Direct Integration Research Articles

Perturbative QCD meets phase quenching: The pressure of cold quark matter

Nonperturbative inequalities constrain the thermodynamic pressure of quantum chromodynamics (QCD) with its phase-quenched version, a sign-problem-free theory amenable to lattice treatment. In the perturbative regime with a small QCD coupling constant αs, one of these inequalities manifests as an O(αs3) difference between the phase-quenched and QCD pressures at large baryon chemical potential. In this work, we generalize state-of-the-art algorithmic techniques used in collider physics to address large-scale multiloop computations at finite chemical potential, by direct numerical integration of Feynman diagrams in momentum space. Using this novel approach, we evaluate this O(αs3) difference and show that it is a gauge-independent and small positive number compared to the known perturbative coefficients at this order. This implies that at high baryon densities, phase-quenched lattice simulations can provide a complementary nonperturbative method for accurately determining the pressure of cold quark matter at O(αs3). Published by the American Physical Society 2024

A study of self-similar vector fields in bianchi type III spacetime via Rif tree approach

Abstract In this study, we use the Rif tree approach to explore self-similar vector fields in Bianchi type III spacetime. This work adopt a computer-based method to transform symmetry equations into an involutive form that is simplified and divides the integration problem into multiple cases, each represented as a tree structure. In some cases, the metric functions are subject to particular constraints. These conditions allow one to solve the system of equations governing self-similar symmetries and provide explicit formulations for the metrics and their corresponding self-similar vector fields. This approach is novel in that it covers not only the analysis of the direct integration strategy but also some metrics that are practically relevant. For a detailed investigation of the created models, stability and physical importance are also considered.

Stretchable and High-Performance Fibrous Sensors Based on Ionic Capacitive Sensing for Wearable Healthcare Monitoring.

Electronic textiles with remarkable breathability, lightweight, and comfort hold great potential in wearable technologies and smart human-machine interfaces. Ionic capacitive sensors, leveraging the advantages of the electric double layer, offer higher sensitivity compared to traditional capacitive sensors. Current research on wearable ion-capacitive sensors has focused mainly on two-dimensional (2D) or three-dimensional (3D) device architectures, which show substantial challenges for direct integration with textiles and compromise their wearing experience on conformability and permeability. One-dimensional (1D) stretchable fiber materials serve as vital components in constructing electronic textiles, allowing for rich structural design, patterning, and device integration through mature textile techniques. Here, a stretchable functional fiber with robust mechanical and electrical performances is fabricated based on semi-solid metal and ionic polymer, which provided a high stretchability and good electrical conductivity, enabling seamless integration with textiles. Consequently, high-performance stretchable fiber sensors are developed through different device architecture designs, including pressure sensors with high sensitivity (7.21kPa-1), fast response (60ms/30ms), and excellent stability, as well as strain sensors with high sensitivity (GF = 1.05), wide detection range (0-300% strain), and excellent sensing stability under dynamic deformations.

An Efficient Analysis of Amplitude and Phase Dynamics in Networked MEMS-Colpitts Oscillators

Abstract This paper explores the interactions of both phase and amplitude in a network of N MEMS-Colpitts oscillators that are resistively coupled. The numerical simulations of the extensive networks of oscillators, required for emerging applications such as clock synchronization and neuromorphic computing, become computationally prohibitive as the number of oscillators increases. This complicates the design and evaluation of such systems, as understanding the effects of changes in coupling and design parameters can require many simulations. This study employs the method of multiple scales (MS) in combination with the harmonic balance method to convert the coupled differential equations governing the system of oscillators into a set of nonlinear evolution equations for the amplitude and phase of the oscillators. The amplitude and phase evolve on a timescale that is slow, commensurate with the damping in the system, compared with the fast timescale of the oscillation frequencies. The approach used in this study to describe the amplitude and phase dynamics offers significant computational efficiency (gains of 10× to 50× are shown) compared to direct numerical integration while maintaining an accurate representation of the response. The results of the presented simulations demonstrate the effect of coupling strength on the dynamics of the network, accounting for both phase and amplitude dynamics.

Optimizing Agricultural and Construction Tool Usage through Android Devices A Comprehensive Survey

An all-encompassing rental and booking platform for agricultural tools and construction tools designed to revolutionize the workflow in the agricultural sector and construction sector respectively. It is a versatile tool of central application that will bridge the gap between demand of tools and its supply. This will help the owners to effectively run their farm-lands. Providers will keep inventory for the tools and implementation of tool allotment. When customers don’t find the tools that they need in the current inventory they may purchase those from hardware shops. In that situation, the customers can buy tools from the selected hardware shops connected with the site by direct integration with the site owner’s shop. Real-time online tool availability checks and vendor invoice generation are required in this process when clients want to buy. A flexible communication system that can be developed as an application to facilitate customer communication directly with suppliers, which will be considerably more convenient than the conventional approaches and will remove the above.

Diverse general solitary wave solutions and conserved currents of a generalized geophysical Korteweg–de Vries model with nonlinear power law in ocean science

This article presents an analytical investigation performed on a generalized geophysical Korteweg–de Vries model with nonlinear power law in ocean science. To start with, achieving diverse solitary wave solutions to the generalized power‐law model involves using wave transformation, which reduces the model to a nonlinear ordinary differential equation. A direct integration approach is adopted to construct solutions in the beginning. This brings the emergence of interesting solutions like non‐topological solitons, trigonometric functions, exponential functions, elliptic functions, and Weierstrass functions in general structures. Besides, in a bid to secure more general exact solutions to the model, one adopts the extended Jacobi elliptic function expansion technique (for some specific cases of ). Thus, various cnoidal, snoidal, and dnoidal wave solutions to the understudied model are attained. The copolar trio explicated in a tabular form reveals that these solutions can be relapsed to various hyperbolic and trigonometric functions under certain criteria. Additionally, diverse graphical exhibitions of the dynamical attributes of the gained results are presented in a bid to have a sound understanding of the physical phenomena of the underlying model. Later, one gives the conserved vectors of the aforementioned equation by employing the standard multiplier approach.

Engineering Epitaxial Interfaces for Topological Insulator — Superconductor Hybrid Devices with Al Electrodes

AbstractProximity‐induced superconductivity in hybrid devices of topological insulators and superconductors offers a promising platform for the pursuit of elusive topological superconductivity and its anticipated applications, such as fault‐tolerant quantum computing. To study and harness such hybrid devices, a key challenge is the realization of highly functional material interfaces with a suitable superconductor featuring 2‐periodic parity‐conserving transport to ensure a superconducting hard‐gap free of unpaired electrons, which is important for Majorana physics. A superconductor well‐known for this characteristic is Al, however, its direct integration into devices based on tetradymite topological insulators has so far been found to yield non‐transparent interfaces. By focusing on Bi2Te3‐Al heterostructures, this study identifies detrimental interdiffusion processes at the interface through atomically resolved structural and chemical analysis, and showcases their mitigation by leveraging different interlayers – namely Nb, Ti, Pd, and Pt – between Bi2Te3 and Al. Through structural transformation of the interlayer materials (X) into their respective tellurides (XTe2) atomically‐sharp epitaxial interfaces are engineered and further characterized in low‐temperature transport experiments on Al‐X‐Bi2Te3‐X‐Al Josephson junctions and in complementary density functional theory calculations. By demonstrating functional interfaces between Bi2Te3 and Al, this work provides key insights and paves the way for the next generation of sophisticated topological devices.

A Comparison of Medical Education Policies in Japan and Singapore with a Focus on Governance: Implications for Korea

Among Asian nations, Japan, Singapore, and South Korea exemplify countries with high standards of medical quality. This review explores the differences in medical education policies between Japan and Singapore, particularly concerning governance, and discusses the implications for South Korea’s medical education policies. Relevant documents were analyzed by referencing scholarly articles and data from governmental and expert organizations in each country. In Japan, advances in medical education policies include initiatives such as the regional quota system and the core curriculum model, which emphasize stakeholder engagement and transparency. However, challenges persist due to limited stakeholder participation, necessitating a transition toward a more equitable governance paradigm. Singapore’s model features robust public-private partnerships with minimal direct governmental intervention, emphasizing innovation and community integration, as seen in the Healthier SG project. These case studies demonstrate effective governance involving significant stakeholder collaboration and strategic financial investments. Conversely, South Korea’s medical education policies face challenges from a predominantly government-centric approach, with an absence of cohesive governance structures and inadequate involvement from essential professional stakeholders. This situation has led to policy inconsistencies and a deficit of strategic direction, exacerbated by insufficient financial support for educational infrastructure and program development. The experiences of Japan and Singapore indicate that it would be beneficial for South Korea to adopt integrated governance frameworks that prioritize transparency and collaboration. Furthermore, increasing financial investment in medical education could mitigate existing deficiencies and improve the quality and effectiveness of its healthcare education system.

Full‐Spectrum Light‐Harvesting Solar Thermal Electrocatalyst Boosts Oxygen Evolution

AbstractEnabling high‐efficiency solar thermal conversion (STC) at catalytic active site is critical but challenging for harnessing solar energy to boost catalytic reactions. Herein, we report the direct integration of full‐spectrum STC and high electrocatalytic oxygen evolution activity by fabricating a hierarchical nanocage architecture composed of graphene‐encapsulated CoNi nanoparticle. This catalyst exhibits a near‐complete 98 % absorptivity of solar spectrum and a high STC efficiency of 97 %, which is superior than previous solar thermal catalytic materials. It delivers a remarkable potential decrease of over 240 mV at various current densities for electrocatalytic oxygen evolution under solar illumination, which is practically unachievable via traditionally heating the system. The high‐efficiency STC is enabled by a synergy between the regulated electronic structure of graphene via CoNi‐carbon interaction and the multiple absorption of lights by the light‐trapping nanocage. Theoretical calculations suggest that high temperature‐induced vibrational free energy gain promotes the potential‐limiting *O to *OOH step, which decreases the overpotential for oxygen evolution.

A block-based numerical strategy for modeling the dynamic out-of-plane behavior of unreinforced brick masonry walls

AbstractIn this paper, a numerical procedure is proposed to simulate the dynamic out-of-plane response of unreinforced masonry (URM) walls. A state-of-the-art damaging block-based model, originally developed for quasi-static simulations, is extended for the first time in a dynamic regime. The blocks are represented using solid 3D finite elements governed by a plastic-damage constitutive law for both tension and compression. A cohesive-frictional contact-based formulation is used to account for interactions between the blocks. A simplified mechanical characterization is formulated to improve efficiency in wall-level analyses. Dynamic simulation is performed using a generalized HHT-$$\alpha$$ α direct integration implicit solver and by implementing Rayleigh damping in the bulk. Such consideration allows the use of both mass and stiffness proportional terms of the Rayleigh damping without compromising efficiency. The strategy is applied to simulate incremental dynamic experiments performed on full-scale walls, showing good agreement between numerical and experimental results. The calibrated numerical model is then optimized to reduce computational effort while maintaining accuracy. The optimized model is used to investigate the effect of relative support motion on the one-way bending out-of-plane seismic response of URM walls, demonstrating the potential of the modeling strategy to explore the effect of boundary conditions that occur in real buildings but are often overlooked in laboratory experiments. This investigation also explores the adequacy of simplifications in capturing the effect of relative support motion, which can be adopted for simple modeling strategies commonly used in standard engineering practice.

Analytical evaluation of the elastic stresses in a multilayer spherical pressure vessel

An explicit-form solution is constructed for a problem on elastic deformation of a multilayer spherical vessel due to uniform internal pressure. The vessel is assembled of perfectly connected elastic layers whose material properties may arbitrarily vary across their thickness. The solution is constructed through the use of the single solid approach along with the modified scheme of the direct integration method which allow for the consideration of the multilayer vessel as a composite sphere with piecewise-variable profiles of the material properties. As a result, the original problem is reduced to solving a governing integral equation of the second kind whose solution is constructed in the form of the explicit dependence on the internal pressure. The solution is verified by the comparison with exact solutions derived by making use the method of tailored solutions for specific benchmark problems. By comparing our with the one for a functionally-graded sphere, whose material properties are evaluated through the use of the micromodular homogenization technique, the specific features of the circumferential stress are analyzed.

Investigation of nonlinear dynamic behaviors of vertical rotor system supported by aerostatic bearings

Abstract A common issue associated with gas bearing-rotor systems is the tendency to generate self-excited vibrations, leading to instability. To address this problem, the fluid-structure coupling model of an aerostatic bearing-rotor system is established in this paper. Then a hybrid method combining the finite difference method and direct integration method, is employed to solve the bearing lubrication equation and rotor motion equation simultaneously. Furthermore, based on the orbit of rotor center,frequency spectrum diagram, Poincaré map, waterfall diagram and bifurcation diagram, the effects of rotational speed, rotor mass, orifice diameter and nominal clearance on the nonlinear dynamic behaviors of the bearing-rotor system are investigated. The results indicate that the system exhibits rich nonlinear behaviors with increasing rotational speed and rotor mass, including the occurrence of typical half-speed whirl. However, the nonlinear vibrations of the system can be restricted by selecting appropriate bearing structural parameters, providing theoretical guidance for the design of aerostatic bearing-rotor systems.

Ultra‐Thin Strain‐Relieving Si1−xGex Layers Enabling III‐V Epitaxy on Si

AbstractThe explosion of artificial intelligence, the possible end of Moore's law, dawn of quantum computing, and the continued exponential growth of data communications traffic have brought new urgency to the need for laser integration on the diversified Si platform. While diode lasers on group III‐V platforms have long‐powered internet data communications and other optoelectronic technologies, direct integration with Si remains problematic. A paradigm‐shifting solution requires exploring new and unconventional materials and integration approaches. In this work, it is shown that a sub‐10‐nm ultra‐thin Si1−xGex buffer layer fabricated by an oxidative solid‐phase epitaxy process can facilitate extraordinarily efficient strain relaxation. The Si1−xGex layer is formed by ion implanting Ge into Si(111) and selectively oxidizing Si atoms in the resulting ion‐damaged layer, precipitating a fully strain‐relaxed Ge‐rich layer between the Si substrate and surface oxide. The efficient strain relaxation results from the high oxidation temperature, producing a periodic network of dislocations at the substrate interface, coinciding with modulations of the Ge content in the Si1−xGex layer and indicating the presence of defect‐mediated diffusion of Si through the layer. The epitaxial growth of high‐quality GaAs is demonstrated on this ultra‐thin Si1−xGex layer, demonstrating a promising new pathway for integrating III‐V lasers directly on the Si platform.

Facilitating Absorption Spectroscopy of Strongly Absorbing Fluids: A High-Throughput Approach.

Measuring absorption spectra of strongly absorbing solutions is usually only possible by diluting the solution. However, the absorption spectra can be heavily influenced by concentration-dependent interactions, so dilution leads to misleading results. To enable reliable absorption measurements of concentrated solutions, we introduce in this work thinning fluid film spectroscopy (TFFS), a simple and highly automatable method. We present three exemplary measurement modes of TFFS suitable for many different applications and validate the TFFS measurements with control data obtained in specialized, low optical path length cuvettes. Additionally, we compare the suitability of the different measurement modes over a broad concentration range and demonstrate the automation possibilities with a spectroscopy robot. Beyond this automated approach for highly efficient and high-throughput lab work, we also show the possibility of direct integration into production systems with an in-line setup, which can be incorporated into a variety of pipe systems. The TFFS method is not limited to samples from material science but can be transferred to a broad variety of research and industry fields, including proteins, food, and pharmaceuticals or also agriculture and forensics.

Magnetic field calculation of a uniformly magnetized sphere using solid angles

A new method to calculate the magnetic field of a uniformly magnetized sphere or spherical shell with surface current density K=Kosinθ using the solid angle concept is presented. The field can be shown easily to be constant inside the shell and dipole-like outside with a direct integral of Biot-Savart’s law without invoking magnetic vector potential or special scalar functions typically used for this classical problem.

Quasi-Diabatization Based on Minimizing Derivative Couplings in a Limited Configuration Space: Elimination of Boundary Condition Dependence.

Due to the cuspidal ridges of adiabatic potential energy surfaces (PESs) and singularities of nonadiabatic couplings (NACs), obtaining an analytical expression for the adiabatic Hamiltonian is difficult. Thereby, nonadiabatic dynamics simulations are often carried out on-the-fly, which is time-consuming. This motivates us to construct quasi-diabatic representations, which have smooth PESs and diabatic couplings. In this study, we propose a new quasi-diabatization method based on minimizing derivative couplings (MDC) in a limited configuration space. The boundary conditions are first considered and finally released to obtain the adiabatic-to-diabatic rotation angles and transformation matrices. As demonstrated in representative one- and two-dimensional models and the widely studied linear H3 molecule, MDC performs significantly better than the direct integration quasi-diabatization approach. In particular, accurate diabatic potential energy matrices have been successfully obtained even when the NACs of all configurations in the considered space are nonnegligible.

A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy.

The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and noncanonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in silico tools for the identification, prediction and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens, high-confidence tumor-specific antigens and tumor-specific noncanonical antigens. We demonstrate the superiority of NeoDisc in accurately prioritizing immunogenic neoantigens over recent prioritization pipelines. We showcase the various features offered by NeoDisc that enable both rule-based and machine-learning approaches for personalized antigen discovery and neoantigen cancer vaccine design. Additionally, we demonstrate how NeoDisc's multiomics integration identifies defects in the cellular antigen presentation machinery, which influence the heterogeneous tumor antigenic landscape.

A novel iterative algorithm for nonlinear inelastic dynamic analysis of truss structures; MCB-Spline+Sp time integration method

The focus of this work is on the development of a novel algorithm for the nonlinear dynamic analysis of structures. In the sake of a general and easy-to-implement solution method, the tangential stiffness matrix is calculated by combining the Cauchy-Riemann equations derived from the differentiation of complex functions and using the nodal displacement perturbation vector. An implicit direct time integration method based on a cubic B-Spline is integrated with the incremental-iterative method using a quadrature rule based on the interpolation of spline functions, which is referred to as the MCB-Spline+Sp time integration method. A step-by-step algorithm for developing a computer code to implement this method is provided. The effectiveness of the proposed approach is evaluated through several nonlinear time history analyses, which demonstrate its accuracy and efficiency by observing less computational efforts and fast convergence rate. Moreover, a comparison is made between the developed method and well-established techniques such as the Newmark and Standard-Bathe time integration methods in combination with the iterative Newton-Raphson method.

Unraveling the Source of Self-Induced Diastereomeric Anisochronism in Chiral Dipeptides.

Mastering of analytical methods for accurate quantitative determinations of enantiomeric excess is a crucial aspect in asymmetric catalysis, chiral synthesis, and pharmaceutical applications. In this context, the phenomenon of Self-Induced Diastereomeric Anisochronism (SIDA) can be exploited in NMR spectroscopy for accurate determinations of enantiomeric composition, without using a chiral auxiliary that could interfere with the spectroscopic investigation. This phenomenon can be particularly useful for improving the quantitative analysis of mixtures with low enantiomeric excesses, where direct integration of signals can be tricky. Here, we describe a novel analysis protocol to correctly determine the enantiomeric composition of scalemic mixtures and investigate the thermodynamic and stereochemical features at the basis of SIDA. Dipeptide derivatives were chosen as substrates for this study, given their central role in drug design. By integrating the experiments with a conformational stochastic search that includes entropic contributions, we provide valuable information on the dimerization thermodynamics, the nature of non-covalent interactions leading to self-association, and the differences in the chemical environment responsible for the anisochronism, highlighting the importance of different stereochemical arrangement and tight association for the distinction between homochiral and heterochiral adducts. An important role played by the counterion was pointed out by computational studies.

Rapid-Learning Collaborative Pushing and Grasping via Deep Reinforcement Learning and Image Masking

When multiple objects are positioned close together or stacked, pre-grasp operations such as pushing objects can be used to create space for the grasp, thereby improving the grasping success rate. This study develops a model based on a deep Q-learning network architecture and introduces a fully convolutional network to accurately identify pixels in the workspace image that correspond to target locations for exploration. In addition, this study incorporates image masking to limit the exploration area of the robotic arm, ensuring that the agent consistently explores regions containing objects. This approach effectively addresses the sparse reward problem and improves the convergence rate of the model. Experimental results from both simulated and real-world environments show that the proposed method accelerates the learning of effective grasping strategies. When image masking is applied, the success rate in the grasping task reaches 80% after 600 iterations. The time required to reach 80% success rate is 25% shorter when image masking is used compared to when it is not used. The main finding of this study is the direct integration of image masking technique with a deep reinforcement learning (DRL) algorithm, which offers significant advancement in robotic arm control. Furthermore, this study shows that image masking technique can substantially reduce training time and improve the object grasping success rate. This innovation enables the robotic arm to better adapt to scenarios that conventional DRL methods cannot handle, thereby improving training efficiency and performance in complex and dynamic industrial applications.