Cinética de imbibición e isotermas de adsorción de humedad de la semilla de jamaica (Hibiscus sabdariffa L.)

La jamaica es un arbusto que se cultiva para comercializar el cáliz de sus flores, pero como subproducto se obtienen las semillas, que por su valor nutritivo y alto rendimiento representan un potencial económico considerable. El objetivo de este trabajo fue describir la cinética de imbibición y las isotermas de adsorción de humedad a 25, 35 y 45ºC en tres variedades cultivadas en México ("Criolla", "China" y "Sudán"). Los resultados mostraron que el proceso de imbibición describe una curva que se ajusta al modelo de Weibull, con coeficientes α de 12.99, 8.81 y 2.21 horas y β de 0.83, 1.70 y 0.72 para las variedades Criolla, China y Sudán, respectivamente. Los modelos de GAB, y de Chung-Pfost describieron adecuadamente las isotermas de adsorción. La humedad de la capa monomolecular (coeficiente a del modelo de GAB) resultó entre 3.97 y 5.71% b.s., lo cual representa una actividad de agua entre 0.1 y 0.30. Los calores isostéricos totales de adsorción obtenidos en el intervalo de humedades de equilibrio de 6 a 22% b.s., oscilaron entre 52.85 y 42.90 .90 kJmּol-1, 60.99 y 43.41 kJmּol-1 y 51.23 y 43.20 kJmּol-1para las variedades Criolla, China y Sudán, respectivamente. A humedades de equilibrio iguales o superiores a 12 % b.s., el calor isostérico fue similar a la entalpía de vaporización del agua, pero a humedades inferiores a 6% b.s., éste alcanzó los valores más elevados

On the Use of Deep Feedforward Neural Networks for Automatic Language Identification

In this work, we present a comprehensive study on the use of deep neural networks (DNNs) for automatic language identification (LID). Motivated by the recent success of using DNNs in acoustic modeling for speech recognition, we adapt DNNs to the problem of identifying the language in a given utterance from its short-term acoustic features. We propose two different DNN- based approaches. In the first one, the DNN acts as an end-to-end LID classifier, receiving as input the speech features and providing as output the estimated probabilities of the target languages. In the second approach, the DNN is used to extract bottleneck features that are then used as inputs for a state-of-the-art i-vector system. Experiments are conducted in two different scenarios: the complete NIST Language Recognition Evaluation dataset 2009 (LRE’09) and a subset of the Voice of America (VOA) data from LRE’09, in which all languages have the same amount of training data. Results for both datasets demonstrate that the DNN-based systems significantly outperform a state-of-art i-vector system when dealing with short-duration utterances. Furthermore, the combination of the DNN-based and the classical i-vector system leads to additional performance improvements (up to 45% of relative improvement in both EER and Cavg on 3s and 10s conditions, respectively)

Improving the PLDA based speaker verification in limited microphone data conditions

A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data

Improving short utterance based I-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations of SUN-LDA are proposed where normalization techniques are used to capture source variation from both short and full-length development i-vectors, one based upon pooling (SUN-LDA-pooled) and the other on concatenation (SUN-LDA-concat) across the duration and source-dependent session variation. Both the SUN-LDA-pooled and SUN-LDA-concat techniques are shown to provide improvement over traditional LDA on NIST 08 truncated 10sec-10sec evaluation conditions, with the highest improvement obtained with the SUN-LDA-concat technique achieving a relative improvement of 8% in EER for mis-matched conditions and over 3% for matched conditions over traditional LDA approaches

Morphology Aspects of Hypothyroidism

Hypothyroidism is a common endocrine disorder resulting of low levels of thyroid circulating hormones. The prevalence in the general population varies between 0.3% and 3.7%. Presents as clinical or subclinical disease based on presence of symptoms and levels of serum TSH and free thyroxine and T4, respectively. Hypothyroidism has numerous etiologies, some of them are originated on the thyroid itself and some others are of extrathyroid origin, with variable manifestations. Classified as primary, secondary, tertiary and peripheral. Thyroid autoimmune disease is the principal cause. A new class of drugs against cancer, like the anti-CTLA-4 and anti-PD-L1/PD1 therapies have been associated with primary or secondary hypothyroidism. Endocrine disorders can be difficult to diagnose based only on morphological features because endocrine manifestations are caused primarily by a hormonal imbalance. Hypothyroidism may have a higher risk of morbidity and mortality. Finally, myxedematous coma is the main complication of terminal stages hypothyroidism

