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11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Silva, Bruno Lopes, Luiz Guerreiro University of Madeira Sre Regional Government of Madeira PhD Program in Computer Engineering Funchal Madeira Portugal University of Madeira Faculty of Exact Sciences and Engineering Department of Mathematics Funchal Madeira9020-105 Portugal

ISBN: (纸本)9798350306941

Population-based computational intelligence algorithms are natural candidates for parallelization and have been utilized to solve a variety of difficult and complex real-world problems. The gray wolf optimizer (GWO) is one of these algorithms. It is a metaheuristic that simulates the leadership hierarchy and hunting mechanism of gray wolves in the wild and has been used successfully to solve several hard optimization problems. However, the study of its applicability to the solution of nonlinear equation systems, which is arguably the most difficult class of numerical problems, is still quite incipient and needs to be better accessed and verified, particularly in the case of large-scale systems of nonlinear equations, which have not been considered until now and whose resolution difficulty increases with the number of equations they contain. This paper presents a new and efficient GPU-based massively parallel implementation of the gray wolf optimizer algorithm for solving large-scale optimization problems. The proposed parallelization of the GWO algorithm is illustrated by its application to solving large systems of nonlinear equations, a class of problems that appear and have great importance in different fields of pure and applied sciences and engineering. The GPU-accelerated version of GWO was implemented in Julia and tested on a GeForce RTX 3090 GPU with 24 GB GDDR6X VRAM and 10 496 CUDA cores using a set of hard, scalable systems of nonlinear equations with dimensions ranging from 500 to 2000. The obtained results, with average speedups between 69.91× and 241.54× , show the efficiency of the proposed GPU-based acceleration of the GWO algorithm. © 2023 IEEE.

关键词： Graphics processing unit

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Differential Co-expression Network Analysis to Investigate Sexual Dimorphism in Colon Cancer

Differential Co-expression Network Analysis to Investigate S...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Alfano, Caterina Farina, Lorenzo Petti, Manuela Sapienza University of Rome PhD Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome PhD Program in Network Oncology and Precision Medicine Dept. of Computer Control and Management Engineering Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9781665468190

Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the disease. This study focuses on mRNA expression profiles of colon cancer patients to look for molecular differences in the development of colon cancer between men and women. We used paired expression data (i.e., data collected in pairs of normal and cancer cells, by taking samples from the same individual), we identified differentially expressed genes (cancer vs normal) and computed co-expression and differential co-expression gene networks (men vs women). Doing so, we inferred the main changes and alterations happening in cancer tissues, and specifically how these changes were different among men and women. We found that the co-expression networks of women and men affected by colon cancer are quite different and we reported the genes that show the most differences in this comparison, checking if they could also be associated to sexual dimorphism or sexual hormones. Among these genes we found a interesting presence of genes associated to the Wnt signaling pathway which has been found to be regulated by estrogen and whose activation is strongly linked with colon cancer. © 2022 IEEE.

关键词： Diseases

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MIRROR: MiRNA regulation-level differential network to study sex and ethnic disparities in cancer 46

MIRROR: MiRNA regulation-level differential network to study...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Alfano, Caterina Filetti, Marco Farina, Lorenzo Petti, Manuela Sapienza University of Rome Dept. of Experimental Medicine Rome Italy Fondazione Policlinico Universitario A. Gemelli Irccs Phase 1 Unit Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering PhD Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350371499

Cancer disparities are adverse differences in cancer measures that exist among certain population groups. Given that the role they play not only in the disease prognosis but also in therapy response, there is an urgent need to understand what causes them. Most studies investigate these disparities by analyzing transcriptomic data and in particular miRNAs for their regulatory role, but only focusing on expression levels. To face this challenge we propose MIRROR, a new method which analyzes a differential co-expression network of miRNAs between patients' cohorts, to study the role they play at the target genes' level. Doing so, we can study the altered molecular mechanism that are linked to cancer disparities. The application of MIRROR to two different cases of cancer disparities has demonstrated its efficacy in identifying molecular players involved in the considered disparity, presenting itself as a viable option to approach this challenge. © 2024 IEEE.

关键词： differential network modeling disparities in cancer graph theory miRNA-target association transcriptomics

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Artificial Intelligence Driven Multivariate Time Series Analysis of Network Traffic Prediction

Artificial Intelligence Driven Multivariate Time Series Anal...

