Signal Values Research Articles

A coumarin-based near infrared fluorescent probe for the detection of hydrogen sulfide/sulfur dioxide and mitochondrial viscosity

Existing studies have implied that H2S, SO2, and viscosity have potential interrelationships in diseases such as inflammation in the body. Developing fluorescent probes that can simultaneously distinguish and detect the three will be beneficial for relevant workers to explore their potential interrelationships in physiology and pathology. Due to the similar chemical properties of HS− and SO32− (both possessing strong nucleophilic properties), it presents a task with certain challenges that demand careful consideration to detect and differentiate between them using a single probe capable of simultaneously monitoring viscosity changes. In this study, we have designed and prepared a near-infrared fluorescent probe capable of distinguishing and detecting HS−, SO32−, and viscosity, as well as targeting mitochondria. The response of this probe to HS− and SO32− is quenching type and ratio type, respectively, with extremely low detection limits (LOD1 = 0.60 nM for HS−, LOD2 = 1.28 μM for SO32−), fast response time (T1 = 1 min for HS−, T2 = 2 min for SO32−), good selectivity and outstanding anti-interference performance. The monitoring of the viscosity of the probe also shows superior performance. As the viscosity enhances from 0.89 cP to 1412 cP, the fluorescence signal value increases by 52 times, and the trend of fluorescence intensity with viscosity well complies with the Förster-Hoffmann equation. To better understand the response mechanism of the probe to viscosity, we conduct a more in-depth exploration using Gaussian calculations, whose results are in excellent agreement with experimental phenomena. In addition, the probe has successfully achieved monitoring and imaging of HS−, SO32−, and viscosity in Hela cells and 97H cells.

Detecting white interference fringes in noisy conditions via supervised learning neural networks

White interferograms are signals recorded using the interference of light with positional information obtained using a white interferometer, which is a laser technology that uses light interference for the non-contact measurement of the surface topography of a sample. In long-range measurements, the reflected light weakens with increasing distance. When the peak-to-peak value of interference fringe signals is less than the noise level interference fringes cannot be visually confirmed. We propose a neural network-based supervised learning method to detect white interference fringes in noisy conditions. The interference fringes obtained were transformed into time series signals and stored as images. Some of the data was used to train the neural network. Some data was used to validate the trained neural network. The trained model could distinguish between the presence and absence of white interference fringes in noise-contaminated conditions with a certain probability. Numerical calculations and optical experiments validated the proposed method. This technique can be applied to detect weak reflections and extend the interferometry measurement range.

Evaluating Neural Network Models For Predicting Dynamic Signature Signals

Abstract A signature is a biometric attribute commonly used for identity verification. It can be represented by a shape created with a classic pen, but it can also contain dynamic information. This information is acquired using a digital input device, such as a graphic tablet or a digital screen and stylus. Information about the dynamics of the signing process is stored in the form of signals that change over time, including pen velocity, pressure, and more. These dynamics are characteristic of an individual and are difficult for a human to forge. However, it is an interesting research issue whether the values of signals describing a dynamic signature can be predicted using artificial intelligence methods. Predicting the dynamics of the signals describing a signature would benefit various scientific problems, including improving the quality of reference signals by detecting anomalies, creating signature templates better suited to individuals, and more effectively detecting potential forgeries by identity verification systems. In this paper, we propose a method for predicting dynamic signature signals using an artificial neural network. The method was evaluated using samples collected in the DeepSignDB database, distributed by BiDA Lab.

Unraveling the interaction mechanism between orphan drug Nitisinone and bovine serum albumin through spectroscopic and in silico approaches

The interaction between Nitisinone (NTBC) and bovine serum albumin (BSA) as the transport protein in a circulating system was investigated for the first time utilizing various analytical (UV–Vis spectrophotometry, fluorescence spectroscopy, dynamic light scattering, and differential scanning calorimetry) and computational (molecular docking and molecular dynamics simulations) methods. The BSA fluorescence intensity was quenched upon interaction with NTBC, and the quenching mechanism was observed as static. The interaction between NTBC and BSA was examined at 288 K, 298 K, and 308 K where the binding constants were found to be 1.44 × 105 ± 0.22 M−1, 5.18 × 104 ± 0.20 M−1, and 3.02 × 104 ± 0.22 M−1 respectively, suggesting an intermediate binding affinity between NTBC and BSA. Changes in the microenvironment surrounding tryptophan and tyrosine residues of BSA were elucidated using 3-D fluorescence spectroscopy. Thermodynamic studies revealed the calculated values of ΔH = − 54.34 ± 5 kJ/mol and ΔS = − 0.0908 ± 0.24 kJ/mol K−1, indicating the involvement of van der Waals forces and hydrogen bonds in the interaction between NTBC and BSA. Moreover, the interaction’s spontaneous nature was evidenced by negative ΔG values across all temperatures. Using dynamic light scattering, it was observed that higher NTBC concentrations led to a gradual rise in hydrodynamic diameter and notable aggregation of the NTBC-BSA complex. Moreover, changing signal values and shifted peaks of BSA, NTBC, and complex in differential scanning calorimetry curves, meant there were molecular interactions between the NTBC and BSA. In silico approaches also elucidated how NTBC binds to active sites on BSA, further supporting other findings. Moreover, molecular docking studies offer a more profound insight into the changing dynamics of hydrophobic, hydrogen, and halogen bonding involved in stabilizing the NTBC-BSA complex.

The egalitarian value of counterfeit goods: Purchasing counterfeit luxury goods to address income inequality

AbstractThe present research demonstrates a novel driver of the growing demand for counterfeit luxury goods: perceptions of income inequality. Across five studies, using different samples and counterfeit luxury goods, we find that as perceptions of income inequality increase, consumers value counterfeit luxury products for their “egalitarian value”—a value associated with counterfeits' perceived ability to restore equality in society. Consumers perceive both public and private counterfeit luxury goods to have egalitarian value, suggesting that their value manifests itself beyond consumers' attempts to signal status via consumption. Moreover, the egalitarian value increases consumers' motivation to purchase counterfeit luxury goods beyond their hedonic, utilitarian, economic, or status signaling value. Finally, the positive effect of the egalitarian value of counterfeit luxury goods on purchase preference is greater among consumers who think equality is more desirable and attainable (i.e., those low in social dominance orientation). Our results outline one psychological mechanism underlying consumers' interests in counterfeit luxury goods, explaining how egalitarian value may link two important societal issues: growing income inequality and increased demand for counterfeits.

Features of Bearing on Underwater Object Using Phase Information of a Differential Stereo Sensor

Introduction. Safety of navigation and development of underwater mineral deposits require the accurate detection of various underwater objects. The literature discusses the issues of tracking their motion and trajectory. Sonar methods are proposed to maintain high accuracy of underwater object positioning. High accuracy of the bearing of stereo sensors with an ultrashort base is noted. However, this equipment is sensitive to the sampling rate of the signals, which causes “sampling noise”. There are no publicly available publications dedicated to the solution to this problem. The presented study is designed to fill this gap. This work is aimed to study the possibility of obtaining data clarifying information about the bearing of underwater objects through using the phase information about echoed probing signals and an additional procedure for resampling the source data.Materials and Methods. The location of the object was determined using the experimental complex for studying hydroacoustic sensors created by V.A. Shirokov and V.N. Milich at the Udmurt Federal Research Center, the Ural Branch of the Russian Academy of Sciences. A stereo sensor with a small base (30 mm) was used compared to the distance to the object (≈800–900 mm). Digital filtering methods and mathematical apparatus of correlation analysis of return hydroacoustic signals obtained by the phase method were used for data processing.Results. The results of comparing two methods for determining the bearing on an object are presented: by the difference in the time of arrival of the pulse-leading edges and by the maximum of the cross-correlation function (CCF). The change in bearing as the object moves, is graphically shown. The use of the leading edge of the signal caused small outliers of values along the entire bearing curve (less than 0.12 rad). At the maximum CCF, emissions were recorded only in some areas, but they were quite significant (about 0.17 rad). It showed how to select points corresponding to a smoother and more valid object trajectory, and how to work with erroneous points. The presented method of error correction can be implemented programmatically. With a quasi-harmonious signal, rare measurements of the original signal are interpolated by frequent calculated values. Thanks to this virtual increase in the sampling rate (oversampling), intermediate indicators can be recorded in the digitized source data. Interpolation of the signal values by a cubic spline allowed us to obtain 20 points for 1 period of the signal instead of 5 points in the original version. In this case, the trajectory formed with the maximum CCF is more correct.Discussion and Conclusion. The direction-finding problem can be solved with the accuracy required for practical application. Taking into account the factor of smoothness and continuity of the object's trajectory makes it possible to qualitatively correct the selection of the maximum of the cross-correlation function of the stereo sensor signals. The proposed methods have great potential for the development of underwater vision systems.

