Standard Model Research Articles

Horizontal ecological compensation standards based on ecosystem services flow

The determination of compensation standards is the core of horizontal ecological compensation (HEC). However, existing studies focused on the ecological value stocks of ecosystem services (ESs) within an administrative area but ignored their spatial mobility when determining standards, so the HEC policies had difficulty in achieving the desired goals. This study takes the upper-middle reaches of the Yangtze River as the study area, adopts the gravity model to calculate the ecosystem services flow (ESF) in the eight provinces of the area, and formulates a HEC standard accounting model to determine the compensation standards. The results show that there are inhomogeneous distributions of ESs supply and demand from 2005 to 2020. The ESs supply tends to decline, then increase, whereas the demand continuously increases. The total ESF volume from the ESs-providing areas (ESPAs) to the ESs-benefiting areas (ESBAs) first increases and then decreases. In 2020, Tibet, Qinghai, Chongqing, and Hunan are the ESPAs, with Qinghai obtaining the highest compensation standard of 308.56 million CNY and accounting for more than 50% of the total. The ESBAs include Sichuan, Yunnan, Hubei, and Jiangxi, among which Sichuan is the main source of HEC funds with payments of 375.79 million CNY. This study can provide theoretical references for improving HEC rationality, as well as resolving the contradictions between environmental protection costs and benefits externalities for large-scale regions

Geo-spatial epidemiology of gallbladder cancer in Bihar, India

Recently, a substantial increase in gallbladder cancer (GBC) cases has been reported in Bihar, India. The region's groundwater can naturally contain harmful concentrations of arsenic, which appears to be epidemiologically linked to the unusually high incidence. However, the root causes remain largely unexplored. Recent findings of uranium in the state's groundwater may also have associations. This study investigates the geo-spatial epidemiology of GBC in Bihar, India—with a focus on the correlation between environmental carcinogens, particularly arsenic and uranium in groundwater, and the incidence of GBC. Utilizing data from 8460 GBC patients' registration records over an 11-year period at a single health center, the research employs Semi-parametric Geographically Weighted Poisson Regression (S-GWPR) to account for non-stationarity associations and explores significant factors contributing to GBC prevalence at a subdistrict level. The S-GWPR model outperformed the standard Poisson regression model. The estimates suggest that arsenic and uranium concentrations in groundwater did not present significant associations; however, this could be due to the lower resolution of this data at the district level, necessitating higher resolution data for accurate estimates. Other socio-environmental factors included demonstrated significant regional heterogeneity in their association with GBC prevalence. Notably, each 1 % increase in the coverage of well- and canal-irrigated areas is associated with a maximum of 3.0 % and 5.2 % rise in the GBC incidence rate, respectively, likely attributable to carcinogen exposure from irrigation water. Moreover, distance to the health center and domestic electricity connections appear to influence the number of reported GBC cases. The latter suggests that access to electricity might have facilitated the use of groundwater pumps—increasing exposure to carcinogens. The results underscore the necessity for targeted health policies and interventions based on fine-resolution spatial analysis, as well as ongoing environmental monitoring and research to better understand the multifaceted risk factors contributing to GBC.

Liner shipping network vulnerability to component disruptions: A China-Europe container flow analysis

This study conducts a vulnerability analysis of the China-Europe liner shipping network, including all relevant liner shipping services and China Railway Express services. The standard multicommodity network flow model is extended to assess network vulnerability and the relative importance of ports and services by simulating container flow redistribution in various disruption scenarios. The results show the network is highly resilient to both individual port disruptions and individual service disruptions. Additionally, the distinct shipping network structures of the three shipping alliances result in varying degrees of vulnerability, highlighting the significance of diversified market suppliers in enhancing the overall network resilience. Specifically, the Ocean Alliance is vital in facilitating China-Europe trade, especially along the Mediterranean route, and is more resilient to individual port disruptions.

A Multivariate Mixture Regression Model for Constrained Responses

Compositional data are vectors typically representing proportions of a whole, that is, those whose elements are strictly positive and subject to a unit-sum constraint. The increasing number of fields where this type of data arises makes the development of proper statistical tools an important issue. From a regression perspective, whenever the multivariate response is a compositional vector, a proper model that accounts for the unit-sum constraint is the well-established Dirichlet regression model. However, there are significant drawbacks mainly due to the limited flexibility of the Dirichlet distribution. The aim of this contribution is to introduce a new multivariate regression model for constrained responses, that is based on the extended flexible Dirichlet distribution (which is a structured mixture with Dirichlet distributed components). The new model is obtained by adopting a novel reparameterization which allows for, among other things, the presence of suitably designed cluster-specific regression patterns. It is shown to provide considerably greater flexibility and better performance than the standard Dirichlet regression model. In particular, from theoretical analysis, intensive simulation studies in many challenging scenarios, as well as from a real data application, it emerges that the new regression model can handle several issues affecting the Dirichlet regression, such as the presence of outliers, latent groups, multi-modality, and positive correlations.

