Future Reserves 2020: the British Army and the Politics of Military Innovation during the Cameron Era

This is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.Since 2001 there has been an increase in the use of reserve forces in conflicts sparking a number of organizational transformations when it comes to reserves. In Britain, the Future Reserves 2020 (FR2020) transformation was a cornerstone of recent defence policy. Yet, the scholarly work on military innovations has ignored reserve forces. This article examines why and how the recent attempt to transform the British Army Reserve was undertaken, and analyses its outcome. In doing so, this article contributes a major new case-study to the literature focused on civilian-directed peacetime innovation and the impact of intra-party and intra-service politics upon it. Firstly, we originally examine how intra-party political motivations were the primary initiator of the innovation. Secondly, contrary to previous intra-service rivalry explanations, we argue that our case is a compelling example of intra-service rivalry between components rather than branches, and over manpower and organizational structure rather than technology and visions of victory. Finally, addressing the lack of theory in innovation studies, we show how the transformation followed post-Fordist principles to address its political, ideological and financial drivers. We conclude that numerous innovation processes can be operant at different times, and that FR2020 has been frustrated by the interaction between these processes

Apparent Predation by Gray Jays, Perisoreus canadensis, on Long-toed Salamanders, Ambystoma macrodactylum, in the Oregon Cascade Range

We report observations of Gray Jays (Perisoreus canadensis) appearing to consume larval Long-toed Salamanders (Ambystoma macrodactylum) in a drying subalpine pond in Oregon, USA. Corvids are known to prey upon a variety of anuran amphibians, but to our knowledge, this is the first report of predation by any corvid on aquatic salamanders. Long-toed Salamanders appear palatable to Gray Jays, and may provide a food resource to Gray Jays when salamander larvae are concentrated in drying temporary ponds

Differential Uptake of Gold Nanoparticles by 2 Species of Tadpole, the Wood Frog (Lithobates Sylvaticus) and the Bullfrog (Lithobates Catesbeianus)

Engineered nanoparticles are aquatic contaminants of emerging concern that exert ecotoxicological effects on a wide variety of organisms. We exposed cetyltrimethylammonium bromide–capped spherical gold nanoparticles to wood frog and bullfrog tadpoles with conspecifics and in combination with the other species continuously for 21 d, then measured uptake and localization of gold. Wood frog tadpoles alone and in combination with bullfrog tadpoles took up significantly more gold than bullfrogs. Bullfrog tadpoles in combination with wood frogs took up significantly more gold than controls. The rank order of weight-normalized gold uptake was wood frogs in combination \u3e wood frogs alone \u3e bullfrogs in combination \u3e bullfrogs alone \u3e controls. In all gold-exposed groups of tadpoles, gold was concentrated in the anterior region compared with the posterior region of the body. The concentration of gold nanoparticles in the anterior region of wood frogs both alone and in combination with bullfrogs was significantly higher than the corresponding posterior regions. We also measured depuration time of gold in wood frogs. After 21 d in a solution of gold nanoparticles, tadpoles lost \u3e83% of internalized gold when placed in gold-free water for 5 d. After 10 d in gold-free water, tadpoles lost 94% of their gold. After 15 d, gold concentrations were below the level of detection. Our finding of differential uptake between closely related species living in similar habitats with overlapping geographical distributions argues against generalizing toxicological effects of nanoparticles for a large group of organisms based on measurements in only one species

Nanobiopsy investigation of the subcellular mtDNA heteroplasmy in human tissues

\ua9 The Author(s) 2024.Mitochondrial function is critical to continued cellular vitality and is an important contributor to a growing number of human diseases. Mitochondrial dysfunction is typically heterogeneous, mediated through the clonal expansion of mitochondrial DNA (mtDNA) variants in a subset of cells in a given tissue. To date, our understanding of the dynamics of clonal expansion of mtDNA variants has been technically limited to the single cell-level. Here, we report the use of nanobiopsy for subcellular sampling from human tissues, combined with next-generation sequencing to assess subcellular mtDNA mutation load in human tissue from mitochondrial disease patients. The ability to map mitochondrial mutation loads within individual cells of diseased tissue samples will further our understanding of mitochondrial genetic diseases

U.S. stock market interaction network as learned by the Boltzmann Machine

We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented analysis shows that binarization preserves market correlation structure. Properties of distributions of external fields and couplings as well as industry sector clustering structure are studied for different historical dates and moving window sizes. We found that a heavy positive tail in the distribution of couplings is responsible for the sparse market clustering structure. We also show that discrepancies between the model parameters might be used as a precursor of financial instabilities.Comment: 15 pages, 17 figures, 1 tabl

A Surveillance of the Causes of Mortality in Three South Dakota Layer Flocks

A surveillance program was conducted during June 1968 through June 1969 to determine the important causes of mortality in certain South Dakota layer flocks that experienced reasonably normal mortality

Bytes not waves: information communication technologies, global jihadism and counterterrorism

© The Author(s) 2020. Rapoport's conceptualization of the last, religious wave of four global waves remains highly influential. But it, and other typologies, have placed too little emphasis on the influence of information and communication technologies (ICTs) on the evolution of global jihadist activities. This article makes two new contributions by developing both a new ICT-based typology for understanding jihadist evolutions, and by focusing on successful attacks. Our central argument is that ICTs' impact on global jihadism has facilitated dramatic transformations of its strategy, organization and tactics since the 1990s, and that these can be understood as four overlapping iterations. ‘Jihadism 1.0’ describes the hierarchical, top-down directed and overseas financed and trained terrorist organizations that conducted iconic attacks at the turn of the millennium. Jihadism has since evolved into ‘Jihadism 2.0’ and then ‘Jihadism 3.0’. Jihadism 2.0 recognizes that a number of smaller, coordinated attacks can have a global impact. Jihadism 3.0 is inspired terrorism that has no links to the central terror organization, utilizing individuals and crude tactics. Finally, jihadism is evolving toward ‘Jihadism 4.0’, or cyberterrorism. We argue this typology provides a useful basis for scholars and practitioners to conceptualize the ICT dynamics influencing global jihadism, and these may be applicable to other global terrorists. The conclusion analyses how counter-terrorism services can respond to these evolutions and charts areas for future research.UK Research and Innovation Future Leaders Fellowship grant reference MR/S034412/1 and the GLOBSEC Intelligence Reform Initiativ

Short-chain fatty acid level and field cancerization show opposing associations with enteroendocrine cell number and neuropilin expression in patients with colorectal adenoma

BACKGROUND: Previous reports have suggested that the VEGF receptor neuropilin-1 (NRP-1) is expressed in a singly dispersed subpopulation of cells in the normal colonic epithelium, but that expression becomes dysregulated during colorectal carcinogenesis, with higher levels in tumour suggestive of a poor prognosis. We noted that the spatial distribution and morphology if NRP-1 expressing cells resembles that of enteroendocrine cells (EEC) which are altered in response to disease state including cancer and irritable bowel syndrome (IBS). We have shown that NRP-1 is down-regulated by butyrate in colon cancer cell lines in vitro and we hypothesized that butyrate produced in the lumen would have an analogous effect on the colon mucosa in vivo. Therefore we sought to investigate whether NRP-1 is expressed in EEC and how NRP-1 and EEC respond to butyrate and other short-chain fatty acids (SCFA - principally acetate and propionate). Additionally we sought to assess whether there is a field effect around adenomas. METHODOLOGY: Biopsies were collected at the mid-sigmoid, at the adenoma and at the contralateral wall (field) of 28 subjects during endoscopy. Samples were fixed for IHC and stained for either NRP-1 or for chromogranin A (CgA), a marker of EEC. Stool sampling was undertaken to assess individuals' butyrate, acetate and propionate levels. RESULT: NRP-1 expression was inversely related to SCFA concentration at the colon landmark (mid-sigmoid), but expression was lower and not related to SCFA concentration at the field. Likewise CgA+ cell number was also inversely related to SCFA at the landmark, but was lower and unresponsive at the field. Crypt cellularity was unaltered by field effect. A colocalisation analysis showed only a small subset of NRP-1 localised with CgA. Adenomas showed extensive, weaker staining for NRP-1 which contrastingly correlated positively with butyrate level. Field effects cause this relationship to be lost. Adenoma tissue shows dissociation of the co-regulation of NRP-1 and EEC. CONCLUSION: NRP-1 is inversely associated with levels of butyrate and other SCFA in vivo and is expressed in a subset of CgA expressing cells. EEC number is related to butyrate level in the same way

Prediction of bioconcentration factors in fish and invertebrates using machine learning

The application of machine learning has recently gained interest from ecotoxicological fields for its ability to model and predict chemical and/or biological processes, such as the prediction of bioconcentration. However, comparison of different models and the prediction of bioconcentration in invertebrates has not been previously evaluated. A comparison of 24 linear and machine learning models is presented herein for the prediction of bioconcentration in fish and important factors that influenced accumulation identified. R2 and root mean square error (RMSE) for the test data (n = 110 cases) ranged from 0.23–0.73 and 0.34–1.20, respectively. Model performance was critically assessed with neural networks and tree-based learners showing the best performance. An optimised 4-layer multi-layer perceptron (14 descriptors) was selected for further testing. The model was applied for cross-species prediction of bioconcentration in a freshwater invertebrate, Gammarus pulex. The model for G. pulex showed good performance with R2 of 0.99 and 0.93 for the verification and test data, respectively. Important molecular descriptors determined to influence bioconcentration were molecular mass (MW), octanol-water distribution coefficient (logD), topological polar surface area (TPSA) and number of nitrogen atoms (nN) among others. Modelling of hazard criteria such as PBT, showed potential to replace the need for animal testing. However, the use of machine learning models in the regulatory context has been minimal to date and is critically discussed herein. The movement away from experimental estimations of accumulation to in silico modelling would enable rapid prioritisation of contaminants that may pose a risk to environmental health and the food chain.</p