12 research outputs found
Inverse design of artificial skins
Mimicking the perceptual functions of human cutaneous mechanoreceptors,
artificial skins or flexible pressure sensors can transduce tactile stimuli to
quantitative electrical signals. Conventional methods to design such devices
follow a forward structure-to-property routine based on trial-and-error
experiments/simulations, which take months or longer to determine one solution
valid for one specific material. Target-oriented inverse design that shows far
higher output efficiency has proven effective in other fields, but is still
absent for artificial skins because of the difficulties in acquiring big data.
Here, we report a property-to-structure inverse design of artificial skins
based on small dataset machine learning, exhibiting a comprehensive efficiency
at least four orders of magnitude higher than the conventional routine. The
inverse routine can predict hundreds of solutions that overcome the intrinsic
signal saturation problem for linear response in hours, and the solutions are
valid to a variety of materials. Our results demonstrate that the inverse
design allowed by small dataset is an efficient and powerful tool to target
multifarious applications of artificial skins, which can potentially advance
the fields of intelligent robots, advanced healthcare, and human-machine
interfaces
A Multi-Factorial Observational Study on Sequential Fecal Microbiota Transplant in Patients with Medically Refractory Clostridioides difficile Infection
Fecal microbiota transplantation (FMT) is highly effective in recurrent Clostridioides difficile infection (CDI); increasing evidence supports FMT in severe or fulminant Clostridioides difficile infection (SFCDI). However, the multifactorial mechanisms that underpin the efficacy of FMT are not fully understood. Systems biology approaches using high-throughput technologies may help with mechanistic dissection of host-microbial interactions. Here, we have undertaken a deep phenomics study on four adults receiving sequential FMT for SFCDI, in which we performed a longitudinal, integrative analysis of multiple host factors and intestinal microbiome changes. Stool samples were profiled for changes in gut microbiota and metabolites and blood samples for alterations in targeted epigenomic, metabonomic, glycomic, immune proteomic, immunophenotyping, immune functional assays, and T-cell receptor (TCR) repertoires, respectively. We characterised temporal trajectories in gut microbial and host immunometabolic data sets in three responders and one non-responder to sequential FMT. A total of 562 features were used for analysis, of which 78 features were identified, which differed between the responders and the non-responder. The observed dynamic phenotypic changes may potentially suggest immunosenescent signals in the non-responder and may help to underpin the mechanisms accompanying successful FMT, although our study is limited by a small sample size and significant heterogeneity in patient baseline characteristics. Our multi-omics integrative longitudinal analytical approach extends the knowledge regarding mechanisms of efficacy of FMT and highlights preliminary novel signatures, which should be validated in larger studies
Effect of ant colonization on spatiotemporal dynamics of readily oxidizable soil carbon across different restoration stages of tropical forests
Tomographic SAR imaging with large elevation aperture: a P-band small UAV demonstration
Elevation resolution is an important indicator in tomographic SAR imaging as it represents the ability to discriminate closed targets in elevation. In general, the elevation resolution is proportional to the length of the elevation aperture. However, as the elevation aperture increases, the geometric consistency of the image will undesirably deteriorate and hence fails the image coregistration approach required by the traditional super-resolution tomographic imaging. In this paper, a new super-resolution tomographic imaging method is proposed to overcome the inconsistency problem caused by the large elevation aperture. The core strategy is to get rid of two-dimensional image coregistration by applying a three-dimensional (3D) back projection like imaging manner: the 3D space is firstly divided into a 3D imaging grid, each of which is individually imaged via compressive sensing for super-resolution. The effectiveness of the proposed approach is evaluated by both computer simulations and real P-band UAV SAR data.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System
The contributions of underground-nesting ants to CO2 emission from tropical forest soils vary with species
Feeding-strategy effect of Pheidole ants on microbial carbon and physicochemical properties in tropical forest soils
LC–MS Profiling of N‑Glycans Derived from Human Serum Samples for Biomarker Discovery in Hepatocellular Carcinoma
Defining
clinically relevant biomarkers for early stage hepatocellular
carcinoma (HCC) in a high-risk population of cirrhotic patients has
potentially far-reaching implications for disease management and patient
health. Changes in glycan levels have been associated with the onset
of numerous diseases including cancer. In the present study, we used
liquid chromatography coupled with electrospray ionization mass spectrometry
(LC–ESI-MS) to analyze N-glycans in sera from 183 participants
recruited in Egypt and the U.S. and identified candidate biomarkers
that distinguish HCC cases from cirrhotic controls. N-Glycans were
released from serum proteins and permethylated prior to the LC–ESI-MS
analysis. Through two complementary LC–ESI-MS quantitation
approaches, global profiling and targeted quantitation, we identified
11 N-glycans with statistically significant differences between HCC
cases and cirrhotic controls. These glycans can further be categorized
into four structurally related clusters, matching closely with the
implications of important glycosyltransferases in cancer progression
and metastasis. The results of this study illustrate the power of
the integrative approach combining complementary LC–ESI-MS
based quantitation approaches to investigate changes in N-glycan levels
between HCC cases and patients with liver cirrhosis