Egret Swarm Optimization Algorithm: An Evolutionary Computation Approach for Model Free Optimization.

A novel meta-heuristic algorithm named Egret Swarm Optimization Algorithm (ESOA) is proposed in this paper, which is inspired by two egret species' hunting behavior (Great Egret and Snowy Egret). ESOA consists of three primary components: a sit-and-wait strategy, aggressive strategy as well as discriminant conditions. The learnable sit-and-wait strategy guides the egret to the most probable solution by applying a pseudo gradient estimator. The aggressive strategy uses random wandering and encirclement mechanisms to allow for optimal solution exploration. The discriminant model is utilized to balance the two strategies. The proposed approach provides a parallel framework and a strategy for parameter learning through historical information that can be adapted to most scenarios and has well stability. The performance of ESOA on 36 benchmark functions as well as 3 engineering problems are compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Harris Hawks Optimization (HHO). The result proves the superior effectiveness and robustness of ESOA. ESOA acquires the winner in all unimodal functions and reaches statistic scores all above 9.9, while the scores are better in complex functions as 10.96 and 11.92.

Bio-inspired Machine Learning for Distributed Confidential Multi-Portfolio Selection Problem.

The recently emerging multi-portfolio selection problem lacks a proper framework to ensure that client privacy and database secrecy remain intact. Since privacy is of major concern these days, in this paper, we propose a variant of Beetle Antennae Search (BAS) known as Distributed Beetle Antennae Search (DBAS) to optimize multi-portfolio selection problems without violating the privacy of individual portfolios. DBAS is a swarm-based optimization algorithm that solely shares the gradients of portfolios among the swarm without sharing private data or portfolio stock information. DBAS is a hybrid framework, and it inherits the swarm-like nature of the Particle Swarm Optimization (PSO) algorithm with the BAS updating criteria. It ensures a robust and fast optimization of the multi-portfolio selection problem whilst keeping the privacy and secrecy of each portfolio intact. Since multi-portfolio selection problems are a recent direction for the field, no work has been done concerning the privacy of the database nor the privacy of stock information of individual portfolios. To test the robustness of DBAS, simulations were conducted consisting of four categories of multi-portfolio problems, where in each category, three portfolios were selected. To achieve this, 200 days worth of real-world stock data were utilized from 25 NASDAQ stock companies. The simulation results prove that DBAS not only ensures portfolio privacy but is also efficient and robust in selecting optimal portfolios.

Quantitative theory of integrating sphere throughput: comparison with experiments.

We present a rigorous approach for measuring the throughput of an integrating sphere, from which the so-called sphere multiplier M can be derived. The critical ingredients of this approach are: (i) the transmitted power is measured at the base of an integrating port to avoid non-ideal port effects associated with reflections on the port wall; (ii) to implement this last point, optical fibers are used for light collection, providing a well-defined collection area and numerical aperture; (iii) the angular-dependent fiber throughput and detector sensitivity are determined experimentally and accounted for. We demonstrate in particular that a more realistic theory, accounting for the propagation of skew rays through the fiber, is needed to quantitatively model the fiber effect on the measured sphere throughput. We show experimentally that failure to fulfill these three points produces erroneous results, by as much as 50%. With an accurate experimentally derived sphere multiplier, agreement with theory is then obtained only if realistic ports (with non-zero reflectivity) are assumed. This provides experimental evidence for recent theoretical predictions of the importance of realistic ports [Tang et al., Appl. Opt.57, 1581 (2018)APOPAI0003-693510.1364/AO.57.001581]. Using the same experimental techniques, we also present clear experimental proof of two other predictions from that study: that the angular distribution exiting the port is strongly altered and that the overall port transmittivity is drastically reduced for high aspect ratio ports. This work will provide a solid basis for future quantitative measurements of absolute throughput and for further developments of the theory of integrating spheres.

Acute destruction of the synaptic ribbon reveals a role for the ribbon in vesicle priming.

In vision, balance and hearing, sensory receptor cells translate sensory stimuli into electrical signals whose amplitude is graded with stimulus intensity. The output synapses of these sensory neurons must provide fast signaling to follow rapidly changing stimuli while also transmitting graded information covering a wide range of stimulus intensity and must be able to sustain this signaling for long time periods. To meet these demands, specialized machinery for transmitter release, the synaptic ribbon, has evolved at the synaptic outputs of these neurons. We found that acute disruption of synaptic ribbons by photodamage to the ribbon markedly reduced both sustained and transient components of neurotransmitter release in mouse bipolar cells and salamander cones without affecting the ultrastructure of the ribbon or its ability to localize synaptic vesicles to the active zone. Our results indicate that ribbons mediate both slow and fast signaling at sensory synapses and support an additional role for the synaptic ribbon in priming vesicles for exocytosis at active zones.

Development of new peptide-based tools for studying synaptic ribbon function.

Synaptic ribbons are proteinaceous specialized electron-dense presynaptic structures found in nonspiking sensory cells of the vertebrate nervous system. Understanding the function of these structures is an active area of research (reviewed in Matthews G, Fuchs P. Nat Rev Neurosci 11: 812-822, 2010). Previous work had shown that ribbons could be effectively labeled and visualized using peptides that bind to the synaptic ribbon protein RIBEYE via a PXDLS motif (Zenisek D, Horst NK, Merrifield C, Sterling P, Matthews G. J Neurosci 24: 9752-9759, 2004). Here, we expand on the previous work to develop new tools and strategies for 1) better visualizing synaptic ribbons, and 2) monitoring and manipulating calcium on the synaptic ribbon. Specifically, we developed a new higher-affinity peptide-based label for visualizing ribbons in live cells and two strategies for localizing calcium indicators to the synaptic ribbon.