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Earlier studies based on censuses of adult birds in spring suggest that the Common Merganser Mergus merganser population in Finland has been rather stable during the last few decades. However, in the beginning of the 1990s, a population increase was followed by a decline. Contrary to the trends detected in breeding populations, wintering populations of the species have increased in Finland and elsewhere in Europe. Along with warming winters, wintering areas have shifted gradually towards northeast. In the present study, a coastal population of the Common Merganser breeding in nest boxes was monitored between 2004 and 2022 in southern Finland. The role of winter weather conditions in population fluctuations and changes was examined. The weather conditions during two preceding winters reflected in the population fluctuations of mergansers. The number of nests in nest boxes increased following increasing winter temperatures in the northeastern end of the wintering area (near the breeding area). The breeding population decreased after warm winters in the southwestern end of the wintering area (far from the breeding area). The present results suggest that established populations decrease after warm winters, because young birds that have not yet bred have shifted to overwinter and breed further eastwards than in general. [ABSTRACT FROM AUTHOR]

Online quality control methods emphasize manufacturing processes to attain maximum conformance with respect to the specifications of the concerned quality characteristics of a product. One key factor that affects the effectiveness of these methods is the diagnosis interval. In this paper, the existing cost model along with its cost components for online quality control methods has been revisited and modified by incorporating new variables like the rate of production, the loss due to false alarm, the loss due to non-detection of process abnormalities, and considering a workable break-up of diagnosis cost for finding the optimal diagnosis interval from the perspective of present-day manufacturing engineering. As already mentioned, the proposed cost model has not ignored the loss due to the generation of defective items as well as the adjustment cost available in the pertinent literature. The modified cost function thus proposed has been appropriately minimized to obtain the corresponding optimal diagnosis interval. The proposed methodology has been compared numerically with other methodologies to establish its effectiveness. The cornerstone of the proposed methodology lies in reinforcing its effectiveness through a real-life case example in manufacturing. Sensitivity analysis has also been carried out for the real-life case example to fortify the proposed methodology. [ABSTRACT FROM AUTHOR]

Aim. To determine the general state of Russia’s high-tech exports in the following areas: the relationship with other sectors of the economy and with the dynamics of GDP, positions on the world stage, relations with partner countries.Tasks. To achieve the aim of the study, the following tasks were set: to consider the dynamics of Russia’s export structure, to explore Russia’s position in the world in high-tech exports, to calculate the time lag of Russia’s lag behind the leading countries in high-tech exports, to analyze Russia’s role in the hightech market of the main partner countries, to explore the structure of Russia’shigh-tech exports in the context of commodity groups.Methods. To determine high-tech exports and imports, the methodology of the World Bank is used, according to which 9 industries (aerospace, computer and office equipment, electronics and telecommunications, pharmaceuticals, scientific instruments, electric machines, chemicals, nonelectric machines and weapons), including 79 commodity nomenclatures. At the same time, based on the availability of information, the values for the export of weapons are not taken into account.Results. The analysis of changes in high-tech exports has been carried out, which identifies periods of negative changes that coincide with periods characterized by adverse circumstances in the country and the world (pandemic, geopolitical and geo-economic tensions). When comparing graphs of high-tech exports and GDP, ambiguous results were obtained, taking into account the consideration of high-tech exports in calculating GDP. The time lags of the backlog have been calculated, according to which, in most cases, the values of the leading countries in high-tech exports are achievable, but the time lags themselves are enormous. The commodity spectrum of high-tech exports and imports of the Russia is considered, according to which Russia exports the entire commodity spectrum of the high-tech industry.Conclusions. The dominant role in Russia’s exports is still assigned to fuel and mining products with observed changes in terms of increasing the share of industrial products, including high-tech products, in which Russia, although an active participant, is nevertheless at a disadvantage in interactions with the main partner countries.

Fine-scale quantitative precipitation forecast is a key issue and challenge in weather forecasting services. In this study, based on hourly precipitation from the 1 km× 1 km resolution Southwest China WRF-based Intelligent Numeric Grid forecast System (SWC-WINGS), a fusion-corrected experiment was conducted using time lag and probability matching methods. The fusion-corrected forecast of hourly pre⁃ cipitation was then verified utilizing the CMA Multi-source Precipitation Analysis System (CMAPS) three-source merged precipitation obser⁃ vation grid data from 1 July to 31 August 2022 in Sichuan. Finally, the fusion-corrected method was applied to a short-term heavy precipita⁃ tion process over the western Sichuan Basin. The results show that: (1) Compared with the model precipitation forecasts, the time-lagged en⁃ semble forecast was over-optimistic for small-scale precipitation and over-conservative for large-scale precipitation. (2) However, the fu⁃ sion-corrected method by time lag and probability matching methods overcame the above difficulties and showed significant improvement in the TS score, particularly in 1~2 h nowcast time. The TS score for hourly precipitation exceeding 0.1 mm, 5 mm, 10 mm, and 20 mm were in⁃ creased on average by 7.2%, 17.2%, 28.3%, and 36.3%, respectively. (3) A case studies also showed that the fusion-corrected method had good improvement and correction capabilities on the hourly precipitation forecast, especially for large-scale precipitation forecasts.

The eco-hydrological process related to vegetation on the Qinghai–Tibet Plateau is special, and the impact of snow cover on the growth of vegetation is unique and important. In this study, we analyzed the multi-year variations in the normalized difference vegetation index (NDVI) and snow cover on the Qinghai–Tibet Plateau from spatial and temporal perspectives and determined the relationship between the changes in the NDVI and snow cover. Results showed that in the last 40 years, the rate of change in the snow depth on the plateau was −0.016 mm/a, and the NDVI changed by 0.0005/a. The correlations (|R| values) between the different factors and the NDVI followed the order of precipitation (0.77) > snow depth (0.76) > temperature (0.67) > solar radiation (0.21). The responses of the NDVI to changes in meteorological elements were synchronous, whereas the opposite was found for the snow cover. The snow cover had more significant impacts on vegetation at higher elevations. The NDVI had a lag of about 2 months from the onset of the snow cover, and heavy snow events had negative impacts on the NDVI for more than 3 years. Our findings will facilitate studies of ecological vulnerability and the predictions of changes in vegetation on the plateau. [ABSTRACT FROM AUTHOR]

