| 1. |
- Zhang, Yongping, et al.
(författare)
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Long/short-term utility aware optimal selection of manufacturing service composition towards Industrial Internet platform
- 2019
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 15:6, s. 3712-3722
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Tidskriftsartikel (refereegranskat)abstract
- As numerous Industrial Internet platforms emerge, manufacturing services are shared among multiple stakeholders more frequently than ever. The optimal selection of shared manufacturing service composition (MSC) should both promise the task completion and the stakeholders’ satisfaction. However, as commercial entities, stakeholders concentrate on not only the temporary benefits but also the long-term acquisitions. Most of the existing MSC problems neglect the stakeholders’ prospect on the manufacturing service sharing. This leads to the disappointment and dissatisfaction of the stakeholders with long-term expectations, who will abandon the participation in Industrial Internet platform. Therefore, the long/short-term preferences of various stakeholders should be satisfied and balanced. In this paper, the long/short-term preferences of three sides (provider, consumer, and operator) are discussed. And the models considering short-term utility of a consumer and long-term utility of providers, are established. The potential tasks assigned to providers are taken into account to estimate the long-term utility if the current task is accepted. Then, to solve the bi-objective optimization problem, an improved Non-dominated Sorting Genetic Algorithm-II algorithm, combining Tabu search and improved K-means mechanism, is proposed to find the optimal solution set. Finally, the effectiveness of the method is verified by the experimental results in terms of solution diversity, astringency and stability, in which a finding is further observed that the changes of consumers’ preferences have little impact on the long-term utility of providers.
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| 2. |
- Abolhassani, Hassan, et al.
(författare)
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Genetic and immunologic evaluation of children with inborn errors of immunity and severe or critical COVID-19
- 2022
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Ingår i: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 150:5, s. 1059-1073
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Tidskriftsartikel (refereegranskat)abstract
- Background: Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals are asymptomatic or only exhibit mild disease. In about 10% of cases, the infection leads to hypoxemic pneumonia, although it is much more rare in children. Objective: We evaluated 31 young patients aged 0.5 to 19 years who had preexisting inborn errors of immunity (IEI) but lacked a molecular diagnosis and were later diagnosed with coronavirus disease 2019 (COVID-19) complications. Methods: Genetic evaluation by whole-exome sequencing was performed in all patients. SARS-CoV-2-specific antibodies, autoantibodies against type I IFN (IFN-I), and inflammatory factors in plasma were measured. We also reviewed COVID-19 disease severity/outcome in reported IEI patients. Results: A potential genetic cause of the IEI was identified in 28 patients (90.3%), including mutations that may affect IFN signaling, T- and B-cell function, the inflammasome, and the complement system. From tested patients 65.5% had detectable virus-specific antibodies, and 6.8% had autoantibodies neutralizing IFN-I. Five patients (16.1%) fulfilled the diagnostic criteria of multisystem inflammatory syndrome in children. Eleven patients (35.4%) died of COVID-19 complications. All together, at least 381 IEI children with COVID-19 have been reported in the literature to date. Although many patients with asymptomatic or mild disease may not have been reported, severe presentation of COVID-19 was observed in 23.6% of the published cases, and the mortality rate was 8.7%. Conclusions: Young patients with preexisting IEI may have higher mortality than children without IEI when infected with SARS-CoV-2. Elucidating the genetic basis of IEI patients with severe/critical COVID-19 may help to develop better strategies for prevention and treatment of severe COVID-19 disease and complications in pediatric patients.
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| 3. |
- Abolhassani, Hassan, et al.
