I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments

Sensor Web Enablement (SWE) technologies have been successfully applied to a great variety of outdoor scenarios but, in practical terms, little effort has been applied for indoor environments, and even less in the field of industrial applications. This article presents an intelligent SWE application for an indoor and industrial scenario, with the aim of improving and increasing the levels of human safety. The base low-level architecture is built on top of wireless sensor networks (WSN) connected to a Sensor Observation Service (SOS). Higher layers in the architecture include services that make real time decisions based on the collected data. Both simulation and experimental results are presented. The paper shows the viability of our approach in terms of performance, scalability, modularity and safety.     

Distance learning for similarity estimation

In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance functions. A new set of distance measures are derived from the harmonic distance, the geometric distance, and their generalized variants according to the Maximum Likelihood theory. These measures can provide a more accurate feature model than the classical Euclidean and Manhattan distances. We also find that the feature elements are often from heterogeneous sources that may have different influence on similarity estimation. Therefore, the assumption of single isotropic distribution model is often inappropriate. To alleviate this problem, we use a boosted distance measure framework that finds multiple distance measures which fit the distribution of selected feature elements best for accurate similarity estimation. The new distance measures for similarity estimation are tested on two applications: stereo matching and motion tracking in video sequences. The performance of boosted distance measure is further evaluated on several benchmark data sets from the UCI repository and two image retrieval applications. In all the experiments, robust results are obtained based on the proposed methods.     

Microfluidic device with dual-channel fluorescence acquisition for quantification/identification of cancer cells

This paper presents an optofluidic device for cell discrimination with two independent interrogation regions. Pumping light is coupled to the device, and cell fluorescence is extracted from the two interrogation zones by using optical fibers embedded in the optofluidic chip. To test the reliability of this device, AU-565 cells—expressing EpCAM and HER2 receptors—and RAMOS cells were mixed in a controlled manner, confined inside a hydrodynamic focused flow in the microfluidic chip and detected individually so that they could be discriminated as positive (signal reception from fluorescently labeled antibodies from the AU-565 cells) or negative events (RAMOS cells). A correlation analysis of the two signals reduces the influence of noise on the overall data.     

An extremely low noise photodetector based on the single electron transistor

We have demonstrated the use of the single electron transistor (SET) as an amplifier for a photodetector operated at 20 mK. The unparalleled low input noise of the SET permits the detection of very small numbers of charge carriers generated in a bulk p-type Si substrate. We present data showing the response of the detector when it is illuminated by extremely low levels of red light (=650 nm). Although we are not able to prove that individual charge carriers are being detected in our system, the magnitude of the detector response and the level of noise in the system are in good agreement with single charge, and therefore single photon, detection. From the dark current noise of 0.06 electron/s, we estimate a noise-equivalent power NEP=2×10^–21 W/Hz for infrared light with =30 µm, and from this calculate a detectivity D*=8×10¹⁷ cm-Hz/W.     

CrAlN coatings deposited by cathodic arc evaporation at different substrate bias

CrAlN is a good candidate as an alternative to conventional CrN coatings especially for high temperature oxidation-resistance applications. Different CrAlN coatings were deposited on hardened steel substrates by cathodic arc evaporation (CAE) from chromium-aluminum targets in a reactive nitrogen atmosphere at negative substrate bias between − 50 and − 400 V. The negative substrate bias has important effects on the deposition growth rate and crystalline structure. All our coatings presented hardness higher than conventional CrN coatings. The friction coefficient against alumina and tungsten carbide balls was around 0.6. The sliding wear coefficient of the CrAlN coatings was very low while an important wear was observed in the balls before a measurable wear were produced in the coatings. This effect was more pronounced as the negative substrate bias was increased.     

CMOS-SOI platform for monolithic integration of crystalline silicon MEMS

A new platform for the fabrication of crystalline micro- and nano-electromechanical systems fully integrable with CMOS is presented. A pre-CMOS process on SOI wafers allows bulk silicon areas for standard CMOS processing and areas with a stack layer of silicon and silicon oxide to be obtained, in which a set of microelectromechanical devices can be fabricated. An integrated resonant beam system with electrical actuation and detection fabricated according to the presented approach is provided.     

Genetics and Epigenetics of Spontaneous Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is a complex and heterogeneous disease, and there is no effective treatment. Spontaneous ICH represents the final manifestation of different types of cerebral small vessel disease, usually categorized as: lobar (mostly related to cerebral amyloid angiopathy) and nonlobar (hypertension-related vasculopathy) ICH. Accurate phenotyping aims to reflect these biological differences in the underlying mechanisms and has been demonstrated to be crucial to the success of genetic studies in this field. This review summarizes how current knowledge on genetics and epigenetics of this devastating stroke subtype are contributing to improve the understanding of ICH pathophysiology and their potential role in developing therapeutic strategies.     

TLR/WNT: A Novel Relationship in Immunomodulation of Lung Cancer

The most frequent cause of death by cancer worldwide is lung cancer, and the 5-year survival rate is still very poor for patients with advanced stage. Understanding the crosstalk between the signaling pathways that are involved in disease, especially in metastasis, is crucial to developing new targeted therapies. Toll-like receptors (TLRs) are master regulators of the immune responses, and their dysregulation in lung cancer is linked to immune escape and promotes tumor malignancy by facilitating angiogenesis and proliferation. On the other hand, over-activation of the WNT signaling pathway has been reported in lung cancer and is also associated with tumor metastasis via induction of Epithelial-to-mesenchymal-transition (EMT)-like processes. An interaction between both TLRs and the WNT pathway was discovered recently as it was found that the TLR pathway can be activated by WNT ligands in the tumor microenvironment; however, the implications of such interactions in the context of lung cancer have not been discussed yet. Here, we offer an overview of the interaction of TLR-WNT in the lung and its potential implications and role in the oncogenic process.     

Integrability conditions for complex kukles systems

In this paper, we provide necessary and sufficient conditions for the existence of local analytic first integrals for a seventh-parameter family of complex cubic systems called the complex Kukles systems.