Housing Design Analysis for Low-Income Families in Hong Kong and Bangkok

Housing and Interior Desig

Construction of a Teaching Package on Promoting Prosocial Internet Use and Preventing Antisocial Internet Use

In the construction of the teaching package on the Internet use, two major moral characters, respect and responsibility, form the core theoretical basis. The respect character consists of respect for others and self-respect while the responsibility character contains social, civil, and global responsibility. There are a total of nine units on the Internet use in the junior secondary curriculum. There are two units in Secondary One curriculum: the first unit deals with cheating behavior and privacy issues concerning the Internet, and the second one discusses the effect of excessive use of the Internet on life and study. In Secondary Two curriculum, we discuss the following social phenomena on the Internet with students: online shopping, pornographic materials on internet, and infringement of a copyright. Finally, we have designed four units on the Internet use in Secondary Three curriculum which focuses more on the relationship between the Internet use and our health. We try to answer the question on how we can use the Internet healthily and also the possibility on how it may hurt us. Similar to the second unit in Secondary One curriculum, we have designed three more units on discussing the effects of excessive use of the Internet with students. We would like to alert students that ineffective use of the Internet will hurt us mentally and physically. For illustrative purposes, two units in the Secondary One and Two curriculums are outlined in this paper

Megapneumonia Coinfection: pneumococcus, Mycoplasma pneumoniae,

We report a young girl who died of Streptococcus pneumoniae 19A pneumonia, septic shock, and hemolytic uremic syndrome despite prior pneumococcal vaccination, appropriate antibiotics, and aggressive intensive care support. Serotype 19A is not covered by the 7- or 10-valent pneumococcal vaccines. Mycoplasma pneumoniae and metapneumovirus were simultaneously detected by PCR in the nasopharyngeal and tracheal aspirates. The pneumococcus is penicillin sensitive. Although infections with each of these pathogens alone are typically mild, this case highlights that co-infection with the triple respiratory pathogens possibly contributed to the fatal outcome of this child. Also, the new policy in Hong Kong to use PCV13 may help prevent further cases of serotype 19A infections

Within- and between-person variability of exhaled breath condensate pH and NH4+ in never and current smokers

SummaryRecent studies have suggested that the collection of exhaled breath condensate (EBC) may be a viable method in occupational field studies to sample secretions of the lower airway because it is simple to perform and non-invasive. However, there are unresolved questions about whether certain laboratory conditions may influence the analysis of EBC biomarker measurements. A total of 12 subjects performed 116 EBC tests. The effect of short and long-term sample storage and sample volume on two biomarkers of acid stress, pH and NH4+, in EBC were investigated and did not significantly influence either marker measurement after argon deaeration. We also investigated the variability and the effect of smoking on the biomarkers by collecting six samples each from five adult never smokers and five adult current smokers over a period of 1 month (n=60 total). For pH, the within-person and between-person variability was larger in current smokers compared to never smokers. Similar results were found for NH4+. Cigarette packs smoked per day now was also associated with both pH (p=0.01) and NH4+ (p=0.04) using mixed effects regression analysis. The variability and smoking results suggest that repeated measurements of EBC pH and NH4+ from the same individual may accurately predict the biological state of the airways of current smokers when compared to never smokers

A Step Toward Workplace Obesity Prevention: Evaluation of Weight Management Program for Hospital-based Health Care Providers

Background: Obesity is a worldwide problem. Healthy workplace and lifestyle are crucial in preventing obesity. A workplace weight management program could create a culture of health and facilitate weight control among health care providers. The present study aims to describe and evaluate the health outcomes of the interaction of professional practice and organizational infrastructure. Method: The hospital-based weight management program was an eight-week pilot randomized controlled study for obese health care providers. The primary outcomes were body weight and body mass index. The secondary outcomes included serum fasting glucose, fasting cholesterol, triglyceride, high- and low-density lipoprotein, body fat percentage, body mass, and quality of life. The RE-AIM framework was used to examine the intervention’s reach, effectiveness, adoption, implementation and maintenance at individual and organizational levels. Results: The program successfully attained the target population. Health care providers demonstrated short-term weight loss and decreased serum fasting cholesterol level after completing the program. The excellent retention rate (95%) of the study suggested that the participants were well-engaged in self-weight management. The program was implemented with adequate resource and support from the health organization. The organization may consider continuing the program in view of its long-term benefits to health care providers. Conclusion: Supportive organizational structure and culture enhanced professional practice and improved the health outcomes of the hospital-based weight management program participants

