Application of artificial neural network and multiple linear regression in modeling nutrient recovery in vermicompost under different conditions

© 2020 Elsevier Ltd Vermicomposting is one of the best technologies for nutrient recovery from solid waste. This study aims to assess the efficiency of Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models in predicting nutrient recovery from solid waste under different vermicompost treatments. Seven chemical and biological indices were studied as input variables to predict total nitrogen (TN) and total phosphorus (TP) recovery. The developed ANN and MLR models were compared by statistical analysis including R-squared (R2), Adjusted-R2, Root Mean Square Error and Absolute Average Deviation. The results showed that vermicomposting increased TN and TP proportions in final products by 1.5 and 16 times. The ANN models provided better prediction for TN and TP with R2 of 0.9983 and 0.9991 respectively, compared with MLR models with R2 of 0.834 and 0.729. TN and C/N ratio were key factors for TP and TN prediction by ANN with percentages of 17.76 and 18.33

Dielectric relaxations in PEEK by combined dynamic dielectric spectroscopy and thermally stimulated current

The molecular dynamics of a quenched poly (ether ether ketone) (PEEK) was studied over a broad frequency range from 10-3 to 106 Hz by combining dynamic dielectric spectroscopy (DDS) and thermo-stimulated current (TSC) analysis. The dielectric relaxation losses e00 KK has been determined from the real part e0 T(x) thanks to Kramers–Kronig transform. In this way, conduction and relaxation processes can be analyzed independently. Two secondary dipolar relaxations, the c and the b modes, corresponding to non-cooperative localized molecular mobility have been pointed out. The main a relaxation appeared close to the glass transition temperature as determined by DSC; it has been attributed to the delocalized cooperative mobility of the free amorphous phase. The relaxation times of dielectric relaxations determined with TSC at low frequency converge with relaxation times extracted from DDS at high frequency. This correlation emphasized continuity of mobility kinetics between vitreous and liquid state. The dielectric spectroscopy exhibits the ac relaxation, near 443 K, which has been associated with the rigid amorphous phase confined by crystallites. This present experiment demonstrates coherence of the dynamics of the PEEK heterogeneous amorphous phase between glassy and liquid state and significantly improve the knowledge of molecular/dynamic structure relationships

Developmental roadmap for antimicrobial susceptibility testing systems

Antimicrobial susceptibility testing (AST) technologies help to accelerate the initiation of targeted antimicrobial therapy for patients with infections and could potentially extend the lifespan of current narrow-spectrum antimicrobials. Although conceptually new and rapid AST technologies have been described, including new phenotyping methods, digital imaging and genomic approaches, there is no single major, or broadly accepted, technological breakthrough that leads the field of rapid AST platform development. This might be owing to several barriers that prevent the timely development and implementation of novel and rapid AST platforms in health-care settings. In this Consensus Statement, we explore such barriers, which include the utility of new methods, the complex process of validating new technology against reference methods beyond the proof-of-concept phase, the legal and regulatory landscapes, costs, the uptake of new tools, reagent stability, optimization of target product profiles, difficulties conducting clinical trials and issues relating to quality and quality control, and present possible solutions

Optimization of flavored drinking yoghurt formula containing date syrup and Bacillus coagulans and evaluation of some physicochemical characteristics and its overall acceptability

BACKGROUND: Today, some countries have focused on dairy-based drinks at the schedule of dairy's production, to solve the problem of high consumption drinks and low intake of dairy. The purpose of this study is producing of flavored drinking yoghurt containing date syrup, In order to remove sugar; and also using Bacillus coagulans to improve the health of product. Methods: In this study, we prepared 5 and 10% of date syrup as a natural sweetener, 0.5 and 1% pectin as a stabilizer; then 109 cfu / ml of Bacillus coagulans (as probiotics) was added. After making healthy and cooling, the samples were packaged in suitable sterile containers. Then some physicochemical properties and general acceptance of this production were investigated during 31 days at low temperature. Findings: The results showed that by increasing the amount of stabilizer (pectin), the sedimentation rate was decreased (from 18.52±0.04% to 11.61±0.09%) and the apparent viscosity was increased (from 105.23 ±0.07 cP to 179.00±0.06 cP), and the apparent viscosity was increased, significantly (p<0.05). The highest overall acceptance (3.67±0.49), compared to other samples, was related to the sample of 10% date syrup and 1% pectin. Conclusion: Drinking yoghurt containing 10% pectin date syrup and 1% has higher score of physicochemical properties and overall acceptability than other received samples; so this product can be introduced as a probiotic dairy and nutritious drin

Towards a Conceptual Model for Enhancing Reasoning about Clinical Guidelines: A case-study on Comorbidity

Computer-Interpretable Guidelines (CIGs) are representations of Clinical Guidelines (CGs) in computer interpretable languages. CIGs have been pointed as an alternative to deal with the various limitations of paper based CGs to support healthcare activities. Although the improvements offered by existing CIG languages, the complexity of the medical domain requires advanced features in order to reuse, share, update, combine or personalize their contents. We propose a conceptual model for representing the content of CGs as a result from an iterative approach that take into account the content of real CGs, CIGs languages and foundational ontologies in order to enhance the reasoning capabilities required to address CIG use-cases. In particular, we apply our approach to the comorbidity use-case and illustrate the model with a realistic case study (Duodenal Ulcer and Transient Ischemic Attack) and compare the results against an existing approach