Near infrared light-induced disassembly of polymeric micelles based on methylene blue conjugated polyethylene glycol

Light-sensitive drug delivery systems are considered ideal for applications in the biomedical fields for their ability to release the payload in an on-demand spatiotemporal controlled manner through the manipulation of the light source. Among the broad radiation spectrum, near infrared (NIR) light is considered advantageous compared to UV and visible light, due to its inherently lower photodamage to normal tissues and deeper penetration to lesion areas. In this study, we report a successful synthesis of a polymer capable of undergoing partial degradation upon irradiation with NIR light by conjugating 10-N-carbamoyl linkage methylene blue (MB) moiety, a NIR photocleavable ligand, with polyethylene glycol (PEG). Through effective coupling of MB, a hydrophobic moiety, to the hydrophilic PEG molecule, an amphiphilic polymer was synthesized, as demonstrated by a lowered surface tension (55 mN/m at 0.1% wt/vol). Subsequently, photo-induced reversal of surface activity associated with self-assembled structure disruption, was displayed by surface tension measurements, size distribution analysis, and burst release profile of paclitaxel (PTX) from polymeric micelles upon the exposure to NIR irradiation.     

Biodegradability and improved mechanical performance of polyhydroxyalkanoates/agave fiber biocomposites compatibilized by different strategies

In this work, biocomposites made of polyhydroxyalkanoates (PHA) with natural fibers were produced via compression molding. In particular, polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-hydroxyvalerate (PHBV) were reinforced with 20 wt% of agave fibers. Different compatibilization strategies were investigated to improve the fiber-matrix interaction: fiber surface treatment in PHA solution, fiber surface treatment in maleated PHA solution, fiber propionylation, and extrusion with maleated PHA. The biocomposites were characterized in terms of morphology, mechanical properties, water absorption, and biodegradability by CO₂ production tracking. In general, fiber propionylation was the best strategy for mechanical properties enhancement and water uptake decreasing. Biocomposites with propionylated fibers showed improved flexural strength (170% for PHB and 84% for PHBV). The flexural modulus was also enhanced with propionylated fibers up to 19% and 18% compared to uncompatibilized biocomposites (PHB and PHBV, respectively). Tensile strength increased by 16% (PHB) and 14% (PHBV), and the water absorption was reduced using propionylated fibers going from 6.6% to 4.4% compared with biocomposites with untreated fibers. Most importantly, the impact strength was also improved for all biocomposites by up to 96% compared with the neat PHA matrices. Finally, it was found that the compatibilization did not negatively modify the PHA biodegradability.     

Image Compression and Video Segmentation Using Hierarchical Self-Organization

Both image compression based on color quantization and image segmentation are two typical tasks in the field of image processing. Several techniques based on splitting algorithms or cluster analyses have been proposed in the literature. Self-organizing maps have been also applied to these problems, although with some limitations due to the fixed network architecture and the lack of representation in hierarchical relations among data. In this paper, both problems are addressed using growing hierarchical self-organizing models. An advantage of these models is due to the hierarchical architecture, which is more flexible in the adaptation process to input data, reflecting inherent hierarchical relations among data. Comparative results are provided for image compression and image segmentation. Experimental results show that the proposed approach is promising for image processing, and the powerful of the hierarchical information provided by the proposed model.     

Angle-of-arrival localization based on antenna arrays for wireless sensor networks

Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices.A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.     

A computer implementation of the partition of the unity procedure and its application to arthropod population dynamics. A case study on the European grape berry moth

This paper presents a new procedure to construct families of spatial approximation-prediction functions which depend on several parameters. The method is based on partitions of the unity. In order to find optimal functions in these families we introduce a Vietoris simplicial set associated to an influence radius. We consider error estimators induced by these Vietoris simplicial sets. A computational implementation of these mathematical models has been developed to be applied to any kind of finite discrete data. Our methods provide a useful tool for the analysis of the spatial distribution of species, which is imperative for developing accurate and efficient management of endangered and invasive species, biological conservation programs, etc. We demonstrate the application of our method to the analysis of the spatial distribution of the grape moth Lobesia botrana (Lepidoptera: Tortricidae) in the vineyards of La Rioja obtaining useful results for the management of this pest.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Finite‐time sliding mode observer for uncertain nonlinear systems based on a tunable algebraic solver

In this paper, a finite‐time sliding mode observer for nonlinear systems with unknown inputs is proposed. The observer is based on a method for the solution of time‐varying algebraic equations. This algebraic solver is shown to converge in finite time by means of Lyapunov analysis; furthermore, a way to tune it so that it converges after a user‐defined amount of time is presented. Through the use of this technique and sliding mode differentiators, the state variables and unknown inputs of a class of nonlinear systems, which do not need to be affine in the inputs, can be estimated without the explicit use of state transformations. Both the algebraic solver and the proposed observer are illustrated through simulation examples. Copyright © 2017 John Wiley & Sons, Ltd.     

Common coupling and pointer variables,with application to a Linux case study

Both common coupling and pointer variables can exert a deleterious effect on the quality of software. The situation is exacerbated when global variables are assigned to pointer variables, that is, when an alias to a global variable is created. When this occurs, the number of global variables increases, and it becomes considerably harder to compute quality metrics correctly. However, unless aliasing is taken into account, variables may incorrectly appear to be unreferenced (neither defined nor used), or to be used without being defined. These ideas are illustrated by means of a case study of common coupling in the Linux kernel.