Melanocytes are selectively vulnerable to UVA-mediated bystander oxidative signaling.

Long-wave UVA is the major component of terrestrial UV radiation and is also the predominant constituent of indoor sunlamps, both of which have been shown to increase cutaneous melanoma risk. Using a two-chamber model, we show that UVA-exposed target cells induce intercellular oxidative signaling to non-irradiated bystander cells. This UVA-mediated bystander stress is observed between all three cutaneous cell types (i.e., keratinocytes, melanocytes, and fibroblasts). Significantly, melanocytes appear to be more resistant to direct UVA effects compared with keratinocytes and fibroblasts, although melanocytes are also more susceptible to bystander oxidative signaling. The extensive intercellular flux of oxidative species has not been previously appreciated and could possibly contribute to the observed cancer risk associated with prolonged UVA exposure

Holographic data storage in a DX-center material

We report on the optical storage of digital data in a semiconductor sample containing DX centers. The diffraction efficiency and the bit-error-rate performance of multiplexed data images are shown to agree well with a simple model of the material. Uniform storage without an exposure schedule is demonstrated. The volume sensitivity is found to be ~10^3 times that of LiNBO3:Fe. The importance of coherent addition of scattered light with diffracted light in holographic data storage is discussed

Synthesis of pentacene nanotubes by melt-assisted template wetting

peer-reviewedno abstract availablePUBLISHEDpeer-reviewe

Computer recommendations for an automatic approach and landing system for V/STOL aircraft. Volume 2 - Equations

Automatic approach and landing system for V/STOL aircraf

Capturing accelerometer outputs in healthy volunteers under normal and simulated-pathological conditions using ML classifiers

Wearable devices offer a possible solution for acquiring objective measurements of physical activity. Most current algorithms are derived using data from healthy volunteers. It is unclear whether such algorithms are suitable in specific clinical scenarios, such as when an individual has altered gait. We hypothesized that algorithms trained on healthy population will result in less accurate results when tested in individuals with altered gait. We further hypothesized that algorithms trained on simulated-pathological gait would prove better at classifying abnormal activity.We studied healthy volunteers to assess whether activity classification accuracy differed for those with healthy and simulated-pathological conditions. Healthy participants (n=30) were recruited from the University of Leeds to perform nine predefined activities under healthy and simulated-pathological conditions. Activities were captured using a wrist-worn MOX accelerometer (Maastricht Instruments, NL). Data were analyzed based on the Activity-Recognition-Chain process. We trained a Neural-Network, Random-Forests, k-Nearest-Neighbors (k-NN), Support-Vector-Machines (SVM) and Naive Bayes models to classify activity. Algorithms were trained four times; once with 'healthy' data, and once with 'simulated-pathological data' for each of activity-type and activity-task classification. In activity-type instances, the SVM provided the best results; the accuracy was 98.4% when the algorithm was trained and then tested with unseen data from the same group of healthy individuals. Accuracy dropped to 52.8% when tested on simulated-pathological data. When the model was retrained with simulated-pathological data, prediction accuracy for the corresponding test set was 96.7%. Algorithms developed on healthy data are less accurate for pathological conditions. When evaluating pathological conditions, classifier algorithms developed using data from a target sub-population can restore accuracy to above 95%.Clinical Relevance - This method remotely establishes health-related data of objective outcome measures of activities of daily living

Dwarf White Clover Supports Pollinators, Augments Nitrogen in Clover-Turfgrass Lawns, and Suppresses Root-Feeding Grubs in Monoculture but Not in Mixed Swards

The runoff or leaching of nitrogen fertilizers from monoculture turfgrass lawns contri-butes to water pollution, and such lawns are susceptible to insect pests and provide few resources for pollinators. One approach to creating more sustainable lawns is to incorporate white clover (Trifolium repens L.), a nitrogen-fixing legume, into grass seed mixtures or existing turfgrass swards. “Dutch” white clover (DWC), a ubiquitous landrace, forms non-uniform clumps when intermixed with turfgrasses, thus it is often considered to be a lawn weed. Recently, several dwarf varieties of white clover have been selected for their small leaf size and low growth habit, allowing them to tolerate low mowing heights and blend better with grasses. To date, there have been no studies published on the entomological aspects of dwarf clover in pure stands or intermixed with turfgrass. We established field plots with combinations of DWC, two cultivars of dwarf clover, and tall fescue (Schedonorus arundinaceus (Schreb.) Dumort.) in monoculture or mixed swards, and compared the invertebrate communities therein. Predatory arthropods and earthworm numbers were similar in all plot types. The clover monocultures were resistant to white grubs, but the grub densities in the clover–tall fescue dicultures were similar to those found in the pure tall fescue swards. Dwarf clovers and DWC were similarly attractive to bees and supported similar bee assemblages. The tall fescue foliar N content was elevated 17–27% in the dicultures with clovers

Two-Loop Calculations with Vertex Corrections in the Walecka Model

Two-loop corrections with scalar and vector form factors are calculated for nuclear matter in the Walecka model. The on-shell form factors are derived from vertex corrections within the framework of the model and are highly damped at large spacelike momenta. The two-loop corrections are evaluated first by using the one-loop parameters and mean fields and then by refitting the total energy/baryon to empirical nuclear matter saturation properties. The modified two-loop corrections are significantly smaller than those computed with bare vertices. Contributions from the anomalous isoscalar form factor of the nucleon are included for the first time. The effects of the implicit density dependence of the form factors, which arise from the shift in the baryon mass, are also considered. Finally, necessary extensions of these calculations are discussed.Comment: 29 pages in REVTeX, 18 figures, preprint IU/NTC 94-02 //OSU--94-11

Northern Bobwhite Response to Control of Red Imported Fire Ants in the Gulf Coast Prairie of Texas

The population decline of northern bobwhite (Colinus virginianus; hereafter, bobwhite) on the Texas Gulf Coast Prairie, USA is largely attributed to habitat loss. However, red imported fire ants (Solenopsis invicta) occur throughout the region and are considered a possible contributing factor to the bobwhite decline. The objectives of our study were to determine the influence of red imported fire ants on bobwhites by comparing bobwhite nest success, survival, and density between sites treated with fire ant bait (treatment) and reference (control) sites. Our study was conducted on 3 private ranches in Goliad and Refugio counties, Texas. Each ranch contained 2 paired experimental units that consisted of a treatment and control site (500 ha each). The treatment sites received an aerial application of fire ant bait (Extinguish® Plus) during April 2018, whereas the control sites were not treated. We estimated mound density by counting fire ant mounds using distance sampling. We used radio-telemetry to monitor bobwhite nest success and survival, and we estimated bobwhite densities using distance sampling via helicopter surveys. Fire ant mound density decreased through time on both treatment and control sites. However, fire ant mound density was lower on treatment sites than control sites, indicating the insecticide was effective at decreasing fire ant mound density. Bobwhite survival, nest success, and density did not statistically differ between control and treated sites either pre-treatment (2017) or post-treatment (2018), but survival and nest success metrics were numerically higher in treated units. Bobwhite survival remained relatively stable in the treatment units 4 weeks after application but decreased in the control units. Following treatment, apparent nest success in the treated units increased by 37.4% while nest success in the control units decreased by 35.2%. Bobwhite populations were low in this ecoregion, which influenced our ability to trap and monitor many bobwhites or monitor many nests. In addition, it may be possible that repeated, annual treatments for fire ants are necessary for a benefit to accrue and be observed in bobwhites. Our results indicate that there may be potential benefits to bobwhites from fire ant reduction that deserve further research attention