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| 1 | CPC, a Single-Repeat R3 MYB, Is a Negative Regulator of Anthocyanin Biosynthesis in Arabidopsis显示文摘象 CPC (突变) 一样的单个重复的 R3 MYB 抄写因素被知道在象根头发区别和毛状体开始那样的发展过程起作用。然而,任何一个都没六个 Arabidopsis 单个重复的 R3 MYB 成员被报导调整 flavonoid 生合成。我们这里证明 CPC 是 anthocyanin 生合成的一个否定管理者。在使用 CPC 测试 GAL4 依赖的司机线的过程,我们在调停 GAL4 的 CPC overexpression 之上观察了 anthocyanin 合成的压抑。我们证明因为更多的根头发,这不由于滋养的举起的增加。更确切地说, CPC 表达式水平紧控制 anthocyanin 累积。整个染色体上的 Microarray 分析显示出那, 37 ? 测试的 000 个特征, 85 基因被镇压比大由 CPC overexpression 三方面。这 85,七是迟了的 anthocyanin 生合成基因。另外, anthocyanin 合成基因被显示在 35S::CPC overexpression 植物下面调整。短暂表示结果建议 CPC 与 R2R3MYB 抄写因素 PAP1/2 竞争,它是 anthocyanin 生合成基因的使活跃之物。这份报告把 anthocyanin 生合成加到在 CPC 控制下面的节目的集合,显示这个管理者为发展节目不仅(例如根头发,毛状体) ,但是罐头影响 anthocyanin 颜料合成。 | Hui-Fen Zhu Karen Fitzsimmons Abha Khandelwal Robert G. Kranz | 2009 | Molecular Plant2009，2，4： | 34 |
| 2 | Evaluation and prediction of blast induced ground vibration using support vector machine显示文摘We present the application of Support Vector Machine (SVM) for the prediction of blast induced ground vibration by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the suitability of this approach, the predictions by SVM have been compared with conventional predictor equations. Blast vibration study was carried out at Magnesite mine of Pithoragarh, India. Total 170 blast vibrations data sets were recorded at different strate-gic and vulnerable locations in and around to mine. Out of 170 data sets, 150 were used for the training of the SVM network as well as to determine site constants of different conventional predictor equations, whereas, 20 new randomly selected data sets were used to compare the prediction capability of SVM network with conventional predictor equations. Results were compared based on Co-efficient of Determination (CoD) and Mean Absolute Error (MAE) between monitored and predicted values of Peak Particle Veloc-ity (PPV). It was found that SVM gives closer values of predicted PPV as compared to conventional predictor equations. The coef-ficient of determination between measured and predicted PPV by SVM was 0.955, whereas it was 0.262, 0.163, 0.337 and 0.232 by USBM, Langefors-Kihlstrom, Ambraseys-Hendron and Bureau of Indian Standard equations, respectively. The MAE for PPV was 11.13 by SVM, whereas it was 0.973, 1.088, 0.939 and 1.292 by USBM, Langefors-Kihlstrom, Ambraseys-Hendron and Bureau of Indian Standard equations respectively. | KHANDELWAL M KANKAR P K HARSHA S P | 2010 | Mining Science and Technology2010，20，1： | 12 |
| 3 | 双轴应力边界和疲劳载荷作用下岩石的力学特性显示文摘本文通过开展双轴压缩试验和双轴疲劳试验,研究了大理岩和砂岩的破裂特性。双轴压缩试验结果表明,随着中间主应力的增大,岩石的双轴抗压强度呈先增大后减小的变化趋势。双轴应力边界内岩石的疲劳破坏与疲劳载荷峰值水平、中间主应力大小和岩性有关。随着疲劳载荷峰值水平的增加,岩石的疲劳寿命降低。中间主应力对岩石抗疲劳性能有明显的强化作用,在相同的应力比下,岩石的疲劳寿命随着中间主应力的增大而增大。通过试验中声发射以及破坏后岩石碎片分析,发现相同试验条件下砂岩具有更高的抗疲劳性能,而大理岩产生更多的小尺寸碎片。疲劳载荷作用下的破岩效率更高,也更容易诱发剧烈的硬岩岩爆灾害。 | 杜坤 李雪锋 杨成志 周健 陈绍杰 MANOJ Khandelwal | 2020 | Journal of Central South University2020，27，10： | 7 |
| 4 | An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine,Iran显示文摘Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects and may cause substantial damage to rock mass as well as nearby structures and human beings.In this paper,an attempt has been made to present an application of artificial neural network(ANN)to predict the blast-induced ground vibration of the Gol-E-Gohar(GEG)iron mine,Iran.A four-layer feed-forward back propagation multi-layer perceptron(MLP)was used and trained with Levenberg–Marquardt algorithm.To construct ANN models,the maximum charge per delay,distance from blasting face to monitoring point,stemming and hole depth were taken as inputs,whereas peak particle velocity(PPV)was considered as an output parameter.A database consisting of69data sets recorded at strategic and vulnerable locations of GEG iron mine was used to train and test the generalization capability of ANN models.Coefficient of determination(R2)and mean square error(MSE)were chosen as the indicators of the performance of the networks.A network with architecture4-11-5-1and R2of0.957and MSE of0.000722was found to be optimum.To demonstrate the supremacy of ANN approach,the same69data sets were used for the prediction of PPV with four common empirical models as well as multiple linear regression(MLR)analysis.The results revealed that the proposed ANN approach performs better than empirical and MLR models. | Mahdi Saadat Manoj Khandelwal M.Monjezi | 2014 | Journal of Rock Mechanics and Geotechnical Engineering2014，6，1： | 7 |
| 5 | 虚拟耳镜检查术前评价慢性化脓性中耳炎病人的听骨链是否有价值?HRCT和虚拟耳镜检查与外科手术所见的对比显示文摘本研究的目的是评价虚拟耳镜检查及听小骨3D重建对慢性化脓性中耳炎病人听小骨术前评价中的作用。对33例伴有传导性耳聋(气-骨差距〉35dB)的慢性化脓性中耳炎病人进行前瞻性研究。所有病人均行多层螺旋CT横断面检查。利用横断面CT数据进行多平面2D重组、虚拟耳镜检查(VO)及3D重组。2名放射科医师根据3点评分系统分别对这两种技术所得影像中听骨链的不同部分进行判读,并与外科所见进行对照。这两种成像技术对听骨较大部分结构的评价具有相似的准确性。 | A.K. Pandey J.R. Bapuraj A.K. Gupta N. Khandelwal 乔辉(译) 刘筠(校) | 2009 | 国际医学放射学杂志2009，32，4： | 6 |
| 6 | A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak显示文摘In blasting operation,the aim is to achieve proper fragmentation and to avoid undesirable events such as backbreak.Therefore,predicting rock fragmentation and backbreak is very important to arrive at a technically and economically successful outcome.Since many parameters affect the blasting results in a complicated mechanism,employment of robust methods such as artificial neural network may be very useful.In this regard,this paper attends to simultaneous prediction of rock fragmentation and backbreak in the blasting operation of Tehran Cement Company limestone mines in Iran.Back propagation neural network(BPNN) and radial basis function neural network(RBFNN) are adopted for the simulation.Also,regression analysis is performed between independent and dependent variables.For the BPNN modeling,a network with architecture 6-10-2 is found to be optimum whereas for the RBFNN,architecture 636-2 with spread factor of 0.79 provides maximum prediction aptitude.Performance comparison of the developed models is fulfilled using value account for(VAF),root mean square error(RMSE),determination coefficient(R2) and maximum relative error(MRE).As such,it is observed that the BPNN model is the most preferable model providing maximum accuracy and minimum error.Also,sensitivity analysis shows that inputs burden and stemming are the most effective parameters on the outputs fragmentation and backbreak,respectively.On the other hand,for both of the outputs,specific charge is the least effective parameter. | A.Sayadi M.Monjezi N.Talebi Manoj Khandelwal | 2013 | Journal of Rock Mechanics and Geotechnical Engineering2013，5，4： | 6 |
| 7 | Autologous bone marrow derived stem cell therapy in patients with type 2 diabetes mellitus-defining adequate administration methods显示文摘AIM To carry out randomized trial for evaluating effects of autologous bone marrow derived stem cell therapy(ABMSCT) through different routes.METHODS Bone marrow aspirate was taken from the iliac crest of patients. Bone marrow mononuclear cells were separatedand purified using centrifugation. These cells were then infused in a total of 21 patients comprising three groups of 7 patients each. Cells were infused into the superior pancreaticoduodenal artery(Group Ⅰ), splenic artery(Group Ⅱ) and through the peripheral intravenous route(Group Ⅲ). Another group of 7 patients acted as controls and a sham procedure was carried out on them(Group Ⅳ). The cells were labelled with the PET tracer F18-FDG to see their homing and in vivo distribution. Data for clinical outcome was expressed as mean ± SE. All other data was expressed as mean ± SD. Baseline and post treatment data was compared at the end of six months, using paired t-test. Cases and controls data were analyzed using independent t-test. A probability(P) value of < 0.05 was regarded as statistically significant. Measures of clinical outcome were taken as the change or improvement in the following parameters:(1) C-peptide assay;(2) HOMA-IR and HOMA-B;(3) reduction in Insulin dose; subjects who showed reduction of insulin requirement of more than 50% from baseline requirement were regarded as responders; and(4) reduction in HbA 1c. RESULTS All the patients, after being advised for healthy lifestyle changes, were evaluated at periodical intervals and at the end of 6 mo. The changes in body weight, body mass index, waist circumference and percentage of body fat in all groups were not significantly different at the end of this period. The results of intra-group comparison before and after ABMSCT at the end of six months duration was as follows:(1) the area under C-peptide response curve was increased at the end of 6 mo however the difference remained statistically non-significant(P values for fasting C-peptide were 0.973, 0.103, 0.263 and 0.287 respectively and the P values for stimulated C-peptide were 0.989, 0.395, 0.325 and 0.408 respectively for groups Ⅰ?to Ⅳ);(2) the Insulin sensitivity indices of HOMA IR and HOMA B also did not show any significant differences(P values for HOMA IR were 0.368, 0.223, 0.918 and 0.895 respectively and P values for HOMA B were 0.183, 0.664, 0.206 and 0.618 respectively for groups Ⅰto Ⅳ);(3) Group Ⅰshowed a significant reduction in Insulin dose requirement(P < 0.01). Group Ⅱ patients also achieved a significant reduction in Insulin dosages(P = 0.01). The Group Ⅰand Group Ⅱ patients together constituted the targeted group wherein the feeding arteries to pancreas were used for infusing stem cells. Group Ⅲ, which was the intravenous group, showed a non-significant reduction in Insulin dose requirement(P = 0.137). Group Ⅳ patients which comprised the control arm also showed a significant reduction in Insulin dosages at the end of six months(P < 0.05); and(4) there was a non-significant change in the Hb A1 c levels at the end of 6 mo across all groups(P = 0.355, P = 0.351, P = 0.999 and P = 0.408 respectively for groups Ⅰto Ⅳ). CONCLUSION Targeted route showed a significant reduction in Insulin requirement at the end of six months of study period whereas the intravenous group failed to show reduction. | Vikas Sood Anil Bhansali Bhagwant Rai Mittal Baljinder Singh Neelam Marwaha Ashish Jain Niranjan Khandelwal | 2017 | World Journal of Diabetes2017，8，7： | 6 |
| 8 | Prediction of flyrock in open pit blasting operation using machine learning method显示文摘Flyrock is one of the most hazardous events in blasting operation of surface mines. There are several empirical methods to predict flyrock. Low performance of such models is due to the complexity of flyrock analysis. Existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict flyrock in blasting operations of Soungun Copper Mine, Iran incorporating rock properties and blast design parameters using support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA), too. Coefficient of determination (CoD) and mean absolute error (MAE) were taken as performance measures. It was found that CoD between measured and predicted flyrock was 0.948 and 0.440 by SVM and MVRA, respectively, whereas MAE between measured and predicted flyrock was 3.11 and 7.74 by SVM and MVRA, respectively. | Manoj Khandelwal M. Monjezi | 2013 | International Journal of Mining Science and Technology2013，23，3： | 5 |
| 9 | Locoregional treatment for hepatocellular carcinoma:The best is yet to come显示文摘Hepatocellular carcinoma(HCC) is the sixth-most common type of cancer worldwide. The only definitive treatment modalities capable of achieving a cure are hepatic resection and hepatic transplantation. However, most patients are not candidates for these therapies. Overall, treatment options are driven by the stage of HCC. Early-stage disease is treated with ablative therapies, with radiofrequency ablation the ablative therapy of choice. Microwave ablation and irreversible electroporation are the other upcoming alternatives. Intermediate-stage disease is managed with transarterial chemoembolization(TACE), while advanced-stage disease is managed by sorafenib, with TACE and radioembolization as other alternatives. | Naveen Kalra Pankaj Gupta Yogesh Chawla Niranjan Khandelwal | 2015 | World Journal of Radiology2015，7，10： | 5 |
| 10 | Imaging in pulmonary hydatid cysts显示文摘Hydatid disease is a zoonosis that can involve almost any organ in the human body. After the liver, the lungs are the most common site for hydatid disease in adults. Imaging plays a pivotal role in the diagnosis of the disease, as clinical features are often nonspecific. Classical radiological signs of pulmonary hydatid cysts have been described in the literature, aiding in the diagnosis of the disease. However, complicated hydatid cysts can prove to be a diagnostic challenge at times due to their atypical imaging features. Radiography is the initial imaging modality. Computed tomography can provide a specific diagnosis in complicated cases. Ultrasound is particularly useful in peripheral lung lesions. The role of magnetic resonance imaging largely remains unexplored. | Mandeep K Garg Madhurima Sharma Ajay Gulati Ujjwal Gorsi Ashutosh N Aggarwal Ritesh Agarwal Niranjan Khandelwal | 2016 | World Journal of Radiology2016，8，6： | 4 |
