Southwest Research Institute assistance to NASA in biomedical areas of the technology utilization program Quarterly progress report, 1 May - 31 Jul. 1969

Dissemination of NASA derived technologies for biomedical applicatio

Prospects of searches for long-lived charged particles with MoEDAL

We study the prospects of searches for exotic long-lived particles with the MoEDAL detector at the LHC, assuming the integrated luminosity of 30 fb$^{-1}$ that is expected at the end of Run 3. MoEDAL incorporates nuclear track detectors deployed a few metres away from the interaction point, which are sensitive to any highly-ionizing particles. Hence MoEDAL is able to detect singly- or doubly-charged particles with low velocities $\beta < 0.15$ or $< 0.3$, respectively, and lifetimes larger than ${\cal O}(1) \,{\rm m}/c$. We examine the MoEDAL sensitivity to various singly-charged supersymmetric particles with long lifetimes and to several types of doubly-charged long-lived particles with different spins and SU(2) charges. We compare the prospective MoEDAL mass reaches to current limits from ATLAS and CMS, which involve auxiliary analysis assumptions. MoEDAL searches for doubly-charged fermions are particularly competitive.Comment: 19 pages, 5 figure

Enemies Within: Redefining the insider threat in organizational security policy

The critical importance of electronic information exchanges in the daily operation of most large modern organizations is causing them to broaden their security provision to include the custodians of exchanged data – the insiders. The prevailing data loss threat model mainly focuses upon the criminal outsider and mainly regards the insider threat as ‘outsiders by proxy’, thus shaping the relationship between the worker and workplace in information security policy. A policy that increasingly takes the form of social policy for the information age as it acquires the power to include and exclude sections of society and potentially to re-stratify it? This article draws upon empirical sources to critically explore the insider threat in organizations. It looks at the prevailing threat model before deconstructing ‘the insider’ into various risk profiles, including the well-meaning insider, before drawing conclusions about what the building blocks of information security policy around the insider might be

Salmonella Pathogenesis and Processing of Secreted Effectors by Caspase-3

The enteric pathogen Salmonella enterica serovar Typhimurium causes food poisoning resulting in gastroenteritis. The S. Typhimurium effector Salmonella invasion protein A (SipA) promotes gastroenteritis by functional motifs that trigger either mechanisms of inflammation or bacterial entry. During infection of intestinal epithelial cells, SipA was found to be responsible for the early activation of caspase-3, an enzyme that is required for SipA cleavage at a specific recognition motif that divided the protein into its two functional domains and activated SipA in a manner necessary for pathogenicity. Other caspase-3 cleavage sites identified in S. Typhimurium appeared to be restricted to secreted effector proteins, which indicates that this may be a general strategy used by this pathogen for processing of its secreted effectors

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining ‘big’ data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype