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

Containment Control of Multi-Agent Systems with Dynamic Leaders Based on a PInPI^n-Type Approach

This paper studies the containment control problem of multi-agent systems with multiple dynamic leaders in both the discrete-time domain and the continuous-time domain. The leaders' motions are described by $(n-1)$-order polynomial trajectories. This setting makes practical sense because given some critical points, the leaders' trajectories are usually planned by the polynomial interpolations. In order to drive all followers into the convex hull spanned by the leaders, a $PI^n$-type ($P$ and $I$ are short for {\it Proportion} and {\it Integration}, respectively; $I^n$ implies that the algorithm includes high-order integral terms) containment algorithm is proposed. It is theoretically proved that the $PI^n$-type containment algorithm is able to solve the containment problem of multi-agent systems where the followers are described by any order integral dynamics. Compared with the previous results on the multi-agent systems with dynamic leaders, the distinguished features of this paper are that: (1) the containment problem is studied not only in the continuous-time domain but also in the discrete-time domain while most existing results only work in the continuous-time domain; (2) to deal with the leaders with the $(n-1)$-order polynomial trajectories, existing results require the follower's dynamics to be $n$-order integral while the followers considered in this paper can be described by any-order integral; and (3) the "sign" function is not employed in the proposed algorithm, which avoids the chattering phenomenon. Furthermore, in order to illustrate the practical value of the proposed approach, an application, the containment control of multiple mobile robots is studied. Finally, two simulation examples are given to demonstrate the effectiveness of the proposed algorithm

Supercontinuum generation and carrier envelope offset frequency measurement in a tapered single-mode fiber

We report supercontinuum generation by launching femtosecond Yb fiber laser pulses into a tapered single-mode fiber of 3 um core diameter. A spectrum of more than one octave, from 550 to 1400 nm, has been obtained with an output power of 1.3 W at a repetition rate of 250 MHz, corresponding to a coupling efficiency of up to 60%. By using a typical f-2f interferometer, the carrier envelope offset frequency was measured and found to have a signal-to-noise ratio of nearly 30 dB.Comment: 10 pages, accepted by Appl Phys

Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion

The force field describing the calculated interaction between atoms or molecules is the key to the accuracy of many molecular dynamics (MD) simulation results. Compared with traditional or semi-empirical force fields, machine learning force fields have the advantages of faster speed and higher precision. We have employed the method of atomic cluster expansion (ACE) combined with first-principles density functional theory (DFT) calculations for machine learning, and successfully obtained the force field of the binary Fe-Co alloy. Molecular dynamics simulations of Fe-Co alloy carried out using this ACE force field predicted the correct phase transition range of Fe-Co alloy.Comment: 17 pages, 6 figure

catena-Poly[zinc(II)-bis­[μ2-3-(3-pyrid­yl)­benzoato]-κ2 O:N;κ2 N:O]

In the title compound, [Zn(C12H8NO2)2]n, the Zn2+ cation is coordinated by a pair of carboxyl­ate O atoms as well as two pyridyl N atoms to afford a distorted tetra­hedral environment. Adjacent Zn2+ cations, with a separation of 8.807 (2) Å, are linked by two 3-(3-pyrid­yl)benzoate ligand bridges, generating an infinite ribbon extending parallel to [001]

Homo- and Hetero-Dimers of CAD Enzymes Regulate Lignification and Abiotic Stress Response in Moso Bamboo

Lignin biosynthesis enzymes form complexes for metabolic channelling during lignification and these enzymes also play an essential role in biotic and abiotic stress response. Cinnamyl alcohol dehydrogenase (CAD) is a vital enzyme that catalyses the reduction of aldehydes to alcohols, which is the final step in the lignin biosynthesis pathway. In the present study, we identified 49 CAD enzymes in five Bambusoideae species and analysed their phylogenetic relationships and conserved domains. Expression analysis of Moso bamboo PheCAD genes in several developmental tissues and stages revealed that among the PheCAD genes, PheCAD2 has the highest expression level and is expressed in many tissues and PheCAD1, PheCAD6, PheCAD8 and PheCAD12 were also expressed in most of the tissues studied. Co-expression analysis identified that the PheCAD2 positively correlates with most lignin biosynthesis enzymes, indicating that PheCAD2 might be the key enzyme involved in lignin biosynthesis. Further, more than 35% of the co-expressed genes with PheCADs were involved in biotic or abiotic stress responses. Abiotic stress transcriptomic data (SA, ABA, drought, and salt) analysis identified that PheCAD2, PheCAD3 and PheCAD5 genes were highly upregulated, confirming their involvement in abiotic stress response. Through yeast two-hybrid analysis, we found that PheCAD1, PheCAD2 and PheCAD8 form homo-dimers. Interestingly, BiFC and pull-down experiments identified that these enzymes form both homo- and hetero- dimers. These data suggest that PheCAD genes are involved in abiotic stress response and PheCAD2 might be a key lignin biosynthesis pathway enzyme. Moreover, this is the first report to show that three PheCAD enzymes form complexes and that the formation of PheCAD homo- and hetero- dimers might be tissue specific

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

<p>Abstract</p> <p>Background</p> <p>To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC.</p> <p>Methods</p> <p>Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens.</p> <p>Results</p> <p>Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage.</p> <p>Conclusions</p> <p>Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.</p