Identification of defected sensors in an array of amperometric gas sensors

Purpose Amperometric gas sensors are commonly used in air quality monitoring in long-term measurements. Baseline shift of sensor responses and power failure may occur over time, which is an obstacle for reliable operation of the entire system. The purpose of this study is to check the possibility of using PCA method to detect defected samples, identify faulty sensor and correct the responses of the sensor identified as faulty. Design/methodology/approach In this work, the authors present the results obtained with six amperometric sensors. An array of sensors was exposed to sulfur dioxide at the following concentrations: 0 ppm (synthetic air), 50 ppb, 100 ppb, 250 ppb, 500 ppb and 1000 ppb. The damage simulation consisted in adding to the sensor response a value of 0.05 and 0.1 µA and replacing the responses of one of sensors with a constant value of 0 and 0.15 µA. Sensor validity index was used to identify a damaged sensor in the matrix, and its responses were corrected via iteration method. Findings The results show that the methods used in this work can be potentially applied to detect faulty sensor responses. In the case of simulation of damage by baseline shift, it was possible to achieve 100% accuracy in damage detection and identification of the damaged sensor. The method was not very successful in simulating faults by replacing the sensor response with a value of 0 µA, due to the fact that the sensors mostly gave responses close to 0 µA, as long as they did not detect SO2 concentrations below 250 ppb and the failure was treated as a correct response. Originality/value This work was inspired by methods of simulating the most common failures that occurs in amperometric gas sensors. For this purpose, simulations of the baseline shift and faults related to a power failure or a decrease in sensitivity were performed.

Prediction of H-Type Hypertension Based on Pulse Wave MFCC Features Using Mixed Attention Mechanism

H-type hypertension increases the risks of stroke and cardiovascular disease, posing a great threat to human health. Pulse diagnosis in traditional Chinese medicine ( TCM ) combined with deep learning can independently predict suspected H-type hypertension patients by analyzing their pulse physiological activities. However, the traditional time-domain feature extraction has a higher noise and baseline drift, affecting the classification accuracy. In this literature, we propose an effective prediction on frequency-domain pulse wave features. First, we filter time-domain pulse waves via removal of high-frequency noises and baseline shift. Second, Hilbert-Huang Transform is explored to transform time-domain pulse wave into frequency-domain waveform characterized by Mel-frequency cepstral coefficients (MFCC). Finally, an improved BiLSTM model, combined with mixed attention mechanism is built to applied for prediction of H-type hypertension. With 337 clinical cases from Longhua Hospital affiliated to Shanghai University of TCM and Hospital of Integrated Traditional Chinese and Western Medicine, the 3-fold cross-validation results show that sensitivity, specificity, accuracy, F1-score and AUC reaches 93.48%, 95.27%, 97.48%, 90.77% and 0.9676, respectively. The proposed model achieves better generalization performance than the classical traditional models. In addition, we calculate the feature importance both in time-domain and frequency-domain according to purity of nodes in Random Forest and study the correlations between features and classification that has a good reference value for TCM clinical auxiliary diagnosis.

Baseline Shift in Neuronal Oscillations and Its Implications for the Interpretation of Evoked Activity Obtained with EEG/MEG

Oscillations and evoked responses are two types of neuronal activity recorded non-invasively with EEG/MEG. Although typically studied separately, they might in fact represent the same process. One possibility to unite them is to demonstrate that neuronal oscillations have non-zero mean which would indicate that stimulus-relating amplitude modulation of neuronal oscillations should lead to the generation of evoked responses. We validated this mechanism using computational modelling and analysis of a large EEG data set. With a biophysical model generating alpha rhythm, we indeed demonstrated that the oscillatory mean is nonzero for a large range of model-parameter values. In EEG data we detected non-zero mean alpha oscillations in about 96% of the participants. Furthermore, using neuronal-ensemble modelling, we provided an explanation for the often observed discrepancies between amplitude modulation and baseline shifts. Overall, our results provide strong support for the unification of neuronal oscillations and evoked responses.

