Explore the vast range of titles available.

The formation of secondary ice in clouds, that is, ice particles that are created at temperatures above the limit for homogeneous freezing without the direct involvement of a heterogeneous ice nucleus, is one of the longest-standing puzzles in cloud physics. Here, we present comprehensive laboratory investigations on the formation of small ice particles upon the freezing of drizzle-sized cloud droplets levitated in an electrodynamic balance. Four different categories of secondary ice formation (bubble bursting, jetting, cracking, and breakup) could be detected, and their respective frequencies of occurrence as a function of temperature and droplet size are given. We find that bubble bursting occurs more often than droplet splitting. While we do not observe the shattering of droplets into many large fragments, we find that the average number of small secondary ice particles released during freezing is strongly dependent on droplet size and may well exceed unity for droplets larger than 300 μm in diameter. This leaves droplet fragmentation as an important secondary ice process effective at temperatures around −10°C in clouds where large drizzle droplets are present.

Because of the advent of discrete memristor, memristor effect in discrete map has become the important subject deserving discussion. To this end, this paper constructs a memristor-based neuron model considering magnetic induction by combining an existing map-based neuron model and a discrete memristor with absolute value memductance. Taking the coupling strength and initial state of the memristor as variables, complex mode transition behaviors induced by the introduced memristor are disclosed using numerical methods, including spiking-bursting behaviors, mode transition behaviors, and hyperchaotic spiking behaviors. In particular, all of these behaviors are greatly dependent on the memristor initial state, resulting in the existence of extreme multistability in the memristive neuron model. Therefore, this memristive neuron model can be used to effectively imitate the magnetic induction effects when complex mode transition behaviors appear in the neuronal action potential. Besides, a hardware platform based on FPGA is developed for implementing the memristive neuron model and various spiking-bursting sequences are experimentally captured therein. The results show that when biophysical memory effect is present, the memristive neuron model can better represent the firing activities of biological neurons than the original map-based neuron model.

The oceans represent a significant global source of atmospheric aerosols. Sea spray aerosol (SSA) particles comprise sea salts and organic species in varying proportions. In addition to size, the overall composition of SSA particles determines how effectively they can form cloud droplets and ice crystals. Thus, understanding the factors controlling SSA composition is critical to predicting aerosol impacts on clouds and climate. It is often assumed that submicrometer SSAs are mainly formed by film drops produced from bursting bubble-cap films, which become enriched with hydrophobic organic species contained within the sea surface microlayer. In contrast, jet drops formed from the base of bursting bubbles are postulated to mainly produce larger supermicrometer particles from bulk seawater, which comprises largely salts and water-soluble organic species. However, here we demonstrate that jet drops produce up to 43% of total submicrometer SSA number concentrations, and that the fraction of SSA produced by jet drops can be modulated by marine biological activity. We show that the chemical composition, organic volume fraction, and ice nucleating ability of submicrometer particles from jet drops differ from those formed from film drops. Thus, the chemical composition of a substantial fraction of submicrometer particles will not be controlled by the composition of the sea surface microlayer, a major assumption in previous studies. This finding has significant ramifications for understanding the factors controlling the mixing state of submicrometer SSA particles and must be taken into consideration when predicting SSA impacts on clouds and climate.

The design and analysis of a simple autonomous memristive chaotic circuit are important in theoretical, numerical, and experimental demonstrations of complex dynamics. In this paper, a simple autonomous memristive circuit is implemented, which only consists of an active second-order memristive diode bridge and a capacitor. Based on the available circuit, the mathematical model is established and its symmetry, dissipativity, and equilibrium stability are analyzed. Numerical simulations show that the proposed circuit exhibits complex behaviors of unipolar periodic and chaotic bursting oscillations along with coexisting attractors. It is worth noting that the circuit exhibits such a special bursting behavior previously unobserved in third-order autonomous memristive circuits. Moreover, spectral entropy complexities are calculated to provide an intuitive and effectual method for the circuit parameter configurations. The circuit simulations and hardware experiments verify the theoretical analyses and numerical simulations.

The bursting liability is very important to evaluate the risk of rock burst in coal mine. Conducting uniaxial compression test is the main method to study the bursting liability of rock (coal). To establish an accurate uniaxial constitutive model, the structure ensemble dynamics theory is adopted. The model of rock (coal) specimen compression by testing machine is simplified. Through dimensional analysis, the stress–strain relationship of the specimen is a power model. The mechanical properties of rock (coal) vary with different levels of deformation and can be divided into four stages. The different states can be considered as different ensembles. By using the analysis method of structural ensembles dynamics, one formula completely represents the four stages accurately. The parameters in the formula are physically meaningful and can be uniquely determined based on experimental data. A criterion for instability criterion of the system of the specimen and the testing machine is derived, and a theoretical explanation of instability failure related to uniaxial compressive strength is given. Parameters sensitivity analysis and verification are conducted on the theoretical results. The theoretical results are highly accurate and can effectively reflect the stress–strain relationship of rock (coal) under uniaxial compression. A bursting liability index which contains the information of the peak and post-peak of the stress–strain relationship is proposed. The new index is positively correlated with the compressive strength and the bursting energy index and a classification of bursting liability levels for the new index was determined based on them.HighlightsThe structure ensemble dynamics theory is used to establish a constitutive model.One formula completely represents the stress-stain relationship accurately.The parameters are physically meaningful and can be uniquely determined.A theoretical explanation of instability failure related to strength is given.A new bursting liability index based on the new constitutive model is proposed.

Many mammalian genes are transcribed during short bursts of variable frequencies and sizes that substantially contribute to cell-to-cell variability. However, which molecular mechanisms determine bursting properties remains unclear. To probe putative mechanisms, we combined temporal analysis of transcription along the circadian cycle with multiple genomic reporter integrations, using both short-lived luciferase live microscopy and single-molecule RNA-FISH. Using the Bmal1 circadian promoter as our model, we observed that rhythmic transcription resulted predominantly from variations in burst frequency, while the genomic position changed the burst size. Thus, burst frequency and size independently modulated Bmal1 transcription. We then found that promoter histone-acetylation level covaried with burst frequency, being greatest at peak expression and lowest at trough expression, while remaining unaffected by the genomic location. In addition, specific deletions of ROR-responsive elements led to constitutively elevated histone acetylation and burst frequency. We then investigated the suggested link between histone acetylation and burst frequency by dCas9p300-targeted modulation of histone acetylation, revealing that acetylation levels influence burst frequency more than burst size. The correlation between acetylation levels at the promoter and burst frequency was also observed in endogenous circadian genes and in embryonic stem cell fate genes. Thus, our data suggest that histone acetylation-mediated control of transcription burst frequency is a common mechanism to control mammalian gene expression.

Using a dynamical scaling analysis of the flow variables and their evolution due to bubble bursting, here we predict the size and speed of ejected droplets for the whole range of experimental Ohnesorge and Bond numbers where ejection occurs. The transient ejection, which requires the backfire of a vortex ring inside the liquid to preserve physical symmetry, shows a delicate balance between inertia, surface tension and viscous forces around a critical Ohnesorge number, akin to an apparent singularity. Like in other natural phenomena, this balance makes the process extremely sensitive to initial conditions. Our model generalizes or displaces other recently proposed ones, impacting on, for instance, the statistical description of sea spray.

Air bubbles at the surface of water end their life in a particular way: when bursting, they may eject drops of liquid in the surrounding environment. Many uncertainties remain regarding collective effects of bubbles at the water–air interface, despite extensive efforts to describe the bursting mechanisms, motivated by their critical importance in mass transfers between the ocean and the atmosphere in the production of sea spray aerosols. We investigate the effect of surfactant on the collective dynamics and statistics of air bubbles evolving freely at the surface of water, through an experimental set-up controlling the bulk distribution of bubbles with nearly monodisperse millimetric air bubbles. We observe that for low contamination, bubble coalescence is inevitable and leads to a broad surface size distribution. For higher surfactant concentrations, coalescence at the surface is prevented and bubble lifetime is increased, leading to the formation of rafts with a surface size distribution identical to the bulk distribution. This shows that surface contamination has a first-order influence on the transfer function from bulk size distribution to surface size distribution, an intermediate step which needs to be considered when developing sea spray source function as droplet production by bubble bursting depends on the bubble size. We measure the bursting and merging rates of bubbles as a function of contamination through a complementary freely decaying raft experiment. We propose a cellular automaton model that includes the minimal ingredients to reproduce the experimental results in the statistically stationary configuration: production, coalescence and bursting after a finite lifetime.

The biological system survives in an appropriate temperature range, and neuronal firing patterns carrying different information will consume energy during the transformation. However, how the different firing kinetics of temperature-sensitive neuron determine energy efficiency is not clear. Therefore, the effect of temperature on energy-efficient firing patterns was investigated. It was found that neural electrical activities exhibit successive complex firing patterns, and the transition between different firing patterns corresponds to the critical state with the highest energy efficiency. Furthermore, under the appropriate system parameters, energy efficiency has several peaks. This optimum energy efficiency corresponds to critical state for the transition from firing state to bursting state, and several extreme values correspond to the transitions between different bursting states. Energy efficiency of transition from firing state to bursting state is higher than energy efficiency of transition between different bursting states. These results give new light on energy efficiency of temperature in the neuronal system.

Predicting how interactions between transcription factors and regulatory DNA sequence dictate rates of transcription and, ultimately, drive developmental outcomes remains an open challenge in physical biology. Using stripe 2 of the even-skipped gene in Drosophila embryos as a case study, we dissect the regulatory forces underpinning a key step along the developmental decision-making cascade: the generation of cytoplasmic mRNA patterns via the control of transcription in individual cells. Using live imaging and computational approaches, we found that the transcriptional burst frequency is modulated across the stripe to control the mRNA production rate. However, we discovered that bursting alone cannot quantitatively recapitulate the formation of the stripe and that control of the window of time over which each nucleus transcribes even-skipped plays a critical role in stripe formation. Theoretical modeling revealed that these regulatory strategies (bursting and the time window) respond in different ways to input transcription factor concentrations, suggesting that the stripe is shaped by the interplay of 2 distinct underlying molecular processes.