Model Experiments Research Articles

Influence of Selenium on the Yield and Content of the Amino Acid Composition of Spring Wheat Grain under Optimal Conditions of Water Supply and during Drought

In model experiments in soil culture, the effect of various methods of applying sodium selenite on the formation of yield and amino acid composition of grain varieties of spring wheat Zlata and Ester, depending on water supply conditions, was studied. Sodium selenite was introduced by pre-sowing seed treatment and leaf treatment of vegetative plants. The study simulated optimal water supply conditions and soil moisture deficiency during the critical period of plant growth. The role of selenium in the regulation of the production process and the formation of the amino acid composition of spring wheat grain was studied. It was found that the production process of wheat plants, both under optimal water supply and in drought conditions, depended on the method of application of selenium and the varietal characteristics of spring wheat. The results allowed us to assume that selenium activated the attenuating ability of the ear by enhancing its acceptor properties. Under these conditions, the grains were better provided with assimilates. this made it possible to form the maximum possible yield of wheat grain. In conditions of drought, during leaf treatment of plants with sodium selenite, favorable conditions were created for the formation of reproductive organs of wheat, which stimulated the restoration of the processes of assimilate outflow from the vegetative mass into the forming grains. This made it possible to influence production processes and reduce the depression of wheat crop formation. The use of selenium revealed an increase in the total content of key amino acids, which had a significant effect on the antioxidant status of plants and contributed to the realization of their adaptive potential. The positive effect of selenium on the content of a number of amino acids, including on the assimilation of methionine, was revealed, which was probably due to the synthesis of selenomethionine, since the ways of their formation are similar and it is not possible to separate them. The greatest effect of selenium was observed in the cultivation of wheat of the Zlata variety compared with wheat of the Ester variety, which was determined by varietal differences inherent genetically and the unequal protein content in the grain.

Software installation threat detection based on attention mechanism and improved convolutional neural network in IOT platform

With of the Internet of Things (IoT) developing and the network technique progressing, malware attacks continue to occur, seriously endangering the information and property security of Internet of Things device users. To ensure the security of the Internet of Things platform and improve the efficiency of malware and vulnerability detection, a software installation threat detection model based on attention mechanism and improved convolutional neural network is constructed. Firstly, the enhanced dynamic symbolic execution module and forward program slicing algorithm are used to extract dynamic features, and then the improved convolutional neural network is utilized to classify malware. In the existing software of IoT devices, the inlining correlation function is studied using the inlining strategy, and the weight between the target pixel and the global pixel is calculated using the attention mechanism, through which the logic and correlation between the triples are correlated. Then, deep residual network is used to detect software vulnerabilities. This enables threat detection before and after software installation. In comparison with the current popular vulnerability detection model experiments, the accuracy, recall rate, accuracy rate and running time of the constructed model in the process of vulnerability detection are 0.975, 0.970, 0.968 and 0.02 s, respectively. Compared with other models, the research design model has better performance. This shows that this built model can effectively detect software installation threats, and has high detection accuracy and operation efficiency, which can provide strong support for the Internet of Things platform’s security protection.

Helmert variance component estimation for mixed additive and multiplicative random error model

Abstract With the development of surveying and mapping science, the object of measurement adjustment has been extended from a single observation of the same kind in the past to different precisions of the same kind, or different kinds of observations. There are additive and multiplicative errors related to electronic instrument measurements, which affect the quality of the adjustment results. A single additive error model is difficult to meet the accuracy requirements, so a mixed additive and multiplicative random error model (MAMREM) is needed. Aiming at the problem of inaccurate MAMREM stochastic model, this paper proposes Helmert Variance Component Estimation (VCE) to determine the weight matrix in different types of observations under MAMREM. In this paper, the formula and iterative algorithm of Helmert variance component estimation applied to MAMREM are derived, and the weights of different kinds of observations in the adjustment process are estimated. In order to verify the effectiveness of the method, the digital elevation model experiment and the side network experiment are used to verify the method. The results prove the effectiveness of the method.

Laboratory Study on Wave Attenuation by Elastic Mangrove Model with Canopy

This study evaluates the effectiveness of artificial Kandelia obovata forests in wave attenuation through physical model experiments conducted in a wave flume. The experiments meticulously replicated real-world hydrodynamic conditions and mangrove movement responses using the principles of gravitational and motion similarity, with a scaled 1:10 model of Kandelia obovata. Our approach included comparative experiments against a 1:100 gradient concrete slope to isolate the effects of seabed friction and flume wall reflections. The wave height was measured using strategically placed wave gauges. The findings indicated that the artificial Kandelia obovata forests significantly attenuated waves, with a decrease in the total attenuation capacity as the water depth increased from 2.75 m to 3.28 m under both regular and irregular waves. The elastic mangrove model with a canopy effect led to a 15% increase in wave attenuation over cylindrical models. Predictive models using multivariate nonlinear regression and back propagation neural networks showed that the latter provided a superior accuracy in estimating wave transmission coefficients

Interdecadal changes and the role of Philippine Sea convection in the intensification of Indian spring heatwaves

Abstract Severe heatwaves have become increasingly frequent over the Indian subcontinent in recent decades. This study found that the increase in extreme heatwaves is related to a significant decadal change in surface temperatures over the Indian subcontinent, and revealed that the increase in convective activity in the Philippine Sea plays a crucial role in this decadal change in surface temperature. Specifically, the surface temperature over the Indian subcontinent in spring has increased significantly by approximately 0.64°C in recent years (1998–2022: post-1998) compared to the past (1959–1997: pre-1998), leading to more intense and frequent heatwaves, particularly in March and April. The difference in atmospheric changes between these two periods shows that the enhancement of convective activity over the Philippine Sea drives an anomalous elongated anticyclonic circulation over the Indian subcontinent. This circulation pattern, marked by clearer skies and increased incident solar radiation, significantly contributes to the heat extremes in the Indian subcontinent. Additionally, stationary wave model experiments demonstrate that local diabatic heating over the Philippine Sea is significantly linked to robust spring Indian heatwaves through the Matsuno-Gill response.

Analysis of Factors Influencing Tunnel Block Collapse in Blocky Rock Masses: Insights from Large-Scale Model Experiments and DDA Simulations

Analysis of Factors Influencing Tunnel Block Collapse in Blocky Rock Masses: Insights from Large-Scale Model Experiments and DDA Simulations

Dynamic Response Characteristics of Foundation of Mined-out Areas under High-speed Railway Load

To reveal the dynamic response characteristics of the foundation of mined-out areas (MOA) under the high-speed railway (HSR) load is important for predicting settlement and safety assessment of the foundation. Taking MOA of Dianshang under the Taiyuan-Jiaozuo HSR as the engineering background, the model experiments and numerical analysis were employed to reveal the dynamic response of both subgrade and the foundation of the HSR, as well as the attenuation law of the acceleration in the overlying strata of the MOA. Results show that within the full frequency range of the HSR load, the dynamic response of the foundation increases with the increase in load frequency. When the depth exceeds 6 m, the dynamic response of the foundation initially increases and subsequently decreases with the increase in load frequency. Contrasted with single-point loading, the superposition effect and moving effect of the HSR load will form a dynamic response superposition zone within 1-4 m below the subgrade, leading to a significant enhancement of the dynamic response of the foundation. Compared to HSR axle load, the driving speed of HSR has a greater impact on the acceleration of both the subgrade and foundation. The obtained conclusions provide a reference for the safety operation of the HSR crossing the MOA

Occurrence and trends of historical tropical cyclone rainfall on near-coastal regions of Australia

Extreme rainfall driven by tropical cyclones (TCs) has profound effects on Australian coastlines at both local and regional scales. Here, we develop methods for comparing TC-driven widespread and localised rainfall on three broad coastal regions of tropical Australia (west, north and east). Trends, average recurrence intervals (ARIs) and the fractional contribution of TC rainfall are explored in three historical datasets: Australian Gridded Climate Data (AGCD), ECMWF Reanalysis (ver. 5, ERA5) and the Bureau of Meteorology Atmospheric high resolution Regional Reanalysis for Australia (ver. 1, BARRA1). Results for trends and ARIs between the different datasets are generally inconsistent and also differ between regions, partially owing to the short-term temporal records of some of the data as well as inconsistencies in extreme values between datasets. By contrast, there is a general agreement between all datasets on the fractional contribution of TC rainfall, signalling an increase in recent years. This result is considered together with the trend towards fewer TCs occurring in this region over recent decades, indicating a trend towards increased rainfall intensity per TC on average, assuming steady landfall rates. The methods developed here can be applied easily to other data types such as regional climate model experiments, facilitating a multiple lines of evidence approach that incorporates both observational-based and model-based data. This research is intended to help provide new methods and guidance for identifying trends in TC-driven extreme rainfall, relevant for enhanced planning and adaptation to the impacts of these extreme weather systems.

