A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- that of automatically learning problem-specific features. With this new paradigm, every problem in computer vision is now being re-examined from a deep learning perspective. Therefore, it has become important to understand what kind of deep networks are suitable for a given problem. Although general surveys of this fast-moving paradigm (i.e. deep-networks) exist, a survey specific to computer vision is missing. We specifically consider one form of deep networks widely used in computer vision - convolutional neural networks (CNNs). We start with "AlexNet" as our base CNN and then examine the broad variations proposed over time to suit different applications. We hope that our recipe-style survey will serve as a guide, particularly for novice practitioners intending to use deep-learning techniques for computer vision.Comment: Published in Frontiers in Robotics and AI (http://goo.gl/6691Bm

Resolution of Inflammation in Periodontitis: A Comprehensive Review

Inflammation, a natural defence mechanism against injury or infection, can become problematic when it fails to resolve, as observed in conditions like periodontitisThis review explores how inflammation is resolved in periodontitis and seeks potential treatments for this chronic condition, which damages the periodontium, including the gingival tissue, periodontal ligament, and alveolar bone. The pathogenesis of this disease is initiated by the inflammatory response triggered by resident leukocytes and endothelial cells upon exposure to bacterial biofilms, resulting in vasodilation and immune cell recruitment. The review stresses the importance of researching targeted approaches for periodontitis treatment, such as inducing neutrophil apoptosis, shifting from M1 to M2 macrophages, and exploring M2-based tissue engineering. Additionally, investigating lymphangiogenesis and Treg cell recruitment at the inflammation site offers promising avenues. In conclusion, further studies are needed to refine lymphangiogenesis and assess the potential of pro-resolving lipid mediators and anti-inflammatory cytokines in managing periodontitis. Ongoing research aims to uncover the underlying biomolecular mechanisms governing immune cells and resolving mediators, with the ultimate goal of restoring tissue equilibrium and promoting healing

APPLICATION OF TAGUCHI METHOD AND ANOVA IN OPTIMIZATION OF CUTTING PARAMETERS FOR MATERIAL REMOVAL RATE AND SURFACE ROUGHNESS IN TURNING OPERATION

ABSTRACT The intend of this research work is to employ Taguchi method and Analysis of Variance to find out the influences of cutting parameters such as spindle speed, depth of cut and feed on material removal rate and surface roughness for their optimization. The experimental results obtained were analyzed to find out the most significant factor effecting MRR and surface roughness. Spindle speed was found to be the most significant parameter influencing material removal rate followed by feed and depth of cut in turning of mild steel (0.18% C). Feed rate was found to be the most influencing parameter in case of surface roughness

AT2018cow: a luminous millimeter transient

We present detailed submillimeter- through centimeter-wave observations of the extraordinary extragalactic transient AT2018cow. The apparent characteristics—the high radio luminosity, the rise and long-lived emission plateau at millimeter bands, and the sub-relativistic velocity—have no precedent. A basic interpretation of the data suggests E_k ≳ 4 x 10^(48) erg coupled to a fast but sub-relativistic (ν ≈ 0.13c) shock in a dense (n_e ≈ 3 x 10^5 cm^(-3)) medium. We find that the X-ray emission is not naturally explained by an extension of the radio-submm synchrotron spectrum, nor by inverse Compton scattering of the dominant blackbody UV/optical/IR photons by energetic electrons within the forward shock. By Δt ≈ 20 days, the X-ray emission shows spectral softening and erratic inter-day variability. Taken together, we are led to invoke an additional source of X-ray emission: the central engine of the event. Regardless of the nature of this central engine, this source heralds a new class of energetic transients shocking a dense medium, which at early times are most readily observed at millimeter wavelengths

Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2

Publisher Copyright: © 2021 O'Toole Á et al.Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.Peer reviewe

Use of multidimensional item response theory methods for dementia prevalence prediction : an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. Conclusions Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18 : a geospatial modelling study

Background More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.Methods We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km x 5 km resolution in 98 LMICs based on 2.1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.Findings Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205000 (95% uncertainty interval 147000-257000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.Interpretation Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe