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PubMed2006

ALAMEDA, a structural-functional model for faba bean crops: morphological parameterization and verification.

BACKGROUND: Plant structural (i.e. architectural) models explicitly describe plant morphology by providing detailed descriptions of the display of leaf and stem surfaces within heterogeneous canopies and thus provide the opportunity for modelling the functioning of plant organs in their microenvironments. The outcome is a class of structural-functional crop models that combines advantages of current structural and process approaches to crop modelling. ALAMEDA is such a model. METHODS: The formalism of Lindenmayer systems (L-systems) was chosen for the development of a structural model of the faba bean canopy, providing both numerical and dynamic graphical outputs. It was parameterized according to the results obtained through detailed morphological and phenological descriptions that capture the detailed geometry and topology of the crop. The analysis distinguishes between relationships of general application for all sowing dates and stem ranks and others valid only for all stems of a single crop cycle. RESULTS AND CONCLUSIONS: The results reveal that in faba bean, structural parameterization valid for the entire plant may be drawn from a single stem. ALAMEDA was formed by linking the structural model to the growth model 'Simulation d'Allongement des Feuilles' (SAF) with the ability to simulate approx. 3500 crop organs and components of a group of nine plants. Model performance was verified for organ length, plant height and leaf area. The L-system formalism was able to capture the complex architecture of canopy leaf area of this indeterminate crop and, with the growth relationships, generate a 3D dynamic crop simulation. Future development and improvement of the model are discussed.

Computer Simulation↗

PubMed2025

A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.

BACKGROUND: A wide range of epidemiological modeling approaches have been applied to the SARS-CoV-2 pandemic, which presents an opportunity to assess common approaches applied to specific research questions. Spatial models interrogate how heterogeneities and host movement dynamics influence local and regional patterns of disease, issues that were of great interest for understanding and controlling SARS-CoV-2. OBJECTIVE: Here we present a systematic review of spatial epidemiological modeling approaches of SARS-CoV-2. We describe common themes and highlight unique strategies, providing a foundation for researchers to devise spatial models most appropriate for future pathogens and epidemics. Our review also categorizes the research questions that were addressed with spatial models, highlights parameter estimation techniques, and describes the cyber infrastructure used for model development. METHODS: We conducted a systematic review using Web of Science and a standardized set of keywords, followed by thorough examination of abstracts and full texts to determine which studies met our inclusion criteria. To guide our description and comparisons of models, we developed a Geography, Population, Movement (GPM) framework that conceptualizes the interactions between three distinct subcomponents of any spatial model. The geographic model represents the physical arena in which the model is implemented, the intra-population model describes the transmission and disease processes that occur within distinct spatial units of the geography, and the movement model describes the algorithms that dictate how hosts move among spatial units within the geography. RESULTS: The search identified a total of 193 articles, of which 109 were included in our review. The most abundant intra-population modeling methods were agent-based (47.7%) and compartmental modeling (29.4%) approaches. Movement models ranged in complexity, with the most complex models implementing commuter movement among many points of interest in the geographic arena, which were sometimes parameterized by fine-scale mobility data. Geographic models ranged from describing microcosms, such as single classrooms, all the way up to multi-country models. Of the 63.3% of models studies that specified the programming language used, we detected ten different languages, with Matlab and Python being the most frequent, although only 30.6% of studies provided open-access code for their models. We also described eight specialized software systems that were used to construct agent-based or compartment models of COVID-19. CONCLUSIONS: Our review identified and characterized a variety of spatial modeling strategies and software that were usefully employed to address many relevant epidemiological questions for COVID-19. Future research is needed to quantitatively assess which modeling approaches are most appropriate in specific situations, to answer specific questions, or to apply to certain disease systems. Moreover, future cyberinfrastructure could help to modularize and standardize modeling approaches, which would increase transparency and reproducibility, and which would facilitate a detailed examination of which model attributes relate to model performance in a variety of contexts.

COVID-19↗

PubMed1997

Evaluation of the MOS SF-36 Physical Functioning Scale (PF-10): II. Comparison of relative precision using Likert and Rasch scoring methods.

This study examined the relative precision (RP) of two methods of scoring the 10-item Physical Functioning Scale (PF-10) from a large sample of patients (n = 3445) of the Medical Outcomes Study. Based on a Likert scaling model, the PF-10 summated scoring method was compared with a Rasch Item Response Theory (IRT) scaling model in which raw scores were transformed into a latent trait variable of physical functioning. Potential differences between scoring methods were hypothesized to be attributed to: (1) the logarithmic nature of the Rasch transformation; (2) the unevenness of the PF-10 item distributions; and (3) reduction of within-group variance. RP ratios favored the Rasch model in discriminating between patients who differed in disease severity. The Rasch and Likert scoring models performed similarly for tests involving sensitivity to change over a two-year follow-up period. In all comparisons, differences between methods were most apparent in clinical groups whose scores most approximated the extremes of the score distribution. Further research is necessary to test for differences between scoring models in discrimination and sensitivity to change among clinical groups whose scores are sufficiently spread across the continuum of physical functioning, in particular patients with either very high or low physical functioning. The Rasch model of scoring may have important implications for the clinical interpretation of individual scores at all ranges of the scale.

Data Interpretation, Statistical↗

PubMed2006

Characterization and prediction of highway runoff constituent event mean concentration.

Highway stormwater runoff quality data were collected from throughout California during 2000-2003. Samples were analyzed for conventional pollutants (pH, conductivity, hardness, and temperature); aggregates (TSS, TDS, TOC, DOC); total and dissolved metals (As, Cd, Cr, Cu, Ni, Pb, and Zn); and nutrients (NO(3)-N, TKN, total P, and ortho-P). Storm event and site characteristics for each sampling site were recorded. A statistical summary for chemical characteristics of highway runoff is provided based on statewide urban and non-urban highways. Constituent event mean concentrations (EMCs) were generally higher in urban highways than in non-urban highways. The chemical characteristics of highway runoff in California were compared with national highway runoff chemical characterization data. The results obtained in California were generally similar to those found in other states. The median EMC for Pb measured in studies conducted in previous decades was much higher than the current median Pb EMC in California. The lower Pb EMC in California compared to previous highway runoff monitoring is believed to be due to the elimination of leaded gasoline. An attempt was also made to identify surrogate constituents within a general family of water quality categories using Spearman correlations and selected pairs with Spearman coefficients greater than 0.8. The strongest correlations were observed among parameters associated with dissolved minerals (EC, TDS, and chloride); organic carbon (TOC and DOC); petroleum hydrocarbons (TPH and O & G); and particulate matter (TSS and turbidity). Within the metals category, total iron concentration was highly correlated with most total metal concentrations. The correlations between total and dissolved concentrations were all less than 0.8, even between total and dissolved concentrations of the same metals. Multiple linear regression (MLR) analyses were performed to evaluate the impact of various site and storm event variables on highway runoff constituent EMCs. Parameters found to have significant impacts on highway runoff constituent EMCs include: total event rainfall (TER); cumulative seasonal rainfall (CSR); antecedent dry period (ADP); contributing drainage area (DA); and annual average daily traffic (AADT). Surrounding land use and geographic regions were also determined to have a significant impact on runoff quality. The MLR model was also used to predict constituent EMCs. Model performance determined by comparing predicted and measured values showed good agreement for most constituents.

California↗

PubMed2006

Predicting operative delivery.

OBJECTIVE: Unplanned operative delivery (vaginal or abdominal) is associated with maternal anxiety, maternal and neonatal morbidity and increased resource use. We aimed to identify potential predictors for emergency operative delivery. METHODS: This was a prospective observational study of 202 nulliparous women in a tertiary antenatal unit between 36 and 40 weeks' gestation. The assessment included an interview, a vaginal examination for Bishop score (optional), and a translabial ultrasound examination performed with the woman in a supine position and after voiding to determine cervical length, bladder position on Valsalva, and fetal head engagement. Clinical data were obtained from the institutional obstetric database and patient records. RESULTS: In the late third trimester, body mass index (P = 0.016), maternal age at due date (P < 0.0001), history of Cesarean section in first-degree relatives (P = 0.009), Bishop score (P = 0.0004), cervical length (P = 0.001), bladder position on Valsalva (P = 0.003) and head engagement (P < 0.0001) were significantly associated with delivery mode. On multivariate logistic regression analysis, the best model for predicting normal vaginal delivery contained maternal age, history of Cesarean section, Bishop score and bladder position on Valsalva and had excellent ability to discriminate between normal vaginal delivery and operative delivery (c = 0.85). The model with the best ability to discriminate between vaginal delivery and Cesarean section contained the same parameters plus body mass index; this model performed even better (c = 0.87). CONCLUSIONS: Identification of women at increased risk of operative delivery appears feasible. A combination of clinical and ultrasound variables yielded a model that is likely to predict delivery mode accurately in up to 87% of cases. Such a model may become useful as an entry criterion for intervention trials in women at low or very high risk of operative delivery.

