Search Results (15)

The process of ultrasonic atomization involves a series of dynamic/topological deformations of free surface, though not always, of a bulk liquid (initially) below the air. This study focuses on such dynamic interfacial alterations realized by changing some acousto-related operating conditions, including ultrasound excitation frequency, acoustic strength or input power density, and the presence/absence of a “stabilizing” nozzle. High-speed, high-resolution imaging made it possible to qualitatively identify four representative transitions/demarcations: (1) the onset of a protrusion on otherwise flat free surface; (2) the appearance of undulation along the growing protuberance; (3) the triggering of emanating beads fountain out of this foundation-like region; and (4) the induction of droplets bursting and/or mist spreading. Quantitatively examined were the two-parameters specifications—on the degrees as well as induction—of the periodicity in the protrusion-surface and beads-fountain oscillations, detected over wider ranges of driving/excitation frequency (0.43–3.0 MHz) and input power density (0.5–10 W/${\mathrm{c}\mathrm{m}}^2$) applied to the ultrasound transducer of flat surface on which the nozzle was either mounted or not. The resulting time sequence of images processed for the extended operating ranges, regarding the fountain structure pertaining, in particular, to recurring beads, confirms the wave-associated nature, i.e., their size “scalability” to the ultrasound wavelength, predictable from the traveling wave relationship. The thresholds in acoustic conditions for each of the four transition states of the fountain structure have been identified—notably, the onset of plausible “bifurcation” in the chain-beads’ diameter below a critical excitation frequency. Full article

Multi-scale dynamical systems may exhibit bursting oscillations, which are typically identified by analyzing time series and phase portraits. However, in cases where bursting oscillations are not apparent, relying solely on these methods may have limitations in accurately detecting their occurrence. This paper introduces the HAVOK analysis framework to the field of bursting oscillations. By using single-variable time series data, models that may produce bursting oscillations are restructured into forced linear models. This approach allows for the rapid prediction of bursting oscillations by observing the forced terms. The results show that the intermittent periodic bursts in the visualizations of the forced eigen time series within the HAVOK framework are strongly correlated with the excitation states in bursting oscillations, enabling the prediction of their occurrence. Especially in cases where it is challenging to determine the presence of bursting oscillations through time series plots alone, this method can still sensitively detect them. Additionally, the embedded and reconstructed flow fields plotted using this approach can help understand the dynamics of bursting oscillations in certain scenarios. Full article

Background: From new results presented in the literature we discuss the hypothesis, presented in an our previous work, that the ultrafast periodic spectral modulations at $f_S=0.607\pm 0.08$ THz found in the spectra of 236 stars of the Sloan Digital Sky Survey (SDSS) were due to oscillations induced by dark matter (DM) cores in their centers that behave as oscillating boson stars. Two other frequencies were found by Borra in the redshift-corrected SDSS galactic spectra, $f_{1,G}={9.71}_{-0.19}^{+0.20}$ THz and $f_{2,G}={9.17}_{-0.16}^{+0.18}$ THz; the latter was then shown by Hippke to be a spurious frequency introduced by the data analysis procedure. Results: Within the experimental errors, the frequency $f_{1,G}$ is the beating of the two frequencies, the spurious one, $f_{2,G}$ and $f_S$ that was also independently detected in a real solar spectrum, but not in the Kurucz’s artificial solar spectrum by Hippke, suggesting that $f_S$ could actually be a real frequency. Independent SETI observations by Isaacson et al., taken at different epochs, of four of these 236 stars could not confirm with high confidence—without completely excluding—the presence of $f_S$ in their power spectra and with the same power initially observed. Instead, the radio SETI deep-learning analysis with artificial intelligence (AI) gave an indirect confirmation of the presence of $f_S$ through the detection of a narrowband Doppler drifting of the observed radio signals in two stars, over a sample of 7 with a high S/N. These two stars belong to the set of the 236 SDSS stars. Numerical simulations confirm that this drifting can be due to frequency and phase modulation in time of the observed frequencies (1.3–1.7 GHz) with $f_S$. Conclusions: Assuming the DM hypothesis, the upper mass limit of the axion-like DM particle is $m_a\simeq 2.4\times {10}^3\mathsf{\mu }\mathrm{eV}$, in agreement with the results from the gamma ray burst GRB221009A, laser interferometry experiments, suggesting new physics with additional axion-like particle fields for the muon g-2 anomaly. Full article

This paper presents an in-depth analysis of an excitable membrane of a biological system by proposing a novel approach that the cells of the excitable membrane can be modeled as the networks of memristors. We provide compelling evidence from the Chay neuron model that the state-independent mixed ion channel is a nonlinear resistor, while the state-dependent voltage-sensitive potassium ion channel and calcium-sensitive potassium ion channel function as generic memristors from the perspective of electrical circuit theory. The mechanisms that give rise to periodic oscillation, aperiodic (chaotic) oscillation, spikes, and bursting in an excitable cell are also analyzed via a small-signal model, a pole-zero diagram of admittance functions, local activity, the edge of chaos, and the Hopf bifurcation theorem. It is also proved that the zeros of the admittance functions are equivalent to the eigen values of the Jacobian matrix, and the presence of the positive real parts of the eigen values between the two bifurcation points lead to the generation of complicated electrical signals in an excitable membrane. The innovative concepts outlined in this paper pave the way for a deeper understanding of the dynamic behavior of excitable cells, offering potent tools for simulating and exploring the fundamental characteristics of biological neurons. Full article

Healthy brains display a wide range of firing patterns, from synchronized oscillations during slow-wave sleep to desynchronized firing during movement. These physiological activities coexist with periods of pathological hyperactivity in the epileptic brain, where neurons can fire in synchronized bursts. Most cortical neurons are pyramidal regular spiking (RS) cells with frequency adaptation and do not exhibit bursts in current-clamp experiments (in vitro). In this work, we investigate the transition mechanism of spike-to-burst patterns due to slow potassium and calcium currents, considering a conductance-based model of a cortical RS cell. The joint influence of potassium and calcium ion channels on high synchronous patterns is investigated for different synaptic couplings ($g_{\mathrm{syn}}$) and external current inputs (I). Our results suggest that slow potassium currents play an important role in the emergence of high-synchronous activities, as well as in the spike-to-burst firing pattern transitions. This transition is related to the bistable dynamics of the neuronal network, where physiological asynchronous states coexist with pathological burst synchronization. The hysteresis curve of the coefficient of variation of the inter-spike interval demonstrates that a burst can be initiated by firing states with neuronal synchronization. Furthermore, we notice that high-threshold ($I_{\mathrm{L}}$) and low-threshold ($I_{\mathrm{T}}$) ion channels play a role in increasing and decreasing the parameter conditions ($g_{\mathrm{syn}}$ and I) in which bistable dynamics occur, respectively. For high values of $I_{\mathrm{L}}$ conductance, a synchronous burst appears when neurons are weakly coupled and receive more external input. On the other hand, when the conductance $I_{\mathrm{T}}$ increases, higher coupling and lower I are necessary to produce burst synchronization. In light of our results, we suggest that channel subtype-specific pharmacological interactions can be useful to induce transitions from pathological high bursting states to healthy states. Full article

As a kind of dynamical system with a particular nonlinear structure, a multi-time scale nonlinear system is one of the essential directions of the current development of nonlinear dynamics theory. Multi-time scale nonlinear systems in practical applications are often complex forms of coupling of high-dimensional and high codimension characteristics, leading to various complex bursting oscillation behaviors and bifurcation characteristics in the system. For exploring the complex bursting dynamics caused by high codimension bifurcation, this paper considers the normal form of the vector field with triple zero bifurcation. Two kinds of codimension-2 bifurcation that may lead to complex bursting oscillations are discussed in the two-parameter plane. Based on the fast–slow analysis method, by introducing the slow variable $W=Asin\left(\omega t\right)$, the evolution process of the motion trajectory of the system changing with W was investigated, and the dynamical mechanism of several types of bursting oscillations was revealed. Finally, by varying the frequency of the slow variable, a class of chaotic bursting phenomena caused by the period-doubling cascade is deduced. Developing related work has played a positive role in deeply understanding the nature of various complex bursting phenomena and strengthening the application of basic disciplines such as mechanics and mathematics in engineering practice. Full article

