Framework for reversible data hiding using cost-effective encoding system for video steganography

Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data

Mechanical characterization of heat treated Al2219 hybrid composites

Aluminium alloy matrix composites with Al2O3 reinforcements exhibit superior mechanical properties and utilize in several demanding fields’ viz., automobile, aerospace, defense, sports equipment, electronics and bio-medical. The present work emphasizes on improvement of microstructure and mechanical properties of age hardened graphite and alumina reinforced Al alloy matrix hybrid composites. Different composites with a constant carbon content of 1 weight % and 0, 2, 4 and 6 weight % Al2O3 as reinforcements are fabricated by using stir casting technic and tested for hardness, tensile and impact strength. Scanning electron microscopy (SEM) is performed to analyse the failure mode under tensile load. All the composites are subjected to age hardening treatment with solutionising temperature of 530oC and aging temperatures of 100 and 200oC. The peak hardness of the composites at two aging temperatures are noted. Tensile and impact tests are conducted for the peak aged specimens. Results show substantial increase in the hardness of the age hardened specimens in the range of 34-44% in comparison with the as cast specimens. Result analysis shows increase in tensile strength (upto 40%) and decrease in impact resistance (upto 33%) with the increase in weight % of reinforcements. As the aging temperature increases a reduction in tensile strength and impact resistance is observed in each composites

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

A Liver Segmentation Algorithm with Interactive Error Correction for Abdominal CT Images: A Preliminary Study

Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceAn automatic method for segmenting the liver from the portal venous phase of abdominal CT images using the K-Means clustering method is described in this paper. We have incorporated an interactive technique for correcting the errors in the liver segmentation results using power law transformation. The proposed method was validated on abdominal CT volumes of fifteen patients obtained from Kasturba Medical College, Manipal. The average values of the various standard evaluation metrics obtained are as follows: Dice coefficient = 0.9361, Jaccard index = 0.8805, volumetric overlap error = 0.1195, absolute volume difference = 4.048%, average symmetric surface distance = 1.7282 mm and maximum symmetric surface distance = 38.039 mm. The quantitative and qualitative results obtained in our preliminary work show that the K-Means clustering technique along with power law transformation is effective in producing good liver segmentation outputs. As future work, we will attempt to automate the power law transformation technique

Resolution of total ophthalmoplegia following treatment in a case of nasopharyngeal carcinoma: A case report

Total ophthalmoplegia can occur due to malignancy, inflammation, infection, and trauma. Nasopharyngeal carcinoma is a tumor arising from epithelium of nasopharynx which can spread locally as well as metastasize to distant sites. We report a case of total ophthalmoplegia in a 15-year-old girl which resolved following chemotherapy. She was diagnosed as stage IV B nasopharyngeal carcinoma with left-sided intraorbital extension leading to proptosis and total ophthalmoplegia with preserved optic nerve function. Following 2 months of chemotherapy, a reduction in the size of cervical lymph nodes, proptosis, and total resolution of extraocular movements was noted

Clinico-etiological study of 30 erythroderma cases from tertiary center in South India

Background: Erythroderma is a morphological reaction pattern of skin having many underlying causes and finding the etiology helps in the proper management of erythroderma cases. Aim: To evaluate the clinical profile, etiology of erythroderma and to correlate clinical diagnosis with histopathology. Materials and Methods: This study was performed at the department of dermatology, Father Muller Medical College and Hospital, Mangalore, South India. We studied 30 consecutive cases of erythroderma with respect to the epidemiological, clinical and histological data. Clinico-histological correlation was analyzed for etiology of erythroderma. Results: The mean age of onset was 52.3 years with a male to female ratio of 14:1. In addition to erythroderma, other co-existent features included pruritus, fever, lymphadenopathy, and edema. Of the pre-existing dermatoses, psoriasis was the most common (33.3%) disease followed by eczema (20%), atopic dermatitis (6.6%), pityriasis rubra pilaris (3.3%) and drug-induced erythroderma (16.6%). In 16.6% of cases, etiology could not be ascertained. Clinico-histopathological correlation could be established in 73.3% of cases. Conclusion: Clinical features were identical irrespective of etiology. Detailed clinico-histopathological examination helps to establish the etiology of erythroderma