3,628 results on '"Malhotra, P"'
Search Results
2. The Sensitivity to initial conditions of the Co-orbital outcomes of Lunar Ejecta
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Castro-Cisneros, Jose Daniel, Malhotra, Renu, and Rosengren, Aaron J.
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Astrophysics - Earth and Planetary Astrophysics - Abstract
Lunar ejecta, produced by meteoroidal impacts, have been proposed for the origin of the near-Earth asteroid (469219) Kamo'oalewa, supported by its unusually Earth-like orbit and L-type reflectance spectrum (Sharkey et al., 2021). In a recent study (Castro-Cisneros et al. 2023), we found with N-body numerical simulations that the orbit of Kamo'oalewa is dynamically compatible with rare pathways of lunar ejecta captured into Earth's co-orbital region, persistently transitioning between horseshoe and quasi-satellite (HS-QS) states. Subsequently, Jiao et al. (2024) found with hydrodynamic and N-body simulations that the geologically young lunar crater Giordano Bruno generated up to 300 Kamo'oalewa-sized escaping fragments, and up to three of those could have become Earth co-orbitals. However, these results are based upon specific initial conditions of the major planets in the Solar System, close to the current epoch. In particular, over megayear time spans, Earth's eccentricity undergoes excursions up to five times its current value, potentially affecting the chaotic orbital evolution of lunar ejecta and their capture into Earth's co-orbital regions. In the present work, we carry out additional numerical simulations to compute the statistics of co-orbital outcomes across different launch epochs, representative of the full range of Earth's eccentricity values. Our main results are as follows: Kamo'oalewa-like co-orbital outcomes of lunar ejecta vary only slightly across the range of Earth's orbital eccentricity, suggesting no privileged ejecta launching epoch for such objects; the probability of co-orbital outcomes decreases rapidly with increasing launch speed, but long-lived HS-QS states are favored at higher launch speeds.
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- 2024
3. CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks
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Paliwal, Bhawna, Saini, Deepak, Dhawan, Mudit, Asokan, Siddarth, Natarajan, Nagarajan, Aggarwal, Surbhi, Malhotra, Pankaj, Jiao, Jian, and Varma, Manik
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Computer Science - Information Retrieval - Abstract
Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approaches for such tasks, but they score each query-item independently, ignoring the joint context of other relevant items. This leads to sub-optimal ranking accuracy and high computational costs. In response, we propose Cross-encoders with Joint Efficient Modeling (CROSS-JEM), a novel ranking approach that enables transformer-based models to jointly score multiple items for a query, maximizing parameter utilization. CROSS-JEM leverages (a) redundancies and token overlaps to jointly score multiple items, that are typically short-text phrases arising in search and recommendations, and (b) a novel training objective that models ranking probabilities. CROSS-JEM achieves state-of-the-art accuracy and over 4x lower ranking latency over standard cross-encoders. Our contributions are threefold: (i) we highlight the gap between the ranking application's need for scoring thousands of items per query and the limited capabilities of current cross-encoders; (ii) we introduce CROSS-JEM for joint efficient scoring of multiple items per query; and (iii) we demonstrate state-of-the-art accuracy on standard public datasets and a proprietary dataset. CROSS-JEM opens up new directions for designing tailored early-attention-based ranking models that incorporate strict production constraints such as item multiplicity and latency.
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- 2024
4. DNN-GDITD: Out-of-distribution detection via Deep Neural Network based Gaussian Descriptor for Imbalanced Tabular Data
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Chudasama, Priyanka, Surisetty, Anil, Malhotra, Aakarsh, and Singh, Alok
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Classification tasks present challenges due to class imbalances and evolving data distributions. Addressing these issues requires a robust method to handle imbalances while effectively detecting out-of-distribution (OOD) samples not encountered during training. This study introduces a novel OOD detection algorithm designed for tabular datasets, titled Deep Neural Network-based Gaussian Descriptor for Imbalanced Tabular Data (DNN-GDITD). The DNN-GDITD algorithm can be placed on top of any DNN to facilitate better classification of imbalanced data and OOD detection using spherical decision boundaries. Using a combination of Push, Score-based, and focal losses, DNN-GDITD assigns confidence scores to test data points, categorizing them as known classes or as an OOD sample. Extensive experimentation on tabular datasets demonstrates the effectiveness of DNN-GDITD compared to three OOD algorithms. Evaluation encompasses imbalanced and balanced scenarios on diverse tabular datasets, including a synthetic financial dispute dataset and publicly available tabular datasets like Gas Sensor, Drive Diagnosis, and MNIST, showcasing DNN-GDITD's versatility., Comment: 17 pages
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- 2024
5. SiTe CiM: Signed Ternary Computing-in-Memory for Ultra-Low Precision Deep Neural Networks
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Thakuria, Niharika, Malhotra, Akul, Thirumala, Sandeep K., Elangovan, Reena, Raghunathan, Anand, and Gupta, Sumeet K.
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Computer Science - Hardware Architecture - Abstract
Ternary Deep Neural Networks (DNN) have shown a large potential for highly energy-constrained systems by virtue of their low power operation (due to ultra-low precision) with only a mild degradation in accuracy. To enable an energy-efficient hardware substrate for such systems, we propose a compute-enabled memory design, referred to as SiTe-CiM, which features computing-in-memory (CiM) of dot products between signed ternary (SiTe) inputs and weights. SiTe CiM is based on cross-coupling of two bit cells to enable CiM of dot products in the signed ternary regime. We explore SiTe CiM with 8T-SRAM, 3T-embedded DRAM (3T-eDRAM) and 3T-ferroelectric metal FET (FEMFET) memories. We propose two flavors of this technique, namely SiTe CiM I/II. In SiTe CiM I, we employ two additional transistors per cell for cross-coupling, achieving fast CiM operations, albeit incurring an area overhead ranging from 18% to 34% (compared to standard ternary memories). In SiTe CiM II, four extra transistors are utilized for every 16 cells in a column, thereby incurring only 6% area cost (but leading to slower CiM than SiTe CiM I). Based on the array analysis, our designs achieve up to 88% lower CiM latency and 78% CiM energy savings across various technologies considered, as compared to their respective near-memory computing counterparts. Further, we perform system level analysis by incorporating SiTe CiM I/II arrays in a ternary DNN accelerator and show up to 7X throughput boost and up to 2.5X energy reduction compared to the near-memory ternary DNN accelerators.
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- 2024
6. A novel probe of graviton dispersion relations at nano-Hertz frequencies
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Atkins, Bill, Malhotra, Ameek, and Tasinato, Gianmassimo
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General Relativity and Quantum Cosmology ,Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
We generalise Phinney's 'practical theorem' to account for modified graviton dispersion relations motivated by certain cosmological scenarios. Focusing on specific examples, we show how such modifications can induce characteristic localised distortions, bumps, in the frequency profile of the stochastic gravitational wave background emitted from distant binary sources. We concentrate on gravitational waves at nano-Hertz frequencies probed by pulsar timing arrays, and we forecast the capabilities of future experiments to accurately probe parameters controlling modified dispersion relations. Our predictions are based on properties of gravitational waves emitted in the first inspiral phase of the binary process, and do not rely on assumptions of non-linear effects occurring during the binary merging phase, Comment: 19 pages, 5 figures, 2 tables
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- 2024
7. Mapping Students' Readiness for E-Learning in Higher Education: A Bibliometric Analysis
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Anamica Maan and Kapil Malhotra
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This paper reports the findings of a bibliometric analysis using VOSviewer on 392 Scopus database documents published from 2003 to 2022, aiming to understand the global landscape of the e-learning field and to identify the most prominent authors, institutions, countries and reference publications, as well as the research topics that have recently received the most attention in students' readiness for e-learning in Higher Education Institutions (HEIs). The findings indicate that there has been an upward trend in e-learning readiness among students in HEIs over time. Among the countries studied, the United States, Taiwan, Australia, and Malaysia were found to have the most effective approaches to addressing students' readiness for e-learning. The most highly cited author in this field is M-L. Hung. Based on the citations, the most recognised journal in this field was "Computers and Education" and the universities that were most persuasive were two Taiwan universities in the first position. The data also revealed relatively low levels of collaboration among authors, institutions and nations regarding students' readiness for e-learning.
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- 2024
8. Dual Use of Cannabis with Tobacco Is Associated with Increased Sugary Food and Drink Intake in Young People
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Malhotra, Niamh, Kasaraneni, Nikita, Ahadian, Zoya, Chang, Howard, Advani, Ira, McDermott, Jade, Truong, Caitlyn, Gaboyan, Samvel, Mittal, Ankita, Perryman, Alexia, Masso-Silva, Jorge A, Steeger, Christine M, Bowler, Russell P, Castaldi, Peter J, Sharma, Sunita, and Alexander, Laura E Crotty
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Biomedical and Clinical Sciences ,Biological Psychology ,Public Health ,Health Sciences ,Psychology ,Pharmacology and Pharmaceutical Sciences ,Cannabinoid Research ,Drug Abuse (NIDA only) ,Clinical Research ,Substance Misuse ,Nutrition ,Behavioral and Social Science ,2.2 Factors relating to the physical environment ,Cardiovascular ,Good Health and Well Being ,Humans ,Adolescent ,Female ,Male ,Young Adult ,Marijuana Smoking ,Adult ,Surveys and Questionnaires ,Dietary Sugars ,Exercise ,THC ,diet ,e-cigarettes ,exercise ,marijuana ,nicotine ,teenagers and young adults ,tobacco ,Toxicology - Abstract
Rates of cannabis initiation among teenagers and young adults are increasing. Further, the use of various forms of cannabis (smoked or vaped) with nicotine (dual use) is increasingly common among young people. The health effects of dual use are lesser known, particularly in the context of high-potency cannabis products and across different routes of administration, which is ominous in terms of predicting future health outcomes. There is a long history of cannabis use being associated with decreased activity and increased snacking, both of which could portend an increased risk of metabolic and cardiovascular disease, particularly when these habits begin during formative years. However, modern forms of cannabis may not have these same effects. Here, we assess whether cannabis use alone and dual use of cannabis with nicotine impact dietary and exercise habits in young people. An anonymous, social media-based survey was designed based on the UC San Diego Inhalant Questionnaire and published diet and exercise questionnaires. A total of 457 surveys were completed. Young sole cannabis users represented 29% of responders, 16% were dual users of cannabis and nicotine, and 55% were non-users of either drug. Although the sole use of cannabis was not associated with dietary or activity differences relative to non-users, dual users of cannabis and nicotine reported higher consumption of unhealthy sugars. This novel finding of dual use being associated with increased sugar intake in young people raises concerns for an increased risk of metabolic syndrome and cardiovascular disease in this population.
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- 2024
9. Efficacy of Lemborexant in Adults ≥ 65 Years of Age with Insomnia Disorder.
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Arnold, Valerie, Ancoli-Israel, Sonia, Dang-Vu, Thien, Mishima, Kazuo, Pinner, Kate, Malhotra, Manoj, and Moline, Margaret
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Elderly ,Insomnia ,Lemborexant ,Orexin receptor antagonists ,Sleep - Abstract
BACKGROUND: Pharmacologic treatments are available to treat insomnia, a common and burdensome sleep disorder, but may be contraindicated in older adults who are prone to side effects from sleep-promoting drugs. These analyses of sleep diary data from Study E2006-G000-303 (Study 303) investigated the benefits of lemborexant 5 mg (LEM5) and 10 mg (LEM10) in the subgroup age ≥ 65 years with insomnia. METHOD: Study 303, a 12-month, double-blind study of LEM5 and LEM10 in adults (age ≥ 18 years) with insomnia disorder (sleep onset and/or maintenance difficulties) assessed subject-reported (subjective) sleep-onset latency (sSOL), sleep efficiency (sSE), wake after sleep onset (sWASO), and total sleep time (sTST). Morning sleepiness/alertness, insomnia severity (Insomnia Severity Index [ISI]), fatigue (Fatigue Severity Scale [FSS]), perceptions of sleep-related medication effects (Patient Global Impression-Insomnia [PGI-I] questionnaire), and safety were also evaluated. RESULTS: In this subgroup of older adults (≥ 65 years; n = 262), there were significantly larger changes from baseline for sSOL, sSE, sTST, and sWASO with LEM5 and LEM10 versus placebo through month 6 (except sWASO month 1), indicating improvement; these improvements were sustained through month 12. Subject-reported increases in morning alertness were significantly greater with one or both LEM doses versus placebo through month 6 and sustained through month 12. There were significantly larger ISI total and daytime functioning score decreases (improvement) from baseline with LEM versus placebo at months 1, 3, and 6 (total score: both doses; daytime functioning: LEM5 month 1 and both doses months 3 and 6) and decreases from baseline FSS at months 1 and 3 (LEM5) and month 6 (both doses), sustained to month 12. Compared with placebo, more subjects reported that LEM (both doses) positively impacted ability to sleep, time to fall asleep, and TST through month 6, sustained to month 12, with no rebound after drug withdrawal. LEM was well tolerated to month 12; mild somnolence was the most common treatment-emergent adverse event. CONCLUSIONS: Improvements in subject-reported efficacy in LEM-treated adults age ≥ 65 years with insomnia were observed as early as the first week of treatment and sustained through end of month 12. LEM was well tolerated. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov identifier NCT02952820: E2006-G000-303; Study 303; SUNRISE-2 (First posted: October 2016); EudraCT 2015-001463-39 (First posted: November 2016).
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- 2024
10. SHA-CNN: Scalable Hierarchical Aware Convolutional Neural Network for Edge AI
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Dhakad, Narendra Singh, Malhotra, Yuvnish, Vishvakarma, Santosh Kumar, and Roy, Kaushik
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Computer Science - Neural and Evolutionary Computing - Abstract
This paper introduces a Scalable Hierarchical Aware Convolutional Neural Network (SHA-CNN) model architecture for Edge AI applications. The proposed hierarchical CNN model is meticulously crafted to strike a balance between computational efficiency and accuracy, addressing the challenges posed by resource-constrained edge devices. SHA-CNN demonstrates its efficacy by achieving accuracy comparable to state-of-the-art hierarchical models while outperforming baseline models in accuracy metrics. The key innovation lies in the model's hierarchical awareness, enabling it to discern and prioritize relevant features at multiple levels of abstraction. The proposed architecture classifies data in a hierarchical manner, facilitating a nuanced understanding of complex features within the datasets. Moreover, SHA-CNN exhibits a remarkable capacity for scalability, allowing for the seamless incorporation of new classes. This flexibility is particularly advantageous in dynamic environments where the model needs to adapt to evolving datasets and accommodate additional classes without the need for extensive retraining. Testing has been conducted on the PYNQ Z2 FPGA board to validate the proposed model. The results achieved an accuracy of 99.34%, 83.35%, and 63.66% for MNIST, CIFAR-10, and CIFAR-100 datasets, respectively. For CIFAR-100, our proposed architecture performs hierarchical classification with 10% reduced computation while compromising only 0.7% accuracy with the state-of-the-art. The adaptability of SHA-CNN to FPGA architecture underscores its potential for deployment in edge devices, where computational resources are limited. The SHA-CNN framework thus emerges as a promising advancement in the intersection of hierarchical CNNs, scalability, and FPGA-based Edge AI.
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- 2024
11. Evolution of H$\alpha$ Equivalent Widths from $z \sim 0.4-2.2$: implications for star formation and legacy surveys with Roman and Euclid
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Khostovan, Ali Ahmad, Malhotra, Sangeeta, Rhoads, James E., Sobral, David, Harish, Santosh, Tilvi, Vithal, Coughlin, Alicia, and Rezaee, Saeed
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Astrophysics - Astrophysics of Galaxies - Abstract
We investigate the `intrinsic' H$\alpha$ EW distributions of $z \sim 0.4 - 2.2$ narrowband-selected H$\alpha$ samples from HiZELS and DAWN using a forward modeling approach. We find an EW - stellar mass anti-correlation with steepening slopes $-0.18\pm0.03$ to $-0.24^{+0.06}_{-0.08}$ at $z \sim 0.4$ and $z\sim 2.2$, respectively. Typical EW increases as $(1+z)^{1.78^{+0.22}_{-0.23}}$ for a $10^{10}$ M$_\odot$ emitter from $15^{+2.4}_{-2.3}$\r{A} ($z \sim 0.4$) to $67.7^{+10.4}_{-10.0}$\r{A} ($z \sim 2.2$) and is steeper with decreasing stellar mass highlighting the high EW nature of low-mass high-$z$ systems. We model this redshift evolving anti-correlation, $W_0(M,z)$, and find it produces H$\alpha$ luminosity and SFR functions strongly consistent with observations validating the model and allowing us to use $W_0(M,z)$ to investigate the relative contribution of H$\alpha$ emitters towards cosmic SF. We find EW$_0 > 200$ \r{A} emitters contribute significantly to cosmic SF activity at $z \sim 1.5 - 2$ making up $\sim 40$% of total SF consistent with sSFR $> 10^{-8.5}$ yr$^{-1}$ ($\sim 45 - 55$%). Overall, this highlights the importance of high EW systems at high-$z$. Our $W_0(M,z)$ model also reproduces the cosmic sSFR evolution found in simulations and observations and show that tension between the two can simply arise from selection effects in observations. Lastly, we forecast Roman and Euclid grism surveys using $W_0(M,z)$ including observational efficiency and limiting resolution effects where we predict $\sim 24000$ and $\sim 30000$ $0.5 < z < 1.9$ H$\alpha$ emitters per deg$^{-2}$, respectively, down to $>5\times10^{-17}$ erg s$^{-1}$ cm$^{-2}$ including $10^{7.2 - 8}$ M$_\odot$ galaxies at $z > 1$ with EW$_0 >1000$\r{A}. Both Roman and Euclid will enable us to observe with unprecedented detail some of the most bursty/high EW, low-mass star-forming galaxies near cosmic noon., Comment: 25 pages, 12 Figures, and 12 Tables. Submitted to MNRAS. Comments are welcomed. (Abridged Abstract)
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- 2024
12. UNCOVERing the Faint-End of the z=7 [OIII] Luminosity Function with JWST's F410M Medium Bandpass Filter
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Wold, Isak G. B., Malhotra, Sangeeta, Rhoads, James E., Weaver, John R., and Wang, Bingjie
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Astrophysics - Astrophysics of Galaxies - Abstract
Strong emission from doubly ionized oxygen is a beacon for some of the most intensely star forming galaxies known. JWST enables the search for this beacon in the early universe with unprecedented sensitivity. In this work, we extend the study of faint [OIII]$_{5008}$ selected galaxies by an order of magnitude in line luminosity. We use publicly available UNCOVER DR1 JWST/NIRCam and HST imaging data of the cluster lensing field, Abell 2744, to identify strong (rest-frame EW$>500$\AA) [OIII]$_{5008}$ emitters at $z\sim7$ based on excess F410M flux. We find $N=68$ $z\sim7$ [OIII] candidates, with a subset of $N=33$ that have deep HST coverage required to rule-out lower redshift interlopers (13.68 arcmin$^2$ with F814W $5\sigma$ depth $>28$ AB). Such strong emission lines can lead to very red colors that could be misinterpreted as evidence for old, massive stellar populations, but are shown to be due to emission lines where we have spectra. Using this deep HST sample and completeness simulations, which calculate the effective survey volume of the UNCOVER lensing field as a function of [OIII] luminosity, we derive a new [OIII] luminosity function (LF) extending to $41.09<\rm{log}_{10}(L/\rm{erg\,s}^{-1})<42.35$ which is an order of magnitude deeper than previous $z\sim6$ [OIII] LFs based on JWST slitless spectroscopy. This LF is well fit by a power law with a faint-end slope of $\alpha=-2.07^{+0.22}_{-0.23}$. There is little or no evolution between this LF and published [OIII] LFs at redshifts $3\lesssim z\lesssim7$, and no evidence of a turnover at faint luminosities. The sizes of these extreme [OIII] emitters are broadly similar to their low redshift counterparts, the green peas. The luminosity function of [OIII] emitters matches that of Lyman-$\alpha$ at the bright end, suggesting that many of them should be Lyman-$\alpha$ emitters., Comment: submitted to ApJ
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- 2024
13. Novel Approach for Predicting the Air Quality Index of Megacities through Attention-Enhanced Deep Multitask Spatiotemporal Learning
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Khan, Harun, Tso, Joseph, Nguyen, Nathan, Kaushal, Nivaan, Malhotra, Ansh, and Rehman, Nayel
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Computer Science - Machine Learning - Abstract
Air pollution remains one of the most formidable environmental threats to human health globally, particularly in urban areas, contributing to nearly 7 million premature deaths annually. Megacities, defined as cities with populations exceeding 10 million, are frequent hotspots of severe pollution, experiencing numerous weeks of dangerously poor air quality due to the concentration of harmful pollutants. In addition, the complex interplay of factors makes accurate air quality predictions incredibly challenging, and prediction models often struggle to capture these intricate dynamics. To address these challenges, this paper proposes an attention-enhanced deep multitask spatiotemporal machine learning model based on long-short-term memory networks for long-term air quality monitoring and prediction. The model demonstrates robust performance in predicting the levels of major pollutants such as sulfur dioxide and carbon monoxide, effectively capturing complex trends and fluctuations. The proposed model provides actionable information for policymakers, enabling informed decision making to improve urban air quality., Comment: 6 pages, 3 figures, 3 tables
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- 2024
14. Evaluating Large Language Models with fmeval
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Schwöbel, Pola, Franceschi, Luca, Zafar, Muhammad Bilal, Vasist, Keerthan, Malhotra, Aman, Shenhar, Tomer, Tailor, Pinal, Yilmaz, Pinar, Diamond, Michael, and Donini, Michele
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Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
fmeval is an open source library to evaluate large language models (LLMs) in a range of tasks. It helps practitioners evaluate their model for task performance and along multiple responsible AI dimensions. This paper presents the library and exposes its underlying design principles: simplicity, coverage, extensibility and performance. We then present how these were implemented in the scientific and engineering choices taken when developing fmeval. A case study demonstrates a typical use case for the library: picking a suitable model for a question answering task. We close by discussing limitations and further work in the development of the library. fmeval can be found at https://github.com/aws/fmeval.
