759 research outputs found
Network Structure and Dynamics of the Mental Workspace
The conscious manipulation of mental representations is central to many creative and uniquely human abilities. How does the human brain mediate such flexible mental operations? Here, multivariate pattern analysis of functional MRI data reveals a widespread neural network that performs specific mental manipulations on the contents of visual imagery. Evolving patterns of neural activity within this mental workspace track the sequence of informational transformations carried out by these manipulations. The network switches between distinct connectivity profiles as representations are maintained or manipulated
MODELLING TECHNICAL SYSTEMS IN THE EARLY PHASE: PROPOSING A FORMAL DEFINITION FOR THE SYSTEM CONCEPT
The task of developing “concepts” is common in all fields of engineering, especially in the early phases of product development. However, an in-depth literature analysis showed that authors - often depending on different contexts in design research, education, and industry - define the term “concept” in differing ways. The aspect of reference-based development is rarely addressed in existing definitions. This indicates that there is a need for an updated and concise concept definition. In this paper, the authors propose a new definition of the term “system concept” within the context of SGE - System Generation Engineering that incorporates the findings from the literature analysis. The definition was reflected on in two case-studies. The first one contained the system concept for automotive display and operating systems, the second one the system concept for a kinesthetic-haptic VR interface. The proposed definition contains the relevant characteristics identified from the literature review and supports both current activity-based process models and reference-based development, as practical application has shown
Tool Wear Segmentation in Blanking Processes with Fully Convolutional Networks based Digital Image Processing
The extend of tool wear significantly affects blanking processes and has a
decisive impact on product quality and productivity. For this reason, numerous
scientists have addressed their research to wear monitoring systems in order to
identify or even predict critical wear at an early stage. Existing approaches
are mainly based on indirect monitoring using time series, which are used to
detect critical wear states via thresholds or machine learning models.
Nevertheless, differentiation between types of wear phenomena affecting the
tool during blanking as well as quantification of worn surfaces is still
limited in practice. While time series data provides partial insights into wear
occurrence and evolution, direct monitoring techniques utilizing image data
offer a more comprehensive perspective and increased robustness when dealing
with varying process parameters. However, acquiring and processing this data in
real-time is challenging. In particular, high dynamics combined with increasing
strokes rates as well as the high dimensionality of image data have so far
prevented the development of direct image-based monitoring systems. For this
reason, this paper demonstrates how high-resolution images of tools at 600 spm
can be captured and subsequently processed using semantic segmentation deep
learning algorithms, more precisely Fully Convolutional Networks (FCN). 125,000
images of the tool are taken from successive strokes, and microscope images are
captured to investigate the worn surfaces. Based on findings from the
microscope images, selected images are labeled pixel by pixel according to
their wear condition and used to train a FCN (U-Net)
Serum periostin levels in early in pregnancy are significantly altered in women with miscarriage
Background: Miscarriage is a common complication in pregnancy and there is still a lack of biomarkers usable in asymptomatic patients before the event occurs. Periostin (PER), whose levels rise particularly during injury or inflammation, has been shown to play an important local role in implantation and early embryonic development. As PER has been described as a biomarker in various medical conditions we intended to evaluate if changes in PER serum levels may help to identify women at risk for spontaneous abortion in the first trimester.
Methods: Women between 18 and 42 years without confounding comorbidities who conceived by IVF/ICSI and ovarian hyperstimulation were analysed in the study after informed consent. Maternal serum samples from 41 patients were assessed at the time of pregnancy testing (PT) and the following first ultrasound checkup (US). Patients were subsequently divided in two groups: (1) patients with subsequent miscarriage in the first trimester (n = 18) and (2) patients with ongoing pregnancy (n = 23), allowing for statistical analysis and investigating the change of PER levels per individual. PER levels were measured using enzyme-linked immunosorbent assay. Statistical analysis was performed using the Fisher exact and Student’s t test. p ≤ 0.05 was considered to be significant.
Results: There was no significant difference concerning possible confounders between the two groups. We did not find any significant difference in PER levels at the time point of PT or US. By investigating the interindividual changes of PER between the two time points however, we observed that patients with a following miscarriage showed increasing levels of PER at the time point of PT compared to US in contrast to patients with an ongoing pregnancy who demonstrated a decrease in PER levels. These alterations were significant in the absolute as well as in the relative comparison.
Conclusion: The relative expression of PER between PT and US is significantly altered in asymptomatic women with subsequent miscarriage compared to women with ongoing pregnancy. Therefore systemic PER levels might represent a potential promising biomarker for the assessment of pregnancy outcome.
Trial registration Not applicable
Recommended from our members
The natverse, a versatile toolbox for combining and analysing neuroanatomical data.
To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community
Recommended from our members
The natverse, a versatile toolbox for combining and analysing neuroanatomical data.
To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community
Gas and Star Formation in the Circinus Galaxy
We present a detailed study of the Circinus Galaxy, investigating its star
formation, dust and gas properties both in the inner and outer disk. To achieve
this, we obtained high-resolution Spitzer mid-infrared images with the IRAC
(3.6, 5.8, 4.5, 8.0 micron) and MIPS (24 and 70 micron) instruments and
sensitive HI data from the Australia Telescope Compact Array (ATCA) and the
64-m Parkes telescope. These were supplemented by CO maps from the Swedish-ESO
Submillimetre Telescope (SEST). Because Circinus is hidden behind the Galactic
Plane, we demonstrate the careful removal of foreground stars as well as large-
and small-scale Galactic emission from the Spitzer images. We derive a visual
extinction of Av = 2.1 mag from the Spectral Energy Distribution of the
Circinus Galaxy and total stellar and gas masses of 9.5 x 10^{10} Msun and 9 x
10^9 Msun, respectively. Using various wavelength calibrations, we find
obscured global star formation rates between 3 and 8 Msun yr^{-1}. Star forming
regions in the inner spiral arms of Circinus, which are rich in HI, are
beautifully unveiled in the Spitzer 8 micron image. The latter is dominated by
polycyclic aromatic hydrocarbon (PAH) emission from heated interstellar dust.
We find a good correlation between the 8 micron emission in the arms and
regions of dense HI gas. The (PAH 8 micron) / 24 micron surface brightness
ratio shows significant variations across the disk of Circinus.Comment: 18 pages, 14 figures. All figures have been compressed. Contact
authors for original figures. Accepted by MNRA
Balanced hydroxyethylstarch (HES 130/0.4) impairs kidney function in-vivo without inflammation
Volume therapy is a standard procedure in daily perioperative care, and there is an ongoing discussion about the benefits of colloid resuscitation with hydroxyethylstarch (HES). In sepsis HES should be avoided due to a higher risk for acute kidney injury (AKI). Results of the usage of HES in patients without sepsis are controversial. Therefore we conducted an animal study to evaluate the impact of 6% HES 130/0.4 on kidney integrity with sepsis or under healthy conditions Sepsis was induced by standardized Colon Ascendens Stent Peritonitis (sCASP). sCASP-group as well as control group (C) remained untreated for 24 h. After 18 h sCASP+HES group (sCASP+VOL) and control+HES (C+VOL) received 50 ml/KG balanced 6% HES (VOL) 130/0.4 over 6h. After 24h kidney function was measured via Inulin- and PAH-Clearance in re-anesthetized rats, and serum urea, creatinine (crea), cystatin C and Neutrophil gelatinase-associated lipocalin (NGAL) as well as histopathology were analysed. In vitro human proximal tubule cells (PTC) were cultured +/- lipopolysaccharid (LPS) and with 0.1–4.0% VOL. Cell viability was measured with XTT-, cell toxicity with LDH-test. sCASP induced severe septic AKI demonstrated divergent results regarding renal function by clearance or creatinine measure focusing on VOL. Soleley HES (C+VOL) deteriorated renal function without sCASP. Histopathology revealed significantly derangements in all HES groups compared to control. In vitro LPS did not worsen the HES induced reduction of cell viability in PTC cells. For the first time, we demonstrated, that application of 50 ml/KG 6% HES 130/0.4 over 6 hours induced AKI without inflammation in vivo. Severity of sCASP induced septic AKI might be no longer susceptible to the way of volume expansio
Recoiled star clusters in the Milky Way halo: N-body simulations and a candidate search through SDSS
During the formation of the Milky Way, > 100 central black holes (BHs) may
have been ejected from their small host galaxies as a result of asymmetric
gravitational wave emission. We previously showed that many of these BHs are
surrounded by a compact cluster of stars that remained bound to the BH during
the ejection process. In this paper, we perform long term N-body simulations of
these star clusters to determine the distribution of stars in these clusters
today. These numerical simulations, reconciled with our Fokker-Planck
simulations, show that stellar density profile follows a power-law with slope ~
-2.15, and show that large angle scattering and tidal disruptions remove 20 -
90% of the stars by ~10^10 yr. We then analyze the photometric and
spectroscopic properties of recoiled clusters accounting for the small number
of stars in the clusters. We use our results to perform a systematic search for
candidates in the Sloan Digital Sky Survey. We find no spectroscopic
candidates, in agreement with our expectations from the completeness of the
survey. Using generic photometric models of present day clusters we identify
~100 recoiling cluster candidates. Follow-up spectroscopy would be able to
determine the nature of these candidates.Comment: Final submission to MNRAS. 15 Pages, 10 figures. Includes new
material on resonant relaxation and incorporates recommendations of the
refere
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