Inhibition of Toll-Like Receptor 4 Signaling Mitigates Microvascular Loss but Not Fibrosis in a Model of Ischemic Acute Kidney Injury

The development of chronic kidney disease (CKD) following an episode of acute kidney injury (AKI) is an increasingly recognized clinical problem. Inhibition of toll-like receptor 4 (TLR4) protects renal function in animal models of AKI and has become a viable therapeutic strategy in AKI. However, the impact of TLR4 inhibition on the chronic sequelae of AKI is unknown. Consequently, we examined the chronic effects of TLR4 inhibition in a model of ischemic AKI. Mice with a TLR4-deletion on a C57BL/6 background and wild-type (WT) background control mice (C57BL/6) were subjected to bilateral renal artery clamping for 19 min and reperfusion for up to 6 weeks. Despite the acute protective effect of TLR4 inhibition on renal function (serum creatinine 1.6 ± 0.4 mg/dL TLR4-deletion vs. 2.8 ± 0.3 mg/dL·WT) and rates of tubular apoptosis following ischemic AKI, we found no difference in neutrophil or macrophage infiltration. Furthermore, we observed significant protection from microvascular rarefaction at six weeks following injury with TLR4-deletion, but this did not alter development of fibrosis. In conclusion, we validate the acute protective effect of TLR4 signal inhibition in AKI but demonstrate that this protective effect does not mitigate the sequential fibrogenic response in this model of ischemic AKI.     

A method for coordinating the distributed transmission of imagery.

Distributed imaging using sensor arrays is gaining popularity among various research and development communities. A common bottleneck within such an imaging sensor network is the large resulting data load. In applications for which transmission power and/or bandwidth are constrained, this can drastically decrease the sensor network lifetime. We present an algorithm that efficiently exploits inter- and intrasensor correlation for the purpose of power-constrained distributed transmission of sensor-network imagery. Gains in network lifetime up to 114% are obtained when using the suggested algorithm with lossless compression. Our results also demonstrate that when lossy compression is employed, much larger gains are achieved. For example, when a normalized root-mean-squared error of 0.78% can be tolerated in the received measurements, the network lifetime increases by a factor of 2.8, as compared to the (optimized) lossless case.     

Improving the SVM gender classification accuracy using clustering and incremental learning

Gender recognition has been playing a very important role in various applications such as human–computer interaction, surveillance, and security. Nonlinear support vector machines (SVMs) were investigated for the identification of gender using the Face Recognition Technology (FERET) image face database. It was shown that SVM classifiers outperform the traditional pattern classifiers (linear, quadratic, Fisher linear discriminant, and nearest neighbour). In this context, this paper aims to improve the SVM classification accuracy in the gender classification system and propose new models for a better performance. We have evaluated different SVM learning algorithms; the SVM‐radial basis function with a 5% outlier fraction outperformed other SVM classifiers. We have examined the effectiveness of different feature selection methods. AdaBoost performs better than the other feature selection methods in selecting the most discriminating features. We have proposed two classification methods that focus on training subsets of images among the training images. Method 1 combines the outcome of different classifiers based on different image subsets, whereas method 2 is based on clustering the training data and building a classifier for each cluster. Experimental results showed that both methods have increased the classification accuracy.     

An ordering algorithm for pattern presentation in fuzzy ARTMAP thattends to improve generalization performance

We introduce a procedure, based on the max-min clustering method, that identifies a fixed order of training pattern presentation for fuzzy adaptive resonance theory mapping (ARTMAP). This procedure is referred to as the ordering algorithm, and the combination of this procedure with fuzzy ARTMAP is referred to as ordered fuzzy ARTMAP. Experimental results demonstrate that ordered fuzzy ARTMAP exhibits a generalization performance that is better than the average generalization performance of fuzzy ARTMAP, and in certain cases as good as, or better than the best fuzzy ARTMAP generalization performance. We also calculate the number of operations required by the ordering algorithm and compare it to the number of operations required by the training phase of fuzzy ARTMAP. We show that, under mild assumptions, the number of operations required by the ordering algorithm is a fraction of the number of operations required by fuzzy ARTMAP.     

Design and model confirmation of the intermediate scale VolturnUS floating wind turbine subjected to its extreme design conditions offshore Maine

Floating offshore wind turbines are gaining considerable interest in the renewable energy sector. Design standards for floating offshore wind turbines such as the American Bureau of Shipping (ABS) Guide for Building and Classing Floating Offshore Wind Turbine Installations are relatively new and few if any floating wind turbines have yet experienced the prescribed design extreme environmental conditions. Only a few pilot floating turbines have been deployed in Europe and Japan. These turbines have been designed for long return period storm events and are not likely to see their extreme design conditions during early deployment periods because of the low probability of occurrence. This paper presents data collected for an intermediate scale floating semi‐submersible turbine intentionally placed offshore Maine in a carefully selected site that subjects the prototype to scale extreme conditions on a frequent basis. This prototype, called VolturnUS 1:8, was the first grid‐connected offshore wind turbine in the Americas, and is a 1:8 scale model of a 6 MW prototype. The test site produces with a high probability 1:8 scale wave environments, and a commercial turbine has been selected so that the wind environment/rotor combination produces 1:8‐scale aerodynamic loads appropriate for the site wave environment. In the winter of 2013–2014, this prototype has seen the equivalent of 50 year to 500 year return period storms exercising it to the limits prescribed by design standards, offering a unique look at the behavior of a floating turbine subjected to extreme design conditions. Performance data are provided and compared to full‐scale predicted values from numerical models. There are two objectives in presenting this data and associated analysis: (i) validate numerical aeroelastic hydrodynamic coupled models and (ii) investigate the performance of a near full‐scale floating wind turbine in a real offshore environment that closely matches the prescribed design conditions from the ABS Guide. Copyright © 2015 John Wiley & Sons, Ltd.     

Hydrogen absorption characteristics of mechanically alloyed Ti–Zr–Ni and Ti–V–Ni powders

A first investigation into the production of amorphous and nanostructured Ti-based alloys with nominal compositions Ti_41.5Zr_41.5Ni₁₇, Ti₆₁Zr₂₂Ni₁₇, Ti_41.5V_41.5Ni₁₇ and Ti₆₁V₂₂Ni₁₇ by mechanical alloying (MA) technique is presented. This technique was adopted to produce alloys' powders with high fresh surface area that were active for hydrogen storage. Hydrogen absorption characteristics and structure changes in the alloys after hydrogenation were investigated. Gas phase hydrogenation of the Ti–Zr–Ni alloys, at 573 K and an initial hydrogen pressure of 2 MPa, exhibited good hydriding properties and started at a maximal rate without induction period with a hydrogenation capacity up to 1.2 wt%. However, hydriding of Ti–V–Ni alloys at the same conditions exhibited slower rates. The Ti₆₁V₂₂Ni₁₇ composition showed high hydrogen absorption capacity of 1.8 wt% and exceeded 4 wt% at 345 K. In addition, the Ti–V–Ni alloys showed structure stability after hydrogenation and retained the amorphous structure.     

A power‐area‐efficient, 3‐band, 2‐RX MIMO,TD‐LTE receiver with direct‐coupled ADC

In this work, a power‐area‐efficient, 3‐band, 2‐RX MIMO, and TD‐LTE (backward compatible with the HSPA+, HSUPA, HSDPA, and TD‐SCDMA) CMOS receiver is presented and implemented in 0.13‐μm CMOS technology. The continuous‐time delta‐sigma A/D converters (CT ?Σ ADCs) are directly coupled to the outputs of the transimpedance amplifiers, eliminating the need of analog anti‐aliasing filters between RX front‐end and ADCs in conventional structures. The strong adjacent channel interference without low‐pass filter attenuation is handled by proper gain control. A low‐power small‐area solution for excess loop delay compensation is implemented in the CT ?Σ ADC. At 20 MHz bandwidth, the CT ?Σ ADC achieves 66 dB dynamic range and 3.5 dB RX chip noise figure is measured. A maximum of 2.4 dB signal‐to‐noise ratio degradation is measured in all the adjacent channel selectivity (ACS) and blocking tests, demonstrating the effectiveness of the strategy against the low‐pass filter removal from the conventional architecture. The receiver dissipates a maximum of 171 mW at 2‐RX MIMO mode. To our best knowledge, it is the first research paper on the design of fully integrated commercial TD‐LTE receiver. Copyright © 2014 John Wiley & Sons, Ltd.     

Microfluidic multi-target sorting by magnetic repulsion

In magnetophoresis-based microfluidic systems, the free-flow sorting is achieved by incrementally navigating the magnetic target toward a designated outlet. This is typically enabled using high-gradient magnetic concentrators (HGMCs), axially aligned or slightly slanted with the streaming sample flow. Such axial and incremental magnetic manipulation critically constraints the throughput and the number of targets that can be sorted simultaneously. To overcome these constraints, we present an alternative repulsion-based sorting method. The repulsion force is due that induced, over a limited angular expanse, around a single ferromagnetic wire. The wire is positioned transversally against the focused sample flow. Differentially repelled by the repulsive force, each target deflects from its focused path to follow a ribbon-like trajectory that leads to a spatially addressable outlet. The mediated sorting takes place more rapidly and is confined to the region facing the transversal wire. More importantly, the introduced concept design allows for a throughput that is geometrically scalable with the length of the wire. The functionality of the systems is demonstrated experimentally and numerically to yield the simultaneous and complete multi-target sorting of two and more magnetic beads.     

Complex fuzzy c-means algorithm

In this paper a new clustering algorithm is presented: A complex-based Fuzzy c-means (CFCM) algorithm. While the Fuzzy c-means uses a real vector as a prototype characterizing a cluster, the CFCM??s prototype is generalized to be a complex vector (complex center). CFCM uses a new real distance measure which is derived from a complex one. CFCM??s formulas for the fuzzy membership are derived. These formulas are extended to derive the complex Gustafson?CKessel algorithm (CGK). Cluster validity measures are used to assess the goodness of the partitions obtained by the complex centers compared those obtained by the real centers. The validity measures used in this paper are the Partition Coefficient, Classification Entropy, Partition Index, Separation Index, Xie and Beni??s Index, Dunn??s Index. It is shown in this paper that the CFCM give better partitions of the data than the FCM and the GK algorithms. It is also shown that the CGK algorithm outperforms the CFCM but at the expense of much higher computational complexity.