Prediction of lymph node metastasis in advanced gastric adenocarcinoma based on dual-energy CT radiomics: focus on the features of lymph nodes with a short axis diameter ≥6 mm.

Objective: To explore the value of the features of lymph nodes (LNs) with a short-axis diameter ≥6 mm in predicting lymph node metastasis (LNM) in advanced gastric adenocarcinoma (GAC) based on dual-energy CT (DECT) radiomics. Materials and methods: Data of patients with GAC who underwent radical gastrectomy and LN dissection were retrospectively analyzed. To ensure the correspondence between imaging and pathology, metastatic LNs were only selected from patients with pN3, nonmetastatic LNs were selected from patients with pN0, and the short-axis diameters of the enrolled LNs were all ≥6 mm. The traditional features of LNs were recorded, including short-axis diameter, long-axis diameter, long-to-short-axis ratio, position, shape, density, edge, and the degree of enhancement; univariate and multivariate logistic regression analyses were used to establish a clinical model. Radiomics features at the maximum level of LNs were extracted in venous phase equivalent 120 kV linear fusion images and iodine maps. Intraclass correlation coefficients and the Boruta algorithm were used to screen significant features, and random forest was used to build a radiomics model. To construct a combined model, we included the traditional features with statistical significance in univariate analysis and radiomics scores (Rad-score) in multivariate logistic regression analysis. Receiver operating curve (ROC) curves and the DeLong test were used to evaluate and compare the diagnostic performance of the models. Decision curve analysis (DCA) was used to evaluate the clinical benefits of the models. Results: This study included 114 metastatic LNs from 36 pN3 cases and 65 nonmetastatic LNs from 28 pN0 cases. The samples were divided into a training set (n=125) and a validation set (n=54) at a ratio of 7:3. Long-axis diameter and LN shape were independent predictors of LNM and were used to establish the clinical model; 27 screened radiomics features were used to build the radiomics model. LN shape and Rad-score were independent predictors of LNM and were used to construct the combined model. Both the radiomics model (area under the curve [AUC] of 0.986 and 0.984) and the combined model (AUC of 0.970 and 0.977) outperformed the clinical model (AUC of 0.772 and 0.820) in predicting LNM in both the training and validation sets. DCA showed superior clinical benefits from radiomics and combined models. Conclusion: The models based on DECT LN radiomics features or combined traditional features have high diagnostic performance in determining the nature of each LN with a short-axis diameter of ≥6 mm in advanced GAC.

Residual Risk in Non-ST-Segment Elevation Acute Coronary Syndrome: Quantitative Plaque Analysis at Coronary CT Angiography.

Background Lipid-rich plaques detected with intravascular imaging are associated with adverse cardiovascular events in patients with non-ST-segment elevation (NSTE) acute coronary syndrome (ACS). But evidence about the prognostic implication of coronary CT angiography (CCTA) in NSTE ACS is limited. Purpose To assess whether quantitative variables at CCTA that reflect lipid content in nonrevascularized plaques in individuals with NSTE ACS might be predictors of subsequent nonrevascularized plaque-related major adverse cardiovascular events (MACEs). Materials and Methods In this multicenter prospective cohort study, from November 2017 to January 2019, individuals diagnosed with NSTE ACS (excluding those at very high risk) were enrolled and underwent CCTA before invasive coronary angiography (ICA) within 1 day. Lipid core was defined as areas with attenuation less than 30 HU in plaques. MACEs were defined as cardiac death, myocardial infarction, hospitalization for unstable angina, and revascularization. Participants were followed up at 6 months, 12 months, and annually thereafter for at least 3 years (ending by July 2022). Multivariable analysis using Cox proportional hazards regression models was performed to determine the association between lipid core burden, lipid core volume, and future nonrevascularized plaque-related MACEs at both the participant and plaque levels. Results A total of 342 participants (mean age, 57.9 years ± 11.1 [SD]; 263 male) were included for analysis with a median follow-up period of 4.0 years (IQR, 3.6-4.4 years). The 4-year nonrevascularized plaque-related MACE rate was 23.9% (95% CI: 19.1, 28.5). Lipid core burden (hazard ratio [HR], 12.6; 95% CI: 4.6, 34.3) was an independent predictor at the participant level, with an optimum threshold of 2.8%. Lipid core burden (HR, 12.1; 95% CI: 6.6, 22.3) and volume (HR, 11.0; 95% CI: 6.5, 18.4) were independent predictors at the plaque level, with an optimum threshold of 7.2% and 10.1 mm3, respectively. Conclusion In NSTE ACS, quantitative analysis of plaque lipid content at CCTA independently predicted participants and plaques at higher risk for future nonrevascularized plaque-related MACEs. Chinese Clinical Trial Registry no. ChiCTR1800018661 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Tavakoli and Duman in this issue.

Preoperative prediction of Lauren classification in gastric cancer: a radiomics model based on dual-energy CT iodine map.

OBJECTIVE: To investigate the value of a radiomics model based on dual-energy computed tomography (DECT) venous-phase iodine map (IM) and 120 kVp equivalent mixed images (MIX) in predicting the Lauren classification of gastric cancer. METHODS: A retrospective analysis of 240 patients undergoing preoperative DECT and postoperative pathologically confirmed gastric cancer was done. Training sets (n = 168) and testing sets (n = 72) were randomly assigned with a ratio of 7:3. Patients are divided into intestinal and non-intestinal groups. Traditional features were analyzed by two radiologists, using logistic regression to determine independent predictors for building clinical models. Using the Radiomics software, radiomics features were extracted from the IM and MIX images. ICC and Boruta algorithm were used for dimensionality reduction, and a random forest algorithm was applied to construct the radiomics model. ROC and DCA were used to evaluate the model performance. RESULTS: Gender and maximum tumor thickness were independent predictors of Lauren classification and were used to build a clinical model. Separately establish IM-radiomics (R-IM), mixed radiomics (R-MIX), and combined IM + MIX image radiomics (R-COMB) models. In the training set, each radiomics model performed better than the clinical model, and the R-COMB model showed the best prediction performance (AUC: 0.855). In the testing set also, the R-COMB model had better prediction performance than the clinical model (AUC: 0.802). CONCLUSION: The R-COMB radiomics model based on DECT-IM and 120 kVp equivalent MIX images can effectively be used for preoperative noninvasive prediction of the Lauren classification of gastric cancer. CRITICAL RELEVANCE STATEMENT: The radiomics model based on dual-energy CT can be used for Lauren classification prediction of preoperative gastric cancer and help clinicians formulate individualized treatment plans and assess prognosis.

Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion.

Background: This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFRCT), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. Methods: The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFRCT, and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFRCT and the plaque variables. Ischemia was defined as a FFR of ≤0.80. Results: The optimal cut-off value of ΔFFRCT was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm3 and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm3 and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFRCT ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. Conclusions: The addition of the plaque assessment and ΔFFRCT to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.

Role of introduced Se element and induced anion vacancies in Mo(SSe)2-x/G van der Waals heterostructure for enhanced hydrogen evolution reaction.

The Gibbs free energy of hydrogen adsorption at the edge of molybdenum disulfide (MoS2) is close to that of Pt, meaning that MoS2 is the best candidate to replace Pt-based materials. However, easy agglomeration between layers to mask active sites, lack of catalytic activity in the basal planes, and poor electronic conductivity make MoS2 exhibit dissatisfactory hydrogen evolution reaction (HER) catalytic performance. Here, we successfully construct a van der Waals heterostructure stacked alternately with Mo(SSe)2-x and graphene (Mo(SSe)2-x/G) to enhance its catalytic ability. The introduction of Se into MoS2 and the thermal treatment induce the sample to generate more anion vacancies. Theoretical and experimental results demonstrate the constructed van der Waals heterostructure, the introduced Se element, and the increased anion vacancies are in favor of promoting the number of active sites and improving the electronic conductivity of the catalyst. Therefore, Mo(SSe)2-x/G exhibits superior HER catalytic performance (the overpotentials of 137 mV and 136 mV at a current of 10 mA cm-2) and long-term stabilities (>90 h and 140 h at a current density of 20 mA cm-2) in both acidic and alkaline media.

