Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling of pressure-driven gas flow in a nodeless Anti-Resonant Hollow Core Fiber for laser absorption spectroscopy

One of the most unique features of the hollow-core fibers (HCF) is the possibility to fill the fiber core with desirable gas, which can be useful, especially in laser absorption spectroscopy (LAS) of gases. Sensitivity of LAS-based gas sensors can be easily and efficiently enhanced by increasing the gas molecules-laser light interaction path within the sensor’s setup. In commonly used multi-pass cells-based sensors, the increase in optical path length comes at the cost of the increased sensor’s complexity, leading to the reduced detection capability. HCFs, that are long, flexible, and devoid of additional optics, allows for constructing gas absorption cells that give the possibility to design less-complex sensor's. One of the main problems in developing HCFs-based sensors is the filling time of the fiber core with the target gas. The core diameter of an Anti-Resonant Hollow Core Fiber (ARHCF) is typically on the order of tens of micrometers, leading to a low volumetric flow rate. It was reported in [1] that the time required to fill a 1 meter-long ARHCF with a core diameter of ~84 μm with the target gas using relatively low overpressure (800 Torr) is about 20 seconds. Additionally, the nodeless type of ARHCF is made of separated capillaries, forming its cladding ( Fig. 1a ). The velocity of gas flow in the gaps between the cladding capillaries is far lower than velocity in the core. We believe that this has a significant impact on the time of pressure-driven gas-filling of such fibers, hence it is necessary to perform simulations on more complex geometric models than for the gap-less ARHCFs, where the core can be approximated by a simple 2D channel.
Direct Writing of 100% Fill-Factor Geometry-Controllable Microlens Arrays with Laser Catapulting

Microlenses and microlens arrays (MLAs) are widely used in various applications, such as lab-on-a-chip, CMOS camera, and solar cells [1] . However, current fabrication methods are restricted to low fill-factor arrays, few geometry options, and flat, often rigid only, substrates. Here, we present a novel additive direct-write method, termed laser catapulting or LCP, for the rapid and customized fabrication of high fill-factor MLAs over a large variety of substrates [2] , [3] . A schematic description of LCP is shown in Fig. 1a . We used a single nanosecond laser pulse to delaminate and catapult, at user-selectable positions, either a single or a multitude of microdisks (up to 260 lenses/mm 2 ) from a donor thin film onto receiver substrate. Following thermal reflow, the printed microdisks are converted into planoconvex microlenses with excellent sphericity and high smoothness ( Fig. 1b,c ). We used as donor a positive photoresist, however, other materials can be transferred in a solid state under appropriate conditions that involve the mechanical and geometrical properties of the selected disk [4] .
3D Shape Modeling Using Perturbation Functions

The paper describes mathematical methods for setting free forms based on perturbation functions. Basic primitives in the form of quadrics are considered. Complex forms are created using quadrics and perturbation functions using set-theoretic operations (Boolean functions). These three-dimensional objects undergo geometric transformations such as scaling, moving, and rotating, and can be deformed, positioned, and oriented anywhere in three-dimensional space. Solid modeling and 3D modeling for 3D printing are briefly considered.
Tunable Thermal Lensing Enabled by Silicate Bonding of Sapphire to SESAMs: Novel Devices for High-Power Lasers

High-power ultrafast laser sources are widely used for industrial applications and scientific research. The leading technology to reach high average powers directly from ultrafast oscillators are SEmiconductor Saturable Absorbed Mirror (SESAM) modelocked Thin-Disk Lasers (TDLs), with average powers up to 350 W [1] . When power-scaling TDLs, thermally induced lensing, especially in the SESAM, is one of the key challenges that needs to be addressed. For this reason, many strategies to reduce the thermal lensing of the SESAM have been investigated, such as thinner substrates, improved contacting [1] , or substrate transfer followed by etching [2] .
An Automatic Loose Defect Detection Method for Catenary Bracing Wire Components Using Deep Convolutional Neural Networks and Image Processing

