Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection

In order to optimize the signal timing for isolated intersection, a new method based on fuzzy programming approach is proposed in this paper. Considering the whole operation efficiency of the intersection comprehensively, traffic capacity, vehicle cycle delay, cycle stops, and exhaust emission are chosen as optimization goals to establish a multiobjective function first. Then fuzzy compromise programming approach is employed to give different weight coefficients to various optimization objectives for different traffic flow ratios states. And then the multiobjective function is converted to a single objective function. By using genetic algorithm, the optimized signal cycle and effective green time can be obtained. Finally, the performance of the traditional method and new method proposed in this paper is compared and analyzed through VISSIM software. It can be concluded that the signal timing optimized in this paper can effectively reduce vehicle delays and stops, which can improve traffic capacity of the intersection as well

Rare Copy Number Variations in a Chinese Cohort of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is heterogeneous in symptom and etiology. Rare copy number variations (CNVs) are important genetic factors contributing to ASD. Currently chromosomal microarray (CMA) detecting CNVs is recommended as a first-tier diagnostic assay, largely based on research in North America and Europe. The feature of rare CNVs has not been well characterized in ASD cohorts from non-European ancestry. In this study, high resolution CMA was utilized to investigate rare CNVs in a Chinese cohort of ASD (n = 401, including 177 mildly/moderately and 224 severely affected individuals), together with an ancestry-matched control cohort (n = 197). Diagnostic yield was about 4.2%, with 17 clinically significant CNVs identified in ASD individuals, of which 12 CNVs overlapped with recurrent autism risk loci or genes. Autosomal rare CNV burden analysis showed an overrepresentation of rare loss events in ASD cohort, whereas the rate of rare gain events correlated with the phenotypic severity. Further analysis showed rare losses disrupting genes highly intolerant of loss-of-function variants were enriched in the ASD cohort. Among these highly constrained genes disrupted by rare losses, RIMS2 is a promising candidate contributing to ASD risk. This pilot study evaluated clinical utility of CMA and the feature of rare CNVs in Chinese ASD, with candidate genes identified as potential risk factors

nature biotechnology VOLUME

To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies. Over the past few decades, a tremendous amount of resources and effort have been invested in mapping human disease loci genetically and later physically 1 . Since the completion of the human genome sequence, especially with advances in genome-wide association studies and ongoing cancer genome sequencing projects, an impressive list of disease-associated genes and their mutations have been produced 2 . However, it has rarely been possible to translate this wealth of information on individual mutations and their association with disease into biological or therapeutic insights 3 . Most of the drugs approved by the US Food and Drug Administration today are palliative 4 -they merely treat symptoms, rather than targeting specific genes or pathways responsible, even if associated genes are known. One main reason for this lack of success is the complex genotype-tophenotype relationships among diseases and their associated genes and mutations. In particular, (i) the same gene can be associated with multiple disorders (gene pleiotropy); and (ii) mutations in any one of many genes can cause the same clinical disorder (locus heterogeneity). For example, mutations in TP53 are linked to 32 clinically distinguishable forms of cancer and cancer-related disorders, whereas mutations in any of at least 12 different genes can lead to long QT syndrome. With the publication of several large-scale protein-protein interaction networks in human 5-8 , researchers have recently begun to use complex cellular networks to explore these genotype-to-phenotype relationships 2,9 , on the basis that many proteins function by interacting with other proteins. However, most analyses model proteins as graph-theoretical nodes, ignoring the structural details of individual proteins and the spatial constraints of their interactions. Here, we investigate on a large-scale the underlying molecular mechanisms for the complex genotype-to-phenotype relationships by integrating three-dimensional (3D) atomic-level protein structure information with high-quality large-scale protein-protein interaction data. Within the framework of this structurally resolved protein interactome, we examine the relationships among human diseases and their associated genes and mutations. RESULTS Structurally resolved protein interactome for human disease We first combined 12,577 reliable literature-curated binary interactions filtered from six widely used databases 10-15 (Online Methods) and 8,173 well-verified, high-throughput, yeast two-hybrid (Y2H) interactions Next, we structurally resolved the interfaces of these interactions using a homology modeling approach 16 . We used both iPfam 17 and 3did 18 to identify the interfaces of two interacting proteins by mapping them to known atomic-resolution 3D structures of interactions in the Protein Data Bank (PDB) Finally, to compile a comprehensive list of disease-associated genes and their mutations, we combined information from both Online Mendelian Inheritance in Man (OMIM

Morphology and evolution of submarine canyons on the northwest South China Sea margin

Submarine canyons are observed along both passive and active continental margins, but the factors controlling their complex morphology are still poorly understood. Here, we use high-resolution multibeam bathymetric and 2D seismic data to investigate an area of the northwest South China Sea in which 48 submarine canyons are identified. These previously unstudied submarine canyons incise the continental shelf, being located at a water depth between 200 m and 2200 m. Canyon morphology varies from southwest to northeast, namely in what their length and incision depth are concerned. We therefore divide these canyons into four main types: a) Types A, B and C showing a predominant NW-SE direction, and b) Type D canyons striking to the north. By analysing their internal architectures, we propose that submarine canyons along the northwest South China Sea margin were initiated in the Late Miocene by retrogressive slope failure in response to the gradual build-up of sediment on the continental slope. Differences in sediment supply and fault activity are recognised here as the main factors controlling the morphology of the investigated submarine canyons. In addition, recurrent mass-transport deposits (MTDs) fed sediment from the northwest South China Sea margin into the study area, accelerating the filling of the Central Canyon system, a giant submarine canyon located to the south of the investigated continental slope. The discovery of gas fields (LS22–1, LS17–2) and a gas hydrate drilling zone (GMGS5) in the Central Canyon system proves that MTDs comprise good reservoir intervals. Our results contribute to a better understanding of the origin and development of submarine canyons and highlight the role of sediment supply and tectonic events in controlling canyon morphology

Control and Data Flow Execution of Java Programs

Since decade understanding of programs has become a compulsory task for the students as well as for others who are involved in the process of developing software and providing solutions to open problems. In that aspect showing the problem in a pictorial presentation in a best manner is a key advantage to better understand it. We provide model and structure for Java programs to understand the control and data flow analysis of execution. Especially it helps to understand the static analysis of Java programs, which is an uttermost important phase for software maintenance. We provided information and model for visualization of Java programs that may help better understanding of programs for a learning and analysis purpose. The idea provided for building visualization tool is extracting data and control analysis from execution of Java programs. We presented case studies to prove that our idea is most important for better understanding of Java programs which may help towards static analysis, software debugging and software maintenance

Genetic Diagnostic Evaluation of Trio-Based Whole Exome Sequencing Among Children With Diagnosed or Suspected Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a group of clinically and genetically heterogeneous neurodevelopmental disorders. Recent tremendous advances in the whole exome sequencing (WES) enable rapid identification of variants associated with ASD including single nucleotide variations (SNVs) and indels. To further explore genetic etiology of ASD in Chinese children with negative findings of copy number variants (CNVs), we applied WES in 80 simplex families with a single affected offspring with ASD or suspected ASD, and validated variations predicted to be damaging by Sanger sequencing. The results showed that an overall diagnostic yield of 8.8% (9.2% in the group of ASD and 6.7% in the group of suspected ASD) was observed in our cohort. Among patients with diagnosed ASD, developmental delay or intellectual disability (DD/ID) was the most common comorbidity with a diagnostic yield of 13.3%, followed by seizures (50.0%) and craniofacial anomalies (40.0%). All of identified de novo SNVs and indels among patients with ASD were loss of function (LOF) variations and were slightly more frequent among female (male vs. female: 7.3% vs. 8.5%). A total of seven presumed causative genes (CHD8, AFF2, ADNP, POGZ, SHANK3, IL1RAPL1, and PTEN) were identified in this study. In conclusion, WES is an efficient diagnostic tool for diagnosed ASD especially those with negative findings of CNVs and other neurological disorders in clinical practice, enabling early identification of disease related genes and contributing to precision and personalized medicine

Over-Expression of a Maize N-Acetylglutamate Kinase Gene (ZmNAGK) Improves Drought Tolerance in Tobacco

Water deficit is a key limiting factor that affects the growth, development and productivity of crops. It is vital to understand the mechanisms by which plants respond to drought stress. Here an N-acetylglutamate kinase gene, ZmNAGK, was cloned from maize (Zea mays). ZmNAGK was expressed at high levels in maize leaves and at lower levels in root, stem, female flower and male flower. The expression of ZmNAGK was significantly induced by PEG, NaCl, ABA, brassinosteroid and H2O2. The ectopic expression of ZmNAGK in tobacco resulted in higher tolerance to drought compared to plants transformed with empty vector. Further physiological analysis revealed that overexpression of ZmNAGK could enhance the activities of antioxidant defense enzymes, and decrease malondialdehyde content and leakage of electrolyte in tobacco under drought stress. Moreover, the ZmNAGK transgenic tobacco accumulated more arginine and nitric oxide (NO) than control plants under drought stress. In addition, the ZmNAGK transgenic tobaccos activated drought responses faster than vector-transformed plants. These results indicate that ZmNAGK can play a vital role in enhancing drought tolerance by likely affecting the arginine and NO accumulation, and ZmNAGK could be involved in different strategies in response to drought stress