Pipeline conflicts arising from data dependencies are a common issue encountered in the hardware implementation of layered QC-LDPC decoders. This paper proposes an efficient layered decoding architecture to reduce pipeline conflicts without introducing stall cycles, by reordering the processing order offline and using the patch method based on variable-to-check message. The experimental results on the LDPC code of the IEEE802.16 standard in the OFDM-PON system demonstrate that the proposed architecture has a sensitivity improvement of 0.125 dBm and 0.375 dBm, respectively, compared with our previous work and the method described in the other work.

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

Polarimetry is used to determine the Stokes parameters of a laser beam. Once all four S0,1,2,3 parameters are determined, the state of polarisation is established. Upon reflection of a laser beam with the defined S polarisation state, the directly measured S parameters can be used to determine the optical properties of the surface, which modified the S-state upon reflection. Here, we demonstrate polarimetry for the determination of surface anisotropies related to birefringence and dichroism from different materials, which have a common feature of linear patterns of different alignments and scales. It is shown that polarimetry in the back-reflected light is complementary to ellipsometry and four-polarisation camera imaging.

The demand for improved service in mobile networks is always increasing. That means signal transmission with higher capacity is required. To achieve that goal a combined optical and wireless link using double polarization multiplexing has been developed. A high quality signal transmission is achieved by applying high polarization extinction ratio. The new concept is validated by experiments varying the bit rate and fiber length. A signal with 12 Gbit/s bit rate was transmitted over a 25 km long combined link with about 1.10-8 bit error rate. That result is much better than the already published data which were measured on links transmitting information with 2.5 Gbit/s bit rate. The polarization multiplexing technique is very practical for capacity enhancement in a specific section of an existing optical fiber by inserting a new link into it without deploying a new fiber.

To address the insufficient mechanical properties of calcined phosphogypsum, this research aims to investigate the utilization of basalt fiber and calcium carbonate whiskers as reinforcing agents. The study examines their impact on the flexural and compressive strength, toughness, water resistance, and tensile strength of calcined phosphogypsum. In the individual tests, basalt fibers with different lengths (3 mm, 6 mm, 9 mm, and 18 mm) were added at dosages of 0%, 0.5%, 1.0%, and 1.5% respectively. The findings demonstrate that basalt fiber effectively enhances the flexural and compressive strength, toughness, and tensile strength of calcined phosphogypsum, albeit potentially compromising water resistance. Among the various fiber lengths, the 6 mm fibers exhibit the most advantageous influence on the performance of calcined phosphogypsum. A subsequent test was conducted to investigate the impact of cross-scale fibers on the properties of calcined phosphogypsum by mixing 6 mm basalt fibers and calcium carbonate whiskers. The results illustrate that calcium carbonate whisker refines the pores, thereby improving the flexural strength and toughness of calcined phosphogypsum. Furthermore, it compensates for the water resistance limitations associated with the sole utilization of basalt fiber while further augmenting the tensile strength and strain capacity. However, it should be noted that increasing the dosage of both calcium carbonate whiskers and basalt fibers concurrently leads to increased porosity of phosphogypsum and reduced compressive strength.

Addressing real-time aircraft target detection in microsatellite-based visible light remote sensing video imaging requires considering the limitations of imaging payload resolution, complex ground backgrounds, and the relative positional changes between the platform and aircraft. These factors lead to multi-scale variations in aircraft targets, making high-precision real-time detection of small targets in complex backgrounds a significant challenge for the detection algorithms. Hence, this paper introduces a real-time aircraft target detection algorithm for remote sensing imaging using an improved lightweight attention mechanism that relies on the YOLOv7 framework (SE-CBAM-YOLOv7). The proposed algorithm replaces the standard convolution (Conv) with a lightweight convolutional SEConv to reduce the computational parameters and accelerate the detection process of small aircraft targets, thus enhancing real-time onboard processing capabilities. Besides, the SEConv-based SPPCSPC (Spatial Pyramid Pooling and Connected Spatial Pyramid Convolution) module extracts image features. It improves detection accuracy while the feature fusion section integrates the CBAM hybrid attention network, forming the CBAMCAT module. Furthermore, it optimizes small aircraft target features in channel and spatial dimensions, improving the model's feature fusion capabilities. Experiments on public remote sensing datasets reveal the proposed SE-CBAM-YOLOv7 improves detection accuracy by 3% and mAP value by 4.2% compared to YOLOv7, significantly enhancing the detection capability for small-sized aircraft targets in satellite remote sensing imaging.

To address the issue of reduced orbit estimation accuracy resulting from discrepancies between in-orbit measured geomagnetic field values and IGRF model values in autonomous orbit estimation of microsatellites based on geomagnetic field measurements, this study introduces an adaptive cubature H-infinity filtering algorithm. Firstly, it presents the low-altitude orbital dynamics model and geomagnetic field measurement model for microsatellites. Subsequently, within the adaptive cubature H-infinity filtering algorithm, a spherical simplex rule and a second-order Gaussian-Legendre quadrature criterion are employed to compute the spherical surface integral and radial integral. Additionally, a spherical simplex-radial quadrature rule is proposed to enhance the approximation accuracy of nonlinear Gaussian weighted integrals. Furthermore, by integrating extended H-infinity filtering based on game theory with the cubature quadrature rule, an inverse proportional relationship between constraint level and filtering innovation is established. This allows for adaptive adjustment of the constraint level to enhance robustness against model errors. Finally, through semi-physical simulation experiments, it is demonstrated that compared with traditional algorithms, the proposed algorithm improves autonomous orbit estimation position accuracy of microsatellites by 7.49%, while also enhancing velocity accuracy by 3.1%, thus validating its effectiveness.

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows an improved sensitivity in optical sensing; while the modal Raman gain of 23.60 m-1·W-1 is 2 times larger than that generated around a nano fiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Besides, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.

A comprehensive modeling framework for the thermoforming of polymer matrix woven laminate composite was developed. Two numerical indicators, the slip path length and traction magnitude, have been identified to be positively correlated to matrix smearing and wrinkling defects. The material model has been calibrated with picture-frame experimental results, and the prediction accuracy for intra-ply shear and thickness distribution were examined with measurements on the physically formed parts. Finally, a parametric study was conducted to determine the relationship between various process parameters and the quality of the formed part. For the trapezoidal part, orienting the laminate at 45-degrees to the mold axis reduces the likelihood of matrix smear and wrinkling defects. Although this laminate orientation yielded a greater spatial variation of part thickness, the thickness deviation is lower than that for the 0-degree orientation case. Higher forming rates were found to result in more defects due to increased slip path lengths and traction magnitudes. Optimal forming speeds should balance rapid shaping within the operating temperature window while avoiding tear. It was discovered that shallower molds benefit from faster ramp rates, while deeper molds require slower rates to manage extensive shearing, stretching, and bending. Faster forming rates lead to smaller thickness increases at high intra-ply shear regions, indicating a shift from intra-ply shear to out-of-plane bending due to the visco-plastic effect of the molten laminate, and can negatively impact part quality. Lastly, it was shown that a well-conceived strategy using darts could improve the part quality by reducing the magnitude of the defect indicators.

Laser machining by ultra-short (sub-ps) pulses at high intensity offers high precision, high throughput in terms of area or volume per unit time, and flexibility to adapt processing protocols to different materials on the same workpiece. Here we consider the challenge of optimization for high throughput: how to use the maximum available laser power and larger focal spots for larger ablation volumes by implementing a fast scan. This implies the use of high-intensity pulses approaching ∼PW/cm2 at the threshold where tunnelling ionization starts to contribute to overall ionization. A custom laser micromachining setup was developed and built to enable high speed, large area processing and easy system reconfiguration for different tasks. The main components include laser, stages, scanners, control system, and software. Machining of metals such as Cu, Al, or stainless steel, and fused silica surfaces at high-fluence and high-exposure doses at high scan speeds up to 3 m/s were tested for the fluence scaling of ablation volume, which was found to be linear. Modified surfaces are color-classified for their appearance, which is dependent on surface roughness and chemical modification. Such colour-coding can be used as a feedback parameter for industrial process control.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

Dynamic optical structural color is always desired in various display applications and usually involves active materials. Full-color generation, especially bi-directional full-color generation in both reflective and transmissive modes, without any active materials included has been rarely investigated. Herein, we demonstrate a scheme of bi-directional full-color generation based on a plasmonic metasurface modulated by rotation of the polarization angle of the incident light without varying the geometry and the optical properties of the materials and the environment where the metasurface resides. The metasurface unit cell consists of plasmonic modules aligning in three directions and is patterned in a square array. The metasurface structural color device generates full colors in both reflection and transmission. Based on the proposed polarization-dependent structural color, information encoding of three multiplexed animal images and quick-responsive (QR) codes is demonstrated to verify the efficient information encoding and decoding of the proposed scheme. The animals can be seen under different polarization incidence and the QR codes can be successfully decoded by the polarization rotation in transmission. The proposed bi-directional full-color generation metasurface has great potential in applications such as kaleidoscope generation, anti-counterfeiting, dynamic color display, and optical information encoding.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

Theoretical studies on the generation of nondiffracting and nondispersive light pulses and their experimental implementation are one of the renowned problems within electromagnetics. Current technologies enable creation of short-duration pulses of a few cycles with high power and fluency. An application of these techniques to the field of nondiffracting and nondispersive pulses requires a proper mathematical description of highly focused vector pulses. In this work, we study vector optical bullets in a dielectric medium with different polarization structures: linear, azimuthal, and radial. We report the differences caused by the vector model compared to the scalar model. We analyze effects caused by superluminal, subluminal, or even negative group velocity on properties of vector optical bullets inside a dielectric material.

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to a deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated to the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air-glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and the sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, and the diameter of the nested tube is d0=29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28×10-4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72×10-2 dB/m. To our knowledge, this is the first research to achieve an anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band erbium laser therapy instrument.

Nowadays, Multi-needle electrospinning has used to be an efficient method for producing nanofiber membranes. But in the process, the fluctuation errors in electrospinning fluid flow rate have directly influence the membrane quality, which bringing instability and still have not been solved yet. For finding out the solution to the inaccurate flow control in multi-needle, it is necessary to develop a multi-stage flow runner spinneret for large-scale production of nanofiber membrane. At first, the paper uses the finite element software COMSOL to numerically simulate the polymer flow in the runner of spinneret. Based on it, the velocity field distribution curve was draw and the velocity instability coefficient of the polymer flow was attained, which are providing theoretical guidance for the optimal design of spinneret. Next, the response surface analysis method (RSM) was used to establish a regression model between the average diameter of the nanofiber membrane and the process parameters. Then, above regression model used to perform variance data processing between the average diameter and the process parameter configuration. After that, the 2D and 3D response surface profiles and the significance analysis were completed. Finally, the stability of the nanofibers production was improved, which attained the optimal adjustment of process configuration in multi-needle electrospinning.

The review aims to assess fifteen (15) academic literature sources, highlighting the application of machine learning algorithms in the maintenance operations of optical fiber networks. It exhibits the collection of data using PRISMA methodology—Preferred Reporting Item for Systems Review and Meta-Analyses. The application, results, and performance metrics are discussed based on the collected observations, computations, and statistics in the studies, which revealed records of high accuracy degrees ranging from 86% to 98% on average and quality ML models including Neural Networks (NNs), Support Vector Machines (SVMs), and LSTM, as well as deep learning models that disclosed effective results of determining challenges and problems within the optical fiber lines. The review mainly centralized on superior machine learning technologies that surpass traditional techniques in fault detection and localization for improved optical fiber networks’ operations while providing insights into the limitations and challenges encountered in real-world applications of these models, offering a comprehensive perspective on the optical fiber network’s domain.

The increasing environmental awareness and carbon-storing capability of wood have amplified its relevance as a building material. The demand for high-quality wood species necessitates exploring alternative, underutilized wood sources due to limited forest areas and premium wood volume. Consequently, the veneer-based industry is considering lower-value hardwood species like grey alder, black alder, and aspen as substitutes for high-quality birch. Initially less appealing due to their lower density and mechanical properties, these species show promise through densification, which enhances their density, strength, and hardness. This study aims to enhance plywood screw withdrawal capacity and surface hardness by densifying low-density wood species and using them in plywood face veneer layers or all layers. The relationship between wood density, surface hardness, and screw withdrawal capacity of plywoods made of low-value species like aspen and black alder is examined. Experimental work with a pilot-scale veneer and plywood production line demonstrates improved surface hardness (65% and 93% for aspen and black alder, respectively) and screw withdrawal capacity (16% and 35% for aspen and black alder, respectively) in face veneer densified low-value hardwood plywood. This research highlights the potential of densified low-value wood species to meet construction requirements, expanding their practical applications.

Aiming at solving difficulties related to aero-engine classification and identification, the infrared spectra of aero-engine hot jets are measured by telemetry Fourier transform infrared spectrometer, and a six types aero-engine hot jet spectrum data set is generated. The spectrum data set were randomly sampled at a ratio of 8:1:1 to generate training set, validation set and prediction set. In this paper, a Peak Finding Siamese Convolutional Neural Network (PF-SCNN) is designed to match and classify spectrum data. In the first place, the matching pairs of training set and validation set are made independently with the labels of positive and negative samples creating. The spectrum feature extraction and distance similarity calculation are carried out by the Siamese convolutional neural network (SCNN). When entering the prediction phase, the prediction set and training set are integrated to predict in the trained model. The prediction set labels are ultimately determined by matching them with the training set labels having the highest similarities to ensure accurate predictions. To improve the operation efficiency of the SCNN, a peak finding method is introduced to extract the spectrum peaks. Peak positions of high frequency are counted, while the peak data are extracted. The peak data are used to take the place of the original data for training and prediction. The performance measures are defined as Accuracy, Precision, Recall, Confusion matrix and F1-score, and the prediction accuracy was up to 99%. The experimental results indicate that the proposed PF-SCNN is suitable for our spectral dataset and can complete the task of infrared spectrum classification of aero-engine hot jets.

Focusing on the problem of identifying and classifying aero-engine models, this paper measures the infrared spectrum data of aero-engine hot jets using a telemetry Fourier transform infrared spectrometer. Simultaneously, infrared spectral data sets with the six different types of aero-engines are created. For the purpose of classifying and identifying infrared spectral data, a CNN architecture based on the continuous wavelet transform peak seeking attention mechanism (CWT-AM-CNN) is suggested. This method calculates the peak value of middle wave band by continuous wavelet transform, and the peak data is extracted by the statistics of the wave number locations with high frequency. Attention mechanism is used for the peak data, and the attention mechanism is weighted to the feature map of the feature extraction block. The training set, vali-dation set and prediction set are divided in the ratio of 8:1:1 for the infrared spectral data sets. For three different data sets, CWT-AM-CNN proposed in this paper is compared with the classical classifier algorithm based on CO2 feature vector and the popular AE, RNN and LSTM spectral processing networks. The prediction accuracy of the proposed algorithm in the three data sets is as high as 97%, and the lightweight network structure design not only guarantees high precision, but also has a fast running speed, which can realize the rapid and high-precision classification of the infrared spectral data of the aero-engine hot jets.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

Current generation witnesses a huge interest in optical waveguide due to their salient feature such as low cost, immune to electromagnetic interference, easy to multiplex, compact size, etc. These features of the optical fibers makes it an useful tool for various sensing applications including medicine, automotive, biotechnology, food quality control, aerospace, physical and chemical monitoring etc. Among all the reported application, the device has been widely exploited to measure the physical and chemical variation in surrounding environment. Optical fiber based temperature sensor plays a crucial role in this decade to detect high fever and tackle COVID like pandemic. Recognizing the major developments in the field of the optical fibers, this article aims to provide recent progress in temperature sensor utilizing several sensing configuration including standard fiber, photonic crystal fiber, and Bragg grating fibers. Additionally, the article also highlights the advantages, limitations, and future possibilities in this area.

The distributed long-range sensing system using the standard telecommunication single-mode optical fiber in a function of a distributed sensor for sensing of mechanical vibrations is described. Various events generating vibrations such as walking or running person, moving cars, trains and others can be detected, localized and classified. The sensor and related sensing system components were designed and constructed and the system was tested both in the laboratory and in the real situation with 88 km telecom optical link, and the results are presented.

Esterquats constitute a unique group of quaternary ammonium salts (QASs) that contain an ester bond in the structure of the cation. Despite the numerous advantages of this class of compounds, only two mini-reviews discuss the subject of esterquats: the first one (2007) briefly summarizes their types, synthesis, and structural elements required for a beneficial environmental profile and only briefly covers their applications whereas the second one only reviews the stability of selected betaine-type esterquats in aqueous solutions. The rationale for writing this review is to critically reevaluate the relevant literature and provide others with a “state-of-the-art” snapshot of choline-type esterquats and betaine-type esterquats. Hence, the first part of this survey thoroughly summarizes the most important scientific reports demonstrating effective synthesis routes leading to the formation of both types of esterquats. In the second section, the susceptibility of esterquats to hydrolysis is explained, and the influence of various factors, such as the pH, the degree of salinity or the temperature of the solution, was subjected to thorough analysis that includes quantitative components. The next two sections refer to various aspects associated with the ecotoxicity of esterquats. Consequently, their biodegradation and toxic effects on microorganisms are extensively analyzed as crucial factors that can affect their commercialization. Then, the reported applications of esterquats are briefly discussed, including functionalization of macromolecules, such as cotton fabric as well as their successful utilization on a commercial scale. The last section demonstrates the most essential conclusions and reported drawbacks that allow us to elucidate future recommendations regarding the development of these promising chemicals.

The accuracy of cosmic ray observation by the Large High Altitude Air Shower Observatory Wide Field-of-view Cherenkov/fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples in 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and A˚ngstro¨m Exponent (AE) at 440-870 nm (AE440−870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD are the order of spring > summer > autumn = winter. The monthly average maximum of AOD440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE440−870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that clean continental background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India region. These results provide a baseline for comparison to the future on-site measurement of extinction coefficient profile and aerosol phase function by LHAASO-WFCTA, also enrich the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

Adult neurogenesis involves generation of functional neurons from neural progenitor cells, which have the potential to complement and restore damaged neurons and neural circuits. Therefore, the development of drugs that stimulate neurogenesis represents a promising strategy in stem cell therapy and neural regeneration, greatly facilitating the reconstruction of neural circuits in cases of neurodegeneration and brain injury. Our study reveals that compound A5, previously designed and synthesized by our team, exhibits remarkable neuritogenic activities, effectively inducing neurogenesis in neural stem/progenitor cells (NSPCs). Subsequently, transcriptome analysis using high-throughput Illumina RNA-seq technology was performed to further elucidate the underlying molecular mechanisms by which compound A5 promotes neurogenesis. Notably, comparative transcriptome analysis showed that the up-regulated genes were mainly associated with neurogenesis and the down-regulated genes were mainly concerned with cell cycle progression. Furthermore, we confirmed that compound A5 significantly affected the expression of transcription factors related to neurogenesis and cell cycle regulatory proteins. Collectively, these findings identify a new compound with neurogenic activity and may provide insights into drug discovery for neural repair and regeneration.

We propose a method for creating parallel Bessel-like vortical optical needles with an arbitrary axial intensity distribution via superposition of different cone-angle Bessel vortices. We analyze the interplay between the separation of individual optical vortical needles and their respective lengths and introduce a super-Gaussian function as their axial profile. We also analyze the physical limitations to observe well-separated optic needles, as they are influenced by mutual interference of the individual beams. To verify our theoretical and numerical results, we generate controllable spatial arrays of individual Bessel beams with various numbers and spatial separations by altering the spectrum of the incoming laser beam via the spatial light modulator. We demonstrate experimentally how to implement such beams using a diffractive mask. The presented method facilitates the creation of diverse spatial intensity distributions in three dimensions, potentially finding applications in specific microfabrication tasks or other contexts. These beams may have benefits in laser material processing applications such as nanochannel machining, glass via production, modification of glass refractive indices, and glass dicing.

Luminescent carbon dots (CDs) were locally synthesized in the core of CYTOP fibers using IR femtosecond laser direct writing (FLDW), a one-step simple method serving as a post-treatment of the genuine fiber. This approach enables the creation of several types of modifications such as ellipsoid voids. The CDs and photoluminescence (PL) distribute at the periphery of the voids. The PL spectral properties were studied through Excitation Emission Matrix in the visible range and excitation/emission spectrum in UV/visible range. Our finding reveals the presence of at least 3 distinct luminescent species, facilitating a broad excitation range extending from UV to green, and light emission spanning from blue to red. The average laser power and dose influence the quantity and ratio of these luminescent CD species. Additionally, we measured the spatially resolved lifetime of the luminescence during and after the irradiation. We found longer lifetimes at the periphery of the laser-induced modified regions and shorter ones closer to the center, with a dominant lifetime ~ 2ns. Notably, unlike many other luminophores, these laser-induced CDs are insensitive to oxygen, enhancing their potential for display or data storage applications.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

Concrete cracks and local damage can affect the bond performance between concrete and steel bars, thereby reducing the durability of reinforced concrete structures. Compared with general concrete crack repair methods, biomineralization repair not only has effective bonding capabilities but is also particularly environmentally friendly. In view of this, this study aimed to apply biomineralization technology to repair damaged fiber-reinforced lightweight aggregate concrete (LWAC). Two groups of LWAC specimens were prepared. The control group used lightweight aggregates (LWAs) without bacterial spores and nutrient sources, and the experimental group used LWAs containing bacterial spores and nutrient sources. These specimens were first subjected to compression tests and pull-out tests, respectively, and thus were damaged. After the damaged specimen healed itself in different ways for 28 days, secondary compression and pull-out tests were conducted. The self-healing method of the control group involved placing the specimens in an incubator. The experimental group was further divided into experimental group I and experimental group II. The self-healing method of experimental group I was the same as that of the control group. The self-healing method of experimental group II involved soaking the specimen in a mixed solution of urea and calcium acetate for two days, and then taking it out and placing it in an incubator for two days, with a cycle of four days. The test results showed that, compared with the control group specimens, the relative bond strength ratio of the experimental group II specimens increased by 17.9%. Moreover, the EDS and XRD analysis results confirmed that the precipitate formed at the crack was calcium carbonate, which improved the compressive strength and bond strength after self-healing. This indicates that the biomineralization maintenance method used in experimental group II is more effective.

The Yb/Al multilayer films exhibit excellent theoretical reflectivity in the 54-90nm wavelength range. This study attempted to incorporate 1.5% wt.% of Si impurities into Al to suppress the crystallization of Al, reduce interfacial roughness, and enhance the actual reflectivity of the prepared Yb/Al multilayer films. The internal microstructure changes of the film layers before and after Si impurity doping were investigated using GIXRR, AFM, and XRD techniques. The reflectivity of two types of multilayer films, Yb/Al(1.5wt.%Si) and Yb/Al(pure), was tested to evaluate the effect of Si impurity on the film performance.

The aim of this research work is to get a method for Galfenol electrodeposition thought which we can control the desired percentage of Ga versus Fe that has the maximum magnetostriction constant. Galfenol is electrodeposited on an optical fiber with an imbedded Fiber Bragg Grating (FBG) in its core. The final objective, that goes further of the scope of this research, is to get an optical magnetostrictive sensor. The device will sense magnetic field or current based on the combination of this magnetostrictive Galfenol, that will stress the optical fiber with the application of magnetic field or current and will change the reflected wavelength of the FBG as a consequence of the variation of the Bragg wavelength. We have developed a method of electrodeposition that allows controlling the density of current in the electrodeposition process in order to get the desired percentage of Ga and Fe in the alloy Ga X Fe 1-x. We have manufactured a set of samples with different parameters (as density of current and pH) and we have characterized these samples morphological, structural and magnetically. With this research we want to give to the scientific community the groundwork to design magnetostrictive optical sensors based on and FBG coated by giant magnetostrictive material. In this paper we have developed a method of covering the optical fiber controlling the composition of (Ga X Fe 1-X) in order to be able to get the maximum magnetostriction constant.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

The object of research is an optical-electronic system for recording and processing signals from fiber-optic sensors. Due to the use of optical fibers as sensitive elements, there is no influence on the measurement result of electromagnetic fields, spurious electromagnetic radiation, channel crosstalk, there are no problems, electrical safety is significantly increased, there are no problems of arcing and sparking. A scheme of a receiving-transmitting module has been developed, which is additionally equipped with a preliminary protection and filtering system. Further, measuring tracks, microcontroller software and functional tests were ordered to determine the metrological properties of the proposed system.Signal integrity analysis is presented, which allows you to check whether the signals present in the device are correctly transmitted between their sources and receivers. The analysis of signal integrity is investigated, which is performed in two stages of the device design process. Modeling of the studied module in the specialized program Altium Designer. With the help of this program, potential problems were found, such as the occurrence of crosstalk between paths, the exact values of some elements, accurate analytical calculation. Learned an impedance analysis trace for a given connection's parameters, where the value affects the shape of the given path, its physical dimensions, distance from other paths, and other physical properties of the board. Optoelectronic system for recording and processing signals from fiber optic sensors based on Bragg fiber gratings resistant to electromagnetic interference and temperature, for use in modern systems for monitoring building structures, bridges, tunnels, dams, high-rise buildings, railways, oil platforms, buildings, pipelines.

In this study, Brillouin optical time-domain analysis (BOTDA) sensing technology was utilized for monitoring settlement in a similarity model of a highway subgrade. As contact winding cannot be used for an optical fiber that is buried directly in soil, uncoupling between. the fiber and the soil can occur. Thus, an optical-fiber-embedded beam (OFEB) was developed, and a method for measuring and calculating the beam deformation was proposed. A calibration test and a test on a similarity model of a subgrade were carried out to investigate the applicability and monitoring accuracy of the OFEB. It was concluded that the OFEB can accurately measure beam deflection, where the maximum relative error between measurements by the optical fiber and a displacement transducer was approximately 5%. The OFEB was embedded directly into a similarity model of a subgrade to monitor settlement. The deflection deformation of the OFEB was found to be close to the subgrade settlement over a certain settlement range with a relative error below 8.1%. Thus, the OFEB can be used to realize measure large-range distributed settlement in a subgrade. A numerical simulation was performed to identify appropriate beam dimensions and material design parameters, thereby extending the measurement range before decoupling of the OFEB and soil occurs. The enhancement of the measurement range and accuracy of the OFEB based on the preliminary experiments carried out in this study enables further investigation of settlement monitoring.

Environmental monitoring is an important topic and serves a vibrant scientific role by revealing long-term trends that can lead to new knowledge and understanding. Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

We propose a spectral filter based on Plastic Optical Fiber with micro-holes as a low-cost, robust, and highly reproducible spectral filter. The spectral filter is explored for two configurations: fiber extended in a straight line, and a fiber optic loop mirror scheme configuration. The transmission traces indicate a spectral blue shift of peak transmission, at 587 nm, 567 nm, 556 nm, and 536 nm for 0, 1, 2, and 3 holes in the fiber, respectively. The filter exhibits a bandpass period of approximately 120 nm. Additionally, we conducted a comparison of the transmission with holes separated by distances of 1 cm and 500 μm. The results demonstrate that the distance between holes does not alter the spectral transmission of the filter. In the case of the fiber loop mirror configuration, we observed that the bandpass can be adjusted, suggesting the presence of multimode interference. Exploring variations in the refractive index within the holes by filling them with glucose solutions at various concentrations, we determined that the filtering band and spectral shape remains unaltered, ensuring a stable and robust operation of our spectral filter.

In this work, two plasmonic structures with two different periodic nanostructures (nanodisk and nanostrip arrays) separated from the gold layer by an ultrathin dielectric Al2O3 layer are proposed, and their optical properties are simulated as 3-dimensional models using COMSOL Multiphysics software tool. The optical responses, such as the amplification of the electric field and the scattering, absorption and extinction cross sections of the two structures, are investigated and compared. The results show that both structures show strong field enhancement in their gap layer, and the structure with the periodic array of metal nanodisks shows stronger field enhancement and larger absorption, extinction, and scattering cross sections in its dipole resonance wavelength, which is defined as a bright plasmonic mode. In addition, some weaker resonant modes are observed for both structures and the reason for their generation is dis-cussed. The analysis of different possible modes in such structures is crucial for their application in various fields.

Membrane gas absorption technology and solar-assisted regeneration system are two promising approaches to reduce high energy consumption associated with carbon dioxide capture from coal fired power plants. In the present study, a solar-assisted hollow fiber membrane contactor (SOL-HFMC) power plant is proposed to capture and desorb CO₂ in hollow fiber membrane contactors with the assistance of solar thermal collectors. Techno-economic assessment and sensitivity analysis of the proposed system is carried out in three studied locations with different weather conditions for a 580 MWe pulverized coal power plant. Research results show that, the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless whether TES system is applied or not. In addition, CEI of the SOL-HFMC power plant with TES system is 4.36 kg CO₂/MWh, 4.45 kg CO₂/MWh and 4.66 kg CO₂/MWh lower than that of the reference power plant. The prices of membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for SOL-HFMC power plant with TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m² for Jinan, 95.20 $/m² for Xining, and 128.70 $/m² for Lhasa, respectively. To be more competitive than solar-assisted ammonia-based post-combustion CO₂ capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively. The findings can provide guidance for decision-making and risk management strategies.

Optical fiber sensors based on tapered optical fiber (TOF) structure have attracted a considerable amount of attention from researchers due to the advantages of simple fabrication, high stability, diverse structures, and have great potential for applications in many fields such as physics, chemistry and biology. Compared with ordinary optical fibers, TOF with their unique structural characteristics significantly improve the sensitivity and response speed of fiber-optic sensors and broaden the application range. This review presents an overview of the latest research status and characteristics of fiber-optic sensors and TOF sensors. Then the working principle of TOF sensors, fabrication schemes of TOF structures, novel TOF structures in recent years, and the growing emerging application areas are described. Finally, the development trends and challenges of TOF sensors are prospected. The objective of this review is to convey novel perspectives and strategies for the performance optimization and design of TOF sensors based on fiber-optic sensing technologies.

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open source Python library called SpectraMap (SpMap). In conclusion, the 1064 nm Raman system can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral imaging.

Concrete being one of the most frequently used construction materials in the field of construction. The use of concrete has increased with the passage of time as the more and more construction activities are taking place around the globe. Different materials have been added in to the concrete mix to provide the concrete more strength and make it more durable and long lasting. This paper looks into a detailed comparison of concrete strength when casted with in the presence of carbon fibers, steel fibers and glass fibers. The compressive strength for cubes and cylinder with carbon fibers is the highest as compare to steel fibers as well as glass fibers. The compressive strength of concrete is measured on 3 day, 7 day, 14 day and 28 day strength. The compressive strength of cube on 28th day strength is 37.52 MPa for carbon fiber steel, for steel fiber it is 34.22 MPa and with glass fiber the strength is 29.335 MPa whereas the compressive strength of cylinder with carbon fibers the 34.88 MPa, with steel fiber it is 34.22 MPa and with glass fiber the strength is 27.447 MPa. For the cubes the maximum difference between different fibers inducted concrete sample is 28% approximately and for cylinder it is 27%, respectively. On the other hand, the tensile strength of concrete was also gained with the carbon fiber. It was determined that carbon fiber provided about 16% and 12.8% tensile strength higher than glass and steel fibers respectively.

Optical polarizers are essential components for the selection and manipulation of light polarization states in optical systems. Over the past decade, the rapid advancement of photonic technologies and devices has led to the development of a range of novel optical polarizers, opening avenues for many breakthroughs and expanding applications across diverse fields. Particularly, two-dimensional (2D) materials, known for their atomic thin film structures and unique optical properties, have become attractive for implementing optical polarizers with high performance and new features that were not achievable before. This paper reviews recent progress in 2D-material-based optical polarizers. First, an overview of key properties of various 2D materials for realizing optical polarizers is provided. Next, the state-of-the-art optical polarizers based on 2D materials, which are categorized into spatial-light devices, fiber devices, and integrated waveguide devices, are reviewed and compared. Finally, we discuss the current challenges of this field as well as the exciting opportunities for future technological advances.

In this study, different configurations based on linear fiber lasers were proposed and experimentally demonstrated to measure the concentration of paracetamol liquid solutions in a range of 52.61 to 201.33 g/kg. The optical gain was provided by a commercial bidirectional Erbium-Doped Fiber Amplifier (EDFA) and the linear cavity was obtained using two commercial Fiber Bragg Gratings (FBGs). The main difference of each configuration was the coupling ratio of the optical coupler used to extract the system signal. The sensing head corresponded to a Single-Mode Fiber (SMF) tip that worked as an intensity sensor. The results reveal that, despite the optical coupler used (50:50, 60:40, 70:30 or 80:20), all the configurations reached the laser condition, however, the concentration sensing was only possible using a laser drive current near to the threshold value. The configurations using a 70:30 and an 80:20 optical coupler allowed to perform paracetamol concentration measurements with a higher sensitivity of (-3.00±0.24) pW/(g/kg). In terms of resolution, the highest value obtained was 1.75 g/kg, when it was extracted 20% of the output power to the linear cavity fiber laser configuration.

In the field of clinical medicine, the real-time monitoring of carbon dioxide gas exhaled by the human body is of great significance. At present, the detection devices in the market are mainly detected by sucking a small amount of gas in the nasal cavity to the detection device, and there are some problems such as too long sampling tubes, easy blockage or distortion, and abnormal gas dispersion. In this paper, a micro-nano optical fiber sensor that can directly detect the concentration of end-tidal carbon dioxide is proposed. The measurement is achieved by using the principle of high evanescent field absorption, and the operating band is 2.004 μm. The sensor uses micro-nano optical fiber as the sensing area, and then detects the presence of carbon dioxide gas exhaled by human body through optical power attenuation. The function of micro-nano fiber is to realize the transmission of signal light and also serve as the absorption medium of the gas to be measured. In addition, the variation of light power also reflects the respiratory cycle of the human body. The sensor can realize rapid real-time response to carbon dioxide gas detection, with small size, low cost, and easy to replace. It has great application potential in clinical scenarios such as Gastrointestinal Endoscopes that require real-time monitoring of human respiration.

Aiming at the problem that dynamic targets in indoor environments lead to low accuracy and large errors in the localization and position estimation of visual SLAM systems and the inability to build maps containing semantic information, a semantic visual SLAM algorithm based on the semantic segmentation network DeepLabV3+ and LK optical flow is proposed based on ORB-SLAM2 system. First, the dynamic target feature points are detected and rejected based on the lightweight semantic segmentation network DeepLabV3+ and LK optical flow method. second, the static environment occluded by the dynamic target is repaired using the time-weighted multi-frame fusion background repair technique. Lastly, the filtered static feature points are used for feature matching and position calculation. Meanwhile, the semantic labeling information of static objects obtained based on the lightweight semantic segmentation network DeepLabV3+ is fused with the static environment information after background repair to generate dense point cloud maps containing semantic information, and the semantic dense point cloud maps are transformed into semantic octree maps using the octree spatial segmentation data structure. The localization accuracy of the visual SLAM system and the construction of the semantic maps are verified using the TUM RGB-D widely used dataset and real scene data, respectively. The experimental results show that the proposed semantic visual SLAM algorithm can effectively reduce the influence of dynamic targets on the system, has a higher localization accuracy, and compared with other advanced algorithms, such as DynaSLAM, has the highest performance in indoor dynamic environments while considering both localization accuracy and real-time performance. In addition, semantic maps can be constructed so that the robot can better understand and adapt to the indoor dynamic environment.

The objective of this paper is to investigate the debonding behavior of the interface between continuously and discontinuously fiber reinforced thermoplastics using the climbing drum peel test. The study emphasizes the importance of considering different climatic boundary conditions due to the properties of thermoplastics. Specimens with varying moisture contents are prepared and tested. It is observed that an increase in moisture content initially results in a higher fracture surface energy being required to separate the two materials, but a further increase results in a decrease of the required energy. The study presents an explanatory model of increasing plasticization of the polymer due to increased polymer chain mobility, which results in more deformation energy being required to propagate the crack. The experiment is also modeled numerically for the first time with cohesive surfaces, which successfully reproduces the force-displacement curve in the experiment.

Due to the renewed variation in government and political systems inside and outside countries, and with the high tariffs at borders, the latter have become an outlet for terrorism and smugglers. Therefore, each country seeks to develop its own protection system, and the technologies used in these systems vary according to the severity and the importance of the installations to be protected, it is found that some of them are expensive and unnecessary, but other have good and variable levels of efficiency. Consequently, the idea of designing a surveillance system that can monitor and control access becomes indispensable. In the same context, this work is of crucial strategic and geopolitical importance. It combines pre-existing alarm and monitoring methods and revolutionary Internet of Things (IoT) application products, of which Wireless Sensor Networks (WSN) and Optical Fiber Sensors (OFS) are part of this application. This article presents the distribution of wireless radar nodes accompanying with a Bragg fiber sensor to identify each rolling intruder incoming the zone to be monitored, from the determination of its speed, weight and wheelbase distance.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to up to a week. However, in recent years, significant efforts have been made towards the development of biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-Shape probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another way of detection was tested where the sensors were calibrated in the air, before immersed in bacterial suspension and then read in the air, making the immunosensor more sensitive and with a faster detection time. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 10 minutes. Currently sub 10 minutes is faster than previous studies using fiber-optic based biosensors. It is also a much simpler and quicker methodology when compared with conventional laboratory technology.

Breakage and damage of fiber optic cable fibers seriously affect the normal operation of fiber optic networks and it is important to quickly and accurately determine the type and location of faults when they occur. The advantages of wavelet transform in singular signal detection and signal filtering are used to analyze Optical Time Domain Reflectometer (OTDR) curve signal and the fault detection method of fiber communication link with no relay and large span in high altitude area is given, which realizes the accurate detection and location of optical fiber communication link fault events under strong noise. The theoretical analysis is basically consistent with the experimental data. The accuracy of optical fiber fault location has been greatly improved in performance. The method has been directly applied to the field detection of ultra-long optical fiber links in high altitude areas, which has certain significance for the future real-time monitoring of optical fiber cables.

This work presents first time successfully fabricated silica few-mode microstructured optical fiber (MOF) with hollow GeO2-doped ring core and strongly induced twisting up to 790 revolutions per meter. Some technological issues for manufacturing of GeO2-doped supporting elements for large hollow cores as well as described above complicated spun MOFs are discussed. We introduce some results of tests, performed for pilot samples of designed and manufactured described above untwisted and twisted MOFs with outer diameter 65 µm and hollow ring core inner diameter 30.5 µm under wall thickness 1.7 µm and refractive index difference n=0.030, including their geometrical parameters, basic transmission characteristics and measurements of far-field laser beam profile patterns.

The success of composite materials is attributed to the nature of bonding at the nanoscale and the resulting structure-related properties. This study reports the interaction, electronic, and optical properties of diamond nanothread/polymers (cellulose and epoxy) and boron nitride nanotube/calcium silicate hydrate composites using density functional theory modeling. Our findings indicate that the interaction between the nanothread and polymer is due to van der Waals-type bonding. Minor modifications in the electronic structures and absorption spectra are noticed. Conversely, the boron nitride nanotube and calcium silicate hydrate composite display an electron-shared type of interaction. The electronic structure and optical absorption spectra of the diamond nanothread and boron nitride nanotube in all configurations studied in the aforementioned composite systems are well maintained. Our findings offer an electronic-level perspective into the bonding characteristics and electronic-optical properties of diamond nanothread/polymer and boron nitride nanotube/calcium silicate hydrate composites for developing next-generation materials.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on barium fluoride substrate close to the sample. Preliminary results of imaging thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and increase in background noise.

To achieve a narrow bandwidth optical filter with a wide swept range for new generation optical spectrum analysis (OSA), an optoelectronic equivalent narrowband filter (OENF) is investigated and a swept optical filter with bandwidth of several MHz and swept range of several ten nanometers is built using electric filters and a swept laser as local oscillator (LO). The principle of OENF is introduced and analysis of OENF system is presented. Two electric filters are optimized to be RBW filters for high and medium spectral resolution application. Both simulations and experiments are conducted to verify OENF principle and results show that power uncertainty is less than 1.2% and spectral resolution can reach 6 MHz. Then, a real-time wavelength calibration system consisting of HCN gas cell and FP etalon is proposed to guarantee a wavelength accuracy of ±0.4 pm at C-band and to reduce the influence of phase noise and nonlinear velocity of swept LO. Finally, experiments on OSA of actual spectra of various optical sensors using OENF system are conducted. Experimental results indicate that OENF system has an excellent capacity in analysis of fine spectrum structures.

This study introduces a Fiber Specklegram Sensor (FSS) design for temperature measurement utilizing a single-multi-single mode optical fiber configuration. FSS technology offers unique advantages for potential development into portable sensing systems. This investigation explores an FSS design compatible with miniaturization by optimizing the interrogation system based on the relationship between speckle grain size and filtering fiber area. Temperature variations are detected through fluctuations in optical power at the sensor output, offering a simple and reduced interrogation scheme. The performance of the FSS is assessed through post-calibration measurements compared to a commercial Fiber Bragg Grating (FBG) sensor, demonstrating comparable results. These findings pave the way for compact and portable fiber optic temperature sensing systems leveraging FSS advantages while maintaining compatibility with established fiber optic measurements.

We report on the study of the temperature dependence of the response of a BSO crystal based polarimetric current sensor with spectral interrogation. Two possible interrogation schemes are discussed. The spectral dependence of the optical rotation along the crystal caused by temperature and current changes has been investigated and approximate dependences for the sensitivities to current SI and temperature ST have been derived. A mixed term in the response with spectral interrogation has been revealed, the elimination of which is done by tracking wavelength shifts of two distinct extrema in the polarimetric response. A temperature independent second degree equation for the current changes as a function of the spectral shifts has been derived and tested.

This paper reports on the fabrication of alumina doped preforms using MCVD-vapor phase chelate delivery system with Al(acac)3 as the precursor. The objectives of the work are to study the deposition process, the efficiency of the fabrication process, and the quality of the fabricated fiber preforms. Two parameters are studied, Al(acac)3 sublimator temperature (TAl°C) and deposition direction (i.e. downstream and upstream). Other parameters such as oxygen flow and deposition temperature are fixed. The results showed that a high uniformity of refractive index difference (%RSD < 2%) and core size (%RSD < 2.4%) was obtained along the preform length using downstream deposition while for the combined upstream and downstream deposition the uniformity was deteriorated. The process efficiency was found to be about 21% for TAl°C of 185°C and downstream deposition. From the EDX elemental analysis, the refractive index was found to increase by 0.0025 per mole percent of alumina.

This paper presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g. a laser diode is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD). The software in the downstream microcontroller identifies the geometric shape’s center, distortion and size, then calculates X, Y, and Z coordinates. These coordinates can then be processed in attached devices. The 3-axis sensor is characterized by its very high resolution, precise reproducibility and plausibility of the coordinates produced. In addition, optical processing of the signal provides a high level of safety against electromagnetic and radio frequency interference. The sensor presented here is adaptive and can be adjusted to fit a user’s range of motion (stroke and force). This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability.

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change of refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. In the experiment, a three-bladed propeller with a diameter of 39mm was selected, the water tank size was 980mm×380mm×380mm, and the laser acted at a distance of 550 mm from the propeller. The experimental results indicate that the wake dissipation time of the propeller in a strong density-stratified water environment is approximately 800s. Following the stabilization of the wake field density, the laser spot position is observed to be stable at 0.341 mm, with a corresponding refractive index change of 2.99×10-6 RIU. The wake dissipation time of the propeller in a linear density-stratified water environment is approximately 750 s. Once the wake field density has reached a stable state, the laser spot position is found to be 0.441mm, corresponding to a refractive index change of 3.87×10-6 RIU. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental device-based wake measurements with the CTD-based wake measurements reveals a consistent trend.

Acousto-Optical Tunable Filters (AOTFs) are a promising technology, exceptionally suited for advanced applications in spectroscopy and imaging across various scientific fields, including space exploration. This is due to their flexibility and high-speed functionality for precise wavelength selection via periodic modulation of the crystal’s refractive index using sound waves. These AOTFs are in turn driven by Radio Frequency (RF) signals through a transducer creating sound waves inside the crystal. This work presents a detailed comparison of three distinct topologies of Radio Frequency Power Amplifiers (RFPAs) for driving these AOTFs within the 30 to 300 MHz frequency range. The analysis focuses on three critical parameters: efficiency, bandwidth, and linearity, which are essential for optimizing the performance of AOTFs. By evaluating the trade-offs among these parameters, this research aims to identify the most effective design approach for RFPAs in this application context.

The calibration of length is related to the national economy and people's livelihood. The traditional calibration of length value was sent the uncalibrated instrument to the laboratory and the intrinsic error of the tested instrument was obtained in the laboratory. However, calibrating the instrument in the site produced additional error. In this article, a remote calibration method of length measurement based on optical fiber information transmission following with a proof of principle system was studied to reduce the additional error. The 1.0-level displacement guide rail was calibrated according to this method. The results showed that the relative error of guide rail displacement under different lengths was within 0.6%. The expanded uncertainties of 10 μm, 100 μm and 1 mm were analyzed respectively. The calibration results meet the actual standards of the guide rail. This optical method is a good candidate for remote calibration.

This work presents results of property researches of fabricated samples of silica few-mode optical fiber (FMF) with induced chirality under twisting 10 and 66 revolutions per meter, core diameter 11 µm, typical “telecommunication” cladding diameter 125 µm and improved height of quasi-step refractive index profile. Proposed FMF supports 4 guided modes over “C”-band. We represent results of computed characteristics, as well as experimentally measured spectral responses of laser-excited optical signals, including researches and analysis of few-mode effects, occurring after fiber Bragg grating writing.

