Arrival Of Wave Research Articles

Meteotsunamis in Japan Associated with the Tonga Eruption in January 2022

Large-amplitude meteotsunamis were observed in many areas in Japan, following the arrival of barometric Lamb waves emitted by an underwater volcanic eruption of Hunga Tonga-Hunga Ha‘apai in January 2022. We modeled the power spectra of the tidal level data obtained from 12 tide stations of the Geospatial Information Authority of Japan, based on a method of transfer function which converts the barometric pressure pulse spectra into the meteotsunami spectra. The obtained transfer functions are similar at 12 stations. The pressure pulse spectra are obtained from the ensemble average of ∼1500 Soratena weather sensors of Weathernews Inc. distributed over Japan. The observed meteotsunami spectra can be characterized by the enhanced seiche eigenmodes at each station excited by the mesoscale pressure pulse within the amplitude error of 50%, which contributes for accumulating the necessary knowledge to understand the potential dangers in various different areas over Japan.

Echo spectrum modulation characteristics of plasma flow field simulated by wind tunnel

<sec>When the aircraft moves through the atmosphere at a very high speed, the aircraft will experience intense friction with the surrounding atmosphere, which causes the air to be ionized into plasma, thus producing a plasma flow field around it. Plasma is constantly generated on the windward side of the aircraft and flows backwards. The velocity of plasma is different from that of the aircraft. In addition to the dispersion characteristics of the plasma and the non-uniform distribution around the target, the plasma flow field will produce the effects of amplitude, frequency and phase modulation on the incident radar wave, which will change the electromagnetic scattering characteristics of the target. </sec><sec>In order to reproduce the non-uniform Doppler phenomenon in the flow field under electromagnetic wave irradiation, the plasma echo spectrum is measured experimentally in the JF-10 wind tunnel of the Institute of Mechanics, the Chinese Academy of Sciences. The echo spectrum data of S band and C band are obtained by using a measurement system composed of signal source, circulator, antenna and spectrometer, and based on the measured data the one-dimensional range profile of the plasma coated target is simulated, and the results show that the plasma flow field has a spectrum modulation effect on the target. When the speed of the flow field cannot be compensated for accurately, the spectral modulation effect will further cause the one-dimensional range profile to defocus, which will affect the ability of radar to detect and track the object. The preliminary analysis shows that the effect is caused mainly by the inhomogeneous velocity distribution of plasma flow field and the sudden change of medium parameters when the shock wave arrives. This experiment can provide data support for verifying the electromagnetic characteristics modeling method of plasma flow field. </sec>

SOCIAL COHESION: A TOOL TO COUNTER PANDEMIC EFFECTS

This research paper explores the role of social cohesion during the pandemic crisis. The adverse impact of pandemic crisis challenged the existence of human beings affecting social stability, economy and mental well-being of people. With the threat of the arrival of concurrent waves of pandemic the people are living in fear and anxiety. In order to understand the role of social cohesion database searches were done in Scopus, Google scholar, Research Gate and PLoS One. From the identified 120 relevant articles, 52 articles were selected and included for review in this paper. These articles helped in preparing the base for proposing 3P model. The 3P(P1= Promoting Participation by Minimizing Inequities, P2= Priority setting, P3= Policy Formulation and Planned Intervention) model suggested in the paper focuses on creating the strategy highlighting that as pandemic creates strain on socio-economic resources, the social cohesion in the society helps in dealing the crisis. The suggested model outlines the importance of social cohesion in dealing the critical situations and emphasizes that social cohesion can act as buffer for people in reducing vulnerabilities to the pandemic crisis in an effective way and crafting reality based approach to deal with crisis from time to time.

Generation of ultrasonic tomography from time-domain propagation spectrum

The projection of several ultrasonic pulse velocity (UPV) measurements is one of the common procedures for the generation of ultrasonic tomographic images. However, only the time of arrival of ultrasonic waves or the first amplitude of the waveform after onset is evaluated. This paper presents a methodology for the generation of tomographic images from the analysis of the time-domain propagation spectrum. Nonlinear optimization techniques were applied with the use of heuristic algorithms, and the methodology effectiveness was demonstrated in simple UPV applications extended to the tomography generation. The approach provided reliable values and images in all numerical applications and showed the analysis of time spectrum significantly reduces the number of measurements required for the generation of a tomogram maintaining the quality of the results.

Simulation of Unsteady Movement in the Downstream of a Hydroelectric Complex During the Destruction of a Soil Dam

153 reservoirs have been created in the Republic of Belarus. During the period of passing catastrophic floods and high waters along the river, there is a risk of overflowing reservoirs, overflow of water masses through the crest of an earthen dam and flooding of significantly large areas. The destruction of the dam is accompanied by the formation of a breach and the outflow through it of an unsteady flow of water in the form of a breakthrough wave into the downstream. A breakthrough wave and catastrophic flooding of the area are the main destructive factors of hydrodynamic accidents. Calculations to determine parameters of the wave and to assess the possible consequences of flooding are necessary when drawing up operational-and-tactical plans for the prevention and elimination of emergencies in case of accidents at retaining structures, determining the probable damage from flooding of the territory in the downstream of a hydraulic structure as a result of the passage of a breakthrough wave. It is necessary to assess the flooding zone and the hydrodynamic parameters of the flow, viz. the maximum values of the depth and velocity of the flow in the zone of catastrophic flooding, the time from the beginning of the accident to the arrival of a breakthrough wave at the particular point of the terrain, the duration of flooding, the boundaries of the zone of catastrophic flooding, the hydrographic flow rate in the section of the eroded dam and the graph of the fall headwater level. The degree of reliability of predictive calculations is determined by the accuracy of the two applied mathematical models, viz.: 1) erosion of the dam; 2) the movement of the breakout wave. The analysis of the applied mathematical models shows that in all cases the hydrodynamic models based on the oneand two-dimensional equations of Boussinesq – Saint-Venant are used to calculate the movement of the breakthrough wave. Wave parameters, i. e. wave height and speed of its propagation, completely depend on the hydrograph of the discharge in the section of the eroded dam, which, in its turn, is determined by the dynamics of its erosion. The aim of the work is to develop a methodology for calculating the flooding of the downstream as a result of the destruction of a soil dam.

Understanding the phase transformation mechanisms that affect the dynamic response of Fe-based microstructures at the atomic scales

Large-scale molecular dynamics (MD) simulations were carried out to investigate the shock-induced evolution of microstructure in Fe-based systems comprising single-crystal and layered Cu/Fe alloys with a distribution of interfaces. The shock compression of pure single-crystal Fe oriented along [110] above a threshold pressure results in a BCC (α) → HCP (ɛ) phase transformation behavior that generates a distribution of ε phase variants in the phase transformed region of the microstructure behind the shock front. The propagation of the release wave through a phase transformed ε phase causes a reverse ɛ → α phase transformation and renders a distribution of twins for the [110] oriented Fe that serve as void nucleation sites during spall failure. The simulations reveal that the α → ɛ → α transformation-induced twinning for shock loading along the [110] direction is due to a dominant ɛ phase variant formed during compression that rotates on the arrival of the release wave followed by a reverse phase transformation to twins in the α phase. The modifications in the evolution of the ɛ phase variants and twins in Fe behavior are also studied for Cu–Fe layered microstructures due to the shock wave interactions with the Cu/Fe interfaces using a newly constructed Cu–Fe alloy potential. The MD simulations suggest that interfaces affect the observed variants during shock compression and, hence, distributions of twins during shock release that affects the void nucleation stresses in the Fe phase of Cu/Fe microstructures.

Respiration, Heartbeat, and Conscious Tactile Perception.

Previous studies have shown that timing of sensory stimulation during the cardiac cycle interacts with perception. Given the natural coupling of respiration and cardiac activity, we investigated here their joint effects on tactile perception. Forty-one healthy female and male human participants reported conscious perception of finger near-threshold electrical pulses (33% null trials) and decision confidence while electrocardiography, respiratory activity, and finger photoplethysmography were recorded. Participants adapted their respiratory cycle to expected stimulus onsets to preferentially occur during late inspiration/early expiration. This closely matched heart rate variation (sinus arrhythmia) across the respiratory cycle such that most frequent stimulation onsets occurred during the period of highest heart rate probably indicating highest alertness and cortical excitability. Tactile detection rate was highest during the first quadrant after expiration onset. Interindividually, stronger respiratory phase-locking to the task was associated with higher detection rates. Regarding the cardiac cycle, we confirmed previous findings that tactile detection rate was higher during diastole than systole and newly specified its minimum at 250-300 ms after the R-peak corresponding to the pulse wave arrival in the finger. Expectation of stimulation induced a transient heart deceleration which was more pronounced for unconfident decision ratings. Interindividually, stronger poststimulus modulations of heart rate were linked to higher detection rates. In summary, we demonstrate how tuning to the respiratory cycle and integration of respiratory-cardiac signals are used to optimize performance of a tactile detection task.SIGNIFICANCE STATEMENT Mechanistic studies on perception and cognition tend to focus on the brain neglecting contributions of the body. Here, we investigated how respiration and heartbeat influence tactile perception: respiration phase-locking to expected stimulus onsets corresponds to highest heart rate (and presumably alertness/cortical excitability) and correlates with detection performance. Tactile detection varies across the heart cycle with a minimum when the pulse reaches the finger and a maximum in diastole. Taken together with our previous finding of unchanged early event-related potentials across the cardiac cycle, we conclude that these effects are not a peripheral physiological artifact but a result of cognitive processes that model our body's internal state, make predictions to guide behavior, and might also tune respiration to serve the task.

Reviews and syntheses: Physical and biogeochemical processes associated with upwelling in the Indian Ocean

Reviews and syntheses: Physical and biogeochemical processes associated with upwelling in the Indian Ocean

The <i>M</i><sub>w</sub> 7.5 Tadine (Maré, Loyalty Islands) earthquake and related tsunami of 5 December 2018: seismotectonic context and numerical modeling

Abstract. On 5 December 2018, a magnitude Mw 7.5 earthquake occurred southeast of Maré, an island of the Loyalty Islands archipelago, New Caledonia. This earthquake is located at the junction between the plunging Loyalty Ridge and the southern part of the Vanuatu Arc, in a tectonically complex and very active area regularly subjected to strong seismic crises and earthquakes higher than magnitude 7 and up to 8. Widely felt in New Caledonia, it was immediately followed by a tsunami warning, confirmed shortly after by a first wave arrival at the Loyalty Islands tide gauges (Maré and Lifou), and then along the east coast of Grande Terre of New Caledonia and in several islands of the Vanuatu Archipelago. Two solutions of the seafloor initial deformation are considered for tsunami generation modeling, one using a non-uniform finite-source model from USGS and the other being a uniform slip model built from the Global Centroid Moment Tensor (GCMT) solution, with the geological knowledge of the region and empirical laws establishing relationships between the moment magnitude and the fault plane geometry. Both tsunami generation and propagation are simulated using the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), an open-source modeling code solving the shallow-water equations on an unstructured grid allowing refinement in many critical areas. The results of numerical simulations are compared to tide gauge records, field observations and testimonials from 2018. Careful inspection of wave amplitude and wave energy maps for the two simulated scenarios shows clearly that the heterogeneous deformation model is inappropriate, while it raises the importance of the fault plane geometry and azimuth for tsunami amplitude and directivity. The arrival times, wave amplitude and polarities obtained with the uniform slip model are globally coherent, especially in far-field locations (Hienghène, Poindimié and Port Vila). Due to interactions between the tsunami waves and the numerous bathymetric structures like the Loyalty and Norfolk ridges in the neighborhood of the source, the tsunami propagating toward the south of Grande Terre and the Isle of Pines is captured by these structures acting like waveguides, allowing it to propagate to the north-northwest, especially in the Loyalty Islands and along the east coast of Grande Terre. A similar observation results from the propagation in the Vanuatu islands, from Aneityum to Efate.

Influence of road blockage on tsunami evacuation: A comparative study of three different coastal cities in Japan

For the case of a near-field tsunami, severe ground shaking prior to the arrival of the first tsunami wave could result in the collapse of many buildings, which could lead to road blockage and hinder evacuation. The present study aims to clarify the influence that seismic damage to the buildings and the debris created will have on the road network, and how this in turn will influence tsunami evacuation and the expected number of casualties. To do so, an agent-based tsunami evacuation simulation model that can consider the changes in evacuation behaviour due to road blockage was developed. The model was then applied to three coastal cities in Japan (Kamakura, Zushi, Fujisawa) by considering a Genroku Kanto Earthquake Tsunami scenario. The simulated results showed that considering the effects of building collapse and associated road blockage significantly increased the expected mortality rates. A correlation analysis also indicated that while mortality rates considering road blockage were strongly correlated with inundation depth, they were also positively correlated with the percentage of collapsed buildings, and blocked roads. This suggests that the inundation depth and the distance to a refuge area/shelter might not be sufficient parameters to determine the likely tsunami risks at a given point in a coastal city in the case of a near-field tsunami, and that the effect of damaged buildings should also be considered.

Recovery of the parameters of a focal zone by the data of earthquakes

We present an approach for solving the inverse kinematic problem of seismic with internal sources, based on the method of multidimensional data approximation on irregular grids. The times of arrival of elastic waves to the seismic stations are considered as known. The hodographs from earthquake to the stations are approximated for further determining the velocities of longitudinal and transverse waves using the eikonal equation. The ratio of these velocities determines the Poisson’s ratio, and the other elastic parameters of the medium can be found in units of the density. The results of implementation of the approach, based on the real data, are presented.

Causality of cortical and cardiovascular activity during cyclic alternating pattern in non-rapid eye movement sleep.

The dynamic interplay between central and autonomic nervous system activities plays a pivotal role in orchestrating sleep. Macrostructural changes such as sleep-stage transitions or phasic, brief cortical events elicit fluctuations in neural outflow to the cardiovascular system, but the causal relationships between cortical and cardiovascular activities underpinning the microstructure of sleep are largely unknown. Here, we investigate cortical-cardiovascular interactions during the cyclic alternating pattern (CAP) of non-rapid eye movement sleep in a diverse set of overnight polysomnograms. We determine the Granger causality in both 507 CAP and 507 matched non-CAP sequences to assess the causal relationships between electroencephalography (EEG) frequency bands and respiratory and cardiovascular variables (heart period, respiratory period, pulse arrival time and pulse wave amplitude) during CAP. We observe a significantly stronger influence of delta activity on vascular variables during CAP sequences where slow, low-amplitude EEG activation phases (A1) dominate than during non-CAP sequences. We also show that rapid, high-amplitude EEG activation phases (A3) provoke a more pronounced change in autonomic activity than A1 and A2 phases. Our analysis provides the first evidence on the causal interplay between cortical and cardiovascular activities during CAP. Granger causality analysis may also be useful for probing the level of decoupling in sleep disorders. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Simultaneous Occurrence of Tropical Cyclones in the Northern Indian Ocean: Differential Response and Triggering Mechanisms

The northern Indian Ocean, comprising of two marginal seas, the Arabian Sea (AS) and the Bay of Bengal (BoB), is known for the occurrence of tropical cyclones. The simultaneous occurrence of the cyclones Luban in the AS and Titli in the BoB is a rare phenomenon, and, in the present study, we examined their contrasting upper ocean responses and what led to their formation in October 2018. Being a category-2 cyclone, the maximum cooling of sea surface temperature associated with Titli was 1°C higher than that of Luban, a category-1 cyclone. The higher tropical cyclone heat potential in the BoB compared with the AS was one of the reasons why Titli was more intense than Luban. The enhancement of chlorophylla(Chl-a) and net primary productivity (NPP) by Luban was 2- and 3.7-fold, respectively, while that by Titli was 3- and 5-fold, respectively. Despite this, the magnitudes of both Chl-aand NPP were higher in the AS compared with the BoB. Consistent with physical and biological responses, the CO2outgassing flux associated with Titli was 12-fold higher in comparison to the pre-cyclone value, while that associated with Luban was 10-fold higher. Unlike the Chl-aand NPP, the magnitude of CO2flux in the BoB was higher than that in the AS. Although the cyclones Luban and Titli originated simultaneously, their generating mechanisms were quite different. What was common for the genesis of both cyclones was the pre-conditioning of the upper ocean in 2018 by the co-occurrence of El Niño and the positive phase of Indian Ocean dipole along with the cold phase of the Pacific decadal oscillation, all of which worked in tandem and warmed the AS and parts of the BoB. What triggered the genesis of Luban in the AS was the arrival of the Madden–Julian oscillation (MJO) and the mixed Rossby-gravity wave during the first week of October. The genesis of Titli in the BoB was triggered by the eastward propagation of the MJO and the associated enhanced convection from the AS into the region of origin of Titli along with the arrival of the downwelling oceanic Rossby wave.

A template-free approach for waveform extraction of gravitational wave events

We develop a general data-driven and template-free method for the extraction of event waveforms in the presence of background noise. Recent gravitational-wave observations provide one of the significant scientific areas requiring data analysis and waveform extraction capability. We use our method to find the waveforms for the reported events from the first, second, and third LIGO observation runs (O1, O2, and O3). Using the instantaneous frequencies derived by the Hilbert transform of the extracted waveforms, we provide the physical time delays between the arrivals of gravitational waves to the detectors.

Preliminary Results of Automatic P-Wave Regional Earthquake Arrival Time Picking using Machine Learning with Kurtosis and Skewness as The Input Parameters

The traditional method in determining first arrival time of earthquake dataset is time consuming process due to waveform manual inspection. Additional waveform attributes can help determine events detection. One of the widely used attribute is The Short Term Averaging/Long Term Averaging (STA/LTA) which is simply division moving average of waveform amplitude between short time and longer time. Alternatively, waveform attribute can also be built using kurtosis and skewness. The kurtosis attribute is defined as sharpness of data distribution. By definition, the maximum signal should be at or close to the P wave arrival. The skewness is typically used to show normal distribution of the data. The uniqueness of this method is that it has an ability to determine whether the first P wave arrival has positive of negative number. The skewness calculation is similar to kurtosis but it uses the power of 3 instead of 4. With the objective of generating efficient scheme to pick first time arrival, we explore use artificial neural network and a combination of kurtosis and skewness attributes. We use a collection of magnitude events with moment magnitude larger than 3 located close to Moluccas island, Indonesia. We collected all events information from the Indonesian Agency of Meteorology, Climatology and Geophysics. The process is started with manually pick all P wave arrivals using manual inspection. Next, we trained the artificial neural network with attributes numbers as inputs and arrival time we manually picked as the output. In total we used 100 regional events that has clear P wave phases. Then, we validated the results until reaching 0.99 accuracy. In the last step, we tested the once trained procedures on new waveforms contained events. Current result shows an average of 0.4s different between manual pick and trained picked from machine learning. The accuracy can be improved by applying a band pass 0.1-2 Hz filtering with an average of 0.2s.

An Attempt to Pick Teleseismic P Wave Arrival Using Envelope and Artificial Neural Network Algorithm

Seismic events detection and phase picking play an essential role in earthquake studies. Typical event detection is done visually or manually on recorded seismogram by choosing a series of higher amplitude signals recorded on at least 4 stations. More sophisticated methods have been used in event detection and picking with additional attributes such as Short Time Average over Long Time Average (STA/LTA). This method is based on average number sampled at multiple predefined windows. However, STA/LTA is dependent on the window size which becomes its drawback. In this study, we explore one derivative attribute, popularly known as envelope or instantaneous amplitude. It has been extensively used in seismic reflection and refraction method. In principle, this method uses the Hilbert Transform to calculate complex seismic trace and take the magnitude of complex seismic trace as envelope amplitude that can be used to analyze P wave arrival time. We employed one of the machine learning methods, Artificial Neural Network (ANN). The ANN method works by analyzing various inputs and training them to recognize patterns in P wave arrival signals. We started our study by applying envelope attribute to synthetic data with noise addition. We found that with noisy data the envelope attribute still gives a clear signal for first-time arrival. Next, we trained 300 seismograms of teleseismic events recorded on IRIS-US networks and tested our trained program on 20 seismograms as a blind test. To compare performance between the two methods, we calculated the difference between the results of automatic picking and manual picking. The final calculation shows an average deviation of 0.355 seconds. Twenty-five percent of testing data (5 samples) has a deviation above 0.5 seconds, and 75% of the remainder (15 samples) already had a deviation under 0.5 seconds. The more significant deviations of the P wave picks are likely due to noisy signals in the data set and complex arrival signals. This study shows that the combination of envelope attribute and machine learning method is promising to distinguish teleseismic P wave arrival and automatically pick them.

