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This study outlines the flutter characteristics of aeroelastic wings under unsteady aerodynamic loading based on an efficient support vector machine assisted k-method. First, the aeroelastic wing flutter speed and flutter frequency are obtained using k-method. Then, the uncertain input parameters distribution is modeled by probability density functions. These parameters are propagated to the aeroelastic wing equations. The Monte Carlo simulation using 12 parallel logical threads is carried out to obtain the flutter speed and the flutter frequency distribution. An optimal robust surrogate model is trained by limited numbers of input and output using support vector machine. Monte Carlo simulation is also carried out in conjunction with the machine learning based k-method computational framework for obtaining the complete probabilistic description of flutter speed and flutter frequency. The coupled support vector regression based k-method is a novel approach that is first used in the aeroelastic wings flutter. The present method is found to reduce the computational time and cost significantly without compromising the accuracy of results.

Porphyry Cu ± Mo ± Au deposits are centered within a distinctive arrangement of alteration assemblages, including sodic-calcic, potassic, propylitic, chlorite-sericite with early and late sericitic, and finally, near-surface advanced argillic alterations. Here we discussed the linkage between feldspar-destructive processes and hypogene sulfide mineralization in the porphyry systems. Also, the chemical composition of white mica in the phyllically altered rocks of weakly mineralized/barren and fertile porphyries was discriminated. Following the new genetic models of porphyry copper systems, it is evident that the mechanism lying in sulfide mineralization could explain the tight association between sulfide mineralization and phyllic alteration. Moreover, under acidic pH conditions during feldspar-destructive processes, the feldspars of mineralized areas are more sensitive to hydrolysis processes, owing to the higher alumina contents (~ higher anorthite %) in their compositions. Combining the mineralization mechanisms of PCDs, which highlights the significant contribution of calcic feldspars in the sulfide precipitation, it is proven that there are much more feldspar-destructive processes in the mineralized zones. These may show that probable geochemical clues for the discovering of highly mineralized porphyry systems have lied in the composition of feldspar remnants and/or products of feldspar-destructive processes. Comparing the white mica composition of weakly mineralized/barren and mineralized porphyry systems indicate they consistently show ideal tschermak’s type substitution. However, weakly mineralized systems exhibit relatively higher contents of Al/Fe + Mg (apfu) and Si + Al (apfu) contents than that of mineralized porphyry systems.

Photodetectors fabricated from low-dimensional materials such as quantum dots, nanowires, and two-dimensional materials show tremendous promise based on reports of very high responsivities. However, it is not generally appreciated that maximizing the internal gain may compromise the detector performance at low light levels, reducing its sensitivity. Here, we show that for most low-dimensional photodetectors with internal gain the sensitivity is determined by the junction capacitance. Thanks to their extremely small junction capacitances and reduced charge screening, low-dimensional materials and devices provide clear advantages over bulk semiconductors in the pursuit of high-sensitivity photodetectors. This mini-review describes and validates a method to estimate the capacitance from external photoresponse measurements, providing a straightforward approach to extract the device sensitivity and benchmark against physical limits. This improved physical understanding can guide the design of low-dimensional photodetectors to effectively leverage their unique advantage and achieve sensitivities that can exceed that of the best existing photodetectors.

In this study, the leaf area was estimated by different regression models and new methods of image processing by using artificial intelligence (AI) in bread (Triticum aestivumL.) and durum wheat (Triticum durumL.) and triticale (×TritosecaleWittm. ex A. Camus) at seedling, booting, and milk development stages. Data on leaf traits in 1,000 plants of breed wheat, triticale, and durum wheat were studied. Among regression models using general data, LA=a+bLW, LA=a+b(W), and LA=a+b(W/L)models had a R2> 90% for all three cultivars (Land Wrepresented length and width of leaves). For wheat bread, models W+(LW)and L×(LW)exhibited a good estimate of the leaf area at all stages of growth, whereas in triticale, the linear models that used the product of W×Land LWwere more suitable to estimate leaf areas in booting and milk development. The multilayer perceptron (MLP) neural network modeling indicated that the ‘trainlm,’ ‘trainlm,’ and ‘traincgb’ algorithms with an optimal structure of 2‐10‐1, 2‐3‐1, and 2‐10‐1 had the least amount of the mean square error for bread wheat, triticale, and durum wheat, respectively, for each of the growth stages. Furthermore, based on the adaptive neuro‐fuzzy inference system (ANFIS) method, a very accurate estimate of the leaf area was obtained for each of the growth stages. The comparison of different models in the leaf area estimation showed that unlike estimating leaf area by regression, AI‐based methods did not depend on plant growth stages. In this study, we suggested the utilization of image processing and artificial intelligence in leaf area estimation. It will accelerate leaf area measurement in the field, by extending these methods and transferring it into smartphone applications.

ABSTRACTObjective:The ubiquitin-proteasome system plays a key role in memory consolidation. Proteasome inhibition and free radical-induced neural damage were implicated in neurodegenerative states. In this study, it was tested whether alpha-tocopherol (αT) in low and high doses could improve the long-term memory impairment induced by proteasome inhibition and protects against hippocampal oxidative stress.Methods:Alpha-tocopherol (αT) (60, 200 mg/kg, i.p. for 5 days) was administered to rats with memory deficit and hippocampal oxidative stress induced by bilateral intra-hippocampal injection of lactacystin (32 ng/μl) and mitochondrial evaluations were performed for improvement assessments.Results:The results showed that lactacystin significantly reduced the passive avoidance memory performance and increased the level of malondialdehyde (MDA), reactive oxygen species (ROS) and diminished the mitochondrial membrane potential (MMP) in the rat hippocampus. Furthermore, Intraperitoneal administration of αT significantly increased the passive avoidance memory, glutathione content and reduced ROS, MDA levels and impaired MMP.Conclusions:The results suggested that αT has neuroprotective effects against lactacystin-induced oxidative stress and memory impairment via the enhancement of hippocampal antioxidant capacity and concomitant mitochondrial sustainability. This finding shows a way to prevent and also to treat neurodegenerative diseases associated with mitochondrial impairment.

Mitochondrial malfunction plays a crucial role in cancer development and progression. Cancer cells show a substantially higher mitochondrial activity and greater mitochondrial transmembrane potential than normal cells. This concept can be exploited for targeting cytotoxic drugs to the mitochondria of cancer cells using mitochondrial-targeting compounds. In this study, a polyamidoamine dendrimer-based mitochondrial delivery system was prepared for curcumin using triphenylphosphonium ligands to improve the anticancer efficacy of the drug in vitro and in vivo. For the in vitro evaluations, various methods, such as viability assay, confocal microscopy, flow cytometry, reactive oxygen species (ROS), and real-time polymerase chain reaction analyses, were applied. Our findings showed that the targeted-dendrimeric curcumin (TDC) could successfully deliver and colocalize the drug to the mitochondria of the cancer cells, and selectively induce a potent apoptosis and cell cycle arrest at G2/M. Moreover, at a low curcumin dose of less than 25 μM, TDC significantly reduced adenosine triphosphate and glutathione, and increased the ROS level of the isolated rat hepatocyte mitochondria. The in vivo studies on the Hepa1-6 tumor-bearing mice also indicated a significant tumor suppression effect and the highest median survival days (Kaplan–Meier survival estimation and log-rank test) after treatment with the TDC construct compared to the free curcumin and untargeted construct. Besides its targeted nature and safety, the expected improved solubility and stability represent the prepared targeted-dendrimeric construct as an up-and-coming candidate for cancer treatment. The results of this study emphasize the promising route of mitochondrial targeting as a practical approach for cancer therapy, which can be achieved by optimizing the delivery method.

Objective: Carbonyl stress, resulting from toxic effects of alpha-dicarbonyls such as glyoxal (GO), plays an important role in mitochondrial dysfunction and subsequent development of diabetic complications. This study evaluated the ability of metformin (MET), berberine (BBR), and their combination to prevent GO-induced carbonyl stress in isolated rat liver mitochondria. Methods: Mitochondria (0.5 mg protein/mL) were isolated from the Wistar rat liver and incubated with various concentrations of GO (1, 2.5, 5, 7.5, and 10 mM) for 30 minutes and IC50 for GO was calculated. The suspensions of mitochondria were incubated with various concentrations of MET (2.5, 5, 10, and 20 mM) or BBR (2.5, 5, 10, and 20 μM) for 30 min and then GO in a dose of IC50 at 37 ºC for 30 min. Mitochondrial complex II activity, mitochondrial membrane potential (MMP), MDA level, reactive oxygen species (ROS) formation, reduced glutathione (GSH) content, and protein carbonylation were assessed. The combination index and isobologram of MET and BBR on GO toxicity were calculated. Results: IC50 of GO was assigned approximately 3 mM. GO disrupted the electron transfer chain and significantly increased mitochondrial ROS formation, protein carbonylation, and MDA level. GO decreased mitochondrial viability, MMP, and GSH content. Pre-treatment with MET and BBR could potentially reverse GO-induced deleterious effects in a concentration-dependent manner. Results of the drug combination indicated that CI for Fa 0.5 (Effect 50 %) was 0.83. Conclusion: These results suggest that BBR in combination with MET has a moderate synergistic effect on GO-induced carbonyl stress in isolated rat liver mitochondria.

We demonstrate the fabrication of all chalcogenide single-mode optical fiber couplers including broadband couplers, wavelength division multiplexers, and polarization beamsplitters. The functionality of each coupler is engineered with a careful design of geometry. As a result, broadband couplers can be set to any arbitrary coupling ratio. Wavelength division multiplexers provide a coupling extinction ratio up to 35 dB, and polarization beamsplitters provide a polarization extinction ratio up to 18 dB.

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden–Fletcher–Goldfarb–Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and non-diagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

The present work attempts to characterize magnetite chemistry in some collisional (Chahfiruzeh and Keder; Miocene) and pre-collisional (Reagan and Daralou; Eocene–Oligocene) porphyry copper systems hosted in the Kerman Cenozoic Magmatic Arc (KCMA). EPMA results for magnetite samples show collisional deposits have higher average contents of Fe and Ca compared to those of pre-collisional systems. Nevertheless, magnetite samples of pre-collisional porphyry Cu systems contain elevated Si values. Highlightly, the frequency of V and Ca in magnetite have a direct relation with mineralization potential of studied deposits decreasing from Chahfiruzeh to Keder, Daralou and Reagan. V/Cr and V/Al in the analyzed magnetite samples show that Reagan porphyry system is quite different than other studied deposits. Moreover, average concentrations of Mo and Cu reach the highest in collisional and pre-collisional deposits, respectively. According to Fe/(V + Ti) diagram, most of the studied magnetite samples have re-equilibrated magmatic nature. Al + Mn versus V + Ti and Ni (Cr + Mn) versus Ti + V diagrams also confirmed that all magnetite samples from collisional and pre-collisional deposits are analogous to those reported previously for porphyry Cu systems. Regarding the condition of oxygen fugacity, based on Ni versus V diagram, the Reagan deposit (pre-collisional) has the highest oxygen fugacity, while the Daralou deposit (pre-collisional) and collisional deposits (Chahfiruzeh and Keder) exhibit moderate to high fugacity. Ti + V versus Al + Mn show that selected deposits were approximately formed in the same temperature conditions.

Spacecraft attitude determination is a crucial task in attitude control subsystems. It provides the necessary feedback to close the control loop. Several sensors such as star trackers, Sun sensors, and horizon sensors are used for this purpose. The development of other methods can help control engineer with newer options to design their systems. Here, an innovative sensor for determining the attitude of a spacecraft is presented. The proposed sensor measures the Lorentz force vector due to the interaction between the magnetic field of the Earth, and the high linear velocity of the spacecraft. This sensor is composed of three series of orthogonal variable capacitors. The capacitors are connected in parallel to increase the total capacitance. The capacitors have movable plates which actuated by alternating current with specific frequency. Due to very high speed of spacecraft relative to magnetic field of earth in low orbit, the Lorentz force is exerted on the charges of the capacitor plates. The plates have same velocity as the spacecraft does. The applied Lorentz force to the plates affects their motion so that the harmonic can be seen in the output. Measuring the amplitude of the mentioned harmonic results in measurement of a component of the Lorentz force in the direction of capacitors. Installing the three capacitors orthogonally can measure the three rectangular components of the Lorentz force. This vector will be in the body frame of the spacecraft. The two-plate and three-plate capacitor are the two different proposed mechanisms and their performance is compared. Once the Lorentz force is known as a vector in the body frame, it can be applied along with data from another sensor to determine the attitude of the spacecraft. Based on simulation results, achievable resolution is better than 3°, which can be improved by further research.

The aim of the present study was to develop a novel HPLC method for the simultaneous determination of 5-fluorouracil (5-FU) and oxaliplatin (OXA) in the PHBV/PLGA nanoparticles (NPs). Chromatographic separation was performed using C18 column at a detection wavelength of 260 nm. The mobile phase consisted of 0.02 M phosphate buffer (pH 4) and methanol (90:10, V/V) and flow rate was 0.8 mL min−1. Column temperature was also maintained at 30 °C. The calibration curves displayed linear concentration ranges of 0.05–40 µg mL−1for 5-FU and 0.5–80 µg mL−1for OXA with correlation coefficients of 0.998. The LOD and LOQ were, respectively, 0.01 and 0.03 µg mL−1for 5-FU and 0.13 and 0.44 µg mL−1for OXA. The values of intra- and inter-day precision and accuracy were within acceptable limits. According to the results, the method was found to be simple, reliable, rapid, and reproducible. In addition, the HPLC assay method presented was successfully applied to the simultaneous determination of 5-FU and OXA in PHBV/PLGA NPs.

The aim of the present study was to design and evaluate the combination of pH-dependent and time-dependent polymers for colon-specific drug delivery using response surface methodology (RSM). Theophylline was selected as a model drug and Eudragit®FS 30D (pH-dependent), Eudragit®RL 30D and Eudragit®RS 30D (as time-dependent) were used as coating polymers. Dissolution test was carried out in different pH media mimicking the transit of capsules from stomach to colon. The morphology of coated capsules was evaluated by scanning electron microscopy (SEM). In vivostudies were performed using fluorescent imaging in order to trace the movement of capsules in gastrointestinal (GI) tract. The results of in vitrostudies showed that optimized formulation had suitable release profile at different pH values, which were in agreement with the predicted value by RSM. The SEM images revealed that surface coated capsules were smooth and also fluorescent imaging indicated that coated capsules disintegrated at the targeted colon region. These findings provide novel insights for the development of enteric coated capsule in order to specify drug delivery to colon.

The objective of this study was to evaluate the combination of pH-dependent and time-dependent polymers on drug release in order to optimize coating for colonic delivery. Response surface methodology (RSM) based on central composite design (CCD) was employed for formulation optimization. Theophylline was used as model drug and Eudragit®FS 30D and hydroxypropyl methylcellulose (HPMC) were used as pH-dependent and time-dependent polymer, respectively. Dissolution test was carried out using the release conditions as follow: pH 1.2 for 2 h, pH 6.8 for 2 h, pH 7.4 for 3 h and pH 6.8 for 3 h. Scanning electron microscopy (SEM) was applied to observe the morphology of coated capsules. Drug release was evaluated spectrophotometrically. In vivoX-ray imaging study was used to trace the movement and behavior of the capsules in gastrointestinal (GI) tract. The optimized formulation containing 0.5% HPMC and 80% Eudragit FS 30D was prepared according to the software determined levels. There was no drug release for 2 h at pH 1.2 and for 2 h at pH 6.8. Optimum values of drug release were 32.57% and 71.37% at pH 7.4 (7 h) and pH 6.8 (10 h), respectively, which were in agreement with the predicted value by RSM. Surface coated capsules were rougher than gelatin capsules as examined by SEM. X-ray analysis confirmed that coated capsules dissolved at the targeted colon region. The results of this study indicate that the designed system can be potentially used as a carrier for colon delivery of drugs.

Capital structure decision is a challenging problem. The choice of optimal capital structure is very important for the company's continuity and leads to survival in the competitive world. Some researchers have presented variety theories for recognise optimal capital structure and a number of them believe that financial flexibility affects on capital structure as well as firms are able to maximise the firm value through mobilise its financial resources. So, due to importance of this matter, in this study MLP and RBF methods are used to review of the relationship between financial flexibility and capital structure of firms. We are using financial flexibility variables as input data and capital structure as output data. Experimental results indicate that both of different sub-models of NN (MLP and RBF) are good tools for predicting the outputs based on inputs and there is an effective relationship between financial flexibility and capital structure as well.

