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arXiv 2021年

作者： Liu, Hang Hu, Menghan Chen, Yuzhen Li, Qingli Zhai, Guangtao Yang, Simon X. Zhang, Xiao-Ping Yang, Xiaokang The Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University The Key Laboratory of Articial Intelligence Ministry of Education The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph The Department of Electrical Computer and Biomedical Engineering Ryerson University

For people who ardently love painting but unfortunately have visual impairments, holding a paintbrush to create a work is a very difficult task. People in this special group are eager to pick up the paintbrush, like Leonardo da Vinci, to create and make full use of their own talents. Therefore, to maximally bridge this gap, we propose a painting navigation system to assist blind people in painting and artistic creation. The proposed system is composed of cognitive system and guidance system. The system adopts drawing board positioning based on QR code, brush navigation based on target detection and bush real-time positioning. Meanwhile, this paper uses human-computer interaction on the basis of voice and a simple but efficient position information coding rule. In addition, we design a criterion to efficiently judge whether the brush reaches the target or not. According to the experimental results, the thermal curves extracted from the faces of testers show that it is relatively well accepted by blindfolded and even blind testers. With the prompt frequency of 1s, the painting navigation system performs best with the completion degree of 89% ± 8.37% and overflow degree of 347% ± 162.14%. Meanwhile, the excellent and good types of brush tip trajectory account for 74%, and the relative movement distance is 4.21 ± 2.51. This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands. In the future, we plan to deploy "Angle's Eyes" on the phone to make it more portable. The demo video of the proposed painting navigation system is available at: https://***/10.6084/***.9760004.v1. © 2021, CC BY.

关键词： Cognitive systems

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Ensemble ranking: An aggregation of multiple multicriteria methods and scenarios and its application to power generation planning

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Decision Analytics Journal 2024年 10卷

作者： Alves, Marcos Antonio Oliveira, Bruno Alberto Soares Guimarães, Frederico Gadelha Graduate Program in Electrical Engineering Av. Antônio Carlos 6627 MG Belo Horizonte 31270-901 Brazil FITec - Technological Innovations Av. Cristóvão Colombo 485 Funcionários MG Belo Horizonte 30140-150 Brazil Department of Computer Science Rua Reitor Píres Albuquerque ICEx MG Belo Horizonte 31270-901 Brazil

Evaluating maintenance plans for power generation is a critical task managed by the National System Operator, as it is directly related to criteria such as operational cost, rationing, and availability of natural resources. This study identifies the most suitable maintenance schedule between uncertainties related to solution ranking methods and future scenarios. We investigated the performance of various multicriteria decision-making methods, including the Analytic Hierarchy Process (AHP), TODIM ((an acronym in Portuguese for Interactive Multicriteria decision-making), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), and Weighted Aggregated Sum Product ASsessment (WASPAS), in prioritizing maintenance plans across three scenarios. These included a scenario derived from an energy generation problem and two others based on variations in hydrology and energy demand parameters. The results analyze and discuss the similarities and differences in the rankings. Due to the lack of consensus among the methods regarding the optimal maintenance plan, we propose an ensemble ranking that considers an important factor for both the method and the scenario. The solution from the ensemble ranking, compared to the lowest-cost solution obtained in the optimization process, showed a slight cost increase of 0.32% and a 9.34% deviation from the base maintenance plan, yet it can deal with different uncertainties. The findings of this study can provide useful and robust information to energy stakeholders and serve as a reference for energy policy. © 2024 The Authors

关键词： Generation maintenance scheduling problems Hydrothermal dispatch Multicriteria decision-making Power generation planning Robust decision-making Uncertainty scenarios

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Integrating LLM, EEG, and Eye-Tracking Biomarker Analysis for Word-Level Neural State Classification in Semantic Inference Reading Comprehension

arXiv

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arXiv 2023年

作者： Zhang, Yuhong Li, Qin Nahata, Sujal Jamal, Tasnia Cheng, Shih-Kuen Cauwenberghs, Gert Jung, Tzyy-Ping The School of Engineering Brown University ProvidenceRI02912 United States Institute for Neural Computation University of California San Diego La Jolla CA92093 United States Department of Radiology and Biomedical Imaging Yale University New HavenCT06520 United States The Department of Bioengineering University of California Los Angeles Los AngelesCA90095 United States The Department of Computer Science and Engineering University of California San Diego La Jolla CA92093 United States The Department of Electrical and Computer Engineering University of California San Diego La Jolla CA92093 United States The Institute of Cognitive Neuroscience National Central University Taoyuan32001 Taiwan The Department of Bioengineering Institute for Neural Computation University of California San Diego La Jolla CA92093 United States The Institute for Neural Computation University of California San Diego La Jolla CA92093 United States

With the recent proliferation of large language models (LLMs), such as Generative Pre-trained Transformers (GPT), there has been a significant shift in exploring human and machine comprehension of semantic language meaning. This shift calls for interdisciplinary research that bridges cognitive science and natural language processing (NLP). This pilot study aims to provide insights into individuals’ neural states during a semantic relation reading-comprehension task. We propose jointly analyzing LLMs, eye-gaze, and electroencephalographic (EEG) data to study how the brain processes words with varying degrees of relevance to a keyword during reading. We also use a feature engineering approach to improve the fixation-related EEG data classification while participants read words with high versus low relevance to the keyword. The best validation accuracy in this word-level classification is over 60% across 12 subjects. Words of high relevance to the inference keyword had significantly more eye fixations per word: 1.0584 compared to 0.6576 when excluding no-fixation words, and 1.5126 compared to 1.4026 when including them. This study represents the first attempt to classify brain states at a word level using LLM knowledge. It provides valuable insights into human cognitive abilities and the realm of Artificial General Intelligence (AGI), and offers guidance for developing potential reading-assisted technologies. Copyright © 2023, The Authors. All rights reserved.

关键词： Computational linguistics

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Analytical Estimation of Out-of-plane Strain in Ultrasound Elastography to Improve Axial and Lateral Displacement Fields*

Analytical Estimation of Out-of-plane Strain in Ultrasound E...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Niusha Kheirkhah Ali Sadeghi-Naini Abbas Samani School of Biomedical Engineering Western University London Canada Department of Electrical Engineering and Computer Science York University Toronto Canada Departments of Medical Biophysics and Electrical and Computer Engineering Western University London Canada

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Many types of cancers are associated with changes in tissue mechanical properties. This has led to the development of elastography as a clinically viable method where tissue mechanical properties are mapped and visualized for cancer detection and staging. In quasi-static ultrasound elastography, a mechanical stimulation is applied to the tissue using ultrasound probe. Using ultrasound radiofrequency (RF) data acquired before and after the stimulation, the tissue displacement field can be estimated. Elasticity image reconstruction algorithms use this displacement data to generate images of the tissue elasticity properties. The accuracy of the generated elasticity images depends highly on the accuracy of the tissue displacement estimation. Tissue incompressibility can be used as a constraint to improve the estimation of axial and, more importantly, the lateral displacements in 2D ultrasound elastography. Especially in clinical applications, this requires accurate estimation of the out-of-plane strain. Here, we propose a method for providing an accurate estimate of the out-of-plane strain which is incorporated in the incompressibility equation to improve the axial and lateral displacements estimation before elastography image reconstruction. The method was validated using in silico and tissue mimicking phantom studies, leading to significant improvement in the estimated displacement.