Can PD-L1 expression be predicted by contrast-enhanced CT in patients with gastric adenocarcinoma? a preliminary retrospective study.

BACKGROUND: This study aimed to construct a computed tomography (CT) radiomics model to predict programmed cell death-ligand 1 (PD-L1) expression in gastric adenocarcinoma patients using radiomics features. METHODS: A total of 169 patients with gastric adenocarcinoma were studied retrospectively and randomly divided into training and testing datasets. The clinical data of the patients were recorded. Radiomics features were extracted to construct a radiomics model. The random forest-based Boruta algorithm was used to screen the features of the training dataset. A receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the model. RESULTS: Four radiomics features were selected to construct a radiomics model. The radiomics signature showed good efficacy in predicting PD-L1 expression, with an area under the receiver operating characteristic curve (AUC) of 0.786 (p < 0.001), a sensitivity of 0.681, and a specificity of 0.826. The radiomics model achieved the greatest areas under the curve (AUCs) in the training dataset (AUC = 0.786) and testing dataset (AUC = 0.774). The calibration curves of the radiomics model showed great calibration performances outcomes in the training dataset and testing dataset. The net clinical benefit for the radiomics model was high. CONCLUSION: CT radiomics has important value in predicting the expression of PD-L1 in patients with gastric adenocarcinoma.

CT-based radiomics signature for differentiating pyelocaliceal upper urinary tract urothelial carcinoma from infiltrative renal cell carcinoma.

Objectives: To develop a CT-based radiomics model and a combined model for preoperatively discriminating infiltrative renal cell carcinoma (RCC) and pyelocaliceal upper urinary tract urothelial carcinoma (UTUC), which invades the renal parenchyma. Materials and methods: Eighty patients (37 pathologically proven infiltrative RCCs and 43 pathologically proven pyelocaliceal UTUCs) were retrospectively enrolled and randomly divided into a training set (n = 56) and a testing set (n = 24) at a ratio of 7:3. Traditional CT imaging characteristics in the portal venous phase were collected by two radiologists (SPH and ZXL, who have 4 and 30 years of experience in abdominal radiology, respectively). Patient demographics and traditional CT imaging characteristics were used to construct the clinical model. The radiomics score was calculated based on the radiomics features extracted from the portal venous CT images and the random forest (RF) algorithm to construct the radiomics model. The combined model was constructed using the radiomics score and significant clinical factors according to the multivariate logistic regression. The diagnostic efficacy of the models was evaluated using receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). Results: The RF score based on the eight validated features extracted from the portal venous CT images was used to build the radiomics model. Painless hematuria as an independent risk factor was used to build the clinical model. The combined model was constructed using the RF score and the selected clinical factor. Both the radiomics model and combined model showed higher efficacy in differentiating infiltrative RCC and pyelocaliceal UTUC in the training and testing cohorts with AUC values of 0.95 and 0.90, respectively, for the radiomics model and 0.99 and 0.90, respectively, for the combined model. The decision curves of the combined model as well as the radiomics model indicated an overall net benefit over the clinical model. Both the radiomics model and the combined model achieved a notable reduction in false-positive and false-negativerates, resulting in significantly higher accuracy compared to the visual assessments in both the training and testing cohorts. Conclusion: The radiomics model and combined model had the potential to accurately differentiate infiltrative RCC and pyelocaliceal UTUC, which invades the renal parenchyma, and provide a new potentially non-invasive method to guide surgery strategies.

Detection of left atrial appendage thrombus by dual-energy computed tomography-derived imaging biomarkers in patients with atrial fibrillation.

Aims: This study aimed to assess the diagnostic performances of dual-energy computed tomography (CT)-derived iodine concentration and effective atomic number (Z eff ) in early-phase cardiac CT in detecting left atrial appendage (LAA) thrombus and differentiating thrombus from spontaneous echo contrast (SEC) in patients with atrial fibrillation using transesophageal echocardiography (TEE) as the reference standard. Methods and results: A total of 389 patients with atrial fibrillation were prospectively recruited. All patients underwent a single-phase cardiac dual-energy CT scan using a third-generation dual-source CT. The iodine concentration, Z eff , and conventional Hounsfield units (HU) in the LAA were measured and normalized to the ascending aorta (AA) of the same slice to calculate the LAA/AA ratio. Of the 389 patients, TEE showed thrombus in 15 (3.9%), SEC in 33 (8.5%), and no abnormality in 341 (87.7%) patients. Using TEE findings as the reference standard, the respective sensitivity, specificity, positive predictive value, and negative predictive value of the LAA/AA HU ratio for detecting LAA thrombus were 100.0, 96.8, 55.6, and 100.0%; those of the LAA/AA iodine concentration ratio were 100.0, 99.2, 83.3, and 100.0%; and those of the LAA/AA Z eff ratio were 100.0, 98.9, 79.0, and 100.0%. The areas under the receiver operator characteristic curve (AUC) of the LAA/AA iodine concentration ratio (0.978; 95% CI 0.945-1.000) and Z eff ratio (0.962; 95% CI 0.913-1.000) were significantly larger than that of the LAA/AA HU ratio (0.828; 95% CI 0.714-0.942) in differentiating the thrombus from the SEC (both P < 0.05). Although the AUC of the LAA/AA iodine concentration ratio was larger than that of the LAA/AA Z eff ratio, no significant difference was found between them (P = 0.259). Conclusion: The dual-energy CT-derived iodine concentration and the Z eff showed better diagnostic performance than the conventional HU in early-phase cardiac CT in detecting LAA thrombus and differentiating the thrombus from the circulatory stasis. However, these results need to be validated in large-cohort studies with late-phase images.

Diagnostic Value of Delayed Contrast-Enhanced Cardiac Computed Tomography for Detecting Left Atrial Appendage Thrombus in Patients With Atrial Fibrillation.

Objective: Delayed enhancement cardiac CT is a reliable tool for the diagnosis of left atrial appendage thrombus but limited for scanning heterogeneity. We aimed to explore the improvement of the 1 and 3-min delay phase at the diagnostic level to detect left atrial appendage thrombus, in order to set up a reasonable CT scanning scheme. Materials and Methods: A total of 6,524 patients were continuously retrieved from January 2015 to September 2020 retrospectively. The patients had undergone Transesophageal echocardiography (TEE) and cardiac CT with complete period include the arterial enhancement phase, 1 and 3-min delay phase, TEE were used as the reference standard. The final study included 329 patients. Three experienced radiologists independently assessed each phase of the cardiac CT images for thrombus diagnosis. We explored the improvement of the diagnostic ability of different delayed contrast-enhanced phases for left atrial appendage thrombus detection. Multiple logistic regression analysis were used for further high-risk stratification to avoid an additional 1-min delayed scan. Results: In total, 29 thrombosis were detected at TEE. For all cardiac CT phases, sensitivity and negative predictive were 100%. The specificity were 0.54, 0.93, and 1.00, respectively; The positive predictive values (PPV) were 0.17, 0.57, and 1.00, respectively; Area under curve (AUC) were 0.75, 0.95, and 0.98, respectively. High risk factors that cannot be clearly diagnosed with 1-min delay phase included reduced cardiac function, increased CHA2DS2-VAScscore and left atrial enlargement. Compared with the arterial enhanced phase, increased radiation doses in the 1 and 3-min delay phases were 1.7 ± 1.3 msv and 1.5 ± 0.8 msv (mean ± standard deviation). Conclusion: Using TEE as the reference standard, early contrast-enhanced CT scanning with 1 and 3-min delay is necessary for the diagnosis of left appendage thrombus, which could significantly improve the diagnostic efficiency. Patients with high-risk stratification are suitable for direct 3-min delayed scanning.

