Jesuit Sanctity: Hypothesizing the Continuity of a Hagiographic Narrative of the Modern Age

The introduction to this special issue provides some considerations on early modern sanctity as a historical object. It firstly presents the major shifts in the developing idea of sanctity between the late medieval period and the nineteenth century, passing through the early modern construction of sanctity and its cultural, social, and political implications. Secondly, it provides an overview of the main sources that allow historians to retrace early modern sanctity, especially canonization records and hagiographies. Thirdly, it offers an overview of the ingenious role of the Society of Jesus in the construction of early modern sanctity, by highlighting its ability to employ, create, and play with hagiographical models. The main Jesuit models of sanctity are then presented (i.e., the theologian, the missionary, the martyr, the living saint), and an important reflection is reserved for the specific martyrial character of Jesuit sanctity. The introduction assesses the continuity of the Jesuit hagiographical discourse throughout the long history of the order, from the origins to the suppression and restoration.

I Seminario permanente Asociación Española Jóvenes Modernistas Nobilities of the Spanish Monarchy. Perspectives and Methodologies for the Study of Power Groups in the Early Modern Age

Conference report

Knowledge Society

This chapter is developed along three conceptual axes: citizenship; knowledge society: transparency; and trust and participation. It begins by explaining the concept of citizenship and its historical roots, the Greek polis and the Roman civitas; the revival of cities in the Late Middle Ages and their consolidation in the Modern Age. It analyzes the citizenship construct with the affirmation of each inhabitant as a citizen involved in improving the several plans of the quality of urban life. The second axis evaluates the characteristics of knowledge societies as promoting factors to a citizenship based on socio-political indicators that build trust between the citizen. The third axis deals with transparency and trust as active disseminators of timely and relevant information to the public and its impact on corruption, as a barrier against a broad citizenship. At the methodological level, the study combines bibliographic research with a field research by questionnaire.

Environmental Impact of EV Batteries and Their Recycling

Electrifying transportation is one of the biggest keys to solving the looming climate crisis. The demand for electric vehicles (EV) is booming in the last five years and will increase in the coming years. In this modern age, where EV is the finest means of transportation due to null exhaust gases, there is a dire need to think about ways of recycling and reusing those batteries associated with EVs. In this context, it is estimated that post-vehicle battery packs application will be crossed from 1.4 million to 6.8 million by the year 2035. Numerous researches have been done on the re-purposing and safe disposal of EV batteries. However, presently, Lithium-ion batteries (LiBs) are the optimal choice for electric transportation due to greater energy density, compact size, and extended life cycles. Nonetheless, the trade-off between re-purposing and disposal of LiBs is substantial for the protection of the environment and human health. Regrettably, Lithium-ion battery recycling percentage is only 3% currently whereas its revival is negligible.

Feature extraction to predict quality of segregating sweet tamarind using image processing

<p>In this modern age, several new methods have been developed, especially in image processing for agriculture business, which consists of technologies derived from artificial intelligence (AI) capabilities called machine learning. Classify is a widely used method to analyze patterns, trends, as well as the body of knowledge from the data visualization. Image classification application improves discrimination and prediction efficiency. The objective of this research was to feature extraction of sweet tamarind and compare the algorithm for classification. This research used images from golden sweet tamarind species with the use of MATLAB and Python language. The steps of this research consisted of 1) preprocessing step for finding the distance to appropriate of the image quality, 2) feature extracting for finding the number of black pixels and the number of white pixels, perimeter, diameter, and centroid, and 3) classifying for algorithms' comparison. The results showed that the camera's distance to the image was 60 cm. The coefficient of determination was at 0.9956, and the Standard Error of Estimate was 7,424.736 pixels. The conclusion of classification found that the random forest had the highest accuracy at 92.00%, SD. = 8.06, precision = 90.12, recall = 92.86, and F1-score = 91.36.</p>