Ground source heat pump (GSHP) is an innovative and perspective technology able to use the ground as a thermal sink or heat source. If combined with system operating at relatively low temperature, it represents a high efficiency solution for the heating of buildings. Complementarily, during cooling operation it has a good advantage with respect to air-cooled systems, because the ground temperature is stably lower than the outdoor air one. Geothermal heat pump systems are able to reduce the environmental impact of buildings for space heating and cooling by using the ground as an energy renewable source. This paper presents a review on the GSHP systems presenting both a summary of different ground-source typologies of heat pumps and a thermodynamic approach for their modeling. The irreversible thermodynamic approach is here summarized and exposed for a complete GSHPs system. This analytical approach is particularly useful for implementing an optimization design tool for GSHP systems. Recently many works have 2 been published about exergy analysis of these systems. Those works suggest that future lines of development may be considered: a) the optimization based on the transient performance of GSHP systems and not on the sole design condition; b) the integration of irreversible thermodynamic optimization approach into the algorithms of control systems. The diffusion of optimized GSHP systems is essential in order to reduce fossil fuel consumption and CO 2 emissions, complying with the EU's directive.

The extremely low frequency electromagnetic stimulation selective for cancer cells elicits growth arrest through a metabolic shift.

To date, the choice of the characteristics of the extremely low-frequency electromagnetic field beneficial in proliferative disorders is still empirical. In order to make the ELF interaction selective, we applied the thermodynamic and biochemical principles to the analysis of the thermo-chemical output generated by the cell in the environment. The theoretical approach applied an engineering bio-thermodynamic approach recently developed in order to obtain a physical-mathematical model that calculated the frequency of the field able to maximize the mean entropy changes as a function of cellular parameters. The combined biochemical approach envisioned the changes of entropy as a metabolic shift leading to a reduction of cell growth. The proliferation of six human cancer cell lines was evaluated as the output signal able to confirm the correctness of the mathematical model. By considering the cell as a reactive system able to respond to the unbalancing external stimuli, for the first time we could calculate and validate the frequencies of the field specifically effective on distinct cells.

A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while their tail obeys the Pareto power law. The recently introduced $$\kappa $$ κ -statistics framework predicts distribution functions with this feature. A growing number of applications in different fields of investigation are beginning to prove the relevance and effectiveness of $$\kappa $$ κ -statistics in fitting empirical data. In this paper, we use $$\kappa $$ κ -statistics to formulate a statistical approach for epidemiological analysis. We validate the theoretical results by fitting the derived $$\kappa $$ κ -Weibull distributions with data from the plague pandemic of 1417 in Florence as well as data from the COVID-19 pandemic in China over the entire cycle that concludes in April 16, 2020. As further validation of the proposed approach we present a more systematic analysis of COVID-19 data from countries such as Germany, Italy, Spain and United Kingdom, obtaining very good agreement between theoretical predictions and empirical observations. For these countries we also study the entire first cycle of the pandemic which extends until the end of July 2020. The fact that both the data of the Florence plague and those of the Covid-19 pandemic are successfully described by the same theoretical model, even though the two events are caused by different diseases and they are separated by more than 600 years, is evidence that the $$\kappa $$ κ -Weibull model has universal features.

The aim of this work was to evaluate differences in energy flows between normal and immortalized cells when these distinct biological systems are exposed to environmental stimulation. These differences were considered using a constructal thermodynamic approach, and were subsequently verified experimentally. The application of constructal law to cell analysis led to the conclusion that temperature differences between cells with distinct behaviour can be amplified by interaction between cells and external fields. Experimental validation of the principle was carried out on two cellular models exposed to electromagnetic fields. By infrared thermography we were able to assess small changes in heat dissipation measured as a variation in cell internal energy. The experimental data thus obtained are in agreement with the theoretical calculation, because they show a different thermal dispersion pattern when normal and immortalized cells are exposed to electromagnetic fields. By using two methods that support and validate each other, we have demonstrated that the cell/environment interaction can be exploited to enhance cell behavior differences, in particular heat dissipation. We propose infrared thermography as a technique effective in discriminating distinct patterns of thermal dispersion and therefore able to distinguish a normal phenotype from a transformed one.

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The exergetic analysis of the biosystems is developed. It takes into account that cells are able to convert only part of the energy absorbed. The result is to highlight the fundamental role of the exergy as a quantity useful to develop considerations on the cells behavior in relation to normal or disease states.