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The effect of colloidal nanoparticles on the phase changes of the amphiphilic AB linear diblock, A1A2B, and A2B heteroarm star copolymers confined between two polymer brush substrates was investigated by using a real-space self-consistent field theory. By changing the concentrations of nanoparticles and polymer brushes, the phase structure of the amphiphilic AB copolymer transforms from lamellar to core-shell hexagonal phase to cylinder phase. The pattern of A2B heteroarm star copolymer changes from core-shell hexagonal phases to lamellar phases and the layer decreases when increasing the density of the polymer brushes. The results showed that the phase behavior of the system is strongly influenced by the polymer brush architecture and the colloidal nanoparticle numbers. The colloidal nanoparticles and the soft confined surface of polymer brushes make amphiphilic AB copolymers easier to form ordered structures. The dispersion of the nanoparticles was also investigated in detail. The soft surfaces of polymer brushes and the conformation of the block copolymers work together to force the nanoparticles to disperse evenly. It will give helpful guidance for making some new functional materials by nano etching technology, nano photoresist, and nanoprinting. [ABSTRACT FROM AUTHOR]

Existing Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods are mostly suitable for simple systems with fewer factors, and lack effective integration of expert knowledge and experience from large-scale group populations, resulting in a potential compromise of the quality of the initial direct relation (IDR) matrix. To make DEMATEL better suited for the identification of critical factors in complex systems, this paper proposes a hierarchical DEMATEL method for large-scale group decision-making. Considering the limitations of expert knowledge and experience, a method based on expert consistency network for constructing the expert weight matrix is designed. The expert consistency network is constructed for different elements, and the weights of experts in different elements are determined using the clustering coefficient. Following the principles of the classic DEMATEL method, the steps for identifying key elements in complex systems using the large-scale group-hierarchical DEMATEL method are summarized. To objectively test the effectiveness and superiority of the decision algorithm, the robustness of the algorithm is analyzed in an interference environment. Finally, the superiority of the proposed method and algorithm is verified through a case study, which demonstrating that the proposed decision-making method is suitable for group decision-making in complex systems, with high algorithm stability and low algorithm deviation. [ABSTRACT FROM AUTHOR]

The core issue of learning-to-rank (LTR) for document retrieval lies in finding an optimal ranking policy to meet the search intent of the user. The majority of proposed LTR approaches treat the ranking as a static process, employing a fixed ranking policy to immediately assign scores to documents. By contrast, ranking is not a static but an interactive process where the user continues interacting with the document retrieval system through information exchange such as search intent (e.g., rating or clicking for the retrieved items). We model the interactive ranking process (IRP), and propose an Attention-Based Interactive LTR model (AIRank) to constitute an intent-aware flexible ranking policy to gratify the user’s need. To enhance the ranking quality, the inherent relations among documents are procured by the self-attention method to contribute to an enriched user intent representation. Furthermore, we mend the policy gradient learning method to train the AIRank in the IRP. Experiments demonstrate the effectiveness of AIRank compared to the state-of-the-art methods in terms of normalized discounted cumulative gain and expected reciprocal rank. [ABSTRACT FROM AUTHOR]

Leveraging global state information to enhance policy optimization is a common approach in multi-agent reinforcement learning (MARL). Even with the supplement of state information, the agents still suffer from insufficient exploration in the training stage. Moreover, training with batch-sampled examples from the replay buffer will induce the policy overfitting problem, i.e., multi-agent proximal policy optimization (MAPPO) may not perform as good as independent PPO (IPPO) even with additional information in the centralized critic. In this paper, we propose a novel noise-injection method to regularize the policies of agents and mitigate the overfitting issue. We analyze the cause of policy overfitting in actor–critic MARL, and design two specific patterns of noise injection applied to the advantage function with random Gaussian noise to stabilize the training and enhance the performance. The experimental results on the Matrix Game and StarCraft II show the higher training efficiency and superior performance of our method, and the ablation studies indicate our method will keep higher entropy of agents' policies during training, which leads to more exploration. [ABSTRACT FROM AUTHOR]

Xanthatin (XT) is a sesquiterpene lactone isolated from the Chinese herb Xanthium, which belongs to the Asteraceae family. In this study, we developed an inflammation model via stimulating macrophage cell line (RAW 264.7 cells) with lipopolysaccharide (LPS), which was applied to assess the anti-inflammatory effect and probable mechanisms of xanthatin. When compared with the only LPS-induced group, cells that were pretreated with xanthatin were found to decrease the amount of nitric oxide (NO), reactive oxygen species (ROS) and associated pro-inflammatory factors (TNF-α, IL-1β and IL-6), and downregulate the mRNA expression of iNOS, COX-2, TNF-α, IL-1β, and IL-6. Interestingly, phosphorylated levels of related proteins (STAT3, ERK1/2, SAPK/JNK, IκBα, p65) were notably increased only with the LPS-activated cells, while the expression of these could be reverted by pre-treatment with xanthatin in a dose-dependent way. Meanwhile, xanthatin was also found to block NF-κB p65 from translocating into the nucleus and activating inflammatory gene transcription. Collectively, these results demonstrated that xanthatin suppresses the inflammatory effects through downregulating the nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription (STATs) signaling pathways. Taken together, xanthatin possesses the potential to act as a good anti-inflammatory medication candidate. [ABSTRACT FROM AUTHOR]

Discovering drug–target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug–target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences. [ABSTRACT FROM AUTHOR]

Objectives. This study is aimed at exploring the relationship of the viral load of coronavirus disease 2019 (COVID-19) with lymphocyte count, neutrophil count, and C-reactive protein (CRP) and investigating the dynamic change of patients' viral load during the conversion from mild COVID-19 to severe COVID-19, so as to clarify the correlation between the viral load and progression of COVID-19. Methods. This paper included 38 COVID-19 patients admitted to the First Hospital of Jiaxing from January 28, 2020, to March 6, 2020, and they were clinically classified according to the Guidelines on the Novel Coronavirus-Infected Pneumonia Diagnosis and Treatment. According to the instructions of the Nucleic Acid Detection Kit for the 2019 novel coronavirus (SARS-CoV-2), respiratory tract specimens (throat swabs) were collected from patients for nucleic acid testing. Patients' lymphocyte count and neutrophil count were determined by blood routine examination, and CRP was measured by biochemical test. Results. The results of our study suggested that the cycle threshold (Ct) value of Nucleocapsid protein (N) gene examined by nucleic acid test was markedly positively correlated with lymphocyte count (p = 0.0445 , R 2 = 0.1203), but negatively correlated with neutrophil count (p = 0.0446 , R 2 = 0.1167) and CRP (p = 0.0393 , R 2 = 0.1261), which indicated that patients with a higher viral load tended to have lower lymphocyte count but higher neutrophil count and CRP. Additionally, we detected the dynamic change of Ct value in patients who developed into a severe case, finding that viral load of 3 patients increased before disease progression, whereas this phenomenon was not found in 2 patients with underlying diseases. Conclusion. The results of this study demonstrated that viral load of SARS-CoV-2 is significantly negatively correlated with lymphocyte count, but markedly positively correlated with neutrophil count and CRP. The rise of viral load is very likely to be the key factor leading to the overloading of the body's immune response and resulting in the disease progression into severe disease. [ABSTRACT FROM AUTHOR]

This paper examines factors of payment decision as well as the role each factor plays in casual configurations leading to high payment intention under systematic and heuristic information processing routes. Based on heuristic-systematic model (HSM), we propose a configurational analytic framework to investigate complex casual relationships between influencing factors and payment decision. In line with this approach, we use fuzzy-set qualitative comparative analysis (fsQCA) to analyze data crawled from Zhihu.com. The number of previous consultations is a necessary element in all five equivalent configurations which lead to high intention in payment decision. The heuristic processing route plays a core role while the systematic processing route plays a peripheral role in payment decision-making process. Research is limited in that moderating effect of professional fields has not been considered in the framework. Configurations in results can assist managers of knowledge communities and paid Q&A service providers in the management of information elements to motivate more payment decision. This paper is one of the few studies to apply HSM theory and fsQCA method with respect to the payment decision in paid Q&A. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future. • A new MDD discrimination method MFMC is proposed. • MFMC is tested on REST-meta-MDD including over 2400 subjects. • MFMC outperforms existing methods with significant improvements. • The good generalizability of MFMC is verified. • MFMC identifies 13 features related with 9 brain regions important for MDD. [ABSTRACT FROM AUTHOR]

Graph clustering has received significant attention in recent years due to the breakthrough of graph neural networks (GNNs). However, GNNs frequently assume strong data homophily, which is not true in many real-world applications. Furthermore, practical graphs are typically noisy and sparse, which inevitably degrades the clustering performance. To this end, we propose a novel Contrastive Graph Clustering (CGC) method with adaptive filter framework. We first design an adaptive filter that can automatically learn a suitable filter for different data, mining holistic information beyond low-frequency components and encoding topology structure information into features. Afterward, we learn a refined graph based on a graph-level contrastive mechanism, which further boosts graph discriminability. Extensive experiments show that the proposed CGC method achieves significant improvement over state-of-the-art methods on several benchmark datasets. In particular, our simple method, which does not employ neural networks, outperforms many deep learning approaches. • High-frequency information is considered for graph clustering. • Contrastive regularizer is applied to refine graph structure. • Homophilic and heterophilic graphs are evaluated. [ABSTRACT FROM AUTHOR]

Multiple drug resistance is the main reason for chemotherapeutic failure in lung cancer patients with complex molecular mechanisms. LncRNA-MALAT1 plays functional roles in the progression of carcinomas and development of drug resistance. We aimed to identify the role of MALAT1 in DDP-resistant non-small cell lung cancer as well as potential mechanisms. Human lung cancer cell line A549 and the DDP-resistant cell line A549/DDP were used. Cell transfection was performed to establish A549/MALAT1 and A549/DDP/shMALAT1 cells. The qRT-PCR analysis was performed to detect lncRNA-MALAT1 level. Cell viability, colony formation assay, apoptosis analysis, western blot analysis, immunohistochemistry, and animal study were carried out. MALAT1 was upregulated in DDP-resistant A549 cell line. MALAT1 decreased DDP sensitivity in vitro and in vivo by upregulating MRP1 and MDR1 via STAT3 activation. Overexpression of MALAT1 contributed to the DDP resistance and might confer a potently poor prognosis. [ABSTRACT FROM AUTHOR]

• Silencing TRIM66 hindered cell malignant phenotype of non-small cell lung cancer; • TRIM66 interacted with MMP9 in non-small cell lung cancer; • MMP9 activated TGF-β/SMAD pathway; • TRIM66/MMP9/TGF-β/SMAD axis promoted non-small cell lung cancer progression. To investigate regulatory function and underlying mechanism of TRIM66 in non-small cell lung cancer (NSCLC). TRIM66 and MMP9 expression in NSCLC cells and tissues was assayed via qRT-PCR and western blot. CCK-8, colony formation, Transwell and flow cytometry assays were conducted to measure cell functional alternations in NSCLC. Western blot was employed to measure expression as well as phosphorylation levels of epithelial-mesenchymal transition-(EMT) and TGF-β/SMAD pathways-related proteins. Co-immunoprecipitation (Co-IP) assay was done to probe interaction between TRIM66 and MMP9. Xenograft in vivo experiment and tumor metastasis model in nude mice were utilized to investigate effects of TRIM66 on tumor growth of NSCLC. TRIM66 and MMP9 were conspicuously highly expressed in NSCLC cells and tissues. High TRIM66 level was markedly correlated with metastasis. Silencing TRIM66 prominently repressed the proliferation, migration and invasion of transfected cells, while inducing cell apoptosis. Whereas forced expression of TRIM66 exerted the opposite effect. The aberrant expression of TRIM66 modulated EMT pathway. TRIM66 also regulated MMP9 expression, and the interaction between them was validated by Co-IP assay. Overexpression of MMP9 could activate TGF-β/SMAD pathway. Rescue experiments manifested that si-MMP9 or SB431542 could partially reverse phenotypes induced by TRIM66. In vivo experiments revealed that silencing TRIM66 could hamper NSCLC tumor growth and metastasis. TRIM66 and MMP9 were up-regulated in NSCLC. TRIM66 facilitated the malignant progression of NSCLC through modulating MMP9-mediated TGF-β/SMAD pathway. [ABSTRACT FROM AUTHOR]

Abstract: This paper considers the problem of computing the Bézier representation for a triangular sub-patch on a triangular Bézier surface. The triangular sub-patch is defined as a composition of the triangular surface and a domain surface that is also a triangular Bézier patch. Based on de Casteljau recursions and shifting operators, previous methods express the control points of the triangular sub-patch as linear combinations of the construction points that are constructed from the control points of the triangular Bézier surface. The construction points contain too many redundancies. This paper derives a simple explicit formula that computes the composite triangular sub-patch in terms of the blossoming points that correspond to distinct construction points and then an efficient algorithm is presented to calculate the control points of the sub-patch. [Copyright &y& Elsevier]

Objective: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).Methods: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.Results: A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718-0.735) and 0.721 (95% CI, 0.709-0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691-0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.Conclusion: We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions. [ABSTRACT FROM AUTHOR]

Highlights • Our study provides the first quantitative and qualitative overview of the events following submerged injection of gas into a thin quiescent liquid sheet with a thickness of a few millimeters. • For the experimentally available range, three different flow regimes are identified and, particularly, we build a phase diagram outlining these regimes in terms of the Weber number and Bond number. • We investigated the complete evolution of periodic bubbling-bursting behavior systematically. The bubbling characteristics, which show great differences with traditional bubbling in deep liquid, are depicted and analyzed. • Using dimensional arguments, we proposed a scaling law for the rupture radius of bubbles which brings out the effects of gravity and inertia. • Focusing on the subsequent liquid jet dynamics, we unravel experimentally the intricate roles of capillary wave velocities, cavity morphology, liquid thickness and gas momentum in bubble collapse. • Our results and conclusions herein provide a new method for the control of the bursting-bubble jet and an important supplement to the physical problem of submerged gas injection. Abstract Submerged injection of gas into a thin liquid sheet is frequently observed in industrial processes. Most studies on submerged gas injection, however, focus on the phenomena happened in deep liquid pool. Few studies have been devoted to a thin liquid layer with a thickness of a few millimeters. Here, we study submerged injection of gas into a thin liquid sheet, where we quantify the behaviors of bubbling/collapse and the resulting liquid jet with a high-speed video system. For the experimentally available range of liquid depths and gas velocities, three different flow regimes are identified and we build a phase diagram outlining these regimes in terms of the Weber number and Bond number. Particularly, the complete evolution of periodic bubbling-bursting behavior is investigated systematically. The bubbling characteristics, which show great differences with traditional bubbling in deep liquid, are depicted and analyzed. Using dimensional arguments, we propose a scaling law for the rupture radius of bubbles which brings out the effects of gravity and inertia. Focusing on the subsequent liquid jet dynamics, we unravel experimentally the intricate roles of capillary wave velocities, cavity morphology, liquid thickness and gas momentum in bubble collapse. With increase of the liquid sheet thickness, jets first become fat and small and then ends up thinner, detaching more and smaller droplets due to Rayleigh-Plateau instability. Our study firstly provides the quantitative overview of the events following submerged gas injection into thin quiescent liquid and provide guides for the control of the bursting-bubble jet. [ABSTRACT FROM AUTHOR]

This study presents an improved constitutive model for concrete under uniaxial cyclic loading which considers the fatigue stiffness degradation, fatigue strength degradation, and fatigue residual strain increment of concrete fatigue damage. According to the constitutive model, the dynamic response and cumulative damage of the tunnel cross structure under various train operation years were analyzed. The results show that the vibration in the middle of the main tunnel is most violent. With the increase of train operation period, the acceleration in the middle of the transverse passage floor, both sides of the wall corner and the vault increase significantly, and the maximum principal stress increases significantly only in both sides of the wall corner. The compressive damage is mainly distributed at both sides of the wall corner, while tensile damage is distributed in both sides of the inner wall corner. The accumulative damage of the cross structure exhibits a two-stage profile. The size and range of accumulative tensile damage of the connecting transverse passage are greater than those of accumulative compressive damage. [ABSTRACT FROM AUTHOR]

Discontinuous contact line pinning phenomenon appears when liquid wets discontinuous sharp features. It provides additional resistance to the gas-liquid interface and sometimes can be used as an effective approach for liquid control, such as avoiding liquid leakage by extraction holes in immersion lithography and other microfluidic devices. The discontinuous pinning effect by a hole row to the gas-liquid interface in a parallel gap was investigated in this study. We designed an experiment to investigate the behavior and the maximum resistance pressure of a hole row blocking the air-water interface in the gap. It was observed that the interface was partially pinned by the hole edges, while the unpinned parts was also stopped by the interface stretching. The pinning effect caused the interface distorted and produced additive Laplace pressure to resist the water pressure. Three failure types of the discontinuous pinning system were found, which were related to not only the hole edge pinning effect, but also the shape and position of the contact line. By analyzing the experimental results, analytical models based on the Laplace equation were built to formulate the pinning effects in the paper. The resistance pressure can be determined dependent on the developed analytical method. The experimental results agreed with the models in the failure types and maximum resistance pressure estimations. [ABSTRACT FROM AUTHOR]

