A comparative analysis of 21 literature search engines

With increasing number of bibliographic software, scientists and health professionals either make a subjective choice of tool(s) that could suit their needs or face a challenge of analyzing multiple features of a plethora of search programs. There is an urgent need for a thorough comparative analysis of the available bio-literature scanning tools, from the user’s perspective. We report results of the first time semi-quantitative comparison of 21 programs, which can search published (partial or full text) documents in life science areas. The observations can assist life science researchers and medical professionals to make an informed selection among the programs, depending on their search objectives. 
Some of the important findings are: 
1. Most of the hits obtained from Scopus, ReleMed, EBImed, CiteXplore, and HighWire Press were usually relevant (i.e. these tools show a better precision than other tools). 
2. But a very high number of relevant citations were retrieved by HighWire Press, Google Scholar, CiteXplore and Pubmed Central (they had better recall). 
3. HWP and CiteXplore seemed to have a good balance of precision and recall efficiencies. 
4. PubMed Central, PubMed and Scopus provided the most useful query systems. 
5. GoPubMed, BioAsk, EBIMed, ClusterMed could be more useful among the tools that can automatically process the retrieved citations for further scanning of bio-entities such as proteins, diseases, tissues, molecular interactions, etc. 
The authors suggest the use of PubMed, Scopus, Google Scholar and HighWire Press - for better coverage, and GoPubMed - to view the hits categorized based on the MeSH and gene ontology terms. The article is relavant to all life science subjects.
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A study on mechanical and thermal behavior of coir fiber reinforced epoxy composites

The main focus of this study is to utilize the properties of natural fibers and make them compatible with polymer resins effectively. Coir fibres have been used as reinforcement in epoxy resin with various weight percentages of 5%, 10% and 15%. Surface treatment method like alkali treatment is done to improve the performance of coir fibre on epoxy resin. Cow dung powder is added as filler to the composite with a purpose of improving the insulation property of the composite. The mechanical properties like tensile strength, flexural strength, impact strength and the micro hardness showed an increment with respect to fibre loading as well as the alkali treatment. The maximum value is found with the composite having 15% treated coir fibre. Flexural strength showed maximum value at 10% treated fibre loading which decreases after 10% fibre loading. When fibre loading was increased, thermal conductivity reduces. By adding cow dung powder to the untreated fibre composite, thermal conductivity is further decreased. From Thermo Gravimetric Analysis (TGA) it is found that the surface treated fibre composites resist the thermal decomposition effectively up to 2600C after that there is a considerable increase in the thermal stability. Differential Scanning Calorimetry (DSC) showed that the specific heat capacity increases with increase in fibre loading. Untreated fibre composites showed better specific heat capacity than the treated ones. Cow dung powder added to the untreated composite showed that maximum specific heat and specific heat capacity increases further to higher values as the quantity of cow dung powder is increased. Glass transition temperature (Tg) showed an increment with surface treatment as well as fibre loading of up to 10% and after that it decrease

IN-VITRO CYTOTOXICITY ACTIVITY OF MALAXIS RHEEDEI SW METHANOL EXTRACT AGAINST HELA CELL LINE AND MCF- 7 CELL LINE.

Cancer is a group of diseases caused by loss of cell cycle control. Cancer is associated with abnormal uncontrolled cell growth. The study was aimed to evaluation of the anticancer activity of the Malaxis rheedei Sw. on the HeLa cell line and MCF- 7cell line. The whole plant part of the Malaxis rheedei methanolic extract were tested for its inhibitory effect on HeLa Cell Line and MCF- 7cell line. The cytotoxicity of Malaxis rheedei on HeLa cell and MCF- 7cell line were evaluated by the MTT assay. Malaxis rheedei methanolic extract has significant cytotoxicity effect on MCF- 7cell line in concentration range between 18.75 to 300 µg/ml by using MTT assay and study also showed that inhibitory action on HeLa cell line inconcentration range between 18.75 to 300 µg/ml by using MTT assay. Methanol extract of  the whole plant part of Malaxis rheedei was found to be 7.3%, 16.6%,  25.4%, 36.3% and 47.1%toxic in HeLa cell line and 7.9%, 13.9%, 26%, 48.4% and 66.3% toxic in MCF- 7cell line. IC50 value of Malaxis rheedei on MCF- 7cell was  167.76  µg/ml and IC50 value of Malaxis rheedei on HeLa Cell was not found by MTT assay. From the performed assay, methanol extract of these drug shows greater activity on MCF- 7cell line and little activity on HeLa cell line and that mean Malaxis rheedei can be used as anticancer activity.Keywords: Cytotoxicity Activity, MTT Assay, Malaxis rheedei Sw. , HeLa CellLine, MCF- 7Cell Line

DATA POISONING ATTACKS ON PHASOR MEASUREMENT UNIT DATA

Phasor Measurement Units (PMUs) have been widely used in several regions to improve bulk power system situational awareness. PMUs provide utilities with enhanced monitoring and control capabilities and are regarded as one of the future\u27s most important measuring devices for power systems. Classifying PMU events is critical for making the power transmission system more reliable. Researchers have made tremendous progress in developing robust event classification models based on machine learning techniques; however, the proposed methods are vulnerable against adversarial attacks which potentially can degrade the event classification performance significantly. In this project, we evaluate the vulnerability of event classification models against data poisoning attacks for PMU data using feature collision attack. Moreover, we will leverage real-world PMU data to generate the poisonous data and observe how the added perturbations can change the measurement data. We will explain how to knowingly generate poisoned PMU data using a feature collision attack and its negative impact on a reliable event classifier