a deeper understanding of the unique characteristics of the mimetic gravity.

Next-generation chemotherapy treatments based on black hole algorithms: From cancer remission to chronic disease management.

PROBLEM: Therapeutic planning strategies have been developed to enhance the effectiveness of cancer drugs. Nevertheless, their performance is highly limited by the inefficient biological representativeness of predictive tumor growth models, which hinders their translation to clinical practice. OBJECTIVE: This study proposes a disruptive approach to oncology based on nature-inspired control using realistic Black Hole physical laws, in which tumor masses are trapped to experience attraction dynamics on their path to complete remission or to become a chronic disease. This control method is designed to operate independently of individual patient idiosyncrasies, including high tumor heterogeneities and highly uncertain tumor dynamics, making it a promising avenue for advancing beyond the limitations of the traditional survival probabilistic paradigm. DESIGN: Here, we provide a multifaceted study of chemotherapy therapeutic planning that includes: (1) the design of a pioneering controller algorithm based on physical laws found in the Black Holes; (2) investigation of the ability of this controller algorithm to ensure stable equilibrium treatments; and (3) simulation tests concerning tumor volume dynamics using drugs with significantly different pharmacokinetics (Cyclophosphamide and Atezolizumab), tumor volumes (200 mm3 and 12 732 mm3) and modeling characterizations (Gompertzian and Logistic tumor growth models). RESULTS: Our results highlight the ability of this new astrophysical-inspired control algorithm to perform effective chemotherapy treatments for multiple tumor-treatment scenarios, including tumor resistance to chemotherapy, clinical scenarios modelled by time-dependent parameters, and highly uncertain tumor dynamics. CONCLUSIONS: Our findings provide strong evidence that cancer therapy inspired by phenomena found in black holes can emerge as a disruptive paradigm. This opens new high-impacting research directions, exploring synergies between astrophysical-inspired control algorithms and Artificial Intelligence applied to advanced personalized cancer therapeutics.

The Holographic Principle Comes from Finiteness of the Universe's Geometry.

Discovered as an apparent pattern, a universal relation between geometry and information called the holographic principle has yet to be explained. This relation is unfolded in the present paper. As it is demonstrated there, the origin of the holographic principle lies in the fact that a geometry of physical space has only a finite number of points. Furthermore, it is shown that the puzzlement of the holographic principle can be explained by a magnification of grid cells used to discretize geometrical magnitudes such as areas and volumes into sets of points. To wit, when grid cells of the Planck scale are projected from the surface of the observable universe into its interior, they become enlarged. For that reason, the space inside the observable universe is described by the set of points whose cardinality is equal to the number of points that constitute the universe's surface.

Universe-inspired algorithms for control engineering: A review.

Control algorithms have been proposed based on knowledge related to nature-inspired mechanisms, including those based on the behavior of living beings. This paper presents a review focused on major breakthroughs carried out in the scope of applied control inspired by the gravitational attraction between bodies. A control approach focused on Artificial Potential Fields was identified, as well as four optimization metaheuristics: Gravitational Search Algorithm, Black-Hole algorithm, Multi-Verse Optimizer, and Galactic Swarm Optimization. A thorough analysis of ninety-one relevant papers was carried out to highlight their performance and to identify the gravitational and attraction foundations, as well as the universe laws supporting them. Included are their standard formulations, as well as their improved, modified, hybrid, cascade, fuzzy, chaotic and adaptive versions. Moreover, this review also deeply delves into the impact of universe-inspired algorithms on control problems of dynamic systems, providing an extensive list of control-related applications, and their inherent advantages and limitations. Strong evidence suggests that gravitation-inspired and black-hole dynamic-driven algorithms can outperform other well-known algorithms in control engineering, even though they have not been designed according to realistic astrophysical phenomena and formulated according to astrophysics laws. Even so, they support future research directions towards the development of high-sophisticated control laws inspired by Newtonian/Einsteinian physics, such that effective control-astrophysics bridges can be established and applied in a wide range of applications.

A secure worst elite sailfish optimizer based routing and deep learning for black hole attack detection.

The Wireless Sensor Network (WSN) is susceptible to two kinds of attacks, namely active attack and passive attack. In an active attack, the attacker directly communicates with the target system or network. In contrast, in passive attack, the attacker is in indirect contact with the network. To preserve the functionality and dependability of wireless sensor networks, this research has been conducted recently to detect and mitigate the black hole attacks. In this research, a Deep learning (DL) based black hole attack detection model is designed. The WSN simulation is the beginning stage of this process. Moreover, routing is the key process, where the data is passed to the base station (BS) via the shortest and finest route. The proposed Worst Elite Sailfish Optimization (WESFO) is utilized for routing. Moreover, black hole attack detection is performed in the BS. The Auto Encoder (AE) is employed in attack detection, which is trained with the use of the proposed WESFO algorithm. Additionally, the proposed model is validated in terms of delay, Packet Delivery Rate (PDR), throughput, False-Negative Rate (FNR), and False-Positive Rate (FPR) parameters with the corresponding outcomes like 25.64 s, 94.83%, 119.3, 0.084, and 0.135 are obtained.

Extended phase space thermodynamics of regular-AdS black hole.

After obtaining an exact regular-AdS black hole resulting from the coupling of general relativity with nonlinear electrodynamics (NED), we explore the thermodynamics of the extended phase space, treating the cosmological constant ( Λ ) as the pressure (P) of the black holes and its conjugate as thermodynamic volume (V). Considering the NED parameter (g), we investigate the Hawking temperature, entropy, Gibb's free energy and specific heat at the horizon radius. Due to the presence of NED charge, the black hole exhibits van der Waals-like phase transition instead of Hawking-Page phase transition, which could be observed through the G - T plots, which display a swallowtail pattern below the critical pressure, and it gives rise to second-order phase transitions when pressure attains its critical value. The first-order phase transition shares similarities with the liquid-gas phase transition. We determine the exact critical points and explore the influence of NED on P - V criticality, revealing that the isotherms undergo a liquid-gas-like phase transition for temperatures below its critical value T C , especially at lower T C . The identical critical exponent to that of the van der Waals fluid suggests that the NED does not alter the critical exponents, as observed in other arbitrary AdS black holes.

Geometrothermodynamics of 3D Regular Black Holes.

We investigate a spherically symmetric exact solution of Einstein's gravity with cosmological constant in (2 + 1) dimensions, non-minimally coupled to a scalar field. The solution describes the gravitational field of a black hole, which is free of curvature singularities in the entire spacetime. We use the formalism of geometrothermodynamics to investigate the geometric properties of the corresponding space of equilibrium states and find their interpretation from the point of view of thermodynamics. It turns out that, as a result of the presence of thermodynamic interaction, the space of equilibrium states is curved with two possible configurations, which depend on the value of a coupling constant. In the first case, the equilibrium space is completely regular, corresponding to a stable thermodynamic system. The second case is characterized by the presence of two curvature singularities, which are shown to correspond to locations where the system undergoes two different phase transitions, one due to the breakdown of the thermodynamic stability condition and the second one due to the presence of a divergence at the level of the response functions.

Enhancing acoustic emission wave attenuation at structural boundaries: Introducing an additional spiral acoustic black hole and assessing its performance.

Acoustic emission (AE) technology plays a crucial role in dynamic nondestructive testing. To investigate material properties, friction characteristics, damage features, and acoustic source localization, AE tests are commonly conducted on metal or composite plates. However, the reflection of AE waves at the boundary often generates strong interference, significantly impacting AE test results. In response to this challenge, this paper introduces an innovative solution: an additional Spiral Acoustic Black Hole (ASABH) affixed to the test plate's boundary. The ASABH is designed to mitigate the reflection of AE signals, enhancing the signal-to-noise ratio collected by the sensor. The study begins by establishing a finite element model of the ASABH to validate its efficacy in reducing boundary reflection waves. Subsequently, the paper explores the impact of structural geometric parameters-such as length, residual thickness, power exponent, pitch, and extended length-on the reduction effect. The investigation also delves into the variation of attenuation degree when connecting the ASABH to plates with different relative thickness, relative widths, and materials. Finally, the effectiveness of the ASABH in attenuating structural boundary reflection waves is verified through pencil-lead breaking tests conducted on both metal and composite plates. Results indicate that the proposed ASABH effectively mitigates the reflection of AE waves at the structural boundary, demonstrating adaptability and providing valuable insights for ASABH design.

Black hole sign migration in short-term brain CT scans: A possible link with clot evolution and histology.

The black hole sign (BHS) is a rare radiological sign seen in the hyperacute phase of bleeding. It manifests within a hemorrhage in early hours, with limited studies exploring clot formation and evolution over a short duration. Despite various hypothesized mechanisms, the precise lifetime and dynamics of black hole sign development remain unclear. We describe the rare finding of a black hole sign within a deep brain hemorrhage, initially observed in the lateral portion of the clot during the first CT scan. Remarkably, in a subsequent CT scan, just 1 hour later, the BHS migrated towards the inner edge. Notably, while the hemorrhage size remained largely unchanged within this short timeframe, hyperacute bleeding led to increased perihematomal edema and sulci flattening. Histopathological features of the "evolving clot" are initially characterized by heightened cellularity. This increased cell density renders the hematoma less resistant to compressive forces, such as heightened endocranial pressure, offering a plausible explanation for the crushing and displacement of the BHS. Our study sheds light on the unique radiological progression of BHS within a deep brain ICH, emphasizing its association with dynamic clot formation and the consequential impact on surrounding structures.

Revisiting the Surface Brightness Profile of the Stellar Disk with the Statistical Mechanics of the Self-Gravitating System with the Central Body.

