Modeling the Drying Kinetics of Green Bell Pepper in a Heat Pump Assisted Fluidized Bed Dryer

In this research, green bell pepper was dried in a pilot plant fluidized bed dryer equipped with a heat pump humidifier using three temperatures of 40, 50 and 60C and two airflow velocities of 2 and 3m/s in constant air moisture. Three modeling methods including nonlinear regression technique, Fuzzy Logic and Artificial Neural Networks were applied to investigate drying kinetics for the sample. Among the mathematical models, Midilli model with R=0.9998 and root mean square error (RMSE)=0.00451 showed the best fit with experimental data. Feed-Forward-Back-Propagation network with Levenberg-Marquardt training algorithm, hyperbolic tangent sigmoid transfer function, training cycle of 1,000 epoch and 2-5-1 topology, deserving R=0.99828 and mean square error (MSE)=5.5E-05, was determined as the best neural model. Overall, Neural Networks method was much more precise than two other methods in prediction of drying kinetics and control of drying parameters for green bell pepper. Practical Applications: This article deals with different modeling approaches and their effectiveness and accuracy for predicting changes in the moisture ratio of green bell pepper enduring fluidized bed drying, which is one of the most concerning issues in food factories involved in drying fruits and vegetables. This research indicates that although efficiency of mathematical modeling, Fuzzy Logic controls and Artificial Neural Networks (ANNs) were all acceptable, the modern prediction methods of Fuzzy Logic and especially ANNs were more productive and precise. Besides, this report compares our findings with previous ones carried out with the view of predicting moisture quotients of other food crops during miscellaneous drying procedures. © 2016 Wiley Periodicals, Inc

Microencapsulation optimization of natural anthocyanins with maltodextrin, gum Arabic and gelatin

The barberry (Berberis vulgaris) extract which is a rich source of anthocyanins was used for spray drying encapsulation with three different wall materials, i.e., combination of maltodextrin and gum Arabic (MD + GA), maltodextrin and gelatin (MD + GE), and maltodextrin (MD). Response Surface Methodology (RSM) was applied for optimization of microencapsulation efficiency and physical properties of encapsulated powders considering wall material type as well as different ratios of core to wall materials as independent variables. Physical characteristics of spray-dried powders were investigated by further analyses of moisture content, hygroscopicity, degree of caking, solubility, bulk and absolute density, porosity, flowability and microstructural evaluation of encapsulated powders. Our results indicated that samples produced with MD + GA as wall materials represented the highest process efficiency and best powder quality; the optimum conditions of microencapsulation process for barberry anthocyanins were found to be the wall material content and anthocyanin load of 24.54 and 13.82, respectively. Under such conditions, the microencapsulation efficiency (ME) of anthocyanins could be as high as 92.83. © 2016 Elsevier B.V

Thermal and mechanical properties of chitosan nanocomposites with cellulose modified in ionic liquids

In this paper, ionic liquid treatment was applied to produce nanometric cellulose particles of two polymorphic forms. A complex characterization of nanofillers including wide-angle X-ray scattering, Fourier transform infrared spectroscopy, and particle size determination was performed. The evaluated ionic liquid treatment was effective in terms of nanocrystalline cellulose production, leaving chemical and supermolecular structure of the materials intact. However, nanocrystalline cellulose II was found to be more prone to ionic liquid hydrolysis leading to formation larger amount of small particles. Each nanocrystalline cellulose was subsequently mixed with a solution of chitosan, so that composite films containing 1, 3, and 5% mass/mass of nanometric filler were obtained. Reference samples of chitosan and chitosan with micrometric celluloses were also solvent casted. Thermal, mechanical, and morphological properties of films were tested and correlated with properties of filler used. The results of both, tensile tests and thermogravimetric analysis showed a significant discrepancy between composites filled with nanocrystalline cellulose I and nanocrystalline cellulose II

Conceptual robustness in simultaneous engineering: An extension of Taguchi's parameter design

Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchi's parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team as conceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release the conceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchi's approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45879/1/163_2005_Article_BF01608400.pd

The January 6 Insurrectionists: Who They Are and What They Did (Dataset)

This is the underlying dataset for the Seton Hall Law Center for Policy and Research paper "The January 6 Insurrectionists: Who They Are and What They Did."THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Data for: The January 6 Insurrectionists: Who They Are and What They Did

This is the underlying dataset for the Seton Hall Law Center for Policy and Research paper "The January 6 Insurrectionists: Who They Are and What They Did."THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Prevalence of depression in patients with cancer in Iran: A systematic review and meta-analysis

Introduction: It is generally accepted that depression, affecting the quality of life, is a serious and common complication in patients with cancer. Given that there is no integrated study on this topic in Iran, the present study sought to investigate the prevalence of depression in patients with cancer by a systematic review and meta-analysis. Methods: To meet the study objectives, all English and Persian papers published from 2000 to January 2018 were systematically collected and the data were extracted for analysis. Results: There were 14 studies which were selected on the basis of the inclusion and exclusion criteria. A total number of 2831 patients with cancer had participated in the studies. The prevalence of depression among Iranian patients with cancer was 35 (95 CI 16 to 70) based on random effects model. Among various types of cancer, the highest prevalence of depression appeared to patients suffering from breast cancer. Conclusion: The prevalence of depression among patients with cancer in Iran was higher than the developed countries. As depression affects the quality of life of patients with cancer, the results can help policymakers and service providers in planning to reduce the prevalence of depression. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