Chance, long tails, and inference: a non-Gaussian, Bayesian theory of vocal learning in songbirds

Traditional theories of sensorimotor learning posit that animals use sensory error signals to find the optimal motor command in the face of Gaussian sensory and motor noise. However, most such theories cannot explain common behavioral observations, for example that smaller sensory errors are more readily corrected than larger errors and that large abrupt (but not gradually introduced) errors lead to weak learning. Here we propose a new theory of sensorimotor learning that explains these observations. The theory posits that the animal learns an entire probability distribution of motor commands rather than trying to arrive at a single optimal command, and that learning arises via Bayesian inference when new sensory information becomes available. We test this theory using data from a songbird, the Bengalese finch, that is adapting the pitch (fundamental frequency) of its song following perturbations of auditory feedback using miniature headphones. We observe the distribution of the sung pitches to have long, non-Gaussian tails, which, within our theory, explains the observed dynamics of learning. Further, the theory makes surprising predictions about the dynamics of the shape of the pitch distribution, which we confirm experimentally

Increasing Efforts in SSMA: What Does it Take?

The inadequate management of conventional ammunition results in negative consequences such as diversion to illicit groups and unplanned explosions at munitions sites (UEMS). Both diversion and unintended blasts can result in a severe humanitarian impact, undermine development efforts, compromise defense capabilities, and lead to instability. In recognition of this recurring danger, political, normative, and operational efforts have increased to promote the safe and secure management of ammunition (SSMA). As the issue enjoys greater national, regional, and international attention, stakeholders should simultaneously take stock of achievements, consider if current efforts address the challenges at hand, and appreciate what further steps are needed to achieve greater success. This article builds on a Geneva International Centre for Humanitarian Demining (GICHD) study depicting the current state of SSMA. It reviews recent normative developments and identifies capacity and implementation gaps for further consideration by relevant stakeholders

Systems and Methods for Structurally Interrelating Components Using Inserts Made from Metallic Glass-Based Materials

Systems and methods in accordance with embodiments of the invention operate to structurally interrelate two components using inserts made from metallic glass-based materials. In one embodiment, a method of structurally interrelating two components includes: forming an insert from a metallic glass-based composition; where the formed insert includes a metallic glass-based material; affixing the insert to a first component; and structurally interrelating the second component to the first component using the insert

What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?

Transportation Networks and Logistics 4.0 work on the basis of integrated systems. These systems are enabled by standards which are widely used for the communication between IT-Systems. Due to individual requirements, standards are customized by companies. The extent of individualization has not yet been investigated. Therefore, we applied an empirical analysis on two mature logistic communication standards to identify the standard-application gap by calculating the interoperability between the applied standards. Within these results, we expand the standardization theory by simulating the network effects and the standard diffusion and quantify the impact of the company specific individualization of logistic standards. The identified findings help to improve the standard diffusion model and to improve the development of logistic standards

Modular Current Stimulation System for Pre-clinical Studies.

Electric stimulators with precise and reliable outputs are an indispensable part of electrophysiological research. From single cells to deep brain or neuromuscular tissue, there are diverse targets for electrical stimulation. Even though commercial systems are available, we state the need for a low-cost, high precision, functional, and modular (hardware, firmware, and software) current stimulation system with the capacity to generate stable and complex waveforms for pre-clinical research. The system presented in this study is a USB controlled 4-channel modular current stimulator that can be expanded and generate biphasic arbitrary waveforms with 16-bit resolution, high temporal precision (μs), and passive charge balancing: the NES STiM (Neuro Electronic Systems Stimulator). We present a detailed description of the system's structural design, the controlling software, reliability test, and the pre-clinical studies [deep brain stimulation (DBS) in hemi-PD rat model] in which it was utilized. The NES STiM has been tested with MacOS and Windows operating systems. Interfaces to MATLAB source codes are provided. The system is inexpensive, relatively easy to build and can be assembled quickly. We hope that the NES STiM will be used in a wide variety of neurological applications such as Functional Electrical Stimulation (FES), DBS and closed loop neurophysiological research

Neutronographic Analysis of Load Partitioning and Micro Residual Stress Development in Duplex Stainless Steels

In the present work, neutronographic in situ diffraction stress analyses during uniaxial loading and subsequent unloading were carried out on the two duplex stainless steels X2CrNiMoN22-5-3 and X3CrNiMoN27-5-2 with nominal phase fractions for ferrite:austenite of 50:50% and 70:30%, respectively. In addition to the different phase fractions, the two steels also differed in their phase-specific crystallographic texture. The load-partitioning behaviour and the phase-specific micro (residual) stress evolution for total strains up to about 9% were investigated. The results indicated that for both materials under load, the phase-specific stress in the ferrite phase was significantly higher than in the austenite phase, while no texture development through the plastic deformation could be observed

On the accuracy and usefulness of analytic energy models for contemporary multicore processors

This paper presents refinements to the execution-cache-memory performance model and a previously published power model for multicore processors. The combination of both enables a very accurate prediction of performance and energy consumption of contemporary multicore processors as a function of relevant parameters such as number of active cores as well as core and Uncore frequencies. Model validation is performed on the Sandy Bridge-EP and Broadwell-EP microarchitectures. Production-related variations in chip quality are demonstrated through a statistical analysis of the fit parameters obtained on one hundred Broadwell-EP CPUs of the same model. Insights from the models are used to explain the performance- and energy-related behavior of the processors for scalable as well as saturating (i.e., memory-bound) codes. In the process we demonstrate the models' capability to identify optimal operating points with respect to highest performance, lowest energy-to-solution, and lowest energy-delay product and identify a set of best practices for energy-efficient execution

First steps towards a generic sample preparation scheme for inorganic engineered nanoparticles in a complex matrix for detection, characterization, and quantification by asymmetric flow-field flow fractionation coupled to multi-angle light scattering and ICP-MS

The applicability of a multi-step generic procedure to systematically develop sample preparation methods for the detection, characterization, and quantification of inorganic engineered nanoparticles (ENPs) in a complex matrix was successfully demonstrated. The research focused on the optimization of the sample preparation, aiming to achieve a complete separation of ENPs from a complex matrix without altering the ENP size distribution and with minimal loss of ENPs. The separated ENPs were detected and further characterized in terms of particle size distribution and quantified in terms of elemental mass content by asymmetric flow-field flow fractionation coupled to a multi-angle light scattering detector and an inductively coupled plasma mass spectrometer. Following the proposed generic procedure SiO2-ENPs were separated from a tomato soup. Two potential sample preparation methods were tested these being acid digestion and colloidal extraction. With the developed method a complete SiO2-ENPs and matrix separation with a Si mass recovery >90% was achieved by acid digestion. The alteration of the particle size distribution was minimized by particle stabilization. The generic procedure which also provides quality criteria for method development is urgently needed for standardized and systematic development of procedures for separation of ENPs from a complex matrix. The chosen analytical technique was shown to be suitable for detecting SiO2-ENPs in a complex food matrix like tomato soup and may therefore be extended to monitor the existence of ENPs during production and safety control of foodstuffs, food labelling, and compliance with legislative limits