关键词： Mathematical model Strain Breast Estimation Elastography Ultrasonic imaging Probes

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Alternate inter-digit finger tapping pattern resembles rudimentary finger grasping pattern

Biomedical Engineering Advances

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biomedical engineering Advances 2025年 9卷

作者： Stefan Manoharan June Seung Lee Hangue Park Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA MetaBioHealth Sungkyunkwan University Suwon South Korea Department of Biomedical Engineering Sungkyunkwan University Suwon South Korea Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University Suwon South Korea

Neurotraumas often result in loss of finger grasping ability, thereby deteriorating quality of life. To develop effective rehabilitation method for finger grasping, objective evaluation metrics of grasping capability is a basic requirement. However, current evaluation methods for grasping confront challenges with their non-rhythmic nature and limited sample size, resulting in low statistical power and high variability. Finger tapping may shed light on this issue, based on its rhythmic nature and a common underlying mechanism between rhythmic finger tapping and rudimentary finger grasping. In this study, we investigated “phase difference” at inter-digit finger tapping, which indicates a deviation from the temporal symmetry of inter-digit tapping and potentially reflects a rudimentary finger grasping pattern. This was accomplished by analysing the metacarpophalangeal (MCP) angle of subjects’ fingers, measured by an infrared hand-motion sensor, during finger-tapping tasks. Subjects performed alternate or simultaneous rhythmic tapping tasks between two adjacent fingers among the thumb, index, and middle fingers while the MCP angle for the fingers was measured. Using the oscillating nature of the MCP angles for each finger, we established phase difference as a metric to describe relative interdigital motion. We identified congruency in phase difference between the alternate inter-digit tapping pattern and the rudimentary grasping pattern. Experimental results with phase analysis suggest that alternate inter-digit tapping, which is a rhythmic and intuitive task, is strongly correlated with the rudimentary grasping in kinematics, while the simultaneous tapping is not. Accordingly, we predict potential applications of alternate inter-digit finger tapping and its metrics in grasping diagnostics and rehabilitation monitoring.

关键词： Finger tapping Grasping pattern Grasping diagnostics Rehabilitation

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MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

arXiv

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arXiv 2025年

作者： Nielsen, Aleksandra Weronika Manoochehri, Hafez Eslami Zhong, Hua Panwar, Vandana Jarmale, Vipul Jasti, Jay Nourani, Mehrdad Rakheja, Dinesh Brugarolas, James Kapur, Payal Rajaram, Satwik Lyda Hill Department of Bioinformatics University of Texas Southwestern Medical Center DallasTX United States Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX United States Department of Pathology University of Texas Southwestern Medical Center DallasTX United States Kidney Cancer Program Simmons Comprehensive Cancer Center University of Texas Southwestern Medical Center DallasTX United States University of Texas Southwestern Medical Center DallasTX United States Department of Urology University of Texas Southwestern Medical Center at Dallas DallasTX United States

The ability of tumors to evolve and adapt by developing subclones in different genetic and epigenetic states is a major challenge in oncology. Traditional tools like multi-regional sequencing used to study tumor evolution and the resultant intra-tumor heterogeneity (ITH) are often impractical because of their resource-intensiveness and limited scalability. Here, we present MorphoITH, a novel framework that leverages histopathology slides to deconvolve molecular ITH through tissue morphology. MorphoITH integrates a self-supervised deep learning similarity measure to capture phenotypic variation across multiple dimensions (cytology, architecture, and microenvironment) with rigorous methods to eliminate spurious sources of variation. Using a prototype of ITH, clear cell renal cell carcinoma (ccRCC), we show that MorphoITH captures clinically-significant biological features, such as vascular architecture and nuclear grades. Furthermore, we find that MorphoITH recognizes differential biological states corresponding to subclonal changes in key driver genes (BAP1/PBRM1/SETD2). Finally, by applying MorphoITH to a multi-regional sequencing experiment, we postulate evolutionary trajectories that largely recapitulate genetic evolution. In summary, MorphoITH provides a scalable phenotypic lens that bridges the gap between histopathology and genomics, advancing precision oncology. © 2025, CC BY-NC-ND.

关键词： Tumors

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Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity

Feasibility of Inferring Spatial Transcriptomics from Single...

