Scaling Up to Increase Community-Based Organization Voice

In the initial phase of a case study of the merger of two already-effective decades-old community-based organizing groups in Chicago, we examine the extent to which the"scaling up"new organization is increasing its power at neighborhood-wide, citywide, regional, statewide, and nationwide levels. The combined geographic based of the new organization covers ten community areas containing 600,000 residents. At the same time, the organization has redoubled efforts to maintain strong grassroots member involvement in internal organizational deliberation and setting organizational priorities. The previous organizations had a history of working on a broad range of issues of importance to equity and the quality of life in local communities. These have included work on public education, affordable housing, mental health justice, violence reduction, mass incarceration, homeless and LGBT youth issues, youth engagement, as well as a stronger voice for the entire community in political decision making. Using more than 30 interviews with old and new organization staff and members along with observation of the new organization's councils, issue teams, and community actions over the past year, we determine the dimensions of power that leaders and members identify as being affected by the scaling up. As the larger project progresses, these dimensions will be used in measuring the impact of the merger on its power and influence. Both organizations had been known for both their confrontational tactics and effective coalition building. We use a community-based participatory research approach in examining the organization which seeks to promote equity in racially, ethnically, and economically diverse communities on Chicago's northside

An Information-Geometric Reconstruction of Quantum Theory, I: The Abstract Quantum Formalism

In this paper and a companion paper, we show how the framework of information geometry, a geometry of discrete probability distributions, can form the basis of a derivation of the quantum formalism. The derivation rests upon a few elementary features of quantum phenomena, such as the statistical nature of measurements, complementarity, and global gauge invariance. It is shown that these features can be traced to experimental observations characteristic of quantum phenomena and to general theoretical principles, and thus can reasonably be taken as a starting point of the derivation. When appropriately formulated within an information geometric framework, these features lead to (i) the abstract quantum formalism for finite-dimensional quantum systems, (ii) the result of Wigner's theorem, and (iii) the fundamental correspondence rules of quantum theory, such as the canonical commutation relationships. The formalism also comes naturally equipped with a metric (and associated measure) over the space of pure states which is unitarily- and anti-unitarily invariant. The derivation suggests that the information geometric framework is directly or indirectly responsible for many of the central structural features of the quantum formalism, such as the importance of square-roots of probability and the occurrence of sinusoidal functions of phases in a pure quantum state. Global gauge invariance is seen to play a crucial role in the emergence of the formalism in its complex form.Comment: 26 page

Ontologies4Chem: The landscape of ontologies in chemistry

For a long time, databases such as CAS, Reaxys, PubChem or ChemSpider mostly rely on unique numerical identifiers or chemical structure identifiers like InChI, SMILES or others to link data across heterogeneous data sources. The retrospective processing of information and fragmented data from text publications to maintain these databases is a cumbersome process. Ontologies are a holistic approach to semantically describe data, information and knowledge of a domain. They provide terms, relations and logic to semantically annotate and link data building knowledge graphs. The application of standard taxonomies and vocabularies from the very beginning of data generation and along research workflows in electronic lab notebooks (ELNs), software tools, and their final publication in data repositories create FAIR data straightforwardly. Thus a proper semantic description of an investigation and the why, how, where, when, and by whom data was produced in conjunction with the description and representation of research data is a natural outcome in contrast to the retrospective processing of research publications as we know it. In this work we provide an overview of ontologies in chemistry suitable to represent concepts of research and research data. These ontologies are evaluated against several criteria derived from the FAIR data principles and their possible application in the digitisation of research data management workflows

Quantum Electrical Dipole in Triangular Systems: a Model for Spontaneous Polarity in Metal Clusters

Triangular symmetric molecules with mirror symmetry perpendicular to the 3-fold axis are forbidden to have a fixed electrical dipole moment. However, if the ground state is orbitally degenerate and lacks inversion symmetry, then a ``quantum'' dipole moment does exist. The system of 3 electrons in D_3h symmetry is our example. This system is realized in triatomic molecules like Na_3. Unlike the fixed dipole of a molecule like water, the quantum moment does not point in a fixed direction, but lies in the plane of the molecule and takes quantized values +/- mu_0 along any direction of measurement in the plane. An electric field F in the plane leads to a linear Stark splitting +/- mu_0 F}. We introduce a toy model to study the effect of Jahn-Teller distortions on the quantum dipole moment. We find that the quantum dipole property survives when the dynamic Jahn-Teller effect is included, if the distortion of the molecule is small. Linear Stark splittings are suppressed in low fields by molecular rotation, just as the linear Stark shift of water is suppressed, but will be revealed in moderately large applied fields and low temperatures. Coulomb correlations also give a partial suppression.Comment: 10 pages with 7 figures included; thoroughly revised with a new coauthor; final minor change

Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures

Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast database comprising 90,000 microstructures drawn from nine different stochastic models, and compute their effective diffusivity and permeability as well as various microstructural descriptors. To the best of our knowledge, this is the largest and most diverse dataset created for studying the influence of 3D microstructure on mass transport. In particular, we establish microstructure-property relationships using analytical prediction formulas, artificial (fully-connected) neural networks, and convolutional neural networks. Again, to the best of our knowledge, this is the first time that these three statistical learning approaches are quantitatively compared on the same dataset. The diversity of the dataset increases the generality of the determined relationships, and its size is vital for robust training of convolutional neural networks. We make the 3D microstructures, their structural descriptors and effective properties, as well as the code used to study the relationships between them available open access

Evaluation of strength characteristics of recycled asphalt pavement materials

Use of recycled asphalt pavement (RAP) can reduce the cost of pavement materials significantly. In Queensland, the Department of Transport and Main Roads is reluctant to increase RAP usages and has placed stricter limits, allowing a maximum RAP content of only 15% by mass of mix. This is due to the fact that the presence of aged and stiffer binder can increase the resilient modulus of the mixtures and reduce fatigue life if no allowance is made. Researchers' suggest adapting a low grade binder as an option when using higher percentage of RAP. This research was to assess whether using a softer binder could help to improve the fatigue life of high percentile RAP mixtures. The mix design tested was a dense grade 20mm base course. Experiments were carried out to find the mechanical properties of batches comprised of 0, 15% RAP with same binder and 30%, 45% and 60% of RAP with one step lower level binder. During batching all possible efforts were taken to maintain homogeneity between the samples, and effective binder volume was adjusted for air voids before estimating the actual modulus. The results were used to estimate the fatigue life using the Austroads' fatigue model. It was found that mixing higher percentile RAP together with the binder one grade lower than usual can be effective in reducing residual modulus and improving fatigue life of the pavement. However, there is also potential to overcompensate, yielding softer mixes which may be more susceptible to rutting. It was also found that 60% mix could give similar mechanical performance to a conventional mix. In summary, using the softer binder had the greatest impact on blended binder fatigue life so Australian guidelines can be improved to make the most effective use of recycled asphalts where further studies are required

Stand Up, Students! Decisional Cues Reduce Sedentary Behavior in University Students

Background: University students are prone to sedentary behavior (SB) which is associated with multiple negative health outcomes. Sit-stand desks may allow for a reduction of SB through standing bouts. To promote standing in university students, decisional cues might be a low-cost approach that can easily be implemented. Purpose: To investigate the effects of decisional cues on students' SB, standing, and active behavior. Method: Over 3 weeks, students were observed in a building on a German university campus, which provides sit-stand-desks in study areas, using an adapted version of the SOPLAY protocol. Baseline data was collected in the first week (T1), before posters and table plaques containing decisional cues were set up in the study areas. Effects were measured in the following 2 weeks (T2 and T3). Results: 2,809 (33% female) students were observed. Sitting decreased from 92.9% [SD = 14.9] to 84.5% [SD = 22.1] from T1 to T3 [F (1, 141) = 15.6; p < 0.01; η2 = 0.10]. Standing increased from 5.6% [SD = 13.5] to 10.9% [SD = 14.4] [F (1, 141) = 9.0; p < 0.01; η2 = 0.06] and being active from 1.5% [SD = 6.9] to 4.5% [SD = 14.8] from T1 to T3 [F (1, 141) = 4.2; p < 0.05; η2 = 0.03). Main effect analyses revealed more students standing in the afternoon compared to morning and lunchtime [F (2, 140) = 3.2; p < 0.05; η2 = 0.04). Discussion: Decisional cues could decrease students' SB and promote standing or being active as alternatives. Future research should use a more rigorous study design. The content of the decisional cues should be explored more and expanded to other health promotion areas on campus

Assessment of myelination in infants and young children by T1 relaxation time measurements using the magnetization-prepared 2 rapid acquisition gradient echoes sequence

Background: Axonal myelination is an important maturation process in the developing brain. Increasing myelin content correlates with the longitudinal relaxation rate (R1=1/T1) in magnetic resonance imaging (MRI). Objective: By using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) on a 3-T MRI system, we provide R1 values and myelination rates for infants and young children. Materials and methods: Average R1 values in white and grey matter regions in 94 children without pathological MRI findings (age range: 3 months to 6 years) were measured and fitted by a saturating-exponential growth model. For comparison, R1 values of 36 children with different brain pathologies are presented. The findings were related to a qualitative evaluation using T2, magnetization-prepared rapid acquisition gradient echo (MP-RAGE) and MP2RAGE. Results: R1 changes rapidly in the first 16 months of life, then much slower thereafter. R1 is highest in pre-myelinated structures in the youngest subjects, such as the posterior limb of the internal capsule (0.74-0.76 +/- 0.04 s(-1)) and lowest for the corpus callosum (0.37-0.44 +/- 0.03 s(-1)). The myelination rate is fastest in the corpus callosum and slowest in the deep grey matter. R1 is decreased in hypo- and dysmyelination disorders. Myelin maturation is clearly visible on MP2RAGE, especially in the first year of life. Conclusion: MP2RAGE permits a quantitative R1 mapping method with an examination time of approximately 6 min. The age-dependent R1 values for children without MRI-identified brain pathologies are well described by a saturating-exponential function with time constants depending on the investigated brain region. This model can serve as a reference for this age group and to search for indications of subtle pathologies. Moreover, the MP2RAGE sequence can also be used for the qualitative assessment of myelinated structures