Formation of misfit dislocations in strained-layer GaAs/In_xGa_1–xAs/GaAs heterostructures during postfabrication thermal processing

It is demonstrated that relaxation of GaAs/InxGa1–xAs/GaAs strained-layer heterostructures can be brought about by postfabrication thermal processing. Misfit dislocations are introduced into the structure during thermal processing, even though the thickness of the strained layer is well below the critical value predicted by the Matthews–Blakeslee model. The misfit dislocations are observed to be of both 60° mixed type and 90° pure edge type. As no relaxation occurs at the lower temperatures encountered during fabrication by molecular-beam epitaxy, it can be inferred that the critical condition for the formation of misfit dislocations is not only a function of strained-layer thickness and composition, but also of temperature. This observation cannot be accounted for by differential thermal expansion or diffusion across the strained-layer interfaces, but the temperature-dependent Peierls force may offer an explanation. The high temperature required to produce relaxation of these structures suggests that they are sufficiently thermally stable for most practical applications

Aviation spirit - past, present, and future

The volatile fuel of the high-speed internal combustion engine has, in the past, consisted almost exclusively of the lighter distillates from crude petroleum. Alternative and supplementary fuels are discussed such as: tetraline, dekalin, alcohol, cyclo-hexenes

The Transformation of Iodate to Iodide in Marine Phytoplankton Cultures

Six species of phytoplankton, representing 6 major phylogenetic groups (2 oceanic species: a cyanobacteria, Synechococcus sp., and a coccolithophorid, Emiliania huxleyi; and 4 coastal species: a prasinophyte, Tetraselmis sp., the green algae Dunaliella tertiolecta, the diatom Skeletonema costatum and a dinoflagellate Amphidinium carterae) were tested for their ability to reduce iodate to iodide in batch cultures. They all did so to varying degrees. Thus, the reduction of iodate to iodide by phytoplankton may be a general phenomenon in the marine environment. At ambient concentrations of iodate, the rates of depletion of iodate and appearance of iodide varied between 0.8 and 0.02, and between 0.3 and 0.02 nmol µg chlorophyll a–1 d–1, respectively. E. huxleyi was the least efficient while A. carterae was the most efficient in the depletion of iodate. However, in the formation of iodide, while E. huxleyi was also the least efficient, Synechococcus sp. were the most efficient. The rates of appearance of iodide were noticeably slower than the corresponding rates of depletion of iodate, suggesting that part of the iodate might have been converted to forms of iodine other than iodide in these cases. The slight mismatch in the rank order of the rates of depletion of iodate and appearance of iodide between the phytoplankton species was traced to this variable and incomplete conversion of iodate to iodide. These rates were increased by up to over an order of magnitude upon enriching the culture medium with 5 and 10 µM of iodate. The depletion of iodate and appearance of iodide occurred in all growth phases. However, the rates might vary with growth phase and the patterns of these variations might be species-specific. Phytoplankton growth was not impeded even under unnaturally high concentrations of iodate implying that there is little interaction between iodine processing and the metabolic activity of cell growth

Raman excitation spectroscopy of carbon nanotubes: effects of pressure medium and pressure

Raman excitation and emission spectra for the radial breathing mode (RBM) are reported, together with a preliminary analysis. From the position of the peaks on the two-dimensional plot of excitation resonance energy against Raman shift, the chiral indices (m, n) for each peak are identified. Peaks shift from their positions in air when different pressure media are added - water, hexane, sulphuric acid - and when the nanotubes are unbundled in water with surfactant and sonication. The shift is about 2 - 3 cm-1 in RBM frequency, but unexpectedly large in resonance energy, being spread over up to 100meV for a given peak. This contrasts with the effect of pressure. The shift of the peaks of semiconducting nanotubes in water under pressure is orthogonal to the shift from air to water. This permits the separation of the effects of the pressure medium and the pressure, and will enable the true pressure coefficients of the RBM and the other Raman peaks for each (m, n) to be established unambiguously.Comment: 6 pages, 3 Figures, Proceedings of EHPRG 2011 (Paris

Mild recessive epidermolytic hyperkeratosis associated with a novel keratin 10 donor splice-site mutation in a family of Norfolk terrier dogs

Background  Epidermolytic hyperkeratosis in humans is caused by dominant-negative mutations in suprabasal epidermal keratins 1 and 10. However, spontaneous keratin mutations have not been confirmed in a species other than human. Objectives  To describe an autosomal recessive, mild, nonpalmar/plantar epidermolytic ichthyosis segregating in an extended pedigree of Norfolk terrier dogs due to a splice-site mutation in the gene encoding keratin 10 (KRT10). Methods  Dogs were evaluated clinically, and skin samples were examined by light and electron microscopy. Genomic DNA samples and cDNA from skin RNA were sequenced and defined a mutation in KRT10. Consequences of the mutation were evaluated by assessing protein expression with immunohistochemistry and Western blotting and gene expression with real-time RT-PCR (reverse transcriptase-polymerase chain reaction). Results  Adult dogs with the disease had generalized, pigmented hyperkeratosis with epidermal fragility. Light microscopic examination defined epidermolysis with hyperkeratosis; ultrastructural changes included a decrease in tonofilaments and abnormal filament aggregation in upper spinous and granular layer keratinocytes. Affected dogs were homozygous for a single base GT→TT change in the consensus donor splice site of intron 5 in KRT10. Keratin 10 protein was not detected with immunoblotting in affected dogs. Heterozygous dogs were normal based on clinical and histological appearance and keratin 10 protein expression. The mutation caused activation of at least three cryptic or alternative splice sites. Use of the cryptic sites resulted in transcripts containing premature termination codons. One transcript could result in shortening of the proximal portion of the 2B domain before the stutter region. Quantitative real-time PCR indicated a significant decrease in KRT10 mRNA levels in affected dogs compared with wild-type dogs. Conclusions  This disease is the first confirmed spontaneous keratin mutation in a nonhuman species and is the first reported recessive form of epidermolytic hyperkeratosis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74670/1/j.1365-2133.2005.06735.x.pd

Pressure coefficients of Raman modes of carbon nanotubes resolved by chirality: Environmental effect on graphene sheet

Studies of the mechanical properties of single-walled carbon nanotubes are hindered by the availability only of ensembles of tubes with a range of diameters. Tunable Raman excitation spectroscopy picks out identifiable tubes. Under high pressure, the radial breathing mode shows a strong environmental effect shown here to be largely independent of the nature of the environment . For the G-mode, the pressure coefficient varies with diameter consistent with the thick-wall tube model. However, results show an unexpectedly strong environmental effect on the pressure coefficients. Reappraisal of data for graphene and graphite gives the G-mode Grueuneisen parameter gamma = 1.34 and the shear deformation parameter beta = 1.34.Comment: Submitted to Physical Review

Associations of sitting accumulation patterns with cardio-metabolic risk biomarkers in Australian adults

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Predicting no-show appointments in a pediatric hospital in Chile using machine learning

The Chilean public health system serves 74% of the country’s population, and 19% of medical appointments are missed on average because of no-shows. The national goal is 15%, which coincides with the average no-show rate reported in the private healthcare system. Our case study, Doctor Luis Calvo Mackenna Hospital, is a public high-complexity pediatric hospital and teaching center in Santiago, Chile. Historically, it has had high no-show rates, up to 29% in certain medical specialties. Using machine learning algorithms to predict no-shows of pediatric patients in terms of demographic, social, and historical variables. To propose and evaluate metrics to assess these models, accounting for the cost-effective impact of possible intervention strategies to reduce no-shows. We analyze the relationship between a no-show and demographic, social, and historical variables, between 2015 and 2018, through the following traditional machine learning algorithms: Random Forest, Logistic Regression, Support Vector Machines, AdaBoost and algorithms to alleviate the problem of class imbalance, such as RUS Boost, Balanced Random Forest, Balanced Bagging and Easy Ensemble. These class imbalances arise from the relatively low number of no-shows to the total number of appointments. Instead of the default thresholds used by each method, we computed alternative ones via the minimization of a weighted average of type I and II errors based on cost-effectiveness criteria. 20.4% of the 395,963 appointments considered presented no-shows, with ophthalmology showing the highest rate among specialties at 29.1%. Patients in the most deprived socioeconomic group according to their insurance type and commune of residence and those in their second infancy had the highest no-show rate. The history of non-attendance is strongly related to future no-shows. An 8-week experimental design measured a decrease in no-shows of 10.3 percentage points when using our reminder strategy compared to a control group. Among the variables analyzed, those related to patients’ historical behavior, the reservation delay from the creation of the appointment, and variables that can be associated with the most disadvantaged socioeconomic group, are the most relevant to predict a no-show. Moreover, the introduction of new cost-effective metrics significantly impacts the validity of our prediction models. Using a prototype to call patients with the highest risk of no-shows resulted in a noticeable decrease in the overall no-show rate.</p