Little is known on how to encourage effortful (rather than effortless) conservation behaviors, and prior research investigated only single (rather than multiple) message appeals in terms of their persuasive power in promoting pro-environmental intentions. The current study uses a framework from evolutionary psychology to propose and test a blend of message appeals that is most likely to drive green behaviors perceived as effortful. An experiment with a 2 (yes versus no anthropomorphic cue) × 2 (negative versus positive message frame) between-subjects design was run, and effort was included as a measured factor. The findings reveal that negatively framed messages are most effective in prompting effortful (but not effortless) pro-environmental intentions only when they are coupled with anthropomorphic cues (no differences between loss and gain messages were found when no anthropomorphism was used). These effects were replicated across two types of behaviors: water conservation and waste reduction.

The paper presents the results of research on the hybrid industrial tomograph electrical impedance tomography (EIT) and ultrasonic tomography (UST) (EIT-UST), operating on the basis of electrical and ultrasonic data. The emphasis of the research was placed on the algorithmic domain. However, it should be emphasized that all hardware components of the hybrid tomograph, including electronics, sensors and transducers, have been designed and mostly made in the Netrix S.A. laboratory. The test object was a tank filled with water with several dozen percent concentration. As part of the study, the original multiple neural networks system was trained, the characteristic feature of which is the generation of each of the individual pixels of the tomographic image, using an independent artificial neural network (ANN), with the input vector for all ANNs being the same. Despite the same measurement vector, each of the ANNs generates its own independent output value for a given tomogram pixel, because, during training, the networks get their respective weights and biases. During the tests, the results of three tomographic methods were compared: EIT, UST and EIT-UST hybrid. The results confirm that the use of heterogeneous tomographic systems (hybrids) increases the reliability of reconstruction in various measuring cases, which is used to solve quality problems in managing production processes.

PurposeThe purpose of this paper is to ask two questions. How does the customer's loyalty in the banking sector change (at both the structural and quantitative level) in the light of the financial and banking crises? Are any differences observed in those changes between developing and developed countries?Design/methodology/approachThe paper consists of two parts: theoretical and empirical. In the theoretical part the authors discuss the nature of the banking and financial crises, the historical perspective of banking crises occurrence and main causes and consequences of those crises. The second part of the paper demonstrates statistical analysis of the obtained data from the Polish and European banking sector. The authors also present socio‐demographic characteristic of the research samples and the character of the bank‐client relations, comparative analysis of customer satisfaction index changes in the European banking sector and structural equation modes for the Polish banking sector for the years 2007‐2009.FindingsThe analyses allowed the authors to confirm the main research hypotheses: first, clients of developing European countries demonstrate generally lower satisfaction and loyalty levels than clients of banks in Western Europe. Second, the recent banking crisis has affected the level of customer satisfaction much more strongly in developing European countries than in developed ones. Third, the recent banking crisis has changed the character of the process of building customer satisfaction and loyalty in Poland by strengthening the influence of the image area.Originality/valueHardly anyone has tried to measure the influence of the banking crises at the level of customers’ satisfaction and the structure of the process of building long‐term relations between banks and their clients before.

The article deals with the problem of detecting moisture in the walls of historical buildings. As part of the presented research, the following four methods based on mathematical modeling and machine learning were compared: total variation, least-angle regression, elastic net, and artificial neural networks. Based on the simulation data, the systems for the reconstruction of “pixel by pixel” tomographic images were trained. In order to test the reconstructive algorithms obtained during the research, images were generated based on real measurements and simulation cases. The method comparison was performed on the basis of three indicators: mean square error, relative image error, and image correlation coefficient. The above indicators were applied to four selected variants that corresponded to various parts of the walls. The variants differed in the dimensions of the tested wall sections, the number of electrodes used, and the resolution of the 3D image meshes. In all analyzed variants, the best results were obtained using the elastic net algorithm. In addition, all machine learning methods generated better tomographic reconstructions than the classic Total Variation method.

The article presents a new concept for monitoring industrial tank reactors. The presented concept allows for faster and more reliable monitoring of industrial processes, which increases their reliability and reduces operating costs. The innovative method is based on electrical tomography. At the same time, it is non-invasive and enables the imaging of phase changes inside tanks filled with liquid. In particular, the hybrid tomograph can detect gas bubbles and crystals formed during industrial processes. The main novelty of the described solution is the simultaneous use of two types of electrical tomography: impedance and capacitance. Another novelty is the use of the LSTM network to solve the tomographic inverse problem. It was made possible by taking the measurement vector as a data sequence. Research has shown that the proposed hybrid solution and the LSTM algorithm work better than separate systems based on impedance or capacitance tomography.