Low-Frequency Raman Modes and Electronic Excitations In Atomically Thin MoS2 Crystals

Atomically thin MoS$_{2}$ crystals have been recognized as a quasi-2D semiconductor with remarkable physics properties. This letter reports our Raman scattering measurements on multilayer and monolayer MoS$_{2}$, especially in the low-frequency range ($<$50 cm$^{-1}$). We find two low-frequency Raman modes with contrasting thickness dependence. With increasing the number of MoS$_{2}$ layers, one shows a significant increase in frequency while the other decreases following a 1/N (N denotes layer-number) trend. With the aid of first-principle calculations we assign the former as the shear mode $E_{2g}^{2}$ and the latter as the compression vibrational mode. The opposite evolution of the two modes with thickness demonstrates novel vibrational modes in atomically thin crystal as well as a new and more precise way to characterize thickness of atomically thin MoS$_{2}$ films. In addition, we observe a broad feature around 38 cm$^{-1}$ (~5 meV) which is visible only under near-resonance excitation and pinned at the fixed energy independent of thickness. We interpret the feature as an electronic Raman scattering associated with the spin-orbit coupling induced splitting in conduction band at K points in their Brillouin zone.Comment: 5 pages, 4 figure

MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing

Manga is a world popular comic form originated in Japan, which typically employs black-and-white stroke lines and geometric exaggeration to describe humans' appearances, poses, and actions. In this paper, we propose MangaGAN, the first method based on Generative Adversarial Network (GAN) for unpaired photo-to-manga translation. Inspired by how experienced manga artists draw manga, MangaGAN generates the geometric features of manga face by a designed GAN model and delicately translates each facial region into the manga domain by a tailored multi-GANs architecture. For training MangaGAN, we construct a new dataset collected from a popular manga work, containing manga facial features, landmarks, bodies, and so on. Moreover, to produce high-quality manga faces, we further propose a structural smoothing loss to smooth stroke-lines and avoid noisy pixels, and a similarity preserving module to improve the similarity between domains of photo and manga. Extensive experiments show that MangaGAN can produce high-quality manga faces which preserve both the facial similarity and a popular manga style, and outperforms other related state-of-the-art methods.Comment: 17 page

A universal optical modulator for synthetic topologically tuneable structured matter

Topologically structured matter, such as metasurfaces and metamaterials, have given rise to impressive photonic functionality, fuelling diverse applications from microscopy and holography to encryption and communication. Presently these solutions are limited by their largely static nature and preset functionality, hindering applications that demand dynamic photonic systems with reconfigurable topologies. Here we demonstrate a universal optical modulator that implements topologically tuneable structured matter as virtual pixels derived from cascading low functionality tuneable devices, altering the paradigm of phase and amplitude control to encompass arbitrary spatially varying retarders in a synthetic structured matter device. Our approach opens unprecedented functionality that is user-defined with high flexibility, allowing our synthetic structured matter to act as an information carrier, beam generator, analyser, and corrector, opening an exciting path to tuneable topologies of light and matter

Adaptive optics and remote focusing in biomedical microscopy

Optical microscopy has been an indispensable tool for many biomedical applications. Compared to rapid developments in research labs striving for higher spatio-temporal resolution and information extraction effcacy, advances towards the clinic, especially those targeted at surgical applications, have been slow in comparison. Complex practicalities make the translation of cutting-edge technology much more challenging. Consequently, there is a constant need to address the limitations of conventional medical imaging devices using optical techniques and to develop new instrumentation that is task-oriented and capable of providing stabilised real-time high-resolution image guidance for improved surgical outcome. In particular, imaging in the human brain entails the most stringent requirements, for which label-free techniques would be most beneficial. Apart from the microscope design, optical aberrations also affect the image quality. Until now, the concept of adaptive optics (AO) has not been introduced to surgical microscopy, as it most noticeably benefits systems with higher theoretical resolution. For a high-resolution surgical microscope, AO would have many roles to play, making its integration a potentially rewarding and meaningful contribution. This thesis concerns to date the focused development of a compact and contactless label-free neurosurgical microscope and the investigation of using AO methods to address practical needs in surgical scenarios. Specifically, a long-working-distance reflectance confocal microscope was designed and built with special considerations for compactness and portable transit. It provides cellular-level resolution over wide imaging fields of view (FOVs) and visualises individual cells even in normal brain tissue exhibiting minimal label-free image contrast. The elimination of direct tissue contact and fluorescence labelling also greatly reduces surgical risk and complexity. Closed-loop sensor-based AO and remote focusing was later implemented and characterised following the development of an open-source Python software, SenAOReFoc, which is now publicly available on GitHub https://github.com/jiahecui/SenAOReFoc for the wider community. It was designed with a user-friendly graphic user interface and modular functional units for easy integration into existing AO microscopes. The use of remote focusing for fast axial scanning avoids slow mechanical movements of the translation stage and simultaneously corrects for system aberrations at each refocusing depth. Both volumetric and depth-wise random access imaging functions have been enabled. To fulfil requirements for real-time display in clinical settings, some post-processing and image enhancement techniques are then demonstrated to remove image artefacts and improve image contrast with minimal computational effort. An extended range autofocusing technique that combines remote focusing with sequence-dependent learning using a bi-directional long short term memory network was developed to address possible respiratory and pulsing movements during surgery. A much larger system-aberration-free autofocusing range as compared to conventional methods was achieved in tissue both exposed to air and immersed in liquid. Network generality has been validated for different imaging FOVs and for specimens not seen during the network training process. Continuous tracking of axial sample motion has also been demonstrated under varying experimental conditions. In the remainder of this thesis, a generalised AO method was proposed for high-numerical aperture aberration-free refocusing in refractive-index-mismatched media involving both stage translation and remote focusing. Two new sets of orthogonal modes were established using QR decomposition for either independent or balanced remote focusing and refractive index mismatch correction. Finally, first investigations of multi-conjugate AO in microscopy were carried out to correct for spatially-variant aberrations and increase the imaging FOV. For this purpose and to incorporate different imaging and AO modalities in the same system, a multi-purpose AO microscope was designed and developed beforehand

Debonding Detection in Grouted Sleeves Using Axisymmetric Longitudinal Guided Waves

Grouted sleeves (GSs) are a type of precast joint that can effectively connect steel rebars with excellent performance. However, the grouting debonding problem, which can occur due to the leakage of the glue plug, can seriously affect the properties of GSs. In this paper, a guided-wave-based structural health monitoring (SHM) method is used to detect debonding in GSs. The axisymmetric longitudinal mode is selected as the incident wave since it is sensitive to axial damage. Eight piezoelectrics (PZTs) are then symmetrically installed to actuate signals. The proposed samples are GSs with four different debonding sizes. First, the relationship between the arrival time of the first wave packet and the debonding size is explored through theoretical derivation. The arrival time decreases linearly with an increasing debonding size. A similar trend is observed when the relationship is verified via a numerical simulation and experimental results. This method will provide a reference for detecting debonding in similar GS multilayer structures

Supporting dataset for Extended range and aberration-free autofocusing via remote focusing and sequence-dependent learning

Extended range and aberration-free autofocusing via remote focusing and sequence-dependent learning Jiahe Cui, Raphael Turcotte, Nigel J. Emptage, Martin J. Booth https://doi.org/10.1364/OE.442025 This folder contains Bi-LSTM network training data and experimental data in forms of Matlab files, Excel files, and Tiff images. The data is grouped by figure number in the paper. Inkscape software was used to create the system schematic, AF workflow, and Bi-LSTM network architecture diagrams in Fig. 1, Fig. 2, and Fig. 4. Matlab software was used to process and analyse raw datasets, Python software was used to build the Bi-LSTM network, ImageJ software was used to process raw images, and Inkscape software was used to rearrange the figure layout

Supporting dataset for Extended range and aberration-free autofocusing via remote focusing and sequence-dependent learning

Extended range and aberration-free autofocusing via remote focusing and sequence-dependent learning Jiahe Cui, Raphael Turcotte, Nigel J. Emptage, Martin J. Booth https://doi.org/10.1364/OE.442025 This folder contains Bi-LSTM network training data and experimental data in forms of Matlab files, Excel files, and Tiff images. The data is grouped by figure number in the paper. Inkscape software was used to create the system schematic, AF workflow, and Bi-LSTM network architecture diagrams in Fig. 1, Fig. 2, and Fig. 4. Matlab software was used to process and analyse raw datasets, Python software was used to build the Bi-LSTM network, ImageJ software was used to process raw images, and Inkscape software was used to rearrange the figure layout

Trends in parthenolide research over the past two decades: A bibliometric analysis

Parthenolide (PTL) is a new compound extracted from traditional Chinese medicine. In recent years, it has been proven to play an undeniable role in tumors, autoimmune diseases, and inflammatory diseases. Similarly, an increasing number of experiments have also confirmed the biological mechanism of PTL in these diseases. In order to better understand the development trend and potential hot spots of PTL in cancer and other diseases, we conducted a detailed bibliometric analysis. The purpose of presenting this bibliometric analysis was to highlight and inform researchers of the important research directions, co-occurrence relationships and research status in this field. Publications related to PTL research from 2002 to 2022 were extracted on the web of science core collection (WoSCC) platform. CiteSpace, VOSviewers and R package “bibliometrix” were applied to build relevant network diagrams. The bibliometric analysis was presented in terms of performance analysis (including publication statistics, top publishing countries, top publishing institutions, publishing journals and co-cited journals, authors and co-cited authors, co-cited references statistics, citation bursts statistics, keyword statistics and trend topic statistics) and science mapping (including citations by country, citations by institution, citations by journal, citations by author, co-citation analysis, and keyword co-occurrence). The detailed discussion of the results explained the focus and latest trends from the bibliometric analysis. Finally, the current status and shortcomings of the research field on PTLwere clearly pointed out for reference by scholars