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Based on the Newtonian mechanics, in this article, we present a heuristic derivation of the Friedmann equations, providing an intuitive foundation for these fundamental relations in cosmology. Additionally, using the first law of thermodynamics and Euler's equation, we derive a set of equations that, at linear order, coincide with those obtained from the conservation of the stress-energy tensor in General Relativity. This approach not only highlights the consistency between Newtonian and relativistic frameworks in certain limits but also serves as a pedagogical bridge, offering insights into the physical principles underlying the dynamics of the universe., Comment: 10 pages including references; comments are welcome

Extreme weather events and other vulnerabilities are causing blackouts with increasing frequency, disrupting traffic control systems and posing significant challenges to urban mobility. To address this growing concern, we introduce \model{}, a naturalistic driving dataset collected during blackouts at complex intersections. Beacon provides detailed traffic data from two unsignalized intersections in Memphis, TN, including timesteps, origin, and destination lanes for each vehicle over four hours. We analyze traffic demand, vehicle trajectories, and density across different scenarios. We also use the dataset to reconstruct unsignalized, signalized and mixed traffic conditions, demonstrating its utility for benchmarking traffic reconstruction techniques and control methods. To the best of our knowledge, Beacon could be the first public available traffic dataset that captures naturalistic driving behaviors at complex intersections.

Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for developing reliable autonomous driving algorithms. Previous dataset surveys either focused on a limited number or lacked detailed investigation of dataset characteristics. Besides, we analyze the annotation processes, existing labeling tools, and the annotation quality of datasets, showing the importance of establishing a standard annotation pipeline. On the other hand, we thoroughly analyze the impact of geographical and adversarial environmental conditions on the performance of autonomous driving systems. Moreover, we exhibit the data distribution of several vital datasets and discuss their pros and cons accordingly. Additionally, this paper provides a comprehensive analysis of publicly available traffic simulators. In addition to informing about traffic datasets, it is also the goal of this paper to provide context and information on the current capabilities of traffic simulators for their specific contributions to autonomous vehicle simulation and development. Furthermore, this paper discusses future directions and the increasing importance of synthetic data generation in simulators to enhance the training and creation of effective simulations. Finally, we discuss the current challenges and the development trend of future autonomous driving datasets.

SHAPE (Spectro-polarimetry of HAbitable Planet Earth) is an experiment onboard the Chandrayaan-3 Mission, designed to study the spectro-polarimetric signatures of the habitable planet Earth in the near-infrared (NIR) wavelength range (1.0 - 1.7 $\mu$m). The spectro-polarimeter is the only scientific payload (experimental in nature) on the Propulsion Module (PM) of the Chandrayaan-3 mission. The instrument is a compact and lightweight spectro-polarimeter with an Acousto-Optic Tunable Filter (AOTF) at its core. The AOTF operates in the frequency range of 80 MHz to 135 MHz with a power of 0.5 - 2.0 Watts. The two output beams (e-beam and o-beam) from the AOTF are focused onto two InGaAs detectors (pixelated, 1D linear array) with the help of focusing optics. The primary (aperture) optics, with a diameter of $\sim$2 mm, collects the NIR light for input to the AOTF, defining the field of view (FOV) of 2.6$^\circ$. The payload has a mass of 4.8 kg and operates at a power of 25 Watts. This manuscript highlights some of the ground-based results, including the post-launch initial performance of the payload while orbiting around the Moon to observe Earth., Comment: Accepted for publication in Journal of Aerospace Sciences and Technologies

Dark matter, one of the fundamental components of the universe, has remained mysterious in modern cosmology and particle physics, and hence, this field is of utmost importance at present moment. One of the foundational questions is the origin of dark matter which directly links with its creation. In the present article we study the gravitational production of dark matter in two distinct contexts: firstly, when reheating occurs through the gravitational particle production, and secondly, when it is driven by the inflaton's decay. We establish a connection between the reheating temperature and the mass of dark matter, and from the reheating bounds, we determine the range of viable dark matter mass values., Comment: 9 pages including bibliography; text overlap with our previous article arXiv:2411.06190 is now fixed; comments are welcome!

