Model Validation for Bridge-Road-Vehicle Dynamic Interaction System

The dynamic response of highway bridges subjected to moving truckloads has been observed to be dependent on (1) dynamic characteristics of the bridge; (2) truck configuration, speed, and lane position on the bridge; and (3) road surface roughness profile of the bridge and its approach. Historically, truckloads were measured to determine the load spectra for girder bridges. However, truckload measurements are either made for a short period of time [for example, weigh-in-motion (WIM) data] or are statistically biased (for example, weigh stations) and cost prohibitive. The objective of this paper is to present results of a 3D computer-based model for the simulation of multiple trucks on girder bridges. The model is based on the grillage approach and is applied to four steel girder bridges tested under normal truck traffic. Actual truckload data collected using a discrete bridge WIM system are used in the model. The data include axle loads, truck gross weight, axle configuration, and statistical data on multiple presence (side by side or following). The results are presented as a function of the static and dynamic stresses in each girder and compared with code provisions for dynamic load factor. The study provides an alternate method for the development of live-load models for bridge design and evaluation.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

Unusual swelling behavior of polymer-clay nanocomposite hydrogels

The swelling behavior and the elastic properties of nanocomposite hydrogels have been investigated. The hydrogels were prepared by free-radical polymerization of the monomers acrylamide (AAm), N,N-dimethylacrylamide (DMA), and N-isopropylacrylamide (NIPA) in aqueous clay suspensions at 21 °C. Laponite with a radius of gyration in distilled water of 20 nm was used as clay particles in the hydrogel preparation. The reactions with AAm monomer were carried out in the presence of the chemical crosslinker N,N′-methylenebis(acrylamide) (BAAm). It was found that the volume of nanocomposite hydrogels immersed in water rapidly increases and attains a maximum value after about one day. Surprisingly, further increase in the swelling time results in the deswelling of the gels until they reach a limiting swelling ratio after about 5 days. This unusual swelling behavior is observable only when the clay concentration in the hydrogel is above the overlap threshold c^∗. Swelling measurements combined with the elasticity tests show that the effective crosslink density first decreases, but then increases with increasing time of swelling of the hydrogels. The results were explained in terms of the rearrangements of the highly entangled polymer chains and clay particles during the gel volume change.     

An experimental evaluation of visual similarity for HDR images

In this paper, we investigate visual similarity for high dynamic range (HDR) images. We collect crowdsourcing data through a web-based experimental interface, in which the participants are asked to choose one of the two candidate images as being more similar to the query image. Triplets forming the query-and-candidates sets are obtained by random sampling from existing HDR data sets. Experimental control factors include choice of tone mapping operator (TMO), choice of distance metric, and choice of image feature. The image features that we experiment with are chosen from the features that are commonly used in the usual low dynamic range setting including features learned via Convolutional Neural Networks. The set of image features also includes combined features where the combination coefficients are estimated using logistic regression. We compute correlations between human judgments and quantitative features to understand how much each feature contributes to visual similarity. Combined features yield nearly 84% agreement with human judgments when applied on tone mapped images. Though we observed that using common features directly on raw or linearly scaled HDR images yield subpar correlation estimates compared to using them on tone mapped HDR images, we did not observe significant effect due to the choice of TMO on the estimates. As an application, we propose an improvement to style-based tone mapping for more correctly imparting desired styles to HDR images with different characteristics.

     

Analysis of defects on BN nano-structures using high-resolution electron microscopy and density-functional calculations

Cubic boron nitride (c-BN) nucleation takes place on hexagonal boron nitride (h-BN) layers growing perpendicular to the substrate surface during thin film synthesis. Studies focused on the nucleation of the cubic phase suggest the possibility that transient phases and/or defects on these h-BN structures have a role in sp3-bonded cubic phase nucleation. In this study, we have investigated the nature, energetics, and structure of several possible defects on BN basal planes, including point defects, 4-, and 5-fold BN rings, that may possibly match the experimentally observed transient phase fine structure. TEM image observations are used to build approximate atomic models for the proposed structures, and DFT calculations are used to relax these structures while minimizing their respective total energies. These optimized atomic geometries are then used to simulate TEM images, which are compared to the experimentally observed structures. Data from DFT calculations and analysis of simulated images from the proposed atomic structures suggest that 4-fold BN rings are more likely to exist on the transient phase possibly leading to c-BN nucleation.     

