This report examines the historiography of social struggles in Republican Brazil from 1889 to 1989, analysing how different theoretical frameworks have shaped our understanding of labour movements, peasant resistance, and urban social mobilisation. The study traces the evolution from traditional labour history to more nuanced approaches incorporating gender, race, and everyday resistance, demonstrating how historiographical debates have reflected broader transformations in Brazilian society and academic discourse.

Molecular electronic transitions represent fundamental quantum mechanical processes that govern the interaction between electromagnetic radiation and molecular systems, determining crucial properties such as colour, photochemical reactivity, and spectroscopic behaviour. This comprehensive review examines the theoretical foundations, computational methodologies, and contemporary applications of molecular electronic transitions, with particular emphasis on recent advances in time-dependent density functional theory (TD-DFT) and experimental techniques. The quantum mechanical framework underlying electronic transitions is explored through detailed mathematical formulations, including the Born-Oppenheimer approximation, transition dipole moments, and selection rules.

This comprehensive article examines the transformative potential of pulse neural networks (PNNs) as we stand at a critical juncture in neuromorphic computing. Drawing upon recent breakthroughs in spike-timing-dependent plasticity, event-driven processing architectures, and bio-inspired learning algorithms, we delineate the trajectory of PNN development over the coming decade. The analysis identifies five pivotal areas poised for revolutionary advancement: the integration of multi-timescale dynamics, the development of hybrid architectures combining pulse-based computation with conventional deep learning paradigms, the emergence of self-organising criticality in large-scale PNN systems, novel training methodologies that transcend the limitations of backpropagation through time, and the potential for PNNs to achieve true continual learning without catastrophic forgetting.

This integrative review synthesizes contemporary understanding of neural-hormonal integration, examining molecular mechanisms, evolutionary adaptations, and technological innovations reshaping the field of neuroendocrine homeostasis.

The evolution of nervous systems represents one of the most remarkable achievements in biological complexity, spanning from simple nerve nets in early metazoans to the sophisticated neural architectures observed in contemporary organisms. This comprehensive review examines the evolutionary trajectory of nervous systems, beginning with the fundamental origins of neurons and progressing through the development of centralised neural networks.

Background: We explore the biophysical mechanisms underlying neuronal communication, including the establishment and maintenance of membrane potentials, the generation and propagation of action potentials, and the diverse forms of synaptic transmission.

Methods: Particular attention is devoted to the mathematical frameworks that describe these processes, notably the Hodgkin-Huxley model and its derivatives, which provide quantitative insights into neural dynamics.

Results: A central focus is placed upon the concept of the tripartite synapse, which incorporates glial cells as active participants in synaptic function, fundamentally altering our understanding of neural communication from a bipartite to a tripartite model.