Using Content Provider Signals to Select Individual Content Items for a Content Item Campaign

This document describes a system and method in which signals from a third-party content provider are used to help select content items in the content item campaign of the third-party content provider. The selected content items are then presented to a resource. The signals may be used to help select between content items for which there are known metrics and content items for which there are no metrics. The signals indicate trends or preferences that may indicate that one content item or type of content item is a better choice compared to other content items

Tunable Automatic Placement Finder for Third Party Content

This document describes a technique for performing tuning in automatic content slot placement process. A data processing system can send a script to a client device for automatic content slot placement. The script can be executed by the client device to obtain a chunk size report and to transmit the chunk size report to the data processing system. The data processing system can analyze data in the chunk size report and perform tuning based on the analysis. Parameters for how long to hold the main execution thread at the client device can be modified. The data processing system can also perform tuning based on device characteristics and network characteristics associated with the client device

DETECTION OF POSITION FIXED CONTENT ITEM SLOTS AND CONTROL OF CONTENT DISPLAYED THEREIN

Implementations described herein relate to detection of fixed position content item slots and control of interactions based on determining a content item slot is a fixed position content item slot, such as click protections, policy enforcement mechanism, and/or auction corrections

PARTIAL CLICK PROTECTIONS FOR ADS

Partial click protections for ads are introduced in this publication. The partial click protections for ads include applying one or more click protections to one or more specific portions of an ad unit instead of the entire ad unit. The one or more specific portions of the ad are differentiated from other portions of the ad based on various criteria. The one or more specific portions of the ad unit include specific portions of a button in the ad unit

An Unsupervised Method to Detect the Left Atrial Appendages and Classify their Morphologies

The left atrial appendage (LAA) is the site where the left atrial thrombi are most likely (90%) to develop. Despite the increasing interest that LAA has attracted over the last decade, the methods currently used to classify its morphology are mainly based on cardiologists’ judgment. Given the remarkable improvement of imaging techniques, we propose an unsupervised quantitative method that can overcome the limits of the current classification systems. The resulting classification system is objective and reproducible

Phototaxis and Impaired Motility in Adenylyl Cyclase and Cyclase Receptor Protein Mutants of Synechocystis sp. Strain PCC 6803

We have carefully characterized and reexamined the motility and phototactic responses of Synechocystis sp. adenylyl cyclase (Cya1) and catabolite activator protein (SYCRP1) mutants to different light regimens, glucose, 3-(3,4-dichlorophenyl)-1,1-dimethylurea, and cyclic AMP. We find that contrary to earlier reports, cya1 and sycrp1 mutants are motile and phototactic but are impaired in one particular phase of phototaxis in comparison with wild-type Synechocystis sp

Rapid, Precise, and Accurate Counts of <i>Symbiodinium</i> Cells Using the Guava Flow Cytometer, and a Comparison to Other Methods

<div><p>In studies of both the establishment and breakdown of cnidarian-dinoflagellate symbiosis, it is often necessary to determine the number of <i>Symbiodinium</i> cells relative to the quantity of host tissue. Ideally, the methods used should be rapid, precise, and accurate. In this study, we systematically evaluated methods for sample preparation and storage and the counting of algal cells using the hemocytometer, a custom image-analysis program for automated counting of the fluorescent algal cells, the Coulter Counter, or the Millipore Guava flow-cytometer. We found that although other methods may have value in particular applications, for most purposes, the Guava flow cytometer provided by far the best combination of precision, accuracy, and efficient use of investigator time (due to the instrument's automated sample handling), while also allowing counts of algal numbers over a wide range and in small volumes of tissue homogenate. We also found that either of two assays of total homogenate protein provided a precise and seemingly accurate basis for normalization of algal counts to the total amount of holobiont tissue.</p></div

Preparation and processing times for algal-counting methods.

<p>^aThe time required for the user to prepare for counting, independent of the number of samples to be counted. Based on multiple trials in our laboratory.</p><p>^bThe time actually expended by the user, independent of machine-running time for the Guava. Based on multiple trials in our laboratory.</p><p>^cCounting 16 1x1 mm squares. The four corner squares were counted in each chamber. Thus, two loadings of each sample were performed, which increases the time required for counting but decreases the chance of being misled by a poor loading of the chamber (one of the well known sources of systematic error with the hemocytometer).</p><p>^dOn the rather unlikely assumption of an indefatigable user.</p><p>^ePreparation time can be considerably longer if the instrument clogs.</p><p>^fUsing a multichannel pipet to load the wells of a 96-well plate.</p><p>Preparation and processing times for algal-counting methods.</p

Differences in precision of different methods for counting algal cells.

<p>Symbiotic anemones of strain CC7 were washed in ASW and suspended in a small volume of solution containing one part ASW, 7 parts dH2O, and ~0.08% SDS. The animals were then homogenized in a manual tissue homogenizer (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135725#sec002" target="_blank">Materials and Methods</a>), and Samples 1, 2, and 3 were prepared by further dilution of the homogenate with the same solution. The concentration of algal cells in each sample was then determined using a hemocytometer (H), the software program Dinofinder (D), the Coulter Counter (C; particles from 6.5–12 μm were scored), and the Guava flow cytometer (G). In this case, the Coulter Counter samples were further diluted and counted in filtered ASW rather than Isoton as described in Materials and Methods. The means ± SEMs of replicate counts by each method are shown (H, n = 16; D, n = 16; C, n = 4; G, n = 8). (Note that for the hemocytometer, each one of the n = 16 itself represented an averaged count of 16 individual 1 x 1 mm squares–see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135725#sec002" target="_blank">Materials and Methods</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135725#pone.0135725.t001" target="_blank">Table 1</a>.)</p