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Plastic Pipes and Their Use in Rainwater Drainage systems

IOP Conference Series: Earth and Environmental Science 2022年第5期988卷 052032页

作者： D I Tarakanov PhD in Engineering Science Dean of the Faculty of Engineering Systems and Environmental Construction Associate Professor of Water Supply and Wastewater Disposal Department Molodogvardeyskaya str. 244 Samara 443100 Russia

This paper studies the conditions for the use of plastic pipes in rainwater drainage systems. In this research, the author undertakes a literature review and finds out that the share of plastic pipes in the construction of gravity sewage network has significantly increased over the past 20 years. Plastic pipes low roughness ensures higher flow rates of wastewater. The peculiarity of rainwater drainage calculating methodology leads to the fact that an increase in the speed of wastewater movement leads to the formation of larger wastewater discharge in the design section of the pipeline with the same rainfall intensity. It is established that at present the cost of rainwater drainage systems construction from polypropylene pipes is 80-100% higher than from reinforced concrete (excluding the construction of pumping stations and wastewater treatment facilities).

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How Microbes Shape Their Communities? A Microbial Community Model Based on Functional Genes

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Genomics, Proteomics & Bioinformatics 2019年第1期17卷 91-105页

作者： Xiaoqing Jiang Xin Li Longshu Yang Chunhong Liu Qi Wang Weilai Chi Huaiqiu Zhu State Key Laboratory for Turbulence and Complex Systems Department of Biomedical Engineering College of Engineering Peking University Center for Quantitative Biology Peking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Biological (PTN) PhD Program and College of Life Sciences Peking University Center for Protein Science Peking University

Exploring the mechanisms of maintaining microbial community structure is important to understand biofilm development or microbiota dysbiosis. In this paper, we propose a functional gene-based composition prediction(FCP) model to predict the population structure composition within a microbial community. The model predicts the community composition well in both a low-complexity community as acid mine drainage(AMD) microbiota, and a complex community as human gut microbiota. Furthermore, we define community structure shaping(CSS) genes as functional genes crucial for shaping the microbial community. We have identified CSS genes in AMD and human gut microbiota samples with FCP model and find that CSS genes change with the conditions. Compared to essential genes for microbes, CSS genes are significantly enriched in the genes involved in mobile genetic elements, cell motility, and defense mechanisms, indicating that the functions of CSS genes are focused on communication and strategies in response to the environment factors. We further find that it is the minority, rather than the majority, which contributes to maintaining community structure. Compared to health control samples, we find that some functional genes associated with metabolism of amino acids, nucleotides, and lipopolysaccharide are more likely to be CSS genes in the disease group. CSS genes may help us to understand critical cellular processes and be useful in seeking addable gene circuitries to maintain artificial self-sustainable communities. Our study suggests that functional genes are important to the assembly of microbial communities.

关键词： Metagenomics Dynamics model Community structure Acid mine drainage Human gut microbiota

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An Adaptive Multi-critic Neuro-fuzzy Control Framework for Intravenous Anesthesia Administration

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IFAC-PapersOnLine 2019年第34期51卷 202-207页

作者： Khodaei, Mohammad Javad Balaghi I., M. Hadi Mehrvarz, Amin Jalili, Nader PhD Student Piezoactive Systems Laboratory Department of Mechanical Industrial Engineering Northeastern University BostonMA02115 United States Eindhoven Netherlands Professor and Author of Correspondence Department Head of Mechanical Engineering The University of Alabama TuscaloosaAL United States Affiliate Professor Department of Mechanical Industrial Engineering Northeastern University BostonMA United States

Development of closed-loop control strategies for drug infusion and delivery is one of the most recent efforts of control engineers and clinicians. This can be used especially in anesthesia during different surgeries to stabilize the patient in the desired awareness condition. In this paper, an adaptive neuro-fuzzy controller is proposed to overcome the current challenges in closed-loop control of anesthesia such as inter and intra patient variability, complex and nonlinear dynamics, measurement noises and surgical disturbances as well as the presence of undershoot and overshoot in the induction phase. The results show an acceptable performance of the proposed controller in solving these problems by providing a learning scheme. © 2019

关键词： Controllers Anesthesiology Closed loop control systems Controlled drug delivery Drug infusion Fuzzy control Fuzzy inference Fuzzy neural networks Surgery Closed loops Fuzzy controllers Inter intra patient variability Intravenous anesthesias Surgical disturbances

