A SOA-driven business intelligence architecture

A business intelligence architecture comprises of different unique components to collect, transform, analyze and present the structured and unstructured raw data in simple formats to assist decision makers in making timely decisions. The introduction of service-oriented architecture (SOA) enables reusable services which are accessible over a network on demand. However, there is still a lack of academic literatures on the business intelligence architecture with service-oriented concept. Based upon various references on BI architectures from major vendors, a novel BI architecture that is built on service-oriented concept is presented and described in this paper. The proposed service-oriented architecture enables enterprises to deploy a more agile, flexible, cheaper, reusable, reliable and responsive BI applications in supporting decision making process.<br /

Technical factors for implementing SOA-Based business intelligence architecture : an exploratory study

Business intelligence (BI) architecture based on service-oriented architecture (SOA) concept enables enterprises to deploy agile and reliable BI applications. However, the key factors for implementing a SOA-based BI architecture from technical perspectives have not yet been systematically investigated. Most of the prior studies focus on organisational and managerial perspectives rather than technical factors. Therefore, this study explores the key technical factors that are most likely to have an impact on the implementation of a SOA-based BI architecture. This paper presents a conceptual model of BI architecture built on SOA concept. Drawing on academic and practitioner literature related to SOA and software architectural design, we propose fourteen key factors that may influence the implementation of a SOA-based BI architecture. This study bridges the gap between academic and practitioners.<br /

State-of-the-art review and critical success factors for mobile business intelligence

Due to ubiquitous information requirements, market interest in mobile business intelligence (BI) has grown markedly. However, mobile BI market is a relatively new area that has been driven primarily by the IT industry. Yet, there is a lack of systematic study on the critical success factors for mobile BI. This research reviews the state-of-the-art of mobile BI, and explores the critical success factors based on a rigorous examination of the academic and practitioner literature. The study reveals that critical success factors of mobile BI generally fall into four key dimensions, namely security, mobile technology, system content and quality, and organisational support perspectives. The various research findings will be useful to organisations which are considering or undertaking mobile business intelligence initiatives

Nickel hydroxide/chemical vapor deposition-grown graphene/nickel hydroxide/nickel foam hybrid electrode for high performance supercapacitors

Rational design of electrode structures has been recognized as an effective strategy to improve the electrochemical performance of electrode materials. Herein, we demonstrate an integrated electrode in which nickel hydroxide (Ni(OH)2) nanosheets are deposited on both sides of chemical vapor deposition-grown graphene on Ni foam, which not only effectively optimizes electrical conductivity of Ni(OH)2, but also accommodates the structural deformation assciated with the large volume change upon cycling. The synthesized Ni(OH)2/graphene/Ni(OH)2/Ni foam electrode exhibits a high specific capacity of 991 C g−1 at a current density of 1 A g−1, which is higher than the theoretical specific capacity of additive sum of Ni(OH)2 and graphene, and retains 95.4% of the initial capacity after 5000 cycles. A hybrid supercapacitor is constructed by using Ni(OH)2/graphene/Ni(OH)2/Ni foam as the positive electrode and activated carbon on Ni foam as the negative electrode, which achieves a maximum energy density of 49.5 W h kg−1 at a power density of 750 W kg−1, and excellent cycling lifespans with 89.3% retention after 10000 cycles at 10 A g−1

Prevalence and correlates of subjective cognitive impairment in Chinese psychiatric patients during the fifth wave of COVID-19 in Hong Kong

IntroductionThe extent of cognitive impairment and its association with psychological distress among people with pre-existing mental illness during COVID-19 is understudied. This study aimed to investigate prevalence and correlates of subjective cognitive impairment (SCI) in Chinese psychiatric patients during fifth-wave of COVID-19 in Hong Kong (HK).MethodsFour-hundred-eight psychiatric outpatients aged 18–64 years were assessed with questionnaires between 28 March and 8 April 2022, encompassing illness profile, psychopathological symptoms, coping-styles, resilience, and COVID-19 related factors. Participants were categorized into moderate-to-severe and intact/mild cognitive impairment (CI+ vs. CI-) groups based on severity of self-reported cognitive complaints. Univariate and multivariate regression analyses were conducted to determine variables associated with CI+ status.ResultsOne-hundred-ninety-nine participants (48.8%) experienced CI+. A multivariate model on psychopathological symptoms found that depressive and post-traumatic-stress-disorder (PTSD)-like symptoms were related to CI+, while a multivariate model on coping, resilience and COVID-19 related factors revealed that avoidant coping, low resilience and more stressors were associated with CI+. Final combined model demonstrated the best model performance and showed that more severe depressive and PTSD-like symptoms, and adoption of avoidant coping were significantly associated with CI+.ConclusionAlmost half of the sample of psychiatric patients reported cognitive complaints during fifth-wave of COVID-19 in HK. Greater depressive and PTSD-like symptom severity, and maladaptive (avoidant) coping were found as correlates of SCI. COVID-19 related factors were not independently associated with SCI in psychiatric patients. Early detection with targeted psychological interventions may therefore reduce psychological distress, and hence self-perceived cognitive difficulties in this vulnerable population

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The Effect of Central Loops in miRNA:MRE Duplexes on the Efficiency of miRNA-Mediated Gene Regulation

MicroRNAs (miRNAs) guide posttranscriptional repression of mRNAs. Hundreds of miRNAs have been identified but the target identification of mammalian mRNAs is still a difficult task due to a poor understanding of the interaction between miRNAs and the miRNA recognizing element (MRE). In recent research, the importance of the 5′ end of the miRNA:MRE duplex has been emphasized and the effect of the tail region addressed, but the role of the central loop has largely remained unexplored. Here we examined the effect of the loop region in miRNA:MRE duplexes and found that the location of the central loop is one of the important factors affecting the efficiency of gene regulation mediated by miRNAs. It was further determined that the addition of a loop score combining both location and size as a new criterion for predicting MREs and their cognate miRNAs significantly decreased the false positive rates and increased the specificity of MRE prediction