Our planet has been facing critical challenges since the late 20th century, including climate change, resource shortages, environmental degradation and pollution, demanding urgent and sustainable solutions. Biochar, a...
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Background: Asthma and atopic dermatitis are common allergic conditions that contribute to substantial health loss, economic burden, and pain across individuals of all ages worldwide. Therefore, as a component of the ...
Background: Asthma and atopic dermatitis are common allergic conditions that contribute to substantial health loss, economic burden, and pain across individuals of all ages worldwide. Therefore, as a component of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, we present updated estimates of the prevalence, disability-adjusted life-years (DALYs), incidence, and deaths due to asthma and atopic dermatitis and the burden attributable to modifiable risk factors, with forecasted prevalence up to 2050. Methods: Asthma and atopic dermatitis prevalence, incidence, DALYs, and mortality, with corresponding 95% uncertainty intervals (UIs), were estimated for 204 countries and territories from 1990 to 2021. A systematic review identified data from 389 sources for asthma and 316 for atopic dermatitis, which were further pooled using the Bayesian meta-regression tool. We also described the age-standardised DALY rates of asthma attributable to four modifiable risk factors: high BMI, occupational asthmagens, smoking, and nitrogen dioxide pollution. Furthermore, as a secondary analysis, prevalence was forecasted to 2050 using the Socio-demographic Index (SDI), air pollution, and smoking as predictors for asthma and atopic dermatitis. To assess trends in the burden of asthma and atopic dermatitis before (2010–19) and during (2019–21) the COVID-19 pandemic, we compared their average annual percentage changes (AAPCs). Findings: In 2021, there were an estimated 260 million (95% UI 227–298) individuals with asthma and 129 million (124–134) individuals with atopic dermatitis worldwide. Asthma cases declined from 287 million (250–331) in 1990 to 238 million (209–272) in 2005 but increased to 260 million in 2021. Atopic dermatitis cases consistently rose from 107 million (103–112) in 1990 to 129 million (124–134) in 2021. However, age-standardised prevalence rates decreased—by 40·0% (from 5568·3 per 100 000 to 3340·1 per 100 000) for asthma and 8·3% (from 1885·4
We present comparator-based gene network designs for feedback control of the concentration of gene products. Two gene circuit designs are proposed, each of which compares concentrations of an input transcription facto...
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Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Glo...
Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r
This paper studies the observer design for the fractional order boundary coupled distributed parameter systems. Firstly, we obtain the decoupled observer error systems from the state system and observer system. Second...
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This paper studies the observer design for the fractional order boundary coupled distributed parameter systems. Firstly, we obtain the decoupled observer error systems from the state system and observer system. Secondly, the advection terms are eliminated through the invertible transformation and we can obtain the general reaction-diffusion partial differential equations, which are more convenient for discussions. Thirdly, Backstepping method and target systems are employed to give kernel partial differential equations and then the related observer gains can be derived from the corresponding kernels. Finally, Mittag-Leffler stability of the designed fractional order observers is analyzed and the main results are illustrated by the simulation graphically.
Background: Forest management aims at obtaining a sustainable production of wood to be harvested to generate products or energy. However, the quantitative influence of forest management and of removals by harvest on b...
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Background: Forest management aims at obtaining a sustainable production of wood to be harvested to generate products or energy. However, the quantitative influence of forest management and of removals by harvest on biomass stocks has rarely been analysed on a large scale based on measurements. Two hypotheses prevail: management induces a reduction of wood stocks due to cuttings, versus no impact because of increased growth of the remaining trees. Using data collected for 2840 permanent plots across Romania from the National Forest Inventory representing^2.5 Mha, we have tested to what extent different management types and treatments can influence the biomass stock and productivity of beech forests, and attempt to quantify these effects both on the short and long terms. Three main types of beech forest management are implemented in Romania with specific objectives: intensive wood production in production forests, protection of ecosystem services (e.g. watersheds, avalanche protection) in protection forests, and protection of the forest and its biodiversity in protected forests. Production forests encompass two treatments differing according to the stand regeneration method: the age class rotation management and the group shelterwood management. Results: We show that forest management had little influence on the biomass stocks at a given stand age. The highest stocks at stand age 100 were observed in production forests (the most intensively managed forests). Consequences of early cuttings were very short-termed because the increase in tree growth rapidly compensated for tree cuttings. The cumulated biomass of production forests exceeded that of protected and protection forests. Regarding the treatment, the group shelterwood forests had a markedly higher production over a full rotation period. The total amount of deadwood was primarily driven by the amount of standing deadwood, and no management effect was detected. Conclusions: Given the relatively low-intensity mana
Following improvements in deep neural networks, stateof-the-Art netwy depends on the training data. An issue with collecting training data is labeling. Labeling by humans is necessary to obtain the ground truth label;...
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The ability to gather manufacturing data from various workstations has been explored for several decades and the advances in sensory and data acquisition techniques have led to the increasing availability of high-dime...
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The ability to gather manufacturing data from various workstations has been explored for several decades and the advances in sensory and data acquisition techniques have led to the increasing availability of high-dimensional data. This paper presents an intelligent metrology informatics system to extract useful information from Multistage Manufacturing Process (MMP) data and predict part quality characteristics such as true position and circularity using neural networks. The input data include the tempering temperature, material conditions, force and vibration while the output data include comparative coordinate measurements. The effectiveness of the proposed method is demonstrated using experimental data from a MMP.
In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic...
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Online transmission line outage detection over the entire network enable timely corrective actions to be taken, which prevents a local event from cascading into a large scale blackout. Line outage detection aims to de...
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