cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Capstone Project Final Report : Recycling and Injection Molding of Aeronautical Post-Consumer Low Density Polyethylene
Creators: name: Chauhan, Ailish
name: Cosovic, Teodora
name: Hamid, Shahil
name: Kapur, Arnav
name: Khattar, Anshul
name: Xu, Chuanhao
Publisher: name: The University of British Columbia
Year: 2023

description: With a wave of technological advancements being made, World View is a revolutionary contributor. With their new cutting-edge technology, the common man can experience near-space tourism. This is achieved by raising a capsule with the help of low-density polyethylene (LDPE) balloons attached using Dyneema rope. To ensure a sustainable step towards the future, World View aims to recycle the single-use LDPE balloon films and Dyneema. However, the short timeline of this project suggests recycling Dyneema will not be feasible due to lack of resources and infrastructure. To increase World View's sustainable contribution to the environment, they hope to build a greenhouse dome entirely made of the recycled materials initially used for the flight, in this case, the LDPE and Dyneema rope (UHMWPE). An experimental study is to be conducted to repurpose the single use plastic into a product through the process of injection molding. The whole cycle involves creating recycled LDPE pellets, designing and creating a part mold and manufacturing the part through injection molding. This report shows the further investigation of the scope and summary of the Capstone project proposed by World View.
Maps and changes in time representation
Creators: name: Kraak, Menno-Jan
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Genetics
subject: FOS: Biological sciences
subject: Neuroscience
subject: Evolutionary Biology
subject: Environmental Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Cancer
subject: Science Policy
subject: Plant Biology
subject: Computational Biology

description: What are the options for mapping changes in geo-temporal data? The traditional cartographic design toolbox still has much to offer. The typical map types suitable for these data are still valid. In recent decades, the possibilities offered by online functionality in interactive environments and the availability of streaming data have had the greatest impact.
Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification
Creators: name: Li, Yu-Yang
name: Bai, Yu
name: Wang, Cunshi
name: Qu, Mengwei
name: Lu, Ziteng
name: Soria, Roberto
name: Liu, Jifeng
Publisher: name: arXiv
Year: 2024
Subjects: subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: Computation and Language (cs.CL)
subject: Machine Learning (cs.LG)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processed to extract astronomical patterns and information. In this study, we present a comprehensive evaluation of deep-learning and large language model (LLM) based models for the automatic classification of variable star light curves, based on large datasets from the Kepler and K2 missions. Special emphasis is placed on Cepheids, RR Lyrae, and eclipsing binaries, examining the influence of observational cadence and phase distribution on classification precision. Employing AutoDL optimization, we achieve striking performance with the 1D-Convolution+BiLSTM architecture and the Swin Transformer, hitting accuracies of 94\% and 99\% correspondingly, with the latter demonstrating a notable 83\% accuracy in discerning the elusive Type II Cepheids-comprising merely 0.02\% of the total dataset.We unveil StarWhisper LightCurve (LC), an innovative Series comprising three LLM-based models: LLM, multimodal large language model (MLLM), and Large Audio Language Model (LALM). Each model is fine-tuned with strategic prompt engineering and customized training methods to explore the emergent abilities of these models for astronomical data. Remarkably, StarWhisper LC Series exhibit high accuracies around 90\%, significantly reducing the need for explicit feature engineering, thereby paving the way for streamlined parallel data processing and the progression of multifaceted multimodal models in astronomical applications. The study furnishes two detailed catalogs illustrating the impacts of phase and sampling intervals on deep learning classification accuracy, showing that a substantial decrease of up to 14\% in observation duration and 21\% in sampling points can be realized without compromising accuracy by more than 10\%.
description: 35 pages, 20 figures
Polarization and kinematic properties of the splitting functions $q\to W^\pm +q'$ and $q\to Z^0 +q$
Creators: name: Bagdatova, Alsu G.
name: Baranov, Sergey P.
Publisher: name: arXiv
Year: 2024
Subjects: subject: High Energy Physics - Phenomenology (hep-ph)
subject: FOS: Physical sciences

description: We consider the processes $g\to W{+}\,q'$ and $q\to Z{+}\,q$ and derive the respective splitting functions as functions of two kinematic variables: the longitudinal momentum fraction $z$ and transverse momentum $p_T$ of the produced bosons with respect to the parent quark. We take into account kinematic (phase space) restrictions connected with nonzero masses of the gauge bosons and with limited initial energy. We separately consider three different polarization states of the bosons.
Lattice Surgery for Dummies
Creators: name: Chatterjee, Avimita
name: Das, Subrata
name: Ghosh, Swaroop
Publisher: name: arXiv
Year: 2024
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum error correction (QEC) plays a crucial role in correcting noise and paving the way for fault-tolerant quantum computing. This field has seen significant advancements, with new quantum error correction codes emerging regularly to address errors effectively. Among these, topological codes, particularly surface codes, stand out for their low error thresholds and feasibility for implementation in large-scale quantum computers. However, these codes are restricted to encoding a single qubit. Lattice surgery is crucial for enabling interactions among multiple encoded qubits or between the lattices of a surface code, ensuring that its sophisticated error-correcting features are maintained without significantly increasing the operational overhead. Lattice surgery is pivotal for scaling QECCs across more extensive quantum systems. Despite its critical importance, comprehending lattice surgery is challenging due to its inherent complexity, demanding a deep understanding of intricate quantum physics and mathematical concepts. This paper endeavors to demystify lattice surgery, making it accessible to those without a profound background in quantum physics or mathematics. This work explores surface codes, introduces the basics of lattice surgery, and demonstrates its application in building quantum gates and emulating multi-qubit circuits.
description: 10 pages, 13 figures, 1 table
การสื่อสารเพื่อสร้างการมีส่วนร่วมในโครงการ 4ม. ขอคืนพื้นที่เขาใหญ่ของกลุ่มเยาวชนต้นกล้าจังหวัดนครนายก
Creators: name: ณัฐกฤตา มัธยมสุข
Publisher: name: คณะบริหารการพัฒนาสิ่งแวดล้อม สถาบันบัณฑิตพัฒนบริหารศาสตร์
Year: 2016
Subjects: การสื่อสารแบบมีส่วนร่วม, การมีส่วนร่วมของเยาวชน, อุทยานแห่งชาติเขาใหญ่

description: 2, 12, วารสารการจัดการสิ่งแวดล้อม
การส่งเสริมคุณค่าท้องถิ่นและความเข้มแข็งของชุมชนผ่านการปรับปรุงภูมิทัศน์ชุมชน
Creators: name: วันดี พินิจวรสิน
Publisher: name: คณะบริหารการพัฒนาสิ่งแวดล้อม สถาบันบัณฑิตพัฒนบริหารศาสตร์
Year: 2016
Subjects: ภูมิทัศน์วัฒนธรรม, ความพอเพียง, การมีส่วนร่วมของชุมชน, อัตลักษณ์ชุมชน, การพัฒนาที่ยั่งยืน

description: 2, 12, วารสารการจัดการสิ่งแวดล้อม
Functional ssDNA for the development of a DNA origami biosensor
Creators: name: Klös, Gunnar
name: Peña, Laura Saa
name: Pavlov, Valeri
name: Cortajarena, Aitziber López
Publisher: name: Zenodo
Year: 2022
Subjects: DeDNAed project, biosensor, DNA origami,

