On the non-blocking conditions of self-routeing multistage interconnection networks

This paper studies the non-blocking conditions of a generic N × N multistage interconnection network, such as an omega network or an n-cube network, in which only one path connects any inlet to each outlet and different I/O paths can share interstage links. It is widely known that any of these networks is non-blocking for a compact and monotone pattern of k ≤ N I/O paths. Recently it has become very important to show the network non-blocking property for permutation sets, wider than the compact and monotone, which are usually encountered in broadband ATM networks. By using a new approach based on the concept of distance between I/O paths, we show here that these networks are non-blocking for a set of I/O paths obtained by shifting cyclically the inlets of a compact and monotone pattern of I/O paths by an arbitrary number of steps.     

An adaptive hybrid surrogate model

The determination of complex underlying relationships between system parameters from simulated and/or recorded data requires advanced interpolating functions, also known as surrogates. The development of surrogates for such complex relationships often requires the modeling of high dimensional and non-smooth functions using limited information. To this end, the hybrid surrogate modeling paradigm, where different surrogate models are combined, offers an effective solution. In this paper, we develop a new high fidelity surrogate modeling technique that we call the Adaptive Hybrid Functions (AHF). The AHF formulates a reliable Crowding Distance-Based Trust Region (CD-TR), and adaptively combines the favorable characteristics of different surrogate models. The weight of each contributing surrogate model is determined based on the local measure of accuracy for that surrogate model in the pertinent trust region. Such an approach is intended to exploit the advantages of each component surrogate. This approach seeks to simultaneously capture the global trend of the function as well as the local deviations. In this paper, the AHF combines four component surrogate models: (i) the Quadratic Response Surface Model (QRSM), (ii) the Radial Basis Functions (RBF), (iii) the Extended Radial Basis Functions (E-RBF), and (iv) the Kriging model. The AHF is applied to standard test problems and to a complex engineering design problem. Subsequent evaluations of the Root Mean Squared Error (RMSE) and the Maximum Absolute Error (MAE) illustrate the promising potential of this hybrid surrogate modeling approach.     

Direct-EI in LC-MS: towards a universal detector for small-molecule applications

This review article will give an up-to-date and exhaustive overview on the efficient use of electron ionization (EI) to couple liquid chromatography and mass spectrometry (LC-MS) with an innovative interface called Direct-EI. EI is based on the gas-phase ionization of the analytes, and it is suitable for many applications in a wide range of LC-amenable compounds. In addition, thanks to its operating principles, it prevents unwelcome matrix effects (ME). In fact, although atmospheric pressure ionization (API) methodologies have boosted the use of LC-MS, the related analytical methods are sometime affected by inaccurate quantitative results, due to unavoidable and unpredictable ME. In addition, API's soft ionization spectra always demand for costly and complex tandem mass spectrometry (MS/MS) instruments, which are essential to acquire an "information-rich" spectrum and to obtain accurate quantitative information. In EI a one-stage analyzer is sufficient for a qualitative investigation and MS/MS detection is only used to improve sensitivity and to cut chemical noise. The technology illustrated here provides a robust and straightforward access to classical, well-characterized EI data for a variety of LC applications, and readily interpretable spectra for a wide range of areas of research. The Direct-EI interface can represent the basis for a forthcoming universal LC-MS detector for small molecules.     

Variable-gradient generator for micro- and nano-HPLC

A new, simple device generates accurate nano- and microflow rate gradients from any conventional HPLC system. The core of the new device is represented by an electric-actuated, computer-controlled, multiposition HPLC valve. The valve hosts six reservoirs for as many different mobile-phase compositions of increasing strength. A low flow rate stream pushes the weakest solvent through the column as long as required and at the desired flow rate, until the chromatographic run is started. From this time on, the electric actuation allows one to select which reservoir will be on-line with the column and for how long, thus generating a specific solvent gradient, through a sequence of controlled segments of precise mobile-phase composition. This permits one not only to exactly reproduce the programmed slope but also to achieve different gradient shapes (i.e., linear, convex, concave) for different separation needs. The new device has proven to be reliable and reproducible even at the lowest flow rate tested (250 nL x min(-1)) and in different chromatographic conditions.     

The 5-V window of polarizability of fluorinated diamond electrodes in aqueous solutions

Heavily doped diamond films are quite actively studied for their promising applications in industrial as well as in fundamental electrochemistry (both for physicochemical studies and in the field of electroanalysis), because of their very high stability toward chemical and electrochemical oxidative attacks. Fluorinated diamond electrodes exhibit an exceptionally lower electrocatalytic activity toward reactions involving adsorbed intermediates, as a result of the F-termination of the surface dangling bonds. This feature allows the investigation of the widest range of potentials for an electrode material in aqueous solution, being limited only by the formation of free hydrogen [E degrees (H*/H2) = -2.3 V(SHE)] and hydroxyl [E degrees (*OH,H+/H2O) = 2.74 V(SHE)] radicals, at the two boundaries of the approximately 5-V polarization window.     

Buffering-deflection tradeoffs in optical burst switching

A very important issue in optical burst switching (OBS) networks is the excessive burst drop when no suitable network resources are found during path reservation. In this study, a network scenario is evaluated in which AWG-based optical nodes are used as burst router nodes within the optical network. The two classical solutions to solve the burst contentions on the channels outgoing from the node are considered, that is, either based on buffering within the node, or by exploiting deflection routing. A performance evaluation is carried out to evaluate and compare these solutions for different network topologies with different node and traffic parameters. Our main contribution is to set numerical tradeoffs between burst deflection through the network and buffering in the node, so that a guidance in optical network design is provided where node buffering is inherently technologically limited.     

Regulatory Noncoding and Predicted Pathogenic Coding Variants of CCR5 Predispose to Severe COVID-19

Genome-wide association studies (GWAS) found locus 3p21.31 associated with severe COVID-19. CCR5 resides at the same locus and, given its known biological role in other infection diseases, we investigated if common noncoding and rare coding variants, affecting CCR5, can predispose to severe COVID-19. We combined single nucleotide polymorphisms (SNPs) that met the suggestive significance level (P ≤ 1 × 10⁻⁵) at the 3p21.31 locus in public GWAS datasets (6406 COVID-19 hospitalized patients and 902,088 controls) with gene expression data from 208 lung tissues, Hi-C, and Chip-seq data. Through whole exome sequencing (WES), we explored rare coding variants in 147 severe COVID-19 patients. We identified three SNPs (rs9845542, rs12639314, and rs35951367) associated with severe COVID-19 whose risk alleles correlated with low CCR5 expression in lung tissues. The rs35951367 resided in a CTFC binding site that interacts with CCR5 gene in lung tissues and was confirmed to be associated with severe COVID-19 in two independent datasets. We also identified a rare coding variant (rs34418657) associated with the risk of developing severe COVID-19. Our results suggest a biological role of CCR5 in the progression of COVID-19 as common and rare genetic variants can increase the risk of developing severe COVID-19 by affecting the functions of CCR5.