Non-destructive evaluation of porosity and its effect on mechanical properties of carbon fiber reinforced polymer composite materials

Structural adhesive bonding is widely used to execute assemblies in automobile and aerospace structures. The quality and reliability of these bonded joints must be ensured during service. In this context non destructive evaluation of these bonded structures play an important role. Evaluation of adhesively bonded composite single lap shear joints has been attempted through experimental approach. Series of tests, non-destructive as well as destructive were performed on different sets of carbon fiber reinforced polymer (CFRP) composite lap joint specimens with varied bond quality. Details of the experimental investigations carried out and the outcome are presented in this paper.

AdFT: An Adaptive Framework for Fault Tolerance on Large Scale Systems using Application Malleability

Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. Malleable applications, where the number of processors on which the applications execute can be changed during executions, can make use of their malleability to better tolerate high failure rates. We present AdFT, an adaptive fault tolerance framework for long running malleable applications to maximize application performance in the presence of failures. AdFT framework includes cost models for evaluating the benefits of various fault tolerance actions including checkpointing, live-migration and rescheduling, and runtime decisions for dynamically selecting the fault tolerance actions at different points of application execution to maximize performance. Simulations with real and synthetic failure traces show that our approach outperforms existing fault tolerance mechanisms for malleable applications yielding up to 23% improvement in application performance, and is effective even for petascale systems and beyond.

Mechanism design for time critical and cost critical task execution via crowdsourcing

An exciting application of crowdsourcing is to use social networks in complex task execution. In this paper, we address the problem of a planner who needs to incentivize agents within a network in order to seek their help in executing an atomic task as well as in recruiting other agents to execute the task. We study this mechanism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner's goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We identify a set of desirable properties that should ideally be satisfied by a crowdsourcing mechanism. In particular, sybil-proofness and collapse-proofness are two complementary properties in our desiderata. We prove that no mechanism can satisfy all the desirable properties simultaneously. This leads us naturally to explore approximate versions of the critical properties. We focus our attention on approximate sybil-proofness and our exploration leads to a parametrized family of payment mechanisms which satisfy collapse-proofness. We characterize the approximate versions of the desirable properties in cost critical and time critical domain.

Threats and trade-fffs in resource critical crowdsourcing tasks over networks

In recent times, crowdsourcing over social networks has emerged as an active tool for complex task execution. In this paper, we address the problem faced by a planner to incen-tivize agents in the network to execute a task and also help in recruiting other agents for this purpose. We study this mecha-nism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner’s goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We define a set of fairness properties that should beideally satisfied by a crowdsourcing mechanism. We prove that no mechanism can satisfy all these properties simultane-ously. We relax some of these properties and define their ap-proximate counterparts. Under appropriate approximate fair-ness criteria, we obtain a non-trivial family of payment mech-anisms. Moreover, we provide precise characterizations of cost critical and time critical mechanisms.

A divide and conquer strategy for scaling weather simulations with multiple regions of interest

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Reconciling transactional conflicts with compiler's help

Software transactional memory(STM) is a promising programming paradigm for shared memory multithreaded programs. While STM offers the promise of being less error-prone and more programmer friendly compared to traditional lock-based synchronization, it also needs to be competitive in performance in order for it to be adopted in mainstream software. A major source of performance overheads in STM is transactional aborts. Conflict resolution and aborting a transaction typically happens at the transaction level which has the advantage that it is automatic and application agnostic. However it has a substantial disadvantage in that STM declares the entire transaction as conflicting and hence aborts it and re-executes it fully, instead of partially re-executing only those part(s) of the transaction, which have been affected due to the conflict. This "Re-execute Everything" approach has a significant adverse impact on STM performance. In order to mitigate the abort overheads, we propose a compiler aided Selective Reconciliation STM (SR-STM) scheme, wherein certain transactional conflicts can be reconciled by performing partial re-execution of the transaction. Ours is a selective hybrid approach which uses compiler analysis to identify those data accesses which are legal and profitable candidates for reconciliation and applies partial re-execution only to these candidates selectively while other conflicting data accesses are handled by the default STM approach of abort and full re-execution. We describe the compiler analysis and code transformations required for supporting selective reconciliation. We find that SR-STM is effective in reducing the transactional abort overheads by improving the performance for a set of five STAMP benchmarks by 12.58% on an average and up to 22.34%.

Co-evolution of specific amino acid in sigma 1.2 region and nucleotide base in the discriminator to act as sensors of small molecule effectors of transcription initiation in mycobacteria

The transcription from rrn and a number of other promoters is regulated by initiating ribonucleotides (iNTPs) and guanosine tetra/penta phosphate (p)ppGpp], either by strengthening or by weakening of the RNA polymerase (RNAP)-promoter interactions during initiation. Studies in Escherichia coli revealed the importance of a sequence termed discriminator, located between -10 and the transcription start site of the responsive promoters in this mode of regulation. Instability of the open complex at these promoters is attributed to the lack of stabilizing interactions between the suboptimal discriminator and the 1.2 region of sigma 70 (Sig70) in RNAP holoenzyme. We demonstrate a different pattern of interaction between the promoters and sigma A (SigA) of Mycobacterium tuberculosis to execute similar regulation. Instead of cytosine and methionine, thymine at three nucleotides downstream to -10 element and leucine 232 in SigA are found to be essential for iNTPs and pppGpp mediated response at the rrn and gyr promoters of the organism. The specificity of the interaction is substantiated by mutational replacements, either in the discriminator or in SigA, which abolish the nucleotide mediated regulation in vitro or in vivo. Specific yet distinct bases and the amino acids appear to have co-evolved' to retain the discriminator-sigma 1.2 region regulatory switch operated by iNTPs/pppGpp during the transcription initiation in different bacteria.

Analysis of composite single lap joints using numerical and experimental approach

Adhesives are widely used to execute the assembly of aerospace and automotive structures due to their ability to join dissimilar materials, reduced stress concentration, and improved fatigue resistance. The mechanical behavior of adhesive joints can be studied either using analytical models or by conducting mechanical tests. However, the complexity owing to multiple interfaces, layers with different properties, material and geometric nonlinearity and its three-dimensional nature combine to increase the difficulty in obtaining an overall system of governing equations to predict the joint behavior. On the other hand, experiments are often time consuming and expensive due to a number of parameters involved. Finite element analysis (FEA) is profoundly used in recent years to overcome these limitations. The work presented in this paper involves the finite element modeling and analysis of a composite single lap joint where the adhesive-adherend interface region was modeled using connector elements. The computed stresses were compared with the experimental stresses obtained using digital image correlation technique. The results showed an agreement. Further, the failure load predicted using FEA was found to be closer to the actual failure load obtained by mechanical tests.

Robust Reentry Guidance of a Reusable Launch Vehicle Using Model Predictive Static Programming

A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

An Implementation of Partitioned Scheduling Scheme for Hard Real-Time Tasks in Multicore Linux with Fair Share for Linux Tasks

The correctness of a hard real-time system depends its ability to meet all its deadlines. Existing real-time systems use either a pure real-time scheduler or a real-time scheduler embedded as a real-time scheduling class in the scheduler of an operating system (OS). Existing implementations of schedulers in multicore systems that support real-time and non-real-time tasks, permit the execution of non-real-time tasks in all the cores with priorities lower than those of real-time tasks, but interrupts and softirqs associated with these non-real-time tasks can execute in any core with priorities higher than those of real-time tasks. As a result, the execution overhead of real-time tasks is quite large in these systems, which, in turn, affects their runtime. In order that the hard real-time tasks can be executed in such systems with minimal interference from other Linux tasks, we propose, in this paper, an integrated scheduler architecture, called SchedISA, which aims to considerably reduce the execution overhead of real-time tasks in these systems. In order to test the efficacy of the proposed scheduler, we implemented partitioned earliest deadline first (P-EDF) scheduling algorithm in SchedISA on Linux kernel, version 3.8, and conducted experiments on Intel core i7 processor with eight logical cores. We compared the execution overhead of real-time tasks in the above implementation of SchedISA with that in SCHED_DEADLINE's P-EDF implementation, which concurrently executes real-time and non-real-time tasks in Linux OS in all the cores. The experimental results show that the execution overhead of real-time tasks in the above implementation of SchedISA is considerably less than that in SCHED_DEADLINE. We believe that, with further refinement of SchedISA, the execution overhead of real-time tasks in SchedISA can be reduced to a predictable maximum, making it suitable for scheduling hard real-time tasks without affecting the CPU share of Linux tasks.

Characterization of rice small heat shock proteins targeted to different cellular organelles

Small heat shock proteins (sHSPs) are a family of ATP-independent molecular chaperones which prevent cellular protein aggregation by binding to misfolded proteins. sHSPs form large oligomers that undergo drastic rearrangement/dissociation in order to execute their chaperone activity in protecting substrates from stress. Substrate-binding sites on sHSPs have been predominantly mapped on their intrinsically disordered N-terminal arms. This region is highly variable in sequence and length across species, and has been implicated in both oligomer formation and in mediating chaperone activity. Here, we present our results on the functional and structural characterization of five sHSPs in rice, each differing in their subcellular localisation, viz., cytoplasm, nucleus, chloroplast, mitochondria and peroxisome. We performed activity assays and dynamic light scattering studies to highlight differences in the chaperone activity and quaternary assembly of sHSPs targeted to various organelles. By cloning constructs that differ in the length and sequence of the tag in the N-terminal region, we have probed the sensitivity of sHSP oligomer assembly and chaperone activity to the length and amino acid composition of the N-terminus. In particular, we have shown that the incorporation of an N-terminal tag has significant consequences on sHSP quaternary structure.

Taming Control Divergence in GPUs through Control Flow Linearization

Branch divergence is a very commonly occurring performance problem in GPGPU in which the execution of diverging branches is serialized to execute only one control flow path at a time. Existing hardware mechanism to reconverge threads using a stack causes duplicate execution of code for unstructured control flow graphs. Also the stack mechanism cannot effectively utilize the available parallelism among diverging branches. Further, the amount of nested divergence allowed is also limited by depth of the branch divergence stack. In this paper we propose a simple and elegant transformation to handle all of the above mentioned problems. The transformation converts an unstructured CFG to a structured CFG without duplicating user code. It incurs only a linear increase in the number of basic blocks and also the number of instructions. Our solution linearizes the CFG using a predicate variable. This mechanism reconverges the divergent threads as early as possible. It also reduces the depth of the reconvergence stack. The available parallelism in nested branches can be effectively extracted by scheduling the basic blocks to reduce the effect of stalls due to memory accesses. It can also increase execution efficiency of nested loops with different trip counts for different threads. We implemented the proposed transformation at PTX level using the Ocelot compiler infrastructure. We evaluated the technique using various benchmarks to show that it can be effective in handling the performance problem due to divergence in unstructured CFGs.

Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Characterization of type I interferon pathway during hepatic differentiation of human pluripotent stem cells and hepatitis C virus infection

Pluripotent stem cells are being actively studied as a cell source for regenerating damaged liver. For long-term survival of engrafting cells in the body, not only do the cells have to execute liver-specific function but also withstand the physical strains and invading pathogens. The cellular innate immune system orchestrated by the interferon (IFN) pathway provides the first line of defense against pathogens. The objective of this study is to assess the innate immune function as well as to systematically profile the IFN-induced genes during hepatic differentiation of pluripotent stem cells. To address this objective, we derived endodermal cells (day 5 post-differentiation), hepatoblast (day 15) and hepatocyte-like cells (day 21) from human embryonic stem cells (hESCs). Day 5, 15 and 21 cells were stimulated with IFN-alpha and subjected to IFN pathway analysis. Transcriptome analysis was carried out by RNA sequencing. The results showed that the IFN-alpha treatment activated STAT-JAK pathway in differentiating cells. Transcriptome analysis indicated stage specific expression of classical and non-classical IFN-stimulated genes (ISGs). Subsequent validation confirmed the expression of novel ISGs including RASGRP3, CLMP and TRANK1 by differentiated hepatic cells upon IFN treatment. Hepatitis C virus replication in hESC-derived hepatic cells induced the expression of ISGs - LAMP3, ETV7, RASGRP3, and TRANK1. The hESC-derived hepatic cells contain intact innate system and can recognize invading pathogens. Besides assessing the tissue-specific functions for cell therapy applications, it may also be important to test the innate immune function of engrafting cells to ensure adequate defense against infections and improve graft survival. (C) 2015 The Authors. Published by Elsevier B.V.