All-fiber single-cavity dual-comb for coherent anti-Stokes Raman scattering spectroscopy based on spectral focusing.

We report an all-fiber free-running bidirectional dual-comb laser system for coherent anti-Stokes Raman scattering spectroscopy based on spectral focusing. The mode-locked oscillator is a bidirectional ring-cavity erbium fiber laser running at a repetition rate of ∼114MHz. One output of the bidirectional laser is wavelength-shifted from 1560 to 1060 nm via supercontinuum generation for use as the pump source. We have been able to record the Raman spectra of various samples such as polystyrene, olive oil, polymethyl methacrylate (PMMA), and polyethylene in the C-H stretching window. We believe that this all-fiber laser design has promising potential for coherent Raman spectroscopy and also label-free imaging for a variety of practical applications.

All-fiber high-power 1700 nm femtosecond laser based on optical parametric chirped-pulse amplification.

We present the design and construction of an all-fiber high-power optical parametric chirped-pulse amplifier working at 1700 nm, an important wavelength for bio-photonics and medical treatments. The laser delivers 1.42 W of output average power at 1700 nm, which corresponds to ∼40 nJ pulse energy. The pulse can be de-chirped with a conventional grating pair compressor to ∼450 fs. Furthermore, the laser has a stable performance with relative intensity noise typically below the -130 dBc/Hz level for the idler pulses at 1700 nm from 10kHz to 16.95 MHz, half of the laser repetition rate f/2.

Characterization of multiphoton microscopes by the nonlinear knife-edge technique.

Imaging submicron fluorescent microspheres are the standard method for measuring resolution in multiphoton microscopy. However, when using high-energy pulsed lasers, photobleaching and heating of the solution medium may deteriorate the images, resulting in an inaccurate resolution measurement. Moreover, due to the weak higher-order response of fluorescent microspheres, measuring three-photon resolution using three-photon fluorescence (3PEF) and third-harmonic generation (THG) signals is more difficult. In this report, we demonstrate a methodology for complete characterization of multiphoton microscopes based on second- and third-harmonic generation signals from the sharp edge of GaAs wafers. This simple methodology, which we call the nonlinear knife-edge technique, provides fast and consistent lateral and axial resolution measurement with negligible photobleaching effect on semiconductor wafers. In addition, this technique provides information on the field curvature of the imaging system, and perhaps other distortions of the imaging system, adding greater capability compared to existing techniques.

Feasibility of multimodal multiphoton microscopy to facilitate surgical margin assessment in pancreatic cancer.

Pancreatic cancer is a common cancer with poor odds of survival for the patient, with surgical resection offering the only hope of cure. Current surgical practice is time-consuming and, due to time constraints, does not sample the whole cut surface sufficiently to check for remaining cancer. Although microscopy with hematoxylin and eosin (H&E) stain is the gold standard for microscopic evaluation, multiphoton microscopy (MPM) has emerged as an alternative tool for imaging tissue architecture and cellular morphology without labels. We explored the use of multimodal MPM for the label-free identification of normal and cancerous tissue of the pancreas in a mouse model by comparing the images to H&E microscopy. Our early studies indicate that MPM using second-harmonic generation, third-harmonic generation, and multiphoton excitation of endogenous fluorescent proteins can each contribute to the label-free analysis of the pancreatic surgical margin.

Watt-level all-fiber optical parametric chirped-pulse amplifier working at 1300 nm.

We report watt-level average output power near 1300 nm from an all-fiber ultrafast optical parametric chirped-pulse amplifier. A compressed output pulse duration of ∼300 fs is achieved. Multiphoton imaging of a variety of samples carried out with this light source shows a good signal-to-noise ratio. With the demonstrated imaging capability, we believe that this high-power ultrafast laser source addresses a key need in deep tissue multiphoton microscopy.

All-fiber dissipative soliton Raman laser based on phosphosilicate fiber.

