Power System Harmonics Estimation Using Adaptive Filters

Accurate estimation and tracking of power quality disturbances requires efficient adaptive model based techniques which should have elegant structures to be implemented in practical systems. Adaptive filters have been used as a popular estimator to track the time-varying power quality events, but the performance is limited due to higher order nonlinearity exists in system dynamics. Harmonics generated in the generation and distribution system are one of the critical power quality issues to be addressed properly. Least mean square (LMS) and recursive least square (RLS) based adaptive estimation models can be used to track the harmonic amplitudes and phases in practical power system applications. Due to time varying nature of harmonic parameters, modifications have to be incorporated in adaptive filters based modeling during estimation of the harmonic parameters and decaying DC components present in the distorted power signals. Volterra expansions can be combined with the adaptive filtering to improve the estimation accuracy and enhance the convergence rate of the estimation model

FABRICATION AND IN VITRO CHARACTERIZATION OF A NOVEL NANOSUSPENSION OF TELMISARTAN: A POORLY SOLUBLE DRUG PREPARED BY ANTISOLVENT PRECIPITATION TECHNIQUE USING 33 FACTORIAL DESIGN

Objective: The motivation behind the current examination was to build the solvency and dissolution rate of an antihypertensive drug telmisartan by the planning of nanosuspension by precipitation method at the research facility scale. We researched the nanoparticle manufacture of telmisartan employing a 33 factorial experimental configuration considering the impacts of nanosuspension on the physical, morphological, and dissolution properties of telmisartan. Methods: To get ready, nanosuspension particles of an ineffectively dissolvable drug are moreover of a drug solution to the anti-solvent leads to abrupt supersaturation and precipitation the making of nanoparticles. The nanosuspension particles of a poorly soluble drug loaded with urea and surfactants (sodium lauryl sulfate (SLS), poloxamer 188, Tween 80) have been prepared by a precipitation method. The nanosuspension particles were characterized for particle size, zeta potential, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), in vitro drug release, and release kinetics. Results: The readily optimized batch nanosuspension particles evaluated and exhibited the particle size (750 nm), zeta potential (-24.33 mV), differential scanning calorimetry (DSC) drug exhibited a change in crystalline form to amorphous, in vitro dissolution (F12 was higher 95% within 5 min) and drug release kinetics. The formulation parameter of surfactant concentration is optimized. Conclusion: The formulation of the nanosuspension approach has been shown to substantial improvement in the dissolution rate, thereby enhancing the oral bioavailability with the future development of this technology

Bioethanol production from alkali-pretreated rice straw: effects on fermentation yield, structural characterization, and ethanol analysis

Current ethanol production technology has a dire need for efficient conversion of lignocellulosic biomass to fermentable sugars. The conversion requires pretreatment of the biomass, one of the most expensive steps, and thus it is quite necessary to identify the most cost-effective and high-efficiency conversion method. In this study, rice straw (RS) biomass was pretreated using 4% NaOH alkali, soaked for 4 h, and autoclaved for 30 min. The structural and morphological changes were examined using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) analysis in both native and alkali-treated RS. The FTIR analysis revealed that native RS contains a considerable amount of lignin that was removed after the pretreatment process. The XRD pattern of the RS revealed an increasing crystallite size of the pretreated lignocellulosic biomass. The study of SEM clearly showed the distorted structure and surface porosity after the pretreatment process. Enzymatic hydrolysis efficiency was checked by comparing the commercial enzymes and microbial hydrolysis extracted from a fungal isolate. The best-reducing sugar yield obtained was 0.62 g/L, achieved at optimized conditions from the commercial enzymes. Fermentation efficiency was checked using the yeast isolate Saccharomyces cerevisiae in both the native and pretreated substrate, and the highest ethanol concentration (21.45%) was achieved using 20% w/v biomass loading, enzyme loading (2:1:1), and fermentation for a week at 30°C and pH 4.5. This concentration was higher than that of the untreated RS (3.67%). The ethanol thus produced was further checked for analysis by the 1H and 13C nuclear magnetic resonance (NMR) methods

Mechanochemical synthesis of a new triptycene-based imine-linked covalent organic polymer for degradation of organic dye

In the present work, a novel triptycene-based imine-linked covalent organic polymer (TP-COP) was designed and synthesized via room-temperature, solvent-free mechanochemical grinding. The as-synthesized TP-COP material was fully characterized by Fourier transform infrared spectroscopy, solid-state NMR, field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), Brunauer-Emmett-Teller method, thermogravimetric analysis, diffuse reflectance spectroscopy (DRS), and electron paramagnetic resonance (EPR). The HRTEM image of TP-COP clearly indicates the presence of graphene-like layered morphology (exfoliated layers). The DRS study reveals that TP-COP exhibited a low optical band gap value of 2.49 eV, implying its semiconducting nature. Further, the EPR study confirmed the semiconducting behavior of TP-COP through the generation of free radicals. These findings suggest that TP-COP could be used as an efficient photocatayst for the degradation of organic dye (RhB) under solar irradiation. Moreover, TP-COP showed excellent reusability in degrading dye (RhB) without obvious performance decay

Engraftment Syndrome: A Retrospective Analysis of the Experience at a Tertiary Care Institute

Engraftment syndrome (ES) is a clinical syndrome that occurs in the early neutrophil recovery phase following hematopoietic stem cell transplant (HSCT). Although also described for allogenic HSCT, it is basically diagnosed in the context of autologous HSCT. We retrospectively reviewed 171 consecutive HSCTs performed between January 2013 and January 2015 in our Bone Marrow Transplant (BMT) unit and analyzed all cases of noninfectious fever and strong clinical features suggestive of ES in the peri-engraftment period for up to 7 days. We observed the incidence of ES to be 12.3% (16/130) in the autologous and 4.8% (2/41) in the allogeneic cohort. Among plasma cell disorders, which constitute 50% of our study population, the incidence of ES was 19.7%. Among the ES cases of autologous transplants, 81.2% (13/16) patients satisfied the Maiolino criteria (MC) and 87.5% (14/16) patients the Spitzer diagnostic criteria (SC). A total of 68.7% (11/16) patients satisfied both MC and SC, and two patients (12.5%) did not satisfy either (MC− SC−). There was no significant difference in days of hospitalization and usage of supportive care between ES and non-ES patients, and there was no mortality due to ES. On univariate analysis, female patients (p < 0.013) and those with diagnosis of a plasma cell disorder (p < 0.03) had higher risk of ES. In conclusion, the incidence of ES in our study population is consistent with that of many others, but severity evaluation needs exploration in larger cohorts with pragmatically modified diagnostic criteria

Evaluation and comparison of the constitutive expression levels of Toll-like receptors 2, 3 and 7 in the peripheral blood mononuclear cells of Tharparkar and crossbred cattle

Aim: This study was undertaken to assess the differential expression levels of toll-like receptors (TLRs) 2, 3 and 7 in peripheral blood mononuclear cells (PBMCs) isolated from Tharparkar and Crossbred cattle belonging to different regions of India. Materials and Methods: PBMCs were isolated from blood samples of Tharparkar cattle from Indian Veterinary Research Institute (IVRI) farm (n=30); Suratgarh farm (n=61); Jaipur farm (n=8) and cross breed cattle from Jaipur (n=47). RNA was isolated from PBMCs and cDNA was synthesized using random hexamers. The expression profiles of TLR 2, 3 and 7 were estimated by real-time PCR and normalized to the expression of β-actin. Results: PBMCs of Tharparkar cattle from Suratgarh, exhibited a significantly higher (p<0.05) constitutive expression levels of TLR2, TLR3 and TLR7 genes as compared to Tharparkar cattle from IVRI or Jaipur as well as the crossbred cattle from Jaipur. PBMCs of crossbred cattle from Jaipur showed higher expression profiles of all the TLRs than Tharparkar cattle from Jaipur and IVRI. Conclusion: Our study indicates, expression levels of TLR2, TLR3 and TLR7 are significantly higher for Tharparkar cattle from Suratgarh than the cattle from Jaipur and IVRI and crossbred cattle from Jaipur. However, crossbred cattle from Jaipur showed higher basal expression levels of all the three TLRs than Tharparkar cattle from Jaipur and IVRI. Results also indicate that PBMCs of Tharparkar cattle show a regional variation in the expression pattern of TLRs

Mechanochemical synthesis of a new triptycene-based imine-linked covalent organic polymer for degradation of organic dye

In the present work, a novel triptycene-based imine-linked covalent organic polymer (TP-COP) was designed and synthesized via room-temperature, solvent-free mechanochemical grinding. The as-synthesized TP-COP material was fully characterized by Fourier transform infrared spectroscopy, solid-state NMR, field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), Brunauer-Emmett-Teller method, thermogravimetric analysis, diffuse reflectance spectroscopy (DRS), and electron paramagnetic resonance (EPR). The HRTEM image of TP-COP clearly indicates the presence of graphene-like layered morphology (exfoliated layers). The DRS study reveals that TP-COP exhibited a low optical band gap value of 2.49 eV, implying its semiconducting nature. Further, the EPR study confirmed the semiconducting behavior of TP-COP through the generation of free radicals. These findings suggest that TP-COP could be used as an efficient photocatayst for the degradation of organic dye (RhB) under solar irradiation. Moreover, TP-COP showed excellent reusability in degrading dye (RhB) without obvious performance decay

A review on the heat and mass transfer phenomena in nanofluid coolants with special focus on automotive applications

Engineered suspensions of nanosized particles (nanofluids) are characterized by superior thermal properties. Due to the increasing need for ultrahigh performance cooling in many industries, nanofluids have been widely investigated as next-generation coolants. However, the multiscale nature of nanofluids implies nontrivial relations between their design characteristics and the resulting thermo-physical properties, which are far from being fully understood. This pronounced sensitivity is the main reason for some contradictory results among both experimental evidence and theoretical considerations presented in the literature. In this Review, the role of fundamental heat and mass transfer mechanisms governing thermo-physical properties of nanofluids is assessed, from both experimental and theoretical point of view. Starting from the characteristic nanoscale transport phenomena occurring at the particle-fluid interface, a comprehensive review of the influence of geometrical (particle shape, size and volume concentration), physical (temperature) and chemical (particle material, pH and surfactant concentration in the base fluid) parameters on the nanofluid properties was carried out. Particular focus was devoted to highlight the advantages of using nanofluids as coolants for automotive heat exchangers, and a number of design guidelines was suggested for balancing thermal conductivity and viscosity enhancement in nanofluids. This Review may contribute to a more rational design of the thermo-physical properties of particle suspensions, therefore easing the translation of nanofluid technology from small-scale research laboratories to large-scale industrial applications

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

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