An Uncertainty Aided Framework for Learning based Liver T1ρT_1\rho Mapping and Analysis

Objective: Quantitative $T_1\rho$ imaging has potential for assessment of biochemical alterations of liver pathologies. Deep learning methods have been employed to accelerate quantitative $T_1\rho$ imaging. To employ artificial intelligence-based quantitative imaging methods in complicated clinical environment, it is valuable to estimate the uncertainty of the predicated $T_1\rho$ values to provide the confidence level of the quantification results. The uncertainty should also be utilized to aid the post-hoc quantitative analysis and model learning tasks. Approach: To address this need, we propose a parametric map refinement approach for learning-based $T_1\rho$ mapping and train the model in a probabilistic way to model the uncertainty. We also propose to utilize the uncertainty map to spatially weight the training of an improved $T_1\rho$ mapping network to further improve the mapping performance and to remove pixels with unreliable $T_1\rho$ values in the region of interest. The framework was tested on a dataset of 51 patients with different liver fibrosis stages. Main results: Our results indicate that the learning-based map refinement method leads to a relative mapping error of less than 3% and provides uncertainty estimation simultaneously. The estimated uncertainty reflects the actual error level, and it can be used to further reduce relative $T_1\rho$ mapping error to 2.60% as well as removing unreliable pixels in the region of interest effectively. Significance: Our studies demonstrate the proposed approach has potential to provide a learning-based quantitative MRI system for trustworthy $T_1\rho$ mapping of the liver

Cerebral small vessel disease burden is associated with poststroke depressive symptoms: A 15-month prospective study

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients with acute ischemic stroke were followed over a 15-month period after the index stroke. A score of _7 on the 15-item Geriatric Depression Scale was defined as clinically significant PDS. Scores of the four SVD markers ascertained on magnetic resonance imaging were summed up to represent total SVD burden. The association between SVD burden and PDS was assessed with generalized estimating equation models. Results: The study sample had a mean age of 67.0 _ 10.2 years and mild-moderate stroke [National Institutes of Health Stroke Scale score: 3, interquartile, 1–5]. PDS were found in 18.3%, 11.6%, and 12.3% of the sample at 3, 9, and 15 months after stroke, respectively. After adjusting for demographic characteristics, vascular risk factors, social support, stroke severity, physical and cognitive functions, and size and locations of stroke, the SVD burden was associated with an increased risk of PDS [odds ratio = 1.30; 95% confidence interval = 1.07–1.58; p = 0.010]. Other significant predictors of PDS were time of assessment, female sex, smoking, number of acute infarcts, functional independence, and social support. Conclusion: SVD burden was associated with PDS examined over a 15-month follow-up in patients with mild to moderate acute ischemic stroke

Identifying the Alteration Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-Brain Voxel-Wise Degree Analysis

Patients with mild cognitive impairment (MCI) are at high risk for developing Alzheimer’s disease (AD), while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI) and stable MCI (SMCI) individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alternation patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer’s Disease Neuroimaging Initiative dataset, and the progression was determined based on a three-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a severe presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective evidence and an indicator to characterize the progression-related brain connectivity changes in MCI patients

Uncertainty-weighted Multi-tasking for T1ρT_{1\rho} and T2_2 Mapping in the Liver with Self-supervised Learning

Multi-parametric mapping of MRI relaxations in liver has the potential of revealing pathological information of the liver. A self-supervised learning based multi-parametric mapping method is proposed to map T$T_{1\rho}$ and T$_2$ simultaneously, by utilising the relaxation constraint in the learning process. Data noise of different mapping tasks is utilised to make the model uncertainty-aware, which adaptively weight different mapping tasks during learning. The method was examined on a dataset of 51 patients with non-alcoholic fatter liver disease. Results showed that the proposed method can produce comparable parametric maps to the traditional multi-contrast pixel wise fitting method, with a reduced number of images and less computation time. The uncertainty weighting also improves the model performance. It has the potential of accelerating MRI quantitative imaging