Staging with class: a specification for typed template Haskell

Multi-stage programming using typed code quotation is an established technique for writing optimizing code generators with strong type-safety guarantees. Unfortunately, quotation in Haskell interacts poorly with type classes, making it difficult to write robust multi-stage programs. We study this unsound interaction and propose a resolution, staged type class constraints, which we formalize in a source calculus λ ⇒ that elaborates into an explicit core calculus F . We show type soundness of both calculi, establishing that well-typed, well-staged source programs always elaborate to well-typed, well-staged core programs, and prove beta and eta rules for code quotations. Our design allows programmers to incorporate type classes into multi-stage programs with confidence. Although motivated by Haskell, it is also suitable as a foundation for other languages that support both overloading and quotation.

Principles of Spatial Transcriptomics Analysis: A Practical Walk-Through in Kidney Tissue

Spatial transcriptomic technologies capture genome-wide readouts across biological tissue space. Moreover, recent advances in this technology, including Slide-seqV2, have achieved spatial transcriptomic data collection at a near-single cell resolution. To-date, a repertoire of computational tools has been developed to discern cell type classes given the transcriptomic profiles of tissue coordinates. Upon applying these tools, we can explore the spatial patterns of distinct cell types and characterize how genes are spatially expressed within different cell type contexts. The kidney is one organ whose function relies upon spatially defined structures consisting of distinct cellular makeup. Thus, the application of Slide-seqV2 to kidney tissue has enabled us to elucidate spatially characteristic cellular and genetic profiles at a scale that remains largely unexplored. Here, we review spatial transcriptomic technologies, as well as computational approaches for cell type mapping and spatial cell type and transcriptomic characterizations. We take kidney tissue as an example to demonstrate how the technologies are applied, while considering the nuances of this architecturally complex tissue.

Seismic inversion with deep learning

This article investigates bypassing the inversion steps involved in a standard litho-type classification pipeline and performing the litho-type classification directly from imaged seismic data. We consider a set of deep learning methods that map the seismic data directly into litho-type classes, trained on two variants of synthetic seismic data: (i) one in which we image the seismic data using a local Radon transform to obtain angle gathers, (ii) and another in which we start from the subsurface-offset gathers, based on correlations over the seismic data. Our results indicate that this single-step approach provides a faster alternative to the established pipeline while being convincingly accurate. We observe that adding the background model as input to the deep network optimization is essential in correctly categorizing litho-types. Also, starting from the angle gathers obtained by imaging in the Radon domain is more informative than using the subsurface offset gathers as input.

The bite-type malocclusion classification – An extended Angle-method. Is the new classification reliable?

Objectives: As part in appraising the usefulness of the new bite-type method, a reliability assessment of the classification system was performed. Materials and Methods: Eighty-five selected dental casts were appraised by six operators and compared to a “Gold Standard.” The reliability of the bite-type method was assessed by double registrations of each of the nine bite-type classes by every operator. Results: An overall acceptable bite-type classification of all examiners existed. Correct assessments were found in 75–90% of the dental casts. Thus, the bite-type classification is a reliable method for categorizing sagittal malocclusions. Conclusion: The procedure could favorably replace the angle classification as it is more precise and detailed, without losing the strength of the basic angle system as an uncomplicated communication tool.

Linear Differential Equations on Some Classes of Weighted Function Spaces

Some weighted-type classes of holomorphic function spaces were introduced in the current study. Moreover, as an application of the new defined classes, the specific growth of certain entire-solutions of a linear-type differential equation by the use of concerned coefficients of certain analytic-type functions, that is the equation h(k)+Kk−1(υ)h(k−1)+…+K1(υ)h′+K0(υ)h=0, will be discussed in this current research, whereas the considered coefficients K0(υ),…,Kk−1(υ) are holomorphic in the disc ΓR={υ∈C:|υ|<R},0<R≤∞. In addition, some non-trivial specific examples are illustrated to clear the roles of the obtained results with some sharpness sense. Hence, the obtained results are strengthen to some previous interesting results from the literature.