Probing structural relaxation in complex fluids by critical fluctuations

Complex fluids, such as polymer solutions and blends, colloids and gels, are of growing interest in fundamental and applied soft-condensed-matter science. A common feature of all such systems is the presence of a mesoscopic structural length scale intermediate between atomic and macroscopic scales. This mesoscopic structure of complex fluids is often fragile and sensitive to external perturbations. Complex fluids are frequently viscoelastic (showing a combination of viscous and elastic behaviour) with their dynamic response depending on the time and length scales. Recently, non-invasive methods to infer the rheological response of complex fluids have gained popularity through the technique of microrheology, where the diffusion of probe spheres in a viscoelastic fluid is monitored with the aid of light scattering or microscopy. Here we propose an alternative to traditional microrheology that does not require doping of probe particles in the fluid (which can sometimes drastically alter the molecular environment). Instead, our proposed method makes use of the phenomenon of "avoided crossing" between modes associated with the structural relaxation and critical fluctuations that are spontaneously generated in the system.Comment: 4 pages, 4 figure

Observation of Phase Fluctuations in Bose-Einstein Condensates

The occurrence of phase fluctuations due to thermal excitations in Bose-Einstein condensates (BECs) is studied for a variety of temperatures and trap geometries. We observe the statistical nature of the appearence of phase fluctuations and characterize the dependence of their average value on temperature, number of particles and the trapping potential. We find pronounced phase fluctuations for condensates in very elongated traps in a broad temperature range. The results are of great importance for the realization of BEC in quasi 1D geometries, for matter wave interferometry with BECs, as well as for coherence properties of guided atom laser beams.Comment: 4 pages, 4 figure

Folate deficiency induces neurodegeneration and brain dysfunction in mice lacking uracil DNA glycosylase

Folate deficiency and resultant increased homocysteine levels have been linked experimentally and epidemiologically with neurodegenerative conditions like stroke and dementia. Moreover, folate deficiency has been implicated in the pathogenesis of psychiatric disorders, most notably depression. We hypothesized that the pathogenic mechanisms include uracil misincorporation and, therefore, analyzed the effects of folate deficiency in mice lacking uracil DNA glycosylase (Ung-/-) versus wild-type controls. Folate depletion increased nuclear mutation rates in Ung-/- embryonic fibroblasts, and conferred death of cultured Ung-/- hippocampal neurons. Feeding animals a folate-deficient diet (FD) for 3 months induced degeneration of CA3 pyramidal neurons in Ung-/- but not Ung+/+ mice along with decreased hippocampal expression of brain-derived neurotrophic factor protein and decreased brain levels of antioxidant glutathione. Furthermore, FD induced cognitive deficits and mood alterations such as anxious and despair-like behaviors that were aggravated in Ung-/- mice. Independent of Ung genotype, FD increased plasma homocysteine levels, altered brain monoamine metabolism, and inhibited adult hippocampal neurogenesis. These results indicate that impaired uracil repair is involved in neurodegeneration and neuropsychiatric dysfunction induced by experimental folate deficiency

Coherent matter wave inertial sensors for precision measurements in space

We analyze the advantages of using ultra-cold coherent sources of atoms for matter-wave interferometry in space. We present a proof-of-principle experiment that is based on an analysis of the results previously published in [Richard et al., Phys. Rev. Lett., 91, 010405 (2003)] from which we extract the ratio h/m for 87Rb. This measurement shows that a limitation in accuracy arises due to atomic interactions within the Bose-Einstein condensate

Coupling of Rotational Motion with Shape Fluctuations of Core-shell Microgels Having Tunable Softness

The influence of shape fluctuations on deformable thermosensitive microgels in aqueous solution is investigated by dynamic light scattering (DLS) and depolarized dynamic light scattering (DDLS). The systems under study consist of a solid core of polystyrene and a thermosensitive shell of cross-linked poly(N-isopropylacrylamide) (PNIPA) without and with embedded palladium nanoparticles. PNIPA is soluble in water, but has a lower critical solution temperature at 32 C (LCST). Below the LCST the PNIPA shell is swollen. Here we find that besides translational and rotational diffusion, the particles exhibit additional dynamics resulting from shape fluctuations. This leads to a pronounced apparent increase of the rotational diffusion coefficient. Above the transition temperature the shell collapses and provides a rather tight envelope of the core. In this state the dynamics of the shell is frozen and the core-shell particles behave like hard spheres. A simple physical model is presented to capture and explain the essentials of the coupling of rotational motion and shape fluctuations.Comment: 9 pages, 7 figure

Can burglary prevention be low-carbon and effective? Investigating the environmental performance of burglary prevention measures

There has been limited study to date on the environmental impacts of crime prevention measures. We address this shortfall by estimating the carbon footprint associated with the most widely used burglary prevention measures: door locks, window locks, burglar alarms, lighting and CCTV cameras. We compare these footprints with a measure of their effectiveness, the security protection factor, allowing us to identify those measures that are both low-carbon and effective in preventing burglary. Window locks are found to be the most effective and low-carbon measure available individually. Combinations of window locks, door locks, external and indoor lightings are also shown to be effective and low-carbon. Burglar alarms and CCTV do not perform as strongly, with low security against burglary and higher carbon footprints. This information can be used to help inform more sustainable choices of burglary prevention within households as well as for crime prevention product design

Deletion of Running-Induced Hippocampal Neurogenesis by Irradiation Prevents Development of an Anxious Phenotype in Mice

Recent evidence postulates a role of hippocampal neurogenesis in anxiety behavior. Here we report that elevated levels of neurogenesis elicit increased anxiety in rodents. Mice performing voluntary wheel running displayed both highly elevated levels of neurogenesis and increased anxiety in three different anxiety-like paradigms: the open field, elevated O-maze, and dark-light box. Reducing neurogenesis by focalized irradiation of the hippocampus abolished this exercise-induced increase of anxiety, suggesting a direct implication of hippocampal neurogenesis in this phenotype. On the other hand, irradiated mice explored less frequently the lit compartment of the dark-light box test irrespective of wheel running, suggesting that irradiation per se induced anxiety as well. Thus, our data suggest that intermediate levels of neurogenesis are related to the lowest levels of anxiety. Moreover, using c-Fos immunocytochemistry as cellular activity marker, we observed significantly different induction patterns between runners and sedentary controls when exposed to a strong anxiogenic stimulus. Again, this effect was altered by irradiation. In contrast, the well-known induction of brain-derived neurotrophic factor (BDNF) by voluntary exercise was not disrupted by focal irradiation, indicating that hippocampal BDNF levels were not correlated with anxiety under our experimental conditions. In summary, our data demonstrate to our knowledge for the first time that increased neurogenesis has a causative implication in the induction of anxiety

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted