The value of USDA reports in commodity futures markets has been intensively researched, but statistical hypothesis tests have been limited by the sheer number of reports and the consequent need to limit parameters to be estimated. This has led most tests of USDA report announcement effects to be based on single coefficients for each report series. We relax the implicit assumption that a report series has a constant impact on futures price volatility or returns in two ways in order to introduce more flexible tests for announcement effects. First, we introduce a time trend into the impact of announcements on futures price volatility to determine if USDA reports are becoming more or less influential over time. Then we allow each report to have a different impact on futures price returns using Theil‐Goldberger mixed estimation. The results show that many, but not all, USDA reports have significant effects on corn and soybean futures market returns or volatility.

Background: Major depressive disorders often involve somatic symptoms and have been found to have fundamental differences from non-somatic depression (NSD). However, the neural basis of this type of somatic depression (SD) is unclear. The aim of this study is to use the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) analyses to examine the abnormal, regional, spontaneous, neuronal activity and the corresponding brain circuits in SD patients. Methods: 35 SD patients, 25 NSD patients, and 27 matched healthy controls were selected to complete this study. The ALFF and seed-based FC analyses were employed, and the Pearson correlation was determined to observe possible clinical relevance. Results: Compared with NSD, the SD group showed a significant ALFF increase in the right inferior temporal gyrus; a significant ALFF decrease in left hippocampus, right inferior frontal orbital gyrus and left thalamus; and a significant decrease in the FC value between the right inferior frontal orbital gyrus and the left inferior parietal cortex ( p < 0.05, corrected). Within the SD group, the mean ALFF value of the right inferior frontal orbital gyrus was associated with the anxiety factor scores (r = –0.431, p = 0.010, corrected). Conclusions: Our findings suggest that abnormal differences in the regional spontaneous neuronal activity of the right inferior frontal orbital gyrus were associated with dysfunction patterns of the corresponding brain circuits during rest in SD patients, including the limbic-cortical systems and the default mode network. This may be an important aspect of the underlying mechanisms for pathogenesis of SD at the neural level.

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Social interactions are composed of coordinated, multimodal behaviors with each individual taking turns and sharing attention. By the second year of life, infants are able to engage in coordinated interactions with their caregivers. Although research has focused on the social behaviors that enable parent-infant dyads to engage in joint attention, little work has been done to understand the sensorimotor mechanisms underlying coordination. Using wireless head-mounted eye trackers and motion sensing, we recorded 31 dyads as they played freely in a home-like laboratory. We identified moments of visual joint attention, when parent and infant were looking at the same object, and then measured the dyad’s head and hand movements during and around joint attention. We found evidence that both parents and infants still their bodies during joint attention. We also compared instances of joint attention that were led by the parent or by the infant and identified different sensorimotor pathways that support the two types of joint attention. These results provide the foundation for continued exploration of the critical role of sensorimotor processes on coordinated social behavior and its development.

The agent-based multi-market model we propose simulates futures and spot markets. On the basis of trading strategies in real markets, four kinds of agents - arbitragers, hedgers, speculators, and noise traders - are included in our model. Interactions of the two markets are generated through various agent trading behavior. We also statistically analyzed futures and spot prices of the Nikkei 225 index, where we found a large positive correlation between the two prices and a fat-tail distribution of the basis. Simulations results show that, instead of the conventional single-market model, only the two-market model reproduces both statistical properties of futures prices.

We study a principal‐agent model wherein the agent is better informed of the prospects of the project, and the project requires both an observable and unobservable input. We characterize the optimal contracts, and explore the trade‐offs between high‐ and low‐powered incentive schemes. We discuss the implications for push and pull programs used to encourage Research and Development (R&D) activity, but our results are relevant in other contexts.

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