Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Periodo de centrifugacao adequado para levantamento da curva de retencao da agua em solos do bioma cerrado.

O periodo de centrifugacao, necessario ao equilibrio da agua no solo, e fator preponderante da precisao da curva de retencao de agua. O estudo foi desenvovido com o objetivo de avaliar o periodo de centrifugacao na curva de retencao de agua, em cinco tipos de solo, representativos do Bioma Cerrado. as curvas de rtencao foram modeladas, por regressao não-linear, e a soma dos erros residuais do ajuste resultante foi utilizada para avaliação das diferencas estatisticas entre elas, pelo teste da razao de verossimilhanca. As curvas de retencao ajustadas para cada tipo de solo foram agrupadas em familias de curvas para facilitar a visualizacao das diferencas observadas. Os resultados mostraram claramente, que o periodo de centrifugacao afetou mais a umidade residual, promovendo uma nitida rotacao nas curvas, em torno do ponto de saturacao. Esse efeito estabeleceu um padrao de erro na agua disponivel, sistematicamente decrescente, com o aumento do periodo de centrifugacao. Utilizando-se da tecnica da regressao inversa foi possível estabelcer o periodo de centrifugacao necessario para cada tipo de solo correspondente ao nível de significancia de 5% e no intervalo de confianca de 90%. Com estudo, conclui-se que o periodo de centrifugacao inferior ao equilibrio altera a curva de retencao determinada por esse procedimento, afetando, principalmente, os valores de umidade nas tensoes mais elevadas. Para os solos estudados, o periodo de centrifugacao necessario a extracao de agua, em cada rotacao aplicada, pelo metodo tradicional da centrifuga, deve ser superior a 80 minutos.

The impact of talent management practices on employee retention: The moderator effect of leader-member exchange and role modeling

Organizations are undergoing serious difficulties to retain talent. Authors argue that Talent Management (TM) practices create beneficial outcomes for individuals and organizations. However, there is no research on the leaders’ role in the functioning of these practices. This study examines how LMX and role modeling influence the impact that TM practices have on employees’ trust in their organizations and retention. The analysis of two questionnaires (Nt1=175; Nt2=107) indicated that TM only reduced turnover intentions, via an increase in trust in the organization, when role modeling was high and not when it was low. Therefore, we can say that leaders are crucial in the TM context, and in sustaining a competitive advantage for organizations.

Peak modeling approach to accurate assignment of first-dimension retention times in comprehensive two-dimensional chromatography

Modeling of first-dimension retention of peaks based on modulation phase and period allows reliable prediction of the modulated peak distributions generated in the comprehensive two-dimensional chromatography experiment. By application of the inverse process, it is also possible to use the profile of the modulated peaks (their heights or areas) to predict the shape and parameters of the original input chromatographic band (retention time, standard deviation, area) for the primary column dimension. This allows an accurate derivation of the firstdimension retention time (RSD 0.02%) which is equal to that for the non-modulated experiment, rather than relying upon the retention time of the major modulated peak generated by the modulation process (RSD 0.16%). The latter metric can produce a retention time that differs by at least the modulation period employed in the experiment, which displays a discontinuity in the retention time vs modulation phase plot at the point of the 180° out-ofphase modulation. In contrast, the new procedure proposed here gives a result that is essentially independent of modulation phase and period. This permits an accurate value to be assigned to the first-dimension retention. The proposed metric accounts for the time on the seconddimension, the phase of the distribution, and the holdup time that the sampled solute is retained in the modulating interface. The approach may also be based on the largest three modulated peaks, rather than all modulated peaks. This simplifies the task of assigning the retention time with little loss of precision in band standard deviation or retention time, provided that these peaks are not all overloaded in the first or second dimension.

