Open AccessArticle
Piecewise Function Hysteretic Model for Cold-Formed Steel Shear Walls with Reinforced End Studs
Appl. Sci. 2017, 7(1), 94; doi:10.3390/app7010094 (registering DOI) -
Abstract
Cold-formed steel (CFS) shear walls with concrete-filled rectangular steel tube (CFRST) columns as end studs can upgrade the performance of mid-rise CFS structures, such as the vertical bearing capacity, anti-overturning ability, shear strength, and fire resistance properties, thereby enhancing the safety of structures.
[...] Read more.
Cold-formed steel (CFS) shear walls with concrete-filled rectangular steel tube (CFRST) columns as end studs can upgrade the performance of mid-rise CFS structures, such as the vertical bearing capacity, anti-overturning ability, shear strength, and fire resistance properties, thereby enhancing the safety of structures. A theoretical hysteretic model is established according to a previous experimental study. This model is described in a simple mathematical form and takes nonlinearity, pinching, strength, and stiffness deterioration into consideration. It was established in two steps: (1) a discrete coordinate method was proposed to determine the load-displacement skeleton curve of the wall, by which governing deformations and their corresponding loads of the hysteretic loops under different loading cases can be obtained; afterwards; (2) a piecewise function was adopted to capture the hysteretic loop relative to each governing deformation, the hysteretic model of the wall was further established, and additional criteria for the dominant parameters of the model were stated. Finally, the hysteretic model was validated by experimental results from other studies. The results show that elastic lateral stiffness Ke and shear capacity Fp are key factors determining the load-displacement skeleton curve of the wall; hysteretic characteristics of the wall with reinforced end studs can be fully reflected by piecewise function hysteretic model, moreover, the model has intuitional expressions with clear physical interpretations for each parameter, paving the way for predicting the nonlinear dynamic responses of mid-rise CFS structures. Full article
Figures

Figure 1

Open AccessArticle
Analysis of MPPT Failure and Development of an Augmented Nonlinear Controller for MPPT of Photovoltaic Systems under Partial Shading Conditions
Appl. Sci. 2017, 7(1), 95; doi:10.3390/app7010095 (registering DOI) -
Abstract
The output–voltage–power curves of photovoltaic (PV) arrays exhibit complex multi-peak shapes when local shading occurs. The existing maximum power point tracking (MPPT) algorithms to solve this multi-peak problem do not consider the possibility of tracking failures due to the time of the irradiance
[...] Read more.
The output–voltage–power curves of photovoltaic (PV) arrays exhibit complex multi-peak shapes when local shading occurs. The existing maximum power point tracking (MPPT) algorithms to solve this multi-peak problem do not consider the possibility of tracking failures due to the time of the irradiance change. In this study, first, the reason for the failure of the global MPPT (GMPPT) algorithm is analyzed based on the PV array mathematical model and its output characteristics under partial shading conditions; then, in order to estimate the MPP voltage, an artificial neural network (ANN) is trained using environmental information such as irradiance. A hybrid MPPT method using an augmented state feedback precise linearization (AFL) controller combined with an ANN is proposed to solve problems such as the shift of the static operating point of the DC/DC boost converter. Finally, numerical simulations are conducted to validate the proposed method and eliminate the possibility of MPPT failure. The proposed hybrid MPPT method is compared with the conventional perturb and observe (P & O) method and the improved P & O method through simulations. Using the proposed neural network and nonlinear control strategy, the MPP can be tracked rapidly, accurately, and statically, proving that the method is feasible and effective. Full article
Figures

Figure 1

Open AccessArticle
Measurement of Soy Contents in Ground Beef Using Near-Infrared Spectroscopy
Appl. Sci. 2017, 7(1), 97; doi:10.3390/app7010097 (registering DOI) -
Abstract
Models for determining contents of soy products in ground beef were developed using near-infrared (NIR) spectroscopy. Samples were prepared by mixing four kinds of soybean protein products (Arconet, toasted soy grits, Profam and textured vegetable protein (TVP)) with ground beef (content from 0%–100%).
[...] Read more.
Models for determining contents of soy products in ground beef were developed using near-infrared (NIR) spectroscopy. Samples were prepared by mixing four kinds of soybean protein products (Arconet, toasted soy grits, Profam and textured vegetable protein (TVP)) with ground beef (content from 0%–100%). NIR spectra of meat mixtures were measured with dispersive (400–2500 nm) and Fourier transform NIR (FT-NIR) spectrometers (1000–2500 nm). Partial least squares (PLS) regression with full leave-one-out cross-validation was used to build prediction models. The results based on dispersive NIR spectra revealed that the coefficient of determination for cross-validation (Rcv2) ranged from 0.91 for toasted soy grits to 0.99 for Arconet. The results based on FT-NIR spectra exhibited the best prediction for toasted soy grits (Rcv2 = 0.99) and Rcv2 > 0.98 for the other three soy types. For identification of different types of soy products, support vector machine (SVM) classification was used and the total accuracy for dispersive NIR and FT-NIR was 95% and 83.33%, respectively. These results suggest that either dispersive NIR or FT-NIR spectroscopy could be used to predict the content and the discrimination of different soy products added in ground beef products. In application, FT-NIR spectroscopy methods would be recommended if time is a consideration in practice. Full article
Figures

Open AccessArticle
Beam Grouping Based RS Resource Reuse and De-Contamination in Large Scale MIMO Systems
Appl. Sci. 2017, 7(1), 96; doi:10.3390/app7010096 (registering DOI) -
Abstract
It is well known that large scale multiple-input multiple-output (LS-MIMO) systems are very attractive technology to increase both spectral efficiency (SE) and energy efficiency (EE). However, one of big obstacles to the realization of the LS-MIMO system is the overhead of reference signals
[...] Read more.
It is well known that large scale multiple-input multiple-output (LS-MIMO) systems are very attractive technology to increase both spectral efficiency (SE) and energy efficiency (EE). However, one of big obstacles to the realization of the LS-MIMO system is the overhead of reference signals (RSs), since the number of RS increases as the number of transmitter (TX) antennas increases. In this paper, the RS overhead problem is analyzed, and we propose an RS overhead reduction scheme based on beam grouping, which is called beam grouping based resource reuse (BGRR). The proposed scheme divides one cell into several sectors and reuses the RS resources for the different sectors. The resource conflict is reduced using beam separability. According to the analysis and the simulation results, the proposed scheme can remarkably reduce the RS overhead and improve the SE performance significantly. Full article
Figures

Open AccessArticle
Modeling and Simulation of a Wave Energy Converter INWAVE
Appl. Sci. 2017, 7(1), 99; doi:10.3390/app7010099 (registering DOI) -
Abstract
INGINE Inc. developed its own wave energy converter (WEC) named INWAVE and has currently installed three prototype modules in Jeju Island, Korea. This device is an on-shore-type WEC that consists of a buoy, pulleys fixed to the sea-floor and a power take off
[...] Read more.
INGINE Inc. developed its own wave energy converter (WEC) named INWAVE and has currently installed three prototype modules in Jeju Island, Korea. This device is an on-shore-type WEC that consists of a buoy, pulleys fixed to the sea-floor and a power take off module (PTO). Three ropes are moored tightly on the bottom of the buoy and connected to the PTO via the pulleys, which are moving back and forth according to the motion of the buoy. Since the device can harness wave energy from all six degrees of movement of the buoy, it is possible to extract energy efficiently even under low energy density conditions provided in the coastal areas. In the PTO module, the ratchet gears convert the reciprocating movement of the rope drum into a uni-directional rotation and determine the transmission of power from the relation of the angular velocities between the rope drum and the generator. In this process, the discontinuity of the power transmission occurs and causes the modeling divergence. Therefore, we introduce the concept of the virtual torsion spring in order to prevent the impact error in the ratchet gear module, thereby completing the PTO modeling. In this paper, we deal with dynamic analysis in the time domain, based on Newtonian mechanics and linear wave theory. We derive the combined dynamics of the buoy and PTO modules via geometric relation between the buoy and mooring ropes, then suggest the ratchet gear mechanism with the virtual torsion spring element to reduce the dynamic errors during the phase transitions. Time domain simulation is carried out under irregular waves that reflect the actual wave states of the installation area, and we evaluate the theoretical performance using the capture width ratio. Full article
Figures

Figure 1

Open AccessArticle
Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG
Appl. Sci. 2017, 7(1), 92; doi:10.3390/app7010092 -
Abstract
Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but also contains a large amount
[...] Read more.
Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but also contains a large amount of physiological or disease information. As a result, it has been fully studied in the field of rehabilitation. To correctly interpret and accurately extract the features of MI-EEG signals, many nonlinear dynamic methods based on entropy, such as Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (FE), and Permutation Entropy (PE), have been proposed and exploited continuously in recent years. However, these entropy-based methods can only measure the complexity of MI-EEG based on a single scale and therefore fail to account for the multiscale property inherent in MI-EEG. To solve this problem, Multiscale Sample Entropy (MSE), Multiscale Permutation Entropy (MPE), and Multiscale Fuzzy Entropy (MFE) are developed by introducing scale factor. However, MFE has not been widely used in analysis of MI-EEG, and the same parameter values are employed when the MFE method is used to calculate the fuzzy entropy values on multiple scales. Actually, each coarse-grained MI-EEG carries the characteristic information of the original signal on different scale factors. It is necessary to optimize MFE parameters to discover more feature information. In this paper, the parameters of MFE are optimized independently for each scale factor, and the improved MFE (IMFE) is applied to the feature extraction of MI-EEG. Based on the event-related desynchronization (ERD)/event-related synchronization (ERS) phenomenon, IMFE features from multi channels are fused organically to construct the feature vector. Experiments are conducted on a public dataset by using Support Vector Machine (SVM) as a classifier. The experiment results of 10-fold cross-validation show that the proposed method yields relatively high classification accuracy compared with other entropy-based and classical time–frequency–space feature extraction methods. The t-test is used to prove the correctness of the improved MFE. Full article
Figures

Figure 1

Open AccessArticle
Evaluation of Interlaminar Stresses in Composite Laminates with a Bolt-Filled Hole Using a Linear Elastic Traction-Separation Description
Appl. Sci. 2017, 7(1), 93; doi:10.3390/app7010093 -
Abstract
Determination of the local interlaminar stress distribution in a laminate with a bolt-filled hole is helpful for optimal bolted joint design, due to the three-dimensional (3D) nature of the stress field near the bolt hole. A new interlaminar stress distribution phenomenon induced by
[...] Read more.
Determination of the local interlaminar stress distribution in a laminate with a bolt-filled hole is helpful for optimal bolted joint design, due to the three-dimensional (3D) nature of the stress field near the bolt hole. A new interlaminar stress distribution phenomenon induced by the bolt-head and clamp-up load, which occurs in a filled-hole composite laminate, is investigated. In order to efficiently evaluate interlaminar stresses under the complex boundary condition, a calculation strategy that using zero-thickness cohesive interface element is presented and validated. The interface element is based on a linear elastic traction-separation description. It is found that the interlaminar stress concentrations occur at the hole edge, as well as the interior of the laminate near the periphery of the bolt head. In addition, the interlaminar stresses near the periphery of the bolt head increased with an increase in the clamp-up load, and the interlaminar normal and shear stresses are not at the same circular position. Therefore, the clamp-up load cannot improve the interlaminar stress distribution in the laminate near the periphery of the bolt head, although it can reduce the magnitude of the interlaminar shear stress at the hole edge. Thus, the interlaminar stress distribution phenomena may lead to delamination initiation in the laminate near the periphery of the bolt head, and should be considered in composite bolted joint design. Full article
Figures

Open AccessArticle
Cooperative Multi-UAV Collision Avoidance Based on Distributed Dynamic Optimization and Causal Analysis
Appl. Sci. 2017, 7(1), 83; doi:10.3390/app7010083 -
Abstract
A critical requirement for unmanned aerial vehicles (UAV) is the collision avoidance (CA) capability to meet safety and flexibility issues in an environment of increasing air traffic densities. This paper proposes two efficient algorithms: conflict detection (CD) algorithm and conflict resolution (CR) algorithm.
[...] Read more.
A critical requirement for unmanned aerial vehicles (UAV) is the collision avoidance (CA) capability to meet safety and flexibility issues in an environment of increasing air traffic densities. This paper proposes two efficient algorithms: conflict detection (CD) algorithm and conflict resolution (CR) algorithm. These two algorithms are the key components of the cooperative multi-UAV CA system. The CD sub-module analyzes the spatial-temporal information of four dimensional (4D) trajectory to detect potential collisions. The CR sub-module calculates the minimum deviation of the planned trajectory by an objective function integrated with track adjustment, distance, and time costs, taking into account the vehicle performance, state and separation constraints. Additionally, we extend the CR sub-module with causal analysis to generate all possible solution states in order to select the optimal strategy for a multi-threat scenario, considering the potential interactions among neighboring UAVs with a global scope of a cluster. Quantitative simulation experiments are conducted to validate the feasibility and scalability of the proposed CA system, as well as to test its efficiency with variable parameters. Full article
Figures

