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Evaporation Residue (ER) cross-sections and ER-gated $\gamma$-ray fold distributions are measured for the $^{32}$S + $^{154}$Sm nuclear reaction above the Coulomb barrier at six different beam energies from 148 to 191 MeV. $\gamma$-ray multiplicities and spin distributions are extracted from the ER-gated fold distributions. The ER cross-sections measured in the present work are found to be much higher than what was reported in a previous work using a very different target-projectile ($^{48}$Ti + $^{138}$Ba) combination, leading to the same compound nucleus $^{186}$Pt, with much less mass asymmetry in the entrance channel than the present reaction. This clearly demonstrates the effect of the entrance channel on ER production cross-section. The ER cross-sections measured in the present work are compared with the results of both the statistical model calculations and the dynamical model calculations. Statistical model calculations have been performed to generate a range of parameter space for both the barrier height and Kramers' viscosity parameter over which the ER cross-section data can be reproduced. The calculations performed using the dinuclear system (DNS) model reproduce the data considering both complete and incomplete fusion processes. DNS calculations indicate the need for the inclusion of incomplete fusion channel at higher energies to reproduce the ER cross-sections., Comment: 13 pages, 18 figures

We study the problem of aligning a video that captures a local portion of an environment to the 2D LiDAR scan of the entire environment. We introduce a method (VioLA) that starts with building a semantic map of the local scene from the image sequence, then extracts points at a fixed height for registering to the LiDAR map. Due to reconstruction errors or partial coverage of the camera scan, the reconstructed semantic map may not contain sufficient information for registration. To address this problem, VioLA makes use of a pre-trained text-to-image inpainting model paired with a depth completion model for filling in the missing scene content in a geometrically consistent fashion to support pose registration. We evaluate VioLA on two real-world RGB-D benchmarks, as well as a self-captured dataset of a large office scene. Notably, our proposed scene completion module improves the pose registration performance by up to 20%., Comment: 8 pages

This paper presents a method to learn hand-object interaction prior for reconstructing a 3D hand-object scene from a single RGB image. The inference as well as training-data generation for 3D hand-object scene reconstruction is challenging due to the depth ambiguity of a single image and occlusions by the hand and object. We turn this challenge into an opportunity by utilizing the hand shape to constrain the possible relative configuration of the hand and object geometry. We design a generalizable implicit function, HandNeRF, that explicitly encodes the correlation of the 3D hand shape features and 2D object features to predict the hand and object scene geometry. With experiments on real-world datasets, we show that HandNeRF is able to reconstruct hand-object scenes of novel grasp configurations more accurately than comparable methods. Moreover, we demonstrate that object reconstruction from HandNeRF ensures more accurate execution of downstream tasks, such as grasping and motion planning for robotic hand-over and manipulation. Homepage: https://samsunglabs.github.io/HandNeRF-project-page/, Comment: In ICRA 2024; 13 pages including the supplementary material, 8 tables, 12 figures

Existing robotic systems have a clear tension between generality and precision. Deployed solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single task, lacking precise generalization, i.e., the ability to solve many tasks without compromising on precision. This paper explores solutions for precise and general pick-and-place. In precise pick-and-place, i.e. kitting, the robot transforms an unstructured arrangement of objects into an organized arrangement, which can facilitate further manipulation. We propose simPLE (simulation to Pick Localize and PLacE) as a solution to precise pick-and-place. simPLE learns to pick, regrasp and place objects precisely, given only the object CAD model and no prior experience. We develop three main components: task-aware grasping, visuotactile perception, and regrasp planning. Task-aware grasping computes affordances of grasps that are stable, observable, and favorable to placing. The visuotactile perception model relies on matching real observations against a set of simulated ones through supervised learning. Finally, we compute the desired robot motion by solving a shortest path problem on a graph of hand-to-hand regrasps. On a dual-arm robot equipped with visuotactile sensing, we demonstrate pick-and-place of 15 diverse objects with simPLE. The objects span a wide range of shapes and simPLE achieves successful placements into structured arrangements with 1mm clearance over 90% of the time for 6 objects, and over 80% of the time for 11 objects. Videos are available at http://mcube.mit.edu/research/simPLE.html ., Comment: 33 pages, 6 figures, 2 tables, submitted to Science Robotics

