Neutrino masses in quartification schemes

The idea of quark-lepton universality at high energies has recently been explored in unified theories based upon the quartification gauge group SU(3)^4. These schemes encompass a quark-lepton exchange symmetry that results upon the introduction of leptonic colour. It has been demonstrated that in models in which the quartification gauge symmetry is broken down to the standard model gauge group, gauge coupling constant unification can be achieved, and there is no unique scenario. The same is also true when the leptonic colour gauge group is only partially broken, leaving a remnant SU(2)_\ell symmetry at the standard model level. Here we perform an analysis of the neutrino mass spectrum of such models. We show that these models do not naturally generate small Majorana neutrino masses, thus correcting an error in our earlier quartification paper, but with the addition of one singlet neutral fermion per family there is a realisation of see-saw suppressed masses for the neutrinos. We also show that these schemes are consistent with proton decay.Comment: 12 pages, minor changes. To appear in Phys. Rev.

Unification via intermediate symmetry breaking scales with the quartification gauge group

The idea of quark-lepton universality at high energies has been introduced as a natural extension to the standard model. This is achieved by endowing leptons with new degrees of freedom -- leptonic colour, an analogue of the familiar quark colour. Grand and partially unified models which utilise this new gauge symmetry SU(3)_\ell have been proposed in the context of the quartification gauge group SU(3)^4. Phenomenologically successful gauge coupling constant unification without supersymmetry has been demonstrated for cases where the symmetry breaking leaves a residual SU(2)_\ell unbroken. Though attractive, these schemes either incorporate ad hoc discrete symmetries and non-renormalisable mass terms, or achieve only partial unification. We show that grand unified models can be constructed where the quartification group can be broken fully [i.e. no residual SU(2)_\ell] to the standard model gauge group without requiring additional discrete symmetries or higher dimension operators. These models also automatically have suppressed nonzero neutrino masses. We perform a systematic analysis of the renormalisation-group equations for all possible symmetry breaking routes from SU(3)^4 --> SU(3)_q x SU(2)_L x U(1)_Y. This analysis indicates that gauge coupling unification can be achieved for several different symmetry breaking patterns and we outline the requirements that each gives on the unification scale. We also show that the unification scenarios of those models which leave a residual SU(2)_\ell symmetry are not unique. In both symmetry breaking cases, some of the scenarios require new physics at the TeV scale, while others do not allow for new TeV phenomenology in the fermionic sector.Comment: 25 page

Forms of social and personal fulfilment and non-fulfilment in the Old French narrative lais

The Old French narrative lais offer an image of the individual in terms of both social and personal relationships. This study considers the extent to which it is possible to derive definitions of forms of social and personal fulfilment and non-fulfilment from these texts. As well as being presented in isolation, they are shown in interaction; there can never be a total divorce of the personal desires of the individual from his/her rights and obligations in society. These two aspects of human existence - love and society - appear in the lais in a state of balance or imbalance. Even in those lais in which the characters themselves do not achieve a balance of social and personal fulfilment, the image of the ideal emerges. Consummate fulfilment in a relationship - be it feudal, familial, sexual - necessarily involves a fusion of social suitability and personal commitment. In his/her aspirations to and/or success in fulfilment, the individual appears variously in these texts both as a pawn of the forces of society or destiny and as endowed with the power to earn his/her own happiness. The degree of importance that the interaction between love and society has in the lais is, in particular, indicated through the extent to which these patterns of interaction define the patterns of narrative structure. From this study, conclusions can be drawn as to the historical reality of the individual in twelfth-century noble society in France; the lais offering a reflection of that society, of which they are a product, and also an expression of its ideals, which allow for the very real obstacles to a fusion of social and personal fulfilment to be overcome

The scientific instrument trade in provincial England during the Industrial Revolution, 1760-1851

SIGLEAvailable from British Library Document Supply Centre- DSC:DXN061782 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Independent Publishing: Making and Preserving Culture in a Global Literary Marketplace

