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Objective: Pain, especially chronic pain, is associated with the experience of depressed mood and anxiety. In turn, experienced depression often leads to the occurrence of physical pain and somatic symptoms. The coexistence of emotional problems and pain can therefore lead to a “vicious cycle”[for full text, please go to the a.m. URL], 72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie

Amorphous silicon (a-Si) is a widely used material, especially for solar cells and thin-film-transistors. Measuring the self-diffusion coefficient of a-Si is experimentally demanding since recrystallization during diffusion annealing must be suppressed. We used Si on insulator (SOI) structures to stabilize the amorphous state during annealing. Isotopically enriched Si multilayers with a thickness per layer of about 10 nm were grown by means of molecular beam epitaxy on top of SOI wafers. Subsequently the whole top crystalline Si layer was amorphized by means of Si ion implantation. Before and after annealing the distribution of the Si isotopes within the isotope structure was measured with SIMS. The observed broadening suggests a significantly higher self-diffusion in the amorphous compared to the crystalline state. Molecular dynamics simulations are employed to gain information about the mechanism of self-diffusion. We used an adjusted Stillinger-Weber potential, as the original Stillinger-Weber parametrization for Si overestimates the mobility of the matrix atoms. The parameters were chosen to simulate the experimentally observed diffusion in a-Si. The coordination numbers and radial-distribution-function were analyzed to confirm the assumption of bond switching as the dominant mechanism of self-diffusion.

Implantation of germanium (Ge), gallium (Ga), or arsenic (As) ions into crystalline and preamorphized isotopically enriched silicon (Si) multilayer structures at temperatures between 20°C and 500°C was performed to study the mechanisms contributing to atomic mixing. Secondary-ion-mass-spectrometry (SIMS) was applied to determine the concentration-depth profiles of the Si isotopes after ion implantation. In contrast to Ge multilayer structures [1] a radiation enhanced self-diffusion (RESD), as well as a dopant dependence of RESD is observed in Si. The contribution of cascade mixing (thermal spike mixing) to the overall atomic mixing is estimated by means of molecular dynamics simulations leaving the contribution due to RESD. Continuum theoretical calculations reveals that the magnitude of RESD can not be described by the diffusion of isolated native defects in supersaturation. Instead RESD is successfully modelled assuming highly mobile di-interstials that form during annealing of the implantation damage. [1] M. Radek et al.: Temperature dependence of ion-beam induced atomic mixing in germanium isotope structures, Appl. Phys. Lett. 115, 023506 (2015)

The purpose of this study was to evaluate the effects of echo planar imaging (EPI) readout bandwidth and its interaction with data processing procedures on the measured blood oxygenation level dependent (BOLD) response and activation in fMRI experiments. Seventeen healthy subjects were scanned during a brief visual stimulation paradigm with two EPI pulse sequences having 'high' (1953 Hz/pixel) and 'low' (780 Hz/pixel) readout bandwidth. Functional data were analyzed with a general linear model including temporal filtering and a basic correlation model following (1) no preprocessing, (2) realignment, or (3) realignment and spatial smoothing. A range of statistical thresholds were used to generate activation maps. Despite slightly higher BOLD signal detected with the high bandwidth sequence from matched ROIs in the primary visual cortex, results showed that the low bandwidth pulse sequence was more sensitive under most conditions evaluated. That is, the low bandwidth sequence detected greater numbers of activated voxels with lower cluster average BOLD signal (e.g., low bandwidth detected 1.4 times more voxels, with average BOLD signal 30% lower compared to high bandwidth for P = 0.05 (corrected) with the 3rd preprocessing procedure using the general linear model). However, there was significant interaction between bandwidth and data preprocessing procedures. Of particular interest, the sensitivity advantage of the low bandwidth pulse sequence decreased for the smoothed data as the activation threshold became less conservative. For the frequently used threshold of P = 0.001 (uncorrected) and cluster size of at least 5 voxels, the bandwidth advantage became insignificant. These findings demonstrate that the effects of bandwidth should be considered carefully in the design, analysis, and interpretation of BOLD fMRI studies.

