This work presents an innovative model-based approach for the development of mathematical transfer functions capable of correlating Solid Oxide Fuel Cells (SOFCs) degradation rate to the applied ...operating conditions. Such functions can be used for fuel cell lifetime prediction and Accelerated Stress Test (AST) protocols design. The proposed approach relies on multiscale modelling methodology and links local degradation to high level performance models to evaluate the key operating variables accelerating voltage decay over time. A thorough simulation analysis is performed to convey the correlation among operating variables and degradation rate into mathematical transfer functions. To better illustrate the overall design and application process of such functions, a case study accounting for Ni agglomeration is addressed. The multiscale modelling framework is applied to correlate microscale (i.e., Ni particles size change) and macroscale (i.e., SOFC voltage reduction) levels through the most affected mesoscale parameters. The model is then used to simulate voltage decay over time and link degradation rates to the applied operating conditions. Afterwards, a parametric analysis is performed to investigate the influence exerted by each operating variable on the degradation rate and derive the transfer functions. An example of application for Accelerated Stress Test (AST) protocols design is then given.
•Novel model-based methodology proposed for Accelerated Stress Test protocols design.•Proposed case study addressing Ni agglomeration in Solid Oxide Fuel Cells.•Multiscale modelling approach addressed to link microscale and macroscale features.•Parametric analysis done to identify the operating variables affecting degradation.•Transfer functions developed to correlate operating conditions and degradation rate.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Anaplastic thyroid cancer (ATC) has a median survival less than 5 months and, to date, no effective therapy exists. Taxanes have recently been stated as the main drug treatment for ATC, and the ...histone deacetylase inhibitor valproic acid efficiently potentiates the effects of paclitaxel in vitro. Based on these data, this trial assessed the efficacy and safety of the combination of paclitaxel and valproic acid for the treatment of ATC. This was a randomized, controlled phase II/III trial, performed on 25 ATC patients across 5 centers in northwest Italy. The experimental arm received the combination of paclitaxel (80 mg/m2/weekly) and valproic acid (1,000 mg/day); the control arm received paclitaxel alone. Overall survival and disease progression, evaluated in terms of progression-free survival, were the primary outcomes. The secondary outcome was the pharmacokinetics of paclitaxel. The coadministration of valproic acid did not influence the pharmacokinetics of paclitaxel. Neither median survival nor median time to progression was statistically different in the two arms. Median survival of operated-on patients was significantly better than that of patients who were not operated on. The present trial demonstrates that the addition of valproic acid to paclitaxel has no effect on overall survival and disease progression of ATC patients. This trial is registered with EudraCT 2008-005221-11.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective: Treatment options for anaplastic thyroid carcinoma (ATC), which is one of the most lethal human malignant tumors, include surgery, chemotherapy and radiotherapy usually combined in a ...multimodal approach, to improve survival and avoid death from local invasion. However, there is no standard protocol for ATC treatment and the optimal sequence within multimodal therapy is debated. We retrospectively report the clinical outcome of 30 ATC patients referred consecutively to the Oncological Endocrinology Unit of San Giovanni Battista Hospital (Turin, Italy) between 2000 and 2005. Design: Patients were treated by one of the following approaches: i) surgery followed by adjuvant-combined chemoradiotherapy; ii) neo-adjuvant chemoradiotherapy followed by surgery and adjuvant chemotherapy; or iii) chemotherapy alone. The surgical procedures were classified as ‘maximal debulking’ or ‘palliative resection’. Maximal debulking entailed total or near-total thyroidectomy and complete resection of all gross tumor or minimal residual disease adherent to vital structures, independently of the presence or absence of distant metastases. In palliative resections, macroscopic residual disease was left in the neck. Survival of patients stratified by treatment was assessed. Results: Analysis of multivariate hazard ratios showed that maximal debulking followed by adjuvant chemoradiotherapy was the only treatment that modified survival of ATC patients (hazard ratio= 0.23, 95% CI: 0.07–0.79), even if factors determining poor prognosis or increased surgical risk were present. Conclusions: Despite the overall grim outcome of ATC, these results justify an attempt at maximal debulking surgery, followed by adjuvant chemoradiotherapy, possibly in all ATC patients.