Adult↗

PubMed2005

Vortex shaped current sources in a physical torso phantom.

Recent studies reported differential information in human magnetocardiogram and in electrocardiogram. Vortex currents have been discussed as a possible source of this divergence. With the help of physical phantom experiments, we quantified the influence of active vortex currents on the strength of electric and magnetic signals, and we tested the ability of standard source localization algorithms to reconstruct vortex currents. The active vortex currents were modeled by a set of twelve single current dipoles arranged in a circle and mounted inside a phantom that resembles a human torso. Magnetic and electric data were recorded simultaneously while the dipoles were switched on stepwise one after the other. The magnetic signal strength increased continuously for an increasing number of dipoles switched on. The electric signal strength increased up to a semicircle and decreased thereafter. Source reconstruction with unconstrained focal source models performed well for a single dipole only (less than 3-mm localization error). Minimum norm source reconstruction yielded reasonable results only for a few of the dipole configurations. In conclusion active vortex currents might explain, at least in part, the difference between magnetically and electrically acquired data, but improved source models are required for their reconstruction.

Action Potentials↗

PubMed1988

Clinical predictors of electrophysiologic findings in patients with syncope of unknown origin.

Unexplained syncope is a common medical problem. Intracardiac electrophysiologic studies (EPS) have been used to uncover the underlying arrhythmic mechanisms. Electrophysiologic studies are especially helpful in the management of patients with inducible tachyarrhythmias, but is of limited usefulness in those with normal EPS findings. We investigated whether clinical and noninvasive laboratory variables can predict the results of EPS in 89 patients with unexplained syncope. The prevalence of inducible ventricular tachycardia (VT) was 15%; supraventricular tachycardia, 15%; bradyarrhythmias, 41%; and normal EPS, 29%. We used multivariate discriminant function analysis to predict the results of EPS. The variables selected for identification of patients with inducible VT by this analysis include New York Heart Association (NYHA) functional class, gender, digitalis use, nonsustained VT, and atrial fibrillation. Based on our statistical model, performing EPS on 45% of the patients with unexplained syncope would result in a 90% sensitivity in detecting patients with inducible VT. The variables selected for identification of patients with normal EPS findings include: New York Heart Association functional class, heart disease, digitalis use, and intraventricular conduction. Based on this model, it would require that all but 12% of patients with unexplained syncope be studied to achieve a 90% predictive accuracy for identification of patients with normal EPS. During follow-up, recurrence rates for the different EPS categories did not differ significantly. The five-year cumulative survival among the EPS groups were as follows: VT, 37% +/- 28%; SVT, 90% +/- 9%; bradyarrhythmias, 71% +/- 10%; and normal EPS, 96% +/- 4%. Survival of the VT group differed significantly from that of the normal group. In patients with unexplained syncope, EPS findings can be predicted from clinical and noninvasive laboratory data. Mortality during follow-up relates to EPS findings.

Adult↗

PubMed2006

Symbiotic adaptive neuro-evolution applied to rainfall-runoff modelling in northern England.

This paper uses a symbiotic adaptive neuro-evolutionary algorithm to breed neural network models for the River Ouse catchment. It advances on traditional evolutionary approaches by evolving and optimising individual neurons. Furthermore, it is ideal for experimentation with alternative objective functions. Recent research suggests that sum squared error may not result in the most appropriate models from a hydrological perspective. Models are bred for lead times of 6 and 24 hours and compared with conventional neural network models trained using backpropagation. The algorithm is also modified to use different objective functions in the optimisation process: mean squared error, relative error and the Nash-Sutcliffe coefficient of efficiency. The results show that at longer lead times the evolved neural networks outperform the conventional ones in terms of overall performance. It is also shown that the sum squared error objective function does not result in the best performing model from a hydrological perspective.

Algorithms↗

PubMed2001

A combined architectural and kinetic interpretation model for breast MR images.

RATIONALE AND OBJECTIVES: The purpose of this study was to integrate contrast material kinetic and architectural data from magnetic resonance (MR) images and to assess the improvement in diagnostic accuracy. MATERIALS AND METHODS: MR imaging data from a diagnostic cohort of 100 patients (50 malignant and 50 benign cases) were analyzed. RESULTS: Qualitative classification of the enhancement curve was the most predictive kinetic feature. Receiver operating characteristic (ROC) curves were calculated for the architectural model alone and for the architectural model combined with the qualitative kinetic classification. The results demonstrated a statistically significant increase in ROC area (P = .03) of the combined model compared with that of the architectural model alone. CONCLUSION: The addition of qualitative classification of the time-signal intensity curve to an architectural interpretation model results in significant improvement in model performance as measured by the area under the ROC curve.

Breast Neoplasms↗

PubMed1978

The determination of average hospital length of stay: an economic approach.

The observed variation in length of hospital stay across the regions of the country has long been of interest to regulators, providers, and third party payors in the hospital industry. The purpose of this article is to provide an economic model of hospital and industry behavior within which these variations can be explained. The model is tested using state data for the year 1973. The model performs well, although the theoretical role of the occupancy rate suggests that additional testing is warranted.

Bed Occupancy↗

PubMedDate not supplied

Optimizing a linear algorithm for real-time robotic control using chronic cortical ensemble recordings in monkeys.

Previous work in our laboratory has demonstrated that a simple linear model can be used to translate cortical neuronal activity into real-time motor control commands that allow a robot arm to mimic the intended hand movements of trained primates. Here, we describe the results of a comprehensive analysis of the contribution of single cortical neurons to this linear model. Key to the operation of this model was the observation that a large percentage of cortical neurons located in both frontal and parietal cortical areas are tuned for hand position. In most neurons, hand position tuning was time-dependent, varying continuously during a 1-sec period before hand movement onset. The relevance of this physiological finding was demonstrated by showing that maximum contribution of individual neurons to the linear model was only achieved when optimal parameters for the impulse response functions describing time-varying neuronal position tuning were selected. Optimal parameters included impulse response functions with 1.0- to 1.4-sec time length and 50- to 100-msec bins. Although reliable generalization and long-term predictions (60-90 min) could be achieved after 10-min training sessions, we noticed that the model performance degraded over long periods. Part of this degradation was accounted by the observation that neuronal position tuning varied significantly throughout the duration (60-90 min) of a recording session. Altogether, these results indicate that the experimental paradigm described here may be useful not only to investigate aspects of neural population coding, but it may also provide a test bed for the development of clinically useful cortical prosthetic devices aimed at restoring motor functions in severely paralyzed patients.

Action Potentials↗

PubMed2000

Effect of selected thallophytic glucans on learning behaviour and short-term potentiation.

This paper reviews the effects of thallophytic glucans on rodent cognitive performance modelled by a combination of behavioural and electrophysiological approaches. Glucans were isolated from thallophytic plants, based on prescriptions used in traditional Chinese and Japanese medicine. In parallel with the already described enhancement of hippocampal synaptic plasticity by disaccharides, polysaccharides isolated from lichens Flavoparmelia caperata and Cetrariella islandica, enhanced hippocampal plasticity and behavioural performance in rats.

Animals↗

PubMed1991

Polychotomous multivariate models for coronary heart disease simulation. I. Tests of a logistic model.

Stochastic compartmental modeling techniques have been employed to simulate coronary heart disease morbidity and mortality. In the current paper, polychotomous logistic models are used to describe the relationship between risk of disease and multiple risk factors, effect modification and confounding variables. The process of estimating the parameters for two risk factors and three types of outcomes is described for a population followed for five years. A Statistical Analysis System (SAS) procedure was used to estimate risk factor coefficients based on two partial periods and on the entire five year epoch. Most of the estimated coefficients were found to be statistically significant. The model performance was evaluated by comparing the observational data with simulated outcomes using a micropopulation and Monte Carlo techniques. Two different tests of goodness of fit were used. Satisfactory fits were obtained both for the risk coefficients based on two partial periods and those based on the entire epoch. This indicates that the model is suitable for simulation of the effects of intervention strategies. The use of the entire epoch involved estimates of one half as many parameters as did the use of two partial periods. Accordingly, it is concluded that only the entire epoch need be considered for future studies of this population.

Adult↗

PubMed1993

Mathematical models for the population biology of Ostertagia ostertagi and the significance of aggregated parasite distributions.