(författare)
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Inherited IFNAR1 Deficiency in a Child with Both Critical COVID-19 Pneumonia and Multisystem Inflammatory Syndrome
- 2022
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Ingår i: Journal of Clinical Immunology. - : Springer Nature. - 0271-9142 .- 1573-2592. ; 42:3, s. 471-483
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Tidskriftsartikel (refereegranskat)abstract
- Background Inborn errors of immunity (IEI) and autoantibodies to type I interferons (IFNs) underlie critical COVID-19 pneumonia in at least 15% of the patients, while the causes of multisystem inflammatory syndrome in children (MIS-C) remain elusive. Objectives To detect causal genetic variants in very rare cases with concomitant critical COVID-19 pneumonia and MIS-C. Methods Whole exome sequencing was performed, and the impact of candidate gene variants was investigated. Plasma levels of cytokines, specific antibodies against the virus, and autoantibodies against type I IFNs were also measured. Results We report a 3-year-old child who died on day 56 of SARS-CoV-2 infection with an unusual clinical presentation, combining both critical COVID-19 pneumonia and MIS-C. We identified a large, homozygous loss-of-function deletion in IFNAR1, underlying autosomal recessive IFNAR1 deficiency. Conclusions Our findings confirm that impaired type I IFN immunity can underlie critical COVID-19 pneumonia, while suggesting that it can also unexpectedly underlie concomitant MIS-C. Our report further raises the possibility that inherited or acquired dysregulation of type I IFN immunity might contribute to MIS-C in other patients.
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| 4. |
- Abolhassani, Hassan, et al.
(författare)
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X-Linked TLR7 Deficiency Underlies Critical COVID-19 Pneumonia in a Male Patient with Ataxia-Telangiectasia
- 2022
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Ingår i: Journal of Clinical Immunology. - : Springer Science and Business Media LLC. - 0271-9142 .- 1573-2592. ; 42:1, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Background Coronavirus disease 2019 (COVID-19) exhibits a wide spectrum of clinical manifestations, ranging from asymptomatic to critical conditions. Understanding the mechanism underlying life-threatening COVID-19 is instrumental for disease prevention and treatment in individuals with a high risk.Objectives We aimed to identify the genetic cause for critical COVID-19 pneumonia in a patient with a preexisting inborn error of immunity (IEI).Methods Serum levels of specific antibodies against the virus and autoantibodies against type I interferons (IFNs) were measured. Whole exome sequencing was performed, and the impacts of candidate gene variants were investigated. We also evaluated 247 ataxia-telangiectasia (A-T) patients in the Iranian IEI registry.Results We report a 7-year-old Iranian boy with a preexisting hyper IgM syndrome who developed critical COVID-19 pneumonia. IgM only specific COVID-19 immune response was detected but no autoantibodies against type I IFN were observed. A homozygous deleterious mutation in the ATM gene was identified, which together with his antibody deficiency, radiosensitivity, and neurological signs, established a diagnosis of A-T. Among the 247 A-T patients evaluated, 36 had SARS-CoV-2 infection, but all had mild symptoms or were asymptomatic except the index patient. A hemizygous deleterious mutation in the TLR7 gene was subsequently identified in the patient.Conclusions We report a unique IEI patient with combined ATM and TLR7 deficiencies. The two genetic defects underlie A-T and critical COVID-19 in this patient, respectively.
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| 5. |
- Chen, Shaoqing, et al.
(författare)
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Anchoring High-Concentration Oxygen Vacancies at Interfaces of CeO2–x/Cu toward Enhanced Activity for Preferential CO Oxidation
- 2015
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Ingår i: ACS Applied Materials & Interfaces. - 1944-8252 .- 1944-8244. ; 7:41, s. 22999-23007
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Tidskriftsartikel (refereegranskat)abstract
- Catalysts are urgently needed to remove the residual CO in hydrogen feeds through selective oxidation for large-scale applications of hydrogen proton exchange membrane fuel cells. We herein propose a new methodology that anchors high concentration oxygen vacancies at interface by designing a CeO2–x/Cu hybrid catalyst with enhanced preferential CO oxidation activity. This hybrid catalyst, with more than 6.1% oxygen vacancies fixed at the favorable interfacial sites, displays nearly 100% CO conversion efficiency in H2-rich streams over a broad temperature window from 120 to 210 °C, strikingly 5-fold wider than that of conventional CeO2/Cu (i.e., CeO2 supported on Cu) catalyst. Moreover, the catalyst exhibits a highest cycling stability ever reported, showing no deterioration after five cycling tests, and a super long-time stability beyond 100 h in the simulated operation environment that involves CO2 and H2O. On the basis of an arsenal of characterization techniques, we clearly show that the anchored oxygen vacancies are generated as a consequence of electron donation from metal copper atoms to CeO2 acceptor and the subsequent reverse spillover of oxygen induced by electron transfer in well controlled nanoheterojunction. The anchored oxygen vacancies play a bridging role in electron capture or transfer and drive molecule oxygen into active oxygen species to interact with the CO molecules adsorbed at interfaces, thus leading to an excellent preferential CO oxidation performance. This study opens a window to design a vast number of high-performance metal-oxide hybrid catalysts via the concept of anchoring oxygen vacancies at interfaces.
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| 6. |
- Huang, Hongyun, et al.
(författare)
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Clinical Cell Therapy Guidelines for Neurorestoration (IANR/CANR 2017)
- 2018
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Ingår i: Cell Transplantation. - : SAGE Publications. - 0963-6897 .- 1555-3892. ; 27:2, s. 310-324
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Forskningsöversikt (refereegranskat)abstract
- Cell therapy has been shown to be a key clinical therapeutic option for central nervous system diseases or damage. Standardization of clinical cell therapy procedures is an important task for professional associations devoted to cell therapy. The Chinese Branch of the International Association of Neurorestoratology (IANR) completed the first set of guidelines governing the clinical application of neurorestoration in 2011. The IANR and the Chinese Association of Neurorestoratology (CANR) collaborated to propose the current version "Clinical Cell Therapy Guidelines for Neurorestoration (IANR/CANR 2017)". The IANR council board members and CANR committee members approved this proposal on September 1, 2016, and recommend it to clinical practitioners of cellular therapy. These guidelines include items of cell type nomenclature, cell quality control, minimal suggested cell doses, patient-informed consent, indications for undergoing cell therapy, contraindications for undergoing cell therapy, documentation of procedure and therapy, safety evaluation, efficacy evaluation, policy of repeated treatments, do not charge patients for unproven therapies, basic principles of cell therapy, and publishing responsibility.
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| 7. |
- Hung, Rayjean J., et al.
(författare)
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Lung Cancer Risk in Never-Smokers of European Descent is Associated With Genetic Variation in the 5(p)15.33 TERT-CLPTM1Ll Region
- 2019
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Ingår i: Journal of Thoracic Oncology. - : ELSEVIER SCIENCE INC. - 1556-0864 .- 1556-1380. ; 14:8, s. 1360-1369
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer. Methods: We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer. Results: We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 x 10(-16)), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 x 10(-16)), and rs4975616 OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 x 10(-14)). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate. Conclusions: We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease. (C) 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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| 8. |
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| 9. |
- Rabe, Benjamin, et al.
(författare)
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The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms
- 2024
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Ingår i: Elementa. - 2325-1026. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.
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| 10. |
- Wang, Yucheng, et al.
(författare)
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Digital twin enhanced fault prediction for the autoclave with insufficient data
- 2021
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 60, s. 350-359
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Tidskriftsartikel (refereegranskat)abstract
- Since any faulty operations could directly affect the composite property, making early prognosis is particularly crucial for complex equipment. At present, data-driven approach has been typically used for fault prediction. However, for part of complex equipment, it is difficult to access reliable and sufficient data to train the fault prediction model. To address this issue, this paper takes autoclave as an example. A Digital Twin (DT) model containing multiple dimensions for the autoclave is firstly constructed and verified. Then the characteristics of autoclave under different conditions are analyzed and presented with specific parameters. The data in normal and faulty conditions are simulated by using the DT model. Both the simulated data and extracted historical data are applied to enhance fault prediction. A convolutional neural network for fault prediction will be trained with the generated data which matches the feature of the autoclave in faulty conditions. The effectiveness of the proposed method is verified through result analysis.
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