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DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

We present anl omnidirectional 3D autostereoscopic aerial display with continuous parallax. Integral photography (IP) combined with polyhedron-shaped aerial imaging plates (AIPs) is utilized to achieve an extended view angle of 3D aerial images. With optical theoretical analysis and an aerial in situ rotation design, a 3D aerial display with an enlarged viewing angle is realized. In particular, the proposed 3D aerial display can realize any assigned angle within 360 deg. We also optimize the aerial display with artifact image removal and floating image brightness analysis. Experiments are performed to prove the 3D aerial display with full-motion parallax, continuous viewpoints, and multiplayer interaction. The proposed system is an attractive prospect of non-contact interaction and multi-person collaboration.

The GAP model was widely used as a simple risk "screening" method for patients with idiopathic pulmonary fibrosis (IPF).We sought to validate the GAP model in Chinese patients with IPF to evaluate whether it can accurately predict the risk for mortality.A total of 212 patients with IPF diagnosed at China-Japan Friendship Hospital from 2015 to 2019 were enrolled. The latest follow-up ended in September 2022. Cumulative mortality of each GAP stage was calculated and compared based on Fine-Gray models for survival, and lung transplantation was treated as a competing risk. The performance of the model was evaluated in terms of both discrimination and calibration.The cumulative mortality in patients with GAP stage III was significantly higher than that in those with GAP stage I or II (Gray's test p 0.0001). The Harrell c-index for the GAP calculator was 0.736 (95% CI: 0.667-0.864). The discrimination for the GAP staging system were similar with that for the GAP calculator. The GAP model overestimated the mortality rate at 1- and 2-year in patients classified as GAP stage I (6.90% vs. 1.77% for 1-year, 14.20% vs. 6.78% for 2-year).Our findings indicated that the GAP model overestimated the mortality rate in mild group.

Autonomous ultrasound imaging by robotic ultrasound scanning systems in complex soft uncertain clinical environments is important and challenging to assist in therapy. To cope with the complex environment faced by the ultrasound probe during the scanning process, we propose an autonomous robotic ultrasound (US) control method based on reinforcement learning (RL) model to build the relationship between the environment and the system. The proposed method requires only contact force as input information to achieve robot control of the posture and contact force of the probe without any a priori information about the target and the environment. First, an RL agent is proposed and trained by a policy gradient theorem-based RL model with the 6-degree-of-freedom (DOF) contact force of the US probe to learn the relationship between contact force and output force directly. Then, a force control strategy based on the admittance controller is proposed for synchronous force, orientation and position control by defining the desired contact force as the action space. The proposed method was evaluated via collected US images, contact force and scan trajectories by scanning an unknown soft phantom. The experimental results indicated that the proposed method differs from the free-hand scanned approach in the US images within 3 ± 0.4%. The analysis results of contact forces and trajectories indicated that our method could make stable scanning processes on a soft uncertain skin surface and obtained US images. We propose a concise and efficient force-guided US robot scanning control method for soft uncertain environment based on reinforcement learning. Experimental results validated our method's feasibility and validity for complex skin surface scanning, and the volunteer experiments indicated the potential application value in the complex clinical environment of robotic US imaging system especially with limited visual information.

For tumor resections near critical structures, accurate identification of tumor boundaries and maximum removal are the keys to improve surgical outcome and patient survival rate, especially in neurosurgery. In this paper, we propose an intelligent optical diagnosis and treatment system for tumor removal, with automated lesion localization and laser ablation. The proposed system contains a laser ablation module, an optical coherence tomography (OCT) unit, and a robotic arm along with a stereo camera. The robotic arm can move the OCT sample arm and the laser ablation front-end to the suspected lesion area. The corresponding diagnosis and treatment procedures include computer-aided lesion segmentation using OCT, automated ablation planning, and laser control. The ablation process is controlled by a deflectable mirror, and a non-common-path ablation planning algorithm based on the transformation from lesion positions to mirror deflection angles is presented. Phantom and animal experiments are carried out for system verification. The robot could reach the planned position with high precision, which is approximately 1.16 mm. Tissue classification with OCT images achieves 91.7% accuracy. The error of OCT-guided automated laser ablation is approximately 0.74 mm. Experiments on mouse brain tumors show that the proposed system is capable of clearing lesions efficiently and precisely. We also conducted an ex vivo porcine brain experiment to verify the whole process of the system. An intelligent optical diagnosis and treatment system is proposed for tumor removal. Experimental results show that the proposed system and method are promising for precise and intelligent theranostics. Compared to conventional cancer diagnosis and treatment, the proposed system allows for automated operations monitored in real-time, with higher precision and efficiency.

Gas-phase nitrous acid (HONO) is a major precursor of hydroxyl radicals that dominate atmospheric oxidizing capacity. Nevertheless, pathways of HONO formation remain to be explored. This study unveiled an important CO2-catalysis mechanism of HONO formation, using Born-Oppenheimer molecular dynamics simulations and free-energy samplings. In the mechanism, HCO3- formed from CO2 hydrolysis reacts with NO2 dimers to produce HONO at water surfaces, and simultaneously, itself reconverts back to CO2 via intermediates OC(O)ONO- and HOC(O)ONO. A flow system experiment was performed to confirm the new mechanism, which indicated that HONO concentrations with CO2 injections were increased by 29.4-68.5%. The new mechanism can be extended to other humid surfaces. Therefore, this study unveiled a previously overlooked vital role of CO2 that catalyzes formation of HONO and affects atmospheric oxidizing capacity.

Using multiple short-sale measures, we examine the predictive power of short sales for future stock returns in 38 countries from July 2006 to December 2014. We find that the days-to-cover ratio and the utilization ratio measures have the most robust predictive power for future stock returns in the global capital market. Our results display significant cross-country and cross-firm differences in the predictive power of alternative short-sale measures. The predictive power of shorts is stronger in countries with nonprohibitive short sale regulations and for stocks with relatively low liquidity, high shorting fees, and low price efficiency.

Detecting mental states in drivers offers an opportunity to reduce accidents by triggering alerts and signaling the need for rest or renewed focus. Here we used electroencephalography (EEG) to measure brain signals in young drivers operating a driving simulator to detect mental states and predict accidents. We measured reaction times to unexpected hazardous events and correlated them with EEG signals measured from the frontal, parietal, and temporal cortices as well as the central sulcus (corresponding to motor cortex). We found that EEG signals in the relative beta (power in beta (13–30 Hz) relative to total power of the EEG (0.5–30 Hz)), alpha/delta, alpha/theta, beta/delta, beta/theta frequency bands were higher for collisions than successful collision avoidance, and that the key decision-making period is the 2nd second before braking. Importantly, a decision tree classifier trained on these neural signals predicted collision avoidance outcomes. Then based on random forest model, we extracted three critical neural signals (beta/delta_frontal, relative beta_parietal and relative beta_central Sulcus) to classify collision avoidance outcomes. Our findings suggest measuring EEG during driving may provide useful signals for enhancing driver safety.

The micro-volume analysis and specific detection are both essential requirements in the field of chemical sensing and biological testing. Membrane prefiltration can be used to improve the selectivity and accuracy of detection. But for traditional porous membrane filtration, it is difficult to achieve the transmembrane transport of micro-volume liquid due to the influence of lateral diffusion on membrane surface. Herein, we studied the focused transmembrane transport of micro-volume liquid in the porous polyethersulfone membrane with asymmetric (Janus) surface wettability. The hydrophilic layer (polydopamine) and hydrophobic layer (fluoropolymer) were deposited with controllable thickness by dip-coating and roller-assisted liquid printing. The micro-volume liquid focusing effect was verified by experiments such as visual wetting circle and fluorescent tracer. The liquid focusing effect of as-prepared Janus membrane was integrated with glucose test strip in the application of micro-volume liquid biosensing. Compared with conventional porous membrane, detected signal amplitude and response time were improved 7.5× and 2.7×, respectively. In summary, this research studied the dynamics of liquid transport through Janus membrane and provides a new strategy for microfluidic detection applications through balancing detection volume, time and selectivity by the advantage of micro-volume liquid focusing effect.

The atmospheric chemistry of nitrous acid (HONO) has received extensive attention because of its significant contribution to hydroxyl (OH) radicals. Heterogeneous reaction of NO

Objective: This study aimed to investigate the relationship between systolic blood pressure (SBP) and alanine aminotransferase (ALT) in children and adolescents with short stature based on growth hormone peak (peak GH).Methods: In this study, 1151 patients diagnosed with short stature in the Shandong Growth and Developmental Disease Follow-up Study Cohort were included and anthropometric and biochemical parameters were measured. In accordance with the peak GH level in the growth hormone challenge test, all subjects were divided into three groups to determine the correlation between SBP and ALT in children and adolescents with schizophrenia: peak GH < 5 ng/mL, 5 ng/mL ≤ peak GH < 10 ng/mL and peak GH ≥ 10 ng/mL. Cross-sectional analysis of the correlation between SBP and ALT in children and adolescents with short stature.Result: The serum ALT levels in the GH peak Conclusion: The serum ALT levels in the GH peak < 5 ng/mL and 5 ng/mL ≤GH peak < 10 ng/mL groups were elevated compared with those in the GH peak ≥ 10 ng/mL group and a nonlinear relationship was found between SBP and ALT. When SBP reached the inflection point, the serum ALT levels were positively correlated with the increase in SBP. Future research is required to explore this relationship and mechanism.

