Optimization of Analytic Window Functions

Analytic functions represent the state-of-the-art way of performing complex data analysis within a single SQL statement. In particular, an important class of analytic functions that has been frequently used in commercial systems to support OLAP and decision support applications is the class of window functions. A window function returns for each input tuple a value derived from applying a function over a window of neighboring tuples. However, existing window function evaluation approaches are based on a naive sorting scheme. In this paper, we study the problem of optimizing the evaluation of window functions. We propose several efficient techniques, and identify optimization opportunities that allow us to optimize the evaluation of a set of window functions. We have integrated our scheme into PostgreSQL. Our comprehensive experimental study on the TPC-DS datasets as well as synthetic datasets and queries demonstrate significant speedup over existing approaches.Comment: VLDB201

Parameter estimation of cocomo model using the jaya algorithm for software cost estimation

In line with the advancement of computer technology, software is increasingly being used in place of hardware to help human do the daily chores. Estimate of the software development costs can be a major issue (i.e. in terms of determining the actual development costs). To date, many techniques have been proposed to help the software engineer determine the actual software cost. This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. The Constructive Cost Model (COCOMO) is a procedural software cost estimation model developed by Barry W. Boehm. In this case, the estimation of value of the COCOMO model parameters are determined for the cost and time estimation of the COCOMO model. As a result, COCOMO Jaya Algorithm (COCOMO JA) has been developed. The dataset NASA 63 project, Turkish dataset, and Kemerer dataset have been used. The experiment result shows the comparison between the standard COCOMO and COCOMO JA. The COCOMO JA demonstrated more minimize error as compare to the standard COCOMO. In conclusion, the JA suitable to evaluate the estimation effort and time for the COCOMO model

Extremely Low-light Image Enhancement with Scene Text Restoration

Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. However, we found out that most of these methods could not sufficiently recover the image details, for instance, the texts in the scene. In this paper, a novel image enhancement framework is proposed to precisely restore the scene texts, as well as the overall quality of the image simultaneously under extremely low-light images conditions. Mainly, we employed a self-regularised attention map, an edge map, and a novel text detection loss. In addition, leveraging synthetic low-light images is beneficial for image enhancement on the genuine ones in terms of text detection. The quantitative and qualitative experimental results have shown that the proposed model outperforms state-of-the-art methods in image restoration, text detection, and text spotting on See In the Dark and ICDAR15 datasets

Dying in cyberworld: violent video games extinguished children’s death concept and attitude

Death is often a taboo topic in society, especially among the Chinese community. Most of the violent video games spread immoral values of life and death. Hence deformed death concept and death attitude are easily moulded in children particularly without proper supervision from parents. The misconception of death concept and death attitude can manipulate primary school children’s attitudes towards death which gradually might lead children to harm themselves or others. This study is aimed at identifying the relationship between violent video games and children’s death concept and death attitude (Fear of death, Death avoidance, Approach Acceptance, Escape Acceptance). The differences between the level of exposure to violent video games towards children’s death concept and death attitude are also carried out in this study. A total of 397 data was collected from Malaysian Chinese schoolchildren between 10 to 12 years of age by using the purposive sampling method. Instruments used in this study consist of demographic information, Death Attitude Media Violence Exposure. The study showed that a high level of exposure towards violent video games had a significant negative correlation with death concept and fear of death, whilst significantly positive correlation with escape acceptance. The result of the independent samples t-test showed that children with high exposure to violent video games had lower death concept and fear of death and a higher level of escape acceptance. Further research is needed to explore the death concept and attitude among children as technology has become an inseparable part of human beings in the 4th Industrial Revolutio

Replication and Meta-analysis of the Association between BDNF Val66Met Polymorphism and Cognitive Impairment in Patients Receiving Chemotherapy.

Cancer-related cognitive impairment (CRCI) adversely affects cancer patients. We had previously demonstrated that the BDNF Val66Met genetic polymorphism is associated with lower odds of subjective CRCI in the multitasking and verbal ability domains among breast cancer patients receiving chemotherapy. To further assess our previous findings, we evaluated the association of BDNF Val66Met polymorphism with subjective and objective CRCI in a temporally separate cohort of patients and pooled findings from both the original (n = 145) and current (n = 193) cohorts in a meta-analysis. Subjective CRCI was assessed using FACT-Cog. Objective CRCI was evaluated using computerized neuropsychological tests. Genotyping was carried out using Sanger sequencing. The association of BDNF Val66Met genotypes and CRCI was examined with logistic regression. A fixed-effect meta-analysis was conducted using the inverse variance method. In the meta-analysis (n = 338), significantly lower odds of CRCI were associated with Met allele carriers based on the global FACT-Cog score (OR = 0.52, 95% CI 0.29-0.94). Furthermore, Met allele carriers were at lower odds of developing impairment in the domains of memory (OR = 0.34, 95% CI: 0.17-0.70), multitasking (OR = 0.33, 95% CI: 0.18-0.59), and verbal ability (OR = 0.46, 95% CI: 0.24-0.88). Consistent with the previous study, lower odds of subjective CRCI among patients with the BDNF Met allele was observed after adjusting for potential confounders in the multitasking (OR = 0.30, 95% CI: 0.14-0.67) domain. In conclusion, carriers of the BDNF Met allele were protected against global subjective CRCI, particularly in the domains of memory, multitasking, and verbal ability. Our findings further contribute to the understanding of CRCI pathophysiology

Regulation of epithelial–mesenchymal IL-1 signaling by PPARβ/δ is essential for skin homeostasis and wound healing

Skin morphogenesis, maintenance, and healing after wounding require complex epithelial–mesenchymal interactions. In this study, we show that for skin homeostasis, interleukin-1 (IL-1) produced by keratinocytes activates peroxisome proliferator–activated receptor β/δ (PPARβ/δ) expression in underlying fibroblasts, which in turn inhibits the mitotic activity of keratinocytes via inhibition of the IL-1 signaling pathway. In fact, PPARβ/δ stimulates production of the secreted IL-1 receptor antagonist, which leads to an autocrine decrease in IL-1 signaling pathways and consequently decreases production of secreted mitogenic factors by the fibroblasts. This fibroblast PPARβ/δ regulation of the IL-1 signaling is required for proper wound healing and can regulate tumor as well as normal human keratinocyte cell proliferation. Together, these findings provide evidence for a novel homeostatic control of keratinocyte proliferation and differentiation mediated via PPARβ/δ regulation in dermal fibroblasts of IL-1 signaling. Given the ubiquitous expression of PPARβ/δ, other epithelial–mesenchymal interactions may also be regulated in a similar manner

Common variants in SOX-2 and congenital cataract genes contribute to age-related nuclear cataract

Nuclear cataract is the most common type of age-related cataract and a leading cause of blindness worldwide. Age-related nuclear cataract is heritable (h2 = 0.48), but little is known about specific genetic factors underlying this condition. Here we report findings from the largest to date multi-ethnic meta-analysis of genome-wide association studies (discovery cohort N = 14,151 and replication N = 5299) of the International Cataract Genetics Consortium. We confirmed the known genetic association of CRYAA (rs7278468, P = 2.8 × 10−16) with nuclear cataract and identified five new loci associated with this disease: SOX2-OT (rs9842371, P = 1.7 × 1

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe