The risk of amputation is a sequelae of diabetic foot ulceration, which are significantly increased in diabetic patients and caused huge morbidly and mortality. However, whether the risk amputation ...in diabetic patients are differing in male and female remains inconclusive. We therefore conducted a systematic review and meta-analysis to assess the sex difference for the risk of amputation in diabetic patients. We systematically searched PubMed, EmBase, and the Cochrane library to identify eligible study from their inception up to November 2020. The diagnostic value of male patients on subsequent amputation risk were assessed by using sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC). Twenty-two studies recruited a total of 33,686,171 diabetic patients were selected for quantitative analysis. The risk of amputation in male diabetic patients was greater than female diabetic patients (DOR: 1.38; 95%CI: 1.13-1.70; P<0.001). The sensitivity and specificity for male diabetic patients on the risk of amputation were 0.72 (95%CI: 0.72-0.73), and 0.51 (95%CI: 0.51-0.51), respectively. Moreover, the PLR and NLR of male diabetic patients for predicting amputation were 1.13 (95%CI: 1.05-1.22), and 0.82 (0.72-0.94), respectively. Furthermore, the AUC for male diabetic patients on amputation risk was 0.56 (95%CI: 0.48-0.63). This study found male diabetic patients was associated with an increased risk of amputation than female diabetic patients, and the predictive value of sex difference on amputation risk in diabetic patients was mild.
The direct functionalization of allylic C−H bonds with nucleophiles minimizes pre‐functionalization and converts inexpensive, abundantly available materials to value‐added alkenyl‐substituted ...products but remains challenging. Here we report an electrocatalytic allylic C−H alkylation reaction with carbon nucleophiles employing an easily available cobalt–salen complex as the molecular catalyst. These C(sp3)−H/C(sp3)−H cross‐coupling reactions proceed through H2 evolution and require no external chemical oxidants. Importantly, the mild conditions and unique electrocatalytic radical process ensure excellent functional group tolerance and substrate compatibility with both linear and branched terminal alkenes. The synthetic utility of the electrochemical method is highlighted by its scalability (up to 200 mmol scale) under low loading of electrolyte (down to 0.05 equiv) and its successful application in the late‐stage functionalization of complex structures.
An electrocatalytic allylic C−H alkylation reaction with carbon nucleophiles is reported, which employs an easily available cobalt–salen complex as the molecular catalyst. The method is characterized by its excellent functional group tolerance, substrate compatibility with both linear and branched terminal alkenes, and scalability (up to 200 mmol scale) with a low loading of electrolyte (down to 0.05 equiv).
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As the numbers of medium- to high-entropy alloys being studied and impressive structural properties they exhibit increase rapidly, questions regarding the role played by their complex ...chemical fluctuations rise concomitantly. Here, using a combination of large-scale molecular dynamics (MD), a hybrid MD and Monte-Carlo simulation method, and crystal defect analysis, we investigate the role lattice distortion (LD) and chemical short-range order (CSRO) play in the nucleation and evolution of dislocations and nanotwins with straining in single crystal and nanocrystalline CoCrNi, a medium entropy alloy (MEA). LD and CSRO effects are elucidated by comparisons with responses from a hypothetical pure A-atom alloy, which bears the same bulk properties of the nominal MEA but no LD and no CSRO. The analysis reveals that yield strengths are determined by the strain to nucleate Shockley partial dislocations, and LD lowers this strain, while higher degrees of CSRO increase it. We show that while these partials prefer to nucleate in the CoCr clusters, regardless of their size, they find it increasingly difficult to propagate away from these sites as the level of CSRO increases. After yield, nanotwin nucleation occurs via reactions of mobile Shockley partials and is promoted in MEAs, due to the enhanced glide resistance resulting from LD and CSRO.
This paper focuses on scalability and robustness of spectral clustering for extremely large-scale datasets with limited resources. Two novel algorithms are proposed, namely, ultra-scalable spectral ...clustering (U-SPEC) and ultra-scalable ensemble clustering (U-SENC). In U-SPEC, a hybrid representative selection strategy and a fast approximation method for <inline-formula><tex-math notation="LaTeX">K</tex-math> <mml:math><mml:mi>K</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq1-2903410.gif"/> </inline-formula>-nearest representatives are proposed for the construction of a sparse affinity sub-matrix. By interpreting the sparse sub-matrix as a bipartite graph, the transfer cut is then utilized to efficiently partition the graph and obtain the clustering result. In U-SENC, multiple U-SPEC clusterers are further integrated into an ensemble clustering framework to enhance the robustness of U-SPEC while maintaining high efficiency. Based on the ensemble generation via multiple U-SEPC's, a new bipartite graph is constructed between objects and base clusters and then efficiently partitioned to achieve the consensus clustering result. It is noteworthy that both U-SPEC and U-SENC have nearly linear time and space complexity, and are capable of robustly and efficiently partitioning 10-million-level nonlinearly-separable datasets on a PC with 64 GB memory. Experiments on various large-scale datasets have demonstrated the scalability and robustness of our algorithms. The MATLAB code and experimental data are available at https://www.researchgate.net/publication/330760669 .
Despite the popularity in modeling complex and arbitrary crack configurations in solids, phase-field damage models suffer from burdensome computational cost. This issue arises largely due to the ...robust but inefficient alternating minimization (AM) or staggered algorithm usually employed to solve the coupled damage–displacement governing equations. Aiming to tackle this difficulty, we propose in this work, for the first time, to use the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm to solve in a monolithic manner the system of coupled governing equations, rather than the standard Newton one which is notoriously poor for problems involving non-convex energy functional. It is found that, the BFGS algorithm yields identical results to the AM/staggered solver, and is also robust for both brittle fracture and quasi-brittle failure with a single or multiple cracks. However, much less iterations are needed to achieve convergence. Furthermore, as the system matrix is less reformed per increment, the quasi-Newton monolithic algorithm is much more efficient than the AM/staggered solver. Representative numerical examples show that the saving in CPU time is about factor 3∼7, and the larger the problem is, the more saving it gains. As the BFGS monolithic algorithm has been incorporated in many commercial software packages, it can be easily implemented and is thus attractive in the phase-field damage modeling of localized failure in solids.
•A robust and efficient quasi-Newton monolithic algorithm is proposed for phase-field damage models.•The robustness comes from the BFGS method with a symmetric and positive-definite stiffness matrix.•The proposed quasi-Newton monolithic algorithm is about 3∼7 times faster than the staggered solver.•The phase-field regularized cohesive zone model is not numerically affected by the solution algorithm.
•The phase-field regularized CZM is applied to fitting test data of size and boundary effects in concrete.•The size and boundary effects in notched and unnotched concrete beams under mode-I failure ...are captured.•The size effect of notched concrete beams transited from mode-I failure to mixed-mode one is predicted.•Not only the predicted peak loads but also the softening regimes agree fairly well with experimental results.
A phase-field regularized cohesive zone model (CZM) was recently proposed for both brittle fracture and cohesive failure within the framework of the unified phase-field damage theory. Motivated from the fact that this model gives length scale and mesh independent global responses for problems with or without elastic singularities, we further apply it in this work against the size and boundary effects of concrete under both mode-I and mixed-mode failure. More specifically, for the two independent experimental campaigns of three-point bending notched and unnotched concrete beams under mode-I failure, the quality of data-fitting is, at least, comparable to the best results reported in the literature. For another series of eccentrically notched concrete beam tests, the size effect with transition from mode-I fracture to mixed-mode failure is also predicted. In all numerical examples, not only the peak loads but also the softening regimes agree well with the experimental results using a single set of material parameters for a specific series of tests. Being accompanied with other merits, e.g., generic softening laws, no lateral widening, no need of extrinsic crack tracking nor the penalty stiffness, etc., the presented phase-field regularized CZM can be used as a promising approach in the modeling of damage and failure in solids and structures.
• An improved OVO strategy is proposed.• A framework for multi-class sentiment classification based on the improved OVO strategy and the SVM algorithm is presented.• A new method for multi-class ...sentiment classification is proposed.• Experimental studies are conducted to verify the effectiveness of the proposed method.