Phytoplankton patterns have been observed widely in aquatic systems. Although pattern formation has been investigated based on many PDEs, discrete models on aquatic systems can provide more complex dynamics. A discrete toxic-phytoplankton–zooplankton model is studied in this paper, with the consideration of Allee effect and cross-diffusion. Focusing on Allee effect coefficient, flip and Neimark–Sacker bifurcation analyses are carried out. And focusing on cross-diffusion coefficient, Turing bifurcation analyses are carried out. Parameter conditions and bifurcation diagram of these bifurcations are obtained correspondingly. Numerical simulations are then performed which are consistent with results of theoretical analysis. Irregular patterns can be formed by flip bifurcation. Spirals can be formed by Neimark–Sacker bifurcation. Spots and stripes can be formed by Turing bifurcation. When Turing and flip, or Turing and Neimark–Sacker bifurcations both occur, special patterns can be obtained.

We aimed to test whether the prediction of presurgical metabolic syndrome for postsurgical survival outcomes of gastric cancer hinges upon cigarette smoking status.This study is a part of the ongoing Fujian prospective investigation of cancer (FIESTA) study. Patients with gastric cancer received radical resection of primary gastric cancer between January 2000 and December 2010, with the latest follow-up ended in December 2015. The 1:1 propensity score matching analysis was adopted to balance confounders between smokers and never-smokers. Effect-size estimates are expressed as hazard ratio (HR) with 95% confidence interval (CI). Model performance was evaluated using the Hosmer and Lemeshow test and 10-fold cross-validated area under the receiver operating characteristic curve (AUROC). Statistical analyses were completed with SAS software (v9.4).Total 2779 patients with gastric cancer were analyzed, including 2223 smokers and 556 never-smokers. Median follow-up time was 45.6 months. Cigarette smoking was not associated with postsurgical survival differences. Presurgical metabolic syndrome complication was significantly associated with increased gastric cancer-specific mortality in smokers (HR [95% CI]: 2.73 [1.53-4.89], p 0.001), but not in never-smokers. Relative excess risk due to interaction was estimated to be 2.43 (95% CI: 0.40-4.45). After constructing a risk assessment score, one unit increment was associated with 10% reduced risk of gastric cancer-specific mortality (HR [95% CI]: 0.90 [0.88-0.91], p 0.001), with 10-fold cross-validated AUROC being 0.82 (95% CI: 0.74-0.92).Our findings showed that the prediction of presurgical metabolic syndrome for gastric cancer-specific mortality was more evident in smokers. Practically, this study provides evidence base for future personalized prediction and helped risk-stratify gastric cancer patients who might experience serious postsurgical consequences.

Atmospheric nitrous acid (HONO) chemistry is of critical importance to air quality during polluted haze events. However, current air quality models generally underestimate the concentration of HONO, indicating that a fundamental understanding of haze pollution is lacking. Here, by combining field observations during haze events in Beijing and modeling results, we developed the new parameterization scheme for heterogeneous nitrogen dioxide (NO2) reaction on aerosol surfaces [with the synergistic effects of relative humidity, ammonia, and sulfur dioxide], which has not been considered in existing air quality models. Including NO2 heterogeneous reactions into modeling significantly improves the estimation accuracy of HONO and OH levels, with the contribution reaching up to 91% and 78% during pollution episodes. The OH derived by HONO can partly explain high concentrations of particulate matter. Together, our work provides a new approach to illustrate the formation of HONO, OH, and haze with the consideration of heterogeneous NO2→HONO chemistry.

Photochemical smog characterized by high concentrations of ozone (O3) is a serious air pollution issue in the North China Plain (NCP) region, especially in summer and autumn. For this study, measurements of O3, nitrogen oxides (NOx), volatile organic compounds (VOCs), carbon monoxide (CO), nitrous acid (HONO), and a number of key physical parameters were taken at a suburban site, Xianghe, in the NCP region during the summer of 2018 in order to better understand the photochemical processes leading to O3 formation and find an optimal way to control O3 pollution. Here, the radical chemistry and O3 photochemical budget based on measurement data from 1−23 July using a chemical box model is investigated. The daytime (0600−1800 LST) average production rate of the primary radicals referred to as ROx (OH + HO2 + RO2) is 3.9 ppbv h−1. HONO photolysis is the largest primary ROx source (41%). Reaction of NO2 + OH is the largest contributor to radical termination (41%), followed by reactions of RO2 + NO2 (26%). The average diurnal maximum O3 production and loss rates are 32.9 ppbv h−1 and 4.3 ppbv h−1, respectively. Sensitivity tests without the HONO constraint lead to decreases in daytime average primary ROx production by 55% and O3 photochemical production by 42%, highlighting the importance of accurate HONO measurements when quantifying the ROx budget and O3 photochemical production. Considering heterogeneous reactions of trace gases and radicals on aerosols, aerosol uptake of HO2 contributes 11% to ROx sink, and the daytime average O3 photochemical production decreases by 14%. The O3-NOx-VOCs sensitivity shows that the O3 production at Xianghe during the investigation period is mainly controlled by VOCs.

