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The mass specific rates and propylene selectivity of ZnO catalysts exhibit a volcano relation with the size of ZnO in the propane dehydrogenation (PDH) reaction.

The adherent colonization of lactic acid bacteria in the animal intestine is the basis for their probiotic effect, and their bacteria surface proteins play an important role in this process. Previous work has demonstrated that Lactobacillus plantarum HC-2 can adhere and colonize the intestine of Penaeus vannamei, modulate the intestinal immune response and microbial diversity, protect the intestinal tissues from pathogenic damage, and improve the protection rate of shrimp. The aim of this work was to identify adhesion molecules on the surface of HC-2 and its adhesion receptors in the intestinal epithelium of shrimp. The elongation factor Tu (EF-Tu) on the surface of HC-2 was found to interact with Fibronectin (Fib) in the shrimp intestine by immunoblotting and yeast two-hybrid assays, and this interaction relationship was verified by immunoprecipitation (Co-IP). The adhesion of HC-2 to Caco-2 cells could be blocked via EF-Tu antibody confinement, and the adhesion of Fib to HC-2 could be blocked by Fib antibody confinement. Expression of Fib on the surface of HEK293T cells revealed a significant increase in the adhesion rate of HC-2 to HEK293T cells. Using immunofluorescence, a significant reduction in HC-2 adhesion to the intestine of shrimp was observed after blocking the Fib site in the shrimp intestine, particularly in Vibrio parahaemolyticus E1-infected intestines. In addition, the recombinant protein rEF-Tu was found to promote the growth of Caco-2 cells in a certain concentration range and significantly inhibit the apoptosis induced by LPS, Staphylococcus aureus and V. parahaemolyticus E1. Our results indicate that EF-Tu might participate in gut immunity and homeostasis, through its binding to the shrimp intestinal cells and inhibiting apoptosis.

Based on the deforming technique of severe plastic deformation (SPD), the grain refinement of a Mg-9Gd-3Y-2Zn-0.5Zr alloy treated with decreasing temperature reciprocating upsetting-extrusion (RUE) and its influence on the mechanical properties and wear behavior of the alloy were studied. The RUE process was carried out for 4 passes in total, starting at 0 °C and decreasing by 10 °C for each pass. The results showed that as the number of RUE passes increased, the grain refinement effect was obvious, and the second phase in the alloy was evenly distributed. Room temperature tensile properties of the alloy and the deepening of the RUE degree showed a positive correlation trend, which was due to the grain refinement, uniform distribution of the second phase and texture weakening. And the microhardness of the alloy showed that the microhardness of RUE is the largest in 2 passes. The change in microhardness was the result of dynamic competition between the softening effect of DRX and the work hardening effect. In addition, the wear resistance of the alloy showed a positive correlation with the degree of RUE under low load conditions. When the applied load was higher, the wear resistance of the alloy treated with RUE decreased compared to the initial state alloy. This phenomenon was mainly due to the presence of oxidative wear on the surface of the alloy, which could balance the positive contribution of severe plastic deformation to wear resistance to a certain extent.

Three-dimensional (3D) graphene-based aerogels have promising applications in oil adsorption and environmental restoration. However, current research of graphene-based aerogels is often hindered by high preparation cost, poor mechanical properties and low recycling efficiency. Here, super-elastic graphene aerogel (SGA) was prepared through one-step freezing and twice hydrothermal reduction followed by drying under ambient pressure. The simple atmospheric drying provides a possibility for large-scale preparation of high performance graphene-based aerogels. The prepared SGA not only has the ability of highly repeatable compression rebound, but also exhibits excellent oil adsorption performance. And the overall performance of SGA is better than most of graphene-based aerogels prepared by freeze drying. After the SGA was cyclically compressed with 70% strain for 300 times, it can return to the original shape and height substantially. SGA retained about 90% of the initial adsorption capacity after 50 cycles of adsorption and compression regeneration for cyclohexane.

A class of silica anchored Schiff base decorated polyamidoamine (PAMAM) dendrimers were synthesized for removing aqueous Cu(II) and Ag(I). The adsorption performance was investigated synthetically and the adsorption mechanism was revealed. Results indicate the adsorption capacity depends on dendrimer generation, solution pH, contact time, temperature and initial metal ion concentration. The optimum adsorption pH is 6 for both metal ion. Adsorption kinetic suggests the adsorption can achieve equilibrium at 180 and 150 min for Cu(II) and Ag(I). The kinetic process is found to be in good agreement with pseudo-second-order model and film diffusion is the rate-controlling step. The adsorption isotherm indicates the adsorption is proceeded by monolayer behavior with chemical mechanism. These adsorbents exhibit competitive adsorption capacity as compared with other reported adsorbents. Theoretical calculation demonstrates the participation of hydroxyl, carbonyl, and amide groups during the adsorption of Cu(II), while hydroxyl and amide groups are mainly responsible for capturing Ag(I).

Aims Short-term blood pressure (BP) time in target range (TTR) independently predicts cardiovascular (CV) outcomes in adults. However, there are limited data regarding long-term TTR for BP among elderly participants. We aimed to determine whether future CV risk varies for those who can maintain a long-term systolic BP (SBP) target range by assessing TTR in elderly individuals with hypertension. Methods and results The Chinese veteran cohort study included 943 elderly participants with hypertension aged over 75 years. The primary outcome was the first occurrence of CV events during annual visits. Time in target range was estimated over 15 years of follow-up using linear interpolation. The target range was defined as 120–140 mmHg according to guidelines. The association between SBP TTR and CV outcomes was estimated using multivariable Cox proportional hazards models. During the 15 year follow-up, the probability of CV events gradually decreased with increasing TTR for SBP. After multivariable adjustment for traditional CV risk factors and mean BP, comparing the highest vs. lowest quartiles of TTR for SBP, the hazard ratios (HRs) [95% confidence intervals (CIs)] were 0.424 (0.289–0.624) for the primary outcome. For each 1 SD increase in TTR, the risk of the primary outcome decreased by 25.4% (HR: 0.746; 95% CI: 0.666–0.834). Consistent findings were observed in sensitivity analyses. Conclusion Greater long-term TTR for SBP was associated with a decreased risk of CV events in elderly individuals independent of mean BP, suggesting that SBP TTR might serve as a modifiable risk factor for future CV health in elderly patients with hypertension.

We fabricated a nanowire-channel intrinsically stretchable neuromorphic transistor (NISNT) that perceives both tactile and visual information and emulates neuromorphic processing capabilities. The device demonstrated excellent stretching endurance of 1000 stretch cycles while retaining stable electrical properties. The device was then applied as a multisensitive afferent nerve that processes information in parallel. Compatible with skin deformation, the devices are attached to fingers to serve as conformal strain sensors and neuromorphic information-processing units for gesture recognition. The excitatory postsynaptic current in each device represents shape changes and is then analyzed using softmax activation processing of the neural network to recognize gestures. A multistage neural network that uses NISNT was used to further confirm the gestures. This work demonstrated an idea toward multisensory artificial nerves and neuromorphic systems.

Water security caused by heavy metals poses a deleterious hazard to public health and the ecological system. The construction of adsorbents by polyamidoamine (PAMAM) dendrimers for efficient removal of metal ions has attracted considerable interest. However, the general method for the fabrication of these adsorbents was achieved by the surface chemical modification of the substrates with PAMAM dendrimer, which usually causes the defects of low density and uneven distribution of the dendrimer, the blocking of pores, and reducing the adsorption performance. Hence, the development of a new method for preparation of PAMAM dendrimer-based adsorbent to realize the efficient and enhanced adsorption of metal ions is still a challenge. Herein, methylisothiocyanate decorated PAMAM dendrimer/mesoporous silica composites (G0-S-1/

This review summarizes the adhesion mechanism and design strategies of underwater adhesion hydrogels, and generalizes their underwater application fields (adhesives, motion monitoring, marine environmental exploration and coatings).

