Elimination Of Interference Research Articles

Combination Networks With End-User-Caches: Novel Achievable and Converse Bounds Under Uncoded Cache Placement

Caching is an efficient way to reduce network traffic congestion during peak hours by storing some content at the users’ local caches. For the shared-link network with end-user-caches, Maddah-Ali and Niesen proposed a two-phase coded caching strategy. In practice, users may communicate with the server through intermediate relays. This paper studies the tradeoff between the memory size M and the network load R for the networks where a server with N files is connected to H relays (without caches), which in turn are connected to K users equipped with caches of M files. When each user is connected to a different subset of r relays, i.e., K = (Hr), the system is referred to as a combination network with end-user-caches. In this work, converse bounds are derived for the practically motivated case of uncoded cache contents, that is, bits of the various files are directly pushed into the user caches without any coding. In this case, once the cache contents and the users’ demands are known, the problem reduces to a general index coding problem. This paper shows that relying on a well-known “acyclic index coding converse bound” results in converse bounds that are not tight for combination networks with end-user-caches. A novel converse bound that leverages the network topology is proposed, which is the tightest converse bound known to date. As a result of independent interest, an inequality that generalizes the well-known sub-modularity of entropy is derived. Several novel caching schemes are proposed, based on the Maddah-Ali and Niesen cache placement. These schemes leverage the structure of the combination network or/and perform interference elimination at the end-users. The proposed schemes are proved: (i) to be (order) optimal for some (N, M, H, r) parameters regimes under the constraint of uncoded cache placement, and (ii) to outperform the state-of-the-art schemes in numerical evaluations.

Subspace Detection for Range-Spread Target to Suppress Interference: Exploiting Persymmetry in Non-Homogeneous Scenario

This paper deals with subspace detection for range-spread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data. Through exploiting the persymmetry of the clutter covariance matrix, we propose two adaptive target detectors, which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference (“PS-Rao-I” and “PS-Wald-I”), respectively. The persymmetry-based design brings in the advantage of easy implementation for small training sample support. The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection, while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection. In addition, both detectors are shown to be constant false alarm rate detectors, significantly improving the detection performance with other competing detectors under the condition of limited training.

Can housing price regulation improve R&D performance in universities? Evidence from China

The house property tax pilot policy (HPTPP) introduced in 2011 has resulted in the redistribution of R&D resources. However, few studies have focused on the impacts of this policy. In this paper, we use the heterogeneous stochastic frontier analysis method to measure the R&D total factor productivity (TFP) growth rate of Chinese universities. Then, the difference-in-differences (DID) method is employed to examine the impact of the HPTPP on R&D performance. Furthermore, a series of robustness tests are conducted on the estimated results, including: a parallel trend test, by advancing the introduced time of policy; a reduction of the self-selection bias, by adopting the propensity score matching (PSM); and an interference elimination of the house-purchasing restriction policy. Finally, based on the extensive margin and the intensive margin, we investigate the mechanisms of the HPTPP on R&D performance. The results show that the R&D TFP of Chinese universities displays a downward trend. After reducing self-selection bias, the HPTPP exerts no significant effect on R&D TFP growth rate of Shanghai's universities, but the HPTPP does reduce the R&D TFP growth rate of universities located in Chongqing. This conclusion remains robust after changing the matching ratio of the PSM strategy and eliminating the interference of the house-purchasing restriction policy. For Shanghai's universities, the effects of the HPTPP on extensive margin (i.e., factor input scale) and intensive margin (quantity of efficient factors) are not clear, resulting in an uncertain impact on R&D TFP growth rate. However, for Chongqing, the negative effect on the scale of factor input leads to a decline in R&D TFP growth rate of universities. Therefore, when restraining housing prices, the government should prevent the negative effect on R&D investment and attract high-end talent through preferential conditions.

Distributed Coordinated Precoding for MIMO Cellular Network Virtualization

This paper presents a new virtualization method for the downlink of a multi-cell multiple-input multiple-output (MIMO) network, to achieve service isolation among multiple Service Providers (SPs) that share the base station resources of an Infrastructure Provider (InP). Each SP designs a virtual precoder for its users in each cell, as its service demand to the InP, without the need to be aware of the existence of the other SPs or to know the channel state information (CSI) outside the cell. The InP performs network virtualization to meet the SPs’ service demands while managing both the inter-SP and inter-cell interference. We consider coordinated multi-cell precoding at the InP and formulate an optimization problem to minimize a weighted sum of signal leakage and precoding deviation, with per-cell transmit power constraints. We propose a fully distributed semi-closed-form solution at each cell, without any CSI exchange across cells. We further propose a low-complexity scheme to allocate the virtual transmit power, for the InP to regulate between interference elimination and virtual demand maximization. Simulation results demonstrate that our precoding solution for network virtualization substantially outperforms the traditional spectrum isolation alternative. It can approach the performance of fully cooperative precoding when the number of antennas is large.

Elimination of Spectral Interference of 87Rb (an Isobar of 87Sr) with 87Sr in ICP–MS Measurement Using Chromatographic Technique

Elimination of Spectral Interference of 87Rb (an Isobar of 87Sr) with 87Sr in ICP–MS Measurement Using Chromatographic Technique

Eliminating Mo isobaric interference using O2 as reaction gas for Tc measurement by triple quadrupole ICP-MS

The introduction of O2 for the elimination of Mo interference for Tc measurement by ICP-MS/MS.

Hormone Immunoassay Interference: A 2021 Update.

Immunoassays are powerful qualitative and quantitative analytical techniques. Since the first description of an immunoassay method in 1959, advances have been made in assay designs and analytical characteristics, opening the door for their widespread implementation in clinical laboratories. Clinical endocrinology is closely linked to laboratory medicine because hormone quantification is important for the diagnosis, treatment, and prognosis of endocrine disorders. Several interferences in immunoassays have been identified through the years; although some are no longer encountered in daily practice, cross-reaction, heterophile antibodies, biotin, and anti-analyte antibodies still cause problems. Newer interferences are also emerging with the development of new therapies. The interfering substance may be exogenous (e.g., a drug or substance absorbed by the patient) or endogenous (e.g., antibodies produced by the patient), and the bias caused by interference can be positive or negative. The consequences of interference can be deleterious when clinicians consider erroneous results to establish a diagnosis, leading to unnecessary explorations or inappropriate treatments. Clinical laboratories and manufacturers continue to investigate methods for the detection, elimination, and prevention of interferences. However, no system is completely devoid of such incidents. In this review, we focus on the analytical interferences encountered in daily practice and possible solutions for their detection or elimination.

A rapid elimination of communication signal interference in complex electromagnetic environment

A rapid elimination of communication signal interference in complex electromagnetic environment

Tensor Dictionary Manifold Learning for Channel Estimation and Interference Elimination of Multi-User Millimeter-Wave Massive MIMO Systems

Millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) systems with hybrid analog-digital architectures can greatly increase system capacity and communicate with multiple users at the same time. Accurate channel estimation is crucial for multi-user communications, but its accuracy is limited as the number of antennas and users increases. In the matrix high-dimensional operation for multi-user channel estimation, not only is it computationally intensive, but also the estimation accuracy is low. It makes our work turn to channel estimation of the user group within a certain region to improve the accuracy of estimation. In this paper, we propose a tensor dictionary manifold learning method for channel estimation and interference elimination of the multi-user mmWave massive MIMO system. A multi-user digital-analog mixed received signal model is presented. The tensor dictionary manifold learning scheme is proposed to model the received signal as a third-order low-rank tensor to handle the high-dimensional user, antenna, and channel. After segmentation, clustering and manifold learning, multiple tensor dictionary manifold models containing a group of user signals are fitted. Tensor dictionary manifold learning can take advantage of the inherent multi-domain properties of signals in the frequency, time, code and spatial domains to maintain inter-user correlation within a user group while reducing the high-dimensional channels of the user group. Using the convex relaxation property of the tensor alternating direction method, we propose a strategy to eliminate interference from other groups. And with the help of the multi-signal classification method, the channel parameters of user groups are obtained to improve the accuracy of multi-user channel estimation. This method can perform channel estimation for multiple users with only a few pilots, and improve the performance of the system. Numerical results confirm the good performance of this method.

