Two-layer Structure Research Articles

Dynamic Byzantine Fault-Tolerant Consensus Algorithm with Supervised Feedback Mechanisms

Among the existing consensus algorithms, there are very few low-latency consensus algorithms that can simultaneously take into account node dynamics, fault tolerance, and scalability, and which are applicable to large-scale open scenarios where low latency is required. Therefore, this paper proposes a low-latency scalable dynamic consensus algorithm with high fault tolerance utilizing a combination of layered and threshold signature technologies, known briefly as LTSBFT. Firstly, LTSBFT achieves linear communication complexity through the utilization of threshold signature technology and a two-layer structure. Secondly, the mutual supervision feedback mechanism among nodes enables the attainment of linear complexity for reaching consensus on the faulty upper-layer nodes during the view-change. Lastly, a node dynamic protocol was proposed for the first time to support dynamic changes in the number of nodes during the consensus process. That is to say, consensus can still be reached when the number of nodes dynamically changes without interrupting the client’s request for consensus in the network. The experimental results indicate that LTSBFT exhibits lower communication latency and higher throughput compared to the classic HotStuff and PBFT algorithms. Furthermore, in comparison to double-layer PBFT, the LTSBFT has been demonstrated to have improved fault tolerance.

Bimolecular Sandwich Aggregates of Porphyrin Nanorings.

Extended π-systems often form supramolecular aggregates, drastically changing their optical and electronic properties. However, aggregation processes can be difficult to characterize or predict. Here, we show that butadiyne-linked 8- and 12-porphyrin nanorings form stable and well-defined bimolecular aggregates with remarkably sharp NMR spectra, despite their dynamic structures and high molecular weights (12.7 to 26.0 kDa). Pyridine breaks up the aggregates into their constituent rings, which are in slow exchange with the aggregates on the NMR time scale. All the aggregates have the same general two-layer sandwich structure, as deduced from NMR spectroscopy experiments, including 1H DOSY, 1H-1H COSY, TOCSY, NOESY, and 1H-13C HSQC. This structure was confirmed by analysis of residual dipolar couplings from 13C-coupled 1H-13C HSQC experiments on one of the 12-ring aggregates. Variable-temperature NMR spectroscopy revealed an internal ring-on-ring rotation process by which two π-π stacked conformers interconvert via a staggered conformation. A slower dynamic process, involving rotation of individual porphyrin units, was also detected by exchange spectroscopy in the 8-ring aggregates, implying partial disaggregation and reassociation. Molecular dynamics simulations indicate that the 8-ring aggregates are bowl-shaped and highly fluxional, compared to the 12-ring aggregates, which are cylindrical. This work demonstrates that large π-systems can form surprisingly well-defined aggregates and may inspire the design of other noncovalent assemblies.

Thickness evaluation of organic coating using active long-pulse transmission thermography

The thickness of the optically translucent coating was evaluated using the transmission thermography. The transmitted temperature of a two-layer structure was theoretically analysed based on the equation of 1D heat transfer in the depth direction, and accordingly, the method for the measurement of coating thickness in a two-layer structure was established based on a long-pulse transmission thermography. The coating thickness was determined based on the characteristic time at the maximum half-rise temperature. Then, the proposed method was experimentally validated and calibrated by coating specimen with a different coating thickness. The thickness measurement method was further applied to measure an uneven coating specimen fabricated by mechanical grinding. The measurements were compared with a 3D digital image correlation method and the averaged relative error was less than 4%. Finally, thermal excitation, sampling rate of thermography and translucence of organic coating were discussed for accurate measurement.

A Study of Improved Two-Stage Dual-Conv Coordinate Attention Model for Sound Event Detection and Localization.

