Water Uptake in Brown Rice during Soaking for Production of No-cooking Rice

Water uptake behavior of brown rice during soaking as a part of the process of producing ‘Komal Chawal’, a kind of no cooking rice tradition to the population in the State of Assam, India, is modelled to Fick’s diffusion equation. Grain swelling resulting from water uptake is accounted by the moving boundary formulation. The model is applied to hydration data of brown rice at soaking temperatures of 40 – 65oC, with saturation moisture content estimated from experimental hydration data. Dependence of effective diffusivity on temperature and moisture content is expressed as a factor estimated from enthalpy-entropy compensation of moisture sorption behavior. Model fitting yielded values of effective diffusivity in a range 2.48 x 10-11 – 1.21 x 10-10 m2/s. Calibrated model could predict the evolution of moisture with soaking time, as validated by comparing with experimental data, enabling the prediction of end of soaking period to reach the desired moisture

Development of ANN-based sorption isotherm algorithm for the prediction of EMC of the paddy

A sorption isotherm algorithm based on artificial neural network (ANN) was developed for the prediction of equilibrium moisture content (EMC) of paddy under low temperature conditions (20 to 400C). ANN architecture was modeled by considering water activity (aw) and temperature (T) as input and EMC as output neurons. A sorption isotherm experiment under low temperature conditions viz. 20, 25, 30 and 35oC was conducted for providing training, testing and validation data of ANN. 2-7-1 was selected as the best ANN architecture on the basis of which sorption isotherm algorithm was developed in MATLAB R2015a. Mathematical modeling was also performed for the analysis of sorption isotherm behavior. Among four models as applied for the analysis, modified Chung-Pfost model showed best results with coefficient of determination (R2) value of 0.98 and mean square error (MSE) value of 8.82X10-05. Hence, this study involves a pioneering approach in the post harvest modeling aspect of sorption isotherm study of paddy

Estimation of drying rate constant from static bed moisture profile by neural network inversion

This study aims at extracting a mathematical expression for describing the moisture loss kinetics from grains dried in the form of a static bed, based on a measured grain moisture profile across the bed, and validating its reliability in predicting the drying times.  The target expression for moisture transfer is the Lewis equation with Arrhenius type dependence of the drying rate constant on temperature, thereby reducing the problem to the determination of two coefficients (i.e., Ea and K0) for the drying rate constant.  The scheme of numerical solution of the non-equilibrium model of the deep bed drying process is represented as a trained neural network, with the values of the coefficients as inputs and the sum squared error (SSE) in the prediction of moisture content at various bed depths as the output.  Training data for the neural network were generated for static bed drying of barley at an airflow rate of 638 kg/m2·h.  The two coefficients were estimated by inversion of the trained neural network.  The derived expression for drying rate constant was found to give a better prediction of the drying time and drying air temperature profiles at different experimental runs with air flow rates close to 638 kg/m2·h.  It underlines the fact that grain moisture loss kinetics, extracted from a known moisture profile across the static bed can reliably be used to predict the batch drying time.   Keywords: static bed drying, non-equilibrium model, drying rate constant, bed moisture profile, neural network inversion, sum squared erro

MEF2C-MYOCD and Leiomodin1 Suppression by miRNA-214 Promotes Smooth Muscle Cell Phenotype Switching in Pulmonary Arterial Hypertension.

BACKGROUND: Vascular hyperproliferative disorders are characterized by excessive smooth muscle cell (SMC) proliferation leading to vessel remodeling and occlusion. In pulmonary arterial hypertension (PAH), SMC phenotype switching from a terminally differentiated contractile to synthetic state is gaining traction as our understanding of the disease progression improves. While maintenance of SMC contractile phenotype is reportedly orchestrated by a MEF2C-myocardin (MYOCD) interplay, little is known regarding molecular control at this nexus. Moreover, the burgeoning interest in microRNAs (miRs) provides the basis for exploring their modulation of MEF2C-MYOCD signaling, and in turn, a pro-proliferative, synthetic SMC phenotype. We hypothesized that suppression of SMC contractile phenotype in pulmonary hypertension is mediated by miR-214 via repression of the MEF2C-MYOCD-leiomodin1 (LMOD1) signaling axis. METHODS AND RESULTS: In SMCs isolated from a PAH patient cohort and commercially obtained hPASMCs exposed to hypoxia, miR-214 expression was monitored by qRT-PCR. miR-214 was upregulated in PAH- vs. control subject hPASMCs as well as in commercially obtained hPASMCs exposed to hypoxia. These increases in miR-214 were paralleled by MEF2C, MYOCD and SMC contractile protein downregulation. Of these, LMOD1 and MEF2C were directly targeted by the miR. Mir-214 overexpression mimicked the PAH profile, downregulating MEF2C and LMOD1. AntagomiR-214 abrogated hypoxia-induced suppression of the contractile phenotype and its attendant proliferation. Anti-miR-214 also restored PAH-PASMCs to a contractile phenotype seen during vascular homeostasis. CONCLUSIONS: Our findings illustrate a key role for miR-214 in modulation of MEF2C-MYOCD-LMOD1 signaling and suggest that an antagonist of miR-214 could mitigate SMC phenotype changes and proliferation in vascular hyperproliferative disorders including PAH

Discovery of Diverse Small Molecule Chemotypes with Cell-Based PKD1 Inhibitory Activity

Protein kinase D (PKD) is a novel family of serine/threonine kinases regulated by diacylglycerol, which is involved in multiple cellular processes and various pathological conditions. The limited number of cell-active, selective inhibitors has historically restricted biochemical and pharmacological studies of PKD. We now markedly expand the PKD1 inhibitory chemotype inventory with eleven additional novel small molecule PKD1 inhibitors derived from our high throughput screening campaigns. The in vitro IC50s for these eleven compounds ranged in potency from 0.4 to 6.1 µM with all of the evaluated compounds being competitive with ATP. Three of the inhibitors (CID 1893668, (1Z)-1-(3-ethyl-5-methoxy-1,3-benzothiazol-2-ylidene)propan-2-one; CID 2011756, 5-(3-chlorophenyl)-N-[4-(morpholin-4-ylmethyl)phenyl]furan-2-carboxamide; CID 5389142, (6Z)-6-[4-(3-aminopropylamino)-6-methyl-1H-pyrimidin-2-ylidene]cyclohexa-2,4-dien-1-one) inhibited phorbol ester-induced endogenous PKD1 activation in LNCaP prostate cancer cells in a concentration-dependent manner. The specificity of these compounds for PKD1 inhibitory activity was supported by kinase assay counter screens as well as by bioinformatics searches. Moreover, computational analyses of these novel cell-active PKD1 inhibitors indicated that they were structurally distinct from the previously described cell-active PKD1 inhibitors while computational docking of the new cell-active compounds in a highly conserved ATP-binding cleft suggests opportunities for structural modification. In summary, we have discovered novel PKD1 inhibitors with in vitro and cell-based inhibitory activity, thus successfully expanding the structural diversity of small molecule inhibitors available for this important pharmacological target

Green process innovation: Where we are and where we are going

Environmental pollution has worsened in the past few decades, and increasing pressure is being put on firms by different regulatory bodies, customer groups, NGOs and other media outlets to adopt green process innovations (GPcIs), which include clean technologies and end-of-pipe solutions. Although considerable studies have been published on GPcI, the literature is disjointed, and as such, a comprehensive understanding of the issues, challenges and gaps is lacking. A systematic literature review (SLR) involving 80 relevant studies was conducted to extract seven themes: strategic response, organisational learning, institutional pressures, structural issues, outcomes, barriers and methodological choices. The review thus highlights the various gaps in the GPcI literature and illuminates the pathways for future research by proposing a series of potential research questions. This study is of vital importance to business strategy as it provides a comprehensive framework to help firms understand the various contours of GPcI. Likewise, policymakers can use the findings of this study to fill in the loopholes in the existing regulations that firms are exploiting to circumvent taxes and other penalties by locating their operations to emerging economies with less stringent environmental regulations.publishedVersio