A super-resolution imaging approach via subwavelength hole resonances

This work presents a new super-resolution imaging approach by using subwavelength hole resonances. We employ a subwavelength structure in which an array of tiny holes are etched in a metallic slab with the neighboring distance $\ell$ that is smaller than half of the wavelength. By tuning the incident wave at resonant frequencies, the subwavelength structure generates strong illumination patterns that are able to probe both low and high spatial frequency components of the imaging sample sitting above the structure. The image of the sample is obtained by performing stable numerical reconstruction from the far-field measurement of the diffracted wave. It is demonstrated that a resolution of $\ell/2$ can be obtained for reconstructed images, thus one can achieve super-resolution by arranging multiple holes within one wavelength. The proposed approach may find applications in wave-based imaging such as electromagnetic and ultrasound imaging. It attains two advantages that are important for practical realization. It avoids the difficulty to control the distance the between the probe and the sample surface with high precision. In addition, the numerical reconstructed images are very stable against noise by only using the low frequency band of the far-field data in the numerical reconstruction

Data_Sheet_1_Integrating teacher data literacy with TPACK: A self-report study based on a novel framework for teachers' professional development.xls

While teachers' knowledge is widely viewed as a key aspect of professional development in the new era, little research attention has been paid to one of its key components: teacher data literacy. Accordingly, this study aimed to combine teacher data literacy with TPACK (technological pedagogical content knowledge), a widely-used framework for understanding and assessing teachers' knowledge. We first used qualitative methods to develop this integrated framework, then distributed a quantitative self-report survey based on the framework to teachers, and analyzed the resulting data. The qualitative phase highlighted five types of teachers' knowledge required in an integrated core knowledge system incorporating data literacy and provided insights for reflecting on teaching and learning in smart learning environments. The quantitative analysis of data from the TDL-TPACK questionnaire indicated that most teachers were competent practitioners but had some areas for improvement. Experienced teachers in their 30s and 40s performed at higher levels, while some of those aged over 50 displayed incremental decreases in performance. Other factors such as the age, experience, academic qualifications, and role of teachers may affect different aspects of their knowledge, including their data literacy. The research findings provide useful insights for additional teacher training and development programs in the context of smart education.</p

Mathematical theory for electromagnetic scattering resonances and field enhancement in a subwavelength annular gap

This work presents a mathematical theory for electromagnetic scattering resonances in a subwavelength annular hole embedded in a metallic slab, with the annulus width $h\ll1$. The model is representative among many 3D subwavelength hole structures, which are able to induce resonant scattering of electromagnetic wave and the so-called extraordinary optical transmission. We develop a multiscale framework for the underlying scattering problem based upon a combination of the integral equation in the exterior domain and the waveguide mode expansion inside the tiny hole. The matching of the electromagnetic field over the hole aperture leads to a sequence of decoupled infinite systems, which are used to set up the resonance conditions for the scattering problem. By performing rigorous analysis for the infinite systems and the resonance conditions, we characterize all the resonances in a bounded domain over the complex plane. It is shown that the resonances are associated with the TE and TEM waveguide modes in the annular hole, and they are close to the real axis with the imaginary parts of order ${\cal O}(h)$. We also investigate the resonant scattering when an incident wave is present. It is proved that the electromagnetic field is amplified with order ${\cal O}(1/h)$ at the resonant frequencies that are associated with the TE modes in the annular hole. On the other hand, one particular resonance associated with the TEM mode can not be excited by a plane wave but can be excited with a near-field electric dipole source, leading to field enhancement of order ${\cal O}(1/h)$

Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Spectral clustering has been one of the widely used methods for community detection in networks. However, large-scale networks bring computational challenges to the eigenvalue decomposition therein. In this paper, we study the spectral clustering using randomized sketching algorithms from a statistical perspective, where we typically assume the network data are generated from a stochastic block model that is not necessarily of full rank. To do this, we first use the recently developed sketching algorithms to obtain two randomized spectral clustering algorithms, namely, the random projection-based and the random sampling-based spectral clustering. Then we study the theoretical bounds of the resulting algorithms in terms of the approximation error for the population adjacency matrix, the misclassification error, and the estimation error for the link probability matrix. It turns out that, under mild conditions, the randomized spectral clustering algorithms lead to the same theoretical bounds as those of the original spectral clustering algorithm. We also extend the results to degree-corrected stochastic block models. Numerical experiments support our theoretical findings and show the efficiency of randomized methods. A new R package called Rclust is developed and made available to the public. Supplementary materials for this article are available online.</p

Effect of Volatile-Char Interaction on Biochar Containing N/O-Functional Group During Reburning Denitrification

The influence of functional groups such as N/O and microcrystalline structure in biochar on NO reduction is critical. The interaction between volatile and char can significantly alter the activity of char, thereby altering its ability to reduce NO. Unfortunately, the impact of this interaction on NO reduction is still unclear. In this study, the effect of this interaction at 900°C on the physicochemical structure of model biochar containing N/O-functional group during reburning denitrification was investigated. This paper simulates the volatile of reactive species containing H and O through pyrolysis of polyethylene and polyethylene glycol, respectively. The results indicate that the H- and O-containing reactive species play distinct roles during the interaction between volatile and char, but both species consume the amorphous carbon structure. The H-containing actives significantly increased the condensation of the aromatic rings and the O and N contents of the char decreased by 1.36% and 0.43% respectively. There were also significant interconversions between the N functional groups, with the content of N-5 increasing by 12% and that of N-6 by 2%. Consequently, the ability of char to reduce NO decreased by 29%. The O-containing reactive species will react with the char to form C-O composite oxides, thus increasing the O content with 1.88% and preventing the carbon structure from being condensed into a large aromatic ring system. Simultaneously, it was found that after the action of O-containing reactive species, the content of N decreased by 0.9%, and the N functional group tended to convert to N-5 (pyrrole or pyridone), increasing its content by 27%. Furthermore, char activity was significantly increased and NO reduction capacity increased by 19%.</p

SE-ResNet architectures for Cifar.

Building modules are shown in brackets, with the numbers of modules stacked. Downsampling is performed by conv3_1, conv4_1, and conv5_1 with a stride of 2.</p

Data_Sheet_2_Effect of blended teaching on college students' EFL acquisition.PDF

The research into the efficacy of blended EFL (English as a Foreign Language) teaching at the collegiate level holds significant importance for comprehending and implementing this novel pedagogical approach on a larger scale within universities. Within this domain, scholars have primarily concentrated on feedback mechanisms and quality assurance, while comparatively neglecting the advancement of college students' foreign language proficiency and the individual variances in the acceptance and rewards of blended teaching across distinct language proficiency groups. In light of this, leveraging micro-data from a provincial normal university's blended college English teaching, this study employs R 3.6.1 and R Studio to implement multiple linear regression and conditional quantile models so as to assess the impact of blended teaching on different language proficiency groups across four dimensions: listening, reading, writing, and overall language proficiency. To mitigate endogenous system risk, students admitted to the same major are selected as samples and their data undergoes additional screening, excluding learners who failed the CET4 exam or did not participate in the CET6 exam. After employing purposive sampling techniques, a valid sample of 676 learners is established, comprising 363 learners in the experimental group for blended teaching intervention and 313 learners in the control group receiving traditional teaching. The study results indicates that the samples had random characteristics. The study findings suggest the following: (1) Blended teaching has a significant positive impact on enhancing the efficiency of English acquisition. (2) The effectiveness of blended teaching in improving learners' reading, listening, and writing skills follows a sequential decrease, exhibiting a downward trend as students' language ability increases. This indicates that blended teaching facilitates the acquisition of foundational language knowledge, however, its impact on more advanced language processing abilities is limited. (3) Blended teaching demonstrates a range effect, primarily benefiting learners at the intermediate level and below in terms of enhancing their language proficiency. Conversely, learners at the medium-high and high proficiency levels derive comparatively lesser benefits from this approach. This study introduces a new methodology by employing multiple linear regression and conditional quantile models to assess the impact of blended teaching. This methodology not only enables us to examine the overall impact of blended teaching, but also allows assessment of its effect on different proficiency groups, helping to identify its effectiveness on individual learners across four dimensions.</p

The accuracies performance of BHCNet-3 for the binary classification.

The accuracies performance of BHCNet-3 for the binary classification.</p

Semiempirical Model of the Drag Force Acting on an Obstacle in Downward Dense Particle Flows as per the Flow-Around Behavior

Determination of the flow-around drag force acting on an internal when particles downwardly flow around the internal is important for the safety of internals in the downward particle flow channel. In this study, the flow behaviors of particles downwardly flowing around different obstacles were investigated and a semiempirical drag force model was proposed based on the characteristics of the flow patterns. The proposed model was validated and key coefficients were correlated using the experimental data. The results indicate that there were three featured flow zones when particles downwardly flowed around an obstacle: the flow stagnant zone (disappear for triangular/conical obstacle), the slip-shear flow zone, and the flow separation zone. The stagnant zone angle and the flow separation angle were proposed to depict transition points of three flow zones when particles flowed around a cylindrical/spherical obstacle, and the two angles were found independent of the flow condition. A drag force model as per the flow patterns was proposed. The model decomposed the drag force into the compression force, the shear force, and the confinement force. The expressions of the compression stress, the shear stress, the effective area, and the confinement force were given. The mathematical form of the proposed model was validated and key coefficients in this model were also correlated using the experimental data. The average error of the drag force model was ±7.6% while the maximum error was within ±15%