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity. [ABSTRACT FROM AUTHOR]

Climate warming hampers grassland growth, particularly in dryland regions. To preserve robust grassland growth and ensure the resilience of grassland in these arid areas, a comprehensive understanding of the interactions between vegetation and climate is imperative. However, existing studies often analyze climate–vegetation interactions using concurrent vegetation indices and meteorological data, neglecting time-lagged influences from various determinants. To address this void, we employed the random forest machine learning method to predict the grassland NDVI (Normalized Difference Vegetation Index) in Asian drylands (including five central Asia countries, the Republic of Mongolia, and Parts of China) from 2001 to 2020, incorporating time-lag influences. We evaluated the prediction model's performance using three indexes, namely the coefficient of determination (R2), root-mean-square error (RMSE), and Mean Absolute Error (MAE). The results underscore the superiority of the model incorporating time-lag influences, demonstrating its enhanced capability to capture the grassland NDVI in Asian drylands (R2 ≥ 0.915, RMSE ≤ 0.033, MAE ≤ 0.019). Conversely, the model without time-lag influences exhibited relatively poor performance, notably inferior to the time-lag-inclusive model. The latter result aligns closely with remote sensing observations and more accurately reproduces the spatial distributions of the grassland NDVI in Asian drylands. Over the study period, the grassland NDVI in Asian drylands exhibited a weak decreasing trend, primarily concentrated in the western region. Notably, key factors influencing the grassland NDVI included the average grassland NDVI in the previous month, total precipitation in the current month, and average soil moisture in the previous month. This study not only pioneers a novel approach to predicting grassland growth but also contributes valuable insights for formulating sustainable strategies to preserve the integrity of grassland ecosystems. [ABSTRACT FROM AUTHOR]

The eddy covariance (EC) method is a standard micrometeorological technique for monitoring the exchange rate of the main greenhouse gases across the interface between the atmosphere and ecosystems. One of the first EC data processing steps is the temporal alignment of the raw, high frequency measurements collected by the sonic anemometer and gas analyser. While different methods have been proposed and are currently applied, the application of the EC method to trace gases measurements highlighted the difficulty of a correct time lag detection when the fluxes are small in magnitude. Failure to correctly synchronise the time series entails a systematic error on covariance estimates and can introduce large uncertainties and biases in the calculated fluxes. This work aims at overcoming these issues by introducing a new time lag detection procedure based on the assessment of the cross-correlation function (CCF) between variables subject to (i) a pre-whitening based on autoregressive filters and (ii) a resampling technique based on block-bootstrapping. Combining pre-whitening and block-bootstrapping facilitates the assessment of the CCF, enhancing the accuracy of time lag detection between variables with correlation of low order of magnitude (i.e. lower than - 1 ) and allowing for a proper estimate of the associated uncertainty. We expect the proposed procedure to significantly improve the temporal alignment of the EC time-series measured by two physically separate sensors, and to be particularly beneficial in centralised data processing pipelines of research infrastructures (e.g. the Integrated Carbon Observation System, ICOS-RI) where the use of robust and fully data-driven methods, like the one we propose, constitutes an essential prerequisite. [ABSTRACT FROM AUTHOR]

A regression model represents the relationship between explanatory and response variables. In real life, explanatory variables often affect a response variable with a certain time lag, rather than immediately. For example, the marriage rate affects the birth rate with a time lag of 1 to 2 years. Although deep learning models have been successfully used to model various relationships, most of them do not consider the time lags between explanatory and response variables. Therefore, in this paper, we propose an extension of deep learning models, which automatically finds the time lags between explanatory and response variables. The proposed method finds out which of the past values of the explanatory variables minimize the error of the model, and uses the found values to determine the time lag between each explanatory variable and response variables. After determining the time lags between explanatory and response variables, the proposed method trains the deep learning model again by reflecting these time lags. Through various experiments applying the proposed method to a few deep learning models, we confirm that the proposed method can find a more accurate model whose error is reduced by more than 60% compared to the original model. [ABSTRACT FROM AUTHOR]

Buildings account for about 40% of total electricity use in the world for artificial cooling and artificial day lighting and they are also responsible for 40% CO2 emissions. The reduction of energy consumption in the building sector is a major challenge to cope with the scarcity of fossil energy resources and the problem of climate change. Hence, to decrease energy consumption and contribute to reducing CO2 emissions, different alternative building materials have been investigated. The aim of this paper is to study the effect of incorporation of fly ash, Ground Granulated Blast Furnace Slag (GGBS), ceramic waste powder (silica and alumina rich) and barite powder (as partial replacement to cement) on the thermal properties and thermal performance of the resulting cement blocks. This study also investigates the thermo-economic performance of building walls constructed with blocks of various cement blocks in distinct climatic zones of India. The building concept with the wall configuration (CC 50) demonstrated the greatest yearly air conditioning savings (0.37 and 0.34 $/m2) and the greatest annual reduction in carbon emissions (7.21 and 6.37 kg/kWh) in both hot-arid (Madras) and composite (Jabalpur) climatic zones. [ABSTRACT FROM AUTHOR]

