Detection Mode Research Articles

Study on the Dynamic Changes in Non-Volatile Metabolites of Rizhao Green Tea Based on Metabolomics.

The processing of tea leaves plays a crucial role in the formation of the taste of the resulting tea. In order to study the compositions of and changes in taste-related substances during the processing of Rizhao green tea, non-targeted metabolomics was used, based on UHPLC-Q Exactive MS. Totals of 529, 349, and 206 non-volatile metabolites were identified using three different detection modes, of which 112 secondary metabolites were significantly changed. Significant variations in secondary metabolites were observed during processing, especially during the drying stage, and the conversion intensity levels of non-volatile metabolites were consistent with the law of "Drying > Fixation > Rolling". The DOT method was used to screen tea-quality-related compounds that contributed significantly to the taste of Rizhao green tea, including (-)-epicatechin gallate, (-)-epicatechin gallate, gallic acid, L-theanine, and L-leucine, which make important contributions to taste profiles, such as umami and bitterness. Metabolic pathway analysis revealed that purine metabolism, caffeine metabolism, and tyrosine metabolism perform key roles in the processing of Rizhao green tea in different processing stages. The results of this study provide a theoretical basis for tea processing and practical advice for the food industry.

Evaluating geospatial context information for travel mode detection

Detecting travel modes from global navigation satellite system (GNSS) trajectories is essential for understanding individual travel behavior and a prerequisite for achieving sustainable transport systems. While studies have acknowledged the benefits of incorporating geospatial context information into travel mode detection models, few have summarized context modeling approaches and analyzed the significance of these context features, hindering the development of an efficient model. Here, we identify context representations from related work and propose an analytical pipeline to assess the contribution of geospatial context information for travel mode detection based on a random forest model and the SHapley Additive exPlanation (SHAP) method. Through experiments on a large-scale GNSS tracking dataset, we report that features describing relationships with infrastructure networks, such as the distance to the railway or road network, significantly contribute to the model's prediction. Moreover, features related to the geospatial point entities help identify public transport travel, but most land-use and land-cover features barely contribute to the task. We finally reveal that geospatial contexts have distinct contributions in identifying different travel modes, providing insights into selecting appropriate context information and modeling approaches. The results from this study enhance our understanding of the relationship between movement and geospatial context and guide the implementation of effective and efficient transport mode detection models.

Cheap and portable paper chip with terrific oxidase-like activity and SERS enhancement performance for SERS-colorimetric bimodal detection of intracellular glutathione

Glutathione (GSH) acts a crucial role in the normal operation of manifold life activities and is closely bound up with many human diseases. Here, a SERS-colorimetric bimodal paper-based biosensor based on Mn-doped CDs/silver nanoparticles (Mn-CDs/AgNPs) has been fabricated for high-efficiency quantification of intracellular GSH. The Mn-CDs/AgNPs with fine oxidase-like characteristic and SERS enhancement ability has been assembled onto the Whatman filter paper (WFP) to cleverly fabricate paper chip (Mn-CDs/AgNPs@WFP) which can trigger the oxidation of colorless 3,3′,5,5′-tetramethylbenzidine (TMB) into blue TMBox and simultaneously enhance the SERS signal of TMBox. However, the introduction of GSH inhibits the oxidation of TMB, leading to color fading of paper chip and diminishment of SERS signal. Considering this, the bimodal paper-based sensing platform can be exploited for SERS-colorimetric detection of GSH, manifesting excellent selectivity, reliable stability, and satisfactory precision. The detection limits of SERS and colorimetric detection modes are as low as 0.41 μM and 0.53 μM, respectively. Furthermore, this proposed bimodal biosensor has been successfully utilized for the determination of intracellular GSH and validated by commercial GSH assay kit, which provides a mighty and convenient tool for intracellular GSH detection and can boost future effort about exploitation of other multimode paper-based biosensors as well as promote their appliances in disease diagnosis.

