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Surface acoustic wave (SAW)-based formaldehyde gas sensor using bi-layer nanofilms of bacterial cellulose (BC) and polyethyleneimine (PEI) was developed on an ST-cut quartz substrate using sol-gel and spin coating processes. BC nanofilms significantly improve the sensitivity of PEI films to formaldehyde gas, and reduces response and recovery times. The BC films have superfine filamentary and fibrous network structures, which provide a large number of attachment sites for the PEI particles. Measurement results obtained using in situ diffuse reflectance Fourier transform infrared spectroscopy showed that the primary amino groups of PEI strongly adsorb formaldehyde molecules through nucleophilic reactions, thus resulting in a negative frequency shift of the SAW sensor due to the mass loading effect. In addition, experimental results showed that the frequency shifts of the SAW devices are determined by thickness of PEI film, concentration of formaldehyde and relative humidity. The PEI/BC sensor coated with three layers of PEI as the sensing layer showed the optimal sensing performance, which had a frequency shift of 35.6 kHz for 10 ppm formaldehyde gas, measured at room temperature and 30 % RH. The sensor also showed good selectivity and stability, with a low limit of detection down to 100 ppb.

Mucosal-like ZnS nanostructures were synthesized on surface of ST-cut quartz surface acoustic wave (SAW) device using a chemical bath deposition method for ammonia sensing applications. Results showed the SAW device with ZnS mucosal nanostructures achieved a good sensitivity, e.g., with a frequency shift of ~190 Hz upon exposure to 1 ppm ammonia gas. This is mainly attributed to the large specific surface areas and more active sites on the surfaces of the ZnS mucosal nanostructures. Selectivity of the SAW device with the ZnS mucosal nanostructure for ammonia sensing was excellent in comparisons with those for other types of gases such as hydrogen sulfide, hydrogen, nitrogen dioxide, carbon monoxide and ethanol.

Visual Abstract, Highlights • SMAD4 is the central intracellular mediator of TGF-β pathway. • CM-specific loss of SMAD4 causes cardiac dysfunction independent of fibrotic remodeling. • Deletion CM-SMAD4 affects CM survival. • CM-SMAD4 loss leads to down-regulation of several ion channels’ genes, resulting in cardiac conduction abnormalities. • CM-SMAD4 deletion alters sarcomere shortening kinetics, in parallel with reduction in cardiac myosin-binding protein C levels. • These results demonstrate a fundamental role for CM-SMAD4–dependent TGF-β signaling in adult heart homeostasis., Summary The role of the transforming growth factor (TGF)-β pathway in myocardial fibrosis is well recognized. However, the precise role of this signaling axis in cardiomyocyte (CM) biology is not defined. In TGF-β signaling, SMAD4 acts as the central intracellular mediator. To investigate the role of TGF-β signaling in CM biology, the authors deleted SMAD4 in adult mouse CMs. We demonstrate that CM-SMAD4–dependent TGF-β signaling is critical for maintaining cardiac function, sarcomere kinetics, ion-channel gene expression, and cardiomyocyte survival. Thus, our findings raise a significant concern regarding the therapeutic approaches that rely on systemic inhibition of the TGF-β pathway for the management of myocardial fibrosis.

Economic unit commitment is a mix-integer large scale optimization problem calling for powerful and efficient tools. On the other hand, environmental impact related to the power generation is attracting increasing attentions due to the global warming trend and urgent calls for sustainable energy development. In this paper, the dual objectives of economic and emission unit commitment is converted into a single objective problem. For solving this, a novel binary Jaya optimization is proposed and integrated with lambda iteration method. The proposed binary Jaya method is inspired by the Jaya evolution and generates binary bits from a v-shape transfer function. Numerical study demonstrates the significant improvement of the binary Jaya in regarding the convergence speed for solving unit commitment problem. The solution distributions of the both objectives also show the effective of the proposed methods.

As a novel family member of the redox flow batteries (RFBs), the single flow zincnickel battery (ZNB) without ion exchange membranes has attracted a lot of interests in recent years due to the high charging and discharging efficiencies. To understand the electrical behaviour is a key for proper battery management system. Unlike the electrochemical mechanism models and equivalent circuit models, the neural network based black-box model does not need knowledge about the electrochemical reactions and is a promising and adaptive approach for the ZNB battery modelling. In this paper, a compact radial basis function neural network is developed using a two-stage layer selection strategy to determine the network structure. While Jaya optimization is utilized to determine the non-linear parameters in the selected hidden nodes of the resultant RBF neural network (RBF-NN) model. The proposed method is implemented to model the ZNB to capture the non-linear electric behaviours through the readily measurable input signals. Experimental results manifest the accurate prediction capability of the resultant neural model and confirm the effectiveness of the proposed approach.

Mo and Al2O3-Mo coatings are fabricated on a low-carbon steel substrate using atmospheric plasma spraying. The microstructure and mechanical properties of two as-sprayed coatings, with a particular focus on the tribological behaviors from room temperature to 300 °C, are comparatively investigated in this study. Microstructural analysis of the coatings shows that the porosity of the Al2O3-Mo coating is higher than that of Mo coating. The addition of Al2O3 particles reduces the coating–substrate adhesion strength. The Al2O3-Mo coating, in comparison to the Mo coating, shows improved mechanical properties, such as hardness and wear resistance. The friction coefficients of both coatings increase with further increases in test temperatures. The friction coefficient of the Al2O3-Mo coating, tested above 100 °C, is lower than that of the Mo coating. The wear failure mechanisms of the two coatings are delamination, brittle fracture, oxidation and adhesion wear. In addition, local plastic deformation was also found in the Mo coating.

In order to solve the power quality issues facing by Smart Grid with the rapidly growing of renewable energy sources and types, a data-driven approach to detect transient evens using Artificial Neural Network modeling and optimization is proposed in this paper. This approach is realized by building a detection model based on the historic dataset, using statistical processing strategy and modeling methods. To be specific, a fault reconstruction stage is first designed to pre-process the group of dataset to check the synchronization of different signals and roughly detect the transients or faults that most likely happened. Then, the unsynchronized signal is further processed using a detection model. In order to improve the model accuracy without adding more inputs or neural network nodes, a recently proposed optimization method named JAYA is applied to tune the parameters of the network, with a simple one phase of evolutionary process. At last, the linear residuals are generated and modeled using partial Principal Component Analysis, and only $T^{2}$ statistic is calculated and monitored instead of the traditional two statistics, thus the new detection scheme is easier and faster to apply. The proposed method is demonstrated to be effective using real-system experiment, and it is a reliable monitoring scheme to improve the level of safety for Smart Grid.

In this paper, an energy consumption monitoring platform for the college compus has been developed. The implemented platform can realize the distributed monitoring and centralized control & management for the real-time energy and water consumption data for four-level measurement. It can provide data analysis, data storage, information remote transmission and intuitive display to the administrative control center and personnel. Furthermore, it can realize the water metering balance and appropriate public air-conditioner energy adjusting consumption. The water and electricity consumption of the student dormitories and office buildings can be monitored, remotely measured and intelligently paid, possessing the antitheft function. Besides, the specific energy APPs are also developed to control the terminals remotely via the mobile phone. The designed energy monitoring system has been implemented in the compus successfully.

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Background: There is lack of further observations on the microstructure and material property of callus during bone defect healing and the relationships between callus properties and the mechanical strength. Methods: Femur bone defect model was created in rabbits and harvested CT data to reconstruct finite element models at 1 and 2 months. Three types of assumed finite element models were compared to study the callus properties, which assumed the material elastic property as heterogeneous (R-model), homogenous (H-model) or did not change from 1 to 2 months (U-model). Results: The apparent elastic moduli increased at 2 months (from 355.58 ± 132.67 to 1139.30 ± 967.43 MPa) in R-models. But there was no significant difference in apparent elastic moduli between R-models (355.58 ± 132.67 and 1139.30 ± 967.43 MPa) and H-models (344.79 ± 138.73 and 1001.52 ± 692.12 MPa) in 1 and 2 months. A significant difference of apparent elastic moduli was found between the R-model (1139.30 ± 967.43 MPa) and U-model group (207.15 ± 64.60 MPa) in 2 months. Conclusions: This study showed that the callus structure stability remodeled overtime to achieve a more effective structure, while the material quality of callus tissue is a very important factor for callus strength. At the meantime, this study showed an evidence that the material heterogeneity maybe not as important as it is in bone fracture model.

Integrated community energy systems have attracted considerable attention due to their capabilities in supporting distributed generation integration and providing various energy services to customers. However, the rising use of gas-fired generations at the community level is pushing the gas distribution network to its operational boundaries and preventing its further applications. This paper investigates the dynamic interactions and mutual dependence between community energy systems and the gas network through an integrated energy system model. The model incorporates the dynamic behaviors of the gas network, distributed generations and the relevant energy management system. Based on this model, disturbance propagations between the gas network and communities are analyzed from the viewpoint of energy exchanges. Numerical results demonstrate that the change of loads and solar panel outputs can cause large pressure drops of the gas network when microturbines are set to compensate for these variations, and the pressure drop can affect the operation of other gas-fired equipment in surrounding areas. The results also show that different communities can influence each other through the gas network, which indicates some coordination is required in order to restrain adverse interactions as well as their impacts on the gas network.

Nearly every form of the heart disease is associated with myocardial fibrosis, which is characterized by the accumulation of activated cardiac fibroblasts (CFs) and excess deposition of extracellular matrix (ECM). Although, CFs are the primary mediators of myocardial fibrosis in a diseased heart, in the traditional view, activated CFs (myofibroblasts) and resulting fibrosis were simply considered the secondary consequence of the disease, not the cause. Recent studies from our lab and others have challenged this concept by demonstrating that fibroblast activation and fibrosis are not simply the secondary consequence of a diseased heart, but are crucial for mediating various myocardial disease processes. In regards to the mechanism, the vast majority of literature is focused on the direct role of canonical SMAD-2/3-mediated TGF-β signaling to govern the fibrogenic process. Herein, we will discuss the emerging role of the GSK-3β, β-catenin and TGF-β1-SMAD-3 signaling network as a critical regulator of myocardial fibrosis in the diseased heart. The underlying molecular interactions and cross-talk among signaling pathways will be discussed. We will primarily focus on recent in vivo reports demonstrating that CF-specific genetic manipulation can lead to aberrant myocardial fibrosis and sturdy cardiac phenotype. This will allow for a better understanding of the driving role of CFs in the myocardial disease process. We will also review the specificity and limitations of the currently available genetic tools used to study myocardial fibrosis and its associated mechanisms. A better understanding of the GSK-3β, β-catenin and SMAD-3 signaling network may provide a novel therapeutic target for the management of myocardial fibrosis in the diseased heart.

The role of canonical transforming growth factor-β (TGF-β) pathway is well recognized in fibroblast biology and fibrosis in diseased hearts. However, its role in cardiomyocyte (CM) biology is not clear. SMAD4 is the central intracellular mediator of canonical TGF-β signaling. Herein, we investigate the role of SMAD4 in CM-biology and cardiac pathophysiology. SMAD4 homozygous floxed ( SMAD4 fl/fl ) and heterozygous floxed ( SMAD4 fl/- ) mice were crossed with α-myosin heavy chain (Mer-Cre-Mer) to create conditional CM-specific SMAD4-KO ( SMAD4 fl/fl Cre +/- ) and SMAD4 haploinsufficiency ( SMAD4 fl/- Cre +/- ), respectively. At 10 Wks of age, mice were subjected to well established tamoxifen diet protocol for 2 Wks. Echocardiographic analysis at 4 Wks post-tamoxifen treatment reveals that CM-specific loss of SMAD4 leads to dilatative ventricular remodeling as reflected by significantly increased LVIDs. This dilatative remodeling was associated with severe ventricular dysfunction as reflected by significantly reduced ejection fraction (EF) and fractional shortening (FS). Both HW/BW and LW/BW were significantly elevated in SMAD4 KO mice, suggesting pathological hypertrophy and heart failure in KOs. Analysis of Masson trichrome stained heart sections reveals a marked increase in fibrosis in the KO hearts. Q-PCR analysis showed the re-expression of fetal gene program (ANP, BNP), further confirming pathological remodeling in the KO hearts. As the heart functions of heterozygous mice and littermate controls were comparable at baseline, we stress them with TAC surgery. Consistent with KO findings, at 4 Wks post-TAC, heterozygous mice demonstrated characteristic heart failure phenotype. Taken together, these findings suggest that SMAD4 is required to maintain basal cardiac function and to prevent adverse ventricular remodeling in a pressure-overloaded heart.

By supplying thermal and electric energies to host facilities, microgrids with combined heat and power can enhance the resilience of urban energy systems. However, the increasing use of gas-fired distributed generations is pushing gas distribution networks to their operating limits, which may cause significant adverse impacts on microgrids. This paper investigates the interactions between gas networks and microgrids from the viewpoint of integrated energy systems. Four operating modes of microgrids are discussed to describe their connections with external energy networks. A novel model for gas-fired distributed generations, particularly microturbines, is first proposed to capture the interactions between gas networks and microgrids. An integrated system model is then developed to characterize the behaviors of the interrelated gas network and microgrids under different scenarios. Numerical results demonstrate that the variation of microturbine outputs may cause a large pressure drop of the gas network, especially during the transient process of gas flow adjustments. The results also reveal that microgrids can alter the operations among themselves through the accessed gas network.

Background The amino acid response ( AAR ) is an evolutionarily conserved protective mechanism activated by amino acid deficiency through a key kinase, general control nonderepressible 2. In addition to mobilizing amino acids, the AAR broadly affects gene and protein expression in a variety of pathways and elicits antifibrotic, autophagic, and anti‐inflammatory activities. However, little is known regarding its role in cardiac stress. Our aim was to investigate the effects of halofuginone, a prolyl‐ tRNA synthetase inhibitor, on the AAR pathway in cardiac fibroblasts, cardiomyocytes, and in mouse models of cardiac stress and failure. Methods and Results Consistent with its ability to inhibit prolyl‐ tRNA synthetase, halofuginone elicited a general control nonderepressible 2–dependent activation of the AAR pathway in cardiac fibroblasts as evidenced by activation of known AAR target genes, broad regulation of the transcriptome and proteome, and reversal by l ‐proline supplementation. Halofuginone was examined in 3 mouse models of cardiac stress: angiotensin II /phenylephrine, transverse aortic constriction, and acute ischemia reperfusion injury. It activated the AAR pathway in the heart, improved survival, pulmonary congestion, left ventricle remodeling/fibrosis, and left ventricular function, and rescued ischemic myocardium. In human cardiac fibroblasts, halofuginone profoundly reduced collagen deposition in a general control nonderepressible 2–dependent manner and suppressed the extracellular matrix proteome. In human induced pluripotent stem cell–derived cardiomyocytes, halofuginone blocked gene expression associated with endothelin‐1‐mediated activation of pathologic hypertrophy and restored autophagy in a general control nonderepressible 2/ eIF 2α‐dependent manner. Conclusions Halofuginone activated the AAR pathway in the heart and attenuated the structural and functional effects of cardiac stress.

Using a seed layer-free hydrothermal method, ZnO nanorods (NRs) were deposited on ST-cut quartz surface acoustic wave (SAW) devices for ammonia sensing at room temperature. For a comparison, a ZnO film layer with a thickness of 30 nm was also coated onto an ST-cut quartz SAW device using a sol-gel and spin-coating technique. The ammonia sensing results showed that the sensitivity, repeatability and stability of the ZnO NR-coated SAW device were superior to those of the ZnO film-coated SAW device due to the large surface-to-volume ratio of the ZnO NRs.

Shear horizontal surface acoustic waves (SH-SAWs) have been regarded as good candidates for liquid sensing applications but are inefficient in fluid manipulation due to a minimal fluid coupling between the fluid and acoustic waves. However, in this letter, a vertical jetting function was realized using the SH-SAW generated from a 36° Y-X LiTaO3 SAW device. The jetting of the droplet induced by the SH-SAWs was observed nearly along the vertical direction, and the aspect ratio of the liquid beam is proportional to the applied power before breaking up, which is dramatically different from those generated from the conventional Rayleigh SAWs. By conducting theoretical simulation and experimental investigation on the SH-SAWs systematically, we concluded that the wave/energy pressure dissipated into the sessile droplets causes this vertical ejection on the device surface.

We report that cellulose nano-crystals (CNCs) can be used as a sensitive and selective layer in surface acoustic wave (SAW) sensors for in-situ HCl gas detection. CNCs were prepared through directly hydrolysis of cotton fiber and were spin-coated on quartz SAW resonators to form the sensitive layer. The CNCs have been identified to have abundant hydroxyl groups on their surfaces, which can act as the perfect adsorption sites for H2O, which can further act as the active sites for HCl gas adsorption. The absorption of HCl on the CNCs layer, thus leads to an increase of its mass, causing negative responses of the SAW sensors. Ambient humidity and thickness of CNCs layer are found to have significant influences on the responses of the SAW sensor. With an 80-nm-thick CNCs layer, the sensor shows a response of −2 kHz to 1 ppm HCl at 25 °C and relative humidity of 50 % with an excellent selectivity and recovery characteristics.

Gas sensors detecting low HCl gas concentrations used for early detection and continuous monitoring of leakage is of great concern because HCl gas is extremely hazardous. In order to tackle the potential hazardous threats, surface acoustic wave HCl gas sensors based on hydroxyl-rich sol-gel AlOxOHy films are reported. The fabricated SAW sensors show negative frequency shifts with exposure to HCl gas. The negative frequency shift is found to be caused by the increasing weight of sensitive films induced by the adsorption of HCl assisted by the hydroxyl groups and H2O captured on the films. The sensing performance of sensors is highly dependent on the heat-treatment temperature and thickness of films, as well as the ambient humidity because these parameters are highly influential on the amount of hydroxyl groups, H2O on films and the pore volume of films. For a sensor with a 198-nm-thick film annealed at 300 °C, it shows a response of ~ -1.4 KHz to HCl at a low concentration level (0.05 ppm) in an environment with a temperature of 25 °C and a RH value of 40%.

Rubidium (Rb) and strontium (Sr) contents and ratios were analyzed in 197 sediment samples collected from the CGS1 segment of the Chagelebulu Section in the Badain Jaran Desert of China to study millennial scale climate change during the Holocene. The results showed that the Rb and Sr contents and Rb/Sr ratios were low in the samples of dune sands and loess (Mz 5.64Φ) and paleosols, these data displayed 11 changing cycles in alternation of peaks and valleys in the chart. In addition, the Rb contents were positively correlated with Mz (mean particle diameter) and clay contents. While the correlations were weaker, Sr contents also showed a tendency to increase with increases in the Mz and clay contents. Based on a comprehensive analysis of the distribution of Rb and Sr within the CGS1 segment, it appears that the observed Rb and Sr contents and ratios varied in accordance with fluctuations of the East Asian winter and summer monsoons. In terms of timing and climate, low values (C1–C11) resulting from winter monsoons had a strong correlation with cold events in the North Atlantic: the period C1 corresponded to times ranging from 400 a to 1400 a and the periods C2, C3, C4, C7, C9, C10, and C11 corresponded to times of 3000 a, 4000 a, 5900 a, 8200 a, 9400 a, 10,300 a, and 11,000 a, respectively. The cold event C5 (6200 a) was also discovered in the North Atlantic in recent; and C6 (7100 a), C8 (8700 a) were discovered in some other places of China. These cold events indicated by Rb and Sr contents and ratios in the Chagelebulu Section of the Badain Jaran Desert recorded the regional response of global climate change during the Holocene.

Surface acoustic wave (SAW) ammonia gas sensors based on ZnO/SiO2 bi-layer nanofilms on ST-cut quartz surface acoustic wave devices were fabricated and characterized. The ZnO and SiO2 layers were coated onto SAW resonators by combining a sol–gel process and a spin-coating technique. The SEM and AFM results revealed the ZnO/SiO2 bi-layer films had porous structures. The gas sensing results showed that the sensitivity of sensors was dependent on the value of sheet conductivity of the sensing films. As a result, the bi-layer nanofilms were much more sensitive than the single layer films due to their appropriate sheet conductivity, and the absolute response value was dependent on the thickness of the top ZnO layer. The sensor based on the bi-layer nanofilm with 60 nm top ZnO layer showed the best gas sensing property. It exhibited a frequency shift of 2000 Hz in 30 ppm ammonia gas with good repeatability and stability.

Surface acoustic wave (SAW) sensors based on Co 3 O 4 /SiO 2 composite sensing films for ammonia detection were investigated at room temperature. The Co 3 O 4 /SiO 2 composite films were deposited onto ST-cut quartz SAW resonators by a sol–gel method. SEM and AFM characterizations showed that the films had porous structures. The existence of SiO 2 was found to enhance the ammonia sensing property of the sensor significantly. The sensor based on a Co 3 O 4 /SiO 2 composite film, with 50% Co 3 O 4 loading, which had the highest RMS value (3.72), showed the best sensing property. It exhibited a positive frequency shift of 3500 Hz to 1 ppm ammonia as well as excellent selectivity, stability and reproducibility at room temperature. Moreover, a 37% decrease in the conductance of the composite film as well as a positive frequency shift of 12,500 Hz were observed when the sensor was exposed to 20 ppm ammonia, indicating the positive frequency shift was derived from the decrease in film conductance.

Background— Myocardial infarction–induced remodeling includes chamber dilatation, contractile dysfunction, and fibrosis. Of these, fibrosis is the least understood. After myocardial infarction, activated cardiac fibroblasts deposit extracellular matrix. Current therapies to prevent fibrosis are inadequate, and new molecular targets are needed. Methods and Results— Herein we report that glycogen synthase kinase-3β (GSK-3β) is phosphorylated (inhibited) in fibrotic tissues from ischemic human and mouse heart. Using 2 fibroblast-specific GSK-3β knockout mouse models, we show that deletion of GSK-3β in cardiac fibroblasts leads to fibrogenesis, left ventricular dysfunction, and excessive scarring in the ischemic heart. Deletion of GSK-3β induces a profibrotic myofibroblast phenotype in isolated cardiac fibroblasts, in post–myocardial infarction hearts, and in mouse embryonic fibroblasts deleted for GSK-3β. Mechanistically, GSK-3β inhibits profibrotic transforming growth factor-β1/SMAD-3 signaling via interactions with SMAD-3. Moreover, deletion of GSK-3β resulted in the significant increase of SMAD-3 transcriptional activity. This pathway is central to the pathology because a small-molecule inhibitor of SMAD-3 largely prevented fibrosis and limited left ventricular remodeling. Conclusions— These studies support targeting GSK-3β in myocardial fibrotic disorders and establish critical roles of cardiac fibroblasts in remodeling and ventricular dysfunction.

Love mode surface acoustic wave devices based on ZnO/42° YX LiTaO3 were characterized with the thickness of the sputtered ZnO guiding layer varied from 250 nm to 1.18 μm. Phase velocity, temperature coefficient of resonant frequency, sensitivity, electromechanical coupling coefficient and humidity sensing of the Love mode SAW devices were studied as a function of the ZnO layer thickness. With increasing ZnO thickness over the range of thickness values we have examined, the sensitivity of 42° YX LiTaO3 to liquid loading increased and the values of electromechanical coupling coefficient decreased. The device with a thickness of 250 nm showed the best humidity response. ZnO nanorods were grown on this device and its humidity sensing performance has been further improved due to their large surface-to-volume ratio of the ZnO nanorods.

This paper addresses the long-term corrosion behavior of microarc oxidation coated Mg alloys immersed in simulated body fluid for 28 days. The coatings on AZ31 Mg alloys were produced in the electrolyte of sodium phosphate (Na3PO4) at the concentration of 20 g/L, 30 g/L and 40 g/L, respectively. Scanning electron microscope (SEM) and optical micrograph were used to observe the microstructure of the samples before and after corrosion. The composition of the MAO coating and corrosion products were determined by X-Ray Diffraction (XRD). Corrosion product identification showed that hydroxyapatite (HA) was formed on the surface of the corroded samples. The ratio of Ca/P in HA determined by the X-ray Fluorescence (XRF) technique showed that HA is an acceptable biocompatible implant material. The potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) were employed to characterize the corrosion rate and the electrochemical impedance. The corrosion resistance of the coated Mg alloys can be enhanced by optimizing the electrolyte concentrations for fabricating samples, and is enhanced after immersing the coated samples in simulated body fluid for more than 14 days. The enhanced corrosion resistance after long-term immersion is attributed to a corrosion product layer formed on the sample surface. The inhibition mechanism of the corrosion process is discussed and presented with an animation.

Microarc oxidation coatings were fabricated on AZ31 magnesium alloy in the electrolyte of sodium phosphate. Potentiodynamic polarization and electrochemical impedance spectroscopy tests were employed to investigate the electrochemical corrosion behavior. The corroded surface was characterized by an optical microscope and X-ray diffraction. The influence of chloride ion concentration on the corrosion resistance of microarc oxidation coated AZ31 alloy is discussed. The corrosion current density enlarged ratio and the charge transfer resistance reduced ratio indicated that the extent of the corrosion damage of microarc oxidation coated AZ31 alloy is much higher when chloride ion concentration is greater than 5%. A corrosion mechanism related to the effect of chloride ion concentrations on the corrosion behavior is proposed.

This paper presents a preliminary study of developing a novel platform for big data management, processing and analysis of modern power systems. The framework comprises a big data acquisition subsystem, a big data analysis subsystem, a decision-making assistance subsystem and an information integration subsystem. For the big data management system, a novel structure is designed according to three different data resources, including database, data files and data stream. Further, powerful open-source computation algorithms and self-developed novel intelligent methods are integrated in the big data analysis system. To be specific, our early work on statistical processing monitoring (Principal Component Analysis (PCA)), advanced modelling methods (Fast Recursive Algorithm (FRA)) and newly developed optimization method (Teaching-Learning Based Optimization (TLBO)) are integrated into a self-developed analysis module. Thus, with the novel big data acquisition structure and data processing engine, the proposed platform can provide a powerful tool for big data analytic based Smart Grid monitoring.

The electrochemical corrosion behavior of microarc oxidation (MAO) coatings produced at various oxidation times on AZ31 Mg alloys was studied in a simulated body fluid (SBF). The potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) were used to characterize the corrosion behavior. The influences of the MAO time on the microstructure and corrosion properties are discussed. The initial porosity of the MAO coating was evaluated by the potentiodynamic polarization method. Post-corrosion phase identification showed that hydroxyapatite (HA) was formed on the surface of the samples. The ratio of Ca/P in HA was determined by the X-ray Fluorescence (XRF) technique. A physical model of the corrosion process with equivalent circuits at different corrosion stages is proposed.

The aim of this study was to evaluate the effects of the novel nanopore Ti surface and amine-terminated Ti surface on peri-implant bone formation and bone-implant bonding strength in a rabbit tibiae model. Characterization of the modified Ti surface, such as root-mean square roughness, contact angle, and surface energy was evaluated using scanning electron microscopy, atomic force microscopy, and a Contact Angle Measurement System, respectively. The results from alkali treatment indicated that an interpenetrating dimensional porosity surface had been formed, whose morphology was similar to the amine-terminated surface of self-assembled monolayers after alkali treatment. The micro-CT demonstrated that the amine-terminated surface had higher bone volume ratio and higher mean trabecular thickness after 4 weeks of implantation. The push-out test and histological examination showed no significant differences in the maximal force and bone-implant contact between the terminated surface and alkali-treated surface. These novel dimensional nanoporous structures can significantly improve the initial stabilization and the osseointegration.

This paper addresses the effect of pulse frequency on the corrosion behavior of microarc oxidation (MAO) coatings on AZ31 Mg alloys in simulated body fluid (SBF). The MAO coatings were deposited by a pulsed DC mode at four different pulse frequencies of 300 Hz, 500 Hz, 1000 Hz and 3000 Hz with a constant pulse ratio. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) tests were used for corrosion rate and electrochemical impedance evaluation. The corroded surfaces were examined by X-ray diffraction (XRD), X-ray fluorescence (XRF) and optical microscopy. All the results exhibited that the corrosion resistance of MAO coating produced at 3000 Hz is superior among the four frequencies used. The XRD spectra showed that the corrosion products contain hydroxyapatite, brucite and quintinite. A model for corrosion mechanism and corrosion process of the MAO coating on AZ31 Mg alloy in the SBF is proposed.

Dense oxidation coatings have been successfully developed on biocompatible AZ31 magnesium alloy, using microarc oxidation technique, to improve the corrosion resistance. Three different deposition voltages of 250, 300, and 350 V have been employed. The effect of voltage on the coating corrosion resistance has been evaluated through electrochemical experiments in a simulated body fluid (SBF) up to 7 days. Potentiodynamic polarization and electrochemical impedance spectroscopy scans were performed in the SBF solution, followed by optical microscopy surface inspection. The results indicate that the corrosion rates of the coatings are in the order of 250 300 > 350 V. Both the electrochemical tests and the surface inspection suggest that the 250 V coating has the highest corrosion resistance, with lowest corrosion current density, highest Rct, and the best surface quality.

Monolayer ZrO 2 sol–gel and physical vapor deposition (PVD) films were prepared by spin method and electron beam evaporation method, respectively. Monolayer sol–gel SiO 2 films were prepared with the dip-coating method from acid and base catalyzed SiO 2 sols, respectively. Some of the SiO 2 base films were subsequently treated in saturated ammonia gas for 20 h. The laser induced damage threshold (LIDT) of each film was measured. Properties of the films were analyzed by using Stanford photo-thermal solutions (SPTSs), ellipsometer, atomic force microscopy (AFM) and optical microscopy. The experimental results showed that porous ratio is an essential factor to decide the LIDT for sol–gel films, which benefits the pressure exerted on the film or substrate by the moving particle to dissipate. The films with lower thermal absorption and higher porous ratio have higher LIDT.

This study described relative humidity (RH) sensing using a graphene/128° YX LiNbO3 surface acoustic wave (SAW) device. The resonant frequency of the device decreased in a two-stage manner as the RH increased. For a low RH range (RH 50%), a frequency downshift of 2.6 kHz per 1% RH change was obtained, which was due to the change in elastic grapheme properties. The mass loading effect of the water layer was less effective at high temperature, resulting in a lower temperature coefficient of resonant frequency (TCF).

Wind direction and speed are both crucial factors for wind farm layout, however, the relationship between the two factors has not been well addressed. To optimize wind farm layout, this study aims to statistically explore wind speed characteristics under different wind directions and wind direction characteristics. For this purpose, the angular&ndash, linear model for approximating wind direction and speed characteristics were adopted and constructed with specified marginal distributions. Specifically, Weibull&ndash, Weibull distribution, lognormal&ndash, lognormal distribution and Weibull&ndash, lognormal distribution were applied to represent the marginal distribution of wind speed. Moreover, the finite mixture of von Mises function (FVMF) model was used to investigate the marginal distribution of wind direction. The parameters of those models were estimated by the expectation&ndash, maximum method. The optimal model was obtained by comparing the coefficient of determination value (R2) and Akaike&rsquo, s information criteria (AIC). In the numerical study, wind data measured at a featured wind farm in north China was adopted. Results showed that the proposed joint distribution function could accurately represent the actual wind data at different heights, with the coefficient of determination value (R2) of 0.99.

Two-layer ZrO 2 /SiO 2 and SiO 2 /ZrO 2 films were deposited on K9 glass substrates by sol–gel dip coating method. X-ray photoelectron spectroscopy (XPS) technique was used to investigate the diffusion of ZrO 2 /SiO 2 and SiO 2 /ZrO 2 films. To explain the difference of diffusion between ZrO 2 /SiO 2 and SiO 2 /ZrO 2 films, porous ratio and surface morphology of monolayer SiO 2 and ZrO 2 films were analyzed by using ellipsometry and atomic force microscopy (AFM). We found that for the ZrO 2 /SiO 2 films there was a diffusion layer with a certain thickness and the atomic concentrations of Si and Zr changed rapidly; for the SiO 2 /ZrO 2 films, the atomic concentrations of Si and Zr changed relatively slowly, and the ZrO 2 layer had diffused through the entire SiO 2 layer. The difference of diffusion between ZrO 2 /SiO 2 and SiO 2 /ZrO 2 films was influenced by the microstructure of SiO 2 and ZrO 2 .

The sol–gel monolayer silica films on K9 glass substrates were prepared with the dip method, and then treated in saturated ammonia gas. The laser-induced damage threshold (LIDT) of silica films with and without ammonia treatment was measured. Properties of the films were analyzed by using Stanford photo-thermal solutions (SPTS), ellipsometry, atomic force microscopy (AFM), and optical microscopy to study the effect of ammonia treatment on laser-induced damage of sol–gel monolayer silica film under laser irradiation. The experimental results showed that compared with the as-grown silica film, the silica film with ammonia treatment had larger absorption and smaller porous ratio, and it had smaller LIDT. Considering the improved abrasion resistance of films with ammonia treatment, a trade-off is always needed between abrasion resistance and LIDT in practice.

An ultraviolet (UV) sensor based on nanostructured zinc oxide (ZnO)/Si surface acoustic wave (SAW) devices was studied in this paper. The ZnO films sputtered onto Si (100) substrate showed a preferred (0002) orientation and good photoluminescence emission. For an SAW device with a wavelength of 64 μm, a frequency downshift of ~1.4 kHz was observed for the Rayleigh mode under a UV light intensity of 0.6 mW cm−2, whereas the frequency downshift for the Rayleigh mode was increased to 8.3 kHz after integrating ZnO nanorods (NRs) in the ZnO/Si SAW devices. For the SAW device with a wavelength of 20 μm irradiated under a UV light intensity of 0.6 mW cm−2, a frequency downshift of 25 kHz for the Sezawa mode was obtained compared to a shift of 12 kHz for the Rayleigh mode. After depositing ZnO NRs, the resonant frequency for the Rayleigh mode was increased to 27.4 kHz under the same UV intensity illumination, due to the significant increase in surface-to-volume ratio.

By sensitizing with 514 nm green light, 488 nm blue light and 390 nm ultraviolet light, respectively, recording with 633 nm red light, effect of wavelength of sensitizing light on holographic storage properties in LiNbO3:Fe:Ni crystal is investigated in detail. It is shown that by shortening the wavelength of sensitizing light gradually, nonvolatile holographic recording properties of oxidized LiNbO3:Fe:Ni crystal is optimized gradually, 390 nm ultraviolet light is the best as the sensitizing light. Considering the absorption of sensitizing light, to obtain the best performance in two-center holographic recording we must choose a sensitizing wavelength that is long enough to prevent unwanted absorptions (band-to-band, etc.) and short enough to result in efficient sensitization from the deep traps. So in practice a trade-off is always needed. Explanation is presented theoretically. (c) 2005 Elsevier GmbH. All rights reserved.

We have investigated ultraviolet (UV) photorefractive effect of lithium niobate doubly doped with Ce and Cu. It is found the diffraction efficiency shows oscillating behavior Under UV-1ight-recording. A model in which electrons and holes can be excited from impurity centers in the UV region is proposed to study the oscillatory behavior of the diffraction efficiency. Oil the basis of the material equations and the coupled-wave equations, we found that the oscillatory behavior is due to the oscillation of the relative spatial phase shift Phi. And the electron-hole competition may cause the oscillation of the relative spatial phase shift. A switch point from electron grating to hole grating is chosen to realize nonvolatile readout by a red light with high sensitivity (0.4 cm/J). (c) 2005 Elsevier GmbH. All rights reserved.