We propose and demonstrate an all-fiber, synchronously pumped Raman laser based on phosphosilicate fiber (P-doped fiber) for deep tissue multiphoton imaging. The laser operates in a dissipative soliton regime and produces 2.2 ps chirped pulses (compressible to 317 fs) with energy up to 9.2 nJ, 0.3 W average power and at 1240 nm center wavelength. We have also found a new cross-polarization Raman lasing operation that offers access to an important wavelength near 930 nm for calcium imaging.

All-reflective multiphoton microscope.

We present the design, construction, and characterization of a multiphoton microscope that uses reflective elements for beam shaping and steering. This compact all reflective design removes the adverse effects of dispersion on laser pulse broadening as well as chromatic aberration in the focusing of broadband and multicolored laser sources. The design of this system is discussed in detail, including aberrations analysis via ray-tracing simulation and opto-mechanical design. The resolution of this mirror based all-reflective microscope is characterized using fluorescent microbeads. The performance of the system at multiple wavelengths is investigated along with some potential multiphoton imaging and writing applications.

Optical characterization of directly deposited graphene on a dielectric substrate.

By using scanning multiphoton microscopy we compare the nonlinear optical properties of the directly deposited and transferred to the dielectric substrate graphene. The direct deposition of graphene on oxidized silicon wafer was done by utilizing sacrificial copper catalyst film. We demonstrate that the directly deposited graphene and bi-layered transferred graphene produce comparable third harmonic signals and have almost the same damage thresholds. Therefore, we believe directly deposited graphene is suitable for the use of e.g. nanofabricated optical setups.

Silicon nanoridge array waveguides for nonlinear and sensing applications.

We fabricate and characterize waveguides composed of closely spaced and longitudinally oriented silicon ridges etched into silicon-on-insulator wafers. Through both guided mode and bulk measurements, we demonstrate that the patterning of silicon waveguides on such a deeply subwavelength scale is desirable for nonlinear and sensing applications alike. The proposed waveguide geometry simultaneously exhibits comparable propagation losses to similar schemes proposed in literature, an enhanced effective third-order nonlinear susceptibility, and high sensitivity to perturbations in its environment.

Multiphoton microscopy as a detection tool for photobleaching of EO materials.

Multi-photon microscopy operating at 1550 nm is employed as a rapid characterization tool for studying the photostability of three well-known electro-optical materials. Different nonlinear optical responses such as multi-photon excitation fluoresence, second-, and third-harmonic generation can be used as detection probes to reveal the degradation mechanisms. This technique is rapid, accurate, and can be used to study the photostability of a broad range of materials.

Observation of two-photon fluorescence for Rhodamine 6G in microbubble resonators.

We report an observation of multi-photon excitation of organic chromophores in microbubble whispering gallery mode resonators. High-Q microbubble resonators were formed by heating a pressurized fused silica capillary to form a hollow bubble that was then filled with liquid. In this work, the microbubble was filled with a solution of Rhodamine 6G dye. The resonator and dye were excited by evanescently coupling continuous wave (CW) light from a 980 nm laser diode using a tapered optical fiber. The two-photon fluorescence of the dye can be seen with pump powers as low as 700 µW.

Self-supervised anomaly detection in computer vision and beyond: A survey and outlook.

Anomaly detection (AD) plays a crucial role in various domains, including cybersecurity, finance, and healthcare, by identifying patterns or events that deviate from normal behavior. In recent years, significant progress has been made in this field due to the remarkable growth of deep learning models. Notably, the advent of self-supervised learning has sparked the development of novel AD algorithms that outperform the existing state-of-the-art approaches by a considerable margin. This paper aims to provide a comprehensive review of the current methodologies in self-supervised anomaly detection. We present technical details of the standard methods and discuss their strengths and drawbacks. We also compare the performance of these models against each other and other state-of-the-art anomaly detection models. Finally, the paper concludes with a discussion of future directions for self-supervised anomaly detection, including the development of more effective and efficient algorithms and the integration of these techniques with other related fields, such as multi-modal learning.

Sub-femtosecond timing jitter, all-fiber, CNT-mode-locked Er-laser at telecom wavelength.

We demonstrate a 490-attosecond timing jitter (integration bandwidth: 10 kHz - 39.4 MHz) optical pulse train from a 78.7-MHz repetition rate, all-fiber soliton Er laser mode-locked by a fiber tapered carbon nanotube saturable absorber (ft-CNT-SA). To achieve this jitter performance, we searched for a net cavity dispersion condition where the Gordon-Haus jitter is minimized while maintaining stable soliton mode-locking. Our result shows that optical pulse trains with well below a femtosecond timing jitter can be generated from a self-starting and robust all-fiber laser operating at telecom wavelength.

High-quality crystallinity controlled ALD TiO2 for waveguiding applications.

We demonstrate a novel atomic layer deposition (ALD) process to make high-quality nanocrystalline titanium dioxide (TiO(2)) with intermediate Al(2)O(3) layers to limit the crystal size. The process is based on titanium chloride (TiCl(4))+water and trimethyl aluminum (TMA)+ozone processes at 250°C deposition temperature. The waveguide losses measured using a prism coupling method for 633 and 1551 nm wavelengths are as low as 0.2±0.1 dB/mm with the smallest crystal size, with losses increasing with crystal size. In comparison, plain TiO(2) deposited at 250°C without the intermediate Al(2)O(3) layers shows high scattering losses and is not viable as waveguide material. The third-order optical nonlinearity decreases with smaller crystal size as verified by third-harmonic generation microscopy but still remains high for all samples. Crystallinity controlled ALD-grown TiO(2) is an excellent candidate for various optical applications, where good thermal stability and high third-order optical nonlinearity are needed.

Low timing jitter and intensity noise from a soliton Er-fiber laser mode-locked by a fiber taper carbon nanotube saturable absorber.

We characterize the timing jitter and intensity noise of an 80-MHz soliton Er-fiber laser mode-locked by a fiber taper carbon nanotube saturable absorber (ft-CNT-SA) up to the Nyquist frequency. The measured rms timing jitter is 3.0 fs (11.0 fs) integrated from 10 kHz (1 kHz) to 40 MHz offset frequency. The measured rms relative intensity noise (RIN) is 0.069% (0.021%) integrated from 10 Hz to 40 MHz (1 MHz) offset frequency. We identify that the resulting timing jitter is dominated by the Gordon-Haus jitter originated from the negative dispersion necessary for soliton mode-locking with a slow saturable absorber.

Spontaneous evolution of equilibrium morphology in phospholipid-cholesterol monolayers.

Competition between intradomain electrostatic repulsions and interdomain line tension leads to domain shape transitions in phase-separating lipid monolayers. The question remains if these morphologies are energy minima or are kinetically trapped metastable states. We show the reversible evolution of uniform width stripe domains from polydisperse semicircular domains in monolayers of dipalmitoylphosphatidylcholine (DPPC), hexadecanol (HD) or palmitic acid (PA), and dihydrocholesterol (DChol). The initial semicircular domains grow at a fixed 2:1 DPPC:HD (or PA) stoichiometry, depleting the liquid phase of HD, leaving behind a liquid enriched in DPPC and DChol. At higher surface pressures, the remaining DPPC precipitates onto existing domains, decreasing the ratio of line tension to the square of the dipole density difference, λ/µ2. Theory predicts that, as λ/µ2 decreases, circular domains reversibly transform to uniform width stripes as the minimum energy structure. Measuring the stripe width provides the first estimates of λ/µ2 at liquid condensed-liquid expanded phase coexistence.

Feature-level ensemble approach for COVID-19 detection using chest X-ray images.

Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as the coronavirus disease 2019 (COVID-19), has threatened many human beings around the world and capsized economies at unprecedented magnitudes. Therefore, the detection of this disease using chest X-ray modalities has played a pivotal role in producing fast and accurate medical diagnoses, especially in countries that are unable to afford laboratory testing kits. However, identifying and distinguishing COVID-19 from virtually similar thoracic abnormalities utilizing medical images is challenging because it is time-consuming, demanding, and susceptible to human-based errors. Therefore, artificial-intelligence-driven automated diagnoses, which excludes direct human intervention, may potentially be used to achieve consistently accurate performances. In this study, we aimed to (i) obtain a customized dataset composed of a relatively small number of images collected from publicly available datasets; (ii) present the efficient integration of the shallow handcrafted features obtained from local descriptors, radiomics features specialized for medical images, and deep features aggregated from pre-trained deep learning architectures; and (iii) distinguish COVID-19 patients from healthy controls and pneumonia patients using a collection of conventional machine learning classifiers. By conducting extensive experiments, we demonstrated that the feature-based ensemble approach provided the best classification metrics, and this approach explicitly outperformed schemes that used only either local, radiomic, or deep features. In addition, our proposed method achieved state-of-the-art multi-class classification results compared to the baseline reference for the currently available COVID-19 datasets.

Deep Learning-Based Multilevel Classification of Alzheimer's Disease Using Non-invasive Functional Near-Infrared Spectroscopy.

The timely diagnosis of Alzheimer's disease (AD) and its prodromal stages is critically important for the patients, who manifest different neurodegenerative severity and progression risks, to take intervention and early symptomatic treatments before the brain damage is shaped. As one of the promising techniques, functional near-infrared spectroscopy (fNIRS) has been widely employed to support early-stage AD diagnosis. This study aims to validate the capability of fNIRS coupled with Deep Learning (DL) models for AD multi-class classification. First, a comprehensive experimental design, including the resting, cognitive, memory, and verbal tasks was conducted. Second, to precisely evaluate the AD progression, we thoroughly examined the change of hemodynamic responses measured in the prefrontal cortex among four subject groups and among genders. Then, we adopted a set of DL architectures on an extremely imbalanced fNIRS dataset. The results indicated that the statistical difference between subject groups did exist during memory and verbal tasks. This presented the correlation of the level of hemoglobin activation and the degree of AD severity. There was also a gender effect on the hemoglobin changes due to the functional stimulation in our study. Moreover, we demonstrated the potential of distinguished DL models, which boosted the multi-class classification performance. The highest accuracy was achieved by Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) using the original dataset of three hemoglobin types (0.909 ± 0.012 on average). Compared to conventional machine learning algorithms, DL models produced a better classification performance. These findings demonstrated the capability of DL frameworks on the imbalanced class distribution analysis and validated the great potential of fNIRS-based approaches to be further contributed to the development of AD diagnosis systems.

Scaling of dissipative soliton fiber lasers to megawatt peak powers by use of large-area photonic crystal fiber.

We report an all-normal dispersion femtosecond laser based on large-mode-area Yb-doped photonic crystal fiber. Self-starting mode-locked pulses are obtained with an average power of 12 W at 84 MHz repetition rate, corresponding to 140 nJ of chirped pulse energy. These are dechirped to a near transform-limited duration of 115 fs. Experimental results are consistent with numerical simulations of dissipative soliton intra-cavity pulse evolution, and demonstrate scaling of 100 fs pulses to megawatt peak powers.

Transition dynamics for multi-pulsing in mode-locked lasers.

We consider experimentally and theoretically a refined parameter space in a laser system near the transition to multi-pulse modelocking. Near the transition, the onset of instability is initiated by a Hopf (periodic) bifurcation. As the cavity energy is increased, the band of unstable, oscillatory modes generates a chaotic behavior between single- and multi-pulse operation. Both theory and experiment are in good qualitative agreement and they suggest that the phenomenon is of a universal nature in mode-locked lasers at the onset of multi-pulsing from N to N +1 pulses per round trip. This is the first theoretical and experimental characterization of the transition behavior, made possible by a highly refined tuning of the gain pump level.