Orthogonal Parallel Research Articles

Theoretical and experimental study of modulation transfer spectroscopy for non-cycling transitions of Rb D1 lines

Modulation transfer spectroscopy (MTS) of the D1 transitions of 85Rb and 87Rb atoms with only non-cycling transitions have been investigated theoretically and experimentally using the density matrix equation for four different polarization configurations: linear orthogonal (lin⊥lin), linear parallel (lin ∥ lin), circular orthogonal (σ+−σ−), and circular parallel (σ+−σ+). MTS signals for the Fg=3→Fe=2 transition of 85Rb atom and Fg=2→Fe=1 transition of the 87Rb atom among D1 transition lines were found to be stronger than those for the other transitions. The two non-cycling transitions have strong MTS signals because of the branching ratios and populations of the relevant ground states. The observed line shapes of the in-phase and quadrature components of MTS signals agree well with the theoretical shapes obtained by solving the density matrix equation.

Microarray Platforms Based on 3D Printing.

This paper introduces an innovative method for the fabrication and infusion of microwell arrays based on digital light processing (DLP) 3D printing. A low-cost DLP 3D printer is employed to fabricate microstructures rapidly with a broad dynamic range while maintaining high precision and fidelity. We constructed microwell arrays with varying diameters, from 200 to 2000 μm and multiple aspect ratios, in addition to microchannels with widths ranging from 45 to 1000 μm, proving the potential and flexibility of this fabrication method. The superimposition of parallel microchannels onto the microwell array, facilitated by positive or negative pressure, enabled the transfer of liquid to the microwells. Upon removal of the microchannel chip, a dispensed microdroplet array was obtained. This array can be modulated by adjusting the volume of the microwells and the inflow fluid. The filled microwell array allows chip-to-chip dispensing to the microreactor array through binding and centrifugation, facilitating multistep and multireagent assays. The 3D printing approach also enables the fabrication of intricate cavity designs, such as micropyramid arrays, which can be integrated with parallel microchannels to generate spheroid flowcells. This device demonstrated the ability to generate spheroids and manipulate their environment. We have successfully utilized precise modulation of spheroids size and performed parallel drug dose-response assays to evaluate its effectiveness. Furthermore, we managed to execute dynamic drug combinations based on a compact spheroids array, utilizing two orthogonal parallel microchannels. Our findings suggest that both the combination and temporal sequence of drug administration have a significant impact on therapeutic outcomes.

Design and development of a continuous harvesting system using solid-liquid cyclone separator for harvesting of Dunaliella salina for mass production of biomass: Part-1: Performance in single-stage

Microalgae is a viable alternative to depleting conventional fuel sources, a solution to the industrial requirement of organic consumables, and an option for a green and sustainable economy for biofuels, pigments, and nutrient production. Dunaliella salina is an efficient choice among various species due to its high lipid/carotenoid content and growth in extreme saline conditions. Existing batch-production harvesting methods, such as centrifugation and flocculation, are neither inexpensive nor environmentally benign. This paper presents the experimental studies on three different Rietema-type solid-liquid cyclone separators (RSLCS) for continuous harvesting of microalgae as a concentrated trap for mass biomass production to achieve an economy for biofuels and other desirable by-products if required. Two of these RSLCS were modified and had two inlets (orthogonal RSLCS and parallel RSLCS) when compared with conventional RSLCS. The experiments were performed to calculate the growth of microalgae culture on different days (Day-7, 14, 21, and 28), and concentrations of outflows on day-28 were used as feed for all the RSLCS. The recorded separation efficiency for conventional, orthogonal, and parallel RSLCS are 61.66 %, 67.95 %, and 60.14 % respectively. CFD simulations were also done to validate the results, and CellProfiler was used to measure the size of Dunaliella salina for hydrodynamic analysis. The CFD simulations showed separation efficiency of 60.72 %, 67.04 %, and 59.52 % for conventional, orthogonal, and parallel RSLCS. Thus, the use of orthogonal RSLCS is proposed as a simple, cheap, and eco-friendly solution to the industry-level requirement of continuous harvesting for microalgae in replacement of existing batch-production techniques.

