SYTO dyes and EvaGreen outperform SYBR Green in real-time PCR

Background: Real-time PCR can be carried out using either probes or DNA dyes. SYBR Green has been used the most, but it suffers from several drawbacks. Numerous other DNA dyes are commercially available, but with limited structural information. Dye behavior in real time PCR is difficult to predict, so empirical data are needed. In the work described here, a panel of 23 different DNA dyes–including green, orange, and red SYTO dyes, EvaGreen, and SYBR Green–were evaluated with respect to their performance in real time PCR. Findings: Data were analyzed for reaction inhibition, effects on amplicon melting temperature, fluorescent signal strength, and reaction efficiency. This is the first report of reaction efficiency using alternatives to SYBR Green. Results indicated substantial variation in performance even within the SYTO dye family. EvaGreen and the SYTO dyes 13, 16, 80, and 82 performed better than SYBR Green in general, and high reaction efficiencies can be achieved using these dyes. Conclusions: Empirical data were generated for 23 DNA dyes. This paper confirms and extends previous findings that among commercially available DNA dyes, EvaGreen and certain SYTO dyes are the most desirable alternatives to the commonly used SYBR Green in real-time PCR. Backgroun

Perceptual Cues and Subjective Organization in a Virtual Information Workspace

The key to effectively using the immense body of data on the Internet is an efficient method of organizing relevant information. Researchers and designers are beginning to promote the advantages of three-dimensional (3D) models of information storage and retrieval; however, the potential benefits of perceptual depth cues have not been systematically studied. The present study used a computer task to examine the effectiveness of three types of virtual desktops. A two-dimensional (2D) virtual desktop display, lacking in the cues that give the illusion of depth, was compared to two different 3D virtual desktops, both of which used perceptual cues to convey a sense of depth. One of the 3D desktop conditions conveyed motion parallax through an automatic rotation. It was expected that performance would increase as the number of perceptual cues increased. The present study also examined the potential benefits of organizing and retrieving documents from a subjectively organized versus a preconstructed, or fixed, information space. An organization that individuals create for their own use may be difficult for others to use. Thus, subjective organization of documents was expected to promote better performance than a fixed organization scheme, which is exactly what the data showed. There was a very strong performance benefit to those who organized their own desktops. Contrary to the other hypothesis, the 2D arrangement was more beneficial to users than either the 3D or 3D with motion arrangements. The 2D advantage may be the result of a number of factors. First, although people live in a 3D world they navigate more on 2D planes. Also, people may naturally encode spatial information in a descriptive or symbolic manner, as opposed to creating a spatial analog in the mind\u27s eye. Designers should not blindly attempt to create interfaces that mimic the real world. The choice between a 2D and 3D interface should be based upon the type of task to which the interface will be applied. Information storage/recall tasks, including the present task, will most likely benefit from a 2D interface. Other tasks that make greater use of navigation in 3D space may be better suited to 3D displays

Mediterranean climate change and Indian Ocean warming

General circulation model (GCM) responses to 20th century changes in sea surface temperatures (SSTs) and greenhouse gases are diagnosed, with emphasis on their relationship to observed regional climate change over the Mediterranean region. A major question is whether the Mediterranean region’s drying trend since 1950 can be understood as a consequence of the warming trend in tropical SSTs. We focus on the impact of Indian Ocean warming, which is itself the likely result of increasing greenhouse gases. It is discovered that a strong projection onto the positive polarity of the North Atlantic Oscillation (NAO) index characterizes the atmospheric response structure to the 1950-1999 warming of Indian Ocean SSTs. This influence appears to be robust in so far as it is reproduced in ensembles of experiments using three different GCMs. Both the equilibrium and transient responses to Indian Ocean warming are examined. Under each scenario, the latitude of prevailing midlatitude westerlies shifts poleward during the November-April period. The consequence is a drying of the Mediterranean region, whereas northern Europe and Scandinavia receive increased precipitation in concert with the poleward shift of storminess. The IPCC (TAR) 20th century coupled ocean-atmosphere simulations forced by observed greenhouse gas changes also yield a post-1950 drying trend over the Mediterranean. We argue that this feature of human-induced regional climate change is the outcome of a dynamical feedback, one involving Indian Ocean warming and a requisite adjustment of atmospheric circulation systems to such ocean warming

