1,721,463 research outputs found
Job satisfaction and job behaviour of university graduates teaching in the secondary schools in Hong Kong : reach report.
Get PDFby Chan Chung-shun.Bibliography: leaves 62-64Thesis (M.B.A.)--Chinese University of Hong Kon
CUHK electronic theses & dissertations collection
No full textChan, Chung Shing.Thesis Ph.D. Chinese University of Hong Kong 2014.Includes bibliographical references.Abstracts also in Chinese.Title from PDF title page (viewed on 20, September, 2016)
A study of the development of securitization in Hong Kong.
No full textby Chan Chung King, Siu Wang Ching.Thesis (M.B.A.)--Chinese University of Hong Kong, 1987.Bibliography: leaves 82-84
CUHK electronic theses & dissertations collection
No full textChan Chung Yee Zenobia."August 2003."Thesis (Ph.D.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (p. 407-438).Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.Mode of access: World Wide Web.Abstracts in English and Chinese
Multi-purpose building in Mong Kok.
Get PDFChan Chung Yee Albert."Architecture Department, Chinese University of Hong Kong, Master of Architecture Programme 1997-98, design report."Includes bibliographical references.Chapter 1.0 --- IntroductionChapter 2.0 --- Project BriefChapter 3.0 --- Client ProfileChapter 4.0 --- Site ParticularsChapter 5.0 --- Design ProcessChapter 6.0 --- Characters in Proposed StreetChapter 7.0 --- Characters in Proposed BuildingChapter 8.0 --- Final DesignChapter 9.0 --- BibliographyChapter 10.0 --- Appendix A Programming ReportChapter 11.0 --- Appendix B Cost Estimatio
Genetic studies on familial genetic generalized epilepsy: A whole exome sequencing approach / Chan Chung Kin
No full textGenetic generalized epilepsy (GGE) is a form of epilepsy that is potentially caused by genetic factors. It accounts for 15-20% of all epilepsy worldwide and 18.7% of the epilepsy cases in Malaysia. Unlike focal epilepsy, patients with generalized epilepsy mainly rely on antiepileptic drugs to achieve seizure control. As a result, understanding of the molecular pathway behind generalized epilepsy would be beneficial as it can aid the treatment decision and the design of newer antiepileptic drugs. The pathway analyses in GGE were conducted on European population and these results may not be applied to Malaysian or Asian due to genetic variation. Hence, this project was conducted to identify the genetic factors and plausible biological processes associated with GGE in Malaysia. The project started with whole exome sequencing on 12 unrelated Malaysian probands (4 Malays, 3 Chinese and 5 Indians) and 2 unrelated Malaysian Chinese proband-parent trios, all the 14 probands were diagnosed with GGE and having family history of epilepsy. The exome sequencing data was then analysed with GATK and the variants were annotated with wANNOVAR. Following variant filtration, a 3-step functional characterization analysis encompassing gene prioritization, protein-protein interaction analysis and DAVID enrichment was conducted. The analysis found the GO terms related with sodium and calcium ion transport, such as GO:0035725, GO:0006814, GO:0070588 and GO:0070509, were highly associated with GGE among Malaysians. The active role of ion channels in epilepsy makes them an ideal therapeutic target for antiepileptic drugs in seizure suppression. From this prospective, the protein-protein interaction analysis has suggested the potential of dystrophin (DMD) to be used as therapeutic target due to its regulatory role on sodium transporters and calcium ion channels. Besides, the functional characterization analysis has also intimated the potential risk of tyrosine kinases NTRK1, NTRK2 and ERBB4 in the pathogenesis of GGE. Additionally, segregation analysis was conducted on 2 families to study the pathogenicity of the SCN1A c.5753C>T and ERBB4 c.1972A>T variants identified from this cohort. The results showed that the SCN1A variant was likely pathogenic but the ERBB4 variant was expected to induce epilepsy via an interaction with gamma-aminobutyric acid type A (GABA-A) receptor gene GABRA1 c.448G>A variant. A disease model illustrating the combined effect between the mutant ERBB4 and GABRA1 in GGE pathogenesis was proposed, this hypothesized disease model may provide a new insight on the impact of ERBB4 in the disturbance of inhibitory postsynaptic current (iPSC) and excitation-inhibition (E/I) balance. While this project is just a preliminary study on the genetics behind GGE among Malaysians, this study has demonstrated that ion channels are not the only cause of GGE, tyrosine kinases may also contribute to GGE by manipulating numerous biological pathways like the expression of GABA-A receptors. Moreover, the identification of DMD as a potential therapeutic target warrants further investigation as the findings may contribute to the design of new antiepileptic drugs in future
Optimization and modeling of microwave-assisted extraction of active compounds from cocoa leaves / Chan Chung Hung
Get PDFMicrowave-assisted extraction (MAE) is a promising technique for extraction of active compounds from plants and it has the potential to be commercialized. However, due to limited significant parameters to describe the MAE process, optimization and modeling of MAE for scaling up are challenging and restricted. To resolve the problem, two intensive energy-related parameters, i.e. absorbed power density (APD) and absorbed
energy density (AED) were introduced and they are respectively defined as the amount of microwave power (W/ml) and energy (J/ml) absorbed in the solvent during the extraction. Following that, three methods namely APD predictive method, AED modeling method and combined APD-AED optimization method were developed to model and optimize MAE at various extraction scales. The methods developed in this work are based on the extraction of anti diabetic compounds, i.e. isoquercitrin (0.13-3.51 mg/g), epicatechin (0.23-2.91 mg/g) and rutin (0.30-7.07 mg/g) from cocoa
(Theobroma cacao L.) leaves. Prior to the evaluation of the developed methods, the optimization and modeling of MAE were performed conventionally using response surface methodology (RSM) and Patricelli model, respectively. The optimum MAE conditions were determined to be 85% (v/v) aqueous ethanol at 50 ml/g (2g), 156 W, and 18 min, and its performance was similar to that obtained in Soxhlet extraction but with lesser solvent (50 ml/g vs. 100 ml/g) and shorter extraction time (18 min vs. 6 hr). From the modeling study, the washing step of MAE is strongly affected by the size of sample while the diffusion step is influenced by both the solvent to feed ratio (S/F) and microwave power (P). The findings obtained from the proposed methods suggest that the APD predictive method is able to predict the optimum extraction time for large scale MAE between 100-300 ml under various microwave power based on the correlation established between the optimum extraction time region and the APD of the extraction system. By conducting MAE at the predicted optimum extraction time region, more than 85% of equilibrium extraction yields can be achieved and the prediction is valid at solvent to feed ratio varying from 20 to 80 ml/g. Besides that, AED modeling method enables the prediction of overall extraction profiles of MAE. By adapting suitable extraction model i.e. film theory model at AED basis, a predictive model can be developed. The AED extraction model is accurate in capturing the experimental extraction profile of MAE at various microwave power (200-600 W) and solvent loading (100-300 ml) with R-square value > 0.87. In addition, APD-AED optimization method standardizes the optimization of MAE based on its extraction mechanisms. According to this method, the optimization can be performed using sequential single factor experiments based on APD and AED and the result obtained was similar to those obtained from the optimization using RSM. Most important, the intensive optimum MAE conditions (S/F = 50 ml/g, APD = 0.3 W/ml, AED = 300 J/ml) determined from this method can be used to determine the optimum operating parameters (S/F, Power, Time) of MAE at varying extraction scale (100-300 ml)
Factors influencing retinal axon pathfinding in developing mouse retinofugal pathway.
Get PDFChan, Chung Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 98-110).Abstracts in English and Chinese.Abstract --- p.iAbstract in Chinese --- p.ivAcknowledgements --- p.vTable of Abbreviations --- p.viTable of Contents --- p.viiChapter Chapter 1 --- General Introduction --- p.1Chapter Chapter 2 --- Functions of hyaluronan in the development of retinofugal pathwayIntroduction --- p.18Materials and Methods --- p.19Results --- p.23Discussion --- p.26Figures --- p.32Chapter Chapter 3 --- Characterization of Nogo and its receptor in retinofugal pathway using Western blot analysisIntroduction --- p.40Materials and Methods --- p.42Results --- p.50Discussion --- p.52Figures --- p.57Chapter Chapter 4 --- Expression patterns and functions of Sonic hedgehogin retinofugal pathwayIntroduction --- p.62Materials and Methods --- p.64Results --- p.69Discussion --- p.76Figures --- p.81Chapter Chapter 5 --- General Discussion --- p.91Figures --- p.95References --- p.9
Endogenous time preference in small open economy models.
Get PDFChan Chung Yan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 57-59).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivTable of Contents --- p.vList of Figures --- p.viChapter 1. --- Introduction --- p.1Chapter 2. --- An Illustration with a Small Open Economy ModelChapter 2.1 --- Review of Obstfeld (1990) --- p.4Chapter 2.2 --- A Model with Socially-Determined Time Preference --- p.6Chapter 3. --- Small Open Economy Models with Socially-Determined Time Preference --- p.15Chapter 3.1 --- The Laursen-Metzler Effect --- p.16Chapter 3.2 --- Exchange-Rate Dynamics --- p.21Chapter 3.3 --- Capital Mobility and Devaluation --- p.28Chapter 4. --- Dynamics of a Small Open Economy Model with Non-Flat Bond Curves --- p.35Chapter 4.1 --- Downward-Sloping Bond Curve --- p.38Chapter 4.2 --- Upward-Sloping Bond Curve --- p.38Chapter 5. --- Investment and Saving in a Small Open Economy Model with Capital AccumulationChapter 5.1 --- The Model --- p.41Chapter 5.2 --- Productivity Shocks --- p.46Chapter 6. --- Saddle-Path Stability of a Closed Economy Growth Model --- p.49Chapter 7. --- Conclusion --- p.54References --- p.57Appendix --- p.6
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