A Frequency Adaptive Scheme Based on Newton Structure of PRRC for LCL-Type Inverter Connected with Weak Grid

Repetitive control (RC) is gradually used in inverters tied with weak grid. To achieve the zero steady-state error tracking of inverter current and compensate the harmonic distortion caused by frequency fluctuation, a frequency adaptive (FA) control scheme for LCL-type inverter connected with weak grid is proposed. This scheme adopts a proportional resonance (PR) controller in parallel with RC (PRRC) to overcome the disadvantages caused by RC inherent one-cycle time delay. A fractional delay (FD) filter based on the Newton structure is proposed to approximate the fraction item of fs/f, where fs and f are sample frequency and grid frequency, respectively. The structure of the proposed FD filter is relatively simple; moreover, coefficients of the filter maintain constant so as not to need online tuning even when grid frequency fluctuates, which decreases the computational burden considerably. The feasibility and effectiveness of the proposed FA control scheme, named as Newton-FAPRRC, are all verified by the simulation and experimental results.

A Robust Multilevel DWT Densely Network for Cardiovascular Disease Classification

Cardiovascular disease is the leading cause of death worldwide. Immediate and accurate diagnoses of cardiovascular disease are essential for saving lives. Although most of the previously reported works have tried to classify heartbeats accurately based on the intra-patient paradigm, they suffer from category imbalance issues since abnormal heartbeats appear much less regularly than normal heartbeats. Furthermore, most existing methods rely on data preprocessing steps, such as noise removal and R-peak location. In this study, we present a robust classification system using a multilevel discrete wavelet transform densely network (MDD-Net) for the accurate detection of normal, coronary artery disease (CAD), myocardial infarction (MI) and congestive heart failure (CHF). First, the raw ECG signals from different databases are divided into same-size segments using an original adaptive sample frequency segmentation algorithm (ASFS). Then, the fusion features are extracted from the MDD-Net to achieve great classification performance. We evaluated the proposed method considering the intra-patient and inter-patient paradigms. The average accuracy, positive predictive value, sensitivity and specificity were 99.74%, 99.09%, 98.67% and 99.83%, respectively, under the intra-patient paradigm, and 96.92%, 92.17%, 89.18% and 97.77%, respectively, under the inter-patient paradigm. Moreover, the experimental results demonstrate that our model is robust to noise and class imbalance issues.

Studies on the correlation between mutation and integration of HBV in hepatocellular carcinoma

It is well known that both the mutation and integration of the Hepatitis B virus (HBV) are of great significance in liver cancer, however, the relationship between mutation and integration is still unclear. In the present study, sequencing data from 426 previously published samples were analyzed and 5374 specific HBV mutations in cancer tissues were discovered. By comparing integrated samples and non-integrated samples, we found that the integrated samples had higher sample single nucleotide variants (SNVs) positive rates and SNV numbers, as well as higher sample frequency of SNV in the X region of the HBV genome. Samples with HBV integration in the telomerase reverse transcriptase (TERT) region showed higher SNV positive rates and numbers than samples without integration. Moreover, the SNVs (209 [T>G] and 531 [T>C; T>G]) were seen with higher frequency in samples with integration in the TERT region. Our study showed that the occurrence of viral integration events is closely related to the occurrence of SNV, and SNV in the X region should be more directly associated with viral integration. The present study provides an initial exploration of the relationship between HBV mutation and integration to help improve our understanding of the relationship between viral integration and mutation.

Taking advantage of Multisensor Synergy: New discovery and analysis tools

<p>Numerous new satellites and sensors have arised during the past decade. This satellite constellation has never been so dense and diverse. It provides a wide range of view angles to the ocean surface from the coast to the open ocean, at various scales and from physical to biological processes. Sentinel 1-2-3 program covers various sensors such as SAR, Optical, radiometer or altimeter with a repeat subcycle of only a few days, yet the repeat frequency for each sensor alone is not enough to monitor meso to submeso scales.</p><p>In the other hand, in-situ data are sparse in space but offers a high sample frequency and therefore complementary to remote sensing<br>observations. Handling consistently these huge heterogeneous datasets in a simple, fast and convenient way is now possible using the free and open Ocean Virtual Laboratory online portal or its standalone version. These tools are starting to be widely used by the scientific community to better discover, understand and monitor oceanic processes. We will demonstrate the potential and functionalities of these tools using various test cases:</p><p>Collocating Sentinel 1-2-3 for wave current interaction analysis<br>Creating synoptic charts of fronts and eddies, highlighting strong and energetic ocean currents<br>Campaign at sea planning and real time analysis of in-situ / remote sensing data. <br>Validation and comparison of currents (derived from satellite and models) with a Lagrangian approach using SEAScope stand alone interactive tool. </p><p><br>Online tool is available at https://ovl.oceandatalab.com and standalone version at https://seascope.oceandatalab.com. A splinter-meeting will<br>be organised at the conference to provide hands-on demonstration. </p>

Measuring Delays for Bicycles at Signalized Intersections Using Smartphone GPS Tracking Data

The article describes an application of global positioning system (GPS) tracking data (floating bike data) for measuring delays for cyclists at signalized intersections. For selected intersections, we used trip data collected by smartphone tracking to calculate the average delay for cyclists by interpolation between GPS locations before and after the intersection. The outcomes were proven to be stable for different strategies in selecting the GPS locations used for calculation, although GPS locations too close to the intersection tended to lead to an underestimation of the delay. Therefore, the sample frequency of the GPS tracking data is an important parameter to ensure that suitable GPS locations are available before and after the intersection. The calculated delays are realistic values, compared to the theoretically expected values, which are often applied because of the lack of observed data. For some of the analyzed intersections, however, the calculated delays lay outside of the expected range, possibly because the statistics assumed a random arrival rate of cyclists. This condition may not be met when, for example, bicycles arrive in platoons because of an upstream intersection. This justifies that GPS-based delays can form a valuable addition to the theoretically expected values.

Sensitive, highly multiplexed sequencing of microhaplotypes from the Plasmodium falciparum heterozygome

BackgroundTargeted next generation sequencing offers the potential for consistent, deep coverage of information rich genomic regions to characterize polyclonal Plasmodium falciparum infections. However, methods to identify and sequence these genomic regions are currently limited.MethodsA bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, WGS data were generated for the same controls.ResultsUsing publicly available genomes, 4465 high diversity genomic regions suited for targeted sequencing were identified, representing the P. falciparum heterozygome. For this study, 93 microhaplotypes with high diversity (median HE = 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%) and sensitivity (90% for haplotypes with 5% within sample frequency in DBS with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic SNP barcodes.DiscussionThe bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high throughput interrogation of the P. falciparum genome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.

Dynamic Measurement of Legs Motion in Sagittal Plane Based on Soft Wearable Sensors

Human motion capture is widely used in exoskeleton robots, human-computer interaction, sports analysis, rehabilitation training, and many other fields. However, soft-sensor-based wearable dynamic measurement has not been well achieved. In this paper, the dynamic measurements of legs were investigated by using dielectric elastomers as stain sensors, and an alternating signal was applied to detect the dynamic rotational angles of the legs. To realize a quick response, parameters of the sensors were optimized by circuit analysis. The sensor can detect hip, knee, and ankle joint motions with a sample frequency of 200 Hz. The measurements of the sensors were compared with a commercial motion capture system from PhaseSpace, and dynamic errors between them were smaller than 3° when squatting and walking at low speed and smaller than 5° when walking at high speed. Experiments therefore demonstrate the feasibility of the integrated wearable stretch sensors with pants.