C. N. R. Rao and the Growth of Solid State and Materials Chemistry as a Central Domain of Research

In celebrating Professor C. N. R. Rao's 80th birthday, this article recalls his singular contributions to solid state and materials chemistry for about sixty years. In so doing, the article also traces the growth of the field as a central domain of research in chemical sciences from its early origins in Europe. Although Rao's major work lies in solid state and materials chemistry - a field which he started and nurtured in India while its importance was being recognized internationally - his contributions to other areas of chemistry (and physics), viz., molecular spectroscopy, phase transitions, fullerenes, graphene, nanomaterials and multiferroics are equally significant. Illustrative examples of his work devoted to rare earth and transition metal oxides, defects and nonstoichiometry, metal-insulator transitions, investigation of crystal and electronic structures of a variety of solids by means of electron microscopies and photoelectron spectroscopy, superconducting cuprates, magnetoresistive manganites, multiferroic metal oxides of various structures and, last but not the least, development of new strategies for chemical synthesis of a wide variety of solids including nanomaterials and framework solids in different dimensionalities, are highlighted. The article also captures his exemplary role as a science teacher, science educationist and institution builder in post-Independence India.

Race Detection for Android Applications

Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings coupled with non-deterministic reorderings of asynchronous tasks can lead to subtle concurrency errors in the applications. In this paper, we formalize the concurrency semantics of the Android programming model. We further define the happens-before relation for Android applications, and develop a dynamic race detection technique based on this relation. Our relation generalizes the so far independently studied happens-before relations for multi-threaded programs and single-threaded event-driven programs. Additionally, our race detection technique uses a model of the Android runtime environment to reduce false positives. We have implemented a tool called DROIDRACER. It generates execution traces by systematically testing Android applications and detects data races by computing the happens-before relation on the traces. We analyzed 1 5 Android applications including popular applications such as Facebook, Twitter and K-9 Mail. Our results indicate that data races are prevalent in Android applications, and that DROIDRACER is an effective tool to identify data races.

Sheltered coastal environments as archives of paleo-tsunami deposits: Observations from the 2004 Indian Ocean tsunami

The 2004 earthquake left several traces of coseismic land deformation and tsunami deposits, both on the islands along the plate boundary and distant shores of the Indian Ocean rim countries. Researchers are now exploring these sites to develop a chronology of past events. Where the coastal regions are also inundated by storm surges, there is an additional challenge to discriminate between the deposits formed by these two processes. Paleo-tsunami research relies largely on finding deposits where preservation potential is high and storm surge origin can be excluded. During the past decade of our work along the Andaman and Nicobar Islands and the east coast of India, we have observed that the 2004 tsunami deposits are best preserved in lagoons, inland streams and also on elevated terraces. Chronological evidence for older events obtained from such sites is better correlated with those from Thailand, Sri Lanka and Indonesia, reiterating their usefulness in tsunami geology studies. (C) 2014 Elsevier Ltd. All rights reserved.

Trace Driven Dynamic Deadlock Detection and Reproduction

Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

Crystal Structure and Prediction

The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

PriDyn: Enabling Differentiated I/O Services in Cloud Using Dynamic Priorities

Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Origin of room temperature weak-ferromagnetism in antiferromagnetic Pb(Fe2/3W1/3)O-3 ceramic

We report the origin of room temperature weak ferromagnetic behavior of polycrystalline Pb(Fe2/3W1/3)O-3 (PFW) powder. The structure and magnetic properties of the ceramic powder prepared by a Columbite method were characterized by X-ray and neutron diffraction, Mossbauer spectroscopy and magnetization measurements. Rietveld analysis of diffraction data confirm the formation of single phase PFW, without traces of any parasitic pyrochlore phase. PFW was found to crystallize in the cubic structure at room temperature. The Rietveld refinement of neutron diffraction data measured at room temperature confirmed the G-type antiferromagnetic structure of PFW in our sample. However, along with the antiferromagnetic (AFM) ordering of the Fe spins, we have observed the existence of weak ferromagnetism at room temperature through: (i) a clear opening of hysteresis (M-H) loop, (ii) bifurcation of the field cooled and zero-field cooled susceptibility; supported by Mossbauer spectroscopy results. The P-E loop measurements showed a non-linear slim hysteresis loop at room temperature due to the electronic conduction through the local inhomogeneities in the PFW crystallites and the inter-particle regions. By corroborating all the magnetic measurements, especially the spin glass nature of the sample, with the conduction behavior of the sample, we report here that the observed ferromagnetism originates at these local inhomogeneous regions in the sample, where the Fe-spins are not perfectly aligned antiferromagnetically due to the compositional disordering. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Enhancement in Strain Hardening on Boron Addition in As-Cast Ti-6Al-4V Alloy

It has been previously reported that the addition of boron to Ti-6Al-4V results in significant refinement of the as-cast microstructure and enhancement in the strain hardening. However, the mechanism for the latter effect has not been adequately studied. The aim of this study was to understand the reasons for the enhancement in room temperature strain hardening on addition of boron to as cast Ti-6Al-4V alloy. A study was conducted on slip transmission using SEM, TEM, optical profilometry and four point probe resistivity measurements on un-deformed and deformed samples of Ti-6Al-4V-xB with five levels of boron. Optical profilometry was used to quantify the magnitude of offsets on slip traces which in turn provided information about the extent of planar or multiple slip. Studies on deformed samples reveal that while lath boundaries appear to easily permit dislocation slip transmission, colony boundaries are potent barriers to slip. From TEM studies it was also observed that while alloys containing lower boron underwent planar slip, deformation was more homogeneous in higher boron alloys due to multiple slip resulting from large number of colony boundaries. Multiple slip is also proposed to be the prime cause of the enhanced strain hardening.

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

Synthesizing Racy Tests

Subtle concurrency errors in multithreaded libraries that arise because of incorrect or inadequate synchronization are often difficult to pinpoint precisely using only static techniques. On the other hand, the effectiveness of dynamic race detectors is critically dependent on multithreaded test suites whose execution can be used to identify and trigger races. Usually, such multithreaded tests need to invoke a specific combination of methods with objects involved in the invocations being shared appropriately to expose a race. Without a priori knowledge of the race, construction of such tests can be challenging. In this paper, we present a lightweight and scalable technique for synthesizing precisely these kinds of tests. Given a multithreaded library and a sequential test suite, we describe a fully automated analysis that examines sequential execution traces, and produces as its output a concurrent client program that drives shared objects via library method calls to states conducive for triggering a race. Experimental results on a variety of well-tested Java libraries yield 101 synthesized multithreaded tests in less than four minutes. Analyzing the execution of these tests using an off-the-shelf race detector reveals 187 harmful races, including several previously unreported ones.

Probabilistic Prediction based Scheduling for Delay Sensitive Traffic in Internet of Things

This paper proposes a probabilistic prediction based approach for providing Quality of Service (QoS) to delay sensitive traffic for Internet of Things (IoT). A joint packet scheduling and dynamic bandwidth allocation scheme is proposed to provide service differentiation and preferential treatment to delay sensitive traffic. The scheduler focuses on reducing the waiting time of high priority delay sensitive services in the queue and simultaneously keeping the waiting time of other services within tolerable limits. The scheme uses the difference in probability of average queue length of high priority packets at previous cycle and current cycle to determine the probability of average weight required in the current cycle. This offers optimized bandwidth allocation to all the services by avoiding distribution of excess resources for high priority services and yet guaranteeing the services for it. The performance of the algorithm is investigated using MPEG-4 traffic traces under different system loading. The results show the improved performance with respect to waiting time for scheduling high priority packets and simultaneously keeping tolerable limits for waiting time and packet loss for other services. Crown Copyright (C) 2015 Published by Elsevier B.V.

Anodization of Aluminium using a fast two-step process

Ultra-fast two-step anodization method is developed for obtaining ordered nano-pores on aluminium (Al) foil. First anodization was carried out for 10 min, followed by 3 min of second anodization at high voltage (150 V) compared to previous reports of anodization times of 12 h (40-60 V). The pore dimensions on anodized alumina are 180 nm for pore diameter and 130 nm for inter-pore distance. It was evident that by increasing the anodization voltage to 150 V, the diameter of the pores formed was above 150 nm. The electrolyte and its temperature affect the shape and size of the pore formation. At lower anodization temperature, controlled pore formation was observed. The anodized samples were characterized using the field emission scanning electron microscope (FE-SEM) to determine the pore diameter and inter-pore distance. Using UV-Visible spectroscopy, the reflectance spectra of anodized samples were measured. The alumina (Al2O3) peaks were identified by x-ray diffraction (XRD) technique. The x-ray photo electron spectroscopy (XPS) analysis confirmed the Al 2p peak at 73.1 eV along with the oxygen O 1s at 530.9 eV and carbon traces C 1s at 283.6 eV.