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At least 721 records · Page 40

Electromagnetic signals of inelastic dark matter scattering

Light dark sectors in thermal contact with the Standard Model can naturally produce the observed relic dark matter abundance and are the targets of a broad experimental search program. A key light dark sector model is the pseudo-Dirac fermion with a dark photon mediator. The dynamics of the fermionic excited states are often neglected. We consider scenarios in which a nontrivial abundance of excited states is produced and their subsequent de-excitation yields interesting electromagnetic signals in direct detection experiments. We study three mechanisms of populating the excited state: a primordial excited fraction, a component up-scattered in the Sun, and a component up-scattered in the Earth. We find that the fractional abundance of primordial excited states is generically depleted to exponentially small fractions in the early universe. Nonetheless, this abundance can produce observable signals in current dark matter searches. MeV-scale dark matter with thermal cross sections and higher can be probed by down-scattering following excitation in the Sun. Up-scatters of GeV-scale dark matter in the Earth can give rise to signals in current and upcoming terrestrial experiments and X-ray observations. We comment on the possible relevance of these scenarios to the recent excess in XENON1T.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Search for periodic signals in the dielectron and diphoton invariant mass spectra using 139 fb -1 of $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for physics beyond the Standard Model inducing periodic signals in the dielectron and diphoton invariant mass spectra is presented using 139 fb -1 of $\sqrt{s}$ = 13 TeV pp collision data collected by the ATLAS experiment at the LHC. Novel search techniques based on continuous wavelet transforms are used to infer the frequency of periodic signals from the invariant mass spectra and neural network classifiers are used to enhance the sensitivity to periodic resonances. In the absence of a signal, exclusion limits are placed at the 95% confidence level in the two-dimensional parameter space of the clock work gravity model. Model-independent searches for deviations from the background-only hypothesis are also performed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25 $\,\mathrm {km}$ (0.22 $^{\circ }$ /jats:inline-formula>) versus 50 $\,\mathrm {km}$ (0.44 $^{\circ }$ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

54 ENVIRONMENTAL SCIENCES↗

Preface to the Special Issue on Signal Processing, Data Acquisition and Front-end Systems for Radiation Detection and Measurements

This special issue of the Journal of Signal Processing Systems focuses on advancement of signal processing and data-acquisition for radiation detection and measurements. The seven articles included cover diverse topics within the scope of radiation detection ranging from understanding of fundamental fission process, instrumentation, and application of radiation interaction (e.g., tomography and imaging). The articles focus on signal processing for fission spectrometer, neutron and gamma-ray computed tomography and artificial intelligence methods, dynamic neutron imaging system, pulse-pileup correction in x-ray spectroscopy and calibration methods in radiation measurement.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction

Abstract Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.

Engineering↗

Reducing systematic bias in machine learning applications to J/ψ signal extraction in high-energy nuclear physics

Machine learning techniques are increasingly used in high-energy nuclear physics because they can exploit multivariate correlations more efficiently than conventional cut-based analyses. A central challenge is the construction of training samples that faithfully reproduce the detector response observed in data. Signal samples are usually derived from detector simulations; therefore, mismatches between simulation and data can degrade classifier performance and introduce systematic biases. This work presents two practical correction procedures, namely cumulative distribution function (CDF) mapping and a shift-and-scale transformation, to align simulated signal features with those measured in data. Their performance is demonstrated with $J$/$\psi$ yield measurements in $\sqrt{s_{nn}}$ = 200 GeV Ru+Ru and Zr+Zr collisions recorded by STAR. A set of self-consistency tests shows that these procedures substantially suppress the systematic bias associated with data-simulation discrepancies in machine-learning-based signal extraction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Phosphorylation barcodes direct biased chemokine signaling at CXCR3

