579 research outputs found
Numerical Analysis of 3-Dimensional Scaling Rules on a 1.2-kV Trench Clustered IGBT
3-dimensional scaling rules for the cathode cells and
threshold voltages of a 1.2-kV Trench Clustered IGBT (TCIGBT)
are investigated using calibrated models in Synopsys Sentaurus
TCAD tools. Scaling down results in an enhancement of current
gain of the inherent thyristor action which reduces the forward
voltage drop even more than that of a scaled Trench IGBT
(TIGBT). For identical switching losses, at a scaling factor k=3,
the forward voltage drop is reduced by 20% at 300K and 30% at
400K when compared to the conventional TCIGBT (k=1). Most
importantly, despite its lower conduction losses than an
equivalent TIGBT, a scaled TCIGBT structure can maintain its
short circuit capability, due to the additional scaling principle
applied to the n-well and p-well regions, maintaining the
self-clamping feature. Thus, TCIGBT is a more efficient
chip-for-chip, reliable replacement of a TIGBT for energy savings
in applications
A novel approach to suppress the collector induced barrier lowering (CIBL) effect in narrow mesa IGBTs
A recessed p+-cathode IGBT (RP-IGBT) structure with very narrow mesa is analysed through 3-D simulations in 1.2-kV, field stop technology. Compared to a conventional narrow mesa IGBTs, the RP-IGBT can effectively restrain the collector- induced barrier lowering (CIBL) effect and hence, two-thirds reduction in saturation current can be achieved. As a result, more than 10μs short circuit capability is enabled at a junction temperature of 400K. Most importantly, the proposed RP-IGBT structure has no influence upon on-state performance and its forward voltage drop remains at 1.1V at a current density of 200A/cm2 at 400K
Charmless Two-body Baryonic B Decays
We study charmless two-body baryonic B decays in a diagramatic approach.
Relations on decay amplitudes are obtained. In general there are more than one
tree and more than one penguin amplitudes. The number of independent amplitudes
can be reduced in the large m_B limit. It leads to more predictive results.
Some prominent modes for experimental searches are pointed out.Comment: 15 pages, 2 figures. To appear in Phys. Rev.
Final state interactions in the decay
In this article, we study the final-state rescattering effects in the decay
, the numerical results indicate the corrections are
comparable with the contribution from the naive factorizable amplitude, and the
total amplitudes can accommodate the experimental data.Comment: 11 pages, 1 figure, revised version, to appear in EPJ
Association of comorbidity with healthcare utilization in people living With dementia, 2010–2019: a population-based cohort study
Evidence on the healthcare utilization associated with comorbidity in people with dementia is lacking in Chinese societies. This study aimed to quantify healthcare utilization associated with comorbidity that is common in people living with dementia. We conducted a cohort study using population-based data from Hong Kong public hospitals. Individuals aged 35+ with a dementia diagnosis between 2010 and 2019 were included. Among 88,151 participants, people with at least two comorbidities accounted for 81.2%. Estimates from negative binomial regressions showed that compared to those with one or no comorbid condition other than dementia, adjusted rate ratios of hospitalizations among individuals with six or seven and eight or more conditions were 1.97 [98.75% CI, 1.89–2.05] and 2.74 [2.63–2.86], respectively; adjusted rate ratios of Accident and Emergency department visits among individuals with six or seven and eight or more conditions were 1.53 [1.44–1.63] and 1.92 [1.80–2.05], respectively. Comorbid chronic kidney diseases were associated with the highest adjusted rate ratios of hospitalizations (1.81 [1.74–1.89]), whereas comorbid chronic ulcer of the skin was associated with the highest adjusted rate ratios of Accident and Emergency department visits (1.73 [1.61–1.85]). Healthcare utilization for individuals with dementia differed substantially by both the number of comorbid chronic conditions and the presence of some specific comorbid conditions. These findings further highlight the importance of taking account of multiple long-term conditions in tailoring the care approach and developing healthcare plans for people with dementia
Predicting dementia diagnosis from cognitive footprints in electronic health records: a case-control study protocol
INTRODUCTION: Dementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case-control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history. METHODS AND ANALYSIS: We will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared. ETHICS AND DISSEMINATION: This study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients' records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities' Action in Response to Dementia project (https://www.tip-card.hku.hk/)
Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study
Background: By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory. Methods: Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age. Findings: A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages. Interpretation: The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively. Funding: The Research Grants Council of Hong Kong under the Early Career Scheme 27110519
Studies of Prototype CsI(Tl) Crystal Scintillators for Low-Energy Neutrino Experiments
Crystal scintillators provide potential merits for the pursuit of low-energy
low-background experiments. A CsI(Tl) scintillating crystal detector is being
constructed to study low-energy neutrino physics at a nuclear reactor, while
projects are underway to adopt this technique for dark matter searches. The
choice of the geometrical parameters of the crystal modules, as well as the
optimization of the read-out scheme, are the results of an R&D program.
Crystals with 40 cm in length were developed. The detector requirements and the
achieved performance of the prototypes are presented. Future prospects for this
technique are discussed.Comment: 32 pages, 14 figure
Test of Factorization Hypothesis from Exclusive Non-leptonic B decays
We investigate the possibility of testing factorization hypothesis in
non-leptonic exclusive decays of B-meson. In particular, we considered the non
factorizable \bar{B^0} -> D^{(*)+} D_s^{(*)-} modes and \bar{B^0} -> D^{(*)+}
(\pi^-, \rho^-) known as well-factorizable modes. By taking the ratios
BR(\bar{B^0}-> D^{(*)+}D_s^{(*)-})/BR(\bar{B^0}-> D^{(*)+}(\pi^-,\rho^-)), we
found that under the present theoretical and experimental uncertainties there's
no evidence for the breakdown of factorization description to heavy-heavy
decays of the B meson.Comment: 11 pages; submitted to PR
Semileptonic decays of , , and
Stimulated by recent observations of the excited bottom-strange mesons
and , we calculate the semileptonic decays , which is relevant for the exploration of the
potential of searching these semileptonic decays in experiment.Comment: 11 pages, 3 figures, 9 tables. More discussion added, some
descriptions changed. The version to appear in EPJ
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