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In the following research, we specifically assessed the feasibility of a novel AS-1411-chitosan (CS)-gold nanoparticle (AuNPs) delivery system to carry methotrexate (MTX) into the cancer cells. The designed system had a spherical shape with average size of 62 ± 2.4 nm, the zeta potential of −32.1 ± 1.4 mV, and released MTX in a controlled pH- and time-dependent manner. CS-AuNPs could successfully penetrate the breast cancer cells and release the therapeutic drug, and ultimately, be accumulated by the nucleolin-AS1411 targeting mechanism within the in vivo environment. The anticancer activity of MTX was attributed to the induction of mitochondria membrane potential loss and nuclear fragmentation, which leads to apoptotic death. Moreover, the cellular internalization confirmed the high potential in the elimination of cancer cells without notable cytotoxicity on non-target cells. Therefore, it was concluded that the AS1411-CS-AuNPs with considerable in vitro and in vivo results could be utilized as a favorable system for breast cancer treatment.

Introduction. Recognizing factors affecting job motivation can be very helpful in increasing efficiency and job satisfaction of university faculty members. In order to Identify the internal and external factors of job motivation, this study was conducted to determine the effective factors on job motivation of faculty members in Rafsanjan Medical University. Methods. In a descriptive study, all faculty members of Rafsanjan Medical University (n=82) completed a questionnaire developed by the investigator based on Herzberg’s theory and consisted of 40 questions. The validty and relability of the quessionnaire was confirmed by content validity and test re-test. The data was analyzed by SPSS software using frequency distribution and chi2. Results. Eighty one percent of faculty members considered external factors and 72% considered internal factors important in job motivation. Among the external factors, wage and sallary, job security, work environment, communication with others, supervision and the work policy had the most important role, respectively. The most important internal factors included nature of the job, appreciation of employees, professional development and job success, respectively. Conclusion. Based on the faculty members’ view points, the external factors (hygiene factors) compared with the internal factors (motivation factors) had a more important role in job motivation which does not conform with the Herzberg’s view. Sallary and job security were the most important motivation factors.

Structural control using energy dissipater devices is emerging as a heavily researched strategy in earthquake engineering. Among several control systems, semiactive control is usually possible and efficient. In this research, a semiactive energy dissipating bracing system based on a viscous damper is proposed. In the conventional bracing systems, it is assumed that the braces can buckle under compression. Therefore, a semiactive on-off brace strategy is implemented to improve the conventional brace performance. Further, an energy absorbing mechanism is implemented. In the proposed system, the buckling of the member is prevented by implementing a one-way valve device. The permanent story drifts at the end of excitations are negligible. In this mechanism, any actuator and/or large power supply are not needed, instead, just battery-size power supplies to switch the one-way valve mechanical system on or off. The developed mechanism is composed of a viscous damper, a length correction control system, and a normal wind bracing on each floor. Despite the fact that this system does not get control command from the outside, it is called a semiactive control system. The hysteresis loop of the braces is almost similar to ductile tensile steel members. Therefore, the system is full capacity design. Nonlinear dynamic analysis of the system has been carried out and structural behavior has been investigated. In addition, damage indices are determined in order to compare the viscous tensile bracing system with the conventional bracing systems. CE Database subject headings: Structural control; Earthquake loads; Damage; Deformation; Buckling; Ductility; Damping; Bracing.

Online selection of the appropriate model and identifying its parameters based on measured vibrational data are among the challenging issues in dynamic system identification. After a severe earthquake, quick monitoring and assessment of structural health status play a crucial role in effective critical risk management for the building owners and decision-makers. The Bayesian multiple modeling approach is a suitable tool for optimal model class selection, which is used in this article mainly for improving data fitting precision, decreasing dimensions of structural unknown vector through removing unnecessary parameters, detecting the occurrence and type of predominant phenomenon related to degradation and pinching, and finally increasing stability and convergence rate of the used identification algorithm. In this study, a reliable and effective time-domain method is proposed for online probabilistic model class selection and joint estimation of structures using the central difference Kalman filter and Bayesian multiple modeling approach. Also, in contrast to existing studies, the performance and efficiency of the proposed algorithm are investigated in nonlinear system identification with a large number of unknowns. The proposed algorithm is implemented on three moment-frame buildings with 8, 54, and 60 unknowns. In addition, a numerical example is provided to analyze the case in which the exact model is not among the plausible models. To verify the performance of the hybrid identification method, robust simulations with synthetic measurement noises and modeling errors were generated using the Monte Carlo random simulation method. The result shows the method can be used to simultaneously select the optimal model class and identify its unknown states and parameters in an online manner. [ABSTRACT FROM AUTHOR]

Rapid assessment of structural safety and performance right after the occurrence of significant earthquake shaking is crucial for building owners and decision-makers to make informed risk management decisions. Hence, it is vital to develop online and pseudo-online health monitoring methods to quantify the health of the building right after significant earthquake shaking. Many Bayesian inference--based methods have been developed in the past which allow the users to estimate the unknown states and parameters. However, one of the most challenging part of the Bayesian inference--based methods is the determination of the parameter noise covariance matrix. It is especially difficult when the number of unknown states and parameters is large. In this study, an effective online joint estimation method for nonlinear hysteretic structures, with consideration of degradation and pinching phenomena, is proposed. Simultaneous estimation of states and parameters is conducted using the combination of a central difference Kalman filter as an effective estimator and the Robbins--Monro stochastic approximation technique as the parameters noise covariance matrix regulator. The proposed algorithm is implemented on three shear buildings with 36, 54, and 90 unknown states and parameters. To verify the performance of the system identification method, robust simulations with synthetic measurement noises and modeling errors were generated using the Monte Carlo random simulation method. The result shows the proposed method can be used to estimate the unknown parameters and states of highly nonlinear systems efficiently and effectively. [ABSTRACT FROM AUTHOR]

Background: Celiac disease (CD) is the most recognized inflammatory small intestine disorder that occurs as a result of an immune response to ingested gluten proteins of wheat, barley, and rye in genetically predisposed individuals. Adhering to a strict gluten-free (GF) diet is required to be assured of nutritional sufficiency and prompt healing the CD manifestations. Therefore, regarding the popularization of mobile technologies, using mobile health (mHealth) applications provide a favored opportunity to encourage patient interest in personal nutrition education and disease symptomatology. Objective: The goal of our study was to develop a Persian-language smartphone application (CeliacPlus; C+) by user-centered design for individuals with CD, to improve adherence to GF diet and enhance patients' knowledge. Material and Methods: This project was a developmental-applied study which involved three phases of analysis, design, and development. At first, a scientific review was performed on existing CD related mobile applications. Also, celiac patients were consulted to realize their preferences, barriers, and facilitators in the use of mHealth. Then, the main learning menu of C+ was designed based on the collected information. Eventually, the final version of C+ was developed under the supervision of the team consists of nutritionists, gastroenterologist and expert app developers. Results: The mobile software can provide consumers with easy-to-understand nutrition information, FAQs, and practical tips for the disease management and also support the selection of GF choices when shopping or cooking food. Conclusion: C+ may be a potentially helpful approach in empowering patients to acquire self-care abilities and ensure overall gut health. [ABSTRACT FROM AUTHOR]