Notwithstanding massive efforts and investment in improving cancer therapy, the limited progress made in reducing overall mortality has mostly been achieved through early diagnosis. Mortality rates ...for cardiovascular disease are in decline, a success attributable in large part to an active prevention approach coupled with identification of risk factors and biomarkers. Promising natural and synthetic molecules including numerous flavonoids have the potential to be used in diabetes care and in prevention of cardiovascular pathologies. These concepts should also be applied to cancer, the incidence of which continues to increase. In cancer chemoprevention low toxicity drugs or dietary constituents are used to prevent or delay onset of malignancy. Evidence is accumulating that cancer chemoprevention is a valuable weapon against human cancer. For example, doubling of fruit and fiber intake is associated with reduction of colorectal cancer whereas fat food consumption appears to increase malignant progression of certain tumors. Breast, colorectal and prostate cancer are the most suitable cancers for dietary prevention and scientists have strong data in these cancers at basic, translational, clinical and epidemiological levels, due to experimental evidence and the large EPIC study. Physical activity is also crucial. Yet, cancer chemoprevention research in oncology is largely underrepresented and lags far behind the efforts dedicated to therapy; it is important to close this gap. Few European phase III clinical trials are ongoing and systematic development of novel agents for cancer prevention is rare in Europe.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We identified MISC-1 (Mitochondrial Solute Carrier) as the C. elegans orthologue of mammalian OGC (2-oxoglutarate carrier). OGC was originally identified for its ability to transfer α-ketoglutarate ...across the inner mitochondrial membrane. However, we found that MISC-1 and OGC are not solely involved in metabolic control. Our data show that these orthologous proteins participate in phylogenetically conserved cellular processes, like control of mitochondrial morphology and induction of apoptosis. We show that MISC-1/OGC is required for proper mitochondrial fusion and fission events in both C. elegans and human cells. Transmission electron microscopy reveals that loss of MISC-1 results in a decreased number of mitochondrial cristae, which have a blebbed appearance. Furthermore, our pull-down experiments show that MISC-1 and OGC interact with the anti-apoptotic proteins CED-9 and Bcl-x(L), respectively, and with the pro-apoptotic protein ANT. Knock-down of misc-1 in C. elegans and OGC in mouse cells induces apoptosis through the caspase cascade. Genetic analysis suggests that MISC-1 controls apoptosis through the physiological pathway mediated by the LIN-35/Rb-like protein. We provide genetic and molecular evidence that absence of MISC-1 increases insulin secretion and enhances germline stem cell proliferation in C. elegans. Our study suggests that the mitochondrial metabolic protein MISC-1/OGC integrates metabolic, apoptotic and insulin secretion functions. We propose a novel mechanism by which mitochondria integrate metabolic and cell survival signals. Our data suggest that MISC-1/OGC functions by sensing the metabolic status of mitochondria and directly activate the apoptotic program when required. Our results suggest that controlling MISC-1/OGC function allows regulation of mitochondrial morphology and cell survival decisions by the metabolic needs of the cell.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We prove existence of infinitely many solutions
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•Development of a model-based diagnostic tool for SOFC fault detection and mitigation.•EIS-based diagnosis combined with lumped modelling approach for lifetime extension.•Real-world application ...oriented methods for mitigating H2 anode inlet leakage fault.•Fault-severity dependent fault mitigation scenarios and guidelines for users and maintainers.•The diagnostic and mitigation tool can be fruitfully embedded in real monitoring hardware.
The present paper describes an innovative and generalizable approach to apply fault mitigation strategies to fuel cell powered systems, upon information on system State of Health and Remaining Useful Life. Model-based approach is proposed to derive useful performance-related indicators for each system component. The model comprises two main parts: a nominal part, providing the key variables behavior in nominal conditions, and a faulty part that can be used for fault identification purposes. The framework of the algorithm firstly addresses a monitoring phase, through which residuals are computed, and if one or more residuals overcome defined thresholds, a fault detection is triggered. Afterwards, fault isolation is performed by means of a Fault Signature Matrix and the fault identification (i.e., its magnitude and time-behavior definition) is performed thanks to the faulty sub-models. Once characterized the fault, several strategies (according to different fault magnitudes) are considered, and the most suitable one can be chosen and applied. A case study is then presented to validate the methodology on a fuel starvation fault caused in a 6-cells solid oxide fuel cell stack by a fuel leakage in the anode pipeline. Once applied the mitigation strategy, it has been verified that the power output of the system safely bounds within 20% of its nominal value, whereas stack efficiency variation is negligible. The methodology herein proposed could substantially help the commercial success of solid oxide fuel cell technology, allowing increasing lifetime, with a much focused control of the main variable for diagnostic and maintenance-oriented applications. Indeed, if used in real applications, the proposed approach will speed up maintenance actions even setting the system in a soft condition to be properly prepared for replacement as well.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Solid Oxide Fuel Cell dynamic lumped model for voltage/temperature estimation.•Combination of modelling with Electrochemical Impedance Spectroscopy information.•Analysis of fuel cell degradation due ...to fuel starvation for lifetime estimation.•5000 h of fuel cell operations analyzed for cell/stack lifetime estimation.•Control, diagnostic and prognostic tool for Solid Oxide Fuel Cell cells/stack.
