Nonlinear Free and Forced Vibrations of a Hyperelastic Micro/Nanobeam Considering Strain Stiffening Effect

In recent years, the static and dynamic response of micro/nanobeams made of hyperelasticity materials received great attention. In the majority of studies in this area, the strain-stiffing effect that plays a major role in many hyperelastic materials has not been investigated deeply. Moreover, the influence of the size effect and large rotation for such a beam that is important for the large deformation was not addressed. This paper attempts to explore the free and forced vibrations of a micro/nanobeam made of a hyperelastic material incorporating strain-stiffening, size effect, and moderate rotation. The beam is modelled based on the Euler–Bernoulli beam theory, and strains are obtained via an extended von Kármán theory. Boundary conditions and governing equations are derived by way of Hamilton’s principle. The multiple scales method is applied to obtain the frequency response equation, and Hamilton’s technique is utilized to obtain the free undamped nonlinear frequency. The influence of important system parameters such as the stiffening parameter, damping coefficient, length of the beam, length-scale parameter, and forcing amplitude on the frequency response, force response, and nonlinear frequency is analyzed. Results show that the hyperelastic microbeam shows a nonlinear hardening behavior, which this type of nonlinearity gets stronger by increasing the strain-stiffening effect. Conversely, as the strain-stiffening effect is decreased, the nonlinear frequency is decreased accordingly. The evidence from this study suggests that incorporating strain-stiffening in hyperelastic beams could improve their vibrational performance. The model proposed in this paper is mathematically simple and can be utilized for other kinds of micro/nanobeams with different boundary conditions.

Enhancing Vibration Isolation Performance by Exploiting Novel Spring-Bar Mechanism

This study investigates the use of a spring-bar mechanism (SBM) in a vibration suppression system to improve its performance. The SBM, comprising bars and springs, is configured with a conventional linear spring-damper isolator unit. The dynamic response, force transmissibility, and vibration energy flow behaviour are studied to evaluate the vibration suppression performance of the integrated system. It is found that the SBM can introduce hardening, softening stiffness, or double-well potential characteristics to the system. By tuning the SBM parameters, constant negative stiffness is achieved so that the natural frequency of the overall system is reduced for enhanced low-frequency vibration isolation. It is also found that the proposed design yields a wider effective isolation range compared to the conventional spring-damper isolator and a previously proposed isolator with a negative stiffness mechanism. The frequency response relation of the force-excited system is derived using the averaging method and elliptical functions. It is also found that the system can exhibit chaotic motions, for which the associated time-averaged power is found to tend to an asymptotic value as the averaging time increases. It is shown that the time-averaged power flow variables can be used as uniform performance indices of nonlinear vibration isolators exhibiting periodic or chaotic motions. It is shown that the SBM can assist in reducing force transmission and input power, thereby expanding the frequency range of vibration attenuations.

The Military Treatment Facility COVID-19 Response in an Isolated Rural Environment: Challenges and Lessons Learned

ABSTRACT The coronavirus disease-2019 (COVID-19) pandemic remains an extraordinary event that continues to strain healthcare systems worldwide. Unlike the military treatment facilities (MTFs) in the USA, which have ready access to tertiary care facilities, those MTFs in foreign countries confront a host of challenges in meeting mission requirements. In this article, we discuss the MTFs’ COVID-19 response in the rural environment of Bavaria, Germany. Relevant factors including regional and clinic response, force health protection, and contingency planning, which influenced the MTFs response, are identified. These factors are further analyzed from a “lessons learned” perspective, and recommendations to shape the future response to a pandemic are provided. This current crisis portends a future where pandemics may remain an omnipresent threat.

Viscoelasticity and Noise Properties Reveal the Formation of Biomemory in Cells

Living cells are neither perfectly elastic nor liquid and return a viscoelastic response to external stimuli. Nanoindentation provides force distance curves allowing the investigation of cell mechanical properties, and yet, these curves can differ from point to point on cell surface revealing its inhomogeneous character. In the present work, we propose a mathematical method to estimate both viscoelastic and noise properties of cells, as these are depicted on the values of the scaling exponents of relaxation function and power spectral density respectively. The method uses as input the time derivative of the response force in a nanoindentation experiment. Generalized moments method and/or rescaled range analysis are used to study the resulting time series depending on their non-stationary or stationary nature. We conducted experiments in living Ulocladium Chartarum spores. We found that spores, in the approaching phase present a viscoelastic behavior with the corresponding scaling exponent in the range 0.25-0.52, and in the retracting phase present a liquid-like behavior with exponents in the range 0.67-0.85. This substantial difference of the scaling exponents in the two phases suggests the formation of biomemory as response of the spores to the indenting AFM mechanical stimulus. The retracting phase may be described as a process driven by bluish noises, while the approaching one is driven by persistent noise.

