STR-960: ELIMINATING ENVIRONMENTAL INFLUENCES IN VIBRATION-BASED DAMAGE DETECTION USING ARMAX RESIDUAL ERROR AND ARTIFICIAL NEURAL NETWORKS

Despite offering a great promise for continuous and automated monitoring of civil infrastructure systems, vibration-based damage detection methods may yield false positives and negatives due to environmental and/or operational effects. This paper presents a method based on ARMAX residual error in conjunction with Artificial Neural Networks (ANNs) to eliminate the environmental effects from damage detection process. A finite element model of a bridge type structure was simulated with different damage scenarios under various temperatures. Damage features obtained from statistical process on ARMAX residual errors were then compared between with and without environmental effects. Artificial neural networks were trained to learn and predict damage features due to temperature change only, by subtracting which the final damage feature was obtained. It is shown that both damage location and damage severity can be accurately identified

The Effect of Country Risk on Foreign Direct Investment: A Dynamic Panel Data Analysis for Developing Countries

Abstract. Issues created by inconsistency make difficult for investors to make healthy decisions. Risks and uncertainty may lead investors to have bad decisions which result in low level of profit from investments. The purpose of this study is to analyze the effect of country risk on the direct foreign investments (FDI). In the study in which annual data between the years of 2002 and 2014 belong to 49 countries are utilized, the relationships between the variables are analyzed through two phase system-GMM dynamic panel method. Three model assumptions are made for the study. According to the assumption results of the first model which focus on the country risk’s effect on the FDI inflows; the decrease in the country risk increases the FDI inflows. The results of second model through which the effects of sub elements of country risk (financial, economic and political risk) on the FDI are analyzed separately show that financial risk does not create statistically meaningful effect while the decrease in economic and political risk affects the FDI inflows in positive means. Finally, according to the results of the third model which focus on the effect of FDI inflows on the country risks; FDI creates a decreasing effect for country risk and indirectly inconsistencies..Keywords.FDI, Developing countries, Country risk, Twostep system-GMM.JEL. C33, C36, E22, F22

Modest Influence of FRET Chromophores on the Properties of Unfolded Proteins

AbstractSingle-molecule Förster resonance energy transfer (FRET) experiments are often used to study the properties of unfolded and intrinsically disordered proteins. Because of their large extinction coefficients and quantum yields, synthetic heteroaromatic chromophores covalently linked to the protein are often used as donor and acceptor fluorophores. A key issue in the interpretation of such experiments is the extent to which the properties of the unfolded chain may be affected by the presence of these chromophores. In this article, we investigate this question using all-atom explicit solvent replica exchange molecular dynamics simulations of three different unfolded or intrinsically disordered proteins. We find that the secondary structure and long-range contacts are largely the same in the presence or absence of the fluorophores, and that the dimensions of the chain with and without chromophores are similar. This suggests that, at least in the cases studied, extrinsic fluorophores have little effect on the structural properties of unfolded or disordered proteins. We also find that the critical FRET orientational factor κ2, has an average value and equilibrium distribution very close to that expected for isotropic orientations, which supports one of the assumptions frequently made when interpreting FRET efficiency in terms of distances

The effect of autumn and spring planting time on seed yield and protein content of chickpea genotypes

The objective of this study was to investigate the effects of autumn and spring plantings on seed yield and quality of chickpea genotypes. Fourteen chickpea genotypes were grown over the consecutive twogrowing seasons in northwest Turkey. The results showed that planting time had significant effects on the investigated traits (P < 0.05). Significant differences for yield were observed between autumn (2050kg ha-1) and spring (1588 kg ha-1) plantings. Line 99 - 59C was the highest yielding genotype both in autumn (2662 kg ha-1) and spring (2000 kg ha-1) plantings. Seed analysis revealed that crude proteincontent in spring planting (23.2%) was higher than in autumn planting (20.5%). The highest protein content (21.1%) was produced by genotype P-2 in autumn planting whereas line 97 - 73C had thehighest content (24.6%) in spring planting. In addition, yield was highly and positively correlated with C/N ratio (r = 0.20**) whereas it was negatively correlated with protein (r = -0.19**). As a result, plantingtime influenced yield, yield components and chemical composition of the genotypes. Autumn planting had advantages for higher seed yield and consequently higher amount of protein per harvested area

