198 research outputs found

    Scavenger: A Cloud Service for Optimizing Cost and Performance of ML Training

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    While the pay-as-you-go nature of cloud virtual machines (VMs) makes it easy to spin-up large clusters for training ML models, it can also lead to ballooning costs. The 100s of virtual machine sizes provided by cloud platforms also makes it extremely challenging to select the ``right'' cloud cluster configuration for training. Furthermore, the training time and cost of distributed model training is highly sensitive to the cluster configurations, and presents a large and complex tradeoff-space. In this paper, we develop principled and practical techniques for optimizing the training time and cost of distributed ML model training on the cloud. Our key insight is that both parallel and statistical efficiency must be considered when selecting the optimum job configuration parameters such as the number of workers and the batch size. By combining conventional parallel scaling concepts and new insights into SGD noise, our models accurately estimate the time and cost on different cluster configurations with < 5% error. Using the repetitive nature of training and our models, we can search for optimum cloud configurations in a black-box, online manner. Our approach reduces training times by 2 times and costs more more than 50%. Compared to an oracle-based approach, our performance models are accurate to within 2% such that the search imposes an overhead of just 10%

    Future Indian Ocean warming patterns

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    Strong negative climatological air-sea interactions effectively damp warming over the eastern Indian Ocean, resulting in weakening of the winds therein. This, in turn, changes the strength of ocean currents, which is considered as the primary mechanism responsible for modulating warming patterns

    Seasonal variability of the surface ocean carbon cycle: A synthesis

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    Abstract The seasonal cycle is the dominant mode of variability in the air‐sea CO 2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes phase 2 project (RECCAP2), we synthesize surface ocean p CO 2 and air‐sea CO 2 flux seasonality from models and observation‐based estimates, focusing on both a present‐day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation‐based estimates ( p CO 2 products) of surface p CO 2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in p CO 2 has increased in amplitude over the last three decades in both p CO 2 products and GOBMs. Third, decadal increases in p CO 2 seasonal cycle amplitudes in subtropical biomes for both p CO 2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO 2 (C ant ). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by C ant invasion, whereas for p CO 2 products an indeterminate combination of C ant invasion and climate change modulates the changes. Fourth, biome‐aggregated decadal changes in the amplitude of p CO 2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high‐quality seasonally‐resolved measurements over these regions

    A Study on Rapidly Exploring Random Tree Algorithms for Robot Path Planning

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    Robot path planning is a critical feature of autonomous systems. Rapidly-exploring Random Trees (RRT) is a path planning technique that randomly samples the robot configuration space to find a path between the start and end point. This thesis studies and compares the performance of four important RRT algorithms, namely, the original RRT, the optimal RRT (also termed RRT*), RRT*-Smart, and Informed RRT* for six different environments. The performance measures include the final path length (which is also the shortest path length found by each algorithm), time to find the first path, run time (of 1000 iterations) for each algorithm, total number of sampling nodes, and success rate (out of 100 runs). It is found that both RRT*-Smart and Informed RRT* algorithm result in shorter path lengths than the original RRT and RRT*. Typically, RRT*-Smart can find a suboptimal path in less number of iterations while the Informed RRT* is able to find the shortest path with increased number of iterations. On the other hand, the original RRT and RRT* are better suited for real-time applications as the Informed RRT* and RRT*-Smart have longer run time due to the additional steps in their processes

    Systems-level analyses of protein-protein interaction network dysfunctions via epichaperomics identify cancer-specific mechanisms of stress adaptation

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    Abstract Systems-level assessments of protein-protein interaction (PPI) network dysfunctions are currently out-of-reach because approaches enabling proteome-wide identification, analysis, and modulation of context-specific PPI changes in native (unengineered) cells and tissues are lacking. Herein, we take advantage of chemical binders of maladaptive scaffolding structures termed epichaperomes and develop an epichaperome-based ‘omics platform, epichaperomics, to identify PPI alterations in disease. We provide multiple lines of evidence, at both biochemical and functional levels, demonstrating the importance of these probes to identify and study PPI network dysfunctions and provide mechanistically and therapeutically relevant proteome-wide insights. As proof-of-principle, we derive systems-level insight into PPI dysfunctions of cancer cells which enabled the discovery of a context-dependent mechanism by which cancer cells enhance the fitness of mitotic protein networks. Importantly, our systems levels analyses support the use of epichaperome chemical binders as therapeutic strategies aimed at normalizing PPI networks

    Correlation between Vascularity and Advancing Histological Grades of Oral Submucous Fibrosis with a Plausible Role in Malignisation: Systematic review of a persisting matter of conflict

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    Objectives: Recent studies showed that as the stage advances there is no significant change in the vascularity as opposed to the conventional concept, thus, the present was designed to quantify the vascularity in histological grades of OSMF and to assess if there is any connection between vasculogenesis and malignisation. Methods: A comprehensive database search was done for published articles on vascularity in oral submucous fibrosis following PRISMA guidelines without date constrains; the search was done till December 2022. The review was registered in Prospero. After screening 607 articles, a total of 13 studies were finally included for systematic evaluation. Results: A total of 607 cases were included, with a definite predilection for the male gender. 11/13 studies evaluated mean vascular density; in more than half, the vascularity decreased as the stage advanced. Similar results were obtained for endothelial cells /square ÎŒm, mean vascular area percentage &amp; mean vascular area. Conclusion: The present review&nbsp;supports the prevailing concept that vascularity decreases with&nbsp;advancement of the stage of OSMF, denying systemic absorption of carcinogens into the circulation with resultant longer exposure of compromised epithelium and malignisation. Keywords: Malignisation; Mean Vascular Density; Oral Submucous Fibrosis; OSMF; Vascularity

    Identification of diphenylurea derivatives as novel endocytosis inhibitors that demonstrate broad-spectrum activity against SARS-CoV-2 and influenza A virus both in vitro and in vivo.

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    Rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A virus (IAV) poses enormous challenge in the development of broad-spectrum antivirals that are effective against the existing and emerging viral strains. Virus entry through endocytosis represents an attractive target for drug development, as inhibition of this early infection step should block downstream infection processes, and potentially inhibit viruses sharing the same entry route. In this study, we report the identification of 1,3-diphenylurea (DPU) derivatives (DPUDs) as a new class of endocytosis inhibitors, which broadly restricted entry and replication of several SARS-CoV-2 and IAV strains. Importantly, the DPUDs did not induce any significant cytotoxicity at concentrations effective against the viral infections. Examining the uptake of cargoes specific to different endocytic pathways, we found that DPUDs majorly affected clathrin-mediated endocytosis, which both SARS-CoV-2 and IAV utilize for cellular entry. In the DPUD-treated cells, although virus binding on the cell surface was unaffected, internalization of both the viruses was drastically reduced. Since compounds similar to the DPUDs were previously reported to transport anions including chloride (Cl-) across lipid membrane and since intracellular Cl- concentration plays a critical role in regulating vesicular trafficking, we hypothesized that the observed defect in endocytosis by the DPUDs could be due to altered Cl- gradient across the cell membrane. Using in vitro assays we demonstrated that the DPUDs transported Cl- into the cell and led to intracellular Cl- accumulation, which possibly affected the endocytic machinery by perturbing intracellular Cl- homeostasis. Finally, we tested the DPUDs in mice challenged with IAV and mouse-adapted SARS-CoV-2 (MA 10). Treatment of the infected mice with the DPUDs led to remarkable body weight recovery, improved survival and significantly reduced lung viral load, highlighting their potential for development as broad-spectrum antivirals

    Very high particulate pollution over northwest India captured by a high-density in situ sensor network

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    Abstract Exposure to particulate matter less than 2.5 ”m in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 ”g m−3 in 6–10 October to up to 500 ”g m−3 on 5–9 November, which subsequently decreased to about 100 ”g m−3 in 20–30 November. Two distinct plumes of PM2.5 over 500 ”g m−3 are tracked from crop residue burning in Punjab to Delhi NCR on 2–3 November and 10–11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales

    Accuracy of smartphone based electrocardiogram for the detection of rhythm abnormalities in limb lead: a cross sectional study, non-randomised, single blinded and single-center study

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    Background: For the identification of arrhythmia and abnormal instances, researchers are examining the reliability of the interpretation offered by smartphone-based portable ECG monitors. The indicator of an unclear alteration in the electrical activity of the heart is a cardiac abnormality. As a result, its early and accurate identification can avoid myocardial infarction and even sudden cardiac death. Objectives of this study were to evaluate and validate the Spandan 12 lead ECG interpretation for accuracy in detection of the cardiac arrhythmias in comparison to the cardiologist diagnosis, and to evaluate the accuracy of the arrhythmia detection of Spandan ECG in comparison to the 12 lead ECG machine. Methods: This cross-sectional study, non-randomised, single blinded and single-center study was carried out at Shri Mahant Indresh Hospital (SMIH), Dehradun, Uttarakhand, India from 1st August 2022 to 31st January 2023. All patients (n=312) visiting the electrocardiogram (ECG) room at the department of cardiology of the SMIH, Dehradun with the prescription of ECG screening during the study period were included in the study were included in the study. Results: In total, 1528 patients with or without a history of cardiovascular disease were enrolled from outpatient and emergency departments of cardiology. A final total of 312 participants considered for accuracy of interpretation of cardiac arrhythmias detected by the standard 12 lead ECG and smartphone ECG in comparison to cardiologists’ diagnosis. Mean age (SD) was 53.90±14.52 years. The male gender (68.78%) showed the maximum frequency than female gender. True Positive cases derived from confusion matrix for 12 lead standard ECG and smartphone ECG in comparison to cardiologist diagnosis was 264 as compared to 273 from 12 lead gold standard. Sensitivity of smartphone Spandan ECG (81.23%) was comparable to gold standard 12 Lead ECG (81.49%). And, specificity, PPV and NPV of smartphone Spandan ECG was recorded to be better than gold standard 12 Lead ECG. Arrhythmia was detected correctly in 403 (70.8%) cases and 431 (61.86%) cases by smartphone ECG and 12 lead gold standards, respectively. Conclusions: Spandan ECG device scored a high accuracy and sensitivity and high specificity. The overall accuracy of smartphone ECG in detecting the rhythm abnormalities increase by 9%, the significance rises in accuracy of computer interpretation when compared to the cardiologist’s diagnosis

    Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis

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    The seasonal cycle is the dominant mode of variability in the air-sea CO₂ flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO₂ and air-sea CO₂ flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO₂ products) of surface pCO₂ seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO₂ has increased in amplitude over the last three decades in both pCO₂ products and GOBMs. Third, decadal increases in pCO₂ seasonal cycle amplitudes in subtropical biomes for both pCO₂ products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO₂ (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO₂ products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO₂ seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions.ISSN:0886-6236ISSN:1944-922
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