A matter of (good) faith?:Understanding the interplay of power and the moral agency of managers in healthcare service reconfiguration

Previous studies of service reconfiguration in healthcare have explored the influence of power on processes and outcomes. However, in these accounts the moral agency of managers is often underemphasised. This paper draws on the theoretical tools provided by the sociology of morality to help deepen understanding of the interaction between power and moral agency in service reconfiguration in healthcare. It presents results from a qualitative study of a pan-organisational service reconfiguration in the NHS in England, involving nineteen in-depth interviews with those leading the change and the analysis of twelve programme documents. We combine concepts of the moral background and epistemic governance to interpret participants' conviction that the service change was 'the right thing to do'. The paper shows how epistemic work carried out by service change regulations shaped the moral background within which participants worked. This, in turn, channelled their moral agency - specifically their commitment to patient care - in a way that also reflected central priorities. The paper adds to sociological understandings of service reconfiguration through considering the interaction of structure, agency and power, while also developing the concept of the moral background to show how power relations can influence moral beliefs.</p

Domestication as innovation : the entanglement of techniques, technology and chance in the domestication of cereal crops

The origins of agriculture involved pathways of domestication in which human behaviours and plant genetic adaptations were entangled. These changes resulted in consequences that were unintended at the start of the process. This paper highlights some of the key innovations in human behaviours, such as soil preparation, harvesting and threshing, and how these were coupled with genetic ‘innovations’ within plant populations. We identify a number of ‘traps’ for early cultivators, including the needs for extra labour expenditure on crop-processing and soil fertility maintenance, but also linked gains in terms of potential crop yields. Compilations of quantitative data across a few different crops for the traits of nonshattering and seed size are discussed in terms of the apparently slow process of domestication, and parallels and differences between different regional pathways are identified. We highlight the need to bridge the gap between a Neolithic archaeobotanical focus on domestication and a focus of later periods on crop-processing activities and labour organization. In addition, archaeobotanical data provide a basis for rethinking previous assumptions about how plant genetic data should be related to the origins of agriculture and we contrast two alternative hypotheses: gradual evolution with low selection pressure versus metastable equilibrium that prolonged the persistence of ‘semi-domesticated’ populations. Our revised understanding of the innovations involved in plant domestication highlight the need for new approaches to collecting, modelling and integrating genetic data and archaeobotanical evidence

Self-assembly of Microcapsules via Colloidal Bond Hybridization and Anisotropy

Particles with directional interactions are promising building blocks for new functional materials and may serve as models for biological structures. Mutually attractive nanoparticles that are deformable due to flexible surface groups, for example, may spontaneously order themselves into strings, sheets and large vesicles. Furthermore, anisotropic colloids with attractive patches can self-assemble into open lattices and colloidal equivalents of molecules and micelles. However, model systems that combine mutual attraction, anisotropy, and deformability have---to the best of our knowledge---not been realized. Here, we synthesize colloidal particles that combine these three characteristics and obtain self-assembled microcapsules. We propose that mutual attraction and deformability induce directional interactions via colloidal bond hybridization. Our particles contain both mutually attractive and repulsive surface groups that are flexible. Analogous to the simplest chemical bond, where two isotropic orbitals hybridize into the molecular orbital of H2, these flexible groups redistribute upon binding. Via colloidal bond hybridization, isotropic spheres self-assemble into planar monolayers, while anisotropic snowman-like particles self-assemble into hollow monolayer microcapsules. A modest change of the building blocks thus results in a significant leap in the complexity of the self-assembled structures. In other words, these relatively simple building blocks self-assemble into dramatically more complex structures than similar particles that are isotropic or non-deformable

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

Effects of Vacuum Annealing on the Conduction Characteristics of ZnO Nanosheets

This paper is open acess and available in full at http://www.nanoscalereslett.com/content/10/1/368 .ZnO nanosheets are a relatively new form of nanostructure and have demonstrated potential as gas-sensing devices and dye sensitised solar cells. For integration into other devices, and when used as gas sensors, the nanosheets are often heated. Here we study the effect of vacuum annealing on the electrical transport properties of ZnO nanosheets in order to understand the role of heating in device fabrication. A low cost, mass production method has been used for synthesis and characterisation is achieved using scanning electron microscopy (SEM), photoluminescence (PL), auger electron spectroscopy (AES) and nanoscale two-point probe. Before annealing, the measured nanosheet resistance displayed a non-linear increase with probe separation, attributed to surface contamination. Annealing to 300 °C removed this contamination giving a resistance drop, linear probe spacing dependence, increased grain size and a reduction in the number of n-type defects. Further annealing to 500 °C caused the n-type defect concentration to reduce further with a corresponding increase in nanosheet resistance not compensated by any further sintering. At 700 °C, the nanosheets partially disintegrated and the resistance increased and became less linear with probe separation. These effects need to be taken into account when using ZnO nanosheets in devices that require an annealing stage during fabrication or heating during use

Global online trade in primates for pets

The trade in primates as pets is a global enterprise and as access to the Internet has increased, so too has the trade of live primates online. While quantifying primate trade in physical markets is relatively straightforward, limited insights have been made into trade via the Internet. Here we followed a three-pronged approach to estimate the prevalence and ease of purchasing primates online in countries with different socioeconomic characteristics. We first conducted a literature review, in which we found that Malaysia, Thailand, the USA, Ukraine, South Africa, and Russia stood out in terms of the number of primate individuals being offered for sale as pets in the online trade. Then, we assessed the perceived ease of purchasing pet primates online in 77 countries, for which we found a positive relationship with the Internet Penetration Rate, total human population and Human Development Index, but not to Gross Domestic Product per capita or corruption levels of the countries. Using these results, we then predicted the levels of online primate trade in countries for which we did not have first-hand data. From this we created a global map of potential prevalence of primate trade online. Finally, we analysed price data of the two primate taxa most consistently offered for sale, marmosets and capuchins. We found that prices increased with the ease of purchasing primates online and the Gross Domestic Product per capita. This overview provides insight into the nature and intricacies of the online primate pet trade and advocates for increased trade regulation and monitoring in both primate range and non-range countries where trade has been substantially reported. © 2023 The Author

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation:A Multi-center, Multi-vendor, and Multi-disease Study

Background: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.Purpose: Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.Study type: Retrospective.Population: A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.Field Strength/Sequence: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.Assessment: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.Statistical Tests: Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of &lt;0.05 was considered statistically significant.Results: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.Data Conclusion: The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.Evidence Level: 4.Technical Efficacy: Stage 1.</p