Background: Peach (Prunus persica L. Batsch) is one of the most popular fruits worldwide. Although the reference genome of 'Lovell' peach has been released, the diversity of genome-level variations cannot be explored with one genome. To detect these variations, it is necessary to assemble more genomes. Results: We sequenced and de novo assembled the genome of 'Feichenghongli' (FCHL), a representative landrace with strict self-pollination, which maintained the homozygosity of the genome as much as possible. The chromosome-level genome of FCHL was 239.06 Mb in size with a contig N50 of 26.93 Mb and only 4 gaps at the scaffold level. The alignment of the FCHL genome with the reference 'Lovell' genome enabled the identification of 432535 SNPs, 101244 insertions and deletions, and 7299 structural variants. Gene family analysis showed that the expanded genes in FCHL were enriched in sesquiterpenoids and triterpenoid biosynthesis. RNA-seq analyses were carried out to investigate the two distinct traits of late florescence and narrow leaves. Two key genes, PpDAM4 and PpAGL31, were identified candidates for the control of flower bud dormancy, and an F-box gene, PpFBX92, was identified as a good candidate gene in the regulation of leaf size. Conclusions: The assembled high-quality genome could deepen our understanding of variations among diverse genomes and provide valuable information for identifying functional genes and improving the molecular breeding process. [ABSTRACT FROM AUTHOR]

Large‐area polymer light‐emitting diodes (PLEDs) manufactured by printing are required for flat‐panel lighting and displays. Nevertheless, it remains challenging to fabricate large‐area and stable deep‐blue PLEDs with narrowband emission due to the difficulties in precisely tuning film uniformity and obtaining single‐exciton emission. Herein, efficient and stable large‐area deep‐blue PLEDs with narrowband emission are prepared from encapsulated polydiarylfluorene. Encapsulated polydiarylfluorenes presented an efficient and stable deep‐blue emission (peak: 439 nm; full width at half maximum (FWHM): 39 nm) in the solid state due to their single‐chain emission behavior without inter‐backbone chain aggregation. Large‐area uniform blade‐coated films (16 cm2) are also fabricated with excellent smoothness and morphology. Benefitting from efficient emission and excellent printed capacity, the blade‐coated PLEDs with a device area of 9 mm2 realized uniform deep‐blue emission (FWHM: 38 nm; CIE: 0.153, 0.067), with a corresponding maximum external quantum efficiency and the brightness comparable to those of devices based on spin‐coated films. Finally, considering the essential role of deep‐blue LEDs, a preliminary patterned PLED array with a pixel size of 800 × 1000 µm2 and a monochrome display is fabricated, highlighting potential full‐color display applications. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory skin disorder accompanied by excessive keratinocyte proliferation. Erianin (Eri) is an ideal drug candidate for inhibiting proliferation and inducing apoptosis in the treatment of psoriasis. However, Eri's poor water solubility and low penetration activity across the skin hinder its application in local medicine. In this study, we developed a novel photo-responsive dendritic mesoporous silica nanoparticle-based carrier to deliver erianin, improved its bioavailability, and achieved sustained-release effects. Spiropyran (SP), 3-aminopropyltriethoxysilane (APTES), and perfluorodecyltriethoxysilane (PFDTES) were conjugated to the outer surface, which allowed Eri to be released in response to UV radiation. The physicochemical properties of photo-responsive dendritic mesoporous silica nanoparticles (Eri-DMSN@FSP) were characterized via multiple techniques, such as using a Fourier-transform infrared spectrometer, a high-resolution transmission electron microscope, and nuclear magnetic resonance (NMR) spectroscopy. The anti-proliferative properties and light-triggered release of erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles were assessed via the MTT assay and a drug release study in vitro. Erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles (UV) exhibit a significantly enhanced HaCat cell-inhibiting efficacy compared to other formulations, as demonstrated by their extremely low cell viability of 10.0% (concentration: 500 mg/mL), indicating their capability to release a drug that responds to UV radiation. The cellular uptake of photo-responsive dendritic mesoporous silica nanoparticles (DMSN@FSP) was observed via confocal laser scanning microscopy (CLSM). These experimental results show that Eri-DMSN@FSP could be effectively endocytosed into cells and respond to ultraviolet light to release Eri, achieving a more effective psoriasis treatment. Therefore, this drug delivery system may be a promising strategy for addressing the question of Eri's delivery and psoriasis therapy. [ABSTRACT FROM AUTHOR]

Objective. The effect of the concept of enhanced recovery after surgery (ERAS) and pain of patients undergoing root canal therapy in oral clinic. Methods. 200 participants in an oral clinic from March 2020 to March 2022 were enrolled in our study. The control group (n = 100) accepted ERAS-based care and the research group (n = 100) accepted ERAS concept and cluster nursing. Nursing satisfaction, comfort, self-efficacy, subjective well-being, self-rating anxiety scale (SAS), and self-rating depression scale (SDS) scores were compared. Results. The research group had 100% satisfaction rate; the control group had 87% satisfaction rate. After nursing, the scores of comforts and self-efficacy of the two groups increased and the scores of comforts and self-efficacy of the research group were higher than those of the control group. After nursing, the scores of subjective well-being of the two groups increased. Furthermore, the higher scores of life satisfaction, interpersonal harmony, and self-efficacy in the research group were found. There was no significant difference in the scores of SAS and SDS between the two groups before nursing (P > 0.05), but after nursing, the scores of SAS and SDS in the two groups decreased, and the scores of SAS and SDS in the research group were lower than those in the control group, and there are statistically significant differences between the groups (P < 0.05). The scores of visual analogue score (VAS) and numerical rating scale (NRS) following intervention decreased, and there are statistically significant differences between the groups (P < 0.05). The less physiological, psychological, social functions, and health self-cognition in the research group were displayed, and there are statistically significant differences between groups (P < 0.05). Conclusion. The adoption of the concept of ERAS and cluster nursing can effectively improve the psychological state and pain score of oral outpatients undergoing root canal therapy, improve comfort and self-efficacy, and enhance subjective well-being and quality of life. ERAS and cluster nursing is of great significance in relieving pain after root canal therapy in the outpatient department, reducing patients' pain and improving patients' quality of life. [ABSTRACT FROM AUTHOR]

Submerged gas-liquid mixture injection into water through a micro-channel shows unique fluid characteristics by various flow regimes in the micro-channel generating special jetting phenomena which have never been systematically studied. We injected air-water mixtures into water through submerged 1.0 and 1.5 mm diameter micro-channels. Bubbly, Taylor, bubble-train Taylor, churn and Taylor-annular flows were observed, and generated respective jetting flow regimes. Overall, two flow regimes namely “unstretched bubbles” and “stretched bubbles” were identified in the jet region. The former consists of three flow patterns, namely discrete bubbles, gathered bubbles and grown irregular bubbles. The latter occured when liquid slugs having strong enough momentum to stretch the bubble interface, from which single-bubble stretched, twin-bubbles stretched and even bubble rupture were further identified. We compared flow regime maps in micro-channels with those of submerged jets, and proposed the correspondence relationship, whose universality was confirmed by the consistency for different sized micro-channels. Transitions between two overall flow regimes of submerged jets, as well as flow patterns of unstretched bubbles were found determined by flow regime transitions in the micro-channel. Besides, transition laws between flow patterns of stretched bubbles were affected by the uniformity of slug length throughout the micro-channel, which were quantitatively analyzed. [ABSTRACT FROM AUTHOR]

Lung cancer has a higher incidence and mortality rate than other cancers, and over 80% of lung cancer cases were classified as non-small-cell lung cancer (NSCLC). TRIM66 is one of the crucial members of TRIM, which has a deep connection with the behavior of various malignant tumors. But it remains uncertain regarding its exact function and underlying mechanism in NSCLC. In our study, qRT-PCR and Western blot were employed to validate that TRIM66 was overexpressed in NSCLC. The migration, invasion, and epithelial-mesenchymal transformation (EMT) progression of NSCLC cells were determined by Western blotting and Transwell experiments after knocking down TRIM66, and it was found that knockdown TRIM66 inhibited the migration, invasion, and EMT processes of NSCLC cells. Next, the binding relationship between TRIM66 and MMP9 was verified by Co-IP assay. After determining the interaction between them, rescue assays showed that overexpression of MMP9 was capable to promote the migration, invasion, and EMT of NSCLC cells. However, the transfection of si-TRIM66 could reverse this facilitating effectiveness. To sum up, we concluded that by targeting MMP9, TRIM66 could exert a cancer-promoting role in the progression of NSCLC cells. [ABSTRACT FROM AUTHOR]

Dehydrins, also known as Group II late embryogenesis abundant (LEA) proteins, are classic intrinsically disordered proteins, which have high hydrophilicity. A wide range of hostile environmental conditions including low temperature, drought, and high salinity stimulate dehydrin expression. Numerous studies have furnished evidence for the protective role played by dehydrins in plants exposed to abiotic stress. Furthermore, dehydrins play important roles in seed maturation and plant stress tolerance. Hence, dehydrins might also protect plasma membranes and proteins and stabilize DNA conformations. In the present review, we discuss the regulatory networks of dehydrin gene expression including the abscisic acid (ABA), mitogen-activated protein (MAP) kinase cascade, and Ca2+ signaling pathways. Crosstalk among these molecules and pathways may form a complex, diverse regulatory network, which may be implicated in regulating the same dehydrin. [ABSTRACT FROM AUTHOR]

Recently, the all- d -metal Ni(Co)MnTi based Heusler compounds are found to have a giant magnetocaloric effect (GMCE) near room temperature and manifest different functionalities like multicaloric effects, which can be employed for solid-state refrigeration. However, in comparison to other traditional Heusler compounds, the relatively large thermal hysteresis (ΔT hys) and moderately steep ferromagnetic phase transition provides limitations for real applications. Here, we present that fast solidification (suction casting) can sufficiently tailor the GMCE performance by modifying the microstructure. Compared with the arc-melted sample, the magnetic entropy change of the suction-casted sample shows a 67% improvement from 18.4 to 29.4 Jkg−1K−1 for a field change (∆ μ 0 H) of 5 T. As the thermal hysteresis has maintained a low Δ T hys value (5.5 K) for the enhanced first-order phase transition, a very competitive reversible magnetic entropy change of 21.8 Jkg−1K−1 for ∆ μ 0 H = 5 T is obtained. Combining high-resolution transmission electron microscopy (HRTEM) and positron annihilation spectroscopy (PAS) results, the difference in lattice defect concentration is found to be responsible for the significant improvement in GMCE for the suction-cast sample, which suggests that defect engineering can be applied to control the GMCE. Our study reveals that fast solidification can effectively regulate the magnetocaloric properties of all- d -metal NiCoMnTi Heusler compounds without sacrificing Δ T hys. [Display omitted] [ABSTRACT FROM AUTHOR]

Purpose: Intergroup contact is an effective strategy to improve intergroup relationships. Although intergroup relationships have been studied extensively, the individual roles of quantity and quality of contact in relationships with cognition, emotion, and intention of behavior toward other ethnic minority groups are not fully understood. This study explores the situation via network analysis among Zhuang and Yao ethnic minorities in Southwest China. Methods: We investigated the quantity and quality of intergroup contact and cognition, emotion, and intention of behavior among a sample of 543 Zhuang and 490 Yao ethnic group members. Data were analyzed using the R-package. Network structures were analyzed via the Qgraph package, and the accuracy and stability of the network were measured via the Bootnet package; communities were detected via the Igraph package; bridge analyses were conducted via the Networktools package; and the network difference was compared via the Network Comparison Test package. Results: The results indicated perceived intimacy is the central node. Quantity of contact constructed a community with "perceived connection," "sense of community," "knowledge about out-group," and "perceived similarity." Meanwhile, quality of contact constructed a community with "intergroup attitude" and a "feeling thermometer." The remainder of the nodes constructed two additional communities. The network global connectivity and structure between the two ethnic groups were highly similar. Conclusion: The study examined the quantity and quality of intergroup contact via network analysis for two ethnic minority groups. It was shown that the two groups' global network structures of intergroup contact and their effects are highly similar. Specifically, quantity and quality of contact produce different effects on intergroup relations. Quantity of contact has proximal effects, including instant cognitive and emotional response without depth cognition, while quality of contact has proximal effects that may change deep-seated cognition and subsequently improve intergroup relations. [ABSTRACT FROM AUTHOR]

