Free energy determination of phase coexistence in model C60: A comprehensive Monte Carlo study

The free energy of the solid and fluid phases of the Girifalco C60 model are determined through extensive Monte Carlo simulations. In this model the molecules interact through a spherical pair potential, characterized by a narrow and attractive well, adjacent to a harshly repulsive core. We have used the Widom test particle method and a mapping from an Einstein crystal, in order to estimate the absolute free energy in the fluid and solid phases, respectively; we have then determined the free energy along several isotherms, and the whole phase diagram, by means of standard thermodynamic integrations. We highlight how the interplay between the liquid-vapor and the liquid-solid coexistence conditions determines the existence of a narrow liquid pocket in the phase diagram, whose stability is assessed and confirmed in agreement with previous studies. In particular, the critical temperature follows closely an extended corresponding-states rule recently outlined by Noro and Frenkel [J. Chem. Phys. 113:2941 (2000)]. We discuss the emerging "energetic" properties of the system, which drive the phase behavior in systems interacting through short-range forces [A. A. Louis, Phil. Trans. R. Soc. A 359:939 (2001)], in order to explain the discrepancy between the predictions of several structural indicators and the results of full free energy calculations, to locate the fluid phase boundaries. More generally, we aim to provide extended reference data for calculations of the free energy of the C60 fullerite in the low temperature regime, as for the determination of the phase diagram of higher order fullerenes and other fullerene-related materials, whose description is based on the same model adopted in this work.Comment: RevTeX, 11 pages, 9 figure

Upgrading of Resolution Elastic Neutron Scattering (RENS)

An update of the Resolution Elastic Neutron Scattering (RENS) approach consisting in measuring the elastically scattered neutron intensity versus the instrumental energy resolution is presented. In particular it is shown that the measured elastic scattering law as a function of the logarithm of the instrumental energy of resolution gives rise to an increasing sigmoid trend whose inflection point can be connected with the system relaxation time. The validity of the RENS approach is supported by a numerical simulation, taking into account a Gaussian resolution function and a Lorentzian scattering law, and experimentally by integrated EINS and QENS measurements performed as a function of temperature on three homologous disaccharide/water mixtures showing different relaxation times. Furthermore, the most important advantages of the RENS approach are discussed; in particular, in comparison with QENS, the RENS approach requires a smaller amount of sample, which is an important point in dealing with biological and exotic systems, is not affected by the use of model functions for fitting spectra, and furnishes a direct access to the system relaxation time

Theory and simulation of short-range models of globular protein solutions

We report theoretical and simulation studies of phase coexistence in model globular protein solutions, based on short-range, central, pair potential representations of the interaction among macro-particles. After reviewing our previous investigations of hard-core Yukawa and generalised Lennard-Jones potentials, we report more recent results obtained within a DLVO-like description of lysozyme solutions in water and added salt. We show that a one-parameter fit of this model based on Static Light Scattering and Self-Interaction Chromatography data in the dilute protein regime, yields demixing and crystallization curves in good agreement with experimental protein-rich/protein-poor and solubility envelopes. The dependence of cloud and solubility points temperature of the model on the ionic strength is also investigated. Our findings highlight the minimal assumptions on the properties of the microscopic interaction sufficient for a satisfactory reproduction of the phase diagram topology of globular protein solutions.Comment: 17 pages, 8 figures, Proc. of Conference "Structural Arrest Transitions in Colloidal Systems with Short-Range Attractions", Messina (ITALY) 17-20 December 200

Theoretical description of phase coexistence in model C60

We have investigated the phase diagram of the Girifalco model of C60 fullerene in the framework provided by the MHNC and the SCOZA liquid state theories, and by a Perturbation Theory (PT), for the free energy of the solid phase. We present an extended assessment of such theories as set against a recent Monte Carlo study of the same model [D. Costa et al, J. Chem. Phys. 118:304 (2003)]. We have compared the theoretical predictions with the corresponding simulation results for several thermodynamic properties. Then we have determined the phase diagram of the model, by using either the SCOZA, or the MHNC, or the PT predictions for one of the coexisting phases, and the simulation data for the other phase, in order to separately ascertain the accuracy of each theory. It turns out that the overall appearance of the phase portrait is reproduced fairly well by all theories, with remarkable accuracy as for the melting line and the solid-vapor equilibrium. The MHNC and SCOZA results for the liquid-vapor coexistence, as well as for the corresponding critical points, are quite accurate. All results are discussed in terms of the basic assumptions underlying each theory. We have selected the MHNC for the fluid and the first-order PT for the solid phase, as the most accurate tools to investigate the phase behavior of the model in terms of purely theoretical approaches. The overall results appear as a robust benchmark for further theoretical investigations on higher order C(n>60) fullerenes, as well as on other fullerene-related materials, whose description can be based on a modelization similar to that adopted in this work.Comment: RevTeX4, 15 pages, 7 figures; submitted to Phys. Rev.

Mycobacterium tuberculosis Drives Expansion of Low-Density Neutrophils Equipped With Regulatory Activities

In human tuberculosis (TB) neutrophils represent the most commonly infected phagocyte but their role in protection and pathology is highly contradictory. Moreover, a subset of low-density neutrophils (LDNs) has been identified in TB, but their functions remain unclear. Here, we have analyzed total neutrophils and their low-density and normal-density (NDNs) subsets in patients with active TB disease, in terms of frequency, phenotype, functional features, and gene expression signature. Full-blood counts from Healthy Donors (H.D.), Latent TB infected, active TB, and cured TB patients were performed. Frequency, phenotype, burst activity, and suppressor T cell activity of the two different subsets were assessed by flow cytometry while NETosis and phagocytosis were evaluated by confocal microscopy. Expression analysis was performed by using the semi-quantitative RT-PCR array technology. Elevated numbers of total neutrophils and a high neutrophil/lymphocyte ratio distinguished patients with active TB from all the other groups. PBMCs of patients with active TB disease contained elevated percentages of LDNs compared with those of H.D., with an increased expression of CD66b, CD33, CD15, and CD16 compared to NDNs. Transcriptomic analysis of LDNs and NDNs purified from the peripheral blood of TB patients identified 12 genes differentially expressed: CCL5, CCR5, CD4, IL10, LYZ, and STAT4 were upregulated, while CXCL8, IFNAR1, NFKB1A, STAT1, TICAM1, and TNF were downregulated in LDNs, as compared to NDNs. Differently than NDNs, LDNs failed to phagocyte live Mycobacterium tuberculosis (M. tuberculosis) bacilli, to make oxidative burst and NETosis, but caused significant suppression of antigen-specific and polyclonal T cell proliferation which was partially mediated by IL-10. These insights add a little dowel of knowledge in understanding the pathogenesis of human TB

Management parameters from the random regressions testday model to advic farmers on cow nutrition

Accurate monitoring and adequate planning of activities at modern dairy farms are important to improve farm profitability. The aim of this study was to investigate the use of test-day information to support farmers in management of Sicilian dairy herds. To this purpose, a test-day random regression model was developed for the analysis of production data of Sicilian dairy herds. Highest between-herd variation found in the variance components analysis using the test day model showed clear evidence of benefits in using a random regression TD model for management improvement. To identify sources of variation able to explain differences between herds in milk and milk components production herd curves, a field study was conducted in Southern Italy (Ragusa province) where diets and chemical composition of the diet was collected at herd level (every 3 months) and testday milk yield records at individual cow level (every month). Data collection was performed from March 2006 through December 2008 on 40 cooperating farms. Animal breed, feeding system, and total mixed ration chemical composition were identified to influence between-herd variation. At the individual cow level, test day model was further used to investigate the production response to changes in chemical and physical composition of diets in Ragusa province. Starch had the greatest effect on milk, fat, and protein production when crude protein and neutral detergent fiber contents were at a high and low value, respectively. Effects of a nutrition component on production changed when the other nutrients were included in the model, suggesting the confounding response one can have when multiple nutrients are not accounted for. </p

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example

Discussion about the Latest Findings on the Possible Relation between Air Particulate Matter and COVID-19

Since SARS-CoV-2 was identified, the scientific community has tried to understand the variables that can influence its spread. Several studies have already highlighted a possible link between particulate matter (PM) and COVID-19. This work is a brief discussion about the latest findings on this topic, highlighting the gaps in the current results and possible tips for future studies. Based on the literature outcomes, PM is suspected to play a double role in COVID-19: a chronic and an acute one. The chronic role is related to the possible influence of long-term and short-term exposure to high concentrations of PM in developing severe forms of COVID-19, including death. The acute role is linked to the possible carrier function of PM in SARS-CoV-2. The scientific community seems sure that the inflammatory effect on the respiratory system of short-term exposure to a high concentration of PM, and other additional negative effects on human health in cases of longer exposure, increases the risk of developing a more severe form of COVID-19 in cases of contagion. On the contrary, the results regarding PM acting as a carrier of SARS-CoV-2 are more conflicting, especially regarding the possible inactivation of the virus in the environment, and no final explanation on the possible acute role of PM in the spread of COVID-19 can be inferred