Chemokine receptors, a group of G protein-coupled receptors (GPCRs), interact with transducers such as G proteins, ß-arrestins, and GPCR kinases (GRKs). In the chemokine system, many chemokine agonists act as “biased agonists” that preferentially activate distinct signaling effectors when binding to the same receptor, resulting in distinct physiological effects. Although one third of FDA-approved drugs target GPCRs, there has been limited success in targeting the chemokine system. Currently, there is little evidence that differential receptor phosphorylation, or “phosphorylation barcodes,” direct these biased responses at chemokine receptors. To address this knowledge gap, we used mass spectrometry to demonstrate that chemokines of CXCR3 promote different ensembles of phosphorylation barcodes that are associated with differential activation of G proteins, ß-arrestins and GRKs. Chemokine stimulation also resulted in distinct changes throughout the kinome in global phosphoproteomic studies. Mutation of specific CXCR3 phosphosites altered ß-arrestin conformation and impacted ß-arrestin activation in molecular dynamics simulations. T-cells expressing phosphorylation-deficient CXCR3 mutants resulted in distinct agonist- and receptor-specific chemotactic and signaling profiles that were not completely explained by engagement of G proteins, ß-arrestins, and GRKs alone. In conclusion, our results directly link distinct GPCR phosphorylation patterns with non-redundant chemokine signaling (Figure 1).

CXCR3↗

Advancing Li-plating detection: Motivating a multi-signal correlation approach

Facilitating fast charging in lithium-ion batteries (LiBs) is often linked to Li-plating, which harms performance, longevity, and safety. Early detection of Li-plating is essential for rapid technological development and for preventing performance deterioration and ensuring safety during operation. Fast and real-time detection, using commonly collected measurements like voltage (V), current (I), temperature (T), and pressure (P), is highly desirable. Existing standalone methods relying on electrochemical and mechanical signatures, using half, smaller, or specially designed cells often operated at lower temperatures, fail to account for real-world fast-charging conditions. These signatures may also have inherent unreliability in aged LiBs, a phenomenon currently not-well understood. All these uncertainties have complicated practical implementation of a robust Li-plating detection technique. This study, through multiple case studies involving real-world fast-charging conditions using automotive-grade 11.6 Ah LiBs, shows that many single signal-based diagnostic techniques may be inadequate to detect Li-plating. Among various signatures, end-of-charge rest pressure, differential pressure-sensing, and end-of-charge rest voltage were identified as particularly useful in detecting Li-plating. Furthermore, A multi-signal-based detection technique is shown to be more robust in detecting Li-plating. Using both fresh and aged cells, the results and analysis highlight how detection capabilities are influenced by various factors, including battery design, size, charging speed, operating temperature, and degradation level. Adopting such a multi-signal Li-plating detection approach may be instrumental in the rapid development of battery technology in laboratories, as well as ensuring the enhanced safety of next-generation LiBs in real-world fast-charging applications.

25 ENERGY STORAGE↗

A conspicuous 27 Al-NMR signal at 72 ppm during isomerization of Keggin Al 13 ions

A sharp signal at 72 ppm was recently observed in 27 Al-NMR spectra during the isomerization of Keggin-Al 13 ions in the presence of calcium and glycine [1]. It has been proposed that this signal corresponds to one of the Keggin isomers. Conversion of the most common ε-isomer of the Keggin series of molecules, having the stoichiometry [AlO 4 Al 12 (OH) 24 (OH 2 ) 12 ] 7+ , is enhanced by the addition of calcium and glycine [2,3]. Here we show that a 72 ppm signal can also be observed in the absence of calcium or glycine; the magnitude of which depends on aluminum concentration and temperature. Additionally, isomerization of the ε-Keggin-Al 13 to the γ-Keggin-Al 13 isomer was observed in the absence of calcium and glycine at elevated temperatures after several days. Furthermore, calcium and glycine were previously shown to enhance rates of γ-Keggin-Al 13 formation. 2.

27Al-NMR↗

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗

Effects of trapped charge on the signal formation and detection efficiency for subsequent pulses in irradiated silicon sensors

Envisaged high energy physics experiments like the Future Circular Collider require unprecedented radiation hardness of the detectors, as well as short readout time due to high luminosity and occupancy. Silicon has proven to be extremely radiation hard. Sufficient signals can be recorded even at fluences close to 1 ∙ 1 0 16 n e q / cm 2 . Here, the signal formation was studied in silicon strip sensors, irradiated and annealed until the phenomenon of charge multiplication occurred. ATLAS12EC R0 mini sensors were tested by means of edge TCT measurements at temperatures around –20 °C. It was observed that the detection of subsequent signals separated up to several microseconds is altered by the charge trapped during the preceding pulses. The effects of trapped charge on the electrical configuration of a sensor are well known as a polarization or pumping effect in larger band-gap materials like diamond, but is often neglected for silicon at this relatively high temperature. The investigation of the effect created by trapped charges in silicon sensors using subsequent pulses allows to gain information on important parameters such as de-trapping times. Furthermore, it shows a severe impact on the sensor performance in a pile-up scenario. The irradiation fluence and hence the effective doping concentration, the temperature and the amount of initially created charge have a large impact on this phenomenon. The measurements presented help to characterize this phenomenon; particular attention was paid to the application point of view.

47 OTHER INSTRUMENTATION↗

Detectable gravitational wave signals from inflationary preheating

We consider gravitational wave (GW) production during preheating in hybrid inflation models where an axion-like waterfall field couples to Abelian gauge fields. Based on a linear analysis, we find that the GW signal from such models can be within the reach of a variety of foreseeable GW experiments such as LISA, AEDGE, ET and CE, and is close to that of LIGO A+, both in terms of frequency range and signal strength. Furthermore, the resultant GW signal is helically polarized and thus may distinguish itself from other sources of stochastic GW background. Finally, such models can produce primordial black holes that can compose dark matter and lead to merger events detectable by GW detectors.

79 ASTRONOMY AND ASTROPHYSICS↗

Zinc chloride affects chondrogenesis via VEGF signaling

Highlights: • ZnCl2 increases expression of various chondrogenic signaling intermediates. • VEGF/VEGFR play a key role in modulating levels of chondrogenesis. • Insulin mimetics are an appealing option for improvement of fracture healing. • Axitinib + ZnCl2 treatment results in decreased transcription of chondrogenic genes. Insulin mimetics, including zinc containing compounds, have previously been shown to influence chondrogenesis as it relates to healing of fractures in various preclinical models. However, the mechanism by which these compounds drive chondrogenic differentiation is yet undefined. Here, via next-generation sequencing (NGS) and in vitro functional validation, we show that Zinc Chloride (ZnCl{sub 2}) induces expression of both chondrogenic genes (Sox9, Runx1, collagen) as well as genes associated with VEGF-mediated signal transduction, including VEGF receptors 1 and 2 and their ligands; VEGF-A and VEGF-B. Noticeably, although insulin was able to also induce expression of these pro-angiogenic and pro-chondrogenic genes, the impact of insulin on expression of VEGF receptor and ligand genes was marginal when compared to that of ZnCl{sub 2.} Furthermore, while the VEGFR antagonist, Axitinib, was able to attenuate the pro-chondrogenic effects of both insulin and ZnCl{sub 2}; a reduction in gene and protein expression was most profoundly observed when the antagonist was applied to cells treated with ZnCl{sub 2.} Taken together, these data suggest an important role for the VEGF-mediated signal transduction pathways in the positive effects observed when applying zinc-based compounds as adjuvants for chondrogenesis-mediated fracture healing. In this regard, further mechanistic evaluation of ZnCl{sub 2} and other zinc-containing insulin mimetics may support rational design of therapies targeted for disease indications associated with impaired fracture healing.

60 APPLIED LIFE SCIENCES↗

Down-regulation of A3AR signaling by IL-6-induced GRK2 activation contributes to Th17 cell differentiation

Highlights: • Cyclic AMP-PKA signaling is involved in Th17 cell differentiation. • IL-6 stimulation triggers the internalization of A{sub 3}AR and promotes cAMP production in T cells. • IL-6 induces A{sub 3}AR internalization in a GRK2 dependent manner. • GRK2 is a potential therapeutic target for treating Th17 driving immune diseases. IL-6-triggered Th17 cell expansion is responsible for the pathogenesis of many immune diseases including rheumatoid arthritis (RA). Traditionally, IL-6 induces Th17 cell differentiation through JAK-STAT3 signaling. In the present work, PKA inhibition reduces in vitro induction of Th17 cells, while IL-6 stimulation of T cells facilitates the internalization of A{sub 3}AR and increased cAMP production in a GRK2 dependent manner. Inhibition of GRK2 by paroxetine (PAR) or genetic depletion of GRK2 restored A{sub 3}AR distribution and prevented Th17 cell differentiation. Furthermore, in vivo PAR treatment effectively reduced the splenic Th17 cell proportion in a rat model of collagen-induced arthritis (CIA) which was accompanied by a significant improvement in clinical manifestations. These results indicate that IL-6-induced Th17 cell differentiation not only occurs through JAK-STAT3-RORγt but is also mediated through GRK2-A{sub 3}AR-cAMP-PKA-CREB/ICER-RORγt. This elucidates the significance of GRK2-controlled cAMP signaling in the differentiation of Th17 cells and its potential application in treating Th17-driven immune diseases such as RA.

