A PROPOSED METHODOLOGY FOR ESTIMATING ECOREGIONAL VALUES FOR OUTDOOR RECREATION IN THE UNITED STATES

This paper provides a methodology for the estimation of recreational demand functions and values using an ecoregional approach. Ten ecoregions in the continental US were defined based on similarly functioning ecosystem characters. The individual travel cost method was employed to estimate the recreational demand functions for activities such as motorboating and waterskiing, developed and primative camping, coldwater fishing, sightseeing and pleasure driving, and big game hunting for each ecoregions. Estimates of per trip net income value range from $12.93 to$218.38 while per day estimates range from $4.31 to$109.19. While our ecoregional approach differs conceptually from previous work, our results appear consistent with the previous travel cost method valuation studies. (Missing tables 1,2,3,4,5 and 6)Recreation, ecoregion, travel cost method, truncated poisson model, Resource /Energy Economics and Policy,

Structure and Properties of Meltblown Polyetherimide as High Temperature Filter Media

Polyetherimide (PEI), an engineering plastic with very high glass transition temperature and excellent chemical and thermal stability, has been processed into a controlled porosity filter media of varying pore size, performance, and surface characteristics. A special grade of the PEI was processed by melt blowing to produce microfiber nonwovens suitable as filter media. The resulting microfiber webs were characterized to evaluate their structure and properties. The fiber webs were further modified by hot pressing, a post processing technique, which reduces the pore size in order to improve the barrier properties of the resulting membranes. This ongoing research has shown that PEI can be a good candidate for filter media requiring high temperature and chemical resistance with good mechanical properties. Also, by selecting the appropriate processing conditions, it is possible to achieve desired filtration performance from this engineering plastic

Evaluation of COVID-19 Vaccination Websites Using DISCERN and Quality Evaluation Scoring (QUEST) Tools

Background: The objective of this paper was to evaluate the COVID-19 vaccine registration website across UN-recognized member states for their portal quality, reliability, Ease Use and help to the general population in informed decision making.Methods: 12 UN member states (Countries) were selected based on the inclusion and exclusion criteria mentioned in the methodology section of this paper. PPS technique was used for sampling and selection of 12 countries from 193 UN member states. Post selection of UN member states the study used 2 step evaluation techniques, Step 1 The DISCERN checklist consists of 16 questions in three sections and is aimed to assess the reliability of information and quality of information; Step 2 The QUEST tool consists of 6 items with a subitem, Authorship, Attribution, Conflict of Interest, Complementarity, Currency, Tone. The authors developed a standard set of instructions for evaluating Vaccination Portals to bring uniformity in understanding and context setting.Results: DISCERN tool overall reliability score on the Likert scale of 0 to 5 was 4 (SD ± 1.28). On Quality of information regarding treatment choices, the average score was 3.4 (SD ± 1.67). The QUEST tool on ease of use, concision, and comprehensiveness demonstrated an average score of 18.1 (SD ± 8.3) out of 28.The vaccine registration portal of the Czech Republic was found to be most informative and was able to provide a piece of scientifically valid information on safety, efficacy, long-term short effects, choice of vaccine with attributable authors details. India, Bangladesh, Nigeria, South Africa scored relatively low to missing critical information on the website. The United Arab Emirates, Republic of South Korea, Indonesia, Australia, and Argentina had minor elements missing.Conclusions: COVID-19 vaccination portals vary in the quality of information, and many were found unable to provide critical information for decision making on getting vaccinated

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

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

Stabilization of pan-based precursors for carbon fibers by Gajanan S. Bhat.

Ph.D.A.S. Abhirama

Penile entrapment: A case where innovation is the need of the hour

Penile entrapment is a rare and unique condition requiring urgent decompression to preserve the organ function and prevent complications. There is no universal method that is applicable to all cases as there are hardly any guidelines. Management of a 35-year-old male who presented to our emergency room with a metal ring around his penis has been described here. The case report highlights the need to devise one's own method to decompress the entrapped penis based on the available technology and manpower on hand in a given situation

Robust Modeling through Causal Priors and Data Purification in Machine Learning

The continued success and ubiquity of machine learning techniques, particularly Deep Learning, have necessitated research in robust model training to enhance generalization capabilities and security against incomplete data, distributional shifts, and adversarial attacks. This thesis presents two primary sets of contributions to robust modeling in machine learning through the use of causal priors and data purification with generative models such as the Variational Autoencoder (VAE), Energy-Based Model (EBM), and Denoising Diffusion Probabilistic Model (DDPM), focusing on image datasets. In the first set of contributions, we use structural causal priors in the latent spaces of VAEs. Initially, we demonstrate counterfactual synthetic data generation outside the training data distribution. This technique allows for the creation of diverse and novel data points, which is critical to enhancing model robustness and generalization capabilities. We utilize a similar VAE architecture to compare causal structural (graphical) hypotheses, showing that the fit of generated data from various hypotheses on distributionally shifted test data is an effective method for hypothesis comparison. Additionally, we explore using augmentations in the latent space of a VAE as an efficient and effective way to generate realistic augmented data. The second set of contributions focuses on data purification using EBMs and DDPMs. We propose a framework of universal data purification methods to defend against train-time data poisoning attacks. This framework utilizes stochastic transforms realized via iterative Langevin dynamics of EBMs, DDPMs, or both, to purify poisoned data with minimal impact on classifier generalization. Our specially trained EBMs and DDPMs provide state-of-the-art defense against various poisoning attacks while preserving natural accuracy. Preprocessing data with these techniques pushes poisoned images into the natural, clean image manifold, effectively neutralizing adversarial perturbations. The framework achieves state-of-the-art performance without needing attack or classifier-specific information, even when the generative models are trained on poisoned or distributionally shifted data. Beyond defense against data poisoning, our framework also shows promise in applications such as the degradation and removal of unwanted intellectual property. The flexibility and generality of these data purification techniques represent a significant step forward in the adversarial model training paradigm. All of these methods enable new perspectives and approaches to robust machine learning, advancing an essential field in artificial intelligence research

Inorganic fullerene-like tungsten disulfide/waterborne polyurethane reinforced Spectra® composites with improved mechanical properties and tensile energy absorption

Fiber-based nanocomposites play a significant role in bullet-resistant, anti-impact, and aerospace applications. This research was conducted to (1) determine the feasibility of preparing inorganic fullerene-like tungsten disulfide (IF-WS2)/waterborne-polyurethane (WPU) dispersions in varying water/ethanol mediums and (2) study the effects of IF-WS2/WPU impregnation on mechanical and tensile energy absorption properties of ultra-high molecular weight polyethylene (UHMWPE) fibers. The characterization results indicate that the WPU showed poor solubility in ethanol causing low distribution uniformity of IF-WS2 and WPU on fibers. Comparable mechanical properties were obtained for the optimal samples prepared with water and water/ethanol mediums. The maximum load, energy to break, and normalized energy to break increased by 26.5%, 44.9%, and 31.1% for the 2 wt% IF-WS2/10 wt% WPU/UHMWPE composite prepared with water medium, respectively. Neat UHMWPE fibers showed failure mechanisms of fiber breakage, delamination, fibrillation, and splitting, while additional ductile breakage and matrix debonding were observed on WPU/IF-WS2 incorporated UHMWPE composites