At present, there are great technical difficulties in achieving microstructure and mechanical properties uniformity in large-size billets prepared by severe plastic deformation technology. How to improve the process route to realize the microstructure and mechanical properties uniformity of the billets has become an urgent problem to be solved at present. In this paper, GWZ932K alloy is used for two reciprocating upsetting-extrusion (RUE) deformation methods with a cumulative strain of 5.38. The influence of isothermal temperature reciprocating upsetting-extrusion (IT-RUE) and decreasing temperature reciprocating upsetting-extrusion (DT-RUE) on the microstructure and mechanical properties uniformity of GWZ932K alloy is discussed in detail. The results show both IT-RUE and DT-RUE deformation methods can effectively refine grains. IT-RUE can prepare Mg alloy billet with uniform microstructure and mechanical properties from center region (CR) to edge region (ER). The microstructure and mechanical properties of the billet prepared by DT-RUE show obvious gradient characteristics from CR to ER. After 4 passes IT-RUE deformation, double-peak textures appear on the (0001) basal texture of the ER, middle region (1/2R) and CR, which is mainly attributed to the occurrence of dynamic recrystallization (DRX) behavior. It should be noted that changes in the deformation temperature will not cause changes in the DRX mechanism. The deformation mechanisms of continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) jointly promote grain refinement.

The mechanisms, common properties and biological applications of different types of metal ion hydrogels are summarized.

The microenvironment surrounding the metal clusters on a carrier produces a tremendous influence on its catalytic performance. In this work, the promotion effect of the zeolitic inner host on catalytic performance of encapsulated platinum nanoclusters is reported. In the reaction of phenylacetylene semihydrogenation to styrene, Pt@X-zeolite, where platinum nanoclusters are encapsulated into the inner microporosity of the X-zeolite, exhibits an ∼3.37 times increased turnover frequency and a much better selectivity of 87.6% in comparison to the referenced Pt/X-zeolite of 79.3% selectivity to styrene at the same reaction conditions, in which the platinum nanoclusters are located at the exterior of the zeolite. Meanwhile, the Pt@X-zeolite displays a higher stability after 10 cycles of the reaction. Through the detailed characteristics, the excellent performance of Pt@X-zeolite is mainly due to the promotion of the zeolitic framework on the encapsulated Pt clusters, resulting in "electron-deficient" Pt clusters, leading to a stronger interaction with the π* molecular orbitals of phenylacetylene and thus enhancing the activation and conversion of phenylacetylene. The zeolite cavity wrapped with encapsulated Pt clusters regulates the adsorption trend of phenylacetylene through the acetylene group on it, promotes the desorption of styrene, and strengthens its selectivity. Meanwhile, Pt@X-zeolite has an excellent stability through the zeolite framework, which protects the Pt species from being lost. This investigation reveals the importance of the zeolitic microenvironment on the catalytic performance of encapsulated metal species and deepens the cognition for this type of catalyst.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and its early detection is critical for preventing complications and optimizing treatment. In this study, a novel AF prediction method is proposed, which is based on investigating a subset of the 12-lead ECG data using a recurrent plot and ParNet-adv model. The minimal subset of ECG leads (II &V1) is determined via a forward stepwise selection procedure, and the selected 1D ECG data is transformed into 2D recurrence plot (RP) images as an input to train a shallow ParNet-adv Network for AF prediction. In this study, the proposed method achieved F1 score of 0.9763, Precision of 0.9654, Recall of 0.9875, Specificity of 0.9646, and Accuracy of 0.9760, which significantly outperformed solutions based on single leads and complete 12 leads. When studying several ECG datasets, including the CPSC and Georgia ECG databases of the PhysioNet/Computing in Cardiology Challenge 2020, the new method achieved F1 score of 0.9693 and 0.8660, respectively. The results suggested a good generalization of the proposed method. Compared with several state-of-art frameworks, the proposed model with a shallow network of only 12 depths and asymmetric convolutions achieved the highest average F1 score. Extensive experimental studies proved that the proposed method has a high potential for AF prediction in clinical and particularly wearable applications.