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2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Filiz, Gözde Yıldız, Ayşenur Kara, Erkan Altıntaş, Suat Çakar, Tuna Computer Sci.& Eng. PhD. Program MEF University Istanbul Turkey Research and Development Andromeda TV Digital Plat. Op. Inc. Istanbul Turkey IT Sytems and Network Andromeda TV Digital Plat. Op. Inc. Istanbul Turkey Computer Engineering MEF University Istanbul Turkey

ISBN: (纸本)9798350379433

The primary objective of this research is to employ artificial intelligence, machine learning, and neural networks in order to construct a network traffic prediction model. The analysis of network traffic data obtained from a digital media and entertainment provider operating in Turkey is conducted through the application of multivariate time-series analysis techniques in order to get insights into the temporal patterns and trends. In model development, Vector Autoregression (VAR), Vector Error Correction Model (VECM), Long-Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) algorithms have been utilized. LSTM and GRU models have performed better with low Mean Absolute Percentage Error (MAPE) and high R-squared Score (R2). LSTM model has reached 0.98 R2 and 8.95% MAPE. These results indicate that the models can be utilized in network management optimization as resource allocation, congestion detection, anomaly detection, and quality of service. © 2024 IEEE.

关键词： Quality of service

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Stratification of metastatic melanoma patients based on mutational signatures

Stratification of metastatic melanoma patients based on muta...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Caterina Alfano Lorenzo Farina Manuela Petti PhD Program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering PhD Program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach.

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Towards cross-modal causal structure and representation learning 2

Towards cross-modal causal structure and representation lear...

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2nd Machine Learning for Health Symposium, ML4H 2022

作者： Mao, Haiyi Liu, Hongfu Xiaotian Dou, Jason Benos, Panayiotis V. Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh United States Michtom School of Computer Science Brandeis University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Epidemiology University of Florida United States

Does the SARS-CoV-2 virus cause patients' chest X-Rays ground-glass opacities? Does an IDH-mutation cause differences in patients' MRI images? Conventional causal discovery algorithms, although well developed to uncover the cause-effect relationships on structured data, cannot elucidate causal relations between unstructured images and structured scalar variables due to the complexity of the former. In this paper, we consider causal discovery between images and structured (scalar) variables. Specifically, we derive low dimensional image representations to analyze with structured variables. We propose a two-module amortized variational algorithm named Cross-Modal Variational Causal representation and structure Learning (CMCL). CMCL jointly learns identifiable representations given a set of independent structured variables and causal relations via formulating latent representations and structured variables into a direct acyclic graph. Moreover, we further enforce counterfactual invariance/variance onto representations. We demonstrate that CMCL outperforms other related methods on synthetic datasets and validate causal relations on semi-synthetic datasets by visualization. © 2022 P.N. Argaw, E. Healey & I.S. Kohane.

关键词： Coronavirus

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Development of 5G Cyber-Physical Production System

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International Journal of Networked and Distributed Computing 2023年第1期11卷 9-19页

作者： Huang, Hsuan-Chao Tsai, Chun-Hsien Lin, Hsiung-Cheng Department of Computer Science and Information Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan PhD program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan Department of Electronic Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd Taiping Dist Taichung Taiwan

The cyber-physical production system (CPPS) was developed for the interconnection between operational technology (OT) and information and communication technology (ICT) among the machines and decentralized production control. However, OT and ICT are now getting more complex in the modern industry. To enhance industrial management and production process, the CPPS based on the 5G architecture under production environments can provide a more comprehensive solution in the context of Industry 4.0. For this purpose, a 5G CPPS model to improve the interoperability of CPPS in ICT and OT is proposed to build a virtualized Industry 4.0 asset management shell system. First, real-time task artifacts and 5G communication modules are bound in a certain form of virtualization. Second, task artifacts are released to the production line in a real-time scheduling. Third, an order is placed on a production line and split into multiple tasks for production process. Single-machine single-workpiece and multi-machine and multi-workpiece processing cases are used for testing in the production line. Experimental results show that the proposed 5G CPPS can efficiently achieve multi-machine work piece processing. © 2022, The Author(s).