The availability of highly enriched stable isotopes enables the preparation of isotopically controlled semiconductors. By means of crystalline (c-Ge) and preamorphized (a-Ge) germanium isotope multilayer structures we investigated the temperature and flux dependence of ion-beam induced self-atom mixing. Low,intermediate,and high temperature regions with different mixing behavior are identified after Ga implantation at 310 keV and various temperatures. In the first region (0K - 470K) the amount of mixing in c-Ge and a-Ge is very similar, an increasing mixing with increasing temperature is observed. Region 2 (470K - 540K) reveals a strong drop of mixing in c-Ge whereas the mixing in a-Ge still increases with temperature. In region 3 (570K and above) the mixing in a-Ge drops to the level of c-Ge. Within region 2 no significant structural change occurs during implantation suggesting an efficient annealing of the radiation damage. In addition we performed Focused-Ion-Beam (FIB) implantations with 60 keV Si ions into Ge using two different fluxes at two different temperatures. The experimental results indicate that the annealing of radiation damage is not only temperature but also flux dependent. Molecular dynamics simulations with a Stillinger-Weber type potential are used to study the self-atom mixing observed in the experiment. It is found that the dominant mechanisms of mixing are thermal spikes formed by transferring kinetic energy of the incident ion to the lattice. If the transferred energy is high enough,locally molten regions are created in which the atoms can move more freely compared to the lattice atoms. With increasing temperature the thermal spikes last longer and the mixing increases. This is in accord with the experimentally observed mixing behavior in region 1. Differences between the mixing in a-Ge and c-Ge in region 2 are related to the initial crystal structure. Qualitative agreement is achieved with molecular dynamics simulations.

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Self-atom mixing induced by Gallium (Ga) implantation in crystalline and amorphous germanium (Ge) is investigated using an isotopic multilayer structure of alternating 73 Ge and nat Ge layers grown by molecular beam epitaxy. The distribution of the implanted Ga atoms and ion-beam induced depth-dependent mixing was determined by means of the secondary ion mass spectroscopy (SIMS). The position and form of the implanted Ga peak is very similar in the amorphous and crystalline Ge and can be reproduced accurately by SRIM simulations, whereas the ion-beam induced self-atom mixing strongly depends on the state of the Ge structure. The data from SIMS-measurements reveal a stronger mixing of the crystalline compared to amorphous structure. Molecular dynamics simulations suggest a higher mixing efficiency in the amorphous structure due to the lower thermal transport capacity. The kinetic energy of the implanted ions cause thermal spikes characterized by localized melted regions. Because of the lower thermal transport capacity of the amorphous structure the thermal spike lasts longer and leads to a higher mixing efficiency. The experimentally observed disparity in the ion-beam mixing efficiency of crystalline and amorphous Ge in comparison with the simulation indicates different mixing mechanisms.

Self-atom mixing induced by Gallium (Ga) implantation in crystalline and amorphous germanium (Ge) is investigated using an isotopic multilayer structure of alternating 73Ge and natGe layers grown by molecular beam epitaxy. The distribution of the implanted Ga atoms and ion-beam induced depth-dependent mixing was determined by means of the secondary ion mass spectroscopy (SIMS). The position and form of the implanted Ga peak is very similar in the amorphous and crystalline Ge and can be reproduced accurately by computer simulations based on binary collision approximation (BCA), whereas the ion-beam induced self-atom mixing strongly depends on the state of the Ge structure. The data from SIMS-measurements reveal a stronger mixing in the crystalline than in the amorphous Ge. Atomistic simulation based on BCA can reproduce the experimental data only if unphysically low displacement energies are assumed. The low displacement energies deduced within the BCA approach are confirmed by experiments with mixing induced by silicon implantation. The disparity observed in the ion-beam mixing efficiency of crystalline and amophous Ge indicates different dominant mixing mechanisms. We propose that self-atom mixing in crystalline Ge is mainly controlled by radiation enhanced diffusion during the early stage of mixing before the crystalline structure turns into an amorpous state, whereas in an already amoprhous state self-atom mixing is mediated by cooperative diffusion events.

