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Large-scale deployment of fully autonomous vehicles requires a very high degree of robustness to unstructured traffic, and weather conditions, and should prevent unsafe mispredictions. While there are several datasets and benchmarks focusing on segmentation for drive scenes, they are not specifically focused on safety and robustness issues. We introduce the IDD-AW dataset, which provides 5000 pairs of high-quality images with pixel-level annotations, captured under rain, fog, low light, and snow in unstructured driving conditions. As compared to other adverse weather datasets, we provide i.) more annotated images, ii.) paired Near-Infrared (NIR) image for each frame, iii.) larger label set with a 4-level label hierarchy to capture unstructured traffic conditions. We benchmark state-of-the-art models for semantic segmentation in IDD-AW. We also propose a new metric called ''Safe mean Intersection over Union (Safe mIoU)'' for hierarchical datasets which penalizes dangerous mispredictions that are not captured in the traditional definition of mean Intersection over Union (mIoU). The results show that IDD-AW is one of the most challenging datasets to date for these tasks. The dataset and code will be available here: http://iddaw.github.io., Comment: 8 pages excluding references. Accepted in WACV 2024

Strong light-matter coupling has shown great potential for modifying the electro-optical properties of semiconducting materials in recent years. In the strong coupling regime, excitons and cavity photons form new states named exciton-polaritons, with their properties a hybrid of each constituent. Herein, we report strong coupling observed in solution-processed donor:acceptor bulk-heterojunction organic solar cells (OSCs) evidenced by the observed Rabi splitting of ~300 meV and the effects of strong coupling on OSC operations. Combining the transient photovoltage decay measurement and nanosecond transient absorption spectroscopy, our results reveal that the effective charge carrier lifetimes are longer in cavity devices, attributed to the reduced bimolecular recombination. It is also found that access to CT state(s) of higher energy is enabled in cavity devices. This study demonstrates that strong coupling can effectively modify the device- and photo-physics in OSCs and opens a new pathway for engineering more efficient OSCs.

According to the literature, Product reviews are an important source of information for customers to support their buying decision. Product reviews improve customer trust and loyalty. Reviews help customers in understanding what other customers think about a particular product and helps in driving purchase decisions. Therefore, for an e-commerce platform it is important to understand the sentiments in customer reviews to understand their products and services, and it also allows them to potentially create positive consumer interaction as well as long lasting relationships. Reviews also provide innovative ways to market the products for an ecommerce company. One such approach is Nudge Marketing. Nudge marketing is a subtle way for an ecommerce company to help their customers make better decisions without hesitation., Comment: Submitted to a Journal for review

One of the key research themes identified by the Astro2020 decadal survey is Worlds and Suns in Context. The Advanced X-ray Imaging Satellite (AXIS) is a proposed NASA APEX mission that will become the prime high-energy instrument for studying star-planet connections from birth to death. This work explores the major advances in this broad domain of research that will be enabled by the AXIS mission, through X-ray observations of stars in clusters spanning a broad range of ages, flaring M-dwarf stars known to host exoplanets, and young stars exhibiting accretion interactions with their protoplanetary disks. In addition, we explore the ability of AXIS to use planetary nebulae, white dwarfs, and the Solar System to constrain important physical processes from the microscopic (e.g., charge exchange) to the macroscopic (e.g., stellar wind interactions with the surrounding interstellar medium)., Comment: This White Paper is part of a series commissioned for the AXIS Probe Concept Mission

Measurements of the mean free path of Lyman-continuum photons in the intergalactic medium during the epoch of reionization can help constrain the nature of the sources as well as sinks of hydrogen-ionizing radiation. A recent approach to this measurement has been to utilize composite spectra of multiple quasars at $z\sim 6$, and infer the mean free path after correcting the spectra for the presence of quasar proximity zones. This has revealed not only a steep drop in the mean free path from $z=5$ to $z=6$, but also potentially a mild tension with reionization simulations. We critically examine such direct measurements of the mean free path for biases due to quasar environment, incomplete reionization, and quasar proximity zones. Using cosmological radiative transfer simulations of reionization combined with one-dimensional radiative transfer calculations of quasar proximity zones, we find that the bias in the mean free path due to overdensities around quasars is minimal at $z\sim 6$. Patchiness of reionization at this redshift also does not affect the measurements significantly. Fitting our model to the data results in a mean free path of $\lambda_{\mathrm{mfp}}=1.49^{+0.47}_{-0.52}$~pMpc at $z=6$, which is consistent with the recent measurements in the literature, indicating robustness with respect to the modelling of quasar proximity zones. We also compare various ways in which the mean free path has been defined in simulations before the end of reionization. Overall, our finding is that recent measurements of the mean free path appear to be robust relative to several sources of potential bias., Comment: Accepted in MNRAS. Mean free path measurement revised to a higher value with narrower uncertainty using full data covariance

