33 research outputs found
Design and build of novel electric machines for transport electrification:(Alternative Format Thesis)
Analysis of Stator End-winding in a Dual Wound Machine Using Biot-Savart Law
Integrated full electric propulsion (IFEP) systems provide both ship propulsion and services with different electrical ratings. Instead of using multiple electrical machine sets, a dual wound machine with two sets of windings sharing the same stator slots can use one prime mover to provide two independent power supplies, achieving a more compact design and maximizing the power density. In order to provide independent power supplies, the windings must eliminate the electromagnetic coupling between them. A 2-pole and 6-pole dual wound machine has been designed previously. The simulation results show that there is no electromagnetic coupling considering the windings in the slots. It is important to investigate if there is any electromagnetic coupling caused by the end-windings. This paper proposes a simplified 2D and 3D end-winding model to analyse the magnetic field distribution and induced voltage using the Biot-Savart law. It is concluded that the end-windings of the dual wound machine are also not electromagnetically coupled, which proves that it is able to produce two independent power supplies for ship propulsion and services
End-to-End Learning for Simultaneously Generating Decision Map and Multi-Focus Image Fusion Result
The general aim of multi-focus image fusion is to gather focused regions of
different images to generate a unique all-in-focus fused image. Deep learning
based methods become the mainstream of image fusion by virtue of its powerful
feature representation ability. However, most of the existing deep learning
structures failed to balance fusion quality and end-to-end implementation
convenience. End-to-end decoder design often leads to unrealistic result
because of its non-linear mapping mechanism. On the other hand, generating an
intermediate decision map achieves better quality for the fused image, but
relies on the rectification with empirical post-processing parameter choices.
In this work, to handle the requirements of both output image quality and
comprehensive simplicity of structure implementation, we propose a cascade
network to simultaneously generate decision map and fused result with an
end-to-end training procedure. It avoids the dependence on empirical
post-processing methods in the inference stage. To improve the fusion quality,
we introduce a gradient aware loss function to preserve gradient information in
output fused image. In addition, we design a decision calibration strategy to
decrease the time consumption in the application of multiple images fusion.
Extensive experiments are conducted to compare with 19 different
state-of-the-art multi-focus image fusion structures with 6 assessment metrics.
The results prove that our designed structure can generally ameliorate the
output fused image quality, while implementation efficiency increases over 30\%
for multiple images fusion.Comment: repor
Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning
Parotid gland tumor is a common type of head and neck tumor. Segmentation of
the parotid glands and tumors by MR images is important for the treatment of
parotid gland tumors. However, segmentation of the parotid glands is
particularly challenging due to their variable shape and low contrast with
surrounding structures. Recently deep learning has developed rapidly, which can
handle complex problems. However, most of the current deep learning methods for
processing medical images are still based on supervised learning. Compared with
natural images, medical images are difficult to acquire and costly to label.
Contrastive learning, as an unsupervised learning method, can more effectively
utilize unlabeled medical images. In this paper, we used a Transformer-based
contrastive learning method and innovatively trained the contrastive learning
network with transfer learning. Then, the output model was transferred to the
downstream parotid segmentation task, which improved the performance of the
parotid segmentation model on the test set. The improved DSC was 89.60%, MPA
was 99.36%, MIoU was 85.11%, and HD was 2.98. All four metrics showed
significant improvement compared to the results of using a supervised learning
model as a pre-trained model for the parotid segmentation network. In addition,
we found that the improvement of the segmentation network by the contrastive
learning model was mainly in the encoder part, so this paper also tried to
build a contrastive learning network for the decoder part and discussed the
problems encountered in the process of building
Effectiveness of BNT162b2 and CoronaVac vaccinations against SARS-CoV-2 omicron infection in people aged 60 years or above: a case–control study
BACKGROUND: In view of limited evidence that specifically addresses vaccine effectiveness (VE) in the older population, this study aims to evaluate the real-world effectiveness of BNT162b2 and CoronaVac in older adults during the Omicron BA.2 outbreak. METHODS: This case-control study analyzed data available between January and March 2022 from the electronic health databases in Hong Kong and enrolled individuals aged 60 or above. Each case was matched with up to 10 controls by age, sex, index date and Charlson Comorbidity Index for the four outcomes (COVID-19 infection, COVID-19-related hospitalization, severe complications, and all-cause mortality) independently. Conditional logistic regression was conducted to evaluate VE of BNT162b2 and CoronaVac against COVID-19-related outcomes within 28 days after COVID-19 infection among participants stratified by age groups (60-79, ≥80 years old). RESULTS: A dose-response relationship between the number of vaccine doses received and protection against severe or fatal disease was observed. Highest VE (95% CI) against COVID-19 infection was observed in individuals aged ≥80 who received three doses of BNT162b2 [75.5% (73.1-77.7%)] or three doses of CoronaVac [53.9% (51.0-56.5%)] compared to those in the younger age group who received three doses of BNT162b2 [51.1% (49.9-52.4%)] or three doses of CoronaVac [2.0% (-0.1-4.1%)]. VE (95% CI) was higher for other outcomes, reaching 91.9% (89.4-93.8%) and 86.7% (84.3-88.8%) against COVID-19-related hospitalization; 85.8% (61.2-94.8%) and 89.8% (72.4-96.3%) against COVID-19-related severe complications; and 96.4% (92.9-98.2%) and 95.0% (92.1-96.8%) against COVID-19-related mortality after three doses of BNT162b2 and CoronaVac in older vaccine recipients, respectively. A similar dose-response relationship was established in younger vaccine recipients and after stratification by sex and Charlson Comorbidity Index. CONCLUSION: Both BNT162b2 and CoronaVac vaccination were effective in protecting older adults against COVID-19 infection and COVID-19-related severe outcomes amidst the Omicron BA.2 pandemic, and VE increased further with the third dose
Mimotope ELISA for Detection of Broad Spectrum Antibody against Avian H5N1 Influenza Virus
Science and Technology Foundation of Fujian Province [2009YZ0002]; National Natural Science Foundation of China [30901077]; National High Technology Research and Development Program [2010AA022801]Background: We have raised a panel of broad spectrum neutralizing monoclonal antibodies against the highly pathogenic H5N1 avian influenza virus, which neutralize the infectivity of, and afford protection against infection by, most of the major genetic groups of the virus evolved since 1997. Peptide mimics reactive with one of these broad spectrum H5N1 neutralizing antibodies, 8H5, were identified from random phage display libraries. Method: The amino acid residues of the most reactive 12mer peptide, p125 (DTPLTTAALRLV), were randomly substituted to improve its mimicry of the natural 8H5 epitope. Result: 133 reactive peptides with unique amino acid sequences were identified from 5 sub-libraries of p125. Four residues (2,4,5.9) of the parental peptide were preserved among all the derived peptides and probably essential for 8H5 binding. These are interspersed among four other residues (1,3,8,10), which exhibit restricted substitution and probably could contribute to binding, and another four (6,7,11,12) which could be randomly substituted and probably are not essential for binding. One peptide, V-1b, derived by substituting 5 of the latter residues is the most reactive and has a binding constant of 3.16x10(-9) M, which is 38 fold higher than the affinity of the parental p125. Immunoassay produced with this peptide is specifically reactive with 8H5 but not also the other related broad spectrum H5N1 avian influenza virus neutralizing antibodies. Serum samples from 29 chickens infected with H5N1 avian influenza virus gave a positive result by this assay and those from 12 uninfected animals gave a negative test result. Conclusion: The immunoassay produced with the 12 mer peptide, V1-b, is specific for the natural 8H5 epitope and can be used for detection of antibody against the broad spectrum neutralization site of H5N1 avian influenza virus
Vaccine Effectiveness of BNT162b2 and CoronaVac against SARS-CoV-2 Omicron BA.2 in CKD
Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has posed increased risks of hospitalization and mortality in patients with underlying CKD. Current data on vaccine effectiveness of COVID-19 vaccines are limited to patients with CKD on dialysis and seroconversion in the non-dialysis population. Methods: A case–control study was conducted of adults with CKD using data extracted from the electronic health record database in Hong Kong. Adults with CKD and COVID-19 confirmed by PCR were included in the study. Each case was matched with up to ten controls attending Hospital Authority services without a diagnosis of COVID-19 on the basis of age, sex, and index date (within three calendar days). The vaccine effectiveness of BNT162b2 and CoronaVac in preventing COVID-19 infection, hospitalizations, and all-cause mortality was estimated using conditional logistic regression adjusted by patients' comorbidities and medication history during the outbreak from January to March 2022. Results: A total of 20,570 COVID-19 cases, 6604 COVID-19–related hospitalizations, and 2267 all-cause mortality were matched to 81,092, 62,803, and 21,348 controls, respectively. Compared with the unvaccinated group, three doses of BNT162b2 or CoronaVac were associated with a reduced risk of infection (BNT162b2: 64% [95% confidence interval (CI), 60 to 67], CoronaVac: 42% [95% CI, 38 to 47]), hospitalization (BNT162b2: 82% [95% CI, 77 to 85], CoronaVac: 80% [95% CI, 76 to 84]), and mortality (BNT162b2: 94% [95% CI, 88 to 97], CoronaVac: 93% [95% CI, 88 to 96]). Vaccines were less effective in preventing infection and hospitalization in the eGFR <15 and 15–29 ml/min per 1.73 m2 subgroups as compared with higher GFR subgroups. However, receipt of vaccine, even for one dose, was effective in preventing all-cause mortality, with estimates similar to the higher eGFR subgroups, as compared with unvaccinated. Conclusions: A dose-response relationship was observed between the number of BNT162b2 or CoronaVac doses and the effectiveness against COVID-19 infection and related comorbidity in the CKD population
Long-term effects of coronavirus disease 2019 on diabetes complications and mortality in people with diabetes:Two cohorts in the UK and Hong Kong
AIM: To evaluate the long-term associations between coronavirus disease 2019 (COVID-19) and diabetes complications and mortality, in patients with diabetes. MATERIALS AND METHODS: People with diabetes diagnosed with COVID-19 infection (exposed group), from 16 March 2020 to 31 May 2021 from the UK Biobank (UKB cohort; n = 2456), and from 1 April 2020 to 31 May 2022 from the electronic health records in Hong Kong (HK cohort; n = 80 546), were recruited. Each patient was randomly matched with participants with diabetes but without COVID-19 (unexposed group), based on age and sex (UKB, n = 41 801; HK, n = 391 849). Patients were followed for up to 18 months until 31 August 2021 for UKB, and up to 28 months until 15 August 2022 for HK. Characteristics between cohorts were further adjusted with Inverse Probability Treatment Weighting. Long-term association of COVID-19 with multi-organ disease complications and all-cause mortality after 21 days of diagnosis was evaluated by Cox regression. RESULTS: Compared with uninfected participants, patients with COVID-19 infection with diabetes were consistently associated with higher risks of cardiovascular diseases (coronary heart disease [CHD]: hazard ratio [HR] [UKB]: 1.6 [95% confidence interval {CI}: 1.0, 2.4], HR [HK]: 1.2 [95% CI: 1.0, 1.5]; and stroke: HR [UKB]: 2.0 [95% CI: 1.1, 3.6], HR [HK]: 1.5 [95% CI: 1.3, 1.8]), microvascular disease (end stage renal disease: HR [UKB]: 2.1 [95% CI: 1.1, 4.0], HR [HK]: 1.2 [95% CI: 1.1, 1.4]) and all-cause mortality (HR [UKB]: 4.6 [95% CI: 3.8, 5.5], HR [HK]: 2.6 [95% CI: 2.5, 2.8]), in both cohorts. CONCLUSIONS: COVID-19 infection is associated with long-term increased risks of diabetes complications (especially cardiovascular complications, and mortality) in people with diabetes. Monitoring for signs/symptoms of developing these long-term complications post-COVID-19 infection in the infected patient population of people with diabetes may be beneficial in minimizing their morbidity and mortality
Association between BNT162b2 and CoronaVac vaccination and risk of CVD and mortality after COVID-19 infection: A population-based cohort study
It is unknown if vaccination affects the risk of post-COVID-19 cardiovascular diseases (CVDs). Therefore, this retrospective cohort study examines the short-term and long-term risks of post-infection CVD among COVID-19 patients with different vaccination status utilizing data from electronic health databases in Hong Kong. Cox proportional hazards regression adjusted with inverse probability of treatment weighting is used to evaluate the risks of incident CVD (coronary heart disease, stroke, heart failure) and all-cause mortality in COVID-19 patients. Compared with unvaccinated patients, vaccinated patients have a lower risk of CVD and all-cause mortality, and the lowest risk is observed in those who completed three doses of vaccine. Similar patterns in the subgroups of different vaccine platforms, age, gender, Charlson comorbidity index, and disease severity are observed. These findings highlight a positive dose-response relationship between overall CVD risk reduction and the number of vaccine doses received