A lattice of microtraps for ultracold atoms based on patterned magnetic films

We have realized a two dimensional permanent magnetic lattice of Ioffe-Pritchard microtraps for ultracold atoms. The lattice is formed by a single 300 nm magnetized layer of FePt, patterned using optical lithography. Our magnetic lattice consists of more than 15000 tightly confining microtraps with a density of 1250 traps/mm$^2$. Simple analytical approximations for the magnetic fields produced by the lattice are used to derive relevant trap parameters. We load ultracold atoms into at least 30 lattice sites at a distance of approximately 10 $\mu$m from the film surface. The present result is an important first step towards quantum information processing with neutral atoms in magnetic lattice potentials.Comment: 7 pages, 7 figure

Pseudogap-less high Tc_{c} superconductivity in BaCox_{x}Fe2−x_{2-x}As2_{2}

The pseudogap state is one of the peculiarities of the cuprate high temperature superconductors. Here we investigate its presence in BaCo$_{x}$Fe$_{2-x}$As$_{2}$, a member of the pnictide family, with temperature dependent scanning tunneling spectroscopy. We observe that for under, optimally and overdoped systems the gap in the tunneling spectra always closes at the bulk T$_{c}$, ruling out the presence of a pseudogap state. For the underdoped case we observe superconducting gaps over large fields of view, setting a lower limit of tens of nanometers on the length scale of possible phase separated regions.Comment: 5 pages, 3 figure

What is the prevalence of fear of cancer recurrence in cancer survivors and patients? A systematic review and individual participant data meta-analysis

This study was supported by the Dutch Cancer Society (KWF) grant number 10936.Objective Care for fear of cancer recurrence (FCR) is considered the most common unmet need among cancer survivors. Yet the prevalence of FCR and predisposing factors remain inconclusive. To support targeted care, we provide a comprehensive overview of the prevalence and severity of FCR among cancer survivors and patients, as measured using the short form of the validated Fear of Cancer Recurrence Inventory (FCRI-SF). We also report on associations between FCR and clinical and demographic characteristics. Methods This is a systematic review and individual participant data (IPD) meta-analysis on the prevalence of FCR. In the review, we included all studies that used the FCRI-SF with adult (≥18 years) cancer survivors and patients. Date of search: 7 February 2020. Risk of bias was assessed using the Joanna Briggs Institute critical appraisal tool. Results IPD were requested from 87 unique studies and provided for 46 studies comprising 11,226 participants from 13 countries. 9311 respondents were included for the main analyses. On the FCRI-SF (range 0–36), 58.8% of respondents scored ≥13, 45.1% scored ≥16 and 19.2% scored ≥22. FCR decreased with age and women reported more FCR than men. FCR was found across cancer types and continents and for all time periods since cancer diagnosis. Conclusions FCR affects a considerable number of cancer survivors and patients. It is therefore important that healthcare providers discuss this issue with their patients and provide treatment when needed. Further research is needed to investigate how best to prevent and treat FCR and to identify other factors associated with FCR. The protocol was prospectively registered (PROSPERO CRD42020142185).Publisher PDFPeer reviewe

Learning form Nature to improve the heat generation of iron-oxide nanoparticles for magnetic hyperthermia applications.

The performance of magnetic nanoparticles is intimately entwined with their structure, mean size and magnetic anisotropy. Besides, ensembles offer a unique way of engineering the magnetic response by modifying the strength of the dipolar interactions between particles. Here we report on an experimental and theoretical analysis of magnetic hyperthermia, a rapidly developing technique in medical research and oncology. Experimentally, we demonstrate that single-domain cubic iron oxide particles resembling bacterial magnetosomes have superior magnetic heating efficiency compared to spherical particles of similar sizes. Monte Carlo simulations at the atomic level corroborate the larger anisotropy of the cubic particles in comparison with the spherical ones, thus evidencing the beneficial role of surface anisotropy in the improved heating power. Moreover we establish a quantitative link between the particle assembling, the interactions and the heating properties. This knowledge opens new perspectives for improved hyperthermia, an alternative to conventional cancer therapies

Pair Correlations in a Bidisperse Ferrofluid in an External Magnetic Field:Theory and Computer Simulations

The pair distribution function g(r) for a ferrofluid modeled by a bidisperse system of dipolar hard spheres is calculated. The influence of an external uniform magnetic field and polydispersity on g(r) and the related structure factor is studied. The calculation is performed by diagrammatic expansion methods within the thermodynamic perturbation theory in terms of the particle number density and the interparticle dipole–dipole interaction strength. Analytical expressions are provided for the pair distribution function to within the first order in number density and the second order in dipole–dipole interaction strength. The constructed theory is compared with the results of computer (Monte Carlo) simulations to determine the range of its validity. The scattering structure factor is determined using the Fourier transform of the pair correlation func-tion g(r) – 1. The influence of the granulometric composition and magnetic field strength on the height and position of the first peak of the structure factor that is most amenable to an experimental study is analyzed. The data obtained can serve as a basis for interpreting the experimental small[1]angle neutron scattering results and determining the regularities in the behavior of the structure factor, its dependence on the fractional com-position of a ferrofluid, interparticle correlations, and external magnetic field. © Pleiades Publishing, Inc., 2014

Modeling alcohol use disorder as a set of interconnected symptoms – Assessing differences between clinical and population samples and across external factors

Alcohol use disorder is argued to be a highly complex disorder influenced by a multitude of factors on different levels. Common research approaches fail to capture this breadth of interconnecting symptoms. To address this gap in theoretical assumptions and methodological approaches, we used a network analysis to assess the interplay of alcohol use disorder symptoms. We applied the exploratory analysis to two US-datasets, a population sample with 23,591 individuals and a clinical sample with 483 individuals seeking treatment for alcohol use disorder. Using a Bayesian framework, we first investigated differences between the clinical and population sample looking at the symptom interactions and underlying structure space. In the population sample the time spent drinking alcohol was most strongly connected, whereas in the clinical sample loss of control showed most connections. Furthermore, the clinical sample demonstrated less connections, however, estimates were too unstable to conclude the sparsity of the network. Second, for the population sample we assessed whether the network was measurement invariant across external factors like age, gender, ethnicity and income. The network differed across all factors, especially for age subgroups, indicating that subgroup specific networks should be considered when deriving implications for theory building or intervention planning. Our findings corroborate known theories of alcohol use disorder stating loss of control as a central symptom in alcohol dependent individuals

A Note on the Structural Change Test in Highly Parameterized Psychometric Models

Equal parameter estimates across subgroups is a substantial requirement of statistical tests. Ignoring subgroup differences poses a threat to study replicability, model specification, and theory development. Structural change tests are a powerful statistical technique to assess parameter invariance. A core element of those tests is the empirical fluctuation process. In the case of parameter invariance, the fluctuation process asymptotically follows a Brownian bridge. This asymptotic assumption further provides the basis for inference. However, the empirical fluctuation process does not follow a Brownian bridge in small samples, and this situation is amplified in large psychometric models. Therefore, common methods of obtaining the sampling distribution are invalid and the structural change test becomes conservative. We discuss an alternative solution to obtaining the sampling distribution—permutation approaches. Permutation approaches estimate the sampling distribution through resampling of the dataset, avoiding distributional assumptions. Hereby, the tests power are improved. We conclude that the permutation alternative is superior to standard asymptotic approximations of the sampling distribution

Size-Dependent Second Virial Coefficients of Quantum Dots from Quantitative Cryogenic Electron Microscopy

Cryogenic transmission electron microscopy (cryo-TEM) is utilized to determine the second virial coefficient of osmotic pressure of PbSe quantum dots (QDs) dispersed in apolar liquid. Cryo-TEM images from vitrified samples provide snapshots of the equilibrium distribution of the particles. These snapshots yield radial distribution functions from which second virial coefficients are calculated, which agree with second virial coefficients determined with analytical centrifugation and small-angle X-ray scattering. The size dependence of the second virial coefficient points to an interparticle interaction that is proportional to the QD surface area. A plausible cause for this attraction is the interaction between the surface ions on adjacent QDs