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The Narratives of Neurodiversity Network (NNN) is a neurodivergent academic, creative, and educator collective that came together with allies during the Covid‐19 pandemic to create a network centred around emerging narratives about neuro-diversity and exploring new ways of learning and socialising. The network focuses on exploring the roles of written, spoken, and visual narratives across cultural locations about neuro‐atypical experiences in generating improved agency and self‐advocacy for those who have been subject to pathologization through neuro‐normativity and intersecting oppression. During the last year, widening access to digital platforms has provided a space to explore these issues outside of traditional academic spaces. We run a monthly “Salon,” our mixed‐media “reading, listening, and watching” group, in an effort to find positive representation within contemporary culture. Discussions have moved beyond mimesis and into a consideration of how narrative and storyworlds can question the supposed naturalness of certain ways of being in and perceiving the world. This article interrogates the network’s core principles of nonhierarchical co‐production, including the roles of creativity, community, identity, and emancipatory research which were animated by the new techno‐social context. We consider the cultural lives of neurodiversity in the West and beyond, including ethical and aesthetic dimensions. We share a faith in the power of storytelling to inform new social identities for neurodivergent people and to inform scientific understandings of atypical cognition. In exploring this, we speak through a porous first‐person plural narrator, to unsettle the idea that there is a hegemonic “we” speaking on behalf of all neurodivergent people.

Interior permanent magnet (IPM) motors in traction applications often employ discrete rotor skewing constructions to reduce torsional excitations and back-EMF harmonics. Although skewing is very effective in reducing cogging torque, the impact on torque ripple is not well understood and can vary significantly over the operating envelope of a motor. Skewing also leads to the creation of a non-zero axial force that may compromise the bearing life if not considered. This paper introduces a holistic methodology for analyzing the effect of skewing, aiming to minimize torsional excitations, axial forces and back-EMF harmonics whilst mitigating the impact on performance and costs. Firstly, analytical models are employed for calculating cogging torque, torque ripple and axial forces. Then, 2D and 3D finite element analysis are used to incorporate the influence of non-linear material behavior. A detailed structural model of the powertrain is employed to calculate the radiated noise and identify key areas allowing a motor designer to reduce noise, vibration and harshness (NVH). A meticulous selection process for the skewing angle, the number of skew stacks and the orientation of skew stacks is developed, giving particular attention to the effect of the selected pattern on NVH in both forward and reverse rotating directions.

Using reverse non-equilibrium molecular dynamics simulations, we have determined the dependences on temperature and pressure of the thermal conductivity tensors for the monoclinic γ and ɛ polymorphs of hexanitrohexaazaisowurtzitane (HNIW or CL20). A recently developed non-reactive force field [X. Bidault and S. Chaudhuri, RSC Adv. 9, 39649–39661 (2019)], designed to study polymorphism and phase transitions in CL20, is employed. The effects of temperature and pressure are investigated between 200 and 500 K and up to 0.5 GPa for γ-CL20 and 2 GPa for ɛ-CL20. In order to obtain the full thermal conductivity tensor, κij, for the monoclinic crystals, four distinct heat propagation directions are used. We find that κij for both polymorphs is more isotropic than for other energetic molecular crystals, including α- and γ-RDX, β-HMX, and PETN, with a maximum difference of 9.8% between orientations observed at 300 K and 0 GPa for γ-CL20 and a maximum difference of 4.8% for ɛ-CL20. The average thermal conductivity, κ̄, of ɛ-CL20 is 6.4% larger than that of γ-CL20 at 300 K and 0 GPa. Analytic linear functions of the inverse temperature and the pressure are provided, which fit the data well and can be used to predict the thermal conductivity of both polymorphs for any orientation, pressure, and temperature in and around the fitting range. Our predictions agree reasonably well with the limited available experimental data, for which the polymorph type is unknown.

The clinical course of chronic lymphocytic leukaemia (CLL) is variable and difficult to predict. Here, the authors conduct a genome wide association study meta-analysis for time to first treatment in CLL patients and report two loci associating with progressive disease.

New Zealand students in the middle and upper school achieve better results in reading than they do in writing. This claim is evident in national assessment data reporting on students' literacy achievement. Research findings also state that teachers report a lack of confidence when teaching writing. Drawing on the National Writing Project developed in the USA, a team of researchers from the University of Waikato (New Zealand) and teachers from primary and secondary schools in the region collaborated to "talk" and "do" writing by building a community of practice. The effects of writing workshop experiences and the transformation this has on teachers' professional identities, self-efficacy, and their students' learning provided the research focus. This paper draws mostly on data collected during the first cycle of the two-year project. It discusses the influence of peer group response--a case study teacher's workshop experiences that transformed her professional identity, building her confidence and deepening her understandings of self as writer and ultimately transforming this expertise into her writing classroom practice. (Contains 2 figures and 3 footnotes.)

Abstract Background Readmission after discharge from a hospital is disruptive and costly, regardless of the reason. However, it can be particularly problematic for psychiatric patients, so predicting which patients may be readmitted is critically important but also very difficult. Clinical narratives in psychiatric electronic health records (EHRs) span a wide range of topics and vocabulary; therefore, a psychiatric readmission prediction model must begin with a robust and interpretable topic extraction component. Results We designed and evaluated multiple multilayer perceptron and radial basis function neural networks to predict the sentences in a patient’s EHR that are associated with one or more of seven readmission risk factor domains that we identified. In contrast to our baseline cosine similarity model that is based on the methodologies of prior works, our deep learning approaches achieved considerably better F1 scores (0.83 vs 0.66) while also being more scalable and computationally efficient with large volumes of data. Additionally, we found that integrating clinically relevant multiword expressions during preprocessing improves the accuracy of our models and allows for identifying a wider scope of training data in a semi-supervised setting. Conclusion We created a data pipeline for using document vector similarity metrics to perform topic extraction on psychiatric EHR data in service of our long-term goal of creating a readmission risk classifier. We show results for our topic extraction model and identify additional features we will be incorporating in the future.

Using novel virtual cities, we investigated the influence of verbal and visual strategies on the encoding of navigation-relevant information in a large-scale virtual environment. In 2 experiments, participants watched videos of routes through 4 virtual cities and were subsequently tested on their memory for observed landmarks and their ability to make judgments regarding the relative directions of the different landmarks along the route. In the first experiment, self-report questionnaires measuring visual and verbal cognitive styles were administered to examine correlations between cognitive styles, landmark recognition, and judgments of relative direction. Results demonstrate a tradeoff in which the verbal cognitive style is more beneficial for recognizing individual landmarks than for judging relative directions between them, whereas the visual cognitive style is more beneficial for judging relative directions than for landmark recognition. In a second experiment, we manipulated the use of verbal and visual strategies by varying task instructions given to separate groups of participants. Results confirm that a verbal strategy benefits landmark memory, whereas a visual strategy benefits judgments of relative direction. The manipulation of strategy by altering task instructions appears to trump individual differences in cognitive style. Taken together, we find that processing different details during route encoding, whether due to individual proclivities (Experiment 1) or task instructions (Experiment 2), results in benefits for different components of navigation-relevant information. These findings also highlight the value of considering multiple sources of individual differences as part of spatial cognition investigations.

Mapping heterogeneity of the ocean’s surface waters is important for understanding biogeographical distributions, ocean surface habitat mapping, and ocean surface stability. This article describes the Ocean-surface Heterogeneity MApping (OHMA) algorithm—an objective, replicable approach that uses hypertemporal, satellite-derived datasets to map the spatio-temporal heterogeneity of ocean surface waters. The OHMA produces a suite of complementary datasets—a surface spatio-temporal heterogeneity dataset, and an optimised spatio-temporal classification of the ocean surface. It was demonstrated here using a hypertemporal Sea Surface Temperature image dataset of the North Atlantic. Validation with Underway-derived temperature data showed higher heterogeneity areas were associated with stronger surface temperature gradients, or an increased presence of locally extreme temperature values. Using four exploratory case studies, spatio-temporal heterogeneity values were related to a range of region-specific surface and sub-surface characteristics including fronts, currents and bathymetry. The values conveyed the interactions between these parameters as a single metric. Such over-arching heterogeneity information is virtually impossible to map from in-situ instruments, or less temporally dense satellite datasets. This study demonstrated the OHMA approach is a useful and robust tool to explore, examine, and describe the ocean’s surface. It advances our capability to map biologically relevant measures of ocean surface heterogeneity. It can support ongoing efforts in Ocean Surface Partitioning, and attempts to understand marine species distributions. The study highlighted the need to establish dedicated spatio-temporal ocean validation sites, specifically measured using surface transits, to support advances in hypertemporal ocean data use, and exploitation. A number of future research avenues are also highlighted.

Remote sensing of plant phenology as an indicator of climate change and for mapping land cover has received significant scientific interest in the past two decades. The advancing of spring events, the lengthening of the growing season, the shifting of tree lines, the decreasing sensitivity to warming and the uniformity of spring across elevations are a few of the important indicators of trends in phenology. The Sentinel-2 satellite sensors launched in June 2015 (A) and March 2017 (B), with their high temporal frequency and spatial resolution for improved land mapping missions, have contributed significantly to knowledge on vegetation over the last three years. However, despite the additional red-edge and short wave infra-red (SWIR) bands available on the Sentinel-2 multispectral instruments, with improved vegetation species detection capabilities, there has been very little research on their efficacy to track vegetation cover and its phenology. For example, out of approximately every four papers that analyse normalised difference vegetation index (NDVI) or enhanced vegetation index (EVI) derived from Sentinel-2 imagery, only one mentions either SWIR or the red-edge bands. Despite the short duration that the Sentinel-2 platforms have been operational, they have proved their potential in a wide range of phenological studies of crops, forests, natural grasslands, and other vegetated areas, and in particular through fusion of the data with those from other sensors, e.g., Sentinel-1, Landsat and MODIS. This review paper discusses the current state of vegetation phenology studies based on the first five years of Sentinel-2, their advantages, limitations, and the scope for future developments.

Introduction: The purpose of this study was to explore the relationship between social norms and attitudes towards ENDS and hookah and use of these products. Methods: We conducted surveys with hookah and ENDS users who regularly used the Internet and social media and analyzed the primary social media account (e.g. Facebook) of each participant, coding all references to nicotine or tobacco products. The survey included domains on perceived favorability, perceived vulnerability and subjective norms. Results: We surveyed 21 ENDS users and 20 hookah users. Both groups used the Internet to look up information about their respective tobacco product (95% for hookah vs. 90% for ENDS). Seventy percent of hookah users had references to hookah on their social media profiles while 43% of ENDS users had references to ENDS on their page. The majority of both groups were exposed to content posted by friends in their social media network about their respective products online. Those who posted on social media about hookah and those who read about ENDS online had lower perceived vulnerability to the health risks associated with tobacco products. Conclusions: Hookah and ENDS users actively use the Internet and social media to obtain and share information about nicotine/tobacco products. Study participants who use hookah were more likely to share photos and discuss hookah related activities via social media than those who use ENDS. Social networks also represent valuable and untapped potential resources for communicating with this group about risks and harm reduction related to emerging nicotine/tobacco products.

This article draws on early data from a two-year project (2009-11) being undertaken in the New Zealand context by the authors entitled: "Teachers as Writers: Transforming Professional Identity and Classroom Practice". Based on the National Writing Project in the USA (and in New Zealand in the 1980s) its hypothesis is that when teachers embrace the professional identity of writer, their practices as teachers of writing undergo a transformation that enhances the experience of and performance in the writing of their students. (Contains 4 tables and 7 notes.)

The offshore wind industry has seen unprecedented growth over the last few years. In line with this growth, there has been a push towards more exposed sites, farther from shore, in deeper water with consequent increased investor risk. There is therefore a growing need for accurate, reliable, met-ocean data to identify suitable sites, and from which to base preliminary design and investment decisions. This study investigates the potential of hyper-temporal satellite remote sensing Advanced Scatterometer (ASCAT) data in generating information necessary for the optimal site selection of offshore renewable energy infrastructure, and hence providing a cost-effective alternative to traditional techniques, such as in situ data from public or private entities and modelled data. Five years of the ASCAT 12.5 km wind product were validated against in situ weather buoys and showed a strong correlation with a Pearson coefficient of 0.95, when the in situ measurements were extrapolated with the log law. Temporal variations depicted by the ASCAT wind data followed the same inter-seasonal and intra-annual variations as the in situ measurements. A small diurnal bias of 0.12 m s−1 was observed between the descending swath (10:00 to 12:00) and the ascending swath (20:30 to 22:30), indicating that Ireland’s offshore wind speeds are slightly stronger in the daytime, especially in the nearshore areas. Seasonal maps showed that the highest spatial variability in offshore wind speeds are exhibited in winter and summer. The mean wind speed extrapolated at 80 m above sea level showed that Ireland’s mean offshore wind speeds at hub height ranged between 9.6 m s−1 and 12.3 m s−1. To best represent the offshore wind resource and its spatial distribution, an operational frequency map and a maximum yield frequency map were produced based on the ASCAT wind product in an offshore zone between 20 km and 200 km from the coast. The operational frequency indicates the percentage of time during which the observed local wind speed is between cut-in (3 m/s) and cut-out (25 m/s) for a standard turbine. The operational frequency map shows that the frequency of the wind speed within the cut-in and cut-off range of wind turbines was between 92.4% and 97.2%, while the maximum yield frequency map showed that between 40.6% and 59.5% of the wind speed frequency was included in the wind turbine rated power range. The results showed that the hyper-temporal ASCAT 12.5 km wind speed product (five consecutive years, two observations daily per satellite, two satellites) is representative of wind speeds measured by in situ measurements in Irish waters, and that its ability to depict temporal and spatial variability can assist in the decision-making process for offshore wind farm site selection in Ireland.

PURPOSE: We aimed to identify putative predictive protein biomarkers of radioresistance. EXPERIMENTAL DESIGN: Three breast cancer cell lines (MCF7, MDA-MB-231, and T47D) were used as in vitro models to study radioresistance. Inherent radiosensitivities were examined using a clonogenic survival assay. It was revealed that each cell line differed in their response to radiotherapy. These parental breast cancer cell lines were used to establish novel derivatives (MCF7RR, MDA-MB-231RR, and T47DRR) displaying significant resistance to ionizing radiation. Derivative cells were compared with parental cells to identify putative biomarkers associated with the radioresistant phenotype. To identify these biomarkers, complementary proteomic screening approaches were exploited encompassing two-dimensional gel electrophoresis in combination with mass spectrometry, liquid chromatography coupled with tandem mass spectrometry and quantitative proteomics using iTRAQ technology. RESULTS: A large number of potential biomarkers were identified, and several of these were confirmed using Western blot analysis. In particular, a decrease in the expression of the 26S proteasome was found in all radioresistant derivatives when compared with the respective parent cells. Decreased expression of this target was also found to be associated with radioresistant laryngeal tumors (P = .05) in a small pilot immunohistochemical study. CONCLUSIONS: These findings suggest that the 26S proteasome may provide a general predictive biomarker for radiotherapy outcome.