Optimal Block Research Articles

Different peripheral nerve blocks for patients undergoing total knee arthroplasty: a network meta-analysis of randomized controlled trials.

To comprehensively compare the effect of different peripheral nerve blocks for patients undergoing total knee arthroplasty (TKA). PubMed, Embase, Cochrane Library, and Web of Science were comprehensively searched. The outcomes included postoperative pain, postoperative function, adverse events, oral morphine equivalent (OME), and perioperative indicators. Network plots, forest plots, league tables and rank probabilities were drawn for all outcomes. Totally 30 studies were included. For postoperative pain, continuous adductor canal block (cACB) + genicular nerve block (GNB) was most likely to be the most effective block regarding rest pain score at 24h; cACB + GNB was most likely to result in the lowest rest pain score at 48h; patients undergoing cACB + infiltration between the popliteal artery and the capsule of the knee (IPACK) + GNB was most likely to have the lowest motion pain score at 24h; patients undergoing cACB + GNB was most likely to have the lowest motion pain score at 48h. For postoperative function, patients undergoing cACB + IPACK + GNB had the highest likelihood to exhibit the shortest time in Timed Up and Go test (TUG); cACB + tibial nerve block (TNB) was most likely to be the most effective block in terms of range of motion (ROM); cACB + IPACK was most likely to be the optimal block concerning the ambulation distance. cACB combined with IPACK/GNB may be the most favorable block after TKA, continuous blocks may be better than single-shot blocks, and combined blocks may be better than separate blocks.

Transducer module apodization to reduce bone heating during focused ultrasound uterine fibroid ablation with phased arrays: A numerical study.

During magnetic resonance-guided focused ultrasound (MRgFUS) surgery for uterine fibroids, ablation of fibrous tissues in proximity to the hips and spine is challenging due to heating within the bone that can cause patients to experience pain and potentially damage nerves. This far-field bone heating limits the volume of fibroid tissue that is treatable viaMRgFUS. To investigate transducer module apodization for improving the ratio of focal-to-bone heating ( ) when targeting fibroid tissue close to the hips and spine, to enable MRgFUS treatments closer to thebone. Acoustic and thermal simulations were performed using 3D magnetic resonance imaging (MRI)-derived anatomies of ten patients who underwent MRgFUS ablation for uterine fibroids using a low-frequency ( ) 6144-element flat fully-populated modular phased array system (Arrayus Technologies Inc., Burlington, Canada) at our institution as part of a larger clinical trial (NCT03323905). Transducer modules ( per module) whose beams intersected with no-pass zones delineated within the field were identified, their output power levels were reduced by varying blocking percentage levels, and the resulting temperature field distributions were evaluated across multiple sonications near the hip and spine bones in each patient. Acoustic and thermal simulations took approximately ( ) and ( ) to run for a single near-spine (near-hip) target,respectively. For all simulated sonications, transducer module blocking improved compared to the no blocking case. In just over half of sonications, full module blocking maximized (increase of 82% 38% in 50% of hip targets and 49% 30% in 62% of spine targets vs. no blocking; mean±SD), at the cost of more diffuse focusing (focal heating volumes increased by 13%±13% for hip targets and 39%±27% for spine targets) and thus requiring elevated total (hip: 6%±17%, spine: 37%±17%) and peak module-wise (hip: 65%±36%, spine: 101%±56%) acoustic power levels to achieve equivalent focal heating as the no blocking control case. In the remaining sonications, partial module blocking provided further improvements in both (increased by 29%±25% in the hip and 15%±12% in the spine) and focal heating volume (decrease of 20%±10% in the hip and 34%±17% in the spine) relative to the full blocking case. The optimal blocking percentage value was dependent on the specific patient geometry and target location of interest. Although not all individual target locations saw the benefit, element-wise phase aberration corrections improved the average compared to the no correction case (increase of 52%±47% in the hip, 35%±24% in the spine) and impacted the optimal blocking percentage value. Transducer module blocking enabled ablative treatments to be carried out closer to both hip and spine without overheating or damaging the bone (no blocking: / , full blocking: / , optimal partial blocking: / for hip/spine). The proposed transducer apodization scheme shows promise for improving MRgFUS treatments of uterine fibroids, and may ultimately increase the effective treatment envelope of MRgFUS surgery in the body by enabling tissue ablation closer to bonystructures.

