Search

The fibres reinforced thin architectural ceramic plates of 900?1800?2.5mm with excellent mechanical properties were prepared by fast-sintering method using a controllable fibre dispersion process. The effects of ball-milling time on dispersity, average length-to-diameter ratio and microstructure of alumina fibres were investigated. Meanwhile, the effects of alumina fibre contents on the bulk density, water absorption, phase transformation and microstructure of the thin ceramic plate were researched. It was found that the two-step ball-milling process can effectively control the average length-to-diameter ratio of alumina fibres, achieving a good dispersion mixture of fibres and ceramic powders. Ceramics bulk density and bending strength increase with fibre contents rise from 0 to 5 wt.% and then decrease with further fibre content addition from 5 to 15wt.%. The in situ formed mullite whiskers via fast-sintering method are beneficial for protecting fibres and fibre/matrix interfaces. The maximum value of bending strength and fracture toughness reach 147MPa for 5 wt.% fibre contents and 2.6MPa?m1/2 for 9 wt.%fibre contents, corresponding to the strengthening of alumina fibres and the formation of mullite whiskers in fibre/matrix interfaces and matrix via fast-sintering process.

The BiDy composite electrode shows good electro-catalytic activity toward l-cysteine and great application potential in electrochemical sensors.

A novel tactic of synergetic electronic coupling is successfully developed for rendering metal-rich phosphides as an efficient pH-universal electrocatalyst for the hydrogen evolution reaction.

A three-dimensional coral-like Zn,O-codoped Ni3S2 nanostructure is grown on nickel foam via a facile solvothermal method, exhibiting excellent electrocatalytic performance at high current density.

The metastable character enables the low intercalation/conversion reaction energy and greatly promotes the fast pseudocapacitive storage mechanism, leading to the high-rate performance of microsized FeCN2@NC.

A superhydrophilic core@shell heterostructure nanorod-integrated electrode (CS–NS/NF) was prepared by an in situ conversion method, which showed excellent hydrogen evolution performance at high current density.

A simple low temperature hydrothermal route has been used for the synthesis of strontium tin hydroxide (SrSn(OH)6) nanoflowers. The synthesized SrSn(OH)6 nanoflowers were investigated by means of powder X-ray diffraction, scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy and solid ultraviolet−visible diffuse reflectance spectroscopy. The SrSn(OH)6 nanoflowers are composed of nanorods with hexagonal structure, length and diameter of about 2 µm and 30–100 nm, respectively. The growth process of the SrSn(OH)6 nanoflowers is proposed as the Ostwald ripening and crystal splitting process based on the morphological evolution from different hydrothermal conditions. The band gap of the nanoflowers is 3.53 eV. The SrSn(OH)6 nanoflowers were utilized for the photocatalytic degradation of gentian violet under ultraviolet light irradiation. The roles of various factors including irradiation time and nanoflower dosage on the photocatalytic activity of the SrSn(OH)6 nanoflowers are discussed. The possible photocatalytic mechanism for gentian violet degradation using the SrSn(OH)6 nanoflowers was determined by radical trapping experiments. The SrSn(OH)6 nanoflowers possess good stability and are an efficient photocatalyst for the removal of organic pollutants.

Building change detection from very high-spatial-resolution (VHR) remote sensing images has gained increasing popularity in a variety of applications, such as urban planning and damage assessment. Detecting fine-grained ``from-to'' changes (change transition from one land cover type to another) of buildings from the VHR images is still challenging as multitemporal representation is complicated. Recently, fully convolutional neural networks (FCNs) have been proven to be capable of feature extraction and semantic segmentation of VHR images, but its ability in change detection is untested and unknown. In this letter, we leverage the semantic segmentation of buildings as an auxiliary source of information for the fine-grained ``from-to'' change detection. A deep multitask learning framework for change detection (MTL-CD) is proposed for detecting building changes from the VHR images. MTL-CD adopts the encoder-decoder architecture and solves the main task of change detection and the auxiliary tasks of semantic segmentation simultaneously. Accordingly, the change detection loss function is constrained by the auxiliary semantic segmentation tasks and enables the back-propagation of the building footprints' detection errors for the improvement of change detection. A building change detection data set named the Guangzhou data set is also developed for model evaluation, in which the bitemporal R-G-B images were collected by airplane (2009) and unmanned aerial vehicle (UAV, 2019) with different flight heights. Experiments on the Guangzhou data set demonstrate that the MTL-CD method effectively detects fine-grained ``from-to'' changes and outperforms the postclassification methods and the direct change detection methods.

A CdS/MnS p–n heterojunction is prepared. The H2 production rate is 5.92 mmol g−1 h−1 with the apparent quantum efficiency of 5.63% at 420 nm, which is 10.57 times and 49.33 times higher than that of CdS nanorods and MnS, respectively.

Molybdenum and cobalt co-doped VC nanoparticles encapsulated in nanocarbon (Mo, Co-VC@C) are successfully synthesized via a one-pot calcination route, exhibiting excellent electrocatalytic HER performance.

Porous (Ta0.2Nb0.2Ti0.2Zr0.2Hf0.2)C high-entropy ceramics (HEC) with a dual-porosity structure were fabricated by pressureless sintering using a mixture powder of ceramic precursor and SiO2 microspheres. The carbothermal reduction in the ceramic precursor led to the formation of pores with sizes of 0.4–3 μm, while the addition of SiO2 microspheres caused the appearance of pores with sizes of 20–50 μm. The porous HECs exhibit competitive thermal insulation (4.12–1.11 W·m−1 k−1) and extraordinary compressive strength (133.1–41.9 MPa), which can be tailored by the porosity of the ceramics. The excellent properties are ascribed to the high-entropy effects and dual-porosity structures. The severe lattice distortions in the HECs lead to low intrinsic thermal conductivity and high compressive strength. The dual-porosity structure is efficient at phonon scattering and inhabiting crack propagations, which can further improve the thermal insulation and mechanical properties of the porous HECs.

Aim Chicken manure can readily produce much odour during aerobic composting. This odour pollutes the surrounding environment and represents the loss of nutrients such as nitrogen and sulfur, which reduces the fertilizer quality. Methods In this paper, biochar combined with MgO desulfurization waste residue (MDWR) was used as a new composting additive. Through composting tests, characterization analysis and pot experiments, the effect of additives in compost on nitrogen retention and deodorization was studied, the mechanism of in situ chemical deodorization was revealed, and the compost quality was verified. Results The results indicated that biochar and MDWR addition optimally reduced ammonia volatilization in chicken manure compost, and the reduction rate reached 60.12%. Volatile organic compound (VOC) emissions originating from chicken manure compost containing biochar and MDWR decreased by 44.63% compared to those originating from the control group. Conclusions The total nitrogen (TN) in the composting product containing chicken manure treated with both biochar and MDWR (CMB) was 67.7% higher than that in the composting product under the blankcontral, and this value was significantly higher than that under the other treatments and better reflected the synergistic effect of these two additives on nitrogen retention. Struvite crystals could be formed in the CMB treatment. According to the pot experiment results in terms of compost products, the CMB treatment increased the yield and quality of vegetables and reduced the nitrate content. Therefore, MDWR significantly affects nitrogen retention and deodorization of chicken manure compost while improving the compost quality; therefore, MDWR exhibits broad application prospects.

Radiation-induced lung injury (RILI), a potentially fatal and dose-limiting complication of radiotherapy for thoracic tumors, is divided into early reversible pneumonitis and irreversible advanced-stage fibrosis. Early detection and intervention contribute to improving clinical outcomes of patients. However, there is still a lack of reliable biomarkers for early prediction and clinical diagnosis of RILI. Given the central role of inflammation in the initiation and progression of RILI, we explored specific inflammation-related biomarkers during the development of RILI in this study. Two expression profiles from the Gene Expression Omnibus (GEO) database were downloaded, in which 75 differentially expressed genes (DEGs) were screened out. Combining Gene Oncology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein–protein interaction (PPI) network analysis, we identified four inflammation-related hub genes in the progression of RILI—MMP9, IL-1β, CCR1 and S100A9. The expression levels of the hub genes were verified in RILI mouse models, with S100A9 showing the highest level of overexpression. The level of S100A9 in bronchoalveolar lavage fluid (BALF) and the expression of S100A9 in lung tissues were positively correlated with the degree of inflammation in RILI. The results above indicate that S100A9 is a potential biomarker for the early prediction and diagnosis of the development of RILI.

A new type of V-Ni2P nanoparticle grafted g-C3N4 nanosheet photocatalyst is successfully prepared and it exhibits high photocatalytic hydrogen evolution performance under visible light.

Background: High sodium intake is an important risk factor for hypertension and cardiovascular disease. However, the association between gut microbiota composition and metabolomic profiles with dietary sodium intake and blood pressure (BP) is not well-understood. The metabolome, microbiome, and dietary salt intervention (MetaSalt) study aimed to investigate microbial and metabolomic profiles related to dietary sodium intake and BP regulation. Methods: This family-based intervention study was conducted in four communities across three provinces in rural northern China in 2019. Probands with untreated prehypertension or stage-1 hypertension were identified through community-based BP screening, and family members including siblings, offspring, spouses, and parents were subsequently included. All participants participated in a 3-day baseline examination with usual diet consumption, followed by a 10-day low-salt diet (3 g/d of salt or 51.3 mmol/d of sodium) and a 10-day high-salt diet (18 g/d of salt or 307.8 mmol/d of sodium). Differences in mean BP levels were compared according to the intervention phases using a paired Student's t-test. Results: A total of 528 participants were included in this study, with a mean age of 48.1 years, 36.7% of whom were male, 76.8% had a middle school (69.7%) or higher (7.1%) diploma, 23.4% had a history of smoking, and 24.4% were current drinkers. The mean arterial pressure at baseline was 97.2 ± 10.5 mm Hg for all participants, and significantly decreased during the low-salt intervention (93.8 ± 9.3, P

The development of cathode materials with a high electric conductivity and a low polarization effect is crucial for enhancing the electrochemical properties of magnesium-ion batteries (MIBs). Herein, Mo doping and nitrogen-doped tubular graphene (N-TG) introduction are carried out for decorating VS4 (Mo-VS4/N-TG) via the one-step hydrothermal method as a freestanding cathode for MIBs. The results of characterizations and density functional theory (DFT) reveal that rich sulfur vacancies are induced by Mo doping, and N-TG as a high conductive skeleton material serves to disperse the active material and forms a tight connection, all of which collectively improved the electrical conductivity of electrode and increased the adsorption energy of Mg2+ (-6.341 eV). Furthermore, the fast reaction kinetics is also confirmed by the galvanostatic intermittent titration technique (GITT) and the pesudocapacitance-like contribution analysis. Benefiting from the synergistic effect of electrical conductivity enhancement and rich vacancy introduction, Mo-VS4/N-TG delivers a steady Mg2+ storage specific capacity of about 140 mAh g-1 at 50 mA g-1, outstanding cycle stability (80.6% capacity retention ratio after 1200 cycles under 500 mA g-1), and excellent rate capability (specific capacity reaches 77.1 mAh g-1 when the current density reaches 500 mA g-1). In addition, the reversible reaction process, intercalation mechanism, and structural stability during the Mg2+ insertion/extraction process are confirmed by a series of ex situ characterizations. This research provides a sustainable and scalable strategy to spur the development of MIBs.

In the continuous development of electrochemical CO2 reduction (ECR), Cu-based electrocatalysts have received great attention, due to their unique ability to produce high value-added multicarbon products. Of particular interest are various Cu-comprising nanocrystals, not only because they usually show better catalytic properties than bulk materials, but also because their well-defined structures and highly tunable compositions facilitate in-depth mechanistic studies. This review aims to summarize the latest developments of electrocatalysts for ECR, with a focus on systems using Cu-comprising nanocrystals. We first give a general introduction to the field of ECR, covering the significance of this process, reaction mechanisms, catalyst evaluation criteria, and electrolytic cell configurations. Next, we discuss Cu-comprising nanocrystals developed for ECR by categorizing them into four groups: monometallic copper, copper-containing bimetals/multimetals, copper compounds, and copper–metal oxide hybrids; among these groups, we choose representative examples for detailed discussion on the synthetic methods, structural and compositional reaction sensitivities, and catalyst evolution during ECR. In the last section, we outline the challenges in this field from the fundamental and applicative aspects, and give perspectives on the expansion of catalyst varieties, the identification and preservation of active sites, and the exploration of industrially relevant operations for these nanocrystals. We hope the insights provided in this review will inspire the design and development of next-generation catalysts for ECR.

CdS has a wide visible-light response range and suitable energy band structure; it has been spotlighted in the field of photocatalysis. Nevertheless, its poor photogenerated carriers separation eff...

CNTs/Ti3C2Tx hybrids are prepared with carbon nanotubes (CNTs) are in-situ grown on the surface of the Ti3C2Tx nanosheets by using the method of chemical vapor deposition. Internal effects between micro-morphology and interface polarization have been research. The results show that the dielectric properties of the CNTs/Ti3C2Tx hybrids increase with the increase of the length of CNTs, the growth time is a direct determinant of the length of CNTs. The factors of the micro capacitors formed by CNTs, the dipoles formed by defects on CNTs greatly increase the dielectric loss. When the growth time reaches 45 min and the thickness of the absorber is 2.0 mm, the minimum reflection coefficient is −60.9 dB in X-band, the absorption bandwidth reaches 2.9 GHz. The CNTs/Ti3C2Tx hybrid shows excellent electromagnetic wave absorption properties.

