Proposed New Antiproton Experiments at Fermilab

Fermilab operates the world's most intense source of antiprotons. Recently various experiments have been proposed that can use those antiprotons either parasitically during Tevatron Collider running or after the Tevatron Collider finishes in about 2010. We discuss the physics goals and prospects of the proposed experiments.Comment: 6 pages, 2 figures, to appear in Proceedings of IXth International Conference on Low Energy Antiproton Physics (LEAP'08), Vienna, Austria, September 16 to 19, 200

Human COQ9 Rescues a coq9 Yeast Mutant by Enhancing Coenzyme Q Biosynthesis from 4-Hydroxybenzoic Acid and Stabilizing the CoQ-Synthome

Coq9 is required for the stability of a mitochondrial multi-subunit complex, termed the CoQ-synthome, and the deamination step of Q intermediates that derive from para-aminobenzoic acid (pABA) in yeast. In human, mutations in the COQ9 gene cause neonatal-onset primary Q10 deficiency. In this study, we determined whether expression of human COQ9 could complement yeast coq9 point or null mutants. We found that expression of human COQ9 rescues the growth of the temperature-sensitive yeast mutant, coq9-ts19, on a non-fermentable carbon source and increases the content of Q6, by enhancing Q biosynthesis from 4-hydroxybenzoic acid (4HB). To study the mechanism for the rescue by human COQ9, we determined the steady-state levels of yeast Coq polypeptides in the mitochondria of the temperature-sensitive yeast coq9 mutant expressing human COQ9. We show that the expression of human COQ9 significantly increased steady-state levels of yeast Coq4, Coq6, Coq7, and Coq9 at permissive temperature. Human COQ9 polypeptide levels persisted at non-permissive temperature. A small amount of the human COQ9 co-purified with tagged Coq6, Coq6-CNAP, indicating that human COQ9 interacts with the yeast Q-biosynthetic complex. These findings suggest that human COQ9 rescues the yeast coq9 temperature-sensitive mutant by stabilizing the CoQ-synthome and increasing Q biosynthesis from 4HB. This finding provides a powerful approach to studying the function of human COQ9 using yeast as a model

Rare B Decays with a HyperCP Particle of Spin One

In light of recent experimental information from the CLEO, BaBar, KTeV, and Belle collaborations, we investigate some consequences of the possibility that a light spin-one particle is responsible for the three Sigma^+ -> p mu^+ mu^- events observed by the HyperCP experiment. In particular, allowing the new particle to have both vector and axial-vector couplings to ordinary fermions, we systematically study its contributions to various processes involving b-flavored mesons, including B-Bbar mixing as well as leptonic, inclusive, and exclusive B decays. Using the latest experimental data, we extract bounds on its couplings and subsequently estimate upper limits for the branching ratios of a number of B decays with the new particle. This can serve to guide experimental searches for the particle in order to help confirm or refute its existence.Comment: 17 pages, 3 figures; discussion on spin-0 case modified, few errors corrected, main conclusions unchange

Human pluripotent stem cell-derived mesenchymal stem cells prevent allergic airway inflammation in mice.

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Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording

To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK’s national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository

Investigation of hollow cylindrical metal terahertz waveguides suitable for cryogenic environments

The field of terahertz (THz) waveguides continues to grow rapidly, with many being tailored to suit the specific demands of a particular final application. Here, we explore waveguides capable of enabling efficient and accurate power delivery within cryogenic environments (< 4 K). The performance of extruded hollow cylindrical metal waveguides made of un-annealed and annealed copper, as well as stainless steel, have been investigated for bore diameters between 1.75 - 4.6 mm, and at frequencies of 2.0, 2.85 and 3.4 THz, provided by a suitable selection of THz quantum cascade lasers. The annealed copper resulted in the lowest transmission losses, < 3 dB/m for a 4.6 mm diameter waveguide, along with 90° bending losses as low as ~2 dB for a bend radius of 15.9 mm. The observed trends in losses were subsequently analyzed and related to measured inner surface roughness parameters. These results provide a foundation for the development of a wide array of demanding low-temperature THz applications, and enabling the study of fundamental physics.Engineering and Physical Sciences Research Council (Grant No. EP/J017671/1, Coherent Terahertz Systems)

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain

Runtime analysis of non-elitist populations: from classical optimisation to partial information

Although widely applied in optimisation, relatively little has been proven rigorously about the role and behaviour of populations in randomised search processes. This paper presents a new method to prove upper bounds on the expected optimisation time of population-based randomised search heuristics that use non-elitist selection mechanisms and unary variation operators. Our results follow from a detailed drift analysis of the population dynamics in these heuristics. This analysis shows that the optimisation time depends on the relationship between the strength of the selective pressure and the degree of variation introduced by the variation operator. Given limited variation, a surprisingly weak selective pressure suffices to optimise many functions in expected polynomial time. We derive upper bounds on the expected optimisation time of non-elitist Evolutionary Algorithms (EA) using various selection mechanisms, including fitness proportionate selection. We show that EAs using fitness proportionate selection can optimise standard benchmark functions in expected polynomial time given a sufficiently low mutation rate. As a second contribution, we consider an optimisation scenario with partial information, where fitness values of solutions are only partially available. We prove that non-elitist EAs under a set of specific conditions can optimise benchmark functions in expected polynomial time, even when vanishingly little information about the fitness values of individual solutions or populations is available. To our knowledge, this is the first runtime analysis of randomised search heuristics under partial information