Prevalence of leukoplakia, oral submucous fibrosis, papilloma and its relation with stress among green marbles mine laborers, India

Objectives: To determine the prevalence of leukoplakia, oral submucous fibrosis and papilloma among ?Green Marble Mines? laborer and uncover its relation with occupational stress. Methods: Mines were divided in four geographic zones, and participants were selected by stratified cluster sampling technique. A total of 513 subjects were included in final study which were alienated among the four age cohort 15-24 , 25-34 , 35-44, 45-54 respectively. The study was been conducted following the research methodology recommended by World Health Organization- Oral Health Surveys 1997. A questionnaire from ?Union of Shops, Distribution and Allied Worker (USDAW) Nationwide, Manchester? was used for stress assessment of mine workers and clinical examination for oral mucosa was conducted by one of the three examiner with the aid of an artificial light source. The kappa statistics for diagnosis of leukoplakia, oral submucous fibrosis and papilloma was determined (field teams versus expert) 0.81, 0.92 and 0.89 respectively two days prior to the examination. Data was analyzed using bivariate and multivariate analysis. Results: An overall elevated prevalence of all three oral-mucosal lesion was found among mine workers (36.7%), mainly leukoplakia affecting 171 mine workers (33.3%). The affected workers were having body problems like headache, backache and stressed due to under-payment. Individuals having papilloma have faced problem at work like noise, dust or fumes and poor maintenance of equipment. Multiple logistic regression analysis model of oral-mucosal lesion have shown highly significant relation (p<0.01) with increased stress, age, alcohol habits and malnutrition. Conclusion: The prevalence of oral mucosal lesion is higher, among marble mine laborers, and occupational stress can intensify the disease condition. Curative services along with prevention and stress reduction program, requires primary anticipation

Perceived stress among gravid and its effect on their oral health in Sri Ganganagar, Rajasthan, India

Background: The gestation period presents unique stresses that challenges overall psychological adaptation of a women. The present study is designed especially to focus on evaluating the effect of perceived stress on pregnant women and its effect on their oral health.Methods: A cross-sectional study was conducted among 18-30 years old, pregnant women in the Sri Ganganagar city. Prior to the clinical examination a questionnaire was used in order to collect the information which comprised of three parts and were completed through an interview. The first part comprised of demographics questionnaire, second part included oral hygiene questionnaire and third part was perceived Stress Scale. Descriptive analysis described demographics and socioeconomic characteristics. Multivariate analysis was used to describe the association between stress and various characteristics. Chi-square and Kruskal-wallis test was used to study the association of independent variables with level of stress.Results: The high stress was reported among those females who were aged > 25 years (46.66%), living in rural areas (73.33%), were employed (57.77%), were in third trimester of pregnancy (96.66%) and had no previous pregnancy experience (67.77%). The mothers in high stress group had high levels of dental diseases when compared to the other two groups (low and moderate stress).Conclusions: Based on the results, this study emphasizes on the need for a continued effort to improve the mental and oral health status of gravid women so as to reduce the incidences of psychological and physical troubles in this population predicted

Instance-Level Semantic Maps for Vision Language Navigation

Humans have a natural ability to perform semantic associations with the surrounding objects in the environment. This allows them to create a mental map of the environment which helps them to navigate on-demand when given a linguistic instruction. A natural goal in Vision Language Navigation (VLN) research is to impart autonomous agents with similar capabilities. Recently introduced VL Maps \cite{huang23vlmaps} take a step towards this goal by creating a semantic spatial map representation of the environment without any labelled data. However, their representations are limited for practical applicability as they do not distinguish between different instances of the same object. In this work, we address this limitation by integrating instance-level information into spatial map representation using a community detection algorithm and by utilizing word ontology learned by large language models (LLMs) to perform open-set semantic associations in the mapping representation. The resulting map representation improves the navigation performance by two-fold (233\%) on realistic language commands with instance-specific descriptions compared to VL Maps. We validate the practicality and effectiveness of our approach through extensive qualitative and quantitative experiments

Route of Drug Abuse and Its Impact on Oral Health-Related Quality of Life among Drug Addicts

Background: Various studies have tested quality of life (QOL) among drug addicts, however very few have reported any association between oral health-related quality of life (OHRQOL) and mode of drug administration among drug addicts. Hence, the present study was conducted aiming to evaluate the impact of mode of administration of drugs on OHRQOL among drug addicts. Methods: Data was collected using respondent-driven sampling (RDS) method among 313 male drug addicts in Sri Ganganagar, Rajasthan, India, using self-administered questionnaires on oral hygiene aids and drug addiction history. OHRQOL was recorded using Oral Health Impact Profile (OHIP-14) questionnaire. The chi-square test, t-test, and Kruskal-Wallis test were used for statistical analysis. Findings: In this study, 56.2% of the drug addicts reported practicing oral hygiene aids. The main drugs abused were heroin, cocaine, and amphetamines as 51.4%, 35.1%, and 13.4%, respectively. Most of the drug addicts were employed (82.4%) and studied up to primary education (46.3%). The highest mean values of community periodontal index (CPI) and decayed, missing, filled surface (DMFS) were found among the cocaine addicts and amphetamine abusers with rates of 3.11 ± 0.98 and 6.69 ± 8.52, respectively. Poor OHRQOL was observed among addicts who consumed drugs in inhalation since a long time irrespective of the type of the drug, but among them heroin addicted subjects had the poorest OHRQOL. Conclusion: OHRQOL was poor among the drug addicts in comparison to general population. Preventive strategies on oral health and other health promotion programs for this vulnerable group can be unified

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health 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

Timing-driven optimization problems in VLSI CAD

We study several optimization problems that arise in the design of VLSI circuits, with the satisfaction of timing constraints as the primary objective. We focus on problems where the underlying architecture is regular. Field Programmable Gate Arrays (FPGAs), identical standard cell based architectures and WSI arrays of blocks having a regular structure are the major architectures that are regular. The regularity of these architectures allows us to use powerful graph theoretic techniques that would not be possible otherwise.In this thesis we study problems at several different steps in the FPGA design flow. We address the problems of timing driven technology mapping and placement. We also study the problem of reconfiguring the placement of a circuit on an FPGA in order to tolerate faults in the logic blocks of the FPGA without significant degradation in the circuit delay. This problem is referred to as the timing driven reconfiguration problem. Timing driven reconfiguration can be used for off-line reconfiguration for yield enhancement and for on-line reconfiguration for fault tolerance. In a typical design flow, the design may be altered several times after the initial design cycle according to minor changes in the design specification either as a result of design debugging or as a result of changes in engineering requirements. In order to speed up the entire design process it is important to efficiently handle these engineering changes. We study the problem of incorporating engineering changes into a design in the presence of timing constraints. We propose a unified approach to solving the timing driven placement, reconfiguration and re-engineering problems using the concept of slack neighborhood graph.U of I OnlyETDs are only available to UIUC Users without author permissio