This is an exploratory paper of the ethical implications for genomic research and mental illness with specific reference to Singapore. Singapore has a unique context due to its social and political systems, and although it is a relatively small country, its population is religiously and culturally diverse. The issues that we identify here, therefore, will offer new perspectives and will also shed light on the existing literature on psychiatric genomics in society. We contextualise issues such as risk and stigma in (...) the identification and diagnosis of psychosis in the way they relate to Singaporean society, and use a current study as a case example. Genomic research has the potential to change significantly he practice of clinical medicine if, as expected, fast and inexpensive sequencing becomes a reality. It will likely also change how society thinks and acts in respect to multi-factorial diseases, conditions, traits, and syndromes that have a genetic component. Genomic research already raises a number of ethical concerns relating to the privacy of individuals, including the disclosure of research results and incidental findings, surreptitious tests, third party access to data, and the re-emergence of genetic determinism. These issues are potentially exacerbated when genomics - the study of whole genomes to understand complex illness and behavioural traits - is applied to psychiatric research, because of the stigma that is often attached to mental illness. In this paper, we discuss some of the issues that have arisen in the context of a study in Singapore that is currently investigating the genomics and biomarkers of psychosis. We argue that although a genomic study rarely creates data that is directly useful to the participant, it can have incidental benefits to the individual who is identified during the study as being at high risk of developing psychosis and its related states. Understanding these potential benefits requires us to examine the implications that this type of research may have on public understandings of genomic data and risk. (shrink)

This is an exploratory paper of the ethical implications for genomic research and mental illness with specific reference to Singapore. Singapore has a unique context due to its social and political systems, and although it is a relatively small country, its population is religiously and culturally diverse. The issues that we identify here, therefore, will offer new perspectives and will also shed light on the existing literature on psychiatric genomics in society. We contextualise issues such as risk and stigma in (...) the identification and diagnosis of psychosis in the way they relate to Singaporean society, and use a current study as a case example. (shrink)

This study reveals that increases in the global population command an augmented demand for products and services that calls for more effective ways of using existing natural resources and materials. The recent development of information and communication technologies, which had a great impact on many areas, also had a damaging effect on the environment and human health. Therefore, societies are moving toward a greener future by reducing the consumption of nonrenewable materials, raw materials, and resources while at the same time (...) decreasing energy pollution and consumption. Since information technology is considered a tool for solving ecological difficulties, the green Internet of things is playing a vital role in creating a sustainable home. Extensive data analysis is required to obtain a valuable overview of the large and diverse data generated by the G-IoT. The gathered information will facilitate forecasting, decision-making, and other activities related to smart urban services and then contribute to the incessant development of G-IoT technology. Therefore, even if sustainable and smart cities become an actuality, the G-IoT approach and the knowledge gained through big data analysis will make cities more sustainable, safer, and smarter. The goal of this article is to combine innovation in technological development with the main focus on resource sharing in creating cities that improve the quality of life while reducing pollution and realizing more efficient use of the raw materials. In the practice of big data science, it is always of interest to provide the best description of the data under consideration. Recent studies have pointed out the applicability of the statistical distributions in modeling data in applied sciences. In this article, we introduce a new family of statistical models to provide the best description of the life span of the wireless sensors network’s data. Based on the proposed approach, a special submodel called new exponent power-Weibull distribution is studied in detail. The applicability of the proposed model is shown by analyzing the life span of the wireless sensors network’s data. (shrink)