Optical fiber sensors have become a widely-used tool to perform life-long monitoring of large structures. Different set-ups of sensors can be used to obtain information at different scopes. In this paper, the application of a portable Brillouin optical time domain analysis sensor applied to reinforced concrete beams is presented. The sensor is made up of a single-mode optical fiber applied to the structure that enables the measurement of tensile and compressive axial strain along the beams. The fiber is embedded into a concrete casting and fixed along the reinforcement bars so that a complete correlation can be obtained regarding strain and displacements in linear and non-linear flexural response. The use of four sensing fibers positioned along the beam's length at different vertical positions makes it possible to read the strain variation within the cross-section. In accordance with Bernoulli’s hypothesis, this allows curvature diagrams to be obtained across the structure. The measured curvature is used to set up the moment–curvature relationship, which highlights the possibility of the sensor monitoring structures continuously in space and time.

As screen sizes are becoming larger and larger, which are beyond human’s physical limitation for direct touching interaction, remote controls are inevitable. However, as techniques applied so far, inertial gyroscopes are susceptible to position inaccuracies, and gesture recognition is limited by cameras’ focus depth and viewing angle. Grating antenna light trapping technology will be an ideal candidate providing the ghost point problem for multipoint inputs can be solved. Therefore, we propose a differential amplitude modulation scheme for grating antenna based multi beam optical touch, which can recognize different incidence points. Where, the amplitude of the incident beams was coded with different pulse width at first. Then, after been trapped by the grating antenna and been transferred into currents by the lined detector arrays, the incident points of the individual beams were recognized and differentiated. The scheme was successfully verified on an 18-inch screen, where two-point optical touch with position accuracy error under 3mm and response time less than 7ms under modulation frequency of 10kHz on both incident beams are obtained. This work paves a practical way for remote multi-point touch, which can make digital mouse in consistent to the users pointing direction obeying natural three-point one ling aiming rule instantaneously.

The undoped and tungsten (W)-doped vanadium dioxide (VO₂) thin films were prepared by electron beam evaporation associated with ion-beam assisted deposition (IAD). The influence of different W-doped contents (3%-5%) on the optical, electrical, structural, and thermos-mechanical properties of VO₂ thin films was investigated experimentally. Spectral transmittance results showed that with the increase of W-doped contents, the transmittance in the visible light range (400-750 nm) decreases from 60.2% to 53.9%, and the transmittance in the infrared wavelength range (2.5 μm to 5.5 μm) drops from 55.8% to 15.4%. As the W-doped content increases, the residual stress in the VO₂ thin film decreases from -0.276 GPa to -0.238 GPa, but the surface roughness increases. For temperature-dependent spectroscopic measurements, heating the VO2 thin films from 30°C to 100°C showed the most significant change in transmittance for the 5% W-doped VO₂ thin film. When the heating temperature exceeds 55°C, the optical transmittance drops significantly, and the visible light transmittance drops by about 11%. Finally, X-ray Diffraction (XRD) and scanning electron microscope (SEM) were used to evaluate the microstructure characteristics of VO₂ thin films.

We present an innovative method harnessing multistability within a diode-pumped erbium-doped fiber laser to construct logic gates. Our approach involves manipulating the intensity of external noise to regulate the probability of transitioning among four concurrent attractors. In this manner, we facilitate the realization of OR, AND, NOT, and NOR logic operations, aligning with the coexisting period-1, period-3, period-4, and period-5 orbits. Employing detrended fluctuation analysis, we establish equilibrium in the probability distributions of these states. The obtained results denote a substantial advancement in the field of optical logic gate development, representing a pivotal stride toward the seamless integration of an all-optical logic gate within laser oscillator-based systems.

Reconstruction of acoustic relaxation absorption curve is a powerful approach to ultrasonic gas sensing, but requires known of a series ultrasonic absorption at various frequencies around effective relaxation frequency. Ultrasonic transducer is a most widely deployed sensor for ultrasonic wave propagation measurement and works only at a fixed frequency or specific environment like water, so a large number of ultrasonic transducers operating at various frequencies are required to recover an acoustic absorption curve with a relative large bandwidth, which cannot suit for large-scale practical applications. This paper proposes a wideband ultrasonic sensor using a distributed Bragg reflector (DBR) fiber laser for gas concentration detection through acoustic relaxation absorption curve reconstruction. With a relative wide and flat frequency response, the DBR fiber laser sensor measures and restores a full acoustic relaxation absorption spectrum of CO2 using a decompression gas chamber between 0.1 and 1 atm to accommodate the main molecular relaxation processes, and interrogates with a non-equilibrium Mach-Zehnder (M-Z) interferometer to gain a sound pressure sensitivity of -45.4 dB. The measurement error of the acoustic relaxation absorption spectrum is less than 1.32%.

For the first time, mathematical models were obtained for evaluating biomedical images using fuzzy set methods on the basis of expert knowledge bases, which made it possible to carry out complex qualitative diagnostics and increase the reliability and efficiency of diagnosis, to form a methodology for analyzing biomedical images based on the fuzzy set apparatus, which allowed to more fully assess the level of the disease for glaucoma. Aspects of practical implementation of the optical-electronic system of biomedical information processing are considered. An algorithm and an optical-electronic system of biomedical image analysis are proposed, which are used to increase the informativeness and reliability of diagnosing eye pathologies, in particular, glaucoma.

In this study, 10%PTFE/PEEK blend were modified by potassium titanate whisker (PTW) and chopped glass fiber (GF), respectively. The blends were prepared by three-screw extruder. Through the investigation of thermal stability, tribological properties, mechanical properties and rheological behavior, the effects of reinforcing agents were determined. The results illustrated that the mechanical properties of 10%PTFE/PEEK blend can be dramatically improved by adding reinforcing agent of PTW or GF, and the reinforcing effect of GF was especially obvious. As for tribological properties, 1% addition was the best proportion. The friction coefficient and wear rate of the blend with 1% PTW were 0.283 and 4.97 × 10^-6 mm³/N · m, which decreased by 7.2% and 21% compared with those of the blend without reinforcing agent.

Open-vocabulary learning has recently gained prominence as a means to enable image segmentation for arbitrary categories based on textual descriptions. This advancement has extended the applicability of segmentation systems to a broader range of generally purpose scenarios. However, current methods often revolve around specialized architectures and parameters tailored to specific segmentation tasks, resulting in a fragmented landscape of segmentation models. In response to these challenges, we introduce OVAMTSeg, a versatile framework designed for Open-Vocabulary and Multitask Image Segmentation. OVAMTSeg harnesses adaptive prompt learning to empower the model to capture category-sensitive concepts, enhancing its robustness across diverse multi-task and scenario contexts. Text prompts are employed to effectively capture semantic and contextual features of the text, while cross-attention and cross-modal interactions enable the fusion of image and text features. Furthermore, a transformer-based decoder is incorporated for dense prediction. Extensive experimental results underscore the effectiveness of OVAMTSeg, showcasing its state-of-the-art performance and superior generalization capabilities across three segmentation tasks. Notable achievements include a 47.5 mIoU in referring expression segmentation, 51.6 mIoU on Pascal-VOC with four unseen classes, 46.6 mIoU on Pascal-Context in zero-shot segmentation, 65.9 mIoU on Pascal-5i, and 35.7 mIoU on COCO-20i datasets for one-shot segmentation.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

The nutrient absorption and utilization efficiency in the roots of seedlings are beneficial for increasing crop yield. Creating marker assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different nitrogen applications on RSA is of great significance for breeding nitrogen efficient wheat varieties. In this study, A total of 243 wheat varieties native to the Yellow and Huai Valley regions of China were utilized for genome-wide association studies (GWAS). Furthermore, a recombinant inbred line (RIL) population of 123 lines derived from the cross between Avocet and Chilero was utilized for linkage examination and confirmation of the hereditary loci distinguished by GWAS. Five RSA traits include the relative number of root tips (RNRT); relative total root length (RTRL); relative total root surface area (RTRS); relative total root volume (RTRV) and relative average root diameter (RARD) where evaluated under two N conditions—normal N (NN) supply and low N (LN)—to characterize the NUE of each accession. GWAS and linkage analysis were performed by integrating data from the wheat 660k single nucleotide polymorphism (SNP) chip and diversity arrays technology (DArT) to identify genetic loci associated with RSA. The results showed that based on the ratio of RSA related traits under two N supply conditions, a total of 598 SNP markers, which are significantly associated with RSA related traits, were detected at 160 genetic loci by GWAS. A total of 10 QTL loci related to RSA were dis-covered and identified by linkage mapping. In which, three significant RSA related Quantitative Trait Locus (QTL) were identified, namely qRtrl-3D, qRnrt-3D, and qRtrl-7D. The study has the potential to enhance the effectiveness of selecting root traits in wheat breeding programs, offering valuable insights into the genetic underpinnings of nitro-gen use efficiency (NUE) in wheat. This could lead to the creation of NUE wheat varieties by implementing focused breeding strategies

With the increasing concern of environment, the energy-efficiency scheduling of manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time can affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer linear programming model for energy-efficient scheduling of flexible flow shop. Accordingly, a new decoding method is developed by considering of the optimization of spindle speed and scheduling scheme simultaneously, and an estimation of distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistical technique with a simplified practical case. In order to validate the proposed method, a case from practical factories is studied, in which the makespan can be shortened by 25.22%, and the consumed energy can be saved by 5.48%. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

Carotid atherosclerotic lesions are a major cause of cerebrovascular disease (CVD). Identification and quantification of carotid plaques are important for categorizing the vulnerability of plaques for rupture and assessing the impact of treatments. The irregularity of plaque surface is associated with previous plaque rupture and plays an important role in the risk of stroke. Thus, the aim of this study is to develop and validate novel vulnerability biomarkers from three-dimensional ultrasound (3DUS) images by analyzing the surface morphological characterization of carotid plaque using fractal geometry features. 3D box-counting and 3D blanket are the two types of 3D fractal dimension that were employed to describe the smoothness of plaques. This fractal dimension analysis tool was used to evaluate the effect of atorvastatin using 3DUS carotid images, which were acquired from 6 patients treated with atorvastatin with 80 mg daily and 5 patients with placebo. The Student's T Test results showed that those two fractal features were effective for detecting the statin-related changes in carotid atherosclerosis with p<0.0068 and p<0.015 respectively, suggesting that 3D fractal dimension measurements can be used effectively to analyze the surface characteristics of carotid plaques, especially for evaluating the impact of the treatment.