Figure 1

Open AccessArticle
The Role of Overloading on the Reduction of Residual Stress by Cyclic Loading in Cold-Drawn Prestressing Steel Wires
Appl. Sci. 2017, 7(1), 84; doi:10.3390/app7010084 -
Abstract
Prestressing steel wires are commonly used as reinforcement elements in structures bearing fatigue loads. These wires are obtained by a conforming process called cold drawing, where a progressive reduction of the wire diameter is produced, causing residual stress in the commercial wire. The
[...] Read more.
Prestressing steel wires are commonly used as reinforcement elements in structures bearing fatigue loads. These wires are obtained by a conforming process called cold drawing, where a progressive reduction of the wire diameter is produced, causing residual stress in the commercial wire. The aim of this paper is to analyze the effect of diverse in-service cyclic loading conditions (cyclic loading and cyclic loading with overload) on such a residual stress field. To achieve this goal, firstly, a numerical simulation of the wire drawing process of a commercial prestressing steel wire was carried out to reveal the residual stress state induced by the manufacture technique. Afterwards, a numerical simulation was performed of the in-service loading conditions of a prestressing steel wire in which the previously calculated residual stress state is included. The analysis of the obtained results shows a significant reduction of the residual stress state of about 50% for common in-service loadings and as high as 90% for certain cases undergoing overloads during cyclic loading. Therefore, an improvement of the mechanical performance of these structural components during their life in-service can be achieved. Full article
Figures

Figure 1

Open AccessArticle
A Metal-Insulator-Metal Deep Subwavelength Cavity Based on Cutoff Frequency Modulation
Appl. Sci. 2017, 7(1), 86; doi:10.3390/app7010086 -
Abstract
We propose a plasmonic cavity using the cutoff frequency of a metal-insulator-metal (MIM) first-order waveguide mode, which has a deep subwavelength physical size of 240 × 210 × 10 (nm3) = 0.00013 λ03. The cutoff frequency is a
[...] Read more.
We propose a plasmonic cavity using the cutoff frequency of a metal-insulator-metal (MIM) first-order waveguide mode, which has a deep subwavelength physical size of 240 × 210 × 10 (nm3) = 0.00013 λ03. The cutoff frequency is a unique property of the first-order waveguide mode and provides an effective mode gap mirror. The cutoff frequency has strong dependence on a variety of parameters including the waveguide width, insulator thickness, and insulator index. We suggest new plasmon cavities using three types of cutoff frequency modulations. The light can be confined in the cavity photonically, which is based on the spatial change of the cutoff frequency. Furthermore, we analyze cavity loss by investigating the metallic absorption, radiation, and waveguide coupling loss; the radiation loss of the higher-order cavity mode can be suppressed by multipole cancellation. Full article
Figures

Open AccessArticle
Optoelectronic Properties and Structural Characterization of GaN Thick Films on Different Substrates through Pulsed Laser Deposition
Appl. Sci. 2017, 7(1), 87; doi:10.3390/app7010087 -
Abstract
Approximately 4-μm-thick GaN epitaxial films were directly grown onto a GaN/sapphire template, sapphire, Si(111), and Si(100) substrates by high-temperature pulsed laser deposition (PLD). The influence of the substrate type on the crystalline quality, surface morphology, microstructure, and stress states was investigated by X-ray
[...] Read more.
Approximately 4-μm-thick GaN epitaxial films were directly grown onto a GaN/sapphire template, sapphire, Si(111), and Si(100) substrates by high-temperature pulsed laser deposition (PLD). The influence of the substrate type on the crystalline quality, surface morphology, microstructure, and stress states was investigated by X-ray diffraction (XRD), photoluminescence (PL), atomic force microscopy (AFM), transmission electron microscopy (TEM), and Raman spectroscopy. Raman scattering spectral analysis showed a compressive film stress of −0.468 GPa for the GaN/sapphire template, whereas the GaN films on sapphire, Si(111), and Si(100) exhibited a tensile stress of 0.21, 0.177, and 0.081 GPa, respectively. Comparative analysis indicated the growth of very close to stress-free GaN on the Si(100) substrate due to the highly directional energetic precursor migration on the substrate’s surface and the release of stress in the nucleation of GaN films during growth by the high-temperature (1000 °C) operation of PLD. Moreover, TEM images revealed that no significant GaN meltback (Ga–Si) etching process was found in the GaN/Si sample surface. These results indicate that PLD has great potential for developing stress-free GaN templates on different substrates and using them for further application in optoelectronic devices. Full article
Figures

