Dual hydrophobic modifications toward anion exchange membranes with both high ion conductivity and excellent dimensional stability

Abstract(#br)Anion exchange membrane (AEMs) as a kind of important functional material are widely used in many fields including fuel cell, electrodialysis and water treatment. However, synthetic AEMs generally suffer a pernicious trade-off: high ion-conductive AEMs lack dimensional stability and vice versa. Herein we demonstrate a versatile strategy to prepare the AEMs with both high ion conductivity and excellent dimensional stability ( i.e. , low swelling ratio) via hydrophobic crosslinking and introducing hydrophobic chains. The hydrophobic length of crosslinkers has great influence on construction of highly efficient ion channels in the AEMs. Amazingly, the hydrophilic poly (phenylene oxide) (PPO) AEM crosslinked by 1,8-diaminooctane has the highest hydroxide conductivity that is further improved to 157.2 mS cm −1 (10% increases) with a low swelling ratio of 12.9% at 80 °C by introducing hydrophobic PPO backbone. This AEM not only overcomes the trade-off between the ion conductivity and the dimensional stability of crosslinked AEMs, but also breaks the upper bound between the ion conductivity and the water uptake. The newly developed strategy of hydrophobic dual-modifications promises to be an effective approach to develop the high-performance AEMs

Insight-HXMT observations of Swift J0243.6+6124 during its 2017-2018 outburst

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\it the Hard X-ray Modulation Telescope} ({\it Insight-\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to $\rm 150~keV$. In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with $B\rm \sim 10^{13}~G$, $D\rm \sim 6~kpc$ and peak luminosity of $\rm >10^{39}~erg~s^{-1}$ which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.Comment: publishe

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443

Transport mechanism of desorbed gas in coalbed methane reservoirs

The gas-liquid two-phase flow and mass transfer principle shows that the diffusion caused by concentration difference only happens in a single-phase fluid; gas-liquid two-phase diffluent solution happens in the way of dissolution; and gas-liquid two-phase insoluble or semi- soluble solution flows under differential pressure driving. These facts demonstrate that the transport of desorbed gas through matrix pores is the flow, and it doesn't conform to Fick law. The dissolution, diffusion, nucleation and bubble processes of desorbed gas through depressurization are studied, and the nonlinear flow model of free gas from matrix pores to the cleat and fracture system is established based on force analyses of the gas bubble and the gas column. Research shows that a small amount of desorbed gas diffuses by dissolution; most of them becomes nucleation and bubble, and then flows to the coal cleat and fracture system under the pressure difference driving; considering the existence of the pressure difference between the matrix pores and cleats, the pressure in coal matrix will reduce more slowly, the investigated radius will be shorter, and the outflow lag phenomenon of desorbed gas will appear. The dynamic reserve should be calculated not by using cleat pressure but by the pressure in coal matrix. The mechanism of enhanced methane recovery by CO2 injection is not only replacement but displacement. Improved methane recovery can be obtained by optimizing the production pressure difference, it is not reasonable that the lower formation pressure gives higher methane recovery. Key words: coalbed methane, diffusion, desorption, percolation, developmen

Retracted: CD248 as a novel therapeutic target in pulmonary arterial hypertension

Abstract Pulmonary vascular remodeling is the most important pathological characteristic of pulmonary arterial hypertension (PAH). No effective treatment for PAH is currently available because the mechanism underlying vascular remodeling is not completely clear. CD248, also known as endosialin, is a transmembrane protein that is highly expressed in pericytes and fibroblasts. Here, we evaluated the role of CD248 in pulmonary vascular remodeling and the processes of PAH pathogenesis. Activation of CD248 in pulmonary artery smooth muscle cells (PASMCs) was found to be proportional to the severity of PAH. CD248 contributed to platelet‐derived growth factor‐BB (PDGF‐BB)‐induced PASMC proliferation and migration along with the shift to more synthetic phenotypes. In contrast, treatment with Cd248 siRNA or the anti‐CD248 therapeutic antibody (ontuxizumab) significantly inhibited the PDGF signaling pathway, obstructed NF‐κB p65‐mediated transcription of Nox4, and decreased reactive oxygen species production induced by PDGF‐BB in PAMSCs. In addition, knockdown of CD248 alleviated pulmonary vascular remodeling in rat PAH models. This study provides novel insights into the dysfunction of PASMCs leading to pulmonary vascular remodeling, and provides evidence for anti‐remodeling treatment for PAH via the immediate targeting of CD248

Highly Conductive Cellulose Strain Sensor with Excellent Negative Resistance Variation and Joule Heating Property

