Soot Oxidation in Hydrocarbon-free Flames

There are high uncertainties in the existing models of soot oxidation rates. To ameliorate this, soot oxidation in flames was examined using a novel ternary flame system, advanced diagnostics, and a detailed examination of past studies. The ternary flame system comprises a coflowing propylene/air diffusion flame to generate a steady soot column that flows into a hydrogen ring flame. The soot is thereby oxidized in a region far separated from soot formation, which is unlike any past study of soot oxidation in diffusion flames. Nonintrusive optical diagnostics were developed using a digital color camera to measure temperature and soot volume fraction. These diagnostics were validated using a steady laminar ethylene/air diffusion flame and were then applied to the ternary flame. Also measured in the soot flame were velocity, soot primary particle diameter, and stable species concentrations along an axial distance of 45 mm. Temperatures were between 1500 to 1750 K, and O2 partial pressures were between 10-2 to 10-1 bar. The soot flame was found to be lean, and its OH (with partial pressures between 10-4 to 10-3 bar) was expected to be equilibrated owing to the catalyzed radical recombination in the presence of soot. Soot flux and soot oxidation rates (0.5 to 6 g/m2-s) were determined. Soot burnout was 90% at 55 mm height. New soot oxidation mechanisms for O2 and OH were developed from a large body of published soot oxidation measurements. The resulting O2 mechanism has an activation energy of 195 kJ/mol, and the OH mechanism has a collision efficiency of 0.10. Predictions using the new mechanisms are within ±80% of the present measurements in the ternary flame system

Differential Features of Culprit Intracranial Atherosclerotic Lesions: A Whole-Brain Vessel Wall Imaging Study in Patients With Acute Ischemic Stroke.

BackgroundIntracranial atherosclerotic disease tends to affect multiple arterial segments. Using whole-brain vessel wall imaging, we sought to study the differences in plaque features among various types of plaques in patients with a recent unilateral anterior circulation ischemic stroke.Methods and resultsSixty-one patients with unilateral anterior circulation ischemic stroke were referred to undergo whole-brain vessel wall imaging (before and after contrast) within 1 month of symptom onset for intracranial atherosclerotic disease evaluations. Each plaque was classified as a culprit, probably culprit, or nonculprit lesion, according to its likelihood of causing the stroke. The associations between plaque features (thickening pattern, plaque-wall contrast ratio, high signal on T1-weighted images, plaque contrast enhancement ratio, enhancement grade, and enhancement pattern) and culprit lesions were estimated using mixed multivariable logistic regression after adjustment for maximum wall thickness. In 52 patients without motion corruption in whole-brain vessel wall imaging, a total of 178 intracranial plaques in the anterior circulation were identified, including 52 culprit lesions (29.2%), 51 probably culprit lesions (28.7%), and 75 nonculprit lesions (42.1%). High signal on T1-weighted images (adjusted odds ratio, 9.1; 95% confidence interval, 1.9-44.1; P=0.006), grade 2 (enhancement ratio of plaque ≥ enhancement ratio of pituitary) contrast enhancement (adjusted odds ratio, 17.4; 95% confidence interval, 1.8-164.9; P=0.013), and type 2 (≥50% cross-sectional wall involvement) enhancement pattern (adjusted odds ratio, 10.1; 95% confidence interval, 1.3-82.2; P=0.030) were independently associated with culprit lesions.ConclusionsHigh signal on T1-weighted images, grade 2 contrast enhancement, and type 2 enhancement pattern are associated with cerebrovascular ischemic events, which may provide valuable insights into risk stratification

Reduced cytotoxicity of insulin-immobilized CdS quantum dots using PEG as a spacer

Cytotoxicity is a severe problem for cadmium sulfide nanoparticles (CSNPs) in biological systems. In this study, mercaptoacetic acid-coated CSNPs, typical semiconductor Q-dots, were synthesized in aqueous medium by the arrested precipitation method. Then, amino-terminated polyethylene glycol (PEG) was conjugated to the surface of CSNPs (PCSNPs) in order to introduce amino groups to the surface. Finally, insulin was immobilized on the surface of PCSNPs (ICSNPs) to reduce cytotoxicity as well as to enhance cell compatibility. The presence of insulin on the surface of ICSNPs was confirmed by observing infrared absorptions of amide I and II. The mean diameter of ICSNPs as determined by dynamic light scattering was about 38 nm. Human fibroblasts were cultured in the absence and presence of cadmium sulfide nanoparticles to evaluate cytotoxicity and cell compatibility. The results showed that the cytotoxicity of insulin-immobilized cadmium sulfide nanoparticles was significantly suppressed by usage of PEG as a spacer. In addition, cell proliferation was highly facilitated by the addition of ICSNPs. The ICSNPs used in this study will be potentials to be used in bio-imaging applications

Atomic H-Induced Mo_2C Hybrid as an Active and Stable Bifunctional Electrocatalyst

Mo_2C nanocrystals (NCs) anchored on vertically aligned graphene nanoribbons (VA-GNR) as hybrid nanocatalysts (Mo_2C-GNR) are synthesized through the direct carbonization of metallic Mo with atomic H treatment. The growth mechanism of Mo2C NCs with atomic H treatment is discussed. The Mo_2C-GNR hybrid exhibits highly active and durable electrocatalytic performance for the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). For HER, in an acidic solution the Mo_2C-GNR has an onset potential of 39 mV and a Tafel slope of 65 mV dec^(-1), in a basic solution Mo_2C-GNR has an onset potential of 53 mV, and Tafel slope of 54 mV dec^(-1). It is stable in both acidic and basic media. Mo2C-GNR is a high activity ORR catalyst with a high peak current density of 2.01 mA cm^(-2), an onset potential of 0.94 V that is more positive vs reversible hydrogen electrode, a high electron transfer number n (∼3.86) and long-term stability

Constructing prediction models for excessive daytime sleepiness by nomogram and machine learning: A large Chinese multicenter cohort study

ObjectiveAlthough risk factors for excessive daytime sleepiness (EDS) have been reported, there are still few cohort-based predictive models for EDS in Parkinson’s disease (PD). This 1-year longitudinal study aimed to develop a predictive model of EDS in patients with PD using a nomogram and machine learning (ML).Materials and methodsA total of 995 patients with PD without EDS were included, and clinical data during the baseline period were recorded, which included basic information as well as motor and non-motor symptoms. One year later, the presence of EDS in this population was re-evaluated. First, the baseline characteristics of patients with PD with or without EDS were analyzed. Furthermore, a Cox proportional risk regression model and XGBoost ML were used to construct a prediction model of EDS in PD.ResultsAt the 1-year follow-up, EDS occurred in 260 of 995 patients with PD (26.13%). Baseline features analysis showed that EDS correlated significantly with age, age of onset (AOO), hypertension, freezing of gait (FOG). In the Cox proportional risk regression model, we included high body mass index (BMI), late AOO, low motor score on the 39-item Parkinson’s Disease Questionnaire (PDQ-39), low orientation score on the Mini-Mental State Examination (MMSE), and absence of FOG. Kaplan–Meier survival curves showed that the survival prognosis of patients with PD in the high-risk group was significantly worse than that in the low-risk group. XGBoost demonstrated that BMI, AOO, PDQ-39 motor score, MMSE orientation score, and FOG contributed to the model to different degrees, in decreasing order of importance, and the overall accuracy of the model was 71.86% after testing.ConclusionIn this study, we showed that risk factors for EDS in patients with PD include high BMI, late AOO, a low motor score of PDQ-39, low orientation score of MMSE, and lack of FOG, and their importance decreased in turn. Our model can predict EDS in PD with relative effectivity and accuracy

Tailoring sub-3.3 angstrom ultramicropores in advanced carbon molecular sieve membranes for blue hydrogen production

Carbon molecular sieve (CMS) membranes prepared by carbonization of polymers containing strongly size-sieving ultramicropores are attractive for high-temperature gas separations. However, polymers need to be carbonized at extremely high temperatures (900&deg; to 1200&deg;C) to achieve sub-3.3 &Aring; ultramicroporous channels for H2/CO2 separation, which makes them brittle and impractical for industrial applications. Here, we demonstrate that polymers can be first doped with thermolabile cross-linkers before low-temperature carbonization to retain the polymer processability and achieve superior H2/CO2 separation properties. Specifically, polybenzimidazole (PBI) is cross-linked with pyrophosphoric acid (PPA) via H bonding and proton transfer before carbonization at &le;600&deg;C. The synergistic PPA doping and subsequent carbonization of PBI increase H2 permeability from 27 to 140 Barrer and H2/CO2 selectivity from 15 to 58 at 150&deg;C, superior to state-of-the-art polymeric materials and surpassing Robeson&rsquo;s upper bound. This study provides a facile and effective way to tailor subnanopore size and porosity in CMS membranes with desirable molecular sieving ability. &nbsp;</p