Approximation theorems for a family of multivariate neural network operators in Orlicz-type spaces

In this paper, we study the theory of a Kantorovich version of the multivariate neural network operators. Such operators, are activated by suitable kernels generated by sigmoidal functions. In particular, the main result here proved is a modular convergence theorem in Orlicz spaces. As special cases, convergence theorem in \(L^p\)-spaces, interpolation spaces, and exponential-type spaces can be deduced. In general, multivariate approximations by constructive neural network algorithms are useful for applications to neurocomputing processes involving high dimensional data. At the end of the paper, several examples of activation functions of sigmoidal-type for which the above theory holds have been described.     

An Informational Theory of Counterfactuals

Backtracking counterfactuals are problem cases for the standard, similarity based, theories of counterfactuals e.g., Lewis (Noûs13.4, 455–476, 1979). These theories usually need to employ extra-assumptions to deal with those cases (e.g., Lewis’ “standard resolution of vagueness”). Hiddleston (Noûs 39(4), 632–657, 2005) proposes a causal theory of counterfactuals that, supposedly, deals well with backtracking. The main advantage of the causal theory is that it provides a unified account for backtracking and non-backtracking counterfactuals (no extra-assumption is needed). In this paper, I present a backtracking counterfactual that is a problem case for Hiddleston’s account. Then I propose an informational theory of counterfactuals, which deals well with this problem case while maintaining the main advantage of Hiddleston’s account (the unified account for backtracking and non-backtracking counterfactuals). In addition, the informational theory offers a general theory of backtracking that provides clues for the semantics and epistemology of counterfactuals. I propose that backtracking is reasonable when the (possibly non-actual) state of affairs expressed in the antecedent of a counterfactual transmits less information about an event in the past than the actual state of affairs.     

A segmentation procedure of the pervious area of the aorta artery from CT images without contrast medium

In this paper, we develop an algorithm for the segmentation of the pervious lumen of the aorta artery in computed tomography (CT) images without contrast medium, a challenging task due to the closeness gray levels of the different zones to segment. The novel approach of the proposed procedure mainly resides in enhancing the resolution of the image by the application of the algorithm deduced from the mathematical theory of sampling Kantorovich operators. After the application of suitable digital image processing techniques, the pervious zone of the artery can be distinguished from the occluded one. Numerical tests have been performed using 233 CT images, and suitable numerical errors have been computed and introduced ex novo to evaluate the performance of the proposed method. The above procedure is completely automatic in all its parts after the initial region of interest (ROI) selection. The main advantages of this approach relies in the potential possibility of performing diagnosis concerning vascular pathologies even for patients with severe kidney diseases or allergic problems, for which CT images with contrast medium cannot be achieved.     

ChemInform Abstract: An ab initio Theoretical Study of the Electronic Structure of UO2+ and [UO2(CO3)3]5‐.

ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.     

Approximation by Nonlinear Multivariate Sampling Kantorovich Type Operators and Applications to Image Processing

In this article, we study a nonlinear version of the sampling Kantorovich type operators in a multivariate setting and we show applications to image processing. By means of the above operators, we are able to reconstruct continuous and uniformly continuous signals/images (functions). Moreover, we study the modular convergence of these operators in the setting of Orlicz spaces L ^?(? ⁿ ) that allows us to deal the case of not necessarily continuous signals/images. The convergence theorems in L ^p (? ⁿ )-spaces, L ^αlog ^β L(? ⁿ )-spaces and exponential spaces follow as particular cases. Several graphical representations, for the various examples and image processing applications are included.     

Method for Measurements of Terrestrial Ultraviolet Radiation on Inclined Surfaces in Personal Dosimetry Field Studies

Understanding personal ultraviolet radiation (UVR) exposure is essential for the evaluation of the health risks and benefits; however, personal dosimetry could be challenging in large‐scale or/and long‐term population studies. Alternatively, personal exposure could be simulated using three‐dimensional models and lifestyle surveys together with data on a body position with respect to the sun. These models require a real‐time input on local environmental UVR. The main challenge in using this method is retrieval of the diffuse irradiance as it requires an often‐expensive tracking of solar position. In this study, a hypothesis that UVR measured on a vertical plane in the north direction can be used in the UK as a proxy for diffuse radiation was tested against direct measurements and compared with models based on solar tracker data in Chilton, UK, (51.57°N) in June–July 2018. The statistical analysis over 17 days under all weather conditions showed that for 45° and 90° tilted surfaces the proposed method performed as well as the best of the models based on solar tracker data. A proposed system could offer a portable and low‐cost alternative to measurements of diffuse radiation by solar tracking radiometers for spatial distribution of terrestrial erythema effective UVR in population field studies.     

Surfactant effect on electrochemical-induced synthesis of α-Ni(OH)2

Nickel hydroxide films were electrosynthesized in the presence of different diluted surfactant solutions by galvanostatic electroprecipitation. Lamellar α-Ni(OH)₂ films are obtained using cationic surfactant cetyltrimethylammonium bromide (CTAB), anionic surfactant sodium dodecyl sulfate (SDS), and also neutral surfactant Tween® 80. The films were structurally and morphologically characterized by X-ray diffraction, thermal gravimetric analysis, Fourier transform infrared spectroscopy, and scanning electron microscopy, and electrochemically by cyclic voltammetry and electrochemical quartz crystal microbalance (EQCM). The results evidenced that SDS remains intercalated between the lamellae of α-Ni(OH)₂. Albeit the presence of CTAB and Tween® 80, it was noticed in FTIR spectra that the surfactants did not intercalate. The morphology was affected by the presence of different surfactants. All studied surfactants displaced the oxidation potential (E _O) of Ni²⁺/Ni³⁺ process to less positive values. Also, the presence of surfactants improved the electrode charge efficiency and the charge response for the same number of moles of nickel ions deposited. The ratio of the charge and frequency change is 4.4 times bigger for films deposited with SDS when compared with pure α-Ni(OH)₂ films.