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- Cousin, E., et al.
(author)
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Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019
- 2022
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In: Lancet Diabetes & Endocrinology. - : Elsevier BV. - 2213-8587. ; 10:3, s. 177-192
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Journal article (peer-reviewed)abstract
- Background Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990-2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73.7% (68.3 to 77.4) were classified as due to type 1 diabetes. The age-standardised death rate was 0.50 (0.44 to 0.58) per 100 000 population, and 15 900 (97.5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0.13 (0.12 to 0.14) per 100 000 population in the high SDI quintile, 0.60 (0.51 to 0.70) per 100 000 population in the low-middle SDI quintile, and 0.71 (0.60 to 0.86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r(2)=0.62). From 1990 to 2019, age-standardised death rates decreased globally by 17.0% (-28.4 to -2.9) for all diabetes, and by 21.0% (-33.0 to -5.9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (-13.6% [-28.4 to 3.4]) and for type 1 diabetes (-13.6% [-29.3 to 8.9]). Interpretation Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.
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- Cao, Bin, et al.
(author)
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Delimiting species in Basidiomycota : a review
- 2021
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In: Fungal diversity. - : Springer Nature. - 1560-2745 .- 1878-9129. ; 109:1, s. 181-237
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Research review (peer-reviewed)abstract
- Species delimitation is one of the most fundamental processes in biology. Biodiversity undertakings, for instance, require explicit species concepts and criteria for species delimitation in order to be relevant and translatable. However, a perfect species concept does not exist for Fungi. Here, we review the species concepts commonly used in Basidiomycota, the second largest phylum of Fungi that contains some of the best known species of mushrooms, rusts, smuts, and jelly fungi. In general, best practice is to delimitate species, publish new taxa, and conduct taxonomic revisions based on as many independent lines of evidence as possible, that is, by applying a so-called unifying (or integrative) conceptual framework. However, the types of data used vary considerably from group to group. For this reason we discuss the different classes of Basidiomycota, and for each provide: (i) a general introduction with difficulties faced in species recognition, (ii) species concepts and methods for species delimitation, and (iii) community recommendations and conclusions.
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- Cao, Bin, et al.
(author)
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Mobility-Aware Multiobjective Task Offloading for Vehicular Edge Computing in Digital Twin Environment
- 2023
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In: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 41:10, s. 3046-3055
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Journal article (peer-reviewed)abstract
- In vehicular edge computing (VEC), vehicle users (VUs) can offload their computation-intensive tasks to edge server (ES) that provides additional computation resources. Due to the edge server being closer to VUs, the propagation delay between the ESs and the VUs is lower compared to cloud computing. Applying digital twin to VEC allows for low-cost trial in task offloading. In real-word, the mobility of VUs cannot be ignored and the downlink delay in receiving process results from ES is related to the mobility of VUs. Therefore, a five-objective optimization model including downlink delay, computation delay, energy consumption, load balancing, and user satisfaction of the VUs is constructed. To solve the above model, an improved CMA-ES algorithm based on the guiding point (GP-CMA-ES) is proposed. When the number of VUs increases, the dimension of variables also increases. Therefore, a convergence-related variable grouping strategy based on the relationship detection between variables and objectives is proposed. The performance of algorithm GP-CMA-ES is compared with five algorithms in the digital twin environment.
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| 7. |
- Cao, Bin, et al.
(author)
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Multiobjective Evolution of the Explainable Fuzzy Rough Neural Network With Gene Expression Programming
- 2022
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In: IEEE transactions on fuzzy systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 1063-6706 .- 1941-0034. ; 30:10, s. 4190-4200
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Journal article (peer-reviewed)abstract
- The fuzzy logic-based neural network usually forms fuzzy rules via multiplying the input membership degrees, which lacks expressiveness and flexibility. In this article, a novel neural network model is designed by integrating the gene expression programming into the interval type-2 fuzzy rough neural network, aiming to generate fuzzy rules with more expressiveness utilizing various logical operators. The network training is regarded as a multiobjective optimization problem through simultaneously considering network precision, explainability, and generalization. Specifically, the network complexity can be minimized to generate concise and few fuzzy rules for improving the network explainability. Inspired by the extreme learning machine and the broad learning system, an enhanced distributed parallel multiobjective evolutionary algorithm is proposed. This evolutionary algorithm can flexibly explore the forms of fuzzy rules, and the weight refinement of the final layer can significantly improve precision and convergence by solving the pseudoinverse. Experimental results show that the proposed multiobjective evolutionary network framework is superior in both effectiveness and explainability.