Research on the propagation mechanism of the arrival time error and wave velocity error under sensor array

To study the propagation mechanism of the arrival time error and wave velocity error under sensor array is an urgent problem in microseismic (MS) source location. To solve it, based on the theory of source location, the elliptic governing equation of source location is established. Combining with the hyperbolic governing equation of source location, it is revealed that the arrival time error and wave velocity error make the source “jump” on the adjacent hyperbola and ellipse. Through the numerical simulation test, the seismogenic time error law under the influence of the arrival time error and the wave velocity error is revealed. It is concluded that the location error of the source inside 1.8 times the array radius is mainly caused by the arrival time error and the wave velocity error, while the location error of the source outside 1.8 times the array radius is mainly caused by the seismogenic time error. Finally, considering the seismogenic time error, the location error law of the source under the influence of the arrival time error and velocity error is studied. The research results improve the understanding of the propagation mechanism of the arrival time error and wave velocity error in MS source location.

Defining the Coseismic Phase of the Crustal Deformation Cycle With Seismogeodesy

AbstractEarth's crustal deformation cycle is traditionally divided into coseismic, postseismic, and interseismic phases upon which transient motions from various sources may be superimposed. Here we present a new seismogeodetic methodology to define and identify the transition from the coseismic to the early postseismic phase. While this early period of postseismic deformation has not been well observed, it plays an important role in better understanding fault processes and crustal rheology because it is where the fastest evolution of fault slip occurs. Current methods often choose to rely on geodetic displacements with several hour to daily resolution to estimate static coseismic offsets. The choice of data span is often arbitrary and introduces some fraction of postseismic motion. Instead, we apply a more physics‐based approach that is applicable to interleaved regional networks of high‐rate Global Navigation Satellite System (GNSS) and seismic sensors. The start time of the coseismic phase is based on P wave arrivals and its end time on the total release of energy derived from seismic velocities integrated from strong‐motion accelerations. In the absence of physical collocations, we interpolate the coseismic time window to the GNSS stations and estimate the static offsets from the high‐rate displacements. We demonstrate our methodology by applying it to 10 earthquakes over a range of magnitudes and fault mechanisms. We observe that the presence of early postseismic motions within the widely used estimates of daily coseismic offsets can lead to an overprediction of coseismic moment and fault slip, up to several meters depending on the magnitude and mechanism of the event.

The Study of Automatic Picking of P and S Wave Arrival and Identification of Earthquake Sequence Pattern using Scalogram in Obspy (Python)

Initial identification on an earthquake record (seismogram) is something that needs to be done precisely and accurately. Moreover, the discovery of a series of unexpected successive earthquake events has caused unpreparedness for the community and related agencies in tackling these events. Determining the arrival time of the P and S waves becomes an important parameter to finding the location of the earthquake source (hypocenter) as well as further information related to the earthquake event. However, manual steps that are currently often used are considered to be less effective, because it requires a lot of time in the process. Continuous Wavelet Transform (CWT) analysis can be a solution for this problem. With further CWT analysis in the form of a scalogram, can help to determine the arrival time of P and S waves automatically (automatic picking) becomes simpler. In addition, further CWT analysis can also be utilized to help identify the sequence of earthquake events (foreshock, mainshock, aftershock) through the resulting scalogram pattern.

Pulse Arrival Time - A Sensitive Vital Parameter for the Detection of Mental Stress

Abstract Mental stress triggers positive inotropic and chronotropic effects as well as peripheral vasoconstriction. This alters the pulse arrival time (PAT), the duration between electrical excitation of the ventricles and arrival of the pulse wave in the periphery. We conducted a study to examine PAT during five rest blocks and under mental stress utilizing the Mannheim Multicomponent Stress Test. Electrocardiograms as well as finger and earlobe photoplethysmograms were recorded. PAT was calculated for over 135,000 heartbeats from 42 healthy volunteers as the time duration between the R peak in the electrocardiogram and the following pulse onset in the respective photoplethysmogram. To identify the effect of mental stress, block-wise PAT means were statistically analyzed with repeated measures ANOVA. The analyses showed significant differences between the block means for both PAT measures (p < 0.001). Post-hoc tests revealed significantly reduced PAT during the stress block compared to all rest blocks for both PAT measures (p < 0.001). We found no significant differences between the rest blocks. Our results support that PAT is a sensitive vital parameter for the detection of mental stress in healthy volunteers. This holds true for both measurement positions, the finger and the earlobe.