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- 2024
15. Transferring spectroscopic stellar labels to 217 million Gaia DR3 XP stars with SHBoost
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Khalatyan, A., Anders, F., Chiappini, C., Queiroz, A. B. A., Nepal, S., Ponte, M. dal, Jordi, C., Guiglion, G., Valentini, M., Elipe, G. Torralba, Steinmetz, M., Pantaleoni-González, M., Malhotra, S., Jiménez-Arranz, Ó., Enke, H., Casamiquela, L., and Ardèvol, J.
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Astrophysics - Solar and Stellar Astrophysics ,Astrophysics - Astrophysics of Galaxies ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest regressor (xgboost), trained on spectroscopic data, capable of producing output parameters with reliable uncertainties from Gaia DR3 data (most notably the low-resolution XP spectra), without ground-based spectroscopic observations. Using Shapley additive explanations, we interpret how the predictions for each star are influenced by each data feature. For the training and testing of the network, we used high-quality parameters obtained from the StarHorse code for a sample of around eight million stars observed by major spectroscopic stellar surveys, complemented by curated samples of hot stars, very metal-poor stars, white dwarfs, and hot sub-dwarfs. The training data cover the whole sky, all Galactic components, and almost the full magnitude range of the Gaia DR3 XP sample of more than 217 million objects that also have reported parallaxes. We have achieved median uncertainties of 0.20 mag in V-band extinction, 0.01 dex in logarithmic effective temperature, 0.20 dex in surface gravity, 0.18 dex in metallicity, and $12\%$ in mass (over the full Gaia DR3 XP sample, with considerable variations in precision as a function of magnitude and stellar type). We succeeded in predicting competitive results based on Gaia DR3 XP spectra compared to classical isochrone or spectral-energy distribution fitting methods we employed in earlier works, especially for parameters $A_V$ and $T_{\rm eff}$, along with the metallicity values. Finally, we showcase some potential applications of this new catalogue, including extinction maps, metallicity trends in the Milky Way, and extended maps of young massive stars, metal-poor stars, and metal-rich stars). [abridged], Comment: A&A, accepted. 13 pages, 13 figures + references & appendices. Data available at https://data.aip.de/projects/shboost2024.html
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- 2024
16. Reverse time-to-death as time-scale in time-to-event analysis for studies of advanced illness and palliative care
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Cheung, Yin Bun, Ma, Xiangmei, Chaudhry, Isha, Liu, Nan, Zhuang, Qingyuan, Yang, Grace Meijuan, Malhotra, Chetna, and Finkelstein, Eric Andrew
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Statistics - Methodology - Abstract
Background: Incidence of adverse outcome events rises as patients with advanced illness approach end-of-life. Exposures that tend to occur near end-of-life, e.g., use of wheelchair, oxygen therapy and palliative care, may therefore be found associated with the incidence of the adverse outcomes. We propose a strategy for time-to-event analysis to mitigate the time-varying confounding. Methods: We propose a concept of reverse time-to-death (rTTD) and its use for the time-scale in time-to-event analysis. We used data on community-based palliative care uptake (exposure) and emergency department visits (outcome) among patients with advanced cancer in Singapore to illustrate. We compare the results against that of the common practice of using time-on-study (TOS) as time-scale. Results: Graphical analysis demonstrated that cancer patients receiving palliative care had higher rate of emergency department visits than non-recipients mainly because they were closer to end-of-life, and that rTTD analysis made comparison between patients at the same time-to-death. Analysis of emergency department visits in relation to palliative care using TOS time-scale showed significant increase in hazard ratio estimate when observed time-varying covariates were omitted from statistical adjustment (change-in-estimate=0.38; 95% CI 0.15 to 0.60). There was no such change in otherwise the same analysis using rTTD (change-in-estimate=0.04; 95% CI -0.02 to 0.11), demonstrating the ability of rTTD time-scale to mitigate confounding that intensifies in relation to time-to-death. Conclusion: Use of rTTD as time-scale in time-to-event analysis provides a simple and robust approach to control time-varying confounding in studies of advanced illness, even if the confounders are unmeasured., Comment: 22 pages (including 2 tables and 2 figures)
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- 2024
17. Medium-scale thermospheric gravity waves in the high-resolution Whole Atmosphere Model: Seasonal, local time, and longitudinal variations
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Malhotra, Garima, Fuller-Rowell, Timothy, Fang, Tzu-Wei, Yudin, Valery, Karol, Svetlana, Becker, Erich, and Kubaryk, Adam Marshall
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Physics - Space Physics ,Physics - Atmospheric and Oceanic Physics ,Physics - Data Analysis, Statistics and Probability ,Physics - Geophysics ,Physics - Plasma Physics - Abstract
This paper presents a study of the global medium-scale (scales<620 km) gravity wave (GW) activity (in terms of zonal wind variance) and its seasonal, local time and longitudinal variations by employing the enhanced-resolution (~50 km) Whole Atmosphere Model (WAMT254) and space-based observations for geomagnetically quiet conditions. It is found that the GW hotspots produced by WAMT254 in the troposphere and stratosphere agree well with previously well-studied orographic and non-orographic sources. In the ionosphere-thermosphere (IT) region, GWs spread out forming latitudinal band-like hotspots. During solstices, a primary maximum in GW activity is observed in WAMT254 and GOCE over winter mid-high latitudes, likely associated with higher-order waves with primary sources in polar night jet, fronts and polar vortex. During all the seasons, the enhancement of GWs around the geomagnetic poles as observed by GOCE (at ~250 km) is well captured by simulations. WAMT254 GWs in the IT region also show dependence on local time due to their interaction with migrating tides leading to diurnal and semidiurnal variations. The GWs are more likely to propagate up from the MLT region during westward/weakly-eastward phase of thermospheric tides, signifying the dominance of eastward GW momentum flux in the MLT. Additionally, as a novel finding, a wavenumber-4 signature in GW activity is predicted by WAMT254 between 6-12 LT in the tropics at ~250 km, which propagates eastward with local time. This behavior is likely associated with the modulation of GWs by wave-4 signal of non-migrating tides in the lower thermospheric zonal winds.
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- 2024
18. Double Mpemba effect in the cooling of trapped colloids
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Malhotra, Isha and Löwen, Hartmut
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Condensed Matter - Soft Condensed Matter - Abstract
The Mpemba effect describes the phenomenon that a system at a hot initial temperature cools faster than at an initial warm temperature in the same environment. Such an anomalous cooling has recently been predicted and realized for trapped colloids. Here, we investigate the freezing behavior of a passive colloidal particle by employing numerical Brownian dynamics simulations and theoretical calculations with a model that can be directly tested in experiments. During the cooling process, the colloidal particle exhibits multiple non-monotonic regimes in cooling rates, with the cooling time decreasing twice as a function of the initial temperature-an unexpected phenomenon we refer to as the Double Mpemba effect. Additionally, we demonstrate that both the Mpemba and Double Mpemba effects can be predicted by various machine learning methods, which expedite the analysis of complex, computationally intensive systems.
