Search Results (11)

Reinforced concrete (RC), renowned for its amalgamation of strength and durability, stands as a cornerstone in modern engineering, extensively employed in various structures such as buildings, bridges, and pipe culverts. However, prevalent issues of concrete spalling and exposed steel bars within RC structures pose significant challenges. An automated identification methodology is proposed to detect concrete spalling and exposed steel bars, leveraging machine vision technology and deep learning algorithms. Initially, a classifier is utilized to discern concrete spalling areas within the image domain at the image level. Subsequently, a semantic segmentation algorithm is applied to precisely delineate the contours of both concrete spalling areas and exposed steel bars at the pixel level. The efficacy and feasibility of the proposed method are validated through training and testing on both a publicly available dataset and actual RC structure images. The results illustrate that the average detection precision, Intersection over Union (IOU), recall, and F1-score for concrete spalling areas are 0.924, 0.872, 0.937, and 0.925, respectively, while for exposed steel areas, the corresponding values are 0.905, 0.820, 0.899, and 0.855. This method demonstrates promising prospects for wide-ranging applications in defect detection within RC structures. Full article

In this paper, the performance of machine learning methods for squirrel cage induction motor broken rotor bar (BRB) fault detection is evaluated. Decision tree classification (DTC), artificial neural network (ANN), and deep learning (DL) methods are developed, applied, and studied to compare their performance in detecting broken rotor bar faults in squirrel cage induction motors. The training data were collected through experimental measurements. The BRB fault features were extracted from measured line-current signatures through a transformation from the time domain to the frequency domain using discrete Fourier Transform (DFT) of the frequency spectrum of the current signal. Eighty percent of the data were used for training the models, and twenty percent were used for testing. A confusion matrix was used to validate the models’ performance using accuracy, precision, recall, and f1-scores. The results evidence that the DTC is less load-dependent, and it has better accuracy and precision for both unloaded and loaded squirrel cage induction motors when compared with the DL and ANN methods. The DTC method achieved higher accuracy in the detection of the magnitudes of the twice-frequency sideband components induced in stator currents by BRB faults when compared with the DL and ANN methods. Although the detection accuracy and precision are higher for the loaded motor than the unloaded motor, the DTC method managed to also exhibit a high accuracy for the unloaded current when compared with the DL and ANN methods. The DTC is, therefore, a suitable candidate to detect broken rotor bar faults on trained data for lightly or thoroughly loaded squirrel cage induction motors using the characteristics of the measured line-current signature. Full article

Lateral modes are responsible for the in-band spurious resonances that appear on BAW resonators, degrading the in-band filter response. In this work, a fast computational method based on the transmission line matrix (TLM) method is employed to model the lateral resonances of BAW resonators. Using the precomputed dispersion curves of Lamb waves and an equivalent characteristic impedance for the TE₁ mode, a network of transmission lines is used to calculate the magnitude of field distributions on the electrodes. These characteristics are specific to the stack layer configuration. The model’s implementation is based on nodal Y matrices, from which particle displacement profiles are coupled to the electric domain via piezoelectric constitutive relations. Consequently, the input impedance of the resonator is obtained. The model exhibits strong agreement with FEM simulations of FBARs and SMRs, and with measurements of several SMRs. The proposed model can provide accurate predictions of resonator input impedance, which is around 200 times faster than conventional FEM. Full article

Induction machines (IMs) play a critical role in various industrial processes but are susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic techniques are essential in addressing these issues. In this study, we propose the utilization of convolutional neural networks (CNNs) for detection of broken rotor bars. To accomplish this, we generated a dataset comprising current samples versus angular position using finite element method magnetics (FEMM) software for a squirrel-cage rotor with 28 bars, including scenarios with 0 to 6 broken bars at every possible relative position. The dataset consists of a total of 16,050 samples per motor. We evaluated the performance of six different CNN architectures, namely Inception V4, NasNETMobile, ResNET152, SeNET154, VGG16, and VGG19. Our automatic classification system demonstrated an impressive 99% accuracy in detecting broken rotor bars, with VGG19 performing exceptionally well. Specifically, VGG19 exhibited high accuracy, precision, recall, and F1-Score, with values approaching 0.994 and 0.998. Notably, VGG19 exhibited crucial activations in its feature maps, particularly after domain-specific training, highlighting its effectiveness in fault detection. Comparing CNN architectures assists in selecting the most suitable one for this application based on processing time, effectiveness, and training losses. This research suggests that deep learning can detect broken bars in induction machines with accuracy comparable to that of traditional methods by analyzing current signals using CNNs. Full article

We consider the theory of quantum gravity in which gravity emerges as a result of the symmetry-breaking transition in the quantum vacuum. The gravitational tetrads, which play the role of the order parameter in this transition, are represented by the bilinear combinations of the fermionic fields. In this quantum gravity scenario the interval $ds$ in the emergent general relativity is dimensionless. Several other approaches to quantum gravity, including the model of superplastic vacuum and $BF$ theories of gravity support this suggestion. The important consequence of such metric dimension is that all the diffeomorphism invariant quantities are dimensionless for any dimension of spacetime. These include the action S, cosmological constant $\mathrm{\Lambda }$, scalar curvature R, scalar field $\mathrm{\Phi }$, wave function $\psi$, etc. The composite fermion approach to quantum gravity suggests that the Planck constant ℏ can be the parameter of the Minkowski metric. Here, we extend this suggestion by introducing two Planck constants, bar ℏ and slash $/h$, which are the parameters of the correspondingly time component and space component of the Minkowski metric, $g_{\mathrm{Mink}}^{\mu \nu }=\mathrm{diag}(-{\hslash }^2,/h^2,/h^2,/h^2)$. The parameters bar ℏ and slash $/h$ are invariant only under $SO\left(3\right)$ transformations, and, thus, they are not diffeomorphism invariant. As a result they have non-zero dimensions—the dimension of time for ℏ and dimension of length for $/h$. Then, according to the Weinberg criterion, these parameters are not fundamental and may vary. In particular, they may depend on the Hubble parameter in the expanding Universe. They also change sign at the topological domain walls resulting from the symmetry breaking. Full article

When an induction motor is running at stable speed and low slip, the fault signal of the induction motor’s broken bar faults are easily submerged by the power frequency (50 Hz) signal. Thus, it is difficult to extract fault characteristics. The left-side harmonic component representing the fault characteristics can be distinguished from power frequency owing to V-shaped trajectory of the fault component in time-frequency (t-f) domain during motor startup. This article proposed a scheme to detect broken bar faults and discriminate the severity of faults under starting conditions. In this scheme, successive variable mode decomposition (SVMD) is applied to analyze the stator starting current to extract the fault component, and the signal reconstruction is proposed to maximize the energy of the fault component. Then, the quadratic regression curve method of instantaneous frequency square value of the fault component is utilized to discriminate whether the fault occurs. In addition, according to the feature that the energy of the fault component increases with the fault severity, the energy of the right part of the fault component is proposed to detect the severity of the fault. In this paper, experiments are carried out based on a 5.5 kW three-pole induction motor. The results show that the scheme proposed in this paper can diagnose the broken bar faults and determine the severity of the fault. Full article

In addition to the receptor-binding domain (DII), the C-terminal domain (DIII) of three-domain Cry insecticidal δ-endotoxins from Bacillus thuringiensis has been implicated in target insect specificity, yet its precise mechanistic role remains unclear. Here, the 21 kDa high-purity isolated DIII fragment derived from the Cry4Ba mosquito-specific toxin was achieved via optimized preparative FPLC, allowing direct rendering analyses for binding characteristics toward its target receptor—Aedes aegypti membrane-bound alkaline phosphatase (Aa-mALP). Binding analysis via dotblotting revealed that the Cry4Ba-DIII truncate was capable of specific binding to nitrocellulose-bound Aa-mALP, with a binding signal comparable to its 65 kDa Cry4Ba-R203Q full-length toxin. Further determination of binding affinity via sandwich ELISA revealed that Cry4Ba-DIII exhibited a rather weak binding to Aa-mALP with a dissociation constant (K_d) of ≈1.1 × 10⁻⁷ M as compared with the full-length toxin. Intermolecular docking between the Cry4Ba-R203Q active toxin and Aa-mALP suggested that four Cry4Ba-DIII residues, i.e., Glu⁵²², Asn⁵⁵², Asn⁵⁷⁶, and Leu⁶¹⁵, are potentially involved in such toxin–receptor interactions. Ala substitutions of each residue (E522A, N552A, N576A and L615A) revealed that only the L615A mutant displayed a drastic decrease in biotoxicity against A. aegypti larvae. Additional binding analysis revealed that the L615A-impaired toxin also exhibited a reduction in binding capability to the surface-immobilized Aa-mALP receptor, while two bio-inactive DII-mutant toxins, Y332A and F364A, which almost entirely lost their biotoxicity, apparently retained a higher degree of binding activity. Altogether, our data disclose a functional importance of the C-terminal domain of Cry4Ba for serving as a potential receptor-binding moiety in which DIII-Leu⁶¹⁵ could conceivably be exploited for the binding to Aa-mALP, highlighting its contribution to toxin interactions with such a target receptor in mediating larval toxicity. Full article

