A quasi solid-state dye-sensitized solar cell made of polypyrrole counter electrodes

Quasi-solid state dye-sensitized solar cells have been constructed using nanocrystalline titania, a Ureasil-based nanocomposite gel electrolyte and polypyrrole-functionalized counter electrode. Polypyrrole was synthesized by potentiostatic electrodeposition using pyrrole monomer as precursor by a simple procedure in aqueous solution. The thus obtained polypyrrole films were very robust. They were characterized by FE-SEM microscopy and electrochemical impedance spectroscopy and they were used for the construction of solar cells. The employment of polypyrrole electrocatalyst was judged satisfactory for the present application since it was only 30% less efficient than the corresponding counter electrodes functionalized with Pt.     

Medium-term energy outlook for Cyprus and its policy implications

This short paper presents results from an energy forecast model for the Republic of Cyprus. The model was used during years 2010–2011 to assist national authorities in their preparation of the National Renewable Energy Action Plan and the Energy Efficiency Action Plan of Cyprus in line with the requirements of European Union Directives. Major macroeconomic and price assumptions of the model are presented, and results from model application under different assumptions with regard to the evolution of energy efficiency are outlined and discussed. On the basis of these scenarios the paper discusses policy implications for Cyprus regarding the country's compliance with EU energy and climate legislation.     

Comparison and analysis of the emissions of a small non-road spark-ignition engine operating under different alcohol–gasoline blended fuels

In this experimental study we focused our interest on comparing the effect of lower and higher molecular mass alcohol–gasoline-blended fuels on the regulated emissions emitted by a small non-road spark-ignition engine. Twenty-one test fuels were used in this experimental study that included gasoline as a reference as well as low and high molecular mass alcohol–gasoline blends containing 5%, 10%, 20% and 40% v/v. In exhaust gases that originated from alcohol gasoline test fuels, low CO/HC and high CO₂/NO_x emissions were observed as the total percentage of alcohol in the blend increased. Methanol–gasoline blends seemed to achieve good combustion efficiency, but the engine will require a catalytic converter against high NO_x emissions. Butanol–gasoline blends in several cases gave lower emissions in comparison with the ethanol and propanol–gasoline blends. Finally, the pentanol–gasoline blends showed exactly the same emission patterns as those of neat gasoline.     

Application of ISO 22000 and Failure Mode and Effect Analysis (FMEA) for industrial processing of salmon: a case study

The Failure Mode and Effect Analysis (FMEA) model was applied for risk assessment of salmon manufacturing. A tentative approach of FMEA application to the salmon industry was attempted in conjunction with ISO 22000. Preliminary Hazard Analysis was used to analyze and predict the occurring failure modes in a food chain system (salmon processing plant), based on the functions, characteristics, and/or interactions of the ingredients or the processes, upon which the system depends. Critical Control points were identified and implemented in the cause and effect diagram (also known as Ishikawa, tree diagram and fishbone diagram). In this work, a comparison of ISO 22000 analysis with HACCP is carried out over salmon processing and packaging. However, the main emphasis was put on the quantification of risk assessment by determining the RPN per identified processing hazard. Fish receiving, casing/marking, blood removal, evisceration, filet-making cooling/freezing, and distribution were the processes identified as the ones with the highest RPN (252, 240, 210, 210, 210, 210, 200 respectively) and corrective actions were undertaken. After the application of corrective actions, a second calculation of RPN values was carried out resulting in substantially lower values (below the upper acceptable limit of 130). It is noteworthy that the application of Ishikawa (Cause and Effect or Tree diagram) led to converging results thus corroborating the validity of conclusions derived from risk assessment and FMEA. Therefore, the incorporation of FMEA analysis within the ISO 22000 system of a salmon processing industry is anticipated to prove advantageous to industrialists, state food inspectors, and consumers.     

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers

We study the leave-one-out and generalization errors of voting combinations of learning machines. A special case considered is a variant of bagging. We analyze in detail combinations of kernel machines, such as support vector machines, and present theoretical estimates of their leave-one-out error. We also derive novel bounds on the stability of combinations of any classifiers. These bounds can be used to formally show that, for example, bagging increases the stability of unstable learning machines. We report experiments supporting the theoretical findings.     

Key Genetic Components of Fibrosis in Diabetic Nephropathy: An Updated Systematic Review and Meta-Analysis

Renal fibrosis (RF) constitutes the common end-point of all kinds of chronic kidney disease (CKD), regardless of the initial cause of disease. The aim of the present study was to identify the key players of fibrosis in the context of diabetic nephropathy (DN). A systematic review and meta-analysis of all available genetic association studies regarding the genes that are included in signaling pathways related to RF were performed. The evaluated studies were published in English and they were included in PubMed and the GWAS Catalog. After an extensive literature review and search of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, eight signaling pathways related to RF were selected and all available genetic association studies of these genes were meta-analyzed. ACE, AGT, EDN1, EPO, FLT4, GREM1, IL1B, IL6, IL10, IL12RB1, NOS3, TGFB1, IGF2/INS/TH cluster, and VEGFA were highlighted as the key genetic components driving the fibrosis process in DN. The present systematic review and meta-analysis indicate, as key players of fibrosis in DN, sixteen genes. However, the results should be interpreted with caution because the number of studies was relatively small.     

Urine Metabolomic Profile of Breast- versus Formula-Fed Neonates Using a Synbiotic-Enriched Formula

The aim of this study was to compare the urine metabolic fingerprint of healthy neonates exclusively breastfed with that of neonates fed with a synbiotic-enriched formula (Rontamil^® Complete 1) at four time points (the 3rd and 15th days of life and the 2nd and 3rd months). The determination of urine metabolic fingerprint was performed using NMR metabolomics. Multivariate data analyses were performed with SIMCA-P 15.0 software and R language. Non-distinct profiles for both groups (breastfeeding and synbiotic formula) for the two first time points (3rd and 15th days of life) were detected, whereas after the 2nd month of life, a discrimination trend was observed between the two groups, which was further confirmed at the 3rd month of life. A clear discrimination of the synbiotic formula samples was evident when comparing the metabolites taken in the first days of life (3rd day) with those taken in the 2nd and 3rd months of life. In both cases, OPLS-DA models explained more than 75% of the metabolic variance. Non-distinct metabolomic profiles were obtained between breastfed and synbiotic-formula-fed neonates up to the 15th day of life. Discrimination trends were observed only after the 2nd month of the study, which could be attributed to breastfeeding variations and the consequent dynamic profile of urine metabolites compared to the stable ingredients of the synbiotic formula.     

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Intensive care unit (ICU) patients with venous thromboembolism (VTE) and/or cancer suffer from high mortality rates. Mortality prediction in the ICU has been a major medical challenge for which several scoring systems exist but lack in specificity. This study focuses on two target groups, namely patients with thrombosis or cancer. The main goal is to develop and validate interpretable machine learning (ML) models to predict early and late mortality, while exploiting all available data stored in the medical record. To this end, retrospective data from two freely accessible databases, MIMIC-III and eICU, were used. Well-established ML algorithms were implemented utilizing automated and purposely built ML frameworks for addressing class imbalance. Prediction of early mortality showed excellent performance in both disease categories, in terms of the area under the receiver operating characteristic curve (AUC–ROC): VTE-MIMIC-III 0.93, eICU 0.87, cancer-MIMIC-III 0.94. On the other hand, late mortality prediction showed lower performance, i.e., AUC–ROC: VTE 0.82, cancer 0.74–0.88. The predictive model of early mortality developed from 1651 VTE patients (MIMIC-III) ended up with a signature of 35 features and was externally validated in 2659 patients from the eICU dataset. Our model outperformed traditional scoring systems in predicting early as well as late mortality. Novel biomarkers, such as red cell distribution width, were identified.     

Dapagliflozin Prevents High-Glucose-Induced Cellular Senescence in Renal Tubular Epithelial Cells

Gliflozins are a new class of antidiabetic drugs with renoprotective properties. In cultures of primary human renal tubular epithelial cells (RPTECs) subjected to high-glucose conditions in the presence or absence of dapagliflozin, we evaluated cellular senescence pathways. High glucose increased sodium–glucose cotransporter-2 (SGLT-2) expression and glucose consumption, enhancing reactive oxygen species production. The latter induced DNA damage, ataxia telangiectasia mutated kinase (ATM), and p53 phosphorylation. Stabilized p53 increased the cell cycle inhibitor p21, resulting in cell cycle arrest and increasing the cellular senescence marker beta-galactosidase (GLB-1). RPTECs under high glucose acquired a senescence-associated secretory phenotype, which was detected by the production of IL-1β, IL-8, and TGF-β1. By decreasing SGLT-2 expression and glucose consumption, dapagliflozin inhibited the above pathway and prevented RPTEC senescence. In addition, dapagliflozin reduced the cell cycle inhibitor p16 independently of the glucose conditions. Neither glucose concentration nor dapagliflozin affected the epithelial-to-mesenchymal transition when assessed with α-smooth muscle actin (α-SMA). Thus, high glucose induces p21-dependent RPTEC senescence, whereas dapagliflozin prevents it. Since cellular senescence contributes to the pathogenesis of diabetic nephropathy, delineating the related molecular mechanisms and the effects of the widely used gliflozins on them is of particular interest and may lead to novel therapeutic approaches.