Characteristics Of Vessels Research Articles

Characteristics of donor vessels and cerebral blood flow in the chronic phase after combined revascularization surgery for moyamoya disease

ObjectiveThis study aimed to analyze whether the development of donor vessels after combined revascularization surgery for moyamoya disease (MMD) is related to cerebral blood flow (CBF) changes. MethodsWe retrospectively reviewed the charts of 11 adult (12 hemispheres) and 13 pediatric (19 hemispheres) patients who underwent combined revascularization in our department. The total vessel cross-sectional area (TVA) was the sum of the cross-sectional areas of the superficial temporal, middle meningeal, and deep temporal arteries imaged using time-of-flight magnetic resonance angiography. The ipsilateral relative CBF (RCBF) on the brain surface in the craniotomy area was calculated by single-photon emission computed tomography. ΔTVA and ΔRCBF were defined as the preoperative and postoperative ratios of TVA and RCBF, and their correlations were analyzed in adult and pediatric patients. ResultsThe TVA and RCBF showed a significant increase after surgery, regardless of the age group. However, there was no significant correlation between ΔTVA and ΔRCBF in either the adult or pediatric groups. While the adult group exhibited significantly higher ΔRCBF values compared to the pediatric group (p < 0.01, r = −0.44), the ΔTVA values were higher in the pediatric group compared to the adult group (p = 0.06). ConclusionsIn the chronic phase after combined revascularization surgery for MMD, the development of measurable TVA of donor vessels does not necessarily correlate with an increase in CBF around the craniotomy area.

Denoised Non-Local Means with BDDU-Net Architecture for Robust Retinal Blood Vessel Segmentation

Retinal blood vessels can be obtained by image segmentation. This study proposes combining image enhancement and segmentation to obtain retinal blood vessels. The image enhancement stages use CLAHE and Denoised Non-Local Means to increase contrast and reduce noise on the original image, and Bottom-Hat (BTH) filtering is used to lighten dark features in the image so the features become lighter and darken the bright features in the image. Bottom Hat is applied to make the features of the blood vessels in the retinal image more visible. The segmentation architecture proposes BDDU-Net architecture which combines U-Net in the encoder part, DenseNet in the bridge part, and Bi-ConvLSTM in the decoder part. Image enhancement performance results are PSNR and SSIM. The PSNR is more than 40 dB on both the DRIVE and STARE datasets. The SSIM results are close to 1 on the DRIVE and STARE datasets. These results show that the image enhancement stages in the proposed method can enhance the quality of the original image. The segmentation performance results of BDDU-Net architecture are measured based on accuracy, sensitivity, specificity, IoU, and F1-Score. The DRIVE dataset obtained 95.578% for accuracy, 85.75% for sensitivity, 96.75% for specificity, 67.407% for IoU, and 80.53% for F1-Score. The STARE dataset obtained 97.63% for accuracy, 84.33% for sensitivity, 98.66% for specificity, 75.67% for IoU, and 86.15% for F1-Score. Based on the image enhancement and image segmentation results, these results show that the proposed method is great for enhancing image quality and excellent for blood vessel segmentation in retinal images, although IoU results on the DRIVE dataset need to be improved.

Application of CFD and nodal expansion method for simulation and analysis of boron dilution accident

Nuclear power, as a low-carbon energy source, provides the steady and reliable electricity. In this power source, safe operation plays a significant role from the point of view of design and economic cost. While nuclear power plants are designed to be safe in their operation and safe in the event of any malfunction or accident, some accidents with considerable occurrence frequency should be considered to provide related safety system and operation. The malfunction of boron injection system is one of this accident affecting the chemical and neutronic characteristics of cooling fluid. The aim of this study is the simulation and analysis of the boron dilution accident as one of Design Basis Accident, by considering the heterogeneous distribution of boron. For this purpose, CFD methods were used for exact evaluation of the boron distribution in each fuel assembly. Also, cross-section correction module and core calculation module are respectively developed by a cell calculation code and nodal expansion method. These modules are employed to apply absorber effects including boron and control banks and calculate 3D relative power. The results reveal the effect of heterogeneous distribution of boron in reactor pressure vessel and non-uniform chemical characteristics of coolant across fuel channels.

Impact of Environmental Conditions on Wood Anatomical Traits of Green Alder (Alnus alnobetula) at the Alpine Treeline

Due to land use change, green alder (Alnus alnobetula), formerly restricted to moist slopes, is now expanding to drier sun-exposed sites at the alpine treeline. The highly productive shrub is forming closed thickets, establishing nitrogen-saturated species poor shrublands. To evaluate wood anatomical adaptations to changing environmental conditions, we analyzed vessel characteristics (mean vessel area, MVA; vessel density, VD; and theoretic conductive area, TCA) and axial parenchyma abundance, as well as their distribution in the annual ring at a moist north-facing and a dry south-facing site at the alpine treeline on Mt. Patscherkofel (Central European Alps, Austria). Results revealed that lower soil water availability and enhanced evaporative demand did not affect MVA while VD and TCA were significantly reduced at the dry south-facing site. This suggests that in green alder, vessel size is a static trait whereas vessel number responds plastic. Limited water availability also triggered a significant increase in axial parenchyma, confirming the important role of xylem parenchyma in water relations. Harsh environmental conditions at the distributional limit of green alder may have affected xylogenesis, leading to a near semi-ring-porous distribution of vessels and an accumulation of parenchyma in the late growing season. We conclude that in a warmer and drier climate, growth limitation and physiological stress may set limits to the distribution of Alnus alnobetula at drought-prone sites in the alpine treeline ecotone.

The ceramic complex of the Transitional Period from the Bronze to the Iron Age of the settle-ment of Mergen 6 in the Lower Ishim River basin (Western Siberia)

The settlement of Mergen 6 is located in the Ishim District of the Tyumen Oblast on the northeastern shore of Lake Mergen by the head of the river Mergenka. It was studied in 1990 and 2002–2011 under the direction of V.A. Zakh and S.N. Skochina. On the site, 1494 m2 were examined. The settlement is multi-layered and contains the materials from the Neolithic Period through to the Middle Ages. The research is aimed at the detailed characterisation of the ceramic complex of the Transitional Period from the Bronze to the Early Iron Age (TPBIA), dated to the 8th–7th cc. BC. The TPBIA ceramic complex is a large one (approximately 7.5 thousand items identified), deposited at a depth predominantly no more than 60 cm from the surface in the layers disturbed by ploughing. It is highly fragmented; whole forms are lacking; in some cases, ceramics was deposited in clusters. Therefore, the object of the research was a subset from the TPBIA ceramic complex of the settlement of Mergen 6 which was analysed on the basis of the formal-classificatory and cultural-historical approaches. With the aid of the methods of mathematical statistics, possible interrelations between the morphological and ornamental traits of the object of the research were established. In the TPBIA ceramic subset, the fragments of the pottery vessels which can be correlated with the ceramics of the archaeological cultures of Krasnoozerka (335 vessels identified by the necks), Gama-yun (no more than 8 items), and Itkul (37 items), and a ceramic group designated as ‘synchretic’ (102 items) were identified. The analy-sis of the morphological and decorative features of the TPBIA ceramics showed quite a close interaction of the diverse population dur-ing the considered period. Elements of the ornament and morphological features of the pottery vessels, constituting the specifics of both the syncretic group of the ceramics, characterised by mixed Krasnoozerka-Gamayun-Itkul traits, as well as by the individual traits of the main cultural groups of the site — on the pottery vessels of the Krasnoozerka group, some elements characteristic of the Gamayun-Itkul decorative patterns; the vessels of the Gamayun-Itkul group have been produced with a deviation from the typical canons — served as markers of the mutual influence.

RCAR-UNet: Retinal vessel segmentation network algorithm via novel rough attention mechanism

The health status of the retinal blood vessels is a significant reference for rapid and non-invasive diagnosis of various ophthalmological, diabetic, and cardio-cerebrovascular diseases. However, retinal vessels are characterized by ambiguous boundaries, with multiple thicknesses and obscured lesion areas. These phenomena cause deep neural networks to face the characteristic channel uncertainty when segmenting retinal blood vessels. The uncertainty in feature channels will affect the channel attention coefficient, making the deep neural network incapable of paying attention to the detailed features of retinal vessels. This study proposes a retinal vessel segmentation via a rough channel attention mechanism. First, the method integrates deep neural networks to learn complex features and rough sets to handle uncertainty for designing rough neurons. Second, a rough channel attention mechanism module is constructed based on rough neurons, and embedded in U-Net skip connection for the integration of high-level and low-level features. Then, the residual connections are added to transmit low-level features to high-level to enrich network feature extraction and help back-propagate the gradient when training the model. Finally, multiple comparison experiments were carried out on three public fundus retinal image datasets to verify the validity of Rough Channel Attention Residual U-Net (RCAR-UNet) model. The results show that the RCAR-UNet model offers high superiority in accuracy, sensitivity, F1, and Jaccard similarity, especially for the precise segmentation of fragile blood vessels, guaranteeing blood vessels’ continuity.

Комплексный анализ тканей амфор и клейм Фасоса по данным фазового и элементного состава

The paper presents the results of studying of the Thasian amphorae fabrics of the second quarter of the 5th — end of the 4th century BC, whose belonging to the island’s products was established on the basis of morphological features of vessels and, in some cases, due to the presence of stamps. A complex approach was used to study amphorae fragments, including the methods of integral (X-ray phase analysis, inductively coupled plasma mass spectrometry) and local (electron microscopy) characterization of the structure and composition. The proven set of methods made it possible to obtain reliable data on the mineral (phase), basic and trace chemical composition of the samples, as well as to study the composition of the fabric base of the samples ceramic body, excluding the influence of mineral impurities and leaners. The analysis of the experimental results allowed to group the objects into separate groups in accordance with the features of the mineralogical and elemental composition. Based on the comparison of the characteristics of these groups with geological and archaeological information about the island of Thasos, the authors advance a hypothesis with a clarification of the origin of Thasos amphorae, namely, their manufacturing in workshops on the eastern and southern coasts of the island.

Macroscopic and Microscopic Anatomical Characteristics of Six Korean Oak Species

The macroscopic and microscopic anatomical characteristics of wood impact its utilization. This study investigated and compared the anatomical characteristics of six Korean oak wood species: Quercus variabilis, Quercus serrata, Quercus mongolica, Quercus dentata, Quercus aliena, and Quercus acutissima. Microscopic anatomical characteristics were evaluated according to the International Association of Wood Anatomists’ list for hardwood identification. Q. variabilis had a corky bark texture, with a color similar to that of Q. serrata. Flat ridges and shallow-fissured barks were observed in Q. serrata and Q. mongolica. The heartwood color was darker than that of sapwood in all species, with color variations. Q. variabilis had heartwood–sapwood colors similar to those of Q. acutissima, while Q. mongolica and Q. aliena presented similar heartwood–sapwood colors. Concerning microscopic features, Q. variabilis and Q. acutissima exhibited similar latewood vessel arrangements, featuring diagonal and/or radial patterns. In contrast, dendritic-to-diagonal patterns of vessels with angular outlines were observed in Q. serrata, Q. mongolica, Q. dentata, and Q. aliena. Additionally, Q. variabilis and Q. acutissima had vasicentric, confluent, and unilateral paratracheal axial parenchyma in the latewood. In summary, bark morphology, bark color, wood color, and latewood vessel characteristics can be used as identification keys for Korean oak species.

Determining basic characteristics of bulk carriers at the early stages of design

This paper considers the task to determine the basic characteristics of bulker vessels. Available studies that define the main characteristics of ships were analyzed. The complexity of the task to choose a prototype in the process of determining the basic characteristics of bulk carriers at the initial stages of design has been shown. The accepted assumption implied that each ship in the sample (a ship database) was designed in such a way that some operational qualities and/or economic characteristics of a vessel are optimal in a certain sense. To solve the task, stochastic factor analysis was used, and the method of principal components was applied, which makes it possible to identify numerical characteristics that affect the parameters of the entire system but are not clearly observed. The factors were compiled that are dimensionless sets of characteristics of sample vessels, which are, in fact, new phase orthogonal coordinates of the problem with unequal variances of the sample along the coordinate directions. Evaluating the significance of correlations of factors and vectors of the sample data makes it possible to discard factors that have a weak influence on the values of the parameters of the sample vessels. Thus, the model of the problem is simplified while preserving essential connections. The analysis of the calculation data revealed that the number of significant factors due to the use of the principal component method decreased from 7 to 3. It was determined that the ships of the same designers are indeed grouped by the value of the factor sets. In the absence of an original algorithm for determining the main characteristics of the vessel at the initial stage of design, the application of the described factor analysis procedure should help with the definition of the main factors that affect the quality of the design. Further, it is possible to apply more subtle mechanisms for project optimization according to selected economic and technical parameters. The data of the numerical calculation of integrated characteristics of the ship are given

One-Shot Learning for Optical Coherence Tomography Angiography Vessel Segmentation Based on Multi-Scale U2-Net

Vessel segmentation in optical coherence tomography angiography (OCTA) is crucial for the detection and diagnosis of various eye diseases. However, it is hard to distinguish intricate vessel morphology and quantify the density of blood vessels due to the large variety of vessel sizes, significant background noise, and small datasets. To this end, a retinal angiography multi-scale segmentation network, integrated with the inception and squeeze-and-excitation modules, is proposed to address the above challenges under the one-shot learning paradigm. Specifically, the inception module extends the receptive field and extracts multi-scale features effectively to handle diverse vessel sizes. Meanwhile, the squeeze-and-excitation module modifies channel weights adaptively to improve the vessel feature extraction ability in complex noise backgrounds. Furthermore, the one-shot learning paradigm is adapted to alleviate the problem of the limited number of images in existing retinal OCTA vascular datasets. Compared with the classic U2-Net, the proposed model gains improvements in the Dice coefficient, accuracy, precision, recall, and intersection over union by 3.74%, 4.72%, 8.62%, 4.87%, and 4.32% respectively. The experimental results demonstrate that the proposed one-shot learning method is an effective solution for retinal angiography image segmentation.

Analysis of pollution prevention performance of vessels in Southeast Asia: Implications towards vessel emission control and reduction

As one of the major sources of pollution emissions in Southeast Asia (SEA), substandard vessels with deficiencies in pollution prevention ability may induce extreme results in local societies and cause pollution to marine environments, an issue that needs to be paid close attention to. Through the incorporation of the tree-augmented naïve learning approach and the maximum a posteriori probability estimation approach, a data-driven Bayesian network focusing on vessel performance in the pollution prevention aspect is trained and developed in this research based on the inspection records in SEA from 2017 to 2022 for the first time. A thorough analysis of the proposed model is conducted subsequently to clarify the influence of different factors on vessel performance in pollution prevention in the SEA. This work reveals insightful implications and contributes to the current research in the following ways: First, key risk variables and sub-areas with strong influence on vessel performance of pollution prevention are identified, i.e., place of detention, vessel size, D141-Marpol Annex I, D144-Marpol Annex IV. Second, characteristics and behaviours of substandard vessels in this aspect are identified for better port supervision and inspection. Third, suggestions to control the unaware actions of ship owners and encourage ship owners to endeavour to enhance the pollution prevention ability of vessels are proposed, i.e., formulate targeted instructions on the vessels with identified characteristics of the substandard vessel and against the violation actions of key sub-areas, implement specialised countermeasures for different countries to restrain the occurrence of substandard vessels in their regions.

SCAN: sequence-based context-aware association network for hepatic vessel segmentation.

Accurate segmentation of hepatic vessel is significant for the surgeons to design the preoperative planning of liver surgery. In this paper, a sequence-based context-aware association network (SCAN) is designed for hepatic vessel segmentation, in which three schemes are incorporated to simultaneously extract the 2D features of hepatic vessels and capture the correlations between adjacent CT slices. The two schemes of slice-level attention module and graph association module are designed to bridge feature gaps between the encoder and the decoder in the low- and high-dimensional spaces. The region-edge constrained loss is designed to well optimize the proposed SCAN, which integrates cross-entropy loss, dice loss, and edge-constrained loss. Experimental results indicate that the proposed SCAN is superior to several existing deep learning frameworks, in terms of 0.845 DSC, 0.856 precision, 0.866 sensitivity, and 0.861 F1-score.

Quantitative Analysis of Bone, Blood Vessels, and Metastases in Mice Tibiae Using Synchrotron Radiation Micro-Computed Tomography

Bone metastases are one of the most dangerous consequences of breast cancer. Early diagnosis and treatment would slow down the development of the disease and increase the survival rates of patients. Bone micro-vasculature is believed to play a major role in the development of bone metastases. It could be used for both diagnosis and as a therapeutic target. Synchrotron radiation micro-computed tomography (SR-µCT) with a contrast agent of blood vessels has been used to analyze the bone vasculature both in healthy and in metastatic bone. However, few studies have investigated the local features of blood vessels around metastases so far. For this purpose, the metastases first need to be automatically segmented. This is a challenging task, however, since the metastases do not contribute a specific contrast to the three-dimensional (3D) SR-µCT images. Here, we propose a new method for the simultaneous segmentation of bone, blood vessels, and metastases from contrast enhanced 3D SR-µCT images based on the nnU-Net architecture. In this study, we showed that only minimal training data was required to achieve a high quality of segmentation. The proposed method allowed for the automatic segmentation of metastases and provided an improved segmentation of bone and blood vessels compared to previous methods while being much more efficient to apply once trained. Further, the automatic segmentation allowed for the measurement of vascular metastases interdistance and to restrict measurements to volumes of interest around the metastases. Finally, we quantitatively analyzed blood vessel parameters locally around metastases. This allowed for the demonstration that a combined anti-angiogenic treatment significantly decreased the volume and thickness of blood vessels close to metastases. The proposed method showed the capacity of the method to reveal new aspects of the blood vessel structure interaction with metastases. This could be further used to both define new targets for precocious detection of metastases as well as to study the kinetics of metastasis development in bone and the action of drugs on this process.

Right-angled vessel characteristics in different stages of type 2 macular telangiectasia (MacTel).

To study right-angled vessels (RAV) in disease progression and macular neovascularization in type 2 macular telangiectasia (MacTel) eyes. This retrospective image analysis study examined type 2 MacTel patients' multicolour® and OCT imaging records from January 2015 to March 2023. Age, gender, laterality, visual acuity, systemic disease, and follow-up duration were recorded. RAV characteristics were assessed using OCT and multicolour® images. This study examined RAV characteristics and type 2 MacTel disease stage. In total, 270 eyes of 146 patients (97 females, 66%) with a mean age of 60.77 ± 9.34 years were studied. 153 (57%) eyes showed RAV. The non-proliferative stage of type 2 MacTel had either no RAV or a normal-calibre right-angled vein, while the proliferative stage had a right-angled artery and a dilated or normal-calibre RAV [p < 0.001]. RAV characteristics differed at the final follow-up (p < 0.001). 11 eyes transitioned from non-proliferative to proliferative after a median period of 26 months (range: 5-96 months). RAV characteristics changed from a normal calibre right-angled vein at presentation to a normal calibre vein and artery in 6 (55%) eyes and to a dilated vein and artery in 5 (45%) eyes respectively. RAV characteristics may indicate type 2 MacTel stages. A right-angled artery in type 2 MacTel may indicate proliferative disease.

Experimental investigation on the deformation and damage of steel ribbon wound vessel for hydrogen storage under external impact and blast loading

Steel ribbon wound vessel is a preferred type for stationary storage of high-pressure hydrogen in refueling stations. However, it is under the threat of fragment impact and blast loads caused by accidental explosions of hydrogen or other vessels. For the first time, the fragment-simulating projectile (FSP) impact tests with impact kinetic energy range from 1.8 × 103 J–4.9 × 103 J and external blast loading tests with TNT equivalent range from 157 g–4 kg of industrial-grade 50 MPa steel ribbon wound vessel were carried out. The damage of vessel under FSP impact loading was studied. The effect of concentrated and distributed blast loads on the deformation and damage of gas-filled vessel was analyzed, and the explosion resistance of vessel under near-field blast loading was explored. It is revealed that: 1) the steel ribbon wound vessels generally have good resistances to external blast and impact loads, 2) the primary damage characteristics of vessel under contact/near-field blast loading was localized depression deformation, accompanied by steel ribbons warping as the shock wave impulse increases, 3) the saddle fails earlier than the vessel under the near-field blast loading. Further, the failure modes of vessel under extreme blast loads were revealed. Results can provide reference for the safe design and validation of dynamic damage/failure analysis models of steel ribbon wound vessels.