On the Selection of Optimal Balanced Incomplete Block Design using Different Types of Designs

The choice of selecting the best among the types of balanced incomplete block designs (BIBDs) have brought about some controversies in combinatorial design. Prominent methods of constructing BIBD have been proposed by different authors, but none has been juxtaposed the designs with respect to type. In this paper, we proposed the adoption of the concept of optimality criteria such as: A-, D-, E- , and T – optimality criterion to select the best design based on their optimality values using a (15, 15, 7, 7, 3) simulated balanced incomplete block design. A dual design, residue design and derived design were selected as the major three types of BIBDs for investigation. The findings revealed that dual design is the best balanced incomplete block design based on its high optimal value. We discovered that residue and derived design obtained from the simulated balanced incomplete block design by method of block selection and intersection becomes a standard balanced incomplete block design.

Suitable material design of temperature-stabilizing device using phase change materials for electric power supply of nanosatellites

This study proposes a new passive thermal-control device utilizing phase-change materials (PCMs) that require minimal active thermal support, such as heaters, to achieve a high-performance and high-reliability power supply for nanosatellites and other space applications. This study evaluated two different PCMs as candidate materials for the device and compares their performances as thermal control devices. One was a solid–solid PCM based on vanadium dioxide doped with tungsten (VWO2), and the other was a microencapsulated PCM containing n-paraffin (NPH-MPCM). For integration into nanosatellites, it is essential to form a PCM as solid blocks. This report adopted a solidification method using epoxy resin (EP) as the binder and determined the optimal block composition for each PCM. The thermal-insulation properties of both PCM blocks in vacuum and low-temperature environments were evaluated and found to be almost equivalent. Considering that the latent heat of VWO2 is only approximately one-fifth that of NPH-MPCM, the practical application of VWO2 as a PCM was demonstrated. Furthermore, VWO2 exhibits a phase-change temperature hysteresis of 4 °C, which is significantly smaller than the 23 °C of NPH-MPCM. This characteristic is expected to help maintain a more constant temperature for power supplies in earth-orbiting micro/nanosatellites. Moreover, lithium-ion battery cells were incorporated into both VWO2-based and NPH-MPCM-based PCM blocks, and their charge–discharge behaviors were evaluated. Only the VWO2-based PCM block could maintain appropriate temperatures to ensure stable charge–discharge operation. Vacuum resistance results suggested that the VWO2-based PCM block is well-suited as a temperature-stabilizing device for electric power supplies in nanosatellites.

Histo-pillar strip for optimal histogel block construction and biomarker analysis in 3D-lung cancer patient-derived organoids

This study proposed an optimized histogel construction method for histological analysis by applying lung cancer patient-derived organoids (PDOs) to the developed histo-pillar strip. Previously, there is the cultured PDOs damage problem during the histogel construction due to forced detachment of the Matrigel spots from the 96-well plate bottom. To address this issue, we cultured PDO on the proposed Histo-pillar strips and then immersed them in 4% paraformaldehyde fixation solution to self-isolate PDO without damage. The 4μl patient-derived cell (PDC)/Matrigel mixtures were dispensed on the surface of a U-shaped histo-pillar strip, and the PDCs were aggregated by gravity and cultured into PDOs. Cultured PDOs were self-detached by simply immersing them in a paraformaldehyde fixing solution without physical processing, showing about two times higher cell recovery rate than conventional method. In addition, we proposed a method for embedding PDOs under conditions where the histogel temperature was maintained such that the histogel did not harden, thereby improving the problem of damaging the histogel block in the conventional sandwich histogel construction method. We performed histological and genotyping analyses using tumor tissues and PDOs from two patients with lung adenocarcinoma. Therefore, the PDO culture and improved histogel block construction method using the histo-pillar strip proposed in this study can be employed as useful tools for the histological analysis of a limited number of PDCs.

