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.     

Nonenzymic browning during storage of white hard grape pekmez (Zile pekmezi)

Effects of storage period on hydroxymethylfurfural, pH and colour were studied in white hard grape pekmez (Zile pekmezi), a Turkish traditional product. Pekmez samples were stored at 20 °C for 8 months. Analysis of variance revealed significant differences in hydroxymethylfurfural, pH, L, a and b values (P<0.01) based on storage time.     

Charge density dependence of elastic modulus of strong polyelectrolyte hydrogels

The mechanical behavior of a series of strong polyelectrolyte hydrogels based on acrylamide and 2-acrylamido-2-methylpropane sulfonic acid sodium salt (AMPS) was investigated. The hydrogels were prepared at a fixed crosslinker ratio and monomer concentration, but at various charge densities, i.e. AMPS contents between 0 and 100 mol%. The elastic modulus of the hydrogels after their preparation first increases with increasing charge density but then decreases continuously. Investigation of the swollen state properties of the hydrogels shows existence of a large number of ionic groups inside the gel that are ineffective in gel swelling. The results indicate two opposite effects of charged groups on the elastic modulus of the hydrogels: formation of multiplets acting as additional crosslinks in the gel increases the elastic modulus of ionic hydrogels, whereas the effect of the electrostatic interaction of charged groups on elastic free energy decreases the modulus.     

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.

     

Studying high impact fix-inducing changes

As software systems continue to play an important role in our daily lives, their quality is of paramount importance. Therefore, a plethora of prior research has focused on predicting components of software that are defect-prone. One aspect of this research focuses on predicting software changes that are fix-inducing. Although the prior research on fix-inducing changes has many advantages in terms of highly accurate results, it has one main drawback: It gives the same level of impact to all fix-inducing changes. We argue that treating all fix-inducing changes the same is not ideal, since a small typo in a change is easier to address by a developer than a thread synchronization issue. Therefore, in this paper, we study high impact fix-inducing changes (HIFCs). Since the impact of a change can be measured in different ways, we first propose a measure of impact of the fix-inducing changes, which takes into account the implementation work that needs to be done by developers in later (fixing) changes. Our measure of impact for a fix-inducing change uses the amount of churn, the number of files and the number of subsystems modified by developers during an associated fix of the fix-inducing change. We perform our study using six large open source projects to build specialized models that identify HIFCs, determine the best indicators of HIFCs and examine the benefits of prioritizing HIFCs. Using change factors, we are able to predict 56 % to 77 % of HIFCs with an average false alarm (misclassification) rate of 16 %. We find that the lines of code added, the number of developers who worked on a change, and the number of prior modifications on the files modified during a change are the best indicators of HIFCs. Lastly, we observe that a specialized model for HIFCs can provide inspection effort savings of 4 % over the state-of-the-art models. We believe our results would help practitioners prioritize their efforts towards the most impactful fix-inducing changes and save inspection effort.     

Computer-based testing: An alternative for the assessment of Turkish undergraduate students

Virtually errorless high speed data processing feature has made computers popular assessment tools in education. An important concern in developing countries considering integrating computers as an educational assessment tool before making substantial investment is the effects of computer-based testing on students’ test scores as compared to paper-and-pencil tests. This study investigated whether test scores of Turkish students were different in the computer-based test and in the paper-and-pencil test, with forty-seven undergraduate students studying at a public university located in the Blacksea region of Turkey. Findings of this study showed that test scores of undergraduate students were not different in the computer-based test and in the paper-and-pencil test which led us to reach the conclusion that computer-based testing can be considered as a promising alternative technique for the undergraduate students in Turkey.     

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.     

Reducing Dimensionality of Multi-regime Data for Failure Prognostics

Journal of Failure Analysis and Prevention - Over the last decade, the prognostics and health management literature has introduced many conceptual frameworks for remaining useful life predictions....