The experimental determination of the properties of the newly discovered boson at the Large Hadron Collider is currently the most crucial task in high-energy physics. We show how information about ...the spin, parity, and, more generally, the tensor structure of the boson couplings can be obtained by studying angular and mass distributions of events in which the resonance decays to pairs of gauge bosons, ZZ, WW, and gamma gamma . A complete Monte Carlo simulation of the process pp arrow right X arrow right VV arrow right 4functionof is performed and verified by comparing it to an analytic calculation of the decay amplitudes X arrow right VV arrow right 4functionof. Our studies account for all spin correlations and include general couplings of a spin J = 0, 1, 2 resonance to Standard Model particles. We also discuss how to use angular and mass distributions of the resonance decay products for optimal background rejection. It is shown that by the end of the 8 TeV run of the LHC, it might be possible to separate extreme hypotheses of the spin and parity of the new boson with a confidence level of 99% or better for a wide range of models. We briefly discuss the feasibility of testing scenarios where the resonance is not a parity eigenstate.
We systematically measure the dielectric function of atomically thin MoS2 films with different layer numbers and demonstrate that excitonic effects play a dominant role in the dielectric function ...when the films are less than 5-7 layers thick. The dielectric function shows an anomalous dependence on the layer number. It decreases with the layer number increasing when the films are less than 5-7 layers thick but turns to increase with the layer number for thicker films. We show that this is because the excitonic effect is very strong in the thin MoS2 films and its contribution to the dielectric function may dominate over the contribution of the band structure. We also extract the value of layer-dependent exciton binding energy and Bohr radius in the films by fitting the experimental results with an intuitive model. The dominance of excitonic effects is in stark contrast with what reported at conventional materials whose dielectric functions are usually dictated by band structures. The knowledge of the dielectric function may enable capabilities to engineer the light-matter interactions of atomically thin MoS2 films for the development of novel photonic devices, such as metamaterials, waveguides, light absorbers, and light emitters.
Abstract
Background
Emerging data suggest variability in susceptibility and outcome to coronavirus disease 2019 (COVID-19) infection. Identifying risk factors associated with infection and outcomes ...in cancer patients is necessary to develop healthcare recommendations.
Methods
We analyzed electronic health records of the US Veterans Affairs Healthcare System and assessed the prevalence of COVID-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for COVID-19 who were positive, as well as outcome attributable to COVID-19, and stratified by clinical characteristics including demographics, comorbidities, cancer treatment, and cancer type. All statistical tests are 2-sided.
Results
Of 22 914 cancer patients tested for COVID-19, 1794 (7.8%) were positive. The prevalence of COVID-19 was similar across age. Higher prevalence was observed in African American (15.0%) compared with White (5.5%; P < .001) and in patients with hematologic malignancy compared with those with solid tumors (10.9% vs 7.8%; P < .001). Conversely, prevalence was lower in current smokers and patients who recently received cancer therapy (<6 months). The COVID-19–attributable mortality was 10.9%. Higher attributable mortality rates were observed in older patients, those with higher Charlson comorbidity score, and in certain cancer types. Recent (<6 months) or past treatment did not influence attributable mortality. Importantly, African American patients had 3.5-fold higher COVID-19–attributable hospitalization; however, they had similar attributable mortality as White patients.
Conclusion
Preexistence of cancer affects both susceptibility to COVID-19 infection and eventual outcome. The overall COVID-19–attributable mortality in cancer patients is affected by age, comorbidity, and specific cancer types; however, race or recent treatment including immunotherapy do not impact outcome.
The high instantaneous luminosity of the CERN Large Hadron Collider leads to multiple proton–proton interactions in the same or nearby bunch crossings (pileup). Advanced pileup mitigation algorithms ...are designed to remove this noise from pileup particles and improve the performance of crucial physics observables. This study implements a semi-supervised graph neural network for particle-level pileup noise removal, by identifying individual particles produced from pileup. The graph neural network is firstly trained on charged particles with known labels, which can be obtained from detector measurements on data or simulation, and then inferred on neutral particles for which such labels are missing. This semi-supervised approach does not depend on the neutral particle pileup label information from simulation, and thus allows us to perform training directly on experimental data. The performance of this approach is found to be consistently better than widely-used domain algorithms and comparable to the fully-supervised training using simulation truth information. The study serves as the first attempt at applying semi-supervised learning techniques to pileup mitigation, and opens up a new direction of fully data-driven machine learning pileup mitigation studies.
Coronavirus disease 2019 (COVID-19) hospitalization definitions do not include a disease severity assessment. Thus, we sought to identify a simple and objective mechanism for identifying hospitalized ...severe cases and to measure the impact of vaccination on trends.
All admissions to a Veterans' Affairs (VA) hospital, where routine inpatient screening is recommended, between March 1, 2020, and November 22, 2021, with laboratory-confirmed severe acute respiratory coronavirus virus 2 (SARS-CoV-2) were included. Moderate-to-severe COVID-19 was defined as any oxygen supplementation or any oxygen saturation (SpO
) <94% between 1 day before and 2 weeks after the positive SARS-CoV-2 test. Admissions with moderate-to-severe disease were divided by the total number of admissions, and the proportion of admissions with moderate-to-severe COVID-19 was modelled using a penalized spline in a Poisson regression and stratified by vaccination status. Dexamethasone receipt and its correlation with moderate-to-severe cases was also assessed.
Among 67,025 admissions with SARS-CoV-2, the proportion with hypoxemia or supplemental oxygen fell from 64% prior to vaccine availability to 56% by November 2021, driven in part by lower rates in vaccinated patients (vaccinated, 52% versus unvaccinated, 58%). The proportion of cases of moderate-to-severe disease identified using SpO
levels and oxygen supplementation was highly correlated with dexamethasone receipt (correlation coefficient, 0.95), and increased after July 1, 2021, concurrent with δ (delta) variant predominance.
A simple and objective definition of COVID-19 hospitalizations using SpO
levels and oxygen supplementation can be used to track pandemic severity. This metric could be used to identify risk factors for severe breakthrough infections, to guide clinical treatment algorithms, and to detect trends in changes in vaccine effectiveness over time and against new variants.
Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods ...to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.
Natural language processing of medical records offers tremendous potential to improve the patient experience. Sentiment analysis of clinical notes has been performed with mixed results, often ...highlighting the issue that dictionary ratings are not domain specific. Here, for the first time, we re-calibrate the labMT sentiment dictionary on 3.5M clinical notes describing 10,000 patients diagnosed with lung cancer at the Department of Veterans Affairs. The sentiment score of notes was calculated for two years after date of diagnosis and evaluated against a lab test (platelet count) and a combination of data points (treatments). We found that the oncology specific labMT dictionary, after re-calibration for the clinical oncology domain, produces a promising signal in notes that can be detected based on a comparative analysis to the aforementioned parameters.
The electron energy band alignment of the monolayer MoSe
2
/oxide/Si system is characterized by internal photoemission spectroscopy, where the oxide is Al
2
O
3
or SiO
2
. Raman and photoluminescence ...spectroscopic measurements confirm the high quality of monolayer MoSe
2
exfoliated with gold film as medium. At the oxide flat-band condition, the band offset from the monolayer MoSe
2
valence band maximum to the Al
2
O
3
and SiO
2
conduction band minimum are measured to be (4.10 ± 0.05) eV and (4.80 ± 0.05) eV, respectively. By referencing the recently reported band gap value of 2.18 eV for monolayer MoSe
2
, we obtain the electron affinity of monolayer MoSe
2
to be (3.8 ± 0.1) eV on Al
2
O
3
/Si and (3.5 ± 0.1) eV on SiO
2
/Si. It is believed that the results from this study will help accelerate the design of electronic and optoelectronic devices that employ this class of two-dimensional materials.
The global COVID-19 pandemic is an opportunity to evaluate factors associated with high levels of adoption of different therapeutics in a real-world setting. The aim of this nationwide, retrospective ...cohort study was to evaluate the diffusion and adoption of novel therapeutics with an emerging evidence basis and to identify factors that influenced physicians' treatment decisions.
Cohort creation: A cohort of Veteran patients with a microbiologically confirmed diagnosis of SARS-CoV2 were identified, and cases were classified by disease severity (outpatient, inpatient with mild and severe disease, intensive care unit ICU). After classification of disease severity, the proportion of cases (outpatients) and admissions (inpatients) in each category receiving each type of medication were plotted as a function of time. Identification of milestones and guidance changes: Key medications used for the management of COVID-19 milestones in the release of primary research results in various forms (e.g. via press release, preprint or publication in a traditional medical journal), policy events and dates of key guidelines were identified and plotted as a timeline. After a timeline was created, time points were compared to changes in medication use, and factors potentially impacting the magnitude (i.e. proportion of patients who received the treatment) and the speed (i.e. the slope of the change in use) of practice changes were evaluated.
Dexamethasone and remdesivir, the first two medications with clinical trial data to support their use, underwent the most rapid, complete and sustained diffusion and adoption; the majority of practice changes occurred after press releases and preprints were available and prior to guideline changes, although some additional uptake occurred following guideline updates. Medications that were not "first in class", that were identified later in the pandemic, and that had higher perceived risk had slower and less complete uptake regardless of the strength and quality of the evidence supporting the intervention.
Our findings suggest that traditional and social media platforms and preprint releases were major catalysts of practice change, particularly prior to the identification of effective treatments. The "first available treatment in class" impact appeared to be the single most important factor determining the speed and scope of diffusion.
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