Nonlinear photonics on integrated platforms.

Nonlinear photonics has unveiled new avenues for applications in metrology, spectroscopy, and optical communications. Recently, there has been a surge of interest in integrated platforms, attributed to their fundamental benefits, including compatibility with complementary metal-oxide semiconductor (CMOS) processes, reduced power consumption, compactness, and cost-effectiveness. This paper provides a comprehensive review of the key nonlinear effects and material properties utilized in integrated platforms.

Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization.

With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researchers developed various approaches to solve the automatic hate speech detection problem using different corpora in various languages, however, research on the Urdu language is rather scarce.

HiMolformer: Integrating graph and sequence representations for predicting liver microsome stability with SMILES.

In the initial stages of drug discovery or pre-clinical studies, understanding the metabolic stability of new molecules is crucial. Recently, research on pre-trained deep learning for molecular property prediction has been actively progressing, with various models being made open-source. However, most of these models rely on either 2D graph or 1D sequence for training, and the representation varies depending on the data format used.

Deep-AutoMO: Deep automated multiobjective neural network for trustworthy lesion malignancy diagnosis in the early stage via digital breast tomosynthesis.

Breast cancer is the most prevalent cancer in women, and early diagnosis of malignant lesions is crucial for developing treatment plans. Digital breast tomosynthesis (DBT) has emerged as a valuable tool for early breast cancer detection, as it can identify more lesions and improve the early detection rate. Deep learning has shown great potential in medical image-based cancer diagnosis, including DBT.

Dual-Band Monopole MIMO Antenna Array for UAV Communication Systems.

This study proposes a compact, low-profile, four-port dual-band monopole multiple-input-multiple-output (MIMO) antenna array for unmanned aerial vehicle (UAV) communication systems. Each monopole antenna of the array features a modified T-shaped radiator configuration and is printed on a Rogers RT5880 substrate with compact dimensions of 134.96 mm × 134.

A Novel Two-Step Channel Estimation Method for RIS-Assisted mmWave Systems.

In this work, we resolve the cascaded channel estimation problem and the reflected channel estimation problem for the reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) systems. The novel two-step method contains modified multiple population genetic algorithm (MMPGA), least squares (LS), residual network (ResNet), and multi-task regression model. In the first step, the proposed MMPGA-LS optimizes the crossover strategy and mutation strategy.

Compact Silicon-Arrayed Waveguide Gratings with Low Nonuniformity.

Array waveguide gratings (AWGs) have been widely used in multi-purpose and multi-functional integrated photonic devices for Microwave photonics (MWP) systems. In this paper, we compare the effect of output waveguide configurations on the performance of AWGs. The AWG with an output waveguide converging on the grating circle had larger crosstalk and lower nonuniformity.

Dual-Band Antenna Array Fed by Ridge Gap Waveguide with Dual-Periodic Interdigital-Pin Bed of Nails.

A dual-band (K-/Ka-band) antenna array is presented. An ultra-wideband antenna element in the shape of a double-ridged waveguide is used as a radiation slot, and a novel dual-periodic ridge gap waveguide (RGW) with an interdigital-pin bed of nails (serving as a filter) is used to realize dual-band operation. By periodically arranging the pins of two different heights in two dimensions, the proposed RGW with interdigital-pin bed of nails is able to realize and flexibly adjust two passbands.

A veracity dissemination consistency-based few-shot fake news detection framework by synergizing adversarial and contrastive self-supervised learning.

With the rapid growth of social media, fake news (rumors) are rampant online, seriously endangering the health of mainstream social consciousness. Fake news detection (FEND), as a machine learning solution for automatically identifying fake news on Internet, is increasingly gaining the attentions of academic community and researchers. Recently, the mainstream FEND approaches relying on deep learning primarily involves fully supervised fine-tuning paradigms based on pre-trained language models (PLMs), relying on large annotated datasets.

Extraction and Validation of Biomechanical Gait Parameters with Contactless FMCW Radar.

A 77 GHz frequency-modulated continuous wave (FMCW) radar was utilized to extract biomechanical parameters for gait analysis in indoor scenarios. By preprocessing the collected raw radar data and eliminating environmental noise, a range-velocity-time (RVT) data cube encompassing the subjects' information was derived. The strongest signals from the torso in the velocity and range dimensions and the enveloped signal from the toe in the velocity dimension were individually separated for the gait parameters extraction.

Fast Low-Sidelobe Pattern Synthesis Using the Symmetry of Array Geometry.

Array pattern synthesis with low sidelobe levels is widely used in practice. An effective way to incorporate sensor patterns in the design procedure is to use numerical optimization methods. However, the dimension of the optimization variables is very high for large-scale arrays, leading to high computational complexity.

A Flexible Terahertz Metamaterial Sensor for Pesticide Sensing and Detection.

Terahertz (THz) waves have garnered significant interest across various fields, particularly in high-sensitivity sensing applications. Metamaterials can be employed in THz sensors, specifically for refractive index sensing and pesticide detection due to their high-sensitivity characteristics. In this Article, a dual-band flexible THz metamaterial sensor based on polyimide is proposed for refractive index and pesticide sensing, which is fabricated using ultraviolet (UV) lithography technology and measured by a THz time-domain spectroscope (TDS) system.

A frequency-response-optimized Shack-Hartmann zonal wavefront reconstructor based on Fan's model.

This paper introduces an optimized method for zonal wavefront reconstruction utilizing Fan's model, specifically tailored to enhance the frequency response. Analysis of the system frequency response demonstrates a 27% increase in bandwidth compared to the Southwell model. Examination of reconstruction errors at various frequency points reveals consistently smaller values when compared to the Southwell model.

Multi-scale perceptual YOLO for automatic detection of clue cells and trichomonas in fluorescence microscopic images.

Vaginitis is a common disease among women and has a high recurrence rate. The primary diagnosis method is fluorescence microscopic inspection, but manual inspection is inefficient and can lead to false detection or missed detection. Automatic cell identification and localization in microscopic images are necessary.

Emission of five OAM dispersive waves in dispersion-engineered double-ring core fiber.

Beams carrying orbital angular momentum (OAM) have exhibited significant potential across various fields, such as metrology, image coding, and optical communications. High-performance broadband coherent OAM sources are critical to the operation of optical systems. The emission of dispersive waves facilitates the efficient transfer of energy to distant spectral domains while preserving the coherence among the generated frequency components.

Dual-Polarization Ambient Backscatter Communications and Signal Detection.

Ambient backscatter communication (AmBC), an emerging mechanism for batteryless communications that can utilize ambient radio-frequency signals to modulate information and thus reduce power consumption, has attracted considerable attention and has been considered as a critical technology in green "Internet of Things" sensor networks due to its ultra-low power consumption. This paper presents the first a complete dual-polarization AmBC (DPAm) system model, which can extend AmBC into polarization diversity and improve the data-transmission rate of backscatter symbols. We proposed two scenarios: direct dual-polarization-based DPAm node structures and polarization-conversion-based DPAm node structures.

CMID: Crossmodal Image Denoising via Pixel-Wise Deep Reinforcement Learning.

Removing noise from acquired images is a crucial step in various image processing and computer vision tasks. However, the existing methods primarily focus on removing specific noise and ignore the ability to work across modalities, resulting in limited generalization performance. Inspired by the iterative procedure of image processing used by professionals, we propose a pixel-wise crossmodal image-denoising method based on deep reinforcement learning to effectively handle noise across modalities.

Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models.

The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has succeeded in various fields such as vision, speech, and text processing. Yet genomics entails unique challenges to deep learning, since we expect a superhuman intelligence that explores beyond our knowledge to interpret the genome from deep learning.

Machine Log File and Calibration Errors-based Patient-specific Quality Assurance (QA) for Volumetric Modulated Arc Therapy (VMAT).

Introduction: Dose reconstructed based on linear accelerator (linac) log-files is one of the widely used solutions to perform patient-specific quality assurance (QA). However, it has a drawback that the accuracy of log-file is highly dependent on the linac calibration. The objective of the current study is to represent a new practical approach for a patient-specific QA during Volumetric modulated arc therapy (VMAT) using both log-file and calibration errors of linac.

A Short Video Classification Framework Based on Cross-Modal Fusion.

The explosive growth of online short videos has brought great challenges to the efficient management of video content classification, retrieval, and recommendation. Video features for video management can be extracted from video image frames by various algorithms, and they have been proven to be effective in the video classification of sensor systems. However, frame-by-frame processing of video image frames not only requires huge computing power, but also classification algorithms based on a single modality of video features cannot meet the accuracy requirements in specific scenarios.

A Four-Port MIMO Cylindrical DRA with High Isolation in Ultra-Compact Size for WLAN Applications.

A novel ultra-compact four-port multiple-input-multiple-output (MIMO) cylindrical dielectric resonator antenna (DRA) with improved isolation is proposed for WLAN applications in this paper. The antenna is originally radiated with the assistance of two different excitation mechanisms to generate decoupled orthogonal modes. To further diminish the coupling field and improve the isolation, a suitable U-shaped slot is created on the common ground plane.