Gel fuel droplets exhibit disruptive burning due to the rupture of their gellant shell, which causes the release of unreacted fuel vapors from the droplet interior to the flame in the form of jets. In addition to pure vaporization, this jetting allows convective transport for fuel vapors, which accelerates gas-phase mixing and is known to improve droplet burn rates. Using high-magnification and high-speed imaging, this study found that the viscoelastic gellant shell at the droplet surface evolves during the droplet’s lifetime, which causes the droplet to burst at different frequencies, thereby triggering a time-varying oscillatory jetting. In particular, the continuous wavelet spectra of the droplet diameter fluctuations show that the droplet bursting exhibits a nonmonotonic (hump-shaped) trend, where the bursting frequency first increases and then decreases to a point where the droplet stops oscillating. The changes in the shell structure are captured by tracking the temporal variation of the area of rupture sites, spatial movement of their centroid, and the degree of overlap between the rupture areas of successive cycles. During the initial period (immediately following its formation) when the shell is newly formed, it is weak and flexible, which causes it to burst at increasingly high frequencies. This is because the area at and around the rupture site becomes progressively weaker with each rupture in an already weak shell. This is shown by a high degree of overlap between the areas of successive ruptures. On the other hand, the shell flexibility during the initial period is demonstrated by a reversal in the motion of rupture site centroids. However, at later stages when the droplet has undergone multiple ruptures, the depletion of the fuel vapor causes accumulation of gellant on the shell, thus causing the shell to become strong and rigid. This thick, strong, and rigid shell suppresses droplet oscillations. Overall, this study provides a mechanistic understanding of how the gellant shell evolves during the combustion of a gel fuel droplet and causes the droplet to burst at different frequencies. This understanding can be used to devise gel fuel compositions that result in gellant shells with tailored properties, and therefore, control the jetting frequencies to tune droplet burn rates. Full article

We analyze neutrino emission channels in energetic ($\gtrsim {10}^{52}$ erg) long gamma-ray bursts within the binary-driven hypernova model. The binary-driven hypernova progenitor is a binary system composed of a carbon-oxygen star and a neutron star (NS) companion. The gravitational collapse leads to a type Ic supernova (SN) explosion and triggers an accretion process onto the NS. For orbital periods of a few minutes, the NS reaches the critical mass and forms a black hole (BH). Two physical situations produce MeV neutrinos. First, during the accretion, the NS surface emits neutrino–antineutrino pairs by thermal production. We calculate the properties of such a neutrino emission, including flavor evolution. Second, if the angular momentum of the SN ejecta is high enough, an accretion disk might form around the BH. The disk’s high density and temperature are ideal for MeV-neutrino production. We estimate the flavor evolution of electron and non-electron neutrinos and find that neutrino oscillation inside the disk leads to flavor equipartition. This effect reduces (compared to assuming frozen flavor content) the energy deposition rate of neutrino–antineutrino annihilation into electron–positron ($e^{+}{e}^{-}$) pairs in the BH vicinity. We then analyze the production of GeV-TeV neutrinos around the newborn black hole. The magnetic field surrounding the BH interacts with the BH gravitomagnetic field producing an electric field that leads to spontaneous $e^{+}{e}^{-}$ pairs by vacuum breakdown. The $e^{+}{e}^{-}$ plasma self-accelerates due to its internal pressure and engulfs protons during the expansion. The hadronic interaction of the protons in the expanding plasma with the ambient protons leads to neutrino emission via the decay chain of $\pi$-meson and $\mu$-lepton, around and far from the black hole, along different directions. These neutrinos have energies in the GeV-TeV regime, and we calculate their spectrum and luminosity. We also outline the detection probability by some current and future neutrino detectors. Full article

The main purpose of this paper is to study point-cycle type bistability as well as induced periodic bursting oscillations by taking a modified Filippov-type Chua’s circuit system with a low-frequency external excitation as an example. Two different kinds of bistable structures in the fast subsystem are obtained via conventional bifurcation analyses; meanwhile, nonconventional bifurcations are also employed to explain the nonsmooth structures in the bistability. In the following numerical investigations, dynamic evolutions of the full system are presented by regarding the excitation amplitude and frequency as analysis parameters. As a consequence, we can find that the classification method for periodic bursting oscillations in smooth systems is not completely applicable when nonconventional bifurcations such as the sliding bifurcations and persistence bifurcation are involved; in addition, it should be pointed out that the emergence of the bursting oscillation does not completely depend on bifurcations under the point-cycle bistable structure in this paper. It is predicted that there may be other unrevealed slow–fast transition mechanisms worthy of further study. Full article

