Expansion Method Research Articles

Genetic Code Expansion for Mechanistic Studies in Ion Channels: An (Un)natural Union of Chemistry and Biology.

Ion channels play central roles in biology and human health by catalyzing the transmembrane flow of electrical charge. These proteins are ideal targets for genetic code expansion (GCE) methods because it is feasible to measure ion channel activity from miniscule amounts of protein and to analyze the resulting data via rigorous, established biophysical methods. In an ideal scenario, the encoding of synthetic, noncanonical amino acids via GCE allows the experimenter to ask questions inaccessible to traditional methods. For this reason, GCE has been successfully applied to a variety of ligand- and voltage-gated channels wherein extensive structural, functional, and pharmacological data exist. Here, we provide a comprehensive summary of GCE as applied to ion channels. We begin with an overview of the methods used to encode noncanonical amino acids in channels and then describe mechanistic studies wherein GCE was used for photochemistry (cross-linking; caged amino acids) and atomic mutagenesis (isosteric manipulation of charge and aromaticity; backbone mutation). Lastly, we cover recent advances in the encoding of fluorescent amino acids for the real-time study of protein conformational dynamics.

Research Methods for Transient Stability Analysis of Power Systems under Large Disturbances

Transient stability analysis is critical for maintaining the reliability and security of power systems. This paper provides a comprehensive review of research methods for transient stability analysis under large disturbances, detailing the modeling concepts and implementation approaches. The research methods for large disturbance transient stability analysis are categorized into five main types: simulation methods, direct methods, data-driven methods, analytical methods, and other methods. Within the analytical method category, several common analytical strategies are introduced, including the asymptotic expansion method, intrusive approximation method, and other analytical methods. The fundamental principles, characteristics, and recent research advancements of these methods are detailed, with particular attention to their performance in various aspects such as computational efficiency, accuracy, applicability to different system models, and stability region estimation. The advantages and disadvantages of each method are compared, offering insights to support further research into transient stability analysis for hybrid power grids under large disturbances.

Chien-physics-informed neural networks for solving singularly perturbed boundary-layer problems

A physics-informed neural network (PINN) is a powerful tool for solving differential equations in solid and fluid mechanics. However, it suffers from singularly perturbed boundary-layer problems in which there exist sharp changes caused by a small perturbation parameter multiplying the highest-order derivatives. In this paper, we introduce Chien’s composite expansion method into PINNs, and propose a novel architecture for the PINNs, namely, the Chien-PINN (C-PINN) method. This novel PINN method is validated by singularly perturbed differential equations, and successfully solves the well-known thin plate bending problems. In particular, no cumbersome matching conditions are needed for the C-PINN method, compared with the previous studies based on matched asymptotic expansions.

Soliton solutions of the TWPA-SNAIL transmission line circuit equation under continuum approximation via the Jacobi elliptic function expansion method

Soliton solutions of the TWPA-SNAIL transmission line circuit equation under continuum approximation via the Jacobi elliptic function expansion method

Unified theory of alpha, mu, and tau rhythms via eigenmodes of brain activity.

A compact description of the frequency structure and topography of human alpha-band rhythms is obtained by use of the first four brain activity eigenmodes previously derived from corticothalamic neural field theory. Just two eigenmodes that overlap in frequency are found to reproduce the observed topography of the classical alpha rhythm for subjects with a single, occipitally concentrated alpha peak in their electroencephalograms. Alpha frequency splitting and relative amplitudes of double alpha peaks are explored analytically and numerically within this four-mode framework using eigenfunction expansion and perturbation methods. These effects are found to result primarily from the different eigenvalues and corticothalamic gains corresponding to the eigenmodes. Three modes with two non-overlapping frequencies suffice to reproduce the observed topography for subjects with a double alpha peak, where the appearance of a distinct second alpha peak requires an increase of the corticothalamic gain of higher eigenmodes relative to the first. Conversely, alpha blocking is inferred to be linked to a relatively small attention-dependent reduction of the gain of the relevant eigenmodes, whose effect is enhanced by the near-critical state of the brain and whose sign is consistent with inferences from neural field theory. The topographies and blocking of the mu and tau rhythms within the alpha-band are explained analogously via eigenmodes. Moreover, the observation of three rhythms in the alpha band is due to there being exactly three members of the first family of spatially nonuniform modes. These results thus provide a simple, unified description of alpha band rhythms and enable experimental observations of spectral structure and topography to be linked directly to theory and underlying physiology.

