Constructing optimum blood brain barrier QSAR models using a combination of 4D-molecular similarity measures and cluster analysis

A new method, using a combination of 4D-molecular similarity measures and cluster analysis to construct optimum QSAR models, is applied to a data set of 150 chemically diverse compounds to build optimum blood-brain barrier (BBB) penetration models. The complete data set is divided into subsets based on 4D-molecular similarity measures using cluster analysis. The compounds in each cluster subset are further divided into a training set and a test set. Predictive QASAR models are constructed for each cluster subset using the corresponding training sets. These QSAR models best predict test set compounds which are assigned to the same cluster subset, based on the 4D-molecular similarity measures, from which the models are derived. The results suggest that the specific properties governing blood-brain barrier permeability may vary across chemically diverse compounds. Partitioning compounds into chemically similar classes is essential to constructing predictive blood-brain barrier penetration models embedding the corresponding key physiochemical properties of a given chemical class.     

Complexities and algorithms for synchronized scheduling of parallel machine assembly and air transportation in consumer electronics supply chain

In this paper, we study the problem of synchronized scheduling of assembly and air transportation to achieve accurate delivery with minimized cost in consumer electronics supply chain. This problem was motivated by a major PC manufacturer in consumer electronics industry. The overall problem is decomposed into two sub-problems, which consist of an air transportation allocation problem and an assembly scheduling problem. The air transportation allocation problem is formulated as an integer linear programming problem with the objective of minimizing transportation cost and delivery earliness tardiness penalties. The assembly scheduling problem seeks to determine a schedule ensuring that the orders are completed on time and catch the flights such that the waiting penalties between assembly and transportation is minimized. The problem is formulated as a parallel machine scheduling problem with earliness penalties. The computational complexities of the two sub-problems are investigated. The air transportation allocation problem with split delivery is shown to be solvable. The parallel machine assembly scheduling problem is shown to be NP-complete. Simulated annealing based heuristic algorithms are presented to solve the parallel machine problem.     

Hyaluronan-based glycoclusters as probes for chemical glycobiology

A strategy is described for the synthesis of β-(1,3)-GlcA-GlcNAc dimeric and tetrameric glycoclusters through the conjugation of disaccharide groups onto a diaminodiamide aromatic scaffold by reductive amination.     

Sustainable routes to amines in recyclable water using ppm Pd catalysis

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Spirulina-based composites for 3D-printing

With material consumption increasing, the need for biodegradable materials derived from renewable resources becomes urgent, particularly in the popular field of 3D-printing. Processed natural fibers have been used as fillers for 3D-printing filaments and slurries, yet reports of utilizing pure biomass to 3D-print structures that reach mechanical properties comparable to synthetic plastics are scarce. Here, we develop and characterize slurries for extrusion-based 3D-printing comprised of unprocessed spirulina and varying amounts of cellulose fibers (CFs). Tuning the micro-morphology, density, and mechanical properties of multilayered structures is achieved by modulating the CF amount or drying method. Densified morphologies are obtained upon desiccator-drying, while oven incubation plasticizes the matrix and leads to intermediate densities. Freeze-drying creates low-density foam microstructures. The compressive strengths of the structures follow the same trend as their density. CFs are critical in the denser structures, as without the fibers, the samples do not retain their shape while drying. The compressive strength and strain to failure of the composites progressively increase with increasing filler content, ranging between 0.8 and 16 MPa and 12%–47%, respectively, at densities of 0.51–1.00 g/cm³. The measured properties are comparable to other biobased composites and commercial plastic filaments for 3D-printing.     

A stochastic Lagrangian proof of global existence of the Navier–Stokes equations for flows with small Reynolds number

We consider the incompressible Navier–Stokes equations with spatially periodic boundary conditions. If the Reynolds number is small enough we provide an elementary short proof of the existence of global in time Hölder continuous solutions. Our proof uses a stochastic representation formula to obtain a decay estimate for heat flows in Hölder spaces, and a stochastic Lagrangian formulation of the Navier–Stokes equations.     

Monaural speech segregation using synthetic speech signals

When listening to natural speech, listeners are fairly adept at using cues such as pitch, vocal tract length, prosody, and level differences to extract a target speech signal from an interfering speech masker. However, little is known about the cues that listeners might use to segregate synthetic speech signals that retain the intelligibility characteristics of speech but lack many of the features that listeners normally use to segregate competing talkers. In this experiment, intelligibility was measured in a diotic listening task that required the segregation of two simultaneously presented synthetic sentences. Three types of synthetic signals were created: (1) sine-wave speech (SWS); (2) modulated noise-band speech (MNB); and (3) modulated sine-band speech (MSB). The listeners performed worse for all three types of synthetic signals than they did with natural speech signals, particularly at low signal-to-noise ratio (SNR) values. Of the three synthetic signals, the results indicate that SWS signals preserve more of the voice characteristics used for speech segregation than MNB and MSB signals. These findings have implications for cochlear implant users, who rely on signals very similar to MNB speech and thus are likely to have difficulty understanding speech in cocktail-party listening environments.     

Two dimensional electrophoretic analysis of human tears: collection method in dry eye syndrome

Tear proteomics, by 2-DE, can give a fingerprint of the protein profile, which is well suited in clinical proteomics for biomarker identification and in diagnostics. The mode of tear collection can influence the representation of the proteins in the tear and therefore it is important to use the appropriate method. In this study, capillary and Schirmer mode of tear collection was done in the healthy controls and the Schirmer method was validated in dry eye syndrome conditions. 2-D PAGE of normal and dry eye tear was performed using pH 3-10 linear IPG strips followed by 13% SDS-PAGE. The spot intensity was analyzed by the PD quest software. The two methods were compared using Bland-Altman statistical tool. The 2-D map of capillary and Schirmer tear showed 147 ± 8 spots and 145 ± 7 spots respectively. Both the collection methods were in agreement with each other and were comparable. Dry eye tear protein showed differential expression of proteins as observed in 25-35 kDa region. One of the significantly reduced protein was identified as proline-rich 4 protein. Schirmer method of tear collection is reliable in patients with dry eye, which can display the differential protein expression and help in biomarker identification.