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)

Robust kernelized graph-based learning

In healthcare, Electrocardiogram (ECG) signal is considered important to study life-threatening heart diseases that include arrhythmia (ARR), congestive heart failure (CHF). Mostly, atrial arrhythmia leads to CHF. Previous studies on ARR and CHF are focused on the binary classification of each category against normal sinus rhythm (NSR). So, there is a requirement to study the above disease cases together to detect the severity of the situation and take remedial action accordingly. The goal of this study is to analyse and classify these three different classes of ECG (namely ARR, CHF, and NSR) in an efficient way. We used 30 ECG recordings for each of the classes from the publicly available Physionet database. Since the temporal and spectral features by themselves may be insufficient to distinguish the classes, we sought to combine information across both. Accordingly, we considered feature representations from heart rate variability (HRV) of the ECG signal and wavelet-based features together with auto-regressive coefficients. To leverage complementary information across feature types, we employed feature-level fusion. We examined the performance of individual and fused feature types with multiple classifiers. The highest accuracy of 93.33% for three-class classification was obtained after feature fusion using Support Vector Machine (SVM). Although the performance of HRV features is relatively poor compared to wavelet-based features, their fusion improved the classification accuracy.

A Fusion Based Classification of Normal, Arrhythmia and Congestive Heart Failure in ECG

The Internet of Things (IoT) is an upcoming technology in our present day network scenario. IoT consists of resource constrained devices which communicate with each other to deliver the required services to the users. As more and more devices are connected to the existing IoT network, security and privacy aspects in IoT have become prominent. Limitations of IoT devices are resource and energy constraints, which restrict its computational capability. Thus, it becomes a challenge for scientists to design suitable security systems for IoT. The Blockchain is a proven distributed and secure system for financial transactions. This paper outlines security and privacy problems in IoT. It also explores the convergence of IoT and Blockchain technology and explores how the underlying technologies of Blockchain can be improved to address the various security problems associated with IoT.

Blockchain-Based Security Aspects in Internet of Things Network

Blood pressure (BP) measurement plays an essential role in the prevention of cardiovascular diseases. Studies have demonstrated Ultrasound (US) based BP analysis method combining with peripheral components of the circulatory system. In this paper, a cuffless BP measurement technique has been proposed using a portable continuous wave Doppler US system which consumes < 4 Watt of power. The US blood flow signal acquired utilizing 8 MHz pencil transducer probe from the brachial artery is denoised using soft thresholding method. The spectrogram envelope of maximum frequency is obtained by an adaptive signal noise slope intersection (SNSI) method to extract hemodynamic features. In the proposed method, 2-element Windkessel (WK) model consisting of peripheral resistance and arterial compliance is employed for BP estimation. Based on the extracted features, a machine learning algorithm determines the WK model parameters. From the experiments conducted on 85 subjects, it has been observed that both systolic and diastolic BP achieve Grade B and Grade C for British Hypertension Society (BHS) and IEEE Std. 1708 protocols, respectively. Regarding Association for the Advancement of Medical Instrumentation (AAMI) standard, diastolic BP estimation error is within an acceptable limit. The robustness of the approach is examined using pre-exercise and post-exercise performance of 10 subjects. Moreover, the effect on arterial compliance for increased BP and aging is observed to characterize the dynamic property of arterial system. The proposed method is non-invasive, non-occlusive, independent of any additional interfaces, operates with a small dataset and worthy of implementation as a portable system for point-of-care application.

Windkessel Model-Based Cuffless Blood Pressure Estimation Using Continuous Wave Doppler Ultrasound System

A major challenge in ASV is to improve performance with short speech segments for end-user convenience in real-world applications. In this paper, we present a detailed analysis of ASV systems to observe the duration variability effects on state-of-the-art i-vector and classical Gaussian mixture model-universal background model (GMM-UBM) based ASV systems. We observe an increase in uncertainty of model parameter estimation for i-vector based ASV with speech of shorter duration. In order to compensate the effect of duration variability in short utterances, we have proposed adaptation technique for Baum-Welch statistics estimation used to i-vector extraction. Information from pre-estimated background model parameters are used for adaptation method. The ASV performance with the proposed approach is considerably superior to the conventional i-vector based system. Furthermore, the fusion of proposed i-vector based system and GMM-UBM further improves the ASV performance, especially for short speech segments. Experiments conducted on two speech corpora, NIST SRE 2008 and 2010, have shown relative improvement in equal error rate (EER) in the range of 12–20%.

Goutam Saha

Papers

Robust kernelized graph-based learning

A Fusion Based Classification of Normal, Arrhythmia and Congestive Heart Failure in ECG

Blockchain-Based Security Aspects in Internet of Things Network

Windkessel Model-Based Cuffless Blood Pressure Estimation Using Continuous Wave Doppler Ultrasound System

Improved i-vector extraction technique for speaker verification with short utterances