Probing the four-fermion operators via the transverse double spin asymmetry at the Electron-Ion Collider

The chirality-flipping operators of light fermions are currently poorly constrained by experimental analyses due to the lack of interference with standard model (SM) amplitudes in traditional observables. In this work, we propose to investigate the semileptonic scalar and tensor four-fermion operators of electron and quarks through the transverse double spin asymmetry (DSA) at Electron-Ion Collider, where both the electron and proton beams could be highly transversely polarized. Due to the chirality-flipping nature of these operators, we demonstrate that their interference with the SM results in an unsuppressed contribution to the DSA, and could lead to nontrivial azimuthal cos2ϕ and sin2ϕ distributions that are linearly dependent on their Wilson coefficients. This new method has the potential to significantly improve the current constraints on these scalar and tensor four-fermion operators without relying on theoretical assumptions about other types of new physics effects, particularly for the tensor-type operator of the u quark. Additionally, our findings indicate that both the real and imaginary parts of these operators can be simultaneously constrained and offer a new opportunity for probing potential CP-violation effects. However, it is important to note that these results would be sensitive to the quark transversity distributions, which are currently poorly constrained by the experimental data, but could be significantly improved at the upcoming Electron-Ion Collider. Therefore, our work opens up a new avenue to utilize this new spin asymmetry for exploring the new physics effects from the scalar/tensor four-fermion operators. Published by the American Physical Society 2024

Gauge invariance, gauge field quantization, and renormalization in autoregularization

Autoregularization, a new divergence-free framework for calculating scattering amplitudes, uses a Lorentz-invariant scale harvested from the kinematics of a scattering process to regularize the amplitude of the process [N. Prabhu, .]. Preliminary validation studies show that autoregularization’s predictions are in good agreement with experimental data—across several scattering processes and a wide range of energy scales. Further, tree-level calculation of the vacuum energy density of the free fields in the Standard Model, using autoregularization, is shown to yield a value that is smaller than the current estimate of the cosmic critical density. In this paper, we prove that the scattering amplitudes in QED, calculated using autoregularization, are gauge invariant. Our proof, which is valid both for autoregularization and current theory, is stronger in that it shows the amplitude of every Feynman diagram is gauge invariant in contrast to previous proofs, which establish gauge invariance only for sum of amplitudes of Feynman diagrams of a process. Next, we show that—unlike in the standard quantization framework, which requires modification of both the quantization framework itself as well as the Lagrangian in order to quantize gauge fields in covariant gauge—in autoregularization the gauge field in QED can be quantized, in covariant gauge, without modifying the standard quantization procedure or the Lagrangian and without introducing the ghost field. Finally, we illustrate renormalization based on autoregularization up to 1-loop in φ4 theory. Since perturbative corrections are finite in autoregularization, the counterterms are not designed to remove divergences but to implement renormalization prescriptions at every order of perturbation. We also derive the renormalization group equation (RGE). Unlike in some regularization schemes (such as dimensional regularization), in which the physical meaning of the fictitious scale introduced by regularization is unclear, in autoregularization the scale in RGE has a transparent physical meaning—it is the Lorentz-invariant kinematic scale of the scattering process of interest. The increasing simplifications resulting within autoregularization and the agreement between its predictions and experimental data, together with the underlying thermodynamic argument, which shows that the framework is essential for a complete description of quantum fields, all converge to suggest that autoregularization provides the proper framework for the description of quantum fields. Published by the American Physical Society 2024

Spontaneous breaking of the SO(2N) symmetry in the Gross-Neveu model

The canonical Gross-Neveu model for N two-component Dirac fermions in 2+1 dimensions suffers a continuous phase transition at a critical interaction gc1∼1/N at large N, at which its continuous symmetry SO(2N) is preserved and a discrete (Ising) symmetry becomes spontaneously broken. A recent mean-field calculation, however, points to an additional transition at a different critical gc2∼−Ngc1, at which SO(2N)→SO(N)×SO(N). To study the latter phase transition we rewrite the Gross-Neveu interaction g(ψ¯ψ)2 in terms of three different quartic terms for the single (L=1) 4N-component real (Majorana) fermion, and then extend the theory to L>1. This allows us to track the evolution of the fixed points of the renormalization group transformation starting from L≫1, where one can discern three distinct critical points which correspond to continuous phase transitions into (1) SO(2N)-singlet mass-order-parameter, (2) SO(2N)-symmetric-tensor mass-order-parameters, and (3) SO(2N)-adjoint nematic-order-parameters, down to L=1 value that is relevant to the standard Gross-Neveu model. Below the critical value of Lc(N)≈0.35N for N≫1 only the Gross-Neveu critical point (1) still implies a diverging susceptibility for its corresponding (SO(2N)-singlet) order parameter, whereas the two new critical points that existed at large L ultimately become equivalent to the Gaussian fixed point at L=1. We interpret this metamorphosis of the SO(2N)-symmetric-tensor fixed point from critical to spurious as an indication that the transition at gc2 in the original Gross-Neveu model is turned first-order by fluctuations. Published by the American Physical Society 2024

γ5 schemes and the interplay of SMEFT operators in the Higgs-gluon coupling

We calculate the four-top-quark operator contributions to Higgs production via gluon fusion in the Standard Model effective field theory. The four-top operators enter for the first time via two-loop diagrams. Owing to their chiral structure they contain γ5, so special care needs to be taken when using dimensional regularization for the loop integrals. We use two different schemes for the continuation of γ5 to D space-time dimensions in our calculations and present a mapping for the parameters in the two schemes. This generically leads to an interplay of different operators, such as four-top operators, chromomagnetic operators, or Yukawa-type operators at the loop level. We validate our results by examples of matching onto UV models. Published by the American Physical Society 2024

Continuous versus intermittent phototherapy in treatment of neonatal jaundice: a randomized controlled trial.

In this study, IPT was found to be at least as effective as CPT in reducing total serum bilirubin. Even though the duration of PT is shorter in IPT, the slower rate of rebound bilirubin, shorter hospital stays and lower incidence of side effects indicated that intermittent phototherapy is superior to continuous phototherapy. Choosing IPT over CPT is a more rational approach in neonatal jaundice. gov Identifier: NCT06386731 (registered retrospectively on 23/04/2024) What is Known: • PT is common used in the treatment of neonatal jaundice. • There is no standard model of application for PT. • The IPT model is as effective as CPT. • Newborns are discharged faster with IPT.

Searching for gluon quartic gauge couplings at muon colliders using the autoencoder

One of the difficulties one has to face in the future phenomenological studies of new physics (NP), is the need to deal with increasing amounts of data. It is therefore increasingly important to improve the efficiency in the phenomenological study of NP. Whether it is the use of the Standard Model effective field theory (SMEFT), the use of machine learning (ML) algorithms, or the use of quantum computing, all are means of improving the efficiency. In this paper, we use a ML algorithm, the autoencoder (AE), to study the dimension-8 operators in the SMEFT which contribute to the gluon quartic gauge couplings (gQGCs) at muon colliders. The AE is one of the ML algorithms that has the potential to be accelerated by the quantum computing. It is found that the AE-based anomaly detection algorithm can be used as event selection strategy to study the gQGCs at the muon colliders, and is effective compared with traditional event selection strategies. Published by the American Physical Society 2024

Exploring nonstandard Hbb¯ interactions at future electron-proton colliders

In this paper, we use the charged-current Higgs boson production process at future electron-proton colliders, e−p→Hjνe, with the subsequent decay of the Higgs boson into a bb¯ pair, to probe the Standard Model effective field theory with dimension-six operators involving the Higgs boson and the bottom quark. The study is performed for two proposed future high-energy electron-proton colliders, the Large Hadron Electron Collider (LHeC) and the Future Circular Collider (FCC-he) at the center-of-mass energies of 1.3 TeV and 3.46 TeV, respectively. Constraints on the CP-even and CP-odd Hbb¯ couplings are derived by analyzing the simulated signal and background samples. A realistic detector simulation is performed and a multivariate technique using the gradient boosted decision trees algorithm is employed to discriminate the signal from background. Expected limits are obtained at 95% confidence level for the LHeC and FCC-he assuming the integrated luminosities of 1, 2 and 10 ab−1. We find that using 1 ab−1 of data, the CP-even and CP-odd Hbb¯ couplings can be constrained with accuracies of the order of 10−3 and 10−2, respectively, and a significant region of the unprobed parameter space becomes accessible. Published by the American Physical Society 2024

Nanofluidic Platform for Studying the First-Order Phase Transitions in Superfluid Helium-3

