Sequential Monte Carlo Methods for System Identification

One of the key challenges in identifying nonlinear and possibly non-Gaussian state space models (SSMs) is the intractability of estimating the system state. Sequential Monte Carlo (SMC) methods, such as the particle filter (introduced more than two decades ago), provide numerical solutions to the nonlinear state estimation problems arising in SSMs. When combined with additional identification techniques, these algorithms provide solid solutions to the nonlinear system identification problem. We describe two general strategies for creating such combinations and discuss why SMC is a natural tool for implementing these strategies.Comment: In proceedings of the 17th IFAC Symposium on System Identification (SYSID). Added cover pag

Size Matters: Problems and Advantages Associated with Highly Miniaturized Sensors

There is no doubt that the recent advances in nanotechnology have made it possible to realize a great variety of new sensors with signal transduction mechanisms utilizing physical phenomena at the nanoscale. Some examples are conductivity measurements in nanowires, deflection of cantilevers and spectroscopy of plasmonic nanoparticles. The fact that these techniques are based on the special properties of nanostructural entities provides for extreme sensor miniaturization since a single structural unit often can be used as transducer. This review discusses the advantages and problems with such small sensors, with focus on biosensing applications and label-free real-time analysis of liquid samples. Many aspects of sensor design are considered, such as thermodynamic and diffusion aspects on binding kinetics as well as multiplexing and noise issues. Still, all issues discussed are generic in the sense that the conclusions apply to practically all types of surface sensitive techniques. As a counterweight to the current research trend, it is argued that in many real world applications, better performance is achieved if the active sensor is larger than that in typical nanosensors. Although there are certain specific sensing applications where nanoscale transducers are necessary, it is argued herein that this represents a relatively rare situation. Instead, it is suggested that sensing on the microscale often offers a good compromise between utilizing some possible advantages of miniaturization while avoiding the complications. This means that ensemble measurements on multiple nanoscale sensors are preferable instead of utilizing a single transducer entity

Polymer brushes in solid-state nanopores form an impenetrable entropic barrier for proteins

Polymer brushes are widely used to prevent the adsorption of proteins, but the mechanisms by which they operate have remained heavily debated for many decades. We show conclusive evidence that a polymer brush can be a remarkably strong kinetic barrier towards proteins by using poly(ethylene glycol) grafted to the sidewalls of pores in 30 nm thin gold films. Despite consisting of about 90% water, the free coils seal apertures up to 100 nm entirely with respect to serum protein translocation, as monitored label-free through the plasmonic activity of the nanopores. The conclusions are further supported by atomic force microscopy and fluorescence microscopy. A theoretical model indicates that the brush undergoes a morphology transition to a sealing state when the ratio between the extension and the radius of curvature is approximately 0.8. The brush-sealed pores represent a new type of ultrathin filter with potential applications in bioanalytical systems

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Marginalizing Gaussian process hyperparameters using sequential Monte Carlo

Gaussian process regression is a popular method for non-parametric probabilistic modeling of functions. The Gaussian process prior is characterized by so-called hyperparameters, which often have a large influence on the posterior model and can be difficult to tune. This work provides a method for numerical marginalization of the hyperparameters, relying on the rigorous framework of sequential Monte Carlo. Our method is well suited for online problems, and we demonstrate its ability to handle real-world problems with several dimensions and compare it to other marginalization methods. We also conclude that our proposed method is a competitive alternative to the commonly used point estimates maximizing the likelihood, both in terms of computational load and its ability to handle multimodal posteriors.Comment: Accepted to the 6th IEEE international workshop on computational advances in multi-sensor adaptive processing (CAMSAP), Cancun, Mexico, December 201

Optical Properties of Nanohole Arrays in Metal–Dielectric Double Films Prepared by Mask-on-Metal Colloidal Lithography

We present the fabrication and optical characterization of plasmonic nanostructures consisting of nanohole arrays in two thin films, a metal and a dielectric. A novel method called mask-on-metal colloidal lithography is used to prepare high aspect ratio holes, providing efficient mass fabrication of stable structures with close to vertical walls and without the need for an adhesion layer under the metal. Our approach for understanding the transmission properties is based on solving the dispersions of the guided modes supported by the two films and calculating the influence from interference. The methodology is generic and can be extended to multilayered films. In particular, the influence from coupling to waveguide modes is discussed. We show that by rational design of structural dimensions it is possible to study only bonding surface plasmons and the associated hole transmission maximum. Further, numerical simulations with the multiple multipole program provide good agreement with experimental data and enable visualization of the asymmetric near-field distribution in the nanohole arrays, which is focused to the interior of the “nanowells”. The refractometric sensitivity is evaluated experimentally both by liquid bulk changes and surface adsorption. We demonstrate how the localized mode provides reasonably good sensitivity in terms of resonance shift to molecular binding inside the voids. Importantly, high resolution sensing can be accomplished also for the surface plasmon mode, despite its extremely low figure of merit. This is accomplished by monitoring the coupling efficiency of light to plasmons instead of conventional sensing which is based on changes in plasmon energy. We suggest that these nanohole structures can be used for studying molecular transport through nanopores and the behavior of molecules confined in volumes of approximately one attoliter

Protein exclusion is preserved by temperature sensitive PEG brushes

Poly(ethylene glycol) (PEG) is widely used in biotechnology-related applications yet its temperature-dependent functionality is not well understood. Here, we use bovine serum albumin (BSA) monomers and cross-linked dimers to directly probe the height of strongly stretched PEG brushes using surface plasmon resonance (SPR) in aqueous solution. Our results show that PEG brush height follows a smooth decrease as a function of increasing temperature commencing near room temperature. Measurements obtained by BSA monomers and dimers are comparable and suggest that BSA effectively probes the leading edge of the brush with minimal penetration into its interior being supported by SPR reflectivity calculations. Further, the BSA-PEG interaction remains largely inert over the entire temperature range. Overall, PEG brushes undergo a smooth conformational transition while fully preserving its protein excluding properties far from the lower critical solution temperature

Simultaneous electrical and plasmonic monitoring of potential induced ion adsorption on metal nanowire arrays

Simultaneous LSPR and electronic sensing of potential induced ion adsorption onto gold nanowire arrays is presented. The formation of a Stern layer upon applying an electrochemical potential generated a complex optical response. Simulation of a lossy atomic layer on the nanowire array using the Multiple Multipole Program (MMP) corresponded very well to the experimentally observed peak position, intensity, and radius of curvature changes. Additionally, a significant voltage-dependent change in the resistance of the gold nanowire array was observed during the controlled formation of the electrical double layer. The results demonstrated that an applied electrochemical potential induces measurable changes in the optical and electrical properties of the gold nanowire surface. This is the first demonstration of combined plasmonic and nanowire resistance-based sensing of a surface process in the literature