Risk-Management Practices for Specialty-Crop Producers in California, Florida, New York, and Pennsylvania

Crop Production/Industries, Risk and Uncertainty,

Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity

We propose a dynamic factor model for the analysis of multivariate time series count data. Our model allows for idiosyncratic as well as common serially correlated latent factors in order to account for potentially complex dynamic interdependence between series of counts. The model is estimated under alternative count distributions (Poisson and negative binomial). Maximum Likelihood estimation requires high-dimensional numerical integration in order to marginalize the joint distribution with respect to the unobserved dynamic factors. We rely upon the Monte-Carlo integration procedure known as Efficient Importance Sampling which produces fast and numerically accurate estimates of the likelihood function. The model is applied to time series data consisting of numbers of trades in 5 minutes intervals for five NYSE stocks from two industrial sectors. The estimated model accounts for all key dynamic and distributional features of the data. We find strong evidence of a common factor which we interpret as reflecting market-wide news. In contrast, sector-specific factors are found to be statistically insignifficant. --Dynamic latent variables,Importance sampling,Mixture of distribution models,Poisson distribution,Simulated Maximum Likelihood

Development and application of a self-referencing glucose microsensor for the measurement of glucose consumption by pancreatic ?-cells

Glucose gradients generated by an artificial source and ?-cells were measured using an enzyme-based glucose microsensor, 8-?m tip diameter, as a self-referencing electrode. The technique is based on a difference measurement between two locations in a gradient and thus allows us to obtain real-time flux values with minimal impact of sensor drift or noise. Flux values were derived by incorporation of the measured differential current into Fick's first equation. In an artificial glucose gradient, a flux detection limit of 8.2 ± 0.4 pmol·cm-2·s-1 (mean ± SEM, n = 7) with a sensor sensitivity of 7.0 ± 0.4 pA/mM (mean ± SEM, n = 16) was demonstrated. Under biological conditions, the glucose sensor showed no oxygen dependence with 5 mM glucose in the bulk medium. The addition of catalase to the bulk medium was shown to ameliorate surface-dependent flux distortion close to specimens, suggesting an underlying local accumulation of hydrogen peroxide. Glucose flux from ?-cell clusters, measured in the presence of 5 mM glucose, was 61.7 ± 9.5 fmol·nL-1·s-1 (mean ± SEM, n = 9) and could be pharmacologically modulated. Glucose consumption in response to FCCP (1 ?M) transiently increased, subsequently decreasing to below basal by 93 ± 16 and 56 ± 6%, respectively (mean ± SEM, n = 5). Consumption was decreased after the application of 10 ?M rotenone by 74 ± 5% (mean ± SEM, n = 4). These results demonstrate that an enzyme-based amperometric microsensor can be applied in the self-referencing mode. Further, in obtaining glucose flux measurements from small clusters of cells, these are the first recordings of the real-time dynamic of glucose movements in a biological microenvironment. <br/

The KaVA and KVN Pulsar Project

We present our work towards using the Korean VLBI (Very Long Baseline Interferometer) Network (KVN) and VLBI Exploration of Radio Astronomy (VERA) arrays combined into the KVN and VERA Array (KaVA) for observations of radio pulsars at high frequencies ($\simeq$22-GHz). Pulsar astronomy is generally focused at frequencies approximately 0.3 to several GHz and pulsars are usually discovered and monitored with large, single-dish, radio telescopes. For most pulsars, reduced radio flux is expected at high frequencies due to their steep spectrum, but there are exceptions where high frequency observations can be useful. Moreover, some pulsars are observable at high frequencies only, such as those close to the Galactic Center. The discoveries of a radio-bright magnetar and a few dozen extended Chandra sources within 15 arc-minute of the Galactic Center provide strong motivations to make use of the KaVA frequency band for searching pulsars in this region. Here, we describe the science targets and report progresses made from the KVN test observations for known pulsars. We then discuss why KaVA pulsar observations are compelling.Comment: To appear in PASJ KaVA Special Issu

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

We study contextual linear bandit problems under uncertainty on features; they are noisy with missing entries. To address the challenges from the noise, we analyze Bayesian oracles given observed noisy features. Our Bayesian analysis finds that the optimal hypothesis can be far from the underlying realizability function, depending on noise characteristics, which is highly non-intuitive and does not occur for classical noiseless setups. This implies that classical approaches cannot guarantee a non-trivial regret bound. We thus propose an algorithm aiming at the Bayesian oracle from observed information under this model, achieving $\tilde{O}(d\sqrt{T})$ regret bound with respect to feature dimension $d$ and time horizon $T$. We demonstrate the proposed algorithm using synthetic and real-world datasets.Comment: 30 page