Detection of collective modes in unconventional superconductors using tunneling spectroscopy

Detection of collective modes in unconventional superconductors using tunneling spectroscopy

Antidisturbance Control for Hidden Markovian Jump Systems: Asynchronous Disturbance Observer Approach

This paper investigates the anti-disturbance control issue for a class of Markovian jump systems (MJSs) with matched/mismatched disturbances by using disturbance observer approach. A key feature here is that the external disturbance is considered to be generated by a Markovian jump exogenous dynamics, in which the disturbance mode may not be synchronized with the system mode. Meanwhile, it is supposed that both system and disturbance modes can just be estimated via a hidden Markov mode detector. To overcome the possible obstacle in handling dual hidden Markov modes, a mapping technique for continuous-time Markov chain is provided firstly. Then, a novel asynchronous disturbance observer is developed to estimate the external disturbance by utilizing the detected mode. Based upon the estimated disturbance, asynchronous anti-disturbance controllers are investigated for matched and mismatched disturbance cases, respectively. By employing a decoupling technique with the idea of completing the square, sufficient conditions are established for guaranteeing the stability in probability of the resultant closed-loop systems. Finally, two numerical examples are provided to verify the effectiveness of the proposed asynchronous anti-disturbance control approaches under inaccessible system and disturbance modes.

Vision transformers motivating superior OAM mode recognition in optical communications.

Orbital angular momentum (OAM) has recently obtained tremendous research interest in free-space optical communications (FSO). During signal transmission within the free-space link, atmospheric turbulence (AT) poses a significant challenge as it diminishes the signal strength and introduce intermodal crosstalk, significantly reducing OAM mode detection accuracy. This issue directly impacts the performance of OAM-based communication systems and leads to a reduction in received information. To address this critical bottleneck of low mode recognition accuracy in OAM-based FSO-communications, a deep learning method based on vision transformers (ViT) is proposed for what we believe is for the first time. Designed carefully by numerous experts, the advanced self-attention mechanism of ViT captures more global information from the input image. To train the model, pretraining on a large dataset, named IMAGENET is conducted. Subsequently, we performed fine-tuning on our specific dataset, consisting of OAM beams that have undergone varying AT strengths. The computer simulation shows that based on ViT method, the multiple OAM modes can be recognized with a high accuracy (nearly 100%) under weak-to-moderate turbulence and with almost 98% accuracy even under long transmission distance with strong turbulence (C N2=1×10-14). Our findings highlight that leveraging ViT enables robust detection of complex OAM beams, mitigating the adverse effects caused by atmospheric turbulence.

XAS studies of vanadium pentoxide thin films

Thin films of 200 nm of VOx RF magnetron sputtered on the SiO2 glass and Si substrates were studied with X-ray Absorption Spectroscopy in the XANES range of the oxygen K and vanadium L2,3 edges. The total electron yield (TEY) detection mode was used. The spectra were collected at several temperatures between room temperature and 300 °C for the unpolarized and linearly polarized beam to study polarization effects. The experimental data were compared with the theoretical model based on DFT-ROCIS (Density Functional Theory, Restricted Open shell Configuration Interaction with Singles) from the literature. Changes in the spectra with temperature, particularly visible at the oxygen K edge are attributed to the loss of surface oxygen and the corresponding changes of population of the single- double- and triple vanadium coordinated oxygen. The corresponding decrease of the surface stoichiometry leads to formation lower than V5+ valency of vanadium ions such as V4+ or V3+ i.e., containing d-electrons. It gives a tentative explanation for the occurrence of metallicity attributed in the literature to a metal–insulator transition (MIT).

Internal and External Pipe Defect Characterization via High-Frequency Lamb Waves Generated by Unidirectional EMAT

Periodic permanent magnet(PPM) electromagnetic acoustic transducers (EMATs) are commonly employed for axial defect inspection in pipelines. However, the lowest-order shear horizontal waves (SH0) guided waves have difficulties in distinctly differentiating internal and external defects. To enhance the signal-to-noise ratio and resolution, a unidirectional electromagnetic acoustic transducer (EMAT) based on Circumferential Lamb waves (CLamb waves) is developed. Through structural parameter optimization and excitation frequency adjustment, high-amplitude and low-dispersion CLamb waves are successfully generated in the high-frequency-thickness product region of the dispersion curve. Finite element simulations and experimental validation confirm the capability of this EMAT in exciting CLamb waves for the detection of crack-like defects. Experimental results demonstrate that the excitation efficiency of the CLamb EMAT exceeds that of the periodic permanent magnet electromagnetic acoustic transducer by more than tenfold. The defect reflection signal of the CLamb EMAT exhibits higher resolution and more significant amplitude compared to the PPM EMAT. The integration of this method with SH0 mode detection allows for the inspection of both internal and external defects in pipelines, offering a new avenue for EMAT applications in pipeline inspection.

Detection and classification of radial carpet beams propagating through an underwater medium

A radial carpet (RC) optical beam is a type of structured light beam that is classified as a subfamily of combined half-integer Bessel-like beams. Coherent detection of such structured modes can be difficult given their structural complexity and the deterioration of the quality of modes during propagation in turbulent environments. In this paper, we first study the detection of RC modes by using fork-shaped diffraction gratings and then propose an incoherent detection approach to classify 16 classes of RC modes based on training a convolutional neural network model using DenseNet-201 architecture. The dataset comprises recorded images of RC modes after a 120 cm propagation length in a turbulent underwater environment. As the evaluations indicate, the classifier has an accuracy of 98% in identifying RC modes measured in moderate turbulence with a strength level of C n 2∼10−12m−2/3. This method eliminates the difficulties caused by the use of multiple optical elements in coherent detection techniques such as diffraction gratings. Besides simplifying the optical system settings, it also reduces the volume and cost of implementation, especially in optical communication applications.

EVALUATING THE RISK OF FAILURE ON INJECTION PUMP USING FMEA METHOD COMPARATED WITH ELECTRE METHOD

This research is aimed at utilizing failure mode and effect analysis (FMEA) which is a reliability analysis method applicable to Rotary Injection Pump design. In traditional FMEA, Risk Priority Number (RPN) ranking system is used to evaluate, the risk level of failures to rank failures and to prioritize actions. RPN is obtained by multiplying the scores of three risk factors like the Severity (S), Occurrence (O) and Detection (D) of each failure mode. RPN method can not emphasise the nature of the problem, which is multi-attributable and has a group of experts’ opinions. Furthermore, attributes are subjective and have different importance levels. In this paper, results obtained with the FMEA method are checked, using a method from decision theory, respectively the ELECTRE method, both applied for prioritizing the failures that could appear in the functioning of Rotary Injection Pump. Two case studies have been shown to demonstrate the methodology thus developed. It is illustrated a parallel between the results obtained by the traditional method FMA and ELECTRE method for determining the potential failures with the highest risk of occurrence in order to prevent them. The results show that the proposed approach somewhat modifies the obtained results and leads to the conclusion that other developments of the two methods are necessary, using fuzzy sets for the accuracy of the results.

Preclinical pharmacokinetic and in vitro metabolic stability study of lysosomotropic autophagy inhibitor, IITZ-01 in mice by using UPLC-MS/MS

The present study evaluates the pharmacokinetics and metabolic stability of a novel lysosomotropic autophagy inhibitor, IITZ-01 using an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC–MS-MS). It is required as this lead molecule awaits pre-clinical studies for development because of significant therapeutic outcomes in triple-negative breast cancer and renal cancer. A bioanalytical method for the quantitative determination of IITZ-01 in the plasma of mice was developed using the UPLC-MS/MS technique. The UPLC-MS/MS method was validated according to US-FDA bioanalytical guidance and successfully applied to study the pharmacokinetics and metabolic stability. Separation of IITZ- 01 and ZSTK474 (IS) from endogenous components with high selectivity and sensitivity (0.5 ng/mL) was achieved using Waters Acquity BEH C-18 column (50 mm × 2.1 mm, 1.7 μm). A gradient mobile phase consisting of 0.1 % formic acid in water and 0.1 % formic acid in acetonitrile was applied at a flow rate of 0.2 mL/min. Electrospray ionization was employed in positive ion mode for detection, while quantification utilized the multiple reaction monitoring (MRM) mode. This involved using [M+H]+fragment ions at m/z 483.19 → 235.09 for IITZ-01 and m/z 418 → 138 for the internal standard (IS). The method was validated over the calibration range of 0.5–800 ng/mL. The LLOQ of IITZ-01 was 0.5 ng/mL in mice plasma. The method demonstrated good in terms of intra- and inter-day precision and accuracy. The matrix effect was found to be negligible, and the stability data were within acceptable limits. The validated technique supports suitability, reliability, reproducibility, and sensitivity for the pre-clinical investigation of IITZ-01 pharmacokinetics in mice and metabolic stability in human liver microsomes.

