Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Power Spectral Density Evaluation of Laser Milled Surfaces.

ABSTRACT: Ablating surfaces with a pulsed laser system in milling processes often leads to surface changes depending on the milling depth. Especially if a constant surface roughness and evenness is essential to the process, structural degradation may advance until the process fails. The process investigated is the generation of precise thrust by laser ablation. Here, it is essential to predict or rather control the evolution of the surfaces roughness. Laser ablative milling with a short pulse laser system in vacuum (?1 Pa) were performed over depths of several 10 µm documenting the evolution of surface roughness and unevenness with a white light interference microscope. Power spectral density analysis of the generated surface data reveals a strong influence of the crystalline structure of the solid. Furthermore, it was possible to demonstrate that this effect could be suppressed for gold.

SUBMITTER: Lorbeer RA

PROVIDER: S-EPMC5793548 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Power Spectral Density Evaluation of Laser Milled Surfaces.

Lorbeer Raoul-Amadeus RA Pastow Jan J Sawannia Michael M Klinkenberg Peter P Förster Daniel Johannes DJ Eckel Hans-Albert HA

Materials (Basel, Switzerland) 20171229 1

Ablating surfaces with a pulsed laser system in milling processes often leads to surface changes depending on the milling depth. Especially if a constant surface roughness and evenness is essential to the process, structural degradation may advance until the process fails. The process investigated is the generation of precise thrust by laser ablation. Here, it is essential to predict or rather control the evolution of the surfaces roughness. Laser ablative milling with a short pulse laser system ...[more]

PMID: 29286313

Similar Datasets

Simulated power spectral density (PSD) of background electrocorticogram (ECoG).

Project description:The ECoG background activity of cerebral cortex in states of rest and slow wave sleep resembles broadband noise. The power spectral density (PSD) then may often conform to a power-law distribution: a straight line in coordinates of log power vs. log frequency. The exponent, x, of the distribution, 1/f(x), ranges between 2 and 4. These findings are explained with a model of the neural source of the background activity in mutual excitation among pyramidal cells. The dendritic response of a population of interactive excitatory neurons to an impulse input is a rapid exponential rise and a slow exponential decay, which can be fitted with the sum of two exponential terms. When that function is convolved as the kernel with pulses from a Poisson process and summed, the resulting "brown" or "black noise conforms to the ECoG time series and the PSD in rest and sleep. The PSD slope is dependent on the rate of rise. The variation in the observed slope is attributed to variation in the level of the background activity that is homeostatically regulated by the refractory periods of the excitatory neurons. Departures in behavior from rest and sleep to action are accompanied by local peaks in the PSD, which manifest emergent nonrandom structure in the ECoG, and which prevent reliable estimation of the 1/f(x) exponents in active states. We conclude that the resting ECoG truly is low-dimensional noise, and that the resting state is an optimal starting point for defining and measuring both artifactual and physiological structures emergent in the activated ECoG.

| S-EPMC2645494 | biostudies-other

Disentangling single-cell omics representation with a power spectral density-based feature extraction.

Project description:Emerging single-cell technologies provide high-resolution measurements of distinct cellular modalities opening new avenues for generating detailed cellular atlases of many and diverse tissues. The high dimensionality, sparsity, and inaccuracy of single cell sequencing measurements, however, can obscure discriminatory information, mask cellular subtype variations and complicate downstream analyses which can limit our understanding of cell function and tissue heterogeneity. Here, we present a novel pre-processing method (scPSD) inspired by power spectral density analysis that enhances the accuracy for cell subtype separation from large-scale single-cell omics data. We comprehensively benchmarked our method on a wide range of single-cell RNA-sequencing datasets and showed that scPSD pre-processing, while being fast and scalable, significantly reduces data complexity, enhances cell-type separation, and enables rare cell identification. Additionally, we applied scPSD to transcriptomics and chromatin accessibility cell atlases and demonstrated its capacity to discriminate over 100 cell types across the whole organism and across different modalities of single-cell omics data.

| S-EPMC9178020 | biostudies-literature

A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders.

