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The computation of power diagrams (or weighted Voronoi diagrams) is a fundamental task in computational geometry and computer graphics. To accomplish the computation, we provide a different way from the existing ones for lifting the weighted seeds to a set of points in the space of one dimension higher, then the power cells can be directly obtained by computing the intersections of the Voronoi cells of these lifting points and the original space. This property enables us to apply the method based on the k -nearest neighbors query to the generation of power diagrams. Each power cell is obtained by sequentially clipping the input domain using the bisectors between its seed and the k -nearest neighbors. Experimental results demonstrate that our method outperforms the state-of-the-art one based on regular triangulation in terms of efficiency for general cases in the 2D and 3D spaces. [Display omitted] • We provide a variant for lifting the weighted seeds to higher dimensional points. • We propose an efficient method for power diagram computation based on the kNN query. [ABSTRACT FROM AUTHOR]

This paper introduces a novel class of fair and interpolatory planar curves called pκ -curves. These curves are comprised of smoothly stitched Bézier curve segments, where the curvature distribution of each segment is made to closely resemble a parabola, resulting in an aesthetically pleasing shape. Moreover, each segment passes through an interpolated point at a parameter where the parabola has an extremum, encouraging the alignment of interpolated points with curvature extrema. To achieve these properties, we tailor an energy functional that guides the optimization process to obtain the desired curve characteristics. Additionally, we develop an efficient algorithm and an initialization method, enabling interactive modeling of the pκ -curves without the need for global optimization. We provide various examples and comparisons with existing state-of-the-art methods to demonstrate the curve modeling capabilities and visually pleasing appearance of pκ -curves. • Introduce fair and interpolatory pκ -curves with parabolic-like curvature distribution. • Customize energy functionals to guide pκ -curve construction. • Develop an efficient and practical algorithm to solve the tailored optimization problem. [ABSTRACT FROM AUTHOR]

In this study, two polysaccharide fractions (TSP-1 and TSP-2) were isolated from Toona sinensis leaves. The physicochemical properties and solution conformations of TSP-1 and TSP-2 were investigated. DSC and TG results showed that TSP-1 and TSP-2 had thermal stability. The intrinsic viscosities of TSP-1 and TSP-2 solutions were 11.42 and 6.13 mL/g, respectively. Rheological results showed that the viscosities of TSP-1 and TSP-2 solutions were affected by polysaccharide concentration, Ca2+ and extreme pH. Furthermore, TSP-1 exhibited a weak gel behavior at the concentrations of 0.5 %–2.0 %, while TSP-2 showed a weak gel behavior at the concentration of 2 %. HPSEC-MALLS analysis revealed that the Rg values of TSP-1 and TSP-2 were 96.8 nm and 56.2 nm, respectively. Conformation analysis indicated that TSP-1 behaved as a sphere, while TSP-2 behaved like a rigid rod. These results suggest that TSP-1 and TSP-2 can be used as additives in food, pharmaceutical and cosmetic industries. • Two polysaccharide fractions (TSP-1 and TSP-2) exhibited thermal stability. • The intrinsic viscosities of TSP-1 and TSP-2 were 11.42 and 6.13 mL/g, respectively. • The viscosities of the polysaccharides were affected by concentration, pH and Ca2+. • TSP-1 behaved as a sphere, while TSP-2 behaved like a rigid rod. [ABSTRACT FROM AUTHOR]

This paper presents the application of triangle configuration B-splines (TCB-splines) for representing and analyzing the Kirchhoff–Love shell in the context of isogeometric analysis (IGA). TCB-splines offer flexibility in modeling complex geometries with C 1 continuity, making them naturally fit into the Kirchhoff–Love shell formulation with complex geometries. We first propose a linear least-squares-based framework to reparametrize the mid-surface of a thin shell, which consists of multiple (trimmed) NURBS patches and is topologically equivalent to an open disk with a finite number of holes, into a single TCB-surface defined over a carefully computed parametric domain. We then utilize TCB-splines for geometric representation and solution approximation in shell analysis. We verify the accuracy and robustness of our method by applying it to linear and nonlinear benchmark shell problems. The applicability of the proposed approach to shell analysis is further exemplified by performing geometrically nonlinear Kirchhoff–Love shell simulations of a pipe junction and a front bumper represented by a single patch of TCB-splines. [ABSTRACT FROM AUTHOR]

Highlights • Two novel polysaccharide fractions are isolated from Toona sinensis leaves. • The compositions and structural features of TSP-1 and TSP-2 are elucidated. • TSP-1 and TSP-2 exhibit protective effects on CCl 4 -induced acute mice liver injury. Abstract Two polysaccharide fractions (TSP-1 and TSP-2) with molecular weights of 833.6 kDa and 81.6 kDa were isolated from Toona sinensis leaves (Meliaceae) by hot water extraction, DEAE Cellulose-52 chromatography and Sephacryl S-400 gel permeation chromatography. Structural analysis indicated that TSP-1 and TSP-2 consisted of Man p , Glc p A, Glc p , Gal p , Xyl p and Ara f with different molar ratios. Methylation and NMR analysis revealed that the backbone of TSP-1 might consist of 1,6-linked-Glc p , 1,3,6-linked-Man p and 1,6-linked-Gal p , while TSP-2 was mainly composed of 1,3,5-linked-Ara f , 1,6-linked-Glc p , 1,4-linked-Xyl p and 1,6-linked-Gal p. Congo red assay indicated that TSP-1 and TSP-2 had no triple-helix structure, which was consistent with the results of AFM. In vivo hepatoprotective activity showed that TSP-1 and TSP-2 could improve CCl 4 -induced mice liver injury by reducing the activities of AST, ALT and the level of MDA, increasing the activities of SOD, GSH-Px, and CAT and the level of GSH in liver and decreasing the expression levels of TNF-α and IL-6 in liver. These results suggest that TSP-1 and TSP-2 have promising potential to serve as hepatoprotective agents. [ABSTRACT FROM AUTHOR]

Highlights • A novel polysaccharide fraction (WAFP) was isolated from wax apple fruits. • The structural characterization of WAFP was elucidated. • The physicochemical properties of WAFP were studied. • WAFP exhibited significant inhibitory effect on α-glucosidase activity. Abstract In this study, a novel water-soluble polysaccharide fraction (WAFP) was isolated from wax apple fruits. The structural characterization, physicochemical properties and α-glucosidase inhibitory activity of WAFP were investigated. The results indicated that WAFP had average molecular weight of 49.9 kDa, it was mainly composed of rhamnose, arabinose, xylose, mannose, glucose, and galactose with a molar ratio of 1.88: 2.20: 6.37: 1.48: 5.47: 2.82. Besides, the backbone of WAFP might consist of →4)-α-D-Glc p -(1→, →3,4)-β-D-Xyl p -(1→ and →3)-β-D-Gal p -(1→, and the side chains might be composed of →3,5)-α-L-Ara f -(1→, T-α-D-Glc p , →3)-β-D-Man p -(1→, →4)-α-D-Gal p A-(1→ and →2)-α-L-Rha p -(1→. AFM images revealed that the height of WAFP molecules was about 12.8 nm. WAFP had no triple-helix structure, and it exhibited a shear-thinning behavior in the solution. SEM results showed that WAFP presented loose and incompact appearance and rough surface with many small irregular particles existed in the state of aggregation. Moreover, WAFP showed significant inhibitory effect on the activity of α-glucosidase. [ABSTRACT FROM AUTHOR]