AbstractThe symmetry-breaking first-order phase transition between superfluid phases $$^3$$ 3 He-A and $$^3$$ 3 He-B can be triggered extrinsically by ionising radiation or heterogeneous nucleation arising from the details of the sample cell construction. However, the role of potential homogeneous intrinsic nucleation mechanisms remains elusive. Discovering and resolving the intrinsic processes may have cosmological consequences, since an analogous first-order phase transition, and the production of gravitational waves, has been predicted for the very early stages of the expanding Universe in many extensions of the Standard Model of particle physics. Here we introduce a new approach for probing the phase transition in superfluid $$^3$$ 3 He. The setup consists of a novel stepped-height nanofluidic sample container with close to atomically smooth walls. The $$^3$$ 3 He is confined in five tiny nanofabricated volumes and assayed non-invasively by NMR. Tuning of the state of $$^3$$ 3 He by confinement is used to isolate each of these five volumes so that the phase transitions in them can occur independently and free from any obvious sources of heterogeneous nucleation. The small volumes also ensure that the transitions triggered by ionising radiation are strongly suppressed. Here we present the preliminary measurements using this setup, showing both strong supercooling of $$^3$$ 3 He-A and superheating of $$^3$$ 3 He-B, with stochastic processes dominating the phase transitions between the two. The objective is to study the nucleation as a function of temperature and pressure over the full phase diagram, to both better test the proposed extrinsic mechanisms and seek potential parallel intrinsic mechanisms.

Mössbauer study of iron oxide nanoparticles

AbstractMagnetic nanoparticles have recently attracted attention for biochemical and medical applications like drug delivery and hyperthermia for a variety of reasons with most important being their stability, chemical compatibility, and suitable magnetic properties like moderate specific mass magnetization. Cobalt ferrites are a well‐studied family of materials and the partial substitution of Fe3+ cations by rare earth (RE) ones may be used to tune the magnetic properties. In the present work pure and substituted Co ferrite nanoparticles with nominal stoichiometry CoFe2‐xRxO4 (R = Yb, Gd; x = 0.05, 0.1, 0.3) synthesized by the co‐precipitation method are studied with 57Fe Mössbauer spectroscopy in order to determine the incorporation of RE ions in the spinel lattice. The fitting procedure was based on the standard spinel model using two sextets for the octahedral and the tetrahedral coordinated positions of Fe atoms. All isomer shift values were found within the typical range of high spin ferric ions while quadrupole splitting values strongly suggest that there is a substitution preference; RE ions replace iron ones in octahedral sites. The inversion parameter was found to decrease with RE content (lowest value about 0.534 for CoFe1.90Yb0.10O4) and thermal treatment always results in changing the material towards normal spinel, while pure CoFe2O4 was inverse. Thermal treatment of substituted materials in ambient air at temperature range 1500‐1700 K for 12 hours increase crystallite size and changes the degree of inversion.This article is protected by copyright. All rights reserved.

Sedenion Algebra Model as an Extension of the Standard Model and Its Link to SU(5)

In the Standard Model, ad hoc hypotheses assume the existence of three generations of point-like leptons and quarks, which possess a point-like structure and follow the Dirac equation involving four anti-commutative matrices. In this work, we consider the sedenion hypercomplex algebra as an extension of the Standard Model and show its close link to SU(5), which is the underlying symmetry group for the grand unification theory (GUT). We first consider the direct-product quaternion model and the eight-element octonion algebra model. We show that neither the associative quaternion model nor the non-associative octonion model could generate three fermion generations. Instead, we show that the sedenion model, which contains three octonion sub-algebras, leads naturally to precisely three fermion generations. Moreover, we demonstrate the use of basis sedenion operators to construct twenty-four 5 × 5 generalized lambda matrices representing SU(5) generators, in analogy to the use of octonion basis operators to generate Gell-Mann’s eight 3 × 3 lambda-matrix generators for SU(3). Thus, we provide a link between the sedenion algebra and Georgi and Glashow’s SU(5) GUT model that unifies the electroweak and strong interactions for the Standard Model’s elementary particles, which obey SU(3)SU(2)U(1) symmetry.

Study on Vector Mediator Top-philic Dark Matter

Abstract We conducted a study on a simplified dark matter (DM) model that introduces a vector-like intermediate particle, facilitating exclusive interactions between DM and the top quark in the Standard Model (SM). The analysis focused on the relic density of Dirac-type fermion DM and highlighted the complementary role of direct detection (DD) in constraining the DM model. Notably, in instances when DM mass is small, the tree-level two-body annihilation process experiences suppression. In such scenarios, the contributions of the three-body process and the one-loop process dominate the relic abundance. Concerning DD, calculations were performed for the two-loop contribution to the DM-gluon interaction, yielding the corresponding spin-independent scattering cross-section.

