Fuzzy-Enhanced Modeling of Lignocellulosic Biomass Enzymatic Saccharification

The enzymatic hydrolysis of lignocellulosic biomass incorporates many physico-chemical phenomena, in a heterogeneous and complex media. In order to make the modeling task feasible, many simplifications must be assumed. Hence, different simplified models, such as Michaelis-Menten and Langmuir-based ones, have been used to describe batch processes. However, these simple models have difficulties in predicting fed-batch operations with different feeding policies. To overcome this problem and avoid an increase in the complexity of the model by incorporating other phenomenological terms, a Takagi-Sugeno Fuzzy approach has been proposed, which manages a consortium of different simple models for this process. Pretreated sugar cane bagasse was used as biomass in this case study. The fuzzy rule combines two Michaelis-Menten-based models, each responsible for describing the reaction path for a distinct range of solids concentrations in the reactor. The fuzzy model improved fitting and increased prediction in a validation data set.

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Development and temporal external validation of a simple risk score tool for prediction of outcomes after severe head injury based on admission characteristics from level-1 trauma centre of India using retrospectively collected data

BMJ Open ◽

10.1136/bmjopen-2020-040778 ◽

2021 ◽

Vol 11 (1) ◽

pp. e040778

Author(s):

Vineet Kumar Kamal ◽

Ravindra Mohan Pandey ◽

Deepak Agrawal

Keyword(s):

Hospital Mortality ◽

External Validation ◽

Trauma Centre ◽

Unfavourable Outcome ◽

Motor Score ◽

Validation Data ◽

Data Set ◽

Development Data ◽

Level 1 ◽

Pupillary Reactivity

ObjectiveTo develop and validate a simple risk scores chart to estimate the probability of poor outcomes in patients with severe head injury (HI).DesignRetrospective.SettingLevel-1, government-funded trauma centre, India.ParticipantsPatients with severe HI admitted to the neurosurgery intensive care unit during 19 May 2010–31 December 2011 (n=946) for the model development and further, data from same centre with same inclusion criteria from 1 January 2012 to 31 July 2012 (n=284) for the external validation of the model.Outcome(s)In-hospital mortality and unfavourable outcome at 6 months.ResultsA total of 39.5% and 70.7% had in-hospital mortality and unfavourable outcome, respectively, in the development data set. The multivariable logistic regression analysis of routinely collected admission characteristics revealed that for in-hospital mortality, age (51–60, >60 years), motor score (1, 2, 4), pupillary reactivity (none), presence of hypotension, basal cistern effaced, traumatic subarachnoid haemorrhage/intraventricular haematoma and for unfavourable outcome, age (41–50, 51–60, >60 years), motor score (1–4), pupillary reactivity (none, one), unequal limb movement, presence of hypotension were the independent predictors as its 95% confidence interval (CI) of odds ratio (OR)_did not contain one. The discriminative ability (area under the receiver operating characteristic curve (95% CI)) of the score chart for in-hospital mortality and 6 months outcome was excellent in the development data set (0.890 (0.867 to 912) and 0.894 (0.869 to 0.918), respectively), internal validation data set using bootstrap resampling method (0.889 (0.867 to 909) and 0.893 (0.867 to 0.915), respectively) and external validation data set (0.871 (0.825 to 916) and 0.887 (0.842 to 0.932), respectively). Calibration showed good agreement between observed outcome rates and predicted risks in development and external validation data set (p>0.05).ConclusionFor clinical decision making, we can use of these score charts in predicting outcomes in new patients with severe HI in India and similar settings.

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A novel ferroptosis related gene signature is associated with prognosis in patients with ovarian serous cystadenocarcinoma

Scientific Reports ◽

10.1038/s41598-021-90126-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhixiang Yu ◽

Haiyan He ◽

Yanan Chen ◽

Qiuhe Ji ◽

Min Sun

Keyword(s):

Cox Regression ◽

Expression Profiles ◽

Critical Role ◽

Gene Signature ◽

Cancer Genome ◽

Training Data ◽

Hub Genes ◽

Validation Data ◽

Data Set ◽

Cox Regression Analysis

AbstractOvarian cancer (OV) is a common type of carcinoma in females. Many studies have reported that ferroptosis is associated with the prognosis of OV patients. However, the mechanism by which this occurs is not well understood. We utilized Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) to identify ferroptosis-related genes in OV. In the present study, we applied Cox regression analysis to select hub genes and used the least absolute shrinkage and selection operator to construct a prognosis prediction model with mRNA expression profiles and clinical data from TCGA. A series of analyses for this signature was performed in TCGA. We then verified the identified signature using International Cancer Genome Consortium (ICGC) data. After a series of analyses, we identified six hub genes (DNAJB6, RB1, VIMP/ SELENOS, STEAP3, BACH1, and ALOX12) that were then used to construct a model using a training data set. The model was then tested using a validation data set and was found to have high sensitivity and specificity. The identified ferroptosis-related hub genes might play a critical role in the mechanism of OV development. The gene signature we identified may be useful for future clinical applications.

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Evaluation of the CONSUME and FOFEM fuel consumption models in pine and mixed hardwood forests of the eastern United States

Canadian Journal of Forest Research ◽

10.1139/cjfr-2013-0499 ◽

2014 ◽

Vol 44 (7) ◽

pp. 784-795 ◽

Cited By ~ 10

Author(s):

Susan J. Prichard ◽

Eva C. Karau ◽

Roger D. Ottmar ◽

Maureen C. Kennedy ◽

James B. Cronan ◽

...

Keyword(s):

United States ◽

Fuel Consumption ◽

Prescribed Burning ◽

Forest Type ◽

Fire Effects ◽

Eastern United States ◽

Validation Data ◽

Data Set ◽

Predicted Values ◽

Fine Fuels

Reliable predictions of fuel consumption are critical in the eastern United States (US), where prescribed burning is frequently applied to forests and air quality is of increasing concern. CONSUME and the First Order Fire Effects Model (FOFEM), predictive models developed to estimate fuel consumption and emissions from wildland fires, have not been systematically evaluated for application in the eastern US using the same validation data set. In this study, we compiled a fuel consumption data set from 54 operational prescribed fires (43 pine and 11 mixed hardwood sites) to assess each model’s uncertainties and application limits. Regions of indifference between measured and predicted values by fuel category and forest type represent the potential error that modelers could incur in estimating fuel consumption by category. Overall, FOFEM predictions have narrower regions of indifference than CONSUME and suggest better correspondence between measured and predicted consumption. However, both models offer reliable predictions of live fuel (shrubs and herbaceous vegetation) and 1 h fine fuels. Results suggest that CONSUME and FOFEM can be improved in their predictive capability for woody fuel, litter, and duff consumption for eastern US forests. Because of their high biomass and potential smoke management problems, refining estimates of litter and duff consumption is of particular importance.

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Design of PDC Controllers by Matrix Reversibility for Synchronization ofYinandYangChaotic Takagi-Sugeno Fuzzy Henon Maps

Abstract and Applied Analysis ◽

10.1155/2012/358201 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Chun-Yen Ho ◽

Hsien-Keng Chen ◽

Zheng-Ming Ge

Keyword(s):

Chaos Synchronization ◽

Matrix Theory ◽

Chinese Philosophy ◽

Fuzzy Model ◽

Invertible Matrix ◽

Henon Maps ◽

Hénon Maps ◽

Feminine Principle ◽

Simulation Results ◽

Takagi Sugeno

This paper investigates the synchronization ofYinandYangchaotic T-S fuzzy Henon maps via PDC controllers. Based on the Chinese philosophy,Yinis the decreasing, negative, historical, or feminine principle in nature, whileYangis the increasing, positive, contemporary, or masculine principle in nature.YinandYangare two fundamental opposites in Chinese philosophy. The Henon map is an invertible map; so the Henon maps with increasing and decreasing argument can be called theYangandYinHenon maps, respectively. Chaos synchronization ofYinandYangT-S fuzzy Henon maps is achieved by PDC controllers. The design of PDC controllers is based on the linear invertible matrix theory. The T-S fuzzy model ofYinandYangHenon maps and the design of PDC controllers are novel, and the simulation results show that the approach is effective.

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Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model

2008 16th Mediterranean Conference on Control and Automation ◽

10.1109/med.2008.4602239 ◽

2008 ◽

Cited By ~ 31

Author(s):

Abdelkader Akhenak ◽

Mohammed Chadli ◽

Jose Ragot ◽

Didier Maquin

Keyword(s):

Fault Detection ◽

Sliding Mode ◽

Fuzzy Model ◽

Sliding Mode Observer ◽

Fault Detection And Isolation ◽

Takagi Sugeno

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Time-varying neuro-fuzzy model using probability density function techniques for batch processes

Journal of Statistical Computation and Simulation ◽

10.1080/00949655.2013.782027 ◽

2013 ◽

Vol 84 (6) ◽

pp. 1249-1260 ◽

Cited By ~ 2

Author(s):

Li Jia ◽

Kai Yuan

Keyword(s):

Probability Density Function ◽

Probability Density ◽

Density Function ◽

Fuzzy Model ◽

Batch Processes ◽

Time Varying ◽

Neuro Fuzzy

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Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽

10.3390/pr9050823 ◽

2021 ◽

Vol 9 (5) ◽

pp. 823

Author(s):

Wen-Jer Chang ◽

Yu-Wei Lin ◽

Yann-Horng Lin ◽

Chin-Lin Pen ◽

Ming-Hsuan Tsai

Keyword(s):

Nonlinear Systems ◽

Fuzzy Controller ◽

Controller Design ◽

Actuator Saturation ◽

Design Method ◽

Fuzzy Model ◽

The Stability ◽

Interval Type ◽

Takagi Sugeno

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

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127 Predicting Dry Matter Intake of Gestating and Lactating Beef Cows

Journal of Animal Science ◽

10.1093/jas/skz397.132 ◽

2020 ◽

Vol 98 (Supplement_2) ◽

pp. 58-58

Author(s):

Megan A Gross ◽

Claire Andresen ◽

Amanda Holder ◽

Alexi Moehlenpah ◽

Carla Goad ◽

...

Keyword(s):

Beef Cattle ◽

Milk Yield ◽

Feed Intake ◽

Beef Cows ◽

Multiple Regression Equation ◽

Validation Data ◽

Data Set ◽

Lactating Cows ◽

Downward Bias ◽

Protein Supply

Abstract In 1996, the NASEM beef cattle committee developed and published an equation to estimate cow feed intake using results from studies conducted or published between 1979 and 1993 (Nutrient Requirements of Beef Cattle). The same equation was recommended for use in the most recent version of this publication (2016). The equation is sensitive to cow weight, diet digestibility and milk yield. Our objective was to validate the accuracy of this equation using more recent published and unpublished data. Criteria for inclusion in the validation data set included projects conducted or published within the last ten years, direct measurement of forage intake, adequate protein supply, and pen feeding (no tie stall or metabolism crate data). The validation data set included 29 treatment means for gestating cows and 26 treatment means for lactating cows. Means for the gestating cow data set was 11.4 ± 1.9 kg DMI, 599 ± 77 kg BW, 1.24 ± 0.14 Mcal/kg NEm per kg of feed and lactating cow data set was 14.5 ± 2.0 kg DMI, 532 ± 116.3 kg BW, and 1.26 ± 0.24 Mcal NEm per kg feed, respectively. Non intercept models were used to determine equation accuracy in predicting validation data set DMI. The slope for linear bias in the NASEM gestation equation did not differ from 1 (P = 0.07) with a 3.5% positive bias. However, when the NASEM equation was used to predict DMI in lactating cows, the slope for linear bias significantly differed from 1 (P < 0.001) with a downward bias of 13.7%. Therefore, a new multiple regression equation was developed from the validation data set: DMI= (-4.336 + (0.086427 (BW^.75) + 0.3 (Milk yield)+6.005785(NEm)), (R-squared=0.84). The NASEM equation for gestating beef cows was reasonably accurate while the lactation equation underestimated feed intake.

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Fuzzy observer–based disturbance rejection control for nonlinear fractional-order systems with time-varying delay

Journal of Vibration and Control ◽

10.1177/10775463211006958 ◽

2021 ◽

pp. 107754632110069

Author(s):

Parvin Mahmoudabadi ◽

Mahsan Tavakoli-Kakhki

Keyword(s):

Fractional Order ◽

Disturbance Rejection ◽

State Feedback ◽

Sufficient Conditions ◽

Fuzzy Model ◽

Linear Matrix ◽

Delayed Systems ◽

Fuzzy Observer ◽

Time Varying Delay ◽

Takagi Sugeno

In this article, a Takagi–Sugeno fuzzy model is applied to deal with the problem of observer-based control design for nonlinear time-delayed systems with fractional-order [Formula: see text]. By applying the Lyapunov–Krasovskii method, a fuzzy observer–based controller is established to stabilize the time-delayed fractional-order Takagi–Sugeno fuzzy model. Also, the problem of disturbance rejection for the addressed systems is studied via the state-feedback method in the form of a parallel distributed compensation approach. Furthermore, sufficient conditions for the existence of state-feedback gains and observer gains are achieved in the terms of linear matrix inequalities. Finally, two numerical examples are simulated for the validation of the presented methods.

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