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671,909 result(s) for "P. D."
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Nanoparticle-Enhanced Engine Oils for Automotive Applications: Thermal Conductivity and Heat Capacity Improvements
The poor thermal and physical properties of conventional engine oils limit vehicle performance and durability. This research aims to investigate the effect of nanoparticles such as fullerene C60, titanium dioxide (TiO2), iron oxide (Fe2O3), and reduced graphene oxide (rGO) nanoparticles on 10W30 Mobil engine oil. In this study, the effect of nanoparticle concentrations at different mass fractions (0.01, 0.05, and 0.1) was examined within the temperature range 30–120 °C. The nanofluids were prepared using a two-step direct mixing method and thermal properties were measured using a LAMBDA thermal conductivity meter, which uses the transient hot wire method according to the ISO standards. Due to the low concentrations of the nanofluids, surfactants were not required at all, and the stability of the nanofluids was visually monitored over a period of four weeks. Accordingly, the largest improvement in thermal conductivity occurred with TiO2/10W30 at a mass fraction of 0.1 wt.% at 80 °C, and the specific heat capacity improved due to Fe2O3/10W30 addition at a mass fraction of 0.1 at 70 °C; these were 5.8% and 14.4%, respectively, for the base oil. Thermal diffusivity remained largely unaffected by the addition of the nanoparticles, and fullerene C60 showed no significant effect on any thermal property. It was concluded that the thermal properties of the engine oil were considerably enhanced by the added nanoparticles at different weight fractions and temperature values.
Sam and the firefly
When Sam, the owl, teaches Gus, the firefly, to write words in the sky, cars crash, movies are free, and hot dogs are cold.
The solar nebula origin of (486958) Arrokoth, a primordial contact binary in the Kuiper Belt
The New Horizons spacecraft’s encounter with the cold classical Kuiper Belt object (486958) Arrokoth (provisional designation 2014 MU₆₉) revealed a contact-binary planetesimal. We investigated how Arrokoth formed and found that it is the product of a gentle, low-speed merger in the early Solar System. Its two lenticular lobes suggest low-velocity accumulation of numerous smaller planetesimals within a gravitationally collapsing cloud of solid particles. The geometric alignment of the lobes indicates that they were a co-orbiting binary that experienced angular momentum loss and subsequent merger, possibly because of dynamical friction and collisions within the cloud or later gas drag. Arrokoth’s contact-binary shape was preserved by the benign dynamical and collisional environment of the cold classical Kuiper Belt and therefore informs the accretion processes that operated in the early Solar System.
The best nest
Mr. and Mrs. Bird search for a place to build a new nest only to discover their old one is better.
Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets
Evidence is presented of a reduction in relative humidity over low‐latitude and midlatitude land areas over a period of about 10 years leading up to 2008, based on monthly anomalies in surface air temperature and humidity from comprehensive European Centre for Medium‐Range Weather Forecasts reanalyses (ERA‐40 and ERA‐Interim) and from Climatic Research Unit and Hadley Centre analyses of monthly station temperature data (CRUTEM3) and synoptic humidity observations (HadCRUH). The data sets agree well for both temperature and humidity variations for periods and places of overlap, although the average warming over land is larger for the fully sampled ERA data than for the spatially and temporally incomplete CRUTEM3 data. Near‐surface specific humidity varies similarly over land and sea, suggesting that the recent reduction in relative humidity over land may be due to limited moisture supply from the oceans, where evaporation has been limited by sea surface temperatures that have not risen in concert with temperatures over land. Continental precipitation from the reanalyses is compared with a new gauge‐based Global Precipitation Climatology Centre (GPCC) data set, with the combined gauge and satellite products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC), Merged Analysis of Precipitation (CMAP), and with CPC's independent gauge analysis of precipitation over land (PREC/L). The reanalyses agree best with the new GPCC and latest GPCP data sets, with ERA‐Interim significantly better than ERA‐40 at capturing monthly variability. Shifts over time in the differences among the precipitation data sets make it difficult to assess their longer‐term variations and any link with longer‐term variations in humidity.
Long-term benefits and risks of frontline nilotinib vs imatinib for chronic myeloid leukemia in chronic phase: 5-year update of the randomized ENESTnd trial
In the phase 3 Evaluating Nilotinib Efficacy and Safety in Clinical Trials–Newly Diagnosed Patients (ENESTnd) study, nilotinib resulted in earlier and higher response rates and a lower risk of progression to accelerated phase/blast crisis (AP/BC) than imatinib in patients with newly diagnosed chronic myeloid leukemia in chronic phase (CML-CP). Here, patients’ long-term outcomes in ENESTnd are evaluated after a minimum follow-up of 5 years. By 5 years, more than half of all patients in each nilotinib arm (300 mg twice daily, 54%; 400 mg twice daily, 52%) achieved a molecular response 4.5 (MR 4.5 ; BCR-ABL ⩽0.0032% on the International Scale) compared with 31% of patients in the imatinib arm. A benefit of nilotinib was observed across all Sokal risk groups. Overall, safety results remained consistent with those from previous reports. Numerically more cardiovascular events (CVEs) occurred in patients receiving nilotinib vs imatinib, and elevations in blood cholesterol and glucose levels were also more frequent with nilotinib. In contrast to the high mortality rate associated with CML progression, few deaths in any arm were associated with CVEs, infections or pulmonary diseases. These long-term results support the positive benefit-risk profile of frontline nilotinib 300 mg twice daily in patients with CML-CP.
Automation and control of laser wakefield accelerators using Bayesian optimization
Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%. Laser wakefield accelerators are compact sources of ultra-relativistic electrons which are highly sensitive to many control parameters. Here the authors present an automated machine learning based method for the efficient multi-dimensional optimization of these plasma-based particle accelerators.