Noise Efficient Integrated Amplifier Designs for Biomedical Applications

The recording of neural signals with small monolithically integrated amplifiers is of high interest in research as well as in commercial applications, where it is common to acquire 100 or more channels in parallel. This paper reviews the recent developments in low-noise biomedical amplifier design based on CMOS technology, including lateral bipolar devices. Seven major circuit topology categories are identified and analyzed on a per-channel basis in terms of their noise-efficiency factor (NEF), input-referred absolute noise, current consumption, and area. A historical trend towards lower NEF is observed whilst absolute noise power and current consumption exhibit a widespread over more than five orders of magnitude. The performance of lateral bipolar transistors as amplifier input devices is examined by transistor-level simulations and measurements from five different prototype designs fabricated in 180 nm and 350 nm CMOS technology. The lowest measured noise floor is 9.9 nV/√Hz with a 10 µA bias current, which results in a NEF of 1.2

New Constraints on Hidden Photons using Very High Energy Gamma-Rays from the Crab Nebula

Extensions of the standard model of particle physics, in particular those based on string theory, often predict a new U(1) gauge symmetry in a hidden sector. The corresponding gauge boson, called hidden photon, naturally interacts with the ordinary photon via gauge kinetic mixing, leading to photon - hidden photon oscillations. In this framework, one expects photon disappearance as a function of the mass of the hidden photon and the mixing angle, loosely constrained from theory. Several experiments have been carried out or are planned to constrain the mass-mixing plane. In this contribution we derive new constraints on the hidden photon parameters, using very high energy gamma-rays detected from the Crab Nebula, whose broad-band spectral characteristics are well understood. The very high energy gamma-ray observations offer the possibility to provide bounds in a broad mass range at a previously unexplored energy and distance scale. Using existing data that were taken with several Cherenkov telescopes, we discuss our results in the context of current constraints and consider the possibilities of using astrophysical data to search for hidden photon signatures.Comment: Proceedings of the "Heidelberg International Symposium on High Energy Gamma-Ray Astronomy", Heidelberg, Germany, July 7-11, 2008, submitted to AIP Conference Proceedings. 4 pages, 2 figures, 1 tabl

A Study of Deep Learning for Network Traffic Data Forecasting

We present a study of deep learning applied to the domain of network traffic data forecasting. This is a very important ingredient for network traffic engineering, e.g., intelligent routing, which can optimize network performance, especially in large networks. In a nutshell, we wish to predict, in advance, the bit rate for a transmission, based on low-dimensional connection metadata ("flows") that is available whenever a communication is initiated. Our study has several genuinely new points: First, it is performed on a large dataset (~50 million flows), which requires a new training scheme that operates on successive blocks of data since the whole dataset is too large for in-memory processing. Additionally, we are the first to propose and perform a more fine-grained prediction that distinguishes between low, medium and high bit rates instead of just "mice" and "elephant" flows. Lastly, we apply state-of-the-art visualization and clustering techniques to flow data and show that visualizations are insightful despite the heterogeneous and non-metric nature of the data. We developed a processing pipeline to handle the highly non-trivial acquisition process and allow for proper data preprocessing to be able to apply DNNs to network traffic data. We conduct DNN hyper-parameter optimization as well as feature selection experiments, which clearly show that fine-grained network traffic forecasting is feasible, and that domain-dependent data enrichment and augmentation strategies can improve results. An outlook about the fundamental challenges presented by network traffic analysis (high data throughput, unbalanced and dynamic classes, changing statistics, outlier detection) concludes the article.Comment: 16 pages, 12 figures, 28th International Conference on Artificial Neural Networks (ICANN 2019

Love at First Sight? A User Experience Study of Self-Sovereign Identity Wallets

Today’s systems for digital identity management exhibit critical security, efficiency, and privacy issues. A new paradigm, called Self-Sovereign Identity (SSI), addresses these shortcomings by equipping users with mobile wallets and empowering them to manage their digital identities. Various companies and governments back this paradigm and promote its development and diffusion. User experience often plays a subordinate role in these efforts, even though it is crucial for user satisfaction and adoption. We thus conduct a comprehensive user experience study of four prominent SSI wallets using a mixed-method approach that involves moderated and remote interviews and the User Experience Questionnaire (UEQ). We find that the examined wallets already provide a decent level of user experience, yet further improvements need to be done. In particular, the examined wallets do not make their novelty and benefits sufficiently apparent to users. Our analysis contributes to user experience research and offers guidance for SSI practitioners

Canine vaccination in Germany: A survey of owner attitudes and compliance

Background: Vaccination is the most important preventive measure for protection against infectious diseases in humans and companion animals. Nevertheless, scepticism about the safety and importance of vaccines is increasing in human and in veterinary medicine. Although owner attitudes towards vaccination have been investigated in cats, there are no similar studies in dogs. The goals of this study were therefore to investigate the vaccination status of dogs in Germany, to determine owner compliance with vaccination and to identify factors that play a role in owners' decisions to have their dogs vaccinated. Methods Data were collected from August 2018 to February 2019 using an online survey targeting dog owners in Germany. A total of 3,881 questionnaires were evaluated, and factors associated with the vaccination status of dogs were determined by a linear logistic regression model using Akaike information criterion. Cohen's kappa statistic was used to evaluate agreement between questionnaire and 340 vaccination passports submitted voluntarily by owners. Results: A total of 46.8% (n = 1,818/3,881) of dogs were vaccinated with core vaccines according to current guidelines with the lowest vaccination rate for leptospirosis (50.1%;n = 1,941/3,874). Dog's age (16 weeks to 15 months) (odds ratio (OR): 3.08;95% CI: 2.05-4.68), type (working dog) (OR: 2.06;95% CI: 1.22-3.53) and travelling abroad within previous 36 months (OR: 1.82;95% CI: 1.12-2.96) had the strongest 'positive' association with the vaccination status. Recommendation from a veterinarian not to vaccinate against leptospirosis had the strongest 'negative' association (OR: 0.08;95% CI: 0.04-0.18). Conclusion The study revealed a need for improvement in vaccination compliance because of inadequate vaccination coverage, especially for leptospirosis, in dogs. Factors influencing owner compliance were numerous. Vaccination recommendations made by the veterinarian had a strong association with the vaccination status and should be used to increase canine vaccination rates

Reproductive performance of pandemic influenza A virus infected sow herds before and after implementation of a vaccine against the influenza A (H1N1)pdm09 virus

Background: Reproductive failure in sow herds due to infection with influenza A viruses has been described in the literature, but only a few studies have focused on the pathogenesis and the clinical signs of the infection. Case reports indicate an association between infections with influenza A viruses and reduced reproductive performance, although it has been difficult to experimentally reproduce the clinical outcome of poor reproductive performance. The aim of the present longitudinal field study was to compare the reproductive performance parameters before and after the implementation of vaccination against the influenza A (H1N1)pdm09 virus in sow herds infected with pandemic influenza A virus. Therefore, farm-specific data of 137 sow herds in Germany, including 60,153 sows, as well as the clinical presentation of the infection were surveyed via questionnaire. Furthermore, average performance parameters (return to oestrus rate, abortion rate, stillbirth rate, number of piglets born alive per litter, preweaning mortality rate and number of piglets weaned per sow per year) were recorded for 6 months before vaccination and 6 months after completion of primary vaccination. Results: In 79.8% of the farms, the clinical presentation of the infection was characterised by a reduced reproductive performance. These findings were confirmed by analysis of the performance parameters, which revealed a significant decline in the return to oestrus rate (p < 0.001), abortion rate (p < 0.001) and preweaning mortality rate (p = 0.023) and a significant increase of the number in piglets born alive (p = 0.001) and piglets weaned per sow per year (p < 0.001) after immunisation. The stillbirth rate did not change significantly. Conclusion: The present study represents the first attempt to demonstrate the association of influenza A virus infection, vaccination and the alteration in reproductive performance parameters, investigating a large number of cases. The results show that by vaccinating against the influenza A (H1N1)pdm09 virus, an improvement in reproductive performance can be achieved in sow herds infected with pandemic influenza A virus. Additionally, the large number of herds that were affected by poor reproductive performance after infection with the aforementioned virus confirms the assumption of an association between pandemic influenza A virus and reproductive losses

The Neural Basis of Age-Related Changes in Motor Imagery of Gait: An fMRI Study

Background. Aging is often associated with modifications of gait. Recent studies have revealed a strong relationship between gait and executive functions in healthy and pathological aging. We hypothesized that modification of gait due to aging may be related to changes in frontal lobe function. Methods. Fourteen younger (27.0±3.6 years) and 14 older healthy adults (66.0±3.5 years) performed a motor imagery task of gait as well as a matched visual imagery task. Task difficulty was modulated to investigate differential activation for precise control of gait. Task performance was assessed by recording motor imagery latencies, eye movements, and electromyography during functional magnetic resonance imaging scanning. Results. Our results showed that both healthy older and young adults recruited a network of brain regions comprising the bilateral supplementary motor cortex and primary motor cortex, right prefrontal cortex, and cerebellum, during motor imagery of gait. We observed an age-related increase in brain activity in the right supplementary motor area (BA6), the right orbitofrontal cortex (BA11), and the left dorsolateral frontal cortex (BA10). Activity in the left hippocampus was significantly modulated by task difficulty in the elderly participants. Executive functioning correlated with magnitude of increases in right primary motor cortex (BA4) during the motor imagery task. Conclusions. Besides demonstrating a general overlap in brain regions recruited in young and older participants, this study shows age-related changes in cerebral activation during mental imagery of gait. Our results underscore the importance of executive function (dorsolateral frontal cortex) and spatial navigation or memory function (hippocampus) in gait control in elderly individual

Twisted light Michelson interferometer for high precision refractive index measurements

Using orbital angular momentum beams in a Michelson interferometer opens the possibility for non-invasive measurements of refractive index changes down to 10(-6) refractive index units. We demonstrate the application of a twisted light interferometer to directly measure the concentration of NaCl and glucose solutions label-free and in situ and to monitor temperature differences in the mK-mu K range. From these measurements we can extract a correlation of the refractive index to concentration and to temperature from a liquid sample which is in good agreement with literature. Applying this type of twisted light interferometry yields a novel, robust, and easily implementable method for in situ monitoring of concentration and temperature changes in microfluidic samples. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreemen