Guiding, focusing, and sensing on the sub-wavelength scale using metallic wire arrays

We show that two-dimensional arrays of thin metallic wires can guide transverse electromagnetic (TEM) waves and focus them to the spatial dimensions much smaller that the vacuum wavelength. This guiding property is retained for the tapered wire bundles which can be used as multi-channel TEM endoscopes: they capture a detailed electromagnetic field profile created by deeply sub-wavelength features of the studied sample and magnify it for observation. The resulting imaging method is superior to the conventional scanning microscopy because of the parallel nature of the image acquisition by multiple metal wires. Possible applications include terahertz and mid-infrared endoscopy with nanoscale resolution.Comment: 3 figure

TOTAL INTRADURAL DISK PROLAPSE IN THE LUMBAR REGION

Penetration of the intervertebral disk material into the intradural space in the lumbar region is a clinical and neurosurgical casuistic. According to literature data available, this pathology occurs in less than 0,3 per cent of the operated patients with lumbar disk herniation. The few clinical reports aim at forming a typical clinical syndrome. The authors presented two own clinical observations of operatively verified patients with total intradural disk protrusion in the lumbar region at the level of L4-L5 vertebrae. The unexpected operative finding required a revision of the intradural space. Good surgical results could be obtained in early decompression of the flattened nerve roots

Sparsest factor analysis for clustering variables: a matrix decomposition approach

We propose a new procedure for sparse factor analysis (FA) such that each variable loads only one common factor. Thus, the loading matrix has a single nonzero element in each row and zeros elsewhere. Such a loading matrix is the sparsest possible for certain number of variables and common factors. For this reason, the proposed method is named sparsest FA (SSFA). It may also be called FA-based variable clustering, since the variables loading the same common factor can be classified into a cluster. In SSFA, all model parts of FA (common factors, their correlations, loadings, unique factors, and unique variances) are treated as fixed unknown parameter matrices and their least squares function is minimized through specific data matrix decomposition. A useful feature of the algorithm is that the matrix of common factor scores is re-parameterized using QR decomposition in order to efficiently estimate factor correlations. A simulation study shows that the proposed procedure can exactly identify the true sparsest models. Real data examples demonstrate the usefulness of the variable clustering performed by SSFA

Active Negative Index Metamaterial Powered by an Electron Beam

A novel active negative index metamaterial that derives its gain from an electron beam is intro- duced. The metamaterial consists of a stack of equidistant parallel metal plates perforated by a periodic array of holes shaped as complementary split-ring resonators. It is shown that this structure supports a negative-index transverse magnetic electromagnetic mode that can resonantly interact with a relativistic electron beam. Such metamaterial can be used as a coherent radiation source or a particle accelerator.Comment: 5 pages, 4 figure

Semi-sparse PCA

It is well-known that the classical exploratory factor analysis (EFA) of data with more observations than variables has several types of indeterminacy. We study the factor indeterminacy and show some new aspects of this problem by considering EFA as a specific data matrix decomposition. We adopt a new approach to the EFA estimation and achieve a new characterization of the factor indeterminacy problem. A new alternative model is proposed, which gives determinate factors and can be seen as a semi-sparse principal component analysis (PCA). An alternating algorithm is developed, where in each step a Procrustes problem is solved. It is demonstrated that the new model/algorithm can act as a specific sparse PCA and as a low-rank-plus-sparse matrix decomposition. Numerical examples with several large data sets illustrate the versatility of the new model, and the performance and behaviour of its algorithmic implementation

Recipes for sparse LDA of horizontal data

Many important modern applications require analyzing data with more variables than observations, called for short horizontal. In such situation the classical Fisher’s linear discriminant analysis (LDA) does not possess solution because the within-group scatter matrix is singular. Moreover, the number of the variables is usually huge and the classical type of solutions (discriminant functions) are difficult to interpret as they involve all available variables. Nowadays, the aim is to develop fast and reliable algorithms for sparse LDA of horizontal data. The resulting discriminant functions depend on very few original variables, which facilitates their interpretation. The main theoretical and numerical challenge is how to cope with the singularity of the within-group scatter matrix. This work aims at classifying the existing approaches according to the way they tackle this singularity issue, and suggest new ones

Heteroarylguanidines as Allosteric Modulators of ASIC1a and ASIC3 Channels.

Acid-sensing ion channels (ASICs) are neuronal Na <sup>+</sup> -selective ion channels that open in response to extracellular acidification. They are involved in pain, fear, learning, and neurodegeneration after ischemic stroke. 2-Guanidine-4-methylquinazoline (GMQ) was recently discovered as the first nonproton activator of ASIC3. GMQ is of interest as a gating modifier and pore blocker of ASICs. It has however a low potency, and exerts opposite effects on ASIC1a and ASIC3. To further explore the molecular mechanisms of GMQ action, we have used the guanidinium moiety of GMQ as a scaffold and tested the effects of different GMQ derivatives on the ASIC pH dependence and maximal current. We report that GMQ derivatives containing quinazoline and quinoline induced, as GMQ, an alkaline shift of the pH dependence of activation in ASIC3 and an acidic shift in ASIC1a. Another group of 2-guanidinopyridines shifted the pH dependence of both ASIC1a and ASIC3 to more acidic values. Several compounds induced an alkaline shift of the pH dependence of ASIC1a/2a and ASIC2a/3 heteromers. Compared to GMQ, guanidinopyridines showed a 20-fold decrease in the IC <sub>50</sub> for ASIC1a and ASIC3 current inhibition at pH 5. Strikingly, 2-guanidino-quinolines and -pyridines showed a concentration-dependent biphasic effect that resulted at higher concentrations in ASIC1a and ASIC3 inhibition (IC <sub>50</sub> > 100 μM), while causing at lower concentration a potentiation of ASIC1a, but not ASIC3 currents (EC <sub>50</sub> ≈ 10 μM). In conclusion, we describe a new family of small molecules as ASIC ligands and identify an ASIC subtype-specific potentiation by a subgroup of these compounds