口红持久度评价体系的建立

口红属于彩妆产品,与功效性产品的不同之处在于其既要带来美的感受又要追求妆容的即时效果。目前鲜有关于口红持妆力测试的论文,本研究旨在建立综合客观的口红持久度评价指标和分级图谱。对涂抹口红的志愿者进行人为干扰处理模拟口红脱妆过程,采集志愿者唇部图像并对口红颜色变化进行数据分析后建立数学模型,对口红持妆给予客观的量化判定,同时建立分级图谱。结果发现,在口红图像数据的客观化评价中,口红的颜色和颜色的均匀度是计算持妆指数的主要影响因素,所建立的口红持妆分级图谱将口红的持妆程度分为6个等级,一级为持妆率100%的状态,随着级别升高持妆率降低。建立了直观、量化的图谱和模型用于判定口红的持妆程度,为彩妆感官评价方法学的发展提供了全新的思路和数据支持。

Car-following Model and Its Stability under Ice and Snowfall Conditions

In order to describe the behavior of the car under ice and snowfall conditions more realistically,a vehicle following model based on the full velocity difference model is proposed under the premise of considering the speed difference and various kinds of ice and snowfall conditions. Under various road conditions,it obtains the critical stability curve of the model,and verifies that the worse the road condition is,the less stable the traffic flow is. In addition,the method of nonlinear analysis is used to obtain the solution of the kink density wave in the space headway under the unstable region. Finally,the conclusions are verified by numerical simulation,that worse road conditions,which means the road surface friction coefficient is small,will lead to greater instability region and worse anti-interference ability of traffic flow,and even cause more congestion and accidents. The conclusions make great contributions to handling the traffic jams and security issues under ice and snowfall conditions.

Extending Qualitative Probabilistic Network with Mutual Information Weights

Bayesian network (BN) is a well-accepted framework for representing and inferring uncertain knowledge. As the qualitative abstraction of BN, qualitative probabilistic network (QPN) is introduced for probabilistic inferences in a qualitative way. With much higher efficiency of inferences, QPNs are more suitable for real-time applications than BNs. However, the high abstraction level brings some inference conflicts and tends to pose a major obstacle to their applications. In order to eliminate the inference conflicts of QPN, in this paper, we begin by extending the QPN by adding a mutual-information-based weight (MI weight) to each qualitative influence in the QPN. The extended QPN is called MI-QPN. After obtaining the MI weights from the corresponding BN, we discuss the symmetry, transitivity and composition properties of the qualitative influences. Then we extend the general inference algorithm to implement the conflict-free inferences of MI-QPN. The feasibility of our method is verified by the results of the experiment.

Influence Maximization for Cascade Model with Diffusion Decay in Social Networks

Maximizing the spread of influence is to select a set of seeds with specified size to maximize the spread of influence under a certain diffusion model in a social network. In the actual spread process, the activated probability of node increases with its newly increasing activated neighbors, which also decreases with time. In this paper, we focus on the problem that selects k seeds based on the cascade model with diffusion decay to maximize the spread of influence in social networks. First, we extend the independent cascade model to incorporate the diffusion decay factor, called as the cascade model with diffusion decay and abbreviated as CMDD. Then, we discuss the objective function of maximizing the spread of influence under the CMDD, which is NP-hard. We further prove the monotonicity and submodularity of this objective function. Finally, we use the greedy algorithm to approximate the optimal result with the ration of 1 ? 1/e.

Selecting Seeds for Competitive Influence Spread Maximization in Social Networks

There exist two or more competing products in viral marketing, and the companies can exploit the social interactions of users to propagate the awareness of products. In this paper, we focus on selecting seeds for maximizing the competitive influence spread in social networks. First, we establish the possible graphs based on the propagation probability of edges, and then we use the competitive influence spread model (CISM) to model the competitive spread under the possible graph. Further, we consider the objective function of selecting k seeds of one product under the CISM when the seeds of another product have been known, which is monotone and submodular, and thus we use the CELF (cost-effective lazy forward) algorithm to accelerate the greedy algorithm that can approximate the optimal with 1 ? 1/e. Experimental results verify the feasibility and effectiveness of our method.

Adsorption behavior of imidacloprid pesticide on polar microplastics under environmental conditions:critical role of photo-aging

The photo-aging behavior of microplastics(MPs)in natural environment has become a global concern.The ultraviolet radiation has enough energy to change the polymer structure and physicalchemical properties of MPs.Less attention has focused on the interactions of the photo-aged polar and biodegradable MPs with organic pollutants.This work investigated the structural properties of aged polar polyamide(PA)MPs and biodegradable polylactic acid(PLA)MPs exposed to ultraviolet irradiation and their adsorption behavior and mechanism for neonicotinoid insecticide imidacloprid(IMI).The results showed that the MPs had extensive changes in surface morphology and chemical properties after photo-aging.The C–N bond of PA MPs was disrupted to form more carbonyl groups.The oxygen-containing functional groups on the surface of aged PLA MPs were broken and generated relatively smaller molecules.The adsorption capacity of IMI on PA MPs decreased by 19.2%,while the adsorption capacity of IMI on PLA MPs increased by 41.2%after photo-aging.This depended on the natural structure of the MPs and their ability to absorb ultraviolet light.The electrostatic interactions,hydrogen bonds,van der Waals interactions,and polar-polar interactions were the main adsorption mechanisms of IMI on MPs.High initial solution pH and low ionic strength favored the adsorption of IMI by altering charge distribution on the MPs surface.The formation of the humic acid-IMI complexes decreased the concentration of IMI in the water phase and further decreased the adsorption on MPs.These results are enlightening for a scientific comprehension of the environmental behavior of the polar MPs.

A review on analytical methods for pharmaceutical and personal care products and their transformation products

Pharmaceutical and personal care products(PPCPs)and corresponding transformation products have caused widespread concern due to their persistent emissions and potential toxicity.They have wide octanol-water partition coefficients(K_(ow))and different ionization constants(pK_(a))resulting in a poor analysis accuracy and efficiency.A suitable analytical method is the first prerequisite for further research on their environmental behavior to prioritize the substances.This study reviewed a full-scale analytical protocol for environmental samples in the recent ten years:from sampling to instrumental methods.Passive sampling techniques were compared and recommended for long-term continuous and scientific observation.A quick and effective sample extraction and clean-up method are highly required.Chromatographic methods coupled to mass spectrometry for determining PPCPs with a wide range of logK_(ow)(-7.53 to 10.80)were summed up.High-resolution mass spectrometry was confirmed to be a promising strategy for screening unknown transformation products,which would provide a nanogram level of detection limits and more accurate mass resolution.Screening strategies and mass change principles were summarized in detail.The recovery rate was important in multiple contaminants analysis identification and factors affecting the recovery rate of PPCPs were also discussed in this review,including sample matrix,target compounds characteristics,extraction method and solid-phase adsorbent.This review provides useful information for the selection of appropriate analytical methods and future development directions.

Fate and risk assessment of emerging contaminants in reclaimed water production processes

Reclaimed water has been widely applied in irrigation and industrial production.Revealing the behavior of emerging contaminants in the production process of reclaimed water is the first prerequisite for developing relevant water quality standards.This study investigated 43 emerging contaminants,including 22 pharmaceuticals and personal care products(PPCPs),11 organophosphorus flame retardants(OPFRs),and 10 antibiotic resistance genes(ARGs)in 3 reclaimed wastewater treatment plants(RWTPs)in Beijing.The composition profiles and removal efficiencies of these contaminants in RWTPs were determined.The results indicated that the distribution characteristics of the different types of contaminants in the three RWTPs were similar.Caffeine,sul2 and tris(1-chloro-2-propyl)phosphate were the dominant substances in the wastewater,and their highest concentrations were 27104 ng/L,1.4×10^(7) copies/mL and 262 ng/L,respectively.Ofloxacin and sul2 were observed to be the dominant substances in the sludge,and their highest concentrations were 5419 ng/g and 3.7×10^(8) copies/g,respectively.Anaerobic/anoxic/oxic system combined with the membrane bioreactor process achieved a relatively high aqueous removal of PPCPs(87%).ARGs and OPFRs were challenging to remove,with average removal rates of 6.5%and 31%,respectively.Quantitative meta-analysis indicated that tertiary treatment processes performed better in emerging contaminant removal than secondary processes.Diethyltoluamide exhibited the highest mass load discharge,with 33.5 mg/d per 1000 inhabitants.Octocrylene and tris(2-ethylhexyl)phosphate posed high risks(risk quotient>1.0)to aquatic organisms.This study provides essential evidence to screen high priority pollutants and develop corresponding standard in RWTPs.

Associative categorization of frequent patterns based on the probabilistic graphical model

Discovering the hierarchical structures of differ- ent classes of object behaviors can satisfy the requirements of various degrees of abstraction in association analysis, be- havior modeling, data preprocessing, pattern recognition and decision making, etc. In this paper, we call this process as associative categorization, which is different from classical clustering, associative classification and associative cluster- ing. Focusing on representing the associations of behaviors and the corresponding uncertainties, we propose the method for constructing a Markov network （MN） from the results of frequent pattern mining, called item-associative Markov net- work （IAMN）, where nodes and edges represent the frequent patterns and their associations respectively. We further dis- cuss the properties of a probabilistic graphical model to guar- antee the IAMN＇s correctness theoretically. Then, we adopt the concept of chordal to reflect the closeness of nodes in the IAMN. Adopting the algorithm for constructing join trees from an MN, we give the algorithm for IAMN-based associa- tive categorization by hierarchical bottom-up aggregations of nodes. Experimental results show the effectiveness, efficiency and correctness of our methods.

Asymmetries of Positive Feedback Trading in Individual Stocks:Evidences from China

The paper investigates the positive feedback trading phenomenon of individual stocks in China’s stock market.Heterogeneous regression models and a non-parametric Sentana-Wadhwani model are developed and applied to prove the existence of rise-favor asymmetric feedback trading.This result is consistent with the reality of China’s stock market,that is,the herding behavior of irrational retail investors has a significant influence on the market.However,the result is in contrast with the stylized findings using market indices.Further empirical research shows that this distinction could be explained by the average effect of indices.The asymmetries of positive feedback trading caused by heterogeneous feedback trading and the uneven distributed retail trading in individual stocks,are covered by the weighted average effect in indices.Therefore,the indices exhibit a different asymmetric pattern from that of individual stocks.