Towards automated software model checking using graph transformation systems and Bogor

Graph transformation systems have become a general formal modeling language to describe many models in software development process. Behavioral modeling of dynamic systems and model-to-model transformations are only a few examples in which graphs have been used to software development. But even the perfect graph transformation system must be equipped with automated analysis capabilities to let users understand whether such a formal specification fulfills their requirements. In this paper, we present a new solution to verify graph transformation systems using the Bogor model checker. The attributed graph grammars （AGG）-like graph transformation systems are translated to Bandera intermediate representation （BIR）, the input language of Bogor, and Bogor verifies the model against some interesting properties defined by combining linear temporal logic （LTL） and special-purpose graph rules. Experimental results are encouraging, showing that in most cases our solution improves existing approaches in terms of both performance and expressiveness.     

Self- and Peer Assessments of Oral Presentations by First-Year University Students

Forty science students received training for 12 weeks on delivering effective presentations and using a tertiary-level English oral presentation scale comprising three subscales (Verbal Communication, Nonverbal Communication, and Content and Organization) measured by 18 items. For their final project, each student was given 10 to 12 min to present on 1 of the 5 compulsory science books for the module and was rated by the tutor, peers, and himself/herself. Many-facet Rasch measurement, correlation, and analysis of variance were performed to mine the data. The results show that the student raters, tutor, items, and rating scales achieved high psychometric quality, though a small number of assessments exhibited bias. Although all of the biased self-assessments were underestimations of presentation skills, the peer and tutor assessment bias had a mixed pattern. In addition, self-, peer, and tutor assessments had low to medium correlations on the subscales, and a significant difference was found between the assessments. Implications are discussed.     

Numerical investigation on a new local preconditioning method for solving the incompressible inviscid, non-cavitating and cavitating flows

A locally power-law preconditioning algorithm is developed. This is applied to compute incompressible inviscid, steady-state, non-cavitating and cavitating flows. The preconditioning parameters are adapted automatically from the pressure of computational domain. This method suggests better convergence rates rather than the standard artificial compressibility and the standard preconditioning method. Single-fluid Euler equations, cast in their conservative form, along with the barotropic cavitation model are employed. The cell-centred Jameson's finite volume discretization technique is used to solve the preconditioned governing equations. The stabilization is achieved via the second and fourth, order artificial dissipation scheme. Explicit four-stage Runge-Kutta time integration is applied to find the steady-state condition. In this paper, the method is assessed through simulations of incompressible inviscid, steady-state, non-cavitating and cavitating flows over a 2D NACA0012 and a 2D NACA66(MOD)+a=0.8 hydrofoil section. The results show satisfactory agreement with others numerical and experimental works in pressure distribution and hydrodynamic forces. Using the power-law preconditioner decreases the convergence rate significantly. In addition, information such as the effects of the new locally power-law preconditioner, the effects of the artificial dissipation terms, and the effects of the artificial compressibility parameter, on convergence speed and solution accuracy is highlighted.     

Middle leadership in international schools: evidence from Malaysia

This paper examines middle leadership of the heads of English, maths and science departments in four international secondary schools in Malaysia. It focuses on their roles, responsibilities, role relationships, instructional engagement and leadership involvement within the theoretical framework of instructional, distributed and teacher leadership. The study is a qualitative multi-method case study, involving observation, documentary analysis, and semi-structured interviews with 12 heads of department, 36 teachers, and four principals. With respect to the middle leaders’ roles and responsibilities, the findings illustrate cross-school and in-school differential developments, with contextual factors contributing to uneasy role relationships. The results also show that, while broad-based leadership opportunities are limited for the middle leaders and teachers, the most powerful and common feature of all these international schools is the centrality of teaching and learning.     

Does EFL Readers' Lexical and Grammatical Knowledge Predict Their Reading Ability? Insights From a Perceptron Artificial Neural Network Study

This study aims to examine the relationship between reading comprehension and lexical and grammatical knowledge among English as a foreign language students by using an Artificial Neural Network (ANN). There were 825 test takers administered both a second-language reading test and a set of psychometrically validated grammar and vocabulary tests. Next, their reading, grammar, and vocabulary abilities were estimated by the Rasch model. A multilayer ANN was used to classify low- and high-ability readers based on their grammar and vocabulary measures. ANN accurately classified approximately 78% of readers with reference to their vocabulary and grammar knowledge. This finding is consistent with the cognitive theories of reading that treat the lexical and grammatical knowledge of learners as a major factor in distinguishing poor from competent readers. The study also confirmed previous research in finding that vocabulary knowledge was associated with reading comprehension more strongly than grammatical knowledge.     

Electromagnetic field exposure as a plausible approach to enhance the proliferation and differentiation of mesenchymal stem cells in clinically relevant scenarios

Mesenchymal stem/stromal cell(MSC)-based therapy has been regarded as one of the most revolutionary breakthroughs in the history of modern medicine owing to its myriad of immunoregulatory and regenerative properties.With the rapid progress in the fields of osteo-and musculoskeletal therapies,the demand for MSC-based treatment modalities is becoming increasingly prominent.In this endeavor,researchers around the world have devised new and innovative techniques to support the proliferation of MSCs while minimizing the loss of hallmark features of stem cells.One such example is electromagnetic field(EMF)exposure,which is an alternative approach with promising potential.In this review,we present a critical discourse on the efficiency,practicability,and limitations of some of the relevant methods,with insurmountable evidence backing the implementation of EMF as a feasible strategy for the clinically relevant expansion of MSCs.