Abstract Seismic landslides are the most harmful natural events in mountainous areas worldwide. They are secondary disasters triggered by earthquakes and can cause a great number of casualties and significant damage to infrastructure. Three areas, Wenchuan, Lushan and Jiuzhaigou, which are highly prone to seismic landslides, were selected for this study. The aim of this study is to compare the prediction accuracy and spatial generalization ability of the logistic regression (LR) and random forest (RF) models in seismic landslide susceptibility mapping. First, using the LR and RF techniques, the susceptibility models of seismic landslides were developed in Wenchuan and Lushan based on thirteen influencing factors. Then, the accuracy of the susceptibility mapping was evaluated by the area under the curve (AUC) values of the receiver operating characteristic (ROC) curves. The results showed that both RF models have excellent prediction capability and strong robustness over large areas compared with the LR models. The AUC values of the RF and LR models were 0.811 vs. 0.946 and 0.905 vs. 0.969 in Wenchuan and Lushan, respectively. Second, we used the seismic landslides of Wenchuan and Lushan to develop the better model (RF), and then applied the developed RF model to produce the landslide susceptibility mapping of Jiuzhaigou County. The prediction accuracy for Jiuzhaigou dropped to 0.704. The results show that the RF model developed in Wenchuan and Lushan has robustness and spatial generalization ability over large areas. However, many landslides that had not been identified by the model, were located in the scenic area of Jiuzhaigou, a popular tourist destination. This suggests that intensive human activities could increase the landslide susceptibility. Thus, we added a new factor related to tourism to produce an improved RF model. The prediction accuracy of the altered model improved significantly, with the AUC value rising from 0.704 to 0.987. Thus, human engineering activities have a significant impact on landslides. Our study indicates that human engineering activities can increase the likelihood of landslides; hence, human engineering activities related to tourism should not be neglected in landslide susceptibility research. Appropriate disaster prevention and mitigation measures should be taken for the twelve geoparks of western China with peak ground acceleration ≥0.2 g. Highlights • The random forest model is more suitable for seismic landslide susceptibility mapping in Western Sichuan Plateau. • Provide a new perspective to analyze the seismic landslide susceptibility over large areas • Human activities do show a significant impact on the susceptibility of landslides. [ABSTRACT FROM AUTHOR]

LaNi 3.50 and La 0.80 Mg 0.20 Ni 3.50 hydrogen storage alloys with single-phase Ce 2 Ni 7 -type structure are prepared, respectively. It is found that the expansion of [A 2 B 4 ] subunits volumes of Mg-containing alloy is bigger than that of Mg-free alloy, while the expansion of [AB 5 ] subunits volumes of the two alloys are almost the same, hence the deviation value of [A 2 B 4 ] and [AB 5 ] subunits volumes and strain value of super stacking structure for Mg-containing alloy are obviously higher than those of Mg-free alloy, and Mg-containing alloy is easier to be pulverized during charge/discharge cycles. Mg-containing alloy has more apparent cracks on the surface of alloy at the same cycle numbers, which demonstrate that Mg-containing alloy has poorer anti-pulverization. Besides, the presence of Mg hydroxides with a regular hexagon shape makes the surface of Mg-containing alloy become loose enough to be easily oxidized after charge/discharge cycles. The corrosion current density of Mg-containing alloy is larger than that of Mg-free alloy, so Mg-containing alloy is easier to be oxidized. Therefore, reducing the deviation value of [A 2 B 4 ] and [AB 5 ] subunits of super stacking structure and the corrosion of alloying element Mg is the basic solution to enhance the electrochemical cycling stability of La Mg Ni alloy. [ABSTRACT FROM AUTHOR]

We construct and analyze piecewise approximations of functional data on arbitrary 2D bounded domains using generalized barycentric finite elements, and particularly quadratic serendipity elements for planar polygons. We compare approximation qualities (precision/convergence) of these partition-of-unity finite elements through numerical experiments, using Wachspress coordinates, natural neighbor coordinates, Poisson coordinates, mean value coordinates, and quadratic serendipity bases over polygonal meshes on the domain. For a convex n -sided polygon, the quadratic serendipity elements have 2 n basis functions, associated in a Lagrange-like fashion to each vertex and each edge midpoint, rather than the usual n ( n + 1 ) / 2 basis functions to achieve quadratic convergence. Two greedy algorithms are proposed to generate Voronoi meshes for adaptive functional/scattered data approximations. Experimental results show space/accuracy advantages for these quadratic serendipity finite elements on polygonal domains versus traditional finite elements over simplicial meshes. Polygonal meshes and parameter coefficients of the quadratic serendipity finite elements obtained by our greedy algorithms can be further refined using an L 2 -optimization to improve the piecewise functional approximation. We conduct several experiments to demonstrate the efficacy of our algorithm for modeling features/discontinuities in functional data/image approximation. [ABSTRACT FROM AUTHOR]

The El-Niño Southern Oscillation (ENSO), one of the most well-known climate modes, can lead to large-scale climate variability and subsequent crop loss, posing a severe risk to global food security. The study's main goal was to examine the synchronous impacts of ENSO and the probability of simultaneous ENSO–related crop loss on the global yields of major crops and investigate the predictability of finer-scale variation in crop yields based on ENSO-related large-scale climate precursors. Here, using updated crop census data for ∼12,000 political units, the study first investigated the synchronous impact of ENSO on yield variability of major crops (i.e., maize, rice, wheat, and soybean) using Synthetic Analysis and bootstrap method, and then estimated the probability of simultaneous crop loss in the top five crop-producing countries by copula approach. Finally, multiple regression was developed to identify the best forecast model, the corresponding ENSO indices, and the lead time for each political unit based on pre-occurred ENSO indices. The results show that 12.8% (2.1%), 13.4% (6.4%), 11.8% (10.2%), and 8.4% (18.3%) of wheat, rice, maize, and soybean harvest areas were significantly negatively (positively) associated with El Niño, respectively; and 7% (11.7%), 20.2% (3.4%), 5.8% (5.6%), and 14% (6.4%) with La Niña. El Niño reduced global-mean crop yield by 1.32%, 1.33%, and 0.37% for wheat, rice, and maize, respectively, but increased it for soybean by 1.9%. La Niña reduced the global mean yield for rice (2.1%), maize (1.5%), and soybean (1.3%) but increased it for wheat (1.0%). Rice (6.6%) had the highest probability of simultaneous loss during the El Niño phase, whereas La Niña is soybean (5.9%). Based on the early ENSO signals, crop yield could be reliably forecasted for ∼32.05%, ∼42.2%, ∼21%, and ∼ 26.37% of global harvest areas, with R2 being 0.24, 0.26, 0.24, and 0.23 and a lead time of 1–12 months, for wheat, rice, maize, and soybean, respectively. The results suggest that although the reliable yield prediction based on ENSO indexes alone can be developed in a limited proportion of harvest areas, it is skillful in the ENSO-sensitive regions. The findings improved the understanding of ENSO-induced crop yield variability and developed novel approaches to forecast global crop yields based on early ENSO signals. [Display omitted] • The synchronous and pre-occurred impacts of ENSO on global yield variation remain elusive. • The predictability of finer-scale yield variation was investigated based on early ENSO signals. • The ENSO impacts varied with the crop type, growing season, location, and ENSO phase. • Approximately a fourth of (23–26%) yield variation could be reliably forecasted by ENSO indices alone. • The resultant global patterns of ENSO impacts on crop yield are valuable for developing an effective early warning system. [ABSTRACT FROM AUTHOR]

Background Pulmonary fibrosis is a scaring process related to chronic lung injury of all causes. The treatment options for pulmonary fibrosis are very limited. Rhapontin has anti-inflammatory effect and anti-proliferative activity which is widely distributed in the medicinal plants of Rheum genus in China. However, the anti-fibrotic activities of rhapontin have not been previously investigated. Methods The effect of rhapontin on TGF-β1-mediated extracellular matrix (ECM) deposition in primary lung fibroblast (PLF) cells, on TGF-β1 secretion in LPS-stimulated human THP-1 derived macrophages in vitro , and on bleomycin (BLM)-induced pulmonary fibrosis was investigated in vivo . Fibrotic mice were induced by intratracheal instillation of bleomycin, and then treated with rhapontin (25, 50, or 100 mg/kg/day) or prednisone (6.5 mg/kg/day, positive drug) for 2 weeks. Results In TGF-β1 stimulated PLFs, treatment with rhapontin resulted in a reduction of ECM with a decrease in Lox2 and p-Smad2/3. In LPS activated macrophages, treatment with rhapontin reduced TGF-β1 production. However, in vitro the attenuated ECM deposition and inflammatory response by rhapontin were closely associated with AMPK activation, and these suppression of rhapontin were significantly abolished by the AMPK inhibitor. Treatment with rhapontin for 2 weeks resulted in an amelioration of the BLM-induced pulmonary fibrosis in rats with a lower Lox2, whereas a higher AMPK expression, with reductions of the pathological score, collagen deposition, TGF-β1, α-SMA, Lox2, and HIF-1α expressions in lung tissues at fibrotic stage at 100 mg/kg. Conclusion In summary, rhapontin reversed ECM, as well as Lox2 proliferation in vitro and prevented pulmonary fibrosis in vivo by modulating AMPK activation and suppressing the TGF-β/Smad pathway. [ABSTRACT FROM AUTHOR]

