Predicting the strength anisotropy in uniaxial compression of some laminated sandstones using multivariate regression analysis

In this study, uniaxial compressive strength (UCS) tests were carried out to investigate the anisotropic strength behavior of laminated sandstones selected from submarine fan deposits in the Neogene Adana Basin of Southern Turkey. The core specimens were prepared at orientation angles (β) of 0°, 30°, 45°, 60°, and 90° with respect to the planes of lamination. U-type strength anisotropy with strength anisotropy ratios (Rc = σ₉₀/σ_min) varying between 1.29 and 1.74 were found, referring to a low degree of anisotropy. An attempt has been made to estimate the anisotropic UCS behavior taking into account orientation angles, unit weight (γ) and porosity (n) as independent variables by multivariate regression analysis. The second orders of each independent variable as well as the third order of the orientation angle values were also considered in regression analyses to take into consideration their nonlinear relationships on UCS. The prediction performance of the best fit regression model was evaluated by the standard error of estimate (SEE), the coefficient of multiple determination (R ²), and the adjusted coefficient of multiple determination (R_a² R_{a}^{2} ), which were obtained as 2.27, 0.927, and 0.923, respectively, indicating high prediction capacity.     

Probabilistic Model for the Assessment of Cyclically Induced Reconsolidation (Volumetric) Settlements

A maximum likelihood framework for the probabilistic assessment of cyclically induced reconsolidation settlements of saturated cohesionless soil sites is described. For this purpose, over 200 case history sites were carefully studied. After screening for data quality and completeness, the resulting database is composed of 49 high-quality, cyclically induced ground settlement case histories from seven different earthquakes. For these case history sites, settlement predictions by currently available methods of Tokimatsu and Seed (1984), Ishihara and Yoshimine (1992), Shamoto et al. (1998), and Wu and Seed (2004) are presented comparatively, along with the predictions of the proposed probabilistic model. As an integral part of the proposed model, the volumetric strain correlation presented in the companion paper is used. The accuracy of the mean predictions as well as their uncertainty is assessed by both linear regression and maximum likelihood methodologies. The analyses results revealed that (1) the predictions of Shamoto et al. and Tokimatsu and Seed are smaller than the actual settlements and need to be calibrated by a factor of 1.93 and 1.45, respectively; and (2) Ishihara and Yoshimine, and Wu and Seed predictions are higher than the actual settlements and need to be calibrated by a factor of 0.90 and 0.98, respectively. The Wu and Seed procedure produced the most unbiased estimates of mean settlements [i.e., their calibration coefficient (0.98) is the closest to unity], but the uncertainty (scatter) of their predictions remains high as revealed by the second to last smaller R2 value, or relatively higher standard deviation (σε) of the model error. In addition to superior model predictions, the main advantage of the proposed methodology is the probabilistic nature of the calibration scheme, which enables incorporation of the model uncertainty into mean settlement predictions. To illustrate the potential use of the proposed model, the probability of cyclically induced reconsolidation settlement of a site after a scenario earthquake to be less than a threshold settlement level is assessed.     

Measurement of Young’s modulus and residual stress of thin SiC layers for MEMS high temperature applications

Silicon carbide (SiC) is a promising material for applications in harsh environments. Standard silicon (Si) microelectromechanical systems (MEMS) are limited in operating temperature to temperatures below 130°C for electronic devices and below 600°C for mechanical devices. Due to its large bandgap SiC enables MEMS with significantly higher operating temperatures. Furthermore, SiC exhibits high chemical stability and thermal conductivity. Young’s modulus and residual stress are important mechanical properties for the design of sophisticated SiC-based MEMS devices. In particular, residual stresses are strongly dependent on the deposition conditions. Literature values for Young’s modulus range from 100 to?400?GPa, and residual stresses range from 98 to?486?MPa. In this paper we present our work on investigating Young’s modulus and residual stress of SiC films deposited on single crystal bulk silicon using bulge testing. This method is based on measurement of pressure-dependent membrane deflection. Polycrystalline as well as single crystal cubic silicon carbide samples are studied. For the samples tested, average Young’s modulus and residual stress measured are 417?GPa and 89?MPa for polycrystalline samples. For single crystal samples, the according values are 388?GPa and 217?MPa. These results compare well with literature values.     

