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11篇 您的检索式:作者名="Sonal Gupta"
    题名 作者 年代 出处 被引量
1Epidemiology of lung cancer and approaches for its prediction:a systematic review and analysis显示文摘Background: Owing to the use of tobacco and the consumption of alcohol and adulterated food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since the last decade of the twentieth century, lung cancer has been the most common cancer type. This study aimed to determine the global status of lung cancer and to evaluate the use of computational methods in the early detection of lung cancer.Methods: We used lung cancer data from the United Kingdom(UK), the United States(US), India, and Egypt. For statistical analysis, we used incidence and mortality as well as survival rates to better understand the critical state of lung cancer.Results: In the UK and the US, we found a significant decrease in lung cancer mortalities in the period of 1990–2014, whereas, in India and Egypt, such a decrease was not much promising. Additionally, we observed that, in the UK and the US, the survival rates of women with lung cancer were higher than those of men. We observed that the data mining and evolutionary algorithms were efficient in lung cancer detection.Conclusions: Our findings provide an inclusive understanding of the incidences, mortalities, and survival rates of lung cancer in the UK, the US, India, and Egypt. The combined use of data mining and evolutionary algorithm can be efficient in lung cancer detection.Ashutosh Kumar Dubey Umesh Gupta Sonal Jain 2016Chinese Journal of Cancer2016,35,9:37
2Corrigendum to “Tillage and residue management effects on soil aggregation, organic carbon dynamics and yield attribute in rice–wheat cropping system under reclaimed sodic soil” [Soil Till. Res. 136 (2014) 76–83]显示文摘Shreyasi Gupta Choudhury Sonal Sivastava Ranbir Singh S.K. Chaudhari D.K. Sharma S.K. Singh Dipak Sarkar 2014Soil & Tillage Research2014,,:1
3显示文摘Gupta H C Sonal Brown 2001International J Inorganic Materials2001,3,:1
4显示文摘Gupta H C Sonal Brown 2002J Phys Chem Solids2002,63,:1
5Requirement of Caleineufin A for the Survival of Naive T Cells显示文摘SANTHAKUMAR MANICASSAMY SONAL GUPTA 2008The Journal of Immunology2008,180,:1
6Green tea extract: Possible mechanism and antibacterial activity on skin pathogens显示文摘Anjali Sharma Sonal Gupta Indira P. Sarethy Shweta Dang Reema Gabrani 2012Food Chemistry2012,,2:1
7Correlation of mycoplasma with unexplained infertility显示文摘Anjali Gupta Anshu Gupta Sonal Gupta Asha Mittal Phool Chandra Amarjit K. Gill 2009Archives of Gynecology and Obstetrics2009,,6:1
8Selective Function of PKC-θin T cells显示文摘T 房间激活是在仅仅通过这个过程后来开始适应有免疫力的反应的一个批评过程特定的 T 房间区分进调停的武装受动器 T 房间的 na (i) ve 抗原实际有免疫力的 response.During T 房间激活, na (i) ve T 房间经历同种细胞的扩大并且获得能力杀死感染病原体的目标房间或生产为调整有免疫力的反应必要的 cytokines 。T 房间的不恰当的激活或 inactivation 导致 autoimmunity 或严重免疫不全。PKC- 有选择地在 T 房间被表示并且为调停要求了 T 房间激活过程。在 PKC- 缺乏的老鼠在 T 房间激活,幸存和 activation-inducedcell 死亡展出缺点。PKC- 有选择地 translocates 到免疫学的触处并且调停为为 T 房间 activation.Furthermore 是必要的 NF-B, AP1 和 NFAT 的激活要求的信号, PKC --/- 鼠标在 vivo 在 T 调停房间的有免疫力的回答的开发显示了多重缺点。PKC- 因此是在 vivo 在 T 调停房间的有免疫力的回答在多重阶段调整 T 房间功能的一个批评分子。细胞与分子的免疫学。2006; 3 (4 ): 263-270。Santhakumar Manicassamy Sonal Gupta 2006Cellular & Molecular Immunology2006,3,4:1
9Medical Data Clustering and Classification Using TLBO and Machine Learning Algorithms显示文摘This study aims to empirically analyze teaching-learning-based optimization(TLBO)and machine learning algorithms using k-means and fuzzy c-means(FCM)algorithms for their individual performance evaluation in terms of clustering and classification.In the first phase,the clustering(k-means and FCM)algorithms were employed independently and the clustering accuracy was evaluated using different computationalmeasures.During the second phase,the non-clustered data obtained from the first phase were preprocessed with TLBO.TLBO was performed using k-means(TLBO-KM)and FCM(TLBO-FCM)(TLBO-KM/FCM)algorithms.The objective function was determined by considering both minimization and maximization criteria.Non-clustered data obtained from the first phase were further utilized and fed as input for threshold optimization.Five benchmark