Energy Information Outline, 2010

A historical view and distribution of energy in Iowa

Energy Information Outline, 2010

A historical view and distribution of energy in Iowa

2010 Energy Independence Plan

Iowans today operate in a world of change. From evolving economic conditions to environmental issues and demographic trends in our communities, we live and work in an atmosphere that constantly challenges us to think anew about our future. In Iowa, we are doing more than embracing these changes – we are seeking them. As a state focused on being the hub of investment and innovation for a new clean energy economy, our long term success depends on us staying ahead of these transformative waves. We do this all with attention to ensuring that we are investing in the right work to guarantee Iowa remains relevant, vibrant and connected to our vision for the next quarter of a century, not just the next quarter.

2011 Energy Independence Plan

Iowa has experienced remarkable progress in the past four years as the state has pursued a vision of becoming the nation’s energy leader. One of the most profound changes over this time has been a richer understanding of the economic future that can be created in Iowa by adding “Made in Iowa” alternatives to our nation’s energy mix. Built around a strong commitment to transforming our economy through innovation, collaboration, and implementation in the energy industry, the role of the Office of Energy Independence (Office) is to bring together the essential prerequisites for maintaining the long-term health and economic growth of our state. What is clearer than ever before is Iowa cannot achieve success if any entity chooses to pursue these goals independently. Rather, success requires that we consistently work to achieve our goals through integrated initiatives that place a high priority on moving us forward simultaneously, and on multiple fronts. Success is what our citizens expect from a leading state in the energy industry whose actions carry such far-reaching implications for the economy and the environment.

Energy Information Report, December 2007

In its 2007 session, the 82nd Iowa General Assembly passed, and Governor Culver signed into law, extensive and far-reaching new state energy policy legislation. Included was a directive to the Department of Natural Resources (DNR) to deliver to the Director of the Office of Energy Independence a report on six broad topics regarding Iowa’s energy resources.

Brain energy consumption induced by electrical stimulation promotes systemic glucose uptake.

BACKGROUND: Controlled transcranial stimulation of the brain is part of clinical treatment strategies in neuropsychiatric diseases such as depression, stroke, or Parkinson's disease. Manipulating brain activity by transcranial stimulation, however, inevitably influences other control centers of various neuronal and neurohormonal feedback loops and therefore may concomitantly affect systemic metabolic regulation. Because hypothalamic adenosine triphosphate-sensitive potassium channels, which function as local energy sensors, are centrally involved in the regulation of glucose homeostasis, we tested whether transcranial direct current stimulation (tDCS) causes an excitation-induced transient neuronal energy depletion and thus influences systemic glucose homeostasis and related neuroendocrine mediators.METHODS: In a crossover design testing 15 healthy male volunteers, we increased neuronal excitation by anodal tDCS versus sham and examined cerebral energy consumption with (31)phosphorus magnetic resonance spectroscopy. Systemic glucose uptake was determined by euglycemic-hyperinsulinemic glucose clamp, and neurohormonal measurements comprised the parameters of the stress systems.RESULTS: We found that anodic tDCS-induced neuronal excitation causes an energetic depletion, as quantified by (31)phosphorus magnetic resonance spectroscopy. Moreover, tDCS-induced cerebral energy consumption promotes systemic glucose tolerance in a standardized euglycemic-hyperinsulinemic glucose clamp procedure and reduces neurohormonal stress axes activity.CONCLUSIONS: Our data demonstrate that transcranial brain stimulation not only evokes alterations in local neuronal processes but also clearly influences downstream metabolic systems regulated by the brain. The beneficial effects of tDCS on metabolic features may thus qualify brain stimulation as a promising nonpharmacologic therapy option for drug-induced or comorbid metabolic disturbances in various neuropsychiatric diseases.

Energy balance, physical activity, and thermogenic effect of feeding in premature infants.

In order to assess the contribution of the thermogenic effect of feeding and muscular activity to total energy expenditure, nine premature infants were studied for 2 consecutive days during which time repeated measurements of energy expenditure by indirect calorimetry were performed throughout the day, combined with a visual activity score based on body movement. The infants were growing at 16.6 +/- 4.0 g/kg/day (mean +/- SD) and received 110 +/- 8 kcal/kg/day metabolizable energy (milk formula) and 522 +/- 40 mgN/kg/day. Their total energy expenditure was 68 +/- 4 kcal/kg/day indicating that 41 +/- 7 kcal/kg/day was retained for growth. Based on the combination of energy + N balances it was estimated that 80% of the weight gain was fat-free tissue and 20% was fat tissue. The rate of energy expenditure measured minute-by-minute was significantly and linearly correlated with the activity score in both the premeal (r = 0.75;p less than 0.001) and the postmeal periods (r = 0.74; p less than 0.001) with no difference in the regression slope, but with a significant difference in intercept. In preset feeding schedules the latter allowed an estimation of the thermogenic effect without the confounding effect of activity. This was found to be 3.1 +/- 1.8% when expressed as a percentage of metabolizable energy intake. However when the "classical" approach was used as a comparison (integration of extra energy expenditure induced by the meal), the thermogenic effect was found to be greater, i.e. 9.5 +/- 3.8% of the meal's metabolizable energy, due to the superimposed effect of physical activity in the postprandial state.(ABSTRACT TRUNCATED AT 250 WORDS)

Changes in sleeping and basal energy expenditure and substrate oxidation induced by short term thyroxin administration in man.

The present study was designed to explore the thermogenic effect of thyroid hormone administration and the resulting changes in nitrogen homeostasis. Normal male volunteers (n = 7) received thyroxin during 6 weeks. The first 3-week period served to suppress endogenous thyroid secretion (180 micrograms T4/day). This dose was doubled for the next 3 weeks. Sleeping energy expenditure (respiratory chamber) and BMR (hood) were measured by indirect calorimetry, under standardized conditions. Sleeping heart rate was continuously recorded and urine was collected during this 12-hour period to assess nitrogen excretion. The changes in energy expenditure, heart rate and nitrogen balance were then related to the excess thyroxin administered. After 3 weeks of treatment, serum TSH level fell to 0.15 mU/L, indicating an almost complete inhibition of the pituitary-thyroid axis. During this phase of treatment there was an increase in sleeping EE and sleeping heart rate, which increased further by doubling the T4 dose (delta EE: +8.5 +/- 2.3%, delta heart rate +16.1 +/- 2.2%). The T4 dose, which is currently used as a substitutive dose, lead to a borderline hyperthyroid state, with an increase in EE and heart rate. Exogenous T4 administration provoked a significant increase in urinary nitrogen excretion averaging 40%. It is concluded that T4 provokes an important stimulation of EE, which is mostly mediated by an excess protein oxidation.

Audit report on the American Recovery and Reinvestment Act (ARRA) - Program of Competitive Grants for Worker Training and Placement in High Growth and Emerging Industry Sectors program for the Iowa Green Renewable Electrical Energy Network Inc. (IGREEN) for the year ended June 30, 2012

Audit report on the American Recovery and Reinvestment Act (ARRA) - Program of Competitive Grants for Worker Training and Placement in High Growth and Emerging Industry Sectors program for the Iowa Green Renewable Electrical Energy Network Inc. (IGREEN) for the year ended June 30, 2012

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

MM-GBSA binding free energy decomposition and T cell receptor engineering.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by class I major histocompatibility complexes (MHC) is the key event in the immune response against virus infected cells or tumor cells. The major determinant of T cell activation is the affinity of the TCR for the peptide-MHC complex, though kinetic parameters are also important. A study of the 2C TCR/SIYR/H-2Kb system using a binding free energy decomposition (BFED) based on the MM-GBSA approach had been performed to assess the performance of the approach on this system. The results showed that the TCR-p-MHC BFED including entropic terms provides a detailed and reliable description of the energetics of the interaction (Zoete and Michielin, 2007). Based on these results, we have developed a new approach to design sequence modifications for a TCR recognizing the human leukocyte antigen (HLA)-A2 restricted tumor epitope NY-ESO-1. NY-ESO-1 is a cancer testis antigen expressed not only in melanoma, but also on several other types of cancers. It has been observed at high frequencies in melanoma patients with unusually positive clinical outcome and, therefore, represents an interesting target for adoptive transfer with modified TCR. Sequence modifications of TCR potentially increasing the affinity for this epitope have been proposed and tested in vitro. T cells expressing some of the proposed TCR mutants showed better T cell functionality, with improved killing of peptide-loaded T2 cells and better proliferative capacity compared to the wild type TCR expressing cells. These results open the door of rational TCR design for adoptive transfer cancer therapy.

Brain glucose sensing, counterregulation, and energy homeostasis.

Neuronal circuits in the central nervous system play a critical role in orchestrating the control of glucose and energy homeostasis. Glucose, beside being a nutrient, is also a signal detected by several glucose-sensing units that are located at different anatomical sites and converge to the hypothalamus to cooperate with leptin and insulin in controlling the melanocortin pathway.

Prediction of resting energy expenditure from fat-free mass and fat mass.

On the basis of literature values, the relationship between fat-free mass (FFM), fat mass (FM), and resting energy expenditure [REE (kJ/24 h)] was determined for 213 adults (86 males, 127 females). The objectives were to develop a mathematical model to predict REE based on body composition and to evaluate the contribution of FFM and FM to REE. The following regression equations were derived: 1) REE = 1265 + (93.3 x FFM) (r2 = 0.727, P < 0.001); 2) REE = 1114 + (90.4 x FFM) + (13.2 x FM) (R2 = 0.743, P < 0.001); and 3) REE = (108 x FFM) + (16.9 x FM) (R2 = 0.986, P < 0.001). FM explained only a small part of the variation remaining after FFM was accounted for. The models that include both FFM and FM are useful in examination of the changes in REE that occur with a change in both the FFM and FM. To account for more of the variability in REE, FFM will have to be divided into organ mass and skeletal muscle mass in future analyses.