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Results for “model predictive control”

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At least 865 records · Page 48Linked to original sources

PubMed2005

Is consumption of breakfast associated with body mass index in US adults?

OBJECTIVE: To test the hypothesis that breakfast consumption is associated with weight status measured by body mass index in US adults. DESIGN: Analyses of data from the National Health and Nutrition Examination Survey, 1999-2000. PARTICIPANTS/SETTING: Men and women aged > or = 19 years (N=4,218), excluding pregnant and/or lactating women. STATISTICAL ANALYSES PERFORMED: SAS (release 8.1, 2000, SAS Institute Inc, Cary, NC) and SUDAAN (release 8.0.2, 2003, Research Triangle Institute, Research Triangle Park, NC) software were used to calculate sample-weighted means, standard errors, and population percentages of breakfast consumers. Multiple logistic and linear regression models, with controls for covariates, were used to determine the predictability of body mass index from breakfast consumption and from inclusion of ready-to-eat cereal (RTEC) in the breakfast meal. RESULTS: Breakfast consumers were more likely than breakfast nonconsumers to be older, female, white, nonsmokers, regular exercisers, and trying to control their weight. For women, daily energy intake was higher among breakfast consumers than among breakfast nonconsumers; for both men and women, energy intake from fat among RTEC breakfast consumers was significantly lower than among non-RTEC breakfast consumers, whereas energy from carbohydrate among RTEC breakfast consumers was significantly higher than among non-RTEC breakfast consumers. For women, the odds ratios for BMI > or = 25 were lower for breakfast consumers (odds ratio = 0.76) and RTEC breakfast consumers (odds ratio = 0.70) compared with breakfast nonconsumers and non-RTEC breakfast consumers, respectively, after adjusting the models for covariates. When RTEC consumption was added as a covariate, breakfast consumers no longer exhibited significantly lower odds ratios compared with breakfast nonconsumers. Furthermore, regression analyses supported an inverse association between RTEC breakfast consumption and body mass index in women (regression coefficient = -0.37, P<.01) after adjusting for covariates. CONCLUSIONS: When we document the association of breakfast consumption with lower prevalence of overweight and obesity, types of meal should be considered as an important determinant. RTEC breakfast consumption, associated with a desirable macronutrient profile for preventing obesity, predicted weight status in women, but not in men. In addition to sex difference in the association of breakfast consumption and RTEC breakfast consumption with lower prevalence of overweight, the effects of physiological variables and health-related behaviors on the relationship between total and RTEC intake at breakfast and weight status, remain to be established.

Adult↗

PubMed2005

Model-based analysis of jaw-movement kinematics using jerk-optimal criterion: simulation of human chewing cycles.

Large intra- and/or inter-individual variability in human masticatory motor behaviors may reduce objectivity in assessing normality/abnormality for jaw movements. Analytical simulation by kinematic modeling based on a universally accepted objective criterion is a potentially useful clinical tool for credible diagnostic quantification of jaw motion. This study aimed to test whether a minimum-jerk (maximum-smoothness) model could accurately simulate the kinematics in each separate gum-chewing cycle of 10 healthy adults, and if so, to examine whether simulation errors reflected an extent of abnormality for chewing movements for 10 patients caused by temporomandibular joint disorders (TMD). The model predicted the lower incisor-point movements of the control group with reasonable accuracy. Overall, the prediction errors for the patients group were greater than the control group, demonstrating that prediction errors for jaw opening velocity were sensitive to the criteria for joint disorders. It was concluded that the present simulation emerged as being capable of scaling the not so smooth masticatory jaw movements performed in the presence of TMD.

Adult↗

PubMed1995

Evolution of drug consumption in a sample of adolescents: the predictive capacity of the genesis model.

This paper analyzes the predictive capacity of the genesis model for drug consumption constructed by the authors in an attempt to identify the characteristics of a drug consumption risk population. Several years' research have shown the model's validity in explaining drug consumption, a behavior understood as one of the many for possible use by adolescents to adapt to the environment in which they develop. The potential for behavior which deviates from the norm depends on a variety of factors considered in the model (including level of self-control, attitudes to drugs, or the existence of peers to reinforce such behavior). The predictive capacity of the model is analyzed in a longitudinal study carried out on a sample of 476 students (238 men and 238 women).

Adolescent↗

PubMed1987

Verbal reasoning deficits in alcoholics.

The Conceptual Level Analogies Test (CLAT), a well-constructed test of analogical reasoning, was given to groups of middle-aged male alcoholics and control subjects in two separate studies. As predicted, the alcoholics had lower CLAT scores than nonalcoholics in both studies. These results support the generalized-diffuse model of the neuropsychological effects of alcoholism. Contrary to prediction, alcoholics differed from control subjects as much on the easy analogies as they did on the hard analogies, which suggested that alcoholics differ both qualitatively and quantitatively from nonalcoholics in cognitive impairment. Finally, in two of three studies in our laboratory, familial alcoholics had significantly lower CLAT scores than nonfamilial alcoholics. These findings emphasize the importance of considering familial history of alcoholism when studying the neuropsychological functioning of alcoholics.

Adult↗

PubMed1999

A multisensory integration model of human stance control.

A model is presented to study and quantify the contribution of all available sensory information to human standing based on optimal estimation theory. In the model, delayed sensory information is integrated in such a way that a best estimate of body orientation is obtained. The model approach agrees with the present theory of the goal of human balance control. The model is not based on purely inverted pendulum body dynamics, but rather on a three-link segment model of a standing human on a movable support base. In addition, the model is non-linear and explicitly addresses the problem of multisensory integration and neural time delays. A predictive element is included in the controller to compensate for time delays, necessary to maintain erect body orientation. Model results of sensory perturbations on total body sway closely resemble experimental results. Despite internal and external perturbations, the controller is able to stabilise the model of an inherently unstable standing human with neural time delays of 100 ms. It is concluded, that the model is capable of studying and quantifying multisensory integration in human stance control. We aim to apply the model in (1) the design and development of prostheses and orthoses and (2) the diagnosis of neurological balance disorders.

Afferent Pathways↗

PubMed1990

Simulation of nitrous oxide concentrations in operating and recovery rooms.

A model was developed to predict nitrous oxide (N2O) concentrations in operating (OR) and recovery rooms. The model incorporates general ventilation characteristics, percentage recirculation and the rate at which N2O is emitted into the OR (emission) for the calculation of environmental exposure. A workplace study was carried out during which N2O concentrations were measured continuously and coupled to anaesthetic activities (type and duration), air-change rate and percentage of recirculated air. The data from this study were used to calculate N2O emission. Subsequently, the model was used to predict the effect of technical measures to reduce emissions on mean environmental exposure. After implementation of the control measures an intervention study was made to check whether the reduction in exposure was predicted by our simulation model. Subsequently the 'validated' simulation model was used: (i) to calculate the exposure for different percentages of recirculation and different air-change rates, and (ii) to estimate N2O levels in another situation, i.e. an operating room in an outpatients clinic. In short, our study shows how modelling can help both occupational hygiene and hospital management to control exposure to anaesthetic gases and to design or adapt ventilation systems of operating rooms and recovery rooms.

Computer Simulation↗

PubMed2004

Theoretical analysis of the effects of viscous losses and abdominal straining on urinary outlet function.

AIMS: The aim of this study was to theoretically explore the relationship between the tube law (TL) of the urethra and the pressure-flow (p-Q) relationship during micturition. The understanding of this relation is important for the evaluation of outlet obstruction by urodynamic interpretation of p-Q plots. METHODS: We simulated the outlet function by a lumped theoretical model, and suggested how the TL can be used to quantitatively predict the p-Q relationship of the system. Our analysis considered the relation between the TL and the steady state p-Q plot for various TLs including the hysteresis of the pressure-area relationship. RESULTS AND CONCLUSIONS: The inclusion of pressure losses distal to the flow controlling zone and experimentally measured p-A relations of the urethra in the model lead to the predictions that flow in the flow controlling zone is not always critical but is often in the sub-critical range, that an increase in abdominal pressure can increase the flow under certain conditions, and that hysteresis in the pressure-area relation is correlated to the hysteresis in the p-Q plot.

Abdomen↗

PubMed1989

Cost effectiveness of current approaches to the control of retinopathy in type I diabetics.

Diabetic retinopathy is a leading cause of blindness among working age Americans. The epidemiology of diabetic eye disease has been well described in population-based studies and the effects of laser treatment have been tested in randomized controlled trials. The authors have designed a computer simulation model using the published reports of these studies to predict the medical and economic effects of applying currently accepted methods for the control of diabetic retinopathy to the population of type I diabetics. Recommendations for screening are taken from the Public Health Committee of the American Academy of Ophthalmology. Treatment recommendations and treatment efficacy are drawn from the reports of the Diabetic Retinopathy Study (DRS) and the Early Treatment Diabetic Retinopathy Study (ETDRS). Costs of screening and treatment are drawn from published Medicare reimbursement data. Over a 60-year period, the model predicts that proliferative diabetic retinopathy (PDR) requiring panretinal photocoagulation (PRP) will eventually develop in 72% of type I diabetics and macular edema will develop in 42%. If these treatments are delivered as recommended in the clinical trials, the model predicts a cost of $966 per person-year of vision saved from proliferative retinopathy and $1118 per person-year of central acuity saved from macular edema. This is only one seventh of the $6900 average cost of 1 year of Social Security Disability for those disabled by vision loss. Therefore, this model supports the use of federally funded eye care to prevent blindness in medically uninsured diabetics.

Adolescent↗

PubMed1999

A model of internal control may improve the response time of an automatic arterial pressure controller.

A simplified model for the arterial pressure control system was implemented on a personal computer using Matlab Simulink. Model responses to variations of systemic vascular resistance were comparable to those predicted by physiology. Computer simulation suggested that including this model of the internal pressure control system within the design of an external controller would achieve better arterial pressure control and faster response than previous systems.

Blood Pressure↗

PubMed2003

Perceived control and distress following sexual assault: a longitudinal test of a new model.

Longitudinal data were collected from female sexual assault survivors (N = 171) at 4 points postassault. Consistent with the predictions of the temporal model (P. Frazier, M. Berman, & J. Steward, 2002), past, present, and future control were differentially related to posttrauma distress. Both personal past (behavioral self-blame) and vicarious past (rapist blame) control were associated with higher distress levels. In addition, the belief that future assaults are less likely was more strongly associated with lower distress levels than was future control. Present control (i.e., control over the recovery process) was most adaptive. Hierarchical linear modeling analyses revealed that changes in perceived control were associated with changes in distress after linear change in distress over time was accounted for.

Adult↗

PubMed1994

Muscle-invasive bladder cancer treated with external beam radiotherapy: prognostic factors.

PURPOSE: To determine the relationship of several potential prognostic factors to the outcome measures of pelvic control, freedom from metastases, and overall survival for bladder cancer patients treated with definitive external beam radiotherapy. METHODS AND MATERIALS: The records of 135 patients treated with high-dose, planned continuous-course, external beam radiotherapy for muscle-invasive transitional cell bladder cancer were reviewed. These patients were treated to an average total dose of 6588 +/- 475 cGy with an average fractional dose of 207 +/- 18 cGy using megavoltage. Median potential follow-up for all patients, including those who died, was 249 months. RESULTS: The actuarial results at 5 year were 31% pelvic control, 58% freedom from metastases, and 26% overall survival. In the univariate analyses, several factors were correlated with disease outcome including clinical stage, tumor morphology, gross total transurethral resection (TURBT), findings at bimanual exam after TURBT, clinical perivesical extension, age, and clinical complete response at first follow-up cystoscopy (Clinical-CR). A Cox proportional hazards model revealed that only Clinical-CR was independently predictive of pelvic control. In terms of freedom from metastases, only Clinical-CR and clinical stage were significantly associated with outcome in the multivariate analysis. When the multivariate analysis was restricted to T2 and T3 tumors only, then clinical perivesical extension replaced stage as being associated with freedom from metastases. The only factors significantly related to overall survival in the Cox proportional hazards model were Clinical-CR, age, and complete TURBT; stage was of borderline significance when only pretreatment factors were considered. CONCLUSIONS: Clearly, the most important prognostic factor was Clinical-CR. The pretreatment factors of stage, clinical perivesical extension, and gross total TURBT also correlated with outcome, but, to a lesser degree. For patients medically unfit for radical cystectomy radiotherapy is a viable option, particularly for selected patients. Patients with T4 tumors are poor candidates for definitive radiotherapy and should be treated palliatively if they cannot tolerate systemic therapy.

Aged↗

PubMed2005

Length-dependent [Ca2+] sensitivity adds stiffness to muscle.

It is well documented that muscle fibers become more sensitive for [Ca2+] with increasing sarcomere length. In mechanical terms this length-dependent [Ca2+] sensitivity (LDCS) adds to the stiffness of muscle fibers, because muscle force, normalized for the force-length relationship at maximal stimulation, increases with contractile element (CE) length. Although LDCS is well-documented in the physiological literature, it is ignored in most motor control studies. The aim of the present study was to investigate the importance of LDCS as a contributor to the stiffness of a muscle. Comparison of experimental data with predictions derived from the model of activation dynamics proposed by Hatze (Myocybernetic Control Models of Skeletal Muscle, University of South Africa, Pretoria, 1981, pp. 31-42) indicated that this model captures the main characteristics of LDCS well. It was shown that LDCS accounts for the experimentally observed shifts in optimum length at sub-maximal stimulation levels. Furthermore, it was shown that in conditions with low-to-medium muscle stimulation, the contribution of LDCS to the total amount of stiffness provided by the muscle is substantial. It was concluded that LDCS is an important muscle property and should be taken into account in studies concerning motor control.

Animals↗

PubMed1998

Predicting lettuce canopy photosynthesis with statistical and neural network models.

An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).

Carbon Dioxide↗

PubMed2002

Preoperative parameters for predicting early prostate cancer recurrence after radical prostatectomy.

OBJECTIVES: To determine whether easily measurable prostate biopsy features could complement Gleason score, prostate-specific antigen (PSA), or clinical stage in predicting recurrence-free survival after prostatectomy. Information relating preoperative parameters to recurrence-free survival is needed to counsel patients with newly diagnosed prostate cancer regarding expectations for postprostatectomy cancer control. METHODS: The data of a cohort of 588 consecutive prostatectomy patients (median age 61 years, range 39 to 83) with ascertained preoperative data and up to 4 years of postprostatectomy follow-up were analyzed. Bivariate and multivariate Cox proportional hazards analysis evaluated preoperative factors (clinical stage, PSA, biopsy Gleason score, greatest percentage of a biopsy core involved by cancer [GPC], number of biopsy cores containing cancer, perineural invasion) to identify those relating significantly to recurrence-free survival. Functional forms of these factors were evaluated to optimize accuracy in predicting cancer control. RESULTS: The baseline parameters significantly affecting PSA-free survival included PSA level (P <0.01), biopsy Gleason score (P = 0.04), and GPC (P <0.01). Although clinical stage and perineural invasion had a marginal association with PSA-free survival as univariate factors, this association was not independently significant in multivariable analysis. The multivariate Cox model using PSA, Gleason score, and GPC was highly predictive of PSA free-survival (chi-square = 48.2, P = 0.0001). A set of plots representing these data can be used to identify the risk of early postoperative PSA recurrence on the basis of specific preoperative PSA, Gleason score, and GPC values. CONCLUSIONS: These findings provide a highly significant model and a simple tool for assisting preoperative patient counseling regarding predicted cancer control after radical prostatectomy.

Adult↗

PubMed1996

Exploring the mechanisms of primary antibody responses to T cell-dependent antigens.

We have developed a model of the early events that occur during a primary antibody response to a T cell-dependent antigen. Within secondary lymphoid organs, B cell proliferation in response to antigen injection gives rise to two kinds of transient structures: foci that develop in the T cell area, and germinal centers, that develop in the secondary follicles of the B cell area. Foci give rise to plasma cells that are responsible for the majority of early circulating antibody, whereas germinal centers are sites of somatic mutation and memory cell formation. Here we model the cell-cell interactions and cell population kinetics involved in the generation of antibody-forming cell foci, and compare our model with experimental data. We focus on fundamental issues involving the control of B cell proliferation and differentiation, using simple kinetic models that depend on direct cell-cell interactions and on the action of cytokines. We show that with realistic parameter assumptions our model can account for both the rapid cellular expansion and the differentiation of B cells into antibody-secreting cells. By summing the expected antibody production of all the plasmablasts and plasma cells that are generated during the focus response we can account for much of the antibody observed in the serum of mice during a primary response. Lastly, we compare the predictions of our model for two different scenarios for the control of B cell proliferation. In one model, we assume that B cells, once activated, proliferate under the control of cytokines without direct interaction with activated T cells. In the other model, we assume that after dividing B cells return to rest and require a contact-dependent signal from an activated T cell to divide again. The first model gives rise to large foci and antibody levels similar to that observed in experiment, whereas the latter model gives rise to four-fold smaller foci and to circulating antibody levels that are one order of magnitude lower than typical experimental values. This result suggests that B cells may be able to divide without further contact with T cells once a cognate interaction has occurred.

Antibody Formation↗

PubMed2006

Cortical reorganization following intradigital tendon transfer.

We distinguish between two models of adult cortical reorganization, adaptive and constant somatotopy, using functional magnetic resonance imaging maps corresponding to individual thumb and fourth-finger digits in a patient with a right-hand fourth digit tendon transfer that salvaged impaired function of the right thumb. Comparison of motor and sensory maps for both digits and both hands was consistent with a model of 'adaptive somatotopy' in which thumb control was taken over by regions adjacent to the fourth finger control cluster rather than at the presurgical lateral region as predicted by a model of 'constant somatotopy'. These findings are the first to demonstrate that rerouting of peripheral input, in the absence of brain injury, is sufficient to drive cortical reorganization resulting in recovery of lost motor function, and further suggest an adaptive mechanism associated with brain tissue engaged in intact motor functions.

Aged, 80 and over↗

PubMedDate not supplied

A mathematical model for cisplatin cellular pharmacodynamics.

A simple theoretical model for the cellular pharmacodynamics of cisplatin is presented. The model, which takes into account the kinetics of cisplatin uptake by cells and the intracellular binding of the drug, can be used to predict the dependence of survival (relative to controls) on the time course of extracellular exposure. Cellular pharmacokinetic parameters are derived from uptake data for human ovarian and head and neck cancer cell lines. Survival relative to controls is assumed to depend on the peak concentration of DNA-bound intracellular platinum. Model predictions agree well with published data on cisplatin cytotoxicity for three different cancer cell lines, over a wide range of exposure times. In comparison with previously published mathematical models for anticancer drug pharmacodynamics, the present model provides a better fit to experimental data sets including long exposure times (approximately 100 hours). The model provides a possible explanation for the fact that cell kill correlates well with area under the extracellular concentration-time curve in some data sets, but not in others. The model may be useful for optimizing delivery schedules and for the dosing of cisplatin for cancer therapy.

Antineoplastic Agents↗

PubMed2026

Integrative machine learning models to unravel gut microbial dysbiosis and functional disruption in polycystic ovary syndrome.

OBJECTIVE: To study gut microbial diversity and metabolic pathway disruptions in women with PolyCystic Ovary Syndrome (PCOS) compared with healthy controls, and to evaluate the diagnostic potential of microbiome-driven machine learning models. DESIGN: Case-controlled metagenomic data analysis SUBJECTS: Gut metagenomic data from women diagnosed with PCOS and age-matched healthy female controls EXPOSURE: Presence of PCOS MAIN OUTCOME MEASURES: The primary outcome measures will include gut microbial alpha and beta diversity indices, microbial taxon abundance, functional pathway profiles, predicted metabolite levels, microbe-functional pathway-metabolite interaction networks, and the diagnostic accuracy of microbiome-based machine learning models. RESULTS: Alpha and beta diversity analyses revealed marked gut microbial dysbiosis in women with PCOS, despite comparable species richness to healthy controls. Differential abundance analysis identified 41 significantly altered microbial species, including enrichment of proinflammatory taxa, such as Bacteroides vulgatus and Ruminococcus gnavus, and depletion of beneficial commensals, including Roseburia hominis and Prevotella copri. These compositional shifts indicate a proinflammatory microbial community structure in PCOS. Functional profiling demonstrated the upregulation of pathways involved in nucleotide turnover, lipid and carbohydrate metabolism, and neurotransmitter synthesis, potentially contributing to metabolic and neuroendocrine disruption. Network analysis revealed fragmented and unstable microbial-metabolite associations in PCOS compared with cohesive networks in controls. Microbiome-based machine learning models achieved a diagnostic accuracy of 84.25% (area under the curve 0.93), underscoring their predictive potential. CONCLUSION: The gut microbiome in PCOS is characterized by a proinflammatory community structure and disrupted metabolic pathways. These findings demonstrate the diagnostic potential of microbiome-based models and underscore the gut microbiome as a promising target for therapeutic interventions in the management of PCOS.

Polycystic Ovary Syndrome↗