Anomaly Detection with Selective Dictionary Learning

In this paper we present new methods of anomaly detection based on Dictionary Learning (DL) and Kernel Dictionary Learning (KDL). The main contribution consists in the adaption of known DL and KDL algorithms in the form of unsupervised methods, used for outlier detection. We propose a reduced kernel version (RKDL), which is useful for problems with large data sets, due to the large kernel matrix. We also improve the DL and RKDL methods by the use of a random selection of signals, which aims to eliminate the outliers from the training procedure. All our algorithms are introduced in an anomaly detection toolbox and are compared to standard benchmark results

Reduced Kernel Dictionary Learning

In this paper we present new algorithms for training reduced-size nonlinear representations in the Kernel Dictionary Learning (KDL) problem. Standard KDL has the drawback of a large size of the kernel matrix when the data set is large. There are several ways of reducing the kernel size, notably Nystr\"om sampling. We propose here a method more in the spirit of dictionary learning, where the kernel vectors are obtained with a trained sparse representation of the input signals. Moreover, we optimize directly the kernel vectors in the KDL process, using gradient descent steps. We show with three data sets that our algorithms are able to provide better representations, despite using a small number of kernel vectors, and also decrease the execution time with respect to KDL

Classification with Incoherent Kernel Dictionary Learning

In this paper we present a new classification method based on Dictionary Learning (DL). The main contribution consists of a kernel version of incoherent DL, derived from its standard linear counterpart. We also propose an improvement of the AK-SVD algorithm concerning the representation update. Our algorithms are tested on several popular databases of classification problems

Anatomic variation of alveolar antral artery

The alveolar antral artery (AAA) was unanimously encountered in a few available studies with an intraosseous course to anastomose with the infraorbital artery. We report here two cases in which dissection revealed an extraosseous placement of this artery, between the lateral wall of the maxillary sinus and the Schneiderian membrane. The frequency of occurrence of the intraosseous anastomosis should be so modified from 100% to < 100%. This arterial course over the Schneiderian membrane is important during surgical procedures: if it is identified preoperatively it can be avoided, or ligaturated, if not, it may be accidentally severed and uncomfortable haemorrhage may disturb the surgical procedure. In the first case reported here hybrid morphology of the AAA was also found, demonstrating that arterial anatomy should be considered with caution, on a case-by-case basis

Decrypting Integrins by Mixed-Solvent Molecular Dynamics Simulations

Integrins are a family of α/β heterodimeric cell surface adhesion receptors which are capable of transmitting signals bidirectionally across membranes. They are known for their therapeutic potential in a wide range of diseases. However, the development of integrin-targeting medications has been impacted by unexpected downstream effects including unwanted agonist-like effects. Allosteric modulation of integrins is a promising approach to potentially overcome these limitations. Applying mixed-solvent molecular dynamics (MD) simulations to integrins, the current study uncovers hitherto unknown allosteric sites within the integrin α I domains of LFA-1 (αLβ2; CD11a/CD18), VLA-1 (α1β1; CD49a/CD29), and Mac-1 (αMβ2, CD11b/CD18). We show that these pockets are putatively accessible to small-molecule modulators. The findings reported here may provide opportunities for the design of novel allosteric integrin inhibitors lacking the unwanted agonism observed with earlier as well as current integrin-targeting drugs.</p

Force and energy dissipation variations in non-contact atomic force spectroscopy on composite carbon nanotube systems

UHV dynamic force and energy dissipation spectroscopy in non-contact atomic force microscopy were used to probe specific interactions with composite systems formed by encapsulating inorganic compounds inside single-walled carbon nanotubes. It is found that forces due to nano-scale van der Waals interaction can be made to decrease by combining an Ag core and a carbon nanotube shell in the Ag@SWNT system. This specific behaviour was attributed to a significantly different effective dielectric function compared to the individual constituents, evaluated using a simple core-shell optical model. Energy dissipation measurements showed that by filling dissipation increases, explained here by softening of C-C bonds resulting in a more deformable nanotube cage. Thus, filled and unfilled nanotubes can be discriminated based on force and dissipation measurements. These findings have two different implications for potential applications: tuning the effective optical properties and tuning the interaction force for molecular absorption by appropriately choosing the filling with respect to the nanotube.Comment: 22 pages, 6 figure

Adsorbate/absorbate interactions with organic ferroelectric polymers

We discuss the interactions of adsorbates with the organic ferroelectric copolymer poly(vinylidene fluoride (PVDF)–trifluoroethylene (TrFE)). Range of molecular adsorbates is discussed from the smaller polar molecules like water, which is small enough to both adsorb and absorb, to the larger macrocyclic metal–organic metal phthalocyanines. The changes in local dipole orientation may affect the strength of the coupling between adsorbate or absorbate and the copolymer poly(vinylidene fluoride–trifluoroethylene). The interface dipole interactions may also affect device properties. The dipole interactions are implicated at the interface between copper phthalocyanine and poly(vinylidene fluoride with trifluoroethylene) affecting the band offsets and the diode properties

Determination of pyrrolizidine alkaloids in dietary sources using a spectrophotometric method

Pyrrolizidine alkaloids (PAs) are a class of toxic compounds found in the composition of more than 6000 plants. People can be exposed to PAs by consuming phytotherapeutic products, food from crops contaminated with seeds of some species with high content of PAs, and/ or contaminated animal products like bee products. For this reason we developed and validated a method for quantitative determination of PAs, from the most frequently contaminated food sources, honey and flour. Colorimetric Ehrlich reagent method was used with standard addition (1mg/kg senecionine). The extraction solvent was methanol 50% acidified with citric acid to pH 2-3, as this solvent can be used for alkaloids and N-oxides. We found that, in extracting the alkaloid only once from the dietary sources, the percent of recovery is low (52.5% for honey, and 45.75% for flour). Using successive extractions, three times with the same solvent, the senecionine retrieval percentage increased to 86.0% for honey and 76.0% for flour. The method was validated using the following parameters: selectivity, linearity (0,25- 20 mg/ mL senecionine), accuracy (average recovery 93.5 - 107.93%) and precision (RSD 3,26-4.55%.). The calculated limit of quantification (0.174 mg/ mL) makes this method applicable for determining Pas occurring at toxic levels for consumers