A preliminary approach of dynamic identification of slender buildings by neuronal networks

The study of the dynamic behavior of slender masonry structures is usually related to the preservation of the historic heritage. This study, for bell towers and industrial masonry chimneys, is particularly relevant in areas with an important seismic hazard. The analysis of the dynamic behavior of masonry structures is particularly complex due to the multiple effects that can affect the variation of its main frequencies along the seasons of the year: temperature and humidity. Moreover, these dynamic properties also vary considerably in structures built in areas where land subsidence due to the variation of the phreatic level along the year is particularly evident: the stiffness of the soil–structure interaction also varies. This paper presents a study to evaluate the possibility of detecting the variation of groundwater level based on the readings obtained using accelerometers in different positions on the structure. To do this a general case study was considered: a 3D numerical model of a bellower. The variation of the phreatic level was evaluated between 0 and −20 m, and 81 cases studies were developed modifying the rigidity of the soil–structure interaction associated to a position of the phreatic level. To simulate the dispositions of accelerometers on a real construction, 16 points of the numerical model were selected along the structure to obtain modal displacements in two orthogonal directions. Through an adjustment by using neural networks, a good correlation has been observed between the predicted position of the water table and acceleration readings obtained from the numerical model. It is possible to conclude that with a discrete register of accelerations on the tower it is possible to predict the water table depth.     

Rapid and label-free classification of pathogens based on light scattering,reduced power spectral features and support vector machine

The rapid identification of pathogens is crucial in controlling the food quality and safety. The proposed system for the rapid and label-free identification of pathogens is based on the principle of laser scattering from the bacterial microbes. The clinical prototype consists of three parts: the laser beam, photodetectors, and the data acquisition system. The bacterial testing sample was mixed with 10 mL distilled water and placed inside the machine chamber. When the bacterial microbes pass by the laser beam, the scattering of light occurs due to variation in size, shape, and morphology. Due to this reason, different types of pathogens show their unique light scattering patterns. The photo-detectors were arranged at the surroundings of the sample at different angles to collect the scattered light. The photodetectors convert the scattered light intensity into a voltage waveform. The waveform features were acquired by using the power spectral characteristics, and the dimensionality of extracted features was reduced by applying minimal-redundancy-maximal-relevance criterion (mRMR). A support vector machine (SVM) classifier was developed by training the selected power spectral features for the classification of three different bacterial microbes. The resulting average identification accuracies of E. faecalis, E. coli and S. aureus were 99%, 87%, and 94%, respectively. The overall experimental results yield a higher accuracy of 93.6%, indicating that the proposed device has the potential for label-free identification of pathogens with simplicity, rapidity, and cost-effectiveness.     

Studies on oral bioavailability and first‐pass metabolism of withaferin A in rats using LC–MS/MS and Q‐TRAP

Withaferin A (WA) is one of the major bioactive steroidal lactones with extensive pharmacological activities present in the plant Withania somnifera. The absolute oral bioavailability of WA remains unknown and human‐related in vitro data are not available. Therefore, in the present study, the absolute oral bioavailability of WA in male rats and the in vitro screening of absorption factors by Q‐trap and LC–MS/MS analysis were conducted to explore possible clinical properties of WA. The developed and validated analytical methods were successfully applied to the pharmacokinetic studies and in vitro measurement of WA. The oral bioavailability was determined to be 32.4 ± 4.8% based on intravenous (5 mg/kg) and oral (10 mg/kg) administrations of WA in male rats. The in vitro results showed that WA could be easily transported across Caco‐2 cells and WA did not show as a substrate for P‐glycoprotein. Moreover, the stability of WA was similar between male rat and human in simulated gastric fluid (stable), in intestinal microflora solution (slow decrease) and in liver microsomes (rapid depletion, with a half‐life of 5.6 min). As such, the first‐pass metabolism of WA was further verified by rat intestine‐liver in situ perfusion, revealing that WA rapidly decreased and 27.1% remained within 1 h, while the content of three major metabolites (M1, M4, M5) identified by Q‐trap increased. This perfusion result is consistent with the oral bioavailability results in vivo. The first‐pass metabolism of WA might be the main barrier in achieving good oral bioavailability in male rats and it is predicted to be similar in humans. This study may hold clinical significance.     