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks

Zazo R, Lozano-Diez A, Gonzalez-Dominguez J, T. Toledano D, Gonzalez-Rodriguez J (2016) Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks. PLoS ONE 11(1): e0146917. doi:10.1371/journal.pone.0146917Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (similar to 3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.This work has been supported by project CMC-V2: Caracterizacion, Modelado y Compensacion de Variabilidad en la Señal de Voz (TEC2012-37585-C02-01), funded by Ministerio de Economia y Competitividad, Spain

Frequency of hereditary transthyretin amyloidosis among elderly patients with transthyretin cardiomyopathy

Transthyretin amyloid cardiomyopathy (ATTR-CM) is increasingly recognized as a cause of heart failure in the elderly. Although wild-type transthyretin amyloidosis is the most frequent form of ATTR-CM found in the elderly, hereditary transthyretin amyloidosis (ATTRv) can also occur. We sought to determine the prevalence of ATTRv among elderly ATTR-CM patients, identify predictors of ATTRv and evaluate the clinical consequences of positive genetic testing in this population. Prevalence of ATTRv in elderly ATTR-CM patients (≥70 years) was assessed in a cohort of 300 consecutive ATTR-CM patients (median age 78 years at diagnosis, 82% ≥70 years, 16% female, 99% Caucasian). ATTRv was diagnosed in 35 (12%; 95% confidence interval [CI] 3.1–8.8) and 13 (5.3%; 95% CI 5.6–26.7) patients in the overall cohort and in those ≥70 years, respectively. Prevalence of ATTRv among elderly female patients with ATTR-CM was 13% (95% CI 2.1–23.5). Univariate analysis identified female sex (odds ratio [OR] 3.66; 95% CI 1.13–11.85; p = 0.03), black ancestry (OR 46.31; 95% CI 3.52–Inf; p = 0.005), eye symptoms (OR 6.64; 95% CI 1.20–36.73; p = 0.03) and polyneuropathy (OR 10.05; 95% CI 3.09–32.64; p<0.001) as the only factors associated with ATTRv in this population. Diagnosis of ATTRv in elderly ATTR-CM patients allowed initiation of transthyretin-specific drug treatment in 5 individuals, genetic screening in 33 relatives from 13 families, and identification of 9 ATTRv asymptomatic carriers. Hereditary transthyretin amyloidosis is present in a substantial number of ATTR-CM patients aged ≥70 years. Identification of ATTRv in elderly patients with ATTR-CM has clinical meaningful therapeutic and diagnostic implications. These results support routine genetic testing in patients with ATTR-CM regardless of ageThis study has been funded by Instituto de Salud Carlos III (ISCIII) through the projects ‘PI18/0765 & PI20/01379’ (co-funded by European Regional Development Fund/European Social Fund ‘A way to make Europe’/‘Investing in your future’). AMB receives grant support by ISCIII (CM20/002209). The CNIC is supported by the ISCIII, MCIN, the Pro-CNIC Foundation, and the Severo Ochoa grant (CEX2020-001041-S

Genetically Confirmed Familial Hypercholesterolemia in Patients With Acute Coronary Syndrome

BACKGROUND: Genetic screening programs in unselected individuals with increased levels of low-density lipoprotein cholesterol (LDL-C) have shown modest results in identifying individuals with familial hypercholesterolemia (FH). OBJECTIVES: This study assessed the prevalence of genetically confirmed FH in patients with acute coronary syndrome (ACS) and compared the diagnostic performance of FH clinical criteria versus FH genetic testing. METHODS: Genetic study of 7 genes (LDLR, APOB, PCSK9, APOE, STAP1, LDLRAP1, and LIPA) associated with FH and 12 common alleles associated with polygenic hypercholesterolemia was performed in 103 patients with ACS, age ≤65 years, and LDL-C levels ≥160 mg/dl. Dutch Lipid Clinic (DLC) and Simon Broome (SB) FH clinical criteria were also applied. RESULTS: The prevalence of genetically confirmed FH was 8.7% (95% confidence interval [CI]: 4.3% to 16.4%; n = 9); 29% (95% CI: 18.5% to 42.1%; n = 18) of patients without FH variants had a score highly suggestive of polygenic hypercholesterolemia. The prevalence of probable to definite FH according to DLC criteria was 27.2% (95% CI: 19.1% to 37.0%; n = 28), whereas SB criteria identified 27.2% of patients (95% CI: 19.1% to 37.0%; n = 28) with possible to definite FH. DLC and SB algorithms failed to diagnose 4 (44%) and 3 (33%) patients with genetically confirmed FH, respectively. Cascade genetic testing in first-degree relatives identified 6 additional individuals with FH. CONCLUSIONS: The prevalence of genetically confirmed FH in patients with ACS age ≤65 years and with LDL-C levels ≥160 mg/dl is high (approximately 9%). FH clinical algorithms do not accurately classify patients with FH. Genetic testing should be advocated in young patients with ACS and high LDL-C levels to allow prompt identification of patients with FH and relatives at risk.This research was supported in part by the Instituto de Salud Carlos III (grants RD012/0042/0066 and CB16/11/00432), Spanish Ministry of Economy and Competitiveness (grant SAF2015-71863-REDT), and Alexion through an Investigator Initiated Research Grant. Grants from the Instituto de Salud Carlos III and the Spanish Ministry of Economy and Competitiveness are supported by the Plan Estatal de I+D+I 2013-2016 European Regional Development Fund (FEDER), "A way of making Europe." The sponsors played no role in the design, collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. Drs. Castillo, Lluis-Ganella, and Quintana are employees of Gendiag.exe/Ferrer inCode.S