Using 4DCBCT simulation and guidance to evaluate inter-fractional tumor variance during SABR for lung tumor within the lower lobe

Inter-fractional tumor variance would lead to insufficient dosage or overdose in tumor region during lung cancer radiotherapy. However, previous works have not considered influence of inter-fractional tumor amplitude variance at treatment position due to lack of effective evaluation method during radiotherapy, especially for lung tumor within the lower lobe. Our objective was to investigate inter-fractional tumor baseline shift and amplitude variance due to respiratory motion with 4DCBCT simulation and guidance during stereotactic ablative body radiotherapy (SABR) for lung tumor. Subject included 19 patients with lung tumor within the lower lobe. 4DCBCT-simulated images at treatment position were acquired sequentially to determine internal tumor volume (ITV) and reference tumor motion at simulation process. Compared with reference tumor motion, 95 4DCBCT-guided images were acquired during each treatment to evaluate inter-fractional tumor baseline shift and amplitude variance, which were − 0.0 ± 1.3 mm and − 0.2 ± 1.4 mm in left–right(LR) direction, 0.9 ± 2.3 mm and 0.4 ± 2.9 mm in superior-inferior (SI) direction, 0.1 ± 1.5 mm and − 0.4 ± 2.0 mm in anterior–posterior (AP) direction. ITV margin were 3.5 mm, 7.5 mm and 5.3 mm in LR, SI and AP directions with van Herk’s (Int J Radiat Oncol Biol Phys 52(5):1407–1422, 2002) formula. 4DCBCT simulation and guidance is a reliable method to evaluate inter-fractional tumor variance during SABR for lung tumor within the lower lobe. ITV margin of 3.5 mm, 7.5 mm and 5.3 mm in LR, SI and AP directions would ensure greater tumor coverage during SABR for lung tumor within the lower lobe.

MEG Oscillatory and Aperiodic neural dynamics contribute to different cognitive aspects of short-term memory decline through lifespan

ABSTRACTNeural communication or signal transmission in the brain propagates via distinct oscillatory frequency bands. With aging, the communication mediated by these frequency bands is hindered by noise, which arises from the increased stochastic variability in the baseline neural spiking. This increase in noise measured as 1/f power-law scaling reflects the global background noise and is often linked to impaired cognition in different tasks. In this study, we quantified the 1/f slope and intercept of MEG brain signal as a putative marker of neural noise and examined its effect on cognitive and metacognitive measures. We hypothesize that as neural communication becomes noisier with age, it impacts global information processing, whereas specific periodic features mediate local aspects of cognition. Using recently proposed parametric Fooof model, we first characterised the normative pattern of periodic and aperiodic features (temporal dynamics) across the lifespan, modelled via spectral peaks (Central frequency, power, bandwidth) and 1/f noise activity (slope and intercept) respectively. Secondly, how this Resting-State (RS) baseline shift in temporal dynamics of the signal is associated with various aspects of visual short-term memory (VSTM). Our results suggest that age-associated global change in noisy baseline affects global information processing and crucially impacts the oscillatory features, which relates to more local processing and selective behavioural measures in the VSTM task. Moreover, we suggest that the task-related differences observed across age groups are due to the baseline shift of periodic and aperiodic features.Significant statementAging is accompanied by the decline in cognitive functions and age itself is a major risk factor for Alzheimer’s Disease and other neurological conditions. Our study provides MEG 1/f aperiodic and periodic markers across the healthy adult lifespan and shows that different frequency bands and their spectral features mediate age-related changes across different brain regions, in multiple cognitive and metacognitive domains, which not only provides us with a better understanding of the aging process but would also help in better prevention of cognitive impairments. A clear characterization of the association between baseline MEG temporal dynamics, healthy aging and cognition, is established in this study.

Alpha-band Activity Tracks the Zoom Lens of Attention

Voluntary control over spatial attention has been likened to the operation of a zoom lens, such that processing quality declines as the size of the attended region increases, with a gradient of performance that peaks at the center of the selected area. Although concurrent changes in activity in visual regions suggest that zoom lens adjustments influence perceptual stages of processing, extant work has not distinguished between changes in the spatial selectivity of attention-driven neural activity and baseline shift of activity that can increase mean levels of activity without changes in selectivity. Here, we distinguished between these alternatives by measuring EEG activity in humans to track preparatory changes in alpha activity that indexed the precise topography of attention across the possible target positions. We observed increased spatial selectivity in alpha activity when observers voluntarily directed attention toward a narrower region of space, a pattern that was mirrored in target discrimination accuracy. Thus, alpha activity tracks both the centroid and spatial extent of covert spatial attention before the onset of the target display, lending support to the hypothesis that narrowing the zoom lens of attention shapes the initial encoding of sensory information.