Seasonal patterns of marine net primary production (NPP) are crucial for understanding the marine ecosystem and biogeochemical cycles. Uncoupling of seasonal variations between NPP and phytoplankton chlorophyll-a over different areas has attracted much attention. In this study, following a review of previous studies, monthly climatological NPP data from 2003 to 2020, estimated using the Size-fractioned Phytoplankton Pigment Absorption (aph)-based NPP Model (SABPM), were selected to study the seasonal variability of NPP in the South China Sea (SCS). Results showed the spatial differences of NPP seasonality and its departures from climatology in extreme El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) years. Cluster analysis for climatological monthly data identified significant differences of NPP seasonality in five typical regions. In coastal regions along the northern SCS and off eastern Vietnam, NPP exhibited the most obvious seasonal cycle with maximum (minimum) values in summer (winter), attributable mainly to river discharge and summer upwelling. In regions off northwestern Luzon and coast of southern SCS, NPP showed peaks in winter, which were related to strong mixing and upwelling. In northwestern SCS, NPP was high during May–September in phase with sea surface temperature and the primary controlling factors were found to be shallow nutricline depth and wind-driven mixing. Owing to the deep nutricline depth in the central basin, NPP exhibited little seasonal variability; only a weak signal was observed in spring in phase with photosynthetically active radiation. Local dynamics on regulating the nutrient supply and light availability contribute to these regional differences in NPP seasonality, which could also be affected by extreme climate events. The largest anomalies of the NPP seasonal cycle coincide with 2015/2016 ENSO and super IOD in 2020. During these events, enhanced (weakened) westerly winds caused fall (rise) of SLA and increase (decrease) of NPP in coastal regions along the northern SCS and that off eastern Vietnam. Overall, theaph-based model shows a new perspective to study the spatiotemporal variations of NPP in the SCS.

Miniaturized rotors based on Marangoni effect have attracted great attentions due to their promising applications in propulsion and power generation. Despite intensive studies, the development of Marangoni rotors with high rotation output and fuel economy remains challenging. To address this challenge, we introduce an asymmetric porosity strategy to fabricate Marangoni rotor composed of thermoresponsive hydrogel and low surface tension anesthetic metabolite. Combining enhanced Marangoni propulsion of asymmetric porosity with drag reduction of well-designed profile, our rotor precedes previous studies in rotation output (~15 times) and fuel economy (~34% higher). Utilizing thermoresponsive hydrogel, the rotor realizes rapid refueling within 33 s. Moreover, iron-powder dopant further imparts the rotors with individual-specific locomotion in group under magnetic stimuli. Significantly, diverse functionalities including kinetic energy transmission, mini-generator and environmental remediation are demonstrated, which open new perspectives for designing miniaturized rotating machineries and inspire researchers in robotics, energy, and environment.

Mesocarp color is an important agronomic trait of Cucurbita maxima and is determined mainly by the contents and compositions of the carotenoids. The two inbred lines with significant differences in fruit flesh color were used in the study, the orange ‘312-1’ and white ‘98-2’. Changes in seven carotenoid contents and compositions in the flesh of fruit produced by inbred lines ‘312-1’ and ‘98-2’ were analyzed during fruit development. The expression of eight key carotenoid biosynthesis genes in the fruit flesh were investigated during five fruit development stage in two inbred lines. As the flesh color intensified, the orange flesh color of ‘312-1’ was determined mainly by the increased contents of lutein, β-carotene and zeaxanthin and the lack of carotenoid accumulation led to the formation of white flesh in ‘98-2’ fruit. The expression of the LCY-e and CHYb genes was significantly stronger in ‘312-1’ than in ‘98-2’, and their expression was strongly correlated with lutein and β-carotene contents during fruit development. This study provides a deep understanding of the molecular mechanism of carotenoid biosynthesis in fruit flesh and provides a basis for additional studies on the highly refined improvement of squash quality.

