Harnessing single board computers for military data analytics

Executive summary: This chapter covers the use of Single Board Computers (SBCs) to expedite onsite data analytics for a variety of military applications. Onsite data summarization and analytics is increasingly critical for command, control, and intelligence (C2I) operations, as excessive power consumption and communication latency can restrict the efficacy of down-range operations. SBCs offer power-efficient, inexpensive data-processing capabilities while maintaining a small form factor. We discuss the use of SBCs in a variety of domains, including wireless sensor networks, unmanned vehicles, and cluster computing. We conclude with a discussion of existing challenges and opportunities for future use.https://digitalcommons.usmalibrary.org/books/1010/thumbnail.jp

A repeat cross-sectional study examining the equitable impact of nutritional standards for school lunches in England in 2008 on the diets of 4-7y olds across the socio-economic spectrum

BACKGROUND: The 2008 nutritional standards for primary school lunch in England improved nutritional content. The impact on socio-economic inequalities is unknown. We examine the impact of the nutritional standards on children’s nutrient intake at lunchtime and in total diet by level of deprivation. METHODS: We conducted cross-sectional studies in 12 English primary schools before and after legislation. Dietary intake was recorded for 4-7y olds using a validated, prospective four-day food diary. Socio-economic status was estimated using the Index of Multiple Deprivation; three groups of approximately equal sizes were created. Linear, mixed-effect models explored the effect of year, lunch type (school or home-packed lunch), level of deprivation and the interaction(s) between these factors on children’s diets. RESULTS: 368 and 624 children participated in 2003–4 and 2008–9 respectively. At lunchtime, between 2003–4 and 2008–9, the increase in non-starch polysaccharide (NSP) intake was larger in the least compared to the most deprived group (difference in mean change 0.8 mg; 95% CI 0.4, 1.3). There were similar differences in mean changes for iron (0.3 mg; 0.2, 0.4) and zinc (0.3 mg; 0.1, 0.5). In total diet, differential effects were observed for NSP, iron and zinc; we found no evidence these changes were associated with lunch type. Lunch type was associated with changes in per cent energy from non-milk-extrinsic sugars (NMES) and vitamin C. Per cent energy from NMES was lower and vitamin C intake higher in school lunches in 2008–9 compared with 2003–4. The corresponding differences in home-packed lunches were not as marked and there were subtle but statistically significant effects of the level of deprivation. CONCLUSIONS: By 2008–9, NMES at lunchtime and in total diet was lower for children consuming a school lunch; this change was equitable across the deprivation groups. Vitamin C intake increased more for children in the most deprived group, narrowing the socio-economic inequality. A range of significant differential effects of the nutritional standards were observed and important socio-economic inequalities in dietary intake remain. Additional interventions to promote equitable nutrition in children are needed to support legislative measures and maximise their impact

MOST Observations of the Flare Star AD Leo

We present continuous, high-precision photometric monitoring data with 1 minute cadence of the dM3e flare star AD Leo with the {\it MOST} satellite. We observed 19 flares in 5.8 days, and find a flare frequency distribution that is similar to previous studies. The light curve reveals a sinusoidal modulation with period of $2.23^{+0.36}_{-0.27}$ days that we attribute to the rotation of a stellar spot rotating into and out of view. We see no correlation between the occurrence of flares and rotational phase, indicating that there may be many spots distributed at different longitudes, or possibly that the modulation is caused by varying surface coverage of a large polar spot that is viewed nearly pole-on. The data show no correlation between flare energy and the time since the previous flare. We use these results to reject a simple model in which all magnetic energy is stored in one active region and released only during flares.Comment: 20 Pages, 8 Figures, PASP Accepte