Spraying opened sugar beet pulp silage with oregano essential oil helps to sustain quality and stability

This study was conducted to determine the effects of spraying oregano essential oil (OEO) onto sugar beet pulp silage (SBPS) on silage quality and aerobic stability after opening. A factorial experiment with three replicates of three treatments and four time periods was conducted using laboratory-type plastic silos. The treatments were an untreated control, silage sprayed with 10 ml/75 cm2 OEO, and silage sprayed with 20 ml/75 cm2 OEO. The silages were sampled at 0, 72, 120, and 168 hours after spraying. Temperature, L*, a*, and b* colour values, pH, water-soluble carbohydrates, crude nutrient contents, Fleig score, metabolizable energy (ME) value, lactic acid bacteria (LAB), total live bacteria (TLB), yeast, and mould formation were assessed. Spraying OEO onto SBPS did not affect L*, a*, and b* values, pH, water-soluble carbohydrates, and Fleig score values, but decreased temperature. Spraying OEO onto the silage increased organic matter, ether extract, acid detergent fibre, neutral detergent fibre and acid detergent lignin contents without affecting crude protein, crude fibre, nitrogen free extract, and ME contents. Irrespective of treatment, crude protein, ether extract, acid detergent fibre, acid detergent lignin, nitrogen free extract, Fleig score, and ME contents of silages increased with time after spraying. The OEO spraying reduced LAB, TLB, and yeast contents in silages. In conclusion, OEO spraying onto opened SBPS reduced LAB, TLB, and yeast formation and stopped mould growth up to 72 hours without affecting their nutritional properties, suggesting that OEO could be used to ensure the stability of SBPS. Keywords: aerobic stability, mould growth, silage microbiology, nutrients, feeding managemen

Site Saturation Mutagenesis Applications on <i>Candida methylica</i> Formate Dehydrogenase

In NADH regeneration, Candida methylica formate dehydrogenase (cmFDH) is a highly significant enzyme in pharmaceutical industry. In this work, site saturation mutagenesis (SSM) which is a combination of both rational design and directed evolution approaches is applied to alter the coenzyme specificity of NAD+-dependent cmFDH from NAD+ to NADP+ and increase its thermostability. For this aim, two separate libraries are constructed for screening a change in coenzyme specificity and an increase in thermostability. To alter the coenzyme specificity, in the coenzyme binding domain, positions at 195, 196, and 197 are subjected to two rounds of SSM and screening which enabled the identification of two double mutants D195S/Q197T and D195S/Y196L. These mutants increase the overall catalytic efficiency of NAD+ to 5.6×104-fold and 5×104-fold value, respectively. To increase the thermostability of cmFDH, the conserved residue at position 1 in the catalytic domain of cmFDH is subjected to SSM. The thermodynamic and kinetic results suggest that 8 mutations on the first residue can be tolerated. Among all mutants, M1L has the best residual activity after incubation at 60°C with 17%. These studies emphasize that SSM is an efficient method for creating “smarter libraries” for improving the properties of cmFDH

Automated detection of e-scooter helmet use with deep learning

E-scooter riders have an increased crash risk compared to cyclists [1 ]. Hospital data finds increasing numbers of injured e-scooter riders, with head injuries as one of the most common injury types [2]. To decrease this high prevalence of head injuries, the use of e-scooter helmets could present a potential countermeasure [3]. Despite this, studies show a generally low rate of helmet use rates in countries without mandatory helmet use laws [4][5][6]. In countries with mandatory helmet use laws for e-scooter riders, helmet use rates are higher, but generally remain lower than bicycle use rates [7]. As the helmet use rate is a central factor for the safety of e-scooter riders in case of a crash and a key performance indicator in the European Commission's Road Safety Policy Framework 2021-2030 [8], efficient e-Scooter helmet use data collection methods are needed. However, currently, human observers are used to register e-scooter helmet use either in direct roadside observations or in indirect video-based observation, which is time-consuming and costly. In this study, a deep learning-based method for the automated detection of e-scooter helmet use in video data was developed and tested, with the aim to provide an efficient data collection tool for road safety researchers and practitioners