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Background The gender disparity in the thyroid cancer incidence rate, which is 3-folds higher in women than in men, has been hypothesized to be related to estrogen and estrogens receptors (ERs). Recent evidence suggests that nuclear receptor-interacting protein 1 (NRIP1) is known as a coregulator of ERs and a direct target of microRNA-346 (miR-346), which was reported as a biomarker for follicular thyroid carcinoma (FTC). In this study, we investigated the roles of miR-346 on behavioral traits and estrogen-associated pathogenesis of FTCs. Methods Two Human follicular thyroid carcinomas (FTC-133 and RO82-W-1) were used. To examine the effects of miR-346 and estrogen on behavioral traits and estrogen-associated pathogenesis of FTCs, FTC-133 and RO82-W-1 were transfected with the inhibitor targeting human miR-346 or the non-specific miR (-Control), then were treated with 100nM or 200nM of estradiol-17 β (E2). Cell migration and invasion assays were performed; gene and protein levels of NRIP1, ERα, and ERβ were examined by qPCR and western blot, respectively. In addition, cell cycle-regulating genes, epithelial biomarkers, mesenchymal biomarkers were also examined. Results E2 decreased the number of invaded and migrated cells regardless of miR-346-downregulation in both FTCs. Downregulation of miR-346 itself also had protective effects on invasion and migration of both FTCs, and it augmented the inhibitory effects of E2. E2 decreased both gene and protein levels of NRIP1 in FTC-133 while miR-346 downregulation did in RO82-W-1. E2 and miR-346 downregulation decreased the gene and protein expressions of ERα while it increased ERβ, accordingly, decreasing the ratio of ERα to ERβ in both FTCs. E2 significantly decreased cellular proliferation in miR-346 downregulated FTCs. These support that miR-346 has significant roles in estrogen-associated pathogenesis of FTCs by regulating NRIP1 and the interaction of ERα and ERβ. Downregulation of miR-346 increased gene expressions of occluding and cloudin-1 (CLDN1) while decreasing vimentin in FTC-133, it significantly increased gene expressions of CLDN1 in RO82-W-1. These suggest miR-346 in involved in maintaining integrity of FTCs. Conclusion Inhibition of miR-346 in FTCs have protective effects on metastasis, thereby, miR-346 is suggested as a therapeutic target for FTC.

Unsteady load calculations for a large wind turbine using two blade element momentum (BEM) codes (FAST, HAWC2) are compared with results from blade resolved computational fluid dynamics simulations (FLOWer). This is to assess the performance of BEM under varying turbulence levels. Instantaneous and mean of power, spectral data and sectional blade forces are analysed for the three codes. The AVATAR research turbine with a radius of 102.88 m is used in this study. Based on comparisons, FLOWer and HAWC2 show a very close trend in mean power variations with different turbulence intensities. In contrast, FAST does not show a similar trend. This is conjectured to be due to different implementation in the BEM codes of the unsteady turbulence inflows, such as azimuthal variation of induction and dynamic inflow. The maximum error of C P is 6 % for FAST and 1 % for HAWC2 compared to FLOWer.

Understanding the energy efficiency of direct contact membrane distillation (DCMD) is important for the widespread application and practical implementation of the process. This study analyzed the available energy, known as exergy, in a DCMD system using computational fluid dynamics (CFD). A CFD model was developed to investigate the hydrodynamic and thermal conditions in a DCMD module. After the CFD model was verified, it was used to calculate the temperature polarization coefficient (TPC) and exergy destruction magnitudes under various operating conditions. The results revealed that slight decreases and increases in the TPC occurred with distance from the inlet in the module. The TPC was found to increase as the feed temperature was reduced and the feed and permeate flow rates were increased. The exergy destruction phenomenon was more significant under higher feed temperatures and higher flux conditions. Although the most significant exergy destruction in the permeate occurred near the feed inlet, the effect became less influential closer to the feed outlet. An analysis of exergy flows revealed that the efficiency loss in the permeate side corresponded to 32.9–45.3% of total exergy destruction.

Many important big data use cases do not require data to be instantly available. Examples are video recordings in TV and film industry, surveillance videos and data from scientific experiments. Archiving such data to high-latency media storage, such as tape and optical disk libraries, results in significant cost savings. In this context, data is accessed by first staging it to low-latency media. However, archiving and staging operations incur additional device and bandwidth costs for both the active and archiving tiers, and might impact user data access performance. For instance, in terms of cost and performance, it is often suboptimal to archive all the data. This paper presents ExaPlan Archive, a scheme to determine the data placement and number of devices required in each tier of a multitiered storage system comprised of archival and active tiers that minimize the latency of the active tiers under budget and staging-time constraints. The efficiency of the proposed optimized archiving scheme is compared with an existing scheme that optimizes multitier storage with only direct-access tiers. The two schemes are evaluated using a staging workload of LOFAR radio telescopes long-term archive for astronomical observation data.

