Social Protection Index Brief: Social Assistance Programs in Asia and the Pacific

[Excerpt] The Asian Development Bank (ADB) report The Social Protection Index: Assessing Results for Asia and the Pacific (2013) documents the role of social assistance in social protection systems across the region. This brief examines the six major subcomponents of social assistance and draws out policy lessons based on comprehensive data for 35 countries in the region. The report uses the Social Protection Index (SPI) as the focal point for its analysis. The SPI is the ratio of total social protection expenditures to the total number of intended beneficiaries. These “expenditures per potential beneficiary” are then compared to a regional poverty line as a reference point (ADB 2012c)

Social Protection Index Brief: Labor Market Programs in Asia and the Pacific

[Excerpt] The Asian Development Bank (ADB) report The Social Protection Index: Assessing Results for Asia and the Pacific (2013) documents the negligible role of labor market programs in social protection programs across the region

Using structural analysis to investigate the function of Suppressor of IKK-epsilon (SIKE)

The innate immune system provides the body’s first line of defense against pathogenic challenge through pathogen recognition and initiation of the immune response. Among the various cellular mechanisms of pathogen recognition in mammals, Toll-like receptor 3 (TLR3) recognizes viral dsRNA. Stimulation of TLR3 signaling pathway leads to transcription of pro-inflammatory cytokines and type-1 Interferons. Suppressor of IKKε (SIKE) interacts with two kinases in the signaling pathway, IKKε and TANK binding kinase 1 (TBK1), inhibiting the transcription of type I interferons. Recently, the Bell Laboratory discovered that SIKE blocks TBK1-mediated activation of type I interferons by acting as a high affinity, alternative substrate of TBK1. To further characterize SIKE’s function within the antiviral response, this study focused on defining the overall SIKE structure. Using recombinant protein expressed from E. coli and purified via immobilized metal affinity chromatography, SIKE crystals were obtained from a sample concentrated to 15 mg/ml under several crystallization conditions. Yet, reproducing these results has been difficult. In this study, we have modified the purification scheme to remove an E. coli contaminant, SlyD. Purification under denaturing conditions, removal of soluble proteins, incorporation of ion exchange and different IMAC (immobilized metal ion affinity chromatography) resins has been tested. For each scheme, size exclusion chromatography and SDS-PAGE/Coomassie/silver stain were used to assess purity. Crystallization trials for samples from each purification scheme were completed. In addition to crystallization trials, hydrogen-deuterium exchange (HDX) was investigated, accompanied with pepsin digests, in order to further characterize the dynamic structure of SIKE

Alien Registration- Mckinley, Charles W. (South Portland, Cumberland County)

https://digitalmaine.com/alien_docs/20137/thumbnail.jp

Regenerating Professional Learning: The Influence Of Relationships On Teacher Identity, Agency, And Advocacy

Professional development for teachers gained more attention with the passage of the Elementary and Secondary Education Act (ESEA) of 2001. However, reform efforts spurred by this act focused mainly on training for specific programs and curriculum materials, resulting in little attention to instruction. In the last thirty or more years, new approaches to professional development have emerged, with teacher leadership, in particular, gaining more attention in studies as an important mechanism for reforming classroom practice to raise student achievement. Research has mainly examined collaborative frameworks to sustain teacher growth through professional learning communities situated within the context of schools and districts. Future research focused on the role of relationships with mentors and professional networks outside schools and districts has the potential to advance a conceptual framework for transforming teacher practice and student learning. This study used social network analysis and narrative analysis as conceptual and analytical frameworks to understand how relationships among teachers in a community of practice influenced their practice and their growth. This study specifically considered the following broad question about professional learning: In what ways do relationships among National Writing Project teacher-consultants influence teacher-consultant’s growth as learners, writers, and teachers of writing? Data was collected through surveys of several participants and interviews with four informants; these teachers worked in the same school district and participated in the State Writing Project (SWP) at different times in their teaching careers. Participants indicated that they believed particular practices, such as reviewing student work and receiving feedback from colleagues was important to their professional growth. However, these participants also noted that they rarely participated in such activities. Also, the informants explained they chose to participate in the SWP because they sought ways to address the needs of their students and goals of their district, needs and goals not necessarily met with professional development experiences. This study analyzed the experiences of these informants in their teaching and learning about writing and their perceptions of their participation in the State Writing Project. Their stories suggest that colleagues with this social network of the SWP had a significant influence on their knowledge about and understanding of teaching writing. These SWP colleagues had an impact on revitalizing the informants’ enthusiasm for teaching, prompting a desire to enact particular practices in their schools and districts. Future studies could focus on these informal structures – these relationships within a network – as a way to support the professional learning of teachers. Additional studies might also examine how narratives serve both as a tool to understand these relationships and as a way to provide teachers opportunities to reflect on their growth as learners and teachers

