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In this paper, artificial intelligence (AI) technology is applied to the electromagnetic imaging of anisotropic objects. Advances in magnetic anomaly sensing systems and electromagnetic imaging use electromagnetic principles to detect and characterize subsurface or hidden objects. We use measured multifrequency scattered fields to calculate the initial dielectric constant distribution of anisotropic objects through the backpropagation scheme (BPS). Later, the estimated multifrequency permittivity distribution is input to a convolutional neural network (CNN) for the adaptive moment estimation (ADAM) method to reconstruct a more accurate image. In the meantime, we also improve the definition of loss function in the CNN. Numerical results show that the improved loss function unifying the structural similarity index measure (SSIM) and root mean square error (RMSE) can effectively enhance image quality. In our simulation environment, noise interference is considered for both TE (transverse electric) and TM (transverse magnetic) waves to reconstruct anisotropic scatterers. Lastly, we conclude that multifrequency reconstructions are more stable and precise than single-frequency reconstructions. [ABSTRACT FROM AUTHOR]

The integration of electromagnetic imaging technology with the Internet of Things plays an important role in fields as diverse as healthcare, geophysics, and industrial diagnostics. This paper presents a novel two-step neural network architecture to solve the electromagnetic imaging for uniaxial objects which can be used in the Internet of Things. We incident TM and TE waves to unknown objects and receive the scattered fields. In order to reduce the training difficulty, we first input the gathered scattered field information into a deep convolutional neural network (DCNN) to obtain the preliminary guess. In the second step, we feed the guessed image into the convolutional neural network (CNN) to reconstruct high-resolution images. Our numerical results demonstrate the real-time imaging capability of our proposed two-step method in reconstructing high-contrast scatterers. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel artificial intelligence technique with an attention mechanism for half-space electromagnetic imaging. A dielectric object in half-space is illuminated by TM (transverse magnetic) waves. Since measurements can only be made in the upper space, the measurement angle will be limited. As a result, we apply a back-propagation scheme (BPS) to generate an initial guessed image from the measured scattered fields for scatterer buried in the lower half-space. This process can effectively reduce the high nonlinearity of the inverse scattering problem. We further input the guessed images into the generative adversarial network (GAN) and the self-attention generative adversarial network (SAGAN), respectively, to compare the reconstruction performance. Numerical results prove that both SAGAN and GAN can reconstruct dielectric objects and the MNIST dataset under same measurement conditions. Our analysis also reveals that SAGAN is able to reconstruct electromagnetic images more accurately and efficiently than GAN. [ABSTRACT FROM AUTHOR]

Transiliac–transsacral screw fixation is widely used to stabilize unstable posterior pelvic ring injuries. Preoperative radiographic assessment of the safe osseous corridor is necessary because the safe space of sacrum is narrower for transiliac–transsacral screw placement than for traditional iliosacral screw placement. However, the radiographic assessment has rarely been studied in the Taiwanese population. We retrospectively analyzed 100 patients with pelvic computed tomography images and divided them into normal and dysmorphic pelvis groups. To determine the safe osseous space, we recorded cross-section area, cross-sectional diameter of the safe zone (CS-szD), and safe zone width on axial view (Ax-szW) in the S1 to S3 segments. The prevalence of dysmorphic pelvis was 48% among all patients. In the S1 segment, no differences were found in the cross-section area and CS-szD been the two groups. However, the Ax-szW was significantly smaller in the dysmorphic pelvis group. In the S2 segment, the cross-section area, CS-szD, and Ax-szW were all significantly larger in the dysmorphic pelvis group. In the S3 segment, the cross-section area and CS-szD of the normal pelvis group were both significantly smaller. No differences were found in the Ax-szW between the two groups. Based on our findings in a Taiwanese population, S1 was the most suitable segment for transiliac–transsacral screw fixation in a normal pelvis, whereas S2, followed by S3, was most suitable in a dysmorphic pelvis. This study offers surgeons information on identifying the optimal sacral segment for transiliac–transsacral screw placement for each pelvic morphology. [Orthopedics. 2024;47(1):e13–e18.] [ABSTRACT FROM AUTHOR]