Miniaturization of elastic scattering lidars: determination of the microstructure of the surface layer of the atmosphere

Miniature elastic scattering lidars with similar schemes for determining the microstructure of the surface layer of the atmosphere are considered. In the considered microlidar model, it is assumed that in the limiting case there may be no particles in a small probed volume. In this case, the minimum value of the return signal corresponds to molecular scattering. The excess of the signal above this level is associated with the presence of a particle. The molecular component of the backscatter signal is constant and can be compared to a tabulated value of the backscatter coefficient using an optical atmospheric model. This makes it possible to compare the average value of the total backscattering signal from molecules and particles with the overall backscattering coefficient. A scheme similar to a microlidar, but on an enlarged scale – a minilidar – is considered. For both such schemes, the average values of atmospheric backscatter signals are the same. For a minilidar, the return signal is formed by scattering from a layer ranging in size from several meters to several tens of meters. In this case, the probed volume can be determined using perforated screens and reflective spheres. It is shown that the ratio of the probed volumes for the minilidar and microlidar is equal to the similarity coefficient to the fourth power. The considered lidars can be used to determine the concentration of equivalent particles.

The ambiguity of frequency determination in digital microwave frequency discriminators

Instantaneous frequency measurement devices are designated for very fast measurements of the current frequency value of microwave signals, even if they are very short in the time domain. Fast measurements of frequency temporary values may be based on the evaluation of the phase difference of signal propagating through the microwave transmission lines with unequal, but known, lengths. This paper presents the principle of determination of temporary values of the microwave signal frequency using the digitalized signals and the binary value of them eventually. In the purpose of increase the frequency discrimination resolution, additional tracks with lines with a larger length are proposed. For the system with elements with analytical model transmission characteristics it is typical that bands of ambiguity of frequency measurement occurs. To tackle this problem in addition to 4 x 4 Butler matrix implementation the method of using combination sine and cosine signals is proposed.

Value of Gold and Silver Signals and their Correlation with Step Scores on OBGYN Interview Offers

Competition for residency positions has led to application inflation. In the 2022-23 cycle, 16 residency specialties allowed applications to be submitted with a virtual “token” - signaling a preferred interest in a program. OBGYN was the only program using a two-tiered system that allowed applicants to assign signals using “gold” to indicate highest interest and “silver” indicating very high interest. We examined the impact of the tiered signals on interview offer trends of senior students pursuing OBGYN at a large allopathic medical school and if the interview rate was correlated with their USMLE step scores. A cross-sectional, anonymous survey included the number of interviews obtained from applications submitted using gold signals (3), silver signals (15), and no signal (no cap). Fifteen students identified as participating in the OBGYN match with 100% participation, ten of whom were from regional campuses (67%). The mean interview rate differed based on signaling, showing increased likelihood of interview offers based on signal type. Step 1 and step 2 quartile rank were not associated with signal interview rate. This study supports the use of tiered signals as a method for students to express an interest in specific programs and have it recognized by programs in extending interview offers. The authors have no conflicts of interest to disclose. This study was IRB exempt.

Early multi-parameter detection study of lithium-ion batteries based on the ratio of blue to infrared light and gas concentration

