Lately, random telegraph noise (RTN) has been deemed, via specific mathematical metrics, to be possibly deterministic-chaotic rather than stochastic, with severe implications for applications that leverage the RTN stochastic nature. Yet, this was claimed by analyzing a limited number of RTN traces. Here, we analyze several RTN traces measured in different devices and conditions, mathematically generated traces and traces resulting from advanced simulations of RTN in metal-insulator-metal (MIM) structures. It is shown that the mathematical metrics employed to reveal the deterministic-chaotic nature of RTN are not robust enough to support that claim. Complex RTN is likely to result from inherently stochastic processes embedded in a deterministic multi-body system which could show stochastic chaos, but hardly any determinism.

In this brief note, we critically examine the common interpretation that an increase in thermal entropy corresponds to an increase in disorder. We argue that it is preferable to adhere strictly to the mathematical definitions of thermal entropy to avoid misconceptions because the interpretation of disorder is subjective and context-dependent. Furthermore, we highlight a similar ambiguity surrounding information entropy, which is inherently subjective just like the related disorder.

In this paper, the reflected Mckean-Vlasov equations with regime-switching over a convex domain is studied for the first time. We first establish the well-posedness of stochastic differential equations with regime-switching by using fixed point Theorem. Then, by using coupling method, the propagation of chaos for the particle system is also obtained.

Fiscal policy fluctuations have significant economic and environmental impacts. However, the environmental impacts of fiscal policy fluctuations across time and quantiles are not well established. Therefore, we investigate the impact of fiscal policy fluctuations on environmental sustainability, proxied by carbon emissions, in the case of China. To investigate the impact of fiscal policy across different levels of intensity is the core ambition. The wavelet quantile regression method has been employed to meet this end. The findings from wavelet quantile regression delineate that positive fluctuations in fiscal policy (i.e., expansionary fiscal policy) promote emissions across quantiles and time. The negative fluctuations in fiscal policy (i.e., contractionary fiscal policy) are responsible for a decrease in emissions. We propose to take measures to offset the critical environmental impacts of positive fluctuations in fiscal policy. These measures may include channelizing the government spending in sustainable sectors as well as the promotion of services sector to extend economic growth objectives while containing emissions.

Although human dynamics exhibit scale-independent properties, different results have emerged from the statistical analyses of various actigraphic or mobility datasets regarding the characterization of their heavy-tailed distributions. By applying approaches from significant studies of this nature of human locomotor activity on our multi-day long acceleration dataset, we examine how the non-standardised activity determination methods and the separation of the resulting activity data into active and passive periods affect the conclusions. We also show that the statistical or model fitting approaches commonly used to study these periods not only influence the results but are also highly sensitive to the actigraphic methodology employed. In contrast, the differently derived activity data – and even the underlying acceleration signals – measured on the wrist, follow universal 1/f noise-based spectral characteristics that have also been previously observed in the context of human spatial motion, thus offering the possibility of a more robust analysis of scale-independence.

Traditional attempts to extend the Nyquist–Johnson formula for thermal fluctuations to non-linear dissipative elements have led to thermodynamically inconsistent models. In this work, we present a Langevin model for thermal noise in non-linear dissipative elements, that is fully consistent with the main requirements of thermodynamics. The model accurately predicts the Gibbs (Maxwell–Boltzmann) distribution at thermal equilibrium and ensures zero expected voltages and currents, thereby resolving the well-known Brillouin’s paradox and confirming compliance with the second law of thermodynamics.

Low-frequency noise (10[Formula: see text]Hz–20[Formula: see text]kHz) and electrical resistivity characteristics of hybrid composites with multi-walled carbon nanotubes (MWCNT) and carbon-coated nickel (Ni@C) were investigated to identify the characteristics of charge carrier transport. Electrical fluctuations in the investigated composite materials are comprised mainly of 1/f type components. In hybrid MWCNT/Ni@C composites, the optimal concentration of Ni@C, where composite resistivity is lowest, is found to be 0.2[Formula: see text]vol.% Ni@C. The resistivity of single-filler Ni@C composites generally increases with temperature. The resistivity dependence on temperature of composites containing MWCNT varies depending on the Ni@C concentration, with suboptimal concentrations of Ni@C resulting in increased resistivity and thermal instability. In composites containing MWCNT and 0 or 0.2 vol.% of Ni@C, Arrhenius’ thermal activation is observed as the dominant charge carrier transfer mechanism in the temperature range of 75–184[Formula: see text]K, with activation energies of approximately 37.7 and 36.13[Formula: see text]meV, respectively.

Highly sensitive high-speed biosensors are key devices for precise diagnostics, which allows the application of medical treatment in a short time. In this paper, noise spectra and characteristic time constants are studied in nanotransistors with channel sizes below 30[Formula: see text]nm. The quantization effect due to the formation of a quantum dot channel is analyzed based on the transport and noise properties of the device structures. Ultra-low flicker noise at the quantum level with a Hooge parameter of about 10[Formula: see text] is registered. A strong dependence of the characteristic switching time on the modulation effect is revealed with a slope ([Formula: see text]) that considerably exceeds the value of 1, which is typically obtained in large-area device structures. This reflects the fact that a 700% amplification of sensitivity in nanotransistor biosensors can be obtained. A dimensionless R-factor introduced by the ratio of the emission time constant to the capture time constant as a function of gate voltage reveals a slope equal to 20, which is promising for the extraction of very small signals from biomolecules with 20 times higher sensitivity.

In this paper, we investigate quantum and quantum-relativistic effects associated with the noise power spectrum and the fluctuation-dissipation relation between current-noise spectra and linear-response conductance at low frequencies of the electromagnetic field. At high frequencies, vacuum catastrophe is shown to be avoided by the presence of Casimir force. At low frequencies, the quantum effect associated with one-dimensional structures under the conditions of ballistic transport typical at the nanometric scale length is briefly reviewed in terms of a universal quasi-particle approach. The case of a photon gas inside an appropriate black-body cavity is found to provide a physical interpretation of the lines spectra of atomic elements within an exact statistical approach based on a physical interpretation of the fine structure constant, [Formula: see text].

The USA has been confronting climate change due to the overuse of non-renewable energy sources. In this scenario, the energy transition from non-renewables to renewable energy is indispensable. Numerous studies in the literature have analyzed the relationship between green finance (GF) and clean energy sources. At the same time, minimal attention has been given to non-renewable energy production, specifically across different financial market conditions. GF is an effective instrument that can expedite energy transition. Therefore, this study examines whether GF fluctuations impact non-renewable energy production (NREP). The study uses the time series dataset of the USA covering the period 1985M1-2020M12. The findings of the quantile-on-quantile regression (QQR) approach explain that positive GF fluctuations decrease NREP across quantiles. The negative fluctuations in GF promote NREP across the quantiles of both variables. The findings directly contribute to achieving the United Nations Sustainable Development Goals (SDGs), specifically those related to affordable and clean energy (SDGs-7) and Climate action (SDGs-13). Based on the findings, the study put forward relevant policy recommendations to promote clean energy transition in the USA.