Effective Field Theory of Chirally-Enhanced Muon Mass and Dipole Operators

We study corrections to observables related to the muon in the context of models of new physics which generate mass-enhanced corrections to the muon dipole moments. Working in the Standard Model effective theory, we demonstrate a correlation between the decay of the Higgs boson to muons, and the magnetic and electric dipole moments of the muon generated by the dominant matching corrections. This defines a novel way to classify predictions for a wide variety of models of new physics based on the pattern of deviations of these three observables. In particular, when applied to specific models we find that this correlation has a potential to rule out whole models or set upper bounds on the scale of new physics motivated by the muon anomalous magnetic moment.Comment: 28 pages + appendices, 8 figures. v2: Matches published versio

Predictions for Muon Electric and Magnetic Dipole Moments from h→μ+μ−h \rightarrow \mu^+ \mu^- in Two-Higgs-Doublet Models with New Leptons

We calculate chirally-enhanced corrections to the muon's electric and magnetic dipole moments in two-Higgs-doublet models extended by vectorlike leptons, and we explore a sharp correlation between $h \rightarrow \mu^+ \mu^-$ and the muon's dipole moments in these models. Among many detailed predictions, for a model with new leptons with the same quantum numbers as standard model leptons, we find that $0.39 \lesssim \tan \beta \lesssim 21$ necessarily requires a muon electric dipole moment to be observed at near-future experiments, assuming $h \rightarrow \mu^+ \mu^-$ is measured within $1\%$ of the standard model prediction for the current central value of the measured muon magnetic moment. In all studied models, the predicted values of the electric dipole moment can reach up to current experimental limits. Moreover, we show that in some models there can be two sources of chiral enhancement, parameterizing the correlation between $h \rightarrow \mu^+ \mu^-$ and the dipole moments by a complex number. This leads to sign-preferred predictions for the electric dipole moment.Comment: 26 pages + 25 pages of appendices, 9 figure

Prognostic significance of sealed-off perforation in colon cancer: a prospective cohort study

Background Perforated colon cancer is a rare complication, but has a high risk of recurrence. However, most studies have not distinguished sealed-off perforation from free perforation, and the prognosis is unclear. The aim of this study was to evaluate the oncologic outcome of colon cancer with sealed-off perforation. Methods Eighty-six consecutive patients who underwent resection for colon cancer with sealed-off or free perforation were included. We defined sealed-off perforation as a colon perforation with localized abscess identified on operative, computed tomography, or pathologic findings, with no evidence of free perforation, including fecal contamination and dirty fluid collection in the peritoneal cavity. Oncologic outcomes were compared between patients with colon cancer with sealed-off perforation and free perforation using a log-rank test and Cox regression analysis. Results The sealed-off perforation group included 62 patients, and 24 patients were in the free perforation group. TNM stage and lymphatic, venous, and perineural invasion were similar between the groups. The median follow-up period was 28.9 months (range 0–159). The sealed-off perforation group had better prognosis compared with the free perforation group in terms of progression-free survival (PFS) and overall survival (OS), although there were no statistically significant differences in PFS (5-year PFS 53.7% vs. 40.5%, p = 0.148; 5-year OS 53.6% vs. 22.9%, p = 0.001). However, in multivariable analysis using the Cox progression test, sealed-off perforation did not show a significant effect on cancer progression (p = 0.138) and OS (p = 0.727). Conclusions Colon cancer with sealed-off perforation showed no difference in prognosis compared with free perforation.Not applicable

Towards a muon collider

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work

Towards a muon collider

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work

Erratum: Towards a muon collider

The original online version of this article was revised: The additional reference [139] has been added. Tao Han’s ORICD ID has been incorrectly assigned to Chengcheng Han and Chengcheng Han’s ORCID ID to Tao Han. Yang Ma’s ORCID ID has been incorrectly assigned to Lianliang Ma, and Lianliang Ma’s ORCID ID to Yang Ma. The original article has been corrected

COVID-19 variants’ cross-reactivity on the paper microfluidic particle counting immunoassay

SARS-CoV-2 has mutated many times since the onset of the COVID-19 pandemic, and the omicron is currently the most dominant variant. Determining the specific strain of the virus is beneficial in providing proper care and containment of the disease. We have previously reported a novel method of counting the number of particle immunoagglutination on a paper microfluidic chip using a smartphone-based fluorescence microscope. A single-copy-level detection was demonstrated from clinical saline gargle samples. In this work, we further evaluated two different SARS-CoV-2 monoclonal antibodies to spike vs. nucleocapsid antigens for detecting omicron vs. delta and spike vs. nucleocapsid proteins. The SARS-CoV-2 monoclonal antibody to nucleocapsid proteins could distinguish omicron from delta variants and nucleocapsid from spike proteins. However, such distinction could not be found with the monoclonal antibody to spike proteins, despite the numerous mutations found in spike proteins among variants. This result may suggest a clue to the role of nucleocapsid proteins in recognizing different variants.Technology and Research Initiative Fund (TRIF) of the Arizona Board of RegentsNo embargo COVID-19This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Machine learning classification of bacterial species using mix-and-match reagents on paper microfluidic chips and smartphone-based capillary flow analysis

Traditionally, specific bioreceptors such as antibodies have rapidly identified bacterial species in environmental water samples. However, this method has the disadvantages of requiring an additional process to conjugate or immobilize bioreceptors on the assay platform, which becomes unstable at room temperature. Here, we demonstrate a novel mix-and-match method to identify bacteria species by loading the bacterial samples with simple bacteria interacting components (not bioreceptors), such as lipopolysaccharides, peptidoglycan, and bovine serum albumin, and carboxylated particles, all separately on multiple channels. Neither covalent conjugation nor surface immobilization was necessary. Interactions between bacteria and the above bacteria interacting components resulted in varied surface tension and viscosity, leading to various flow velocities of capillary action through the paper fibers. The smartphone camera and a custom Python code recorded multiple channel flow velocity, each loaded with different bacteria interacting components. A multi-dimensional data set was obtained for a given bacterial species and concentration and used as a machine learning training model. A support vector machine was applied to classify the six bacterial species: Escherichia coli, Salmonella Typhimurium, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus faecium, and Bacillus subtilis. Under optimized conditions, the training model predicts the bacterial species with an accuracy of > 85% of the six bacteria species.University of Arizona Test All Test Smart Program12 month embargo; published: 28 March 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Ellipse of Muon Dipole Moments

We show that any new interaction resulting in a chirally-enhanced contribution to the muon magnetic moment necessarily modifies the decay rate of the Higgs boson to muon pairs or generates the muon electric dipole moment. These three observables are highly correlated, and near future measurements of $h\to \mu^+\mu^-$ will carve an ellipse in the plane of dipole moments for any such model. Together with the future measurements of the electric dipole moment many models able to explain the muon g-2 anomaly can be efficiently tested.Comment: 4 pages + references, 4 figure