We perform a detailed investigation of interacting phantom cosmology, by applying the powerful method of dynamical system analysis. We consider two well-studied interaction forms, namely one global and one local one, while the novel ingredient of our work is the examination of new potentials for the phantom field. Our analysis shows the existence of saddle matter-dominated points, stable dark-energy dominated points, and scaling accelerating solutions, that can attract the Universe at late times. As we show, some of the stable accelerating scaling attractors, in which dark matter and dark energy can co-exist, alleviating the cosmic coincidence problem, are totally new, even for the previously studied interaction rates, and arise purely from the novel potential forms., Comment: 17 pages including bibliography; 10 tables, 4 figures; comments are welcome

In this article, we study the effect of invisible neutrino decay of the third neutrino state for accelerator neutrino experiments at two different baselines, 1300 km with a liquid argon time projection chamber (LArTPC) detector (similar to DUNE) and 2588 km with a water Cherenkov detector (similar to P2O). For such baselines, the matter effect starts to become important. Our aim is to ascertain the sensitivity to mass hierarchy and octant of $\theta_{23}$ in these two experiments in the presence of a decaying neutrino state. We compare and contrast the results of the two experimental setups. We find that, in general, hierarchy sensitivity decreases in the presence of decay. However, if we consider decay only in the opposite hierarchy (test scenario), in the 2588 km setup, the hierarchy sensitivity with the true hierarchy as IH is larger than the no decay case. We also study the dependence of hierarchy sensitivity with true $\theta_{23}$. We find that the dominant muon background in P2O plays an important role in how the hierarchy sensitivity depends on $\theta_{23}$. The octant sensitivity for both setups increases in the presence of decay except for the LArTPC setup in case true $\theta_{23}=49^\circ$. To understand the octant sensitivity results in the two setups, we check the synergy in sensitivity between electron and muon channels as a function of test $\theta_{23}$. We also study the degeneracies in the test $\theta_{23}-\delta_{CP}$ plane and find that combined analysis of the two setups removes all the degeneracies in the test $\theta_{23}-\delta_{CP}$ plane at $5\sigma$ significance., Comment: v1: 24 pages, 12 captioned figures, 3 tables

The reheating temperature plays a crucial role in the early universe's evolution, marking the transition from inflation to the radiation-dominated era. It directly impacts the number of $e$-folds and, consequently, the observable parameters of inflation, such as the spectral index of scalar perturbations. By establishing a relationship between the gravitational reheating temperature and the spectral index, we can derive constraints on inflationary models. Specifically, the range of viable reheating temperatures imposes bounds on the spectral index, which can then be compared with observational data, such as those from the Planck satellite, to test the consistency of various models with cosmological observations. Additionally, in the context of dark matter production, we demonstrate that gravitational reheating provides a viable mechanism when there is a relationship between the mass of the dark matter particles and the mass of the particles responsible for reheating. This connection offers a pathway to link dark matter genesis with inflationary and reheating parameters, allowing for a unified perspective on early universe dynamics., Comment: 13 pages (including references), 2 figures, 6 tables; comments are welcome

In this work, we focus on two important aspects of modern cosmology: reheating and Hubble constant tension within the framework of a unified model, namely, quintessential inflation connecting the early inflationary era and late-time cosmic acceleration. In the context of reheating, we use instant preheating and gravitational reheating, two viable reheating mechanisms when the evolution of the universe is not affected by an oscillating regime. After obtaining the reheating temperature, we analyze the number of $e$-folds and establish its relationship with the reheating temperature. This allows us to connect, for different quintessential inflation models, the reheating temperature with the spectral index of scalar perturbations, thereby enabling us to constrain its values. In the second part of this article, we explore various alternatives to address the $H_0$ tension, a discrepancy which indicates a possible revision of the $\Lambda$CDM model. Initially, we establish that quintessential inflation alone cannot mitigate the Hubble tension by solely deviating from the concordance model at low redshifts. The introduction of a phantom fluid, capable of increasing the Hubble rate at the present time, becomes a crucial element in alleviating the Hubble tension, resulting in a deviation from the $\Lambda$CDM model only at low redshifts. On a different note, by utilizing quintessential inflation as a source of early dark energy, thereby diminishing the physical size of the sound horizon close to the baryon-photon decoupling redshift, we observe a reduction in the Hubble tension. This alternative avenue, which has the same effect of a cosmological constant changing its scale close to the recombination, sheds light on the nuanced interplay between the quintessential inflation and the Hubble tension, offering a distinct perspective on addressing this cosmological challenge., Comment: 13 pages including bibliography, 5 figures; Invited article from Symmetry; Abstract has been shortened, but the full abstract is kept in the journal version; published version

In this article we calculate the reheating temperature in the cosmological scenarios where heavy scalar particles are gravitationally produced, due to a conformally coupled interaction between a massive scalar quantum field and the Ricci scalar, during the oscillations of the inflaton field. We explore two distinct cases, namely the one in which these particles decay during the domination of the inflaton's energy density and the other one where the decay occurs after this phase. For each scenario, we have derived formulas to calculate the reheating temperatures based on the energy density of the produced particles and their decay rate. We establish bounds for the maximum reheating temperature, defined as the temperature reached by the universe when the decay of gravitationally produced particles concludes at the onset of the radiation-dominated epoch. Finally, we use the Born approximation to find analytic formulas for the reheating temperature., Comment: 15 pages including bibliography and 1 figure; Accepted for publication in Phys. Rev. D

We investigate the possibility of observable neutrinoless double beta decay $( 0 \nu \beta\beta)$ and viable leptogenesis within a low-scale extended inverse seesaw mechanism with additional sterile neutrinos. General effective field theory (EFT) considerations suggest that if there are experimentally observable signatures in $0 \nu \beta \beta$-decay and a lepton asymmetry generated by heavy right-handed neutrino decays, thermal leptogenesis is likely to be unviable. However, in this work, we show that in the context of low-scale leptogenesis, one can obtain the observed baryon asymmetry of the universe and observable signatures of $0 \nu \beta \beta$ decay in the presence of additional sterile neutrinos. In this framework, the light neutrino masses are suppressed by the extended seesaw parameter, $\mu$, thereby allowing for $\mathcal{O}(10\, \mathrm{TeV})$ right-handed (RH) neutrinos, while avoiding small Yukawa couplings as in other neutrino mass models and near degeneracies in the RH neutrino spectrum as required by the low-scale leptogenesis paradigm. Contributions to the $0 \nu \beta \beta$-decay rate from additional sterile neutrinos can be appreciable, while the corresponding contributions to the early universe lepton asymmetry washout rate are suppressed by other parameters not entering the $0 \nu \beta \beta$-decay amplitudes. We show that for keV-MeV scale, sterile neutrinos future ton-scale $0\nu\beta\beta$-decay experiments offer potential signals while maintaining viable leptogenesis., Comment: 11 + 3 pages; 12 figures

In recent years, there has been significant effort to align large language models with human preferences. This work focuses on developing a chatbot specialized in the real estate domain, with an emphasis on incorporating compliant behavior to ensure it can be used without perpetuating discriminatory practices like steering and redlining, which have historically plagued the real estate industry in the United States. Building on prior work, we present a method for generating a synthetic general instruction-following dataset, along with safety data. Through extensive evaluations and benchmarks, we fine-tuned a llama-3-8B-instruct model and demonstrated that we can enhance it's performance significantly to match huge closed-source models like GPT-4o while making it safer and more compliant. We open-source the model, data and code to support further development and research in the community.

Network Intrusion Detection Systems (NIDS) are essential for protecting computer networks from malicious activities, including Denial of Service (DoS), Probing, User-to-Root (U2R), and Remote-to-Local (R2L) attacks. Without effective NIDS, networks are vulnerable to significant security breaches and data loss. Machine learning techniques provide a promising approach to enhance NIDS by automating threat detection and improving accuracy. In this research, we propose an Enhanced Convolutional Neural Network (EnCNN) for NIDS and evaluate its performance using the KDDCUP'99 dataset. Our methodology includes comprehensive data preprocessing, exploratory data analysis (EDA), and feature engineering. We compare EnCNN with various machine learning algorithms, including Logistic Regression, Decision Trees, Support Vector Machines (SVM), and ensemble methods like Random Forest, AdaBoost, and Voting Ensemble. The results show that EnCNN significantly improves detection accuracy, with a notable 10% increase over state-of-art approaches. This demonstrates the effectiveness of EnCNN in real-time network intrusion detection, offering a robust solution for identifying and mitigating security threats, and enhancing overall network resilience., Comment: 7 Pages , 2 figures , 4 Tables , Conference paper