Active species in chloroaluminate ionic liquids catalyzing low-temperature polyolefin deconstruction

Chloroaluminate ionic liquids selectively transform (waste) polyolefins into gasoline-range alkanes through tandem cracking-alkylation at temperatures below 100 °C. Further improvement of this process necessitates a deep understanding of the nature of the catalytically active species and the correlated performance in the catalyzing critical reactions for the tandem polyolefin deconstruction with isoalkanes at low temperatures. Here, we address this requirement by determining the nuclearity of the chloroaluminate ions and their interactions with reaction intermediates, combining in situ 27Al magic-angle spinning nuclear magnetic resonance spectroscopy, in situ Raman spectroscopy, Al K-edge X-ray absorption near edge structure spectroscopy, and catalytic activity measurement. Cracking and alkylation are facilitated by carbenium ions initiated by AlCl3-tert-butyl chloride (TBC) adducts, which are formed by the dissociation of Al2Cl7− in the presence of TBC. The carbenium ions activate the alkane polymer strands and advance the alkylation cycle through multiple hydride transfer reactions. In situ 1H NMR and operando infrared spectroscopy demonstrate that the cracking and alkylation processes occur synchronously; alkenes formed during cracking are rapidly incorporated into the carbenium ion-mediated alkylation cycle. The conclusions are further supported by ab initio molecular dynamics simulations coupled with an enhanced sampling method, and model experiments using n-hexadecane as a feed.

Traction-separation law parameters for the description of age-related changes in the delamination strength of the human descending thoracic aorta.

Aortic dissection is a life-threatening disease that consists in the development of a tear in the wall of the aorta. The initial tear propagates as a discontinuity leading to separation within the aortic wall, which can result in the creation of a so-called false lumen. A fatal threat occurs if the rupture extends through the whole thickness of the aortic wall, as blood may then leak. It is generally accepted that the dissection, which can sometime extend along the entire length of the aorta, propagates via a delamination mechanism. The aim of the present paper is to provide experimentally validated parameters of a mathematical model for the description of the wall's cohesion. A model of the peeling experiment was built in Abaqus. The delamination interface was described by a piecewise linear traction-separation law. The bulk behavior of the aorta was assumed to be nonlinearly elastic, anisotropic, and incompressible. Our simulations resulted in estimates of the material parameters for the traction-separation law of the human descending thoracic aorta, which were obtained by minimizing the differences between the FEM predictions and the delamination force given by the regression of the peeling experiments. The results show that the stress at damage initiation, Tc, should be understood as an age-dependent quantity, and under the assumptions of our model this dependence can be expressed by linear regression as Tc = - 13.03·10-4·Age + 0.2485 if the crack front advances in the axial direction, and Tc = - 7.58·10-4·Age + 0.1897 if the crack front advances in the direction of the aortic circumference (Tc [MPa], Age [years]). Other model parameters were the stiffness K and the separation at failure, δf-δc (K = 0.5MPa/mm, δf-δc = 0.1mm). The material parameters provided by our study can be used in numerical simulations of the biomechanics of dissection propagation through the aorta especially when age-associated phenomena are studied.

Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed.

Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop control that effect powerful causal interventions. At the same time, improved computational models are capable of reproducing behavior and neural activity with increasing fidelity. Unfortunately, these advances have drastically increased the complexity of integrating different lines of research, resulting in the missed opportunities and untapped potential of suboptimal experiments. Experiment simulation can help bridge this gap, allowing model and experiment to better inform each other by providing a low-cost testbed for experiment design, model validation, and methods engineering. Specifically, this can be achieved by incorporating the simulation of the experimental interface into our models, but no existing tool integrates optogenetics, two-photon calcium imaging, electrode recording, and flexible closed-loop processing with neural population simulations. To address this need, we have developed Cleo: the Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed. Cleo is a Python package enabling injection of recording and stimulation devices as well as closed-loop control with realistic latency into a Brian spiking neural network model. It is the only publicly available tool currently supporting two-photon and multi-opsin/wavelength optogenetics. To facilitate adoption and extension by the community, Cleo is open-source, modular, tested, and documented, and can export results to various data formats. Here we describe the design and features of Cleo, validate output of individual components and integrated experiments, and demonstrate its utility for advancing optogenetic techniques in prospective experiments using previously published systems neuroscience models.

Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture

The innovative aquaculture equipment known as high-density polyethylene (HDPE) floating rafts has gained popularity among fishermen in the southeast coastal regions of China. Compared to deep-water anti-wave fish cages, the construction costs of HDPE floating rafts are 50% to 75% less. There is a dearth of comprehensive publicly available records of HDPE floating rafts sea trial data, despite substantial numerical studies on the motion response of aquaculture fish cages and scale model experiments under controlled-wave conditions. This study involves sea trial techniques under operational and extreme environmental conditions for motion responses of HDPE floating rafts, presents a comprehensive procedure for sea trials of HDPE floating rafts, summarizes the issues encountered during the trials, and suggests solutions. Using MATLAB for independent programming, motion videos and photos collected from the sea trials are processed for image capture, yielding the original time history curve of vertical displacement. Based on the sea trials’ data, including motion displacement, acceleration, mooring line force, overall deformation patterns, and current and wave data, recommendations are provided for the design and layout of HDPE floating rafts. Based on the Fast Fourier Transform (FFT) method for spectral analysis, the influence of interference items on the observational data is eliminated; the rationality of the observational data is verified in conjunction with the results of the Gabor Transform. This study offers a scientific analytical method for the structural design and safe operation of HDPE floating rafts and provides a reference for subsequent numerical simulations.

Past and Future Trends in Clear‐Air Turbulence Over the Northern Hemisphere

AbstractClear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is not detectable due to a weak signal to noise ratio related to large internal variability. Future climate projections show that over several Northern Hemisphere regions, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and different results between the various CAT diagnostics.

Nonlinear similarity characterisation and validation of dynamic response of ship stiffened plate structure under explosion load impacts

The similarity test of ship stiffened plate structures under underwater explosions is a cost-effective and efficient method to evaluate the vitality of ships and guide the design of their shock resistance. This study focuses on the nonlinear impact response model tests of ship stiffened plate structures and their similarity laws with actual ships. The vertical motion of the ship stiffened plate structure is characterized by the Hurst index, and an equivalent relationship between the Hurst index of the model and the prototype is derived from classical similarity law. Based on the Hurst index, a similarity transformation relationship between the strain signals of the model and prototype is established. To verify the conclusions, similarity experiments of underwater explosions were conducted on both the model and the prototype. The original signals were grouped by the natural vibration period to determine the variation of the Hurst index over time. The model experiment strain signals for each natural vibration period were converted and compared with the prototype experiment results to verify the method's effectiveness. Simultaneously, the Hurst index of the stiffened plate structure under explosive shock load and its similarity transformation relationship with the prototype were simulated and analyzed. This provides theoretical and technical support for conducting analogous nonlinear response experiments for ship underwater explosions.

Nonlinear similarity characterisation and validation of dynamic response of ship stiffened plate structure under explosion load impacts

The similarity test of ship stiffened plate structures under underwater explosions is a cost-effective and efficient method to evaluate the vitality of ships and guide the design of their shock resistance. This study focuses on the nonlinear impact response model tests of ship stiffened plate structures and their similarity laws with actual ships. The vertical motion of the ship stiffened plate structure is characterized by the Hurst index, and an equivalent relationship between the Hurst index of the model and the prototype is derived from classical similarity law. Based on the Hurst index, a similarity transformation relationship between the strain signals of the model and prototype is established. To verify the conclusions, similarity experiments of underwater explosions were conducted on both the model and the prototype. The original signals were grouped by the natural vibration period to determine the variation of the Hurst index over time. The model experiment strain signals for each natural vibration period were converted and compared with the prototype experiment results to verify the method's effectiveness. Simultaneously, the Hurst index of the stiffened plate structure under explosive shock load and its similarity transformation relationship with the prototype were simulated and analyzed. This provides theoretical and technical support for conducting analogous nonlinear response experiments for ship underwater explosions.

Past and Future Trends in Clear‐Air Turbulence Over the Northern Hemisphere

AbstractClear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is not detectable due to a weak signal to noise ratio related to large internal variability. Future climate projections show that over several Northern Hemisphere regions, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and different results between the various CAT diagnostics.

Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture

The innovative aquaculture equipment known as high-density polyethylene (HDPE) floating rafts has gained popularity among fishermen in the southeast coastal regions of China. Compared to deep-water anti-wave fish cages, the construction costs of HDPE floating rafts are 50% to 75% less. There is a dearth of comprehensive publicly available records of HDPE floating rafts sea trial data, despite substantial numerical studies on the motion response of aquaculture fish cages and scale model experiments under controlled-wave conditions. This study involves sea trial techniques under operational and extreme environmental conditions for motion responses of HDPE floating rafts, presents a comprehensive procedure for sea trials of HDPE floating rafts, summarizes the issues encountered during the trials, and suggests solutions. Using MATLAB for independent programming, motion videos and photos collected from the sea trials are processed for image capture, yielding the original time history curve of vertical displacement. Based on the sea trials’ data, including motion displacement, acceleration, mooring line force, overall deformation patterns, and current and wave data, recommendations are provided for the design and layout of HDPE floating rafts. Based on the Fast Fourier Transform (FFT) method for spectral analysis, the influence of interference items on the observational data is eliminated; the rationality of the observational data is verified in conjunction with the results of the Gabor Transform. This study offers a scientific analytical method for the structural design and safe operation of HDPE floating rafts and provides a reference for subsequent numerical simulations.

A Potential Surface Warming Regime for Volcanic Super‐Eruptions Through Stratospheric Water Vapor Increases

AbstractLarge volcanic eruptions are known to influence the climate through a variety of mechanisms including aerosol‐forced cooling and warming via emitted CO2. The January 2022 Hunga shallow underwater eruption caused an increase in stratospheric water vapor, and demonstrated how the associated positive radiative forcing can be an important component of an eruption's climate forcing. We present interactive stratospheric aerosol model simulations of super‐volcanic eruptions with a range of SO2 emissions that can produce climate warming through feedback effects produced by a large igneous province (or “flood basalt”) mid‐latitude super‐eruption using Goddard Earth Observing System Chemistry Climate Model climate model simulations. The model experiments suggest total SO2 emissions ≳4,000 Tg/4 Gt generate a multi‐year period of sustained aerosol absorptive local‐heating of the upper troposphere and lower stratosphere and hence produce net climate warming after strong initial cooling. The eruptions produce stratospheric water vapor increases of factors of 8–600. The initiation of these feedbacks within the simulations suggest they could occur for individual stratovolcano eruptions of the scale of the Toba or Tambora eruptions. We note the sensitivity of our results to volcanic sulfate aerosol microphysics and model chemistry.

Graph Feature Refinement and Fusion in Transformer for Structural Damage Detection

Structural damage detection is of significance for maintaining the structural health. Currently, data-driven deep learning approaches have emerged as a highly promising research field. However, little progress has been made in studying the relationship between the global and local information of structural response data. In this paper, we have presented an innovative Convolutional Enhancement and Graph Features Fusion in Transformer (CGsformer) network for structural damage detection. The proposed CGsformer network introduces an innovative approach for hierarchical learning from global to local information to extract acceleration response signal features for structural damage representation. The key advantage of this network is the integration of a graph convolutional network in the learning process, which enables the construction of a graph structure for global features. By incorporating node learning, the graph convolutional network filters out noise in the global features, thereby facilitating the extraction to more effective local features. In the verification based on the experimental data of four-story steel frame model experiment data and IASC-ASCE benchmark structure simulated data, the CGsformer network achieved damage identification accuracies of 92.44% and 96.71%, respectively. It surpassed the existing traditional damage detection methods based on deep learning. Notably, the model demonstrates good robustness under noisy conditions.

A Potential Surface Warming Regime for Volcanic Super‐Eruptions Through Stratospheric Water Vapor Increases

AbstractLarge volcanic eruptions are known to influence the climate through a variety of mechanisms including aerosol‐forced cooling and warming via emitted CO2. The January 2022 Hunga shallow underwater eruption caused an increase in stratospheric water vapor, and demonstrated how the associated positive radiative forcing can be an important component of an eruption's climate forcing. We present interactive stratospheric aerosol model simulations of super‐volcanic eruptions with a range of SO2 emissions that can produce climate warming through feedback effects produced by a large igneous province (or “flood basalt”) mid‐latitude super‐eruption using Goddard Earth Observing System Chemistry Climate Model climate model simulations. The model experiments suggest total SO2 emissions ≳4,000 Tg/4 Gt generate a multi‐year period of sustained aerosol absorptive local‐heating of the upper troposphere and lower stratosphere and hence produce net climate warming after strong initial cooling. The eruptions produce stratospheric water vapor increases of factors of 8–600. The initiation of these feedbacks within the simulations suggest they could occur for individual stratovolcano eruptions of the scale of the Toba or Tambora eruptions. We note the sensitivity of our results to volcanic sulfate aerosol microphysics and model chemistry.