15 research outputs found
DISCRETE GREEN’S FUNCTION BASED PREDICTIVE FRAMEWORK FOR TRIPLY PERIODIC MINIMAL SURFACES
No full text74 pagesTriply Periodic Minimal Surfaces (TPMS) are advanced porous geometries known for their high surface area, thermal efficiency, and tunable transport properties, making them ideal for thermal applications such as heat exchangers, energy storage, and catalytic systems. Accurate prediction of heat transfer in TPMS is essential for design optimization, as traditional methods like Computational Fluid Dynamics (CFD) are computationally expensive and impractical for iterative design. The Discrete Green’s Function (DGF) method, known for its computational efficiency through linear superposition, has been primarily applied to simpler geometries due to its dependence on analytical solutions or CFD-derived metrics. This work presents a novel framework that integrates DGF with Signed Distance Function (SDF)-based geometry representation, enabling mesh-free and rapid heat transfer evaluation in TPMS. By voxelizing the SDF, extracting geometric properties slice-wise, and constructing a convection-based DGF matrix via local temperature perturbations, the method allows efficient computation of heat flux and convective coefficients. This SDF-driven DGF approach retains physical accuracy while eliminating CFD dependence, offering a scalable and robust solution for rapid thermal analysis and optimization of complex porous media
Identifying Novel Emotions and Wellbeing of Horses from Videos Through Unsupervised Learning
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Open AccessArticle
Identifying Novel Emotions and Wellbeing of Horses from Videos Through Unsupervised Learning
by Aarya Bhave 1ORCID,Emily Kieson 2ORCID,Alina Hafner 3 andPeter A. Gloor 1,*ORCID
1
Massachusetts Institute of Technology, System Design & Management, Cambridge, MA 02142, USA
2
Equine International, Cambridge CB22 5LD, UK
3
TUM School of Computation, Information and Technology, Technical University of Munich, Arcisstraße 21, 80333 Munich, Germany
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(3), 859; https://doi.org/10.3390/s25030859
Submission received: 5 January 2025 / Revised: 22 January 2025 / Accepted: 30 January 2025 / Published: 31 January 2025
(This article belongs to the Special Issue Emotion Recognition and Cognitive Behavior Analysis Based on Sensors)
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Abstract
This research applies unsupervised learning on a large original dataset of horses in the wild to identify previously unidentified horse emotions. We construct a novel, high-quality, diverse dataset of 3929 images consisting of five wild horse breeds worldwide at different geographical locations. We base our analysis on the seven Panksepp emotions of mammals “Exploring”, “Sadness”, “Playing”, “Rage”, “Fear”, “Affectionate” and “Lust”, along with one additional emotion “Pain” which has been shown to be highly relevant for horses. We apply the contrastive learning framework MoCo (Momentum Contrast for Unsupervised Visual Representation Learning) on our dataset to predict the seven Panksepp emotions and “Pain” using unsupervised learning. We significantly modify the MoCo framework, building a custom downstream classifier network that connects with a frozen CNN encoder that is pretrained using MoCo. Our method allows the encoder network to learn similarities and differences within image groups on its own without labels. The clusters thus formed are indicative of deeper nuances and complexities within a horse’s mood, which can possibly hint towards the existence of novel and complex equine emotions
Poems on Home, Family, and the Self
No full textabstract: This collection entitled “Poems on Home, Family, and the Self� is about the author’s role as a daughter to immigrant parents, who is finding her drive, and understanding where she comes from and how she will use that to find her purpose. The poems in this collection touch upon the author’s upbringing in Northern California, her transitioning relationship with her parents and her brother, as well as her experiences relative to her growth in Arizona. These pieces are greatly inspired by author Arundhati Roy and poet Li-Young Li. Specifically, the author is influenced by Li-Young Li’s approach to poetry – his commentary and storytelling of his life and his parents are objective, observatory, and allow the readers to make opinions for themselves. In this collection, the author aims to make statements about her family and upbringing and show the readers her new understanding of life and her ambitions. (abstract
Normal-guided Detail-Preserving Neural Implicit Functions for High-Fidelity 3D Surface Reconstruction
No full textNeural implicit representations have emerged as a powerful paradigm for 3D
reconstruction. However, despite their success, existing methods fail to
capture fine geometric details and thin structures, especially in scenarios
where only sparse RGB views of the objects of interest are available. We
hypothesize that current methods for learning neural implicit representations
from RGB or RGBD images produce 3D surfaces with missing parts and details
because they only rely on 0-order differential properties, i.e. the 3D surface
points and their projections, as supervisory signals. Such properties, however,
do not capture the local 3D geometry around the points and also ignore the
interactions between points. This paper demonstrates that training neural
representations with first-order differential properties, i.e. surface normals,
leads to highly accurate 3D surface reconstruction even in situations where
only as few as two RGB (front and back) images are available. Given multiview
RGB images of an object of interest, we first compute the approximate surface
normals in the image space using the gradient of the depth maps produced using
an off-the-shelf monocular depth estimator such as Depth Anything model. An
implicit surface regressor is then trained using a loss function that enforces
the first-order differential properties of the regressed surface to match those
estimated from Depth Anything. Our extensive experiments on a wide range of
real and synthetic datasets show that the proposed method achieves an
unprecedented level of reconstruction accuracy even when using as few as two
RGB views. The detailed ablation study also demonstrates that normal-based
supervision plays a key role in this significant improvement in performance,
enabling the 3D reconstruction of intricate geometric details and thin
structures that were previously challenging to capture.Comment: Original version. Project page with images and code:
https://sn-nir.github.io
Comparative Evaluation of Predictive Models on Kidney, Lung Cancer and Heart Disease
No full textThis study supports advances in machine learning to improve early detection and treatment planning for lung cancer, cardiovascular disease, and kidney disease. We compare traditional models such as decision trees and logistic regression with complex techniques such as support vector machines, random forests, and KNN and evaluate them on publicly available data. This hybrid approach uses random forest and decision tree classifiers, leveraging adaptive learning to improve model accuracy. Results showed high prediction accuracy for kidney disease and lung cancer , while prediction accuracy for heart disease was average . This difference indicates the need for better work and more information. Future studies will focus on improving cardiovascular models, addressing data uncertainty, and integrating predictive models into clinical practice to support early diagnosis and personalized treatment to improve patient outcomes. This study demonstrates the potential for machine learning to have a major impact on diagnosis and patient management
Biology Poster Session
No full textAssessing the functional consequences of the rapid evolution of an essential DNA binding proteinFaculty Mentor: Geoff Findlay Michele Oldrati \u2725 Sarah Obrycki \u2726 Ashley Zilora \u2726
Role of the 3\u27 untranslated region in the post-transcriptional regulation of a newly evolved spermatogenesis geneFaculty Mentor: Geoff Findlay Junyi Wu \u2726 Rosalyn Pantoja-Ramirez \u2727 Emma Murphy \u2726 Biounce Casildo Ramirez \u2727
The Lingering Effects of the Asian Longhorned Beetle: Impact on the Changing Composition of a New England Campus ArboretumFaculty Mentor: Kelly Wolfe-Bellin Elizabeth Silver \u2726 Russell Cleary \u2726
Discovery of unknown larval stage of Pseudanophthalmus cave beetles using DNA barcodingFaculty Mentor: Karen Ann Ober Juliette Peel \u2726
Determining the impacts of resource acquisition mode on wound recovery in Astrangia poculataFaculty Mentor: Justin McAlister Emma Min \u2725 Jane Doyle \u2725
Acute temporal exposure to tire particle leachate in larvae of the sea urchin, Arbacia punctulataFaculty Mentor: Justin McAlister Luke Cuypers \u2725 Emma Service \u2726
Investigating the Interplay Between Glycogen Storage, Apoptosis, & Fertility Decline in C. elegans on a High-Glucose DietFaculty Mentor: Michelle Mondoux Khushi Patel \u2725
Identifying proteins that regulate apoptosis and are required to decrease fertility in C. elegans on a high-glucose dietFaculty Mentor: Michelle Mondoux Ava Navarro \u2725
Regulation of the Decrease in Fertility and Increase in Apoptosis in C. elegans Fed a High-Glucose DietFaculty Mentor: Michelle Mondoux Matthew DeLucia \u2725
Investigating the Effects of Grape Juice on Protein Aggregation and Mobility in a C. elegans Model of Huntington\u27s DiseaseFaculty Mentor: Michelle Mondoux Amelia Kratzer \u2725 Stephen McGovern \u2726 Nachelle Duque \u2725 Dana Ansah \u2727Alexa Rodriguez Villatoro \u2728
An Uninvited Guest: An Analysis of Late-Summer Cyanobacteria Dynamics in Owasco Lake, New YorkFaculty Mentor: William Sobczak Fiona McCarthy \u2725
Drought and Cold Stress on Eastern Hemlock Stands in Worcester County with Hemlock Woolly Adelgid InfestationFaculty Mentor: William Sobczak Mattison Albano \u2725
Balancing recreation and restoration: Adaptive management plan for stocking “Nutrient Bomb” trout in the Quinapoxet River during dam removal and drought in Fall 2024Faculty Mentor: William Sobczak Carter Titus \u2725 Arion Kennedy \u2725
Urban stream hyporheic zones provide macroinvetebrate refugia during a severe drought (Fall 2024)Faculty Mentor: William Sobczak Jackson Harris \u2725 Leonardo Cruz \u2725
Optimizing Cocoa Fermentation: The Impact of Yeast Starter Cultures on Microbial Diversity and Flavor DevelopmentFaculty Mentor: William Sobczak Jackson Harris \u2725
Breathing Through the Ages: Investigating Wnt10A and a-SMA Expression in Lung-Resident Mesenchymal Stem CellsFaculty Mentor: Julia Paxson Eric Carlson \u2725 Emily Bubonovich \u2725
Young Again? Examining the Effects of Substrate Stiffness On Aging Lung-Resident Mesenchymal Stem CellsFaculty Mentor: Julia Paxson Heather Paglia \u2725 Gianna Garifo-McPartland \u2725
Transcriptomic Analysis of Differentially Regulated Genes in Canine Lung Mesenchymal Stem Cells: Insights into Functional DifferencesFaculty Mentor: Julia Paxson Amanda Grace Wambui \u2725 Latoya Okundaye \u2725
Exploring the Role of Stromal Fibroblasts in Mammary Tumor Development Using a Disease-on-a-Chip DeviceFaculty Mentor: Rob Bellin Carolyn Calegari \u2725 Ashley Giorgio \u2726 Abbey Brown \u2727 Alina Doolan \u2728
Investigating the functional evolution of combinatorial p53 post-translational modificationsFaculty Mentor: Dan LuBrianna Fountain \u2725
Investigating a Hypercatalytic Variant of the anti-HIV protein, APOBEC3G (A3G)Faculty Mentor: Ann Sheehy Adam Zivny \u2725 Henry Argueta \u2726
Concordance between assays examining the catalytic activity of APOBEC3G, an anti-HIV proteinFaculty Mentor: Ann Sheehy Iris Diaz-Achilla \u2725 Michael Clarke \u2725
Impact of APOBEC3G, an anti-HIV protein, on Cellular ProliferationFaculty Mentor: Ann Sheehy Kim Nguyen \u2725 Josel Perez \u2726
Examination of the enhanced anti-HIV activity of F119F a clinically-important variant of APOBEC3GFaculty Mentor: Ann Sheehy Aarya Rumde \u2725 Katherine Laraia \u2726
Investigation of the HIV suppression of APOBEC3G F119F, a clinically-important variantFaculty Mentor: Ann Sheehy Derek Desrosiers
How does tooth arrangement affect crushing ability?Faculty Mentor: Stephanie Crofts Ahana Nagarkatti \u2725
How does defensive armor coverage vary with environment in Gasterosteus aculeatus?Faculty Mentor: Stephanie Crofts Kyra Khrsigara \u2725
Glial knockdown of the Drosophila ion transporter Ncc69 during development modulates adult seizure susceptibilityFaculty Mentor: Alexis Hill Marcus Williams \u2725 EJ Murphy \u2726
Using Fluorescence Microscopy to Measure Germline Apoptosis in C. elegans Faculty Mentor: Michelle Mondoux Mathew MacDonald \u272
COVID-19 Associated Mucormycosis::A Review of an Emergent Epidemic Fungal Infection in 3 Era of COVID-19 Pandemic
No full textAt a time when the COVID-19’s second wave is still picking up in countries like India, a number of reports describe the potential association with rise in the number of cases of mucormycosis, commonly known as the black fungus. This fungal infection has been around for centuries and affects those people whose immunity has been compromised due to severe health conditions. In this article, we provide a detailed overview of mucormycosis and discuss how COVID-19 could have caused a sudden spike in an otherwise rare disease in countries like India. The article discusses the various symptoms of the disease, class of people most vulnerable to this infection, preventive measures to avoid the disease, and various treatments that exist in clinical practice and research to manage the disease
Optimizing MASLD trial recruitment: LiverPRO vs. FIB-4 in reducing false positives and unnecessary biopsies
No full texttardis-sn/tardis: TARDIS v2023.10.20
No full text<p>This release has been created automatically by the TARDIS continuous delivery pipeline.</p>
<p>A complete list of changes for this release is available at <a href="https://github.com/tardis-sn/tardis/blob/master/CHANGELOG.md">CHANGELOG.md</a>.</p>
