Salesforce contracting under model uncertainty

This paper considers a firm's salesforce contracting problem under model uncertainty. Based on the notion of multiplier preferences, we capture model uncertainty and explicitly characterize the structure of the optimal contract. Our findings provide guidelines on the design of salesforce compensation contracts in practical situations.     

Comparison of different gas models to calculate the spring force of a hydropneumatic suspension

When developing any simulation model some compromise must be made between computational efficiency and the accuracy of the model. This study compares the performance of three ideal gas (IG) law variations (IG with the energy equation (EE), isothermal and adiabatic), and two real gas approaches (Benedict Webb Rubin (BWR) equation with and without the EE) to model the spring force of a hydropneumatic suspension. These models are compared with experimental data obtained from laboratory tests on a single hydropneumatic suspension unit. Both the BWR and IG models with the EE offer a significant improvement in correlation compared to the models without the EE. The real gas BWR approach offers a small improvement over the IG approach under the test conditions. The best (BWR with EE) and worst (IG isothermal) models are then used to model the spring forces in a full vehicle model of a 4 × 4 Sports Utility vehicle (SUV). The data is again compared with experimental results and the BWR model with the EE correlates significantly better than the IG isothermal model. It is thus concluded that the inclusion of the EE will yield significantly better results and it should only be omitted if the parameters investigated are not sensitive to errors in the spring model.     

SE-MCNN-CTC的中文语音识别声学模型

针对国内外缺少对振动轮噪声预估的问题,以某型振动轮为研究对象,首先基于动力学有限元理论对振动轮进行频率响应分析,其次采用声学边界元技术对振动轮辐射噪声进行了数值模拟,并通过实验验证了仿真结果的准确性,然后比较了垂直振动与圆周振动两种不同激振形式对辐射噪声的影响,得出垂直振动辐射噪声低的结论,最后对驾驶室声腔模态进行了仿真,与振动轮激振频率相近发生共振。通过调整激振频率,降低了司机耳旁噪声。所得研究成果可为振动轮辐射噪声的预估与改进提供一种切实可行的参考依据。     

A dynamical systems model of unorganized segregation

We consider Schelling’s bounded neighborhood model (BNM) of unorganized segregation, from the perspective of modern dynamical systems theory. We carry out a complete quantitative analysis of the system for linear tolerance schedules. We derive a fully predictive model and associate each term with a social meaning. We recover and generalize Schelling’s qualitative results.

For the case of unlimited population movement, we derive exact formulae for regions in parameter space where stable integrated population mixes can occur, and show how neighborhood tipping can be explained in terms of basins of attraction.

When population movement is limited, we derive exact criteria for the occurrence of new population mixes.

For nonlinear tolerance schedules, we illustrate our approach with numerical simulations.     

Cosmic inflation and model comparison

We analyze the implications for inflation of the recently released Planck Cosmic Microwave Background data and explain why the single-field slow-roll scenarios with minimal kinetic terms are favored. Within this class of models, we show how Bayesian model comparison can be used to further exclude about one third of the inflationary scenarios. We also study the end of inflation and show that Planck can already constrain the reheating phase. Finally, we conclude by discussing how future missions will be able to improve our knowledge of the inflationary mechanism.     

英国国家科研与创新署学科交叉研究资助机制及启示

Newly established in 2018, the UK Research and Innovation (UKRI) strengthens the strategic coordination of the UK research and innovation system by bringing together seven Research Councils, Research England, and Innovate UK. Through its nine organizations, UKRI funds multidisciplinary and interdisciplinary research in a number of priority areas. It also runs the Strategic Priorities Fund to support multidisciplinary and interdisciplinary research in strategic areas identified by government policies as well as the Global Challenges Research Fund to promote challenge-led interdisciplinary research needed by developing countries. The UKRI makes significant efforts to engage stakeholders in the development, design, and implementation of multidisciplinary and interdisciplinary programs. It has also developed a range of mechanisms to improve the evaluation of multidisciplinary and interdisciplinary projects. Chinese science and innovation funding agencies could draw upon the UKRI experience from four aspects to advance interdisciplinary research in China.     

Identifying mutated driver pathways in cancer by integrating multi-omics data

Since the driver pathway in cancer plays a crucial role in the formation and progression of cancer, it is very imperative to identify driver pathways, which will offer important information for precision medicine or personalized medicine. In this paper, an improved maximum weight submatrix problem model is proposed by integrating such three kinds of omics data as somatic mutations, copy number variations, and gene expressions. The model tries to adjust coverage and mutual exclusivity with the average weight of genes in a pathway, and simultaneously considers the correlation among genes, so that the pathway having high coverage but moderate mutual exclusivity can be identified. By introducing a kind of short chromosome code and a greedy based recombination operator, a parthenogenetic algorithm PGA-MWS is presented to solve the model. Experimental comparisons among algorithms GA, MOGA, iMCMC and PGA-MWS were performed on biological and simulated data sets. The experimental results show that, compared with the other three algorithms, the PGA-MWS one based on the improved model can identify the gene sets with high coverage but moderate mutual exclusivity and scales well. Many of the identified gene sets are involved in known signaling pathways, most of the implicated genes are oncogenes or tumor suppressors previously reported in literatures. The experimental results indicate that the proposed approach may become a useful complementary tool for detecting cancer pathways.     

Analysis of risk bounds in partially specified additive factor models

The study of worst case scenarios for risk measures (e.g. the Value at Risk) when the underlying risk vector (or portfolio of risks) is not completely specified is a central topic in the literature on robust risk measurement. In this paper we discuss partially specified factor models as introduced in Bernard et al. (2017) in more detail for the class of additive factor models which admit more explicit results. These results allow to describe in more detail the reduction of risk bounds obtainable by this method in dependence on the degree of positive resp. negative dependence induced by the systematic risk factors. The insight may help in applications of this reduction method to get a better qualitative impression on the range of influence of the partially specified factor structure.     

Non parametric estimation of the diffusion coefficients of a diffusion with jumps

In this article, we consider a jump diffusion process ${\left(X_t\right)}_{t\ge 0}$, with drift function $b$, diffusion coefficient $\sigma$ and jump coefficient ${\xi }^2$. This process is observed at discrete times $t=0,\Delta ,\dots ,n\Delta$. The sampling interval $\Delta$ tends to 0 and the time interval $n\Delta$ tends to infinity. We assume that ${\left(X_t\right)}_{t\ge 0}$ is ergodic, strictly stationary and exponentially $\beta$-mixing. We use a penalized least-square approach to compute adaptive estimators of the functions ${\sigma }^2+{\xi }^2$ and ${\sigma }^2$. We provide bounds for the risks of the two estimators.     

直觉模糊模型检测在工程决策上的应用

将直觉模糊Kripke结构扩展到加权直觉模糊Kripke结构,将直觉模糊计算树逻辑诱导到加权直觉模糊计算树逻辑;研究在此之上的直觉模糊期望测度和多属性工程决策问题。用加权直觉模糊Kripke结构的权值自然地刻画了工程问题中的成本和收益,直觉模糊测度量化工程进展的不确定性,用加权直觉模糊计算树逻辑描述不确定性工程属性约束。给出了基于直觉模糊模型检测的多属性工程寻优算法,并讨论了算法的复杂度。