Terahertz optical fibers [Invited]

Abstract not available.Md. Saiful Islam, Cristiano M.B. Cordeiro, Marcos A.R. Franco, Jakeya Sultana, Alice L.S. Cruz, and Derek Abbot

Soil penetration resistance analysis by multivariate and geostatistical methods

The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.La resistencia a la penetración (RP) es un atributo del suelo que permite identificar zonas con restricciones debido a la compactación, que se traduce en impedancia mecánica para el desarrollo de las raíces y en una menor productividad de los cultivos. El objetivo del presente trabajo fue caracterizar la RP de un suelo agrícola, mediante análisis geoestadístico y multivariado. El muestreo se realizó de manera aleatoria en 90 puntos, hasta una profundidad de 0,60 m. Se determinaron los modelos de distribución espacial de la RP y se delimitaron áreas con problemas de impedancia mecánica de las raíces. La RP presentó distribución aleatoria a 0,55 y 0,60 m de profundidad. La RP en las otras profundidades analizadas mostraron dependencia espacial, con ajustes a modelos exponenciales y esféricos. El análisis jerárquico que consideró puntos de muestreo, permitió establecer zonas con problemas de compactación, identificadas en los mapas obtenidos mediante interpolación por kriging. El análisis de componentes principales permitió identificar tres capas de suelo, donde la capa intermedia fue la que presentó los mayores valores de RP

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Vegetative propagation of insulin (Cissus verticillata (L.) Nicolson & C.E. Jarvis) by cutting

Propagation techniques may support handling, this way providing an alternative for producers of medicinal plants, thus avoiding indiscriminate collection. We aimed to evaluate the size of cuttings with and without leaves on the seedling production of insulin (Cissus verticillata (L.) Nicolson & C.E. Jarvis). The herbaceous apical cuttings were prepared with diagonal cut at the bottom and straight cut at the apex, with 5, 10 or 15 cm in length, kept with two whole leaves, two leaves cut in half or without leaves, being sterilized with sodium hypochlorite at 0.5% for 15 minutes. The cuttings were planted in plastic containers with 180 mL capacity with vermiculite as substrate and placed in greenhouse at the temperature of 22 ± 2° C. The experimental design was completely randomized and means were compared by Tukey's test at 5% probability. After 60 days, we found that the cutting of 5 cm with whole leaves and with leaves cut in half and the cutting of 10 cm with whole leaves had rates above 70% of rooting with the best means for number and length of roots. There was a high mortality rate for cuttings made without leaves. The callus and the percentage of live cuttings were not significant for the treatments. Therefore, 5 cm long cuttings with whole or half leaves and 10 cm long cuttings with whole leaves are the most suitable for the vegetative propagation of insulin

Correction to: “experimental study on glass and polymers: determining the optimal material for potential use in terahertz technology”

Abstract not availableSaiful Islam, Cristiano M. B. Cordeiro, J. Nine, Jakeya Sultana, Alice L. S. Cruz, Alex Dinovitser … et al

Análise de coeficiente de trilha para os componentes de produção em arroz Path coefficient analysis of rice yield components

Com o objetivo de avaliar a influência dos componentes de produção de arroz no rendimento de grãos através da análise de trilha, avaliaram-se 88 genótipos de arroz em quatro anos agrícolas. Em cada ano, os experimentos foram conduzidos no delineamento em blocos completos casualizados, com quatro repetições. As variáveis analisadas foram: estatura de plantas, rendimento de grãos, esterilidade de espiguetas, número de grãos por panícula, massa de mil grãos e rendimento de engenho. As análises de variância, correlação e de trilha (Path Analysis) foram realizadas para cada variável, utilizando-se o programa computacional GENES. Os genótipos avaliados apresentaram diferenças significativas para todas as variáveis analisadas, nos quatro anos de experimento. A seleção de variáveis deve ser realizada em grupos de cultivares semelhantes entre si e a utilização de um maior número de variáveis possibilita melhores inferências sobre os componentes da produção do arroz. A massa de grãos é o componente de produção que mais afeta o rendimento da cultura do arroz.<br>Eighty eight rice genotypes were evaluated during four years aiming to study the relationship among yield components. In each year, the experimental design was a completely randomized block design with four replications and the variables studied were: plant height, seed yield, spikelet sterility, number of seeds per panicle, 1000 seeds weight and head grains. The estimation of correlations and the path coefficient analysis were conducted with the GENES software. The genotypes showed significant variability for all the variables analyzed within each one of years. It was concluded that variable selection must be carried out among the cultivars that are more similar and using a greater number of variables allows better inferences about rice yield components. Grain weight was the yield of component that most affected seed yield rice plants