RESUMEN
With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution.
Asunto(s)
Arsénico , Monitoreo del Ambiente , Ríos , Contaminantes Químicos del Agua , Arsénico/análisis , China , Contaminantes Químicos del Agua/análisis , Ríos/química , Monitoreo del Ambiente/métodos , Modelos Químicos , Modelos TeóricosRESUMEN
A major next step in hematopoietic stem cell (HSC) biology is to enhance our quantitative understanding of cellular and evolutionary dynamics involved in undisturbed hematopoiesis. Mathematical models have been and continue to be key in this respect, and are most powerful when parameterized experimentally and containing sufficient biological complexity. In this paper, we use data from label propagation experiments in mice to parameterize a mathematical model of hematopoiesis that includes homeostatic control mechanisms as well as clonal evolution. We find that nonlinear feedback control can drastically change the interpretation of kinetic estimates at homeostasis. This suggests that short-term HSC and multipotent progenitors can dynamically adjust to sustain themselves temporarily in the absence of long-term HSCs, even if they differentiate more often than they self-renew in undisturbed homeostasis. Additionally, the presence of feedback control in the model renders the system resilient against mutant invasion. Invasion barriers, however, can be overcome by a combination of age-related changes in stem cell differentiation and evolutionary niche construction dynamics based on a mutant-associated inflammatory environment. This helps us understand the evolution of e.g., TET2 or DNMT3A mutants, and how to potentially reduce mutant burden.
Asunto(s)
Diferenciación Celular , Hematopoyesis , Células Madre Hematopoyéticas , Mutación , Animales , Células Madre Hematopoyéticas/citología , Células Madre Hematopoyéticas/metabolismo , Ratones , Hematopoyesis/genética , Hematopoyesis/fisiología , ADN Metiltransferasa 3A/metabolismo , Homeostasis , ADN (Citosina-5-)-Metiltransferasas/metabolismo , ADN (Citosina-5-)-Metiltransferasas/genética , Modelos Biológicos , Linaje de la Célula , Dioxigenasas , Proteínas de Unión al ADN/genética , Proteínas de Unión al ADN/metabolismo , Evolución Clonal , Modelos TeóricosRESUMEN
In this paper, the buckling behaviour of rectangular and skew plates with elastically restrained edges subjected to non-uniform mechanical edge loading is investigated. An analysis method is developed for calculating the critical buckling load of plates using the Ritz method under non-uniform mechanical edge loading, in which the shape function is expressed as Legendre polynomials. The in-plane stress distribution under non-uniform mechanical edge loading is defined by the pre-buckling analysis. Contributions of elastic boundary conditions are taken into accounted by giving different edge spring stiffnesses. The proposed method for buckling analysis of plates is validated by the comparison of exiting results in literature. Finally, the effects of the edge restrained stiffness, non-uniform edge loading, skew angle, aspect ratio and combined compression-shear load are discussed by parametric analysis.
Asunto(s)
Estrés Mecánico , Elasticidad , Modelos TeóricosRESUMEN
The model of bipolar complex fuzzy linguistic set is a very famous and dominant principle to cope with vague and uncertain information. The bipolar complex fuzzy linguistic set contained the positive membership function, negative membership function, and linguistic variable, where the technique of fuzzy sets to bipolar fuzzy sets are the special cases of the bipolar complex fuzzy linguistic set. In this manuscript, we describe the model of Aczel-Alsina operational laws for bipolar complex fuzzy linguistic values based on Aczel-Alsina t-norm and Aczel-Alsina t-conorm. Additionally, we compute the Aczel-Alsina power aggregation operators based on bipolar complex fuzzy linguistic data, called bipolar complex fuzzy linguistic Aczel-Alsina power averaging operator, bipolar complex fuzzy linguistic Aczel-Alsina power weighted averaging operator, bipolar complex fuzzy linguistic Aczel-Alsina power geometric operator, and bipolar complex fuzzy linguistic Aczel-Alsina power weighted geometric operator with some dominant and fundamental laws such as idempotency, monotonicity, and boundedness. Moreover, we initiate the model of the Weighted Aggregates Sum Product Assessment technique with the help of consequent theory. In the context of geographic information systems and spatial information systems, coupling aims to find out the relationships among different components within a geographic information system, where coupling can occur at many stages, for instance, spatial coupling, data coupling, and functional coupling. To evaluate the above dilemma, we perform the model of multi-attribute decision-making for invented operators to compute the best technique for addressing geographic information systems. In the last, we deliberate some numerical examples for comparing the ranking results of proposed and prevailing techniques.
