3D Surface Reconstruction of Noisy Point Clouds Using Growing Neural Gas: 3D Object/Scene Reconstruction

With the advent of low-cost 3D sensors and 3D printers, scene and object 3D surface reconstruction has become an important research topic in the last years. In this work, we propose an automatic (unsupervised) method for 3D surface reconstruction from raw unorganized point clouds acquired using low-cost 3D sensors. We have modified the growing neural gas network, which is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation, to perform 3D surface reconstruction of different real-world objects and scenes. Some improvements have been made on the original algorithm considering colour and surface normal information of input data during the learning stage and creating complete triangular meshes instead of basic wire-frame representations. The proposed method is able to successfully create 3D faces online, whereas existing 3D reconstruction methods based on self-organizing maps required post-processing steps to close gaps and holes produced during the 3D reconstruction process. A set of quantitative and qualitative experiments were carried out to validate the proposed method. The method has been implemented and tested on real data, and has been found to be effective at reconstructing noisy point clouds obtained using low-cost 3D sensors.     

Simultaneous domestic wastewater treatment and renewable energy production using microbial fuel cells (MFCs)

Microbial fuel cells (MFCS) can be used in wastewater treatment and to simultaneously produce electricity (renewable energy). MFC technology has already been applied successfully in lab-scale studies to treat domestic wastewater, focussing on organic matter removal and energy production. However, domestic wastewater also contains nitrogen that needs to be treated before being discharged. The goal of this paper is to assess simultaneous domestic wastewater treatment and energy production using an air-cathode MFC, paying special attention to nitrogen compound transformations. An air-cathode MFC was designed and run treating 1.39 L d(-1) of wastewater with an organic load rate of 7.2 kg COD m(-3) d(-1) (80% removal efficiency) and producing 1.42 W m(-3). In terms of nitrogen transformations, the study demonstrates that two different processes took place in the MFC: physical-chemical and biological. Nitrogen loss was observed increasing in line with the power produced. A low level of oxygen was present in the anodic compartment, and ammonium was oxidised to nitrite and nitrate.     

Recent Advances on High-Speed and Holographic Two-Photon Direct Laser Writing

Two-Photon Lithography, thanks to its very high sub-diffraction resolution, has become the lithographic technique par excellence in applications requiring small feature sizes and complex 3D pattering. Despite this, the fabrication times required for extended structures remain much longer than those of other competing techniques (UV mask lithography, nanoimprinting, etc.). Its low throughput prevents its wide adoption in industrial applications. To increase it, over the years different solutions have been proposed, although their usage is difficult to generalize and may be limited depending on the specific application. A promising strategy to further increase the throughput of Two-Photon Lithography, opening a concrete window for its adoption in industry, lies in its combination with holography approaches: in this way it is possible to generate dozens of foci from a single laser beam, thus parallelizing the fabrication of periodic structures, or to engineer the intensity distribution on the writing plane in a complex way, obtaining 3D microstructures with a single exposure. Here, the fundamental concepts behind high-speed Two-Photon Lithography and its combination with holography are discussed, and the literary production of recent years that exploits such techniques is reviewed, and contextualized according to the topic covered.     

Sorafenib delivery nanoplatform based on superparamagnetic iron oxide nanoparticles magnetically targets hepatocellular carcinoma

Currently,sorafenib is the only systemic therapy capable of increasing overall survival of hepatocellular carcinoma patients.Unfortunately,its side effects,particularly its overall toxicity,limit the therapeutic response that can be achieved.Superparamagnetic iron oxide nanoparticles (SPIONs) are very attractive for drug delivery because they can be targeted to specific sites in the body through application of a magnetic field,thus improving intratumoral accumulation and reducing adverse effects.Here,nanoformulations based on polyethylene glycol modified phospholipid micelles,loaded with both SPIONs and sorafenib,were successfully prepared and thoroughly investigated by complementary techniques.This nanovector system provided effective drug delivery,had an average hydrodynamic diameter of about 125 nm,had good stability in aqueous medium,and allowed controlled drug loading.Magnetic analysis allowed accurate determination of the amount of SPIONs embedded in each micelle.An in vitro system was designed to test whether the SPION micelles can be efficiently held using a magnetic field under typical flow conditions found in the human liver.Human hepatocellular carcinoma (HepG2) cells were selected as an in vitro system to evaluate tumor cell targeting efficacy of the superparamagnetic micelles loaded with sorafenib.These experiments demonstrated that this delivery platform is able to enhance sorafenib's antitumor effectiveness by magnetic targeting.The magnetic nanovectors described here represent promising candidates for targeting specific hepatic tumor sites,where selective release of sorafenib can improve its efficacy and safety profile.     

Intestinal gas dynamics and tolerance in humans

Carbohydrate-deficient-glycoprotein syndrome type 1 (CDG1; also known as "Jaeken syndrome") is an autosomal recessive disorder characterized by defective glycosylation. Most patients show a deficiency of phosphomannomutase (PMM), the enzyme that converts mannose 6-phosphate to mannose 1-phosphate in the synthesis of GDP-mannose. The disease is linked to chromosome 16p13, and mutations have recently been identified in the PMM2 gene in CDG1 patients with a PMM deficiency (CDG1A). The availability of the genomic sequences of PMM2 allowed us to screen for mutations in 56 CDG1 patients from different geographic origins. By SSCP analysis and by sequencing, we identified 23 different missense mutations and 1 single-base-pair deletion. In total, mutations were found on 99% of the disease chromosomes in CDG1A patients. The R141H substitution is present on 43 of the 112 disease alleles. However, this mutation was never observed in the homozygous state, suggesting that homozygosity for these alterations is incompatible with life. On the other hand, patients were found homozygous for the D65Y and F119L mutations, which must therefore be mild mutations. One particular genotype, R141H/D188G, which is prevalent in Belgium and the Netherlands, is associated with a severe phenotype and a high mortality. Apart from this, there is only a limited relation between the genotype and the clinical phenotype.     

Path integral study of the 4He wetting transition

The ⁴ He wetting transition on a Cs surface is for the first time studied by Path Integral Monte Carlo simulation. Numerical results for a system of 64 ⁴ He atoms are qualitatively consistent with a wetting transition at a temperature T 2 K.     

On the observational theory of the CPS-calculus

We apply powerful proof-techniques of concurrency theory to study the observational theory of Thielecke’s CPS-calculus, a distillation of the target language of Continuation-Passing Style transforms. We define a labelled transition system from which we derive a (weak) labelled bisimilarity that completely characterises Morris’ context-equivalence. We prove a context lemma showing that Morris’ context-equivalence coincides with a simpler context-equivalence closed under a smaller class of contexts. Then we profit of the determinism of the CPS-calculus to give a simpler labelled characterisation of Morris’ equivalence, in the style of Abramsky’s applicative bisimilarity. We enhance our bisimulation proof-methods with up to bisimilarity and up to context proof techniques. We use our bisimulation proof techniques to investigate a few algebraic properties on diverging terms that cannot be proved using the original axiomatic semantics of the CPS-calculus.     

Enabling energy-efficient and lossy-aware data compression in wireless sensor networks by multi-objective evolutionary optimization

Nodes of wireless sensor networks (WSNs) are typically powered by batteries with a limited capacity. Thus, energy is a primary constraint in the design and deployment of WSNs. Since radio communication is in general the main cause of power consumption, the different techniques proposed in the literature to improve energy efficiency have mainly focused on limiting transmission/reception of data, for instance, by adopting data compression and/or aggregation. The limited resources available in a sensor node demand, however, the development of specifically designed algorithms. To this aim, we propose an approach to perform lossy compression on single node based on a differential pulse code modulation scheme with quantization of the differences between consecutive samples. Since different combinations of the quantization process parameters determine different trade-offs between compression performance and information loss, we exploit a multi-objective evolutionary algorithm to generate a set of combinations of these parameters corresponding to different optimal trade-offs. The user can therefore choose the combination with the most suitable trade-off for the specific application. We tested our lossy compression approach on three datasets collected by real WSNs. We show that our approach can achieve significant compression ratios despite negligible reconstruction errors. Further, we discuss how our approach outperforms LTC, a lossy compression algorithm purposely designed to be embedded in sensor nodes, in terms of compression rate and complexity.     

A hybrid particle swarm optimization approach for the sequential ordering problem

The sequential ordering problem is a version of the asymmetric travelling salesman problem where precedence constraints on vertices are imposed. A tour is feasible if these constraints are fulfilled, and the objective is to find a feasible solution with minimum cost.     

A hybrid positioning system for technology‐independent location‐aware computing

Location‐aware computing is a form of context‐aware mobile computing that refers to the ability of providing users with services that depend on their position. Locating the user terminal, often called positioning, is essential in this form of computing. Towards this aim, several technologies exist, ranging from personal area networking, to indoor, outdoor, and up to geographic area systems. Developers of location‐aware software applications have to face with a number of design choices, that typically depend on the chosen technology. This work addresses the problem of easing the development of pull location‐aware applications, by allowing uniform access to multiple heterogeneous positioning systems. Towards this aim, the paper proposes an approach to structure location‐aware mobile computing systems in a way independent of positioning technologies. The approach consists in structuring the system into a layered architecture, that provides application developers with a standard Java Application Programming Interface (JSR‐179 API), and encapsulates location data management and technology‐specific positioning subsystems into lower layers with clear interfaces. In order to demonstrate the proposed approach we present the development of HyLocSys. It is an open hybrid software architecture designed to support indoor/outdoor applications, which allows the uniform (combined or separate) use of several positioning technologies. HyLocSys uses a hybrid data model, which allows the integration of different location information representations (using symbolic and geometric coordinates). Moreover, it allows support to handset‐ and infrastructure‐based positioning approaches while respecting the privacy of the user. The paper presents a prototypal implementation of HyLocSys for heterogeneous scenarios. It has been implemented and tested on several platforms and mobile devices. Copyright © 2009 John Wiley & Sons, Ltd.