Faithfulness is arguably the most critical metric to assess the reliability of explainable AI. In NLP, current methods for faithfulness evaluation are fraught with discrepancies and biases, often failing to capture the true reasoning of models. We introduce Adversarial Sensitivity as a novel approach to faithfulness evaluation, focusing on the explainer's response when the model is under adversarial attack. Our method accounts for the faithfulness of explainers by capturing sensitivity to adversarial input changes. This work addresses significant limitations in existing evaluation techniques, and furthermore, quantifies faithfulness from a crucial yet underexplored paradigm., Comment: Accepted as a Full Paper at EMNLP 2024 Workshop BlackBoxNLP

We explore constraints on the parameter space of the alternative left-right model originating from the leptonic sector. We analyse focuses on both lepton-flavour conserving observables, particularly the anomalous magnetic moment of the muon, and lepton-flavour-violating processes like $\mu \to e \gamma $ decay and $\mu-e$ conversions in nuclei. While contributions to the anomalous magnetic moment fall below the measured values at 2$\sigma$, current and future experimental sensitivities to flavour-violating branching rations of the Standard Model leptons are expected to impose lower bounds on the mass of the peculiar $SU(2)_R$ gauge boson of the model. This provides complementary constraints relative to existing limits, which are indirect and derived from collider bounds on the mass of the associated neutral gauge boson $Z^\prime$., Comment: 23 pages, 12 figures, 8 tables

The stability of plane Poiseuille flow of a viscous Newtonian fluid in a multilayer channel with anisotropic porous walls is analyzed using the classical modal analysis, the energy method, and the non-modal analysis. The influence of porous wall parameters such as depth ratio (ratio of porous layer thickness to fluid layer thickness) and anisotropic permeability (in terms of meanpermeability and anisotropy parameter) on flow instability are investigated. The modal stability analysis and energy method show that the anisotropy parameter can stabilize the flow, whereas the depth ratio and mean permeability effects can cause destabilization. Furthermore, the energy budget analysis reveals that the energy production term transfers energy to the disturbance from the base flow through the Reynolds stress, amplifying the kinetic energies in all layers and, hence, enhancing the growth rates of the unstable modes. A significant disparity is observed between the critical Reynolds number obtained through modal analysis and the one determined by the energy method, which confirms the growth of transient perturbation kinetic energy. Specifically, transient growth and response functions are examined to understand the flow response to initial conditions and external excitation (receptivity analysis). It turns out that there is substantial transient growth at a sub-critical Reynolds number. These transient growths are greatly enhanced by increasing the mean permeability or the depth ratio and reducing the anisotropy parameter. The optimal perturbations leading to the maximum transient amplification are determined for various parameters, including counter-rotating vortices (rolls) and streaks.

Computationally hard problems based on coding theory, such as the syndrome decoding problem, have been used for constructing secure cryptographic schemes for a long time. Schemes based on these problems are also assumed to be secure against quantum computers. However, these schemes are often considered impractical for real-world deployment due to large key sizes and inefficient computation time. In the recent call for standardization of additional post-quantum digital signatures by the National Institute of Standards and Technology, several code-based candidates have been proposed, including LESS, CROSS, and MEDS. These schemes are designed on the relatively new zero-knowledge framework. Although several works analyze the hardness of these schemes, there is hardly any work that examines the security of these schemes in the presence of physical attacks. In this work, we analyze these signature schemes from the perspective of fault attacks. All these schemes use a similar tree-based construction to compress the signature size. We attack this component of these schemes. Therefore, our attack is applicable to all of these schemes. In this work, we first analyze the LESS signature scheme and devise our attack. Furthermore, we showed how this attack can be extended to the CROSS signature scheme. Our attacks are built on very simple fault assumptions. Our results show that we can recover the entire secret key of LESS and CROSS using as little as a single fault. Finally, we propose various countermeasures to prevent these kinds of attacks and discuss their efficiency and shortcomings., Comment: 35 pages including appendix and bibliography

Combining high peak and high average power has long been a key challenge of ultrafast laser technology, crucial for applications such as laser-plasma acceleration and strong-field physics. A promising solution lies in post-compressed ytterbium lasers, but scaling these to high pulse energies presents a major bottleneck. Post-compression techniques, particularly Herriott-type multi-pass cells (MPCs), have enabled large peak power boosts at high average powers but their pulse energy acceptance reaches practical limits defined by setup size and coating damage threshold. In this work, we address this challenge and demonstrate a novel type of compact, energy-scalable MPC (CMPC). By employing a novel MPC configuration and folding the beam path, the CMPC introduces a new degree of freedom for downsizing the setup length, enabling compact setups even for large pulse energies. We experimentally and numerically verify the CMPC approach, demonstrating post-compression of 8 mJ pulses from 1 ps down to 51 fs in atmospheric air using a cell roughly 45 cm in length at low fluence values. Additionally, we discuss the potential for energy scaling up to 200 mJ with a setup size reaching 2.5 m. Our work presents a new approach to high-energy post-compression, with up-scaling potential far beyond the demonstrated parameters. This opens new routes for achieving the high peak and average powers necessary for demanding applications of ultrafast lasers., Comment: 18 pages, 13 figures

Since an ion-beam is a viable attractive alternative to other material surface patterning techniques like an electron-beam, a study of the structure, composition and dimension of patterned lines created on surfaces of Si and SrTiO3 wafers with a Ga ion-beam was carried out. A combination of top-view SEM and cross-sectional STEM imaging and EDX spectroscopy applied to the patterned lines showed that the total ion-dose (DI) is the key parameter affecting the characteristics of the patterned lines, which can be adjusted by the degree of overlap between adjacent spots, beam dwell time at each spot, and the number of beam-passes for every beam size and current. A strong dependence between the used ion-doses and the patterned lines sizes was observed and quantified. At higher ion-doses (DI > 10^15 ions/cm^2), the Ga ions remove part of the material in the exposed area creating channels surrounded with amorphized regions whereas, at lower ion-doses only amorphization occurs, creating a ridge on the wafer surface. Further, to pattern lines with similar sizes, an order of magnitude different ion-doses might be required in different materials as was the case with Si and SrTiO3. The quantification of line sizes showed that with this approach, lines as fine as 10 nm can be reproducibly patterned and characterized on the surfaces of materials, when low ion-doses are used, typically in the range of 10^14-10^15 ions/cm^2.

Modern Education is not \textit{Modern} without AI. However, AI's complex nature makes understanding and fixing problems challenging. Research worldwide shows that a parent's income greatly influences a child's education. This led us to explore how AI, especially complex models, makes important decisions using Explainable AI tools. Our research uncovered many complexities linked to parental income and offered reasonable explanations for these decisions. However, we also found biases in AI that go against what we want from AI in education: clear transparency and equal access for everyone. These biases can impact families and children's schooling, highlighting the need for better AI solutions that offer fair opportunities to all. This chapter tries to shed light on the complex ways AI operates, especially concerning biases. These are the foundational steps towards better educational policies, which include using AI in ways that are more reliable, accountable, and beneficial for everyone involved., Comment: Technical Report, UROP-2023

Modular architectures are a promising approach to scale quantum devices to the point of fault tolerance and utility. Modularity is particularly appealing for superconducting qubits, as monolithically manufactured devices are limited in both system size and quality. Constructing complex quantum systems as networks of interchangeable modules can overcome this challenge through `Lego-like' assembly, reconfiguration, and expansion, in a spirit similar to modern classical computers. First prototypical superconducting quantum device networks have been demonstrated. Interfaces that simultaneously permit interchangeability and high-fidelity operations remain a crucial challenge, however. Here, we demonstrate a high-efficiency interconnect based on a detachable cable between superconducting qubit devices. We overcome the inevitable loss in a detachable connection through a fast pump scheme, enabling inter-module SWAP efficiencies at the 99%-level in less than 100 ns. We use this scheme to generate high-fidelity entanglement and operate a distributed logical dual-rail qubit. At the observed ~1% error rate, operations through the interconnect are at the threshold for fault-tolerance. These results introduce a modular architecture for scaling quantum processors with reconfigurable and expandable networks., Comment: 15 pages, 9 figures, 1 table

