Central Nervous System Processing of Floral Odor and Mother's Milk Odor in Infants.

Newborns have a functioning sense of smell at birth, which appears to be highly significant for feeding and bonding. Still, little is known about the cerebral odor processing in this age group. Studies of olfactory function relied mostly on behavioral, autonomic, and facial responses of infants. The aim of the present study was to investigate central odor processing in infants focusing on electroencephalography (EEG)-derived responses to biologically significant odors, namely a food and a non-food odor. A total of 21 term-born, healthy infants participated (11 boys and 10 girls; age range 2-9 months, mean 5.3 ± 2.2 months). Odor stimuli were presented using a computer-controlled olfactometer. Breast milk was used as food odor. Farnesol was presented as a non-food odor. In addition, odorless air was used as a control stimulus. Each stimulus was presented 30 times for 1 s with an interstimulus interval of 20 s. EEG was recorded from 9 electrodes and analyzed in the frequency domain. EEG amplitudes in the delta frequency band differed significantly after presentation of food (breast milk) odor in comparison to the control condition and the non-food odor (farnesol). These changes were observed at the frontal recording positions. The present study indicates that central odor processing differs between a food and a non-food odor in infants. Results are interpreted in terms of focused attention towards a physiologically relevant odor (breast milk), suggesting that olfactory stimuli are of specific significance in this age group.

Capacitive Heart-Rate Sensing on Touch Screen Panel with Laterally Interspaced Electrodes.

It is demonstrated that the heart-rate can be sensed capacitively on a touch screen panel (TSP) together with touch signals. The existing heart-rate sensing systems measure blood pulses by tracing the amount of light reflected from blood vessels during a number of cardiac cycles. This type of sensing system requires a considerable amount of power and space to be implemented in multi-functional mobile devices such as smart phones. It is found that the variation of the effective dielectric constant of finger stemming from the difference of systolic and diastolic blood flows can be measured with laterally interspaced top electrodes of TSP. The spacing between a pair of non-adjacent top electrodes turns out to be wide enough to distinguish heart-rate signals from noises. With the aid of fast Fourier transform, the heart-rate can be extracted reliably, which matches with the one obtained by actually counting heart beats on the wrist.

Diurnal variations and pulpal status: is there a need for FFT besides LDF?

The aim of this article was to investigate the use of laser Doppler flowmetry (LDF) combined with a fast Fourier transformation (FFT). LDF data in relation to three different scenarios were evaluated: (a) LDF records of a right central upper incisor of one patient were used for FFT analysis. These records were obtained by means of 30 pre-manufactured splints, handled by dentists without any experience in LDF recording. (b) Diurnal variations in one patient were analysed with LDF and FFT using 11 splints by one and same experienced investigator at four specific moments of the day. (c) Pulpal status was analysed using 17 splints. Eleven for a patient, standing as case model and six splints for six other patients. In this specific group, each patient had one vital and one non-vital central maxillary incisor and was analysed separately by LDF and FFT. The data of assessment (b) showed diurnal variations on LDF values of almost 80%, indicating that LDF registration is best performed in the same time period of the day. Data verification with FFT confirmed the findings without FFT of assessment (a) and (b). In assessment, (c) FFT demonstrated a clear distinction between a vital and a non-vital pulp for those cases with one vital tooth and one root canal treated tooth. In those cases with one vital incisor and the other traumatised, FFT was undeterminated. Considered that FFT was obtained after LDF recording and remained undeterminated for a decision in cases with decreasing pulpal blood flow in time, the added value of FFT in pulpal traumatology was minimal.

[Analysis of blood flow energy characteristics of pulsatile and non-pulsatile flow during extracorporeal circulation].

Objective: To analyze the magnitude of blood flow energy and characteristics of frequency domain between pulsatile flow and nonpulsatile flow during cardiopulmonary bypass and physiological flow. Methods: From January 2017 to December 2017, 60 cases of patients with mitral valve disease scheduled for mitral valve replacement or repair at Department of Cardiasurgery, Shanghai Chest Hospital, Shanghai Jiaotong University were randomly divided into 2 groups: pulsatile perfusion (PP) and non-pulsatile perfusion (NP). The magnitude of blood flow energy during pulsatile and non-pulsatile was calculated using energy equivalent pressure (EEP) and surplus hemodynamic energy (SHE) while fast Fourier transformation (FFT) was used to perform power spectral density analysis to identify the frequency domain characteristics between artificial and physiological flow (prior to CPB). The data was analyzed by analysis of variance or t test. Results: At the different time-points after occlusion, the EEP and SHE in PP group were respectively 1.52 to 1.62 and 2.03 to 2.22 times higher than NP at the distal of artery filter. The power density analysis revealed that the blood flow energy of physiological pulsatile flow patterns was within 40 Hz and the ratio of low frequency energy was more than 90% before clamp. The spectral energy ratio of low frequency decreased in both group compared with physiological flow was more obvious in NP group at the radial artery. The ratio of estimated value of power density of PP and NP groups analysis showed the corresponding 0 to 5 Hz, 0 to 10 Hz, 0 to 40 Hz frequency range values measured at the radial artery and filter were 9.51, 4.68, 3.59 and 3.87, 2.69, 2.38 respectively after occulusion. In each frequency range, the energy of PP is higher than that of NP, and the lower the frequency, the greater the difference. The ratio of estimated value of power density of PP and NP groups for the three frequencies measured at the radial artery before and after occlusion were 2.86, 2.83, 2.75 and 14.70, 12.74, 9.85 respectively, and decreased significantly in NP group and low frequency energy. The ratio of estimated value of power density of PP and NP groups under the three different frequencies measured at the radial artery and filter were 26.35, 33.15, 37.36 and 37.41, 54.18, 56.64 respectively, in the conduction process from filter to radial artery, energy exhaustion is significant, especially in group NP. Conclusions: The PP provides significantly more energy than the NP whereby the PP is closer to the physiological pulsatile on the energy frequency structure and attenuation characteristics, with mainly low frequency energy of 0 to 5 Hz and weak energy attenuation. The energy loss of non-pulsatile flow is obvious, especially the low frequency energy.

Microelectrode array-induced neuronal alignment directs neurite outgrowth: analysis using a fast Fourier transform (FFT).

Many studies have shown that the topography of the substrate on which neurons are cultured can promote neuronal adhesion and guide neurite outgrowth in the same direction as the underlying topography. To investigate this effect, isotropic substrate-complementary metal-oxide-semiconductor (CMOS) chips were used as one example of microelectrode arrays (MEAs) for directing neurite growth of spiral ganglion neurons. Neurons were isolated from 5 to 7-day-old rat pups, cultured 1 day in vitro (DIV) and 4 DIV, and then fixed with 4% paraformaldehyde. For analysis of neurite alignment and orientation, fast Fourier transformation (FFT) was used. Results revealed that on the micro-patterned surface of a CMOS chip, neurons orient their neurites along three directional axes at 30, 90, and 150° and that neurites aligned in straight lines between adjacent pillars and mostly followed a single direction while occasionally branching perpendicularly. We conclude that the CMOS substrate guides neurites towards electrodes by means of their structured pillar organization and can produce electrical stimulation of aligned neurons as well as monitoring their neural activities once neurites are in the vicinity of electrodes. These findings are of particular interest for neural tissue engineering with the ultimate goal of developing a new generation of MEA essential for improved electrical stimulation of auditory neurons.

Light Emitting Marker for Robust Vision-Based On-The-Spot Bacterial Growth Detection.

Simple methods using the striped pattern paper marker and FFT (fast Fourier transformation) have been proposed as alternatives to measuring the optical density for determining the level of bacterial growth. The marker-based method can be easily automated, but due to image-processing-base of the method, the presence of light or the color of the culture broth can disturb the detection process. This paper proposes a modified version of marker-FFT-based growth detection that uses a light emitting diode (LED) array as a marker. Since the marker itself can emit the light, the measurements can be performed even when there is no light source or the bacteria are cultured in a large volume of darkly colored broth. In addition, an LED marker can function as a region of interest (ROI) indicator in the image. We expect that the proposed LED-based marker system will allow more robust growth detection compared to conventional methods.

Vision Marker-Based In Situ Examination of Bacterial Growth in Liquid Culture Media.

The detection of bacterial growth in liquid media is an essential process in determining antibiotic susceptibility or the level of bacterial presence for clinical or research purposes. We have developed a system, which enables simplified and automated detection using a camera and a striped pattern marker. The quantification of bacterial growth is possible as the bacterial growth in the culturing vessel blurs the marker image, which is placed on the back of the vessel, and the blurring results in a decrease in the high-frequency spectrum region of the marker image. The experiment results show that the FFT (fast Fourier transform)-based growth detection method is robust to the variations in the type of bacterial carrier and vessels ranging from the culture tubes to the microfluidic devices. Moreover, the automated incubator and image acquisition system are developed to be used as a comprehensive in situ detection system. We expect that this result can be applied in the automation of biological experiments, such as the Antibiotics Susceptibility Test or toxicity measurement. Furthermore, the simple framework of the proposed growth measurement method may be further utilized as an effective and convenient method for building point-of-care devices for developing countries.

Disrupted cross-laminar cortical processing in ß amyloid pathology precedes cell death.

Disruption of neuronal networks in the Alzheimer-afflicted brain is increasingly recognized as a key correlate of cognitive and memory decline in Alzheimer patients. We hypothesized that functional synaptic disconnections within cortical columnar microcircuits by pathological ß-amyloid accumulation, rather than cell death, initially causes the cognitive impairments. During development of cortical ß-amyloidosis with still few plaques in the transgenic 5xFAD mouse model single cell resolution mapping of neuronal thallium uptake revealed that electrical activity of pyramidal cells breaks down throughout infragranular cortical layer V long before cell death occurs. Treatment of 5xFAD mice with the glutaminyl cyclase inhibitor, PQ 529, partially prevented the decline of pyramidal cell activity, indicating pyroglutamate-modified forms, potentially mixed oligomers of Aß are contributing to neuronal impairment. Laminar investigation of cortical circuit dysfunction with current source density analysis identified an early loss of excitatory synaptic input in infragranular layers, linked to pathological recurrent activations in supragranular layers. This specific disruption of normal cross-laminar cortical processing coincided with a decline of contextual fear learning.

Comparing region of interest selection and whole-field analysis for measurement of ciliary beat frequency in high-speed video analysis.

BACKGROUND: Ciliary beat frequency (CBF) is crucial in mucociliary clearance. High-speed video analysis (HSVA) is commonly used to measure CBF but lacks standardization. We compared visual observation and computer-assisted calculation using fast Fourier transformation (FFT) in freshly collected bronchial ciliary epithelial cells and cultured cells. METHODS: Bronchial epithelial cells were obtained from 12 patients who required bronchoscopic examination. Eighty-five videos of ciliary movement of freshly collected and cultured cells were recorded and used to calculate CBF using manual observation, region of interest (ROI) selection, and whole-field analysis. RESULTS: CBF measured by the ROI selection method strongly correlated with that measured using manual observation, especially in freshly collected cells. However, 27.8% of the manual observation method values were doubled in the ROI selection method, probably because a round trip of cilia was calculated as two cycles and needed to be corrected to 1/2 value. Upon increasing the number of ROIs, the results of the ROI selection method came closer to that of WFA. CONCLUSIONS: Computer-assisted calculation using FFT can aid in measuring CBF; however, current methods require visual confirmation. Further automated evaluation techniques are needed to establish more standardized and generalized CBF measurement methods using HSVA.

An epilepsy classification based on FFT and fully convolutional neural network nested LSTM.

Background and objective: Epilepsy, which is associated with neuronal damage and functional decline, typically presents patients with numerous challenges in their daily lives. An early diagnosis plays a crucial role in managing the condition and alleviating the patients' suffering. Electroencephalogram (EEG)-based approaches are commonly employed for diagnosing epilepsy due to their effectiveness and non-invasiveness. In this study, a classification method is proposed that use fast Fourier Transform (FFT) extraction in conjunction with convolutional neural networks (CNN) and long short-term memory (LSTM) models. Methods: Most methods use traditional frameworks to classify epilepsy, we propose a new approach to this problem by extracting features from the source data and then feeding them into a network for training and recognition. It preprocesses the source data into training and validation data and then uses CNN and LSTM to classify the style of the data. Results: Upon analyzing a public test dataset, the top-performing features in the fully CNN nested LSTM model for epilepsy classification are FFT features among three types of features. Notably, all conducted experiments yielded high accuracy rates, with values exceeding 96% for accuracy, 93% for sensitivity, and 96% for specificity. These results are further benchmarked against current methodologies, showcasing consistent and robust performance across all trials. Our approach consistently achieves an accuracy rate surpassing 97.00%, with values ranging from 97.95 to 99.83% in individual experiments. Particularly noteworthy is the superior accuracy of our method in the AB versus (vs.) CDE comparison, registering at 99.06%. Conclusion: Our method exhibits precise classification abilities distinguishing between epileptic and non-epileptic individuals, irrespective of whether the participant's eyes are closed or open. Furthermore, our technique shows remarkable performance in effectively categorizing epilepsy type, distinguishing between epileptic ictal and interictal states versus non-epileptic conditions. An inherent advantage of our automated classification approach is its capability to disregard EEG data acquired during states of eye closure or eye-opening. Such innovation holds promise for real-world applications, potentially aiding medical professionals in diagnosing epilepsy more efficiently.

Role of triggering pulmonary veins in the maintenance of sustained paroxysmal atrial fibrillation.

BACKGROUND: Triggers from thoracic veins have been implicated not only in the initiation, but also in the perpetuation of paroxysmal atrial fibrillation (PAF). To investigate their role we studied the distribution and stability of dominant frequencies (DFs) during PAF and the response to isolation of the triggering pulmonary vein (PV). METHODS AND RESULTS: Triggering structures inducing PAF were identified during isoproterenol challenge in 26 patients (15 males, 55 ± 8.5 years). During sustained PAF, sequential recordings were made with a decapolar circular mapping catheter from each PV and the left atrial posterior wall (LAPW), together with coronary sinus (CS) and right atrium (RA) recordings. DF was determined using fast Fourier transformation. Recordings were repeated after ≥15 minutes of PAF. Radiofrequency ablation was directed first at the triggering PVs. PAF initiated from the PVs in 24 patients and from RA in two. There was a significant frequency gradient from the triggering structure to the PVs, CS, LAPW, and RA (P < 0.0001). During the second recording, DF decreased at all sites (P < 0.02), but the frequency gradient remained unchanged. Despite isolation of the triggering PV, PAF continued in 53% of patients, although DF measured in the CS was lower. AF termination occurred with contralateral PV isolation in half of the remaining patients and further AF slowing was noted in the rest. CONCLUSIONS: Triggering structures harbor the fastest activity during sustained PAF pointing to their leading role in arrhythmia perpetuation. However, nontriggering PVs also seem to contribute to PAF maintenance.

Extracting epileptic features in EEGs using a dual-tree complex wavelet transform coupled with a classification algorithm.

The detection of epileptic seizures from electroencephalogram (EEG) signals is traditionally performed by clinical experts through visual inspection. It is a long process, is error prone, and requires a highly trained expert. In this research, a new method is presented for seizure classification for EEG signals using a dual-tree complex wavelet transform (DT-CWT) and fast Fourier transform (FFT) coupled with a least square support vector machine (LS-SVM) classifier. In this method, each EEG signal is divided into four segments. Each segment is further split into smaller sub-segments. The DT-CWT is applied to decompose each sub-segment into detailed and approximation coefficients (real and imaginary parts). The obtained coefficients by the DT-CWT at each decomposition level are passed through an FFT to identify the relevant frequency bands. Finally, a set of effective features are extracted from the sub-segments, and are then forwarded to the LS-SVM classifier to classify epileptic EEGs. In this paper, two epileptic EEG databases from Bonn and Bern Universities are used to evaluate the extracted features using the proposed method. The experimental results demonstrate that the method obtained an average accuracy of 97.7% and 96.8% for the Bonn and Bern databases, respectively. The results prove that the proposed DT-CWT and FFT based features extraction is an effective way to extract discriminative information from brain signals. The obtained results are also compared to those by k-means and Naïve Bayes classifiers as well as with the results from the previous methods reported for classifying epileptic seizures and identifying the focal and non-focal EEG signals. The obtained results show that the proposed method outperforms the others and it is effective in detecting epileptic seziures in EEG signals. The technique can be adopted to aid neurologists to better diagnose neurological disorders and for an early seizure warning system.

EMG Signal Processing for the Study of Localized Muscle Fatigue-Pilot Study to Explore the Applicability of a Novel Method.

