cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Household Cooking with Solid Fuels Contributes to Ambient PM2.5 Air Pollution and the Burden of Disease
Creators: name: Chafe, Zoë A.
name: Brauer, Michael (Of University Of British Columbia)
name: Klimont, Zbigniew
name: Van Dingenen, Rita
name: Mehta, Sumi
name: Rao, Shilpa
name: Riahi, Keywan
name: Dentener, Frank
name: Smith, Kirk R.
Publisher: name: The University of British Columbia
Year: 2015

description: Background: Approximately 2.8 billion people cook with solid fuels. Research has focused on the health impacts of indoor exposure to fine particulate pollution. Here, for the 2010 Global Burden of Disease project (GBD 2010), we evaluated the impact of household cooking with solid fuels on regional population-weighted ambient PM₂.₅ (particulate matter ≤ 2.5 μm) pollution (APM₂.₅). Objectives: We estimated the proportion and concentrations of APM₂.₅ attributable to household cooking with solid fuels (PM₂.₅-cook) for the years 1990, 2005, and 2010 in 170 countries, and associated ill health. Methods: We used an energy supply–driven emissions model (GAINS; Greenhouse Gas and Air Pollution Interactions and Synergies) and source-receptor model (TM5-FASST) to estimate the proportion of APM₂.₅ produced by households and the proportion of household PM₂.₅ emissions from cooking with solid fuels. We estimated health effects using GBD 2010 data on ill health from APM₂.₅ exposure. Results: In 2010, household cooking with solid fuels accounted for 12% of APM₂.₅ globally, varying from 0% of APM₂.₅ in five higher-income regions to 37% (2.8 μg/m³ of 6.9 μg/m³ total) in southern sub-Saharan Africa. PM₂.₅-cook constituted > 10% of APM₂.₅ in seven regions housing 4.4 billion people. South Asia showed the highest regional concentration of APM₂.₅ from household cooking (8.6 μg/m³). On the basis of GBD 2010, we estimate that exposure to APM₂.₅ from cooking with solid fuels caused the loss of 370,000 lives and 9.9 million disability-adjusted life years globally in 2010. Conclusions: PM₂.₅ emissions from household cooking constitute an important portion of APM₂.₅ concentrations in many places, including India and China. Efforts to improve ambient air quality will be hindered if household cooking conditions are not addressed.
title: Wise-GNN: Enhancing GNNs with Wise Embeddings
Creators: name: Uddin, Md Joshem
name: Tola, Astrit
name: Akcora, Cuneyt Gurcan
name: Coskunuzer, Baris
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Mathematics
subject: FOS: Mathematics
subject: Computer science

description: Graph Neural Networks (GNNs) have become the cornerstone of graph representation learning. However, recent studies highlight their struggle to capture information from distant nodes, resulting in poor performance in tasks like node classification, especially in heterophilic settings. To address this, we developed a new model called Wise-GNN. This model directly integrates attribute proximity information into GNN embeddings, improving the understanding of attribute similarities among distant nodes. Additionally, we enhance the robustness of node representations by using the topological signatures of node neighborhoods through persistent homology. Extensive experiments on various GNN models show that combining Wise embeddings with topological signatures significantly boosts GNN performance on benchmark datasets for node classification tasks. We observed average accuracy increases of up to 15% in both homophilic and heterophilic contexts. Our work advances the capabilities of GNNs by incorporating attribute awareness, thereby paving the way for more robust and efficient graph representation learning.
Depressive symptoms in Brazilian Parkinson’s disease patients treated with subthalamic nucleus deep brain stimulation: A Cross-Sectional study
Creators: name: de Souza Arten, Thayná Laís
name: Hamdan, Amer Cavalheiro
Publisher: name: Taylor & Francis
Year: 2024
Subjects: subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Biotechnology
subject: Immunology
subject: FOS: Clinical medicine
subject: Mental Health

description: Parkinson’s disease (PD) is a neurological disorder that primarily affects movement and is often accompanied by depressive symptoms. Subthalamic nucleus (STN) deep brain stimulation (DBS) has emerged as a therapeutic intervention for PD, although its impact on depressive symptoms remains complex. This study investigates the relationship between PD, DBS, and depressive symptoms, focusing on how DBS influences cognitive function and mood among PD patients in Brazil. The study involved two cohorts: one in 2019 with 46 participants and another in 2022 with 31 patients. Distinct assessment instruments, including the Geriatric Depression Scale-15 and Beck Depression Inventory-II, were employed to evaluate depressive symptoms. The results revealed no significant correlation between participants’ gender and the presence of DBS, but substantial differences were observed in age, disease duration, and Activities of Daily Living scores. Patients undergoing DBS showed notably poorer cognitive performance compared to those treated solely with medication. Furthermore, the use of DBS was associated with higher scores on depressive symptoms scales within one of the cohorts. These findings underscore the intricate interplay among PD, DBS treatment, and depressive symptoms, highlighting the necessity for tailored approaches to patient care.
title: Low Data Medical Imaging using Topological Machine Learning
Creators: name: Koung, Philmore
name: Nuwagira, Brighton
name: Korkmaz, Caner
name: Coskunuzer, Baris
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Medicine
subject: Computer science

