The Role of Standards in Modern Military and Civilian Telemetering Applications
This paper describes the role of standardization in the implementation of modern telemetry communications systems.
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This paper describes the role of standardization in the implementation of modern telemetry communications systems.
The National Aeronautics and Space Administration has traditionally left the task of specifying design and test criteria to each of the several NASA Centers. Faced with the wide variety fo resulting criteria used for resolving similar or identical problems, the NASA Office of Chief Engineer initiated a program to develop consistent NASA-wide standards if the various NASA Centers could agree to a set of common requirements.
Non-standard neutrino self interactions (NSSI) could be stronger than Fermi interactions. We investigate the ability to constrain these four-neutrino interactions by their effect on the flux of neutrinos originating from a galactic supernova. In the dense medium of a core collapse supernova, these new self interactions can have a significant impact on neutrino oscillations, leading to changes at the flavor evolution and spectra level. We use simulations of the neutrino flux from a 13 solar mass, core collapse supernova at 10 kpc away, and numerically propagate these neutrinos through the stellar medium taking into account vacuum/MSW oscillations, SM ν – ν scattering as well as ν – ν interactions that arise from NSSI. We pass the resulting neutrino flux to a simulation of the future Hyper-Kamiokande detector to see what constraints on NSSI parameters are possible when the next galactic supernova becomes visible. We find that these constraints depend strongly on the neutrino mass hierarchy and if the NSSI is flavor-violating or preserving. Sensitivity to NSSI in the normal hierarchy (NH) at Hyper-K is limited by the experiment’s ability to efficiently detect ν e , but deviations from no NSSI could be seen if the NSSI is particularly strong. In the inverted hierarchy (IH) scenario, Hyper-K can significantly improve constraints on flavor-violating NSSI down to O(10 –1 )G F .
The dispersion relation of an elastic 4-point amplitude in the forward direction leads to a sum rule that connects the low energy amplitude to the high energy observables. We perform a classification of these sum rules based on massless helicity amplitudes. With this classification, we are able to systematically write down the sum rules for the dimension-6 operators of the Standard Model Effective Field Theory (SMEFT), some of which are absent in previous literatures. These sum rules offer distinct insights on the relations between the operator coefficients in the EFT and the properties of the full theory that generates them. Their applicability goes beyond tree level, and in some cases can be used as a practical method of computing the one loop contributions to low energy observables. They also provide an interesting perspective for understanding the custodial symmetries of the SM Higgs and fermion sectors.
The vanishing of the Higgs quartic coupling at a high energy scale may be explained by Intermediate Scale Supersymmetry, where supersymmetry breaks at (10 9 -10 12 ) GeV. The possible range of supersymmetry breaking scales can be narrowed down by precise measurements of the top quark mass and the strong coupling constant. On the other hand, nuclear recoil experiments can probe Higgsino or sneutrino dark matter up to a mass of 1012 GeV. We derive the correlation between the dark matter mass and precision measurements of standard model parameters, including supersymmetric threshold corrections. The dark matter mass is bounded from above as a function of the top quark mass and the strong coupling constant. The top quark mass and the strong coupling constant are bounded from above and below respectively for a given dark matter mass. We also discuss how the observed dark matter abundance can be explained by freeze-out or freeze-in during a matter-dominated era after inflation, with the inflaton condensate being dissipated by thermal effects.
Spherically symmetric magnetic and dyonic black holes with a magnetic charge $\textit{Q}$ = 2 are studied in the Standard Model and general relativity. A magnetically charged black hole with mass below 9.3 × 10 35 GeV has a “hairy” cloud of electroweak gauge and Higgs fields outside the event horizon with 1/$m_W$ in size. An extremal magnetic black hole has a hair mass of 3.6 TeV, while an extremal dyonic black hole has an additional mass of $q^2$ × 1.6 GeV for a small electric charge $q \ll 2π/e^2$. A hairy dyonic black hole with an integer charge is not stable and can decay into a magnetic one plus charged fermions. On the other hand, a hairy magnetic black hole can evolve via Hawking radiation into a nearly extremal one that is cosmologically stable and an interesting object to be searched for.
The full data set of the Daya Bay reactor neutrino experiment is used to probe the effect of the charged current non-standard interactions (CC-NSI) on neutrino oscillation experiments. Two different approaches are applied and constraints on the corresponding CC-NSI parameters are obtained with the neutrino flux taken from the Huber-Mueller model with a 5% uncertainty. For the quantum mechanics-based approach (QM-NSI), the constraints on the CC-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ are extracted with and without the assumption that the effects of the new physics are the same in the production and detection processes, respectively. The approach based on the weak effective field theory (WEFT-NSI) deals with four types of CC-NSI represented by the parameters [ε X ] eα . For both approaches, the results for the CC-NSI parameters are shown for cases with various fixed values of the CC-NSI and the Dirac CP-violating phases, and when they are allowed to vary freely. We find that constraints on the QM-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ from the Daya Bay experiment alone can reach the order O(0.01) for the former and O(0.1) for the latter, while for WEFT-NSI parameters [ε X ] eα , we obtain O(0.1) for both cases.
Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb –1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at √s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterizing the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators O tG and $O$ $^{(8)}_{tq}$, where the limits on the latter are the most stringent to date.
If dark matter (DM) interacts with the Standard Model (SM) via the kinetic mixing (KM) portal, it necessitates the existence of portal matter (PM) particles which carry both dark and SM quantum numbers that will appear in vacuum polarization-like loop graphs. In addition to the familiar ~ eϵQ strength, QED-like interaction for the dark photon (DP), in some setups different loop graphs of these PM states can also induce other coupling structures for the SM fermions that may come to dominate in at least some regions of parameter space regions and which can take the form of ‘dark’ moments, e.g., magnetic dipole-type interactions in the IR, associated with a large mass scale, Λ. In this paper, motivated by a simple toy model, we perform a phenomenological investigation of a possible loop-induced dark magnetic dipole moment for SM fermions, in particular, for the electron. We show that at the phenomenological level such a scenario can not only be made compatible with existing experimental constraints for a significant range of correlated values for Λ and the dark U(1) D gauge coupling, g D , but can also lead to quantitatively different signatures once the DP is discovered. In this setup, assuming complex scalar DM to satisfy CMB constraints, parameter space regions where the DP decays invisibly are found to be somewhat preferred if PM mass limits from direct searches at the LHC and our toy model setup are all taken seriously. High precision searches for, or measurements of, the e + e - → γ + DP process at Belle II are shown to provide some of the strongest future constraints on this scenario.
A search for new physics in top quark production with additional final-state leptons is performed using data collected by the CMS experiment in proton-proton collisions at $ \sqrt{s} $ = 13 TeV at the LHC during 2016–2018. The data set corresponds to an integrated luminosity of 138 fb$^{−1}$. Using the framework of effective field theory (EFT), potential new physics effects are parametrized in terms of 26 dimension-six EFT operators. The impacts of EFT operators are incorporated through the event-level reweighting of Monte Carlo simulations, which allows for detector-level predictions. The events are divided into several categories based on lepton multiplicity, total lepton charge, jet multiplicity, and b-tagged jet multiplicity. Kinematic variables corresponding to the transverse momentum (p$_{T}$) of the leading pair of leptons and/or jets as well as the p$_{T}$ of on-shell Z bosons are used to extract the 95% confidence intervals of the 26 Wilson coefficients corresponding to these EFT operators. No significant deviation with respect to the standard model prediction is found.[graphic not available: see fulltext]
Buildings are responsible for 30% of total energy consumption worldwide. To address building energy, jurisdictions in the USA have enacted Building Performance Standards (BPS) legislation. The objective of BPS is to reduce energy consumption in buildings, thereby reducing the energy burden on utility infrastructure and other externalities. This is accomplished by setting mandatory energy use limits coupled with penalties for exceeding those limits. One of the key questions in BPS policymaking is how these penalties might impact the finances of building owners and tenants. This paper presents an analysis of BPS penalties in Aurora, Colorado, specifically targeting buildings impacted by the adopted statewide BPS legislation. Several BPS penalty structures were applied to the affected building stock in Aurora, and the potential impacts on building owner returns and tenant rents were estimated. The results show that for some combinations of building types and penalty structures, potential rent increases due to penalties could match or exceed typical yearly rent increases. The results also show that in most cases, for Aurora, there was no statistically significant difference in impact between buildings located in under-resourced and well-resourced areas.
Characterization techniques for powder feedstocks used in additive manufacturing (AM) have long been relied upon to describe the inputs to an AM workflow. However, functional gaps remain between tests to measure intrinsic and extrinsic properties with the direct performance within AM equipment. Furthermore, the common practice of reusing powder through multiple build cycles introduces effects and changes to feedstock performance that are otherwise difficult to measure quantitatively. Here, standardization and the development of new test methods have not kept pace with the rapid evolution of the AM industry and its reliance on highly coupled process-structure–property-performance relationships.
Here, we discuss comparatively local versus gauged Weyl symmetry beyond Standard Model (SM) and Einstein gravity and their geometric interpretation. The SM and Einstein gravity admit a natural embedding in Weyl integrable geometry which is a special limit of Weyl conformal (non-metric) geometry. The theory has a local Weyl scale symmetry but no associated gauge boson. Unlike previous models with such symmetry, this embedding is truly minimal i.e. with no additional fields beyond SM and underlying geometry. This theory is compared to a similar minimal embedding of SM and Einstein gravity in Weyl conformal geometry (SMW) which has a full gauged scale invariance, with an associated Weyl gauge boson. At large field values, both theories give realistic, Starobinsky–Higgs like inflation. The broken phase of the current model is the decoupling limit of the massive Weyl gauge boson of the broken phase of SMW, while the local scale symmetry of the current model is part of the larger gauged scale symmetry of SMW. Hence, the current theory has a gauge embedding in SMW. Unlike in the SMW, we note that in models with local scale symmetry the associated current is trivial, which is a concern for the physical meaning of this symmetry. Therefore, the SMW is a more fundamental UV completion of SM in a full gauge theory of scale invariance that generates Einstein gravity in the (spontaneously) broken phase, as an effective theory.
