95,728 results on '"A. Rivero"'
Search Results
2. Impact of an enhanced screening program on the detection of non-AIDS neoplasias in patients with human immunodeficiency virus infection
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M. Masiá, S. Padilla, G. Estañ, J. Portu, A. Silva, A. Rivero, A. González-Cordón, L. García-Fraile, O. Martínez, E. Bernal, C. Galera, V. Boix Martínez, J. Macias, M. Montero, D. García-Rosado, M. J. Vivancos-Gallego, J. Llenas-García, M. Torralba, J. A. García, V. Agulló, M. Fernández-González, F. Gutiérrez, E. Martínez, and IMPAC-NEO Study Group
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HIV infection ,Neoplasms ,Cancer ,Non-AIDS-defining cancers ,Screening ,Early detection of cancer ,Medicine (General) ,R5-920 - Abstract
Abstract Background The incidence of non-AIDS defining cancer (NADC) is higher in people living with HIV (PLWH) than in the general population, and it is already one of the leading causes of death in the HIV-infected population. It is estimated that the situation will be aggravated by the progressive aging of PLWH. Early diagnosis through intensive cancer screening may improve the ability for therapeutic interventions and could be critical in reducing mortality, but it might also increase expenditure and harms associated with adverse events. The aim of this study is to evaluate an enhanced screening program for early diagnosis of cancer in PLWH compared to standard practice. The specific objectives are (1) to compare the frequency of cancer diagnosed at an early stage, (2) to analyze safety of the enhanced program: adverse events and unnecessary interventions, (3) to analyze the cost-utility of the program, and (4) to estimate the overall and site-specific incidence of NADC in PLWH. Methods We will conduct a multicenter, non-blinded, randomized, controlled trial, comparing two parallel arms: conventional vs enhanced screening. Data will be recorded in an electronic data collection notebook. Conventional intervention group will follow the standard of care screening in the participating centers, according to the European AIDS Clinical Society recommendations, and the enhanced intervention group will follow an expanded screening aimed to early detection of lung, liver, anal, cervical, breast, prostate, colorectal, and skin cancer. The trial will be conducted within the framework of the Spanish AIDS Research Network Cohort (CoRIS). Discussion The trial will evaluate the efficacy, safety, and efficiency of an enhanced screening program for the early diagnosis of cancer in HIV patients compared to standard of care practice. The information provided will be relevant since there are currently no studies on expanded cancer screening strategies in patients with HIV, and available data estimating cost effectiveness or cost-utility of such as programs are scarce. An enhanced program for NADC screening in patients with HIV could lead to early diagnosis and improve the prognosis of these patients, with an acceptable rate of unnecessary interventions, but it is critical to demonstrate that the benefits clearly outweigh the harms, before the strategy could be implemented. Trial registration ClinicalTrials.gov NCT04735445. Registered on 25 June 2019
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- 2021
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3. Impact of Human Leukocyte Antigen Allele-Killer Cell Immunoglobulin-like Receptor Partners on Sexually Transmitted Human Immunodeficiency Virus Type 1 Infection.
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Serrano-Rísquez, Carmen, Omar, Mohamed, Rallón, Norma, Benito, José, Gómez-Vidal, Amparo, Márquez, Francisco, Alján, Martina, Rivero-Juárez, Antonio, Pérez-Valero, Ignacio, Rivero, Antonio, Sinangil, Faruk, Saulle, Irma, Biasin, Mara, Clerici, Mario, Forthal, Donald, Saéz, Maria, and Caruz, Antonio
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GWAS ,HESN ,HIV-1 ,HLA ,KIR ,Humans ,HIV-1 ,HIV Infections ,Receptors ,KIR ,Male ,Female ,HLA Antigens ,Adult ,Viral Load ,Alleles ,Genome-Wide Association Study ,Genotype ,Genetic Predisposition to Disease ,Middle Aged - Abstract
Human leukocyte antigen (HLA) class I/killer cell immunoglobulin-like receptor (KIR) genotypes influence human immunodeficiency virus type 1 (HIV-1) disease progression and viral load, but their role in primary infection is uncertain. Inconsistent results from previous studies suggest that the inoculum size and transmission route-parenteral versus sexual-may influence this association. We conducted a genome-wide association study in a population of people with HIV-1 and HIV-1-exposed seronegative individuals exposed to the virus through the sexual route. Our data do not support any role of the HLA/KIR system in susceptibility to sexually transmitted HIV-1 infection. The genetics basis of HIV-1 viral load and disease progression are distinct from the genetics of HIV resistance, a paradox worth exploring.
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- 2024
4. Genetic Algorithm Based System for Path Planning with Unmanned Aerial Vehicles Swarms in Cell-Grid Environments
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Puente-Castro, Alejandro, Fernandez-Blanco, Enrique, and Rivero, Daniel
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Computer Science - Robotics ,Computer Science - Artificial Intelligence - Abstract
Path Planning methods for autonomously controlling swarms of unmanned aerial vehicles (UAVs) are gaining momentum due to their operational advantages. An increasing number of scenarios now require autonomous control of multiple UAVs, as autonomous operation can significantly reduce labor costs. Additionally, obtaining optimal flight paths can lower energy consumption, thereby extending battery life for other critical operations. Many of these scenarios, however, involve obstacles such as power lines and trees, which complicate Path Planning. This paper presents an evolutionary computation-based system employing genetic algorithms to address this problem in environments with obstacles. The proposed approach aims to ensure complete coverage of areas with fixed obstacles, such as in field exploration tasks, while minimizing flight time regardless of map size or the number of UAVs in the swarm. No specific goal points or prior information beyond the provided map is required. The experiments conducted in this study used five maps of varying sizes and obstacle densities, as well as a control map without obstacles, with different numbers of UAVs. The results demonstrate that this method can determine optimal paths for all UAVs during full map traversal, thus minimizing resource consumption. A comparative analysis with other state-of-the-art approach is presented to highlight the advantages and potential limitations of the proposed method.
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- 2024
5. Mass measurements of neutron-rich nuclides using the Canadian Penning Trap to inform predictions in the $r$-process rare-earth peak region
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Ray, D., Vassh, N., Liu, B., Valverde, A. A., Brodeur, M., Clark, J. A., McLaughlin, G. C., Mumpower, M. R., Orford, R., Porter, W. S., Savard, G., Sharma, K. S., Surman, R., Buchinger, F., Burdette, D. P., Callahan, N., Gallant, A. T., Hoff, D. E. M., Kolos, K., Kondev, F. G., Morgan, G. E., Rivero, F., Santiago-Gonzalez, D., Scielzo, N. D., Varriano, L., Weber, C. M., Wilson, G. E., and Yan, X. L.
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Nuclear Experiment ,Nuclear Theory - Abstract
Studies aiming to determine the astrophysical origins of nuclei produced by the rapid neutron capture process ($r$ process) rely on nuclear properties as inputs for simulations. The solar abundances can be used as a benchmark for such calculations, with the $r$-process rare-earth peak (REP) around mass number ($A$) 164 being of special interest due to its presently unknown origin. With the advancement of rare isotope beam production over the last decade and improvement in experimental sensitivities, many of these REP nuclides have become accessible for measurement. Masses are one of the most critical inputs as they impact multiple nuclear properties, namely the neutron-separation energies, neutron capture rates, $\beta$-decay rates, and $\beta$-delayed neutron emission probabilities. In this work, we report masses of 20 neutron-rich nuclides (along the Ba, La, Ce, Pr, Nd, Pm, Gd, Dy and Ho isotopic chains) produced at the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility at Argonne National Laboratory. The masses were measured with the Canadian Penning trap (CPT) mass spectrometer using the Phase-Imaging Ion-Cyclotron-Resonance (PI-ICR) technique. We then use these new masses along with previously published CPT masses to inform predictions for a Markov Chain Monte Carlo (MCMC) procedure aiming to identify the astrophysical conditions consistent with both solar data and mass measurements. We show that the MCMC responds to this updated mass information, producing refined results for both mass predictions and REP abundances., Comment: 11 pages, 8 figures
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- 2024
6. Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey
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Essakine, Amer, Cheng, Yanqi, Cheng, Chun-Wun, Zhang, Lipei, Deng, Zhongying, Zhu, Lei, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Implicit Neural Representations (INRs) have emerged as a paradigm in knowledge representation, offering exceptional flexibility and performance across a diverse range of applications. INRs leverage multilayer perceptrons (MLPs) to model data as continuous implicit functions, providing critical advantages such as resolution independence, memory efficiency, and generalisation beyond discretised data structures. Their ability to solve complex inverse problems makes them particularly effective for tasks including audio reconstruction, image representation, 3D object reconstruction, and high-dimensional data synthesis. This survey provides a comprehensive review of state-of-the-art INR methods, introducing a clear taxonomy that categorises them into four key areas: activation functions, position encoding, combined strategies, and network structure optimisation. We rigorously analyse their critical properties, such as full differentiability, smoothness, compactness, and adaptability to varying resolutions while also examining their strengths and limitations in addressing locality biases and capturing fine details. Our experimental comparison offers new insights into the trade-offs between different approaches, showcasing the capabilities and challenges of the latest INR techniques across various tasks. In addition to identifying areas where current methods excel, we highlight key limitations and potential avenues for improvement, such as developing more expressive activation functions, enhancing positional encoding mechanisms, and improving scalability for complex, high-dimensional data. This survey serves as a roadmap for researchers, offering practical guidance for future exploration in the field of INRs. We aim to foster new methodologies by outlining promising research directions for INRs and applications.
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- 2024
7. Soft Condorcet Optimization for Ranking of General Agents
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Lanctot, Marc, Larson, Kate, Kaisers, Michael, Berthet, Quentin, Gemp, Ian, Diaz, Manfred, Maura-Rivero, Roberto-Rafael, Bachrach, Yoram, Koop, Anna, and Precup, Doina
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Computer Science - Multiagent Systems ,Computer Science - Machine Learning - Abstract
A common way to drive progress of AI models and agents is to compare their performance on standardized benchmarks. Comparing the performance of general agents requires aggregating their individual performances across a potentially wide variety of different tasks. In this paper, we describe a novel ranking scheme inspired by social choice frameworks, called Soft Condorcet Optimization (SCO), to compute the optimal ranking of agents: the one that makes the fewest mistakes in predicting the agent comparisons in the evaluation data. This optimal ranking is the maximum likelihood estimate when evaluation data (which we view as votes) are interpreted as noisy samples from a ground truth ranking, a solution to Condorcet's original voting system criteria. SCO ratings are maximal for Condorcet winners when they exist, which we show is not necessarily true for the classical rating system Elo. We propose three optimization algorithms to compute SCO ratings and evaluate their empirical performance. When serving as an approximation to the Kemeny-Young voting method, SCO rankings are on average 0 to 0.043 away from the optimal ranking in normalized Kendall-tau distance across 865 preference profiles from the PrefLib open ranking archive. In a simulated noisy tournament setting, SCO achieves accurate approximations to the ground truth ranking and the best among several baselines when 59\% or more of the preference data is missing. Finally, SCO ranking provides the best approximation to the optimal ranking, measured on held-out test sets, in a problem containing 52,958 human players across 31,049 games of the classic seven-player game of Diplomacy.
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- 2024
8. A novel conjunction filter based on the minimum distance between perturbed trajectories
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Rivero, Ana S., Baù, Giulio, Vazquez, Rafael, and Bombardelli, Claudio
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Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The increasing congestion in the near-Earth space environment has amplified the need for robust and efficient conjunction analysis techniques including the computation of the minimum distance between orbital paths in the presence of perturbations. After showing that classical Minimum Orbit Intersection Distance (MOID) computation schemes are unsuitable to treat Earth orbiting objects, the article presents an analytical approach to provide a more accurate estimate of the true distance between perturbed trajectories by incorporating the effect of zonal harmonics of arbitrary order. Cook's linear secular theory for the motion of the eccentricity vector is extended to include higher order eccentricity effects and applied to the computation of the minimum and maximum radii attained by two orbits at their mutual nodes, which can be employed to estimate the true distance between the two orbital paths and to establish an efficient algorithm for determining or excluding potential conjunctions. Extensive testing and validation are conducted using a high-fidelity propagator and a comprehensive dataset of resident space objects. The results demonstrate an accuracy below the km level for the orbit distance computation in 99\% of cases, which enables high-efficiency conjunction filtering.
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- 2024
9. RESISTO Project: Automatic detection of operation temperature anomalies for power electric transformers using thermal imaging
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López-García, David, Segovia, Fermín, Rodríguez-Rivero, Jacob, Ramírez, Javier, Pérez, David, Serrano, Raúl, and Górriz, Juan Manuel
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Electrical Engineering and Systems Science - Systems and Control ,Electrical Engineering and Systems Science - Signal Processing - Abstract
The RESISTO project represents a pioneering initiative in Europe aimed at enhancing the resilience of the power grid through the integration of advanced technologies. This includes artificial intelligence and thermal surveillance systems to mitigate the impact of extreme meteorological phenomena. RESISTO endeavors to predict, prevent, detect, and recover from weather-related incidents, ultimately enhancing the quality of service provided and ensuring grid stability and efficiency in the face of evolving climate challenges. In this study, we introduce one of the fundamental pillars of the project: a monitoring system for the operating temperature of different regions within power transformers, aiming to detect and alert early on potential thermal anomalies. To achieve this, a distributed system of thermal cameras for real-time temperature monitoring has been deployed in The Do\~nana National Park, alongside servers responsible for the storing, analyzing, and alerting of any potential thermal anomalies. An adaptive prediction model was developed for temperature forecasting, which learns online from the newly available data. In order to test the long-term performance of the proposed solution, we generated a synthetic temperature database for the whole of the year 2022. Overall, the proposed system exhibits promising capabilities in predicting and detecting thermal anomalies in power electric transformers, showcasing potential applications in enhancing grid reliability and preventing equipment failures.
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- 2024
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10. RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena
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Rodríguez-Rivero, Jacob, López-García, David, Segovia, Fermín, Ramírez, Javier, Górriz, Juan Manuel, Serrano, Raúl, Pérez, David, Maza, Iván, Ollero, Aníbal, Solà, Pol Paradell, Selga, Albert Gili, Domínguez-García, José Luis, Romero, A., Berro, A., Domínguez, Rocío, and Prieto, Inmaculada
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Computer Science - Other Computer Science ,Electrical Engineering and Systems Science - Systems and Control - Abstract
The RESISTO project, a pioneer innovation initiative in Europe, endeavors to enhance the resilience of electrical networks against extreme weather events and associated risks. Emphasizing intelligence and flexibility within distribution networks, RESISTO aims to address climatic and physical incidents comprehensively, fostering resilience across planning, response, recovery, and adaptation phases. Leveraging advanced technologies including AI, IoT sensors, and aerial robots, RESISTO integrates prediction, detection, and mitigation strategies to optimize network operation. This article summarizes the main technical aspects of the proposed solutions to meet the aforementioned objectives, including the development of a climate risk detection platform, an IoT-based monitoring and anomaly detection network, and a fleet of intelligent aerial robots. Each contributing to the project's overarching objectives of enhancing network resilience and operational efficiency.