description: Deep Learning (DL) has revolutionized medical image analysis by providing automated techniques to extract valuable insights from large datasets. However, challenges such as interpretability and reliance on extensive labeled data persist. Topological Data Analysis (TDA) has emerged as a complementary approach that captures underlying topological structures in data, potentially enhancing the performance of DL models. In this paper, we present a comprehensive evaluation of TDA methods for computer-aided diagnosis from two perspectives. We examine the effectiveness of topological methods in data-limited settings by comparing the standalone performance of DL models, TDA approaches, and their fusion. Our results demonstrate that integrating topological features into DL models significantly improves performance when labeled data are scarce. These findings suggest that the fusion of TDA and DL methods can enhance the accuracy and robustness of computer-aided diagnosis, particularly in low-data or 3D imaging scenarios. Leveraging the resources of the Texas Advanced Computing Center (TACC), we generated the topological features for the entire MedMNIST collection, which includes 12 sets of 2D and 6 sets of 3D medical image datasets, encompassing a total of over 600,000 images.
Metodické odporúčanie a model na tvorbu a implementáciu inštitucionálnej politiky otvorenej vedy pre inštitúcie vykonávajúce vedu a výskum
Creators: name: CVTI SR
Publisher: name: Zenodo
Year: 2022
Subjects: inštitucionálna politika
otvorená veda
open science
metodika

description: Dokument obsahuje dve časti, Metodické odporúčanie a Model politiky otvorenej vedy. Je určený vysokým školám, Slovenskej akadémii vied a iným vedecko-výskumným inštitúciám, ktoré ho môžu využiť pri tvorbe svojich politík otvorenej vedy.
Comparative study on the preparation of belite cement from nano-silicas extracted from different agricultural wastes with calcium carbide residue
Creators: name: Kunchariyakun, K
name: Sinyoung, S
name: Asavapisit, S
name: MacKenzie, Kenneth
Publisher: name: Open Access Te Herenga Waka-Victoria University of Wellington
Year: 2022
Subjects: subject: 90599 Civil Engineering not elsewhere classified
subject: FOS: Civil engineering

description: Belite cement was prepared using nano-silicas extracted from three different agricultural wastes–black rice husk ash (BRHA), bagasse ash (BA), and palm oil fuel ash (POFA)–which were reacted at 1200 − 1400 °C with CaC2 residue as calcium source. The product was compared with that from CaCO3. Nano-silica extracted from BRHA was of very fine particle size (surface area 312.4 m2/g and V/S ratio 0.35 × 106 cm) and being highly reactive, forms β-C2S at lower firing temperatures; however, at higher temperatures, less-desirable γ-polymorphs are formed. Nano-silica extracted from POFA contains Na2O, Al2O3, and K2O impurities, which stabilize the β and α-forms and delay the transformation to γ-phase. This is reflected in relatively high compressive strength at firing temperature above 1200 °C, compared to other mixtures. Thus, these results indicate that the best combination of these waste materials for the preparation of belite cement phases is POFA ash and CaC2 residue.
Metodické odporúčanie a model na tvorbu a implementáciu inštitucionálnej politiky otvorenej vedy pre inštitúcie vykonávajúce vedu a výskum
Creators: name: CVTI SR
Publisher: name: Zenodo
Year: 2022
Subjects: inštitucionálna politika
otvorená veda
open science
metodika

description: Dokument obsahuje dve časti, Metodické odporúčanie a Model politiky otvorenej vedy. Je určený vysokým školám, Slovenskej akadémii vied a iným vedecko-výskumným inštitúciám, ktoré ho môžu využiť pri tvorbe svojich politík otvorenej vedy.
Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms
Creators: name: Farahani, Mojtaba A.
name: McCormick, M. R.
name: Harik, Ramy
name: Wuest, Thorsten
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Manufacturing is gathering extensive amounts of diverse data, thanks to the growing number of sensors and rapid advances in sensing technologies. Among the various data types available in SMS settings, time-series data plays a pivotal role. Hence, TSC emerges is crucial in this domain. The objective of this study is to fill this gap by providing a rigorous experimental evaluation of the SoTA ML and DL algorithms for TSC tasks in manufacturing and industrial settings. We first explored and compiled a comprehensive list of more than 92 SoTA algorithms from both TSC and manufacturing literature. Following, we selected the 36 most representative algorithms from this list. To evaluate their performance across various manufacturing classification tasks, we curated a set of 22 manufacturing datasets, representative of different characteristics that cover diverse manufacturing problems. Subsequently, we implemented and evaluated the algorithms on the manufacturing benchmark datasets, and analyzed the results for each dataset. Based on the results, ResNet, DrCIF, InceptionTime, and ARSENAL are the top-performing algorithms, boasting an average accuracy of over 96.6% across all 22 manufacturing TSC datasets. These findings underscore the robustness, efficiency, scalability, and effectiveness of convolutional kernels in capturing temporal features in time-series data, as three out of the top four performing algorithms leverage these kernels for feature extraction. Additionally, LSTM, BiLSTM, and TS-LSTM algorithms deserve recognition for their effectiveness in capturing features within time-series data using RNN-based structures.
description: Published in Robotics and Computer-Integrated Manufacturing journal
Enacting a framework for community development: Engagement and outcomes for students and faculty co-researchers
Creators: name: Budgen, Claire
name: Callaghan, Doris
name: Hatt, Linda
name: Kurtz, Donna
name: Fedderson, Melissa
name: Wiebe, Robyn
name: More, Curt
name: Hamilton, Casey
name: Geddes, Alexa
Publisher: name: Common Ground
Year: 2014

description: Healthy community development in cities, workplaces and educational settings has been the focus of considerable research, policy and practice activity. Healthy community development emphasizes changing health determinants. While the theory is appealing, engaging community members to translate theory into action is challenging. This paper outlines a framework for healthy community development which brings together cross-sector community members to change health determinants. Use of the VOICE framework in a long term project with a university campus is described. In the project, campus community members work as co-researchers to assess the health of the community, identify priority issues, mobilize existing resources, and create health-promoting change. Project achievements have included improvements in campus community health and increases in research and healthy community development capacity of all types of co-researchers. This paper focuses on the engagement of students and faculty as co-researchers and outcomes for each group from participation. Outcomes for non-academic co-researchers (other community members) are briefly described. Related literature on community service learning and undergraduate student researchers is reviewed. Other campuses and communities can easily adapt the VOICE framework and engagement strategies to change health determinants in their settings.
title: Εγκλήματα κατά της τιμής τελούμενα δια του τύπου και των μέσων κοινωνικής δικτύωσης
title: Honor crimes commited throught the Press and Social Media
titleType: AlternativeTitle
Creators: name: Πρίντεζης, Εδουάρδος-Φραγκίσκος
Publisher: name: Πανεπιστήμιο Πελοποννήσου
Year: 2024
Subjects: subject: Ποινικό δίκαιο
subject: Εγκλήματα κατά της τιμής
subject: Δυσφήμηση
subject: Εξύβριση (Ποινικό δίκαιο)
subject: Μέσα μαζικής ενημέρωσης
subject: Έγκλημα και τύπος
subject: Μέσα κοινωνικής δικτύωσης
subject: Ελευθερία του τύπου
subject: Τύπος
subject: Μέσα Κοινωνικής Δικτύωσης
subject: Διαδίκτυο
subject: Αδικήματα κατά της Τιμής
subject: Εξύβριση
subject: Συκοφαντική Δυσφήμηση
subject: Like
subject: Share
subject: Ποινικές ευθύνες παρόχου
subject: Press
subject: Social Media
subject: Internet
subject: Offenses against Honor
subject: Abuse
subject: Defamation
subject: Libel
subject: Provider's criminal responsibilities

description: Σκοπός της εργασίας αυτής , είναι να αποσαφηνιστεί το νομικό πλαίσιο εκ ποινικού δικαίου , με παράλληλη συνταγματική ερμηνεία , σχετικά με την τέλεση των αδικημάτων κατά της τιμής δια του τύπου και των Μέσων Κοινωνικής Δικτύωσης ( Social Media ). Αρχικά , στην παρούσα , παρουσιάζεται μία γενική ανάλυση της τέλεσης των εν θέματι αδικημάτων διά μέσω των προαναφερομένων τρόπων. Εν συνεχεία παρουσιάζεται η ανάγκη να αποσαφηνιστεί σε πρώτο στάδιο η έννοια του εννόμου αγαθού , αφού αυτός είναι και ο πρωταρχικός σκοπός προστασίας του ποινικού δικαίου και σε δεύτερο στάδιο , να επιτευχθεί μια περισσότερο εξειδικευμένη ανάλυση της τιμής ως μία υποκατηγορία των εννόμων αγαθών. Στο δεύτερο μέρος της εργασίας , η μελέτη εκκινά από την ανάλυση της ελευθερίας έκφρασης, όπως διατυπώνεται στο Σύνταγμα, αλλά και από την ΕΣΔΑ. Σύμφωνα με την παραπάνω σκοπιά γίνεται , μία ανάλυση των όρων , ελευθερία του τύπου , ελευθερία του διαδικτύου , τους συνταγματικούς περιορισμούς των , καθώς και του άρθρου 15 Συντάγματος για την προστασία της ραδιοτηλεόρασης. Στο τρίτο και τελευταίο κεφάλαιο , πρωτίστως αναλύονται , ερμηνευτικά , κατ’ άρθρο , τα αδικήματα κατά της τιμής κατόπιν και της αναθεώρησης του ποινικού κώδικα , με τον ν.5090/2024 . Κατόπιν , της ανάλυσης αυτής , εξετάζονται κάποιες ειδικές περιστάσεις , άκρως σημαντικές για την ανάλυση των εγκλημάτων αυτών , που όμως δε συμπεριλαμβάνονται στο παραπάνω κεφάλαιο του ποινικού κώδικα , είτε γιατί καταργήθηκαν , είτε γιατί η αντικειμενική τους υπόσταση δεν εξυπηρετεί μονάχα αυτό το σκοπό. Τέλος , αναλύονται σχοινοτενώς οι ποινικές ευθύνες των συμμετεχόντων και των παρόχων , κατά την τέλεση των αδικημάτων αυτών.
Conditions d’une formation et d’un accompagnement d’un programme intégrant des aides technologiques pour développer l’orthographe lexicale d’élèves dysorthographiques
Creators: name: RICS, Revue
name: Moreau, André C.
name: Fontaine, Myriam
Publisher: name: figshare
Year: 2022
Subjects: Education

