Orientation Constraints Research Articles

Adaptive orientational beamforming techniques for narrowband interference rejection

In this paper, the adaptive theory of the orientational beamforming (OBF) system is investigated. Three adaptive OBF algorithms, namely the orientational maximum signal-to-interference-plus-noise ratio (O-MSINR), the orientational linearly constrained minimum variance (O-LCMV), and the orientational generalized sidelobe canceller (O-GSC) algorithms, are proposed to reject narrowband interferences (NBIs) and recover the desired ultra-wideband (UWB) signal in the OBF system. They are developed by applying adaptive techniques in conventional directional beamforming systems to the OBF system, taking into account the similarities and differences between the OBF system and the conventional beamforming system. These algorithms are constructed on the orientation dimension, and orientational constraints instead of directional constraints are used to guarantee an orientational gain. Therefore, they are independent of signal directions. This perfectly solves the problem when an NBI has the same direction as the desired UWB signal, which current adaptive beamforming algorithms cannot handle. If all the NBIs have the same center frequency, the three algorithms work effectively regardless of the number of NBIs. If all the NBIs have different center frequencies, the O-LCMV and O-GSC algorithms outperform the O-MSINR algorithm. Simulation results show that the proposed algorithms significantly reduce the bit error rates as compared with the original OBF system.

Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia.

MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.

Application of the Improved Grey Wolf Algorithm in Spacecraft Maneuvering Path Planning

In many space missions, spacecraft are required to have the ability to avoid various obstacles and finally reach the target point. In this paper, the path planning of spacecraft attitude maneuver under boundary constraints and pointing constraints is studied. The boundary constraints and orientation constraints are constructed as finite functions of path evaluation. From the point of view of optimal time and shortest path, the constrained attitude maneuver problem is reduced to optimal time and path solving problem. To address this problem, a metaheuristic maneuver path planning method is proposed (cross-mutation grey wolf algorithm (CMGWO)). In the CMGWO method, we use angular velocity and control torque coding to model attitude maneuver, which increases the difficulty of solving the problem. In order to deal with this problem, the grey wolf algorithm is used for mutation and evolution, so as to reduce the difficulty of solving the problem and shorten the convergence time. Finally, simulation analysis is carried out under different conditions, and the feasibility and effectiveness of the method are verified by numerical simulation.

Instant Orientation Correction Strategy: Holonomic System-Based Decentralized Control for Nonholonomic Agents

This study proposes an instant orientation correction strategy to perform an orientation alignment-based formation control applicable to nonholonomic agents. Generally, an orientation alignment-based formation control cannot be applied to nonholonomic agents with orientation constraints because it is originally a protocol for holonomic agents. Therefore, we improved the orientation alignment-based formation control using an instant orientation correction strategy that modifies the local frame of the nonholonomic agents. To examine the effect of the proposed method, simulations and experiments using representative parameters were conducted for unicycle-modeled nonholonomic agents. As a result, nonholonomic agents could execute a holonomic system-based control law by applying the proposed correction strategy. The simulation confirmed the change in the convergence time and the cumulative error of the angular velocity according to the number of agents and the updated step size of the local desired position. As the updated step size increased, the cumulative error of the angular velocity tended to increase (0.3 rad/s~0.4rad/s). Also, the convergence time was not dramatically affected by the update step size and the number of the agents (~400 converge step).

Active depletion torque between two passive rods.

The active depletion torque experienced by two anisotropic objects in an active bath is a conceptional generalization of the equilibrium entropic torque. Using Brownian dynamics simulations, we compute the active depletion torque suffered by two passive rods immersed in an ensemble of active Brownian particles. Our results demonstrate that the active depletion torque is qualitatively different from its passive counterpart. Interestingly, we find that the active depletion torque can be greatly affected by the external constraint applied on the rotational degree of freedom of the rods, and even the direction may be changed with the orientational constraint, which is in contrast to the equilibrium depletion torque. The main reason for the remarkable features of the active depletion torque is that the active particles can significantly accumulate in the vicinity of the rods due to persistent self-propulsion, which is sensitively dependent on the constraint strength and the rod configurations. Our findings could be relevant for understanding the self-assembly and dynamics of anisotropic macromolecules in living environments.

Linear and nonlinear shelf space allocation problemswith vertical and horizontal bands

Aim/purpose – Shelf space is one of the most important tools for attracting customers’ attention in a retail store. This paper aims to develop a practical shelf space allocation model with visible vertical and horizontal categories. and formulate it in linear and non- -linear forms. Design/methodology/approach – The research is mainly based on operational research. Simulation, mathematical optimization, and linear and nonlinear programming methods are mainly used. Special attention is given to the decision variables and constraints. Changing the dimensioning of the decision variables results in an improvement in the formulation of the problem, which in turn allows for obtaining an optimal solution. Findings – A comparison of the developed shelf space allocation models with visible vertical and horizontal categories in linear and nonlinear forms is presented. The compu- tational experiments were performed with the help of CPLEX solver, which shows that the optimal solution of the linear problem formulation was obtained within a couple of seconds. However, a nonlinear form of this problem found the optimal solution only in 19 out of 45 instances. An increase in the time limits slightly improves the performance of the solutions of the nonlinear form. Research implications/limitations – The main implication of research results for sci- ence is related to the possibility of determining an optimal solution to the initially formu- lated nonlinear shelf space allocation problem. The main implication for practice is to take into consideration the practical constraints based on customers’ requirements. The main limitations are the lack of storage conditions and holding time constraints. Originality/value/contribution – The main contribution is related to developing math- ematical models that consider simultaneous categorization of products vertically, based on one characteristic, and horizontally, based on another characteristic. Contribution is also related to extending the shelf space allocation theory with the shelf space allocation problem model in relation to four sets of constraints: shelf constraints, product con- straints, orientation constraints, and band constraints. Keywords: Retailing, decision making/process, merchandising, shelf space allocation, planogram. JEL Classification: C61, L81.

Heuristics for shelf space allocation problem with vertical and horizontal product categorization

In this research, we proposed a practical shelf space allocation model with the vertical and horizontal categorization of products. Five groups of constraints, such as shelf, product, multi-shelves, orientation and band constraints, are implemented in the model. We proposed two heuristics to solve the retailer's profit maximization problem. The experiments were performed on small instances, and the solution was compared to the optimal solution found by the CPLEX solver. The experiments proved that heuristics could find the optimal solution in most cases (14/20 for heuristics H1 and 16/20 for heuristics H2) without checking the whole solutions space. The lowest solution quality is 97.68% which shows that the heuristics allow finding high-quality near-optimal solutions. Therefore the steps implemented in the proposed heuristics should be used in more complicated shelf space allocation problems for which it is impossible to find a solution by the solvers.

Entre effacement et étalement ce que peut Merleau-Ponty pour le partage hétéronormé de l’espace

Building on Merleau-Ponty’s recognition of the mutually expressive relation between the body and the space it occupies, I borrow from queer and feminist phenomenologies to reflect on the spatiality of subjects constrained to heterosexuality – a constraint that functions as a common ground, always already present, of the kind that Merleau-Ponty argued was constitutive of subject/world relations. If it is the case, as many feminist theorists after Adrienne Rich argued, that the patriarchal norm orients us early on toward the opposite gender, then there is much to be learned from studying the notion of feminine space and the erasure of the subject in this space -an erasure that has been largely discussed within recent feminist phenomenological work, notably in relation to the contrasting extension of men in space –, particularly as both are established in relation to male desire. Our aim is to argue that because it is temporal, and because it involves sedimentation and habit, the study of this orientational constraint through the lens of Merleau-Ponty could allow us to open up the future of gendered norms, and, through this, of gendered practices of sharing space.

Research on the Orientation Error of the Translational Cable-Driven Parallel Robots

Abstract Parallel cables are widely used in cable-driven parallel robots (CDPR) to provide constraints to the end-effector and to realize translational degrees-of-freedom(DOFs). However, when there are structural errors, parallel cables become no longer parallel and will cause orientation errors of the end-effector, which cannot be compensated by kinematic calibration. In this paper, the orientation assurance method is studied considering a 3DOFs translational CDPR. First, the kinematic model and error mapping model of the CDPR are established by using the closed-loop method, considering the pulley radius. Second, the influence of the structural parameters errors on the error of the end-effector is analyzed with the sensitivity index, which establishes a theoretical basis for the simplification of the accuracy synthesis process. Third, the design tolerances of the cable connection points are determined through accuracy synthesis, which is implemented with the genetic algorithm considering the optimal manufacturing cost and the orientation constraints of the end-effector. Finally, to reduce the influence of cable length error, the method of adjusting the initial pose was proposed and studied, which is verified as an effective approach to reduce the orientation error.

