Quantum phase transitional patterns in the SD-pair shell model

Patterns of shape-phase transition in the proton-neutron coupled systems are studied within the $SD$-pair shell model. The results show that some transitional patterns in the $SD$-pair shell model are similar to the $U(5)-SU(3)$, $U(5)-SO(6)$ transitions with signatures of the critical point symmetry of the interacting boson model.Comment: 13 pages, 7 figure

Differences in Principals\u27 Data Use for Decision Making: An Administrative Probelm-Solving Perspective

As school leaders, principals must seek, use, and make sense of data and information. This study presents the findings of a survey study of 182 high school principals’ data use and examines the differences in the extent of principals’ data use for decision making in solving various dimensions of administrative problems. Results show principals used data frequently for decision-making in instructional leadership, organization operational leadership and school vision leadership, among which data use in instructional leadership was most frequent. Principals’ use of data was significantly less frequent in the leadership dimension of collaborative partnerships and larger-context politics. This article ends with implications with regard to improving school leadership programs in meeting the emergent need of preparing data driven decision makers and suggestions for research relevant to the central topic of data-driven decision making

Intruder level and deformation in the SD-pair shell model

The influence of the intruder level on nuclear deformation is studied within the framework of the nucleon-pair shell model truncated to an SD-pair subspace. The results suggest that the intruder level has a tendency to soften the deformation and plays an important role in determining the onset of rotational behavior.Comment: 2 input TeX files, 2 figures, submitted to Phys. Lett.

Artificial Neural Networks Used to Predict Electrical Properties of Polymers

The ability to predict properties of molecules prior to their synthesis can be of great importance in optimizing their design. Substantial savings in time as well as cost can be achieved if some desired properties can be predicted prior to the synthesis of the molecule. The outer orbitals of a molecule are primarily responsible for many different properties of the molecules. These outer orbital parameters can be utilized by an intelligent computing system like an Artificial Neural Network to extract necessary knowledge about the properties of the molecule. An Artificial Neural Network was trained to extract electrical parameters of several polymers. The former was then tested using a number of molecules set aside (not used in training) solely for this purpose

Distinguishing schemes and tasks in children's development of multiplicative reasoning

We present a synthesis of findings from constructivist teaching experiments regarding six schemes children construct for reasoning multiplicatively and tasks to promote them. We provide a task-generating platform game, depictions of each scheme, and supporting tasks. Tasks must be distinguished from children’s thinking, and learning situations must be organized to (a) build on children’s available schemes, (b) promote the next scheme in the sequence, and (c) link to intended mathematical concepts