The bracing wire is one of the most important components of catenary support devices (CSCs) in the high-speed railway, which is used to connect the messenger wire base and bracing wire hook for stabilizing the contact line receiving current. However, it is prone to a loose defect due to the frequent impact of the pantograph. Therefore, in this article, an automatic defect detection method for catenary bracing wires using computer vision technologies is proposed. First, the catenary images are enhanced through a deep convolutional neural network (CNN) called image-adaptive 3-D LUTs (3-D lookup tables) to make the image more clear and easier to identify. Next, the bracing wire is localized by an angle-based CNN called dynamic anchor learning (DAL), which introduces the angle parameter into the object detection network to make the bracing wire more accurate to localization and easier to follow up failure analysis. Last, bracing wires are detected by the Hough transformation (HT), and based on the peak distribution of HT, a looseness defect criterion of bracing wires is proposed according to the curvature change. Experimental results prove that the proposed method can effectively enhance the catenary images, and the bracing wires are precisely localized, and all the defects of bracing wire components under different conditions accurately.
Time-resolved imaging and simulations of SiO2 films dynamic fracture due to laser-induced confined micro-explosion at Si/SiO2 interface

Confined laser-matter interactions can be initiated by short laser pulses either in a transparent medium through nonlinear absorption in the focal region of a tightly focused beam, or at the interface of a film/substrate system, one of which is transparent for laser radiation. In the latter case, a near-interface confined micro-explosion at a certain energetic threshold leads to a localized fracture of the film above the irradiated area. The process was recently studied using 1-4 μm thick SiO 2 films grown on Si wafers by PECVD [1] . It was noted that at certain conditions, the fracture leads to ejection of a conoid/disk-like flyer, often found intact nearby the irradiation site. This phenomenon is of interest for a relatively novel class of additive microfabrication processes – the laser-induced forward and backward transfer (LIFT and LIBT) of functional materials in solid phase. Flyer ejection during LIBT of solid polymer films was previously studied using time-resolved imaging [2] .
Targeted Positioning of Quantum Dots Inside 3D Silicon Photonic Crystals Revealed by Synchrotron X-ray Fluorescence Tomography

It is a major challenge in nanotechnology to precisely position active nanoparticles, like quantum dots, inside a three-dimensional (3D) nanostructure in order to realize novel functions. This is notably relevant to tune and control spontaneous emission and lasing of embedded quantum emitters [1] , [2] . Here, we study 3D photonic band gap crystals made from silicon that are infiltrated with PbS nanocrystal quantum dots that emit in the near infrared including telecom. Our crystals have the inverse woodpile structure and exhibit a broad full 3D band gap. Such crystals strongly inhibit emission of semiconductor quantum dots [3] . The material distribution in the crystals is defined by two perpendicular arrays of pores ( Fig. 1(A) ), running in the Z and X-directions. The crystal are made by CMOS-compatible means by deep reactive ion-etching through tailored masks. The PbS nanocrystals are covalently bonded to polymer brush layers that are grafted to the Si-air interfaces inside the 3D nanostructure using surface-initiated atom transfer radical polymerization (SI-ATRP) [4] .
Computer-Aided Molecular Design of New Task-Specific Ionic Liquids for Extractive Desulfurization of Gasoline

New ionic liquids (ILs) for extractive removal of organic sulfur compounds from gasoline are proposed following the results of computer-aided molecular design (CAMD), comprising application of the extensive group contribution model for infinite dilution activity coefficients of molecular solutes in ILs presented previously [J. Chem. Inf. Model. 2016, 56, 1420–1437]. Infinite dilution selectivity of model system thiophene/n-heptane was adopted as a benchmark property. The proposed structures, selected on the basis of screening of almost 25 800 cation–anion combinations, were synthesized and characterized from the point of view of their thermal behavior and fundamental physical properties, density, and dynamic viscosity. Besides, general remarks regarding an impact of cation/anion structure on extraction selectivity are highlighted and discussed based on the calculations carried out. Liquid–liquid phase equilibrium diagrams in ternary systems {IL + thiophene + n-heptane} were determined at T = 308.15 K in t.
Start-up of a sequential anaerobic/aerobic batch reactor for the mineralization of p-nitrophenol

