Microscopic mechanisms of cooperative communications within single nanocatalysts

Catalysis is a method of accelerating chemical reactions that is critically important for fundamental research as well as for industrial applications. It has been recently discovered that catalytic reactions on metal nanoparticles exhibit cooperative effects. The mechanism of these observations, however, remains not well understood. In this work, we present a theoretical investigation on possible microscopic origin of cooperative communications in nanocatalysts. In our approach, the main role is played by positively charged holes on metal surfaces. A corresponding discrete-state stochastic model for the dynamics of holes is developed and explicitly solved. It is shown that the observed spatial correlation lengths are given by the average distances migrated by the holes before they disappear, while the temporal memory is determined by their lifetimes. Our theoretical approach is able to explain the universality of cooperative communications as well as the effect of external electric fields. Theoretical predictions are in agreement with experimental observations. The proposed theoretical framework quantitatively clarifies some important aspects of the microscopic mechanisms of heterogeneous catalysis.

Nonlinear differential equations based on the B-S-M model in the pricing of derivatives in financial markets

The pricing and hedging of financial derivatives have become one of the hot research issues in mathematical finance today. In the case of non-risk neutrality, this article uses the martingale method and probability measurement method to study the pricing method and hedging strategy of financial derivatives. This paper also further studies the hedging strategy of financial derivatives in the incomplete market based on the BSM model and converts the solution of this problem into solving a vector on the Hilbert space to its closure. The problem of space projection is to use projection theory to decompose financial derivatives under a given martingale measure. In the imperfect market, the vertical projection theory is used to obtain the approximate pricing method and hedging strategy of financial derivatives in which the underlying asset follows the martingale process; the projection theory is further expanded, and the pricing problem of financial derivatives under the mixed-asset portfolio is obtained. Approximate pricing of financial derivatives; in the discrete state, the hedging investment strategy of financial derivatives H in the imperfect market is found through the method of variance approximation.

WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications

ABSTRACTThe weighted ensemble (WE) family of methods is one of several statistical-mechanics based path sampling strategies that can provide estimates of key observables (rate constants, pathways) using a fraction of the time required by direct simulation methods such as molecular dynamics or discrete-state stochastic algorithms. WE methods oversee numerous parallel trajectories using intermittent overhead operations at fixed time intervals, enabling facile interoperability with any dynamics engine. Here, we report on major upgrades to the WESTPA software package, an open-source, high-performance framework that implements both basic and recently developed WE methods. These upgrades offer substantial improvements over traditional WE. Key features of the new WESTPA 2.0 software enhance efficiency and ease of use: an adaptive binning scheme for more efficient surmounting of large free energy barriers, streamlined handling of large simulation datasets, exponentially improved analysis of kinetics, and developer-friendly tools for creating new WE methods, including a Python API and resampler module for implementing both binned and “binless” WE strategies.

PP409 Cost-Effectiveness Of Ruxolitinib For Patients With Myelofibrosis: A Review Of The Literature

IntroductionMyelofibrosis (MF) is a rare (annual incidence estimated to be 1/100,000 in Europe), chronic hematologic disorder associated with morbidity and mortality as well as the risk of evolution to acute myeloid leukemia. Ruxolitinib (Jakavi®, Novartis) is the first JAK 1/2 inhibitor approved by the FDA and EMA in 2011 in treating MF. Ruxolitinib is considered a high-cost and life-time treatment. UK-based estimates of the cost of treatment are in the region of GBP43,000/year/patient (in 2013). Against the background of the challenge of treatments for rare diseases reaching cost-effectiveness thresholds, this study identified, collected, and appraised the available evidence on the cost-effectiveness of ruxolitinib in the treatment of MF.MethodsA systematic approach was taken to conducting the literature review. Databases searched included PubMed, EMBASE, MEDLINE, and the Cochrane Library based on search terms informed by PICO: myelofibrosis, ruxolitinib, best available therapy/standard of care, and cost-effectiveness/cost-utility/pharmacoeconomics. The search was limited to studies published in the English language. A narrative synthesis was used to evaluate studies and the CHEERS checklist to explore the quality of reporting of the cost-effectiveness analysis.ResultsThe narrative synthesis included five studies conducted in the UK, Portugal, Chile, Canada, and Finland. All cost-effectiveness analyses used data from the same two large, randomized controlled, double-blind, phase III studies (COMFORT-I and -II). Ruxolitinib was compared to the best available therapy (BAT), including hydroxyurea, no medication, and prednisone/prednisolone. Perspectives and included costs varied among analyses. Markov models and discrete state cohort models were used to evaluate the cost-effectiveness and clinical benefit was measured in quality-adjusted life years (QALY) or life years (LY) gained.These analyses estimated the base-case incremental cost-effectiveness ratios (ICER) per QALY of (converted into USD, if appropriate, at the historic average annual exchange rate) GBP44,905 in the UK (2013; USD 70,226), EUR40,000 in Portugal (2016; USD44,272), USD54,500 (2016), CAD61,444 in Canada (2012; USD61,474), and EUR42,367 in Finland (2015; USD42,027). Based upon the cost-effectiveness thresholds applied in each of these countries, ruxolitinib was found to be universally cost-effective, albeit with price adjustments as part of the wider pricing and reimbursement processes used in these countries.ConclusionsRuxolitinib was found to be cost-effective in treating MF informed by different types of models and from different perspectives; however, there was some uncertainty around available data due to limited data sources.

A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems

Currently, industry is undergoing an exponential increase in binary-based combinatorial problems. In this regard, metaheuristics have been a common trend in the field in order to design approaches to successfully solve them. Thus, a well-known strategy includes the employment of continuous swarm-based algorithms transformed to perform in binary environments. In this work, we propose a hybrid approach that contains discrete smartly adapted population-based strategies to efficiently tackle binary-based problems. The proposed approach employs a reinforcement learning technique, known as SARSA (State–Action–Reward–State–Action), in order to utilize knowledge based on the run time. In order to test the viability and competitiveness of our proposal, we compare discrete state-of-the-art algorithms smartly assisted by SARSA. Finally, we illustrate interesting results where the proposed hybrid outperforms other approaches, thus, providing a novel option to tackle these types of problems in industry.

A general theoretical framework to design base editors with reduced bystander effects

Base editors (BEs) hold great potential for medical applications of gene therapy. However, high precision base editing requires BEs that can discriminate between the target base and multiple bystander bases within a narrow active window (4 – 10 nucleotides). Here, to assist in the design of these optimized editors, we propose a discrete-state stochastic approach to build an analytical model that explicitly evaluates the probabilities of editing the target base and bystanders. Combined with all-atom molecular dynamic simulations, our model reproduces the experimental data of A3A-BE3 and its variants for targeting the “TC” motif and bystander editing. Analyzing this approach, we propose several general principles that can guide the design of BEs with a reduced bystander effect. These principles are then applied to design a series of point mutations at T218 position of A3G-BEs to further reduce its bystander editing. We verify experimentally that the new mutations provide different levels of stringency on reducing the bystander editing at different genomic loci, which is consistent with our theoretical model. Thus, our study provides a computational-aided platform to assist in the scientifically-based design of BEs with reduced bystander effects.