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| 8. |
- Cao, Bin, et al.
(author)
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Multiobjective Image Compression based on Tensor Decomposition
- 2023
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In: 2023 8th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA. - : IEEE. - 9781665455336 - 9781665455343 ; , s. 545-550
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Conference paper (peer-reviewed)abstract
- Most of the traditional image compression methods vectorize the data contained in the image and then compress it. However, this approach does not take into account the high-dimensional information inside the image. To solve this problem, this paper regards the color image as a third-order tensor, and proposes a method of color image compression based on Tucker decomposition and multiobjective optimization. The tensor size compression ratio and Hu invariant moment similarity are proposed to measure the image compression quality. And to more comprehensively consider the sensitivity of human visual system to different visual signals, the five-objective optimization model of image compression is constructed. The five-objective optimization model includes: the above two indexes, information content weighted structure similarity index, color image feature similarity and information fidelity criterion. In addition, an angle-aware opposition-based learning strategy is proposed to improve the reference vector guided selection strategy of RVEA*. In the experiments, this method could effectively solve the problem of color image compression.
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- Cao, Yang, Associate Professor, 1972-, et al.
(author)
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Comparison of piecewise structural equation modeling and Bayesian network for de novo construction of a quantitative adverse outcome pathway network
- 2023
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In: Altex. - : Springer Spektrum. - 1868-596X .- 1868-8551. ; 40:2, s. 287-298
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Journal article (peer-reviewed)abstract
- Quantitative adverse outcome pathway network (qAOPN) is gaining momentum due to the predictive nature, alignment with quantitative risk assessment and great potential as a computational new approach methodology (NAM) to reduce laboratory animal tests. The present work aimed to demonstrate two advanced modeling approaches, piecewise structural equation modeling (PSEM) and Bayesian network (BN), for de novo qAOPN model construction based on routine ecotoxicological data. A previously published AOP network comprised of four linear AOPs linking excessive reactive oxygen species production to mortality in aquatic organisms was employed as a case study. The demonstrative case study intended to answer: Which linear AOP in the network contributed the most to the AO? Can any of the upstream KEs accurately predict the AO? What are the advantages and limitations of PSEM or BN in qAOPN development? The outcomes from the two approaches showed that both PSEM and Bayesian network were suitable for constructing a complex qAOPN based on limited experimental data. Besides quantification of response-response relationships, both approaches were capable of identifying the most influencing linear AOP in a complex network and evaluating the predictive ability of the AOP, albeit some discrepancies in predictive ability were identified for the two approaches using this specific dataset. The PROs and CONs of the two approaches for qAOPN construction were discussed in detail and suggestions on optimal workflows of PSEM and BN were provided to guide future qAOPN development.
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| 10. |
- Cao, Zhen, et al.
(author)
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Nanoparticle-Assisted Pool Boiling Heat Transfer on Micro-Pin-Fin Surfaces
- 2021
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In: Langmuir. - : American Chemical Society (ACS). - 0743-7463 .- 1520-5827. ; 37:3, s. 1089-1101
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Journal article (peer-reviewed)abstract
- Boiling heat transfer intensification is of significant relevance to energy conversion and various cooling processes. This study aimed to enhance the saturated pool boiling of FC-72 (a dielectric liquid) by surface modifications and explore mechanisms of the enhancement. Specifically, circular and square micro pin fins were fabricated on silicon surfaces by dry etching and then copper nanoparticles were deposited on the micro-pin-fin surfaces by electrostatic deposition. Experimental results indicated that compared with a smooth surface, the micro pin fins increased the heat transfer coefficient and the critical heat flux by more than 200 and 65–83%, respectively, which were further enhanced by the nanoparticles up to 24% and more than 20%, respectively. Correspondingly, the enhancement mechanism was carefully explored by high-speed bubble visualizations, surface wickability measurements, and model analysis. It was quantitatively found that small bubble departure diameters with high bubble departure frequencies promoted high heat transfer coefficients. The wickability, which characterizes the ability of a liquid to rewet a surface, played an important role in determining the critical heat flux, but further analyses indicated that evaporation beneath bubbles was also essential and competition between the wicking and the evaporation finally triggered the critical heat flux.
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