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- Aprile, E., et al.
(författare)
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Effective Field Theory and Inelastic Dark Matter Results from XENON1T
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In this work we expand on the XENON1T nuclear recoil searches and study the individual signals of Dark Matter interactions from operators up to dimension-eight in a Chiral Effective Field Theory (ChEFT) as well as a model of inelastic Dark Matter using data from the two science runs of the detector totalling 1 tonne*year exposure. For these analyses we extended the region of interest from [4.9, 40.9]keVnr to [4.9, 54.4]keVnr to enhance our sensitivity for signals that peak at nonzero energies. We show that the data is consistent with a background only hypothesis, with small excesses in the models which peak between 20 and 50keVnr, obtaining a maximum local discovery significance of 1.7 for the VVs ChEFT model for a WIMP mass of 70GeV/c2, and 1.8 for an iDM particle of 50GeV/c2 with a mass splitting of 100keV/c2. For each model we report 90% confidence level upper limits. We also report limits on three benchmark models of WIMP interaction using ChEFT for which we investigate the effect of isospin breaking interactions, reporting up to 6 orders of magnitude weaker limits with respect to the isospin conserving case driven by cancellations in the expected rate.
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- Wu, Felix, et al.
(författare)
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draft-wu-pana-dpac-framework-00
- 2003
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This informational draft describes the DPAC (Data Packet Access Control) framework, potentially under PANA, to efficiently control "data packets" to access the network. Instead of using potentially more expensive crypto-based mechanisms such as IPSec (layer 3) or IEEE 802.11i (layer 2), DPAC introduces the possibility of using and negotiating a range of light-weight per-data-packet source authentication methods to control the data packets from PANA Clients (PaC). In DPAC, each data packet sent from PaCs to Enhanced Point (EP) can be classified, with high probability, as either valid or invalid. Furthermore, under this framework, it is possible for EP and PAA to account reliably on the network usage of each PaC.
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| 7. |
- Pfeiffer, Thomas, et al.
(författare)
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Predicting the replicability of social and behavioural science claims in a crisis: The COVID-19 Preprint Replication Project
- 2023
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Replications are important for assessing the reliability of published findings. However, they are costly, and it is infeasible to replicate everything. Accurate, fast, lower-cost alternatives such as eliciting predictions could accelerate assessment for rapid policy implementation in a crisis. We elicited judgments from participants on 100 claims from preprints about an emerging area of research (COVID-19 pandemic) using an interactive structured elicitation protocol, and we conducted 29 new high-powered replications. After interacting with their peers, participant groups with lower task expertise (‘beginners’) updated their estimates and confidence in their judgements significantly more than groups with greater task expertise (‘experienced’). For experienced individuals, the average accuracy was 0.57 (95% CI: [0.53, 0.61]) after interaction, and they correctly classified 61% of claims; beginners’ average accuracy was 0.58 (95% CI: [0.54, 0.62]), correctly classifying 69% of claims. The difference in accuracy between groups was not statistically significant, and their judgments on the full set of claims were correlated (r=.48). These results suggest that both beginners and more experienced participants using a structured process have some ability to make better-than-chance predictions about the reliability of ‘fast science’ under conditions of high uncertainty. However, given the importance of such assessments for making evidence-based critical decisions in a crisis, more research is required to understand who the right experts in forecasting replicability are and how their judgements ought to be elicited.
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| 9. |
- Wulf Hanson, Sarah, et al.
(författare)
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A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Importance: While much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID.Objective: To estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery.Design: We jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study.Results: Analyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8-312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38-7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9-92.4), 60.4% (18.9-89.1), and 35.4% (9.4-75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84-4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10-9.78]). At twelve months, 15.1% (10.3-21.1) continued to experience long COVID symptoms.Conclusions and relevance: The occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane.Key Points: Question: What are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021?Findings: Globally, 144.7 million people experienced one or more of three symptom clusters (fatigue; cognitive problems; and ongoing respiratory problems) of long COVID three months after infection, in 2020 and 2021. Most cases arose from milder infections. At 12 months after infection, 15.1% of these cases had not yet recovered.Meaning: The substantial number of people with long COVID are in need of rehabilitative care and support to transition back into the workplace or education when symptoms start to wane.
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