Which States Support Which Ones? Predicting Federal Flow Through From the Feds to the States

While politicians in Washington, who have already authorized trillions of funds for businesses in the past 3 years, have been arguing over allocating funds for state and local governments, there have been a number of suggestions that stimulus packages potentially benefit certain states at the expense to others. The arguments primarily appear to come down to politics – “red,” Republican-led states versus “blue,” Democratically-led states. The insinuation is that that the “blue” states are more poorly run than the red states and that the better run “red” states should not be “bailing out” poorly run “blue” states. A linear regression model was developed that perfectly predicted both federal fund recipients and “red” or “blue” designations. Correlation and principal component analysis was run to determine the factors that were the best predictors. The truth appears to be as Governor Cuomo states, “blue” states are better run, better funded and are more productive than “red” states when measuring gross domestic product, income and net tax revenue per person. Educational funding was a major reason “blue” states were ahead of their “red” neighbors

Final Technical Report

During the contract period noted above, the Syracuse University Industrial Assessment Center conducted 97.5 assessment days for 98 different industrial clients. These assessments developed 818 assessment recommendations with an overall implementation rate of 51 % (AR’s). Total recommended dollar savings for the period was $17,386,758.00, with$8,893,212.00 actually implemented, for a dollar implementation rate of 57%. The Center employed a total of sixteen undergraduate interns throughout the contract period. Nine of these students stayed on at Syracuse University for graduate study with Center support; five students pursued graduate study at other universities. Ten of these students have, or will, accept professional positions in the energy consulting field. The Center has successfully engaged with a wide variety of professional and development organizations, including the Manufacturers Association of Central New York, The Central New York Technical Development Organization, (the local MEP), the New York State Energy Research and Development Authority, The New York Power Authority, the Onondaga County Citizens Energy Committee, and the New York State Center of Excellence on Indoor Environmental Systems

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F

Testing microscopically derived descriptions of nuclear collectivity : Coulomb excitation of 22Mg

Many-body nuclear theory utilizing microscopic or chiral potentials has developed to the point that collectivity might be studied within a microscopic or ab initio framework without the use of effective charges; for example with the proper evolution of the E2 operator, or alternatively, through the use of an appropriate and manageable subset of particle–hole excitations. We present a precise determination of E2 strength in 22Mg and its mirror 22Ne by Coulomb excitation, allowing for rigorous comparisons with theory. No-core symplectic shell-model calculations were performed and agree with the new B(E2) values while in-medium similarity-renormalization-group calculations consistently underpredict the absolute strength, with the missing strength found to have both isoscalar and isovector components. The discrepancy between two microscopic models demonstrates the sensitivity of E2 strength to the choice of many-body approximation employed

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

Minimizing Hypoglycemia in Diabetes.

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