Holographic optical elements for optical backplane bus targeted at high speed data transfer

Background Here we present a novel single-channel multiplex qPCR assay with real-time detection in 3 separate readouts in a single optical channel. Traditional multiplex qPCR technologies are limited to detection of one target per optical channel, limiting throughput and utility of existing instruments. This assay utilizes multiple probes that each fluoresce at a specific temperature in a single optical channel such as FAM, but only in the presence of their respective targets. The fluorescence signals from each probe are contained within their discrete temperature range, ensuring no cross talk between temperatures. Probes are universal and cleaved by target-specific PlexZymes®, making this probe system adaptable for any targets of interest. A reverse transcriptase qPCR assay (3T Respi) was developed for detection of 5 viral targets in 3 readouts in the FAM channel; Respiratory Syncytial Viruses A and B (RSV A and B) were detected at the first temperature (45°C); Influenza A (Flu A) and Influenza B (Flu B) were detected at the second temperature (61°C); and SARS-CoV-2 (ORF1ab and RdRp gene targets) was detected at the third temperature (78°C). Methods The assay performance was assessed in a retrospective evaluation of 657 nasopharyngeal swab (NPS) extracts provided by symptomatic individuals, on the CFX96™ Touch Real-Time PCR Detection System (Bio-Rad) against the CE-IVDR approved comparator PKamp™ Respiratory SARS-CoV-2 RT-PCR panel 1 (Revvity). The samples had been previously extracted with the Chemagic™ Viral DNA/RNA 300 Kit (Revvity). Any discordant extracts were tested with the CE-IVDR approved PlexPCR® Flu/RSV/SARS-CoV-2 (SpeeDx) on the Applied Biosystems™ QuantStudio5 Real-Time PCR instrument. Sensitivity of detection was established using commercial genomic RNA. Results The 3T Respi showed a positive percent agreement (PPA) of 83.5%, 92.9% and 96.0% for RSV A/B, Flu A/B and SARS-CoV-2 respectively with NPS extracts. Sample degradation over prolonged storage in -80°C was suspected as the reason for the PPA below 90% with RSV A/B. The negative percent agreement (NPA) was 99.8%, 95.8% and 99.1% for RSV A/B, Flu A/B and SARS-CoV-2 respectively. Further, the 3T Respi detected down to 9 copies of target per reaction (cps/rxn) of RSV A, FluA (H1N1), FluB and SARS-CoV-2, and 3 cps/rxn of RSV B and FluA (H3N2). Conclusion The 3T Respi assay showed detection of 5 viral targets in 3 independent readouts in a single optical channel, with detection down to 9 copies of target per reaction. In a retrospective clinical evaluation study against a comparator qPCR test, this assay demonstrated a PPA >90% for Flu A/B and SARS-CoV-2 targets, and a PPA of 83.5% for RSV A/B; lower PPA for RSV A/B was likely due to sample degradation over prolonged storage. NPA was over 95% for all targets. This assay can be run on standard qPCR instruments as demonstrated, or on point-of-care qPCR instruments typically with less optical channels. Overall, this data exemplifies the suitability of the utilised single-channel multiplex qPCR probe system for clinical applications, adaptable to any targets of interest.

The transmission rate between two nodes is usually very low in underwater acoustic networks due to the low available bandwidth of underwater acoustic channels. Therefore, increasing the transmission parallelism among network nodes is one of the most effective ways to improve the performance of underwater acoustic networks. In this paper, we propose a new collision-free hybrid medium access control (MAC) protocol for distributed multi-channel underwater acoustic networks. In the proposed protocol, handshaking and data transmission are implemented as a pipeline on multiple acoustic channels. Handshaking is implemented using the time division multiple access (TDMA) technique in a dedicated control channel, which can support multiple successful handshakes in a transmission cycle and avoid collision in the cost of additional delay. Data packets are transmitted in one or multiple data channels, where an algorithm for optimizing the transmission schedule according to the inter-nodal propagation delays is proposed to achieve collision-free parallel data transmission. Replication computation technique, which is usually used in parallel computation to reduce the requirement of communication or execution time, is used in the data packet scheduling to reduce communication overhead in distributed environments. Simulation results show that the proposed protocol outperforms the slotted floor acquisition multiple access (SFAMA), reverse opportunistic packet appending (ROPA), and distributed scheduling based concurrent transmission (DSCT) protocols in throughput, packet delivery rate, and average energy consumption in the price of larger end-to-end delay introduced by TDMA based handshaking.

Existing systems to measure insect emergence patterns have limitations; they are only partially automated and are limited in the maximum number of emerging insects they can detect. In order to obtain precise measurement of insect emergence, it is necessary for systems to be semi-automated and able to measure large numbers of emerging insects. We addressed these issues by designing and building a system that is automated and can measure emergence of up to 1200 insects. We modified the existing "falling-ball" system using Arduino microcontrollers to automate data collection and expand the sample size through multiple data channels. Multiple data channels enable the user to not only increase their sample size, but also allows for multiple treatments to be run simultaneously in a single experiment. Furthermore, we created an R script to automatically visualize the data as a bubble plot, while also calculating the median day and time of emergence. The current system was designed using 3D printing so the user can modify the system to be adjusted for different species of insects. The goal of this protocol is to investigate important questions in chronobiology and stress physiology, using this precise and automated system to measure insect emergence patterns.

We propose to use power pins to carry data signals while simultaneously delivering power. A direct superposition of a data signal on a power pin would fail due to the inherent high noise level on power lines and this precludes the possibility for multiple data channels. To address the problem, we suggest adoption of the UWB (ultra wideband) and direct sequence-code division multiple access (DS-CDMA) communication technologies. Because of the wide bandwidth, a UWB signal can reduce its average power level practically to the noise level. DS-CDMA further mitigates the noise and allows multiple data channels to share interconnected power lines. We studied the feasibility of the proposed scheme through SPICE simulations and present the simulation results.

SummarySMLocalizer combines the availability of ImageJ with the power of GPU processing for fast and accurate analysis of single molecule localization microscopy data. Analysis of 2D and 3D data in multiple channels is supported.Availability and implementationPlugin freely available for Fiji and ImageJ2.0 through https://sourceforge.net/projects/smlocalizer/. Plugin also available for continuous updates through ImageJ update system, add http://sites.imagej.net/Cellular-Biophysics-KTH/ as update site in ImageJ. Java and CUDA source code freely available on the web at https://github.com/KristofferBernhem/SMlocalizer.Supplementary informationSupplementary data are available at Bioinformatics online.

Multiscale multifractal detrended fluctuation analysis of multivariate time series

International audience

Whole-body MR receives increasing interest as potential alternative to many conventional diagnostic methods. Typical whole-body MR scans contain multiple data channels and are acquired in a multistation manner. Quantification of such data typically requires correction of two types of artefacts: different intensity scaling on each acquired image stack, and intensity inhomogeneity (bias) within each stack. In this work, we present an all-in-one method that is able to correct for both mentioned types of acquisition artefacts. The most important properties of our method are: 1) All the processing is performed jointly on all available data channels, which is necessary for preserving the relation between them, and 2) It allows easy incorporation of additional knowledge for estimation of the bias field. Performed validation on two types of whole-body MR data confirmed superior performance of our approach in comparison with state-of-the-art bias removal methods.

Physiological measurements in neuroscience experiments often involve complex stimulus paradigms and multiple data channels. Ephus (http://www.ephus.org) is an open-source software package designed for general-purpose data acquisition and instrument control. Ephus operates as a collection of modular programs, including an ephys program for standard whole-cell recording with single or multiple electrodes in typical electrophysiological experiments, and a mapper program for synaptic circuit mapping experiments involving laser scanning photostimulation based on glutamate uncaging or channelrhodopsin-2 excitation. Custom user functions allow user-extensibility at multiple levels, including on-line analysis and closed-loop experiments, where experimental parameters can be changed based on recently acquired data, such as during in vivo behavioral experiments. Ephus is compatible with a variety of data acquisition and imaging hardware. This paper describes the main features and modules of Ephus and their use in representative experimental applications.

Neural complexity is thought to be associated with efficient information processing but the exact nature of this relation remains unclear. Here, the relationship of fluid intelligence (gf) with the resting‐state EEG (rsEEG) complexity over different timescales and different electrodes was investigated. A 6‐min rsEEG blocks of eyes open were analyzed. The results of 119 subjects (57 men, mean age = 22.85 ± 2.84 years) were examined using multivariate multiscale sample entropy (mMSE) that quantifies changes in information richness of rsEEG in multiple data channels at fine and coarse timescales. gf factor was extracted from six intelligence tests. Partial least square regression analysis revealed that mainly predictors of the rsEEG complexity at coarse timescales in the frontoparietal network (FPN) and the temporo‐parietal complexities at fine timescales were relevant to higher gf. Sex differently affected the relationship between fluid intelligence and EEG complexity at rest. In men, gf was mainly positively related to the complexity at coarse timescales in the FPN. Furthermore, at fine and coarse timescales positive relations in the parietal region were revealed. In women, positive relations with gf were mostly observed for the overall and the coarse complexity in the FPN, whereas negative associations with gf were found for the complexity at fine timescales in the parietal and centro‐temporal region. These outcomes indicate that two separate time pathways (corresponding to fine and coarse timescales) used to characterize rsEEG complexity (expressed by mMSE features) are beneficial for effective information processing.

The QuickSilver Event Processing Module (EPM), an electronics module used in Siemens Inveon PET and SPECT systems, provides data acquisition, event processing and coincidence determination functions. Custom mixed-signal CMOS ASICs and high speed ADCs are utilized to provide the front-end analog portion of the data acquisition. A high performance FPGA provides the digital portion of the data acquisition running at 100 MHz, the subsequent event processing, and the coincidence determination. The high performance FPGA also provides multiple high speed serial data channels for external interconnection. This interconnection allows the module to be replicated as needed in a distributed parallel processing architecture to provide flexible, high performance, PET and SPECT imaging. The module also provides controllable high voltage needed to bias detectors. A 64 channel, LSO based PET system built using 16 EPMs yielded 1.22 ns FWHM system timing and better than 14% energy resolution.

3D object recognition from static 2D views using multiple coarse data channels

We have developed and tested a photonic high speed analog data recording system that, when compared with conventional oscilloscope-based systems, offers greater economy, higher bandwidth, electrical isolation, and compactness. The basis of this approach is to record analog photonic signals rather than analog electrical signals. A key component is a prototype High Speed Multi-Channel Data Recorder (HSMCDR). It uses a picosecond streak camera with a digital readout to record multiple fiber-optic data channels, and a dedicated microcomputer to reduce and process that data. To record signals from analog electrical sensors, laser diode transmitters provide an interface to the HSMCDR. Interactive software written for the HSMCDR separates, calibrates, and plots up to 20 waveforms in the customary amplitude versus time format. We describe the HSMCDR, its performance, applications in pulsed power experiments, and its impact in diagnostic technology.

Industrial Applications of Lasers

Time Series data collected from wearable sensors such as Inertial Measurement Units (IMU) are becoming popular for use in classification tasks in the exercise domain. The data from these IMU sensors tend to have multiple channels of data as well as the potential to augment new time series based features. However, this data also tends to have high correlations between the channels which means that often only a small subset of features are required for classification. A challenge in working with human movement data is that there tends to be inter-subject variabilities which makes it challenging to build a generalised model that works across subjects. In this work, the feasibility of generating generalisable feature subsets to predict fatigue in runners using a correlation based feature subset selection approach was investigated. It is shown that personalised classification systems where the feature selection is also tuned to the individual provides the best overall performance.