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[Display omitted] • The SPR and fluorescence dual-mode detection system were applied. • The whole cell and membrane region of a single cell were analyzed simultaneously. • The temporal and spatial correspondences were established. • Effectiveness of multiple drugs on A549 cells was tested. The investigation of the interactions between cells and drugs forms a crucial aspect of biological and clinical medical studies. Generally, single-cell or local-cellular studies require a microscopic imaging system with high magnifications, which suffers from low detection throughputs and poor time responses. The study presented in this paper combined SPR and fluorescence to achieve cell localization, real-time monitoring of cell images and quantitative analysis of drugs. In order to obtain more comprehensive, accurate and real-time data, a dual-mode system based on surface plasmon resonance (SPR) and fluorescence was constructed based on a 4× magnification lens. This enables simultaneous studies of an entire cell and a specific region of the cell membrane. An adaptive adjustment algorithm was established for distorted SPR images, achieving temporal and spatial matching of the dual-mode detection. The combination of SPR and fluorescence not only achieved micro-detection but also complemented the qualitative or quantitative limitations of SPR or fluorescence method alone. In system characterization, the response signal of SPR was noticed to increase with the increasing concentration of EGF in stimulated cells. It indicated that this platform could be employed for quantitative detection of the cell membrane region. Upon addition of EGF, a peak in the SPR curve was observed, and the cells in the corresponding SPR image turned whiter. This indicated that the platform can simultaneously monitor the SPR response signal and image changes. The response time of fluorescence in EGF testing was several seconds earlier than SPR, revealing that signal transduction first occurred in the whole cell and then propagated to the cell membrane region. The inhibitory ability of Gefitinib on cells was verified in a fast and real-time manner within 20 min. The results indicated that the detection limit of this method was 20 IU/mL for EGF and 10 µg/mL for Gefitinib. In conclusion, this study demonstrates the advantages of SPR and fluorescence dual-mode techniques in the analysis of cell-drug interactions, as well as their strong potential in drug screening. [ABSTRACT FROM AUTHOR]

In lake ecosystems, pelagic-benthic coupling strength (PBCS) is closely related to foodweb structure and pollutant transport. However, the trophic transfer of antibiotics in a benthic-pelagic coupling foodweb (BPCFW) and the manner in which PBCS influences the trophic magnification factor (TMFs) of antibiotics is still not well understood in the whole lake. Herein, the trophic transfer behavior of 12 quinolone antibiotics (QNs) in the BPCFW of Baiyangdian Lake were studied during the period of 2018–2019. It was revealed that 24 dominant species were contained in the BPCFW, and the trophic level was 0.42–2.94. Seven QNs were detected in organisms, the detection frequencies of ofloxacin (OFL), flumequine (FLU), norfloxacin (NOR), and enrofloxacin (ENR) were higher than other QNs. The ∑QN concentration in all species was 11.3–321 ng/g dw. The TMFs for ENR and NOR were trophic magnification, while for FLU/OFL it was trophic dilution. The PBCS showed spatial-temporal variation, with a range of 0.6977–0.7910. The TMFs of ENR, FLU, and OFL were significantly positively correlated with PBCS. Phytoplankton and macrophyte biomasses showed indirect impact on the TMFs of QNs by directly influencing the PBCS. Therefore, the PBCS was the direct influencing factor for the TMFs of chemicals. [Display omitted] • First illustrated the PBCS was the direct impact factor for the TMFs of QNs. • Two-baseline approach is better to assess TMFs of chemicals in BPCFW. • Temporal variation of PBCS was significant while spatial variation was not. • The TMFs of ENR, FLU, and OFL were significantly positive correlation with PBCS. • PB and MB showed indirectly impact the TMFs of QNs by directly influence PBCS. [ABSTRACT FROM AUTHOR]

Microplastic (MP), as a new pollutant, not only affects the growth and development of plants but also may affect the secondary metabolites of plants. The anti-tumor role of Pinellia ternata is related to secondary metabolites. The role of brassinolide (BR) in regulating plant resistance is currently one of the research hotspots. The paper mainly explores the regulation of BR on growth and physiology of Pinellia ternata under MP stress. The experimental design includes two levels of MP (0, 1%) and two levels of BR (0, 0.1 mg/L). MP led to a marked reduction in plant height (15.0%), Fv/Fm (3.2%), SOD and APX activity (15.0%, 5.1%), whereas induced an evident raise in the rate of O 2 ·- production (29.6%) and GSH content (4.4%), as well as flavonoids (6.8%), alkaloids (75%), and β-sitosterol (26.5%) contents. Under MP addition, BR supply significantly increased plant height (15.7%), aboveground and underground biomass (16.1%, 10.3%), carotenoid and GSH content (11.8%, 4.2%), Fv/Fm (2.9%), and activities of SOD, GR, and MDHAR (32.2%, 21.08%, 20.9%). These results indicate that MP suppresses the growth of P. ternata , although it promotes secondary metabolism. BR can alleviate the inhibitory effect of MP on growth by improving photosynthesis, redox homeostasis, and the AsA-GSH cycle. [Display omitted] • MP reduces growth and antioxidant capacity of P. ternata. • MP promotes the generation of secondary metabolic substances in P. ternata. • BR enhances growth and antioxidant capacity of P. ternata under MP stress. • BR have a potential role in mitigating adverse effects of MP on P. ternata. [ABSTRACT FROM AUTHOR]

Motivated by the impressive success of deep learning in a wide range of scientific and industrial applications, we explore in this work the application of deep learning into a specific class of optimization problems lacking explicit formulas for both objective function and constraints. Such optimization problems exist in many design problems, e.g., rotor profile design, in which objective and constraint values are available only through experiment or simulation. They are especially challenging when design parameters are high-dimensional due to the curse of dimensionality. In this work, we propose a data-informed deep optimization (DiDo) approach emphasizing on the adaptive fitting of the the feasible region as follows. First, we propose a deep neural network (DNN) based adaptive fitting approach to learn an accurate DNN classifier of the feasible region. Second, we use the DNN classifier to efficiently sample feasible points and train a DNN surrogate of the objective function. Finally, we find optimal points of the DNN surrogate optimization problem by gradient descent. To demonstrate the effectiveness of our DiDo approach, we consider a practical design case in industry, in which our approach yields good solutions using limited size of training data. We further use a 100-dimension toy example to show the effectiveness of our approach for higher dimensional problems. Our results indicate that, by properly dealing with the difficulty in fitting the feasible region, a DNN-based method like our DiDo approach is flexible and promising for solving high-dimensional design problems with implicit objective and constraints. [ABSTRACT FROM AUTHOR]

Continuous urban development leads to urban heat island effects. Research suggests that urban green spaces can help effectively reduce urban heat island effects in the summer. Previous studies have mainly focused on the influence of different underlying surfaces on air cooling and humidification. There is a lack of in-depth research on the relationship between park structure and microclimatic effects. Here, we examined the main landscape parameters of green spaces in 15 parks located in Suzhou Industrial Park (SIP) with a subtropical maritime monsoon climate zone during the summer to analyze their influence on the microclimate. We adopted a multiple regression method to perform a quantitative analysis of the correlation between the factors and the cooling and humidifying effects. We used one-way ANOVA (analysis of variance) and multiple linear regression statistical analysis methods to study the influence of woodland density and water bodies on the microclimatic effect of the green areas. The result shows that the average cooling and humidifying effect of medium-size green spaces was most significant during high-temperature hours in the daytime. Also, the result shows that the shape and size of water areas within a green space have a significant influence on local cooling and humidification. [ABSTRACT FROM AUTHOR]