Synthesis of linear chitosan-block-dextran copolysaccharides with dihydrazide and dioxyamine linkers

Dihydrazide (ADH) and dioxyamine (PDHA) were assessed for their efficacy in coupling chitosan and dextran via their reducing ends. Initially, the end-functionalization of the individual polysaccharide blocks was investigated. Under non-reducing conditions, chitosan with a 2,5-anhydro-D-mannose unit at its reducing end exhibited high reactivity with both PDHA and ADH. Dextran, with a normal reducing end, showed superior reactivity with PDHA compared to ADH, although complete conversion with ADH could be achieved under reductive conditions with NaBH3CN. Importantly, the oxime bond in PDHA conjugates exhibited greater stability against hydrolysis compared to the hydrazone bond in ADH conjugates. The optimal block coupling method consisted in reacting chitosan with an excess of dextran pre-functionalized with PDHA. The copolysaccharides could be synthesized in high yields under both reducing and non-reducing conditions. This methodology was applied to relatively long polysaccharide blocks with molecular weight up to 14,000 g/mol for chitosan and up to 40,000 g/mol for dextran. Surprisingly, block copolysaccharides did not self-assemble at neutral or basic pH; rather, they precipitated due to hydrogen bonding between neutralized amino groups of chitosan. However, nanoparticles could be obtained through a nanoprecipitation approach.

Freshness-in-air: An AoI-inspired UAV-assisted wireless sensor networks

The Age-of-Information (AoI) metric has emerged as a performance measurement metric for evaluating time-sensitive wireless communications systems. Maintaining the freshness and reliability of data is critical in time-critical wireless networks, where outdated information can have significant consequences. Moreover, short packet transmissions are used in wireless sensor networks (WSNs) to maintain energy efficiency and low latency. This paper proposes a theoretical model that utilizes the AoI metric and finite block length information theory to estimate information freshness in an unmanned aerial vehicle (UAV)-assisted WSN. This network includes multiple sensing nodes and relies on short-packet communication for transmission. In this paper, closed-form expressions for average AoI (AAoI) and the block error rate are derived. Furthermore, the optimal altitude and block length that ensures the freshness of received information at the destination is determined. The results of the analysis provide valuable insights into the performance characteristics of UAV-assisted WSNs and have important implications for the design and optimization of such systems.

INCEPTION SH: A NEW CNN MODEL BASED ON INCEPTION MODULE FOR CLASSIFYING SCENE IMAGES

In this study, a light-weight model with an optimum block structure that can be used in autonomous unmanned aerial vehicles (UAVs) was designed. The Inception SH model, which was developed based on the Inception V3 model, was compared on "Intel Image Dataset", a publicly available dataset in the literature. As a result of the comparison, values of 0.882, 0.883, 0.882 and 0.882 were obtained for the accuracy, precision, recall, and F1 score metrics for the Inception V3 model, respectively. In the Inception SH model, values of 0.958, 0.957, 0.974 and 0.967 were obtained for accuracy, precision, recall and F1 score metrics, respectively. As can be seen from these values, the proposed Inception SH model offers higher performance values than the underlying Inception V3 model. The Inception SH model was compared with different models in the literature using the same data set and was superior in accuracy, precision, recall and F1 score metrics compared to the compared models. According to the results obtained, it is predicted that the Inception SH model can be used as a lightweight model in various IoT devices, considering the popularity of autonomous UAVs.