The phenomenon of seasonal hysteresis between urban heat islands (UHIs) and background surface temperature was reported in many studies, but a unifying explanation for the causes of its magnitude, shape and looping direction remained less clear, and the impacts of urban landscapes and background climate on such hysteresis were also the subject of enquiry. Here we performed a systematic study based on a long‐term offline simulation for surface energy budgets, surface air and skin temperature of the urban‐biosphere system in East China. It was carried out with an up‐to‐date land surface model — the CLM5‐LCZs (the Community Land Model version 5 (CLM5) coupled with a newly developed urban canopy model representing diverse urban landscapes with the local climate zones classification scheme). To isolate the causes of UHIs hysteresis, a simplified framework was constructed by combining a mathematical representation of grid/subgrid model outputs, the two‐resistance mechanism method and the time‐lagged cross correlation analysis. The results exhibited distinct hysteresis patterns of UHIs such as twisted, concave‐down, concave‐up and convex‐up curve across diverse background climates and urban landscapes. The basic shapes of hysteresis depict a gradual transition from concave/convex‐up to concave/convex‐down by characterized by a larger winter UHIs from a wetter and warmer climate to a drier and colder climate. Magnitude and seasonality of surface UHIs are separately dominated by the urban‐rural contrast of evapotranspiration and heat storage at daytime and nighttime, whereas across‐climate variations of daytime and nighttime surface UHIs hysteresis are regulated by the phase shift of convection efficiency and anthropogenic heat. Urban landscapes affect the hysteresis mainly by altering the amplitude rather than the shape of looping curves. Our work could provide a fuller picture of how to mitigate urban warming considering inter‐seasonal tradeoffs over a broader region. Plain Language Summary: The seasonality of urban heat islands (UHIs) has been investigated toward its characteristics and controls, of which analyses were conducted on several cities and left intra‐urban variations out of account. It was essential to understand whether the local seasonality‐arguments can be extended to broader geographic regions or lots of cities with different landscapes. In this study, an updated urban climate model describing intra‐urban heterogeneity better was utilized to simulate surface energy fluxes and UHIs. Based on the subgrid outputs of this model and the hypothesis of phase shift mechanism, we presented a simplified framework to isolate the contribution of time lags of different biophysical factors to the magnitude, shape and looping direction of UHIs hysteresis. These hysteretic characteristics are varied with background climates and urban landscapes. The time lags of evaporative cooling and heat storage corresponding to background surface temperature between urban and rural areas account for different hysteresis patterns at daytime and nighttime. Hysteretic typology for different urban classes or cities in diverse background climates is regulated by the time lead/lag of other secondary biophysical factors. The results could serve as a valuable reference for coping with the growing heat risk in cities. Key Points: The seasonality of surface and canopy urban heat island exhibited hysteresis‐like curves, whose looping patterns vary across background climate and urban featuresA simplified conceptual model to explain hysteretic behaviors was constructed based on a second‐order Fourier representation, the attribution method and a newly developed land surface modelThe urban‐biosphere time lags of evaporative cooling rates and storage heat, dominated such hysteresis at daytime and nighttime respectively [ABSTRACT FROM AUTHOR]

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems. [ABSTRACT FROM AUTHOR]

During the 2008 financial crisis, central banks (such as the Fed) adopted a quantitative easing (QE) policy to stimulate their countries' economies and overcome severe economic and financial recessions. However, apart from stimulating the economy by issuing a substantial amount of currency to purchase long-term bonds and suppress interest rates, QE policy also contributed to a boom in the real estate and construction sectors. Therefore, this study employs data envelopment analysis to measure the business performance (BP) of construction companies, and explore the impact of QE policy on the BP of construction companies, between 2004 and 2015, using hierarchical regression. We also examine the moderating role of the debt ratio on the relationship. Focused on publicly listed construction companies in Taiwan, this research reveals three encouraging findings. Firstly, QE policy indeed enhanced the BP of Taiwanese construction companies. Secondly, performance improvements in construction companies due to QE policy show a time-diminishing trend, suggesting the importance of seizing the initial policy benefits of QE implementation. Lastly, construction companies with appropriate financial leverage may exhibit better BP. These findings can provide valuable insights for relevant government entities and decision-makers in the industry for policy and investment decisions. [ABSTRACT FROM AUTHOR]

Social media not only changes the traditional communication environment but also brings new changes to agenda-setting. The main body of agenda-setting has shifted from the traditional media to the politicians, political parties and grassroots people. With the increasing use of social bots in public opinion manipulation and political election interference, whether they can participate in or influence agenda-setting has become an urgent concern. So far, there has been less literature focusing on engagement in agenda-setting for social bots. This paper studies the social media discussion content of the South Korean presidential election, determines the participation of social bots, and explores the connection between media agenda, bot agenda, and public agenda from the perspective of agenda setting. This study finds that while the main agendas of media, social bots, and the public are not the same, their agendas are relevant. In addition, the media agenda is not timely ahead of the bot agenda and the public agenda, and the time order only appears between the social bots and the public. [ABSTRACT FROM AUTHOR]

Purpose: Climate change, largely caused by elevated carbon dioxide (CO2) concentrations, is a driver of lasting disturbances that cause changes in forest ecosystem functioning. This study aimed to investigate how Japanese cypress (Chamaecyparis obtusa) and Japanese cedar (Cryptomeria japonica D. Don) plantations in the subtropical forests of China respond to disturbances in tree growth under climate change. Materials and methods: In this study, 23 canopy gaps were selected from two species in the Lushan National Nature Reserve of Jiangxi Province, China. Increment cores were obtained from trees retained near the edges of gaps and within the forest. Tree-ring chronologies were established, and the basal area increment (BAI) was calculated. The growth averaging method was used to detect growth release and analyze two key parameters of tree radial growth: magnitude and time lag. Moving correlation analyses were used to assess the long-term relationship between tree growth and climate, and regression analyses were used to quantify the relationship between the BAI and atmospheric CO2 concentrations. Results and discussion: Species characteristics, tree distance from the gap center, gap size, and elevation all influenced tree growth release which was greater for Japanese cedar than Japanese cypress, and decreased with increasing distance from the gap center. Diameter at breast height (DBH) and pre-release growth influenced the time lag in growth release. The time-lag effect was more significant with smaller DBH and pre-release growth and did not differ between the two species. The correlations among growth, temperature, and precipitation were altered by the microclimatic environment created by the gaps. The BAI of Japanese cypress and Japanese cedar responded quadratically with increasing CO2 concentration (Ca), and the BAI increased with rising Ca, peaking at 360–380 ppm, followed by a decreasing trend. Due to the effect of the disturbance, there was a BAI increase of approximately 400 ppm (2015) for trees at the gap edge. Conclusions: Growth characteristics were influenced by tree- and gap-level variables. Disturbance altered the link between tree growth and climate responses, increasing tree growth sensitivity to climatic influences, shifting the quadratic relationship between BAI and CO2 concentration, and providing growth potential to trees that crossed the CO2 tipping point. [ABSTRACT FROM AUTHOR]

In this study, we devise a parameter-uniform second-order numerical method for two-parameter singularly perturbed partial differential equations with large time lag. The equations are discretized using the Crank–Nicolson method in time direction on uniform mesh and the cubic spline method in space direction on a Bakhvalov mesh. The theoretical parameter-uniform convergence analysis and the numerical results proves that the present method gives second-order ɛ−uniform convergence both in space and time directions. Two numerical experiments are performed.