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, has become a current threat to humanity. The second wave of the SARS-CoV-2 virus has hit many countries, and the confirmed COVID-19 cases are quickly spreading. Therefore, the epidemic is still passing the terrible stage. Having idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are the risk factors of the COVID-19, but the molecular mechanisms that underlie IPF, COPD, and CVOID-19 are not well understood. Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients. Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs. A total of 65 common DEGs among these three datasets were identified. Various combinatorial statistical methods and bioinformatics tools were used to build the protein–protein interaction (PPI) and then identified Hub genes and essential modules from this PPI network. Moreover, we performed functional analysis under ontologies terms and pathway analysis and found that IPF and COPD have some shared links to the progression of COVID-19 infection. Transcription factors–genes interaction, protein–drug interactions, and DEGs-miRNAs coregulatory network with common DEGs also identified on the datasets. We think that the candidate drugs obtained by this study might be helpful for effective therapeutic in COVID-19. [ABSTRACT FROM AUTHOR]

Background. Prognosis is a main factor affecting the survival of patients with lung adenocarcinoma (LUAD), yet no robust prognostic model of high effectiveness has been developed. This study is aimed at constructing a stable and practicable gene signature-based model via bioinformatics methods for predicting the prognosis of LUAD sufferers. Methods. The mRNA expression data were accessed from the TCGA-LUAD dataset, and paired clinical information was collected from the GDC website. R package "edgeR" was employed to select the differentially expressed genes (DEGs), which were then used for the construction of a gene signature-based model via univariate COX, Lasso, and multivariate COX regression analyses. Kaplan-Meier and ROC survival analyses were conducted to comprehensively evaluate the performance of the model in predicting LUAD prognosis, and an independent dataset GSE26939 was accessed for further validation. Results. Totally, 1,655 DEGs were obtained, and a 7-gene signature-based risk score was developed and formulated as risk _ score = 0.000245 ∗ NTSR 1 + 7.13 E − 05 ∗ RHOV + 0.000505 ∗ KLK 8 + 7.01 E − 05 ∗ TNS 4 + 0.000288 ∗ C 1 QTNF 6 + 0.00044 ∗ IVL + 0.000161 ∗ B 4 GALNT 2. Kaplan-Meier survival curves revealed that the survival rate of patients in the high-risk group was lower in both the TCGA-LUAD dataset and GSE26939 relative to that of patients in the low-risk group. The relationship between the risk score and clinical characteristics was further investigated, finding that the model was effective in prognosis prediction in the patients with different age (age > 65 , age < 65) and TNM stage (N0&N1, T1&T2, and tumor stage I/II). In sum, our study provides a robust predictive model for LUAD prognosis, which boosts the clinical research on LUAD and helps to explore the mechanism underlying the occurrence and progression of LUAD. [ABSTRACT FROM AUTHOR]

Objective. To develop a new type infusion set and apply it to the clinic, as well as explore its effectiveness in the prevention from needle stick injuries. Methods. A total of 200 inpatients who were in need of intravenous infusion with a disposable infusion needle were included and randomly divided into two groups: intervention group and control group. Disposable infusion needles with a separation-free safety tube were used in the intervention group, whereas conventional ones were used in the control group. Then, effects of the two types of infusion sets were observed and compared. Results. As for the operation time for infusion, it was (82.19 ± 1.80) seconds in the intervention group and (83.02 ± 1.83) seconds in the control group, with the difference statistically significant (P < 0.05). Besides, the exposure time of the needles after infusion in the intervention group was (3.36 ± 0.17) seconds while (18.85 ± 1.18) seconds in the control group; the difference between which was statistically significant (P < 0.05). In terms of the time for needle disposal, (18.60 ± 0.84) seconds was required in the intervention group, while for the control group, it took (18.85 ± 1.18) seconds, and the difference between two groups was of statistical significance as well (P < 0.05). Nevertheless, there was no statistically significant difference in the accidental slip rate of the needles as that turned out 0% in both groups (P > 0.05). It was worth noting that the block rate of the disposed needles in the intervention group was 100%. Conclusion. The separation-free safety tube on the disposable infusion needle could instantly block the sharp needle after infusion, which reduces the needle exposure time and lowers the risk of needle stick injuries. In the meantime, the safety tube is convenient to use, and its application can shorten the time for infusion and needle disposal, consequently improving the working efficiency of nurses. As the new type safety tube has above advantages and would not raise the risk of needle slippage, it is worthy of clinical promotion. [ABSTRACT FROM AUTHOR]

The tumorgenesis process of lung cancer involves the regulatory dysfunctions of multiple pathways. Although many signaling pathways have been identified to be associated with lung cancer, there are little quantitative models of how inactions between genes change during the process from normal to cancer. These changes belong to different dynamic co-expressions patterns. We quantitatively analyzed differential co-expression of gene pairs in four datasets. Each dataset included a large number of lung cancer and normal samples. By overlapping their results, we got 14 highly confident gene pairs with consistent co-expression change patterns. Some of they, such as ARHGAP30 and GIMAP4, had been recorded in STRING network database while some of them were novel discoveries, such as C9orf135 and MORN5, TEKT1 and TSPAN1 were positively correlated in both normal and cancer but more correlated in normal than cancer. These gene pairs revealed the underlying mechanisms of lung cancer occurrence. • We analyzed differential co-expression of gene pairs in four datasets. • We got 14 highly confident gene pairs with consistent co-expression change patterns. • We uesd an R package DiffCorr. [ABSTRACT FROM AUTHOR]

Background: Treatment of steroid-resistant nephrotic syndrome (SRNS) remains a challenge for paediatricians. SRNS accounts for 10~20% of childhood cases of nephrotic syndrome (NS). Individuals with SRNS overwhelmingly progress to chronic kidney disease (CKD) and end-stage kidney disease (ESRD). Genetic research is of great significance for diagnosis and treatment. More than 39 recessive or dominant genes have been found to cause human SRNS, including COQ2. COQ2 gene mutations not only cause primary coenzyme Q10 deficiency but also cause SRNS without extrarenal manifestations. The concept of COQ2 nephropathy has been proposed for a long time. Mutations in the COQ2 gene have rarely been reported. Worldwide, only 5 cases involving 4 families have been reported. Case presentation: We present the case of a 6-month-old girl with steroid-resistant glomerulopathy due to a COQ2 defect with no additional systemic symptoms. The patient was identified as a homozygote for the c.832 T > C (p. Cys278Arg) missense mutation and a single base homozygous mutation in ARSB gene in c.1213 + 1G > A. The father and mother were heterozygous mutation carriers in both COQ2 and ARSB, and her healthy sister was only a heterozygous mutation carrier in COQ2. In this case, hormone therapy was ineffective, and progressive deterioration of renal function occurred within 1 week after onset, leading to acute renal failure and eventual death. Conclusions: We reported a consanguinity married family which had COQ2 and ARSB dual mutant. Kidney diseases caused by COQ2 gene mutations can manifest as SRNS, with poor prognosis. The C. 832 T > c (p.csc 278arg) is a new mutation site. Genetic assessment for children with steroid-resistant nephrotic syndrome, especially in infancy, is very important. Families with a clear family history should receive genetic counselling and prenatal examinations, and children without a family phenotype should also receive genetic screening as early as possible. [ABSTRACT FROM AUTHOR]

Abstract Modelling of received ultrasonic signals can provide basis for both signal analysis and process in various instrumentations based on ultrasonic measurement. At present, some empirical models where the resonance frequencies set to fixed values have been proposed for this purpose. However, significant errors can be found between the existing models and actual ultrasonic signals. This paper proposes a modelling method of received ultrasonic signal based on variable frequency analysis, which is then validated by application on ultrasonic gas flowmeter. In this method, the traditional exponential model is modified to contain a time-varying frequency parameter, whose value can be estimated by analyzing the sampled signal using the Teager Energy Operator (TEO). Other parameters in the model can be further determined by parameter estimation algorithms. In order to meet TEO's application conditions, a sinusoidal transformation of the received signal using Hilbert transform before the time-varying frequency estimation is proposed. Wavelet packet de-noising method, lag parameter and smoothing spline are introduced to improve the performance of the time-varying frequency acquisition in the presence of noise. A number of numerical tests are conducted on simulated signals with different time-varying frequencies and noise to confirm the effectiveness of the proposed method. The actual application significance is validated by analysis of the actual received signals on ultrasonic gas flowmeter. Highlights • Modelling ultrasonic signal with time-varying frequency. • Time-varying frequency estimated by Teager Energy Operator. • Sinusoidal transformation of signal to improve frequency estimation precision. • Possible zero-drift compensation and standard wave gain applications. [ABSTRACT FROM AUTHOR]

Double-threshold method is a typical and simple time-of-flight (TOF) measurement method for time-difference-based ultrasonic flowmeter. Some improvements have been proposed to suppress the cycle-skip phenomenon in double-threshold method. However, there are still some application limitations when the waveform is distorted caused by the environment change, especially the temperature change. This paper proposes a similarity judgment-based double-threshold method to deal with the cycle-skip problem. In this method, time values of three consecutive positive zero-crossing points after the feature point are acquired and five consecutive cycles after the first obtained time are saved. The TOF is automatically selected from three acquired time values according to an adaptive determination function which bases on the similarity between signals from two adjacent measurements. These operations guarantee that the obtained TOF locates on the same positive zero-crossing point in each measurement. The proposed method was validated by both numerical and experimental tests. Comparison between the proposed method and other double-threshold methods shows that the proposed method successfully eliminates cycle-skip phenomenon under different working conditions. [ABSTRACT FROM PUBLISHER]

Accurate determination of time-of-flight (TOF) is crucially important for precise ultrasonic flow measurement. Detection of ultrasonic signal onset (USO) is considered as an effective approach to determine the actual value of TOF. The USO can be estimated by signal fitting methods. However, the estimation accuracy and reliability of existing methods still need to be improved. This paper proposes a signal fitting method based on artificial fish swarm algorithm and particle swarm optimization combined algorithm (AFSA-PSO). In the method, AFSA is introduced to search all possible solution spaces firstly, considering the multi-modal characteristic of the objective function in signal fitting which is easily being amplified by the strong noise. Then, a feasible solution extraction strategy is proposed to extract the local optimal solution in every space. Finally, PSO is employed to further process the local solutions to obtain the accurate USO. The method is validated by both numerical and experiment tests, using simulated signals with different strength noise and measured signal in actual ultrasonic flowmeter respectively. Comparisons with the methods proposed by other researchers are also given in the paper. The proposed AFSA-PSO is found to be more accurate, more robust, having better anti-noise ability and less time-consuming under a given accuracy requirement. [ABSTRACT FROM AUTHOR]

Over the past decade, immersion lithography has been the primary technology for exposure process in semiconductor manufacturing. Compared with traditional dry lithography method, this technology improves the exposure resolution greatly by inserting a high index liquid into the gap between lens and wafer surface. Keeping the immersion liquid pure and uniform as well as avoiding residual droplets during high speed scanning motion are two challenges faced by the development of immersion lithography. Contaminations, particles, bubbles, heating and stress in the liquid will destroy the continuity of the refractive index. High speed motion of the wafer during scanning may break the meniscus stability on the interface between the liquid and the gas surrounding it, and then generate residual droplets on the wafer. All above phenomena will affect the exposure performance of immersion lithography and corresponding flow behavior control methods are required to solve the problems. This paper gives a review of the studies on flow behavior control in immersion lithography, which contains two parts: studies for liquid purity and uniformity and studies for meniscus stability. In each part, the mechanism and character of the flow behaviors as well as their effects to exposure performance are presented firstly. Then, control approaches adopted by now, including material and surface modifications as well as immersion head utilization, are introduced. In addition, the challenges faced in future studies are also pointed out. The purpose of this review paper is to help the researchers to understand the flow control problems in immersion lithography and to provide better control approaches for exposure performance improvement. [ABSTRACT FROM AUTHOR]