The exceptional performance advantages of the fiber optic gyroscope (FOG) position it as a dominant player in middle and high-end inertial navigation systems. To prevent the loss of sensor precision caused by algorithm design and simplify the complex modeling strategy in traditional methods. We gradually demonstrate the significant role of Convolutional Neural Network (CNN) in the navigation system based on FOG, and utilize the particle swarm optimization algorithm (PSO) to expedite the convergence of the network. The experimental results demonstrate that the initial alignment method based on deep learning is more accurate than the traditional method. The attitude angle error is reduced by 81.25%, 92.54% and 36.53% respectively. The research provides support for the future application of deep learning in optical navigation systems.

The world is struggling with the increasing rate at which water bodies are constantly polluted due to rapid modernization and industrialization. The different types of water contaminants include both anthropogenic and natural contaminants. Environmentalists are mainly concerned about heavy metals such as cadmium ions, as they are considered poisonous and carcinogenic even if they are present at a minimum concentration, and they are considered an immediate concern, according to the World Health Organization. Recently, many methods, such as solvent extraction, ion exchange, electrochemical precipitation, and reverse osmosis, have been developed to remove heavy metals from wastewater. These methods have been reported to be expensive and inefficient; hence, more cost-effective and eco-friendly alternative strategies are needed. Amidst these challenges, a ray of hope emerges in the form of biosorbents. These abundant, eco-friendly, and cost-efficient materials have shown promise as an alternative method for removing heavy metals from wastewater. They are equipped with functional groups that can effectively absorb metal ions onto their surfaces, offering a potential solution to our water contamination woes. This review is significant as it delves into the potential use of several biosorbents to decontaminate cadmium ions from wastewater. This review is significant as it delves into the potential use of several biosorbents to decontaminate cadmium ions from wastewater

Cymbidium faberi Rolfe is one of the traditional Chinese orchids with important ornamental value, and the cultivation of Cymbidium faberi Rolfe mutant strains with different appearances is essential to increase its economic value, but at present, the acquisition of Cymbidium faberi Rolfe mutant strains basically relies on natural mutation.The objectives of this research were to mutagenize Cymbidium faberi Rolfe protocorm-like bodies (PLBs) and shoots in vitro using sodium azide (NaN3), and to screen and evaluate mutants in mutagenized Cymbidium faberi Rolfe seedlings using morphological characteristics.Cymbidium faberi Rolfe PLBs and shoots were used as mutagenic materials, and co-cultivated in induced shoots growth medium with the addition of 0.0 (control), 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 mg/L and 0.0 (control), 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, and 10.0 mg/L NaN3 to induce the mutations, and the mortality rates of the PLBs and shoots were increased with the increase of the NaN3 concentration.At 14 d of co-cultivation, PLBs and shoots were most efficiently mutagenized with 1.5 mg/L and 4.0 mg/L NaN3, respectively.After the explants were cultured for 3 months, changes in leaf and flower morphology were observed in some mutants: shorter and thicker leaves, shorter node length, reduced height, and mid-translucent leaves compared with controls; and some Cymbidium faberi Rolfe bloomed prematurely, with single flowers with large, thick petal sepals and small inflorescences, and colours include light green throughout, and a few with purple stamens.This suggests that NaN3 can effectively mutagenise Cymbidium faberi Rolfe PLBs and shoots to satisfy people's demand for Cymbidium faberi Rolfe's ornamental properties while increasing its economic value.

Road cracks significantly affect the serviceability and safety of roadways, especially in mountainous terrain. Traditional inspection methods, such as manual detection, are excessively time-consuming, labor-intensive, and inefficient. Additionally, multi-function detection vehicles equipped with various sensors are expensive and not suitable for mountainous roads due to poor conditions. To address these challenges, this study proposes a customized Unmanned Aerial Vehicles (UAV) inspection system designed for automatic crack detection. The system focuses on enhancing autonomous capabilities in mountainous terrains by incorporating embedded algorithms for route planning, autonomous navigation, and automatic crack detection. The slide window method is proposed to enhance the autonomous navigation of UAV flights by generating path planning in mountainous roads. This method compensates for GPS/IMU positioning errors, particularly in GPS-denied or GPS-drift scenarios. Moreover, the YOLOv8 algorithm is introduced to conduct autonomous crack detection from UAV imagery in the offboard module. To validate our UAV inspection system's performance, we conducted several experiments to assess its accuracy, robustness, and efficiency. The experimental results demonstrate that our UAS inspection system accurately estimates the flight trajectory along the mountainous road for autonomous navigation. Furthermore, the experimental detection results also demonstrate that the YOLOv8 algorithm achieves higher recognition accuracy compared to the YOLOv5, and YOLOv7-tiny algorithms, exceeding 3.1%,and 6.8% of mAP, respectively. In summary, the UAV inspection system proposed in this study can provide a useful tool and technological guidance for the regular inspection of mountainous roads.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Electrochemical methods are used for the treatment of both municipal and industrial wastewater, either independently or in conjunction with biological methods. This conjunction is used for pretreatment or posttreatment of biologically treated wastewater. In our work, we focused on the combination of these processes, where pre-electrolysis was used to produce dissolved iron before the activation process. Electrolysis was also directly introduced into the activation using either iron or carbon electrodes. The surface of one iron electrode was 32.2 cm2, the applied voltage was 21 V, and the supplied current was 270 mA. The surface of one carbon electrode was 7.54 cm2, the supplied current was 82.5 mA, and the applied voltage was 21 V. From laboratory research on the treatment of synthetic municipal wastewater using a combination of electrolysis and activation processes, it resulted that the use of iron electrodes increased the efficiency of phosphorus removal compared to its precipitation with iron salts. The electrolysis had a positive effect on the sedimentation properties of sludge and the destruction of filamentous microorganisms. Electrolysis negatively affected the respiration rates of activated sludge and the efficiency of denitrification. However, it did not have a negative impact on the nitrification activity of the sludge.

In this project, four of fibers Bragg gratings were fabricated by injecting different volumes of liquids (star line Glass Mechanix optical adhesive material, olive oil diluted with ethanol) into the hollow core fiber. The amplitude splitting interferometric technique with a high resolution specially designed translation stage was used for the fabrication process. The fabrication was done using ultraviolet laser operated at wavelength 405nm. The fabricated Bragg length of the four fibers is equal to 3.8 cm. The results presented fiber Bragg grating (FBG) with successful fabrication at 653.3 nm Bragg reflected wavelength.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Panax notoginseng is a traditional Chinese medicine, and saponins are its main active ingredients. The content of saponins in flower of P. notoginseng is the highest in the whole plant. Minor ginsenosides have stronger pharmacological activity than main ginsenosides, but its content in nature is very low. We can use extracted total saponins from P. notoginseng flower as the substrate to produce minor ginsenosides by biotransformation method. In this study, we used the fungus Talaromyces flavus and its crude enzymes to transform the extracted total saponins of P. notoginseng flower. Through the qualitative and quantitative analysis of the transformation substrates and products, it was found that minor ginsenosides Gyp-XVII, ginsenosides C-Mc1, C-Mx1, F2, Rg3, 20(R)-Rg3, Rk1 and Rg5 were found in the products and the conversion rate of the major saponins in P. notoginseng flower ranged from 44.16 to 55.22%, the yields of the minor ginsenosides ranged from 0.05 to 3.24%. This study provided a good experimental idea, greatly increased the utilization rate of total saponins in P. notoginseng flower, and laid a foundation for promoting the wide application of minor saponins.

Quantitative determination of the critical size of inclined coal pillar in old goaf water affected area is of great significance for water damage prevention and safe mining. The critical size of inclined waterproof coal pillar is derived by using theoretical analysis, numerical calculation and field engineering practice for the stability of the waterproof coal pillar in old goaf water affected area of 1303 working face of Dananhu I mine in Xinjiang region. Firstly, a force model of inclined waterproof coal pillar was established to reveal the law that the critical size of the coal pillar increases with the increase of coal seam inclination under the action of asymmetric load. Then, numerical simulation was applied to reveal the dynamic evolution process of plastic deformation-destabilization-destruction of section coal pillar under the influence of mining and single-side water pressure, and the critical size of waterproof coal pillar in study area was determined to be 19.09m. Finally, measures such as pumping and pressure relief and slurry reinforcement were adopted to reduce the deformation rate of the roadway on side of waterproof coal pillar, which ensured the stability of the coal pillar and roadway and the safe recovery of the working face.

