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Abstract Background Despite the efficacy of absolute ethanol (EtOH), its radiolucency introduces several risks in interventional therapy for treating vascular malformations. This study aims to develop a novel radiopaque ethanol injection (REI) to address this issue. Methods Iopromide is mixed with ethanol to achieve radiopacity and improve the physicochemical properties of the solution. Overall, 82 male New Zealand white rabbits are selected for in vivo radiopacity testing, peripheral vein sclerosis [animals were divided into the following 5 groups (n = 6): negative control (NC, saline, 0.250 ml/kg), positive control (EtOH, 0.250 ml/kg), low-dose REI (L-D REI, 0.125 ml/kg), moderate-dose REI (M-D REI, 0.250 ml/kg), and high-dose REI (H-D REI 0.375 ml/kg)], pharmacokinetic analyses (the blood sample was harvested before injection, 5 min, 10 min, 20 min, 40 min, 1 h, 2 h, 4 h, and 8 h after injection in peripheral vein sclerosis experiment), peripheral artery embolization [animals were divided into the following 5 groups (n = 3): NC (saline, 0.250 ml/kg), positive control (EtOH, 0.250 ml/kg), L-D REI (0.125 ml/kg), M-D REI (0.250 ml/kg), and H-D REI (0.375 ml/kg)], kidney transcatheter arterial embolization [animals were divided into the following 4 groups (n = 3): positive control (EtOH, 0.250 ml/kg), L-D REI (0.125 ml/kg), M-D REI (0.250 ml/kg), and H-D REI (0.375 ml/kg); each healthy kidney was injected with saline as negative control], and biosafety evaluations [animals were divided into the following 5 groups (n = 3): NC (0.250 ml/kg), high-dose EtOH (0.375 ml/kg), L-D REI (0.125 ml/kg), M-D REI (0.250 ml/kg), and H-D REI (0.375 ml/kg)]. Then, a prospective cohort study involving 6 patients with peripheral venous malformations (VMs) is performed to explore the clinical safety and effectiveness of REI. From Jun 1, 2023 to August 31, 2023, 6 patients [age: (33.3 ± 17.2) years] with lingual VMs received sclerotherapy of REI and 2-month follow-up. Adverse events and serious adverse events were evaluated, whereas the efficacy of REI was determined by both the traceability of the REI under DSA throughout the entire injection and the therapeutic effect 2 months after a single injection. Results The REI contains 81.4% ethanol (v/v) and 111.3 mg/ml iodine, which can be traced throughout the injection in the animals and patients. The REI also exerts a similar effect as EtOH on peripheral venous sclerosis, peripheral arterial embolization, and renal embolization. Furthermore, the REI can be metabolized at a similar rate compared to EtOH and Ultravist® and did not cause injury to the animals’ heart, liver, spleen, lungs, kidneys and brain. No REI-related adverse effects have occurred during sclerotherapy of VMs, and 4/6 patients (66.7%) have achieved complete response at follow-up. Conclusion In conclusion, REI is safe, exerts therapeutic effects, and compensates for the radiolucency of EtOH in treating VMs. Trial registration The clinical trial was registered as No. ChiCTR2300071751 on May 24 2023.

Land surface emissivity (LSE) is a crucial variable in thermal infrared (TIR) remote sensing, providing unique information about the land surface across different channels. It is essential for applications such as surface energy budget estimation, resource exploration, and land cover change monitoring. However, current methods for retrieving LSE have certain limitations in terms of applicability or accuracy levels. Furthermore, the relative importance of various parameters in LSE retrieval studies remains unclear. To address these challenges, a practical and transferrable method has been proposed to retrieve LSE of different TIR channels using machine-learning technique. The proposed method uses visible and near-infrared (VNIR) as well as short-wave infrared (SWIR) data at the pixel scale to analyze key parameters for LSE retrieval and to estimate LSE for channels centered around 8.6 μm, 11.0 μm and 12.0 μm. Importance analysis identified crucial variables for LSE retrieval, including reflectivity in channels of SWIR3 (∼2.13 μm), RED (∼0.66 μm) and BLUE (∼0.47 μm), as well as the Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), Normalized Difference Built-up Index (NDBI) and the view zenith angle (VZ). Compared to the data used in existing methods, the core variables offer a more comprehensive representation of surface information, potentially enhancing both the accuracy and usability of the proposed method. Using these core variables, LSE was retrieved across eleven study areas through a machine learning method. Cross-validation with MODIS products showed that the Root Mean Square Error (RMSE) of the estimated LSE is 0.02 for the channel around 8.6 μm, and 0.01 for the channels around 11.0 μm and 12.0 μm, respectively. Direct-validation with in-situ measurements also demonstrated impressive retrieval accuracies in sandy areas. Furthermore, the model trained using 2019 data exhibited high retrieval accuracy when applied to data from 2017, highlighting its transferability across different time periods. Additionally, the proposed method produced promising results for LSE estimation using Landsat 8 imageries, indicating its potential for generating emissivity products from satellites with high spatial resolution but limited TIR channels.

