Recoil tritium-C60 interaction: a channel for endohedral encapsulation of tritium in C60

The introduction of tritium (T), with an initial kinetic energy of 2.7 MeV into the cavity of C₆₀ using recoil implantation is studied in a ⁶Li(n,α)T activated homogenized compound matrix of Li₂CO₃ and C_60. Radioactive endohedral T@C₆₀ could be detected through the liquid scintillation spectrometry coupled with high-pressure liquid chromatography (HPLC). Fast atom bombardment mass spectrometry provided evidence for the retainment of C₆₀ cage as against radiation damage. Solid state temperature-programmed desorption based on evolved gas showed the desorption of ³He gas (as a β⁻ decay product from T) from the endohedral C₆₀ cage at a higher temperature than the T₂ and T₂O trapped species at the defect sites and from the ordered crystallographic network of Li₂CO₃, respectively. The non-isothermal kinetics of the helium desorption, as a function of temperature evidenced a diffusion controlled process.     

Copolymerization of N‐(4‐carboxyphenyl) itaconimide or N‐(4‐carboxyphenyl) itaconamic acid with methyl methacrylate

This paper describes the synthesis and characterization of N‐(4‐carboxyphenyl) itaconamic acid (CPA) and N‐(4‐carboxyphenyl) itaconimide (CPI) obtained by reacting itaconic anhydride with p‐aminobenzoic acid. Structural and thermal characterization of CPA and CPI was done using ¹H‐NMR, FTIR, and differential scanning calorimetry (DSC). Copolymerization of CPA or CPI with methyl methacrylate (MMA) in solution was carried out at 60 °C using azobisisobutyronitrile as an initiator and dimethyl acetamide or THF as solvent. Feed compositions having varying mole fractions of CPA or CPI ranging from 0.05–0.20 or 0.1–0.5 were taken to prepare copolymers. Copolymerizations were terminated at low percentage conversion. Structural characterization of copolymers was done by ¹H‐NMR and elemental analysis. Copolymer composition was determined using percentage nitrogen content. The reactivity ratios were r₁ (MMA) = 0.68 ± 0.06 and r₂ (CPI) = 0.46 ± 0.06. The intrinsic viscosity [η] was determined using an Ubbelohde suspension level viscometer. [η] decreased with increasing mole fraction of N‐(p‐carboxyphenyl) itaconimide or N‐(p‐carboxyphenyl) itaconamic acid in copolymers. Glass transition temperature and thermal stability of the copolymers were determined using DSC and thermogravimetric analysis, respectively. The glass transition temperature (T_g) as determined from DSC scans increased with increasing amounts of CPA or CPI in copolymers. A significant improvement in the char yield was observed upon copolymerization. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 1909–1915, 2005     

Microtextural analysis of coke from single and binary blend and its impact on coke quality

Coke microtexture and microstructure is a function of feed coal composition and carbonisation process. If the process remains constant, the composition plays a vital role in developing the microtexture and microstructure which also reflects the coke quality. Knowledge of the influence of coal composition and characteristics on coke quality is a must for formulating a coal blend for coke making. To better understand how the coal transforms into coke requires the ability to correlate the microtextural and microstructural features to coal properties. Petrography is an important tool for comparing the feed coal and corresponding coke. In the present study, cokes manufactured from single coals and two-component blends under similar coking conditions were studied under the microscope to provide valuable information to coke makers. Not only the rank and quantification of macerals but also the association of macerals and minerals play an important role. Also the size and type of inertinite affect the coke quality. Micro-cracking, crack lengths and fissures identify the zone of weakness, whereas microtexture of cell walls suggests the strength-controlling parameters of coke. Pictorial concept followed in the present study is given below:     

Middleware Architecture for Next Generation Heterogeneous Networks

In this paper we present a framework, called Futon, which provides a platform to integrate heterogeneous radio access networks. Futon is a hybrid fibre-radio network that replaces legacy base stations with simple remote antenna units, which are connected to a central unit. As a part of the Futon framework, a generic middleware architecture is discussed in detail, which provides interoperability, cooperative management and service provisioning to both underlying radio access networks (RANs) and IP layer for a heterogeneous network scenario. One of the middleware??s functionality is to provide vertical handover between heterogeneous IP-based radio access technologies and to ensure seamless mobility and service continuity, which is implemented on top of an IPv4/IPv6 Mobile IP (MIP) core. In this paper, the Futon framework and a generic middleware architecture as a part of Futon framework for heterogeneous RANs is discussed. The main modules of the middleware, namely common radio resource management (CRRM), media independent handover, Service/Connection Manager and link selection are explained in detail. Radio over fibre (RoF) Manager is an important part of Central unit, which does performance, fault and security management of network elements. RoF manager helps middleware during handoff, by providing the status of fibre optic links. The implementation of Security management module as a part of RoF manager, and results of authentication with AAA protocol are explained. The CRRM as part of middleware is simulated and the results of experimental evaluation are presented.     

Implementation of AES Key Schedule Using Look-Ahead Technique

The commencement of decryption process of Advanced Encryption Standard (AES) algorithm is dependent on availability of the last round key. In this paper, we propose a look-ahead technique for increasing the speed of implementation of AES key schedule using which the last round key can be made available fast. The other round keys can also be computed in a parallel path using the proposed technique. Applications such as key search engines need to be agile to key changes for decrypting given encrypted messages using all the keys in the available key space so that fast decryption is possible. The FPGA implementation results using Xilinx XC5VLX85 are also provided.     

Random Mobility and Heterogeneity-Aware Hybrid Synchronization for Wireless Sensor Network

Random mobility of a node in wireless sensor networks (WSNs) causes the frequent changes in the network dynamics with increased cost in terms of energy and bandwidth. During data collections and transmission, they need the additional efforts to synchronize and schedule the activities of nodes. A key challenge is to maintain the global clock scale for synchronization of nodes at different levels to minimize the energy consumption and clock skew. It is also difficult to schedule the activities for effective utilization of slots allocated for aggregated data transmission. The paper proposes the Random Mobility and Heterogeneity-aware Hybrid Synchronization Algorithm (MHS) for WSN. The proposed algorithm uses the cluster-tree for efficient synchronization of CH and nodes in the cluster and network, level-by-level. The network consists of three nodes with random mobility and are heterogeneous regarding energy with static sink. All the nodes and CH are synchronized with the notion of the global timescale provided by the sink as a root node. With the random mobility of the node, the network structure frequently changes causing an increase in energy consumption. To mitigate this problem, MHS aggregate data with the notion of a global timescale throughout the network. Also, the hierarchical structure along with pair-wise synchronization reduces the clock skews hence energy consumption. In the second phase of MHS, the aggregated data packets are passed through the scheduled and synchronized slots using TDMA as basic MAC layer protocol to reduce the collision of packets. The results are extended by using the hybrid approach of scheduling and synchronization algorithm on the base protocol. The comparative results show that MHS is energy and bandwidth efficient, with increased throughput and reduced delay as compared with state-of-the-art solutions.     

A novel route for the synthesis of indium nanoparticles in ionic liquid

In this paper, we report a novel preparation of indium nanoparticles by the reduction of indium chloride in ionic liquid by methanolic solution of NaBH₄. The particles are characterized by means of transmission electron microscopy (TEM), X-ray diffraction and UV-visible studies indicated that the powder consist of the cubic phase of indium. The particle size of indium nanoparticles is in the range of 20 nm mean diameter by Transmission electron microscopy (TEM). The samples display a strong surface plasma absorption band at 231 nm, which indicates that the sample is metal indium and the particle size is less than 20 nm. The thermal analysis of the sample indicate indium not indium oxide. Electrochemical studies show that indium nanoparticles have very good electrical properties.     

Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges

Cardiovascular diseases (CVDs) in India and globally are the major cause of mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace of heartbeats, called cardiac arrhythmias or heart arrhythmias, are one of the commonly diagnosed CVDs caused by ischemic heart disease, hypertension, alcohol intake, and stressful lifestyle. Other than the listed CVDs, the abnormality in the cardiac rhythm caused by the long term mental stress (stimulated by Autonomic Nervous System (ANS)) is a challenging issue for researchers. Early detection of cardiac arrhythmias through automatic electronic techniques is an important research field since the invention of electrocardiogram (ECG or EKG) and advanced machine learning algorithms. ECG (EKG) provides the record of variations in electrical activity associated with the cardiac cycle, used by cardiologists and researchers as a gold standard to study the heart function. The present work is aimed to provide an extensive survey of work done by researchers in the area of automated ECG analysis and classification of regular & irregular classes of heartbeats by conventional and modern artificial intelligence (AI) methods. The artificial intelligence (AI) based methods have emerged popularly during the last decade for the automatic and early diagnosis of clinical symptoms of arrhythmias. In this work, the literature is explored for the last two decades to review the performance of AI and other computer-based techniques to analyze the ECG signals for the prediction of cardiac (heart rhythm) disorders. The existing ECG feature extraction techniques and machine learning (ML) methods used for ECG signal analysis and classification are compared using the performance metrics like specificity, sensitivity, accuracy, positive predictivity value, etc. Some popular AI methods, which include, artificial neural networks (ANN), Fuzzy logic systems, and other machine learning algorithms (support vector machines (SVM), k-nearest neighbor (KNN), etc.) are considered in this review work for the applications of cardiac arrhythmia classification. The popular ECG databases available publicly to evaluate the classification accuracy of the classifier are also mentioned. The aim is to provide the reader, the prerequisites, the methods used in the last two decades, and the systematic approach, all at one place to further purse a research work in the area of cardiovascular abnormalities detection using the ECG signal. As a contribution to the current work, future challenges for real-time remote ECG acquisition and analysis using the emerging technologies like wireless body sensor network (WBSN) and the internet of things (IoT) are identified.

     

Dynamic height anomaly from Argo profiles and sea-level anomaly from satellite altimetry: a comparative study in the Indian Ocean

Altimeter-derived sea-level anomaly (SLA) has been compared with Argo-derived dynamic height anomaly (DHA) in the Indian Ocean. The anomalies have been found to agree quite well in the region above 10°S. The agreement is improved when climatological salinity is replaced by Argo salinity. Seasonal variation of correlation of DHA computed with Argo salinity and SLA has also been studied. The reasons for the poor correlation could be attributed to the fact that there is a barotropic (non-steric) component of the SLA, not captured by DHA, which is a purely steric effect. It has been also found that the impact of halosteric component on dynamic height is quite high in certain regions of the Arabian Sea because of (i) low-salinity water of southern region advected into the region by Somali and North Equatorial Current, (ii) upwelled water of low salinity during south-west monsoon along the Arabian coast and (iii) precipitation and river run-off from rivers in the eastern Arabian sea contributing to the local formation of low-salinity water. In the Bay of Bengal, the factors responsible for the large impact of halosteric component are precipitation and river influx in the northern part. In the south-eastern Indian Ocean, Indonesian Throughflow is the governing factor for this impact.     

Evaluation of enzymatic and non-enzymatic softening in low salt cucumber fermentations

Retention of a firm, crisp fruit texture is a major consideration for pickled vegetables including pickles made from fermented cucumbers. It is known that cucumbers soften rapidly when fermented at low salt concentrations (<0.5 M) without added calcium. This study has shown that there is non-enzymatic softening in low salt fermentations because cucumbers soften even when heated sufficiently to inactivate pectinesterase and several glycosidases that can hydrolyse glycosidic linkages that are present in cell wall polysaccharides. Though pectinesterase activity declines and these glycosidases lose activity within the first week of fermentation there is generally greater loss of cucumber tissue firmness when enzymes are not inactivated by heat. While heating cucumbers prior to fermentation reduces softening during subsequent storage, a heat treatment after 2 weeks of fermentation does not reduce softening. This result suggested that the enzymatic reactions responsible for softening occur early in the fermentation process even though the softening does not become evident until later in the storage period. Despite the evidence of an enzymatic component of tissue softening in low salt cucumbers, softening could not be associated with specific enzymes.