A Morphology-Preserving Algorithm for Denoising of EMG-Contaminated ECG Signals.

Goal: Clinical interpretation of an electrocardiogram (ECG) can be detrimentally affected by noise. Removal of the electromyographic (EMG) noise is particularly challenging due to its spectral overlap with the QRS complex. The existing EMG-denoising algorithms often distort signal morphology, thus obscuring diagnostically relevant information. Methods: Here, a new iterative regeneration method (IRM) for efficient EMG-noise suppression is proposed. The main hypothesis is that the temporary removal of the dominant ECG components enables extraction of the noise with the minimum alteration to the signal. The method is validated on SimEMG database of simultaneously recorded reference and noisy signals, MIT-BIH arrhythmia database and synthesized ECG signals, both with the noise from MIT Noise Stress Test Database. Results: IRM denoising and morphology-preserving performance is superior to the wavelet- and FIR-based benchmark methods. Conclusions: IRM is reliable, computationally non-intensive, fast and applicable to any number of ECG channels recorded by mobile or standard ECG devices.

Mobocertinib in Patients with EGFR Exon 20 Insertion-Positive Non-Small Cell Lung Cancer (MOON): An International Real-World Safety and Efficacy Analysis.

EGFR exon 20 (EGFR Ex20) insertion mutations in non-small cell lung cancer (NSCLC) are insensitive to traditional EGFR tyrosine kinase inhibitors (TKIs). Mobocertinib is the only approved TKI specifically designed to target EGFR Ex20. We performed an international, real-world safety and efficacy analysis on patients with EGFR Ex20-positive NSCLC enrolled in a mobocertinib early access program. We explored the mechanisms of resistance by analyzing postprogression biopsies, as well as cross-resistance to amivantamab. Data from 86 patients with a median age of 67 years and a median of two prior lines of treatment were analyzed. Treatment-related adverse events (TRAEs) occurred in 95% of patients. Grade ≥3 TRAEs were reported in 38% of patients and included diarrhea (22%) and rash (8%). In 17% of patients, therapy was permanently discontinued, and two patients died due to TRAEs. Women were seven times more likely to discontinue treatment than men. In the overall cohort, the objective response rate to mobocertinib was 34% (95% CI, 24-45). The response rate in treatment-naïve patients was 27% (95% CI, 8-58). The median progression-free and overall survival was 5 months (95% CI, 3.5-6.5) and 12 months (95% CI, 6.8-17.2), respectively. The intracranial response rate was limited (13%), and one-third of disease progression cases involved the brain. Mobocertinib also showed antitumor activity following EGFR Ex20-specific therapy and vice versa. Potential mechanisms of resistance to mobocertinib included amplifications in MET, PIK3CA, and NRAS. Mobocertinib demonstrated meaningful efficacy in a real-world setting but was associated with considerable gastrointestinal and cutaneous toxicity.

A novel variable neighborhood search approach for cell clustering for spatial transcriptomics.

This paper introduces a new approach to cell clustering using the Variable Neighborhood Search (VNS) metaheuristic. The purpose of this method is to cluster cells based on both gene expression and spatial coordinates. Initially, we confronted this clustering challenge as an Integer Linear Programming minimization problem. Our approach introduced a novel model based on the VNS technique, demonstrating the efficacy in navigating the complexities of cell clustering. Notably, our method extends beyond conventional cell-type clustering to spatial domain clustering. This adaptability enables our algorithm to orchestrate clusters based on information gleaned from gene expression matrices and spatial coordinates. Our validation showed the superior performance of our method when compared to existing techniques. Our approach advances current clustering methodologies and can potentially be applied to several fields, from biomedical research to spatial data analysis.

A Database of Simultaneously Recorded ECG Signals With and Without EMG Noise.

Goal: Noise on recorded electrocardiographic (ECG) signals may affect their clinical interpretation. Electromyographic (EMG) noise spectrally coincides with the QRS complex, which makes its removal particularly challenging. The problem of evaluating the noise-removal techniques has commonly been approached by algorithm testing on the contaminated ECG signals constructed ad hoc as an additive mixture of a noise-free ECG signal and noise. Consequently, there is an absence of a unique/standard database for testing and comparing different denoising methods. We present a SimEMG database recorded by a novel acquisition method that allows for direct recording of the genuine EMG-noise-free and -contaminated ECG signals. The database is available as open source.

Microstructural Analysis of Thermally Treated Geopolymer Incorporated with Neodymium.

The following investigation presents the thermal treatment of geopolymer at 300 °C, 600 °C and 900 °C. We investigated what happens to the geopolymer base when incorporated with 1% and 5% of neodymium in the form Nd2O3. A total of six samples were synthesized. Geopolymer 1 contained 1% and geopolymer 2 contained 5% Nd2O3, and these samples were treated at 300 °C; then, samples geopolymer 3 and geopolymer 4 also had the same percentage composition of Nd2O3 and were treated at 600 °C, while samples geopolymer 5 and geopolymer 6were treated at 900 °C. Physical and chemical changes in the aluminosilicate geopolymer matrix were monitored. The incorporation of rare earths into the polymer network of aluminosilicates has been proven to disrupt the basic structure of geopolymers; however, with increased temperatures, these materials show even more unusual properties. Diffuse reflectance infrared Fourier transform (DRIFT) analysis showed that the intensity of the vibrational band decreases with the increase in temperature during thermal treatment, suggesting alterations in the chemical structure of the geopolymers. Transmission electron microscopy (TEM) analysis showed that the diameter of the nanoparticles containing Al2O3 is in the range 5-10 nm, while larger crystallites range from 30 to 80 nm. Scanning electron microscopy (SEM) analysis revealed that the temperature of the thermal treatment increases to 300 °C and 600 °C; the porosity of geopolymer increases in the form of the appearance of large pores and cracks in material. X-ray photoelectron spectroscopy (XPS) analysis was used to investigate the surface chemistry of geopolymers, including the chemical composition of the surface, the oxidation state of the elements, and the presence of functional groups. The UV/Vis spectra of the synthesized geopolymers doped with Nd3+ show interesting optical properties at 900 °C; the geopolymer matrix completely disintegrates and an amorphous phase with a rare-earth precipitate appears.

Increased tryptophan, but not increased glucose metabolism, predict resistance of pembrolizumab in stage III/IV melanoma.

Clinical trials of combined IDO/PD1 blockade in metastatic melanoma (MM) failed to show additional clinical benefit compared to PD1-alone inhibition. We reasoned that a tryptophan-metabolizing pathway other than the kynurenine one is essential. We immunohistochemically stained tissues along the nevus-to-MM progression pathway for tryptophan-metabolizing enzymes (TMEs; TPH1, TPH2, TDO2, IDO1) and the tryptophan transporter, LAT1. We assessed tryptophan and glucose metabolism by performing baseline C11-labeled α-methyl tryptophan (C11-AMT) and fluorodeoxyglucose (FDG) PET imaging of tumor lesions in a prospective clinical trial of pembrolizumab in MM (clinicaltrials.gov, NCT03089606). We found higher protein expression of all TMEs and LAT1 in melanoma cells than tumor-infiltrating lymphocytes (TILs) within MM tumors (n = 68). Melanoma cell-specific TPH1 and LAT1 expressions were significantly anti-correlated with TIL presence in MM. High melanoma cell-specific LAT1 and low IDO1 expression were associated with worse overall survival (OS) in MM. Exploratory optimal cutpoint survival analysis of pretreatment 'high' vs. 'low' C11-AMT SUVmax of the hottest tumor lesion per patient revealed that the 'low' C11-AMT SUVmax was associated with longer progression-free survival in our clinical trial (n = 26). We saw no such trends with pretreatment FDG PET SUVmax. Treatment of melanoma cell lines with telotristat, a TPH1 inhibitor, increased IDO expression and kynurenine production in addition to suppression of serotonin production. High melanoma tryptophan metabolism is a poor predictor of pembrolizumab response and an adverse prognostic factor. Serotoninergic but not kynurenine pathway activation may be significant. Melanoma cells outcompete adjacent TILs, eventually depriving the latter of an essential amino acid.

Design of PEI and Amine Modified Metakaolin-Brushite Hybrid Polymeric Composite Materials for CO2 Capturing.

In this paper, the properties of organic-inorganic hybrid polymer materials, which were synthesized from an aluminosilicate inorganic matrix with the addition of brushite and aminosilane grafted on one side and PEI covalently bonded composites on the other side, were examined. The synthesized organic-inorganic hybrid polymers were examined in terms of a structural, morphological, thermo-gravimetric, and adsorption-desorption analysis and also as potential CO2 capturers. The structural and phase properties as well as the percentage contents of the crystalline and amorphous phase were determined by the X-ray diffraction method. The higher content of the amorphous phase in the structure of hybrid polymers was proven in metakaolin and metakaolin-brushite hybrid samples with the addition of amino silane and with 1,000,000 PEI in a structure. The DRIFT method showed the main band changes with the addition of an organic phase and inorganic matrix. Microstructural studies with the EDS analysis showed a uniform distribution of organic and inorganic phases in the hybrid geopolymers. The thermo-gravimetric analysis showed that organic compounds are successfully bonded to inorganic polymer matrix, while adsorption-desorption analysis confirmed that the organic phase completely covered the surface of the inorganic matrix. The CO2 adsorption experiments showed that the amine-modified composites have the higher capture capacity, which is 0.685 mmol·g-1 for the GM10 sample and 0.581 mmol·g-1 for the BGM10 sample, with 1,000,000 PEI in the structure.

Distribution of Natural Radionuclides and 137Cs in Urban Soil Samples from the City of Novi Sad, Serbia-Radiological Risk Assessment.

This work presents the natural radioactivity distribution of 21 surface soil samples taken in the city of Novi Sad, Serbia. The analysis for radioactivity was performed using a gas low-level proportional counter for gross alpha and gross beta activity, while the specific activities of radionuclides were determined using HPGe detectors. The gross alpha activity of 20 samples was below the minimum detectable concentration (MDC), while in 1 sample it was 243 Bq kg-1; the gross beta activity ranged from the MDC (11 samples) to 566 Bq kg-1. The gamma spectrometry measurements showed naturally occurring radionuclides 226Ra, 232Th, 40K, and 238U in all investigated samples, with average values (Bq kg-1) of 33.9, 36.7, 513.8, and 34.7, respectively. Natural radionuclide 235U was detected in 18 samples with activity concentrations in the range of 1.3-4.1 Bq kg-1, while in the other 3 samples, the values were below the MDC. The artificial 137Cs radionuclide was detected in 90 percent of the samples, with a maximum value of 21 Bq kg-1, while the other artificial radionuclides were not detected. Based on the obtained concentrations of natural radionuclides, hazard indexes were estimated, and radiological health risk was assessed. The results present the absorbed gamma dose rate in the air, annual effective dose, radium equivalent activity, external hazard index, and lifetime cancer risk.

Novel approach for strontium preconcentration from seawater and rapid determination of 89,90Sr in emergency situations.

A novel approach for rapid 89,90Sr determination in seawater samples is developed. For the first time in the radioanalytical application, the features of the synthetic zeolite Z4A and a highly selective material for Sr separation were synergically employed. Seawater composition significantly reduces Sr yield on highly selective solid-phase extraction materials, making the preconcentration step essentially important but laborious and time-consuming. To address this issue, the ability of zeolite 4A to concentrate the Sr from the seawater matrix was employed. With the proposed method, two important goals were achieved: (i) simple preconcentration of Sr that can be conducted directly at the sampling site, enabling a rapid procedure for 89,90Sr determination in emergencies, and (ii) high and stable Sr recoveries (89 ± 4%) necessary for lowering detection limits. Strontium is effectively separated from 1 L of seawater in less than 1.5 h, which is especially important in emergency situations, such as the Fukushima Daiichi Nuclear Power Plant accident. Minimum detectable activities achieved for 89Sr:90Sr activity ratio ∼10:1 were 0.74 Bq/L for 89Sr, and 1.47 Bq/L for 90Sr, detected by Cherenkov counting, 36-38 h after separation, and 30 min counting time.

Heat Treatment of Geopolymer Samples Obtained by Varying Concentration of Sodium Hydroxide as Constituent of Alkali Activator.

In this paper, raw natural metakaolin (MK, Serbia) clay was used as a starting material for the synthesis of geopolymers for thermal treatment. Metakaolin was obtained by calcination of kaolin at 750 °C for 1 h while geopolymer samples were calcined at 900 °C, which is the key transition temperature. Metakaolin was activated by a solution of NaOH of various concentrations and sodium silicate. During the controlled heat treatment, the geopolymer samples began to melt slightly and coagulate locally. The high-temperature exposure of geopolymer samples (900 °C) caused a significant reduction in oxygen, and even more sodium, which led to the formation of a complex porous structure. As the concentration of NaOH (6 mol dm-3 and 8 mol dm-3) increased, new semi-crystalline phases of nepheline and sanidine were formed. Thermal properties were increasingly used to better understand and improve the properties of geopolymers at high temperatures. Temperature changes were monitored by simultaneous use of thermogravimetric analysis (TGA) and differential thermal analysis (DTA). The loss of mass of the investigated samples at 900 °C was in the range of 8-16%. Thermal treatment of geopolymers at 900 °C did not have much effect on the change in compressive strength of investigated samples. The results of thermal treatment of geopolymers at 900 °C showed that this is approximately the temperature at which the structure of the geopolymer turns into a ceramic-like structure. All investigated properties of the geopolymers are closely connected to the precursors and the constituents of the geopolymers.

Solid cancer patients achieve adequate immunogenicity and low rate of severe adverse events after SARS-CoV-2 vaccination.

Background: SARS-CoV-2 vaccination in cancer patients is crucial to prevent severe COVID-19 disease course. Methods: This study assessed immunogenicity of cancer patients on active treatment receiving mRNA-based SARS-CoV-2 vaccine by detection of anti-SARS-CoV-2 S1 IgG antibodies in serum, before, after the first and second doses and 3 months after a complete primary course of vaccination. Results were compared with healthy controls. Results: Of 112 patients, the seroconversion rate was 96%. A significant reduction in antibody levels was observed 3 months after vaccination in patients receiving immune checkpoint inhibitors versus control participants (p < 0.001). Adverse events were mostly mild. Conclusion: Immunogenicity after mRNA-based vaccine in cancer patients is adequate but influenced by the type of anticancer therapy. Antibody levels decline after 3 months, and thus a third vaccination is warranted.

Because cancer patients are especially endangered by SARS-CoV-2 infection and have worse disease course and outcomes, it is crucial to protect them from this infection. This study was aimed at assessing protective antibodies after patients received mRNA-based SARS-CoV-2 vaccines. Protective antibodies (e.g., anti-SARS-CoV-2 S1 IgG antibodies) were assessed in patients' blood before vaccination, after the first and second doses and 3 months after a complete primary course vaccination. Patients' oncological treatment was unaffected by the vaccination received. The results of protective antibodies were also compared with healthy control subjects who were vaccinated in the same manner. More than 110 cancer patients participated and agreed to have their blood samples analyzed. The rate of antibody production was 96% after a complete primary course of vaccination and was similar with that of healthy control subjects. However, there were some differences noted regarding the oncological treatment that the patients were receiving, with patients who were treated with targeted therapy achieving the highest levels of protective antibodies. Adverse events after vaccination were mostly mild and did not interfere with patients' general performance. The rate of antibody production for cancer patients after SARS-CoV-2 vaccination is high and similar to that in healthy control subjects but varies with regard to the oncological treatment that patients are receiving. However, antibodies decline substantially after 3 months, and thus a third vaccination is desirable. There were no new safety concerns after vaccination, and most adverse events were mild and short-lived.

The influence of atrial flutter in automated detection of atrial arrhythmias - are we ready to go into clinical practice?"

OBJECTIVE: To investigate the impact of atrial flutter (Afl) in the atrial arrhythmias classification task. We additionally advocate the use of a subject-based split for future studies in the field in order to avoid within-subject correlation which may lead to over-optimistic inferences. Finally, we demonstrate the effectiveness of the classifiers outside of the initially studied circumstances, by performing an inter-dataset model evaluation of the classifiers in data from different sources. METHODS: ECG signals of two private and three public (two MIT-BIH and Chapman ecgdb) databases were preprocessed and divided into 10s segments which were then subject to feature extraction. The created datasets were divided into a training and test set in two ways, based on a random split and a patient split. Classification was performed using the XGBoost classifier, as well as two benchmark classification models using both data splits. The trained models were then used to make predictions on the test data of the remaining datasets. RESULTS: The XGBoost model yielded the best performance across all datasets compared to the remaining benchmark models, however variability in model performance was seen across datasets, with accuracy ranging from 70.6% to 89.4%, sensitivity ranging from 61.4% to 76.8%, and specificity ranging from 87.3% to 95.5%. When comparing the results between the patient and the random split, no significant difference was seen in the two private datasets and the Chapman dataset, where the number of samples per patient is low. Nonetheless, in the MIT-BIH dataset, where the average number of samples per patient is approximately 1300, a noticeable disparity was identified. The accuracy, sensitivity, and specificity of the random split in this dataset of 93.6%, 86.4%, and 95.9% respectively, were decreased to 88%, 61.4%, and 89.8% in the patient split, with the largest drop being in Afl sensitivity, from 71% to 5.4%. The inter-dataset scores were also significantly lower than their intra-dataset counterparts across all datasets. CONCLUSIONS: CAD systems have great potential in the assistance of physicians in reliable, precise and efficient detection of arrhythmias. However, although compelling research has been done in the field, yielding models with excellent performances on their datasets, we show that these results may be over-optimistic. In our study, we give insight into the difficulty of detection of Afl on several datasets and show the need for a higher representation of Afl in public datasets. Furthermore, we show the necessity of a more structured evaluation of model performance through the use of a patient-based split and inter-dataset testing scheme to avoid the problem of within-subject correlation which may lead to misleadingly high scores. Finally, we stress the need for the creation and use of datasets with a higher number of patients and a more balanced representation of classes if we are to progress in this mission.

Structural and Chemical Properties of Geopolymer Gels Incorporated with Neodymium and Samarium.

The present work was focused on doping of 1% and 5% both of Nd2O3 and Sm2O3 in geopolymer gels. One of the main goals was to determine the influence of the behavior of Nd and Sm as dopants and structural nanoparticles changes of the final geopolymer formed. It is shown that the disorder formed by alkali activation of metakaolin can accommodate the rare earth cations Nd3+ and Sm3+ into their aluminosilicate framework structure. The main geopolymerization product identified in gels is Al-rich (Na)-AS-H gel comprising Al and Si in tetrahedral coordination. Na+ ions were balancing the negative charge resulting from Al3+ in tetrahedral coordination. The changes in the structures of the final product (geopolymer/Nd2O3; Sm2O3), has been characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) analysis with energy dispersive spectrometry (EDS). Nucleation at the seed surfaces leads to the formation of phase-separated gels from rare earth phase early in the reaction process. It is confirmed that Nd and Sm have been shown to form unstable hydroxides Nd(OH)3 and Sm(OH)3 that are in equilibrium with the corresponding oxides.

Immunotherapy for Metastatic Non-Small Cell Lung Cancer: Real-World Data from an Academic Central and Eastern European Center.

BACKGROUND: Immunotherapy with immune checkpoint inhibitors (ICIs) recently became the standard treatment for patients with advanced non-small cell lung cancer (NSCLC). Here, we present the first results of a real-world observational study on the effectiveness of ICI monotherapy in patients with advanced NSCLC treated at a single academic center in a Central and Eastern European (CEE) country. MATERIALS AND METHODS: Overall, 66 consecutive patients with advanced NSCLC treated with ICIs in everyday clinical practice, either with first-line pembrolizumab (26 patients) or second-line atezolizumab, nivolumab, or pembrolizumab (40 patients), from August 2015 to November 2018, were included. All data were retrieved from a hospital lung cancer registry, in which the data is collected prospectively. RESULTS: Included patients had a median age of 64 years, most were male (55%), 6% were in performance status ≥2, and 18% had controlled central nervous system metastases at baseline. In first-line, the median progression-free survival (mPFS) was 9.3 months, while the median overall survival (mOS) was not reached. The 1-year overall survival (OS) was 62%. In second-line, the mPFS and mOS were 3.5 months and 9.9 months, respectively, with a 1-year OS of 35%. In the overall population, adverse events of any grade were recorded in 79% of patients and of severe grade (3-4) in 12% of patients. CONCLUSION: The first real-world outcomes of NSCLC immunotherapy from a CEE country suggest comparable effectiveness to those observed in clinical trials and other real-world series, mainly coming from North America and Western European countries. Further data to inform on the real-world effectiveness of immunotherapy worldwide are needed. IMPLICATIONS FOR PRACTICE: Immunotherapy is a standard treatment of advanced non-small cell lung cancer (NSCLC). The real-world data on immunotherapy are still limited. This article presents the first data on the effectiveness of mono-immunotherapy with immune checkpoint inhibitors for patients with advanced NSCLC treated at a single academic center in a Central and Eastern European country. The survival rates and toxicity are comparable to those achieved in randomized clinical trials and other real-world series, coming mainly from North American and Western European countries. There is a pressing need to gather further data on the effectiveness of immunotherapy in everyday practice worldwide.

Efficient separation of strontium radionuclides from high-salinity wastewater by zeolite 4A synthesized from Bayer process liquids.

The efficient, selective, and economical sorbents for the removal of Sr radionuclides are largely needed for the decontamination of effluents with high salinity. In this study, the removal of Sr was investigated using the zeolite produced from the Bayer process liquids. Based on the XRD, SEM/EDS analysis, the product was pure and highly crystalline zeolite 4A (Z4A). Removal of Sr was fast (5 min for 100% removal at 8.80 mg/L), with high maximum sorption capacity (252.5 mg/L), and independent on the initial pH in the range 3.5-9.0. Specific sorption of Sr by protonated groups on the Z4A surface was operating in addition to ion-exchange with Na ions. The selectivity of Z4A decreased in the order Sr > Ca > K > Mg > Na. 84% of Sr was separated from seawater within 5 min, at the Z4A dose of 5 g/L, while efficiency increased to 99% using the dose of 20 g/L. Desorption of radioisotope 89Sr from seawater/Z4A solid residue was very low in deionized water (0.1-0.2%) and groundwater (0.7%) during 60 days of leaching. Z4A is a cost-effective, selective, and high-capacity medium for Sr removal, which provides high stability of retained radionuclides.

ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients.

The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 min of post-shock waveform. Patients' ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation.

Predicting defibrillation success in out-of-hospital cardiac arrested patients: Moving beyond feature design.

OBJECTIVE: Optimizing timing of defibrillation by evaluating the likelihood of a successful outcome could significantly enhance resuscitation. Previous studies employed conventional machine learning approaches and hand-crafted features to address this issue, but none have achieved superior performance to be widely accepted. This study proposes a novel approach in which predictive features are automatically learned. METHODS: A raw 4s VF episode immediately prior to first defibrillation shock was feed to a 3-stage CNN feature extractor. Each stage was composed of 4 components: convolution, rectified linear unit activation, dropout and max-pooling. At the end of feature extractor, the feature map was flattened and connected to a fully connected multi-layer perceptron for classification. For model evaluation, a 10 fold cross-validation was employed. To balance classes, SMOTE oversampling method has been applied to minority class. RESULTS: The obtained results show that the proposed model is highly accurate in predicting defibrillation outcome (Acc = 93.6 %). Since recommendations on classifiers suggest at least 50 % specificity and 95 % sensitivity as safe and useful predictors for defibrillation decision, the reported sensitivity of 98.8 % and specificity of 88.2 %, with the analysis speed of 3 ms/input signal, indicate that the proposed model possesses a good prospective to be implemented in automated external defibrillators. CONCLUSIONS: The learned features demonstrate superiority over hand-crafted ones when performed on the same dataset. This approach benefits from being fully automatic by fusing feature extraction, selection and classification into a single learning model. It provides a superior strategy that can be used as a tool to guide treatment of OHCA patients in bringing optimal decision of precedence treatment. Furthermore, for encouraging replicability, the dataset has been made publicly available to the research community.

Properties of different types of dry electrodes for wearable smart monitoring devices.

Wearable smart monitors (WSMs) applied for the estimation of electrophysiological signals are of utmost interest for a non-stressed life. WSM which records heart muscle activities could signalize timely a life-threatening event. The heart muscle activities are typically recorded across the heart at the surface of the body; hence, a WSM monitor requires high-quality surface electrodes. The electrodes used in the clinical settings [i.e. silver/silver chloride (Ag/AgCl) with the gel] are not practical for the daily out of clinic usage. A practical WSM requires the application of a dry electrode with stable and reproducible electrical characteristics. We compared the characteristics of six types of dry electrodes and one gelled electrode during short-term recordings sessions (≈30 s) in real-life conditions: Orbital, monolithic polymer plated with Ag/AgCl, and five rectangular shaped 10 × 6 × 2 mm electrodes (Orbital, Ag electrode, Ag/AgCl electrode, gold electrode and stainless-steel AISI304). The results of a well-controlled analysis which considered motion artifacts, line noise and junction potentials suggest that among the dry electrodes Ag/AgCl performs the best. The Ag/AgCl electrode is in average three times better compared with the stainless-steel electrode often used in WSMs.

Cadmium retention and distribution in contaminated soil: effects and interactions of soil properties, contamination level, aging time and in situ immobilization agents.

As soil cadmium (Cd) contamination becomes a serious concern and one of the significant environmental pollution issues all over the world, knowledge of the basic chemistry, origin, inputs, sources, quantity, chemical forms, reactions, as well as the fate and transport of Cd in different types of soil is crucial for better understanding Cd bioavailability, health risks and remedial options. This study aimed to increase the current knowledge on the complex interdependence between the factors affecting behavior, transport and fate of Cd in the soil and to test and compare the performance of the stabilization agents in different soil types. Soils demonstrated various sorption affinity and capacity for Cd accumulation, which proved to be positively correlated with soil pH and the cation exchange capacity (CEC). With increasing levels of contamination, sequential extraction analysis showed the highest increase of relative Cd amounts in the exchangeable fraction regardless of the soil properties, suggesting that added Cd is principally associated with the easily accessible and mobile fraction. For different initial Cd concentrations and soil types, Cd sorption reached the quasi-equilibrium within 24 h of contact. Prolonged aging (two months) influenced the natural stabilization of Cd in all types of soil, but only at low contamination level. The application of both, conventional (slaked lime Ca(OH)2) and alternative phosphate-rich (annealed bovine bones B400) amendments, resulted in Cd relocation and reduction of exchangeable Cd content. Although the effect was smaller when apatite amendment was utilized, observed re-distribution of Cd to more stable soil fractions is preferable for achieving long-term stabilization. Cd concentrations extracted in exchangeable and acid soluble fractions after the treatments of contaminated soil samples suggest that the practical applicability of in situ immobilization depends on the soil properties and the level of contamination, as well as that effect, should be monitored for the possible re-mobilization of Cd.

Deep Learning Approach for Highly Specific Atrial Fibrillation and Flutter Detection based on RR Intervals.

Atrial fibrillation (AF) and atrial flutter (AFL) represent atrial arrhythmias closely related to increasing risk for embolic stroke, and therefore being in the focus of cardiologists. While the reported methods for AF detection exhibit high performances, little attention has been given to distinguishing these two arrhythmias. In this study, we propose a deep neural network architecture, which combines convolutional and recurrent neural networks, for extracting features from sequence of RR intervals. The learned features were used to classify a long term ECG signals as AF, AFL or sinus rhythm (SR). A 10-fold cross-validation strategy was used for choosing an architecture design and tuning model hyperparameters. Accuracy of 88.28 %, with the sensitivities of 93.83%, 83.60% and 83.83% for SR, AF and AFL, respectively, was achieved. After choosing optimal network structure, the model was trained on the entire training set and finally evaluated on the blindfold test set which resulted in 89.67% accuracy, and 97.20%, 94.20%, and 77.78% sensitivity for SR, AF and AFL, respectively. Promising performances of the proposed model encourage continuing development of highly specific AF and AFL detection procedure based on deep learning. Distinction between these two arrhythmias can make therapy more efficient and decrease the recovery time to normal heart rhythm.