Although the salient object detection method based on the fully convolutional neural network has achieved better performance, how to learn effective feature representations in complex scenes to obtain more accurate saliency maps is still a challenge. In order to cope with the above-mentioned challenges, an addition or cascade structure is generally used to fuse feature information between multiple levels. However, these methods are susceptible to the influence of messy background information. The network may regard non-salient objects with similar salient appearances as target predictions, and the prediction results may be incomplete due to different appearance areas of salient objects. We design a network composed of multiple attention mechanisms to selectively integrate deep and shallow feature information, and more effectively deal with the transfer and fusion of features. In this paper, we propose a multi-attention embedded network (MAENet), which introduces attention mechanisms to give different feature information with different weights for handling the transfer and aggregation of features at different levels. The multi-attention feature aggregation (MAFA) module is proposed, which uses the channel attention mechanism to give different weights to the features to be fused, and then uses the spatial attention mechanism to selectively aggregate shallow edge information and deep abstract semantic features to avoid excessive redundant information which affects the saliency mapping, as well as suppressing non-salient areas with “salient” appearance. In addition, The multi-scale feature extraction (MFE) module and the self-attention (SA) module are also proposed for obtaining sufficiently rich and useful multi-scale context information and enhancing the function of the top layer. Finally, the attentional residual refinement (ARR) module is utilized to refine the saliency map after each feature fusion and further improve the input function. MAENet can accurately segment salient objects and provide clear local details. Experimental results on five benchmark datasets show that the proposed method achieves the favorable performance against 14 state-of-the-art methods on popular evaluation metrics.

Pulmonary function testing (PFT) has important clinical value for the early detection of lung diseases, assessment of the disease severity, causes identification of dyspnea, and monitoring of critical patients. However, traditional PFT can only be carried out in a hospital environment, and it is challenging to meet the needs for daily and frequent evaluation of chronic respiratory diseases. In this study, we propose a novel method for accurately assessing pulmonary function by analyzing recorded forced cough sounds by mobile device without time and location restrictions. In the experiment, 309 clips of cough sound segments were separated from 133 patients who underwent PFT by using Audacity software. There are 247 clips of training samples and 62 clips of testing samples. Totally 52 features were extracted from the dataset, and principal component analysis (PCA) was used for feature reduction. Combined with biological attributes, the normalized features were regressed by using machine learning models with pulmonary function parameters (i.e., FEV1, FVC, FEV1/FVC, FEV1%, and FVC%). And a 5-fold cross-validation was applied to evaluate the performance of the regression models. As described in the experimental result, the result of coefficient of determination (R2) indicates that the support vector regression (SVR) model performed best in assessing FVC (0.84), FEV1% (0.61), and FVC% (0.62) among these models. The gradient boosting regression (GBR) model performs best in evaluating FEV1 (0.86) and FEV1/FVC (0.54). The result confirmed that the proposed method was capable of accurately assessing pulmonary function with forced cough sound. Besides, the cough sound sampling by a smartphone made it possible to conduct sampling and assess pulmonary function frequently in the home environment.

To assess the efficacy and safety of liraglutide to reduce visceral and ectopic fat in adults with or without type 2 diabetes mellitus (T2DM).Four databases were searched up to 6 May 2022 for randomized clinical trials assessing the effect of liraglutide on visceral and ectopic fat. The mean and standard deviation of the values of visceral fat, ectopic fat and body mass index were calculated. Subgroup analyses were performed based on the type of disease (T2DM or non-T2DM), duration of intervention, dosage of liraglutide and whether life interventions were added to liraglutide therapy. We extracted and integrated the safety assessments reported in each article.Sixteen randomized clinical trials with, in total, 845 participants were included in the meta-analysis. Liraglutide could significantly decrease visceral fat [standard mean difference (SMD) = -0.72, 95% confidence interval (CI; -1.12, -0.33)], liver fat [SMD = -0.78, 95% CI (-1.24, -0.32)] and body mass index [weighted mean difference = -1.44, 95% CI (-1.95, -0.92)] in adult patients with or without T2DM when compared with the control group. However, reduction of epicardial fat by liraglutide [SMD = -0.74, 95% CI (-1.82, 0.34)] was not statistically significant. Subgroup analysis revealed that an adequate dosage (≥1.8 mg/day) and appropriate duration of treatment (ranging from 16 to 40 weeks) were the decisive factors for liraglutide to reduce visceral fat effectively. Mild gastrointestinal reactions were the main adverse event of liraglutide.Liraglutide significantly and safely reduces visceral and ectopic liver fat irrespective of T2DM status, and reduces visceral fat provided adequate dosage and duration of therapy are ensured.