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Probabilistic genotype-phenotype maps reveal mutational robustness of RNA folding, spin glasses, and quantum circuits

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Physical Review Research 2025年第1期7卷 013118-013118页

作者： Anna Sappington Vaibhav Mohanty Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard-MIT Program in Health Sciences and Technology Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard/MIT MD-PhD Program Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

Recent studies of genotype-phenotype maps have reported universally enhanced phenotypic robustness to genotype mutations, a feature essential to evolution. Virtually all of these studies make a simplifying assumption that each genotype—represented as a sequence—maps deterministically to a single phenotype, such as a discrete structure. Here we introduce probabilistic genotype-phenotype (PrGP) maps, where each genotype maps to a vector of phenotype probabilities, as a more realistic and universal language for investigating robustness in a variety of physical, biological, and computational systems. We study three model systems to show that PrGP maps offer a generalized framework which can handle uncertainty emerging from various physical sources: (1) thermal fluctuation in RNA folding, (2) external field disorder in the spin-glass ground state search problem, and (3) superposition and entanglement in quantum circuits, which are realized experimentally on IBM quantum computers. In all three cases, we observe a biphasic robustness scaling which is enhanced relative to random expectation for more frequent phenotypes and approaches random expectation for less frequent phenotypes. We derive an analytical theory for the behavior of PrGP robustness, and we demonstrate that the theory is highly predictive of empirical robustness.

关键词： Quantum computers

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Medical Image Segmentation by Improved Nested Unet 2nd

Medical Image Segmentation by Improved Nested Unet

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2nd International Conference on Intelligent Systems and Data science, ISDS 2024

作者： Tran, Song-Toan Le, Minh-Hai Nguyen, Thai-Son Nghi, Vinh-Khanh Nguyen, Thanh-Nguyen School of Engineering and Technology Tra Vinh University Tra Vinh87000 Viet Nam Resource Development Institute Tra Vinh University Tra Vinh87000 Viet Nam PhD program in Computer Science Tra Vinh University Tra Vinh87000 Viet Nam Facilities Management Department Tien Giang University Tien Giang84000 Viet Nam

ISBN: (纸本)9789819796120

Deep learning is revolutionizing the field of medical image segmentation. The U-shaped (Unet) model, with its encoder-decoder architecture and skip connections, has become the dominant architecture for this task. However, variations like Nested-Unet are necessary to address the challenge of adapting network size for datasets of varying scales. This study proposes a novel model based on a multilayer Unet architecture that leverages all output features within nodes of a Nested Unet network. We evaluate the proposed model on four key medical image datasets: electron microscopy (EM), nuclei, polyps (CVC-ClinicDB), and skin lesions. The model achieves impressive Dice scores: 94.08% for EM, 92.68% for nuclei, 87.20% for skin lesions, and 93.02% for the CVC-ClinicDB dataset. These outstanding results demonstrate the superior performance of our proposed model compared to recent advancements in the field. Remarkably, the model achieves this performance while maintaining a size that is half that of a traditional Unet model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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CIWARS: A Web Server for Antibiotic Resistance Surveillance Using Longitudinal Metagenomic Data

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Journal of Molecular Biology 2025年

作者： Emon, Muhit Islam Cheung, Yat Fei Stoll, James Rumi, Monjura Afrin Brown, Connor Choi, Joung Min Moumi, Nazifa Ahmed Ahmed, Shafayat Song, Haoqiu Sein, Justin Yao, Shunyu Khan, Ahmad Gupta, Suraj Kulkarni, Rutwik Butt, Ali Vikesland, Peter Pruden, Amy Zhang, Liqing Department of Computer Science Virginia Tech Blacksburg 24060 VA United States Fralin Life Science Institute Virginia Tech Blacksburg 24060 VA United States Department of Civil and Environmental Engineering Virginia Tech Blacksburg 24060 VA United States The Interdisciplinary PhD Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg 24060 VA United States

