Visibility Representations of Boxes in 2.5 Dimensions

We initiate the study of 2.5D box visibility representations (2.5D-BR) where vertices are mapped to 3D boxes having the bottom face in the plane $z=0$ and edges are unobstructed lines of sight parallel to the $x$- or $y$-axis. We prove that: $(i)$ Every complete bipartite graph admits a 2.5D-BR; $(ii)$ The complete graph $K_n$ admits a 2.5D-BR if and only if $n \leq 19$; $(iii)$ Every graph with pathwidth at most $7$ admits a 2.5D-BR, which can be computed in linear time. We then turn our attention to 2.5D grid box representations (2.5D-GBR) which are 2.5D-BRs such that the bottom face of every box is a unit square at integer coordinates. We show that an $n$-vertex graph that admits a 2.5D-GBR has at most $4n - 6 \sqrt{n}$ edges and this bound is tight. Finally, we prove that deciding whether a given graph $G$ admits a 2.5D-GBR with a given footprint is NP-complete. The footprint of a 2.5D-BR $\Gamma$ is the set of bottom faces of the boxes in $\Gamma$.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

β-Lactam Effects on Mixed Cultures of Common Respiratory Isolates as an Approach to Treatment Effects on Nasopharyngeal Bacterial Population Dynamics

BACKGROUND: Streptococcus pneumoniae, Streptococcus pyogenes and Haemophilus influenzae are bacteria present in the nasopharynx as part of normal flora. The ecological equilibrium in the nasopharynx can be disrupted by the presence of antibiotics. METHODOLOGY/PRINCIPAL FINDINGS: A computerized two-compartment pharmacodynamic model was used to explore beta-lactam effects on the evolution over time of a bacterial load containing common pharyngeal isolates by simulating free serum concentrations obtained with amoxicillin (AMX) 875 mg tid, amoxicillin/clavulanic acid (AMC) 875/125 mg tid and cefditoren (CDN) 400 mg bid regimens over 24 h. Strains and MICs (microg/ml) of AMX, AMC and CDN were: S. pyogenes (0.03, 0.03 and 0.015), S. pneumoniae (2, 2 and 0.25), a beta-lactamase positive H. influenzae (BL(+); >16, 2 and 0.06) and a beta-lactamase positive AMC-resistant H. influenzae (BLPACR, >16, 8 and 0.06). Mixture of identical 1:1:1:1 volumes of each bacterial suspension were prepared yielding an inocula of approximately 4 x 10(6) cfu/ml. Antibiotic concentrations were measured both in bacterial and in bacteria-free antibiotic simulations. beta-lactamase production decreased AMX concentrations and fT(>MIC) against S. pneumoniae (from 43.2% to 17.7%) or S. pyogenes (from 99.9% to 24.9%), and eradication was precluded. The presence of clavulanic acid countered this effect of co-pathogenicity, and S. pyogenes (but not BL(+) and S. pneumoniae) was eradicated. Resistance of CDN to TEM beta-lactamase avoided this co-pathogenicity effect, and CDN eradicated S. pyogenes and H. influenzae strains (fT(>MIC) >58%), and reduced in 94% S. pneumoniae counts (fT(>MIC) approximately 25%). CONCLUSIONS/SIGNIFICANCE: Co-pathogenicity seems to be gradual since clavulanic acid countered this effect for strains very susceptible to AMX as S. pyogenes but not for strains with AMX MIC values in the limit of susceptibility as S. pneumoniae. There is a potential therapeutic advantage for beta-lactamase resistant cephalosporins with high activity against streptococci

Open access solutions for biodiversity journals : Do not replace one problem with another

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Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners.</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes.</p> <p>Results</p> <p>Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (<it>p </it>= 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported.</p> <p>Conclusions</p> <p>Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such as system design, user interface, local context, implementation strategy, and evaluate impact on user satisfaction and workflow, costs, and unintended consequences.</p

The scale, governance, and sustainability of central places in pre-Hispanic Mesoamerica

Examinations of the variation and relative successes or failures of past large-scale societies have long involved attempts to reconcile efforts at generalization and the identification of specific factors with explanatory value for regional trajectories. Although historical particulars are critical to understanding individual cases, there are both scholarly and policy rationales for drawing broader implications regarding the growing corpus of cross-cultural data germane to understanding variability in the constitution of human societies, past and present. Archaeologists have recently highlighted how successes and failures in communal-resource management can be studied over the long term through the material record to both engage and enhance transdisciplinary research on cooperation and collective action. In this article we consider frameworks that have been traditionally employed in studies of the rise, diversity, and fall of preindustrial urban aggregations. We suggest that a comparative theoretical perspective that foregrounds collective-action problems, unaligned individual and group interests, and the social mechanisms that promote or hamper cooperation advances our understanding of variability in these early cooperative arrangements. We apply such a perspective to an examination of pre-Hispanic Mesoamerican urban centers to demonstrate tendencies for more collective systems to be larger and longer lasting than less collective ones, likely reflecting greater sustainability in the face of the ecological and cultural perturbations specific to the region and era.Accepted manuscrip

Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007)

Computerised clinical decision support systems (CDSSs) are used widely to improve quality of care and patient outcomes. This systematic review evaluated the impact of CDSSs in targeting specific aspects of prescribing, namely initiating, monitoring and stopping therapy. We also examined the influence of clinical setting (institutional vs ambulatory care), system- or user-initiation of CDSS, multi-faceted vs stand alone CDSS interventions and clinical target on practice changes in line with the intent of the CDSS. We searched Medline, Embase and PsychINFO for publications from 1990-2007 detailing CDSS prescribing interventions. Pairs of independent reviewers extracted the key features and prescribing outcomes of methodologically adequate studies (experiments and strong quasi-experiments). 56 studies met our inclusion criteria, 38 addressing initiating, 23 monitoring and three stopping therapy. At the time of initiating therapy, CDSSs appear to be somewhat more effective after, rather than before, drug selection has occurred (7/12 versus 12/26 studies reporting statistically significant improvements in favour of CDSSs on = 50% of prescribing outcomes reported). CDSSs also appeared to be effective for monitoring therapy, particularly using laboratory test reminders (4/7 studies reporting significant improvements in favour of CDSSs on the majority of prescribing outcomes). None of the studies addressing stopping therapy demonstrated impacts in favour of CDSSs over comparators. The most consistently effective approaches used system-initiated advice to fine-tune existing therapy by making recommendations to improve patient safety, adjust the dose, duration or form of prescribed drugs or increase the laboratory testing rates for patients on long-term therapy. CDSSs appeared to perform better in institutional compared to ambulatory settings and when decision support was initiated automatically by the system as opposed to user initiation. CDSSs implemented with other strategies such as education were no more successful in improving prescribing than stand alone interventions. Cardiovascular disease was the most studied clinical target but few studies demonstrated significant improvements on the majority of prescribing outcomes. Our understanding of CDSS impacts on specific aspects of the prescribing process remains relatively limited. Future implementation should build on effective approaches including the use of system-initiated advice to address safety issues and improve the monitoring of therapy

Tracking human multiple myeloma xenografts in NOD-Rag-1/IL-2 receptor gamma chain-null mice with the novel biomarker AKAP-4

<p>Abstract</p> <p>Background</p> <p>Multiple myeloma (MM) is a fatal malignancy ranking second in prevalence among hematological tumors. Continuous efforts are being made to develop innovative and more effective treatments. The preclinical evaluation of new therapies relies on the use of murine models of the disease.</p> <p>Methods</p> <p>Here we describe a new MM animal model in NOD-Rag1null IL2rgnull (NRG) mice that supports the engraftment of cell lines and primary MM cells that can be tracked with the tumor antigen, AKAP-4.</p> <p>Results</p> <p>Human MM cell lines, U266 and H929, and primary MM cells were successfully engrafted in NRG mice after intravenous administration, and were found in the bone marrow, blood and spleen of tumor-challenged animals. The AKAP-4 expression pattern was similar to that of known MM markers, such as paraproteins, CD38 and CD45.</p> <p>Conclusions</p> <p>We developed for the first time a murine model allowing for the growth of both MM cell lines and primary cells in multifocal sites, thus mimicking the disease seen in patients. Additionally, we validated the use of AKAP-4 antigen to track tumor growth <it>in vivo </it>and to specifically identify MM cells in mouse tissues. We expect that our model will significantly improve the pre-clinical evaluation of new anti-myeloma therapies.</p