Noninfluentials and information dissemination in the microblogging community

Firms are increasingly focusing on understanding and managing their social media strategies in order to create discussions and optimize the spread of news in their communities. Most prior studies on information dissemination have mainly focused on the roles of influentials but ignored the essential for noninfluentials. To fill this gap, this paper takes a holistic view of the information dissemination process and investigates how the participation of both influentials and noninfluentials plays a role in affecting the volume and sentiment of microblogs, which are precursors to raise awareness and attraction for brands. To test our hypotheses, we build a novel econometric model and apply it to a dataset collected from the popular microblogging site Twitter. We have the following main results: (1) back-and-forth-type discussions and retweets are effective in generating awareness and positive attractiveness; (2) influentials or mavens (who have many followers but seldom follow others) help generate initial sparks toward microblogging, but during the cascading periods, the noninfluentials play an important role in driving the conversations; and (3) new users who gradually join the discussions also help increase awareness, although they may not generate a positive sentiment. Our results provide important implications for mediating consumer interactions and firms’ marketing strategies.     

Two fault detection and isolation schemes for robot manipulators using soft computing techniques

With growing technology, fault detection and isolation (FDI) have become one of the interesting and important research areas in modern control and signal processing. Accomplishment of specific missions like waste treatment in nuclear reactors or data collection in space and underwater missions make reliability more important for robotics and this demand forces researchers to adapt available FDI studies on nonlinear systems to robot manipulators, mobile robots and mobile manipulators.In this study, two model-based FDI schemes for robot manipulators using soft computing techniques, as an integrator of Neural Network (NN) and Fuzzy Logic (FL), are proposed. Both schemes use M-ANFIS for robot modelling. The first scheme isolates faults by passing residual signals through a neural network. The second scheme isolates faults by modelling faulty robot models for defined faults and combining these models as a generalized observers scheme (GOS) structure. Performances of these schemes are tested on a simulated two-link planar manipulator and simulation results and a comparison according to some important FDI specifications are presented.     

HFE gene mutation is a risk factor for tissue iron accumulation in hemodialysis patients

Introduction: HFE gene mutations are responsible from iron overload in general population. Studies in hemodialysis patients investigated the effect of presence of HFE gene mutations on serum ferritin and transferrin saturation (TSAT) with conflicting results. However effect of HFE mutations on iron overload in hemodialysis patients was not previously extensively studied. Methods: 36 hemodialysis patients (age 51.3 ± 15.6, (18/18) male/female) and 44 healthy control subjects included in this cross sectional study. Hemoglobin, ferritin, TSAT in the preceding 2 years were recorded. Iron and erythropoietin (EPO) administered during this period were calculated. Iron accumulation in heart and liver was detected by MRI. Relationship between HFE gene mutation, hemoglobin, iron parameters and EPO doses, and tissue iron accumulation were determined. Findings: Iron overload was detected in nine (25%) patients. Hemoglobin, iron parameters, weekly EPO doses, and monthly iron doses of patients with and without iron overload were similar. There was no difference between control group and hemodialysis patients with respect to the prevalence of HFE gene mutations. Iron overload was detected in five of eight patients who had HFE gene mutations, but iron overload was present in 4 of 28 patients who had no mutations (P = 0.01). Hemoglobin, iron parameters, erythropoietin, and iron doses were similar in patients with and without gene mutations. HFE gene mutations remained the main determinant of iron overload after multivariate logistic regression analysis (P = 0.02; OR, 11.6). Discussion: Serum iron parameters were not adequate to detect iron overload and HFE gene mutation was found to be an important risk factor for iron accumulation.     

Adsorption of boron from boron-containing wastewaters by ion exchange in a continuous reactor

In this study, boron removal from boron-containing wastewaters prepared synthetically was investigated. The experiments in which Amberlite IRA 743, boron specific resin was used were carried out in a column reactor. The bed volume of resin, boron concentration, flow rate and temperature were selected as experimental parameters. The experimental results showed that percent of boron removal increased with increasing amount of resin and with decreasing boron concentration in the solution. Boron removal decreased with increasing of flow rate and the effect of temperature on the percent of total boron removal increased the boron removal rate. As a result, it was seen that about 99% of boron in the wastewater could be removed at optimum conditions.     

Utilization of borogypsum as set retarder in Portland cement production

Boron ores are used in the production of various boron compounds such as boric acid, borax and boron oxide. Boric acid is produced by reacting colemanite(2CaO·3B₂O₃·5H₂O) with sulphuric acid and a large quantity of borogypsum is formed during this production. This waste causes various environmental problems when discharged directly to the environment. Portland cement is the most important material in the building industry. This material is produced by adding about 3-5% gypsum (CaSO₄·2H₂O) to clinker as a set retarder. The aim of this study was to stabilize borogypsum, and to produce cements by adding borogypsum instead of natural gypsum to clinker. Concrete using cement produced with borogypsum was tested to find the mechanical properties and the test values were compared with those of concrete from cement with natural gypsum. Compressive strength of concrete from cement produced with borogypsum was found to be higher than that of natural gypsum. Also, the setting time of cement with borogypsum was longer than that of the Portland cement.