Recent Advances in the Development of Non‐Invasive Imaging Probes for Cancer Immunotherapy

AbstractThe last two decades have witnessed a major revolution in the field of tumor immunology including clinical progress using various immunotherapy strategies. These advances have highlighted the potential for approaches that harness the power of the immune system to fight against cancer. While cancer immunotherapies have shown significant clinical successes, patient responses vary widely due to the complex and heterogeneous nature of tumors and immune responses, calling for reliable biomarkers and therapeutic strategies to maximize the benefits of immunotherapy. Especially, stratifying responding individuals from non‐responders during the early stages of treatment could help avoid long‐term damage and tailor personalized treatments. In efforts to develop non‐invasive means for accurately evaluating and predicting tumor response to immunotherapy, multiple affinity‐based agents targeting immune cell markers and checkpoint molecules have been developed and advanced to clinical trials. In addition, researchers have recently turned their attention to substrate and activity‐based imaging probes that can provide real‐time, functional assessment of immune response to treatment. Here, we highlight some of those recently designed probes that image functional proteases as biomarkers of cancer immunotherapy with a focus on their chemical design and detection modalities and discuss challenges and opportunities for the development of imaging tools utilized in cancer immunotherapy.

Recent Advances in the Development of Non-Invasive Imaging Probes for Cancer Immunotherapy.

The last two decades have witnessed a major revolution in the field of tumor immunology including clinical progress using various immunotherapy strategies. These advances have highlighted the potential for approaches that harness the power of the immune system to fight against cancer. While cancer immunotherapies have shown significant clinical successes, patient responses vary widely due to the complex and heterogeneous nature of tumors and immune responses, calling for reliable biomarkers and therapeutic strategies to maximize the benefits of immunotherapy. Especially, stratifying responding individuals from non-responders during the early stages of treatment could help avoid long-term damage and tailor personalized treatments. In efforts to develop non-invasive means for accurately evaluating and predicting tumor response to immunotherapy, multiple affinity-based agents targeting immune cell markers and checkpoint molecules have been developed and advanced to clinical trials. In addition, researchers have recently turned their attention to substrate and activity-based imaging probes that can provide real-time, functional assessment of immune response to treatment. Here, we highlight some of those recently designed probes that image functional proteases as biomarkers of cancer immunotherapy with a focus on their chemical design and detection modalities and discuss challenges and opportunities for the development of imaging tools utilized in cancer immunotherapy.

Axillary node evaluation and biopsy: Predictors of malignancy based on sonographic morphology and mode of detection

PurposeThe purpose of this study was to evaluate various morphologic features of axillary nodes on ultrasound (US) in predicting malignancy and estimate the incidence of malignancy in axillary nodes based on their imaging mode of detection. Methods and materialsA retrospective review of all percutaneous US-guided biopsies on axillary nodes performed at our institution between 1/1/2019–09/30/2021 was performed. Sonographic morphologic features of the biopsied node, imaging mode of detection and size of primary breast malignancy were correlated with malignancy. ResultsThere were 224 malignancies detected in a total of 594 patients who underwent an axillary node biopsy. The positive predictive value (PPV) was significantly associated with the extent of nodal cortical thickening (p < 0.0001). The PPV of malignancy was significantly higher in nodes which lacked a normal hilum (0.61 vs 0.23). The PPV of malignancy in nodes detected on screening mammography (18.8%) or MRI (15.8%) was much lower than those detected on diagnostic imaging, by palpation or on CT/PET (48.4%, 43.8% and 65.3% respectively). Of all screening detected nodes in patients with no history of malignancy and mild cortical thickening, only 2 (4.3%) demonstrated malignancy. ConclusionsMorphology of axillary nodes on sonography is vital in predicting nodal metastasis. Cortical thickness > 5 mm and/or absence of a normal hilum had the highest PPV for metastatic disease. Using clinical history in conjunction with imaging findings will help improve accuracy of axillary nodal biopsies, especially for incidental nodes detected on screening.

Communication-less adaptive directional overcurrent protection strategy considering islanded mode detection in active distribution networks

The integration of distributed energy resources (DERs) in electric distribution networks originates the Active Distribution Networks (ADNs). The presence of DERs introduces challenges to conventional protection schemes due to bidirectional power flows and variations in fault current magnitudes; furthermore, the connection and disconnection of DERs result in multiple ADN operating modes (OMs), deteriorating the effective operation of protective relays. Considering the above, this document presents an adaptive protection strategy to address the challenges related to the variable nature of the ADN operation. The main contribution of the proposed approach is accurate islanded mode detection without requiring communication links, enabling fault detection in all ADN operating modes. The protection strategy maintains directional overcurrent relays' coordination using local voltage and current measurements to continuously estimate the Thevenin equivalent, fault currents, and adaptive coefficients.Relay coordination is maintained through tests conducted on a modified IEEE 34-bus feeder, considering several OMs, fault types, and locations. A comparison between the proposed adaptive protection strategy and a conventional overcurrent scheme shows that relay operating time is better in 100% of the analysed cases for the former strategy. On the other hand, the maximum errors in the fault current estimation using the Thevenin equivalent parameters are between 0.05% to 2.6% for all of the analysed operating modes when compared with the true fault current magnitudes. Finally, the adequate results validate the potential of the proposed communication-less protection strategy for modern protective relaying applications.

Enhanced Nonlinearity of Epsilon‐Near‐Zero Indium Tin Oxide Nanolayers with Tamm Plasmon‐Polariton States

AbstractRecently, materials with vanishingly small permittivity, known as epsilon‐near‐zero (ENZ) media, emerged as promising candidates to achieve nonlinear optical effects of unprecedented magnitude on a solid‐state platform. In particular, the ENZ behavior of indium tin oxide (ITO) thin films resulted in Kerr‐type nonlinearity with non‐perturbative refractive index variations that are key to developing more efficient Si‐compatible devices with sub‐wavelength dimensions. In this contribution, exceptional enhancement of the nonlinear index variation of 30 nm‐thick ITO nanolayers by silicon dioxide/silicon nitride (SiO2/SiN) Tamm plasmon‐polariton structures fabricated by radio‐frequency magnetron sputtering on transparent substrates under different annealing conditions is proposed and demonstrated. In particular, the linear and nonlinear optical properties of ITO thin films and resonant photonic structures are investigated using broadband spectroscopic ellipsometry and intensity‐dependent Z‐scan nonlinear characterization, demonstrating enhancement of optical nonlinearity with refractive index variations as large as Δn ≈ 2 in the non‐perturbative regime. This study reveals that the efficient excitation of strongly confined plasmon‐polariton Tamm states substantially boosts the nonlinear optical response of ITO nanolayers, providing a stepping stone for the engineering of more efficient infrared devices and nanostructures for a broad range of applications, including all‐optical data processing, nonlinear spectroscopy, sensing, and novel quantum detection modalities.

Fluorescence and absorbance dual-mode immunoassay for detection of Ochratoxin A based on 2-aminoterephthalic acid and p-nitrophenol

In this work, a dual-mode immunoassay to detect Ochratoxin A (OTA) was developed relied on p-nitrophenyl phosphate (PNPP) and 2-aminoterephthalic acid (PTA-NH2). This proposed immunoassay based on microplate immunoenzyme technique used alkaline phosphatase (ALP) as a label for forming immune complexes. The ALP was used to catalyze the dephosphorization of PNPP to generate yellow p-nitrophenol (PNP). Since the absorption wavelength of PNP overlapped with the fluorescence emission of PTA-NH2, the fluorescence of PTA-NH2 can be quenched by PNP. The color of PNP and the fluorescence of PTA-NH2 were used as double signals to detect OTA. In this dual-mode immunoassay, the limit of detection (LOD) and the linear detection range of fluorescence mode were 0.57 ng/mL (about 0.57 μg/kg) and 1.56–50.00 ng/mL (about 1.56–50.00 μg/kg), respectively. For absorbance mode, the LOD and linear range were 0.07 ng/mL (about 0.07 μg/kg) and 0.39–25.00 ng/mL (about 0.39–25.00 μg/kg), respectively. Both detection modes showed good selectivity for OTA. The recoveries rates of fluorescence mode and absorption mode in maize flours were 91.80–128.85% and 100.10–114.00%, respectively.

