Indian Institute of Technology Madras

About: Indian Institute of Technology Madras is a facility organization based out in Chennai, Tamil Nadu, India. It is known for research contribution in the topics: Catalysis & Heat transfer. The organization has 20118 authors who have published 36499 publications receiving 590447 citations.

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

Abstract: Background: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. Results: A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew’s Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53%, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35%) the macro-averaged precision ranged between 50% and 80%, with a maximum F-Score of 55%.

Mechanical properties of palmyra/glass fiber hybrid composites

Abstract: Use of eco friendly composites gains attraction due to its lightweight and moderate strength in the recent years. Palmyra fiber is a natural fiber obtained from Palmyra (Borassus flabellifer) tree. Mechanical properties of randomly mixed short fiber composites are studied and optimum fiber length and wt% are estimated. This paper deals with the properties of (randomly mixed) palmyra fiber, glass fiber hybrid composites. Two types of specimens are prepared, one by mixing the palmyra and glass fiber and the other by sandwiching palmyra fiber between the glass fiber mats. Composite plates are prepared for different palmyra/glass fiber weight ratio. Rooflite resin is used as matrix. Tensile, impact, shear and bending properties are studied. The mechanical properties of the composites are improved due to the addition of glass fiber along with palmyra fiber in the matrix. The glass fiber skin–palmyra fiber core construction exhibits better mechanical properties than dispersed construction. Moisture absorption studies are conducted and the results are presented as a function of square root of time. Addition of glass fiber with palmyra fiber in the matrix decreases the moisture absorption of the composites.

Graphene: A reusable substrate for unprecedented adsorption of pesticides

Abstract: U nprecedented adsorption of chlorpyrifos (CP), endosulfan (ES), and malathion (ML) onto graphene oxide (GO) and reduced graphene oxide (RGO) from water is reported. The observed adsorption capacities of CP, ES, and ML are as high as ∼ 1200, 1100, and 800 mg g − 1 , respectively. Adsorption is found to be insensitive to pH or background ions. The adsorbent is reusable and can be applied in the fi eld with suitable modifi cations. A fi rst-principles pseudopotential-based density functional analysis of graphene‐water‐pesticide interactions showed that the adsorption is mediated through water, while direct interactions between graphene and the pesticides is rather weak or unlikely.