Recently, new non-tensor product splines, called as triangle configuration B-splines (TCB-splines), have been proposed, which generalize the Delaunay configuration B-splines (DCB-splines) by introducing more flexibility in knot geometry while preserving the most attractive properties of univariate B-splines ( Liu and Snoeyink, 2007 ). In this paper, we present a surface reconstruction framework that explores the flexibility of this spline for its use in shape modeling. Starting from a carefully designed feature-sensitive triangulation, we apply the so-call link triangulation procedure to obtain a feature-sensitive configuration family and then construct simplex spline bases as well as spline surface on it. The approximation quality of the surface is then progressively improved by adaptively adding more knots onto the parametric domain according to the fitting errors obtained in the previous fit procedure and updating the feature-sensitive configurations. Conditions to ensure the C 1 continuity of the whole result surface are also provided. Our framework is tested on several models to demonstrate its efficacy and ability in preserving geometric features. Compared with DCB-splines, our splines can generate visually pleasant surfaces with smaller fitting errors by using the same number of knots and iterations. With almost the same number of control points, our framework produces more accurate and visually pleasant results than the classical B-spline surface fitting method based on adaptive knot placement strategy ( Park, 2011 ). In addition, the resultant surface provides a control net, which enables an intuitive user interactive design. [ABSTRACT FROM AUTHOR]

The prevailing of Web 2.0 techniques has led to the boom of web video content as well as its social network. To overcome the information overload problem, effective web video topic discovery and structuring techniques are highly demanded. To this end, existing works go to two respective directions: video topic discovery based on content or community detection in social network, with limited interplay between topics and network structures. In this paper, we construct the video social network based on web user interactions over videos. By comparing the topics and communities discovered on this network, we unveil the loose correspondence relationship between content and social network, and correspondingly propose a novel community-driven web video topic discovery model, which regularizes the topic model in relaxed community-level. Quantitatively analysis on real-world YouTube data shows that our model has achieved a significant improvement over the purely content-based or network-based baselines. Meanwhile, we propose a community-based topic structuralization framework, which decomposes a topic in social network space, and tracks the spreading trajectory of this topic among different communities on the time line. This structuralization can help users to catch the important facets of topics, such as “Who is interested with this topic” and “How does it propagate among the communities”, which provide valuable insights in related applications such as web monitoring and market development. [ABSTRACT FROM AUTHOR]

A new gadolinium diethylenetriamine pentaacetic acid (DTPA) complex (Gd-DTPA-DMABA-CS 11 ) as a potential bimodal magnetic resonance imaging (MRI) contrast agent with fluorescence was synthesized. It was synthesized by the incorporation of 4-dimethylaminobenzaldehyde (DMABA) and chitosan oligosaccharide (CS n ; n = 11) with low polydispersity index to DTPA anhydride and then chelated with gadolinium chloride. The structure was characterized by Fourier transform infrared (FTIR), 1 H NMR, elemental analysis and size exclusion chromatography (SEC). MRI measurements in vitro were evaluated. The results indicated that Gd-DTPA-DMABA-CS 11 provided higher molar longitudinal relaxivity ( r 1 ) (12.95 mM − 1 · s − 1 ) than that of commercial Gd-DTPA (3.63 mM − 1 · s − 1 ) at 0.5 T. Gd-DTPA-DMABA-CS 11 also emitted fluorescence, and the intensity was much stronger than that of Gd-DTPA. Therefore, it can be meanwhile used in fluorescent imaging for improving the sensitivity in clinic diagnosis. Gd-DTPA-DMABA-CS 11 as a potential contrast agent is preliminarily stable in vitro . The results of thermodynamic action between Gd-DTPA-DMABA-CS 11 and bovine serum albumin (BSA) illustrated that the binding process was exothermic and spontaneous, and the main force was van der Waals’ interaction and hydrogen bond. The preliminary study suggested that Gd-DTPA-DMABA-CS 11 could be used in both magnetic resonance and fluorescent imaging as a promising bimodal contrast agent. [ABSTRACT FROM AUTHOR]

Isogeometric analysis (IGA) was introduced to integrate methods for analysis and computer-aided design (CAD) into a unified process. High-quality parameterization of a physical domain plays a crucial role in IGA. However, obtaining high-quality parameterizations for complex geometries retains a challenge. Triangle configuration based bivariate simplex splines (TCB-splines) and their rational extensions provide an attractive alternative to classical nonuniform rational B-splines (NURBS) in the context of IGA, as they not only share many desired properties with NURBS but also can be defined over general polygonal domains. In this work, using TCB-splines in IGA is suggested to overcome the limits posed by the tensor-product structure of NURBS. We present the methodology for IGA to use rational TCB-splines over general polygonal domains. Then a method to generate the parametric domain according to given physical domain boundaries is proposed. This allows us to obtain a high-quality parameterization easily without resorting to the optimization method. Several numerical examples with complex physical domains demonstrate the flexibility of our TCB-spline-based IGA method, the high quality of the parameterization, and the accuracy of the numerical solutions. [ABSTRACT FROM AUTHOR]

This paper proposes a method for the construction of quadratic serendipity element (QSE) shape functions on planar convex and concave polygons. Existing approaches for constructing QSE shape functions are linear combinations of the pair-wise products of generalized barycentric coordinates with linear precision, restricted to the convex polygonal domain or resort to numerical optimization. We extend the construction to general polygons with no more than three collinear consecutive vertices. This is done by defining coefficients of the linear combination as the oriented area of triangles with vertices from the polygonal domain, which can be either convex or concave. The proposed shape functions possess linear to quadratic precision. We prove the interpolation error estimates for mean value coordinate-based QSE shape functions on convex and concave polygonal domains satisfying a set of geometric constraints for standard finite element analysis. We also tailor a polygonal mesh generation scheme that improves the uniformity and avoids short edges of Voronoi diagrams for their use in the QSE-based polygonal finite element computation. Numerical tests for the 2D Poisson equations on various domains are presented, demonstrating the optimal convergence rates in both the L 2 -norm and the H 1 -seminorm. • Construction of quadratic serendipity shape functions on convex/concave polygons. • Interpolation error estimates for MVC-based quadratic serendipity shape functions. • Mesh generation for quadratic serendipity element based finite element computation. [ABSTRACT FROM AUTHOR]

Abstract: Spectral clustering consists of two distinct stages: (a) construct an affinity graph from the dataset and (b) cluster the data points through finding an optimal partition of the affinity graph. The focus of the paper is the first step. Existing spectral clustering algorithms adopt Gaussian function to define the affinity graph since it is easy to implement. However, Gaussian function is hard to depict the intrinsic structure of the data, and it has to specify a scaling parameter whose selection is still an open issue in spectral clustering. Therefore, we propose a new definition of affinity graph for spectral clustering from the graph partition perspective. In particular, we propose two consistencies: smooth consistency and constraint consistency, for affinity graph to hold, and then define the affinity graph respecting these consistencies in a regularization framework of ranking on manifolds. Meanwhile the proposed definition of affinity graph is applicable to both unsupervised and semi-supervised spectral clustering. Encouraging experimental results on synthetic and real world data demonstrate the effectiveness of the proposed approach. [Copyright &y& Elsevier]

Abstract: Recently, a new bivariate simplex spline scheme based on Delaunay configuration has been introduced into the geometric computing community, and it defines a complete spline space that retains many attractive theoretic and computational properties. In this paper, we develop a novel shape modeling framework to reconstruct a closed surface of arbitrary topology based on this new spline scheme. Our framework takes a triangulated set of points, and by solving a linear least-square problem and iteratively refining parameter domains with newly added knots, we can finally obtain a continuous spline surface satisfying the requirement of a user-specified error tolerance. Unlike existing surface reconstruction methods based on triangular B-splines (or DMS splines), in which auxiliary knots must be explicitly added in advance to form a knot sequence for construction of each basis function, our new algorithm completely avoids this less-intuitive and labor-intensive knot generating procedure. We demonstrate the efficacy and effectiveness of our algorithm on real-world, scattered datasets for shape representation and computing. [Copyright &y& Elsevier]

Abstract: Topic models have been successfully used in information classification and retrieval. These models can capture word correlations in a collection of textual documents with a low-dimensional set of multinomial distribution, called “topics”. However, it is important but difficult to select the appropriate number of topics for a specific dataset. In this paper, we study the inherent connection between the best topic structure and the distances among topics in Latent Dirichlet allocation (LDA), and propose a method of adaptively selecting the best LDA model based on density. Experiments show that the proposed method can achieve performance matching the best of LDA without manually tuning the number of topics. [Copyright &y& Elsevier]