We have explored the exponential surface brightness profile (SBP) of stellar disks, a topic extensively discussed by many authors yet seldom integrated with the study of correlations between black holes, bulges, and entire disks. Building upon our prior work in the statistical mechanics of disk-shaped systems and aligning with methodologies from other research, we analyze the influence of the central body. This analysis reveals analytical relationships among black holes, bulges, and the entire stellar disk. Additionally, we incorporate a specific angular momentum distribution (SAMD) that aligns more closely with observational data, showing that for the self-gravitating disk, with the same surface density, a reduction in its spin results in only a slight decrease in its radius, whereas with the same SAMD, an increment in its spin significantly limits its extent. A key feature of our model is its prediction that the surface density profile of an isolated disk will invariably exhibit downbending at a sufficient distance, a hypothesis that future observations can test. Our refined equations provide a notably improved fit for SBPs, particularly in the central regions of stellar disks. While our findings underscore the significance of statistical mechanics in comprehending spiral galaxy structures, they also highlight areas in our approach that warrant further discussion and exploration.

Corrections to the Bekenstein-Hawking Entropy of the HNUTKN Black Hole Due to Lorentz-Breaking Fermionic Einstein-Aether Theory.

A hot NUT-Kerr-Newman black hole is a general stationary axisymmetric black hole. In this black hole spacetime, the dynamical equations of fermions at the horizon are modified by considering Lorentz breaking. The corrections to the Hawking temperature and Bekenstein-Hawking entropy at the horizon of the black hole are studied in depth. Based on the semiclassical theory correction, the Bekenstein-Hawking entropy of this black hole is quantum-corrected by considering the perturbation effect of the Planck constant ℏ. The latter part of this paper presents a detailed discussion of the obtained results and their physical implications.

Trust-Based Optimized Reporting for Detection and Prevention of Black Hole Attacks in Low-Power and Lossy Green IoT Networks.

The Internet of Things (IoT) is empowering various sectors and aspects of daily life. Green IoT systems typically involve Low-Power and Lossy Networks (LLNs) with resource-constrained nodes. Lightweight routing protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL), are increasingly being applied for efficient communication in LLNs. However, RPL is susceptible to various attacks, such as the black hole attack, which compromises network security. The existing black hole attack detection methods in Green IoT rely on static thresholds and unreliable metrics to compute trust scores. This results in increasing false positive rates, especially in resource-constrained IoT environments. To overcome these limitations, we propose a delta-threshold-based trust model called the Optimized Reporting Module (ORM) to mitigate black hole attacks in Green IoT systems. The proposed scheme comprises both direct trust and indirect trust and utilizes a forgetting curve. Direct trust is derived from performance metrics, including honesty, dishonesty, energy, and unselfishness. Indirect trust requires the use of similarity. The forgetting curve provides a mechanism to consider the most significant and recent feedback from direct and indirect trust. To assess the efficacy of the proposed scheme, we compare it with the well-known trust-based attack detection scheme. Simulation results demonstrate that the proposed scheme has a higher detection rate and low false positive alarms compared to the existing scheme, confirming the applicability of the proposed scheme in green IoT systems.

ANN-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks (VANETs) Using Enhanced AODV.

A vehicular ad hoc network (VANET) is a sophisticated wireless communication infrastructure incorporating centralized and decentralized control mechanisms, orchestrating seamless data exchange among vehicles. This intricate communication system relies on the advanced capabilities of 5G connectivity, employing specialized topological arrangements to enhance data packet transmission. These vehicles communicate amongst themselves and establish connections with roadside units (RSUs). In the dynamic landscape of vehicular communication, disruptions, especially in scenarios involving high-speed vehicles, pose challenges. A notable concern is the emergence of black hole attacks, where a vehicle acts maliciously, obstructing the forwarding of data packets to subsequent vehicles, thereby compromising the secure dissemination of content within the VANET. We present an intelligent cluster-based routing protocol to mitigate these challenges in VANET routing. The system operates through two pivotal phases: first, utilizing an artificial neural network (ANN) model to detect malicious nodes, and second, establishing clusters via enhanced clustering algorithms with appointed cluster heads (CH) for each cluster. Subsequently, an optimal path for data transmission is predicted, aiming to minimize packet transmission delays. Our approach integrates a modified ad hoc on-demand distance vector (AODV) protocol for on-demand route discovery and optimal path selection, enhancing request and reply (RREQ and RREP) protocols. Evaluation of routing performance involves the BHT dataset, leveraging the ANN classifier to compute accuracy, precision, recall, F1 score, and loss. The NS-2.33 simulator facilitates the assessment of end-to-end delay, network throughput, and hop count during the path prediction phase. Remarkably, our methodology achieves 98.97% accuracy in detecting black hole attacks through the ANN classification model, outperforming existing techniques across various network routing parameters.