The start-up of a sequencing batch biofilter integrating anaerobic and aerobic conditions, for the mineralization of P-nitrophenol (PNP) was studied. In this study a reactor packed with volcanic stones and inoculated with microorganisms from activated sludge processes treating municipal and industrial wastewater was used. The reactor was acclimated with a concentration of PNP of 25 mg/l during 75 days (25 cycles). The duration of the first two operation cycles was 8 days. As the bacterial population acclimated to the anaerobic/aerobics conditions, cycles duration was reduced to 40 h (30 h anaerobic stage and 10 h aerobic one). The PNP was transformed to p-aminophenol (PAP) in the anaerobic phase. The mineralization of PAP was found in the oxidative phase. Removal efficiencies of 100% were obtained for initial concentrations of 25 and 55 mg/l of PNP. In the reductive phase (anaerobic) 60% of biotransformation of the PNP to PAP was observed. In the aerobic phase the amines mineralization was 100%.
Optical-Mechanical Configuration of Imaging Operation for Endoscopic Scanner: A Review

Miniaturized endoscopic scanners have had a significant impact on high-resolution optical imaging. Technological advancements in micro-electromechanical systems and optical fiber technology have resulted in various optical-mechanical configurations designed to fulfill specific requirements. However, it is still challenging to provide comprehensive, undistorted images with high-resolution images of target samples. This paper reviews the optical imaging techniques utilized in cantilever-based endoscopic scanners by analyzing and comparing their key performances, pros and cons, and corresponding optical components needed to develop the system. The concept of multimodal imaging is then highlighted by discussing its principle and current status in endoscopic scanners. We also reviewed the scanning configurations concerning their mechanical components, general structures, and drive signals for different scanning patterns. The feedback control aspect in endoscopic scanners is then highlighted. We discuss its role in mitigating undesired nonlinear vibration effects and provide a survey of the current implementations. Finally, we discuss the endoscopic scanners’ current and potential applications, artificial intelligence techniques in image reconstruction, and disease detection and provide recommendations on endoscopic scanner system design for future reference.
Gapless high-resolution QCL dual-comb spectroscopy with real-time data processing for dynamic gas-phase measurements

Quantum cascade laser frequency combs (QCL-FCs) are mid-infrared sources capable of producing several hundred comb lines spanning tens of cm -1 . In the dual comb configuration, two nearly identical frequency combs with slightly different comb spacing are used as an interrogating and local oscillator comb to probe the absorption or refractive index of a sample [1] . The repetition frequency of the interrogating comb determines the point spacing of the measured absorption spectra; in quantum cascade lasers, this value is typically around 10 GHz.
Exploration of the optical behavior of phase-change materials integrated in silicon photonics platforms

Silicon photonics is rapidly emerging as a viable and robust technology for a large range of applications thanks to its high versatility and to its CMOS-compatibility. Nonetheless, there is a strong interest in achieving monolithic integration of novel materials to provide additional functionalities. In particular, phase change materials (PCMs) have started to receive considerable attention due to their unique optical and electrical properties. PCMs such as Ge 2 Sb 2 Te 5 (GST) exhibit a large optical index contrast between their amorphous and crystalline phases [1] . Phase transitions in these materials can be initiated by locally increasing the temperature either optically (light absorption) or electrically (Joule heating), with response times potentially below the ns range [1] . These characteristics have already been exploited in multiple applications such as circuit elements for neuromorphic architectures and multi-level optical memories, where PCMs are deposited as thin-film patches over integrated waveguides [2] – [4] .
Increased glutathione S-transferase activity in 35S(CaMV)-Zmgstf4 transgenic Arabidopsis thaliana

Clones of 35S-Zmgstf4 transgenic Arabidopsis thaliana expressing the glutathione S-transferase F4 gene of Zea mays was tested for stress-inductive GST (glutathione S-transferase) activity following treatments with the heavy metals Zn (150 and 1500 μM), Cd (20 and 30 μM) and chloroacetanilide herbicide metolachlor (2000 μM). The overexpression of Zmgstf4 gene in Arabidopsis resulted in an extreme resistance to all treatments. The GST activity of the transgenic plants was almost the double compared to the wild type plant in the untreated samples. After Cd (20 and 30 μM), and Zn (150 and 1500 μM) exposure the stress response activity of GSTs increased in both wild type and transgenic plants, however with significantly higher levels in transgenic plants with the extreme level at 20 μM CdSO 4 treatment (0.24 in transgenic and 0.13 in wild-type). To compare GST responsivity, Zn treatments was less inductive compared to Cd. Metolachlor (200 μM) was totally tolerated by transgenic plants, compared to wild type plants, which died in 11 days.
Ab Initio Description of Ultrafast Dynamics in Solids

When we theoretically investigate interaction of an intense and ultrashort laser pulse with solids, there are two aspects that should be considered: the strong electric field of the light pulse induces extremely nonlinear electron dynamics in solids that cannot be described by perturbation theory. The nonlinear electron dynamics manifests as a nonlinear polarization in macroscopic scale that determines the propagation of the light pulse. Therefore, to describe the propagation of the intense light pulse, it is necessary to treat the coupled dynamics of the light electromagnetic fields and the electron dynamics. The scheme should also take into account the separation of the spatial scale of two dynamics. We have developed a theoretical and computational approach based on ab initio time-dependent density functional theory for interaction of strong and ultrashort laser pulse with solids and have applied the method to various phenomena. In my presentation, I will show our recent progresses of ab initio simulation in nano-optics.
Evaluation of Machine Learning Algorithms for the Prediction of Simulated Company Parking Space Occupancy

Parking lots of cities and companies are congested when employees get to work in the morning hours. Some people might need to switch to public parking spaces if there is no spot left at their workplace. This is a serious challenge, as nowadays and especially in the future, the ratio of electric vehicles in transportation is growing. Therefore, electric vehicle users require guaranteed charging spots for the continuation of their journey. To enable reservations of parking and charging spots ahead of time, companies want to gain knowledge on upcoming vehicle numbers. So, there is a need for prediction models. However, there is little research done on prediction technologies for company parking spaces. In this paper, four different models from machine learning and statistics are compared in predicting the presence of vehicles from the user groups employees, fleet and visitors. They are trained on simulated occupancy data throughout one year. An evaluation shows that decision trees and artificial neural networks perform well for the case of company parking.
DC-Offset Compensation for Three-Phase Grid-Tied SPV-DSTATCOM Under Partial Shading Condition With Improved PR Controller

This work deals with a single-stage three-phase grid-connected solar photovoltaic distribution static compensator (SPV-DSTATCOM) under partial shading condition (PSC). During PSC, the SPV-DSTATCOM is connected to the distribution network to solve issues like active current sharing, reactive power control, and harmonic elimination. The conventional Proportional Resonant (PR) controller for SPV-DSTATCOM behaves as a notch filter at resonance frequency with high gain of magnitude and has less DC offset rejection capability. Here, an improved PR based on second-order generalized integrator (IPR-SOGI) control architecture with unity gain at the fundamental frequency and more DC offset rejection capability is presented to address the drawback of the conventional PR controller. The performance of the proposed controller is examined under different loading conditions in steady-state and dynamic conditions. Finally, a comparison between the proposed controller with the conventional PR controller and adaptive PR controller are provided with the experimental validation.
Automated Vehicle Sideslip Angle Estimation Considering Signal Measurement Characteristic

