采场覆岩两带与采空区自燃三带相关关系研究

为研究采煤工作面覆岩两带（冒落带、裂隙带）与自燃三带（散热带、窒息带、氧化带）的关系，通过建立覆岩运移模型，应用CDEM软件模拟分析了试验工作面采动空间上覆岩层两带的扩展过程，分析垂向方向覆岩两带分布对水平方向上垮落煤岩堆积状态的影响情况。通过现场埋管实测的手段以及氧体积分数法进行了采空区煤自燃三带的划分。研究表明，冒落带高度稳定情况下，采煤推进距离（48 m）与采空区散热带和氧化带的分界线（进风侧采空区以里50 m左右，回风侧采空区以里40 m左右）有较好的吻合关系。裂隙带高度稳定情况（顶板150 m处的岩层最大下沉值趋于基本稳定）下，采煤推进距离（126 m）与采空区氧化带和窒息带的分界线有较好的对应关系。     

Synthesis and Characterization of Telmisartan-Derived Cell Death Modulators to Circumvent Imatinib Resistance in Chronic Myeloid Leukemia

New strategies to eradicate cancer stem cells in chronic myeloid leukemia (CML) include a combination of imatinib with peroxisome proliferator-activated receptor gamma (PPARγ) ligands. Recently, we identified the partial PPARγ agonist telmisartan as effective sensitizer of resistant K562 CML cells to imatinib treatment. Here, the importance of the heterocyclic core on the cell death-modulating effects of the telmisartan-derived lead 4′-((2-propyl-1H-benzo[d]imidazol-1-yl)methyl)-[1,1′-biphenyl]-2-carboxylic acid ( 3 b ) was investigated. Inspired by the pharmacodynamics of HYL-6d and the selective PPARγ ligand VSP-51, the benzimidazole was replaced by a carbazole or an indole core. The results indicate no correlation between PPARγ activation and sensitization of resistant CML cells to imatinib. The 2-COOH derivatives of the carbazoles or indoles achieved low activity at PPARγ, while the benzimidazoles showed 60-100 % activation. Among the 2-CO₂CH₃ derivatives, only the ester of the lead ( 2 b ) slightly activated PPARγ. Sensitizing effects were further observed for this non-cytotoxic 2 b (80 % cell death), and to a lesser extent for the lead 3 b or the 5-Br-substituted ester of the benzimidazoles ( 5 b ).     

Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships

Efforts to improve dairy production in smallholder farming systems of East Africa over the past decade have had limited impact because of the lack of records on performance to guide targeted breeding programs. Estimates of genetic parameters in these systems are lacking. Using data generated through a project (“Germplasm for Dairy Development in East Africa”) in Kenya and a genomic relationship matrix from genotypic records, we examined the potential impact of different models handling contemporary groups or herd effects on estimates of genetic parameters using a fixed regression model (FRM) for test-day (TD) milk yields, and the covariance structure for TD milk yield at various stages of lactation for animals using a random regression model (RRM). Models in which herd groups were defined using production levels derived from the data fitted the data better than those in which herds were grouped depending on management practices or were random. Lactation curves obtained for animals under different production categories did not display the typical peak yield characteristic of improved dairy systems in developed countries. Heritability estimates for TD milk yields using the FRM varied greatly with the definition of contemporary herd groups, ranging from 0.05 ± 0.03 to 0.27 ± 0.05 (mean ± standard error). The analysis using the RRM fitted the data better than the FRM. The heritability estimates for specific TD yields obtained by the RRM were higher than those obtained by the FRM. Genetic correlations between TD yields were high and positive for measures within short consecutive intervals but decreased as the intervals between TD increased beyond 60 d and became negative with intervals of more than 5 mo. The magnitude of the genetic correlation estimates among TD records indicates that using TD milk records beyond a 60-d interval as repeated measures of the same trait for genetic evaluation of animals on smallholder farms would not be optimal. Although each individual smallholder farmer retains only a few animals, using the genomic relationship between animals to link the large number of farmers operating under specified environments provides a sufficiently large herd-group for which a breeding program could be developed.     

Predicting the principal strong ground motion parameters: A deep learning approach

In this research, new models are developed to estimate the three principal time-domain parameters of seismic ground motion. A novel deep learning (DL) approach coupled with artificial neural network (ANN), namely deep neural network (DNN) is employed for predicting the strong ground motion parameters such as peak ground acceleration (PGA), peak ground velocity (PGV) and peak ground displacement (PGD). This robust technique that has extended the applications of conventional neural networks improves learning of complicated and nonlinear features via increasing the number of layers as well as the neurons in each layer. The proposed models are constructed upon the NGA-West2 database provided by PEER (Pacific Earthquake Engineering Research Center). This database is more comprehensive than NGA-West1 which was mainly considered for developing previous artificial intelligence-based prediction models. Therefore, the new models are more reliable and can be used for wider ranges of predictors. The DNN attenuation models yield accurate estimates of the site PGA, PGV and PGD based on earthquake magnitude, rake angle, source to site distance and soil shear wave velocity. In addition, it is shown that the developed models, with correlation coefficients of 0.902, 0.899 and 0.911 (for PGA, PGV and PGD respectively), outperform the existing soft computing models. Furthermore, the average values of error measures such as MAE, MAPE and RMSE for PGA, PGV and PGD equal to 0.456, 0.758 and 0.581 compare favorably with those of previous models.     

基于注意力机制的双向长短时记忆网络模型突发事件演化关系抽取

针对现有突发事件关系抽取研究多集中于因果关系抽取而忽略了其他演化关系的问题，为了提高应急决策中信息抽取的完备性，应用一种基于注意力机制的双向长短时记忆（LSTM）网络模型进行突发事件演化关系抽取。首先，结合突发事件演化关系的概念，构建演化关系模型并进行形式化定义，依据模型对突发事件语料进行标注；其次，搭建双向LSTM网络结构，并引入注意力机制计算注意力概率以突出关键词汇在文本中的重要程度；最终，使用搭建的网络模型进行演化关系抽取得到结果。在演化关系抽取实验中，相对于现有因果关系抽取方法，所提方法不仅抽取出更加充分的演化关系，为突发事件应急决策提供了更完善的信息；同时，在正确率、召回率和F1分数上分别平均提升了7.3%、6.7%和7.0%，有效提高了突发事件演化关系抽取的准确性。     

The role of relationship promoter in new product development collaboration

Since new product development (NPD) collaborations with external partners have become the next generation in NPD practices, relationship promoters have become especially relevant as key contributors to the success of this type of inter-organisational collaboration. To realise successful outcomes in NPD collaborations, partners face the challenge of effectively integrating the role of relationship promoter into their existing and essential relationships of trust. It is within this context that this paper examines the role of the relationship promoter, by analysing its moderating effect on the relationship between trust and the outcomes of NPD collaboration – including new product competitiveness and partner satisfaction. We test our hypotheses against survey data from 107 innovative firms involved in NPD collaboration with the help of relationship promoters. The results show that, while a non-significant influence can be reported about the presence of a relationship promoter in terms of partner satisfaction, the relationship promotor weakens the influence of trust on new product competitiveness, making trust less important when it comes to creating a competitive new product.     

基于变异算子和邻域值自适应的MOEA/D算法

基于分解的多目标进化算法（MOEA/D）在解决多目标问题时，具有简单有效的特点。但多数MOEA/D采用固定的控制参数，导致全局搜索能力差，难以平衡收敛性和多样性。针对以上问题提出一种基于变异算子和邻域值自适应的多目标优化算法。该算法根据种群中个体适应度值的分散或集中程度进行判断，并据此对变异算子进行自适应的调节，从而增强算法的全局搜索能力；根据进化所处的阶段以及个体适应度值的集中程度，自适应地调节邻域值大小，保证每个个体在不同的进化代数都有一个邻域值大小；在子问题邻域中，统计子问题对应个体的被支配数，通过判断被支配数是否超过设定的上限，来决定是否将Pareto支配关系也作为邻域内判断个体好坏的准则之一。将提出的算法与传统的MOEA/D在标准测试问题上进行对比。实验结果表明，提出的算法求得的解集具有更好的收敛性和多样性，在求解性能上具有一定的优势。     

Effect of Ti content on the microstructure and mechanical behavior of (Fe36Ni18Mn33Al13)100−xTix high entropy alloys

The microstructure and mechanical properties studies of a series of two-phase f.c.c./B2 (ordered b.c.c.) lamellar-structured, high entropy alloys (HEA) Fe₃₆Ni₁₈Mn₃₃Al₁₃Ti_x with x up to 6 at. % Ti have been investigated. X-ray microanalysis in a TEM showed that the Ti resided mostly in the B2 phase. The lamellar spacing decreased significantly with increasing Ti content from 1.56 μm for the undoped alloy to 155 nm with an addition of 4 at. % Ti, leading to a sharp increase in room-temperature yield strength,σ_y, from 270 MPa to 953 MPa, but with a concomitant decrease in ductility from 22% elongation to 2.3%. Annealing at 1173 K for 20 h greatly increased the lamellar spacing of Fe₃₆Ni₁₈Mn₃₃Al₁₃Ti₄ to 577 nm, producing a corresponding decrease in σ_y to 511 MPa. The yield strengths of all the doped alloys decreased significantly when tensile tested at 973 K with a concomitant increase in ductility due to softening of the B2 phase. The fracture mode changed from cleavage at room temperature to a ductile dimple-type rupture at 973 K. The results are discussed in terms of the Hall-Petch-type relationship.