Abstract: The Class A Bézier curves presented in Farin (2006) were constructed by so-called Class A matrix, which are special matrices satisfying two appropriate conditions. The speciality of the Class A matrix causes the Class A Bézier to possess two properties, which are sufficient conditions for the proof of the curvature and torsion monotonicity. In this paper, we discover that, in Farin (2006), the conditions Class A matrix satisfied cannot guarantee one of the two properties of the Class A Bézier curves, then the proof of the curvature and torsion monotonicity becomes incomplete. Furthermore, we modified the conditions for the Class A matrices to complete the proof. [Copyright &y& Elsevier]

In this paper, a set of quasi-Bernstein polynomials of degree n with one parameter is presented, which is an extension of the Bernstein polynomials over the triangular domain. Using the presented polynomials as basis functions, we construct a class of shape adjusting surfaces defined over the triangular domain with a shape parameter, namely, quasi-B-B parametric surfaces. These surfaces share many properties with the B-B parametric surfaces. In particular, when shape parameters equal 1, they degenerate to be the B-B parametric surfaces. By changing the value of the shape parameter, we can get different surfaces under the fixed control net. [ABSTRACT FROM AUTHOR]

• Two polysaccharide fractions (WXA-1 and AXA-1) are obtained from wheat bran. • The compositions and structural characterizations of WXA-1 and AXA-1 are different. • AXA-1 exhibits stronger α-amylase and α-glucosidase inhibitory activities compared with WXA-1. In this study, two polysaccharide fractions were isolated from wheat bran by sequential extraction with water and alkaline solution, DEAE Cellulose-52 chromatography and Sephacryl S-400 gel permeation chromatography, they were named as WXA-1 and AXA-1, respectively. Structural analyses indicated that both polysaccharide fractions were heteropolysaccharides, their average molecular weights were 193 kDa and 107 kDa, respectively. The backbone of WXA-1 was → 4)-β- d -Xyl p -(1→, which was substituted at O -3 positions by arabinose, glucose and galactose residues, while the backbone of AXA-1 was → 4)-β- d -Xyl p -(1→, which was mainly substituted at O -3 positions by arabinose. AXA-1 exerted a stronger inhibitory effect on the activities of α-amylase and α-glucosidase compared with WXA-1. Moreover, AXA-1 exhibited a competitive inhibition of α-amylase and a mixed-type noncompetitive inhibition of α-glucosidase. These results suggest that AXA-1 can be used as α-amylase and α-glucosidase inhibitors. [ABSTRACT FROM AUTHOR]

• Adapting three machine/deep learning models to predict rice yield at county-level • LSTM performs better than RF and LASSO models • Combining EVI and SIF together improves yield prediction than using EVI or SIF • Develop a scalable, simple and inexpensive framework for timely predicting rice yield • The yield prediction framework use publicly available multi-source data Timely and reliable yield prediction at a large scale is imperative and prerequisite to prevent climate risk and ensure food security, especially with climate change and increasing extreme climate events. In this study, integrating the publicly available data (i.e., satellite vegetation indexes, meteorological indexes, and soil properties) within the Google Earth Engine (GEE) platform, we developed one Least Absolute Shrinkage and Selection Operator (LASSO) regression, one machine learning (Random Forest, RF), and one deep learning (Long Short-Term Memory Networks, LSTM) model to predict rice yield at county-level across China. For satellite data, we compared the contiguous solar-induced chlorophyll fluorescence (SIF), a newly emerging satellite retrieval, with a traditional vegetation index (enhanced vegetation index, EVI). The results showed that LSTM (with R2 ranging from 0.77 to 0.87, RMSE from 298.11 to 724kg/ha) and RF (with R2 ranging from 0.76 to 0.82, RMSE from 366 to 723.3 kg/ha) models outperformed LASSO (with R2 ranging from 0.33 to 0.42, RMSE from 633.46 kg/ha to 1231.39 kg/ha) in yield prediction; and LSTM was better than RF. Besides, ESI (combining EVI and SIF together) could slightly improve the model performance compared with only using EVI or SIF as the single input, primarily due to the ability of satellite-based SIF in capturing extra information on drought and heat stress. Furthermore, we also explored the potential for timely rice yield prediction, and concluded that the optimal prediction could be achieved with approximately two/one-month leading-time before single/double rice maturity. Our findings demonstrated a scalable, simple and inexpensive methods for timely predicting rice yield over a large area with publicly available multi-source data, which can potentially be applied to areas with sparsely observed data and worldwide for estimating crop yields. [ABSTRACT FROM AUTHOR]

• Develop a scalable and simple framework to timely estimate yields. • Adapt deep learning and machine learning models to predict yields over large areas. • Spatial characteristics parameters are important for predicting wheat yields. • Machine learning sometimes performs better than deep learning. To meet the challenges of climate change, increasing population and food demand, a timely, accurate and reliable estimation of crop yield at a large scale is more imperative than ever for crop management, food security evaluation, food trade and policy-making. In this study, taking the major winter wheat production regions of China as an example, we compared a traditional machine learning method (random forest, RF) and three deep learning (DL) models, including DNN (deep neural networks), 1D-CNN (1D convolutional neural networks), and LSTM (long short-term memory networks) to predict crop yields by integrating publicly available data within the GEE (Google Earth Engine) platform, including climate, satellite, soil properties, and spatial information data. The results showed that all four models could capture winter wheat yield variations in all the county-years, with R2 of recorded and simulated yields ranging from 0.83 to 0.90 and RMSE ranging from 561.18 to 959.62 kg/ha. They all performed well for winter wheat yield prediction at a county level from 2011 to 2015, with mean R2≥0.85 and RMSE ≤ 768 kg/ha. At a field level, the spatial pattern of estimated winter wheat yield could capture the spatial heterogeneity and yield differences between individual fields across a county fairly well. However, only the DNN and RF models had relatively good performance at the field level, with mean R2 values of 0.71, 0.66 and RMSE values of 1127 kg/ha and 956 kg/ha, respectively. The model comparisons showed that the performance of RF was not always worse than DL at both the county and field levels. Our findings demonstrated a scalable, simple and inexpensive framework for estimating crop yields at various scales in a timely manner and with reliable accuracy, which has important implications for crop yield forecasting, agricultural disaster monitoring, food trade policy, and food security warning. [ABSTRACT FROM AUTHOR]

• We propose an improved dataset for research on image privacy. • We build a knowledge graph that represents the relevance between the objects and image privacy. • Based on the graph, we deal with the traditional image classification problem with the novel graph-based neural network. • The introduction of the knowledge graph not only makes the model more explainable but also makes better use of the information of objects provided by the images. • Our method relies on the intrinsic relevance in the dataset rather than extra knowledge, thus is applicable for other tasks. With the development of social media and smartphones, people share their daily lives via a large number of images, but the convince also raises a problem of privacy leakage. Therefore, effective methods are needed to infer the privacy risk of images and identify images that may disclose privacy. Several works have tried to solve this problem with deep learning models. However, we know little about how the models infer the privacy label of an image, thus it is not easy to understand why the image may disclose privacy. Inspired by recent research on graph neural networks, we introduce prior knowledge to the deep models to make the inference more explainable. We propose the Graph-based neural networks for Image Privacy (GIP) to infer the privacy risk of images. The GIP mainly focuses on objects in an image, and the knowledge graph is extracted from the objects in the dataset without reliance on extra knowledge. Experimental results show that the GIP achieves higher performance compared with the object-based methods and comparable performance even compared with the multi-modal fusion method. The results show that the introduction of the knowledge graph not only makes the deep model more explainable but also makes better use of the information of objects provided by the images. Combing the knowledge graph with deep learning is a promising way to help protect image privacy that is worth exploring. [ABSTRACT FROM AUTHOR]

The grain size of sediment delivered to a river by hillslope processes is an important factor which could impact fluvial erosion, sediment transport, and associated geomorphic changes. Grain size distribution (GSD) is increasingly recognised as an important factor for the impact of landslides on sediment pulses and long-term erosion rates. Therefore a better comprehension of grain size control on landslide-generated sediment transport and dynamics will help with understanding post-seismic fluvial processes and landscape evolution. In this study, we modelled the recovery of the Hongxi River basin affected by the Wenchuan earthquake under different landslide GSD scenarios. The CAESAR-Lisflood (CL) model was first modified to enable the spatial input of sediment GSD, which allows the model to distinguish the grain size composition of landslide sediment and the background sediment sourced from other areas. Using the modified CL model, we simulated three different landslide GSD scenarios (Original, Coarser, Finer) by altering the original landslide sediment GSD observed from a post-earthquake basin. In particular, we analysed the fate of landslide-generated sediment using a new sediment tracing function embedded in CL. This enabled us to evaluate the role of landslide GSD variation on the spatio-temporal heterogeneity of sediment transport. Our results show that the GSD of landslide material exerts a clear control on both sediment yield and channel deposition, the sediment transport of landslides disconnected to the fluvial system is more sensitive to grain size variation, while the GSD of landslides connected to the fluvial system has less impact on sediment dynamics. The duration of landslide disturbances on basin sediment dynamics can largely be dependent on the period of time (e.g., 20 years in this study basin) taken for grain coarsening (the grain size is increasing upward), which is dominated by the evacuation of fine sediments. The modelling results and findings highlight the importance of grain size distribution of landslide material and provide information to support basin sediment management and environmental risk mitigation. [ABSTRACT FROM AUTHOR]

• Circ-0060428 high expressed in osteosarcoma cells. • Circ-0060428 promoted proliferation and reduced apoptosis of osteosarcoma cells. • Circ-0060428 target sponges miR-375 to upregulate RBPJ. Osteosarcoma (OS) is the most common primary bone tumor, and mainly occurs in children and early adults. The overall pathogenesis of osteosarcoma remains unclear. Circular RNAs (circRNAs) have been demonstrated to be one of the regulators in tumors as non-coding RNAs. In present study, we identified an elevated expressed circ-0060428 in osteosarcoma cells. The results of CCK-8 and flow cytometry assay showed that circ-0060428 promoted cell proliferation and reduced cell apoptosis of osteosarcoma cells. Bioinformatics analyses predicted the binding site between miR-375 to RPBJ and circ-0060428, and dual luciferase reporter assay verified this prediction. Furthermore, miRNA inhibitor of miR-375 could recover the influence of cell proliferation and apoptosis by knocking down the expression of circ-0060428. Meanwhile, knockdown of both circ-0060428 and RBPJ resulted in a lower apoptosis rate than circ-0060428 alone. Western blot analyses indicated that circ-0060428 regulated the expression of apoptosis related proteins (Bax, Bcl-2, and cleaved-Caspase-3) by upregulating RPBJ expression in osteosarcoma cells. Altogether, we confirmed the up-regulated circ-0060428 could improve the proliferation and survival of osteosarcoma cells by sponging miR-375 to upregulate RBPJ expression. This finding supported a novel clinically biomarker and treatment target for osteosarcoma therapy. [ABSTRACT FROM AUTHOR]

Recently, triangle configuration based bivariate simplex splines (referred to as TCB-spline) have been introduced to the geometric computing community. TCB-splines retain many attractive theoretic properties of classical B-splines, such as partition of unity, local support, polynomial reproduction and automatic inbuilt high-order smoothness. In this paper, we propose a computational framework for isogeometric analysis using TCB-splines. The centroidal Voronoi tessellation method is used to generate a set of knots that are distributed evenly over the domain. Then, knot subsets are carefully selected by a so-called link triangulation procedure (LTP), on which shape functions are defined in a recursive manner. To achieve high-precision numerical integration, triangle faces served as background integration cells are obtained by triangulating the entire domain restricted to all knot lines, i.e., line segments defined by any two knots in a knot subset. Various numerical examples are carried out to demonstrate the efficiency, flexibility and optimal convergence rates of the proposed method. • A TCB-splines based method is proposed for FEA on general domains. • Local refinement is flexible without introducing undesirable propagation. • Spline functions are globally C1-continuous. • Optimal convergence rates are numerically demonstrated. [ABSTRACT FROM AUTHOR]

The traditional Chinese medicine formula Danggui-Shaoyao-San (DSS) has been reported to have estrogen-like effects and therapeutic effects on the symptoms of Alzheimer's disease (AD). To explore whether the central oxytocin and neuroendocrine system is involved in the modulating effects of DSS on the cognition and neuropsychiatric hebaviors in female AD rats, and to investigate the pharmacokinetics of paeoniflorin and ferulic acid in female AD rats with DSS treatment. DSS (1.2, 3.2, 8.6 g/kg/day) was orally administered to ovariectomized (OVX) rats, and saline was orally administered to sham operation rats as control group. The Morris water maze test, novel object recognition test, and passive avoidance test were conducted for evaluation of learning and memory abilities, while elevated plus maze test and forced swim test were performed to assess anxiety- and depressive-like behaviors. ELISA kits were used to detect the levels of estrogen (E), estrogen receptor α (ERα), oxytocin (OT), oxytocin receptor (OTR), acetylcholine (Ach), acetylcholin esterase (AchE), and choline acetyl transferase (ChAT) in the cortex. The concentrations of Ach, glutamate (Glu), γ-aminobutyric acid (GABA), 5-hydroxytryptamine (5-HT), norepinephrine (NE) and dopamine (DA) in the hippocampus were assessed by HPLC-MS. The changes of neuronal morphology in the hippocampus were observed by Nissl staining. The pharmacokinetics of paeoniflorin and ferulic acid in OVX rats with DSS treatment were studied by HPLC. In the Morris water maze test, novel object recognition test, and passive avoidance test, OVX rats showed cognitive impairment. In the elevated plus maze test and forced swim test, the anxiety- and depressive-like behaviors of OVX rats were significant as compared to the control group. Treatment of DSS significantly imporved the cognitive deficits, and ameliorated anxiety- and depressive-like behaviors of OVX rats. The expression of E, ERα, OT, OTR, AchE and ChAT in the cortex of model group were significantly decreased, and DSS significantly reversed these changes. The concentrations of Ach, Glu, GABA, 5-HT and NE in the hippocampus of OVX rats were significantly decreased, whereas DSS significantly increased the levels of Ach, Glu, GABA, 5-HT and NE. There was no significant difference in the concentration of DA in the hippocampus among groups. Degenerating neurons in the hippocampal CA3 region were observed in OVX rats, and the number of neurons was decreased. DSS treatment reduced the degenerating neurons, and incresed the number of neurons. The MRT (0 - ∞), AUC (0 - ∞), Cmax and t1/2z values of paeoniflorin, and the AUC 0-∞ and C max value of ferulic acid were higher in DSS-treated OVX rats than those in the DSS-treated control rats. DSS improves the learning and memory ability, and attenuates anxiety- and depressive-like behaviors of OVX rats. The mechanism may be through increasing estrogen, reducing cholinergic damage, and modulating neurotransmitters. The increase in absorption and elimination time of paeoniflorin and ferulic acid in OVX rats may enhance the efficacy of DSS. [Display omitted] • DSS can improve the learning and memory ability and pathological changes of OVX rats, which may be related to the increase of estrogen level, inhibition of AChE and up-regulation of ChAT expression. • DSS can improve the neurotransmitters related to anxiety and depression in OVX rats. • DSS in OVX rats were increased, and the time of drug effect in vivo was prolonged, thus the efficacy of DSS was enhanced. [ABSTRACT FROM AUTHOR]

Abstract Polynomial Pythagorean hodograph (PH) curves have a polynomial arc length function and rational offsets, which distinguish PH curves from general polynomial parametric curves. However, these algebraic properties can hardly be used directly for the identification of PH curves. In order to determine whether or not a given septic planar polynomial curve is a PH curve, Zheng et al. (2016) studied a class of septic curves' geometric properties and proposed an efficient algorithm. In this paper, we further complete their work on Bézier control polygons of septic PH curves. We point out that there are three classes of septic PH curves according to different factorizations of their derivatives. Except the first class which has been studied, geometric characteristics of the other two classes are proposed. By introducing auxiliary points, the results are in terms of angles and lengths of legs of their Bézier control polygons. Moreover, we give feasible methods for the construction of auxiliary points, including various degenerate cases. [ABSTRACT FROM AUTHOR]

