OXYGEN K

The O K spectra of these 3 products, at -160 Deg, show a prominent peak at 532 eV. In ice and solid MeOH, the principal peak occurs at 526 eV. The ice spectrum has also a well-defined subpeak at 520 eV; it is due to a transition from 1 of the MO. The main band and also the subpeak are broader in MeOH than in ice. The transition at 526 eV results from a 1b1 nonbonding orbital (2pp lone pair) and thus can be called an ionic transition. The O subband at 520 eV stems from a 1b2 bonding orbital (2ps type). The spectrum from solidified CO2 also shows 2 peaks, at 527 and 523 eV, the former one being an ionic peak. EtOH, PrOH, and BuOH yield spectra indistinguishable from that of MeOH

Multiple Mini-Interview Performance And First Semester Achievement In A Baccalaureate Respiratory Care Program

Success in an undergraduate respiratory care program requires that students demonstrate skills that, although not traditionally assessed in the admissions process, are indicative of success in the clinical environment. Attributes like critical and interpersonal skills, empathy, and self-appraisal are competencies developed by different yet integrated intellectual processes and contribute significantly to the overall perception of intelligence. However, despite limited efficacy in predicting rate of attrition in an undergraduate clinical program such respiratory care, traditional admissions criteria continue to focus solely on objective indicators of academic ability. The purpose of this quantitative case study was to investigate the utility of the multiple mini-interview (MMI) as an adjunct method of selecting candidates to a small cohort-based baccalaureate respiratory care program. The MMI is a method of student assessment designed to more accurately evaluate non-cognitive skills inherent to successful clinicians during the admissions process. A three-station MMI was integrated into the 2016 cohort admission process at the participating institution. Data including performance on the MMI, course achievement, and rate of attrition in the first semester of core respiratory care curriculum were recorded. Data for sixty-nine students across three separate cohort groups were collected and analyzed. Results of this study indicated a significant relationship between both total MMI points and MMI rank and achievement in the introductory clinical component of this program (r (23) =.528, p= .007 and r (23) = .509, p= .009, respectively). A logistic regression analysis revealed that a multidimensional assessment model may be more effective in predicting likelihood of attrition in any of the cohorts, X2(2) = 11.19, p = .004. Limitations include a small sample and differences across cohort scoring methods. The MMI was found to have a predictive role in identifying key competencies required for success in a baccalaureate respiratory care program. Future research should include a larger sample and a mixed-method approach to investigate the student and faculty perception of utilizing a multimodal approach to undergraduate admissions

Theory of spin-orbit coupling in bilayer graphene

Theory of spin-orbit coupling in bilayer graphene is presented. The electronic band structure of the AB bilayer in the presence of spin-orbit coupling and a transverse electric field is calculated from first-principles using the linearized augmented plane wave method implemented in the WIEN2k code. The first-principles results around the K points are fitted to a tight-binding model. The main conclusion is that the spin-orbit effects in bilayer graphene derive essentially from the single-layer spin-orbit coupling which comes almost solely from the d orbitals. The intrinsic spin-orbit splitting (anticrossing) around the K points is about 24\mu eV for the low-energy valence and conduction bands, which are closest to the Fermi level, similarly as in the single layer graphene. An applied transverse electric field breaks space inversion symmetry and leads to an extrinsic (also called Bychkov-Rashba) spin-orbit splitting. This splitting is usually linearly proportional to the electric field. The peculiarity of graphene bilayer is that the low-energy bands remain split by 24\mu eV independently of the applied external field. The electric field, instead, opens a semiconducting band gap separating these low-energy bands. The remaining two high-energy bands are spin-split in proportion to the electric field; the proportionality coefficient is given by the second intrinsic spin-orbit coupling, whose value is 20\mu eV. All the band-structure effects and their spin splittings can be explained by our tight-binding model, in which the spin-orbit Hamiltonian is derived from symmetry considerations. The magnitudes of intra- and interlayer couplings---their values are similar to the single-layer graphene ones---are determined by fitting to first-principles results.Comment: 16 pages, 13 figures, 5 tables, typos corrected, published versio

Electronic coupling between Bi nanolines and the Si(001) substrate: An experimental and theoretical study

Atomic nanolines are one dimensional systems realized by assembling many atoms on a substrate into long arrays. The electronic properties of the nanolines depend on those of the substrate. Here, we demonstrate that to fully understand the electronic properties of Bi nanolines on clean Si(001) several different contributions must be accounted for. Scanning tunneling microscopy reveals a variety of different patterns along the nanolines as the imaging bias is varied. We observe an electronic phase shift of the Bi dimers, associated with imaging atomic p-orbitals, and an electronic coupling between the Bi nanoline and neighbouring Si dimers, which influences the appearance of both. Understanding the interplay between the Bi nanolines and Si substrate could open a novel route to modifying the electronic properties of the nanolines.Comment: 6 pages (main), 2 pages (SI), accepted by Phys. Rev.

Tendency Bias Correction in Coupled and Uncoupled Global Climate Models with a Focus on Impacts over North America

We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the models climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphereocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summerlong-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill

Diabetes induced by gain-of-function mutations in the Kir6.1 subunit of the KATP channel

Gain-of-function (GOF) mutations in the pore-forming (Kir6.2) and regulatory (SUR1) subunits of K(ATP) channels have been identified as the most common cause of human neonatal diabetes mellitus. The critical effect of these mutations is confirmed in mice expressing Kir6.2-GOF mutations in pancreatic β cells. A second K(ATP) channel pore-forming subunit, Kir6.1, was originally cloned from the pancreas. Although the prominence of this subunit in the vascular system is well documented, a potential role in pancreatic β cells has not been considered. Here, we show that mice expressing Kir6.1-GOF mutations (Kir6.1[G343D] or Kir6.1[G343D,Q53R]) in pancreatic β cells (under rat-insulin-promoter [Rip] control) develop glucose intolerance and diabetes caused by reduced insulin secretion. We also generated transgenic mice in which a bacterial artificial chromosome (BAC) containing Kir6.1[G343D] is incorporated such that the transgene is only expressed in tissues where Kir6.1 is normally present. Strikingly, BAC-Kir6.1[G343D] mice also show impaired glucose tolerance, as well as reduced glucose- and sulfonylurea-dependent insulin secretion. However, the response to K(+) depolarization is intact in Kir6.1-GOF mice compared with control islets. The presence of native Kir6.1 transcripts was demonstrated in both human and wild-type mouse islets using quantitative real-time PCR. Together, these results implicate the incorporation of native Kir6.1 subunits into pancreatic K(ATP) channels and a contributory role for these subunits in the control of insulin secretion

Inferring soil moisture memory from streamflow observations using a simple water balance model

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. The authors investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Their approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography