bluuebunny/crossref_metadata_2025 huggingface dataset:
Interacting and noninteracting dark energy models in f(R) gravity
Authors: Sharif M. , Nawazish Iqra
Published: March 2018

In this paper, we study cosmic evolution and current expansion via generalized ghost pilgrim dark energy (PDE) model for FRW universe in [Formula: see text] gravity. For this purpose, we consider both interacting and non-interacting forms of dark energy (DE) model and reconstruct [Formula: see text] model using red-shift parameter. In order to analyze the effects of the DE model, we formulate some standard cosmological parameters such as Hubble, effective equation of state (EoS) and statefinder parameters as well as [Formula: see text]–[Formula: see text] plane. We also investigate the stability criteria for both interacting and noninteracting models through the squared speed of sound. It is concluded that the best-fit results are found for the positive curvature parameter in the presence of the noninteracting model. For the interacting model, the cosmic evolution is well explained by closed and open universe models while the flat geometry effectively describes the current cosmos.
Multiscale Analysis of Concrete Damage and Crack Propagation Under High Cycle Loading
Authors: Sun Xiaoxiao , Guo Xiaoming , Guo Li , Wu Baijian , Wang Ying
Published: March 2018

Concrete is a typical multiphase composite material in which the initiation and propagation of cracks under fatigue load are mainly determined by its mesoscopic structure. In this paper, a concrete multiphase mesoscopic model which considers thickness of interfacial transition zone (ITZ) varying with aggregate’s size is established by the integrated scripting method. The model comprehensively contains the stochastic characteristics of concrete mesoscopic structure. According to the fatigue crack propagation characteristics in different stages, a multiscale method is proposed by establishing the interactive mesoscopic and macroscopic models to targetedly analyze the whole process of fatigue crack initiation, propagation and failure of concrete specimen. Based on the technique of cycle block, concurrent simulation of concrete damage and crack propagation under high-cycle fatigue load is realized. The analysis results show that fatigue cracks in concrete mainly born near the ITZ and gradually enter into the cement mortar matrix to formulate the cracks with finite size. These cracks influence each other until the dominant crack appears and insatiably propagates to result in the failure of specimen.
Analysis of Fatigue Crack Growth Rate Data in an Aircraft 7175-T7351 Al-Alloy Generated at Different Accredited Laboratories with Probability Life Assessment Example
Authors: Černý Ivo
Published: March 2018

Estimation of safety and reliability of engineering structures and components containing cracks or crack-like defects is one of the most important application field of fracture mechanics particularly in components, where limited defects can be accepted. Such design philosophy is usually called “damage tolerance”, formerly “safe life”. In such cases, safety and reliability of further operation, residual life assessment and specification of interval of damage development inspections are important issues. Existing exact knowledge on fatigue crack growth (FCG) parameters is an essential condition. Results of FCG measurement in an Al 7175-T7351 alloy of a particularly high homogeneity, carried out as a part of the Proficiency Test Program organized by Exova in France are presented in this work. Results were evaluated in terms of parameters C and m of the Paris dependence in the stable growth region. To pass the test program successfully, a particular attention was paid to improve and verify direct current potential drop (DCPD) method being used for the crack length measurement. In the paper, the results of the FCG measurements generated by different participating laboratories were analyzed. A distinct correlation between C and m values, so called “coupling”, was found and demonstrated. Some paradoxes of the assessment of laboratories were addressed, namely the fact that a laboratory assessed as unacceptable concerning one of the parameters generated much more accurate and useful data than another laboratory with a better assessment. Eventually, the results including their scatter were used to provide an example of probabilistic assessment of a simple beam residual life to show practical actual impacts of the scatter on the life assessment.
The Short-Term Price Impact of Trades is Universal
Authors: Tóth Bence , Eisler Zoltán , Bouchaud Jean-Philippe
Published: March 2018

We analyze a proprietary dataset of trades by a single asset manager, comparing their price impact with that of the trades of the rest of the market. In the context of a linear propagator model, we find no significant difference between the two, suggesting that both the magnitude and time dependence of impact are universal in anonymous, electronic markets. This result is important as optimal execution policies often rely on propagators calibrated on anonymous data. We also find evidence that in the wake of a trade, the order flow of other market participants first adds further copy-cat trades enhancing price impact on very short time scales. The induced order flow then quickly inverts, thereby contributing to impact decay.
Deconstructing the Energy Consumption of the Mobile Page Load
Authors: Cao Yi , Nejati Javad , Wajahat Muhammad , Balasubramanian Aruna , Gandhi Anshul
Published: March 2018

Modeling the energy consumption of applications on mobile devices is an important topic that has received much attention in recent years. However, there has been very little research on modeling the energy consumption of the mobile Web. This is primarily due to the short-lived yet complex page load process that makes it infeasible to rely on coarse-grained resource monitoring for accurate power estimation.

We present RECON, a modeling approach that accurately estimates the energy consumption of any Web page load and deconstructs it into the energy contributions of individual page load activities. Our key intuition is to leverage low-level application semantics in addition to coarse-grained resource utilizations for modeling the page load energy consumption. By exploiting fine-grained information about the individual activities that make up the page load, RECON enables fast and accurate energy estimations without requiring complex models. Experiments across 80 Web pages and under four different optimizations show that RECON can estimate the energy consumption for a Web page load with an average error of less than 7%. Importantly, RECON helps to analyze and explain the energy effects of an optimization on the individual components of Web page loads.
Persistent Spread Measurement for Big Network Data Based on Register Intersection
Authors: Zhou You , Zhou Yian , Chen Min , Chen Shigang
Published: March 2018

Persistent spread measurement is to count the number of distinct elements that persist in each network flow for predefined time periods. It has many practical applications, including detecting long-term stealthy network activities in the background of normal-user activities, such as stealthy DDoS attack, stealthy network scan, or faked network trend, which cannot be detected by traditional flow cardinality measurement. With big network data, one challenge is to measure the persistent spreads of a massive number of flows without incurring too much memory overhead as such measurement may be performed at the line speed by network processors with fast but small on-chip memory. We propose a highly compact Virtual Intersection HyperLogLog (VI-HLL) architecture for this purpose. It achieves far better memory efficiency than the best prior work of V-Bitmap, and in the meantime drastically extends the measurement range. Theoretical analysis and extensive experiments demonstrate that VI-HLL provides good measurement accuracy even in very tight memory space of less than 1 bit per flow.
Exploiting Data Longevity for Enhancing the Lifetime of Flash-based Storage Class Memory
Authors: Choi Wonil , Arjomand Mohammad , Jung Myoungsoo , Kandemir Mahmut
Published: March 2018

Storage-class memory (SCM) combines the benefits of a solid-state memory, such as high-performance and robustness, with the archival capabilities and low cost of conventional hard-disk magnetic storage. Among candidate solid-state nonvolatile memory technologies that could potentially be used to construct SCM, flash memory is a well-established technology and have been widely used in commercially available SCM incarnations. Flash-based SCM enables much better tradeoffs between performance, space and power than disk-based systems. However, write endurance is a significant challenge for a flash-based SCM (each act of writing a bit may slightly damage a cell, so one flash cell can be written 10^4-10^5 times, depending on the flash technology, before it becomes unusable). This is a well-documented problem and has received a lot of attention by manufactures that are using some combination of write reduction and wear-leveling techniques for achieving longer lifetime. In an effort to improve flash lifetime, first, by quantifying data longevity in an SCM, we show that a majority of the data stored in a solid-state SCM do not require long retention times provided by flash memory (i.e., up to 10 years in modern devices); second, by exploiting retention time relaxation, we propose a novel mechanism, called Dense-SLC (D-SLC), which enables us perform multiple writes into a cell during each erase cycle for lifetime extension; and finally, we discuss the required changes in the flash management software (FTL) in order to use D-SLC mechanism for extending the lifetime of the solid-state part of an SCM. Using an extensive simulation-based analysis of an SLC flash-based SCM, we demonstrate that D-SLC is able to significantly improve device lifetime (between 5.1X and 8.6X) with no performance overhead and also very small changes at the FTL software.
Tomographic Node Placement Strategies and the Impact of the Routing Model
Authors: Pignolet Yvonne-Anne , Schmid Stefan , Tredan Gilles
Published: March 2018

Fault-tolerant computer networks rely on mechanisms supporting the fast detection of link failures. Tomographic techniques can be used to implement such mechanisms at low cost: it is often sufficient to deploy a small number of tomography nodes exchanging probe messages along paths between them and detect link failures based on these messages. Our paper studies a practically relevant aspect of network tomography: the impact of the routing model.

While the relevance of the routing model on path diversity and hence tomography cost is obvious and well-known on an anecdotal level, we lack an analytical framework to quantify the influence of different routing models (such as destination-based routing) exists. This paper fills this gap and introduces a formal model for asymmetric network tomography and a taxonomy of path routing models. This facilitates algorithmic reasoning about tomographic placement problems and quantifying the difference between routing models. In particular, we provide optimal and near-optimal algorithms to deploy a minimal number of asymmetric and symmetric tomography nodes for basic network topologies (modelled as graphs) under different routing model classes. Interestingly, we find that in many cases routing according to a more restrictive routing model gives better results: compared to a more general routing model, computing a good placement is algorithmically more tractable and does not entail high monitoring costs, a desirable trade-off in practice.
Pictures in Your Mind
Authors: Reichinger Andreas , Carrizosa Helena Garcia , Wood Joanna , Schröder Svenja , Löw Christian , Luidolt Laura Rosalia , Schimkowitsch Maria , Fuhrmann Anton , Maierhofer Stefan , Purgathofer Werner
Published: March 2018

Tactile reliefs offer many benefits over the more classic raised line drawings or tactile diagrams, as depth, 3D shape, and surface textures are directly perceivable. Although often created for blind and visually impaired (BVI) people, a wider range of people may benefit from such multimodal material. However, some reliefs are still difficult to understand without proper guidance or accompanying verbal descriptions, hindering autonomous exploration.

In this work, we present a gesture-controlled interactive audio guide (IAG) based on recent low-cost depth cameras that can be operated directly with the hands on relief surfaces during tactile exploration. The interactively explorable, location-dependent verbal and captioned descriptions promise rapid tactile accessibility to 2.5D spatial information in a home or education setting, to online resources, or as a kiosk installation at public places.

We present a working prototype, discuss design decisions, and present the results of two evaluation studies: the first with 13 BVI test users and the second follow-up study with 14 test users across a wide range of people with differences and difficulties associated with perception, memory, cognition, and communication. The participant-led research method of this latter study prompted new, significant and innovative developments.
SynchroTrace
Authors: Sangaiah Karthik , Lui Michael , Jagtap Radhika , Diestelhorst Stephan , Nilakantan Siddharth , More Ankit , Taskin Baris , Hempstead Mark
Published: March 2018

Trace-driven simulation of chip multiprocessor (CMP) systems offers many advantages over execution-driven simulation, such as reducing simulation time and complexity, allowing portability, and scalability. However, trace-based simulation approaches have difficulty capturing and accurately replaying multithreaded traces due to the inherent nondeterminism in the execution of multithreaded programs. In this work, we present SynchroTrace, a scalable, flexible, and accurate trace-based multithreaded simulation methodology. By recording synchronization events relevant to modern threading libraries (e.g., Pthreads and OpenMP) and dependencies in the traces, independent of the host architecture, the methodology is able to accurately model the nondeterminism of multithreaded programs for different hardware platforms and threading paradigms. Through capturing high-level instruction categories, the SynchroTrace average CPI trace Replay timing model offers fast and accurate simulation of many-core in-order CMPs. We perform two case studies to validate the SynchroTrace simulation flow against the gem5 full-system simulator: (1) a constraint-based design space exploration with traditional CMP benchmarks and (2) a thread-scalability study with HPC-representative applications. The results from these case studies show that (1) our trace-based approach with trace filtering has a peak speedup of up to 18.7× over simulation in gem5 full-system with an average of 9.6× speedup, (2) SynchroTrace maintains the thread-scaling accuracy of gem5 and can efficiently scale up to 64 threads, and (3) SynchroTrace can trace in one platform and model any platform in early stages of design.
Improving Energy Efficiency of Coarse-Grain Reconfigurable Arrays Through Modulo Schedule Compression/Decompression
Authors: Lee Hochan , Moghaddam Mansureh S. , Suh Dongkwan , Egger Bernhard
Published: March 2018

Modulo-scheduled course-grain reconfigurable array (CGRA) processors excel at exploiting loop-level parallelism at a high performance per watt ratio. The frequent reconfiguration of the array, however, causes between 25% and 45% of the consumed chip energy to be spent on the instruction memory and fetches therefrom. This article presents a hardware/software codesign methodology for such architectures that is able to reduce both the size required to store the modulo-scheduled loops and the energy consumed by the instruction decode logic. The hardware modifications improve the spatial organization of a CGRA’s execution plan by reorganizing the configuration memory into separate partitions based on a statistical analysis of code. A compiler technique optimizes the generated code in the temporal dimension by minimizing the number of signal changes. The optimizations achieve, on average, a reduction in code size of more than 63% and in energy consumed by the instruction decode logic by 70% for a wide variety of application domains. Decompression of the compressed loops can be performed in hardware with no additional latency, rendering the presented method ideal for low-power CGRAs running at high frequencies. The presented technique is orthogonal to dictionary-based compression schemes and can be combined to achieve a further reduction in code size.
An Empirical Analysis of Amazon EC2 Spot Instance Features Affecting Cost-Effective Resource Procurement
Authors: Wang Cheng , Liang Qianlin , Urgaonkar Bhuvan
Published: March 2018

Many cost-conscious public cloud workloads (“tenants”) are turning to Amazon EC2’s spot instances because, on average, these instances offer significantly lower prices (up to 10 times lower) than on-demand and reserved instances of comparable advertised resource capacities. To use spot instances effectively, a tenant must carefully weigh the lower costs of these instances against their poorer availability. Toward this, we empirically study four features of EC2 spot instance operation that a cost-conscious tenant may find useful to model. Using extensive evaluation based on historical spot instance data, we show shortcomings in the state-of-the-art modeling of these features that we overcome. As an extension to our prior work, we conduct data analysis on a rich dataset of the latest spot price traces collected from a variety of EC2 spot markets. Our analysis reveals many novel properties of spot instance operation, some of which offer predictive value whereas others do not. Using these insights, we design predictors for our features that offer a balance between computational efficiency (allowing for online resource procurement) and cost efficacy. We explore “case studies” wherein we implement prototypes of dynamic spot instance procurement advised by our predictors for two types of workloads. Compared to the state of the art, our approach achieves (i) comparable cost but much better performance (fewer bid failures) for a latency-sensitive in-memory Memcached cache and (ii) an additional 18% cost savings with comparable (if not better than) performance for a delay-tolerant batch workload.
SIMPO
Authors: Zhang Mingzhe , Lam King Tin , Yao Xin , Wang Cho-Li
Published: March 2018

While CPU architectures are incorporating many more cores to meet ever-bigger workloads, advance in fault-tolerance support is indispensable for sustaining system performance under reliability constraints. Emerging non-volatile memory technologies are yielding fast, dense, and energy-efficient NVRAM that can dethrone SSD drives for persisting data. Research on using NVRAM to enable fast in-memory data persistence is ongoing. In this work, we design and implement a persistent object framework, dubbed
scalable in-memory persistent object (SIMPO)
, which exploits NVRAM, alongside DRAM, to support efficient object persistence in highly threaded big data applications. Based on operation logging, we propose a new programming model that classifies functions into instant and deferrable groups. SIMPO features a streamlined execution model, which allows lazy evaluation of deferrable functions and is well suited to big data computing workloads that would see improved data locality and concurrency. Our log recording and checkpointing scheme is effectively optimized towards NVRAM, mitigating its long write latency through write-combining and consolidated flushing techniques. Efficient persistent object management with features including safe references and memory leak prevention is also implemented and tailored to NVRAM. We evaluate a wide range of SIMPO-enabled applications with machine learning, high-performance computing, and database workloads on an emulated hybrid memory architecture and a real hybrid memory machine with NVDIMM. Compared with native applications without persistence, experimental results show that SIMPO incurs less than 5% runtime overhead on both platforms and even gains up to 2.5× speedup and 84% increase in throughput in highly threaded situations on the two platforms, respectively, thanks to the streamlined execution model.
Optimizing Convolutional Neural Networks on the Sunway TaihuLight Supercomputer
Authors: Zhao Wenlai , Fu Haohuan , Fang Jiarui , Zheng Weijie , Gan Lin , Yang Guangwen
Published: March 2018

The Sunway TaihuLight supercomputer is powered by SW26010, a new 260-core processor designed with on-chip fusion of heterogeneous cores. In this article, we present our work on optimizing the training process of convolutional neural networks (CNNs) on the Sunway TaihuLight supercomputer. Specifically, a highly efficient library (swDNN) and a customized Caffe framework (swCaffe) are proposed. Architecture-oriented optimization methods targeting the many-core architecture of SW26010 are introduced and are able to achieve 48× speedup for the convolution routine in swDNN and 4× speedup for the complete training process of the VGG-16 network using swCaffe, compared to the unoptimized algorithm and framework. Compared to the cuDNN library and the Caffe framework based on the NVIDIA K40m GPU, the proposed swDNN library and swCaffe framework on SW26010 have nearly half the performance of K40m in single -precision and have 3.6× and 1.8× speedup over K40m in double precision, respectively.
Enabling SIMT Execution Model on Homogeneous Multi-Core System
Authors: Chen Kuan-Chung , Chen Chung-Ho
Published: March 2018

Single-instruction multiple-thread (SIMT) machine emerges as a primary computing device in high-perfor-mance computing, since the SIMT execution paradigm can exploit data-level parallelism effectively. This article explores the SIMT execution potential on homogeneous multi-core processors, which generally run in multiple-instruction multiple-data (MIMD) mode when utilizing the multi-core resources. We address three architecture issues in enabling SIMT execution model on multi-core processor, including multithreading execution model, kernel thread context placement, and thread divergence. For the SIMT execution model, we propose a fine-grained multithreading mechanism on an ARM-based multi-core system. Each of the processor cores stores the kernel thread contexts in its L1 data cache for per-cycle thread-switching requirement. For divergence-intensive kernels, an Inner Conditional Statement First (ICS-First) mechanism helps early re-convergence to occur and significantly improves the performance. The experiment results show that effectiveness in data-parallel processing reduces on average 36% dynamic instructions, and boosts the SIMT executions to achieve on average 1.52× and up to 5× speedups over the MIMD counterpart for OpenCL benchmarks for single issue in-order processor cores. By using the explicit vectorization optimization on the kernels, the SIMT model gains further benefits from the SIMD extension and achieves 1.71× speedup over the MIMD approach. The SIMT model using in-order superscalar processor cores outperforms the MIMD model that uses superscalar out-of-order processor cores by 40%. The results show that, to exploit data-level parallelism, enabling the SIMT model on homogeneous multi-core processors is important.
Visual Program Manipulation in the Polyhedral Model
Authors: Zinenko Oleksandr , Huot Stéphane , Bastoul Cédric
Published: March 2018

Parallelism is one of the key performance sources in modern computer systems. When heuristics-based automatic parallelization fails to improve performance, a cumbersome and error-prone manual transformation is often required. As a solution, we propose an interactive visual approach building on the polyhedral model that visualizes exact dependencies and parallelism; decomposes and replays a complex automatically computed transformation step by step; and allows for directly manipulating the visual representation as a means of transforming the program with immediate feedback. User studies suggest that our visualization is understood by experts and nonexperts alike, and that it may favor an exploratory approach.
Improving Parallelism in Hardware Transactional Memory
Authors: Dice Dave , Herlihy Maurice , Kogan Alex
Published: March 2018

Today’s hardware transactional memory (HTM) systems rely on existing coherence protocols, which implement a requester-wins strategy. This, in turn, leads to poor performance when transactions frequently conflict, causing them to resort to a non-speculative fallback path. Often, such a path severely limits parallelism. In this article, we propose very simple architectural changes to the existing requester-wins HTM implementations that enhance conflict resolution between hardware transactions and thus improve their parallelism. Our idea is compatible with existing HTM systems, requires no changes to target applications that employ traditional lock synchronization, and is shown to provide robust performance benefits.
Energy-Performance Considerations for Data Offloading to FPGA-Based Accelerators Over PCIe
Authors: Mbakoyiannis Dimitrios , Tomoutzoglou Othon , Kornaros George
Published: March 2018

Modern data centers increasingly employ FPGA-based heterogeneous acceleration platforms as a result of their great potential for continued performance and energy efficiency. Today, FPGAs provide more hardware parallelism than is possible with GPUs or CPUs, whereas C-like programming environments facilitate shorter development time, even close to software cycles. In this work, we address limitations and overheads in access and transfer of data to accelerators over common CPU-accelerator interconnects such as PCIe. We present three different FPGA accelerator dispatching methods for streaming applications (e.g., multimedia, vision computing). The first uses zero-copy data transfers and on-chip scratchpad memory (SPM) for energy efficiency, and the second uses also zero-copy but shared copy engines among different accelerator instances and local external memory. The third uses the processor’s memory management unit to acquire the physical address of user pages and uses scatter-gather data transfers with SPM. Even though all techniques exhibit advantages in terms of scalability and relieve the processor from control overheads through using integrated schedulers, the first method presents the best energy-efficient acceleration in streaming applications.
GeoMF++
Authors: Lian Defu , Zheng Kai , Ge Yong , Cao Longbing , Chen Enhong , Xie Xing
Published: March 2018

Location recommendation is an important means to help people discover attractive locations. However, extreme sparsity of user-location matrices leads to a severe challenge, so it is necessary to take implicit feedback characteristics of user mobility data into account and leverage the location’s spatial information. To this end, based on previously developed GeoMF, we propose a scalable and flexible framework, dubbed GeoMF++, for joint geographical modeling and implicit feedback-based matrix factorization. We then develop an efficient optimization algorithm for parameter learning, which scales linearly with data size and the total number of neighbor grids of all locations. GeoMF++ can be well explained from two perspectives. First, it subsumes two-dimensional kernel density estimation so that it captures spatial clustering phenomenon in user mobility data; Second, it is strongly connected with widely used neighbor additive models, graph Laplacian regularized models, and collective matrix factorization. Finally, we extensively evaluate GeoMF++ on two large-scale LBSN datasets. The experimental results show that GeoMF++ consistently outperforms the state-of-the-art and other competing baselines on both datasets in terms of NDCG and Recall. Besides, the efficiency studies show that GeoMF++ is much more scalable with the increase of data size and the dimension of latent space.
Creating Thermal Icons—A Model-Based Approach
Authors: Singhal Anshul , Jones Lynette A.
Published: March 2018

The objective of this set of experiments was to evaluate thermal pattern recognition on the hand and arm and to determine which features of thermal stimuli are encoded by cutaneous thermoreceptors and perceived by the user of a thermal display. Thermal icons were created by varying the direction, rate, and magnitude of change in temperature. It was found that thermal icons were identified more accurately when presented on the thenar eminence or the wrist, as compared to the fingertips and that thermal patterns as brief as 8s could be reliably identified. In these experiments, there was no difference in performance when identifying warm or cool stimuli. A dynamic model of the change in skin temperature as a function of the thermal input was developed based on linear system identification techniques. This model was able to predict the change in skin temperature from an unrelated experiment involving thermal icons. This opens the possibility of using a model-based approach to the development of thermal icons.
Dynamic Merging of Frontiers for Accelerating the Evaluation of Betweenness Centrality
Authors: Vella Flavio , Bernaschi Massimo , Carbone Giancarlo
Published: March 2018

Betweenness Centrality (BC) is a widely used metric of the relevance of a node in a network. The fastest-known algorithm for the evaluation of BC on unweighted graphs builds a tree representing information about the shortest paths for each vertex to calculate its contribution to the BC score. Actually, for specific vertices, the shortest-path trees of neighboring nodes could be leveraged to reduce the computational burden, but existing BC algorithms do not exploit that information and carry out redundant computations. We propose a new algorithm, called dynamic merging of frontiers, which makes use of such information to derive the BC score of degree-2 vertices by re-using the results of the sub-trees of the neighbors. We implemented our idea in parallel fashion exploiting Graphics Processing Units. Compared to state-of-the-art implementations, our approach achieves a linear improvement in the number of degree-2 vertices and an average improvement of × over a variety of real-world graphs.
Single- to Few-Layered, Graphene-Based Separation Membranes
Authors: Zhou Fanglei , Fathizadeh Mahdi , Yu Miao
Published: March 2018

Two-dimensional, graphene-based materials have attracted great attention as a new membrane building block, primarily owing to their potential to make the thinnest possible membranes and thus provide the highest permeance for effective sieving, assuming comparable porosity to conventional membranes and uniform molecular-sized pores. However, a great challenge exists to fabricate large-area, single-layered graphene or graphene oxide (GO) membranes that have negligible undesired transport pathways, such as grain boundaries, tears, and cracks. Therefore, model systems, such as a single flake or nanochannels between graphene or GO flakes, have been studied via both simulations and experiments to explore the transport mechanisms and separation potential of graphene-based membranes. This article critically reviews literature related to single- to few-layered graphene and GO membranes, from material synthesis and characteristics, fundamental membrane structures, and transport mechanisms to potential separation applications. Knowledge gaps between science and engineering in this new field and future opportunities for practical separation applications are also discussed.
Design Considerations for Artificial Water Channel–Based Membranes
Authors: Song Woochul , Lang Chao , Shen Yue-xiao , Kumar Manish
Published: March 2018

Aquaporins (AQPs) are naturally occurring water channel proteins. They can facilitate water molecule translocation across cellular membranes with exceptional selectivity and high permeability that are unmatched in synthetic membrane systems. These unique properties of AQPs have led to their use as functional elements in membranes in recent years. However, the intricate nature of AQPs and concerns regarding their stability and processability have encouraged researchers to develop synthetic channels that mimic the structure and properties of AQPs and other biological water-conducting channels. These channels have been termed artificial water channels. This article reviews current progress and provides a historical perspective as well as an outlook toward developing scalable membranes based on artificial water channels.
Targeted disruption of regulated endocrine-specific protein (Resp18) in Dahl SS/Mcw rats aggravates salt-induced hypertension and renal injury
Authors: Kumarasamy Sivarajan , Waghulde Harshal , Cheng Xi , Haller Steven T. , Mell Blair , Abhijith Basrur , Ashraf Usman M. , Atari Ealla , Joe Bina
Published: March 2018

Hypertension is a classic example of a complex polygenic trait, impacted by quantitative trait loci (QTL) containing candidate genes thought to be responsible for blood pressure (BP) control in mammals. One such mapped locus is on rat chromosome 9, wherein the proof for a positional candidate gene, regulated endocrine-specific protein-18 ( Resp18) is currently inadequate. To ascertain the status of Resp18 as a BP QTL, a custom targeted gene disruption model of Resp18 was developed on the Dahl salt-sensitive (SS) background. As a result of this zinc-finger nuclease (ZFN)-mediated disruption, a 7 bp deletion occurred within exon 3 of the Resp18 locus. Targeted disruption of Resp18 gene locus in SS rats decreases its gene expression in both heart and kidney tissues regardless of their dietary salt level. Under a high-salt dietary regimen, both systolic and diastolic BP of Resp18mutantrats were significantly increased compared with SS rats. Resp18mutantrats demonstrated increased renal damage, as evidenced by higher proteinuria and increased renal fibrosis compared with SS rats. Furthermore, under a high-salt diet regimen, the mean survival time of Resp18mutantrats was significantly reduced compared with SS rats. These findings serve as evidence in support of Resp18 as a gene associated with the development of hypertension and renal disease.
Transcriptome-seq provides insights into sex-preference pattern of gene expression between testis and ovary of the crucifix crab (Charybdis feriatus)
Authors: Zhang Yin , Miao Guidong , Fazhan Hanafiah , Waiho Khor , Zheng Huaiping , Li Shengkang , Ikhwanuddin Mhd , Ma Hongyu
Published: March 2018

The crucifix crab, Charybdis feriatus, which mainly inhabits Indo-Pacific region, is regarded as one of the most high-potential species for domestication and incorporation into the aquaculture sector. However, the regulatory mechanisms of sex determination and differentiation of this species remain unclear. To identify candidate genes involved in sex determination and differentiation, high throughput sequencing of transcriptome from the testis and ovary of C. feriatus was performed by the Illumina platform. After removing adaptor primers, low-quality sequences and very short (<50 nt) reads, we obtained 80.9 million and 66.2 million clean reads from testis and ovary, respectively. A total of 86,433 unigenes were assembled, and ~43% (37,500 unigenes) were successfully annotated to the NR, NT, Swiss-Prot, KEGG, COG, GO databases. By comparing the testis and ovary libraries, we obtained 27,636 differentially expressed genes. Some candidate genes involved in the sex determination and differentiation of C. feriatus were identified, such as vasa, pgds, vgr, hsp90, dsx-f, fem-1, and gpr. In addition, 88,608 simple sequence repeats were obtained, and 61,929 and 77,473 single nucleotide polymorphisms from testis and ovary were detected, respectively. The transcriptome profiling was validated by quantitative real-time PCR in 30 selected genes, which showed a good consistency. The present study is the first high-throughput transcriptome sequencing of C. feriatus. These findings will be useful for future functional analysis of sex-associated genes and molecular marker-assisted selections in C. feriatus.
The MDA-9/Syntenin/IGF1R/STAT3 Axis Directs Prostate Cancer Invasion
Authors: Das Swadesh K. , Pradhan Anjan K. , Bhoopathi Praveen , Talukdar Sarmistha , Shen Xue-Ning , Sarkar Devanand , Emdad Luni , Fisher Paul B.
Published: March 2018

Although prostate cancer is clinically manageable during several stages of progression, survival is severely compromised once cells invade and metastasize to distant organs. Comprehending the pathobiology of invasion is required for developing efficacious targeted therapies against metastasis. Based on bioinformatics data, we predicted an association of melanoma differentiation-associated gene-9 [syntenin, or syndecan binding protein (SDCBP)] in prostate cancer progression. Using tissue samples from various Gleason stage prostate cancer patients with adjacent normal tissue, a series of normal prostate and prostate cancer cell lines (with differing tumorigenic/metastatic properties), mda-9/syntenin-manipulated variants (including loss-of-function and gain-of-function cell lines), and CRISPR/Cas9 stable MDA-9/Syntenin knockout cells, we now confirm the relevance of and dependence on MDA-9/syntenin in prostate cancer invasion. MDA-9/Syntenin physically interacted with insulin-like growth factor-1 receptor following treatment with insulin-like growth factor binding protein-2 (IGFBP2), regulating downstream signaling processes that enabled STAT3 phosphorylation. This activation enhanced expression of MMP2 and MMP9, two established enzymes that positively regulate invasion. In addition, MDA-9/syntenin-mediated upregulation of proangiogenic factors including IGFBP2, IL6, IL8, and VEGFA also facilitated migration of prostate cancer cells. Collectively, our results draw attention to MDA-9/Syntenin as a positive regulator of prostate cancer metastasis, and the potential application of targeting this molecule to inhibit invasion and metastasis in prostate cancer and potentially other cancers.

Significance: This study provides new mechanistic insight into the proinvasive role of MDA-9/Syntenin in prostate cancer and has potential for therapeutic application to prevent prostate cancer metastasis. Cancer Res; 78(11); 2852–63. ©2018 AACR.
Therapeutic Targeting of Sunitinib-Induced AR Phosphorylation in Renal Cell Carcinoma
Authors: Adelaiye-Ogala Remi , Damayanti Nur P. , Orillion Ashley R. , Arisa Sreevani , Chintala Sreenivasulu , Titus Mark A. , Kao Chinghai , Pili Roberto
Published: March 2018

Androgen receptor (AR) plays a crucial role in the development and progression of prostate cancer. AR expression has also been reported in other solid tumors, including renal cell carcinoma (RCC), but its biological role here remains unclear. Through integrative analysis of a reverse phase protein array, we discovered increased expression of AR in an RCC patient–derived xenograft model of acquired resistance to the receptor tyrosine kinase inhibitor (RTKi) sunitinib. AR expression was increased in RCC cell lines with either acquired or intrinsic sunitinib resistance in vitro. An AR signaling gene array profiler indicated elevated levels of AR target genes in sunitinib-resistant cells. Sunitinib-induced AR transcriptional activity was associated with increased phosphorylation of serine 81 (pS81) on AR. Additionally, AR overexpression resulted in acquired sunitinib resistance and the AR antagonist enzalutamide-induced AR degradation and attenuated AR downstream activity in sunitinib-resistant cells, also indicated by decreased secretion of human kallikrein 2. Enzalutamide-induced AR degradation was rescued by either proteasome inhibition or by knockdown of the AR ubiquitin ligase speckle-type POZ protein (SPOP). In vivo treatment with enzalutamide and sunitinib demonstrated that this combination efficiently induced tumor regression in a RCC model following acquired sunitinib resistance. Overall, our results suggest the potential role of AR as a target for therapeutic interventions, in combination with RTKi, to overcome drug resistance in RCC.

Significance: These findings highlight the therapeutic potential of targeting the androgen receptor to overcome RCC resistance to receptor tyrosine kinase inhibitors. Cancer Res; 78(11); 2886–96. ©2018 AACR.
Distance from Home to Research Center: A Barrier to In-Person Visits but Not Treatment Adherence in a Stroke Trial
Authors: Leira Enrique C. , Viscoli Catherine M. , Polgreen Linnea A. , Gorman Mark , Kernan Walter N. ,   on behalf of the IRIS Trial Investigators
Published: March 2018

Background and Purpose: Clinical trials often seek to enroll patients from both urban and rural areas to safeguard the generalizability of results. However, maintaining contact with patients who live away from a recruitment site, including rural areas, can be challenging. In this research we examine the effect of distance between patient and study centers on treatment adherence and retention. Methods: Secondary analysis of 2,466 participants in the Insulin Resistance Intervention after Stroke trial who were enrolled from research sites in the United States. Driving distance between the zipcodes of patient’s reported place of residence and the study center was calculated. Outcome measures were loss to follow-up, completion of annual in-person visits, adherence to preventive therapy, and adherence to study drug in the first 3 years of participation. Logistic regression models were used to adjust for confounders. Results: Distance from residence to research center was not associated with loss to follow-up, adherence to study drug, or adherence to preventive therapy (p > 0.05 for each). However, patients who lived farther from the research center (>120 miles), compared to patients who lived closer (<60 miles), were less likely to complete the second annual in-person visit (62 vs. 81%; adjusted OR 0.48; 95% CI 0.31–0.75) and third visit (53 vs. 75%; adjusted OR 0.44; 95% CI 0.29–0.67). Conclusions: Distance between patient and study center was an independent predictor of missed in-person visits but not with adherence to study treatment or preventive care.
Proteomic Analysis of Dacryoliths from Patients with or without Topical Rebamipide Treatment
Authors: Mano Fukutaro , Takimoto Hiroki , Oe Masako , Chang Kuo-chung , Mano Tomiya , Yoshida Yutaka
Published: March 2018

Background: A dacryolith mainly contains organic material, but its specific protein content is unknown. We observed a unique dacryolith formation in patients with long-term use of rebamipide eye drops and tried to identify the differences in protein compositions of dacryoliths from patients with or without use of rebamipide eye drops using novel proteomic analysis. Methods: Dacryolith samples were obtained from 7 patients (4 samples were without rebamipide usage, 3 were with rebamipide usage) who underwent endo-dacryocystorhinostomy or lacrimal endoscopic surgery and were subjected to protein identification and metaproteomic analysis. Results: The proteomic analysis revealed that most core proteins of dacryoliths are involved in immune and inflammatory responses and rebamipide-related proteins participated in several biological processes, including immune response, receptor-mediated endocytosis, and negative regulation of endopeptidase activity. Metaproteomic analysis of taxonomic diversity of dacryolith proteomes suggested less involvement of bacterial infections in dacryoliths from patients with long-term use of rebamipide. Conclusion: This is the first report to clinically detect the different features of dacryoliths related with long-term use of rebamipide eye drops with proteomic analysis. It is possible that lacrimal protein alteration may be accelerated by topical rebamipide treatment with less bacterial infection involvement, but this requires further study. Long-term rebamipide eye drop use may be restricted in patients with nasolacrimal duct obstruction.
Electrical Stimulation Enhances Migratory Ability of Transplanted Bone Marrow Stromal Cells in a Rodent Ischemic Stroke Model
Authors: Morimoto Jun , Yasuhara Takao , Kameda Masahiro , Umakoshi Michiari , Kin Ittetsu , Kuwahara Ken , Kin Kyohei , Okazaki Mihoko , Takeuchi Hayato , Sasaki Tatsuya , Toyoshima Atsuhiko , Tajiri Naoki , Agari Takashi , Borlongan Cesario V. , Date Isao
Published: March 2018

Background/Aims: Bone marrow stromal cells (BMSCs) transplantation is an important strategy for the treatment of ischemic stroke. Currently, there are no effective methods to guide BMSCs toward the targeted site. In this study, we investigated the effect of electrical stimulation on BMSCs migration in an ischemic model of rats. Methods: Adult male Wistar rats weighing 200 to 250 g received right middle cerebral artery occlusion (MCAO) for 90 minutes. BMSCs (2.5×105 cells/ 4 µl PBS) were stereotaxically injected into the left corpus callosum at 1 day after MCAO. After BMSCs injection, a plate electrode with a diameter of 3 mm connected to an implantable electrical stimulator was placed on the right frontal epidural space and a counter electrode was placed in the extra-cranial space. Electrical stimulation at preset current (100 µA) and frequency (100 Hz) was performed for two weeks. Behavioral tests were performed at 1, 4, 8, and 15 days after MCAO using the modified Neurological Severity Score (mNSS) and cylinder test. Rats were euthanized at 15 days after MCAO for evaluation of infarction area and the migration distance and area of BMSCs found in the brain tissue. After evaluating cell migration, we proceeded to explore the mechanisms guiding these observations. MCAO rats without BMSCs transplantation were stimulated with same current and frequency. At 1 and 2 weeks after MCAO, rats were euthanized to evaluate stromal cell-derived factor 1 alpha (SDF-1α) level of brain tissues in the bilateral cortex and striatum. Results: Behavioral tests at 4, 8, and 15 days after MCAO revealed that stimulation group displayed significant amelioration in mNSS and cylinder test compared to control group (p<0.05). Similarly, the infarction areas of stroke rats in stimulation group were significantly decreased compared to control group (p<0.05). Migration distance and area of transplanted BMSCs were significantly longer and wider respectively in stimulation group. An increased concentration gradient of SDF-1α in stimulation group accompanied this enhanced migration of transplanted cells. Conclusions: These results suggest that electrical stimulation enhances migratory ability of transplanted BMSCs in ischemic stroke model of rats. If we can direct the implanted BMSCs to the site of interest, it may lead to a greater therapeutic effect.