关键词： 5G Cyber-physical production system (CPPS) Digital twin (DT) Industry 4.0 Information technology Operational technology

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Spleen-preserving distal pancreatectomy from multi-port to reducedport surgery approach

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World Journal of Gastrointestinal Surgery 2023年第7期15卷 1501-1511页

作者： Ching-Lung Hsieh Tung-Sheng Tsai Cheng-Ming Peng Teng-Chieh Cheng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724TaiwanChina Department of Surgery Chung Shan Medical University HospitalTaichung 40201TaiwanChina PhD Program of Electrical and Communications Engineering Feng Chia UniversityTaichung 40724Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Da Vinci Minimally Invasive Surgery Center Chung Shan Medical University HospitalTaichung 40201Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

BACKGROUND Minimally invasive pancreatic surgery via the multi-port approach has become a primary surgical method for distal pancreatectomy(DP)due to its advantages of lower wound pain and superior cosmetic *** studies have applied reduced-port techniques for DP in an attempt to enhance cosmetic outcomes due to the minimally invasive *** recent review studies have compared multi-port laparoscopic DP(LDP)and multi-port robotic DP(RDP);most of these studies concluded multi-port RDP is more beneficial than multi-port LDP for spleen ***,there have been no comprehensive reviews of the value of reduced-port LDP and reduced-port *** To search for and review the studies on spleen preservation and the clinical outcomes of minimally invasive DP that compared reduced-port DP surgery with multi-port DP *** The PubMed medical database was searched for articles published between 2013 and *** search terms were implemented using the following Boolean search algorithm:(“distal pancreatectomy”OR“left pancreatectomy”OR“peripheral pancreatic resection”)AND(“reduced-port”OR“single-site”OR“single-port”OR“dual-incision”OR“single-incision”)AND(“spleen-preserving”OR“spleen preservation”OR“splenic preservation”).A literature review was conducted to identify studies that compared the perioperative outcomes of reduced-port LDP and reduced-port *** Fifteen articles published in the period from 2013 to 2022 were retrieved using three groups of search *** studies were added after manually searching the related ***,10 papers were selected after removing case reports(n=3),non-English language papers(n=1),technique papers(n=1),reviews(n=1),and animal studies(n=1).The common items were defined as items reported in more than five papers,and data on these common items were extracted from all *** ten studies included a total of 337 patients(females/males:231/106)who underwent *** total,166 patients(females/male

关键词： Minimally invasive surgery Robotic distal pancreatectomy Laparoscopic distal pancreatectomy Spleen preservation Reduced-port Multi-port

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A multimodal integrative approach to model transcriptional addiction of thyroid cancer on RUNX2

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Cancer Communications 2022年第9期42卷 892-896页

作者： Emanuele Vitale Elisabetta Sauta Mila Gugnoni Federica Torricelli Veronica Manicardi Alessia Ciarrocchi Laboratory of Translational Research Azienda Unità Sanitaria Locale-IRCCS di Reggio EmiliaReggio Emilia 42123Italy Clinical and Experimental Medicine PhD Program University of Modena and Reggio EmiliaModena 41121Italy Department of Electrical Computer and Biomedical EngineeringUniversity of PaviaPavia 27100Italy

Dear Editor Aberrant gene expression sustains massive proliferation and stress adaptation under the regulation of oncogenic transcription factors(TFs)whose binding across the genome orchestrates in space and time *** dependency defines the addiction of cancer cells to TFs on top of the regulatory hierarchy governing cancer dysregulated programs[1].These factors and their dependent mechanisms are an attractive and unexplored reservoir of potential targets for new anticancer ***,while the transcriptional landscape of many cancer-supportive TFs has been revealed,this information remains purely descriptive and confined to in vitro *** foster transferability,new approaches that integrate clinical data into the transcriptional networks are needed.

关键词： addiction modal reservoir

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A GPU-Based Parallel Implementation of the GWO Algorithm: Application to the Solution of Large-Scale Nonlinear Equation Systems

A GPU-Based Parallel Implementation of the GWO Algorithm: Ap...

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International Symposium on Computing and Networking Workshops (CANDARW)

作者： Bruno Silva Luiz Guerreiro Lopes PhD Program in Computer Engineering University of Madeira SRE Regional Government of Madeira Funchal Madeira Is. Portugal Department of Mathematics Faculty of Exact Sciences and Engineering University of Madeira Funchal Madeira Is. Portugal

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