The fluctuations in groundwater levels (GWLs) in the Beijing Plain area are profoundly affected by precipitation (Pre) and groundwater (GW) overexploitation, altering regional water cycle processes and constraining regional economic and ecological development. The South-to-North Water Diversion Project (SWDP) has altered water supply structure in Beijing, leading to a new pattern in GWL fluctuations. This study quantitatively analyzes the evolution patterns of shallow GWLs and quantifies the response relationship between Pre-driven GWL-response on spatial and temporal scales before and after the SWDP. Using GWL and Pre data from 2000 to 2021, employs the coefficient of variation to analyze interannual variability, identifies variation points using the Pettitt and sliding T-test combined with correlation coefficient-based method for the classification of jump degree (R_Jump degree), subsequently divides the sub-sequences. The hydrological trend variation classification method based on correlation coefficient (R_Trend) is used to quantify the spatiotemporal evolution patterns of GWLs in each sub-sequence, and cross-correlation analysis is utilized to examine the time-lag characteristics of GWL responses to Pre in each sub-sequence. The results indicate: (1) GWLs exhibited jump variations in 2015 and 2017, with variation degrees mainly of moderate and strong, and correlation coefficients ranging from 0.18 to 0.67; (2) The overall trend of GWLs shifted from a significant decline to a substantial rebound before and after the SWDP. However, GWLs in the toe of the alluvial fan continued to show a decreasing trend until 2017; (3) The time lag between Pre and GWLs shortened by 6–10 months before and after the SWDP, with the toe of the alluvial fan showing a longer lag time due to over-exploitation. The Pre-GWL lag pattern mainly depends on GW extraction. Compared to existing methods, this paper proposes a research framework for systematically and comprehensively quantifying the evolution of GWLs and their response patterns to Pre, clearly revealing the natural-artificial water cycle processes in the Beijing Plain, providing scientific basis for ecological conservation and water resource management.

This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal performance. The finite element approach was used to solve the incompressible Navier-Stokes and energy equations to analyze the dynamic thermal response of walls exposed to real thermal excitations of the Marrakesh climate. The results show that increasing the emissivity from 0.1 to 0.9 significantly increases the total heat load over 24 h. Furthermore, filling 100% of the cavities with insulation materials delayed the temperature peak by about 2.3 h and lowered the decrement factor by roughly 43%, with a value smaller than 0.07. In addition, it is demonstrated that the total thermal load is reduced by approximately 28% for improved wall configurations (100% insulation filling cavities) compared to traditional wall configurations (100% air filling cavities), which aids in improving building energy efficiency.

Summary: Global change has accelerated local species extinctions and colonizations, often resulting in losses and gains of evolutionary lineages with unique features. Do these losses and gains occur randomly across the phylogeny?We quantified: temporal changes in plant phylogenetic diversity (PD); and the phylogenetic relatedness (PR) of lost and gained species in 2672 semi‐permanent vegetation plots in European temperate forest understories resurveyed over an average period of 40 yr.Controlling for differences in species richness, PD increased slightly over time and across plots. Moreover, lost species within plots exhibited a higher degree of PR than gained species. This implies that gained species originated from a more diverse set of evolutionary lineages than lost species. Certain lineages also lost and gained more species than expected by chance, with Ericaceae, Fabaceae, and Orchidaceae experiencing losses and Amaranthaceae, Cyperaceae, and Rosaceae showing gains. Species losses and gains displayed no significant phylogenetic signal in response to changes in macroclimatic conditions and nitrogen deposition.As anthropogenic global change intensifies, temperate forest understories experience losses and gains in specific phylogenetic branches and ecological strategies, while the overall mean PD remains relatively stable. [ABSTRACT FROM AUTHOR]

This study presents our first discovery about two abnormal problems in the blackbody calibration target associated with the antenna unit A2 in the Metop-C AMSU-A instrument. The problems include the anomalous patterns in both blackbody kinetic temperature T w and radiative temperature (measured in warm count or C w ), and the time lag between orbital cycles of T w and C w . This study further determines solar intrusion as the root cause of the anomalous pattern problem. According to our analysis, solar illumination is constantly observed during each orbit near the satellite terminator, causing anomalous changes in C w and T w , characterized by sudden and abnormal increases typically for more than 16 min. The resultant maximum antenna temperature errors due to abnormal increases in C w are approximately in the range from 0.15 K to 0.25 K, while the maximum errors due to the abnormal increase in T w are in the range from 0.04 K to 0.07 K, varying with orbit, season, and channel. The time shift feature is characterized with a changeable time lag with the season in the T w orbital cycle in comparison with the C w cycle. The longest time lag up to about 18 min occurs in summer through early fall, while the time lag can be decreased down to about 9 min in winter through early spring. Hence, this study underscores the imperative need for future research to rectify radiance errors and reconstruct a more accurate long-term Metop-C AMSU-A radiance data set for channels 1 and 2, crucial for climate studies. [ABSTRACT FROM AUTHOR]

The building sector's energy consumption remains a significant problem, requiring the development of powerful energy management systems to improve energy efficiency. The main aim of this research is to forecast energy use through indoor temperature, relative humidity, time, and time lag as crucial factors. The research project aims to enhance power consumption forecasting throughout the operating phase of buildings by using advanced machine learning (ML) regression models such as XGBoost, LightGBM, Extra Trees, and Random Forest. The dataset includes 10 days during which the building's operation testing took place, illustrating the complexities of real-world conditions. The inclusion of time-related characteristics and time delay arises as a critical element in enhancing prediction accuracy, emphasizing the temporal sensitivity of power use. A hyperparameter tuning method was used to improve the performance of the implemented ML algorithms. The results emphasize the effectiveness of Extra Trees as the most suitable model for forecasting power consumption in building operations with an accuracy of 88.41%. [ABSTRACT FROM AUTHOR]

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We introduce a parabolic version of the so-called John–Nirenberg space that is a generalization of functions of parabolic bounded mean oscillation. Parabolic John–Nirenberg inequalities, which give weak type estimates for the oscillation of a function, are shown in the setting of the parabolic geometry with a time lag. Our arguments are based on a parabolic Calderón–Zygmund decomposition and a good lambda estimate. Chaining arguments are applied to change the time lag in the parabolic John–Nirenberg inequality. [ABSTRACT FROM AUTHOR]

