Artificial Mixtures Research Articles

Towards quantifying microbial dispersal in the environment.

Towards quantifying microbial dispersal in the environment.

Comparison of Single Molecule, Real-Time Sequencing and Nanopore Sequencing for Analysis of the Size, End-Motif, and Tissue-of-Origin of Long Cell-Free DNA in Plasma.

Recent studies using single molecule, real-time (SMRT) sequencing revealed a substantial population of analyzable long cell-free DNA (cfDNA) in plasma. Potential clinical utilities of such long cfDNA in pregnancy and cancer have been demonstrated. However, the performance of different long-read sequencing platforms for the analysis of long cfDNA remains unknown. Size biases of SMRT sequencing by Pacific Biosciences (PacBio) and nanopore sequencing by Oxford Nanopore Technologies (ONT) were evaluated using artificial mixtures of sonicated human and mouse DNA of different sizes. cfDNA from plasma samples of pregnant women at different trimesters, hepatitis B carriers, and patients with hepatocellular carcinoma were sequenced with the 2 platforms. Both platforms showed biases to sequence longer (1500 bp vs 200 bp) DNA fragments, with PacBio showing a stronger bias (5-fold overrepresentation of long fragments vs 2-fold in ONT). Percentages of cfDNA fragments 500 bp were around 6-fold higher in PacBio compared with ONT. End motif profiles of cfDNA from PacBio and ONT were similar, yet exhibited platform-dependent patterns. Tissue-of-origin analysis based on single-molecule methylation patterns showed comparable performance on both platforms. SMRT sequencing generated data with higher percentages of long cfDNA compared with nanopore sequencing. Yet, a higher number of long cfDNA fragments eligible for the tissue-of-origin analysis could be obtained from nanopore sequencing due to its much higher throughput. When analyzing the size and end motif of cfDNA, one should be aware of the analytical characteristics and possible biases of the sequencing platforms being used.

Evaluation of 2-phosphatebutane-1, 2, 4-tricarboxylic acid as a depressant in the flotation separation of fluorite from barite

It is hard to separate barite from fluorite due to their similar surface properties. In this work, to achieve the separation of barite from fluorite, 2-phosphatebutane-1, 2, 4-tricarboxylic acid (PBTCA) was used to depress fluorite, and the floatability, separation efficiency and mechanism were researched by micro-flotation tests, zeta potential measurements, solution chemistry calculation and XPS analysis. Micro-flotation results showed that sodium dodecyl sulfonate (SDS) had an extremely good collecting capability for fluorite and barite, while PBTCA selectively depressed the floatability of fluorite and then allowed the recovery of barite. The flotation tests of artificial mineral mixtures showed that barite and fluorite can be effectively separated using PBTCA/SDS in a reasonable way. The zeta potential results indicated that PBTCA hindered the interaction of SDS with fluorite surface while had no influence on that for barite. The XPS analysis indicated that chemical interaction occurred between PBTCA and fluorite surface. Hence, it can be inferred PBTCA could be utilized as a promising depressant for the separation of fluorite from barite.

A Physicochemical Study of Cost-Effective Liquid Desiccants for Use in an air conditioning systems

Liquid desiccant systems (LDS) have attracted attention as promising low-energy alternative cooling solutions relative to conventional systems. An integral part of the LDS dehumidification capability depends on the composition of the hygroscopic desiccants utilized. The vapour pressure of different hygroscopic salt solutions and mixtures thereof have been measured at a temperature of 298.15K using a Yamamoto configuration. The initial validation of the measurement configuration using a single salt solution has exhibited a satisfactory correlation with vapour pressures reported by previous authors at various concentrations. The performance of MgCl2 solution was found to be comparable to that of LiCl. The results have shown that MgCl2 solution with 30% w/v concentration is sufficient to maintain the equilibrium relative humidity (ERH) at 50%, the recommended value for the human comfort zone, a value close to that obtained from LiCl solution (ERH = 55%) with the same concentration. Moreover, the best performing salt solution mixtures were found to be magnesium and lithium chlorides. Considering that the cost of LiCl is 23 times higher than that of MgCl2, the potential replacement of LiCl with MgCl2 in LDS is very promising from both a performance and cost point of view. The concentrated seawater brines have also shown a very promising performance comparable with that of 50% CaCl2– 50% MgCl2 artificial mixture.

Quantifying the contribution of dust sources in the arid area of northwest China using multivariate statistical techniques and Bayesian mixing models

In this study, topsoil samples and dust samples during dust storms were collected from the main dust source in northwest China, the geochemical elements were measured, and the contribution of dust sources was quantified using a discriminant function analysis (DFA) model and a MixSIAR model. Finally, the accuracy of the model was evaluated using an artificial mixture sample. The results showed that the dust sources and their contributions were significantly heterogeneous due to the natural and anthropogenic influences on the source-transport-sink process. DFA and MixSIAR models showed that the main dust sources in Dunhuang and Jiuquan were the Western Gobi and Western oasis, and Zhangye was mainly influenced by the Western Gobi, Western oasis, Middle Gobi, and Central oasis, with the influence of the Middle oasis being more pronounced. The Eastern Gobi, Eastern oasis, Badain Jaran desert, and Tengger desert have a greater influence on Jinchang, Wuwei, Baiyin, and Lanzhou. The contribution of each dust source in the Hexi region was found to show a significant distance effect. The accuracy of the models varied depending on the number of dust sources. The study provides new ideas for quantifying the contribution of dust source and for global dust storm control.

Investigation of the effects of particle size on the performance of classical gravity concentration equipment

ABSTRACT The use of gravity concentrators involves several challenges, such as determination of the liberation sizes of the minerals, selection of appropriate particle sizes for the applied concentration method, and the severity of the beneficiation of fines.In this study, the effects of fully liberated (artificial mixtures of magnetite and quartz) and non-liberated particles (chromite ore collected from a chromite processing plant) on various gravity concentration equipment were investigated as a function of particle size considering recoveries, separation efficiencies, and grades of products. A series of tests were conducted on shaking tables, spiral concentrators, and a Falcon concentrator with different design features under various operating conditions. Finally, the separation efficiencies were correlated with the settling rates of the particles.The test results confirmed a certain trend in the separation efficiency as a function of particle size for each condition. The separation efficiency initially increased with increasing particle size, peaked, and eventually decreased with increasing particle size. The maximum separation efficiency attained was 90% for 141 µm particles in the shaking table and 54% for 245 µm particles in the Falcon concentrator, both of which were used to treat the artificial feed. In the spiral concentrator, which treated chromite ore as feed, the maximum separation efficiency attained was 82% for 178 µm particles.This experimental study provides data to identify the concentration behavior of particles by investigating possible separation mechanisms. Consequently, it provides an understanding of the relationships between particle size and separation efficiency in terms of settling rates, especially in spiral concentrators.

Using particle size distributions to fingerprint suspended sediment sources—Evaluation at laboratory and catchment scales

AbstractApplications of sediment source fingerprinting studies are growing globally despite the high costs and workloads associated with the analyses of conventional fingerprint properties on target sediment samples collected using traditional methods. To this end, there is a need to test new fingerprint properties that can overcome these challenges. Sediment particle size could potentially contribute here since it is relatively easy to measure but, until now, has rarely been deployed as a fingerprint itself. Instead, particle size has been used to ensure that source and target sediment samples are more directly comparable on the basis of the fingerprints used. Accordingly, this work examined whether particle size distributions (PSDs) could be used as a reliable fingerprint for apportioning sediment sources, in combination with a grain size un‐mixing model. Application of PSDs as a fingerprint was tested at two scales: (i) in a laboratory setting where soil samples with known PSDs were used to generate artificial mixtures to evaluate un‐mixing model results, and (ii) a catchment setting comparing PSDs in a confluence‐based approach to test if downstream target sediment PSDs could be un‐mixed into the contributions of sediment coming from an upstream and a tributary sampling site. Laboratory results showed that the known proportions of the two, three and four soil samples in the artificial mixtures were predicted accurately using the AnalySize grain size un‐mixing model, giving average absolute errors of 9%, 8% and 6%, respectively. Catchment results showed variable performances when comparing un‐mixing results with sediment budget estimations, with the best results obtained at higher discharge values during storm runoff events. Overall, our results suggest the potential of using PSDs for estimating contributions of sediment sources delivering SS with distinct PSDs when sources are located at short distance to the downstream sampling site.

Assessing the lysis of diverse pollen from bulk environmental samples for DNA metabarcoding

Pollen is ubiquitous year-round in bulk environmental samples and can provide useful information on previous and current plant communities. Characterization of pollen has traditionally been completed based on morphology, requiring significant time and expertise. DNA metabarcoding is a promising approach for characterizing pollen from bulk environmental samples, but accuracy hinges on successful lysis of pollen grains to free template DNA. In this study, we assessed the lysis of morphologically and taxonomically diverse pollen from one of the most common bulk environmental sample types for DNA metabarcoding, surface soil. To achieve this, a four species artificial pollen mixture was spiked into surface soils collected from Colorado, North Carolina, and Pennsylvania, and subsequently subjected to DNA extraction using both the PowerSoil and PowerSoil Pro Kits (Qiagen) with a heated incubation (either 65 °C or 90 °C). Amplification and Illumina sequencing of the internal transcribed spacer subunit 2 (ITS2) was completed in duplicate for each sample (total n, 76), and the resulting sequencing reads taxonomically identified using GenBank. The PowerSoil Pro Kit statistically outperformed the PowerSoil Kit for total DNA yield. When using either kit, incubation temperature (65 °C or 90 °C) used had no impact on the recovery of DNA, plant amplicon sequence variants (ASVs), or total plant ITS2 reads. This study highlighted that lysis of pollen in bulk environmental samples is feasible using commercially available kits, and downstream DNA metabarcoding can be used to accurately characterize pollen DNA from such sample types.

Conversion of Syngas from Entrained Flow Gasification of Biogenic Residues with Clostridium carboxidivorans and Clostridium autoethanogenum

Synthesis gas fermentation is a microbial process, which uses anaerobic bacteria to convert CO-rich gases to organic acids and alcohols and thus presents a promising technology for the sustainable production of fuels and platform chemicals from renewable sources. Clostridium carboxidivorans and Clostridium autoethanogenum are two acetogenic bacteria, which have shown their high potential for these processes by their high tolerance toward CO and in the production of industrially relevant products such as ethanol, 1-butanol, 1-hexanol, and 2,3-butanediol. A promising approach is the coupling of gasification of biogenic residues with a syngas fermentation process. This study investigated batch processes with C. carboxidivorans and C. autoethanogenum in fully controlled stirred-tank bioreactors and continuous gassing with biogenic syngas produced by an autothermal entrained flow gasifier on a pilot scale >1200 °C. They were then compared to the results of artificial gas mixtures of pure gases. Because the biogenic syngas contained 2459 ppm O2 from the bottling process after gasification of torrefied wood and subsequent syngas cleaning for reducing CH4, NH3, H2S, NOX, and HCN concentrations, the oxygen in the syngas was reduced to 259 ppm O2 with a Pd catalyst before entering the bioreactor. The batch process performance of C. carboxidivorans in a stirred-tank bioreactor with continuous gassing of purified biogenic syngas was identical to an artificial syngas mixture of the pure gases CO, CO2, H2, and N2 within the estimation error. The alcohol production by C. autoethanogenum was even improved with the purified biogenic syngas compared to reference batch processes with the corresponding artificial syngas mixture. Both acetogens have proven their potential for successful fermentation processes with biogenic syngas, but full carbon conversion to ethanol is challenging with the investigated biogenic syngas.

Citric acid secretion from rice roots contributes to reduction and immobilization of Cr(VI) by driving microbial sulfur and iron cycle in paddy soil

Root exudates released by plants can promote microbial growth and activity, thereby affecting the transformation and availability of soil pollutants. However, the effects of the root exudates of rice plants on chromium (Cr) transformation in paddy soils and the underlying mechanisms are yet to be elucidated properly. The present study investigated how rice root exudates interact with rhizosphere microorganisms to influence the transformation of Cr and explored the key components in root exudates that affect Cr(VI) reduction. The results showed that the addition of root exudate and citric acid markedly decreased soil pH and increased dissolved organic carbon content that created favorable conditions and provided sufficient electron donors for Cr(VI) reduction, thereby greatly facilitating the reduction of Cr(VI) and the transformation of HOAc-extractable Cr into more stable oxidizable and residual Cr. Additionally, Desulfovibrio-related sulfate-reducing bacteria, Thiobacillus-related sulfide-oxidizing bacteria, and Geobacter-related Fe(III)-reducing bacteria were enriched with the addition of root exudate and citric acid. Among them, sulfate would be reduced by Desulfovibrio to sulfide, which would be further utilized by Thiobacillus to reduce Cr(VI), thereby enabling the continuous reduction of Cr(VI); simultaneously, Geobacter would sustain the reduction of Cr(VI) by reducing Fe(III) to Fe(II). Furthermore, based on the high-level secretion of citric acid in response to Cr(VI) exposure and the similar effects of root exudates and citric acid on Cr(VI) reduction, it is proposed that citric acid is the key component in rice root exudates that affects Cr(VI) reduction. These results suggest that root exudates (citric acid as the key component) contribute to the reduction and immobilization of Cr(VI) by driving microbial S and Fe cycles, with Desulfovibrio, Thiobacillus, and Geobacter being the keystone genera. The study provides a novel insight into the Fe/S/Cr co-transformation processes with microbial involvement, and the artificial root exudate mixtures designed to reduce Cr(VI).

216.17: Multiplex Digital PCR for the Detection of Donor-derived Cell-free DNA

Introduction: Graft damage and failure are major problems after solid-organ transplantation. Biomarkers for monitoring transplanted patients provide new opportunities to substantially improve patient management, graft lifespan, and patient survival. There is strong evidence that donor-derived cell-free DNA (DD-cfDNA) increases when transplanted organs are damaged. The majority of this information is derived from tests using next-generation sequencing. Here we present an evaluation of new technology, multiplex digital PCR (mdPCR), which has the potential to revolutionize DD-cfDNA testing. Method: This mdPCR method takes advantage of Luminex’s DigiMAP multiplex PCR chemistry and the QuantStudio Absolute Q Digital PCR platform (Thermo Fisher Scientific, previously Combinati). The bench work for mdPCR is completed in less than five hours. Data is analyzed using a custom R package. Assay performance characteristics were determined using artificial mixtures of genomic DNA, and inter-laboratory reproducibility was assessed. Blood was collected from kidney and heart transplant recipients, cf-DNA was isolated using a variety of methods, and mdPCR was used to quantify DD-cfDNA levels. Results: This methodology distinguished donor and recipient DNA and provided absolute quantification of the number of DNA copies. The following performance characteristics were determined: sensitivity, the limit of detection, and linear range, inter- and intra- assay consistency. Several factors affected performance including: DNA characteristics, probe design, primer design, and PCR reaction components. Results showed that high levels of DD-cfDNA are consistent with clinical observations and that rapid testing is feasible (< five hours). Conclusion: The mdPCR approach has high promise to revolutionize diagnostic testing in cancer, infectious disease, and transplant monitoring. Our study demonstrates the advantages of this technology for the detection of DD-cfDNA which includes absolute quantitation, sensitivity, ease of use, short turn-around-time, and a relatively low cost when compared to next-generation sequencing techniques. A test with these features could transform the management of transplant recipients and lead to prolonged graft and patient survival.

Reprocessing of magnesite beneficiation waste to recover mineral value and minimise environmental footprint

The current paper deals with the re-processing of mineralised mine waste from magnesite processing operations aiming at the recovery of the value. Two cases of mineralised waste were examined. First, waste derived from the removal of “fine” before hand-sorting, with particle size of -40 mm; this waste is usually stockpiled, comprises mostly of relatively coarse particles and is of relatively high-grade in magnesite. The separation methods applied were sorting, sink-float tests and magnetic separation. In general, the results from the application of physical separation methods were satisfactory. Commercial concentrates were obtained from sorting with MgCO3-grade ranging between 94 and 97% MgCO3 and yield about 46%; in case of mixing concentrate with middling, yield rises to 58-64% while grade slightly drops to 91-94%. Equally satisfactory were the results from sink-float separation at sp.gr. 2.88 (grade 95%, yield 45%) but questions arise from the small sp.gr. difference of magnesite and gangues. Finally, the less satisfactory results obtained from magnetic separation (grade around 80-85%, yield 33-65%) may be due to inefficient particles liberation and higher magnetic field is maybe required. Second, mineralised waste consisting of fine particles from size reduction operations were tested. These fines were processed with selective magnetic coating as well as co-agglomeration / magnetic separation techniques. In general, the results of physicochemical processing of fines were very encouraging both on single minerals and their artificial mixtures. In case of magnetic coating, the effect of pH, collector concentration and kerosene dose was studied first on single minerals. Optimum results were obtained for pH=9, dodecylamine solution 4.5x10-5 M and kerosene 2.5 L/t. Tests on artificial mineral mixtures at optimum conditions and magnetic separation at 0.8 A resulted in non-magnetic product with MgCO3-grade higher than 99%. The parameters examined in co-agglomeration / magnetic separation tests were the same as with magnetic coating. Best conditions for co-agglomeration on single minerals were pH=8, dodecylamine 2 kg/t, kerosene 4 L/t. Tests on mineral mixture reveals that the MgCO3-grade increases with dodecylamine but the yield drops.

Continuous wavelet transform approach for the assay of active components in tablets

Two continuous wavelets transform (CWT) methods were developed for the simultaneous determination of candesartan cilexetil (CAN) and hydrochlorothiazide (HCT) in tablets. The CWT methods were applied to the ratio spectra (RS) of the CAN and HCT. The CWT approaches based on the application of Haar and Mexican hat function (RS-HAAR-CWT and RS-MEXH-CWT, respectively) to the transformation of the ratio spectra were found to be suitable to reach a good spectral quantification. In the use of transformed ratio spectra, the calibration graphs for CAN and HCT were computed by using the RS-CWT-amplitudes at 244.5 and 264.5 nm in RS-HAAR-CWT spectra and at 255.6 and 250.0 nm in RS-MEXH-CWT spectra, respectively. The LOD and LOQ values for RS-HAAR-CWT and RS-MEXH-CWT were 0.39 - 0.58 and 0.43 - 0.33, 1.28 - 1.92 and 1.44 - 1.10 for CAN and HCT, respectively. The recovery results obtained by applying RS-HAAR-CWT and RS-MEXH-CWT calibrations to the artificial mixtures were found between 99.3 and 103.5% and obtained RSD values were found between 1.38 and 2.42. The validity and applicability of the CWT methods was performed by using the recovery study, standard addition technique and intra-day and inter-day tests. The proposed methods were successfully applied to the analysis of the CAN- HCT tablets.

Understanding the Entrainment Behavior of Gangue Minerals in Flake Graphite Flotation

Flotation is one of the most used methods to upgrade natural graphite resources. However, the efficiency is usually decreased due to the entrainment of undesirable fine gangue minerals. In this work, the impact of different factors such as particle size, pulp density, and flotation reagent on the entrainment of mica and quartz in a flake graphite flotation was studied. The single gangue mineral flotation results showed increased gangue entrainment when reducing the particle size of gangue minerals and increasing the pulp density. Moreover, the flotation of artificial mixtures indicated enhanced entrainment of mica and quartz in the presence of graphite particles. The collector and frother also strongly affect gangue entrainment by modifying the structure and stability of the froth. Kerosene, which has a prominent deforming feature, can reduce gangue entrainment more effectively than diesel.

Integration of leave-one-out method and real-time live cell reporter array system to assess the toxicity of mixtures

The ever-increasing number of chemicals and complex mixtures demands a time-saving and cost-effective platform for environmental risk assessment. However, there is limit promising tool for evaluating the contribution of each component to the total toxicity effects of the mixture. Here, four widely distributed environmental pollutants with different mode-of-actions, i.e., cadmium chloride (Cd), nitrofurazone (NFZ), triclosan (TCS), and tris(2-chloroethyl) phosphate (TCEP), were selected as components of artificial mixture. Integration of leave-one-out method and high-dimensional live cell array system was used to explore relative contribution of each component from the mixture. A quaternary mixture (All_4_chems) and four ternary mixtures (Leave_Cd, Leave_NFZ, Leave_TCS and Leave_TCEP) were investigated by Escherichia coli (E. coli) live cell array system with 90 environmental stress genes modified by green fluorescent protein (GFP) expressing reporter vectors. E. coli cytotoxicity tests demonstrated that TCS has antagonism effect with other three chemicals (Cd, NFZ and TCEP), while it was additive effect in other three binary combinations. A total of 26, 23, 13, 31 and 23 genes were significantly altered with fold-change greater than 2 over the 4 h exposure by All_4_chems, Leave_Cd, Leave_NFZ, Leave_TCS and Leave_TCEP, respectively. Clustering analysis based on time-series gene expression patterns and transcriptional effect level index (TELI) showed that Leave_TCEP has similar profiles with All_4_chems, demonstrating TCEP has the least contribution among four components to the quaternary mixture. Leave_NFZ has the least number of significantly altered genes, implying NFZ has the largest toxicity effect contribution to the quaternary mixture. The relative contribution in different pathways indicated that Cd has the most contribution to the mixture in redox stress, while TCS has the least contribution in DNA stress pathway. Collectively, our results demonstrated the utility of high-dimensional toxicogenomics data and leave-one-out method in prioritizing the relative contribution of each component in mixture.

Using Deep Neural Networks for On-Load Tap Changer Audio-Based Diagnostics

This paper proposes a sound separation methodology based on deep learning neural network (DLNN) to extract useful diagnostic material in non-invasive audio-based On-Load Tap Changer (OLTC) diagnostics. The proposed methodology has been experimentally verified on both artificial mixtures (created by reproducing the targeted data by the speakers placed next to the active transformers) and actual mixtures (recorded by the microphone during OLTC live operation in the field). The results show that the method produces high-quality estimates (correlation to referent fingerprints <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rho &gt; 0.9$</tex-math></inline-formula> ) compared to other sound separation methods, e.g. Independent Component Analysis (ICA). The proposed framework can also perform source separation from a monaural mixture (mixture recorded with a single microphone only), which is impossible for ICA methods. Moreover, the results show that DLNN trained with healthy OLTC data produces diagnostically valuable estimates even when fed with a faulty OLTC audio mixture. For that reason, once trained, the DLNN can produce the diagnostic signal estimates from monaural mixtures that can be used with existing vibration-based diagnostic methods.

Forecasting worldwide empty container availability with machine learning techniques

Due to imbalances in the global transport of containerised goods, liner shipping companies go to great lengths to match the regional supply and demand for empty containers by transporting equipment from surplus to deficit regions. Making accurate forecasts of regional empty container availability could support liner companies and other involved actors by making better relocation decisions, thus avoiding unnecessary transport costs of empty equipment. Previously proposed container availability prediction models are limited to the application in individual regions and typically characterized by a high degree of temporal aggregation. Against this background, this paper introduces two novel approaches based on machine learning and probabilistic techniques to predict the future weekly availability of empty containers for more than 280 locations worldwide. The machine learning and probabilistic prediction models are built by analysing a unique data set of more than 100 million events from past container journeys. These events represent different stages during the transport process of a container. Both models use a two-step forecast logic. First, the expected future location of a container is predicted. Second, the expected timestamp for arriving at that location is estimated. The machine learning model uses artificial neural networks and mixture density networks to forecast the movements of containers. The models are quantitatively assessed and compared to the actual availability of containers and two more conventional forecasting approaches. The results indicate that the probabilistic prediction approach can keep up with conventional approaches while the neural network approach significantly outperforms the other approaches concerning every evaluation metric.

Use of a Hydrophobic Azo Dye for the Centrifuge-Less Cloud Point Extraction-Spectrophotometric Determination of Cobalt.

The hydrophobic azo dye 6-hexyl-4-(2-thiazolylazo)resorcinol (HTAR, H2L) was studied as part of a system for the centrifuge-less cloud point extraction (CL-CPE) and spectrophotometric determination of traces of cobalt. The extracted 1:2 (Co:HTAR) complex, [CoIII(HL−)(L2−)]0, shows an absorption maximum at 553 nm and contains HTAR in two different acid–base forms. Optimum conditions for its formation and CL-CPE were found as follows: 1 × 10−5 mol L−1 of HTAR, 1.64% of Triton X-114, pH of 7.8, incubation time of 20 min at ca. 50 °C, and cooling time of 30 min at ca. −20 °C. The linear range, limit of detection, and apparent molar absorptivity coefficient were 5.4–189 ng mL−1, 1.64 ng mL−1, and 2.63 × 105 L mol−1 cm−1, respectively. The developed procedure does not use any organic solvents and can be described as simple, cheap, sensitive, convenient, and environmentally friendly. It was successfully applied to the analysis of artificial mixtures and real samples, such as steel, dental alloy, rainwater, ampoules of vitamin B12, and saline solution for intravenous infusion.

Comparison of Blind Source Separation Methods to Surface Electromyogram for Extensor Muscles of the Index and Little Fingers.

Crosstalk is the result of the propagation of muscle electrical signals on surface electromyogram channels simultaneously. The objective of this paper is to study the behavior of three blind source separation (BSS) methods for crosstalk reduction during finger extensor muscle contractions: FastICA, joint diagonalization of covariance matrices and optimal filtering. These methods have been tested on artificial mixtures defined by a temporal sum of the real signals from isolated contraction of two independent biomechanical muscles for the extension of the index and little finger. Artificial mixtures display a ground truth for comparison between the methods. The separation was better using the optimal filtering compared to the other two methods. The optimal filtering have then be tested on real mixtures recorded during a simultaneous contraction of the two muscles. The results are less satisfactory but open doors to new perspectives.

Muscle Artifact Removal in Single-Channel Electrocardiograms using Temporal Convolutional Networks.

The electrocardiogram (ECG) is a vital diagnostic tool used in many health applications. In practice, interference by muscle artifacts is very common and may significantly complicate interpretation of the ECG waveform. In this work we investigate the removal of muscle artifacts in single-channel ECG signals using neural network models. To this end, we compare two neural network architectures which were previously used for ECG denoising and propose a novel third method based on the ConvTasNet. The neural networks are trained on simulated data using artificial mixtures of single-channel ECG (lead II) and surface EMG signals taken from publicly available datasets. ECG data were sampled from the MIT-BIH Arrhythmia and the PTB-XL database. The former provides recordings of ambulatory ECGs while the latter contains a large variety of cardiac pathologies recorded in a clinical setting. The muscle artifacts were sampled from the MIT-BIH Noise Stress Test database and the TaiChi database. In the past, most denoising methods were only tested on the two smaller MIT-BIH datasets. In this work, we report performances on larger datasets and thus provide stronger evidence for a clinical use-case. We also report out-of distribution performance of the three methods by switching the ECG dataset between training and test. The herein investigated variant of the ConvTasNet substantially reduces interference by muscle artifacts, outperforms state-of-the-art methods and thus, may support clinical decision making.