General scene reconstruction refers to the task of estimating the full 3D geometry and texture of a scene containing previously unseen objects. In many practical applications such as AR/VR, autonomous navigation, and robotics, only a single view of the scene may be available, making the scene reconstruction task challenging. In this paper, we present a method for scene reconstruction by structurally breaking the problem into two steps: rendering novel views via inpainting and 2D to 3D scene lifting. Specifically, we leverage the generalization capability of large visual language models (Dalle-2) to inpaint the missing areas of scene color images rendered from different views. Next, we lift these inpainted images to 3D by predicting normals of the inpainted image and solving for the missing depth values. By predicting for normals instead of depth directly, our method allows for robustness to changes in depth distributions and scale. With rigorous quantitative evaluation, we show that our method outperforms multiple baselines while providing generalization to novel objects and scenes.

The excellent sensitivity and optimum resolution of LoTSS DR2 at 144 MHz has enabled us to discover a giant radio galaxy (J1225+4011) with three distinct episodes of jet activity, making it a member of a class of objects called triple-double radio galaxies (TDRGs). The source extends overall up to 1.35 Mpc in projected size, with the second episode extending to 572 kpc, and the inner episode to 118 kpc. J1225+4011 is only the fourth radio source showing a triple-double radio structure. All four sources have overall sizes greater than 700 kpc, making them giants. We also present the LoTSS 144 MHz map of the TDRG J0929+4146 and report its updated size. Lastly, we have summarised and discussed the radio properties of all TDRGs for the first time to understand their growth and evolution. Our observations suggest that the power of their jets may decrease with time., Comment: Accepted for publication in MNRAS Letters. 2 tables and 5 figures. Comments are welcome

Environmental effects, such as stellar fly-bys and external irradiation, are thought to affect the evolution of protoplanetary disks in clustered star formation. Previous ALMA images at 225 GHz of the ISO-Oph 2 binary revealed a peculiar morphology in the disk of the primary, perhaps due to a possible fly-by with the secondary. Here we report on new ALMA continuum observations of this system at 97.5 GHz, 145 GHz and 405 GHz, which reveal strong morphological variations. Multi-frequency positional alignment allows to interpret these spectral variations in terms of underlying physical conditions. ISO-Oph 2A is remarkably offset from the centroid of its ring, at all frequencies, and the disk is lopsided, pointing at gravitational interactions. However, the dust temperature also varies in azimuth, with two peaks whose direction connects with HD 147889, the earliest-type star in the Ophiuchus complex, suggesting that it is the dominant heat source. The stellar environment of ISO-Oph 2 appears to drive both its density structure and its thermal balance.Simon Casassus, Lucas Cieza, Miguel C\'arcamo, \'Alvaro Ribas, Valentin Christiaens, Abigali Rodr\'iguez-Jim\'enez, Carla Arce-Tord, Trisha Bhowmik, Prachi Chavan, Camilo Gonz\'alez-Ruilova, Rafael Mart\'inez-Brunner, Valeria Guidotti, Mauricio Leiva, Comment: accepted in MNRAS

ADITYA-L1 is India's first dedicated mission to observe the sun and its atmosphere from a halo orbit around L1 point. Visible emission line coronagraph (VELC) is the prime payload on board at Aditya-L1 to observe the sun's corona. VELC is designed as an internally occulted reflective coronagraph to meet the observational requirements of wide wavelength band and close to the solar limb (1.05 Ro). Images of the solar corona in continuum and spectra in three emission lines 5303{\AA} [Fe xiv], 7892{\AA} [Fe xi] and 10747 [Fe xiii] obtained with high cadence to be analyzed using software algorithms automatically. A reasonable part of observations will be made in synoptic mode, those, need to be analyzed and results made available for public use. The procedure involves the calibration of instrument and detectors, converting the images into fits format, correcting the images and spectra for the instrumental effects, align the images etc. Then, develop image processing algorithms to detect the occurrence of energetic events using continuum images. Also derive physical parameters, such as temperature and velocity structure of solar corona using emission line observations. Here, we describe the calibration of detectors and the development of software algorithms to detect the occurrence of CMEs and analyze the spectroscopic data.

The research on code-mixed data is limited due to the unavailability of dedicated code-mixed datasets and pre-trained language models. In this work, we focus on the low-resource Indian language Marathi which lacks any prior work in code-mixing. We present L3Cube-MeCorpus, a large code-mixed Marathi-English (Mr-En) corpus with 10 million social media sentences for pretraining. We also release L3Cube-MeBERT and MeRoBERTa, code-mixed BERT-based transformer models pre-trained on MeCorpus. Furthermore, for benchmarking, we present three supervised datasets MeHate, MeSent, and MeLID for downstream tasks like code-mixed Mr-En hate speech detection, sentiment analysis, and language identification respectively. These evaluation datasets individually consist of manually annotated \url{~}12,000 Marathi-English code-mixed tweets. Ablations show that the models trained on this novel corpus significantly outperform the existing state-of-the-art BERT models. This is the first work that presents artifacts for code-mixed Marathi research. All datasets and models are publicly released at https://github.com/l3cube-pune/MarathiNLP .

We present Generalized LoRA (GLoRA), an advanced approach for universal parameter-efficient fine-tuning tasks. Enhancing Low-Rank Adaptation (LoRA), GLoRA employs a generalized prompt module to optimize pre-trained model weights and adjust intermediate activations, providing more flexibility and capability across diverse tasks and datasets. Moreover, GLoRA facilitates efficient parameter adaptation by employing a scalable, modular, layer-wise structure search that learns individual adapter of each layer. Originating from a unified mathematical formulation, GLoRA exhibits strong transfer learning, few-shot learning and domain generalization abilities, as it adapts to new tasks through not only weights but also additional dimensions like activations. Comprehensive experiments demonstrate that GLoRA outperforms all previous methods in natural, specialized, and structured vision benchmarks, achieving superior accuracy with fewer parameters and computations. The proposed method on LLaMA-1 and LLaMA-2 also show considerable enhancements compared to the original LoRA in the language domain. Furthermore, our structural re-parameterization design ensures that GLoRA incurs no extra inference cost, rendering it a practical solution for resource-limited applications. Code and models are available at: https://github.com/Arnav0400/ViT-Slim/tree/master/GLoRA., Comment: Technical report. v2: Add LLaMA-1&2 results. Code and models at https://github.com/Arnav0400/ViT-Slim/tree/master/GLoRA

We introduce and study Dirichlet-type spaces $\mathcal D(\mu_1, \mu_2)$ of the unit bidisc $\mathbb D^2,$ where $\mu_1, \mu_2$ are finite positive Borel measures on the unit circle. We show that the coordinate functions $z_1$ and $z_2$ are multipliers for $\mathcal D(\mu_1, \mu_2)$ and the complex polynomials are dense in $\mathcal D(\mu_1, \mu_2).$ Further, we obtain the division property and solve Gleason's problem for $\mathcal D(\mu_1, \mu_2)$ over a bidisc centered at the origin. In particular, we show that the commuting pair $\mathscr M_z$ of the multiplication operators $\mathscr M_{z_1},$ $\mathscr M_{z_2}$ on $\mathcal D(\mu_1, \mu_2)$ defines a cyclic toral $2$-isometry and $\mathscr M^*_z$ belongs to the Cowen-Douglas class ${\bf B}_1(\mathbb D^2_r)$ for some $r >0.$ Moreover, we formulate a notion of wandering subspace for commuting tuples and use it to obtain a bidisc analog of Richter's representation theorem for cyclic analytic $2$-isometries. In particular, we show that a cyclic analytic toral $2$-isometric pair $T$ with cyclic vector $f_0$ is unitarily equivalent to $\mathscr M_z$ on $\mathcal D(\mu_1, \mu_2)$ if and only if $\ker T^*,$ spanned by $f_0,$ is a wandering subspace for $T.$, Comment: Preliminary draft; 22 pages

The B-operators (abbreviation for Brownian-type operators) are upper triangular 2x2 block matrix operators that satisfy certain algebraic constraints. The purpose of this paper is to characterize the weak, the strongand the uniform stability of B-operators, respectively. This is achieved by giving equivalent conditions for the convergence of powers of a B-operator in each of the corresponding topologies. A more subtle characterization is obtained for B-operators with subnormal (2,2) entry. The issue of the strong stability of the adjoint of a B-operator is also discussed., Comment: 15 pages