The aim of this contribution is to present the theory of intentionality proposed by the Spanish Dominican Lope de Barrientos (1382–1469), as it is offered by his Clavis Sapentiae: in this erudite work, written at the turn of the 15th century in the context of the new-born School of Salamanca, the terms proper to the gnoseological lexicon of the Thomist scholasticism are taken into consideration, analysed and renewed in a new original way. This makes possible to demonstrate from one hand how the tradition opened by Thomas Aquinas is inherited in the upcoming Renaissance and from another hand to look how a typical Renaissance scholar as Barrientos builds a theory of knowledge that is original, although faithful to the Thomist tradition to which it has been continuously and cogently referred and consulted.

In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed for classifying sonar targets and non-targets from the acoustic backscattered signals. Besides the capabilities of MLP NNs, it uses Back Propagation (BP) and Gradient Descent (GD) for training; therefore, MLP NNs face with not only impertinent classification accuracy but also getting stuck in local minima as well as lowconvergence speed. To lift defections, this study uses Adaptive Best Mass Gravitational Search Algorithm (ABGSA) to train MLP NN. This algorithm develops marginal disadvantage of the GSA using the bestcollected masses within iterations and expediting exploitation phase. To test the proposed classifier, this algorithm along with the GSA, GD, GA, PSO and compound method (PSOGSA) via three datasets in various dimensions will be assessed. Assessed metrics include convergence speed, fail probability in local minimum and classification accuracy. Finally, as a practical application assumed network classifies sonar dataset. This dataset consists of the backscattered echoes from six different objects: four targets and two non-targets. Results indicate that the new classifier proposes better output in terms of aforementioned criteria than whole proposed benchmarks.

The manufacturing industry has been reshaping its operations using digital technologies for a smart production towards a more customized demand. Nevertheless, the flexibility to attend the production plan changes in real time is still challenging. Although the Internet of Services (IoS) has been addressed as a key element for Industry 4.0, there is still a lack of clarity about the IoS contribution for advanced manufacturing. Through a case study, the paper aims to validate the adherence of a theoretical model named Service-Oriented Manufacturing Architecture (SOMA) in two manufacturing companies that have been already engaged in Industry 4.0. As main results, it was concluded that IoS could suit in one case of Industry 4.0 flexible production process but not in a mass production one. Considering the scarcity of research that exemplifies the IoS contribution, the present paper brings an important assessment on a real manufacturing scenario.

The subject of research was urban and urban-rural communes in the peripheral areas of voivodships, that is outside the functional areas of their capitals and outside the Silesian agglomerations. The aim of the research was to: (1) recognize the most economically developed entities in the studied areas, (2) recognize how development factors and their combinations that can create territorial capital are perceived and used in municipal strategies. The methods included: (1) analysis of indicators (2) analysis of texts of 10 strategies of entities with a high level of development. It was found, that there was deficiency of specific factors of development and recognition of their combination as well as the lack of using them to create a competitive advantage.

This paper described a determination of volatile organic compounds (such as benzene, toluene, ethylbenzene, xylene and phenol) and polycyclic aromatic hydrocarbons (16 by US EPA method) in atmospheric air in Zabrze in 1997. Samples were collected on sorbents (graphitized carbon for BTEX, Chromosorb 102 for phenol and polypropylene filter for PAH) capable of selectivity trapping a wide range of substances. Samples were than analysed using an extraction by solvents followed by capillary gas chromatography with flame ionised detector or ion trap mass detector. The lower limit of detection was circa O.Ol μg/m3 for most compounds. Using a gas chromatograph with ion trap mass detector it was possible to identify 35 organic compounds in urban air in Zabrze. GC-MS is powerful tool for identification organic compounds, but GC with FID detector is most sensitive for quantitative determination of volatile organic compounds.