A fuzzy alignment approach to sizing surface cracks by the AC field measurement technique

In real world applications, one major issue with most of non-phenomenological methods is the need for a large and complete databanks. In most practical cases, it is impossible to obtain a complete and representative database that includes sufficient number of representative examples. This fact renders most of available defects and cracks databases useless. In this paper, an aligning method is formalized by a fuzzy recursive least square algorithm as a learning methodology for electromagnetic alternative current field measurement (ACFM) probe signals of a crack (data). This method along with a set of fuzzy linguistic rules, including adequate adaptation of different crack shapes (knowledge) for combining knowledge and data whenever the superposition theory can be utilized, provide a means to compensate for the lack of sufficient samples in available crack databases. We have shown that the combination of this fuzzy inference method and the method of the adaptation for different crack shapes provides sufficient means as a priori empirical knowledge for the training system. This approach significantly reduces the need for a large and complete crack databases. The validity of the proposed methodology is demonstrated by examining the sizing errors in the case of several surface cracks with elliptical depth profile when inverting their respective ACFM signals.     

Using a wavelet network for reconstruction of fatigue crack depth profile from AC field measurement signals

This paper presents a wavelet-network-based technique for reconstructing the crack depth profile of a fatigue crack in a metal from the output signal of an alternating current field measurement (ACFM) probe. The main feature of this technique is that it requires only the ACFM probe output signals along the crack opening. The database for training the network is established by developing a random crack-depth generator, using a fast pseudo-analytic ACFM probe output simulator. The validity of the proposed technique is demonstrated by comparing the actual and reconstructed depth profiles of several simulated and machine-made cracks with no predetermined geometries.     

Analysis of complex protein mixtures with improved sequence coverage using (CE-MS/MS)n

Identification of proteins, in a complex protein mixture, using one-dimensional high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis of its digest, usually suffers from low sequence coverage. There are several reasons for the low coverage including undersampling, wide concentration dynamic range of the proteins in a complex protein mixture, and wide range of electrospray ionization efficiency of peptides under each mobile-phase composition. To address this low sequence coverage, we introduce a novel technique, (CE-MS/MS)n, which utilizes the most significant advantages of CE-MS/MS, including economy of sample size, fast analysis time, and high separation efficiency, to increase the sequence coverage of a complex protein mixture. Based on these characteristics, (CE-MS/MS)n can be performed in which multiple CE-MS/MS subanalyses (injections followed by analyses) are analyzed and experimental variables are manipulated during each CE-MS/MS subanalysis in order to maximize sequence coverage. (CE-MS/MS)n is a practical technique since each CE-MS/MS subanalysis consumes <10 nL, and each CE-MS/MS subanalysis takes approximately 10 min; therefore, several subanalyses can be performed in approximately 1 h consuming only nanoliters of the sample. Two techniques have been introduced to address the undersampling: (1) (CE-MS/MS)n using dynamic exclusion. In this technique, several CE-MS/MS analyses (injection followed by separation) were performed in one run using the dynamic exclusion capability of the mass spectrometer until all peptide peaks were analyzed by MS/MS. (2) Gas-phase fractionation. In this technique, (CE-MS/MS)n is performed by scanning a narrow mass range (every approximately 100 m/z) during each CE-MS/MS subanalysis without using dynamic exclusion. Under this condition, in each subanalysis, the number of peptides available for MS/MS analysis is significantly reduced, and peptides with the same nominal masses are analyzed, thereby increasing sequence coverage. Additionally, to address the lack of detection of low-level peptides in a mixture containing a wide concentration dynamic range, the concentration of the sample was systematically increased in each subanalysis (while utilizing dynamic exclusion) so that low-intensity peptides would rise above the mass spectrometer threshold and, consequently, undergo MS/MS analysis. Moreover, to alter the ionization efficiency of peptides with low electrospray ionization efficiency, and to change the migration behavior of comigrating peptides under a specific liquid composition, the CE background electrolyte was modified in several subanalyses to further improve sequence coverage. The combination of the above-mentioned techniques was applied to the analysis of the tryptic digests of three well-characterized protein mixtures: a six-protein mixture with average MW of approximately 26,000 (standard I), a six-protein mixture with an average MW approximately 49,000 (standard II), and a more complex protein mixture containing 55 proteins (E. coli ribosomal proteins). In approximately 1 h, when the MS/MS of the peptides were manually checked, all peptides that produced peaks under electrospray ionization in the scanned range of the analysis (500-2000 m/z) and within the practical fragmentation capability of the MS (peptides with MW <3500) were identified for standard I by consuming only 200 fmol of each protein. When searched against a Swissprot database, the average sequence coverage for the standard I, II, and E. coli's ribosomal proteins were 57, 34, and 15%, respectively.     

