Distance Dependence of the Energy Transfer Rate From a Single Semiconductor Nanostructure to Graphene

The near-field Coulomb interaction between a nano-emitter and a graphene monolayer results in strong F\"orster-type resonant energy transfer and subsequent fluorescence quenching. Here, we investigate the distance dependence of the energy transfer rate from individual, i) zero-dimensional CdSe/CdS nanocrystals and ii) two-dimensional CdSe/CdS/ZnS nanoplatelets to a graphene monolayer. For increasing distances $d$, the energy transfer rate from individual nanocrystals to graphene decays as $1/d^4$. In contrast, the distance dependence of the energy transfer rate from a two-dimensional nanoplatelet to graphene deviates from a simple power law, but is well described by a theoretical model, which considers a thermal distribution of free excitons in a two-dimensional quantum well. Our results show that accurate distance measurements can be performed at the single particle level using graphene-based molecular rulers and that energy transfer allows probing dimensionality effects at the nanoscale.Comment: Main text (+ 5 figures) and Supporting Information (+ 7 figures

Image-based Early Detection System for Wildfires

Wildfires are a disastrous phenomenon which cause damage to land, loss of property, air pollution, and even loss of human life. Due to the warmer and drier conditions created by climate change, more severe and uncontrollable wildfires are expected to occur in the coming years. This could lead to a global wildfire crisis and have dire consequences on our planet. Hence, it has become imperative to use technology to help prevent the spread of wildfires. One way to prevent the spread of wildfires before they become too large is to perform early detection i.e, detecting the smoke before the actual fire starts. In this paper, we present our Wildfire Detection and Alert System which use machine learning to detect wildfire smoke with a high degree of accuracy and can send immediate alerts to users. Our technology is currently being used in the USA to monitor data coming in from hundreds of cameras daily. We show that our system has a high true detection rate and a low false detection rate. Our performance evaluation study also shows that on an average our system detects wildfire smoke faster than an actual person.Comment: Published in Tackling Climate Change with Machine Learning workshop, Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022

Hyaline Vascular-Type Castleman Disease Presenting as an Esophageal Submucosal Tumor: Case Report

Castleman disease is a relatively rare disorder of lymphoid tissue that involves the gastrointestinal tract in a variety of clinical and pathologic manifestations. A submucosal location has never been described in the medical literature. We report a case of esophageal Castleman disease involving thesubmucosal layer in a 62-year-old man, which was confirmed on pathology. Esophagography and CT demonstrated an intramural tumor, and a leiomyoma or leiomyosarcoma was suspected based on the known incidence of such tumors

First-time comparison between NO2 vertical columns from GEMS and Pandora measurements

The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV&ndash;visible spectrometer onboard the GEO-KOMPSAT-2B satellite launched into geostationary orbit in February 2020. To evaluate GEMS NO2 column data, comparison was carried out using NO2 vertical column density (VCD) measured using direct-sunlight observations by the Pandora spectrometer system at four sites in Seosan, South Korea, during November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7 &times; 1015 molec. cm-2 to 5.5 &times; 1015 molec. cm-2 for cloud fraction (CF) &lt; 0.7. Higher correlation coefficients of 0.62&ndash;0.78 with lower RMSEs from 3.3 &times; 1015 molec. cm-2 to 4.3 &times; 1015 molec. cm-2 were found with CF &lt; 0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less-cloudy conditions. Overall, GEMS NO2 column data tend to be lower than those of Pandora due to differences in representative spatial coverage, with a large negative bias under high-CF conditions. With correction for horizontal representativeness in Pandora measurement coverage, the correlation coefficients range from 0.69 to 0.81 with RMSEs from 3.2 &times; 1015 molec. cm-2 to 4.9 &times; 1015 molec. cm-2 were achieved for CF &lt; 0.3, showing the better correlation with the correction than that without the correction.</p

First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements

The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV-visible (UV-Vis) spectrometer on board the GEO-KOMPSAT-2B (Geostationary Korea Multi-Purpose Satellite 2B) satellite launched into a geostationary orbit in February 2020. To evaluate the GEMS NO2 total column data, a comparison was carried out using the NO2 vertical column density (VCD) that measured direct sunlight using the Pandora spectrometer system at four sites in Seosan, South Korea, from November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7×1015 to 5.5×1015 molec. cm−2 for a cloud fraction (CF) &lt;0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3×1015 to 5.0×1015 molec. cm−2 were found with CF &lt;0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less cloudy conditions. Overall, the GEMS NO2 total column data tended to be lower than the Pandora data, owing to differences in the representative spatial coverage, with a large negative bias under high CF conditions. With a correction for horizontal representativeness in the Pandora measurement coverage, correlation coefficients ranging from 0.69 to 0.81, with RMSEs from 3.2×1015 to 4.9×1015 molec. cm−2, were achieved for CF &lt;0.3, showing a better correlation with the correction than without the correction.</p

