Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm.

Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse's optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters' impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design.

Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning.

Thoracic echocardiography (TTE) can provide sufficient cardiac structure information, evaluate hemodynamics and cardiac function, and is an effective method for atrial septal defect (ASD) examination. This paper aims to study a deep learning method based on cardiac ultrasound video to assist in ASD diagnosis. We chose four standard views in pediatric cardiac ultrasound to identify atrial septal defects; the four standard views were as follows: subcostal sagittal view of the atrium septum (subSAS), apical four-chamber view (A4C), the low parasternal four-chamber view (LPS4C), and parasternal short-axis view of large artery (PSAX). We enlist data from 300 children patients as part of a double-blind experiment for five-fold cross-validation to verify the performance of our model. In addition, data from 30 children patients (15 positives and 15 negatives) are collected for clinician testing and compared to our model test results (these 30 samples do not participate in model training). In our model, we present a block random selection, maximal agreement decision, and frame sampling strategy for training and testing respectively, resNet18 and r3D networks are used to extract the frame features and aggregate them to build a rich video-level representation. We validate our model using our private dataset by five cross-validation. For ASD detection, we achieve [Formula: see text] AUC, [Formula: see text] accuracy, [Formula: see text] sensitivity, [Formula: see text] specificity, and [Formula: see text] F1 score. The proposed model is a multiple instances learning-based deep learning model for video atrial septal defect detection which effectively improves ASD detection accuracy when compared to the performances of previous networks and clinical doctors.

LOANet: a lightweight network using object attention for extracting buildings and roads from UAV aerial remote sensing images.

Semantic segmentation for extracting buildings and roads from uncrewed aerial vehicle (UAV) remote sensing images by deep learning becomes a more efficient and convenient method than traditional manual segmentation in surveying and mapping fields. In order to make the model lightweight and improve the model accuracy, a lightweight network using object attention (LOANet) for buildings and roads from UAV aerial remote sensing images is proposed. The proposed network adopts an encoder-decoder architecture in which a lightweight densely connected network (LDCNet) is developed as the encoder. In the decoder part, the dual multi-scale context modules which consist of the atrous spatial pyramid pooling module (ASPP) and the object attention module (OAM) are designed to capture more context information from feature maps of UAV remote sensing images. Between ASPP and OAM, a feature pyramid network (FPN) module is used to fuse multi-scale features extracted from ASPP. A private dataset of remote sensing images taken by UAV which contains 2431 training sets, 945 validation sets, and 475 test sets is constructed. The proposed basic model performs well on this dataset, with only 1.4M parameters and 5.48G floating point operations (FLOPs), achieving excellent mean Intersection-over-Union (mIoU). Further experiments on the publicly available LoveDA and CITY-OSM datasets have been conducted to further validate the effectiveness of the proposed basic and large model, and outstanding mIoU results have been achieved. All codes are available on https://github.com/GtLinyer/LOANet.

Transition Metal-Promoted Carbon-Silicon Solid Acid Catalysts for the Synthesis and Process Optimization of Benzaldehyde Glycol Acetal.

A series of transition metal (M)-promoted carbon-silicon (C-M-Si; M=Mn, Fe, Co, Ni, Cu, Zn, Zr) solid acid catalysts with designated molar ratio of M/Si=1 : 8 were fabricated and exploited for acetalization of benzaldehyde (BzH) with ethylene glycol (EG). The physical and chemical properties of these C-M-Si catalysts prepared by sol-gel method were characterized by various techniques, namely, SEM, EDS, TGA-DTG, BET, XRD, FTIR, XPS, and NH3 -TPD. Among various examined acidic C-M-Si catalysts, the C-Fe-Si catalyst exhibited the optimal catalytic activity with the benzaldehyde glycol acetal (BEGA) yield of 97.67 %, in excellent agreement with the value (97.88 %) predicted by the response surface methodology (RSM) based on a Box-Behnken design (BBD). C-Fe-Si catalyst with the high catalytic activities and excellent stability and reusability may be ascribed to the suitable acidity and uniform surface distribution of active sites requisite for the acid-catalyzed acetalization reaction.

Microwave-ultrasonic technique development coupled with natural deep eutectic solvents in anthocyanin extraction from perilla leaves (Perilla frutescens var. Acuta).

BACKGROUND: As potent antioxidants, anthocyanins can protect the body from free radicals. However, the traditional solvent extraction method has the disadvantages of requiring a high extraction temperature and long extraction time, so it is necessary to develop an efficient extraction method for anthocyanins. RESULTS: In this study, the technique of natural deep eutectic solvents (DESs) was applied to extract anthocyanins from purple perilla leaves with the aid of microwave-ultrasonic assisted extraction (MUAE). The response surface methodology (RSM), based on the Box-Behnken design (BBD), predicted the maximum extraction yield of anthocyanins to be 619.62 mg (100 g)-1 under the following conditions: x1 (ultrasonic extraction power) = 357.25 W, x2 (time) = 25.62 min, and x3 (temperature) = 57.80 °C. The biological activity of the extract obtained was evaluated by examining its radical-scavenging effect on 1,1-diphenyl-2-picrylhydrazyl, hydroxyl radical, and superoxide anion radicals. Its bacteriostatic impact was investigated on four typical bacteria: Shewanella putrefaciens (S. putrefaciens), Pseudomonas fluorescens (P. fluorescens), Escherichia coli (E. coli), and Staphylococcus aureus (S. aureus). CONCLUSION: The integrated extraction method of DESs with MUAE was efficient, energy-saving, green, and sustainable. © 2022 Society of Chemical Industry.

A lightweight segmentation network for endoscopic surgical instruments based on edge refinement and efficient self-attention.

In robot-assisted surgical systems, surgical instrument segmentation is a critical task that provides important information for surgeons to make informed decisions and ensure surgical safety. However, current mainstream models often lack precise segmentation edges and suffer from an excess of parameters, rendering their deployment challenging. To address these issues, this article proposes a lightweight semantic segmentation model based on edge refinement and efficient self-attention. The proposed model utilizes a lightweight densely connected network for feature extraction, which is able to extract high-quality semantic information with fewer parameters. The decoder combines a feature pyramid module with an efficient criss-cross self-attention module. This fusion integrates multi-scale data, strengthens focus on surgical instrument details, and enhances edge segmentation accuracy. To train and evaluate the proposed model, the authors developed a private dataset of endoscopic surgical instruments. It containing 1,406 images for training, 469 images for validation and 469 images for testing. The proposed model performs well on this dataset with only 466 K parameters, achieving a mean Intersection over Union (mIoU) of 97.11%. In addition, the model was trained on public datasets Kvasir-instrument and Endovis2017. Excellent results of 93.24% and 95.83% were achieved on the indicator mIoU, respectively. The superiority and effectiveness of the method are proved. Experimental results show that the proposed model has lower parameters and higher accuracy than other state-of-the-art models. The proposed model thus lays the foundation for further research in the field of surgical instrument segmentation.

In Situ Simultaneous Analysis of Nitrogen and Phosphorus Migration in Urban Black Odorous Runoff.

The extremely serious urban runoff eutrophication and black odorous phenomenon pose a significant threat to the lake aquatic ecosystem, resulting in a significantly increased frequency, magnitude, and duration of algal blooms in lakes. However, few investigations focus on small tributaries of the lakes, despite the ubiquity and potential local importance of these runoffs. Thus, the labile sediments NH4+-N, NO3--N, PO43-, Fe2+, and S2- in black odorous runoff at Wuxi were overall analyzed at high resolution using diffusive gradients in thin films (DGT). The variations in labile N, P, Fe, and S distribution profiles at different sampling sites indicated high heterogeneity in sediments. The concentrations of labile P, Fe, and S showed synchronous variation from the sediment-water interface (SWI) up to -20 mm along sediment profiles. Moreover, there existed a significant positive correlation among labile P, Fe, and S concentrations (p < 0.05), which might represent typical odor compounds' FeS and H2S synchronous release process in urban runoff. Furthermore, the apparent diffusion fluxes of labile P, Fe, and S across the SWI were all released upward, while fluxes of NH4+-N and NO3--N release downward, indicating the sediments act as source and sink of P and N, respectively. Sediments' potential for endogenous P and N fractions release results in the black-odorous water, and sediment finally abouchement the Taihu, which intensifies further lake eutrophication phenomenon.

