Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data

Machine learning approaches are valuable methods in hyperspectral remote sensing, especially for the classification of land cover or for the regression of physical parameters. While the recording of hyperspectral data has become affordable with innovative technologies, the acquisition of reference data (ground truth) has remained expensive and time-consuming. There is a need for methodological approaches that can handle datasets with significantly more hyperspectral input data than reference data. We introduce the Supervised Self-organizing Maps (SuSi) framework, which can perform unsupervised, supervised and semi-supervised classification as well as regression on high-dimensional data. The methodology of the SuSi framework is presented and compared to other frameworks. Its different parts are evaluated on two hyperspectral datasets. The results of the evaluations can be summarized in four major findings: (1) The supervised and semi-Supervised Self-organizing Maps (SOM) outperform random forest in the regression of soil moisture. (2) In the classification of land cover, the supervised and semi-supervised SOM reveal great potential. (3) The unsupervised SOM is a valuable tool to understand the data. (4) The SuSi framework is versatile, flexible, and easy to use. The SuSi framework is provided as an open-source Python package on GitHub

ACTman:Automated preprocessing and analysis of actigraphy data

Objectives: To introduce a novel software-library called Actigraphy Manager (ACTman) which automates labor-intensive actigraphy data preprocessing and analyses steps while improving transparency, reproducibility, and scalability over software suites traditionally used in actigraphy research practice. Design: Descriptive. Methods: Use cases are described for performing a common actigraphy task in ACTman and alternative actigraphy software. Important inefficiencies in actigraphy workflow are identified and their consequences are described. We explain how these hinder the feasibility of conducting studies with large groups of athletes and/or longer data collection periods. Thereafter, the information flow through the ACTman software is described and we explain how it alleviates aforementioned inefficiencies. Furthermore, transparency, reproducibility, and scalability issues of commonly used actigraphy software packages are discussed and compared with the ACTman package. Results: It is shown that from an end-user perspective ACTman offers a compact workflow as it automates many preprocessing and analysis steps that otherwise have to be performed manually. When considering transparency, reproducibility, and scalability the design of the ACTman software is found to outperform proprietary and open-source actigraphy software suites. As such, ACTman alleviates important bottlenecks within actigraphy research practice. Conclusions: ACTman facilitates the current transition towards larger datasets containing data of multiple athletes by automating labor-intensive preprocessing and analyses steps within actigraphy research. Furthermore, ACTman offers many features which enhance user-convenience and analysis customization, such as moving window functionality and period selection options. ACTman is open-source and thus fully verifiable, in contrast with many proprietary software packages which remain a black box for researchers

In-Flight Reconfiguration with System-On-Module Based Architectures for Science Instruments on Nanosatellites

For science payloads on nanosatellite missions, there is a great interest in cost-effective, reliable and state-of-the-art computing performance. Highly integrated system architectures combine reconfigurable System-on-Chip (SoC) devices, memory and peripheral interfaces in a single System-on-Module (SoM) and offer low resource requirements regarding power and mass, but moderate to high processing power capabilities. The major advantages of these architectures are flexibility, (re)programmability, modularity and module reuse. However, it is a challenge to use SoM with COTS based memories devices in a radiation sensitive environment. In order to achieve these requirements, mitigation measures, such as the use of redundant or alternative memory devices and in-flight reconfiguration, are important in terms of reliability. Reprogramming strategies e.g. partial dynamic reconfiguration and scrubbing techniques are published in the past. With a remote sensing instrument for atmospheric temperature measurements using a SRAM-based Xilinx Zynq-7000 SoM, we combine some of these techniques with supervisor circuits to select the boot image from alternative memory devices. The approach distinguishes between programmable logic and processing system reconfiguration, and enables in-flight firmware updates in the case of Single Event Effect (SEE) hazards or changing measurement conditions

Microfluidics: A Groundbreaking Technology for PET Tracer Production?

Application of microfluidics to Positron Emission Tomography ( PET) tracer synthesis has attracted increasing interest within the last decade. The technical advantages of microfluidics, in particular the high surface to volume ratio and resulting fast thermal heating and cooling rates of reagents can lead to reduced reaction times, increased synthesis yields and reduced by-products. In addition automated reaction optimization, reduced consumption of expensive reagents and a path towards a reduced system footprint have been successfully demonstrated. The processing of radioactivity levels required for routine production, use of microfluidic-produced PET tracer doses in preclinical and clinical imaging as well as feasibility studies on autoradiolytic decomposition have all given promising results. However, the number of microfluidic synthesizers utilized for commercial routine production of PET tracers is very limited. This study reviews the state of the art in microfluidic PET tracer synthesis, highlighting critical design aspects, strengths, weaknesses and presenting several characteristics of the diverse PET market space which are thought to have a significant impact on research, development and engineering of microfluidic devices in this field. Furthermore, the topics of batch- and single-dose production, cyclotron to quality control integration as well as centralized versus de-centralized market distribution models are addressed

A solvent resistant lab-on-chip platform for radiochemistry applications

The application of microfluidics to the synthesis of Positron Emission Tomography (PET) tracers has been explored for more than a decade. Microfluidic benefits such as superior temperature control have been successfully applied to PET tracer synthesis. However, the design of a compact microfluidic platform capable of executing a complete PET tracer synthesis workflow while maintaining prospects for commercialization remains a significant challenge. This study uses an integral system design approach to tackle commercialization challenges such as the material to process compatibility with a path towards cost effective lab-on-chip mass manufacturing from the start. It integrates all functional elements required for a simple PET tracer synthesis into one compact radiochemistry platform. For the lab-on-chip this includes the integration of on-chip valves, on-chip solid phase extraction (SPE), on-chip reactors and a reversible fluid interface while maintaining compatibility with all process chemicals, temperatures and chip mass manufacturing techniques. For the radiochemistry device it includes an automated chip-machine interface enabling one-move connection of all valve actuators and fluid connectors. A vial-based reagent supply as well as methods to transfer reagents efficiently from the vials to the chip has been integrated. After validation of all those functional elements, the microfluidic platform was exemplarily employed for the automated synthesis of a Gastrin-releasing peptide receptor (GRP-R) binding the PEGylated Bombesin BN(7-14)-derivative (F-18]PESIN) based PET tracer

Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients:An actigraphy study

Early-warning signals (EWS) have been successfully employed to predict transitions in research fields such as biology, ecology, and psychiatry. The predictive properties of EWS might aid in foreseeing transitions in mood episodes (i.e. recurrent episodes of mania and depression) in bipolar disorder (BD) patients. We analyzed actigraphy data assessed during normal daily life to investigate the feasibility of using EWS to predict mood transitions in bipolar patients. Actigraphy data of 15 patients diagnosed with BD Type I collected continuously for 180 days were used. Our final sample included eight patients that experienced a mood episode, three manic episodes and five depressed episodes. Actigraphy data derived generic EWS (variance and kurtosis) and context-driven EWS (autocorrelation at lag-720) were used to determine if these were associated to upcoming bipolar episodes. Spectral analysis was used to predict changes in the periodicity of the sleep/wake cycle. The study procedures were pre-registered. Results indicated that in seven out of eight patients at least one of the EWS did show a significant change-up till four weeks before episode onset. For the generic EWS the direction of change was always in the expected direction, whereas for the context-driven EWS the observed effect was often in the direction opposite of what was expected. The actigraphy data derived EWS and spectral analysis showed promise for the prediction of upcoming transitions in mood episodes in bipolar patients. Further studies into false positive rates are suggested to improve effectiveness for EWS to identify upcoming bipolar episode onsets

Stability of chronotype over a 7-year follow-up period and its association with severity of depressive and anxiety symptoms

Background: Chronotype is an individual's preferred timing of sleep and activity, and is often referred to as a later chronotype (or evening-type) or an earlier chronotype (or morning-type). Having an evening chronotype is associated with more severe depressive and anxiety symptoms. Based on these findings it is has been suggested that chronotype is a stable construct associated with vulnerability to develop depressive or anxiety disorders. To examine this, we test the stability of chronotype over 7 years, and its longitudinal association with the change in severity of depressive and anxiety symptoms. Methods: Data of 1,417 participants with a depressive and/or anxiety disorder diagnosis and healthy controls assessed at the 2 and 9-year follow-up waves of the Netherlands Study of depression and anxiety were used. Chronotype was assessed with the Munich chronotype questionnaire. Severity of depressive and anxiety symptoms were assessed with the inventory of depressive symptomatology and Beck anxiety inventory. Results: Chronotype was found to be moderately stable (r = 0.53) and on average advanced (i.e., became earlier) with 10.8 min over 7 years (p <.001). Controlling for possible confounders, a decrease in severity of depressive symptoms was associated with an advance in chronotype (B = 0.008, p =.003). A change in severity of anxiety symptoms was not associated with a change in chronotype. Conclusion: Chronotype was found to be a stable, trait-like construct with only a minor level advance over a period of 7 years. The change in chronotype was associated with a change in severity of depressive, but not anxiety, symptoms

The microRNA regulated SBP-box genes SPL9 and SPL15 control shoot maturation in Arabidopsis

Throughout development the Arabidopsis shoot apical meristem successively undergoes several major phase transitions such as the juvenile-to-adult and floral transitions until, finally, it will produce flowers instead of leaves and shoots. Members of the Arabidopsis SBP-box gene family of transcription factors have been implicated in promoting the floral transition in dependence of miR156 and, accordingly, transgenics constitutively over-expressing this microRNA are delayed in flowering. To elaborate their roles in Arabidopsis shoot development, we analysed two of the 11 miR156 regulated Arabidopsis SBP-box genes, i.e. the likely paralogous genes SPL9 and SPL15. Single and double mutant phenotype analysis showed these genes to act redundantly in controlling the juvenile-to-adult phase transition. In addition, their loss-of-function results in a shortened plastochron during vegetative growth, altered inflorescence architecture and enhanced branching. In these aspects, the double mutant partly phenocopies constitutive MIR156b over-expressing transgenic plants and thus a major contribution to the phenotype of these transgenics as a result of the repression of SPL9 and SPL15 is strongly suggested