ChatGPT, an advanced language generation model developed by OpenAI, has the potential to revolutionize healthcare delivery and support for individuals with various conditions, including Down syndrome. This article explores the applications of ChatGPT in assisting children with Down syndrome, highlighting the benefits it can bring to their education, social interaction, and overall well-being. While acknowledging the challenges and limitations, we examine how ChatGPT can be utilized as a valuable tool in enhancing the lives of these children, promoting their cognitive development, and supporting their unique needs.
The spread of the novel coronavirus COVID-19 resulted in unprecedented worldwide countermeasures such as lockdowns and suspensions of all retail, recreational, and religious activities for the majority of 2020. Nonetheless, no adequate scientific data have been provided thus far about the impact of COVID-19 on driving behavior and road safety, especially in Malaysia. This study examined the effect of COVID-19 on driving behavior using naturalistic driving data. This was accomplished by comparing the driving behaviors of the same drivers in three periods: before COVID-19 lockdown, during COVID-19 lockdown, and after COVID-19 lockdown. Thirty people were previously recruited in 2019 to drive an instrumental vehicle on a 25 km route while recording their driving data such as speed, acceleration, deceleration, distance to vehicle ahead, and steering. The data acquisition system incorporated various sensors such as an OBDII reader, a lidar, two ultrasonic sensors, an IMU, and a GPS. The same individuals were contacted again in 2020 to drive the same vehicle on the same route in order to capture their driving behavior during the COVID-19 lockdown. Participants were approached once again in 2022 to repeat the procedure in order to capture their driving behavior after the COVID-19 lockdown. Such valuable and trustworthy data enable the assessment of changes in driving behavior throughout the three time periods. Results showed that drivers committed more violations during the COVID-19 lockdown, with young drivers in particular being most affected by the traffic restrictions, driving significantly faster and performing more aggressive steering behaviors during the COVID-19 lockdown than any other time. Furthermore, the locations where the most speeding offenses were committed are highlighted in order to provide lawmakers with guidance on how to improve traffic safety in those areas, in addition to various recommendations on how to manage traffic during future lockdowns.
Ambient Intelligence is a concept that relates to a new paradigm of pervasive computing and has the objective of automating responses from the system to humans without any human intervention. In social media forensics, gathering, analyzing, storing, and validating relevant evidence for investigation in a heterogeneous environment is still questionable. There is no hierarchy for automation, even though standardization and secure processes from data collection to validation have not yet been discussed. This poses serious issues for the current investigation procedures and future evidence chain of custody management. This paper contributes threefold. First, it proposes a framework using a blockchain network with a dual chain of data transmission for privacy protection, such as on-chain and off-chain. Second, a protocol is designed to detect and separate local and global cyber threats and undermine multiple federated principles to personalize search space broadly. Third, this study manages personalized updates by means of optimizing backtracking parameters and automating replacements, which directly affects the reduction of negative influence on the social networking environment in terms of imbalanced and distributed data issues. This proposed framework enhances stability in digital investigation. In addition, the simulation uses an extensive social media dataset in different cyberspaces with a variety of cyber threats to investigate. The proposed work outperformed as compared to traditional single-level personalized search and other state-of-the-art schemes.
Copy number variations can be identified using newer genotyping arrays with higher single nucleotide polymorphisms (SNPs) density and copy number probes accompanied by newer algorithms. McCarroll et al. (2008) applied these to the HapMap II samples and identified 1316 copy number polymorphisms (CNPs). In our study, we applied the same approach to 859 samples from three Singapore populations and seven HapMap III populations. Approximately 50% of the 1291 autosomal CNPs were found to be polymorphic only in populations of non-African ancestry. Pairwise comparisons among the 10 populations showed substantial differences in the CNPs frequencies. Additionally, 698 CNPs showed significant differences with false discovery rate (FDR)<0.01 among the 10 populations and these loci overlap with known disease-associated or pharmacogenetic-related genes such as CFHR3 and CFHR1 (age related macular degeneration), GSTTI (metabolism of various carcinogenic compounds and cancers) and UGT2B17 (prostate cancer and graft-versus-host disease). The correlations between CNPs and genome-wide association studies-SNPs were investigated and several loci, which were previously unreported, that may potentially be implicated in complex diseases and traits were found; for example, childhood acute lymphoblastic leukaemia, age-related macular degeneration, breast cancer, response to antipsychotic treatment, rheumatoid arthritis and type-1 diabetes. Additionally, we also found 5014 novel copy number loci that have not been reported previously by McCarroll et al. (2008) in the 10 populations.
Research on the role of copy number variations (CNVs) in the genetic risk of diseases in Asian populations has been hampered by a relative lack of reference CNV maps for Asian populations outside the East Asians. In this article, we report the population characteristics of CNVs in Chinese, Malay, and Asian Indian populations in Singapore. Using the Illumina Human 1M Beadchip array, we identify 1,174 CNV loci in these populations that corroborated with findings when the same samples were typed on the Affymetrix 6.0 platform. We identify 441 novel loci not previously reported in the Database of Genomic Variations (DGV). We observe a considerable number of loci that span all three populations and were previously unreported, as well as population-specific loci that are quite common in the respective populations. From this we observe the distribution of CNVs in the Asian Indian population to be considerably different from the Chinese and Malay populations. About half of the deletion loci and three-quarters of duplication loci overlap UCSC genes. Tens of loci show population differentiation and overlap with genes previously known to be associated with genetic risk of diseases. One of these loci is the CYP2A6 deletion, previously linked to reduced susceptibility to lung cancer.
The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.