Asunto(s)
Lógica Difusa , Sistemas de Información Geográfica , Lingüística , Modelos Teóricos , Algoritmos , HumanosRESUMEN
To address the conflict between pressure relief and support effectiveness caused by large-diameter boreholes in roadway surrounding rock, this paper proposes a method involving variable-diameter boreholes for pressure relief and energy dissipation. With a typical rock burst coal mine as the engineering context, the study establishes a mechanical model for variable-diameter boreholes through theoretical analysis to examine the elastic stress distribution around boreholes within the coal body. Physical similarity simulation tests are conducted to investigate the influence of conventional borehole and variable diameter borehole on the transmission pattern of dynamic load stress waves. Furthermore, numerical simulations are employed to explore the effects of reaming diameter, depth, and spacing on pressure relief, energy dissipation, and attenuation of dynamic stress wave transmission in roadway surrounding rock. The results demonstrate that stress within the coal surrounding the variable-diameter borehole correlates with the borehole radius, lateral pressure coefficient, and distance from the point to the borehole center, the extent of the plastic zone is influenced by borehole diameter, spacing, and depth. Increased diameter, reduced spacing, and greater depth of deep reaming holes exacerbate the transfer of stress concentration from the surrounding rock of the roadway to the deeper regions, facilitating the formation of stress double peak areas. Moreover, the variable diameter position should be within the original stress peak position of the surrounding rock in the roadway, with deep reaming passing through the stress concentration area for optimal results. This study offers guidance on the prevention and control technology for rock bursts in deep coal mining operations.
Asunto(s)
Presión , Modelos Teóricos , Minas de Carbón , Estrés Mecánico , Simulación por Computador , Carbón MineralRESUMEN
Mathematical modeling of drug release from drug delivery systems is crucial for understanding and optimizing formulations. This research provides a comparative mathematical analysis of drug release from lipid-based nanoparticles. Drug release profiles from various types of lipid nanoparticles, including liposomes, nanostructured lipid carriers (NLCs), solid lipid nanoparticles (SLNs), and nano/micro-emulsions (NEMs/MEMs), were extracted from the literature and used to assess the suitability of eight conventional mathematical release models. For each dataset, several metrics were calculated, including the coefficient of determination (R2), adjusted R2, the number of errors below certain thresholds (5%, 10%, 12%, and 20%), Akaike information criterion (AIC), regression sum square (RSS), regression mean square (RMS), residual sum of square (rSS), and residual mean square (rMS). The Korsmeyer-Peppas model ranked highest among the evaluated models, with the highest adjusted R2 values of 0.95 for NLCs and 0.93 for other liposomal drug delivery systems. The Weibull model ranked second, with adjusted R2 values of 0.92 for liposomal systems, 0.94 for SLNs, and 0.82 for NEMs/MEMs. Thus, these two models appear to be more effective in forecasting and characterizing the release of lipid nanoparticle drugs, potentially making them more suitable for upcoming research endeavors.
Asunto(s)
Sistemas de Liberación de Medicamentos , Liberación de Fármacos , Lípidos , Liposomas , Nanopartículas , Nanopartículas/química , Lípidos/química , Liposomas/química , Sistemas de Liberación de Medicamentos/métodos , Modelos Teóricos , Portadores de Fármacos/química , Emulsiones/química , Química Farmacéutica/métodosRESUMEN
In order to analyze the growth pattern of tree height of planted Pinus koraiensis and screen the provenances with fastest growth, we grouped the provenances using the differences in tree height, diameter at breast height (DBH) and volume of timber of 234 individuals of planted P. koraiensis from 26 provenances in Maoershan Experimental Forest Farm. We constructed the growth equation for tree height by combining the base models of Gompertz, Korf, Richards, Logistic, and Schumacher, and then selected the optimal one. We introduced the prove-nance grouping as a dummy variable into the base model, and evaluated the optimal tree height growth equation by a comprehensive evaluation of the model according to the coefficient of determination (R2), the root-mean-square error (RMSE), the Akaikei Information Criterion (AIC), and the model's predictive precision (FP). The results showed that the growth traits of the 26 provenances had significant difference among the groups, and that tree height and DBH showed significant differences among the provenances. According to the comprehensive consideration of different growth traits, the four groups of provenance growth were divided into group A (Wuying, Hebei, Linjiang, Dongfanghong, Huanan, Lushuihe, Fangzheng) >group B (Aihuisanzhan, Liangshui, Tieli, Qinghe) > group C (Wuyiling, Zhanhe, Liangzihe, Baihe, Chaihe, Caohekou, Bajiazi) >group D (Tongzigou, Dashitou, Wangqing, Helong, Yanshou, Dahailin, Xiaobeihu, Muling). The optimal base tree height growth model of the four groups was the Gompertz model, and the fitting accuracy of the model after the introduction of dummy variables (R2=0.9353) was higher than that of the base model (R2=0.9303), and the model prediction accuracy was also improved. The tree height growth curves of each provenance group conformed to the "S"-shaped rule of change. There were obvious differences among the groups, with the best performance of the provenances in group A. The growth of P. koraiensis from different provenances was different, and the tree height growth model with dummy variables of provenance groups could effectively improve the prediction accuracy of the model, reflect the differences in height growth of P. koraiensis of different provenances, which could provide the scientific basis for the selection and cultivation of P. koraiensis plantations.
Asunto(s)
Pinus , Pinus/crecimiento & desarrollo , China , Ecosistema , Modelos TeóricosRESUMEN
The lower limit temperature in the crop water stress index (CWSI) model refers to the canopy temperature (Tc) or the canopy-air temperature differences (dT) under well-watered conditions, which has significant impacts on the accuracy of the model in quantifying plant water status. At present, the direct estimation of lower limit temperature based on data-driven method has been successfully used in crops, but its applicability has not been tes-ted in forest ecosystems. We collected continuously and synchronously Tc and meteorological data in a Quercus variabilis plantation at the southern foot of Taihang Mountain to evaluate the feasibility of multiple linear regression model and BP neural network model for estimating the lower limit temperature and the accuracy of the CWSI indicating water status of the plantation. The results showed that, in the forest ecosystem without irrigation conditions, the lower limit temperature could be obtained by setting soil moisture as saturation in the multiple linear regression mo-del and the BP neural network model with soil water content, wind speed, net radiation, vapor pressure deficit and air temperature as input parameters. Combining the lower limit temperature and the upper limit temperature determined by the theoretical equation to normalize the measured Tc and dT could realize the non-destructive, rapid, and automatic diagnosis of the water status of Q. variabilis plantation. Among them, the CWSI obtained by combining the lower limit temperature determined by the dT under well-watered condition calculated by the BP neural network model and the upper limit temperature was the most suitable for accurate monitoring water status of the plantation. The coefficient of determination, root mean square error, and index of agreement between the calculated CWSI and measured CWSI were 0.81, 0.08, and 0.90, respectively. This study could provide a reference method for efficient and accurate monitoring of forest ecosystem water status.
Asunto(s)
Quercus , Temperatura , Agua , Quercus/crecimiento & desarrollo , Agua/análisis , China , Redes Neurales de la Computación , Ecosistema , Modelos Teóricos , Estrés Fisiológico , BosquesRESUMEN
Investigating the wind speed flow field and aerodynamic characteristics of shelterbelts with different structural features is of significant importance for the rational arrangement of shelterbelts and the mitigation of wind-blown sand disasters. Considering five cross-sectional shapes of shelterbelts (rectangle, windward right-angle triangle, leeward right-angle triangle, isosceles triangle, and parabolic) and four layout forms (single shelterbelt, L-shaped network, U-shaped network, and rectangular network), we conducted computational fluid dynamics (CFD) simulations using the large eddy simulation (LES) turbulence model to understand mean wind speed flow field and turbulence structure of shelterbelts with different structural features, and investigated the effects of shelterbelt cross-sectional shapes and layout forms on windbreak indicators, such as protection distance and area. We considered tree canopies as porous media and conducted simulation with the 'Tsujimatsu' shelterbelt in Japan with a total height (H) of 7 m, canopy height of 5.8 m, and a canopy base width of 2 m. The results showed that the average relative errors of mean wind speed and turbulent kinetic energy at different heights obtained by numerical simulations and field measurement were small, being 5.5% and 12%, respectively, indicating that the porous medium canopy model successfully reproduced the mean wind speed and turbulent kinetic energy in the leeward area of the shelterbelt. The rectangular cross-section shelterbelt, with the largest canopy volume, significantly obstructed airflow. The mean wind speed and turbulent kinetic energy showed a notable reduction in the leeward area near the shelterbelt, especially in the upper region (z≥0.5H, where z denoted the height), showing the largest protection range. The parabolic cross-section shelterbelt ranked second in terms of protection range, followed by shelterbelts with windward right-angle, leeward right-angle, and isosceles triangular cross-sections. In the downstream area where horizontal distance x≥10H, the mean wind speed and turbulent kinetic energy of shelterbelts with different cross-sectional shapes tended to be the same. Comparing the flow field structures of single shelterbelts and L-shaped, U-shaped, and rectangular networks, it revealed that the more shelterbelts oriented perpendicular to the incoming wind speed, the more pronounced the wind speed attenuation behind the canopy, a longer distance would be required for airflow to recover to the incoming wind speed. In contrast, the wind protection effect of shelterbelts paralleled to the wind direction was extremely limited, making the U-shaped and rectangular networks more effective in wind protection than single shelterbelts and L-shaped networks. The findings would provide references for the structural configuration and optimal layout of shelterbelt systems.