An insulated building-integrated photovoltaic (PV) roof prototype is designed, developed, and experimentally monitored for the composite climatic conditions in the current work. The prototype is monitored based on hourly indoor room temperature, relative humidity, discomfort index, decrement factor time lag, and power generation. To validate the results, a heat conduction equation was developed and simulated considering actual lower income group (LIG) building size and materials. Second-order polynomial equations were derived from simulation results to optimize insulation thickness. Additionally, the economic analysis of the insulated building-integrated Photovoltaic (BIPV) roof was analyzed and compared to the reinforced concrete cement (RCC) roof. The results reveal that insulated BIPV roofs outperform the RCC roof, reducing indoor temperatures by 3.34 ℃ to 1.37 ℃ within an optimum thickness range of 0.0838–0.1056 m. A time lag of 1 h and a significant reduction in decrement factor up to 0.29 are achieved. The average discomfort index of the proposed roof during sunshine hours was found to be between 23 and 26.5. The insulated BIPV roofs with levelized cost of electricity (LCOE) of the 3.38 Rs/kWh gave a payback period of 6.32 years and a higher internal rate of return of 29.4 compared to RCC roof. The current study increases the feasibility of PV modules to be used as building material. [ABSTRACT FROM AUTHOR]

Due to multiple land‐cover changes, forest herb populations residing in forest patches embedded in agricultural landscapes display different ages and, thus, experience differences in genetic exchange, mutation accumulation and genetic drift. The extent of divergence in present‐day population genetic structure among these populations of different ages remains unclear, considering their diverse breeding systems and associated pollinators. Answering this question is essential to understand these species' persistence, maintenance of evolutionary potential and adaptability to changing environments. We applied a multi‐landscape setup to compare the genetic structure of forest herb populations across forest patches of different ages (18–338 years). We studied the impact on three common slow‐colonizer herb species with distinct breeding systems and associated pollinators: Polygonatum multiflorum (outcrossing, long‐distance pollinators), Anemone nemorosa (outcrossing, short‐distance pollinators) and Oxalis acetosella (mixed breeding). We aimed to assess if in general older populations displayed higher genetic diversity and lower differentiation than younger ones. We also anticipated that P. multiflorum would show the smallest while O. acetosella the largest difference, between old and young populations. We found that older populations had a higher observed heterozygosity (Ho) but a similar level of allelic richness (Ar) and expected heterozygosity (He) as younger populations, except for A. nemorosa, which exhibited higher Ar and He in younger populations. As populations aged, their pairwise genetic differentiation measured by DPS decreased independent of species identity while the other two genetic differentiation measures showed either comparable levels between old and young populations (G"ST) or inconsistency among three species (cGD). The age difference of the two populations did not explain their genetic differentiation. Synthesis: We found restricted evidence that forest herb populations with different ages differ in their genetic structure, indicating that populations of different ages can reach a similar genetic structure within decades and thus persist in the long term after habitat disturbance. Despite their distinct breeding systems and associated pollinators, the three studied species exhibited partly similar genetic patterns, suggesting that their common characteristics, such as being slow colonizers or their ability to propagate vegetatively, are important in determining their long‐term response to land‐cover change. [ABSTRACT FROM AUTHOR]

Understanding developments in the trunk sap flow of prevalent tree species within the hilly areas of the Haihe River basin is imperative for ecosystem conservation. Nevertheless, the changes in sap flow of local trees and their response to environmental factors remain elusive. This study focuses on seven dominant tree species in the hilly area of the Haihe River basin and analyzed the relationship between tree sap flow rate and environmental factors at different time scales (hourly and daily). Our findings suggested: (1) Regardless of the time scale, total solar irradiance played a primary role in influencing sap flow rate. Conversely, as the time scale grew, the associations between most soil factors and sap flow rate enhanced, while those with meteorological factors declined. Notably, soil temperature exerted a more profound influence on sap flow rate than soil moisture and conductivity. (2) At the hourly scale, the sap flow rate of each species had a lag effect of 1–2 h with vapour pressure deficit, relative humidity and temperature, and 1 h or no lag effect with total solar irradiance and wind speed. (3) The response model of sap flow rate and environmental factors showed that, except for Pinus tabuliformis Carr., other tree species fit well at various time scales (R2 ≥ 0.59). As the time scale of most tree species increased from hourly scale to daily scale, the fit gradually weakened. Concurrently, considering the time-lag effect, the accuracy of the model has been improved, and the fitting accuracy of Koelreuteria paniculata Laxm. and Pinus tabuliformis Carr. has been significantly improved. [ABSTRACT FROM AUTHOR]

This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal performance. The finite element approach was used to solve the incompressible Navier-Stokes and energy equations to analyze the dynamic thermal response of walls exposed to real thermal excitations of the Marrakesh climate. The results show that increasing the emissivity from 0.1 to 0.9 significantly increases the total heat load over 24 h. Furthermore, filling 100% of the cavities with insulation materials delayed the temperature peak by about 2.3 h and lowered the decrement factor by roughly 43%, with a value smaller than 0.07. In addition, it is demonstrated that the total thermal load is reduced by approximately 28% for improved wall configurations (100% insulation filling cavities) compared to traditional wall configurations (100% air filling cavities), which aids in improving building energy efficiency. [ABSTRACT FROM AUTHOR]

Wastewater surveillance has been widely implemented to monitor COVID-19 incidences in communities worldwide. One notable application of wastewater surveillance is for providing early warnings of disease outbreaks. Many studies have reported time lags between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) wastewater concentrations and confirmed clinical COVID-19 cases. To our best knowledge, only a few studies to date have explored time lags between SARS-CoV-2 wastewater concentrations and other clinical metrics. In this study, we investigated time lags between SARS-CoV-2 wastewater concentrations and three COVID-19 clinical metrics: confirmed clinical cases, hospitalizations, and intensive care unit (ICU) admissions, in the Tricounty Detroit Area, Michigan, US. The COVID-19 clinical metrics were dated between September 1, 2020, and October 31, 2022, and were collected from public data sources. SARS-CoV-2 N1 and N2 gene concentrations between September 1, 2020, and May 31, 2022, were generated using two sampling and concentration methods: virus adsorption-elution (VIRADEL) and polyethylene glycol precipitation (PEG). The data were collected from our recently published study. Time-lagged cross correlation was implemented to estimate time lags between gene concentrations and the three clinical metrics. Original gene concentrations were normalized by wastewater flow parameters through nine approaches to estimate the impact of wastewater flow on time lags. Vector autoregression models were established to analyze the relationship between gene concentrations and clinical metrics. The results indicate that VIRADEL gene concentrations in wastewater preceded all clinical metrics prior to the COVID-19 Omicron surge, for instance, 32, 47, and 51 days preceding confirmed cases, hospitalizations, and ICU admissions, respectively (gene concentrations unit: gc/day). When translated to a public health context, these time lags become critical lead times for officials to prepare and react. During the Omicron surge, there were significant reductions in time lags, with VIRADEL measurements trailing total ICU admissions. PEG measurements lagged behind the three clinical metrics and did not provide early warnings of disease surges. [ABSTRACT FROM AUTHOR]