Estimating crown diameters in urban forests with Unmanned Aerial System-based photogrammetric point clouds

Field measurements are the main source of information when determining stand parameters, which are essential to produce an effective forest management plan. However, conducting terrestrial measurements is neither time- nor cost-efficient in most cases. In recent years, the advent of sophisticated remote sensing technologies has enabled the extraction of accurate and robust information about the physical characteristics of trees. Crown diameter is one of the most important stand parameters that should be measured or estimated. This study proposes a Polynomial Fitting Based (PFB) methodology to estimate crown diameters of urban trees with Unmanned Aerial System (UAS)-based data. Crown diameters estimated with the PFB methodology were compared not only to a reference data but also to those estimated based on five widely used image segmentation algorithms, which were the Mean Shift Segmentation (MSS), Morphological Profiles Based Segmentation (MPBS), Multiresolution Segmentation (MRS), Seeded Region Growing Segmentation (SRGS) and Watershed Segmentation (WS). Quantitative investigations revealed that the PFB approach outperformed the other segmentation-based approaches. The PFB approach estimated the crown diameters with root-mean-square errors (RMSE) ranging from 0.69 m to 0.92 m. The PFB methodology was found to be a practical and robust approach for the estimation of crown diameters, which plays a very significant role in effective forest management.     

Exploiting Narrow Values for Soft Error Tolerance

Soft errors are an important challenge in contemporary microprocessors. Particle hits on the components of a processor are expected to create an increasing number of transient errors with each new microprocessor generation. In this paper we propose simple mechanisms that effectively reduce the vulnerability to soft errors In a processor. Our designs are generally motivated by the fact that many of the produced and consumed values in the processors are narrow and their upper order bits are meaningless. Soft errors canted by any particle strike to these higher order bits can be avoided by simply identifying these narrow values. Alternatively soft errors can be detected or corrected on the narrow values by replicating the vulnerable portion of the value inside the storage space provided for the upper order bits of these operands. We offer a variety of schemes that make use of narrow values and analyze their efficiency in reducing soft error vulnerability of level-1 data cache of the processor     

Cross-Layer Optimized Rate Adaptation and Scheduling for Multiple-User Wireless Video Streaming

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a multi-objective optimization (MOO) framework that aims to serve the user with the least remaining playback time, highest delivered video seconds per transmission slot and maximum video quality. Experiments with the IS-856 (1timesEV-DO) standard numerology and ITU pedestrian A and vehicular B environments show significant improvements over the state-of- the-art wireless schedulers in terms of user QoS, QoS fairness, and the system throughput.     

The effect of soy protein concentrate addition on the physical, chemical, and sensory properties of strawberry flavored ice cream

The effect of soy protein concentrate (0, 1.5, 3, and 4.5%) on the physical, chemical, and sensory properties of strawberry flavored (0, 0.01 and 0.02%) ice cream samples was examined. All samples were analyzed for pH, titratable acidity, total solids, nitrogen, fat, ash, overrun, viscosity, meltdown, Hunter L-, a-, b- values, flavor, body and texture, and appearance. Substituting soy protein concentrate (SPC) in ice cream formula for non-fat dry milk (NFDM) positively influenced the nitrogen content, viscosity values, and melting and appearance properties of the ice cream samples while overrun values and flavor scores were negatively affected. SPC could be incorporated into the ice cream formula in the range of 1.5–3% devoid of significantly diminishing the physical, chemical, and sensory properties.