Fast Beat Research Articles

Auditory Rhythm Encoding during the Last Trimester of Human Gestation: From Tracking the Basic Beat to Tracking Hierarchical Nested Temporal Structures.

Rhythm perception and synchronization to periodicity hold fundamental neurodevelopmental importance for language acquisition, musical behavior, and social communication. Rhythm is omnipresent in the fetal auditory world and newborns demonstrate sensitivity to auditory rhythmic cues. During the last trimester of gestation, the brain begins to respond to auditory stimulation and to code the auditory environment. When and how during this period do the neural capacities for rhythm processing develop? We conducted a cross-sectional study in 46 neonates (24 male) born between 27 and 35 weeks gestational age (wGA), measuring their neural responses to auditory rhythms with high-density electroencephalography during sleep. We developed measures to evaluate neural synchronization to nested rhythmic periodicities, including the fast isochronous beat and slower metrical (beat grouping) structures. We show that neural synchronization to beat and meter becomes stronger with increasing GA, converging on small phase differences between stimulus and neural responses near term, similar to those observed in adults. Dividing the cohort into subpopulations born before and after 33 wGA revealed that both younger and older groups showed neural synchronization to the fast periodicity related to the isochronous beat, whereas only the older group showed significant neural synchronization to the slower meter frequencies related to beat groupings, suggesting that encoding of nested periodicities arrives during late gestation. Together, our results shed light on the rapid evolution of neural coding of external hierarchical auditory rhythms during the third trimester of gestation, starting from the age when the thalamocortical axons establish the first synapses with the cortical plate.

Thrills of Twilight: Flappers in Edith Wharton’s Twilight Sleep (1927)

Abstract This article explores the tumultuous 1920s, a decade of vibrant urban culture that witnessed the birth of a new female figure, the flapper. The young flappers, who were products of fin-de-siècle urban modernity, were caught in-between conventional backgrounds and eccentric self-definitions, in the liminal twilight zone of their indeterminate desires. In Edith Wharton’s Twilight Sleep (1927) the flappers Nona Manford and Lita Cliffe Wyant are tied to the bodily gratifications of dancing, sports, alcohol, and sex, a cause for cultural anxiety, particularly when nonheteronormative. The homoerotic relationship between Nona and Lita becomes exposed through Nona’s gaze resting on Lita and her sensual body. Wharton’s flappers immerse themselves in sensory experiences that just like those of others are “permeated with social values,” according to David Howes. The way Nona and Lita engage their senses and explore sensations reflect their social status as their lives move on, extravagantly, with the fast beat of jazz, which in Nona’s case is later contrasted by immobility as she lies in her bed physically and emotionally wounded. In the end, Nona and Lita are pressured toward conventionality, but before then, they are most alive when engaged in the thrills of twilight that send tremors through their bodies.

Long Term Health Problems and Associated Factors among COVID-19 Recovered Patients

