A sound evaluation of the cadmium (Cd) mass balance in agricultural soils needs accurate data of Cd leaching. Reported Cd concentrations from in situ studies are often one order of magnitude lower ...than predicted by empirical models, which were calibrated to pore water data from stored soils. It is hypothesized that this discrepancy is related to the preferential flow of water (non-equilibrium) and/or artefacts caused by drying and rewetting soils prior to pore water analysis. These hypotheses were tested on multiple soils (n = 27) with contrasting properties. Pore waters were collected by soil centrifugation from field fresh soil samples and also after incubating the same soils (28 days, 20 °C), following two drying-rewetting cycles, the idea being that chemical equilibrium in the soil is reached after incubation. Incubation increased pore water Cd by a factor 4, on average, and up to a factor 16. That increase was statistically related to the decrease of pore water pH and the increase of nitrate, both mainly related to incubation-induced nitrification. After correcting for both factors, the Cd rise was also highest at higher pore water Ca. This suggests that higher Ca in soil enlarges Cd concentration gradients among pore classes in field fresh soils because high Ca promotes soil aggregation and separation of mobile from immobile water. Several empirical models were used to predict pore water Cd. Predictions exceeded observations up to a factor 30 for the fresh pore waters but matched well with those of incubated soils; again, deviations from the 1:1 line in field fresh soils were largest in high Ca (>0.8 mM) soils, suggesting that local equilibrium conditions in field fresh soils are not found at higher Ca. Our results demonstrate that empirical models need recalibration with field fresh pore water data to make accurate soil Cd mass balances in risk assessments.
Display omitted
•Soil incubation after drying and rewetting alters pore water Cd.•Incubation promotes chemical equilibrium and nitrification.•Low pore water Ca is concurrent with high Cd in pore waters from field fresh soils.•Empirical models based on incubated soils overestimate Cd in solution if equilibrium is unlikely.
•A reactive CFD-DEM model was developed on the open-source MFIX-DEM software.•The model was validated with the experimental data and simulation results.•The sensitivity analysis was conducted about ...contact and drag models.
A user-defined solver towards the high-fidelity CFD-DEM method with thermochemical sub-models integrating is developed based on the open-source MFIX-DEM software for simulating biomass gasification in a fluidized bed reactor. In this method, the fluid phase is solved under Eulerian framework while the solid motion is solved under Lagrangian framework. The inter-particle and inter-phase interactions, heat and mass transfer, gas turbulence, radiation, particle conversion, drying, pyrolysis, and homogeneous reactions are synthetically considered. The method is validated with experimental data and simulation results, and the sensitivity analysis is conducted for assessing the influence of contact and drag models on the CFD-DEM simulation of biomass gasification. Results show that the magnitude of total calculation time for the non-linear Hertzian contact model is 6.8 times of that for the linear LSD contact model. The drag models significantly affect the gas-solid flow dynamics while having a slight influence on the thermochemical results obtained at the reactor exit. As a result, the present work delivers a promising perspective for modeling thermochemical processes (e.g., fast pyrolysis, coal combustion, iron smelting, and tablet coating) in dense reactive particulate systems by using the open-source MFIX-DEM software.
The extensive exploitation and use of land resources has caused a variety of land degradation problems including soil erosion, desertification and salinization in China, which gradually raises our ...concerns of ecological security. However, there still lacks an understanding of ecological security of land resources at the national scale. Moreover, few studies conduct the validation and uncertainty analysis of models for ecological security evaluation, which tends to undermine the reliability of evaluation results. Here we followed the Pressure-State-Response (PSR) framework to systematically construct the evaluation index system for ecological security, and developed fuzzy evaluation models to convert the original index data into individual index scores. After that, we used the multiplicative model to aggregate the individual index scores into a comprehensive evaluation score for the ecological security level of land resources across the Chinese mainland. To enhance the reliability of evaluation results, we validated our results by comparing with the proxies of ecological effects including landscape pattern index, land use change rate and net primary productivity, and made uncertainty analysis using the Monte Carlo method. Finally, we applied an obstacle model to quantify the negative contribution of pressure, state and response which would deter the security from achieving the optimal condition. The results showed that our model could effectively reflect the ecological security level of land resources. The pressure was higher in the east and lower in the west of China, and that of urban areas was much higher than the rural areas, reflecting the disturbance of socio-economic activities. The state condition was strongly related to natural conditions. The response level, determined mainly by socio-economic conditions, was higher in the southeast and northwest of China but lower in the northeast and southwest of China. The ecological security level was structured by natural and socio-economic conditions and demonstrated a high level of security in the southeast while a low level in the northwest. Developed urban areas often had low security due to strong socio-economic pressure. Areas with unfavorable natural and environmental conditions had poor state level, which tended to cause lower response capability, and consequently led to a low security level. Our research improves the understanding of national ecological security and its obstacle factors, which supports the management and sustainable use of land resources at the national scale.
