Automated Quantification of Human Alpha Rhythm

This thesis seeks to quantify human alpha rhythm in order to obtain better measures to test theoretical models of neurodynamics, with potential clinical applications for the method of identification. An automated algorithm is developed in Chapter 2 to facilitate collection of objective data from an expanded alpha band (4–14 Hz) in a large number of subjects. This method avoids subjective bias inherent to traditional visual identification of the alpha activity, produced multiple peak information (if multiple peaks exist) that is absent in qEEG measures, and uses information from multiple electrode sites to eliminate spurious peaks. This method is tested and validated on 100 subjects. In addition to traditional measures of alpha activities such as the frequency and amplitude, further measures were devised to better quantify the alpha rhythm and its spatial characteristics. Background spectra in the alpha range are also characterized. In Chapter 3 the algorithm is applied to a large (1498 subjects) database of normal healthy subjects of approximately equal number in each sex, as well as a large span in age (6–86 years), in order to establish typical parameter ranges. Analysis is done comparing the age and the topological trends that are known variants in the alpha rhythm. Investigations are also performed to test for potential sex differences and/or lateralities. Key results are that double alpha peaks are resolved in a large proportion of the subjects ( 50%), while single alpha peak cases are likely to be double-peak cases in which the two peaks are not resolved. Age trends in measures of alpha activity show increase of alpha frequency from childhood to adolescence, a plateau in adulthood, and a slight decline in old age; a decrease in alpha amplitude in old age is also observed. These findings are consistent with previous literature and provide better statistics. Topological distribution of the alpha activity on the head is also explored, with little lateral asymmetry observed. No statistically significant differences between the sexes are found. The C++ code that was developed and utilized in this thesis is included in Appendix B. It is provided on disk and is available online. A study carried out on the same group of subjects to determine age-related trends of EEG parameters produced by model fitting is included in Appendixes C, to provide a comparison between the methods and highlights corresponding results

Structural Influences on Participation Rates: A Canada-U.S. Comparison

In contrast to the decline in labour force participation in Canada in the 1990s, the aggregate participation rate in the United States actually rose slightly (up 0.5 percentage points between 1989 and 1997). This US experience provides a useful benchmark for the analysis of the Canadian developments. In the second article of the symposium, Irene Ip, Sheryl King and Geneviève Verdier, while recognizing that cyclical influences have contributed significantly to the decline in labour force participation in the 1990s in Canada relative to the United States, focus on supply-side factors at play in the behviour of the participation rate in the two countries. A key structural variable influencing youth labour force participation is enrolment rates. As the participation rate of students is below that of non-students, increased enrolment tends to reduce aggregate participation. Enrolment rates for teenagers increased 7 percentage points in Canada between 1989 and 1997, and 5 points in the United States; rates for youth adults increased 11 points in Canada and 7 points in the United States. As the U.S. economy enjoyed low unemployment in both 1989 and 1997, the rise in enrolment rates was related to structural factors, such as the growing recognition of the importance of education for success on the job market. Structural factors were undoubtedly at play in Canada . However, the authors suggest that the increase in enrolment rates beyond that experienced in the United States (29 per cent of the increase in enrolment rates for teens and 36 per cent for young adults) may be interpreted as a cyclical response to weak employment opportunities in Canada. The authors find composition changes in the age structure of the population account for about one percentage point of the decline in the aggregate participation rate in Canada between 1989 and 1997, as the relative importance of low-participation rate groups has increased. Based on an analysis of the factors affecting labour force participation of the major age-sex groups, the authors forecast a rise in the aggregate participation rate in Canada from 65.1 per cent in 1998 to 66.6 per cent in 2006. For the United States, the Bureau of Labor Statistics is forecasting a smaller increase, but from a higher level, to 67.6 per cent in 2006 from 67.1 per cent in 1998. The authors expect increases in labour force participation for all age-sex groups in Canada. Between 1998 and 2006, the participation rate is forecast to rise 4.6 percentage points for older men (55 and over), 3.8 points for older women, 3.7 points for prime age women, 8.9 points for teenagers, 3.5 points for young adults, and even 1.0 points for prime-aged men. The 1.5 point increase in the aggregate participation rate is much smaller than almost all the increases in the age-sex group specific rates because of the changing age structure, in particular the increasing proportion of the population in older age groups.Canada, United States, Labour Force Participation, Labor Force Participation, Participation Rate, Labour Force Participation Rate, Labor Force Participation Rate, Age Structure, Age, Sex, Gender, Aging, Ageing

FastMap: A Fast Algorithm for Indexing, Data-Mining and Visualization of Traditional and Multimedia Datasets

A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in k-d space, using k feature-extraction functions, provided by a domain expert rJag91]. Thus. we can subsequently use highly fine-tuned spatia l access methods (SAMs), to answer several types of queries, including the 'Query By Example' type (which translates to a range query); the 'all pairs' query (which translates to a spatial join [BKSS94]); the nearest-neighbor or best-match query, etc. However, designing feature extraction functions can be hard. It is relatively easier for a domain expert to assess the similarity/distance of two objects. Given only the distance information though, it is not obvious how to map objects into points. This is exactly the topic of this paper. We describe a fast algorithm to map objects into points in some k-dimensional space (k is user-defined), such that the dissimilarities are preserved. There are two benefits from this mapping: (a) efficient retriev al, in conjunction with a SAM, as discussed before and (b) visualization and data-mining: the objects can now be plotted as points in 2-d or Sd space, revealing potential clusters, correlations among attributes and other regularities that data-mining is l ooking for. We introduce an older method from pattern recognition, namely, Multi-Dimcnsional Scaling (MDS) [Tor52]; although unsuitable for indexing, we use it as yardstick for our method. Then, we propose a much faster algorithm to solve the problem in hand, while in addition it allows for indexing. Experiments on real and synthetic data indeed show that the proposed algorithm is significantly faster than MDS, (being linear, as opposed to quadratic, on the database size N), while it manages to preserve distances an d the overall structure of the data-set. (Also cross-referenced as UMIACS-TR-94-132

Metamorphic testing of constraint solvers

Constraint solvers are complex pieces of software and are notoriously difficult to debug. In large part this is due to the difficulty of pinpointing the source of an error in the vast searches these solvers perform, since the effect of an error may only come to light long after the error is made. In addition, an error does not necessarily lead to the wrong result, further complicating the debugging process. A major source of errors in a constraint solver is the complex constraint propagation algorithms that provide the inference that controls and directs the search. In this paper we show that metamorphic testing is a principled way to test constraint solvers by comparing two different implementations of the same constraint. Specifically, specialised propagators for the constraint are tested against the general purpose table constraint propagator. We report on metamorphic testing of the constraint solver Minion. We demonstrate that the metamorphic testing method is very effective for finding artificial bugs introduced by random code mutation

Deep learning predicts the malignant-transformation-free survival of oral potentially malignant disorders

Machine-intelligence platforms for the prediction of the probability of malignant transformation of oral potentially malignant disorders are required as adjunctive decision-making platforms in contemporary clinical practice. This study utilized time-to-event learning models to predict malignant transformation in oral leukoplakia and oral lichenoid lesions. A total of 1098 patients with oral white lesions from two institutions were included in this study. In all, 26 features available from electronic health records were used to train four learning algorithms—Cox-Time, DeepHit, DeepSurv, random survival forest (RSF)—and one standard statistical method—Cox proportional hazards model. Discriminatory performance, calibration of survival estimates, and model stability were assessed using a concordance index (c-index), integrated Brier score (IBS), and standard deviation of the averaged c-index and IBS following training cross-validation. This study found that DeepSurv (c-index: 0.95, IBS: 0.04) and RSF (c-index: 0.91, IBS: 0.03) were the two outperforming models based on discrimination and calibration following internal validation. However, DeepSurv was more stable than RSF upon cross-validation. External validation confirmed the utility of DeepSurv for discrimination (c-index—0.82 vs. 0.73) and RSF for individual survival estimates (0.18 vs. 0.03). We deployed the DeepSurv model to encourage incipient application in clinical practice. Overall, time-to-event models are successful in predicting the malignant transformation of oral leukoplakia and oral lichenoid lesions

Using Latent Class Analyses to Examine Health Disparities among Young Children in Socially Disadvantaged Families during the COVID-19 Pandemic

