Discrete Set Research Articles

The Impact of Digital Transformation on the Economy: Technological Innovation and Efficiency

"The investigation into the evolution of the digital economy has yielded profound insights into its fundamental nature, the pivotal drivers guiding its advancement, and the trajectories characterizing the metamorphosis of economic operations within organizations. The outcomes of this inquiry are primed to underpin the effectiveness, calibre, and dependability of information-driven and analytical underpinnings, indispensable for informed managerial judgments geared towards nurturing the inventive potential inherent in the digital economy. Furthermore, these findings address the impediments that curtail seamless digital transformation. Among the preeminent findings engendering novelty in this research, the subsequent elements stand out: the formulation of a comprehensive framework for the delineation and taxonomy of economic activities within the digital economy domain, encompassing both a classification schema for economic pursuits intrinsic to the digital sector and another for economic endeavours facilitated by the integration of digital technologies. A comprehensive array of metrics has been systematically devised to assess the evolution of the digital economy. This framework encompasses indicators derived from information and communication technology (ICT) statistics, national economic accounts, fixed asset investments, and foreign trade, as well as indicators custom-developed in consonance with the proposed taxonomy of economic pursuits within the digital economy. This classification system comprises five distinct blocks, each comprising discrete sets of indicators: those about the ICT sector, the digital sector, organizational outlays on digital technologies, digital proficiency of the workforce, and a holistic gauge of the digital economy. An intricate methodology has been formulated to quantitatively evaluate the ICT sector’s state, progression, and competitive standing. This methodological construct encompasses algorithms for the computation of physical quantities of gross value added and fixed capital investment segregated by the nature of economic undertakings associated with the production of ICT goods and provisioning ICT services. Also included are computations for the index of fixed capital formation rate, alongside indicators appraising the extent of the economy’s engagement with international trade concerning diverse digital products."

Geant4 implementation of axial channeling radiation in classical description

The progress in developing a C++ module for simulation of channeling radiation in Geant4 using classical description is being discussed. The created module is built into Geant4 as a discrete set of physical processes, which allows combining it with other physical processes of Geant4. The direct simulation of CR in Geant4 allows describing devices such as, e. g. positron sources, without using external programs for CR calculation. In previous version, the module was capable to simulate only planar channeling radiation. In this paper, the implementation of axial channeling radiation in Geant4 is shown. The module now simulates both planar and axial channeling radiation from ultra-relativistic electrons channeled in Si, C, Ge and W single crystals. The simulation results are compared with available experimental data.

Systematic identification and characterization of five transcription factors mediating the oxidative stress response in Candida albicans

Candida albicans is an opportunistic human fungal pathogen that causes superficial and systemic infections, particularly in immunocompromised individuals. In response to C. albicans infection, innate immune cells of the host produce and accumulate reactive oxygen species (ROS), which can lead to irreversible damage and apoptosis of fungal cells. Several transcription factors involved in this oxidative stress response have been identified; however, a systematic study to identify the transcription factors that mediate the oxidative stress response has not yet been conducted. Here, we screened a comprehensive transcription factor mutant library consisting of 211 transcription factor deletion mutant strains in the presence and absence of hydrogen peroxide (H2O2), a potent ROS inducer, and identified five transcription factors (Skn7, Dpb4, Cap1, Dal81, and Stp2) that are sensitive to H2O2. Genome-wide transcriptional profiling revealed that H2O2 induces a discrete set of differentially regulated genes among the five identified transcription factor mutant strains. Functional enrichment analysis identified KEGG pathways pertaining to glycolysis/gluconeogenesis, amino sugar and nucleotide sugar metabolism, and ribosome synthesis as the most enriched pathways. GO term analysis of the top common differentially expressed genes among the transcription factor mutant strains identified hexose catabolism and iron transport as the most enriched GO terms upon exposure to H2O2.This study is the first to systematically identify and characterise the transcription factors involved in the response to H2O2. Based on our transcriptional profiling results, we found that exposure to H2O2 modulates several downstream genes involved in fungal virulence. Overall, this study sheds new light on the metabolism, physiological functions, and cellular processes involved in the H2O2-induced oxidative stress response in C. albicans.

Algorithms for Right-sizing Heterogeneous Data Centers

Power consumption is a dominant and still growing cost factor in data centers. In time periods with low load, the energy consumption can be reduced by powering down unused servers. We resort to a model introduced by Lin, Wierman, Andrew, and Thereska [ 23 , 24 ] that considers data centers with identical machines and generalize it to heterogeneous data centers with d different server types. The operating cost of a server depends on its load and is modeled by an increasing, convex function for each server type. In contrast to earlier work, we consider the discrete setting, where the number of active servers must be integral. Thereby, we seek truly feasible solutions. For homogeneous data centers ( d =1), both the offline and the online problem were solved optimally in References [ 3 , 4 ]. In this article, we study heterogeneous data centers with general time-dependent operating cost functions. We develop an online algorithm based on a work function approach that achieves a competitive ratio of 2 d + 1 + ε for any ε > 0. For time-independent operating cost functions, the competitive ratio can be reduced to 2 d + 1. There is a lower bound of 2d shown in Reference [ 5 ], so our algorithm is nearly optimal. For the offline version, we give a graph-based (1+ε)-approximation algorithm. Additionally, our offline algorithm is able to handle time-variable data-center sizes.

Finite range decompositions of Gaussian fields with applications to level-set percolation

In a recent work [19], Muirhead has studied level-set percolation of (discrete or continuous) Gaussian fields, and has shown sharpness of the associated phase transition under the assumption that the field has a certain multiscale white noise decomposition, a variant of a finite-range decomposition. We show that a large class of Gaussian fields have such a white noise decomposition with optimal decay parameter. Examples include the discrete Gaussian free field, the discrete membrane model, and the mollified continuous Gaussian free field. This answers various questions from [19].Our construction of the white-noise decomposition is a refinement of Bauerschmidt's construction of a finite-range decomposition [3]. In the continuous setting our construction is very similar to Bauerschmidt's, while in the discrete setting several new ideas are needed, including the use of a result by Pólya and Szegő on polynomials that take positive values on the positive real line.

Neural structure fields with application to crystal structure autoencoders

Representing crystal structures of materials to facilitate determining them via neural networks is crucial for enabling machine-learning applications involving crystal structure estimation. Among these applications, the inverse design of materials can contribute to explore materials with desired properties without relying on luck or serendipity. Here, we propose neural structure fields (NeSF) as an accurate and practical approach for representing crystal structures using neural networks. Inspired by the concepts of vector fields in physics and implicit neural representations in computer vision, the proposed NeSF considers a crystal structure as a continuous field rather than as a discrete set of atoms. Unlike existing grid-based discretized spatial representations, the NeSF overcomes the tradeoff between spatial resolution and computational complexity and can represent any crystal structure. We propose an autoencoder of crystal structures that can recover various crystal structures, such as those of perovskite structure materials and cuprate superconductors. Extensive quantitative results demonstrate the superior performance of the NeSF compared with the existing grid-based approach.

NREL-5MW Wind Turbine Noise Prediction by FWH-LES

This paper deals with large onshore wind turbine aeroacoustics. Noise from the NREL 5 MW device is predicted by the permeable-surface Ffowcs Williams–Hawkings equation (FWH-P), starting from the postprocessing of LES data on different acoustic surfaces S. Their size and placement is aimed at embedding most of the aerodynamic sources of sound surrounding rotor and nacelle. Due to the presence of eddies that inevitably cross S, this paper compares results from open and closed acoustic surfaces, and the outflow disk averaging technique. The issues related to the interpolation process of LES data on S is discussed as well. In order to assess the LES/FWH-P aeroacoustic platform, LES and FWH-P pressures are compared in the very-near field. It is shown that, within the limits of the discretization settings imposed by the interpolation procedure and for the Reynolds number working condition investigated herein, the lack of quadrupole sources outside the permeable surface(s) deeply affect the quality of FWH-P acoustic pressures with respect to direct LES signals.

Absolutely continuous and BV-curves in 1-Wasserstein spaces

We extend the result of Lisini (Calc Var Partial Differ Equ 28:85–120, 2007) on the superposition principle for absolutely continuous curves in p-Wasserstein spaces to the special case of p=1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p=1$$\\end{document}. In contrast to the case of p>1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$p>1$$\\end{document}, it is not always possible to have lifts on absolutely continuous curves. Therefore, one needs to relax the notion of a lift by considering curves of bounded variation, or shortly BV-curves, and replace the metric speed by the total variation measure. We prove that any BV-curve in a 1-Wasserstein space can be represented by a probability measure on the space of BV-curves which encodes the total variation measure of the Wasserstein curve. In particular, when the curve is absolutely continuous, the result gives a lift concentrated on BV-curves which also characterizes the metric speed. The main theorem is then applied for the characterization of geodesics and the study of the continuity equation in a discrete setting.

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The investigation into the evolution of the digital economy has yielded profound insights into its fundamental nature, the pivotal drivers guiding its advancement, as well as the trajectories characterizing the metamorphosis of economic operations within organizations. The outcomes of this inquiry are primed to underpin the effectiveness, calibre, and dependability of information-driven and analytical underpinnings, indispensable for informed managerial judgments geared towards nurturing the inventive potential inherent in the digital economy. Furthermore, these findings aim to address the impediments that curtail seamless digital transformation. Among the preeminent findings engendering novelty in this research, the subsequent elements stand out: the formulation of a comprehensive framework for the delineation and taxonomy of economic activities within the digital economy domain, encompassing both a classification schema for economic pursuits intrinsic to the digital sector and another for economic endeavours facilitated by the integration of digital technologies. A comprehensive array of metrics has been systematically devised to assess the evolution of the digital economy. This framework encompasses a gamut of indicators derived from information and communication technology (ICT) statistics, national economic accounts, fixed asset investments, and foreign trade, as well as indicators custom-developed in consonance with the proposed taxonomy of economic pursuits within the digital economy. This classification system comprises five distinct blocks, each comprising discrete sets of indicators: those pertaining to the ICT sector, the digital sector, organizational outlays on digital technologies, digital proficiency of the workforce, and a holistic gauge of the digital economy. An intricate methodology has been formulated to quantitatively evaluate the state, progression, and competitive standing of the ICT sector. This methodological construct encompasses algorithms for the computation of physical quantities of gross value added and fixed capital investment segregated by the nature of economic undertakings associated with the production of ICT goods and provisioning of ICT services. Also included are computations for the index of fixed capital formation rate, alongside indicators appraising the extent of the economy's engagement with international trade concerning diverse digital products.

Pole-skipping of gravitational waves in the backgrounds of four-dimensional massive black holes

Pole-skipping is a property of gravitational waves dictated by their behaviour at horizons of black holes. It stems from the inability to unambiguously impose ingoing boundary conditions at the horizon at an infinite discrete set of Fourier modes. The phenomenon has been best understood, when such a description exists, in terms of dual holographic (AdS/CFT) correlation functions that take the value of ‘0/0’ at these special points. In this work, we investigate details of pole-skipping purely from the point of view of classical gravity in 4d massive black hole geometries with flat, spherical and hyperbolic horizons, and with an arbitrary cosmological constant. We show that pole-skipping points naturally fall into two categories: the algebraically special points and a set of pole-skipping points that is common to the even and odd channels of perturbations. Our analysis utilises and generalises (to arbitrary maximally symmetric horizon topology and cosmological constant) the ‘integrable’ structure of the Darboux transformations, which relate the master field equations that describe the evolution of gravitational perturbations in the two channels. Finally, we provide new insights into a number of special cases: spherical black holes, asymptotically Anti-de Sitter black branes and pole-skipping at the cosmological horizon in de Sitter space.

Concise extraction and characterization of the pore-throat network in unconventional hydrocarbon reservoirs: A new perspective

In this study, a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed. “Pore-throat solidity”, which is analogous to particle solidity, and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced. Additionally, the “pore-throat combination” and “pure pore” are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point. When the discrete grid set is recognized as a pore-throat combination, Legendre ellipse fitting and minimum Feret diameter are used. When the pore and throat grid sets are identified as pure pores, the pore diameter can be directly calculated. Using the new method, the analytical results for the physical parameters and pore radius agree well with most prior studies. The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales. The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.

