Active-learning for global optimization of Ni-Ceria nanoparticles: The case of Ce4-xNixO8- x (x = 1, 2, 3).

Ni-CeO2 nanoparticles (NPs) are promising nanocatalysts for water splitting and water gas shift reactions due to the ability of ceria to temporarily donate oxygen to the catalytic reaction and accept oxygen after the reaction is completed. Therefore, elucidating how different properties of the Ni-Ceria NPs relate to the activity and selectivity of the catalytic reaction, is of crucial importance for the development of novel catalysts. In this work the active learning (AL) method based on machine learning regression and its uncertainty is used for the global optimization of Ce(4-x)NixO(8-x) (x = 1, 2, 3) nanoparticles, employing density functional theory calculations. Additionally, further investigation of the NPs by mass-scaled parallel-tempering Born-Oppenheimer molecular dynamics resulted in the same putative global minimum structures found by AL, demonstrating the robustness of our AL search to learn from small datasets and assist in the global optimization of complex electronic structure systems.

European Pediatric Cardiac Anesthesia Fellowship Program: A First Proof of Concept.

The Pediatric Cardiac Anesthesia (PCA) fellowship is a demanding training program in Europe and the United States. Successful completion of the program requires years of training in anesthesiology, a thorough understanding of cardiovascular anatomy and physiology, and extensive experience in the perioperative management of neonates and children with heart disease. In the context of the first candidate to successfully complete the PCA program in Europe, this article presents excerpts from the design and structure of the European PCA program. The PCA program is evaluated critically by both external and internal reviewers, and points are highlighted that could be included in the next version of the program.

Pd8 Cluster: Too Small to Melt? A BOMD Study.

The question of whether a solid-liquid phase transition occurs in small clusters poses a fundamental challenge. In this study, we attempt to elucidate this phenomenon through a thorough examination of the thermal behavior and structural stability of Pd8 clusters employing ab initio simulations. Initially, a systematic global search is carried out to identify the various isomers of the Pd8 cluster. This is accomplished by employing an ab initio basin-hopping algorithm and using the PBE/SDD scheme integrated in the Gaussian code. The resulting isomers are further refined through reoptimization using the deMon2k package. To ensure the structural firmness of the lowest-energy isomer, we calculated normal modes. The structural stability as a function of temperature is analyzed through the Born-Oppenheimer molecular dynamics (BOMD) approach. Multiple BOMD trajectories at distinct simulated temperatures are examined with data clustering analysis to determine cluster isomers. This analysis establishes a connection between the potential energy landscape and the simulated temperature. To address the question of cluster melting, canonical parallel-tempering BOMD runs are performed and analyzed with the multiple-histogram method. A broad maximum in the heat capacity curve indicates a melting transition between 500 and 600 K. To further examine this transition, the mean-squared displacement and the pair-distance distribution function are calculated. The results of these calculations confirm the existence of a solid-liquid phase transition, as indicated by the heat capacity curve.

The Efficacy and Safety of a Low-Dose Tranexamic Acid Bolus-Only Protocol Compared with the Moderate-Dose Protocol in Valvular Heart Surgery.

In 873 propensity score-matched pairs of patients undergoing valvular heart surgery, we compared a "moderate dose" of tranexamic acid (TXA) protocol (group 1; median TXA dose: 24 mg/kg body weight) with a 1.5-g "bolus-only" protocol (group 2; median TXA dose: 19 mg/kg body weight). The number of transfused patients was higher in group 2 than in group 1 (74.5 vs 66.0%, p < 0.001), as was the number of transfused red blood cell concentrates (p = 0.001). The risks of re-exploration and convulsive seizures were similar between groups (p > 0.50). Data indicate an impaired efficacy following the "bolus-only" protocol, without a significant safety improvement.

How important is the amount of exact exchange for spin-state energy ordering in DFT? Case study of molybdenum carbide cluster, Mo4C2.

Since the form of the exact functional in density functional theory is unknown, we must rely on density functional approximations (DFAs). In the past, very promising results have been reported by combining semi-local DFAs with exact, i.e. Hartree-Fock, exchange. However, the spin-state energy ordering and the predictions of global minima structures are particularly sensitive to the choice of the hybrid functional and to the amount of exact exchange. This has been already qualitatively described for single conformations, reactions, and a limited number of conformations. Here, we have analyzed the mixing of exact exchange in exchange functionals for a set of several hundred isomers of the transition metal carbide, Mo4C2. The analysis of the calculated energies and charges using PBE0-type functional with varying amounts of exact exchange yields the following insights: (1) The sensitivity of spin-energy splitting is strongly correlated with the amount of exact exchange mixing. (2) Spin contamination is exacerbated when correlation is omitted from the exchange-correlation functional. (3) There is not one ideal value for the exact exchange mixing which can be used to parametrize or choose among the functionals. Calculated energies and electronic structures are influenced by exact exchange at a different magnitude within a given distribution; therefore, to extend the application range of hybrid functionals to the full periodic table the spin-energy splitting energies should be investigated.

Defining heparin resistance: communication from the ISTH SSC Subcommittee of Perioperative and Critical Care Thrombosis and Hemostasis.

The term heparin resistance (HR) is used by clinicians without specific criteria. We performed a literature search and surveyed our SSC membership to better define the term when applied to medical and intensive care unit patients. The most common heparin dosing strategy reported in the literature (53%) and by survey respondents (80.4%) was the use of weight-based dosing. Heparin monitoring results were similar based on the proportion of publications and respondents that reported the use of anti-Xa and activated partial thromboplastin time. The most common literature definition of HR was >35 000 U/d, but no consensus was reported among survey respondents regarding weight-based and the total dose of heparin when determining resistance. Respondent consensus on treating HR included antithrombin supplementation, direct thrombin inhibitors, or administering more heparin as the strategies available for treating HR. A range of definitions for HR exist. Given the common use of heparin weight-based dosing, future publications employing the term HR should include weight-based definitions, monitoring assay, and target level used. Further work is needed to develop a consensus for defining HR.

QMLMaterial─A Quantum Machine Learning Software for Material Design and Discovery.

Structural elucidation of chemical compounds is challenging experimentally, and theoretical chemistry methods have added important insight into molecules, nanoparticles, alloys, and materials geometries and properties. However, finding the optimum structures is a bottleneck due to the huge search space, and global search algorithms have been used successfully for this purpose. In this work, we present the quantum machine learning software/agent for materials design and discovery (QMLMaterial), intended for automatic structural determination in silico for several chemical systems: atomic clusters, atomic clusters and the spin multiplicity together, doping in clusters or solids, vacancies in clusters or solids, adsorption of molecules or adsorbents on surfaces, and finally atomic clusters on solid surfaces/materials or encapsulated in porous materials. QMLMaterial is an artificial intelligence (AI) software based on the active learning method, which uses machine learning regression algorithms and their uncertainties for decision making on the next unexplored structures to be computed, increasing the probability of finding the global minimum with few calculations as more data is obtained. The software has different acquisition functions for decision making (e.g., expected improvement and lower confidence bound). Also, the Gaussian process is available in the AI framework for regression, where the uncertainty is obtained analytically from Bayesian statistics. For the artificial neural network and support vector regressor algorithms, the uncertainty can be obtained by K-fold cross-validation or nonparametric bootstrap resampling methods. The software is interfaced with several quantum chemistry codes and atomic descriptors, such as the many-body tensor representation. QMLMaterial's capabilities are highlighted in the current work by its applications in the following systems: Na20, Mo6C3 (where the spin multiplicity was considered), H2O@CeNi3O5, Mg8@graphene, Na3Mg3@CNT (carbon nanotube).

Perioperative Considerations in Management of the Severely Bleeding Coagulopathic Patient.

Inherited and acquired coagulopathy are frequently associated with major bleeding in severe trauma, cardiac surgery with cardiopulmonary bypass, and postpartum hemorrhage. Perioperative management is multifactorial and includes preoperative optimization and discontinuation of anticoagulants and antiplatelet therapy in elective procedures. Prophylactic or therapeutic use of antifibrinolytic agents is strongly recommended in guidelines and has been shown to reduce bleeding and need for allogeneic blood administration. In the context of bleeding induced by anticoagulants and/or antiplatelet therapy, reversal strategies should be considered when available. Targeted goal-directed therapy using viscoelastic point-of-care monitoring is increasingly used to guide the administration of coagulation factors and allogenic blood products. In addition, damage control surgery, which includes tamponade of large wound areas, leaving surgical fields open, and other temporary maneuvers, should be considered when bleeding is refractory to hemostatic measures.

Efficient implementation of time-dependent auxiliary density functional theory.

The random phase approximation of time-dependent auxiliary density functional theory (TDADFT) is rederived from auxiliary density perturbation theory. Our exhaustive validation of TDADFT reveals an upshift of the excitation energies by ∼0.1 eV with respect to standard time-dependent density functional theory. For the computationally efficient implementation of TDADFT, floating point operation optimized three-center electron repulsion integral recurrence relations and their double asymptotic expansions are implemented into the Davidson solver. The computational efficiency of TDADFT is benchmarked with four sets of molecules comprising alkanes, fullerenes, DNA fragments, and zeolites. The results show that TDADFT has a computational scaling between 1.3 and 1.9 with respect to the number of basis functions, which is lower than the scaling of standard time-dependent density functional theory. Due to its computational simplifications, TDADFT is particularly well suited for Born-Oppenheimer molecular dynamics simulations. As illustrative examples, we present the temperature effects on the gas-phase absorption spectra of benzene, naphthalene, and anthracene.

