cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Revealing hidden standard tripartite nonlocality by local filtering
Creators: name: Lv, Qiao-Qiao
name: Liang, Jin-Min
name: Wang, Zhi-Xi
name: Fei, Shao-Ming
Publisher: name: arXiv
Year: 2022
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: Quantum nonlocality is a kind of significant quantum correlation that is stronger than quantum entanglement and EPR steering. The standard tripartite nonlocality can be detected by the violation of the Mermin inequality. By using local filtering operations, we give a tight upper bound on the maximal expected value of the Mermin operators. By detailed examples we show that the hidden standard nonlocality can be revealed by local filtering which can enhance the robustness of the noised entangled states.
description: 10 pages, 4 figures
Estudio de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía de la Universidad Central del Ecuador
Creators: name: Elizabeth Caguana, Malena
Publisher: name: Humanities Commons
Year: 2023

description: Breve descripción de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía de la Universidad Central del Ecuador, tomando en cuenta los resultados obtenidos de la investigación del artículo científico usado
Espacios de formación y comercialización ecológica: Lecciones aprendidas en la Universidad Central del Ecuador
Creators: name: Andrade, Emily
Publisher: name: unknown
Year: 2023

description: Los espacios de comercialización agroecológica se han expandido en el país, debido a la importancia que los productores y consumidores le están dando al origen y la forma de producción de los alimentos. Sin embargo, poco se ha estudiado sobre la interacción entre consumidores y productores en las ferias, y cómo éstas se convierten en espacios de aprendizaje y comercialización para ambos actores. Por ello, se analizó la feria de la Universidad Central del Ecuador, ya que es uno de los pocos casos en el país que es impulsado por un establecimiento educativo. Para lo cual se planteó indicar las principales lecciones aprendidas de la feria, como un espacio de formación y comercialización entre estudiantes, productores y consumidores. Se emplearon diversas técnicas de recolección de datos, como entrevistas, encuestas y revisión bibliográfica sobre agroecología, mercados agroecológicos, circuitos cortos, redes y comercialización agroecológica. Se aplicaron dos encuestas a los consumidores de la feria. La primera encuesta fue realizada a los consumidores frecuentes en los primeros seis meses de funcionamiento, y la segunda encuesta después
de un año, una vez que la feria estaba funcionando regularmente, para corroborar sus preferencias de consumo. Los principales resultados indican que los consumidores son en su mayoría jóvenes y mujeres, que perciben a los productos agroecológicos como más sanos y naturales, lo cual influye en sus preferencias de compra. Se recomienda para futuras investigaciones de la Universidad profundizar en los roles, conocimientos y procesos de decisión inmersos en el consumo de productos agroecológicos.
Espacios de formación y comercialización ecológica: Lecciones aprendidas en la Universidad Central del Ecuador
Creators: HC User
Publisher: name: Humanities Commons
Year: 2023

description: Los espacios de comercialización agroecológica se han expandido en el país, debido a la importancia que los productores y consumidores le están dando al origen y la forma de producción de los alimentos. Sin embargo, poco se ha estudiado sobre la interacción entre consumidores y productores en las ferias, y cómo éstas se convierten en espacios de aprendizaje y comercialización para ambos actores. Por ello, se analizó la feria de la Universidad Central del Ecuador, ya que es uno de los pocos casos en el país que es impulsado por un establecimiento educativo. Para lo cual se planteó indicar las principales lecciones aprendidas de la feria, como un espacio de formación y comercialización entre estudiantes, productores y consumidores. Se emplearon diversas técnicas de recolección de datos, como entrevistas, encuestas y revisión bibliográfica sobre agroecología, mercados agroecológicos, circuitos cortos, redes y comercialización agroecológica. Se aplicaron dos encuestas a los consumidores de la feria. La primera encuesta fue realizada a los consumidores frecuentes en los primeros seis meses de funcionamiento, y la segunda encuesta después de un año, una vez que la feria estaba funcionando regularmente, para corroborar sus preferencias de consumo. Los principales resultados indican que los consumidores son en su mayoría jóvenes y mujeres, que perciben a los productos agroecológicos como más sanos y naturales, lo cual influye en sus preferencias de compra. Se recomienda para futuras investigaciones de la Universidad profundizar en los roles, conocimientos y procesos de decisión inmersos en el consumo de productos agroecológicos.
A Comprehensive 3-D Framework for Automatic Quantification of Late Gadolinium Enhanced Cardiac Magnetic Resonance Images
Creators: name: Wei, Dong
name: Sun, Ying
name: Ong, Sim-Heng
name: Chai, Ping
name: Teo, Lynette L
name: Low, Adrian F
Publisher: name: arXiv
Year: 2022
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Medical Physics (physics.med-ph)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences
subject: FOS: Physical sciences