Unmixing aware compression of hyperspectral image by rank aware orthogonal parallel factorization decomposition

Unmixing aware compression of hyperspectral image by rank aware orthogonal parallel factorization decomposition

Crystal Structure of de Novo Designed Coiled-Coil Protein Origami Triangle.

Coiled-coil protein origami (CCPO) uses modular coiled-coil building blocks and topological principles to design polyhedral structures distinct from those of natural globular proteins. While the CCPO strategy has proven successful in designing diverse protein topologies, no high-resolution structural information has been available about these novel protein folds. Here we report the crystal structure of a single-chain CCPO in the shape of a triangle. While neither cyclization nor the addition of nanobodies enabled crystallization, it was ultimately facilitated by the inclusion of a GCN2 homodimer. Triangle edges are formed by the orthogonal parallel coiled-coil dimers P1:P2, P3:P4, and GCN2 connected by short linkers. A triangle has a large central cavity and is additionally stabilized by side-chain interactions between neighboring segments at each vertex. The crystal lattice is densely packed and stabilized by a large number of contacts between triangles. Interestingly, the polypeptide chain folds into a trefoil-type protein knot topology, and AlphaFold2 fails to predict the correct fold. The structure validates the modular CC-based protein design strategy, providing molecular insight underlying CCPO stabilization and new opportunities for the design.

Parallel EM optimization using improved pole‐residue‐based neuro‐TF surrogate and isomorphic orthogonal DOE sampling for microwave components design

AbstractDirect electromagnetic (EM) optimization for microwave components design is usually a time‐consuming process. To improve the optimization efficiency, this paper proposes a novel parallel EM optimization technique exploiting improved pole‐residue‐based neuro‐transfer function (neuro‐TF) surrogate and isomorphic orthogonal design of experiment (DOE) sampling strategy. We propose a new sampling method combining isomorphic orthogonal DOE and parallel EM simulations to generate training data for developing the neuro‐TF surrogate. This proposed sampling method can ensure the scattered distribution of data samples in the overall optimization process, thus effectively improving the surrogate accuracy and increasing the optimization speed. We also propose a new pole‐residue tracking technique for order‐changing to solve the discontinuity problem of pole/residues during the neuro‐TF surrogate development. Different from the fixed split ratio in existing pole‐residue tracking technique, the split ratio of poles and residues in the proposed technique is adaptive and determined according to the information of neighboring samples. Therefore, the continuity and smoothness of pole/residues after the splitting are improved, so as the neuro‐TF surrogate accuracy. In addition, the trust region algorithm is exploited during EM optimization to improve the convergence speed. In this way, the proposed EM optimization technique obtains the optimal solution in a shorter time with fewer iterations than the existing techniques. Two examples of EM optimizations of microwave components are used to illustrate the proposed technique.

RMAML: Riemannian meta-learning with orthogonality constraints

Meta-learning is the core capability that enables intelligent systems to rapidly generalize their prior experience to learn new tasks. In general, the optimization-based methods formalize the meta-learning as a bi-level optimization problem, that is a nested optimization framework, in which meta-parameters are optimized (or learned) at the outer-level, while the inner-level optimizes the task-specific parameters. In this paper, we introduce RMAML, a meta-learning method that enforces orthogonality constraints to the bi-level optimization problem. We develop a geometry aware framework that generalizes the bi-level optimization problem to the Riemannian (constrained) setting. Using the Riemannian operations such as orthogonal projection, retraction and parallel transport, the bi-level optimization is reformulated so that it respects the Riemannian geometry. Moreover, we observe that a superior stable optimization and an improved generalization ability can be achieved when the parameters and meta-parameters of the method are modeled using a Stiefel Manifold. We empirically show that RMAML can easily reach competitive performances against several state of the art algorithms for few-shot classification and consistently outperforms its Euclidean counterpart, MAML. For example, by using the geometry of the Stiefel manifold to structure the fully-connected layers in a deep neural network, a 7% increase in single-domain few-shot classification accuracy is achieved. For the cross-domain few-shot learning, RMAML outperforms MAML by up to 9% of accuracy. Our ablation study also demonstrates the effectiveness of RMAML over MAML in terms of higher accuracy with a reduced number of tasks and (or) inner-level updates.