A new algorithm for location parameter estimation in DTV ground broadcast network

In the city, terrestrial digital TV network is the most perfect TV network, so the location of terrestrial broadcast signal based on digital TV has become one of the research hots-pots in recent years. Because multi-path in DTV wireless channel will cause serious signal fading, it becomes more difficult to detect DTV signal in the process of positioning, which directly affects the accuracy of positioning. Therefore, how to improve the detection accuracy of DTV signal through parameter estimation has become the focus of this paper. Based on the detailed study of DTV system based on wireless transmission channel characteristics and system structure, through the analysis based on linear least square (LS) channel estimation algorithm, the advantages and disadvantages of interference elimination is given based on the data, a new method of channel estimation, the simulation results verify the algorithm presented in this paper can well improve the channel estimation performance.

PathTracer: Understanding Response Time of Signal Processing Applications on Heterogeneous MPSoCs

In embedded and cyber-physical systems, the design of a desired functionality under constraints increasingly requires parallel execution of a set of tasks on a heterogeneous architecture. The nature of such parallel systems complicates the process of understanding and predicting performance in terms of response time. Indeed, response time depends on many factors related to both the functionality and the target architecture. State-of-the-art strategies derive response time by examining the operations required by each task for both processing and accessing shared resources. This procedure is often followed by the addition or elimination of potential interference due to task concurrency. However, such approaches require an advanced knowledge of the software and hardware details, rarely available in practice. This work presents an alternative “top-down” strategy, called PathTracer, aimed at understanding software response time and extending the cases in which it can be analyzed and estimated. PathTracer leverages on dataflow-based application representation and response time estimation of signal processing applications mapped on heterogeneous Multiprocessor Systems-on-a-Chip (MPSoCs). Experimental results demonstrate that PathTracer provides (i) information on the nature of the application (work-dominated, span-dominated, or balanced parallel), and (ii) response time modeling which can reach high accuracy when performed post-execution, leading to prediction errors with average and standard deviation under 5% and 3% respectively.

Visualization of Acute Inflammation through a Macrophage-Camouflaged Afterglow Nanocomplex.

Acute inflammation is a basic innate, immediate, and stereotyped immune response to injury, which is characterized by rapid recruitment of immune cells to the vasculature and extravasation into the damaged parenchyma. Visualization of acute inflammation plays an important role in monitoring the disease course and understanding pathogenesis, which lacks specific targeted and observing tools in vivo. Here, we report a Trojan horse strategy of a macrophage-camouflaged afterglow nanocomplex (UCANPs@RAW) to specifically visualize acute inflammation. Due to the advantages of optical antibackground interference elimination, as well as particular immune homing and long-term tracking capacity, UCANPs@RAW demonstrates an excellent acute inflammatory recognition ability. In an arthritis model, previously intravenously injected UCANPs@RAW could directionally migrate from the liver to the inflammation site as soon as 3 h after the model was induced, which could be continuously lighted for at least 36 h with the highest imaging signal-to-background ratio (SBR) as 382 at the time point of 9 h. Additionally, UCANPs@RAW is observed to penetrate the blood-brain barrier and image the deep brain inflamed region covered by the thick skull in an acute brain inflammation model with an SBRmax of 258, which is based on the strong recruiting ability of macrophages to immune response. In view of this smart nanocomplex, our strategy holds great potential for inflammatory detection and treatments.

Deep Learning-Based RIS Channel Extrapolation With Element-Grouping

Reconfigurable intelligent surface (RIS) is considered as a revolutionary technology for future wireless communication networks. In this letter, we consider the acquisition of the cascaded channels, which is a challenging task due to the massive number of passive RIS elements. To reduce the pilot overhead, we adopt the element-grouping strategy, where each element in one group shares the same reflection coefficient and is assumed to have the same channel condition. We analyze the channel interference caused by the element-grouping strategy and further design two deep learning based networks. The first one aims to refine the partial channels by eliminating the interference, while the second one tries to extrapolate the full channels from the refined partial channels. We cascade the two networks and jointly train them. Simulation results show that the proposed scheme provides significant gain compared to the conventional element-grouping method without interference elimination.

Broadband Spectral Analysis Algorithm with High-Frequency Resolution for Elimination of Overlap Interference between Adjacent Channels

Spectral lines can be analysed to determine the physical properties of molecular clouds and the astrochemical processes in the formation area of massive stars. To improve the observation technology of radio astronomy, this paper proposes and compares two spectral analysis algorithms (improved weighted overlap-add (IWOLA) + FFT and IWOLA + weighted overlap-add (WOLA)). The proposed algorithms can obtain an ultra-high-frequency resolution for real-valued wideband signals, eliminate the signal overlapping interference between adjacent channels, substantially decrease the required hardware resources, especially multipliers, adders, and memory resources, and reduce the system design complexity. The IWOLA + FFT algorithm consists of an improved weighted overlap-add (IWOLA) filter bank, fast Fourier transform (FFT), a specific decimation for the output data from the IWOLA filter bank, and a selection for part of the output data from the FFT. The IWOLA + WOLA algorithm consists of the same modules as the IWOLA + FFT algorithm, with the second-stage FFT replaced by the modules of the weighted overlap-add (WOLA) filter bank and the accumulation for each sub-band. Based on an analysis of the underlying principles and characteristics of both algorithms, the IWOLA + FFT algorithm demonstrated a spectrum with a high frequency resolution and a comparable performance to an ultra-large-scale FFT, based on two smaller FFTs and a flexible architecture instead of a ultra-large-scale FFT. The IWOLA + WOLA algorithm contains the same function as the IWOLA + FFT algorithm and demonstrates a higher performance. The proposed algorithms eliminated the interference between the adjacent channels within the entire Nyquist frequency bandwidth. The simulation results verify the accuracy and spectral analysis performances of the proposed algorithms.

Two New Kinds of Interference Alignment Schemes for Cellular $K$-User MIMO Downlink Networks

It is known that interference alignment (IA) plays an important role in improving the degree of freedom (DoF) of multi-input and multi-output (MIMO) systems. However, most of the traditional IA schemes suffer from the high computational complexity and require the global and instantaneous channel state information (CSI), both of which make them difficult to be extended to cellular MIMO systems. To handle these issues, two new IA schemes, i.e., the retrospective interference regeneration (RIR) scheme and the beamforming based distributed retrospective interference alignment (B-DRIA) scheme, are proposed for cellular <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> -user MIMO downlink networks. For the RIR scheme, it adopts interference elimination algorithm to erase redundant symbols in inter-cell interference (ICI) signals, and then uses interference regeneration algorithm to avoid secondary interference. The RIR scheme obtains greater DoF gain than the retrospective interference alignment (RIA) scheme, but incurs performance degradation when the transceiver antennas ratio (TAR) approaches 1. Therefore, the B-DRIA scheme is further proposed. For the B-DRIA scheme, the cellular beamforming matrix is introduced to eliminate the ICI, and meanwhile distributed RIA algorithm is adopted to align inter-user interference (IUI). The simulation results show that the B-DRIA scheme obtains larger DoF than the RIR scheme locally. Specifically, when TAR approaches 1, two schemes obtain the same DoF. While TAR approaches 2, the DoF of the B-DRIA scheme is superior than the RIR scheme.

Microelectrocehmical Sensors for Water Quality Monitoring

The aim of this work is to micro-fabricate lead sensors that they will be low powered, cheap to make and easily mass-produced for distribution as hand-held portable devices1 or as long-term deployable devices. Lead is a toxic heavy metal that is linked to several adverse health effects. A report by the WHO identified lead as being responsible for 143,000 deaths annually. As of 2013, the WHO reduced the maximum allowable level of lead in drinking water from 50 ppb to 10 ppb. Microelectrodes fabricated by lithographic techniques on silicon are of great interest as they typically have a higher sensitivity than macroelectrodes of conventional size. This work will specifically focus on interdigitated microelectrodes. Interdigitated electrodes (IDEs) consist of two interlocking combs of electrodes and are typically used as generator-collector electrodes. Generator-collector (GC) electrodes are electrodes in which one side of the array is the generator and the other side of the array is the collector, the analyte of interest reacts at the generator and is converted into a new species which is then collected by the collector electrode and converted back to its original form where it is available again for reaction at the generator. This is known as a redox loop and can help boost the signal and decrease the limit of detection of the analyte. The arrangement of GC electrodes can also be exploited to electrochemically control the local pH of the electrodes. In this instance, the collector is held at a potential where it generates protons that locally change the pH of the solution of surrounding the IDE.2-5 The optimised IDE geometry, GC performance and pH control were all established using simulations carried out in COMSOL Multiphysics® software.The optimised fabricated IDEs were used to carry out analysis for the detection of lead. Unlike most electrochemical reactions where a potential is applied and the reaction of interest occurs, the detection of lead requires a two-step process. The first is a pre-concentration or deposition step where lead is deposited onto the electrode at a constant potential for a certain amount of time, and the second is the stripping step. In the stripping step a graph is obtained plotting current against the potential, the peak current obtained in this graph is proportional to the amount of lead in the sample being analysed. In this work, square wave voltammetry is being used for the stripping step. The detection of lead was further enhanced with nanoporous material,6-8 resulting in a 1.5-fold increase in current for the detection of lead at microelectrodes with nanoporous material compared to planar gold. Analysis of lead in both pH-controlled acetate buffer and tap water indicate the benefit of pH control for the detection of lead. The use of IDEs for pH control are also investigated for further enhanced detection of lead in tap water. Murphy, A; Seymour, I; Rohan, J. F; O’Riordan, A; O’Connell, I; Portable Data Acquisition System for Nano and Ultra-Micro Scale Electrochemical Sensors, IEEE Sensors Journal, 21(3), 2021, 3210-3215, 9186668.Seymour, I; O’Sullivan, B; Lovera, P; Rohan, J. F.; O’Riordan, A; Electrochemical detection of free-chlorine in Water samples facilitated by in-situ pH control using interdigitated microelectrodes, Sensors & Actuators B: Chemical, 2020.O’Sullivan, B; Patella, B; Daly, R; Seymour, I; Lovera, P; Rohan, J. F.; Inguanta, R; O’Riordan, A; A Simulation and Experimental Study of Electrochemical pH Control at Gold Interdigitated Microband Arrays, Electrochmica Acta, 395, 2021, 139113.Seymour, I; Narayan, T; Creedon, N; Kennedy, K; Murphy, A; Sayers, R; Kennedy, E; O’Connell, I; Rohan, J. F.; O’Riordan, A; Advanced Solid State Nano-electrochemical Sensors and Systems for Agri 4.0 Application, Sensors, 21, 2021, 3149.Seymour, I; O’Sullivan, B; Lovera, P; Rohan, J. F.; O’Riordan, A; Elimination of Oxygen Interference in the Electrochemical Detection of Monochloramine, using in-situ pH Control at Interdigitated Electrodes, ACS Sensors, 6, 2021, 1030.Nagle, L. C.; Rohan, J. F., Nanoporous Gold Catalyst for Direct Ammonia Borane Fuel Cells, Journal of the Electrochemical Society, 2011.Nagle, L.C.; Wahl, A; Ogurstov, V; Seymour, I; Barry, F; Rohan, J. F.; Mac Loughlin, R. Electrochemical Discrimination of Salbultamol from its Excipients in VentolinTM at Nanoporous Gold Microdisc Arrays, Sensors, 21, 2021, 3975.Twomey, K; Nagle, L. C.; Said, A; Barry, F, Ogurstov, V. I.; Characterisation of Nanaoporous Gold for Use in a Dissolved Oxygen Sensing Application, BioNanoSiences, 2015, 5:55-63. Figure 1

Quo vadis Spectroscopy?

Since the early days of modern chemistry, analytical chemistry always tried to offer solutions to real-life problems. This is how, in the midst of the Industrial Revolution, Margueritte developed the titrimetric determination of iron using the chameleon solution (potassium permanganate). In 1860, for the first time, Bunsen and Kirchhoff used element-specific light emission and absorption of flame-evaporated alkali metal salts for qualitative analysis. Their discovery was groundbreaking because the analytical sensitivity and detection capability of the proposed method was several orders of magnitude lower than that of the contemporary classical analytical ones. Application of this method, leading to the establishment of spectroscopic techniques, also allowed the discovery of about ten chemical elements. Another timeless merit of spectroscopy is the ability to determine the elemental composition of a star in a distant galaxy. In the second half of the 20th century, an era of rapid development of instrumental analysis, atomic spectroscopy also brought several revolutionary results. One such breakthrough was the reduction of the sample volume required for analysis down to microliters with the introduction of graphite furnace atomic absorption spectrometry (GFAAS). The detection limit of GFAAS also decreased by several orders of magnitude. Another important advance was the combination of inductively coupled plasma as a high-temperature ion source with a mass spectrometer (ICP-MS). In the late 1980s, the hyphenation of atomic spectrometric devices to chromatographs, aiming at elemental speciation, also emerged. In Central and Eastern Europe, spectroscopic research was driven by the embargo of the Coordinating Committee for Multilateral Export Controls established by the Western Bloc during the Cold War. In this emerging era, scientific research and applications went hand in hand. Therefore, the science education program and fundamental research were very strong in those countries, contributing considerably to the development of spectrochemistry in Hungary. By the end of the 20th century, development of new equipment and procedures was increasingly carried out by instrument manufacturers, and fundamental research at universities and institutes was relegated to second place. Analytical chemistry has experienced a considerable shift from determination of inorganic compounds and small organic molecules towards that of large (bio)molecules. Expansion of the application of analytical chemistry to forensic, environmental and biochemical questions has been observed and the role of atomic spectrometric techniques seemed to fade away. However, sheer use of these high-performance instruments is not always appropriate or cost-effective; the reliability of the results and elimination of interference must be thoroughly explored. However, when publishing such results, there is a risk that our communications will be rejected due to lack of novelty. Nevertheless, carrying out fundamental research cannot be avoided, as it is not possible to offer appropriate decisions to stakeholders based on questionable results. Presently, GFAAS and ICP-MS allow reliable quantitative determination of virtually any element in any sample. Recently, microwave plasma using nitrogen isolated from the air was launched on the market. This device requires significantly lower operating costs compared to the conventional ICP and reliable simultaneous multi-element analysis has also become possible. Another promising direction is single-particle ICP-MS applied for the characterization of inorganic nanoparticles. Most of the articles of the current issue of BrJAC also demonstrate that atomic spectrometry has become indispensable in many areas of our life. Enjoy reading the current issue!

Измерение напряженно-деформированного состояния деталей АГТД методом тензометрии

The subject of study in the article is various methods of measuring the stress-strain state of AGTE parts by the tensometry method. Differences were revealed when measuring the stress-strain state of rotor and stator parts, in different frequency ranges (study of static, static-dynamic and dynamic deformations). Methods for compensating or reducing the influence of external factors on the measurement results, such as temperature changes and electromagnetic interference, are indicated. The aim is to develop recommendations for research of AGTE parts in a test bench in a gradient of varying temperatures and in a complex electromagnetic environment of the engine. A review of the sources of inaccuracies, errors and interference arising during preparation for testing and directly during the measurement of the SDS of AGTE parts is performed. The effects of wiring, cabling, grounding and shielding can not only increase the level of errors, but can also negate the advantages of an expensive and extremely reliable electronic part of the system. The advantages and disadvantages of the most common schemes for connecting strain gages, as well as their areas of application are presented. Possible ways to compensate for imaginary deformations at temperatures outside the range of thermal compensation of primary converters. A list of common strain gauge systems with their advantages and disadvantages is given for each type of parts and frequency ranges of measurements. When strain measurement rotary parts to output the signal from the strain gauge to recording equipment used various current collector. The possibility of using wireless interfaces for communication between the primary converter and the recording equipment is also indicated. The described methods are: ways to compensate for imaginary deformations caused by changes in the temperature of the investigated part and connecting wires. Elimination or minimization of electromagnetic interference on the measuring channel. An estimate is given of the total error in measuring the deformation for a particular object under study for the final loading cycle, the specificity of the bench strain gauge path, the errors of the current collector in bench conditions, and others in the process of static strain gauging.

Luminescent nanostructures for the detection of latent fingermarks: A review

AbstractMulticolored, multipatterned, and luminescent substrates remain significant challenges for successful detection of latent fingermarks. One effective way to overcome issues with these substrates when visualizing latent fingermarks is the elimination of any background interference through the use of approaches based on luminescence. Luminescent nanoparticles with their unique characteristics including tunable size, high surface energy, and capability of being surface engineered, have sparked great interest in their potential to be utilized for the detection of latent fingermarks on these challenging substrates. These nanoparticles can be inherently luminescent, engineered to luminesce, possibly over specific wavelength ranges, or combined with luminescent agents. This article discusses the reported luminescence‐based nanotechnology applied for enhanced visualization of latent fingermarks to cast light on future possibilities.This article is categorized under: Forensic Chemistry and Trace Evidence &gt; Fingermarks and Other Marks Forensic Chemistry and Trace Evidence &gt; Emerging Technologies and Methods

Targeting Enrichment and Correlation Studies of Glutathione and Homocysteine in IgAVN Patient Urine Based on a Core-Shell Zr-Based Metal-Organic Framework.

Aminothiols are closely related to chronic kidney disease, but little is known regarding levels of related aminothiols in the urine of immunoglobulin A vasculitis with nephritis (IgAVN) patients. Herein, a well-defined core-shell Zr-based metal-organic framework (Zr-MOF) composite SiO2@50Benz-Cys was constructed as a mercury ion affinity material via a solvent-assisted ligand exchange strategy for the selective extraction and enrichment of low-concentration aminothiols in IgAVN patient urine. SiO2@50Benz-Cys was competent to enrich the total glutathione (GSH) and total homocysteine (Hcy) in virtue of the excellent affinity after chelation with mercury ions. The extraction efficiencies were closely related to the pH, dithiothreitol amount, and the dose of functional Zr-MOF. Coupled with HPLC-MS/MS in optimized conditions, GSH and Hcy were determined with low detection limits of 0.5 and 1 nmol L-1, respectively. The recoveries of GSH and Hcy for the urine sample at three spiked levels were in the range of 85.3-105% and 79.5-103%, which showed good precision and accuracy. Benefiting from the matrix interference elimination in the process of extraction, the simultaneous detection of aminothiols in the urine of the healthy group and immunoglobulin A vasculitis (IgAV) and IgAVN patients was successfully carried out, suggesting that the Zr-MOF and the robust method together provided a potential application in the analysis of urinary biomolecules. The analysis of variance (ANOVA) showed that the levels of GSH and Hcy had significant differences between the patients and the control. This work is very valuable as it provides a better understanding of concentration alterations of GSH and Hcy in urine involved with IgAVN for clinical research.