Vehicle slip angle (VSA) estimation is of paramount importance for connected automated vehicle dynamic control, especially in critical lateral driving scenarios. In this paper, a novel kinematic-model-based VSA estimation method is proposed by fusing information from a global navigation satellite system (GNSS) and an inertial measurement unit (IMU). First, to reject the gravity components induced by the vehicle roll and pitch, a vehicle attitude angle observer based on the square-root cubature Kalman filter (SCKF) is designed to estimate the roll and pitch. A novel feedback mechanism based on the vehicle intrinsic information (the steering angle and wheel speed) for the pitch and roll is designed. Then, the integration of the reverse smoothing and grey prediction is adopted to compensate for the cumulative velocity errors during the relatively low sampling interval of the GNSS. Moreover, the GNSS signal delay has been addressed by an estimation-prediction integrated framework. Finally, the results confirm that the proposed method can estimate the VSA under both the slalom and double lane change (DLC) scenarios.
Frequency-Comb-Assisted Swept-Wavelength Interferometry

Swept-wavelength interferometry (SWI) is a highly sensitive and versatile technique implemented in a diverse array of industrial and scientific applications. SWI uses a continuously tunable laser to capture the magnitude and phase response of a device under test (DUT). The prevalent non-linear tuning of the laser calls for an auxiliary interferometer for the calibration of the laser frequency on the fly [1] . However, this approach is susceptible to environmental perturbations, and the inherent dispersion of the interferometer introduces systematic errors. Laser frequency combs can be used as optical rulers against which to calibrate tunable lasers with high- precision and, when self-referenced, with high accuracy [2] . Here, we apply this comb-based calibration approach in the context of SWI for the first time and illustrate its relevance for the characterization of high-Q microresonators.
Photonics-Based Cholesky Decomposition

Matrix decomposition approaches are the techniques that partition a complex matrix into its constituents in order to reduce the computational complexity of different matrix calculations. Among different decomposition techniques, Cholesky decomposition [1] , in which a Hermitian positive semi-definite matrix is decomposed into the product between a lower triangular matrix and its conjugate transpose, has been employed in different applications [2] . In particular, Cholesky decomposition has been widely used to compute the inverse of large matrices [3] , because of the advantages it offers terms of the computational complexity and memory requirements [4] . While matrix decomposition reduces the computational complexity, the hardware in which the decomposition is performed affects the overall efficiency and the time required to decompose the matrix. Photonics-based computation has been proposed as a promising approach that offers low-computational cost for ultra-fast data processing [5] . In this paper, a photonic computing architecture is proposed to improve the time and power efficiency of Cholesky decomposition. This is specifically attractive for wireless communication systems, where computational resources are limited and the data needs to be processed on the fly. The proposed architecture is based on Broadcast-and-Weight (B&W) protocol [6] , in which a bank of microring modulators and wavelength division multiplexing scheme are utilized to implement dot product in an optical platform. In the proposed architecture, a feedback control procedure is designed to set the weights by applying voltages to microring resonators.
A Thresholded Gabor-CNN Based Writer Identification System for Indic Scripts

Writer identification is the procedure of identifying individuals from handwriting. Writer identification is a common interest in biometric authentication and verification systems, and numerous studies are available for English, Chinese, Arabic, and Persian specific handwriting. This paper introduces a supervised offline Indic script writer identification system that can identify individuals using less than a single page of handwriting. A lightweight Convolutional Neural Network (CNN) architecture fused with non-trainable Gabor filters is used as an identification model that can recognize writers from scarce data. For the experiment, we used BanglaWriting dataset, which is openly available for Bengali writing and writer recognition. Further, we added Devanagari and Telugu datasets for evaluation. The overall evaluation shows that the proposed thresholded Gabor-based CNN architecture performs superior to numerous deep CNN architectures for Indic writer recognition.