Protecting transformative optimism in the art classroom: exploring aspirant art teachers’ shifting ideals

This extended, normative case study was initiated in response to my professional concerns regarding the capacity of student art and design teachers to defend and extend their personal ideals for future classroom practice. Placement in schools, a majority component of initial teacher education (ITE) in England, appeared to be limiting the hopes and disciplinary intent of many of my own students, instead exposing them to a context of increasingly standardised pedagogic expectation, lacking in agentic opportunities. Through a qualitative study designed with Freirean intent, I employed visual methods and elicitation interviews to better understand how a cohort of ITE art students’ ideals were altered or reinforced through adaptation or integration with placement classroom practices. Artistic data collected from nine participants was transcribed through novel application of Feldman’s critical framework, and hybrid thematic analysis resulted in the presentation of six interpretive themes. Deductive codes were drawn from two influential sources: Dennis Atkinson’s (2018) characterisation of an English neoliberal school art context, and César Rossatto’s (2005) typology of teacher optimisms. I found that aspirant art teachers arrived with ideals of an art education celebratory of the authentic attributes of the discipline, typically expressed as chaotic or organic in nature. They championed liberal, critical, and dynamic aspects of teaching and learning about art. On placement, homogenised expectations and reproductive curricula were frequently encountered oppressing students’ agency, and participant cynicism grew. Some adapted their ideals to satisfy institutional requirements. Others described subversive attempts to enact personal aspirations, or a renewed sense of transformative purpose forged in ideal/real tensions. It was important that I could use this knowledge to reconsider my own practices as teacher educator, to protect a pluralistic, dynamic visual art education in future secondary school classrooms. My findings suggest enhanced opportunity for focused dialogue, community, and critical reflection during ITE could strengthen future student art teachers’ capacity to retain, and activate, their own ideals

Whole-genome sequencing for national surveillance of Shiga toxin–producing Escherichia coli O157

Background. National surveillance of gastrointestinal pathogens, such as Shiga toxin–producing Escherichia coli O157 (STEC O157), is key to rapidly identifying linked cases in the distributed food network to facilitate public health interventions. In this study, we used whole-genome sequencing (WGS) as a tool to inform national surveillance of STEC O157 in terms of identifying linked cases and clusters and guiding epidemiological investigation. Methods. We retrospectively analyzed 334 isolates randomly sampled from 1002 strains of STEC O157 received by the Gastrointestinal Bacteria Reference Unit at Public Health England, Colindale, in 2012. The genetic distance between each isolate, as estimated by WGS, was calculated and phylogenetic methods were used to place strains in an evolutionary context. Results. Estimates of linked clusters representing STEC O157 outbreaks in England and Wales increased by 2-fold when WGS was used instead of traditional typing techniques. The previously unidentified clusters were often widely geographically distributed and small in size. Phylogenetic analysis facilitated identification of temporally distinct cases sharing common exposures and delineating those that shared epidemiological and temporal links. Comparison with multi locus variable number tandem repeat analysis (MLVA) showed that although MLVA is as sensitive as WGS, WGS provides a more timely resolution to outbreak clustering. Conclusions. WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations

Designing healthcare information technology to catalyse change in clinical care

The gap between best practice and actual patient care continues to be a pervasive problem in our healthcare system. Efforts to improve on this knowledge_performance gap have included computerised disease management programs designed to improve guideline adherence. However, current computerised reminder and decision support interventions directed at changing physician behaviour have had only a limited and variable effect on clinical outcomes. Further, immediate pay-for-performance financial pressures on institutions have created an environmentwhere disease management systems are often created under duress, appended to existing clinical systems and poorly integrated into the existing workflow, potentially limiting their realworld effectiveness. The authors present a review of disease management as well as a conceptual framework to guide the development of more effective health information technology (HIT) tools for translating clinical information into clinical action

