Virtual reality for the built environment: A critical review of recent advances

This paper reviews the current state of the art for Virtual Reality (VR) and Virtual Environment (VE) applications in the field of the built environment. The review begins with a brief overview of technological components involved in enabling VR technology. A classification framework is developed to classify 150 journal papers in order to reveal the scholarly coverage of VR and VE from 2005 to 2011, inclusive. The classification framework summarizes achievements, established knowledge, research issues and challenges in the area. The framework is based on four layers of VR: concept and theory, implementation, evaluation and industrial adoption. These layers encompass architecture and design, urban planning and landscape, engineering, construction, facility management, lifecycle integration, training and education. This paper also discusses various representative VR research work in line with the classification framework. Finally the paper predicts future research trends in this area

Do Seasons Have an Influence on the Incidence of Depression? The Use of an Internet Search Engine Query Data as a Proxy of Human Affect

Background: Seasonal depression has generated considerable clinical interest in recent years. Despite a common belief that people in higher latitudes are more vulnerable to low mood during the winter, it has never been demonstrated that human's moods are subject to seasonal change on a global scale. The aim of this study was to investigate large-scale seasonal patterns of depression using Internet search query data as a signature and proxy of human affect. Methodology/Principal Findings: Our study was based on a publicly available search engine database, Google Insights for Search, which provides time series data of weekly search trends from January 1, 2004 to June 30, 2009. We applied an empirical mode decomposition method to isolate seasonal components of health-related search trends of depression in 54 geographic areas worldwide. We identified a seasonal trend of depression that was opposite between the northern and southern hemispheres; this trend was significantly correlated with seasonal oscillations of temperature (USA: r = −0.872, <0.001; Australia: r = −0.656, <0.001). Based on analyses of search trends over 54 geological locations worldwide, we found that the degree of correlation between searching for depression and temperature was latitude-dependent (northern hemisphere: r = −0.686; <0.001; southern hemisphere: r = 0.871; <0.0001). Conclusions/Significance: Our findings indicate that Internet searches for depression from people in higher latitudes are more vulnerable to seasonal change, whereas this phenomenon is obscured in tropical areas. This phenomenon exists universally across countries, regardless of language. This study provides novel, Internet-based evidence for the epidemiology of seasonal depression

pKNOT: the protein KNOT web server

Knotted proteins are more commonly observed in recent years due to the enormously growing number of structures in the Protein Data Bank (PDB). Studies show that the knot regions contribute to both ligand binding and enzyme activity in proteins such as the chromophore-binding domain of phytochrome, ketol–acid reductoisomerase or SpoU methyltransferase. However, there are still many misidentified knots published in the literature due to the absence of a convenient web tool available to the general biologists. Here, we present the first web server to detect the knots in proteins as well as provide information on knotted proteins in PDB—the protein KNOT (pKNOT) web server. In pKNOT, users can either input PDB ID or upload protein coordinates in the PDB format. The pKNOT web server will detect the knots in the protein using the Taylor's smoothing algorithm. All the detected knots can be visually inspected using a Java-based 3D graphics viewer. We believe that the pKNOT web server will be useful to both biologists in general and structural biologists in particular

Triptolide Transcriptionally Represses HER2 in Ovarian Cancer Cells by Targeting NF- κ

Triptolide (TPL) inhibits the proliferation of a variety of cancer cells and has been proposed as an effective anticancer agent. In this study, we demonstrate that TPL downregulates HER2 protein expression in oral, ovarian, and breast cancer cells. It suppresses HER2 protein expression in a dose- and time-dependent manner. Transrepression of HER2 promoter activity by TPL is also observed. The interacting site of TPL on the HER2 promoter region is located between −207 and −103 bps, which includes a putative binding site for the transcription factor NF-κB. Previous reports demonstrated that TPL suppresses NF-κB expression. We demonstrate that overexpression of NF-κB rescues TPL-mediated suppression of HER2 promoter activity and protein expression in NIH3T3 cells and ovarian cancer cells, respectively. In addition, TPL downregulates the activated (phosphorylated) forms of HER2, phosphoinositide-3 kinase (PI3K), and serine/threonine-specific protein kinase (Akt). TPL also inhibits tumor growth in a mouse model. Furthermore, TPL suppresses HER2 and Ki-67 expression in xenografted tumors based on an immunohistochemistry (IHC) assay. These findings suggest that TPL transrepresses HER2 and suppresses the downstream PI3K/Akt-signaling pathway. Our study reveals that TPL can inhibit tumor growth and thereby may serve as a potential chemotherapeutic agent

Clustering Heart Rate Dynamics Is Associated with β-Adrenergic Receptor Polymorphisms: Analysis by Information-Based Similarity Index

Background: Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β -AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β -AR gene polymorphisms and heart rate dynamics. Methods: A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6610.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β$_1$-AR Ser49Gly, β$_2$-AR Arg16Gly and β$_2$-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results: With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β$_2$-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions: We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β$_2$-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control

System Verification and Runtime Monitoring with Multiple Weakly-Hard Constraints

A weakly-hard fault model can be captured by an (m,k) constraint, where 0≤ m ≤ k , meaning that there are at most m bad events (faults) among any k consecutive events. In this article, we use a weakly-hard fault model to constrain the occurrences of faults in system inputs. We develop approaches to verify properties for all possible values of (m,k) , where k is smaller than or equal to a given  K , in an exact and efficient manner. By verifying all possible values of (m,k) , we define weakly-hard requirements for the system environment and design a runtime monitor based on counting the number of faults in system inputs. If the system environment satisfies the weakly-hard requirements, then the satisfaction of desired properties is guaranteed; otherwise, the runtime monitor can notify the system to switch to a safe mode. This is especially essential for cyber-physical systems that need to provide guarantees with limited resources and the existence of faults. Experimental results with discrete second-order control, network routing, vehicle following, and lane changing demonstrate the generality and the efficiency of the proposed approaches. </jats:p

Cross-National Differences in Victimization : Disentangling the Impact of Composition and Context

Varying rates of criminal victimization across countries are assumed to be the outcome of countrylevel structural constraints that determine the supply ofmotivated o¡enders, as well as the differential composition within countries of suitable targets and capable guardianship. However, previous empirical tests of these ‘compositional’ and ‘contextual’ explanations of cross-national di¡erences have been performed upon macro-level crime data due to the unavailability of comparable individual-level data across countries. This limitation has had two important consequences for cross-national crime research. First, micro-/meso-level mechanisms underlying cross-national differences cannot be truly inferred from macro-level data. Secondly, the e¡ects of contextual measures (e.g. income inequality) on crime are uncontrolled for compositional heterogeneity. In this paper, these limitations are overcome by analysing individual-level victimization data across 18 countries from the International CrimeVictims Survey. Results from multi-level analyses on theft and violent victimization indicate that the national level of income inequality is positively related to risk, independent of compositional (i.e. micro- and meso-level) di¡erences. Furthermore, crossnational variation in victimization rates is not only shaped by di¡erences in national context, but also by varying composition. More speci¢cally, countries had higher crime rates the more they consisted of urban residents and regions with lowaverage social cohesion.