We characterized the size, distribution, and fluidity of microdomains in a lipid bilayer containing phosphatidylinositol (PI) and revealed their roles during the two-dimensional assembly of a membrane deformation protein (FBP17). The morphology of the supported lipid bilayer (SLB) consisting of PI and phosphatidylcholine (PC) on a mica substrate was observed with atomic force microscope (AFM). Single particle tracking (SPT) was performed for the PI+PC-SLB on the mica substrate by using the diagonal illumination setup. The AFM topography showed that PI-derived submicron domains existed in the PI+PC-SLB. The spatiotemporal dependence of the lateral lipid diffusion obtained by SPT showed that the microdomain had lower fluidity than the surrounding region and worked as the obstacles for the lipid diffusion. We observed the two-dimensional assembly of FBP17, which is one of F-BAR family proteins included in endocytosis processes and has the function generating lipid bilayer tubules in vitro. At the initial stage of the FBP17 assembly, the PI-derived microdomain worked as a scaffold for the FBP17 adsorption, and the fluid surrounding region supplied FBP17 to grow the FBP17 domain via the lateral molecular diffusion. This study demonstrated an example clearly revealing the roles of two lipid microregions during the protein reaction on a lipid bilayer. Full article

The budding yeast Saccharomyces cerevisiae has an actin cytoskeleton that comprises a set of protein components analogous to those found in the actin cytoskeletons of higher eukaryotes. Furthermore, the actin cytoskeletons of S. cerevisiae and of higher eukaryotes have some similar physiological roles. The genetic tractability of budding yeast and the availability of a stable haploid cell type facilitates the application of molecular genetic approaches to assign functions to the various actin cytoskeleton components. This has provided information that is in general complementary to that provided by studies of the equivalent proteins of higher eukaryotes and hence has enabled a more complete view of the role of these proteins. Several human functional homologues of yeast actin effectors are implicated in diseases. A better understanding of the molecular mechanisms underpinning the functions of these proteins is critical to develop improved therapeutic strategies. In this article we chose as examples four evolutionarily conserved proteins that associate with the actin cytoskeleton: (1) yeast Hof1p/mammalian PSTPIP1, (2) yeast Rvs167p/mammalian BIN1, (3) yeast eEF1A/eEF1A1 and eEF1A2 and (4) yeast Yih1p/mammalian IMPACT. We compare the knowledge on the functions of these actin cytoskeleton-associated proteins that has arisen from studies of their homologues in yeast with information that has been obtained from in vivo studies using live animals or in vitro studies using cultured animal cell lines. Full article

Acoustic devices have found wide applications in chemical and biosensing fields owing to their high sensitivity, ruggedness, miniaturized design and integration ability with on-field electronic systems. One of the potential advantages of using these devices are their label-free detection mechanism since mass is the fundamental property of any target analyte which is monitored by these devices. Herein, we provide a concise overview of high frequency acoustic transducers such as quartz crystal microbalance (QCM), surface acoustic wave (SAW) and film bulk acoustic resonators (FBARs) to compare their working principles, resonance frequencies, selection of piezoelectric materials for their fabrication, temperature-frequency dependency and operation in the liquid phase. The selected sensor applications of these high frequency acoustic transducers are discussed primarily focusing on the two main sensing domains, i.e., biosensing for working in liquids and gas/vapor phase sensing. Furthermore, the sensor performance of high frequency acoustic transducers in selected cases is compared with well-established analytical tools such as liquid chromatography mass spectrometry (LC-MS), gas chromatographic (GC) analysis and enzyme-linked immunosorbent assay (ELISA) methods. Finally, a general comparison of these acoustic devices is conducted to discuss their strengths, limitations, and commercial adaptability thus, to select the most suitable transducer for a particular chemical/biochemical sensing domain. Full article

Eukaryotic cells have complicated membrane systems. The outermost plasma membrane contains various substructures, such as invaginations and protrusions, which are involved in endocytosis and cell migration. Moreover, the intracellular membrane compartments, such as autophagosomes and endosomes, are essential for cellular viability. The Bin-Amphiphysin-Rvs167 (BAR) domain superfamily proteins are important players in membrane remodeling through their structurally determined membrane binding surfaces. A variety of BAR domain superfamily proteins exist, and each family member appears to be involved in the formation of certain subcellular structures or intracellular membrane compartments. Most of the BAR domain superfamily proteins contain SH3 domains, which bind to the membrane scission molecule, dynamin, as well as the actin regulatory WASP/WAVE proteins and several signal transduction molecules, providing possible links between the membrane and the cytoskeleton or other machineries. In this review, we summarize the current information about each BAR superfamily protein with an SH3 domain(s). The involvement of BAR domain superfamily proteins in various diseases is also discussed. Full article