While recent years have witnessed the high potential of various machine learning based schemes in wind turbine fault prognosis (WTFP), none of them effectively tackle the challenging yet practical issue of severe operational data loss during WTFP. To address this issue, this paper develops an intelligent time series (TS) data analytics approach for missing data-tolerant WTFP. Instead of struggling to impute missing data, a powerful TS subsequence nearest neighbor (SNN) profiling technique is introduced to directly characterize TS data with missing values and transform them into discerning SNN profiles. Taking such profiles as inputs, the long short-term memory based recurrent network is further leveraged to perform in-depth faulty feature learning from temporal evolution trends. This eventually results in a discriminative multi-fault classification model, which can implement reliable online WTFP in severe missing data contexts. Experimental test results with field data collected from an actual wind turbine demonstrate the efficacy of the proposed approach.

PurposeThe objective of this study is to estimate the gender wage gap in Vietnam and its rural and urban areas, especially with the presence of foreign firms.Design/methodology/approachThe authors use cross-sectional data from three rounds of the Vietnam Household Living Standards Survey (VHLSS 2008, 2012, and 2016) to investigate this issue. The unconditional quantile regression and Oaxaca–Blinder (OB) decomposition are used in this article.FindingsThe article finds the gender wage gap favouring men, especially in higher quantiles of the wage distribution. The gap in urban Vietnam was higher than in rural areas. The OB decomposition indicates that gender wage gap is mainly driven by gender discrimination. The differences in return to participation in foreign companies only contributed significantly and positively to such a gap in some models. It suggests that the gap in those models is affected by gender discrimination in employment opportunities in foreign companies. Regarding the endowment effect, some models provide the significantly negative impacts of foreign firms on gender wage inequality.Originality/valueThe study suggests that policies to reduce the gender wage gap should pay more attention to foreign firms, especially at higher wage classes.

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a broadly expressed lncRNA involved in many aspects of cellular processes. To further delineate the underlying molecular mechanism, we employed a high-throughput strategy to characterize the interacting proteins of MALAT1 by combining RNA pull-down, quantitative proteomics, bioinformatics, and experimental validation. Our approach identified 127 potential MALAT1-interacting proteins and established a highly connected MALAT1 interactome network consisting of 788 connections. Gene ontology annotation and network analysis showed that MALAT1 was highly involved in five biological processes: RNA processing; gene transcription; ribosomal proteins; protein degradation; and metabolism regulation. The interaction between MALAT1 and depleted in breast cancer 1 (DBC1) was validated using RNA pull-down and RNA immunoprecipitation. Further mechanistic studies reveal that MALAT1 binding competes with the interaction between sirtuin1 (SIRT1) and DBC1, which then releases SIRT1 and enhances its deacetylation activity. Consequently, the deacetylation of p53 reduces the transcription of a spectrum of its downstream target genes, promotes cell proliferation and inhibits cell apoptosis. Our results uncover a novel mechanism by which MALAT1 regulates the activity of p53 through the lncRNA-protein interaction.

As an important phase-change material, GeTe has many high-pressure phases as well, but its phase transitions under pressure are still lack of clarity. It is challenging to identify high-pressure GeTe crystal structures owing to the phase coexistence in a wide pressure range and the reversibility of phase transitions. Hence, first-principles calculations are required to provide further information in addition to limited experimental characterizations. In this work, a new orthorhombic Cmca GeTe high-pressure phase has been predicted via the CALYPSO method as the most energetically favorable phase in the pressure range between ∼30 and ∼38.5 GPa, which would update the GeTe high-pressure phase transition sequence. The crystal structure of the Cmca phase is composed of alternate stacking puckered layers of Ge six-membered rings and Te four-membered rings along the b direction. The high density of states near the Fermi level and delocalization of electrons from the two-dimensional electron localization function indicate a strong metallic property of the Cmca phase. Electron–phonon coupling calculations indicate that the Cmca phase is superconductive below ∼4.2 K at 35 GPa. The simulated x-ray diffraction pattern of the Cmca phase implies that this phase might coexist with the Pnma-boat phase under high pressure. These results offer further understanding on the high-pressure structural evolution and physical properties in GeTe and other IV–VI semiconductors.