Optimization of Applied Water Depth Under Water Limiting Conditions

Water productivity is a major challenge in all agricultural regions and despite water shortages, farmers do not welcome water management strategies due to a lack of knowledge of possible economic consequences. This study aimed to introduce the optimum applied water depths under limiting conditions through mathematical optimization. The effects of optimization were coupled with irrigation scheduling to assess yield, water productivity, and net income. Production and cost functions were created based on two scenarios for the applied water. According to the results, the best applied water depth under water limiting conditions depends on land limiting conditions and how severe water limitation is. In mild to moderate water limiting conditions, by using the optimum applied water depth (W_w), water can be saved by 26% causing a 3 to 4% decrease in the net income per unit of land and a 16% increase in the net income per unit of water. As water supply is severely limited, using the equivalent optimum applied water depth (W_ew) results in the highest productivity. Although using W_ew causes a 14 to 17% decrease in the net income per unit of land, it saves water by 46%. In water limiting conditions, if the land is not limited, using W_ew causes the maximum net income per unit of land. A sensitivity analysis was conducted for the net income and the optimum applied water depths, as well. Furthermore, irrigation scheduling caused a 27% increase in the net income per unit of land. Overall, using optimum applied water depths and irrigation scheduling are highly recommended for addressing water scarcity.

     

Numerical simulation of electromagnetic fields radiated by lightning return stroke channels: a wavelet-based approach

The antenna theory model is widely employed to numerically simulate the propagation of current wave along lightning return stroke channels and compute the radiated electromagnetic fields. In this model, the channel is approximated as a vertically straight or a horizontally bent thin-wire antenna above perfectly conducting ground for which the numerical solution of the governing electric field integral equation in frequency domain by the conventional method of moment is prohibitively slow. This paper proposes an efficient algorithm to substantially reduce the computation time of the numerical process for the entire frequency components of the excitation current. In this algorithm, a class of predefined wavelet packet transform is first used to effectively sparsify the resulting moment matrix equations. A proper iterative solver is then utilized to take the full advantages of manipulatory sparse matrices. To accelerate the construction of the original moment matrix, the reciprocal closed-form mutual impedance of sinusoidal electric dipoles and the symmetry of the model are fully exploited. A good agreement is observed with computed data found in technical literature while the overall computational time is reduced remarkably.     

Chemical Compositions of Oils from Several Wild Almond Species

Chemical compositions of oils extracted from three wild almond species [Amygdalus scoparia from Beyza, Iran (AZ); A. scoparia from Borazjan, Iran (AJ), and A. hausknechtii from the Firuzabad region, (AH)] and a domestic species, A. dulcis from Estahban, Iran (AD), as a reference, were investigated. Total oil content ranged from 44.4% in AJ to 51.4% in AD. Saponification numbers were in the range of 173.5 (for AJ) to 192.9 for AD. Oxidative stability, total phenolic contents and total wax contents were found to be within the ranges 11.7–14.0 h, 33.9–43.2 and 2.05–2.53%, respectively. The main monounsaturated fatty acid (MUFA) was oleic acid ranging from 66.7% for AH to 69.7% for AZ. The only polyunsaturated fatty acid (PUFA) was linoleic acid ranging from 18.2% for AZ to 23.0% for AD. The major saturated fatty acid was palmitic acid. MUFA contents and MUFA to PUFA ratio in the oils from wild almond species as well as those in the domestic one were found at higher levels than those in the common vegetable oils such as soybean, various nut oils, and also those from the seeds of pomegranate, grape, date and sesame. Oils from wild almond species investigated here are rich in oleic acid and can be considered as potential vegetable oils in the human diet.