Deflections of concrete beams reinforced with FRP bars

The aim of this study is to experimentally and theoretically investigate the flexural behavior of concrete beams reinforced with fiber reinforced polymer (FRP) bars. In this research, three types of experiments were made. First, the tensile properties of FRP and steel bars were tested, then the bond-slip behavior between bars and concrete was tested on standard specimens and, in the end, three series of concrete beams reinforced with GFRP, CFRP and steel bars were tested up to failure. The theoretical model for calculating deflections was developed, which included bond-slip behavior of FRP bars. The theoretical results were compared to the test results of beam deflections, as well to deflection results obtained by theoretical models developed by other authors.     

Quantitation of steroid hormones in thin fresh frozen tissue sections

As analytical technologies in proteomics and metabolomics continue to mature, there is an increasing need to apply these to clinically relevant biologic samples. In this study, a liquid chromatography-tandem mass spectrometry method that utilizes selected reaction monitoring was used to measure the absolute quantity of estrogens and estrogen metabolites and testosterone in 8-microm tissue sections obtained from a fresh frozen lymph node tumor infiltrated by metastatic breast carcinoma. Total (conjugated plus unconjugated) and unconjugated levels of these steroid hormones were measured using two cohorts, each containing five adjacent serial sections cut from this tumor. The results were highly reproducible across replicate samples, showing that typical histological tissue sections represent an important sample type for the measurement of these specific metabolites.     

Mitochondrial DNA Fragmentation as a Molecular Tool to Monitor Thermal Processing of Plant‐Derived,Low‐Acid Foods,and Biomaterials

Cycle threshold (Ct) increase, quantifying plant‐derived DNA fragmentation, was evaluated for its utility as a time‐temperature integrator. This novel approach to monitoring thermal processing of fresh, plant‐based foods represents a paradigm shift. Instead of using quantitative polymerase chain reaction (qPCR) to detect pathogens, identify adulterants, or authenticate ingredients, this rapid technique was used to quantify the fragmentation of an intrinsic plant mitochondrial DNA (mtDNA) gene over time‐temperature treatments. Universal primers were developed which amplified a mitochondrial gene common to plants (atp1). These consensus primers produced a robust qPCR signal in 10 vegetables, 6 fruits, 3 types of nuts, and a biofuel precursor. Using sweet potato (Ipomoea batatas) puree as a model low‐acid product and simple linear regression, Ct value was highly correlated to time‐temperature treatment (R² = 0.87); the logarithmic reduction (log CFU/mL) of the spore‐forming Clostridium botulinum surrogate, Geobacillus stearothermophilus (R² = 0.87); and cumulative F‐value (min) in a canned retort process (R² = 0.88), all comparisons conducted at 121 °C. D₁₂₁ and z‐values were determined for G. stearothermophilus ATCC 7953 and were 2.71 min and 11.0 °C, respectively. D₁₂₁ and z‐values for a 174‐bp universal plant amplicon were 11.3 min and 9.17 °C, respectively, for mtDNA from sweet potato puree. We present these data as proof‐of‐concept for a molecular tool that can be used as a rapid, presumptive method for monitoring thermal processing in low‐acid plant products.     

Thermophysical and Dielectric Properties of Salsa Con Queso and its Vegetable Ingredients at Sterilization Temperatures

Aseptic processing of a low-acid multiphase food product using continuous flow microwave heating system can combine the advantages of an aseptic process along with those of microwave heating. The objective of this study was to determine the thermophysical and dielectric properties of salsa con queso and its vegetable ingredients (tomatoes, bell peppers, jalapeno peppers, and onions) at a temperature range of 20 to 130°C to design a safe process for aseptic processing of salsa con queso using a continuous flow microwave system. The influence of temperature on apparent viscosity of salsa con queso was described by an Arrhenius-type relationship. Second order polynomial correlations for the dependence of thermophysical and dielectric properties (at 915 MHz) of salsa con queso and its vegetable ingredients on temperature were developed. The results showed that the dielectric constant decreased with an increase in temperature and the dielectric loss factor increased with an increase in temperature.     

Improved structured light 3D scanner with application to anthropometric parameter estimation

Obtaining accurate anthropometric body segment parameters in a fast and reliable manner is an essential step in biomechanical analysis of human motion. With advance of computer vision, and reduction in cost of electronic components, building a customized computer-vision based measurement device becomes possible. In the paper a novel structured light pattern for 3D structured light scanner is proposed. During development, accuracy and robustness of the proposed system were tested on artificial objects with known surface configurations, after which measurements were performed on human subjects. Simultaneous measurements with standard structured light pattern were achieved and obtained results compared. Volumetric parameters of both artificial object and human body segment obtained by 3D scanning were compared to the immersion method and were found to be in a good agreement and were used for segment mass estimation. Obtained results are presented and analyzed, and conclusions about system performance with possible improvements are discussed.     

Behavior of AISI 316L Steel Subjected to Uniaxial State of Stress at Elevated Temperatures

This paper presents an experimental investigation on an AISI 316L stainless steel regarding mechanical properties and short uniaxial creep tests at elevated temperatures. The short time creep tests were carried out under different but constant stresses. The obtained data of ultimate tensile strength, yield strength, creep curves and effects of elevated temperatures on mechanical properties were presented. For a selected rheological model,material parameters were obtained. As a justification, such rheological model is implemented in the finite element procedure for an uniaxially stressed specimen in selected environmental conditions.     

Distributed Computation Multi-agent System

This article addresses a formal model of a distributed computation multi-agent system. This model has evolved from the experimental research on using multi-agent systems as a ground for developing fuzzy cognitive maps. The main paper contribution is a distributed computation multi-agent system definition and mathematical formalization based on automata theory. This mathematical formalization is tested by developing distributed computation multi-agent systems for fuzzy cognitive maps and artificial neural networks – two typical distributed computation systems. Fuzzy cognitive maps are distributed computation systems used for qualitative modeling and behavior simulation, while artificial neural networks are used for modeling and simulating complex systems by creating a non-linear statistical data model. An artificial neural network encapsulates in its structure data patterns that are hidden in the data used to create the network. Both of these systems are well suited for formal model testing. We have used evolutionary incremental development as an agent design method which has shown to be a good approach to develop multi-agent systems according to the formal model of a distributed computation multi-agent system.     

Planning-based security testing of web applications with attack grammars

Web applications are deployed on machines around the globe and offer almost universal accessibility. These applications assure functional interconnectivity between different components on a 24/7 basis. One of the most important requirements is data confidentiality and secure authentication. However, implementation flaws and unfulfilled requirements often result in security leaks that malicious users eventually exploited. In this context, the application of different testing methods is of utmost importance in order to detect software defects during development and to prevent unauthorized access in advance. In this paper, we contribute to test automation for web applications. In particular, we focus on using planning for testing where we introduce underlying models covering attacks and their use in testing of web applications. The planning model offers a high degree of extendibility and configurability and as well overcomes limits of traditional graphical representations. New testing possibilities emerge that eventually lead to better vulnerability detection, therefore ensuring more secure web services and applications.

     

Nomadic Input on Mobile Devices: The Influence of Touch Input Technique and Walking Speed on Performance and Offset Modeling

In everyday life, people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this article, we analyze the influence of walking speed, gait pattern, and input techniques on commonly used performance parameters like error rate, accuracy, and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input, and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed-specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a trade-off between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods.