Photosynthetic Response of Soybeans with Genetically Altered Chlorophyll

Author Institution: Department of Biological Sciences, Bowling Green State UniversityThe photosynthetic response of soybean plants (Glycine max (L.) Merr. Strain T219) at the start of a photoperiod showed that both normally pigmented plants (dark green) and chlorophyll-deficient plants (light green) had an induction period averaging 6 min, before a net CO2 uptake could be measured. The induction period was followed by a rapid increase in photosynthesis until a maximum rate was reached after 15 min and then gradually declined. Both chlorophyll content and ribulose diphosphate carboxylase activity were greatest in dark green plants. Plants tested at mid-day exhibited the highest carboxylase activity and plants assayed at mid-night the lowest activity. During the first 5 min of illumination (following a 12 hr dark period) the carboxylase activity increased 1.5 times in dark green and 1.9 times in light green plants. This indicated that initiation of the photoperiod enhanced ribulose diphosphate carboxylase activity

Interim Report on S3D/LEAPS Integration

The Naval Surface Warfare Center Carderock Division has created the Leading Edge Architecture for Prototyping Systems, or LEAPS, as the data repository for ship design, and a significant number of the early-stage ship design tools interface directly or through a translator with LEAPS. Separately, the Office of Naval Research has funded Smart Ship Systems Design (S3D), a ship design tool effort that expands the Navy’s toolkit to include simulation and distributed system design among other capabilities. The current project will integrate S3D with LEAPS. This report provides an interim status report on progress for the integration project. The project plan and use case are described, underlying terms are defined and correlated between the two databases, and the initial version of the translator code is described

Developing a methodology for social network sampling (abstract)

Researchers are increasingly turning to network theory to describe and understand the social nature of animal populations. To make use of the statistical tools of network theory, ecologists need to gather relational data, typically by sampling the social relations of a population of animals over a given time-period. Due to effort constraints and the practical difficulty involved in tracking animals, these sampled relational data are almost always a subset of the actual network. Measurements of the sample – such as average path length, clustering, and assortativity – are assumed to be informative as to the structure of the real-world social network. However, this assumption is problematic. Due to artefacts of the sampling process, the various network measures taken on the sample may be biased estimators of the true values. For example, just as we would get a biased estimate of mean human height by selecting for a sample those people who stood out in a crowd, we will get a biased estimate of a measure like mean connectivity if we sample individuals who are socially prominent. This problem can only be solved by developing a qualitative theory of network sampling, answering questions such as what proportion of the whole network needs to be sampled before a given level of accuracy is achieved, and what sampling procedures are least biased? To develop such a theory, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures. But currently available data on animal social networks are unsuitable as these networks were themselves sampled. The simulation methods of artificial life provide the way forward. We have developed a computational tool for generating artificial social networks that have user-defined distributions for network properties (such as the number of nodes, and the density) and for key the measures of interest to ecologists (such as the average degree, average path length, clustering, betweenness, and assortativity). This tool allows us to perform the required systematic analyses of the biases inherent in different sampling regimes (e.g., snowball sampling) applied to different network structures. We will present details of this system, and show we are using it to develop robust sampling methods for social network data. We see the system as the first in a series of works that will allow us to develop a qualitative theory of social network sampling to aid ecologists, and eventually social scientists, in their social network data collection

Multiple dispatch in practice

Multiple dispatch uses the run time types of more than one argument to a method call to determine which method body to run. While several languages over the last 20 years have provided multiple dispatch, most object-oriented languages still support only single dispatch — forcing programmers to implement multiple dispatch manually when required. This paper presents an empirical study of the use of multiple dispatch in practice, considering six languages that support multiple dispatch, and also investigating the potential for multiple dispatch in Java programs. We hope that this study will help programmers understand the uses and abuses of multiple dispatch; virtual machine implementors optimise multiple dispatch; and language designers to evaluate the choice of providing multiple dispatch in new programming languages

Detection of a Substantial Molecular Gas Reservoir in a brightest cluster galaxy at z = 1.7

We report the detection of CO(2-1) emission coincident with the brightest cluster galaxy (BCG) of the high-redshift galaxy cluster SpARCS1049+56, with the Redshift Search Receiver (RSR) on the Large Millimetre Telescope (LMT). We confirm a spectroscopic redshift for the gas of z = 1.7091+/-0.0004, which is consistent with the systemic redshift of the cluster galaxies of z = 1.709. The line is well-fit by a single component Gaussian with a RSR resolution-corrected FWHM of 569+/-63 km/s. We see no evidence for multiple velocity components in the gas, as might be expected from the multiple image components seen in near-infrared imaging with the Hubble Space Telescope. We measure the integrated flux of the line to be 3.6+/-0.3 Jy km/s and, using alpha_CO = 0.8 Msun (K km s^-1 pc^2)^-1 we estimate a total molecular gas mass of 1.1+/-0.1x10^11 Msun and a M_H2/M_star ~ 0.4. This is the largest gas reservoir detected in a BCG above z > 1 to date. Given the infrared-estimated star formation rate of 860+/-130 Msun/yr, this corresponds to a gas depletion timescale of ~0.1Gyr. We discuss several possible mechanisms for depositing such a large gas reservoir to the cluster center -- e.g., a cooling flow, a major galaxy-galaxy merger or the stripping of gas from several galaxies -- but conclude that these LMT data are not sufficient to differentiate between them.Comment: accepted for publication in ApJ Letter

Bifurcations of discrete breathers in a diatomic Fermi-Pasta-Ulam chain

Discrete breathers are time-periodic, spatially localized solutions of the equations of motion for a system of classical degrees of freedom interacting on a lattice. Such solutions are investigated for a diatomic Fermi-Pasta-Ulam chain, i. e., a chain of alternate heavy and light masses coupled by anharmonic forces. For hard interaction potentials, discrete breathers in this model are known to exist either as ``optic breathers'' with frequencies above the optic band, or as ``acoustic breathers'' with frequencies in the gap between the acoustic and the optic band. In this paper, bifurcations between different types of discrete breathers are found numerically, with the mass ratio m and the breather frequency omega as bifurcation parameters. We identify a period tripling bifurcation around optic breathers, which leads to new breather solutions with frequencies in the gap, and a second local bifurcation around acoustic breathers. These results provide new breather solutions of the FPU system which interpolate between the classical acoustic and optic modes. The two bifurcation lines originate from a particular ``corner'' in parameter space (omega,m). As parameters lie near this corner, we prove by means of a center manifold reduction that small amplitude solutions can be described by a four-dimensional reversible map. This allows us to derive formally a continuum limit differential equation which characterizes at leading order the numerically observed bifurcations.Comment: 30 pages, 10 figure

The development, application and analysis of an enhanced recovery programme for major oesophagogastric resection

Background: Enhanced recovery programmes improve outcomes in surgery, but their implementation after upper gastrointestinal resection has been limited. The aim of this study was to compare short-term outcomes for patients undergoing oesophagogastric surgery in an enhanced recovery programme (EROS). Methods: EROS was developed after a multidisciplinary meeting by multiple rounds of revision. EROS was applied to all patients undergoing major upper GI resection at a university teaching hospital in the UK from 20/9/13, with data reviewed at 18/09/15. EROS was assessed to identify predictors for compliance. Results: One hundred six patients underwent major upper GI resection including 81 oesophagectomies, 24 gastrectomies and 1 colonic interposition graft. Major complications (ClavienDindo≥3) occurred in 12 patients with 1 in-hospital death. Thirty-five patients (44%) were discharged on target day 8 of the EROS programme. Age and complications were independently associated with missing this discharge target. Conclusion: Enhanced recovery is feasible and safe after major upper gastrointestinal surgery.<br/

Apparent Loss of Vibrio vulnificus from North Carolina Oysters Coincides with a Drought-Induced Increase in Salinity

ABSTRACT Despite years of successful isolation of Vibrio vulnificus from estuarine waters, beginning in 2007, it was extremely difficult to culture V. vulnificus from either North Carolina estuarine water or oyster samples. After employing culture-based methods as well as PCR and quantitative PCR for the detection of V. vulnificus , always with negative results, we concluded that this pathogen had become nearly undetectable in the North Carolina estuarine ecosystem. We ensured that the techniques were sound by seeding North Carolina oysters with V. vulnificus and performing the same tests as those previously conducted on unadulterated oysters. V. vulnificus was readily detected in the seeded oysters using both classes of methods. Furthermore, oysters were obtained from the Gulf of Mexico, and V. vulnificus was easily isolated, confirming that the methodology was sound but that the oysters and waters of North Carolina were lacking the V. vulnificus population studied for decades. Strikingly, the apparent loss of detectable V. vulnificus coincided with the most severe drought in the history of North Carolina. The drought continued until the end of 2009, with an elevated water column salinity being observed throughout this period and with V. vulnificus being nearly nonexistent. When salinities returned to normal after the drought abated in 2010, we were again able to routinely isolate V. vulnificus from the water column, although we were still unable to culture it from oysters. We suggest that the oysters were colonized with a more salt-tolerant bacterium during the drought, which displaced V. vulnificus and may be preventing recolonization

Variability between human experts and artificial intelligence in identification of anatomical structures by ultrasound in regional anaesthesia: a framework for evaluation of assistive artificial intelligence

Background: ScanNavTM Anatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-time B-mode ultrasound to highlight key anatomical structures for regional anaesthesia. This study compares consistency of identification of sono-anatomical structures between expert ultrasonographers and ScanNav™. Methods: Nineteen experts in ultrasound-guided regional anaesthesia (UGRA) annotated 100 structures in 30 ultrasound videos across six anatomical regions. These annotations were compared with each other to produce a quantitative assessment of the level of agreement amongst human experts. The AI colour overlay was then compared with all expert annotations. Differences in human–human and human–AI agreement are presented for each structure class (artery, muscle, nerve, fascia/serosal plane) and structure. Clinical context is provided through subjective assessment data from UGRA experts. Results: For human–human and human–AI annotations, agreement was highest for arteries (mean Dice score 0.88/0.86), then muscles (0.80/0.77), and lowest for nerves (0.48/0.41). Wide discrepancy exists in consistency for different structures, both with human–human and human–AI comparisons; highest for sartorius muscle (0.91/0.92) and lowest for the radial nerve (0.21/0.27). Conclusions: Human experts and the AI system both showed the same pattern of agreement in sono-anatomical structure identification. The clinical significance of the differences presented must be explored; however the perception that human expert opinion is uniform must be challenged. Elements of this assessment framework could be used for other devices to allow consistent evaluations that inform clinical training and practice. Anaesthetists should be actively engaged in the development and adoption of new AI technology

The role of caretakers in disease dynamics

One of the key challenges in modeling the dynamics of contagion phenomena is to understand how the structure of social interactions shapes the time course of a disease. Complex network theory has provided significant advances in this context. However, awareness of an epidemic in a population typically yields behavioral changes that correspond to changes in the network structure on which the disease evolves. This feedback mechanism has not been investigated in depth. For example, one would intuitively expect susceptible individuals to avoid other infecteds. However, doctors treating patients or parents tending sick children may also increase the amount of contact made with an infecteds, in an effort to speed up recovery but also exposing themselves to higher risks of infection. We study the role of these caretaker links in an adaptive network models where individuals react to a disease by increasing or decreasing the amount of contact they make with infected individuals. We find that pure avoidance, with only few caretaker links, is the best strategy for curtailing an SIS disease in networks that possess a large topological variability. In more homogeneous networks, disease prevalence is decreased for low concentrations of caretakers whereas a high prevalence emerges if caretaker concentration passes a well defined critical value.Comment: 8 pages, 9 figure