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- 2024
19. Chandra detects low-luminosity AGN with $M_\mathrm{BH}=10^{4}-10^{6}~M_\mathrm{\odot}$ in nearby ($z<0.5$), dwarf and star-forming galaxies
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Singha, Mainak, Sarmiento, Julissa, Malhotra, Sangeeta, Rhoads, James E., Yung, L. Y. Aaron, Wang, Junxian, Zheng, Zhen-Ya, Lin, Ruqiu, Kim, Keunho, Kang, Jialai, and Harish, Santosh
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Astrophysics - Astrophysics of Galaxies - Abstract
We searched the Chandra and XMM archives for observations of 900 green pea galaxies to find AGN signatures. Green peas are low-mass galaxies with prominent emission lines, similar in size and star formation rate to high-redshift dwarf galaxies. Of the 29 observations found, 9 show X-ray detections with $S/N>3$. The 2-10 keV X-ray luminosity for these 9 sources exceeds $10^{40}~\mathrm{erg~s}^{-1}$, with 2 sources exceeding $10^{41}~\mathrm{erg~s}^{-1}$, suggesting the presence of intermediate-mass black holes (IMBH) or low-luminosity AGN (LLAGN) with BH masses between $100-10^6M_\mathrm{\odot}$. All X-ray detected sources (plus 6 additional sources) show He~II$\lambda4686$ emission and a broad component of the H$\alpha$ emission line, indicating winds. The line widths of the broad H$\alpha$ and He II$\lambda4686$ emitting gas clouds are weakly correlated ($R^{2}=0.15$), suggesting He II$\lambda4686$ emission is inconsistent with winds from super-Eddington accretors. However, the ratio of X-ray luminosity to star formation rate shows an anti-correlation with metallicity in 5 out of 9 X-ray detected sources, implying ultraluminous X-ray sources are key contributors to the observed X-ray luminosity. This could be due to super-Eddington accretors or IMBH. The X-ray emission is much higher than that produced by Wolf-Rayet stars and supernovae-driven winds. Thus, the X-ray luminosity in these 9 sources can only be explained by black holes with masses over $100~M_\mathrm{\odot}$. Our findings suggest the presence of LLAGN in these galaxies, with broad H$\alpha$ line widths implying BH masses of $10^4-10^6M_\mathrm{\odot}$. Given Green Peas' role as significant Lyman Continuum leakers, LLAGN in these galaxies could have contributed significantly to cosmic reionization., Comment: Submitted to ApJ. 17 pages, 11 figures and 3 tables. Comments welcome
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- 2024
20. Memory Faults in Activation-sparse Quantized Deep Neural Networks: Analysis and Mitigation using Sharpness-aware Training
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Malhotra, Akul and Gupta, Sumeet Kumar
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Computer Science - Machine Learning - Abstract
Improving the hardware efficiency of deep neural network (DNN) accelerators with techniques such as quantization and sparsity enhancement have shown an immense promise. However, their inference accuracy in non-ideal real-world settings (such as in the presence of hardware faults) is yet to be systematically analyzed. In this work, we investigate the impact of memory faults on activation-sparse quantized DNNs (AS QDNNs). We show that a high level of activation sparsity comes at the cost of larger vulnerability to faults, with AS QDNNs exhibiting up to 11.13% lower accuracy than the standard QDNNs. We establish that the degraded accuracy correlates with a sharper minima in the loss landscape for AS QDNNs, which makes them more sensitive to perturbations in the weight values due to faults. Based on this observation, we employ sharpness-aware quantization (SAQ) training to mitigate the impact of memory faults. The AS and standard QDNNs trained with SAQ have up to 19.50% and 15.82% higher inference accuracy, respectively compared to their conventionally trained equivalents. Moreover, we show that SAQ-trained AS QDNNs show higher accuracy in faulty settings than standard QDNNs trained conventionally. Thus, sharpness-aware training can be instrumental in achieving sparsity-related latency benefits without compromising on fault tolerance., Comment: arXiv admin note: substantial text overlap with arXiv:2301.00675
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- 2024
21. Logical Distillation of Graph Neural Networks
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Pluska, Alexander, Welke, Pascal, Gärtner, Thomas, and Malhotra, Sagar
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
We present a logic based interpretable model for learning on graphs and an algorithm to distill this model from a Graph Neural Network (GNN). Recent results have shown connections between the expressivity of GNNs and the two-variable fragment of first-order logic with counting quantifiers (C2). We introduce a decision-tree based model which leverages an extension of C2 to distill interpretable logical classifiers from GNNs. We test our approach on multiple GNN architectures. The distilled models are interpretable, succinct, and attain similar accuracy to the underlying GNN. Furthermore, when the ground truth is expressible in C2, our approach outperforms the GNN., Comment: To Appear in the Proceedings of KR 2024
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- 2024
22. Towards a Personal Health Large Language Model
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Cosentino, Justin, Belyaeva, Anastasiya, Liu, Xin, Furlotte, Nicholas A., Yang, Zhun, Lee, Chace, Schenck, Erik, Patel, Yojan, Cui, Jian, Schneider, Logan Douglas, Bryant, Robby, Gomes, Ryan G., Jiang, Allen, Lee, Roy, Liu, Yun, Perez, Javier, Rogers, Jameson K., Speed, Cathy, Tailor, Shyam, Walker, Megan, Yu, Jeffrey, Althoff, Tim, Heneghan, Conor, Hernandez, John, Malhotra, Mark, Stern, Leor, Matias, Yossi, Corrado, Greg S., Patel, Shwetak, Shetty, Shravya, Zhan, Jiening, Prabhakara, Shruthi, McDuff, Daniel, and McLean, Cory Y.
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich, longitudinal data for personal health monitoring. Here we present Personal Health Large Language Model (PH-LLM), fine-tuned from Gemini for understanding and reasoning over numerical time-series personal health data. We created and curated three datasets that test 1) production of personalized insights and recommendations from sleep patterns, physical activity, and physiological responses, 2) expert domain knowledge, and 3) prediction of self-reported sleep outcomes. For the first task we designed 857 case studies in collaboration with domain experts to assess real-world scenarios in sleep and fitness. Through comprehensive evaluation of domain-specific rubrics, we observed that Gemini Ultra 1.0 and PH-LLM are not statistically different from expert performance in fitness and, while experts remain superior for sleep, fine-tuning PH-LLM provided significant improvements in using relevant domain knowledge and personalizing information for sleep insights. We evaluated PH-LLM domain knowledge using multiple choice sleep medicine and fitness examinations. PH-LLM achieved 79% on sleep and 88% on fitness, exceeding average scores from a sample of human experts. Finally, we trained PH-LLM to predict self-reported sleep quality outcomes from textual and multimodal encoding representations of wearable data, and demonstrate that multimodal encoding is required to match performance of specialized discriminative models. Although further development and evaluation are necessary in the safety-critical personal health domain, these results demonstrate both the broad knowledge and capabilities of Gemini models and the benefit of contextualizing physiological data for personal health applications as done with PH-LLM., Comment: 72 pages
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- 2024
23. Transforming Wearable Data into Health Insights using Large Language Model Agents
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Merrill, Mike A., Paruchuri, Akshay, Rezaei, Naghmeh, Kovacs, Geza, Perez, Javier, Liu, Yun, Schenck, Erik, Hammerquist, Nova, Sunshine, Jake, Tailor, Shyam, Ayush, Kumar, Su, Hao-Wei, He, Qian, McLean, Cory Y., Malhotra, Mark, Patel, Shwetak, Zhan, Jiening, Althoff, Tim, McDuff, Daniel, and Liu, Xin
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
Despite the proliferation of wearable health trackers and the importance of sleep and exercise to health, deriving actionable personalized insights from wearable data remains a challenge because doing so requires non-trivial open-ended analysis of these data. The recent rise of large language model (LLM) agents, which can use tools to reason about and interact with the world, presents a promising opportunity to enable such personalized analysis at scale. Yet, the application of LLM agents in analyzing personal health is still largely untapped. In this paper, we introduce the Personal Health Insights Agent (PHIA), an agent system that leverages state-of-the-art code generation and information retrieval tools to analyze and interpret behavioral health data from wearables. We curate two benchmark question-answering datasets of over 4000 health insights questions. Based on 650 hours of human and expert evaluation we find that PHIA can accurately address over 84% of factual numerical questions and more than 83% of crowd-sourced open-ended questions. This work has implications for advancing behavioral health across the population, potentially enabling individuals to interpret their own wearable data, and paving the way for a new era of accessible, personalized wellness regimens that are informed by data-driven insights., Comment: 38 pages
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- 2024
24. Measuring the circular polarization of gravitational waves with pulsar timing arrays
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Cruz, N. M. Jiménez, Malhotra, Ameek, Tasinato, Gianmassimo, and Zavala, Ivonne
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Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology - Abstract
The circular polarization of the stochastic gravitational wave background (SGWB) is a key observable for characterising the origin of the signal detected by Pulsar Timing Array (PTA) collaborations. Both the astrophysical and the cosmological SGWB can have a sizeable amount of circular polarization, due to Poisson fluctuations in the source properties for the former, and to parity violating processes in the early universe for the latter. Its measurement is challenging since PTA are blind to the circular polarization monopole, forcing us to turn to anisotropies for detection. We study the sensitivity of current and future PTA datasets to circular polarization anisotropies, focusing on realistic modelling of intrinsic and kinematic anisotropies for astrophysical and cosmological scenarios respectively. Our results indicate that the expected level of circular polarization for the astrophysical SGWB should be within the reach of near future datasets, while for cosmological SGWB circular polarization is a viable target for more advanced SKA-type experiments., Comment: 28 pages, 9 figures
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- 2024
25. Asteroid Kamo`oalewa's journey from the lunar Giordano Bruno crater to Earth 1:1 resonance
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Jiao, Yifei, Cheng, Bin, Huang, Yukun, Asphaug, Erik, Gladman, Brett, Malhotra, Renu, Michel, Patrick, Yu, Yang, and Baoyin, Hexi
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Astrophysics - Earth and Planetary Astrophysics - Abstract
Among the nearly 30,000 known near-Earth asteroids (NEAs), only tens of them possess Earth co-orbital characteristics with semi-major axes $\sim$1 au. In particular, 469219 Kamo`oalewa (2016 HO3), upcoming target of China's Tianwen-2 asteroid sampling mission, exhibits a meta-stable 1:1 mean-motion resonance with Earth. Intriguingly, recent ground-based observations show that Kamo`oalewa has spectroscopic characteristics similar to space-weathered lunar silicates, hinting at a lunar origin instead of an asteroidal one like the vast majority of NEAs. Here we use numerical simulations to demonstrate that Kamo`oalewa's physical and orbital properties are compatible with a fragment from a crater larger than 10--20 km formed on the Moon in the last few million years. The impact could have ejected sufficiently large fragments into heliocentric orbits, some of which could be transferred to Earth 1:1 resonance and persist today. This leads us to suggest the young lunar crater Giordano Bruno (22 km diameter, 1--10 Ma age) as the most likely source, linking a specific asteroid in space to its source crater on the Moon. The hypothesis will be tested by the Tianwen-2 mission when it returns a sample of Kamo`oalewa. And the upcoming NEO Surveyor mission will possibly help us to identify such a lunar-derived NEA population., Comment: 29 pages, 4 figures. Published in Nature Astronomy, 19 April 2024
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- 2024
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26. Cosmological constraints on curved quintessence
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Bhattacharya, Sukannya, Borghetto, Giulia, Malhotra, Ameek, Parameswaran, Susha, Tasinato, Gianmassimo, and Zavala, Ivonne