Modeling the co-transport of viruses and colloids in unsaturated porous media

A mathematical model is developed to simulate the co-transport of viruses and colloids in unsaturated porous media under steady-state flow conditions. The virus attachment to the mobile and immobile colloids is described using a linear reversible kinetic model. Colloid transport is assumed to be decoupled from virus transport; that is, we assume that colloids are not affected by the presence of attached viruses on their surface. The governing equations,are solved numerically using an alternating three-step operator splitting approach. The model is verified by fitting three sets of experimental data published in the literature: (1) Syngouna and Chrysikopoulos (2013) and (2) Walshe et al. (2010), both on the co-transport of viruses and clay colloids under saturated conditions, and (3) Syngouna and Cluysikopoulos (2015) for the co-transport of viruses and clay colloids under unsaturated conditions. We found a good agreement between observed and fitted breakthrough curves (BTCs) under both saturated and unsaturated conditions. Then, the developed model was used to simulate the co-transport of viruses and colloids in porous media under unsaturated conditions, with the aim of understanding the relative importance of various processes on the co-transport of viruses and colloids in unsaturated porous media. The virus retention in porous media in the presence of colloids is greater during unsaturated conditions as compared to the saturated conditions due to: (1) virus attachment to the air-water interface (AWI), and (2) co-deposition of colloids with attached viruses on its surface to the AWL A sensitivity analysis of the model to various parameters showed that the virus attachment to AWI is the most sensitive parameter affecting the BTCs of both free viruses and total mobile viruses and has a significant effect on all parts of the BTC. The free and the total mobile viruses BTCs are mainly influenced by parameters describing virus attachment to the AIM, virus interaction with mobile and immobile colloids, virus attachment to solid-water interface (SWI), and colloid interaction with SWI and AWL The virus BTC is relatively insensitive to parameters describing the maximum adsorption capacity of the AWI for colloids, inlet colloid concentration, virus detachment rate coefficient from the SW!, maximum adsorption capacity of the AWI for viruses and inlet virus concentration. (C) 2015 Elsevier B.V. All rights reserved.

Modeling and optimization for separation of ionic solutes in pressurized flow capillary electrochromatography

By manipulation of applied pressure or voltage, pressurized flow capillary electrochromatography (P-CEC) permits unique control of selectivity for ionic solutes. A simple mathematical model has been developed to describe the quantitative relationship between the electrochromatographic retention factor (k(*)) of charged solutes and the applied voltage and pressure. The validity of the model was verified experimentally with hydrophilic interaction mode CEC (HI-CEC). On the basis of the model developed, it was found that the value of k(*) could be predicted accurately using only a limited number of data points from the initial experiments at different voltages or pressures. Correlation between the experimentally measured and calculated k(*) was excellent, with a correlation coefficient greater than 0.999. Optimization for the separation of peptides by P-CEC was also performed successfully on the basis of the proposed model.

Concrete damage plasticity model for modeling FRP-to-concrete bond behavior

The technique of externally bonding fiber-reinforced polymer (FRP) composites has become very popular worldwide for retrofitting existing reinforced concrete (RC) structures. Debonding of FRP from the concrete substrate is a typical failure mode in such strengthened structures. The bond behavior between FRP and concrete thus plays a crucial role in these structures. The FRP-to-concrete bond behavior has been extensively investigated experimentally, commonly using a single or double shear test of the FRP-to-concrete bonded joint. Comparatively, much less research has been concerned with numerical simulation, chiefly due to difficulties in the accurate modeling of the complex behavior of concrete. This paper presents a simple but robust finite-element (FE) model for simulating the bond behavior in the entire debonding process for the single shear test. A concrete damage plasticity model is proposed to capture the concrete-to-FRP bond behavior. Numerical results are in close agreement with test data, validating the model. In addition to accuracy, the model has two further advantages: it only requires the basic material parameters (i.e., no arbitrary user-defined parameter such as the shear retention factor is required) and it can be directly implemented in the FE software ABAQUS.

Modeling of Suspended Sediment Dynamics in Tropical River Basins

It is proposed to study the suspended sediment transport characteristics of river basins of Kerala and to model suspended sediment discharge mechanism for typical micro-watersheds. The Pamba river basin is selected as a representative hydrologic regime for detailed studies of suspended sediment characteristics and its seasonal variation. The applicability of various erosion models would be tested by comparing with the observed event data (by continuous monitoring of rainfall, discharge, and suspended sediment concentration for lower order streams). Empirical, conceptual and physically distributed models were used for making the comparison of performance of the models. Large variations in the discharge and sediment quantities were noticed during a particular year between the river basins investigated and for an individual river basin during the years for which the data was available. In general, the sediment yield pattern follows the seasonal distribution of rainfall, discharge and physiography of the land. This confirms with similar studies made for other Indian rivers. It was observed from this study, that the quantity of sediment transported downstream shows a decreasing trend over the years corresponding to increase in discharge. For sound and sustainable management of coastal zones, it is important to understand the balance between erosion and retention and to quantify the exact amount of the sediments reaching this eco-system. This, of course, necessitates a good length of time series data and more focused research on the behaviour of each river system, both present and past. In this realm of river inputs to ocean system, each of the 41 rivers of Kerala may have dominant yet diversified roles to influence the coastal ecosystem as reflected from this study on the major fraction of transport, namely the suspended sediments

Modeling growth strategy in a biotechnology startup firm

The top managers of a biotechnology startup firm agreed to participate in a system dynamics modeling project to help them think about the firm's growth strategy. The article describes how the model was created and used to stimulate debate and discussion about growth management. The paper highlights several novel features about the process used for capturing management team knowledge. A heavy emphasis was placed on mapping the operating structure of the factory and distribution channels. Qualitative modeling methods (structural diagrams, descriptive variable names, and friendly algebra) were used to capture the management team's descriptions of the business. Simulation scenarios were crafted to stimulate debate about strategic issues such as capacity allocation, capacity expansion, customer recruitment, customer retention, and market growth, and to engage the management team in using the computer to design strategic scenarios. The article concludes with comments on the impact of the project.

Modeling plant transpiration under limited soil water: comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models

Accurate estimates of how soil water stress affects plant transpiration are crucial for reliable land surface model (LSM) predictions. Current LSMs generally use a water stress factor, β, dependent on soil moisture content, θ, that ranges linearly between β = 1 for unstressed vegetation and β = 0 when wilting point is reached. This paper explores the feasibility of replacing the current approach with equations that use soil water potential as their independent variable, or with a set of equations that involve hydraulic and chemical signaling, thereby ensuring feedbacks between the entire soil–root–xylem–leaf system. A comparison with the original linear θ-based water stress parameterization, and with its improved curvi-linear version, was conducted. Assessment of model suitability was focused on their ability to simulate the correct (as derived from experimental data) curve shape of relative transpiration versus fraction of transpirable soil water. We used model sensitivity analyses under progressive soil drying conditions, employing two commonly used approaches to calculate water retention and hydraulic conductivity curves. Furthermore, for each of these hydraulic parameterizations we used two different parameter sets, for 3 soil texture types; a total of 12 soil hydraulic permutations. Results showed that the resulting transpiration reduction functions (TRFs) varied considerably among the models. The fact that soil hydraulic conductivity played a major role in the model that involved hydraulic and chemical signaling led to unrealistic values of β, and hence TRF, for many soil hydraulic parameter sets. However, this model is much better equipped to simulate the behavior of different plant species. Based on these findings, we only recommend implementation of this approach into LSMs if great care with choice of soil hydraulic parameters is taken

Managing B2B customer churn, retention and profitability

It is now widely accepted that firms should direct more effort into retaining existing customers than to attracting new ones. To achieve this, customers likely to defect need to be identified so that they can be approached with tailored incentives or other bespoke retention offers. Such strategies call for predictive models capable of identifying customers with higher probabilities of defecting in the relatively near future. A review of the extant literature on customer churn models reveals that although several predictive models have been developed to model churn in B2C contexts, the B2B context in general, and non-contractual settings in particular, have received less attention in this regard. Therefore, to address these gaps, this study proposes a data-mining approach to model non-contractual customer churn in B2B contexts. Several modeling techniques are compared in terms of their ability to predict true churners. The best performing data-mining technique (boosting) is then applied to develop a profit maximizing retention campaign. Results confirm that the model driven approach to churn prediction and developing retention strategies outperforms commonly used managerial heuristics. © 2014 Elsevier Inc.

Mathematical modeling and analysis of the flocculation process in chambers in series

In this study, the flocculation process in continuous systems with chambers in series was analyzed using the classical kinetic model of aggregation and break-up proposed by Argaman and Kaufman, which incorporates two main parameters: K (a) and K (b). Typical values for these parameters were used, i. e., K (a) = 3.68 x 10(-5)-1.83 x 10(-4) and K (b) = 1.83 x 10(-7)-2.30 x 10(-7) s(-1). The analysis consisted of performing simulations of system behavior under different operating conditions, including variations in the number of chambers used and the utilization of fixed or scaled velocity gradients in the units. The response variable analyzed in all simulations was the total retention time necessary to achieve a given flocculation efficiency, which was determined by means of conventional solution methods of nonlinear algebraic equations, corresponding to the material balances on the system. Values for the number of chambers ranging from 1 to 5, velocity gradients of 20-60 s(-1) and flocculation efficiencies of 50-90 % were adopted.

Modeling of continuous thermal processing of a non-Newtonian liquid food under diffusive laminar flow in a tubular system

The classic conservative approach for thermal process design can lead to over-processing, especially for laminar flow, when a significant distribution of temperature and of residence time occurs. In order to optimize quality retention, a more comprehensive model is required. A model comprising differential equations for mass and heat transfer is proposed for the simulation of the continuous thermal processing of a non-Newtonian food in a tubular system. The model takes into account the contribution from heating and cooling sections, the heat exchange with the ambient air and effective diffusion associated with non-ideal laminar flow. The study case of soursop juice processing was used to test the model. Various simulations were performed to evaluate the effect of the model assumptions. An expressive difference in the predicted lethality was observed between the classic approach and the proposed model. The main advantage of the model is its flexibility to represent different aspects with a small computational time, making it suitable for process evaluation and design. (C) 2012 Elsevier Ltd. All rights reserved.

The discovery of new 11beta-hydroxysteroid dehydrogenase type 1 inhibitors by common feature pharmacophore modeling and virtual screening

11beta-Hydroxysteroid dehydrogenase (11beta-HSD) enzymes catalyze the conversion of biologically inactive 11-ketosteroids into their active 11beta-hydroxy derivatives and vice versa. Inhibition of 11beta-HSD1 has considerable therapeutic potential for glucocorticoid-associated diseases including obesity, diabetes, wound healing, and muscle atrophy. Because inhibition of related enzymes such as 11beta-HSD2 and 17beta-HSDs causes sodium retention and hypertension or interferes with sex steroid hormone metabolism, respectively, highly selective 11beta-HSD1 inhibitors are required for successful therapy. Here, we employed the software package Catalyst to develop ligand-based multifeature pharmacophore models for 11beta-HSD1 inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed several selective inhibitors. Efficient inhibition of recombinant human 11beta-HSD1 in intact transfected cells as well as endogenous enzyme in mouse 3T3-L1 adipocytes and C2C12 myotubes was demonstrated for compound 27, which was able to block subsequent cortisol-dependent activation of glucocorticoid receptors with only minor direct effects on the receptor itself. Our results suggest that inhibitor-based pharmacophore models for 11beta-HSD1 in combination with suitable cell-based activity assays, including such for related enzymes, can be used for the identification of selective and potent inhibitors.