Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Numerical Computation of a Certain Dirichlet Series Attached to Siegel Modular Forms of Degree Two

The Rankin convolution type Dirichlet series D-F,D-G(s) of Siegel modular forms F and G of degree two, which was introduced by Kohnen and the second author, is computed numerically for various F and G. In particular, we prove that the series D-F,D-G(s), which shares the same functional equation and analytic behavior with the spinor L-functions of eigenforms of the same weight are not linear combinations of those. In order to conduct these experiments a numerical method to compute the Petersson scalar products of Jacobi Forms is developed and discussed in detail.

Impact of Various Insurance Types on Level and Appropriateness of Health Care Consumption

The goal of this study was to examine the extent to which insurance type, or method of care management, impact the appropriate delivery of health care. Previous studies indicate a relationship between insurance type and patterns of consumption but do not directly link the incentives or disincentives inherent in each plan with trends inconsumption of health care. This study explores how different types of health insurance coverage affect the location, the degree, and the frequency of health care consumption in order to gain insight into which plans promote appropriate delivery and consumption ofcare.

Deviation from Murray's law is associated with a higher degree of calcification in coronary bifurcations

Murray's law describes the optimal branching anatomy of vascular bifurcations. If Murray's law is obeyed, shear stress is constant over the bifurcation. Associations between Murray's law and intravascular ultrasound (IVUS) assessed plaque composition near coronary bifurcations have not been investigated previously.

Learned irrelevance and associative learning is attenuated in individuals at risk for psychosis but not in asymptomatic first-degree relatives of schizophrenia patients: translational state markers of psychosis?

Learned irrelevance (LIrr) refers to a form of selective learning that develops as a result of prior noncorrelated exposures of the predicted and predictor stimuli. In learning situations that depend on the associative link between the predicted and predictor stimuli, LIrr is expressed as a retardation of learning. It represents a form of modulation of learning by selective attention. Given the relevance of selective attention impairment to both positive and cognitive schizophrenia symptoms, the question remains whether LIrr impairment represents a state (relating to symptom manifestation) or trait (relating to schizophrenia endophenotypes) marker of human psychosis. We examined this by evaluating the expression of LIrr in an associative learning paradigm in (1) asymptomatic first-degree relatives of schizophrenia patients (SZ-relatives) and in (2) individuals exhibiting prodromal signs of psychosis ("ultrahigh risk" [UHR] patients) in each case relative to demographically matched healthy control subjects. There was no evidence for aberrant LIrr in SZ-relatives, but LIrr as well as associative learning were attenuated in UHR patients. It is concluded that LIrr deficiency in conjunction with a learning impairment might be a useful state marker predictive of psychotic state but a relatively weak link to a potential schizophrenia endophenotype.

Wound healing following regenerative procedures in furcation degree III defects: histomorphometric outcomes

Degree III furcation involvements were surgically created at four first molars in each of three monkeys. Following 6 weeks of healing, full-thickness flaps were elevated. Following 24% EDTA gel conditioning, the defects were treated with one of the following: (1) enamel matrix proteins (EMD), (2) guided tissue regeneration (GTR) or (3) a combination EMD and GTR. The control defects did not receive any treatment. After 5 months of healing, the animals were sacrificed. Three 8 μm thick histological central sections, 100 μm apart, were used for histomorphometric analysis in six zones of each tooth either within the furcation area or on the pristine external surface of the root. In all specimens, new cementum with inserting collagen fibres was formed. Following GTR or GTR + EMD, cementum was formed up to and including the furcation fornix indicating complete regeneration on the defect periphery. Periodontal ligament fibres were less in all four modalities compared to pristine tissues. In the teeth treated with GTR and GTR + EMD a higher volume of bone and periodontal ligament tissues was observed compared to EMD. After 5 months of healing, regenerated tissues presented quantitative differences from the pristine tissues. In the two modalities where GTR alone or combined with EMD was used, the regenerated tissues differed in quantity from the EMD-treated sites.

Utilization of Probabilistic Models in Short Read Assembly from Second-Generation Sequencing

With the advent of cheaper and faster DNA sequencing technologies, assembly methods have greatly changed. Instead of outputting reads that are thousands of base pairs long, new sequencers parallelize the task by producing read lengths between 35 and 400 base pairs. Reconstructing an organism’s genome from these millions of reads is a computationally expensive task. Our algorithm solves this problem by organizing and indexing the reads using n-grams, which are short, fixed-length DNA sequences of length n. These n-grams are used to efficiently locate putative read joins, thereby eliminating the need to perform an exhaustive search over all possible read pairs. Our goal was develop a novel n-gram method for the assembly of genomes from next-generation sequencers. Specifically, a probabilistic, iterative approach was utilized to determine the most likely reads to join through development of a new metric that models the probability of any two arbitrary reads being joined together. Tests were run using simulated short read data based on randomly created genomes ranging in lengths from 10,000 to 100,000 nucleotides with 16 to 20x coverage. We were able to successfully re-assemble entire genomes up to 100,000 nucleotides in length.

Examination of Priorities for Therapeutic Drug Utilization Review

Therapeutic Drug Utilization Review (DUR) is an important component of state-level pharmaceutical assistance programs.