Appl. Sci., Volume 7, Issue 1 (January 2017) – 108 articles

Human activity recognition (HAR) is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR. Full article

This work improved upon an effective micromechanical method to analyze the mechanical properties of three-dimensional particle-reinforced composites (PRC) with consideration of the interfacial debonding. By incorporating the interfacial debonding model, Mises yield criterion, and failure theory, the effects of particle shape, particle volume fraction, and loading condition on the mechanical properties are studied. A comparison of simulation results obtained from the established method and published experimental data is presented. Good consistency can be found in this study. On this basis, the interfacial cohesive strength and particle shape effects on the biaxial failure strength of particle-reinforced composites with interfacial debonding were also studied. The results revealed that both interfacial strength and particle shape have significant effects on biaxial tensile failure strength. However, the different interfacial strength influence on failure envelope can hardly be discerned in biaxial compressive loading. Full article

Titanium is one of the most attractive materials for biomedical applications due to having excellent biocompatibility accompanied by good corrosion resistance. One popular processing technique for Ti is Metal Injection Moulding (MIM). However, there are several issues associated with the use of this technique, such as the high cost of the fine powder used, the high level of contamination and consequent alteration to material properties, as well as the large volume shrinkage that occurs during sintering. In this study, the use of a relatively coarse Ti powder with a mean particle size of 75 μm to process Ti parts with the potential for biomedical applications by MIM will be examined, compared to a commercial Ti feedstock, and subsequently coated using Plasma Electrolytic Oxidation (PEO). The results show that samples produced with the coarse powder shrink 35% less and have a relative density 14% less with an average pore size three-times larger than that of the commercial feedstock. This helps increase the potential competitiveness of MIM in the production of biomedical parts, as it reduces cost, shrinkage and results in more intentionally-induced micropores, such as are desired for biomedical implants. PEO treatment of the samples yields a thick rough coating comprised of a mixture of rutile and anatase with interconnected microporous channels and openings resembling the mouth of a volcanic crater. Full article

The objective of this study was to develop a nondestructive method to evaluate chemical components such as moisture content (MC), pH, and soluble solid content (SSC) in intact tomatoes by using hyperspectral imaging in the range of 1000–1550 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and multivariate calibration models were built by using partial least squares (PLS) regression with different preprocessing spectra. The results showed that the regression model developed by PLS regression based on Savitzky–Golay (S–G) first-derivative preprocessed spectra resulted in better performance for MC, pH, and the smoothing preprocessed spectra-based model resulted in better performance for SSC in intact tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (r_pred) of 0.81, 0.69, and 0.74 with root mean square error of prediction (RMSEP) of 0.63%, 0.06, and 0.33% Brix respectively. The full wavelengths were used to create chemical images by applying regression coefficients resulting from the best PLS regression model. These results obtained from this study clearly revealed that hyperspectral imaging, together with suitable analysis model, is a promising technology for the nondestructive prediction of chemical components in intact tomatoes. Full article

A novel shape memory polymer composite was fabricated by introducing various amounts of silicon carbide whiskers (SiCws) into a shape memory epoxy. The relationship between the thermomechanical properties of the system and structural changes were investigated via dynamic mechanical analysis, scanning electron microscopy, and bending tests. The results show that the bend strength of composites can improve by 64.1% when SiCw content reaches 12 wt %. The shape transition temperatures of SiCw/epoxy composites decreased slightly with the increase in SiCw content, but it was noted that all of the composites showed excellent shape memory properties. The shape fixity ratio increased as SiCw content increased (>99%), and the shape recovery ratio slightly decreased as SiCw content increased (>95%). All of the composites nearly recovered to their original shape within 2 min (not 100%), and the shape recovery speed significantly improved at a higher temperature. It is anticipated that tagging products will be used in the aerospace industry. Full article

Wire ropes in marine applications often encounter relatively fast and noticeable wear, a result of the fatigue to which they are exposed coupled with harsh operational conditions. This paper addresses some of the aspects of fatigue damage that occur in wire ropes. Using the finite element method, stress and fatigue analysis of three different design types (6 × 7, 7 × 7, 8 × 7) of wire rope is performed. The size of the wire rope cross-section area is varied in order to simulate the progressive damage of the wires so that consequential stress levels and remaining fatigue life can be numerically predicted. The aim was to provide a better understanding of the mechanical behavior of damaged wire ropes under various conditions, since an appropriate choice of wire rope design could then be made from engineering and economic points of view. Additionally, potential failures can be predicted, resulting in effective maintenance and the avoidance of potential risks of rope failure, especially important regarding economical and safety aspects of transportation in the marine industry. Full article

This paper presents a newly developed active device, referred to as a multiplied input differential difference amplifier (MIDDA), which allows operations of summation/subtraction and multiplication of input signals. It was designed and fabricated using I3T25 0.35 μm ON (ON Semiconductor, Phoenix, AZ, USA) Semiconductor technology. The achieved results, which describe the experimentally verified behaviour of the fabricated device, are introduced, as well as the simple applications of MIDDA with electronically controllable parameters, useful for analogue signal processing. Moreover, the paper discusses an interesting example of nonlinear application to a double-sideband amplitude modulator, based on the utilization of multiplication and summation of particular signals. The laboratory experimental results which are achieved through the use of a fabricated prototype (both in time and frequency domain), confirm the workability of the concept. Full article

Most existing ICP (Iterative Closet Point)-based 3D ear recognition approaches resort to the coarse-to-fine ICP algorithms to match 3D ear models. With such an approach, the gallery-probe pairs are coarsely aligned based on a few local feature points and then finely matched using the original ear point cloud. However, such an approach ignores the fact that not all the points in the coarsely segmented ear data make positive contributions to recognition. As such, the coarsely segmented ear data which contains a lot of redundant and noisy data could lead to a mismatch in the recognition scenario. Additionally, the fine ICP matching can easily trap in local minima without the constraint of local features. In this paper, an efficient and fully automatic 3D ear recognition system is proposed to address these issues. The system describes the 3D ear surface with a local feature—the Local Surface Variation (LSV), which is responsive to the concave and convex areas of the surface. Instead of being used to extract discrete key points, the LSV descriptor is utilized to eliminate redundancy flat non-ear data and get normalized and refined ear data. At the stage of recognition, only one-step modified iterative closest points using local surface variation (ICP-LSV) algorithm is proposed, which provides additional local feature information to the procedure of ear recognition to enhance both the matching accuracy and computational efficiency. On an Inter^®Xeon^®W3550, 3.07 GHz work station (DELL T3500, Beijing, China), the authors were able to extract features from a probe ear in 2.32 s match the ear with a gallery ear in 0.10 s using the method outlined in this paper. The proposed algorithm achieves rank-one recognition rate of 100% on the Chinese Academy of Sciences’ Institute of Automation 3D Face database (CASIA-3D FaceV1, CASIA, Beijing, China, 2004) and 98.55% with 2.3% equal error rate (EER) on the Collection J2 of University of Notre Dame Biometrics Database (UND-J2, University of Notre Dame, South Bend, IN, USA, between 2003 and 2005). Full article

The ability of ferritin to bind and deliver metals and metal-based drugs to human neuroblastoma SH-SY5Y cells was studied. We used heavy chain (H) ferritin-based metal-containing nanocarriers to test whether these constructs, which are able to cross the blood-brain barrier, may be used for the delivery of toxic molecules to brain cells, and to study their effect on the viability and cellular redox homeostasis of human neuroblastoma cells. We show that metal-containing nanocarriers are efficiently captured by SH-SY5Y cells. Iron-containing nanocarriers have a proliferative effect, while silver and cisplatin-encapsulated nanocarriers determine concentration-dependent neuroblastoma cell death. This work is a proof of concept for the use of ferritins for the delivery of toxic molecules to brain tumors. Full article

The traditional model of the electromagnetic force and torque does not take the coil corners into account, which is the major cause for the motor fluctuation. To reduce the fluctuation, a more accurate real-time computation model, which considers the influence of the coil corners, is proposed in this paper. Three coordinate systems respectively for the stator, the mover, and the corner are established. The first harmonic of the magnetic flux density distribution of a Halbach magnet array is taken into account in this model. The coil is divided into the straight coil segment and the corner coil segment based on its structure. For the straight coil segment, the traditional Lorenz force method can be used to compute its electromagnetic force and torque, which is a function of the mover position. For the corner coil segment, however, the numerical calculation method can be used to get its respective electromagnetic force and torque. Based on the above separate analysis, an electromagnetic model can be derived, which is suitable for practical application. Compared with the well-known harmonic model, the proposed real-time computation model is found to have less model inaccuracy. Additionally, the real-time ability of the maglev planar motor model and the decoupling computation is validated by NI PXI platform (Austin, TX, USA). Full article

The 2016 Ecuador M 7.8 earthquake ruptured the subduction zone boundary between the Nazca plate and the South America plate. This M 7.8 earthquake may have promoted failure in the surrounding crust, where six M ≥ 6 aftershocks occurred following this mainshock. These crustal ruptures were triggered by the high coulomb stress changes produced by the M 7.8 mainshock. Here, we investigate whether the six M ≥ 6 aftershocks are consistent with the positive coulomb stress region due to the mainshock. To explore the correlation between the mainshock and the aftershocks, we adopt a recently published high-quality finite fault model and focal mechanisms to study the coulomb stress triggers during the M 7.8 earthquake sequence. We compute the coulomb failure stress changes (ΔCFS) on both of the focal mechanism nodal planes. We compare the ΔCFS imparted by the M 7.8 mainshock on the subsequent aftershocks with the epicenter location of each aftershock. In addition, the shear stress, normal stress, and coulomb stress changes in the focal sources of each aftershock are also computed. Coulomb stress changes in the focal source for the six M ≥ 6 aftershocks are in the range of −2.17–7.564 bar. Only one computational result for the M 6.9 aftershock is negative; other results are positive. We found that the vast majority of the six M ≥ 6 aftershocks occurred in positive coulomb stress areas triggered by the M 7.8 mainshock. Our results suggest that the coulomb stress changes contributed to the development of the Ecuador M 7.8 earthquake sequence. Full article

Welded beam-to-column connections of high-rise steel structures are susceptive to fatigue damage under wind loading. However, most fatigue assessments in the field of civil engineering are mainly based on nominal stress or hot spot stress theories, which has the disadvantage of dependence on the meshing styles and massive curves selected. To address this problem, in this paper, the equivalent structural stress method with advantages of mesh-insensitive quality and capability of unifying different stress-life curves (S-N curves) into one is introduced to the wind-induced fatigue assessment of a large-scale complicated high-rise steel structure. The multi-scale finite element model is established and the corresponding wind loading is simulated. Fatigue life assessments using equivalent structural stress method, hot spot stress method and nominal stress method are performed, and the results are verified and comparisons are made. The mesh-insensitive quality is also verified. The results show that the lateral weld toe of the butt weld connecting the beam flange plate and the column is the location where fatigue damage most likely happens. Nominal stress method considers fatigue assessment of welds in a more global way by averaging all the stress on the weld section while in equivalent structural stress method and hot spot method local stress concentration can be taken into account more precisely. Full article

In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK), Quadrature Phase Shift Keying (QPSK), 16-Quadrature Amplitude Modulation (QAM) and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks. Full article

Process intensification strategy (PIS) is emerging as an interesting guideline to revolutionize process industry in terms of improved efficiency and sustainability. Membrane engineering has appeared as a strong candidate to implement PIS. The most significant progress has been observed in desalination where substantial reduction in overall energy demand, environmental footprint, and process hazards has already been accomplished. Recent developments in membrane engineering are shaping the desalination industry into raw materials and energy production where fresh water will be produced as a byproduct. The present study discusses the current and perspective role of membrane engineering in achieving the objectives of PIS in the field of desalination. Full article

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

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 (R_cv²) 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 (R_cv² = 0.99) and R_cv² > 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

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

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

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 K_e and shear capacity F_p 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

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

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

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

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, D_1–2 (the group consisted of D₁ and D₂), D_3–4 (D₃ and D₄), and D_5–7 (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

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

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

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

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

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

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

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