A proposal for dependent optimization in scalabale region-based coding systems

We address in this paper the problem of optimal coding in the framework of region-based video coding systems, with a special stress on content-based functionalities. We present a coding system that can provide scaled layers (using PSNR or temporal content-based scalability) such that each one has an optimal partition with optimal bit allocation among the resulting regions. This coding system is based on a dependent optimization algorithm that can provide joint optimality for a group of layers or a group of frames.Peer ReviewedPostprint (published version

Time travel paradoxes, path integrals, and the many worlds interpretation of quantum mechanics

We consider two approaches to evading paradoxes in quantum mechanics with closed timelike curves (CTCs). In a model similar to Politzer's, assuming pure states and using path integrals, we show that the problems of paradoxes and of unitarity violation are related; preserving unitarity avoids paradoxes by modifying the time evolution so that improbable events bewcome certain. Deutsch has argued, using the density matrix, that paradoxes do not occur in the "many worlds interpretation". We find that in this approach account must be taken of the resolution time of the device that detects objects emerging from a wormhole or other time machine. When this is done one finds that this approach is viable only if macroscopic objects traversing a wormhole interact with it so strongly that they are broken into microscopic fragments.Comment: no figure

Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation

The detection and sizing of fruits with computer vision methods is of interest because it provides relevant information to improve the management of orchard farming. However, the presence of partially occluded fruits limits the performance of existing methods, making reliable fruit sizing a challenging task. While previous fruit segmentation works limit segmentation to the visible region of fruits (known as modal segmentation), in this work we propose an amodal segmentation algorithm to predict the complete shape, which includes its visible and occluded regions. To do so, an end-to-end convolutional neural network (CNN) for simultaneous modal and amodal instance segmentation was implemented. The predicted amodal masks were used to estimate the fruit diameters in pixels. Modal masks were used to identify the visible region and measure the distance between the apples and the camera using the depth image. Finally, the fruit diameters in millimetres (mm) were computed by applying the pinhole camera model. The method was developed with a Fuji apple dataset consisting of 3925 RGB-D images acquired at different growth stages with a total of 15,335 annotated apples, and was subsequently tested in a case study to measure the diameter of Elstar apples at different growth stages. Fruit detection results showed an F1-score of 0.86 and the fruit diameter results reported a mean absolute error (MAE) of 4.5 mm and R2 = 0.80 irrespective of fruit visibility. Besides the diameter estimation, modal and amodal masks were used to automatically determine the percentage of visibility of measured apples. This feature was used as a confidence value, improving the diameter estimation to MAE = 2.93 mm and R2 = 0.91 when limiting the size estimation to fruits detected with a visibility higher than 60%. The main advantages of the present methodology are its robustness for measuring partially occluded fruits and the capability to determine the visibility percentage. The main limitation is that depth images were generated by means of photogrammetry methods, which limits the efficiency of data acquisition. To overcome this limitation, future works should consider the use of commercial RGB-D sensors. The code and the dataset used to evaluate the method have been made publicly available at https://github.com/GRAP-UdL-AT/Amodal_Fruit_SizingThis work was partly funded by the Departament de Recerca i Universitats de la Generalitat de Catalunya (grant 2021 LLAV 00088), the Spanish Ministry of Science, Innovation and Universities (grants RTI2018-094222-B-I00 [PAgFRUIT project], PID2021-126648OB-I00 [PAgPROTECT project] and PID2020-117142GB-I00 [DeeLight project] by MCIN/AEI/10.13039/501100011033 and by “ERDF, a way of making Europe”, by the European Union). The work of Jordi Gené Mola was supported by the Spanish Ministry of Universities through a Margarita Salas postdoctoral grant funded by the European Union - NextGenerationEU. We would also like to thank Nufri (especially Santiago Salamero and Oriol Morreres) for their support during data acquisition, and Pieter van Dalfsen and Dirk de Hoog from Wageningen University & Research for additional data collection used in the case study.info:eu-repo/semantics/publishedVersio

AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation

The present dataset comprises a collection of RGB-D apple tree images that can be used to train and test computer vision-based fruit detection and sizing methods. This dataset encompasses two distinct sets of data obtained from a Fuji and an Elstar apple orchards. The Fuji apple orchard sub-set consists of 3925 RGB-D images containing a total of 15,335 apples annotated with both modal and amodal apple segmentation masks. Modal masks denote the visible portions of the apples, whereas amodal masks encompass both visible and occluded apple regions. Notably, this dataset is the first public resource to incorporate on-tree fruit amodal masks. This pioneering inclusion addresses a critical gap in existing datasets, enabling the development of robust automatic fruit sizing methods and accurate fruit visibility estimation, particularly in the presence of partial occlusions. Besides the fruit segmentation masks, the dataset also includes the fruit size (calliper) ground truth for each annotated apple. The second sub-set comprises 2731 RGB-D images capturing five Elstar apple trees at four distinct growth stages. This sub-set includes mean diameter information for each tree at every growth stage and serves as a valuable resource for evaluating fruit sizing methods trained with the first sub-set. The present data was employed in the research paper titled “Looking behind occlusions: a study on amodal segmentation for robust on-tree apple fruit size estimation” [1].This work was partly funded by the Departament de Recerca i Universitats de la Generalitat de Catalunya (grant 2021 LLAV 00088), the Spanish Ministry of Science, Innovation and Universities (grants RTI2018-094222-B-I00 [PAgFRUIT project], PID2021-126648OB-I00 [PAgPROTECT project] and PID2020-117142GB-I00 [DeeLight project] by MCIN/AEI/10.13039/501100011033 and by “ERDF, a way of making Europe”, by the European Union). Data presented in this paper is also part of a Public Private Partnership project Precisie Tuinbouw, WP Fruit 4.0 (PPS KV 1604-025) and financed by Topsector Tuinbouw & Uitgangsmateriaal and various private companies. The work of Jordi Gené Mola was supported by the Spanish Ministry of Universities through a Margarita Salas postdoctoral grant funded by the European Union - NextGenerationEU. We would also like to thank Nufri (especially Santiago Salamero and Oriol Morreres) for their support during data acquisition.info:eu-repo/semantics/publishedVersio

Uso de redes neuronales convolucionales para la detección remota de frutos con cámaras RGB-D

La detección remota de frutos será una herramienta indispensable para la gestión agronómica optimizada y sostenible de las plantaciones frutícolas del futuro, con aplicaciones en previsión de cosecha, robotización de la recolección y elaboración de mapas de producción. Este trabajo propone el uso de cámaras de profundidad RGB-D para la detección y la posterior localización 3D de los frutos. El material utilizado para la adquisición de datos consiste en una plataforma terrestre autopropulsada equipada con dos sensores Kinect v2 de Microsoft y un sistema de posicionamiento RTK-GNSS, ambos conectados a un ordenador de campo que se comunica con los sensores mediante un software desarrollado ad-hoc. Con este equipo se escanearon 3 filas de manzanos Fuji de una explotación comercial. El conjunto de datos adquiridos está compuesto por 110 capturas que contienen un total de 12,838 manzanas Fuji. La detección de frutos se realizó mediante los datos RGB (imágenes de color proporcionadas por el sensor). Para ello, se implementó y se entrenó una red neuronal convolucional de detección de objetos Faster R-CNN. Los datos de profundidad (imagen de profundidad proporcionada por el sensor) se utilizaron para generar las nubes de puntos 3D, mientras que los datos de posición permitieron georreferenciar cada captura. Los resultados de test muestran un porcentaje de detección del 91.4% de los frutos con un 15.9% de falsos positivos (F1-score = 0.876). La evaluación cualitativa de las detecciones muestra que los falsos positivos corresponden a zonas de la imagen que presentan un patrón muy similar a una manzana, donde, incluso a percepción del ojo humano, es difícil de determinar si existe o no manzana. Por otro lado, las manzanas no detectadas corresponden a aquellas que estaban ocultas casi en su totalidad por otros órganos vegetativos (hojas o ramas), a manzanas cortadas por los márgenes de la imagen, o bien a errores humanos en el proceso de etiquetaje del dataset. El tiempo de computación medio fue de 17.3 imágenes por segundo, lo que permite su aplicación en tiempo real. De los resultados experimentales se concluye que el sensor Kinect v2 tiene un gran potencial para la detección y localización 3D de frutos. La principal limitación del sistema es que el rendimiento del sensor de profundidad se ve afectado en condiciones de alta iluminación. Palabras clave: Cámaras de profundidad, RGB-D, Detección de frutos, Redes neuronales convolucionales, Robótica agrícol

Eleven-month longitudinal study of antibodies in SARS-CoV-2 exposed and naïve primary health care workers upon COVID-19 vaccination

We evaluated the kinetics of antibody responses to Two years into the COVID-19 pandemic and 1 year after the start of vaccination rollout, the world faced a peak of cases associated with the highly contagious Omicron variant of concern (VoC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) and nucleocapsid (N) antigens over five cross-sectional visits (January-November 2021), and the determinants of pre-booster immunoglobulin levels, in a prospective cohort of vaccinated primary health care workers in Catalonia, Spain. Antibodies against S antigens after a full primary vaccination course, mostly with BNT162b2, decreased steadily over time and were higher in pre-exposed (n = 247) than naive (n = 200) individuals, but seropositivity was maintained at 100% (100% IgG, 95.5% IgA, 30.6% IgM) up to 319 days after the first dose. Antibody binding to variants of concern was highly maintained for IgG compared to wild type but significantly reduced for IgA and IgM, particularly for Beta and Gamma. Factors significantly associated with longer-term antibodies included age, sex, occupation, smoking, adverse reaction to vaccination, levels of pre-vaccination SARS-CoV-2 antibodies, interval between disease onset and vaccination, hospitalization, oxygen supply, post COVID and symptomatology. Earlier morning vaccination hours were associated with higher IgG responses in pre-exposed participants. Symptomatic breakthroughs occurred in 9/447 (2.01%) individuals, all among naive (9/200, 4.5%) and generally boosted antibody responses. Additionally, an increase in IgA and/or IgM seropositivity to variants, and N seroconversion at later time points (6.54%), indicated asymptomatic breakthrough infections, even among pre-exposed. Seropositivity remained highly stable over almost a year after vaccination. However, gradually waning of anti-S IgGs that correlate with neutralizing activity, coupled to evidence of an increase in breakthrough infections during the Delta and Omicron predominance, provides a rationale for booster immunization

Paratextual subversion: Herrera and his poetry in the anotaciones

The year 1580 saw the publication of the Anotaciones a las obras de Garcilaso de la Vega by the critic and poet Fernando de Herrera (c. 1534–97). This study develops previous scholarship on the paratextual strategies employed by Herrera, especially with regard to the inclusion of his own poetry within the Anotaciones. Two Garcilasian sonnets, ‘D’aquella vista pura i ecelente’ (VIII) and ‘Si para refrenar este desseo’ (XII), in conjunction with Herrera’s poetic responses, lie at the heart of this investigation, representing two respectively dominant cultural currents of the period: Neoplatonism and Classical mythography. It will be shown how Herrera exploits Counter-Reformation attitudes towards secularity and mythography to engage in a critique that goes deeper than the attacks previously noted by Navarrete’s 1991 study. Indeed, Herrera’s lyric occupies a central role in a complete re-evaluation of Garcilasian lyric that not only moves to subvert the supremacy of the Toledan but also the hegemonic rule of intellectuals from Castile. Herrera presents himself as a learned Andalusian model for Neoplatonic poetics and as the model for imitation for Spanish letters in the wake of the Counter-Reformation. En 1580 el poeta y crítico Fernando de Herrera (c. 1534–97) publicó sus Anotaciones a las obras de Garcilaso de la Vega. Este artículo desarrolla estudios anteriores sobre esta obra en relación con las estrategias paratextuales empleadas por Herrera, sobre todo por lo que respecta a la inclusión de su propia poesía en el texto de las Anotaciones. Este trabajo se centra en dos sonetos de Garcilaso, ‘D’aquella vista pura i ecelente’ (VIII) y ‘Si para refrenar este deseo’ (XII), en conjunción con otros tantos textos poéticos de Herrera, teniendo en cuenta sus deudas con dos corrientes culturales contemporáneas: el neoplatonismo y la mitología clásica. Las actitudes hacia el amor neoplatónico y la mitología fueron explotadas por Herrera de una manera más profunda de lo que se suele creer. En efecto, la poesía de Herrera ocupa un papel central en la reevaluación completa de Garcilaso que no sólo subvierte la posición del poeta en el canon literario sino también la hegemonía de los intelectuales de Castilla. Herrera se presenta como un andaluz sabio y defensor de la poesía neoplatónica y como el modelo de referencia para la imitación poética en la nueva era que se abre con la Contrarreforma.This is the author accepted manuscript. The final version is available from Maney via http://dx.doi.org/10.1179/1468273715Z.00000000012

Incidence rates of narcolepsy diagnoses in Taiwan, Canada, and Europe: The use of statistical simulation to evaluate methods for the rapid assessment of potential safety issues on a population level in the SOMNIA study

BACKGROUND & OBJECTIVES: Vaccine safety signals require investigation, which may be done rapidly at the population level using ecological studies, before embarking on hypothesis-testing studies. Incidence rates were used to assess a signal of narcolepsy following AS03-adjuvanted monovalent pandemic H1N1 (pH1N1) influenza vaccination among children and adolescents in Sweden and Finland in 2010. We explored the utility of ecological data to assess incidence of narcolepsy following exposure to pandemic H1N1 virus or vaccination in 10 sites that used different vaccines, adjuvants, and had varying vaccine coverage.METHODS: We calculated incidence rates of diagnosed narcolepsy for periods defined by influenza virus circulation and vaccination campaign dates, and used Poisson regression to estimate incidence rate ratios (IRRs) comparing the periods during which wild-type virus circulated and after the start of vaccination campaigns vs. the period prior to pH1N1 virus circulation. We used electronic health care data from Sweden, Denmark, the United Kingdom, Canada (3 provinces), Taiwan, Netherlands, and Spain (2 regions) from 2003 to 2013. We investigated interactions between age group and adjuvant in European sites and conducted a simulation study to investigate how vaccine coverage, age, and the interval from onset to diagnosis may impact the ability to detect safety signals.RESULTS: Incidence rates of narcolepsy varied by age, continent, and period. Only in Taiwan and Sweden were significant time-period-by-age-group interactions observed. Associations were found for children in Taiwan (following pH1N1 virus circulation) and Sweden (following vaccination). Simulations showed that the individual-level relative risk of narcolepsy was underestimated using ecological methods comparing post- vs. pre-vaccination periods; this effect was attenuated with higher vaccine coverage and a shorter interval from disease onset to diagnosis.CONCLUSIONS: Ecological methods can be useful for vaccine safety assessment but the results are influenced by diagnostic delay and vaccine coverage. Because ecological methods assess risk at the population level, these methods should be treated as signal-generating methods and drawing conclusions regarding individual-level risk should be avoided

Narcolepsy and adjuvanted pandemic influenza A (H1N1) 2009 vaccines – Multi-country assessment

Background: In 2010, a safety signal was detected for narcolepsy following vaccination with Pandemrix, an AS03-adjuvanted monovalent pandemic H1N1 influenza (pH1N1) vaccine. To further assess a possible association and inform policy on future use of adjuvants, we conducted a multi-country study of narcolepsy and adjuvanted pH1N1 vaccines. Methods: We used electronic health databases to conduct a dynamic retrospective cohort study to assess narcolepsy incidence rates (IR) before and during pH1N1 virus circulation, and after pH1N1 vaccination campaigns in Canada, Denmark, Spain, Sweden, Taiwan, the Netherlands, and the United Kingdom. Using a case-control study design, we evaluated the risk of narcolepsy following AS03- and MF59-adjuvanted pH1N1 vaccines in Argentina, Canada, Spain, Switzerland, Taiwan, and the Netherlands. In the Netherlands, we also conducted a case-coverage study in children born between 2004 and 2009. Results: No changes in narcolepsy IRs were observed in any periods in single study sites except Sweden and Taiwan; in Taiwan incidence increased after wild-type pH1N1 virus circulation and in Sweden (a previously identified signaling country), incidence increased after the start of pH1N1 vaccination. No association was observed for Arepanrix-AS03 or Focetria-MF59 adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the case-control study nor for children born between 2004 and 2009 in the Netherlands case-coverage study for Pandemrix-AS03. Conclusions: Other than elevated narcolepsy IRs in the period after vaccination campaigns in Sweden, we did not find an association between AS03- or MF59-adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the sites studied, although power to evaluate the AS03-adjuvanted Pandemrix brand vaccine was limited in our study