Elimination Of Interference Research Articles

High-Resolution Elemental Mass Spectrometry Using LC-ICP-Nanospray-Orbitrap for Simultaneous and Species-Independent Quantitation of Fluorinated and Chlorinated Compounds.

Simultaneous elemental detection of F and Cl offers quantitation of fluorinated and chlorinated compounds and their transformation products without compound-specific standards. Despite wide-ranging applications, this capability has been hindered by fundamental and technical shortcomings of current inductively coupled plasma (ICP)-MS methods in ion formation and isobaric interference elimination. These hurdles are alleviated here via a chemical ionization method. Fluorine and chlorine in analytes are first converted to HF and HCl by an ICP with post-plasma recombination and subsequently react with barium-containing ions supplied by a nanospray, yielding BaF+ and BaCl+ as elemental reporter ions. Notably, the method is readily interfaced to an Orbitrap MS which eliminates isobaric interferences at resolving powers as low as 35,000, far greater than that of current ICP-MS instruments. Moreover, the instrument is easily reverted to the ESI-MS mode for complementary molecular characterization. To demonstrate analytical capabilities, a workflow for rapid quantitation of compounds separated by reversed-phase liquid chromatography is developed using a species-independent calibration. The independent F and Cl measurements agree with each other, providing recoveries of >90% and LODs of 8-12 pmol Cl and 5-12 pmol F on the column. The workflow along with LC-ESI-MS on the same instrument is then applied to identify and quantify in-vitro drug metabolites, yielding total drug-related material recoveries of >80% and quantitation of minor metabolites summing to 8% of the total drug-related compounds. These results highlight the strengths of simultaneous F and Cl speciation for rapid quantitation with applications in early drug development.

Programmable molecular circuit discriminates multidrug-resistant bacteria.

Recognizing multidrug-resistant (MDR) bacteria with high accuracy and precision from clinical samples has long been a difficulty. For reliable detection of MDR bacteria, we investigated a programmable molecular circuit called the Background-free isothermal circuital kit (BRICK). The BRICK method provides a near-zero background signal by integrating four inherent modules equivalent to the conversion, amplification, separation, and reading modules. Interference elimination is largely owing to a molybdenum disulfide nanosheets-based fluorescence nanoswitch and non-specific suppression mediated by molecular inhibitors. In less than 70 ​min, an accurate distinction of various MDR bacteria was achieved without bacterial lysis. The BRICK technique detected 6.73 ​CFU/mL of methicillin-resistant Staphylococcus aureus in clinical samples in a proof-of-concept trial. By simply reprogramming the sequence panel, such a high signal-to-noise characteristic has been proven in the four other superbugs. The proposed BRICK method can provide a universal platform for infection surveillance and environmental management thanks to its superior programmability.

Outage Performance of Cognitive Radio Networks With a Coverage-Limited RIS for Interference Elimination

In this letter, considering the reconfigurable intelligent surface’ (RIS’) service coverage limitation, we investigate the outage probability (OP) of an RIS-aided cognitive radio network where the RIS is used only to eliminate the interference from the secondary transmitter to the primary receiver. Specifically, a closed-form expression for the OP is derived and the asymptotic OP is obtained at high signal-to-noise ratio (SNR). We also present the asymptotic OP when the number of reflecting elements is large. Simulation results validate our analysis, and show that at low tolerable interference-to-noise ratio (INR), the considered scheme can achieve significant performance gains over the coverage-neglected scheme and the signal enhancement scheme.

Periodic Monitoring and Filtering Suppression of Signal Interference in Mine 5G Communication

Diverse IoT applications, such as unmanned driving, intelligent video, unmanned working face, industrial control, and intelligent robot inspection, are the key technologies in the field of intelligent mines. In order to fully meet the requirements of underground IoT systems of high bandwidth, low latency, and massive connections, it is necessary to study 5G technologies suitable for underground environments to achieve effective deployment in mines. In key areas, such as main transport roadways, fully mechanized mining faces, and underground substations, both spurs and crosstalk in the frequency domain are the dominant factors affecting the stability and reliability of 5G signals. For the purpose of improving the performance of mine 5G, a fusion anti-interference scheme is designed here. Based on a deep complex network and blind source separation, periodic monitoring and filtering suppression of signal interference can be achieved. The test results show that the frequency domain spurs’ suppression capability of the proposed method is 20% higher than that of the traditional equalization method. For frequency domain crosstalk, 90% interference elimination could be achieved by the proposed method without additional delays when compared with the conventional blind source separation. The high-bandwidth and low-latency characteristics of 5G communication can be guaranteed by this method.

Investigation of 33 types of honey samples: application of an efficient dispersive liquid-liquid microextraction technique coupled with gas chromatography-mass spectrometry to determine 16 polycyclic aromatic hydrocarbons

In this research, for the first time, 16 polycyclic aromatic hydrocarbons (PAHs) in 33 types of honey samples have been analyzed using an efficient, sensitive and rapid high-density solvent-microextraction (HDS-ME) technique coupled to gas chromatography-mass spectrometry (GC-MS). Important parameters in the extraction process were optimized using central composite design (CCD). Good linear relationships were chosen for 16 PAHs in the range of 1–200 ng g−1, with a correlation coefficient (R2) higher than 0.94. The limits of detection and limits of quantification were 0.3–0.8 ng g−1 and 0.9–2.4 ng g−1, respectively. The relative standard deviations for six similar analyses at the optimized point were less than 9%. The recoveries of the proposed method were obtained between 86% and 102%. High recovery, low consumption of the solvent, speed, ease of use and good elimination of matrix interference compared to other methods are the advantages of the proposed method. The performance of the present work was confirmed by the standard addition method and satisfactory results were obtained. The concentrations of PAHs in honey samples were found lower than 11 ng g−1.

Асимптотически робастный инвариантный алгоритм демодуляции DPSK-сигналов при воздействии внешних помех с априорно неопределенными параметрами

The study aims at synthesizing an asymptotically robust invariant demodulation algorithm for DPSK signals with arbitrary modulation multiplicity used in aircraft communication systems and observed against the background of noise with an unknown probability distribution and a noise complex with a priori uncertain parameters. The analysis of the efficiency of the proposed algorithm is carried out by a computer simulation modeling. The algorithm implies automatic detection and rejection of narrowband pulse noise. This type of interference is typical for radio-navigation systems. It has been shown that the narrowband pulse noise should be eliminated if the signal-to-interference ratio becomes less than -10 dB. The use of the asymptotic robustness principle ensures the stability of the algorithm characteristics to changes in the character of the noise probability distribution density. It was found that the joint application of narrowband pulse interference elimination and the asymptotically robust approach provides reliable demodulation performance both when receiving against the background Gaussian noise and under the action of pulse interference and noise with "heavy tails". In addition, it has been shown that the use of signals with differential phase modulation, direct sequence spread spectrum, and the sidelobe levels of less than 10% effectively suppresses interference caused by multipath signal propagation.

A Novel Model for Calculating Uplink-Downlink Spectral Efficiency in Cooperative Communication MIMO Systems

Cooperative communication that enables the use of relays between a base station (BS) and end users is an effective technique against fading to improve network performance, especially in increasing spectral efficiency (SE) and network coverage. However, systems that use cooperative communication have weaknesses in the structure, such as resistance to latency and an increase in the bandwidth of substitute users (SU), which can be improved by optimizing the relay selection method effectively. The system due to insufficient spacing between antennas and insufficient scattering in the channel has spatially faded that leads to spatial correlation. We use Kronecker statistical model correlated multiantenna channels to implement detection techniques and eliminate interference in cooperative communication. The validity of the Kronecker model lies in the fact that correlation coefficients of transmission are independent of the receiving antennas. In other words, the spatial correlation model separates both ends of the communication link. Therefore, using the minimum mean-squared-error (MMSE) technique, we have removed the need for optimal elimination of interference between SU and relay service provider or primary user (PU). Regardless of BS performance, the scope of this work is restricted to the layer after the BS in the interaction between the service providers and substitute users. The primary purpose of the presented method is to improve the spectral gain through the elimination of interference. Simulation results show about 10% of SE improvement along with considerable traffic gain.

Over‐the‐air equalization with reconfigurable intelligent surfaces

Reconfigurable intelligent surface (RIS)-empowered communications is on the rise and is a promising technology envisioned to aid in 6G and beyond wireless communication networks. RISs can manipulate impinging waves through their electromagnetic elements enabling some sort of control over the wireless channel. In this paper, the potential of RIS technology is explored to perform a sort of virtual equalization over-the-air for frequency-selective channels whereas, equalization is generally conducted at either the transmitter or receiver in conventional communication systems. Specifically, with the aid of an RIS, the frequency-selective channel from the transmitter to the RIS is transformed to a frequency-flat channel through elimination of inter-symbol interference (ISI) components at the receiver. ISI is eliminated by adjusting the phases of impinging signals particularly to maximize the incoming signal of the strongest tap. First, a general end-to-end system model is provided and a continuous to discrete-time signal model is presented. Subsequently, a probabilistic analysis for the elimination of ISI terms is conducted and reinforced with computer simulations. Furthermore, a theoretical error probability analysis is performed along with computer simulations. It is analyzed and demonstrated that conventional RIS phase alignment methods, can successfully eliminate ISI and the RIS-aided communication channel can be converted from frequency-selective to frequency-flat.

Energy Efficiency Optimization for Rate-Splitting Multiple Access-Based Indoor Visible Light Communication Networks

With the explosive proliferation of connected devices and mobile users in the Internet-of-things, multiple access techniques are urged to be developed for the next generation wireless communications. Recently, rate-splitting multiple access (RSMA) has been a promising communication technology that holds advantages of strong robustness, low complexity, and high spectral efficiency, which can be integrated with the indoor visible light communication (VLC) broadcast system to compensate for the shortcomings of limited modulation bandwidth of LEDs. However, the research on the RSMA-based VLC systems is still in its infancy and there exist various problems to be explored. To benefit from the RSMA technique, this paper investigates the energy efficiency optimizations for both single-cell and multi-cell RSMA-based VLC broadcast systems. Specifically, these two systems are modeled, where the VLC broadcast channel follows Lambertian radiation model, and the splitting design and successive interference cancellation of RSMA are employed to mitigate the multi-user interference. Especially for multi-cell networks, the zero-forcing approach is adopted to eliminate the inter-cell interference. To maximize the energy efficiency, the precoding and power allocation problems are formulated for single-cell and multi-cell networks while accommodating multiple constraints including dynamic operation ranges of LEDs, QoS requirements, and interference elimination. For solving these non-convex fractional problems, two pieces of successive convex approximation (SCA)-based algorithms are proposed, in which the variable transformation and linear approximation are adopted. Simulation results indicate that the proposed schemes can achieve superior energy efficiency with fast convergence for various network loads and user deployments.

Noncoherent Massive Random Access for Inhomogeneous Networks: From Message Passing to Deep Learning

Massive machine-type communications (mMTC) are expected to support a large amount of randomly deployed users for short package transmissions. Noncoherent random access provides an efficient and practical multi-access protocol for mMTC, and also poses new challenges for the receiver design. In this paper, we leverage two well-known methods, i.e., message passing and deep learning, to jointly detect the user activity and the desired data for the noncoherent mMTC. First, by exploiting the exact distribution information of the received signal, a generalized approximate message passing (GAMP)-based algorithm is proposed, which is shown to jointly detect the user activity and the desired data by two modules: inter-user interference elimination and data detection for each user. Inspired by the two-module GAMP-based algorithm, we then propose a model-driven deep learning method, which utilizes the deep neural networks (DNNs) to approximate both the two modules. The loss function for training the DNNs is derived by formulating the two-module detection as an unconstrained optimization problem. Simulation results reveal that the proposed GAMP-based algorithm outperforms the proposed deep learning method when the channel distribution is perfectly known, while it suffers from a significant performance degradation for the case with imperfect channel distribution information.

Adapted technique for demonstrating argyrophilic nucleolar organizer regions in the cytologic samples of canine mast cell tumors.

Argyrophilic nucleolar organizer regions (AgNORs) are nonhistone argyrophilic nucleolar proteins associated with ribosomal genes found in the nucleolar organizer region that reflect cell proliferation and have an affinity for silver. AgNOR staining may be useful to evaluate prognosis in several neoplasms because higher AgNOR counts are related to higher grade tumors, metastases, and shorter survival times. We aimed to report on a quick and practical technique to identify AgNORs adapted for use in routine cytology. The cytopathologic diagnosis of mast cell tumor (MCT) in samples collected by fine-needle aspiration (FNA) was determined. Next, slides were impregnated with a solution containing silver nitrate; the main modification of our technique included incubation of these slides at a controlled temperature of 25 °C. Some slides were previously stained with Diff-Quik and others were only fixed with methanol. The slides were analyzed under a microscope, and the number of blackened intranuclear points (AgNORs) was counted. Slides prestained with Diff-Quik were easily counted compared with slides only fixed in methanol. Technical issues encountered with the methanol-fixed slides included insufficient cellularity, background precipitation, and an absence of silver impregnation. The technique reported in this study showed satisfactory results for AgNOR counting in cytologic smears from MCT, such as good impregnation and the elimination of background interferents. Further evaluation of this method comparing AgNOR counts with histologic examinations, tumor grades, other prognostic markers, and survival times are needed to fully evaluate the benefit of this technique.

Tracking the location of bearing outer raceway defects using multidimensional synchronous signal fusion and tensor Rank-1 decomposition

A generalised Warblet tensor rank-1 decomposition (GWTTR1) method is developed in this study to realise location diagnosis for bearing outer raceway defects in low signal-to-noise ratio (SNR) scenarios. Firstly, a novel third-order tensor model (channel–time–frequency) with comprehensive information is established to reveal key information hidden in multidimensional signals and realise feature fusion among two-channel signals. Secondly, the defect characteristic frequency and correlation coefficient between rank-1 tensors are introduced as optimal selection indices for the factor matrix to decompose the tensor model effectively and overcome the inherent shortcomings of decomposition. Thirdly, a novel location diagnosis dimensionless index, namely, the horizontal-vertical synchronisation factor (HVSF), is proposed for the optimised tensor model. Finally, the performance of the proposed GWTTR1 method and novel HVSF index in location diagnosis for bearing outer raceway defects and noise interference elimination is evaluated comprehensively with low SNR dynamic simulation and experimental signals. The comparison results reveal that the GWTTR1 method outperforms existing noise reduction techniques.

Elimination of oxygen interference in the photoelectrochemical sensor with ferricyanide shield oxygen reduction for point of care testing

As a sensitive and promising detection method, photoelectrochemical (PEC) sensor has been widely used in biochemical analysis field. However, the interferences from environment, especially dissolved oxygen, often impact the stability and precision of PEC sensors, which limit its practical applications. Here, we report a dissolved oxygen insensitive PEC sensor based on a proposed indirect electron transfer model. Through the detailed study of the charge transfer process, we determined that the photocurrent mainly comes from the electrochemical reaction between the photochemical products and the electrode, rather than direct charge transfer between the photoelectric materials and the electrode. The newly designed PEC sensor used ferricyanide to shield oxygen reduction and eliminated the influence from variable oxygen solubility. This sensor maintained robust responses over an extremely wide range (1.0–7.5 mg/L) of dissolved oxygen concentrations. To further demonstrate its capability, a smartphone based portable immunosensor was constructed for the detection of human serum albumin (HSA), which exhibited excellent stability and accuracy. The relative error of current was reduced by 81.3% over traditional electron donor solution. This work effectively improves the stability of PEC sensors, and lays the foundation for the subsequently practical applications of PEC sensor in point-of-care testing.

Rare Earth Elements Determination by Inductively Coupled Plasma Mass Spectrometry after Alkaline Fusion Preparation

There is an increasing worldwide demand for rare earth elements (REEs) in new technological applications—such as electronics, superconductors, space applications, etc. The determination of low concentration REEs in geological samples is extremely important since they are the source materials for all REE products. In order to improve the accuracy and precision of REE measurements by inductively coupled plasma mass spectrometry (ICP-MS); complete digestion of refractory phases and minerals in the samples, low procedural blanks, separation of interfering matrix, and elimination of interference on the mass of the analytes of interest must be fulfilled. Conventional methods that use a hotplate and a mixture of four acids are effective but can take time to achieve complete dissolution of samples that contain highly refractory phases, which is unacceptable in the mining and metallurgical industry. Such difficult samples necessitate high-temperature alkaline flux fusion as it offers a faster and more efficient alternative to acid digestion. This paper presents an accurate, precise, rapid, and reliable method for rare earth element analysis by ICP-MS with low detection limits, which involves no sample pre-concentration, and is therefore able to deliver data rapidly. The analytical performance of the developed method was tested successfully on various REE rock-type certified reference materials and evaluated statistically. The results obtained were in reasonable agreement with published certificate values.