Redox-induced structural changes in Keggin-type tungstophosphate investigated by high-energy-resolution fluorescence detection X-ray absorption spectroscopy

Redox-active heteropolyanions are widely applied to redox catalysts and electron acceptors and the understanding of their reduced states in solution is essential. In this study, the structural changes of Keggin-type tungstophosphate: [PW12O40]3− induced by electrochemical reduction were investigated using W L3-edge X-ray absorption near-edge structure (XANES) spectra in high-energy-resolution fluorescence detection (HERFD) mode. W L3-edge HERFD-XANES spectra revealed the changes in the electronic state of W species and local structure of {WO6} units, which were negligible in conventional transmittance mode; the peak intensities of the split two white line peaks were switched by the electrochemical reduction accompanied by enlargement of the splitting width. Our findings suggest that the injected electron was delocalized on whole {WO6} units in [PW12O40]3− and that the improved symmetry of {WO6} units compensated for the change in valence due to the injected electron.

Copper-pyridine-2,4,6-tricarboxylate metal organic framework nanoparticles based opto-electrochemical sensor for sensitive detection of matrix metalloproteinase‑2

We designed a multiple signal sensing probe based on highly luminescent nanosized Cu-PTC metal-organic framework (MOF). The as synthesized nano-MOF was characterized by various techniques to confirm its morphology, crystallinity and elemental composition. A positively charged matrix metalloproteinase-2 (MMP-2) substrate (a polypeptide) was designed and prepared to interact electrostatically with the negatively charged Cu-PTC MOF probe, resulting in decrease in fluorescence response of the probe. Subsequently, MMP-2 was specifically recognized by the MMP-2 substrate and cleavage of the MMP-2 substrate resulted in “turn-on” fluorescence response from 1 to 175 ng/mL of MMP-2 concentrations with a limit of detection (LOD) of 0.8 ng/mL. In addition, the developed Cu-PTC MOF also exhibited peroxidase-like activity, which was exploited in the electrochemical detection of MMP-2 subjected to the catalysis of 3,3,5,5-tetramethylbenzidine (TMB) in the presence of H2O2. The large surface area of the probe and unique catalytic activity toward TMB facilitated fabrication of an excellent sensing platform to detect MMP-2 with a linear range of 0.5–200 ng/mL with a LOD of 0.25 ng/mL. Various potential interfering biomolecules were evaluated and the stability of the constructed biosensor was assessed in optical and electrochemical modes. The reliability of the electrochemical detection mode was further executed by monitoring MMP-2 in biological samples (human serum and cell samples) and good recoveries were recorded.

A rapid and green method for the simultaneous extraction and determination of copper, arsenic and lead in edible oil

Detecting heavy metals in edible oil is time-consuming and unfriendly to analysts and the environment due to the heavy fat content of oil. This work investigates a rapid and green method for extracting trace concentrations of copper, arsenic and lead in edible oils. To improve the method sensitivity and reduce detection interference, the method was optimized by studying the influence of several parameters, such as the extractant type, extraction time, temperature and mode, concentration of L-cysteine hydrochloride, sedimentation mode and ICP-MS detection conditions. The limits of detection (LOD) of copper, arsenic and lead in the oil samples were 0.027, 0.010 and 0.004 μg/kg, respectively. Recovery tests were performed to determine the method's accuracy, with recovery percentages in the 95.1–104.1% range. The relative standard deviation (RSD, n = 6) of three analyte elements was 1.74–2.05%. The proposed method does not need corrosive or highly toxic organic reagents and completes the extraction process of three heavy metals in edible oil in 5 minutes. The developed green method is suitable for rapid extraction and determination of heavy metals in oil samples from different sources.