Hospital service levels during drug shortages: Stocking and transshipment policies for pharmaceutical inventory

Journal of Global Optimization - In this study, we consider a health network that faces uncertain supply disruptions in the form of regional, nationwide, or worldwide drug shortages. Each hospital...     

Molecular dynamics simulation study of the structural features and inclusion capacities of cucurbit[6]uril derivatives in aqueous solutions

Molecular dynamics (MD) simulations were performed for cucurbit[6]uril (CB6) methyl and cyclohexyl derivatives in aqueous solutions. Furthermore, MD simulations have been conducted to study the inclusion complexes between each CB6 derivative with α,ω-pentane diammonium ion (NH₃⁺(CH₂)₅NH₃⁺) to estimate the binding free energies, the complex geometries and the intermolecular forces responsible for complex formation. Results show a complete inclusion of the guest molecule in the cavity of the host for all complexes. Results also indicate that the guest dynamics inside the cavity of the substituted host is similar to that for the unsubstituted host. This demonstrates that the molecular recognition of the host is not affected by the alkyl substitution at the equator. Also, there is an insignificant conformational change of the macrocyclic structure upon inclusion of the guest. Molecular mechanics/Poisson Boltzmann surface area method was used to estimate the binding free energy of each complex. Results indicate that host–guest electrostatic interactions make the largest contribution to the complex binding free energy. Moreover, van der Waals interactions add significantly to the complex stability. The guest molecules show more or less similar binding free energies with the substituted CB6 that exhibits slightly more negative values than unsubstituted CB6 which is proved also by umbrella sampling.     

Raman spectroscopy and support vector machines for quick toxicological evaluation of titania nanoparticles

With the rapid development of nanotechnology products, there is a significant concern on the adverse effects that might be associated with them. Traditional biological assays are typically used to asses the toxicity in vitro. There are, however, questions regarding the suitability of these assays for this purpose, mainly due to the potential interaction of the particles with the utilized dyes. In addition, this process can be costly and time consuming, as a large number of different assays have to be used. To address some of these issues, Raman spectroscopy is used in this study to investigate the particle‐cell interactions. The spectrum of a living cell is a very complex and rich collection of data directly related to its chemical composition. To enhance the data resolution and make the detection of toxicity more robust, data‐mining techniques have been deployed. Furthermore, data‐mining techniques enable full automation of the entire process, minimizing user input. The Raman spectroscopy successfully evaluated the toxicity of TiO₂ nanoparticles by both the peak‐by‐peak analysis and with the implementation of support vector machines. The particles were found to display cytotoxicity after 36 h of exposure. The results were confirmed by MTT (3‐(4,5‐Dimethylthiazol‐2‐Yl)‐2,5‐Diphenyltetrazolium Bromide) assay and are in agreement with the existing literature on the subject. Overall, Raman spectroscopy appears to be among the very few techniques that exhibit low levels of interferences (obscuration, fluorescence, emission, etc.) from the particle addition. Since it does not rely on biomarkers, it can be used in situ for an extended period with minimal effects on the cellular biochemistry. Copyright © 2011 John Wiley & Sons, Ltd.     

Robust support vector machines for multiple instance learning

This paper presents the multiple instance classification problem that can be used for drug and molecular activity prediction, text categorization, image annotation, and object recognition. In order to model a more robust representation of outliers, hard margin loss formulations that minimize the number of misclassified instances are proposed. Although the problem is $\mathcal{NP}$ -hard, computational studies show that medium sized problems can be solved to optimality in reasonable time using integer programming and constraint programming formulations. A three-phase heuristic algorithm is proposed for larger problems. Furthermore, different loss functions such as hinge loss, ramp loss, and hard margin loss are empirically compared in the context of multiple instance classification. The proposed heuristic and robust support vector machines with hard margin loss demonstrate superior generalization performance compared to other approaches for multiple instance learning.     

Adsorption of basic dyes from aqueous solution onto pumice powder

The adsorption of methylene blue and crystal violet on pumice powder samples of varying compositions was investigated using a batch adsorption technique. The effects of various experimental parameters, such as adsorbent dosage, initial dye concentration, and contact time, were also investigated. The extent of dye removal increased with decreased initial concentration of the dye and also increased with increased contact time and amount of adsorbent used. Adsorption data were modeled using the Freundlich adsorption isotherm. The adsorption kinetic of methylene blue and crystal violet could be described by the pseudo-second-order reaction model.     

An EOQ model with deteriorating items and self-selection constraints

Optimization Letters - In this paper, we consider a store that sells two vertically differentiated items that might substitute each other. These items do not only differ in quality and price, but...