Modeling mode choice behavior incorporating household and individual sociodemographics and travel attributes based on rough sets theory

Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxing county which contains information on both household and individual travel behaviors for model estimation and evaluation. The knowledge is presented in the form of easily understood IF-THEN statements or rules which reveal how each attribute influences mode choice behavior. These rules are then used to predict travel mode choices from information held about previously unseen individuals and the classification performance is assessed. The rough sets model shows high robustness and good predictive ability. The most significant condition attributes identified to determine travel mode choices are gender, distance, household annual income, and occupation. Comparative evaluation with the MNL model also proves that the rough sets model gives superior prediction accuracy and coverage on travel mode choice modeling

Cytotoxicity in the Age of Nano: The Role of Fourth Period Transition Metal Oxide Nanoparticle Physicochemical Properties

A clear understanding of physicochemical factors governing nanoparticle toxicity is still in its infancy. We used a systematic approach to delineate physicochemical properties of nanoparticles that govern cytotoxicity. The cytotoxicity of fourth period metal oxide nanoparticles (NPs): TiO2, Cr2O3, Mn2O3, Fe2O3, NiO, CuO, and ZnO increases with the atomic number of the transition metal oxide. This trend was not cell-type specific, as observed in non-transformed human lung cells (BEAS-2B) and human bronchoalveolar carcinoma-derived cells (A549). Addition of NPs to the cell culture medium did not significantly alter pH. Physiochemical properties were assessed to discover the determinants of cytotoxicity: (1) point-of-zero charge (PZC) (i.e., isoelectric point) described the surface charge of NPs in cytosolic and lysosomal compartments; (2) relative number of available binding sites on the NP surface quantified by X-ray photoelectron spectroscopy was used to estimate the probability of biomolecular interactions on the particle surface; (3) band-gap energy measurements to predict electron abstraction from NPs which might lead to oxidative stress and subsequent cell death; and (4) ion dissolution. Our results indicate that cytotoxicity is a function of particle surface charge, the relative number of available surface binding sites, and metal ion dissolution from NPs. These findings provide a physicochemical basis for both risk assessment and the design of safer nanomaterials

Comparative genome analysis of plant ascomycete fungal pathogens with different lifestyles reveals distinctive virulence strategies

Background: Pathogens have evolved diverse lifestyles and adopted pivotal new roles in both natural ecosystems and human environments. However, the molecular mechanisms underlying their adaptation to new lifestyles are obscure. Comparative genomics was adopted to determine distinct strategies of plant ascomycete fungal pathogens with different lifestyles and to elucidate their distinctive virulence strategies. Results: We found that plant ascomycete biotrophs exhibited lower gene gain and loss events and loss of CAZyme-encoding genes involved in plant cell wall degradation and biosynthesis gene clusters for the production of secondary metabolites in the genome. Comparison with the candidate effectome detected distinctive variations between plant biotrophic pathogens and other groups (including human, necrotrophic and hemibiotrophic pathogens). The results revealed the biotroph-specific and lifestyle-conserved candidate effector families. These data have been configured in web-based genome browser applications for public display (http://lab.malab.cn/soft/PFPG). This resource allows researchers to profile the genome, proteome, secretome and effectome of plant fungal pathogens. Conclusions: Our findings demonstrated different genome evolution strategies of plant fungal pathogens with different lifestyles and explored their lifestyle-conserved and specific candidate effectors. It will provide a new basis for discovering the novel effectors and their pathogenic mechanisms