Despite recent advancements in immunotherapy, urothelial carcinoma patients with liver metastasis have a poor response to immune checkpoint inhibitors (ICIs) and short survival durations. Here, we investigated the clinical activity and molecular correlates of resistance to ICI in patients with metastatic urothelial carcinoma (mUC), focusing on liver metastasis. In this study, 755 patients with mUC who received pembrolizumab (JUOG cohort), 144 mUC patients who were treated with atezolizumab (IMvigor210 cohort), and 59 mUC patients who had metastatic samples available were enrolled. The presence of liver metastasis was associated with increased peripheral monocytes and a reduction in lymphocytes when compared with other metastatic sites, and a poor prognosis for ICI therapy. The peripheral monocyte-to-lymphocyte ratio was significantly correlated with the CD163+M2-like tumor-associated macrophage (TAM)/CD8+ tumor-infiltrative lymphocyte (TIL) ratio in the primary and metastatic UC lesions. Exploratory molecular analyses indicated that ICI-resistant status, such as decreased tumor mutation burden, low CD8+ TILs and immune checkpoint signatures, and increased M2-like TAM markers, in primary tumors was correlated with the presence of liver metastasis. In metastatic lesions, the CD163+M2-like TAM/CD8+TIL ratio and expression of cancer-associated fibroblasts induced by the TGFβ signaling pathway were higher in the liver versus the lung metastatic tumors. This study indicated that tumor-infiltrating lymphocyte and macrophage status in primary and metastatic lesions, which correlate with peripheral monocyte and lymphocyte status, may predict immunotherapy outcomes in UC patients with liver metastasis.
{"title":"Clinical and molecular correlates of response to immune checkpoint blockade in urothelial carcinoma with liver metastasis.","authors":"Takashi Yoshida, Chisato Ohe, Katsuhiro Ito, Hideaki Takada, Ryoichi Saito, Yuki Kita, Takeshi Sano, Koji Tsuta, Hidefumi Kinoshita, Hiroshi Kitamura, Hiroyuki Nishiyama, Takashi Kobayashi","doi":"10.1007/s00262-022-03204-6","DOIUrl":"10.1007/s00262-022-03204-6","url":null,"abstract":"<p><p>Despite recent advancements in immunotherapy, urothelial carcinoma patients with liver metastasis have a poor response to immune checkpoint inhibitors (ICIs) and short survival durations. Here, we investigated the clinical activity and molecular correlates of resistance to ICI in patients with metastatic urothelial carcinoma (mUC), focusing on liver metastasis. In this study, 755 patients with mUC who received pembrolizumab (JUOG cohort), 144 mUC patients who were treated with atezolizumab (IMvigor210 cohort), and 59 mUC patients who had metastatic samples available were enrolled. The presence of liver metastasis was associated with increased peripheral monocytes and a reduction in lymphocytes when compared with other metastatic sites, and a poor prognosis for ICI therapy. The peripheral monocyte-to-lymphocyte ratio was significantly correlated with the CD163<sup>+</sup>M2-like tumor-associated macrophage (TAM)/CD8<sup>+</sup> tumor-infiltrative lymphocyte (TIL) ratio in the primary and metastatic UC lesions. Exploratory molecular analyses indicated that ICI-resistant status, such as decreased tumor mutation burden, low CD8<sup>+</sup> TILs and immune checkpoint signatures, and increased M2-like TAM markers, in primary tumors was correlated with the presence of liver metastasis. In metastatic lesions, the CD163<sup>+</sup>M2-like TAM/CD8<sup>+</sup>TIL ratio and expression of cancer-associated fibroblasts induced by the TGFβ signaling pathway were higher in the liver versus the lung metastatic tumors. This study indicated that tumor-infiltrating lymphocyte and macrophage status in primary and metastatic lesions, which correlate with peripheral monocyte and lymphocyte status, may predict immunotherapy outcomes in UC patients with liver metastasis.</p>","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"4 1","pages":"2815-2828"},"PeriodicalIF":5.8,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10992465/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74253250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp211-219
M. Khadem, M. Karami
The plug-in electric vehicles (PEVs) including plug-in hybrid electric and all-electric vehicles will play a key role in the transportation future throughout the World. Consequently, a variety of works must be done to decrease the cost, improve the structure and increase the convenience of PEVs. This study proposed a single-phase, non-isolated and on-board battery charger with no use of any transformer which reduced the volume and weight of the system for PEVs. The main purpose is to provide an accurate control structure in order to achieve an acceptable charging in the wide range of voltage. The proposed structure is simulated by matrix laboratory (MATLAB) software. The results showed a high-power density, high efficiency and appropriate power factor from the structure of the non-isolated and single-phase charger.