Changes in Biomarkers and Hemodynamics According to Antibiotic Susceptibility in a Model of Bacteremia

Proper selection of susceptible antibiotics in drug-resistant bacteria is critical to treat bloodstream infection. Although biomarkers that guide antibiotic therapy have been extensively evaluated, little is known about host biomarkers targeting in vivo antibiotic susceptibility. Therefore, we aimed to evaluate the trends of hemodynamics and biomarkers in a porcine bacteremia model treated with insusceptible antibiotics compared to those in susceptible models. Extended-spectrum beta-lactamase (ESBL)-producing Escherichia colt (E coli, 5.0 * 10&lt;^&gt;9 CFU) was intravenously administered to 11 male pigs. One hour after bacterial infusion, pigs were assigned to two groups of antibiotics, ceftriaxone (n = 6) or ertapenem (n = 5). Pigs were monitored up to 7 h after bacterial injection with fluid and vasopressor support to maintain the mean arterial blood pressure over 65 mmHg. Blood sampling for blood culture and plasma acquisition was performed before and every predefined hour after E. coli injection. Cytokine (tumor necrosis factor-alpha, interleukin [IL]-1 beta, IL-6, IL-8, IL-10, C-reactive protein, procalcitonin, presepsin, heparan sulfate, syndecan, and soluble triggering receptor expressed on myeloid cells-1 [sTRE-M1]) levels in plasma were analyzed using enzyme-linked immunosorbent assays. Bacteremia developed after intravenous injection of E coil, and negative conversion was confirmed only in the ertapenem group. While trends of other biomarkers failed to show differences, the trend of sTREM-1 was significantly different between the two groups (P = 0.0001, two-way repeated measures analysis of variance). Among hemodynamics and biomarkers, the sTREM-1 level at post 2 h after antibiotics administration represented a significant difference depending on susceptibility, which can be suggested as a biomarker candidate of in vivo antibiotics susceptibility. Further clinical studies are warranted for validation. IMPORTANCE Early and appropriate antibiotic treatment is a keystone in treating patients with sepsis. Despite its importance, blood culture which requires a few days remains as a pillar of diagnostic method for microorganisms and their antibiotic susceptibility. Whether changes in biomarkers and hemodynamics indicate treatment response of susceptible antibiotic compared to resistant one is not well understood to date. In this study using extended-spectrum beta-lactamase -producing E. coli bacteremia porcine model, we have demonstrated the comprehensive cardiovascular hemodynamics and trends of plasma biomarkers in sepsis and compared them between two groups with susceptible and resistant antibiotics. While other hemodynamics and biomarkers have failed to differ, we have identified that levels of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) significantly differed between the two groups over time. Based on the data in this study, trends of sTREM-1 obtained before the antibiotics and 2 similar to 4 h after the antibiotics could be a novel host biomarker that triggers the step-up choice of antibiotics

Hadron Energy Reconstruction for the ATLAS Calorimetry in the Framework of the Non-parametrical Method

This paper discusses hadron energy reconstruction for the ATLAS barrel prototype combined calorimeter (consisting of a lead-liquid argon electromagnetic part and an iron-scintillator hadronic part) in the framework of the non-parametrical method. The non-parametrical method utilizes only the known $e/h$ ratios and the electron calibration constants and does not require the determination of any parameters by a minimization technique. Thus, this technique lends itself to an easy use in a first level trigger. The reconstructed mean values of the hadron energies are within $\pm 1$ of the true values and the fractional energy resolution is $[(58\pm3)/\sqrt{E}+(2.5\pm0.3)$. The value of the $e/h$ ratio obtained for the electromagnetic compartment of the combined calorimeter is $1.74\pm0.04$ and agrees with the prediction that $e/h > 1.7$ for this electromagnetic calorimeter. Results of a study of the longitudinal hadronic shower development are also presented. The data have been taken in the H8 beam line of the CERN SPS using pions of energies from 10 to 300 GeV.Comment: 33 pages, 13 figures, Will be published in NIM

Search for supersymmetry with a dominant R-parity violating LQDbar couplings in e+e- collisions at centre-of-mass energies of 130GeV to 172 GeV

A search for pair-production of supersymmetric particles under the assumption that R-parity is violated via a dominant LQDbar coupling has been performed using the data collected by ALEPH at centre-of-mass energies of 130-172 GeV. The observed candidate events in the data are in agreement with the Standard Model expectation. This result is translated into lower limits on the masses of charginos, neutralinos, sleptons, sneutrinos and squarks. For instance, for m_0=500 GeV/c^2 and tan(beta)=sqrt(2) charginos with masses smaller than 81 GeV/c^2 and neutralinos with masses smaller than 29 GeV/c^2 are excluded at the 95% confidence level for any generation structure of the LQDbar coupling.Comment: 32 pages, 30 figure

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO