Servitization and business models in project‐based firms: the case of energy efficient architecture

Purpose:In the context of energy-­efficient buildings, technological innovation and the particularities of design, installations, maintenance and use are presented as an ideal framework for studying the introduction of the phenomenon of servitization into the business models of project‐based firms (PBFs). In this article, we attempt to evaluate how servitization gains a leading role in existing business models in this area

Effect of various dietary regimens on oral challenge with Mycobacterium avium subsp. paratuberculosis in a rabbit model

Rabbits are susceptible to infection by Mycobacterium avium subspecies paratuberculosis (MAP) in both wildlife and experimental conditions. Under the hypotheses that nutrient balance might influence the establishment of infection, we designed an experiment where MAP intestinal colonization was assessed under three dietary regimens: high fiber, high protein, and regular diet in New Zealand white rabbits submitted to oral challenge with MAP.Lowest weight gain (F=5.17, p=0.024), higher tissue culture positivity rates (X2=7.43, p=0.024) and especially extended MAP-compatible lesions (F=5.78, p=0.017) were detected in the regular diet.Taken altogether, results indicate that paratuberculosis infection was achieved affecting mostly regular diet animals and showing that dietary changes may modulate the course of the infection

Inputazio tekniken errendimenduaren ebaluazioa bi neurketako luzeranzko datuetan

Neurketa errepikatuetan oinarrituriko behaketa-ikerketak menpeko aldagaien aldaketak denboran zehar aztertzeko erabiltzen dira. Bi neurketa baizik bakarrik egiten ez direnean, ikerketa helburu nagusietariko bat izan daiteke menpeko aldagaiaren batez besteko aldaketa aurresaten dituzten faktoreak zehaztea. Menpeko aldagaian faltako balioak ohikoak dira ikerketa mota hauetan, behaturiko datuen analisiaren emaitzak alboratuak gerta daitezkeelarik. Lan honetan inputazio teknika desberdinak proposatuko ditugu datu-analisiak egiterakoan faltako balioei aurre egiteko aukera gisa. Hiru inputazio metodoren errendimendua aztertu dugu (K-Nearest Neighbor, Propensity Score eta Markov Chain Monte Carlo algoritmoak), faltako balioek datu multzo osoaren % 10a eta % 30a osatzen dutenean

La Formación de Utrillas en el borde sur de la cuenca Vasco-Cantábrica: aspectos estratigráficos, mineralógicos y genéticos

The Utrillas formation, located in the southem border of the Basque-Cantabrian basin, is mainly composed of sandy materials deposited in a fluvial environment. Two informal units have been distinguished due to field data: a lower coarse-grained unit, interpreted as braider river channel-fills, and a upper fine-grained unit which suggests a meandering river environment. Mineralogy consists of quartz and phyllosilicates, with minor amounts of feldspars. The analysis of tourmalines has pointed two possible sources for these sediments: granitoids and low grade-metasediments. The identified clay minerals are mica and kaolinite. Texturals observations have pointed out an inherited origin for mica, while kaolinite is partly inherited and partly authigenic. This authigenic origin seems to be associated with the alteration of potassic feldspars during the stage of late diagenesis (telodiagenesis).La Formación de Utrillas, aflorante en el borde sur de la cuenca Vasco-Cantábrica, está formada por materiales mayoritariamente areniscosos depositados en un ambiente fluvial. Los datos de campo han permitido distinguir de una manera informal dos unidades: una inferior de granulometría gruesa, representativa de un relleno de canal de tipo trenzado, y una superior más fina que sugiere un entorno de río meandriforme. La mineralogía está compuesta por cuarzo y filosilicatos, con cantidades menores de feldespatos. Como mineral accesorio aparece la turmalina, cuyo análisis ha permitido identificar dos posibles fuentes para los sedimentos: granitoides y metasedimentos de bajo grado. Los minerales de la arcilla presentes son exclusivamente la mica y la caolinita. A partir de criterios texturales, se ha constatado que la mica es de origen heredado, mientras que la caolinita es en parte heredada o bien autigénica, estando asociada a la alteración de feldespato potásico en una etapa de diagénesis tardía (telodiagénesis)

COPD classification models and mortality prediction capacity

Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. Patients and methods: A total of 543 patients with COPD (FEV1 < 80% and FEV1/ FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index. Results: Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV1% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLDABCD, GOLD2017 and cluster analysis for pre-dicting mortality, cluster system was found to be superior compared with GOLD2017 (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001). Conclusion: Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortalit

Automated location of orofacial landmarks to characterize airway morphology in anaesthesia via deep convolutional neural networks

Background:A reliable anticipation of a difficult airway may notably enhance safety during anaesthesia. In current practice, clinicians use bedside screenings by manual measurements of patients’ morphology. Objective:To develop and evaluate algorithms for the automated extraction of orofacial landmarks, which characterize airway morphology. Methods:We defined 27 frontal + 13 lateral landmarks. We collected n=317 pairs of pre-surgery photos from patients undergoing general anaesthesia (140 females, 177 males). As ground truth reference for supervised learning, landmarks were independently annotated by two anaesthesiologists. We trained two ad-hoc deep convolutional neural network architectures based on InceptionResNetV2 (IRNet) and MobileNetV2 (MNet), to predict simultaneously: (a) whether each landmark is visible or not (occluded, out of frame), (b) its 2D-coordinates (x, y). We implemented successive stages of transfer learning, combined with data augmentation. We added custom top layers on top of these networks, whose weights were fully tuned for our application. Performance in landmark extraction was evaluated by 10-fold cross-validation (CV) and compared against 5 state-of-the-art deformable models. Results:With annotators’ consensus as the ‘gold standard’, our IRNet-based network performed comparably to humans in the frontal view: median CV loss L=1.277·10-3, inter-quartile range (IQR) [1.001, 1.660]; versus median 1.360, IQR [1.172, 1.651], and median 1.352, IQR [1.172, 1.619], for each annotator against consensus, respectively. MNet yielded slightly worse results: median 1.471, IQR [1.139, 1.982]. In the lateral view, both networks attained performances statistically poorer than humans: median CV loss L=2.141·10-3, IQR [1.676, 2.915], and median 2.611, IQR [1.898, 3.535], respectively; versus median 1.507, IQR [1.188, 1.988], and median 1.442, IQR [1.147, 2.010] for both annotators. However, standardized effect sizes in CV loss were small: 0.0322 and 0.0235 (non-significant) for IRNet, 0.1431 and 0.1518 (p<0.05) for MNet; therefore quantitatively similar to humans. The best performing state-of-the-art model (a deformable regularized Supervised Descent Method, SDM) behaved comparably to our DCNNs in the frontal scenario, but notoriously worse in the lateral view. Conclusions:We successfully trained two DCNN models for the recognition of 27 + 13 orofacial landmarks pertaining to the airway. Using transfer learning and data augmentation, they were able to generalize without overfitting, reaching expert-like performances in CV. Our IRNet-based methodology achieved a satisfactory identification and location of landmarks: particularly in the frontal view, at the level of anaesthesiologists. In the lateral view, its performance decayed, although with a non-significant effect size. Independent authors had also reported lower lateral performances; as certain landmarks may not be clear salient points, even for a trained human eye.BERC.2022-2025 BCAM Severo Ochoa accreditation CEX2021-001142-S / MICIN / AEI / 10.13039/50110001103

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: A cohort study

Background: Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD. Methods: We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50 %) and validation samples (50 %). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample. Results: Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0 % to 55 % in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95 % CI: 0.783, 0.888) and 0.794 (95 % CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95 % CI: 0.776, 0.859) and 0.770 (95 % CI: 0.716, 0.823) in the validation sample. Conclusions: We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care. Trial registration: NCT02434536

Combining statistical techniques to predict post-surgical risk of 1-year mortality for patients with colon cancer

Introduction: Colorectal cancer is one of the most frequently diagnosed malignancies and a common cause of cancer-related mortality. The aim of this study was to develop and validate a clinical predictive model for1-year mortality among patients with colon cancer who survive for at least 30 days after surgery. Methods: Patients diagnosed with colon cancer who had surgery for the first time and who survived 30 days after the surgery were selected prospectively. The outcome was mortality within 1 year. Random forest, genetic algorithms and classification and regression trees were combined in order to identify the variables and partition points that optimally classify patients by risk of mortality. The resulting decision tree was categorized into four risk categories. Split-sample and bootstrap validation were performed. Results: A total of 1945 patients were enrolled in the study. The variables identified as the main predictors of 1-year mortality were presence of residual tumour, ASA risk score, pathological tumour staging, Charlson comorbidity index, intraoperative complications, adjuvant chemotherapy and recurrence of tumour. The model was internally validated; the area under the curve (AUC) was 0.896 in the derivation sample and 0.835 in the validation sample. Risk categorization leads to AUC values of 0.875 and 0.832 in the derivation and validation samples, respectively. Optimal cut-off point of estimated risk had a sensitivity of 0.889 and a specificity of 0.758. Conclusions: The decision-tree was a simple, interpretable, valid and accurate prediction rule of 1-year mortality among colon cancer patients who survived for at least 30 days after surgery.Instituto de Salud Carlos III (PS09/00314, PS09/00910, PS09/00746, PS09/00805, PI09/90460, PI09/90490, PI09/90453, PI09/90441, PI09/90397 and the thematic networks REDISSEC - Red de Investigación en Servicios de Salud en Enfermedades Crónicas), co-funded by European Regional Development Fund/European Social Fund (ERDF/ESF "Investing in your future"); Research Committee of the Hospital Galdakao Department of Health and the Department of Education, Language Policy and Culture from the Basque Government (2010111098, IT620-13) MINECO and FEDER (MTM2013-40941-P, MTM2016-74931-P)

Chronic obstructive pulmonary disease subtypes. transitions over time

Background Although subtypes of chronic obstructive pulmonary disease are recognized, it is unknown what happens to these subtypes over time. Our objectives were to assess the stability of cluster-based subtypes in patients with stable disease and explore changes in clusters over 1 year. Methods Multiple correspondence and cluster analysis were used to evaluate data collected from 543 stable patients included consecutively from 5 respiratory outpatient clinics. Results Four subtypes were identified. Three of them, A, B, and C, had marked respiratory profiles with a continuum in severity of several variables, while the fourth, subtype D, had a more systemic profile with intermediate respiratory disease severity. Subtype A was associated with less dyspnea, better health-related quality of life and lower Charlson comorbidity scores, and subtype C with the most severe dyspnea, and poorer pulmonary function and quality of life, while subtype B was between subtypes A and C. Subtype D had higher rates of hospitalization the previous year, and comorbidities. After 1 year, all clusters remained stable. Generally, patients continued in the same subtype but 28% migrated to another cluster. Together with movement across clusters, patients showed changes in certain characteristics (especially exercise capacity, some variables of pulmonary function and physical activity) and changes in outcomes (quality of life, hospitalization and mortality) depending on the new cluster they belonged to Conclusions Chronic obstructive pulmonary disease clusters remained stable over 1 year. Most patients stayed in their initial subtype cluster, but some moved to another subtype and accordingly had different outcomes

Fluido magnetikoen portaera magneto-reologiko eta biskoelastikoa

Fluido magnetikoak likido eramaile eta partikula magnetikoez daude osatuta, eta beraien portaera aplikatutako eremu magnetikoaren menpekoa da. Lan honetan, olio mineralez, sufaktante batez, likatzaile batez eta partikula magnetikoz osatutako fluido magnetikoak sintetizatu dira, partikula magnetikoen bolumen kontzentrazio ezberdinak erabiliz. Fluidoak aplikatutako eremu magnetikoaren arabera karakterizatu dira Anton Paar MCR-501 erreometro birakorraren bidez eta plater paralelo konfigurazioa erabiliz. Bi entsegu mota burutu dira, likatasun eta oszilometria motatakoak. Lehenengoen bidez, fluidoaren fluxu-portaera zehaztu da aplikatutako eremu magnetikoaren arabera. Oszilometria entseguetan, lehenbizi, deformazio-ekortze baten bidez, eremu biskoelastiko linealaren muga ezarri da. Ondoren, eremu horren barnean, maiztasun- ekortzeak burutu dira. Entsegu hauen bitartez, materialaren propietate biskoelastikoak ezarri dira partikula magnetikoen kontzentrazioaren eta ezarritako eremu magnetikoaren arabera