{"title":"An effective control structure of on-board battery charger for electric vehicles","authors":"M. Khadem, M. Karami","doi":"10.11591/ijaas.v11.i3.pp211-219","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp211-219","url":null,"abstract":"The plug-in electric vehicles (PEVs) including plug-in hybrid electric and all-electric vehicles will play a key role in the transportation future throughout the World. Consequently, a variety of works must be done to decrease the cost, improve the structure and increase the convenience of PEVs. This study proposed a single-phase, non-isolated and on-board battery charger with no use of any transformer which reduced the volume and weight of the system for PEVs. The main purpose is to provide an accurate control structure in order to achieve an acceptable charging in the wide range of voltage. The proposed structure is simulated by matrix laboratory (MATLAB) software. The results showed a high-power density, high efficiency and appropriate power factor from the structure of the non-isolated and single-phase charger.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"11 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77780430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp220-231
S. Vasudevan, Venkatachalam Moorthy Kondayampalayam, A. Murugesan
This paper deals with offshore wind power generation technologies, power transmission and grid communication features, and associated power system studies for effective implementation of offshore wind energy systems, explaining its various stages of implementation. Also, this paper reviews the latest trends in offshore wind energy systems, addressing various aspects like large wind farm siting, power evacuation studies, cable selection, high-voltage direct current/flexible alternating current transmission systems (HVDC/FACTS) technology options, reliability evaluation, and autonomous monitoring. India's renewable power generation capacity through off-shore wind generation is also outlined to ensure low carbon energy emissions with improved energy efficiency. The policy and regulatory framework factors for reaching five gigawatts (GW) of offshore wind projects in the states of Tamilnadu and Gujarat by the year 2032 using current methods and advanced technology are discussed here. This goal can be accomplished using current practices and advanced technologies. For effective implementation of offshore wind farms, suitable measures and likely actions by various stakeholders are suggested.
{"title":"Recent developments in offshore wind energy systems: Technologies and practices","authors":"S. Vasudevan, Venkatachalam Moorthy Kondayampalayam, A. Murugesan","doi":"10.11591/ijaas.v11.i3.pp220-231","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp220-231","url":null,"abstract":"This paper deals with offshore wind power generation technologies, power transmission and grid communication features, and associated power system studies for effective implementation of offshore wind energy systems, explaining its various stages of implementation. Also, this paper reviews the latest trends in offshore wind energy systems, addressing various aspects like large wind farm siting, power evacuation studies, cable selection, high-voltage direct current/flexible alternating current transmission systems (HVDC/FACTS) technology options, reliability evaluation, and autonomous monitoring. India's renewable power generation capacity through off-shore wind generation is also outlined to ensure low carbon energy emissions with improved energy efficiency. The policy and regulatory framework factors for reaching five gigawatts (GW) of offshore wind projects in the states of Tamilnadu and Gujarat by the year 2032 using current methods and advanced technology are discussed here. This goal can be accomplished using current practices and advanced technologies. For effective implementation of offshore wind farms, suitable measures and likely actions by various stakeholders are suggested.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"93 24","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72492318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp194-198
Mohammed Razzok, A. Badri, Ilham El Mourabit, Y. Ruichek, A. Sahel
Pedestrian detection is a rapidly growing field of computer vision with applications in smart cars, surveillance, automotive safety, and advanced robotics. Most of the success of the last few years has been driven by the rapid growth of deep learning, more efficient tools capable of learning semantic, high-level, deeper features of images are proposed. In this article, we investigated the task of pedestrian detection on roads using models based on convolutional neural networks. We compared the performance of standard state-of-the-art object detectors like Faster region-based convolutional network (R-CNN), single shot detector (SSD), and you only look once, version 3 (YOLOv3). Results show that YOLOv3 is the best object detection model than others for pedestrians in terms of detection and time prediction.
{"title":"Pedestrian detection system based on deep learning","authors":"Mohammed Razzok, A. Badri, Ilham El Mourabit, Y. Ruichek, A. Sahel","doi":"10.11591/ijaas.v11.i3.pp194-198","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp194-198","url":null,"abstract":"Pedestrian detection is a rapidly growing field of computer vision with applications in smart cars, surveillance, automotive safety, and advanced robotics. Most of the success of the last few years has been driven by the rapid growth of deep learning, more efficient tools capable of learning semantic, high-level, deeper features of images are proposed. In this article, we investigated the task of pedestrian detection on roads using models based on convolutional neural networks. We compared the performance of standard state-of-the-art object detectors like Faster region-based convolutional network (R-CNN), single shot detector (SSD), and you only look once, version 3 (YOLOv3). Results show that YOLOv3 is the best object detection model than others for pedestrians in terms of detection and time prediction.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"21 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79157458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp242-252
Noor Syafina Mahamad Jainalabidin, Aqib Fawwaz Mohd Amidon, N. Ismail, Z. Mohd Yusoff, S. N. Tajuddin, M. Taib
Agarwood oil is well known for its unique scent and has many usages; as an incense, as ingredient in perfume, is burnt during religious ceremonies and is used in traditional medical preparation. Therefore, agarwood oil has high demand and is traded at different price based on its quality. Basically, the oil quality is classified by using physical properties (odor and color) and this technique has several problems: not consistent in term of accuracy. Thus, this study presented a new technique to classify the quality of agarwood oil based on chemical properties. The work focused on the k-Nearest Neighbor (k-NN) modelling by varying Mahalanobis and Correlation in distance metric for agarwood oil quality classification. It involved of 96 samples of agarwood oil, data pre-processing (data randomization, data normalization, and data division to testing and training datasets) and the development of k-NN model. The training dataset is used to train the k-NN model, and the testing dataset is used to test the developed model. During the model development, Mahalanobis and Correlation are varied in k-NN distance metric. The k-NN values are ranging from 1 to 10. Several performance criteria including resubstitution error (closs), cross-validation error (kloss) and accuracy were applied to measure the performance of the built k-NN model. All the analytical work was performed via MATLAB software version R2020a. The result showed that the accuracy of Mahalanobis distance metric has a better performance compared to Correlation from k=1 to k=5 with the value of 100.00%. This finding is important as it proved the capabilities of k-NN modelling in classifying the agarwood oil quality. Not limited to that, it also contributed to the agarwood oil research area as well as its industry.
沉香油以其独特的香味和多种用途而闻名;作为一种香，作为香水的成分，在宗教仪式上燃烧，并用于传统的医学制剂。因此沉香油的需求量很大，并根据其质量以不同的价格进行交易。基本上，油品质量是根据物理性质(气味和颜色)分类的，这种技术有几个问题:在准确性方面不一致。因此，本研究提出了一种基于化学性质对沉香油质量进行分类的新方法。研究了k-最近邻(k-NN)模型，通过改变距离度量中的Mahalanobis和Correlation来进行沉香油质量分类。它涉及96个沉香油样本，数据预处理(数据随机化，数据归一化，数据划分到测试和训练数据集)和k-NN模型的开发。训练数据集用于训练k-NN模型，测试数据集用于测试开发的模型。在模型开发过程中，k-NN距离度量中的马氏比和相关系数发生了变化。k-NN的取值范围是1 ~ 10。采用几种性能标准，包括重新替换误差(closs)、交叉验证误差(kloss)和准确性来衡量所构建的k-NN模型的性能。所有分析工作均通过R2020a版本的MATLAB软件进行。结果表明，与k=1 ~ k=5的相关性(Correlation from k=1 ~ k=5)相比，马氏距离度量的精度为100.00%，具有更好的性能。这一发现很重要，因为它证明了k-NN建模在沉香油质量分类中的能力。不仅如此，它还为沉香油研究领域和沉香油产业做出了贡献。
{"title":"The k-Nearest Neighbor modelling by varying Mahalanobis and Correlation in distance metric for agarwood oil quality classification","authors":"Noor Syafina Mahamad Jainalabidin, Aqib Fawwaz Mohd Amidon, N. Ismail, Z. Mohd Yusoff, S. N. Tajuddin, M. Taib","doi":"10.11591/ijaas.v11.i3.pp242-252","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp242-252","url":null,"abstract":"Agarwood oil is well known for its unique scent and has many usages; as an incense, as ingredient in perfume, is burnt during religious ceremonies and is used in traditional medical preparation. Therefore, agarwood oil has high demand and is traded at different price based on its quality. Basically, the oil quality is classified by using physical properties (odor and color) and this technique has several problems: not consistent in term of accuracy. Thus, this study presented a new technique to classify the quality of agarwood oil based on chemical properties. The work focused on the k-Nearest Neighbor (k-NN) modelling by varying Mahalanobis and Correlation in distance metric for agarwood oil quality classification. It involved of 96 samples of agarwood oil, data pre-processing (data randomization, data normalization, and data division to testing and training datasets) and the development of k-NN model. The training dataset is used to train the k-NN model, and the testing dataset is used to test the developed model. During the model development, Mahalanobis and Correlation are varied in k-NN distance metric. The k-NN values are ranging from 1 to 10. Several performance criteria including resubstitution error (closs), cross-validation error (kloss) and accuracy were applied to measure the performance of the built k-NN model. All the analytical work was performed via MATLAB software version R2020a. The result showed that the accuracy of Mahalanobis distance metric has a better performance compared to Correlation from k=1 to k=5 with the value of 100.00%. This finding is important as it proved the capabilities of k-NN modelling in classifying the agarwood oil quality. Not limited to that, it also contributed to the agarwood oil research area as well as its industry.