Mutations in collagen VI genes cause two major clinical myopathies, Bethlem myopathy (BM) and Ullrich congenital muscular dystrophy (UCMD), and the rarer myosclerosis myopathy. In addition to congenital muscle weakness, patients affected by collagen VI-related myopathies show axial and proximal joint contractures, and distal joint hypermobility, which suggest the involvement of tendon function. To gain further insight into the role of collagen VI in human tendon structure and function, we performed ultrastructural, biochemical, and RT-PCR analysis on tendon biopsies and on cell cultures derived from two patients affected with BM and UCMD. In vitro studies revealed striking alterations in the collagen VI network, associated with disruption of the collagen VI-NG2 (Collagen VI-neural/glial antigen 2) axis and defects in cell polarization and migration. The organization of extracellular matrix (ECM) components, as regards collagens I and XII, was also affected, along with an increase in the active form of metalloproteinase 2 (MMP2). In agreement with the in vitro alterations, tendon biopsies from collagen VI-related myopathy patients displayed striking changes in collagen fibril morphology and cell death. These data point to a critical role of collagen VI in tendon matrix organization and cell behavior. The remodeling of the tendon matrix may contribute to the muscle dysfunction observed in BM and UCMD patients.Sea clutter simulation is a well-known research endeavour in radar detector analysis and design, and many approaches to it have been proposed in recent years, among which zero memory non-linear (ZMNL) and spherically invariant random process (SIRP) are the most two widely used methods for compound Gaussian distribution. However, the shape parameter of the compound Gaussian clutter model cannot be a non-integer nor non-semi-integer in the ZMNL method, and the computational complexity of the SIRP method is very high because of the complex non-linear operation. Although some improved methods have been proposed to solve the problem, the fitting degree of these methods is not high because of the introduction of Beta distribution. To overcome these disadvantages, a novel Gamma distributed random variable (RV) generation method for clutter simulation is proposed in this paper. In our method, Gamma RV with non-integral or non-semi-integral shape parameters is generated directly by multiplying an integral-shape-parameter Gamma RV with a Beta RV whose parameters are larger than 0.5, thus avoiding the deviation of simulation of Beta RV. A large number of simulation experimental results show that the proposed method not only can be used in the clutter simulation with a non-integer or non-semi-integer shape parameter value, but also has higher fitting degree than the existing methods.The global positioning system (GPS) is an essential technology that provides positioning capabilities and is used in various applications such as navigation, surveying, mapping, robot simultaneous localization and mapping (SLAM), location-based service (LBS), etc. However, the GPS is known to be vulnerable to intentional attacks such as spoofing because of its simple signal structure. In this study, a direct method is proposed for GPS spoofing detection, using Attitude and Heading Reference System (AHRS) accelerometer and analyzing the detection performance with corresponding probability density functions (PDFs).  https://www.selleckchem.com/products/capsazepine.html  The difference in the acceleration between the GPS receiver and the accelerometer is used to detect spoofing. The magnitude of the acceleration error may be used as a decision variable. Additionally, using the magnitude of the north (or east) component of the acceleration error as another decision variable is proposed, which shows better performance in some conditions. The performance of the two decision variables is compared by calculating the probability of spoofing detection and the detectable minimum spoofing acceleration (DMSA), given a pre-defined false alarm probability and a pre-defined detection probability. It turns out that both decision variables need to be used together to obtain the best spoofing detection performance.With the proliferation of sensors and IoT technologies, stream data are increasingly stored and analyzed, but rarely combined, due to the heterogeneity of sources and technologies. Semantics are increasingly used to share sensory data, but not so much for annotating stream data. Semantic models for stream annotation are scarce, as generally semantics are heavy to process and not ideal for Internet of things (IoT) environments, where the data are frequently updated. We present a light model to semantically annotate streams, IoT-Stream. It takes advantage of common knowledge sharing of the semantics, but keeping the inferences and queries simple. Furthermore, we present a system architecture to demonstrate the adoption the semantic model, and provide examples of instantiation of the system for different use cases. The system architecture is based on commonly used architectures in the field of IoT, such as web services, microservices and middleware. Our system approach includes the semantic annotations that take place in the pipeline of IoT services and sensory data analytics. It includes modules needed to annotate, consume, and query data annotated with IoT-Stream. In addition to this, we present tools that could be used in conjunction to the IoT-Stream model and facilitate the use of semantics in IoT.The ability of plasmonic structures to confine and enhance light at nanometer length scales has been traditionally exploited to boost the magneto-optical effects in magneto-plasmonic structures. These platforms allows for light control via externally applied magnetic fields, which is of prime importance for sensing, data storage, optical-isolation, and telecommunications applications. However, applications are hindered by the high-level of ohmic losses associated to metallic and ferromagnetic components. Here, we use a lossless all-dielectric platform for giant enhancement of the magneto-optical effects. Our structure consists of a high-refractive index dielectric film on top of a magnetic dielectric substrate. We numerically demonstrate an extraordinarily enhanced transverse magneto-optical Kerr effect due to the Fabry-Perot resonances supported by the high-refractive index slab. Potential applications for sensing and biosensing are also illustrated in this work.