A cross-sectional, descriptive study was conducted among 181 individuals recovered from COVID-19 infection and had been missing infection (negative rt-PCR test) or signs-symptoms for minimum three months. The study aims determine newly developed health problems in patients, which was conducted at Post-COVID Unit of Anwer Khan Modern Medical College Hospital, Dhaka, Bangladesh, between July 2021 and June 2022. Through convenient sampling, data were collected by face-to-face interview and history of signs/ symptoms during the infection were recorded from reviewing prescription and interview as well by using a semi-structured questionnaire. The mean age of the participants was 39.56±6.92 years and male-female ratio was 1.45:1. The mean monthly family income of the participants was 36,022.09±4130.56 BDT which represents lower middle to middle class family in terms of Bangladesh context. During COVID-19 infection most of the (97%) respondents had fever, and 87%, 79% of the patients had sore throat and cough respectively as common symptoms; in addition, more than one-third (34%) had diarrhea. Several constitutional symptoms also recorded during their course of illness like headache (74%) and malaise (54%). More than one-third (34%) of the respondents required admission in hospital. During the course of infection, 41%, 26% and 31% participants were suffered from mild, moderate and severe form of COVID-19 illness. Most of the respondents developed long term health problems following COVID infection and post-viral fatigue was the most prevalent (85%) among the post COVID individuals and this long-term health problem-post viral fatigue was found to be associated with monthly income and it was statistically significant (p<0.05). Others long term health problems including shortness of breath (74%), loss of memory (38%), difficulty in concentration (41%), loss of hair (30%), fast beating or pounding heart (33%) were also noticed. Insomnia (56%), persistent cough (35%), loss of taste (32%) and change of bowel habit (28%) were other health problems revealed in this study. Association between loss of memory and gender (p<0.0001), diabetes mellitus and severity of COVID-19 (p<0.05), sore throat, cough and severity of COVID-19 (P<0.05) were also found significant. diabetes mellitus (35%), hypertension (34%) and bronchial asthma (24%) were observed to be most common comorbidities. Shortness of breath – one of the post-COVID consequence was found significantly associated with diabetes mellitus and bronchial asthma (p<0.05). Our study found that persistence of various signs and symptoms from COVID-19 infection and newly yield complications in individual who recovered from COVID-19 infection are collectively comprise long term health problems of post-COVID patients. This long-term health problem of post-COVID people is a major public health concern. Fatigue, dyspnea, difficulty to concentrate, memory loss, persistent cough, fast beating or pounding heart, loss of smell, loss of taste, insomnia are the most common long term health problems in COVID-19 recovered people. Long-term follow up may be recommended to understand future consequences of COVID-19 patients and well-being for the post-COVID people. CBMJ 2024 July: vol. 13 no. 02 P: 158-168

Disturbance-rejection position tracking control of industrial robots via a discrete-time super-twisting observer–based fast terminal sliding mode approach

Facing the system uncertainties caused by unmodeled dynamics and unpredictable external disturbances, the robot position control for meeting the high-performance control requirements on higher accuracy and faster beat is vital for many industrial applications, such as welding and laser cutting tasks. This work aims to cope with the problem of precise and fast position tracking for robot manipulators with an effective and safe control scheme. Specifically, a discrete-time super-twisting observer (STO) is integrated into the scheme to estimate the uncertain dynamics (e.g. unmodeled dynamics and external disturbances) in the feedforward compensation part of the dynamics. Subsequently, a discrete-time fast terminal sliding mode controller (FTSMC) dominates the robot control to guarantee fast convergence of the position tracking error. The significant improvement of the proposed method with respect to other discrete-time sliding mode control approaches lies in that it is capable of alleviating the chattering-like problem, achieving a fast convergence and improving the robustness of sliding mode control against uncertain dynamics. To illustrate the effectiveness of the presented control scheme, several experiments on a six degrees of freedom (6DoF) robot manipulator are provided.

Timbral effects on consonance disentangle psychoacoustic mechanisms and suggest perceptual origins for musical scales

The phenomenon of musical consonance is an essential feature in diverse musical styles. The traditional belief, supported by centuries of Western music theory and psychological studies, is that consonance derives from simple (harmonic) frequency ratios between tones and is insensitive to timbre. Here we show through five large-scale behavioral studies, comprising 235,440 human judgments from US and South Korean populations, that harmonic consonance preferences can be reshaped by timbral manipulations, even as far as to induce preferences for inharmonic intervals. We show how such effects may suggest perceptual origins for diverse scale systems ranging from the gamelan’s slendro scale to the tuning of Western mean-tone and equal-tempered scales. Through computational modeling we show that these timbral manipulations dissociate competing psychoacoustic mechanisms underlying consonance, and we derive an updated computational model combining liking of harmonicity, disliking of fast beats (roughness), and liking of slow beats. Altogether, this work showcases how large-scale behavioral experiments can inform classical questions in auditory perception.

Colloid-like tools fast beat viral bio-colloids: Micron-surface enrichment and in-situ inactivation induced by interface-decorated microbubbles

With ever-increasing occurrence of global epidemics originating from viral pathogens, the as-generated viral pollution in waters needs to be efficiently treated with robust technology. This study employed the surface- and core-functionalized colloidal microbubbles (O3_CMBs) to simultaneously capture and inactive the viral bio-colloids from waters. The results denote that more than 3.00-lg removal of the model viruses was reached in 3 min or even shorter time. The Al(III)-coagulant modifier worked as “tentacles” on the bubble surface and confined the efficient virion capture on the gas–liquid interface, hence, the O3_CMB treatment could be different from the commonly-known microflocculation of colloids in the traditional ozone-involved coagulation process. Ozone encapsulation tests combined with continuous flow chemiluminescence online analysis further demonstrate that O3_CMBs performed outstandingly in holding up ozone in the liquid matrix and could continuously generate reactive oxygen species (i.e., O3, O3•-, O2•- and •OH) within the contact time between O3_CMBs and virions. The integrated capture, inactivation and separation process retained steady performance in a wide pH range and at extremely high salinity (i.e., 35 ‰) thanks to the bi-functionalization and mass transfer of the microbubble system. The protein-like and humic acid-like natural dissolved organic matter was found to be removed along with viral bio-colloids though the co-existing organic matter interacted and competed with viruses for O3_CMBs. The present study suggested to fast beat the viral bio-colloid pollutants with the smartly-designed colloid-like microbubbles, which could be a promising strategy in response to the severe water pollution accompanied with outbreak emergency.

Music influences performance without increasing perceived exertion during high-intensity rowing intervals: a cross-over design study.

This study assessed how exposure to slow (SBM) versus fast beat music (FBM) during high-intensity rowing intervals affects performance, heart rate (HR), lactate levels, relative perceived exertion (RPE), and recovery. The A/B crossover design involved 21 participants performing 5 × 500 m rowing intervals under two conditions: FBM and SBM. Primary endpoint was the difference in total rowing time. Secondary endpoints included average HR, average RPE as well as rowing interval times, RPE, and HR per interval. For exploratory purpose, HR and lactate drop during the initial 5 min post completion was analyzed. Listening to FBM resulted in significantly shorter total rowing times (p = 0.009, rB = 0.59), especially during the 1st interval. The 1st interval was also significantly faster than intervals 2-5 (p < 0.001), with the greatest performance drop between the 1st and 2nd interval during FBM. Average HR was significantly lower when listening to SBM (p = 0.03, rB = 0.48), while average RPE showed no significant difference (p = 0.47, rB = 0.02). Lactate values after interval 5 were significantly lower in SBM (p = 0.05, rB = 0.41), but no significant difference was found for lactate drop (p = 0.21, rB = 0.21). However, participants exhibited a higher HR drop rate with SBM (p = 0.05, rB = 0.42). FBM improved performance without increasing RPE, while SBM proved superior for recovery. Systematic customization of music based on intended training stimuli holds broad potential for the competitive sports, fitness, and health sector.

Jamet Stereotyping in Jedag-Jedug Music: An Analysis of Jedag-Jedug Music Stereotype

Several music genres have stereotypes from the society, especially music that comes from low culture. One of the types of music that is stereotyped is jedag-jedug music, a music that is identical with fast beats and specific video editing. This type of music is widely known due to the influence of the TikTok application, which is a social media platform that offers audio-visual content. Jedag-Jedug music is often stereotyped as jamet music and also considered as tacky or alay. This research aims to find out how jamet stereotypes in Jedag-Jedug music can change and become a popular trend on social media. The approach used in this research is a qualitative approach using in-depth interviews with participants. The criteria for participants were participants aged 18 years and over and who had listened to jedag-jedug music with various economic and educational backgrounds. Primary data in this research are interview transcripts and secondary data used are journal articles, books and other supporting sources. To analyze the data, researchers used Dual-Process by Shelly Chaiken. There are three aspects that form a stereotype which are cognitive, affective, and behavioral aspects that will be used to see how stereotypes are changed in the jedag-jedug music. The result found in this study was that participants experienced a change in their views towards the stereotypes that exist in jedag-jedug music. The shifting of the stereotypes occurred because of the popularization of jedag-jedug music in social media which influence the participants’ cognitive, affective, and behavior.

High-Speed and High-Precision Online Measurement Technology for Engine Connecting Rod Weight and Barycenter

With the rapid advancement of manufacturing science and technology, the associated measurement technology has also been transformed. Traditional manual and single-instrument detection modes are unable to meet the requirements of fast beat, high precision, and online measurement in intelligent manufacturing. As connecting rods are typical and key components for automobile engines, their precision performance highly impacts the ultimate quality of engine assemblies. The online measurement of connecting rods was studied in this paper. According to the structural characteristics and parameter requirements of the connecting rods, an online multi-station measurement platform was designed and developed to measure, mark, and classify the measurements of the connecting rods in an automatic assembly line. Among these measurements, two significant parameters, the weight and the barycenter, were focused on in our work. A multi-point balance method was developed and applied to obtain the weights of the big and small ends as well as the position of the barycenter. An approach for weight sensor calibration and measurement data processing was also proposed. Finally, automatic and online measurement platforms were built for experimental verification. The results show that the measurement beats of the weight and the barycenter can reach 3 s/piece. The measured data were compared with a high-precision balance, and the average error of the connecting rod’s weight was 0.27%. The on-site application verification further proved the effectiveness and efficiency of our proposed measurement methods and machine, which enables fast and high-precision online measurement of connecting rods.

PITX2 Knockout Induces Key Findings of Electrical Remodeling as Seen in Persistent Atrial Fibrillation.

Electrical remodeling in human persistent atrial fibrillation is believed to result from rapid electrical activation of the atria, but underlying genetic causes may contribute. Indeed, common gene variants in an enhancer region close to PITX2 (paired-like homeodomain transcription factor 2) are strongly associated with atrial fibrillation, but the mechanism behind this association remains unknown. This study evaluated the consequences of PITX2 deletion (PITX2-/-) in human induced pluripotent stem cell-derived atrial cardiomyocytes. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) was used to delete PITX2 in a healthy human iPSC line that served as isogenic control. Human induced pluripotent stem cell-derived atrial cardiomyocytes were differentiated with unfiltered retinoic acid and cultured in atrial engineered heart tissue. Force and action potential were measured in atrial engineered heart tissues. Single human induced pluripotent stem cell-derived atrial cardiomyocytes were isolated from atrial engineered heart tissue for ion current measurements. PITX2-/- atrial engineered heart tissue beats slightly slower than isogenic control without irregularity. Force was lower in PITX2-/- than in isogenic control (0.053±0.015 versus 0.131±0.017 mN, n=28/3 versus n=28/4, PITX2-/- versus isogenic control; P<0.0001), accompanied by lower expression of CACNA1C and lower L-type Ca2+ current density. Early repolarization was weaker (action potential duration at 20% repolarization; 45.5±13.2 versus 8.6±5.3 ms, n=18/3 versus n=12/4, PITX2-/- versus isogenic control; P<0.0001), and maximum diastolic potential was more negative (-78.3±3.1 versus -69.7±0.6 mV, n=18/3 versus n=12/4, PITX2-/- versus isogenic control; P=0.001), despite normal inward rectifier currents (both IK1 and IK,ACh) and carbachol-induced shortening of action potential duration. Complete PITX2 deficiency in human induced pluripotent stem cell-derived atrial cardiomyocytes recapitulates some findings of electrical remodeling of atrial fibrillation in the absence of fast beating, indicating that these abnormalities could be primary consequences of lower PITX2 levels.

The Effect of Different Genres of Music on Blood Pressure among Different Age Groups

Many people listen to music during their day to day activities. Music is a combination of frequency, beat, density, tone, rhythm, repetition, loudness and lyrics. When we listen to fast beat music we get excited and slow beat music makes us to relax.There are different genres of music like rock, hip hop, pop ,classical, country, fazzy and these types of music has effect on blood pressure.The aim of the study is to know whether different types of music has effect on blood pressure or not. For this a cross sectional survey was conducted. This survey consisted of a self structured questionnaire. The sample size used for the study is 101. This standard questionnaire has been prepared and uploaded in google forms and circulated among the population, all the data were collected and the data has been analysed by using chi square analysis using the software IBM SPSS. The aim of the study is to evaluate the effect of different genres of music on blood pressure among the different age groups.

Does Fast Beat Thorough? Comparing RTAA* and LSS-LRTA*

The RTAA* algorithm has been proposed as an alternative to the LSS-LRTA* algorithm for heuristic search under hard time constraints. It uses a cruder but faster learning procedure. Experimental results on pathfinding in mazes in the unknown terrain setting indicated that RTAA* was superior to LSS-LRTA*. In this paper, we attempt to replicate those results and we extend the analysis to additional domains. Our results suggest that RTAA* is superior to LSS-LRTA* only in situations where the heuristic is already relatively accurate, either inherently or because of large lookahead. Overall, neither algorithm seems superior to the other.

Research on Temperature Compensation Method in Crankshaft Online Measurement System

The crankshaft online measurement system has realized the full inspection function with fast beats, at the same time it requires for high-precision measurement. Considering the effect of ambient temperature and temperature changes on measuring machine, the calibration part, the measured crankshaft and displacement sensor, a temperature compensation method is proposed. Firstly, relationship between calibration part and ambient temperature can be get through the zero calibration. Then use the material properties to obtain compensation values of the calibration part and the measured crankshaft part at different temperatures. Finally, the compensation parameters for displacement sensor can be obtained through the BP algorithm. The improved dragonfly algorithm (DA) is used to optimize the parameters of BP neural network algorithm. Experiments verify the effectiveness of IDA-BP for LVDT in temperature compensation. After temperature compensation, the error range of main journal radius is reduced from 0.0156 mm to 0.0028 mm, the residual error decreased from −0.0282 mm~+0.0018 mm to −0.0058 mm~−0.0008 mm. The influence of temperature changes on the measurement is reduced and measurement accuracy is improved through the temperature compensation method. The effectiveness of the method is proved.

Turn the beat around: Commentary on \u201cSlow and fast beat sequences are represented differently through space" (De Tommaso & Prpic, 2020, in Attention, Perception, & Psychophysics)

There has been increasing interest in the spatial mapping of various perceptual and cognitive magnitudes, such as expanding the spatial-numerical association of response codes (SNARC) effect into domains outside of numerical cognition. Recently, De Tommaso and Prpic (Attention, Perception, & Psychophysics, 82, 2765–2773, 2020) reported in this journal that only fast tempos over 104 beats per minute have spatial associations, with more right-sided associations and faster responses for faster tempos. After discussing the role of perceived loudness and possible response strategies, we propose and recommend methodological improvements for further research.

Explainable artificial intelligence for heart rate variability in ECG signal.

Electrocardiogram (ECG) signal is one of the most reliable methods to analyse the cardiovascular system. In the literature, there are different deep learning architectures proposed to detect various types of tachycardia diseases, such as atrial fibrillation, ventricular fibrillation, and sinus tachycardia. Even though all types of tachycardia diseases have fast beat rhythm as the common characteristic feature, existing deep learning architectures are trained with the corresponding disease-specific features. Most of the proposed works lack the interpretation and understanding of the results obtained. Hence, the objective of this letter is to explore the features learned by the deep learning models. For the detection of the different types of tachycardia diseases, the authors used a transfer learning approach. In this method, the model is trained with one of the tachycardia diseases called atrial fibrillation and tested with other tachycardia diseases, such as ventricular fibrillation and sinus tachycardia. The analysis was done using different deep learning models, such as RNN, LSTM, GRU, CNN, and RSCNN. RNN achieved an accuracy of 96.47% for atrial fibrillation data set, 90.88% accuracy for CU-ventricular tachycardia data set, and also achieved an accuracy of 94.71, and 94.18% for MIT-BIH malignant ventricular ectopy database for ECG lead I and lead II, respectively. The RNN model could only achieve an accuracy of 23.73% for the sinus tachycardia data set. A similar trend is shown by other models. From the analysis, it was evident that even though tachycardia diseases have fast beat rhythm as their common feature, the model was not able to detect different types of tachycardia diseases. The deep learning model could only detect atrial fibrillation and ventricular fibrillation and failed in the case of sinus tachycardia. From the analysis, they were able to interpret that, along with the fast beat rhythm, the model has learned the absence of P-wave which is a common feature for ventricular fibrillation and atrial fibrillation but sinus tachycardia disease has an upright positive P-wave. The time-based analysis is conducted to find the time complexity of the models. The analysis conveyed that RNN and RSCNN models could achieve better performance with lesser time complexity.

Keamanan Kunci Ruang Dosen Elektro UMSIDA Menggunakan Ketukan Berbasis Arduino

The development of modern technology now are much more advanced and it can make doing a job much easier such as security problems for door locks that are applied to the electrical lecturer room UMSIDA. This tool is designed to run a solenoid lock by using a knock code applied to the door locking system by using microcontroller and piezo electric sensor which will be seen with a security system with knock method. The purpose of this study was to determine the constraints of the door safety device using an electric piezo sensor based on the Atmega328 microcontroller and the system can correctly recognize the beat pattern received and process it. This tool system works when there is an input in the form of a password code through the beats detected by electric piezo if the password code is applied correctly then the microcontroller provides input on relay to activate the solenoid and stepper motor, so the door would open. The result of this research shows that it can identify the correct number of beats a maximum of 15 beats, if it is more than 15 times the beat is wrong. From the result of the trial, fast or not a knock is declared true if the beat time ratio is slow by 4 times knock and the door opens. If the knock pattern is different from what has been determined, then the knock is declared wrong and the door can not open. The test results indicated that it can be concluded that from the test or trial carried out by the object provides true overall results even though the results do not provide 100% results. The results of the analysis of the trial carried out by each objects for 15 times, which affects fast or slow beats, number of beats, the ratio of time between knock

Effect of Background Music for Attentive Concentration in Working

Purpose: Recently, many young people have preferred to work in café than traditional library because the café is equipped with coffee, music, and cozy seats. When working in the café, whether listeners’ attentive concentration could be affected by a kind of the background music needs to be investigated as the purpose of the present study. We also aimed to confirm the attentive concentration of listeners might be caused by their music inclination.Methods: A total of ninety young adults was randomly assigned as five kinds of background music [e.g., rhythm and blues (R&amp;B)/ballad, dance/rock, classic/jazz, fast beats, slow beats] and no music after responding to simple questions to ask their preference of music genre. While listening to the music, the subjects took an attentive concentration test, namely Frankfurter aufmerksamkeits-inventar (FAIR). The obtained data were analyzed by three subcategories of the FAIR test which consists of performance, quality, and continuity.Results: For the music genre, classic/jazz showed significantly higher continuity scores than R&amp;B/ballad, fast beats, and no music, which means that classic/jazz music of the café could help the workers maintain the attention. In the subgroup who listened to preferred music genre, their performance scores (i.e., selective attention) was significantly higher than that of the participants who being exposed to non-preferred music.Conclusion: Current results supports that music genre and individual music inclination may partially affect listener’s ability of the attentive concentration when background music was presented in the café, although a further study to find certain possible causal factors with objective methods should be followed.

Abstract 470: Recording Cell Migration Dynamics in Mouse Tissues With Cells Secreting Fluorescence Protein-tagged Collagen

Background: Cell migration is an important step involved in heart regeneration and many cardiovascular diseases. However, cell migration dynamics in vivo is poorly understood due to the challenges from mammal hearts, which are opaque and fast beating, and thus individual cardiac cells cannot be imaged or tracked. Aims: In this study, cell migration dynamics in the heart is recorded with a novel strategy, in which fluorescence protein-tagged collagen is secreted from cells and deposited into extracellular matrix, forming visible trails when cells are moving in tissues. As a proof-of-concept, transplanted migration dynamics of cardiac progenitor cells in mouse hearts were investaged. Methods: Stable cell lines expressing mCherry-tagged type I collagen were generated from isolated cardiac progenitor cells, ABCG2 + CD45 - CD31 - cells (side populations), or c-kit + CD45 - CD31 - cells (c-kit + CPCs). The cell migration dynamics were monitored and measured based on the cell trails after cell transplantation into mouse tissues. Results: The stable cell lines form red cell trails both in vitro and in vivo (Fig. 1A &amp; 1B, Green: GFP; Red: mCherry-collagen I, Blue: DAPI, bar: 50 microns). In culture dishes, the cells form visible cell trails of fluorescence protein. The cell moving directions are random, with a speed of 288 +/- 79 microns/day (side populations, n=3) or 143 +/-37 microns/day (c-kit + CPCs, n=3). After transplantation into wild-type mouse hearts, the cells form highly tortuous trails along the gaps between the heart muscle fibers. Angle between a cell trail and a muscle fiber is 16+/-16 degree (n=3). Side populations migrate twice as fast as c-kit+ CPCs in the heart (16.0 +/-8.7 microns/day vs. 8.1+/-0.0 microns/day, n=3, respectively), 18 time slower than the respective speeds in vitro . Additionally, side populations migrate significantly faster in the heart than in the skeletal muscles (26.4+/-5.8 microns/day, n=3). The side populations move significantly faster in immunodeficient mouse hearts (36.7+/-13.3 microns/day, n=3, typically used for studying cell therapies) than in wild-type mouse hearts. Conclusion: For the first time, cell migration dynamics in living hearts is monitored and examined with genetically modified cell lines. This study may greatly advance the fields of cardiovascular biology.

Frequency pulling in optoelectronic oscillator by RF signal injection

This paper brings the results of a study of the frequency pulling in a single loop optoelectronic oscillator (OEO) when injected by weak and strong radio frequency (RF) signal. An experiment was performed for three different injection signal powers to study the frequency pulling and the average frequency of the OEO. The analysis is made on the basis of OEO output spectra due to RF signal injection, beat frequency, lock-range and average frequency by extracting the values from the experimental data. It is also illustrated that the spectral components present in the injection signal side are responsible for frequency pulling. The influence of the RF injection signal on the phase noise performance of the free running OEO and injection locked OEO is also studied. The significant improvement in dipping the spurs of the OEO output spectra by injection locking technique is highlighted. Also the effect of Gaussian minimum shift keying signal injection on the injection locked OEO output spectrum has been investigated. The experimental evidence of the pulled OEO output characteristics from fast beat state to locked state is also provided.

A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study.

BackgroundElectrocardiographic (ECG) monitors have been widely used for diagnosing cardiac arrhythmias for decades. However, accurate analysis of ECG signals is difficult and time-consuming work because large amounts of beats need to be inspected. In order to enhance ECG beat classification, machine learning and deep learning methods have been studied. However, existing studies have limitations in model rigidity, model complexity, and inference speed.ObjectiveTo classify ECG beats effectively and efficiently, we propose a baseline model with recurrent neural networks (RNNs). Furthermore, we also propose a lightweight model with fused RNN for speeding up the prediction time on central processing units (CPUs).MethodsWe used 48 ECGs from the MIT-BIH (Massachusetts Institute of Technology-Beth Israel Hospital) Arrhythmia Database, and 76 ECGs were collected with S-Patch devices developed by Samsung SDS. We developed both baseline and lightweight models on the MXNet framework. We trained both models on graphics processing units and measured both models’ inference times on CPUs.ResultsOur models achieved overall beat classification accuracies of 99.72% for the baseline model with RNN and 99.80% for the lightweight model with fused RNN. Moreover, our lightweight model reduced the inference time on CPUs without any loss of accuracy. The inference time for the lightweight model for 24-hour ECGs was 3 minutes, which is 5 times faster than the baseline model.ConclusionsBoth our baseline and lightweight models achieved cardiologist-level accuracies. Furthermore, our lightweight model is competitive on CPU-based wearable hardware.