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"20 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77766997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp232-241
A. Alqaisi, Loay E. George
Skin cancer is one of the most dangerous types of cancer. Some types of this cancer lead to death, so cancer must be discovered and indexed to avoid its spread through initial detection in the impulsive stage. This paper deals with the detection and indexing of different types of melanomas using an artificial neural network (ANN) depending on the international skin imaging collaboration (ISIC) 2018 dataset that was used. The pre-processing is the most important part because it formulates an image by insolated the cancer part from the skin image. It consists of four stages, removable, cropping, thinning, and normalization. This phase has been used to eliminate all the undesirable hair particles on the image lesion. The cropped image transforms into frequency domain coefficients using discrete cosine transform (DCT), discrete wavelet transform (DWT), and gradient transform for sub-band images to extract its feature. The statistical feature extraction is implemented to minimize the size of data for ANN training. The experimental analysis used dataset ISIC 2018 consisting of seven different types of dermoscopic images (this paper deals with four types only). For classification purposes, ANN was implemented and the accuracy obtained is about 88.98% for DWT, 85.44% for sub-band DCT, and 76.07% for sub-band gradient transform.
{"title":"Skin cancers image classification using transformation and first order statistic features with artificial neural network classifier","authors":"A. Alqaisi, Loay E. George","doi":"10.11591/ijaas.v11.i3.pp232-241","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp232-241","url":null,"abstract":"Skin cancer is one of the most dangerous types of cancer. Some types of this cancer lead to death, so cancer must be discovered and indexed to avoid its spread through initial detection in the impulsive stage. This paper deals with the detection and indexing of different types of melanomas using an artificial neural network (ANN) depending on the international skin imaging collaboration (ISIC) 2018 dataset that was used. The pre-processing is the most important part because it formulates an image by insolated the cancer part from the skin image. It consists of four stages, removable, cropping, thinning, and normalization. This phase has been used to eliminate all the undesirable hair particles on the image lesion. The cropped image transforms into frequency domain coefficients using discrete cosine transform (DCT), discrete wavelet transform (DWT), and gradient transform for sub-band images to extract its feature. The statistical feature extraction is implemented to minimize the size of data for ANN training. The experimental analysis used dataset ISIC 2018 consisting of seven different types of dermoscopic images (this paper deals with four types only). For classification purposes, ANN was implemented and the accuracy obtained is about 88.98% for DWT, 85.44% for sub-band DCT, and 76.07% for sub-band gradient transform.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"9 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80760906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.11591/ijaas.v11.i3.pp263-276
G. Aziz, S. W. Shneen, Fatin Nabeel Abdullah, D. H. Shaker
The current work aims to use traditional control algorithms and advanced optimization algorithms that was chosen for its ease of control and the possibility of using it in many industrial applications. By setting the appropriate specifications for the simulation model and after conducting the planned tests that simulate different applications of the motor’s work within electrical systems, the results proved to obtain good performance of the motor’s work, better response, high accuracy, in addition to the speed. The goal is to design and tune a proportional–integral–derivative (PID) controller by grey wolf optimization (GWO) using T.F for a direct current (DC) motor. To adjust the parameters of the traditional controllers using the optimum advanced, an appropriate mechanism and technology from the advanced optimization techniques were chosen, as the gray wolf technology algorithm was chosen as an optimization technique and integral time absolute error (ITAE) to adjust the parameters of the traditional PID controller.