Sunspot observations by Hisako Koyama: 1945–1996

ABSTRACT Sunspot records are the only observational tracer of solar activity that provides a fundamental, multicentury reference. Its homogeneity has been largely maintained with a succession of long-duration visual observers. In this article, we examine observations of one of the primary reference sunspot observers, Hisako Koyama. By consulting original archives of the National Museum of Nature and Science of Japan (hereafter, NMNS), we retrace the main steps of her solar-observing career, from 1945 to 1996. We also present the reconstruction of a full digital data base of her sunspot observations at the NMNS, with her original drawings and logbooks. Here, we extend the availability of her observational data from 1947–1984 to 1945–1996. Comparisons with the international sunspot number (Version 2) and with the group sunspot number series show a good global stability of Koyama's observations, with only temporary fluctuations over the main interval 1947–1982. Identifying drawings made by alternate observers throughout the series, we find that a single downward baseline shift in the record coincides with the partial contribution of replacement observers mostly after 1983. We determine the correction factor to bring the second part (1983–1996) to the same scale with Koyama's main interval (1947–1982). We find a downward jump by 9 per cent after 1983, which then remains stable until 1995. Overall, the high quality of Koyama's observations with her life-long dedication leaves a lasting legacy of this exceptional personal achievement. With this comprehensive recovery, we now make the totality of this legacy directly accessible and exploitable for future research.

Real-time coseismic deformations from adaptively tight integration of high-rate GNSS and strong motion records

SUMMARY In traditional tight integration of high-rate GNSS and strong motion sensors, an appropriate process variance is crucial for obtaining accurate broad-band coseismic deformations. In this paper, instead of using a subjectively empirical value, we present an approach for determining the process variance adaptively based on the adaptive Kalman filter for real-time use. The performance of the approach was validated by the colocated stations collected during the 2010 Mw 7.2 earthquake in El-Mayor, 2016 Mw 7.8 earthquake in New Zealand and 2016 Mw 6.5 earthquake in central Italy. The results show that this method complements the advantages of GNSS and strong motion accelerometers and can provide more accurate coseismic waveforms especially during the strong shaking period, due to the ability of the method to adjust the process variance in real time according to the actual status of the station. In addition, this method is also free from the influence of the baseline shift. Testing of the new method for the integration of strong motion and multi-GNSS indicates that multi-GNSS has an obvious improvement in the precision while single GPS has a poor observation condition.

Multiple mechanisms link prestimulus neural oscillations to sensory responses

Spontaneous fluctuations of neural activity may explain why sensory responses vary across repeated presentations of the same physical stimulus. To test this hypothesis, we recorded electroencephalography in humans during stimulation with identical visual stimuli and analyzed how prestimulus neural oscillations modulate different stages of sensory processing reflected by distinct components of the event-related potential (ERP). We found that strong prestimulus alpha- and beta-band power resulted in a suppression of early ERP components (C1 and N150) and in an amplification of late components (after 0.4 s), even after controlling for fluctuations in 1/f aperiodic signal and sleepiness. Whereas functional inhibition of sensory processing underlies the reduction of early ERP responses, we found that the modulation of non-zero-mean oscillations (baseline shift) accounted for the amplification of late responses. Distinguishing between these two mechanisms is crucial for understanding how internal brain states modulate the processing of incoming sensory information.

Hair cell and neural contributions to the cochlear summating potential

The cochlear summating potential (SP) to a tone is a baseline shift that persists for the duration of the burst. It is often considered the most enigmatic of cochlear potentials because its magnitude and polarity vary across frequency and level and its origins are uncertain. In this study, we used pharmacology to isolate sources of the SP originating from the gerbil cochlea. Animals either had the full complement of outer and inner hair cells (OHCs and IHCs) and an intact auditory nerve or had systemic treatment with furosemide and kanamycin (FK) to remove the outer hair cells. Responses to tone bursts were recorded from the round window before and after the neurotoxin kainic acid (KA) was applied. IHC responses were then isolated from the post-KA responses in FK animals, neural responses were isolated from the subtraction of post-KA from pre-KA responses in NH animals, and OHC responses were isolated by subtraction of post-KA responses in FK animals from post-KA responses in normal hearing (NH) animals. All three sources contributed to the SP; OHCs with a negative polarity and IHCs and the auditory nerve with positive polarity. Thus the recorded SP in NH animals is a sum of contributions from different sources, contributing to the variety of magnitudes and polarities seen across frequency and intensity. When this information was applied to observations of the SP recorded from the round window in human cochlear implant subjects, a strong neural contribution to the SP was confirmed in humans as well as gerbils. NEW & NOTEWORTHY Of the various potentials produced by the cochlea, the summating potential (SP) is typically described as the most enigmatic. Using combinations of ototoxins and neurotoxins, we show contributions to the SP from the auditory nerve and from inner and outer hair cells, which differ in polarity and vary in size across frequency and level. This complexity of sources helps to explain the enigmatic nature of the SP.