Differences In Signal Levels Research Articles

Transcutaneous fluorescence spectroscopy: development and characterization of a compact, portable, and fiber-optic sensor.

The integrity of the intestinal barrier is gaining recognition as a significant contributor to various pathophysiological conditions, including inflammatory bowel disease, celiac disease, environmental enteric dysfunction (EED), and malnutrition. EED, for example, manifests as complex structural and functional changes in the small intestine leading to increased intestinal permeability, inflammation, and reduced absorption of nutrients. Despite the importance of gut function, current techniques to assess intestinal permeability (such as endoscopic biopsies or dual sugar assays) are either highly invasive, unreliable, and/or difficult to perform in certain patient populations (e.g., infants). We present a portable, optical sensor based on transcutaneous fluorescence spectroscopy to assess gut function (in particular, intestinal permeability) in a fast and noninvasive manner. Participants receive an oral dose of a fluorescent contrast agent, and a wearable fiber-optic probe detects the permeation of the contrast agent from the gut into the blood stream by measuring the fluorescence intensity noninvasively at the fingertip. We characterized the performance of our compact optical sensor by comparing it against an existing benchtop spectroscopic system. In addition, we report results from a human study in healthy volunteers investigating the impact of skin tone and contrast agent dose on transcutaneous fluorescence signals. The first study with eight healthy participants showed good correlation between our compact sensor and the existing benchtop spectroscopic system [correlation coefficient , ]. Further experiments in 14 healthy participants revealed an approximately linear relationship between the ingested contrast agent dose and the collected signal intensity. Finally, a parallel study on the impact of different skin tones showed no significant differences in signal levels between participants with different skin tones (). In this paper, we demonstrate the potential of our compact transcutaneous fluorescence sensor for noninvasive monitoring of intestinal health.

Detection and Recognition of Environmental Sounds by Musicians and Non-Musicians

The article reports three experiments conducted to determine whether musicians possess better ability of recognising the sources of natural sounds than non-musicians. The study was inspired by reports which indicate that musical training develops not only musical hearing, but also enhances various non-musical auditory capabilities. Recognition and detection thresholds were measured for recordings of environmental sounds presented in quiet (Experiment 1) and in the background of a noise masker (Experiment 2). The listener’s ability of sound source recognition was inferred from the recognition-detection threshold gap (RDTG) defined as the difference in signal level between the thresholds of sound recognition and sound detection. Contrary to what was expected from reports of enhanced auditory abilities of musicians, the RDTGs were not smaller for musicians than for non-musicians. In Experiment 3, detection thresholds were measured with an adaptive procedure comprising three interleaved stimulus tracks with different sounds. It was found that the threshold elevation caused by stimulus interleaving was similar for musicians and non-musicians. The lack of superiority of musicians over non-musicians in the auditory tasks explored in this study is explained in terms of a listening strategy known as casual listening mode, which is a basis for auditory orientation in the environment.

Individual Recognition Based on Gait Using Multi-Distance Signal Level Difference Sample Entropy

Individual Recognition Based on Gait Using Multi-Distance Signal Level Difference Sample Entropy

Self-Sensing Antenna for Soil Moisture: Beacon Approach.

On the way from the Internet of things (IoT) to the Internet of underground things (IoUT) the main challenge is antenna design. The enabling technologies still rely on simple design and low cost, but the systems are more complex. The LoRa-based system combined with a machine learning approach can be used for the estimation of soil moisture by using signal strength data, but for the improvement of the system performance we propose the optimization of the antenna for underground use. The soil properties are frequency-dependent and varying in time, which may cause variations in the signal wavelength and input impedance of the antenna underground. Instead of using wideband antenna design or standard helical antenna provided in LoRa module, which are typical in the IoUT research community for communication links, we propose a narrow-band antenna design for the application in soil moisture sensing. It is shown that the approach of simply matching the antenna buried in dry sand can provide a substantial signal level difference, ranging from approximately 10 dB (achieved by proof-of-concept measurements) to as much as 40 dB (calculated by a full wave simulator) in reflection coefficient when the moisture content is being increased by 20%. This can ensure more reliable radio sensing in novel sensorless technology where soil moisture information is extracted from the signal strength of a transmitting device.