First paragraph: This report results from a Programme of Enquiry funded and hosted by the Scottish Insight Universities Institute (Scottish Insight), on the theme of Independent Publishing: Making and Preserving Culture in a Global Literary Marketplace. A series of events was held from June-August 2011 in Scottish Insight's premises in Glasgow, with an additional event held at the Edinburgh International Book Festival in association with Publishing Scotland in August 2011. The events brought together publishers, authors, policy makers, government, librarians, academics from multidisciplinary backgrounds, publishing students, and others with an involvement in books and publishing from Scotland, the UK and beyond. The Programme was supplemented by a series of interviews with independent publishers

Psychosocial impact of alternative management policies for low-grade cervical abnormalities : results from the TOMBOLA randomised controlled trial

Background: Large numbers of women who participate in cervical screening require follow-up for minor cytological abnormalities. Little is known about the psychological consequences of alternative management policies for these women. We compared, over 30-months, psychosocial outcomes of two policies: cytological surveillance (repeat cervical cytology tests in primary care) and a hospital-based colposcopy examination. Methods: Women attending for a routine cytology test within the UK NHS Cervical Screening Programmes were eligible to participate. 3399 women, aged 20–59 years, with low-grade abnormal cytology, were randomised to cytological surveillance (six-monthly tests; n = 1703) or initial colposcopy with biopsies and/or subsequent treatment based on colposcopic and histological findings (n = 1696). At 12, 18, 24 and 30-months post-recruitment, women completed the Hospital Anxiety and Depression Scale (HADS). A subgroup (n = 2354) completed the Impact of Event Scale (IES) six weeks after the colposcopy episode or first surveillance cytology test. Primary outcomes were percentages over the entire follow-up period of significant depression (≥8) and significant anxiety (≥11; “30-month percentages”). Secondary outcomes were point prevalences of significant depression, significant anxiety and procedure-related distress (≥9). Outcomes were compared between arms by calculating fully-adjusted odds ratios (ORs) for initial colposcopy versus cytological surveillance. Results: There was no significant difference in 30-month percentages of significant depression (OR = 0.99, 95% CI 0.80–1.21) or anxiety (OR = 0.97, 95% CI 0.81–1.16) between arms. At the six-week assessment, anxiety and distress, but not depression, were significantly less common in the initial colposcopy arm (anxiety: 7.9% vs 13.4%; OR = 0.55, 95% CI 0.38–0.81; distress: 30.6% vs 39.3%, OR = 0.67 95% CI 0.54–0.84). Neither anxiety nor depression differed between arms at subsequent time-points. Conclusions: There was no difference in the longer-term psychosocial impact of management policies based on cytological surveillance or initial colposcopy. Policy-makers, clinicians, and women themselves can be reassured that neither management policy has a significantly greater psychosocial cost

Biopsy and selective recall compared with immediate large loop excision in management of women with low grade abnormal cervical cytology referred for colposcopy : multicentre randomised controlled trial

Peer reviewedPublisher PD

Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning (ML) models. For this purpose, ML models were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli associated with urinary tract infections. This is an important common infection in humans and companion animals from which multidrug-resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage was measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features, and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of &gt;0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive ML models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.</p

Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning models (MLM). For this purpose, MLM were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli (E. coli) associated with urinary tract infections. This is an important common infection in humans and companion animals from which multi-drug resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage were measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of &gt;0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.Significance Statement With the growing challenge of antimicrobial resistance there is an urgency for alternative treatments for common bacterial diseases including urinary tract infections (UTIs). Escherichia coli is the main causative agent of UTIs in both humans and companion animals with multidrug resistant strains such as the globally disseminated ST131 becoming more common. Bacteriophage (phage) are natural predators of bacteria and potentially an alternative therapy. However, a major barrier for phage therapy is the specificity of phage on target bacteria and therefore difficulty efficiently selecting the appropriate phage. Here, we demonstrate a genomics driven approach using machine learning prediction models combined with phage activity clustering to select phage cocktails based only on the genome sequence of the infecting bacterial strain