Drug/nondrug classification using Support Vector Machines with various feature selection strategies

In conjunction with the advance in computer technology, virtual screening of small molecules has been started to use in drug discovery. Since there are thousands of compounds in early-phase of drug discovery, a fast classification method, which can distinguish between active and inactive molecules, can be used for screening large compound collections. In this study, we used Support Vector Machines (SVM) for this type of classification task. SVM is a powerful classification tool that is becoming increasingly popular in various machine-learning applications. The data sets consist of 631 compounds for training set and 216 compounds for a separate test set. In data pre-processing step, the Pearson's correlation coefficient used as a filter to eliminate redundant features. After application of the correlation filter, a single SVM has been applied to this reduced data set. Moreover, we have investigated the performance of SVM with different feature selection strategies, including SVM–Recursive Feature Elimination, Wrapper Method and Subset Selection. All feature selection methods generally represent better performance than a single SVM while Subset Selection outperforms other feature selection methods. We have tested SVM as a classification tool in a real-life drug discovery problem and our results revealed that it could be a useful method for classification task in early-phase of drug discovery.     

Do tests of divergent thinking have an experiential bias?

Divergent thinking (DT) tests are widely used as an estimate of creativity. However, tests of DT may be biased by experience. Scores from these tests may depend on the amount and types of experiences of examinees. This investigation was designed to determine the degree to which personal and social experiences influence DT scores. Two different tasks were administered: Uses task and Problem Generation (PG). Fluency and originality scores were calculated for each. Analyses indicated that the impact of experience was similar in the PG and Uses tasks. Personal and social experience explained 44% and 30% of fluency scores for PG and Uses tasks, respectively, and 65% of originality scores for both PG and Uses. The differences between uncorrected scores (all ideas, including those reflecting experience) and corrected scores (where ideas tied to personal or social experiences were eliminated) were statistically significant, with the largest discrepancy in Uses fluency and lowest in Uses originality. Findings supported the claim that divergent thinking tests may depend heavily on experience. Alternatives for using DT tests without an experiential bias are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A mathematical approach for integrating the cell design and production planning decisions

A mixed integer programming model that selects cells that can handle demand variability is presented. Valid inequalities are added to the linear programming relaxation of the model. By adding these valid inequalities, the lower bound on the model's optimal objective function value is significantly improved. An efficient heuristic procedure that generates good solutions to this model is also presented.     

Object and Combination Shedding Schemes for Adaptive Media Workflow Execution

Complex media fusion operations can be costly in terms of the time they need to process input objects. If data arrive faster to fusion nodes than the speed with which they can consume the inputs, this will result in some input objects not being processed. In this paper, we develop load shedding mechanisms which take into consideration both data quality and expensive nature of media fusion operators. In particular, we present quality assessment models for objects and multistream fusion operators and highlight that such quality assessments may impose partial orders on objects. We highlight that the most effective load control approach for fusion operators involves shedding of (not the individual input objects but) combinations of objects. Yet, identifying suitable combinations of objects in real time will not be possible if efficient combination selection algorithms do not exist. We develop efficient combination selection schemes for scenarios with different quality assessment and target characteristics. We first develop efficient combination-based load shedding when the fusion operator has unambiguously monotone semantics. We then extend this to the more general ambiguously monotone case and present experimental results that show the performance gains using quality-aware combination-based load shedding strategies under the various fusion scenarios.     

High performance chromium (VI) removal from water by polyacrylonitrile‐co‐poly (2‐ethyl hexylacrylate) and polyaniline nanoporous membranes

This article reports the chromium (VI) removal from water by preparing polyacrylonitrile‐co‐poly (2‐ethyl hexylacrylate) (PAN(92)‐co‐P2EHA(8)) and polyaniline (PANI) nanoporous membranes at various PANI loadings. It was observed that chromium (VI) rejections of nanoporous membranes are highly concentration and pH dependent. Almost complete chromium removal (99.9%) with higher flux values (120–177 L m^?2 h^?1) was observed for nanoporous membranes. Moreover, nanoporous membranes were also demonstrated as fouling resistant. Total flux loss was low and a part was attributed to reversible flux loss, which cannot cause any permanent hysteresis and easily overcome with simple washing. Scanning electron microscopy (SEM) studies were performed for identifying cross sectional morphology. It was pointed out that pore size should be small enough for filtration and optimized for higher flux but pores should be functionalized for rejection. Chemical structure, swelling ratios, sheet resistivity, and fracture morphologies of nanoporous membranes were reported. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Assessment of permeability and injection depth at the Atasu dam site (Turkey) based on experimental and numerical analyses

This study was performed in order to evaluate the permeability of the basalts and pyroclastics and the maximum depth of grout injection at the Atasu dam site, Turkey, using the equations of Kiraly and Hoek and Bray based on values obtained from Lugeon tests. In order to evaluate maximum discharge values and depth of injection, seepage analyses were performed using the finite element technique for each 10 m up to 100 m. The results indicate that to establish an impermeable zone at the dam site, the depth of injection should be taken as 50 m for the left and right slopes and 40 m for the river bed.     

Process and formulation variables of pregabalin microspheres prepared by w/o/o double emulsion solvent diffusion method and their clinical application by animal modeling studies

Pregabalin is an anticonvulsant drug used for neuropathic pain and as an adjunct therapy for partial seizures with or without secondary generalization in adults. In conventional therapy recommended dose for pregabalin is 75?mg twice daily or 50?mg three times a day, with maximum dosage of 600?mg/d. To achieve maximum therapeutic effect with a low risk of adverse effects and to reduce often drug dosing, modified release preparations; such as microspheres might be helpful. However, most of the microencapsulation techniques have been used for lipophilic drugs, since hydrophilic drugs like pregabalin, showed low-loading efficiency and rapid dissolution of compounds into the aqueous continous phase. The purpose of this study was to improve loading efficiency of a water-soluble drug and modulate release profiles, and to test the efficiency of the prepared microspheres with the help of animal modeling studies. Pregabalin is a water soluble drug, and it was encapsulated within anionic acrylic resin (Eudragit S 100) microspheres by water in oil in oil (w/o/o) double emulsion solvent diffusion method. Dichloromethane and corn oil were chosen primary and secondary oil phases, respectively. The presence of internal water phase was necessary to form stable emulsion droplets and it accelerated the hardening of microspheres. Tween 80 and Span 80 were used as surfactants to stabilize the water and corn oil phases, respectively. The optimum concentration of Tween 80 was 0.25% (v/v) and Span 80 was 0.02% (v/v). The volume of the continous phase was affected the size of the microspheres. As the volume of the continous phase increased, the size of microspheres decreased. All microsphere formulations were evaluated with the help of in vitro characterization parameters. Microsphere formulations (P1–P5) exhibited entrapment efficiency ranged between 57.00?±?0.72 and 69.70?±?0.49%; yield ranged between 80.95?±?1.21 and 93.05?±?1.42%; and mean particle size were between 136.09?±?2.57 and 279.09?±?1.97?µm. Pregabalin microspheres having better results among all formulations (Table 3) were chosen for further studies such as differential scanning calorimetry, Fourier transform infrared analysis and dissolution studies. In the last step, the best pregabalin microsphere formulation (P3) was chosen for in vivo animal studies. The pregabalin-loaded microspheres (P3) and conventional pregabalin capsules were applied orally in rats for three days, resulted in clinical improvement of cold allodynia, an indicator of peripheral neuropathy. This result when evaluated together with the serum pregabalin levels and in vitro release studies suggests that the pregabalin microspheres prepared with w/o/o double emulsion solvent diffusion method can be an alternative form for neuropathic pain therapy. Conclusively, a drug delivery system successfully developed that showed modified release up to 10?h and could be potentially useful to overcome the frequent dosing problems associated with pregabalin conventional dosage form.     

Comparison of surface roughness of Locust acacia (Robinia pseudoacacia L.) and European oak (Quercus petraea (Mattu.) Lieble.) in terms of the preparative process by planing

Effects of number of the cutters (planing knives), feed rate (operational speed) and cutting depth (biting thickness) on the surface roughness of Locust acacia (Robinia pseudoacacia L.) and European oak (Quercus petraea (Mattu.) Lieble.) were investigated on the base of the preparative differences by planing. The specimens were prepared by planing with two and four knives at 5 and 9 m/min feed rates in 1, 2 and 4 mm cutting depths. Surface roughness was measured from the radial face of each sample according to TS 930 (1989) by using Mitutoyo SJ-301 stylus scanner device. These measurements were performed perpendicular to the fibers by the sampling length of 12.5 mm at a sensitivity level of ±0.01 μm. Considering between all types of the experimental preparations, Locust acacia had the smoothest surfaces than that of European oak. Comparing the results of the surface roughness of both species, it has been obtained that the surface roughness decreases when the feed rate and the cutting depth decreases, whereas it increases when the knives on the cutter heads decreases. Therefore, it may be suggested that the perfect faces could be particularly prepared for this considered species by the greater number of the knives (four) at the slow feed rate (5 m/min) in the condition of the light cutting depth (1 mm).     

Simulating colliding flows in smoothed particle hydrodynamics with fractional derivatives

We propose a new method based on the use of fractional differentiation for improving the efficiency and realism of simulations based on smoothed particle hydrodynamics (SPH). SPH represents a popular particle‐based approach for fluid simulation and a high number of particles is typically needed for achieving high quality results. However, as the number of simulated particles increase, the speed of computation degrades accordingly. The proposed method employs fractional differentiation to improve the results obtained with SPH in a given resolution. The approach is based on the observation that effects requiring a high number of particles are most often produced from colliding flows, and therefore, when the modeling of this behavior is improved, higher quality results can be achieved without changing the number of particles being simulated. Our method can be employed to reduce the resolution without significant loss of quality, or to improve the quality of the simulation in the current chosen resolution. The advantages of our method are demonstrated with several quantitative evaluations. Copyright © 2013 John Wiley & Sons, Ltd.     

Recent Developments in Friction Stir Welding of Al-alloys

The diversity and never-ending desire for a better life standard result in a continuous development of the existing manufacturing technologies. In line with these developments in the existing production technologies the demand for more complex products increases, which also stimulates new approaches in production routes of such products, e.g., novel welding procedures. For instance, the friction stir welding (FSW) technology, developed for joining difficult-to-weld Al-alloys, has been implemented by industry in manufacturing of several products. There are also numerous attempts to apply this method to other materials beyond Al-alloys. However, the process has not yet been implemented by industry for joining these materials with the exception of some limited applications. The microstructures and mechanical properties of friction stir welded Al-alloys existing in the open literature will be discussed in detail in this review. The correlations between weld parameters used during FSW and the microstructures evolved in the weld region and thus mechanical properties of the joints produced will be highlighted. However, the modeling studies, material flow, texture formation and developments in tool design are out of the scope of this work as well as the other variants of this technology, such as friction stir spot welding (FSSW).