Gay Marriage: Analyzing Legal Strategies for Reform in Hong Kong and the United States

Like many countries, both the United States and Hong Kong face the question of whether to legalize gay marriage due to social, legal, and political forces within and beyond their borders. The legalization of same-sex marriage in one jurisdiction forces other jurisdictions to decide whether to recognize marriages celebrated there. Comparing the current state of U.S. and Hong Kong law reveals that only a direct challenge to discriminatory marriage laws will successfully effect change. Two U.S. state supreme court decisions provide examples of effective legal arguments in a direct challenge. Conflict of laws analysis for marriage and the public policy exception to the place of celebration rule in the United States and Hong Kong preclude importing gay marriage by availing oneself of friendlier law in another forum. Ultimately, the timing must be ripe to effectively mount a direct challenge. In the meantime, every effort made, even if unsuccessful, raises awareness within a forum, and slowly gives rise to tolerance

Just the Tip of the Iceberg: Using the 100th Anniversary of the Titanic Sinking to Teach Information Literacy

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Why clothes don’t fall apart : tension transmission in staple yarns

The problem of how staple yarns transmit tension is addressed within abstract models in which the Amontons-Coulomb friction laws yield a linear programing (LP) problem for the tensions in the fiber elements. We find there is a percolation transition such that above the percolation threshold the transmitted tension is in principle unbounded. We determine that the mean slack in the LP constraints is a suitable order parameter to characterize this supercritical state. We argue the mechanism is generic, and in practical terms, it corresponds to a switch from a ductile to a brittle failure mode accompanied by a significant increase in mechanical strength

COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings

We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a smartphone. This type of screening is non-contact, easy to apply, and can reduce the workload in testing centres as well as limit transmission by recommending early self-isolation to those who have a cough suggestive of COVID-19. The datasets used in this study include subjects from all six continents and contain both forced and natural coughs, indicating that the approach is widely applicable. The publicly available Coswara dataset contains 92 COVID-19 positive and 1079 healthy subjects, while the second smaller dataset was collected mostly in South Africa and contains 18 COVID-19 positive and 26 COVID-19 negative subjects who have undergone a SARS-CoV laboratory test. Both datasets indicate that COVID-19 positive coughs are 15\%-20\% shorter than non-COVID coughs. Dataset skew was addressed by applying the synthetic minority oversampling technique (SMOTE). A leave-$p$-out cross-validation scheme was used to train and evaluate seven machine learning classifiers: LR, KNN, SVM, MLP, CNN, LSTM and Resnet50. Our results show that although all classifiers were able to identify COVID-19 coughs, the best performance was exhibited by the Resnet50 classifier, which was best able to discriminate between the COVID-19 positive and the healthy coughs with an area under the ROC curve (AUC) of 0.98. An LSTM classifier was best able to discriminate between the COVID-19 positive and COVID-19 negative coughs, with an AUC of 0.94 after selecting the best 13 features from a sequential forward selection (SFS). Since this type of cough audio classification is cost-effective and easy to deploy, it is potentially a useful and viable means of non-contact COVID-19 screening.Comment: This paper has been accepted in "Computers in Medicine and Biology" and currently under productio

Applications of a “Whole Community” Framework for Enhancing Community or Campus Resilience

AbstractThe Community and Regional Resilience Institute (CARRI) has developed a unique approach to community resilience based on a “Whole Community” concept. It treats communities as a collection of systems, each with its own resilience. CARRI has applied its approach to two kinds of communities: civil communities, and institutions of higher education (IHEs). For both civil communities and IHEs, CARRI carried out a pilot program. For each participant, their leadership directed an assessment of the resilience of the component systems to the types of changes most relevant to that community. Each assessment provided suggestions for filling any gaps identified as part of the assessment. The pilot for the seven IHEs followed that for the seven civil communities and was able to take advantage of lessons learned from the first. These two pilot programs led to the following conclusions:•CARRI's systems-based approach is both understandable and usable by both types of communities. In practice, it seemed to provide a natural way to look at a community.•In general, IHEs were able to make better use of the approach than civil communities. This is due, in part, to the improvements made in the IHE pilot program based on the civil communities’ results. However, it also reflects the more hierarchical nature of IHEs, the tighter coupling of systems within an IHE and greater discretion in the use of resources in an IHE.•College campuses can be crucial catalysts for enhancing the resilience of civil communities.•Leadership is a key, perhaps the key, element in the success of a community resilience initiative

Effects of telemonitoring on glycaemic control and healthcare costs in type 2 diabetes: a randomised controlled trial

Introduction: This study examined the effect of a telehealth intervention on the control of type 2 diabetes, and subsequent potential cost-savings to the health system. Methods: This prospective randomised controlled trial randomised adults with type 2 diabetes to the intervention (diabetes program) or control (usual care) arm. Key eligibility criteria included an HbA1c level of at least 58 mmol/mol (7.5%) without severe or unstable comorbidities. All participants continued their usual healthcare, but participants in the intervention arm received additional diabetes care from a diabetes care coordinator via a home monitor that captured clinical measures. Data collected included biomedical, quality of life measures and healthcare (GP, outpatient and inpatient) costs. The primary outcome was HbA1c collected at baseline and six-months. Analysis was conducted on a complete case intention-to-treat basis. The healthcare system perspective was taken to calculate the incremental cost per percentage-point reduction in HbA1c. Results: Results from 63 participants from each study arm were analysed. HbA1c in the intervention group decreased from a median 68 mmol/mol (8.4%) to 58 mmol/mol (7.5%), and remained unchanged in the control group at median 65 mmol/mol (8.1%) at the six-month endpoint. The intervention effect on HbA1c change was statistically significant (p=0.004). Total healthcare costs in the intervention group, including the intervention costs, were lower (mean $3,781 vs$4,662; p<0.001) compared to usual care. Discussion: There was a clinically meaningful and statistically significant benefit from the telehealth intervention at a lower cost; thus, telehealth was cost-saving and produced greater health benefits compared to usual care

Don't bite! Earlier detection of deceptive intent facilitates skilled responses to rugby sidesteps [Abstract]

Conference abstract

Neuropsychological, academic, and adaptive functioning in children who survive inhospital cardiac arrest and resuscitation

Children suffering cardiac arrest (CA) are not uncommon in certain pediatric populations. Due to the increasing suruival rates of child CA patients, there is a growing interest in, and concern for, their long-term intellectual, academic, emotional, and adaptive functioning. This article describes the possible neurologic sequelae of CA in children and presents standardized assessment results on 25 children, 2 to 15 years of age, who suruived a CA while in the hospital. A majority of these children exhibited low-average to deficient levels of performance on neuropsychologic, achievement, and adaptive behavior measures. Duration of cardiac arrest and a medical risk score were significantly correlated with decreased functioning in child CA patients. Children who suffer a cardiac arrest are at high risk for academic struggles, and many may need special education seruices

Deceptive actions bias responses and impair discriminability: Signal detection analysis of rugby sidesteps [Abstract]

Conference abstract