description: Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can directly visualize nonviable myocardium with hyperenhanced intensities with respect to normal myocardium. For heart attack patients, it is crucial to facilitate the decision of appropriate therapy by analyzing and quantifying their LGE CMR images. To achieve accurate quantification, LGE CMR images need to be processed in two steps: segmentation of the myocardium followed by classification of infarcts within the segmented myocardium. However, automatic segmentation is difficult usually due to the intensity heterogeneity of the myocardium and intensity similarity between the infarcts and blood pool. Besides, the slices of an LGE CMR dataset often suffer from spatial and intensity distortions, causing further difficulties in segmentation and classification. In this paper, we present a comprehensive 3-D framework for automatic quantification of LGE CMR images. In this framework, myocardium is segmented with a novel method that deforms coupled endocardial and epicardial meshes and combines information in both short- and long-axis slices, while infarcts are classified with a graph-cut algorithm incorporating intensity and spatial information. Moreover, both spatial and intensity distortions are effectively corrected with specially designed countermeasures. Experiments with 20 sets of real patient data show visually good segmentation and classification results that are quantitatively in strong agreement with those manually obtained by experts.
description: IEEE Transactions on Biomedical Engineering ( Volume: 60, Issue: 6, June 2013)
Estudio de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía de la Universidad Central del Ecuador
Creators: name: Andrade, Emily
Publisher: name: unknown
Year: 2023

description: El presente artículo es el resultado del estudio de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía. El poco interés que presentan los investigadores a la investigación educativa en las Ciencias Agrícolas, da paso a que esta investigación sea relevante. El instrumento utilizado fue el cuestionario de Procesos de Estudio - Revisado R-SPQ-2F, su aplicación se realizó en forma virtual y voluntaria por medio del utilitario Google Drive. La muestra estuvo conformada por 79 estudiantes de la cohorte marzo 2015; 66 estudiantes de la cohorte octubre 2015; 75
estudiantes de la cohorte abril 2016 y 45 estudiantes de la cohorte octubre 2016. Se relacionaron los enfoques de aprendizaje obtenidos por los estudiantes entre cohortes. Los resultados muestran que la mayoría de los participantes optan por el enfoque de aprendizaje profundo, que tiene como características la búsqueda de la significación de lo aprendido, un grado alto de interés intrínseco y la interiorización del aprendizaje; seguido de cerca del enfoque de aprendizaje superficial donde prima la memorización y la finalidad es aprobar sus estudios aun con notas mínimas, finalmente y con poca aceptación se encuentra un grupo de estudiantes que no tienen un enfoque definido. Se concluye que es importante el conocimiento de los enfoques de aprendizaje utilizado por los estudiantes para implementar correctivos al proceso educativo y lograr el aprendizaje significativo.
Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer
Creators: name: Liu, Zhengyi
name: Zhang, Zhili
name: Wu, Wei
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: Camouflaged object detection intends to discover the concealed objects hidden in the surroundings. Existing methods follow the bio-inspired framework, which first locates the object and second refines the boundary. We argue that the discovery of camouflaged objects depends on the recurrent search for the object and the boundary. The recurrent processing makes the human tired and helpless, but it is just the advantage of the transformer with global search ability. Therefore, a dual-task interactive transformer is proposed to detect both accurate position of the camouflaged object and its detailed boundary. The boundary feature is considered as Query to improve the camouflaged object detection, and meanwhile the object feature is considered as Query to improve the boundary detection. The camouflaged object detection and the boundary detection are fully interacted by multi-head self-attention. Besides, to obtain the initial object feature and boundary feature, transformer-based backbones are adopted to extract the foreground and background. The foreground is just object, while foreground minus background is considered as boundary. Here, the boundary feature can be obtained from blurry boundary region of the foreground and background. Supervised by the object, the background and the boundary ground truth, the proposed model achieves state-of-the-art performance in public datasets. https://github.com/liuzywen/COD
description: Accepted by ICPR2022
Estudio de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía de la Universidad Central del Ecuador
Creators: HC User
Publisher: name: Humanities Commons
Year: 2023

description: El presente artículo es el resultado del estudio de los enfoques de aprendizaje en cuatro cohortes de estudiantes de Agronomía. El poco interés que presentan los investigadores a la investigación educativa en las Ciencias Agrícolas, da paso a que esta investigación sea relevante. El instrumento utilizado fue el cuestionario de Procesos de Estudio - Revisado R-SPQ-2F, su aplicación se realizó en forma virtual y voluntaria por medio del utilitario Google Drive. La muestra estuvo conformada por 79 estudiantes de la cohorte marzo 2015; 66 estudiantes de la cohorte octubre 2015; 75 estudiantes de la cohorte abril 2016 y 45 estudiantes de la cohorte octubre 2016. Se relacionaron los enfoques de aprendizaje obtenidos por los estudiantes entre cohortes. Los resultados muestran que la mayoría de los participantes optan por el enfoque de aprendizaje profundo, que tiene como características la búsqueda de la significación de lo aprendido, un grado alto de interés intrínseco y la interiorización del aprendizaje; seguido de cerca del enfoque de aprendizaje superficial donde prima la memorización y la finalidad es aprobar sus estudios aun con notas mínimas, finalmente y con poca aceptación se encuentra un grupo de estudiantes que no tienen un enfoque definido. Se concluye que es importante el conocimiento de los enfoques de aprendizaje utilizado por los estudiantes para implementar correctivos al proceso educativo y lograr el aprendizaje significativo.
Bayesian methods and liquefaction
Creators: name: Christian, John T.
name: Baecher, Gregory B.
Publisher: name: The University of British Columbia
Year: 2015

