Laminar Flame Speeds and Strain Sensitivities of Mixtures of H 2 with CO, CO 2 and N 2 at Elevated Temperatures

ABSTRACT Laminar flame speed and strain sensitivities have been measured for mixtures of H 2 /CO/CO 2 /N 2 /O 2 with a wall stagnation flame technique at high preheat temperature (700 K) and lean conditions. The measurements are compared with numerical predictions based on two reaction mechanisms: GRI Mech 3.0 and a H 2 /CO mechanism (Davis et al.). For H 2 :CO 50:50 fuel mixtures, both models tend to over predict the temperature dependence of the flame speed especially at very lean conditions, which confirms the trend found in an earlier study employing a Bunsen flame technique. The predicted strain sensitivities are in good agreement with the measurements. For 50:50 H 2 :CO fuel mixtures diluted with 40% CO 2 , the amount of over prediction by the models is about the same as in the undiluted case, which suggests that radiation effects associated with CO 2 addition are not important for this mixture at highly preheated lean condition. For low H 2 content (5 to 20%) H 2 /CO fuel mixtures at 5 atm and fuel lean condition, the predicted unstrained flame speeds are in excellent agreement with the measurements, but the models fail to predicted the strain sensitivity as the amount of H 2 increases to 20%. Results are also presented for pure H 2 with N 2 diluted air (O 2 :N 2 1:9) over a range of equivalence ratios. At lean conditions, the models over predict the measured flame speed by as much as 30%, and the amount of over prediction decreases as the equivalence ratio increases to stoichiometric and rich condition. The measured strain sensitivities are three times higher than the model predictions at lean conditions. More importantly, the predicted strain sensitivities do not change with equivalence ratio for both models, while the measurements reveal a clear trend (decreasing and then increasing) as the fuel-air ratio changes from lean to rich

Functional network disorganization and cognitive decline following fractionated whole-brain radiation in mice

Cognitive dysfunction following radiotherapy (RT) is one of the most common complications associated with RT delivered to the brain, but the precise mechanisms behind this dysfunction are not well understood, and to date, there are no preventative measures or effective treatments. To improve patient outcomes, a better understanding of the effects of radiation on the brain\u27s functional systems is required. Functional magnetic resonance imaging (fMRI) has shown promise in this regard, however, compared to neural activity, hemodynamic measures of brain function are slow and indirect. Understanding how RT acutely and chronically affects functional brain organization requires more direct examination of temporally evolving neural dynamics as they relate to cerebral hemodynamics for bridging with human studies. In order to adequately study the underlying mechanisms of RT-induced cognitive dysfunction, the development of clinically mimetic RT protocols in animal models is needed. To address these challenges, we developed a fractionated whole-brain RT protocol (3Gy/day for 10 days) and applied longitudinal wide field optical imaging (WFOI) of neural and hemodynamic brain activity at 1, 2, and 3 months post RT. At each time point, mice were subject to repeated behavioral testing across a variety of sensorimotor and cognitive domains. Disruptions in cortical neuronal and hemodynamic activity observed 1 month post RT were significantly worsened by 3 months. While broad changes were observed in functional brain organization post RT, brain regions most impacted by RT occurred within those overlapping with the mouse default mode network and other association areas similar to prior reports in human subjects. Further, significant cognitive deficits were observed following tests of novel object investigation and responses to auditory and contextual cues after fear conditioning. Our results fill a much-needed gap in understanding the effects of whole-brain RT on systems level brain organization and how RT affects neuronal versus hemodynamic signaling in the cortex. Having established a clinically-relevant injury model, future studies can examine therapeutic interventions designed to reduce neuroinflammation-based injury following RT. Given the overlap of sequelae that occur following RT with and without chemotherapy, these tools can also be easily incorporated to examine chemotherapy-related cognitive impairment

Diagnostic Armamentarium of Infectious Keratitis: A Comprehensive Review

Infectious keratitis (IK) represents the leading cause of corneal blindness worldwide, particularly in developing countries. A good outcome of IK is contingent upon timely and accurate diagnosis followed by appropriate interventions. Currently, IK is primarily diagnosed on clinical grounds supplemented by microbiological investigations such as microscopic examination with stains, and culture and sensitivity testing. Although this is the most widely accepted practice adopted in most regions, such an approach is challenged by several factors, including indistinguishable clinical features shared among different causative organisms, polymicrobial infection, long diagnostic turnaround time, and variably low culture positivity rate. In this review, we aim to provide a comprehensive overview of the current diagnostic armamentarium of IK, encompassing conventional microbiological investigations, molecular diagnostics (including polymerase chain reaction and mass spectrometry), and imaging modalities (including anterior segment optical coherence tomography and in vivo confocal microscopy). We also highlight the potential roles of emerging technologies such as next-generation sequencing, artificial intelligence-assisted platforms. and tele-medicine in shaping the future diagnostic landscape of IK

Patients with fibromyalgia show increased beta connectivity across distant networks and microstates alterations in resting-state electroencephalogram

Fibromyalgia (FM) is a chronic condition characterized by widespread pain of unknown etiology associated with alterations in the central nervous system. Although previous studies demonstrated altered patterns of brain activity during pain processing in patients with FM, alterations in spontaneous brain oscillations, in terms of functional connectivity or microstates, have been barely explored so far. Here we recorded the EEG from 43 patients with FM and 51 healthy controls during open-eyes resting-state. We analyzed the functional connectivity between different brain networks computing the phase lag index after group Independent Component Analysis, and also performed an EEG microstates analysis. Patients with FM showed increased beta band connectivity between different brain networks and alterations in some microstates parameters (specifically lower occurrence and coverage of microstate class C). We speculate that the observed alterations in spontaneous EEG may suggest the dominance of endogenous top-down influences; this could be related to limited processing of novel external events and the deterioration of flexible behavior and cognitive control frequently reported for FM. These findings provide the first evidence of alterations in long-distance phase connectivity and microstate indices at rest, and represent progress towards the understanding of the pathophysiology of fibromyalgia and the identification of novel biomarkers for its diagnosis.Spanish Government (Ministerio de Economía y Competitividad; grant number PSI2016-75313-R) and from the Galician Government (Consellería de Cultura, Educación e Ordenación Universitaria; axudas para a consolidación e Estruturación de unidades de investigación competitivas do Sistema universitario de Galicia; grant number GRC GI-1807-USC; REF: ED431-2017/27). A.G.V. was partially supported by a grant from Xunta de Galicia (Axudas de apoio á etapa de formación posdoutoral 2018) and by the Portuguese Foundation for Science and Technology within the scope of the Individual Call to Scientific Employment Stimulus 201

A Prospective Evaluation of Infant Cerebellar-Cerebral Functional Connectivity in Relation to Behavioral Development in Autism Spectrum Disorder

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection. Methods: Data from the Infant Brain Imaging Study (n = 94, 68 male) were used to examine 6-month cerebellar functional connectivity magnetic resonance imaging in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning–based predictive tests examined cerebellar–frontoparietal network (FPN; subserves error signaling in support of EBL) and cerebellar–default mode network (DMN; broadly implicated in ASD) connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven functional connectivity magnetic resonance imaging enrichment examined brain-wide behavioral associations, with post hoc tests of cerebellar connections. Results: Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. Functional connectivity magnetic resonance imaging enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post hoc tests did not suggest a role for cerebellar connections. Conclusions: We failed to identify cerebellar functional connectivity–based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities

Characterization of extinction events near blowout in swirl-dump combustors

This work examines the evolution of the lean blowout (LBO) process in a swirl-dumpstabilized combustor with center body. Previous studies identified extinction-reignition events as precursors to LBO. These events are investigated in greater detail using simultaneous fiber optic-based chemiluminescence sensors and high speed imaging in an atmospheric pressure, premixed methane-air combustor. It is found that the flame, which is stabilized above the center body, at first partially detaches due to turbulent fluctuations. This detached region moves around the center body due to the swirl and the feedback mechanism of the inner recirculation zone. As the LBO limit is approached, the weaker flame detaches more often and over a larger extent of the center body. When the flame is detached beyond a certain extent, enough cold packets of unburned gases move around the inner recirculation zone to reduce the feedback needed for stabilization and the flame detaches completely from the center body. This is the source of the extinction events previously noted in the sensor data. The flow field responds to the decreased heat release with a larger recirculation zone and stronger swirl. The flame shape and flame stabilization change to a tornado mode. In this mode, the flame is stabilized much farther downstream of the combustor inlet, but an occasional packet of burning gases is convected back to the inlet. If this flame packet is sufficiently strong, the original flow field and flame shape are restored. This return of the original stable flame mode is the onset of the reignition events found in the sensor data. Several occurrences of these events in time gradually weaken the combustion process and eventually the convected flame packets are not strong enough to restabilize the combustor, i.e., the combustor blows out. This understanding of the process of flame stabilization loss provides the necessary insight for improved design and analysis of LBO sensors systems