• Solving balance search problems among local search and global search. • Objective black-box functions are constructed by Hierarchical Gauss process model. • A generalized hierarchical expected improvement method is proposed to solve bayesian optimization problem. • Hyperparmeter prior distribution models are adjusted by increasing the number of samples during the search process. With the improvement of the accuracy of numerical simulation experiments, the computational costs of black–box function problems are increasing. In the process of global optimization using the Bayesian optimization method, the sampling cost and the optimization accuracy are the keys for measuring the effectiveness of the Bayesian optimization method. The expected improvement method has a closed-form of the acquisition function, which can realize the effective use of the sampled points, thereby reducing the sampling cost and improving the optimization accuracy. Therefore, this method has been widely used to solve practical engineering problems. The current expected improvement methods are based on fixed local–global search strategy. These methods have difficulty adapting to black-box functions of different complexities, and they have significant limitations in balancing local and global search capabilities. This article proposes a generalized hierarchical expected improvement (GHEI) Bayesian optimization method with an adaptive search strategy. By introducing the balance parameters to adjust the improvement functions, the local–global search criterion is further changed. On this basis, an adaptive search strategy based on the equivalent expectation to improve the optimization is proposed, and it improves the ability to deal with black-box functions of different complexities. The accuracy of the hierarchical Gaussian process model is further improved through methods such as related parameter estimation, hyperparameter determination, and basis function order selection. Comparative analysis with numerical calculation examples verified the effectiveness of the proposed method. Finally, the adaptive GHEI method is applied on the spacecraft radiation resistance equivalent test analysis, and results show that the adaptive GHEI method exhibits a strong search efficiency and applicability. [ABSTRACT FROM AUTHOR]

With the successful development of unconventional hydrocarbons, the production of unconventional hydrocarbons has increased rapidly. However, a single conventional or unconventional model is not suitable for the mechanism of hydrocarbon accumulation in a given basin or sag. Based on data from drilling, logging, and geophysical analysis, the hydrocarbon accumulation mechanism in the Hari sag in the Yingen-Ejinaqi basin, China, was analyzed. There are three sets of source rocks in the Hari sag: the K1y source rocks were evaluated as having excellent source rock potential with low thermal maturity and kerogen Type I-II1; the K1b2 source rocks were evaluated as having good source rock potential with mature to highly mature stages and kerogen Type II1-II2; and the K1b1 source rocks were evaluated as having moderate source rock potential with mature to highly mature stages and kerogen Type II1-II2. Reservoir types were found to be conventional sand reservoirs, unconventional carbonate-shale reservoirs, and volcanic rock reservoirs. There were two sets of fault-lithologic traps in the Hari sag, which conform to the intra-source continuous hydrocarbon accumulation model and the approaching-source discontinuous hydrocarbon accumulation model. The conclusions of this research provide guidance for exploring multi-type reservoirs and multi-type hydrocarbon accumulation models. [ABSTRACT FROM AUTHOR]

Background. Abdominal aortic aneurysm (AAA) is a fatal disease characterized by high morbidity and mortality in old population. Globally, effective drugs for AAA are still limited. Si-Miao-Yong-An decoction (SMYAD), a traditional Chinese medicine (TCM) formula with a high medical value, was reported to be successfully used in an old AAA patient. Thus, we reason that SMYAD may serve as a potential anti-AAA regime. Objective. The exact effects and detailed mechanisms of SMYAD on AAA were explored by using the experimental study and bioinformatics analysis. Methods. Firstly, C57BL/6N mice induced by Bap and Ang II were utilized to reproduce the AAA model, and the effects of SMYAD were systematically assessed according to histology, immunohistochemistry, and enzyme-linked immunosorbent assay (ELISA). Then, network pharmacology was applied to identify the biological processes, pathways, and hub targets of SMYAD against AAA; moreover, molecular docking was utilized to identify the binding ability and action targets. Results. In an animal experiment, SMYAD was found to effectively alleviate the degree of pathological expansion of abdominal aorta and reduce the incidence of Bap/Ang II-induced AAA, along with reducing the damage to elastic lamella, attenuating infiltration of macrophage, and lowering the circulating IL-6 level corresponding to the animal study, and network pharmacology revealed the detailed mechanisms of SMYAD on AAA that were related to pathways of inflammatory response, defense response, apoptotic, cell migration and adhesion, and reactive oxygen species metabolic process. Then, seven targets, IL-6, TNF, HSP90AA1, RELA, PTGS2, ESR1, and MMP9, were identified as hub targets of SMYAD against AAA. Furthermore, molecular docking verification revealed that the active compounds of SMYAD had good binding ability and clear binding site with core targets related to AAA formation. Conclusion. SMYAD can suppress AAA development through multicompound, multitarget, and multipathway, which provides a research direction for further study. [ABSTRACT FROM AUTHOR]

Real-time matching of millimeter wave (mmWave) narrow beams is a great challenge in dynamic vehicle to infrastructure (V2I) environments due to the mobility of vehicles. In this paper, a novel beam search strategy based on spectrum-environment awareness is proposed. Combining the technique of label iterative optimization with three-dimensional (3D) grid encoding, the strategy treats the optimal beam pair indexes (BPIs) as labels and encodes the environments as features. Three-dimensional grid encoding is a symmetry-based environmental coding technology. A new Convolutional Neural Network (CNN) model is also constructed, which is trained by the features. The situational beam search of actual vehicles is performed under the trained CNN model. As a result, real-time mmWave narrow beam matching can be achieved. Simulation results demonstrate that the proposed strategy can effectively reduce the beam search overhead and improve the efficiency while guaranteeing the matching accuracy. [ABSTRACT FROM AUTHOR]

Motivation High-dimensional mass cytometry (CyTOF), which provides both cellular signatures and inter-cluster interactions like the antagonism between immune activation and suppression, and the pro-inflammatory synergy, sheds light on the cellular and molecular basis of disease pathogenesis. However, revealing the aberrance of inter-cluster communication networks in CyTOF datasets remains a significant challenge. Results Here, we developed Sample Classification and direct Association Network among Cell clusters (SCANCell) that quantifies the direct association (DA) network of cell clusters. SCANCell was applied to profile inter-cluster interaction patterns of a well-recruited systemic lupus erythematosus (SLE) cohort, including 8 healthy controls, 10 active SLE patients (APs) and 8 remission SLE patients (RPs). SCANCell identified decreased inter-cluster interactions of CD8+ T cells in APs compared with RPs, and enhanced DA of CD8+ T cells after stimulation with immunostimulatory cytokine interleukin-2 in vitro. These discoveries prove that SCANCell can uncover pathology- and drug stimulation-associated inter-cluster interactions, which potentially benefits understanding of pathogenesis and novel therapeutic strategies. Availability and implementation The main processing scripts of SCNACell are available at https://github.com/Lxc417/SCANCell. Other codes for the following data statistics are available from the corresponding author upon request. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Compared with HC participants, patients with MDD had significantly higher ALFF in the left cerebellum and significantly lower ALFF in the right rolandic opercular cortex (all I p i < 0.001, AlphaSim correction) (Table 1) (Figures 1-3). Keywords: major depressive disorder; first-episode; ALFF; fALFF; fMRI EN major depressive disorder first-episode ALFF fALFF fMRI 555 561 7 04/13/22 20220301 NES 220301 Introduction Major depressive disorder (MDD) is a common mental disorder;[1] however, its precise underlying mechanisms remain to be elucidated. Spearman rank correlation analysis showed that neither ALFF nor fALFF values of brain regions in patients with MDD significantly correlated with the total HAMD SB 17 sb scores (all I p i > 0.05). Thus, we examined the characteristics of ALFF and fALFF in first-episode drug-naive patients with MDD to better elucidate the alterations in resting brain function in patients with MDD. [Extracted from the article]