Maintaining the Status Quo: Simultaneous Estimation and Elimination for Multiple Interference in Transform Domain Vehicular Communication

Wireless communication in vehicular networks is highly vulnerable to electromagnetic interference, which seriously undermines the communication effectiveness. Thus, interference estimation and elimination are essential in vehicular communications. To solve the multitasking problem of interference estimation and cancelation within the transformation domain of vehicular communications where they are divided into the consistency and inconsistency based on the different conditions of spectrum sensing, the present study proposes an iterative Bayesian sparse learning approach for simultaneous interference recovery and elimination which applies multiple Bayesian learning for measured signals, and the structured sparse learning method for simultaneous interference mitigation with signal recovery. Furthermore, the updating optimization based on Bayesian estimation framework is performed to facilitate the learning process and improve the performance of interference estimation and signal reconstruction. Simulation results show that the proposed algorithms achieved more rapid convergence and more accurate recovery (31.84% and 27.88% higher in spectrum sensing with consistency and inconsistency, respectively) than conventional algorithms. During all iterations, the proposed algorithms, because of updating optimization, were more robust than conventional ones, but the computational complexity remained largely the same. To explore the correlation between the parameters and the interference recovery performance, we performed experiments, which revealed linear, logarithmic, and exponential regression correlations for particular forms of interference. We also compared the demodulation performance of the proposed algorithm with existing methods, and it turned out the proposed algorithm also obtained higher gains on average in the bit error rate.

Elimination of Roll Interference by Increasing Radius of Variable Section Forming Roll

Elimination of Roll Interference by Increasing Radius of Variable Section Forming Roll

Arsenic speciation analysis in porewater by a novel colorimetric assay

Arsenic is common toxic contaminant, but tracking its mobility through submerged soils is difficult because microscale processes dictate its speciation and affinity to minerals. Analyses on environmental dissolved arsenic (As) species such as arsenate and arsenite currently require highly specialized equipment and large sample volumes. In an effort to unravel arsenic dynamics in sedimentary porewater, a novel, highly sensitive, and field-usable colorimetric assay requiring 100 μL of sample was developed. Two complementary protocols are presented, suitable for sub-micromolar and micromolar ranges. Phosphate is a main interfering substance, but can be separated by measuring phosphate and arsenate under two different acidities. Arsenite is assessed by oxidation of arsenite to arsenate in the low-acidity reagent. Optimization of the protocol and spectral analyses resulted in elimination of various interferences (silicate, iron, sulfide, sulfate), and the assay is applicable across a wide range of salinities and porewater compositions. The new assay was used to study As mobilization processes through the soil of a contaminated brook. Water column sources of arsenic were limited to a modest input by a groundwater source along the flow path. In one of the sites, the arsenite and arsenate porewater profiles showed active iron-driven As redox cycling in the soil, which may play a role in arsenic mobilization and releases arsenite and arsenate into the brook water column. Low arsenic concentrations downstream from the source sites indicated arsenic retention by soil and dilution with additional sources of water. Arsenic is thus retained by the Bossegraben before it merges with larger rivers.

Development of isotope dilution-liquid chromatography/tandem mass spectrometry for the accurate determination of zearalenone and its metabolites in corn

A method using isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC/MS/MS) was developed for the accurate determination of zearalenone (ZEN) and its five major metabolites in corn. 13C- or 2H-labeled analogues of the target mycotoxins were used as internal standards. As the immunoaffinity columns used demonstrated selectivity to a specific chiral isomer of a racemic mixture of zearalanone-d6, a clean-up cartridge without stereoselectivity (Mycosep 226 column) was selected for the same recovery of the analyte and its internal standard with adequate elimination of matrix interferences. The method demonstrated sufficient selectivity, sensitivity, accuracy and precision over a concentration range of 20–400 µg/kg. The limit of detections and limit of quantifications were 0.14–0.33 µg/kg and 0.45–1.11 µg/kg, respectively. The accuracy values were 96.7%−103.6%, with intra and inter-day precisions of less than 3% and 4%, respectively. The expanded measurement uncertainty was less than 7% (with a 95% confidence level).

Risk factors for temporomandibular disorders in young people

Aim to investigate the prevalence and risk factors for signs and symptoms of temporomandibular joint disorders (TMDs) in young people.
 Material and methods. A clinical examination and questionnaire were randomly administered to 199 students aged 17 to 28 years using a specially designed questionnaire chart. The respondents with identified laterotrusive or mediatrusive occlusal interferences underwent electromyography (4-channel EMG system "Synapsis", Neurotech) of masticatory muscles before and after elimination of occlusal interferences. Psychoemotional state was assessed using the Spielberger Hanin situational and personal anxiety test.
 Results. The results obtained revealed a high prevalence of signs and symptoms of dysfunctional disorders (87.9%), the leading signs of which were pain or stiffness in the head and neck region (52.7%), sounds (squeaks, clicks, crepitus) in one or both temporomandibular joints when chewing and opening the mouth (39.2%), feeling of pressure, stuffiness or noise in the ears (25.1%), pain when opening the mouth (21.6%). The number of such signs and symptoms was greater in persons with postural disorders and respondents after orthodontic treatment.
 Electromyographic study of patients with mediotrusive and laterotrusive contacts showed asynchronous contraction of the masticatory muscles during "protrusion / retrusion" and "opening / closing", increased electrical activity of the temporal muscle on the opposite side in the "right / left mediotrusion" test (111.5 27.1 V) compared with the indices of the subjects after the elimination of occlusal interferences (75 19.3 V; p 0.05). Assessment of the psychoemotional state of the examined patients revealed a moderate level of situational (38.9 points) and personal (38.3 points) anxiety.
 Conclusion. The signs and symptoms of TMDs are a common finding among young people, such as pain, stiffness in the head and neck, sounds in one or both joints when chewing and opening the mouth, a feeling of pressure, stuffiness or noise in the ears. The most significant risk factors for the development of TMDs in this age group are posture disorders, orthodontic treatment and occlusal obstructions, which affect muscle tone and increase the symptoms of TMDs.

Direct Oral Anticoagulant removal by a DOAC filter: Impact on lupus anticoagulant testing – Evaluation on spiked and patient samples

BackgroundDOAC Filter (DF) is a new device to overcome interference in lupus anticoagulant (LAC) testing by direct oral anticoagulants (DOACs). ObjectivesWe evaluated DOAC removal from plasma and elimination of DOAC interference in LAC testing by DF, and impact of DF on LAC assays in a representative patient cohort, including a comparison with DOAC‐Stop (DS). MethodsNormal pooled plasma (NPP) was spiked with increasing concentrations of apixaban, rivaroxaban, edoxaban, and dabigatran. DOAC and LAC was measured on untreated, DF‐treated, and DS‐treated spiked samples. Coagulation parameters and thrombin generation were measured on patient samples (n = 20) before and after DF. Patients treated with DOAC, vitamin K antagonist, or heparin and nonanticoagulated patient samples (n = 139) were tested for LAC before and after DF. ResultsIn spiked NPP, levels were below the lower limit of quantification (LLoQ) after DF/DS treatment for all DOAC concentrations. Following DF, levels were below LLoQ for 53 of 56 DOAC‐containing patient samples. Twenty‐eight of 33 LAC‐positive DOAC‐containing samples became negative after filtration, whereas 5 remained LAC‐positive (1/5 from a patient with antiphospholipid syndrome [APS]). Four LAC‐positive DOAC‐containing samples (from patients without APS), became negative after filtration, whereas they remained LAC positive after DS. In the non‐DOAC patient groups following DF, LAC changed from positive to negative in 8 (due to a procoagulant effect) and vice versa in 2 cases. ConclusionDF reduces DOAC interference in LAC testing. As incomplete DOAC removal may occur, DOAC measurements should be performed after filtration. A procoagulant effect after filtration may lead to erroneous LAC results in non–DOAC‐containing samples. Therefore, using DF should be restricted to DOAC‐containing samples.