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PurposeThis paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs.Design/methodology/approachA mixed integer programming (MIP) model is built and five types of valid inequalities for tightening the solution space are derived. An improved variable neighborhood search (IVNS) algorithm is presented combining the developed multistart initial solution strategy and modified neighborhood local search procedure.FindingsExperimental results demonstrate that: with less decision variables considered, the proposed model can solve more instances compared to the existing model in previous literature. The valid inequalities utilized to tighten the searching space can efficiently help the model to obtain optimal solutions or high-quality lower bounds. The improved algorithm is efficient to obtain optimal or near-optimal solutions and superior to the compared algorithm in terms of solution quality, computational time and robustness.ractical implicationsThis research not only can help reduce operational costs and improve logistics efficiency for relevant enterprises, but also can provide guidance for constructing the decision support system of logistics intelligent scheduling platform to cater for centralized management and control.Originality/valueThis paper develops a more compact model and some stronger valid inequalities. Moreover, the proposed algorithm is easy to implement and performs well.

PurposeTo develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound.Materials and MethodsA total of 619 participants pathologically diagnosed with invasive breast cancer underwent breast ultrasound examinations were recruited from a multicenter of 17 hospitals in China from August 2016 to August 2017. Conventional ultrasound and SWE features were compared between positive and negative LN metastasis groups. The regression equation, the weighting, and the counting methods were used to predict axillary LN metastasis. The sensitivity, specificity, and the areas under the receiver operating characteristic curve (AUC) were calculated.ResultsA significant difference was found in the Breast Imaging Reporting and Data System (BI-RADS) category, the “stiff rim” sign, minimum elastic modulusof the internal tumor and peritumor region of 3 mm between positive and negative LN groups (p < 0.05 for all). There was no significant difference in the diagnostic performance of the regression equation, the weighting, and the counting methods (p > 0.05 for all). Using the counting method, a 0–4 grade risk stratification system based on the four characteristics was established, which yielded an AUC of 0.656 (95% CI, 0.617–0.693, p < 0.001), a sensitivity of 54.60% (95% CI, 46.9%–62.1%), and a specificity of 68.99% (95% CI, 64.5%–73.3%) in predicting axillary LN metastasis.ConclusionA 0–4 grade risk stratification system was developed based on SWE characteristics and BI-RADS categories, and this system has the potential to predict axillary LN metastases in invasive breast cancer.

As a kind of passive control device, viscoelastic damper has been successfully applied to allkinds of engineering structures. However, the viscoelastic material in viscoelastic dampers is mainly basedon rubber. Therefore, in this thesis, the viscoelastic material is the main line of study. Different viscoelasticmaterial formulas are being used to make the corresponding damper and study the correlation performanceof such damper in the low frequency region. In this thesis, we mainly study the polyurethane elastomermaterial, but simplex polyurethane elastomer materials have low damping and cannot achieve the effect ofbuilding damping, so it's necessary to study the modification. In this experiment, four kinds of inorganicfillers, mica powder, zinc oxide, silica and glass fiber were used to modify the polyurethane elastomer. Itsdamping performance then is tested by a dynamic load testing machine in a low frequency region of 0.1Hz-1.0Hz.