With Fe3+ as both the morphology-controlling agent and dopant, Fe-doped NiS 2 microcrystals with the exposed chemically stable {0 0 1} facets were synthesized hydrothermally for electrocatalytic OER. After the electrocatalytic activation, the iron-rich surface transformed into active Fe-doped nickel oxyhydroxide, while the inner {0 0 1}-oriented NiS 2 retained, endowing the catalysts with high OER activity and long-term stability. [Display omitted] Developing high-performance electrocatalysts with favorable phase, surface structure and electronic structure for oxygen evolution reaction (OER) is crucial for efficient electrocatalytic water splitting. With Fe3+ ions as both dopant and morphology-controlling agent, Fe-doped NiS 2 microcrystals with the exposed chemically stable {0 0 1} facets were synthesized hydrothermally for electrocatalytic OER. The initial electrocatalytic OER activation processes led to the conversion of iron-rich surface layers of the NiS 2 microcrystals into Fe-doped Ni (oxy)hydroxide as the shell and the residual inner of the NiS 2 microcrystals as the core. Such Fe-doped NiS 2 microcrystals with the derived core/shell structure only required a small OER overpotential of 277 mV to reach an electrochemical current density of 10 mA/cm2, and showed a good stability in a more than 20 h duration test almost without overpotential increase. [ABSTRACT FROM AUTHOR]

Real point cloud registration, involving homologous and cross-source 3D data, poses significant challenges such as partial overlap, high noise, density disparities, and scale variations. In this paper, we introduce a framework called OEFM to guide transform estimation on the basis of feature metrics through overlap estimation with overlap region center weighting, which estimates transform parameters by minimizing feature projection error on overlap region features. Our proposed approach utilizes an overlap filtering module with a center-weighting mechanism to filter overlap points and feeds these points into a feature metric framework with a forward–backward transformation to estimate the transformation parameters. The rationale behind our approach is that only overlapping regions are useful for point cloud registration, while non-overlapping regions are anomalous. Furthermore, our proposed approach requires no correspondence search, making it robust to partial overlaps, large noise, density differences, and scale variations. We show that our approach achieves the highest registration recall for 3DMatch and 3DCSR in extensive experiments on both homologous and cross-source datasets. • We present an efficient unsupervised training module for transform estimation with forward–backward transformation, which could enhance the performance of unsupervised training as well as transform estimation. • We provide a robust point cloud registration technique combined with feature matching, without using the common correspondence search. [ABSTRACT FROM AUTHOR]

Rainfall-induced soil slope failures are among the most frequent and widespread landslides in the world. The infiltration of water plays a critical role in the instability of slopes under rainfall conditions. By employing the physical models, field monitoring data becomes instrumental for the back analysis of soil parameters, providing critical insights into the mechanisms of slope instability. In this review, the initial section investigates the hydraulic characteristics of unsaturated soils, encompassing the soil-water characteristic curve, permeability function, and their variability nature. Subsequently, a comprehensive overview of infiltration models for unsaturated soil, coupled with their numerical and analytical solutions, is provided. The subsequent section systematically introduces physical model-based Bayesian parameter inference, with a particular emphasis on the formulations of likelihood functions. The exploration then shifts towards investigating the impacts of prior knowledge, likelihood, model structure, and assimilation approach on an unsaturated soil slope monitoring case. Finally, the limitations of the current approaches and future outlooks in this field are presented. [ABSTRACT FROM AUTHOR]

This paper reports an experimental investigation of the membrane residual stresses in S690 high strength steel welded π-shaped and cruciform sections. The experimental programme was performed on three π-shaped sections and two cruciform sections, fabricated from 5 mm thick S700MC high strength steel plates by means of gas metal arc welding, and included material tensile coupon tests and membrane residual stress measurements, with two measurements for each of the five S690 high strength steel welded π-shaped and cruciform sections. The measured tensile and compressive membrane residual stresses were analysed and the self-equilibrium of the measured membrane residual stresses in each constituent plate element was also verified, with the maximum unbalanced membrane residual stress to yield stress ratios of 3.3% for π-shaped sections and 3.2% for cruciform sections. The existing membrane residual stress predictive models, as given in the European convention and Swedish regulations, were assessed for their applicability to S690 high strength steel welded π-shaped and cruciform sections, revealing inaccuracy. Finally, two sets of new predictive models for membrane residual stresses in S690 high strength steel welded π-shaped and cruciform sections were proposed and shown to result in accurate predictions of the measured membrane residual stress data. • The membrane residual stresses in S690 high strength steel welded π-shaped and cruciform sections are studied. • Ten sets of measurements are conducted on three π-shaped sections and two cruciform sections. • The measured tensile and compressive membrane residual stresses are analysed. • The codified membrane residual stress predictive models are assessed, indicating inaccuracy. • New improved membrane residual stress predictive models are proposed. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effectiveness of the cascadic multigrid method applied to improved Picard iteration method for nonlinear problems arising in deforming variably saturated porous media. The finite element method with 6-node triangular elements is applied to discretize the space and obtain nonlinear algebraic equations. Then the nonlinear iterative method is used for iterative solution. Since the classical nonlinear Picard iteration method (PI) can be slow to converge, two improved Picard iteration methods are proposed. One is the improved Picard method with iterations k on the coarse grid and number of multiple grids m (PI-MG(m , k)), and the other is the improved Picard method based on the cascadic multigrid method without parameter k (PI-NMG(m)). Three numerical examples are given to verify the effectiveness of the improved method. Results indicate that the convergence rate of PI is the slowest (10–25 nonlinear iterations per time step), followed by PI-MG(m , k) (3–5 nonlinear iterations), and PI-NMG(m) is the fastest (stable 2 nonlinear iterations). The computational efficiency of PI-NMG(m) is improved by about 90% relative to PI and by about 70% relative to AR-PI. This method can be applied to large-scale numerical calculation of seepage and deformation in unsaturated deforming porous media. [ABSTRACT FROM AUTHOR]

The ordinary differential equation is a powerful tool for analyzing optimization algorithm. Motivated by the fact, this paper revisits Halpern fixed-point algorithm from an ordinary differential equation. More specifically, we establish a second-order ordinary differential equation with Hessian-driven damping, which is the limit of Halpern fixed-point algorithm. The Hessian-driven damping makes it possible to significantly attenuate the oscillations. [ABSTRACT FROM AUTHOR]

[Display omitted] • CdS/CdWO 4 heterojunction photocatalysts based on two crystal forms of CdWO 4 were synthesized via an in-situ anion-exchange reaction. • CdS/M-CdWO 4 follows the traditional type II charge transfer mechanism. • For CdS/T-CdWO 4 with oxygen vacancies, the charge transfer shifts to S-scheme transport mechanism. • Compared to CdS/M-CdWO 4 , the CdS/T-CdWO 4 gives a 14-fold enhanced H 2 evolution rate under the full spectrum irradiation. • It realized improved photocatalytic performance from the point of polycrystalline engineering and surface defects. Regulation of the carrier migration path in heterojunction photocatalysts is an effective strategy to improve the performance of photocatalytic hydrogen evolution. Herein, CdS/CdWO 4 heterojunction photocatalysts based on two crystal forms of CdWO 4 were synthesized via an in-situ anion-exchange reaction. It was discovered that crystal structure and surface defect have a significant impact on the charge carrier migration mechanism during photocatalysis. When CdS was loaded onto monoclinic CdWO 4 (M-CdWO 4), the resulting CdS/M-CdWO 4 heterojunction followed the conventional type- II charge transfer mechanism. In contrast, tetragonal CdWO 4 (T-CdWO 4) with a substantial number of oxygen vacancies resulted in the CdS/T-CdWO 4 composite adopting an S-scheme transport mechanism. Driven by the distinct carrier migration path, the CdS/T-CdWO 4 heterojunction demonstrated superior hydrogen evolution performance compared to the CdS/M-CdWO 4. Significantly, the hydrogen evolution rate of CdS/T-CdWO 4 was 2.56 mmol h−1 g−1, which is about 14 times higher than CdS/M-CdWO 4. The excellent photocatalytic activity of CdS/T-CdWO 4 could be mainly ascribed to the efficient separation of photogenerated charge carriers and the higher reduction capacity showcasing in S-scheme. Several techniques such as electron paramagnetic resonance (EPR), in-situ X-ray photoelectron spectroscopy (XPS), and selective photodeposition were employed to confirm the regulation of the carrier migration path from type II to S-scheme over CdS-loaded CdWO 4 polymorphs. This study provides comprehensive insights into the construction of highly efficient photocatalytic heterojunctions in the viewpoint of polymorph engineering and surface defects from a deeper perspective. [ABSTRACT FROM AUTHOR]

Recent studies show that the API p - y method may underestimate the pile-soil initial stiffness of offshore wind turbine (OWT) monopiles in clay while overestimate that in sand. To facilitate the reliability-based design of OWT monopiles with the API p - y design method, a two-stage evaluation method of the model bias factor for the p - y method (ε py) of monopiles under the serviceability limit state (SLS) was presented. The model bias factor ε py is derived by comparing field test data with high-fidelity 3D finite element model (FEM) results, and the p - y method predictions, addressing the issues of limited field test data for OWT monopiles. Results show that the mean of the model bias factor ε py depends on the characteristics of piles, the soil properties, and the composition of the layered ground. The systematic dependency is expressed by a trend function and the residual model bias factor follows a lognormal distribution with a mean of 1.01 and a COV of 0.14. The significance of the model uncertainty is illustrated using a case study. The results of the field example show that the design in clay sites may be considerably conservative and may be less conservative in sand sites if ignoring the model uncertainty. The result of this work can provide a basis for promoting reliability-based design for OWT monopiles. • A two-stage approach is presented to characterize the model bias factor for the API p-y method of OWT monopiles underSLS. • The proposed approach addresses the issues of limited field test data for OWT monopiles. • The model bias factor is applied to evaluate the reliability index of OWT monopiles under SLS in a real project in China. • Ignoring the model bias factor causes a conservative design in clay sites and a less conservative design in sand sites. • The result of this work can provide a basis for promoting reliability-based design for OWT monopiles. [ABSTRACT FROM AUTHOR]

Cellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics examination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co-culture with drugs, which are relatively complex and time-consuming. Moreover, these methods can only indicate the drug effectiveness on cell colony rather than single cells. Thus, to meet the requirements of personal precision medicine, the development of drug response analysis on the high resolution of single cell is demanded. To provide precise result for drug response on single-cell level, a microfluidic platform coupled with the label-free hyperspectral imaging was developed. With the help of horizontal single-cell trapping sieves, hundreds of single cells were trapped independently in microfluidic channels for the purposes of real-time drug delivery and single-cell hyperspectral image recording. To significantly identify the cellular hyperspectral change after drug stimulation, the differenced single-cell spectrum was proposed. Compared with the deep learning classification method based on hyperspectral images, an optimal performance can be achieved by the classification strategy based on differenced spectra. And the cellular response to different reagents, for example, K+, Epidermal Growth Factor (EGF), and Gefitinib at different concentrations can be accurately characterized by the differenced single-cell spectra analysis. The high-throughput, rapid analysis of cellular response to drugs at the single-cell level can be accurately performed by our platform. After systematically analyzing the materials and the structures of the single-cell microfluidic chip, the optimal single-cell trapping method was proposed to contribute to the further application of hyperspectral imaging on microfluidic single-cell analysis. And the hyperspectral characterization of single-cell with cancer drug stimulation proved the application potential of our method in personal cancer medication. [Display omitted] • A microfluidic single-cell chip with hundreds of single-cell traps was developed to simultaneously achieve single cell trapping, drug delivery, and hyperspectral image recording. • Two different analysis methods, the ANN model for hyperspectral images, and the algorithm of differenced single-cell spectra were systematically analyzed and compared. • The cellular response of A549 cells to different reagents, such as K+, Epidermal Growth Factor (EGF), and Gefitinib with different concentrations can be precisely characterized by the differenced single-cell spectra. [ABSTRACT FROM AUTHOR]

Background: This study was performed to identify the association between the total magnetic resonance imaging burden of small vessel disease and the occurrence of post-stroke dysphagia in patients with a single recent small subcortical infarct (RSSI).Methods: We retrospectively identified all patients with a magnetic resonance imaging-confirmed single RSSI. The water-swallowing test and volume-viscosity swallow test were performed within the first 24 h following admission to assess swallowing. Demographic and clinical data were extracted from our stroke database. Based on brain magnetic resonance imaging, we independently rated the presence of cerebral microbleeds, lacunes, white matter hyperintensities and enlarged perivascular spaces. The presence of each small vessel disease feature was summed to determine the total small vessel disease burden, ranging from 0 to 4.Results: In total, 308 patients with a single RSSI were enrolled. Overall, 54 (17.5%) were diagnosed with post-stroke dysphagia. The risk factors related to post-stroke dysphagia included the following: older age, higher National Institute of Health Stroke Scale scores, higher C-reactive protein level and higher fibrinogen level. Based on multiple logistic regression, National Institute of Health Stroke Scale scores and total small vessel disease burden were independent risk factors of post-stroke dysphagia in patients with a single RSSI, after adjusting for age, gender, history of hypertension, C-reactive protein level and fibrinogen level.Conclusions: Dysphagia in patients with a single RSSI was associated with a more severe total small vessel disease burden as reflected by MRI. Total MRI of cerebral small vessel disease burden may predict dysphagia in these patients. Furthermore, more severe total small vessel disease burden was associated with systemic inflammation. [ABSTRACT FROM AUTHOR]

Ginger is widely used as either a food product or a herbal medicine around the globe. In the current study, we used headspace solid-phase microextraction and gas chromatography-mass spectrometry technology (HS-SPME-GC-MS) with n-butyl acetate as an internal standard to characterize three kinds of ginger oil in Xilin fire ginger, which included ginger essential oil (GEO), ginger oleoresin extracted with petroleum ether (PEGO) and ginger oleoresin extracted with absolute ethanol (AEGO). Cluster analysis of heatmap was used to reveal the differences in concentration in these oils. Odor activity value, in combination with principal component analysis, was further used to analyze the contribution to the aroma. This study demonstrated that despite the similarities in the aroma compounds and content of three kinds of ginger oil, GEO exhibited a better aroma quality, followed by AEGO and PEGO. [ABSTRACT FROM AUTHOR]

The collision risk of ships is a fuzzy concept, which is the measurement of the likelihood of a collision between ships. Most of existed studies on the risk of multi-ship collision are based on the assessment of two-ship collision risk, and collision risk between the target ship and each interfering ship is calculated respectively, to determine the key avoidance ship. This method is far from the actual situation and has some defects. In open waters, it is of certain reference value when there are fewer ships, but in busy waters, it cannot well represent the risk degree of the target ship, since it lacks the assessment of the overall risk of the perceived area of the target ship. Based on analysis of complexity of ships group situation, the concept of relative domain was put forward and the model was constructed. On this basis, the relative collision risk was proposed, and the corresponding model was obtained, so as to realize risk assessment. Through the combination of real ship and simulation experiments, the variation trend, stability and sensitivity of the model were verified. The results showed that risk degree of the environment of ships in open and busy waters could be well assessed, and good references for decision-making process of ships collision avoidance could be provided. [ABSTRACT FROM AUTHOR]

