Function Model Research Articles

Radial Basis Function Model for Obesity Classification Based on Lifestyle and Physical Condition

Obesity is a chronic condition affecting millions worldwide, influenced by genetic predispositions, environmental factors, lifestyle habits, and excessive caloric intake surpassing energy expenditure. widespread prevalence, existing studies lack a comprehensive exploration of classification models that effectively address the complex interplay between lifestyle and physical attributes. This study tackles the absence of an optimal machine learning model for accurately classifying obesity based on these multifaceted factors. To address this gap, the study evaluates the performance of three machine learning algorithms: Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel, Naïve Bayes, and K-Nearest Neighbor (KNN). The primary objectives are to identify the most accurate classification approach, analyze the strengths of these algorithms, and highlight the importance of lifestyle and physical attributes in obesity prediction. Experimental findings show that SVM with RBF kernel achieves the highest accuracy at 89%, surpassing the performance of the other models. This study advances the field of obesity classification by offering a detailed comparative analysis of machine learning algorithms and underscoring the critical role of integrating lifestyle and physical factors into predictive modeling.

Acquiring the structure of a writing system is important in learning to read: a test of the character-word dual-focus approach in learning Chinese as a second language

Abstract An important question in literacy education is whether reading instruction should focus on whole words or subword constituents. We tested whether this question captures something general across writing systems by examining the functionalities of words and characters in learning Chinese. We introduce a character-word dual-focus instructional approach based on the Character-Word Dual Function model and test its predictions with American undergraduate students enrolled in a beginner-level Chinese course. One group learned new words through dual-focus instruction: characters for pronunciation and words for meaning. A second group followed typical word-focus instruction prevalent in classrooms, learning word-level pronunciation and meaning. Results indicated that while both approaches produced comparable levels of word pronunciation and meaning learning, the dual-focus instruction significantly enhanced character pronunciation and transfer to new word learning. The advantages of dual-focus instruction highlight the importance of learning the subword components through acquiring the systematic structure of the writing system in learning to read.

Fatigue Life of Pre-Cut Seam Asphalt Mixture Composite Beams: A Combined Study of Fatigue Damage Evolution and Reflective Cracking Extension

This study investigated the impact of reflective cracking on the fatigue performance of asphalt pavements after milling and resurfacing under various conditions. Fatigue life was assessed through four-point flexural fatigue tests, while the crack extension pattern of composite beams was analyzed by digital image correlation (DIC) at both macroscopic and microscopic scales. Evaluation parameters such as stress ratios, immersion time, porosity, and types of viscous oils were assessed. A fatigue life prediction model of composite beams was established, accounting for the combined influence of these factors. To enhance the accuracy of determining composite beam failure, the critical fatigue damage was calculated by defining the damage variable in terms of the dynamic modulus. A nonlinear fatigue damage model was proposed, incorporating this critical damage under the combined influence of various factors. Additionally, a modified logistic function model was developed to describe the relationship between crack extension and failure life under different stress ratios, porosities, and viscous layer oil conditions. It was found that the modulus decay curves and the crack extension curves intersected at different stress levels as the life ratio increased. At the intersection, the modulus ratios were consistently around 0.55, marking the transition of the specimen from a stable to an unstable state. Beyond this point, the crack rapidly propagated, leading to a sharp reduction in the modulus until the specimen ultimately failed. Our results provide a basis for timing and conservation decisions.

Theoretical insights into charge transfer plasmon lifetime

In this Letter, we present a theoretical study based on the Lorentz function and harmonic oscillator model to explore temporal dynamics of charge transfer plasmon (CTP) resonances. By fitting scattering curves and near-field oscillations, we determine the dephasing time of CTP modes in conductively connected gold nanodisk dimers. We show that, compared with the well-known particle plasmon and dimer plasmon modes, the CTP mode has a narrow spectral width and longer lifetime. Moreover, quantitative analysis of optical near-fields reveals that CTP modes oscillate completely out-of-phase with the particle plasmon and dimer plasmon modes. The dephasing time, near-field decay rate and charge transfer time of the CTP mode are found to be on a few femtosecond timescales, implying that conductively connected plasmonic nanoparticles hold great promise as channels for ultrafast transfer of information in all-optical computing and optoelectronic devices.

Long non-coding RNA Malat1 fine-tunes bone homeostasis and repair by orchestrating cellular crosstalk and β-catenin-OPG/Jagged1 pathway.

The IncRNA Malat1 was initially believed to be dispensable for physiology due to the lack of observable phenotypes in Malat1 knockout (KO) mice. However, our study challenges this conclusion. We found that both Malat1 KO and conditional KO mice in the osteoblast lineage exhibit significant osteoporosis. Mechanistically, Malat1 acts as an intrinsic regulator in osteoblasts to promote osteogenesis. Interestingly, Malat1 does not directly affect osteoclastogenesis but inhibits osteoclastogenesis in a non-autonomous manner in vivo via integrating crosstalk between multiple cell types, including osteoblasts, osteoclasts, and chondrocytes. Our findings substantiate the existence of a novel remodeling network in which Malat1 serves as a central regulator by binding to β-catenin and functioning through the β-catenin-OPG/Jagged1 pathway in osteoblasts and chondrocytes. In pathological conditions, Malat1 significantly promotes bone regeneration in fracture healing. Bone homeostasis and regeneration are crucial to well-being. Our discoveries establish a previous unrecognized paradigm model of Malat1 function in the skeletal system, providing novel mechanistic insights into how a lncRNA integrates cellular crosstalk and molecular networks to fine tune tissue homeostasis, remodeling and repair.

A Comparative Analysis of the Diffusion of Mobile Technologies in the Visegrad Four Using an ECM Model

Objective: The aim of the paper is to assess the size and rate of diffusion of mobile technologies in the processing industry, and to determine the nature and strength of the impact of investment specialisation (investment attractiveness) and industry export specialisation on this phenomenon in the four Visegrad Group countries. Research Design & Methods: The occurrence of innovation diffusion and its dynamics were examined using an econometric model of the Gompertz function. To study the impact of specialisation according to foreign direct investments (FDI) located in V4 countries and their export specialisation on the process of innovation diffusion, an error correction model (ECM) estimated for selected industrial processing sectors was used. It was based on data for 2010–2021 from Eurostat, UNCTAD and the national statistical offices of individual V4 countries. Findings: The phase of rapid increase in innovation diffusion calculated on the basis of the Gompertz function was significantly longer in high- and medium-high technology enterprises than in low- and medium-low technology enterprises. In the short term, the determinants of mobile technology diffusion in all V4 countries in industries with low and medium-low technology are both export specialisation and investment attractiveness. Implications / Recommendations: The results lead to the conclusion that the diffusion of mobile technologies takes place in various industries in the V4, but its pace varies depending on the individual industry’s technological development. The results indicate the need to develop industries with high technologies and sectors with high intensity of knowledge. Contribution: A comparative analysis of the pace of diffusion of mobile technology innovations in the V4 was performed for the first time in this article. The combination of the Gompertz model with the ECM model can also be considered a pioneering solution in the analysis of innovation diffusion.

Spectroscopic confirmation of the galaxy clusters CARLA J0950+2743 at z = 2.363 and CARLA-Ser J0950+2743 at z = 2.243

Galaxy clusters are the largest gravitationally bound structures in the Universe and therefore are a powerful tool for studying mass assembly at different epochs. At z > 2, they provide the unique opportunity to place solid constraints not only on the growth of the dark matter halo, but also on the mechanisms of galaxy quenching and morphological transformation when the Universe was younger than 3.3 Gyr. However, the currently available sample of confirmed z > 2 clusters remains very limited. We present the spectroscopic confirmation of the galaxy cluster CARLA J0950+2743 at z = 2.363 ± 0.005 and a new serendipitously discovered cluster, CARLA-Ser J0950+2743 at z = 2.243 ± 0.008, in the same region. We confirm eight star-forming galaxies in the first and five in the second cluster by detecting [OII], [OIII], and Hα emission lines. The analysis of an archival X-ray Chandra dataset that covers the cluster position revealed a counterpart with a total luminosity of L0.5−5keV = 2.9 ± 0.6 × 1045 erg s−1. Because the depth of the X-ray observations is limited, we cannot distinguish the 1D profile of the source from a point spread function model, but our statistical analysis of the 2D profile favors an extended component that might be associated with a thermal contribution from the intracluster medium. If the extended X-ray emission is due to the hot intracluster medium, the total combined dark matter mass for the two clusters would be M200 ≈ 3.0−0.23(stat)+0.20 −0.85(sys)+1.13 × 1014 M⊙, assuming a ∼30% contribution from the active galactic nucleus. Our two clusters are therefore interesting targets for studies of the structure growth in the cosmological context. However, future investigation will require deeper high-resolution X-ray and spectroscopic observations to rule out the hypotheses that the emission is entirely due to the active galactic nucleus or that it originates from other contaminating radio galaxies and structures.

Evidential Belief Function (EBF) Model for Landslide Susceptibility Analysis in Idukki District, Kerala, India

A Geo-statistical Dempster-Shafer Theory Evidential Belief Function (DST-EBF) model is selected for Landslide susceptibility evaluation. The aim of the study is to delineate zones prone to landslides within the Idukki district, Kerala using the EBF model and Geographical Information System (GIS) Technique. The objective is to integrate diverse datasets to assess and predict the landslide-prone areas, providing valuable insights for risk management and mitigation startgies. Topographical, Anthropogenic, and Geological factors are considered Landslide Conditioning Factors (LCFs), and Landslide Inventory data are used to establish and validate the Suscebtlity zones. Landslide inventory data is randomly divided into Training(70%) and Testing (30%) data. The resultant Landslide Susceptibility map is categorized into five zones using natural breaking classification method: Very low (20.96%), Low (29.71%), Medium (24.50%), High (18.63%), and Very high (6.20%), respectively, within the study area. The success rate and prediction rate were calculated using the AUC_ROC method and the EBF Model achieved the highest precision with a success rate of 0.935, and a prediction rate of 0.943 in the current study.

Risk scores for allograft failure: Are they still useful in liver recipients from donation after circulatory death?

Liver grafts from donation after circulatory death (DCD) are associated with a higher risk of early graft dysfunction, determined by the warm ischemia and cold ischemia times. It is essential to have precise criteria to identify this complication in order to guide therapeutic strategies. To validate different graft and recipient survival scores in patients undergoing liver transplantation (LT) with DCD grafts. A retrospective and observational unicentric study was conducted on 65 LT patients with grafts obtained from controlled DCD donors from November 2013 to November 2022. The United Kingdom (UK) risk score, early allograft dysfunction (EAD) Olthoff score, and model for early allograft function (MEAF) score were used to evaluate the risk of graft and recipient survival post-transplant. For survival analysis purposes, we used the Kaplan-Meier method, and the differences between subgroups were compared using the log-rank (Mantel-Cox) test. Sixty-five patients were included in the study. The UK risk score did not demonstrate predictive capacity for recipient or graft survival. However, in donors aged over 70 years old (18.4%), it significantly predicted graft survival (P < 0.05). According to Kaplan-Meier survival curves, graft survival rates at 6 months, 2 years, and 5 years in the futility group dramatically decreased to 50% compared to the other groups (log-rank 8.806, P < 0.05). The EAD Olthoff and MEAF scores did not demonstrate predictive capacity for recipient or graft survival. Based on Kaplan-Meier survival curves, patients with a MEAF score ≥ 7 had a lower graft survival rate at 6 months, 2 years, and 5 years compared to patients with a lower MEAF score (log-rank 4.667, P < 0.05). In our series, both UK DCD risk score and MEAF score showed predictive capability for graft survival.

Adaptive compensation for multi-axial real-time hybrid simulation via nonlinear parameter estimation

For Real-time hybrid simulation (RTHS) to be stable and accurate, it is essential to address the time desynchronization issue between the numerical and physical substructures. Desynchronization is primarily caused by time delays, inherent dynamics of the control plant, system uncertainties, and noises. While existing adaptive compensators have shown effective tracking performance in single-input single-output (SISO) RTHS, their effectiveness in multi-input multi-output (MIMO) RTHS has not been fully demonstrated. MIMO-RTHS presents additional challenges due to its larger solution space, and significant dynamic coupling between actuators. To address these challenges, this study introduces an adaptive compensation framework for MIMO-RTHS. The proposed framework utilizes a control law based on the inverse dynamics of the control plant, incorporating real-time adaptive parameter updates through Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) methods. Both the transfer function (TF) and discrete-time state-space (SS) models of the plant are employed in distinct parameter estimation cases. The performance of the proposed compensation is validated through a multi-axial RTHS (maRTHS) benchmark problem. Extensive simulations on the maRTHS incorporating various earthquake inputs, sensor noise, and model uncertainties, demonstrated an excellent tracking performance and strong robustness across four parameter estimation cases (EKF-TF, UKF-TF, EKF-SS, and UKF-SS). The use of UKF with SS model (UKF-SS) achieved superior performance, effectively managing nonlinearities and noise without requiring low-pass filtering.

Locus coeruleus signal intensity and emotion regulation in agitation in Alzheimer's disease.

Hyperphosphorylated tau accumulation is seen in the noradrenergic locus coeruleus from the earliest stages of Alzheimer's disease onwards and has been associated with symptoms of agitation. It is hypothesized that compensatory locus coeruleus-noradrenaline system overactivity and impaired emotion regulation could underlie agitation propensity, but to our knowledge this has not previously been investigated. A better understanding of the neurobiological underpinnings of agitation would help the development of targeted prevention and treatment strategies. Using a sample of individuals with amnestic mild cognitive impairment and probable mild Alzheimer's disease dementia from the German Center for Neurodegenerative Diseases (DZNE)-Longitudinal Cognitive Impairment and Dementia (DELCODE) study cohort (N = 309, aged 67-96 years, 51% female), we assessed cross-sectional relationships between a latent factor representing the functional integrity of an affect-related executive regulation network and agitation point prevalence and severity scores. In a subsample of individuals with locus coeruleus MRI imaging data (N = 37, aged 68-93 years, 49% female), we also investigated preliminary associations between locus coeruleus MRI contrast ratios (a measure of structural integrity, whole or divided into rostral, middle, and caudal thirds) and individual affect-related regulation network factor scores and agitation measures. Regression models controlled for effects of age and clinical disease severity and, for models including resting-state functional MRI connectivity variables, grey matter volume and education years. Agitation point prevalence showed a positive relationship with a latent factor representing the functional integrity (and a negative relationship with a corresponding structural measure) of the affect-related executive regulation network. Locus coeruleus MRI contrast ratios were positively associated with agitation severity (but only for the rostral third, in N = 13) and negatively associated with the functional affect-related executive regulation latent factor scores. Resting-state functional connectivity between a medial prefrontal cortex region and the left amygdala was related to locus coeruleus MRI contrast ratios. These findings implicate the involvement of locus coeruleus integrity and emotion dysregulation in agitation in Alzheimer's disease and support the presence of potential compensatory processes. At the neural level, there may be a dissociation between mechanisms underlying agitation risk per se and symptom severity. Further studies are needed to replicate and extend these findings, incorporating longitudinal designs, measures of autonomic function and non-linear modelling approaches to explore potential causal and context-dependent relationships across Alzheimer's disease stages.

A Hybrid Harmonic Curve Model for Multi-Streamer Hydrophone Positioning in Seismic Exploration.

Towed streamer positioning is a vital and essential stage in marine seismic exploration, and accurate hydrophone coordinates exert a direct and significant influence on the quality and reliability of seismic imaging. Current methods predominantly rely on analytical polynomial models for towed streamer positioning; however, these models often produce significant errors when fitting to streamers with high curvature, particularly during turning scenarios. To address this limitation, this study introduces a novel multi-streamer analytical positioning method that uses a hybrid harmonic function to model the three-dimensional coordinates of streamers. This approach mitigates the substantial modeling errors associated with polynomial models in high-curvature conditions and better captures the dynamic characteristics of streamer fluctuations. Firstly, the mathematical model for the hybrid harmonic function is constructed. Then, the algorithmic implementation of the model is detailed, along with the derivation of the error equation and the multi-sensor fusion solution process. Finally, the validity of the model is verified using both simulated and field data. The results demonstrate that, in the turning scenario without added error, the proposed harmonic model improves simulation accuracy by 35.5% compared to the analytical polynomial model, and by 27.2% when error is introduced. For field data, accuracy improves by 18.1%, underscoring the model's effectiveness in significantly reducing errors associated with polynomial models in turning scenarios. The performance of the harmonic function model is generally comparable to that of the polynomial model in straight scenarios.

MASTER RECESSION CURVE VISUALIZATION USING SEVEN BASEFLOW RECESSION MODELS IN PAIRED WATERSHEDS

River flow recession analysis plays a crucial role in understanding how watersheds release water during dry periods. Consequently, modeling baseflow recession is closely related to the characteristics of unconfined aquifers, storage behavior, and the discharge properties of the watershed. While several theories exist on modeling recession curves, limited research has compared different approaches regarding baseflow recession characteristics. This study aims to model seven baseflow recession equations in paired watersheds in Ambon City. The research methodology involves calibrating seven baseflow recession models using the Recession Curve (RC) 4.0 Hydro Office software. The tested models include Linear Reservoir, Exponential Reservoir, Double Exponential Horton, Dupuit-Boussinesq Aquifer Storage, Depression Storage, Turbulent Flow Model, and Hyperbolic Function Model. The calibration results yield optimal combinations of recession parameters. The parameterization order from highest to lowest is as follows: Depression Storage, followed by the Hyperbolic Function, Exponential Reservoir, Turbulent Flow Model, Double Exponential Horton, Linear Reservoir, and Dupuit-Boussinesq Aquifer Storage. Quantifying baseflow recession constants and coefficients is essential for understanding baseflow behavior. Visualizing the slope of the Recession Curve (MRC) reveals that models with high recession constants tend to have gradual MRCs, while low recession constants result in steep MRCs. The MRC slope further describes the relationship between storage conditions and discharge from the watershed. The advantage of creating MRCs from discontinuous recession segments lies in their ability to appropriately describe the MRC process and provide quantitative parameters relevant to drainage mechanisms. MRCs also serve as an optimal automated computational tool.

An Improved Spider Wasp Optimizer for UAV Three-Dimensional Path Planning.

This paper proposes an Improved Spider Wasp Optimizer (ISWO) to address inaccuracies in calculating the population (N) during iterations of the SWO algorithm. By innovating the population iteration formula and integrating the advantages of Differential Evolution and the Crayfish Optimization Algorithm, along with introducing an opposition-based learning strategy, ISWO accelerates convergence. The adaptive parameters trade-off probability (TR) and crossover probability (Cr) are dynamically updated to balance the exploration and exploitation phases. In each generation, ISWO optimizes individual positions using Lévy flights, DE's mutation, and crossover operations, and COA's adaptive update mechanisms. The OBL strategy is applied every 10 generations to enhance population diversity. As the iterations progress, the population size gradually decreases, ultimately yielding the optimal solution and recording the convergence process. The algorithm's performance is tested using the 2017 test set, modeling a mountainous environment with a Gaussian function model. Under constraint conditions, the objective function is updated to establish a mathematical model for UAV flight. The minimal cost for obstacle-avoiding flight within the specified airspace is obtained using the fitness function, and the flight path is smoothed through cubic spline interpolation. Overall, ISWO generates high-quality, smooth paths with fewer iterations, overcoming premature convergence and the insufficient local search capabilities of traditional genetic algorithms, adapting to complex terrains, and providing an efficient and reliable solution.

Platelet storage in small bags as a model of platelet function in full-sized containers.

Evaluation of additive solutions, storage containers, new collection and storage methods, and other potential modifications is resource intensive, resulting in diversion of platelets away from blood bank inventories and significant time to complete study recruitments. Our goal was to evaluate the feasibility of a small bag for the study of platelet storage, and, by using a standardized respirometry test, separate daily metabolic capacity from observations made in the dynamic storage environment of changing pH, fuels, and end products. Single-donor apheresis platelets collected in 100% plasma had small volumes removed to meet secondary processing requirements. Small volumes (23 ± 1.4 mL) were placed in 50-mL bags constructed of platelet storage material, stored 7 days, and assessed with a panel of in vitro assays. Platelet bioenergetics (oxygen consumption and acid production rates) were measured with a respirometer. The patterns of platelet pH decline, activation, and potency by thrombin generation were consistent with historical reports. Lactate production rates (54.1 ± 11.3 μmol/1012plt/h) were significantly correlated with pH decrease, increased activation, and thrombin generation potency by Day 7. Respirometry revealed a reduction of the glycolytic capacity and accumulating damage to the oxidative system for ATP production over storage. Small bags present a storage profile of metabolic changes and activation consistent with historical data for full bag storage. Therefore, this system has promise to provide a platform for scaling experiments of platelet storage in a manner that maximizes platelets collected in research settings and does not compromise availability for patient treatment as exercised in this study.

Clinical modeling of motor function to predict treatment efficacy and enable in silico treatment comparisons in infantile-onset Pompe disease.

Infantile-onset Pompe disease (IOPD) is a rare, deadly, quickly-progressing degenerative disease. Even with life-sustaining treatment (e.g., alglucosidase alfa [ALGLU]), many patients experience continued motor impairment. The Mini-COMET trial evaluated avalglucosidase alfa (AVAL) versus ALGLU on motor and other outcomes in IOPD. However, treatment groups were imbalanced at baseline and the trial was not powered to directly compare treatments. To supplement this limited data, we developed a modeling and simulation approach to compare AVAL versus ALGLU head-to-head in in silico (i.e., computer-simulated) trials. We first developed a longitudinal clinical model to establish the relationship between changes in motor function and changes in urinary hexose tetrasaccharide (uHex4), an established biomarker in IOPD. This model was based on pooled data from Mini-COMET (n = 21) and COMET trials (n = 100 patients with late-onset Pompe disease, LOPD). We then conducted in silico trials mimicking Mini-COMET. Simulated trials were informed by motor data generated from the clinical model and uHex4 profiles simulated in a quantitative systems pharmacology model. The virtual IOPD population was based on observed Mini-COMET baseline characteristics but engineered to have well-balanced baseline characteristics across treatment cohorts. In silico trials showed that patients with IOPD would have the greatest improvements in motor function with AVAL 40 mg/kg every other week (Q2W), suboptimal improvement with ALGLU 40 mg/kg Q2W, and no improvement with ALGLU 20 mg/kg Q2W. This study provides information on the relative efficacy of IOPD treatments and mitigates the confounding effects of imbalanced treatment cohorts. Our approach could also be applied in other rare diseases.

Modelling of the Interrelationships Between Population Sex Ratio and Food Content and Ecological Niches in the Marine Lampreys

In this paper, a model related to sex ratio and food content was developed and solved. Through logistic function fitting, it was found that the sex ratio of the Marine lampreys was affected by environmental conditions, with approximately 56% males when food was plentiful and up to 78% when conditions changed. A correlation function model between sex ratio and food content was developed and the normality and absence of autocorrelation of the model was verified by residual analysis (Shapiro-Wilk and Durbin-Watson tests).In order to further explore the interrelationships between sea sevengill eels and their ecological niches, this paper extends the classical Lotka-Volterra model to include competitor and predator equations, and analyses the changes of the various populations under the initial conditions by numerical simulations. Through Spearman correlation analysis, it was found that sex ratio significantly affects the number of predators, competitors and prey in the ecosystem, where an increase in the proportion of males suppresses the growth of the number of prey and competitors, and promotes the increase of the number of predators.

Simulation of nitrate nitrogen concentrations and DOM characteristics in groundwater from Southwest China's Karst Wetlands using an improved GMS model.

Existing models often face limitations in the understanding and prediction of nitrate nitrogen (NO3--N) concentrations in karst groundwater. In this study, to tackle this issue, a Gaussian function model was coupled with the Groundwater Modeling System (GMS) to simulate NO3--N concentration changes in the southwest karst wetland of China. Additionally, fluorescence spectroscopy was employed to measure dissolved organic matter (DOM) components in the groundwater, providing insights into their variation and influence on NO3--N dynamics. The results demonstrated that coupling the Gaussian curve fitting method with the GMS model accurately simulated NO3--N concentration changes in the study area. The simulation revealed lower NO3--N levels in the northern region, with higher concentrations in the central area, peaking at 20.73mg/L at lower elevations. NO3--N was primarily distributed in the southwestern region and upper Mudong Lake, exhibiting a diffusion trend from west to east. DOM analysis indicated significant autochthonous contributions, particularly microbial metabolic by-products. The total fluorescence intensity and DOM components increased downstream, with the lowest values at the source and the highest values at river confluences. The humification index (HIX) was correlated with NO3--N concentrations, where lower NO3--N levels corresponded to lower HIX values, and higher NO3--N levels corresponded to higher HIX values. In conclusion, this study provides valuable insights into NO3--N prediction in groundwater and the role of DOM, offering a reference for groundwater protection in the southwest China karst basin.

Path-based DEA models in multiplier form and returns-to-scale analysis

AbstractData envelopment analysis (DEA) models appear in envelopment and multiplier forms, which are in a primal-dual relationship. In this paper, we derive the general multiplier form of path-based models, encompassing radial, directional distance function, and hyperbolic distance function models as special cases. We investigate the economic interpretation of the multiplier models and uncover the link between shadow profit inefficiency and technical inefficiency provided by path-based models. Using the optimality conditions for the primal-dual pair, we precisely describe the two-way relationship between the optimal solutions of the multiplier model and the supporting hyperplanes of the technology set at the projection. This relationship serves as a mathematical justification for extending one of the early approaches to measuring returns-to-scale (RTS) onto the entire class of path-based models. Moreover, we demonstrate the eligibility of this method by revealing the fact that the set of all strongly efficient benchmarks for the assessed unit in path-based models does not need to belong to a single strongly efficient face of technology set. This finding changes the view on traditional approaches to RTS measurement that rely on supporting hyperplanes encompassing a single strongly efficient face of the technology set. In this new perspective, we propose two methods for RTS measurement. The first is based on the hyperplanes at the projection, and the second method adapts the minimum face method to be suitable for path-based models. Both methods are fully justified and brought to an algorithmic form.

Orthographic and Meaning Processes in Reading Chinese Compounds: Comparisons Between L1 and L2 Reading.

Research on alphabetic reading presents conflicting findings concerning the timing of orthographic and meaning processes in reading morphologically complex words. Chinese characters offer distinct visual cues for morphemes, enabling straightforward manipulations to examine orthographic and meaning processes. Guided by the Character-Word Dual Function model, we report four priming experiments that test how a reader's lexical quality impacts the emergence of orthographic and semantic priming effects in reading Chinese compounds. We conducted comparisons between native Chinese speakers and Chinese L2 learners, who vary in their quality of lexical representations. By manipulating the semantic transparency of prime-target pairs, we distinguished meaning from orthographic effects. The emergence of these effects was revealed by varying prime exposure durations. Orthographic effects emerged at shorter exposures for both L1 and L2 readers. However, meaning effects appeared at longer exposure durations only for L1 readers. These results confirm the generality of the orthography-first emergence of morphological effect in reading Chinese and suggest that readers' access to morphological meaning relations increases with experience.