Sol–gel (ZrO2/SiO2)12 ZrO2 films were prepared by spin coating method. The reflectivity spectrum of the films was measured with a Lambda 900 spectrometer. In order to investigate laser-induced damage threshold (LIDT) characteristic of highly reflective films, one-layer ZrO2 and SiO2 films, two-layer ZrO2/SiO2 and SiO2/ZrO2 films were also prepared by spin coating method. LIDT of each film was measured. Damage morphology after laser irradiation was characterized by optical microscopy (Nikon E600K). The experimental results showed that the reflectivity of (ZrO2/SiO2)12 ZrO2 film at 1064 nm and 355 nm wavelength is 99.7%. The LIDT results decreases as the number of layer of films increases. All the films have similar damage morphology. The experimental results are explained by the different temperature profiles of the films.

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearlyauto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

Nanocrystalline ZnO films with both C-axis vertical grown and inclined angled grown were sputter-deposited onto aluminium foils (50 μm thick) and characterised for using as flexible ultrasonic transducers. As-deposited C-axis grown ZnO films were annealed at different temperatures up to 600 °C to enhance film crystallinity and reduce film stress. The C-axis grown ZnO film on the Al foil were bonded onto steel plates, and the pulse-echo tests verified a good performance (with dominant longitudinal waves) of the ultrasonic transducers made from both as-deposited and post-annealed films. Inclined angled ZnO films on the Al foil glued onto steel plates generated mixed shear and longitudinal waves in the pulse-echo test.

This paper presents the application of a fault detection method based on the principal component analysis (PCA) and support vector machine (SVM) for the detection and classification of faults in power system transmission lines. Consider that the data may be huge with a number of strongly correlated variables, method which incorporates both the principal component analysis (PCA) and support vector machine (SVM) is proposed. This algorithm has two stages. The first stage involves the use of the PCA to reduce the dimensionality as well as to find violating point of the signals according to the confidential limit. The features of each fault extracted from the data are used in the second stage to construct SVM networks. The second stage is to use pattern recognition method to distinguish the phase of the faulty situation. The proposed scheme is able to solve the problems encountered in traditional magnitude and frequency based methods. The benefits of this improvement are demonstrated.

Anti-islanding protection is becoming increasingly important due to the rapid installation of distributed generation from renewable resources like wind, tidal and wave, solar PV, bio-fuels, as well as from other resources like diesel. Unintentional islanding presents a potential risk for damaging utility plants and equipment connected from the demand side, as well as to public and personnel in utility plants. This paper investigates automatic islanding detection. This is achieved by deploying a statistical process control approach for fault detection with the real-time data acquired through a wide area measurement system, which is based on Phasor Measurement Unit (PMU) technology. In particular, the principal component analysis (PCA) is used to project the data into principal component subspace and residual space, and two statistics are used to detect the occurrence of fault. Then a fault reconstruction method is used to identify the fault and its development over time. The proposed scheme has been used in a real system and the results have confirmed that the proposed method can correctly identify the fault and islanding site.

An oscillatory characteristic of diffraction is observed du ring holographic recording period in an oxidized LiNbO 3 :Cr:Cu crystal with 514 nm green light as the recording light and 390 nm UV light as the sensitizing light. The optimal switching time from the recording step to the fixing step for high diffraction of a fixed hologram is studied. It is shown that switching after the first diffraction maximum leads to hi gher fixed diffraction efficien cy. The theoretical explanation is presented according to time-space dynamic theory of the nonvolatile holographic recording in doubly-doped LiNbO 3 crystals. Keywords: optimization of fixed diff raction efficiency, LiNbO 3 :Cr:Cu, two-color holographic recording, optimal switching time 1. INTRODUCTION Lithium niobate (LiNbO 3 ) has been extensively studied as one of the most promising materials for volume holographic data storage systems. Its advantages are the large crystal sizes available which allow for increased capacity and high angular selectivity, long storage lifetime among photorefractive crystals, and high diffraction efficiencies. It is known that the photorefractive effect in LiNbO

Two-dimensional phase unwrapping (PhU) is one of the most important processing steps in optical phase-shifting interferometry. It aims to reconstruct the continuous phase field, but in fact, it becomes very difficult to perform the PhU due to the existence of noise, low modulation, under sampling, discontinuities or other defects. For solving the problem, we present a new PhU method which is based on the local parameter-guided fitting plane. It relies on the basic plane-approximated assumption for phase value of local pixels and is guided by our proposed parameter map- Modulation-Gradient and Pseudo-Correlation (MGPC) parameter map. This new map is the combination of fringe modulation and wrapped phase, thus it's reliable in estimating the quality or goodness of phase data. Meanwhile, the adoption of fitting plane for the 3×3 window of pixels makes the process of PhU very fast. In applications, we offer the simulated and the experimental data to compare our method with the two previously reported path-following unwrapping algorithms. The unwrapped results show our proposed PhU method not only is efficient, but also has higher noise robustness in recovering the true phase field.