Performance analysis of over-constrained orthogonal parallel six-axis force sensor

An over-constrained orthogonal parallel six-axis force sensor is an improvement over the traditional parallel six-axis force sensor and has the advantage of simple mapping relations. According to this improved configuration, performance parameters, such as decoupling characteristics, uniform-load characteristics, and range-limited characteristics, were used for performance analysis and were mathematically established. Then, the relation between the performance parameters and sensor design parameters was analysed numerically. Finally, a sensor prototype was designed and optimised into a second prototype based on the analysis of performance parameters. Results show that the vertical branch decoupling characteristic of the first and second prototypes were 19 % and 8.8 % full-scale (FS), respectively, and the range-limited characteristics of the first and second prototypes are 7.1 % in the Fz direction and 3.9 % FS, respectively. This shows that the proposed performance parameters can better analyse the performance of the over-constrained orthogonal parallel six-axis force sensor and optimise the sensor structure.

Study on Impact Test System of Manipulator Based on Six Axis Force Sensor and Intelligent Controller

With the development and application of intelligent nervous system, intelligent control system represented by machine vision has been promoted and used in various fields, including manipulator control system. Mechanical arm is the main actuator of robot and other mechanical components, but the application environment of mechanical arm is extremely complex, and with the development of industrial process, the sensitivity of technology and operating system for its arbitrary posture operation is also steadily improved. Based on the above problems, this paper designs a manipulator control system based on machine vision theory and orthogonal parallel six-dimensional force sensor to meet the working requirements of manipulator in high-precision environment. Systems hardware are consisted by machine vision structure and six dimensions of force sensor. The practical application effect of the model was verified by collision detection experiment. The relevant research can provide theoretical guidance and practical reference for the research of manipulator control field. Dance and practical application reference for the research of manipulator control field.

Dual-Polarized Reconfigurable Metasurface for Multifunctional Control of Electromagnetic Waves

This article presents a reconfigurable multifunctional metasurface (RMM) with independent control of orthogonally polarized waves. Each meta-atom of RMM has four varactor diodes (two sets of orthogonal parallel diodes) connected and voltage biased. The voltage difference of the two sets of parallel varactor diodes is a constant. Thus, the orthogonally polarized reflected wave can be tuned independently. Unlike in other reported voltage-controlled RMMs, in the developed RMM, biasing voltages can be applied in one direction only. A tunable range from 7.2 to 7.8 GHz can be achieved. Two functionalities of the proposed RMM, namely, beam steering and polarization conversion, are demonstrated numerically and experimentally. Beam steering can be independently achieved in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${x}-/y$ </tex-math></inline-formula> -directions when the incident plane wave is an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x-/y$ </tex-math></inline-formula> -polarized plane wave. For an arbitrary linear polarized incident plane wave, the decomposed orthogonally polarized waves can also be reflected toward two predefined directions based on the dual-polarized independent tunability of the proposed design. As for polarization conversion, the reflected waves can be flexibly switched among linear-to-orthogonal (LP-to-XP), linear-to-circular, and linear-to-elliptical polarizations in the operating frequencies depending on the phase requirement. The polarization conversion ratio is up to 90% for LP-to-XP polarization and the axial ratio is smaller than 3 dB for linear-to-circular polarizations.

SLA-Based Orthogonal Parallel Detection of Global Rotationally Coherent Lagrangian Vortices

Abstract In this paper, we present a highly effective orthogonal parallel algorithm for identifying global rotationally coherent Lagrangian vortices (RCLVs) in heterogeneous systems and a long-time-scale global sea level anomaly (SLA)-based RCLVs product. First, a many-core parallel computing method is used to accelerate the Lagrangian-averaged vorticity deviation (LAVD) computing process. The computation is approximately 8000 times faster than that of a previous method. Second, the global LAVD field is divided into several regions. These regions are searched with a multiprocess CPU parallel pool to identify simultaneously RCLVs. All the identified RCLVs in these regions are merged seamlessly into a global eddy map. The algorithm improves the global RCLV identification efficiency, making the proposed method approximately 20 times faster than a single-threaded method. The LAVD many-core computing method and the RCLV multiprocess parallel method are orthogonally combined. The resulting algorithm is at least 500 times faster than previous nonparallel methods, making the computing of global RCLVs feasible. Third, the advection of Lagrangian particles in RCLVs and Eulerian eddies is analyzed to demonstrate the material coherence of RCLVs and the reliability of our algorithm. Finally, a global RCLVs product from 1993 to 2019 containing 52 567 eddies is produced with a 90-day time interval. This is the first time that a long-time-scale global Lagrangian eddy product has been presented.

Integration modeling and control of a 12-degree-of-freedom macro–micro dual parallel manipulator

Parallel manipulator systems with large workspace and high-accuracy positioning are attractive for a variety of accuracy engineering applications. In this article, a new 12-DOF macro–micro dual parallel manipulator is presented, which comprises a 6-PSU macro symmetrical parallel manipulator and a 6-SPS micro orthogonal parallel manipulator. This novel mechanism can not only realize a large range of movement but also accurate positioning. To achieve high-accuracy control, a macro–micro integrated model of the macro–micro dual parallel mechanism is proposed, including a mechanical system model and drive system model. Aiming at the trajectory planning for a multi-degree-of-freedom (DOF) manipulator, a smooth optimization trajectory planner for the 12-DOF macro–micro dual parallel manipulator is presented to realize smooth trajectory generation. A high-accuracy motion controller combining feedback and feedforward is developed based on the drive system model. Finally, the experiment well validates the correctness of the integrated model and motion control algorithm and reveals that the proposed mechanism is expected to be adopted into micro scale manipulations.

THE INFLUENCE OF THE CHARACTERISTICS VARIATIONS OF THE CONCENTRATING PLANT CONTROL OBJECT ON THE IDENTIFICATION RESULTS USING THE HAMMERSTEIN MODEL

As a result of the identification based on the Hammerstein model of objects of the first stage of iron ore magnetic separation, the adequacy of the model is obtained. All results of the testing of the developed identification algorithms show that the subsystem of identification of the automated process control systems of processing plants based on the Hammerstein hybrid model allows to carry out satisfactory identification of objects and, as a consequence, to improve the quality of technological processes. The study of the influence of the coefficient of various typical links on the results of identification using orthogonal parallel and parallel-recursive Hammerstein models showed that these models allow considering the differences in the properties of identifiable objects adequately.

Antiphase Oscillations in the Time-Resolved Spin Structure Factor of a Photoexcited Mott Insulator.

Motivated by the recent development of time-resolved resonant-inelastic x-ray scattering (TRRIXS) in photoexcited antiferromagnetic Mott insulators, we numerically investigate momentum-dependent transient spin dynamics in a half-filled Hubbard model on a square lattice. After turning off a pumping photon pulse, the intensity of a dynamical spin structure factor temporally oscillates with frequencies determined by the energy of two magnons in the antiferromagnetic Mott insulator. We find an antiphase behavior in the oscillations between two orthogonal momentum directions, parallel and perpendicular to the electric field of a pump pulse. The phase difference comes from the B_{1g} channel of the two-magnon excitation. Observing the antiphase oscillations will be a big challenge for TRRIXS experiments when their time resolution will be improved by more than an order of magnitude.

Modeling and Analysis of Stochastic Mobile-Edge Computing Wireless Networks

To realize the vision of the Internet of Things (IoT), mobile-edge computing (MEC) has recently emerged as a promising paradigm to meet the computation demand from mobile users (MUs). In this article, we study the network performance in large-scale stochastic MEC wireless networks, where the tasks can be computed locally by the local computation capabilities (LCCs) or be offloaded to MEC servers for edge computing. To this end, a MEC network is modeled featuring random node distribution, dynamic task requests, orthogonal frequency-division multiple access, task retransmission, and parallel computing in MEC servers. Given the model, a 2-D discrete-time Markov chain is first adopted to characterize the task execution process, including local computing and task offloading. Based on the coupling between communication and computing, the average outage probability of the task transmission and the average MEC computation load are derived by integrating the stochastic geometry and queuing theory. Furthermore, by jointly analyzing the local computation latency, transmission latency, and edge computation latency, we derive the average end-to-end latency of the task execution. Our results show that the LCCs in MUs can improve the network performance, including communication and computation performance, in stochastic MEC networks. In addition, useful guidelines for MEC network provisioning and planning are provided to avoid either the local computing or the task offloading being the latency performance bottleneck.

The importance of axonal directions in the brainstem injury during neurosurgical interventions.

Brainstem, which connects the distal part of the brain and the spinal cord, contains main motor and sensory nerves and facilitates communication between the cerebrum, cerebellum, and spinal cord. Due to the complicated anatomy and neurostructure of brainstem, surgical interventions to resect brainstem tumors are particularly challenging, and new approaches to reduce the risk of surgical brain injury are of utmost importance. Although previous studies have investigated the structural anisotropy of brain white matter, the effect of axonal fibers on the mechanical properties of white matter has not yet been fully understood. The current study aims to compare the effect of axonal orientation on changes in material properties of brainstem under large deformations and failure through a novel approach. Using diffusion tensor imaging (DTI) on ex-vivo bovine brains, we determined the orientation of axons in brainstem. We extracted brainstem samples in two orthogonal directions, parallel and perpendicular to the axons, and subjected to uniaxial tension to reach the failure at loading rates of 50mm/min and 150mm/min. The results showed that the tearing energy and failure strain of samples with axons parallel to the force direction were approximately 1.5 times higher than the samples with axons perpendicular to the force direction. The results also revealed that as the sample's initial length increases, its failure strain decreases. These results emphasize the importance of the axon orientation in the mechanical properties of brainstem, and suggest that considering the directional-dependent behavior for this tissue could help to propose new surgical interventions for reducing the risk of injury during tumor resection.

Structural Anisotropy vs. Mechanical Anisotropy: The Contribution of Axonal Fibers to the Material Properties of Brain White Matter.

Brain's micro-structure plays a critical role in its macro-structure material properties. Since the structural anisotropy in the brain white matter has been introduced due to axonal fibers, considering the direction of axons in the continuum models has been mediated to improve the results of computational simulations. The aim of the current study was to investigate the role of fiber direction in the material properties of brain white matter and compare the mechanical behavior of the anisotropic white matter and the isotropic gray matter. Diffusion tensor imaging (DTI) was employed to detect the direction of axons in white matter samples, and tensile stress-relaxation loads up to 20% strains were applied on bovine gray and white matter samples. In order to calculate the nonlinear and time-dependent properties of white matter and gray matter, a visco-hyperelastic model was used. The results indicated that the mechanical behavior of white matter in two orthogonal directions, parallel and perpendicular to axonal fibers, are significantly different. This difference indicates that brain white matter could be assumed as an anisotropic material and axons have contribution in the mechanical properties. Also, up to 15% strain, white matter samples with axons parallel to the force direction are significantly stiffer than both the gray matter samples and white matter samples with axons perpendicular to the force direction. Moreover, the elastic moduli of white matter samples with axons both parallel and perpendicular to the loading direction and gray matter samples at 15-20% strain are not significantly different. According to these observations, it is suggested that axons have negligible roles in the material properties of white matter when it is loaded in the direction perpendicular to the axon direction. Finally, this observation showed that the anisotropy of brain tissue not only has effects on the elastic behavior, but also has effects on the viscoelastic behavior.

Root Based Optimization Algorithm for Task-Oriented Structural Design of a Multi-Axial Road Test Rig

A novel root based optimization algorithm (ROA), which mimics the proliferation of plant roots, is proposed to evaluate the performances of a multi-axial road test rig over a prescribed workspace. Plant roots have developed complex behavior patterns to search for nutrients in the soil and even exhibit swarm intelligence. The growing roots can adapt their actions such as elongation, branching, and tropistic movement according to the environment. During the process of foraging for water and nutrients, the adaptive growth behavior of roots can be simulated to tackle the optimization problem. The efficiency of the proposed ROA has been validated by comparing it with well-known intelligent algorithms using classical and IEEE CEC 2019 benchmark functions. Computational results indicate that ROA outperforms other algorithms to search a global optimum on several benchmarks. Furthermore, the results are tested with nonparametric statistical methods, e.g., Wilcoxon rank-sum test. Besides, ROA is applied to the optimal dimensioning synthesis of the multi-axial road test rig (MRTR) based on the orthogonal 6-RSS parallel manipulator to promote the device's performance. The inverse kinematics of the multi-axial road test rig based on the asymmetrical orthogonal 6-RSS parallel mechanism is analyzed in detail. Applying the achieved dimensionless Jacobian, the performance criteria involving the global isotropy index, the force/velocity transmissibility index, the decoupling index are established. By simultaneously taking account the proposed criteria of performance, structural optimization is carried out resorting to ROA. Finally, a set of optimized dimensional parameters is obtained. The practical application further illustrates that ROA has the potential to deal with complex optimization problems.

Geometrically nonlinear refined shell theories by Carrera Unified Formulation

In this work, a unified formulation of full geometrically nonlinear refined shell theory is developed for the accurate analysis of highly flexible shell structures. The tensor calculus is utilized to explicitly derive the linear and nonlinear differential operator matrices of the geometrical relation in the orthogonal parallel curvilinear coordinate system. By employing the Carrera Unified Formulation (CUF), various kinematics of two-dimensional shell structures are consistently formulated via an appropriate index notation and a generalized expansion of the primary variables by arbitrary functions in the thickness direction, leading to lower- to higher-order shell models with only pure displacement variables. Furthermore, the principle of virtual work and a finite element approximation are exploited to straightforwardly formulate the nonlinear governing equations in a total Lagrangian approach. Particularly, the path-following Newton–Raphson linearization method based on the arc-length constraint is used to deal with the full geometrically nonlinear problem. Independent of the theory approximation order, the forms of the fundamental nuclei of the secant and tangent stiffness matrices of the unified shell element are formulated via the CUF and the three-dimensional Green-Lagrange strain components. Numerical assessments and comparisons of the present results with those provided in the literature for popular benchmark problems involving different metallic shell structures are found to be excellent and demonstrate the capabilities of the developed CUF shell model to predict the post-buckling, large-deflection, snap-through and snap-back nonlinear responses with high accuracy.

Error analysis of the orthogonal parallel calibration device for six-axis heavy force sensor

An orthogonal parallel mechanism is employed to design the calibration device for six-axis heavy force sensor. The relationship between the input and output is proposed. The kinematics error of the orthogonal parallel mechanism is analyzed. The influence of the hinges and the electric cylinders on the calibration accuracy is calculated. The fixture positioning error is analyzed. All the results provide the theory evidence for the manufacture and assembling to reduce the calibration error.