Multi-Distance Dispersion Entropy for ECG Signal Classification

Automatic detection of heartbeat is critical for early cardiovascular disease prevention and diagnosis. Traditional feature methodologies based on expert knowledge cannot abstract and represent multidimensional and multi-view information. Hence traditional research on heartbeat detection pattern recognition cannot produce adequate results. The proposed method in this research used Dispersion Entropy (DisEn) on Multidistance Signal Level Difference (MSLD) for feature extraction and Support Vector Machine (SVM) method for classifying the ECG signals. DisEn generates 20 DE values as feature vectors for each MSLD signal with a distance D of 1 to 20. The datasets used in this research were obtained from the MIT-BIH Arrhythmia database of ECG signals that consist of forty-five patients was captured using 200 [adu/mV] amplification and a sampling frequency of 360 Hz. The experiments result using 5-fold cross-validation revealed that at distance D= 1-15 had the highest accuracy of 91% to classify the ECG data into Normal Sinus Rhythm (NSR), Left Bundle Branch Block (LBBB), and Atrial Fibrillation (AFIB) from the MIT-BIH Arrhythmias database.
 

Association of ABO Blood Group, Age, Body Mass Index and Symptomatic COVID-19 Infection with Signal Levels of Antibodies to COVID-19

Objective: To determine if ABO blood group, age, body mass index (BMI), or symptomatic COVID-19 infection are associated with COVID-19 antibody response in unvaccinated COVID-19 antibody positive pregnant women at time of delivery. Methods: At the time of delivery, 2,499 consecutive pregnant women were tested for ABO blood group and antibodies to both the spike protein and nucleocapsid protein of the COVID-19 virus. The DiaSorin assay was used for antibody to spike protein analysis and the Roche assay for antibody to nucleocapsid protein. Gamma regression models with a log link were used to compare antibody signals, with blood group, age, and BMI as the predictors. Results: 260 (10.4%) of 2,499 women who had not been vaccinated for COVID-19, were positive for both spike and nucleocapsid protein antibodies to COVID-19. The mean signal for COVID-19 nucleocapsid antibody was significantly lower for blood group AB (p=0.028) compared with blood group O. A relationship between blood group and presence of symptomatic COVID-19 was detected (p = 0.028), with asymptomatic individuals having blood group B at a higher rate than the symptomatic individuals do. No other significant pairwise differences between blood groups were detected. There was no significant difference in signal level of antibodies to COVID-19 spike protein between any of the blood groups. Mean signals for antibodies to spike and nucleocapsid proteins were significantly higher in older women (p=0.001 for spike protein antibody and p=0.002 for nucleocapsid antibody). Significantly higher signal levels of antibody to spike and nucleocapsid proteins were found in women with class 2/3 obesity (p=0.022 and p=0.003, respectively). Conclusions: Pregnant women of AB blood group had lower antibody signal to nucleocapsid protein compared to the O blood group, and women of older age and greater BMI had higher antibody signal to COVID-19 spike and nucleocapsid proteins. There was a significant association between women with blood group B and asymptomatic infections.

A novel hardware duo of beam modulation and shielding toreduce scatter acquisition and dose in cone-beam breastCT.

