http://repository.ias.ac.in/39608/1/49_pub.pdf

A review of imperative technologies for wastewater treatment I: oxidation technologies at ambient conditions

A review of imperative technologies for wastewater treatment II: hybrid methods

The [2 + 2] photocycloaddition is undisputedly the most important and most frequently used photochemical reaction. In this review, it is attempted to cover all recent aspects of [2 + 2] photocycloaddition chemistry with an emphasis on synthetically relevant, regio-, and stereoselective reactions. The review aims to comprehensively discuss relevant work, which was done in the field in the last 20 years (i.e., from 1995 to 2015). Organization of the data follows a subdivision according to mechanism and substrate classes. Cu(I) and PET (photoinduced electron transfer) catalysis are treated separately in sections 2 and 4, whereas the vast majority of photocycloaddition reactions which occur by direct excitation or sensitization are divided within section 3 into individual subsections according to the photochemically excited olefin.

http://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.5b00723

Recent Advances in the Synthesis of Cyclobutanes by Olefin [2+2] Photocycloaddition Reactions

A review of applications of cavitation in biochemical engineering/biotechnology

CLINICAL NEUROSURGERY Edited by Barnes Wordall. Vol. 18. (Pp. 557; illustrated; £8 25.) Churchill Livingstone: Edinburgh. 1971. CLINICAL NEUROSURGERY Edited by G. T. Tindall. Vol. 19. (Pp. 598; illustrated; £12.) Churchill Livingstone: Edinburgh. 1972. The Congress of Neurosurgeons began in 1951 on the initiative of a group of younger neurosurgeons. In the last 20 years its membership has grown from 69 to over 1,000, but it has retained its original intentions and virility by a constitution which ensured that the office bearers and organizers were always young men. Residents in training are encouraged to join, financial concessions make it possible for them to attend meetings, and these are organized as an educational exercise, by inviting established authorities to give lectures on selected topics, chosen to provide a balanced programme. As a result Clinical Neurosurgery is a valuable volume which all neurosurgeons look forward to each year; it is in quite a different class from the usual conference tome, full of brief and unconnected papers of widely varying quality. As the title suggests Clinical Neurosurgery includes excellent clinical reviews but the two recent volumes include also a section of seminars on fundamental research-in volume 18 on coma and sleep, in volume 19 on basic mechanisms of memory. It is also the custom to invite a senior neurosurgical citizen as guest of honour and his two or three papers afford an opportunity for historical and philosophical reflections as well as an experienced perspective on clinical and experimental work. Add to this the refreshing presidential address, from one of the (angry?) young men of neurosurgery and it will be clear that these volumes really do include something of interest for every neurosurgeon, whatever his own interests or prejudices. It is a relief to be able so warmly to recommend these books, when the question posed by so many other books is whether anyone would really want to read them. The most recent volume has a more consistent theme than former ones, and that is 'head injury'. It includes papers on mechanisms as revealed by animal experiment and by a pathologist who visited the scene of the accident before examining the brains of head injury fatalities. There are chapters on engineering and socio-psychological aspects of accident prevention, as well as down to earth clinical accounts of metabolic disorders, testing for acoustic vestibular 36 damage, and aspects of prognosis. This is a significant contribution to the literature on head injury.

https://jnnp.bmj.com/content/jnnp/37/3/361.3.full.pdf

The working brain (an introduction to neuropsychology)

Biological databases, containing genetic information of patients, are undergoing tremendous growth beyond our analysing capability However such analysis can reveal new findings about the cause and subsequent treatment of any disease Interactions between genes and the proteins they synthesize shape Genetic Regulatory Networks (GRN) In this context, it has been developed a model capable of representing small dominant GRN, combining characteristics from the Rough Set and Bayesian Network The investigation has been carried out on the publicly available microarray dataset for Lung Adenocarcinoma, obtained from the National Center for Biotechnology Information (NCBI) website The analysis revealed that Rough Set Theory (RST) is able to extract the various dominant genes in term of reducts which play an important role in causing the disease and also able to provide a unique simplified rule set for building expert systems in medical sciences with high accuracy and coverage factor The next part of this work is based on reconstruction of GRN using Bayesian network, which is a mathematical tool for modelling conditional independences between stochastic variables like different gene expression This proposed Bayesian approach using scaled mutual information for scoring is applied to the dataset corresponding to most dominant responsible genes for Adenocarcinoma to uncover, gene/protein interactions and key biological features of the cellular system Finally different interacting regulatory path which are the gene signature for a particular disease, between dominating genes are inferred from the probability distribution table and Bayesian Graph Such reconstructed regulatory network is attractive for their ability to describe complex stochastic processes like gene transcription, classification of biological sequencing and intuitive model of causal influence successfully This may serve as a signature pattern of the disease Adenocarcinoma, which has been extracted from huge microarray dataset Extraction of this signature pattern is very useful for diagnosis of this disease

/pdf/reconstruction-of-dominant-gene-regulatory-network-from-1r411c1i4r.pdf

Reconstruction of Dominant Gene Regulatory Network from Microarray Data Using Rough Set and Bayesian Approach

The correct inference of gene regulatory network plays a critical role in understanding biological regulation in cells and genome based therapeutics. DNA microarray is the most widely used technology for extracting the relationships between thousands of genes simultaneously. Since S-system is based on the rate law, it is considered as a suitable mathematical model for representing complex biological reactions between genes. As, this problem has multiple solutions, optimized solution need to be identified via different nature inspired metaheuristic algorithms. So, in this paper, a new method is elaborated that helps to infer gene regulatory network for Lung Adenocarcinoma using S-system and Firefly Optimization which is an efficient but simple metaheuristic inspired by natural motion of fireflies. By optimizing the values of parameters of the S-system model, gene network can be easily reconstructed and inferred. Though direct biological validation of the network is not possible, but accuracy of the proposed method can be described as how well the network fit with the initial training data for different genes which is quite satisfactory for our research work.

S-system based gene regulatory network reconstruction using Firefly algorithm

Detection of lung abnormalities by characterizing lung sounds has been a primary step for clinical examination for a pulmonologist. This work focuses on utilization of cepstral features for lung sound analysis and classification. The proposed method incorporates statistical properties of cepstral features along with artificial neural network (ANN) based classification. Experimental results indicate that the proposed features outperform the wavelet-based features and conventional mel-frequency cepstral features. Further analyses have been performed on the proposed features to experimentally optimize the frame size and feature dimensionality. We also look at optimizing number of hidden layer nodes to improve robustness. We have found that the optimized features perform better for a wide range of signal-to-noise ratio (SNR) values.

Optimization of cepstral features for robust lung sound classification

The accurate reconstruction of gene regulatory networks for proper understanding of the intricacies of complex biological mechanisms still provides motivation for researchers. Due to accessibility of various gene expression data, we can now attempt to computationally infer genetic interactions. Among the established network inference techniques, S-system is preferred because of its efficiency in replicating biological systems though it is computationally more expensive. This provides motivation for us to develop a similar system with lesser computational load. In this work, we have proposed a novel methodology for reverse engineering of gene regulatory networks based on a new technique: half-system . Half-systems use half the number of parameters compared to S-systems and thus significantly reduce the computational complexity. We have implemented our proposed technique for reconstructing four benchmark networks from their corresponding temporal expression profiles: an 8-gene, a 10-gene, and two 20-gene networks. Being a new technique, to the best of our knowledge, there are no comparable results for this in the contemporary literature. Therefore, we have compared our results with those obtained from the contemporary literature using other methodologies, including the state-of-the-art method, GENIE3 . The results obtained in this work stack favourably against the competition, even showing quantifiable improvements in some cases.

Goutam Saha

Papers

Reconstruction of Dominant Gene Regulatory Network from Microarray Data Using Rough Set and Bayesian Approach

S-system based gene regulatory network reconstruction using Firefly algorithm

Optimization of cepstral features for robust lung sound classification

Modified Half-System Based Method for Reverse Engineering of Gene Regulatory Networks

Detection of peripheral arterial disease using Doppler spectrogram based expert system for Point-of-Care applications