An efficient and extensible approach for compressing phylogenetic trees

Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. TreeZip is a novel method for compressing phylogenetic trees. Recently, we extended our TreeZip algorithm to support branch lengths and show how it can be used to extract sets of trees of interest quickly. The key advantage of TreeZip over standard compression methods like 7zip is its ability to interpret and compress tree collections semantically, making it immune to branch rotations and allowing key operations (such calculating a consensus tree) to be performed quickly and without a loss of space savings. On unweighted phylogenetic trees, TreeZip is able to compress Newick files in excess of 98%. On weighted phylogenetic trees, TreeZip is able to compress a Newick file by at least 73%. TreeZip can be combined with 7zip with little overhead, allowing space savings in excess of 99 % (unweighted) and 92%(weighted). Unlike TreeZip, 7zip is not immune to branch rotations, and performs worse as the level of variability in the Newick string representation increases. Finally, since the TreeZip compressed text (TRZ) file contains all the semantic information in a collection of trees, we can easily filter and decompress a subset of trees of interest (such as the set of unique trees), or build the resulting consensus tree in a matter of seconds. We also show the ease of which set operations can be performed on TRZ files, at speeds quicker than those performed on Newick or 7zip compressed Newick files, and without loss of space savings. TreeZip is an efficient approach for compressing large collections of phylogenetic trees. The semantic and compact nature of the TRZ file allow it to be operated upon directly and quickly, without a need to decompress the original Newick file. We believe that TreeZip will be vital for compressing and archiving trees in the biological community.

MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees

<p>Abstract</p> <p>Background</p> <p>MapReduce is a parallel framework that has been used effectively to design large-scale parallel applications for large computing clusters. In this paper, we evaluate the viability of the MapReduce framework for designing phylogenetic applications. The problem of interest is generating the all-to-all Robinson-Foulds distance matrix, which has many applications for visualizing and clustering large collections of evolutionary trees. We introduce MrsRF (<it>MapReduce Speeds up RF</it>), a multi-core algorithm to generate a <it>t </it>× <it>t </it>Robinson-Foulds distance matrix between <it>t </it>trees using the MapReduce paradigm.</p> <p>Results</p> <p>We studied the performance of our MrsRF algorithm on two large biological trees sets consisting of 20,000 trees of 150 taxa each and 33,306 trees of 567 taxa each. Our experiments show that MrsRF is a scalable approach reaching a speedup of over 18 on 32 total cores. Our results also show that achieving top speedup on a multi-core cluster requires different cluster configurations. Finally, we show how to use an RF matrix to summarize collections of phylogenetic trees visually.</p> <p>Conclusion</p> <p>Our results show that MapReduce is a promising paradigm for developing multi-core phylogenetic applications. The results also demonstrate that different multi-core configurations must be tested in order to obtain optimum performance. We conclude that RF matrices play a critical role in developing techniques to summarize large collections of trees.</p

Patient-derived xenograft models of ALK+ ALCL reveal preclinical promise for therapy with brigatinib

Anaplastic large-cell lymphoma (ALCL) is a T-cell malignancy predominantly driven by the oncogenic anaplastic lymphoma kinase (ALK), accounting for approximately 15% of all paediatric non-Hodgkin lymphoma. Patients with central nervous system (CNS) relapse are particularly difficult to treat with a 3-year overall survival of 49% and a median survival of 23.5 months. The second-generation ALK inhibitor brigatinib shows superior penetration of the blood–brain barrier unlike the first-generation drug crizotinib and has shown promising results in ALK+ non-small-cell lung cancer. However, the benefits of brigatinib in treating aggressive paediatric ALK+ ALCL are largely unknown. We established a patient-derived xenograft (PDX) resource from ALK+ ALCL patients at or before CNS relapse serving as models to facilitate the development of future therapies. We show in vivo that brigatinib is effective in inducing the remission of PDX models of crizotinib-resistant (ALK C1156Y, TP53 loss) ALCL and furthermore that it is superior to crizotinib as a second-line approach to the treatment of a standard chemotherapy relapsed/refractory ALCL PDX pointing to brigatinib as a future therapeutic option.</p

High resolution spatial modelling of greenhouse gas emissions from land use change to energy crops in the UK

We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land-use transitions from existing land use, rotational cropland, permanent grassland or woodland, to six bioenergy crops; three ‘first-generation’ energy crops: oilseed rape, wheat and sugar beet, and three ‘second-generation’ energy crops: Miscanthus, short rotation coppice willow (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest beneficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio-physical factors (e.g. the energy density of the crop) and socio-economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation

How can onchocerciasis elimination in Africa be accelerated? Modelling the impact of increased ivermectin treatment frequency and complementary vector control

Background: Great strides have been made toward onchocerciasis elimination by mass drug administration (MDA) of ivermectin. Focusing on MDA-eligible areas, we investigated where the elimination goal can be achieved by 2025 by continuation of current practice (annual MDA with ivermectin) and where intensification or additional vector control is required. We did not consider areas hypoendemic for onchocerciasis with loiasis coendemicity where MDA is contraindicated. Methods: We used 2 previously published mathematical models, ONCHOSIM and EPIONCHO, to simulate future trends in microfilarial prevalence for 80 different settings (defined by precontrol endemicity and past MDA frequency and coverage) under different future treatment scenarios (annual, biannual, or quarterly MDA with different treatment coverage through 2025, with or without vector control strategies), assessing for each strategy whether it eventually leads to elimination. Results: Areas with 40%–50% precontrol microfilarial prevalence and ≥10 years of annual MDA may achieve elimination with a further 7 years of annual MDA, if not achieved already, according to both models. For most areas with 70%–80% precontrol prevalence, ONCHOSIM predicts that either annual or biannual MDA is sufficient to achieve elimination by 2025, whereas EPIONCHO predicts that elimination will not be achieved even with complementary vector control. Conclusions: Whether elimination will be reached by 2025 depends on precontrol endemicity, control history, and strategies chosen from now until 2025. Biannual or quarterly MDA will accelerate progress toward elimination but cannot guarantee it by 2025 in high-endemicity areas. Long-term concomitant MDA and vector control for high-endemicity areas might be useful

Structure-Guided Evolution of Potent and Selective CHK1 Inhibitors through Scaffold Morphing

Pyrazolopyridine inhibitors with low micromolar potency for CHK1 and good selectivity against CHK2 were previously identified by fragment-based screening. The optimization of the pyrazolopyridines to a series of potent and CHK1-selective isoquinolines demonstrates how fragment-growing and scaffold morphing strategies arising from a structure-based understanding of CHK1 inhibitor binding can be combined to successfully progress fragment-derived hit matter to compounds with activity in vivo. The challenges of improving CHK1 potency and selectivity, addressing synthetic tractability, and achieving novelty in the crowded kinase inhibitor chemical space were tackled by multiple scaffold morphing steps, which progressed through tricyclic pyrimido[2,3-b]azaindoles to N-(pyrazin-2-yl)pyrimidin-4-amines and ultimately to imidazo[4,5-c]pyridines and isoquinolines. A potent and highly selective isoquinoline CHK1 inhibitor (SAR-020106) was identified, which potentiated the efficacies of irinotecan and gemcitabine in SW620 human colon carcinoma xenografts in nude mice

The role of mathematical modelling in understanding the epidemiology and control of sheep transmissible spongiform encephalopathies: a review

To deal with the incompleteness of observations and disentangle the complexities of transmission much use has been made of mathematical modelling when investigating the epidemiology of sheep transmissible spongiform encephalopathies (TSE) and, in particular, scrapie. Importantly, these modelling approaches allow the incidence of clinical disease to be related to the underlying prevalence of infection, thereby overcoming one of the major difficulties when studying these diseases. Models have been used to investigate the epidemiology of scrapie within individual flocks and at a regional level; to assess the efficacy of different control strategies, especially selective breeding programmes based on prion protein (PrP) genotype; to interpret the results of scrapie surveillance; and to inform the design of surveillance programmes. Furthermore, mathematical modelling has played an important role when assessing the risk to human health posed by the possible presence of bovine spongiform encephalopathy in sheep. Here, we review the various approaches that have been taken when developing and analysing mathematical models for the epidemiology and control of sheep TSE and assess their impact on our understanding of these diseases. We also identify areas that require further work, discuss future challenges and identify data gaps