Smoke inhalation injury (SII) is an independent risk factor for morbidity and mortality in patients with severe burns, however, the underlying mechanisms of SII are still not fully understood. In our study, we established an advanced rat model of SII based on the previous work, and explored the dynamic changes of pathophysiology and inflammatory factors during 28days post SII. We also measured the different expressions of miRNAs in bronchoalveolar lavage fluid (BALF) between SII and normal control rats by miRNA microarray. At 1day after smoke inhalation, the histopathological results exhibited inflammatory exudates in the lung tissue with significant edema. As time went on, the lung injuries gradually appeared at alveolar septum thickening and alveolar collapse, which suggested that it further induced damage to lung parenchyma by smoke inhalation. Particularly, the collagen deposition indicating pulmonary fibrosis happened at 28days post-injury. Plasma IL-6 and TNF-a were significantly increased after 1day of smoke inhalation. Plasma IL-10, BALF TNF-α and IL-10 were significantly increased after 2days of smoke inhalation. By extending the observation time, the levels of plasma IL-6, BALF TNF-a and IL-10 appeared a second peak again after 14days of injury. Compared with the normal control group, there were 23 upregulated miRNAs and 2 downregulated miRNAs in BALF of SII group at 1day post-injury. RT-qPCR validation assay confirmed that the changes of miR-34c-5p, miR-92b-3p, miR-205, miR-34b-3p, miR-92a-3p, let-7b-5p, let-7c-5p in BALF were consistent with the conclusion of the miRNA microarray. In summary, we showed the dynamic changes of pathologic changes and inflammatory factors in rats with SII, and a subset of seven miRNAs changed in BALF after SII which may be used for diagnosis and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Abstract Although vitamin D is essential for bone health, little is known about prevalence of vitamin D deficiency and low bone mineral density (BMD) among children, especially those in developing countries. It also remains unclear whether serum 25-hydroxyvitamin D [25(OH)D] is associated with BMD among children. We investigated these questions among children and adolescents in Yinchuan (latitude: 38° N), Ningxia, an economically underdeveloped province in Northwest China. A total of 1582 children (756 boys and 826 girls), aged 6–18 years, were recruited from schools using the stratified random sampling method in fall 2015. Serum 25(OH)D concentrations were measured by enzyme-linked immunosorbent assay, and BMD was quantified by dual-energy X-ray absorptiometry. Vitamin D deficiency (defined as serum 25(OH)D ≤ 37.5 nmol/L) was present in 35.5% of study subjects. There were no clear patterns of differences in serum 25(OH)D concentrations across the four age groups compared (6–9 years, 10–13 years, 14–16 years, and 17–18 years). The prevalence of low total body less head (TBLH) BMD (defined as a Z -score of ≤ −2.0 standard deviations away from the mean BMD values of the Chinese pediatric reference population) among children examined was 1.8% and was not significantly different among the four age groups considered. Linear regression analysis revealed that age, weight, and height were significantly and positively associated with TBLH BMD and that the strongest determinant of TBLH BMD was age in boys and weight in girls. There were no significant correlations between serum 25(OH)D concentrations and BMD obtained for total body and at various skeletal sites (r ranged from −0.005 to 0.014) regardless of whether children evaluated were sufficient, insufficient, or deficient in vitamin D. In conclusion, more than one-third of children and adolescents in a Northwest Chinese city were deficient in vitamin D but only <2% of them developed low BMD. Highlights • Vitamin D deficiency (serum 25(OH)D ≤37.5 nmol/L) existed in 35.5% of 1582 school children in a Northwest Chinese city. • The prevalence of low total body less head (TBLH) bone mineral density (BMD) among school children examined was 1.8%. • Age, weight, and height were positively associated with TBLH BMD among this pediatric Chinese population in both sexes. • The strongest determinant of TBLH BMD was age in boys and weight in girls. • Serum 25(OH)D was overall not associated with BMD (total body and various skeletal sites) regardless of vitamin D status. [ABSTRACT FROM AUTHOR]

This paper presents a novel technique for resampling point clouds of a smooth surface. The key contribution of this paper is the generalization of centroidal Voronoi tessellation (CVT) to point cloud datasets to make point resampling practical and efficient. In particular, the CVT on a point cloud is efficiently computed by restricting the Voronoi cells to the underlying surface, which is locally approximated by a set of best-fitting planes. We also develop an efficient method to progressively improve the resampling quality by interleaving optimization of resampling points and update of the fitting planes. Our versatile framework is capable of generating high-quality resampling results with isotropic or anisotropic distributions from a given point cloud. We conduct extensive experiments to demonstrate the efficacy and robustness of our resampling method. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel method for generating cell complexes with anisotropy conforming to the Hessian of an arbitrary given function. This is done by variationally optimizing the discontinuous piecewise linear approximation of the given functions over power diagrams. The resulting cell complexes corresponding to the approximations are referred to as Optimal Power Diagram (OPD). A hybrid optimization technique, coupling a modified Monte Carlo method with a local search strategy, is tailored for effectively solving the specific optimization task. In contrast to the Optimal Voronoi Tessellation (OVT) method (Budninskiy et al., 2016), our OPD method does not restrict the target functions to be convex, providing more diverse classes of tessellations of the domain. Furthermore, our OPD method generally yields smaller approximation errors than the OVT method, which uses underlaid approximants. We conduct several experiments to demonstrate the efficacy of our optimization algorithm in finding good local minima and generating high-quality anisotropic polytopal meshes. [ABSTRACT FROM AUTHOR]

Atmospheric carbonyls are important precursors of PM 2.5 and ground-level ozone, and some carbonyls are toxic and harmful; thus, it is crucial to obtain accurate information on the ambient levels of carbonyls. However, the detection of carbonyls is difficult due to their relatively higher reactivities and chemical instabilities; therefore, accurate determination of atmospheric carbonyls is important. In this study, an analytical method for atmospheric carbonyls with high concentration or reactivity was developed, the precursor ion of each carbonyl compound was selected, and the declustering potential (DP) and entrance potential (EP) for each precursor ion were optimized. A 2,4-dinitrophenylhydrazine cartridge derivatization-high performance liquid chromatography/atmospheric pressure chemical ionization-mass spectrometry (DNPH-HPLC/APCI-MS) method for the determination of 30 carbonyls was established. The results showed that the linear range of 24 carbonyls was 1.2–600 ng/mL, while other 6 carbonyls was 1.2–300 ng/mL, and the detection limits of 30 carbonyls ranged from 0.092 to 0.947 ng/mL (0.005–0.049 μg/m3 with an ambient air sampling volume of 96 L). The intra-day and inter-day repeatability ranges were 0.55–4.20% and 1.40–12.48%, respectively. A preliminary application of the method was carried out in the urban area of Beijing in spring and summer of 2021, and it was found that the mean total mass concentration of 30 carbonyls was 35.894 μg/m3. This study provided additional concentration information for 14 atmospheric carbonyls, including mono-, di-, oxygen-containing and heterocyclic carbonyls, which accounted for 38% and 35% of the total mass concentration and OH radical reactivities of 30 carbonyls, respectively. This is the first investigation of simultaneous quantitative analysis of multiple atmospheric carbonyls based on commercial standard derivatives. The optimized method could provide more comprehensive information for atmospheric carbonyls and further support research concerning the role of chemical reaction processes and health effects than traditional measuring techniques. [Display omitted] • A comprehensive method for detecting 30 carbonyls using HPLC/MS was investigated. • Simultaneous detection can be applied with simple pre-treatment. • 30 atmospheric carbonyls were quantified in Beijing by this optimized method. • The top three species in Beijing urban area were acetone, formaldehyde and nonanal. • This study highlights the necessity and advancement of carbonyl determination. [ABSTRACT FROM AUTHOR]

To investigate the effect of low-level occupational benzene exposure on human peripheral blood leukocyte counts of the workers, domestic and foreign published research data on the change of human peripheral blood leukocyte counts under low-level occupational benzene exposure from January 1990 to December 2020 were collected and analyzed. According to the literature inclusion and exclusion criteria, 18 independent studies from 12 publications were selected for meta-analysis to explore the effect of low-level occupational benzene exposure on human peripheral blood leukocyte counts. The results showed that the peripheral blood leukocyte counts abnormal rates of low-level occupational benzene exposure group were higher than those of the control group, and the difference was statistically significant. Low-level occupational benzene exposure could result in a relatively higher abnormal rate of peripheral blood leukocyte counts in the exposed population, indicating that low-level occupational benzene exposure at workplaces specified by the current benzene occupational exposure limit in China would affect the peripheral blood leukocyte counts of the workers, thus benzene with concentrations under the limit in the ambient air of workplace could be still harmful to the health of the exposed workers. The results of this study could provide a scientific basis for future revision of the benzene occupational exposure limit in China, and could also be a reference for the formulation of environmental standard concerning benzene in China in the future. [Display omitted] [ABSTRACT FROM AUTHOR]

