Response Lag Research Articles

On the dual-phase-lag thermal response in the pulsed photoacoustic effect: A theoretical and experimental 1D-approach

In a recent work, assuming a Beer–Lambert optical absorption and a Gaussian laser time profile, it was shown that the exact solutions for a 1D photoacoustic (PA) boundary-value-problem predict a null pressure for optically strong absorbent materials. In order to overcome this inconsistency, a heuristic correction was introduced by assuming that heat flux travels a characteristic length during the duration of the laser pulse [M. Ruiz-Veloz et al., J. Appl. Phys. 130, 025104 (2021)] τp. In this work, we obtained exact analytical solutions in the frequency domain for a 1D boundary-value-problem for the Dual-Phase-Lag (DPL) heat equation coupled with a 1D PA-boundary-value-problem via the acoustic wave equation. Temperature and pressure solutions were studied by assuming that the sample and its surroundings have a similar characteristic thermal lag response time τT; therefore, the whole system is assumed to have a similar thermal relaxation. A second assumption for τT is that it is considered as a free parameter that can be adjusted to reproduce experimental results. Solutions for temperature and pressure were obtained for a one-layer 1D system. It was found that for τT<τp, the DPL temperature has a similar thermal profile of the Fourier heat equation; however, when τT≥τp, this profile is very different from the Fourier case. Additionally, via a numerical Fourier transform, the wave-like behavior of DPL temperature is explored, and it was found that as τT increases, thermal wave amplitude is increasingly attenuated. Exact solutions for pressure were compared with experimental PA signals, showing a close resemblance between both data sets, particularly in time domain, for an appropriated value of τT; the transference function was also calculated, which allowed us to find the maximum response in frequency for the considered experimental setup.

Unravelling the Influence of ENSO and SAM Patterns on Skate Growth: The Case of the Shorttail Yellownose Skate in Patagonia, Argentina

ABSTRACTIn recent decades, the growth, physiology and distribution of many elasmobranch species have been altered as a result of environmental changes that affect prey abundance, availability and composition. Consequently, variations in nutrient input during climate events could manifest in the growth of their hard tissues. This study focuses on assessing the impact of the El Niño‐Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) on the growth of Shorttail Yellownose skate (Zearaja brevicaudata) in Patagonia, Argentina. To achieve this, vertebrae from 115 Z. brevicaudata specimens were analysed, and growth rings were dated and measured. By using cubic splines with varying flexibility, we constructed three standard chronologies. Generalized additive models (GAMs), the chronology with the best the R‐bar () and expressed population signal (EPS) were employed and values obtained from them linked to annual time series data of the Multivariate ENSO Index (MEI) and SAM, considering lags in the biological response. Surprisingly, no significant association was found with the MEI time series. However, a noteworthy positive association emerged between the chronology and the SAM time series lagged by 1 year, suggesting that SAM‐related climatic conditions could delay their transfer into the Patagonian marine ecosystem, subsequently impacting the growth of this ectothermic predator.

Rapid shifts in grassland communities driven by climate change.

Many terrestrial plant communities, especially forests, have been shown to lag in response to rapid climate change. Grassland communities may respond more quickly to novel climates, as they consist mostly of short-lived species, which are directly exposed to macroclimate change. Here we report the rapid response of grassland communities to climate change in the California Floristic Province. We estimated 349 vascular plant species' climatic niches from 829,337 occurrence records, compiled 15 long-term community composition datasets from 12 observational studies and 3 global change experiments, and analysed community compositional shifts in the climate niche space. We show that communities experienced significant shifts towards species associated with warmer and drier locations at rates of 0.0216 ± 0.00592 °C yr-1 (mean ± s.e.) and -3.04 ± 0.742 mm yr-1, and these changes occurred at a pace similar to that of climate warming and drying. These directional shifts were consistent across observations and experiments. Our findings contrast with the lagged responses observed in communities dominated by long-lived plants and suggest greater biodiversity changes than expected in the near future.

Analysis of the Response of Shallow Groundwater Levels to Precipitation Based on Different Wavelet Scales—A Case Study of the Datong Basin, Shanxi

The rise in shallow groundwater levels is typically triggered by precipitation recharge, exhibiting a certain lag relative to precipitation changes. Therefore, identifying the response mechanism of shallow groundwater levels to precipitation is crucial for clarifying the interaction between precipitation and groundwater. However, the response mechanism of groundwater levels to precipitation is complex and variable, influenced by various hydrogeological and geographical conditions, and often exhibits significant nonlinear characteristics. To address this issue, this study employs methods such as continuous wavelet transform, cross wavelet transform, and wavelet coherence to analyze the response patterns of groundwater levels to precipitation at different wavelet scales in the Datong Basin from 2013 to 2022: (i) At short wavelet scales (10.33~61.96 d), the groundwater level dynamics respond almost instantaneously to extreme rainfall; (ii) At medium wavelet scales(61.96~247.83 d), the precipitation-groundwater recharge process shows characteristics of either rapid recovery or significant delay; (iii) At long wavelet scales (247.83~495.67 d), three potential groundwater processes were identified in the Datong Basin, exhibiting long-term lag responses throughout this study period, with lag times of 11.18 days, 148.75 days, and 151.49 days, respectively. Furthermore, the results indicate that the lag response time of shallow groundwater levels to precipitation is not only related to the wavelet scale but also to the identified depth conditions of different groundwater regions, groundwater extraction intensity, precipitation intensity, and aquifer lithology. This study distinguishes the temporal and spatial response mechanisms of shallow groundwater to precipitation at different wavelet scales, and this information may further aid in understanding the interaction between precipitation and groundwater levels.

Satellite Based Composite Weather Insurance Product for assessing mid-term adversary

The present study formulated a satellite-based rainfall insurance product (SRIP) at sub-seasonal scale during 2015–2020 by integrating meteorological, geophysical and vegetation index products e.g. rainfall (CHIRPS:Climate Hazards Group InfraRed Precipitation with Station), soil moisture (SMAP), normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) from moderate resolution imaging spectro-radiometer (MODIS). The SRIP was meticulously designed to integrate both cause (rainfall) and impact (NDVI, NDWI, soil moisture) parameters to enhance the assessment of min-season crop risks, with a particular emphasis on deficit rainfall. The performance evaluation of SRIP was conducted in two distinct agro-climatic zones viz. Deoria district of Uttar Pradesh (Upper Gangetic Plain Region) and Krishna district of Andhra Pradesh (Southern Plateau and Hills Region) spanned from June to October, which aligns with the major crop-growing season corresponding to the Southwest monsoon period in India. Three sets of SRIPs were investigated i.e. SRIP with cause parameter (SRIP1), SRIP with cause-impact parameters with no lag response (SRIP2) and SRIP with cause-impact parameters with one-month lag response (SRIP3). The SRIP was structured to provide a numerical index on a scale ranging from 0 to 1, representing poor to good crop-growing conditions that could effectively identify the rainfall deficit threshold (SRIP≤0.43) corresponding to negative percent deviation in rainfall (PDR≤−20%). This threshold level was recognized for compensation of triggers at the multiple crop growth phases during the crop-growing season. The district average of SRIP and PDR showed fair correlation co-efficient (0.77 ≤ r ≤ 0.88). Good correlation between sub-seasonal (monthly, bi-monthly, tri-monthly) SRIP and normalized MODIS Gross Primary Productivity (0.65 ≤ r ≤ 0.98), and SRIP deviation and yield deviation (0.45 ≤ r ≤ 0.97) reflect sensitivity of SRIP to crop carbon productivity and crop yield. The findings of the present study recommend SRIP not only a multi-phase composite index for assessing mid-season crop risks in terms of rainfall deficit for clusters of insurance units, but it has the potential to be used by insurance agencies to settle the claims by farmers in a transparent and faster manner for crop loss due to large-scale rainfall deficits. However, SRIP needs to be customized in future to make it more adaptable to settle insurance claims due to weather adversaries at individual farm level.

Distinctive water bodies surrounding lakes: An effective indicator for drought monitoring and assessment

The response mechanisms of surface water to drought and the potential and performance of water body changes in drought monitoring and assessment remain insufficiently elucidated. We take the Poyang Lake Basin, which suffers from drastic water body changes and frequent droughts, as a representative. Through integrating multisource data to extract long-term precise water bodies, we construct standardized water body area/number anomaly indices (SAAI/SNAI). Subsequently, we quantify the correlation and time lag response between SAAI, SNAI and drought. Our findings reveal that overall, water body area and number in the Poyang Lake Basin all exhibit a significant correlation with typical drought indices. Among them, the large water body area has a higher correlation coefficient with drought, making it a more effective indicator for drought monitoring. Water body changes of Poyang Lake surrounding area offer a more precise reflection of drought conditions than other sub-basins and exhibit greater sensitivity to drought. Meanwhile, water body area changes in Poyang Lake surrounding area lag behind meteorological drought by approximately half a month. And the basin’s water body area can typically respond with changes to some prolonged and severe hydrological droughts about 1 to 2 months in advance. We propose an integrated mechanism for drought monitoring and assessment informed by these conclusions and use actual drought events for qualitative validation. The results indicate that it is possible to assess water body drought conditions for the next approximately half month based on current meteorological drought conditions. Also, combining water body area changes with meteorological drought severity can aid in evaluating hydrological drought conditions for the following about 1–2 months. We extend our investigation to explore the universality of these phenomenon across eight shallow lakes globally characterized by significant water fluctuations. The results reveal that the water body changes in most of these lakes exhibit good potential for drought monitoring and assessment, and present a strong consistency with deep soil moisture, allowing for the accurate reflection of deep soil drought conditions. The lag response patterns between water bodies and drought in Dongting Lake, Hongze Lake, and Tonlé Sap Lake—also situated in the monsoon climate zone—are more similar to those observed in Poyang Lake. These distinctive lake water bodies can serve as an innovative indicator for drought monitoring and assessment, providing potential support for endeavors in drought prevention and mitigation.

On the Piezomagnetism of Magnetoactive Elastomeric Cylinders in Uniform Magnetic Fields: Height Modulation in the Vicinity of an Operating Point by Time-Harmonic Fields.

Soft magnetoactive elastomers (MAEs) are currently considered to be promising materials for actuators in soft robotics. Magnetically controlled actuators often operate in the vicinity of a bias point. Their dynamic properties can be characterized by the piezomagnetic strain coefficient, which is a ratio of the time-harmonic strain amplitude to the corresponding magnetic field strength. Herein, the dynamic strain response of a family of MAE cylinders to the time-harmonic (frequency of 0.1-2.5 Hz) magnetic fields of varying amplitude (12.5 kA/m-62.5 kA/m), superimposed on different bias magnetic fields (25-127 kA/m), is systematically investigated for the first time. Strain measurements are based on optical imaging with sub-pixel resolution. It is found that the dynamic strain response of MAEs is considerably different from that in conventional magnetostrictive polymer composites (MPCs), and it cannot be described by the effective piezomagnetic constant from the quasi-static measurements. The obtained maximum values of the piezomagnetic strain coefficient (∼102 nm/A) are one to two orders of magnitude higher than in conventional MPCs, but there is a significant phase lag (35-60°) in the magnetostrictive response with respect to an alternating magnetic field. The experimental dependencies of the characteristics of the alternating strain on the amplitude of the alternating field, bias field, oscillation frequency, and aspect ratio of cylinders are given for several representative examples. It is hypothesized that the main cause of observed peculiarities is the non-linear viscoelasticity of these composite materials.

Physically Guided Estimation of Vehicle Loading-Induced Low-Frequency Bridge Responses with BP-ANN

The intersectional relationship in bridge health monitoring refers to the mapping function that correlates bridge responses across different locations. This relationship is pivotal for estimating structural responses, which are then instrumental in assessing a bridge’s service status and identifying potential damage. The current research landscape is heavily focused on high-frequency responses, especially those associated with single-mode vibration. When it comes to low-frequency responses triggered by multi-mode vehicle loading, a prevalent strategy is to regard these low-frequency responses as “quasi-static” and subsequently apply time-series prediction techniques to simulate the intersectional relationship. However, these methods are contingent upon data regarding external loading, such as traffic conditions and air temperatures. This necessitates the collection of long-term monitoring data to account for fluctuations in traffic and temperature, a task that can be quite daunting in real-world engineering contexts. To address this challenge, our study shifts the analytical perspective from a static analysis to a dynamic analysis. By delving into the physical features of bridge responses of the vehicle–bridge interaction (VBI) system, we identify that the intersectional relationship should be inherently time-independent. The perceived time lag in quasi-static responses is, in essence, a result of low-frequency vibrations that are aligned with driving force modes. We specifically derive the intersectional relationship for low-frequency bridge responses within the VBI system and determine it to be a time-invariant transfer matrix associated with multiple mode shapes. Drawing on these physical insights, we adopt a time-independent machine learning method, the backpropagation–artificial neural network (BP-ANN), to simulate the intersectional relationship. To train the network, monitoring data from various cross-sections were input, with the responses at a particular section designated as the output. The trained network is now capable of estimating responses even in scenarios where time-related traffic conditions and temperatures deviate from those present in the training data set. To substantiate the time-independent nature of the derived intersectional relationship, finite element models were developed. The proposed method was further validated through the in-field monitoring of a continuous highway bridge. We anticipate that this method will be highly effective in estimating low-frequency responses under a variety of unknown traffic and air temperature conditions, offering significant convenience for practical engineering applications.

Increased Sensitivity and Accelerated Response of Vegetation to Water Variability in China from 1982 to 2022

Understanding how plants adapt to shifting water availability is imperative for predicting ecosystem vulnerability to drought. However, the spatial–temporal dynamics of the plant–water relationship remain uncertain. In this study, we employed the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI4g), an updated version succeeding GIMMS NDVI3g spanning from 1982 to 2022. We integrated this dataset with the multiple scale Standardized Precipitation Evapotranspiration Index (SPEI 1 to 24) to investigate the spatial–temporal variability of sensitivity and lag in vegetation growth in response to water variability across China. Our findings indicate that over 83% of China’s vegetation demonstrates positive sensitivity to water availability, with approximately 66% exhibiting a shorter response lag (lag < 1 month). This relationship varies across aridity gradients and diverges among plant functional types. Over 66% of China’s vegetation displays increased sensitivity to water variability and 63% manifests a short response lag to water changes over the past 41 years. These outcomes significantly contribute to understanding vegetation dynamics in response to changing water conditions, implying a heightened susceptibility of vegetation to drought in a future warming world.

Solar Cycle Dependence of Migrating Diurnal Tide in the Equatorial Mesosphere and Lower Thermosphere

Atmospheric migrating diurnal tide (DW1) is one of the prominent variabilities in the mesosphere and lower thermosphere (MLT). The existence of the solar cycle dependence of DW1 is debated, and there exist different and even opposite findings at different latitudes. In this paper, the solar cycle dependence of temperature DW1 in the equatorial mesosphere and lower thermosphere (MLT) is investigated using temperature global observations from TIMED/SABER spanning 22 years (2002–2023). The results show that (a) the solar cycle dependence of temperature DW1 is seen very clearly at the equator. The maximum correlation coefficient between DW1 and the F10.7 index occurs at 87km, with 0.72; the second maximum coefficient occurs at 99 km, with 0.62. The coefficient could reach 0.87 at 87 km and 0.67 at 99 km after dropping the years influenced by the Stratosphere Quasi-biennial oscillation (SQBO) disruption event. (b) DW1 shows a lag response to the solar cycle at the equator. DW1 amplitudes show a 1-year lag to the F10.7 index at 87 km and a 2-year lag to the F10.7 index at 99 km.

Evolution Characteristics of Heilongtan Spring Discharge and Its Response Law to Precipitation in Lijiang City, China

The contradiction between water supply and spring preservation issues is becoming increasingly apparent as Lijiang City develops. An investigation into the dynamic variations in the discharge rate of Heilongtan Spring in Lijiang City and the response law between the water level of the spring and precipitation is crucial for safeguarding the landscape water of Heilongtan Spring. This study employed linear regression analysis, Mann–Kendall (MK) mutation test, wavelet analysis, and vector autoregression (VAR) to examine the fluctuating pattern of the Heilongtan Spring discharge and the response of the Heilongtan Spring water level to precipitation in Lijiang City. Furthermore, the study discussed the influence of human activities on the alteration of Heilongtan Spring. The results indicate that the mean discharge rate of Heilongtan Spring is 0.94 m3/s, with an annual variation of 0.05 m3/s. The time series analysis reveals that the variation pattern of Heilongtan Spring discharge aligns with the precipitation trend in Lijiang City. Nevertheless, there is a distinction between the timing of the Heilongtan Spring discharge station point and the precipitation mutation point in Lijiang City. The significant primary cycle of spring discharge change occurs every 18 months, with a cycle length of 12 months. The vector autoregression (VAR) model demonstrates a lagged relationship between the water level of Heilongtan Spring and the precipitation in Lijiang City. Specifically, the water level of Heilongtan Spring has a four-month lag response to precipitation variability in Lijiang City. The results can provide a beneficial reference for preserving spring water and managing regional water resources.

Compensation control of commercial vehicle platoon considering communication delay and response lag

The real-time accurate control of vehicle is of great significance for the stability of platoon driving. To address the impact of random time-varying communication delays, communication packet loss, data disorder, and significant response lag of commercial vehicle on platoon control performance in non-ideal communication environment, a novel compensation control method for commercial vehicle platoon is proposed to overcome the abovementioned issues. The proposed method significantly improves the impact of communication issues and vehicle response lag on platoon control, ensuring platoon safety while reducing inter-vehicle spacing and spacing error, and maintaining platoon stability. In addition, this method combines the comprehensive compensation mechanism with the Distributed Model Predictive Controller (DMPC), avoiding the establishment of additional compensation control modules and effectively reducing the computational burden. The results under emergency braking condition show that, compared with the method without compensation, the proposed method significantly reduces inter-vehicle spacing and spacing error, reducing the average maximum spacing error from 29.25 m to 1.44 m, shortening the error convergence time of the platoon by 28 %, and ensuring platoon stability. Additionally, compared to the compensation method based on Kalman Filtering (KF) and Smith predictor, the proposed method can reduce the average maximum spacing error by 60 % while maintaining similar convergence time and platoon stability.

Effect of material anisotropy on the first-order vibration of piezoelectric oscillators in circular plate configurations

Valveless piezoelectric pumps are widely used in microfluidic actuation because of their simple structure, ease of integration, absence of electromagnetic interference, minimal valve wear, and absence of frequency–response lag issues. These pumps primarily rely on chamber volume changes, causing most piezoelectric oscillators to operate in the first-order vibration mode. However, recent studies on valveless piezoelectric pumps have observed that many pumps exhibit two flow peaks at similar operating frequencies; the underlying mechanism behind this anomaly remains underexplored. In this study, we investigated the impact of substrate metal on the first-order vibrations of piezoelectric oscillators. By conducting tensile tests on rolled pure copper sheets, we measured Poisson's ratio and the elastic modulus in both the parallel and perpendicular rolling directions. Subsequently, we derived the natural frequencies on the plane. Experimental verification of the theoretical predictions was achieved through amplitude experiments conducted on piezoelectric oscillators in air. The dual-peak flow phenomenon was demonstrated to be solely related to the substrate metal of the piezoelectric oscillator. This is attributed to the presence of two first-order vibration natural frequencies on the plane of the substrate metal, resulting in the generation of two amplitude peaks and consequently the appearance of two flow peaks.

Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm

Long-term trend forecast of chlorophyll-a concentration (Chla) holds significant implications for eutrophication management and pollution control planning on lakes, especially under the background of climate change. However, it is a challenging task due to the mixture of trend, seasonal and residual components in time series and the nonlinear relationships between Chla and the hydro-environmental factors. Here we developed a hybrid approach for long-term trend forecast of Chla in lakes, taking the Lake Taihu as an instantiation case, by the integration of Seasonal and Trend decomposition using Loess (STL), wavelet coherence, and Convolutional Neural Network with Bidirectional Long Short-Term Memory (CNN-BiLSTM). The results showed that long-term trends of Chla and the hydro-environmental factors could be effectively separated from the seasonal and residual terms by STL method, thereby enhancing the characterization of long-term variation. The resonance pattern and time lag between Chla and the hydro-environmental factors in the time-frequency domain were accurately identified by wavelet coherence. Chla responded quickly to variations in TP, but showed a time lag response to variations in WT in Lake Taihu. The forecasting method using multivariate and CNN-BiLSTM largely outperformed the other methods for Lake Taihu with regards to R2, RMSE, IOA and peak capture capability, owning to the combination of CNN for extracting local features and the integration of bidirectional propagation mechanism for the acquisition of higher-level features. The proposed hybrid deep learning approach offers an effective solution for the long-term trend forecast of algal blooms in eutrophic lakes and is capable of addressing the complex attributes of hydro-environmental data.

Electrified Nano-Gaps Under AC Field: A Molecular Dynamics Study

Solid-Liquid Interfaces (SLIs) hold immense significance in various areas such as materials science, chemistry, physics, biology and medicine [1]. Many studies aim to decipher the molecular details of SLIs through analytical, computational or experimental methods [2]-[3], each optimized for different aspects of SLIs. Analytical methods are mainly based on the mean field approximation and work best for dilute solutions. Computational methods are bound by their maximum accessible time and length scales, while the limitation of experimental approach tend to lie in minimum values accessible of these scales. The concomitant deployment of both the approaches is a powerful tool in studying SLIs.In the current study both the computational and experimental tools are employed to study the interface of silica with aqueous saline solutions under electric fields. Molecular Dynamics (MD) simulation are utilized to investigate the relative response of the ions and waters exposed to an external AC field in a nanoscale silica-elecrolyte-gold system. Complementary experimental measurements are conducted with atomic force microscopy (AFM) which measures the dielectric force exerted on the nanoscale AFM probe. The impact of external factors such as salt concentration, AC voltage frequency and the system size is systematically investigated.Simulations reveal both the transient and stable response of water and ions as the main component of the system to the AC field. In the transient response, the water electric dipole increases monotonically with the voltage at the first cycle while it takes longer for ions to react to the field, limited by their diffusion time. When the ionic response becomes large enough to screen the field, the dipole moment of water molecules decreases and lead the phase of the applied field. The lag in the ionic response is owing to the time required for the ionic diffusion, while the lead in the water response is due to ionic lag.To obtain the stable response through MD simulation, Fourier transform was deployed with the results showing that electric dipole of ions and water have a periodic behavior with a frequency similar to the AC field and waters in lead and ions in lag. The dipole-voltage plots for ions and waters depicted an energy transfer between water and ions in each cycle. Decreasing the frequency to 10MHz, no energy exchange was observed concomitant to the removal of water lead. Besides, in the frequency range of 100MHz-200MHz in which the water phase lead reaches its maximum value, there is also a maximum in the energy exchange. Thus, there is a direct relation between the water-ion energy exchange and lead in the water response.The stable response is affected by various factors including the separation distance between the surfaces, the ionic concentration and the AC frequency. The MD observations of a decrease in the water lead and ionic lag with reducing the electrolyte gap could explain AFM measurements where the dielectric force appears to decrease for small gaps, a counter-intuitive result if bulk electrolyte properties are assumed. The simulation results also show that the sum of the electric dipole of water and ions is always in phase with the applied voltage implying that the field is totally screened by the combination of both of them. To provide the same amount of screening in larger separation distance the electric dipole of ions has to increase to counteract its larger lag which is observed in the ionic dipole values. As the ionic dipole despite water molecules are caused by translational entropy, larger ionic dipole translates to larger forces which is observed in the AFM experiments.[1] Taketoshi et al. Japanese Journal of Applied Physics (2021).[2] T. Fukuma and R. Garcia, ACS nano (2018).[3] J.M. Andanson and A. Baiker, Chemical Society Reviews (2010).

Research on Evolution and Recommendations of China’s PM2.5 and O3 Pollution Control Policies under the Carbon Peak and Carbon Neutrality Targets

In recent years, the issue of PM2.5 and O3 pollution in China has gradually become a hot topic in air pollution control. Powerful, precise, and clear policies are important to guide the efficient control of PM2.5 and O3 pollution. However, research on PM2.5 and O3 pollution policies is very limited. Moreover, these reports have failed to identify all the specific characteristics of the PM2.5 and O3 pollution policies in China, leading to inefficient control of PM2.5 and O3 pollution. Therefore, based on the external features and internal structures of relevant policy documents, this paper conducts a detailed bibliometric analysis to elucidate the evolution of PM2.5 and O3 pollution control policies in China. The results reveal the following: (1) The PM2.5 and O3 pollution control policies in China exhibit a characteristic of “top-down cross-level response lag”, transitioning from individual pollutant control to coordinated control of PM2.5 and O3 pollution. (2) The Ministry of Environmental Protection and the Ministry of Ecology and Environment have been the two major policy issuers in China’s government, focusing on “Technology” and “Monitoring”, respectively. However, the aforementioned policies are mainly implemented by local governments, with limited interregional cooperation but an overemphasis on enterprise pollution control and emergency systems. (3) In terms of policy instruments, supply- and environment-oriented policy instruments are predominant, whereas demand-oriented policy instruments are inadequate. Therefore, it is suggested to utilize the synergistic effect of pollution reduction and carbon mitigation to achieve the goal of the “dual carbon” strategy, enhance public participation to strengthen cooperation among diverse stakeholders, strengthen cross-regional cooperation to overcome governance barriers, and reasonably optimize the use of policy instruments to form an effective combination of policy instruments.

Dynamic Modeling and Analysis of Flexible-Joint Robots with Clearance.

The coupling effects of flexible joints and clearance on the dynamics of a robotic system were investigated. A numerical analysis was undertaken to reveal the coupling effects between flexible joints and clearance. The nonlinear spring-damping model and Coulomb model were applied to characterize the contact characteristics of the clearance, and a model for the flexible joint was formulated using the equivalent spring theory. An accurate robot model was established based on the clearance and joint flexibility characterization. The dynamic equation of a robot was obtained according to the Newton-Euler method. A comparative analysis was performed to assess the impacts of both the joint action of clearance and flexible joints and varying joint clearance values on the performance of the robot. The results showed that the coupling effects of flexible joints and clearance had a negative impact on the system dynamic performance. The amplitudes of the dynamic responses caused by the clearance are weakened by the flexible joint, but it leads to the lag of the system response. This study served as the theoretical foundation for exploring precise control techniques in robotics research.

Delayed photosynthesis response causes carbon assimilation reduction in soybean under fluctuating light

Plants experience dynamic light environments in the field, and the mechanisms for physiological and biochemical acclimation to fluctuating light (FL) vary among species. How soybean (Glycine max (L.) Merr.) integrates multiple physiological changes to acclimate to FL remains unclear. This study evaluated the impact of FL conditions on soybean morphology and photosynthetic characteristics by analyzing changes in photosynthetic gas exchange parameters and chlorophyll (Chl) a fluorescence parameters under alternating high and low light conditions. Results showed that soybeans subjected to FL conditions had low dry matter mass, small and thin leaves, and a low Chl a to Chl b ratio, resembling the traits of soybeans grown in low-light environments. However, their photosynthetic gas exchange rates and photosynthetic capacity remained constant, which was not the case under consistent low-light conditions. The adaptation processes for fluctuating and lowlight conditions are distinct. Correlation analyses indicated that the drop in carbon assimilation under FL primarily resulted from two aspects: the speed of recovery in stomatal conductance when transitioning to bright light and the slow relief of nonphotochemical quenching as light levels decreased. Thus, the decrease in carbon assimilation under FL conditions cannot be ascribed to adjustments during low-light phases but is due to a lag in photosynthetic response.

Drought and wetness events encounter and cascade effect in the Yangtze River and Yellow River Basin

Under the background of global change, the multivariate attributes, multi-temporal and multi-watershed regional characteristics of extreme drought and flood disasters are significant. It is very important to identify the drought and wetness encounter law and spatial cascade effect in the source region-upper-middle-lower reaches of the basin. In this paper, the Yangtze River and Yellow River basins are taken as the research objects. Based on the standardized precipitation index (SPI) characterizing meteorological drought and wetness and the standardized runoff index (SRI) characterizing hydrological drought and wetness, the evolution law of extreme drought and flood events in the source region-upper-middle-lower reaches of the two basins is analyzed. On this basis, the correlation analysis and transfer function analysis are used to explore the response relationship and lag effect between the two in different partitions. A two-dimensional joint distribution model is constructed by Copula function to quantitatively analyze the joint probability of drought and wetness encounters of 9 combined events, and to deeply analyze the impact of different drought and wetness encounter scenarios. The results show that: from 1957 to 2020, the two basins showed a trend from drought to wet. The SPI-12 in the Yellow River Basin ranged from-1.57 to 1.32, and that in the Yangtze River Basin ranged from-1.24 to 1.11. The severity of drought and wetness in the Yellow River Basin was higher than that in the Yangtze River Basin; The correlation coefficients between SPI and SRI in the source-upper-middle-lower reaches of the Yellow River (Yangtze River) were 0.78 (0.76), 0.23 (0.73), 0.44 (0.55) and 0.23 (0.63), respectively. The correlation degree of meteorological-hydrological drought and wetness in the Yangtze River Basin was significantly higher than that in the Yellow River Basin. The average probability of synchronous combination events of drought and wetness in the two basins is greater than 51.43 %. The probability of drought in the Yellow River Basin is greater than that of flood, while the Yangtze River Basin is the opposite. In the same drought and wetness scenario, an average of 54.1% of the event pairs were aggravated by disasters, and more than 52 % of the events in the wetness-drought scenario had obvious drought mitigation effects. The research results can provide important support for improving the early warning and risk management of river basin disasters.

Temporal variation in river ice phenology of the Heilongjiang River in response to climate change

Study regionUpstream of the Heilongjiang River, located in Northeast Asia, is the transboundary river between China and Russia. Study focusUsing long-term hydrological records provided by the Mohe station in combination with multiple statistical approaches, we investigate how river ice phenology of the Heilongjiang River has varied during the period 1957–2016, and quantitatively assess the individual contribution of changes in different climatic factors to such variation in river ice phenology. New insights for the regionWe show the later occurrence for newly formed ice date, ice-on date, and freeze-up date and the earlier occurrence for beak-up date and ice-off date, ultimately leading to a decrease in persistence of river ice in the Heilongjiang River. River ice phenology exhibits a general lag response to climate change, with ranging from 1 to 5 months. Further attribution analysis that explicitly considers time-lag effect suggests that climate change plays a dominant role in regulating river ice phenology. More specifically, compared to other climatic factors, air pressure and maximum and minimum temperature changes have larger contributions to variation in river ice phenology, particularly for the delay of formation time. These findings provide technical basis and beneficial reference to the development of regional river management strategies involved in climate change adaptation framework.