Electromagnetic radiation (EMR) technology makes it possible to evaluate changes in the stress-strain state (SSS) in the “tunnel lining-enclosing rock mass” system at a high level of interference, and to create schemes of long-term EMR control in tunnels (geotechnical monitoring systems). The issues of the variations in EMR signals are extremely important for monitoring systems: based on anomalous deviations from the normal regime one can draw conclusions about changes in the SSS, leading to geodynamic phenomena (e.g., rock bursts). This article presents data obtained during laboratory studies on samples and field studies in transport tunnels. Also, some results of long-term geotechnical monitoring by a set of methods is presented: EMR and tensometry of the tunnel lining, both methods are in the automatic mode. The ability of an EMR control system to respond to earthquakes affecting tunnel structures is shown. An analysis of long-term EMR studies was conducted, which showed the periodic oscillation of the “tunnel lining-enclosing rock mass” system. In a stable compressed state, minima of EMR pulses are recorded; when the rock mass and lining material are stretched, charges are separated on the edges of micro-defects and EMR increases; complete separation of the edges of micro-defects leads to the termination of intense EMR. The same occurs in the opposite direction during the compression of micro-defects and micro-fractures in the rock mass and concrete lining. The periods of compression and expansion are closely related to temperature fluctuations. The results differ in detail and, therefore, in to be more confident, additional studies are needed in various host rock massifs and types of tunnel lining. Full article

Spikes are typical radio bursts in solar flares, which are proposed to be the signal of energy release in the solar corona. The whole group of spikes always shows different spectral patterns in the dynamic spectrum. Here, we present a special new feature at 0.6–2 GHz in a confined flare. Each group of spikes is composed of many quasi-periodic sub-clusters, which are superposed on the broadband quasi-periodic pulsations (QPPs). The quasi-periodic cluster of spikes (QPSs) have very intense emissions, and each cluster includes tens of individual spikes. When the intensity of background pulsation is increased, the intensity, duration and bandwidth of the spike cluster are also enlarged. There are 21 groups of QPSs throughout the confined flare. The central frequency of the whole group shifts from 1.9 to 1.2 GHz, and the duration of each cluster shows a negative exponential decay pattern. We propose that nonthermal electron beams play a crucial role in emitting both pulsations and spikes. The tearing-mode oscillations of a confined flux rope produce periodic accelerated electron beams. These electron beams travel inside the closed magnetic structure to produce frequency drifting pulsations via plasma emission and scattered narrowband spikes by electron-cyclotron maser emission (ECME). The slow rise of flux rope makes the source region move upward, and thus, QPSs shift towards low frequency. We propose that the confined flux rope may provide the essential conditions for the formation of QPSs. Full article

Optical injection is a key nonlinear laser configuration both for applications and fundamental studies. An important figure for understanding the optically injected laser system is the two parameter stability mapping of the dynamics found by examining the output of the injected laser under different combinations of the injection strength and detuning. We experimentally and theoretically generate this map for an optically injected quantum dot laser, biased to emit from the first excited state and optically injected near the ground state. Regions of different dynamical behaviours including phase-locking, excitability, and bursting regimes are identified. At the negatively detuned locking boundary, ground state dropouts and excited state pulses are observed near a hysteresis cycle for low injection strengths. Higher injection strengths reveal $\mathsf{\mu }$s duration square wave trains where the intensities of the ground state and excited state operate in antiphase. A narrow region of extremely slow oscillations with periods of several tens of milliseconds is observed at the positively detuned boundary. Two competing optothermal couplings are introduced and are shown to reproduce the experimental results extremely well. In fact, the dynamics of the system are dominated by these optothermal effects and their interplay is central to reproducing detailed features of the stability map. Full article

Presently, the cloud computing environment attracts many application developers to deploy their web applications on cloud data centers. Kubernetes, a well-known container orchestration for deploying web applications on cloud systems, offers an automatic scaling feature to meet clients’ ever-changing demands with the reactive approach. This paper proposes a system architecture based on Kubernetes with a proactive custom autoscaler using a deep neural network model to handle the workload during run time dynamically. The proposed system architecture is designed based on the Monitor–Analyze–Plan–Execute (MAPE) loop. The main contribution of this paper is the proactive custom autoscaler, which focuses on the analysis and planning phases. In analysis phase, Bidirectional Long Short-term Memory (Bi-LSTM) is applied to predict the number of HTTP workloads in the future. In the planning phase, a cooling-down time period is implemented to mitigate the oscillation problem. In addition, a resource removal strategy is proposed to remove a part of the resources when the workload decreases, so that the autoscaler can handle it faster when the burst of workload happens. Through experiments with two different realistic workloads, the Bi-LSTM model achieves better accuracy not only than the Long Short-Term Memory model but also than the state-of-the-art statistical auto-regression integrated moving average model in terms of short- and long-term forecasting. Moreover, it offers 530 to 600 times faster prediction speed than ARIMA models with different workloads. Furthermore, as compared to the LSTM model, the Bi-LSTM model performs better in terms of resource provision accuracy and elastic speedup. Finally, it is shown that the proposed proactive custom autoscaler outperforms the default horizontal pod autoscaler (HPA) of the Kubernetes in terms of accuracy and speed when provisioning and de-provisioning resources. Full article

Obtaining differentiated cells with high physiological functions by an efficient, but simple and rapid differentiation method is crucial for modeling neuronal diseases in vitro using human pluripotent stem cells (hPSCs). Currently, methods involving the transient expression of one or a couple of transcription factors have been established as techniques for inducing neuronal differentiation in a rapid, single step. It has also been reported that microRNAs can function as reprogramming effectors for directly reprogramming human dermal fibroblasts to neurons. In this study, we tested the effect of adding neuronal microRNAs, miRNA-9/9*, and miR-124 (miR-9/9*-124), for the neuronal induction method of hPSCs using Tet-On-driven expression of the Neurogenin2 gene (Ngn2), a proneural factor. While it has been established that Ngn2 can facilitate differentiation from pluripotent stem cells into neurons with high purity due to its neurogenic effect, a long or indefinite time is required for neuronal maturation with Ngn2 misexpression alone. With the present method, the cells maintained a high neuronal differentiation rate while exhibiting increased gene expression of neuronal maturation markers, spontaneous calcium oscillation, and high electrical activity with network bursts as assessed by a multipoint electrode system. Moreover, when applying this method to iPSCs from Alzheimer’s disease (AD) patients with presenilin-1 (PS1) or presenilin-2 (PS2) mutations, cellular phenotypes such as increased amount of extracellular secretion of amyloid β42, abnormal oxygen consumption, and increased reactive oxygen species in the cells were observed in a shorter culture period than those previously reported. Therefore, it is strongly anticipated that the induction method combining Ngn2 and miR-9/9*-124 will enable more rapid and simple screening for various types of neuronal disease phenotypes and promote drug discovery. Full article

Brain-derived neurotrophic factor (BDNF) is one of the key signaling molecules that supports the viability of neural cells in various brain pathologies, and can be considered a potential therapeutic agent. However, several methodological difficulties, such as overcoming the blood–brain barrier and the short half-life period, challenge the potential use of BDNF in clinical practice. Gene therapy could overcome these limitations. Investigating the influence of viral vectors on the neural network level is of particular interest because viral overexpression affects different aspects of cell metabolism and interactions between neurons. The present work aimed to investigate the influence of the adeno-associated virus (AAV)-Syn-BDNF-EGFP virus construct on neural network activity parameters in an acute hypobaric hypoxia model in vitro. Materials and methods. An adeno-associated virus vector carrying the BDNF gene was constructed using the following plasmids: AAV-Syn-EGFP, pDP5, DJvector, and pHelper. The developed virus vector was then tested on primary hippocampal cultures obtained from C57BL/6 mouse embryos (E18). Acute hypobaric hypoxia was induced on day 21 in vitro. Spontaneous bioelectrical and calcium activity of neural networks in primary cultures and viability tests were analysed during normoxia and during the posthypoxic period. Results. BDNF overexpression by AAV-Syn-BDNF-EGFP does not affect cell viability or the main parameters of spontaneous bioelectrical activity in normoxia. Application of the developed virus construct partially eliminates the negative hypoxic consequences by preserving cell viability and maintaining spontaneous bioelectrical activity in the cultures. Moreover, the internal functional structure, including the activation pattern of network bursts, the number of hubs, and the number of connections within network elements, is also partially preserved. BDNF overexpression prevents a decrease in the number of cells exhibiting calcium activity and maintains the frequency of calcium oscillations. Conclusion. This study revealed the pronounced antihypoxic and neuroprotective effects of AAV-Syn-BDNF-EGFP virus transduction in an acute normobaric hypoxia model. Full article