Health problems due to heavy metals have become a worldwide concern. Along with its carcinogenicity, arsenic exposure results in impairment of glucose metabolism and insulin secretion as well as altered gene expression and signal transduction. However, the exact mechanism behind the behaviour of arsenic on glucose homeostasis and insulin secretion has not yet been fully understood.

The qanat system is one of the most balanced water recovery methods. The qanat has been a traditional method of water supply in Iran. In arid regions, qanats were invented to deal with water shortages, while, water supply were considered using springs and wells. Qanats have been effective for nearly 3000 years and are still being used as one of the main ways of procuring water for irrigation and agricultural activities. The current study aims to investigate qanats at the Kurdistan Province, Iran. The qanats were dug on a fault zone so that have formed the low rate but the permanent aquifers. Observations indicated this method is applicable for villages by maximum 1,000 persons' population. In addition, this system can meet the need of water in all seasons of the year.

AbstractSulphate and zinc removal from a synthetic wastewater by sulphate-reducing bacteria was evaluated using an anaerobic moving-liquid/fixed-bed bioreactor packed with ceramic media. The system was initially augmented by adding sewage sludge as a source of the bacteria. Calcium sulphate dihydrate as a source of sulphate and sodium lactate as a source of carbon were added to the reactor. The system was operated under batch and anoxic conditions with inlet zinc concentrations from 30 to 110 mg/L at different retention times (4–24 h). After adaptation of the system and reaching a steady-state, for a zinc inlet load of 100 mg/L, a maximum removal of 98.7% was attained with a retention time of 24 h. With an optimum inlet sulphate concentration (1,500 mg/L) and with a retention time of 24 h, a maximum sulphate removal efficiency of about 89.2% was achieved. However, these values were declined by decreasing the retention time. The system showed low capacity to COD removal, e.g. at a COD/loading ratio of 2.26, the effluent COD was eliminated by 35%. The amount of hydrogen sulphide (H2S) produced among the processes, the concentrations of sulphide (S2−) and sulphite () in the effluent were also measured.

A simple and compact telecentric lens based on two hemispheric optical elements arranged in a formation resembling an “hourglass” is proposed and evaluated. Our modeling and experimental results show the ability of this lens in achieving high resolution over a large field of view. A prototype with 500 μm total thickness is built using silicon micromachining methods for a center wavelength of 1500 nm. Experimental measurement shows near-diffraction-limited performance and good telecentricity over an 80° field of view at a numerical aperture of 0.2. All elements of the hourglass lens are in direct contact, and hence the alignment is extremely simple. We believe the proposed lens is a good candidate for compact and low-cost multi-aperture imagers.

Sulphate and zinc removal from a synthetic wastewater by sulphate-reducing bacteria was evaluated using an anaerobic moving-liquid/fixed-bed bioreactor packed with ceramic media. The system was initially augmented by adding sewage sludge as a source of the bacteria. Calcium sulphate dihydrate as a source of sulphate and sodium lactate as a source of carbon were added to the reactor. The system was operated under batch and anoxic conditions with inlet zinc concentrations from 30 to 110 mg/L at different retention times (4–24 h). After adaptation of the system and reaching a steady-state, for a zinc inlet load of 100 mg/L, a maximum removal of 98.7% was attained with a retention time of 24 h. With an optimum inlet sulphate concentration (1,500 mg/L) and with a retention time of 24 h, a maximum sulphate removal efficiency of about 89.2% was achieved. However, these values were declined by decreasing the retention time. The system showed low capacity to COD removal, e.g. at a COD/SO42-loading ratio of 2.26, the effluent COD was eliminated by 35%. The amount of hydrogen sulphide (H2S) produced among the processes, the concentrations of sulphide (S2−) and sulphite (SO32-) in the effluent were also measured.

Although Iran has rich reserves of oil and gas, it should not only rely on these resources and should take policies to develop renewable energies (REs). This study developed two forecasting models (ANN and ARIMA) to estimate the renewable energy generation of Iran. After comparison of the developed models, the best model is chosen to predict the renewable energy generation by 2015. Then the prediction is compared with government plan by the end of the Fifth Five-Year Economic Development Plan. The results indicated that RE generation will increase, but, the government will not meet its objectives of producing 5% of total electric power generation through RE resources.

In this Letter, we present a single-exposure deep-UV projection lithography at 254-nm wavelength that produces nanopatterns in a scalable area with a feature size of 80 nm. In this method, a macroscopic lens projects a pixelated optical mask on a monolayer of hexagonally arranged microspheres that reside on the Fourier plane and image the mask’s pattern into a photoresist film. Our macroscopic lens shrinks the size of the mask by providing an imaging magnification of ∼1.86×10^4, while enhancing the exposure power. On the other hand, microsphere lens produces a sub-diffraction limit focal point—a so-called photonic nanojet—based on the near-surface focusing effect, which ensures an excellent patterning accuracy against the presence of surface roughness. Ray-optics simulation is utilized to design the bulk optics part of the lithography system, while a wave-optics simulation is implemented to simulate the optical properties of the exposed regions beneath the microspheres. We characterize the lithography performance in terms of the proximity effect, lens aberration, and interference effect due to refractive index mismatch between photoresist and substrate.

Due to considerable noise in the industrial environments, wireless packet transmission is usually unreliable. Designing an efficient routing algorithm for these environments poses significant challenges. Current routing algorithms consider the quality of service parameters such as node energies and delay, but packet losses need a novel strategy to compensate for the decline in signal to noise ratio (SNR) in noisy industrial environments. The proposed routing algorithm is based on multi-hop neighbour information. The multi-hop neighbour nodes provide vital information for the source node, enabling it to select the proper relay node. In noisy channel conditions the transmitted packets should meet the deadline and be delivered to the sink node on time. Performance evaluation via simulations indicates significant improvement in reliability, lifetime of network, and real-time performance. The proposed algorithm is more robust than previous methods. The most beneficial features of the proposed algorithm are its uniform distribution of energy among nodes and deliverance of deadline packets with the lowest losses.

The bending performance of standard nanoplasmonic slot waveguides is substantially improved by reducing the leakage loss and reflection in a systematic way. The out-of-plane power leakage is suppressed by using square metallic patches above and below the bend. The in-plane power leakage is reduced by elimination of the asymmetry between the electrical length of the inner and outer corners of the bend. The unwanted reflection is decreased by changing the shape of the outer corner of the bend. The partial reflections caused by the indentations of the modified shape destructively interfere with each other and thereby decrease the unwanted back reflection.

Gear systems are the most useful and essential power transmission systems in the high-speed industry due to their accuracy. It is necessary to make sure that these systems work without defects such as tooth cracks. Therefore, detecting the location and depth of cracks in gear systems is very important. In this research, a new approach is proposed to detect the crack location, and accordingly, some statistical indicators are used to estimate the crack depth in the helical gear tooth. To this end, after explaining the helical gear mesh stiffness and tooth-root crack modeling, the helical gear pair dynamic is modeled. Then, the vibration data of a helical gear system is obtained by an experimental test rig, and the moving average method is undertaken to precisely detect the crack location. The crack depth ratio is estimated using the crest factor, impulse factor, clearance factor, and Srand Sαwhich are applied to the simulation results and the experimental signal. According to these results, the crest factor, impulse factor, and clearance factor calculated the crack depth ratio with a good agreement, and the indicators Srand Sαestimated it with a more significant error. Also, the average of estimated values is calculated, indicating a better result than each indicator alone.

A simple and efficient transmission line model is proposed here to study how the transmission characteristics of photonic crystal waveguides are tailored by introduction of stubs patterned in the photonic crystal lattice. It is shown that band-pass and band-stop optical filters can be easily designed and optimized when stubs of appropriate length are brought in. Since the lengths of the designed stubs are not necessarily integer multiples of the photonic crystal lattice constant, a geometric shift in a portion of the photonic crystal structure is shown to be essential. The proposed model is verified by using a rigorous numerical method. An excellent agreement is observed between the numerical results and the transmission characteristics as extracted by the proposed model.