In this work, an online natural aging estimation algorithm is developed, coupled with an Electrochemical Impedance Spectroscopy (EIS)-based diagnostic algorithm, to refine detection features extraction during Solid Oxide Fuel Cell (SOFC) stack operation and to predict its Remaining Useful Life (RUL). A combination of a lumped dynamic model along with features extracted from real-time EIS measurements is herein proposed for on-line applications. An Equivalent Circuit Model (ECM) is considered to identify parameters, such as ohmic and total resistance, that are coupled with an Area Specific Resistance (ASR) approach within the lumped model. The information derived from the EIS spectrum allows to estimate the voltage degradation over time along with its nominal behaviour. Indeed, the time trend of the identified parameters is proportional to the aging of the cell if no other abnormal condition occurs. This guarantees an on-line RUL estimation and a more robust diagnostic algorithm for fault detection and isolation. The approach has been applied to a 6-cells anode supported short stack tested for about 5000 h, and the related RUL estimation identified a critical issue on the middle cell, affecting its neighbours.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Metal−organic frameworks (MOFs) are novel microporous materials with large surface areas, porosities, and thermal stabilities. Even though many thousand MOFs have been identified, few MOF materials ...have been evaluated for gas mixtures separations and fuel gas storage. In this work, using grand canonical Monte Carlo simulations, we calculated adsorption isotherms of pure and binary mixtures of hydrogen−methane in two large surface area MOFs (MOF-5 and MOF-177), two catenated MOFs (IRMOF-11 and MOF-14), and a high affinity open metal site MOF with strong Znδ+−Oδ− dipoles on the surface that create strong energetic interaction with the adsorbates (MOF-74). The pure and mixture adsorption isotherms were calculated at 298 K and up to pressures of approximately 80 bar. The results of this study indicate that separation of hydrogen from methane in these materials would be successful, since hydrogen in a 50% bulk mixture at low pressures has selectivities on the order of 25 for MOF-74, 20 for IRMOF-11, and 18 for MOF-14, compared to low selectivities values on the order of 5 for the two large surface area MOFs, MOF-5 and MOF-177. From this study, we also found that MOF-74 has a large methane storage capacity of 170 cm3 (STP)/cm3 at 298 K and 35 atm, close to the 180 cm3 (STP)/cm3 DOE target for practical methane storage. None of the materials studied has hydrogen gravimetric uptakes in excess of 0.4% wt.
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IJS, KILJ, NUK, PNG, UL, UM
En este trabajo se describe el proceso de predicción de toxicidad de los líquidos iónicos, en particular con respecto a la línea celular en ratas IPC-81. Se estudiaron 355 estructuras moleculares de ...líquidos iónicos, cuya geometría tridimensional está codificada mediante cadenas de símbolos en lenguaje Simplified Molecular Input Line Entry System (SMILES). La alimentación de los datos de entrada a los diferentes modelos de aprendizaje máquina requiere que la información geométrica y de contactos atómicos cercanos de cada liquido iónico sea mapeada o trasformada a notación vectorial numérica (xi) utilizando los siguientes descriptores moleculares: funciones de simetría centradas en cada átomo Atom-Centered Symmetry Functions (ACSF), y huellas digitales de conectividad extendida Extended Connectivity Fingerprints (ECFP). Se usaron tres algoritmos de aprendizaje máquina: Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR) y Kernel Ridge Regression (KRR) para construir el modelo matemático de regresión predictivo que relacione los valores de entrada xi con el valor de respuesta representado por el logaritmo de la concentración media efectiva (yi = logEC50) en la evaluación de toxicidad, usando como métrica del grado de ajuste, el coeficiente de determinación (r2). Los resultados indican que la combinación ECFP, con una distancia radial de 6 vecinos atómicos, en conjunto con el algoritmo KRR, proporciona el mejor ajuste promedio con r2=0.8602±0.032, y con respecto al descriptor molecular ACSF, el mejor ajuste promedio se obtuvo con el algoritmo XGBoost con r2=0.8029±0.055.
This work describes the process of toxicity prediction of ionic liquids, specifically toxicity with respect to the IPC-81 rat cell line. We studied 355 molecular structures of ionic liquids, whose three-dimensional geometry is encoded by means of symbol strings such as Simplified Molecular Input Line Entry System (SMILES) language. The feeding of the input data to the different machine learning models requires that the geometrical and near atomic neighbor information of each ionic liquid be mapped or transformed to numerical vector notation (xi) using the following two molecular descriptors: Atom-Centered Symmetry Functions (ACSF), and Extended Connectivity Fingerprints (ECFP). Three machine learning algorithms: Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR) and Kernel Ridge Regression (KRR) were used to build the predictive mathematical regression model relating the input values xi to the response value represented by the logarithm of the mean effective concentration (yi = logEC50) in the toxicity assessment, using the coefficient of determination (r2) as a metric of the degree of fitness. The results obtained indicated that the ECFP combination with a radial distance of 6 atomic neighbors in conjunction with the KRR algorithm provides the best average fit with r2=0.8602±0.032, and with respect to the ACSF molecular descriptor the best average fit was obtained with the XGBoost algorithm with r2=0.8029±0.055.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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