datasets were considered from theUniversity of California,Irvine(UCI)Machine Learning Repository for comparative study and experimentation.These are breast cancer Wisconsin(BCW),Pima Indians Diabetes,Heart-Statlog,Hepatitis,and Cleveland Heart Disease datasets.The combined average accuracy obtained collectively is approximately 99.4%in case of TLBO-KM and 98.6%in case of TLBOFCM.This approach is also capable of finding the dominating attributes.The findings indicate that TLBO-KM/FCM,considering different computational measures,perform well on the non-clustered data where k-means and FCM,if employed independently,fail to provide significant results.Evaluating different feature sets,the TLBO-KM/FCM and SVM(GS)clearly outperformed all other classifiers in terms of sensitivity,specificity and accuracy.TLBOKM/FCM attained the highest average sensitivity(98.7%),highest average specificity(98.4%)and highest average accuracy(99.4%)for 10-fold cross validation with different test data.Ashutosh Kumar Dubey Umesh Gupta Sonal Jain 2022Computers, Materials & Continua2022,,3:0
10Down-conversion materials for organic solar cells:Progress,challenges,and perspectives显示文摘Organic solar cells(OSCs)in terms of power conversion efficiency(PCE)and operational lifetime have made remarkable progress during the last decade by improving the active layer materials and introducing new interlayers.The newly developed wide bandgap organic donor and low bandgap acceptor molecules covered the absorption from the visible to the near-infrared region.Whereas the incident high energy region(UV)is not in favor of OSCs.Its absorption causes thermalization losses and photoinduced degradation,which hinders the PCE and lifetime of OSCs.Recently,lanthanide and non-lanthanide-based down-conversion(DC)materials have been introduced,which can effectively convert the high-energy photons(UV)to low-energy photons(visible)and resolve the spectral mismatch losses that limit the absorption of OSCs in high energy incident spectrum.Furthermore,the DC materials also protect the OSCs from UV-induced degradation.The DC materials were also proposed to cross the Shockley-Queisser efficiency limit of the solar cell.In this review,the need for DC materials and their processing method for OSCs have been thoroughly discussed.However,the main emphasis has been given to developing lanthanides and non-lanthanides-based DC materials for OSCs,their applications,and their impact on photovoltaic device performance,stability,and future perspectives.Ram Datt Swati Bishnoi Harrison Ka Hin Lee Sandeep Arya Sonal Gupta Vinay Gupta Wing Chung Tsoi 2022Aggregate2022,3,3:0
11BE-SONOS flash memory along with metal gate and high-k dielectrics in tunnel barrier and its impact on charge retention dynamics显示文摘We investigate the effect of a high-k dielectric in the tunnel layer to improve the erase speed-retention trade-off. Here, the proposed stack in the tunnel layer is AlLaO_3/Hf AlO/SiO_2. These proposed materials possess low valence band offset with high permittivity to improve both the erase speed and retention time in barrier engineered silicon-oxide-nitride-oxide-silicon(BE-SONOS). In the proposed structure Hf Al O and AlLaO_3 replace Si_3N_4 and the top SiO_2 layer in a conventional oxide/nitride/oxide(ONO) tunnel stack. Due to the lower conduction band offset(CBO) and high permittivity of the proposed material in the tunnel layer, it offers better program/erase(P/E) speed and retention time. In this work the gate length is also scaled down from 220 to 55 nm to observe the effect of high-k materials while scaling, for the same equivalent oxide thickness(EOT). We found that the scaling down of the gate length has a negligible impact on the memory window of the devices. Hence, various investigated tunnel oxide stacks possess a good memory window with a charge retained up to 87.4%(at room temperature) after a period of ten years. We also examine the use of a metal gate instead of a polysilicon gate, which shows improved P/E speed and retention time.Sonal Jain Deepika Gupta Vaibhav Neema Santosh Vishwakarma 2016Journal of Semiconductors2016,37,3:0
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