Diagnosis of Serosal Invasion in Gastric Adenocarcinoma by Dual-Energy CT Radiomics: Focusing on Localized Gastric Wall and Peritumoral Radiomics Features.

Objectives: To build a radiomics model and combined model based on dual-energy CT (DECT) for diagnosing serosal invasion in gastric adenocarcinoma. Materials and methods: 231 gastric adenocarcinoma patients were enrolled and randomly divided into a training (n = 132), testing (n = 58), and independent validation (n = 41) cohort. Radiomics features were extracted from the rectangular ROI of the 120-kV equivalent mixed images and iodine map (IM) images in the venous phase of DECT, which was manually delineated perpendicularly to the gastric wall in the deepest location of tumor infiltration, including the peritumoral adipose tissue within 5 mm outside the serosa. The random forest algorithm was used for radiomics model construction. Traditional features were collected by two radiologists. Univariate and multivariate logistic regression was used to construct the clinical model and combined model. The diagnostic efficacy of the models was evaluated using ROC curve analysis and compared using the Delong's test. The calibration curves were used to evaluate the calibration performance of the combined model. Results: Both the radiomics model and combined model showed high efficacy in diagnosing serosal invasion in the training, testing and independent validation cohort, with AUC of 0.90, 0.90, and 0.85 for radiomics model; 0.93, 0.93, and 0.89 for combined model. The combined model outperformed the clinical model (AUC: 0.76, 0.76 and 0.81). Conclusion: The radiomics model and combined model constructed based on tumoral and peritumoral radiomics features derived from DECT showed high diagnostic efficacy for serosal invasion in gastric adenocarcinoma.

High Performance 3D Self-Supporting Cu-Bi Aerogels for Electrocatalytic Reduction of CO2 to Formate.

The electrocatalytic reduction of CO2 (CO2 RR) to CO, formate, methane, and other high-value compounds is a promising technique. However, current electrocatalysts suffer from drawbacks such as few active catalytic sites, poor selectivity and low stability, etc, which restrict the practical application. Although monatomic metal catalysts have been widely reported in recent years, high performance non-noble metal aerogels were rarely investigated for electrocatalytic CO2 RR. Herein, Cu-Bi aerogels with boosted CO2 RR activity were well constructed by a simple one-step self-assembly method. The resultant Cu1 Bi2 exhibits excellent CO2 RR activity with high faradaic efficiency (FE) of 96.57 % towards HCOOH at a potential of -0.9 V vs. RHE, and the FEHCOOH remains over 80.18 % in a wide potential window (-0.8 V to -1.2 V vs. RHE). It demonstrated that the enhanced CO2 RR activity of Cu-Bi aerogels could be attributed to the 3D self-supporting structure of the catalysis, synergistic effect, and low interfacial charge transfer resistance.

Solvent-Controlled Morphology of Amino-Functionalized Bimetal Metal-Organic Frameworks for Asymmetric Supercapacitors.