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- 2024
11. Determining sensor geometry and gain in a wearable MEG system
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Hill, Ryan M., Rivero, Gonzalo Reina, Tyler, Ashley J., Schofield, Holly, Doyle, Cody, Osborne, James, Bobela, David, Rier, Lukas, Gibson, Joseph, Tanner, Zoe, Boto, Elena, Bowtell, Richard, Brookes, Matthew J., Shah, Vishal, and Holmes, Niall
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Physics - Medical Physics - Abstract
Optically pumped magnetometers (OPMs) are compact and lightweight sensors that can measure magnetic fields generated by current flow in neuronal assemblies in the brain. Such sensors enable construction of magnetoencephalography (MEG) instrumentation, with significant advantages over conventional MEG devices including adaptability to head size, enhanced movement tolerance, lower complexity and improved data quality. However, realising the potential of OPMs depends on our ability to perform system calibration, which means finding sensor locations, orientations, and the relationship between the sensor output and magnetic field (termed sensor gain). Such calibration is complex in OPMMEG since, for example, OPM placement can change from subject to subject (unlike in conventional MEG where sensor locations or orientations are fixed). Here, we present two methods for calibration, both based on generating well-characterised magnetic fields across a sensor array. Our first device (the HALO) is a head mounted system that generates dipole like fields from a set of coils. Our second (the matrix coil (MC)) generates fields using coils embedded in the walls of a magnetically shielded room. Our results show that both methods offer an accurate means to calibrate an OPM array (e.g. sensor locations within 2 mm of the ground truth) and that the calibrations produced by the two methods agree strongly with each other. When applied to data from human MEG experiments, both methods offer improved signal to noise ratio after beamforming suggesting that they give calibration parameters closer to the ground truth than factory settings and presumed physical sensor coordinates and orientations. Both techniques are practical and easy to integrate into real world MEG applications. This advances the field significantly closer to the routine use of OPMs for MEG recording., Comment: 36 pages, 10 figures
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- 2024
12. Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization
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Wu, Hongtao, Yang, Yijun, Aviles-Rivero, Angelica I, Ren, Jingjing, Chen, Sixiang, Chen, Haoyu, and Zhu, Lei
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Snow degradations present formidable challenges to the advancement of computer vision tasks by the undesirable corruption in outdoor scenarios. While current deep learning-based desnowing approaches achieve success on synthetic benchmark datasets, they struggle to restore out-of-distribution real-world snowy videos due to the deficiency of paired real-world training data. To address this bottleneck, we devise a new paradigm for video desnowing in a semi-supervised spirit to involve unlabeled real data for the generalizable snow removal. Specifically, we construct a real-world dataset with 85 snowy videos, and then present a Semi-supervised Video Desnowing Network (SemiVDN) equipped by a novel Distribution-driven Contrastive Regularization. The elaborated contrastive regularization mitigates the distribution gap between the synthetic and real data, and consequently maintains the desired snow-invariant background details. Furthermore, based on the atmospheric scattering model, we introduce a Prior-guided Temporal Decoupling Experts module to decompose the physical components that make up a snowy video in a frame-correlated manner. We evaluate our SemiVDN on benchmark datasets and the collected real snowy data. The experimental results demonstrate the superiority of our approach against state-of-the-art image- and video-level desnowing methods.
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- 2024
13. Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs
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Cheng, Chun-Wun, Huang, Jiahao, Zhang, Yi, Yang, Guang, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I
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Computer Science - Machine Learning ,Mathematics - Numerical Analysis - Abstract
Partial differential equations (PDEs) are widely used to model complex physical systems, but solving them efficiently remains a significant challenge. Recently, Transformers have emerged as the preferred architecture for PDEs due to their ability to capture intricate dependencies. However, they struggle with representing continuous dynamics and long-range interactions. To overcome these limitations, we introduce the Mamba Neural Operator (MNO), a novel framework that enhances neural operator-based techniques for solving PDEs. MNO establishes a formal theoretical connection between structured state-space models (SSMs) and neural operators, offering a unified structure that can adapt to diverse architectures, including Transformer-based models. By leveraging the structured design of SSMs, MNO captures long-range dependencies and continuous dynamics more effectively than traditional Transformers. Through extensive analysis, we show that MNO significantly boosts the expressive power and accuracy of neural operators, making it not just a complement but a superior framework for PDE-related tasks, bridging the gap between efficient representation and accurate solution approximation.
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- 2024
14. Precise Mass Measurement of the Longest Odd-Odd Chain of \boldmath $1^+$ Ground States
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Liu, B., Brodeur, M., Clark, J. A., Dedes, I., Dudek, J., Kondev, F. G., Ray, D., Savard, G., Valverde, A. A., Burdette, D. P., Houff, A. M., Orford, R., Porter, W. S., Rivero, F., Sharma, K. S., and Varriano, L.
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Nuclear Experiment ,Nuclear Theory - Abstract
Precise mass measurements of the odd-odd $^{108, 110, 112, 114, 116}$Rh ground and isomeric states were performed using the Canadian Penning Trap at Argonne National Laboratory, showing a good agreement with recent JYFLTRAP measurements. A new possible isomeric state of $^{114}$Rh was also observed. These isotopes are part of the longest odd-odd chain of identical ground state spin-parity assignment, of 1$^+$, spanning $^{104-118}$Rh, despite being in a region of deformation. Realistic phenomenological mean-field calculations using ``universal'' Wood-Saxon Hamiltonian were performed, explaining this phenomenon for the first time. In addition, multi-quasiparticle blocking calculations were conducted to study the configuration of low-lying states in the odd-odd Rh nuclei and elucidate the observed anomalous isomeric yield ratio of $^{114}$Rh.
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- 2024
15. Correction: Impact of an enhanced screening program on the detection of non-AIDS neoplasias in patients with human immunodeficiency virus infection
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M. Masiá, S. Padilla, G. Estañ, J. Portu, A. Silva, A. Rivero, A. González-Cordón, L. García-Fraile, O. Martínez, E. Bernal, C. Galera, V. Boix Martínez, J. Macias, M. Montero, D. García-Rosado, M. J. Vivancos-Gallego, J. Llenas-García, M. Torralba, J. A. García, V. Agulló, M. Fernández-González, F. Gutiérrez, E. Martínez, and IMPAC-NEO Study Group
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Medicine (General) ,R5-920 - Published
- 2023
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16. Striving for Relationship-Centered Schools: Insights from a Community-Based Transformation Campaign. Brief
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Learning Policy Institute, Laura E. Hernández, and Eddie Rivero
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While research indicates that relationship-centered environments support student learning and success, it has been difficult to redesign secondary schools based on the factory model in ways that center relationships, particularly at the secondary level. This brief to the full report focuses on efforts to advance relationship-centering schooling in high schools. It examines the Relationship Centered Schools (RCS) campaign, a youth-led effort supported by Californians for Justice (CFJ) and conducted in collaboration with educators and district leaders. The study focuses on two settings--the Long Beach Unified School District and Fresno's McLane High School--and the efforts of local actors to center relationship-building as a catalyst for change.
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- 2024
17. Meta-Narrative Review of Gender Portrayal in Disney Movies for Young Children and Its Pedagogical Implications
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Xuan Jiang, Linlin Zhang, Diana Rivero, and Brittany Torres
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Many of Disney movies have been criticized for perpetuating traditional gender stereotypes which constrain opportunities for children at large. Its recent characters have also incurred heated discussions on gender portrayal. Moreover, stereotypes of gender roles, developed early on, can exert an immediate impact on individuals' behaviors and utterances and a long-term impact on individuals' perceived options academically, professionally, personally, and socially. Recognizing the significance of this matter, this paper employed a meta-narrative review to collect and conceptually and empirically synthesize previous literature on the impact of Disney movies on young children's gender awareness. Through an academic database search, 49 articles were collected using combinations of the keywords "Disney character, Disney movie, young children, early childhood education, classroom practices," and "gender." Furthermore, this review, in the pedagogical implication section, highlights the authors' call for teachers to develop critical mindfulness of gender and shares hands-on activities for children to play with Disney characters in a reconstructive and agentic way.
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- 2024
18. The comprehensive management of patients with rhino-orbito-cerebral mucormycosis; a perspective from antifungal treatment to prosthetic rehabilitation: A descriptive cohort study
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Castrejon, Angelica Julian, Hernandez Martinez, Rosa Marene, Mendez, Diana Rivero, Gil Velazquez, Israel Nayensei, Rodriguez Pina, Juan Heriberto, Salgado Camacho, Juan Manuel, Calva, Nicolas Teyes, Espindola Chavarria, Sayuri I, Meza-Meneses, Patricia A, and Castro-Fuentes, Carlos Alberto
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- 2024
19. AlgoRitmo Literacies in Gaming: Leveraging Chicanx Praxis to Reimagine AI Systems
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Arturo Cortez, José Ramón Lizárraga, and Edward Rivero
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This article reports on findings from a social design-based study conducted with an intergenerational group of youth, educators and researchers participating in the Learning to Transform (LiTT) Gaming Lab. We advance the notion of AlgoRitmo Literacies, to highlight the ingenuity of youth and educators as they used a tool called Character AI to author lore emerging within a virtual city called LiTT City. We conceptualize AlgoRitmo--a play on the word algorithm--as part inquiry and reflection (the algo or "something" of AI tools), and part action and future-oriented (ritmo as in movement). Inspired by cosmogonies influenced by Coyolxauhqui, the fragmented Aztec moon goddess, this paper illustrates how young people reconfigure AI artifacts, reshape relationships with AI-governed non-playable characters, and repurpose AI tools to envision alternative futures and identities. In identifying AlgoRitmo Literacies, we provide examples of how ChicanX communities subvert ideologies embedded in AI through creative and ingenious interventions in video games and the construction of cyborg Chicanx subjectivities. This paper offers implications for how educators across content areas can leverage gaming, and AI tools, toward consequential literacy development.
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- 2024
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20. Association of personalized and tumor-informed ctDNA with patient survival outcomes in pancreatic adenocarcinoma.
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Botta, Gregory, Abdelrahim, Maen, Drengler, Ronald, Aushev, Vasily, Esmail, Abdullah, Laliotis, George, Brewer, Chris, George, Giby, Abbate, Steven, Chandana, Sreenivasa, Tejani, Mohamedtaki, Malla, Midhun, Bansal, Dhruv, Rivero-Hinojosa, Samuel, Spickard, Erik, McCormick, Nicole, Cecchini, Michael, Lacy, Jill, Fei, Naomi, Kasi, Pashtoon, Kasi, Anup, Dayyani, Farshid, Hanna, Diana, Sharma, Shruti, Malhotra, Meenakshi, Aleshin, Alexey, Liu, Minetta, and Jurdi, Adham
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KRAS ,ctDNA ,molecular residual disease ,pancreatic adenocarcinoma ,Humans ,Circulating Tumor DNA ,Male ,Pancreatic Neoplasms ,Female ,Aged ,Middle Aged ,Retrospective Studies ,Carcinoma ,Pancreatic Ductal ,Aged ,80 and over ,Precision Medicine ,Adult ,Biomarkers ,Tumor ,Adenocarcinoma - Abstract
INTRODUCTION: Personalized and tumor-informed circulating tumor DNA (ctDNA) testing is feasible and allows for molecular residual disease (MRD) identification in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: In this retrospective analysis of commercial cases from multiple US institutions, personalized, tumor-informed, whole-exome sequenced, and germline-controlled ctDNA levels were quantified and analyzed in patients with PDAC. Plasma samples (n = 1329) from 298 clinically validated patients were collected at diagnosis, perioperatively (MRD-window; within 2-12 weeks after surgery, before therapy), and during surveillance (>12 weeks post-surgery if no ACT or starting 4 weeks post-ACT) from November 2019 to March 2023. RESULTS: Of the initially diagnosed patients with stages I-III PDAC who went for resection, the median follow-up time from surgery was 13 months (range 0.1-214). Positive ctDNA detection rates were 29% (29/100) and 29.6% (45/152) during the MRD and surveillance windows, respectively. Positive ctDNA detection was significantly associated with shorter DFS within the MRD window (median DFS of 6.37 months for ctDNA-positive vs 33.31 months for ctDNA-negative patients; HR: 5.45, P
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- 2024
21. Photonic bands and normal mode splitting in optical lattices interacting with cavities
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Courteille, Philippe Wilhelm, Rivero, Dalila, de França, Gustavo Henrique, Junior, Claudio Alves Pessoa, Cipris, Ana, Portela, Mayerlin Núñez, Teixeira, Raul Celistrino, and Slama, Sebastian
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Quantum Physics ,Physics - Atomic Physics ,Physics - Optics - Abstract
Strong collective interaction of atoms with an optical cavity causes normal mode splitting of the cavity's resonances, whose width is given by the collective coupling strength. At low optical density of the atomic cloud the intensity distribution of light in the cavity is ruled by the cavity's mode function, which is solely determined by its geometry. In this regime the dynamics of the coupled atom-cavity system is conveniently described by the open Dicke model, which we apply to calculating normal mode splitting generated by periodically ordered clouds in linear and ring cavities. We also show how to use normal mode splitting as witness for Wannier-Bloch oscillations in the tight-binding limit. At high optical density the atomic distribution contributes to shaping the mode function. This regime escapes the open Dicke model, but can be treated by a transfer matrix model provided the saturation parameter is low. Applying this latter model to an atomic cloud periodically ordered into a one-dimensional lattice, we observe the formation of photonic bands gaps competing with the normal mode splitting. We discuss the limitations of both models and point out possible pathways to generalized theories., Comment: 10 pages, 14 figures
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- 2024
22. Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging
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Chow, Tsz Ching, Huang, Chaoyan, Wu, Zhongming, Zeng, Tieyong, and Aviles-Rivero, Angelica I.
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Mathematics - Optimization and Control - Abstract
Imaging tasks are typically tackled using a structured optimization framework. This paper delves into a class of algorithms for difference-of-convex (DC) structured optimization, focusing on minimizing a DC function along with a possibly nonconvex function. Existing DC algorithm (DCA) versions often fail to effectively handle nonconvex functions or exhibit slow convergence rates. We propose a novel inertial proximal DC algorithm in Bregman geometry, named iBPDCA, designed to address nonconvex terms and enhance convergence speed through inertial techniques. We provide a detailed theoretical analysis, establishing both subsequential and global convergence of iBPDCA via the Kurdyka-{\L}ojasiewicz property. Additionally, we introduce a Plug-and-Play variant, PnP-iBPDCA, which employs a deep neural network-based prior for greater flexibility and robustness while ensuring theoretical convergence. We also establish that the Gaussian gradient step denoiser used in our method is equivalent to evaluating the Bregman proximal operator for an implicitly weakly convex functional. We extensively validate our method on Rician noise and phase retrieval. We demonstrate that iBPDCA surpasses existing state-of-the-art methods.
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- 2024
23. Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction
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Yang, Liutao, Huang, Jiahao, Fang, Yingying, Aviles-Rivero, Angelica I, Schonlieb, Carola-Bibiane, Zhang, Daoqiang, and Yang, Guang
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Sparse-View Computed Tomography (SVCT) offers low-dose and fast imaging but suffers from severe artifacts. Optimizing the sampling strategy is an essential approach to improving the imaging quality of SVCT. However, current methods typically optimize a universal sampling strategy for all types of scans, overlooking the fact that the optimal strategy may vary depending on the specific scanning task, whether it involves particular body scans (e.g., chest CT scans) or downstream clinical applications (e.g., disease diagnosis). The optimal strategy for one scanning task may not perform as well when applied to other tasks. To address this problem, we propose a deep learning framework that learns task-specific sampling strategies with a multi-task approach to train a unified reconstruction network while tailoring optimal sampling strategies for each individual task. Thus, a task-specific sampling strategy can be applied for each type of scans to improve the quality of SVCT imaging and further assist in performance of downstream clinical usage. Extensive experiments across different scanning types provide validation for the effectiveness of task-specific sampling strategies in enhancing imaging quality. Experiments involving downstream tasks verify the clinical value of learned sampling strategies, as evidenced by notable improvements in downstream task performance. Furthermore, the utilization of a multi-task framework with a shared reconstruction network facilitates deployment on current imaging devices with switchable task-specific modules, and allows for easily integrate new tasks without retraining the entire model.
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- 2024
24. Conditioning the logistic continuous-state branching process on non-extinction via its total progeny
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Foucart, Clément, Rivero, Víctor, and Winter, Anita
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Mathematics - Probability - Abstract
The problem of conditioning a continuous-state branching process with quadratic competition (logistic CB process) on non-extinction is investigated. We first establish that non-extinction is equivalent to the total progeny of the population being infinite. The conditioning we propose is then designed by requiring the total progeny to exceed arbitrarily large exponential random variables. This is related to a Doob's $h$-transform with an explicit excessive function $h$. The $h$-transformed process, i.e. the conditioned process, is shown to have a finite lifetime almost surely (it is either killed or it explodes continuously). When starting from positive values, the conditioned process is furthermore characterized, up to its lifetime, as the solution to a certain stochastic equation with jumps. The latter superposes the dynamics of the initial logistic CB process with an additional density-dependent immigration term. Last, it is established that the conditioned process can be starting from zero. Key tools employed are a representation of the logistic CB process through a time-changed generalized Ornstein-Uhlenbeck process, as well as Laplace and Siegmund duality relationships with auxiliary diffusion processes.
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- 2024
25. Contrastive Learning with Adaptive Neighborhoods for Brain Age Prediction on 3D Stiffness Maps
- Author
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Träuble, Jakob, Hiscox, Lucy, Johnson, Curtis, Schönlieb, Carola-Bibiane, Schierle, Gabriele Kaminski, and Aviles-Rivero, Angelica
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Computer Science - Machine Learning - Abstract
In the field of neuroimaging, accurate brain age prediction is pivotal for uncovering the complexities of brain aging and pinpointing early indicators of neurodegenerative conditions. Recent advancements in self-supervised learning, particularly in contrastive learning, have demonstrated greater robustness when dealing with complex datasets. However, current approaches often fall short in generalizing across non-uniformly distributed data, prevalent in medical imaging scenarios. To bridge this gap, we introduce a novel contrastive loss that adapts dynamically during the training process, focusing on the localized neighborhoods of samples. Moreover, we expand beyond traditional structural features by incorporating brain stiffness - a mechanical property previously underexplored yet promising due to its sensitivity to age-related changes. This work presents the first application of self-supervised learning to brain mechanical properties, using compiled stiffness maps from various clinical studies to predict brain age. Our approach, featuring dynamic localized loss, consistently outperforms existing state-of-the-art methods, demonstrating superior performance and paving the way for new directions in brain aging research.
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- 2024
26. Diagonalization of large many-body Hamiltonians on a quantum processor
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Yoshioka, Nobuyuki, Amico, Mirko, Kirby, William, Jurcevic, Petar, Dutt, Arkopal, Fuller, Bryce, Garion, Shelly, Haas, Holger, Hamamura, Ikko, Ivrii, Alexander, Majumdar, Ritajit, Minev, Zlatko, Motta, Mario, Pokharel, Bibek, Rivero, Pedro, Sharma, Kunal, Wood, Christopher J., Javadi-Abhari, Ali, and Mezzacapo, Antonio
- Subjects
Quantum Physics - Abstract
The estimation of low energies of many-body systems is a cornerstone of computational quantum sciences. Variational quantum algorithms can be used to prepare ground states on pre-fault-tolerant quantum processors, but their lack of convergence guarantees and impractical number of cost function estimations prevent systematic scaling of experiments to large systems. Alternatives to variational approaches are needed for large-scale experiments on pre-fault-tolerant devices. Here, we use a superconducting quantum processor to compute eigenenergies of quantum many-body systems on two-dimensional lattices of up to 56 sites, using the Krylov quantum diagonalization algorithm, an analog of the well-known classical diagonalization technique. We construct subspaces of the many-body Hilbert space using Trotterized unitary evolutions executed on the quantum processor, and classically diagonalize many-body interacting Hamiltonians within those subspaces. These experiments show that quantum diagonalization algorithms are poised to complement their classical counterpart at the foundation of computational methods for quantum systems., Comment: 25 pages, 13 figures
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- 2024
27. NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning
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Zhang, Yi, Cheng, Chun-Wun, Yu, Ke, He, Zhihai, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I.
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Computer Science - Computer Vision and Pattern Recognition - Abstract
In this paper, we consider the problem of prototype-based vision-language reasoning problem. We observe that existing methods encounter three major challenges: 1) escalating resource demands and prolonging training times, 2) contending with excessive learnable parameters, and 3) fine-tuning based only on a single modality. These challenges will hinder their capability to adapt Vision-Language Models (VLMs) to downstream tasks. Motivated by this critical observation, we propose a novel method called NODE-Adapter, which utilizes Neural Ordinary Differential Equations for better vision-language reasoning. To fully leverage both visual and textual modalities and estimate class prototypes more effectively and accurately, we divide our method into two stages: cross-modal prototype construction and cross-modal prototype optimization using neural ordinary differential equations. Specifically, we exploit VLM to encode hand-crafted prompts into textual features and few-shot support images into visual features. Then, we estimate the textual prototype and visual prototype by averaging the textual features and visual features, respectively, and adaptively combine the textual prototype and visual prototype to construct the cross-modal prototype. To alleviate the prototype bias, we then model the prototype optimization process as an initial value problem with Neural ODEs to estimate the continuous gradient flow. Our extensive experimental results, which cover few-shot classification, domain generalization, and visual reasoning on human-object interaction, demonstrate that the proposed method significantly outperforms existing state-of-the-art approaches.
