Hacia una web independiente del dispositivo mediante CC/PP

Composite Capabilities/Preferences Profiles (CC/PP) es el nuevo lenguaje estándar creado por el World Wide Web Constortium (W3C) para que la gran diversidad de dispositivos que disponen, o dispondrán, de un acceso a Internet (móvil, PDA, PC, TV ... ), sean capaces de expresar sus capacidades y las preferencias del usuario mediante perfiles, tal y como su nombre indica. Para expresar estas características, los perfiles CC/PP emplean Resource Descripción Framework (RDF), otro estándar del W3C y pilar de la web semántica, el cual, a su vez, se encuentra construido sobre Extensible Markup Language (XML). La especificación User Agent Profile (UAProf) definida por la Open Mobile Alliance (OMA), antiguo W APForum, utiliza CC/PP para la descripción de los teléfonos móviles. Se puede entender como el primer gran desarrollo CC/PP y ya se encuentra incluido en los últimos dispositivos móviles, implicando la existencia actual de millones de dispositivos que usan CC/PP.Mediante CCIPP los dispositivos tienen la habilidad de enviar la información CCIPP conjuntamente con las peticiones HTTP a los servidores, de manera que éstos puedan procesar la información CC/PP y realizar la adaptación o selección de contenidos adecuados a las características del di spositivo, consiguiendo así una Web independiente del dispositivo, acercándose cada vez más a uno de las principales metas del W3C: El Acceso Universal a laWeb. En este artículo se pone de manifiesto la problemática actual de la negociación de contenidos utilizando HTTP/l.l y se describe la especificación CCIPP, el estándar propuesto por W3C para solucionar esta carencia, justificando sus claves de diseño. También se describe el estándar de la OMA, UAProf, la primera implementación de CCIPP para la descripción de los terminales móviles que se encuentra incluido en la nueva especificación W AP 2.0. Palabras clave- CC/PP, UAProJ, RDF, Adaptación de contenidos, móvil, WebPeer Reviewe

Hacia una web independiente del dispositivo mediante CC/PP

Composite Capabilities/Preferences Profiles (CC/PP) es el nuevo lenguaje estándar creado por el World Wide Web Constortium (W3C) para que la gran diversidad de dispositivos que disponen, o dispondrán, de un acceso a Internet (móvil, PDA, PC, TV ... ), sean capaces de expresar sus capacidades y las preferencias del usuario mediante perfiles, tal y como su nombre indica. Para expresar estas características, los perfiles CC/PP emplean Resource Descripción Framework (RDF), otro estándar del W3C y pilar de la web semántica, el cual, a su vez, se encuentra construido sobre Extensible Markup Language (XML). La especificación User Agent Profile (UAProf) definida por la Open Mobile Alliance (OMA), antiguo W APForum, utiliza CC/PP para la descripción de los teléfonos móviles. Se puede entender como el primer gran desarrollo CC/PP y ya se encuentra incluido en los últimos dispositivos móviles, implicando la existencia actual de millones de dispositivos que usan CC/PP.Mediante CCIPP los dispositivos tienen la habilidad de enviar la información CCIPP conjuntamente con las peticiones HTTP a los servidores, de manera que éstos puedan procesar la información CC/PP y realizar la adaptación o selección de contenidos adecuados a las características del di spositivo, consiguiendo así una Web independiente del dispositivo, acercándose cada vez más a uno de las principales metas del W3C: El Acceso Universal a laWeb. En este artículo se pone de manifiesto la problemática actual de la negociación de contenidos utilizando HTTP/l.l y se describe la especificación CCIPP, el estándar propuesto por W3C para solucionar esta carencia, justificando sus claves de diseño. También se describe el estándar de la OMA, UAProf, la primera implementación de CCIPP para la descripción de los terminales móviles que se encuentra incluido en la nueva especificación W AP 2.0. Palabras clave- CC/PP, UAProJ, RDF, Adaptación de contenidos, móvil, WebPeer Reviewe

Implementation of context-aware network architecture for smart objects based on functional composition

Lack of flexibility of current Internet architecture led researchers to come up with new paradigms for a novel Internet architecture, which would be able to reduce complexity and increase flexibility compared to current Internet architecture. Functional co mposition is a promising approach to flexible and evolvable architecture design. The idea is composing complex protocol suites by dynamically bind and arrange different functions to obtain certain behavior. Herein, we present the implementation of a contex t - aware network architecture based on functional composition for smart objects. A sub - set of those basic functional blocks has been implemented and validated on an experimental testbed using different network topologies .Peer ReviewedPostprint (author’s final draft

Thinking of fish population discrimination: population average phenotype vs. population phenotypes

The genetic polymorphism and phenotypic variation are key in ecology and evolution. The morphological variability of the contour of fish otoliths has been extensively used for the delimitation of stocks. These studies are conventionally based on average phenotype using elliptic Fourier analysis and lineal discriminant analysis as classifier. Considering new analytical options, such as the wavelet transformand non-parametric algorithms, we here analyzed the otolith shape of Trachurus picturatus (blue jack mackerel) from mainland Portugal, Madeira, and the Canaries. We explore the phenotypic variation throughout a latitudinal gradient, establish a hypothesis to explain this variability based on the reaction norms, and determine how the use of average phenotype and/or morphotypes influences in the delimitation of stocks. Four morphotypes were identified in all regions, with an increase of phenotypes in warmer waters. The findings demonstrated that stocks were clearly separated with classification rates over 90%. The use of morphotypes, revealed seasonal variations in their frequencies and per region. The presence of shared phenotypes in different proportions among fishing grounds may open new management approaches in migratory species. These results show the importance of the phenotypic diversity in fisheries management.Preprin

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis

Background: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes. Methods: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation. Results: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observed when we used a 48-h time-point for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth waves, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (HFNC) (n=294) who were intubated earlier. The subgroup of patients undergoing noninvasive ventilation (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. Conclusions: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received HFNC

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic : a matched analysis

The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with COVID-19-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior non-invasive respiratory support on outcomes. This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICU) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of intensive care unit (ICU) admission. Propensity score (PS) matching was used to achieve balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different timepoint (48 h from ICU admission) for early and delayed intubation. Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After PS matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%, p =0.01), ICU mortality (25.7% versus 36.1%, p=0.007) and 90-day mortality (30.9% versus 40.2%, p=0.02) when compared to the early intubation group. Very similar findings were observed when we used a 48-hour timepoint for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth wave, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (n=294) who were intubated earlier. The subgroup of patients undergoing NIV (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received high-flow nasal cannul

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study

Background The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p<0.01). Interpretation Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study

Background: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.11 página

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis