20 research outputs found
Evaluation methodology for fake samples detection in biometrics
Nowadays biometrics is being used in many applications where security is required. This fact causes that new threatens have appeared and that the number of attempts to break biometric systems has increased. From all potential attacks, those involving damage or thefts to users are the most worrying. Most of them could be avoided if acquisition sensors would have suitable approaches for aliveness detection at the capture process. Many providers claim that their products support these methods but unfortunately it has been discovered that some products do not detect fake samples. In this paper a methodology based on Common Criteria is given to evaluate, in an independent way, whether biometric capture devices implement methods for fake samples detection, and till which extent such methods are effective. This methodology has been tested with sensors from different modalities
Capacidad antioxidante y compuestos fenólicos en dos estadios de madurez de Capsicum pubescens Ruiz & Pav. “rocoto”
Se ejecutó este trabajo con el objetivo de determinar la capacidad antioxidante y
cuantificar el contenido de compuestos fenólicos en dos estadios de madurez del
fruto Capsicum pubescens Ruiz & Pav. “rocoto”. La investigación fue tipo básica,
no experimental, descriptiva, transversal con enfoque cuantitativo. La muestra tuvo
procedencia el caserío Caulimalca-Usquil, se utilizó el mesocarpo para cada
estadio (pintón y maduro) y se obtuvo los extractos etanólicos mediante
maceración. La capacidad antioxidante se determinó a través del método DPPH y
para cuantificar el contenido de compuestos fenólicos se utilizó Folin Ciocalteu. Los
resultados reportaron 10,29 mM EAA/g MS con IC50 de 409,53 mg/ml en el estadio
pintón y 33,42 mM EAA/g MS con IC50 de 190,79 mg/ml en estadio maduro. Del
mismo modo, el contenido de fenoles totales arrojó 779,17 ± 58,97 mg EAG/100 g
MS en el estadio pintón, mientras que 1112,12 ± 41,97 mg EAG/100 g MS en
estadio maduro. Concluyendo que el estadio maduro presenta una mayor
capacidad antioxidante y contenido de compuestos fenólicos, mostrando una
significancia menor a 0,05 en los resultados
Análisis de la narrativa transmedia de la campaña Queremos ser vistas Lima 2020
La presente investigación se centró en analizar cómo se presenta la Narrativa
Transmedia en la campaña Queremos ser vistas Lima 2020, se tomó como referencia
para este trabajo, la teoría de la comunicación digital interactivas y la teoría del
interaccionismo simbólico. El enfoque utilizado fue el cualitativo, tipo aplicada, fue un
estudio de caso. Se analizó la narrativa transmedia mediante fichas de observación,la
cual se aplicó a cinco publicaciones que se encontraban en diferentes plataformas
digitales y que comprobaron el supuesto teórico. En conclusión, se demostró que la
historia de la campaña Queremos ser vistas se despliega a través de múltiples medios
y plataformas de comunicación de manera clara ya que se presenta gran interés de
ser una estrategia comunicacional que cumple la publicidad, expansión y visibilización
de la campaña
Correlation of Xpert MTB/RIF with measures to assess Mycobacterium tuberculosis bacillary burden in high HIV burden areas of Southern Africa.
Traditionally, smear microscopy has been used as a point-of-care measure of bacillary burden in tuberculosis patients to inform infection control and contact tracing. Xpert MTB/RIF has the potential to replace smear. However, data to support the use of its quantitative output [cycle threshold (CT)] as an alternate point-of-care measure of bacillary burden are limited. This study assessed the correlation (Spearman's) between CT, smear, culture time-to-positivity (TTP), and clinical factors in patients with Xpert-positive sputum from Mozambique (n = 238) and South Africa (n = 462). Mean CT and smear grade correlated well (ρ0.72); compared to TTP and smear (ρ0.61); and mean CT and TTP (ρ0.50). In multivariate analyses, lower CT (higher bacillary load) was associated with negative HIV serostatus and low BMI. A smear positivity rule-out (95% sensitivity) CT cut-off of 28.0 was identified, with 54.1% specificity, 2.07 positive likelihood ratio, 0.09 negative likelihood ratio and 79.0% correctly classified. Cut-offs were higher for HIV positive compared to HIV negative individuals for any set sensitivity level. This study suggests Xpert CT values correlate well with smear, both in HIV positive and negative individuals, and that CT cut-offs might be broadly applicable to multiple settings. Studies to directly assess the association of CT with infectiousness are needed
Phosphatidylinositol 3-kinase function at very early symbiont perception: a local nodulation control under stress conditions?