description: Le présent texte vise à répondre à la question : quelles sont les conditions de la formation-accompagnement des orthopédagogues, notamment au sujet de l’intégration d’aides technologiques et de l’implantation d’un programme d’intervention orthopédagogique? Cette étude s’inscrit dans un programme de recherche visant à documenter, à développer, à fidéliser et à évaluer la contribution de pratiques orthopédagogiques, structurées dans un programme destiné aux élèves dysorthographiques, dont leurs besoins nécessitent un haut niveau de soutien après avoir résisté à des interventions ciblées en orthographe lexicale en classe. Les données fournies par les orthopédagogues sur la formation et l’accompagnement reçus lors de la phase de l’expérimentation de ce programme sont analysées. Les sections précisent le contexte, la problématique et l’objectif, enchainés par la méthodologie, les résultats et la discussion. Les conditions d’une telle formation - accompagnement sont dégagées.
Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature Review
Creators: name: Bach, Tita A.
name: Kristiansen, Jenny K.
name: Babic, Aleksandar
name: Jacovi, Alon
Publisher: name: arXiv
Year: 2023
Subjects: subject: Human-Computer Interaction (cs.HC)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Ensuring quality human-AI interaction (HAII) in safety-critical industries is essential. Failure to do so can lead to catastrophic and deadly consequences. Despite this urgency, existing research on HAII is limited, fragmented, and inconsistent. We present here a survey of that literature and recommendations for research best practices that should improve the field. We divided our investigation into the following areas: 1) terms used to describe HAII, 2) primary roles of AI-enabled systems, 3) factors that influence HAII, and 4) how HAII is measured. Additionally, we described the capabilities and maturity of the AI-enabled systems used in safety-critical industries discussed in these articles. We found that no single term is used across the literature to describe HAII and some terms have multiple meanings. According to our literature, seven factors influence HAII: user characteristics (e.g., user personality), user perceptions and attitudes (e.g., user biases), user expectations and experience (e.g., mismatched user expectations and experience), AI interface and features (e.g., interactive design), AI output (e.g., perceived accuracy), explainability and interpretability (e.g., level of detail, user understanding), and usage of AI (e.g., heterogeneity of environments). HAII is most measured with user-related subjective metrics (e.g., user perceptions, trust, and attitudes), and AI-assisted decision-making is the most common primary role of AI-enabled systems. Based on this review, we conclude that there are substantial research gaps in HAII. Researchers and developers need to codify HAII terminology, involve users throughout the AI lifecycle (especially during development), and tailor HAII in safety-critical industries to the users and environments.
description: Accepted for publication in IEEE Access
title: Αγροτουρισμός στην Παύλιανη
title: Σχεδιασμός Εταιρικής Ταυτότητας Αγροτουριστικού καταλύματος
titleType: AlternativeTitle
Creators: name: Δρίτσα, Αθανασία
Publisher: name: Πανεπιστήμιο Δυτικής Αττικής
Year: 2024
Subjects: Λογότυπο
Φιλοξενία
Περιβάλλον
Ιστοσελίδα
Εταιρική ταυτότητα
Social media

description: Το αντικείμενο της διπλωματικής αφορά το κατάλυμα αγροτουρισμού Posto Verde, μια υποθετική επιχείρηση που δεν υφίσταται πραγματικά στην ελληνική αγορά, αλλά αποτελεί αφορμή για έναν πρω- τότυπο σχεδιασμό με βασικό γνώμονα την περιβαλλοντολογική συνείδηση. Το ζητούμενο είναι η δημι- ουργία της οπτικής ταυτότητας, ενός απλού αλλά παράλληλα δυναμικού σχεδιασμού που αντανακλά τις αξίες και τη φιλοσοφία του καταλύματος και του τόπου.
Observations of a PT-like phase transition and limit cycle oscillations in non-reciprocally coupled optomechanical oscillators levitated in vacuum
Creators: name: Liška, Vojtěch
name: Zemánková, Tereza
name: Jákl, Petr
name: Šiler, Martin
name: Simpson, Stephen H.
name: Zemánek, Pavel
name: Brzobohatý, Oto
Publisher: name: arXiv
Year: 2023
Subjects: subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: Nanoparticles levitated in an optical trap provide a versatile platform to study mechanical oscillators in a controlled environment with tuneable parameters. Recently, it has become possible to couple two of these optomechanical oscillators. Here, we demonstrate the collective non-Hermitian dynamics of such a pair of non-conservatively coupled oscillators. We take advantage of the tunability of the optical interactions between the particles in our system and set the optical interaction between the particles to be purely non-reciprocal. By continuously varying the relative power of the trapping beams, we take the system through a transition, similar to a parity-time phase transition. A Hopf bifurcation at a critical point results in the formation of collective limit cycle oscillations, resembling those observed in phonon lasers. These coupled levitated oscillators provide a platform for exceptional point optomechanical sensing and can be extended to multi-particle systems, paving the way for the development of topological optomechanical media.
description: Nat. Phys. (2024)
SMART-Plant_IWARR2019_Environmental Technology Verification of the Full Scale Short-Cut Enhanced Nutrients Abatement (SCENA) Process
Creators: name: V. Conca
name: N. Frison
name: M. Tartini
name: A. Piasentin
name: A.L. Eusebi
name: F. Fatone
Publisher: name: Zenodo
Year: 2020

description: Abstract: This work reports the long-term operation of the Short-Cut Enhanced Nutrients Abatement
 (SCENA) for the treatment of anaerobic reject water. SCENA process adopted the via-nitrite pathway
 for an efficient nitrogen removal combined with the on-site VFAs production through acidogenic
 fermentation of sewage sludge. The system was operated for more than 450 days, where the applied
 vNLR was maintained between 0.50 to 0.66 kgN/m3 day, while the average removal efficiency was
 stable at around 82% (average). Currently, the energy consumption for nitrogen removal (kWh/kgN
 removed) and related N2O emissions (gN2O-N/kgN removed) are the performance claims target under
 evaluation to achieve the Environmental Technology Verification (ETV), which will establish the
 environmental added value of the process through independent assessment.
 Keywords: Environmental technology verification; short-cut enhanced nutrient abatement (SCENA);
 external carbon source; SBR; Horizon 2020 – Smart-Plant
Observation of the Quantum Zeno Effect on a NISQ Device
Creators: name: Alessandrini, Andrea
name: Ciaramelletti, Carola
name: Paganelli, Simone
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: We study the Quantum Zeno Effect (QZE) on a single qubit on IBM Quantum Experience devices under the effect of multiple measurements. We consider two possible cases: the Rabi evolution and the free decay. SPAM error mitigations have also been applied. In both cases we observe the occurrence of the QZE as an increasing of the survival probability with the number of measurements.
Space-time symmetry and nonreciprocal parametric resonance in mechanical systems
Creators: name: Melkani, Abhijeet
name: Paulose, Jayson
Publisher: name: arXiv
Year: 2023
Subjects: subject: Classical Physics (physics.class-ph)
subject: Soft Condensed Matter (cond-mat.soft)
subject: FOS: Physical sciences

description: Linear mechanical systems with time-modulated parameters can harbor oscillations with amplitudes that grow or decay exponentially with time due to the phenomenon of parametric resonance. While the resonance properties of individual oscillators are well understood, those of systems of coupled oscillators remain challenging to characterize. Here, we determine the parametric resonance conditions for time-modulated mechanical systems by exploiting the internal symmetries arising from the real-valued and symplectic nature of classical mechanics. We also determine how these conditions are further constrained when the system exhibits external symmetries. In particular, we analyze systems with space-time symmetry where the system remains invariant after a combination of discrete translation in both space and time. For such systems, we identify a combined space-time translation operator that provides more information about the dynamics of the system than the Floquet operator does, and use it to derive conditions for one-way amplification of traveling waves. Our exact theoretical framework based on symmetries enables the design of exotic responses such as nonreciprocal transport and one-way amplification in dynamic mechanical metamaterials, and is generalizable to all physical systems that obey space-time symmetry.
description: 15 pages, 5 figures. V2: New figure and discussion. Accepted version
SMART-Plant_Via-nitrite selection of PHA storing biomass through fermentation liquid of cellulosic primary sludge
Creators: name: F.Fatone
Publisher: name: Zenodo
Year: 2020

description: Outline •The Horizon2020 «SMART-Plant» Innovation Action •Cellulose in wastewater and recovery/valorization routes •Controlled fermentation to recover propionate-rich volatile fatty acids •Bio(co)polymers (PHB-coPHV) production in the sidestream SCEPPHAR system •What’snext: scale-up to demo in real environment at Carbonera WRRF
Ferromagnetic Haldane state and dimer multiplet state of quantum ferromagnets
Creators: name: Miyahara, Shin
name: Maruyama, Isao
Publisher: name: arXiv
Year: 2023
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: Statistical Mechanics (cond-mat.stat-mech)
subject: FOS: Physical sciences

description: We present a theory of the realization of a ferromagnetic Haldane state in a spin-2 bilinear-biquadratic spin system on an orthogonal-dimer chain. The coexistence of a ferromagnetic state and a Haldane state is due to the rigorous correspondence between the eigenstates of a spin-2 model and a spin-1/2 Heisenberg model; i.e., "eigensystem embedding." Numerical exact-diagonalization calculations indicate that the ground state in the model is a fractionally magnetized M = 3/4 Haldane state. Moreover, a ferromagnetic-dimer multiplet state is an exact ground state on a lattice, where the direct product of dimer singlet states is the ground state in a spin-1/2 Heisenberg model that includes one-, two-, and three-dimensional orthogonal-dimer lattices. Eigensystem embedding demonstrates that a quantum ferromagnet can be obtained for an arbitrary spin S >= 2 in any dimension and for any lattice in which anomalous ground states are realized in a spin-1/2 Heisenberg model.
Highly Efficient Creation and Detection of Ultracold Deeply-Bound Molecules via Chainwise Stimulated Raman Shortcut-to-Adiabatic Passage
Creators: name: Zhang, Jiahui
name: Deng, Li
name: Niu, Yueping
name: Gong, Shangqing
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Chainwise stimulated Raman adiabatic passage (C-STIRAP) in M-type molecular system is a good alternative in creating ultracold deeply-bound molecules when the typical STIRAP in Λ-type system does not work due to weak Frank-Condon factors between states. However, its creation efficiency under the smooth evolution is generally low. During the process, the population in the intermediate states may decay out quickly and the strong laser pulses may induce multi-photon processes. In this paper, we find that shortcut-to-adiabatic (STA) passage fits very well in improving the performance of the C-STIRAP. Currently, related discussions on the so-called chainwise stimulated Raman shortcut-to-adiabatic passage (C-STIRSAP) are rare. Here, we investigate this topic under the adiabatic elimination. Given a relation among the four incident pulses, it is quite interesting that the M-type system can be generalized into an effective Λ-type structure with the simplest resonant coupling. Consequently, all possible methods of STA for three-state system can be borrowed. We take the counter-diabatic driving and "chosen path" method as instances to demonstrate our treatment on the molecular system. Although the "chosen path" method does not work well in real three-state system if there is strong decay in the excited state, our C-STIRSAP protocol under both the two methods can create ultracold deeply-bound molecules with high efficiency in the M-type system. The evolution time is shortened without strong laser pulses and the robustness of STA is well preserved. Finally, the detection of ultracold deeply-bound molecules is discussed.
Isotopic composition of CO2 in gasoline, diesel and natural gas combustion exhaust in Vancouver, BC, Canada
Creators: name: Semmens, Caitlin
name: Ketler, Rick
name: Schwendenmann, Luitgard
name: Nesic, Zoran
name: Christen, Andreas
Publisher: name: The University of British Columbia
Year: 2014