In cone-beam breast CT, scattered photons form a large portion of the acquired signal, adversely impacting image quality throughout the frequency response of the imaging system. Prior simulation studies provided proof of concept for utilization of a hardware solution to prevent scatter acquisition. Here, we report the design, implementation, and characterization of an auxiliary apparatus of fluence modulation and scatter shielding that does indeed lead to projections with a reduced level of scatter. An apparatus was designed for permanent installation within an existing cone-beam CT system. The apparatus is composed of two primary assemblies: a "Fluence Modulator" (FM) and a "Scatter Shield" (SS). The design of the assemblies enables them to operate in synchrony during image acquisition, converting the sourced x-rays into a moving narrow beam. During a projection, this narrow beam sweeps the entire fan angle coverage of the imaging system. As the two assemblies are contingent on one another, their joint implementation is described in the singular as apparatus FM-SS. The FM and the SS assemblies are each comprised a metal housing, a sensory system, and a robotic system. A controller unit handles their relative movements. A series of comparative studies were conducted to evaluate the performance of a cone-beam CT system in two "modes" of operation: with and without FM-SS installed, and to compare the results of physical implementation with those previously simulated. The dynamic range requirements of the utilized detector in the cone-beam CT imaging system were first characterized, independent of the mode of operation. We then characterized and compared the spatial resolution of the imaging system with, and without, FM-SS. A physical breast phantom, representative of an average size breast, was developed and imaged. Actual differences in signal level obtained with, versus without, FM-SS were then compared to the expected level gains based on previously reported simulations. Following these initial assessments, the scatter acquisition in each projection in both modes of operation was investigated. Finally, as an initial study of the impact of FM-SS on radiation dose in an average size breast, a series of Monte Carlo simulations were coupled with physical measurements of air kerma, with and without FM-SS. With implementation of FM-SS, the detector's required dynamic range was reduced by a factor of 5.5. Substantial reduction in the acquisition of the scattered rays, by a factor of 5.1 was achieved. With the implementation of FM-SS, deposited dose was reduced by 27% in the studied breast. The disclosed implementation of FM-SS, within a cone-beam breast CT system, results in reduction of scatter-components in acquired projections, reduction of dose deposit to the breast, and relaxation of requirements for the detector's dynamic range. Controlling or correcting for patient motion occurring during image acquisition remains an open problem to be solved prior to practical clinical usage of FM-SS cone-beam breast CT.

Multi-distance fluctuation based dispersion fractal for epileptic seizure detection in EEG signal

The developmental methods for evaluating the complexity of univariate signals has attracted extensive attention. Therefore, entropy was discovered to be one of the best methods for evaluating the complexity of a biological signal. Recent studies on signal complexity using fractal dimension have been able to tackle the domination of entropy measurement. It was found that Fluctuation-based dispersion entropy (FDispEn) is one of the recently proposed methods based on permutation (PE) and Shannon entropies (SE). This method analyzes the signal’s uncertainty and deals with its fluctuations. FDispEn mainly calculates the differences between adjacent elements of the dispersion patterns based on Shannon entropy, however, it is limited by distance. Therefore, this study proposes a new feature extraction method based on FDispEn by expanding adjacent elements’ measurement distance using the multi-distance signal level differences (MSLD) method. MSLD is an upgrade of the gray-level difference (GLD) that is used to evaluate one-dimensional signals. Furthermore, it is used to calculate several distances of adjacent dispersion patterns. The MSLD is also applied in FDispEn to form multi-distance FDispEn (MFDispEn). Other signal complexity evaluations involving two fractal dimension methods, namely Higuchi and Katz’s were used in forming the multi-distance fluctuation-based dispersion fractal (MFDF). The performance of FDispEn, MFDispEn, and three variations of MFDF were compared to evaluate the epileptic EEG signals. The results showed that the multi-distance application on MFDispEn and MFDF produced a better separability than FDispEn. Meanwhile, the MFDF outperformed the FDispEn and MFDispEn as it showed a higher accuracy, sensitivity, and specificity in classifying epileptic EEG signals.