A high-sensitivity fiber sensor integrated by two cascaded balloon-shaped bent single-mode fiber (BBSMF) Mach-Zehnder interferometers is proposed and demonstrated. A high-order mode can be greatly stimulated due to embedding a seven-core fiber (SCF) between the two BBSMFs. The experimental results show that the maximum temperature sensitivity of the proposed sensor is − 3.35 nm/°C between 13 °C and 71 °C, which is currently the highest temperature sensitivity, in the BBSMF structure as far as we have ever known. Furthermore, the temperature sensitivity can be optimized by changing the length of the SCF and the diameter of the BBSMF. The proposed sensor has the advantages of easy production, low cost, and high sensitivity, which makes it well-suited for precise temperature measurement applications. [Display omitted] • A fiber sensor integrated by two cascaded balloon-shaped bent single-mode fiber (BBSMF) Mach-Zehnder interferometers is proposed. • The maximum intensity temperature sensitivity is − 3.35 nm/°C in the range of 13–71 °C. • The sensor provides a novel way to fabricate a high-sensitivity sensor by combining different types of optical fibers. [ABSTRACT FROM AUTHOR]

• We proposed a hybrid framework for the crop yield forecasting at regional level. • This framework integrates data assimilation, crop model, and machine learning. • The framework was successfully applied with a higher accuracy than previous studies. • This framework is helpful for developing regional food security early warning system. Timely and reliable regional crop yield forecasting before harvest is critical for managing climate risk, adjusting agronomic management, and making food trade policy. Although various methods exist for crop yield forecasting, including process-based crop models and machine learning techniques, the potential of integrating these methods for early-season yield forecasts has not been well investigated. In this study, we proposed a hybrid framework for crop yield forecasting that firstly assimilated leaf area index and soil moisture into a crop model and then combined the data-assimilated crop model with machine learning techniques to improve the prediction skill further. The proposed framework was applied to winter wheat yield forecasting in the North China Plain during 2009–2015. We found that the assimilation significantly enhances wheat yield estimates, achieving additional ACC = 0.27, MAPE = 6.12 %. Incorporating weather forecasts enabled reliable winter wheat yield forecasts up to 1–3 months in advance, achieving ACC = 0.69, MAPE = 7.79 %. Furthermore, integrating the assimilated crop model with machine learning techniques improved the forecasting further, achieving ACC = 0.97 and MAPE = 1.74 %. The proposed framework for crop yield forecasting can be adapted to other crops and regions and has great potential in developing food security early warning system at a regional scale. [ABSTRACT FROM AUTHOR]

Abstract: New bounds on the magnitudes of the first- and second-order partial derivatives of rational triangular Bézier surfaces are presented. Theoretical analysis shows that the proposed bounds are tighter than the existing ones. The superiority of the proposed new bounds is also illustrated by numerical tests. [Copyright &y& Elsevier]

Abstract: This paper studies the asymptotic behavior of solutions for the discrete coupled nonlinear Schrödinger–Boussinesq equations. The authors first prove the existence of a global attractor for the generated semigroup and then obtain an upper bound of the Kolmogorov ε-entropy for the obtained global attractor. Finally, they establish the upper semicontinuity of the global attractor when the infinite lattice systems are approximated by finite lattice systems. [Copyright &y& Elsevier]

• The pH-responsive hydrogel has a good adhesion performance to skin tissue. • The adhesive hydrogel did not cause damage to tissues during the second operation. • Double Schiff base bonds promoted rapid release of AgNPs and DFO at the wound sites. • Dual-mechanisms to promote wound healing included antibacterial and angiogenesis. • The hydrogel was biodegradable and had great biocompatibility. The healing of chronic diabetic wounds remains a key challenge due to its susceptibility to bacterial infection, the inflammatory wound microenvironment, and difficulty in angiogenesis. Herein, a pH-responsive, mussel-inspired, double-crosslinking injectable, and adhesive smart hydrogel formula was exploited to overcome these obstacles simultaneously. The multifunctional double-crosslinking hydrogel was developed through the formation of catechol-catechol adducts and a Schiff-based reaction between amino groups (−NH 2) in chitosan quaternary ammonium salt (HTCC) and aldehyde groups (–CHO) in oxidized dextran-dopamine (OD-DA). The double-crosslinking mechanism gave the hydrogels great mechanical properties. Most importantly, via the effective encapsulation of silver nanoparticles (AgNPs) and pro-angiogenic drug deferoxamine (DFO), the hydrogel was given with antibacterial and angiogenic features respectively. At the infected diabetic wound area, the double Schiff base bonds (DA and OD; HTCC and OD-DA) in the hydrogels could quickly achieve pH-response and accomplish a sustained and controlled release of drugs to accelerate wound healing. Through the combination of AgNPs and HTCC, the hydrogel exhibited antimicrobial capacities to gram-positive bacteria (S. aureus) and gram-negative bacteria (E. coli), it did not cause toxic side effects and avoided drug resistance. The DFO released at the infected diabetic wound area promoted angiogenesis by enhancing the expression of hypoxia-inducible factor-1 alpha (HIF-1α) and vascular endothelial growth factor (VEGF). We elucidated the mechanisms by which the designed hydrogels accelerated the healing of bacterial infected diabetic wounds in vitro and in vivo , and our hydrogels represented a general strategy for the healing of a wide range of tissue injuries. [ABSTRACT FROM AUTHOR]

Prognostic value of soluble suppression of tumorigenecity (sST2), a novel circulating biomarker for myocardial fibrosis, remains elusive in the heart failure patients with preserved ejection fraction (HFpEF). 405 consecutive patients with heart failure (HF) were enrolled prospectively, and were grouped into HF with reduced ejection fraction (HFrEF, N = 215), HF with mid-range ejection fraction (HFmrEF, N = 80) and HFpEF (N = 110). The primary endpoint was the composite endpoint of all-cause death and HF rehospitalization. After a median of 12 months, 139 patients reached the primary endpoint, with 57 patients died and 82 patients rehospitalized. Multivariate analysis confirmed that sST2 was an independent risk factor of the primary endpoint for all HF patients [hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.30–4.22, P = 0.004]. Predicting efficacy of sST2 on outcomes was higher for HFpEF (HR 6.48, 95%CI 1.89–22.21, P = 0.003) as compared to HFrEF (HR 3.21, 95% CI 1.67–6.19, P = 0.000). But the association between sST2 and outcomes in HFmrEF is not statistical (HR 3.38, 95%CI 0.82–13.86, P = 0.091). The combined use of sST2 and N terminal pro B type natriuretic peptide (NT-proBNP) could improve the prognostic value compared to using NT-proBNP alone in HFrEF (AUC = 0.794 vs. 0.752, P = 0.034). Higher baseline sST2 levels are associated with increased risk of all-cause death and HF rehospitalization in patients with HF independent of ejection fraction. The combined use of sST2 and NT-proBNP could improve the prognostic value than using these two values alone, especially for HFrEF patients. • Serum sST2 levels were similar among HFrEF, HFmrEF and HFpEF patients. • sST2 remained as the independent risk factor of the adverse outcomes. • Predicting efficacy of sST2 on outcomes was higher for HFpEF as compared to HFrEF. • The combined use of sST2 and NT-proBNP could improve the prognostic value in HFrEF. [ABSTRACT FROM AUTHOR]

• A high-sensitivity temperature and curvature micro-fiber Mach-Zehnder interferometer (MMZI) sensor is proposed and demonstrated. The composite structure with the tapered seven-core fiber (SCF) and the SCF-SMF peanut structure is fabricated. The new structure sensor can significantly improve the coupling efficiency and stimulate high-order modes in the sensor for high sensitivity. • The maximum temperature sensitivity is 836.67 pm/ °C in the range of 35 °C to 40 °C, which is the highest temperature sensitivity of the peanut-shaped MMZI sensor to the best of our knowledge. Furthermore, the sensor can be used for curvature measurement. When the curvature change from 0 nm/m−1 to 0.0522449 nm/m−1, the sensitivity can achieve 93.33664 nm/m−1. • This composite structure of the proposed sensor provides a novel method to fabricate a high-sensitivity sensor by combining different types of optical fibers. A high sensitivity temperature and curvature micro-fiber Mach-Zehnder interferometer (MMZI) sensor is proposed and demonstrated. A peanut structure is fused by a section of seven-core fiber (SCF) and a section of single-mode fiber (SMF). Then the SCF is connected to another SMF and tapered. Finally, the composite structure with the tapered SCF and the SCF-SMF peanut structure is fabricated. The coupling efficiency can be significantly improved, and more high-order modes can be stimulated via the new sensor structure. The experimental results demonstrated that the maximum temperature sensitivity is 836.67 pm/ °C in the range of 35 °C to 40 °C, which is the highest temperature sensitivity of the peanut-shaped MMZI sensor to the best of our knowledge. Furthermore, the sensor can be used for curvature measurement. When the curvature changes from 0 m−1 to 0.0522449 m−1, the sensitivity can achieve 93.33664 nm/m−1. The proposed sensor not only provides a novel method to fabricate a high-sensitivity sensor by combining different types of fibers, but it also has a meaningful application prospect in the fields of biological detection and environmental monitoring. [ABSTRACT FROM AUTHOR]