The rational design of a wearable strain sensor with heating property has attracted great interest. In this study, a flexible conductivity hierarchical cellulose strain sensor (MX@Ag@CY) with heating property was fabricated via in situ formation of silver nanoparticles (Ags) on cotton yarn (CY) and subsequent dip-coating with MXene (MX). Ags coupled with MX coating endowed the cotton yarn with a high conductivity, where the resistance of the optimized composite [email protected]@CY was about 22 Ω/cm. Compared with the previously reported strain sensors, the woven [email protected]@CY fabric strain sensor showed a distinctive negative resistance variation, wherein it showed an enhanced conductivity with the increased strain owing to its unique architecture. The woven [email protected]@CY fabric strain sensor exhibited a repeatable response and displayed long-term stability in the strain range of 0–55%. In addition, the strain sensor demonstrated great detectability on large-scale human movements when directly attached to the elbow, wrist, or knee. Furthermore, when [email protected]@CY served as a heater (at an applied DC voltage of 6 V), it presented high heating temperature (92.4 °C), homogeneous temperature distribution, low operation voltage (1–6 V), and excellent thermal stability even under strain

Sedimentary mercury and antimony revealed orbital-scale dynamics of the Kuroshio Current

As an integral part of the Earth's climate system, the Kuroshio Current (KC) plays a crucial role in shaping the regional oceanography and climate in the Northern Hemisphere. However, how the KC dynamics have varied over glacial-interglacial cycles is still under debate. The dynamic transfer and accumulation of submarine hydrothermal source materials by deep-reaching KC offer us a unique opportunity to examine the variations in dynamics of the KC. Here, we used novel proxies of sedimentary mercury (Hg) and antimony (Sb) in core MD01-2404 retrieved from the middle Okinawa Trough (OT) to reconstruct the evolution of the KC hydrodynamics over the last 92,000 years. We infer the enrichments of sedimentary Hg and Sb to signify hydrothermal input, which is delivered laterally to the study site by deep circulation in association with the KC, thus indicating the dynamics of KC. Overall, both the sedimentary Hg and Sb in core MD01-2404 indicate a persistent influence on the KC dynamics within the OT over the last glacial-interglacial cycles. Furthermore, our Hg and Sb proxies suggest a significantly weakened influence during the last deglaciation and last glacial period while a strengthened influence during the Holocene and late Marine Isotope Stage 5. Our studies imply that the orbital-scale dynamics of KC are controlled by tropical atmosphere-ocean interactions induced by sea surface temperature changes and regulated by the extratropical climate conditions

Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage

Abstract Background Spontaneous intracerebral hemorrhage (sICH) is associated with significant mortality and morbidity. Predicting the prognosis of patients with sICH remains an important issue, which significantly affects treatment decisions. Utilizing readily available clinical parameters to anticipate the unfavorable prognosis of sICH patients holds notable clinical significance. This study employs five machine learning algorithms to establish a practical platform for the prediction of short-term prognostic outcomes in individuals afflicted with sICH. Methods Within the framework of this retrospective analysis, the model underwent training utilizing data gleaned from 413 cases from the training center, with subsequent validation employing data from external validation center. Comprehensive clinical information, laboratory analysis results, and imaging features pertaining to sICH patients were harnessed as training features for machine learning. We developed and validated the model efficacy using all the selected features of the patients using five models: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), XGboost and LightGBM, respectively. The process of Recursive Feature Elimination (RFE) was executed for optimal feature screening. An internal five-fold cross-validation was employed to pinpoint the most suitable hyperparameters for the model, while an external five-fold cross-validation was implemented to discern the machine learning model demonstrating the superior average performance. Finally, the machine learning model with the best average performance is selected as our final model while using it for external validation. Evaluation of the machine learning model’s performance was comprehensively conducted through the utilization of the ROC curve, accuracy, and other relevant indicators. The SHAP diagram was utilized to elucidate the variable importance within the model, culminating in the amalgamation of the above metrics to discern the most succinct features and establish a practical prognostic prediction platform. Results A total of 413 patients with sICH patients were collected in the training center, of which 180 were patients with poor prognosis. A total of 74 patients with sICH were collected in the external validation center, of which 26 were patients with poor prognosis. Within the training set, the test set AUC values for SVM, LR, RF, XGBoost, and LightGBM models were recorded as 0.87, 0.896, 0.916, 0.885, and 0.912, respectively. The best average performance of the machine learning models in the training set was the RF model (average AUC: 0.906 ± 0.029, P < 0.01). The model still maintains a good performance in the external validation center, with an AUC of 0.817 (95% CI 0.705–0.928). Pertaining to feature importance for short-term prognostic attributes of sICH patients, the NIHSS score reigned supreme, succeeded by AST, Age, white blood cell, and hematoma volume, among others. In culmination, guided by the RF model’s variable importance weight and the model's ROC curve insights, the NIHSS score, AST, Age, white blood cell, and hematoma volume were integrated to forge a short-term prognostic prediction platform tailored for sICH patients. Conclusion We constructed a prediction model based on the results of the RF model incorporating five clinically accessible predictors with reliable predictive efficacy for the short-term prognosis of sICH patients. Meanwhile, the performance of the external validation set was also more stable, which can be used for accurate prediction of short-term prognosis of sICH patients