A dynamic free-entry oligopoly with sluggish entry and exit adjustments

We study a dynamic free-entry oligopoly with sluggish entry and exit of firms under general demand and cost functions. We show that the number of firms in a steady-state open-loop solution for a dynamic free-entry oligopoly is smaller than that at static equilibrium and that the number of firms in a steady-state memoryless closed-loop solution is larger than that in an open-loop solution.     

Prospects for the combination of mechanochemistry and flow applied to catalytic transformations

The urge of developing modern alternatives regarding industrial production has led to the creation of novel techniques that help overcome critical disadvantages from traditional batch mechanochemistry. One promising strategy includes the merging of flow processes with mechanochemistry. Two technologies are herein highlighted: twin-screw extrusion (TSE) and Impact (induction) in Continuous flow HEated Mechanochemistry (I-CHEM) allowing not only the industrial production of polymers but also active pharmaceutical ingredients, synthesis of (nano)materials, and the obtention of high-added value products from biomass and wastes valorization.     

工业催化:选择性提升策略

工业催化直接或间接贡献了世界GDP的20%-30%,推动了产业变革和社会进步.对于工业催化,开发高活性、高选择性和高稳定性的多相催化剂至关重要,而选择性是最主要的挑战.因为实现催化选择性的精确控制是绿色化学的重要概念之一,更是工业催化可持续发展的重要驱动力;而且,选择性不仅决定了催化过程的原子经济性,也影响到后续分离过程的能耗.针对多数工业催化反应存在'活性越高、选择性越低'的相互制约与矛盾问题,本文以若干能源化工催化反应为例,试图总结催化选择性提升的一般策略,以期为有关工业应用的催化新过程提供科学参考.多相催化一般经历与反应物有关的步骤(反应物的外扩散、内扩散和化学吸附)、与反应有关的步骤(活化和表面反应)、以及与产物相关的步骤(产物脱附、内扩散和外扩散).本文依此归纳并举例说明提高选择性的一般策略.在汽油催化吸附脱硫中,主要利用了催化剂中零价镍-氧化锌耦合活性中心的选择吸附策略,使零价镍优先吸附含硫化合物,从而实现选择性脱硫而不饱和烯烃.在甲苯和甲醇侧链烷基化反应中,主要利用了特定空间分布的酸碱吸附位,实现吸附甲苯和稳定甲醛中间体的协同匹配.在乙苯脱乙基型二甲苯异构化反应中,主要利用了双床层对催化剂功能的分离策略,在不同的择形催化剂床层中分别进行乙苯脱乙基反应和二甲苯异构化反应,从而提高对二甲苯的产量.在苯选择加氢制环己烯反应中,主要利用强化产品脱附的策略,促进环己烯产品从亲水改性的催化剂表面脱附,实现环己烯选择性的提升.这些炼油与化工研究案例中同时存在多个连串-平行反应,主要是利用吸附中心、反应中心在时间或空间上的耦合、解耦或限域策略,调控不同途径的扩散能垒、反应能垒,实现了催化剂选择性的提升.多相催化多是复杂过程,基于提高选择性的初步认识,还要结合具体复杂催化过程,系统研究单策略以及多策略组合作用下的选择催化过程,实现在合理时间尺度、空间尺度上设计高选择性的催化剂,而这本质上是一种介尺度催化.     

波士顿矩阵法在河南承接产业转移中的应用

承接产业转移是加速区域经济发展的"助推器",提升产业集聚能力是提高区域产业竞争力的关键,如何科学地选择承接产业,并提升产业集聚能力是河南亟待解决的问题.选取2010年和2014年两个时点,运用产业梯度系数和产业动态集聚指数对工业进行分行业分析,并借鉴波士顿矩阵分析法将其划分为明星、金牛、问题、瘦狗和衰退等产业.根据河南的自然资源、劳动力、区位条件、市场需求等比较优势,并考虑产业集聚发展的能力,来确定河南承接产业转移的重点产业.     

A switching-based Moving Target Defense against sensor attacks in control systems

Moving Target Defense (MTD) prevents adversaries from being able to predict the effect of their attacks by adding uncertainty in the state of a system during runtime. In this paper, we present an MTD algorithm that randomly changes the availability of the sensor data, so that it is difficult for adversaries to tailor stealthy attacks while, at the same time, minimizing the impact of false-data injection attacks. Using tools from the design of state estimators, namely, observers, and switched systems, we formulate an optimization problem to find the probability of the switching signals that increase the visibility of stealthy attacks while decreasing the deviation caused by false data injection attacks. We show that the proposed MTD algorithm can be designed to guarantee the stability of the closed-loop system with desired performance. In addition, we formulate an optimization problem for the design of the parameters so as to minimize the impact of the attacks. The results are illustrated in two case studies, one about a generic linear time-invariant system and another about a vehicular platooning problem.     

Near infrared spectroscopy and multivariate analysis to evaluate wheat flour doughs leavening and bread properties

A mixture design of experiment approach was followed to explore formulation effects on the technological properties of wheat flours optimized for industrial bread-making purposes. Ten different flour mixtures were investigated by means of near infrared spectroscopy (NIRS) to obtain information on flour performance in a critical phase such as dough leavening. For each mixture, a laboratory-scale bread making experiment was carried out according to a standardized recipe and the leavening phase of each dough sample was monitored by means of NIRS at different times. Parallel factor analysis (PARAFAC) was used to highlight the existence of differences among the mixtures on the basis of NIR spectrum variability with respect to the leavening time. Additionally, the relationship among the 3-way NIR dataset and some parameters measured on the baked bread loaves (dimensions, volume, weight) was investigated by means of the n-way extension of partial least squares regression (nPLS), in order to evaluate product properties from its leavening step and mixture formulation. The results give better insight on the relationships among wheat flour formulation and its performance in the leavening phase and as far as some properties of the final product are concerned, thus offering a way to monitor the leavening phase and give information on its influence on the final product properties.     

Remediation of azo-dyes based toxicity by agro-waste cotton boll peels mediated palladium nanoparticles

The present study reports an environmental benign route for the synthesis of palladium nanoparticles (Pd NPs) using agro-waste empty cotton boll peels aqueous extract for the first time. Surface Plasmon Resonance (SPR) band in absorption spectrum of Pd NPs at 275 nm confirmed the formation of Pd NPs by using UV–Vis spectroscopy. Crystalline nature of Pd NPs was confirmed by powder XRD analysis. Size and morphology was studied by transmission electron microscopy (TEM). The cotton peels extract acted as a source of phytochemicals which primarily reduced Pd⁺² to Pd⁰ nanoparticles (Pd NPs) and imparted stability of Pd NPs by surface capping. The characteristic functional groups of phytochemicals in extract and capped Pd NPs surfaces were identified by FT-IR analysis. Catalytic activity of the synthesised Pd NPs was checked against reduction of hazardous azo-dyes such as Congo red, Methyl orange, Sunset yellow and Tartrazine with NaBH₄ as electron donors. Pd NPs catalysed reduction of all azo-dyes by NaBH₄ in aqueous medium was monitored by UV–visible spectroscopy where Pd NPs mediated transfer of electrons from NaBH₄ to azo-dyes as carrier. The synthesized Pd NPs acted as a good catalyst and could be a promising material in degrading toxic azo-dyes from industrial effluents and wastewater.     

Simulation of metastable zone width and induction time for a seeded aqueous solution of potassium sulfate

The metastable zone width (MSZW, ΔT_m) and induction time (t_ind) were determined with computer simulation for seeded batch crystallization of potassium sulfate from aqueous solution. The MSZW and induction time determined with simulation showed the same behavior as experimental values reported in the literature; log (ΔT_m) increased linearly with an increase in log R (R: cooling rate) and t_ind decreases in proportion to (ΔT)⁻ⁿ (ΔT: supercooling, n: nucleation order in the secondary rate expression of B=k_n(ΔT)ⁿ). The secondary nucleation parameters (k_n and n) were deduced both from the simulated MSZW and induction times by using the previously proposed model [J. Cryst. Growth, 2010, 312, 548–554]. The secondary nucleation rate calculated with the deduced parameters was in agreement with that calculated with the parameters input for simulation.     

On the predictive ability of narrative disclosures in annual reports

We investigate whether narrative disclosures in 10-K and 10K-405 filings contain value-relevant information for predicting market performance. We apply text classification techniques from computer science to machine code text disclosures in a sample of 4280 filings by 1236 firms over five years. Our methodology develops a model using documents and actual performance for a training sample. This model, when applied to documents from a test set, leads to performance prediction. We find that a portfolio based on model predictions earns significantly positive size-adjusted returns, indicating that narrative disclosures contain value-relevant information. Supplementary analyses show that the text classification model captures information not contained in document-level features of clarity, tone and risk sentiment considered in prior research. However, we find that the narrative score is not providing information incremental to traditional predictors such as size, market-to-book and momentum, but rather affects investors’ use of price momentum as a factor that predicts excess returns.