Graphene and graphene oxide induce ROS production in human HaCaT skin keratinocytes: The role of xanthine oxidase and NADH dehydrogenase

The extraordinary physicochemical properties of graphene-based nanomaterials (GBNs) make them promising tools in nanotechnology and biomedicine. Considering the skin contact as one of the most feasible exposure routes to GBNs, the mechanism of toxicity of two GBNs (few-layer-graphene, FLG, and graphene oxide, GO) towards human HaCaT skin keratinocytes was investigated. Both materials induced a significant mitochondrial membrane depolarization: 72 h cell exposure to 100 \u3bcg mL 12 1 FLG or GO increased mitochondrial depolarization by 44% and 56%, respectively, while the positive control valinomycin (0.1 \u3bcg mL 121) increased mitochondrial depolarization by 48%. Since the effect was not prevented by cyclosporine-A, it appears to be unrelated to mitochondrial transition pore opening. By contrast, it seems to be mediated by reactive oxygen species (ROS) production: FLG and GO induced time- and concentration- dependent cellular ROS production, significant already at the concentration of 0.4 \u3bcg mL 121 after 24 h exposure. Among a panel of specific inhibitors of the major ROS-producing enzymes, diphenyliodonium, rotenone and allopurinol significantly reverted or even abolished FLG- or GO-induced ROS production. Intriguingly, the same inhibitors also significantly reduced FLG- or GO-induced mitochondrial depolarization and cytotoxicity. This study shows that FLG and GO induce a cytotoxic effect due to a sustained mitochondrial depolarization. This seems to be mediated by a significant cellular ROS production, caused by the activation of flavoprotein-based oxidative enzymes, such as NADH dehydrogenase and xanthine oxidase

Analysis of candidates for interacting galaxy clusters: I. A1204 and A2029/A2033

Merging galaxy clusters allow for the study of different mass components, dark and baryonic, separately. Also, their occurrence enables to test the ΛCDM scenario, which can be used to put constraints on the selfinteracting cross-section of the dark-matter particle. It is necessary to perform a homogeneous analysis of these systems. Hence, based on a recently presented sample of candidates for interacting galaxy clusters, we present the analysis of two of these cataloged systems. In this work, the first of a series devoted to characterizing galaxy clusters in merger processes, we perform a weak lensing analysis of clusters A1204 and A2029/2033 to derive the total masses of each identified interacting structure together with a dynamical study based on a two-body model. We also describe the gas and the mass distributions in the field through a lensing and an X-ray analysis. This is the first of a series of works which will analyze these type of system in order to characterize them. Neither merging cluster candidate shows evidence of having had a recent merger event. Nevertheless, there is dynamicalevidence that these systems could be interacting or could interact in the future. It is necessary to include more constraints in order to improve the methodology of classifying merging galaxy clusters.Characterization of these clusters is important in order to properly understand the nature of these systems and their connection withdynamical studies.Fil: Gonzalez, Elizabeth Johana. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: de Los Rios, Martín Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Oio, Gabriel Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Hernández Lang, Daniel. Universidad de La Serena; ChileFil: AguirreTagliaferro, Tania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Dominguez Romero, Mariano Javier de Leon. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Nilo Castellon, Jose Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina. Universidad de la Serena; ChileFil: Cuevas L., H.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; ArgentinaFil: Valotto, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomía Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomía Teórica y Experimental; Argentina. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba; Argentin