Kinetic Trapping of Charge-Transfer Molecules at Metal Interfaces

Despite the common expectation that conjugated organic molecules on metals adsorb in a flat-lying layer, several recent studies have found coverage-dependent transitions to upright-standing phases, which exhibit notably different physical properties. In this work, we argue that from an energetic perspective, thermodynamically stable upright-standing phases may be more common than hitherto thought. However, for kinetic reasons, this phase may often not be observed experimentally. Using first-principles kinetic Monte Carlo simulations, we find that the structure with lower molecular density is (almost) always formed first, reminiscent of Ostwald's rule of stages. The phase transitions to the upright-standing phase are likely to be kinetically hindered under the conditions typically used in surface science. The simulation results are experimentally confirmed for the adsorption of tetracyanoethylene on Cu(111) using infrared and X-ray photoemission spectroscopy. Investigating both the role of the growth conditions and the energetics of the interface, we find that the time for the phase transition is determined mostly by the deposition rate and, thus, is mostly independent of the nature of the molecule.

Workplace health promotion: results of a combined multidisciplinary intervention over a long period - preliminary results

OBJECTIVE

Obesity is a multifactorial disease that is one of the major public health problems. It is the result of the interaction between behavioral, social and endocrine-metabolic components. Already in the 80s, it was highlighted by the World Health Organization (WHO) that the workplace is an ideal setting for introducing health promotion programs. The aim of the present study was to implement a health promotion program among healthcare workers (HCWs) operating in an Emergency Hospital in Southern Italy, combining diet, sports activity and motivational support over a 24-month period.

PATIENTS AND METHODS

Participants were HCWs operating in an Emergency Hospital in Southern Italy. The inclusion criteria were as follows: overweight or obesity, i.e., body mass index (BMI) >25 kg/m2, or waist circumference >102 cm (males), >88 cm (females); dyslipidemia without pharmacological treatment, i.e., total cholesterol >220 mg/dL, or high-density lipoprotein (HDL) cholesterol <35 mg/dL, or low-density lipoprotein cholesterol (LDL) >130 mg/dL, or triglycerides >200 mg/dL; fasting glucose levels >120 mg/dl and/or reduced tolerance to glucose or diabetes mellitus, without pharmacological treatment was determined through HbA1c.

RESULTS

The analysis was conducted on 36 participants. Follow-up was performed after twelve (T12) and twenty-four months (T24). The average systolic blood pressure (SBP) and diastolic blood pressure (DBP) values decreased during the time period. The average BMI of both male and female HCWs was significantly reduced from T0 to T12 and from T0 to T24. The triglyceride levels gradually decreased, but not significantly, from T0 to T24. The average blood glucose values decreased from T0 to T12 and from T12 to T24. The number of subjects who started to perform physical activity increased significantly between T0 and T12 and between T0 and T24.

CONCLUSIONS

The findings have led to a significant change in HCWs' lifestyles and body perceptions, as well as their ability to work.

Efficient global sensitivity analysis of kinetic Monte Carlo simulations using Cramérs-von Mises distance

Typically, the parameters entering a physical simulation model carry some kind of uncertainty, e.g., due to the intrinsic approximations in a higher fidelity theory from which they have been obtained. Global sensitivity analysis (GSA) targets quantifying which parameter uncertainties impact the accuracy of the simulation results, e.g., to identify which parameters need to be determined more accurately. We present a GSA approach based on the Cramérs-von Mises distance. Unlike prevalent approaches, it combines the following properties: (i) it is equally suited for deterministic as well as stochastic model outputs, (ii) it does not require gradients, and (iii) it can be estimated from numerical quadrature without further numerical approximations. Using quasi-Monte Carlo for numerical integration and a first-principles kinetic Monte Carlo model for the CO oxidation on RuO2(110), we examine the performance of the approach. We find that the results agree very well with what is known in the literature about the sensitivity of this model and that the approach converges in a modest number of quadrature points. Furthermore, it appears to be robust against even extreme relative noise. All these properties make the method particularly suited for expensive (kinetic) Monte Carlo models because we can reduce the number of simulations as well as the target variance of each of these.

A fuzzy classification framework to identify equivalent atoms in complex materials and molecules

The nature of an atom in a bonded structure-such as in molecules, in nanoparticles, or in solids, at surfaces or interfaces-depends on its local atomic environment. In atomic-scale modeling and simulation, identifying groups of atoms with equivalent environments is a frequent task, to gain an understanding of the material function, to interpret experimental results, or to simply restrict demanding first-principles calculations. However, while routine, this task can often be challenging for complex molecules or non-ideal materials with breaks in symmetries or long-range order. To automatize this task, we here present a general machine-learning framework to identify groups of (nearly) equivalent atoms. The initial classification rests on the representation of the local atomic environment through a high-dimensional smooth overlap of atomic positions (SOAP) vector. Recognizing that not least thermal vibrations may lead to deviations from ideal positions, we then achieve a fuzzy classification by mean-shift clustering within a low-dimensional embedded representation of the SOAP points as obtained through multidimensional scaling. The performance of this classification framework is demonstrated for simple aromatic molecules and crystalline Pd surface examples.

P140 EFFICACY AND SAFETY OF CHEMOTHERAPY CONTAINING NON–PEGYLATED LIPOSOMAL DOXORUBICIN IN PATIENTS AT HIGH CARDIOVASCULAR RISK: A SINGLE–CENTER EXPERIENCE

 

Anthracyclines represent the most effective chemotherapeutic agent in the treatment of non–Hodgkin‘s lymphoma (NHL), although their use is limited due to the risk of cardiac toxicity. This occurs mainly in elderly patients, those with a history of cardiovascular (CV) disease and/or multiple concomitant risk factors. Liposomal doxorubicin has been shown to reduce this toxicity. The aim of this retrospective study is to investigate the use of non–pegylated liposomal doxorubicin in high–risk patients in terms of haematological response rate and CV events. In a single centre, 15 patients undergoing R–COMP regimen (Rituximab, Prednisone, Cyclophosphamide, Vincristine, Myocet liposomal doxorubicin) were consecutively collected from January 2020 to December 2021. The mean age of patients was 73.9 years and 60% were male. The baseline mean left ventricular ejection fraction (LVEF) was 55.9%; four patients had a baseline FE of &lt; 50%, two of them had a severe reduction in LVEF. Among all patients, 86.7% had systemic hypertension, 40% diabetes mellitus, 46.7% dyslipidaemia and 20% a family history of CV disease. Moreover, 46.7% of patients had at least two concomitant risk factors and 20% at least three. 20% had a history of ischemic heart disease, 13.3% had previous exposure to anthracyclines and 20% with mediastinal radiotherapy; 26.7% had moderate to severe aortic valvulopathy. According to the joint Cardio–Oncology evaluation, 100% of patients had been considered unsuitable for conventional doxorubicin.. More than 85% of the cases were already on cardioactive therapy at baseline evaluation and 66.7% required titration or modification during chemotherapy. With R–COMP, the whole population was able to finish treatment achieved complete haematological remission. The mean LVEF at the end of treatment was 55.8% (p = 0.814).

Conclusions

Our results support the efficacy and safety of R–COMP in a population at high risk for cardiac events, otherwise excluded from anthracycline–containing therapy. Liposomal formulatio reduces doxorubicin cardiomyocyte accumulation and thus toxicity, providing the best possible treatment for the majority of the onco–haematological population.

P351 “HOLDING AREA AND SHORT STAY HOSPITAL: A NEW MODEL OF ORGANIZATION

In A.O. San Camillo–Forlanini, dedicated “Holding Areas” (HA) are active. They enable a rapid allocation of patients (pts), avoiding their long stay in the Emergency Department (ER) and therefore reducing the overcrowding. Moreover they allow the optimization of diagnosis and care, thanks to the direct management of specialists and reduce improper hospitalizations. Our HA is committed to receive (except on weekends) 3 pts/day destined to hospitalization in Cardiology. Here the patients are re–examined and quickly undergo to further specific tests, aiming at identifying those who can be addressed to alternative paths (Day Hospital/Day Service) and those who need to be hospitalized. For the latter, the HA allows to select the most appropriate diagnostic/therapeutic path according to the model of the intensity of care: critical area (ICU); ordinary hospitalization; short stay (SHS). In 2020 (with a total of 206 of Cardiology HA opening days, net of the lockdown and summer closure periods) 402 patients from the ER were admitted to cardiology HA. Among those, 20% (81 pts) was assigned to the SHS (availability of 2 beds/day, except for weekends) while another 4.3% (17 pts) was allocated to outpatient care. 52% of SHS pts had ischemic pathology (NSTE–ACS at low risk, CCS – Chronic Coronary Syndrome – with positive stress test, doubtful chest pain with multiple risk factors), 33% arrhythmic pathology (66% tachyarrhythmias, 34% bradyarrhythmias) and 12.6% heart failure (Killip class I–III). The HA reduced the average hospital stay (AHS): for SCA–NSTE, for example, from 5.1 days to 3.6 and the waiting time for diagnostic procedures (for example, for coronary angiography from 1.8 to 0.3 days). The opening of the SHS has further reduced the duration of the AHS: 1.5 nights for the CCS (the need for revascularization was not indicated in 68% of cases); 1 night for tachyarrhythmias (electrical cardioversion in 89% of cases); 3.75 nights for bradyarrhythmias (PMK implantation in 55% of patients). The overall average stay in SHS was very brief (2.5 nights) allowing a rapid turnover even with more difficult procedures. While criticalities persist (limited availability of SHS beds, “short” week opening), the results obtained confirm the need for dedicated and specialized HA in order to reduce improper hospitalizations, trim hospitalization times and broaden the appropriateness of care.

Solving the time-independent Schrödinger equation for chains of coupled excitons and phonons using tensor trains

We demonstrate how to apply the tensor-train format to solve the time-independent Schrödinger equation for quasi-one-dimensional excitonic chain systems with and without periodic boundary conditions. The coupled excitons and phonons are modeled by Fröhlich-Holstein type Hamiltonians with on-site and nearest-neighbor interactions only. We reduce the memory consumption as well as the computational costs significantly by employing efficient decompositions to construct low-rank tensor-train representations, thus mitigating the curse of dimensionality. In order to compute also higher quantum states, we introduce an approach that directly incorporates the Wielandt deflation technique into the alternating linear scheme for the solution of eigenproblems. Besides systems with coupled excitons and phonons, we also investigate uncoupled problems for which (semi-)analytical results exist. There, we find that in the case of homogeneous systems, the tensor-train ranks of state vectors only marginally depend on the chain length, which results in a linear growth of the storage consumption. However, the central processing unit time increases slightly faster with the chain length than the storage consumption because the alternating linear scheme adopted in our work requires more iterations to achieve convergence for longer chains and a given rank. Finally, we demonstrate that the tensor-train approach to the quantum treatment of coupled excitons and phonons makes it possible to directly tackle the phenomenon of mutual self-trapping. We are able to confirm the main results of the Davydov theory, i.e., the dependence of the wave packet width and the corresponding stabilization energy on the exciton-phonon coupling strength, although only for a certain range of that parameter. In future work, our approach will allow calculations also beyond the validity regime of that theory and/or beyond the restrictions of the Fröhlich-Holstein type Hamiltonians.

Addressing global uncertainty and sensitivity in first-principles based microkinetic models by an adaptive sparse grid approach

In the last decade, first-principles-based microkinetic modeling has been developed into an important tool for a mechanistic understanding of heterogeneous catalysis. A commonly known, but hitherto barely analyzed issue in this kind of modeling is the presence of sizable errors from the use of approximate Density Functional Theory (DFT). We here address the propagation of these errors to the catalytic turnover frequency (TOF) by global sensitivity and uncertainty analysis. Both analyses require the numerical quadrature of high-dimensional integrals. To achieve this efficiently, we utilize and extend an adaptive sparse grid approach and exploit the confinement of the strongly non-linear behavior of the TOF to local regions of the parameter space. We demonstrate the methodology on a model of the oxygen evolution reaction at the Co₃O₄ (110)-A surface, using a maximum entropy error model that imposes nothing but reasonable bounds on the errors. For this setting, the DFT errors lead to an absolute uncertainty of several orders of magnitude in the TOF. We nevertheless find that it is still possible to draw conclusions from such uncertain models about the atomistic aspects controlling the reactivity. A comparison with derivative-based local sensitivity analysis instead reveals that this more established approach provides incomplete information. Since the adaptive sparse grids allow for the evaluation of the integrals with only a modest number of function evaluations, this approach opens the way for a global sensitivity analysis of more complex models, for instance, models based on kinetic Monte Carlo simulations.

Local-metrics error-based Shepard interpolation as surrogate for highly non-linear material models in high dimensions

Many problems in computational materials science and chemistry require the evaluation of expensive functions with locally rapid changes, such as the turn-over frequency of first principles kinetic Monte Carlo models for heterogeneous catalysis. Because of the high computational cost, it is often desirable to replace the original with a surrogate model, e.g., for use in coupled multiscale simulations. The construction of surrogates becomes particularly challenging in high-dimensions. Here, we present a novel version of the modified Shepard interpolation method which can overcome the curse of dimensionality for such functions to give faithful reconstructions even from very modest numbers of function evaluations. The introduction of local metrics allows us to take advantage of the fact that, on a local scale, rapid variation often occurs only across a small number of directions. Furthermore, we use local error estimates to weigh different local approximations, which helps avoid artificial oscillations. Finally, we test our approach on a number of challenging analytic functions as well as a realistic kinetic Monte Carlo model. Our method not only outperforms existing isotropic metric Shepard methods but also state-of-the-art Gaussian process regression.

Efficient Implicit Solvation Method for Full Potential DFT

With the advent of efficient electronic structure methods, effective continuum solvation methods have emerged as a way to, at least partially, include solvent effects into simulations without the need for expensive sampling over solvent degrees of freedom. The multipole moment expansion (MPE) model, while based on ideas initially put forward almost 100 years ago, has recently been updated for the needs of modern electronic structure calculations. Indeed, for an all-electron code relying on localized basis sets and-more importantly-a multipole moment expansion of the electrostatic potential, the MPE method presents a particularly cheap way of solving the macroscopic Poisson equation to determine the electrostatic response of a medium surrounding a solute. In addition to our implementation of the MPE model in the FHI-aims electronic structure theory code [ Blum , V. ; Comput. Phys. Commun. 2009 , 180 , 2175 - 2196 , DOI: 10.1016/j.cpc.2009.06.022 ], we describe novel algorithms for determining equidistributed points on the solvation cavity-defined as a charge density isosurface-and the determination of cavity surface and volume from just this collection of points and their local density gradients. We demonstrate the efficacy of our model on an analytically solvable test case, against high-accuracy finite-element calculations for a set of ≈140000 2D test cases, and finally against experimental solvation free energies of a number of neutral and singly charged molecular test sets [ Andreussi , O. ; J. Chem. Phys. 2012 , 136 , 064102 , DOI: 10.1063/1.3676407 ; Marenich , A. V. ; Minnesota Solvation Database , Version 2012; University of Minnesota : Minneapolis, MN, USA , 2012 . ]. In all test cases we find that our MPE approach compares very well with given references at computational overheads < 20% and sometimes much smaller compared to a plain self-consistency cycle.

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO₂(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

Cytokine modulation in patients with idiopathic pulmonary fibrosis undergoing treatment with steroids, immunosuppressants, and IFN-γ 1b

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease of unknown etiology and pathogenic mechanisms. From an etiopathogenic point of view, alveolar macrophages play a key role in accumulation of fibroblasts and deposition of collagen and extracellular matrix by releasing specific cytokines and inflammatory mediators. IPF seems to be also associated with circulating fibrocytes, which might be involved with an abnormal pulmonary vascular repair and remodeling. Based on its hypothesized pathologic mechanisms, anti-inflammatory, anti-fibrotic and immunosuppressive therapies are often used. For these reasons, Interferon-g (IFN-g) has been used to exploit its activity on macrophages and fibroblasts. The aim of this study was to investigate the response to corticosteroids and/or IFN-g 1b treatments based on pulmonary function tests and on inflammatory cytokine patterns of expression on bronchoalveolar lavage (BAL), at baseline and during and after the therapies. Unlike previous studies, we analyzed a period of therapy longer than 1 year. Our results demonstrated the effectiveness of IFN-γ in a group of IPF patients in whom the treatment was prolonged for over a year. These data suggest a positive role of IFN-γ; treatment in patients in the initial stage of the disease.

Function-Space-Based Solution Scheme for the Size-Modified Poisson-Boltzmann Equation in Full-Potential DFT

The size-modified Poisson-Boltzmann (MPB) equation is an efficient implicit solvation model which also captures electrolytic solvent effects. It combines an account of the dielectric solvent response with a mean-field description of solvated finite-sized ions. We present a general solution scheme for the MPB equation based on a fast function-space-oriented Newton method and a Green's function preconditioned iterative linear solver. In contrast to popular multigrid solvers, this approach allows us to fully exploit specialized integration grids and optimized integration schemes. We describe a corresponding numerically efficient implementation for the full-potential density-functional theory (DFT) code FHI-aims. We show that together with an additional Stern layer correction the DFT+MPB approach can describe the mean activity coefficient of a KCl aqueous solution over a wide range of concentrations. The high sensitivity of the calculated activity coefficient on the employed ionic parameters thereby suggests to use extensively tabulated experimental activity coefficients of salt solutions for a systematic parametrization protocol.

In situ x-ray photoelectron spectroscopy of model catalysts: at the edge of the gap

We present high-pressure x-ray photoelectron spectroscopy (HP-XPS) and first-principles kinetic Monte Carlo study addressing the nature of the active surface in CO oxidation over Pd(100). Simultaneously measuring the chemical composition at the surface and in the near-surface gas phase, we reveal both O-covered pristine Pd(100) and a surface oxide as stable, highly active phases in the near-ambient regime accessible to HP-XPS. Surprisingly, no adsorbed CO can be detected during high CO(2) production rates, which can be explained by a combination of a remarkably short residence time of the CO molecule on the surface and mass-transfer limitations in the present setup.