description: Since the beginning of serious study of liquefaction in the 1960s, uncertainties in both observed data and in processing field and laboratory tests have been major concerns. Assigning reasonable coefficients of variation to the parameters and correction factors in the conventional deterministic analyses indicates that a site with SPT N values between 12 and 22 and deterministic factors of safety of 1.5 can actually have liquefaction probability above 20%. About a third of the variance in the factor of safety comes from uncertainty in the load (magnitude scaling, stress reduction factor, etc.), which is independent of the method used to estimate the resistance. Researchers have traditionally presented the results of case studies in the form of charts showing instances in which liquefaction did and did not occur and have developed relations to separate the two. Although the original researchers developed the separation lines informally, recent work has applied statistical methods, such as discriminant analysis and logistic regression or combinations of them. In their original form, these methods give the sampling distributions of the observed data (i.e., the probability of observing the data given the hypothesis) rather than the probability of the hypothesis given the data, but the engineer needs the latter, that is, the probability of liquefaction given a set of observations. Researchers have addressed this issue using Bayesian methods, adopting non-informative priors to develop the results. Published curves of liquefaction probabilities can thus be interpreted as likelihood ratios. Other, independent work demonstrates that geological, meteorological, and historical data can be used to develop prior liquefaction probabilities that are not non-informative, so it may not be necessary to assume a non-informative prior. The actual prior can then be combined with the previously developed likelihood ratios to provide rational probabilities of liquefaction.
Myocardial Segmentation of Late Gadolinium Enhanced MR Images by Propagation of Contours from Cine MR Images
Creators: name: Wei, Dong
name: Sun, Ying
name: Chai, Ping
name: Low, Adrian
name: Ong, Sim Heng
Publisher: name: arXiv
Year: 2022
Subjects: subject: Image and Video Processing (eess.IV)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Computer and information sciences

description: Automatic segmentation of myocardium in Late Gadolinium Enhanced (LGE) Cardiac MR (CMR) images is often difficult due to the intensity heterogeneity resulting from accumulation of contrast agent in infarcted areas. In this paper, we propose an automatic segmentation framework that fully utilizes shared information between corresponding cine and LGE images of a same patient. Given myocardial contours in cine CMR images, the proposed framework achieves accurate segmentation of LGE CMR images in a coarse-to-fine manner. Affine registration is first performed between the corresponding cine and LGE image pair, followed by nonrigid registration, and finally local deformation of myocardial contours driven by forces derived from local features of the LGE image. Experimental results on real patient data with expert outlined ground truth show that the proposed framework can generate accurate and reliable results for myocardial segmentation of LGE CMR images.
description: MICCAI 2011
Risk, resilience, and sustainability assessment of infrastructure systems in a life-cycle context considering uncertainties
Creators: name: Dong, You
name: Frangopol, Dan M.
Publisher: name: The University of British Columbia
Year: 2015

description: Within a life-cycle context, infrastructure systems may be subjected to abnormal events, which can hamper functionality of these systems. Maintaining functionality of highway bridges under hazard effects is gaining increased attention. In this paper, a framework for performance assessment of highway bridges under seismic hazard considering risk and resilience is presented. The time effects and uncertainties are integrated within the proposed seismic risk and resilience assessment procedure. Overall, the risk and resilience assessment of a bridge under seismic activity is based on a set of damage states, which are mutually exclusive and collectively exhaustive. Additionally, the probabilistic direct loss, indirect loss, and resilience of a bridge under seismic hazard are investigated. Sustainability assessment of highway bridges is also investigated. The assessment of probabilistic risk, resilience, and sustainability of highway bridges under seismic hazard can aid in implementing risk-informed seismic mitigation and equip decision makers with a better understanding of structural seismic performance in a life-cycle context. The proposed methodology is illustrated on an existing bridge located in California.
Additional file 1 of Predictive ability of visit-to-visit glucose variability on diabetes complications
Creators: name: Teh, Xin Rou
name: Looareesuwan, Panu
name: Pattanaprateep, Oraluck
name: Pattanateepapon, Anuchate
name: Attia, John
name: Thakkinstian, Ammarin
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified

description: Supplementary Material 1
Broadband tunable mid-infrared absorber based on conductive strip-like meta-atom elements
Creators: name: Parsamyan, Henrik
name: Haroyan, Hovhannes
name: Nerkararyan, Khachatur
Publisher: name: arXiv
Year: 2022
Subjects: subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: A metamaterial composed of thin metallic strips as an efficient broadband absorber in the mid-infrared spectrum is investigated. Here the matching between dielectric and geometrical properties of the individual elements is critical to ensure high absorption. Detailed theoretical analysis based on the electric dipole approximation is performed to characterize the absorption and scattering properties of the individual elements of the unit cell and the results are used to design the metamaterial composed of such configurations. The absorption cross-section of a strip-shaped element can exceed its longitudinal geometrical cross-section area by 17 times. It was shown that the absorptance of the Ni-based metal-insulator-metal (MIM) metamaterial structure can exceed 90 % in about 8.2 - 18 um spectrum. The broadband absorption is associated with the excitation of the low-Q-factor dipole modes of the strips. Such an absorber demonstrates good polarization and incident angle tolerance for transverse-electric (TE) waves. The absorption spectrum can be tuned by varying individual element parameters.
description: 16 equations, 6 figures
Determination of supermassive black hole spins in local active galactic nuclei
Creators: name: Piotrovich, M. Yu.
name: Buliga, S. D.
name: Natsvlishvili, T. M.
Publisher: name: arXiv
Year: 2022
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: We estimated the radiative efficiency and spin value for a number of local active galactic nuclei with z < 0.34 using 3 popular models connecting the radiative efficiency with such parameters of AGNs as mass of supermassive black hole, angle between the line of sight and the axis of the accretion disk and bolometric luminosity. Analysis of the obtained data shown that the spin value decreases with cosmic time, which is in agreement with results of theoretical calculations for low redshift AGNs of other authors. Also we found that the spin value increases with the increasing mass of SMBH and bolometric luminosity. This is the expected result that corresponds to theoretical calculations. Analysis of the distribution of the spin values shown a pronounced peak in the distribution in 0.75 < a < 1.0 range. ~ 40% of objects have spin a > 0.75 and ~ 50% of objects have spin a > 0.5. This results are in a good agreement with our previous results and with the results of other authors.
description: 7 pages, 6 figures
Additional file 9 of Enhanced dynamicity: evolutionary insights into amphibian mitogenomes architecture
Creators: name: Xiao, Yi
name: Niu, Gengyun
name: Shi, Haihe
name: Wang, Zhenyu
name: Du, Renzeng
name: Li, Yankuo
name: Wei, Meicai
Publisher: name: figshare
Year: 2025
Subjects: subject: Genetics
subject: FOS: Biological sciences

description: Supplementary File 9
Communicating risk in major incidents : the public's perception
Creators: name: Swan, Lauren
name: Waring, Sara
name: Alison, Laurence
name: Beer, Michael
Publisher: name: The University of British Columbia
Year: 2015

description: There are many examples of unpredicted natural and man-made disasters occurring over the past few decades, for example Hillsborough (1989) and the 7/7 Bombings (2005). Most of these incidents led to legislative reform to either improve infrastructure or the operational response, in an attempt to minimise future risks. However, suggested changes have not taken into consideration how to manage and communicate risk to the public. This is despite the impact that ineffective risk communication could have on both potential casualties and the environment. For example, during the Fukushima accident (2011) people were evacuated from light radioactive areas and ended up in more heavily contaminated areas, partly due to poor risk communication (Robertson et al., 2012). In order to investigate the current status of acceptance from the public when receiving risk information in an emergency, a large-scale live multi-agency training event was developed. This event was based on a ferry collision, which resulted in the release of a potential contaminant, requiring members of the public to undergo mass decontamination. Data was collected using questionnaires and conducting post incident debriefs with a total of 53 members of the public who played the role of ‘passengers’ on-board the ferry. Data was analysed using a combination of qualitative and quantitative methods. Findings indicate that the operational element was accepted, and often praised, but participants had problems with the non-technical side of the response, particularly the communication; this had a significant impact on the perception of the services involved. It is recommended that there is more frequent, clear and direct communication given to the public throughout a disaster as it will potentially increase the level of compliance and reassurance, and will reduce anxiety. This will benefit the agencies involved as effective communication has been found to increase trust and promote future confidence in agencies (Carter et al., 2013). This research has future implications for policy making, disaster management, and improving risk communication to members of the public.
Additional file 1 of Obsessional thinking and autistic traits are each uniquely associated with greater traits of gender dysphoria in clinical and nonclinical adult samples
Creators: name: Mears, Karl
name: Rai, Dheeraj
name: Shah, Punit
name: Ashwin, Chris
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Cell Biology
subject: Neuroscience
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Science Policy
subject: Mental Health

description: Additional file 1.
Likelihood of progressive collapse of buildings from terrorist attacks
Creators: name: Stewart, Mark G.
name: Grant, Matthew J.
Publisher: name: The University of British Columbia
Year: 2015

description: The paper develops a Probabilistic Risk Assessment model that estimates of the probability of terrorist threat, hazard, damage and loss for progressive collapse of large federal government buildings in the United States. It was found that the existing annual fatality risk for building occupants are lower than acceptable risk criteria, and that progressive collapse is an exceedingly rare event in Western countries. A cost-benefit analysis of UFC and GSA design provisions to mitigate against progressive collapse showed that these design measures only becomes cost-effective when the threat likelihood is a very high one in a thousand per building per year.
How small brands grow. Dirichlet analysis of the small brand syndrome
Creators: name: Franke, Katrin
Publisher: name: London South Bank University
Year: 2020
Subjects: deficit loyalty, loyalty, small brands, behavioural loyalty, Dirichlet, NBD-Dirichlet

description: Until now, too little has been known about how small brands compete. Where conventional marketing advocates segmentation, targeting and positioning (STP) to establish strong relationships with loyal buyers, there is almost no evidence whether this approach works for small brands. Instead, research focus has been squarely fixed on the titanic struggles of the market leading brands. Their small rivals are ignored to the point that there is cast disagreement on what a "small brand" is – let alone on how their customers behave.

