A Light Stop with a Heavy Gluino: Enlarging the Stop Gap

It is widely thought that increasing bounds on the gluino mass, which feeds down to the stop mass through renormalization group running, are making a light stop increasingly unlikely. Here we present a counter-example. We examine the case of the Minimal Composite Supersymmetric Standard Model which has a light composite stop. The large anomalous dimension of the stop from strong dynamics pushes the stop mass toward a quasi-fixed point in the infrared, which is smaller than standard estimates by a factor of a large logarithm. The gluino can be about three times heavier than the stop, which is comparable to hierarchy achieved with supersoft Dirac gluino masses. Thus, in this class of models, a heavy gluino is not necessarily indicative of a heavy stop.Comment: 6 pages, 1 figur

Marginal Breaking of Conformal SUSY QCD

We provide an example of a 4D theory that exhibits the Contino-Pomarol-Rattazzi mechanism, where breaking conformal symmetry by an almost marginal operator leads to a light pseudo-Goldstone boson, the dilaton, and a parametrically suppressed contribution to vacuum energy. We consider SUSY QCD at the edge of the conformal window and break conformal symmetry by weakly gauging a subgroup of the flavor symmetry. Using Seiberg duality we show that for a range of parameters the singlet meson in the dual theory reaches the unitarity bound, however, this theory does not have a stable vacuum. We stabilize the vacuum with soft breaking terms, compute the mass of the dilaton, and determine the range of parameters where the leading contribution to the dilaton mass is from the almost marginal coupling.Comment: 12 pages, no figure

In-situ and remote monitoring of environmental water quality

Environmental water pollution affects human health and reduces the quality of our natural water ecosystems and resources. As a result, there is great interest in monitoring water quality and ensuring that all areas are compliant with legislation. Ubiquitous water quality monitoring places considerable demands upon existing sensing technology. The combined challenges of system longevity, autonomous operation, robustness, large-scale sensor networks, operationally difficult deployments and unpredictable and lossy environments collectively represents a technological barrier that has yet to be overcome[1]. Ubiquitous sensing envisages many aspects of our environment being routinely sensed. This will result in data streams from a large variety of heterogeneous sources, which will often vary in their volume and accuracy. The challenge is to develop a networked sensing infrastructure that can support the effective capture, filtering, aggregation and analysis of such data. This will ultimately enable us to dynamically monitor and track the quality of our environment at multiple locations. Microfluidic technology provides a route to the development of miniaturised analytical instruments that could be deployed remotely, and operate autonomously over relatively long periods of time (months–years). An example of such a system is the autonomous phosphate sensor[2] which has been developed at the CLARITY Centre, in Dublin City University. This technology, in combination with the availability of low power, reliable wireless communications platforms that can link sensors and analytical devices to online databases and servers, form the basis for extensive networks of autonomous analytical ‘stations’ or ‘nodes’ that will provide high quality information about key chemical parameters that determine the quality of our aquatic environment. The system must also have sufficient intelligence to enable adaptive sampling regimes as well as accurate and efficient decision-making responses. A particularly exciting area of development is the combination of remote satellite/aircraft based monitoring with the in-situ ground-based monitoring described above. Remote observations from satellites and aircraft can provide significant amounts of information on the state of the aquatic environment over large areas. As in-situ deployments of sensor networks become more widespread and reliable, and satellite data becomes more widely available, information from each of these sources can complement and validate the other, leading to an increased ability to rapidly detect potentially harmful events, and to assess the impact of environmental pressures on scales ranging from small river catchments to the open ocean. In this paper, we will assess the current status of these approaches, and the challenges that must be met in order to realise the vision of true internet- or global-scale monitoring of our environment. References: [1] Integration of analytical measurements and wireless communications – Current issues and future strategies. King Tong Lau, Sarah Brady, John Cleary and Dermot Diamond, Talanta 75 (2008) 606–612. [2] An autonomous microfluidic sensor for phosphate: on-site analysis of treated wastewater. John Cleary, Conor Slater, Christina McGraw and Dermot Diamond, IEEE Sensors Journal, 8 (2008) 508-515

Automatically linking MEDLINE abstracts to the Gene Ontology

Much has been written recently about the need for effective tools and methods for mining the wealth of information present in biomedical literature (Mack and Hehenberger, 2002; Blagosklonny and Pardee, 2001; Rindflesch et al., 2002)—the activity of conceptual biology. Keyword search engines operating over large electronic document stores (such as PubMed and the PNAS) offer some help, but there are fundamental obstacles that limit their effectiveness. In the first instance, there is no general consensus among scientists about the vernacular to be used when describing research about genes, proteins, drugs, diseases, tissues and therapies, making it very difficult to formulate a search query that retrieves the right documents. Secondly, finding relevant articles is just one aspect of the investigative process. A more fundamental goal is to establish links and relationships between facts existing in published literature in order to “validate current hypotheses or to generate new ones” (Barnes and Robertson, 2002)—something keyword search engines do little to support

Development and deployment of a microfluidic platform for water quality monitoring

There is an increasing demand for autonomous sensor devices which can provide reliable data on key water quality parameters at a higher temporal and geographical resolution than is achievable using current approaches to sampling and monitoring. Microfluidic technology, in combination with rapid and on-going developments in the area of wireless communications, has significant potential to address this demand due to a number of advantageous features which allow the development of compact, low-cost and low-powered analytical devices. Here we report on the development of a microfluidic platform for water quality monitoring. This system has been successfully applied to in-situ monitoring of phosphate in environmental and wastewater monitoring applications. We describe a number of the technical and practical issues encountered and addressed during these deployments and summarise the current status of the technology

A semantics and implementation of a causal logic programming language

The increasingly widespread availability of multicore and manycore computers demands new programming languages that make parallel programming dramatically easier and less error prone. This paper describes a semantics for a new class of declarative programming languages that support massive amounts of implicit parallelism

Datalog as a parallel general purpose programming language

The increasing available parallelism of computers demands new programming languages that make parallel programming dramatically easier and less error prone. It is proposed that datalog with negation and timestamps is a suitable basis for a general purpose programming language for sequential, parallel and distributed computers. This paper develops a fully incremental bottom-up interpreter for datalog that supports a wide range of execution strategies, with trade-offs affecting efficiency, parallelism and control of resource usage. Examples show how the language can accept real-time external inputs and outputs, and mimic assignment, all without departing from its pure logical semantics

A Parallel semantics for normal logic programs plus time

It is proposed that Normal Logic Programs with an explicit time ordering are a suitable basis for a general purpose parallel programming language. Examples show that such a language can accept real-time external inputs and outputs, and mimic assignment, all without departing from its pure logical semantics. This paper describes a fully incremental bottom-up interpreter that supports a wide range of parallel execution strategies and can extract significant potential parallelism from programs with complex dependencies