Recent Baryon Acoustic Oscillation (BAO) measurements released by DESI, when combined with Cosmic Microwave Background (CMB) data from Planck and two different samples of Type Ia supernovae (Pantheon-Plus and DESY5) reveal a preference for Dynamical Dark Energy (DDE) characterized by a present-day quintessence-like equation of state that crossed into the phantom regime in the past. A core ansatz for this result is assuming a linear Chevallier-Polarski-Linder (CPL) parameterization $w(a) = w_0 + w_a (1-a)$ to describe the evolution of the DE equation of state (EoS). In this paper, we test if and to what extent this assumption impacts the results. To prevent broadening uncertainties in cosmological parameter inference and facilitate direct comparison with the baseline CPL case, we focus on 4 alternative well-known models that, just like CPL, consist of only two free parameters: the present-day DE EoS ($w_0$) and a parameter quantifying its dynamical evolution ($w_a$). We demonstrate that the preference for DDE remains robust regardless of the parameterization: $w_0$ consistently remains in the quintessence regime, while $w_a$ consistently indicates a preference for a dynamical evolution towards the phantom regime. This tendency is significantly strengthened by DESY5 SN measurements. By comparing the best-fit $\chi^2$ obtained within each DDE model, we notice that the linear CPL parameterization is not the best-fitting case. Among the models considered, the EoS proposed by Barboza and Alcaniz consistently leads to the most significant improvement., Comment: 44 pages, 7 figures, 7 tables. V2: additional references, more details and discussion on the results and their interpretation, added a new Appendix presenting additional constraints on interesting properties of the DE EoS across the different models analyzed. Version accepted for publication in JCAP

In this article, we investigate a coupled phantom dark-energy cosmological model in which the coupling term between a phantom scalar field with an exponential potential and a pressureless dark-matter fluid is motivated by the warm inflationary paradigm. Using methods of qualitative analysis of dynamical systems, complemented by numerical solutions of the evolution equations, we study the late-time behavior of our model. We show that contrary to the uncoupled scenario, the coupled phantom model admits accelerated scaling solutions. However, they do not correspond to a final state of the universe's evolution and, therefore, cannot be used to solve the cosmological coincidence problem. Furthermore, we show that, for certain coupling parameter values, the total equation-of-state parameter's asymptotic behavior is significantly changed when compared to the uncoupled scenario, allowing for solutions less phantom even for steeper potentials of the phantom scalar field., Comment: 13 pages including references, 3 tables and 4 captioned figures; version accepted by Phys. Rev. D

The measurements of the cosmic microwave background (CMB) have played a significant role in understanding the nature of dark energy. In this article, we investigate the dynamics of the dark energy equation of state, utilizing high-precision CMB data from multiple experiments. We begin by examining the Chevallier-Polarski-Linder (CPL) parametrization, a commonly used and recognized framework for describing the dark energy equation of state. We then explore the general Exponential parametrization, which incorporates CPL as its first-order approximation, and extensions of this parametrization that incorporate nonlinear terms. We constrain these scenarios using CMB data from various missions, including the Planck 2018 legacy release, the Wilkinson Microwave Anisotropy Probe (WMAP), the Atacama Cosmology Telescope (ACT), and the South Pole Telescope (SPT), as well as combinations with low-redshift cosmological probes such as Baryon Acoustic Oscillations (BAO) and the Pantheon sample. While the $\Lambda$CDM cosmology remains consistent within the 68\% confidence level, we observe that the extensions of the CPL parametrization are indistinguishable for Planck data. However, for ACT and SPT data, the inclusion of additional terms begins to reveal a peak in $w_{\rm a, DE}$ that was previously unconstrained., Comment: 14 pages, 6 tables and 4 captioned figures; version published in Phys. Dark. Univ

Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events., Comment: IEEE 25th International Conference on Information Reuse and Integration for Data Science (IEEE IRI-2024)

This research compares PDF parsing and Optical Character Recognition (OCR) methods for extracting Nepali content from PDFs. PDF parsing offers fast and accurate extraction but faces challenges with non-Unicode Nepali fonts. OCR, specifically PyTesseract, overcomes these challenges, providing versatility for both digital and scanned PDFs. The study reveals that while PDF parsers are faster, their accuracy fluctuates based on PDF types. In contrast, OCRs, with a focus on PyTesseract, demonstrate consistent accuracy at the expense of slightly longer extraction times. Considering the project's emphasis on Nepali PDFs, PyTesseract emerges as the most suitable library, balancing extraction speed and accuracy.