The escalating frequency and severity of extreme climate greatly impact the carbon dynamics of terrestrial ecosystems worldwide. To understand the multi-temporal response of net ecosystem productivity (NEP) to extreme climate, we investigated 11 temperature and precipitation extreme indices across different vegetation types in China. From 1981 to 2019, the results showed that NEP in China increased at a rate of 0.64 g·m−2·a−2. Extreme climate demonstrated a significant warming trend and a non-significant moistening trend; specifically, maximum daily minimum temperature (TNx) exhibited a significant increase at a rate of 0.34 °C/10 a, while maximum 5-day precipitation (Rx5day) showed an insignificant increase at a rate of 1.78 mm/10 a. NEP was significantly impacted by extreme temperature at the annual, seasonal, and monthly scales, but moderately impacted by extreme precipitation. Specifically, extreme temperature had the most significant effect on grassland, with minimal influence on cropland. In contrast, extreme precipitation had the most significant effect on forest, with minimal impact on cropland. Moreover, the lagged time for extreme precipitation was longer than that for extreme temperature. Extreme precipitation exhibited a corresponding lagged time of at least 2 months (p < 0.01), while extreme temperature exhibited a lagged time of at least 1 month (p < 0.01). The maximum lag time observed was 4 months (p < 0.01). Our findings provide valuable insights into the multi-temporal response of NEP to extreme climate in China and inform sustainable development practices in the region. [ABSTRACT FROM AUTHOR]

The Lower Yellow River (LYR) is a vital water resource for agriculture, industry, and domestic use in the surrounding areas. Understanding the delayed response of local streamflow response to remote reservoir operations is crucial for effective water management and flood control. In this work, we utilize historical hydrological data and statistical analysis techniques to investigate the time-lagged response of streamflow in the LYR to water regulation by the Xiaolangdi Reservoir. The results demonstrate that there is a time lag of 1.98 days, 2.86 days, and 3.93 days between the record of water regulation at Xiaolangdi Reservoir and the arrival time at Gaocun, Aishan, and Lijin stations, respectively. Time lag correction is proven to be crucial when establishing the relationship between the daily streamflows in the LYR and those at Xiaolangdi station. Further analysis reveals that the travel distance of streamflow is the dominant factor determining the lag time, with a time lag coefficient of 0.57 days per hundred kilometers. It is expected that the findings in this study could offer a fundamental basis for decision-makers in water resource management. [ABSTRACT FROM AUTHOR]

Jatiluhur dam, located in West Java province, is one of the most extensive reservoirs in Indonesia and is used to secure the water supply for 240,000 ha of rice fields to prevent agricultural drought in the downstream Citarum watershed. During the last two decades, several areas in the downstream Citarum watershed have been experiencing agricultural drought following meteorological drought events. This study aimed to examine the spatiotemporal patterns of agricultural drought and their correlation with meteorological drought occurrence by utilizing a remote sensing image processing technique. The Normalized Difference Drought Index (NDDI) and Standardized Precipitation Index (SPI) derived from MODIS and CHIRPS data were used to estimate agricultural and meteorological drought events, respectively. The results showed that the magnitude of agricultural drought in the downstream Citarum watershed was varied and related to earlier meteorological drought. The agricultural drought mainly occurred after a meteorological event with the magnitude mostly related to the magnitude of the ONI and DMI. A strong El Nino and positive IOD will cause a higher magnitude of agricultural drought. The time lag between the two drought occurrences was found to be related to the distance of the paddy fields from the main irrigation network and the proximity of the main irrigation network to the Jatiluhur Dam spillway.

Abstract Background Mara River Basin is an ecologically fragile area in East Africa, with a pattern of alternating wet and dry seasons shaped by periodic precipitation. Considering the regional biological traits and climatic change, the vegetation's response to seasonal variation is complicated and frequently characterized by time lags. This study analyzed the variation of the Normalized Difference Vegetation Index (NDVI) and investigated its time lag to precipitation at the monthly scale. NDVI characteristic peaks were proposed from the perspective of seasonal mechanisms and were quantified to assess the lag effect. Results The results showed that the Anomaly Vegetation Index could identify low precipitation in 2006, 2009, and 2017. The NDVI showed an increasing trend in 75% of areas of the basin, while showed a decreased significance in 3.5% of areas, mainly in savannas. As to the time lag, the 1-month lag effect dominated most months, and the spatiotemporal disparities were noticeable. Another method considering the alternations of wet and dry seasons found that the time lag was approximately 30 days. Based on the time distribution of NDVI characteristic peaks, the average time lag was 35.5 days and increased with the range of seasons. Conclusions The findings confirmed an increasing trend of NDVI in most regions from 2001 to 2020, while the trends were most obvious in the downstream related to human activities. The results could reflect the time lag of NDVI response to precipitation, and the 1-month lag effect dominated in most months with spatial heterogeneity. Four NDVI characteristic peaks were found to be efficient indicators to assess the seasonal characteristics and had a great potential to quantify vegetation variation.

Purpose: For the drop-induced shock mitigation system with magnetorheological energy absorbers (MREAs), the time lag of MREA has a nonnegligible influence on the shock mitigation performance. This paper proposed a minimum transmitted load control method considering time lag (MTL-T) is proposed. Methods: First, the influence of a time lag on the shock mitigation performance is analyzed, and the relationship between the theoretical controllable force and the actual controllable force of the MREA with a time lag is given. Then, taking the controllable force of traditional MTL control method as the theoretical value and the "soft-landing" as the control target, the control algorithm of MTL-T control method is derived. Finally, the simulation is conducted for the shock mitigation system with variable parameters controlled by MTL-T, and the comparative performance of MTL-T control method and other methods is given. Results: The theoretical analysis shows that MTL-T control method can make the shock mitigation system with a time lag achieve the control target of "soft-landing". The advantages of MTL-T control method are shown by the comparative performance of the MTL-T control method and other methods. Conclusions: Once the parameters of the system and the impact intensity are obtained, the MTL-T can be determined. The adaptability of MTL-T control method is verified. Compared with other control method, the MTL-T has a small peak transmitted load while making full use of MREA. [ABSTRACT FROM AUTHOR]

Ionospheric responses to geomagnetic storms can cause irregular plasma structures and scintillation of Global Navigation Satellite System (GNSS) signals. In this paper, we investigate time lags between the detection of GNSS signal scintillation at northern hemisphere auroral latitudes and the onset of 15 geomagnetic storms that occurred in 2015–2017. The results show that the time lags between the detection of ground‐based GNSS scintillations and the observed sudden change in solar wind parameters are between tens of minutes and 15 hr. This time lag consists of two segments. The first segment is about 30–80 min, which is the lag between observed disturbances in the geomagnetic field and solar wind disturbances detected by orbiting spacecrafts around the L1 point. The second segment is between the observed GNSS signal scintillation and the storm sudden commencement (SSC). This second lag segment varies in the range of about 10–830 min and highly depends on the storm onset time and geomagnetic locations of GNSS signal propagation paths. Longer time lags over 450 min were observed with the signal ionospheric piercing point at 60–70° geomagnetic latitudes (MLAT) on the dayside, while shorter lags of 10∼450 min were observed with the signal IPPs at 68–81° MLAT and on the nightside at the time of SSC. The lag time variations can be explained by ionospheric irregularity production and transport processes associated with a variety of auroral and polar cap phenomena in response to solar wind coupling to the magnetosphere and ionosphere. Key Points: Time lags between storm sudden commencement and scintillation detections by ground‐based Global Navigation Satellite System receivers at northern auroral latitudes were surveyedThe time lags varied with geomagnetic latitude and magnetic local time of satellite‐receiver line‐of‐sight signal paths assumed at ionospheric piercing pointsShorter time lag was detected by the observations close to aurora cusp as well as those on the nightside at the storm onset [ABSTRACT FROM AUTHOR]

Quantitative criminologists often use temporally lagged variables to estimate the structural forces contributing to variation in crime rates. We elucidate the relevance of temporal lags for cross-national research by looking specifically at the lagged longitudinal relationship between urbanization and homicide rates. Using cross-national time-series data for (n = 83) nations, we run a series of 10 separate panel models, in which we incrementally increase the time lag between the dependent variable homicide rate and two independent measures of urbanization, controlling for changes in GDP and age-structure as well as fixed effects for time and unit. Results from these panel models confirm that the two measures of urbanization are oppositely associated with homicide rates. Moreover, while the magnitudes of the associations for both predictors decline as lag time increases, they continue to be statistically significant. These results provide evidence that urbanization has countervailing and persistent consequences for homicide rates that ripple through time. These results also lead us to conclude that a more systematic approach to lag time in longitudinal research is needed. [ABSTRACT FROM AUTHOR]

Background: Mara River Basin is an ecologically fragile area in East Africa, with a pattern of alternating wet and dry seasons shaped by periodic precipitation. Considering the regional biological traits and climatic change, the vegetation's response to seasonal variation is complicated and frequently characterized by time lags. This study analyzed the variation of the Normalized Difference Vegetation Index (NDVI) and investigated its time lag to precipitation at the monthly scale. NDVI characteristic peaks were proposed from the perspective of seasonal mechanisms and were quantified to assess the lag effect. Results: The results showed that the Anomaly Vegetation Index could identify low precipitation in 2006, 2009, and 2017. The NDVI showed an increasing trend in 75% of areas of the basin, while showed a decreased significance in 3.5% of areas, mainly in savannas. As to the time lag, the 1-month lag effect dominated most months, and the spatiotemporal disparities were noticeable. Another method considering the alternations of wet and dry seasons found that the time lag was approximately 30 days. Based on the time distribution of NDVI characteristic peaks, the average time lag was 35.5 days and increased with the range of seasons. Conclusions: The findings confirmed an increasing trend of NDVI in most regions from 2001 to 2020, while the trends were most obvious in the downstream related to human activities. The results could reflect the time lag of NDVI response to precipitation, and the 1-month lag effect dominated in most months with spatial heterogeneity. Four NDVI characteristic peaks were found to be efficient indicators to assess the seasonal characteristics and had a great potential to quantify vegetation variation. [ABSTRACT FROM AUTHOR]

A theoretical study was conducted to examine the flame transfer function (FTF) of a diverging premixed flame subject to uniform and/or convective velocity disturbances considering developing turbulent flame speed. The FTF under uniform velocity disturbances with developing flame speed is less oscillatory compared with constant flame speed, and the magnitude of the aforementioned FTF is decreased more rapidly with an increase in turbulent time scale or flame length. The peak overshoot of the FTF under convective velocity disturbances is observed in a certain frequency range, which is known to be a typical nature of the FTF of a diverging flame under convective velocity disturbances. Such peak overshoot is quite sensitive to how the turbulent flame speed varies along the flame front in case of developing flame speed while the amplitude of the peak overshoot rarely changes with the mean flame length in case of constant flame speed. [ABSTRACT FROM AUTHOR]

This research focuses on the integration of waste materials derived from sugar sediment and recycled AAC into the manufacturing process of autoclaved aerated concrete (AAC) to enhance its physical, mechanical, and thermal characteristics. Furthermore, the investigation explores the prospect of augmenting the thermal efficiency of the AAC composite by applying different quantities of paraffin phase change material (PCM) coatings to its external surface. Throughout the thermal testing phase, temperature control was consistently maintained at three distinct levels: 40 °C, 50 °C, and 60 °C, facilitated by a heater serving as the thermal source. The investigation unveiled that the optimal composition encompassed a 10% by weight replacement of sand with recycled AAC content. This formulation resulted in a peak compressive strength of around 5.85 N/mm2, along with a maximum tobermorite phase ratio of 25.5%. The elevated strength is directly associated with the heightened crystalline nature of the tobermorite phase. The most favorable configuration incorporated a 20 g PCM-coated material, demonstrating remarkable outcomes, including an extension of the time lag by about 55%, a reduction in the decrement factor by around 56.4%, as well as a substantial reduction in room temperature of roughly 15.8% compared to standard AAC without PCM coating, all at a stable temperature of 60 °C. The integration of sustainable waste materials and PCM technology, as illustrated in this study, notably contributes to resource conservation and the advancement of energy-efficient architectural practices. [ABSTRACT FROM AUTHOR]