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18th International Joint Conference on biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Fatemi, Michael Y. Lu, Yunrui Azher, Zarif L. Sharma, Cyril Feng, Eric Diallo, Alos B. Srinivasan, Gokul Rosner, Grace M. Pointer, Kelli B. Christensen, Brock C. Salas, Lucas A. Tsongalis, Gregory J. Palisoul, Scott M. Perreard, Laurent Kolling, Fred W. Vaickus, Louis J. Levy, Joshua J. University of Virginia CharlottesvilleVA United States Emerging Diagnostic and Investigative Technologies Department of Pathology and Laboratory Medicine Dartmouth Health LebanonNH United States Department of Computer Science Purdue University West LafayetteIN United States Thomas Jefferson High School for Science and Technology AlexandriaVA United States Department of Epidemiology Dartmouth College Geisel School of Medicine HanoverNH United States Program in Quantitative Biomedical Sciences Dartmouth College Geisel School of Medicine HanoverNH United States Department of Medicine Section of Radiology Oncology Dartmouth Health LebanonNH United States Department of Molecular and Cell Biology Dartmouth College Geisel School of Medicine HanoverNH United States Genomics Shared Resource Dartmouth Cancer Center LebanonNH United States Department of Dermatology Dartmouth Health LebanonNH United States Department of Pathology and Laboratory Medicine Cedars Sinai Medical Center Los AngelesCA United States Department of Computational Biomedicine Cedars Sinai Medical Center Los AngelesCA United States Division of Biology and Biological Engineering California Institute of Technology PasadenaCA United States

Spatial transcriptomics (ST) enables studying spatial organization of gene expression within tissues, offering insights into the molecular diversity of tumors. Recent methods have demonstrated the capability to disaggregate this information at subspot resolution by leveraging both expression and histological patterns. Elucidating such information from histology alone presents a significant challenge, but if solved can enable spatial molecular analysis at cellular resolution even where ST data is not available, reducing study costs. This study explores integrating single-cell histological and transcriptomic data to infer spatial mRNA expression patterns in colorectal cancer whole slide images. A cell-graph neural network algorithm was developed to align histological information extracted from detected cells with single cell RNA, facilitating the analysis of cellular groupings and gene relationships. We demonstrate that single-cell transcriptional heterogeneity within a spot could be predicted from histological markers extracted from cells detected within it. Our model exhibited proficiency in delineating overarching gene expression patterns across whole-slide images. This approach compared favorably to traditional computer vision methods which did not incorporate single cell expression during the model training. This innovative approach augments the resolution of spatial molecular assays utilizing histology as sole input through co-mapping of histological and transcriptomic datasets at the single-cell level. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Tumors

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Explainable semantic space by grounding language to vision with cross-modal contrastive learning

arXiv

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arXiv 2021年

作者： Zhang, Yizhen Choi, Minkyu Han, Kuan Liu, Zhongming Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Department of Neurological Surgery University of California San Francisco San FranciscoCA94143 United States Department of Biomedical Engineering University of Michigan Ann ArborMI48109 United States

In natural language processing, most models try to learn semantic representations merely from texts. The learned representations encode the "distributional semantics" but fail to connect to any knowledge about the physical world. In contrast, humans learn language by grounding concepts in perception and action and the brain encodes "grounded semantics" for cognition. Inspired by this notion and recent work in vision-language learning, we design a two-stream model for grounding language learning in vision. The model includes a VGG-based visual stream and a Bert-based language stream. The two streams merge into a joint representational space. Through cross-modal contrastive learning, the model first learns to align visual and language representations with the MS COCO dataset. The model further learns to retrieve visual objects with language queries through a cross-modal attention module and to infer the visual relations between the retrieved objects through a bilinear operator with the Visual Genome dataset. After training, the model's language stream is a stand-alone language model capable of embedding concepts in a visually grounded semantic space. This semantic space manifests principal dimensions explainable with human intuition and neurobiological knowledge. Word embeddings in this semantic space are predictive of human-defined norms of semantic features and are segregated into perceptually distinctive clusters. Furthermore, the visually grounded language model also enables compositional language understanding based on visual knowledge and multimodal image search with queries based on images, texts, or their combinations. © 2021, CC BY.

关键词： Embeddings

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Dielectric spectroscopy of liver mixture model for millimetre-wave imaging

Dielectric spectroscopy of liver mixture model for millimetr...