Multi-class sentiment classification is a valuable research topic with extensive applications; however, studies in the field remain relatively scarce. In the present paper, a method for multi-class sentiment classification based on an improved one-vs-one (OVO) strategy and the support vector machine (SVM) algorithm is proposed. First, an improved OVO strategy is proposed wherein the relative competence weight of each binary classifier is determined according to the K nearest neighbors and the class center of each class in the training sample set concerning the binary classifier. A method for multi-class sentiment classification is proposed based on this improved OVO strategy and the SVM algorithm. After converting the training texts into term feature vectors, the important features (terms) for multi-class sentiment classification are selected using the information gain (IG) algorithm. A binary SVM classifier is then trained on the training feature vectors of each pair of sentiment classes. To identify the sentiment class of a test text, a confidence score matrix of multiple SVM classifiers is constructed based on the results of multiple SVM classifiers. Using this score matrix, the sentiment class of the test text can be determined using the improved OVO strategy. The results of our experimental studies show that the performance of the proposed method is significantly better than that of the existing methods for multi-class sentiment classification.
•Three different implementation strategies of phase-field damage models in Abaqus are addressed.•The sources codes and input files of all these three implementation schemes can be open ...accessed.•Representative examples validating the implementation strategies and source codes are presented.•The UEL subroutine together with the BFGS monolithic solver is of best numerical performances.•The UMAT subroutine is viable if the BFGS solver is available in coupled thermal–stress analyses.
Despite the versatility in modeling complex crack configurations, phase-field damage models for fracture usually count only on in-house codes, greatly restricting their potential applications. It is thus of vital importance to implement them in those commonly used commercial software packages like Abaqus. However, so far only the less robust Newton’s monolithic algorithm or the inefficient staggered solver has been considered. In this work, taking the unified phase-field damage theory (Wu, 2017) as the particular example, we present three distinct strategies of implementing phase-field damage models into Abaqus: (i) UMAT-Newton-M: a thermo-mechanically coupled user-defined material (UMAT) implementation of the modified Newton monolithic solver; (ii) UEL-Staggered: a novel user-defined element (UEL) implementation of the iterative staggered (alternate minimization) algorithm with dummy dofs; (iii) UEL-BFGS: a UEL implementation of the recently advocated BFGS quasi-Newton monolithic algorithm. The aforesaid implementation strategies are then validated against several representative benchmark problems of brittle fracture and quasi-brittle failure. It is found that, the UMAT-Newton-M implementation is the simplest but not robust enough, while the UEL-Staggered implementation is robust but extremely inefficient. Comparatively, in all cases the UEL-BFGS scheme is of the best numerical performance with lest iterations and sufficient robustness. For the sake of reproducibility of the presented numerical results and the promotion of phase-field damage models, the source codes (programmed in the free format syntax of FORTRAN90) are also provided and interested users can download them at https://github.com/jianyingwu/pfczm-abaqus.
This paper proposes a methodology for conducting importance-performance analysis (IPA) through online reviews. The methodology is composed of three stages: (1) mining useful information from online ...reviews, (2) estimating each attribute's performance and importance, and (3) constructing IPA plot, where the latent dirichlet allocation (LDA), the improved one-vs-one strategy based support vector machine (IOVO-SVM) and the ensemble neural network based model (ENNM) are respectively used. A case study on two five-star hotels is given, and the results obtained by the proposed methodology through online reviews are compared with those obtained by the existing methods through questionnaires (or online ratings). The results indicate that the proposed methodology can obtain effective analysis results with lower cost and shorter time since online reviews are publicly available and easily collected. The proposed methodology can give managers or market analysts one more choice for conducting IPA or serve as a preparing process of large-scale survey.
•A novel methodology for conducting IPA through online reviews is proposed.•The performance of each attribute is estimated according to the sentiment strengths of online reviews.•The importance of each attribute is estimated using ENNM.•Four types of IPA can be easily conducted through online reviews.•A case study of IPA for two five-star hotels is given.
Accurate forecasting of daily tourism demand is a meaningful and challenging task, but studies on this issue are scarce. To address this issue, multisource time series data, relating to past tourist ...volumes, web search information, daily weather conditions, and the dates of public holidays, are selected as the forecasting variables. To fully capture the relationship between these forecasting variables and actual tourism demand automatically, an ensemble of long short-term memory (LSTM) networks is proposed with a correlation-based predictor selection (CPS) algorithm. The effectiveness of the proposed method is verified in daily tourism demand forecasting for the Huangshan Mountain Area, benchmarked against 11 forecasting methods. This study contributes to the literature by (1) introducing the use of big data in daily tourism demand forecasting, (2) proposing an ensemble of LSTM networks for daily tourism demand forecasting, and (3) providing an effective predictor selection algorithm in ensemble learning.
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