On a nonlinear heat equation associated with Dirichlet -- Robin conditions

This paper is devoted to the study of a nonlinear heat equation associated with Dirichlet-Robin conditions. At first, we use the Faedo -- Galerkin and the compactness method to prove existence and uniqueness results. Next, we consider the properties of solutions. We obtain that if the initial condition is bounded then so is the solution and we also get asymptotic behavior of solutions as. Finally, we give numerical resultsComment: 20 page

Study of Micro-hardness of High-Speed W9Mo4Co8 Steel Plates in Pendulum Grinding by Abrasive Wheel Periphery

In cutting tool assembly, grinding is the most important technological step of the finishing treatment, largely determining the workmanship. An increase of micro-hardness after grinding relative to the original one indicates the dominant role of abrasive tool force impact on the ground surface. A decrease, in contrast, evidences a significant softening under the influence of heat source. This research based on nonparametric statistics to predict the effect of wheel characteristics with abrasives 25A, 92A/25A, 34A, 5A, EKE, 5NQ, TGX, 5SG and with graininess 46 (F46), 60 (F60), 80 with different porosities (structure numbers 6-12), and the expected measures of position and dispersion on the micro-hardness of the surface of a high-speed cutting plate (HSCP) made of W9Mo4Co8 steel. It was found that grinding this HSCP by wheels 5NQ46I6VS3, 5SG46K12VXP, 5SG60K12VXP, 5SG46I12VXP, 25AF46M12V5–PO, 25AF46M12V5–PO3, 25АF46M10V5–PO, 25AF46M10V5–PO3, 25AF46K10V5–PO3, 25AF60M10V5–PO3, 25AF46L10V5–KF35, EKE46K3V, 92A/25AF46L6V20 occurred without surface softening for 50% of the details from the operating batch

On a viscoelastic heat equation with logarithmic nonlinearity

This work deals with the following viscoelastic heat equations with logarithmic nonlinearity ut − ∆u + Z t 0 g(t − s)∆u(s)ds = |u| p−2u ln |u|. In this paper, we show the effects of the viscoelastic term and the logarithmic nonlinearity to the asymptotic behavior of weak solutions. Our results extend the results of Peng and Zhou [Appl. Anal. 100(2021), 2804–2824] and Messaoudi [Progr. Nonlinear Differential Equations Appl. 64(2005), 351–356.]

Pairing effects on the collectivity of quadrupole states around 32Mg

The first 2+ states in N=20 isotones including neutron-rich nuclei 32Mg and 30Ne are studied by the Hartree-Fock-Bogoliubov plus quasiparticle random phase approximation method based on the Green's function approach. The residual interaction between the quasiparticles is consistently derived from the hamiltonian density of Skyrme interactions with explicit velocity dependence. The B(E2) transition probabilities and the excitation energies of the first 2+ states are well described within a single framework. We conclude that pairing effects account largely for the anomalously large B(E2) value and the very low excitation energy in 32Mg.Comment: 14 pages, 9 figure

Deep Learning-Based Signal Detection for Dual-Mode Index Modulation 3D-OFDM

In this paper, we propose a deep learning-based signal detector called DuaIM-3DNet for dual-mode index modulation-based three-dimensional (3D) orthogonal frequency division multiplexing (DM-IM-3D-OFDM). Herein, DM-IM-3D- OFDM is a subcarrier index modulation scheme which conveys data bits via both dual-mode 3D constellation symbols and indices of active subcarriers. Thus, this scheme obtains better error performance than the existing IM schemes when using the conventional maximum likelihood (ML) detector, which, however, suffers from high computational complexity, especially when the system parameters increase. In order to address this fundamental issue, we propose the usage of a deep neural network (DNN) at the receiver to jointly and reliably detect both symbols and index bits of DM-IM-3D-OFDM under Rayleigh fading channels in a data-driven manner. Simulation results demonstrate that our proposed DNN detector achieves near-optimal performance at significantly lower runtime complexity compared to the ML detector

Surface Potential of MIBC at Air/Water Interface: a Molecular Dynamics Study

The interfacial behavior of alcohols is significantly different from bulk due to amphiphilic structures. Such behavior can dramatically change the interfacial properties within the nano-scale of interfacial layer and have significant applications in industrial processes such as mineral flotation. In this study, the adsorption of MIBC (methyl isobutyl carbinol), a popular frother, was investigated by molecular dynamics. Surface potential was obtained at different surface concentration and compared to experimental data. The simulations results compared well with theoretical data using a single adjustable parameter. It has been found that the disordered water molecules contribute to surface potential more than MIBC molecules. The study demonstrates the application of MD in investigating the efficiency of frother systems

Systematic review of respiratory viral pathogens identified in adults with community-acquired pneumonia in Europe

Community-acquired pneumonia (CAP) is an important respiratory disease and the fifth leading cause of mortality in Europe. The development of molecular diagnostic tests has highlighted the contributions of respiratory viruses to the aetiology of CAP, suggesting the incidence of viral pneumonia may have been previously underestimated. We performed a systematic review and meta analysis to describe the overall identification of respiratory viruses in adult patients with CAP in Europe, following PRISMA guidelines (PROSPERO; CRD42016037233). We searched EMBASE, MEDLINE, CINAHL, WHOLIS, COCHRANE library and grey literature sources for relevant studies, and screened these against protocol eligibility criteria. Two researchers performed data extraction and risk of bias assessments, independently, using a piloted form. Results were synthesised narratively, and random effects meta-analyses performed to calculate pooled estimates of effect; heterogeneity was quantified using I2.Twenty-eight studies met inclusion criteria of which 21 were included in the primary meta-analysis. The pooled proportion of patients with identified respiratory viruses was 22.0% (95% CI: 18.0%-27.0%), rising to 29.0% (25.0%–34.0%) in studies where polymerase chain reaction (PCR) diagnostics were performed. Influenza virus was the most frequently detected virus in 9% (7%-12%) of adults with CAP. Respiratory viruses make a substantial contribution to the aetiology of CAP in adult patients in Europe; one or more respiratory viruses are detected in about one quarter of all cases

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

Continuum quasiparticle random phase approximation and the time dependent Hartree-Fock-Bogoliubov approach

Quadrupole excitations of neutron-rich nuclei are analyzed by using the linear response method in the Quasiparticle Random Phase Approximation (QRPA). The QRPA response is derived starting from the time-dependent Hartree-Fock-Bogoliubov (HFB) equations. The residual interaction between the quasiparticles is determined consistently from the two-body force used in the HFB equations, and the continuum coupling is treated exactly. Calculations are done for the neutron-rich oxygen isotopes. It is found that pairing correlations affect the low-lying states, and that a full treatment of the continuum can change the structure of the states in the giant resonance region.Comment: 17 pages, 7 figures. Revised version with comments and references adde