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Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
Dynamical dark energy has gained renewed interest due to recent theoretical and observational developments. In the present paper, we focus on a string-motivated dark energy set-up, and perform a detailed cosmological analysis of exponential quintessence with potential $V=V_0 e^{-\lambda\phi}$, allowing for non-zero spatial curvature. We first gain some physical intuition into the full evolution of such a scenario by analysing the corresponding dynamical system. Then, we test the model using a combination of Planck CMB data, DESI BAO data, as well as recent supernovae datasets. For the model parameter $\lambda$, we obtain a preference for nonzero values: $\lambda = 0.48^{+0.28}_{-0.21},\; 0.68^{+0.31}_{-0.20},\; 0.77^{+0.18}_{-0.15}$ at 68% C.L. when combining CMB+DESI with Pantheon+, Union3 and DES-Y5 supernovae datasets respectively. We find no significant hint for spatial curvature. We discuss the implications of current cosmological results for the exponential quintessence model, and more generally for dark energy in string theory., Comment: 34 pages, 13 figures, 10 tables. Comments welcome! V2 - updated plots and added references
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- 2024
27. Towards Counting Markov Equivalence Classes with Logical Constraints
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Bizzaro, Davide, Serafini, Luciano, and Malhotra, Sagar
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Computer Science - Logic in Computer Science - Abstract
We initiate the study of counting Markov Equivalence Classes (MEC) under logical constraints. MECs are equivalence classes of Directed Acyclic Graphs (DAGs) that encode the same conditional independence structure among the random variables of a DAG model. Observational data can only allow to infer a DAG model up to Markov Equivalence. However, Markov equivalent DAGs can represent different causal structures, potentially super-exponentially many. Hence, understanding MECs combinatorially is critical to understanding the complexity of causal inference. In this paper, we focus on analysing MECs of size one, with logical constraints on the graph topology. We provide a polynomial-time algorithm (w.r.t. the number of nodes) for enumerating essential DAGs (the only members of an MEC of size one) with arbitrary logical constraints expressed in first-order logic with two variables and counting quantifiers (C^2). Our work brings together recent developments in tractable first-order model counting and combinatorics of MECs., Comment: Under Review
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- 2024
28. Repelling Planet pairs by Ping-pong Scattering
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Wu, Yanqin, Malhotra, Renu, and Lithwick, Yoram
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Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
The Kepler mission reveals a peculiar trough-peak feature in the orbital spacing of close-in planets near mean-motion resonances: a deficit and an excess that are a couple percent to the narrow, respectively wide, of the resonances. This feature has received two main classes of explanations, one involving eccentricity damping, the other scattering with small bodies. Here, we point out a few issues with the damping scenario, and study the scattering scenario in more detail. We elucidate why scattering small bodies tends to repel two planets. As the small bodies random-walk in energy and angular momentum space, they tend to absorb, fractionally, more energy than angular momentum. This, which we call "ping-pong repulsion", transports angular momentum from the inner to the outer planet and pushes the two planets apart. Such a process, even if ubiquitous, leaves identifiable marks only near first-order resonances: diverging pairs jump across the resonance quickly and produce the MMR asymmetry. To explain the observed positions of the trough-peaks, a total scattering mass of order a few percent of the planet masses is required. Moreover, if this mass is dominated by a handful of Mercury-sized bodies, one can also explain the planet eccentricities as inferred from transit-time-variations. Lastly, we suggest how these conditions may have naturally arisen during the late stages of planet formation., Comment: 14 pages, submitted to AAS journal
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- 2024
29. Inflationary Gravitational Wave Spectral Shapes as test for Low-Scale Leptogenesis
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Borboruah, Zafri A., Ghoshal, Anish, Malhotra, Lekhika, and Yajnik, Urjit
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High Energy Physics - Phenomenology ,Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
We study thermal and non-thermal resonant leptogenesis in a general setting where a heavy scalar $\phi$ decays to right-handed neutrinos (RHNs) whose further out-of-equilibrium decay generates the required lepton asymmetry. Domination of the energy budget of the Universe by the $\phi$ or the RHNs alters the evolution history of the primordial gravitational waves (PGW), of inflationary origin, which re-enter the horizon after inflation, modifying the spectral shape. The decays of $\phi$ and RHNs release entropy into the early Universe while nearly degenerate RHNs facilitate low and intermediate scale leptogenesis. We show that depending on the coupling $y_R$ of $\phi$ to radiation species, RHNs can achieve thermal abundance before decaying, which gives rise to thermal leptogenesis. A characteristic damping of the GW spectrum resulting in two knee-like features or one knee-like feature would provide evidence for low-scale thermal and non-thermal leptogenesis respectively. We explore the parameter space for the lightest right-handed neutrino mass $M_1\in[10^2,10^{14}]$ GeV and washout parameter $K$ that depends on the light-heavy neutrino Yukawa couplings $\lambda$, in the weak ($K < 1$) and strong ($K > 1$) washout regimes. The resulting novel features compatible with observed baryon asymmetry are detectable by future experiments like LISA and ET. By estimating signal-to-noise ratio (SNR) for upcoming GW experiments, we investigate the effect of the scalar mass $M_\phi$ and reheating temperature $T_\phi$, which depends on the $\phi-N$ Yukawa couplings $y_N$., Comment: 57 pages, 21 figures
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- 2024
30. Machine Learning Assisted Dynamical Classification of Trans-Neptunian Objects
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Volk, Kathryn and Malhotra, Renu
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Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics ,Computer Science - Machine Learning - Abstract
Trans-Neptunian objects (TNOs) are small, icy bodies in the outer solar system. They are observed to have a complex orbital distribution that was shaped by the early dynamical history and migration of the giant planets. Comparisons between the different dynamical classes of modeled and observed TNOs can help constrain the history of the outer solar system. Because of the complex dynamics of TNOs, particularly those in and near mean motion resonances with Neptune, classification has traditionally been done by human inspection of plots of the time evolution of orbital parameters. This is very inefficient. The Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to increase the number of known TNOs by a factor of $\sim$10, necessitating a much more automated process. In this chapter we present an improved supervised machine learning classifier for TNOs. Using a large and diverse training set as well as carefully chosen, dynamically motivated data features calculated from numerical integrations of TNO orbits, our classifier returns results that match those of a human classifier 98% of the time, and dynamically relevant classifications 99.7% of the time. This classifier is dramatically more efficient than human classification, and it will improve classification of both observed and modeled TNO data., Comment: Accepted chapter to appear in the Elsevier book "Machine Learning for Small Solar System Bodies", edited by Valerio Carruba, Evgeny Smirnov, and Dagmara Oszkiewicz
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- 2024
31. UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
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Kharbanda, Siddhant, Gupta, Devaansh, K, Gururaj, Malhotra, Pankaj, Hsieh, Cho-Jui, and Babbar, Rohit
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Extreme Multi-label Classification (XMC) involves predicting a subset of relevant labels from an extremely large label space, given an input query and labels with textual features. Models developed for this problem have conventionally used modular approach with (i) a Dual Encoder (DE) to embed the queries and label texts, (ii) a One-vs-All classifier to rerank the shortlisted labels mined through meta-classifier training. While such methods have shown empirical success, we observe two key uncharted aspects, (i) DE training typically uses only a single positive relation even for datasets which offer more, (ii) existing approaches fixate on using only OvA reduction of the multi-label problem. This work aims to explore these aspects by proposing UniDEC, a novel end-to-end trainable framework which trains the dual encoder and classifier in together in a unified fashion using a multi-class loss. For the choice of multi-class loss, the work proposes a novel pick-some-label (PSL) reduction of the multi-label problem with leverages multiple (in come cases, all) positives. The proposed framework achieves state-of-the-art results on a single GPU, while achieving on par results with respect to multi-GPU SOTA methods on various XML benchmark datasets, all while using 4-16x lesser compute and being practically scalable even beyond million label scale datasets.
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- 2024
32. A therapy for suppressing canonical and noncanonical SARS-CoV-2 viral entry and an intrinsic intrapulmonary inflammatory response
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Leibel, Sandra L, McVicar, Rachael N, Murad, Rabi, Kwong, Elizabeth M, Clark, Alex E, Alvarado, Asuka, Grimmig, Bethany A, Nuryyev, Ruslan, Young, Randee E, Lee, Jamie C, Peng, Weiqi, Zhu, Yanfang P, Griffis, Eric, Nowell, Cameron J, James, Brian, Alarcon, Suzie, Malhotra, Atul, Gearing, Linden J, Hertzog, Paul J, Galapate, Cheska M, Galenkamp, Koen MO, Commisso, Cosimo, Smith, Davey M, Sun, Xin, Carlin, Aaron F, Sidman, Richard L, Croker, Ben A, and Snyder, Evan Y
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Medical Microbiology ,Biomedical and Clinical Sciences ,Biological Sciences ,Stem Cell Research - Induced Pluripotent Stem Cell ,Stem Cell Research ,Infectious Diseases ,Stem Cell Research - Induced Pluripotent Stem Cell - Human ,Lung ,Coronaviruses ,Emerging Infectious Diseases ,2.1 Biological and endogenous factors ,Inflammatory and immune system ,Infection ,Humans ,SARS-CoV-2 ,COVID-19 ,Virus Internalization ,Organoids ,COVID-19 Drug Treatment ,Induced Pluripotent Stem Cells ,Angiotensin-Converting Enzyme 2 ,Inflammation ,Cytokines ,Apoptosis ,inflammation ,lung organoids ,macropinocytosis ,surfactant - Abstract
The prevalence of "long COVID" is just one of the conundrums highlighting how little we know about the lung's response to viral infection, particularly to syndromecoronavirus-2 (SARS-CoV-2), for which the lung is the point of entry. We used an in vitro human lung system to enable a prospective, unbiased, sequential single-cell level analysis of pulmonary cell responses to infection by multiple SARS-CoV-2 strains. Starting with human induced pluripotent stem cells and emulating lung organogenesis, we generated and infected three-dimensional, multi-cell-type-containing lung organoids (LOs) and gained several unexpected insights. First, SARS-CoV-2 tropism is much broader than previously believed: Many lung cell types are infectable, if not through a canonical receptor-mediated route (e.g., via Angiotensin-converting encyme 2(ACE2)) then via a noncanonical "backdoor" route (via macropinocytosis, a form of endocytosis). Food and Drug Administration (FDA)-approved endocytosis blockers can abrogate such entry, suggesting adjunctive therapies. Regardless of the route of entry, the virus triggers a lung-autonomous, pulmonary epithelial cell-intrinsic, innate immune response involving interferons and cytokine/chemokine production in the absence of hematopoietic derivatives. The virus can spread rapidly throughout human LOs resulting in mitochondrial apoptosis mediated by the prosurvival protein Bcl-xL. This host cytopathic response to the virus may help explain persistent inflammatory signatures in a dysfunctional pulmonary environment of long COVID. The host response to the virus is, in significant part, dependent on pulmonary Surfactant Protein-B, which plays an unanticipated role in signal transduction, viral resistance, dampening of systemic inflammatory cytokine production, and minimizing apoptosis. Exogenous surfactant, in fact, can be broadly therapeutic.
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- 2024
33. Clinical characteristics and treatment patterns of patients with NTRK fusion-positive solid tumors: A multisite cohort study at US academic cancer centers.
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Willis, Connor, Au, Trang, Hejazi, Andre, Griswold, Cassia, Schabath, Matthew, Thompson, Jonathan, Malhotra, Jyoti, Federman, Noah, Ko, Gilbert, Appukkuttan, Sreevalsa, Warnock, Neil, Kong, Sheldon, Hocum, Brian, Brixner, Diana, and Stenehjem, David
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Humans ,Female ,Male ,Retrospective Studies ,Middle Aged ,United States ,Neoplasms ,Receptor ,trkC ,Aged ,Receptor ,trkA ,Adult ,Protein Kinase Inhibitors ,Receptor ,trkB ,Academic Medical Centers ,Membrane Glycoproteins ,Oncogene Proteins ,Fusion ,Cohort Studies ,Pyrimidines ,Pyrazoles ,Benzamides ,Young Adult ,Indazoles - Abstract
BACKGROUND: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are rare oncogenic drivers prevalent in 0.3% of solid tumors. They are most common in salivary gland cancer (2.6%), thyroid cancer (1.6%), and soft-tissue sarcoma (1.5%). Currently, there are 2 US Food and Drug Administration-approved targeted therapies for NTRK gene fusions: larotrectinib, approved in 2018, and entrectinib, approved in 2019. To date, the real-world uptake of tyrosine receptor kinase inhibitor (TRKi) use for NTRK-positive solid tumors in academic cancer centers remains largely unknown. OBJECTIVE: To describe the demographics, clinical and genomic characteristics, and testing and treatment patterns of patients with NTRK-positive solid tumors treated at US academic cancer centers. METHODS: This was a retrospective chart review study conducted in academic cancer centers in the United States. All patients diagnosed with an NTRK fusion-positive (NTRK1, NTRK2, NTRK3) solid tumor (any stage) and who received cancer treatment at participating sites between January 1, 2012, and July 1, 2023, were included in this study. Patient demographics, clinical characteristics, genomic characteristics, NTRK testing data, and treatment patterns were collected from electronic medical records and analyzed using descriptive statistics as appropriate. RESULTS: In total, 6 centers contributed data for 55 patients with NTRK-positive tumors. The mean age was 49.3 (SD = 20.5) years, 51% patients were female, and the majority were White (78%). The median duration of time from cancer diagnosis to NTRK testing was 85 days (IQR = 44-978). At the time of NTRK testing, 64% of patients had stage IV disease, compared with 33% at cancer diagnosis. Prevalent cancer types in the overall cohort included head and neck (15%), thyroid (15%), brain (13%), lung (13%), and colorectal (11%). NTRK1 fusions were most common (45%), followed by NTRK3 (40%) and NTRK2 (15%). Across all lines of therapy, 51% of patients (n = 28) received a TRKi. Among TRKi-treated patients, 71% had stage IV disease at TRKi initiation. The median time from positive NTRK test to initiation of TRKi was 48 days (IQR = 9-207). TRKis were commonly given as first-line (30%) or second-line (48%) therapies. Median duration of therapy was 610 (IQR = 182-764) days for TRKi use and 207.5 (IQR = 42-539) days for all other first-line therapies. CONCLUSIONS: This study reports on contemporary real-world NTRK testing patterns and use of TRKis in solid tumors, including time between NTRK testing and initiation of TRKi therapy and duration of TRKi therapy.
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- 2024
34. Spanish Translation and Cultural Adaptation of the Intensive Care Unit Delirium Playbook.
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Fuentes, Ana, Makhija, Hirsh, Fine, Janelle, Alicea Reyes, Paola, Diaz De Leon, Bianca, Sanchez-Azofra, Ana, Rodriguez-Flores, Leslie, Weston, Julia, Marquine, María, Hu, Esmeralda, Espinosa-Meza, Romina, Serafin Higuera, Idanya, Vacas Jacques, Paulino, Pollack, Daniel, Novelli, Francesca, Ely, E, Malhotra, Atul, Needham, Dale, Martin, Jennifer, Kamdar, Biren, Arroyo-Novoa, Carmen, and Figueroa-Ramos, Milagros
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critical illness ,delirium ,early diagnosis ,nursing education ,translating - Abstract
BACKGROUND: A lack of high-quality provider education hinders the delivery of standard-of-care delirium detection and prevention practices in the intensive care unit (ICU). To fill this gap, we developed and validated an e-learning ICU Delirium Playbook consisting of eight videos and a 44-question knowledge assessment quiz. Given the increasing Spanish-speaking population worldwide, we translated and cross-culturally adapted the playbook from English into Spanish. OBJECTIVE: To translate and culturally adapt the ICU Delirium Playbook into Spanish, the second most common native language worldwide. METHODS: The translation and cross-cultural adaptation process included double forward and back translations and harmonization by a 14-person interdisciplinary team of ICU nurses and physicians, delirium experts, methodologists, medical interpreters, and bilingual professionals representing many Spanish-speaking global regions. After a preeducation quiz, a nurse focus group completed the playbook videos and posteducation quiz, followed by a semistructured interview. RESULTS: The ICU Delirium Playbook: Spanish Version maintained conceptual equivalence to the English version. Focus group participants posted mean (standard deviation) pre- and post-playbook scores of 63% (10%) and 78% (12%), with a 15% (11%) pre-post improvement (P = 0.01). Participants reported improved perceived competency in performing the Confusion Assessment Method for the ICU and provided positive feedback regarding the playbook. CONCLUSION: After translation and cultural adaptation, the ICU Delirium Playbook: Spanish Version yielded significant knowledge assessment improvements and positive feedback. The Spanish playbook is now available for public dissemination.
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- 2024
35. Developing a novel mobile application for cognitive behavioral therapy for insomnia for people with schizophrenia: integration of wearable and environmental sleep sensors
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Jeon, Jae Min, Ma, Junhua, Kwak, Paulyn, Dang, Bing, Buleje, Italo, Ancoli-Israel, Sonia, Malhotra, Atul, and Lee, Ellen E
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Biomedical and Clinical Sciences ,Clinical Sciences ,Brain Disorders ,Sleep Research ,Schizophrenia ,Bioengineering ,Behavioral and Social Science ,Mental Illness ,Mental Health ,Clinical Research ,Clinical Trials and Supportive Activities ,Serious Mental Illness ,Rehabilitation ,Networking and Information Technology R&D (NITRD) ,Mind and Body ,Mental health ,Good Health and Well Being ,Humans ,Sleep Initiation and Maintenance Disorders ,Mobile Applications ,Cognitive Behavioral Therapy ,Wearable Electronic Devices ,Digital health technology ,Application development ,Sensors ,Psychology ,Respiratory System ,Clinical sciences - Abstract
BackgroundPeople with serious mental illnesses (SMIs) have three-fold higher rates of comorbid insomnia than the general population, which has downstream effects on cognitive, mental, and physical health. Cognitive Behavioral Therapy for Insomnia (CBT-i) is a safe and effective first-line treatment for insomnia, though the therapy's effectiveness relies on completing nightly sleep diaries which can be challenging for some people with SMI and comorbid cognitive deficits. Supportive technologies such as mobile applications and sleep sensors may aid with completing sleep diaries. However, commercially available CBT-i apps are not designed for individuals with cognitive deficits. To aid with this challenge, we have developed an integrated mobile application, named "Sleep Catcher," that will automatically incorporate data from a wearable fitness tracker and a bed sensor to track nightly sleep duration, overnight awakenings, bed-times, and wake-times to generate nightly sleep diaries for CBT-i.MethodsThe application development process will be described-writing algorithms to generating useful data, creating a clinician web portal to oversee patients and the mobile application, and integrating sleep data from device platforms and user input.ResultsThe mobile and web applications were developed using Flutter, IBM Code Engine, and IBM Cloudant database. The mobile application was developed with a user-centered approach and incremental changes informed by a series of beta tests. Special user-interface features were considered to address the challenges of developing a simple and effective mobile application targeting people with SMI.ConclusionThere is strong potential for synergy between engineering and mental health expertise to develop technologies for specific clinical populations. Digital health technologies allow for the development of multi-disciplinary solutions to existing health disparities in vulnerable populations, particularly in people with SMI.
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- 2024
36. Prediction of Readmission Following Sepsis Using Social Determinants of Health.
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Amrollahi, Fatemeh, Kennis, Brent, Shashikumar, Supreeth, Taylor, Stephanie, Ford, James, Rodriguez, Arianna, Weston, Julia, Maheshwary, Romir, Nemati, Shamim, Wardi, Gabriel, Meier, Angela, and Malhotra, Atul
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Humans ,Patient Readmission ,Female ,Male ,Social Determinants of Health ,Retrospective Studies ,Middle Aged ,Sepsis ,Aged ,Adult ,United States ,Logistic Models ,Risk Factors ,Cohort Studies - Abstract
OBJECTIVES: To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. DESIGN: Multicenter retrospective cohort study using patient-level data, including demographic, clinical, and survey data. SETTINGS: Thirty-five hospitals across the United States from 2017 to 2021. PATIENTS: Two hundred seventy-one thousand four hundred twenty-eight individuals in the AllofUs initiative, of which 8909 had an index sepsis hospitalization. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Unplanned 30-day readmission to the hospital. Multinomial logistic regression models were constructed to account for survival in determination of variables associate with 30-day readmission and are presented as adjusted odds rations (aORs). Of the 8909 sepsis patients in our cohort, 21% had an unplanned hospital readmission within 30 days. Median age (interquartile range) was 54 years (41-65 yr), 4762 (53.4%) were female, and there were self-reported 1612 (18.09%) Black, 2271 (25.49%) Hispanic, and 4642 (52.1%) White individuals. In multinomial logistic regression models accounting for survival, we identified that change to nonphysician provider type due to economic reasons (aOR, 2.55 [2.35-2.74]), delay of receiving medical care due to lack of transportation (aOR, 1.68 [1.62-1.74]), and inability to afford flow-up care (aOR, 1.59 [1.52-1.66]) were strongly and independently associated with a 30-day readmission when adjusting for survival. Patients who lived in a ZIP code with a high percentage of patients in poverty and without health insurance were also more likely to be readmitted within 30 days (aOR, 1.26 [1.22-1.29] and aOR, 1.28 [1.26-1.29], respectively). Finally, we found that having a primary care provider and health insurance were associated with low odds of an unplanned 30-day readmission. CONCLUSIONS: In this multicenter retrospective cohort, several SDoH variables were strongly associated with unplanned 30-day readmission. Models predicting readmission following sepsis hospitalization may benefit from the addition of SDoH factors to traditional clinical variables.
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- 2024
37. The effects of Facebook and Instagram on the 2020 election: A deactivation experiment.
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Allcott, Hunt, Gentzkow, Matthew, Mason, Winter, Wilkins, Arjun, Barberá, Pablo, Brown, Taylor, Cisneros, Juan, Crespo-Tenorio, Adriana, Dimmery, Drew, Freelon, Deen, González-Bailón, Sandra, Guess, Andrew, Kim, Young, Lazer, David, Malhotra, Neil, Moehler, Devra, Nair-Desai, Sameer, Nait El Barj, Houda, Nyhan, Brendan, Paixao de Queiroz, Ana, Pan, Jennifer, Settle, Jaime, Thorson, Emily, Tromble, Rebekah, Velasco Rivera, Carlos, Wittenbrink, Benjamin, Zahedian, Saam, Franco, Annie, Kiewiet de Jonge, Chad, Stroud, Natalie, Tucker, Joshua, and Wojcieszak, Magdalena
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Facebook ,Instagram ,election ,polarization ,social media ,Politics ,Humans ,Social Media ,United States ,Attitude ,Male ,Female - Abstract
We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.
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- 2024
38. Association Between Sleep Apnea Treatment and Health Care Resource Use in Patients With Atrial Fibrillation
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Sterling, Kimberly L, Alpert, Naomi, Malik, Anita S, Pépin, Jean‐Louis, Benjafield, Adam V, Malhotra, Atul, Piccini, Jonathan P, Cistulli, Peter A, Nunez, Carlos M, Barrett, Meredith, and Armitstead, Jeff
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Clinical Sciences ,Heart Disease ,Clinical Research ,Health Services ,Sleep Research ,Lung ,Cardiovascular ,Good Health and Well Being ,Humans ,Female ,Atrial Fibrillation ,Male ,Middle Aged ,Retrospective Studies ,Aged ,Sleep Apnea ,Obstructive ,Continuous Positive Airway Pressure ,United States ,Health Resources ,Health Care Costs ,Hospitalization ,Patient Compliance ,Treatment Outcome ,adherence ,atrial fibrillation ,health care resource use ,obstructive sleep apnea ,positive airway pressure ,medXcloud group ** ,Cardiorespiratory Medicine and Haematology ,Cardiovascular medicine and haematology - Abstract
BackgroundObstructive sleep apnea (OSA) contributes to the generation, recurrence, and perpetuation of atrial fibrillation, and it is associated with worse outcomes. Little is known about the economic impact of OSA therapy in atrial fibrillation. This retrospective cohort study assessed the impact of positive airway pressure (PAP) therapy adherence on health care resource use and costs in patients with OSA and atrial fibrillation.Methods and resultsInsurance claims data for ≥1 year before sleep testing and 2 years after device setup were linked with objective PAP therapy use data. PAP adherence was defined from an extension of the US Medicare 90-day definition. Inverse probability of treatment weighting was used to create covariate-balanced PAP adherence groups to mitigate confounding. Of 5867 patients (32% women; mean age, 62.7 years), 41% were adherent, 38% were intermediate, and 21% were nonadherent. Mean±SD number of all-cause emergency department visits (0.61±1.21 versus 0.77±1.55 [P=0.023] versus 0.95±1.90 [P
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- 2024
39. A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy
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Shaw, Wendy J, Kidder, Michelle K, Bare, Simon R, Delferro, Massimiliano, Morris, James R, Toma, Francesca M, Senanayake, Sanjaya D, Autrey, Tom, Biddinger, Elizabeth J, Boettcher, Shannon, Bowden, Mark E, Britt, Phillip F, Brown, Robert C, Bullock, R Morris, Chen, Jingguang G, Daniel, Claus, Dorhout, Peter K, Efroymson, Rebecca A, Gaffney, Kelly J, Gagliardi, Laura, Harper, Aaron S, Heldebrant, David J, Luca, Oana R, Lyubovsky, Maxim, Male, Jonathan L, Miller, Daniel J, Prozorov, Tanya, Rallo, Robert, Rana, Rachita, Rioux, Robert M, Sadow, Aaron D, Schaidle, Joshua A, Schulte, Lisa A, Tarpeh, William A, Vlachos, Dionisios G, Vogt, Bryan D, Weber, Robert S, Yang, Jenny Y, Arenholz, Elke, Helms, Brett A, Huang, Wenyu, Jordahl, James L, Karakaya, Canan, Kian, Kourosh Cyrus, Kothandaraman, Jotheeswari, Lercher, Johannes, Liu, Ping, Malhotra, Deepika, Mueller, Karl T, O’Brien, Casey P, Palomino, Robert M, Qi, Long, Rodriguez, José A, Rousseau, Roger, Russell, Jake C, Sarazen, Michele L, Sholl, David S, Smith, Emily A, Stevens, Michaela Burke, Surendranath, Yogesh, Tassone, Christopher J, Tran, Ba, Tumas, William, and Walton, Krista S
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Chemical Sciences ,Climate Action ,Responsible Consumption and Production ,Chemical sciences - Abstract
Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.
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- 2024
40. Mandibular Jaw Movement Automated Analysis for Oral Appliance Monitoring in Obstructive Sleep Apnea: A Prospective Cohort Study
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Pépin, Jean-Louis, Cistulli, Peter A, Crespeigne, Etienne, Tamisier, Renaud, Bailly, Sébastien, Bruwier, Annick, Le-Dong, Nhat-Nam, Lavigne, Gilles, Malhotra, Atul, and Martinot, Jean-Benoît
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Dental/Oral and Craniofacial Disease ,Sleep Research ,Clinical Research ,Lung ,Humans ,Sleep Apnea ,Obstructive ,Prospective Studies ,Male ,Polysomnography ,Female ,Middle Aged ,Adult ,Mandible ,Aged ,Continuous Positive Airway Pressure ,Movement ,Monitoring ,Physiologic ,mandibular advancement device ,OSA ,oral appliance titration ,artificial intelligence ,mandibular jaw movements ,Cardiovascular medicine and haematology ,Clinical sciences - Abstract
Rationale: Oral appliances are second-line treatments after continuous positive airway pressure for obstructive sleep apnea (OSA) management. However, the need for oral appliance titration limits their use as a result of monitoring challenges to assess the treatment effect on OSA. Objectives: To assess the validity of mandibular jaw movement (MJM) automated analysis compared with polysomnography (PSG) and polygraphy (PG) in evaluating the effect of oral appliance treatment and the effectiveness of MJM monitoring for oral appliance titration at home in patients with OSA. Methods: This observational, prospective study included 135 patients with OSA eligible for oral appliance therapy. The primary outcome was the apnea-hypopnea index (AHI), measured through in-laboratory PSG/PG and MJM-based technology. Additionally, MJM monitoring at home was conducted at regular intervals during the titration process. The agreement between PSG/PG and MJM automated analysis was revaluated using Bland-Altman analysis. Changes in AHI during the home-based oral appliance titration process were evaluated using a generalized linear mixed model and a generalized estimating equation model. Results: The automated MJM analysis demonstrated strong agreement with PG in assessing AHI at the end of titration, with a median bias of 0.24/h (limits of agreement, -11.2 to 12.8/h). The improvement of AHI from baseline in response to oral appliance treatment was consistent across three evaluation conditions: in-laboratory PG (-59.6%; 95% confidence interval, -59.8% to -59.5%), in-laboratory automated MJM analysis (-59.2%; -65.2% to -52.2%), and at-home automated MJM analysis (-59.7%; -67.4% to -50.2%). Conclusions: Incorporating MJM automated analysis into the oral appliance titration process has the potential to optimize oral appliance therapy outcomes for OSA.
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- 2024
41. Differences between Stable and Unstable Architectures of Compact Planetary Systems
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Volk, Kathryn and Malhotra, Renu
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Astrophysics - Earth and Planetary Astrophysics - Abstract
We present a stability analysis of a large set of simulated planetary systems of three or more planets based on architectures of multiplanet systems discovered by \textit{Kepler} and \textit{K2}. We propagated 21,400 simulated planetary systems up to 5 billion orbits of the innermost planet; approximately 13% of these simulations ended in a planet-planet collision within that timespan. We examined trends in dynamical stability based on dynamical spacings, orbital period ratios, and mass ratios of nearest-neighbor planets as well as the system-wide planet mass distribution and the spectral fraction describing the system's short-term evolution. We find that instability is more likely in planetary systems with adjacent planet pairs that have period ratios less than two and in systems of greater variance of planet masses. Systems with planet pairs at very small dynamical spacings (less than $\sim10-12$ mutual Hill radius) are also prone to instabilities, but instabilities also occur at much larger planetary separations. We find that a large spectral fraction (calculated from short integrations) is a reasonable predictor of longer-term dynamical instability; systems that have a large number of Fourier components in their eccentricity vectors are prone to secular chaos and subsequent eccentricity growth and instabilities., Comment: accepted for publication in AJ
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- 2024
42. MindSet: Vision. A toolbox for testing DNNs on key psychological experiments
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Biscione, Valerio, Yin, Dong, Malhotra, Gaurav, Dujmovic, Marin, Montero, Milton L., Puebla, Guillermo, Adolfi, Federico, Heaton, Rachel F., Hummel, John E., Evans, Benjamin D., Habashy, Karim, and Bowers, Jeffrey S.