Ambient ammonia (NH3) plays an important compound in forming particulate matters (PMs), and therefore, it is crucial to comprehend NH3′s properties in order to better reduce PMs. However, it is not easy to achieve this goal due to the limited range/real-time NH3 data monitored by the air quality stations. While there were other studies to predict NH3 and its source apportionment, this manuscript provides a novel method (i.e., GEO-AI)) to look into NH3 predictions and their contribution sources. This study represents a pioneering effort in the application of a novel geospatial-artificial intelligence (Geo-AI) base model with parcel tracking functions. This innovative approach seamlessly integrates various machine learning algorithms and geographic predictor variables to estimate NH3 concentrations, marking the first instance of such a comprehensive methodology. The Shapley additive explanation (SHAP) was used to further analyze source contribution of NH3 with domain knowledge. From 2016 to 2018, Taichung's hourly average NH3 values were predicted with total variance up to 96%. SHAP values revealed that waterbody, traffic and agriculture emissions were the most significant factors to affect NH3 concentrations in Taichung among all the characteristics. Our methodology is a vital first step for shaping future policies and regulations and is adaptable to regions with limited monitoring sites.

Abstract Due to multiple land‐cover changes, forest herb populations residing in forest patches embedded in agricultural landscapes display different ages and, thus, experience differences in genetic exchange, mutation accumulation and genetic drift. The extent of divergence in present‐day population genetic structure among these populations of different ages remains unclear, considering their diverse breeding systems and associated pollinators. Answering this question is essential to understand these species' persistence, maintenance of evolutionary potential and adaptability to changing environments. We applied a multi‐landscape setup to compare the genetic structure of forest herb populations across forest patches of different ages (18–338 years). We studied the impact on three common slow‐colonizer herb species with distinct breeding systems and associated pollinators: Polygonatum multiflorum (outcrossing, long‐distance pollinators), Anemone nemorosa (outcrossing, short‐distance pollinators) and Oxalis acetosella (mixed breeding). We aimed to assess if in general older populations displayed higher genetic diversity and lower differentiation than younger ones. We also anticipated that P. multiflorum would show the smallest while O. acetosella the largest difference, between old and young populations. We found that older populations had a higher observed heterozygosity (Ho) but a similar level of allelic richness (Ar) and expected heterozygosity (He) as younger populations, except for A. nemorosa, which exhibited higher Ar and He in younger populations. As populations aged, their pairwise genetic differentiation measured by DPS decreased independent of species identity while the other two genetic differentiation measures showed either comparable levels between old and young populations (G"ST) or inconsistency among three species (cGD). The age difference of the two populations did not explain their genetic differentiation. Synthesis: We found restricted evidence that forest herb populations with different ages differ in their genetic structure, indicating that populations of different ages can reach a similar genetic structure within decades and thus persist in the long term after habitat disturbance. Despite their distinct breeding systems and associated pollinators, the three studied species exhibited partly similar genetic patterns, suggesting that their common characteristics, such as being slow colonizers or their ability to propagate vegetatively, are important in determining their long‐term response to land‐cover change.

To solve the problems of time lag and high repetition rate of information released in the media-oriented information display of college libraries, this paper improves the media-oriented information display platform based on the numerical method of generalized differential equations. The intervals of the generalized differential equations solutions for the media-oriented information display of college libraries are discretized using a grid to obtain sub-intervals. The points on the grid for each subinterval are approximated continuously using the K-step edge-value method to obtain the information dissemination cycle solution. The bifurcated periodic solution is used to check the obtained information release period solution, and the final information update period is 7 days. The results of improving the media-based information display platform of university libraries and putting it into operation of university libraries show that: Using the information update cycle determined by the generalized differential function to improve the media-based information display platform of university libraries, the repetition rate of language information release decreases from 30% to 10%. The working hours of librarians were reduced from 5 hours per week to 3.5 hours per week. It can be seen that after improving the media-based information display platform of university libraries based on the numerical method of a generalized differential equation, the repetition rate of information release and the work efficiency of librarians of the platform is improved.

Based on empirical data, this paper attempts modelling, in general terms, the relationship between money supply and inflation, i.e., the relationship between the inflation rate and monetary aggregates. Our basic idea is to estimate time-shift parameters and, subsequently, a leading indicator that would provide information on whether and with what delay changes in the money supply will be reflected in the price level evolution. The aim of the paper is to formulate and, on the basis of the data, to confirm or refute the hypothesis that changes in the value of monetary aggregates imply changes in the inflation rate and, therefore, whether or not monetary aggregates are certain indicators signalling further evolution of the inflation rate. Monthly data for the Czech Republic from the years 2002–2022 have been used to model and test our hypotheses. The analysis has failed to show a statistically significant relationship between the individual monetary aggregates and the inflation rate.

The eco-hydrological process related to vegetation on the Qinghai–Tibet Plateau is special, and the impact of snow cover on the growth of vegetation is unique and important. In this study, we analyzed the multi-year variations in the normalized difference vegetation index (NDVI) and snow cover on the Qinghai–Tibet Plateau from spatial and temporal perspectives and determined the relationship between the changes in the NDVI and snow cover. Results showed that in the last 40 years, the rate of change in the snow depth on the plateau was −0.016 mm/a, and the NDVI changed by 0.0005/a. The correlations (|R| values) between the different factors and the NDVI followed the order of precipitation (0.77) > snow depth (0.76) > temperature (0.67) > solar radiation (0.21). The responses of the NDVI to changes in meteorological elements were synchronous, whereas the opposite was found for the snow cover. The snow cover had more significant impacts on vegetation at higher elevations. The NDVI had a lag of about 2 months from the onset of the snow cover, and heavy snow events had negative impacts on the NDVI for more than 3 years. Our findings will facilitate studies of ecological vulnerability and the predictions of changes in vegetation on the plateau.