Dilation Rate Research Articles

Flame Self-interaction and Flow Topology in Turbulent Homogeneous Mixture n-Heptane MILD Combustion

Moderate or Intense Low-oxygen Dilution (MILD) combustion has potential to achieve both high energy efficiency and ultra-low emissions. This analysis adopts the critical point theory to characterise the Flame-Self Interaction (FSI) events and flow topologies in turbulent, homogeneous mixture, n-Heptane MILD combustion using Direct Numerical Simulations (DNS) with reduced chemical mechanism. The local flame geometry has also been categorised using the mean and Gauss curvatures. It was found that the Tunnel Formation (TF) and Tunnel Closure (TC) topologies are the most probable FSI events at all values of the reaction progress variable c, while the Unburned Pocket (UP) and Burned Pocket (BP) topologies were mostly present towards the unburned and burned mixtures of the flame, respectively. Moreover, increasing the turbulence intensity did not result in any significant changes in the distribution of FSI events. Investigation of the flow topology distribution showed that the features associated with non-zero dilatation rate did not exist in the MILD cases considered. This is a consequence of the negligible thermal expansion effect due to the small temperature rise in MILD combustion cases. Increasing the dilution factor caused a reduction in the frequency of FSI events for all c levels. The distributions of flame self-interaction events in homogeneous mixture MILD combustion have been found to be significantly different from previously reported distributions for conventional turbulent premixed combustion.

Moderate continuous- and high-intensity interval training elicit comparable cardiovascular effect among middle-aged men regardless of recovery mode

ABSTRACT To assess the effect of active and passive intra-interval recovery modes in time-efficient high-intensity interval training (HIT) on cardiorespiratory fitness, autonomic function, and endothelial function in sedentary middle-aged men. Participants (n = 62; age: 49.5 ± 5.8 y; BMI: 29.7 ± 3.7 kg·m−2) completed the assessments of cardiorespiratory fitness, flow-mediated dilation (FMD) and heart rate variability before being randomly allocated to control (CON; n = 14), moderate intensity continuous training (MICT; n = 15), HIT with passive (P-HIT; n-15), or active recovery (A-HIT; n = 15). Participants performed thrice weekly exercise sessions for 12 weeks. MICT completed 50–60 min of continuous cycling at 60–70% heart rate (HR) maximum. HIT completed 30-s work intervals (∼85% HR) interspaced with 2.5 min of active or passive recovery. All exercise modalities increased oxygen uptake (V̇O2) (MD: ≥ 3.1 ml·kg−1·min−1, 95%CI: 1.5–4.7 ml·kg−1·min−1; P < 0.001), power output (MD: ≥ 26 W, 95%CI: 15–37 W; P < 0.001) and cycle duration (MD: ≥ 62 s, 95%CI: 36–88 s; P < 0.001) at 85% HRM. Significant pre-to-post differences were observed among all exercise groups for FMD (MD: ≥ 3.4%, 95%CI: 0.3–6.5%; P < 0.05), while MICT and P-HIT significantly increased the standard deviation of all NN intervals (SDNN) pre-to-post intervention (MD: ≥ 7 ms, 2–13 ms; P ≤ 0.05). Time-efficient HIT elicits significant improvements in cardiorespiratory fitness, FMD and autonomic modulation following a thrice weekly 12-week exercise intervention among sedentary middle-aged men. Active recovery between successive high-intensity intervals provided no additional benefit among this deconditioned cohort.

Murine model of elastase-induced proximal thoracic aortic aneurysm through a midline incision in the anterior neck.

This study was performed to develop a murine model of elastase-induced proximal thoracic aortic aneurysms (PTAAs). The ascending thoracic aorta and aortic arch of adult C57BL/6J male mice were exposed through a midline incision in the anterior neck, followed by peri-adventitial elastase or saline application. The maximal ascending thoracic aorta diameter was measured with high-resolution micro-ultrasound. Twenty-eight days after the operation, the aortas were harvested and analyzed by histopathological examination and qualitative polymerase chain reaction to determine the basic characteristics of the aneurysmal lesions. Fourteen days after the operation, the dilation rate (mean ± standard error) in the 10-min elastase application group (n = 10, 71.44 ± 10.45%) or 5-min application group (n = 9, 42.67 ± 3.72%) were significantly higher than that in the saline application group (n = 9, 7.37 ± 0.94%, P < 0.001 for both). Histopathological examination revealed aortic wall thickening, degradation of elastin fibers, loss of smooth muscle cells, more vasa vasorum, enhanced extracellular matrix degradation, augmented collagen synthesis, upregulated apoptosis and proliferation capacity of smooth muscle cells, and increased macrophages and CD4+ T cells infiltration in the PTAA lesions. Qualitative analyses indicated higher expression of the proinflammatory markers, matrix metalloproteinase-2 and -9 as well as Collagen III, Collagen I in the PTAAs than in the controls. We established a novel in vivo mouse model of PTAAs through a midline incision in the anterior neck by peri-adventitial application of elastase. This model may facilitate research into the pathogenesis of PTAA formation and the treatment strategy for this devastating disease.

