Random Bit Multilevel Algorithms for Stochastic Differential Equations

We study the approximation of expectations \E(f(X)) for solutions $X$ of SDEs and functionals $f \colon C([0,1],\R^r) \to \R$ by means of restricted Monte Carlo algorithms that may only use random bits instead of random numbers. We consider the worst case setting for functionals $f$ from the Lipschitz class w.r.t.\ the supremum norm. We construct a random bit multilevel Euler algorithm and establish upper bounds for its error and cost. Furthermore, we derive matching lower bounds, up to a logarithmic factor, that are valid for all random bit Monte Carlo algorithms, and we show that, for the given quadrature problem, random bit Monte Carlo algorithms are at least almost as powerful as general randomized algorithms

Random Bit Quadrature and Approximation of Distributions on Hilbert Spaces

We study the approximation of expectations \E(f(X)) for Gaussian random elements $X$ with values in a separable Hilbert space $H$ and Lipschitz continuous functionals $f \colon H \to \R$. We consider restricted Monte Carlo algorithms, which may only use random bits instead of random numbers. We determine the asymptotics (in some cases sharp up to multiplicative constants, in the other cases sharp up to logarithmic factors) of the corresponding $n$-th minimal error in terms of the decay of the eigenvalues of the covariance operator of $X$. It turns out that, within the margins from above, restricted Monte Carlo algorithms are not inferior to arbitrary Monte Carlo algorithms, and suitable random bit multilevel algorithms are optimal. The analysis of this problem leads to a variant of the quantization problem, namely, the optimal approximation of probability measures on $H$ by uniform distributions supported by a given, finite number of points. We determine the asymptotics (up to multiplicative constants) of the error of the best approximation for the one-dimensional standard normal distribution, for Gaussian measures as above, and for scalar autonomous SDEs

Maximizing the benefits and minimizing the risks of intervention programs to address micronutrient malnutrition: symposium report.

Interventions to address micronutrient deficiencies have large potential to reduce the related disease and economic burden. However, the potential risks of excessive micronutrient intakes are often not well determined. During the Global Summit on Food Fortification, 9-11 September 2015, in Arusha, a symposium was organized on micronutrient risk-benefit assessments. Using case studies on folic acid, iodine and vitamin A, the presenters discussed how to maximize the benefits and minimize the risks of intervention programs to address micronutrient malnutrition. Pre-implementation assessment of dietary intake, and/or biomarkers of micronutrient exposure, status and morbidity/mortality is critical in identifying the population segments at risk of inadequate and excessive intake. Dietary intake models allow to predict the effect of micronutrient interventions and their combinations, e.g. fortified food and supplements, on the proportion of the population with intakes below adequate and above safe thresholds. Continuous monitoring of micronutrient intake and biomarkers is critical to identify whether the target population is actually reached, whether subgroups receive excessive amounts, and inform program adjustments. However, the relation between regular high intake and adverse health consequences is neither well understood for many micronutrients, nor do biomarkers exist that can detect them. More accurate and reliable biomarkers predictive of micronutrient exposure, status and function are needed to ensure effective and safe intake ranges for vulnerable population groups such as young children and pregnant women. Modelling tools that integrate information on program coverage, dietary intake distribution and biomarkers will further enable program makers to design effective, efficient and safe programs

POWTEX Neutron Diffractometer at FRM II - new perspectives for in-situ rock deformation analysis

EGU2012-13521 In Geoscience quantitative texture analysis here defined as the quantitative analysis of the crystallographic preferred orientation (CPO), is a common tool for the investigation of fabric development in mono- and polyphase rocks, their deformation histories and kinematics. Bulk texture measurements also allow the quantitative characterisation of the anisotropic physical properties of rock materials. A routine tool to measure bulk sample volumes is neutron texture diffraction, as neutrons have large penetration capabilities of several cm in geological sample materials. The new POWTEX (POWder and TEXture) Diffractometer at the neutron research reactor FRM II in Garching, Germany is designed as a high-intensity diffractometer by groups from the RWTH Aachen, Forschungszentrum Jülich and the University of Göttingen. Complementary to existing neutron diffractometers (SKAT at Dubna, Russia; GEM at ISIS, UK; HIPPO at Los Alamos, USA; D20 at ILL, France; and the local STRESS-SPEC and SPODI at FRM II) the layout of POWTEX is focused on fast time-resolved experiments and the measurement of larger sample series as necessary for the study of large scale geological structures. POWTEX is a dedicated beam line for geoscientific research. Effective texture measurements without sample tilting and rotation are possible firstly by utilizing a range of neutron wavelengths simultaneously (Time-of-Flight technique) and secondly by the high detector coverage (9.8 sr) and a high flux (�~1x10 7 n/cm2s) at the sample. Furthermore the instrument and the angular detector resolution is designed also for strong recrystallisation textures as well as for weak textures of polyphase rocks. These instrument characteristics allow in-situ time-resolved texture measurements during deformation experiments on rocksalt, ice and other materials as large sample environments will be implemented at POWTEX. The in-situ deformation apparatus is operated by a uniaxial spindle drive with a maximum axial load of 250 kN, which will be redesigned to minimize shadowing effects inside the cylindrical detector. The HT deformatione experiments will be carried out in uniaxial compression or extension and an upgrade to triaxial deformation conditions is envisaged. The load frame can alternatively be used for ice deformation by inserting a cryostat cell for temperatures down to 77 K with a triaxial apparatus allowing also simple shear experiments on ice. Strain rates range between 10-8 and 10-3 s-1 reaching to at least 50% axial strain. The deformation apparatus is designed for continuous long-term deformation experiments and can be exchanged between in-situ and ex-situ placements during continuous operation inside and outside the neutron detector