Exploring and Analyzing a Hybrid PAPR Reduction Method for OFDM Optimization

Orthogonal Frequency Division Multiplexing (OFDM) is a effective modulation technique widely used in modern communication systems, including 5G and wireless networks because of its high spectral efficiency and robustness towards multipath fading. However, OFDM signals are characterized by a high Peak-to-Average Power Ratio (PAPR), which can severely impact the power efficiency and operational cost of these systems. This research investigates and analyse effectiveness of two conventional PAPR reduction methods that is Selective Mapping (SLM), and Partial Transmit Sequence (PTS) with incorporating their approach of PAPR reduction to develop a hybrid variant: SLM-PTS. This study utilized MATLAB simulations to implement and test each PAPR reduction technique on a standard OFDM system model. Parameters such as the number of subcarriers, oversampling factor, and modulation types were systematically varied to analyze the impact on PAPR, BER, and computational complexity. The effectiveness of each technique was measured using the Complementary Cumulative Distribution Function (CCDF) of PAPR values and BER performance under different channel conditions. Key findings reveal that hybrid techniques, particularly SLM & PTS, offer significant improvements in PAPR reduction compared to traditional methods alone, without a corresponding increase in BER or computational overhead. The research underscores the potential of hybrid PAPR reduction techniques to significantly enhance the efficiency and reliability of OFDM systems. These findings have important implications for the design and optimization of next-generation wireless communication systems, suggesting that hybrid approaches can provide a balanced solution to the longstanding issue of PAPR in OFDM transmissions. This study contributes valuable insights into the practical application of combined PAPR reduction strategies, offering a pathway toward more power-efficient and robust OFDM technologies. Keywords : OFDM, PAPR, CCDF, SLM and PTS

Fractional stochastic volatility model

This article introduces a discrete‐time fractional stochastic volatility model (FSV) based on fractional Gaussian noise. The new model includes the standard stochastic volatility model as a special case and has the same limit as the fractional integrated stochastic volatility (FISV) model, which is the continuous‐time fractional Ornstein–Uhlenbeck process. A simulated maximum likelihood method, which maximizes the time‐domain log‐likelihood function calculated by the importance sampling technique, and a frequency‐domain quasi maximum likelihood method (or quasi Whittle) are employed to estimate the model parameters. Simulation studies suggest that, while both estimation methods can accurately estimate the model, the simulated maximum likelihood method outperforms the quasi Whittle method. As an illustration, we fit the FSV and FISV models with the proposed estimation techniques to the S&P 500 composite index over a sample period spanning 45 years.

An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets

Data from influenza A virus (IAV) infected ferrets provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human, avian, swine, and other zoonotic strains without prior adaptation, and permit evaluation of virus transmissibility by multiple modes. While ferrets have been employed in risk assessment settings for >20 years, results from this work are typically reported in discrete stand-alone publications, making aggregation of raw data from this work over time nearly impossible. Here, we describe a dataset of 728 ferrets inoculated with 126 unique IAV, conducted by a single research group under a uniform experimental protocol. This collection of morbidity, mortality, and viral titer data represents the largest publicly available dataset to date of in vivo-generated IAV infection outcomes on a per-ferret level.

Positivity from J-Basis operators in the standard model effective Field Theory

In the effective field theory (EFT), the positivity bound on dim-8 effective operators tells us that the s2 contribution in the scattering amplitude of 2-to-2 process geometrically corresponds to the convex cone composed of the ultraviolet (UV) states as the extremal rays. The J-Basis method can provide a complete group theory decomposition of the scattering amplitude on the direct product of the gauge group and the Lorentz group, thus to search for all UV states. Compared to previous methods, which can only perform direct product decomposition on the gauge groups, the J-Basis method greatly improves the strictness of the restrictions and also provides a systematic scheme for calculating the positivity bounds of the dim-8 operators.

Collider signatures of near-continuum dark matter

In this paper we study a near-continuum dark matter model, in which dark sector consists of a tower of closely spaced states with weak-scale masses. We construct a five-dimensional model which naturally realizes this spectrum. The dark matter is described by a bulk field, which interacts with the brane-localized Standard Model sector via a Z portal. We then study collider signatures of this model. Near-continuum dark matter states produced in a collider undergo cascade decays, resulting in events with high multiplicity of jets and leptons, large missing energy, and displaced vertices. A custom-built Monte Carlo tool described in this paper allows for detailed simulation of the signal events. We present results of such simulations for the case of electron-positron collisions.