This pilot study aimed to explore a method for characterization of the electromyogram frequency spectrum during a sustained exertion task, performed by the upper limb. Methods: Nine participants underwent an isometric localized muscle fatigue protocol on an isokinetic dynamometer until exhaustion, while monitored with surface electromyography (sEMG) of the shoulder's external rotators. Firstly, three methods of signal energy analysis based on primer frequency contributors were compared to the energy of the entire spectrum. Secondly, the chosen method of analysis was used to characterize the signal energy at beginning (T1), in the middle (T2) and at the end (T3) of the fatigue protocol and compared to the torque output and the shift in the median frequencies during the trial. Results: There were statistically significant differences between T1 and T3 for signal energy (p < 0.007) and for central frequency of the interval (p = 0.003). Moreover, the isometric peak torque was also different between T1 and T3 (p < 0.001). Overall, there were no differences between the signal energy enclosed in the 40 primer frequency contributors and the analysis of the full spectrum energy; consequently, it was the method of choice. The reported fatigue and the decrease in the produced muscle torque was consistent with fatigue-induced alterations in the electromyogram frequency spectrum. In conclusion, the developed protocol has potential to be considered as an easy-to-use method for EMG-based analysis of isometric muscle exertion until fatigue. Thus, the novelty of the proposed method is to explore, in muscle fatigue, the use of only the main contributors in the frequency domain of the EMG spectrum, avoiding surplus information, that may not represent muscle functioning. However, further studies are needed to investigate the stability of the present findings in a more comprehensive sample.

Spectral analysis of body movement during deep brain stimulation in Parkinson's disease.

BACKGROUND: The characteristics of Parkinson's disease (PD) include postural instability and resting tremor. However, reductions of tremor amplitude do not always improve postural stability. RESEARCH QUESTION: What is the effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) on spectral analysis of body movement in patients with PD when tested without anti-PD medication? The effect of visual cues was also studied. METHODS: Ten patients with PD (mean age 64.3 years, range 59-69 years) and 17 control participants (mean age 71.2 years, range 65-79 years) were recruited. Spectral power following a period of quiet stance (35 s) was analysed in three different spectral power bands (0-4 Hz, 4-7 Hz and 7-25 Hz). Motion markers were secured to the head, shoulder, hip, and knee, which recorded movements in two directions, the anteroposterior and lateral. RESULTS: DBS STN significantly changed the spectral distribution pattern across the body in the anteroposterior (p = 0.029) and lateral directions (p ≤ 0.003). DBS predominantly reduced spectral power at the head (p ≤ 0.037) and shoulder (p ≤ 0.031) in the lateral direction. The spectral power of the lower and upper body in patients with PD, with DBS ON, were more similar to the control group, than to DBS OFF. Visual cues mainly reduced spectral power in the anteroposterior direction at the shoulder (p ≤ 0.041) in controls and in patients with PD with DBS ON. SIGNIFICANCE: There is an altered postural strategy in patients with PD with DBS ON as shown by an altered spectral power distribution pattern across body segments and a reduction of spectral power in the lateral direction at the head and shoulder. A reduction of spectral power in controls and in patients with PD with DBS ON suggests that visual cues are able to reduce spectral power to some extent, but not with DBS OFF where postural sway and power are larger.

Algorithm for frequency capture and rectification in a low-orbit satellite IoT communication network.

In satellite communication systems, due to relative motion between satellites and that between satellites and the ground, the resulting Doppler frequency offset adversely affects communication synchronization. In this research, Doppler frequency offset compensation and phase offset compensation method eliminate the influence of the Doppler effect on synchronization. The proposed algorithm divides frequency estimate into two steps, coarse and precision. Finally, the corresponding frequency offset and phase offset compensation are performed. The simulation results show that the demodulated output results after frequency offset and phase offset compensation agree well with the original modulation data, indicating that the algorithm is valid and accurate.

A Tragic Case of Wearable Cardioverter-Defibrillator Failure.

The American College of Cardiology/American Heart Association guidelines recommend a wearable cardioverter defibrillator (WCD) for certain conditions or scenarios. WCD is felt to provide adequate protection against ventricular arrhythmias. This case highlights failure of a WCD to detect and deliver life-saving therapy and the need for improved detection algorithms. (Level of Difficulty: Beginner.).

Determination of diclofenac on a dysprosium nanowire- modified carbon paste electrode accomplished in a flow injection system by advanced filtering.

A new detection technique called Fast Fourier Transform Square-Wave Voltammetry (FFT SWV) is based on measurements of electrode admittance as a function of potential. The response of the detector (microelectrode), which is generated by a redox processes, is fast, which makes the method suitable for most applications involving flowing electrolytes. The carbon paste electrode was modified by nanostructures to improve sensitivity. Synthesized dysprosium nanowires provide a more effective nanotube-like surface [1-4] so they are good candidates for use as a modifier for electrochemical reactions. The redox properties of diclofenac were used for its determination in human serum and urine samples. The support electrolyte that provided a more defined and intense peak current for diclofenac determination was a 0.05 mol L(-1) acetate buffer pH = 4.0. The drug presented an irreversible oxidation peak at 850 mV vs. Ag/AgCl on a modified nanowire carbon paste electrode which produced high current and reduced the oxidation potential by about 100 mV. Furthermore, the signal-to-noise ratio was significantly increased by application of a discrete Fast Fourier Transform (FFT) method, background subtraction and two-dimensional integration of the electrode response over a selected potential range and time window. To obtain the much sensivity the effective parameters such as frequency, amplitude and pH was optimized. As a result, C(DL) of 2.0 × 10(-9) M and an LOQ of 5.0 × 10(-9) M were found for the determination for diclofenac. A good recovery was obtained for assay spiked urine samples and a good quantification of diclofenac was achieved in a commercial formulation.