Display omitted
•We built a fuzzy evaluation model for ecological security using PSR framework.•Model was validated by proxies of ecological security and showed better reliability.•Uncertainty derived from weighing process was assessed.•We derived the pattern of ecological security of land resources in China.•Security in southeast of the Hu Huanyong Line is significantly higher than that in the northwest.
Abstract
Background
Rigorous evaluation of the calibration and discrimination of breast-cancer risk-prediction models in prospective cohorts is critical for applications under clinical guidelines. We ...comprehensively evaluated an integrated model incorporating classical risk factors and a 313-variant polygenic risk score (PRS) to predict breast-cancer risk.
Methods
Fifteen prospective cohorts from six countries with 239 340 women (7646 incident breast-cancer cases) of European ancestry aged 19–75 years were included. Calibration of 5-year risk was assessed by comparing expected and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50–70 years in those countries was evaluated by the proportion of women and future cases crossing clinically relevant risk thresholds.
Results
Among women <50 years old, the median (range) expected-to-observed ratio for the integrated model across 15 cohorts was 0.9 (0.7–1.0) overall and 0.9 (0.7–1.4) at the highest-risk decile; among women ≥50 years old, these were 1.0 (0.7–1.3) and 1.2 (0.7–1.6), respectively. The proportion of women identified above a 3% 5-year risk threshold (used for recommending risk-reducing medications in the USA) ranged from 7.0% in Germany (∼841 000 of 12 million) to 17.7% in the USA (∼5.3 of 30 million). At this threshold, 14.7% of US women were reclassified by adding the PRS to classical risk factors, with identification of 12.2% of additional future cases.
Conclusion
Integrating a 313-variant PRS with classical risk factors can improve the identification of European-ancestry women at elevated risk who could benefit from targeted risk-reducing strategies under current clinical guidelines.
Addressing heat stress in dairy farming is a substantial challenge, and there is an increasing need for efficient cooling systems, even in regions with moderate climates. Accurately predicting the ...efficacy of diverse cooling options under different climatic conditions is crucial for reducing heat stress in modern high-producing dairy cows, aligning with sustainability goals. This study assessed the effectiveness and feasibility of different cooling measures, including fans, sprinklers with fans, and evaporative air cooling, using a dynamic thermoregulatory model. This 3-node dynamic model was developed based on recent animal data simulating the processes of dairy cows' physiological regulation and heat dissipation under various environmental conditions. The cooling methods were based on two principles: enhancing heat loss from cows using fans with/without sprinklers; lowering the ambient temperature by evaporative air cooling. The predicted results were discussed and partly validated using the experimental data from the literature. The predictions indicated that fan cooling alone was effective in ambient temperatures below 26 °C, while higher temperatures required a combination of fans and sprinklers for effective heat stress alleviation. Consideration of individual cow characteristics and environmental factors, including fan speed and wetting area, is crucial for optimal cooling. In regions with high relative humidity, evaporative air cooling could be counterproductive to some extent. The model's predictions largely aligned with experimental data, demonstrating its capability to forecast cooling effects under various climatic conditions. Future model improvements included refining calculations for water holding capacity, wetted skin area, and dry time, depending on the influence of spraying time and rate.
•Effectiveness of different cooling interventions on cows was predicted.•The selection of cooling measures should consider individual cows and environmental factors.•In humid regions, evaporative air cooling could be counterproductive.
•PLS-PM has been subject to many improvements in last years.•Prior PLS guidelines have not covered the entire recent developments.•We explain how to perform and report an up-to-date empirical ...analysis with PLS.•We provide a fictive illustrative example on business value of social media.
Partial least squares path modeling (PLS-PM) is an estimator that has found widespread application for causal information systems (IS) research. Recently, the method has been subject to many improvements, such as consistent PLS (PLSc) for latent variable models, a bootstrap-based test for overall model fit, and the heterotrait-to-monotrait ratio of correlations for assessing discriminant validity. Scholars who would like to rigorously apply PLS-PM need updated guidelines for its use. This paper explains how to perform and report empirical analyses using PLS-PM including the latest enhancements, and illustrates its application with a fictive example on business value of social media.
Wave resource characterization is an essential step for wave energy converter development in the ocean. However, accurate and detailed resource characterization at a regional scale poses a great ...challenge because of the requirements for high model grid resolution, extensive model validation, and a high-performance-computing resource. This study presents a multi-scale, multi-resolution approach using the WaveWatchIII and Simulating WAve Nearshore (SWAN) wave models to provide accurate long-term wave hindcasts with a spatial resolution of approximate 300 m in the nearshore region on the U.S. West Coast. Extensive model validation for the six wave resource parameters recommended by the International Electrotechnical Commission, bivariate histograms, and frequency-directional spectra distributions were conducted using a set of model performance metrics and measurements from 28 wave buoys along the West Coast. Model skills in simulating large waves under extreme storm events were also evaluated. Model results showed that the high-resolution SWAN model is able to accurately simulate the wave climate on the West Coast, especially in the nearshore region. This study also demonstrates that the multi-scale and multi-resolution modeling framework is an efficient approach for generating accurate long-term, high-resolution wave hindcasts for wave resource characterization at the regional scale.
•A multi-scale, multi-resolution wave modeling system for the U.S. West Coast.•Unstructured-grid SWAN model with 300 m resolution for the nearshore region.•Extensive model validation using up to 32 years of wave data at 28 buoys.•Good model skills in simulating spatial and temporal variabilities of wave climate.•High-resolution modeling system improved model accuracy in large wave prediction.
•Model which simulates dairy farm electricity use in 15-min intervals.•Validated on 3 dairy farms of varying size.•Suitable for studying renewable energy integration and demand side ...management.•Reliable tool for decision support for dairy operations.
The objective of this paper was to define, validate and demonstrate a model capable of accurately simulating dairy farm electricity consumption across varying herd and parlour sizes, to facilitate research investigating renewable energy systems (RES) and demand side management (DSM). The Farm Electricity System Simulator (FESS) was developed using grey-box modelling techniques utilizing empirical data for parameter tuning. Empirical data were gathered from nine spring calving, pasture based dairy farms located in the Republic of Ireland. A k-means clustering analysis was conducted, separating the farms into three, near homogenous groups, from which representative farms were selected. FESS was trained using 12 months of data from three representative farms using the repeat hold out method for data partitioning with 75 % of data used for training and 25 % used for validation. An optimisation algorithm was used to minimize the error during model training. Through cross-validation, FESS achieved a root mean squared error (RMSE) of 7.65 kWh, mean absolute percentage error (MAPE) of 7.10 %, mean percentage error (MPE) of −0.86 % and a relative prediction error (RPE) of 7.56 % for total daily electricity consumption. Across the three farms, the simulated outputs of FESS achieved an average R2 value of 0.72, demonstrating good agreement with observed data. FESS’s utility was demonstrated by analysing the effects of different electricity pricing structures and on-site solar photovoltaic electricity generation on total farm energy costs. We concluded that FESS simulated on-farm electricity consumption with sufficient accuracy for the intended application. FESS accurately simulated dairy farm electricity consumption across three dairy farms of different herd and parlour sizes while evaluating the effects of demand side management and renewable generation on farm electricity consumption and costs.
•Few practical guidelines exist on the best guidelines of ecological niche models.•We present a step by step guideline with best practices for correlative models.•We focus on data preparation; model ...calculation, evaluation, and model application.•This guideline will help to obtain better results when using correlative models.
The use of correlative ecological niche models has highly increased in the last decade. Despite all literature and textbooks in this field, few practical guidelines exist on the correct application of these techniques. We present here a step-by-step guideline explaining best practices for calculating correlative ecological niche models considering their conceptual and statistical assumptions and limitations. We divided the modelling process into four stages: 1) data collection and preparation; 2) model calculation; 3) model evaluation and validation; 4) and model application. Based on ecological niche theory, we review the concepts of ecological niche and how they can be modelled; classes of correlative models; modelling software; selection of study area; data sources for species records and environmental variables; types of species records and their influence on correlative models; errors in species records; minimum number of species records and environmental variables; effects of prevalence, sampling design, biases, and collinearity between variables; model calculation; model projection to different scenarios in time and space; ensemble modelling; model validation; classification, discrimination and calibration metrics; calculation of null models; analysis of model results; and model thresholding. This guideline is expected to help potential users to obtain better results when using correlative ecological niche models.
PDF
