Thermocurrents and their Role in high Q Cavity Performance

Over the past years it became evident that the quality factor of a superconducting cavity is not only determined by its surface preparation procedure, but is also influenced by the way the cavity is cooled down. Moreover, different data sets exists, some of them indicate that a slow cool-down through the critical temperature is favourable while other data states the exact opposite. Even so there where speculations and some models about the role of thermo-currents and flux-pinning, the difference in behaviour remained a mystery. In this paper we will for the first time present a consistent theoretical model which we confirmed by data that describes the role of thermo-currents, driven by temperature gradients and material transitions. We will clearly show how they impact the quality factor of a cavity, discuss our findings, relate it to findings at other labs and develop mitigation strategies which especially addresses the issue of achieving high quality factors of so-called nitrogen doped cavities in horizontal test

Two-photon Lithography for 3D Magnetic Nanostructure Fabrication

Ferromagnetic materials have been utilised as recording media within data storage devices for many decades. Confinement of the material to a two dimensional plane is a significant bottleneck in achieving ultra-high recording densities and this has led to the proposition of three dimensional (3D) racetrack memories that utilise domain wall propagation along nanowires. However, the fabrication of 3D magnetic nanostructures of complex geometry is highly challenging and not easily achievable with standard lithography techniques. Here, by using a combination of two-photon lithography and electrochemical deposition, we show a new approach to construct 3D magnetic nanostructures of complex geometry. The magnetic properties are found to be intimately related to the 3D geometry of the structure and magnetic imaging experiments provide evidence of domain wall pinning at a 3D nanostructured junction

Interleukin-8 and Plasmodium falciparum malaria in Thailand

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31036/1/0000713.pd

Making the diagnosis of Chronic Fatigue Syndrome/Myalgic Encephalitis in primary care: a qualitative study

<p>Abstract</p> <p>Background</p> <p>NICE guidelines emphasise the role of the primary care team in the management of patients with Chronic Fatigue Syndrome/Myalgic Encephalitis (CFS/ME). A key stage in effective management is making an accurate early diagnosis, supported by appropriate referral.</p> <p>Methods</p> <p>A nested qualitative study within a multi-centre randomised controlled trial which aimed to explore GPs' views on their role in making the diagnosis of CFS/ME and subsequent management of patients in primary care. Semi-structured interviews with 22 GPs. Interviews were transcribed verbatim and an iterative approach used to develop themes from the dataset.</p> <p>Results</p> <p>GPs described difficulties in defining CFS/ME and suggested that their role in making a diagnosis was to exclude physical causes for the patient's symptoms, but they reported little confidence in positively attributing the label of CFS/ME to a patient and their symptoms. GPs suggested that the label of CFS/ME could be potentially harmful for the patient. The role of referral to secondary care was debated and GPs struggled defining their own role in management of this group of patients.</p> <p>Conclusions</p> <p>Until GPs feel comfortable making the diagnosis of CFS/ME and facilitating initial management, and have appropriate services to refer patients to, there will continue to be delays in confirming the diagnosis and patients presenting in primary care with fatigue may not receive appropriate care.</p> <p>Trial Registration</p> <p>ISRCTN 74156610</p

Developing a digital intervention for cancer survivors: an evidence-, theory- and person-based approach

This paper illustrates a rigorous approach to developing digital interventions using an evidence-, theory- and person-based approach. Intervention planning included a rapid scoping review which identified cancer survivors’ needs, including barriers and facilitators to intervention success. Review evidence (N=49 papers) informed the intervention’s Guiding Principles, theory-based behavioural analysis and logic model. The intervention was optimised based on feedback on a prototype intervention through interviews (N=96) with cancer survivors and focus groups with NHS staff and cancer charity workers (N=31). Interviews with cancer survivors highlighted barriers to engagement, such as concerns about physical activity worsening fatigue. Focus groups highlighted concerns about support appointment length and how to support distressed participants. Feedback informed intervention modifications, to maximise acceptability, feasibility and likelihood of behaviour change. Our systematic method for understanding user views enabled us to anticipate and address important barriers to engagement. This methodology may be useful to others developing digital interventions

Defective sphingosine-1-phosphate receptor 1 (S1P1) phosphorylation exacerbates TH17-mediated autoimmune neuroinflammation

Sphingosine-1-phosphate (S1P) signaling regulates lymphocyte egress from lymphoid organs into systemic circulation. Sphingosine phosphate receptor 1 (S1P1) agonist, FTY-720 (Gilenya™) arrests immune trafficking and prevents multiple sclerosis (MS) relapses. However, alternative mechanisms of S1P-S1P1 signaling have been reported. Phosphoproteomic analysis of MS brain lesions revealed S1P1 phosphorylation on S351, a residue crucial for receptor internalization. Mutant mice harboring a S1pr1 gene encoding phosphorylation-deficient receptors [S1P1(S5A)] developed severe experimental autoimmune encephalomyelitis (EAE) due to T helper (TH) 17-mediated autoimmunity in the peripheral immune and nervous system. S1P1 directly activated Janus-like kinase–signal transducer and activator of transcription 3 (JAK-STAT3) pathway via interleukin 6 (IL-6). Impaired S1P1 phosphorylation enhances TH17 polarization and exacerbates autoimmune neuroinflammation. These mechanisms may be pathogenic in MS

Astrometry and geodesy with radio interferometry: experiments, models, results

Summarizes current status of radio interferometry at radio frequencies between Earth-based receivers, for astrometric and geodetic applications. Emphasizes theoretical models of VLBI observables that are required to extract results at the present accuracy levels of 1 cm and 1 nanoradian. Highlights the achievements of VLBI during the past two decades in reference frames, Earth orientation, atmospheric effects on microwave propagation, and relativity.Comment: 83 pages, 19 Postscript figures. To be published in Rev. Mod. Phys., Vol. 70, Oct. 199

App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74–0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model