MagCPP: a C++ toolbox for combining neurofeedback with Magstim transcranial magnetic stimulators

Transcranial magnetic stimulation (TMS) is an established method to treat various neurological diseases, such as depression, Alzheimer's disease, and tinnitus. New applications for TMS are closed loop neurofeedback (NF) scenarios, which require software control of the TMS system, instead of the currently used manual control. Hence, the MagCPP (https://github.com/MagCPP) toolbox was developed and is described in this work. The toolbox enables the external control of Magstim TMS devices via a C++ interface. Comparing MagCPP to two other toolboxes in a TMS application scenario with 40% power, we found that MagCPP works faster and has lower variability in repeated runs (MagCPP, Python, MATLAB [mean±std in seconds]: 1.19±0.00, 1.59±0.01, 1.44±0.02). An integration of MagCPP in a real-time data processing platform MNE-CPP with an optional GUI demonstrates its ability as part of a closed-loop NF-scenario. With its performing advantages over other toolboxes, MagCPP is a first step towards a complete closed loop NF scenario and offers possibilities for novel study designs

Process-Based Design and Integration of Wireless Sensor Network Applications

Abstract Wireless Sensor and Actuator Networks (WSNs) are distributed sensor and actuator networks that monitor and control real-world phenomena, enabling the integration of the physical with the virtual world. They are used in domains like building automation, control systems, remote healthcare, etc., which are all highly process-driven. Today, tools and insights of Business Process Modeling (BPM) are not used to model WSN logic, as BPM focuses mostly on the coordination of people and IT systems and neglects the integration of embedded IT. WSN development still requires significant special-purpose, low-level, and manual coding of process logic. By exploiting similarities between WSN applications and business processes, this work aims to create a holistic system enabling the modeling and execution of executable processes that integrate, coordinate, and control WSNs. Concretely, we present a WSNspecific extension for Business Process Modeling Notation (BPMN) and a compiler that transforms the extended BPMN models into WSN-specific code to distribute process execution over both a WSN and a standard business process engine. The developed tool-chain allows modeling of an independent control loop for the WSN.

Demo Abstract: From Business Process Specifications to Sensor Network Deployments

makeSenseCONE

Towards Business Processes Orchestrating the Physical Enterprise with Wireless Sensor Networks

The industrial adoption of wireless sensor net- works (WSNs) is hampered by two main factors. First, there is a lack of integration of WSNs with business process modeling languages and back-ends. Second, programming WSNs is still challenging as it is mainly performed at the operating system level. To this end, we provide makeSense: a unified programming framework and a compilation chain that, from high-level business process specifications, generates code ready for deployment on WSN nodes

High power, single-frequency, monolithic fiber amplifier for the next generation of gravitational wave detectors

Low noise, high power single-frequency lasers and amplifiers are key components of interferometric gravitational wave detectors. One way to increase the detector sensitivity is to increase the power injected into the interferometers. We developed a fiber amplifier engineering prototype with a pump power limited output power of 200 W at 1064 nm. No signs of stimulated Brillouin scattering are observed at 200 W. At the maximum output power the polarization extinction ratio is above 19 dB and the fractional power in the fundamental transverse mode (TEM00) was measured to be 94.8 %. In addition, measurements of the frequency noise, relative power noise, and relative pointing noise were performed and demonstrate excellent low noise properties over the entire output power slope. In the context of single-frequency fiber amplifiers, the measured relative pointing noise below 100 Hz and the higher order mode content is, to the best of our knowledge, at 200 W the lowest ever measured. A long-term test of more than 695 h demonstrated stable operation without beam quality degradation. It is also the longest single-frequency fiber amplifier operation at 200 W ever reported. © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Broadening the phenotypic and molecular spectrum of FINCA syndrome: Biallelic NHLRC2 variants in 15 novel individuals

FINCA syndrome [MIM: 618278] is an autosomal recessive multisystem disorder characterized by fibrosis, neurodegeneration and cerebral angiomatosis. To date, 13 patients from nine families with biallelic NHLRC2 variants have been published. In all of them, the recurrent missense variant p.(Asp148Tyr) was detected on at least one allele. Common manifestations included lung or muscle fibrosis, respiratory distress, developmental delay, neuromuscular symptoms and seizures often followed by early death due to rapid disease progression.Here, we present 15 individuals from 12 families with an overlapping phenotype associated with nine novel NHLRC2 variants identified by exome analysis. All patients described here presented with moderate to severe global developmental delay and variable disease progression. Seizures, truncal hypotonia and movement disorders were frequently observed. Notably, we also present the first eight cases in which the recurrent p.(Asp148Tyr) variant was not detected in either homozygous or compound heterozygous state.We cloned and expressed all novel and most previously published non-truncating variants in HEK293-cells. From the results of these functional studies, we propose a potential genotype-phenotype correlation, with a greater reduction in protein expression being associated with a more severe phenotype.Taken together, our findings broaden the known phenotypic and molecular spectrum and emphasize that NHLRC2-related disease should be considered in patients presenting with intellectual disability, movement disorders, neuroregression and epilepsy with or without pulmonary involvement

Hot packets:a systematic evaluation of the effect of temperature on low power wireless transceivers

Temperature is known to have a significant effect on the performance of radio transceivers: the higher the temperature, the lower the quality of links. Analysing this effect is particularly important in sensor networks because several applications are exposed to harsh environmental conditions. Daily or hourly changes in temperature can dramatically reduce the throughput, increase the delay, or even lead to network partitions. A few studies have quantified the impact of temperature on low-power wireless links, but only for a limited temperature range and on a single radio transceiver. Building on top of these preliminary observations, we design a low-cost experimental infrastructure to vary the onboard temperature of sensor nodes in a repeatable fashion, and we study systematically the impact of temperature on various sensornet platforms. We show that temperature affects transmitting and receiving nodes differently, and that all platforms follow a similar trend that can be captured in a simple first-order model. This work represents an initial stepping stone aimed at predicting the performance of a network considering the particular temperature profile of a given environment

MagCPP: A C++ toolbox for Combining Neurofeedback with Magstim transcranial magnetic stimulators

Transcranial magnetic stimulation (TMS) is an established method to treat various neurological diseases, such as depression, Alzheimer’s disease, and tinnitus. New applications for TMS are closed loop neurofeedback (NF) scenarios, which require software control of the TMS system, instead of the currently used manual control. Hence, the MagCPP (https://github.com/MagCPP) toolbox was developed and is described in this work. The toolbox enables the external control of Magstim TMS devices via a C++ interface. Comparing MagCPP to two other toolboxes in a TMS application scenario with 40% power, we found that MagCPP works faster and has lower variability in repeated runs (MagCPP, Python, MATLAB [mean±std in seconds]: 1.19±0.00, 1.59±0.01, 1.44±0.02). An integration of MagCPP in a real-time data processing platform MNE-CPP with an optional GUI demonstrates its ability as part of a closed-loop NF-scenario. With its performing advantages over other toolboxes, MagCPP is a first step towards a complete closed loop NF scenario and offers possibilities for novel study designs