Multiple-Emitting Luminescent Metal-Organic Framework as an Array-on-a-MOF for Rapid Screening and Discrimination of Nitroaromatics.

Fluorescence array technologies have attracted great interest in the sensing field because of their high sensitivity, low cost, and capability of multitarget detection. However, traditional array sensing relies on multiple independent sensors and thus often requires time-consuming and laborious measurement processes. Herein, we introduce a novel fluorescence array strategy of the array-on-a-metal-organic framework (MOF), which integrates multiple array elements into a single MOF matrix to achieve facile sensing and discrimination of multiple target analytes. As a proof-of-concept system, we constructed a luminescent MOF containing three different emitting channels, including a lanthanide ion (europium/Eu3+, red emission), a fluorescent dye (7-hydroxycoumarin-4-acetic acid/HCAA, blue emission), and the MOF itself (UiO-66-type MOF, blue-violet emission). Five structurally similar nitroaromatic compounds (NACs) were chosen as the targets. All three channels of the array-on-a-MOF displayed rapid and stable fluorescence quenching responses to NACs (response equilibrium achieved within 30 s). Different responses were generated for each channel against each NAC due to the various quenching mechanisms, including photoinduced electron transfer, energy competition, and the inner filter effect. Using linear discriminant analysis, the array-on-a-MOF successfully distinguished the five NACs and their mixtures at varying concentrations and demonstrated good sensitivity to quantify individual NACs (detect limit below the advisory concentration in drinking water). Moreover, the array also showed feasibility in the sensing and discrimination of multiple NACs in real water samples. The proposed "array-on-a-MOF" strategy simplifies multitarget discrimination procedures and holds great promise for various sensing applications.

Robust Activity and Stability of P-Doped Fe-Carbon Composites Derived from MOF for Bromate Reduction.

Iron-based materials are effective for the reductive removal of the disinfection byproduct bromate in water, while the construction of highly stable and active Fe-based materials with wide pH adaptability remains greatly challenging. In this study, highly dispersed iron phosphide-decorated porous carbon (Fe2P(x)@P(z)NC-y) was prepared via the thermal hydrolysis of Fe@ZIF-8, followed by phosphorus doping (P-doping) and pyrolysis. The reduction performances of Fe2P(x)@P(z)NC-y for bromate reduction were evaluated. Characterization results showed that the Fe, P, and N elements were homogeneously distributed in the carbonaceous matrix. P-doping regulated the coordination environment of Fe atoms and enhanced the conductivity, porosity, and wettability of the carbonaceous matrix. As a result, Fe2P(x)@P(1.0)NC-950 exhibited enhanced reactivity and stability with an intrinsic reduction kinetic constant (kint) 1.53-1.85 times higher than Fe(x)@NC-950 without P-doping. Furthermore, Fe2P(0.125)@P(1.0)NC-950 displayed superior reduction efficiency and prominent stability with very low Fe leaching (4.53-22.98 µg L-1) in a wide pH range of 4.0-10.0. The used Fe2P(0.125)@P(1.0)NC-950 could be regenerated by phosphating, and the regenerated Fe2P(0.125)@P(1.0)NC-950 maintained 85% of its primary reduction activity after five reuse cycles. The study clearly demonstrates that Fe2P-decorated porous carbon can be applied as a robust and stable Fe-based material in aqueous bromate reduction.

Establishment of an Efficient Genetic Transformation System in Sanghuangporus baumii.

(1) Background: Sanghuangporus baumii, a valuable medicinal fungus, has limited studies on its gene function due to the lack of a genetic transformation system. (2) Methods: This study aimed to establish an efficient Agrobacterium tumefaciens-mediated transformation (ATMT) system for S. baumii. This study involved cloning the promoter (glyceraldehyde-3-phosphate dehydrogenase, gpd) of S. baumii, reconstructing the transformation vector, optimizing the treatment of receptor tissues, and inventing a new method for screening positive transformants. (3) Results: The established ATMT system involved replacing the CaMV35S promoter of pCAMBIA-1301 with the gpd promoter of S. baumii to construct the pCAMBIA-SH-gpd transformation vector. The vectors were then transferred to A. tumefaciens (EHA105) for infection. This study found that the transformation efficiency was higher in the infection using pCAMBIA-SH-gpd vectors than using pCAMBIA-1301 vectors. The mycelia of S. baumii were homogenized for 20 s and collected as the genetic transformation receptor. After 20 min of co-culture and 48 h of incubation in 15 mL PDL medium at 25 °C, new colonies grew. (4) Conclusions: These colonies were transferred to PDA medium (hygromycin 4 µg/mL, cefotaxime 300 µg/mL), and the transformation efficiency was determined to be 33.7% using PCR.

Efficient Catalytic Oxidation of Ethylene at 0 °C on an in Situ Carbon Modified Pt Catalyst Supported on SBA-15.

The design of efficient catalysts for catalytic ethylene (C2H4) oxidation is of crucial importance for extending the shelf life of fruits and vegetables. Herein, a carbon modified SBA-15 supported Pt catalyst (Pt/CSBA-15) was prepared in situ by a facile solid phase grinding-infiltration-inert atmosphere calcination method. Characterization results reveal that in the Pt/CSBA-15 catalysts thin carbon layers are successfully formed in the hexagonal pores of SBA-15. Additionally, Pt particles are well dispersed in the channels of SBA-15, and Pt/CSBA-15 has a smaller Pt particle size than the catalyst without carbon modification (i.e., Pt/SBA-15). O2 is more feasibly adsorbed and activated on small-sized Pt particles, and in situ formed carbon species enhance the hydrophobicity of catalysts. As a result, both 3Pt/CSBA-15 and 5Pt/CSBA-15 are able to maintain 100% conversion of 50 ppm of C2H4 for more than 7 h at 0 °C. 3Pt/CSBA-15 even achieves 81.5% C2H4 conversion and 71.6% CO2 yield after 20 h, exhibiting much more prominent catalytic performances than 3Pt/SBA-15. DFT calculations and in situ FTIR measurements confirm that small-sized Pt particles possess strong O2 affinity to promote O2 adsorption, and in situ formed hydrophobic carbon layers efficiently suppress competitive H2O adsorption. Such a unique one-step catalyst preparation method for regulating the size of metal particles and the hydrophobicity of catalysts can be perfectly utilized to develop simple and efficient hydrophobic catalysts applied in low-temperature oxidation of C2H4.

Benzenepoly(carboxylic acid)s as Exclusive Intrinsic Markers to Assess Riverine Export of Dissolved Black Carbon.

Landscape fires annually generate large quantities of black carbon. The water-soluble fraction of black carbon (i.e., dissolved black carbon/DBC) is an important constituent of the dissolved organic carbon (DOC) pool, playing a crucial role in the global budget of refractory carbon and climate change. A key challenge in constraining the flux and fate of riverine DBC is to develop targeted and accurate quantification methods. Herein, we report that benzenepentacarboxylic acid (B5CA) intrinsically present in DBC can be used as an exclusive and holistic marker (representing both condensed aromatics and less-/nonaromatic fractions) for DBC quantification. B5CA was universally detected in water extractions of biochar and fire-affected soils with relatively large abundance but not produced by nonthermogenic processes. It has good mobility in the environment as it is not readily precipitated by cations or adsorbed by common geosorbents. B5CA also represents the recalcitrant components of DBC with excellent stability against photodegradation and biodegradation. Applying B5CA as the DBC marker in surface waters of the Changjiang River (i.e., the third largest river in the world), we calculate the DBC concentration in the downstream Changjiang River to be 4.8 ± 5.5% of the DOC flux. Our work provides a simple and reliable approach for the accurate quantification and source tracking of DBC in the soil and aquatic carbon pools.

A joint method of coherence factor and nonlinear beamforming for synthetic aperture imaging with a ring array.

Ultrasound computed tomography (USCT) with a ring array is an emerging diagnostic method for breast cancer. In the literature, synthetic aperture (SA) imaging has employed the delay-and-sum (DAS) beamforming technique for ring-array USCT to obtain isotropic resolution reflection images. However, the images obtained by the conventional DAS beamformer suffer from off-axis clutter and low resolution due to inhomogeneity of the medium and phase distortion. To address these issues, researchers have developed adaptive beamforming methods, such as coherence factor (CF) and convolutional beamforming algorithm (COBA), that improve image quality. In this study, we propose a joint method that combines CF with short-lag COBA (SLCOBA). First, we estimate the average sound speed using CF to address tissue inhomogeneity. Based on the corrected sound speed map, SLCOBA effectively suppresses side lobes and enhances image quality. Numerical results show that the proposed method reduces clutter and noise, improving resolution performance. These findings suggest that the proposed method may be a practical option for breast imaging in inhomogeneous mediums in the future.

A deep supervised transformer U-shaped full-resolution residual network for the segmentation of breast ultrasound image.

PURPOSE: Breast ultrasound (BUS) is an important breast imaging tool. Automatic BUS image segmentation can measure the breast tumor size objectively and reduce doctors' workload. In this article, we proposed a deep supervised transformer U-shaped full-resolution residual network (DSTransUFRRN) to segment BUS images. METHODS: In the proposed method, a full-resolution residual stream and a deep supervision mechanism were introduced into TransU-Net. The residual stream can keep full resolution features from different levels and enhance features fusion. Then, the deep supervision can suppress gradient dispersion. Moreover, the transformer module can suppress irrelevant features and improve feature extraction process. Two datasets (dataset A and B) were used for training and evaluation. The dataset A included 980 BUS image samples and the dataset B had 163 BUS image samples. RESULTS: Cross-validation was conducted. For the dataset A, the proposed DSTransUFRRN achieved significantly higher Dice (91.04 ± 0.86%) than all compared methods (p < 0.05). For the dataset B, the Dice was lower than that for the dataset A due to the small number of samples, but the Dice of DSTransUFRRN (88.15% ± 2.11%) was significantly higher than that of other compared methods (p < 0.05). CONCLUSIONS: In this study, we proposed DSTransUFRRN for BUS image segmentation. The proposed methods achieved significantly higher accuracy than the compared previous methods.

An evaluation of cervical maturity for Chinese women with labor induction by machine learning and ultrasound images.

BACKGROUND: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. METHODS: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. RESULTS: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. CONCLUSION: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

Effect of low molecular weight organic acids on the lead and chromium release from widely-used lead chromate pigments under sunlight irradiation.

Lead chromate pigments are commonly used yellow inorganic pigments. They can pose environmental risks as they contain toxic heavy metals lead and chromium. Low molecular weight organic acids (LMWOAs), as widespread dissolved organic matter (DOM), affect the lead and chromium release from the pigment in water. In this work, the role of LMWOAs in the photodissolution of commercial lead chromate pigment was investigated. The pigment underwent significant photodissolution under simulated sunlight exposure with LMWOAs, and subsequently released Cr(III) and Pb(II). The photodissolution process is caused by the reduction of Cr(VI) by photogenerated electrons of the lead chromate pigment. The LMWOAs promoted photodissolution of the pigment by improving the electron-hole separation. The formation of Cr(III)-contained compounds leads to a slower release of chromium than lead. The photodissolution kinetics increase with decreasing pH and increasing LMWOAs concentration. The photodissolution of lead chromate pigment was basically positively related to the total number of hydroxyl and carboxyl groups in LMWOAs. The LMWOAs with stronger affinity to lead chromate pigment, lower adiabatic ionization potential (AIP) and higher energy of the highest occupied molecular orbital (EHOMO) are favorable to Cr(VI) reduction by photogenerated electrons and pigment photodissolution. 2.39% of chromium and 10.34% of lead released from the lead chromate pigment in natural conditions during a 6-h sunlight exposure. This study revealed the photodissolution mechanism of lead chromate pigment mediated by LMWOAs with different molecular structures, which helps understand the environmental photochemical behavior of the pigment. The present results emphasize the important role of DOM in the heavy metals release from commercial inorganic pigments.

Black carbon, soil organic matter molecular signatures under different land uses in Shenyang, China and relationship with PAHs.

The content, composition and molecular signatures of soil organic matter (SOM) have important influences on the cycle of soil organic carbon (SOC) and the partitioning of polycyclic aromatic hydrocarbons (PAHs) in soil. Seventy-nine soil samples from farmland, forest and urban areas were collected in Shenyang, China to investigate black carbon (BC) content, SOM molecular signatures varied with land use patterns, as well as the relationship with PAHs. The content of BC in urban soils was significantly higher than that of farmland and forest. BC was a key contributor of urban SOM which accounted for 0.35 ± 0.31 of SOC in urban soil. Based on BC/SOC ratio, the main sources of BC were identified as fossil fuel combustion for urban soils, while for farmland and forest soils, it is the mixed results of fossil fuel combustion and biomass burning. All categories of PAHs in urban soils showed the highest level compared to farmland and forest soils. Pearson's correlation analysis results showed there were significant positive correlations between BC and PAHs categories in urban soils, indicating the important role of BC in the accumulation of PAHs in soil. SOM from each of the two different land use patterns can be distinguished by molecular signatures. Urban SOM had abundant molecular markers derived from condensed organic carbon inputs, which was consistent with the BC/SOC value. Farmland SOM had abundant carbon from vegetation and microorganisms, and forest SOM was rich in organic carbon from fresh plant materials. The markers enriched in urban SOM showed significant correlations with most PAHs categories, highlighting the affinity of urban SOM for PAHs at the molecular level. This study contributed to understanding the impact of land management methods on SOM molecular composition signatures and its influence on PAHs occurrence in soil, providing a theoretical basis for regional soil pollution management.

Ni12P5 Confined in Mesoporous SiO2 with Near-Unity CO Selectivity and Enhanced Catalytic Activity for CO2 Hydrogenation.

CO2 hydrogenation via the reverse water gas shift (RWGS) reaction is a promising strategy for CO2 utilization while constructing Ni-based catalysts with high catalytic activity and perfect CO selectivity remains a great challenging. Here, we demonstrate that the product selectivity for CO2 hydrogenation can be significantly tuned from CH4 to CO by phosphating of SiO2-supported Ni catalysts due to the geometric effect. Interestingly, nickel phosphide catalysts with different crystalline phases (Ni12P5 and Ni2P) differ sharply in CO2 conversion, and Ni12P5 is remarkably more active. Furthermore, we developed a facile strategy to confine small Ni12P5 nanoparticles in mesoporous SiO2 channels (Ni12P5@SBA-15). Enhanced activity is exhibited on Ni12P5@SBA-15, ascribed to the highly effective confinement effect. The in situ diffuse reflectance infrared Fourier transform spectroscopy and density functional theory calculations unveil that catalytic CO2 hydrogenation follows a direct CO2 dissociation route with adsorbed CO as the key intermediate. Notably, strong multibonded CO (threefold and bridge-bonded CO) is feasibly formed on the Ni catalyst accounting for CH4 as the dominant product whereas only weak linearly bonded CO exists on nickel phosphide catalysts resulting in almost 100% CO selectivity. The present results indicate that Ni12P5@SBA-15 combining the geometric effect and the confinement effect can achieve near-unity CO selectivity and enhanced activity for CO2 hydrogenation.

Complex Transformer Network for Single-Angle Plane-Wave Imaging.

OBJECTIVE: Plane-wave imaging (PWI) is a high-frame-rate imaging technique that sacrifices image quality. Deep learning can potentially enhance plane-wave image quality, but processing complex in-phase and quadrature (IQ) data and suppressing incoherent signals pose challenges. To address these challenges, we present a complex transformer network (CTN) that integrates complex convolution and complex self-attention (CSA) modules. METHODS: The CTN operates in a four-step process: delaying complex IQ data from a 0° single-angle plane wave for each pixel as CTN input data; extracting reconstruction features with a complex convolution layer; suppressing irrelevant features derived from incoherent signals with two CSA modules; and forming output images with another complex convolution layer. The training labels are generated by minimum variance (MV). RESULTS: Simulation, phantom and in vivo experiments revealed that CTN produced comparable- or even higher-quality images than MV, but with much shorter computation time. Evaluation metrics included contrast ratio, contrast-to-noise ratio, generalized contrast-to-noise ratio and lateral and axial full width at half-maximum and were -11.59 dB, 1.16, 0.68, 278 µm and 329 µm for simulation, respectively, and 9.87 dB, 0.96, 0.62, 357 µm and 305 µm for the phantom experiment, respectively. In vivo experiments further indicated that CTN could significantly improve details that were previously vague or even invisible in DAS and MV images. And after being accelerated by GPU, the CTN runtime (76.03 ms) was comparable to that of delay-and-sum (DAS, 61.24 ms). CONCLUSION: The proposed CTN significantly improved the image contrast, resolution and some unclear details by the MV beamformer, making it an efficient tool for high-frame-rate imaging.

Intrinsic peroxidase-like activity of dissolved black carbon released from biochar.

Dissolved black carbon (DBC) is an important constituent of the natural organic carbon pool, influencing the global carbon cycling and the fate processes of many pollutants. In this work, we discovered that DBC released from biochar has intrinsic peroxidase-like activity. DBC samples were derived from four biomass stocks, including corn, peanut, rice, and sorghum straws. All DBC samples catalyze H2O2 decomposition into hydroxyl radicals, as determined by the electron paramagnetic resonance and the molecular probe. Similar to enzymes that exhibit saturation kinetics, the steady-state reaction rates follow the Michaelis-Menten equation. The peroxidase-like activity of DBC is controlled by the ping-pong mechanism, as suggested by parallel Lineweaver-Burk plots. Its activity increases with temperature from 10 to 80 °C and has an optimum at pH 5. The peroxidase-like activity of DBC is positively correlated with its aromaticity as aromatics can stabilize the reactive intermediates. The active sites in DBC also involve oxygen-containing groups, as inferred by increased activity after the chemical reduction of carbonyls. The peroxidase-like activity of DBC has significant implications for biogeochemical processing of carbon and potential health and ecological impacts of black carbon. It also highlights the need to advance the understanding of the occurrence and role of organic catalysts in natural systems.

A nanozyme-like colorimetric sensing strategy based on persulfate activation on Co-based metal-organic frameworks.

A nanozyme-like colorimetric sensing strategy based on persulfate activation on Co-based metal-organic frameworks is developed for biomolecule detection in solution and on paper strips. By switching from H2O2 activation on nanozymes to catalytic persulfate activation, this general strategy provides higher sensitivity, faster speed, and wider application ranges for detection.

ZnO Nanorod-Immobilized Pt Single-Atoms as an Ultrasensitive Sensor for Triethylamine Detection.

Triethylamine (TEA) is a flammable and highly toxic gas, and the fast, accurate, and sensitive detection of gas TEA remains greatly challenging. Herein, we report a ZnO nanorod anchored with a single-atom Pt catalyst (Pt1/ZnO) as a gas sensor for TEA detection. The sensor shows high selectivity and high response to gas TEA with a response value of 4170 at 200 °C, which is 92 times higher than that of pure ZnO. Moreover, the Pt1/ZnO sensor has very short response and recovery times of only 34 and 76 s, respectively, and also has a high response to ppb-level TEA gas (100 ppb-21.6). The gas-sensing enhancement mechanism of the Pt1/ZnO sensor to gas TEA was systematically investigated using band structure analysis, in situ diffuse reflectance infrared Fourier transformation spectroscopy, and density functional theory calculations. The results show that the oxygen vacancies on Pt1/ZnO can effectively activate the adsorbed oxygen. Moreover, chemical bonds can be formed between Pt single atoms and N atoms in TEA to achieve effective adsorption and activation of TEA molecules, facilitating the reaction between TEA and the adsorbed oxygen on Pt1/ZnO, and thereby obtaining high gas-sensing performance. This work highlights the crucial role of Pt single-atom in improving the sensing performance for gas TEA detection, paving the way for developing more advanced gas sensors.

Impacts of dissolved organic matter on the aggregation and photo-dissolution of cadmium pigment nanoparticles in aquatic systems.

Cadmium pigments are a group of inorganic pigments used in consumer products. The aggregation behavior and photo-dissolution process of cadmium pigment nanoparticles in aquatic systems control their environmental fate, which is largely unknown. Herein, we investigated the influence of dissolved organic matter (DOM) on the aggregation behavior and photo-dissolution process of CdS nanoparticles in aquatic systems. Bare CdS nanoparticles are prone to aggregation in both NaCl and CaCl2 solutions. DOM can remarkably increase the colloidal stability of CdS nanoparticles owing to the steric hindrance and enhanced electrostatic repulsion. With 10 mg/L Suwannee River natural organic matter (SRNOM), the colloidal stability of CdS nanoparticles is significantly enhanced in NaCl solutions (i.e., the critical coagulation concentration, CCCNa, is 707.2 mM). Suwannee River humic acid (SRHA) has a stronger stabilization effect than SRNOM due to its higher molecular weight and aromaticity. The Ca2+ cations can induce charge neutralization and structural compacting of DOM corona, efficiently reducing the colloidal stability of CdS nanoparticles. The CCCCa is 10.8 mM and 14.9 mM with 10 mg/L SRNOM and SRHA, respectively. Upon solar irradiation, the presence of a low concentration of SRNOM (3 mg/L) can enhance the photo-dissolution of CdS nanoparticles and the consequent Cd2+ leaching. This is caused by the facilitated electron transfer from CdS nanoparticles to O2 induced by SRNOM corona, leading to better electron-hole separation. However, a high concentration of SRNOM inhibited the photo-dissolution of CdS nanoparticles due to the strong inner filter effect and the scavenging of phototransients. The colloidal stability of SRNOM-coated CdS nanoparticles increases in NaCl but decreases in CaCl2 solutions after irradiation owing to the oxidation of SRNOM corona. Our results highlight the decisive role of DOM in the environmental fate of cadmium pigments.

Effective catalytic hydrodechlorination removal of chloroanisole odorants in water using palladium catalyst confined in zeolite Y.

Chloroanisoles is a class of odorous pollutants commonly identified in drinking water. In the present study, we confined noble metal palladium (Pd) in the micropores of zeolite Y (ie-Pd@Y) using an ion exchange method, and applied it for the catalytic hydrodechlorination removal of chloroanisoles (represented by 2,4,6-trichloroanisole/TCA) in water. Pd supported on zeolite Y surface (im-Pd/Y, prepared by conventional impregnation method) was used as the benchmarking catalyst. The characterization results revealed that ie-Pd@Y had smaller Pd particle size and higher Pdn+/Pd0 ratio than im-Pd/Y. The catalytic hydrodechlorination of TCA followed a concerted dechlorination pathway and the Langmuir-Hinshelwood model. The ie-Pd@Y catalysts with different Pd loadings exhibit excellent catalytic activities with more than 95% of TCA removed within 30 min, which is far superior to the im-Pd/Y catalysts (27-70%). Moreover, due to the confinement effect of zeolite Y, ie-Pd@Y displayed enhanced catalytic stability as compared with im-Pd/Y. The initial activity of ie-Pd@Y was more than 20 times higher than that of im-Pd/Y after five reaction cycles. Additionally, with the assistance of sieving effect, ie-Pd@Y displayed much stronger capability against the interference from dissolved organic matter than im-Pd/Y. The present results demonstrate that the confined catalysts ie-Pd@Y can be applied in liquid phase catalytic hydrogenation to effectively eliminate halogenated odorants in waters.

Deep-Learning-Based Ultrasound Sound-Speed Tomography Reconstruction with Tikhonov Pseudo-Inverse Priori.

Ultrasound sound-speed tomography (USST) is a promising technology for breast imaging and breast cancer detection. Its reconstruction is a complex non-linear mapping from the projection data to the sound-speed image (SSI). The traditional reconstruction methods include mainly the ray-based methods and the waveform-based methods. The ray-based methods with linear approximation have low computational cost but low reconstruction quality; the full wave-based methods with the complex non-linear model have high quality but high cost. To achieve both high quality and low cost, we introduced traditional linear approximation as prior knowledge into a deep neural network and treated the complex non-linear mapping of USST reconstruction as a combination of linear mapping and non-linear mapping. In the proposed method, the linear mapping was seamlessly implemented with a fully connected layer and initialized using the Tikhonov pseudo-inverse matrix. The non-linear mapping was implemented using a U-shape Net (U-Net). Furthermore, we proposed the Tikhonov U-shape net (TU-Net), in which the linear mapping was done before the non-linear mapping, and the U-shape Tikhonov net (UT-Net), in which the non-linear mapping was done before the linear mapping. Moreover, we conducted simulations and experiments for evaluation. In the numerical simulation, the root-mean-squared error was 6.49 and 4.29 m/s for the UT-Net and TU-Net, the peak signal-to-noise ratio was 49.01 and 52.90 dB, the structural similarity was 0.9436 and 0.9761 and the reconstruction time was 10.8 and 11.3 ms, respectively. In this study, the SSIs obtained with the proposed methods exhibited high sound-speed accuracy. Both the UT-Net and the TU-Net achieved high quality and low computational cost.

Synergistic effects boost electrocatalytic reduction of bromate on supported bimetallic Ru-Cu catalyst.

Bromate is a commonly identified carcinogenic and genotoxic disinfection byproduct in water. In the present work, bimetallic Ru-Cu catalyst supported on carbon nanotube (RuCu/CNT) was prepared and the structural properties of the catalysts were characterized. The results show that the presence of Ru enhances the dispersion and reduction of Cu particles in the RuCu/CNT catalyst in comparison with the monometallic Cu catalyst supported on CNT (Cu/CNT). For electrocatalytic reaction on Cu/CNT, bromate is reduced on metallic Cu surface via a redox process. For Ru/CNT, highly active H* radicals are generated on metallic Ru surface via the Volmer process and are used for bromate reduction. As for the RuCu/CNT, bromate is reduced through two main pathways, including direct redox reaction on metallic Cu and indirect reduction by active H* radicals on Ru surface. Accordingly, RuCu/CNT exhibits the highest catalytic activity, ascribed to the synergistic effect between metallic Ru and Cu. Furthermore, the bimetallic catalyst displays much higher catalytic efficiency as compared with previously reported results. The pH, initial bromate concentration, in-situ electrochemical reduction of the electrodes and working potential have strong impacts on the removal efficiency of bromate on RuCu/CNT.