Network Approach
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2022 ◽  
Vol 13 (1) ◽  
Chia-Chin Wu ◽  
Y. Alan Wang ◽  
J. Andrew Livingston ◽  
Jianhua Zhang ◽  
P. Andrew Futreal

AbstractOwing to a lack of response to the anti-PD1 therapy for most cancer patients, we develop a network approach to infer genes, pathways, and potential therapeutic combinations that are associated with tumor response to anti-PD1. Here, our prediction identifies genes and pathways known to be associated with anti-PD1, and is further validated by 6 CRISPR gene sets associated with tumor resistance to cytotoxic T cells and targets of the 36 compounds that have been tested in clinical trials for combination treatments with anti-PD1. Integration of our top prediction and TCGA data identifies hundreds of genes whose expression and genetic alterations that could affect response to anti-PD1 in each TCGA cancer type, and the comparison of these genes across cancer types reveals that the tumor immunoregulation associated with response to anti-PD1 would be tissue-specific. In addition, the integration identifies the gene signature to calculate the MHC I association immunoscore (MIAS) that shows a good correlation with patient response to anti-PD1 for 411 melanoma samples complied from 6 cohorts. Furthermore, mapping drug target data to the top genes in our association prediction identifies inhibitors that could potentially enhance tumor response to anti-PD1, such as inhibitors of the encoded proteins of CDK4, GSK3B, and PTK2.

Brenda McCowan ◽  
Jessica Vandeleest ◽  
Krishna Balasubramaniam ◽  
Fushing Hsieh ◽  
Amy Nathman ◽  

The notion of dominance is ubiquitous across the animal kingdom, wherein some species/groups such relationships are strictly hierarchical and others are not. Modern approaches for measuring dominance have emerged in recent years taking advantage of increased computational power. One such technique, named Percolation and Conductance (Perc), uses both direct and indirect information about the flow of dominance relationships to generate hierarchical rank order that makes no assumptions about the linearity of these relationships. It also provides a new metric, known as ‘dominance certainty’, which is a complimentary measure to dominance rank that assesses the degree of ambiguity of rank relationships at the individual, dyadic and group levels. In this focused review, we will (i) describe how Perc measures dominance rank while accounting for both nonlinear hierarchical structure as well as sparsity in data—here we also provide a metric of dominance certainty estimated by Perc, which can be used to compliment the information dominance rank supplies; (ii) summarize a series of studies by our research team reflecting the importance of ‘dominance certainty’ on individual and societal health in large captive rhesus macaque breeding groups; and (iii) provide some concluding remarks and suggestions for future directions for dominance hierarchy research. This article is part of the theme issue ‘The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies’.

Jiří Hadrava ◽  
Anna Talašová ◽  
Jakub Straka ◽  
Daniel Benda ◽  
Jan Kazda ◽  

2022 ◽  
Vol 3 (2) ◽  
pp. 120-125
Almighty C. Tabuena

The establishment of the K-12 curriculum has had a significant impact on subject requirements related to the outcome-based education plan and the requisite output for a given research report or requirement. Social networking platforms enable students to effortlessly complete a variety of tasks, such as learning and performance. By intervening in research, social networking sites break down the barriers that limit both students and teachers in the research process. Three methodologies or ideas have arisen, known as approaches, that could help you facilitate teaching research, even if you are not in the research discipline: the Facebook-Personality Network Approach, the Virtual Research Journal, and the Google Immersion Approach. It is considered favorably by some students and users, but there are those who take advantage of its negative aspects. Instead of focusing on the emerging ideas or topics created by coding, I used social networking sites to demonstrate that research can be done anytime, anyplace, for any purpose or cause. According to the outcome-based education paradigm, students found the three techniques highly engaging. In order to be a teacher-researcher, you must utilize your originality and resourcefulness when it comes to all of the resources, devices, and technology, as well as the available social networking sites.

Computers ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 10
Dillip Ranjan Nayak ◽  
Neelamadhab Padhy ◽  
Pradeep Kumar Mallick ◽  
Dilip Kumar Bagal ◽  
Sachin Kumar

Deep learning has surged in popularity in recent years, notably in the domains of medical image processing, medical image analysis, and bioinformatics. In this study, we offer a completely autonomous brain tumour segmentation approach based on deep neural networks (DNNs). We describe a unique CNN architecture which varies from those usually used in computer vision. The classification of tumour cells is very difficult due to their heterogeneous nature. From a visual learning and brain tumour recognition point of view, a convolutional neural network (CNN) is the most extensively used machine learning algorithm. This paper presents a CNN model along with parametric optimization approaches for analysing brain tumour magnetic resonance images. The accuracy percentage in the simulation of the above-mentioned model is exactly 100% throughout the nine runs, i.e., Taguchi’s L9 design of experiment. This comparative analysis of all three algorithms will pique the interest of readers who are interested in applying these techniques to a variety of technical and medical challenges. In this work, the authors have tuned the parameters of the convolutional neural network approach, which is applied to the dataset of Brain MRIs to detect any portion of a tumour, through new advanced optimization techniques, i.e., SFOA, FBIA and MGA.