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2019 European Microwave Conference in Central Europe, EuMCE 2019

作者： Farhat, Iman Bonello, Julian Farrugia, Lourdes Di Meo, Simona Pollacco, Daphne-Anne Sammut, Charles Department of Physics University of Malta Malta Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9782874870675

In this paper, we present a technique to mimic the dielectric properties for liver at 0.2-50 GHz based on the effective medium theory. A mathematical model based on Bruggeman mixture equation is presented to describe the dielectric properties of liver. The dielectric response of the mixture system considers two dielectric media, referred to as the host and inclusion media. In fact, proposed mixture solution consists of concentrations of Bovine Serum Albumin (BSA) in PBS solution, synthesized to mimic in-vivo liver tissue using physiological saline solutions coupled with protein additions. Generally, when testing an electromagnetic medical device in prototype phase, such solutions are required to assess the feasibility of the technology. The dielectric properties as measured experimentally are correlated to the calculated effective permittivity using Bruggemann equation. Results were then analysed, implying that such solutions can be utilised in the construction of human body phantoms for narrowband and ultra-wideband microwave devices for both millimeter-wave imaging and applications in hyperthermia and other ablation modalities. The frequency range studied could also lead to realistic phantoms for dosimetry studies related to human safety concerns. Hence, a stratified liver mixture model has been proposed which can be used as a theoretical basis for taking further steps in liver cancer research. © 2019 EuMCE.

关键词： Phantoms

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Layer-dependent optically induced spin polarization in InSe

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Physical Review B 2023年第11期107卷 115304-115304页

作者： Jovan Nelson Teodor K. Stanev Dmitry Lebedev Trevor LaMountain J. Tyler Gish Hongfei Zeng Hyeondeok Shin Olle Heinonen Kenji Watanabe Takashi Taniguchi Mark C. Hersam Nathaniel P. Stern Applied Physics Program Northwestern University Evanston Illinois 60208 USA Department of Physics and Astronomy Northwestern University Evanston Illinois 60208 USA Department of Material Science and Engineering Northwestern University Evanston Illinois 60208 USA Computational Science Division Argonne National Laboratory Lemont Illinois 60439 USA Material Science Division Argonne National Laboratory Lemont Illinois 60439 USA Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Department of Chemistry Northwestern University Evanston Illinois 60208 USA Department of Electrical Engineering and Computer Science Northwestern University Evanston Illinois 60208 USA

Optical control of spin in semiconductors has been pioneered using nanostructures of III-V and II-VI semiconductors, but the emergence of two-dimensional van der Waals materials offers an alternative low-dimensional platform for spintronic phenomena. Indium selenide (InSe), a group-III monochalcogenide van der Waals material, has shown promise for optoelectronics due to its high electron mobility, tunable direct band gap, and quantum transport. In addition to these confirmed properties, there are predictions of spin-dependent optical selection rules, suggesting the potential for all-optical excitation and control of spin in a two-dimensional layered material. Despite these predictions, layer-dependent optical spin phenomena in InSe have yet to be explored. Here, we present measurements of layer-dependent optical spin dynamics in few-layer and bulk InSe. Polarized photoluminescence reveals layer-dependent optical orientation of spin, thereby demonstrating the optical selection rules in few-layer InSe. Spin dynamics are also studied in many-layer InSe using time-resolved Kerr rotation spectroscopy. By applying out-of-plane and in-plane static magnetic fields for polarized emission measurements and Kerr measurements, respectively, the g factor for InSe was extracted. Further investigations are done by calculating precession values using a k·p model, which is supported by ab initio density functional theory. Comparison of predicted precession rates with experimental measurements highlights the importance of excitonic effects in InSe for understanding spin dynamics. Optical orientation of spin is an important prerequisite for optospintronic phenomena and devices, and these first demonstrations of layer-dependent optical excitation of spins in InSe lay the foundation for combining layer-dependent spin properties with advantageous electronic properties found in this material.

关键词： Magneto-optics Spin dynamics Chalcogenides Layered semiconductors Van der Waals systems Density functional theory Kerr effect Photoluminescence k dot p method

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