Project description:There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson's disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.

| S-EPMC6806079 | biostudies-literature

PaSD-qc: quality control for single cell whole-genome sequencing data using power spectral density estimation.

Project description:Single cell whole-genome sequencing (scWGS) is providing novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, the whole-genome amplification process required for scWGS introduces biases into the resulting sequencing that can confound downstream analysis. Here, we present a statistical method, with an accompanying package PaSD-qc (Power Spectral Density-qc), that evaluates the properties and quality of single cell libraries. It uses a modified power spectral density to assess amplification uniformity, amplicon size distribution, autocovariance and inter-sample consistency as well as to identify chromosomes with aberrant read-density profiles due either to copy alterations or poor amplification. These metrics provide a standard way to compare the quality of single cell samples as well as yield information necessary to improve variant calling strategies. We demonstrate the usefulness of this tool in comparing the properties of scWGS protocols, identifying potential chromosomal copy number variation, determining chromosomal and subchromosomal regions of poor amplification, and selecting high-quality libraries from low-coverage data for deep sequencing. The software is available free and open-source at https://github.com/parklab/PaSDqc.

| S-EPMC5829578 | biostudies-literature

EEG power spectral density in locked-in and completely locked-in state patients: a longitudinal study.

Project description:Persons with their eye closed and without any means of communication is said to be in a completely locked-in state (CLIS) while when they could still open their eyes actively or passively and have some means of communication are said to be in locked-in state (LIS). Two patients in CLIS without any means of communication, and one patient in the transition from LIS to CLIS with means of communication, who have Amyotrophic Lateral Sclerosis were followed at a regular interval for more than 1 year. During each visit, resting-state EEG was recorded before the brain-computer interface (BCI) based communication sessions. The resting-state EEG of the patients was analyzed to elucidate the evolution of their EEG spectrum over time with the disease's progression to provide future BCI-research with the relevant information to classify changes in EEG evolution. Comparison of power spectral density (PSD) of these patients revealed a significant difference in the PSD's of patients in CLIS without any means of communication and the patient in the transition from LIS to CLIS with means of communication. The EEG of patients without any means of communication is devoid of alpha, beta, and higher frequencies than the patient in transition who still had means of communication. The results show that the change in the EEG frequency spectrum may serve as an indicator of the communication ability of such patients.

| S-EPMC8131474 | biostudies-literature

Laser-Milled Microslits Improve the Bonding Strength of Acrylic Resin to Zirconia Ceramics.

Project description:Heightened aesthetic considerations in modern dentistry have generated increased interest in metal-free "zirconia-supported dentures." The lifespan of the denture is largely determined by the strength of adhesion between zirconia and the acrylic resin. Thus, the effect on shear bond strength (SBS) was investigated by using an acrylic resin on two types of zirconia ceramics with differently sized microslits. Micromechanical reticular retention was created on the zirconia surface as the novel treatment (microslits (MS)), and air-abrasion was used as the control (CON). All samples were primed prior to acrylic resin polymerization. After the resin was cured, the SBS was tested. The obtained data were analyzed by using multivariate analysis of variance(? = 0.05). After the SBS test, the interface failure modes were observed by scanning electron microscopy. The MS exhibited significantly higher bond strength after thermal cycles (p < 0.05) than the CON. Nevertheless, statistically comparisons resulted in no significant effect of the differently sized microslits on SBS (p > 0.05). Additionally, MS (before thermal cycles: 34.8 ± 3.6 to 35.7 ± 4.0 MPa; after thermal cycles: 26.9 ± 3.1 to 32.6 ± 3.3 MPa) demonstrated greater SBS and bonding durability than that of CON (before thermal cycles: 17.3 ± 4.7 to 17.9 ± 5.8 MPa; after thermal cycles: 1.0 ± 0.3 to 1.7 ± 1.1 MPa), confirming that the micromechanical retention with laser-milled microslits was effective at enhancing the bonding strength and durability of the acrylic resin and zirconia. Polycrystalline zirconia-based ceramics are a newly accessible material for improving removable prosthodontic treatment, as the bond strength with acrylic resin can be greatly enhanced by laser milling.

| S-EPMC7240430 | biostudies-literature

Correlation between defect density in mechanically milled graphite and total oxygen content of graphene oxide produced from oxidizing the milled graphite.