As the use of lithium-ion batteries in energy storage and transportation grows, the number of fires and explosions caused by battery thermal runaway increases, emphasizing the vital need for enhanced early detection technology. Existing research does not clarify the effect of airflow environment and detection location on battery smoke flow and detection effectiveness. The purpose of this study is to illuminate the environmental effects on battery smoke diffusion, allowing for the selection of more appropriate detection parameters while also improving detection sensitivity and robustness. Here, the investigation focuses on the smoke characteristics of 18650 LiFePO4 (LFP) batteries, using the ratio of blue to infrared light and concentrations of CO and H2. Additionally, a detrending algorithm was developed to interpret smoke signals, and the smoke characteristics of batteries in different states of diffusion after thermal runaway occurred at different states of charge (SOC) were further investigated. It is shown that the smoke signal values processed by the detrending algorithm are more suitable for smoke detection in thermal runaway batteries. Using smoke and fugitive gas growth rate parameters, the results show that airflow interference is important in promoting smoke diffusion. Notably, the ambient state and the SOC of the battery have a greater influence on the maximum concentration of CO compared to H2. The linear equations and the addition of the environmental influence parameter DR imply that H2 is a better choice as the primary gas parameter for identifying battery runaway. The airflow disruption reduced the smoke response time by around 40 % while having minimal influence on gas diffusion. This study establishes a theoretical foundation for optimizing battery operating environments and gives practical guidelines for the use of multi-parameter monitoring and early detection of lithium-ion batteries. Furthermore, this study improves the safe management and protection of lithium batteries in their application.

Muscle texture features on preoperative MRI for diagnosis and assessment of severity of congenital muscular torticollis

ObjectivesTo develop an objective method based on texture analysis on MRI for diagnosis of congenital muscular torticollis (CMT).Material and methodsThe T1- and T2-weighted imaging, Q-dixon, and T1-mapping MRI data of 38 children with CMT were retrospectively analyzed. The region of interest (ROI) was manually drawn at the level of the largest cross-sectional area of the SCM on the affected side. MaZda software was used to obtain the texture features of the T2WI sequences of the ROI in healthy and affected SCM. A radiomics diagnostic model based on muscle texture features was constructed using logistic regression analysis. Fatty infiltration grade was calculated by hematoxylin and eosin staining, and fibrosis ratio by Masson staining. Correlation between the MRI parameters and pathological indicators was analyzed.ResultsThere was positive correlation between fatty infiltration grade and mean value, standard deviation, and maximum value of the Q-dixon sequence of the affected SCM (correlation coefficients, 0.65, 0.59, and 0.58, respectively, P < 0.05).Three muscle texture features—S(2,2)SumAverg, S(3,3)SumVarnc, and T2WI extreme difference—were selected to construct the diagnostic model. The model showed significant diagnostic value for CMT (P < 0.05). The area under the curve of the multivariate conditional logistic regression model was 0.828 (95% confidence interval 0.735–0.922); the sensitivity was 0.684 and the specificity 0.868.ConclusionThe radiomics diagnostic model constructed using T2WI muscle texture features and MRI signal values appears to have good diagnostic efficiency. Q-dixon sequence can reflect the fatty infiltration grade of CMT.

Transcriptional switches in melanoma T Cells: Facilitating polarizing into regulatory T cells

Melanoma is a malignant skin tumor with a high mortality rate. Regulatory T cells (Tregs) are immune cells with immunosuppressive roles, however, the precise mechanisms governing Treg involvement in melanoma remain enigmatic. Experimental findings unveiled different transcription factor switches between normal and tumor T cell, with heightened FOXP3 and BATF in the latter. These factors induced immunosuppressive molecules and Treg maintenance genes, polarizing tumor T cells into Tregs. Spatial transcriptomics illuminated the preferential settlement of Tregs at the melanoma periphery. Within this context, FOXP3 in Tregs facilitated direct enhancement of specific ligand gene expression, fostering communication with neighboring cells. Novel functional molecules bound to FOXP3 or BATF in Tregs, such as SPOCK2, SH2D2A, and ligand molecules ITGB2, LTA, CLEC2C, CLEC2D, were discovered, which had not been previously reported in melanoma Treg studies. Furthermore, we validated our findings in a large number of clinical samples and identified the Melanoma Treg-Specific Regulatory Tag Set (Mel TregS). ELISA analysis showed that the protein levels of Mel TregS in melanoma Tregs were higher than in normal Tregs. We then utilized SERS technology to measure the signal values of Mel TregS in exosome, and successfully discriminated between healthy individuals and melanoma patients, as well as early and late-stage patients. This approach significantly enhanced detection sensitivity. In sum, our research elucidated fresh insights into the mechanisms governing Treg self-maintenance and communication with surrounding cells in melanoma. We also introduced an innovative method for clinical disease monitoring through SERS technology.

Efficient Cyberattack Detection Methods in Industrial Control Systems.

The article deals with the issue of detecting cyberattacks on control algorithms running in a real Programmable Logic Controller (PLC) and controlling a real laboratory control plant. The vulnerability of the widely used Proportional-Integral-Derivative (PID) controller is investigated. Four effective, easy-to-implement, and relatively robust methods for detecting attacks on the control signal, output variable, and parameters of the PID controller are researched. The first method verifies whether the value of the control signal sent to the control plant in the previous step is the actual value generated by the controller. The second method relies on detecting sudden, unusual changes in output variables, taking into account the inertial nature of dynamic plants. In the third method, a copy of the controller parameters is used to detect an attack on the controller's parameters implemented in the PLC. The fourth method uses the golden run in attack detection.

Directly power system harmonics estimation using Equilibrium Optimizer

In power systems, the frequency values of current and voltage signals are expected to be at the fundamental frequency. Harmonic components may occur due to the effect of non-linear loads. Accurate estimation of harmonic components is important in determining the precautions to be taken. In this study, Equilibrium Optimizer (EO) based harmonic estimator has been proposed and applied to solve the harmonic and sub/inter-harmonic estimation problems. In addition to estimation amplitude, phase and frequency, unlike the literature, DC offset decaying values of power signals have been estimated with proposed method. Most common used synthetic stationary signals and dynamic signal with different noisy levels have been used in order to shown effectiveness. From the outputs, it has been seen that the proposed method gives high resolution results and has an impressive performance even if the parameters of the harmonics increase and/or the harmonics have high SNR levels. Moreover, obtained results indicate the EO-based estimator can robustly and accurately estimate all unknown or specified parameters of the harmonics simultaneously with high accuracy and higher resolution.

Camelids in the hyperarid core of the Atacama desert 12,000–11,000 years ago? A stable isotope study and its consequences for early human settlement

How did hunter-gatherers initially settle and move across extreme environments? We conducted a multi-disciplinary study to tackle this question, focusing on how Paleoindigenous populations inhabited the hyperarid core of the Atacama Desert. Particularly, we examined the stable isotopic values of ∼12,000–11,200-year-old camelid and rodent bones and hair samples retrieved from low-elevation archaeological sites (Pampa del Tamarugal basin - PdT, 800–1200 masl). By integrating novel and existing data into a regional stable isotope ecology, we offer a baseline for interpreting our results. δ13C and δ15N values on archaeological remains show animals with different geographical origins. A first group includes camelids and rodents with lower δ15N values and δ13C values indicating a dominantly C3 diet, corresponding to animals either local to the PdT or from the Andean Steppe, at least ∼80 km away and between 4000 and 4500 masl. Most of these remains, however, come from residential sites and belong to young camelids, indicating a local origin. A second group presents a higher δ15N signal and δ13C values indicative of a mixed C3–C4 based diet. These animals were not local but source to the Puna at least ∼60 km away between 3200 - 4000 masl. We hypothesize that the first would correspond to animals associated with hunter-gatherer bands settled around a wetland and grove environment in the PdT. The second group could correspond to remains brought by humans from the Puna to the PdT. Our results demonstrate that during the Late Pleistocene/Early Holocene the Atacama was very different than today, supporting life that included large and mid-size game. These results also show that the core of the Atacama attracted animals and people and counters the notion of this ecosystem as a barren passageway from the Andes to the coast.

A new di-recognition and di-functional nanosurface aptamer molecularly imprinted polymer probe for trace glyphosate with SERS/RRS/Abs trimode technique

A new di-recognition nitrogen-doped carbon dot nanosurface aptamer molecularly imprinted polymer (CDNAg@MIPApt) nanocatalytic di-functional probe was prepared by microwave irradiation. The probe was utilized nitrogen-doped silver carbon dots (CDNAg) as the matrix, glyphosate (Gly) as the template molecule, α-methyl acrylate as the monomer, ethylene glycol dimethacrylate as the cross-linker, and aptamer as the biorecognition element. It could not only recognize Gly but also exhibits catalytic amplification function. It was found that CDNAg@MIPApt catalyzed the redox reaction of polyethylene glycol 400 (PEG400)-AgNO3 to generate silver nanoparticles (AgNPs). The AgNPs indicator component exhibit the effects of surface-enhanced Raman scattering (SERS), resonance Rayleigh scattering (RRS) and surface plasmon resonance absorption (Abs). In the presence of Gly, it binds to the surface imprinted site of CDNAg@MIPApt, to reduce AgNPs generation due to the catalytic activity of CDNAg@MIPApt decreasing. Thus, the SERS/RRS/Abs signal values decreased linearly. The linear ranges of SERS/RRS/Abs assay were 0.1–2.5 nM, 0.25–2.75 nM and 0.5–5 nM respectively. The detection limits were 0.034 nM, 0.071 nM and 0.18 nM Gly.

Application of an Improved Laplacian-of-Gaussian Filter for Bearing Fault Signal Enhancement of Motors

The presence of strong noise and vibration interference in fault vibration signals poses challenges for extracting fault features from motor bearings. Therefore, appropriate pre-filtering procedures can effectively suppress the impact of the noise interference and further enhance fault-related signals. In this work, an improved Laplacian-of-Gaussian (ILoG) filter is proposed to enhance the fault-related signal. The proposed ILoG approach employs an enhanced Kurtosis-based indicator known as Correlated Kurtosis (CK). The CK capitalizes on the cyclostationarity of fault-related impulses and mitigates the random nature of impulse noise. Subsequently, an objective function, based on CK statistics, is suggested to iteratively update LoG coefficients by maximizing the CK value of the output signal. Therefore, the ILoG filter can better highlight the fault cyclic impulses associated with bearing faults. Furthermore, the ILoG filter is capable of attenuating impulsive noise, a feature that is absent in the original LoG filter. The simulation and experimental results demonstrate that the proposed ILoG method provides a remarkable capability to effectively enhance the fault-induced components, thereby improving the diagnostic accuracy. Consequently, the ILoG filter holds great potential for application in motor bearing fault diagnosis.

Command Filter-Based Adaptive Neural Control for Nonstrict-Feedback Nonlinear Systems with Prescribed Performance

In this paper, a new command filter-based adaptive NN control strategy is developed to address the prescribed tracking performance issue for a class of nonstrict-feedback nonlinear systems. Compared with the existing performance functions, a new performance function, the fixed-time performance function, which does not depend on the accurate initial value of the error signal and has the ability of fixed-time convergence, is proposed for the first time. A radial basis function neural network is introduced to identify unknown nonlinear functions, and the characteristic of Gaussian basis functions is utilized to overcome the difficulties of the nonstrict-feedback structure. Moreover, in contrast to the traditional Backstepping technique, a command filter-based adaptive control algorithm is constructed, which solves the “explosion of complexity” problem and relaxes the assumption on the reference signal. Additionally, it is guaranteed that the tracking error falls within a prescribed small neighborhood by the designed performance functions in fixed time, and the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB). The effectiveness of the proposed control scheme is verified by numerical simulation.

Research on measuring method of self-mixing interference magnetic field based on Faraday effect

In this paper, the magnetic field measurement method of laser self-mixing interference based on the Faraday effect is proposed. The polarization plane of the linearly polarized light is changed by the terbium gallium garnet crystal with the influence of the magnetic field. The light modulated by the magnetic field reentered into the laser cavity through the Brewster window and formed the self-mixing effect. The theoretical analysis of the self-mixing interference model based on the Faraday effect is conducted, which explains essential features of the experimental results. The magnetic field is measured by the peak-to-peak value of self-mixing interference signal. The experimental results show that the relative error of the magnetic field measurement is within ±1.6%. The measurement method has the advantage of simple and compact structure with strong anti-interference ability.

Depth Evaluation of Subsurface Defects in Lead Seal Based on Accumulated Value Feature from Pulsed Eddy Current Signals

The lead seal is one of the piezoelectric cable components that is prone to failure. In this paper, the accumulated value of pulsed eddy current signals was utilized to characterize the subsurface defect depth of the lead seal for the safety of the lead seal in service. The characterization method of the defect depth was analyzed by the finite element model. The simulation results showed that the accumulated value feature had a linear relationship with the subsurface defect depth in a semilogarithmic coordinate system, and the linear fitting coefficient was 0.9982. The experimental results showed that the accuracy of the accumulated value feature in characterizing the subsurface defect depth was better than that of the peak value feature. Specifically, the maximum relative errors of the measurements were 12.51% and 9.07%, while the average relative errors were 5.83% and 8.00%, respectively.