Molecular dynamics simulations using Stillinger-Weber-type interatomic potentials were performed in order to investigate ion-beam mixing by 400 eV self-ion implantation at different fluences and temperatures. In general the magnitude of mixing in an amorphous structure was found to be higher than in its crystalline counterpart. This supports the results of earlier calculations (K. Nordlund et al., J. Appl. Phys. 83 (1998) 1238). The trends observed in our simulations are compared to our experimental results on ion beam mixing in crystalline and amorphous isotopically modulated Si and Ge multilayer structures.

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Gallium (Ga) implantation induced self-atom mixing in crystalline and amorphous germanium (Ge) is investigated utilizing isotopically controlled Ge multilayer structures grown by molecular beam epitaxy. The distribution of the Ga ions and the ion-beam induced depth-dependent mixing of the isotope structure was determined by means of secondary ion mass spectrometry. Whereas the distribution of Ga in the crystalline and amorphous Ge is very similar and accurately reproduced by computer simulations based on binary collision approximation (BCA), the ion-beam induced self-atom mixing is found to depend strongly on the state of the Ge structure. The experiments reveal stronger self-atom mixing in crystalline than in amorphous Ge. Atomistic simulations based on BCA reproduce the experimental results only when unphysically low Ge displacement energies are assumed. Analysis of the self-atom mixing induced by silicon implantation confirms the low displacement energy deduced within the BCA approach. This demonstrates that thermal spike mixing contributes significantly to the overall mixing of the Ge isotope structures. The disparity observed in the ion-beam mixing efficiency of crystalline and amorphous Ge indicates different dominant mixing mechanisms. We propose that self-atom mixing in crystalline Ge is mainly controlled by radiation enhanced diffusion during the early stage of mixing before the crystalline structure turns amorphous, whereas in an already amorphous state self-atom mixing is mediated by cooperative diffusion events.

Functional magnetic resonance imaging (fMRI) was performed in 30 healthy adults to identify the location, magnitude, and extent of activation in brain regions that are engaged during the performance of Conners' Continuous Performance Test (CPT). Performance on the task during fMRI was highly correlated with performance on the standard Conners' CPT in the behavioral testing laboratory. An extensive neural network was activated during the task that included the frontal, cingulate, parietal, temporal, and occipital cortices; the cerebellum and the basal ganglia. There was also a network of brain regions which were more active during fixation than task. The magnitude of activation in several regions was correlated with reaction time. Among regions that were more active during task, the overall volume of supratentorial activation and cerebellar activation was greater in the left hemisphere. Frontal activation was greater in dorsal than in ventral regions, and dorsal frontal activation was bilateral. Ventral frontal region and parietal lobe activation were greater in the right hemisphere. The volume of clusters of activation in the extrastriate ventral visual pathway was greater in the left hemisphere. This network is consistent with existing models of motor control, visual object processing and attentional control and may serve as a basis for hypothesis-driven fMRI studies in clinical populations with deficits in Conners' CPT performance.

This contribution describes the Space Mapping (SM) technique which is relevant to engineering optimization. The SM technique utilizes different models of the same physical object. Similarly to approximation, interpolation, variable-complexity, response surface modeling, surrogate models, and related techniques, the idea is to replace computationally intensive simulations of an accurate model by faster though less accurate evaluations of another model. In contrast, SM attempts to establish a mapping between the input parameter spaces of those models. This mapping allows us to redirect the optimization-related calculations to the fast model while preserving the accuracy and confidence offered by a few well-targeted evaluations of the accurate model. The SM technique has been successfully applied in the area of microwave circuit design. In principle, however, it is applicable to a wide range of problems where models of different complexity and computational intensity are available, although insight into engineering modeling in the specific application area might be essential.