In many wind engineering applications such as wake developments in a wind farm, dynamic loads on bridges and pollutant dispersions in urban streets, a RANS/LES hybrid turbulence model is a good compromise between fidelity of solutions and computational costs. When such a model is used with non-oscillatory schemes, an extra caution is needed, especially, where the modelled contribution of turbulence is small and thus it is comparable with numerical dissipations, i.e. LES branch. To quantify effects of an explicit SGS model on solutions using a non-oscillatory scheme, decaying homogeneous isotropic turbulence is simulated with and without an SGS model (explicit and implicit LES respectively) on coarse, medium and fine meshes. All statistical results, such as a decay rate of the turbulence kinetic energy, energy spectra and probability density functions, show that the contribution of the explicit SGS model is small, and thus it does not modify the statistical solutions. For further analysis, the effective numerical viscosity ν eff is calculated, and it is one order of the magnitude higher than the SGS viscosity ν t except with the finest mesh. At the end, some practical guidelines are drawn for the current method as a generation of inflow turbulence in wind engineering applications.

Membrane distillation (MD), which uses hydrophobic porous membranes with a temperature gradient to produce pure water, has the potential to treat high-salinity wastewater. However, it cannot directly treat wastewater containing surfactants, which lower the surface tension and thus result in membrane wetting. To overcome this limitation, this study proposed a hybrid process consisting of powdered activated carbon (PAC) adsorption and MD, where PAC removes the surfactants in the wastewater to alleviate the wetting of the MD membranes. A bench-scale vacuum-assisted air gap MD (V-AGMD) equipment was adopted for the treatment of synthetic wastewater containing inorganic salts and surfactants. The conductivity of the permeate from V-AGMD was continuously monitored to detect membrane wetting. Without the use of PAC, the MD membrane was wetted within a short period, which decreased as the surfactant concentration increased. On the other hand, the addition of PAC retards the onset of wetting even at higher surfactant concentrations. The effectiveness of the PAC addition to the MD system on wetting control was examined under various conditions to elucidate its mechanism.

In multi-tier storage systems with large amounts of data, most of the data is stored on inexpensive slower tiers such as cloud or tape to achieve cost savings. This also implies that retrieving the data from the slower storage tiers incurs high latency. Therefore, it would be beneficial to proactively prefetch data from slower tiers to faster tiers by predicting future data accesses. State-of-the-art access prediction methods typically record access history of individual files, data objects, or data segments. However, in systems with large amounts of infrequently accessed (or cold) data, file-level access history is often unavailable for much of the data due to the low frequency of access. In this paper, we extract information from file metadata to predict file accesses in a storage system. The proposed method relies on the hypothesis that users and applications access data stored in the system in a given context and that the context and, therefore, the set of files that are likely to be accessed can be identified by detecting access patterns in file metadata. As an application, we consider the LOFAR radio telescope's long term archive, where the access patterns are learned based on a rich set of metadata, and these patterns are then used to make predictions as to likely future accesses by the astronomers.

Synthetic turbulence for inflow conditions formulated on a 2-D plane generally produces unphysically large pressure fluctuations in direct numerical and large-eddy simulations. To reduce such artificial fluctuations a divergencefree method is developed with incompressible flow solvers. The procedure of the velocity-pressure solvers is slightly modified on a vertical plane near (rather than at) the inlet by inserting the synthetic turbulence on that plane during the procedure. Simple analytic and numerical error estimations are used to show that the impact of the modified solvers on solution accuracy is small. The final synthetic turbulence satisfies the divergence-free condition. No additional CPU time is required to achieve this condition. The method was tested via simulations of a plane channel flow with Re_tau = 395. Reynolds stresses, wall skin friction and power spectra of velocity fluctuations are compared with those obtained from using periodic inlet-outlet boundary conditions. In particular, the variances and power spectra of pressure fluctuations are shown to be accurately predicted only when the divergence-free inlet condition is used.

Parallel processing is a way to use resources efficiently by processing several jobs simultaneously on different servers. In a well-controlled environment where the status of the servers and the jobs are well known, everything is nearly deterministic and replicating jobs on different servers is obviously a waste of resources. However, in a poorly controlled environment where the servers are unreliable and/or their capacity is highly variable, it is desirable to design a system that is robust in the sense that it is not affected by the poorly performing servers. By replicating jobs and assigning them to several different servers simultaneously, we not only achieve robustness but we can also make the system more efficient under certain conditions so that the jobs are processed at a faster rate overall. In this paper we consider the option of replicating jobs and study how the performance of different ‘degrees’ of replication, ranging from no replication to full replication, affects the performance of a system of parallel servers.

Multi-tiered storage, where each tier comprises one type of storage device, e.g., SSD, HDD, is a commonly used approach to achieve both high performance and cost efficiency in large-scale systems that need to store data with vastly different access characteristics. By aligning the access characteristics of the data to the characteristics of the storage devices, higher performance can be achieved for any given cost. This article presents ExaPlan, a method to determine both the data-to-tier assignment and the number of devices in each tier that minimize the system's mean response time for a given budget and workload. In contrast to other methods that constrain or minimize the system load, ExaPlan directly minimizes the system's mean response time estimated by a queueing model. Minimizing the mean response time is typically intractable as the resulting optimization problem is both non-convex and combinatorial in nature. ExaPlan circumvents this intractability by introducing a parameterized data-placement approach that makes it a highly scalable method that can be easily applied to exascale systems. Through experiments that use parameters from real-world storage systems, such as CERN and LOFAR, it is demonstrated that ExaPlan provides solutions that yield lower mean response times than previous works. It is also capable of determining a data-to-tier assignment both at the level of files and at the level of fixed-size extents. For some of the workloads evaluated, file-level placement exhibited a significant performance improvement over extent-level placement.

Representing turbulence by a small number of quantities, such as intensity and length scale, for example, is appropriate and efficient in many engineering situations. Resolving most of or even all turbulent motion by means of Large-Eddy Simulation (LES) or Direct Numerical Simulation (DNS), respectively, provides much more information but is computationally very demanding. Recent years have witnessed an ever-increasing availability of computer power so that the approach can now be applied by many researchers. Indeed, a minimum number of operations, determined by the grid size and the required time steps, needs to be executed to obtain sound separation of length and timescales between the smallest and the largest resolved ones. During recent years, the required performance threshold is met by more and more computer systems. Also, discretization methods and solution algorithms have improved as a result of decades of scientific activities in this field. As a consequence, meaningful DNS and LES can now be performed for more and more applications. For the same reason, a central issue of LES, subgrid-scale modelling, has become less critical today as the grid scales are further away from the resolved scales than before. Still, these methods present lots of pitfalls, and a cost-effective simulation requires optimal models. Much work has been done on improving discretization schemes, subgrid-scale models and other model contributions such as generation of in flow turbulence. On this basis, the development and application of these methods and models continues to be a very active field of research. More and more data sets from DNS nowadays provide detailed and accurate reference for improved understanding and development of physical models.

Wind turbines operate in the atmospheric boundary layer and their rotating mechanisms provide complicated aerodynamic phenomena within their operating environments. When the upstream wind is uniform and normal to the plane of a rotating blade, rotational effects (i.e. rotational augmentation) emerge. Rotational augmentation means that stall occurs at a higher angle of attack on the rotating blade section than it does on an analogous stationary airfoil.

The present studies are addressed to gain more insights into the inflow turbulence effect on rotational augmentation using computational fluid dynamics. Three different cases were simulated and analysed focusing on the three-dimensional effects in the inboard blade region of a 10 MW generic wind turbine rotor. The evidence of rotational augmentation was presented and compared to two-dimensional simulations of the blade sections at consistent inflow conditions. Inflow turbulence has a very strong impact on the instantaneous blade loads and standard deviations, but the effect on the mean values is small. The amplitudes of the blade load fluctuations are amplified under turbulent inflow conditions and these are related to the blade passing frequency and the specified turbulence length scale at the inlet. Detailed examinations of these phenomena were performed and are presented in the present manuscript.

International audience; E-science is moving from grids to clouds. Getting the best of both worlds needs to build on the experience gained by the steady operation of production grids since some years. With the Grid Observatory initiative, trace data are publicly available to the computer science and engineering community and can be used for dimensioning and optimizing infrastructure. This paper proposes a new approach for analyzing behavioral traces: as most of them are indeed text documents, state of the art techniques in text mining, and specifically Latent Dirichlet Allocation, can be exploited. The advantages are twofold: providing some level of explanation inferred from the data; and a relatively scalable way to capture the temporal variability of the behavior of interest, while retaining the full dimensionality of the problem at hand. We experiment the text mining analogy approach by characterizing file access behavior. We validate the resulting probabilistic model by showing that it is capable of generating synthetic traces statistically consistent with the real ones.