Tackling Latency Using FG

Applications that operate on datasets which are too big to fit in main memory, known in the literature as external-memory or out-of-core applications, store their data on one or more disks. Several of these applications make multiple passes over the data, where each pass reads data from disk, operates on it, and writes data back to disk. Compared with an in-memory operation, a disk-I/O operation takes orders of magnitude (approx. 100,000 times) longer; that is, disk-I/O is a high-latency operation. Out-of-core algorithms often run on a distributed-memory cluster to take advantage of a cluster\u27s computing power, memory, disk space, and bandwidth. By doing so, however, they introduce another high-latency operation: interprocessor communication. Efficient implementations of these algorithms access data in blocks to amortize the cost of a single data transfer over the disk or the network, and they introduce asynchrony to overlap high-latency operations and computations. FG, short for Asynchronous Buffered Computation Design and Engineering Framework Generator, is a programming framework that helps to mitigate latency in out-of-core programs that run on distributed-memory clusters. An FG program is composed of a pipeline of stages operating on buffers. FG runs the stages asynchronously so that stages performing high-latency operations can overlap their work with other stages. FG supplies the code to create a pipeline, synchronize the stages, and manage data buffers; the user provides a straightforward function, containing only synchronous calls, for each stage. In this thesis, we use FG to tackle latency and exploit the available parallelism in out-of-core and distributed-memory programs. We show how FG helps us design out-of-core programs and think about parallel computing in general using three instances: an out-of-core, distribution-based sorting program; an implementation of external-memory suffix arrays; and a scientific-computing application called the fast Gauss transform. FG\u27s interaction with these real-world programs is symbiotic: FG enables efficient implementations of these programs, and the design of the first two of these programs pointed us toward further extensions for FG. Today\u27s era of multicore machines compels us to harness all opportunities for parallelism that are available in a program, and so in the latter two applications, we combine FG\u27s multithreading capabilities with the routines that OpenMP offers for in-core parallelism. In the fast Gauss transform application, we use this strategy to realize an up to 20-fold performance improvement compared with an alternate fast Gauss transform implementation. In addition, we use our experience with designing programs in FG to provide some suggestions for the next version of FG

GLOBAL RESEARCH TRENDS IN ENTOMOLOGY DURING 2012 – 2016: AN ANALYTICAL STUDY

The present study explores the quantum of productivity in the field of Entomology. For this study, the data were downloaded from the ‘Web of Science Core Collection’ database and there were 1671 records contributed globally level over a period of five years i.e. 2012-2016. The study contributes to the different aspects of Entomology research, such as year wise distribution, country wise, authorship pattern, the degree of collaboration, and most prolific authors etc. The highest number of records was published in the year 2016, while lowest numbers of records was published in 2012. The doubling time for publications at the decreased level has been computed during 2013 - 2016. The frequency occurrence of words among the publications revealed that the word ‘Diptera’ is found more with 276 (16.5%). Lotka\u27s law with regard to author productivity of Entomology research output was applied. It could be seen that the proportion of all output based on single contribution is important. The total numbers of publications in entomology with collaboration among the top 10 countries are presented. Largest contribution of USA was 307 (18.4%), followed by South Korea with 264 (15.8%)

LNA probes substantially improve the detection of bacterial endosymbionts in whole mount of insects by fluorescent in-situ hybridization

BACKGROUND: Detection of unculturable bacteria and their localization in the host, by fluorescent in-situ hybridization (FISH), is a powerful technique in the study of host-bacteria interaction. FISH probes are designed to target the 16 s rRNA region of the bacteria to be detected. LNA probes have recently been used in FISH studies and proven to be more efficient. To date no report has employed LNA probes for FISH detection of bacterial endosymbiont in the whole mount tissues. Further, though speculated, bacteriocytes have not been reported from males of Bemisia tabaci. RESULTS: In this study, we compared the efficiency in detecting bacteria by fluorescent DNA oligonucleotides versus modified probes containing Locked Nucleic Acid (LNA) substitution in their structure. We used the insect Bemisia tabaci as the experimental material since it carried simultaneous infection by two bacteria: one a primary endosymbiont, Portiera (and present in more numbers) while the other a secondary endosymbiont Arsenophonus (and present in less numbers). Thus a variation in the abundance of bacteria was expected. While detecting both the bacteria, we found a significant increase in the signal whenever LNA probes were used. However, the difference was more pronounced in detecting the secondary endosymbiont, wherein DNA probes gave weak signals when compared to LNA probes. Also, signal to noise ratio for LNA probes was higher than DNA probes. We found that LNA considerably improved sensitivity of FISH, as compared to the commonly used DNA oligonucleotide probe. CONCLUSION: By employing LNA probes we could detect endosymbiotic bacteria in males, which have never been reported previously. We were able to detect bacteriocytes containing Portiera and Arsenophonus in the males of B. tabaci. Thus, employing LNA probes at optimized conditions will help to significantly improve detection of bacteria at the lowest concentration and may give a comprehensible depiction about their specific distribution within samples

Research Productivity in Human Genetics during 2014 – 2018: A Scientometric Approach

