77 research outputs found
A water soluble Ni-Schiff base complex for homogeneous green catalytic C S cross-coupling reactions
No full textSince the embarkation of C – S cross-coupling from aryl halides with thiols a handful of works have been
contemplated in aqueous medium. Herein, we report an example of a water soluble Ni-Schiff base complex as the green catalyst for the synthesis of thioethers. We have synthesized a Ni-Schiff base complex [NiL(H2O)2 ](ClO4)2 using N 4 -donor Schiff base ligand (1,3-bis(((E)-pyridin-2-ylmethylene)amino)propan-2-ol) and characterized by single crystal X-ray diffraction (SC-XRD) study along with different spectral analyses. The complex is mono-nuclear and cationic in nature having two perchlorate anions. Two water molecules remain coordinated with the Ni(II)-centre. The hydrogen bonding interaction through coordinated water and perchlorate anions connect the monomeric units to form 2D supramolecular structure. Based on its aqueous solubility, the complex has been used for the catalytic C – S cross-coupling reaction between aryl iodide and aryl or alkyl thiols using TBAB at 60 ◦ C in aqueous media (yield 92%). At room temperature, an isolated yield of 57% can be achieved. This environmentally benign protocol is paramount in view of the environmental sustainability
Green Energy Based Smart Farming System for Rural Living hood using Arduino
No full text<p>FOSET Academic MEET 2023</p>
Hyperaeschra innotata
No full textHyperaeschra innotata (Hampson, 1896) Phalera innotata * Hampson, 1896; 4: 455. Hyperaeschra innotata; Schintlmeister, 2013; 11: 222. TL: Khasis [Meghalaya, India]; TD: unknown type depository. Distribution: India: Meghalaya. Note: Endemic to NE India. *Hampson mentioned “Swinh. MS.” against the species in volume 4 of Fauna of British India, Moths. Since the species was described there for the first time, the credit as the main author is given to Hampson.Published as part of Chandra, Kailash, Mazumder, Arna, Sanyal, Abesh Kumar, Ash, Anirban, Bandyopadhyay, Uttaran, Mallick, Kaushik & Raha, Angshuman, 2018, Catalogue of Indian Notodontidae Stephens, 1829 (Lepidoptera: Noctuoidea), pp. 1-84 in Zootaxa 4505 (1) on page 37, DOI: 10.11646/zootaxa.4505.1.1, http://zenodo.org/record/260670
Discovering Play Store Reviews Related to Specific Android App Issues
No full textMobile App reviews may contain information relevant to developers. Developers can investigate these reviews to see what users of their apps are complaining about. However, the huge volume of incoming reviews is impractical to analyze manually. Existing research that attempts to extract this information suffers from two major issues: supervised machine learning methods are usually pre-trained, and thus, does not provide the developers the freedom to define the app issue they are interested in, whereas unsupervised methods do not guarantee that a particular app issue topic will be discovered.
In this thesis, we attempt to devise a framework that would allow developers to define topics related to app issues at any time, and with minimal effort, discover as many reviews related to the issue as possible. Scalable Continuous Active Learning (S-CAL) is an algorithm that can be used to quickly train a model to retrieve documents with high recall. First, we investigate whether S-CAL can be used as a tool for training models to retrieve reviews about a specific app issue. We also investigate whether a model trained to retrieve reviews about a specific issue for one app can be used to do the same for a separate app facing the same issue. We further investigate transfer learning methods to improve retrieval performance for the separate apps.
Through a series of experiments, we show that S-CAL can be used to quickly train models that can to retrieve reviews about a particular issue. We show that developers can discover relevant information during the process of training the model and that the information discovered is more than the information that can be discovered using keyword search under similar time restrictions. Then, we show that models trained using S-CAL can indeed be reused for retrieving reviews for a separate app and that performing additional training using transfer learning protocols can improve performance for models that performed below expectation.
Finally, we compare the performance of the models trained by S-CAL at retrieving reviews for a separate app against that of two state-of-the-art app review analysis methods one of which uses supervised learning, while the other uses unsupervised learning. We show that at the task of retrieving relevant reviews about a particular topic, models trained by S-CAL consistently outperform existing state-of-the-art methods
Insight into the molecular mechanism of the sulfur oxidation process by reverse sulfite reductase (rSiR) from sulfur oxidizer Allochromatium vinosum
No full text
Intermolecular Interaction Study of Dissimilatory Sulfite Reductase (DsrAB) from Sulfur Oxidizing Proteobacteria Allchromatium vinosum
No full textAnalysis of the Structural Details of DsrO Protein from Allochromatium vinosum to Identify the Role of the Protein in the Redox Transport Process Through the dsr Operon
No full textStructural analyses of the interactions of SoxY and SoxZ from thermo-neutrophilic &lt;i&gt;Hydrogenobacter thermophilus&lt;/i&gt;
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