Neuromodulatory inputs from the basal forebrain (BF) and locus ceruleus (LC) are widespread in the mammalian cerebral cortex and are known to play important roles in attention and arousal, but little is known about the selectivity of their cortical projections. Using a dual retrobead tracing technique along with optogenetic stimulation, we have identified anatomic and functional differences in the way cholinergic BF neurons and noradrenergic LC neurons project into primary sensory cortices. While BF projections are highly selective to individual sensory cortices, LC projections diverge into multiple sensory cortices. To our knowledge, this is the first definitive proof that BF and LC projections to primary sensory cortices show both anatomic and functional differences in selectivity for modulating cortical activity.

When conflicts occur during integration of visual and auditory information, one modality often dominates the other, but the underlying neural circuit mechanism remains unclear. Using auditory-visual discrimination tasks for head-fixed mice, we found that audition dominates vision in a process mediated by interaction between inputs from the primary visual (VC) and auditory (AC) cortices in the posterior parietal cortex (PTLp). Co-activation of the VC and AC suppresses VC-induced PTLp responses, leaving AC-induced responses. Furthermore, parvalbumin-positive (PV+) interneurons in the PTLp mainly receive AC inputs, and muscimol inactivation of the PTLp or optogenetic inhibition of its PV+ neurons abolishes auditory dominance in the resolution of cross-modal sensory conflicts without affecting either sensory perception. Conversely, optogenetic activation of PV+ neurons in the PTLp enhances the auditory dominance. Thus, our results demonstrate that AC input-specific feedforward inhibition of VC inputs in the PTLp is responsible for the auditory dominance during cross-modal integration.

This article develops a new quantile approach utilizing partial moments to evaluate risk exposure and illustrate risk valuation, and then applies it to examine the potential importance of 'fat tails', downside risk, and risk mitigation options associated with a highly controlled but stochastic production system − irrigated rice production in Korea. The econometric approach exploits a rich panel dataset to develop consistent and robust econometric estimates of the partial moments needed to implement the quantile-based decomposition of risk outcomes.Our results demonstrate that the costs of downside risk associated with Korean rice production system are quite large, providing an empirical validation of Weitzman's dismal theory.

The paper investigates the linkages between technological change and production risk, with an application to corn. The effects of technology on risk exposure are analyzed. We define technological progress to be risk-increasing (risk-decreasing) if it increases (decreases) the relative risk premium. The analysis is applied to panel data from Wisconsin research stations. Conditional moments (including mean, variance and skewness) of corn yield, grain moisture and corn profit are estimated for different sites. We investigate how the trade-off between expected return and the risk premium varies over time and over space. The empirical results indicate that technological progress contributes to reducing the exposure to risk as well as downside risk in corn production, although this effect varies across sites. They also stress the role of the relative maturity of corn hybrids as a means of managing risk.

Identifying the health benefits of phytochemicals is an essential step in drug and functional food development. While many in vitro screening methods have been developed to identify the health effects of phytochemicals, there is still room for improvement because of high cost and low productivity. Therefore, researchers have alternatively proposed in silico methods, primarily based on three types of approaches; utilizing molecular, chemical or ethnopharmacological information. Although each approach has its own strength in analyzing the characteristics of phytochemicals, previous studies have not considered them all together. Here, we apply an integrated in silico analysis to identify the potential health benefits of phytochemicals based on molecular analysis and chemical properties as well as ethnopharmacological evidence. From the molecular analysis, we found an average of 415.6 health effects for 591 phytochemicals. We further investigated ethnopharmacological evidence of phytochemicals and found that on average 129.1 (31%) of the predicted health effects had ethnopharmacological evidence. Lastly, we investigated chemical properties to confirm whether they are orally bio-available, drug available or effective on certain tissues. The evaluation results indicate that the health effects can be predicted more accurately by cooperatively considering the molecular analysis, chemical properties and ethnopharmacological evidence.

This article examines the factors that account for agricultural biotechnology patenting success among universities using a dynamic count data model. It builds a theoretical and econometric model to capture the inherently dynamic and nonlinear process of technological innovation, wherein a feedback mechanism from previous success partially determines current patent counts. The econometric estimates reveal the importance to agricultural biotechnology patent production of land grant infrastructure, quality faculty, patent-oriented technology transfer offices, as well as dynamic feedback effects.

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm-level panel data, the analysis studies farm productivity in a multi-input multi-output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize. JEL classifications: D22, D24, Q12

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