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An Assessment Model for Hospital Resilience according to the Simultaneous Consideration of Key Performance Indicators: A System Dynamics Approach

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Perioperative Care and Operating Room Management 2020年 20卷 100118-100118页

作者： Pishnamazzadeh, Mohammad Sepehri, Mohammad Mehdi Ostadi, Bakhtiar PhD Candidate Faculty of Industrial and Systems Engineering Tarbiat Modares University Tehran *** Iran Professor of Healthcare Systems Engineering Faculty of Industrial and Systems Engineering Tarbiat Modares University Tehran *** Iran Hospital Management Research Center (HMRC) Iran University of Medical Sciences (IUMS) Tehran *** Iran Assistant Professor Faculty of Industrial and Systems Engineering Tarbiat Modares University Tehran *** Iran

Background: Globalization allows the effects of disruptions to cascade in the systems rapidly and a small disruption could lead to a broad catastrophe. Nowadays, disruptions are becoming more unpredictable, more frequent and more damaging. Hospitals are critical facilities which play an important role after disruptions. Number of deaths and injuries from disasters depends heavily on how hospitals serve people. Therefore, assuring the proper performance of hospitals under disruption is an important issue. Our approach to improve hospital performance is modelling the performance from resilience engineering perspective. Methods: First step towards building or designing a resilient organization is assessment and based on that a set of strategies or actions could be defined to increase resilience level. To address this issue, we considered hospital resilience as the maximum disruption that a hospital can tolerate and not be turbulent. We have proposed a model to assess hospital resilience. Four Key Performance Indicators (KPI) of hospitals, consisting patient satisfaction, patient waiting time, staff burnout and staff satisfaction, as well as variables affecting them were considered. System dynamics approach has been used to investigate the effect of disruptions on the four KPIs and multiple scenarios has been developed to assess the toleration of the hospital KPIs. Results: The results showed that human resources related factors has a significant impact on the resilience of the hospitals and their changes could lead to performance loss. In addition, number of beds can change the resilience level of the hospital dramatically. Conclusion: Disruptions change the exogenous factors. Therefore, hospital managers should define some strategies in order to prevent them such as staff related factors. The most important factor is number of beds and they should consider some extra capacities for emergency circumstances. © 2020

关键词： Assessment Model Hospital Resilience Key Performance Indicators System Dynamics Approach

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Constructor of compositions of machine learning models for solving classification problems

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Procedia Computer Science 2020年 169卷 780-786页

作者： Igor Lavrov Jenny Domashova student of the Institute of Cyber Intelligence Systems National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) Kashirskoe highway 31 Moscow 115409 Russian Federation Candidate of Sciences (PhD) in Economics Associate Professor of the Institute of Cyber Intelligence Systems National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) Kashirskoe highway 31 Moscow 115409 Russian Federation

The article concerns the description of program software that gives an opportunity to solve classification problem by machine learning methods on input data in context of different subject areas. The list of such tasks can include: identification of suspicious state contracts for collusion of suppliers, forecasting the execution of a government contract, forecasting license revocation from credit organizations and insurance companies, etc. The application allows a user to build a composition of several base machine learning models to solve classification problems. As part of the study, the functional requirements for the product being created are presented, the architecture has been developed, the design and testing of the proposed process for creating machine learning model compositions has been carried out. The use of the application will allow to build compositions of machine learning models in a user-friendly mode in order to increase the accuracy of the classification problem. The use of the proposed tools improves the accuracy of solving the classification problem on input data in the context of various subject areas through the utilization of a composition of machine learning methods.

关键词： machine learning neural networks decision trees model constructor model composition classification problem

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Initial human study of an AWSM-PET Device for Augmented Whole-body PET Imaging

Initial human study of an AWSM-PET Device for Augmented Whol...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Y. Chen M. Hamdi S. Komarov A. Thomas R. A. Mintzer S. Cho D. Pocci J. Corbeil J. Breuer M. S. Judenhofer N. Wu L. Cai J. Frye F. Dehdashti J. A. O’Sullivan R. Laforest S. B. Siegel Y.-C. Tai Washington University in St.Louis Imaging Science PhD program St. Louis Missouri United States of America Washington University in St.Louis Radiology St. Louis Missouri United States of America Washington University in St.Louis Chemistry St. Louis Missouri United States of America Siemens Medical Solutions USA Inc. Molecular Imaging Knoxville Tennessee United States of America Washington University in St.Louis Public Health Sciences St. Louis Missouri United States of America Washington University in St.Louis Electrical & Systems Engineering St. Louis Missouri United States of America

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

The Augmented Whole-body Scanning via Magnifying PET (AWSM-PET) device is a novel technology designed to improve the detectability of lesions in whole-body PET/CT imaging. We have developed a prototype AWSM-PET device that consists of two panels of high-resolution time-of-flight (TOF) PET detectors, integrated with the standard readout electronics and event processing architecture of the Biograph Vision (Siemens Healthineers). The system exhibits excellent spatial, energy and timing resolution, with an average coincidence resolving time of $\sim 217$ ps FWHM and an average energy resolution of $\sim 11 \%$ FWHM at 511 keV. Custom firmware and software have been developed to encode the large number of detector elements and to form coincidences between the AWSM-PET detectors and the Biograph Vision scanner. We have pioneered a specialized image reconstruction approach utilizing a GPU-based list-mode framework, which incorporates the system’s point-spread function (PSF) to optimize image quality and spatial resolution. Continuous-bed motion (CBM) whole-body imaging protocols have been implemented for the AWSM-PET operation to improve the uniformity of sensitivity across the patient’s body. Sensitivity enhancement was evaluated using a point source. The first human subject study was a head-andneck cancer patient scheduled for a standard-of-care (SOC) FDG PET/CT scan following treatment. Both the SOC-PET/CT images and the AWSM-PET images were acquired simultaneously for a total of 17 minutes using the CBM mode. Results show high-resolution and high-quality AWSM-PET images. We anticipate to image more patients in the summer, refine AWSM-PET image reconstruction parameters and correction techniques. Comparison between the AWSM-PET and the SOC-PET/CT will be presented at the 2024 IEEE MIC conference.

关键词： Microwave integrated circuits Sensitivity Biographies Energy resolution Whole-body PET Software Timing

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Split-Net: Dual Transformer Encoder with Splitting Scene Text Image for Script Identification

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Pattern Recognition Letters 2025年

作者： Ayush Roy Shivakumara Palaiahnakote Umapada Pal Cheng-Lin Liu PhD Department of Computer Science and Engineering State University of New York Buffalo USA School of Science Engineering and Environment University of Salford Manchester UK Computer Vision and Pattern Recognition Indian Statistical Institute Kolkata India State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation of the Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

Script identification is vital for understanding scenes and video images. It is challenging due to high variations in physical appearance, typeface design, complex background, distortion, and significant overlap in the characteristics of different scripts. Unlike existing models, which aim to tackle the script images utilizing the scene text image as a whole, we propose to split the image into upper and lower halves to capture the intricate differences in stroke and style of various scripts. Motivated by the accomplishments of the transformer, a modified script-style-aware Mobile-Vision Transformer (M-ViT) is explored for encoding visual features of the images. To enrich the features of the transformer blocks, a novel Edge Enhanced Style Aware Channel Attention Module (EESA-CAM) has been integrated with M-ViT. Furthermore, the model fuses the features of the dual encoders (extracting features from the upper and the lower half of the images) by a dynamic weighted average procedure utilizing the gradient information of the encoders as the weights. In experiments on three standard datasets, MLe2e, CVSI2015, and SIW-13, the proposed model yielded superior performance compared to state-of-the-art models.

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Image Filtering Algorithm Based on the Analysis of the Main Components

Image Filtering Algorithm Based on the Analysis of the Main ...

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2019 International Conference on Information Science and Communications Technologies, ICISCT 2019

作者： Nosirov, Khabibullo Norinov, Muhammadyunus Abdukadirov, Bakhtiyor PhD Tashkent University of Information Technology Head of the Department of Broadcasting Systems Tashkent Uzbekistan Tashkent University of Information Technology Tashkent Uzbekistan University of Information Technology Department of Software Engineering Ferghana Branch of Tashkent Ferghana Uzbekistan

the paper considers an algorithm that allows to solve the problem of filtering images based on the analysis of the main components, also presents simulation results showing the main features of this algorithm. © ... 详细信息

ISBN: (纸本)9781728125640

关键词： Image analysis

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Initial Results of a Prototype AWSM-PET Device for Augmented Whole-body PET Imaging

Initial Results of a Prototype AWSM-PET Device for Augmented...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Y. Chen M. Hambdi S. Komarov R. A. Mintzer S. Cho D. Pocci A. Thomas J. Corbeil J. Breuer M. Judenhofer N. Wu J. Frye F. Dehdashti J. A. O’Sullivan R. Laforest S. B. Siegel Y.-C. Tai Imaging Science PhD Program Washington University in St.Louis St. Louis Missouri United States of America Mallinckrodt Institute of Radiology Washington University in St. Louis St. Louis Missouri United States of America Molecular Imaging Siemens Medical Solutions USA Inc Knoxville Tennessee United States of America Department of Chemistry Washington University in St. Louis St. Louis Missouri United States of America Department of Biostatistics Washington University in St. Louis St. Louis United States of America Department of Electrical and Systems Engineering Washington University in St. Louis Missouri St. Louis United States of America

The Augmented Whole-body Scanning via Magnifying PET (AWSM-PET) is a technology designed to enhance the diagnostic accuracy of whole-body (WB) PET/CT imaging for the detection of small lesions. We recently constructed the first prototype AWSM-PET device that consists of two panels of high-resolution time-of-flight (TOF) PET detectors (using ~1mm pitched LSO crystals), integrated with the standard readout electronics and event processing architecture of the Siemens Biograph Vision scanner. The system exhibits excellent spatial, energy and timing resolution, with an average coincidence resolving time of ~183 ps FWHM and an average energy resolution of ~11% FWHM at 511 keV. Custom firmware and software have been developed to encode the large number of detector elements and to enable coincidence detection between the AWSM-PET detectors and the Biograph Vision *** tests of the AWSM-PET device show the image resolution of the Biograph Vision scanner is improved from the original >3mm to ~2mm FWHM. A GPU-based list-mode image reconstruction framework has been expanded to incorporate the point-spread function (PSF) of the native scanner and the AWSM-PET detectors to optimize the spatial resolution and improve image *** step-and-shoot and continuous-bed motion imaging protocols are supported for the AWSM-PET operation and are being evaluated for the reconstructed image resolution and the uniformity of the overall system sensitivity across a long axial FOV. Extensive phantom imaging studies are ongoing to evaluate the system's performance. Initial human imaging studies will be presented in the upcoming 2023 Medical Imaging Conference.

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Epigenetic factor competition reshapes the EMT landscape

arXiv

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arXiv 2022年

作者： Ali Al-Radhawi, M. Tripathi, Shubham Zhang, Yun Sontag, Eduardo D. Levine, Herbert Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Center for Theoretical Biological Physics Northeastern University BostonMA02115 United States PhD Program in Systems Synthetic and Physical Biology Rice University HoustonTX77005 United States Whitehead Institute for Biomedical Research CambridgeMA02142 United States Department of Bioengineering Northeastern University BostonMA02115 United States Department of Physics Northeastern University BostonMA02115 United States Laboratory of Systems Pharmacology Harvard Medical School BostonMA02115 United States State Key Laboratory of Molecular Oncology National Cancer Center National Clinical Research Center for Cancer Cancer Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100021 China

The emergence of and transitions between distinct phenotypes in isogenic cells can be attributed to the intricate interplay of epigenetic marks, external signals, and gene regulatory elements. These elements include chromatin remodelers, histone modifiers, transcription factors, and regulatory RNAs. Mathematical models known as Gene Regulatory Networks (GRNs) are an increasingly important tool to unravel the workings of such complex networks. In such models, epigenetic factors are usually proposed to act on the chromatin regions directly involved in the expression of relevant genes. However, it has been well-established that these factors operate globally and compete with each other for targets genome-wide. Therefore, a perturbation of the activity of a regulator can redistribute epigenetic marks across the genome and modulate the levels of competing regulators. In this paper, we propose a conceptual and mathematical modeling framework that incorporates both local and global competition effects between antagonistic epigenetic regulators in addition to local transcription factors, and show the counter-intuitive consequences of such interactions. We apply our approach to recent experimental findings on the Epithelial-Mesenchymal Transition (EMT). We show that it can explain the puzzling experimental data as well provide new verifiable predictions. © 2022, CC BY-NC-ND.

关键词： Transcription factors

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