Universal deformation rings and self-injective Nakayama algebras

Let k be a field and let Λ be an indecomposable finite dimensional k-algebra such that there is a stable equivalence of Morita type between Λ and a self-injective split basic Nakayama algebra over k. We show that every indecomposable finitely generated Λ-module V has a universal deformation ring $R(\mathrm{\Lambda },V)$ and we describe $R(\mathrm{\Lambda },V)$ explicitly as a quotient ring of a power series ring over k in finitely many variables. This result applies in particular to Brauer tree algebras, and hence to p-modular blocks of finite groups with cyclic defect groups.     

On the Effect of Secondary Nucleation on Deracemization through Temperature Cycles

Herein, the pivotal role of secondary nucleation in a crystallization-enhanced deracemization process is reported. During this process, complete and rapid deracemization of chiral conglomerate crystals of an isoindolinone is attained through fast microwave-assisted temperature cycling. A parametric study of the main factors that affect the occurrence of secondary nucleation in this process, namely agitation rate, suspension density, and solute supersaturation, confirms that an enhanced stereoselective secondary nucleation rate maximizes the deracemization rate. Analysis of the system during a single temperature cycle showed that, although stereoselective particle production during the crystallization stage leads to enantiomeric enrichment, undesired kinetic dissolution of smaller particles of the preferred enantiomer occurs during the dissolution step. Therefore, secondary nucleation is crucial for the enhancement of deracemization through temperature cycles and as such should be considered in further design and optimization of this process, as well as in other temperature cycling processes commonly applied in particle engineering.     

Secondary Formation of Aromatic Nitroderivatives of Environmental Concern: Photonitration Processes Triggered by the Photolysis of Nitrate and Nitrite Ions in Aqueous Solution

Aromatic nitroderivatives are compounds of considerable environmental concern, because some of them are phytotoxic (especially the nitrophenols, and particularly 2,4-dinitrophenol), others are mutagenic and potentially carcinogenic (e.g., the nitroderivatives of polycyclic aromatic hydrocarbons, such as 1-nitropyrene), and all of them absorb sunlight as components of the brown carbon. The latter has the potential to affect the climatic feedback of atmospheric aerosols. Most nitroderivatives are secondarily formed in the environment and, among their possible formation processes, photonitration upon irradiation of nitrate or nitrite is an important pathway that has periodically gained considerable attention. However, photonitration triggered by nitrate and nitrite is a very complex process, because the two ionic species under irradiation produce a wide range of nitrating agents (such as ^•NO₂, HNO₂, HOONO, and H₂OONO⁺), which are affected by pH and the presence of organic compounds and, in turn, deeply affect the nitration of aromatic precursors. Moreover, aromatic substrates can highly differ in their reactivity towards the various photogenerated species, thereby providing different behaviours towards photonitration. Despite the high complexity, it is possible to rationalise the different photonitration pathways in a coherent framework. In this context, this review paper has the goal of providing the reader with a guide on what to expect from the photonitration process under different conditions, how to study it, and how to determine which pathway(s) are prevailing in the formation of the observed nitroderivatives.     

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。     

The survival probability of critical and subcritical branching processes in finite state space Markovian environment

Let ${\left(Z_n\right)}_{n\ge 0}$ be a branching process in a random environment defined by a Markov chain ${\left(X_n\right)}_{n\ge 0}$ with values in a finite state space $\mathbb{X}$. Let ${\mathbb{P}}_i$ be the probability law generated by the trajectories of ${\left(X_n\right)}_{n\ge 0}$ starting at $X_0=i\in \mathbb{X}.$ We study the asymptotic behaviour of the joint survival probability ${\mathbb{P}}_i\left(Z_n>0,X_n=j\right)$, $j\in \mathbb{X}$ as $n\to +\infty$ in the critical and strongly, intermediate and weakly subcritical cases.     

Heavy tails for an alternative stochastic perpetuity model

In this paper we consider a stochastic model of perpetuity-type. In contrast to the classical affine perpetuity model of Kesten (1973) and Goldie (1991) all discount factors in the model are mutually independent. We prove that the tails of the distribution of this model are regularly varying both in the univariate and multivariate cases. Due to the additional randomness in the model the tails are not pure power laws as in the Kesten–Goldie setting but involve a logarithmic term.     

Neural network modeling of hydrological systems: A review of implementation techniques

This paper presents a review of procedural steps and implementation techniques used in the development of artificial intelligence models, generally referred to as artificial neural networks (ANNs), within the water resources domain. It focusses on identifying different areas wherein ANNs have found application thereby elucidating its advantages and disadvantages as well as various challenges encountered in its use. Results from this review provide useful insights into how the performance of ANNs can be improved and potential areas of application that are yet to be explored in hydrological modeling. Recommendations for Resource Managers

• Development of integrated and hybrid artificial intelligent tools is critical to achieving improved forecasts in hydrological modeling studies.

• Further research into comprehending the internal mechanisms of neural networks is required to obtain a practical meaning of each network component deployed to solve real‐world problems.

• More robust optimization techniques and tools like differential evolution, particle swarm optimization and deep neural nets, are yet to be fully explored in the water resources analysis, and should be given more attention to enhance neural networks aptitude for modeling complex and nonlinear hydrological processes.

     

高中化学创新实验课程的设计与实施*

将学生所学的化学理论知识与生活实际和学科最前沿的研究热点相结合,开发并实施了 “氢氧化镁纳米材料的制备及其在处理重金属废水中的应用” 创新实验课程。该课程通过文献调研、方案设计、实验操作、结果与讨论以及论文撰写等环节,激发学生的创新潜能,系统培养学生的创新综合素质和责任意识,这有助于更好地达成化学学科核心素养。     

金色梦想，一触即发——化学专业校外实践教学基地建设与思考

高等教育要适应世界潮流和时代变化,本科教育须进一步提高实践教学的比重,加强理论教学与实践教学相结合,完善协同育人机制。结合学科发展和企业发展需求,中山大学化学学院与金发科技股份有限公司(简称金发科技)共同建设大学生实践教学基地。本文以中山大学-金发科技本科实践教学基地为例,探讨大学生校外实践基地建设过程中遇到的问题以及实践基地的建设内容与成果体会。