The composition-tuned, structure-modified, and morphology-controlled nanoscale metal-organic frameworks (MOFs) are quite important to improve the electrochemical performances for supercapacitors. In this work, a solvent-controlled method to prepare amino-functionalized bimetal MOFs with various morphologies is proposed. Three different morphologies of NiCo-MOFs, such as nanospheres, nanosheet-assembled hollow spheres (NSHSs), and rhombus sheets, have been successfully synthesized by using different solvents. The as-prepared three nanoscale NiCo-MOFs are comparatively characterized and are endowed a possible mechanism on nucleation and crystal growth controlling morphology. When used as electrode materials for supercapacitors, all NiCo-MOFs have excellent electrochemical properties. Specifically, the NiCo-MOF NSHS owns the best specific capacitance, which can achieve 1126.7 F g-1 at the current density of 0.5 A g-1 and maintain 93% of its original capacitance at the current density of 10 A g-1 after 3000 charge-discharge cycles. Moreover, an asymmetric supercapacitor device (NiCo-MOF NSHS//AC) assembled with NiCo-MOF NSHS as the positive electrode and activated carbon (AC) as the negative electrode achieves an energy density of 20.94 Wh kg-1 at a power density of 750.84 W kg-1. This work is facile and highly reproducible and can be extended to prepare other nano-MOFs in energy storage and conversion fields. In addition, it opens up an effective approach to synthesizing amino-functionalized MOFs by a solvent-controlled method without any other changes in the experimental conditions.

MOF-assisted construction of a Co9S8@Ni3S2/ZnS microplate array with ultrahigh areal specific capacity for advanced supercapattery.

Transition metal sulfides are important candidates of battery-type electrode materials for advanced supercapatteries due to their high electric conductivity and electrochemical activity. The Co9S8@Ni3S2/ZnS composite microplate array was prepared by a metal-organic framework-assisted strategy because the electrochemical properties of composite arrays are governed by the synergistic effects of their diverse structures and compositions. As a battery-type material, the Co9S8@Ni3S2/ZnS electrode expressed an ultrahigh areal specific capacity of 8192 C cm-2 at the current density of 2 mA cm-2, and excellent cycling stability of 79.7% capacitance retention after 4000 cycles. An assembled supercapattery device using the Co9S8@Ni3S2/ZnS microplate array as a positive electrode and active carbon as the negative electrode delivered a high energy density of 0.377 mW h cm-2 at a high power density of 1.517 mW cm-2, and outstanding retention of 95.2% after 5000 cycles. As a result, the obtained Co9S8@Ni3S2/ZnS shows potential for applications in high-performance supercapattery.

Metal-Organosulfide Coordination Polymer Nanosheet Array as a Battery-Type Electrode for an Asymmetric Supercapacitor.

Metal-organosulfide coordination polymers (MOSCPs) are important functional materials with attractive application prospects. Herein a two-dimensional structural MOSCP was fabricated on nickel foam with nanosheet array morphology. When as the binder-free battery-type electrode for a supercapacitor, the as-prepared Co-based MOSCP showed high specific capacitance (759 F g-1/379.5 C g-1/105.4 mAh g-1 at 0.5 A g-1), excellent rate performance (58.8% after the current density increased 20 times), and good cycle stability (73.4% after 5000 cycles). In addition, a maximum energy density of 31.97 Wh kg-1 was obtained at a power density of 375.01 W kg-1 in the assembled asymmetric supercapacitor device. These results indicated that this work would open up a new path to design and prepare the battery-type electrode for a supercapacitor by exploring nanoscale MOSCP materials.

Design of MoS2/Graphene van der Waals Heterostructure as Highly Efficient and Stable Electrocatalyst for Hydrogen Evolution in Acidic and Alkaline Media.

The thermodynamically stable phase of molybdenum disulfide (MoS2) is evaluated as a promising and durable nonprecious-metal electrocatalyst toward the hydrogen evolution reaction (HER); however, its actual catalytic activity is restricted by an inert basal plane, low electronic conductivity, low density, and using efficiency of edged atoms. Moreover, 2D/2D van der Waals (vdws) heterostructures (HSs) with face-to-face contact can construct a highly coupled interface and are demonstrated to have immense potential for catalytic applications. In the present work, a 2D/2D hetero-layered architecture of an electrocatalyst, based on the alternate arrangement of ultrasmall monolayer MoS2 nanosheets (approximately 5-10 nm) and ultrathin graphene (G) sheets, is prepared by a facilely chemical process, which is named as MoS2/G HS. The unique structural characteristic of MoS2/G HS is in favor of accommodating more active sites as the centers of ad/desorption hydrogen and transferring and separating the charges at a coupled interface to improve the electronic conductivity and durability. The density functional theory calculation results further confirm that the alternately arranged G layers and MoS2 monolayers, as well as the expanded interplanar distance of 1.104 nm for MoS2/G HS, can exhibit a superior HER performance in both 0.5 M H2SO4 and 1.0 M KOH.

