Generation Mechanism Research Articles

Resonance of literati spirit and space: investigating the cultural atmosphere within traditional Chinese academy architecture

ABSTRACT Traditional Chinese academies have historically played a vital role in nurturing intellectual elites and preserving the literati spirit, with their architectural remnants continuing to imbue contemporary settings with a distinct cultural essence. This research aims to revisit and reinterpret the “literati ambiance” through a multidisciplinary lens, integrating literature research and case studies. It explores the nature and generative mechanisms of the cultural atmosphere inherent in traditional Chinese academy architecture, providing a new interpretation of constructing and experiencing this unique ambiance. By drawing on atmospheric aesthetics and the concept of Genius Loci, the study analyzes the interplay between the physical environment, human emotions, and cultural contexts in generating the literati ambiance. The findings enhance comprehension of this ambiance and offer insights into its conservation and dissemination. The research also addresses potential constraints and suggests areas for further study, including verification through case studies, cross-cultural comparisons, and detailed examinations of specific locations.

A Maneuver Coordination Analysis Using Artery V2X Simulation Framework

This paper examines the impact of Vehicle-to-Everything (V2X) communications on vehicle cooperation, focusing on increasing the robustness and feasibility of Cooperative, Connected, and Automated Vehicles (CCAVs). V2X communications enable CCAVs to obtain a holistic environmental perception, facilitating informed decision making regarding their trajectory. This technological innovation is essential to mitigate accidents resulting from inadequate or absent communication on the roads. As the importance of vehicle cooperation grows, the European Telecommunications Standards Institute (ETSI) has been standardizing messages and services for V2X communications, in order to improve the synchronization of CCAVs actions. In this context, this preliminary work explores the use of Maneuver Coordination Messages (MCMs), under standardization by ETSI, for cooperative path planning. This work presents a novel approach by implementing these messages as well as the associated Maneuver Coordination Service (MCS) with a Cooperative Driving System to process maneuver coordination. Additionally, a trajectory approach is introduced along with a message generation mechanism and a process to dynamically handle collisions. This was implemented in an Artery V2X simulation framework combining both network communications and SUMO traffic simulations. The obtained results demonstrate the effectiveness of using V2X communications to ensure the safety and efficiency of Cooperative Intelligent Transportation Systems (C-ITS).

Effects of variable blowouts on aerodynamic loss reduction performance of compressor bionic blades

Abstract A passive flow control method, inspired by blowouts, is employed to eliminate flow separation and reduced losses associated with higher compressor loads. By implementing bionic-blowout variant dimples on the blade suction surface, the flow characteristics of the dimple-shaped cascade were investigated. The loss generation mechanism was also analysed. Firstly, the reliability of the numerical method was confirmed through experimental validation. Subsequently, biomimetic principles were applied to arrange dimples on the suction surface of the cascade blades, and the effects of various blowouts were analysed The result revealed that vortices within the dimples induce external fluid into the dimples, enhancing the turbulent kinetic energy of the external fluid and improving wall-adjacent flow adherence. The bionic-blowout variant dimples creates a "rolling bearing" effect that reduces frictional losses, which control flow separation. Within a certain blowout range, the bionic-blowout variant dimples significantly improve the flow conditions. At -6° angle of attack, the total pressure loss of the dimple-structured cascade decreased by 35.85%, and the pressure ratio increased by 2.35%. The bionic-blowout variant dimples on the blade suction surface exhibit a three-dimensional disturbance effect. The induced vortex structures regulates the boundary layer transition and suppress the formation of laminar separation bubbles, effectively improving the flow conditions near the corner region.

Overlooked Generation of Reactive Oxidative Species from Water and Dioxygen by Far UV Light.

Far UV light at 222 nm (UV222) is gaining much attention for efficient water purification in UV222 irradiation and UV222-based advanced oxidation processes (AOPs). The direct photolysis of pollutants is regraded to be their major removal mechanism by a sole UV222 treatment. However, this paper reports the important roles of reactive oxidative species (ROS) generated from dioxygen and water under only UV222 radiation. Multiple ROSs are identified, including hydroxyl radical (HO·), singlet oxygen (1O2), superoxide radical anion (·O2-), and ozone (O3). HO· is the major ROS for the degradation of 18 organic micropollutants under UV222 radiation, with an observed quantum yield of 0.447 and the concentration of 10-13 M at pH 7. Dioxygen is the initial source of ROS, while water mainly serves as a medium to react with the photolytic intermediate of O3 (i.e., O(1D)) to form HO·. Water matrix components of HCO3- and natural organic matter can inhibit the HO· concentration, whereas NO3- significantly enhances it. In drinking water, UV222 alone removes 18 micropollutants more efficiently than the typical UV254/H2O2 AOP (150 μM), with reduced energy consumption. This study discloses a novel mechanism of ROS generation in UV222 irradiation and underscores UV222 as an emerging chemical-free AOP for water purification.

AB-LSTM: a mesoscale eddy feature prediction method based on an improved Conv-LSTM model

Mesoscale eddies are the most important mesoscale phenomena in the oceans, and determining how to predict their spatial and temporal characteristics is a very challenging task. Most previous studies focused on the accuracy of full-domain prediction and ignored the accuracy of single-eddy prediction. To solve this problem, in this paper, we first apply multi-year sea surface height data to produce a spatiotemporal sequence sample dataset with a bidirectional prediction mechanism. Then, we introduce an adversarial generative mechanism through stacked spatiotemporal prediction blocks and rely on the strong generative ability of the generative adversarial network models to construct an adversarial bidirectional long- and short-term memory model (AB-LSTM). Next, the mesoscale eddy mixing algorithm is used to extract the matching eddy pair features from the real and predicted data, and several evaluation metrics are used to conduct error analysis. The experiments yield the following results. Prediction sequence days 1–7: the root mean square error (RMSE) values are 1.97–7.70 cm, the structural similarity index (SSIM) values are >0.61, the accuracy is >54.6%, and the eddy centre distance error is 6.34 km. The result is 11.61 km, which is consistent with many spatiotemporal prediction models and passes the generalisation test in many different sea areas. Finally, we carry out single eddy prediction on the basis of the evaluation of the entire prediction of the sea surface height and also obtain a more satisfactory experimental effect. This method has a better prediction ability than the original spatiotemporal method and has a certain reference significance for mesoscale eddy spatiotemporal feature prediction technology and subsequent underwater reconstruction.

Linear control of lift in dragonfly vertical flight

Abstract The lift generation mechanisms of dragonflies have been extensively and deeply studied. As research advances, controlling the lift coefficient faces significant challenges. How the lift coefficient varies and whether a unified model can predict lift tendency remains unresolved. In this study, we propose a flapping amplitude partial advanced model (FAPAM) to control the linear variation of lift in dragonfly vertical flight. The FAPAM model can predict the average lift coefficient by the spatial plane and control the dragonfly lift coefficient over a large range. In this model, the maximum lift coefficient is 2.01 times higher than the weight of a dragonfly. The control parameters of the FAPAM are flapping amplitude (FA) and partial lead percent (PLP). Any linear combination of FA and PLP ensures a linear variation of the average lift coefficient. When FA and advanced rotation angle (ARA) increase by one degree, respectively, the increased lift coefficient of FA is 5.38~9.52 times higher than that of ARA, which is closely related to the leading-edge vortex, trailing-edge vortex, and positive pressure zone. The FAPAM model seamlessly integrates vertical ascending mode and vertical climbing mode by introducing transition mode. Additionally, FAPAM can effectively simulate the lift coefficient required for the vertical undulating motion of dragonflies during their oviposition process on water. Most importantly, the FAPAM model can maximize the energy efficiency of different motion modes.

Multilayered heterojunction-based zinc oxide nanoneedles/polyaniline/titania nanoparticles as a self-powered ultraviolet light photodetector

Nowadays, self-powered ultraviolet photodetectors (SPDs) with improved photoresponse features have attracted considerable attention due to their great pivotal applications in military and civilian fields. In the present work, for the first time, we investigate and report the construction and photoresponse features of a SPD based on multilayered heterojunction-based zinc oxide nanoneedles/polyaniline/titania nanoparticles (ZET). The structure, morphology, and optical properties of the ZET and its components were comprehensively investigated. A significant dependence was observed between the changes in I-V characteristics of the ZET-based SPD (SPZ) and the temperature change, resulting in a short reverse saturation current, proper ideality factor, and low dark current. I-V characteristics of the SPZ revealed nonlinear asymmetric rectifying behavior with the improved current under the influence and increase of power densities (PDiss) of ultraviolet (UV) light irradiation. Moreover, the self-powered feature of the SPZ was confirmed by the generation of short-circuit current and notable contrast ratio under UV light illumination at zero bias voltage. The device displayed remarkable photoresponsivity of 4.46A/W, high significant normalized detectivity of 63.1×1012Jones, good fill factor of 50.64%, and excellent external quantum efficiency of 1514% at the PDis of 0.77mW/cm2. In addition, the SPZ exposed a short rise time of 540 ms, a high maximum photocurrent of 99.9µA, and a significant gain dynamic range of 499.5 at PDis of 19.11mW/cm2. Finally, the imaginable mechanism of the current generation in our hand-made device was discussed in detail by exerting a standard thermionic emission-diffusion model and energy band diagram.

Shot noise as a diagnostic in the ν = 2/3 fractional quantum Hall edge zoo

The ν=2/3 filling is the simplest paradigmatic example of a fractional quantum Hall state, which contains counter-propagating edge modes. These modes can be either in the unequilibrated regime or equilibrated to different extents, on top of a possible edge reconstruction. In the unequilibrated regime, two distinct renormalization group fixed points have been previously proposed, namely Kane–Fischer–Polchinski and Wang–Meir–Gefen. In the equilibration regime, different degree of thermal equilibration may occur, while charge is fully equilibrated. Here, we show that this rich variety of models can give rise to three possible conductance plateaus at e2/2h (recently observed in experiments), 5e2/9h (predicted here), and e2/3h (observed earlier in experiments) in a quantum point contact geometry. We identify different mechanisms for electrical shot noise generation at these plateaus, which provides an experimentally accessible venue for distinguishing among the distinct models.

Barriers to and Facilitators of e-Learning Health Education Based on the Mental Workload Framework: A Scoping Review.

This scoping review of studies on patients' mental workload (MWL) in health education via e-learning was conducted to characterize the state of research and to identify barriers to and facilitators of e-learning. The Cochrane Library, PubMed, Embase, Web of Science, and PsycINFO electronic databases were searched through September 10, 2023. A descriptive analysis of study characteristics and a content analysis of barriers to and facilitators of MWL were conducted. Among the 2837 studies screened for eligibility, 38 were included. A relatively small number of articles used a comprehensive framework to explore barriers to and facilitators of e-learning or used indicators of MWL to assess application usability and user experience. Analyses of factors influencing the effectiveness of e-learning in health education identified key predictors across five domains: individual, task, technical, environmental, and interactive aspects. The incorporation of multifaceted influencing factors that contribute to optimizing the MWL should be a priority when using e-learning in health education. Future research should give more attention to investigating the generative mechanism of e-learning in health education to enhance targeted program design.

Characterizing interactive compound flood drivers in the Pearl River Estuary: A case study of Typhoon Hato (2017)

Tropical cyclone (TC) induced compound floods involve dynamic interactions among astronomical tides, storm surges, precipitation, and associated river pulses. This study employs a one-way coupled WRF, Delft3D, and HEC-RAS model to investigate the impacts of oceanic, pluvial, and fluvial processes on compound flood dynamics during Typhoon Hato (2017) in the Pearl River Estuary (PRE), South China. Total water levels driven by different combinations of flood drivers are modeled and analyzed. Relative contributions of each type of flood driver are quantified and used to categorize flood zones. This study highlights the persistent impacts of storm surges and their nonlinear interactions with other flood drivers. They can modify both the timing and magnitude of maximum water levels, thereby distorting tidal signals and contributing to post-TC landfall water level peaks. Along coastal regions, water levels exhibit three successive peaks, predominantly driven by storm surge, rainfall, and the combined actions of both factors, respectively. In upstream regions and coastal areas sheltered from islands, a singular water level peak arises exclusively from rainfall-runoff processes. Moreover, nonlinear interactions between surge and rainfall-runoff have non-negligible impacts on the relative contribution of individual flood drivers, which underscores the necessity of considering both rainfall and storm surge in modeling compound flood water levels. During the flooding period, peak storm surge and the following peak rainfall resulted in a time-varying distribution of flood zones. Alternating feedback between compounded and ocean-dominant areas manifests in the midsections of the upper PRE. Maximum flooding depth, extent, and duration are mainly influenced by rainfall. Storm surges play a secondary role, causing intense but short-lived flooding in coastal regions. These findings aid in understanding the generation mechanism of compound floods and provide references for hazard mitigation strategies.