description: The development of novel biosensors with increased performance strongly relies on the incorporation and combination of various nanotechnologies, such as functional nanoparticles (NPs) and DNA origami [1,2]. On the basis of these technologies, the DeDNAed project is creating an advanced bioanalytical sensor-platform with advanced sensitivity and versatility by utilizing SERS as an ultrafast optical analysis method. DNA origami will be used like a “nano-breadboard” to precisely control the nanoscale positioning of biorecognition elements (bioREs) with respect to the plasmonic hotspots of NPs, which are positioned on the DNA origami in a similar fashion, for enabling highly sensitive SERS measurements [3]. To combine these technologies while guaranteeing high spacial precision, we use short oligonucleotide sequences, an established method for the attachment of NP, and active elements to DNA origami [4]. Additionally, the concept includes the integration of metallic atomic cluster (AC) within the bioRE, providing enhanced fluorescence properties compared to other NP based systems while their synthesis is based on novel etching methods that avoid the denaturation of the bioRE [5]. Here we present first findings on the development of an aptamer based bioRE, with a strong focus on the synthesis of the AC and optimization of their fluorescent properties. The bioRE consists of three segments, one for its attachment to the DNA origami, one for the target specific binding and one for the AC coordination. The three segments have been analysed and optimised independently and in combination, verifying their combined functionality. Furthermore, we present the first development iteration of the plasmonic NPs for SERS and their functionalisation for the integration on the DNA origami.
MLQAOA: Graph Learning Accelerated Hybrid Quantum-Classical Multilevel QAOA
Creators: name: Bach, Bao
name: Falla, Jose
name: Safro, Ilya
Publisher: name: arXiv
Year: 2024
Subjects: subject: Quantum Physics (quant-ph)
subject: Computational Engineering, Finance, and Science (cs.CE)
subject: Computational Physics (physics.comp-ph)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Learning the problem structure at multiple levels of coarseness to inform the decomposition-based hybrid quantum-classical combinatorial optimization solvers is a promising approach to scaling up variational approaches. We introduce a multilevel algorithm reinforced with the spectral graph representation learning-based accelerator to tackle large-scale graph maximum cut instances and fused with several versions of the quantum approximate optimization algorithm (QAOA) and QAOA-inspired algorithms. The graph representation learning model utilizes the idea of QAOA variational parameters concentration and substantially improves the performance of QAOA. We demonstrate the potential of using multilevel QAOA and representation learning-based approaches on very large graphs by achieving high-quality solutions in a much faster time. Reproducibility: Our source code and results are available at https://github.com/bachbao/MLQAOA
description: 18 pages, 3 figures, 4 tables
Real-world effectiveness of homologous and heterologous BNT162b2, CoronaVac, and AZD1222 booster vaccination against Delta and Omicron SARS-CoV-2 infection
Creators: name: Suah, Jing Lian
name: Tng, Boon Hwa
name: Tok, Peter Seah Keng
name: Husin, Masliyana
name: Thevananthan, Thevesh
name: Peariasamy, Kalaiarasu M.
name: Sivasampu, Sheamini
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Immunology
subject: FOS: Clinical medicine
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Given emerging evidence of immune escape in the SARS-CoV-2 Omicron viral variant, and its dominance, effectiveness of heterologous and homologous boosting schedules commonly used in low-to-middle income countries needs to be re-evaluated. We conducted a test-negative design using consolidated national administrative data in Malaysia to compare the effectiveness of homologous and heterologous BNT162b2, CoronaVac, and AZD1222 booster vaccination against SARS-CoV-2 infection in predominant-Delta and predominant-Omicron periods. Across both periods, homologous CoronaVac and AZD1222 boosting demonstrated lower effectiveness than heterologous boosting for CoronaVac and AZD1222 primary vaccination recipients and homologous BNT162b2 boosting. Broadly, marginal effectiveness was smaller by 40–50 percentage points in the Omicron period than the Delta period. Without effective and accessible second-generation vaccines, heterologous boosting using BNT162b2 for inactivated and vectored primary vaccination recipients is preferred.
Easy Steps to Goa Game Login – Start Playing Instantly
Creators: name: Easy Steps to Goa Game Login – Start Playing Instantly
Publisher: name: Zenodo
Year: 2025

description: If you're ready to jump into the thrilling world of Goa Game, the first step is a smooth and secure login. Whether you're a new user or a returning player, accessing your account at Goa Game is easy and takes just a few seconds.

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Rethinking model prototyping through the MedMNIST+ dataset collection
Creators: name: Doerrich, Sebastian
name: Di Salvo, Francesco
name: Brockmann, Julius
name: Ledig, Christian
Publisher: name: arXiv
Year: 2024
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Machine Learning (cs.LG)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: The integration of deep learning based systems in clinical practice is often impeded by challenges rooted in limited and heterogeneous medical datasets. In addition, the field has increasingly prioritized marginal performance gains on a few, narrowly scoped benchmarks over clinical applicability, slowing down meaningful algorithmic progress. This trend often results in excessive fine-tuning of existing methods on selected datasets rather than fostering clinically relevant innovations. In response, this work introduces a comprehensive benchmark for the MedMNIST+ dataset collection, designed to diversify the evaluation landscape across several imaging modalities, anatomical regions, classification tasks and sample sizes. We systematically reassess commonly used Convolutional Neural Networks (CNNs) and Vision Transformer (ViT) architectures across distinct medical datasets, training methodologies, and input resolutions to validate and refine existing assumptions about model effectiveness and development. Our findings suggest that computationally efficient training schemes and modern foundation models offer viable alternatives to costly end-to-end training. Additionally, we observe that higher image resolutions do not consistently improve performance beyond a certain threshold. This highlights the potential benefits of using lower resolutions, particularly in prototyping stages, to reduce computational demands without sacrificing accuracy. Notably, our analysis reaffirms the competitiveness of CNNs compared to ViTs, emphasizing the importance of comprehending the intrinsic capabilities of different architectures. Finally, by establishing a standardized evaluation framework, we aim to enhance transparency, reproducibility, and comparability within the MedMNIST+ dataset collection. Code is available at https://github.com/sdoerrich97/rethinking-model-prototyping-MedMNISTPlus .
Discover Goa Game – India's Exciting New Online Gaming Platform
Creators: name: Discover Goa Game – India's Exciting New Online Gaming Platform
Publisher: name: Zenodo
Year: 2025

description: In the ever-evolving world of online entertainment, Goa Game has emerged as one of India’s most exciting platforms for gamers who love competition, rewards, and real-time action. Whether you’re a casual player or a skilled gamer, Goa Game offers a dynamic environment where you can play, win, and earn — all in one place.

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title: Aiding and abetting the looting of nations : the impact of aid on growth in autocracies
Creators: name: Sarr, Mare
name: Swanson, Timothy M
name: Ravetti, Chiara
name: Wingaard, Siri A.H.
Publisher: name: Graduate Institute of International and Development Studies
publisherIdentifier: https://ror.org/007ygn379
publisherIdentifierScheme: ROR
Year: 2013

description: CIES Research Paper ; no.15
Goa Game Login – Easy Steps to Access & Start Playing Instantly
Creators: name: Goa Game Login – Easy Steps to Access & Start Playing Instantly
Publisher: name: Zenodo
Year: 2025

description: Learn how to complete your Goa Game login in seconds and start playing fun, real-money games. Simple OTP-based login and instant access to your wallet and games.

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Goa Game Download – How to Install GoaGameIndia App and Start Playing Today
Creators: name: goagameindia
Publisher: name: Zenodo
Year: 2025

description: Learn how to the Goa Game download  from GoaGameIndia.in and start playing fun real-money games. Easy APK install for Android users with secure login and fast rewards.

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Robust and Efficient Adversarial Defense in SNNs via Image Purification and Joint Detection
Creators: name: Chen, Weiran
name: Xu, Qi
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Spiking Neural Networks (SNNs) aim to bridge the gap between neuroscience and machine learning by emulating the structure of the human nervous system. However, like convolutional neural networks, SNNs are vulnerable to adversarial attacks. To tackle the challenge, we propose a biologically inspired methodology to enhance the robustness of SNNs, drawing insights from the visual masking effect and filtering theory. First, an end-to-end SNN-based image purification model is proposed to defend against adversarial attacks, including a noise extraction network and a non-blind denoising network. The former network extracts noise features from noisy images, while the latter component employs a residual U-Net structure to reconstruct high-quality noisy images and generate clean images. Simultaneously, a multi-level firing SNN based on Squeeze-and-Excitation Network is introduced to improve the robustness of the classifier. Crucially, the proposed image purification network serves as a pre-processing module, avoiding modifications to classifiers. Unlike adversarial training, our method is highly flexible and can be seamlessly integrated with other defense strategies. Experimental results on various datasets demonstrate that the proposed methodology outperforms state-of-the-art baselines in terms of defense effectiveness, training time, and resource consumption.
Viral RNA and infectious virus in mucosal specimens from guinea pigs modelling early phases of lethal and non-lethal Lassa fever
Creators: name: Welch, Stephen R.
name: Genzer, Sarah C.
name: Coleman-McCray, JoAnn D.
name: Harmon, Jessica R.
name: Scholte, Florine E.M.
name: Montgomery, Joel M.
name: Spiropoulou, Christina F.
name: Spengler, Jessica R.
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: 60506 Virology
subject: Computational Biology

description: Lassa fever (LF) is endemic to broad regions of West Africa. Infection with Lassa virus (LASV), the etiologic agent of LF, results in a spectrum of clinical signs in humans, including severe and lethal hemorrhagic disease. Person-to-person transmission occurs through direct contact with body fluids or contaminated bedding and clothing. To investigate transmission risk in acute LASV infection, we evaluated viral RNA and infectious virus obtained from conjunctival, nasal, oral, genital, and rectal swab specimens from guinea pigs modelling lethal and non-lethal LF. Viral RNA and infectious virus were detected in all specimen types beginning 8 days post infection, prior to onset of fever. In the pre-clinical and clinical period, virus was isolated from a subset of nasal, oral, genital, and rectal swabs, and from all conjunctival swabs. Overall, conjunctival and nasal specimens most frequently yielded infectious virus. These findings indicate mucosal transmission risk based on virus isolation from various sites early in infection and support potential utility of minimally invasive specimen evaluation by RT-qPCR for LASV diagnostics.
Validation of the Maudsley Addiction Profile Health Symptoms Scale as a Measure of Symptom Severity in Concurrent Mental Health and Substance Use Disorder Inpatients
Creators: name: Hemmerich, Max H.
name: Thiessen, Karina A.
name: Schütz, Christian G.
Publisher: name: The University of British Columbia
Year: 2023

description: The Maudsley Addiction Profile is often used in research on concurrent disorders (comorbid mental health and substance use disorders). However, its Health Symptoms Scale (MAP-HSS) has not been validated and psychological and somatic mental health symptom severity scores from this measure are rarely reported. In this study, the concurrent validity of the MAP-HSS was assessed via correlations with the Symptom Checklist-90-Revised. The MAP-HSS had acceptable concurrent validity (rho’s = 0.717-0.781, p’s < 0.001) and internal consistency (a = 0.934). The validity of the MAP-HSS supports its utility as a measure of overall psychological wellbeing in research with concurrent disorder populations.
Real-World Effectiveness of Homologous and Heterologous BNT162b2, CoronaVac, and AZD1222 Booster Vaccination Against Delta and Omicron SARS-CoV-2 Infection
Creators: name: BSc, Jing Lian Suah
name: Tng, Boon Hwa
name: Tok, Peter Seah Keng
name: MBBchBAO, Masliyana Husin
name: BAEcon, Thevesh Thevananthan
name: MSc, Kalaiarasu M. Peariasamy
name: MMed, Sheamini Sivasampu
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Immunology
subject: FOS: Clinical medicine
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Given emerging evidence of immune escape in the SARS-CoV-2 Omicron viral variant, and its dominance, effectiveness of heterologous and homologous boosting schedules commonly used in low-to-middle income countries needs to be re-evaluated. We conducted a test-negative design using consolidated national administrative data in Malaysia to compare the effectiveness of homologous and heterologous BNT162b2, CoronaVac, and AZD1222 booster vaccination against SARS-CoV-2 infection in predominant-Delta and predominant-Omicron periods. Across both periods, homologous CoronaVac and AZD1222 boosting demonstrated lower effectiveness than heterologous boosting for CoronaVac and AZD1222 primary vaccination recipients and homologous BNT162b2 boosting (PPP). Broadly, marginal effectiveness was smaller by 40 to 50 percentage points in the Omicron period than the Delta period. Without effective and accessible second-generation vaccines, heterologous boosting using BNT162b2 for inactivated and vectored primary vaccination recipients is preferred.
Continuity of the continued fraction mapping revisited
Creators: name: Ahn, Min Woong
Publisher: name: arXiv
Year: 2024
Subjects: subject: Number Theory (math.NT)
subject: Classical Analysis and ODEs (math.CA)
subject: FOS: Mathematics
subject: Primary 11A55, Secondary 26A15

description: The continued fraction mapping maps a number in the interval $[0,1)$ to the sequence of its partial quotients. When restricted to the set of irrationals, which is a subspace of the Euclidean space $\mathbb{R}$, the continued fraction mapping is a homeomorphism onto the product space $\mathbb{N}^{\mathbb{N}}$, where $\mathbb{N}$ is a discrete space. In this short note, we examine the continuity of the continued fraction mapping, addressing both irrational and rational points of the unit interval.
description: 11 pages, Introduction revised
Multidimensional Compressed Sensing for Spectral Light Field Imaging
Creators: name: Cao, Wen
name: Miandji, Ehsan
name: Unger, Jonas
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Graphics (cs.GR)
subject: Machine Learning (cs.LG)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: This paper considers a compressive multi-spectral light field camera model that utilizes a one-hot spectralcoded mask and a microlens array to capture spatial, angular, and spectral information using a single monochrome sensor. We propose a model that employs compressed sensing techniques to reconstruct the complete multi-spectral light field from undersampled measurements. Unlike previous work where a light field is vectorized to a 1D signal, our method employs a 5D basis and a novel 5D measurement model, hence, matching the intrinsic dimensionality of multispectral light fields. We mathematically and empirically show the equivalence of 5D and 1D sensing models, and most importantly that the 5D framework achieves orders of magnitude faster reconstruction while requiring a small fraction of the memory. Moreover, our new multidimensional sensing model opens new research directions for designing efficient visual data acquisition algorithms and hardware.
description: 8 pages, published of VISAPP 2024
Viral RNA and infectious virus in mucosal specimens from guinea pigs modeling early phases of lethal and non-lethal Lassa fever
Creators: name: Welch, Stephen R.
name: Genzer, Sarah C.
name: Coleman-McCray, JoAnn D.
name: Harmon, Jessica R.
name: Scholte, Florine E.M.
name: Montgomery, Joel M.
name: Spiropoulou, Christina F.
name: Spengler, Jessica R.
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: 60506 Virology
subject: Computational Biology

description: Lassa fever (LF) is endemic to broad regions of West Africa. Infection with Lassa virus (LASV), the etiologic agent of LF, results in a spectrum of clinical signs in humans, including severe and lethal hemorrhagic disease. Person-to-person transmission occurs through direct contact with body fluids or contaminated bedding and clothing. To investigate transmission risk in acute LASV infection, we evaluated viral RNA and infectious virus obtained from conjunctival, nasal, oral, genital, and rectal swab specimens from guinea pigs modeling lethal and non-lethal LF. Viral RNA and infectious virus were detected in all specimen types beginning 8 days post infection, prior to onset of fever. In the pre-clinical and clinical period, virus was isolated from a subset of nasal, oral, genital, and rectal swabs, and from all conjunctival swabs. Overall, conjunctival and nasal specimens most frequently yielded infectious virus. These findings indicate mucosal transmission risk based on virus isolation from various sites early in infection and support potential utility of minimally invasive specimen evaluation by RT-qPCR for LASV diagnostics.
Detection of human, porcine and canine picornaviruses in municipal sewage sludge using pan-enterovirus amplicon-based long-read Illumina sequencing
Creators: name: Faleye, Temitope O. C.
name: Driver, Erin M.
name: Bowes, Devin A.
name: Holm, Rochelle H.
name: Talley, Daymond
name: Yeager, Ray
name: Bhatnagar, Aruni
name: Smith, Ted
name: Varsani, Arvind
name: Halden, Rolf U.
name: Scotch, Matthew
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: Cancer
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Plant Biology
subject: 60506 Virology

description: We describe the successful detection of human, porcine and canine picornaviruses (CanPV) in sewage sludge (at each stage of treatment) from Louisville, Kentucky, USA, using Pan-enterovirus amplicon-based long-read Illumina sequencing. Based on publicly available sequence data in GenBank, this is the first detection of CanPV in the USA and the first detection globally using wastewater-based epidemiology. Our findings also suggest there might be clusters of endemic porcine enterovirus (which have been shown capable of causing systemic infection in porcine) circulation in the USA that have not been sampled for around two decades. Our findings highlight the value of WBE coupled with amplicon based long-read Illumina sequencing for virus surveillance and demonstrates this approach can provide an avenue that supports a “One Health” model to virus surveillance. Finally, we describe a new CanPV assay targeting the capsid protein gene region that can be used globally, especially in resource limited settings for its detection and molecular epidemiology.
The dark side of body positivity
Creators: name: Goomany, Deepika K.
name: Thomas, Irein
name: Bareket-Shavit, Carmelle
name: Thomas, Claire
name: Laurin, Kristin
Publisher: name: The University of British Columbia
Year: 2023

description: Previous research has shown that body positive content, while having beneficial effects (increased body appreciation, increased positive mood, and so on), also increases state self-objectification in women. Since self-objectification limits the cognitive resources we can use to perform tasks, we seek to investigate: if body positive content increases self-objectification, can it have the same negative effects on our cognitive resources, as self-objectification does? We will be comparing the effects of body positive messages and non-body-related positive messages on cognitive and attentional performance. We expect that participants are more likely to have depleted cognitive resources and thus poorer performance when exposed to body positive content rather than non-body-related positive content and the control condition.
THE USE OF LAUGHTER AS AN EXTRALINGUISTIC STRATEGY IN INTERCULTURAL ACADEMIC COMMUNICATION: A COMPARATIVE PERSPECTIVE ON UZBEK AND JAPANESE STUDENTS
Creators: name: To'raboyeva, Dilsora
name: Xolmatjonova, Sarvinoz
name: Jumayeva, Marjona
Publisher: name: Zenodo
Year: 2025

description: Laughter is usually seen as a reaction to humor, but in reality, it plays a much more complex role in communication. In academic settings, especially in multicultural classrooms, laughter can carry different meanings depending on cultural backgrounds. This paper looks at how laughter is used by Uzbek and Japanese students as an extralinguistic strategy in academic environments. By comparing cultural norms and drawing from existing literature, this study sheds light on the subtle ways laughter helps manage social interaction, express emotion, and maintain group harmony in academic discourse.
Colin: A Multimodal Human-AI Co-Creation Storytelling System To Support Children's Multi-Level Narrative Skills
Creators: name: Ye, Lyumanshan
name: Jiang, Jiandong
name: Liu, Yuhan
name: Ran, Yihan
name: Liu, Pengfei
name: Chang, Danni
Publisher: name: arXiv
Year: 2024
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences

description: Children develop narrative skills by understanding and actively building connections between elements, image-text matching and consequences. However, it is challenging for children to clearly grasp these multi-level links only through explanations of text or facilitator's speech. To address this, we developed Colin, an interactive storytelling tool that supports children's multi-level narrative skills through both voice and visual modalities. In the generation stage, Colin supports facilitator to define and review generated text and image content freely. In the understanding stage, a question-feedback model helps children understand multi-level connections while co-creating stories with Colin. In the building phase, Colin actively encourages children to create connections between elements through drawing and speaking. A user study with 20 participants evaluated Colin by measuring children's engagement, understanding of cause-and-effect relationships, and the quality of their new story creations. Our results demonstrated that Colin significantly enhances the development of children's narrative skills across multiple levels.
Invasive listeriosis outbreaks and salmon products: a genomic, epidemiological study
Creators: name: Lachmann, Raskit
name: Halbedel, Sven
name: Lüth, Stefanie
name: Holzer, Alexandra
name: Adler, Marlen
name: Pietzka, Ariane
name: Al Dahouk, Sascha
name: Stark, Klaus
name: Flieger, Antje
name: Kleta, Sylvia
name: Wilking, Hendrik
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: 69999 Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: 110309 Infectious Diseases
subject: FOS: Health sciences

description: Invasive listeriosis, caused by Listeria (L.) monocytogenes, is a severe foodborne infection, especially for immunocompromised individuals. The aim of our investigation was the identification and analysis of listeriosis outbreaks in Germany with smoked and graved salmon products as the most likely source of infection using whole-genome sequencing (WGS) and patient interviews. In a national surveillance programme, WGS was used for subtyping and core genome multi locus sequence typing (cgMLST) for cluster detection of L. monocytogenes isolates from listeriosis cases as well as food and environmental samples in Germany. Patient interviews were conducted to complement the molecular typing. We identified 22 independent listeriosis outbreaks occurring between 2010 and 2021 that were most likely associated with the consumption of smoked and graved salmon products. In Germany, 228 cases were identified, of 50 deaths (22%) reported 17 were confirmed to have died from listeriosis. Many of these 22 outbreaks were cross-border outbreaks with further cases in other countries. This report shows that smoked and graved salmon products contaminated with L. monocytogenes pose a serious risk for listeriosis infection in Germany. Interdisciplinary efforts including WGS and epidemiological investigations were essential to identifying the source of infection. Uncooked salmon products are high-risk foods frequently contaminated with L. monocytogenes. In order to minimize the risk of infection for consumers, food producers need to improve hygiene measures and reduce the entry of pathogens into food processing. Furthermore, susceptible individuals should be better informed of the risk of acquiring listeriosis from consuming smoked and graved salmon products.
The fermionic massless modular Hamiltonian
Creators: name: La Piana, Francesca
name: Morsella, Gerardo
Publisher: name: arXiv
Year: 2024
Subjects: subject: Mathematical Physics (math-ph)
subject: Information Theory (cs.IT)
subject: Operator Algebras (math.OA)
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: 81P45, 94A17, 46L60, 81T05, 81V74

description: We provide an explicit expression for the modular hamiltonian of the von Neumann algebras associated to the unit double cone for the (fermionic) quantum field theories of the 2-component Weyl (helicity 1/2) field, and of the 4-component massless Dirac and Majorana fields. To this end, we represent the one particle spaces of these theories in terms of solutions of the corresponding wave equations, and obtain the action of the modular group on them. As an application, we compute the relative entropy between the vacuum of the massless Majorana field and one particle states associated to waves with Cauchy data localized in the spatial unit ball.
description: 24 pages, one figure. One figure and several explanations added. Version accepted for publication
Learning 3-Manifold Triangulations
Creators: name: Costantino, Francesco
name: He, Yang-Hui
name: Heyes, Elli
name: Hirst, Edward
Publisher: name: arXiv
Year: 2024
Subjects: subject: Geometric Topology (math.GT)
subject: High Energy Physics - Theory (hep-th)
subject: Machine Learning (stat.ML)
subject: FOS: Mathematics
subject: FOS: Physical sciences
subject: FOS: Computer and information sciences

description: Real 3-manifold triangulations can be uniquely represented by isomorphism signatures. Databases of these isomorphism signatures are generated for a variety of 3-manifolds and knot complements, using SnapPy and Regina, then these language-like inputs are used to train various machine learning architectures to differentiate the manifolds, as well as their Dehn surgeries, via their triangulations. Gradient saliency analysis then extracts key parts of this language-like encoding scheme from the trained models. The isomorphism signature databases are taken from the 3-manifolds' Pachner graphs, which are also generated in bulk for some selected manifolds of focus and for the subset of the SnapPy orientable cusped census with $<8$ initial tetrahedra. These Pachner graphs are further analysed through the lens of network science to identify new structure in the triangulation representation; in particular for the hyperbolic case, a relation between the length of the shortest geodesic (systole) and the size of the Pachner graph's ball is observed.
description: 35 pages; 23 figures; 7 tables. v2: accepted version