Enhancement of speech scrambles using DNA technique and chaotic maps over transformation domain

This work presents and describes a new method for speech scrambles in light of chaotic maps and DNA coding. Both a wavelet transform (DWT) and Discrete cosine transform (DCT) are used to change the speech signal into another format for processing. The chaotic maps are represented by Logistic-Chebyshev map (LCH) and Random Logistic map (RLM) which are employed for generating sequences of keys that are used in the proposed system, hence the use of DNA encoding technology as an emerging technology for enhancing the security of speech. The proposed system is illustrated explicitly and tested with various security speech signals metrics, such as the coefficient, signal to noise ratio and peak signal to noise ratio. All tests of the proposed system concluded that the speech signal is reliably secure and undetectable, and hence the proposed system provides a sufficient security level

Enhanced the prediction approach of diabetes using an autoencoder with regularization and deep neural network

Diabetes mellitus is considered one of the foremost common and extreme diseases worldwide. A precise and early diagnosis of diabetes is essential to avoid complications and is of crucial importance to the medical care that patients get. To achieve that, we need to develop a model to predict diabetes. There are many prediction models, but they suffer from some problems such as the accuracy of prediction being poor and the time complexity. The prediction process is highly dependent on important features. So, in this paper, we proposed a new model called (CAER-DNN) that depends on an unsupervised technique for generating newly important features and a deep neural network for the prediction process. The unsupervised technique is called complete autoencoder with regularization techniques (CAER) that uses to reconstruct the original features (newly learned features). It is focused too much on training the most important learned features and misses out on less important features. Thus, improving the performance of the prediction process. These important features are used as input to the deep neural network for the prediction of diabetes. Our model is applied to two sets of data including Pima Indian and Mendeley diabetic datasets. Based on the 10-fold cross-validation technique Pima Indian dataset achieves high performance in evaluation measures (f1-score 97.38%, accuracy, recall 97.25%, specificity 97.59%, precision 97.53%,). While the Mendeley diabetes dataset achieved high performance in evaluation measures (f1-score 94.51%, accuracy 98.48, recall 91.74%, accuracy-balance 98.21%, precision 98.21%) based on the holdout technique. compared with other existing machine learning and deep learning techniques our model outperformed existing techniques

Hemodynamic Effects of Vecuronium at Time of Induction

Objective: The aim of the study to evaluate the influence of vecuronium on heart rate, systolic & diastolic arterial blood pressure (hemodynamic stress response) during nitrous oxide – halothane anesthesia.A double-blind study was done in Aljamhori teaching hospital, Mosul city, Iraq from (February 2011 – May2013); All the patients were in the age of 16-47 years, and ASA1. In this study 60 patients males & females prepared for elective surgery; Vecuronium was administered to 30 patients named (Group A) & normal saline was administered to another 30 patients (Group B); Heart rate & arterial blood pressure were monitored immediately before induction, at time of induction & (0, 3, 4, 5) minutes after induction of anesthesia. There were no significant differences in sex, weight & age of patients also there was no significant differences statistically between the two groups (P > 0.05) in heart rate & arterial blood pressure in pre induction, after induction & maintenance of anesthesia. In conclusion; Vecuronium had no effect on hemodynamic stress response during general anesthesia

New Conjugate Gradient Method for Unconstrained Optimization with Logistic Mapping

In this paper , we suggested a new conjugate gradient algorithm for unconstrained optimization based on logistic mapping, descent condition and sufficient descent condition for our  method are provided. Numerical results show that our presented algorithm is more efficient for solving nonlinear unconstrained optimization problems comparing with (DY)

It is time to define an organizational model for the prevention and management of infections along the surgical pathway : a worldwide cross-sectional survey

Background The objectives of the study were to investigate the organizational characteristics of acute care facilities worldwide in preventing and managing infections in surgery; assess participants' perception regarding infection prevention and control (IPC) measures, antibiotic prescribing practices, and source control; describe awareness about the global burden of antimicrobial resistance (AMR) and IPC measures; and determine the role of the Coronavirus Disease 2019 pandemic on said awareness. Methods A cross-sectional web-based survey was conducted contacting 1432 health care workers (HCWs) belonging to a mailing list provided by the Global Alliance for Infections in Surgery. The self-administered questionnaire was developed by a multidisciplinary team. The survey was open from May 22, 2021, and June 22, 2021. Three reminders were sent, after 7, 14, and 21 days. Results Three hundred four respondents from 72 countries returned a questionnaire, with an overall response rate of 21.2%. Respectively, 90.4% and 68.8% of participants stated their hospital had a multidisciplinary IPC team or a multidisciplinary antimicrobial stewardship team. Local protocols for antimicrobial therapy of surgical infections and protocols for surgical antibiotic prophylaxis were present in 76.6% and 90.8% of hospitals, respectively. In 23.4% and 24.0% of hospitals no surveillance systems for surgical site infections and no monitoring systems of used antimicrobials were implemented. Patient and family involvement in IPC management was considered to be slightly or not important in their hospital by the majority of respondents (65.1%). Awareness of the global burden of AMR among HCWs was considered very important or important by 54.6% of participants. The COVID-19 pandemic was considered by 80.3% of respondents as a very important or important factor in raising HCWs awareness of the IPC programs in their hospital. Based on the survey results, the authors developed 15 statements for several questions regarding the prevention and management of infections in surgery. The statements may be the starting point for designing future evidence-based recommendations. Conclusion Adequacy of prevention and management of infections in acute care facilities depends on HCWs behaviours and on the organizational characteristics of acute health care facilities to support best practices and promote behavioural change. Patient involvement in the implementation of IPC is still little considered. A debate on how operationalising a fundamental change to IPC, from being solely the HCWs responsibility to one that involves a collaborative relationship between HCWs and patients, should be opened.Peer reviewe

It is time to define an organizational model for the prevention and management of infections along the surgical pathway: a worldwide cross-sectional survey

Background The objectives of the study were to investigate the organizational characteristics of acute care facilities worldwide in preventing and managing infections in surgery; assess participants' perception regarding infection prevention and control (IPC) measures, antibiotic prescribing practices, and source control; describe awareness about the global burden of antimicrobial resistance (AMR) and IPC measures; and determine the role of the Coronavirus Disease 2019 pandemic on said awareness. Methods A cross-sectional web-based survey was conducted contacting 1432 health care workers (HCWs) belonging to a mailing list provided by the Global Alliance for Infections in Surgery. The self-administered questionnaire was developed by a multidisciplinary team. The survey was open from May 22, 2021, and June 22, 2021. Three reminders were sent, after 7, 14, and 21 days. Results Three hundred four respondents from 72 countries returned a questionnaire, with an overall response rate of 21.2%. Respectively, 90.4% and 68.8% of participants stated their hospital had a multidisciplinary IPC team or a multidisciplinary antimicrobial stewardship team. Local protocols for antimicrobial therapy of surgical infections and protocols for surgical antibiotic prophylaxis were present in 76.6% and 90.8% of hospitals, respectively. In 23.4% and 24.0% of hospitals no surveillance systems for surgical site infections and no monitoring systems of used antimicrobials were implemented. Patient and family involvement in IPC management was considered to be slightly or not important in their hospital by the majority of respondents (65.1%). Awareness of the global burden of AMR among HCWs was considered very important or important by 54.6% of participants. The COVID-19 pandemic was considered by 80.3% of respondents as a very important or important factor in raising HCWs awareness of the IPC programs in their hospital. Based on the survey results, the authors developed 15 statements for several questions regarding the prevention and management of infections in surgery. The statements may be the starting point for designing future evidence-based recommendations. Conclusion Adequacy of prevention and management of infections in acute care facilities depends on HCWs behaviours and on the organizational characteristics of acute health care facilities to support best practices and promote behavioural change. Patient involvement in the implementation of IPC is still little considered. A debate on how operationalising a fundamental change to IPC, from being solely the HCWs responsibility to one that involves a collaborative relationship between HCWs and patients, should be opened

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill &amp; Melinda Gates Foundation

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