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The aim of this study was to examine whether, when a person reads, there is a boost to all material related to the context in Najdi Arabic (NA) as was found in English in was found in Rodd et al. (2013). The study employs Arabic language features of orthographic style and diglossia to answer the research question.

Forty-two participants were asked to come on two sessions to complete a reading task, a filler task and a word recognition task. The word recognition task included 14 homographs that could mean one thing in Modern Standard Arabic and another in NA.

The findings show that the assumption that all related materials are ready to be used when readers are exposed to the context is not valid for the two Arabic variants.

One limitation of this study was that the participants were all female.

The findings could help writers write better texts to help individuals who struggle with reading comprehension whether it is because of dyslexia, Attention Deficit Disorder (ADD) or Attention Deficit Hyperactivity Disorder (ADHD) as when researchers understand how priming works, they might be able to help readers in their reading fluency and comprehension (Rodd et al., 2016). This could be by producing better texts to comprehend or using semantic priming in classroom setups.

This paper presents a Monotonic Unbounded Schemes Transformer (MUST) approach to bound/monotonize (remove undershoots and overshoots) unbounded spatial differencing schemes automatically, and naturally. Automatically means the approach (1) captures the critical cell Peclet number when an unbounded scheme starts to produce physically unrealistic solution automatically, and (2) removes the undershoots and overshoots as part of the formulation without requiring human interventions. Naturally implies, all the terms in the discretization equation of the unbounded spatial differencing scheme are retained.

The authors do not formulate new higher-order scheme. MUST transforms an unbounded higher-order scheme into a bounded higher-order scheme.

The solutions obtained with MUST are identical to those without MUST when the cell Peclet number is smaller than the critical cell Peclet number. For cell Peclet numbers larger than the critical cell Peclet numbers, MUST sets the nodal values to the limiter value which can be derived for the problem at-hand. The authors propose a way to derive the limiter value. The authors tested MUST on the central differencing scheme, the second-order upwind differencing scheme and the QUICK differencing scheme. In all cases tested, MUST is able to (1) capture the critical cell Peclet numbers; the exact locations when overshoots and undershoots occur, and (2) limit the nodal value to the value of the limiter values. These are achieved by retaining all the discretization terms of the respective differencing schemes naturally and accomplished automatically as part of the discretization process. The authors demonstrated MUST using one-dimensional problems. Results for a two-dimensional convection–diffusion problem are shown in Appendix to show generality of MUST.

The authors present an original approach to convert any unbounded scheme to bounded scheme while retaining all the terms in the original discretization equation.