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision. In almost all cases these benchmarks are observational in the sense they are composed of behavioural and brain responses to naturalistic images that have not been manipulated to test hypotheses regarding how DNNs or humans perceive and identify objects. Here we introduce the toolbox MindSet: Vision, consisting of a collection of image datasets and related scripts designed to test DNNs on 30 psychological findings. In all experimental conditions, the stimuli are systematically manipulated to test specific hypotheses regarding human visual perception and object recognition. In addition to providing pre-generated datasets of images, we provide code to regenerate these datasets, offering many configurable parameters which greatly extend the dataset versatility for different research contexts, and code to facilitate the testing of DNNs on these image datasets using three different methods (similarity judgments, out-of-distribution classification, and decoder method), accessible at https://github.com/MindSetVision/mindset-vision. We test ResNet-152 on each of these methods as an example of how the toolbox can be used.
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- 2024
43. Direct, simple, and efficient computation of all components of the virtual-casing magnetic field in axisymmetric geometries with Kapur-Rokhlin quadrature
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Toler, Evan, Cerfon, Antoine, and Malhotra, Dhairya
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Physics - Plasma Physics - Abstract
In a recent publication (Toler et al. 2023), we demonstrated that for axisymmetric geometries, the Kapur-Rokhlin quadrature rule provided an efficient and high-order accurate method for computing the normal component, on the plasma surface, of the magnetic field due to the toroidal current flowing in the plasma, via the virtual-casing principle. The calculation was indirect, as it required the prior computation of the magnetic vector potential from the virtual-casing principle, followed by the computation of its tangential derivative by Fourier differentiation, in order to obtain the normal component of the magnetic field. Our approach did not provide the other components of the virtual-casing magnetic field. In this letter, we show that a more direct and more general approach is available for the computation of the virtual-casing magnetic field. The Kapur-Rokhlin quadrature rule accurately calculates the principal value integrals in the expression for all the components of the magnetic field on the plasma boundary, and the numerical error converges at a rate nearly as high as the indirect method we presented previously., Comment: 14 pages, 6 figures
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- 2024
44. Towards Inclusive Video Commenting: Introducing Signmaku for the Deaf and Hard-of-Hearing
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Chen, Si, Cheng, Haocong, Situ, Jason, Kirst, Desirée, Su, Suzy, Malhotra, Saumya, Angrave, Lawrence, Wang, Qi, and Huang, Yun
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Computer Science - Human-Computer Interaction ,F.2.2 ,I.2.7 - Abstract
Previous research underscored the potential of danmaku--a text-based commenting feature on videos--in engaging hearing audiences. Yet, for many Deaf and hard-of-hearing (DHH) individuals, American Sign Language (ASL) takes precedence over English. To improve inclusivity, we introduce "Signmaku," a new commenting mechanism that uses ASL, serving as a sign language counterpart to danmaku. Through a need-finding study (N=12) and a within-subject experiment (N=20), we evaluated three design styles: real human faces, cartoon-like figures, and robotic representations. The results showed that cartoon-like signmaku not only entertained but also encouraged participants to create and share ASL comments, with fewer privacy concerns compared to the other designs. Conversely, the robotic representations faced challenges in accurately depicting hand movements and facial expressions, resulting in higher cognitive demands on users. Signmaku featuring real human faces elicited the lowest cognitive load and was the most comprehensible among all three types. Our findings offered novel design implications for leveraging generative AI to create signmaku comments, enriching co-learning experiences for DHH individuals., Comment: 14 pages, CHI 2024
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- 2024
45. Understanding Domain-Size Generalization in Markov Logic Networks
- Author
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Chen, Florian, Weitkämper, Felix, and Malhotra, Sagar
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Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
We study the generalization behavior of Markov Logic Networks (MLNs) across relational structures of different sizes. Multiple works have noticed that MLNs learned on a given domain generalize poorly across domains of different sizes. This behavior emerges from a lack of internal consistency within an MLN when used across different domain sizes. In this paper, we quantify this inconsistency and bound it in terms of the variance of the MLN parameters. The parameter variance also bounds the KL divergence between an MLN's marginal distributions taken from different domain sizes. We use these bounds to show that maximizing the data log-likelihood while simultaneously minimizing the parameter variance corresponds to two natural notions of generalization across domain sizes. Our theoretical results apply to Exponential Random Graphs and other Markov network based relational models. Finally, we observe that solutions known to decrease the variance of the MLN parameters, like regularization and Domain-Size Aware MLNs, increase the internal consistency of the MLNs. We empirically verify our results on four different datasets, with different methods to control parameter variance, showing that controlling parameter variance leads to better generalization., Comment: To Appear in Proceedings of ECML 2024-Research Track
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- 2024
46. Who Uses Personas in Requirements Engineering: The Practitioners' Perspective
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Wang, Yi, Arora, Chetan, Liu, Xiao, Hoang, Thuong, Malhotra, Vasudha, Cheng, Ben, and Grundy, John
- Subjects
Computer Science - Software Engineering - Abstract
Personas are commonly used in software projects to gain a better understanding of end-users' needs. However, there is a limited understanding of their usage and effectiveness in practice. This paper presents the results of a two-step investigation, comprising interviews with 26 software developers, UI/UX designers, business analysts and product managers and a survey of 203 practitioners, aimed at shedding light on the current practices, methods and challenges of using personas in software development. Our findings reveal variations in the frequency and effectiveness of personas across different software projects and IT companies, the challenges practitioners face when using personas and the reasons for not using them at all. Furthermore, we investigate the coverage of human aspects in personas, often assumed to be a key feature of persona descriptions. Contrary to the general perception, our study shows that human aspects are often ignored for various reasons in personas or requirements engineering in general. Our study provides actionable insights for practitioners to overcome challenges in using personas during requirements engineering stages, and we identify areas for future research.
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- 2024
47. On the Metallicity Gradients in the Galactic Disk using Open Clusters
- Author
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Joshi, Yogesh C., Deepak, and Malhotra, Sagar
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Astrophysics - Astrophysics of Galaxies - Abstract
We study the metallicity distribution and evolution in the Galactic disk based on the largest sample of open star clusters in the Galaxy. From the catalogue of 1879 open clusters in the range of Galactocentric distance (R_GC) from 4 to 20 kpc, we investigate the variation of metallicity in the Galactic disk as functions of R_GC, vertical distance (Z), and ages of the clusters. In the direction perpendicular to the Galactic plane, variation in metallicity is found to follow a stepped linear relation. We estimate a vertical metallicity gradient d[Fe/H]/dZ of -0.545+/-0.046 dex/kpc for |Z| < 0.487 kpc, and -0.075+/-0.093 dex/kpc for 0.487 < |Z| < 1.8 kpc. On average, metallicity variations above and below the Galactic plane are found to change at similar rates. The change in metallicity in the radial direction is also found to follow a two-function linear relation. We obtain a radial metallicity gradient d[Fe/H]/d[R_GC] of -0.070+/-0.002 dex/kpc for 4.0
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- 2024
48. Beyond the Mean: Testing Consumer Rationality through Higher Moments of Demand
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Maes, Sebastiaan and Malhotra, Raghav
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Economics - Theoretical Economics - Abstract
We study a setting where an analyst has access to purely aggregate information about the consumption choices of a heterogenous population of individuals. We show that observing the statistical moments of market demand allows the analyst to test aggregate data for rationality. Interestingly, just the mean and variance of demand carry observable restrictions. This is in stark contrast to impossibility result of the Sonnenschein-Mantel-Debreu theorem, which shows that aggregate demand carries no observable restrictions at all. We leverage our approach to deliver a characterization of rationality in terms of moments for the common two-good case. We illustrate the usefulness of moment-based restrictions through two applications: (i) improving the precision of demand and welfare estimates; and (ii) testing for the existence of a welfare-relevant representative consumer., Comment: arXiv admin note: substantial text overlap with arXiv:2303.01231
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- 2024
49. Summary Paper: Use Case on Building Collaborative Safe Autonomous Systems-A Robotdog for Guiding Visually Impaired People
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Malhotra, Aman and Saidi, Selma
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Computer Science - Robotics ,Computer Science - Artificial Intelligence ,Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Multiagent Systems ,Electrical Engineering and Systems Science - Systems and Control - Abstract
This is a summary paper of a use case of a Robotdog dedicated to guide visually impaired people in complex environment like a smart intersection. In such scenarios, the Robotdog has to autonomously decide whether it is safe to cross the intersection or not in order to further guide the human. We leverage data sharing and collaboration between the Robotdog and other autonomous systems operating in the same environment. We propose a system architecture for autonomous systems through a separation of a collaborative decision layer, to enable collective decision making processes, where data about the environment, relevant to the Robotdog decision, together with evidences for trustworthiness about other systems and the environment are shared.
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- 2024
50. Measuring kinematic anisotropies with pulsar timing arrays
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Cruz, N. M. Jiménez, Malhotra, Ameek, Tasinato, Gianmassimo, and Zavala, Ivonne
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General Relativity and Quantum Cosmology ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
Recent Pulsar Timing Array (PTA) collaborations show strong evidence for a stochastic gravitational wave background (SGWB) with the characteristic Hellings-Downs inter-pulsar correlations. The signal may stem from supermassive black hole binary mergers, or early universe phenomena. The former is expected to be strongly anisotropic while primordial backgrounds are likely to be predominantly isotropic with small fluctuations. In case the observed SGWB is of cosmological origin, our relative motion with respect to the SGWB rest frame is a guaranteed source of anisotropy, leading to $\textit{O}(10^{-3})$ energy density fluctuations of the SGWB. For such cosmological SGWB, kinematic anisotropies are likely to be larger than the intrinsic anisotropies, akin to the cosmic microwave background (CMB) dipole anisotropy. We assess the sensitivity of current PTA data to the kinematic dipole anisotropy, and we also forecast at what extent the magnitude and direction of the kinematic dipole can be measured in the future with an SKA-like experiment. We also discuss how the spectral shape of the SGWB and the location of the pulsars to monitor affect the prospects of detecting the kinematic dipole with PTA. In the future, a detection of this anisotropy may even help resolve the discrepancy in the magnitude of the kinematic dipole as measured by CMB and large-scale structure observations., Comment: 29 pages, 6 figures. V2: corrected upper limit, updated forecasts
- Published
- 2024
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