description: The isotopic composition (δ¹³ and δ¹⁸) in atmospheric carbon dioxide (CO₂) originating from gasoline and diesel vehicle exhaust and from natural gas combustion was determined. Gasoline and diesel samples were taken in the exhaust of representative vehicles of the fleet in Vancouver, BC, Canada between November 2013 and May 2014. The fleet average gasoline exhaust (which contained a fraction bioethanol) was determined with a δ¹³C of -27.27 (±0.93)‰ and a δ¹⁸O of -12.46 (±3.45)‰ (w.r.t. VPD-CO₂). The fleet average for diesel vehicles exhibited a slightly lower δ¹³C of -28.81 (±0.40)‰ and a δ¹⁸O of -18.63 (±0.72)‰ close to unfractionated combustion. For natural gas, samples were taken from a open torch using the city’s natural gas supply network at different dates over the year. The mean δ¹³C for natural gas samples was -41.64 (±0.82)‰, while the mean δ¹⁸O was lower than for internal combustion engines at -22.74 (±0.56)‰. In conclusion, δ¹³C depends on the fuel type and origin and there is evidence that δ¹⁸O is fractionated in the combustion process and presence and state of catalytic converters causes different δ¹⁸O.
Guidelines for Improving English Communication Skills of Undergraduate Students at Rajabhat Maha Sarakham University by Using three Instructional Models
Creators: name: Narongrit Sopa
Publisher: name: DR.KEN Institute of Academic Development and Promotion
Year: 2022
Subjects: Guidelines
Improving English Communication Skills
Undergraduate Students
Three Instructional Models

description: International Journal of Sociologies and Anthropologies Science Reviews, 2, 3, 9-20
title: Numerical Implementation of the Barrier Lowering Effect at Metal Surfaces
Creators: name: Baikadi, Pranay
name: Vandenberghe, William G.
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Semiconductor physics

description: When a charged particle in vacuum or a semiconductor is in the proximity of a grounded metal, the Coulombic interaction between the charged particle and electrons inside the metal results in the formation of a thin charged layer of opposite polarity near the metal surface. The oppositely charged surface layer in turn exerts an attractive force on the charged particle, reducing the potential barrier seen by the charged particle in the presence of an electric field. This complex many-body phenomenon at the metal surface, known as the image-force barrier lowering (IFBL) effect, is particularly relevant to carrier transport at metal-semiconductor interfaces, which are ubiquitous across all transistor architectures. An accurate treatment of this effect requires invoking density functional theory (DFT) at the GW level, which becomes computationally expensive when considering large simulation domains involving non-uniform dielectric setups. Furthermore, beyond a few simple grounded metal geometries, it is difficult to derive analytical expressions of IFBL in arbitrary structures. Many quantum transport studies in the literature have therefore ignored the effect or relied on the one-dimensional analytical expression for IFBL corresponding to a 1D metal plate to incorporate IFBL into their calculations. In this work, we present a novel numerical approach to calculate the image force potential in arbitrary metal geometries and with non-uniform dielectric environments. Our approach, based on the method of images on a non-Euclidean manifold and eigenvalue decomposition of the Laplacian matrix, can handle large simulation domains with complex dielectric setups, a regime typically inaccessible to DFT based approaches. We will compare and contrast our numerical approach with the closed-form expressions of IFBL reported recently for top and side contacts to transition-metal dichalogenides (TMDs). Lastly, the numerically evaluated image force potential will be imported into our open-source quantum transport solver and the effect of IFBL on the Schottky barrier height (ϕB) and contact resistance (RC) of metal-MoS2 contact will be demonstrated.
Search for narrow trijet resonances in proton-proton collisions at $\sqrt{s}$ = 13 TeV
Creators: name: CMS Collaboration
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Experiment (hep-ex)
subject: FOS: Physical sciences

description: The first search for singly produced narrow resonances decaying to three well-separated hadronic jets is presented. The search uses proton-proton collision data corresponding to an integrated luminosity of 138 fb$^{-1}$ at $\sqrt{s}$ = 13 TeV, collected at the CERN LHC. No significant deviations from the background predictions are observed between 1.75-9.00 TeV. The results provide the first mass limits on a right-handed boson Z$_{\mathrm{R}}$ decaying to three gluons and on an excited quark decaying via a vector boson to three quarks, as well as updated limits on a Kaluza-Klein gluon decaying via a radion to three gluons.
description: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables, including additional supplementary figures, can be found at http://cms-results.web.cern.ch/cms-results/public-results/publications/EXO-22-008 (CMS Public Pages)
title: TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis
Creators: name: Fatema, Saba
name: Nuwagira, Brighton
name: Chakraborty, Sayoni
name: Gedik, Reyhan
name: Coskunuzer, Baris
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Topology
subject: Deep Learning
subject: Histopathology