Tiresias: Predicting Security Events Through Deep Learning

With the increased complexity of modern computer attacks, there is a need for defenders not only to detect malicious activity as it happens, but also to predict the specific steps that will be taken by an adversary when performing an attack. However this is still an open research problem, and previous research in predicting malicious events only looked at binary outcomes (e.g., whether an attack would happen or not), but not at the specific steps that an attacker would undertake. To fill this gap we present Tiresias, a system that leverages Recurrent Neural Networks (RNNs) to predict future events on a machine, based on previous observations. We test Tiresias on a dataset of 3.4 billion security events collected from a commercial intrusion prevention system, and show that our approach is effective in predicting the next event that will occur on a machine with a precision of up to 0.93. We also show that the models learned by Tiresias are reasonably stable over time, and provide a mechanism that can identify sudden drops in precision and trigger a retraining of the system. Finally, we show that the long-term memory typical of RNNs is key in performing event prediction, rendering simpler methods not up to the task

Sequence analysis of an Archaeal virus isolated from a hypersaline lake in Inner Mongolia, China

<p>Abstract</p> <p>Background</p> <p>We are profoundly ignorant about the diversity of viruses that infect the domain <it>Archaea</it>. Less than 100 have been identified and described and very few of these have had their genomic sequences determined. Here we report the genomic sequence of a previously undescribed archaeal virus.</p> <p>Results</p> <p>Haloarchaeal strains with 16S rRNA gene sequences 98% identical to <it>Halorubrum saccharovorum </it>were isolated from a hypersaline lake in Inner Mongolia. Two lytic viruses infecting these were isolated from the lake water. The BJ1 virus is described in this paper. It has an icosahedral head and tail morphology and most likely a linear double stranded DNA genome exhibiting terminal redundancy. Its genome sequence has 42,271 base pairs with a GC content of ~65 mol%. The genome of BJ1 is predicted to encode 70 ORFs, including one for a tRNA. Fifty of the seventy ORFs had no identity to data base entries; twenty showed sequence identity matches to archaeal viruses and to haloarchaea. ORFs possibly coding for an origin of replication complex, integrase, helicase and structural capsid proteins were identified. Evidence for viral integration was obtained.</p> <p>Conclusion</p> <p>The virus described here has a very low sequence identity to any previously described virus. Fifty of the seventy ORFs could not be annotated in any way based on amino acid identities with sequences already present in the databases. Determining functions for ORFs such as these is probably easier using a simple virus as a model system.</p

Bellway Homes "The Future Home" Baseline Performance Report

This report examines the fabric thermal performance of a prototype home (The Future Home, or TFH) built by Bellway Homes. The home was designed and built to meet the anticipated Future Homes Standard in terms of fabric performance. The research was carried out under controlled conditions at the Energy House 2.0 facility at the University of Salford (UK). The aim of the research was to characterise the building and identify any gaps between the design values and the actual performance.The researchers examined the whole house heat loss, measured U-values, and the airtightness characteristics of the home. The overall fabric heat loss of TFH was 7.7% worse than the SAP design model predicted, a significant contribution to this underperformance was the measured air permeability of TFH, which was found to be worse 61% than the design. However when this whole house heat loss is compared to other studies on new build homes then this is considered to be well performing

Saint Gobain & Barratt Developments “eHome2” Baseline Performance Report

This report examines the fabric thermal performance of a prototype home (eHome2) built through a partnership with Saint Gobain and Barratt homes. The home was designed and built to meet the anticipated Future Homes Standard in terms of fabric performance. The research was carried out under controlled conditions at the Energy House 2.0 facility at the University of Salford (UK). The aim of the research was to characterise the building and identify any gaps between the design values and the actual performance.The researchers examined the whole house heat loss, measured U-values, and the airtightness characteristics of the home. The overall fabric heat loss of eHome2 was 3.9% worse than the SAP design model predicted, the majority of the 3.9% difference was due to the plane element heat loss, such as walls, roofs, doors, and windows, being greater than the design value. The measured air permeability of eHome2, was found to be better than the design, with an over-performance of 6.3%. When this whole house heat loss is compared to other studies on new build homes then this is considered to be well performing