Insufficient flexibility is a major barrier to the development of new power systems. Leveraging the resource allocation function of the electricity market is a promising way to enhance the flexibility of power systems and promote the consumption of renewables. The reasonable allocation of ancillary service costs plays a pivotal role in this function. Towards the target of “who causes, who shares,” various research related to cost allocation has been conducted. However, there is a lack of quantitative analysis of the impact of different cost allocation mechanisms on the market participants’ revenues. Whether various cost allocation mechanisms can alleviate the insufficient flexibility problem of power systems needs to be validated. With this in mind, taking operating reserve ancillary services as an example, a long-term market operation simulation model with energy-reserve joint clearing is established in this paper based on the time series production simulation. According to this, the revenues of market participants under different reserve cost allocation mechanisms are quantified. Besides, a self-dispatch model for the energy storage (ES) equipped by renewables is established, based on which the impact of ES on the revenues of renewables under different cost allocation mechanisms is analyzed. Case studies based on practical data from a provincial power grid in China demonstrate that with the well-designed reserve cost allocation mechanism, the revenues of flexible resources can be ensured. Meanwhile, renewables are incentivized to reduce their fluctuations and uncertainties by equipping the ES. Hence, the insufficient flexibility problem of power systems can be alleviated from both supply and requirements perspectives.

Abstract Background Postoperative pneumonia (POP) is the most prevalent of all nosocomial infections in patients who underwent cardiac surgery. The aim of this study was to identify independent risk factors for pneumonia after cardiac surgery, from which we constructed a nomogram for prediction. Methods The clinical data of patients admitted to the Department of Cardiothoracic Surgery of Nanjing Drum Tower Hospital from October 2020 to September 2021 who underwent cardiac surgery were retrospectively analyzed, and the patients were divided into two groups according to whether they had POP: POP group (n=105) and non-POP group (n=1083). Preoperative, intraoperative, and postoperative indicators were collected and analyzed. Logistic regression was used to identify independent risk factors for POP in patients who underwent cardiac surgery. We constructed a nomogram based on these independent risk factors. Model discrimination was assessed via area under the receiver operating characteristic curve (AUC), and calibration was assessed via calibration plot. Results A total of 105 events occurred in the 1188 cases. Age (>55 years) (OR: 1.83, P=0.0225), preoperative malnutrition (OR: 3.71, P 135 min (OR: 2.80, P 20 hours (OR: 3.11, P

Abstract CALF-20 was recently identified as a benchmark sorbent for CO2 capture at the industrial scale, however comprehensive atomistic insight into its mechanical/thermal properties under working conditions is still lacking. In this study, we developed a general-purpose machine-learned potential (MLP) for the CALF-20 MOF framework that predicts the thermodynamic and mechanical properties of the structure at finite temperatures within first-principles accuracy. Interestingly, CALF-20 was demonstrated to exhibit both negative area compression and negative thermal expansion. Most strikingly, upon application of the tensile strain along the [001] direction, CALF-20 was shown to display a distinct two-step elastic deformation behaviour, unlike typical MOFs that undergo plastic deformation after elasticity. Furthermore, this MOF was shown to exhibit a fracture strain of up to 27% along the [001] direction at room temperature comparable to that of MOF glasses. These abnormal thermal and mechanical properties make CALF-20 as attractive material for flexible and stretchable electronics and sensors.

Abstract Background Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation. Methods A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023. Of these patients, 124 exhibited poor outcomes. In order to investigate the optimal cut-off values for poor outcomes, logistic and receiver operating characteristic analyses were performed on the following parameters on the first postoperative day: procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), and systemic immune-inflammation index (SII). These cut-off points were used to separate the patients into hyper-inflammatory (n = 52) and control (n = 353) groups. Finally, the logistic were used to find the risk factors of hyper-inflammatory. Results PCT, CRP, IL-6, and SII were independent risk factors of poor outcomes in the multivariate logistic model. Cut-off points of these biomarkers were 2.18 ng/ml, 49.76 mg/L, 301.88 pg/ml, 2509.96 × 109/L respectively. These points were used to define postoperative hyper-inflammation (OR 2.97, 95% CI 1.35–6.53, P 180 min, and deep hypothermia circulatory arrest (DHCA) > 40 min were the independent risk factors for hyper-inflammation. Conclusions PCT > 2.18, CRP > 49.76, IL-6 > 301.88, and SII 180 min and DHCA > 40 min were separate risk factors for postoperative hyper-inflammation.

ABSTRACTSoil moisture plays a crucial role in understanding the hydrological cycle and the ecological environment. This research presents an improved change detection method that leverages time series data from Sentinel-1 radar and Sentinel-2 optical sensors (2019–2021) to estimate surface soil moisture. The response of backscatter to soil moisture in bare soil was expressed in a logarithmic form, and the influence function of the normalized difference vegetation index (NDVI) on the backscatter difference was established for various vegetation-covered surfaces. Therefore, the impact of vegetation on backscatter is effectively mitigated, and the resulting change in backscatter relative to bare soil conditions can be obtained. An empirical function is subsequently formulated to ascertain the reference values of soil moisture in each pixel. The retrieval of soil moisture is demonstrated in the Wudaoliang permafrost region of the Qinghai-Tibet Plateau and validated against ground measurements. The retrieval results of the improved change detection method exhibit correlation coefficients ranging from 0.672 to 0.941, with root mean squared errors (RMSE) ranging from 0.031 [Formula: see text] to 0.073 [Formula: see text]. Compared to the Soil Moisture Active Passive (SMAP) 9-km product, our new method demonstrates higher correlation (0.898 vs. 0.867) and lower RMSE (0.037 [Formula: see text] vs. 0.044[Formula: see text]). The soil moisture retrieved from Sentinel shows a strong correlation with the SMAP 9-km soil moisture in the time series, thereby providing a better representation of the region’s soil moisture heterogeneity. Our method demonstrates the feasibility of combining Sentinel-1 and 2 for high-resolution (100 m) soil moisture mapping in permafrost regions.

Abstract Herein, a robust microporous aluminum tetracarboxylate framework, MIL‐120(Al)‐AP, (MIL, AP: Institute Lavoisier and Ambient Pressure synthesis, respectively) is reported, which exhibits high CO2 uptake (1.9 mmol g−1 at 0.1 bar, 298 K). In situ Synchrotron X‐ray diffraction measurements together with Monte Carlo simulations reveal that this structure offers a favorable CO2 capture configuration with the pores being decorated with a high density of µ2‐OH groups and accessible aromatic rings. Meanwhile, based on calculations and experimental evidence, moderate host‐guest interactions Qst (CO2) value of MIL‐120(Al)‐AP (−40 kJ mol−1) is deduced, suggesting a relatively low energy penalty for full regeneration. Moreover, an environmentally friendly ambient pressure green route, relying on inexpensive raw materials, is developed to prepare MIL‐120(Al)‐AP at the kilogram scale with a high yield while the Metal‐ Organic Framework (MOF) is further shaped with inorganic binders as millimeter‐sized mechanically stable beads. First evidences of its efficient CO2/N2 separation ability are validated by breakthrough experiments while operando IR experiments indicate a kinetically favorable CO2 adsorption over water. Finally, a techno‐economic analysis gives an estimated production cost of ≈ 13 $ kg−1, significantly lower than for other benchmark MOFs. These advancements make MIL‐120(Al)‐AP an excellent candidate as an adsorbent for industrial‐scale CO2 capture processes.

Abstract Background The increasing prevalence of the Galvanized and dry battery industries has led to a rise in zinc proportions in landfills, posing environmental risks. This study explores the potential of bentonite, renowned for its metal adsorption capability, as a landfill barrier material. Methods Adsorption characteristics of Zn(II) in natural bentonite and Shanghai clay were investigated. Various factors affecting Zn(II) adsorption, including pH, Na ion strength, contact time, initial Zn(II) concentration, and adsorption temperature, were analyzed through batch-type adsorption tests. Results The change in pH and Na strength demonstrates no significant impact on the adsorption of Zn(II) onto bentonite, highlighting the strong selectivity of bentonite for Zn(II). Conversely, the equilibrium adsorption capacity of Zn(II) onto clay increases with rising pH or decreasing ion strength. The Zn(II) adsorption onto bentonite is well-described by the pseudo-second-order, intra-particle diffusion, and Elovih models, each achieving an R2 value exceeding 0.9. While both physical and chemical adsorption coexist in Zn(II) adsorption onto bentonite or clay, the primary determinant of the adsorption rate is chemical adsorption. The adsorption onto bentonite is spontaneous, whereas onto clay it is not. The mechanism involves van der Waals forces, ion exchange, and chemical actions such as inner-sphere complexation for Zn(II) adsorption onto both bentonite and clay.