The physics and technology of gallium antimonide: An emerging optoelectronic material

Recent advances in nonsilica fiber technology have prompted the development of suitable materials for devices operating beyond 1.55 mu m. The III-V ternaries and quaternaries (AlGaIn)(AsSb) lattice matched to GaSb seem to be the obvious choice and have turned out to be promising candidates for high speed electronic and long wavelength photonic devices. Consequently, there has been tremendous upthrust in research activities of GaSb-based systems. As a matter of fact, this compound has proved to be an interesting material for both basic and applied research. At present, GaSb technology is in its infancy and considerable research has to be carried out before it can be employed for large scale device fabrication. This article presents an up to date comprehensive account of research carried out hitherto. It explores in detail the material aspects of GaSb starting from crystal growth in bulk and epitaxial form, post growth material processing to device feasibility. An overview of the lattice, electronic, transport, optical and device related properties is presented. Some of the current areas of research and development have been critically reviewed and their significance for both understanding the basic physics as well as for device applications are addressed. These include the role of defects and impurities on the structural, optical and electrical properties of the material, various techniques employed for surface and bulk defect passivation and their effect on the device characteristics, development of novel device structures, etc. Several avenues where further work is required in order to upgrade this III-V compound for optoelectronic devices are listed. It is concluded that the present day knowledge in this material system is sufficient to understand the basic properties and what should be more vigorously pursued is their implementation for device fabrication. (C) 1997 American Institute of Physics.

Volume modelling for emerging manufacturing technologies

The next generation manufacturing technologies will draw on new developments in geometric modelling. Based on a comprehensive analysis of the desiderata of next generation geometric modellers, we present a critical review of the major modelling paradigms, namely, CSG, B-Rep, non-manifold, and voxel models. We present arguments to support the view that voxel-based modellers have attributes that make it the representation scheme of choice in meeting the emerging requirements of geometric modelling.

Greater Bangalore: Emerging Urban Heat Island

Bangalore is experiencing unprecedented urbanisation and sprawl in recent times due to concentrated developmental activities with impetus on industrialisation for the economic development of the region. This concentrated growth has resulted in the increase in population and consequent pressure on infrastructure, natural resources and ultimately giving rise to a plethora of serious challenges such as climate change, enhanced green-house gases emissions, lack of appropriate infrastructure, traffic congestion, and lack of basic amenities (electricity, water, and sanitation) in many localities, etc. This study shows that there has been a growth of 632% in urban areas of Greater Bangalore across 37 years (1973 to 2009). Urban heat island phenomenon is evident from large number of localities with higher local temperatures. The study unravels the pattern of growth in Greater Bangalore and its implication on local climate (an increase of ~2 to 2.5 ºC during the last decade) and also on the natural resources (76% decline in vegetation cover and 79% decline in water bodies), necessitating appropriate strategies for the sustainable management.

A fast algorithm for finding frequent episodes in event streams

Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the frequency of an episode is some suitable measure of how often the episode occurs in the data sequence. Recently,we proposed a new frequency measure for episodes based on the notion of non-overlapped occurrences of episodes in the event sequence, and showed that, such a definition, in addition to yielding computationally efficient algorithms, has some important theoretical properties in connecting frequent episode discovery with HMM learning. This paper presents some new algorithms for frequent episode discovery under this non-overlapped occurrences-based frequency definition. The algorithms presented here are better (by a factor of N, where N denotes the size of episodes being discovered) in terms of both time and space complexities when compared to existing methods for frequent episode discovery. We show through some simulation experiments, that our algorithms are very efficient. The new algorithms presented here have arguably the least possible orders of spaceand time complexities for the task of frequent episode discovery.

Consumerist Predators"? Emerging lifestyles between McDonaldization and sustainability perspectives: the case of highly qualified employees (HQEs) in India

In industrializing countries new groups of consumers with remarkable purchasing power are emerging. Representing a ?new middle class? they are seen as a carrier and promoter of a so-called ?western way of life? beyond the OECD countries. They are presented as having a consumerist predator lifestyle which stands in conflict with the requirements for a sustainable future. Furthermore, they are imputed a profound lack of a sense of responsibility towards society. However, such a ?civil society spirit? is a core prerequisite for coping with the challenge of changing existing lifestyles to insure a more sustainable future....

Existing and emerging strategies for the synthesis of nanoscale heterostructures

Development of new multifunctional nanostructures relies on the ability to make new materials at the nanoscale with control over size, shape and composition. While this control is extremely important to tune several properties, an alternative strategy is to create active interfaces between two or more nanostructures to form nanoscale heterostructures. In these heterostructures, the interfaces play a key role in stabilizing and enhancing the efficiency of the individual components for various applications. In this article, we discuss synthesis methods of different types of nanoscale heterostructures and the role of interfaces in various applications. We present the current state-of-the-art in designing heterostructures and possible upcoming synthetic strategies with their advantages and disadvantages. We present how such heterostructures are highly efficient for catalytic, photovoltaic and nanoelectronic applications drawing several examples from our own studies and from the literature.

Discovering injective episodes with general partial orders

Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.

Generalized frequent episodes in Event Sequences

Discovering patterns in temporal data is an important task in Data Mining. A successful method for this was proposed by Mannila et al. [1] in 1997. In their framework, mining for temporal patterns in a database of sequences of events is done by discovering the so called frequent episodes. These episodes characterize interesting collections of events occurring relatively close to each other in some partial order. However, in this framework(and in many others for finding patterns in event sequences), the ordering of events in an event sequence is the only allowed temporal information. But there are many applications where the events are not instantaneous; they have time durations. Interesting episodesthat we want to discover may need to contain information regarding event durations etc. In this paper we extend Mannila et al.’s framework to tackle such issues. In our generalized formulation, episodes are defined so that much more temporal information about events can be incorporated into the structure of an episode. This significantly enhances the expressive capability of the rules that can be discovered in the frequent episode framework. We also present algorithms for discovering such generalized frequent episodes.

Draft Genome Sequence of Staphylococcus aureus ST672, an Emerging Disease Clone from India

We report the draft genome sequence of methicillin-resistant Staphylococcus aureus (MRSA) strain ST672, an emerging disease clone in India, from a septicemia patient. The genome size is about 2.82 Mb with 2,485 open reading frames (ORFs). The staphylococcal cassette chromosome mec (SCCmec) element (type V) and immune evasion cluster appear to be different from those of strain ST772 on preliminary examination.

Catalytic Enantioselective Halocyclizations beyond Lactones: Emerging Routes to Enantioenriched Nitrogenous Heterocycles

Electrophilic halogen-induced reactions of unactivated olefins are an important class of transformations, whose catalytic enantioselective variants have surfaced during the past few years as effective means of olefin heterodifunctionalization. This article covers important developments in the area of enantioselective halocyclizations, specifically in the context of the synthesis of nitrogenous heterocycles.

Emerging roles of MCPH1: Expedition from primary microcephaly to cancer

Genetic mutations in microcephalinl (MCPH1) cause primary autosomal recessive microcephaly which is characterized by a marked reduction in brain size. MCPH1 encodes a centrosomal protein with three BRCT (BRCA1 C-terminal) domains. Also, it is a key regulator of DNA repair pathway and cell cycle checkpoints. Interestingly, in the past few years, many research studies have explored the role of MCPH1, a neurodevelopmental gene in several cancers and its tumor suppressor functions have been elucidated. Given the diverse new emerging roles, it becomes critical to review and summarize the multiple roles of MCPH1 that is currently lacking in the literature. In this review after systematic analysis of literature, we summarise the multiple functional roles of MCPH1 in centrosomal, DNA repair and apoptotic pathways. Additionally, we discuss the considerable efforts taken to understand the implications of MCPH1 in diseases such as primary microcephaly and its other emerging association with cancer and otitis media. The promising view is that MCPH1 has distinct roles and its clinical associations in various diseases makes it an attractive therapeutic target. (C) 2014 Elsevier GmbH. All rights reserved.