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.     

A new deep intuitionistic fuzzy time series forecasting method based on long short-term memory

The Journal of Supercomputing - In recent years, deep artificial neural networks can have better forecasting performance than many other artificial neural networks. The long short-term memory...     

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.     

A modified genetic algorithm for forecasting fuzzy time series

Fuzzy time series approaches are used when observations of time series contain uncertainty. Moreover, these approaches do not require the assumptions needed for traditional time series approaches. Generally, fuzzy time series methods consist of three stages, namely, fuzzification, determination of fuzzy relations, and defuzzification. Artificial intelligence algorithms are frequently used in these stages with genetic algorithms being the most popular of these algorithms owing to their rich operators and good performance. However, the mutation operator of a GA may cause some negative results in the solution set. Thus, we propose a modified genetic algorithm to find optimal interval lengths and control the effects of the mutation operator. The results of applying our new approach to real datasets show superior forecasting performance when compared with those obtained by other techniques.     

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.     

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.     

The Training of Pi-Sigma Artificial Neural Networks with Differential Evolution Algorithm for Forecasting

Computational Economics - Looking at the artificial neural networks’ literature, most of the studies started with feedforward artificial neural networks and the training of many feedforward...     

The relation between EA effectiveness and stakeholder satisfaction

Enterprise Architecture (EA) is increasingly being used by large organizations to get a grip on the complexity of their business processes, information systems and technical infrastructure. Although seen as an important instrument to help solve major organizational problems, effectively applying EA seems no easy task. Active participation of EA stakeholders is one of the main critical success factors for EA. This participation depends on the degree in which EA helps stakeholders achieve their individual goals. A highly related topic is effectiveness of EA, the degree in which EA helps to achieve the collective goals of the organization. In this article we present our work regarding EA stakeholder satisfaction and EA effectiveness, and compare these two topics. We found that, regarding EA, the individual goals of stakeholders map quite well onto the collective goals of the organization. In a case study we conducted, we found that the organization is primarily concerned with the final results of EA, while individual stakeholders also worry about the way the architects operate.