Use of the CytoSorb® filter for elimination of residual therapeutic argatroban concentrations during heparinized cardiopulmonary bypass for heart transplantation.

INTRODUCTION: No antidote or established extracorporeal elimination strategy is available for argatroban. Hemadsorption facilitates elimination of smaller drugs. CASE REPORT: A 34-year-old patient underwent urgent heart transplantation. Because of a history of heparin-induced thrombocytopenia, preoperative anticoagulation was performed with argatroban. Despite ceasing of the continuous infusion of argatroban 2 h before surgery, concentration only declined from 0.60 µg/ml to 0.58 µg/ml before surgery, and the activated clotting time (ACT) value shortly was 223 s. Microvascular bleeding had been observed when starting surgery. A CytoSorb® absorption column was integrated into the system of the heparin-anticoagulated cardiopulmonary bypass (CPB) circuit and a flow of 400 mL/min provided during the 2 h of extracorporeal circulation. The argatroban concentration after weaning from CPB was 0.04 µg/ml and satisfying hemostasis had been achieved after protamine administration. CONCLUSION: Data indicate that the CytoSorb® absorption column might be an effective tool for quick extracorporeal removal of therapeutic concentrations of argatroban.

Moderate Dose of Tranexamic Acid and Complications after Valvular Heart Surgery.

BACKGROUND: In valvular open-heart surgery, data regarding the effect of a moderate dose of tranexamic acid (TXA) on clinical outcomes are limited. METHODS: Out of a cohort of 13,293 patients, we performed a propensity-score-matched analysis in 6,106 patients and assessed the risk of convulsive seizures (CS, primary endpoint), stroke, renal replacement therapy, and mortality (secondary endpoints). In the entire study cohort of 13,293 patients, we also assessed the multivariable-adjusted association of CS with postoperative outcomes. RESULTS: The risk of CS was significantly higher in the TXA group (2.4%; n = 72) than in the non-TXA group (1.0%; n = 32), with a relative risk ratio (RR) of 2.28 (95% confidence interval [CI]: 1.50-3.47; p < 0.001). The risk of CS was also higher in patients receiving TXA doses ≥25 mg/kg body weight (3.7%; n = 40) than in patients receiving <25 mg/kg body weight (1.6%; n = 32; p < 0.001). Perioperative secondary clinical endpoints and 1-year mortality did not differ significantly between study groups (p-value > 0.05). Compared with non-CS patients (n = 13,000), patients with nonhemorrhagic, nonembolic CS (n = 253) revealed higher multivariable-adjusted in-hospital risks of stroke (RR: 3.82 [95% CI: 2.44-5.60; p < 0.001]) and mortality (RR: 2.07 [95% CI: 1.23-3.48; p = 0.006]), and a higher 1-year mortality risk (RR: 1.85 [95% CI: 1.42-2.41; p < 0.001]). CONCLUSION: A moderate TXA dose was associated with a significantly higher risk of seizure, but not with other clinical complications such as stroke, renal replacement therapy, and mortality. However, in the small group of patients experiencing a seizure, the risks of stroke and short- and mid-term mortality were substantially higher than in patients not experiencing a seizure, indicating that the use of a low-dose TXA protocol (<25 mg/kg body weight) should be considered.

GAMaterial-A genetic-algorithm software for material design and discovery.

Genetic algorithms (GAs) are stochastic global search methods inspired by biological evolution. They have been used extensively in chemistry and materials science coupled with theoretical methods, ranging from force-fields to high-throughput first-principles methods. The methodology allows an accurate and automated structural determination for molecules, atomic clusters, nanoparticles, and solid surfaces, fundamental to understanding chemical processes in catalysis and environmental sciences, for instance. In this work, we propose a new genetic algorithm software, GAMaterial, implemented in Python3.x, that performs global searches to elucidate the structures of atomic clusters, doped clusters or materials and atomic clusters on surfaces. For all these applications, it is possible to accelerate the GA search by using machine learning (ML), the ML@GA method, to build subsequent populations. Results for ML@GA applied for the dopant distributions in atomic clusters are presented. The GAMaterial software was applied for the automatic structural search for the Ti6 O12 cluster, doping Al in Si11 (4Al@Si11 ) and Na10 supported on graphene (Na10 @graphene), where DFTB calculations were used to sample the complex search surfaces with reasonably low computational cost. Finally, the global search by GA of the Mo8 C4 cluster was considered, where DFT calculations were made with the deMon2k code, which is interfaced with GAMaterial.