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Presents a robust and unconditionally stable return‐mapping algorithm based on the discrete counterpart of the principle of maximum plastic dissipation. Develops the explicit expression for the consistent elasto‐plastic tangent modulus. All expressions are derived via tensor formulation showing the advantage over the classical matrix notation. The integration algorithm is implemented in the formulation of the four‐node isoparametric assumed‐strain finite‐rotation shell element employing the Mindlin‐Reissner‐type shell model. By applying the layered model, plastic zones can be displayed through the shell thickness. Material non‐linearity described by the von Mises yield criterion and isotropic hardening is combined with a geometrically non‐linear response assuming finite rotations. Numerical examples illustrate the efficiency of the present formulation in conjunction with the standard Newton iteration approach, in which no line search procedures are required. Demonstrates the excellent performance of the algorithm for large time respective load steps.

This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.

A bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view is given. The bibliography at the end of the paper contains 1,726 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1996‐1999.

The introduction of digital resources has not only had considerable impact on the role of libraries in the information society, but it has also had a remarkable effect on back office procedures, i.e. on the way the library is organised. This article presents a case study of a reengineering process at the Bayerische Staatsbibliothek (Bavarian State Library) in Munich, Germany, the central regional library of the State of Bavaria and one of the largest academic research libraries in Europe with local, regional and supraregional responsibilities. Due to the multiple roles of this library, it was particularly important not only to bridge the gap between traditional and new material, but also to create a flexible organisational platform for the various tasks at the different levels indicated.

The Covid-19 pandemic has profoundly affected urban communities, generating the need for an immediate response from local governance. The availability of urban data platforms in some smart cities helped the relevant actors to develop various solutions in an innovative and highly contextual way. The purpose of this paper is to explore the role of data platforms in smart cities in the context of the Covid-19 crisis.

A total of 85 studies were identified using the Clarivate Analytics Web of Science electronic library. After applying exclusion and inclusion criteria, 61 publications were considered appropriate and reasonable for the research, being read in-depth. Finally, only 52 studies presented relevant information for the topic and were synthesized following the defined research questions. During the research, the authors included in the paper other interesting references found in selected articles and important information regarding the role of data in the fight against Covid-19 in smart cities available on the Internet and social media, with the intention to capture both academic and practical perspectives.

The authors' main conclusion suggests that based on their previous expertise in collecting, processing and analyzing data from multiple sources, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The results highlight the importance of open data, data sharing, innovative thinking, the collaboration between public and private stakeholders, and the participation of citizens, especially in these difficult times.

The city managers and data operators can use the presented case studies and findings to identify relevant data-driven smart solutions in the fight against Covid-19 or another crisis.

The performance of smart cities is a social concern since the population of urban communities is continuously growing. By reviewing the adoption of information technologies-based solutions to improve the quality of citizens' life, the paper emphasizes their potential in societies in which information technology is embedded, especially during a major crisis.

This research re-emphasizes the importance of collecting data in smart cities, the role of the diversity of their sources and the necessity of citizens, companies and government synergetic involvement, especially in a pandemic context. The existence of smart solutions to process and extract information and knowledge from large data sets was essential for many actors involved in smart cities, helping them in the decision-making process. Based on previous expertise, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The paper analyzes also these success cases that can be considered models to be adopted by other municipalities in similar circumstances.

Die Festlegung des Zeitpunktes für Kuraufenthalte, Erholungsferien und Vergnügungsreisen ist das komplexe Ergebnis verschiedenartiger Faktoren; diese sind teils individueller, teils kollektiver Natur. Zu den individuellen Einflüssen zählen persönliche Liebhabereien oder die Notwendigkeit einer Erholungskur infolge Erkrankung oder während der Rekonvaleszenz nach einer Krankheit oder einer Operation; zu den kollektiven Faktoren gehören dagegen Schul‐ oder Betriebsferien, günstige Reisegelegenheiten oder besonders geeignete Jahreszeit.

Excessive use of work-related information technology (IT) devices can lead to major performance and well-being concerns for organizations. Extant research has provided evidence of the incidence of such problematic IT use in organizations. We extend the understanding of problematic IT use by examining its individual (proximal) and organizational (distal) antecedents.

Drawing from the self-worth theory and the concept of fear of being left behind, we address proximal antecedents that lead to problematic IT use. Drawing from the concept of autonomy paradox, we address distal antecedents of problematic IT use through a positive association with the two proximal antecedents. We report the results of a field study involving 846 individuals who use IT for work. Structural equation modeling was employed to analyze the data.

The results indicate that the proximal antecedents (IT insecurity and fear of missing out) are positively associated with problematic IT use. The distal antecedents (IT use autonomy and involvement facilitation) are positively associated with the proximal antecedents except for the relationship between IT use autonomy and IT insecurity, which was found statistically non-significant. Furthermore, fear of missing out fully mediates the effect of IT use autonomy on problematic IT use, whereas IT insecurity and fear of missing out fully mediate the effects of involvement facilitation on problematic IT use.

The paper theoretically extends the understanding of problematic IT use and identifies novel its proximal and distal antecedents.

Purpose – In recent decades, some sociologists have turned to evolutionary biology, neuroscience, and cognitive science to support, modify, and reconfigure existing social psychological theory. In this chapter, we build on this momentum by considering the relevance of current work in affective and cognitive neuroscience for understanding emotions and the self. Our principal aim is to enlarge the range of phenomena currently considered by sociologists who study emotion while showing how affective dynamics play an important role across most outcomes and processes of interest to social scientists.

Approach – We focus on the ways external social objects become essential to, and emotionally significant for, the self. To that end, we draw on ideas from phenomenology, pragmatism, classic symbolic interactionism, and dramaturgy. We show how basic affective systems graft on, build from, and extend current social psychological usages of emotions as well as the important sociological work being done on self, from both symbolic interactionist (SI) and identity theory (IT) perspectives. Finally, we turn to the promising directions in studying emotional biographies and various aspects related to embodiment.

Findings – Affective systems consist of brain networks whose connections deepen when activated, with interesting variations observable at the neural, individual, and social levels in which one or more system is more salient than others. Affective systems may come to saturate the construction and maintenance of an autobiography or collective biography, with consequences for self-projection, self-other attunement, and embodied action. In turning to embodiment, however, we consider aspects of cognitive neuroscience that can contribute to ongoing work in neurosociology building on symbolic interactionism.

Practical Implications – The focus on affective systems suggests new research agendas in leveraging emerging neurosociological methods in the laboratory, while pushing for novel, naturalistic observational strategies. The latter, in particular, may be key to deepening sociology's contributions to neuroscience, better positioned to bring the full disciplinary toolkit to bear on these questions.

Social Implications – In considering the embodied and projective aspects of the self, we show how work examining convergence and divergence between embodied and linguistic pathways opens up new insights into how the self develops or acquires behavioral repertoires. As such, this chapter points to the need for holistic approach to understanding the social actor and, thereby, how political, economic, historical, and cultural factors shape self as much as biogenetic and psychological.

Originality of the Chapter – Sociologists think of emotions as either dependent or intervening variables: (1) signaling identity or situational incongruence, (2) states to be managed, and (3) structural dimensions of superordinate–subordinate relationships. Our integration of the theory of affective systems emphasizes the causal primacy emotions have over other behavioral and cognitive functions, clarifying how they play into the construction and maintenance of self and social experience.