A voltage tunable CMOS differential active resistor and its application

We propose a novel CMOS differential voltage-controlled equivalent active resistor based on a modified common-source cross-coupled pair. The equivalent resistance exhibited by the circuit can be tuned to be either positive or negative through the tail current, which is controlled by a bias voltage. The complete cell comprises four transistors, two resistors in addition to the bias voltage, and tail current source. Application to the design of oscillators is demonstrated by theoretical analysis, circuit simulations, and verified experimentally through measurements on prototypes implemented using discrete transistors.     

Phase noise analysis in CMOS differential Armstrong oscillator topology

This paper reports a phase noise analysis in a differential Armstrong oscillator circuit topology in CMOS technology. The analytical expressions of phase noise due to flicker and thermal noise sources are derived and validated by the results obtained through SpectreRF simulations for oscillation frequencies of 1, 10, and 100 GHz. The analysis captures well the phase noise of the oscillator topology and shows the impact of flicker noise contribution as the major effect leading to phase noise degradation in nano‐scale CMOS LC oscillators. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive local learning techniques for multiple-step-ahead wind speed forecasting

A massive deployment of wind energy in power systems is expected in the near future. However, a still open issue is how to integrate wind generators into existing electrical grids by limiting their side effects on network operations and control. In order to attain this objective, accurate short and medium-term wind speed forecasting is required.This paper discusses and compares a physical (white-box) model (namely a limited-area non hydrostatic model developed by the European consortium for small-scale modeling) with a family of local learning techniques (black-box) for short and medium term forecasting. Also, an original model integrating machine learning techniques with physical knowledge modeling (grey-box) is proposed.A set of experiments on real data collected from a set of meteorological sensors located in the south of Italy supports the methodological analysis and assesses the potential of the different forecasting approaches.     

Colorectal Cancer Apoptosis Induced by Dietary δ-Valerobetaine Involves PINK1/Parkin Dependent-Mitophagy and SIRT3

Understanding the mechanisms of colorectal cancer progression is crucial in the setting of strategies for its prevention. δ-Valerobetaine (δVB) is an emerging dietary metabolite showing cytotoxic activity in colon cancer cells via autophagy and apoptosis. Here, we aimed to deepen current knowledge on the mechanism of δVB-induced colon cancer cell death by investigating the apoptotic cascade in colorectal adenocarcinoma SW480 and SW620 cells and evaluating the molecular players of mitochondrial dysfunction. Results indicated that δVB reduced cell viability in a time-dependent manner, reaching IC50 after 72 h of incubation with δVB 1.5 mM, and caused a G2/M cell cycle arrest with upregulation of cyclin A and cyclin B protein levels. The increased apoptotic cell rate occurred via caspase-3 activation with a concomitant loss in mitochondrial membrane potential and SIRT3 downregulation. Functional studies indicated that δVB activated mitochondrial apoptosis through PINK1/Parkin pathways, as upregulation of PINK1, Parkin, and LC3B protein levels was observed (p < 0.0001). Together, these findings support a critical role of PINK1/Parkin-mediated mitophagy in mitochondrial dysfunction and apoptosis induced by δVB in SW480 and SW620 colon cancer cells.     

The Role of Endothelium in COVID-19

The 2019 novel coronavirus, known as severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) or coronavirus disease 2019 (COVID-19), is causing a global pandemic. The virus primarily affects the upper and lower respiratory tracts and raises the risk of a variety of non-pulmonary consequences, the most severe and possibly fatal of which are cardiovascular problems. Data show that almost one-third of the patients with a moderate or severe form of COVID-19 had preexisting cardiovascular comorbidities such as diabetes mellitus, obesity, hypertension, heart failure, or coronary artery disease. SARS-CoV2 causes hyper inflammation, hypoxia, apoptosis, and a renin–angiotensin system imbalance in a variety of cell types, primarily endothelial cells. Profound endothelial dysfunction associated with COVID-19 can be the cause of impaired organ perfusion that may generate acute myocardial injury, renal failure, and a procoagulant state resulting in thromboembolic events. We discuss the most recent results on the involvement of endothelial dysfunction in the pathogenesis of COVID-19 in patients with cardiometabolic diseases in this review. We also provide insights on treatments that may reduce the severity of this viral infection.     

Translesion Synthesis or Repair by Specialized DNA Polymerases Limits Excessive Genomic Instability upon Replication Stress

DNA can experience “replication stress”, an important source of genome instability, induced by various external or endogenous impediments that slow down or stall DNA synthesis. While genome instability is largely documented to favor both tumor formation and heterogeneity, as well as drug resistance, conversely, excessive instability appears to suppress tumorigenesis and is associated with improved prognosis. These findings support the view that karyotypic diversity, necessary to adapt to selective pressures, may be limited in tumors so as to reduce the risk of excessive instability. This review aims to highlight the contribution of specialized DNA polymerases in limiting extreme genetic instability by allowing DNA replication to occur even in the presence of DNA damage, to either avoid broken forks or favor their repair after collapse. These mechanisms and their key regulators Rad18 and Polθ not only offer diversity and evolutionary advantage by increasing mutagenic events, but also provide cancer cells with a way to escape anti-cancer therapies that target replication forks.     

Influence of plasticizers and cryogenic grinding on the high‐cooling‐rate solidification behavior of PBT/PET blends

Two structurally different plasticizers (cyclic and linear) and the effect of cryogenic grinding on the solidification behavior at high cooling rates by a continuous cooling transformation approach of poly(butylene terephthalate)/poly(ethylene terephthalate), PBT/PET, blends are described. The solidification curve (density versus cooling rate) is confirmed as an effective tool to compare the differences in crystallization behavior under conditions mimicking processing. In comparison to the bulky cyclic plasticizer, the linear oligomeric one was found to have a more pronounced influence on the crystallization behavior. A 60/40 by weight PBT/PET blend shows a drop‐off of density at ～50 K/s. In the plasticized sample, the long‐range crystalline order appears up to a cooling rate of ～250K/s, making the blend comparable to pure PBT. Grinding the components before blending further improves crystallizability and synergy to the addition of the plasticizer. The results suggest the important role of local chain mobility in the solidification behavior at high cooling rates. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43083.     

Mechanical properties of virgin and recycled polyolefin‐based composite laminates reinforced with jute fabric

Polyolefin‐based composite laminates reinforced with jute fabric were prepared by compression molding and investigated in terms of flexural properties and impact behavior. The use of a virgin polypropylene as the matrix was compared with two polyolefin matrices coming from discarded car bumpers and selected packaging wastes, respectively, and mainly constituted by mixtures of polyethylene and polypropylene resins. The influence of a coupling agent (maleated polypropylene) was always considered in order to improve the interfacial adhesion and, consequently, the composite strength. The effect of this coupling agent, clearly dependent on the amount of polypropylene phase in the overall mixture, was found to be satisfactory only in the case of virgin polypropylene‐based systems. These latter, in presence of maleated polypropylene, have shown higher flexural parameters, lower propagation energy and higher breaking impact load with respect to uncompatibilized ones. Results were supported by morphological observations of impact surfaces, always highlighting a poor adhesion at the reinforcement–matrix interface except in compatibilized virgin polypropylene‐based laminates. POLYM. COMPOS., 36:2022–2029, 2015. © 2014 Society of Plastics Engineer     

Synthesis of Yb nanoparticles by laser ablation of ytterbium target in sodium bis(2-ethylhexyl)sulfosuccinate reverse micellar solution

Surfactant-coated ytterbium nanoparticles were produced by Nd:YAG laser ablation of a Yb bulk target immersed in sodium bis(2-ethylhexyl)sulfosuccinate (AOT)/n-heptane micellar solution. In our experimental conditions, as highlighted by IR spectroscopy, AOT molecules are not decomposed by the intense laser pulses but play a pivotal role in the stabilisation of Yb nanoparticles. The formation of Yb nanoparticles in the liquid phase was monitored by UV-Vis spectroscopy whereas the Yb/AOT composites obtained by evaporation of the organic solvent were characterised by XPS and TEM. Data analysis consistently shows the presence of surfactant-coated, nearly spherical and non-interacting Yb nanoparticles of mean diameter of 3 nm.Moreover, the presence of bigger polycrystalline nanoparticles (about 30%) in coexistence with smaller mono crystalline ones indicates that, after the rapid formation of the pristine Yb nanoparticles from plume condensation, two processes effectively compete for their size distribution: nanoparticle agglomeration and surfactant adsorption.     

Empirical Likelihood for Outlier Detection and Estimation in Autoregressive Time Series

Identification and estimation of outliers in time series is proposed by using empirical likelihood methods. Theory and applications are developed for stationary autoregressive models with outliers distinguished in the usual additive and innovation types. Some other useful outlier types are considered as well. A simulation experiment is used for studying the behaviour of the empirical likelihood‐based method in finite samples and indicates that the proposed methods are preferable when dealing with the non‐Gaussian data. Our simulations suggest that the usual sequential procedure for multiple outlier detection is suitable also for the methods based on empirical likelihood.