description: The microscopic evaluation of tissue samples is crucial for identifying and classifying cancerous cells. This manual process, while effective, is labor-intensive and demands the specialized knowledge of experienced pathologists. With recent strides in deep learning, there is great potential to improve diagnostic efficiency and accuracy, offering faster, more consistent results that could help alleviate the burden on clinicians. Despite these advancements, one of the key challenges is the need for large, labeled datasets to train deep learning models effectively. In this work, we introduce the integration of topological deep learning techniques as a way to enhance the performance of histopathological image analysis models. Topological data analysis (TDA) is employed to capture important topological structures across different image color channels, offering a distinctive approach to feature extraction. While deep learning models typically excel at capturing localized details within images, TDA adds global insights, making it a valuable complement. Our experiments using publicly accessible datasets of histopathological images demonstrate that incorporating topological features leads to a marked improvement in distinguishing between different tumor types, particularly in ovarian and breast cancer classifications.
Localized chaos due to rotating shock waves in Kerr-AdS black holes and their ultraspinning version
Creators: name: Prihadi, Hadyan Luthfan
name: Zen, Freddy Permana
name: Dwiputra, Donny
name: Ariwahjoedi, Seramika
Publisher: name: arXiv
Year: 2023
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: General Relativity and Quantum Cosmology (gr-qc)
subject: FOS: Physical sciences

description: The butterfly velocity of four-dimensional rotating charged asymptotically AdS black hole is calculated to probe chaos using localized rotating shock waves. In this work, we obtain the angular momentum dependence of the butterfly velocity due to rotation in the shock wave probes. In general, the angular momentum $\mathcal{L}$ of the shock waves increases the butterfly velocity. The localized shocks also generate butterfly velocities which vanish when we approach extremality, indicating no entanglement spread near extremality. One of the butterfly velocity modes is well bounded by both the speed of light and the Schwarzschild-AdS result, while the other may become superluminal. Aside from the logarithmic behavior of the scrambling time which indicates chaos, the Lyapunov exponent is also positive and bounded by $κ=2πT_H/(1-μ\mathcal{L})$. The Kerr-NUT-AdS and Kerr-Sen-AdS solutions and their ultraspinning versions are used as examples to attain a better understanding of the chaotic phenomena in rotating black holes, especially those with extra conserved charges.
description: 26 pages, 4 captioned figures. Major revision. Accepted for publication in General Relativity and Gravitation
Deterministic Impartial Selection with Weights
Creators: name: Cembrano, Javier
name: Griesbach, Svenja M.
name: Stahlberg, Maximilian J.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Science and Game Theory (cs.GT)
subject: Theoretical Economics (econ.TH)
subject: FOS: Computer and information sciences
subject: FOS: Economics and business

description: In the impartial selection problem, a subset of agents up to a fixed size $k$ among a group of $n$ is to be chosen based on votes cast by the agents themselves. A selection mechanism is impartial if no agent can influence its own chance of being selected by changing its vote. It is $α$-optimal if, for every instance, the ratio between the votes received by the selected subset is at least a fraction of $α$ of the votes received by the subset of size $k$ with the highest number of votes. We study deterministic impartial mechanisms in a more general setting with arbitrarily weighted votes and provide the first approximation guarantee, roughly $1/\lceil 2n/k\rceil$. When the number of agents to select is large enough compared to the total number of agents, this yields an improvement on the previously best known approximation ratio of $1/k$ for the unweighted setting. We further show that our mechanism can be adapted to the impartial assignment problem, in which multiple sets of up to $k$ agents are to be selected, with a loss in the approximation ratio of $1/2$.
description: Extended version to appear in the ACM Transactions on Economics and Computation (TEAC)
title: Enhancing Large Language Model Fine-Tuning for Text-to-SQLs through SQL Quality Measurement and Prompt Engineering
Creators: name: Sarker, Shouvon
name: Li, Xiangfang
name: Dong, Xishuang
name: Qian, Lijun
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Generative AI

description: Text-to-SQLs enables non-expert users to effortlessly retrieve desired information from relational databases using natural language queries. While recent advancements, particularly with Large Language Models (LLMs) like GPT and T5, have shown impressive performance on large-scale benchmarks such as BIRD, current state-of-the-art (SOTA) LLM-based Text-to-SQLs models often require significant efforts to develop auxiliary tools like SQL classifiers to achieve high performance. This paper proposed a novel approach that integrates LLMs reasoning and SQL quality assessment to achieve competitive Text-to-SQLs performance without the need for complex auxiliary tool building. It customizes self-discover reasoning to thoroughly analyze the SQL query generation process, enhancing Text-to-SQLs capabilities. Additionally, it establishes a SQL quality evaluation mechanism to assess the generated SQL queries against predefined criteria and actual database responses in real-time. This feedback loop enables continuous learning and refinement of model outputs based on both syntactic correctness and semantic accuracy. The proposed method undergoes comprehensive validation on theBIRD benchmark, assessing Execution Accuracy (EX) and Valid Efficiency Score (VES) across various Text-to-SQLs difficulty levels.
Hopf Bifurcations of Twisted States in Phase Oscillators Rings with Nonpairwise Higher-Order Interactions
Creators: name: Bick, Christian
name: Böhle, Tobias
name: Omel'chenko, Oleh E.
Publisher: name: arXiv
Year: 2023
Subjects: subject: Dynamical Systems (math.DS)
subject: Disordered Systems and Neural Networks (cond-mat.dis-nn)
subject: Adaptation and Self-Organizing Systems (nlin.AO)
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: Synchronization is an essential collective phenomenon in networks of interacting oscillators. Twisted states are rotating wave solutions in ring networks where the oscillator phases wrap around the circle in a linear fashion. Here, we analyze Hopf bifurcations of twisted states in ring networks of phase oscillators with nonpairwise higher-order interactions. Hopf bifurcations give rise to quasiperiodic solutions that move along the oscillator ring at nontrivial speed. Because of the higher-order interactions, these emerging solutions may be stable. Using the Ott--Antonsen approach, we continue the emergent solution branches which approach anti-phase type solutions (where oscillators form two clusters whose phase is $π$ apart) as well as twisted states with a different winding number.
description: 24 pages, 8 figures
Strongly anisotropic vortices in dipolar quantum droplets
Creators: name: Li, Guilong
name: Zhao, Zibin
name: Jiang, Xunda
name: Chen, Zhaopin
name: Liu, Bin
name: Malomed, Boris A.
name: Li, Yongyao
Publisher: name: arXiv
Year: 2023
Subjects: subject: Quantum Gases (cond-mat.quant-gas)
subject: Pattern Formation and Solitons (nlin.PS)
subject: FOS: Physical sciences