Sound Event Detection and Localization (SELD) is a comprehensive task that aims to solve the subtasks of Sound Event Detection (SED) and Sound Source Localization (SSL) simultaneously. The task of SELD lies in the need to solve both sound recognition and spatial localization problems, and different categories of sound events may overlap in time and space, making it more difficult for the model to distinguish between different events occurring at the same time and to locate the sound source. In this study, the Dual-conv Coordinate Attention Module (DCAM) combines dual convolutional blocks and Coordinate Attention, and based on this, the network architecture based on the two-stage strategy is improved to form the SELD-oriented Two-Stage Dual-conv Coordinate Attention Model (TDCAM) for SELD. TDCAM draws on the concepts of Visual Geometry Group (VGG) networks and Coordinate Attention to effectively capture critical local information by focusing on the coordinate space information of the feature map and dealing with the relationship between the feature map channels to enhance the feature selection capability of the model. To address the limitation of a single-layer Bi-directional Gated Recurrent Unit (Bi-GRU) in the two-stage network in terms of timing processing, we add to the structure of the two-layer Bi-GRU and introduce the data enhancement techniques of the frequency mask and time mask to improve the modeling and generalization ability of the model for timing features. Through experimental validation on the TAU Spatial Sound Events 2019 development dataset, our approach significantly improves the performance of SELD compared to the two-stage network baseline model. Furthermore, the effectiveness of DCAM and the two-layer Bi-GRU structure is confirmed by performing ablation experiments.

An Evaluation Model for Node Influence Based on Heuristic Spatiotemporal Features.

The accurate assessment of node influence is of vital significance for enhancing system stability. Given the structural redundancy problem triggered by the network topology deviation when an empirical network is copied, as well as the dynamic characteristics of the empirical network itself, it is difficult for traditional static assessment methods to effectively capture the dynamic evolution of node influence. Therefore, we propose a heuristic-based spatiotemporal feature node influence assessment model (HEIST). First, the zero-model method is applied to optimize the network-copying process and reduce the noise interference caused by network structure redundancy. Second, the copied network is divided into subnets, and feature modeling is performed to enhance the node influence differentiation. Third, node influence is quantified based on the spatiotemporal depth-perception module, which has a built-in local and global two-layer structure. At the local level, a graph convolutional neural network (GCN) is used to improve the spatial perception of node influence; it fuses the feature changes of the nodes in the subnetwork variation, combining this method with a long- and short-term memory network (LSTM) to enhance its ability to capture the depth evolution of node influence and improve the robustness of the assessment. Finally, a heuristic assessment algorithm is used to jointly optimize the influence strength of the nodes at different stages and quantify the node influence via a nonlinear optimization function. The experiments show that the Kendall coefficients exceed 90% in multiple datasets, proving that the model has good generalization performance in empirical networks.

Revealing the Relationship between Critical Inlet Velocity and a Double-Layer Oxide Film Combined with Low-Pressure Casting Technology

In the context of low-pressure casting, an excessive inlet velocity may result in the introduction of an oxide film and air into a liquid metal, leading to the formation of a two-layer film structure within the casting. Such defects can significantly degrade the mechanical properties of the castings. In order to optimize the advantages of low-pressure casting, an empirically designed equation for the inlet velocity was formulated and the concept of critical inlet velocity was further refined. A comprehensive numerical simulation was conducted to meticulously analyze the liquid metal spreading phase within the cavity. Subsequently, low-pressure casting experiments were carried out with actual castings of an A357 alloy, using two different entrance velocities—one critical and the other exceeding the critical entrance velocity. Tensile test specimens were extracted from the castings for the comparative evaluation of mechanical properties. It was observed that the average tensile strength of specimens cast at the critical inlet velocity exhibited a notable 16% enhancement. In contrast, specimens cast at velocities exceeding the critical inlet velocity manifested the presence of double oxide film defects. This evidence suggests that casting at a velocity faster than the critical inlet velocity leads to the formation of double oxide film defects, which in turn reduces the mechanical properties of the castings.

Mean-flow structures of the turbulent boundary layers bounding a two-dimensional separation bubble

Understanding the mean-flow structures of a separated turbulent boundary layer (TBL) is crucial for turbulence modeling. This study investigates the spatial scaling properties of the total shear stress and mixing length in the TBLs bounding a two-dimensional (2D) separation bubble, aiming to derive analytical descriptions for the entire mean-velocity profiles of the TBLs. For the adverse pressure gradient (APG) TBL upstream of the separation bubble, the total shear stress possesses a two-layer structure with an inner layer adhering to a linear law and an outer layer conforming to a defect power law. In contrast, the mixing length profile consists of four layers, namely the viscous sublayer, the buffer layer, the overlap layer, and the wake region. Each of the layers exhibits a power law or a defect power law relationship with the spatial coordinate normal to the wall. In the four-layer structure, three parameters are sensitive to the variation of the APG: the buffer-layer thickness, the relative magnitude of the mixing length at the boundary layer edge, and a defect power law exponent quantifying the extent of the wake region. For the reattached TBL downstream of the separation bubble, the total shear stress consists of two parts. One part is induced by the pressure gradient and retains the two-layer structure, while the other, engendered by the intense turbulence advected from the separated shear layer, exhibits a dual-power-law distribution. The advected turbulence also significantly alters the four-layer structure of the mixing length, resulting in an augmented buffer layer, a diminished overlap layer, and a wake region that mimics a turbulent mixing layer. Via a dilation ansatz to describe the scaling transition between adjacent layers, the study formulates the complete profiles of the total shear stress and mixing length. The formulation leads to the derivation of novel analytical expressions for the entire mean-velocity profiles of the TBLs. The expressions are in precise accord with the direct numerical simulations of an incompressible 2D separation-bubble flow and a 2D impinging shock wave/TBL interaction. The elucidation of the mean-flow structures through this study is anticipated to facilitate the analysis of turbulence models, thereby enhancing their performance in simulating separated TBLs. The construction of the mean-flow descriptions by inspecting the spatial scaling properties of turbulence paves a promising way for theoretical exploration of complex nonequilibrium TBLs.

Fabrication of composite nanostructures for impedance biosensors using anodic aluminum oxide templates and carbon nanotubes

A hybrid material consisting of an array of vertically ordered carbon nanotubes (CNTs) in porous anodic alumina was fabricated directly on oxidized Si substrates. Individual CNTs with vertical orientation were grown using the catalyst Ni nanoparticles (NPs) embedded in the pore walls of a thin template based on porous anodic alumina with a pore diameter of 40 ± 5 nm. The initial film was a two-layer Ti-Al structure on a Si/SiO2 substrate. A vertically oriented porous structure was formed by anodizing the Al layer. Electrochemical deposition was used to form the catalyst Ni-NPs with dimensions of 30 ± 5 nm. CNTs were synthesized by high-temperature chemical vapor deposition. Scanning and transmission electron microscopy, Raman spectroscopy, and X-ray diffraction were used to analyze the surface morphology and microstructure of the composite nanostructures. The CNT length was (0.6–1.5) μm, and the CNT spacing was 110 ± 10 nm. It is expected that the resulting structure will serve as a basis for the development of CNT-based electrodes for electrochemical impedance biosensors. Electrochemical impedance spectroscopy was used for the electrochemical characterization of the fabricated CNT-based electrodes. The results showed that the CNT-based electrodes are characterized by improved electron transfer kinetics.

SRCNN: Stacked-Residual Convolutional Neural Network for Improving Human Activity Classification Based on Micro-Doppler Signatures of FMCW Radar

Current methods for daily human activity classification primarily rely on optical images from cameras or wearable sensors. Despite their high detection reliability, camera-based approaches suffer from several drawbacks, such as low-light conditions, limited range, and privacy concerns. To address these limitations, this article proposes the use of a frequency-modulated continuous wave radar sensor for activity recognition. A stacked-residual convolutional neural network (SRCNN) is introduced to classify daily human activities based on the micro-Doppler features of returned radar signals. The model employs a two-layer stacked-residual structure to reuse former features, thereby improving the classification accuracy. The model is fine-tuned with different hyperparameters to find a trade-off between classification accuracy and inference time. Evaluations are conducted through training and testing on both simulated and measured datasets. As a result, the SRCNN model with six stacked-residual blocks and 64 filters achieves the best performance, with accuracies exceeding 95% and 99% at 0 dB and 10 dB, respectively. Remarkably, the proposed model outperforms several state-of-the-art CNN models in terms of classification accuracy and execution time on the same datasets.

A hyper-heuristic algorithm via proximal policy optimization for multi-objective truss problems

This paper proposes a hyper-heuristic evolutionary algorithm via proximal policy optimization, named HHEA-PPO, for solving multi-objective truss optimization problems. HHEA-PPO has a two-layer structure: a high-level strategy and low-level heuristics. The high-level strategy consists of proximal policy optimization, while the low-level heuristics consist of ten predefined heuristic operators. During the iteration process, the high-level strategy selects the most promising low-level heuristic according to the state of the individuals and the population. To maintain the convergence and distribution of the external Pareto archive, a dynamic crowding distance mechanism is employed. HHEA-PPO is applied to eight multi-objective truss optimization problems and compared with thirteen state-of-the-art optimization algorithms in terms of success rate, average computation duration, and average fitness evaluations to evaluate its performance. The results show that HHEA-PPO has higher search efficiency and greater stability, demonstrating its ability to solve large-scale engineering design problems.

Designing an OAM fiber with a two-layer seven-core structure to support 322 OAM-mode transmissions

In this paper, a two-layer seven-core structural fiber (TLSCSF) is proposed to support and improve the propagation of more orbital angular momentum (OAM) mode beams, thus increasing the transmission capacity and spectrum efficiency (SE) of an optical communication system. The TLSCSF is composed of seven sub-cores, each containing two inner and outer layers of core rings and a central air hole. The two core rings are prepared using two materials with different doping concentrations. The supported OAM modes can be propagated in the fiber core ring. A finite element method (FEM) is used to analyze the designed fiber, and the calculated results show that the TLSCSF can stably transmit 322 OAM modes without higher order radial modes in the wavelength range of 1.5∼1.6 um. The corresponding effective refractive index difference between two adjacent vector modes (HE/EH) is more than 10−4. The measured effective mode areas (Aeff) and the confinement losses (CL) of HE or EH modes are larger than 54 um2 and smaller than 10−10 dB m−1, respectively. Moreover, the calculated dispersion variations and the mode qualities are lower than 230 ps nm−1 km−1 and more than 90%, respectively. Finally, the 10ps walk-off lengths of all vector modes supported by TLSCSF at a wavelength of 1.55 um are also evaluated, where the measured results show that except for HE2,1 and EH1,1, all other modes achieve a 10ps walk-off length of the order of 103 to 105. Consequently, the TLSCSF can contributes to improving the channel capacity and SE by supporting 322 fundamental radial OAM modes with robust performances in an optical communication system.

Заметки о власти и её легитимности

The article examines three points of view on the nature of power, and the author believes that power, although it belongs to the social whole, is exercised by people and is therefore anthropologically determined. At the same time, he considers sociality within the framework of a cultural approach. Examples of historically early and later forms of awareness of power are analyzed. Based on this analysis, a concept of power and an explanation of its legitimacy are proposed. The author believes that the two-layer structure of power (socio-cultural structure (order) and anthropological basis) allows us to understand both its normal functioning and, so to speak, “deviant social deviations” (anomies). Examples of both are given. The ideas about power and legitimacy proposed by the author should be considered as ideal-typical constructions according to M. Weber. That is, these are diagrams that allow one to schematize empirical material and navigate it. When the researcher encounters new types of power, these schemes must be adjusted or new schemes must be introduced.

