arXiv subjects

Avtar Singh

Publications and source records attributed to Avtar Singh.

7 recordsLinked to original sources

arXiv2026

Particulate analysis of post-thermal runaway soot of Li-ion battery using X-ray computed tomography

The microstructural characteristics of soot generated during thermal runaway events in lithium-ion batteries have been examined, with a focus on the associated health risks. X-ray computed tomography (Nano-CT) offers advanced 3D imaging for accurate analysis of particle shape, size, and distribution. Its primary benefit is the detection of core-shell structures that contain thin shell of carcinogenic materials. In contrast, traditional techniques like X-ray diffraction can only quantify the mass fraction of these hazardous phases, which is often minimal. Nevertheless, even a small mass fraction of carcinogenic materials on carbonaceous surfaces poses significant health risks when inhaled, potentially compromising internal organ function. This research underscores the need for a deeper understanding of particulate composition to inform safety regulations and respiratory protection measures.

physics.ins-det↗

arXiv2025

HypoGeneAgent: A Hypothesis Language Agent for Gene-Set Cluster Resolution Selection Using Perturb-seq Datasets

Large-scale single-cell and Perturb-seq investigations routinely involve clustering cells and subsequently annotating each cluster with Gene-Ontology (GO) terms to elucidate the underlying biological programs. However, both stages, resolution selection and functional annotation, are inherently subjective, relying on heuristics and expert curation. We present HYPOGENEAGENT, a large language model (LLM)-driven framework, transforming cluster annotation into a quantitatively optimizable task. Initially, an LLM functioning as a gene-set analyst analyzes the content of each gene program or perturbation module and generates a ranked list of GO-based hypotheses, accompanied by calibrated confidence scores. Subsequently, we embed every predicted description with a sentence-embedding model, compute pair-wise cosine similarities, and let the agent referee panel score (i) the internal consistency of the predictions, high average similarity within the same cluster, termed intra-cluster agreement (ii) their external distinctiveness, low similarity between clusters, termed inter-cluster separation. These two quantities are combined to produce an agent-derived resolution score, which is maximized when clusters exhibit simultaneous coherence and mutual exclusivity. When applied to a public K562 CRISPRi Perturb-seq dataset as a preliminary test, our Resolution Score selects clustering granularities that exhibit alignment with known pathway compared to classical metrics such silhouette score, modularity score for gene functional enrichment summary. These findings establish LLM agents as objective adjudicators of cluster resolution and functional annotation, thereby paving the way for fully automated, context-aware interpretation pipelines in single-cell multi-omics studies.

q-bio.QM↗

arXiv2023

Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images

Various strategies for label-scarce object detection have been explored by the computer vision research community. These strategies mainly rely on assumptions that are specific to natural images and not directly applicable to the biological and biomedical vision domains. For example, most semi-supervised learning strategies rely on a small set of labeled data as a confident source of ground truth. In many biological vision applications, however, the ground truth is unknown and indirect information might be available in the form of noisy estimations or orthogonal evidence. In this work, we frame a crucial problem in spatial transcriptomics - decoding barcodes from In-Situ-Sequencing (ISS) images - as a semi-supervised object detection (SSOD) problem. Our proposed framework incorporates additional available sources of information into a semi-supervised learning framework in the form of privileged information. The privileged information is incorporated into the teacher's pseudo-labeling in a teacher-student self-training iteration. Although the available privileged information could be data domain specific, we have introduced a general strategy of pseudo-labeling enhanced by privileged information (PLePI) and exemplified the concept using ISS images, as well on the COCO benchmark using extra evidence provided by CLIP.

cs.CV↗

arXiv2023

Cell-format-dependent mechanical damage in silicon anodes

It is generally believed that silicon-based anodes for Li-ion batteries would benefit from stronger binders, as cyclic volume changes would not disrupt the cohesion of the composite electrode. Here, we put this belief to the proof by testing electrodes containing SiOx particles and an aromatic polyimide binder. We observe that the electrodes can stretch laterally by as much as 6% during the first cycle, indicating that internal stresses are high enough to induce plastic deformation on the copper current collector. Remarkably, no coating delamination is observed. Additional consequences were size-dependent: while pouch-cell-sized electrodes developed wrinkles, coin-cell-sized ones remained mostly smooth. We demonstrate that wrinkling of the current collector damages the electrode coating, inactivating SiOx domains and accelerating capacity fade. This size-dependent performance decay indicates that, in extreme cases, testing outcomes are highly dependent on scale. Novel battery materials may require testing at larger cell formats for complete validation.

physics.chem-ph↗

arXiv2022

Task Scheduling in Cloud Computing Using Hybrid Meta-heuristic: A Review

In recent years with the advent of high bandwidth internet access availability, the cloud computing applications have boomed. With more and more applications being run over the cloud and an increase in the overall user base of the different cloud platforms, the need for highly efficient job scheduling techniques has also increased. The task of a conventional job scheduling algorithm is to determine a sequence of execution for the jobs, which uses the least resources like time, processing, memory, etc. Generally, the user requires more services and very high efficiency. An efficient scheduling technique helps in proper utilization of the resources. In this research realm, the hybrid meta-heuristic algorithms have proven to be very effective in optimizing the task scheduling by providing better cost efficiency than when singly employed. This study presents a systematic and extensive analysis of task scheduling techniques in cloud computing using the various hybrid variants of meta-heuristic methods, like Genetic Algorithm, Tabu Search, Harmony Search, Artificial Bee Colony, Particle Swarm Optimization, etc. In this research review, a separate section discusses the use of various performance evaluation metrics throughout the literature.

cs.DC↗

arXiv2016

Anisotropic superconductivity in La(O,F)BiSeS crystals revealed by field-angle dependent Andreev reflection spectroscopy

From field-angle dependent Andreev reflection spectroscopy on single crystals of La(O,F)BiSeS, which belongs to the recently discovered BiCh 2 (Ch = S, Se) based layered superconductors, we found that the superconductivity in La(O,F)BiSeS is highly anisotropic. We measured a superconducting energy gap of 0.61 meV for current injected along c-axis at 1.5 K. Detailed temperature and magnetic field dependent studies of the gap also reveal the presence of unconventional pairing in La(O,F)BiSeS. We show that the observed anisotropic superconducting properties can be attributed to the anisotropy in the superconducting order parameter with a complex symmetry in superconducting La(O,F)BiSeS.

cond-mat.supr-con↗

arXiv2016

Evidence of a pseudogap driven by competing orders of multi-band origin in the ferromagnetic superconductor Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$

From temperature and magnetic field dependent point-contact spectroscopy on the ferromagnetic superconductor Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$ (bulk superconducting $T_c$ = 2.5 K) we observe (a) a pseudogap in the normal state that sustains to a remarkably high temperature of 40 K and (b) two-fold enhancement of $T_c$ upto 5 K in the point-contact geometry. In addition, Andreev reflection spectroscopy reveals a superconducting gap of 6 meV for certain point-contacts suggesting that the mean field $T_c$ of this system could be approximately 40 K, the onset temperature of pseudo-gap. Our results suggest that quantum fluctuations originating from other competing orders in Sr$_{0.5}$Ce$_{0.5}$FBiS$_2$ forbid a global phase coherence at high temperatures thereby suppressing $T_c$. Apart from the known ordering to a ferromagnetic state, our first-principles calculations reveal nesting of a multi-band Fermi surface and a significant electron-phonon coupling that could result in charge density wave-like instabilities.

cond-mat.supr-con↗