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)

Reductive Cleavage of Carbon-Carbon Bond. A Facile Route to Bridged Eight Membered Rings Related to Taxanes.

In this paper, we have proposed a novel method for the reduction of the number of inferred false positives in gene regulatory networks, constructed from time-series microarray genetic expression datasets. We have implemented a hybrid statistical/swarm intelligence technique for the purpose of reverse engineering genetic networks from temporal expression data. The theory of combination has been used to reduce the search space of network topologies effectively. Recurrent neural networks have been employed to obtain the underlying dynamics of the expression data accurately. Two swarm intelligence techniques, namely, Particle Swarm Optimisation and a Bat Algorithm inspired variant of the same, have been used to train the corresponding model parameters. Subsequently, we have identified and used their common portions to construct a final network where the incorrect predictions have been filtered out. We have done preliminary investigations on experimental (in vivo) data sets of the real-world SOS DNA repair network in Escherichia coli. Furthermore, we have implemented our proposed algorithm on medium-scale networks, consisting of 10 and 20 genes. Experimental results are quite encouraging, and they suggest that the proposed methodology is capable of reducing the number of false positives, thus, increasing the overall accuracy and the biological plausibility of the predicted genetic networks.

A Novel Technique for Reduction of False Positives in Predicted Gene Regulatory Networks

Segmentation is typically the most computationally expensive step involved in majority of speaker diarization systems. Bayesian Information Criterion (BIC) is a very widely adopted method for segmentation of audio data. While BIC returns fairly good results in terms of segmentation performance, it suffers from the problem of enormous complexity. Moreover, BIC based diarization systems encounter the worst case complexity when there is no change point in the input audio stream at all. Many audio streams contain fairly large segments separated by a very few change points. In such cases, it becomes impractical to employ BIC segmentation because of its complexity. In this paper, we have proposed a modification to the baseline BIC segmentation scheme, which makes use of local search information to reduce the overall complexity of the segmentation procedure. The results have been tested on several audio streams from broadcast news and the diarization runtime has been found to get reduced by a factor of 3.45, with a marginally better segmentation performance.

Faster BIC segmentation using local speaker modeling

Hippocampus, a region of brain is considered to be essential for memory and navigation. This is a feature which is functionally and structurally quite similar among the mammals. As invasive studies in human are not advised and that in laboratory animals give an equivalent result this region was the subject of much research in the past three decades. Most of the researches were focused on the structural aspects of the region. This paper proposes a pattern recognition system to study the neural activity profile for male Evans rat performing delayed non-match to sample (DNMS) task. This system, takes into account the practical constraints during acquisition of the neural signals. The best result found in this study shows 5.2%, 5.3%, 5.5% prediction error for 1 sec, 2 sec and 3 sec ahead prediction respectively.

Neural activity profile for short time memory task

Context-aware devices and applications can benefit when audio from real-life environments is categorized into different acoustic scenes. Such categorization is referred to as acoustic scene classification (ASC). However, the scene labels are database dependent. For most of the ASC applications, rather than giving explicit scene labels (like home, park etc), a general estimate of the type of surroundings (e.g. indoor or outdoor) might be enough. ASC has been generally achieved with mel-scaled cepstral features by the state-of-the-art systems. The characteristics that differentiate one scene class from the other are embedded in the texture of the time-frequency representation of the audio. In this paper, we propose to capture this textural information through statistics of local binary pattern of the mel-filterbank energies. The experiments were conducted on two datasets having same scene classes but varying audio sample duration and unequal total amount of data. The proposed framework outperforms two mel-scale based benchmark systems.

Goutam Saha

Papers

Reductive Cleavage of Carbon-Carbon Bond. A Facile Route to Bridged Eight Membered Rings Related to Taxanes.

A Novel Technique for Reduction of False Positives in Predicted Gene Regulatory Networks

Faster BIC segmentation using local speaker modeling

Neural activity profile for short time memory task

Texture Features for High-level Classification of Acoustic Scenes