Understanding how anthropogenic environmental signals reorganize over time is central to Environmental Data Science, particularly because long-run emission trajectories reflect interacting technological, institutional, behavioral, and macroeconomic processes whose effects need not appear as smooth changes in level. This study develops a reproducible analytical framework that combines rolling spectral entropy with Bayesian change-point inference to examine structural transitions in annual transport-related CO2 emissions across the G7 economies from 1970 to 2023. The analysis adopts a structure-aware interpretation of the series while specifying what spectral entropy can and cannot establish in short annual windows. Entropy is interpreted as the concentration or dispersion of detrended within-window variability across resolvable Fourier components, rather than as a direct physical measure of resilience. The baseline window is $ W=10 $ years, with $ W=8 $ and $ W=12 $ used for sensitivity assessment. Country-specific Bayesian single-mean-shift models are estimated independently, and posterior means are reported together with 90% credible intervals and the shape of the complete posterior distribution. The results reveal recurrent entropy troughs and collapse-rate spikes in the early 1980s, around 1998–2000, and in the late 2000s. The late-1990s episode constitutes a conspicuous descriptive cross-country alignment, but the Bayesian evidence is heterogeneous: several countries exhibit broad or multimodal posteriors, so the analysis does not treat a common G7 change year as established. The recent-collapse calculation is interpreted in light of the exceptional COVID-19 shock. Overall, the evidence supports the value of spectral descriptors as exploratory indicators of changing temporal organization, provided that short-window frequency resolution, autocorrelation, transient shocks, and posterior uncertainty are made explicit.

Two examples of anionic complexes having vapochromic behavior are investigated: [K(H2O)][Pt(ppy)(CN)2] “Pt(ppy)” and [K(H2O)][Pt(bzq)(CN)2] “Pt(bzq)”, where ppy = 2-phenylpyridinate and bzq = 7,8-benzoquinolate. These monohydrate-potassium salts exhibit a change in color from purple to yellow [Pt(ppy)] and from red to yellow [Pt(bzq)] upon heating to 110 °C, and they transform back into the original color upon absorption of water molecules from the environment. Available only in the form of polycrystalline samples, no structural information on such compounds is accessible, due to highly overlapping peaks in powder diffraction profiles. We use in situ Pair Distribution Function measurements on powder samples to investigate the dynamics of the structural changes induced by temperature variations. By means of a multivariate approach, we were able to extract dynamic structural information from collected profiles without using prior knowledge on the static crystal structure of the compounds. The critical temperature and the characteristics of the vapochromic transition have been identified, as well as the main structural changes causing it.

Evidence is emerging that the role of protein structure in disease needs to be rethought. Sequence mutations in proteins are often found to affect the rate at which a protein switches between structures. Modeling structural transitions in wildtype and variant proteins is central to understanding the molecular basis of disease. This paper investigates an efficient algorithmic realization of the stochastic roadmap simulation framework to model structural transitions in wildtype and variants of proteins implicated in human disorders. Our results indicate that the algorithm is able to extract useful information on the impact of mutations on protein structure and function.

The cauliflower mosaic virus (CaMV) 35 S RNA functions as both messenger and pregenomic RNA under the control of its 600-nt leader, which contains regulatory elements involved in splicing, polyadenylation, translation, reverse transcription, and packaging. We have recently documented that the 35 S RNA leader adopts an elongated hairpin conformation and additional higher-order structures, a long-range pseudoknot and a dimer. Alternative structures might coexist, probably fulfilling specialized functions. In this paper, we analyze the biological significance of the elongated hairpin structure. We have introduced a spectrum of large deletions and small substitutions in the 35 S RNA leader and characterized their impact on the structure by temperature gradient gel electrophoresis. This analysis showed that the elongated hairpin consists of three sections of different stability (stem section I, II, and III). The overall secondary structure is relatively stable in the range of 10–32°C. It melts between 32 and 38°C in a manner indicating that the most stable base pairing occurs at the base of the elongated hairpin (stem section I). Mutations that destabilize stem section I decrease both the melting temperature of the leader and the expression in vitro and in vivo of the downstream CAT-reporter gene. Compensatory mutations restoring the stable elongated hairpin upregulate the translation efficiency. Our results demonstrate that the regulation of translation of the CaMV 35 S RNA is mediated by a stable hairpin in the leader.