Preconditioning effects of intermittent stream flow on leaf litter decomposition

Autumnal input of leaf litter is a pivotal energy source in most headwater streams. In temporary streams, however, water stress may lead to a seasonal shift in leaf abscission. Leaves accumulate at the surface of the dry streambed or in residual pools and are subject to physicochemical preconditioning before decomposition starts after flow recovery. In this study, we experimentally tested the effect of photodegradation on sunlit streambeds and anaerobic fermentation in anoxic pools on leaf decomposition during the subsequent flowing phase. To mimic field preconditioning, we exposed Populus tremula leaves to UV-VIS irradiation and wet-anoxic conditions in the laboratory. Subsequently, we quantified leaf mass loss of preconditioned leaves and the associated decomposer community in five low-order temporary streams using coarse and fine mesh litter bags. On average, mass loss after approximately 45 days was 4 and 7% lower when leaves were preconditioned by irradiation and anoxic conditions, respectively. We found a lower chemical quality and lower ergosterol content (a proxy for living fungal biomass) in leaves from the anoxic preconditioning, but no effects on macroinvertebrate assemblages were detected for any preconditioning treatment. Overall, results from this study suggest a reduced processing efficiency of organic matter in temporary streams due to preconditioning during intermittence of flow leading to reduced substrate quality and repressed decomposer activity. These preconditioning effects may become more relevant in the future given the expected worldwide increase in the geographical extent of intermittent flow as a consequence of global change. © 2011 Springer Basel AG

Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally

Evaluación continua, clase inversa y cooperación activa en Matemáticas para ingenieros

La Universitat Politècnica de Valencia (UPV) facilita la creación de equipos de innovación y calidad educativa (EICE). Uno de dichos equipos es GRIM4E (GRoup of Innnovative Methodologies and Assessment For Engineering education) que comenzó a realizar innovaciones metodológicas al adaptar las asignaturas de matemáticas a los grados surgidos dentro del proceso de Bolonia. Algunas de dichas innovaciones ya habían sido iniciadas con anterioridad como una evaluación continua de todas las actividades de aprendizaje desarrolladas durante el curso, con más de 30 actos de evaluación en la actualidad en las asignaturas anuales y 10 en las semestrales. Otras fueron pioneras como el empleo sistemático de la clase inversa en las prácticas informáticas de las asignaturas involucradas. Una innovación reciente destacada en nuestro ámbito ha sido el fomento de una actitud activa y colaborativa de los alumnos en la preparación de los actos de evaluación más relevantes.En este trabajo presentamos estas líneas desarrolladas por GRIM4E e incluimos resultados de encuestas anónimas realizadas para recabar la percepción de los alumnos sobre la metodología mixta empleada

HLA association with the susceptibility to anti-synthetase syndrome

Objective: To investigate the human leukocyte antigen (HLA) association with anti-synthetase syndrome (ASSD). Methods: We conducted the largest immunogenetic HLA-DRB1 and HLA-B study to date in a homogeneous cohort of 168 Caucasian patients with ASSD and 486 ethnically matched healthy controls by sequencing-based-typing. Results: A statistically significant increase of HLA-DRB1*03:01 and HLA-B*08:01 alleles in patients with ASSD compared to healthy controls was disclosed (26.2% versus 12.2%, P = 1.56E–09, odds ratio–OR [95% confidence interval–CI] = 2.54 [1.84–3.50] and 21.4% versus 5.5%, P = 18.95E–18, OR [95% CI] = 4.73 [3.18–7.05]; respectively). Additionally, HLA-DRB1*07:01 allele was significantly decreased in patients with ASSD compared to controls (9.2% versus 17.5%, P = 0.0003, OR [95% CI] = 0.48 [0.31–0.72]). Moreover, a statistically significant increase of HLA-DRB1*03:01 allele in anti-Jo-1 positive compared to anti-Jo-1 negative patients with ASSD was observed (31.8% versus 15.5%, P = 0.001, OR [95% CI] = 2.54 [1.39–4.81]). Similar findings were observed when HLA carrier frequencies were assessed. The HLA-DRB1*03:01 association with anti-Jo-1 was unrelated to smoking history. No HLA differences in patients with ASSD stratified according to the presence/absence of the most representative non-anti-Jo-1 anti-synthetase autoantibodies (anti-PL-12 and anti-PL-7), arthritis, myositis or interstitial lung disease were observed. Conclusions: Our results support the association of the HLA complex with the susceptibility to ASSD

Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment

[EN] Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analysesThis study used computing resources from Artemisa, co-funded by the European Union through the 2014-2020 FEDER Operative Programme of the Comunitat Valenciana, project DIFEDER/2018/048. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. The NEXT collaboration acknowledges support from the following agencies and institutions: Xunta de Galicia (Centro singularde investigacion de Galicia accreditation 2019-2022), by European Union ERDF, and by the "Maria de Maeztu" Units of Excellence program MDM-2016-0692 and the Spanish Research State Agency"; the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the European Union's Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Grant Agreements No. 674896, 690575 and 740055; the Ministerio de Economia y Competitividad and the Ministerio de Ciencia, Innovacion y Universidades of Spain under grants FIS2014-53371-C04, RTI2018-095979, the Severo Ochoa Program grants SEV-20140398 and CEX2018-000867-S; the GVA of Spain under grants PROMETEO/2016/120 and SEJI/2017/011; the Portuguese FCT under project PTDC/FIS-NUC/2525/2014 and under projects UID/FIS/04559/2020 to fund the activities of LIBPhys-UC; the U.S. Department of Energy under contracts number DE-AC02-07CH11359 (Fermi National Accelerator Laboratory), DE-FG02-13ER42020 (Texas A&M) and DE-SC0019223/DE SC0019054 (University of Texas at Arlington); and the University of Texas at Arlington. DGD acknowledges Ramon y Cajal program (Spain) under contract number RYC-2015 18820. JMA acknowledges support from Fundacion Bancaria "la Caixa" (ID 100010434), grant code LCF/BQ/PI19/11690012. We also warmly acknowledge the Laboratori Nazionali del Gran Sasso (LNGS) and the Dark Side collaboration for their help with TPB coating of various parts of the NEXT-White TPC. Finally, we are grateful to the Laboratorio Subterraneo de Canfranc for hosting and supporting the NEXT experiment.Kekic, M.; Adams, C.; Woodruff, K.; Renner, J.; Church, E.; Del Tutto, M.; Hernando Morata, JA.... (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. Journal of High Energy Physics (Online). 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Sun, Three-dimensional convolutional neural networks for neutrinoless double-beta decay signal/background discrimination in high-pressure gaseous Time Projection Chamber, 2018 JINST 13 P08015 [arXiv:1803.01482] [INSPIRE].NEXT collaboration, Background rejection in NEXT using deep neural networks, 2017 JINST 12 T01004 [arXiv:1609.06202] [INSPIRE].NEXT collaboration, Sensitivity of NEXT-100 to Neutrinoless Double Beta Decay, JHEP 05 (2016) 159 [arXiv:1511.09246] [INSPIRE].D. Nygren, High-pressure xenon gas electroluminescent TPC for 0-ν ββ-decay search, Nucl. Instrum. Meth. A 603 (2009) 337 [INSPIRE].NEXT collaboration, Calibration of the NEXT-White detector using 83mKr decays, 2018 JINST 13 P10014 [arXiv:1804.01780] [INSPIRE].J. Martín-Albo, The NEXT experiment for neutrinoless double beta decay searches, Ph.D. Thesis, University of Valencia, Valencia Spain (2015) [INSPIRE].GEANT4 collaboration, GEANT4 — a simulation toolkit, Nucl. Instrum. Meth. A 506 (2003) 250 [INSPIRE].A. 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Highlights from the Pierre Auger Observatory

The Pierre Auger Observatory is the world's largest cosmic ray observatory. Our current exposure reaches nearly 40,000 km$^2$ str and provides us with an unprecedented quality data set. The performance and stability of the detectors and their enhancements are described. Data analyses have led to a number of major breakthroughs. Among these we discuss the energy spectrum and the searches for large-scale anisotropies. We present analyses of our X$_{max}$ data and show how it can be interpreted in terms of mass composition. We also describe some new analyses that extract mass sensitive parameters from the 100% duty cycle SD data. A coherent interpretation of all these recent results opens new directions. The consequences regarding the cosmic ray composition and the properties of UHECR sources are briefly discussed.Comment: 9 pages, 12 figures, talk given at the 33rd International Cosmic Ray Conference, Rio de Janeiro 201

Anisotropy and chemical composition of ultra-high energy cosmic rays using arrival directions measured by the Pierre Auger Observatory

The Pierre Auger Collaboration has reported evidence for anisotropy in the distribution of arrival directions of the cosmic rays with energies $E>E_{th}=5.5\times 10^{19}$ eV. These show a correlation with the distribution of nearby extragalactic objects, including an apparent excess around the direction of Centaurus A. If the particles responsible for these excesses at $E>E_{th}$ are heavy nuclei with charge $Z$, the proton component of the sources should lead to excesses in the same regions at energies $E/Z$. We here report the lack of anisotropies in these directions at energies above $E_{th}/Z$ (for illustrative values of $Z=6,\ 13,\ 26$). If the anisotropies above $E_{th}$ are due to nuclei with charge $Z$, and under reasonable assumptions about the acceleration process, these observations imply stringent constraints on the allowed proton fraction at the lower energies

Measurement of the Depth of Maximum of Extensive Air Showers above 10^18 eV

We describe the measurement of the depth of maximum, Xmax, of the longitudinal development of air showers induced by cosmic rays. Almost four thousand events above 10^18 eV observed by the fluorescence detector of the Pierre Auger Observatory in coincidence with at least one surface detector station are selected for the analysis. The average shower maximum was found to evolve with energy at a rate of (106 +35/-21) g/cm^2/decade below 10^(18.24 +/- 0.05) eV and (24 +/- 3) g/cm^2/decade above this energy. The measured shower-to-shower fluctuations decrease from about 55 to 26 g/cm^2. The interpretation of these results in terms of the cosmic ray mass composition is briefly discussed.Comment: Accepted for publication by PR