{"title":"Advanced optimal GWO-PID controller for DC motor","authors":"G. Aziz, S. W. Shneen, Fatin Nabeel Abdullah, D. H. Shaker","doi":"10.11591/ijaas.v11.i3.pp263-276","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i3.pp263-276","url":null,"abstract":"The current work aims to use traditional control algorithms and advanced optimization algorithms that was chosen for its ease of control and the possibility of using it in many industrial applications. By setting the appropriate specifications for the simulation model and after conducting the planned tests that simulate different applications of the motor’s work within electrical systems, the results proved to obtain good performance of the motor’s work, better response, high accuracy, in addition to the speed. The goal is to design and tune a proportional–integral–derivative (PID) controller by grey wolf optimization (GWO) using T.F for a direct current (DC) motor. To adjust the parameters of the traditional controllers using the optimum advanced, an appropriate mechanism and technology from the advanced optimization techniques were chosen, as the gray wolf technology algorithm was chosen as an optimization technique and integral time absolute error (ITAE) to adjust the parameters of the traditional PID controller.","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"26 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81889370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.11591/ijaas.v11.i2.pp126-145
E. Pankratov
In this paper, we introduce an approach to increase the density of field-effect transistors framework nulling-resistor output amplifier. In the framework of the approach, we consider manufacturing the amplifier in a heterostructure with a specific configuration. Several required areas of the heterostructure should be doped by diffusion or ion implantation. After that dopant and radiation defects should be annealed framework optimized scheme. We also consider an approach to decrease the value of mismatch-induced stress in the considered heterostructure. We introduce an analytical approach to analyze mass and heat transport in heterostructures during the manufacturing of integrated circuits with account for mismatch-induced stress.
{"title":"A nulling-resistor output amplifier in the framework of heterostructures based on nonlinear partial differential equations","authors":"E. Pankratov","doi":"10.11591/ijaas.v11.i2.pp126-145","DOIUrl":"https://doi.org/10.11591/ijaas.v11.i2.pp126-145","url":null,"abstract":"In this paper, we introduce an approach to increase the density of field-effect transistors framework nulling-resistor output amplifier. In the framework of the approach, we consider manufacturing the amplifier in a heterostructure with a specific configuration. Several required areas of the heterostructure should be doped by diffusion or ion implantation. After that dopant and radiation defects should be annealed framework optimized scheme. We also consider an approach to decrease the value of mismatch-induced stress in the considered heterostructure. We introduce an analytical approach to analyze mass and heat transport in heterostructures during the manufacturing of integrated circuits with account for mismatch-induced stress. ","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"15 4 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77075909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1007/s12572-022-00320-5
A. Ruhi, S. V. Raghurama Rao, S. Muddu
{"title":"A lattice Boltzmann relaxation scheme for incompressible fluid flows","authors":"A. Ruhi, S. V. Raghurama Rao, S. Muddu","doi":"10.1007/s12572-022-00320-5","DOIUrl":"https://doi.org/10.1007/s12572-022-00320-5","url":null,"abstract":"","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"14 1","pages":"34-47"},"PeriodicalIF":0.9,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45311298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1007/s12572-022-00319-y
P. Maheswari, E. Tejaswini, P. Sridhar, S. R. Ambati
{"title":"Fuzzy logic control of biological wastewater treatment plants with non-ideal sensors and actuators","authors":"P. Maheswari, E. Tejaswini, P. Sridhar, S. R. Ambati","doi":"10.1007/s12572-022-00319-y","DOIUrl":"https://doi.org/10.1007/s12572-022-00319-y","url":null,"abstract":"","PeriodicalId":44367,"journal":{"name":"International Journal of Advances in Engineering Sciences and Applied Mathematics","volume":"14 1","pages":"24-33"},"PeriodicalIF":0.9,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43893917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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