Christopher Potter

Bio: Christopher Potter is an academic researcher from University of Cambridge. The author has contributed to research in topics: Large Hadron Collider & Lepton. The author has an hindex of 66, co-authored 389 publications receiving 21355 citations. Previous affiliations of Christopher Potter include Yale University & Johns Hopkins University School of Medicine.

The ATLAS Experiment at the CERN Large Hadron Collider

Abstract: The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper. A brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is also presented.

Large-scale impoverishment of Amazonian forests by logging and fire

Abstract: Amazonian deforestation rates are used to determine human effects on the global carbon cycle1,2,3 and to measure Brazil's progress in curbing forest impoverishment1,4,5. But this widely used measure of tropical land use tells only part of the story. Here we present field surveys of wood mills and forest burning across Brazilian Amazonia which show that logging crews severely damage 10,000 to 15,000 km2 yr−1 of forest that are not included in deforestation mapping programmes. Moreover, we find that surface fires burn additional large areas of standing forest, the destruction of which is normally not documented. Forest impoverishment due to such fires may increase dramatically when severe droughts provoke forest leaf-shedding and greater flammability; our regional water-balance model indicates that an estimated 270,000 km2 of forest became vulnerable to fire in the 1998 dry season. Overall, we find that present estimates of annual deforestation for Brazilian Amazonia capture less than half of the forest area that is impoverished each year, and even less during years of severe drought. Both logging and fire increase forest vulnerability to future burning6,7 and release forest carbon stocks to the atmosphere, potentially doubling net carbon emissions from regional land-use during severe El Nino episodes. If this forest impoverishment is to be controlled, then logging activities need to be restricted or replaced with low-impact timber harvest techniques, and more effective strategies to prevent accidental forest fires need to be implemented.

Akt regulates growth by directly phosphorylating Tsc2.

Abstract: The direct mechanism by which the serine/threonine kinase Akt (also known as protein kinase B (PKB)) regulates cell growth is unknown. Here, we report that Drosophila melanogaster Akt/PKB stimulates growth by phosphorylating the tuberous sclerosis complex 2 (Tsc2) tumour suppressor and inhibiting formation of a Tsc1-Tsc2 complex. We show that Akt/PKB directly phosphorylates Drosophila Tsc2 in vitro at the conserved residues, Ser 924 and Thr 1518. Mutation of these sites renders Tsc2 insensitive to Akt/PKB signalling, increasing the stability of the Tsc1-Tsc2 complex within the cell. Stimulating Akt/PKB signalling in vivo markedly increases cell growth/size, disrupts the Tsc1-Tsc2 complex and disturbs the distinct subcellular localization of Tsc1 and Tsc2. Furthermore, all Akt/PKB growth signals are blocked by expression of a Tsc2 mutant lacking Akt phosphorylation sites. Thus, Tsc2 seems to be the critical target of Akt in mediating growth signals for the insulin signalling pathway.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Global Consequences of Land Use

Abstract: Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet’s resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

Data clustering: 50 years beyond K-means

Abstract: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organisms into a system of ranked taxa: domain, kingdom, phylum, class, etc. Cluster analysis is the formal study of methods and algorithms for grouping, or clustering, objects according to measured or perceived intrinsic characteristics or similarity. Cluster analysis does not use category labels that tag objects with prior identifiers, i.e., class labels. The absence of category information distinguishes data clustering (unsupervised learning) from classification or discriminant analysis (supervised learning). The aim of clustering is to find structure in data and is therefore exploratory in nature. Clustering has a long and rich history in a variety of scientific fields. One of the most popular and simple clustering algorithms, K-means, was first published in 1955. In spite of the fact that K-means was proposed over 50 years ago and thousands of clustering algorithms have been published since then, K-means is still widely used. This speaks to the difficulty in designing a general purpose clustering algorithm and the ill-posed problem of clustering. We provide a brief overview of clustering, summarize well known clustering methods, discuss the major challenges and key issues in designing clustering algorithms, and point out some of the emerging and useful research directions, including semi-supervised clustering, ensemble clustering, simultaneous feature selection during data clustering, and large scale data clustering.

mTOR Signaling in Growth Control and Disease

Abstract: The mechanistic target of rapamycin (mTOR) signaling pathway senses and integrates a variety of environmental cues to regulate organismal growth and homeostasis. The pathway regulates many major cellular processes and is implicated in an increasing number of pathological conditions, including cancer, obesity, type 2 diabetes, and neurodegeneration. Here, we review recent advances in our understanding of the mTOR pathway and its role in health, disease, and aging. We further discuss pharmacological approaches to treat human pathologies linked to mTOR deregulation.