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Contribution: This article shares the learning ecosystem of a project-based embedded systems course, identifying course elements that support self-directed learning and how assignments guide students toward becoming adaptive experts. Background: The technology advances while the fundamentals of electrical engineering remain static. Educators can increasingly prepare students to identify what they need to know to solve problems and avail themselves of resources to learn. This article seeks to further understand ways that a project-based learning approach in an undergraduate embedded systems course can facilitate students’ self-directed learning. Research Question: In what ways can a project-based learning approach in an undergraduate embedded systems course facilitates the self-directed learning amongst students? Methodology: This article, conducted in the context of an existing embedded systems design (ESD) course, relied on interviews of students, teaching assistants, and faculty along with document analysis and a mixed inductive–deductive thematic analysis. Findings: A learning ecology of the course is presented. This includes descriptions of space and facilities that influence student motivation, means by which the pedagogical intent of the instructor impacts the student experience, how the course builds on project-based learning knowledge, how the content is distributed using knowledge sharing, how Making supported the ecosystem, how students and instructor occupy similar roles, how the curricular design process was conducted, and how the open ecology promotes student self-direction.

The global goal to reduce dependence on fossil fuels and to mitigate greenhouse gas emissions has resulted in research focused on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bio-energy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment. Applicability of the stochastic model is illustrated through a case study of switchgrass-based biofuel in west Tennessee.

Pennycress can be used as a renewable biomass because its harvested seeds can be converted into biofuel, supplying, for example the aviation industry. Pennycress can be adopted as a winter cover crop to make extra profit in addition to summer cash crops. This study ascertains influences on row crop farmers’ interest in growing pennycress to supply a biofuels industry. The study uses data from a survey of row-crop farmers in seven US states. Effects of farm and farmer attributes on acceptance of a farmgate pennycress price are measured. Nearly 58% were interested in growing pennycress if profitable. Among those interested, 54.4% would accept the farmgate pennycress price offered. Positive influences on interest included farm size, education, and familiarity with pennycress, while concern about knowledge on growing pennycress, and use of no-till practices had negative influences. Farmers aged 40 to 65 were more likely to accept the price, while share of rented hectares and no debt had positive influences. More risk-averse farmers and those using no-till were less likely to accept. Results suggest that the majority of row crop farmers would be interested in growing pennycress if profitable, while the overall willingness to accept the farmgate price was when it was at $0.28/kg.

This research combines Geographic Information Systems (GIS) and Mixed Integer Programming (MIP) model to determine feedstock supply, preprocessing facility, and biorefinery locations at a highly resolved spatial scale with the objective of meeting a large-scale annual biofuel production and demand goal for Tennessee, USA. Simultaneous determination of this supply chain network using MIP is computationally expensive. Memory limitation of typical personal computers constrain the network problem. High Performance Computing environments may require days to solve, and without any assurance of a feasible solution. This paper proposes a two-stage optimization procedure to overcome these computational challenges while maintaining theoretical consistency with conventional firm location theory paradigms. The two-stage procedure assumes that firms first identify biorefinery locations with comparative advantage in terms of supplying biomass. Step two entails determining if costs can be lowered with the addition of preprocessing facilities, and their optimal location relative to the biorefinery sites. In contrast, a single step optimization procedure siting multiple biorefineries and concomitantly preprocessing units and biomass supply areas assumes a different strategy for a single firm. Results suggest that the two-stage optimization approach is able to identify a feasible solution of multiple feedstock areas, feedstock preprocessing and fuel production locations using high-resolution spatial layers over a relatively large geographic region in a fraction of the computer resources required to solve a single, simultaneous location problem. The optimal supply chain network solutions generated from the two-stage and single simultaneous approaches are different. The absolute difference in the smaller scaled models’ objective values is less than 1%.

South Korea is currently the world leader in digital network infrastructure and the leading example of ICT-driven development. However, the explanation of how and why Korea accomplished these things is not clearly apparent from a review of mainstream scholarship. A deeper understanding of Korea’s “miracle on the Han” requires more historical, cultural, political and social context. This study addresses questions of how, when and why a nation whose infrastructures were utterly destroyed at the 1953 cessation of hostilities in the Korean War could emerge as the world’s digital network leader. It examines policy issues bearing on digitization of networks, network architecture and network technologies, along with broader context in which these policies were considered, drafted and implemented. Chronologically, the study explains the origins of digital development in the revolutionary decade of the 1980s, Korea’s rise to world broadband leader in the 1990s and its ambitious plans for next generation networks. The study concludes with a review of policy “lessons”, including both successes and failures, that may be drawn from the Korean experience.

Investment risk and uncertainty about the availability of biomass feedstock hinders the development of a mature cellulosic biofuel sector. The Biomass Crop Assistance Program (BCAP) is a federal program designed to subsidize farmers to establish, produce and deliver biomass feedstock to biorefineries. This study evaluated the impacts of BCAP on the optimal biofuel supply chain decisions considering feedstock yield uncertainty and associated investment risk given diverse risk preferences of the biofuel sector. The expected cost for a risk-neutral biofuel sector was minimized using a two-stage stochastic mixed integer linear program, whereas the Conditional Value-at-Risk of the supply chain was optimized for a risk-averse sector. Ex-ante analysis of a switchgrass-based biofuel sector in west Tennessee indicates BCAP payments could lower expected cost and investment risk for both risk-averse and risk-neutral biofuel sectors. However, the cost saving and risk reduction resulting from BCAP incentives for the risk-averse biofuel sector were higher than the risk-neutral biofuel sector. In addition, BCAP payments may drive more cropland to be converted for switchgrass, which potentially mitigates water-induced soil erosion and reduces greenhouse gas emissions associated with net carbon sequestration, but may also create unintended consequence of competition for land between food and fuel use.

This study considered the environmental advantages of switchgrass, along with the economic challenges in its logistics, in the design of a sustainable switchgrass supply chain in Tennessee. Applying a multi-objective optimization model to high-resolution spatial data, potential tradeoffs among the objectives of minimizing feedstock costs, GHG (greenhouse gas) emissions, and soil erosion were identified for a set of conversion facilities on an efficient frontier. The tradeoff relationship was primarily driven by the type of agricultural land converted to switchgrass. Hay and pasture lands were more cost effective but resulted in higher soil carbon losses and soil erosion after being converted to switchgrass. Converting crop lands reduced GHG emissions and soil erosion but caused higher feedstock cost primarily due to the higher opportunity cost of land use. The respective average costs of abating GHG emissions and soil erosion on the efficient frontier were $2378 Mg−1 and $10 Mg−1. The compromise solution conversion facility site generated 63% higher feedstock cost compared to the cost minimizing location, while reducing soil erosion by 70 fold and diminishing GHG emissions by 27%. Reducing soil erosion may be a more cost effective environmental criterion than reducing GHG emissions in developing a sustainable switchgrass supply chain in Tennessee.

Growing biomass crops for energy production on low productivity lands not used for food production has been suggested as an alternative to reduce dependence on fossil fuels and to mitigate greenhouse gas emissions from transportation fuel. Switchgrass is considered a potential feedstock in various states, including Tennessee, given its high biomass content in a wide range of environments. However, its low density relative to energy value and resulting high logistics costs impede the profitability of switchgrass-based bioenergy. The objective of this study is to determine the optimal logistics configuration for a collection/distribution hub to market Tennessee-produced switchgrass for bioenergy production. A mathematical programming model integrated with a geographic information system is used to maximize the net present value of profit from a hub that serves switchgrass producers and bioenergy markets. Six logistics configurations delivering switchgrass to local or international bioenergy markets are evaluated. The results highlight the economic challenges of penetrating energy markets for a switchgrass collection/distribution hub – only one logistics configuration that targets the local market is profitable. However, serving local and international markets becomes more feasible as investment risk declines. The results imply that a clear direction for national bioenergy policy is crucial to developing a biomass feedstock for the U.S. bioenergy industry.

Information sharing is essential for learning and performance in groups and organizations. This chapter examines factors that either encourage or discourage information sharing, particularly during group meetings convened for the purpose of solving a problem or making a decision. Such purposes are usually best served when members share with one another the task-relevant information they hold that others in the group do not possess (i.e., uniquely held information). Yet meetings are often dominated by discussion of information that most members already know (i.e., commonly held information), to the relative exclusion of their uniquely held information. We examine in some detail the information sampling process that gives rise to this phenomenon, and we consider a range of situational and motivational factors that moderate it, including features of the information held, the task performed, and the group performing it. Finally, we offer recommendations for how information sharing during group meetings might be improved.

The objective of this paper is to design two types of subsidies for biofuel feedstock production and water quality improvement and to analyze how each subsidy affects biomass supply and the abatement of nutrient runoff associated with the conversion of cropland to biomass production. Per-hectare (per-ha) subsidy was designed as a system that pays producers for each ha of cropland converted to switchgrass production and per-megagram (per-Mg) subsidy was a system that pays producers for each Mg of switchgrass produced. This study focuses on Oostanaula Creek watershed in East Tennessee. The analysis used a dynamic programming model coupled with a Soil and Water Assessment Tool (SWAT) simulation model to predict profit-maximizing fertilizer application rates, crop yields, and nitrogen (N) runoff for a biofuel feedstock (switchgrass) and a conventional crop (corn) across 28 different landscapes in the watershed. A Monte Carlo analysis was conducted to simulate the impact of stochastic N fertilizer and corn prices and yields on subsidies over a ten-year planning horizon. A per-ha subsidy system is more cost effective and feasible than a per-Mg system because the former has significantly lower subsidy than the latter for each kilogram (kg) of N reduction and for each Mg of switchgrass harvested. Converting all of the cropland from corn to switchgrass over ten years results in 124,084 dry Mg of switchgrass and 23% reduction in nitrogen runoff for the per-ha system and 122,347 dry Mg of switchgrass and 3% reduction for the per-Mg subsidy system.

Understanding how field geometry is related to over-application of inputs may help farmers make more informed decisions about investment in automatic section control (ASC) technology. The technology helps reduce input application overlap and therefore reduces input costs. The influence of field geometry on the profitability of ASC technology for chemical application was evaluated using overlap data estimated for 44 farm fields in Tennessee, USA. Reduction in overlap with ASC was defined as the difference in area sprayed controlling the entire boom as one section and area sprayed using seven-section ASC. Perimeter (m)-to-area (m2) ratio (P/A, m−1) was used to categorize estimated chemical overlap by field size and shape. Estimated median reductions in overlap with ASC were 3.00 % for fields with P/A = 0.01, 9.65 % for fields with P/A = 0.02 and 13.50 % for fields with P/A ≥ 0.03. For a typical size cotton farm in Tennessee, investing in ASC was not likely to be profitable for fields with P/A = 0.01 but was generally profitable for fields with P/A ≥ 0.02. The low reduction in overlap for P/A = 0.01 with ASC resulted in chemical savings that were too small to pay back the investment in ASC within the useful life assumed for the technology and provide a minimum rate of return. Thus, P/A as a measure of field geometry may be useful for evaluating investments in ASC technologies.

Little is known about the potential impacts of storage losses on the optimal design of a switchgrass ( Panicum virgatum ) supply chain for an ethanol conversion facility. This study analyzed how storage losses impact plant-gate cost and feedstock inventory management for a 94,635 kL year −1 switchgrass-based ethanol conversion facility in East Tennessee. A spatially-oriented, mixed-integer mathematical programming model was used to analyze plant-gate cost and harvest, storage, and delivery schedule for switchgrass packaged in large round or rectangular bales. Results indicate that last in, first out inventory management of feedstock minimized plant-gate cost. The key factor influencing inventory management was dry matter loss increasing at a decreasing rate with time in storage and distance of switchgrass production from the conversion facility. Our findings imply that the conversion facility can optimize the feedstock inventory and delivery management through coordinating the timing and location of switchgrass harvest with storage and delivery.

In the process of brewing and packaging beer, many secondary streams are produced that are not part of the beer product stream, and they cannot be used in the final product. Around the world, large breweries and small craft breweries alike have adopted sustainability programs. This chapter examines the different areas of brewery operations and how they affect the profits, people, and the planet in terms of effluents, emissions, and energy usage. Emissions and effluents are described along with various treatment options. Progress in reducing energy usage and beer losses throughout the process is also reviewed. Receiving and conveying grains and other raw materials into the brewery can be a source of dust emissions into the atmosphere. The brewhouse generates liquid waste streams produced during lautering or mash filtration, from processes that separate hops and trub in hot wort after boiling, and cleaning-in-place (CIP) rinses and cleaning solution discharges.

Supplemental irrigation in corn production is increasing for humid regions across the world. Little is known about the profitability of irrigating corn in the humid southeastern region of the United States. Our objective was to determine the breakeven price of corn where investment in center-pivot irrigation would be profitable in Tennessee. We considered the effects of field size, energy price, and energy source on the breakeven price of corn. We estimated yield response to nitrogen (N) for irrigated and non-irrigated corn, and allowed expected yield and economically optimal N fertilization to vary with the breakeven price. Field size and the cost of running electricity to the center-pivot were two important factors in choosing between diesel and electricity as the energy source. The breakeven price of corn ranged between $249–$283 Mg −1 for the small-sized field, $168–$190 Mg −1 for the medium-sized field, and $149–$171 Mg −1 for the large-sized field. As field size increased, electricity became more economically viable relative to diesel. At current corn prices, irrigating corn appears profitable on fields greater than 51 ha. However, historically, the probability for the breakeven corn price occurring is zero for the small-sized field, between 6–14% for the medium-sized field, and 12–27% for the large-sized field.

The timing of technology adoption is influenced by profitability and farmer ability to bear risk. Innovators are typically more risk tolerant than laggards. Understanding the factors influencing early adoption of precision agriculture (PA) technologies by cotton farmers is important for anticipating technology diffusion over time. The factors influencing the timing of grid soil sampling (GSS), yield monitoring (YMR) and remote sensing (RMS) adoption by cotton producers was evaluated using multivariate censored regression. Data for cotton farmers in 12 states were obtained from a survey conducted in 2009. The factors hypothesized to influence the timing of adoption included farm characteristics, operator characteristics, PA information sources, adoption of other PA technologies, and farm location. The results suggest that different factors influenced when cotton farmers adopted GSS, YMR and RMS after these technologies became commercially available. For example, land ownership was associated with the timing of GSS adoption, but not YMR or RMS adoption; farmer age was correlated with the timing of GSS and YMR adoption, but not RMS adoption; and obtaining PA information from consultants affected the timing of GSS and RMS adoption, but not YMR adoption. The only factors correlated with the early adoption of all three technologies were beliefs that PA would improve environmental quality and the adoption of at least one other PA technology. Thus, the potential for improved environmental quality appears to be a strong adoption motivator across PA technologies, as is the earlier adoption of other PA technologies. This research may be useful for farmers, researchers, Extension personnel, machinery manufacturers, PA information providers and agricultural retailers to anticipate the future adoption of new and emerging PA technologies.

At the interface of the Great Lakes and their tributary rivers lies the rivermouths, a class of aquatic ecosystem where lake and lotic processes mix and distinct features emerge. Many rivermouths are the focal point of both human interaction with the Great Lakes and human impacts to the lakes; many cities, ports, and beaches are located in rivermouth ecosystems, and these human pressures often degrade key ecological functions that rivermouths provide. Despite their ecological uniqueness and apparent economic importance, there has been relatively little research on these ecosystems as a class relative to studies on upstream rivers or the open-lake waters. Here we present a synthesis of current knowledge about ecosystem structure and function in Great Lakes rivermouths based on studies in both Laurentian rivermouths, coastal wetlands, and marine estuarine systems. A conceptual model is presented that establishes a common semantic framework for discussing the characteristic spatial features of rivermouths. This model then is used to conceptually link ecosystem structure and function to ecological services provided by rivermouths. This synthesis helps identify the critical gaps in understanding rivermouth ecology. Specifically, additional information is needed on how rivermouths collectively influence the Great Lakes ecosystem, how human alterations influence rivermouth functions, and how ecosystem services provided by rivermouths can be managed to benefit the surrounding socioeconomic networks.

Reducing double-planted area in row crop production fields where planter overlap is unavoidable, such as end rows, point rows, and areas around internal field obstacles, can improve net returns by reducing seed costs and increasing revenue. The objective of this case study was to present a summary of results from 52 fields that highlight potential losses from double-planted areas and therefore potential savings associated with an investment in an Automatic Section Control system (ASC) for planters. Percentage of double-planted area ranged from 0.1% to 15.5% depending on field size and shape. Fields were classified into low, moderate and high double-planted fields, based on percentage of double planted area. Potential savings from adopting ASC system for planters were evaluated using this information. Savings from the adoption of this technology ranged from $4 per ha to $26 per ha depending on the distribution of field types in a farming operation. The results indicated that savings and the minimum period of time over which an investment in ASC on planters would have to be finance to guarantee a positive net cash flow every year was determined by farm size and distribution of field types in a farming operation.

The Energy Independence and Security Act of 2007 mandates that by 2022 at least 1.36 × 10 11 L of fuel ethanol be produced in the United States, with at least 6.06 × 10 10 L being derived from lignocellulosic biomass. However, the market for cellulosic biofuels is still developing and little is known about the willingness of agricultural producers to grow dedicated energy crops. While there have been some studies done on factors that determine farmers' willingness to produce switchgrass, these have been localized in nature and largely focused on factors other than price. This study analyzes the factors that influence interest among producers in the 12 southeastern U.S. states in growing switchgrass as a biomass feedstock and the share of farmland interested producers would be willing to devote to switchgrass production. The results suggest that about two-thirds of the producers in the region have some interest in growing switchgrass. Among those who are interested and willing to accept the hypothetical price, the predicted land conversion share is 35.8% or 56 ha per farm. At these rates, a commercial scale bio-refinery in the southeast might have to purchase switchgrass from as many as 567 different producers.

Phlegmonous gastritis is a rare and often fatal condition that can affect healthy individuals in 50% of cases. The condition has been described in accounts dating back to the pre-antibiotic era, during which time mortality was nearly 100%. Over the past century, case reports average about one per year. The etiology remains unclear, although Streptococcus species is isolated frequently. The optimum treatment has not been delineated clearly but likely involves a combination of antibiotics with or without surgical resection.A case report was presented and the pertinent literature was reviewed.A 45-year-old man with a history of recent paranasal sinus surgery presented with acute abdominal pain and criteria consistent with toxic shock syndrome. Computed tomography scan showed diffuse thickening of the gastric wall and free intraperitoneal fluid. Exploratory laparotomy revealed a thickened stomach wall with outer fibrinous exudate and murky peritoneal fluid, which grew Streptococcus pyogenes. Intraoperative esophagogastroduodenoscopy revealed thickened gastric folds with a "cobblestone" appearance and no evidence of perforation. He was treated with antibiotics intravenously and sustained a difficult intensive care unit course complicated by ventilator-dependent respiratory failure, renal failure, and coagulopathy, but survived without major disability.This is an unusual case presentation of a rare but potentially lethal condition, whose optimal treatment is unclear. Phlegmonous gastritis should be considered when isolated gastric wall thickening is encountered in the clinical setting of toxic shock syndrome.