Spectrum contrast enhancement of fiber fabry-perot sensor by coupling efficiency improvement

This paper investigates the impact of interface angles on the coupling efficiency of a fiber Fabry-Perot interferometer (FFPI) sensor using both simulation and experimental methods. The FFPI sensor, which consists of a single-mode fiber (SMF), hollow-core fiber (HCF), and diaphragm, has its coupling efficiency determined by the generalized scattering matrix of the cascaded fiber system. To obtain the interface angles of the FFPI sensor, a new on-line monitoring system is developed based on microscopic images of the FFPI cavity and an image processing algorithm using OpenCV. By combining the eigenmode expansion method (EME) model and the online interface angle measurement technique, the coupling efficiency and spectral contrast of the FFPI cavity are evaluated and improved. Additionally, the corresponding working point in the intensity demodulation based FFPI sensor can be quickly identified. Using this method, an FFPI sensor with a spectral contrast of over 35 dB is achieved, which is significantly higher than existing similar sensors, and its sensitivity also reaches 50.80 mV/MPa. This work also holds significance for controlling and enhancing the spectral characteristics of other cascaded fiber optic sensors.

Flexibility provision in the Swiss integrated power, hydrogen, and methane infrastructure

The renewable energy transition hinges on balancing energy supply and demand across seasons. This paper investigates the potential flexibility of Switzerland’s integrated power, hydrogen, and methane infrastructure to balance temporal mismatches while complying with national energy policies for sustainability and security. It develops an optimization method for energy system expansion and operation planning, filling crucial research gaps by (1) explicitly modeling power and gas transmission networks to guide technology placement and pinpoint network expansions, and (2) incorporating flexibility in power demand via shedding and shifting and in hydrogen and methane demands via price elasticity. The findings suggest that a 6.7-fold capacity expansion of variable renewables (i.e., photovoltaic, wind, run-of-river) by 2050 offsets nuclear phase-out and demand growth. The winter power gap is filled by power imports, hydropower generation, and gas turbines fueled by cost-effective hydrogen or methane imports. However, fuel embargoes escalate winter hydrogen and methane prices, reducing demand by 3.8%–10.4% and increasing domestic fuel production from biomass and excess renewable power in summer. To bridge the seasonal hydrogen and methane supply–demand gaps, up to 1.9 terawatt-hours of gas cavern storage is deployed in geologically viable locations, while costly tank storage plays a minor role. Power-to-gas requirements and power trade restrictions necessitate further renewable expansion, including 8.0 to 9.5 gigawatts of wind installations.

Fully heavy tetraquark resonant states with different flavors

We use the quark potential model to calculate the mass spectrum of the S-wave fully heavy tetraquark systems with different flavors, including the bcb¯c¯,bbc¯c¯,ccc¯b¯, and bbb¯c¯ systems. We employ the Gaussian expansion method to solve the four-body Schrödinger equation, and the complex scaling method to identify resonant states. The bcb¯c¯,bbc¯c¯,ccc¯b¯, and bbb¯c¯ resonant states are obtained in the mass regions of (13.2, 13.5), (13.3, 13.6), (10.0, 10.3), (16.5, 16.7) GeV, respectively. Among these states, the bcb¯c¯ tetraquark states are the most promising ones to be discovered in the near future. We recommend the experimental exploration of the 1++ and 2++ bcb¯c¯ states with masses near 13.3 GeV in the J/ψϒ channel. From the root-mean-square radii, we find that all the resonant states we have identified are compact tetraquark states. Published by the American Physical Society 2024

Prediction of midpalatal suture maturation stage based on transfer learning and enhanced vision transformer

BackgroundMaxillary expansion is an important treatment method for maxillary transverse hypoplasia. Different methods of maxillary expansion should be carried out depending on the midpalatal suture maturation levels, and the diagnosis was validated by palatal plane cone beam computed tomography (CBCT) images by orthodontists, while such a method suffered from low efficiency and strong subjectivity. This study develops and evaluates an enhanced vision transformer (ViT) to automatically classify CBCT images of midpalatal sutures with different maturation stages.MethodsIn recent years, the use of convolutional neural network (CNN) to classify images of midpalatal suture with different maturation stages has brought positive significance to the decision of the clinical maxillary expansion method. However, CNN cannot adequately learn the long-distance dependencies between images and features, which are also required for global recognition of midpalatal suture CBCT images. The Self-Attention of ViT has the function of capturing the relationship between long-distance pixels of the image. However, it lacks the inductive bias of CNN and needs more data training. To solve this problem, a CNN-enhanced ViT model based on transfer learning is proposed to classify midpalatal suture CBCT images. In this study, 2518 CBCT images of the palate plane are collected, and the images are divided into 1259 images as the training set, 506 images as the verification set, and 753 images as the test set. After the training set image preprocessing, the CNN-enhanced ViT model is trained and adjusted, and the generalization ability of the model is tested on the test set.ResultsThe classification accuracy of our proposed ViT model is 95.75%, and its Macro-averaging Area under the receiver operating characteristic Curve (AUC) and Micro-averaging AUC are 97.89% and 98.36% respectively on our data test set. The classification accuracy of the best performing CNN model EfficientnetV2_S was 93.76% on our data test set. The classification accuracy of the clinician is 89.10% on our data test set.ConclusionsThe experimental results show that this method can effectively complete CBCT images classification of midpalatal suture maturation stages, and the performance is better than a clinician. Therefore, the model can provide a valuable reference for orthodontists and assist them in making correct a diagnosis.

High-throughput analysis of topographical cues for the expansion of murine pluripotent stem cells

The expansion of pluripotent stem cells (PSCs)in vitroremains a critical barrier to their use in tissue engineering and regenerative medicine. Biochemical methods for PSC expansion are known to produce heterogeneous cell populations with varying states of pluripotency and are cost-intensive, hindering their clinical translation. Engineering biomaterials to physically control PSC fate offers an alternative approach. Surface or substrate topography is a promising design parameter for engineering biomaterials. Topographical cues have been shown to elicit profound effects on stem cell differentiation and proliferation. Previous reports have shown isotropic substrate topographies to be promising in expanding PSCs. However, the optimal feature to promote PSC proliferation and the pluripotent state has not yet been determined. In this work, the MultiARChitecture (MARC) plate is developed to conduct a high-throughput analysis of topographical cues in a 96-well plate format. The MARC plate is a reproducible and customizable platform for the analysis of multiple topographical patterns and features and is compatible with both microscopic assays and molecular biology techniques. The MARC plate is used to evaluate the expression of pluripotency markersOct4, Nanog, andSox2and the differentiation markerLmnAas well as the proliferation of murine embryonic stem (mES) cells. Our systematic analyses identified three topographical patterns that maintain pluripotency in mES cells after multiple passages: 1µm pillars (1µm spacing, square arrangement), 2µm wells (c-c (x, y) = 4, 4µm), and 5µm pillars (c-c (x, y) = 7.5, 7.5µm). This study represents a step towards developing a biomaterial platform for controlled murine PSC expansion.

Exploration of different multi-peak solitons and vibrant breather type waves’ solutions of nonlinear Schrödinger equations with advanced dispersion and cubic–quintic nonlinearity, unveiling their applications

Abstract The nonlinear Schrödinger equations (NLSEs) of higher order illustrate the transmission of extremely short light pulses in fiber optics. In this manuscript, we employ the two-variable (1/G, G′/G)-expansion technique to construct bright and multi-peak solitons, periodic multi-solitons, breather type solitary waves, periodic peakon solitons, and other wave solutions of higher-order NLSE in mono-mode optical fiber and generalized NLSE with cubic–quintic nonlinearity. The two-variable (1/G, G′/G)-expansion method is a generalization of the (G′/G)-expansion method, offering a more robust mathematical tool for solving various nonlinear partial differential equations (PDEs) in mathematical physics. We also analyze the characteristics of waves conducive to the formation of bright–dark and other soliton forms within this medium. Additionally, we provide graphical representations of the obtained results to visually depict the dynamical models under consideration. Our findings highlight the potency, reliability, and versatility of the proposed technique, which holds promise for solving a wide array of similar models encountered in applied sciences and engineering.

Abundant solitary wave solutions to the new extended (3+1)-dimensional nonlinear evolution equation arising in fluid dynamics

Nonlinear evolution equations appear in various branches of physics, including fluid dynamics, solid mechanics, quantum mechanics, and other fields. They are essential for describing systems where interactions and nonlinearity play a significant role, providing a more accurate representation of real-world phenomena than linear equations in certain cases. The study of nonlinear evolution equations involves exploring their solutions, stability properties, and the behavior of the systems they describe over time. In this study, we provide plenty of analytical solutions to a very recently proposed water wave model using the modified generalized exponential rational function, modified extended tanh-function, and the [Formula: see text]-expansion methods. To examine the dynamic characteristics of these results, we displayed three-dimensional (3D), contour, and two-dimensional (2D) visual representations of specific solutions. The outcomes reveal a multitude of novel solutions, emphasizing the robustness and effectiveness of the applied methodologies. It is important to note that all the solutions derived in this study are original and have not been previously documented in the existing literature. These novel solutions hold significant value for researchers in the realms of fluids and plasma physics, providing insights into the dynamics of nonlinear waves within various physical systems. Furthermore, this research contributes to a deeper understanding of the nature of nonlinear waves prevalent in seas and oceans, offering valuable knowledge for the broader study of such phenomena.

The impact of standard Wiener process on the optical solutions of the stochastic nonlinear Kodama equation using two different methods

The stochastic nonlinear Kodama (SNLK) equation forced in the Stratonovich sense by multiplicative noise is considered here. New elliptic, hyperbolic, trigonometric, and rational stochastic solutions are acquired using ( G′/ G)-expansion method and mapping method. Because the SNLK equation is extensively used in is extensively used in nonlinear optics, fluid dynamics, and plasma physics, the obtained solutions may be used to study a broad range of relevant physical phenomena. In order to interpret the effects of multiplicative noise, the dynamic performances of the various obtained solutions are displayed utilizing 3D and 2D graphs. We infer that multiplicative noise impacts and stabilizes the solutions of SNLK equation.

Dynamics, stability and bifurcations of a planar three-link swimmer with passive visco-elastic joint using “ideal fluid” model

Articulated swimming robots have a promising potential for various marine applications. A common theoretical model assumes ideal fluid, where the viscosity is negligible and the swimmer–fluid interaction is induced by reactive forces originating from added mass effect. Some previous works used this model to study planar multi-link swimmers under kinematic input prescribing all joint angles. Inspired by biological swimmers in nature that utilize body flexibility, in this work we consider an underactuated three-link swimmer where one joint is periodically actuated while the other joint is passive and viscoelastic. Analysis of the swimmer’s nonlinear dynamics reveals that its motion depends significantly on the amplitude and frequency of the actuated joint angle. Optimal frequency is found where the swimmer’s net displacement per cycle is maximized, under symmetric periodic oscillations of the passive joint. In addition, upon crossing critical values of amplitude or frequency, the system undergoes a bifurcation where the symmetric periodic solution loses stability and asymmetric solutions evolve, for which the swimmer moves along an arc. We analyze these phenomena using numerical simulations and analytical methods of perturbation expansion, harmonic balance, Floquet theory, and Hill’s determinant. The results demonstrate the important role of parametric excitation in stability and bifurcations of motion for flexible underactuated locomotion.

Design of 16-wavelength high-power heterogeneous III-V/Si laser arrays with varying stripe width and grating period

Multi-wavelength laser array is currently one of the most attractive technologies to provide high density links for advanced optical communications and computing. The conventional scheme of varying grating period is almost impossible to achieve 8-wavelength or more. And, the optical output power of heterogeneously integrated quantum dot laser can hardly meet the commercial demand. In this paper, we report a 16-wavelength high-power heterogeneously integrated quantum dot distributed feedback laser array. To the best of our knowledge, this is the first heterogeneously integrated quantum dot laser array that tunes the lasing wavelength by combining the scheme of varying the stripe width and grating period of laser units. The effective refractive index of gratings is calculated by eigenmode expansion method. When the grating period is fixed at 198 nm, and the stripe widths of laser units are 2.00 μm, 2.25 μm, 2.60 μm and 3.15 μm, respectively, the corresponding lasing wavelengths are 1307.94 nm, 1308.49 nm, 1309.06 nm and 1309.63 nm, respectively, and the wavelength spacing of the adjacent laser units is about 100 GHz. By additionally adjusting the grating period between 196 nm and 202 nm with 2 nm spacing of grating period, a 16-wavelength QD DFB laser array is designed with the wavelength range from 1294.73 nm to 1336.09 nm. In addition, asymmetric distributed feedback grating is adopted to improve the optical output power at the front-end of laser arrays. The maximum ratio of the output power at the both end of laser units is 19.6 when the grating duty cycles of the front-end and the back-end of the λ/4 phase-shift is 0.7 and 0.5, respectively, and the grating lengths is 250 μm and 450 μm, respectively. This work will promote the performance improvement of heterogeneously integrated quantum dot lasers and develop the quantum dot lasers towards multi-wavelength.

A complete dynamical analysis of discrete electric lattice coupled with modified Zakharov–Kuznetsov equation

The behavior of nonlinear waves within a modified Zakharov–Kuznetsov equation and their interactions with discrete electric lattice structures are examined in this study. The ϕ6−model expansion method is utilized to acquire substantial knowledge into the complex dynamics of the system under consideration, particularly with regard to the discrete electric lattice and analytical electrical solitons. By incorporating higher-order effects and improving accuracy in representing specific physical conditions, the study achieves a more realistic portrayal of nonlinear wave dynamics. The investigation also sheds light on the relationship between non-linearity, discreteness, and equation dynamics by exploring the conditions that lead to the formation of solitons and other nonlinear structures. In addition, a unique set of electrical solitons is defined to explore dynamic behaviors such as chaotic, quasi-periodic, and periodic motions under various parameterized conditions, including an external damping force. Phase plane analysis is visualized by using dynamic structure 3D and 2D phase plots, is used for bifurcation and sensitivity inspections. Finally, time series graphs are offered as mathematical depictions of solitary waves, and Lyapunov exponents with real and complex eigenvalues are used to study the stability and chaotic behaviors of the system.

Mechanical response and failure mechanism of circular inclusion embedded in brittle materials under dynamic impact

Inclusions are prevalent in both natural and synthetic materials. Gaining a comprehensive understanding of their dynamic response and interaction with the surrounding matrix is essential in fundamental mechanics and engineering applications. This study aims to achieve such understanding through theoretical analysis, experimental investigations, and numerical simulations, focusing on the dynamic destruction of inclusions and the underlying mechanisms. Firstly, the circumferential, radial, and shear stresses around elastic heterogeneous inclusions were derived by the wave function expansion and Duhamel integration methods. Subsequently, a set of experiments on sandstone specimens containing three types of inclusions (plaster, epoxy resin, cement) were conducted utilizing the Split Hopkinson Pressure Bar (SHPB) system in conjunction with high-speed photography and Digital Image Correlation (DIC) techniques to obtain the surface deformation of inclusion specimens. Eventually, a series of Finite Element Method (FEM) numerical simulations adopted suitable materials were also carried out to investigate the fracture process of inclusion and matrix under dynamic impact. The results demonstrate that the stress distributions and fracture mode of matrix and inclusion are highly dependent on the physical and mechanical properties of the inclusions and the surrounding matrix, specifically, density ρ, elastic modulus E, Poisson's ratio v, and strength. With an increase in the E and v, there is a reduction in the concentration of circumferential stress, while the radial and shear stresses experience an increase. The experimental and numerical results corroborated the theoretical findings and indicated that the localized dynamic stress concentrations induced by wave scattering around the inclusions directly dominated both local and overall specimen failure. Due to the dissimilarities in elastic parameters and strength between the inclusion and the matrix, the stress state of the inclusion and the interface is not homogeneous. Under dynamic loading, the weaker inclusion experiences tensile cracking at both ends of the loading, and as the mechanical properties (ρ, E, v, and strength) of the inclusion rise, a transition from tensile- hybrid-shear failure occurs within the inclusion. The findings of this study help us understand the dynamic failure mechanisms of dissimilar inclusions in brittle material.

Dynamic force identification considering modeling errors using modal expansion method and relevant vector regression algorithm

Accurate identification and estimation of external forces on launch vehicles, aircraft, and other in-service engineering structures plays a vital role in structural design and health monitoring. Considering structural modeling errors, this paper develops a novel force identification method based on modal expansion and relevant vector regression (RVR). Initially, the incomplete and noisy experimental modal data are used to modify the stiffness and mass matrices of the finite element (FE) model, reducing the impact of modeling errors on force identification accuracy. Subsequently, to account for noise disturbances and potential information about unknown initial conditions in the measured acceleration responses, the external forces and the unknown initial conditions are respectively expanded using trigonometric functions and the mode shapes based on the function fitting technique. On this basis, the force identification equation is established for the updated model. The RVR algorithm is integrated into modal expansion and force identification. Firstly, the mode shapes of the FE model are utilized to expand the incomplete and noisy experimental mode shapes to their full degree of freedom, significantly enhancing the accuracy of the model updating. Secondly, by combining the measured acceleration responses, the base coefficients can be solved sparsely, effectively identifying the dynamic forces even when unknown initial conditions are present.

Strategies for Improving CAR T Cell Persistence in Solid Tumors.

CAR T cells require optimization to be effective in patients with solid tumors. There are many barriers affecting their ability to succeed. One barrier is persistence, as to achieve an optimal antitumor response, infused CAR T cells must engraft and persist. This singular variable is impacted by a multitude of factors-the CAR T cell design, lymphodepletion regimen used, expansion method to generate the T cell product, and more. Additionally, external agents can be utilized to augment CAR T cells, such as the addition of novel cytokines, pharmaceutical drugs that bolster memory formation, or other agents during either the ex vivo expansion process or after CAR T cell infusion to support them in the oppressive tumor microenvironment. This review highlights many strategies being used to optimize T cell persistence as well as future directions for improving the persistence of infused cells.

Perception-Driven Soft-Edge Occlusion for Optical See-Through Head-Mounted Displays.

Systems with occlusion capabilities, such as those used in vision augmentation, image processing, and optical see-through head-mounted display (OST-HMD), have gained popularity. Achieving precise (hard-edge) occlusion in these systems is challenging, often requiring complex optical designs and bulky volumes. On the other hand, utilizing a single transparent liquid crystal display (LCD) is a simple approach to create occlusion masks. However, the generated mask will appear defocused (soft-edge) resulting in insufficient blocking or occlusion leakage. In our work, we delve into the perception of soft-edge occlusion by the human visual system and present a preference-based optimal expansion method that minimizes perceived occlusion leakage. In a user study involving 20 participants, we made a noteworthy observation that the human eye perceives a sharper edge blur of the occlusion mask when individuals see through it and gaze at a far distance, in contrast to the camera system's observation. Moreover, our study revealed significant individual differences in the perception of soft-edge masks in human vision when focusing. These differences may lead to varying degrees of demand for mask size among individuals. Our evaluation demonstrates that our method successfully accounts for individual differences and achieves optimal masking effects at arbitrary distances and pupil sizes.