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In this work, we present a method to simultaneously detect the mass and the position of an attached microparticle using a bridge-type micro-beam resonant mass sensor under axial pre-tension. Simultaneous detection of the mass and the position is innovatively enabled by deliberately varying the axial pre-tension, utilizing only the fundamental frequency. As an important dissipation mechanism, thermoelastic damping (TED) in micro-/nano-resonators imposes an upper limit on the quality factor and the minimum detectable mass of resonant mass sensors. Accordingly, TED of micro-/nano-beam resonant mass sensors with axial pre-tension is analyzed by the thermal energy method, and heat conduction along both the thickness direction and axial direction is considered. The effects exerted by the pre-tension on the sensitivity and TED of resonant mass sensors are systematically investigated. Numerical results reveal that axial pre-tension not only enhances the mass sensitivity but also reduces the TED of the resonant mass sensor. Furthermore, effects of other factors, such as aspect ratio, vibration mode, mass and position of the attached particle, on TED are examined as well. This work provides a theoretical guidance to the extraction of mass of microparticles, cells and molecules by experiment.

Polymer adhesives are widely used in daily applications and in industry owing to their flexibility and overall non-toxicity, particularly in interfacial adhesion. The spreading of polymer adhesives on adherend is one of the essential considerations for the interfacial adhesion of polymer adhesives, which is strongly related to their wetting behaviors. While relationships between polymer microstructure and adhesion have been investigated in previous studies, it remains challenging to unveil the effect of polymer microstructure on wettability. To address this issue, here we utilize coarse-grained molecular dynamics (CGMD) simulations to systematically elucidate how the wettability of a polymer adhesive droplet on a surface depends on bending stiffness. The wetting dynamics and the contact angle are studied to show the evolution of morphology of droplets during the wetting process. The results indicate the wettability is weakened by the increase of bending stiffness of polymer chain. Detailed thermodynamic property analysis is further conducted, revealing that the adhesion between the polymer droplet and substrate deteriorates due to the decline of wettability. Interestingly, we observe such deterioration becomes more significant by both increasing the temperature and decreasing the bending stiffness. Our study sheds light on the dependence of chain bending stiffness and temperature on the wetting behavior of polymer adhesive droplets, and offers insights, which, upon experimental validation can then be used for the design of adhesives or hydrogels.

In this study, we developed a micromechanics scheme to predict the upper and lower bounds on the creep strain and stress relaxation induced by interface diffusion in metal-matrix particulate composites. The normal stress acting on the matrix-inclusion interface, which is the driving force for interface diffusion, is estimated by using the Hashin-Shtrikman bounds and mean-field micromechanics theory. Analytical solutions of upper and lower bounds on the creep strain under constant stress and the relaxed stress at fixed strain are obtained. Results of this work show that the ultimate creep strain and relaxed stress are only related to the material properties and the percentage of each component, such as volume fraction of inclusion and elastic modulus ratio of inclusion to matrix. The parameters of interface diffusion only influence the rate of creep strain. It is found that the creep deformation and stress relaxation of composites are more sensitive to the volume fraction of inclusion than the elastic modulus ratio. The methodology of this study also applies to analysis of creep deformation of composites where both the matrix creep and interface diffusional creep need to be considered. The present study offers new perspectives for in-depth understanding of creep behavior of composites driven by mass diffusion along inclusion-matrix interface.

Chitin-based bio-composites in nature such as the exoskeleton of crustaceans and squid pen usually exhibit hierarchical structures, where the chitin crystal is the most fundamental structural hierarchy as the load-bearing scaffold. Previous studies have unveiled the mechanical design of the structures at high hierarchies in these biomaterials, while the structure–property relationship remains unclear for the chitin crystal at the bottom hierarchy. In this paper, we investigate the mechanical properties of chitin crystals with $$\alpha$$ - and $$\beta$$ -polymorphic structures that mainly exist over the animal kingdom using the reactive force field molecular dynamics simulations. We first validate the force field parameters adopted from literature then study the mechanical behaviors of chitin polymorphs in response to the tensile and shear deformation. It is found that the mechanical performance of $$\alpha$$ -chitin crystal is comprehensively superior to that of $$\beta$$ -chitin crystal, such as the elastic modulus, work of fracture, shear modulus and strength. Different from the $$\beta$$ -chitin, yielding caused by the transformation of crystalline structure is observed in the $$\alpha$$ -chitin during uniaxial tension. Based on the mechanical properties obtained from simulations and theoretical analysis, we can deduce that the $$\alpha$$ -chitin shows higher wear resistance than the $$\beta$$ -chitin, implying better protection against the surface scratch that is one of the environmental threats to organisms. Our results shed light on the structure–property relationship of chitin crystals at the molecular level. The fundamental understanding of mechanical properties of chitin polymorphs is of great significance for the bottom-up modeling and design of chitin-based bio-composites.

In this paper, the creep behavior due to interface diffusion in unidirectional fiber-reinforced metal matrix composites under general transverse loading conditions is studied. A micromechanics model is adopted to estimate the average stresses in fibers, which is demonstrated to be of reasonable accuracy by comparing with finite element analysis. The creep deformation due to interface diffusion is characterized by a tensor-form creep strain rate, which is related to the components of average stress in fibers and possesses incompressibility. The derived creep strain tensor is then introduced into fibers as eigenstrain to estimate the effect of creep strain on stress redistribution in composites. Eventually, the macroscopic creep strain of composites under constant external loads and the stress relaxation at fixed displacements due to interface diffusion are calculated by the incremental creep analysis procedures based on the average field theory. The effects of loading conditions on the overall creep behavior are examined in detail. Results of this study show that under the fixed strain condition, the initial biaxial stress ratio actually varies rather than remains unchanged during the stress relaxation process. In both constant stress and constant strain conditions, stresses in fibers have a propensity to approach hydrostatic stress state, thus suppressing the interface diffusion. These findings were not reported in previous researches and may bring new understanding on diffusion-induced creep deformation in metal matrix composite materials.

Understanding the relationship between the microstructures and overall properties is one of the basic concerns for material design and applications. As a ubiquitous structural configuration in nature, the folded morphology is also widely observed in graphene-based nanomaterials, namely grafold. Recently, a self-folded graphene film (SF-GF) material has been successfully fabricated by the assembly of grafolds and exhibits promising applications in thermal management. However, the dependence of thermal properties of SF-GF on the structural features of grafold has remained unclear. We here develop a theoretical model to describe the thermal transport behavior in SF-GF. Our model demonstrates the relationship between the fold length of grafolds and thermal properties of SF-GF. It serves as an efficient and portable tool to predict the temperature profile and thermal conductivity of SF-GF with good validations by large-scale molecular dynamics simulations. Using this model, we further study the evolution of thermal conductivity of SF-GF with the unfolding deformation during the stretch. Moreover, the effect of geometrical irregularity of grafolds is uncovered. The model developed in this work not only provides practical guidelines for the manipulation and design of thermal properties of SF-GF, but also benefits the understanding of thermal transport behaviors in other two-dimensional nanomaterials with folded structures.

Thermoelastic damping (TED) is one of the main energy dissipation mechanisms in micro/nano resonators and one of the major concerns in respect to performance of micro-electromechanical systems and ...

It has been reported that application of tensile axial stress can simultaneously increase quality factor and resonant frequency for micromechanical resonators. In this study, we formulate a...

In this study, we present a new micromechanics method to predict the transverse creep rate induced by interface diffusion in unidirectional fiber-reinforced composites and evolution of overall creep strain under constant applied stress. An analytical solution for creep rate induced by interfacial diffusion, depending on the applied stress, fiber volume fraction and radius of the fiber, as well as the modulus ratio between the fiber and the matrix, is obtained. A micromechanics model is proposed to estimate the stress field in the fiber, which is related to the driving force for the interface diffusion, the normal stress on the interface. Comparison with finite element analysis shows that the present micromechanics model is of good accuracy, especially for high fiber volume fraction and large elastic modulus ratio between fiber and matrix. With the proposed micromechanics method based on the average field theory, the variation of overall creep strains and stresses with time in fibers under constant external load are analyzed by the incremental creep analysis procedures.

Highly thermally conductive carbon fibers (CFs) have become an important material to meet the increasing demand for efficient heat dissipation. To date, high thermal conductivity has been only achieved in specific pitch-based CFs with high crystallinity. However, obtaining high graphitic crystallinity and high thermal conductivity beyond pitch-CFs remains a grand challenge. Here, a 2D-topology-seeded graphitization method is presented to mediate the topological incompatibility in graphitization by seeding 2D graphene oxide (GO) sheets into the polyacrylonitrile (PAN) precursor. Strong mechanical strength and high thermal conductivity up to 850 W m

Outbreaks of coronaviruses, especially SARS-CoV-2, pose a serious threat to global public health. Development of vaccines to prevent the coronaviruses that can infect humans has always been a top priority., Coronaviruses that infect humans belong to the Alphacoronavirus (including HCoV-229E) and Betacoronavirus (including SARS-CoV and SARS-CoV-2) genera. In particular, SARS-CoV-2 is currently a major threat to public health worldwide. The spike (S) homotrimers bind to their receptors via the receptor-binding domain (RBD), which is a major target to block viral entry. In this study, we selected Alphacoronavirus (HCoV-229E) and Betacoronavirus (SARS-CoV and SARS-CoV-2) as models. Their RBDs exist two different conformational states (“lying” or “standing”) in the prefusion S-trimer structure. Then, the differences in the immune responses to RBDs from these coronaviruses were analyzed structurally and immunologically. Our results showed that more RBD-specific antibodies (antibody titers: 1.28 × 105 and 2.75 × 105, respectively) were induced by the S-trimer with the RBD in the standing state (SARS-CoV and SARS-CoV-2) than the S-trimer with the RBD in the lying state (HCoV-229E; antibody titers

African swine fever (ASF) is an acute, hemorrhagic, and highly contagious disease caused by African swine fever virus (ASFV). The mortality rate of acute infection up to 100% have posed an unprecedented challenge of the swine industry. Currently no commercial antiviral drug is available for the control and treatment of ASFV. The structural resolution of ASFV virions reveals the details of ASFV morphogenesis, providing a new perspective for the research and promotion of the development of ASFV vaccines. Although the architecture of ASFV have been solved via cryo-EM, the structural details of four of the five viral layers remain unclear (except the outer capsid). In this study, we resolved the crystal structure of the ASFV core shell protein p15. The secondary structural elements of a protomer include four α-helix structures and six antiparallel β-strands. Further analysis revealed that ASFV p15 forms disulfide-linked trimers between the Cys9 from one protomer and Cys30 from other protomer. Additionally, the nucleic acid-binding property was characterized by electrophoretic mobility shift assay. Two critical amino acid Lys10 and Lys39 have been identified which is essential to the nucleic acid-binding affinity of ASFV p15. Together, these findings may provide new insight into antiviral drug development.

Liver ischemia-reperfusion (I/R) injury is a pathological process that often occurs during liver and trauma surgery. This study aimed to investigate the protective effect and potential mechanisms of sufentanil on hepatic I/R injury. I/R rat model and hypoxic/reoxygenation (H/R)-induced buffalo rat liver (BRL)-3A cell model were established. Following pretreatment with sufentanil, the enzymatic activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in rat serum and the changes of hepatic histopathology were evaluated to track the extent of liver injury. The levels of inflammatory factors were determined with ELISA kits and RT-qPCR. The infiltration of macrophages was assessed after detecting monocyte chemoattractant protein 1 (MCP-1) and F4/80 expression. Additionally, apoptosis was measured by means of TUNEL staining, and gene expression related to apoptosis was examined using RT-qPCR and western blotting. Then, TP53BP2 was overexpressed in BRL-3A cells exposed to H/R condition to evaluate whether sufentanil defended the liver against injury by regulating TP53BP2 expression. Moreover, the potential binding site of ATF4 on the TP53BP2 promoter was analyzed using JASPAR databases and verified by chromosomal immunoprecipitation (ChIP) assay. Furthermore, TP53BP2 expression and endoplasmic reticulum stress (ERS)-related protein levels were determined after ATF4 was overexpressed in sufentanil-treated BRL-3A cells. Results revealed that sufentanil significantly improved hepatic I/R injury, decreased the levels of inflammatory factors, and alleviated hepatocyte apoptosis. Notably, upregulated TP53BP2 expression was observed in hepatic tissues, and TP53BP2 overexpression markedly reversed the protective effects of sufentanil on the inflammation and apoptosis in H/R-stimulated BRL-3A cells. Additionally, ATF4 was confirmed to combine with the TP53BP2 promoter. ATF4 upregulation attenuated the inhibitory effects of sufentanil on the expression of TP53BP2 and ERS-associated proteins. These findings demonstrated that sufentanil protects the liver from inflammation and apoptosis injury induced by I/R by inhibiting ATF4 expression and further suppressing TP53BP2 expression, suggesting a promising therapeutic candidate for the treatment of liver I/R injury.