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- 2024
28. LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos
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Xu, Huihui, Yang, Yijun, Aviles-Rivero, Angelica I, Yang, Guang, Qin, Jing, and Zhu, Lei
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Regular screening and early discovery of uterine fibroid are crucial for preventing potential malignant transformations and ensuring timely, life-saving interventions. To this end, we collect and annotate the first ultrasound video dataset with 100 videos for uterine fibroid segmentation (UFUV). We also present Local-Global Reciprocal Network (LGRNet) to efficiently and effectively propagate the long-term temporal context which is crucial to help distinguish between uninformative noisy surrounding tissues and target lesion regions. Specifically, the Cyclic Neighborhood Propagation (CNP) is introduced to propagate the inter-frame local temporal context in a cyclic manner. Moreover, to aggregate global temporal context, we first condense each frame into a set of frame bottleneck queries and devise Hilbert Selective Scan (HilbertSS) to both efficiently path connect each frame and preserve the locality bias. A distribute layer is then utilized to disseminate back the global context for reciprocal refinement. Extensive experiments on UFUV and three public Video Polyp Segmentation (VPS) datasets demonstrate consistent improvements compared to state-of-the-art segmentation methods, indicating the effectiveness and versatility of LGRNet. Code, checkpoints, and dataset are available at https://github.com/bio-mlhui/LGRNet, Comment: MICCAI2024 Early Accept
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- 2024
29. Stability of (sub)critical non-local spatial branching processes with and without immigration
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Horton, Emma, Kyprianou, Andreas E., Martín-Chávez, Pedro, Powell, Ellen, and Rivero, Victor
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Mathematics - Probability ,60J80, 60J25 - Abstract
We consider the setting of either a general non-local branching particle process or a general non-local superprocess, in both cases, with and without immigration. Under the assumption that the mean semigroup has a Perron-Frobenious type behaviour for the immigrated mass, as well as the existence of second moments, we consider necessary and sufficient conditions that ensure limiting distributional stability. More precisely, our first main contribution pertains to proving the asymptotic Kolmogorov survival probability and Yaglom limit for critical non-local branching particle systems and superprocesses under a second moment assumption on the offspring distribution. Our results improve on existing literature by removing the requirement of bounded offspring in the particle setting [21] and generalising [43] to allow for non-local branching mechanisms. Our second main contribution pertains to the stability of both critical and sub-critical non-local branching particle systems and superprocesses with immigration. At criticality, we show that the scaled process converges to a Gamma distribution under a necessary and sufficient integral test. At subcriticality we show stability of the process, also subject to an integral test. In these cases, our results complement classical results for (continuous-time) Galton-Watson processes with immigration and continuous-state branching processes with immigration; see [22,40,42,48,51], among others. In the setting of superprocesses, the only work we know of at this level of generality is summarised in [34]. The proofs of our results, both with and without immigration, appeal to similar technical approaches and accordingly, we include the results together in this paper., Comment: 35 pages
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- 2024
30. An interpretation of scalars in SO(32)
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Rivero, Alejandro
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High Energy Physics - Phenomenology - Abstract
We propose an interpretation for the adjoint representation of the $SO(32)$ group to classify the scalars of a generic Supersymmetric Standard Model having just three generations of particles, via a flavour group $SU(5)$. We show that this same interpretation arises from a simple postulate of self-consistence of composites for these scalars. The model looks only for colour and electric charge, and it pays the cost of an additional chiral $+4/3$ quark per generation., Comment: 8 pages, added discussion on mass spectrum and partners
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- 2024
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31. Pathway towards an ideal and sustainable framework agreement for the public procurement of vaccines in Spain: a multi-criteria decision analysis
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N. Zozaya González, B. Alcalá Revilla, P. Arrazola Martínez, J. R. Chávarri Bravo, I. Cuesta Esteve, A. J. García Rojas, F. Martinón-Torres, E. Redondo Margüello, A. Rivero Cuadrado, S. Tamames Gómez, J. Villaseca Carmena, and A. Hidalgo-Vega
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vaccines ,award criteria ,public procurement ,spain ,multi-criteria decision analysis ,framework agreement ,Immunologic diseases. Allergy ,RC581-607 ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Objective: To advance the development of an ideal and sustainable framework agreement for the public procurement of vaccines in Spain, and to agree on the desirable award criteria and their relative weight. Methods: A multidisciplinary committee of seven health-care professionals and managers developed a partial multi-criteria decision analysis to determine the award criteria that should be considered and their specific weights for the public procurement of routine vaccines and seasonal influenza vaccines, considering their legal viability. A re-test of the results was carried out. The current situation was analyzed through 118 tender specifications and compared to the ideal framework. Results: Price is the prevailing award criterion for the public procurement of both routine (weighting of 60% versus 40% for all other criteria) and influenza (36% versus 64%) vaccines. Ideally, 22 criteria should be considered for routine vaccines, grouped and weighted into five domains: efficacy (weighting of 29%), economic aspects (27%), vaccine characteristics (22%), presentation form and packaging (13%), and others (9%). Per criteria set, price was the most important criterion (22%), followed by effectiveness (9%), and composition/formulation (7%). Regarding influenza vaccines, 20 criteria were selected, grouped, and weighted: efficacy (29%), economic aspects (25%), vaccine characteristics (20%), presentation form and packaging (16%), and others (11%). Per criteria set, price was also the most relevant criterion (19%), followed by composition/formulation (8%), and effectiveness (8%). Conclusions: Contrary to the current approach, technical award criteria should prevail over economic criteria in an ideal and sustainable framework agreement for the public procurement of vaccines.
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- 2020
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32. Physicochemical Properties of Two Mexican Stingless Bee Honeys to Strengthen Their Biocultural Value
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Xolalpa-Aroche, Aurora, Hernández-Mena, David I., Moguel-Chin, Wilson I., Contreras-Peruyero, Haydeé, Rivero-Cruz, Blanca E., Ortiz-Vázquez, Elizabeth, Rivero-Cruz, J. Fausto, M., Rodrigo A. Velarde, and Delgado-Suárez, Enrique J.
- Published
- 2024
- Full Text
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33. Striving for Relationship-Centered Schools: Insights from a Community-Based Transformation Campaign
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Learning Policy Institute, Laura E. Hernández, and Eddie Rivero
- Abstract
In recent years, there has been a growing understanding that consistent developmental relationships support student learning and well-being. Research shows that youth who have positive connections with adults at their schools demonstrate higher levels of motivation, self-esteem, and prosocial behavior than their peers in less relationship-centered contexts. Relationship-centered schools also enable a range of positive student academic outcomes, including increased attendance, graduation rates, achievement on English language arts and math assessments, and college-going rates. Relationship-centered schools challenge ingrained structures that have come to characterize U.S. secondary schools and often inhibit their growth and sustainability through institutional, normative, and policy barriers. While research indicates that relationship-centered environments positively support student learning and success, it has been difficult to build and sustain schools with relationships at their foundation, particularly at the secondary level. This report focuses on one relationship-centered high school transformation effort--the Relationship Centered Schools (RCS) campaign, a youth-led effort supported by the community-based organization Californians for Justice (CFJ). Through interviews with CFJ organizers, district and school leaders, practitioners, and current and former youth organizers, this report highlights examples of uptake in two settings--the Long Beach Unified School District and Fresno's McLane High School. The cases demonstrate how local schools and districts have furthered relationship-centered schooling, the conditions and factors that have enabled or hindered RCS work, and the emerging impacts of RCS efforts on practice and policy.
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- 2023
34. P1277: MUTATIONAL LANDSCAPE AND COPY NUMBER ALTERATIONS IN TESTICULAR LARGE B-CELL LYMPHOMA
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C. López, A. Rivas-Delgado, F. Nadeu, M. Grau, A. Rivero, J. Boschs-Schips, M. Alcoceba, G. Tapia, L. Luizaga, C. Bárcena, N. Kelleher, M. Pablo, O. Balague, G. Frigola, N. Villamor, L. Magnano, T. Baumann, A. Muntañola, J. M. Sancho-Cia, A. M. García-Sancho, E. Gonzalez Barca, F. Climent, E. Campo, E. Giné, A. López-Guillermo, and S. Beà
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Diseases of the blood and blood-forming organs ,RC633-647.5 - Published
- 2022
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35. PB2088: IMMUNE PROFILE OF PATIENTS WITH FOLLICULAR LYMPHOMA ASSESSED BY FLOW CYTOMETRY IN PERIPHERAL BLOOD: CHARACTERISTICS AT DIAGNOSIS AND AT RELAPSE OF THE DISEASE
- Author
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A. Rivero Arango, P. Mozas, J. Correa, A. Rivas-Delgado, F. Araujo-Ayala, K. Guinetti, A. Bataller, M. Condom, A. Gaya, J. Delgado, E. Giné, P. Perez-Galán, E. Campo, A. Vlagea, E. Matutes, A. López-Guillermo, N. Villamor, and L. Magnano
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Diseases of the blood and blood-forming organs ,RC633-647.5 - Published
- 2022
- Full Text
- View/download PDF
36. Beyond Building Blocks: A Reorganization of Mathematical Content
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Ana Patricia García-Amado, Maythe García-Rivero, José Luis Cruz-Canales, Rubén Abraham Moreno Segura, and Asuman Oktaç
- Abstract
The aim of this study is to explore the possibility of introducing the general notions of function and inverse function through a mathematical activity on linear functions, focusing on the quantitative meaning associated to the connection between a relation and its inverse. We present a genetic decomposition, that is, a viable cognitive path for learning these introductory concepts, in terms of mental structures and mechanisms, from the viewpoint of APOS (Action-Process-Object-Schema) theory. One of the innovative aspects of this study consists in the design of a genetic decomposition that involves the construction of two concepts. Through interviews, we explore the conceptions that two high school students--who had not been introduced to the function concept before--developed in connection with the notions in question. Our results confirm that not only it is possible to study a relation and its inverse together, but also doing that can enhance the understanding of the meanings involved in the mathematical relation. This leads us to question the learning of mathematics being linear, and to open a discussion about the organization of mathematical content for instructional purposes. We offer suggestions for further research both involving other mathematical concepts, and in terms of theoretical constructs.