Project description:It has been reported that defect density in ball-milled graphite lattice increases with the milling time. Guided by this, we hypothesized that the oxygen content of graphene oxide can be substantially enhanced by oxidizing ball-milled graphite and also, the oxygen content would monotonically increase with the milling time as the defect sites would be preferred sites for oxidation. Interestingly, we observed that this correlation was not directly proportional for all milling hours. Even though, the defect density of graphite monotonically increased with milling time, the oxygen content of graphene oxide initially increased and then decreased. This was due to milling time dependent change in the size of the graphite plates and consequent relative abundance of the different oxygen containing functional groups on graphene oxide (GO) produced from the milled graphite.

| S-EPMC6202385 | biostudies-literature

Alterations in power spectral density in motor- and pain-related networks on neuropathic pain after spinal cord injury.

Project description:BackgroundThe mechanisms by which mobility function and neuropathic pain are mutually influenced by supraspinal plasticity in motor- and pain-related brain networks following spinal cord injury (SCI) remains poorly understood.ObjectiveTo determine cortical and subcortical resting-state network alterations using power spectral density (PSD) analysis and investigate the relationships between these intrinsic alterations and mobility function and neuropathic pain following SCI.MethodsA total of 41 patients with incomplete SCI and 33 healthy controls were included. The degree of mobility and balance function and severity of neuropathic pain and depressive mood were evaluated. The resting-state functional magnetic resonance imaging data of low-frequency fluctuations were analyzed based on PSD. Differences in PSD values between patients with SCI and controls were assessed using the two-sample t-test (false discovery rate-corrected P < 0.05). The relationship between PSD values and mobility function and pain intensity was assessed using Pearson's correlation coefficient adjusted for the severity of depressive mood.ResultsCompared with healthy controls, lower PSD values in supplementary motor and medial prefrontal areas (the anterior cingulate cortex, ventral medial prefrontal cortex, and superior orbito-prefrontal cortex) were associated with greater pain severity and poorer postural balance and mobility (P < 0.05) in patients with SCI, whereas higher PSD values in the primary motor cortex, premotor cortex, thalamus, and periaqueductal gray were associated with greater pain severity and poorer postural balance and mobility (P < 0.05).ConclusionsCortical and subcortical plastic alterations in intrinsic motor- and pain-related networks were observed in patients with SCI and were simultaneously associated with neuropathic pain intensity and degree of mobility function.

| S-EPMC7453139 | biostudies-literature

Alterations of Power Spectral Density in Salience Network during Thought-action Fusion Induction Paradigm in Obsessive-compulsive Disorder.

Project description:ObjectiveRecent studies highlighted the triple-network model which illustrated the interactions among three large-scale networks including salience network (SN). The functional magnetic resonance imaging used in this study was designed to investigate the characteristics of three large-scale networks associated with the thought-action fusion (TAF) in patients with obsessive-compulsive disorder (OCD) using power spectral density (PSD) analysis.MethodsThis study included 32 OCD patients and 38 age-matched healthy controls (HC). The TAF task was modified from the experiment of Rassin. PSD from time courses in large-scale networks of each subject was measured to compare between the groups for both TAF and resting state.ResultsIn SN, OCD reported lower power in the low-frequency domain of SN compared to HC using the two-sample t test during the TAF task (t = -2.395, p = 0.019) but not in the resting state. The PSD in the low-frequency domain of the SN had a significant negative correlation with state score in the guilty inventory (r = -0.361, p = 0.042) in OCD patients.ConclusionThis study suggests that OCD patients showed reduced SN power which can be prominent in a certain situation, such as TAF. In addition, the PSD alterations in SN cause difficulty in processing ambiguous emotional cues in social situations, and the difficulty can be connected with a negative feeling (e.g., guilt).

| S-EPMC9329118 | biostudies-literature

Robust power spectral estimation for EEG data.

Project description:Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates.Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox.Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors.The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor.In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation.

| S-EPMC4903894 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data