In this paper, we present the microwave imaging of anisotropic objects by artificial intelligence technology. Since the biaxial anisotropic scatterers have different dielectric constant components in different transverse directions, the problems faced by transverse electronic (TE) polarization waves are more complex than those of transverse magnetic (TM) polarization waves. In other words, measured scattered field information can scarcely reconstruct microwave images due to the high nonlinearity characteristic of TE polarization. Therefore, we first use the dominant current scheme (DCS) and the back-propagation scheme (BPS) to compute the initial guess image. We then apply a trained convolution neural network (CNN) to regenerate the microwave image. Numerical results show that the CNN possesses a good generalization ability under limited training data, which could be favorable to deploy in image processing. Finally, we compare DCS and BPS reconstruction images for anisotropic objects by the CNN and prove that DCS is better than BPS. In brief, successfully reconstructing biaxial anisotropic objects with a CNN is the contribution of this proposal. [ABSTRACT FROM AUTHOR]

Featured Application: Electromagnetic imaging. Featured applications include military measurements, medical imaging, industrial applications, underground gas pipe and electrical high-voltage cable detection, etc. In the past, many conventional algorithms, such as self-adaptive dynamic differential evolution and asynchronous particle swarm optimization, were used to reconstruct buried objects in the frequency domain; these were unfortunately time-consuming during the iterative, repeated computing process of the scattered field. Consequently, we propose an innovative deep convolutional neural network approach to solve the electromagnetic inverse scattering problem for buried conductors in this paper. Different shapes of conductors are buried in one half-space and the electromagnetic wave from the other half-space is incident. The shape of the conductor can be reconstructed promptly by inputting the received scattered fields measured from the upper half-space into the deep convolutional neural network module, which avoids the computational complexity of Green's function for training. Numerical results show that the root mean square error for differently shaped—circular, elliptical, arrow, peanut, four-petal, and three-petal—reconstructed images are, respectively, 2.95%, 3.11%, 17.81%, 15.10%, 14.14%, and 15.24%. Briefly speaking, not only can circular and elliptical buried conductors be reconstructed; some irregular shapes can be reconstructed well. On the contrary, the reconstruction result by U-Net for buried objects is worse since it is not able to obtain a good preliminary image by processing only the upper scattered field—that is, rather than the full space. In other words, our proposed deep convolutional neural network can efficiently solve the electromagnetic inverse scattering problem of buried conductors and provide a novel method for the microwave imaging of the buried conductors. This is the first successful attempt at using deep convolutional neural networks for buried conductors in the frequency domain, which may be useful for practical applications in various fields such as the medical, military, or industrial fields, including magnetic resonance imaging, mine detection and clearance, non-destructive testing, gas or wire pipeline detection, etc. [ABSTRACT FROM AUTHOR]

This research implements the whale optimization algorithm (WOA) and spotted hyena optimizer (SHO) in inverse scattering to regenerate the conductor shape concealed in the half-space. TM waves are irradiated from the other half-space to a perfect conductor with an unknown shape buried in one half-space. The scattered field measured outside the conductor surface with the boundary condition is used to reconstruct the object using the WOA and SHO algorithms. Several scenarios of reconstruction accuracy were compared for the WOA and SHO. The numerical simulations prove that the WOA has a better reconstruction capability. [ABSTRACT FROM AUTHOR]

In recent years, the social network has become popular and people have started trading transactions on the Internet. Many counterfeit websites have begun to appear which create websites with counterfeit products or use the digital advertiser's services to promote their websites on social media. Malicious sellers disguise high-quality products to attract consumers since buyers cannot receive transparent information. If there is asymmetry information, a secondary market will be formed. To solve the above problems, this research explored the machine-learning-based method to classify counterfeit and legitimate websites with symmetry information. The data set is 1612 websites used in this paper and a total of 15 feature values and takes 804 counterfeit websites and 808 legitimate websites. The Random Forest and Deep Neural Network algorithms were used to classify fake websites. This study also used statistical tests, such as Chi-square and ANOVA detection, to compare the importance of features in feature selection. The experiment results show that the RF accuracy is 99.2% and the DNN accuracy is 93.2%. The RF Precision and Recall are 100% and 98.5%, respectively. The DNN Precision and Recall are less than RF. Then, the RF F1-score is 99.2% which is higher than DNN. [ABSTRACT FROM AUTHOR]

Antenna beamforming for Simultaneous Wireless Information and Power Transfer (SWIPT) and Wireless Power Transfer (WPT) in an indoor 6G communication system is presented in this paper. The objective function is to maximize the total harvesting power for the SWIPT and WPT nodes with the constraints of the bit error rate and minimum harvesting power. In the study, the power-splitting ratio between harvesting power and decoding information can be adjusted for the SWIPT node. Due to the non-convex problem, we use Self-Adaptive Dynamic Differential Evolution (SADDE) to optimize the designed multi-objective function. We use a symmetric antenna array to study three situations of distance—closer, farther, and similar—between the transmitting antenna and the individual SWIPT and WPT nodes in this paper. Experimental results show that the overall harvesting efficiency is improved, especially in the case of SWIPT nodes closer to the transmitter. The total harvesting power can be improved by 86.7% in the total short-distance case, and by 7.87% in the total long-distance case. [ABSTRACT FROM AUTHOR]