The evolution of Cuban medical diplomacy

The author examines the evolution of Cuban medical diplomacy under the governments of Raul Castro and Miguel Diaz-Canel. The author shows that the essence of the Cuban national health system, which developed after the 1959 Revolution, is its accessibility. At the time of collapse of the socialist bloc, the Cuban government managed to maintain and surpass the achieved level of development of medicine. The presence of a large number of medical specialists allows the socialist government of Cuba to organize cooperation with dozens of states around the world. Under the leadership of Castro, the export of medical goods and services has become the main source of foreign exchange earnings and a driver of economic growth, and medical diplomacy has become an important tool of soft power, which is used to form an attractive image of the state among the world community. In doing so, the government combines pragmatism, increasing the cost-effectiveness of the programs, and altruism, providing gratuitous aid to the countries most in need. The main difficulty in developing this direction in Cuba’s foreign policy is associated with the North American embargo. In 2018, the US government launched a large-scale campaign to discredit Cuban medical internationalism. This policy aims to further restrict already limited access to essential resources. The country was also negatively affected by the ‘right turn’ in the region: the neoliberal governments of several countries refused to continue medical cooperation with Cuba. At the same time, the trends of recent years indicate an imminent repetition of the shift to the left, which in the future can significantly strengthen the Cuban positions in the region. In addition, the coronavirus pandemic showed that the world community needs a rapid medical response force with Cuban missions serving as a basis thereof.

Decoding continuous variables from EEG data using linear support vector regression (SVR) analysis with the Decision Decoding Toolbox (DDTBOX)

Multivariate classification analysis for non-invasively acquired neuroimaging data is a powerful tool in cognitive neuroscience research. However, an important constraint of such pattern classifiers is that they are restricted to predicting categorical variables (i.e. assigning trials to classes). Here, we present an alternative approach, Support Vector Regression (SVR), which uses single-trial neuroimaging (e.g., EEG or MEG) data to predict a continuous variable of interest such as response time, response force, or any kind of subjective rating (e.g., emotional state, confidence, etc.). We describe how SVR can be used, how it is implemented in the Decision Decoding Toolbox (DDTBOX), and how it has been used in previous research. We then report results from two simulation studies, designed to closely resemble real EEG data, in which we predicted a continuous variable of interest across a range of analysis parameters. In Simulation Study 1, we observed that SVR was effective for analysis windows ranging from 2 ms - 100 ms, and that it was relatively unaffected by temporal averaging. In Simulation Study 2, we showed that prediction was still successful when only a small number of channels encoded information about the output variable, and that it was robust to temporal jitter regarding when that information was present in the EEG. Finally, we reanalysed a previously published dataset of similar size and observed highly comparable results in real EEG data. We conclude that linear SVR is a powerful tool for the investigation of single-trial EEG data in relation to continuous and more nuanced variables, which are not well-captured using classification approaches requiring distinct classes.

An Accelerating Sweep Frequency Excitation Method for the Rotordynamic Coefficients Identification of Annular Gas Seals Based On Computational Fluid Dynamics

This paper proposes a rotordynamic identification method using the accelerating sweep frequency excitation method (ASFE). The CFD transient solution combined with the moving grid method is utilized to obtain the transient flow field of the seal excited by the whirling rotor with an accelerating frequency. Rotordynamic coefficients at swept frequencies are obtained by analyzing the transient response force acting on the rotor. Rotordynamic coefficients of three published experimental seals including a labyrinth seal (LABY), a fully partitioned pocket damper seal (FPDS) and a honeycomb seal (HC) are identified to validate the proposed method. The results show that the predicted rotordynamic coefficients are all well agreement with the experimental data. Compared with the existing numerical models based on transient solutions, the CPU consumption of the proposed method is substantially reduced by 98% when achieving the same frequency resolution. In addition, the impact of the exciting acceleration on the identification accuracy is also illustrated.

Viscoelastic properties of wheat gluten in a molecular dynamics study

Wheat (Triticum spp.) gluten consists mainly of intrinsincally disordered storage proteins (glutenins and gliadins) that can form megadalton-sized networks. These networks are responsible for the unique viscoelastic properties of wheat dough and affect the quality of bread. These properties have not yet been studied by molecular level simulations. Here, we use a newly developed α-C-based coarse-grained model to study ∼ 4000-residue systems. The corresponding time-dependent properties are studied through shear and axial deformations. We measure the response force to the deformation, the number of entanglements and cavities, the mobility of residues, the number of the inter-chain bonds, etc. Glutenins are shown to influence the mechanics of gluten much more than gliadins. Our simulations are consistent with the existing ideas about gluten elasticity and emphasize the role of entanglements and hydrogen bonding. We also demonstrate that the storage proteins in maize and rice lead to weaker elasticity which points to the unique properties of wheat gluten.