Is 25Hz enough to accurately measure a dynamic change in the ocular accommodation?

BACKGROUND: Accommodation is often recorded at a low sampling rate using devices such as autorefractors that are designed to measure the static refractive error. It is therefore important to determine if that resolution is sufficient to accurately measure the dynamic properties of accommodation. The current study provides both theoretical and empirical evidence on the ideal sampling rate necessary to measure a dynamic response. METHODS: Accommodative and disaccommodative step stimuli ranging from 1-3D (1D steps) were presented using a Badal optical system. Responses from 12 children (8-13 years) and 6 adults (20-35 years) were recorded using a dynamic photorefractor (DPR). Fast Fourier transformation was applied to the unsmoothed dynamic responses including position, velocity and acceleration. Also, velocity and acceleration main sequence (MS) characteristics were compared between three photorefractor conditions on 3 subjects. RESULTS: The Nyquist sampling limit necessary to accurately estimate position, velocity and acceleration was at least 5, 10 and 70Hz, respectively. Peak velocity and acceleration were significantly underestimated at a lower rate (p<0.5). However, the slope of MS remained invariant with sampling rate (p>0.5). CONCLUSION: Contrary to the previous findings, a dynamic accommodative response exhibited frequencies larger than 10Hz. Stimulus direction and amplitude had no influence on the frequencies present in the dynamic response. Peak velocity and acceleration can be significantly underestimated when sampled at a lower rate. Taken as a whole, low sampling rate instruments can accurately estimate static accommodation, however, caution needs to be exercised when using them for dynamic accommodation.

Coulometric differential FFT admittance voltammetry determination of Amlodipine in pharmaceutical formulation by nano-composite electrode.

An electrochemical detection technique based on combination of was coulometric differential fast Fourier transformation admittance voltammetry (CDFFTAV) and nano-composite film modified glassy carbon electrode was successfully applied for sensitive determination of Amlodipine. The nano-composite film was made by a mixture of ionic liquid, 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF4), multiwall carbon nanotube and Au nanoparticles as electrochemical mediators. Studies reveal that the irreversible oxidation of Amlodipine was highly facile on the electrode surface. The electrochemical response was established on calculation of the charge under the admittance peak, which was obtained by discrete integration of the admittance response in a selected potential range, obtained in a flow injection analysis. Once established the best operative optimum conditions, the resulting nano-composite film electrode showed a catalytic effect on the oxidation of the analyte. The response is linear in the Amlodipine concentration range of 1.0 × 10(-9) to 2.0 × 10(-7)M with a detection limit of 1.25 × 10(-10)M. Moreover, the proposed technique exhibited high sensitivity, fast response time (less than 6s) and long-term stability and reproducibility around 96%, and it was successfully used to the determination of Amlodipine content in the pharmaceutical formulation.

Friction behavior of a microstructured polymer surface inspired by snake skin.

The aim of this study was to understand the influence of microstructures found on ventral scales of the biological model, Lampropeltis getula californiae, the California King Snake, on the friction behavior. For this purpose, we compared snake-inspired anisotropic microstructured surfaces to other microstructured surfaces with isotropic and anisotropic geometry. To exclude that the friction measurements were influenced by physico-chemical variations, all friction measurements were performed on the same epoxy polymer. For frictional measurements a microtribometer was used. Original data were processed by fast Fourier transformation (FFT) with a zero frequency related to the average friction and other peaks resulting from periodic stick-slip behavior. The data showed that the specific ventral surface ornamentation of snakes does not only reduce the frictional coefficient and generate anisotropic frictional properties, but also reduces stick-slip vibrations during sliding, which might be an adaptation to reduce wear. Based on this extensive comparative study of different microstructured polymer samples, it was experimentally demonstrated that the friction-induced stick-slip behavior does not solely depend on the frictional coefficient of the contact pair.