Measurement of focal light spot at single-photon level with silicon photomultipliers.

Focal spot (light spot) at single-photon level have important applications in many fields. This report demonstrates a method for measuring focal spot size at the single-photon level indirectly. This method utilizes Silicon Photomultiplier (SiPM) as the single-photon sensitive detectors, combined with a nano-positioning stage. The approach involves one- or two-dimensional space scanning and a deconvolution operation, which enable evaluations of the size and spatial distribution of the focal spot formed by a single-photon-level pulsed laser. The results indicate that the average full width at half maximum of the focal spot is about 0.657 µm, which is close to the nominal resolution of the objective lens of the microscope (i.e. 0.42 µm). The proposed method has two key advantages: (1) it can measure focal spot at the single-photon level, and (2) the focal spot can easily be aligned with the detector because the array area of the Geiger mode avalanche photodiode (Gm-APD) cells in SiPM is usually on the order of square millimeter, and there is no need to put an optical slit, knife edge, or pinhole in front of the detector. The method described herein is applicable in weak focal spot detection related fields.

The variations of labile arsenic diffusion driven by algal bloom decomposition in eutrophic lake ecosystems.

The vertical labile arsenic (As) concentration and diffusion pattern variations in eutrophic lakes were investigated using in situ techniques of diffusive gradients in thin films (DGT) and high-resolution dialysis (HR-Peeper) in the typical eutrophic system of Lake Taihu in China. In addition, simulation experiments were used to reveal labile As distributions in sediment profiles under the influence of algae blooms and wind fluctuations. Our results indicated that eutrophication could lead to the migration and transformation of As fractions, including increased As bioavailability, as well as varied diffusion patterns. The sulfate released from algae decomposition reduced to H2S and formed FeS, which weak adsorbability contributed to the increased mobility of the As fractions. Meanwhile, further decomposition released a large quantity of algae-derived organic matter which competed with the adsorbed As, leading to more endogenous As migrating to the overlying water. Accordingly, the H2S production presented a likely explanation for the changed distribution of labile As and contributed to labile As concentrations in the sediment profiles significantly increasing at depths of -20 mm to -60 mm in the early stages of the simulation experiment. Moreover, the areas of enhanced diffusion patterns with high concentrations of As obviously expanded. However, following the complete decomposition of the algae, the organic matter component significantly changed, suggesting an explanation for the variations in distribution of labile As. All the diffusion pattern variations showed similar trends. Consequently, variation of labile As diffusion patterns could indicate the decomposition and eutrophication levels of freshwater ecosystems.

Preparation, characterization and antibacterial activity of new ionized chitosan.

In order to improve the solubility and antibacterial activity of chitosan and expand its application range, ionized chitosan (ICS) was successfully synthesized from chitosan through methylation and sulfonation reactions in this study. The chemical structures of the polymers were verified by Fourier transform infrared spectroscopy (FTIR) and 1H NMR, and a series of characterizations of the polymer were carried out by analytical methods such as element analysis (EA), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and X-ray diffraction (XRD). The results showed that the water solubility of the modified ICS was significantly improved. The introduction of propyl sulfonic acid groups with particle size decreasing and potential increasing greatly improved the antibacterial activity of chitosan, indicating that the ICS had the potential as a water-soluble antibacterial agent.

High-resolution characteristics and mechanisms of endogenous phosphorus migration and transformation impacted by algal blooms decomposition.

Extremely high phosphorus (P) concentrations can be found in eutrophic freshwater sediments during algal blooms (ABs). However, few investigations have revealed the mechanism of labile P production in anoxic sediments following ABs decomposition. This limits our understanding of P cycling and mitigation of ABs in aquatic ecosystems. To identify such a mechanism, we conducted a microcosm experiment to identify how ABs decomposition enhances endogenous P release, using the combined techniques of diffusive gradients in thin films, high-resolution dialysis, and 16S rRNA amplicon sequencing. We show the concentrations of labile iron, manganese, sulfide, and P can be well predicted by quality and quantity of algal biomass. The relative abundance of iron reduction bacteria positively correlated with the decrease of pH induced by ABs decomposition, suggesting that this decomposition facilitates microbial iron and manganese reduction. In addition, the reductive dissolution of iron and manganese oxides leads to the labile P release, resulting in higher concentrations of labile P in those sediments affected by ABs compared with those not affected. The P fluxes in the algae-dominated regions exhibited higher values in the algae group than in the control group, with gains of 14.07-100.04%. Furthermore, endogenous P release is strongly controlled by Mn when the Fe(II):Mn(II) ratio is low (below 0.47), and by both Fe and Mn when the Fe(II):Mn(II) ratio is high (above 0.63). Our results quantify the endogenous P diffusion fluxes across the sediment-water interface can be attributed to ABs decomposition, and are therefore useful for further understanding of P cycling in freshwater.

2D MoTe2 film as a saturable absorber for a wavelength-tunable ultrafast fiber laser.

We have demonstrated the realization of wavelength-tunable pulse outputs in a mode-locked fiber laser by utilizing 2D ${{\rm MoTe}_2}$MoTe2 film as the saturable absorber (SA). The SA is synthesized by coating 2D ${{\rm MoTe}_2}$MoTe2 film on the pinhole of the fiber pigtail and it can work stably at the mode-locking state for several weeks, indicating that the 2D ${{\rm MoTe}_2}$MoTe2 film is a suitable SA for ultrafast optics. The ${{\rm MoTe}_2}$MoTe2 film mode-locked fiber laser can operate well at a wide spectral band, and the central wavelength of pulses is tunable in the range from 1530 to 1560 nm, which is attributed to the polarization-sensitive feature of the proposed SA. Our new SA will benefit high-power pulsed lasers, materials processing, and frequency comb spectroscopy.

Green chemical synthesis of new chelating fiber and its mechanism for recovery gold from aqueous solution.

A novel environmentally-friendly polyacrylonitrile-2-amino-2-thiazoline chelating fiber (PANF-ATL) with good adsorption performance and thermal stability was synthesized in one step by nucleophilic addition reaction using water as a solvent. The optimum synthesis conditions for the chelating fibers are determined by controlling the synthesis temperature and the molar ratio of the reagents. The sulfur content and functional group capacity of the finally synthesized PANF-ATL were 3.82% and 1.19 mmol/g, respectively. PANF-ATL was characterized by elemental analysis, FTIR, TGA, SEM and XPS. Meanwhile, the adsorption characteristics and mechanism of PANF-ATL were evaluated. The Langmuir model and the pseudo-second-order model well described the adsorption of Au(Ⅲ) by PANF-ATL. The adsorption capacity of PANF-ATL obtained from Langmuir isotherm model towards Au(Ⅲ) was 130.58 mg/g (298 K). In addition, Au(Ⅲ) adsorbed on the fibers was completely eluted using a mixed solution of 4 mol/L HCl and 12% thiourea. It still has good adsorption performance after 5 adsorption-desorption cycles. Overall, PANF-ATL is a cost-effective adsorbent that can effectively adsorb Au(Ⅲ) in aqueous solution.

Conventional soliton or stretched pulse delivered by nanotube-mode-locked fiber laser.

We propose a nanotube-mode-locked erbium-doped fiber laser that can deliver conventional solitons (CSs) or stretched pulses (SPs) based on a D-shaped fiber saturable absorber where evanescent-field interaction works. The net cavity dispersion of the laser is slightly negative. In our experiment, by optimizing the polarization controller in the cavity, CS and SP can be obtained at the central wavelengths of 1530.6 nm and 1530.3 nm due to carbon nanotubes and the spectral filtering effect induced by nonlinear polarization rotation. Although the acquired CS and SP nearly have the same central wavelengths, they show distinct optical spectra, 3-dB bandwidths. The proposed fiber laser is attractive for practical applications.

Dual-channel dispersionless slow light based on plasmon-induced transparency.

I have proposed a dual-channel dispersionless slow-light waveguide system based on plasmon-induced transparency. By appropriately tuning the stub depth, two transparency windows in the transmission spectrum can be achieved due to the destructive interference between the electromagnetic fields from the three stubs. Two flat bands can be achieved in the transparency windows, which have nearly constant group indices over the bandwidth of 2 THz. The analytical results show that the group velocity dispersion parameters of the two channels equal zero, which indicates that the incident pulse can be slowed down without distortion. The proposed plasmonic waveguide system can realize slow-light effect without pulse distortion, and thus can find important applications on slow-light systems, optical buffers, and all-optical signal processors in highly integrated optical circuits.

Ultrasound-assisted extraction of polysaccharides from mulberry leaves.

Ultrasound-assisted extraction (UAE) of polysaccharides from mulberry leaves was studied. The effects of four factors on the yield of polysaccharides were investigated. The results showed that optimum conditions were extraction power of 60W, extraction temperature of 60°C, extraction time of 20min and ratio of water to raw material of 15:1 (ml/g). The three different methods (UAE, MAE and CSE) were compared for extracting polysaccharides from the mulberry leaves by SEM images. Totally, UAE had the largest yield of polysaccharides. The crude polysaccharides obtained from UAE were purified and two components (MPS-1 and MPS-2) were obtained. Their structure was analysed with chemical methods. From FT-IR, they were polysaccharides. MPS-1 had more functional groups than MPS-2. From HP GPC analysis, molecular weights of MPS-1 and MPS-2 were 24898D and 61131D, respectively. From GC analysis, MPS-1 was composed of Sor, Ara, Xyl and Glc, and MPS-2 was composed of Rha, Ara, Xyl, Glc, Gal and Man.

[Comparative study on effects of three traditional Chinese medicinal compounds on energy metabolism related enzymes in cerebral tissue of rats after focal cerebral ischemia and reperfusion].

OBJECTIVE: To compare the effects of three traditional Chinese medicinal compounds on energy metabolism related enzymes in cerebral tissue of rats after focal cerebral ischemia and reperfusion (I/R). METHODS: The local cerebral I/R model was established by ligation of the middle cerebral arteries (MCA). The animals were divided into the sham-operative group, the model group, the Yiqi Huoxue Recipe (YHR) group, the Zhengan Xifeng Decoction (ZXD) group and the Xinglou Chengqi Decoction (XCD) group. The mitochondria in brain tissue was obtained by density-centrifugation and differential centrifugation, then the activities of succinate dehydrogenase (SDH), Na+ -K+ -ATPase, creatine kinase-BB (CK-BB) in homogenate of brain tissue were measured by chemical chromometry. RESULTS: Activities of SDH and Na+-K+ -ATPase were lower and that of CK-BB was higher in the model group than those in the sham -operative group at all time points after I/R (P< 0.01). Compared with those in the model group, activity of Na+ -K+ -ATPase was higher only in the ZXD group at 24 h after I/R, while at 48 h and 72 h after I/R, activities of both SDH and Na+ -K+ -ATPase were higher in all the treatment groups. As for the activity of CK-BB, it was lower in all the treatment groups (P < 0.05). The optimal effect was shown in the ZXD group at 24 h, in the XCD group at 48 h, and in the YHR group at 72 h after I/R. CONCLUSION: The three traditional Chinese medicinal compounds could reduce pathologic injury after focal cerebral I/R in rats by promoting activity of SDH and Na+ -K+ -ATPase and inhibiting that of CK-BB, the optimal effect of ZXD was shown at 24 h after I/R, that of XCD at 48 h after I/R and of YHR at 72 h after I/R.