Introducing the Special Series

How do sound, militarism, and ecologies relate to each other? Mindful of Jim Sykes’s criticism of a tendency in sound studies scholarship to attend to the most spectacular aspects of “wartime sound and listening,” we are particularly invested in contributions decentering “war” or, rather, showing how it is already dispersed through militarized ecologies. We seek to remain mindful of the profoundly uneven asymmetries that mark the workings, experience, spatializations, and life-and-death gradations and permutations of militarized ecologies. We do not conceive of “militarized ecologies” as a thing, as an already constituted field of inquiry or current topic, or as a discrete set of sites and sounds that can be archived, but as an invitation to consider how these auralities and terrains have come to distinguish themselves and in turn prompt proliferating interpretive gestures. How is sound central to these processes? The keywords auralities, incorporations, and terrains are not postulates but prompts, each of them registering a degree of irresolution while opening, in their juxtaposition, what we hope is room for critical vacillation.

Suppressing instability in a Vlasov–Poisson system by an external electric field through constrained optimization

Maintaining the stability and shape of a plasma is a crucial task in many technological applications ranging from beam shaping to fusion energy. This is often challenging as plasma systems tend to be naturally unstable and kinetic effects can play an important role in the behavior of the instabilities. Due to the large energies involved, the primary way to control plasma systems is the application of external electromagnetic fields.In this work, we deploy a PDE-constrained optimization formulation that uses a kinetic description for plasma dynamics as the constraint. This is to optimize, over all possible controllable external electric fields, the stability of the plasma dynamics under the condition that the Vlasov–Poisson (VP) equation is satisfied. Mathematically we formulate it as a PDE-constrained optimization. For computing the functional derivative with respect to the external field in the optimization updates, the adjoint equation is derived. Furthermore, in the discrete setting, where we employ the semi-Lagrangian method as the forward solver, we also explicitly formulate the corresponding adjoint solver and the gradient as the discrete analogy to the adjoint equation and the Fréchet derivative. A distinct feature we observed of this constrained optimization is the complex landscape of the objective function and the existence of numerous local minima, largely due to the hyperbolic nature of the VP system. To overcome this issue, we utilize a gradient-accelerated genetic algorithm, leveraging the advantages of the genetic algorithm's exploration feature to cover a broader search of the solution space and the fast local convergence aided by the gradient information. We show that our algorithm obtains good electric fields that are able to maintain a prescribed profile in a beam shaping problem and uses nonlinear effects to suppress plasma instability in a two-stream configuration.

An incremental singular value decomposition approach for large-scale spatially parallel & distributed but temporally serial data – applied to technical flows

The article presents a strategy and its algorithm to compile a simulation-accompanying, incremental Singular Value Decomposition (SVD) for time-evolving, spatially parallel discrete data sets. The framework addresses state-of-the-art PDE solvers for computational science and engineering applications. An important characteristic of such applications is that the spatial size of the data is often time-invariant and significantly exceeds the temporal size due to the large computational grid in 3D applications. Typical examples, which are also considered in this article, relate to results extracted from unsteady flow simulations. Herein, the flow data, which progresses over time, is frequently calculated spatially parallel based on domain decomposition strategies, which allow to parallelize the simulation on distributed memory machines following a Single Instruction Multiple Data (SIMD) concept.With a view to the memory-efficient reuse of (compressed) simulation results and their CPU time-saving, sufficiently accurate generation, the paper scrutinizes the efficiency of incremental/parallel SVD approaches for such simulation examples. To improve the computational efficiency, the introduction of a bunch matrix is proposed, which enables the aggregation of multiple time steps and SVD updates, and significantly increases the efficiency. The suggested strategy is verified and validated by simple 2D laminar single-phase flows and subsequently applied to more complex 2D and 3D turbulent two-phase flows. Emphasis is given to (a) the accuracy of SVD-based reconstruction, (b) the physical realizability of the reconstructed quantities, (c) the independence of domain partitioning, (d) an efficient snapshot bunching, and (e) related implementation aspects. In addition, the influence of lower and (adaptive) upper rank thresholds on the effort and accuracy is evaluated. A final application renders the practical benefits of the approach and refers to a merchant ship in head waves at Re = 1.4×107 and Fn = 0.26. The simulation involves 2880 processor cores and the related full-rank snapshot matrix has (108×104) entries. With a numerical overhead of O(10%), this snapshot matrix can be incrementally generated and compressed by O(95%). The compression is accompanied by only small errors in the integral force and local wave elevation of O(10−2%). This qualifies the method for an efficient subsequent data processing.

Maternal Group B Streptococcus Prophylaxis Improvement using an Electronic Medical Record Dynamic Order Set.

To develop and implement a Group B Streptococcal (GBS) dynamic order set to improve adherence to the American College of Obstetricians and Gynecologists/Centers for Disease Control and Prevention (ACOG/CDC) guidelines. A team of information technology and clinical experts developed a dynamic order block. The content was patterned after the CDC "Prevent GBS" mobile app. It was then embedded in the labor and delivery/induction order set and piloted at a single high-volume obstetric unit. Following the pilot and incorporation of the 2019 ACOG update of the CDC guidelines, the order set was rolled out in five additional hospitals within a region of a large health system. Information on GBS prophylaxis performance before and after implementation was available for the pilot site and four of the additional hospitals. Information before implementation was obtained electronically from electronic medical record (EMR) laboratory and pharmacy data and supplemented by manual chart review. Postimplementation data were obtained from discrete order set EMR data elements. Adherence to the guidelines before and after were compared using chi-squared test. There were 7,114 deliveries before implementation and 4,502 after implementation. Preterm delivery occurred in 6.8 and 6.9%, respectively. There was an increase in appropriate treatment of preterm patients (positive and unknown GBS) delivering after implementation (88.7-99.1%, p < 0.001). More patients were reported to have a penicillin allergy before implementation than after implementation (14.7 vs. 11.1%, respectively, p = 0.01). Associated changes in therapy noted after implementation included a nonsignificant decrease in the proportion reporting a high-risk allergy (50.3 vs. 41.9%, p = 0.18), an increase in the appropriate use of clindamycin and vancomycin (64.4 vs. 92.3%, p < 0.001) and a decrease in clindamycin use in those without sensitivity testing. Routine universal use of a dynamic admission labor/induction order set was associated with high and improved adherence to GBS prophylaxis guidelines. · Lapses in GBS prophylaxis are associated with early-onset GBS disease.. · Preterm delivery and penicillin allergic patients are commonly associated with lapses in prophylaxis.. · Dynamic EMR order set use can improve adherence to clinical guidelines..

The Clinical Significance of MicroRNAs in Colorectal Cancer Signaling Pathways: A Review.

Colorectal carcinoma (colon and rectum) is currently considered among the most prevalent malignancies of Western societies. The pathogenesis and etiological mechanisms underlying colorectal cancer (CRC) development remain complex and heterogeneous. The homeostasis and function of normal human intestinal cells is highly regulated by microRNAs. Therefore, it is not surprising that mutations and inactivation of these molecules appear to be linked with progression of colorectal tumors. Recent studies have reported significant alterations of microRNA expression in adenomas and CRCs compared with adjacent normal tissues. This observed deviation has been proposed to correlate with the progression and survival of disease as well as with choice of optimal treatment and drug resistance. MicroRNAs can adopt either oncogenic or tumor-suppressive roles during regulation of pathways that drive carcinogenesis. Typically, oncogenic microRNAs termed oncomirs, target and silence endogenous tumor-suppressor genes. On the other hand, tumor-suppressive microRNAs are critical in downregulating genes associated with cell growth and malignant capabilities. By extensively evaluating robust studies, we have emphasized and distinguished a discrete set of microRNAs that can modulate tumor progression by silencing specific driver genes crucial in signaling pathways including Wnt/b-catenin, epidermal growth factor receptor, P53, mismatch repair DNA repair, and transforming-growth factor beta.

Slip boundary condition near the wall-interface contact line in axial stratified two-phase flow

The behavior of the velocity and shear stresses in two-phase laminar stratified flow near a triple point (TP), formed in the flow cross-section by the intersection of the interface with the conduit wall, is reconsidered. Differently from the no-slip boundary condition that showed a possibility of diverging shear stresses upon approaching the TP, we allow a slip of the fluids at the wall that can be prominent in the TP region. The Navier's boundary condition is used, which considers a linear relationship between the slip velocity and the strain rate component perpendicular to the surface. The solution for the velocity field in the TP region is obtained in terms of a power series of the distance from the TP having a discrete set of powers. Similarly to the solution obtained with no-slip B.C., a so-called ‘characteristic equation’ is obtained. Its solution yields a discrete set of non-integer powers that are dependent on the dynamic viscosity ratio and the contact angle. However, contrary to the no-slip solution, with Navier's B.C, each of these powers introduces a tower of terms resulting from the relation between the slip velocity and the velocity derivative at the wall. In addition, the solution also includes a tower of integer powers. The solution yields the velocity and the shear stress fields, as well as the flux of the force per length that acts on an arbitrary surface in the flow field. The latter is obtained by considering an equivalent 2D representation of the stress tensor. These are examined in comparison to the corresponding results obtained when no-slip at the wall is imposed. The relaxation of the wall shear stresses in cases where the no-slip condition predicts diverging wall shear stresses at the TP is demonstrated. It is shown that if the local velocity in the TP region is a limit of a global no-slip solution, the scaled velocity field in the TP region is independent of the details of the global flow field.

Optimal Transport and Seismic Rays

We present a theoretical framework that links Fermat’s principle of least time to optimal transport theory via a cost function that enforces local transport. The proposed cost function captures the physical constraints inherent in wave propagation; when paired with specific mass distributions, it yields shortest paths in the considered media through the optimal transport plans. In the discrete setting, our formulation results in physically significant optimal couplings, whose off-diagonal entries identify shortest paths in both directed and undirected graphs. For undirected graphs with positive edge weights, commonly used to parameterize seismic media, our method provides solutions to the Eikonal equation consistent with those from the Dijkstra algorithm. For directed negative-weight graphs, corresponding to transportation cost matrices with negative entries, our approach aligns with the Bellman–Ford algorithm but offers considerable computational advantages. We also highlight potential research directions. These include the use of sparse cost matrices to reduce the number of unknowns and constraints in the considered transportation problem, and solving specific classes of optimal transport problems through the Dijkstra algorithm to enhance computational efficiency.

Over-the-Air Computation with Quantized CSI and Discrete Power Control Levels

In this paper, an Over-the-Air Computation (AirComp) scheme for fast data aggregation is considered. Multisource data are simultaneously transmitted by single-antenna mobile devices to a single-antenna fusion center (FC) through a wireless multiple-access channel. The optimal power levels at the devices and a postprocessing scaling function at the FC are jointly derived such that mean square error of the computation is minimized. Different than the existing approaches that rely on perfect channel state information (CSI) at the FC and assume that the devices’ optimal power levels can be selected from an infinite solution set, in the present paper, it is assumed that only quantized CSI is available at the FC and that the aforementioned optimal power levels lie in a finite discrete set of solutions. To derive the optimal power levels and FC’s scaling factor, a difficult nonconvex constrained optimization problem is formulated. An efficient and robust solution to quantization errors is developed via the deep reinforcement learning framework. Numerical results verify the good performance of the proposed approach while it exhibits a significant reduction in the required feedback.

A fault-tolerant variational quantum algorithm with limited T-depth

We propose a variational quantum eigensolver (VQE) algorithm that uses a fault-tolerant (FT) gate-set, and is hence suitable for implementation on a future error-corrected quantum computer. VQE quantum circuits are typically designed for near-term, noisy quantum devices and have continuously parameterized rotation gates as the central building block. On the other hand, an FT quantum computer (FTQC) can only implement a discrete set of logical gates, such as the so-called Clifford+T gates. We show that the energy minimization of VQE can be performed with such an FT discrete gate-set, where we use the Ross–Selinger algorithm to transpile the continuous rotation gates to the error-correctable Clifford+T gate-set. We find that there is no loss of convergence when compared to the one of parameterized circuits if an adaptive accuracy of the transpilation is used in the VQE optimization. State preparation with VQE requires only a moderate number of T-gates, depending on the system size and transpilation accuracy. We demonstrate these properties on emulators for two prototypical spin models with up to 16 qubits. This is a promising result for the integration of VQE and more generally variational algorithms in the emerging FT setting, where they can form building blocks of the general quantum algorithms that will become accessible in an FTQC.