A Test of the Martingale Hypothesis

This paper proposes a statistical test of the martingale hypothesis. It can be used to test whether a given time series is a martingale process against certain non-martingale alternatives. The class of alternative processes against which our test has power is very general and it encompasses many nonlinear non-martingale processes which may not be detected using traditional spectrum-based or variance-ratio tests. We look at the hypothesis of martingale, in contrast with other existing methods which test for the hypothesis of martingale difference. Two different types of test are considered: one is a generalized Kolmogorov-Smirnov test and the other is a Cramer-von Mises type test. For the processes that are first order Markovian in mean, in particular, our approach yields the test statistics that neither depend upon any smoothing parameter nor require any resampling procedure to simulate the null distributions. Their null limiting distributions are nicely characterized as functionals of a continuous stochastic process so that the critical values are easily tabulated. We prove consistency of our tests and further investigate their finite sample properties via simulation. Our tests are found to be rather powerful in moderate size samples against a wide variety of non-martingales including exponential autoregressive, threshold autoregressive, markov switching, chaotic, and some of nonstationary processes.

Multi-jet electrospinning of polystyrene/polyamide 6 blend: thermal and mechanical properties

Citation: Yoon, J. W., Park, Y., Kim, J., & Park, C. H. (2017). Multi-jet electrospinning of polystyrene/polyamide 6 blend: thermal and mechanical properties. Fashion and Textiles, 4, 12. doi:10.1186/s40691-017-0090-4Polystyrene (PS) has high thermal resistance thus can be applied as thermally comfortable textile. However, the application is limited due its low mechanical strength. In this study, polyamide 6 (PA6) was blended with PS to improve the mechanical strength of PS, by means of a multi-jet electrospinning. Content ratio of the blend web was measured by chemical immersion test and confocal microscopy analysis. Fiber content was in accordance with the number of syringes used for PS and PA6 respectively. The effects of content ratio on the web morphology, thermal resistance, tensile behavior, air and water vapor permeability, and surface hydrophilicity were investigated. The influence of environmental humidity during electrospinning process on three dimensional (3D) web structure was also reported. PS web produced from higher humidity had more pores and corrugations at the surface. The increased surface roughness and porosity led to the increased hydrophobicity and thermal resistance. Though the blending of PA6 with PS enhanced the mechanical strength, the added PA6 decreased air/water vapor permeability and thermal resistance. The lowered thermal resistance by the addition of PA6 was mainly attributed to higher thermal conductivity of PA6 material and lowered air content with PA6 fibers

Toward a Better Understanding of Loss Functions for Collaborative Filtering

Collaborative filtering (CF) is a pivotal technique in modern recommender systems. The learning process of CF models typically consists of three components: interaction encoder, loss function, and negative sampling. Although many existing studies have proposed various CF models to design sophisticated interaction encoders, recent work shows that simply reformulating the loss functions can achieve significant performance gains. This paper delves into analyzing the relationship among existing loss functions. Our mathematical analysis reveals that the previous loss functions can be interpreted as alignment and uniformity functions: (i) the alignment matches user and item representations, and (ii) the uniformity disperses user and item distributions. Inspired by this analysis, we propose a novel loss function that improves the design of alignment and uniformity considering the unique patterns of datasets called Margin-aware Alignment and Weighted Uniformity (MAWU). The key novelty of MAWU is two-fold: (i) margin-aware alignment (MA) mitigates user/item-specific popularity biases, and (ii) weighted uniformity (WU) adjusts the significance between user and item uniformities to reflect the inherent characteristics of datasets. Extensive experimental results show that MF and LightGCN equipped with MAWU are comparable or superior to state-of-the-art CF models with various loss functions on three public datasets.Comment: Accepted by CIKM 202

Isolation of p-hydroxycinnamaldehyde as an antibacterial substance from the saw fly, Acantholyda parki S.

AbstractWe purified an antibacterial substance from larvae of the saw fly, Acantholyda parki S., and identified its molecular structure as p-hydroxycinnamaldehyde. We then synthesized it by reduction of p-hydroxycinnamic acid. The antibacterial activity of the synthetic p-hydroxycinnamaldehyde was equal to that of the authentic substance. This molecule was found to have a broad antibacterial spectrum against not only Gram-negative, but also Gram-positive bacteria. Furthermore, it showed antifungal activity against Candida albicans. We suggest that this substance may play a role in the defense system of this insect. This is the first report of p-hydroxycinnamaldehyde of animal origin