PEA-Net: A progressive edge information aggregation network for vessel segmentation

Automatic vessel segmentation is a critical area of research in medical image analysis, as it can greatly assist doctors in accurately and efficiently diagnosing vascular diseases. However, accurately extracting the complete vessel structure from images remains a challenge due to issues such as uneven contrast and background noise. Existing methods primarily focus on segmenting individual pixels and often fail to consider vessel features and morphology. As a result, these methods often produce fragmented results and misidentify vessel-like background noise, leading to missing and outlier points in the overall segmentation. To address these issues, this paper proposes a novel approach called the progressive edge information aggregation network for vessel segmentation (PEA-Net). The proposed method consists of several key components. First, a dual-stream receptive field encoder (DRE) is introduced to preserve fine structural features and mitigate false positive predictions caused by background noise. This is achieved by combining vessel morphological features obtained from different receptive field sizes. Second, a progressive complementary fusion (PCF) module is designed to enhance fine vessel detection and improve connectivity. This module complements the decoding path by combining features from previous iterations and the DRE, incorporating nonsalient information. Additionally, segmentation-edge decoupling enhancement (SDE) modules are employed as decoders to integrate upsampling features with nonsalient information provided by the PCF. This integration enhances both edge and segmentation information. The features in the skip connection and decoding path are iteratively updated to progressively aggregate fine structure information, thereby optimizing segmentation results and reducing topological disconnections. Experimental results on multiple datasets demonstrate that the proposed PEA-Net model and strategy achieve optimal performance in both pixel-level and topology-level metrics.

Retinal Vascular Changes in Response to Hypoxia: A High-Altitude Expedition Study.

Westwood, Jessica, India Mayhook-Walker, Ciaran Simpkins, Andrew Darby-Smith, Dan Morris, and Eduardo Normando. Retinal vascular changes in response to hypoxia: a high-altitude expedition study. High Alt Med Biol. 25:49-59, 2024. Background: Increased tortuosity and engorgement of retinal vasculature are recognized physiological responses to hypoxia. This can lead to high-altitude retinopathy (HAR), but incidence reports are highly variable, and our understanding of the etiological mechanisms remains incomplete. This study quantitatively evaluated retinal vascular changes during an expedition to 4,167 m. Methods: Ten healthy participants summited Mount Toubkal, Morocco. Fundus images were taken predeparture, daily throughout the expedition, and 1 month postreturn. Diameter and tortuosity of four vessels were assessed, in addition to vessel density and features of HAR. Results: Significant (p ≤ 0.05) increases in tortuosity and diameter were observed in several vessels on high-altitude exposure days. There was a strong correlation between altitude and supratemporal retinal artery diameter on days 2, 3, and 6 of the expedition (r = 0.7707, 0.7951, 0.7401, respectively; p < 0.05). There was a significant increase in median vessel density from 6.7% at baseline to 10.0% on summit day. Notably there were no incidences of HAR. Conclusion: Physiological but not pathological changes were seen in this cohort, which gives insight into the state of the cerebral vasculature throughout this expedition. These results are likely attributable to relatively low altitude exposure, a conservative ascent profile, and the cohort's demographic. Future study must include daily retinal images at higher altitudes and take steps to mitigate environmental confounders. This study is relevant to altitude tourists, patients with diabetic retinopathy or retinal vein occlusion, and critically ill patients.

Influence of parent vessel feature on the risk of internal carotid artery aneurysm rupture via computational method

In this study, the role of sac section area and parent vessel diameter on the hemodynamic feature of the blood flow in selected internal carotid artery (ICA) aneurysms is comprehensively investigated. The changes of wall shear stress, pressure, and oscillatory shear index (OSI) of blood stream on the vessel for various aneurysms with coiling treatment. To attain hemodynamic factors, computational technique is used for the modeling of non-Newtonian transient blood flow inside the three different ICA aneurysms. Three different saccular models with various Parent vessel mean Diameter is investigated in this study. The achieved outcomes show that increasing the diameter of the parent vessel directly decreases the OSI value on the sac surface. In addition, the mean wall shear stress decreases with the increase of the parent vessel diameter.

Methods for Estimating Hydrogen Fuel Tank Characteristics

Abstract The pressure vessels needed to store hydrogen for next-generation hydrogen fuel cell vehicles are expected to be a substantial portion of the total system mass, volume, and cost. Gravimetric capacity, volumetric capacity, and cost per kilogram of usable hydrogen are key performance metrics that the U.S. Department of Energy (DOE) uses to determine the viability of hydrogen fuel cell systems. Research and development related to hydrogen storage systems covers a wide range of potential operating conditions, from cryogenic temperatures to high temperatures (above ambient) and low pressure to high pressure. Researchers at PNNL have developed methods for estimating these key pressure vessel characteristics to support on-board hydrogen storage system design and performance evaluation and to support decision-making about DOE hydrogen storage system research investments. This article describes the pressure tank estimation methodology that has been used as a stand-alone calculation and has been incorporated into larger system evaluation tools. The methodology estimates the geometry, mass, and material cost of type I, type III, and type IV pressure vessels based on operating pressure and material strength at the system's operating temperature, using classical thin-wall and thick-wall pressure vessel stress calculations. The geometry, mass, and material cost requirements of the pressure vessel have significant impacts on the total system performance. For example, hydrogen storage materials that can separately achieve a very high hydrogen density can be deemed impractical for use in fuel cell vehicle hydrogen storage systems because the pressure tank containing them is too large, heavy, or expensive. This article describes the design philosophy and analytical process of the tank characteristic estimation methodology, which has been implemented in spreadsheet calculation tools and system-level analysis tools used by DOE researchers. Each of the three tank types (type I, type III, and type IV) uses a different analysis methodology with some common elements. This article also provides examples of implementing the methodology to perform parametric studies of all three pressure vessel types. The goal of this article is to present the methodology in sufficient detail so it can be implemented in other hydrogen fuel cell vehicle design and analysis tools.

Correlation and asynchronization of electroencephalogram and cerebral blood flow in active and passive stimulations

Objective. Real-time brain monitoring is of importance for intraoperative surgeries and intensive care unit, in order to take timely clinical interventions. Electroencephalogram (EEG) is a conventional technique for recording neural excitations (e.g. brain waves) in the cerebral cortex, and near infrared diffuse correlation spectroscopy (DCS) is an emerging technique that can directly measure the cerebral blood flow (CBF) in microvasculature system. Currently, the relationship between the neural activities and cerebral hemodynamics that reflects the vasoconstriction features of cerebral vessels, especially under both active and passive situation, has not been elucidated thus far, which triggers the motivation of this study. Approach. We used the verbal fluency test as an active cognitive stimulus to the brain, and we manipulated blood pressure changes as a passive challenge to the brain. Under both protocols, the CBF and EEG responses were longitudinally monitored throughout the cerebral stimulus. Power spectrum approaches were applied the EEG signals and compared with CBF responses. Main results. The results show that the EEG response was significantly faster and larger in amplitude during the active cognitive task, when compared to the CBF, but with larger individual variability. By contrast, CBF is more sensitive when response to the passive task, and with better signal stability. We also found that there was a correlation (p < 0.01, r = 0.866, R 2 = 0.751) between CBF and EEG in initial response during the active task, but no significant correlation (p > 0.05) was found during the passive task. The similar relations were also found between regional brain waves and blood flow. Significance. The asynchronization and correlation between the two measurements indicates the necessity of monitoring both variables for comprehensive understanding of cerebral physiology. Deep exploration of their relationships provides promising implications for DCS/EEG integration in the diagnosis of various neurovascular and psychiatric diseases.