Modern Internet of Things (IoT) applications generate enormous amounts of data, making data-driven machine learning essential for developing precise and reliable statistical models. However, data is often stored in silos, and strict user-privacy legislation complicates data utilization, limiting machine learning's potential in traditional centralized paradigms due to diverse data probability distributions and lack of personalization. Federated learning, a new distributed paradigm, supports collaborative learning while preserving privacy, making it ideal for IoT applications. By employing cryptographic techniques, IoT systems can securely store and transmit data, ensuring consistency. The integration of federated learning and blockchain is particularly advantageous for handling sensitive data, such as in healthcare. Despite the potential of these technologies, a comprehensive examination of their integration in edge-fog-cloud-based IoT computing systems and healthcare applications is needed. This survey article explores the architecture, structure, functions, and characteristics of federated learning and blockchain, their applications in various computing paradigms, and evaluates their implementations in healthcare.

Predicting the spatiotemporal variation in streamflow along with uncertainty quantification enables decision-making for sustainable management of scarce water resources. Process-based hydrological models (aka physics-based models) are based on physical laws, but using simplifying assumptions which can lead to poor accuracy. Data-driven approaches offer a powerful alternative, but they require large amount of training data and tend to produce predictions that are inconsistent with physical laws. This paper studies a constrained reasoning and learning (CRL) approach where physical laws represented as logical constraints are integrated as a layer in the deep neural network. To address small data setting, we develop a theoretically-grounded training approach to improve the generalization accuracy of deep models. For uncertainty quantification, we combine the synergistic strengths of Gaussian processes (GPs) and deep temporal models (i.e., deep models for time-series forecasting) by passing the learned latent representation as input to a standard distance-based kernel. Experiments on multiple real-world datasets demonstrate the effectiveness of both CRL and GP with deep kernel approaches over strong baseline methods.

For a prime $p$ and a commutative ring $R$ with unity, let $W(R)$ denote the ring of $p$-typical Witt vectors. The ring $W(R)$ is endowed with a Verschiebung operator $W(R)\xrightarrow{V}W(R)$ and a Teichm\"{u}ller map $R\xrightarrow{\langle \ \rangle}W(R)$. One of the properties satisfied by $V, \langle \ \rangle$ is that the map $R \to W(R)$ given by $x\mapsto V\langle x^p\rangle - p\langle x \rangle$ is an additive map. In this paper we show that for $p\neq 2$, this property essentially characterises the functor $W$. Unlike other characterisations, this only uses the group structure on $W(R)$ and hence is suitable for generalising to the non-commutative setup. We give a conjectural characterisation of Hesselholt's functor of $p$-typical Witt vectors using a universal property for $p\neq 2$. Moreover we provide evidence for this conjecture., Comment: 13 pages, comments are welcome

The framework of three-flavor neutrino oscillation is a well-established phenomenon, but results from the short-baseline experiments, such as the Liquid Scintillator Neutrino Detector (LSND) and MiniBooster Neutrino Experiment (MiniBooNE), hint at the potential existence of an additional light neutrino state characterized by a mass-squared difference of approximately $1\,\rm eV^2$. The new neutrino state is devoid of all Standard Model (SM) interactions, commonly referred to as a 'sterile' state. In addition, a sterile neutrino with a mass-squared difference of $10^{-2}$ $\rm eV^2$ has been proposed to improve the tension between the results obtained from the Tokai to Kamioka (T2K) and the NuMI Off-axis $\nu_e$ Appearance (NO$\nu$A) experiments. Further, the non-observation of the predicted upturn in the solar neutrino spectra below 8 MeV can be explained by postulating an extra light sterile neutrino state with a mass-squared difference around $10^{-5} \rm eV^2$. The hypothesis of an additional light sterile neutrino state introduces four distinct mass spectra depending on the sign of the mass-squared difference. In this paper, we discuss the implications of the above scenarios on the observables that depend on the absolute mass of the neutrinos, namely the sum of the light neutrino masses $(\Sigma)$ from cosmology, the effective mass of the electron neutrino from beta decay $(m_{\beta})$, and the effective Majorana mass $( m_{\beta\beta})$ from neutrinoless double beta decay. We show that some scenarios can be disfavored by the current constraints of the above variables. The implications for projected sensitivity of Karlsruhe Tritium Neutrino Experiment (KATRIN) and future experiments like Project-8, next Enriched Xenon Observatory (nEXO) have been discussed., Comment: 32 pages (with appendix), 45 figures and 10 tables

Optically confined colloidal particles, when placed in close proximity, form a dissipatively coupled system through hydrodynamic interactions. Here, we demonstrate that these interactions can be harnessed to design systems with non-trivial and highly tunable non-equilibrium characteristics, directly quantifiable from experimental data. Furthermore, we clarify that such interactions do not modify the underlying potential energy function, nor do they violate the energy balance at the level of individual trajectories, as was believed earlier. Moreover, they offer new opportunities for tailored control and design of mesoscale systems with emergent and targeted nonequilibrium properties., Comment: 13 pages, 6 figures (supplementary informations included)

The ISMR profoundly impacts over a billion people across the region. ISMR extremes have been linked to the ENSO and modulated by the Indian Ocean Dipole (IOD). ISMR of 2022 displayed intriguing spatial patterns: above-normal precipitation over the south peninsula and central India, normal over Northwest India, and below-normal over East and NE India. In 2022, La Nina conditions associated with a negative IOD (nIOD), were prevalent over the equatorial Pacific Ocean (PO) and IO. This study investigates the often-overlooked Oceanic subsurface contribution to large-scale atmospheric convection over the tropical IO. By undertaking a comprehensive analysis, we find that strong equatorial westerly wind anomalies prevailed over the equatorial IO during co-occurring years generating eastward propagating downwelling Kelvin waves which deepens the D20 in the eastern equatorial IO. The Kelvin waves then propagates into BoB and gets reflected from southern tip of India as westward propagating Rossby waves deepening the D20 and causing low level wind convergence in the Northern Arabian Sea(NAS). We identify two centres of low-level wind convergence, one over NAS and another over Maritime Continent during co-occurrence years. These wind convergence centres play a pivotal role in channeling moisture towards their core, also, significantly deepen D20, increase the Ocean heat content and thus maintaining warmer SSTs over area of conversions. Together, these interrelated factors create an environment that is conducive for enhanced convective activity over the zone of convergence, enhancing and sustaining the convective conditions. This study underscores the significant contribution of ocean dynamics in shaping large-scale atmospheric convection during the co-occurrence years, highlighting the significance of considering broader Oceanic variables in comprehending and forecasting monsoonal variability., Comment: 47 pages, 10 main figures, 08 supplementary figures; under review in Climate Dynamics

We present a comprehensive reassessment of the state of Interacting Dark Energy (IDE) cosmology, namely models featuring a non-gravitational interaction between Dark Matter (DM) and Dark Energy (DE). To achieve high generality, we extend the dark sector physics by considering two different scenarios: a non-dynamical DE equation of state $w_0\neq-1$, and a dynamical $w(a)=w_0+w_a(1-a)$. In both cases, we distinguish two different physical regimes resulting from a phantom or quintessence equation of state. To circumvent early-time superhorizon instabilities, the energy-momentum transfer should occur in opposing directions within the two regimes, resulting in distinct phenomenological outcomes. We study quintessence and phantom non-dynamical and dynamical models in light of two independent Cosmic Microwave Background (CMB) experiments - the Planck satellite and the Atacama Cosmology Telescope. We analyze CMB data both independently and in combination with Supernovae (SN) distance moduli measurements from the Pantheon-Plus catalog and Baryon Acoustic Oscillations (BAO) from the SDSS-IV eBOSS survey. Our results update and extend the state-of-the-art analyses, significantly narrowing the parameter space allowed for these models and limiting their overall ability to reconcile cosmological tensions. Although considering different combinations of data leaves some freedom to increase $H_0$ towards the value measured by the SH0ES collaboration, our most constraining dataset (CMB+BAO+SN) indicates that fully reconciling the tension solely within the framework of IDE remains challenging., Comment: 21 pages, 4 figures, 9 tables. V2: additional references added, clarified some aspects of the results, their interpretation, and implications. Version accepted for publication in PRD