To better understand small brand competitiveness, an empirical-generalist approach was adopted using commercial consumer panel data provided by Kantar WorldPanel. The longitudinal analysis demonstrated robust and generalizable buying behaviour patterns from a built-in replication design of over 500 brands in more than 30 product categories. The data include the continuously reported fast-moving consumer good (FMCG) purchase records of 15,000 UK households that were used to generate standard brand performance measures (i.e. market share, penetration, repeat purchases, buying frequency and purchase duplication). The NBD-Dirichlet was utilised as a theoretical foundation – as in prior studies on brand performance (see Kahn et al., 1988; Pare et al., 2006).

Repeat purchasing for small brands was analysed over periods ranging from one to five years. Their brand buying patterns were near-stationary and replicated and generalised over time. They were also similar to earlier results for larger brands. Category buying was mostly as expected, hence (small) brand performance is closely predictable. Loyalty was largely a function of brand size, and the Dirichlet benchmarks were used to document and quantify deviations. It was found that niche brands are rare; and so are change-of-pace brands. In fact, the majority of small brands underperformed Dirichlet loyalty predictions yet they managed to maintain the same size (±1% share) over time. They did this by attracting a large proportion of infrequent buyers, year-on-year. The few small brands that grew, did so through significant increases in penetration – in line with Double Jeopardy expectations.

Altogether, the in-depth analysis provides a comprehensive insight into how small brands compete. This is vital because small brands vastly out-number big ones. Plus, even todays giants started out small.

These findings run counter to dominant marketing beliefs and are therefore a major contribution to knowledge and practice. The key limitations are that this study is restricted to one geographical market (the UK), the industry of FMCGs and a period of five consecutive years. Several future research avenues are revealed and discussed.
ЭПИСТЕМОЛОГИЧЕСКАЯ ТЕОРИЯ ЭВОЛЮЦИИ КАРЛА ПОППЕРА
Creators: name: Хайдарова Акида Хуррам кизи Докторант факультета социальных наук  Национального университета Узбекистана, Доктор философии (PhD) по специальности «Философия»
Publisher: name: Zenodo
Year: 2025

description: The article discusses the concept of evolutionary epistemology, its philosophical interpretation, the evolutionary theory of Karl Popper and its unique aspects.

Keywords: evolution, epistemology, theory, concept, innovation
Additional file 1 of Burden and characteristics of Respiratory Syncytial Virus-associated respiratory tract infections in adult patients in the winter season 2023/2024 at the conservative emergency department of the university hospital in Dresden
Creators: name: Ronczka, J
name: von Bonin, S
name: Laubner, A
name: Hochauf-Stange, K
name: Rank, M
name: Kolditz, M
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Immunology
subject: FOS: Clinical medicine
subject: Cancer
subject: Mental Health
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Virology
subject: Computational Biology

description: Supplementary Material 1
A mathematical model of reward-mediated learning in drug addiction
Creators: name: Chou, Tom
name: D'Orsogna, Maria
Publisher: name: arXiv
Year: 2022
Subjects: subject: Neurons and Cognition (q-bio.NC)
subject: FOS: Biological sciences

description: Substances of abuse are known to activate and disrupt neuronal circuits in the brain reward system. We propose a simple and easily interpretable dynamical systems model to describe the neurobiology of drug addiction that incorporates the psychiatric concepts of reward prediction error (RPE), drug-induced incentive salience (IST), and opponent process theory (OPT). Drug-induced dopamine releases activate a biphasic reward response with pleasurable, positive "a-processes" (euphoria, rush) followed by unpleasant, negative "b-processes" (cravings, withdrawal). Neuroadaptive processes triggered by successive intakes enhance the negative component of the reward response, which the user compensates for by increasing drug dose and/or intake frequency. This positive feedback between physiological changes and drug self-administration leads to habituation, tolerance and eventually to full addiction. Our model gives rise to qualitatively different pathways to addiction that can represent a diverse set of user profiles (genetics, age) and drug potencies. We find that users who have, or neuroadaptively develop, a strong b-process response to drug consumption are most at risk for addiction. Finally, we include possible mechanisms to mitigate withdrawal symptoms, such as through the use of methadone or other auxiliary drugs used in detoxification.
description: 12 pages, 7 figures
Additional file 1 of Perivascular space and white matter hyperintensities in Alzheimer’s disease: associations with disease progression and cognitive function
Creators: name: Schirge, Philine Marie
name: Perneczky, Robert
name: Taoka, Toshiaki
name: Ruiz-Rizzo, Adriana L.
name: Ersoezlue, Ersin
name: Forbrig, Robert
name: Guersel, Selim
name: Kurz, Carolin
name: Brendel, Matthias
name: Hellmann-Regen, Julian
name: Priller, Josef
name: Schneider, Anja
name: Jessen, Frank
name: Düzel, Emrah
name: Buerger, Katharina
name: Teipel, Stefan
name: Laske, Christoph
name: Peters, Oliver
name: Spruth, Eike
name: Fliessbach, Klaus
name: Rostamzadeh, Ayda
name: Glanz, Wenzel
name: Janowitz, Daniel
name: Kilimann, Ingo
name: Sodenkamp, Sebastian
name: Ewers, Michael
name: Rauchmann, Boris-Stephan
Publisher: name: figshare
Year: 2025
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Neuroscience
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Mental Health

description: Supplementary Material 1
Artificial intelligence for tracking in space experiments
Creators: name: Cuna, Federica
name: Gargano, Fabio
name: Mazziotta, Nicola Mario
Publisher: name: INFN Open Access Repository
Year: 2024
Subjects: Artificial intelligence
Graph neural network
Tracking
Space experiments

description: This is the slides presented at the spoke3 general meeting about the developent of AI tracking algorithm for space experiment.  We discussed a novel GNN approach for particle reconstruction in space experiments. Specifically, by using the Geant4 toolkit, we simulated the response of 4 scintillating fiber tracking layers, aiming to mimic the setup employed during a beam test at CERN, which utilized a 10 GeV/c negative pion beam. Our approach involves training and evaluating different node-classifying GNN algorithms to distinguish between noise and signal hits in the simulated detector data. These GNN algorithms utilize techniques such as message passing and graph convolution to iteratively aggregate information from neighboring hits and learn discriminative features for classification tasks. We compared the performances of these GNN algorithms with those of traditional analytical tracking approaches, highlighting the advantages of leveraging deep learning techniques for particle reconstruction in space experiments.
Additional file 1 of Potential of MR-based radiomics and optimized statistical machine learning in grading patients with glioma
Creators: name: Sultan, Mohamed N.
name: Yehia, Sherif
name: Khalil, Magdy M.
Publisher: name: figshare
Year: 2025
Subjects: subject: Statistics
subject: FOS: Mathematics
subject: Artificial Intelligence and Image Processing
subject: FOS: Computer and information sciences

description: Additional file 1
TCGA2BED and CAMUR for cancer NGS data processing
Creators: name: Weitschek, Emanuel
name: Cumbo, Fabio
name: Fiscon, Giulia
name: Cestarelli, Valerio
name: Ceri, Stefano
name: Masseroli, Marco
Publisher: name: F1000Research
Year: 2016

description: In this work, we focus on data retrieval, conversion, integration and querying of Next Generation Sequencing (NGS) data and their clinical information extracted from TCGA. In particular, we focus on all publicly available Copy Number Variation (CNV), DNA-methylation, DNA-sequencing (DNA-seq), Gene Expression (RNA-seq V1 and V2), microRNA sequencing (miRNA-seq), and meta (clinical and biospecimen) data.

We propose TCGA2BED (http://bioinf.iasi.cnr.it/tcga2bed/), a software tool able to retrieve genomic and clinical data from TCGA and convert them into the tab-delimited BED format. Additionally, it integrates them with external data (e.g., gene coordinates) from other state-of-the-art biological databases and services such as UCSC Genome Browser, HUGO Gene Nomenclature Committee (HGNC), NCBI Gene, and miRBase.

Using TCGA2BED, we downloaded and converted all publicly available CNV, DNA-methylation, DNA-seq, miRNA-seq, and RNA-seq V1 and V2 experimental and meta data from TCGA.

The TCGA converted data can be easily processed and analysed with wide-spread bioinformatics tools, including the GenoMetric Query Language (GMQL), a key instrument for the integrative querying of genomic and clinical big data from heterogeneous sources.

The use of the BED format reduces the time spent in managing and analyzing the valuable TCGA data: it is possible to efficiently deal with huge amounts of cancer data, and to easily integrate and query them using GMQL. The BED format facilitates the investigators in easily performing knowledge discovery analyses aiming at aiding cancer treatments. For example, the TCGA data in BED format can be straightforwardly analyzed with CAMUR, a tool using a supervised approach able to elicit a high amount of knowledge by computing many rule-based classification models, and therefore able to identify most of the clinical and genomic features related to the predicted cancer type.
Reliability-based progressive collapse and redundancy analysis of suspension bridges
Creators: name: Yang, Jian
name: Ghosn, Michel
Publisher: name: The University of British Columbia
Year: 2015

description: This paper describes a reliability-based approach for evaluating the performance of suspension bridges susceptible to local damage from rare extreme events. The approach accounts for the uncertainties in evaluating the ambient loads during the occurrence of sudden damage and in evaluating the load carrying capacities of the members as well as the damaged system. A method to develop appropriate reliability-based and equivalent deterministic criteria that can be used to assess the potential for progressive collapse are proposed based on risk tolerance levels. Latin Hypercube Simulations (LHS) are used for the system reliability analysis and the consequences of failure are estimated in monetary terms accounting for the cost of rebuilding the bridge, loss of life, traffic and user costs. The risk analysis methodology and the determination of equivalent reliability and deterministic criteria are illustrated using an example suspension bridge subjected to different initial damage scenarios.
Additional file 1 of Detecting Schistosoma infections in endemic countries: a diagnostic accuracy study in rural Madagascar
Creators: name: Lorenz, Eva
name: Razafindrakoto, Ravo
name: Rausche, Pia
name: Rasolojaona, Zaraniaina Tahiry
name: Razafindralava, Nantenaina Matthieu
name: Zerbo, Alexandre
name: Höppner, Yannick
name: von Thien, Heidrun
name: Rakotozandrindrainy, Njary
name: Doumbia, Cheick Oumar
name: Klein, Philipp
name: Kutz, Jean-Marc
name: Corstjens, Paul L. A. M.
name: de Dood, Claudia
name: Hoekstra, Pytsje T.
name: van Dam, Govert J.
name: Jaeger, Anna
name: Schwarz, Norbert Georg
name: Tannich, Egbert
name: Andrianarivelo, Mala Rakoto
name: Rakotozandrindrainy, Raphael
name: Rakotoarivelo, Rivo Andry
name: May, Jürgen
name: Rasamoelina, Tahinamandranto
name: Fusco, Daniela
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Science Policy
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Infectious Diseases
subject: FOS: Health sciences

description: Supplementary material 1
Additional file 1 of The perception of safety regarding the transfer of infants from the neonatal intensive care unit to a level II neonatology department: a mixed-method cohort study using a Safety-II approach
Creators: name: de Bijl-Marcus, Karen
name: Mossel, Fenna
name: Ahaus, Kees
name: Pluut, Bettine
name: Benders, Manon
name: Bruintjes, Arjan
name: Buljac-Samardzic, Martina
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Sociology
subject: FOS: Sociology
subject: Mathematical Sciences not elsewhere classified
subject: Mental Health

description: Supplementary Material 1
Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities
Creators: name: Wang, Shoujin
name: Zhang, Qi
name: Hu, Liang
name: Zhang, Xiuzhen
name: Wang, Yan
name: Aggarwal, Charu
Publisher: name: arXiv
Year: 2022
Subjects: subject: Information Retrieval (cs.IR)
subject: Artificial Intelligence (cs.AI)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: In recent years, sequential recommender systems (SRSs) and session-based recommender systems (SBRSs) have emerged as a new paradigm of RSs to capture users' short-term but dynamic preferences for enabling more timely and accurate recommendations. Although SRSs and SBRSs have been extensively studied, there are many inconsistencies in this area caused by the diverse descriptions, settings, assumptions and application domains. There is no work to provide a unified framework and problem statement to remove the commonly existing and various inconsistencies in the area of SR/SBR. There is a lack of work to provide a comprehensive and systematic demonstration of the data characteristics, key challenges, most representative and state-of-the-art approaches, typical real-world applications and important future research directions in the area. This work aims to fill in these gaps so as to facilitate further research in this exciting and vibrant area.
Supplementary document for Emergent optical nonreciprocity and chirality-controlled magneto-optical resonance in a hybrid magneto-chiral metamaterial. - 6209523.pdf
Creators: name: Peng, Peisong
name: Thapa, Grija
name: Zhou, Jiangfeng
name: Talbayev, Diyar
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplemental Document
Estilos de aprendizaje universitarios
Creators: name: Catota, Stefania
Publisher: name: Humanities Commons
Year: 2023

description: El conocimiento por parte del docente de los estilos de aprendizaje preferidos de los estudiantes ayuda a establecer estrategias de enseñanza-aprendizaje que favorezcan una educación holística. Se sugiere aplicar estrategias con base en organizadores no redactados para promover el análisis, la evaluación y la criticidad. También se aconseja que los docentes conozcan su propio estilo de aprendizaje para poder revelar posibles influencias en el proceso educativo.
Estilos de aprendizaje en estudiantes universitarios
Creators: name: fernando fercho1234, Muñoz
Publisher: name: Humanities Commons
Year: 2023

description: Los estilos  de aprendizaje son simplemente categorías generales, y que cada estudiante puede tener preferencias y combinaciones únicas de estilos de aprendizaje. Es importante que los estudiantes universitarios identifiquen su propio estilo de aprendizaje para optimizar su proceso de estudio y adquisición de conocimientos.
A Domain-adaptive Pre-training Approach for Language Bias Detection in News
Creators: name: Krieger, Jan-David
name: Spinde, Timo
name: Ruas, Terry
name: Kulshrestha, Juhi
name: Gipp, Bela
Publisher: name: arXiv
Year: 2022
Subjects: subject: Computation and Language (cs.CL)
subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences

description: Media bias is a multi-faceted construct influencing individual behavior and collective decision-making. Slanted news reporting is the result of one-sided and polarized writing which can occur in various forms. In this work, we focus on an important form of media bias, i.e. bias by word choice. Detecting biased word choices is a challenging task due to its linguistic complexity and the lack of representative gold-standard corpora. We present DA-RoBERTa, a new state-of-the-art transformer-based model adapted to the media bias domain which identifies sentence-level bias with an F1 score of 0.814. In addition, we also train, DA-BERT and DA-BART, two more transformer models adapted to the bias domain. Our proposed domain-adapted models outperform prior bias detection approaches on the same data.
Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential Recommendation
Creators: name: Fan, Xinyan
name: Lian, Jianxun
name: Zhao, Wayne Xin
name: Liu, Zheng
name: Li, Chaozhuo
name: Xie, Xing
Publisher: name: arXiv
Year: 2022
Subjects: subject: Information Retrieval (cs.IR)
subject: FOS: Computer and information sciences

description: A large-scale recommender system usually consists of recall and ranking modules. The goal of ranking modules (aka rankers) is to elaborately discriminate users' preference on item candidates proposed by recall modules. With the success of deep learning techniques in various domains, we have witnessed the mainstream rankers evolve from traditional models to deep neural models. However, the way that we design and use rankers remains unchanged: offline training the model, freezing the parameters, and deploying it for online serving. Actually, the candidate items are determined by specific user requests, in which underlying distributions (e.g., the proportion of items for different categories, the proportion of popular or new items) are highly different from one another in a production environment. The classical parameter-frozen inference manner cannot adapt to dynamic serving circumstances, making rankers' performance compromised. In this paper, we propose a new training and inference paradigm, termed as Ada-Ranker, to address the challenges of dynamic online serving. Instead of using parameter-frozen models for universal serving, Ada-Ranker can adaptively modulate parameters of a ranker according to the data distribution of the current group of item candidates. We first extract distribution patterns from the item candidates. Then, we modulate the ranker by the patterns to make the ranker adapt to the current data distribution. Finally, we use the revised ranker to score the candidate list. In this way, we empower the ranker with the capacity of adapting from a global model to a local model which better handles the current task.
description: 12 pages
Additional file 1 of Oxytocin signaling in the ventral tegmental area mediates social isolation-induced craving for social interaction
Creators: name: Chang, Hsin-Tzu
name: Cheng, Kuan-Hsiang
name: Hung, Yu-Chieh
name: Hsu, Kuei-Sen
Publisher: name: figshare
Year: 2025
Subjects: subject: Neuroscience
subject: Ecology
subject: FOS: Biological sciences
subject: Science Policy
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Mental Health

description: Additional file 1.
Additional file 2 of The perception of safety regarding the transfer of infants from the neonatal intensive care unit to a level II neonatology department: a mixed-method cohort study using a Safety-II approach
Creators: name: de Bijl-Marcus, Karen
name: Mossel, Fenna
name: Ahaus, Kees
name: Pluut, Bettine
name: Benders, Manon
name: Bruintjes, Arjan
name: Buljac-Samardzic, Martina
Publisher: name: figshare
Year: 2025
Subjects: subject: Medicine
subject: Sociology
subject: FOS: Sociology
subject: Mathematical Sciences not elsewhere classified
subject: Mental Health

description: Supplementary Material 2
Estilos de aprendizaje en estudiantes universitarios.
Creators: name: Estephanía Gutiérrez, Daniela
Publisher: name: Humanities Commons
Year: 2023

description: Se realizó una investigación en la Universidad Central del Ecuador para analizar los estilos de aprendizaje de los estudiantes de dos facultades. Se utilizó el cuestionario CHAEA y se observaron preferencias por los estilos reflexivo, pragmático, teórico y activo. La preferencia por el estilo reflexivo se mantuvo constante en todos los semestres estudiados. Los resultados de este estudio pueden ser útiles para mejorar las estrategias de enseñanza-aprendizaje en la educación universitaria.
A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning
Creators: name: Wang, Zhi
name: Chen, Chunlin
name: Dong, Daoyi
Publisher: name: arXiv
Year: 2022
Subjects: subject: Machine Learning (cs.LG)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: While reinforcement learning (RL) algorithms are achieving state-of-the-art performance in various challenging tasks, they can easily encounter catastrophic forgetting or interference when faced with lifelong streaming information. In the paper, we propose a scalable lifelong RL method that dynamically expands the network capacity to accommodate new knowledge while preventing past memories from being perturbed. We use a Dirichlet process mixture to model the non-stationary task distribution, which captures task relatedness by estimating the likelihood of task-to-cluster assignments and clusters the task models in a latent space. We formulate the prior distribution of the mixture as a Chinese restaurant process (CRP) that instantiates new mixture components as needed. The update and expansion of the mixture are governed by the Bayesian non-parametric framework with an expectation maximization (EM) procedure, which dynamically adapts the model complexity without explicit task boundaries or heuristics. Moreover, we use the domain randomization technique to train robust prior parameters for the initialization of each task model in the mixture, thus the resulting model can better generalize and adapt to unseen tasks. With extensive experiments conducted on robot navigation and locomotion domains, we show that our method successfully facilitates scalable lifelong RL and outperforms relevant existing methods.
description: Manuscript accepted by IEEE Transactions on Cybernetics, 2022, DOI: DOI: 10.1109/TCYB.2022.3170485
Additional file 1 of Nurses’ perspectives on the adoption of new smart technologies for patient care: focus group interviews
Creators: name: Choi, Hyein
name: Tak, Sunghee H.
name: Song, Young Ae
name: Park, Jiyeon
Publisher: name: figshare
Year: 2025
Subjects: subject: Space Science
subject: Medicine
subject: Environmental Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: Infectious Diseases
subject: FOS: Health sciences

description: Supplementary Material 1.