An Ultra-Wideband Microwave Diagnostic Method for Detecting Cracks in Polymeric Insulators

To realize an embedded online diagnosis system for accurate detection of internal defects in high voltage polymeric insulators, a novel ultra-wideband (UWB) microwave diagnostic system for fault detection is proposed in this article. The UWB system is based on the multimode transferring theory on dielectric waveguides, where the level difference of transmission signals of mode transferring has been employed to detect internal defects, such as cracks. First, an investigation by simulations is performed regarding the interfacial millimeter-order cracks in both transverse and longitudinal orientations. Differences of 30-50 and 20-40 dB in receiving signals of mode-transferring between non-crack and crack cases have been observed over 3-10 GHz to transverse and longitudinal oriented cracks, respectively. Then, a test prototype is designed and manufactured for experimental verification. The measurement results have a significant 40-60 dB receiving signal level difference between the non-crack reference case and the crack case. The proposed method is promising for further development of online systems to detect millimeter-order cracks in energized polymeric insulators.

Comparison of multi-distance signal level difference Hjorth descriptor and its variations for lung sound classifications

A biological signal has the multi-scale and signals complexity properties. Many studies have used the signal complexity calculation methods and multi-scale analysis to analyze the biological signal, such as lung sound. Signal complexity methods used in the biological signal analysis include entropy, fractal analysis, and Hjorth descriptor. Meanwhile, the commonly used multi-scale methods include wavelet analysis, coarse-grained procedure, and empirical mode decomposition (EMD). One of the multi-scale methods in the biological signal analysis is the multi-distance signal level difference (MSLD), which calculates a difference between two signal samples at a specific distance. In previous studies, MSLD was combined with Hjorth descriptor for lung sound classification. MSLD has the potential to be developed by modifying the fundamental equation of MSLD. This study presents the comparison of MSLD and its variations combined with Hjorth descriptor for lung sound classification. The results showed that MSLD and its variations had the highest accuracy of 98.99% for five lung sound data classes. The results of this study provided several alternatives for multi-scale signal complexity analysis method for biological signals.

Comparison of multi-distance signal level difference Hjorth descriptor and its variations for lung sound classifications

A biological signal has the multi-scale and signals complexity properties. Many studies have used the signal complexity calculation methods and multi-scale analysis to analyze the biological signal, such as lung sound. Signal complexity methods used in the biological signal analysis include entropy, fractal analysis, and Hjorth descriptor. Meanwhile, the commonly used multi-scale methods include wavelet analysis, coarse-grained procedure, and empirical mode decomposition (EMD). One of the multi-scale methods in the biological signal analysis is the multi-distance signal level difference (MSLD), which calculates a difference between two signal samples at a specific distance. In previous studies, MSLD was combined with Hjorth descriptor for lung sound classification. MSLD has the potential to be developed by modifying the fundamental equation of MSLD. This study presents the comparison of MSLD and its variations combined with Hjorth descriptor for lung sound classification. The results showed that MSLD and its variations had the highest accuracy of 98.99% for five lung sound data classes. The results of this study provided several alternatives for multi-scale signal complexity analysis method for biological signals.

Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification

Epilepsy is a disorder of the brain's nerves as a result of excessive brain cell activity. It is generally characterized by the recurrent unprovoked seizures. This neurological abnormality can be detected and evaluated using Electroencephalogram (EEG) signal. Many algorithms have been applied to achieve high performance for the EEG classification of epileptic. However, the complexity and randomness of EEG signals become a challenge to researchers in applying the appropriate algorithms. In this research, sample entropy on Multidistance Signal Level Difference (MSLD) was applied to obtain the characteristic of EEG signals, especially towards the epilepsy patients. The test was performed on three classes of EEG data: EEG signals of epilepsy patient in ictal (seizure), interictal conditions (occurring between seizures) and normal EEG signals from healthy subjects with a closed eye condition. In this study, classification and verification were done using the Support Vector Machine (SVM) method. Through the 5-fold cross-validation, experimental results showed the highest accuracy of 97.7%.

