Possible interaction between dark energy and dark matter has previously shown promise in alleviating the clustering tension, without exacerbating the Hubble tension, when Baryon Acoustic Oscillations (BAO) data from the Sloan Digital Sky Survey (SDSS) DR16 is combined with Cosmic Microwave Background (CMB) and Type-Ia Supernovae (SNIa) data sets. With the recent Dark Energy Spectroscopic Instrument (DESI) BAO DR2, there is now a compelling need to re-evaluate this scenario. We combine DESI DR2 with Planck 2018 and Pantheon+ SNIa data sets to constrain interacting dark matter dark energy models, accounting for interaction effects in both the background and perturbation sectors. Our results exhibit similar trends to those observed with SDSS, albeit with improved precision, reinforcing the consistency between the two BAO data sets. In addition to offering a resolution to the $S_8$ tension, in the phantom-limit, the dark energy equation of state exhibits an early-phantom behaviour, aligning with DESI DR2 findings, before transitioning to $w\sim-1$ at lower redshifts, regardless of the DE parametrization. However, the statistical significance of excluding $w=-1$ is reduced compared to their non-interacting counterparts.

One of the key features of the $R^2$-gravity is the embedding of a scalar field, scalaron, into the gravity sector. The scalaron interacts with the Standard Model (SM) matter fields through Planck-suppressed couplings. If the scalaron serves as a viable dark matter (DM) candidate, it can account for the lack of evidence of DM interactions beyond gravity in experimental and observational probes to date. The realization of the scalaron, as a cold DM candidate, depends on an induced trilinear interaction with the SM Higgs, despite its suppressed coupling strength. Here, we introduce a Higgs non-minimal coupling to gravity that additionally contributes to the induced trilinear interaction with its existing competing part, originated from the $R^2$-gravity. We study the interplay between these two contributions in the early universe, which determines both the initial conditions and evolution of the scalaron, leading to cold DM behavior at a later epoch. The trilinear interaction vanish identically for certain combinations of the Higgs non-minimal coupling and the scalaron mass, thereby setting the scalaron density through misalignment mechanism, similar to axions. Consequently, we find that the observed DM relic density is obtained for a scalaron mass between $1.38$ keV and $0.7$ MeV. The lower limit on the mass stems from the LHC constraints on the Higgs non-minimal coupling, whereas the upper bound arises from INTEGRAL/SPI limits on the excess gamma-ray flux from possible scalaron decays to two photons.

Rising urban populations have led to a surge in vehicle use and made traffic monitoring and management indispensable. Acoustic traffic monitoring (ATM) offers a cost-effective and efficient alternative to more computationally expensive methods of monitoring traffic such as those involving computer vision technologies. In this paper, we present MVD and MVDA: two open datasets for the development of acoustic traffic monitoring and vehicle-type classification algorithms, which contain audio recordings of moving vehicles. The dataset contain four classes- Trucks, Cars, Motorbikes, and a No-vehicle class. Additionally, we propose a novel and efficient way to accurately classify these acoustic signals using cepstrum and spectrum based local and global audio features, and a multi-input neural network. Experimental results show that our methodology improves upon the established baselines of previous works and achieves an accuracy of 91.98% and 96.66% on MVD and MVDA Datasets, respectively. Finally, the proposed model was deployed through an Android application to make it accessible for testing and demonstrate its efficacy.

We investigate uncertainties in the estimation of the Hubble constant ($H_0$) arising from Gaussian Process (GP) reconstruction, demonstrating that the choice of kernel introduces systematic variations comparable to those arising from different cosmological models. To address this limitation, we introduce the Generalized Gaussian Process (Gen GP) framework, in which the Matérn smoothness parameter $\nu$ is treated as a free parameter, allowing for data-driven kernel optimization. Using the cosmic chronometer Hubble data, we find that while standard GP with $\Lambda$CDM mean function exhibits noticeable reconstruction differences between optimized and marginalized approaches, particularly at $z > 1$, Gen GP maintains methodological consistency. In Gen GP, slight increases in $\chi^2$ per degree of freedom relative to standard GP, for both the zero-mean and $\Lambda$CDM prior mean cases, reflect added flexibility rather than performance degradation. Our results emphasize that robust cosmological inference requires treating kernel parameters as free variables and implementing full Bayesian marginalization to avoid artificial precision from fixed hyperparameters. As machine learning becomes central to cosmological discovery, the Gen GP framework provides a principled approach to model-independent inference that properly accounts for methodological uncertainties while maintaining necessary flexibility for reliable parameter estimation.

We do a careful investigation of the prospects of dark energy (DE) interacting with cold dark matter in alleviating the $S_8$ clustering tension. To this end, we consider various well-known parametrizations of the DE equation of state (EoS) and consider perturbations in both the dark sectors, along with an interaction term. Moreover, we perform a separate study for the phantom and non-phantom regimes. Using cosmic microwave background (CMB), baryon acoustic oscillations, and Type Ia supernovae data sets, constraints on the model parameters for each case have been obtained and a generic reduction in the $H_0-\sigma_{8,0}$ correlation has been observed, both for constant and dynamical DE EoS. This reduction, coupled with a significant negative correlation between the interaction term and $\sigma_{8,0}$, contributes to easing the clustering tension by lowering $\sigma_{8,0}$ to somewhere in between the early CMB and late-time clustering measurements for the phantom regime, for almost all the models under consideration. Additionally, this is achieved without exacerbating the Hubble tension. In this regard, the interacting Chevallier-Polarski-Linder and Jassal-Bagla-Padmanabhan models perform the best in relaxing the $S_8$ tension to <1\sigma. However, for the non-phantom regime the $\sigma_{8,0}$ tension tends to have worsened, which reassures the merits of phantom DE from latest data. We further investigate the role of redshift space distortion data sets and find an overall reduction in tension, with a $\sigma_{8,0}$ value relatively closer to the CMB value. We finally check whether further extensions of this scenario, such as the inclusion of the sound speed of DE and warm dark matter interacting with DE, can have some effects.

Molecular Property Prediction (MPP) plays a pivotal role across diverse domains, spanning drug discovery, material science, and environmental chemistry. Fueled by the exponential growth of chemical data and the evolution of artificial intelligence, recent years have witnessed remarkable strides in MPP. However, the multifaceted nature of molecular data, such as molecular structures, SMILES notation, and molecular images, continues to pose a fundamental challenge in its effective representation. To address this, representation learning techniques are instrumental as they acquire informative and interpretable representations of molecular data. This article explores recent AI/-based approaches in MPP, focusing on both single and multiple modality representation techniques. It provides an overview of various molecule representations and encoding schemes, categorizes MPP methods by their use of modalities, and outlines datasets and tools available for feature generation. The article also analyzes the performance of recent methods and suggests future research directions to advance the field of MPP.

The $\sim 5\sigma$ mismatch between the value of the Hubble parameter measured by SH0ES and the one inferred from the inverse distance ladder (IDL) constitutes the biggest tension afflicting the standard model of cosmology, which could be pointing to the need of physics beyond $\Lambda$CDM. In this paper we study the background history required to solve the $H_0$ tension if we consider standard prerecombination physics, paying special attention to the role played by the data on baryon acoustic oscillations (BAO) employed to build the IDL. We show that the anisotropic BAO data favor an ultra-late-time (phantom-like) enhancement of $H(z)$ at $z\lesssim 0.2$, accompanied by a transition in the absolute magnitude of supernovae of Type Ia $M(z)$ in the same redshift range. This agrees with previous findings in the literature. The effective dark energy (DE) density must be smaller than in the standard model at higher redshifts. Instead, when angular BAO data (claimed to be less subject to model dependencies) is employed in the analysis, we find that the increase of $H(z)$ starts at much higher redshifts, typically in the range $z\sim 0.5-0.8$. In this case,$M(z)$ could experience also a transition (although much smoother) and the effective DE density becomes negative at $z\gtrsim 2$. Both scenarios require a violation of the weak energy condition (WEC), but leave an imprint on completely different redshift ranges and might also have a different impact on the perturbed observables. They allow for the effective crossing of the phantom divide. Finally, we employ two alternative methods to show that current data from cosmic chronometers do not exclude the violation of the WEC, but do not add any strong evidence in its favor neither. Our work puts the accent on the utmost importance of the choice of the BAO data set in the study of the possible solutions to the $H_0$ tension.

We investigate strong gravitational lensing using magnetized Kerr black holes (MKBHs), which are accurate Kerr-Bertotti-Robinson solutions for Kerr black holes in a uniform magnetic field with additional magnetic field strength $B$ apart from mass $M$ and spin $a$. Unlike previous magnetized spacetimes, the MKBH geometry is Petrov type D, devoid of conical singularities, allowing photons to reach asymptotic infinity and making the concept astrophysically feasible. We use the strong deflection limit formalism to calculate the photon sphere radius, critical impact parameter, deflection angle, and lensing observables including the image position $\theta_\infty$, angular separation $s$ and relative magnification $r_{\text{mag}}$, as well as their relationships with the parameters $a$ and $B$. Our results reveal that the relativistic image's photon sphere and angular size increase with $B$, whereas lensing observables deviate significantly from the Kerr scenario. For M87*, with $a=0.9$, the angular position of relativistic images increases from $10.8~\mu$as (Kerr) to $12.02~\mu$as, and the time delay between the first two images increases from $158.5$ h to $176$ h at $B=0.4$. Similarly, for Sgr A*, the image position increases from $14.4~\mu$as to $16~\mu$as, with time delays enhanced by approximately $0.7$ minutes. The relative magnification $r_{\text{mag}}$ grows with $B$ and deviates by $0.53$ from Kerr black holes at $B=0.4$. Our findings highlight strong gravitational lensing as a powerful tool to probe the presence of magnetic fields around astrophysical black holes, and in particular, we demonstrate that the MKBH spacetime enables constraints on the parameters $a$ and $B$.

We explore the implications of incorporating an Anti-de Sitter (AdS) vacua in the Dark Energy (DE) sector using the recent DESI BAO measurements in combination with Planck-2018 CMB, Pantheon-Plus(+SH0ES) supernovae and KiDS weak lensing data. We show that the presence of a {\it Negative Cosmological Constant} (\Lambda < 0, nCC) together with an evolving part (modelled by the CPL parametrisation) in DE sector allows a {\it non-phantom} region for the DE in the constrained parameter space consistent with different observational data. This essentially solves the problem of {\it phantom} behaviour in the DE sector which is difficult to obtain through reasonable field theory. The implications nCC in the DE sector for different cosmological tensions are also studied. Our findings highlight the importance of the presence of AdS in the DE sector for theoretical model building, especially in the context of quantum gravity theories, e.g. string theory.

The recently obtained hairy Kerr black holes, due to additional sources or surrounding fluid, like dark matter, with conserved energy-momentum tensor, have a deviation $\alpha$ and primary hair $l_0$, apart from rotation parameter $a$ and mass $M$. In the wake of the \textit{Event Horizon Telescope} (\textit{EHT}) observations of the supermassive black hole M87*, a recent surge in interest in black hole shadows suggests comparing the black holes in general relativity (GR) and modified theories of gravity (MoG) to assess these models' differences. Motivated by this, we take on an extensive study of the rotating hairy Kerr black holes, which encompasses, in particular cases, the Kerr black hole ($\alpha=0$). We investigate ergosphere and shadows of the black holes to infer that their size and shape are affected due to the $l_0$ and are found to harbour a richer chaotic structure. In particular, the hairy Kerr black holes possess smaller size but more distorted shadows when compared with Kerr black holes. We also estimate the parameters $l_0$ and $a$ associated with hairy Kerr black holes using the shadow observables. The inferred circularity deviation $\Delta C \leq 0.1$ for the M87* black hole is satisfied, whereas shadow angular diameter $\theta_{d}=42 \pm 3 \mu as$, within $1 \sigma$ region, for a given choice of $\alpha$, places bounds on the parameters $a$ and $l_0$. Interestingly, the shadow axial ratio obeying 1< D_x \lesssim 4/3 is in agreement with the \textit{EHT} results and thus eventuates in the hairy Kerr black holes being suitable candidates for astrophysical black holes.

Recent experimental progresses in controlling classical and quantum fluids have made it possible to realize acoustic analogues of gravitational black holes, where a flowing fluid provides an effective spacetime on which sound waves propagate, demonstrating Hawking-like radiation and superradiance. We propose the exciting possibility that new hydrodynamic systems might provide insights to help resolve mysteries associated with quantum gravity, including the black hole information-loss paradox and the removal of spacetime singularities.

We introduce three-parameter extensions of the two-parameter minimal Akhtar-Hossain (mAH) parametrization, termed modified minimal AH (MmAH1,2), which provide greater flexibility in the dynamics of dark energy. These models are compared with $\Lambda$CDM, $w$CDM, mAH, CPL, and three-parameter CPL (CPL-$w_{\rm b}$) using a joint data set of the CMB compressed likelihood, DESI DR2, Pantheon$+$ supernovae, $H(z)$ measurements, and redshift-space distortions. While the common cosmological parameters remain stable across models, CPL and the MmAH1,2 yield modest improvements in fit, with $\Delta\chi^2\simeq -6$ to $-7$ and corresponding $\Delta{\rm AIC}\simeq -1$ to $-2$ relative to $\Lambda$CDM, suggesting a mild preference for dynamical dark energy. Statistical consistency with $\Lambda$CDM is quantified via the Mahalanobis distance in one, two, and three dimensional parameter subspaces. In 1D, the strongest deviation occurs for MmAH1 ($2.5\sigma$), followed by CPL ($2.3\sigma$). In 2D, CPL-$w_{\rm b}$ shows the highest discrepancy ($2.3\sigma$), while other models remain at the $1.7$-$2.1\sigma$ level. In 3D, CPL-$w_{\rm b}$ continues to exhibit the largest tension ($\sim2\sigma$), though this arises in the presence of very strong correlations, particularly between $w_{\rm a}$ and $w_{\rm b}$, whereas the MmAH extensions display slightly weaker but still non-negligible discrepancies ($1.4$-$1.8\sigma$). Overall, these results indicate consistent evidence for departures from $\Lambda$CDM.

The detection of hate speech in political discourse is a critical issue, and this becomes even more challenging in low-resource languages. To address this issue, we introduce a new dataset named IEHate, which contains 11,457 manually annotated Hindi tweets related to the Indian Assembly Election Campaign from November 1, 2021, to March 9, 2022. We performed a detailed analysis of the dataset, focusing on the prevalence of hate speech in political communication and the different forms of hateful language used. Additionally, we benchmark the dataset using a range of machine learning, deep learning, and transformer-based algorithms. Our experiments reveal that the performance of these models can be further improved, highlighting the need for more advanced techniques for hate speech detection in low-resource languages. In particular, the relatively higher score of human evaluation over algorithms emphasizes the importance of utilizing both human and automated approaches for effective hate speech moderation. Our IEHate dataset can serve as a valuable resource for researchers and practitioners working on developing and evaluating hate speech detection techniques in low-resource languages. Overall, our work underscores the importance of addressing the challenges of identifying and mitigating hate speech in political discourse, particularly in the context of low-resource languages. The dataset and resources for this work are made available at this https URL.

We study the robustness and physical implications of a set of characteristic redshifts that capture key features of the late-time Universe. Using both model-independent reconstructions as well as different dark energy (DE) parameterizations, we show that these redshifts remain stable across cosmological models and reconstruction algorithm, making them reliable geometric anchors of the expansion history. Moreover, the Alcock-Paczyński corrections at these redshift anchors are found to be unity with high statistical significance, making them natural isotropy points in the comoving distance-redshift relation. We also find that certain redshifts anchors (z < 1) coincide with epochs where strong deviations from the Planck $\Lambda$CDM baseline are apparent irrespective of DE parametrisation like CPL or reconstruction algorithm, indicating their potential as probes of new physics in cosmological evolution. Finally, we demonstrate, for the first time, that a Raychaudhuri Equation Informed Reconstruction Algorithm, substantially enhances the precision of the inferred distance measures and the Hubble expansion rate as well as results tighter constraints in the DE parameter space. These results demonstrate that combining geometric reconstruction with physics-informed kinematic information offers a powerful and consistent algorithm to probe new physics in the late-time dynamics of our Universe.

We perform a model-independent reconstruction of the angular diameter distance ($D_{A}$) using the Multi-Task Gaussian Process (MTGP) framework with DESI-DR1 BAO and DES-SN5YR datasets. We calibrate the comoving sound horizon at the baryon drag epoch $r_d$ to the Planck best-fit value, ensuring consistency with early-universe physics. With the reconstructed $D_A$ at two key redshifts, $z\sim 1.63$ (where $D_{A}^{\prime} =0$) and at $z\sim 0.512$ (where $D_{A}^{\prime} = D_{A}$), we derive the expansion rate of the Universe $H(z)$ at these redshifts. Our findings reveal that at $z\sim 1.63$, the $H(z)$ is fully consistent with the Planck-2018 $\Lambda$CDM prediction, confirming no new physics at that redshift. However, at $z \sim 0.512$, the derived $H(z)$ shows a more than $5\sigma$ discrepancy with the Planck-2018 $\Lambda$CDM prediction, suggesting a possible breakdown of the $\Lambda$CDM model as constrained by Planck-2018 at this lower redshift. This emerging $\sim 5\sigma$ tension at $z\sim 0.512$, distinct from the existing ``Hubble Tension'', may signal the first strong evidence for new physics at low redshifts.

Hubble constant $H_0$ and weighted amplitude of matter fluctuations $S_8$ determinations are biased to higher and lower values, respectively, in the late Universe with respect to early Universe values inferred by the Planck collaboration within flat $\Lambda$CDM cosmology. If these anomalies are physical, i.e. not due to systematics, they naively suggest that $H_0$ decreases and $S_8$ increases with effective redshift. Here, subjecting matter density today $\Omega_{m}$ to a prior, corresponding to a combination of Planck CMB and BAO data, we perform a consistency test of the Planck-$\Lambda$CDM cosmology and show that $S_8$ determinations from $f \sigma_8(z)$ constraints increase with effective redshift. Due to the redshift evolution, a $\sim 3 \sigma$tension in the$S_8$ parameter with Planck at lower redshifts remarkably becomes consistent with Planck within $1 \sigma$ at high redshifts. This provides corroborating support for an $S_8$ discrepancy that is physical in origin. We further confirm that the flat $\Lambda$CDM model is preferred over a theoretically ad hoc model with a jump in $S_8$ at a given redshift. In the absence of the CMB+BAO $\Omega_m$ prior, we find that $> 3 \sigma$ tensions with Planck in low redshift data are ameliorated by shifts in the parameters in high redshift data. Results here and elsewhere suggest that the $\Lambda$CDM cosmological parameters are redshift dependent. Fitting parameters that evolve with redshift is a recognisable hallmark of model breakdown.

We investigate the shadow features of magnetized Kerr black holes (MKBHs) using a deviation parameter $B$ that captures the effect of an external magnetic field on spacetime geometry. These spacetimes, of Petrov type $D$, are asymptotically non-flat. We use the separability of the Hamilton--Jacobi equation to generate null geodesics and examine the crucial impact parameters for unstable photon orbits that define the black hole shadow. We carefully study how the magnetic field intensity $B$ and spin parameter $a$ influence shadow morphology, discovering that increasing $B$ enlarges the shadow while also introducing additional distortions, especially at high spins. We compute the shadow observables -- area $A$ and oblateness $D$ -- and create contour plots in the parameter space $$(a/M, \, BM)$$ to facilitate parameter estimation. We also investigate the dependence of the shadow on observer position, specifically altering the radial coordinate $r_{\mathrm{O}}$ and inclination angle $\theta$. The results reveal that as $B$ increases, so does the shadow size, and the distortion is affected by both spin and observer orientation. For far observers, the shadow approaches its asymptotic shape, but finite-distance observers perceive substantial deviations. Our findings demonstrate that MKBH shadows encode clear imprints of magnetic deviations, thereby offering a potential avenue to distinguish Kerr from non-Kerr spacetimes and to probe magnetic effects in the strong-gravity regime.

We study the collision of two particles with equal masses moving in the equatorial plane near horizon of the rotating regular Ay\'on-Beato-Garc\'ia (ABG) black hole (BH) and calculate the center-of-mass (CM) energy for the colliding particles for both extremal and non-extremal cases. It turns out that CM energy depends not only on rotation parameter $a$ but also on charge $Q$. Particularly for the extremal rotating regular ABG BH, CM energy of two colliding particles could be arbitrarily high for critical angular momentum of particles. Furthermore, we also show that, for a non-extremal BH, there exist a finite upper limit of CM energy, which changes with charge $Q$. A comparison, with Kerr and Kerr-Newman black holes, is included.

The $\Lambda$ Cold Dark Matter ($\Lambda$CDM) cosmological model has been highly successful in predicting cosmic structure and evolution, yet recent precision measurements have highlighted discrepancies, especially in the Hubble constant inferred from local and early-Universe data. Gamma-ray bursts (GRBs) present a promising alternative for cosmological measurements, capable of reaching higher redshifts than traditional distance indicators. This work leverages GRBs to refine cosmological parameters independently of the $\Lambda$CDM framework. Using the Platinum compilation of long GRBs, we calibrate the Dainotti relations-empirical correlations among GRB luminosity properties-as standard candles through artificial neural networks (ANNs). We analyze both the 2D and 3D Dainotti calibration relations, leveraging an ANN-driven Markov Chain Monte Carlo approach to minimize scatter in the calibration parameters, thereby achieving a stable Hubble diagram. This ANN-based calibration approach offers advantages over Gaussian processes, avoiding issues such as kernel function dependence and overfitting. Our results emphasize the need for model-independent calibration approaches to address systematic challenges in GRB luminosity variability, ultimately extending the cosmic distance ladder in a robust way. By addressing redshift evolution and reducing systematic uncertainties, GRBs can serve as reliable high-redshift distance indicators, offering critical insights into current cosmological tensions.

Conventional calibration of Baryon Acoustic Oscillations (BAO) data relies on estimation of the sound horizon at drag epoch $r_d$ from early universe observations by assuming a cosmological model. We present a recalibration of two independent BAO datasets, SDSS and DESI, by employing deep learning techniques for model-independent estimation of $r_d$, and explore the impacts on $\Lambda$CDM cosmological parameters. Significant reductions in both Hubble ($H_0$) and clustering ($S_8$) tensions are observed for both the recalibrated datasets. Moderate shifts in some other parameters hint towards further exploration of such data-driven approaches.