The nucleolus is best known for its cellular role in regulating ribosome production and growth. More recently, an unanticipated role for the nucleolus in innate immunity has recently emerged whereby downregulation of fibrillarin and nucleolar contraction confers pathogen resistance across taxa. The mechanism of this downregulation, however, remains obscure. Here we report that rather than fibrillarin itself being the proximal factor in this pathway, the key player is a fibrillarin‐stabilizing deubiquitinylase USP‐33. This was discovered by a candidate‐gene search of Caenorhabditis elegans in which CED‐3 caspase was revealed to execute targeted cleavage of USP‐33, thus destabilizing fibrillarin. We also showed that cep‐1 and ced‐3 mutant worms altered nucleolar size and decreased antimicrobial peptide gene, spp‐1, expression rendering susceptibility to bacterial infection. These phenotypes were reversed by usp‐33 knockdown, thus linking the CEP‐1‐CED‐3‐USP‐33 pathway with nucleolar control and resistance to bacterial infection in worms. Parallel experiments with the human analogs of caspases and USP36 revealed similar roles in coordinating these two processes. In summary, our work outlined a conserved cascade that connects cell death signaling to nucleolar control and innate immune response. [ABSTRACT FROM AUTHOR]

Ribosome biogenesis takes place in the nucleolus, the size of which is often coordinated with cell growth and development. However, how metazoans control nucleolar size remains largely unknown. Caenorhabditis elegans provides a good model to address this question owing to distinct tissue distribution of nucleolar sizes and a mutant, ncl-1, which exhibits larger nucleoli than wild-type worms. Here, through a series of loss-of-function analyses, we report that the nucleolar size is regulated by a circuitry composed of microRNA let-7, translation repressor NCL-1, and a major nucleolar pre-rRNA processing protein FIB-1/fibrillarin. In cooperation with RNA binding proteins PUF and NOS, NCL-1 suppressed the translation of FIB-1/fibrillarin, while let-7 targeted the 3’UTR of ncl-1 and inhibited its expression. Consequently, the abundance of FIB-1 is tightly controlled and correlated with the nucleolar size. Together, our findings highlight a novel genetic cascade by which post-transcriptional regulators interplay in developmental control of nucleolar size and function. [ABSTRACT FROM AUTHOR]

Normal embryogenesis requires complex regulation and precision, which depends on multiple mechanistic details. Defective embryogenesis can occur by various mechanisms. Maintaining redox homeostasis is of importance during embryogenesis. NADPH, as produced from the action of glucose-6-phosphate dehydrogenase (G6PD), has an important role in redox homeostasis, serving as a cofactor for glutathione reductase in the recycling of glutathione from oxidized glutathione and for NADPH oxidases and nitric oxide synthases in the generation of reactive oxygen (ROS) and nitrogen species (RNS). Oxidative stress differentially influences cell fate and embryogenesis. While low levels of stress (eustress) by ROS and RNS promote cell growth and differentiation, supra-physiological concentrations of ROS and RNS can lead to cell demise and embryonic lethality. G6PD-deficient cells and organisms have been used as models in embryogenesis for determining the role of redox signaling in regulating cell proliferation, differentiation and migration. Embryogenesis is also modulated by anti-oxidant enzymes, transcription factors, microRNAs, growth factors and signaling pathways, which are dependent on redox regulation. Crosstalk among transcription factors, microRNAs and redox signaling is essential for embryogenesis. [ABSTRACT FROM AUTHOR]

Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and Harvesting Power (HP) are investigated in the broadband communication. Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Self-Adaptive Dynamic Differential Evolution (SADDE) and Asynchronous Particle Swarm Optimization (APSO) are used to optimize the feed length of the antenna array. Two different object functions are proposed in the paper. The first one is the weighting factor multiplying the constraint BER and HP plus HP. The second one is the constraint BER multiplying HP. Simulations show that the first object function is capable of optimizing the total harvesting power under the BER constraint and APSO can quickly converges quicker than SADDE. However, the weighting for the final object function requires a pretest in advance, whereas the second object function does not need to set the weighting case by case and the searching is more efficient than the first one. From the numerical results, the proposed criterion can achieve the SWIPT requirement. Thus, we can use the novel proposed criterion (the second criterion) to optimize the SWIPT problem without testing the weighting case by case. [ABSTRACT FROM AUTHOR]