The rise of antibiotic resistance (AR) poses a substantial threat to human and animal health, food security, and economic stability. Wastewater-based surveillance (WBS) has emerged as a powerful strategy for population-level AR monitoring, providing valuable data to guide public health and policy decisions. Metagenomic sequencing is especially promising, as it can yield comprehensive profiles of antibiotic resistance genes (ARGs) and other genes relevant to AR in a single run. However, online analytical platforms to facilitate analysis of longitudinal metagenomic data are lacking. To address this, we introduce CyberInfrastructure for Waterborne Antibiotic Resistance Surveillance (CIWARS), a web server configured for characterizing key AR trends from longitudinal metagenomic WBS data. CIWARS offers comprehensive profiling of ARGs and taxonomic profiling of pathogen-associated bacterial taxonomic groups, identifies potential associations of ARGs with mobile genetic elements (MGEs) and pathogen-containing taxa, and assesses resistome risk based on the co-occurrence of ARGs, MGEs, and pathogen-like sequences. Additionally, it detects anomalous AR indicators over time, aiding in identifying potential events of concern, such as the emergence of resistant strains or outbreaks. Through interactive temporal data visualization, CIWARS enables AR monitoring and can serve as a tool to inform effective and timely interventions to mitigate the spread and transmission of AR. Here, CIWARS is demonstrated using longitudinal metagenomic data from a wastewater treatment plant (WWTP) influent and effluent, but it can be extended to any environment. CIWARS provides a valuable tool to support global efforts to combat the evolution and spread of AR, while also guiding agricultural and public health efforts aimed at optimizing antibiotic use. The web server is freely available at https://***/. © 2025 Elsevier Ltd

关键词： anomaly detection antibiotic resistance (AR) AR indicator profiling longitudinal metagenomics wastewater-based surveillance

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A data-driven approach to discover and quantify systemic lupus erythematosus etiological heterogeneity from electronic health records

arXiv

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arXiv 2025年

作者： Mota, Marco Barbero Still, John M. Gamboa, Jorge L. Strobl, Eric V. Stein, Charles M. Kawai, Vivian K. Lasko, Thomas A. Vanderbilt University Medical Center Department of Biomedical Informatics United States Vanderbilt University Medical Center Department of Medicine United States Vanderbilt University Medical Center Department of Psychiatry and Behavioral Sciences United States Vanderbilt University Medical Center Department of Computer Science United States Vanderbilt DBMI PhD program 2525 West End Ave NashvilleTN United States

Systemic lupus erythematosus (SLE) is a complex heterogeneous disease with many manifestational facets. We propose a data-driven approach to discover probabilistic independent sources from multimodal imperfect EHR data. These sources represent exogenous variables in the data generation process causal graph that estimate latent root causes of the presence of SLE in the health record. We objectively evaluated the sources against the original variables from which they were discovered by training supervised models to discriminate SLE from negative health records using a reduced set of labelled instances. We found 19 predictive sources with high clinical validity and whose EHR signatures define independent factors of SLE heterogeneity. Using the sources as input patient data representation enables models to provide with rich explanations that better capture the clinical reasons why a particular record is (not) an SLE case. Providers may be willing to trade patient-level interpretability for discrimination especially in challenging cases. © 2025, CC BY-NC-ND.

关键词： Electronic health record

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Learning by collaboration in intelligent autonomous systems

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作者： Ierache, Jorge García-Martínez, Ramón De Giusti, Armando Computer Science PhD Program La Plata National University Buenos Aires University Argentina

ISBN: (纸本)3642152856

Very few learning systems applied to problem solving have focused on learning operator definitions from the interaction with a completely unknown environment. Autonomous Intelligent Systems (AIS) deal with that issue by means of architectures where learning is achieved by establishing plans, executing those plans in the environment, analyzing the results of the execution, and combining new evidence with prior evidence. This paper proposes a selective mechanism of learning allowing an AIS to learn new operators by receiving them from another AIS in a higher stage in the Learning Life Cycle (LLC) with more cycles of interaction in the environment. The proposed collaboration mechanism also considers how to deal with theory ponderation (operators ponderation) and how to include the new operators (provided for) in the set of theories of the receiver AIS. The experimental results show how using collaboration-based learning among AIS provides a better percentage of successful plans, plus an improved convergence rate, than the individual AIS alone. © 2010 IFIP.

