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The structural properties such as high specific surface area, good electrical conductivity, rich-defects of the catalyst surface guarantee outstanding catalytic performance and durability of oxygen reduction reaction (ORR) electrocatalysts. It is still a challenging task to construct ORR catalysts with excellent performance. Herein, we have reported column-like MoS2/rGO with defect-rich ultrathin nanosheets prepared by a convenient solvothermal method. The structure and composition of MoS2/rGO are systematically investigated. MoS2/rGO shows a remarkable electrocatalytic performance, which is characterized by an outstanding onset potential of 0.97 V, a half-wave potential of 0.83 V, noticeable methanol tolerance, and durability of 93.7% current retention, superior to commercial Pt/C. The ORR process occurring on MoS2/rGO is a typical four electron pathway. Therefore, this study achieves the design of a low-cost, highly efficient and stable nonprecious metal ORR electrocatalyst in alkaline media.

This paper considers efficient spectral solutions for weakly singular nonlocal diffusion equations with Dirichlet-type volume constraints. The equation we consider contains an integral operator that typically has a singularity at the midpoint of the integral domain, and the approximation of the integral operator is one of the essential difficulties in solving nonlocal equations. To overcome this problem, two-sided Jacobi spectral quadrature rules are proposed to develop a Jacobi spectral collocation method for nonlocal diffusion equations. A rigorous convergence analysis of the proposed method with the $L^\infty$ norm is presented, and we further prove that the Jacobi collocation solution converges to its corresponding local limit as nonlocal interactions vanish. Numerical examples are given to verify the theoretical results.

Femur is a thigh bone in humans, which is particularly prone to injury and difficult to mend if damaged. The stress shielding effect is caused by a change in bone mechanics transmission route as a result of femur bone damage. The formation of a porous structure provides a better solution to the problem of stress shielding effect reduction. The porous material is basically a solid which has empty space(s) which is not covered by the primary structure of particles that build up the solid’s structure. Traditional porous materials have a uniform density distribution in their microstructure. The density distribution of a material should be established according to different loads in each location of the material to completely represent its characteristics. In this paper, to acquire the ideal density distribution of porous materials and construct high-performance variable-density porous structures, topological optimization is applied into the design of the lattice structure. According to a structure constructed utilising individualised parameters paired with computed tomography (CT) data of the human femur, a topological optimization design of a multiscale femoral prosthesis model based on the homogenization approach is presented. Experiments on different femoral prosthesis architectures revealed that variable-density porous prostheses have superior material and stress distributions than equal-density porous prostheses under the same stress and successfully decreased femoral stress shielding to improve prosthetic stability.

The dense point clouds of Terracotta Warriors obtained by a 3D scanner have a lot of redundant data, which reduces the efficiency of the transmission and subsequent processing. Aiming at the problems that points generated by sampling methods cannot be learned through the network and are irrelevant to downstream tasks, an end-to-end specific task-driven and learnable down-sampling method named TGPS is proposed. First, the point-based Transformer unit is used to embed the features and the mapping function is used to extract the input point features to dynamically describe the global features. Then, the inner product of the global feature and each point feature is used to estimate the contribution of each point to the global feature. The contribution values are sorted by descending for different tasks, and the point features with high similarity to the global features are retained. To further learn rich local representation, combined with the graph convolution operation, the Dynamic Graph Attention Edge Convolution (DGA EConv) is proposed as a neighborhood graph for local feature aggregation. Finally, the networks for the downstream tasks of point cloud classification and reconstruction are presented. Experiments show that the method realizes the down-sampling under the guidance of the global features. The proposed TGPS-DGA-Net for point cloud classification has achieved the best accuracy on both the real-world Terracotta Warrior fragments and the public datasets.

Although many recent deep learning methods have achieved good performance in point cloud analysis, most of them are built upon the heavy cost of manual labeling. Unsupervised representation learning methods have attracted increasing attention due to their high label efficiency. How to learn more useful representations from unlabeled 3D point clouds is still a challenging problem. Addressing this problem, we propose a novel unsupervised learning approach for point cloud analysis, named ULD-Net, consisting of an equivariant-crop (equiv-crop) module to achieve dense similarity learning. We propose dense similarity learning that maximizes consistency across two randomly transformed global–local views at both the instance level and the point level. To build feature correspondence between global and local views, an equiv-crop is proposed to transform features from the global scope to the local scope. Unlike previous methods that require complicated designs, such as negative pairs and momentum encoders, our ULD-Net benefits from the simple Siamese network that relies solely on stop-gradient operation preventing the network from collapsing. We also utilize the feature separability constraint for more representative embeddings. Experimental results show that our ULD-Net achieves the best results of context-based unsupervised methods and comparable performances to supervised models in shape classification and segmentation tasks. On the linear support vector machine classification benchmark, our ULD-Net surpasses the best context-based method spatiotemporal self-supervised representation learning (STRL) by 1.1% overall accuracy. On tasks with fine-tuning, our ULD-Net outperforms STRL under fully supervised and semisupervised settings, in particular, 0.1% accuracy gain on the ModelNet40 classification benchmark, and 0.6% medium intersection of union gain on the ShapeNet part segmentation benchmark.

A series of β-ionone-curcumin hybrid derivatives were designed and chosen to merge the biological characteristics of two parent molecules and to obtain a leading compound with higher biological activity. Through the initial screening, the structure activity relationship of their hybrid derivatives as inhibitors of nitric oxide (NO) production showed that meta-substituted derivatives exhibited the best inhibitory activity, among which 1h was the best one. In lipopolysaccharide-induced Raw264.7 macrophage cells, 1h showed anti-inflammatory activity by inhibiting the productions of NO and reactive oxygen species, the expressions of Interleukin-1β and tumor necrosis factor-α, and the translocation of nuclear factor (NF)-κB from the cytosol to the nucleus. Furthermore, molecular docking simulation displayed that 1h could interact with cluster of differentiation 14 to inhibit the toll-like receptor 4/NF-κB signaling. In dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) of mice, 100 mg/kg of 1h could significantly reduce the colon length shortening and protect against colon injury, liver injury and oxidative stress in DSS-induced UC of mice. Besides, 1h was safety in vivo. In conclusion, 1h was the potential anti-inflammatory agent, and further investigations were underway in our laboratory.

Low-temperature atmospheric calcination is a new technology for solving the current environmental issues associated with activated clay production. In this study, the structural alteration of montmorillonite during the production of activated clay was investigated by this new technology. The results revealed that the increase in temperature aggravates the destruction of montmorillonite layers, which mainly constituted octahedral sheets due to the continuous dissolution of cations in the sheets, with relatively stable tetrahedral sheets. Activated montmorillonite layers became curled and stacked in disorder, which was different from that in the original. The maximum acidity of 230 mmol/kg was achieved at an optimum temperature of 200°C. Under this condition, the specific surface area and total pore volume increased from 78.4 m2/g to 226 m2/g and from 0.107 cm3/g to 0.318 cm3/g, respectively. With the improvement in the decolorization ability of the clay, the absorbance of the rapeseed oil decreased to 0.867 from 4.070.

A novel localization algorithm, which considers nonline-of-sight (NLOS) propagation, is proposed in this paper. By introducing a transfer function that relates the field at a given receiver to the source as a function of frequency and position, the NLOS effect can be mitigated and the propagation channel can be calibrated back to free space. The simulation results demonstrate that the proposed algorithm performs much better than that using the usual line-of-sight time difference of arrival (TDOA) localization, and the accuracy is only limited by the sampling frequency. The measurements verify the improvement in using the improved TDOA method versus the usual TDOA method.

The structural properties such as high specific surface area, good electrical conductivity, rich-defects of the catalyst surface guarantee outstanding catalytic performance and durability of oxygen reduction reaction (ORR) electrocatalysts. It is still a challenging task to construct ORR catalysts with excellent performance. Herein, we have reported column-like MoS