Figure 1

Open AccessArticle
Enhanced Iron and Selenium Uptake in Plants by Volatile Emissions of Bacillus amyloliquefaciens (BF06)
Appl. Sci. 2017, 7(1), 85; doi:10.3390/app7010085 -
Abstract
Volatile organic compounds (VOCs) released by plant growth-promoting rhizobacteria (PGPR) are involved in promoting growth and triggering systemic resistance (ISR) in plants. Importantly, the release of VOCs by some PGPR strains confers improved plant uptake of nutrient elements from the soil. However, the
[...] Read more.
Volatile organic compounds (VOCs) released by plant growth-promoting rhizobacteria (PGPR) are involved in promoting growth and triggering systemic resistance (ISR) in plants. Importantly, the release of VOCs by some PGPR strains confers improved plant uptake of nutrient elements from the soil. However, the underlying mechanisms of VOCs-regulated nutrient acquisition remain elusive. In this study, VOCs were extracted and identified from Bacillus amyloliquefaciens (strain BF06) using gas chromatography–mass spectrometry (GC–MS). BF06 VOCs exposure significantly promoted the growth and photosynthesis of Arabidopsis plants. To explore how microbial VOCs stimulate growth in plants, gene expression profiles of Arabidopsis seedlings exposed to BF06 VOCs were examined using transcriptomic analyses. In screening differentially expressed genes (DEGs), most upregulated DEGs were found to be related to amino acid transport, iron (Fe) uptake and homeostasis, and sulfate transport. Furthermore, BF06 VOCs significantly enhanced Fe absorption in plants under Fe-limited conditions. However, when nitric oxide (NO) synthesis was inhibited, BF06 VOCs exposure could not substantially augment Fe acquisition in plants under alkaline stress, indicating that VOCs-mediated plant uptake of Fe was required for induction of root NO accumulation. In addition, BF06 VOCs exposure led to a marked increase in some genes encoding for sulfate transporters, and further increased Se accumulation in plants. Intriguingly, BF06 VOCs exposure failed to increase Se uptake in sultr1;2 mutants, which may indicate that high-level transcription of these sulfate transporters induced by BF06 VOCs was essential for enhancing Se absorption by plants. Taken together, our results demonstrated the potential of VOCs released by this strain BF06 to increase Fe and Se uptake in plants. Full article
Figures

Figure 1

Open AccessArticle
Early Detection of Aspergillus parasiticus Infection in Maize Kernels Using Near-Infrared Hyperspectral Imaging and Multivariate Data Analysis
Appl. Sci. 2017, 7(1), 90; doi:10.3390/app7010090 -
Abstract
Fungi infection in maize kernels is a major concern worldwide due to its toxic metabolites such as mycotoxins, thus it is necessary to develop appropriate techniques for early detection of fungi infection in maize kernels. Thirty-six sterilised maize kernels were inoculated each day
[...] Read more.
Fungi infection in maize kernels is a major concern worldwide due to its toxic metabolites such as mycotoxins, thus it is necessary to develop appropriate techniques for early detection of fungi infection in maize kernels. Thirty-six sterilised maize kernels were inoculated each day with Aspergillus parasiticus from one to seven days, and then seven groups (D1, D2, D3, D4, D5, D6, D7) were determined based on the incubated time. Another 36 sterilised kernels without inoculation with fungi were taken as control (DC). Hyperspectral images of all kernels were acquired within spectral range of 921–2529 nm. Background, labels and bad pixels were removed using principal component analysis (PCA) and masking. Separability computation for discrimination of fungal contamination levels indicated that the model based on the data of the germ region of individual kernels performed more effectively than on that of the whole kernels. Moreover, samples with a two-day interval were separable. Thus, four groups, DC, D1–2 (the group consisted of D1 and D2), D3–4 (D3 and D4), and D5–7 (D5, D6, and D7), were defined for subsequent classification. Two separate sample sets were prepared to verify the influence on a classification model caused by germ orientation, that is, germ up and the mixture of germ up and down with 1:1. Two smooth preprocessing methods (Savitzky-Golay smoothing, moving average smoothing) and three scatter-correction methods (normalization, standard normal variate, and multiple scatter correction) were compared, according to the performance of the classification model built by support vector machines (SVM). The best model for kernels with germ up showed the promising results with accuracies of 97.92% and 91.67% for calibration and validation data set, respectively, while accuracies of the best model for samples of the mixed kernels were 95.83% and 84.38%. Moreover, five wavelengths (1145, 1408, 1935, 2103, and 2383 nm) were selected as the key wavelengths in the discrimination of fungal contamination levels. In general, near-infrared hyperspectral imaging can be used for early detection of fungal contamination in maize kernels. Full article
Figures

Figure 1

Open AccessArticle
The Personal Viewpoint on the Meaning of Tranquility Affects the Appraisal of the Urban Park Soundscape
Appl. Sci. 2017, 7(1), 91; doi:10.3390/app7010091 -
Abstract
Previous research has shown that tranquil areas in the city, such as urban parks, are usually perceived as positive and have a restorative effect on visitors. However, visitors could experience these spaces differently depending on the meaning they assign to the concept of
[...] Read more.
Previous research has shown that tranquil areas in the city, such as urban parks, are usually perceived as positive and have a restorative effect on visitors. However, visitors could experience these spaces differently depending on the meaning they assign to the concept of tranquility. To investigate how individuals’ personal views on tranquility affect their perception of the sonic environment, a soundscape study was conducted in several city parks in Antwerp, Belgium. Mobile sound measurements were combined with a questionnaire survey amongst 660 park visitors. Within the survey, the participants’ viewpoint on tranquility was evaluated using their agreement with a set of previously established prototypical statements, categorizing them into one out of three main tranquility viewpoint groups: people that associate tranquility with silence, those that associate it with hearing natural sounds, or those that associate it with social relationships. Next to this, the sounds that participants had heard during their visit were noted, and their perception of the overall quality of the soundscape and the degree to which it matched their expectation were assessed. Results show that the park visitors who associate tranquility with natural sounds or to silence are more often found amongst those that report hearing mechanical sounds a lot. The same groups of visitors rate the overall quality of the sonic environment of the park more often bad to very bad. These findings suggest that park visitors pay attention more to the sounds they do not expect to hear, and that the higher their expectations about the soundscape, the more critical they become in their appraisal of the soundscape. Full article
Figures

Figure 1

Open AccessArticle
Rapid Synthesis of Gold Nanoparticles from Quercus incana and Their Antimicrobial Potential against Human Pathogens
Appl. Sci. 2017, 7(1), 29; doi:10.3390/app7010029 -
Abstract
In current study, bioreduction of tetrachloroauric acid (HAuCl4·3H2O) was carried out using leaves extract of Quercus incana for nanoparticle synthesis. The nanoparticles were characterized by ultraviolet visible spectrum (UV), Fourier-transform infrared (FT-IR), and transmission electron microscopy (TEM) analysis. The
[...] Read more.
In current study, bioreduction of tetrachloroauric acid (HAuCl4·3H2O) was carried out using leaves extract of Quercus incana for nanoparticle synthesis. The nanoparticles were characterized by ultraviolet visible spectrum (UV), Fourier-transform infrared (FT-IR), and transmission electron microscopy (TEM) analysis. The gold nanoparticles (GNPs) were generally clumpy agglomerates of polydispersed particles, with an average size in the range 5.5–10 nm. The Gas chromatography–mass spectrometry (GC–MS) qualitative analysis and FT-IR data supported the presence of bioactive compounds, which are responsible for the metal reduction and nanoparticles stabilization. The biocompatibility of synthesized GNPs was evaluated via antibacterial activity by using human bacterial pathogens. The results showed that synthesized GNPs showed enhanced antibacterial activity against all bacterial pathogens. Full article
Figures

Figure 1

Open AccessArticle
A Temperature Sensor Clustering Method for Thermal Error Modeling of Heavy Milling Machine Tools
Appl. Sci. 2017, 7(1), 82; doi:10.3390/app7010082 -
Abstract
A clustering method is an effective way to select the proper temperature sensor location for thermal error modeling of machine tools. In this paper, a new temperature sensor clustering method is proposed. By analyzing the characteristics of the temperature of the sensors in
[...] Read more.
A clustering method is an effective way to select the proper temperature sensor location for thermal error modeling of machine tools. In this paper, a new temperature sensor clustering method is proposed. By analyzing the characteristics of the temperature of the sensors in a heavy floor-type milling machine tool, an indicator involving both the Euclidean distance and the correlation coefficient was proposed to reflect the differences between temperature sensors, and the indicator was expressed by a distance matrix to be used for hierarchical clustering. Then, the weight coefficient in the distance matrix and the number of the clusters (groups) were optimized by a genetic algorithm (GA), and the fitness function of the GA was also rebuilt by establishing the thermal error model at one rotation speed, then deriving its accuracy at two different rotation speeds with a temperature disturbance. Thus, the parameters for clustering, as well as the final selection of the temperature sensors, were derived. Finally, the method proposed in this paper was verified on a machine tool. According to the selected temperature sensors, a thermal error model of the machine tool was established and used to predict the thermal error. The results indicate that the selected temperature sensors can accurately predict thermal error at different rotation speeds, and the proposed temperature sensor clustering method for sensor selection is expected to be used for the thermal error modeling for other machine tools. Full article
Figures

Open AccessArticle
Nonlinear Integral Type Observer Design for State Estimation and Unknown Input Reconstruction
Appl. Sci. 2017, 7(1), 67; doi:10.3390/app7010067 -
Abstract
This paper is concerned with model-based robust observer designs for state observation and its application for unknown input reconstruction. Firstly, a sliding mode observer (SMO), which provides exponential convergence of estimation error, is designed for a class of multivariable perturbed systems. Observer gain
[...] Read more.
This paper is concerned with model-based robust observer designs for state observation and its application for unknown input reconstruction. Firstly, a sliding mode observer (SMO), which provides exponential convergence of estimation error, is designed for a class of multivariable perturbed systems. Observer gain matrices subject to specific structures are going to be imposed such that the unknown perturbation will not affect estimate precision during the sliding modes; Secondly, to improve discontinuous control induced in the SMO as well as pursue asymptotic estimate precision, a proportional-integral type observer (PIO) is further developed. Both the design procedures of the SMO and PIO algorithms are characterized as feasibility issues of linear matrix inequality (LMI) and thus the computations of the control parameters can be efficiently solved. Compared with the SMO, it will be demonstrated that the PIO is capable of achieving better estimation precision as long as the unknown inputs are continuous. Finally, a servo-drive flexible robot arm is selected as an example to demonstrate the applications of the robust observer designs. Full article
Figures

Open AccessArticle
Arbuscular Mycorrhizal Fungi Regulate the Growth and Phyto-Active Compound of Salvia miltiorrhiza Seedlings
Appl. Sci. 2017, 7(1), 68; doi:10.3390/app7010068 -
Abstract
Roots and rhizomes of Salvia miltiorrhiza (S. miltiorrhiza) are widely used for the treatment of cardiovascular diseases. Arbuscular mycorrhizal fungi (AMFs) have been shown to enhance plant growth and increase secondary metabolites concentration in many plant species. However, effects of AMFs
[...] Read more.
Roots and rhizomes of Salvia miltiorrhiza (S. miltiorrhiza) are widely used for the treatment of cardiovascular diseases. Arbuscular mycorrhizal fungi (AMFs) have been shown to enhance plant growth and increase secondary metabolites concentration in many plant species. However, effects of AMFs on S. miltiorrhiza have not been explored. A pot culture was designed as one control (non-AMF) treatment and four AMFs (G.m, Glomus mosseae; G.a, Glomus aggregatum; G.v, Glomus versiforme; G.i, Glomus intraradices) treatments were performed in order to evaluate the effects of AMFs on plant growth, as well as phyto-active compounds’ concentration of S. miltiorrhiza seedlings. Plants were harvested after 90 days: agronomic traits and concentration; and an accumulation of mineral elements, as well as phyto-active compounds were detected. All AMFs inoculated plants formed mycorrhizal structures, and an infection ratio; also, the intensity of inoculated roots was higher than 84.61% and 23.86%, respectively. Mycorrhizal dependency was above 144.62%. Seedlings with AMFs inoculation had significantly higher plant height, leather leaf length, top leaflet size, base leaflet length, taproot length, taproot diameter and biomass than those with non-AMF inoculation. In addition, inoculation with AMFs increased N, P, and K accumulation significantly, but barely had any effect on mineral elements’ concentrations. AMFs inoculation also significantly improved tanshinones concentrations and stimulation in order to accumulate salvianolic acid B. G.v and G.i were effective for seedlings growth; G.m and G.i were also effective for phyto-active compounds. In total, S. miltiorrhiza inoculation with AMFs had positive effects on growth and active components, especially inoculation with G.v. Full article
Figures