In this paper, the stochastic boundary element method of piezoelectric problems with randomness of material parameters and randomness of applied loads is proposed. By using the method of first-order Taylor expansion, each random quantity is written into the sum of the mean and deviation. The boundary integral equations corresponding to the means and deviations of the displacements and electric potential are derived, respectively. It is demonstrated that the randomness of material parameters can be transformed into the equivalent random body forces and equivalent random charge density, so that the fundamental solutions of deterministic piezoelectric problems can be used in boundary integral equations of the means or deviations due to the similarity between the governing equations with randomness and those of deterministic piezoelectric problems. Finally, several numerical examples are performed to verify the validity of the proposed stochastic boundary element method.

Japanese encephalitis virus (JEV) infection induces brain tissue disease characterized by neuron death. however, little is known about the underlying mechanism. Using RNA sequencing, we profiled global mRNA expression changes in response to in vitro and in vivo JEV infection. Integration analysis of in vitro and in vivo mRNA transcriptome revealed that JEV infection regulated apoptosis-related Foxo signaling pathway. Foxo expression was reduced by JEV infection in vitro and in vivo. Knockdown of Foxo promoted apoptosis, while its overexpression reduced apoptosis in JEV-infected Neuro-2a cells. JEV infection in Neuro-2a cells decreased the expression of Foxo downstream genes including pro-apoptotic protein Bim, anti-apoptotic protein Bcl-6 and p21. Overexpression of anti-apoptotic proteins Bcl-6 and p21 repressed JEV-induced apoptosis. These findings suggest that Foxo primarily exerts an anti-apoptotic function via Bcl-6 and p21 in JEV-infected Neuro-2a cells. A STAT3 binding site was identified in the promoter region of Foxo by TFBIND software and confirmed by ChIP and reporter assays. JEV infection reduced STAT3 expression as well as its binding at the Foxo promoter compared to mock infection in Neuro-2a cells. Moreover, STAT3 knockdown reduced Foxo promoter activity and Foxo expression. Therefore, JEV reduced Foxo expression, at least in part, by downregulating STAT3. Taken together, we found that JEV induced cell apoptosis by inhibiting STAT3-Foxo-Bcl-6/p21 pathway, which provides a novel insight into JEV-caused encephalitis.

This paper presents an analytical study on evaluation of support loss in micromechanical resonators undergoing in-plane flexural vibrations. Two-dimensional elastic wave theory is used to determine the energy transmission from the vibrating resonator to the support. Fourier transform and Green's function technique are adopted to solve the problem of wave motions on the surface of the support excited by the forces transmitted by the resonator onto the support. Analytical expressions of support loss in terms of quality factor, taking into account distributed normal stress and shear stress in the attachment region, and coupling between the normal stress and shear stress as well as material disparity between the support and the resonator, have been derived. Effects of geometry of micro-beam resonators, and material dissimilarity between support and resonator on support loss are examined. Numerical results show that ‘harder resonator’ and ‘softer support’ combination leads to larger support loss. In addition, the Perfectly Matched Layer (PML) numerical simulation technique is employed for validation of the proposed analytical model. Comparing with results of quality factor obtained by PML technique, we find that the present model agrees well with the results of PML technique and the pure-shear model overestimates support loss noticeably, especially for resonators with small aspect ratio and large material dissimilarity between the support and resonator.

The physical and morphological properties of particles and interfaces can seriously impact the whole mechanical behavior of particle-reinforced composites. In this work, we devise a robust coupling model of the discrete element method (DEM) and the finite element method (FEM) to numerically investigate the effective elastic moduli of particle-reinforced composites consisting of elliptical particles of high packing density, compliant interfaces and homogeneous matrix. In the numerical model, a novel parametric equation for the topological geometry of an interface that is treated as an interphase model is formulated to realize a compliant (penetrable) layer with a constant finite thickness coated surrounding each elliptical particle. Additionally, a convenient strategy is implemented to cope with periodic boundary conditions containing numerous particles. On the other hand, we also propose a micromechanical theoretical framework to derive the effective elastic properties of such three-phase composites by incorporating the fraction of compliant interfaces that is theoretically computed by using the statistical geometry of composites. It is shown that our numerical and theoretical models lead to the prediction of elastic moduli of particle-reinforced composites with nonspherical particles of high packing density to a reasonable accuracy by comparing with available experimental data. Moreover, utilizing the proposed models, we systematically investigate the influence of the characteristics of particles and interphase such as the high packing density and geometries of elliptical particles, and interphase fraction, thickness and stiffness on the elastic moduli of particle-reinforced composites. We find that these physical characteristics play significant roles in determining the mechanical behavior of composites, suggesting that the properties of such materials can be tailored via proper composites engineering and design.

In this study, a micromechanics framework considering both interface diffusion and matrix creep is proposed to analyze the creep behavior of PM alloys. Based on the mean-field micromechanics theory, the creep strain rate induced by interface diffusion in the particulate composite under uniaxial loading is derived. The creep strain is introduced as an eigenstrain into the inclusion, whose rate is expressed in the tensor-form with three non-zero components and naturally satisfies incompressibility. An incremental analysis procedure is employed to model the creep behavior of particulate composites. The aluminum alloy is treated as a composite material, with precipitated particles as the reinforcements. We then adopt the proposed micromechanics approach to study the creep behavior of the powder metallurgy aluminum alloy with continuous precipitation, accounting for both the creep of matrix and the creep induced by interfacial diffusion along the precipitate/matrix interface. The predicted creep curves agree well with experimental results and the explanation for the creep phenomenon has never been proposed before. We have also derived the minimum or steady-state creep rate of the alloy by the micromechanics approach, which turns out to be similar to the expression of improved power-law creep with a threshold stress.

In this paper, the crushing responses of tubes with different shapes of windows as well as the simple tube are investigated under axial and oblique loading conditions. Numerical model was constructed with FE code LS-DYNA and was validated by experiment. The model was then employed for the dynamic crush simulation of each tube at different load angles. The initial peak, crush force efficiency, energy absorption and specific energy absorption of windowed and simple tubes were compared and their overall crushing performances were evaluated by TOPSIS method. The results have proven the effectiveness of introducing windows to improve the tube's crushing performance and have showed that square and rectangle are the best window shapes.

Extracting buildings from high resolution remotely sensed images is very practical, which can be applied to urban modeling and so on. The development of computer vision has become better, and the accuracy of recognition of convolutional neural networks has exceeded the accuracy of recognition of human eyes. In this paper, we used a deep convolutional neural network in remote sensing to achieve building extraction. The method in this paper is not based on semantic segmentation, but instance segmentation, which considered each building as an independent individual to achieve building extraction. The results showed that the proposed method is able to extract buildings with high accuracy.

Building extraction is a hotspot of research. Buildings in remote sensing images are numerous, and buildings have different distribution patterns in different regions, which means it is difficult to extract buildings by one traditional method for all areas. Deep learning plays more and more important part of computer version and image processing, which has made some progress in target detection and identification, especially in medical graphic recognition. In this paper, we compared three common datasets, and selected the most suitable one. Mask R- CNN is applied to this dataset. We provided a better method and this method can be used in different areas when dataset is rich enough for training. The method in this paper just need high resolution aerial images to extract buildings automatically without any other steps, because identification and extraction are achieved in one network. The research showed: the dataset we selected is suitable; Mask R-CNN can be used in high resolution remotely images; Mask R-CNN is good at building extraction, and greatly reduce the loss of classification and leakage. Therefore, this paper provided a suitable method for automatic building extraction.

Background: Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy.Methods: RESTART was a prospective, randomised, open-label, blinded-endpoint, parallel-group trial at 122 hospitals in the UK that assessed whether starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. For this prespecified subgroup analysis, consultant neuroradiologists masked to treatment allocation reviewed brain CT or MRI scans performed before randomisation to confirm participant eligibility and rate features of the intracerebral haemorrhage and surrounding brain. We followed participants for primary (recurrent symptomatic intracerebral haemorrhage) and secondary (ischaemic stroke) outcomes for up to 5 years (reported elsewhere). For this report, we analysed eligible participants with intracerebral haemorrhage according to their treatment allocation in primary subgroup analyses of cerebral microbleeds on MRI and in exploratory subgroup analyses of other features on CT or MRI. The trial is registered with the ISRCTN registry, number ISRCTN71907627.Findings: Between May 22, 2013, and May 31, 2018, 537 participants were enrolled, of whom 525 (98%) had intracerebral haemorrhage: 507 (97%) were diagnosed on CT (252 assigned to start antiplatelet therapy and 255 assigned to avoid antiplatelet therapy, of whom one withdrew and was not analysed) and 254 (48%) underwent the required brain MRI protocol (122 in the start antiplatelet therapy group and 132 in the avoid antiplatelet therapy group). There were no clinically or statistically significant hazards of antiplatelet therapy on recurrent intracerebral haemorrhage in primary subgroup analyses of cerebral microbleed presence (2 or more) versus absence (0 or 1) (adjusted hazard ratio [HR] 0·30 [95% CI 0·08–1·13] vs 0·77 [0·13–4·61]; pinteraction=0·41), cerebral microbleed number 0–1 versus 2–4 versus 5 or more (HR 0·77 [0·13–4·62] vs 0·32 [0·03–3·66] vs 0·33 [0·07–1·60]; pinteraction=0·75), or cerebral microbleed strictly lobar versus other location (HR 0·52 [0·004–6·79] vs 0·37 [0·09–1·28]; pinteraction=0·85). There was no evidence of heterogeneity in the effects of antiplatelet therapy in any exploratory subgroup analyses (all pinteraction>0·05).Interpretation: Our findings exclude all but a very modest harmful effect of antiplatelet therapy on recurrent intracerebral haemorrhage in the presence of cerebral microbleeds. Further randomised trials are needed to replicate these findings and investigate them with greater precision.Funding: British Heart Foundation.

Background: Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects.Methods: FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762.Findings: Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months.Interpretation: Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function.Funding: UK Stroke Association and NIHR Health Technology Assessment Programme.

Architected materials consisting of periodic unit cells are desirable for many engineering applications. Characterizing the elastic isotropy is of great significance for the mechanical design of architected materials. However, prevailing experimental and numerical approaches are normally too costly and time-consuming to screen out isotropic architected materials in the large design space. Here, a deep learning-based approach is developed as a highly efficient and portable tool to identify the elastic isotropy of architected materials directly from images of their unit cells with arbitrary component distributions. The measure of elastic isotropy for heterogeneous architected materials is derived firstly in this paper to construct a database with associated images of unit cells. Then a convolutional neural network is fully trained with the database, performing well on the isotropy identification with about 90% accuracy and milliseconds processing time per sample. Meanwhile, it exhibits enough robustness to maintain its performance under the fluctuating material properties in test sets. Moreover, the transfer learning of the convolutional neural network is successfully implemented among architected materials with different numbers of material components, which further promotes the efficiency of the deep learning-based approach without scarifying its identification performance. This study gives new inspirations on the rapid mechanical characterization of architectured materials, which holds promising applications in the big-data driven topological design and nondestructive testing of architected materials.

In this work, thermoelastic damping in microbeam resonators is evaluated using the generalized thermoelasticity theory based on the dual-phase-lagging thermal conduction model with relaxation between temperature increment and thermal expansion. An explicit formula of thermoelastic damping has been derived. Influences of various affecting factors on thermoelastic damping, such as the beam height, aspect ratio, and relaxation time between temperature increment and thermal expansion, are examined. Numerical results show that the thermoelastic damping, obtained by the generalized thermoelasticity theory in the present study, exhibits distinctive features at nanoscale. This work reveals that non-Fourier thermal conduction and relaxation between temperature increment and thermal expansion may play a nonnegligible role at nanometer scale.

Selective laser melting (SLM) has received increasing attention in recent years as an innovative manufacturing technique. The present SLM process only uses a single laser beam to melt and consolidate the powder, which may result in excessive evaporation. In this paper, a double beam scanning strategy is investigated in which the first laser beam preheats the powder just below the sintering point while the second laser beam completely melts the powder. An analytical solution on the temperature distribution heated by a moving laser beam in the powder-bulk domain is derived and is used to determine the critical radius of the first laser beam. The single and double beam scanning strategies are compared numerically and it is found that double beam scanning can effectively reduce material evaporation and increase the amount of powder melted in the SLM process.

This paper studies thermoelastic damping in the longitudinal vibration mode. Expression of thermoelastic damping is obtained by using the thermal-energy method and is then validated by comparing with the exact solutions deduced from the coupled thermoelasticity equations. It is demonstrated that Landau–Lifshitz's model overestimates thermoelastic energy loss by employing the adiabatic assumption. Results of the present study indicate that the peak value of thermoelastic damping for isothermal boundary condition is lower than that for adiabatic boundary condition in the longitudinal vibration mode. Furthermore, a comparison was made between longitudinal vibration mode and flexural vibration mode to distinguish their different characteristics. It manifests that thermoelastic damping of rods or beams reaches peak values at the length scale of 10 −8 m for longitudinal vibration in contrast to the order of 10 −5 m or above for flexural vibration in the numerical examples of the present study.

This study investigates the thermoelastic dissipation of micro-plate resonators by using the generalized thermoelasticity theory of dual-phase-lagging model. Explicit formulae of thermoelastic damping and frequency shift are derived. Influences of the plate thickness and vibration frequency on the thermoelastic damping are examined. Phenomena distinct from those of classical theory are observed in the numerical results of thermoelastic damping in micro-plate resonators. These results may bring new insights into the study of thermoelastic damping at submicrometer or nanometer scale.

In this study, we report a new energy dissipation mechanism of nanomechanical resonators due to the Casimir effect originating from quantum fluctuation of the vacuum electromagnetic field at the nanoscale. An analytical study on the evaluation of the Casimir effect-induced energy loss in nanobeam resonators undergoing in-plane flexural vibration is presented. Two-dimensional elastic wave theory is employed to determine the energy transmission from the vibrating resonator to the substrate. Fourier transform and Green's function technique are adopted to solve the problem of wave motions on the surface of the substrate excited by the Casimir force. Analytical expressions of the Casimir effect-induced energy loss in terms of the quality factor, taking into account both pressure wave propagation in the noncontact substrate and shear wave propagation in the supporting substrate, as well as linear and nonlinear terms of time-varying Casimir force, have been derived. Effects of beam geometry, initial separation gap, and structural boundary conditions on energy loss are examined. Results of the present study demonstrate that the Casimir effect-induced energy loss plays an important role in the dissipation of the nanobeam resonators, in which the influence of shear wave propagation is remarkable. Also, as reflected by our results, the influence of nonlinear terms of time-varying Casimir force on the energy dissipation cannot be neglected for large-amplitude vibration, which is obviously a feature of nonlinear damping. Furthermore, we propose a possible way to experimentally measure the Casimir force by using the energy dissipation mechanism due to the Casimir force.

Thermo-elastic dissipation of microbeam resonators is studied by the generalized thermo-elasticity theory of Lord and Shulman's model. Explicit formulae of thermo-elastic damping and frequency shift have been derived. Influences of the beam height and aspect ratio are examined. The thermal relaxation time is determined by Chester's formula, where the phonon velocity is replaced by the flexural wave velocity in the microbeam. Numerical results show that the discrepancy between results of the present non-Fourier theory and classical ones increase with decrease of aspect ratio of the beam resonator. For fixed aspect ratios thermo-elastic damping tends to increase from lower vibration modes to higher modes.

The Bleustein–Gulyaev (B–G) wave in piezoelectric materials of orthorhombic mm2 crystal class is reported to be a promising candidate for application to liquid sensing. In this work we present a rigorous quantitative investigation of the propagation of B–G wave in mm2 crystals in contact with a viscous liquid. An inversion algorithm is formulated to determine the liquid viscosity from the wave speed and attenuation data. Numerical results and discussions are given for potassium niobate (KNbO3). The inversion results demonstrate that the liquid viscosity can be successfully determined from wave propagation characteristics.