Titanium dioxide is often used to capture polysulfides due to its strong surface polarity. Surface activity of titanium dioxide is produced by defects, which possesses an important impact on abilities to capture polysulfides. However, the reaction mechanism of defective titanium dioxide in the process of capturing polysulfide is not clear. In this paper, we introduced cobalt source as an additive to titanium dioxide/biomass carbon composite materials to prepare titanium dioxide with many defects and strong surface activities. The crystallinity of biomass carbon surface is also continuously improved by introducing cobalt sources. Under combined performance of highly active titanium dioxide and highly conductive biomass carbon, composite materials possess strong and reversible polysulfide-capturing abilities. In particular, types of polysulfides captured is increased. Herein, the addition of cobalt source is beneficial to enhance abilities of titanium dioxide to capture multiple polysulfides, improve conductivity of composite materials and achieve high reversible capacity (375.0 mA h·g−1 after 500 cycles at 1C).

Polysulfides can be captured rapidly by defects, which possess strong catalytic redox abilities. Species of defects have important influence on rate performance of metal-sulfur electrodes. However, catalytic reaction mechanisms have not been explored in depth. This paper focuses on comparing differences between intrinsic defect carbon materials (IDC) and external introduced defect carbon materials (EIDC) in promoting polysulfide redox abilities and exploring catalytic redox reaction mechanism deeply. Results show that IDC have stronger catalytic redox reaction abilities than EIDC, which is mainly due to stable C–S bonds on surface of IDC. After cycling, C–S bond contents in IDC electrodes maintain more than 70 %. During cycling process, C–S bonds can quickly adsorb polysulfides and promote their conversion into final products, thereby achieving high rate performance. Weak catalytic redox abilities of EIDC electrodes is mainly due to loss of C–S bonds. When the current density is 5C, capacities of IDC electrodes is twice as much as that of EIDC electrodes. Good rate performance of IDC electrodes reflects important roles of stable C–S bonds in promoting redox reaction of polysulfides, which has important research significance for preparation of carbon-based composite electrodes.

As the most widespread and practical digital representations of living cells, metabolic network models have become increasingly precise and accurate. By integrating cellular resources and abiotic constraints, the prediction functions were significantly expanded in recent years. However, we found that if unreasonable modeling methods were adopted due to the lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of L-serine and L-tryptophan. Specific analysis explains the application method of EcoETM-like model, demonstrating its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Finally, we provide a preliminary comparison of the thermodynamic feasibility of ammonia and glutamine as amino donors, which revealed that the direct utilization of ammonia does not have a decisive impact on the thermodynamic feasibility of the anthranilate pathway. Our work is of great value for the structural improvement of constraints-based models.

For the International Thermonuclear Experimental Reactor magnets, a significant fraction of the Nb3Sn conductors will be operating at a low field (B < 4 T), such as the outer turns of the central solenoid modules and toroidal field winding packs, while so far, the Ic(B,T, ) parameterization has been derived from measurements carried out at higher fields (B ≥ 7 T). It may not be accurate enough to adopt this parameterization for the extrapolation of the conductors' operating performance in terms of critical current (Ic) and current sharing (Tcs). The critical current characteristic can be effectively extended to the lower field region by means of a relation between the magnetization and critical current. The parameterization of the derived critical current scaling law Jc(B) is processed for the field range of the magnetization measurement (0 < B ≤ 9 T) and the critical current measurements (7 ≤ B < 12 T) in order to cover the full range up to 12 T.

The aim of this study was to evaluate the association between fruit intake and stroke risk considering the genetic predisposition. We used data from 34,871 participants from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR project) from 2007 to 2020. A polygenic risk score comprising 534 genetic variants associated with stroke and its related factors was constructed to categorize individuals into low, intermediate, and high genetic risk groups. The associations of genetic and fruit intake with incident stroke were assessed by the Cox proportional hazard regression. We documented 2586 incident strokes during a median follow-up of 11.2 years. Compared with fruit intake < 200 g/week, similar relative risk reductions in stroke with adherence to fruit intake > 100 g/day across the genetic risk categories were observed (28–32%), but the absolute risk reductions were relatively larger in the highest genetic risk group (p for trend = 0.03). In comparison to those with a fruit intake < 200 g/week, those with a fruit intake >100 g/day in the low, intermediate, and high genetic risk groups had an average of 1.45 (95% CI, 0.61–2.31), 2.12 (1.63–2.59), and 2.19 (1.13–3.22) additional stroke-free years at aged 35, respectively. Our findings suggest that individuals with a high genetic risk could gain more absolute risk reductions and stroke-free years than those with a low genetic risk from increasing fruit intake for the stroke primary prevention.

BackgroundArtificial intelligence (AI)-assisted diagnosis is considered to be the future direction of improving the efficiency and accuracy of pediatric diseases diagnosis, while the existing research based on AI are far from sufficient because of limited data amount, inadequate coverage of disease types, or high construction costs, and have not been applied on a large scale. We aimed to develop an accurate deep learning model trained on millions of real-world data to verify the feasibility of the technology, and build the whole process of outpatient auxiliary diagnosis.Methods and findingsWe applied a Chinese Natural Language Processing (NLP) and an end-to-end deep neural network classifier to the outpatient’s electronic medical records (EMRs) in a single child care center in Shanghai, China, to unstructured text processing and construct an auxiliary diagnostic model, all patients were aged from 0 to 18 years. A training cohort with millions of records and an independent validation cohort with tens of thousands of records were intake separately and calculate diagnosis concordance rate (DCR) of model in each diseases group. The records with inconsistent diagnoses between human and AI were evaluated by clinical experts’ group, and calculate the relative correct rate (RCR) to evaluate the diagnostic performance of the model. A total of 5,271,347 medical records were intake in model training covering sixteen categories of diseases according to disease coding, reaching a DCR of 95· 49% (95· 48∼95· 51). For validation, 91,880 records were obtained from validation dataset, which reached a DCR of 93· 51% (93· 35∼93· 67) and FDCR of 72.04% (71· 75∼72· 33). It was confirmed that the accuracy of the model was still higher than that of human with most RCR>1 in validation dataset.ConclusionsThe deep learning system could support diagnosis of pediatric diseases, which has high diagnostic performance, comprehensive disease coverage, feasible technology, and can be promoted in multiple sites in the future.FundingThe Authors received no specific funding for this work.

Cuproptosis is a newly discovered non-apoptotic form of cell death that may be related to the development of tumors. Nonetheless, the potential role of cuproptosis-related lncRNAs in tumor microenvironment (TME) formation and patient-tailored treatment optimization of gastric cancer (GC) is still unclear. In this study, the six-lncRNA signature was constructed to quantify the molecular patterns of GC using LASSO-Cox regression model. Receiver operating characteristic (ROC) curves, C-index curves, independent prognostic analysis and principal component analysis (PCA) were conducted to verify and evaluate the model. The results showed that this risk model was accurate and reliable in predicting GC patient survival. In addition, two distinct subgroups were identified based on the risk model, which showed significant difference in biological functions of the associated genes, TME scores, characteristics of infiltrating immune cells and immunotherapy responses. We found that the high-risk subgroup was associated with immune activation and tumor-related pathways. Furthermore, compared with the low-risk subgroup, the high-risk subgroup had higher TME scores, richer immune cell infiltration and a better immunotherapy response. To accurately identify immune cold tumors and hot tumors, all samples of GC were divided into four distinct clusters by consensus clustering. Among them, Cluster 3 was identified as an immune hot tumor and was more sensitive to immunotherapy. Overall, this study demonstrates that cuproptosis-related lncRNAs could accurately predict the prognosis of patients with GC, help make a distinction between immune cold tumors and hot tumors and provide a basis for the precision medicine of GC.

Developing low-cost, environmentally friendly and efficient non-precious metal electrocatalysts as alternatives to noble metals for the hydrogen evolution reaction (HER) is highly essential for the sustainable advancement of green hydrogen energy. Herein, a novel heterostructured Ni

Carbon quantum dots (CQDs) as a rising class of carbon family have gained widespread attention in view of their multiple properties such as great photoluminescence (PL) properties, facile synthesis route, needing economical and cheap raw material, high physiochemical stability, and simple functionalization. This makes CQDs highly versatile and with potential for different applications. To date, CQDs-enabled photocatalysts are regarded as one of the most efficient technologies to degrade pollutants in water; however, poor activity under visible light and the recombination of photogenerated electron and hole pairs hinder getting an ideal performance that may be applied on a large scale. Conventional techniques have been modified via a new advanced method. In this review, we highlighted the strategies to improve the activity of conventional semiconductor photocatalysis via coupling with CQDs, and strategies to improve the photocatalytic activity such as functionalization, doping, and Z-scheme heterojunctions were discussed in detail. This review also covered the CQDs heterojunction application in pollutant degradation and discussed several examples with high-performance photocatalytic activity.