Asunto(s)
Simulación por Computador , Bosques , Viento , Modelos Teóricos , Conservación de los Recursos Naturales , Pinus/crecimiento & desarrollo , Ecosistema , Árboles/crecimiento & desarrollo , ChinaRESUMEN
Understanding the responses of ecosystem service trade-offs and synergies in metropolitan areas to the multidimensional expansion of urban space is of great significance for the optimization of regional land spatial pattern and high-quality development. With the Guangfo Metropolitan Area as research region, we used land use data and natural ecological environment data from 2000 to 2020 to measure the expansion characteristics of urban space in the dimensions of scale, distribution, and morphology by using the landscape pattern indices. We further calculated four main ecosystem services: urban cooling, habitat quality, recreation, and water conservation by the InVEST model, quantified the trade-off and synergistic relationship of multiple ecosystem services by the coupling coordination degree model, and explored its response to multidimensional urban spatial expansion by using the multi-scale geographically weighted regression model. The results showed that urban land use scale in the Guangfo Metropolitan Area continued to increase from 2000 to 2020, with an accelerated growth rate from 2010 to 2020. The ave-rage patch area of urban land in the central area and the urban land of small patches in the northeast increased, evolving from a "dual-center" structure to a "single-center" one. The distance between urban land patches in the Guangfo Metropolitan Area was relatively small, indicating a compact distribution of urban land. The distance between newly developed urban land patches was also small, but had gradually increased in recent years. The patch shape of urban land was relatively regular and less complex, but the complexity of the newly added urban land gra-dually increased. The ecosystem service trade-offs and synergies in the Guangfo Metropolitan Area had undergone significant changes, with a decrease in synergies and an increase in trade-off, and extreme trade-offs had gradually become dominant. The response of ecosystem services synergies to changes in urban land use scale was the most intense and had spatial heterogeneity, while the response to the change of distribution and morphological characte-ristics of urban land showed periodic differences.
Asunto(s)
Ciudades , Conservación de los Recursos Naturales , Ecosistema , China , Planificación de Ciudades , Urbanización , Monitoreo del Ambiente/métodos , Modelos TeóricosRESUMEN
"Planting conifer and reserving broadleaved tree" is an effective way to restore broad-leaved pine forest of temperate zone in Northeast China. Liberation cutting can promote the growth of Korean pine (Pinus koraiensis) under forest crown and accelerate the succession. However, how liberation cutting intensity affects the growth of Korean pine in secondary forest is still unclear. Taking the "Planting conifer and reserving broadleaved tree" Korean pine forest in Changbai Mountain as the object, we constructed a growth model of diameter at breast height (DBH) and tree height of Korean pine with double dummy variables (liberation cutting intensity and tree classification) to predict the growth of Korean pine plantation under different liberation cutting intensities, i.e. control (no liberation cutting), light-intensity liberation cutting (retaining upper canopy closure 0.6), medium-intensity liberation cutting (0.4), heavy-intensity liberation cutting (0.2) and clear cutting (cutting all upper broadleaf trees) stands. We analyzed the effects of liberation cutting intensities on DBH, tree height, and the ratio of tree height to DBH. The results showed that among six theoretical growth equations, the Gompertz model on the DBH (R2=0.46) and tree height (R2=0.81) was optimal basic model. The R2 of the DBH model was increased to 0.65 and 0.89, respectively, after the single dummy variable and the double dummy variable were introduced into the basic model, while the R2 of the tree height model was increased to 0.84 and 0.94. Therefore, the double dummy variable model was the most suitable for predicting the growth of Korean pine. The growth of DBH of pressed tree increased with the increases of liberation cutting intensity (increase by 145.8%-933.3%) during the whole simulation period (0-80 a). Average and dominant trees showed the same pattern at 42 and 60 a. In the early and middle stages of liberation cutting (20 and 42 a), clear cutting and heavy-intensity liberation cutting had similar effects on the height growth of dominant trees (64.8%-68.5%), average trees (100.0%-144.2%), and pressed trees (138.5%-183.9%). The effects of medium-intensity liberation cutting and light-intensity liberation cutting on the height growth were similar (24.3%-35.1%, 56.0%-92.3%, 84.6%-103.2%). While in the middle and late period (42 and 80 a), height growth of three grade trees increased with the increases of liberation cutting intensity. Under each liberation cutting intensity, the ratio of height to DBH of the dominant, average, and pressed trees increased successively, ranging from 0.50-0.95, 0.64-1.23, and 0.73-4.33, respectively. Only the pressed tree decreased with the increases of liberation cutting intensity at 0-80 a. Therefore, about 40 years after the implementation of liberation cutting, the promoting effect of different liberation cutting intensities on DBH growth was significantly weakened, the promoting effect on tree height growth was significantly enhanced, and the ratio of tree height to diameter began to increase. In order to alleviate forest competition, second liberation cutting should be carried out for light-intensity liberation cutting and medium-intensity liberation cutting stands to further release the growth potential of Korean pine, and thinning management should be carried out in clear cutting and heavy-intensity liberation cutting stands.
Asunto(s)
Bosques , Pinus , Pinus/crecimiento & desarrollo , China , Modelos Teóricos , Ecosistema , Conservación de los Recursos Naturales , PredicciónRESUMEN
We established a mixed-effects model incorporating climatic factors for the base diameter and length of the primary branches of Larix kaempferi using stepwise regression, based on climatic data from a total of 40 standard plots located in Xiaolongshan, Gansu Province, Changlinggang Forest Farm in Jianshi County, Hubei Province, and Dagujia Forest Farm in Qingyuan County, Liaoning Province, as well as the data from 120 L. kaempferi sample trees. Additionally, we created prediction charts for the fixed effects portion of the optimal mixed model to determine the relationship between climatic factors and base diameter and branch length, to explore the differential response of L. kaempferi branches to climatic variables. The results showed that the base diameter mixing model with annual mean temperature and water vapor deficit and the branch length mixing model with annual mean temperature had the best fitting effect, with R2 of 0.6152 and 0.6823, respectively. Based on the fixed effects prediction chart of the mixed model, the overall basal diameter showed an increasing trend with the increases of relative branch depth. The average basal diameter size was in an order of young-aged plantationAsunto(s)
Clima
, Larix
, Larix/crecimiento & desarrollo
, China
, Temperatura
, Tallos de la Planta/crecimiento & desarrollo
, Modelos Teóricos
, Ecosistema
RESUMEN
Quantifying the impact of competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.
Asunto(s)
Biomasa , Bosques , Larix , Larix/crecimiento & desarrollo , China , Predicción , Modelos Teóricos , Ecosistema , Modelos BiológicosRESUMEN
The construction of road infrastructure has resulted in the degradation of wildlife habitat and the decrease of ecological network connectivity and stability. Studying the impacts of road infrastructure on wildlife life and migration is significant for regional wildlife conservation and ecological network optimization. We assessed the impacts of road infrastructure on habitat suitability using the MaxEnt model based on wildlife occurrence point data in the Guangdong-Hong Kong-Macao Greater Bay Area. We constructed the ecological networks and identified ecological breakpoints using the minimum cumulative resistance model, and compared the ecological network connectivity of different scenarios with the landscape connectivity index and graph theory index. The results showed that railway and motorway significantly affected habitat suitability, causing a decrease in wildlife habitat suitability. Affected by road infrastructure, the fragmentation of ecological sources intensified, the resistance of ecological corridors increased, and the ecological network connectivity and stability significantly decreased. A total of 536 ecological breakpoints were identified, which were concentrated in the area adjacent to ecological sources. The results would provide important scientific references for wildlife habitat conservation and ecological restoration in the Guangdong-Hong Kong-Macao Greater Bay Area.