Ping Wang ◽  
Qimeng Li ◽  
Peng Yin ◽  
Zhonghao Wang ◽  
Yu Ling ◽  

AbstractAccording to the World Health Organization and other authorities, falls are one of the main causes of accidental injuries among the elderly population. Therefore, it is essential to detect and predict the fall activities of older persons in indoor environments such as homes, nursing, senior residential centers, and care facilities. Due to non-contact and signal confidentiality characteristics, radar equipment is widely used in indoor care, detection, and rescue. This paper proposes an adaptive channel selection algorithm to separate the activity signals from the background using an ultra-wideband radar and to generalize fused features of frequency- and time-domain images which will be sent to a lightweight convolutional neural network to detect and recognize fall activities. The experimental results show that the method is able to distinguish three types of fall activities (i.e., stand to fall, bow to fall, and squat to fall) and obtain a high recognition accuracy up to 95.7%.

2021 ◽  
Vol 7 (1) ◽  
pp. 4
Edward Anuat ◽  
Douglas L. Van Bossuyt ◽  
Anthony Pollman

The ability to provide uninterrupted power to military installations is paramount in executing a country’s national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term “energy resilience impact” to identify and address supply chain disruption risks to energy security. The proposed methodology addresses a gap in the literature and practice where it is assumed supply chains will not be disrupted during incidents involving microgrids. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids. The fictional case study shows how supply chain disruptions can impact the ability of a microgrid to successfully supply electricity to critical loads throughout an islanding event.

2021 ◽  
Vol 13 (4) ◽  
pp. 88
Mateusz Surma ◽  
Mateusz Kaluza ◽  
Patrycja Czerwińska ◽  
Paweł Komorowski ◽  
Agnieszka Siemion

Terahertz (THz) optics often encounters the problem of small f number values (elements have relatively small diameters comparing to focal lengths). The need to redirect the THz beam out of the optical axis or form particular intensity distributions resulted in the application of iterative holographic methods to design THz diffractive elements. Elements working on-axis do not encounter significant improvement while using iterative holographic methods, however, for more complicated distributions the difference becomes meaningful. Here, we propose a totally different approach to design THz holograms, utilizing a neural network based algorithm, suitable also for complicated distributions. Full Text: PDF ReferencesY. Tao, A. Fitzgerald and V. Wallace, "Non-Contact, Non-Destructive Testing in Various Industrial Sectors with Terahertz Technology", Sensors, 20(3), 712 (2020). CrossRef J. O'Hara, S. Ekin, W. Choi and I. Song, "A Perspective on Terahertz Next-Generation Wireless Communications", Technologies, 7(2), 43 (2019). CrossRef L. Yu et al., "The medical application of terahertz technology in non-invasive detection of cells and tissues: opportunities and challenges", RSC Advances, 9(17), 9354 (2019). CrossRef A. Siemion, "The Magic of Optics—An Overview of Recent Advanced Terahertz Diffractive Optical Elements", Sensors, 21(1), 100 (2020). CrossRef A. Siemion, "Terahertz Diffractive Optics—Smart Control over Radiation", J. Infrared Millim. Terahertz Waves, 40(5), 477 (2019). CrossRef M. Surma, I. Ducin, P. Zagrajek and A. Siemion, "Sub-Terahertz Computer Generated Hologram with Two Image Planes", Appl. Sci., 9(4), 659 (2019). CrossRef S. Banerji and B.Sensale-Rodriguez, "A Computational Design Framework for Efficient, Fabrication Error-Tolerant, Planar THz Diffractive Optical Elements", Sci. Rep., 9(1), 5801 (2019). CrossRef J. Sun and F. Hu, "Three-dimensional printing technologies for terahertz applications: A review", Int. J. RF. Microw. C. E., 30(1) (2020). CrossRef E. Castro-Camus, M. Koch and A. I. Hernandez-Serrano, "Additive manufacture of photonic components for the terahertz band", J. Appl. Phys., 127(21), 210901 (2020). CrossRef DirectLink P. Komorowski, et al., "Three-focal-spot terahertz diffractive optical element-iterative design and neural network approach", Opt. Express, 29(7), 11243-11253 (2021) CrossRef M. Sypek, "Light propagation in the Fresnel region. New numerical approach", Opt. Commun., 116(1-3), 43 (1995). CrossRef

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