Figure 1

Open AccessArticle
Luminescent Properties of Silicon Nanocrystals:Spin on Glass Hybrid Materials
Appl. Sci. 2017, 7(1), 72; doi:10.3390/app7010072 -
Abstract
The photoluminescence characteristics of films consisting of Si nanocrystals either coated with or embedded into Spin on Glass (SOG) were studied. Si nanocrystals showing red or blue luminescence when suspended in alcohol solution were obtained from porous silicon films. These were then either
[...] Read more.
The photoluminescence characteristics of films consisting of Si nanocrystals either coated with or embedded into Spin on Glass (SOG) were studied. Si nanocrystals showing red or blue luminescence when suspended in alcohol solution were obtained from porous silicon films. These were then either deposited in Si substrates and coated with SOG, or mixed in an SOG solution that was later spun on Si substrates. Both types of films were thermally annealed at 1100 °C for three hours in N2 atmosphere. Transmission electron microscopy measurements showed a mean diameter of 2.5 nm for the Si nanocrystals, as well as the presence of polycrystalline Si nanoagglomerates. These results were confirmed by X-ray diffraction studies, which revealed the (111), (220) and (311) Bragg peaks in Si nanocrystals. Fourier transform infrared spectroscopy studies showed that the coated films present higher chemical reactivity, promoting the formation of non-stoichiometric SiO2, while the embedded films behave as a stoichiometric SiO2 after the thermal annealing. The PL (photoluminescence) characterization showed that both embedded and coated films present emission dominated by the Quantum Confinement Effect before undergoing any thermal treatment. After annealing, the spectra were found to be modified only in the case of the coated films, due to the formation of defects in the nanocrystals/SiO2 interface. Full article
Figures

Figure 1

Open AccessArticle
Tribological Properties of Aluminum Nanoparticles as Additives in an Aqueous Glycerol Solution
Appl. Sci. 2017, 7(1), 80; doi:10.3390/app7010080 -
Abstract
The object of this research is to investigate the tribological properties of glycerol lubricant with aluminum nanoparticles as an additive and sodium dodecyl sulfate (SDS) as the dispersive medium for iron to iron friction using a thrust collar tribotester. Meanwhile, the effects of
[...] Read more.
The object of this research is to investigate the tribological properties of glycerol lubricant with aluminum nanoparticles as an additive and sodium dodecyl sulfate (SDS) as the dispersive medium for iron to iron friction using a thrust collar tribotester. Meanwhile, the effects of different concentrations of aluminum nanoparticles, SDS, and deionized water in glycerol on tribology properties of iron to iron friction were studied. The experimental parameters were set up according to the Taguchi technique, their influence on the coefficient of friction (COF) and wear rate were examined by response surface methodology (RSM) and analysis of variance (ANOVA) methods. The analysis results were employed to optimize the parameters to obtain the best lubricant effects. The optimal combination of the parameters for both minimum COF and wear rate was found to be 0.6667 weight percent (wt %) of aluminum nanoparticles, 2 wt % of SDS, and 10 wt % of deionized water content of glycerol. The wear surface topography and the average roughness of the surface were also examined using a scanning electron microscope (SEM) and a Mitutoyo Surftest SJ-400 instrument. The results show that aluminum nanoparticles used as an additive in lubricant reduce the surface roughness of a collar remarkably. The energy dispersive spectrometer (EDS) was utilized to confirm the deposition of aluminum nanoparticles on the collar surface leading to decreased friction and wear. Full article
Figures

Figure 1