60 APPLIED LIFE SCIENCES↗

The NRG3/ERBB4 signaling cascade as a novel therapeutic target for canine glioma

Highlights: • miR-190a was downregulated in canine brain tumors. • miR-190a functioned as a tumor-suppressor through targeting NRG3. • A pan-ERBB inhibitor exhibited a tumor suppressive effect in canine glioma cells. Canine glioma is a common brain tumor with poor prognosis despite surgery and/or radiation therapy. Therefore, newer and more effective treatment modalities are needed. Neuregulin 3 (NRG3) has known to be a ligand of ERBB4. This study aimed to investigate the usefulness of the NRG3/ERBB4 signaling cascade as a novel therapeutic target in canine glioma. We found out that microRNA (miR)-190a was downregulated in canine brain tumor tissues, including glioma and meningioma. miR-190a directly targeted NRG3 and inhibited the growth of canine glioma cells. The level of p-Akt, which is a downstream target of ERBB4 signaling, was decreased by transfection with miR-190a. NRG3 silencing also suppressed cell growth and decreased the levels of p-Akt and p-ERK1/2, and NRG3 overexpression exhibited opposed effects in canine glioma J3T-1 cells. The mRNA level of erbb4 was significantly upregulated in glioma tissues compared with that in normal brain tissues and meningioma tissues. Furthermore, compared with gefitinib and lapatinib, afatinib exerted a greater inhibitory effect on the growth of canine glioma cells. In conclusion, NRG3/ERBB4 signaling is negatively regulated by miR-190a and contributes to the growth of canine glioma cells, indicating that it may be a promising therapeutic target in canine glioma.

60 APPLIED LIFE SCIENCES↗

PHF19 activates hedgehog signaling and promotes tumorigenesis in hepatocellular carcinoma

Aberrant activation of Hedgehog-Gli1 signaling and accumulation of Gli1 in hepatocellular carcinoma (HCC) are frequently observed. However, the mechanisms leading to the overactivation of this signaling pathway are not fully understood. In this study, we show that the short isoform of PHD finger protein 19 (PHF19) interacts with β-TrCP, the E3 ligase of Gli1, and that knocking down PHF19 promotes the ubiquitination of Gli1. In a biological function study, PHF19 was found to promote the growth of HCC cells both in liquid culture and in soft agar. Moreover, knocking out PHF19 in a HCC mouse model (Myc{sup F/F}) using the hydrodynamic method inhibited tumorigenesis and improved survival. Taken together, these results demonstrate that PHF19 promotes the growth of HCC cells by activating the Hedgehog signaling pathway.

60 APPLIED LIFE SCIENCES↗

PLEKHA7 signaling is necessary for the growth of mutant KRAS driven colorectal cancer

Plekha7 (Pleckstrin homology [PH] domain containing, family A member 7) regulates the assembly of proteins of the cytoplasmic apical zonula adherens junction (AJ), thus ensuring cell-cell adhesion and tight-junction barrier integrity. Little is known of Plekha7 function in cancer. In colorectal cancer (CRC) Plekha7 expression is elevated compared to adjacent normal tissue levels, increasing with clinical stage. Plekha7 was present at plasma membrane AJ with wild-type KRas (wt-KRas) but was dispersed in cells expressing mutant KRas (mut-KRas). Fluorescence lifetime imaging microscopy (FLIM) indicated a direct Plekha7 interaction with wt-KRas but scantily with mut-KRas. Inhibiting Plekha7 specifically decreased mut-KRas cell signaling, proliferation, attachment, migration, and retarded mut-KRAS CRC tumor growth. Binding of diC8-phosphoinositides (PI) to the PH domain of Plekha7 was relatively low affinity. This may be because a D175 amino acid residue plays a “sentry” role preventing PI(3,4)P{sub 2} and PI(3,4,5)P{sub 3} binding. Molecular or pharmacological inhibition of the Plekha7 PH domain prevented the growth of mut-KRas but not wt-KRas cells. Taken together the studies suggest that Plekha7, in addition to maintaining AJ structure plays a role in mut-KRas signaling and phenotype through interaction of its PH domain with membrane mut-KRas, but not wt-KRas, to increase the efficiency of mut-KRas downstream signaling.

60 APPLIED LIFE SCIENCES↗