The main components of polycyclic aromatic hydrocarbons (PAHs) and the degree of contamination of soil with different oils (gasoline, diesel oil, and lubricating oil) were examined. Malus prunifolia var. Ringo was planted in soil contaminated by gasoline, diesel oil, or lubricating oil with three different concentrations which were low concentration (0.1 g kg−1), medium concentration (0.2 g kg−1), and high concentration (0.5 g kg−1) in April 2016. The changes in PAH contents and soil index in the soil were measured from July to September 2016. It showed that more naphthalene, anthracene, phenanthrene, fluorene, and flexion were detected in the three oil treatments. From July to September, three high-concentration oil treatments had inhibited soil urease activity in soil significantly except the diesel oil treatment with high concentration in August. The diesel and lubricating oil treatments had inhibited phosphatase and invertase activities in soil significantly. Three oil treatments inhibited the number of bacteria significantly in July. The total number of bacteria and fungi was highest in gasoline, and the total number of actinomycetes was highest in lubricating oil. The three oils affected the soil enzyme activity and the number of soil microorganisms and caused some damage to the soil ecological environment. [ABSTRACT FROM AUTHOR]

Because of the complex etiology, the treatment of gastric cancer is a formidable challenge for contemporary medical. The current treatment method focuses on traditional surgical procedures, supplemented by other treatments. Among these other treatments, Traditional Chinese Medicine (TCM) plays an important role. Here, we used the systems pharmacology approach to reveal the potential molecular mechanism of PRGRC on gastric cancer which composes of Pinellia ternata(Thunb.) Breit., Rheum palmatumL., Gentiana scabraBunge, Radix Aucklandiae and Citrus aurantium L. This approach combines pharmacokinetics analysis with pharmacodynamics evaluation for the active compounds screening, targets prediction and pathways assessing. Firstly, through pharmacokinetic evaluation and target prediction models, 83 potential compounds and 184 gastric cancer-related targets were screened out. Then, the results of network analysis suggested that the targets of PRGRC were mainly involved two aspects: apoptosis and inflammation. Finally, we verified the reliability of the above analysis at the cellular level by using naringenin and luteolin with good pharmacokinetic activity as representative compounds. Overall, we found that PRGRC could influence the development of gastric cancer from a multi-scale perspective. This study provided a new direction for analyzing the mechanism of TCM. [ABSTRACT FROM AUTHOR]

The wireless capsule endoscopy (WCE) procedure produces tens of thousands of images of the digestive tract, for which the use of the manual reading process is full of challenges. Convolutional neural networks are used to automatically detect lesions in WCE images. However, studies on clinical multilesion detection are scarce, and it is difficult to effectively balance the sensitivity to multiple lesions. A strategy for detecting multiple lesions is proposed, wherein common vascular and inflammatory lesions can be automatically and quickly detected on capsule endoscopic images. Based on weakly supervised learning, EfficientNet is fine-tuned to extract the endoscopic image features. Combining spatial features and channel features, the proposed attention network is then used as a classifier to obtain three classifications. The accuracy and speed of the model were compared with those of the ResNet121 and InceptionNetV4 models. It was tested on a public WCE image dataset obtained from 4143 subjects. On the computer-assisted diagnosis for capsule endoscopy database, the method gives a sensitivity of 96.67% for vascular lesions and 93.33% for inflammatory lesions. The precision for vascular lesions was 92.80%, and that for inflammatory lesions was 95.73%. The accuracy was 96.11%, which is 1.11% higher than that of the latest InceptionNetV4 network. Prediction for an image only requires 14 ms, which balances the accuracy and speed comparatively better. This strategy can be used as an auxiliary diagnostic method for specialists for the rapid reading of clinical capsule endoscopes. [ABSTRACT FROM AUTHOR]

Label-specific features learning can effectively exploit the unique features of each label, which alleviates the high dimensionality and improves the classification performance of multi-label. However, most existing label-specific features learning algorithms assume that label space is complete, ignoring the effect of missing labels on the classification accuracy. Some methods try to recover the missing labels first and then learn the mapping between the completed label matrix and the feature matrix. However, early intervention in the recovery of missing labels may affect the distribution of original labels to a certain extent. In this paper, feature-label dual-mapping for missing label-specific features learning is proposed. According to the information that the label depends on the feature, the dual-mapping weight of the complete feature space and the missing label space is jointly learned. Therefore, the proposed algorithm is to conduct latent missing labels recovery by feature-label dual-mapping to directly obtain target weight in this paper, avoiding the negative influence of early label recovery intervention. Compared with several state-of-the-art methods in 10 benchmark multi-label data sets, the results show that the proposed algorithm is reasonable and effective. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon nanospheres (CNSs) were synthesized via pressure-PSSMA assisted. • Pressure-PSSMA reduced the size of CNSs by increasing the number of carbon nuclei. • Pressure-PSSMA improved the size uniformity of CNSs by shortening nucleation time. • The application performance of CNSs was better than the large-size carbon spheres. Strict control of the monodispersity and size of hydrothermal carbon nanospheres (CNSs) with a size less than 150 nm is a prerequisite for many applications. However, designing and achieving the mass production of high-quality glucose-derived CNSs have been very challenging. Herein, we successfully synthesize PCNSs-PSSMA through a simple method that is synergistically assisted by an external pressure (2.0 MPa) and a small amount of poly(4-styrenesulfonic acid-co-maleic acid) sodium salt (PSSMA). The mechanism of the external pressure and PSSMA effect on the synthesis of PCNSs-PSSMA is investigated. On the one hand, the pressure and PSSMA can increase the glucose hydrothermal carbonation (HTC) rate and increase the number of carbon nuclei. On the other hand, PSSMA adsorbs on the surface of the CNSs to inhibit their growth so that more raw materials can be used for nucleation. When limited by the raw materials, it is difficult for CNSs to continue to grow. Furthermore, we also verify that PCNSs-PSSMA is superior in terms of adsorption and catalysis to large carbon spheres prepared by traditional methods. Our findings provide potential guidance for the mass production of other small particle size nanomaterials. [ABSTRACT FROM AUTHOR]

The National Metrology Institute of Japan (NMIJ) will realize the new kilogram by the X-ray crystal density (XRCD) method using a 28Si-enriched sphere. This article describes an accurate thickness measurement of a surface layer on the Si sphere by X-ray photoelectron spectroscopy (XPS). We focused on the effect of crystal orientation of the core sphere on thickness determination by XPS. The changes in the intensities of the Si core sphere and a surface oxide along the main crystallographic directions were first investigated. The variations in intensities were enhanced, resulting in a large variation in thickness. By avoiding the lines of longitude of crystallographic planes with low plane indices, the uncertainty of the thickness of the oxide layer (OL) was reduced. The structure of the carbonaceous layer (CL), including ethanol and hydrocarbon sublayers on the sphere, was also investigated, and the average thickness and uncertainty budget were evaluated. [ABSTRACT FROM AUTHOR]

The novel Z‐scheme photocatalytic system of In2O3/OV/In2S3 has been obtained by a facile two‐step in situ deposition method, where oxygen vacancies and In2S3 are in situ located on the surface of In2O3 in sequence. In such a photocatalytic system, oxygen vacancy anchored tightly on the surface of In2O3 serves as an electron mediator, efficiently extracting electrons from In2O3 and modulating the electron transfer paths to facilize constructing a Z‐scheme system. Due to the presence of another tight contact interface between the In2O3 and In2S3, the transfer rate of electrons from In2O3 to In2S3 can be further accelerated. Therefore, the synergistic effect of the above‐mentioned dual‐tight contact interface over In2O3/OV/In2S3 Z‐scheme system simultaneously enhances the charge separation and transfer, resulting in the high performance of photocatalytic H2 evolution. [ABSTRACT FROM AUTHOR]

Edible pentacyclic triterpenes (PTs) are a group of nutraceutical ingredients commonly distributed in human diets. Existing evidence has proven that they have various biological functions, including anticancer, antioxidant, anti-inflammatory and hypoglycemic activities, making them as "functional factor" for a long time. However, their properties of strong hydrophobicity, poor permeability, poor absorption, and rapid metabolism result in low oral bioavailability, which dramatically hinders their efficacy for use. Recently, free PTs have successively been found to self-assemble or co-assemble into self-contained nanostructures with enhanced water dispersibility and oral bioavailability, which seems to be an efficient processing method for increased oral efficacy. Of particular interest, formulating them into nanostructures can also be introduced as functional delivery carriers for bioactive compounds or drugs with various advantages, such as improved stability, controlled release, enhanced oral bioavailability, synergistic bioactivity, and targeted delivery. This review systematically summarized the chemical structures, plant sources, bioactivities, absorption, metabolism, and oral bioavailability of PTs. Notably, we emphasized their self-assembly properties and emerging role as functional delivery carriers for nutrients, suggesting that PT nanostructures are not only efficient oral forms when introduced into foods but also functional delivery materials for nutrients to expand their commercial food applications. [ABSTRACT FROM AUTHOR]

Background: Parental psychopathology is associated with their children's posttraumatic stress symptoms (PTSS). However, the mechanisms through which this occurs remain unclear. We hypothesized that exposure to childhood adversities is the mechanism linking parental psychopathology to child PTSS and that parenting practices moderated these associations. Methods: Participants (N = 1,402) with an average age of 24.03 years old (SD = 2.20), were all Puerto Ricans (50% Male and 50% Female) from the Boricua Youth Study, which is a four‐wave longitudinal study spanning almost 20 years, following individuals from childhood (ages 5–13 at Wave 1) to young adulthood. Measured variables include parental psychopathology at Wave 1, childhood adversities and parenting practices at Waves 2–3, and PTSS at Wave 4. A traditional mediation model estimated the association between parental psychopathology and child PTSS via childhood adversities. A moderated mediation model was used to examine whether parenting practices moderated this mediation model. Results: Results showed that the total effect of parental psychopathology at Wave 1 on PTSS at Wave 4 was fully mediated by childhood adversities at Waves 2–3 (direct effect b = 1.72, 95% CI = [−0.09, 3.83]; indirect effect b = 0.40, 95% CI = [0.15, 0.81]). In addition, the magnitude of this pathway varied by levels of parenting practices (i.e. parental monitoring and parent–child relationship quality). Specifically, the indirect effect of additional adversities in the psychopathology‐PTSS link was stronger with higher levels of parental monitoring but weaker with higher parent–child relationship quality scores. Conclusions: Intergenerational continuity of psychopathology may be mitigated through the prevention of additional childhood adversities via upstream interventions, emphasizing providing parents with mental health needs with parenting tools. Family‐based interventions focused on providing families with the tools to improve parent–child relationships may reduce the negative impact of childhood adversities on mental health across the life course. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a Bayesian optimization algorithm, a deep neural network is structured to evaluate the whole charging curve of the battery using partial charging curve data as input. A 0.74 Ah battery is used for experiments, and the effect of different input data lengths is also investigated to check the high flexibility of the approach. The consequences show that using only 20 points of partial charging data as input, the whole charging profile of a cell can be exactly predicted with a root-mean-square error (RMSE) of less than 19.16 mAh (2.59% of the nominal capacity of 0.74 Ah), and its mean absolute percentage error (MAPE) is less than 1.84%. In addition, critical information including battery state-of-charge (SOC) and state-of-health (SOH) can be extracted in this way to provide a basis for safe and long-lasting battery operation. [ABSTRACT FROM AUTHOR]

Purpose: Despite increased attention to the positive development of left-behind adolescents, research findings remain inconclusive. Utilizing latent profile analysis, we identified various positive development profiles among the left-behind adolescents and explored the association between resilience and positive development profiles, alongside the mediating role of making sense of adversity. Methods: A multi-stage cluster sampling procedure was employed, randomly selecting four provinces–Zhejiang, Guangdong, Henan, and Jiangxi–from the central and coastal regions. The sample comprised 718 left-behind adolescents recruited from primary and junior high schools across grades 4, 5, 7, and 8. Three scales were utilized, and analyses included latent profile analysis and mediation analysis. Results: Three latent subgroups of positive development among left-behind adolescents were identified: low, moderate, and high. Those with higher resilience and positive perceptions of adversity tended to belong to the high group rather than the low (β = − 0.45, p < 0.001; β = − 0.09, p < 0.001) or moderate group (β = − 0.23, p < 0.001; β = − 0.04, p < 0.05). Left-behind adolescents with higher negative perceptions of adversity tended to belong to the high group rather than the moderate group (β = − 0.07, p < 0.01). Mediation analysis revealed that resilience facilitated the development of positive appraisals of adversity, subsequently increasing the likelihood of being categorized into the high (95% CI of − 0.09 to − 0.03) or moderate group (95% CI of − 0.05 to − 0.01) rather than the low group. Conclusion: These findings hold significant implications for intervention formulation. Educators should focus on strengthening resilience and fostering positive perceptions of adversity among the low group. For the moderate group, maintaining moderate negative perceptions of adversity may stimulate the intrinsic potential for positive development more effectively. [ABSTRACT FROM AUTHOR]

Key message: Endogenous hydrogen peroxide (H2O2) is involved in regulating the gibberellic acid-induced programmed cell death (PCD) of the aleurone layers by cooperating with OsVPE3 during rice seed germination. Preliminary experiments revealed that H2O2 produced by the NOX pathway is the key factor affecting rice germination. Histochemical analysis indicated that H2O2 is located in the aleurone layer. Both the H2O2 scavenger DMTU and the NOX inhibitor DPI decreased H2O2 content and significantly slowed down vacuolation in a dose-dependent manner. Interestingly, DMTU down-regulated the OsNOX8 transcript or DMTU and DPI decreased the intracellular H2O2 level, resulting in a delay of PCD. In contrast, GA and H2O2 up-regulated the OsNOX8 transcript and intracellular H2O2 level, leading to premature PCD, and the effects of GA and H2O2 were reversed by DMTU and DPI, respectively. These results showed that the imbalance of intracellular H2O2 levels leads to the delayed or premature PCD. Further experiments indicated that GA up-regulated the OsVPE3 transcript and VPE activity, and the effect was reversed by DPI. Furthermore, Ac-YVAD-CMK significantly blocked H2O2 accumulation, and DPI + Ac-YVAD-CMK had a more significant inhibitory effect compared with DPI alone, resulting in the delayed PCD, suggesting that OsVPE3 regulates PCD by promoting H2O2 generation. Meanwhile, DPI significantly inhibited the OsVPE3 transcript and VPE activity, and in turn delayed PCD occurrence, suggesting that the H2O2 produced by the NOX pathway may regulate PCD by up-regulating the OsVPE3 transcript. Thus, the endogenous H2O2 produced by the NOX pathway mediates the GA-induced PCD of rice aleurone layers by interacting with OsVPE3. [ABSTRACT FROM AUTHOR]

This paper probes into the synchronization for memristor-based hybrid neural networks via nonlinear coupling. At first, a new condition is established to judge whether quadratic functions are negative or not on a closed interval regardless of their concavity or convexity. Then, by utilizing Legendre orthogonal polynomials, a recent extended integral inequality with free matrices is popularized to get tighter lower bound of some integral terms. Next, based on a novel Lyapunov functional, by applying our new integral inequality with free matrices, linear convex combination method and the new criterion, a new delay-dependent condition is gained to reach the global synchronization for the considered neural networks. At last, an example is presented to account for the validity of our results. [ABSTRACT FROM AUTHOR]

The voltage‐gated sodium channel (VGSC) currents in dorsal root ganglion (DRG) neurons contain mainly TTX‐sensitive (TTX‐S) and TTX‐resistant (TTX‐R) Na+ currents. Magnolol (Mag), a hydroxylated biphenyl compound isolated from the bark of Magnolia officinalis, has been well documented to exhibit analgesic effects, but its mechanism is not yet fully understood. The aim of the present study was to investigate whether the antinociceptive effects of Mag is through inhibition of Na+ currents. Na+ currents in freshly isolated mouse DRG neurons were recorded with the whole cell patch clamp technique. Results showed that Mag inhibited TTX‐S and TTX‐R Na+ currents in a concentration‐dependent manner. The IC50 values for block of TTX‐S and TTX‐R Na+ currents were 9.4 and 7.0 μmol/L, respectively. Therefore, TTX‐R Na+ current was more susceptible to Mag than TTX‐S Na+ current. For TTX‐S Na+ channel, 10 μmol/L Mag shifted the steady state inactivation curve toward more negative by 9.8 mV, without affecting the activation curve. For TTX‐R Na+ channel, 7 μmol/L Mag shifted the steady state activation and inactivation curves toward more positive and negative potentials by 6.5 and 11.7 mV, respectively. In addition, Mag significantly postponed recovery of TTX‐S and TTX‐R Na+ currents from inactivation, and produced frequency dependent blocks of both subtypes of Na+ currents. These results suggest that the inhibitory effects of Mag on Na+ channels may contribute to its analgesic effect. [ABSTRACT FROM AUTHOR]

Endogenous sulfur dioxide is a novel inhibitor of hypoxia-induced mast cell degranulation. Endogenous SO 2 /AAT pathway exists in MCs. Mast cell-derived SO 2 upregulates cAMP level through activation of AC and inhibition of PDE, thereby suppressing degranulation of MCs. [Display omitted] • Endogenous SO 2 /AAT pathway exists in mast cells (MCs). • Endogenous SO 2 is a novel MC membrane stabilizer under hypoxic circumstance. • MC-derived SO 2 upregulates cAMP level, thereby suppressing MC degranulation. Mast cell (MC) degranulation is an important step in the pathogenesis of inflammatory reactions and allergies; however, the mechanism of stabilizing MC membranes to reduce their degranulation is unclear. SO 2 content in MC culture supernatant was measured by HPLC-FD. The protein and mRNA expressions of the key enzymes aspartate aminotransferase 1 (AAT1) and AAT2 and intracellular AAT activity were detected. The cAMP level in MCs was detected by immunofluorescence and ELISA. The release rate of MC degranulation marker β-hexosaminidase was measured. The expression of AAT1 and cAMP, the MC accumulation and degranulation in lung tissues were detected. To exam whether an endogenous sulfur dioxide (SO 2) pathway exists in MCs and if it serves as a novel endogenous MC stabilizer. We firstly show the existence of the endogenous SO 2 /AAT pathway in MCs. Moreover, when AAT1 was knocked down in MCs, MC degranulation was significantly increased, and could be rescued by a SO 2 donor. Mechanistically, AAT1 knockdown decreased the cyclic adenosine monophosphate (cAMP) content in MCs, while SO 2 prevented this reduction in a dose-independent manner. Pretreatment with the cAMP-synthesizing agonist forskolin or the cAMP degradation inhibitor IBMX significantly blocked the increase in AAT1 knockdown-induced MC degranulation. Furthermore, in hypoxia-stimulated MCs, AAT1 protein expression and SO 2 production were markedly down regulated, and MC degranulation was activated, which were blunted by AAT1 overexpression. The cAMP synthesis inhibitor SQ22536 disrupted the suppressive effect of AAT1 overexpression on hypoxia-induced MC degranulation. In a hypoxic environment, mRNA and protein expression of AAT1 was significantly reduced in lung tissues of rats. Supplementation of SO 2 elevated the cAMP level and reduced perivascular MC accumulation and degranulation in lung tissues of rats exposed to a hypoxic environment in vivo. SO 2 serves as an endogenous MC stabilizer via upregulating the cAMP pathway under hypoxic circumstance. [ABSTRACT FROM AUTHOR]

Background. At present, the diagnostic accuracy of alpha-fetoprotein (AFP) for hepatocellular carcinoma (HCC) surveillance is insufficient. It remains controversial whether prothrombin induced by vitamin K absence II (PIVKA-II) has a better diagnostic value than AFP for HCC patients. Objective. To investigate the diagnostic role of PIVKA-II alone or in combination with AFP in Chinese HCC patients. Methods. Serum AFP and PIVKA-II levels were detected and analyzed in 308 HCC afflicted patients and 120 unafflicted controls. The receiver operator curve (ROC) and area under the curve (AUC) were conducted to evaluate the clinical value of AFP and PIVKA-II for diagnosing HCC and early HCC. Results. In the whole HCC cohort, the diagnostic values of PIVKA-II were better than that of AFP. The AUC of PIVKA-II and AFP was 0.90 (95% CI 0.87-0.94) and 0.79 (95% CI 0.74-0.84), respectively. "AFP + PIVKA-II" yielded a high sensitivity of 95.1% and a specificity of 83.3%, with the AUC 0.89 (95% CI 0.85-0.93). In the early stage HCC group, the diagnostic accuracy of PIVKA-II was also better than that of AFP. The AUC of PIVKA-II and AFP was 0.83 (95% CI 0.77-0.89) and 0.75 (95% CI 0.68-0.81), respectively. "AFP + PIVKA-II" achieved the sensitivity of 83.3% and specificity of 89.1%, with an AUC of 0.86 (95% CI 0.81-0.91). Moreover, for AFP-negative HCC patients, serum PIVKA-II showed good diagnostic performance, with an AUC of 0.804 (95% CI 0.720-0.887). Besides, elevated PIVKA-II level was a strong independent risk factor for HCC patients with portal vein tumor thrombus (PVTT) (OR = 4.890 , P = 0.020). Conclusion. PIVKA-II is superior to AFP in HCC screening, and AFP in combination with PIVKA-II significantly improves the diagnostic value for Chinese HCC patients. PIVKA-II could effectively indicate HCC accompanied by PVTT and help to optimize the therapeutic strategy. [ABSTRACT FROM AUTHOR]

In the rapidly changeable market, product innovation is critical for enterprises to improve their product competitiveness. Product innovation can be described as an evolutionary process of technical systems where the relationship between technologies follows the evolution from parasitism to symbiosis in technological parasitism theory. The existing research on the technological parasitism theory mainly focuses on explaining and verifying the evolution law of product systems from parasitism to symbiosis in the product innovation process. However, these research activities are a post-hoc summary, which limits the guidance for enterprises to proactively realize the evolution of products from parasitism to symbiosis in an ex-ante perspective. For the development of innovative products in the engineering field, enterprises lack an effective ex-ante design method to proactively find the appropriate parasitic technology, and integrate it with the host technology for the product system evolving towards a symbiotic state. To fill this gap, this paper proposes a product innovation design process based on the recombination of host and target genes under the technological parasitism framework. Product scenario analysis is used to explore the potential function needs to determine the search direction of parasitic technologies. The min-complement distance measure method is introduced to identify the appropriate parasitic technology. Based on four recombination operations, the construction process of new product genome through the recombination of host and target genes is proposed. The concept of new product is formed through the transcription of the product genome. The final scheme is developed objectively by using the coefficient variation method and Dempster combination rule. The proposed method is applied in the ex-ante design of a Chinese medicine dispensing machine for its feasibility and effectiveness. [ABSTRACT FROM AUTHOR]

Chronic high sodium dietary intake is largely associated with the pathogenesis of some cardiovascular diseases, and processed solid foods are the main contributors to human sodium intake. Although many strategies have been effectively used to control sodium levels in these foods, reducing NaCl often leads to loss of flavor and reduced consumer acceptability. Therefore, a strategy for sodium reduction that maintains acceptability, especially applicable to solid foods, requires further research. One effective and applicable strategy is particle size reduction, which involves preparing NaCl microcrystals or nanocrystals to enhance saltiness in solid foods. The common strategies for sodium reduction in solid foods have been presented, followed by a discussion of various representative top-down, bottom-up, and combination technologies for crystal size reduction. Additionally, the factors influencing the application of NaCl microcrystals in solid foods, as well as the evaluation methods for assessing the saltiness enhancement effect, have been discussed. This article provides a comprehensive and practical sodium reduction strategy in solid food development while maintaining consumer acceptance from a long-term perceptive. • Reducing particle size effectively decreases sodium content. • A combination technology efficiently prepares NaCl microcrystals. • Both cellular and animal models are useful for evaluating saltiness enhancement. • Sensory evaluation methods are applicable for assessing the enhancement of saltiness. [ABSTRACT FROM AUTHOR]

[Display omitted] • Structure-property relationships of MOFs were established with the capture of CWAs. • The number of hydrogen bond acceptors was a key factor governing the co-adsorption of CWAs by machine learning. • The similarities of top-performing MOFs were defined for the metals, organic links and topology. To effectively capture the low-concentration chemical warfare agents (CWAs) and their simulants which are extremely harmful to human health and environment, the properties of thousands of Computation-Ready, Experimental Metal-Organic Frameworks (CoRE-MOFs) for the adsorption and separation of four CWAs and simulants (dimethyl methyl phosphonate, soman, mustard gas, and 2-chloroethyl ethyl sulfide) from the air were calculated by high-throughput computational screening. To reasonably identify the top-performing MOFs, the trade-off between selectivity and adsorption capacity (TSN) was introduced to measure the properties of MOFs. Five machine learning algorithms were employed to quantitatively evaluate the structure-performance relationships of MOFs for the adsorption of CWAs and validate that Extreme Gradient Boosting algorithms had the best prediction accuracy. Furthermore, four MOF descriptors (henry coefficient, number of hydrogen bonds, porosity, and volumetric surface area) were found to have significant influence on the properties of MOFs. Finally, it was determined that the number of hydrogen bond acceptors was a key factor governing the co-adsorption of CWAs and their simulants, and the similarities of adsorbents with good adsorption performance included Zn for metal center, trimesic acid for organic linker, and srs for topology. The microscopic insights obtained from our bottom-up approach are very helpful for the development of MOFs and other nanoporous materials for the capture of CWAs from the air. [ABSTRACT FROM AUTHOR]

This study aims to explore the relationship between e-cigarette social environment exposure, perceptions, and susceptibility. We surveyed 4290 middle school students aged 13–18 in Shanghai, China. A multivariate logistic regression was performed to assess the correlation of e-cigarette social environment exposure, perceptions, and susceptibility in adolescents. A structural equation model was performed to explore the mediation effects of perception. It was found that there was a high rate of social environment exposure to e-cigarettes among adolescents in Shanghai, China. The exposure rate of e-cigarette secondhand aerosol, e-cigarette sales, and e-cigarette information was 42.1%, 69.1%, and 82.3%, respectively. E-cigarette social environment exposure could not only directly affect e-cigarette susceptibility, but also played a role through the mediation effect of perceptions, which accounted for 37.48%. E-cigarette exposure had a greater impact on benefit perceptions than harm perceptions. The influence of various types of e-cigarette exposure and perceptions on susceptibility was different. Among the exposure factors, the risk of secondhand aerosol exposure was the highest (OR = 1.56, 95% CI: 1.16–2.11). Among the perceptual factors, the risk of self-benefit perception was the highest (OR = 4.06, 95% CI: 2.91–5.68), and the risk of socio-environmental benefit perception was the lowest (OR = 1.85, 95% CI: 1.40–2.45). Hence, it is necessary to supervise exposure to e-cigarettes more strictly and strengthen the education of adolescents on e-cigarette cognition. [ABSTRACT FROM AUTHOR]

This paper reports laboratory testing and numerical modelling on the cross-sectional behaviour and resistances of press-braked S690 high strength steel slender channel section stub columns under combined compression and minor-axis bending. A testing programme, including initial geometric imperfection measurements and ten minor-axis eccentric compression tests, was firstly conducted. This was accompanied by a numerical modelling programme, including a validation study, where finite element models were developed and validated against test results, and a series of parametric studies, where the validated finite element models were used to generate further numerical data. The obtained test and numerical data were then adopted to evaluate the current codified design interaction curves for press-braked S690 high strength steel slender channel section stub columns under combined compression and minor-axis bending, as provided in the European code, North American specification and Australian/New Zealand standard. The evaluation results revealed that the codified design interaction curves led to conservative and scattered resistance predictions, mainly due to the conservative end points (i.e. the cross-section compression and bending resistances). Finally, a new design interaction curve, anchored to more accurate end points, was proposed and shown to result in a higher level of design accuracy and consistency than the codified design interaction curves. • The behaviour of S690 high strength steel slender channel sections under minor-axis combined loading was studied. • Minor-axis eccentric compression tests were carried out. • FE models were developed and validated against the test results and then used to perform parametric studies. • The codified design interaction curves were evaluated, revealing a high level of conservatism. • A new interaction curve, anchored to the CSM end points, was proposed and shown to yield higher design accuracy. [ABSTRACT FROM AUTHOR]

The characterization of in situ ground conditions is essential for geotechnical practice. The probabilistic estimation of soil parameters can be achieved via updating with monitoring data within the Bayesian framework. The estimation of spatially varying soil parameters is seldom undertaken with time-variant monitoring data. In this study, an efficient Bayesian method is presented for the estimation of spatially varied saturated hydraulic conductivity ks of unsaturated soil slope with spatiotemporal monitoring data. The computationally cheap surrogate model of the adaptive sparse polynomial chaos expansion method is adopted to approximate the transient numerical model. Markov chain Monte Carlo method is used for the probabilistic estimation of basic random variables. Based on the hypothetical cases, the effects of monitoring frequency and stage are studied. The errors and the uncertainties of the estimated ks fields are increased with the decreasing monitoring frequency. Bayesian estimation of spatial variability is more accurate when using the later stage of monitoring data. The estimated method is further verified with a real case study by the comparison of borehole data, dynamic probe test (DPT) data, and field monitoring data. The distribution of the soil types acquired from boreholes is reflected in the estimated ks. The estimated field of ks has a certain agreement with the borehole log and DPT measurements and can reproduce the spatial variability of the site to an acceptable degree. [ABSTRACT FROM AUTHOR]

Coronavirus Disease 2019 (COVID-19) has caused a global pandemic. Here we profiled the humoral response against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by measuring immunoglobulin (Ig) A, IgM, and IgG against nucleocapsid and spike proteins, along with IgM and IgG antibodies against receptor-binding domain (RBD) of the spike protein and total neutralizing antibodies (NAbs). We tested 279 plasma samples collected from 176 COVID-19 patients who presented and enrolled at different stages of their disease. Plasma dilutions were optimized and based on the data, a single dilution of plasma was used. The mean absorbance at 450 nm was measured for Ig levels and NAbs were measured using geometric mean titers. We demonstrate that more severe cases have a late-onset in the humoral response compared to mild/moderate infections. All the antibody titers continue to rise in patients with COVID-19 over the disease course. However, these levels are mostly unrelated to disease severity. The appearance time and titers of NAbs showed a significant positive correlation to the antibodies against spike protein. Our results suggest the late onset of antibody response as a risk factor for disease severity, however, there is a limited role of antibody titers in predicting disease severity of COVID-19. Lili Ren et al. investigate antibody response from 176 COVID-19 patients who presented different stages of their disease. This study suggests the late onset of antibody response as a risk factor for disease severity and a limited role of antibody titers in predicting the disease severity of COVID-19. [ABSTRACT FROM AUTHOR]