A-1 Monthly Public Assistance Statistical Report Family Investment Program, January 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program for January 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program, February 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program - February 2007

Modeling of the TCR-MHC-peptide complex.

The methodology for generating a homology model of the T1 TCR-PbCS-K(d) class I major histocompatibility complex (MHC) class I complex is presented. The resulting model provides a qualitative explanation of the effect of over 50 different mutations in the region of the complementarity determining region (CDR) loops of the T cell receptor (TCR), the peptide and the MHC's alpha(1)/alpha(2) helices. The peptide is modified by an azido benzoic acid photoreactive group, which is part of the epitope recognized by the TCR. The construction of the model makes use of closely related homologs (the A6 TCR-Tax-HLA A2 complex, the 2C TCR, the 14.3.d TCR Vbeta chain, the 1934.4 TCR Valpha chain, and the H-2 K(b)-ovalbumine peptide), ab initio sampling of CDR loops conformations and experimental data to select from the set of possibilities. The model shows a complex arrangement of the CDR3alpha, CDR1beta, CDR2beta and CDR3beta loops that leads to the highly specific recognition of the photoreactive group. The protocol can be applied systematically to a series of related sequences, permitting the analysis at the structural level of the large TCR repertoire specific for a given peptide-MHC complex.

Making sense of AMPA receptor trafficking by modeling molecular mechanisms of synaptic plasticity.

Synaptic plasticity involves a complex molecular machinery with various protein interactions but it is not yet clear how its components give rise to the different aspects of synaptic plasticity. Here we ask whether it is possible to mathematically model synaptic plasticity by making use of known substances only. We present a model of a multistable biochemical reaction system and use it to simulate the plasticity of synaptic transmission in long-term potentiation (LTP) or long-term depression (LTD) after repeated excitation of the synapse. According to our model, we can distinguish between two phases: first, a "viscosity" phase after the first excitation, the effects of which like the activation of NMDA receptors and CaMKII fade out in the absence of further excitations. Second, a "plasticity" phase actuated by an identical subsequent excitation that follows after a short time interval and causes the temporarily altered concentrations of AMPA subunits in the postsynaptic membrane to be stabilized. We show that positive feedback is the crucial element in the core chemical reaction, i.e. the activation of the short-tail AMPA subunit by NEM-sensitive factor, which allows generating multiple stable equilibria. Three stable equilibria are related to LTP, LTD and a third unfixed state called ACTIVE. Our mathematical approach shows that modeling synaptic multistability is possible by making use of known substances like NMDA and AMPA receptors, NEM-sensitive factor, glutamate, CaMKII and brain-derived neurotrophic factor. Furthermore, we could show that the heteromeric combination of short- and long-tail AMPA receptor subunits fulfills the function of a memory tag.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, March 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - March 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program, April 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - April 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program, May 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - May 2007

Emotion and reason in everyday risk perception

Although research has documented the importance of emotion in risk perception, little is knownabout its prevalence in everyday life. Using the Experience Sampling Method, 94 part-timestudents were prompted at random via cellular telephones to report on mood state and threeemotions and to assess risk on thirty occasions during their working hours. The emotions valence, arousal, and dominance were measured using self-assessment manikins (Bradley &Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explainedsignificant variance in risk perception. In addition, valence and arousal accounted for varianceover and above reason (measured by severity and possibility of risks). Six risks were reassessedin a post-experimental session and found to be lower than their real-time counterparts.The study demonstrates the feasibility and value of collecting representative samples of data withsimple technology. Evidence for the statistical consistency of the HLM estimates is provided inan Appendix.

Associationism and electoral participation: A multilevel study of 2000 Spanish general election

This work presents an application of the multilevel analysis techniques tothe study of the abstention in the 2000 Spanish general election. Theinterest of the study is both, substantive and methodological. From thesubstantive point of view the article intends to explain the causes ofabstention and analyze the impact of associationism on it. From themethodological point of view it is intended to analyze the interaction betweenindividual and context with a modelisation that takes into account thehierarchical structure of data. The multilevel study of this paper validatesthe one level results obtained in previous analysis of the abstention andshows that only a fraction of the differences in abstention are explained bythe individual characteristics of the electors. Another important fraction ofthese differences is due to the political and social characteristics of thecontext. Relating to associationism, the data suggest that individualparticipation in associations decrease the probability of abstention. However,better indicators are needed in order to catch more properly the effect ofassociationism in electoral behaviour.

A-1 Monthly Public Assistance Statistical Report Family Investment Program, June 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - June 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program, July 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - July 2007

A-1 Monthly Public Assistance Statistical Report Family Investment Program, August 2007

A-1 - Monthly Public Assistance Statistical Report Family Investment Program - August 2007

Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Iowa Sales and Use Tax Annual Statistical Report 1998

Iowa Sales and Use Tax Annual Statistical Report 1998