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)

Gene regulatory networks are generally robust in nature. However, unwanted perturbations arising out of extreme environmental conditions or external pathogen attacks may lead them to malfunction. Potentially, this can have an adverse effect on the biochemical functions of a living system. In this work, we have proposed a computational model based on negative feedback control to eliminate the effects of such unwanted perturbations. We have implemented the recurrent neural network formalism for modelling the underlying network dynamics from a given time-series gene expression dataset. The artificial bee colony optimisation technique has been employed for model parameter estimation. The controller used in this work is of the proportional-integral-derivative type. To the best of our knowledge, this is one of the first research works in this domain to consider a completely non-linear scenario. A 10-gene DREAM4 benchmark network has been considered in this work. The results obtained herein show that the proposed formalism can mitigate the unwanted effects of external disturbances effectively.

Mitigating the Effects of External Perturbations on a Gene Regulatory Network using Feedback Controllers

This brief presents a memory based fast binary logarithmic converter based on a piecewise linear approximation technique. The proposed method is simple and arithmetic operation-less, which achieves 10−4 to 10−3 maximum absolute error (MAE) while maintaining a high speed. The approach partitions the logarithmic curve of the fractional component into $2^{L}$ uniform regions and a block RAM (size $2^{L} \times $ bits) stores the approximate value of each sub-region. For any number, most significant $L$ bits of the fractional component address the memory location of the logarithmic converter. The hardware synthesis result, implemented with 26 bits fractional precision on Virtex-6 field-programmable gate array device, shows 75% improvement in MAE and 27% decrease in critical path delay compared to the current state-of-the-art techniques in the worst-case scenario. In Otsu’s image thresholding algorithm, the proposed logarithmic converter with 3.08 ( $=2^{8} \times 12$ ) kbits memory size adequately meets the accuracy requirement for improved image segmentation.

A Low-Error, Memory-Based Fast Binary Logarithmic Converter

In this paper we investigate a technique to find out vocal source based features from the LP residual of speech signal for automatic speaker identification. Autocorrelation with some specific lag is computed for the residual signal to derive these features. Compared to traditional features like MFCC, PLPCC which represent vocal tract information, these features represent complementary vocal cord information. Our experiment in fusing these two sources of information in representing speaker characteristics yield better speaker identification accuracy. We have used Gaussian mixture model (GMM) based speaker modeling and results are shown on two public databases to validate our proposition.

In Search of Autocorrelation Based Vocal Cord Cues for Speaker Identification

This paper describes an approach to select the most relevant subspace in Kernel PCA feature space applied on MFCC coefficients for speech recognition. It has been seen that the relevant information about a supervised classification problem is contained in a finite number of leading Kernel PCA components if the Kernel matches the underlying classification problem. In this paper our contribution is to foster an understanding about the appropriate Kernel selection for different phonemes in a speech database and then create an insight about the most relevant dimensions for those phonemes in that Kernel space. Using this approach we have obtained better results for speech recognition as compared to standard technique.

Relevant subspace selection in Kernel feature space for speech recognition

Emerging areas like the IoT, etc., have computing environments that consist of numerous resource-constraint devices that are interconnected and communicated to each other. These devices need to operate in a secured environment; however, conventional cryptography is not suitable as they have low computational and memory resources. Security for such devices can be ensured by using lightweight cryptography instead. In this paper, a technique was proposed to design smaller S-boxes that can be used in lightweight block ciphers, hash functions, etc. The design technique used in the AES S-box was adopted and simplified in order to make these smaller S-boxes. The proposed S-boxes were compared with those used in the PRESENT cipher and the LUFFA hash function in terms of the different cryptographic properties and parameters. In addition, a change in the nonlinearity value of the proposed S-box was also calculated with reference to that of an AES S-box.

Goutam Saha

Papers

Mitigating the Effects of External Perturbations on a Gene Regulatory Network using Feedback Controllers

A Low-Error, Memory-Based Fast Binary Logarithmic Converter

In Search of Autocorrelation Based Vocal Cord Cues for Speaker Identification

Relevant subspace selection in Kernel feature space for speech recognition

Designing Lightweight S-Box Using Simplified Finite Field Inversion Mapping