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BACKGROUND: Muscle stretch reflexes are widely used to examine neural muscle function. The knowledge of reflex response in muscles crossing the shoulder is limited. OBJECTIVE: To quantify reflex modulation according to various subject postures and different procedures of muscle pre-activation steering. METHODS: Thirteen healthy male participants performed two sets of external shoulder rotation stretches in various positions and with different procedures of muscle pre-activation steering on an isokinetic dynamometer over a range of two different pre-activation levels. All stretches were applied with a dynamometer acceleration of 104∘/s2 and a velocity of 150∘/s. Electromyographical response was measured via sEMG. RESULTS: Consistent reflexive response was observed in all tested muscles in all experimental conditions. The reflex elicitation rate revealed a significant muscle main effect (F (5,288) = 2.358, ρ= 0.040; η2= 0.039; f= 0.637) and a significant test condition main effect (F (1,288) = 5.884, ρ= 0.016; η2= 0.020; f= 0.143). Reflex latency revealed a significant muscle pre-activation level main effect (F (1,274) = 5.008, ρ= 0.026; η2= 0.018; f= 0.469). CONCLUSION: Muscular reflexive response was more consistent in the primary internal rotators of the shoulder. Supine posture in combination with visual feedback of muscle pre-activation level enhanced the reflex elicitation rate.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.
The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.
The treatment of septic wounds with curative dressings based on biocomposites containing sage and marigold phytoextracts was effective in in vitro and in vivo experiments. These dressings caused the purification of the wound surface from purulent-necrotic masses three days earlier than in the other experimental groups. The consequence of an increase in incidents of severe course of the wound and the observed tendency to increase the number of adverse effects is the development of long-term recurrent wound processes. To treat purulent wounds, the following tactics were used: The purulent wounds of animals were covered with the examined wound dressing, and then the next day samples were taken, the procedure was performed once in 2 days. To obtain the active nanostructured sorbents such as carbonized rice husks, they are functionalized with biologically active components possessing antimicrobial, anti-inflammatory, antitoxic, immunomodulating, antiallergic and other types of properties.
Coronavirus disease 2019 (COVID-19) is a novel human infectious disease provoked by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, no specific vaccines or drugs against COVID-19 are available. Therefore, early diagnosis and treatment are essential in order to slow the virus spread and to contain the disease outbreak. Hence, new diagnostic tests and devices for virus detection in clinical samples that are faster, more accurate and reliable, easier and cost-efficient than existing ones are needed. Due to the small sizes, fast response time, label-free operation without the need for expensive and time-consuming labeling steps, the possibility of real-time and multiplexed measurements, robustness and portability (point-of-care and on-site testing), biosensors based on semiconductor field-effect devices (FEDs) are one of the most attractive platforms for an electrical detection of charged biomolecules and bioparticles by their intrinsic charge. In this review, recent advances and key developments in the field of label-free detection of viruses (including plant viruses) with various types of FEDs are presented. In recent years, however, certain plant viruses have also attracted additional interest for biosensor layouts: Their repetitive protein subunits arranged at nanometric spacing can be employed for coupling functional molecules. If used as adapters on sensor chip surfaces, they allow an efficient immobilization of analyte-specific recognition and detector elements such as antibodies and enzymes at highest surface densities. The display on plant viral bionanoparticles may also lead to long-time stabilization of sensor molecules upon repeated uses and has the potential to increase sensor performance substantially, compared to conventional layouts. This has been demonstrated in different proof-of-concept biosensor devices. Therefore, richly available plant viral particles, non-pathogenic for animals or humans, might gain novel importance if applied in receptor layers of FEDs. These perspectives are explained and discussed with regard to future detection strategies for COVID-19 and related viral diseases.
We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.
Elastic transmission eigenvalues and their computation via the method of fundamental solutions
(2020)
A stabilized version of the fundamental solution method to catch ill-conditioning effects is investigated with focus on the computation of complex-valued elastic interior transmission eigenvalues in two dimensions for homogeneous and isotropic media. Its algorithm can be implemented very shortly and adopts to many similar partial differential equation-based eigenproblems as long as the underlying fundamental solution function can be easily generated. We develop a corroborative approximation analysis which also implicates new basic results for transmission eigenfunctions and present some numerical examples which together prove successful feasibility of our eigenvalue recovery approach.
We propose the so-called chance constrained programming model of stochastic programming theory to analyze limit and shakedown loads of structures under random strength with a lognormal distribution. A dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) is used with three-node linear triangular elements.