| 11 | Recent Developments in Integrated Solar Combined Cycle Power Plants显示文摘Global concern for depleting fossil fuel reserves have been compelling for evolving power generation options using renewable energy sources. The solar energy happens to be a potential source for running the power plants among renewable energy sources. Integrated Solar Combined Cycle(ISCC) power plants have gained popularity among the thermal power plants. Traditional ISCC power plants use Direct Steam Generation(DSG) approach. However, with the DSG method, the ISCC plant’s overall thermal efficiency does not increase significantly due to variations in the availability of solar energy. Thermal Energy Storage(TES) systems when integrated into the solar cycle can address such issues related to energy efficiency, process flexibility, reducing intermittency during non-solar hours. This review work focuses and discusses the developments in various components of the ISCC system including its major cycles and related parameters. The main focus is on CSP technologies, Heat Transfer Fluid(HTF), and Phase Change Material(PCM) used for thermal energy storage. Further, study includes heat enhancement methods with HTF and latent heat storage system. This study will be beneficial to the power plant professionals intending to modify the solar-based Combined Cycle Power Plant(CCPP) and to retrofit the existing Natural Gas Combined Cycle(NGCC) plant with the advanced solar cycle. | KHANDELWAL Neelam SHARMA Meeta SINGH Onkar SHUKLA Anoop Kumar | 2020 | Journal of Thermal Science2020，29，2： | 4 |
| 12 | Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization显示文摘The advance rate(AR)of a tunnel boring machine(TBM)under hard rock conditions is a key parameter in the successful implementation of tunneling engineering.In this study,we improved the accuracy of prediction models by employing a hybrid model of extreme gradient boosting(XGBoost)with Bayesian optimization(BO)to model the TBM AR.To develop the proposed models,1286 sets of data were collected from the Peng Selangor Raw Water Transfer tunnel project in Malaysia.The database consists of rock mass and intact rock features,including rock mass rating,rock quality designation,weathered zone,uniaxial compressive strength,and Brazilian tensile strength.Machine specifications,including revolution per minute and thrust force,were considered to predict the TBM AR.The accuracies of the predictive models were examined using the root mean squares error(RMSE)and the coefficient of determination(R^(2))between the observed and predicted yield by employing a five-fold cross-validation procedure.Results showed that the BO algorithm can capture better hyper-parameters for the XGBoost prediction model than can the default XGBoost model.The robustness and generalization of the BO-XGBoost model yielded prominent results with RMSE and R^(2) values of 0.0967 and 0.9806(for the testing phase),respectively.The results demonstrated the merits of the proposed BO-XGBoost model.In addition,variable importance through mutual information tests was applied to interpret the XGBoost model and demonstrated that machine parameters have the greatest impact as compared to rock mass and material properties. | Jian Zhou Yingui Qiu Shuangli Zhu Danial Jahed Armaghani Manoj Khandelwal Edy Tonnizam Mohamad | 2021 | Underground Space2021，6，5： | 4 |
| 13 | 厚度依赖的聚合物稳定胆甾相液晶的电控红外反射器件(英文)显示文摘本文报道了基于聚合物胆甾相液晶的、可电场调控的红外反射器件的制备,并系统研究了器件厚度对器件性能的影响.即施加直流电场后,厚度较小的器件的反射带宽仅发生红移;厚度较大的器件的反射带宽增宽.这种现象是由于不同厚度的胆甾相液晶薄膜中不同的螺距梯度导致的.本工作的研究结果表明在制备基于聚合物胆甾相液晶的电控红外反射器件时,厚度是决定反射性能的重要因素.由于该红外反射器件具有较快的响应时间和较好的工作稳定性,在建筑和汽车等的节能窗领域有较好的应用前景. | 胡小文 Laurens T.de Haan Hitesh Khandelwal Albertus P.H.J.Schenning 辇理 周国富 | 2018 | Science China Materials2018，61，5： | 3 |
| 14 | Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms显示文摘The main purpose of blasting operation is to produce desired and optimum mean size rock fragments.Smaller or fine fragments cause the loss of ore during loading and transportation,whereas large or coarser fragments need to be further processed,which enhances production cost.Therefore,accurate prediction of rock fragmentation is crucial in blasting operations.Mean fragment size(MFS) is a crucial index that measures the goodness of blasting designs.Over the past decades,various models have been proposed to evaluate and predict blasting fragmentation.Among these models,artificial intelligence(AI)-based models are becoming more popular due to their outstanding prediction results for multiinfluential factors.In this study,support vector regression(SVR) techniques are adopted as the basic prediction tools,and five types of optimization algorithms,i.e.grid search(GS),grey wolf optimization(GWO),particle swarm optimization(PSO),genetic algorithm(GA) and salp swarm algorithm(SSA),are implemented to improve the prediction performance and optimize the hyper-parameters.The prediction model involves 19 influential factors that constitute a comprehensive blasting MFS evaluation system based on AI techniques.Among all the models,the GWO-v-SVR-based model shows the best comprehensive performance in predicting MFS in blasting operation.Three types of mathematical indices,i.e.mean square error(MSE),coefficient of determination(R^(2)) and variance accounted for(VAF),are utilized for evaluating the performance of different prediction models.The R^(2),MSE and VAF values for the training set are 0.8355,0.00138 and 80.98,respectively,whereas 0.8353,0.00348 and 82.41,respectively for the testing set.Finally,sensitivity analysis is performed to understand the influence of input parameters on MFS.It shows that the most sensitive factor in blasting MFS is the uniaxial compressive strength. | Enming Li Fenghao Yang Meiheng Ren Xiliang Zhang Jian Zhou Manoj Khandelwal | 2021 | Journal of Rock Mechanics and Geotechnical Engineering2021，13，6： | 3 |
| 15 | The role of intermediaries in facilitating trade显示文摘 | JaeBin Ahn Amit K. Khandelwal Shang-Jin Wei | 2011 | Journal of International Economics2011，，1： | 2 |
| 16 | Expression of hemagglutinin protein of Rinderpest virus in transgenic pigeon pea [Cajanus cajan (L.) Millsp.] plants显示文摘 | V. Satyavathi V. Prasad Abha khandelwal M. Shaila Lakshmi G. Sita | 2003 | Plant Cell Reports2003，，7： | 2 |
| 17 | Enhancing diamond drilling performance by the addition of non-ionic polymer to the flushing media显示文摘钻是在挖掘工业的很重要、关键的操作。与调查钻性能的钻石的改进的目的,详细实验室调查在磷酸盐岩石上被执行。效果(乙烯氧化物)(PEO ) Poly 补充说水被改变机器参数和 PEO 集中学习到钻。回答在小点岩石接口是穿入和转矩的率。消除耐久性测试也被执行在 PEO 答案理解磷酸盐岩石的消除行为。 | BHATNAGAR Anupam KHANDELWAL Manoj RAO Karanam Uma Maheshwar | 2010 | Mining Science and Technology2010，20，3： | 2 |
| 18 | Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors显示文摘Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated database.Four assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual index.The corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are analyzed.The combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the samples.Ultimately,the established ensemble model is further validated through test samples with 100%accuracy.The results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines. | Jian Zhou Chao Chen Mingzheng Wang Manoj Khandelwal | 2021 | International Journal of Mining Science and Technology2021，31，5： | 2 |
| 19 | Endoscopic balloon dilation compared with sphincterotomy for extraction of bile duct stones显示文摘 | James A. DiSario Martin L. Freeman David J. Bjorkman Padraic MacMathuna Bret T. Petersen Philip E. Jaffe Thomas G. Morales Lee J. Hixson Stuart Sherman Glen A. Lehman M. Mazen Jamal Firas H. Al-Kawas Mukul Khandelwal Joseph P. Moore Gregory A. Derfus Priy | 2004 | Gastroenterology2004，，： | 2 |
| 20 | Congestive heart failure and QRS duration:Establishing prognosis study显示文摘 | Shenkman HJ pampati V Khandelwal AK | 2002 | Chest2002，122，2： | 1 |
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