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The inerter is a vibration control element related to the acceleration between its two ends, which can increase inertia through a speed-increasing mechanism. Applying the inerter to a vibration isolator can enhance its low-frequency vibration isolation performance. Frictional force always exists in the high-speed mechanism of the inerter. Even if it is not large, its influence on the dynamic performance of the low-speed end cannot be ignored. This study analyzes the force of a ball-screw inerter using the kinetic energy theorem. The inerter force is then expanded into the first-order Taylor approximation, from which the inerter coefficient and apparent friction coefficient are determined. Based on the approximate formula of the inerter force, the nonlinear dynamic model and its corresponding dynamic equation for the inerter vibration isolator under base excitation are established. The nonlinear dynamic equation is then solved by averaging method, and the approximate analytical solutions for the relative displacement, absolute displacement, and displacement transmissibility are obtained. The analysis results show that a larger apparent friction coefficient reduces the resonance peaks of the displacement transmissibility and relative displacement amplitude, but it slightly increases the initial vibration isolation frequency, as well as the resonance and valley frequencies of the displacement transmissibility and relative displacement. Increasing the inerter-mass ratio can reduce the resonance frequency and initial vibration isolation frequency, thereby broadening the vibration isolation frequency domain. When friction is considered, increasing the inerter-mass ratio can suppress the resonance peaks of the displacement transmissibility and relative displacement.

The Delta variant is now replacing all other SARS-CoV-2 variants. We found a mean R0 of 5.08, which is much higher than the R0 of the ancestral strain of 2.79. Rapidly ramping up vaccine coverage rates while enhancing public health and social measures is now even more urgent and important.

The major variant of concerns (VOCs) have shared mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins, mostly on the S1 unit and resulted in higher transmissibility rate and affect viral virulence and clinical outcome. The spike protein mutations and other non-structural protein mutations in the VOCs may lead to escape approved vaccinations in certain extend. We will discuss these VOC mutations and discuss the need for combination therapeutic strategies targeting viral cycle and immune host responses.

Background As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. Methods In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number ( R 0 ) from the RP model to assess the transmissibility of the SARS-CoV-2. Results The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. Conclusions Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

A quasi-zero-stiffness (QZS) vibration isolator is an ideal device for low-frequency vibration isolation. However, its stiffness increases steeply against the displacement, which renders a QZS isolator to be less effective in an ultra-low-frequency range. Aiming at solving this issue, a new nonlinear ultra-low-frequency vibration isolator with a dual quasi-zero-stiffness (DQZS) mechanism is put forward by combining two subordinate QZS mechanisms with a vertical linear spring in parallel. The subordinate mechanism itself has a QZS feature, which provides negative stiffness along the vertical direction through an oblique link rod. The parameter design of the isolator is carried out to fulfil quasi-zero stiffness, which shows that the stiffness–displacement curve is much lower and more flat than the traditional QZS (TQZS) isolator in a wide displacement range. The dynamic behaviours of the DQZS vibration isolation system (VIS) are determined by employing the harmonic balance method, and the vibration isolation performance is evaluated by using theoretical, numerical and experimental transmissibility. It shows that both the beginning frequency of the vibration isolation and the peak transmissibility of the DQZS VIS are lower than the TQZS isolator, which indicates better vibration isolation performance of this ultra-low-stiffness DQZS VIS.

We aimed to clarify the epidemiologic and clinical importance of evolutionary events that occurred in carbapenem-resistant Klebsiella pneumoniae (CRKP). We collected 203 CRKP causing bloodstream infections in a tertiary hospital in China during 2013-2017. We detected a subclonal shift in the dominant clone sequence type (ST) 11 CRKP in which the previously prevalent capsular loci (KL) 47 had been replaced by KL64 since 2016. Patients infected with ST11-KL64 CRKP had a significantly higher 30-day mortality rate than other CRKP-infected patients. Enhanced virulence was further evidenced by phenotypic tests. Phylogenetic reconstruction demonstrated that ST11-KL64 is derived from an ST11-KL47-like ancestor through recombination. We identified a pLVPK-like virulence plasmid carrying rmpA and peg-344 in ST11-KL64 exclusively from 2016 onward. The pLVPK-like-positive ST11-KL64 isolates exhibited enhanced environmental survival. Retrospective screening of a national collection identified ST11-KL64 in multiple regions. Targeted surveillance of this high-risk CRKP clone is urgently needed.

The vibration characteristics of car seats directly influence the ride comfort. Polyurethane foam is the key part of a seat, and its physical parameters have an important impact on the seat. In this study, the influence of the foam thickness and foam hardness on the vibration characteristics of seat cushion with different excitation magnitudes was investigated by using transmissibility and seat effective amplitude transmissibility (SEAT) value. First, vibration tests were carried out at a vertical vibration simulator with width-limited white noise vibration frequencies from 0.5 to 20 Hz with root-mean-square (r.m.s.) values of 0.4, 0.8, and 1.2 m/s2, the acceleration at the platform and the body-foam interfaces were measured to calculate the transmissibility, and the influence of the foam physical properties on the transmissibility was analyzed. Then, the SEAT value was introduced to assess the vibration isolation efficiency of the foam cushion, and the influence of the foam physical properties of the foam cushion on the vibration isolation efficiency was analyzed. With increasing thickness of the foam and decreasing hardness of the foam at the seat pan, the peak transmissibility increased and the resonance frequency decreased. The SEAT values show that increasing the foam thickness is beneficial to the improvement of the vibration isolation efficiency of the seat, but there is a diminishing return; the combination of physical parameters of low hardness and high thickness could make the vibration isolation performance of the seat better. In addition, the nonlinearity of human-seat system during different vibration magnitude was found.

Vibration-based data-driven structural damage identification methods have gained large popularity because of their independence of high-fidelity models of target systems. However, the effectiveness of existing methods is constrained by critical shortcomings. For example, the measured vibration responses may contain insufficient damage-sensitive features and suffer from high instability under the interference of random excitations. Moreover, the capability of conventional intelligent algorithms in damage feature extraction and noise influence suppression is limited. To address the above issues, a novel damage identification framework was established in this study by integrating massive datasets constructed by structural transmissibility functions (TFs) and a deep learning strategy based on one-dimensional convolutional neural networks (1D CNNs). The effectiveness and efficiency of the TF-1D CNN framework were verified using an American Society of Civil Engineers (ASCE) structural health monitoring benchmark structure, from which dynamic responses were captured, subject to white noise random excitations and a number of different damage scenarios. The damage identification accuracy of the framework was examined and compared with others by using different dataset types and intelligent algorithms. Specifically, compared with time series (TS) and fast Fourier transform (FFT)-based frequency-domain signals, the TF signals exhibited more significant damage-sensitive features and stronger stability under excitation interference. The utilization of 1D CNN, on the other hand, exhibited some unique advantages over other machine learning algorithms (e.g., traditional artificial neural networks (ANNs)), particularly in aspects of computation efficiency, generalization ability, and noise immunity when treating massive, high-dimensional datasets. The developed TF-1D CNN damage identification framework was demonstrated to have practical value in future applications.

Genetic variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2) have been globally surging and devastating many countries around the world. There are at least eleven reported variants dedicated with inevitably catastrophic consequences. In 2021, the most dominant Delta and Omicron variants were estimated to lead to more severity and deaths than other variants. Furthermore, these variants have some contagious characteristics involving high transmissibility, more severe illness, and an increased mortality rate. All outbreaks caused by the Delta variant have been rapidly skyrocketing in infection cases in communities despite tough restrictions in 2021. Apart from it, the United States, the United Kingdom and other high-rate vaccination rollout countries are still wrestling with this trend because the Delta variant can result in a significant number of breakthrough infections. However, the pandemic has changed since the latest SARS-CoV-2 variant in late 2021 in South Africa, Omicron. The preliminary data suggest that the Omicron variant possesses 100-fold greater than the Delta variant in transmissibility. Therefore, this paper aims to review these characteristics based on the available meta-data and information from the first emergence to recent days. Australia and the five most affected countries, including the United States, India, Brazil, France, as well as the United Kingdom, are selected in order to review the transmissibility, severity and fatality due to Delta and Omicron variants. Finally, the vaccination programs for each country are also reviewed as the main factor in prevention.

On March 11, 2020, Italy imposed a national lockdown to curtail the spread of severe acute respiratory syndrome coronavirus 2. We estimate that, 14 days after lockdown, the net reproduction number had dropped below 1 and remained stable at »0.76 (95% CI 0.67-0.85) in all regions for >3 of the following weeks.