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Abstract Neutrinoless double-beta decay ( $0\nu \beta \beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu \beta \beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in⁷⁶Ge to achieve a half-life sensitivity of 10²⁷(10²⁸) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of ${0.024}_{-0.003}^{+0.004}\mathrm{\%}$after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000. 

This work describes a method in which the digital image correlation (DIC) method and finite element analysis (FEA) were used to create a quasi-static mixed-mode fracture envelope for bonded joints consisting of 2024-T3 Al adherends and a tough structural epoxy adhesive. Symmetric and asymmetric versions of double cantilever beam, single-leg bend, and end-notched flexure tests are used to populate the mixed-mode fracture envelope with results at several mode mixities. Experiments are conducted in a universal testing machine while recording images for subsequent DIC analysis. Finite element analysis is used to implement cohesive zone models (CZMs) of the adhesive fracture and to account for plastic deformation of adherends. Mode I and mode II traction separation laws (TSLs) are determined from a property identification method with a Benzeggagh–Kenane mixed-mode coupling law used to model mixed-mode behavior. FEA results are shown to provide a good agreement to both the crosshead displacement and DIC data. The methods in this paper serve as a potential framework for future calibration of mixed-mode fracture envelopes for joints bonded with very tough adhesives that complicate assessment with traditional data analysis methods. 

The neurovascular unit (NVU) is composed of vascular cells, glia, and neurons that form the basic component of the blood brain barrier. This intricate structure rapidly adjusts cerebral blood flow to match the metabolic needs of brain activity. However, the NVU is exquisitely sensitive to damage and displays limited repair after a stroke. To effectively treat stroke, it is therefore considered crucial to both protect and repair the NVU. Mitochondrial calcium (Ca²⁺) uptake supports NVU function by buffering Ca²⁺and stimulating energy production. However, excessive mitochondrial Ca²⁺uptake causes toxic mitochondrial Ca²⁺overloading that triggers numerous cell death pathways which destroy the NVU. Mitochondrial damage is one of the earliest pathological events in stroke. Drugs that preserve mitochondrial integrity and function should therefore confer profound NVU protection by blocking the initiation of numerous injury events. We have shown that mitochondrial Ca²⁺uptake and efflux in the brain are mediated by the mitochondrial Ca²⁺uniporter complex (MCU_cx) and sodium/Ca²⁺/lithium exchanger (NCLX), respectively. Moreover, our recent pharmacological studies have demonstrated that MCU_cxinhibition and NCLX activation suppress ischemic and excitotoxic neuronal cell death by blocking mitochondrial Ca²⁺overloading. These findings suggest that combining MCU_cxinhibition with NCLX activation should markedly protect the NVU. In terms of promoting NVU repair, nuclear hormone receptor activation is a promising approach. Retinoid X receptor (RXR) and thyroid hormone receptor (TR) agonists activate complementary transcriptional programs that stimulate mitochondrial biogenesis, suppress inflammation, and enhance the production of new vascular cells, glia, and neurons. RXR and TR agonism should thus further improve the clinical benefits of MCU_cxinhibition and NCLX activation by increasing NVU repair. However, drugs that either inhibit the MCU_cx, or stimulate the NCLX, or activate the RXR or TR, suffer from adverse effects caused by undesired actions on healthy tissues. To overcome this problem, we describe the use of nanoparticle drug formulations that preferentially target metabolically compromised and damaged NVUs after an ischemic or hemorrhagic stroke. These nanoparticle-based approaches have the potential to improve clinical safety and efficacy by maximizing drug delivery to diseased NVUs and minimizing drug exposure in healthy brain and peripheral tissues.