On nonlinear boundary value problem corresponding to N-dimensional inverse spectral problem

We establish a relationship between an inverse optimization spectral problem for the N-dimensional Schrödinger equation $?\mathrm{\Delta }?+q(x)?=\lambda ?$ and a solution of the nonlinear boundary value problem $?\mathrm{\Delta }u+q(x)u=\lambda u?u^{\gamma ?1},u>0,u{|}_{?\mathrm{\Omega }}=0$. Using this relationship, we find an exact solution for the inverse optimization spectral problem, investigate its stability and obtain new results on the existence and uniqueness of the solution for the nonlinear boundary value problem.     

Serum pharmacochemistry combined with multiple data processing approach to screen the bioactive components and their metabolites in Mutan Cortex by ultra‐performance liquid chromatography tandem mass spectrometry

Root cortex of Paeonia suffruticosa Andrews (Paeoniaceae), known as Moutan Cortex (MC), is known to have anti‐allergic and anti‐inflammatory properties. However, the constituents absorbed into blood after oral administration of MC remain unknown. A sensitive and rapid method by ultra‐high‐pressure liquid chromatography–electrospray ionization–quadrupole‐time‐of‐flight mass spectrometry (UPLC‐ESI‐Q‐TOF‐MS) technology and the MetaboLynx^TM software combined with multiple data processing approach (Mdpa) was established to investigate the absorbed constituents in rats after oral administration of MC, providing unique high‐throughput capabilities for drug metabolism study. A hyphenated electrospray ionization and quadrupole‐time‐of‐flight analyzer was used for the determination of accurate mass of the fragment ion in negative mode, with excellent MS mass accuracy and enhanced data acquisition. This rapid automated analysis method was successfully applied for screening and identification of the constituents absorbed and metabolized studies of MC after oral administration to rats. A total of 46 peaks were obtained from MC, 41 of which were tentatively characterized. In the VIP‐plot of orthogonal partial least‐squares discriminant analysis, 23 interesting ions in serum samples were extracted, and 16 parent components and seven metabolites were detected in vivo. The integrative serum pharmacochemistry technique, UPLC‐ESI‐Q‐TOF‐MS, and Mdpa method were successfully applied for rapid discovery of multiple components from MC. Copyright © 2013 John Wiley & Sons, Ltd.     

Detectability conditions for output-only subspace identification

ABSTRACT

The scope of output-only/blind identification is restricted to stochastic/statistical processes, but for the first time in this study, the detectability conditions for general output-only subspace identification are investigated. This aids the range of input sources to be extended in a much realistic manner, beyond the only stochastic inputs. For this purpose, the subspace framework is assigned to make a connection between the output signal contents and the LTI system order. A few substantial hypotheses and algebraic statements are propounded affirming the sufficiency of the genuine output sequences for the identification purpose. This can be perceived as the cornerstone of state-space model reconstruction. In order to consolidate the notions according to reality, several examples are studied and examined for different input classes with stochastic disturbance.     

Contingent derivatives and regularization for noncoercive inverse problems

Abstract

We study the inverse problem of parameter identification in noncoercive variational problems that commonly appear in applied models. We examine the differentiability of the set-valued parameter-to-solution map using the first-order and the second-order contingent derivatives. We explore the inverse problem using the output least-squares and the modified output least-squares objectives. By regularizing the noncoercive variational problem, we obtain a single-valued regularized parameter-to-solution map and investigate its smoothness and boundedness. We also consider optimization problems using the output least-squares and the modified output least-squares objectives for the regularized variational problem. We give a complete convergence analysis showing that for the output least-squares and the modified output least-squares, the regularized minimization problems approximate the original optimization problems suitably. We also provide the first-order and the second-order adjoint method for the computation of the first-order and the second-order derivatives of the output least-squares objective. We provide discrete formulas for the gradient and the Hessian calculation and present numerical results.