Radiation therapy is a major treatment modality used in > 60% of cancer patients as definitive local treatment for inoperable locoregionally confined tumors and as palliative therapy. Although cytotoxic chemotherapy enhances the effectiveness of treatment, the benefit over radiation therapy alone is modest. There is a need to enhance the effectiveness of local tumor control over what sequentially or concurrently administered cytotoxic chemotherapy provides. Although many biological pathways are known to enhance the effectiveness of radiation therapy, there is currently a paucity of drugs approved for use in combination. Several clinical trials have tested the effectiveness of combining targeted agents or immunotherapies with radiation therapy, but the results of these trials have been negative, likely stemming from the relative lack of preclinical evidence using appropriate experimental standardization or model systems. Accelerating the identification of agents tested in an appropriate clinical context and experimental systems or models would greatly enhance the potential to bring forward early testing of drugs that would not only be safe but also more effective. This article provides an overview of the opportunities and challenges of developing therapeutics to combine with radiation therapy, and some guidance toward preclinical and early clinical testing to improve the chance that advanced phase testing of drug-radiation combinations would be successful in the long term.
Accurately modeling fracture of ductile materials poses open challenges in the field of computational mechanics due to the multiphysics nature of their failure processes. Integrating the interplay between thermodynamics and damage into ductile fracture models is vital for predicting critical failure modes. Here, in this paper, we develop a versatile phase-field (PF) framework for modeling ductile fracture, taking into account finite-strain elasto-plasticity. The framework stems from a variational formulation of constitutive relations for generalized standard materials (GSMs), whose response is described by a Helmholtz free energy and a dissipation pseudo-potential. Its variational structure is based on a minimum principle for a functional that expresses the sum of power densities for reversible and irreversible processes. By minimizing this functional with a constraint on a von Mises yield function, we derive the evolution equation for the equivalent plastic strain and an associative flow rule. This constrained optimization problem is analytically solved for a wide class of thermo-viscoplasticity models. The key innovations of the current work include (i) a cubic plastic degradation function that accounts for a non-vanishing damage-dependent yield stress, (ii) closed-form expressions of the Helmholtz free energy and dissipation pseudo-potential for three thermo-viscoplasticity models, (iii) an extended Johnson–Cook plasticity model with a nonlinear hardening law, and (iv) a plastic work heat source that depends on the plastic degradation function and a variable Taylor–Quinney (TQ) coefficient. The capabilities of the proposed framework are tested with the aid of four ductile fracture problems, including the Sandia Fracture Challenge. In each of these problems, we examine the evolution of relevant field variables such as the PF order parameter, the equivalent plastic strain, the temperature, and the internal power dissipation density, in addition to the overall structural response quantified by the force–displacement curve. These numerical studies demonstrate that the proposed framework effectively represents ductile fracture, yielding computational results that exhibit good agreement with experimental data.
Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.
The complexity and variability of biological data has promoted the increased use of machine learning methods to understand processes and predict outcomes. These same features complicate reliable, reproducible, interpretable, and responsible use of such methods, resulting in questionable relevance of the derived. outcomes. Here we systematically explore challenges associated with applying machine learning to predict and understand biological processes using a well- characterized in vitro experimental system. We evaluated factors that vary while applying machine learning classifers: (1) type of biochemical signature (transcripts vs. proteins), (2) data curation methods (pre- and post-processing), and (3) choice of machine learning classifier. Using accuracy, generalizability, interpretability, and reproducibility as metrics, we found that the above factors significantly mod- ulate outcomes even within a simple model system. Our results caution against the unregulated use of machine learning methods in the biological sciences, and strongly advocate the need for data standards and validation tool-kits for such studies.
This analytical study focuses on loading standardized transportation, aging, and disposal canisters (STADs) at commercial reactor sites and subsequent transportation, e.g., to a consolidated interim storage facility (CISF). Specifically, the amount of spent nuclear fuel (SNF) available to load into STADs with varying deployment dates is explored, and the scenarios are compared with a scenario in which STADs are never loaded at reactor sites. Two key findings are that about half of the U.S. inventory of commercial SNF could be captured in STADs if they were fully deployed by 2035 and that the percentage of SNF available to load into STADs decreases as STAD deployment is delayed.In additional scenarios, the effects of shipping STADs directly from at-reactor spent fuel pools (SFPs) to a CISF are analyzed for a STAD full deployment year of 2035. A key finding from the analysis is that the dry storage of SNF in STADs at reactor sites can be minimized by direct shipment to a CISF from reactor site SFPs. Furthermore, minimizing dry storage at reactor sites means maximizing the receipt rate for STADs at a CISF, and there is likely a more optimal point between the two scenarios for an overall cost-effective operation of waste management systems.