Gasoline flame behavior at elevated temperature and pressure

Freely propagating laminar premixed flames of stoichiometric mixtures of gasoline surrogate and iso-octane with air are computed using three chemi- cal kinetics mechanisms of varied complexity and detail. A good agreement of the computed burning velocities with past experimental data is observed. The burning velocities of these mixtures at temperature of 850 ≤ T ≤ 950 decrease with pressure up to about 3 MPa and starts to increase beyond this pressure. This contrasting behavior is related to the role of pressure dependent reaction involving OH and the influence of this radical on the fuel consumption rate. The results suggest that the overall order of the com- bustion reaction is larger than two at pressures higher than 3 MPa. Hence, one must be cautious in extending the commonly used laminar flame speed correlation with pressure to thermo-chemical conditions of interest for future engines.KACS

Dysphagia and dyspnea by lingual thyroid mass: An appropriate approach

Lingual thyroid is a rare embryological anomaly originated from the thyroid gland failure that descends from the foramen cecum to its normal eutopic pre-laryngeal site. The case in this study was a 39. year old female, presenting with the sensation of a foreign body, progressive dysphagia and dyspnea. Indirect laryngoscopy revealed a large well-defined mass in the tongue base. Imaging studies confirmed the diagnosis of large ectopic lingual thyroid. The surgery was performed via an external cervical approach due to the mass size. The decision on the best treatment looks into the mass position, size, symptoms, airway emergency and medical facilities. © 2014

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

We focus on the challenging task of real-time semantic segmentation in this paper. It finds many practical applications and yet is with fundamental difficulty of reducing a large portion of computation for pixel-wise label inference. We propose an image cascade network (ICNet) that incorporates multi-resolution branches under proper label guidance to address this challenge. We provide in-depth analysis of our framework and introduce the cascade feature fusion unit to quickly achieve high-quality segmentation. Our system yields real-time inference on a single GPU card with decent quality results evaluated on challenging datasets like Cityscapes, CamVid and COCO-Stuff.Comment: ECCV 201

Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery

Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster management. The huge variation in object scale, orientation, category, and complex backgrounds, as well as the different camera sensors pose great challenges for current algorithms. In this work, we propose a new method consisting of a novel joint image cascade and feature pyramid network with multi-size convolution kernels to extract multi-scale strong and weak semantic features. These features are fed into rotation-based region proposal and region of interest networks to produce object detections. Finally, rotational non-maximum suppression is applied to remove redundant detections. During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular. Our method achieves 68.16% mAP on horizontal and 72.45% mAP on oriented bounding box detection tasks on the challenging DOTA dataset, outperforming all published methods by a large margin (+6% and +12% absolute improvement, respectively). Furthermore, it generalizes to two other datasets, NWPU VHR-10 and UCAS-AOD, and achieves competitive results with the baselines even when trained on DOTA. Our method can be deployed in multi-class object detection applications, regardless of the image and object scales and orientations, making it a great choice for unconstrained aerial and satellite imagery.Comment: ACCV 201

Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study

Background: The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown. Methods: 32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence. Results: While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally. Limitations: All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas. Conclusions: An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression

Isolation and confirmation of viral nervous necrosis (VNN) disease in golden grey mullet (Liza aurata) and leaping mullet (Liza saliens) in the Iranian waters of the Caspian Sea

The present study was conducted on 428 moribund mullet fish samples to isolate and identify the causative agent of a mysterious acute mortality which recently occurred in wild mullets in Iranian waters of Caspian Sea, suspected to be due to viral nervous necrosis (VNN) disease. Disease investigation was carried out employing various diagnostic procedures such as virology, bacteriology, parasitology, haematology, histopathology, IFAT, IHC and nested RT-PCR. Brain and eye samples of affected fishes were collected in sterile conditions and then kept at -80 °C for cell culture isolation and nested RT-PCR detection of the causative agent. Other tissue samples were also collected and fixed for histopathology, IHC and EM examinations. CPE was observed in cell cultures at 6 days after inoculation. Nine samples were found positive with virological assay. Nested RT-PCR, performed on suspected tissues and CPE positive samples, showed that about 21 tissue samples and all the CPE positive samples were positive for VNN virus (VNNV). IFAT was selected as a confirmatory method for detecting the presence of Betanodavirus antigen, cell culture isolation results and nested RT-PCR findings. Moreover, VNNV particles with 25-30 nm in diameter were also visualized in the infected brain and retina. In pathogenicity studies, guppy fishes bathed in VNNV-infected tissue culture (10-4 TCID50) showed clinical signs similar to naturally infected mullet after 15 days post infection (dpi), with mortality rates reaching up to 100% at 30 dpi. Affected organ samples as examined by cell culture isolation, IFAT, IHC and histopathology, revealed the presence of VNNV in the guppy fishes. In conclusion, it was confirmed that VNNV was the main causative agent for the disease outbreak in mullet fish in the Caspian Sea, and this is such first official report of VNN disease from Iran

Assessment of SGS closure for isochoric combustion of hydrogen-air mixture

Direct numerical simulation (DNS) data of freely propagating turbulent premixed flame of stoichiometric hydrogen air mixture inside a closed vessel is analysed to study a sub-grid combustion closure based on unstrained flamelet approach. This modelling framework needs closures for the sub-grid scale (SGS) reaction rate and scalar dissipation rate. The results show that the closure models for these two SGS quantities work quite well. The dissipation rate closure involves a scale dependent parameter, β c , which is related to the flame curvature induced effects. The reactivity of reactant mixture increases with time in isochoric combustion because the mixture temperature and pressure increases with time. This also influences the parameter β c and thus the dynamic evaluation of this parameter is investigated using the DNS data

Investigation of the effect of flow rate on fluid heat transfer in counter-flow helical heat exchanger using CFD method

Heat exchangers are generally used in the process of heat transfer between two different fluids separated from each other by a solid wall in order to save time and reduce expenses. Fluids behavior change by adding a wire-insert in its path. To investigate heat transfer parameters, we need to simulate the whole system. In this study, heat transfer of counter-flow helical double pipe heat exchanger was modelled by using Computational Fluid Dynamics (CFD) in "Ansys CFX". The cold and hot fluids temperature were in the ranges of 10-20C° and 30-50C° respectively. The Reynolds number of flows were in the range of 4×103 to 42×103 and the process was singlephase. The model was eventually evaluated by experimental data after simulation. The results indicated that the model was able to interpret the experimental results with correlation coefficients of 0.98 and 0.97 for hot and cold streams respectively. Furthermore, the wire-insert installed to the cold flow path caused more fluid turbulence and increased the temperature difference of the cold fluid inlet and outlet proportional to the hot fluid