3D deformation analysis for earth dam monitoring based on terrestrial laser scanning (TLS) and the iterative closest point (ICP) algorithm

Introduction: The conventional 3-D point cloud-based deformation analysis methods, such as the shortest distance (SD), cloud-to-cloud (C2C), and multiscale model-to-model cloud comparison (M3C2), essentially regard the closest distance between two periods of point cloud data as the deformation, rather than the true position of the same point in 3-D space before and after deformation.Methods: This paper proposes a method based on the ICP algorithm to calculate the differences between the chunked multi-period point clouds to recognizes the 3-D deformations.Results and discussion: The results show that the obtained results are very close to the GNSS data but with a much larger spatial monitoring range. The accuracy is higher than that of the SD method. Moreover, we analyze the statistical relationship between the point cloud block size and the deformation vector error and determine the optimal block size. The aim of this article is to optimize the deformation analysis method and improve its accuracy to provide techniques and ideas for the wider surface deformation monitoring research field. For instance, combining this method with data from contact methods constructs a 3D overall deformation model of the mountain, enabling real-time monitoring and early warning of debris flows.

Impact of blocking layers based on TiO2 and ZnO prepared via direct current reactive magnetron sputtering on DSSC solar cells

The optimization of dye-sensitized solar cells (DSSCs) technology towards suppressing charge recombination between the contact and the electron transport layer is a key factor in achieving high conversion efficiency and the successful commercialization of this type of product. An important aspect of the DSSC structure is the front blocking layer (BL): optimizing this component may increase the efficiency of photoelectron transfer from the dye to the semiconductor by reduction charge recombination at the TiO2/electrolyte and FTO/electrolyte interfaces. In this paper, a series of blocking layer variants, based on TiO2 and ZnO:TiO2, were obtained using the reactive magnetron sputtering method. Material composition, structure and layer thickness were referred to each process parameters. Complete DSSCs with structure FTO/BL/m-TiO2@N719/ EL-HSE/Pt/FTO were obtained on such bases. In the final results, verification of opto-electrical parameters of these cells were tested and used for the conclusions on the optimal blocking layer composition. As the conclusion, application of blocking layer consists of neat TiO2 resulted in improvement of device efficiency. It should be noted that for TiO2:ZnO/CuxO and TiO2/CuxO cells, higher efficiencies were also achieved when pure TiO2 was used as window layer. Additionally it was proven that the admixture of ZnO phase inspires Voc and FF growth, but is overall unfavorable compared to pristine TiO2 blocking layer and the reference cell, according to the final cell efficiency.

Construction of trend-free optimal block designs under some correlation structures

Construction of trend-free optimal block designs under some correlation structures

SWattention: designing fast and memory-efficient attention for a new Sunway Supercomputer

In the past few years, Transformer-based large language models (LLM) have become the dominant technology in a series of applications. To scale up the sequence length of the Transformer, FlashAttention is proposed to compute exact attention with reduced memory requirements and faster execution. However, implementing the FlashAttention algorithm on the new generation Sunway Supercomputer faces many constraints such as the unique heterogeneous architecture and the limited memory bandwidth. This work proposes SWattention, a highly efficient method for computing the exact attention on the SW26010pro processor. To fully utilize the 6 core groups (CG) and 64 cores per CG on the processor, we design a two-level parallel task partition strategy. Asynchronous memory access is employed to ensure that memory access overlaps with computation. Additionally, a tiling strategy is introduced to determine optimal SRAM block sizes. Compared with the standard attention, SWattention achieves around 2.0x speedup for FP32 training and 2.5x speedup for mixed-precision training. The sequence lengths range from 1k to 8k and scale up to 16k without being out of memory. As for the end-to-end performance, SWattention achieves up to 1.26x speedup for training GPT-style models, which demonstrates that SWattention enables longer sequence length for LLM training.

Low-carbon-oriented commercial district urban form optimization and impact assessment analysis

Commercial buildings have become one of the main sources of carbon emissions. However, the current research on urban form optimization has lacked analyses of the low-carbon indicators of buildings. With the Beijing commercial district as an example, a low-carbon-oriented urban form optimization path is established in this study, and a new method of urban form optimization is developed from a low-carbon perspective. With the help of the parametric platform and multiobjective optimization algorithm, a dynamic optimization model of urban morphology based on parametric modeling, numerical simulation and algorithm optimization is developed, and the morphological characteristics of low-carbon commercial blocks in Beijing are assessed with a Pareto-optimal solution set. Through principal component regression analysis, the correlations between urban form factors and low-carbon evaluation indicators are discussed. The study shows that the multiobjective optimization algorithm effectively optimizes the low-carbon indicators of buildings at the block scale. The urban forms obtained from the Pareto solution set display several commonalities reflected from three perspectives: building type, vertical dimension and building orientation. It is found that the optimal block layout form reduces the building carbon emission intensity and the building outer skin radiation difference, and the renewable energy-based carbon reduction is large. The urban form factors that have a significant impact on the carbon emission intensity of buildings include the maintenance coefficients, the average area to perimeter ratio, and the sky view factor, with respective impact coefficients of 0.301, −0.309, and −0.319.

Optimizacija i projektiranje novog energetski učinkovitog betonskog samoizolirajućeg bloka

This study was designed to satisfy the requirements of energy-saving insulation blocks in severely cold regions, with the thermal and mechanical properties and bulk density comprehensively optimised. An optimal block type was obtained, with the necessary parameters provided and further suggestions for improvement proposed. This study investigated the preparation process and material properties of a new energy-saving self-insulation block. Additionally, both thermal performance and compression tests were designed and conducted on the wall, with the compression performance of the brick and the shear resistance of the wall experimentally studied and optimised using ANSYS.

Transducer module apodization for reducing bone heating during focused ultrasound uterine fibroid ablation

During MR-guided focused ultrasound (MRgFUS) for uterine fibroids, thermoablation of tissue near spine/hips is challenging due to bone heating that can cause patient pain and potentially damage nerves. Here we investigate transducer module apodization for maximizing the focal-to-bone heating ratio (ΔT ;ratio) in silico using a 6144-element flat fully populated phased array operating at 0.5 MHz (Arrayus Technologies, Inc.). Acoustic and thermal simulations were performed using anatomies of ten patients who underwent MRgFUS ablation for uterine fibroids with this device as part of a clinical trial (NCT03323905). Transducer modules (64 elements/module) whose beams intersected no-pass regions were identified, their amplitudes were reduced by varying blocking percentage levels, and the resulting temperature field distributions were evaluated across multiple sonications per patient. For all simulated sonications transducer module blocking improved ΔT ;ratio compared to no blocking. In 42% of sonications, full module blocking maximized ΔT ;ratio, with mean improvements of 97% ± 55% and 47% ± 36% in hip and spine compared to no blocking, at the cost of increased focal thermal volumes and acoustic power levels. In the remaining sonications, partial module blocking provided increased ΔT ;ratio values (39% ± 45% in hip, 19% ± 15% in spine targets) relative to full blocking. The optimal blocking percentage varied depending on the specific treatment geometry.

Massively parallel implementation of iterative eigensolvers in large-scale plane-wave density functional theory

The Kohn-sham density functional theory (DFT) is a powerful method to describe the electronic structures of molecules and solids in condensed matter physics, computational chemistry and materials science. However, large and accurate DFT calculations within plane waves process a cubic-scaling computational complexity, which is usually limited by expensive computation and communication costs. The rapid development of high performance computing (HPC) on leadership supercomputers brings new opportunities for developing plane-wave DFT calculations for large-scale systems. Here, we implement parallel iterative eigensolvers in large-scale plane-wave DFT calculations, including Davidson, locally optimal block preconditioned conjugate gradient (LOBPCG), projected preconditioned conjugate gradient (PPCG) and the Chebyshev subspace iteration (CheFSI) algorithms, and analyze the performance of these algorithms in massively parallel plane-wave computing tasks. We adopt a two-level parallelization strategy that combines the message passing interface (MPI) with open multi-processing (OpenMP) parallel programming to handle data exchange and matrix operations in the construction and diagonalization of large-scale Hamiltonian matrix within plane waves. Numerical results illustrate that these iterative eigensolvers can scale up to 42,592 processing cores with high peak performance of 30% on leadship supercomputers to study the electronic structures of bulk silicon systems containing 10,648 atoms. Program summaryProgram Title: Plane wave density functional theory (PWDFT)CPC Library link to program files:https://doi.org/10.17632/c8v2mx5vn4.1Developer's repository link:https://bitbucket.org/berkeleylab/scalesLicensing provisions: BSD 3-clauseProgramming language: C++Nature of problem: PWDFT is used for electronic structure calculations based on Kohn-Sham density functional theory. The key challenge to address is a constrained energy minimization problem, which can also be formulated as a nonlinear eigenvalue problem. MPI/OpenMP-based approaches are employed to provide multi-core acceleration for the study of the chemical and material properties of larger-scale molecules and solids.Solution method: PWDFT implements self-consistent field (SCF) iterations and direct constrained minimization algorithms with various acceleration strategies. It is written in C++ and offers parallel acceleration based on MPI/OpenMP.

Fully automated chemiluminescence microarray immunoassay for detection of antinuclear antibodies in systemic autoimmune rheumatic diseases

Abstract Objectives Detection of specific antinuclear antibodies is very important in term of diagnosis, prognosis and management of patients with systemic autoimmune rheumatic diseases. Chemiluminescence microarray immunoassay (CLMIA) is a microdot array-based method that allows simultaneous detection of multiple antinuclear antibodies, which received increasing attention. Methods A CLMIA method that can detect 14 kinds of antinuclear antibodies was established and optimized. Basic performance and diagnostic performance of CLMIA was evaluated by comparing it with line immunoassay (LIA) and indirect immunofluorescence (IIF). Results Through conditional exploration, the optimal blocking time and blocking temperature were determined to be 18 h and 25 °C, respectively. The enzyme-labeled secondary antibody reaction concentration was 0.1 μg/mL, the incubation temperature of serum and enzyme-labeled secondary antibody were 30 °C, and the incubation time of serum and enzyme-labeled secondary antibody were 40 min. After parameter optimization, CLMIA demonstrated high accuracy with a relative bias <15 %; high sensitivity with detection limits below 3 IU/mL for dsDNA and below 1 RU/mL for other ANAs; and high reproducibility with both intra-assay and inter-assay coefficients of variation (CV) <15 %.The CLMIA detection method established in this study was also demonstrated to have good clinical diagnostic performance, showing the highest area under curve (AUC=0.87, p=0.042 and p=0.03). The CLMIA and LIA revealed substantial to good agreements on specific antinuclear antibodies except anti-dsDNA, with the Cohen’s kappa from 0.72 to 0.89. Samples that produced discrepant results between the CLMIA and LIA methods were further analyzed. Upon additional testing, most of these samples were ultimately determined to have been correctly detected by the CLMIA assay rather than the LIA assay, suggesting that CLMIA also shows some superiority in diagnosing dsDNA. Conclusions The CLMIA could become a potential routine method for detecting ANAs with the advantages of good detection performance.

Trans-reflective tunable color filter using electro-optic material

This research presents designing a tunable trans-reflective color filter utilizing Barium Titanate (BTO) and optimizing its performance by applying an artificial intelligence (AI) based inverse design model. The AI-based color filter design process is efficient and minimizes design challenges. The AI model comprising two sub-blocks is trained using a dataset that correlates geometrical parameters, refractive index, and input voltage variations with desired color outputs to precisely control the color filter's performance. The first is the parametric optimization block (POB), which employs two deep neural networks (DNNs) in the forward and inverse directions to achieve the optimized geometry of the proposed meta-atoms. Once the optimal parameters are completed, the next block, i.e., voltage tuning block (VTB), is employed to map specific colors onto the refractive index and the applied voltage of the BTO layer. In this way, by changing the voltage of the BTO layer, we can leverage BTO's tunable optical properties, which allow for a broad range of vibrant and customizable colors. The optimized color filter demonstrates enhanced tunability and efficiency, opening up new possibilities for applications in displays and imaging devices.

Update of [formula omitted]: Newly added functions and methods in versions 2 and 3

HΦ [aitch-phi] is an open-source software package of numerically exact and stochastic calculations for a wide range of quantum many-body systems. In this paper, we present the newly added functions and the implemented methods in vers. 2 and 3. In ver. 2, we implement spectrum calculations by the shifted Krylov method, and low-energy excited state calculations by the locally optimal block preconditioned conjugate gradient (LOBPCG) method. In ver. 3, we implement the full diagonalization method using ScaLAPACK and GPGPU computing via MAGMA. We also implement a real-time evolution method and the canonical thermal pure quantum (cTPQ) state method for finite-temperature calculations. The Wannier90 format for specifying the Hamiltonians is also implemented. Using the Wannier90 format, it is possible to perform the calculations for the abinitio low-energy effective Hamiltonians of solids obtained by the open-source software RESPACK. We also update Standard mode—simplified input format in HΦ—to use these functions and methods. We explain the basics of the implemented methods and how to use them. Program summaryProgram Title:HΦ [aitch-phi]CPC Library link to program files:https://doi.org/10.17632/vnfthtyctm.2Developer's repository link:https://github.com/issp-center-dev/HPhiLicensing provisions: GPLv3Programming language: C, FortranJournal reference of previous version: Comput. Phys. Commun. 217 (2017) 180–192Does the new version supersede the previous version?: Yes. The latest version has compatibility with the old versions. Although most functions are available in newer versions, some redundant/unnecessary functions were abolished in newer versions.Reasons for the new version: Implementation of new functions and methods, development of utilities, and bug fixes.Summary of revisions: We added new functions to obtain excited spectrum, low-energy excited states, and time-dependent physical quantities. We also implemented the full diagonalization method by using MAGMA on GPGPUs and finite-temperature simulations by using the canonical thermal pure quantum state method. In addition, we developed utilities for connection with RESPACK and a submodule for a generator of input files.Nature of problem: Physical properties in quantum lattice models with finite system sizesSolution method: In HΦ, we implemented several numerical methods such as the Lanczos method, the full diagonalization method, the locally optimal block preconditioned conjugate gradient (LOBPCG) method, the real-time evolution method based on the Taylor expansion, the shifted Krylov method, and the microcanonical/canonical thermal pure quantum state method.

Efficient and reliable divergence-conforming methods for an elasticity-poroelasticity interface problem

We present a finite element discretization to model the interaction between a poroelastic structure and an elastic medium. The consolidation problem considers fully coupled deformations across an interface, ensuring continuity of displacement and total traction, as well as no-flux for the fluid phase. Our formulation of the poroelasticity equations incorporates displacement, fluid pressure, and total pressure, while the elasticity equations adopt a displacement-pressure formulation. Notably, the transmission conditions at the interface are enforced without the need for Lagrange multipliers. We demonstrate the stability and convergence of the divergence-conforming finite element method across various polynomial degrees. The a priori error bounds remain robust, even when considering large variations in intricate model parameters such as Lamé constants, permeability, and storativity coefficient. To enhance computational efficiency and reliability, we develop residual-based a posteriori error estimators that are independent of the aforementioned coefficients. Additionally, we devise parameter-robust and optimal block diagonal preconditioners. Through numerical examples, including adaptive scenarios, we illustrate the scheme's properties such as convergence and parameter robustness.