Parasite frequency distributions are frequently aggregated. Such distributions are conveniently described using the negative binomial frequency distribution. This distribution is completely characterized by two parameters: the mean of the distribution and an exponent, k. The degree of aggregation is inversely proportional to the value of k. Aggregated parasite distributions enhance the ability of regulatory processes to maintain parasite populations at or near their equilibrium level but incorporating parasite frequency distributions in realistic models of parasite population biology is fraught with difficulty (several simplified examples are given). Indeed, it is not always possible to incorporate parasite frequency distributions and the question arises whether this compromises model performance. Trichostronglyid nematodes, including Ostertagia ostertagi, are aggregated but the estimated value of k for such populations is usually greater than 1. This is typical of populations with high population means (tens of thousands). It is shown that when the degree of aggregation is such that k > 1, the results of a model which recognizes parasite frequency distribution is not much different from the results of a model which assumes all hosts contain exactly the same number of parasites.

Animals↗

PubMed2006

[Prediction of PAHs uptake by ryegrass with a partition-limited model].

The performance of a partition-limited model on prediction of four PAHs (acenaphthene, fluorene, phenanthrene and pyrene) uptake by ryegrass simultaneously was evaluated using a hydroponic system. Results suggest that the model has a good performance on prediction of PAHs uptake. However, the model focused on root translocation only, while excluded foliar uptake, which resulted in a poor performance on prediction of PAHs in shoots. The differences of simulated and experimented concentrations of PAHs were less than 57.4% for roots and less than 98.5% for shoots respectively. If the influence of foliar uptake on the performance of the model was taken into account, the differences for all the four PAHs would be reduced significantly. Since the influence of foliar uptake increased with the increase of the hydrophobic property of the PAHs, the differences decreased with an order of pyrene> phenanthrene> fluorene> acenaphthene, among which the maximum difference for pyrene decreased from 98.5% down to 69.4%.

Biodegradation, Environmental↗

PubMed2006

Comparison of mortality prediction models after open abdominal aortic aneurysm repair.

OBJECTIVES: Comparison of the accuracy of prediction of contemporary mortality prediction models after open Abdominal Aortic Aneurysm (AAA) surgery. METHODS: Post-operative data were collected from AAA patients from 2 UK Intensive Care Units (ICU). POSSUM and VBHOM based models were compared to the APACHE-AAA model which was able to adjust for the hospital-related effect on outcome. Model performance was assessed using measures of calibration, discrimination and subgroup analysis. RESULTS: 541 patients were studied. The in-hospital mortality rate for elective AAA repair (325 patients) was: 6.2% (95% confidence interval (c.i.) 3.5 to 8.8) and for emergency repair (216 patients) was: 28.7% (95% c.i. 22.5-34.9). The APACHE-based model had the best overall fit to the whole population of AAA patients, and also separately in elective and emergency patients. The V-POSSUM physiology-only (p<0.001) and VBHOM (p=0.011) models had a poor fit in elective patients. The RAAA-POSSUM physiology-only (p<0.001) and VBHOM models (p=0.010) had a poor fit in emergency patients. CONCLUSIONS: The APACHE-AAA model with its ability to adjust for both the hospital-related "effect" as well as the patient case-mix, was a more accurate risk stratification model than other contemporary models, in the post-operative AAA patient managed in ICU.

APACHE↗

PubMed2000

The 'consciousness primitive': a competence model of mind and will.

Questions about mind and will are usually raised as though mind and will are either present or absent. Here, a view is presented to suggest that they are only a particular instantiation of a 'consciousness primitive', present in lower animals as well as in primitive portions of the human brain. Physiological variables, drugs and transmitters alter it in order to produce discontinuous products, such as learning, motivation, emotions etc., which are usually studied by performance models as though they are distinctive functions of the brain.

Animals↗

PubMed2026

Unveiling m7G modification patterns and causal drivers governing intracranial aneurysm rupture risk through multi-omics validation and m7G-MeRIP-seq profiling.

Intracranial aneurysm (IA) rupture causes severe brain hemorrhage with high mortality, yet its molecular drivers remain unclear and better risk prediction is urgently needed. Using transcriptomics, single-cell analysis, and genetic data, we investigated the role of N7-methylguanosine (m7G) RNA modification in IA. We identified distinct m7G modification patterns, validated their methylation features in patient samples, and incorporated these patterns into a machine learning-based rupture prediction model. The presence and characteristics of m7G patterns significantly improved model performance, achieving high predictive accuracy across three independent cohorts (AUC 0.91-0.95). Genetic analyses further identified three causal m7G-related genes (NSUN2, IFIT5, SNUPN), and laboratory experiments confirmed their altered expression and methylation in ruptured aneurysms. Overall, our findings demonstrate that m7G modifications play a key role in IA rupture. The validated prediction model offers strong clinical potential for rupture risk assessment, and the identified genes represent promising therapeutic targets.

Humans↗