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- 2024
37. Bacillary hemoglobinuria in beef cattle infected with Fascioloides magna in Missouri.
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Ierardi, Rosalie, Burnum, Annabelle, Camp, Lauren, Delaney, Lauren, Gull, Tamara, Havis, Brett, Johnson, Gayle, Kim, Dae, Kuroki, Kei, Mammone, Renata, Mitchell, William, Navarro, Mauricio, Rivero, Luis, Shapiro, Karen, Smith, Amanda, Valerio, Courtney, Williams, Fred, Zinn, Michael, and Uzal, Francisco
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Clostridium haemolyticum ,Clostridium novyi ,Fascioloides magna ,bacillary hemoglobinuria ,cattle ,clostridial hepatitis ,fluke ,hemoglobinuria - Abstract
Bacillary hemoglobinuria (BH) is an infectious disease, mostly affecting cattle, caused by Clostridium haemolyticum (C. novyi type D), with acute hepatic necrosis and intravascular hemolysis. Cattle are typically predisposed to BH by liver injury caused by Fasciola hepatica, although cases have been reported in cattle without evidence of this parasite. Here we describe a cluster of 14 BH cases from 7 counties in north-central to central Missouri submitted to a veterinary diagnostic laboratory between December 2020 and April 2023. Postmortem examination in all cases revealed hemoglobinuria and acute hepatic necrosis with large numbers of gram-positive bacilli with terminal-to-subterminal spores. Flukes, fluke ova, and/or fluke pigment consistent with Fascioloides magna were identified in 12 of 14 cases. Sequences of the nuclear ribosomal internal transcribed spacer 1 (ITS1) from one fluke had 100% identity to F. magna. C. novyi was detected by fluorescent antibody testing of liver impression smears (11 of 12 cases) and by immunohistochemistry of liver sections (7 of 7 cases). PCR on formalin-fixed, paraffin-embedded tissues amplified the C. haemolyticum beta toxin gene in each of the 7 cases tested. To our knowledge, a confirmed cluster of BH associated with F. magna has not been reported previously in cattle.
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- 2024
38. Associations among MHC genes, latitude, and avian malaria infections in the rufous-collared sparrow (Zonotrichia capensis).
- Author
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Rivero de Aguilar, Juan, Barroso, Omar, Bonaccorso, Elisa, Cadena, Hector, Hussing, Lucas, Jorquera, Josefina, Martinez, Javier, Martínez-de la Puente, Josué, Marzal, Alfonso, León Miranda, Fabiola, Merino, Santiago, Matta, Nubia, Ramenofsky, Marilyn, Rozzi, Ricardo, Valeris-Chacín, Carlos, Vásquez, Rodrigo, Vianna, Juliana, and Wingfield, John
- Subjects
haemosporidian parasites ,major histocompatibility complex ,parasite‐mediated selection - Abstract
The major histocompatibility complex (MHC) is a genetic region in jawed vertebrates that contains key genes involved in the immune response. Associations between the MHC and avian malaria infections in wild birds have been observed and mainly explored in the Northern Hemisphere, while a general lack of information remains in the Southern Hemisphere. Here, we investigated the associations between the MHC genes and infections with Plasmodium and Haemoproteus blood parasites along a latitudinal gradient in South America. We sampled 93 rufous-collared sparrows (Zonotrichia capensis) individuals from four countries, Colombia, Ecuador, Peru, and Chile, and estimated MHC-I and MHC-II allele diversity. We detected between 1-4 (MHC-I) and 1-6 (MHC-II) amino acidic alleles per individual, with signs of positive selection. We obtained generalized additive mixed models to explore the associations between MHC-I and MHC-II diversity and latitude. We also explored the relationship between infection status and latitude/biome. We found a non-linear association between the MHC-II amino acidic allele diversity and latitude. Individuals from north Chile presented a lower MHC genetic diversity than those from other locations. We also found an association between deserts and xeric shrublands and a lower prevalence of Haemoproteus parasites. Our results support a lower MHC genetic in arid or semi-arid habitats in the region with the lower prevalence of Haemoproteus parasites.
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- 2024
39. Ab Initio Molecular Dynamics calculations on NO oxidation over oxygen functionalized Highly Oriented Pyrolytic Graphite
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Angulo, Gilberto A. Alou, Santamaría, Alejandro Rivero, Toubin, Céline, and Monnerville, Maurice
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Physics - Chemical Physics - Abstract
The oxidation of NO molecules on epoxy-functionalized highly oriented pyrolytic graphite, thermalized at 300 K, was studied by means of ab initio molecular dynamics (AIMD) calculations. Four collision energies and two different orientations were analyzed where the reaction, adsorption, and scattering probabilities were computed. Our results reveal that NO$_2$ formation can occur even at the lowest collision energy investigated (0.025 eV), approximately equivalent to room temperature (300 K), which agrees qualitatively with the experimental results. This underscores the influence of dynamics on the NO oxidation process, since this oxidation barrier was previously theoretically estimated to be about 0.1 eV at 0 K, which is four times higher than our lowest collision energy. Additionally, we obtained angular and energy distributions of the products under selected simulation conditions. Scattered NO molecules show low specular reflection, lose half of their initial translational energy, and remain vibrationally cold with minimal rotational excitation. Furthermore, a statistical analysis of all reactive trajectories, focusing on configurations at specific reaction moments, elucidated the structural requirements for the reaction to occur under dynamic conditions. Finally, this study demonstrates the potential of oxygen-doped carbon surfaces for the conversion of NO to NO$_2$.
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- 2024
40. Magnon sensing of NO, NO$_2$ and NH$_3$ gas capture on CrSBr monolayer
- Author
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Rivero-Carracedo, Gonzalo, Rybakov, Andrey, and Baldoví, José J.
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Condensed Matter - Materials Science - Abstract
Air pollution and greenhouse emissions are a significant problem across various sectors, urging the need for advanced technologies to detect and capture harmful gases. In recent years, two-dimensional (2D) materials have attracted an increasing attention due to their large surface-to-volume ratio and reactivity. Herein, we investigate the potential of single-layer CrSBr for gas sensing and capturing by means of first-principles calculations. We explore the adsorption behaviour of different pollutant gases (H$_2$S, NH$_3$, NO, NO$_2$, CO and CO$_2$) on this 2D ferromagnet and the impact of intrinsic defects on its magnetic properties. Interestingly, we find that Br vacancies enhance the adsorption of NH$_3$, NO and NO$_2$ and induces a selective frequency shift on the magnon dispersion. This work motivates the creation of novel magnonic gas sensing devices based on 2D van der Waals magnetic materials., Comment: 13 pages, 5 figures, 1 table
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- 2024
41. Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems
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Huang, Chaoyan, Wu, Zhongming, Cheng, Yanqi, Zeng, Tieyong, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I.
- Subjects
Mathematics - Numerical Analysis - Abstract
Image restoration is typically addressed through non-convex inverse problems, which are often solved using first-order block-wise splitting methods. In this paper, we consider a general type of non-convex optimisation model that captures many inverse image problems and present an inertial block proximal linearised minimisation (iBPLM) algorithm. Our new method unifies the Jacobi-type parallel and the Gauss-Seidel-type alternating update rules, and extends beyond these approaches. The inertial technique is also incorporated into each block-wise subproblem update, which can accelerate numerical convergence. Furthermore, we extend this framework with a plug-and-play variant (PnP-iBPLM) that integrates deep gradient denoisers, offering a flexible and robust solution for complex imaging tasks. We provide comprehensive theoretical analysis, demonstrating both subsequential and global convergence of the proposed algorithms. To validate our methods, we apply them to multi-block dictionary learning problems in image denoising and deblurring. Experimental results show that both iBPLM and PnP-iBPLM significantly enhance numerical performance and robustness in these applications., Comment: 6 figures, 3 tables
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- 2024
42. Optimised ProPainter for Video Diminished Reality Inpainting
- Author
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Li, Pengze, Liu, Lihao, Schönlieb, Carola-Bibiane, and Aviles-Rivero, Angelica I
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Computer Science - Computer Vision and Pattern Recognition - Abstract
In this paper, part of the DREAMING Challenge - Diminished Reality for Emerging Applications in Medicine through Inpainting, we introduce a refined video inpainting technique optimised from the ProPainter method to meet the specialised demands of medical imaging, specifically in the context of oral and maxillofacial surgery. Our enhanced algorithm employs the zero-shot ProPainter, featuring optimized parameters and pre-processing, to adeptly manage the complex task of inpainting surgical video sequences, without requiring any training process. It aims to produce temporally coherent and detail-rich reconstructions of occluded regions, facilitating clearer views of operative fields. The efficacy of our approach is evaluated using comprehensive metrics, positioning it as a significant advancement in the application of diminished reality for medical purposes., Comment: Accepted to ISBI 2024
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- 2024
43. Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba
- Author
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Huang, Jiahao, Yang, Liutao, Wang, Fanwen, Nan, Yang, Wu, Weiwen, Wang, Chengyan, Shi, Kuangyu, Aviles-Rivero, Angelica I., Schönlieb, Carola-Bibiane, Zhang, Daoqiang, and Yang, Guang
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Deep learning has been extensively applied in medical image reconstruction, where Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) represent the predominant paradigms, each possessing distinct advantages and inherent limitations: CNNs exhibit linear complexity with local sensitivity, whereas ViTs demonstrate quadratic complexity with global sensitivity. The emerging Mamba has shown superiority in learning visual representation, which combines the advantages of linear scalability and global sensitivity. In this study, we introduce MambaMIR, an Arbitrary-Masked Mamba-based model with wavelet decomposition for joint medical image reconstruction and uncertainty estimation. A novel Arbitrary Scan Masking (ASM) mechanism "masks out" redundant information to introduce randomness for further uncertainty estimation. Compared to the commonly used Monte Carlo (MC) dropout, our proposed MC-ASM provides an uncertainty map without the need for hyperparameter tuning and mitigates the performance drop typically observed when applying dropout to low-level tasks. For further texture preservation and better perceptual quality, we employ the wavelet transformation into MambaMIR and explore its variant based on the Generative Adversarial Network, namely MambaMIR-GAN. Comprehensive experiments have been conducted for multiple representative medical image reconstruction tasks, demonstrating that the proposed MambaMIR and MambaMIR-GAN outperform other baseline and state-of-the-art methods in different reconstruction tasks, where MambaMIR achieves the best reconstruction fidelity and MambaMIR-GAN has the best perceptual quality. In addition, our MC-ASM provides uncertainty maps as an additional tool for clinicians, while mitigating the typical performance drop caused by the commonly used dropout.
- Published
- 2024
44. MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
- Author
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Liu, Jiuming, Han, Jinru, Liu, Lihao, Aviles-Rivero, Angelica I., Jiang, Chaokang, Liu, Zhe, and Wang, Hesheng
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
Point cloud videos can faithfully capture real-world spatial geometries and temporal dynamics, which are essential for enabling intelligent agents to understand the dynamically changing world. However, designing an effective 4D backbone remains challenging, mainly due to the irregular and unordered distribution of points and temporal inconsistencies across frames. Also, recent transformer-based 4D backbones commonly suffer from large computational costs due to their quadratic complexity, particularly for long video sequences.To address these challenges, we propose a novel point cloud video understanding backbone purely based on the State Space Models (SSMs). Specifically, we first disentangle space and time in 4D video sequences and then establish the spatio-temporal correlation with our designed Mamba blocks. The Intra-frame Spatial Mamba module is developed to encode locally similar geometric structures within a certain temporal stride. Subsequently, locally correlated tokens are delivered to the Inter-frame Temporal Mamba module, which integrates long-term point features across the entire video with linear complexity. Our proposed Mamba4d achieves competitive performance on the MSR-Action3D action recognition (+10.4% accuracy), HOI4D action segmentation (+0.7 F1 Score), and Synthia4D semantic segmentation (+0.19 mIoU) datasets. Especially, for long video sequences, our method has a significant efficiency improvement with 87.5% GPU memory reduction and 5.36 times speed-up.
- Published
- 2024
45. Doing the right thing (or not) in a lemons-like situation: on the role of social preferences and Kantian moral concerns
- Author
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Alger, Ingela and Rivero-Wildemauwe, José Ignacio
- Subjects
Economics - General Economics - Abstract
We conduct a laboratory experiment using framing to assess the willingness to ``sell a lemon'', i.e., to undertake an action that benefits self but hurts the other (the ``buyer''). We seek to disentangle the role of other-regarding preferences and (Kantian) moral concerns, and to test if it matters whether the decision is described in neutral terms or as a market situation. When evaluating an action, morally motivated individuals consider what their own payoff would be if -- hypothetically -- the roles were reversed and the other subject chose the same action (universalization). We vary the salience of role uncertainty, thus varying the ease for participants to envisage the role-reversal scenario.
- Published
- 2024
46. L\'evy processes resurrected in the positive half-line
- Author
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Caballero, María Emilia, Chaumont, Loïc, and Rivero, Víctor
- Subjects
Mathematics - Probability - Abstract
A L\'evy processes resurrected in the positive half-line is a Markov process obtained by removing successively all jumps that make it negative. A natural question, given this construction, is whether the resulting process is absorbed at 0 or not. We first describe the law of the resurrected process in terms of that of the initial L\'evy process. Then in many important classes of L\'evy processes, we give conditions for absorption and conditions for non absorption bearing on the characteristics of the initial L\'evy process.
- Published
- 2024
47. POS-556 VASCULAR MORBIDITY ASSOCIATED WITH TUNNELIZED CATHETERS FOR HEMODIALYSIS IN THE POST-TRANSPLANT PERIOD
- Author
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A. ALONSO BETHENCOURT, M.J. Reguera Carmona, C. Rodríguez Álvarez, D. Luis Rodríguez, A. Jarque López, P. García García, E.M. Martín Izquierdo, O. Siverio Morales, V. Domínguez Pimentel, A. Rivero González, N. Del Castillo, E. Gallego Mora-Esperanza, and M. Macía
- Subjects
Diseases of the genitourinary system. Urology ,RC870-923 - Published
- 2021
- Full Text
- View/download PDF
48. Comparative efficacy of probiotic mixture Bifidobacterium longum KABP042 plus Pediococcus pentosaceus KABP041 vs. Limosilactobacillus reuteri DSM17938 in the management of infant colic: a randomized clinical trial
- Author
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Moreno-Villares, J. M., Andrade-Platas, D., Soria-López, M., Colomé-Rivero, G., Catalan Lamban, A., Martinez-Figueroa, M. G., Espadaler-Mazo, J., and Valverde-Molina, J.
- Published
- 2024
- Full Text
- View/download PDF
49. Serological and Molecular Survey of Hepatitis E Virus in Small Ruminants from Central Portugal
- Author
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Santos-Silva, Sérgio, Romalde, Jesús L., Bento, Jaqueline T., Cruz, Andreia V. S., López-López, Pedro, Gonçalves, Helena M. R., Van der Poel, Wim H. M., Nascimento, Maria S. J., Rivero-Juarez, António, and Mesquita, João R.
- Published
- 2024
- Full Text
- View/download PDF
50. New Methods for Old Questions: The Use of Elliptic Fourier Analysis for the Formal Study of Palaeolithic Art
- Author
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García-Bustos, Miguel, García Bustos, Paula, and Rivero, Olivia
- Published
- 2024
- Full Text
- View/download PDF
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