An attempt is made for bringing out the growth of literature on human genetics. Web of Science database has been used to retrieve the data of five years (2014-2018) by searching a keyword “Human Genetics in the combined topics, abstract and keywords fields. The scientometric tools and techniques such as document type, year wise distributions, language, and country wise distribution are used for measuring the outputs. Findings of the study indicate that more than 1966 (20.51%) research articles were published in the year 2016. English was the dominant language with 9393 (97.9%) followed by German with 71(0.7%). For the contributing top ten most productive countries, USA topped the list with 46.8%, followed by UK (12.9%), and China (10.1%). The frequency occurrence of words among the publications revealed that the word ‘Human’ is largely found with 1545 (16.1%) and followed by a word ‘genetics’ which occurred in 1389 (14.5%) publications. The results of Straight-line Equation and Time Series Analysis predict future trend of growth of research outputs in human genetics to reach 6374 research papers in the year 2034

When One Pipeline Is Not Enough

Pipelines that operate on buffers often work well to mitigate the high latency inherent in interprocessor communication and in accessing data on disk. Running a single pipeline on each node works well when each pipeline stage consumes and produces data at the same rate. If a stage might consume data faster or slower than it produces data, a single pipeline becomes unwieldy. We describe how we have extended the FG programming environment to support multiple pipelines in two forms. When a node might send and receive data at different rates during interprocessor communication, we use disjoint pipelines that send and receive on each node. When a node consumes and produces data from different streams on the node, we use multiple pipelines that intersect at a particular stage. Experimental results for two out-of-core sorting algorithms---one based on columnsort and the other a distribution-based sort---demonstrate the value of multiple pipelines

Comparative analysis of the remineralization potential of CPP?ACP with Fluoride, Tri-Calcium Phosphate and Nano Hydroxyapatite using SEM/EDX ? An in vitro study

In recent years, the non-invasive management of non cavitated caries lesions using remineralization systems to repair the enamel have received more attention from the scientific community. Aim: To quantitatively evaluate the remineralization potential of Casein phosphopeptide-amorphous calcium phosphate-fluoride(CPP-ACPF), Tri-calcium phosphate(TCP) & Nano-hydroxyapatite(nHAP) using Scanning Electron Microscopy(SEM) and Energy dispersive X-ray Analysis(EDX). 40 enamel specimens were prepared, and immersed in demineralising solution at a pH of 4.4 for 96 hours at 37°C, to induce artificial carious lesions. Remineralization was carried out for a period of 30 days using CPP-ACPF, TCP, nHAP. The specimens were evaluated for calcium and phosphorus content using SEM-EDX. The Ca/P mass % after remineralization was significantly higher with CPP-ACP-F and TCP-F followed by nHAP. CPP-ACP-F and TCP can promote significant remineralization of incipient carious lesions. These are excellent delivery vehicles available in a slow release amorphous form to localize calcium, phosphate and fluoride at the tooth surface

Rapid production of therapeutic proteins using plant system

Plant molecular farming is simply defined as the production of proteins therapeutics (PT) in plants, which involves transient gene expression in plants and purification of expressed protein to a great scale for diagnosis, treatment and other applications.  This is therapid,economical, safe and reproducible approach for the production of PTas compared to bacterial and mammalian systems. Protein yield and post-translational modifications are the major roadblocks that can be overcome byhigh expression strategies includes over expression constructs, suitable plant host systems and glycoengineering of proteins. The inherent ability of ideally producing safe, functional protein is the most striking phenomenon recognized by the pharmaceutical industries and developed many therapeutic products within few weeks to meet escalating demands during pandemic/epidemic outbreaks recentl

Association of dopamine receptor polymorphisms with schizophrenia and antipsychotic response in a South Indian population

<p>Abstract</p> <p>Background</p> <p>Alterations in the dopamine transmission and receptor density are hypothesized in the pathophysiology of schizophrenia but ethnic disparities are reported to exist in disease association and therapeutic response to psychotropic medication. Antipsychotics have higher binding affinity to D2 subtype of dopamine receptor. DRD2 Cys311, TaqIB1 and TaqIA1 variants are considered to have either reduced affinity for dopamine and hypo-dopaminergic activity.</p> <p>Methods</p> <p>We examined the role of Taq1B, Taq1D, S311C, H313H and Taq1A polymorphisms of DRD2 gene in schizophrenia and antipsychotic treatment response in 213 patients and 196 controls from a homogenous South Indian population. A more detailed genotype phenotype association analysis was carried out to understand the disease in terms of its socio-cultural factors.</p> <p>Results</p> <p>H313HTT genotype was found to be associated with schizophrenia (P = 0.004) while TaqIB1B1 genotype was significantly associated with higher psychopathology score. When treatment response was considered H313HCC, TaqIA2A2 and Taq1D1D1 had higher mean improvement scores. TaqID1D1 and H313HTT genotype were found to be significantly higher in responders than in nonresponder group. Distinct shift in the LD patterns of responder and non-responder group was observed. Certain symptoms were characteristic of our patient population. Following medication the scores and presentation of these symptoms tend to vary in the responder and non-responder groups.</p> <p>Conclusion</p> <p>Based on genotype phenotype correlations it can be suggested that certain polymorphisms can be defined for their critical functions in disease and their role in treatment response in South Indian population. The present study suggests that in addition to ethnic bias, socio-cultural factors should also be considered while evaluating genotype phenotype correlations, in association and treatment response to complex disorders like schizophrenia.</p