Signal Decay Research Articles

Extending global fits of 4D Composite Higgs Models with partially composite leptons

We perform the first convergent Bayesian global fits of 4D Composite Higgs Models with partially-composite third generation quarks and leptons based on the minimal SO(5) → SO(4) symmetry breaking pattern. We consider two models with the τ lepton and its associated neutrino in different representations of SO(5). Fitting each model with a wide array of experimental constraints allows us to analyse the Bayesian evidence and currently-observed fine-tuning of each model by calculating the Kullback-Leibler divergence between their respective priors and posteriors. Notably both models are found to be capable of satisfying all constraints simultaneously at the 3σ level at scales of < 5 TeV. From a Bayesian viewpoint of naturalness the model with leptons in the 14 and 10 representations is preferred over those in the 5 representation due to its lower fine-tuning. Finally, we consider the experimental signatures for the preferred parameters in these models, including lepton partner decay signatures and gluon-fusion produced Higgs signal strengths, and discuss their potential phenomenology at future high-luminosity LHC runs.

An integrated machine-learning model to predict nucleosome architecture.

We demonstrate that nucleosomes placed in the gene body can be accurately located from signal decay theory assuming two emitters located at the beginning and at the end of genes. These generated wave signals can be in phase (leading to well defined nucleosome arrays) or in antiphase (leading to fuzzy nucleosome architectures). We found that the first (+1) and the last (-last) nucleosomes are contiguous to regions signaled by transcription factor binding sites and unusual DNA physical properties that hinder nucleosome wrapping. Based on these analyses, we developed a method that combines Machine Learning and signal transmission theory able to predict the basal locations of the nucleosomes with an accuracy similar to that of experimental MNase-seqbased methods.

Determination of the polarization of Xe nuclear spin using transverse and longitudinal Rb in-situ magnetometers in NMR co-magnetometers

NMR co-magnetometers, as novel atomic sensors, can measure the angular velocity information in inertial measurements by detecting the spin precession of Xe nuclei. The Xe polarization plays a crucial role in the sensing unit of co-magnetometers, as it enhances the signal-to-noise ratio (SNR) and sensitivity of NMR sensors. Here we elucidated the Rabi dynamics of Xe nuclear spin and demonstrated two methods to determine the Xe polarization based on the classical Bloch equations. By detecting the optical rotation angle signal, we acquired the amplitude and the phase variations information in two methods, respectively. The transverse magnetometer relies on the amplitude of the free induction decay (FID) signal and applies a short pulse to flip the Xe fields into the transverse plane, enabling precise measurements. On the other hand, the longitudinal magnetometer offers an intuitive approach to measuring the demodulated phase variations by capturing the repetitive flips of longitudinal Xe fields. This paper discusses the advantages and disadvantages of both proposed methods, with the aim of enhancing the accuracy and authenticity of nuclear spin polarization measurements for noble gas atoms in atomic sensors.

Multifunctional MOF: Cold/hot adapted sustainable oxidase-like MOF nanozyme with ratiometric and color tonality for nitrite ions detection

Integrating multiple functionalities into a single entity is highly important, especially when a broad spectrum of application is required. In the present work, we synthesized a novel manganese-based MOF (denoted as UoZ-6) that functions as a cold/hot-adapted and recyclable oxidase nanozyme (Km 0.085 mM) further developed for ratiometric-based colorimetric and color tonality visual-mode detection of nitrite in water and food. Nitrite ions promote the diazotization process of the oxTMB product, resulting in a decay in the absorbance signal at 652 nm and the emergence of a new signal at 461 nm. The dual-absorbance ratiometric platform for nitrite ion detection functions effectively across a wide temperature range (0 °C to 100 °C), offering a linear detection range of 5–45 μM with a detection limit of 0.15 μM using visual-mode. This approach is sensitive, reliable, and selective, making it effective for detecting nitrite ions in processed meat and water.

Two-Dimensional Laplace NMR Reconstruction through Deep Learning Enhancement.

Laplace NMR is a powerful tool for studying molecular dynamics and spin interactions, providing diffusion and relaxation information that complements Fourier NMR used for composition determination and structure elucidation. However, Laplace NMR demands sophisticated signal processing algorithms such as inverse Laplace transform (ILT). Due to the inherently ill-posed nature of ILT problems, it is generally challenging to perform satisfactory Laplace NMR processing and reconstruction, particularly for two-dimensional Laplace NMR. Herein, we propose a proof-of-concept approach that blends a physics-informed strategy with data-driven deep learning for two-dimensional Laplace NMR reconstruction. This approach integrates prior knowledge of mathematical and physical laws governing multidimensional decay signals by constructing a forward process model to simulate relationships among different decay factors. Benefiting from a noniterative neural network algorithm that automatically acquires prior information from synthetic data during training, this approach avoids tedious parameter tuning and enhances user friendliness. Experimental results demonstrate the practical effectiveness of this approach. As an advanced and impactful technique, this approach brings a fresh perspective to multidimensional Laplace NMR inversion.

Separation and Evaluation of the Gradient Relaxation in the Atomic Comagnetometer

AbstractIn the atomic comagnetometer, nuclear spin relaxation is a core parameter that affects the magnetic field suppression ability and stability, and is influenced by various gradient fields. It is necessary to measure and separate the effects of different gradients on nuclear spin, which helps to effectively suppress them separately. This article proposes a periodic optical pumping method for separating and measuring polarization gradient relaxation and magnetic field gradient relaxation, considering the effects of pump light and applied magnetic field. The comprehensive influence model for pump light on transverse nuclear spin relaxation is established, and the measurement steps and parameter selection criteria for the proposed method considering signal decay characteristics are provided. Furthermore, the proportion of various gradient relaxations is quantified. This work provides an evaluation method for gradient relaxation suppression, supporting the improvement of the measurement sensitivity and stability of the atomic comagnetometer.

Melting entropy of crystals determined by electron-beam-induced configurational disordering.

Upon melting, the molecules in a crystal explore numerous configurations, reflecting an increase in disorder. The molar entropy of disorder can be defined by Boltzmann's formula ΔSd = Rln(Wd), where Wd is the increase in the number of microscopic states, so far inaccessible experimentally. We found that the Arrhenius frequency factor A of the electron diffraction signal decay provides Wd through an experimental equation A = AINTWd, where AINT is an inelastic scattering cross section. The method connects Clausius and Boltzmann experimentally and supplements the Clausius approach, being applicable to a femtogram quantity of thermally unstable and biomolecular crystals. The data also showed that crystal disordering and crystallization of melt are reciprocal, both governed by the entropy change but manifesting in opposite directions.

ЗАСТОСУВАННЯ ФІЛЬТРА ЧАСТОЧОК ДО ЗАДАЧ САМОЛОКАЛІЗАЦІЇ ЛИШЕ ЗА ВІДСТАННЮ ДО ДЖЕРЕЛ РАДІОСИГНАЛІВ

This work is aimed at searching for a relatively accurate and computationally efficient algorithm for range-only self-localization. Key requirement to the data sources is cost effectiveness. The radio signal strength indicator (RSSI)-based distance estimation model was chosen, due to wide availability of hardware and cost effectiveness. Key requirements to the algorithm are robustness towards noise introduced by RSSI-based distance estimation errors and flexibility to introduce additional data sources. Particle filter algorithm was chosen, because it satisfies both requirements, although it has bigger computational costs comparing to Kalman filter. A simulation environment was created to conduct experiments with assumed transmitted signal strength of 1W and square root signal decay law. A Particle filter-based actor was implemented. Actor starts by translating geo-spatial coordinates of beacons into relative planar cartesian coordinates, generates particles around beacons. Particles are placed with uniform distribution within a torus with co-planar circular axis radius equal to distance estimation. In each experiment, simulation software walks actor through a pre-defined path, compares obtained position estimates with expected state and calculates MAE and RMSE. Obtained results were satisfactory, in some cases showing MAE=2.5981 and RMSE=2.8474 after short stabilization period of few iterations. This period exists due to suboptimal initial particles placement. A Kalman filter-based actor was implemented as a comparison. A reference Kalman filter-based implementation showed slightly worse overall results with MAE=12.5199 and RMSE=13.2238. This can be explained by a lack of input from IMU. Further research will be directed towards UAV swarm self-localization and collision avoidance.

From ECG to broadband ECG, focused on the ventricular activation

Abstract Background An ultra-high-frequency ECG (UHF-ECG) technique, recently introduced, provides ventricular activation patterns and identifies electrical dyssynchrony. UHF-ECG interpretation assumes that the ECG amplitude decreases rapidly at higher frequencies with increasing distance from the source. Based on this property, nearby sources can be distinguished. Unfortunately, this assumption has never been experimentally proven. Purpose The study aims to show whether there is a decrease in ECG amplitude with distance from the source and whether this decrease is frequency-dependent. Methods UHF-ECG resting recordings were acquired in 106 subjects. We used a standard electrode setup for a 12-lead ECG. In addition, we recorded UHF-ECG from six extended precordial electrodes. With the help of magnetic resonance images, we measured the distance of all precordial leads to the ventricular geometrical center. For each lead, we determined the amplitude of frequency components by computing the area of the averaged amplitude envelopes in the region of the QRS complex. We analyzed five frequency bands: LF (0.2-20 Hz), MF (20-80 Hz), HF (80-300 Hz), UHF1 (300-500 Hz), and UHF2 (800-1000 Hz). Results The left panel in the figure shows the relative amplitude decrease in five frequency bands with relative distance from the depolarization source. The decay coefficient in the LF band is only 0.56 [0.84, 0.29] median [percentile 25,75] and gradually grows up to 1.23 [1.40, 0.98] in the UHF2 band, p&amp;lt;0.005. It indicates that the amplitude of the ECG signal from distant areas of the ventricles in the LF band drops approximately 50 percent of the original value, and the amplitude in the UHF2 band drops to only 20 percent of the original value. The right panel demonstrates an amplitude decrease with distance and frequency in the background of heart geometry. The circle's area corresponds to the relative signal intensity recorded in a particular body surface electrode V1, V4, and V6 from RV, LV, and septal ventricular segments. The circle marked in red has a size of 1 and is at the smallest distance from the electrode. The right panel includes the LF band (regular ECG) and the UHF2 band of 800-1000 Hz. Conclusion The results show significant differences in ECG signal decay between frequency bands and the ability to localize nearby sources using UHF-ECG. Verifying the principle of frequency dependence of ECG properties opens possibilities for a more accurate description of activation patterns. Combining multiple frequency bands (broadband ECG) has the potential to distinguish the activation of near and distant sources.Different decrease in ECG amplitude

A novel proton decay signature at DUNE, JUNO, and Hyper-K

Proton decay, although unobserved so far, is a natural expectation when attempting to explain the baryon asymmetry of the universe. p→K+ν¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ p\ o {K}^{+}\\overline{\ u} $$\\end{document} or p→K+χ~10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ p\ o {K}^{+}{\\overset{\\sim }{\\chi}}_1^0 $$\\end{document}, with χ~10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {\\overset{\\sim }{\\chi}}_1^0 $$\\end{document} a light exotic neutral particle, represent possible decay channels achievable in models of physics beyond the Standard Model, such as the MSSM with trilinear R-parity-violating terms, or the Standard Model extended by a heavy neutral lepton. Among the decay products of these modes, the neutral fermions would typically appear as missing energy in collider searches. The present study considers how such decay modes could be differentiated in experimental settings, as the exotic χ~10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {\\overset{\\sim }{\\chi}}_1^0 $$\\end{document} may further decay if it is not protected by a symmetry (such as R-parity in the MSSM). We assess the detection prospects of the proposed experiments DUNE, JUNO and Hyper-K in this context.

Loss Control-Based Key Distribution under Quantum Protection.

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. We meet this challenge by experimentally realizing the Quantum-Protected Control-Based Key Distribution (QCKD) protocol, utilizing physical control over signal losses. By ensuring significant non-orthogonality of the leaked quantum states, this control severely constrains eavesdroppers' capacities. We demonstrate the performance and scale of our protocol by experiments over a 1707 km long fiber line. The scalability of the QCKD opens the route for globally secure quantum-resistant communication.

Indoor Infrastructure Maintenance Framework Using Networked Sensors, Robots, and Augmented Reality Human Interface

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0.

DSFworld: A flexible and precise tool to analyze differential scanning fluorimetry data.

Differential scanning fluorimetry (DSF) is a method to determine the apparent melting temperature (Tma) of a purified protein. In DSF, the raw unfolding curves from which Tma is calculated vary widely in shape and complexity. However, the tools available for calculating Tma are only compatible with the simplest of DSF curves, hindering many otherwise straightforward applications of the technology. To overcome this limitation, we designed new mathematical models for Tma calculation that accommodate common forms of variation in DSF curves, including the number of transitions, the presence of high initial signal, and temperature-dependent signal decay. When tested these models against DSFbase, an open-source database of 6235 raw, real-life DSF curves, these models outperformed the existing standard approaches of sigmoid fitting and maximum of the first derivative. To make these models accessible, we created an open-source software and website, DSFworld (https://gestwickilab.shinyapps.io/dsfworld/). In addition to these improved fitting capabilities, DSFworld also includes features that overcome the practical limitations of many analysis workflows, including automatic reformatting of raw data exported from common qPCR instruments, labeling of data based on experimental variables, and flexible interactive plotting. We hope that DSFworld will enable more streamlined and accurate calculation of Tma values for DSF experiments.

Search for heavy dark matter from dwarf spheroidal galaxies: leveraging cascades and subhalo models

The Fermi Large Area Telescope (Fermi-LAT) has been widely used to search for Weakly Interacting Massive Particle (WIMP) dark matter signals due to its unparalleled sensitivity in the GeV energy band. The leading constraints for WIMP by Fermi-LAT are obtained from the analyses of dwarf spheroidal galaxies within the Local Group, which are compelling targets for dark matter searches due to their relatively low astrophysical backgrounds and high dark matter content. In the meantime, the search for heavy dark matter with masses above TeV remains a compelling and relatively unexplored frontier. In this study, we utilize 14-year Fermi-LAT data to search for dark matter annihilation and decay signals in 8 classical dwarf spheroidal galaxies within the Local Group. We consider secondary emission caused by electromagnetic cascades of prompt gamma rays and electrons/positrons from dark matter, which enables us to extend the search with Fermi-LAT to heavier dark matter cases. We also update the dark matter subhalo model with informative priors respecting the fact that they reside in subhalos of our Milky Way halo aiming to enhance the robustness of our results. We place constraints on dark matter annihilation cross section and decay lifetime for dark matter masses ranging from 103 GeV to 1011 GeV, where our limits are more stringent than those obtained by many other high-energy gamma-ray instruments.

Image denoising and model-independent parameterization for IVIM MRI

Objective. To improve intravoxel incoherent motion imaging (IVIM) magnetic resonance Imaging quality using a new image denoising technique and model-independent parameterization of the signal versus b-value curve. Approach. IVIM images were acquired for 13 head-and-neck patients prior to radiotherapy. Post-radiotherapy scans were also acquired for five of these patients. Images were denoised prior to parameter fitting using neural blind deconvolution, a method of solving the ill-posed mathematical problem of blind deconvolution using neural networks. The signal decay curve was then quantified in terms of several area under the curve (AUC) parameters. Improvements in image quality were assessed using blind image quality metrics, total variation (TV), and the correlations between parameter changes in parotid glands with radiotherapy dose levels. The validity of blur kernel predictions was assessed by the testing the method's ability to recover artificial ‘pseudokernels’. AUC parameters were compared with monoexponential, biexponential, and triexponential model parameters in terms of their correlations with dose, contrast-to-noise (CNR) around parotid glands, and relative importance via principal component analysis. Main results. Image denoising improved blind image quality metrics, smoothed the signal versus b-value curve, and strengthened correlations between IVIM parameters and dose levels. Image TV was reduced and parameter CNRs generally increased following denoising. AUC parameters were more correlated with dose and had higher relative importance than exponential model parameters. Significance. IVIM parameters have high variability in the literature and perfusion-related parameters are difficult to interpret. Describing the signal versus b-value curve with model-independent parameters like the AUC and preprocessing images with denoising techniques could potentially benefit IVIM image parameterization in terms of reproducibility and functional utility.

Fast Structural Dynamics in Concentrated HCl Solutions: From Proton Hopping to the Bulk Viscosity.

Concentrated acid solutions, particularly HCl, have been studied extensively to examine the proton hopping and infrared spectral signatures of hydronium ions. Much less attention has been given to the structural dynamics of concentrated HCl solutions. Here, we apply optical heterodyne detected-optical Kerr effect (OHD-OKE) measurements to examine HCl concentration-dependent dynamics from moderate (0.8 m) to very high (15.5 m) concentrations and compare the results to the dynamics of NaCl solutions, as Na+ is similar in size to the hydronium cation. Both HCl and NaCl OHD-OKE signals decay as triexponentials at all concentrations, in contrast to pure water, which decays as a biexponential. Two remarkable features of the HCl dynamics are the following: (1) the bulk viscosity is linearly related to the slowest decay constant, t3, and (2) the concentration-dependent proton hopping times, determined by ab initio MD simulations and 2D IR chemical exchange experiments, both obtained from the literature, fall on the same line as the slowest structural dynamics relaxation time, t3, within experimental error. The structural dynamics of hydronium/chloride/water clusters, with relaxation times t3, are responsible for the concentration dependence of microscopic property of proton hopping and the macroscopic bulk viscosity. The slowest time constant (t3), which does not have a counterpart in pure water, is 3 ps at 0.8 m and increases by a factor of ∼2 by 15.5 m. The two fastest HCl decay constants, t1 and t2, are similar to those of pure water and increase mildly with the concentration.

Thermoluminescence dosimetry and microstructural characteristics of gamma-irradiated natural flake graphite

Thermoluminescence (TL) and microstructural analysis were conducted on natural flake graphite (NFG) to assess its suitability for radiotherapeutic x-ray dose measurements. The investigations encompassed the examination of TL glow curves, linearity, sensitivity, signal decay, and repeatability. NFG samples were exposed to 60Co gamma radiation doses ranging from 2 Gy to 20 Gy. The microstructure of the irradiated NFG was probed using a 532 nm laser Raman spectrometer. Promisingly, the NFG exhibited remarkable characteristics, including a moderately higher response to dose (R2 of about 96%), increased sensitivity at lower doses, and good repeatability (∼4%). Nevertheless, its fading rate reached about 80% after 14 days of irradiation. Additionally, the NFG intensity ratios of defect (D) to graphite (G), denoted as ID/IG, closely mirrored the oscillatory pattern observed in 50 μm thick graphite sheets and were approximately 1.6 times lower than those of similar graphite sheets with comparable carbon content (about 98% carbon). These findings suggest that NFG holds potential for the development of an affordable, non-hygroscopic, and tissue-equivalent TL dosimeter, with possible applications in the medical field.

Assessment of Left Lung Remodeling With Magnetic Resonance Imaging in a Murine Model Following Exposure to Douglas Fir Smoke.

Wildland firefighters (WLFFs) experience lung function decline due to occupational exposure to fire smoke. WLFFs typically do not wear respiratory personal protective equipment, and if they do, it is a simple bandana, which is not effective at filtering smoke. To pinpoint the biological underpinnings of abnormal respiratory function following 3-7 years of WLFF service, we exposed mice to Douglas fir smoke (DFS) over 8 weeks. Following exposure, we assessed changes in lung structure through Magnetic Resonance Imaging (MRI) and histological analysis, which was supported by immunohistochemistry staining. With MRI, we found that the signal decay time, T2*, from ultrashort echo time (UTE) images was significantly shorter in mice exposed to DFS compared to air controls. In addition, the variation in T2* was more heterogeneously distributed throughout the left lung in DFS-exposed mice, compared to air controls. As confirmed by histological analysis, shorter T2* was caused by larger parenchyma airspace sizes and not fibrotic remodeling. Destruction of the alveolar spaces was likely due to inflammation, as measured by an influx of CD68+ macrophages and destruction due to enhanced neutrophil elastase. In addition, measurements of airspace dimensions from histology were more heterogeneously distributed throughout the lung, corroborating the enhanced relative dispersion of T2*. Findings from this study suggest that the decline in lung function observed in WLFFs may be due to emphysema-like changes in the lung, which can be quantified with MRI.

Gauge and scalar boson mediated proton decay in a predictive SU(5) GUT model

We assess proton decay signatures in the simplest viable SU(5) model with regard to constraints on parameters governing the Standard Model fermion mass spectrum. Experimental signals for all eight two-body proton decay processes result from exchange of two gauge bosons, a single scalar leptoquark, or their combination. Consequently, it enables us to delve into an in-depth anatomy of proton decay modes and anticipate future signatures. Our findings dictate that observing a proton decay into p→π0e+ indicates gauge boson mediation, with the potential for observation of p→η0e+ mode. Alternatively, if decay is through the p→K+ν¯ process, it is mediated by a scalar leptoquark, possibly allowing the observation of p→π0μ+. Detection of both p→π0e+ and p→K+ν¯ could enhance p→π0μ+ through constructive interference. The model predicts inaccessibility of p→π+ν¯, p→η0μ+, p→K0e+, and p→K0μ+, regardless of the dominant mediation type, in the coming decades. In summary, through a comprehensive analysis of proton decay signals, gauge coupling unification, and fermion masses and mixing, we both accurately and precisely constrain the parameter space of the SU(5) model in question. Published by the American Physical Society 2024

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak.

Traditionally, mass spectrometry (MS) output is the ion abundance plotted versus the ionic mass-to-charge ratio m/z. While employing only commercially available equipment, Charge Determination Analysis (CHARDA) adds a third dimension to MS, estimating for individual peaks their charge states z starting from z = 1 and color coding z in m/z spectra. CHARDA combines the analysis of ion signal decay rates in the time-domain data (transients) in Fourier transform (FT) MS with the interrogation of mass defects (fractional mass) of biopolymers. Being applied to individual isotopic peaks in a complex protein tandem (MS/MS) data set, CHARDA aids peptide mass spectra interpretation by facilitating charge-state deconvolution of large ionic species in crowded regions, estimating z even in the absence of an isotopic distribution (e.g., for monoisotopic mass spectra). CHARDA is fast, robust, and consistent with conventional FTMS and FTMS/MS data acquisition procedures. An effective charge-state resolution Rz ≥ 6 is obtained with the potential for further improvements.