Micro Electrical Discharge Machining Thermal Effect on Micro-Cracks Generation on Silicon Material

Various novel 3D micro machining technologies were researched and developed for silicon micro mechanical system fabrication. Micro EDM is one of them. The material removal mechanism is thermal sparking erosion and is completely independent with regards to the crystalline orientation of silicon, therefore there is no orientation constraint in processing the complex 3D geometry of silicon wafers. As thermal sparking implied, the process features local area high temperature melting and evaporating, and this characteristic has an adverse side-effect on the sparked surface integrity. One important concern is the generation of micro cracks, which would provide an adverse effect on the fatigue life of the micro feature element made of silicon. For this consideration, in this paper, with the experiment and SEM picture analysis approach, the author explored the micro crack generation characteristics on mono crystalline silicon wafers under micro EDM with available sparking energies and on the different crystal orientation surface machining. The generation of micro cracking is not only related with the sparking energy but also related with the crystalline orientation. The {100} orientation is the strongest surface to resist crack generation. For a strong-doped P type silicon wafer, there exists a maximum crack energy threshold. If single sparking energy is over this threshold, micro cracks unavoidably would be generated on any orientation surface. Two types of chemical etching post processes that can remove cracks on sparked surfaces are also tested and discussed.

Global properties of regulatory sequences are predicted by transcription factor recognition mechanisms

BackgroundMammalian genomes contain millions of putative regulatory sequences, which are delineated by binding of multiple transcription factors. The degree to which spacing and orientation constraints among transcription factor binding sites contribute to the recognition and identity of regulatory sequence is an unresolved but important question that impacts our understanding of genome function and evolution. Global mechanisms that underlie phenomena including the size of regulatory sequences, their uniqueness, and their evolutionary turnover remain poorly described.ResultsHere, we ask whether models incorporating different degrees of spacing and orientation constraints among transcription factor binding sites are broadly consistent with several global properties of regulatory sequence. These properties include length, sequence diversity, turnover rate, and dominance of specific TFs in regulatory site identity and cell type specification. Models with and without spacing and orientation constraints are generally consistent with all observed properties of regulatory sequence, and with regulatory sequences being fundamentally small (~ 1 nucleosome). Uniqueness of regulatory regions and their rapid evolutionary turnover are expected under all models examined. An intriguing issue we identify is that the complexity of eukaryotic regulatory sites must scale with the number of active transcription factors, in order to accomplish observed specificity.ConclusionsModels of transcription factor binding with or without spacing and orientation constraints predict that regulatory sequences should be fundamentally short, unique, and turn over rapidly. We posit that the existence of master regulators may be, in part, a consequence of evolutionary pressure to limit the complexity and increase evolvability of regulatory sites.

A de novo protein structure prediction by iterative partition sampling, topology adjustment and residue-level distance deviation optimization.

With the great progress of deep learning-based inter-residue contact/distance prediction, the discrete space formed by fragment assembly cannot satisfy the distance constraint well. Thus, the optimal solution of the continuous space may not be achieved. Designing an effective closed-loop continuous dihedral angle optimization strategy that complements the discrete fragment assembly is crucial to improve the performance of the distance-assisted fragment assembly method. In this article, we proposed a de novo protein structure prediction method called IPTDFold based on closed-loop iterative partition sampling, topology adjustment and residue-level distance deviation optimization. First, local dihedral angle crossover and mutation operators are designed to explore the conformational space extensively and achieve information exchange between the conformations in the population. Then, the dihedral angle rotation model of loop region with partial inter-residue distance constraints is constructed, and the rotation angle satisfying the constraints is obtained by differential evolution algorithm, so as to adjust the spatial position relationship between the secondary structures. Finally, the residue distance deviation is evaluated according to the difference between the conformation and the predicted distance, and the dihedral angle of the residue is optimized with biased probability. The final model is generated by iterating the above three steps. IPTDFold is tested on 462 benchmark proteins, 24 FM targets of CASP13 and 20 FM targets of CASP14. Results show that IPTDFold is significantly superior to the distance-assisted fragment assembly method Rosetta_D (Rosetta with distance). In particular, the prediction accuracy of IPTDFold does not decrease as the length of the protein increases. When using the same FastRelax protocol, the prediction accuracy of IPTDFold is significantly superior to that of trRosetta without orientation constraints, and is equivalent to that of the full version of trRosetta. The source code and executable are freely available at https://github.com/iobio-zjut/IPTDFold. Supplementary data are available at Bioinformatics online.

Designing 2D and 3D Non-Orthogonal Frame Fields

We present a method for direction field design on surface and volumetric meshes supporting non-orthogonality. Our approach is a generalization of the representation of 3D cross fields in spherical harmonic basis. As such it induces a geometrically meaningful measure of smoothness, allows orthogonality control by a simple parameter and enables orientation constraints of a single direction. To the best of our knowledge this is the first work to propose non-orthogonal 3D frame field design. We demonstrate the applicability of our method to generate anisotropic quadrangular and hexahedral meshes which are particularly useful for remeshing CAD models.

EXPLOITING MULTI-CAMERA CONSTRAINTS WITHIN BUNDLE BLOCK ADJUSTMENT: AN EXPERIMENTAL COMPARISON

Abstract. The growing deployment of multi-head camera systems encouraged the emergence of specific processing algorithms, able to face the challenges posed by slanted view geometry. Such multi-camera systems are rigidly tied by their manufacturers hence the exploitation of this internal constraint should be further exploited. Several approaches have been proposed to deal with orientation constraints, with the aim of reducing the number of unknowns, computational time and possibly improve the accuracy. In this paper we compare the results provided by publicly available implementations in order to further investigate the advantages of enforcing relative orientation constraints for aerial and terrestrial triangulation of multi-head camera systems. Data from a Leica CityMapper and a Stereopolis-Ladybug are considered, reporting how constrained solution can improve accuracy with respect to traditional (unconstrained) bundle block adjustment solutions.

On Perpendicular Curve-Based Model-Less Control Considering Incomplete Orientation Constraint

With the emerging trend of soft and reconfigurable robots, model-less control methods become more and more popular. However, the incomplete orientation constraint (IOC) remains a challenge for the existing model-less control methods, due to the nonlinear structure of the rotation group. To address the IOC problems, in this article, we develop a novel perpendicular curve-based approach, which provides a closed-form expression of the shortest path from current orientation to the target geodesic in SO(3). Based on our approach, we propose a new model-less robot motion control framework considering the IOC. Compared with the existing methods, the proposed method can easily accommodate any robots with four or more actuators regardless if they are functionally redundant or not. The proposed method has been conducted on a four-DOF reconfigurable manipulator with an unknown kinematic model, which is the most challenging case since the dimension of the configurational space is smaller than the dimension of the task space. The simulation and physical experiment results demonstrate the effectiveness and advantages of the proposed method.

Static postural transition-based technique and efficient feature extraction for sensor-based activity recognition

Abstract Smartphone sensor-based activity recognition seeks broad, high-level knowledge about human behaviors from multitudes of low-level sensor readings, and makes considerable headway in healthcare domain. Our primary contribution is to study the effective pre-processing technique and the extraction of robust features for the classification of sensor data for human activity recognition (HAR). In the pre-processing stages, we investigated multiple filtering parameters for reducing waveform delay, smartphone orientation constraint by introducing magnitude and jerk-based features, and optimum window length for analyzing the trade-off between model performance and latency. Besides, we proposed a feature named “Average Height” that summarizes the average peak to trough distance of the activity and encodes any change of motion for classification. We also proposed two feature selection techniques for offline and real-time faster activity recognition, and analyzed the impact of different feature sets on classifying different activities. Moreover, after performing the classification with optimized hyperparameters, we proposed a Static Postural Transition-based Post-Processing (SPTPP) technique. This post-processing approach analyzes the existence of postural transition from previous window activity to current window activity, and helps to improve the model output by analyzing the posture change. The impact of our proposed techniques are demonstrated on three benchmark datasets named HASC, HAR, and HAPT, where we obtained the state-of-the-art results. We used HASC dataset for optimizing model parameters in different stages, and explored HAR and HAPT datasets as test-beds to verify our optimizations and postprocessing technique.

Graphene-Nanorod Enhanced Quasi-Van Der Waals Epitaxy for High Indium Composition Nitride Films.

The nitride films with high indium (In) composition play a crucial role in the fabrication of In-rich InGaN-basedoptoelectronic devices. However, a major limitation is In incorporation requiring a low temperature during growth at the expense of nitride dissociation. Here, to overcome this limitation, a strain-modulated growth method, namely the graphene (Gr)-nanorod (NR) enhanced quasi-van der Waals epitaxy, is proposed to increase the In composition in InGaN alloy. The lattice transparency of Gr enables constraint of in-plane orientation of nitride film and epitaxial relationships at the heterointerface. The Gr interlayer together with NRs buffer layer substantially reduces the stress of the GaN film by 74.4%, from 0.9 to 0.23GPa, and thus increases the In incorporation by 30.7%. The first principles calculations confirm that the release of strain accounts for the dramatic improvement. The photoluminescence peak of multiple quantum wells shifts from 461 to 497nm and the functionally small-sized cyan light-emitting diodes of 7×9mil2 are demonstrated. These findings provide an efficient approach for the growth of In-rich InGaN film and extend the applications of nitrides in advanced optoelectronic, photovoltaic, and thermoelectric devices.

Solid-State NMR of Membrane Proteins in Lipid Bilayers: To Spin or Not To Spin?

Membrane proteins mediate a plethora of cellular functions and represent important targets for drug development. Unlike soluble proteins, membrane proteins require native-like environments to fold correctly and be active. Therefore, modern structural biology techniques have aimed to determine the structure and dynamics of these membrane proteins at physiological temperature and in liquid crystalline lipid bilayers. With the flourishing of new NMR methodologies and improvements in sample preparations, magic angle spinning (MAS) and oriented sample solid-state NMR (OS-ssNMR) spectroscopy of membrane proteins is experiencing a new renaissance. Born as antagonistic approaches, these techniques nowadays offer complementary information on the structural topology and dynamics of membrane proteins reconstituted in lipid membranes. By spinning biosolid samples at the magic angle (θ = 54.7°), MAS NMR experiments remove the intrinsic anisotropy of the NMR interactions, increasing spectral resolution. Internuclear spin interactions (spin exchange) are reintroduced by RF pulses, providing distances and torsion angles to determine secondary, tertiary, and quaternary structures of membrane proteins. OS-ssNMR, on the other hand, directly detects anisotropic NMR parameters such as dipolar couplings (DC) and anisotropic chemical shifts (CS), providing orientational constraints to determine the architecture (i.e., topology) of membrane proteins relative to the lipid membrane. Defining the orientation of membrane proteins and their interactions with lipid membranes is of paramount importance since lipid-protein interactions can shape membrane protein conformations and ultimately define their functional states.In this Account, we report selected studies from our group integrating MAS and OS-ssNMR techniques to give a comprehensive view of the biological processes occurring at cellular membranes. We focus on the main experiments for both techniques, with an emphasis on new implementation to increase both sensitivity and spectral resolution. We also describe how the structural constraints derived from both isotropic and anisotropic NMR parameters are integrated into dynamic structural modeling using replica-averaged orientational-restrained molecular dynamics simulations (RAOR-MD). We showcase small membrane proteins that are involved in Ca2+ transport and regulate cardiac and skeletal muscle contractility: phospholamban (PLN, 6 kDa), sarcolipin (SLN, 4 kDa), and DWORF (4 kDa). We summarize our results for the structures of these polypeptides free and in complex with the sarcoplasmic reticulum (SR) Ca2+-ATPase (SERCA, 110 kDa). Additionally, we illustrate the progress toward the determination of the structural topology of a six transmembrane protein associated with succinate and acetate transport (SatP, hexamer 120 kDa). From these examples, the integrated MAS and OS-ssNMR approach, in combination with modern computational methods, emerges as a way to overcome the challenges posed by studying large membrane protein systems.

Multi-agent path planning with nonlinear restrictions

This paper presents a novel simplified mathematical modeling that can solve a path planning problem comprising three agents in a triangular formation. The problem is modeled to optimize the trajectories of the agents and to minimize the distances traveled. The trajectories are obtained in a way that deviates them from fixed obstacles whose dimensions are known. Furthermore, geometry and orientation constraints of the formation of the multi-agent are imposed. Heuristics methods such as the Genetic Algorithm, Differential Evolution and Particle Swarm Optimization are applied to solve the non-linear algebraic equations which represent the system. Comparisons are presented among the results of the different methods highlighting the processing time and the convergence to the global minimum solution. The results prove that all the algorithms can be applied to the path planning problem with constraints. The Particle Swarm Optimization method presents the lowest processing time for all simulated cases. However, the Differential Evolution method is more robust than the others when searching for the global minimum solution.

Determination of Configuration and Conformation of a Reserpine Derivative with Seven Stereogenic Centers Using Molecular Dynamics with RDC-Derived Tensorial Constraints*.

NMR‐based determination of the configuration of complex molecules containing many stereocenters is often not possible using traditional NOE data and coupling patterns. Making use of residual dipolar couplings (RDCs), we were able to determine the relative configuration of a natural product containing seven stereocenters, including a chiral amine lacking direct RDC data. To identify the correct relative configuration out of 32 possible ones, experimental RDCs were used in three different approaches for data interpretation: by fitting experimental data based singular value decomposition (SVD) using a single alignment tensor and either (i) a single conformer or (ii) multiple conformers, or alternatively (iii) using molecular dynamics simulations with tensorial orientational constraints (MDOC). Even though in all three approaches one and the same configuration could be selected and clear discrimination between possible configurations was achieved, the experimental data was not fully satisfied by the methods based on single tensor approaches. While these two approaches are faster, only MDOC is able to fully reproduce experimental results, as the obtained conformational ensemble adequately covers the conformational space necessary to describe the molecule with inherent flexibility.