Stimuli-responsive, smart, or intelligent polymers are materials that significantly change their physical or chemical properties when there is a small change in the surrounding environment due to either internal or external stimuli. In the last two decades or so, there has been tremendous growth in the strategies to develop various types of stimuli-responsive polymer (SRP) materials/systems that are suitable for various fields, including biomedical, material science, nanotechnology, biotechnology, surface and colloid sciences, biochemistry, and the environmental field. The wide acceptability of SRPs is due to their availability in different architectural forms such as scaffolds, aggregates, hydrogels, pickering emulsions, core-shell particles, nanogels, micelles, membranes, capsules, and layer-by-layer films. The present review focuses on different types of SRPs, such as physical, chemical, and biological, and various important applications, including controlled drug delivery (CDD), stabilization of colloidal dispersion, diagnostics (sensors and imaging), tissue engineering, regenerative medicines, and actuators. The applications of SRPs have immense potential in various fields, and the author hopes these polymers will add a new field of applications through new concepts.

Research on community resilience has been ongoing for decades. Several studies have been carried out on resilience in different groups and contexts. However, few address the relationship between community resilience and depopulated rural areas. This study aims to dig deeper into this, considering the concrete impact of population decline in Spain. We carried out a systematic review of the most relevant contributions. A search protocol was developed and used to consult ten databases. Different combinations of terms such as ‘community resilience’, ‘rural’, and ‘depopulation’, or related terms, were used. 22 scientific texts were analysed. We obtained a set of publications that demonstrate the heterogeneity of research methods, approaches and analytical processes applied to the study of this relationship. A mostly qualitative approach was observed, either as the main technique or complementary to documentary reviews. The results underscore the complex nature of rural depopulation and related constructs. It emphasizes the specific importance of community resilience in these territories in terms of social capital, endogenous resources, sustainability, economic dynamism, local responsibility and effective governance. The findings identify a scarce mention to social intervention professions, which should have a more important role due to their core values. In the studies reviewed, it appears as an emerging and scientifically relevant area to explore, both for investigation and intervention purposes. The strength of a multidisciplinary approach to addressing the phenomena appears in the discussion as a main potential line of research.

The study of authoritarian leadership has undergone significant development, with researchers exploring its different dimensions and consequences. This leadership style, characterized by a top-down approach and centralized decision-making authority, has been extensively examined in psychology, organizational behavior, and management literature. Scholars have delved into the effects of authoritarian leadership on various aspects of organizations such as employee satisfaction, motivation levels, productivity rates, turnover rates, and team dynamics. The research landscape surrounding authoritarian leadership has witnessed a recent surge in interest as scholars strive to understand its intricate connections with different variables. The primary objective of this study is to conduct a comprehensive bibliometric analysis on authoritarian leadership, aiming to identify the key research areas, influential authors, prominent journals in the field, and citation patterns. To our knowledge, no bibliometric analysis on authoritarian leadership can be found in the Scopus database, highlighting the novelty of our research. Through a source-based examination of scholarly articles and their citations pertaining to authoritarian leadership, this analysis offers valuable insights into the current state of research in this domain. By focusing on publications from the past decade onwards, we aim to uncover trends and potential gaps within existing literature while also providing guidance for future research endeavors. Our research findings will provide valuable insights into the phenomenon of authoritarian leadership, contributing to a deeper understanding of its implications. By delving into this topic, we hope to pave the way for future studies and investigations in this field that can build upon our findings and expand knowledge even further.

Three-dimensional (3D) bioprinting is a promising technological approach for various applications in the biomedical field. Natural polymers, which comprise the majority of 3D printable “bioinks”, have played a crucial role in various 3D bioprinting technologies during the layered 3D manufacturing processes in the last decade. However, the polymers must be customized for printing and effector function needs in cancer, dental care, oral medicine and biosensors, cardiovascular disease, and muscle restoration. This review provides an overview of 3D bio-printed natural polymers—commonly employed in various medical fields—and their recent development.

The paper deals with the issues of the influence of forest cover on the average annual runoff of rivers in the Pripyat River basin. In the study area, under the influence of solar radiation, the temperature of the air and the soil surface increases, evaporation from the water surface also increases, and the moisture content of the upper layers of the soil decreases. In general, with an increase in forest cover, the annual layer of the runoff of the studied rivers increases, as well as with an increase in the amount of precipitation (in contrast to the runoff of short-term floods). However, with a forest cover of more than 20%–30% and a relatively small amount of precipitation, the runoff decreases, which is associated with the retention of part of the precipitation by the forest cover. With a large amount of precipitation and low forest cover, the runoff also decreases, which is probably due to the loss of precipitation water for evaporation, etc. The conducted studies show that, just as the forest affects water resources, the flow of moisture to watersheds also affects the state of forest systems. Moreover, this interaction is expressed by evaporation from forests. Under influence of change of a climate growth of evaporation is observed.

Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.