Introduction:Current dietary recommendations encourage increased fibre and reduced sugar consumption. In the UK, specific targets and benchmarks have been established for the sugar content of some foods but not for fibre. National Food Consumption Surveys provide comprehensive information of all foods consumed by representative population samples. The Irish national food surveys as completed by the Irish Universities Nutrition Alliance (IUNA) capture dietary data at brand level with all details as gathered on pack entered into a discrete but inter-linked database, the Irish National Food Ingredient Database (INFID). The aim of this study was to profile the carbohydrate quality of a convenience sub-sample of packaged foods as eaten by Irish children during the National Children's Food Survey II (2017/2018) as entered into INFID.Materials and Methods:All on-pack details from 385 available foods in the categories ‘white breads and rolls’; ‘brown breads and rolls’; ‘other breads and scones’; ‘ready to eat breakfast cereals (RTEBC)’; ‘biscuits’; and ‘cakes, buns and pastries’ were entered in to INFID and quality control completed. The carbohydrate profile of the products was assessed with respect to fibre labelling criteria and UK sugar guidelines and targets. SPSS Version 25 was used for all analyses.Results:Although 56% (n210) of all products entered were eligible to make a ‘source of’ or ‘high’ fibre claim, only 20% (n78) made such a claim. Of this, 46% stated ‘high fibre’ and 32% ‘source’, predominately in the ‘brown breads and rolls’ and ‘RTEBC’ groups. When compared to UK Department of Health guidance for ‘low’, ‘medium’ and ‘high’ sugar, 65% of all products examined (n250) were either ‘low’ or ‘medium’ sugar. Comparison of median sugar contents with Public Health England sugar reformulation targets revealed different responses in each category, with all categories other than foods deemed as “morning goods” yet to meet the 2020 target of 20% reduction in sugar content.Discussion:This small pilot study of a convenience sample of foods suggests that for the limited number of foods examined, for some there remains challenges to reduce sugar and increase fibre contents. Strategies such as reformulation, change in portion size, flexibility in labelling and/or a shift in sales portfolios could be considered but only alongside technological and safety considerations. Further research to broaden this analysis and to link nutrient levels as listed on pack with actual consumption patterns could help ensure all recent initiatives including reformulation are recognised.

Under Regulation (EC) No 1924/2006 the usage of nutrition and health claims are permitted, however foods that are high in fat, sugars and salt are advised not to use such claims as foods promoted with these claims may influence consumer food choice. The use of nutrient profiles has been proposed as a means of avoiding the potential of such claims masking the overall nutritional status of a product. Ready to eat breakfast cereals (RTEBC) often display nutrition claims whilst also contributing significantly to total sugar and energy intake. The aim of this study was to profile a variety of RTEBC and compare nutrient composition and claim information between nutrient profile categories.The Irish National Food Ingredient database (INFID) is a record of brand specific information from food labels collected during the Irish national food surveys. A convenience sub-sample of RTEBC as eaten by Irish children during the National Children's Food Survey 2 (2017/2018) were selected (n = 102). Nutrient profile (NP) scores were calculated using the UK Nutrient Profiling Model (FSA). NP scores were calculated based on a set of negative macronutrient indicators (energy, saturated fat, total sugars and sodium) minus positive indicators (protein, fibre, “fruit, vegetables and nuts”) present per 100 g. Foods scoring four points or more were classified as “less healthy”.More than half of RTEBC were classed “less healthy” (53%) with a median NP score of 8.0 with “healthy” RTEBC scoring significantly lower at -0.0 (p < 0.001). “Healthy” RTEBC had a median sugar content of 13.4g/100 g compared to 24g/100 g in the “less healthy” (p < 0.001). “Healthy” RTEBC had a higher fibre content of 8.8g/100 g compared to 5.72g/100 g in the “less healthy” (p = 0.001), with 35% of healthy and 28% of less healthy RTEBC making a substantiated “high in fibre” claim. Micronutrient contents of all RTEBC were similar, with only iron significantly higher in “healthy” (13.3mg/100g) compared to “less healthy” (9.5mg/100g) (p = 0.02). The prevalence of substantiated micronutrient related claims was the same between “healthy” and “less healthy” RTEBC.“Healthy” and “less healthy” RTEBC display similar micronutrient profiles, with most of the nutrition claims on both pertaining to the micronutrient and fibre content, potentially overshadowing the macronutrient contribution of the cereals. This analysis shows the ability of nutrient profiling to distinguish products by macronutrient profiles however it identifies the complexity of application with respect to micronutrient content. Further research is required to investigate the contribution of the profiled RTEBC to total nutrient intakes.