Rising income inequality is strongly linked to health disparities, particularly in regions where uneven distribution of wealth and income has long been a concern. Despite emerging evidence of COVID-19-related health inequalities for adults, limited evidence is available for children and their parents. This study aimed to explore subtypes of families of preschoolers living in the disadvantaged neighborhoods of Hong Kong based on patterns of family hardship and to compare their patterns of parenting behavior, lifestyle practices, and wellbeing during the COVID-19 pandemic. Data were collected from 1338 preschoolers and their parents during March to June 2020. Latent class analysis was performed based on 11 socioeconomic and disease indicators. Multivariate logistic regressions were used to examine associations between identified classes and variables of interest during the COVID-19 pandemic. Four classes of family hardship were identified. Class 1 (45.7%) had the lowest disease and financial burden. Class 2 (14.0%) had the highest financial burden. Class 3 (5.9%) had the highest disease burden. Class 4 (34.5%) had low family income but did not receive government welfare assistance. Class 1 (low hardship) had lower risks of child maltreatment and adjustment problems than Class 2 (poverty) and Class 3 (poor health). However, children in Class 1 (low hardship) had higher odds of suffering psychological aggression and poorer physical wellbeing than those in Class 4 (low income), even after adjusting for child age and gender. The findings emphasize the need to adopt flexible intervention strategies in the time of large disease outbreak to address diverse problems and concerns among socially disadvantaged families

Subduction zone forearc serpentinites as incubators for deep microbial life

Serpentinization-fueled systems in the cool, hydrated forearc mantle of subduction zones may provide an environment that supports deep chemolithoautotrophic life. Here, we examine serpentinite clasts expelled from mud volcanoes above the Izu–Bonin–Mariana subduction zone forearc (Pacific Ocean) that contain complex organic matter and nanosized Ni–Fe alloys. Using time-of-flight secondary ion mass spectrometry and Raman spectroscopy, we determined that the organic matter consists of a mixture of aliphatic and aromatic compounds and functional groups such as amides. Although an abiotic or subduction slab-derived fluid origin cannot be excluded, the similarities between the molecular signatures identified in the clasts and those of bacteria-derived biopolymers from other serpentinizing systems hint at the possibility of deep microbial life within the forearc. To test this hypothesis, we coupled the currently known temperature limit for life, 122 °C, with a heat conduction model that predicts a potential depth limit for life within the forearc at ∼10,000 m below the seafloor. This is deeper than the 122 °C isotherm in known oceanic serpentinizing regions and an order of magnitude deeper than the downhole temperature at the serpentinized Atlantis Massif oceanic core complex, Mid-Atlantic Ridge. We suggest that the organic-rich serpentinites may be indicators for microbial life deep within or below the mud volcano. Thus, the hydrated forearc mantle may represent one of Earth’s largest hidden microbial ecosystems. These types of protected ecosystems may have allowed the deep biosphere to thrive, despite violent phases during Earth’s history such as the late heavy bombardment and global mass extinctions

Health-related quality of life during chemoradiation in locally advanced rectal cancer : impacts and ethnic disparities

Aims: There is limited data on health-related quality of life (HRQoL) in locally advanced rectal cancer. We assessed HRQoL before, during and after neoadjuvant chemoradiation, correlated this to corresponding clinician-reported adverse events (CR-AEs) and explored disparities between patients of Asian ethnicity versus Caucasians. Correlation between HRQoL and treatment response was also assessed. Methods: A consecutive sample of patients was recruited. HRQoL was assessed with the EORTC QLQ-C30 before chemoradiation, week three of chemoradiation and one-week pre-surgery. Clinical variables including CR-AEs were recorded at these time-points. Patients self-reported socio-demographic variables. Treatment response was assessed by the tumour regression grade. HRQoL data were analysed with multilevel models. Results: Fifty-one patients were recruited. HRQoL completion rates were ≥86%. Cognitive and role functioning worsened significantly during treatment. Emotional, role and social functioning improved significantly at pre-surgery. Fatigue and nausea/vomiting worsened during treatment while fatigue, appetite loss, diarrhoea and financial difficulties improved from treatment to pre-surgery. Almost 30% of the cohort were Asian ethnicity. Differences were found in multiple HRQoL domains between Asians and Caucasians, with Asians faring worse. Significant differences were evident in physical, role and cognitive functioning, and in seven out of the 8 symptom scales. The correlation between patient-reported outcomes and clinician-reported outcomes was weak, with diarrhoea having the strongest correlation (r = 0.58). Vomiting during treatment correlated with poor response, whilst baseline constipation correlated with good response. Conclusion: Chemoradiation for locally advanced rectal cancer affects multiple HRQoL domains. Our findings highlight the importance of psychological aspects of treatment. Significant differences were identified between the Asian and Caucasian populations, with Asians consistently performing worse. Poor correlations between patient and clinician reporting strongly support the inclusion of patient-reported outcomes in clinical studies. HRQoL domains of vomiting and constipation are potential biomarkers of treatment response

Body Mass Index (BMI) assessment among Macau students: age group differences and weight management strategies

There is evidence that rapid weight gain during the first year of life is associated with being overweight later in life. Therefore, overweight tendencies need to be detected at an appropriate age, and suitable strategies need to be implemented for weight management to achieve optimal long-term health. The objective of this study was to investigate comparisons in BMI status and associated categories in male and female students over ten years in two phases, including 2008-2013 and 2009-2014. Weight and height data were collected to obtain BMI (Body Mass Index) over ten years in two phases. The first phase occurred from 2008 to 2013, and the second phase occurred from 2009 to 2014 in a population of 10846 school children (Males: 6970, 64.3%, and females: 3875, 35.7%) in Macau. Their ages ranged from 6 years old in 2008 to 11 years old in 2013. The same age range was observed in the second phase, i.e., 2009-2014. Statistical analyses included descriptive statistics, such as the mean, standard deviation, t-tests to determine gender differences (year-wise) and a Chi square test for independence to determine the relationship between BMI (Underweight, Standard, Overweight and Obese) and age groups. In the first phase (2008-2013), the findings indicated a higher BMI level among the male students than the female students across all age groups (2008 t = 5.24, 2009 t = 88.25, 2010 t = 11.32, 2011 t = 17.45, 2012 t = 19.70 and 2013 t = 19.92). In the second phase (2009-2014), a higher BMI level was found among the male students than the female students across all age groups (2009 t = 2.68, 2010 t = 2.886, 2011 t = 3.076, 2013 t = 4.228, and 2014 t = 2.405). The results of the two phases combined (2008 to 2014 and 2009 to 2014) revealed that male students in 2008 had a higher BMI level than their counterparts in 2009 in the two age categories (8 years t = 3.025 and 11 years t = 3.377). Female students in the second phase (2009-2014) showed a higher BMI level than their male counterparts (9 years, t = 3.151). The results indicate the need to have focused strategies and structured interventions for male students at the critical age range of 8 to 9 years old. The results of this study also imply the need for the delivery of suitable school intervention activities at the appropriate time. Specifically, the prevention of weight gain should start early in life to encourage the development of healthier behaviours and habits throughout childhood and later ages

Effect of Pokémon Go on self-harm using population-based interrupted time-series analysis: quasi-experimental study

Background: Pokémon Go is a very popular location-based augmented reality game with widespread influences over the world. An emerging body of research demonstrates that playing Pokémon Go can lead to improvements in physical activity and psychosocial well-being; however, whether Pokémon Go reduces self-harm incidence at the population-level is still questionable. Objective: This study aimed to quantify how the launch of Pokémon Go in Hong Kong affected the incidence of self-harm using a quasi-experimental design. Methods: An interrupted time-series design with Poisson segmented regression adjusted for time and seasonality trends was used on data from 2012 to 2018 to detect any changes in the number of accident and emergency attendances due to self-harm, after Pokémon Go was launched. The findings were validated using a baseline control period and using other intentional injuries and minor noninjuries as control outcomes. We also assessed intervention effects by age group. Results: From January 1, 2012 to July 31, 2018, there were 13,463 accident and emergency attendances due to self-harm in Hong Kong. During the period after launching Pokémon Go, self-harm attendances dropped by 34% (adjusted incidence rate ratio: 0.66, 95% CI 0.61-0.73). When analyzed by age group, a reduction in self-harm incidence was only apparent in adults (18 to 24 years of age: adjusted incidence rate ratio: 0.78, P=.02; 25 to 39 years of age: adjusted incidence rate ratio: 0.75, P<.001; 40 years of age and older: adjusted incidence rate ratio: 0.57, P<.001). Conclusions: Self-harm incidence in the population, particularly in adults, showed a significant decline in the period after Pokémon Go was launched. Augmented reality games such as Pokémon Go show great promise as a tool to enhance psychosocial well-being and improve mental health