Sessile droplet evaporation on superheated superhydrophobic surfaces

This fluid dynamics video depicts the evaporation of sessile water droplets placed on heated superhydrophobic (SH) surfaces of varying cavity fraction, F_c, and surface temperature, T_s, above the saturation temperature, T_sat. Images were captured at 10,000 FPS and are played back at 30 FPS in this video. Teflon-coated silicon surfaces of F_c = 0, 0.5, 0.8, and 0.95 were used for these experiments. T_s ranging from 110{\deg}C to 210{\deg}C were studied. The video clips show how the boiling behavior of sessile droplets is altered with changes in surface microstructure. Quantitative results from heat transfer rate experiments conducted by the authors are briefly discussed near the end of the video.Comment: videos include

Validation of an improved batch model in a coupled combustion space/melt tank/batch melting glass fumace simulation

An improved coupled combustion space model, model for the transport processes in the melting tank, and batch blanket melting model has been developed which is capable of predicting the transport phenomena in a float glass furnace. Model predictions are compared with experimental furnace measurements reported previously. The batch blanket has been approximated as continuous and discrete (island) regions in an attempt to simulate the formation of discrete batch clumps ("logs") observed in real furnaces. Both the boundary location between the continuous blanket and batch island zones, and the batch coverage fraction in the batch island zone are specified as model inputs. The heat fluxes and temperatures at the interfaces between the combustion space, the batch coverage, and the glass tank are calculated in a coupled fashion rather than assumed as input boundary conditions as it must be done in traditional, uncoupled models. Α 455-metric-ton pull rate per day, air-fuel fired float-glass melting furnace was simulated. The 100 % batch blanket simulation (absence of batch islands) yields over-prediction of glass surface temperature, crown incident heat flux, and crown temperature. The assumption of 85 % batch coverage and 15 % free glass surface in the batch island zone agrees well with most experimental measurements. The batch island concept added to the batch melting model is a significant improvement over previous approaches for this case

Predicted and measured glass surface temperatures in an industrial, regeneratively gas-fired flat glass furnace

This study reports optically measured glass surface temperatures along the furnace center-line in the combustion space of a sideport, 455 (metric) t/d industrial, gas-fired flat glass furnace. The measurements were made using a water-cooled two-color pyrometer inserted through holes in the crown at six locations along the length of the furnace. Both average and time-resolved glass surface temperature measurements were performed during the approximately 20 s reversal period of the furnace. The measured glass surface temperature data are supplemented by observations of the batch location using a specially designed, water-cooled video probe. The average temperatures were found to rise from a low near 1700 Κ near the batch blanket to a peak of approximately 1900 K, then drop to a level of 1800 K. Evidence of batch Islands or "logs" is observed in the surface temperature data collected at the measurement location nearest the batch blanket. Large temperature excursions are seen here, indicative of measurement alternately of both the batch surface and the molten glass. Also reported in this study are results of a numerical model for the three-dimensional melt flow and heat transfer in the tank, coupled with a batch melting model. The radiant heat flux distribution incident on the melt and batch blanket surfaces is assumed. The melt tank model includes bubbling. The numerical predictions agree well with the timeaveraged glass surface temperature data collected experimentally The measurements and model predictions illustrate the complex transport phenomena in the melting section of the furnace

Surveys of Stylisma Pickeringii var. Pattersonii (Convolvulaceae), its Associated Plant Species, and its Insect Visitors

Stylisma pickeringii var. pattersonii (Convolvulaceae) is endangered in Illinois and Iowa, and occurs in scattered populations in other states. During 1999 and 2000, two insect species previously unreported from Illinois were observed visiting its flowers. This study was undertaken to survey additional insect visitors, as well as to characterize the plant community where S. pickeringii occurs. The objectives were to survey: 1) floral traits (anthesis and flower density) of S. pickeringii, 2) associated plant species, and 3) insect visitor characteristics. Floral traits were determined and associated plant species surveyed in Mason County (degraded hay field on private property) and Henderson County (dry sand prairie at the Big River State Forest), Illinois. Insects visiting flowers were collected at 10:00 a.m., 12:30 p.m., and 3:00 p.m. during June, July, and August in 2001 and 2002. Individual flowers lasted one day and remained open for 6–8 hours. Peak flowering occurred from early to the middle of July when S. pickeringii was the dominant species in flower. Henderson County contained a greater diversity of native plant species with less bare ground and fewer non-native species than the Mason County site. Fortyseven insect species were observed visiting S. pickeringii flowers. Most frequent visitors were Apis mellifera (Hymenoptera: Apidae), Bombylius fraudulentus (Diptera: Bombyliidae), and Heterostylum croceum (Diptera: Bombliidae). The diversity of visiting insects was higher earlier than later in the day, in July and August than June, and in Henderson than Mason County

Net Hydrogenation of Pt-NHPh Bond Is Catalyzed by Elemental Pt

This article discusses the net hydrogenation of Pt-NHPh bond catalyzed by elemental Pt

Status of the LUX Dark Matter Search

The Large Underground Xenon (LUX) dark matter search experiment is currently being deployed at the Homestake Laboratory in South Dakota. We will highlight the main elements of design which make the experiment a very strong competitor in the field of direct detection, as well as an easily scalable concept. We will also present its potential reach for supersymmetric dark matter detection, within various timeframes ranging from 1 year to 5 years or more.Comment: 4 pages, in proceedings of the SUSY09 conferenc

Deep sequencing-based transcriptome analysis of Plutella xylostella larvae parasitized by Diadegma semiclausum

Background: Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported

The completion of the Mammalian Gene Collection (MGC)

Since its start, the Mammalian Gene Collection (MGC) has sought to provide at least one full-protein-coding sequence cDNA clone for every human and mouse gene with a RefSeq transcript, and at least 6200 rat genes. The MGC cloning effort initially relied on random expressed sequence tag screening of cDNA libraries. Here, we summarize our recent progress using directed RT-PCR cloning and DNA synthesis. The MGC now contains clones with the entire protein-coding sequence for 92% of human and 89% of mouse genes with curated RefSeq (NM-accession) transcripts, and for 97% of human and 96% of mouse genes with curated RefSeq transcripts that have one or more PubMed publications, in addition to clones for more than 6300 rat genes. These high-quality MGC clones and their sequences are accessible without restriction to researchers worldwide

Harnessing learning biases is essential for applying social learning in conservation

Social learning can influence how animals respond to anthropogenic changes in the environment, determining whether animals survive novel threats and exploit novel resources or produce maladaptive behaviour and contribute to human-wildlife conflict. Predicting where social learning will occur and manipulating its use are, therefore, important in conservation, but doing so is not straightforward. Learning is an inherently biased process that has been shaped by natural selection to prioritize important information and facilitate its efficient uptake. In this regard, social learning is no different from other learning processes because it too is shaped by perceptual filters, attentional biases and learning constraints that can differ between habitats, species, individuals and contexts. The biases that constrain social learning are not understood well enough to accurately predict whether or not social learning will occur in many situations, which limits the effective use of social learning in conservation practice. Nevertheless, we argue that by tapping into the biases that guide the social transmission of information, the conservation applications of social learning could be improved. We explore the conservation areas where social learning is highly relevant and link them to biases in the cues and contexts that shape social information use. The resulting synthesis highlights many promising areas for collaboration between the fields and stresses the importance of systematic reviews of the evidence surrounding social learning practices.BBSRC David Phillips Fellowship (BB/H021817/1