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Biomimetics is a well-known approach for technical innovation. However, most of its influence remains in the academic field. One option for increasing its application in the practice of technical design is to enhance the use of the biomimetic process with a step-by-step standard, building a bridge to common engineering procedures. This article presents the endeavor of an interdisciplinary expert panel from the fields of biology, engineering science, and industry to develop a standard that links biomimetics to the classical processes of product development and engineering design. This new standard, VDI 6220 Part 2, proposes a process description that is compatible and connectable to classical approaches in engineering design. The standard encompasses both the solution-based and the problem-driven process of biomimetics. It is intended to be used in any product development process for more biomimetic applications in the future.
Biomimetics is the interdisciplinary co-operation of various scientific disciplines and fields of innovation, and it aims to solve practical problems using biological models. Biomimetic research and its fields of application are manifold, and the community is made up of a wide range of disciplines, from biologists and engineers to designers. Guidelines and standards can build a common ground for understanding of the field, communication across disciplines, present and future projects and implementation of biomimetic knowledge. Since 2015, three international standards have been published and defined terms and definitions, as well as specific applications. The scientific literature and patents in several databases were searched for citations of the published standards. Standards or technical guidelines on biomimetics are represented both in the scientific literature and in patents. However, taking into account the increasing number of publications in biomimetics, the number of publications (52) citing the international standards is low. This shows that the perception of technical rules is still underrepresented in the academic field. Greater awareness and acceptance of the importance of standards for quality assurance even in the academic environment is discussed, and active participation in the corresponding International Organization for Standardization committee on biomimetics is asked for.
As a rule, an experiment carried out at school or in undergraduate study
courses is rather simple and not very informative. However, when the experiments
are to be performed using modern methods, they are often abstract and
difficult to understand. Here, we describe a quick and simple experiment,
namely the enzymatic characterization of ptyalin (human salivary amylase)
using a starch degradation assay. With the experimental setup presented here,
enzyme parameters, such as pH optimum, temperature optimum, chloride
dependence, and sensitivity to certain chemicals can be easily determined. This
experiment can serve as a good model for enzyme characterization in general,
as modern methods usually follow the same principle: determination of the
activity of the enzyme under different conditions. As different alleles occur in
humans, a random selection of test subjects will be quite different with regard
to ptyalin activities. Therefore, when the students measure their own ptyalin
activity, significant differences will emerge, and this will give them an idea of
the genetic diversity in human populations. The evaluation has shown that the
pupils have gained a solid understanding of the topic through this experiment.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.