Accuracy of flow rate determination is very critical to an ultrasonic gas flowmeter, which is sensitive to the flow profile under measurement and cannot be obviously improved with traditional weighted integration methods for multipath transducers. Therefore, on one hand, more attentions are paid to intelligent learning algorithms (e.g. artificial neural networks) in recent studies to accurately construct the mapping relation between multipath velocities and the flow rate. However, the bottleneck that a trained network is only customized for a certain flow profile greatly restricts its application. On the other hand, many researchers turn to reconstruct the flow field but so far all flow visualization methods cost too much and are difficult to realize online. In this paper, an intelligent method of flow profile identification for multipath ultrasonic flowmeters is developed to solve the above predicament. Based on support vector machine, a multiclass identifier is constructed to automatically identify the flow profile to be measured from 65 typical flow patterns. Extremely high identification accuracy of 99.49% for test and 100% for training is achieved while the test result still reaches 88.46% even when a measurement uncertainty of ±2% is considered. A comparison with extreme leaning machine further reveals the identification performance and robustness of the proposed flow profile identifier. Different piping configurations, installation positions and angles can be therefore accurately identified, which indirectly realizes the flow visualization and can comprise an intelligent system of ultrasonic flow measurement when combined with the intelligent flow rate determination algorithms. [ABSTRACT FROM AUTHOR]

To reduce the large integration errors brought by traditional methods in gas flow measurement under complex flow field, artificial neural network, support vector machine and other intelligent algorithms have been put into use. But these intelligent methods consume much time for training and need intensive user intervention for network design. This paper proposes to apply extreme learning machine to multipath ultrasonic flowmeters, which can analytically determine the output weights of networks instead of error backpropagation algorithm and iterative tuning of the parameters, and therefore provide high metering accuracy at extremely fast learning speed as well as require least human intervention. To test its effectiveness under different flow field and sensitivity to complex flow profiles, extreme learning machine is applied to determine the flow rate under two piping configurations, which can produce mild and severe flow disturbances. The determination errors are compared with a traditional integration method on the position of 5D and 10D as well as with the path orientation of 0° and 90°. Then 7 installation angles and 9 installation positions are respectively configured to study the performance and sensitivity of UFMs to installation effects. Finally, a comparison between extreme learning machine and other two intelligent algorithms is made in training and test time, the mean squared error and the maximal metering error under severe flow disturbance. It is found that extreme learning machine has rather high determination accuracy for flow rate at extremely fast learning speed and it is insensitive to the installation effects of ultrasonic gas flowmeter. [ABSTRACT FROM AUTHOR]

• 3D GO-CTF aerogels could effectively adsorb trace concentration of UV filters. • The spent aerogels can be regenerated by utilizing sunlight. • Regenerated 3D GO-CTF remained effective for adsorption of UV filters from natural water. • Hybrid block can be easily recycled from natural water bodies. UV filters, a kind of personal care product (PCP), are intractably degraded using conventional processes because of their trace concentration in the environment. The exploration of high-performance, stable, and reusable materials for the highly efficient removal of UV filters is of great importance. In this study, a series of three-dimensional graphene oxide-covalent triazine-based frameworks aerogels (3D GO-CTF) prepared with different concentration ratios were designed to remove trace concentrations of benzophenone (BP), 2,4-dihydroxybenzophenone (BP-1) and 2-hydroxy-4-methoxybenzophenone (BP-3) from water, which are regenerated by sunlight. 3D GO-CTF not only adsorbs UV filters with high efficiency (0.0311 ± 0.0009 g/(μmol·s)) and capacity (2963.708 ± 4.637 μmol/g), but can also be regenerated with an extremely high percentage recovery of 90–95% in the 4th cycle. These 3D GO-CTF materials exhibit switchable selectivity between the adsorption of the UV filters and regeneration of the 3D GO-CTF by regulating the content of GO to function as the adsorbent and CTF for photocatalytic regeneration. Moreover, the high reusability and extreme stability of the 3D GO-CTF aerogels were verified over seven cycles of night-day testing in a real water matrix, which demonstrated their potential application in the efficient removal of micropollutants from the environment. [ABSTRACT FROM AUTHOR]

• A new gas-liquid interface jet was observed during a suspended liquid suck process. • The jet is developed from a pressure-driven flow and maintained by coaxial gas flow. • The gas superficial velocities almost don't influence the jet spout below the nozzle. • The shear force generated by gas flow cause interface instabilities inside the tube. In the tubular co-flowing gas-liquid jet, liquid is sucked through a nozzle suspended above the flat gas-liquid interface. The liquid hump can be induced by the sudden pressure change just beneath the nozzle entrance. At a sufficiently fast initial gas superficial velocity, the interface undergoes a transition and liquid starts to be sucked. The suction flow is in the form of an axisymmetric liquid jet surrounded by an upwards coaxial gas flow. In the present study, we discuss the evolution and characteristics of the suspended liquid suction flow. The jet dynamics include the interface deformation and development (the hump stage), the tubular co-flowing jet (the spout state) and the destabilization of the liquid jet (the jet state). Tube inner diameter, suspension height, and initial gas superficial velocity are three important parameters that influence the suction flow. Due to the inward gas flow, a relatively large amount of pressure gradients is imparted to a small mass of liquid near a free surface, which leads to interface deformation. The lateral boundary of the liquid hump circumferentially shrinks and the top liquid gradually rises following the shrinkage. There is a comparatively stable axisymmetric liquid jet surrounded by an upwards coaxial gas flow inside the tube. Surprisingly, no evidence is shown the dependence of jet spout with initial gas axisymmetric superficial velocity below the nozzle through plenty of experiment figures and statistical analysis. On the other hand, the velocity difference between the fast light gas flow and the slow dense liquid is critical to the destabilization of the liquid jet. [ABSTRACT FROM AUTHOR]