description: We construct strongly anisotropic quantum droplets with embedded vorticity in the 3D space, with mutually perpendicular vortex axis and polarization of atomic magnetic moments. Stability of these anisotropic vortex quantum droplets (AVQDs) is verified by means of systematic simulations. Their stability area is identified in the parametric plane of the total atom number and scattering length of the contact interactions. We also construct vortex-antivortex-vortex bound states and find their stability region in the parameter space. The application of a torque perpendicular to the vorticity axis gives rise to robust intrinsic oscillations or rotation of the AVQDs. The effect of three-body losses on the AVQD stability is considered too. The results show that the AVQDs can retain the topological structure (vorticity) for a sufficiently long time if the scattering length exceeds a critical value.
description: 7 pages, 6 figures, and 80 References, Physical Review Letters, in press
title: Assessing the Role of Natural Barriers in Protecting Crops in the Rio Grande Valley, Texas
Creators: name: Nwamadi, Stone
name: Narang, Ira
name: Marden, Alex
name: Shensky, Michael
name: Dawson, Clint
name: Proft, Jennifer
name: Brown, Katherine
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Agriculture

description: Floods pose significant threats to crop and vegetation areas, particularly in the southern Texas region of the lower Rio Grande Valley [1]. Geological software analysis demonstrates that nature-based solutions, such as dunes and barrier islands, are crucial for mitigating flood damage in this area. The Quantum Geographic Information System (QGIS) was used for the mapping of crop data. The Advanced Circulation (ADCIRC) model output [2], generated using Frontera at TACC, was used for data collection of flood-induced water level changes. Three main categories were analyzed when determining the effectiveness of nature based solutions against flooding- agriculture, vegetation, and social vulnerability. Generating and layering crop maps with QGIS and combining them with the flooding areas shown by the ADCIRC model was the process used to see the effects of natural based barriers in flooding in the lower Rio Grande Valley. The objective this research aims to accomplish is to communicate the importance of natural barriers in agricultural preservation and protection. Local communities that rely on agriculture and policy makers in flood-prone regions would benefit from this information by implementing mitigation strategies that have been proven to be effective against floods and promote agricultural development. This work has been supported by the Wellcome Trust, Planet Texas 2050, a research grant challenge at the University of Texas at Austin and by Empowering Future Agricultural Scientists (EFAS-REEU, grant no. 2016-67032-25013) from the USDA National Institute of Food and Agriculture. We gratefully acknowledge the use of the “ADCIRC” allocations on the Frontera supercomputer at the Texas Advanced Computing Center at the University of Texas at Austin.
title: Graph Neural Networks for Contact Between Deformable Bodies
Creators: name: Dubey, Vijay
name: Haese, Collin E.
name: Fuhg, Jan
name: Rausch, Manuel K.
name: Gültekin, Osman
Publisher: name: The University of Texas at Austin
Year: 2024
Subjects: subject: Computational mechanics

description: Traditional methods, such as finite elements, are compute- and time-intensive when used to solve for displacements in nonlinear continuum mechanics, especially when multi-body contacts are involved. This is a roadblock for applications where such simulations need to be completed quickly. Machine learning can alleviate this. We present an implementation of Graph Neural Network for accelerating such simulations. We utilized training data based on past simulations done using the finite-element method. This can be done due to the natural representation of meshes as graphs. The architecture employs multiple rounds of message passing based on encoded nodal and edge features (Dalton et al., 2022). Two types of edges are defined based on either connectivity in mesh or proximity in physical space (Pfaff et al., 2022). The learning is done through a composite loss term consisting of data-based dynamic losses arising from predictions of nodal accelerations and a self-supervised contact loss term. The contact loss computation is made tractable by using filters like bounding-boxes, sweep direction, vertex-face, and edge-edge tests to cull collision pairs (Zhu et al.,2022). The framework differs from those in the past as it can be applied to contact between deformable bodies, unlike tool-object interactions, where the tool is considered rigid. We present the application of this framework to an example problem that demonstrates its capability to handle contact. Results on error statistics are also presented.
SMART-Plant_Circular management of municipal water
Creators: name: F.Fatone
Publisher: name: Zenodo
Year: 2020

description: Outline of the presentation •Brief outline of our R&D&I activities to deliver circular economy in water and waste sectors •Circular economy in the water sector: The SMART-Plant Innovation Action •Technologies •Business models •Market exploitation and replicability •Wastewater treatment plant as urban biorefinery