A Survey on Job and Task Scheduling in Big Data

Bigdata handles the datasets which exceeds the ability of commonly used software tools for storing, sharing and processing the data. Classification of workload is a major issue to the Big Data community namely job type evolution and job size evolution. On the basis of job type, job size and disk performance, clusters are been formed with data node, name node and secondary name node. To classify the workload and to perform the job scheduling, mapreduce algorithm is going to be applied. Based on the performance of individual machine, workload has been allocated. Mapreduce has two phases for processing the data: map and reduce phases. In map phase, the input dataset taken is splitted into keyvalue pairs and an intermediate output is obtained and in reduce phase that key value pair undergoes shuffle and sort operation. Intermediate files are created from map tasks are written to local disk and output files are written to distributed file system of Hadoop. Scheduling of different jobs to different disks are identified after completing mapreduce tasks. Johnson algorithm is used to schedule the jobs and used to find out the optimal solution of different jobs. It schedules the jobs into different pools and performs the scheduling. The main task to be carried out is to minimize the computation time for entire jobs and analyze the performance using response time factors in hadoop distributed file system. Based on the dataset size and number of nodes which is formed in hadoop cluster, the performance of individual jobs are identified\ud Keywords — \ud hadoop; mapreduce; johnson algorith

The Classic: A Morphogenetic Matrix for Differentiation of Bone Tissue

This Classic Article is a reprint of the original work by Marshall R. Urist, A Morphogenetic Matrix for Differentiation of Bone Tissue. An accompanying biographical sketch of Marshall R. Urist, MD is available at DOI 10.1007/s11999-009-1067-4; a second Classic Article is available at DOI 10.1007/s11999-009-1068-3; and a third Classic Article is available at DOI 10.1007/s11999-009-1069-2. The Classic Article is © 1970 by Springer and is reprinted with permission from Urist MR. A morphogenetic matrix for differentiation of bone tissue. Calc Tiss Res. 1970:4(Suppl);98–101

Antinuclear antibodies (ANA) in chronic hepatitis C virus infection: correlates of positivity and clinical relevance.

We examined correlates of antinuclear antibody (ANA) positivity (ANA+) in individuals with chronic hepatitis C virus (HCV) infection and the effect of positivity on clinical outcome of HCV. Pretreatment sera from 645 patients from three centres in Sweden (n = 225), the UK (n = 207) and Italy (n = 213) were evaluated by indirect immunofluorescence on Hep-2 cells for ANA pattern and titre by a single laboratory. Liver biopsies were all scored by one pathologist. A total of 258 patients were subsequently treated with interferon monotherapy. There was a significant difference in the prevalence of ANA (1:40) by geographic location: Lund 4.4%, London 8.7%, Padova 10.3% [odds ratio (OR) = 0.66; 95% CI: 0.46-0.94; P = 0.023]. Duration of HCV infection, age at infection, current age, route of infection, viral genotype, alcohol consumption, fibrosis stage and inflammatory score were not correlated with ANA+ or ANA pattern. Female gender was correlated with ANA+ and this association persisted in multivariable analyses (OR = 3.0; P = 0.002). Increased plasma cells were observed in the liver biopsies of ANA-positive individuals compared with ANA-negative individuals, while a trend towards decreased lymphoid aggregates was observed [hazard ratio (HR) = 9.0, P = 0.037; HR = 0.291, P = 0.118, respectively]. No correlations were observed between ANA positivity and nonresponse to therapy (OR = 1.4; P = 0.513), although ANA+ was correlated with faster rates of liver fibrosis, this was not statistically significant (OR = 1.8; P = 0.1452). Low titre ANA+ should not be a contraindication for interferon treatment. Our observation of increased plasma cells in ANA+ biopsies might suggest B-cell polyclonal activity with a secondary clinical manifestation of increased serum immunoglobulins