We construct the effective Hamiltonian for hadronic parity violation in strangeness-nonchanging ($\Delta S=0$) processes in next-to-leading order (NLO) in QCD, for all isosectors, and at a renormalization scale of 2 GeV, thus extending our earlier leading-order (LO) analysis. Hadronic parity violation, studied in the context of the low-energy interactions of nucleons and nuclei, exposes the complex interplay of weak and strong interactions in these systems, and thus supports our extension to NLO. Here we exploit the flavor-blind nature of QCD interactions to construct the needed anomalous dimension matrices from those computed in flavor physics, which we then use to refine our effective Hamiltonian and finally our predicted parity-violating meson-nucleon coupling constants, to find improved agreement with few-body experiments.

The cosmic dawn 21-cm signal is enabled by Ly~$\alpha$ photons through a process called the Wouthuysen-Field effect. An accurate model of the signal in this epoch hinges on the accuracy of the computation of the Ly~$\alpha$ coupling, which requires one to calculate the specific intensity of UV radiation from sources such as the first stars. Most traditional calculations of the Ly~$\alpha$ coupling assume a delta-function scattering cross-section, as the resonant nature of the Ly~$\alpha$ scattering makes an accurate radiative transfer solution computationally expensive. Attempts to improve upon this traditional approach using numerical radiative transfer have recently emerged. However, the radiative transfer computation in these treatments suffers from assumptions such as a uniform density of intergalactic gas, zero gas temperature, and absence of gas bulk motion, or numerical approximations such as core skipping. We investigate the role played by these approximations in setting the value of the Ly~$\alpha$ coupling and the 21-cm signal at cosmic dawn. We present results of Monte Carlo radiative transfer simulations, without core skipping, and show that neglecting gas temperature in the radiative transfer significantly underestimates the scattering rate and hence the Ly~$\alpha$ coupling and the 21-cm signal. We also discuss the effect of these processes on the 21-cm power spectrum from the cosmic dawn. This work points the way towards higher-accuracy models to enable better inferences from future measurements., Comment: 20 pages, 14 figures, 2 appendices. Submitted to MNRAS. Comments are welcome

The adoption of diagnosis and prognostic algorithms in healthcare has led to concerns about the perpetuation of bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around modifying models, optimization strategies, and threshold calibration with varying levels of success. Here, we generate a data-centric, model-agnostic, task-agnostic approach to evaluate dataset bias by investigating the relationship between how easily different groups are learned at small sample sizes (AEquity). We then apply a systematic analysis of AEq values across subpopulations to identify and mitigate manifestations of racial bias in two known cases in healthcare - Chest X-rays diagnosis with deep convolutional neural networks and healthcare utilization prediction with multivariate logistic regression. AEq is a novel and broadly applicable metric that can be applied to advance equity by diagnosing and remediating bias in healthcare datasets.

In the recent progress in embodied navigation and sim-to-robot transfer, modular policies have emerged as a de facto framework. However, there is more to compositionality beyond the decomposition of the learning load into modular components. In this work, we investigate a principled way to syntactically combine these components. Particularly, we propose Exploitation-Guided Exploration (XGX) where separate modules for exploration and exploitation come together in a novel and intuitive manner. We configure the exploitation module to take over in the deterministic final steps of navigation i.e. when the goal becomes visible. Crucially, an exploitation module teacher-forces the exploration module and continues driving an overridden policy optimization. XGX, with effective decomposition and novel guidance, improves the state-of-the-art performance on the challenging object navigation task from 70% to 73%. Along with better accuracy, through targeted analysis, we show that XGX is also more efficient at goal-conditioned exploration. Finally, we show sim-to-real transfer to robot hardware and XGX performs over two-fold better than the best baseline from simulation benchmarking. Project page: xgxvisnav.github.io, Comment: Code and results available at http://xgxvisnav.github.io

Erd\H{o}s and West (Discrete Mathematics'85) considered the class of $n$ vertex intersection graphs which have a {\em $d$-dimensional} {\em $t$-representation}, that is, each vertex of a graph in the class has an associated set consisting of at most $t$ $d$-dimensional axis-parallel boxes. In particular, for a graph $G$ and for each $d \geq 1$, they consider $i_d(G)$ to be the minimum $t$ for which $G$ has such a representation. For fixed $t$ and $d$, they consider the class of $n$ vertex labeled graphs for which $i_d(G) \leq t$, and prove an upper bound of $(2nt+\frac{1}{2})d \log n - (n - \frac{1}{2})d \log(4\pi t)$ on the logarithm of size of the class. In this work, for fixed $t$ and $d$ we consider the class of $n$ vertex unlabeled graphs which have a {\em $d$-dimensional $t$-representation}, denoted by $\mathcal{G}_{t,d}$. We address the problem of designing a succinct data structure for the class $\mathcal{G}_{t,d}$ in an attempt to generalize the relatively recent results on succinct data structures for interval graphs (Algorithmica'21). To this end, for each $n$ such that $td^2$ is in $o(n / \log n)$, we first prove a lower bound of $(2dt-1)n \log n - O(ndt \log \log n)$-bits on the size of any data structure for encoding an arbitrary graph that belongs to $\mathcal{G}_{t,d}$. We then present a $((2dt-1)n \log n + dt\log t + o(ndt \log n))$-bit data structure for $\mathcal{G}_{t,d}$ that supports navigational queries efficiently. Contrasting this data structure with our lower bound argument, we show that for each fixed $t$ and $d$, and for all $n \geq 0$ when $td^2$ is in $o(n/\log n)$ our data structure for $\mathcal{G}_{t,d}$ is succinct. As a byproduct, we also obtain succinct data structures for graphs of bounded boxicity (denoted by $d$ and $t = 1$) and graphs of bounded interval number (denoted by $t$ and $d=1$) when $td^2$ is in $o(n/\log n)$., Comment: 21 pages, 5 figures

In this work, we discuss two modifications that can be made to a known variational quantum singular value decomposition algorithm popular in the literature. The first is a change to the objective function which hints at improved performance of the algorithm. The second modification introduces a new way of computing expectation values of general matrices, which is a key step in the algorithm. We then benchmark this modified algorithm and compare the performance of our new objective function with the existing one., Comment: 8 pages, 10 figures, 2 tables

An unconventional bosonization approach that employs a modified Fermi-Bose correspondence is used to obtain the tunneling density of states (TDOS) of fractional quantum Hall (FQHE) edges in the vicinity of a point contact. The chiral Luttinger liquid model is generally used to describe FQHE edge excitations. We introduce a bosonization procedure to study edge state transport in Laughlin states at filling $\nu = 1/m$ with $m$ odd (single edge mode) in the presence of a point contact constriction that brings the top and bottom edges of the sample into close proximity. The unconventional bosonization involves modifying the Fermi-Bose correspondence to incorporate backscattering at the point contact, leaving the action of the theory purely quadratic even in presence of the inhomogeneity. We have shown convincingly in earlier works that this procedure correctly reproduces the most singular parts of the Green functions of the system even when mutual forward scattering between fermions are included. The most singular part of the density-density correlation function (DDCF) relevant to TDOS calculation is computed using a generating functional approach. The TDOS for both the electron tunneling as well as the Laughlin quasiparticle tunneling cases is obtained and is found to agree with previous results in the literature. For electron tunneling the well-known universal power laws for TDOS viz. $ \sim \mbox{ }\omega^{ m-1 }$ and for quasi-particle tunneling the power law $ \sim \mbox{ } \omega^{ \frac{1}{m}-1 } $ are both correctly recovered using our unconventional bosonization scheme. This demonstrates convincingly the utility of the present method which unlike conventional approaches, does not treat the point-contact as an afterthought and yet remains solvable so long as only the most singular parts of the correlation functions are desired., Comment: 14 pages, 2 figures