Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains

Latent Gaussian process (GP) models are widely used in neuroscience to uncover hidden state evolutions from sequential observations, mainly in neural activity recordings. While latent GP models provide a principled and powerful solution in theory, the intractable posterior in non-conjugate settings necessitates approximate inference schemes, which may lack scalability. In this work, we propose cvHM, a general inference framework for latent GP models leveraging Hida-Mat\'ern kernels and conjugate computation variational inference (CVI). With cvHM, we are able to perform variational inference of latent neural trajectories with linear time complexity for arbitrary likelihoods. The reparameterization of stationary kernels using Hida-Mat\'ern GPs helps us connect the latent variable models that encode prior assumptions through dynamical systems to those that encode trajectory assumptions through GPs. In contrast to previous work, we use bidirectional information filtering, leading to a more concise implementation. Furthermore, we employ the Whittle approximate likelihood to achieve highly efficient hyperparameter learning.Comment: Published at ICML 202

Rigidity−Stability Relationship in Interlocked Model Complexes Containing Phenylene-Ethynylene-Based Disubstituted Naphthalene and Benzene

Structural rigidity has been found to be advantageous for molecules if they are to find applications in functioning molecular devices. In the search for an understanding of the relationship between the rigidity and complex stability in mechanically interlocked compounds, the binding abilities of two π-electron-rich model compounds (2 and 4), where rigidity is introduced in the form of phenylacetylene units, toward the π-electron deficient tetracationic cyclophane, cyclobis(paraquat-p-phenylene) (CBPQT^(4+)), were investigated. 1,4-Bis(2-(2-methoxyethoxy)ethoxy)-2,5-bis(2-phenylethynyl)benzene 2 and 1,5-bis(2-(2-methoxyethoxy)ethoxy)- 2,6-bis(2-phenylethynyl)naphthalene 4 were synthesized, respectively, from the appropriate precursor dibromides 1 and 3 of benzene and naphthalene carrying two methoxyethoxyethoxy side chains. The rigid nature of the compounds 2 and 4 is reflected in the reduced stabilities of their 1:1 complexes with CBPQT^(4+). Binding constants for both 2 (100 M^(-1)) and 4 (140 M^(-1)) toward CBPQT^(4+) were obtained by isothermal titration microcalorimetry (ITC) in MeCN at 25 °C. Compounds 1-4 were characterized in the solid state by X-ray crystallography. The stabilization within and beyond these molecules is achieved by a combination of intra- and intermolecular [C-H· · · O], [C-H· · ·π], and [π-π] stacking interactions. The diethyleneglycol chains present in compounds 1-4 are folded as a consequence of both intra- and intermolecular hydrogen bonds. The preorganized structures in both precursors 1 and 3 are repeated in both model compounds 2 and 4. In the structures of compounds 2 and 4, the geometry of the rigid backbone is differentsthe two terminal phenyl groups are twisted with respect to the central benzenoid ring in compound 2 and roughly perpendicular to the plane central naphthalene core in compound 4. To understand the significantly decreased stabilities of these complexes toward rigid guest molecules, relative to more flexible systems, we performed density functional theory (DFT) calculations using the newly developed M06-suite of density functionals. We conclude that the reduced binding abilities are a consequence of electronic and not steric factors, originating from the extended delocalization of the aromatic system

Spin transport and accumulation in the persistent photoconductor Al0.3_{0.3}Ga0.7_{0.7}As

Electrical spin transport and accumulation have been measured in highly Si doped Al0.3Ga0.7As utilizing a lateral spin transport device. Persistent photoconductivity allows for the tuning of the effective carrier density of the channel material in situ via photodoping. Hanle effect measurements are completed at various carrier densities and the measurements yield spin lifetimes on the order of nanoseconds, an order of magnitude smaller than in bulk GaAs. These measurements illustrate that this methodology can be used to obtain a detailed description of how spin lifetimes depend on carrier density in semiconductors across the metal-insulator transition

Effect of hydrogen on the nanomechanical behavior of dual-phase nanocrystalline high-entropy alloy

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Spherical indentation study on incipient plasticity of medium-/high-entropy alloys

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A Thrust Allocation Method for Efficient Dynamic Positioning of a Semisubmersible Drilling Rig Based on the Hybrid Optimization Algorithm

A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP) algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig