RELATIVE EFFECTIVENESS OF USDA'S NONPRICE EXPORT PROMOTION INSTRUMENTS

The USDA'Â’s Foreign Agricultural Service funds three types of activities to promote agricultural exports: consumer promotion, technical assistance, and trade servicing. These "instruments" are analyzed using an adaptation of Muth's model. Results indicate that consumer promotion always increases the derived demand for the U.S. agricultural commodity, but that under certain conditions technical assistance and trade servicing can have a perverse effect. Applying the model to cotton promotion in Japan, the results suggest that, owing to cotton's modest share of retail value, the current emphasis on consumer promotion may be misplaced. Specifically, it appears that producer returns can be enhanced by emphasizing technical assistance projects that save on the marketing input.Agricultural and Food Policy, International Relations/Trade,

COOPERATIVE ADVERTISING RENT DISSIPATION

Generic advertising is used by fish producers to accelerate demand growth to alleviate temporary surpluses. Whether this cooperative promotional venture is profitable depends on a number of factors including industry supply response. A rent-dissipation model applied to the U.S. catfish industry suggests the quasi-rents generated by increased advertising are more than sufficient to cover incremental costs over any reasonable time horizon.Marketing,

ADVERTISING, STRUCTURAL CHANGE, AND U.S. NON-ALCOHOLIC BEVERAGE DEMAND

The dominant trend in U.S. non-alcoholic consumption over the past two decades has been a steady increase in soft-drink consumption, largely at the expense of milk and coffee and tea consumption. Our analysis suggests that the primary factors affecting this is that the price, advertising, and demographic elasticities estimated from the Rotterdam model are much smaller than the adjusted trend coefficients and the expenditure elasticities.Consumer/Household Economics, Demand and Price Analysis, Marketing,

MODELING ADVERTISING CARRYOVER IN FLUID MILK: COMPARISON OF ALTERNATIVE LAG SPECIFICATIONS

The performance of restricted estimators such as Almon and Shiller in modeling advertising carryover is tested and compared to the unrestricted OLS estimator, using 1971-1988 monthly New York City fluid milk market data. Results indicate that in the absence of autocorrelation and multicollinearity among the lagged advertising variables, the unrestricted OLS estimator is still the preferred estimator, based on Mean Square Error and Root Mean Square Percent Error criteria. In this case, the Almon and Shiller estimators perform equally well, although next only to the OLS estimator. In the presence of autocorrelation or multicollinearity however, the restricted estimators may outperform the OLS estimator, in a MSE sense, with the flexible Shiller estimator (which subsumes the Almon) being more desirable.Marketing,

Plant-Made Oral Vaccines Against Human Infectious Diseases—Are we There yet?

Although the plant-made vaccine field started three decades ago with the promise of developing low-cost vaccines to prevent infectious disease outbreaks and epidemics around the globe, this goal has not yet been achieved. Plants offer several major advantages in vaccine generation, including low-cost production by eliminating expensive fermentation and purification systems, sterile delivery and cold storage/transportation. Most importantly, oral vaccination using plant-made antigens confers both mucosal (IgA) and systemic (IgG) immunity. Studies in the past 5 years have made significant progress in expressing vaccine antigens in edible leaves (especially lettuce), processing leaves or seeds through lyophilization and achieving antigen stability and efficacy after prolonged storage at ambient temperatures. Bioencapsulation of antigens in plant cells protects them from the digestive system; the fusion of antigens to transmucosal carriers enhances efficiency of their delivery to the immune system and facilitates successful development of plant vaccines as oral boosters. However, the lack of oral priming approaches diminishes these advantages because purified antigens, cold storage/transportation and limited shelf life are still major challenges for priming with adjuvants and for antigen delivery by injection. Yet another challenge is the risk of inducing tolerance without priming the host immune system. Therefore, mechanistic aspects of these two opposing processes (antibody production or suppression) are discussed in this review. In addition, we summarize recent progress made in oral delivery of vaccine antigens expressed in plant cells via the chloroplast or nuclear genomes and potential challenges in achieving immunity against infectious diseases using cold-chain-free vaccine delivery approaches

Adaptive particle swarm optimization

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic control of inertia weight, acceleration coefficients, and other algorithmic parameters at run time to improve the search efficiency and convergence speed. Then, an elitist learning strategy is performed when the evolutionary state is classified as convergence state. The strategy will act on the globally best particle to jump out of the likely local optima. The APSO has comprehensively been evaluated on 12 unimodal and multimodal benchmark functions. The effects of parameter adaptation and elitist learning will be studied. Results show that APSO substantially enhances the performance of the PSO paradigm in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability. As APSO introduces two new parameters to the PSO paradigm only, it does not introduce an additional design or implementation complexity

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Ability of γδ T cells to modulate the Foxp3 T cell response is dependent on adenosine.

Whether γδ T cells inhibit or enhance the Foxp3 T cell response depends upon their activation status. The critical enhancing effector in the supernatant is adenosine. Activated γδ T cells express adenosine receptors at high levels, which enables them to deprive Foxp3+ T cells of adenosine, and to inhibit their expansion. Meanwhile, cell-free supernatants of γδ T cell cultures enhance Foxp3 T cell expansion. Thus, inhibition and enhancement by γδ T cells of Foxp3 T cell response are a reflection of the balance between adenosine production and absorption by γδ T cells. Non-activated γδ T cells produce adenosine but bind little, and thus enhance the Foxp3 T cell response. Activated γδ T cells express high density of adenosine receptors and have a greatly increased ability to bind adenosine. Extracellular adenosine metabolism and expression of adenosine receptor A2ARs by γδ T cells played a major role in the outcome of γδ and Foxp3 T cell interactions. A better understanding of the functional conversion of γδ T cells could lead to γδ T cell-targeted immunotherapies for related diseases

Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO