Supersymmetric KdV equation: Darboux transformation and discrete systems

For the supersymmetric KdV equation, a proper Darboux transformation is presented. This Darboux transformation leads to the B\"{a}cklund transformation found early by Liu and Xie \cite{liu2}. The Darboux transformation and the related B\"{a}cklund transformation are used to construct integrable super differential-difference and difference-difference systems. The continuum limits of these discrete systems and of their Lax pairs are also considered.Comment: 13pages, submitted to Journal of Physics

An Examination Of Underreporting Of Time And Premature Signoffs By Internal Auditors

The passage of the Sarbanes-Oxley Act of 2002 (SOX) heightened the importance of internal controls and accordingly, a key control - the internal audit function.  Consequently, management and external auditors have both increased their reliance on internal auditors’ work.  While there has been considerable research regarding the impact of the underreporting of time and premature sign-offs on the external audit, there has only been one study that has examined the impact of these two items on the internal auditors’ work.  Such research is dated (1994) and prior to the passage of SOX.  We surveyed members of the Institute of Internal Auditors (IIA) in the Midwest to examine their behavior and perceptions regarding these two items.  The respondents in our study believe the underreporting of time is unethical and is supported by their reporting of all time worked, even if such time exceeded the budget.  Our findings also show that the respondents feel premature sign-offs are unethical and result primarily from lack of professional skepticism and inadequate training.  Increasing training in audit areas and improving communications within the audit team are possible solutions to reduce premature sign-offs.  Premature sign-offs are more likely to occur in operational audits and to a lesser degree in financial audits and compliance audits.&nbsp

Multi-task learing for subspace segmentation

Subspace segmentation is the process of clustering a set of data points that are assumed to lie on the union of multiple linear or affine subspaces, and is increasingly being recognized as a fundamental tool for data analysis in high dimensional settings. Arguably one of the most successful approaches is based on the observation that the sparsest representation of a given point with respect to a dictionary formed by the others involves nonzero coefficients associated with points originating in the same subspace. Such sparse representations are computed independently for each data point via ℓ1-norm minimization and then combined into an affinity matrix for use by a final spectral clustering step. The downside of this procedure is two-fold. First, unlike canonical compressive sensing scenarios with ideally-randomized dictionaries, the data-dependent dictionaries here are unavoidably highly structured, disrupting many of the favorable properties of the ℓ1 norm. Secondly, by treating each data point independently, we ignore useful relationships between points that can be leveraged for jointly computing such sparse representations. Consequently, we motivate a multi-task learning-based framework for learning coupled sparse representations leading to a segmentation pipeline that is both robust against correlation structure and tailored to generate an optimal affinity matrix. Theoretical analysis and empirical tests are provided to support these claims.Y. Wang is sponsored by the University of Cambridge Overseas Trust. Y. Wang and Q. Ling are partially supported by sponsorship from Microsoft Research Asia. Q. Ling is also supported in part by NSFC grant 61004137. W. Chen is supported by EPSRC Research Grant EP/K033700/1 and the Natural Science Foundation of China 61401018.This is the final version of the article. It first appeared from JMLR via http://jmlr.org/proceedings/papers/v37/wangc15.htm

TimeMachine: Timeline Generation for Knowledge-Base Entities

We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.Comment: To appear at ACM SIGKDD KDD'15. 12pp, 7 fig. With appendix. Demo and other info available at http://cs.stanford.edu/~althoff/timemachine

Optimization of enantioselective production of chiral epichlorohydrin catalyzed by a novel epoxide hydrolase from domestic duck liver by response surface methodology

Enantiopure epichlorohydrin is a valuable epoxide intermediate for preparing optically active pharmaceuticals. In the present study, a novel epoxide hydrolase prepared from domestic duck liver was used as biocatalyst for producing (S)-epichlorohydrin which preparation process was optimized by response surface methodology. Response surface methodology was performed to evaluate the effects of reaction temperature, pH and reaction time on production of (S)-epichlorohydrin by the novel epoxide hydrolase. (S)-epichlorohydrin production was optimized by Box-Behnken. Three reaction parameters were optimized as follows: pH value 7.10, reaction temperature 32.44°C and reaction time11.06 h. The adequately high R2 value 0.9599 and F score 13.29 indicated the statistical significance of the model. The enantioselective excess of (S)-epichlorohydrin after optimization was 86.14% while thepredicted value was 85.55%. In conclusion, enantioselective hydrolysis conditions optimization to enhance optical purity of (S)-epichlorohydrin could be easily and effectively done by response surfacemethodology; the developed production process indicated the novel epoxide hydrolase from domestic duck liver was high efficient biocatalyst for preparing enantiopure epichlorohydrin

Demonstrating Additional Law of Relativistic Velocities based on Squeezed Light

Special relativity is foundation of many branches of modern physics, of which theoretical results are far beyond our daily experience and hard to realized in kinematic experiments. However, its outcomes could be demonstrated by making use of convenient substitute, i.e. squeezed light in present paper. Squeezed light is very important in the field of quantum optics and the corresponding transformation can be regarded as the coherent state of SU(1; 1). In this paper, the connection between the squeezed operator and Lorentz boost is built under certain conditions. Furthermore, the additional law of relativistic velocities and the angle of Wigner rotation are deduced as well

Vertically Aligned Gold Nanorod Monolayer on Arbitrary Substrates: Self-Assembly and Femtomolar Detection of Food Contaminants

Cataloged from PDF version of article.Public attention to the food scandals raises an urgent need to develop effective and reliable methods to detect food contaminants. The current prevailing detections are primarily based upon liquid chromatography, mass spectroscopy, or colorimetric methods, which usually require sophisticated and time-consuming steps or sample preparation. Herein, we develop a facile strategy to assemble the vertically aligned monolayer of Au nanorods with a nominal 0.8 nm gap distance and demonstrate their applications in the rapid detection of plasticizers and melamine contamination at femtomolar level by surface-enhanced Raman scattering spectroscopy (SERS). The SERS signals of plasticizers are sensitive down to 0.9 fM concentrations in orange juices. It is the lowest detection limit reported to date, which is 7 orders of magnitude lower than the standard of United States (6 ppb). The highly organized vertical arrays generate the reproducible "SERS-active sites" and can be achieved on arbitrary substrates, ranging from silicon, gallium nitride, glass to flexible poly(ethylene naphthalate) substrates