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In frustrated magnetic systems, the competition amongst interactions can introduce extremely high degeneracy and prevent the system from readily selecting a unique ground state. In such cases, the magnetic order is often exquisitely sensitive to the balance among the interactions, allowing tuning among novel magnetically ordered phases. In antlerite, Cu3SO4(OH)4, Cu2+ (S=1/2) quantum spins populate three-leg zigzag ladders in a highly frustrated quasi-one-dimensional structural motif. We demonstrate that at zero applied field, in addition to its recently reported low-temperature phase of coupled ferromagnetic and antiferromagnetic spin chains, this mineral hosts an incommensurate helical+cycloidal state, an idle-spin state, and a multiple-q phase which is the magnetic analog of misfit crystal structures. The antiferromagnetic order on the central leg is reentrant. The high tunability of the magnetism in antlerite makes it a particularly promising platform for pursuing exotic magnetic order., This project was funded by the German Research Foundation (DFG) via the projects B01, B03, C03, and C06 of the Collaborative Research Center SFB 1143 (project-id 247310070); Research Training Group GRK 1621 (project-id 129760637); the Würzburg-Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter – ct.qmat (EXC 2147, project-id 390858490); and through grants No. IN 209/9-1, PE 3318/2-1, and LI 244/12-2, and Project No. 422219907.

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We report 75As nuclear magnetic resonance measurements on single crystals of RbFe2As2 and CsFe2As2. Taking previously reported results for KFe2As2 into account, we find that the anisotropic electronic correlations evolve towards a magnetic instability in the AFe2As2 series (with A = K, Rb, Cs). Upon isovalent substitution with larger alkali-metal ions, a drastic enhancement of the anisotropic nuclear spin-lattice relaxation rate and decreasing Knight shift reveal the formation of pronounced spin fluctuations with stripe-type modulation. Furthermore, a decreasing power-law exponent of the nuclear spin-lattice relaxation rate (1/T1)HIIab, probing the in-plane spin fluctuations, evidences an emergent deviation from Fermi-liquid behavior. All these findings clearly indicate that the expansion of the lattice in the AFe2As2 series tunes the electronic correlations towards a quantum critical point at the transition to a yet unobserved ordered phase.

Quality management systems had originally been designed for industrial purposes and were hardly applicable for small enterprises, there have been adjustments to the two main applications EFQM and ISO enabling utilisation also in ambulatory care. There are also different approaches like the Dutch Visitatiae concept which reflects the needs of GP's and is based on peer exchange. The presented paper gives an overview of existing quality management and certification systems and presents an instrument for evaluation. This checklist was developed by an interdisciplinary expert panel of the Agency for Quality in Medicine and serves as an aid for users and graders of quality management systems with regard to the feasibility of these systems.

PURPOSE To define the diagnostic efficacy of MR imaging, "time of flight" (TOF) and phase contrast (PC) MR angiography in craniocervical arterial dissections. MATERIAL AND METHODS The MR examinations of 16 patients with proven arterial dissections (n = 20) were retrospectively analysed by three independent readers. The MR protocol included T1w spin echo sequences with and without fat saturation (SPIR), T2w-turbo-spin echo, 2D- and 3D-TOF- and 3D-PC-MRA. The study was undertaken to assess the diagnostic sensitivity of each technique in detecting typical pathological features. RESULTS The overall sensitivity was best in 3D-PC-MRA; reaching 88% of all possible points. Intramural haematoma could be easily detected with T1W spin echo with fat saturation (100%). Intimal flap and lumen narrowing was best defined with 3D-TOF-MRA in 86% resp. 96% and 3D-PC-MRA in 69% resp. 97%. 3D-PC-MRA was superior to all other sequences in 5 cases of aneurysmal dissection (100%). CONCLUSIONS An accurate evaluation of craniocervical arterial dissections should rely on a combined protocol including T1w spin echo with fat saturation and an axial 3D-MR angiography (if possible 3D-phase contrast MRA).

Purpose To evaluate stroke risk assessment of balloon test occlusion of the internal carotid artery (ICA) with enlarged haemodynamic monitoring prior to permanent ICA occlusion. Material and methods 24 patients with cervical metastasis (n = 18), cavernous meningiomas (n = 3) or inoperable cavernous aneurysms (n = 3) were examined. The test occlusion was monitored by EEG, neurological examinations and transcranial Doppler sonography of the ipsilateral middle cerebral artery with evaluation of the cerebrovascular reserve capacity. Additionally 99mTc-HMPAO-SPECT imaging was added showing the perfusion during test occlusion. Results In one (4%) patient the test occlusion had to be interrupted previously due to an acute neurological deficit. This patient and two (8%) patients with highly pathological test results in SPECT and TCD were excluded from permanent carotid occlusion. In 6 (25%) patients quantitative TCD monitoring could improve the stroke risk assessment by differentiating the patients in a low and high risk group. 6 (25%) patients were definitely occluded without haemodynamic complications, but two patients suffered from embolic infarctions which cannot be predicted by this procedure. Conclusions The multimodal balloon test occlusion with enlarged haemodynamic monitoring allows haemodynamic stroke risk assessment prior to permanent occlusion of the ICA.

Input modeling is the selection of a probability distribution to capture the uncertainty in the input environment of a stochastic system. Example applications of input modeling include the representation of the randomness in the time to failure for a machining process, the time between arrivals of calls to a call center, and the demand received for a product of an inventory system. Building simulations of stochastic systems requires the development of input models that adequately represent the uncertainty in such random variables. Since there are an abundance of probability distributions that can be used for this purpose, a natural question to ask is how to identify the probability distribution that best represents the particular situation under study. For example, is the exponential distribution a reasonable choice to represent the time to failure for a machining process, or is it better to use an empirical distribution function obtained from the historical time-to-failure data? Recognizing the fact that there is no true input model waiting to be found, the goal of stochastic input modeling is to obtain an approximation that captures the key characteristics of the system inputs.The development of a good input model requires the collection of as much information as possible about the relevant randomness in the system as well as the historical data consisting of the past realizations of the random variables of interest. In the presence of a data set, the input model can be identified by fitting a probability distribution to the historical data. However, it may be difficult and/or costly to collect data for the stochastic system under study; it can also be impossible to properly collect any data at all such as when the proposed system does not exist. In the absence of historical data, any relevant information (e.g., expert opinion and the conventional bounds suggested by the underlying physical situation) can be used for input modeling. This article addresses the key issues that arise in stochastic input modeling both in the presence and in the absence of historical data.The first step in input modeling is to identify the sources of randomness in the input environment of the system under study. Many stochastic systems contain multiple sources of uncertainty, e.g., the completion time of an item on a particular machine, the potential breakdown of the machine, and the percentage of defective items produced by the machine might be among the sources of uncertainty in a manufacturing setting. Throughout, the random vector X = (X1, X2, …, X K )′ is used to represent the collection of K different inputs of a stochastic system, where X k is the random variable denoting the kth system input. The K components of this random vector might also be correlated with each other. Therefore, the stochastic properties of the random inputs X k , k = 1, 2, …, K, are captured in the joint probability

Northeast Atlantic 2004 Cruise No. 61, Leg 1 April 19 to May 4, 2004, Lisbon – Cork