A Study on a Compact Double Layer Sub-GHz Reflectarray Design Suitable for Wireless Power Transfer

The paper presents a novel small-footprint varactor diode-based reconfigurable reflectarray (RRA) design and investigates its power reflection efficiency theoretically and experimentally in a real-life indoor environment. The surface is designed to operate at 865.5 MHz and is intended for simultaneous use with other wireless power transfer (WPT) efficiency-improving techniques that have been recently reported in the literature. To the best of the authors’ knowledge, no RRA intended to improve the performance of antenna-based WPT systems operating in the sub-GHz range has been designed and studied both theoretically and experimentally so far. The proposed RRA is a two-layer structure. The top layer contains electronically tunable phase shifters for the local phase control of an incoming electromagnetic wave, while the other one is fully covered by metal to reduce the phase shifter size and RRA’s backscattering. Each phase shifter is a pair of diode-loaded 8-shaped metallic patches. Extensive numerical studies are conducted to ascertain a suitable set of RRA unit cell parameters that ensure both adequate phase agility and reflection uniformity for a given varactor parameter. The RRA design parameter finding procedure followed in this paper comprises several steps. First, the phase and amplitude responses of a virtual infinite double periodic RRA are computed using full-wave solver Ansys HFSS. Once the design parameters are found for a given set of physical constraints, the phase curve of the corresponding finite array is retrieved to estimate the side lobe level due to the finiteness of the RRA aperture. Then, a diode reactance combination is found for several different RRA reflection angles, and the corresponding RRA radiation pattern is computed. The numerical results show that the side lobe level and the deviation of the peak reflected power angles from the desired ones are more sensitive to the reflection coefficient magnitude uniformity than to the phase agility. Furthermore, it is found that for scanning angles less than 50°, satisfactory reflection efficiency can be achieved by using the classical reactance profile synthesis approach employing the generalized geometrical optics (GGO) approximation, which is in accord with the findings of other studies. Additionally, for large reflection angles, an alternative synthesis approach relying on the Floquet mode amplitude optimization is utilized to verify the maximum achievable efficiency of the proposed RRA at large angles. A prototype consisting of 36 elements is fabricated and measured to verify the proposed reflectarray design experimentally. The initial diode voltage combination is found by applying the GGO-based phase profile synthesis method to the experimentally obtained phase curve. Then, the voltage combination is optimized in real time based on power measurement. Finally, the radiation pattern of the prototype is acquired using a pair of identical 4-director printed Yagi antennas with a gain of 9.17 dBi and compared with the simulated. The calculated results are consistent with the measured ones. However, some discrepancies attributed to the adverse effects of biasing lines are observed.

A clinical case of isolated non-compact left ventricular myocardium in a 29-year-old patient

BACKGROUND: Non-compact left ventricular myocardium is a rare heterogeneous pathology, which in the two-layer structure of the myocardium. There is no generally accepted definition of this form of pathology for both echocardiography and cardiac magnetic resonance imaging. Non-compact left ventricular myocardium can occur at any age and is often asymptomatic. Treatment of non-compact left ventricular myocardium is nonspecific and symptomatic. DESCRIPTION: This study describes a clinical case of a young patient who was diagnosed with non-compact left ventricular myocardium. The disease debuted in the form of cardiac arrhythmia. Holter monitoring showed frequent ventricular extrasystole and atrioventricular block of the first and second degrees. Moreover, echocardiography revealed a decrease in global contractile function of the left ventricle. The diagnosis was made after magnetic resonance imaging of the heart, which revealed the presence of non-compact myocardium of the anterior, lateral, and inferior walls of the left ventricle in the apical and middle segments. Sustained rhythm disturbances were not induced in electrophysiological research by rapid and programmed stimulation. The patient was prescribed antiarrhythmic therapy, followed by echocardiography Holter monitoring. In the future, the patient needs regular monitoring by a cardiologist. CONCLUSION: Non-compact left ventricular myocardium should be diagnosed at an early stage, so that life expectancy can be increased owing to timely treatment of heart failure and the use of oral anticoagulants, antiarrhythmic drugs, cardiac resynchronization therapy, cardioverter-defibrillator implantation, and heart transplantation when other treatment options are ineffective.

Plankton and benthos in Lake Blagodatnoye (Iturup Island) in summer

Lake Blagodatnoye is an oligohaline meromictic reservoir with the two-layer vertical structure — a typical lagoon lake for the southern Far East of Russia. Its upper layer is occupied by fresh water and the lower layer — by brackish water. The greatest warming of water (up to 22 оC) is observed at the lake surface in late July — early August. In total, 274 species are found in phytoplankton of the lake that is the largest number among all surveyed lagoon lakes in the south of Sakhalin-Kuril region. Bacillariophyta form the basis of the phytoplankton species composition (64 % of species). Abundance and biomass of the phytoplankton vary widely from 1.15 . 106 to 160.44 . 106 cells/L and from 0.41 to 6.14 g/m3, respectively. Several peaks are noted in seasonal dynamics of these indices. Zooplankton in the lake includes 25 species. All these species are typical for lagoon lakes in the south of Sakhalin-Kuril region. Wide variations in abundance and biomass are noted for the zooplankton: from 10550 to 99350 ind./m3 and from 47.1 to 231.0 mg/m3, respectively. Two types of species composition are identified in the summer succession of the phytoand zooplankton communities. The phytoplankton groups change at the border between June and July, when temperature at the surface passes the value of 14–16 оC. The key species of the early-summer phytoplankton are Cyanobacteria of genera Aphanocapsa, Chroococcus, Microcystis, Anabaena and Bacillariophyta of the genus Asterionella, whereas Aulacoseira granulata and A. granulata var. angutissima are the most abundant in late summer. For zooplankton, the boundary between the early-summer and late-summer seasons is shifted to middle July when the water temperature rises to 17–18 оC. Rotifera of Asplanchna priodonta, Cladocera of Bosmina sp., younger copepodites of Cyclops and Eurytemora caspica tethysiana dominate in early summer, whereas Bosmina sp. and juveniles of Cyclops — in late summer. Macrozoobenthos in the lake is represented by 25 species of invertebrates. The basis of species diversity is formed by amphibiotic insects. Number of species and total distribution density and biomass of macrozoobenthos mostly declined with the depth: there were 18 species, 370 ± 50 ind./m2, 3.023 ± 0.459 g/m2 in the intertidal zone, 14 species, 580 ± 59 ind./m2, 3.477 ± 0.447 g/m2 in the elittoral zone, and 10 species, 364 ± 36 ind./m2, 2.110 ± 0.248 g/m2 in the profundal zone, and dominant species were changed from Amphipoda Eogammarus barbatus in the intertidal zone to Chironomidae Chironomus dorsalis in the elittoral zone and to Gastropoda Cincinna japonica, Oligochaeta Lumbriculus variegatus and Chironomidae C. dorsalis in the profundal zone. The phytoplankton production in the coastal zone (depth of 0–3 m) was estimated as 552.86 kcal/m2 in June-August. Zooplankton consumed only 0.7 % of this production and produced 767 cal/m2. The production of non-predatory zoobenthos was 8644 cal/m2, with the inputs of 70.2 % for detritus feeders of 70.2 %, 11.8 % for macroalgae feeders, 11.6 % for deposit feeders, 5.8 % for grazers, and 0.6 % for filtered suspension feeders. A part of this production (6.9 %) was transmitted to the feed of carnivorous zoobenthos, so 8286 cal/m2 of the macrozoobenthos production could be used for fish feeding in the coastal zone. The phytoplankton production in the open waters (depth of 3–9 m) was estimated in 2580 kcal/m2. Zooplankton consumed 1.01 % of this production and produced 3578 cal/m2. The production of non-predatory zoobenthos in this zone was 6179 cal/m2 (detritus feeders 68.1 %, deposit feeders 18.8 %, grazers 6.6 %, macroalgae feeders 3.0 %, and filtered suspension feeders 3.5 %). The portion of 12.7 % of this production was transmitted to the feed of carnivorous zoobenthos. The total macrozoobenthos production in the open waters was 5708 cal/m2. The total reserve of food for fish, including zooplankton and benthos, was evaluated in 9286 cal/m2.

Integrative implementation of scattering reduction and radiation enhancement for an electrically small antenna by subwavelength plasmas

The integrative design of scattering and radiation characteristics of antennas is of great practical significance for modern wireless communication. In this work, from the perspective of separate and cooperative modes, we comprehensively discussed the possibility of simultaneously and harmoniously implementing scattering suppression and radiation enhancement for an electrically small antenna by subwavelength plasmas. For the separate mode where the two functions are decoupled based on a two-layer structure, it is shown that an overdense–underdense core–shell density profile is preferred to achieve the optimal synergism between radiation enhancement and plasmonic-cloaking-induced invisibility, where the angular frequency of detecting waves (ωd) is supposed to be lower than that of communication signals (ωc). For the cooperative mode where the two functions are coupled within one plasma shell, the collaborative strategies between plasmonic-cloaking/Fano-resonance-induced invisibility and radiation enhancement are analyzed. The results show that the plasmonic-cloaking type requires ωd > ωc, while for the Fano-resonance type, ωd is larger/less than ωc when radiation enhancement is dominated by the symmetrically/asymmetrically coupled plasmon modes. Also, we provided clearer perspectives to distinguish the physical differences between plasmonic-cloaking and Fano-resonance-induced invisibility and between radiation enhancement underlying the two modes. Our results provide promising solutions for designing next-generation plasma-based tunable and intelligent stealth antennas.

Different mechanisms for enhanced ocean response and feedback during sequential super typhoons

Relative to a single typhoon, the ocean response and feedback mechanisms during sequential super typhoon process have yet to be fully understood. The upper ocean responses to super typhoons Trami and Kong-Rey that occurred sequentially in autumn 2018 over the northwestern Pacific (NWP) Ocean were investigated using multi satellite and Argo float data. As a slow-moving typhoon, the location of maximum sea surface temperature (SST) cooling induced by Trami was determined by the typhoon's translation speed and the preexisting cyclonic eddy (CE). The most significant SST cooling was observed near the abrupt turning point, where Trami nearly stalled over the ocean, rather than in the CE region, although the CE could enhance the SST cooling. For the subsequent, fast-moving typhoon Kong-Rey, the most significant SST cooling was observed in the CE region. Two different mechanisms (i.e., slow translation and cyclonic eddy) for the enhancement of SST cooling, salinity and chlorophyll-a were also compared. For salinity and chlorophyll-a concentration, slow translation speed plays a more important role than the preexisting cold eddy. Additionally, both typhoons experienced rapid weakening, suggesting that typhoon-induced negative feedback affects not only the intensification of the typhoon itself but also the subsequent typhoon. An analysis of data from Argo floats demonstrated that weak mixing and upwelling contributed to a three-layer structure in the upper ocean temperature on the left side of the typhoon track; strong upwelling played a more important role in the cooling of the whole upper ocean near the typhoon track center; and strong vertical mixing was the dominant factor for the two-layer temperature structure on the right side.

Large-scale semi-organized rolls in a sheared convective turbulence: Mean-field simulations

Based on a mean-field theory of a non-rotating turbulent convection [T. Elperin et al., Phys. Rev. E 66, 066305, (2002)], we perform mean-field simulations (MFS) of sheared convection that takes into account an effect of modification of the turbulent heat flux by the non-uniform large-scale motions. This effect is caused by the production of additional essentially anisotropic velocity fluctuations generated by tangling of the mean-velocity gradients by small-scale turbulent motions due to the influence of the inertial forces during the lifetime of turbulent eddies. These anisotropic velocity fluctuations contribute to the turbulent heat flux. As the result of this effect, there is an excitation of large-scale convective-shear instability, which causes the formation of large-scale semi-organized structures in the form of rolls. The lifetimes and spatial scales of these structures are much larger compared to the turbulent scales. By means of MFS performed for stress-free and no-slip vertical boundary conditions, we determine the spatial and temporal characteristics of these structures. Our study demonstrates that the modification of the turbulent heat flux by non-uniform flows leads to a strong reduction of the critical effective Rayleigh number (based on the eddy viscosity and turbulent temperature diffusivity) required for the formation of the large-scale rolls. During the nonlinear stage of the convective-shear instability, there is a transition from a two-layer vertical structure with two rolls in the vertical direction before the system reaches steady-state to a one-layer vertical structure with one roll after the system reaches steady state. This effect is observed for all effective Rayleigh numbers. We find that inside the convective rolls, the spatial distribution of the mean potential temperature includes regions with a positive vertical gradient of the potential temperature caused by the mean heat flux of the convective rolls. This study might be useful for understanding the origin of large-scale rolls observed in atmospheric convective boundary layers, as well as in numerical simulations and laboratory experiments.

A lightweight deep learning-based android malware detection framework

Android, as the most prevalent mobile operating system (OS) in recent years, has been widely applied in various cell phones, tablets, and embedded devices, greatly facilitating people’s lives. However, Android malware is also emerging, which significantly endangers people’s information security. The current Android malware detection systems are often suffering from cumbersome structures and massive computational resources, which seriously limits their direct deployment on mobile devices. We design a lightweight Android malware detection system named MCADS, which consists of a two-layer structure. At the first layer, we use an augmented Multilayer Perceptron (MLP) for the preliminary analysis of malware. At the second layer, we propose a new lightweight variant of Convolutional Neural Network (CNN) to further analyze the Apps that cannot be accurately identified in the first layer. Finally, a careful experimental investigation has been conducted. The proposed method achieves an accuracy of 98.12%, surpassing that of the compared methods. The promising results demonstrate the potential of MCADS as a practical adjunctive solution for detecting malware, complementing existing complex detection methods.

Microbial interactions in mixed-species biofilms on the surfaces of Baijiu brewing environments

Environmental microorganisms commonly inhabit dense multispecies biofilms, fostering mutualistic relationships and co-evolution. However, the mechanisms underlying biofilm formation and microbial interactions within the Baijiu fermentation microecosystem remain poorly understood. Hence, the objective of this study was to investigate the composition, structure, and interactions of microorganisms residing in biofilms on environmental surfaces in Baijiu production. The results revealed a shift in the bacteria-fungi interaction network following fermentation, transitioning from a cooperative/symbiotic relationship to a competitive/antagonistic dynamic. Core microbiota within the biofilms comprised lactic acid bacteria (LAB), yeast, and filamentous fungi. From the environmental surface samples, we isolated two strains of LAB (Lactiplantibacillus pentosus EB27 and Pediococcus pentosaceus EB35) and one strain of yeast (Pichia kudriavzevii EF8), all displaying remarkable biofilm formation and fermentation potential. Co-culturing LAB and yeast demonstrated a superior capacity for dual-species biofilm formation compared to mono-species biofilms. The dual-species biofilm displayed a two-layer structure, with LAB in the lower layer and serving as the foundation for the yeast community in the upper layer. The upper layer exhibited a dense distribution of yeast, enhancing aerobic respiration. Metabolic activities in the dual-species biofilm, such as ABC transporter, oxidative phosphorylation, citric acid cycle, sulfur metabolism, glycine, serine, threonine metabolism, lysine degradation, and cysteine and methionine metabolism, showed significant alterations compared to LAB mono-species biofilms. Moreover, bacterial chemotaxis, starch, and sucrose metabolism in the dual-species biofilm exhibited distinct patterns from those observed in the yeast mono-species biofilm. This study demonstrated that a core microbiota with fermentation potential may exist in the form of a biofilm on the surface of a Baijiu brewing environment. These findings provide a novel strategy for employing synthetic stable microbiotas in the intelligent brewing of Baijiu.