Constitutive modeling and characterization of nanocomposite hydrogel for blast resistant materials

In the recent trend of advanced material research, manufacturing novel materials with improved properties and multifunctionality is an important focus across disciplines. As a material, hydrogel finds several applications in the area of biomedical engineering. They are used widely in tissue regeneration, scaffolding, drug delivery, etc. However, using hydrogels for mechanical load bearing application is still limited because of its poor stiffness and low toughness. Like other polymers hydrogels have viscoelasticity which indicates it has potentials to be used as an energy absorbing material. Researchers have already been working on producing tough hydrogels by manufacturing double network hydrogels and nanocomposite hydrogels. As expected, the area of research on hydrogels greatly focus on its material science and chemistry perspective and to a lesser extent on constitutive characterization of the material. In order to produce a superior material out of hydrogels, which will have improved mechanical properties and multifunctionality, a mathematical framework needs to be developed for characterizing the constitutive response of these materials. A physically motivated mathematical model would essentially fasten manufacturing novel hydrogels for various engineering applications. In this study, the goal is to develop a constitutive model for predicting the high rate response of nanocomposite hydrogels. The model is proposed in finite deformation framework because deformation associated with hydrogel is substantially higher than other polymers. In order to predict the viscoelastic response of hydrogels a time-dependent nonlinear stress–strain law is proposed where parameters evolve over time. The constitutive model consists of several branches of spring and dashpot combinations to account for the viscoelastic property in terms of multiple characteristic relaxation times. The nonlinear behavior is modeled using Arruda–Boyce hyperelastic potential function to capture the high stretch behavior in hydrogel. Experimental stress relaxation data from literature for covalently crosslinked alginate hydrogel was fitted to find the characteristic relaxation times. The requirement for a blast resistant material is to have moderately high stiffness, high energy absorbing capacity, with significantly high fracture toughness and preferably a self-healing capacity. The model will also be extended to consider the stimuli sensitive behavior of the hydrogels and eventually will focus on providing guidelines for manufacturing hydrogels which can be used as blast resistant materials

Recent Advances in Angiogenesis Assessment Methods and their Clinical Applications

Angiogenesis, a natural phenomenon of developing new blood vessels, is an integral part of normal developmental processes as well as numerous pathological states in humans. The angiogenic assays are reliable predictors of certain pathologies in particular tumor growth, metastasis, inflammation, wound healing, tissue regeneration, ischemia, cardiovascular, and ocular diseases. The angiogenic inducer and inhibitor studies rely on both in vivo and in vitro angiogenesis methods, and various animal models are also standardized to assess qualitative and quantitative angiogenesis. Analogously, the discovery and development of anti-angiogenic agents are also based on the choice of suitable angiogenic assays and potential drug targeted sites within the angiogenic process. Similarly, the selection of cell types and compatible experimental conditions resembling the angiogenic disease being studied are also potential challenging tasks in recent angiogenesis studies. The imaging analysis systems for data acquisition from in vivo, in vitro, and in ova angiogenesis assay to preclinic, and clinical research also requires novel but easy-to-use tools and well-established protocols. The proposition of this pragmatic book chapter overviews the recent advances in angiogenesis assessment methods and discusses their applications in numerous disease pathogenesis

Dichlorvos Induced AChE Inhibition in Discrete Brain Regions and the Neuro-Cognitive Implications: Ameliorative Effect of Nigella Sativa

Background: There has been a rise in accidental poisoning cases resulting from the indiscriminate use and exposure to Dichlorvos (DDVP), especially in developing countries, and no antidote with satisfactory efficacy is currently available. Thus, we investigated the AChE reactivation potential of Nigella sativa oil (NSO) following DDVP induced AChE inhibition patterns in the brain and the associated cognitive implications. Methods: Fourty Wistar rats were randomly divided into four groups of 10 each.; The controls were administered PBS (1 ml/kg); DDVP (8.8 mg/kg) was given to the experimental group I; while DDVP+NSO (8.8 mg/kg + 1 ml/kg) and NSO (1 ml/kg) was administered orally to the experimental groups II and III respectively. All treatments lasted for 14 consecutive days. Morris Water Maze (MWM) paradigm was used to assess the working memory, then rats were euthanized, the brain excised, three brains were fixed for histological examination (Nissl staining), and the other seven brains were homogenized for AChE activity and Ca2+ concentrations. Data were analyzed statistically, using ANOVA method and P values of ≤0.05 was considered as significant. Results: In this study, DDVP differentially inhibited AChE activities in various brain regions: cerebellum (86.1%), hippocampus (40.6%), frontal cortex (33.2%), medulla (21.5%), spinal cord (14.8%), and occipital cortex (8.9%). It reduced Ca2+ concentration, but had no effect on the delayed escape latency in the MWM, nor impaired the neuro-architectures. NSO caused increased AChE activities, Ca2+ concentration and reduced escape latency, and improved histologic architectures. Conclusion: We concluded that NSO reactivated DDVP-induced AChE inhibition and improved memory indices, thus, it may serve as a potential treatment in the management of DDVP poisoning cases

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 & Melinda Gates Foundation

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Design, deformation mechanics, and failure of architectured polymeric materials

The ever-increasing demand for identifying materials with better functionality, drives the current trend in material\u27s research. Several applications in the aerospace, defense, and sports industries require the materials to have high stiffness, decent damping, high toughness, and impact resistance. Such demand gives rise to the concept of creating architecture at multiple length scales within a structural material. The focus of this dissertation is on the (i) design based on the deformation mechanics, and failure of fully dense architectured materials where the individual building blocks are geometrically interlocked, and (ii) an interface constitutive model to predict rate dependent fracture of polymeric interfaces. Starting with a brief introduction in Chapter 1, the possibility of improving both the stiffness and energy absorption in interlocking, architectured, brittle polymer blocks is investigated in Chapter 3. The interlocking mechanism allows load transfer between two different material blocks by means of contact at the mating surfaces. The contacting surfaces further act as weak interfaces that allow the polymer blocks to fail gradually under different loading conditions. Such controlled failure enhances the energy absorption of the polymer blocks but with a penalty in stiffness. It is seen from finite element simulations and experiments that incorporating hierarchy in the form of another degree of interlocking at the weak interfaces, improves stress transfer between contacting material blocks, thereby, improvement in terms of stiffness and energy absorption is achieved. In Chapter 3, a naturally inspired ``interconnection is considered within a composite material made of dissimilar mechanical properties with an objective to improve stiffness, toughness, and wave attenuation capability. The computational study showed that creation of weak interfaces along with the ``interconnection works two-fold in terms of mechanical property improvement. The interconnection provides an additional load-transfer mechanism through contact-friction between two dissimilar materials, whereas the cohesive (weak) interfaces results in higher toughness (area under the stress-strain curve) of the material promoting distributed interface failure and delaying bulk material yielding. It was further identified that the presence of weak interfaces acts better in wave attenuation for the proposed composite. In Chapter 4, a new interface constitutive model is proposed to study rate-dependent, mixed-mode interface failure for polymeric adhesives. The model accounts for both reversible elastic as well as irreversible rate dependent separation-sliding deformation at the interface. The underlying assumption is that the viscous dissipation and the irreversible separation-sliding deformation at the interface can be modeled using an elastic-viscoplastic framework. The constitutive model is implemented in a commercial finite element code following an explicit scheme. A reasonable agreement has been found between finite element simulations and experimental observations, which reinstates the predictive capability of the proposed model for estimating the rate dependent response of polymer interfaces. Finally, few future recommendations have been provided in Chapter 5

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MODELLING OF TRIP GENERATION IN FEDERAL CAPITAL TERRITORY, ABUJA (FCTA): INFLUENCE OF RESIDENTS SOCIOECONOMIC FEATURES ON TRIPS MAKING

The goal of this study is to model the numbers of trip generated in FCT, Abuja using socioeconomic characteristics of inhabitants to determine trip making. The authors utilized a correlational research design to evaluate the association between the number of trips made per day and socioeconomic characteristics (such as age, gender, marital status, monthly income, education, occupation, and the number of cars owned). The authors purposefully administered1500 surveys to Abuja residents using simple random approaches. The collected data was analyzed with frequency and percentages. While the numbers of trips per day was modelled with multiple linear regression. The findings reveals that 33.9% of the residents of Abuja make 6-7 trips per day. In addition to the findings, the socioeconomic characteristics stated above were a good predictor of the number of trips made per day by Abuja residents. The study concluded that since there is higher proportion of private car on FCT, Abuja’s Road compares to the public transport this may results to serious traffic challenge in the future. The study recommends that the Federal Government of Nigeria (FGN) through the ministry of transport should resurrect the abandoned light rail project in Abuja and ensure that the metro lines are effectively connected, which will minimize the number of private cars on Abuja's roads