Chemical Analyses of Water from Selected Wells and Springs in the Yucca Mountain Area, Nevada and Southeastern California

Chemical analysis of water samples from 279 wells and springs in the Yucca Mountain area are presented. Where data are available, this report includes: site location expressed as Nevada Central Coordinates and latitude and longitude; source of data; name of analyzing laboratory; geologic unit from which water was obtained; lithology; water use; elevation of well or spring; well depth; depth to water; time pumped before taking the sample; yield; type of filtration; sampling method; date the sample was collected; and anion-cation balance. Yucca Mountain, Nevada (fig. 1), is being investigated by the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, as a possible repository for the disposal of high-level nuclear wastes. Yucca Mountain is underlain by partially altered volcanic tuffs that probably extend to depths greater than 3,000 m (Snyder and Carr, 1982). If approved, the repository will most likely be excavated within the unsaturated zone, 150 to 300 m above the water table. One concern is that radionuclides might be leached from the stored wastes and eventually reach the saturated zone, where they would be transported in the ground-water system away from the repository. The purpose of this report is to present a data base that consolidates the available ground-water data for the area surrounding the potential Yucca Mountain nuclear-waste repository. The objective of assembling this data is to provide a data base that potentially could be used to help determine: (1) Ground-water flow paths; (2) velocities and residence times of ground water; (3) the degree of vertical and lateral chemical heterogeneity of the ground-water system; and (4) chemical processes that affect the potential movement radionuclide species

Scientific Machine Learning for Modeling and Simulating Complex Fluids

The formulation of rheological constitutive equations -- models that relate internal stresses and deformations in complex fluids -- is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine learning constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data, and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these 'digital fluid twins' to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation -- a task that is not achievable using any previously developed data-driven rheological equation of state.Comment: 13 pages, 4 figure

The Medium Amplitude Response of Nonlinear Maxwell-Oldroyd Type Models in Simple Shear

A general framework for Maxwell-Oldroyd type differential constitutive models is examined, in which an unspecified nonlinear function of the stress and rate-of-deformation tensors is incorporated into the well-known corotational version of the Jeffreys model discussed by Oldroyd. For medium amplitude simple shear deformations, the recently developed mathematical framework of medium amplitude parallel superposition (MAPS) rheology reveals that this generalized nonlinear Maxwell model can produce only a limited number of distinct signatures, which combine linearly in a well-posed basis expansion for the third order complex viscosity. This basis expansion represents a library of MAPS signatures for distinct constitutive models that are contained within the generalized nonlinear Maxwell model. We describe a framework for quantitative model identification using this basis expansion, and discuss its limitations in distinguishing distinct nonlinear features of the underlying constitutive models from medium amplitude shear stress data. The leading order contributions to the normal stress differences are also considered, revealing that only the second normal stress difference provides distinct information about the weakly nonlinear response space of the model. After briefly considering the conditions for time-strain separability within the generalized nonlinear Maxwell model, we apply the basis expansion of the third order complex viscosity to derive the medium amplitude signatures of the model in specific shear deformation protocols. Finally, we use these signatures for estimation of model parameters from rheological data obtained by these different deformation protocols, revealing that three-tone oscillatory shear deformations produce data that is readily able to distinguish all features of the medium amplitude, simple shear response space of this generalized class of constitutive models.Comment: 26 pages, 11 figure