The New Standard in Town: An Updated Look at Computer-Aided Surgery Metrology

Computer-aided surgery capabilities for arthroplasty interventions emerged in the late 1990s with limited capabilities and use in the field. The goal of computer-aided surgery in the field of arthroplasty remains to reduce the need for excessive drilling tissue damage to the surgical site by reducing the need for cutting guides and related jigs. In order to assess the capabilities of computer-aided surgery systems in terms of both their accuracy and precision, the development and adherence to an industry standard for testing is necessary. A phantom device with divots of a known coordinate location was used in conjunction with proprietary software to assess the accuracy and precision of the complete surgical system. Measured coordinate data of a single point using the proprietary software was transformed according to the balloted ASTM standard for the generation of an accuracy and precision report. Results indicate 0.255 mm accuracy and sub-millimeter precision under conditions most similar to an operating room. Functional extreme tests indicate a loss of performance, leading to maximum decreased accuracy of 1.71 mm during standard orientation and 4.32 mm during extreme orientation of the phantom. The results suggest the tracking and software system meet manufacturer data under standard orientation and location conditions yet experience an expected significant loss of ability in extreme conditions. These loses in capability may lead to inaccurate alignment of tools and implants when using the proprietary computer-aided surgery software. Additional research is needed to determine the effect of larger reference frames with additional tracking points. Additionally, development of software to limit data return when near functional extremes will improve ease of use of the system.https://digitalcommons.unmc.edu/surp2022/1015/thumbnail.jp

Evaluation of a Tool for Airborne-Managed In-Trail Approach Spacing

The Advanced Terminal Area Approach Spacing (ATAAS) tool uses Automatic Dependent Surveillance-Broadcast aircraft state data to compute a speed command for an ATAAS-equipped aircraft to follow and obtain a required time interval behind another aircraft. The ATAAS tool and candidate operational procedures were tested in a high-fidelity, full mission simulator with active airline subject pilots flying an arrival scenario to obtain pilot perceptions of acceptability and workload for the concept. The aircraft consistently achieved the target spacing interval within 1 s when the ATAAS speed guidance was autothrottle-coupled and a slightly greater (4 - 5 s) but consistent interval with pilot-controlled speed changes. The subject pilots rated the ATAAS workload as similar to one with standard procedures for a nominal Instrument Landing System (ILS) approach. They also rated highly various procedural aspects (including amount of head-down time required). Eyetracker data showed only slight changes in instrument scan patterns for ATAAS versus standard ILS procedures

High Arctic ecosystem states : Conceptual models of vegetation change to guide long-term monitoring and research

Acknowledgements Open Access funding provided by Norwegian Polar Institute. We are grateful to our colleagues in COAT—Climate-ecological Observatory for Arctic Tundra for discussions, and to the editor Niels Martin Schmidt and anonymous reviewers for their thoughtful and constructive comments on earlier versions of this paper.Peer reviewedPublisher PD

MACHINE LEARNING FOR CLASSIFICATION OF AN ERODING SCARP SURFACE USING TERRESTRIAL PHOTOGRAMMETRY WITH NIR AND RGB IMAGERY

Abstract. Increasingly advanced and affordable close-range sensing techniques are employed by an ever-broadening range of users, with varying competence and experience. In this context a method was tested that uses photogrammetry and classification by machine learning to divide a point cloud into different surface type classes. The study site is a peat scarp 20 metres long in the actively eroding river bank of the Rotmoos valley near Obergurgl, Austria. Imagery from near-infra red (NIR) and conventional (RGB) sensors, georeferenced with coordinates of targets surveyed with a total station, was used to create a point cloud using structure from motion and dense image matching. NIR and RGB information were merged into a single point cloud and 18 geometric features were extracted using three different radii (0.02 m, 0.05 m and 0.1 m) totalling 58 variables on which to apply the machine learning classification. Segments representing six classes, dry grass, green grass, peat, rock, snow and target, were extracted from the point cloud and split into a training set and a testing set. A Random Forest machine learning model was trained using machine learning packages in the R-CRAN environment. The overall classification accuracy and Kappa Index were 98% and 97% respectively. Rock, snow and target classes had the highest producer and user accuracies. Dry and green grass had the highest omission (1.9% and 5.6% respectively) and commission errors (3.3% and 3.4% respectively). Analysis of feature importance revealed that the spectral descriptors (NIR, R, G, B) were by far the most important determinants followed by verticality at 0.1 m radius

Causes and Predictability of the 2012 Great Plains Drought

Central Great Plains precipitation deficits during May-August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in summer owing to large-scale subsidence and atmospheric stabilization. Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in summertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability for severe summer Great Plains drought may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail-risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. Implications of this study's findings for U.S. seasonal drought forecasting are discussed