Root hair curling is an early and essential morphological change required for the success of the symbiotic interaction between legumes and rhizobia. At this stage rhizobia grow as an infection thread within root hairs and are internalized into the plant cells by endocytosis, where the PI3K enzyme plays important roles. Previous observations show that stress conditions affect early stages of the symbiotic interaction, from 2 to 30 min post-inoculation, which we term as very early host responses, and affect symbiosis establishment. Herein, we demonstrated the relevance of the very early host responses for the symbiotic interaction. PI3K and the NADPH oxidase complex are found to have key roles in the microsymbiont recognition response, modulating the apoplastic and intracellular/endosomal ROS induction in root hairs. Interestingly, compared with soybean mutant plants that do not perceive the symbiont, we demonstrated that the very early symbiont perception under sublethal saline stress conditions induced root hair death. Together, these results highlight not only the importance of the very early host-responses on later stages of the symbiont interaction, but also suggest that they act as a mechanism for local control of nodulation capacity, prior to the abortion of the infection thread, preventing the allocation of resources/energy for nodule formation under unfavorable environmental conditions.Instituto de Fisiología y Recursos Genéticos VegetalesFil: Robert, German. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Fisiología y Recursos Genéticos Vegetales; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Cátedra de Fisiología Vegetal; ArgentinaFil: Muñoz, Nacira Belen. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Fisiología y Recursos Genéticos Vegetales; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Cátedra de Fisiología Vegetal; ArgentinaFil: Alvarado-Affantranger, Xochitl. Universidad Nacional Autónoma de México. Instituto de Biotecnología. Departamento de Biología Molecular de Plantas; MéxicoFil: Saavedra, Laura. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Cátedra de Fisiología Vegetal; ArgentinaFil: Davidenco, Vanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Fisiología y Recursos Genéticos Vegetales; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Cátedra de Fisiología Vegetal; ArgentinaFil: Rodríguez-Kessler, Margarita. Universidad Nacional Autónoma de México. Instituto de Biotecnología. Departamento de Biología Molecular de Plantas; MéxicoFil: Estrada-Navarrete, Georgina. Universidad Nacional Autónoma de México. Instituto de Biotecnología. Departamento de Biología Molecular de Plantas; MéxicoFil: Sanchez, Federico. Universidad Nacional Autónoma de México. Instituto de Biotecnología. Departamento de Biología Molecular de Plantas; MéxicoFil: Lascano, Hernan Ramiro. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Cátedra de Fisiología Vegetal; Argentin
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications
Robust quantification of predictive uncertainty is critical for understanding
factors that drive weather and climate outcomes. Ensembles provide predictive
uncertainty estimates and can be decomposed physically, but both physics and
machine learning ensembles are computationally expensive. Parametric deep
learning can estimate uncertainty with one model by predicting the parameters
of a probability distribution but do not account for epistemic uncertainty..
Evidential deep learning, a technique that extends parametric deep learning to
higher-order distributions, can account for both aleatoric and epistemic
uncertainty with one model. This study compares the uncertainty derived from
evidential neural networks to those obtained from ensembles. Through
applications of classification of winter precipitation type and regression of
surface layer fluxes, we show evidential deep learning models attaining
predictive accuracy rivaling standard methods, while robustly quantifying both
sources of uncertainty. We evaluate the uncertainty in terms of how well the
predictions are calibrated and how well the uncertainty correlates with
prediction error. Analyses of uncertainty in the context of the inputs reveal
sensitivities to underlying meteorological processes, facilitating
interpretation of the models. The conceptual simplicity, interpretability, and
computational efficiency of evidential neural networks make them highly
extensible, offering a promising approach for reliable and practical
uncertainty quantification in Earth system science modeling. In order to
encourage broader adoption of evidential deep learning in Earth System Science,
we have developed a new Python package, MILES-GUESS
(https://github.com/ai2es/miles-guess), that enables users to train and
evaluate both evidential and ensemble deep learning
IP-10 Kinetics in the First Week of Therapy are Strongly Associated with Bacteriological Confirmation of Tuberculosis Diagnosis in HIV-Infected Patients
Simple effective tools to monitor the long treatment of tuberculosis (TB) are lacking. Easily measured host derived biomarkers have been identified but need to be validated in larger studies and different population groups. Here we investigate the early response in IP-10 levels (between day 0 and day 7 of TB therapy) to identify bacteriological status at diagnosis among 127 HIV-infected patients starting TB treatment. All participants were then classified as responding or not responding to treatment blindly using a previously described IP-10 kinetic algorithm. There were 77 bacteriologically confirmed cases and 41 Xpert MTB/RIF® and culture negative cases. Most participants had a measurable decline in IP-10 during the first 7 days of therapy. Bacteriologically confirmed cases were more likely to have high IP-10 levels at D0 and had a steeper decline than clinically diagnosed cases (mean decline difference 2231 pg/dl, 95% CI: 897-3566, p = 0.0013). Bacteriologically confirmed cases were more likely to have a measurable decline in IP-10 at day 7 than clinically diagnosed cases (48/77 (62.3%) vs 13/41 (31.7%), p < 0.001). This study confirms the association between a decrease in IP-10 levels during the first week of treatment and a bacteriological confirmation at diagnosis in a large cohort of HIV positive patients
Involvement of PPAR-γ in the neuroprotective and anti-inflammatory effects of angiotensin type 1 receptor inhibition: effects of the receptor antagonist telmisartan and receptor deletion in a mouse MPTP model of Parkinson's disease
<p>Abstract</p> <p>Background</p> <p>Several recent studies have shown that angiotensin type 1 receptor (AT1) antagonists such as candesartan inhibit the microglial inflammatory response and dopaminergic cell loss in animal models of Parkinson's disease. However, the mechanisms involved in the neuroprotective and anti-inflammatory effects of AT1 blockers in the brain have not been clarified. A number of studies have reported that AT1 blockers activate peroxisome proliferator-activated receptor gamma (PPAR γ). PPAR-γ activation inhibits inflammation, and may be responsible for neuroprotective effects, independently of AT1 blocking actions.</p> <p>Methods</p> <p>We have investigated whether oral treatment with telmisartan (the most potent PPAR-γ activator among AT1 blockers) provides neuroprotection against dopaminergic cell death and neuroinflammation, and the possible role of PPAR-γ activation in any such neuroprotection. We used a mouse model of parkinsonism induced by the dopaminergic neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and co-administration of the PPAR-γ antagonist GW9662 to study the role of PPAR-γ activation. In addition, we used AT1a-null mice lesioned with MPTP to study whether deletion of AT1 in the absence of any pharmacological effect of AT1 blockers provides neuroprotection, and investigated whether PPAR-γ activation may also be involved in any such effect of AT1 deletion by co-administration of the PPAR-γ antagonist GW9662.</p> <p>Results</p> <p>We observed that telmisartan protects mouse dopaminergic neurons and inhibits the microglial response induced by administration of MPTP. The protective effects of telmisartan on dopaminergic cell death and microglial activation were inhibited by co-administration of GW9662. Dopaminergic cell death and microglial activation were significantly lower in AT1a-null mice treated with MPTP than in mice not subjected to AT1a deletion. Interestingly, the protective effects of AT1 deletion were also inhibited by co-administration of GW9662.</p> <p>Conclusion</p> <p>The results suggest that telmisartan provides effective neuroprotection against dopaminergic cell death and that the neuroprotective effect is mediated by PPAR-γ activation. However, the results in AT1-deficient mice show that blockage of AT1, unrelated to the pharmacological properties of AT1 blockers, also protects against dopaminergic cell death and neuroinflammation. Furthermore, the results show that PPAR-γ activation is involved in the anti-inflammatory and neuroprotective effects of AT1 deletion.</p
Comparative Study of FDA and Time Series Approaches for Seabed Classification from Acoustic Curves
Seabed classification in coastal environments is usually accomplished using multivariate methods applied to acoustic features from corrected or uncorrected echoes. This paper presents a comparative study of alternative statistical tools based on time series clustering and non-hierarchical clustering methods for functional data. This allows us to consider the entire acoustic signal without information reduction and assess performance using data acquired in a controlled environment with three different seabed types. The methods considered are used to both analyse the classification power of the recorded echoes and identify the most significant portions of signal.Fil: Tarrío Saavedra, Javier. Universidad da Coruña; EspañaFil: Sanchez Carnero, Noela Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Prieto, Andrés. Universidad da Coruña; Españ