RvMDM and lepton flavor violation

A model relating radiative seesaw and minimal dark matter mass scales without beyond the standard model (SM) gauge symmetry (RνMDM) is constructed. In addition to the SM particles, the RνMDM contains, a Majorana fermion multiplet N _R and scalar multiplet χ that transform respectively as (1, 5, 0) and (1,6,−1/2) under the SM gauge group SU(3)_C × SU(2) _L × U(1)_Y . The neutral component N_R^0 plays the role of dark matter with a mass in the range of 9 to 10 TeV. This scale also sets the lower limit for the scale for the heavy degrees of freedom in N_R and χ which generate light neutrino masses through the radiative seesaw mechanism. The model predicts an N_R^0-nucleus scattering cross section that would be accessible with future dark matter direct detection searches as well as observable effects in present and searches for charged lepton flavor violating processes, such as l_i → l_j γ and μ − e conversion

Are State-Ranking Indicators Correlated with State Economic Performance?

A variety of rankings appear regularly in the popular press.  Such rankings purport to indicate livability, economic well-being, crime propensity, obesity, and business climate, to name a few.  An investigation was conducted to assess whether state-ranking indicators developed by Forbes would be correlated with overall economic performance. We find that labor and quality of life have relatively high correlation with per capita gross state product; that business costs, the economic climate, and quality of life are well correlated with the unemployment rate; and the negative impact of high business costs on the growth rate of civilian employment is relatively high. The correlation coefficient between business costs and per capita gross state product has an unexpected sign. Growth prospects exhibit little correlation with state overall economic performance. The relatively low correlation coefficient between overall ranking and per capita gross state product or the growth rate of civilian employment suggests that it is not a good predictor for state workforce productivity or employment growth

Impacts Of Accountability Indicators And Socioeconomic Factors On Test Scores And Policy Implications

Based on a sample of 63 school districts in the state of Louisiana during academic year 2003-2004, we find that a higher (IOWA) test score is associated with higher attendance rates, smaller class sizes, more qualified teachers, more discipline, less spending per student, lower poverty rates, and lower per capita personal income. Therefore, we need to continue to pursue qualified teachers, smaller class sizes, and more discipline

Interaction Profile-Based Protein Classification of Death Domain

Background: The increasing number of protein sequences and 3D structure obtained fromgenomic initiatives is leading many of us to focus on proteomics, and to dedicate our experimentaland computational efforts on the creation and analysis of information derived from 3D structure.In particular, the high-throughput generation of protein-protein interaction data from a feworganisms makes such an approach very important towards understanding the molecularrecognition that make-up the entire protein-protein interaction network. Since the generation ofsequences, and experimental protein-protein interactions increases faster than the 3D structuredetermination of protein complexes, there is tremendous interest in developing in silico methodsthat generate such structure for prediction and classification purposes. In this study we focused onclassifying protein family members based on their protein-protein interaction distinctiveness.Structure-based classification of protein-protein interfaces has been described initially by Ponstinglet al. [1] and more recently by Valdar et al. [2] and Mintseris et al. [3], from complex structures thathave been solved experimentally. However, little has been done on protein classification based onthe prediction of protein-protein complexes obtained from homology modeling and dockingsimulation.Results: We have developed an in silico classification system entitled HODOCO (Homologymodeling, Docking and Classification Oracle), in which protein Residue Potential InteractionProfiles (RPIPS) are used to summarize protein-protein interaction characteristics. This systemapplied to a dataset of 64 proteins of the death domain superfamily was used to classify eachmember into its proper subfamily. Two classification methods were attempted, heuristic andsupport vector machine learning. Both methods were tested with a 5-fold cross-validation. Theheuristic approach yielded a 61% average accuracy, while the machine learning approach yielded an89% average accuracy.Conclusion: We have confirmed the reliability and potential value of classifying proteins via theirpredicted interactions. Our results are in the same range of accuracy as other studies that classifyprotein-protein interactions from 3D complex structure obtained experimentally. While ourclassification scheme does not take directly into account sequence information our results are inagreement with functional and sequence based classification of death domain family members

Relationship between Insertion/Deletion (Indel) Frequency of Proteins and Essentiality

Background: In a previous study, we demonstrated that some essential proteins from pathogenicorganisms contained sizable insertions/deletions (indels) when aligned to human proteins of highsequence similarity. Such indels may provide sufficient spatial differences between the pathogenicprotein and human proteins to allow for selective targeting. In one example, an indel difference wastargeted via large scale in-silico screening. This resulted in selective antibodies and smallcompounds which were capable of binding to the deletion-bearing essential pathogen proteinwithout any cross-reactivity to the highly similar human protein. The objective of the current studywas to investigate whether indels were found more frequently in essential than non-essentialproteins.Results: We have investigated three species, Bacillus subtilis, Escherichia coli, and Saccharomycescerevisiae, for which high-quality protein essentiality data is available. Using these data, wedemonstrated with t-test calculations that the mean indel frequencies in essential proteins weregreater than that of non-essential proteins in the three proteomes. The abundance of indels in bothtypes of proteins was also shown to be accurately modeled by the Weibull distribution. However,Receiver Operator Characteristic (ROC) curves showed that indel frequencies alone could not beused as a marker to accurately discriminate between essential and non-essential proteins in thethree proteomes. Finally, we analyzed the protein interaction data available for S. cerevisiae andobserved that indel-bearing proteins were involved in more interactions and had greaterbetweenness values within Protein Interaction Networks (PINs).Conclusion: Overall, our findings demonstrated that indels were not randomly distributed acrossthe studied proteomes and were likely to occur more often in essential proteins and those thatwere highly connected, indicating a possible role of sequence insertions and deletions in theregulation and modification of protein-protein interactions. Such observations will provide newinsights into indel-based drug design using bioinformatics and cheminformatics tools

Macroeconomic Policies And Economic Growth: The Case Of Costa Rica

Applying the well-known GARCH/ARCH (Engle, 1982, 2001) model, we find that real output in Costa Rica is positively affected by real M2 money, the expected inflation rate, and the U.S. output and negatively influenced by the depreciation of the colon. Consistent with the Barro-Ricardo (1989) hypothesis, deficit spending does not affect real output. Therefore, the Costa Rican government may need to pursue a balanced budget and maintain the stability of the colon because the costs of currency depreciation outweigh the benefits. &nbsp

Impacts Of Changing Financial And International Market Conditions On Output For Colombia

Potential effects of financial stock values, world market demand, exchange rate fluctuations and other factors on output variations for Colombia are examined. An open macroeconomic model is developed to include the goods market, the monetary policy, and the formulation of inflation. The sample consists of quarterly data ranging from 1994.Q1 to 2007.Q2 with a total of 54 observations. A generalized least squares (GLS) method is employed in order to correct for both heteroskedasticity and autocorrelation simultaneously. The results indicate a higher stock market value, real appreciation of the peso, higher world market demand, a lower U.S. real interest rate, and a lower expected inflation rate would increase real output for Colombia. Increased deficit spending would not help raise real output, suggesting that fiscal prudence may be needed

Addressing A Compensation Anomaly In An Academic Setting

Faculty compensation is a serious matter.  Rewards for performance are an expectation.  Managers recognize that rewards often drive performance and productivity.  Faculty members who perform well expect to be rewarded well.  Faculty members expend considerable time and effort developing evaluation instruments and procedures for assessing and rewarding peer performance.  Depending on how the reward process is implemented faculty performance rewards may not result as expected.  This paper contrasts faculty compensation models including one that produces a high performance, low compensation anomaly for higher paid faculty

Heads Or Tails (Success Or Failure)? Using Logit Modeling To Predict Student Retention And Progression

Using a sample of 2,137 university students and applying the logit model, we find that the probability for students to return in fall 2008 is higher with a higher cumulative GPA, a higher grade for SE 101, and a returning status in the previous semester.  Several other explanatory variables are tested and have insignificant coefficients. A few variables such as the Board of Regent’s core requirements (CORE) and high school graduating GPA (HSGPA) have the expected signs and z-statistics closer to one, suggesting that the correlation coefficient may rise if the sample size were larger.  The findings suggest that the cumulative GPA is a dominant factor and that the large number of failures in SE 101 may need to be examined in order to fulfill its described purpose: “a course designed to ensure first-year student success.&rdquo