Precision agriculture technologies are increasingly important in cotton production because input prices continue to rise. Farmers increase input efficiency using precision agriculture technologies by adjusting inputs to match soil fertility and plant nutrition requirements. This research examines the factors affecting changes in fertilizer use following variable-rate fertilizer application in cotton production. Data from a 2009 survey of cotton producers in 12 states of the United States were used in the analysis. Farmers who used precision soil sampling, planted larger cotton area, relied on other farmers for information about PA, grew picker cotton, and had higher household income were more likely to decrease fertilizer application with VRT. Results from this analysis are useful to farmers and policy makers interested in reducing fertilizer use in the face of rising fertilizer prices and growing concerns about the environmental impacts of farming.

PurposeThe US Department of Energy has a goal to make ethanol from biomass cost competitive with petroleum by 2012. Feedstock procurement is expected to represent a significant portion of the operating costs for a refinery that produces ethanol from biomass such as switchgrass. Thus, cost‐effective feedstock logistics will be a key factor for the future development of a capital intensive cellulosic ethanol industry. The purpose of this paper is to analyze the cost of various logistic methods of switchgrass production, harvesting, storing, and transportation.Design/methodology/approachThis study applied enterprise budgeting and geographical information system (GIS) software to analyze the costs of three logistic methods of acquiring switchgrass feedstock for a 25 million gallon per year refinery. Procurement methods included traditional large round and rectangular bale harvest and storage systems and satellite preprocessing facilities using field‐chopped material. The analysis evaluated tradeoffs in operating costs, dry matter losses during storage, and investment requirements among the three systems.FindingsResults suggest that the preprocessing system outperformed the conventional bale harvest methods in the delivered costs of switchgrass.Practical implicationsThe cost savings in harvest, transportation, and dry matter losses for the preprocessing system offset their extensive capital costs and generated cost advantages over the conventional methods.Social implicationsThe traditional round bale system has a higher overall investment cost, may not be the most cost‐effective way to procure switchgrass feedstock for a refinery, and may limit farmer participation in the feedstock value chain.Originality/valueGIS methods combined with enterprise budgeting can be useful tools for evaluating investment in feedstock supply chain infrastructure.

Using data from a survey of cotton producers in 14 US states, and a bivariate probit regression, this study examined the effects of the following measured parameters on the adoption of Automatic Section Control (ASC) technologies and GPS Auto-Guidance (AG) systems: age, education, farm size, field geometry, information sources, as well as the use of specific production practices and other Precision Agriculture (PA) technologies. Results suggest that younger, more educated producers, consulting farm dealers for information about PA technologies, using other PA technologies, and managing larger farming operations located in counties with more irregularly shaped fields are more likely to adopt ASC technologies and AG systems. Predicted adoption probabilities estimated using regression results suggest the use of other PA technologies and farm dealers as a source of precision farming information have the largest impact on the probability of adopting ASC by cotton farmers. Additionally, these results suggest farmers with operations in eastern Arkansas, western Tennessee, and a couple of counties in middle Tennessee are more likely to adopt ASC technologies. Producers in these regions had the highest percentages of users of other PA technologies and farm dealers to obtain PA information.

Technology adoption in precision agriculture has received considerable attention, while abandonment has received little. Survey data are now available to evaluate adoption and abandonment decisions. Understanding the factors motivating technology adoption and abandonment has implications for educational efforts directed toward improving the efficiency of production inputs and for research and development to improve the value of precision agriculture technologies. The objective of this research was to identify factors motivating the adoption and abandonment of grid soil sampling in precision cotton production. These decisions were evaluated assuming a random utility model. Data were obtained from a 2005 survey of cotton producers in 11 Southeastern states in the USA. Results from limited dependent variable regressions indicate that younger producers who farmed more cotton area, owned more of their cropland, planted larger amounts of non-cotton area, used a computer for farm management and used a Personal Digital Assistant (PDA) in the field were more likely to adopt grid soil sampling for cotton precision farming. Results also suggest that producers with more cotton area who owned livestock and adopted management zone soil sampling were more likely to abandon grid soil sampling, while those who used a PDA in the field, used grid soil sampling for more years and followed up grid soil sampling with variable-rate fertilizer application were less likely to abandon grid soil sampling for cotton production.

Comparing Internet diffusion policies in the United States and France from an implementation perspective brings to light institutional and historical differences, even though both countries used the same top-down approach. We find that France not only followed the technological lead of the United States in information technology but also emulated some of its more business-oriented approaches in the implementation of the Internet, despite its own longstanding tradition of government intervention in industrial and commercial matters. This policy shift appears to be spurred by the global economy. Traditionally state-controlled national economies are now increasingly leveraging private interests for successful industrial policy. When applying Sabatier and Jenkins-Smith's advocacy coalition framework to the American and French diffusion of the Internet, we find policy communities actually expanding to private and public actors, including industry captains, legislators, and civil servants. These subsystems work together through classic lawmaking and lobbying under technological and economic constraints.

Site-specific information technologies help cotton farmers make decisions to improve nitrogen (N) fertilizer efficiency. Various information technologies, as well as farm and farmer characteristics, could affect fertilizer decisions differently. Knowing these differences could assist the targeting of specific groups of farmers for the adoption of various site-specific information technologies to improve N fertilizer efficiency and reduce negative environmental impacts. Ordered logit analysis was used to identify the information technologies and farm and farmer characteristics that influence the importance farmers place on precision farming (PF) technologies in improving the efficiency of N fertilization of cotton (Gossypium hirsutum L.). Data were obtained from a 2001 mail survey of cotton farmers in six southeastern states in the United States of America. Results indicated that yield monitoring, management zone and grid soil sampling, and on-the-go sensing increased farmers' perceptions of the importance of PF in improving N fertilizer efficiency. Farmers who used geospatial mapping were more likely than other farmers to find PF unimportant. Older cotton farmers who rented a larger portion of the land they farmed were more likely to place greater importance on PF for improving N efficiency.

The purpose of the study is to assess the outcome of the Expanded Program on Immunization (EPI) in Nigeria, as well as to examine systemic factors influencing its high under-five mortality rate (UFMR). The principal objective of the EPI program when it was implemented in 1978 was to reduce mortality, morbidity and disability associated with six vaccine preventable diseases namely tuberculosis, tetanus, diphtheria, measles, pertussis and poliomyelitis. The methodological approach to this study is quantitative, using secondary time series data from 1970 to 2003. The study tested three hypotheses using time series multiple regression analysis with autocorrelation adjustment as a statistical model. The results showed that the EPI program had little effect on UFMR in Nigeria. Only the literacy rate and domestic spending on healthcare had statistically significant effects on the UFMR. The military government was not a significant factor in reducing or increasing the UFMR. It appears that Nigeria needs a unified approach to healthcare delivery, rather than fragmented programs, to overcome cultural and political divisions in society.

STUDY DESIGN Clinical, biochemical, and histologic analysis was performed after in vivo delivery of cDNA encoding various anabolic cytokines and marker genes to the lumbar epidural space of New Zealand white rabbits, using both adenoviral and adeno-associated viral vectors. OBJECTIVE To mimic errant or misplaced doses of gene therapy to better ascertain the potential risks associated with alternative vectors and transgene products with regard to their application to problems of the intervertebral disc. SUMMARY OF BACKGROUND DATA Work done with several anabolic cytokines including bone morphogenic proteins and transforming growth factors, has demonstrated the potential of gene therapy. Recently, data has been published demonstrating that improperly dosed or delivered adenoviral-mediated gene therapy within the subarachnoid space can result in significant morbidity in rabbits. There are currently no studies examining the effect of these errors within the epidural space or using an adeno-associated viral (AAV) vector. METHODS Using either adenoviral or AAV vectors, complementary DNA (cDNA) encoding anabolic cytokines bone morphogenic protein-2 (BMP-2) and transforming growth factor-beta 1 and marker proteins LacZ and green fluorescent protein were injected into the epidural space of 37 New Zealand white rabbits at the L5/6 level. Rabbits were then observed clinically for up to 6 weeks, after which the rabbits were sacrificed in order to perform a comprehensive biochemical and histologic analysis. RESULTS Following adenoviral-mediated delivery of anabolic cytokine cDNA, up to eighty percent of rabbits demonstrated significant clinical, biochemical, and histologic morbidity. Conversely, AAV-mediated delivery of any cDNA and adenoviral-mediated delivery of marker protein cDNA resulted in no clinical, histologic, or biochemical morbidity. CONCLUSION Properly dosed and directed gene therapy seems to be both safe and potentially efficacious. This study suggests that side effects of gene therapy may be due to a combination of dosing, transgene product, and vector choice, and that newer AAV vectors may reduce these side-effects and decrease the risk of this technology.

This research evaluated the factors that influenced cotton (Gossypium hirsutum L.) producers to adopt remote sensing for variable-rate application of inputs. A logit model estimated with data from a 2005 mail survey of cotton producers in 11 southern USA states was used to evaluate the adoption of remote sensing. The most frequently made management decisions using remote sensing were the application of plant growth regulators, the identification of drainage problems and the management of harvest aids. A producer who was younger, more highly educated and had a larger farm with irrigated cotton was more likely to adopt remote sensing. In addition, farmers who used portable computers in fields and produced their own map-based prescriptions had a greater probability of using remote sensing. The results suggest that value-added map-making services from imagery providers greatly increased the likelihood of a farmer being a user of remote sensing.

The Behavioral Risk Factor Surveillance Survey is used to compare three predictors of self-rated health, specifically exercise, tobacco smoking, and a diagnosis of diabetes (a proxy for obesity). Exercise is found to be the best predictor, and the remainder of the article discusses the role of exercise in disease prevention and the all-important concept of exercise adherence. Government policy in the future needs to promote exercise adherence in a more rigorous way, because it is a key to both individual and societal health. Exercise habits need to be instilled from youth, and physical education requirements in school need to be re-established at all levels through high school. Adults also need encouragement with better neighborhood planning of exercise trails for walking and biking, as well as planned community activities to encourage fitness through one’s lifetime. The article concludes with six recommendations for formal government action to encourage exercise adherence.

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer's decision to adopt GPS guidance systems.

Screening applicants for the position of peace officer is a very uncertain process. Concomitantly, trying to select applicants who will be successful throughout their careers adds another, important dimension. Unfortunately, the selection process has primarily been one of screening-out those who are for one reason or another unfit. This article used the Thurstone Scale as the methodological basis to identify those traits that experts agreed are the ones that are meaningful in predicting police officer career success.

Site-specific information technologies (IT) provide knowledge about the spatial variability within a field to improve the efficiency of inputs through variable-rate (VR) applications. Identifying factors that influence farmers’ perceptions of the importance of precision farming (PF) technologies in improving the efficiency of phosphorus (P) and potassium (K) fertilizer applications can help to determine why different groups of farmers adopt PF. Knowing these factors can be useful in targeting specific groups of farmers to adopt PF and increase fertilizer efficiency to meet crop needs and reduce P and K losses to the environment. Data were obtained from a 2001 mail survey of cotton (Gossypium hirsutum L.) farmers in six southeastern states in the United States of America. Ordered logit analysis was used to evaluate the level of importance to those who had adopted PF technologies placed on such technologies they had used to improve the efficiency of P and K applications. Results showed that such farmers found soil sampling by management zone or on a grid, and on-the-go sensing most important. Precision farmers who used mapping and remote sensing found PF technologies least important. Older precision farmers who rented larger proportions of their land and used computers for farm management were more likely than other precision farmers to place greater importance on PF technologies in improving the efficiency of P and K applications.

Intervertebral disc degeneration is a chronic process that can become manifest in clinical disorders such as idiopathic low back pain, sciatica, disc herniation, spinal stenosis, and myelopathy. The limited available treatment options (including discectomy and spinal fusion) for these and other disabling conditions that arise from intervertebral disc degeneration are highly invasive, achieve limited success, and only address acute symptoms while doing nothing to halt the process of degeneration. Although the precise pathophysiology of intervertebral disc degeneration has yet to be clearly delineated, the progressive decline in aggrecan, the primary proteoglycan of the nucleus pulposus, appears to be a final common pathway. Animal models as well as in vitro studies of the process of disc degeneration have yielded many potentially useful targets for the reversal of disc degeneration. One current research trend is the use of established animal models of disc degeneration to study the role of therapeutic modalities in reversing the process of degeneration, often with use of the delivery of genes or gene products that influence the anabolic and catabolic pathways of the disc. This article reviews the ability of gene-product delivery systems and gene therapy to alter biologic processes in animal models of disc degeneration and examines future trends in this field.

Summary Brownfield and derelict sites are a global issue and within inner city neighbourhoods they are often associated with poverty, crime, drugs and neglect. In the current climate of Agenda 21 these negative issues are not conducive to the issue of sustainability. This poses the question of what can be done in these areas to reduce these problems and help create more sustainable communities. A comparative study explores the benefits and key features of German allotment gardens and American community gardens with a view to their possible implementation into inner city derelict and Brownfield regeneration in the UK and other countries. Their benefits can be appreciated through comparison of the two models, whilst considering whether community gardens have a role in helping to create sustainable communities that positively impact the negative social, economic and environmental issues associated with derelict sites in inner city neighbourhoods.

This study identified the factors that influenced whether farmers in the Southeastern United States perceived an improvement in environmental quality from adopting precision farming technologies (PFTs). Farmers with larger farms or higher yields were more likely to believe that they observed positive externalities associated with PFTs. Farmers who found PFTs profitable or who believed input reduction was important had higher probabilities whereas those with higher incomes or who were more dependent on farm income were less likely to perceive such benefits. Interestingly, the importance of environmental quality and length of time using PFTs were not found to affect the probability of perceiving an improvement in environmental quality.

This article introduces the Cotton Yield Monitor Investment Decision Aid (CYMIDA), a stand alone, interactive, and user-friendly computerized decision aid for analyzing the cotton yield monitor information system investment choice. Because electronic cotton yield monitors are a relatively new technology, the decision aid was developed to meet the need for better educational information about annual ownership costs and required returns for the cotton yield monitoring information investment decision. The partial budgeting and breakeven analysis methods and data used in CYMIDA are documented. In addition, the use of the decision aid is explained and three example investment analyses using the decision aid are described.

Providers of geriatric care in Arkansas were surveyed to determine the desire for more information on their specialty as well as opportunities for further training. Those in the nursing profession were most interested in further training, and the major area of interest for all providers was in cognitive decline and mental health information. Specifically, information was sought in the areas of dementia, depression, and memory loss. It is recommended that improvement in geriatric care in the future should focus on nursing education and on raising the level of knowledge and academic prestige in the treatment of elderly patients, especially in the mental health areas.

It was predicted that preference factions within decision-making groups would have greater influence to the extent that faction-member preferences are based on a common pool of decision-relevant information. Such factions are said to exhibit high informational commonality (IC). Four-person groups decided how much money to invest in each of two pharmaceutical companies developing new cholesterol-lowering drugs. Prior to discussion, information about these companies and drugs was distributed among members such that two would initially prefer investing in one company and two would initially prefer investing in the other company. Further, whereas half of the information held by members of one preference faction was held in common between them (high IC), almost none of the information held by those in the other faction was held in common between them (low IC). It was found that groups invested more money in a given company when that company was initially preferred by their high-IC faction. Additionally, high-IC factions exerted greater influence on members' private allocation preferences. These effects appear to have been due to the ability of members in the high-IC factions to work together in a more coordinated manner to argue their position. Copyright © 2004 John Wiley & Sons, Ltd.

This article is written frompersonal experiences with the recent death of the authors’ mother. It highlights the problems the authors encountered, while acknowledging the positive aspects of treatment during a difficult time. The overall purpose is to improve end-of-life care by advancing policy through research, legislation, and education. The impetus for writing this article is personal experience, but its larger purpose is to address issues that many readers will face in the future and suggest possible reforms, especially in the area of education.

This paper examines the emerging techniques associated with computer aided interviewing. The methodology is viewed as a management information system, and experienced based guide lines are offered for the design of the research project which will utilize CAI. Characteristics of good software are presented with the hope that this will aid in software selection and development. CAI has received limited methodological research in the marketing literature, so several issues are presented in the hope that such research will be stimulated.

Cleaning in distilleries requires establishing acceptable levels of cleanliness in each area of the physical plant as well as through the processes. For efficient cleaning, chemicals and procedures must be matched to the soils that are present. Validation of the cleaning process and the final result is an important part of the cleaning program. Keeping the distillery clean also requires attention to sanitary design and sanitation standards for the building, the process equipment and the piping systems.

In recent years, bioenergy has become a promising renewable energy source that can potentially reduce the greenhouse emissions and generate economic growth in rural areas. Gaining understanding and controlling biomass chemical composition contributes to an efficient biofuel generation. This paper presents a principal component analysis (PCA) that shows the influence and relevance of selected controllable factors over the chemical composition of switchgrass and, therefore, in the generation of biofuels. The study introduces the following factors: (1) storage days; (2) particle size; (3) wrap type; and (4) weight of the bale. Results show that all the aforementioned factors have an influence in the chemical composition. The number of days that bales have been stored was the most significant factor regarding changes in chemical components due to its effect over principal components 1 and 2 (PC1 and PC2, approximately 80% of the total variance). The storage days are followed by the particle size, the weight of the bale and the type of wrap utilized to enclose the bale. An increment in the number of days (from 75–150 days to 225 days) in storage decreases the percentage of carbohydrates by −1.03% while content of ash increases by 6.56%.

This study examined the discussion of information among mixed-status clinical teams while constructing differential diagnoses. Twenty-four ad hoc teams, each consisting of a resident, an intern, and a third-year medical student, were given two hypothetical patient cases to discuss and diagnose. Prior to discussion, team members individually viewed different versions of a videotaped interview with a "patient" (trained actor) Each videotape contained some information that was present in all three versions (shared information) and some that was present in only that version (unique information). In addition, half of the time, the cases were constructed so that the unique information that appeared in only one tape was crucial for a correct diagnosis (a "hidden profile" condition) After viewing the videotapes, team members met to discuss the case and develop a differential diagnosis. Discussions were videotaped and analyzed. Overall, shared information was mentioned more often than unique information (p < 0.0001). Furthermore, teams offered incorrect diagnoses significantly more often for hidden-profile cases than for control cases (p < 0.01). The teams' overreliance on previously shared information (inability to appropriately utilize unique information) was detrimental when a correct diagnosis demanded the inclusion of such information. Clinical discussions that require the consideration of uniquely held information may be susceptible to error. Key words: clinical teams; decision making; communication patterns; diagnostic error; information sharing. (Med Decis Making 2000;20:45-50)