This study investigates the impact of specimen size on the mechanical properties of wood, specifically focusing on compression strength, elastic modulus, and Poisson's ratio. Compression tests were conducted using three different specimen sizes (20mm×20mm×30mm, 40mm×40mm×60mm, 60mm×90mm×90mm) in the longitudinal, radial, and tangential directions. Mechanical parameters, failure mechanisms, load-displacement curves, and stress-strain relationships were systematically analyzed for each size. The study also evaluated the influence of specimen size on the accuracy of finite element numerical simulations by utilizing the obtained mechanical parameters. The results reveal a significant correlation between compressive strength and specimen size, indicating a decrease in compressive strength with increasing specimen size. Conversely, elastic modulus and Poisson's ratio exhibit less sensitivity to variations in specimen size. Notably, parameters derived from small-sized specimens (20mm×20mm×30mm) exhibited substantial errors, while those obtained from medium-sized (40mm×40mm×60mm) and large-sized specimens (60mm×90mm×90mm) demonstrated greater reliability, providing precise results in finite element numerical simulations.

In the realm of power delivery to end-users, transformers are indispensable, with their malfunctions leading to substantial economic, safety, and environmental repercussions. The need for persistent surveillance is accentuated for in-situ oil-filled transformers, given the potential degradation of oil and the emergence of related ageing by-products. As the focus tilts towards online detection methodologies for transformer oil ageing, bypassing challenges associated with traditional offline methods such as sample contamination and misinterpretation, fiber optic sensors are gaining trac-tion due to their compact nature, cost-effectiveness, and resilience to electromagnetic disturbances typical in high-voltage environments. This work delves into the sensitivity analysis of intensi-ty-modulated plastic optical fiber sensors. The investigation encompasses key determinants such as the influence of optical source wavelengths, noise response dynamics, ramifications of varying sensing lengths, and repeatability assessments. Findings underscore that elongating the sensing length detrimentally affects both the linearity response and repeatability, largely attributed to the diminished resistance to external noise. Additionally, the choice of the optical source wavelength proved to be a critical variable in assessing sensor sensitivity.

The use of fiber optics as a tool for different kinds of geotechnical monitoring can become highly attractive and cost effective when compared to conventional instruments such as piezometers, inclinometers, among others. A single fiber optic cable may cover a larger monitoring area compared to conventional instrumentation, and the possibility of monitoring more than one physical quantity with the same fiber optic cable. Consulting the literature, it is possible to find several different examples where distributed fiber optic systems are being used. For the use of any sensor, a calibration curve is required. In the case of strain sensors, calibration is required to derive strain values from the frequency measurement quantity. However, fiber optic sensor cable manufacturers often do not provide their own calibration parameters and consult the values in specialized literature, which can result in monitoring errors. In this context, this article presents a bench adjusted for tests on single mode fiber optic cables, as well as results of tensile tests aimed at defining the function of strain variations of two different optical fiber cables, manufactured by different companies, using two different distributed interrogators. This paper also proposes a methodology for calibrating of the fiber optic cables deformation since the calibration parameters are provided by the cable manufacturers, which can result in errors depending on the application. It should be noted that there are few manufacturers of fiber optic cables aimed at application in civil engineering. Therefore, with the calibration methodology proposed in this paper, it is intended to transmit to the academic community the possibility of obtaining calibration parameters of any fiber optic cable, even those manufactured for telecommunications purposes and not only for cables manufactured with the intended use in civil engineering. Because of this fact, researchers will not be restricted to the acquisition of special cables for their applications. Based on the results, it was possible to conclude that the application of calibrated fiber optic sensors in experimental piles foundations is viable, in order to evaluate the load-displacement behavior of these elements, under different loading conditions.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

Iron tailings are solid waste generated after the mining of iron mines, which have caused serious damage to the surrounding ecology and environment and have attracted widespread attention. By analyzing the formation causes, main components, and environmental effect mechanisms of iron tailings, the article systematically elaborates on the degree and mechanism of the harm of iron tailings to water bodies, atmosphere, soil, and ecosystems, and evaluates its impact on human health and sustainable development of society. On this basis, specific prevention and control measures have been proposed to reduce iron tailings emissions, realize resource recycling, and restore ecosystems. Research shows that iron tailings containing heavy metals can widely pollute the environment through dissolution and migration, and have significant biological toxicity effects. The research results can provide a theoretical reference for decision-making departments to formulate scientific and reasonable iron tailings disposal and ecological protection policies. It is recommended to strengthen specific research on the infiltration of toxic and harmful components in tailings in the future, and develop efficient and stable solidification technology, and vegetation-microbial joint restoration models to further reduce the ecological and environmental risks of iron tailings.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Cloud computing refers to applications delivered as services over the Internet. Cloud systems employ policies that are inherently dynamic in nature and that depend on temporal conditions defined in terms of external events, such as the measurement of bandwidth, use of hosts, intrusion detection or specific time events. In this paper, we investigate an optimized resource management scheme named v-Mapper. The basic premise of v-Mapper is to exploit application-awareness concepts using software-defined networking (SDN) features. This paper makes three key contributions to the field: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. An evaluation was carried out with various benchmarks and demonstrated that v-Mapper shows improved performance over other state-of-the-art approaches in terms of average task completion time, service delay time and bandwidth utilization. Given the growing importance of supporting large-scale data processing and analysis in datacentres, the v-Mapper system has the potential to make a positive impact in improving datacentre performance in the future.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

An optical frequency comb (OFC) generator based on an electro-optic Talbot laser and cross-phase modulation (XPM) in a high nonlinear fiber (HNLF) is designed and demonstrated. The Talbot laser is an electro-optic frequency shifting loop to produce repetition rate multiplied pulses, and these pulses working as a pump signal induce XPM process in the HNLF to modulate the phase of a probe signal. At the output of the HNLF, OFCs with a multiplied line-spacing can be generated. The effects of the pump power and the HNLF length on the performance of the generated OFCs are theoretically analyzed. In the experiments, the line-spacing of the generated OFCs is respectively multiplied to be 10 GHz, 15 GHz and 20 GHz with a factor of 2, 3 and 4. The center of the OFCs is tuned in a 4-nm range by adjusting the wavelength of the probe signal.

X-ray Fluorescence Computed Tomography (XFCT) is an emerging non-invasive imaging technique providing molecular-level data, gaining attention for high-resolution imaging. However, increased sensitivity with benchtop X-ray sources raises radiation exposure. Artificial Intelligence (AI), particularly deep learning (DL), has revolutionized medical imaging by delivering high-quality images in the presence of noise. In XFCT, traditional methods rely on complex algorithms for noise reduction, but AI holds promise in addressing high-dose concerns. We present an optimized SCUNet model for noise reduction in low-concentration XRF images. Compared to higher-dose images, our method’s effectiveness is evaluated. While various denoising techniques exist for X-ray and CT, few address to XFCT. The DL model is trained and assessed using the augmented data, focusing on background noise reduction. Image quality is measured using PSNR and SSIM, comparing outcomes with 100% X-ray dose images. Results show the proposed algorithm achieves high-quality images from low-dose and low-contrast agents, with a maximum PSNR of 39.05 and SSIM of 0.86. The model outperforms BM3D, NLM, DnCNN, and SCUNet in both visual inspection and quantitative analysis, particularly in high-noise scenarios. This indicates the potential of AI, specifically the SCUNet model, in significantly improving XFCT imaging by mitigating the trade-off between sensitivity and radiation exposure.

The effect of H2S with high concentrations on catalytic dry reforming of methane (DRM) process has seldom been focused on previously. Herein, a thermodynamic analysis of the DRM reactions in the presence of H2S with the concentration varying in 0-20 vol% was conducted firstly. Several typical types of catalysts including MgO, NiO/MgO and LaNiO3 in different states were prepared for executing DRM at 800 C, 0.1 MPa in the feed of 20 vol% CO2 and 20 vol% CH4 balanced with N2. The catalytic performance of each catalyst for DRM process under conditions of absence and presence of H2S was compared. A promotion effect of increasing H2S concentration on both the conversions of CO2 and CH4 and the molar yields of CO and H2 was observed on all the catalysts especially the MgO and the pristine NiO/MgO. While a significant decline in catalytic activity of either the reduced NiO/MgO or the reduced LaNiO3 catalyst after adding H2S, moderate reactant conversions still sustained. The results of process analysis and catalyst structure characterization suggest that H2S participation can contribute to the increment in CO2 and CH4 conversion, and active S-adsorbed species may play the key role of catalysis in the reactions involving H2S.

To achieve n-type doping in diamond, extensive investigations employing first principles have been conducted on various models of phosphorus doping and boron-phosphorus co-doping. The primary focus of this study is to comprehensively analyze the formation energy, band structure, density of states, and ionization energy of these structures. It is observed that within a diamond structure solely composed of phosphorus atoms, the formation energy of an individual carbon atom is excessively high. However, the substitution of two carbon atoms leads to the conversion of diamond into a p-type semiconductor. Upon examining the P-B co-doping structure, it is revealed that the doped impurities exhibit a tendency to form more stable cluster configurations. As the separation between the freely doped atoms and the cluster impurity structure increases, the overall stability of the structure diminishes, consequently resulting in an elevation of the ionization energy. Analysis of the electronic density of states demonstrates that the electron orbit of the B atom makes negligible contributions to the impurity levels during P-B doping.