In-Situ Synthesis of Hydrophobic Polyurethane Ternary Composite Induced by Hydroxyethyl Cellulose through A Green Method for Efficient Oil Removal.

Hydroxyethyl cellulose (HEC) was introduced to activate the surface of polyurethane (PU) sponge to successfully prepare a hydrophobic ternary composite PU/HEC/SiO2. The hydrophobic layer of the composite was realized by in-situ polymerization of methyltriethoxysilane (MTES) onto the surface of PU sponge. The formation of a stable hydrophobic SiO2 layer solved successfully the problem of ease of SiO2 particles shedding from the composite. Moreover, the amphiphilic molecules produced by the hydrolysis of MTES monomers facilitated the preparation of hydrophobic materials by aqueous dispersion polymerization. Aqueous synthesis made the reaction process environmentally-friendly and pollution-free. The as-prepared composite PU/HEC/SiO2 not only retains high porosity and low density of the PU sponge, but also considerably reduced the surface free energy and increased the surface roughness of the PU sponge. Therefore, outstanding hydrophobicity and high porosity endow the composite with excellent oil removal capability as a high-efficiency absorbent. Moreover, the hydrophobic composite that had absorbed oil could be regenerated easily by squeezing and recycling.

Dual apodization with cross-correlation combined with robust Capon beamformer applied to ultrasound passive cavitation mapping.

PURPOSE: Passive acoustic mapping (PAM) has received increasing attention in recent years and has an extremely widespread application prospect in real-time monitoring of ultrasound treatment. When using a diagnostic ultrasound transducer, such as a linear-array transducer, the initially used time exposure acoustics (TEA) algorithm will produce high-level artifacts. To address this problem, we recently proposed an enhanced algorithm for linear-array PAM by introducing dual apodization with the cross-correlation (DAX) method into TEA. But due to that the delay and sum beamformer used to create RX1 and RX2 is non-adaptive, the remaining X-type artifacts cannot be completely suppressed, yielding unsatisfactory image quality. This study aims to propose an improved version by combining DAX and robust Capon beamformer (DAX-RCB). METHODS: Different from the delay and sum beamformer in the DAX-TEA algorithm, in the proposed version, the two sets of channel signals from a pair of complementary receive apodizations are beamformed by the RCB method, which may make passive cavitation images much less sensitive to X-type artifacts. The performance of the DAX-RCB algorithm is validated by simulations and in vitro experiments and compared with the initially used TEA algorithm and the previous DAX-TEA and RCB algorithms. Four indexes, including passive energy beam (PEB) size, image signal-to-background ratio (ISBR), energy estimation ratio (EER), and computing time, are used to evaluate the algorithm performance. RESULTS: Consider an example of the 8-8 alternating pattern (a pair of complementary apodizations are obtained by extracting eight elements every eight elements), the experimental results show that the A-6dB area (2D PEB size) of the proposed DAX-RCB is significantly reduced by 11.0 and 6.8 mm2 when compared with TEA and DAX-TEA and is not significantly reduced when compared with RCB, the ISBR is significantly improved by 19.6, 10.8, and 5.6 dB compared with TEA, DAX-TEA, and RCB, and the EER of DAX-RCB is over 90%. The simulation tests indicate that the DAX-RCB algorithm is also applicable to the image enhancement in the double-source scenario and the high-level noise scenario but at a risk of low energy estimation. The improvement of algorithm performance is accompanied by an increase in the computing time. The proposed DAX-RCB consumes 113.3%, 29.5%, and 17.8% more time than TEA, DAX-TEA, and RCB. CONCLUSIONS: The proposed DAX-RCB can be considered as an effective reconstruction algorithm for passive cavitation mapping and provide an appropriate monitoring means for ultrasound therapy, especially for cavitation-mediated applications.

Zeolitic imidazolate framework derived ZnCo2O4 hollow tubular nanofibers for long-life supercapacitors.

Uniform one-dimensional metal oxide hollow tubular nanofibers (HTNs) have been controllably prepared using a calcination strategy using electrospun polymer nanofibers as soft templates and zeolitic imidazolate framework nanoparticles as precursors. Utilizing the general synthesis method, the ZnO HTNs, Co3O4 HTNs and ZnCo2O4 HTNs have been successfully prepared. The optimal ZnCo2O4 HTNs, as a representative substance applied in supercapacitors as the positive electrode, delivers a high specific capacity of 181 C g-1 at a current density of 0.5 A g-1, an excellent rate performance of 75.14% and a superior capacity retention of 97.42% after 10 000 cycles. Furthermore, an asymmetric supercapacitor assembled from ZnCo2O4 HTNs and active carbon also shows a stable and ultrahigh cycling stability with 95.38% of its original capacity after 20 000 cycle tests.

MOF-derived Bi2O3@C microrods as negative electrodes for advanced asymmetric supercapacitors.

Bismuth oxide (Bi2O3) with high specific capacity has emerged as a promising negative electrode material for supercapacitors (SCs). Herein, we propose a facile metal-organic framework (MOF) derived strategy to prepare Bi2O3 microrods with a carbon coat (Bi2O3@C). They exhibit ultrahigh specific capacity (1378 C g-1 at 0.5 A g-1) and excellent cycling stability (93% retention at 4000 cycles) when acting as negative electrode material for advanced asymmetric SCs. The assembled Bi2O3@C//CoNi-LDH asymmetric supercapacitor device exhibits a high energy density of 49 W h kg-1 at a power density of 807 W kg-1. The current Bi-MOF-derived strategy would provide valuable insights to prepare Bi-based inorganic nanomaterials for high-performance energy storage technologies and beyond.

Delay multiply and sum beamforming method applied to enhance linear-array passive acoustic mapping of ultrasound cavitation.

PURPOSE: Passive acoustic mapping (PAM) has been proposed as a means of monitoring ultrasound therapy, particularly nonthermal cavitation-mediated applications. In PAM, the most common beamforming algorithm is a delay, sum, and integrate (DSAI) approach. However, using DSAI leads to low-quality images for the case where a narrow-aperture receiving array such as a standard B-mode linear array is used. This study aims to propose an enhanced linear-array PAM algorithm based on delay, multiply, sum, and integrate (DMSAI). METHODS: In the proposed algorithm, before summation, the delayed signals are combinatorially coupled and multiplied, which means that the beamformed output of the proposed algorithm is the spatial coherence of received acoustic emissions. We tested the performance of the proposed DMSAI using both simulated and experimental data and compared it with DSAI. The reconstructed cavitation images were evaluated quantitatively by using source location errors between the two algorithms, full width at half maximum (FWHM), size of point spread function (A50 area), signal-to-noise ratio (SNR), and computational time. RESULTS: The results of simulations and experiments for single cavitation source show that, by introducing DMSAI, the FWHM and the A50 area are reduced and the SNR is improved compared with those obtained by DSAI. The simulation results for two symmetric or nonsymmetric cavitation sources and multiple cavitation sources show that DMSAI can significantly reduce the A50 area and improve the SNR, therefore improving the detectability of multiple cavitation sources. CONCLUSIONS: The results indicate that the proposed DMSAI algorithm outperforms the conventionally used DSAI algorithm. This work may have the potential of providing an appropriate method for ultrasound therapy monitoring.