关键词： Problem solving

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Promoting active behaviours in schoolchildren using the socio-ecological model in the physical education class: study protocol of the ACTIBESE project

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BMC Pediatrics 2025年第1期25卷 1-14页

作者： Rodríguez-Rodríguez, Fernando Cristi-Montero, Carlos Zurita-Corvalán, Natalia Brand, Caroline Mota, Jorge Chillón, Palma Gaya, Anelise Reis Brazo-Sayavera, Javier Aguilar-Farias, Nicolás IRyS Group Physical Education School Pontificia Universidad Católica de Valparaíso Valparaíso Chile Laboratory for Integrative and Translational Research in Population Health (ITR) Research Center in Physical Activity Health and Leisure (CIAFEL) Faculty of Sports University of Porto (FADEUP) Porto Portugal Department of Physical Education and Sports Faculty of Sport Sciences Sport and Health University Research Institute (iMUDS) University of Granada Granada Spain Graduate Program in Human Movement Sciences Federal University of Rio Grande do Sul (UFRGS) RS Porto Alegre Brazil Department of Sports and Computer Science Universidad Pablo de Olavide (UPO) Seville 41013 Spain Department of Physical Education Sports and Recreation Universidad de La Frontera Temuco Chile PhD Program in Educational Sciences University of Granada Granada Spain

Background: The correlation between parental and child physical activity levels has been the subject of significant investigation. Existing research has illuminated this association, particularly emphasising its influence during childhood. However, as children transition into adolescence, this relationship appears to weaken. Despite the recognised importance of parental involvement in promoting physical activity among children, scant attention has been directed towards understanding effective strategies and interventions to bolster this relationship. Consequently, there exists a critical gap in the literature concerning actionable measures to enhance parent-child physical activity engagement during the pivotal stage of adolescence. Methods: The ACTIBESE project aims to assess and intervene in Chilean schoolchildren’s active behaviours by examining the influence of personal, interpersonal, and school factors. This study includes a cross-sectional and intervention study involving schools in the Valparaíso and Araucanía Regions, representing urban and rural areas. Participants, divided into children (8–11 years old) and adolescents (12–16 years old), will undergo a comprehensive evaluation, including sociodemographic characteristics, physical activity (PA) levels, parental and peer support, teaching styles of the teachers, and school environment characteristics. In the intervention study, a 5-month continuous training program for teachers will be implemented, focusing on improving teaching styles and enhancing teaching competencies related to physical education and health classes. The research will use mixed models, ANCOVA, and logistic regressions for data analysis, network analysis, exploratory factors analysis, and structural equation modelling. Discussion: Through innovative research methods, interventions involving schoolteachers, and a diverse geographical scope, this project aims to make significant contributions to both the scientific understanding of promoting

关键词： Exercise Health Intervention Physical activity Well-being

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An incremental approach for niching and building block detection via clustering

An incremental approach for niching and building block detec...

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7th International Conference on Intelligent Systems Design and Applications, ISDA'07

作者： Emmendorfer, Leonardo Ramos Pozo, Aurora Trinidad Ramirez Numerical Methods in Engineering PhD Program Federal University of Paraná Brazil Department of Computer Science Federal University of Paraná Brazil

ISBN: (纸本)0769529763

Diversity preservation has already been established as an important concern for evolutionary computation. Clustering techniques were, among others, successfully applied to this purpose. Another important aspect of the research on evolutionary computation is related to linkage learning - the detection of the problem structure avoiding disruption of building blocks when new individuals are generated. This paper presents a novel approach which is a new estimation of distribution algorithm (EDA) where clustering plays two roles: diversity preservation and linkage learning. Initial empirical investigations illustrate the behavior of the algorithm when solving two benchmark optimization problems. © 2007 IEEE.

关键词： Evolutionary algorithms

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Deriving processes of information mining based on semantic nets and frames

Deriving processes of information mining based on semantic n...

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27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014

作者： Martins, Sebastian Rodríguez, Darío García-Martínez, Ramón Information Systems Research Group National University of Lanus Argentina PhD Program on Computer Science National University of la Plata Argentina

ISBN: (纸本)9783319074665

There are information mining methodologies that emphasize the importance of planning for requirements elicitation along the entire project in an orderly, documented, consistent and traceable manner. However, given the characteristics of this type of project, the approach proposed by the classical requirements engineering is not applicable to the process of identifying the problem of information mining, nor allows to infer from the business domain modelling, the information mining process which solves it. This paper proposes an extension of semantic nets and frames to represent knowledge of the business domain, business problem and problem of information mining;and a methodology to derive the information mining process from the proposed knowledge representations is introduced. © 2014 Springer International Publishing Switzerland.

关键词： Requirements engineering

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Optimizing regional power production under thermal pollution constraints 7

Optimizing regional power production under thermal pollution...

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7th International Green and Sustainable Computing Conference, IGSC 2016

作者： Bald, Samuel Johnson, Matthew P. Rybalov, Levi PhD Program in Computer Science Graduate Center City University of New York United States Department of Mathematics and Computer Science Lehman College City University of New York United States

ISBN: (纸本)9781509051175

A majority of electricity generation in the US is produced by thermoelectric power plants which require a constant supply of water for cooling. Many of these plants eject large quantities of hot water that was used for cooling into an adjacent river - a phenomenon known as thermal pollution - causing harm to local ecosystems and aquatic life. Commonly, plants lie within interconnected river networks, whence thermal pollution from plants upstream is translated to plants dowstream, causing less-effective cooling, and decreases in efficiency. By default, plants are managed locally, and government regulations combating thermal pollution take the form of local river temperature constraints. We propose analyzing this situation regionally, seeking to balance the trade-off between power demand and required pollution minimization in a region. We first consider fractional variants of this problem where plants may operate at some fraction of their total capacity. We provide optimal poly-time algorithms for such cases. We show that the integer version of the problem - where plants are either fully on or off - is already NP-hard when the river network topology is a path graph. We provide a dynamic programming FPTAS in this case. We compare the results of our algorithms to baseline heuristics in simulation. © 2016 IEEE.

关键词： Cooling

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Using prosody to improve dependency parsing 10

Using prosody to improve dependency parsing

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10th International Conference on Speech Prosody 2020

作者： Ghaly, Hussein Mandel, Michael Linguistics PhD Program Graduate Center City University of New York United States Computer and Information Science Brooklyn College United States

The goal of the present study is to use prosodic information to improve automatic syntactic parsing of conversational speech in the Switchboard Corpus. To achieve this, an ensemble classifier, based on a Recurrent Neural Network, is developed to predict the parse with the highest Unlabelled Attachment Score (UAS) from the outputs of multiple dependency parsers, based on syntactic and prosodic features. The main syntactic features proposed, which we refer to as "dependency configurations," represent the relative dependency location of each of a pair of consecutive words. Empirical analysis indicates that configurations with a direct dependency between consecutive words are less likely to be associated with major prosodic breaks. Using syntactic features alone, the system achieved an improvement of 1.1% of UAS on the test set, above the best parser in the ensemble, while using syntactic features combined with prosodic features (pauses and normalized duration) led to a further improvement of 0.4%. Both empirical analysis of dependency configurations and parsing improvement suggest a relationship between prosody and direct dependency relationships between consecutive words. © 2020 International Speech Communications Association. All rights reserved.

关键词： Recurrent neural networks

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