Asunto(s)
Conservación de los Recursos Naturales , Ecosistema , China , Animales , Animales Salvajes/crecimiento & desarrollo , Bahías , Ecología , Hong Kong , Modelos Teóricos , Transportes , Vías FérreasRESUMEN
Recurrent epidemics of respiratory infections have drawn attention from the academic community and the general public in recent years. Aircraft plays a pivotal role in facilitating the cross-regional transmission of pathogens. In this study, we initially utilized an Airbus A320 model for computational fluid dynamics (CFD) simulations, subsequently validating the model's efficacy in characterizing cabin airflow patterns through comparison with empirical data. Building upon this validated framework, we investigate the transport dynamics of droplets of varying sizes under three air supply velocities. The Euler-Lagrangian method is employed to meticulously track key parameters associated with droplet transport, enabling a comprehensive analysis of particle behavior within the cabin environment. This study integrates acquired data into a novel PCR (Personal Contamination Rate) equation to assess individual contamination rates. Numerical simulations demonstrate that increasing air supply velocity leads to enhanced stability in the movement of larger particles compared to smaller ones. Results show that the number of potential infections in the cabin decreases by 51.8% at the highest air supply velocity compared to the base air supply velocity, and the total exposure risk rate reduced by 26.4%. Thus, optimizing air supply velocity within a specific range effectively reduces the potential infection area. In contrast to previous research, this study provides a more comprehensive analysis of droplet movement dynamics across various particle sizes. We introduce an improved method for calculating the breathing zone, thereby enhancing droplet counting accuracy. These findings have significant implications for improving non-pharmacological public health interventions and optimizing cabin ventilation system design.
Asunto(s)
Aeronaves , Humanos , Medición de Riesgo/métodos , Microbiología del Aire , Simulación por Computador , Hidrodinámica , Movimientos del Aire , Modelos TeóricosRESUMEN
While live commerce provides consumers with a new shopping experience, it also leads them to experience shopping failures and to develop a self-protection mechanism to prevent wrong purchases. To address this issue, merchants have attempted to explore new marketing methods for live commerce, giving rise to an offense and defense game between streamers and consumers. In this study, we sought to confirm the effectiveness of consumer protection mechanisms and the impact of streamers' information overload marketing strategy in live commerce. Accordingly, we constructed a hypothetical model based on protection motive theory and information overload theory. In addition, we analyzed the data from the simulated live streaming marketing on seven hundred people through partial least squares structural equation modeling. The results indicate that product utilitarian value uncertainty, consumers' experiential efficacy, and response costs, which are the main factors in the formation of consumer protection mechanisms, influence consumers' intention to stop their purchases. Streamers can circumvent consumer self-protection mechanisms through information overload marketing by reducing utilitarian value uncertainty and consumers' experiential efficacy and increasing consumers' response costs. However, consumers would be able to rebuild their self-protection mechanism through consumer resilience, which moderates the effects of information overload. This study's results provide important theoretical perspectives and new ideas for formulating marketing strategies for live commerce.
Asunto(s)
Comportamiento del Consumidor , Mercadotecnía , Motivación , Humanos , Mercadotecnía/métodos , Comercio , Masculino , Femenino , Adulto , Modelos TeóricosRESUMEN
Objective structured clinical examinations (OSCEs) are a widely used performance assessment for medical and dental students. A common limitation of OSCEs is that the evaluation results depend on the characteristics of raters and a scoring rubric. To overcome this limitation, item response theory (IRT) models such as the many-facet Rasch model have been proposed to estimate examinee abilities while taking into account the characteristics of raters and evaluation items in a rubric. However, conventional IRT models have two impractical assumptions: constant rater severity across all evaluation items in a rubric and an equal interval rating scale among evaluation items, which can decrease model fitting and ability measurement accuracy. To resolve this problem, we propose a new IRT model that introduces two parameters: (1) a rater-item interaction parameter representing the rater severity for each evaluation item and (2) an item-specific step-difficulty parameter representing the difference in rating scales among evaluation items. We demonstrate the effectiveness of the proposed model by applying it to actual data collected from a medical interview test conducted at Tokyo Medical and Dental University as part of a post-clinical clerkship OSCE. The experimental results showed that the proposed model was well-fitted to our OSCE data and measured ability accurately. Furthermore, it provided abundant information on rater and item characteristics that conventional models cannot, helping us to better understand rater and item properties.
Asunto(s)
Evaluación Educacional , Humanos , Evaluación Educacional/métodos , Competencia Clínica , Estudiantes de Medicina , Modelos Teóricos , Estudiantes de OdontologíaRESUMEN
Greenhouse gas emissions, as one of the primary contributors to global warming, present an urgent environmental challenge that requires attention. Accurate prediction of carbon dioxide (CO2) emissions from the industrial sector is crucial for the development of low-carbon industries. However, existing time series models often suffer from severe overfitting when data volume is insufficient. In this paper, we propose a carbon emission prediction method based on meta-learning and differential long- and short-term memory (MDL) to address this issue. Specifically, MDL leverages Long Short-Term Memory (LSTM) to capture long-term dependencies in time series data and employs a meta-learning framework to transfer knowledge from multiple source task datasets for initializing the carbon emission prediction model for the target task. Additionally, the combination of differential LSTM and the meta-learning framework reduces the dependency of the differential long- and short-term memory network on data volume. The smoothed difference method, included in this approach, mitigates the randomness of carbon emission sequences, consequently benefiting the fit of the LSTM model to the data. To evaluate the effectiveness of our proposed method, we validate it using carbon emission datasets from 30 provinces in China and the industrial sector in Xinjiang. The results show that the average absolute error (MAE), Coefficient of Determination (R2) and root mean square error (RMSE) of the method have been reduced by 61.8% and 63.8% on average compared with the current mainstream algorithms. The method provides an efficient and accurate solution to the task of industrial carbon emission prediction, and helps environmental policy makers to formulate environmental policies and energy consumption plans.
Asunto(s)
Dióxido de Carbono , Dióxido de Carbono/análisis , Memoria a Corto Plazo/fisiología , China , Carbono , Industrias , Monitoreo del Ambiente/métodos , Modelos Teóricos , Algoritmos , Redes Neurales de la ComputaciónRESUMEN
As the six central provinces account for 23% of total national carbon emissions (CE), research into the decoupling status of their economic growth (EG) and carbon emissions is critical to achieving the Dual Carbon Goals and the Rise of Central China Plan. This research initially examines the decoupling status between CE and EG using the Tapio decoupling model, based on energy consumption (EC) dataset from six central provinces in China between 2000 and 2019. The decoupling index (DI) is then divided into five decoupling drivers using the LMDI method. Finally, an enhanced STIRPAT model is used to examine the decoupling status of CE and EG in the six central provinces from 2020 to 2040. The research findings are: (1) The six central provinces exhibited a stable decoupling status between 2000 and 2019. The DI of the six central provinces ranged from -1.2 to 3.4. (2) The decoupling performance is influenced mainly by the inhibitory effect of economic development (GI) and the promoting effect of energy intensity (EI). The GI consistently maintains an impact value of around 0.9. EI performance varies widely across provinces. (3) From 2020 to 2040, Anhui, Hubei, Henan, and Hunan show significantly strong decoupling indices distributed between -2.21 and -0.07 in all three scenarios. It is important to note that Shanxi and Jiangxi provinces will experience a Reverse Decoupling phenomenon. These findings are helpful in developing regionally coordinated development policies and strategies for reducing CE.
Asunto(s)
Carbono , Desarrollo Económico , China , Carbono/análisis , Carbono/metabolismo , Dióxido de Carbono/análisis , Modelos TeóricosRESUMEN
Based on panel data collected from 2003 to 2020 across 30 provinces in China, the paper employs the spatial vector angle method and spatial Durbin model to investigate industrial agglomeration's nonlinear and spatial spillover effects on the energy consumption structure's low-carbon transition process (Lct). The results indicate the following: First, the influence of industrial agglomeration on Lct exhibits an inverted U-shaped pattern. As the degree of industrial agglomeration expands, its effect on Lct shifts from positive to negative. Second, industrial agglomeration demonstrates spatial spillover effects. It promotes the improvement of Lct in neighboring provinces through agglomeration effects. However, the continuous expansion of industrial agglomeration inhibits the improvement of Lct in neighboring provinces through congestion effects. Third, the heterogeneity test finds that industrial agglomeration has a significant role in promoting Lct in the samples of eastern region, but this effect is not significant in the samples of western and middle regions.