This was an experiment in which chloride was externally permeated into cement paste. The influence of Cl- on the content and distribution of free-form NO2- in the cement paste was researched using the chemical quantitative analysis method. The action mechanism was investigated by the micro-means of X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results show that the physical competitive adsorption of Cl- with NO2- on C-S-H and the chemical substitution of Cl- to NO2-AFm caused more free-form NO2- in the cement paste. In the cement paste with chloride salt erosion, the NO2- concentration in the erosion surface was the lowest, and the NO2- concentration reached the highest value at 10mm from the erosion surface. The concentration decreased gradually with the depth from the erosion surface.

By using XRD diffraction patterns and SEM scanning electron microscopy, the study included exploring the effects of carbonation on the types of cations, namely Na+ and Mg2+, on the chloride concentration and mechanism, which is an important factor that has received little attention. The results show that carbonization has a greater negative impact on the binding capacity of chloride ions in cement mixed with NaCl, and CaCl2 can weaken the negative effect of carbonization on the binding capacity of chloride ions and improve the binding capacity of free chloride ion ;During the carbonization of cement mixed with NaCl, the chloride content corresponding to the maximum chloride ion binding rate was reduced from 0.9 % to 0.8 %, while the value was 0.8 % in cement mixed with CaCl2;Carbonization can improve the structure of the cement and reduce the porosity in the cement structure.

Chemical quantitative analysis of effective anticorrosion component and micro-analysis of hydration products of fly ash and slag on the influence of the nitrites corrosion inhibition was studied by the free nitrite ion concentration and X-ray diffraction pattern. The free nitrite ion concentration was used to describe the corrosion inhibition effect of nitrites. And the X-ray diffraction patterns were used to analyze the adsorption properties. The research results show that fly ash and slag were beneficial for improving the corrosion inhibition effect of nitrites. Cement-based materials with slag at low content presented high free nitrite ion concentration, but the addition of low content of fly ash harmed the corrosion inhibition effect of nitrites. The specimens incorporated with both fly ash and slag can reach the highest free nitrite ion concentration when the compounding proportion was 1:1. It was concluded that the extent of mineral admixtures of the corrosion inhibition effect of nitrites was affected by its type and content.

A novel source localization algorithm that combines the time difference of arrival (TDOA) method and a technique for the de-embedding of the propagation transfer function for non-line-of-sight (NLOS) propagation is proposed, in order to achieve accurate source localization under NLOS conditions. An iterative implementation of the method is given, and results are shown for a simple case of a single wall obstacle.

The time difference of arrival (TDOA) positioning method is a classic method that is used to determine the unknown location of a transmitting wireless device, based on the time differences in the signals that are received at different receivers. In this investigation the method is studied for two-dimensional (2-D) problems for simplicity, using a vertical dipole source radiating a carrier wave that is modulated by a baseband signal. By maximizing the cross-correlation between the signals arriving at any two receivers, the TDOA between these two receivers is estimated. In principle, only three receivers are needed for source localization in 2-D problems in the absence of noise, using the TDOA between any two pairs of receivers. However, the accuracy can be influenced significantly by non-line-of-sight effects when multiple walls, realistic ground effects, and scattering objects are added to the propagation route. A more accurate result can be obtained by using a modified method discussed here, which incorporates a transfer function that relates the field at a given receiver to the dipole source amplitude as a function of frequency. A “processed signal” is calculated at each receiver by de-embedding the transfer function from the received signals and multiplying back by a free-space propagation term for each frequency in the signal spectrum, thus removing the effects of the environment and calibrating the channel back to free space. Since the transfer function is different at each possible source position, an iterative method is proposed to do the localization.

The time difference of arrival (TDOA) positioning method is a classic method that is used to determine the unknown location of a transmitting wireless terminal, based on the time differences in the signals that are received at different receivers. In this research the method is studied for two- dimensional (2-D) problems for simplicity, for an electromagnetic dipole source radiating a carrier wave that is modulated by a baseband signal. By maximizing the cross-correlation between the signals arriving at any two receivers, the TDOA between these two receivers is estimated. In principle, only three receivers are needed for source localization in 2-D problems in the absence of noise, using the TDOA between any two pairs of receivers. The source is then constrained to lie at the intersection of two hyperbolas, arising from these two pair of receivers. Localization in the presence of noise is usually based on minimizing the square error between the measured TDOA between all possible pairs of receivers (multiplied by the speed of light) and the difference in distances between the estimated transmitter location and the corresponding pair of receivers.