企业自主研发与合作创新的风险测度及组合优化

企业在整合内部创新要素进行自主研发的同时,也会寻求外部创新资源进行合作创新,当前同时从事多个R&D项目已成为常见的企业经营活动,如何在不确定条件下分析多个R&D项目投资的策略选择及风险优化,对于企业的长期发展具有重要意义。根据企业是否采取合作创新策略,可将其R&D项目分为自主研发与合作创新两类,以项目的研发成功率和投资收益率代表技术风险和市场风险,分别测度自主研发与合作创新项目的风险特性,并在此基础上构建企业R&D项目投资组合优化模型,以在自主研发与合作创新项目之间进行权衡取舍。结果表明,企业对于自主研发与合作创新项目投资组合的最优投资权重,主要取决于这两类组合的期望收益率、收益率方差、期望成功率以及两组合之间的协方差。企业可基于关键参数制定出最优的R&D项目投资组合选择策略,合理分配资金以达到风险最小化的投资目标。     

Transferred multipolar atom model for 10β,17β‐dihydroxy‐17α‐methylestr‐4‐en‐3‐one dihydrate obtained from the biotransformation of methyloestrenolone

Biotransformation is the structural modification of compounds using enzymes as the catalysts and it plays a key role in the synthesis of pharmaceutically important compounds. 10β,17β‐Dihydroxy‐17α‐methylestr‐4‐en‐3‐one dihydrate, C₁₉H₂₈O₃·2H₂O, was obtained from the fungal biotransformation of methyloestrenolone. The structure was refined using the classical independent atom model (IAM) and a transferred multipolar atom model using the ELMAM2 database. The results from the two refinements have been compared. The ELMAM2 refinement has been found to be superior in terms of the refinement statistics. It has been shown that certain electron‐density‐derived properties can be calculated on the basis of the transferred parameters for crystals which diffract to ordinary resolution.     

Search of truncation of (N−1) electron basis containing full connected triple excitations in computing main and satellite ionization potentials via Fock‐space coupled cluster approach

A valence‐universal multireference coupled cluster (VUMRCC) theory, realized via the eigenvalue independent partitioning (EIP) route, has been implemented with full inclusion of triples excitations for computing and analyzing the entire main and several satellite peaks in the ionization potential spectra of several molecules. The EIP‐VUMRCC method, unlike the traditional VUMRCC theory, allows divergence‐free homing‐in to satellite roots which would otherwise have been plagued by intruders, and is thus numerically more robust to obtain more efficient and dependable computational schemes allowing more extensive use of the approach. The computed ionization potentials (IPs) as a result of truncation of the (N−1) electron basis manifold involving virtual functions such as 2h‐p and 3h‐2p by different energy thresholds varying from 5 to 15 a.u. with 1 a.u. intervals as well as thresholds such as 20, 25, and 30 a.u. have been carefully looked into. Cutoff at around 25 a.u. turns out to be an optimal threshold. Molecules such as C₂H₄ and C₂H₂ (X = D,T), and N₂ and CO (X = D,T,Q) with Dunning's cc‐pVXZ bases have been investigated to determine all main and 2h‐p shake‐up and 3h‐2p double shake‐up satellite IPs. We believe that the present work will pave the way to a wider application of the method by providing main and satellite IPs for some problematic N‐electron closed shell systems. © 2013 Wiley Periodicals, Inc.     

A New Series of C‐6 Unsubstituted Tetrahydropyrimidines: Convenient One‐Pot Chemoselective Synthesis,Aggregation‐Induced and Size‐Independent Emission Characteristics

A new series of C‐6 unsubstituted tetrahydropyrimidines 6 have been directly synthesized via a convenient urea‐catalyzed chemoselective five‐component reaction (5CR) under mild conditions. Compounds 6 show typical aggregation‐induced emission enhancement (AIEE) characteristics because they are practically no emissive in solution but emit blue or green fluorescence in aggregates with fluorescence yield up to 93 %. One of the 5CR products, 6 aa , exhibits blue‐ and green‐fluorescence aggregates (bf‐ and gf‐aggregates). The bf‐ and gf‐aggregates are prepared under different conditions and proved to result from different J‐aggregations by single‐crystal X‐ray analysis. In addition, the bf‐ and gf‐aggregates of 6 aa show unusual size‐independent emission (SIE) characteristics because their maximum emission wavelengths in different sizes (suspension particles, film, powder and crystals) are the same, 434 and 484 nm, respectively. Based on the obtained experimental results, the 5CR mechanism, the origins of AIEE and SIE characteristics are discussed.     

面向高阶思维培养的自主型实验教学模式的设计与实践*

基于教育现代化、发展“互联网+教育”、培养创新性人才的指导思想,结合“超星学习通”网络平台与实验课堂的优势,设计了面向高阶思维培养的“预习自测-讲授讨论-自主实践-总结反思”的四段自主型实验教学模式,并应用于化学与化工类专业分析化学实验课程的教学实践。该实验教学模式增加了学生自主学习时间,培养了学生“分析、综合、评价和创造”等高阶思维能力,提高了实验课程的教学效率,为高等院校实践实验教学的改革提供了参考依据。     

CORSICA: correction of structured noise in fMRI by automatic identification of ICA components

When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR data sets (typically acquired with TR >1 s), such spatial priors can be applied to fMRI data, regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR data sets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.     

Derivative temporal clustering analysis: detecting prolonged neuronal activity

Temporal clustering analysis (TCA) and independent component analysis (ICA) are promising data-driven techniques in functional magnetic resonance imaging (fMRI) experiments to obtain brain activation maps in conditions with unknown temporal information regarding the neuronal activity. Although comparable to ICA in detecting transient neuronal activities, TCA fails to detect prolonged plateau brain activations. To eliminate this pitfall, a novel derivative TCA (DTCA) method was introduced and its algorithms with different subtraction intervals were tested on simulated data with a pattern of prolonged plateau brain activation. It was found that the best performance of DTCA method in generating functional maps could be obtained if the subtraction interval is equal to or larger than the length of the rising time of the fMRI response. The DTCA method and its theoretical predication were further investigated and validated using in vivo fMRI data sets. By removing the limitations in the previous TCA, DTCA has shown its powerful capability in detecting prolonged plateau neuronal activities.     

On independent sets in random graphs

The independence number of a sparse random graph G(n,m) of average degree d = 2m/n is well‐known to be with high probability, with in the limit of large d. Moreover, a trivial greedy algorithm w.h.p. finds an independent set of size , i.e., about half the maximum size. Yet in spite of 30 years of extensive research no efficient algorithm has emerged to produce an independent set with size for any fixed (independent of both d and n). In this paper we prove that the combinatorial structure of the independent set problem in random graphs undergoes a phase transition as the size k of the independent sets passes the point . Roughly speaking, we prove that independent sets of size form an intricately rugged landscape, in which local search algorithms seem to get stuck. We illustrate this phenomenon by providing an exponential lower bound for the Metropolis process, a Markov chain for sampling independent sets. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 436–486, 2015     

Entropy, independent sets and antichains: A new approach to Dedekind's problem

For -regular, -vertex bipartite graphs with bipartition , a precise bound is given for the sum over independent sets of the quantity . (In other language, this is bounding the partition function for certain instances of the hard-core model.) This result is then extended to graded partially ordered sets, which in particular provides a simple proof of a well-known bound for Dedekind's Problem given by Kleitman and Markowsky in 1975.

     

Uniform dimension results of multi-parameter stable processes

The problem of uniform dimensions for multi-parameter processes, which may not possess the uniform stochastic Hölder condition, is investigated. The problem of uniform dimension for multi-parameter stable processes is solved. That is, ifZ is a stable (N,d, α)-process and αN ?d, then $\forall E \subseteq \mathbb{R}_ + ^N , \dim Z\left( E \right) = \alpha \cdot \dim E$ holds with probability 1, whereZ(E) = {x : ?t ∈E,Z _t =x} is the image set ofZ onE. The uniform upper bounds for multi-parameter processes with independent increments under general conditions are also given. Most conclusions about uniform dimension can be considered as special cases of our results.