The generation mechanism of cutting heat and the theoretical prediction model for temperature on the rake face of the cutting tool in Zirconia ceramics

Cutting temperature and its distribution are crucial factors influencing tool strength and wear rate, due to the hardness and brittleness of Zirconia (ZrO2) ceramics, significant challenges arise in both direct temperature measurement in the cutting zone and theoretical analysis of cutting heat. Thus, focusing on the turning characteristics of ZrO2 ceramics, this study analyzes the mechanism of cutting heat generation and proposes utilizing thermodynamic state equations to determine the cutting heat source on rake face of tool. Based on the heat source method, a theoretically prediction model for temperature distribution on rake face is established. This model considers primary cutting parameters, workpiece material properties, crack fracture characteristics of the machined surface, and thermal characterizations of the tool material. The relationship between tool wear and cutting temperature is experimentally analyzed to determine the characteristic temperature that indicates the initial stage of tool wear. The validity of the theoretical model is verified, as the predicted results show high consistency with experimental results within the range of experimental parameters, with a relative error within 15.2 %.The results reveal the highest temperature during brittle cutting occurs within the cutting layer area, with the highest temperature occurring approximately 50 μm from the tool tip, followed by a gradual decrease beyond 150-200 μm. This study also demonstrates that cutting heat in ceramic turning does not solely originate from friction heat between tool flank-workpiece but also includes impact heat from tool rake face-workpiece, which under certain cutting parameters exerts a more significant influence on cutting temperature. This model can facilitate the selection and optimization of cutting process parameters for brittle materials and provide a theoretical basis for analyzing the relationship between tool thermal damage, thermophysical properties, and tool wear.

Cryptography based on Fingerprint Bio Metrics

Fingerprints remain consistent and stable throughout a human’s lifetime. This research exhibits the utilization of fingerprint bio-metrics to generate secured keys for improved security. The main contribution is the generation of 87 keys, achieved by enhancing the fingerprint image and sharpening it with a Laplacian filter. Three types of geometrical shapes chosen arbitrary, such as circle, square, and triangle, are separately drawn on the fingerprint after binarization, morphological operations, and thinning. Each shape is drawn five times on the fingerprint with different radii for each type to increase the number of keys. The end and bifurcation points are extracted as features inside and outside these shapes and these features are considered as keys. Chaotic-Pseudo-Random-Number Generator (CPRNG) technique is used, and the generated keys are merged with those generated from the positions of minutiae (end and bifurcation) points. The process was implemented using MATLAB R2021b. The simulation results demonstrate that it is difficult to crack the keys generated by this technique because the attacker requires a very long time, almost 7.5595e+159 years, to decrypt the encrypted message. Using geometrical shapes and CPRNG) technique increases the number of keys. The contribution of 87 keys is raising the time needed to break the encrypted text to this time, which is greater than the time required to crack the keys generated in some previous research compared to them. Therefore, the proposed technique enhances privacy and security. It can be used via deep learning in fingerprint identification, recognition, and key generation mechanisms and can use any other geometrical shapes.

Quantifying and predicting evolutionary networks

The process of network evolution is typically characterized by the emergence of topological structures and the intricate interplay between determinism and stochasticity. Our work introduces a novel structural analysis framework to observe fluctuations in the network evolution process, profoundly influenced by the underlying network generation mechanisms. Based on theoretical reasoning and empirical examination, utilizing synthetic, static, and temporal networks, we arrive at two principal conclusions. Firstly, we reveal that the degree and distance distributions of networks exhibit two dynamic phenomena, convergence and divergence on high- and low-frequency curves, depend on the reflections of the network generation mechanism at both topological extreme values and the overall distribution. Secondly, we develop a novel link prediction method based on the convergence of topological fluctuations, which significantly outperforms benchmark algorithms in both real static and temporal networks. These findings are of considerable significance to the study of real network evolution mechanisms, contributing to a more comprehensive understanding of network behavior over time.

THz generation by exchange-coupled spintronic emitters

The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintronic THz emitters separated by a thin (tCr≤ 3nm) wedge-shaped Cr spacer. In such an arrangement, magnetization alignment of the two Fe films can be controlled by the interplay between Cr-mediated interlayer exchange coupling (IEC) and an external magnetic field. This in turn results in a strong variation of the THz amplitude A, with A↑↓ reaching up to 14 times A↑↑ (arrows indicate the relative alignment of the magnetization of the two magnetic layers). This observed functionality is ascribed to the interference of THz transients generated by two closely spaced THz emitters. Moreover, the magnetic field dependence A(H) shows a strong asymmetry that points to an additional performance modulation of the THz emitter via IEC and multilayer design.

A new data-driven production scheduling method based on digital twin for smart shop floors

As a mainstream means for solving smart shop floor production scheduling problems, the data-driven scheduling method has gained considerable attention in recent years. However, extant studies have primarily utilized physical shop floor data with limited quantity and quality to train scheduling models, which suffer from the drawbacks of long training time and poor scheduling performance. Therefore, this study proposes a new data-driven scheduling method based on digital twin for smart shop floors, which utilizes the data from physical shop floor and digital shop floor constructed by digital twin to train scheduling models. Specifically, in this method, a model-level data fusion mechanism is designed to achieve the fusion and complementary advantages of these two types of data, thus providing sufficient and high-quality data support for high-precision model training. Additionally, a multi-layer feedforward neural network with a generative adversarial network-based sample expansion mechanism is further integrated to efficiently generate scheduling decisions. Experiments in a semiconductor production shop floor are conducted to confirm the effectiveness of the proposed method.

Symmetric Dopant-Free Si Solar Cells Enabled by TiOx Nanolayers: An In-Depth Study on Bipolar Carrier Selectivity.

High-efficiency solar cells require two contact structures, engineered for efficient extraction of photogenerated holes and electrons at the respective electrodes. Herein, crystalline Si solar cell featuring hole- and electron-selective passivating contacts composed entirely of a single material, amorphous titanium oxide (TiOx), without extrinsic doping is demonstrated. The hole/electron selectivity of the TiOx layers (≈5 nm) is tailored by the oxidation process and the choice of Ti precursor in the atomic layer deposition (ALD). Ex situ and in situ X-ray photoelectron spectroscopy measurements elucidate that the hole-selective TiOx induces significant band bending in the Si (Φ≈0.7 eV), generating a p-type inversion layer in the n-Si absorber. The electron-selective TiOx induces a smaller band bending of Φ<0.35 eV. This clarifies that the bipolar carrier selectivity of TiOx is associated with the different amount of negative fixed charges generated during the ALD process, depending on the choice of Ti precursor and oxidant. In addition, the growth of a hydrogen-containing SiOy nanolayer (≈1-1.5 nm) at the Si/TiOx interface during postdeposition oxidation is crucial for providing chemical passivation in both types of TiOx. These findings pave the way for a deeper understanding of the charge generation mechanism and chemistry at the Si/metal oxide interfaces.

Numerical simulation of YSO jet collimated by toroidal magnetic fields and radiative cooling effect

Abstract The mechanism of generation and collimation of YSO jets remains an unsolved problem and is a research hotspot in contemporary astrophysics. Here, we conducted a two-dimensional (2D) cylindrical coordinates simulation experiment using radiative magnetic-hydro-dynamic FLASH code and systematically analyzed the effects of toroidal magnetic fields generated by Biermann Battery term and radiative cooling effect on jet evolution. In the simulation, strong toroidal magnetic fields are generated at the boundary of the plasma flow. A comparison of jets generated in different cases indicates that the magnetic fields play a significant role in hydrocarbon (CH) plasma jet collimation, surpassing the impact of radiative cooling effects. Additionally, it is observed that the magnetic fields can alter knots velocities. This platform provides a way to investigate the role of toroidal magnetic fields in jet evolution without external devices and provides a better understanding of the evolution of protostellar jets.