Signal Level Comparison Between TerraSAR-X and COSMO-SkyMed SAR Sensors

Soil and vegetation biophysical parameter retrieval using synthetic-aperture-radar images requires radiometrically well-calibrated sensors. In this letter, a comparison of signal levels between TerraSAR-X (TSX) and the COSMO-SkyMed (CSK) constellation (CSK1, CSK2, CSK3, and CSK4) was carried out in order to analyze the ability to use jointly all current X-band sensors. The analysis of the X-band signal over forest stands showed a stable signal (variation lower than 1 dB) over time for each of the studied sensors, but a significant difference was observed between the different X-band sensors. Differences between radar signals were higher in HH than in HV polarization. TSX and CSK4 showed similar backscatter signals, with signal level differences of 0.6 dB in HH and 1.4 dB in HV. The CSK3 signal was observed to be lower than those from TSX and CSK4 by about 2.1 dB and 1.5 dB in HH against 3.2 dB and 1.8 dB in HV, respectively. Moreover, CSK2 and CSK1 which showed slightly different backscatter signals (within 1.1 dB in HH and 1.9 dB in HV) had signal levels lower than those obtained from TSX (2.2-3.3 dB in HH and 3.2-5.1 dB in HV for about 29° incidence angle). These results show that it is currently difficult to use jointly the available X-band satellites (CSK and TSX) for estimating the biophysical parameters of soil or vegetation. This is due to the significant difference in the radar signal level between some of the analyzed satellites, which will cause a high overor underestimation of biophysical parameters.

RSS Based Bridge Scour Measurement Using Underwater Acoustic Sensor Networks

Bridge Scour is one of the major causes of bridge failures all around the world and there have been significant efforts for its detection and measurement using different acoustic approaches. In this paper, we propose and investigate an effective method to utilize Received Signal Strength (RSS) for measuring scour depth where acoustic sensors are deployed. We also extend a statistical testing to determine the difference in signal levels at the sensor nodes prior to and after scour formation and subsequently determine the actual depth of scour. Additionally, we make an attempt to evaluate underwater distance and depth using signal strength perceived at the receiver which makes it free from the requirement of accurate receiver-sender synchronization in contrast to Time of Flight (ToF) or Time of Arrival (ToA) techniques. The scour depths are eventually compared for the conditions when the bottom is composed of a single or multiple layers. The simulation results clearly show that different depths are calculated for the case of multilayered bottom (0.8 to 3.9 meters for instance) as compared to a constant depth of 2 meters for the case of a single layered bottom.

Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7–9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD.

Direct detection of guidance receptor activity during border cell migration

Guidance receptor signaling is crucial for steering migrating cells. Despite this, we generally lack direct measurements of such signaling. Border cells in Drosophila migrate as a tightly associated group, but dynamically, with front and rear cells exchanging places. They use the receptor tyrosine kinase (RTK) PDGF/VEGF receptor (PVR) as a guidance receptor, perceiving the attractant Pvf1. Here we determine the spatial distribution of PVR signaling by generating an antibody that specifically detects activated PVR in situ. PVR activity is very low in migrating border cells, due to strong activity of cellular phosphatases. Measurements of signal at the cell cortex show variability but a strong bias for both total active PVR and specific activity of PVR to be elevated at the front versus side of the leading cell, often with several-fold difference in signal levels. This polarized active PVR signal requires the E3 ubiquitin ligase Cbl and the recycling regulator Rab11, indicating a dependency on receptor trafficking. The endogenous ligand gradient contributes to shaping of signaling by increasing the specific activity of PVR toward the source in front cells. Surprisingly, signaling is also elevated at the back versus the side of rear cells. This distally polarized distribution of active PVR is ligand independent. Thus the actual guidance signal transmitted in border cells appears to integrate perceived ligand distribution with cell polarity or cell orientation with respect to the cluster. A general implication is that both group configuration and extrinsic cues can directly modulate guidance receptor signaling during collective cell migration.

Attenuation in marine sediments: In situ measurements versus propagation‐loss inversions.

Acoustic attenuation in marine sediments may be measured either in situ, from the difference in signal level at two embedded probes, or from an inversion of transmission loss in the water column. Most in situ measurements are performed above 10 kHz and return an attenuation that scales as the first power of frequency, whereas transmission‐loss inversions are performed at lower frequencies, returning a near‐square‐law variation with frequency. The difference between the in situ and transmission‐loss estimates could be due to a combination of factors, including bottom roughness, which may lead to an enhanced attenuation from the transmission‐loss inversions. The nonoverlapping frequency bands of the two techniques could also account for the differences in the estimated scalings of attenuation with frequency. Thus, the attenuation could scale roughly as the square of the frequency below a few kilohertz, transitioning to a linear dependence above 10 kHz. Such behavior would be consistent with the recently dev...

The CNS glycoprotein Shadoo has PrPC-like protective properties and displays reduced levels in prion infections

The cellular prion protein, PrPC, is neuroprotective in a number of settings and in particular prevents cerebellar degeneration mediated by CNS-expressed Doppel or internally deleted PrP (‘ΔPrP'). This paradigm has facilitated mapping of activity determinants in PrPC and implicated a cryptic PrPC-like protein, ‘π'. Shadoo (Sho) is a hypothetical GPI-anchored protein encoded by the Sprn gene, exhibiting homology and domain organization similar to the N-terminus of PrP. Here we demonstrate Sprn expression and Sho protein in the adult CNS. Sho expression overlaps PrPC, but is low in cerebellar granular neurons (CGNs) containing PrPC and high in PrPC-deficient dendritic processes. In Prnp0/0 CGNs, Sho transgenes were PrPC-like in their ability to counteract neurotoxic effects of either Doppel or ΔPrP. Additionally, prion-infected mice exhibit a dramatic reduction in endogenous Sho protein. Sho is a candidate for π, and since it engenders a PrPC-like neuroprotective activity, compromised neuroprotective activity resulting from reduced levels may exacerbate damage in prion infections. Sho may prove useful in deciphering several unresolved facets of prion biology.

Two distinct modes of guidance signalling during collective migration of border cells

Although directed migration is a feature of both individual cells and cell groups, guided migration has been studied most extensively for single cells in simple environments. Collective guidance of cell groups remains poorly understood, despite its relevance for development and metastasis. Neural crest cells and neuronal precursors migrate as loosely organized streams of individual cells, whereas cells of the fish lateral line, Drosophila tracheal tubes and border-cell clusters migrate as more coherent groups. Here we use Drosophila border cells to examine how collective guidance is performed. We report that border cells migrate in two phases using distinct mechanisms. Genetic analysis combined with live imaging shows that polarized cell behaviour is critical for the initial phase of migration, whereas dynamic collective behaviour dominates later. PDGF- and VEGF-related receptor and epidermal growth factor receptor act in both phases, but use different effector pathways in each. The myoblast city (Mbc, also known as DOCK180) and engulfment and cell motility (ELMO, also known as Ced-12) pathway is required for the early phase, in which guidance depends on subcellular localization of signalling within a leading cell. During the later phase, mitogen-activated protein kinase and phospholipase Cgamma are used redundantly, and we find that the cluster makes use of the difference in signal levels between cells to guide migration. Thus, information processing at the multicellular level is used to guide collective behaviour of a cell group.

Compensation for the mutual coupling effect in the ESPRIT direction finding algorithm by using a more effective method

An effective method is introduced to compensate for the mutual coupling effect in the estimation of signal parameter via rotational invariance techniques (ESPRIT) direction finding algorithm. The compensation method seeks to quantify the mutual coupling more accurately by using a new mutual impedance. Study of two closely spaced arriving signals shows that the high-resolution capability of ESPRIT can be achieved only when the mutual coupling effect is compensated for by using our new compensation method. Critical situations with a large signal level difference, with an increased mutual coupling effect resulting from a more compact-size antenna array, and with signals coming from a nonhorizontal elevation angle are also studied using the ESPRIT algorithm. Results show that the new compensation method, when applied to ESPRIT, is more accurate, more robust, and more flexible than the previous open-circuit voltage method.