Numerical investigation on the effects of single-mode microwave treatment on rock breakage system

[EN] In this study, a rock model which consists of a conceptual block (host rock and ore sample) is numerically modeled by using the finite element method. The rock model is subjected to several single-mode microwave treatments with different power levels, distances from the antenna, and exposure times in order to calculate and compare the corresponding effects including temperature distribution and mechanical stress/damage profiles. The main objective of the present study is to analyze the distribution of temperature and mechanical stress at the boundary of two different attached rocks when exposed to microwaves. This enables comparing the intensity of the distribution with respect to the applied microwave input operating parameters and, consequently, understanding rock preconditioning. The results of the present study verify that an increase in temperature by microwave treatment facilitates the rock weakening process. Also, a more efficient selection of the distance from the antenna and the power level can maximize the overall impact of the microwave treatment on rock preconditioning which ultimately helps with the rock breakage mechanism.Financial support for this work from the Natural Sciences and Engineering Research Council (NSERC) of Canada, the McGill Engineering Doctoral Award (MEDA) Award is gratefully acknowledged.Teimoori, K.; Hassani, F.; Sasmito, A.; Madiseh, A. (2019). Numerical investigation on the effects of single-mode microwave treatment on rock breakage system. En AMPERE 2019. 17th International Conference on Microwave and High Frequency Heating. Editorial Universitat Politècnica de València. 270-278. https://doi.org/10.4995/AMPERE2019.2019.9646OCS27027

Experimental Investigations of Microwave Effects on Rock Breakage Using SEM Analysis

[EN] Preconditioning of hard rocks by microwave energy has recently been considered a potentially effective technology in mechanical rock breakage for civil and mining engineering. To obtain the amount of mechanical damage that a single-mode microwave treatment produces in rocks, it is necessary to analyze and evaluate the thermal cracking process by microwave heating at different power levels, exposure times, and distances from the antenna. The current study employs the scanning electron microscopy imaging technique to capture images from surfaces of irradiated rock specimens and to compare them with a nontreated specimen. To evaluate and quantify the amount of cracking (i.e. crack density, crack size, etc.) in a rock specimen after microwave irradiation with different microwave input operating parameters, the following steps were evaluated. First, several experiments of single-mode microwave treatments with different operating parameters were performed on rectangular specimens of basalt. Then, cylindrical core samples with a dimension of r = 0.5 cm, h = 2cm, were drilled from the center of the irradiated specimens and prepared for image processing. The results of the present study show that there are significant differences between the number of microcracks present in samples irradiated at different power levels and distances from the antenna. Also, longer exposure times result in more severe cracks.Financial support for this work from the Natural Sciences and Engineering Research Council of Canada (NSERC), De Beers Group, Argex, Metso and the McGill Engineering Doctoral Award (MEDA) Award is gratefully acknowledged.Teimoori, K.; Hassani, F.; Sasmito, A.; Madiseh, A. (2019). Experimental Investigations of Microwave Effects on Rock Breakage Using SEM Analysis. En AMPERE 2019. 17th International Conference on Microwave and High Frequency Heating. Editorial Universitat Politècnica de València. 1-8. https://doi.org/10.4995/AMPERE2019.2019.96471

Canal Transportation and Centering after Using PathFile and R-Pilot in Mesiobuccal Canals of Maxillary Molars Using Cone-Beam Computed Tomography

Introduction: This study aimed to compare the changes in root canal anatomy following the use of PathFile and R-Pilot using cone-beam computed tomography (CBCT). Methods and Materials: In this in vitro, experimental study, 60 extracted maxillary first and second molars with 20 to 40° mesiobuccal root curvature, minimum of 19 mm of root length, no calcified root canals and no history of previous treatment were divided into two groups (n=30). CBCT scans were taken before and after the treatment, and sections at 1, 2 and 3 mm from the apex were compared. Pairwise comparisons were carried out using the Mann Whitney-U test. The centering ratio data were analyzed using the Chi-square test and Fisher’s exact test. All statistical analyses were carried out using Sigma Stat 4 software. Results: The difference between PathFile and R-Pilot in canal transportation in mesiodistal direction was significant at 1 and 2 mm from the apex (P<0.01). The R-Pilot file was significantly superior to PathFile in centering ability in mesiodistal direction at 1 mm from the apex (P<0.05). Canal transportation direction was towards the mesiolingual and distobuccal in R-Pilot and PathFile groups, respectively. Conclusion: Within the limitations of this study, the results showed that R-Pilot with reciprocal movement is a safe and easy to use instrument for creating a glide path.Keywords: Canal Transportation; Cone-Beam Computed Tomography; Glide Path; PathFile; R-Pilo

Principles and applications of CRISPR toolkit in virus manipulation, diagnosis, and virus-host interactions

Viruses are one of the most important concerns for human health, and overcoming viral infections is a worldwide challenge. However, researchers have been trying to manipulate viral genomes to overcome various disorders, including cancer, for vaccine development purposes. CRISPR (clustered regularly interspaced short palindromic repeats) is becoming one of the most functional and widely used tools for RNA and DNA manipulation in multiple organisms. This approach has provided an unprecedented opportunity for creating simple, inexpensive, specific, targeted, accurate, and practical manipulations of viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human immunodeficiency virus-1 (HIV-1), and vaccinia virus. Furthermore, this method can be used to make an effective and precise diagnosis of viral infections. Nevertheless, a valid and scientifically designed CRISPR system is critical to make more effective and accurate changes in viruses. In this review, we have focused on the best and the most effective ways to design sgRNA, gene knock-in(s), and gene knock-out(s) for virus-targeted manipulation. Furthermore, we have emphasized the application of CRISPR technology in virus diagnosis and in finding significant genes involved in virus-host interactions

Thyroid Function in Epileptic Children who Receive Carbamazepine, Primidone, Phenobarbital and Valproic Acid

ObjectiveIn this study, we investigated the changes of the serum levels of thyroidhormones including Thyroxine (T4), Triiodothyronine (T3), T3 resin uptake andThyroid stimulating hormone (TSH) in epileptic children during treatment withanti-epileptic drugs (AEDs) including carbamazepine (CBZ), primidone (PRM),phenobarbital and valproic acid (VPA).Materials and MethodsThis study consisted of four case-series comparisons, was conducted on 115epileptic children (37 girls and 78 boys with an age range between 2 monthsand 15 years, mean: 62.06 ± 44.97 months). These children were divided into4 groups who took either phenobarbital (n=29), PRM (n=28), CBZ (n=29), orVPA (n=29) for 3 months. Thyroid hormone levels (T3, T3 resin uptake, T4 andTSH) were measured at the beginning and three months after starting the study.ResultsAt first, all patients were euthyroid and there were no clinical or laboratoryfindings suggestive of hypothyroidism. Regarding thyroid hormones before andafter the administration of phenobarbital, carbamazepine, valproic acid andprimidone, there were no significant changes in serum T3, T4, T3 resin uptakeand TSH levels.ConclusionOur findings showed that short term therapy with phenobarbital, carbamazepine,valproic acid and primidone had no effect on thyroid function etsts.Key words: Anti-epileptic drugs; Thyroid hormones; Epileptic children.  

Parechovirus and enteroviruses among young infants with sepsis in Iran

Background and Objectives: Human parechoviruses (HPeV) and Human enteroviruses (EV) frequently cause a sepsis-like illness in young infants (younger than three months). Therefore, this study was conducted to determine the frequency of HPeV and EV among the young infants with clinical signs and symptoms of sepsis in Ahvaz city, Iran. Materials and Methods: The blood specimens were collected from 100 (younger than 90 days hospitalized infants) including 54 (56.25%) males and 46 (43.75%) females with clinical signs and symptoms of sepsis-like disease. The RNA was extracted and tested for detection of VP1 region of HPeV and 5 UTR (Untranslated Region) of EV by RT-PCR. The sequences of positive of HPeV were further analyzed to determine HPeV genotyping. Results: 5/100 (5%) of patients including 2/46 (2%) females and 3/54 (3%) males tested positive for HPeV (P=0.85). The analysis of 5 positive VP1 region of HPeV revealed the genotype 1. The analysis of sequencing and phylogenetic tree revealed that the isolated HPeVs were genotype 1. While 38/100 (38%) specimens including 16 (16%) females and 22 (22%) males were tested positive for EV (P=0.68). Conclusion: The frequency of HPeV genotype 1 was 5% among the young infants with sepsis. While frequency of EV was 38% among the young infants with sepsis. This study showed HPeV genotype 1 and EV are dominant in this region

Genomic prediction for growth using a low-density SNP panel in dromedary camels

For thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value \u3c 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value \u3c 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees

Genomic prediction for growth using a low-density SNP panel in dromedary camels

For thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value \u3c 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value \u3c 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world

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