• An acoustic sensor with high sensitivity is proposed. • It combines the characteristics of polarization-maintaining fiber, balloon-shaped loop structure and MMZI. • Sensitive to acoustic signals and simple sensor structure. • The acoustic sensitivity is up to 115 mV/Pa, and the minimum detection pressure of the noise limit is 2.1 mPa/√Hz. An acoustic sensor based on balloon-shaped microfiber Mach-Zehnder Interferometer (BSMZI) is proposed and demonstrated. The BSMZI is constructed by bending a tapered polarization-maintaining fiber (PMF), which has the interference phenomenon due to the phase difference between the fundamental mode and cladding modes of the balloon-shaped loop structure. When placing the sensor in front of a loudspeaker and using a fiber Bragg grating (FBG) as the signal reflector, the transmission spectra of the sensor can be changed with the acoustic signals correspondingly. Furthermore, by changing the bending radius of the BSMZI, the maximum sensitivity of the sensor is 115 mV/Pa, and the minimum detection pressure of the noise limit is 2.1 mPa/√Hz when the acoustic frequency range change from 100 Hz to 2000 Hz. The experimental results show that the sensor has a good ability in acoustic detection and has potential application in the fields of nuclear magnetic medical treatment and security interception. [ABSTRACT FROM AUTHOR]

A curvature and temperature sensor based on a double peanut-shaped hollow-core fiber (HCF) Mach–Zehnder interferometer (MZI) is reported and demonstrated for the first time. In the sensor, the two ends of the HCF are fused into two spherical shapes and sandwiched with two spherical-shaped single-mode fibers (SMFs) to form a double peanut-shaped structure (PSS). When incident light injects the HCF through the PSS, the light can greatly stimulate form fundamental mode to cladding modes and achieve high sensitivity in external environment detection. We successfully adjust the curvature and temperature sensitivity by controlling the length of HCF. The maximum curvature sensitivity is -648.17 pm/m−1 when the HCF is 0.73 mm, and the maximum temperature sensitivity is 25.42 pm/°C when the HCF is 0.97 mm. In addition, the simulation shows that the coupling efficiency of the sensor can be significantly improved by changing the diameter of the PSS, which provides a new method for making high-sensitivity sensors by using HCF in the future. • A curvature and temperature sensor with high sensitivity is proposed. • It combines the characteristics of Hollow core fiber, spherical structure and MZI. • The curvature sensitivity is up to −648.17 pm/m−1, and the temperature sensitivity is 25.42 pm/°C. [ABSTRACT FROM AUTHOR]

Abstract We have demonstrated the generation of widely tunable spectral multi-wavelength all-normal-dispersion (ANDi) Yb-doped fiber laser based on nonlinear polarization evolution (NPE) as the passively mode-locking mechanism. An easy-controlling tunable passband filter fabricated through a phase-shift long-period grating (PS-LPG) is employed to tune and control the wavelength in the laser cavity. By combining the character of the emission cross section of Yb-doped fiber, the tunable spectral ranges of the dual- and triple-wavelength pulses output is up to ∼20 nm and ∼7 nm, respectively. To our knowledge, it's the widest of tuning spectral range in the both dual- and triple-wavelength ANDi Yb-doped fiber laser with controllable and all-fiber format filter. The proposed method may provide a simple way to obtain a broad spectral range with multi-wavelength output in fiber laser systems. [ABSTRACT FROM AUTHOR]

This paper focuses on printing a 2D color image by using a desktop fused deposition modeling (FDM) 3D printer. A fully automatic framework is presented to convert a 2D image into a non-photorealistic line drawing which is suitable for 3D printing. Firstly, an image is partitioned into a moderate number of regions, and contours of these regions are extracted to deliver the high level abstraction of the image. The contour lines are further refined by taking into consideration the restrictions of 3D printing. Next, an orientation field based on the contours and feature lines at a finer level is computed to guide the placement of streamlines. The distances between streamlines are carefully controlled such that the density respects the pixel intensity values. Finally, the resulting streamlines are converted into printing paths and printed by using filaments with specified colors. Experimental results show the feasibility and efficacy of our method on portraying a given image by using a few of 3D printable non-intersecting lines while preserving features and tone variation in the image. [ABSTRACT FROM AUTHOR]

To decrease the self-discharge rate of the nickel metal hydride batteries, the self-discharge characteristic and mechanism of single-phase PuNi 3 -, Gd 2 Co 7 -, and Pr 5 Co 19 -type Nd–Mg–Ni-based alloys are studied from the perspective of structure in this work. It is found that the self-discharge rate of the alloy electrodes gradually increases with a rising [NdNi 5 ]/[NdMgNi 4 ] subunit ratio. The factors resulting in reversible and irreversible self-discharge are analyzed by electrochemical pressure-composition isotherms, Tafel and SEM measurements. Electrochemical P-C isotherms show that with the increasing [NdNi 5 ]/[NdMgNi 4 ] subunit ratio, the hydrogen desorption plateau pressure sharply elevates, leading to less stability of the corresponding hydride and more reversible self-discharge of the alloys; whereas, corrosion current density of the three alloy electrodes gradually decreases and SEM shows that the amount of hydroxide accumulating on the alloy surface diminishes, indicating the oxidation/corrosion degree alleviates and less irreversible self-discharge with the higher [NdNi 5 ]/[NdMgNi 4 ] ratio. By calculating the proportion of reversible and irreversible self-discharge in total capacity loss, we find that the reversible self-discharge is nearly more than 90% for the three single-phase alloys, while irreversible self-discharge is less than 10%, which illustrates that reversible self-discharge is the dominate factor in self-discharge of Nd–Mg–Ni-based alloys in this study. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of generating a line drawing from a given image for fused deposition modeling. The abstracted line drawing, comprising of lines with a single color and thickness, would preserve both tone and edges of the input image. We first partition the image into sub-regions manually. The boundaries of the sub-regions are extracted as the feature lines of the image. Next, a proper number of points are randomly placed on the image plane with a density proportional to the darkness of the image. We use Lloyd’s method to push the sampling points away from each other and the feature lines. The points within each sub-region are then connected by solving a travelling salesman problem (TSP). Finally, we further optimize the fairness and the spacing of the lines by minimizing a tailored objective function. A variety of experimental results are presented to show the effectiveness of our method for generating line drawings for 3D printing. [ABSTRACT FROM AUTHOR]

Pr 5 Co 19 -type single-phase Pr 4 MgNi 19 and La 4 MgNi 19 alloys are prepared by powder sintering, and the capacity degradation behavior of the two alloys is investigated. The Pr 4 MgNi 19 and La 4 MgNi 19 alloy electrodes have similar discharge capacities but exhibit large differences in cycling stability. The capacity loss rate of Pr 4 MgNi 19 alloy electrode is 22.5% at the 200 th cycle, while that of La 4 MgNi 19 alloy electrode is 43.5%. It is found that the hydroxides on surface of La 4 MgNi 19 alloys accumulate disorderly while the hydroxides on surface of Pr 4 MgNi 19 alloys form a compact layer that protects the active material from corrosion. After 200 cycles, the abundance of Pr(OH) 3 in Pr 4 MgNi 19 alloy is 8.07 wt%, which is far less than that of La(OH) 3 in La 4 MgNi 19 alloy (24.74 wt%). Pr 4 MgNi 19 alloys not only have lower surface oxidization but also possess higher anti-pulverization ability. The abundance of the Pr 5 Co 19 -type phase in Pr 4 MgNi 19 alloy remains 80.88 wt% after 200 cycles, while that of La 4 MgNi 19 alloy is 32.01 wt%. The difference between the expansion rates of [A 2 B 4 ] and [AB 5 ] subunits in Pr 4 MgNi 19 alloy is 4.26%, which is smaller than that in La 4 MgNi 19 alloy (10.14%). The dense corrosion-resistant protective layer and lower lattice mismatch jointly contribute to the superior cycling stability of Pr 4 MgNi 19 alloy. [ABSTRACT FROM AUTHOR]