Efficient Thermal Electric Skipping Strategy Applied to the Control of Series/Parallel Hybrid Powertrain

The optimal control of hybrid powertrains represents one of the most challenging tasks for the compliance with the legislation concerning CO2 and pollutant emission of vehicles. Most common off-line optimization strategies (Pontryagin minimum principle-PMP-or dynamic programming) allow to identify the optimal control along a predefined driving mission at the expense of a quite relevant computational effort. On-line strategies, suitable for on-vehicle implementation, involve a certain performance degradation depending on their degree of simplification and computational effort. In this work, a simplified control strategy is presented, where the conventional power-split logics, typical of the above-mentioned strategies, is here replaced with an alternative utilization of the thermal and electric units for the vehicle driving (Efficient Thermal Electric Skipping Strategy-ETESS). The choice between the units is realized at each time and is based on the comparison between the effective fuel rate of the thermal engine and an equivalent fuel rate related to the electrical power consumption. The equivalent fuel rate in a pure electric driving is associated to a combination of brake specific fuel consumption of the thermal engine, and electro-mechanical efficiencies along the driveline. The ETESS is applied for the simulation of segment C hybrid vehicle, equipped with a thermal engine and two electric units (motor and generator). The methodology is tested along regulatory driving cycles (WLTP, Artemis) and RDE, with different powertrain variants. Numerical results underline that the proposed approach performs very close to most common control strategies (consumed fuel per kilometer higher than PMP of about 1% on average). The main advantage is a reduced computational effort (decrease of 99% on average). The ETESS is straightforwardly adapted for an on-line implementation, through the introduction of an adaptative factor, preserving the computational effort and the fuel economy

Employment of an auto-regressive model for knock detection supported by 1D and 3D analyses

In this work, experimental data, carried out on a twin-cylinder turbocharged engine at full load operations and referred to a spark advance of borderline knock, are used to characterize the effects of cyclic dispersion on knock phenomena. 200 consecutive incylinder pressure signals are processed through a refined Auto-Regressive Moving Average (ARMA) mathematical technique, adopted to define the percentage of knocking cycles, through a prefixed threshold level. The heuristic method used for the threshold selection is then verified by 1D and 3D analyses. In particular, a 1D model, properly accounting for cycle-by-cycle variations, and coupled to a reduced kinetic sub-model, is used to reproduce the measured cycles, in terms of statistical distribution of a theoretical knock index. In addition, few individual cycles, representative of the whole dataset, are selected in a single operating condition in order to perform a more detailed knock analysis by means of a 3D CFD approach, coupled to a tabulated chemistry technique for auto-ignition modeling. Outcomes of 1D and 3D models are compared to the ARMA results and a substantial coherence of the numerical and experimental results is demonstrated. The integrated 1D and 3D analyses can hence help in supporting the choice of the experimental threshold level for knock identification, following a more standardized theoretical approach

Secondary metabolites in xylella fastidiosa-plant interaction

During their evolutionary history, plants have evolved the ability to synthesize and accumulate small molecules known as secondary metabolites. These compounds are not essential in the primary cell functions but play a significant role in the plants’ adaptation to environmental changes and in overcoming stress. Their high concentrations may contribute to the resistance of the plants to the bacterium Xylella fastidiosa, which has recently re‐emerged as a plant pathogen of global importance. Although it is established in several areas globally and is considered one of the most dangerous plant pathogens, no cure has been developed due to the lack of effective bactericides and the difficulties in accessing the xylem vessels where the pathogen grows and produces cell aggregates and biofilm. This review highlights the role of secondary metabolites in the defense of the main economic hosts of X. fastidiosa and identifies how knowledge about biosynthetic pathways could improve our understanding of disease resistance. In addition, current developments in non-invasive techniques and strategies of combining molecular and physiological techniques are examined, in an attempt to identify new metabolic engineering options for plant defense

A novel human aquaporin-4 splice variant exhibits a dominant-negative activity: a new mechanism to regulate water permeability.

Two major isoforms of aquaporin-4 (AQP4) have been described in human tissue. Here we report the identification and functional analysis of an alternatively spliced transcript of human AQP4, AQP4-Δ4, that lacks exon 4. In transfected cells AQP4-Δ4 is mainly retained in the endoplasmic reticulum and shows no water transport properties. When AQP4-Δ4 is transfected into cells stably expressing functional AQP4, the surface expression of the full-length protein is reduced. Furthermore, the water transport activity of the cotransfectants is diminished in comparison to transfectants expressing only AQP4. The observed down-regulation of both the expression and water channel activity of AQP4 is likely to originate from a dominant-negative effect caused by heterodimerization between AQP4 and AQP4-Δ4, which was detected in coimmunoprecipitation studies. In skeletal muscles, AQP4-Δ4 mRNA expression inversely correlates with the level of AQP4 protein and is physiologically associated with different types of skeletal muscles. The expression of AQP4-Δ4 may represent a new regulatory mechanism through which the cell-surface expression and therefore the activity of AQP4 can be physiologically modulated

1D numerical and experimental investigations of an ultralean pre-chamber engine

In recent years, lean-burn gasoline Spark-Ignition (SI) engines have been a major subject of investigations. With this solution, in fact, it is possible to simultaneously reduce NOx raw emissions and fuel consumption due to decreased heat losses, higher thermodynamic efficiency, and enhanced knock resistance. However, the real applicability of this technique is strongly limited by the increase in cyclic variation and the occurrence of misfire, which are typical for the combustion of homogeneous lean air/fuel mixtures. The employment of a Pre-Chamber (PC), in which the combustion begins before proceeding in the main combustion chamber, has already shown the capability of significantly extending the lean-burn limit. In this work, the potential of an ultralean PC SI engine for a decisive improvement of the thermal efficiency is presented by means of numerical and experimental analyses. The SI engine is experimentally investigated with and without the employment of the PC with the aim to analyze the real gain of this innovative combustion system. For both configurations, the engine is tested at various speeds, loads, and air-fuel ratios. A commercial gasoline fuel is directly injected into the Main Chamber (MC), while the PC is fed in a passive or active mode. Compressed Natural Gas (CNG) or Hydrogen (H2) is used in the actual case. A 1D model of the engine under study is implemented in a commercial modeling framework and is integrated with “in-house developed” sub-models for the simulation of the combustion and turbulence phenomena occurring in this unconventional engine. The numerical approach proves to reproduce the experimental data with good accuracy, without requiring any case-dependent tuning of the model constants. Both the numerical and experimental results show an improvement of the indicated thermal efficiency of the active PC, compared to the conventional ignition device, especially at high loads and low speeds. The injection of H2 into the PC leads to a significant benefit only with very lean mixtures. With the passive fueling of the PC, the lean-burn limit is less extended, with the consequent lower improvement potential for thermal efficiency

Effects of the ionizing radiation disinfection treatment on historical leather

Microorganisms often cause significant damage on historical objects. The archive or library materials as well as textile or leather artifacts suffer serious attacks that need appropriate care treatments. Several biocide processes have been implemented but often their application does not preserve the material of the good. The objective of this work is the disinfection through ionizing radiation of leather wallpaper from the museum building Palazzo Chigi in Ariccia (Rome, Italy). The controlled sterilization treatments were carried out using X-ray beams to eliminate the microorganisms present on the leather and maintaining unchanged the properties of the constituent material. Some fragments of decorated leather wallpaper, dating back to the 1700s, were irradiated with X-rays up to 5,000 Gy. The amount of microorganisms was evaluated by microbiological analysis before and after X-ray irradiation treatments to identify the dose that inhibits the bacterial load. It will be shown how the results obtained by the application of different chemical-physical techniques (Scanning Electron Microscopy, Fourier Transform Infrared spectroscopy and Light Transmission Analysis) have helped in the evaluation of the impact of the X-rays on leather chemical and physical integrity

Tumour sublines with different metastatic capacity induce similar blood coagulation changes in the host.

This paper is aimed at investigating how metastatic tumour growth influenced the haemostatic system of the host. Blood platelet count, blood fibrinogen level, the activated partial thromboplastin time (APTT) and the prothrombin time (PT) were determined at various intervals during growth and metastasis of a murine fibrosarcoma (mFS6) or one of its sublines with different metastatic capacity. Progressive thrombocytopenia and increase in fibrinogen level were observed during development of the tumour in all the animal groups studied, irrespective of the metastatic potential of the various sublines. No significant changes were observed in the PT or APTT values. These data support the concept that primary rather than metastatic growth influences the haemostatic system of tumour-bearing animals

Candidate Genes and MiRNAs Linked to the Inverse Relationship Between Cancer and Alzheimer’s Disease: Insights From Data Mining and Enrichment Analysis

The incidence of cancer and Alzheimer\u2019s disease (AD) increases exponentially with age. A growing body of epidemiological evidence and molecular investigations inspired the hypothesis of an inverse relationship between these two pathologies. It has been proposed that the two diseases might utilize the same proteins and pathways that are, however, modulated differently and sometimes in opposite directions. Investigation of the common processes underlying these diseases may enhance the understanding of their pathogenesis and may also guide novel therapeutic strategies. Starting from a text-mining approach, our in silico study integrated the dispersed biological evidence by combining data mining, gene set enrichment, and protein-protein interaction (PPI) analyses while searching for common biological hallmarks linked to AD and cancer. We retrieved 138 genes (ALZCAN gene set), computed a significant number of enriched gene ontology clusters, and identified four PPI modules. The investigation confirmed the relevance of autophagy, ubiquitin proteasome system, and cell death as common biological hallmarks shared by cancer and AD. Then, from a closer investigation of the PPI modules and of the miRNAs enrichment data, several genes (SQSTM1, UCHL1, STUB1, BECN1, CDKN2A, TP53, EGFR, GSK3B, and HSPA9) and miRNAs (miR-146a-5p, MiR-34a-5p, miR-21-5p, miR-9-5p, and miR-16-5p) emerged as promising candidates. The integrative approach uncovered novel miRNA-gene networks (e.g., miR-146 and miR-34 regulating p62 and Beclin1 in autophagy) that might give new insights into the complex regulatory mechanisms of gene expression in AD and cancer

Biomarkers to personalize the treatment of rheumatoid arthritis: Focus on autoantibodies and pharmacogenetics

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is very complex and heterogeneous. If not adequately treated, RA patients are likely to manifest excess of morbidity and disability with an important impact on the quality of life. Pharmacological treatment is based on the administration of the disease-modifying antirheumatic drugs (DMARDs), subdivided into conventional synthetic (csDMARDs), targeted synthetic (tsDMARDs), and biological (bDMARDs). bDMARDs are now frequently administered in patients, both as alternative treatment and together with csDMARDs. Unfortunately, there is a therapeutic response variability both to old and new drugs. Therefore, to identify pre-therapeutic and on-treatment predictors of response is a priority. This review aims to summarize recent advances in understanding the causes of the variability in treatment response in RA, with particular attention to predictive potential of autoantibodies and DMARD pharmacogenetics. In recent years, several biomarkers have been proposed to personalize the therapy. Unfortunately, a magic bullet does not exist, as many factors concur to disease susceptibility and treatment outcomes, acting around the patient’s congenital background. Models integrating demographic, clinical, biochemical, and genetic data are needed to enhance the predictive capacity of specific factors singularly considered to optimize RA treatment in light of multidisciplinary patient management