Coherent backscattering of Bose-Einstein condensates in two-dimensional disorder potentials

We study quantum transport of an interacting Bose-Einstein condensate in a two-dimensional disorder potential. In the limit of vanishing atom-atom interaction, a sharp cone in the angle-resolved density of the scattered matter wave is observed, arising from constructive interference between amplitudes propagating along reversed scattering paths. Weak interaction transforms this coherent backscattering peak into a pronounced dip, indicating destructive instead of constructive interference. We reproduce this result, obtained from the numerical integration of the Gross-Pitaevskii equation, by a diagrammatic theory of weak localization in presence of a nonlinearity.Comment: 4 pages, 4 figure

OpenSceneVLAD: Appearance Invariant, Open Set Scene Classification

Scene classification is a well-established area of computer vision research that aims to classify a scene image into pre-defined categories such as playground, beach and airport. Recent work has focused on increasing the variety of pre-defined categories for classification, but so far failed to consider two major challenges: changes in scene appearance due to lighting and open set classification (the ability to classify unknown scene data as not belonging to the trained classes). Our first contribution, SceneVLAD, fuses scene classification and visual place recognition CNNs for appearance invariant scene classification that outperforms state-of-the-art scene classification by a mean F1 score of up to 0.1. Our second contribution, OpenSceneVLAD, extends the first to an open set classification scenario using intra-class splitting to achieve a mean increase in F1 scores of up to 0.06 compared to using state-of-the-art openmax layer. We achieve these results on three scene class datasets extracted from large scale outdoor visual localisation datasets, one of which we collected ourselves.</p

Standards of practice in forensic age estimation with CT of the medial clavicular epiphysis-a systematic review.

The AGFAD (Arbeitsgemeinschaft für Forensische Alterdiagnostik, Study Group on Forensic Age Diagnostics) has published several recommendations regarding both technical aspects of computed tomography (CT) of the medial clavicular epiphysis (MCE) and the process of reading and interpreting the CT images for forensic age estimations (FAE). There are, however, no published recommendations regarding CT scan protocols and no dose reference values for CT of the MCE. The objective of this analysis was to assess adherence to AGFAD recommendations among practitioners of FAE and analyse reported dose-relevant CT scan parameters with the objective of helping to establish evidence-based dose reference values for FAE. A systematic literature search was conducted in PubMed and in Google Scholar with specific MeSH terms to identify original research articles on FAE with CT of the MCE from 1997 to 2022. A total of 48 studies were included. Adherence to AGFAD recommendations among practitioners of FAE is high regarding the use of Schmeling main stages (93%), bone window (79%), ≤ 1 mm CT slices (67%), axial/coronal CT images (65%), and Kellinghaus sub-stages (59%). The reporting of CT technique and CT dose-relevant scan parameters is heterogeneous and often incomplete in the current literature. Considering the success achieved by the AGFAD in creating standards of practice of FAE in living subjects, there is potential for the AGFAD to establish standards for radiation protection in FAE as well

IP-10/CXCL10 induction in human pancreatic cancer stroma influences lymphocytes recruitment and correlates with poor survival

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundant desmoplastic reaction driven by pancreatic stellate cells (PSCs) that contributes to tumor progression. Here we sought to characterize the interactions between pancreatic cancer cells (PCCs) and PSCs that affect the inflammatory and immune response in pancreatic tumors. Conditioned media from mono- and cocultures of PSCs and PCCs were assayed for expression of cytokines and growth factors. IP-10/CXCL10 was the most highly induced chemokine in coculture of PSCs and PCCs. Its expression was induced in the PSCs by PCCs. IP-10 was elevated in human PDAC specimens, and positively correlated with high stroma content. Furthermore, gene expression of IP-10 and its receptor CXCR3 were significantly associated with the intratumoral presence of regulatory T cells (Tregs). In an independent cohort of 48 patients with resectable pancreatic ductal adenocarcinoma, high IP-10 expression levels correlated with decreased median overall survival. Finally, IP-10 stimulated the ex vivo recruitment of CXCR3+ effector T cells as well as CXCR3+ Tregs derived from patients with PDAC. Our findings suggest that, in pancreatic cancer, CXCR3+ Tregs can be recruited by IP-10 expressed by PSCs in the tumor stroma, leading to immunosuppressive and tumor-promoting effects