Standard Model Research Articles

Certificateless Aggregate Signature Scheme With Security Proofs in the Standard Model Suitable for Internet of Vehicles

Certificateless Aggregate Signature Scheme With Security Proofs in the Standard Model Suitable for Internet of Vehicles

Enhancing Hydraulic Performance and Discharge Efficiency of a Type-C Piano Key Weir Through Stage Incorporation

Weirs are hydraulic constructions typically employed in dam spillways and channel control structures. The shape and size of the crest will determine whether the weir is linear or non-linear. Of the two types, non-linear weirs are often selected due to their ability to allow different discharge levels at the minimal heads. A recently introduced variation of the non-linear kind is the piano key weir. This research undertakes a comprehensive analysis of the hydraulic functionality of the type-C piano key weir under conditions of free flow. The research methodology involved modifying the models by adding stages to the sides and monitoring the effect on the efficacy of discharge, represented by the discharge coefficient. The study further extrapolated formulae linking critical variables to the discharge coefficient, using dimensional analysis and SPSS software. The findings of this study revealed that the introduction of stages significantly bolstered the discharge coefficient in the altered models compared to the standard model. This enhancement was reflected in a 6% and 11% ascent with length expansion of the stages and a 6% and 8% rise with height increase of the stages. Additionally, the model's performance was augmented with a drop in the total head ratio

Quantitative Total-Body Imaging of Blood Flow with High Temporal Resolution Early Dynamic 18F-Fluorodeoxyglucose PET Kinetic Modeling.

The first two minutes of dynamic PET scans were reconstructed at high temporal resolution (60×1 s, 30×2 s) to resolve the rapid passage of the radiotracer through blood vessels. In contrast to existing methods that use blood-to-tissue transport rate ( ) as a surrogate of blood flow, our method directly estimates blood flow using a distributed kinetic model (adiabatic approximation to the tissue homogeneity model; AATH). To validate our 18F-FDG measurements of blood flow against a flow radiotracer, we analyzed total-body dynamic PET images of six human participants scanned with both 18F-FDG and 11C-butanol. An additional thirty-four total-body dynamic 18F-FDG PET scans of healthy participants were analyzed for comparison against literature blood flow ranges. Regional blood flow was estimated across the body and total-body parametric imaging of blood flow was conducted for visual assessment. AATH and standard compartment model fitting was compared by the Akaike Information Criterion at different temporal resolutions. 18F-FDG blood flow was in quantitative agreement with flow measured from 11C-butanol across same-subject regional measurements (Pearson R=0.955, p<0.001; linear regression y=0.973x-0.012), which was visually corroborated by total-body blood flow parametric imaging. Our method resolved a wide range of blood flow values across the body in broad agreement with literature ranges (e.g., healthy cohort average: 0.51±0.12 ml/min/cm3 in the cerebral cortex and 2.03±0.64 ml/min/cm3 in the lungs, respectively). High temporal resolution (1 to 2 s) was critical to enabling AATH modeling over standard compartment modeling. Total-body blood flow imaging was feasible using early-dynamic 18F-FDG PET with high-temporal resolution kinetic modeling. Combined with standard 18F-FDG PET methods, this method may enable efficient single-tracer flow-metabolism imaging, with numerous research and clinical applications in oncology, cardiovascular disease, pain medicine, and neuroscience.

New Physics in the 3-3-1 models

The fundamental basics of the Standard Model such as local gauge symmetry and mass generation via the Higgs mechanism are widely confirmed by current experimental data. However, some problems such as neutrino masses, dark matter, baryon asymmetry of Universe have clearly indicated that the Standard Model cannot be the ultimate theory of Nature. To surpass the mentioned puzzles, many extensions of the Standard Model (called beyond Standard Model) have been proposed. Among beyond Standard Models, the 3-3-1 models have some intriguing features and they get wide attention. The pioneer models develop in some directions. In this paper, some versions of the 3-3-1 models and new consequences are presented.

The consequence of higher-order curvature-based constraints on [formula omitted] gravity

In this investigation, we perform an observational statistical analysis in the theory of f(R,Lm) gravity. The proposed theoretical model is based on the Ricci scalar’s non-linear contribution. We use a distinct parametrization for the deceleration parameter and constrain the model parameters by using various observational data. To determine the best-fit model for the cosmological parameters, we use different observational datasets such as the Hubble Space Telescope, the Pantheon Supernova Survey, the Gold dataset, the Gamma-Ray Burst (GRB), and the Baryon Acoustic Oscillations (BAO). Furthermore, we study the late-time cosmic evolution of the Universe in detail and examine the implications of the constraint values on cosmological parameters. Additionally, we conduct a thorough comparison with the standard cosmological model ΛCDM and other standard models obtained by Odintsov et al. (2024); Odintsov et al. (2023) to examine the validity of our proposed model in the low-redshift regimes. Finally, we find that the proposed model encapsulates an intriguing transition from early deceleration at high redshift to acceleration at low redshift, a quintessence dark energy scenario, and convergence towards the well-established ΛCDM model in late-time Universe’s evolution.

Single production of vectorlike quarks with charge 5/3 at the 14 TeV LHC

In a framework of the Standard Model (SM) simply extended by an SU(2) doublet (X,T) including a vectorlike X-quark (VLQ-X), with electric charge |QX|=5/3, we investigate the single production of the VLQ-X induced by the couplings between the VLQ-X with the first and the third generation quarks at the Large Hadron Collider (LHC) operating at s=14 TeV. The signal is searched in events including same-sign dileptons (electrons or muons), one b-tagged jet and missing energy, where the X quark is assumed to decay into a top quark and a W boson, both decaying leptonically. After a rapid simulation of signal and background events, the 95% CL exclusion limits and the 5σ discovery reach are respectively obtained at the LHC with an integrated luminosity of 300 and 3000 fb−1, respectively.

Fire after earthquake assessment of 3D reinforced concrete structures

Despite that, an earthquake's occurrence can lead to dramatic effects with significant damage in urban areas, including human and material losses. Fire after an earthquake amplifies the overall impact and becomes a catastrophic event. Most constructions in Algeria are made of reinforced concrete, and current regulations overlook fires after earthquakes. Structural designs are inadequate to handle such events. This study aims to investigate the behaviour of 3D reinforced concrete frames, as part of a residential building, designed according to internal codes, CBA93 and RPA99 v2003. This 3D RC structure is exposed to several load levels of its vertical load bearing capacity. The structural system is assumed to undergo seismic scenarios characterised by various levels of story drift and damage level types. The structure is then exposed to the standard fire ISO834 model. Numerical investigations are carried out for thermo-mechanical analysis using the finite element software ANSYS, taking into account geometric and material non-linearities. Results highlight the significant impact of vertical loads, story drifts, fire scenarios, and structural damage on a building's response to fire following an earthquake. These factors collectively influence the collapse probabilities, underlining the importance of holistic risk assessment in structural design.

Performance comparison of alternative volatility models applied to economic indexes: the role of asymmetric effects

ABSTRACT This article examines the empirical relationship between economic indexes – namely the industrial production and the consumer confidence – and their volatility by using the United States data over the periods 1919–2023 and 1960–2023, respectively. To address this topic, several GARCH-family models including volatility feedback and the asymmetric effects are estimated. We find that (i) the industrial production index exhibits asymmetric effects, with significant fitting performance over the standard GARCH model; (ii) the inclusion of t -distributed innovations in the error term improves the fitting performance of the competing models against their counterparts with a normal distribution assumption; (iii) both models tested for the consumer confidence index exhibit similar performance to fit with the data; (iv) by excluding the months during and after the COVID-19 pandemics and the Russia–Ukraine conflict, it leads to the same results and conclusions for both economic indexes. Conditional heteroscedasticity, economic growth, GARCH models, asymmetric effects, volatility feedback

Delayed kernels for longitudinal survival analysis and dynamic prediction.

Predicting patient survival probabilities based on observed covariates is an important assessment in clinical practice. These patient-specific covariates are often measured over multiple follow-up appointments. It is then of interest to predict survival based on the history of these longitudinal measurements, and to update predictions as more observations become available. The standard approaches to these so-called 'dynamic prediction' assessments are joint models and landmark analysis. Joint models involve high-dimensional parameterizations, and their computational complexity often prohibits including multiple longitudinal covariates. Landmark analysis is simpler, but discards a proportion of the available data at each 'landmark time'. In this work, we propose a 'delayed kernel' approach to dynamic prediction that sits somewhere in between the two standard methods in terms of complexity. By conditioning hazard rates directly on the covariate measurements over the observation time frame, we define a model that takes into account the full history of covariate measurements but is more practical and parsimonious than joint modelling. Time-dependent association kernels describe the impact of covariate changes at earlier times on the patient's hazard rate at later times. Under the constraints that our model (a) reduces to the standard Cox model for time-independent covariates, and (b) contains the instantaneous Cox model as a special case, we derive two natural kernel parameterizations. Upon application to three clinical data sets, we find that the predictive accuracy of the delayed kernel approach is comparable to that of the two existing standard methods.

Smooth reheating and dark matter via non-Abelian gauge theory

We demonstrate how a dark sector can provide a crucial link between a vacuum-dominated early universe and the later radiation-dominated epoch. As an example, we consider a feeble axion-like coupling of dark non-Abelian gauge fields with a single inflaton. In this scenario, a dark heat bath emerges at the end of inflation. As the dark sector cools down, its gauge fields confine into composite glueball states. The reheating of the visible sector is realized through portal interactions. After confinement, discrete symmetries protect part of the glueball states that form relic dark matter, while the others keep decaying into Standard Model degrees of freedom. The dark relic abundance depends mostly on the departure from equilibrium dynamics after the phase transition, constraining the confinement scale of the dark sector. Moreover, indirect detection and Big-Bang nucleosynthesis set bounds on the scale of portal interactions. We show that in a narrow but non-vanishing region of the parameter space, the correct dark matter abundance and sufficient reheating temperature are simultaneously reached.

Probing new physics at the LHC and future colliders: SMEFT and beyond

In this talk, I review our progresses on probing new physics at the LHC and future colliders by using the Standard Model Effective Field Theory (SMEFT) and beyond. This includes to probe new physics effects in the Higgs boson couplings via leading dimension-6 operators and in the neutral triple gauge couplings (nTGCs) via leading dimension-8 operators. I also discuss the probe of Higgs self-couplings involving the SM Higgs-boson-pair plus a new heavy Higgs boson of the extended Higgs sector via the resonant diHiggs production channels.

Temperature- and gate voltage-dependent I–V modeling of GaN HEMTs based on ASM-HEMT

Abstract In this paper, a temperature and gate voltage dependent current-voltage (I-V) model for Gallium nitride (GaN) high electron mobility transistors (HEMTs) devices is studied. In order to help researchers and designers simulate devices in the absence of experimental data and improve parameter extraction efficiency, the temperature and gate voltage dependence of mobility are discussed and incorporated into the proposed model which is revised from the standard advanced SPICE model (ASM) for GaN HEMTs. The mobility variations with gate voltage from -2 V to 6 V and temperature from 10 K to 1000 K are analyzed. The simulation results of our model are compared with the standard ASM-HEMT model, and the output and transfer characteristics of the device from 270 K to 420 K are simulated. Thereby, our model may simulate various applications of GaN HEMTs at different gate voltages and temperatures in the early stages of design and research.

A common framework for fermion mass hierarchy, leptogenesis and dark matter

In this work, we explore an extension of the Standard Model designed to elucidate the fermion mass hierarchy, account for the dark matter relic abundance, and explain the observed matter-antimatter asymmetry in the universe. Beyond the Standard Model particle content, our model introduces additional scalars and fermions. Notably, the light active neutrinos and the first two generations of charged fermions acquire masses at the one-loop level. The model accommodates successful low-scale leptogenesis, permitting the mass of the decaying heavy right-handed neutrino to be as low as 10 TeV. We conduct a detailed analysis of the dark matter phenomenology and explore various interesting phenomenological implications. These include charged lepton flavor violation, muon and electron anomalous magnetic moments, constraints arising from electroweak precision observables, and implications for collider experiments.

SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences

The rapid growth of earthquake catalogs, driven by machine learning-based phase picking and denser seismic networks, calls for the application of a broader range of models to determine whether the new data enhances earthquake forecasting capabilities. Additionally, this growth demands that existing forecasting models efficiently scale to handle the increased data volume. Approximate inference methods such as inlabru, which is based on the Integrated nested Laplace approximation, offer improved computational efficiencies and the ability to perform inference on more complex point-process models compared to traditional MCMC approaches. We present SB-ETAS: a simulation based inference procedure for the epidemic-type aftershock sequence (ETAS) model. This approximate Bayesian method uses sequential neural posterior estimation (SNPE) to learn posterior distributions from simulations, rather than typical MCMC sampling using the likelihood. On synthetic earthquake catalogs, SB-ETAS provides better coverage of ETAS posterior distributions compared with inlabru. Furthermore, we demonstrate that using a simulation based procedure for inference improves the scalability from O(n2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {O}(n^2)$$\\end{document} to O(nlogn)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {O}(n\\log n)$$\\end{document}. This makes it feasible to fit to very large earthquake catalogs, such as one for Southern California dating back to 1981. SB-ETAS can find Bayesian estimates of ETAS parameters for this catalog in less than 10 h on a standard laptop, a task that would have taken over 2 weeks using MCMC. Beyond the standard ETAS model, this simulation based framework allows earthquake modellers to define and infer parameters for much more complex models by removing the need to define a likelihood function.

Diagnostic approaches for interacting generalized holographic Ricci dark energy models

In this paper, we present an analytical solution for the interacting generalized holographic dark energy model, assuming a linear interaction rate between dark energy and dark matter. We determine the equation of state parameter, the generalized holographic Ricci dark energy density, the matter density, and the deceleration parameter. By analyzing the behavior of these cosmological parameters, we demonstrate that our model aligns with recent observations and reproduces the late-time accelerated expansion of the Universe. To compare our model with the ΛCDM model, we use various diagnostic tools including statefinder, Om(z)-diagnostic, statefinder hierarchy, growth rate analysis, and ωH-ωH′ plane. We also analyze the stability of the model by examining the speed of sound. These methods show that the dynamics of the Universe remain very close to that of the standard cosmological model.

Reopening the Z portal with semi-annihilations

In one-component dark matter (DM) scenarios is commonly assumed that a scalar weakly interacting massive particle must either be part of an SU(2)L multiplet with zero hypercharge or have suppressed vector interactions with the Z-gauge boson to circumvent stringent direct detection (DD) bounds. In this work, we demonstrate that multicomponent scenarios with a dark scalar doublet exhibiting vectorlike interactions with the Z boson are also compatible with bounds arising from DD searches. Specifically, we consider a simple extension of the Standard Model wherein the dark sector comprises a doublet and a complex singlet ϕ, both charged under a Z6 symmetry. We find that semi-annihilation processes drastically reduce the relic abundance of the neutral component of the doublet, H0, sufficiently attenuating the effects of its large Z-mediated elastic scattering cross-section with nucleons to satisfy the DD constraints. Although the contribution of H0 to the total relic abundance is nearly negligible, with ϕ dominating, both dark matter components are expected to be detectable in ongoing and future DD experiments. The viability of the model is tested against several theoretical and experimental constraints, resulting in a parameter space featuring a nondegenerate mass spectrum at the electroweak scale. Published by the American Physical Society 2024