Imparting machine intelligence into direct ink write manufacturing

While digital manufacturing methods such as computer numerical control machining and additive manufacturing have enabled the creation of small lots of components with various complex shapes and materials. Understated, is the degree of individual process engineering and expertise required to tune material behavior, processing conditions to achieve expected properties. Current robotic manufacturing control frameworks lack the sensing and autonomy to effectively perceive and decide a course of action in response to these dynamic manufacturing environments. As a result, many commercial platforms limit user control over materials to ensure repeatability at the cost of agility. This paradigm fundamentally prevents the maturation of processes like direct ink write (DIW) additive manufacturing, which has been used to 3D print tissue scaffolds, ceramics, metals, magnets, and free-form structures.[1-5] In DIW additive manufacturing, both the materials behavior and desired structure are constantly changing, but the machine itself is rigid and never “learns” from past experiences. In general, only the user learns, thereby creating experienced “super users”. Using DIW as an example, we will present how materials and printed device development spurred the push to address the gap between robot and human experience by combining image classification, adaptive feedback, and analytical methods. A generalizable image classification method was developed to characterize the spanning behavior of a thixotropic fluid printed across 2- and 3-D gaps. The automated classification informed how to adapt the tool path and subsequently predict printing conditions for log-pile structures. By harvesting the relevant data and outcomes with user context, we seek to build an open knowledge community to enable more task-agnostic direct ink write manufacturing. Please click Additional Files below to see the full abstract

The secret world of shrimps: polarisation vision at its best

Animal vision spans a great range of complexity, with systems evolving to detect variations in optical intensity, distribution, colour, and polarisation. Polarisation vision systems studied to date detect one to four channels of linear polarisation, combining them in opponent pairs to provide intensity-independent operation. Circular polarisation vision has never been seen, and is widely believed to play no part in animal vision. Polarisation is fully measured via Stokes' parameters--obtained by combined linear and circular polarisation measurements. Optimal polarisation vision is the ability to see Stokes' parameters: here we show that the crustacean \emph{Gonodactylus smithii} measures the exact components required. This vision provides optimal contrast-enhancement, and precise determination of polarisation with no confusion-states or neutral-points--significant advantages. We emphasise that linear and circular polarisation vision are not different modalities--both are necessary for optimal polarisation vision, regardless of the presence of strongly linear or circularly polarised features in the animal's environment.Comment: 10 pages, 6 figures, 2 table

Role of a functional polymorphism in the F2R gene promoter in sarcoidosis

Sarcoidosis is a multisystem granulomatous disease of unknown aetiology characterized by increased inflammation, and results from gene-environment interactions. Proteinase-activated receptor-1 mediates the interplay between coagulation and inflammation. The rs2227744G > A promoter single nucleotide polymorphism has been linked to inflammation, cardiovascular disease and chronic obstructive pulmonary disease exacerbations. Using a case-control study (184 cases with sarcoidosis and 368 controls), we show that the rs2227744A allele significantly associates with protection from sarcoidosis (P = 0.003, OR = 0.68 (0.52-0.88))

Structural basis of dimerization and nucleic acid binding of human DBHS proteins NONO and PSPC1.

The Drosophila behaviour/human splicing (DBHS) proteins are a family of RNA/DNA binding cofactors liable for a range of cellular processes. DBHS proteins include the non-POU domain-containing octamer-binding protein (NONO) and paraspeckle protein component 1 (PSPC1), proteins capable of forming combinatorial dimers. Here, we describe the crystal structures of the human NONO and PSPC1 homodimers, representing uncharacterized DBHS dimerization states. The structures reveal a set of conserved contacts and structural plasticity within the dimerization interface that provide a rationale for dimer selectivity between DBHS paralogues. In addition, solution X-ray scattering and accompanying biochemical experiments describe a mechanism of cooperative RNA recognition by the NONO homodimer. Nucleic acid binding is reliant on RRM1, and appears to be affected by the orientation of RRM1, influenced by a newly identified 'β-clasp' structure. Our structures shed light on the molecular determinants for DBHS homo- and heterodimerization and provide a basis for understanding how DBHS proteins cooperatively recognize a broad spectrum of RNA targets