A Review of Adversarial Attacks and Defense Techniques in Text Processing Models

Abstract. With the rise of neural networks, the need for accuracy, robustness, and security has increased. Research has shown that small, carefully crafted perturbations, known as adversarial examples, can deceive models and lead to incorrect predictions. Current research focuses on the image domain, while there is a notable lack of exploration in the text domain, due to its discrete nature. This paper reviews adversarial attack techniques and defense strategies in text-based neural network models, aiming to improve the security and resilience of these models in practical applications. Adversarial examples, which can deceive models with small perturbations, expose vulnerabilities in their robustness and security. Techniques such as TextFooler focus on synonym replacement for generating adversarial examples, while Text Random Smooth (Text-RS) enhances defense through adaptive noise strategies. The research of search space aims to explore the feature of that, proposing search space for Imperceptibility (SSIP) and Search Space for Effectiveness (SSET) to estimate the different attack methods. Furthermore, the Chinese Variation Graph Integration (CHANGE) method improves the resilience of Chinese language models by leveraging variation graphs. These advancements highlight the importance of developing effective generation and defense mechanisms for adversarial examples in text processing models. Future research should enhance adversarial example techniques, explore efficient defense strategies, and investigate transferability to improve the security and robustness of text processing models.

Mechanistic Insights into Oxygen-Independent DNA Photodegradation by Pheophorbide a: Implications for Future Photodynamic Therapy Applications.

This study explores the unique properties of Pheophorbidea(Pheda) in the photodegradation of G-quadruplex DNA under anoxic conditions, emphasizing its potential for photodynamic therapy (PDT) in hypoxic tumor environments. We used electron spin resonance (ESR), circular dichroism (CD), and nuclear magnetic resonance (NMR) spectroscopies to assess the radical generation and DNA interaction capabilities of Phedacompared to Pyropheophorbidea(Pyroa) under both oxygenated and anoxic conditions. Our results reveal that Phedaeffectively degrades G-quadruplex DNA in the absence of oxygen, whereas Pyroadoes not. Under anoxic conditions, Phedagenerates unique carbon-centered radicals, as indicated by distinctive ESR signals, which are not observed in aerobic environments or with Pyroa. These radicals facilitate DNA decomposition without relying on reactive oxygen species (ROS). Pheda's ability to degrade DNA independently of oxygen underscores its potential as a versatile and effective PDT agent, especially for hypoxic tumors where traditional photosensitizers are ineffective. This study paves the way for the development of new PDT agents that can operate under different oxygen levels. Pheda's radical generation and oxygen-independent DNA degradation mechanisms make it a promising candidate for future PDT applications.

Electrochemically monitored electron transport for wide-bandgap oxides and enhanced antibacterial ROS production

Metal-loaded semiconductor nanomaterials have been extensively studied for years as excellent photocatalytic antibacterial materials, efficiently catalyzing the production of reactive oxygen species (ROS). However, the precise antibacterial mechanism and pathway of ROS generation for metal-loaded wide-bandgap oxides, which exhibit excellent antibacterial efficacy under dark conditions, are still not fully understood. In order to elucidate their antibacterial mechanisms, Ag-loaded MgO is synthesized to verify an increase in the electron density at the interface of the composite and enhanced electron transfer capability, facilitating the formation of ROS, supported by theoretical reasoning and experimental validation. Furthermore, the innovative electrochemical testing system links the electrochemical performance of antibacterial materials with their antibacterial properties, and monitoring the electron transfer pathways between the materials and bacteria. The synergistic antibacterial activity of affinity contact between MgO and the electron transfer effect of Ag-MgO results in a 99.99 % contact-killing effect against Escherichia coli (E. coli) within 5 min. Our work has made significant progress in understanding the ROS generation mechanism of wide-bandgap oxides under dark conditions, and has proposed new insights into electrochemical monitoring of the electron transfer characteristics of antibacterial materials.