The correlation between dip width and peak flux in Cir X-1

In this work we analyzed the long-term X-ray variation of Cir X-1 and its spectra. The dip width and the peak flux after periastron are obtained. Our findings show a negative correlation between the dip width and the peak flux. A new scenario is introduced to explain the correlation. The disk height is higher at a larger radius in the standard model. When the neutron star (NS) moves away from periastron, the contraction of the equipotential surface causes the height of the outer disk to increase significantly. It blocks the X-ray emission near the NS. Subsequently, the height of the outer disk gradually decreases due to the viscosity. The viscous timescale is inversely proportional to the height of the disk, and the height of the outer disk is proportional to the mass transferred from the companion near periastron, thus the peak flux. Consequently, the duration of the obscuring, corresponding to the dip width, is inversely proportional to the peak flux. Moreover, we introduce a new ephemeris MJD (N) = 43075.0+16.5843N-4.778 N^2$ based on the dip-in phases (ingress phase of the dip).

Probing electroweak phase transition in extended singlet scalar model with resonant HH production in bbZZ channel using parameterized machine learning

In this paper, a collider signature of a heavy Higgs boson at 14 TeV HL-LHC is studied, where the heavy Higgs boson decays into a pair of standard model (SM) Higgs boson, which further decays to bbZZ state and subsequently to bb ℓ + ℓ − ν ℓ ν ℓ final state. To study this, we consider singlet scalar extension of the SM and select the parameter space and mass of the heavy Higgs boson such that it prefers a strong first-order electroweak phase transition (EWPT). The study is done following the bbZZ analysis of CMS Collaboration and further using parameterized machine learning for final discrimination which simplifies the training process along with an improved discrimination between signal and background over the range of benchmark points. Despite the lower branching fraction, this channel can be a potential probe of the EWPT with the data sets collected by the CMS and ATLAS experiments at the 14 TeV HL-LHC with 3 ab−1 of integrated luminosity and a production of resonant di-Higgs signal can be potentially discovered up to 490 GeV of resonance mass.

Feasibility of structuring electronic health record data to facilitate real-world data research: ICAREdata methods applied to multicenter cancer clinical trials.

The use of electronic health record (EHR) data for research is limited by a lack of structure and a standard data model. The objective of the ICAREdata (Integrating Clinical Trials and Real-World Endpoints Data) project was to structure key research data elements in EHRs using a minimal Common Oncology Data Elements (mCODE) data model to extract and transmit data. The ICAREdata project captured two EHR data elements essential to clinical trials: cancer disease status and treatment plan change. The project was implemented in clinical sites participating in Alliance for Clinical Trials in Oncology trials. Data were extracted from EHRs and sent by secure Fast Healthcare Interoperability Resource messaging (a standard for exchanging EHRs) to a database. Selected elements were compared with corresponding data from the trial's electronic data capture (EDC) system, Medidata Rave. By December 2023, data were extracted and transmitted from 10 sites for 35 patients, involving 367 clinical encounters across 15 clinical trials. Data through March 2023 demonstrated that concordance for the elements treatment plan change and cancer disease status was 79% and 34%, respectively. When disease evaluation was reported by both EHR and EDC (n=15), there was 87% agreement on cancer disease status. Documentation, extraction, and aggregation of structured data elements in EHRs using mCODE and ICAREdata methods is feasible in multi-institutional cancer clinical trials. EDC as a reference data setallowed assessment of the completeness of EHR data capture. Future initiatives will focus on elements with shared definitions in clinical and research environments and efficient workflows. Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming. ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records.

Economic uncertainty and time-varying return predictability

We propose a predictive regression for stock returns in which the parameter variation is driven by economic uncertainty. A locally weighted least squares approach is developed to obtain parameter estimates which are used to generate forecasts of returns for the S&P 500 index. Our results indicate that the time-varying parameter model accounting for the role of economic uncertainty (TVP-EU) significantly improves upon the standard ordinary least squares model and the historical average benchmark.