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In this paper, we explore the Weak Gravity Conjecture (WGC) within the context of photon spheres in charged black holes, framed by Perfect Fluid in Rastall Theory. We aim to validate the WGC by identifying the extremality states of these black holes. We highlight the interplay between quantum dynamics and gravitational forces, opening new avenues in high-energy physics and quantum gravity. Our analysis reveals significant system changes with varying perfect fluid intensity $(\alpha)$ and Rastall parameters ( $k$ and $\lambda$ ). For dust field $(\omega=0)$, the WGC is met in extremality $(T=0)$ with $(Q / M)_{\text {ext }}>1$, indicating a black hole due to the presence of photon spheres (PS) with a total charge-1. However, further increases in $k$ and $\lambda$ or decreases $(\alpha)$ lead to $P S=0$ that determines a singularity, not a black hole. We observed that the radiation field $(\omega=1 / 3)$, quintessence field ( $\omega=-2 / 3$ ), and phantom fields field ( $\omega=-4 / 3$ ) also confirmed the WGC and maintaining a total charge of $P S=-1$ in some regions of the free parameters. Our numerical solutions identify points satisfying the WGC, establishing a bridge between quantum and cosmic realms. The results are summarized in Table (I). We also examine Duans topological current $\phi$-mapping theory by analyzing generalized Helmholtz free energy methods to study the topological classes of our black hole. We reveal that for given values of the free parameters, the total topological numbers $(W=0)$ exist for the generalized Helmholtz free energy method for $\omega=0,1 / 3,-2 / 3,-4 / 3$., Comment: 16 Pages, 9 Figures, 1 Table

In this study, we investigate the Weak Gravity Conjecture (WGC) in the context of quantum-corrected AdS-Reissner-Nordstrom (AdS-RN) black holes within Kiselev spacetime. Our focus is on photon spheres, which serve as markers for stable and unstable photon spheres. We confirm the validity of the WGC by demonstrating that quantum corrections do not alter the essential charge-to-mass ratio, thereby supporting the conjecture's universality. Our analysis reveals that black holes with a charge greater than their mass ($Q > M$) possess photon spheres or exhibit a total topological charge of the photon sphere (PS = -1), which upholds the WGC. This finding is significant as it reinforces the conjecture's applicability even in the presence of quantum corrections. Furthermore, we examine various parameter configurations to understand their impact on the WGC. Specifically, we find that configurations with $\omega = -\frac{1}{3}$ and $\omega = -1$ maintain the conjecture, indicating that these values do not disrupt the charge-to-mass ratio required by the WGC. However, for $\omega = -\frac{4}{3}$, the conjecture does not hold, suggesting that this particular parameter value leads to deviations from the expected behavior. These results open new directions for research in quantum gravity, as they highlight the importance of specific parameter values in maintaining the WGC. The findings suggest that while the WGC is robust under certain conditions, there are scenarios where it may be challenged, prompting further investigation into the underlying principles of quantum gravity, Comment: 13 pages, 6 figures, 1 Table

In this paper, we investigate the topological charge and the conditions for the existence of the photon sphere (PS) in Kiselev-AdS black holes within \(f(R, T)\) gravity. We employ two different methods based on Duan's topological current \(\phi\)-mapping theory viz analize of temperature and the generalized Helmholtz free energy methods to study the topological classes of our black hole. By considering the mentioned black hole, we discuss the critical and zero points (topological charges and topological numbers) for different parameters. Our findings reveal that the Kiselev parameter \(\omega\) and the \(f(R, T)\) gravity parameter \(\gamma\) influence the number of topological charges of black holes, leading to novel insights into topological classifications. We observe that for given values of the free parameters, there exist total topological charges (\(Q_{total} = -1\)) for T-method and total topological numbers (\(W = +1\)) for the generalized Helmholtz free energy method. Our research findings elucidate that, in contrast to the scenario where \(\omega = 1/3\), in other cases, increasing the parameter \(\gamma\) increases the number of total topological charges for the black hole. Interestingly, for the phantom field (\(\omega = -4/3\)), we observed that decreasing the parameter \(\gamma\) increases the number of topological charges. Additionally, we study the results for the photon sphere. The studied models clearly reveal that the simultaneous presence of \(\gamma\) and \(\omega\) effectively expands the permissible range for \(\gamma\). In other words, the model can exhibit black hole behavior over a larger domain. Additionally, it is evident that with the stepwise reduction of \(\omega\), the region covered by singularity also diminishes and becomes more restricted. However, An interesting point about all three ranges is the elimination of the forbidden region in this model., Comment: 25 pages, 19 figures, 4 table

Experiment 1. Rooting of quince hardwood cuttings: Rooting success was influenced by both the concentrations of IBA and the selection of rooting media. However, the control group (without IBA) notably enhanced rooting when compared to the various IBA concentrations. Cuttings in the control group (without IBA) and those planted in river sand exhibited notably high percentages of successful rooting, underscoring the importance of the selected planting medium. Experiment 2. Bench grafting of loquat: The success of grafting loquat cutting stocks varied based on grafting dates, types of cuttings, and concentrations of IBA. However, IBA at different concentrations did not have a significant impact. Notably, certain interactions such as grafting on February 20 with loquat stock cuttings, yielded higher percentages of successful graft bud sprouting. Experiment 3. Performance of grafting loquats onto different rootstocks: Grafting success was notably influenced by the selection of rootstock, with loquat rootstock demonstrating superior performance compared to quince. The highest significant levels of successful grafting were attained on February 20, underscoring the crucial role of grafting dates. Experiment 4. Impact of tree stock types on grafting success: Grafting success percentage was higher in loquat tree stock when compared to quince. The consistency of grafting success percentages across three dates underscores the significant influence of rootstock type. Experiment 5. Bench grafting of loquat cutting stocks: Graft bud sprout percentages exhibited variations, with loquat stock cuttings surpassing quince. Grafting success demonstrated a consistent increase from February 20 to March 30, underscoring the importance of selecting appropriate grafting dates.

In-memory computing (IMC) has been shown to be a promising approach for solving binary optimization problems while significantly reducing energy and latency. Building on the advantages of parallel computation, we propose an IMC-compatible parallelism framework inspired by parallel tempering (PT), enabling cross-replica communication to improve the performance of IMC solvers. This framework enables an IMC solver not only to improve performance beyond what can be achieved through parallelization, but also affords greater flexibility for the search process with low hardware overhead. We justify that the framework can be applied to almost any IMC solver. We demonstrate the effectiveness of the framework for the Boolean satisfiability (SAT) problem, using the WalkSAT heuristic as a proxy for existing IMC solvers. The resulting PT-inspired cooperative WalkSAT (PTIC-WalkSAT) algorithm outperforms the traditional WalkSAT heuristic in terms of the iterations-to-solution in 76.3% of the tested problem instances and its na\"ive parallel variant (PA-WalkSAT) does so in 68.4% of the instances. An estimate of the energy overhead of the PTIC framework for two hardware accelerator architectures indicates that in both cases the overhead of running the PTIC framework would be less than 1% of the total energy required to run each accelerator., Comment: 21 pages, 9 figures

In recent years, inflationary models have been studied from different perspectives using different conditions. Now, in this paper, we want to investigate the inverse monomial Inflation $(IMI)$ on the brane. We limit our results to the potentials of the form $\frac{M^{4+\sigma}}{\phi^{\sigma}}$. We calculate some cosmological parameters and then we investigate the satisfaction of the model with some conjectures of the swampland program. We will check the model's compatibility with the refined dS swampland conjecture(RDSSC), further refining the de Sitter swampland conjecture (FRSDC), scalar weak gravity (SWGC), and strong scalar weak gravity conjecture (SSWGC). Despite the incompatibility with (DSSC), We find a specific region of compatibility with other ones which means it satisfied the (FRDSSC) for example with (a=0.982873, b=0.017127, q=2.2). Also, the model is compatible with the (SWGC) with the ($\phi\leq \sigma+2$) condition and consistent with the (SSWGC) with the ($\phi \leq \sqrt{(\sigma+2)(\sigma+1)}$) condition. Since inverse monomial Inflation(IMI) on the brane could satisfy some swampland conjecture simultaneously, it has the potential to be a "real" inflation model of the universe., Comment: 16 pages, 1 Table

The topology of black hole thermodynamics is a fascinating area of study that explores the connections between thermodynamic properties and topological features of black holes. This paper has led to several significant findings: We successfully derive the field equations for $F(R)$-Euler-Heisenberg theory, providing a framework for studying the interplay between modified gravity and non-linear electromagnetic effects. We obtain an analytical solution for a static, spherically symmetric, energy-dependent black hole with constant scalar curvature. Also, our analysis of black holes in F(R)-Euler-Heisenberg gravity's Rainbow reveals significant insights into their topological properties. We identified the total topological charges by examining the normalized field lines along various free parameters. Our findings indicate that the parameters $( R_0 )$ and $( f_{\epsilon} = g_{\epsilon} )$ influence the topological charges. These results are comprehensively summarized in Table I. Additionally, a general overview of Tables II, III, and IV related to the photon sphere of the mentioned black hole reveals that with an increase in $f_{\varepsilon}$, the permissible range of negative $\lambda$ in the first case gradually transitions into a non-permissible region in the third case. On the other hand, it is known that the QED parameter, which measures the strength of nonlinear effects, can be either positive or negative. A positive QED parameter reduces the electric field near the horizon and increases the black hole's mass, whereas a negative QED parameter increases the electric field and decreases the mass. According to the two statements above, it can be concluded that the increase in $f_{\varepsilon}$ actually decreases the strength of the electric field near the horizon and strengthens the effects of gravity., Comment: 21 pages, 11 figures, 4 Tables

Renewable prosumers face the complex challenge of balancing self-sufficiency with seamless grid and market integration. This paper introduces a novel prosumers network framework aimed at mitigating peak loads in Iran, particularly under the uncertainties inherent in renewable energy generation and demand. A cost-oriented integrated prediction and optimization approach is proposed, empowering prosumers to make informed decisions within a distributed contextual stochastic optimization (DCSO) framework. The problem is formulated as a bi-level two-stage multi-time scale optimization to determine optimal operation and interaction strategies under various scenarios, considering flexible resources. To facilitate grid integration, a novel consensus-based contextual information sharing mechanism is proposed. This approach enables coordinated collective behaviors and leverages contextual data more effectively. The overall problem is recast as a mixed-integer linear program (MILP) by incorporating optimality conditions and linearizing complementarity constraints. Additionally, a distributed algorithm using the consensus alternating direction method of multipliers (ADMM) is presented for computational tractability and privacy preservation. Numerical results highlights that integrating prediction with optimization and implementing a contextual information-sharing network among prosumers significantly reduces peak loads as well as total costs., Comment: 10 pages, 26 figure, journal paper

Iran's power grid faces mounting challenges due to the widening gap between rapidly increasing peak demand and lagging sustainable capacity expansion or load management. Prosumers have become key players in reducing grid load and offering valuable flexible services, but their effectiveness is hampered by a lack of knowledge about uncertain parameters and their probability distributions. This study introduces a novel two-stage multi-time scale distributionally robust optimization framework integrated with joint chance constraints to effectively manage the operation of prosumers and their energy sharing to mitigate overall peak load imbalances under uncertainties. In a data-driven setting and by leveraging historical data, the proposed model is reformulated as a tractable second-order conic constrained quadratic programing (SOCP). By considering real-world complexities based on realistic-data such as diverse load profiles and intermittent renewable generation, our approach demonstrates enhanced energy management system performance, even in out-of-sample scenarios. The synergy of distributed energy resources and coordinated flexibility within the network is instrumental in achieving substantial reductions in peak load and improving grid resilience., Comment: 9 pages; 11 figures, journal paper

In this paper, we delve into the intricate thermodynamic topology of quantum-corrected Anti-de Sitter-Reissner-Nordstrm (AdS-RN) black hole within the framework of Kiselev spacetime. By employing the generalized off-shell Helmholtz free energy approach, we meticulously compute the thermodynamic topology of these selected black holes. Furthermore, we establish their topological classifications. Our findings reveal that quantum correction terms influence the topological charges of black holes in Kiselev spacetime, leading to novel insights into topological classifications. Our research findings elucidate that, in contrast to the scenario in which $\omega=0$ and $a=0.7$ with total topological charge $W=0$ and $\omega=-4/3$ with total topological charge $W=-1$, in other cases, the total topological charge for the black hole under consideration predominantly stabilizes at +1. This stabilization occurs with the significant influence of the parameters a, c, and $\omega$ on the number of topological charges. Specifically, when $\omega$ assumes the values of $\omega=-1/3$, $\omega=-2/3$ , $\omega=-1$, the total topological charge consistently be to W = +1., Comment: 17 pages, 5 figures. Accepted for publication in Chinese Physics C

In this paper, we delve into the study of thermodynamics and phase transition of charged Gauss-Bonnet black holes within the context of anti-de Sitter (AdS) space, with particular emphasis on the central charge's role within the dual conformal field theory (CFT). We employ a holographic methodology that interprets the cosmological constant and the Newton constant as thermodynamic variables, leading to the derivation of a modified first law of thermodynamics that incorporates the thermodynamic volume and pressure. Our findings reveal that the central charge of the CFT is intrinsically linked to the variation of these constants, and its stability can be ensured by simultaneous adjustment of these constants. We further explore the phase structures of the black holes, utilizing the free energy. Our research uncovers the existence of a critical value of the central charge, beyond which the phase diagram displays a first-order phase transition between small and large black holes. We also delve into the implications of our findings on the complexity of the CFT. Our conclusions underscore the significant role of the central charge in the holographic thermodynamics and phase transition of charged Gauss-Bonnet black holes. Furthermore, we conclude that while the central charge considered provides suitable and satisfactory solutions for this black hole in 4 and 5 dimensions, it becomes necessary to introduce a unique central charge for this structure of modified gravity. In essence, the central charge in holographic thermodynamics is not a universal value and requires modification in accordance with different modified gravities. Consequently, the physics of the problem will significantly deviate from the one discussed in this article, indicating a rich and complex landscape for future work., Comment: 26 pages, 4 figures, accepted for publication in General Relativity and Gravitation

The Hulth\'{e}n potential is a short-range potential that has been widely used in various fields of physics. In this paper, we investigate the distribution functions for the Hulth\'{e}n potential by using statistical and superstatistical methods. We first review the ordinary statistics and superstatistics methods. We then consider some distribution functions, such as uniform, 2-level, gamma, and log-normal and F distributions. Finally, we investigate the behavior of the Hulth\'{e}n potential for statistical and superstatistical methods and compare the results with each other. We use the Tsallis statistics of the superstatistical system. We conclude that the Tsallis behavior of different distribution functions for the Hulth\'{e}n potential exhibits better results than the statistical method. We examined the thermal properties of the Hulth\'{e}n potential for five different distributions: Uniform, 2-level, Gamma, Log-normal, and F. We plotted the Helmholtz free energy and the entropy as functions of temperature for various values of q. It shows that the two uniform and 2-level distributions have the same results due to the universal relationship and that the F distribution does not become ordinary statistics at q=1. It also reveals that the curves of the Helmholtz free energy and the entropy change their order and behavior as q increases and that some distributions disappear or coincide at certain values of q. One can discuss the physical implications of our results and their applications in nuclear and atomic physics in the future., Comment: 27 pages, 10 figures

In this study, we investigate the dynamics and frame-by-frame phase transition of the first order in black hole thermodynamics. For our analysis, we will utilize the Kramers escape rate. Our focus is on charged anti-de Sitter (AdS) black holes influenced by Kaniadakis and Barrow statistics. The selection of these black holes aims to examine the effects of entropy variation on the dynamics of phase transition and to demonstrate that the Kramers escape rate, as an efficient tool, can effectively represent the dynamic transition from a small to a large black hole within the domain of first-order phase transitions. It is noteworthy that while the transition from small to large black holes should ostensibly dominate the entire process, our results indicate that the escape rate undergoes changes as it passes through the midpoint of the phase transition, leading to a reverse escape phenomenon. The findings suggest that the dynamic phase transition in charged AdS black holes affected by entropy change bears a significant resemblance to the outcomes of models influenced by Bekenstein-Hawking entropy\cite{23}. This similarity in results could serve as an additional motivation to further explore the potential capabilities of Kaniadakis and Barrow statistics in related cosmological fields. These capabilities could enhance our understanding of other cosmological properties, Comment: 20 pages, 9 figures

This paper derives a complete set of quadratic constraints (QCs) for the repeated ReLU. The complete set of QCs is described by a collection of matrix copositivity conditions. We also show that only two functions satisfy all QCs in our complete set: the repeated ReLU and flipped ReLU. Thus our complete set of QCs bounds the repeated ReLU as tight as possible up to the sign invariance inherent in quadratic forms. We derive a similar complete set of incremental QCs for repeated ReLU, which can potentially lead to less conservative Lipschitz bounds for ReLU networks than the standard LipSDP approach. The basic constructions are also used to derive the complete sets of QCs for other piecewise linear activation functions such as leaky ReLU, MaxMin, and HouseHolder. Finally, we illustrate the use of the complete set of QCs to assess stability and performance for recurrent neural networks with ReLU activation functions. We rely on a standard copositivity relaxation to formulate the stability/performance condition as a semidefinite program. Simple examples are provided to illustrate that the complete sets of QCs and incremental QCs can yield less conservative bounds than existing sets.

Domain Generalization techniques aim to enhance model robustness by simulating novel data distributions during training, typically through various augmentation or stylization strategies. However, these methods frequently suffer from limited control over the diversity of generated images and lack assurance that these images span distinct distributions. To address these challenges, we propose FDS, Feedback-guided Domain Synthesis, a novel strategy that employs diffusion models to synthesize novel, pseudo-domains by training a single model on all source domains and performing domain mixing based on learned features. By incorporating images that pose classification challenges to models trained on original samples, alongside the original dataset, we ensure the generation of a training set that spans a broad distribution spectrum. Our comprehensive evaluations demonstrate that this methodology sets new benchmarks in domain generalization performance across a range of challenging datasets, effectively managing diverse types of domain shifts. The implementation is available at: \url{https://github.com/Mehrdad-Noori/FDS.git}.

When ions move through solids, they interact with the solid's constituent atoms and cause them to vibrate around their equilibrium points. This vibration, in turn, modifies the potential landscape through which the mobile ions travel. Because the present-time potential depends on past interactions, the coupling is inherently non-local in time, making its numerical and analytical treatment challenging. For sufficiently slow-moving ions, we linearize the phonon spectrum to show that these non-local effects can be ignored, giving rise to a drag-like force. Unlike the more familiar drag coefficient in liquids, the drag takes on a matrix form due to the crystalline structure of the framework. We numerically simulate trajectories and dissipation rates using both the time-local and non-local formulas to validate our simplification. The time-local formula dramatically reduces the computational cost of calculating the motion of mobile particle through a crystalline framework and clearly connects the properties of the material to the drag experienced by the particle., Comment: 12 pages, 6 figures

Vision-Language Models (VLMs) such as CLIP have yielded unprecedented performance for zero-shot image classification, yet their generalization capability may still be seriously challenged when confronted to domain shifts. In response, we present Weight Average Test-Time Adaptation (WATT) of CLIP, a pioneering approach facilitating full test-time adaptation (TTA) of this VLM. Our method employs a diverse set of templates for text prompts, augmenting the existing framework of CLIP. Predictions are utilized as pseudo labels for model updates, followed by weight averaging to consolidate the learned information globally. Furthermore, we introduce a text ensemble strategy, enhancing overall test performance by aggregating diverse textual cues. Our findings underscore the efficacy of WATT in enhancing performance across diverse datasets, including CIFAR-10-C, CIFAR-10.1, CIFAR-100-C, VisDA-C, and several other challenging datasets, effectively covering a wide range of domain shifts. Notably, these enhancements are achieved without necessitating additional model transformations or trainable modules. Moreover, compared to other Test-Time Adaptation methods, our approach can operate effectively with just a single image. Highlighting the potential of innovative test-time strategies, this research emphasizes their role in fortifying the adaptability of VLMs. The implementation is available at: \url{https://github.com/Mehrdad-Noori/WATT.git}.

In this paper, we investigate the weak cosmic censorship conjecture (WCCC) for the Reissner-Nordstrom (R-N) AdS black hole in a restricted phase space thermodynamics (RPST). Also here, we consider energy flux and equivalence mass-energy principle and examine the weak gravity conjecture (WGC) and the weak cosmic censorship conjecture. The incoming and outgoing energy flux leads to changes in the black hole. In that case, by applying the first law, we examined whether the second law of thermodynamics is valid. And also one can say that, in the case where absorption and superradiance are in the saturated to an equilibrium. Also, by using the thermodynamics of black holes in the restricted phase space, we show that if the black hole is in an extreme or close to an extreme state with radiation and particle absorption, the weak cosmic censorship conjecture is established. In addition, with the help of equivalence mass and energy principle and second-order approximation, in the near extremity, we find that when the black hole radiates and its central charge is greater than the scaled electric charge, the superradiance particles obey the weak gravity conjecture, and this causes the black hole to move further away from its extreme state. But when the particles that obey the weak gravity conjecture are attracted to the black hole when the black hole is very small. Then, in this case, we note that the black hole becomes closer to its extreme state., Comment: 15 pages, 1 table

In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwears. The recommended approach uses the YOLO v7 (You Only Look Once) object detection algorithm to precisely locate these safety items. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a mAP@0.5 score of 87.7\%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research makes a contribution to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry

Commercially impactful quantum algorithms such as quantum chemistry and Shor's algorithm require a number of qubits and gates far beyond the capacity of any existing quantum processor. Distributed architectures, which scale horizontally by networking modules, provide a route to commercial utility and will eventually surpass the capability of any single quantum computing module. Such processors consume remote entanglement distributed between modules to realize distributed quantum logic. Networked quantum computers will therefore require the capability to rapidly distribute high fidelity entanglement between modules. Here we present preliminary demonstrations of some key distributed quantum computing protocols on silicon T centres in isotopically-enriched silicon. We demonstrate the distribution of entanglement between modules and consume it to apply a teleported gate sequence, establishing a proof-of-concept for T centres as a distributed quantum computing and networking platform., Comment: 14 pages, 13 figures

We introduce a pioneering approach to self-supervised learning for point clouds, employing a geometrically informed mask selection strategy called GeoMask3D (GM3D) to boost the efficiency of Masked Auto Encoders (MAE). Unlike the conventional method of random masking, our technique utilizes a teacher-student model to focus on intricate areas within the data, guiding the model's focus toward regions with higher geometric complexity. This strategy is grounded in the hypothesis that concentrating on harder patches yields a more robust feature representation, as evidenced by the improved performance on downstream tasks. Our method also presents a complete-to-partial feature-level knowledge distillation technique designed to guide the prediction of geometric complexity utilizing a comprehensive context from feature-level information. Extensive experiments confirm our method's superiority over State-Of-The-Art (SOTA) baselines, demonstrating marked improvements in classification, and few-shot tasks.

The aqueous extract of Salix spp contains many compounds which may act as root-promoting agents in cuttings. S. alba is a deciduous tree containing variable phytochemicals which are variable throughout the year. So, in this study, one- and two-year-old shoots of S. alba were collected on the 15th of each month in the year 2022, extracted in 2% ethanol at 9 g.L-1, and placed in a water bath at 35 {\deg}C, then they applied to thornless blackberry cuttings for 1.5 hr. The results explained that the highest rooting percentage (66.67%) was obtained in the cuttings soaked in the extract of willow shoots collected on 15th of January. They were not significantly different from control cuttings, but they were different from the cuttings soaked in the extract of willow shoots collected on 15th of August and October (33.33%). The majority of other shoot and root traits were high in the cuttings soaked in the extract of willow shoots collected on 15th of December. The willow shoots collected on 15th of January contained the lowest total phenols (51.4 {\mu}g.mL-1) and total flavonoids (29.07 {\mu}g.mL-1). Moreover, the highest total phenols (57 {\mu}g.mL-1) and IAA (365.17 {\mu}g.mL-1) were recorded in the willow shoots collected on 15th of March, however each total flavonoids (44.96 {\mu}g.mL-1) and salicylic acid (492.61 {\mu}g.mL-1) were the highest in the willow shoots collected on 15th of April. Generally, based on rooting percentage, it is advisable to collect willow shoots on 15th of January and February for extraction and application to the thornless blackberry cuttings.

This paper presents sufficient conditions for the stability and $\ell_2$-gain performance of recurrent neural networks (RNNs) with ReLU activation functions. These conditions are derived by combining Lyapunov/dissipativity theory with Quadratic Constraints (QCs) satisfied by repeated ReLUs. We write a general class of QCs for repeated RELUs using known properties for the scalar ReLU. Our stability and performance condition uses these QCs along with a "lifted" representation for the ReLU RNN. We show that the positive homogeneity property satisfied by a scalar ReLU does not expand the class of QCs for the repeated ReLU. We present examples to demonstrate the stability / performance condition and study the effect of the lifting horizon.

Pre-trained vision-language models (VLMs), exemplified by CLIP, demonstrate remarkable adaptability across zero-shot classification tasks without additional training. However, their performance diminishes in the presence of domain shifts. In this study, we introduce CLIP Adaptation duRing Test-Time (CLIPArTT), a fully test-time adaptation (TTA) approach for CLIP, which involves automatic text prompts construction during inference for their use as text supervision. Our method employs a unique, minimally invasive text prompt tuning process, wherein multiple predicted classes are aggregated into a single new text prompt, used as pseudo label to re-classify inputs in a transductive manner. Additionally, we pioneer the standardization of TTA benchmarks (e.g., TENT) in the realm of VLMs. Our findings demonstrate that, without requiring additional transformations nor new trainable modules, CLIPArTT enhances performance dynamically across non-corrupted datasets such as CIFAR-10, corrupted datasets like CIFAR-10-C and CIFAR-10.1, alongside synthetic datasets such as VisDA-C. This research underscores the potential for improving VLMs' adaptability through novel test-time strategies, offering insights for robust performance across varied datasets and environments. The code can be found at: https://github.com/dosowiechi/CLIPArTT.git

Traditional static methods in phase transition studies, such as the swallowtail bifurcation diagram, provide good insights into the thermodynamics of black holes. However, they practically lose sight of the dynamic aspects and temporal sequence of events. The Kramers escape rate, central to our research, offers a somewhat dynamic approach to phase transition. We examine the free energy landscapes for black holes under the influence of ’dark’ and ’stringy+dark’ structures, assessing how additional parameters affect the escape rates and dynamics of the transition during the first-order phase transition from small to large black holes. In our analysis, we consider the escape rate as a function of the black hole radius and study its variations. We will observe that, on one hand, the escape rate well represents our assumption based on the movement from zero, increasing to a maximum point, and then decreasing back to zero as reactive structures become active during the phase transition interval. However, the critical point in this method is the encounter with a specific and distinct point. This is where the diagram of the direct process (escape rate from small to large black holes) intersects with the reverse process (large to small black holes), becoming equally probable (contact point). The point, which seems improbable at the onset of the phase transition or very negligible, gains more significance as the process progresses. This increase indicates the dominance of a region where the escape rate from larger black holes to smaller ones prevails. The predominance of the reverse process, which increases as we approach the end of the process and is necessarily accompanied by a variation in radius, may be considered as a natural reaction of the black hole against the ’phase change’ action. A reaction which attempting to prevent any uncontrolled radial growth that could jeopardize the stability of the black hole., Comment: 32 pages, 11 figures. The updated version of manuscript includes new calculations, discussions, and optimization of the results

A possible violation of the weak gravity conjecture (WGC) by cosmic censorship is one of the major challenges in the field of general relativity. However, in this paper, we explore the possibility of reconciling the WGC and the WCCC by considering Reissner-Nordstr\"om (R-N) black holes embedded in perfect fluid dark matter (PFDM) in asymptotically flat spacetimes. These two conjectures are seemingly unrelated, but a recent proposal suggested that they are connected surprisingly. In particular, We argue a promising class of valid counterexamples to the WCCC in the four-dimensional Einstein-Maxwell theory, considering a charged black hole when WGC is present. We demonstrate that by imposing certain constraints on the parameters of the metric, the WGC and the WCCC can be compatible. Furthermore, we investigate the properties of the charged black hole in the presence of PFDM for $Q > M$ and present some intriguing figures to test the validity of the WGC and the WCCC simultaneously. When PFDM is absent ($\gamma=0$), the RN black hole either has two event horizons if $Q^2/M^2\leq 1$ or none if $Q^2/M^2> 1$. The second scenario results in a naked singularity, which contradicts the WCCC. But when PFDM is present ($\gamma\neq 0$), the RN black hole has event horizons with regard to Q and M. This implies that the singularity is always covered, and the WGC and the WCCC are fulfilled. Furthermore, we demonstrate that there is a critical value of $\gamma$, called $\gamma_{ext}$, that makes the RN black hole extremal when $\gamma=\gamma_{ext}$. In this situation, the black hole has an event horizon, and the WGC and the WCCC are still fulfilled. We infer that PFDM can make the WGC and the WCCC compatible with the RN black hole and that the WGC and the WCCC agree with each other when PFDM is present., Comment: 17 pages, 2 figures

In this paper, we explore the intriguing interplay between fundamental theoretical physics concepts within the context of charged black holes. Specifically, we focus on the consistency of the weak gravity conjecture (WGC) and weak cosmic censorship conjecture (WCCC) in the thermodynamics of conformal field theory (CFT), and restricted phase space (RPS) for AdS Reissner-Nordstr$\"o$m black holes with a perfect fluid dark matter (RN-PFDM). The WGC ensures that gravity remains the weakest force in the system. Meanwhile, the WCCC addresses the cosmic censorship problem by preventing the violation of fundamental physical laws near the black hole singularity. First, we analyze the RN black hole's free energy in both spaces, revealing a distinctive swallowtail pattern indicative of a first-order phase transition when certain free parameter conditions are met. We explore the WGC across different phase spaces, emphasizing the need for certain conditions in EPST, RPST, and CFT. We demonstrate that PFDM $( \gamma )$ and the radius of AdS ($l$) have a vital role in proving the satisfaction of the WGC. Also, these values have a linear relation with the range compatibility of WGC. The range of compatibility for WGC in RPST and EPST is the same while for CFT, this range is larger than EPST, and RPST. It means somehow the WGC and CFT are more consistent. The WCCC was examined at the critical juncture, confirming its validity with $( f(M_c, Q_c, r_c) = 0 )$. We conclude that the WGC is supported at the critical point of black holes, and the WCCC is also maintained, demonstrating the robustness of these conjectures within the critical ranges of black hole parameters., Comment: 29 pages, 7 figures

Voice based applications are ruling over the era of automation because speech has a lot of factors that determine a speakers information as well as speech. Modern Automatic Speech Recognition (ASR) is a blessing in the field of Human-Computer Interaction (HCI) for efficient communication among humans and devices using Artificial Intelligence technology. Speech is one of the easiest mediums of communication because it has a lot of identical features for different speakers. Nowadays it is possible to determine speakers and their identity using their speech in terms of speaker recognition. In this paper, we presented a method that will provide a speakers geographical identity in a certain region using continuous Bengali speech. We consider eight different divisions of Bangladesh as the geographical region. We applied the Mel Frequency Cepstral Coefficient (MFCC) and Delta features on an Artificial Neural Network to classify speakers division. We performed some preprocessing tasks like noise reduction and 8-10 second segmentation of raw audio before feature extraction. We used our dataset of more than 45 hours of audio data from 633 individual male and female speakers. We recorded the highest accuracy of 85.44%.

The strict selectivity of the blood-brain barrier (BBB) represents one of the most formidable challenges to successful central nervous system (CNS) drug delivery. Computational methods to generate BBB permeable drugs in silico may be valuable tools in the CNS drug design pipeline. However, in real-world applications, BBB penetration alone is insufficient; rather, after transiting the BBB, molecules must bind to a specific target or receptor in the brain and must also be safe and non-toxic. To discover small molecules that concurrently satisfy these constraints, we use multi-objective generative AI to synthesize drug-like BBB-permeable small molecules. Specifically, we computationally synthesize molecules with predicted binding affinity against dopamine receptor D2, the primary target for many clinically effective antipsychotic drugs. After training several graph neural network-based property predictors, we adapt SyntheMol (Swanson et al., 2024), a recently developed Monte Carlo Tree Search-based algorithm for antibiotic design, to perform a multi-objective guided traversal over an easily synthesizable molecular space. We design a library of 26,581 novel and diverse small molecules containing hits with high predicted BBB permeability and favorable predicted safety and toxicity profiles, and that could readily be synthesized for experimental validation in the wet lab. We also validate top scoring molecules with molecular docking simulation against the D2 receptor and demonstrate predicted binding affinity on par with risperidone, a clinically prescribed D2-targeting antipsychotic. In the future, the SyntheMol-based computational approach described here may enable the discovery of novel neurotherapeutics for currently intractable disorders of the CNS., Comment: 20 pages, 4 figures, Generative and Experimental Perspectives for Biomolecular Design Workshop at the 12th International Conference on Learning Representations

Despite their exceptional performance in vision tasks, deep learning models often struggle when faced with domain shifts during testing. Test-Time Training (TTT) methods have recently gained popularity by their ability to enhance the robustness of models through the addition of an auxiliary objective that is jointly optimized with the main task. Being strictly unsupervised, this auxiliary objective is used at test time to adapt the model without any access to labels. In this work, we propose Noise-Contrastive Test-Time Training (NC-TTT), a novel unsupervised TTT technique based on the discrimination of noisy feature maps. By learning to classify noisy views of projected feature maps, and then adapting the model accordingly on new domains, classification performance can be recovered by an important margin. Experiments on several popular test-time adaptation baselines demonstrate the advantages of our method compared to recent approaches for this task. The code can be found at:https://github.com/GustavoVargasHakim/NCTTT.git

Ionic conductivity in solid electrolytes is commonly expected to exhibit Arrhenius dependence on temperature, determined by a well-defined activation energy. Consequently, a standard approach involves calculating this energy using quasi-static methods and using the Arrhenius form to extrapolate the numerical results from one temperature range to another. Despite the ubiquity of this Arrhenius-based modeling, disagreements frequently arise between theory and experiment, and even between different theoretical studies. By considering a tractable minimal model, we elucidate the reason behind the breakdown of the Arrhenius conductivity form. This breakdown is driven by non-trivial phase-space boundaries between conducting and non-conducting regimes, and depends on the kinetic properties of the system., Comment: 7 pages; 5 figures

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI's ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies.

New near-capacity continuous-variable quantum key distribution (CV-QKD) reconciliation schemes are proposed, where both the authenticated classical channel (ClC) and the quantum channel (QuC) for QKD are protected by separate forward error correction (FEC) coding schemes. More explicitly, a new codeword-based - rather than syndrome-based - QKD reconciliation scheme is proposed, where Alice sends an FEC-protected codeword to Bob through a ClC, while Bob sends a separate FEC protected codeword to Alice through a QuC. Upon decoding the codeword received from the other side, the final key is obtained by applying a simple modulo-2 operation to the local codeword and the decoded remote codeword. As a result, first of all, the proposed codeword-based QKD reconciliation system ensures protection of both the QuC and of the ClC. Secondly, the proposed system has a similar complexity at both sides, where both Alice and Bob have an FEC encoder and an FEC decoder. Thirdly, the proposed system makes QKD reconciliation compatible with a wide range of FEC schemes, including polar codes, CCs and irregular convolutional codes (IRCCs), where a near-capacity performance can be achieved for both the QuC and for the ClC.Our simulation results demonstrate that thanks to the proposed regime, the performance improvements of the QuC and of the ClC benefit each other, hence leading to an improved secret key rate (SKR) that inches closer to both the Pirandola-Laurenza-Ottaviani-Banchi (PLOB) bound and to the maximum achieveable rate bound.