Chlorine dioxide (ClO2), an alternative disinfectant to chlorine, has been widely applied in water and wastewater disinfection. This paper aims at presenting an overview of the inactivation kinetics and mechanisms of ClO2 with viruses. The inactivation efficiencies vary greatly among different virus species. The inactivation rates for different serotypes within a family of viruses can differ by over 284%. Generally, to achieve a 4-log removal, the exposure doses, also being referred to as Ct values (mutiplying the concentration of ClO2 and contact time) vary in the range of 0.06–10 mg L−1 min. Inactivation kinetics of viruses show two phases: an initial rapid inactivation phase followed by a tailing phase. Inactivation rates of viruses increase as pH or temperature increases, but show different trends with increasing concentrations of dissolved organic matter (DOM). Both damages in viral proteins and in the 5′ noncoding region within the genome contribute to virus inactivation upon ClO2 disinfection. Supplementary Information The online version contains supplementary material available at 10.1007/s00128-021-03137-3.

Selective, hard to realize growth retardation of the π-stacking direction over the edge-packing direction has been achieved in perylene microcrystals using an aryl amphiphile. The perylene microcrystals grow predominantly along the edge-packing direction resulting in novel and hitherto unknown perylene square rods. The rods show exciton-polariton waveguiding along the rod axis even though it corresponds to pure edge-packing of the molecules, which is unprecedented in organic microcrystals.

Osteoporosis (OP) is a major systemic bone disease leading to an imbalance in bone homeostasis which remains a challenge in the current treatment of bone defects. Our previous studies on strontium (Sr) doping apparently stimulated osteogenesis of bioceramics, which suggested a promising strategy for the treatment of bone defects. However, the potential effects and the underlying mechanisms of Sr-doping on osteoporotic bone defects still remain unclear. Autophagy is a conventional self-degradation process of cells involved in bone homeostasis and regeneration under physiological and pathological conditions. Therefore, it is essential to design appropriate biomaterials and investigate the associated osteogenic mechanisms via autophagy. Based on this hypothesis, Sr-doped 45S5 bioglass (Sr/45S5) was fabricated, and ovariectomy bone marrow-derived mesenchymal stem cells (OVX-BMSCs) were applied as the in vitro cell culture model. First, the optimal Sr-doping concentration of 10 mol% was screened by cell proliferation, ALP staining, alizarin red S staining and the real-time PCR assay. Then, the results of western blot (WB) analysis showed that Sr-induced osteogenic differentiation of OVX-BMSCs was associated with time-dependent modulation of autophagy and related to the AKT/mTOR signaling pathway. Meanwhile, the autophagy in Sr-induced osteogenic differentiation of OVX-BMSCs was detected by WB, immunofluorescence staining and transmission electron microscopy. Furthermore, the effect of osteogenic differentiation of OVX-BMSCs has been significantly inhibited by the administration of autophagy inhibitors and the AKT/mTOR pathway inhibitors, respectively, in the early and late periods of osteogenic differentiation. Finally, the results of the model of femoral condyle defects in OVX-rats indicated that Sr10/45S5 granules remarkably enhanced bone regeneration which provided the evidences in vivo. Our research indicates that Sr-doping provides a promising strategy to promote osteogenic differentiation of OVX-BMSCs and bone regeneration in osteoporotic bone defects via early improvement of autophagy and late activation of the Akt/mTOR signaling pathway.

Enhancing the fluorescence of perovskite nanocrystals (PNCs) will not only boost the development of perovskite light-emitting devices (LEDs), but also broaden their applications in various photoelectronic areas. However, an effective approach to flexibly enhance different emission colors with high enhancement factors is still desired. In this work, SiO2 photonic crystals (PCs) are designed to couple with the radiative emission of PNCs. Blue, green, and red fluorescent PNCs emitting at 460, 517 and 620 nm are coated onto PCs with SiO2 particle sizes of 200, 230, and 274 nm, respectively. Fluorescence enhancement factors of 22, 12, and 19 are acquired when the excitation power is 0.078 W. Moreover, the enhancement factor noticeably increases with the excitation power. The enhancement factor for blue PNCs is over 250 with an excitation power of 0.09 W. The enhanced fluorescence of PNCs will facilitate the fluorescence signal acquisition with low noise, which is favorable for optical sensing. As a proof of concept, we demonstrate that the luminescence temperature sensing capability of the PNCs on SiO2 PCs is significantly boosted compared to that of the PNCs on glass.

Chlorine radicals, including Cl• and Cl2•-, can be produced in sunlight waters (rivers, oceans, and lakes) or water treatment processes (e.g., electrochemical and advanced oxidation processes). Dissolved organic matter (DOM) is a major reactant with, or a scavenger of, Cl• and Cl2•- in water, but limited quantitative information exists regarding the influence of DOM structure on its reactivity with Cl• and Cl2•-. This study aimed at quantifying the reaction rates and the formation of chlorinated organic byproducts produced from Cl• and Cl2•- reactions with DOM. Laser flash photolysis experiments were conducted to quantify the second-order reaction rate constants of 19 DOM isolates with Cl• (kDOM-Cl•) and Cl2•- (kDOM-Cl2•-), and compare those with the hydroxyl radical rate constants (kDOM-•OH). The values for kDOM-Cl• ((3.71 ± 0.34) × 108 to (1.52 ± 1.56) × 109 MC-1 s-1) were orders of magnitude greater than the kDOM-Cl2•- values ((4.60 ± 0.90) × 106 to (3.57 ± 0.53) × 107 MC-1 s-1). kDOM-Cl• negatively correlated with the weight-averaged molecular weight (MW) due to the diffusion-controlled reactions. DOM with high aromaticity and total antioxidant capacity tended to react faster with Cl2•-. During the same experiments, we also monitored the formation of chlorinated byproducts through the evolution of total organic chlorine (TOCl) as a function of chlorine radical oxidant exposure (CT value). Maximum TOCl occurred at a CT of 4-8 × 10-12 M·s for Cl• and 1.1-2.2 × 10-10 M·s for Cl2•-. These results signify the importance of DOM in scavenging chlorine radicals and the potential risks of producing chlorinated byproducts of unknown toxicity.

Objective: Two-dimensional fluoroscopy is the standard guidance imaging method for closed endovascular intervention. However, two-dimensional fluoroscopy lacks depth perception for the intervention catheter and causes radiation exposure for both surgeons and patients. In this paper, we extend our previous study and develop the improved three-dimensional (3D) catheter shape estimation using ultrasound imaging. In addition, we perform further quantitative evaluations of endovascular navigation. Method: First, the catheter tracking accuracy in ultrasound images is improved by adjusting the state vector and adding direction information. Then, the 3D catheter points from the catheter tracking are further optimized based on the 3D catheter shape optimization with a high-quality sample set. Finally, the estimated 3D catheter shapes from ultrasound images are overlaid with preoperative 3D tissue structures for the intuitive endovascular navigation. Results: the tracking accuracy of the catheter increased by 24.39%, and the accuracy of the catheter shape optimization step also increased by approximately 17.34% compared with our previous study. Furthermore, the overall error of catheter shape estimation was further validated in the catheter intervention experiment of in vitro cardiovascular tissue and in a vivo swine, and the errors were 2.13 mm and 3.37 mm, respectively. Conclusion: Experimental results demonstrate that the improved catheter shape estimation using ultrasound imaging is accurate and appropriate for endovascular navigation. Significance: Improved navigation reduces the radiation risk because it decreases use of X-ray imaging. In addition, this navigation method can also provide accurate 3D catheter shape information for endovascular surgery.

The triplet states of dissolved organic matter (

Dissolved organic matter (DOM), ubiquitous in natural waters, is known to inhibit the degradation of micropollutants in the advanced oxidation processes such as the UV/peroxydisulfate process. However, the quantitative understanding of the inhibitory pathways is missing. In this study, guanosine, aniline and catechol belonging to amines, purines and phenols were first investigated due to their resistance to UV irradiation at 254 nm and similar reactivity with SO

Chlorine, chlorine dioxide, and ozone are widely used as disinfectants in drinking water treatments. However, the combined use of different disinfectants can result in the formation of various organic and inorganic disinfection byproducts (DBPs). The toxic interactions, including synergism, addition, and antagonism, among the complex DBPs are still unclear. In this study, we established and verified a real-time cell analysis (RTCA) method for cytotoxicity measurement on Chinese hamster ovary (CHO) cell. Using this convenient and accurate method, we assessed the cytotoxicity of a series of binary combinations consisting of one of the 3 inorganic DBPs (chlorite, chlorate, and bromate) and one of the 32 regulated and emerging organic DBPs. The combination index (CI) of each combination was calculated and evaluated by isobolographic analysis to reflect the toxic interactions. The results confirmed the synergistic effect on cytotoxicity in the binary combinations consisting of chlorite and one of the 5 organic DBPs (2 iodinated DBPs (I-DBPs) and 3 brominated DBPs (Br-DBPs)), chlorate and one of the 4 organic DBPs (3 aromatic DBPs and dibromoacetonitrile), and bromate and one of the 3 organic DBPs (2 I-DBPs and dibromoacetic acid). The possible synergism mechanism of organic DBPs on the inorganic ones may be attributed to the influence of organic DBPs on cell membrane and cell antioxidant system. This study revealed the toxic interactions among organic and inorganic DBPs, and emphasized the latent adverse outcomes in the combined use of different disinfectants.

Oral and maxillofacial surgery demands high precision navigation to achieve optimal surgical outcomes. Augmented reality (AR) has been a promising solution for intuitive and accurate guidance, whereas existing systems have room for improvement.We propose a high quality and accurate in situ AR navigation system. Enhanced image quality is achieved by deploying eye tracking in lenticular-based autostereoscopic display. Viewpoint tracking and optical tracking are integrated to assure accurate in situ images.The proposed system can provide in situ AR images in real-time, with a viewing angle of 59.5° × 49.1°, 3D image resolution of 0.35 × 0.21 mm, and image accuracy of 0.99 ± 0.70 mm. A maxillary drilling experiment obtains average position error of 1.12 ± 0.30 mm and localization time of 8.7 ± 3.9 s, significantly better than conventional 2D navigation system.The proposed system can display high-quality AR images and therefore reduce positioning error and operating time.

The results of ambient signals-based load modelling are more sensitive to phasor measurement unit (PMU) measurement errors due to the relatively smaller disturbance magnitudes of ambient signals. To analyse the impact of PMU measurement errors, the stochastic distributions and frequency spectra of PMU measurement errors are required. In this study, the measurement errors of Sifang CDS361 PMU are experimentally tested, and then their impacts on load modelling results are analysed. The following contributions have been made in this study. Firstly, the stochastic distributions and frequency spectra of PMU measurement errors are experimentally tested, from which it can be concluded that systematic errors occupy a larger proportion compared with accidental errors. Secondly, the impacts of PMU measurement errors on load modelling results are analysed. It can be concluded that accidental errors have more severe impacts on the accuracy of both dynamic and static load models. Besides, systematically errors also impact the accuracy of static load models. Thirdly, the function of low-pass filters in recovering measurement signals from PMU measurement errors and enhancing the accuracy of load modelling results are validated. It can be further concluded that load model parameters can be accurately identified with current PMU measurement accuracy.

Materials with specific wettability properties have aroused enormous interest and research for their broad application prospects in chemical reaction, medical diagnosis, biological analysis, etc. Here, inspired by the unique Janus wettability of lotus leaf and Bragg stacks of beetles, we present a free-standing film with Janus wettability and tunable structural color for water quality monitoring. This film is constructed by using a flexible polymer polyurethane (PU) to pack poly(

The demand for xylenes is projected to increase over the coming decades. The separation of xylene isomers, particularly p- and m-xylenes, is vital for the production of numerous polymers and materials. However, current state-of-the-art separation is based upon fractional crystallisation at 220 K which is highly energy intensive. Here, we report the discrimination of xylene isomers via refinement of the pore size in a series of porous metal–organic frameworks, MFM-300, at sub-angstrom precision leading to the optimal kinetic separation of all three xylene isomers at room temperature. The exceptional performance of MFM-300 for xylene separation is confirmed by dynamic ternary breakthrough experiments. In-depth structural and vibrational investigations using synchrotron X-ray diffraction and terahertz spectroscopy define the underlying host–guest interactions that give rise to the observed selectivity (p-xylene < o-xylene < m-xylene) and separation factors of 4.6–18 for p- and m-xylenes., Separation of xylene isomers is essential for the production of a wide range of materials, but current separation methods are energy intensive. Here the authors report separation of the three xylene isomers at room temperature, via refinement of the pore size in a series of porous MOFs at sub-angstrom precision.

Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle (V2V) links, and high signaling overhead of centralized resource allocation approaches become bottlenecks. In this article, we investigate a joint optimization problem of transmission mode selection and resource allocation for cellular V2X communications. In particular, the problem is formulated as a Markov decision process, and a deep reinforcement learning (DRL)-based decentralized algorithm is proposed to maximize the sum capacity of vehicle-to-infrastructure users while meeting the latency and reliability requirements of V2V pairs. Moreover, considering training limitation of local DRL models, a two-timescale federated DRL algorithm is developed to help obtain robust models. Wherein, the graph theory-based vehicle clustering algorithm is executed on a large timescale and in turn, the federated learning algorithm is conducted on a small timescale. The simulation results show that the proposed DRL-based algorithm outperforms other decentralized baselines, and validate the superiority of the two-timescale federated DRL algorithm for newly activated V2V pairs.

This paper investigates the impact of network structures on small-disturbance voltage stability of power systems in the long-term. A differential-algebraic model is established in terms of network topology characteristics and the aggregate nonlinear recovery load model. We define the weighted load connectivity (WLC) as an index to indicate the stability of network structures. Then robust stability assessment is used to eliminate the impact of uncertain recovery time of loads. The Monte Carlo method is used to study the relationship between WLC and small-disturbance voltage stability (SDVS) for a broad range of network topologies and parameters. We discover from the simulation results that the network with a larger value of WLC has a stronger ability to maintain SDVS. To further study the impact of renewable energy sources (RESs), we improve the system model by including an inverter-based distributed generator in parallel with each aggregated nonlinear dynamic load. The simulation results of the Hong Kong power grid show that the WLC can still indicate the stability of network structures effectively, and the systems with more stable network structures are less impacted by the penetration of RESs. The proposed WLC appears useful in providing guidance for power network planning and operation.

The vector tracking structure is receiving growing attention due to its better tracking performance than the traditional scalar tracking structure. For the scalar tracking structure, signal quality monitoring (SQM) methods can effectively detect spoofing attacks based on the influence of correlation peaks overlap on the coherent integration results. However, the methods are invalid when the overlap is inexistent. While for the vector tracking structure, the authors find that because of the combined tracking of all received signals, the coherent integration results are affected by spoofing attacks regardless of whether the overlap exists. It implies that SQM techniques have a wider application range for the vector tracking structure. To this end, an SQM-based spoofing detection method for the vector tracking structure is proposed in this study. Analysis and simulation results demonstrate that the proposed method is useful even in the spoofing scenarios where the correlation peaks do not overlap. And it can detect spoofing attacks on both pseudo-code and carrier Doppler by using the existing observations in the tracking process, which is highly practical for the vector tracking structure.

Rationale: High-intensity focused ultrasound (HIFU) therapy represents a noninvasive surgical approach to treat uterine fibroids. The operation of HIFU therapy relies on the information provided by medical images. In current HIFU therapy, all operations such as positioning of the lesion in magnetic resonance (MR) and ultrasound (US) images are manually performed by specifically trained doctors. Manual processing is an important limitation of the efficiency of HIFU therapy. In this paper, we aim to provide an automatic and accurate image guidance system, intelligent diagnosis, and treatment strategy for HIFU therapy by combining multimodality information. Methods: In intelligent HIFU therapy, medical information and treatment strategy are automatically processed and generated by a real-time image guidance system. The system comprises a novel multistage deep convolutional neural network for preoperative diagnosis and a nonrigid US lesion tracking procedure for HIFU intraoperative image-assisted treatment. In the process of intelligent therapy, the treatment area is determined from the autogenerated lesion area. Based on the autodetected treatment area, the HIFU foci are distributed automatically according to the treatment strategy. Moreover, an image-based unexpected movement warning and other physiological monitoring are used during the intelligent treatment procedure for safety assurance. Results: In the experiment, we integrated the intelligent treatment system on a commercial HIFU treatment device, and eight clinical experiments were performed. In the clinical validation, eight randomly selected clinical cases were used to verify the feasibility of the system. The results of the quantitative experiment indicated that our intelligent system met the HIFU clinical tracking accuracy and speed requirements. Moreover, the results of simulated repeated experiments confirmed that the autodistributed HIFU focus reached the level of intermediate clinical doctors. Operations performed by junior- or middle-level operators with the assistance of the proposed system can reach the level of operation performed by senior doctors. Various experiments prove that our proposed intelligent HIFU therapy process is feasible for treating common uterine fibroid cases. Conclusion: We propose an intelligent HIFU therapy for uterine fibroid which integrates multiple medical information processing procedures. The experiment results demonstrated that the proposed procedures and methods can achieve monitored and automatic HIFU diagnosis and treatment. This research provides a possibility for intelligent and automatic noninvasive therapy for uterine fibroid.

Designing high-efficiency and low-cost bifunctional electrocatalysts for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is of great significance to produce hydrogen by water electrolysis. Herein, a hierarchical FeCo2S4@CoFe layered double hydroxide (LDH) core–shell structure catalyst was successfully fabricated via a hydrothermal–sulfuration–electrodeposition three-step method. The unique structure can provide more abundant catalytically active sites for the electrochemical reaction. The resulting FeCo2S4@CoFe LDH electrode only requires overpotentials of 115 and 247 mV to reach a current density of 10 mA cm−2 for the HER and OER in 1 M KOH electrolyte, respectively. The electrode also exhibits a low Tafel slope and excellent stability. Furthermore, the bifunctional catalyst for overall water splitting can exhibit a cell voltage of 1.6 V at 10 mA cm−2, along with outstanding durability for 24 h testing. This work provides a new strategy to design effective bifunctional catalysts for overall water splitting.

A detailed analysis of the electrical response of In0.3Ga0.7As surface quantum dots (SQDs) coupled to 5-layer buried quantum dots (BQDs) is carried out as a function of ethanol and acetone concentration while temperature-dependent photoluminescence (PL) spectra are also analyzed. The coupling structure is grown by solid source molecular beam epitaxy. Carrier transport from BQDs to SQDs is confirmed by the temperature-dependent PL spectra. The importance of the surface states for the sensing application is once more highlighted. The results show that not only the exposure to the target gas but also the illumination affect the electrical response of the coupling sample strongly. In the ethanol atmosphere and under the illumination, the sheet resistance of the coupling structure decays by 50% while it remains nearly constant for the reference structure with only the 5-layer BQDs but not the SQDs. The strong dependence of the electrical response on the gas concentration makes SQDs very suitable for the development of integrated micrometer-sized gas sensor devices.