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No significant differences in workload measures (p > 0.05) were observed in the four weeks leading up to each short trail competition; however, leading up to the long trail, ultra-trail medium, and ultra-trail long/extra-long competitions, the differences in the runners' workload measures were significant (p less then 0.05). In the short trail, pace was found to be moderately correlated with the ACWR of total distance (r = -0.334) and with training monotony of rate of perceived exertion (RPE) (r = -0.303). In the ultra-trail, a large correlation was observed between pace and elevation accumulated (r = 0.677). We concluded that significant workload differences from one week to the next only occurred in preparation for longer-distance competitions, with sudden acute load decreases and very low ACWR values reported mainly in weeks 1 and 2 of the taper. Meaningful relationships were found between performance (pace) and MAS for longer trails and between pace and MAS for ultra-trail competitions.Achieving the educational inclusion of students with special educational needs (SEN) is one of the significant challenges of the current Spanish educational system. This is a group of students with a high rate of bullying that leads to academic failure, as well as significant psychological and social consequences. Despite the fact that the behaviours and psychological characteristics of their peers seem to influence the degree of inclusion, there is no detail on this subject. Therefore, the aim of this paper is to determine the relationship between emotional intelligence, psychological flexibility, prosocial behaviour and inclusive behaviour. To carry out this study, a sample of 642 students between the ages of 12 and 19 years old participated and answered four questionnaires, one for each variable under study. The relationships established were extracted from different statistical analyses and a hypothesised predictive model. The results obtained revealed that emotional intelligence is positively related to psychological flexibility and prosocial behaviour and that these, in turn, are positively related to the development of inclusive behaviour. Therefore, the importance of considering the variables under study during the teaching-learning processes carried out in the classroom is highlighted.Morphological characteristics of any nanomaterial are critical in defining its properties. In this context, a method to control morphological parameters of polyaniline (PANI) has been investigated by producing its composite with gold nanoparticles (AuNPs). Herein, we report for the first time the successful control on the physical/chemical properties of PANI composites synthesized via interfacial polymerization through functionalization of its AuNP composite component with citrate, ascorbate, glutathione (GSH), and cetyl trimethyl ammonium bromide (CTAB). A significant difference in the polymerization pattern, morphologies, and electrical properties was recognized in these composites according to the functionality of the modified AuNPs. The obtained composites of AuNPs/PANI exhibited highly diverse morphologies (e.g., nodule, hollow hemisphere, flake, and spider-web galaxy type) and electrical characteristics according to functionalization. Hence, this study is expected to offer better insight into control of the polymerization pattern of AuNP/PANI composites and their associated properties.The cytoskeleton and its associated proteins present at the plasma membrane not only determine the cell shape but also modulate important aspects of cell physiology such as intracellular transport including secretory and endocytic pathways. Continuous remodeling of the cell structure and intense communication with extracellular environment heavily depend on interactions between cytoskeletal elements and plasma membrane. This review focuses on the plasma membrane-cytoskeleton interface in neurons, with a special emphasis on the axon and nerve endings. Raf inhibitor We discuss the interaction between the cytoskeleton and membrane mainly in two emerging topics of neurobiology (i) production and release of extracellular vesicles and (ii) local synthesis of new proteins at the synapses upon signaling cues. Both of these events contribute to synaptic plasticity. Our review provides new insights into the physiological and pathological significance of the cytoskeleton-membrane interface in the nervous system.Target tracking technology that is based on aerial videos is widely used in many fields; however, this technology has challenges, such as image jitter, target blur, high data dimensionality, and large changes in the target scale. In this paper, the research status of aerial video tracking and the characteristics, background complexity and tracking diversity of aerial video targets are summarized. Based on the findings, the key technologies that are related to tracking are elaborated according to the target type, number of targets and applicable scene system. The tracking algorithms are classified according to the type of target, and the target tracking algorithms that are based on deep learning are classified according to the network structure. Commonly used aerial photography datasets are described, and the accuracies of commonly used target tracking methods are evaluated in an aerial photography dataset, namely, UAV123, and a long-video dataset, namely, UAV20L. Potential problems are discussed, and possible future research directions and corresponding development trends in this field are analyzed and summarized.Deep learning models are widely employed in hyperspectral image processing to integrate both spatial features and spectral features, but the correlations between them are rarely taken into consideration. However, in hyperspectral mineral identification, not only the spectral and spatial features of minerals need to be considered, but also the correlations between them are crucial to further promote identification accuracy. In this paper, we propose hierarchical spatial-spectral feature extraction with long short term memory (HSS-LSTM) to explore correlations between spatial features and spectral features and obtain hierarchical intrinsic features for mineral identification. In the proposed model, the fusion spatial-spectral feature is primarily extracted by stacking local spatial features obtained by a convolution neural network (CNN)-based model and spectral information together. To better exploit spatial features and spectral features, an LSTM-based model is proposed to capture correlations and obtain hierarchical features for accurate mineral identification.