Nested Densely Atrous Spatial Pyramid Pooling and Deep Dense Short Connection for Skeleton Detection

The skeleton shows the local symmetry and the shape/topology of the object, and it is utilized for human pose recognition, road detection, text detection, and the representation of industrial parts. However, the size of the skeleton is variable, which makes high-level feature representation difficult. Existing methods only attempt to integrate multilevel features but ignore the extraction of high-level features and multiscales of contextual information that are helpful for the skeleton detection task. Thus, the contributions of this article include two aspects. The first contribution is to propose a nested densely atrous spatial pyramid pooling method that connects the atrous convolutions with different dilation rates in a nested cascade mode, which can provide the multiscale denser contextual information, a larger receptive field, and more local features. The second one is to propose a deep dense short connection (DDSC) that explores the role of features at different levels in the task of skeleton detection. DDSC adopts concatenation to fuse high-level semantic information with shape information. The proposed method is evaluated on four common datasets, and the experimental results show the effectiveness of the proposed method.

Spatio-Temporal Graph Attention Network for Sintering Temperature Long-Range Forecasting in Rotary Kilns

Monitoring and forecasting of sintering temperature (ST) is vital for safe, stable, and efficient operation of rotary kiln production process. Due to the complex coupling and time-varying characteristics of process data collected by the distributed control system, its long-range prediction remains a challenge. In this article, we propose a multivariate time series forecasting model based on dynamic spatio-temporal graph attention network (GAT) to model time-varying spatio-temporal correlation between the process data and perform long-range forecasting of ST. Aiming at the problem that there is no preset graph structure for multivariate data, we first propose an adaptive adjacency matrix generation algorithm to construct an elementary graph structure for the process data. Then, we design a spatio-temporal graph attention module, which consists of a multihead GAT for extracting time-varying spatial features and a gated dilated convolutional network for temporal features. Finally, considering the different time delay and rhythm of each process variable, we use dynamic system analysis to estimate the delay time and rhythm of each variable to guide the selection of dilation rates in dilated convolutional layers. The application results based on actual data show that the method has high prediction accuracy, and has broad application prospects in industrial processes.

Probability of additional intervention and long-term follow-up of esophagomyotomy.

Two common surgical procedures used to treat esophageal motility disorders are laparoscopic Heller myotomy (LHM) with partial fundoplication and per-oral endoscopic myotomy (POEM). The difference in frequency of follow-up interventions following these procedures is unknown. This study was designed to report differences in post-surgical interventions as one of the major long-term follow-up expectations. An IRB approved registry was used to identify all patients undergoing surgery with LHM or POEM. Following surgery, patients requiring additional interventions with esophageal non-pneumatic dilation, botox injection, or repeat myotomy, as well as persistent proton pump inhibitor (PPI) use were recorded. Multivariable logistic regression analysis was performed to estimate risk factors associated with return for additional post-operative intervention. A total of 203 patients were identified, 139 met inclusion criteria (33 LHM and 106 POEM). There was a higher rate of non-pneumatic EGD dilation (33% vs 15%, p = 0.04), repeat myotomy (18% vs 2%, p < 0.01), and higher rate of overall post-operative intervention in LHM than POEM. With POEM, there was a higher rate of post-operative PPI use (63 vs 29%, p < 0.01). There was no difference in time to post-operative intervention for either group, but if intervention were to occur the median time was within the first year. Patients with a change in pre- to post-operative Eckardt score of 4 or greater decreased their chance of having a post-operative intervention. Our results for both LHM and POEM emphasize the importance of long-term follow-up in patients with an esophageal motility disorder. We have found that patients undergoing LHM are more likely to have a post-operative intervention as well as a higher rate of repeat myotomy than POEM. With both interventions, a greater change in Eckardt score decreased the likelihood of reintervention.

MSC-DNet: An efficient detector with multi-scale context for defect detection on strip steel surface

The strip steel has been widely used in the manufacturing industry. Defects on the surface are main factors to determine the quality of strip steel. Due to the various shapes of the defects and background interference, the CNN-based algorithm cannot give full play to its best performance. In this paper, a defect detection module, named detection network with multiscale context (MSC-DNet), is proposed to localize the precise position of defect and classify the specific category of surface defects. In MSC-DNet, a parallel architecture of dilated convolution (PADC) with different dilation rate is built up to capture the multi-scale context information containing multiscale defects. Furthermore, a feature enhancement and selection module (FESM) is proposed to enhance the single-scale features and select the multi-scale features for reducing the confusing information. During the training, the auxiliary image-level supervision (AIS) is adopted to speed up the convergence and to enhance the feature discrimination of the target defects. The experiment results show that the proposed MSC-DNet reaches the accuracy of 79.4% mAP and 14.1 FPS on NEU-DET dataset, and 71.6% mAP on GC10-DET dataset among all the benchmark methods, which satisfies the quasi-real-time requirement in multiscale defect detection task.

The Relationship Between Uterine Activity, Oxytocin Dosing, Labor Progress, and Mode of Birth in Nulliparas with Obesity: Minimal Usefulness of Montevideo Unit Measurement.

Maternal obesity and cesarean birth disproportionately affect Black parturients; thus, prevention of cesarean birth is a key modifiable factor to improve pregnancy outcomes and reduce disparities. The primary driver of unplanned cesarean birth among people with higher body mass index is prolonged labor duration. However, strategies to optimize outcomes in these situations have not been established. We aimed to evaluate the influence of oxytocin augmentation on uterine activity and labor progression in nulliparas with obesity. This secondary analysis involved nulliparas with obesity (BMI ≥30kg/m2) who had spontaneous labor onset followed by oxytocin augmentation and an intrauterine pressure catheter. Using Linear Mixed Models, we evaluated relationships between uterine activity measured in Montevideo units (MVU), oxytocin dose, and rate of cervical dilation normalized by labor duration. In this diverse sample (35.6% Caucasian, 16.11% African American, 40.2% Hispanic) of nulliparas with obesity (n = 87; BMI 35.54 ± 4.38kg/m2), 31% ended labor with cesarean birth. Among those with vaginal birth, only 13% had MVU ≥200 prior to the final 2hours of labor. MVUs were only minimally responsive to oxytocin dose and were not associated with labor progression nor birth route. MVU measurements may not be useful to diagnose labor arrest in nulliparas with obesity. Optimizing care for birthing people with obesity is essential for improving perinatal outcomes and for reducing racial health disparities.

DSTEELNet: A Real-Time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling for Detecting and Classifying Defects in Surface Steel Strips.

Automatic defects inspection and classification demonstrate significant importance in improving quality in the steel industry. This paper proposed and developed DSTEELNet convolution neural network (CNN) architecture to improve detection accuracy and the required time to detect defects in surface steel strips. DSTEELNet includes three parallel stacks of convolution blocks with atrous spatial pyramid pooling. Each convolution block used a different dilation rate that expands the receptive fields, increases the feature resolutions and covers square regions of input 2D image without any holes or missing edges and without increases in computations. This work illustrates the performance of DSTEELNet with a different number of parallel stacks and a different order of dilation rates. The experimental results indicate significant improvements in accuracy and illustrate that the DSTEELNet achieves of 97% mAP in detecting defects in surface steel strips on the augmented dataset GNEU and Severstal datasets and is able to detect defects in a single image in 23ms.

Korozif Madde Alan Çocukların Hastane Süreci: Türkiye'de Tek Merkezli Retrospektif Çalışma

Objective: This study retrospectively was aimed to determine how the treatment and care processes of children ingestion corrosive substances are maintained. Material and Methods: The population of the study is children with ingested corrosive substances, and the sample consisted of pediatric patients who ingestion corrosive substances from the pediatric surgery department of a university hospital in western Türkiye. Medical and nursing files of children with corrosive substance ingestion from the university's electronic patient file were examined. The sample of the study consisted of 70 pediatric patients who came between the years 2018-2021. The analysis of data was calculated using SPSS 24.0 program, frequency, percentage, median, interquartile range, comparison analysis and logistic regression. Results: The median age at first admission of pediatric patients was 4.0 years and 57.1% were girls. 35.7% of the pediatric patients due to oil consumption, 30.0% of them applied to the pediatric surgery department in the summer season, and the hospital was not the first application center for 61.4%. According to the Rush Medicus Patient Classification System, 40% of the children were defined as low-level dependent patients. The first arrival age of children affects the level of nursing dependency. It was determined that the rate of dilatation in pediatric patients varied according to the hospital first application center. Conclusion: As a result, although the dependency level of the children taking corrosive substances to the nurse is low, it was determined that the child's first admission age and dilatation status affect the level of addiction.

Oriented Infrared Vehicle Detection in Aerial Images via Mining Frequency and Semantic Information

Infrared vehicle detection based on aerial images has significant applications in military and civilian fields for the perception ability under low-light and foggy conditions. However, it remains challenging due to the following characteristics. First, infrared textures and edges are blurred, implying a plenty of low-frequency signals and a shortage of detailed descriptions. Second, objects in infrared images present different patterns depending on their thermal radiations, which hamper the feature extraction of convolution kernels. Third, infrared images lack color information, which means fewer features for classification and regression can be used. Inspired by cognitive neuroscience that humans perceive the entirety from low-frequency information and discern details from high-frequency information, we devise a new framework for oriented infrared vehicle detection called I <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> MDet (Infrared Information Mining Detector) to tackle the above challenges. It consists of two significant designs: the kaleidoscope module and the semantic feature supplement module (SFSM). In the kaleidoscope module, we explore the effect of kernel sizes and dilation rates on frequency information mining with kaleidoscope-like equivalent kernels. Features in this module are extracted by adaptive involution operators instead of convolution kernels to deal with multiple patterns. The SFSM provides the network with features beneficial for classification and regression. On the one hand, the network is guided to learn more meaningful features under semantic supervision. On the other hand, features output by the SFSM supplement the detection head with semantic information. Experimental results on the public dataset DroneVehicle demonstrate that our proposed approach achieves outstanding performance on oriented infrared vehicle detection.

Increasing Rates of Esophageal Stricture and Dilation Over 2 Decades in Eosinophilic Esophagitis.

Increasing Rates of Esophageal Stricture and Dilation Over 2 Decades in Eosinophilic Esophagitis.

Multiscale Fusion Network Based on Global Weighting for Hyperspectral Feature Selection

Feature selection is an important way to achieve high precision and efficient classification of hyperspectral remote sensing images. However, most existing FS methods use a fixed scale to extract features and the relationship between spatial and spectral dimensions is ignored. In fact, this correlation is useful for classification. In this paper, a multi-scale feature fusion network (MSFGW) is proposed in which a global weighting mechanism is explored to catch spatial-spectral information at multiple scales. First, the multi-scale feature extraction module composed of group convolution and dilated convolution is utilized to extract the multi-scale features. With the increase of the dilation rate, the module takes the spatial differences at varying scales. Secondly, a 3D weighting mechanism is used to combine the spatial and spectral correlated information for reducing the interference of homologous and heterologous and boosting the feature discrimination ability. Then, multi-scale weighted features are fused to integrate the internal information of all bands at different scales. Finally, the band reconstruction network is used to select representative bands according to their entropy. The experimental results with the state-of-the-art feature selection algorithms on three widely hyperspectral datasets demonstrate that the features selected by MSFGW have obvious advantages in classification with only a few training samples.

A novel abdominal aortic aneurysm model produced by periarterial application of hydrochloric acid.

Previous abdominal aortic aneurysm (AAA) animal modeling methodologies were either expensive or complicated. Here, we developed a novel AAA model which was simple to set up and generated minimal calcification. Twenty-four rats were divided randomly into four groups. Groups 1, 2 and 3 underwent surgery in which 15% hydrochloric acid (HCl) was applied periarterially to the abdominal aorta for 5 min, followed by sacrifice 1 week (group 1), 2 weeks (group 2), and 4 weeks (group 3) after surgery. The maximum aortic diameter (MAD) was measured at surgery and before animal sacrifice. Rats in group 4 were sham-treated. The MADs in group 1, 2 and 3 showed significant dilation compared with group 4, with a mean dilation rate of 33.8% in the first week after surgery. Histopathological examination revealed infiltration of macrophages into the adventitia, obvious apoptosis of smooth muscle cells, and rupture and collapse of the elastic fibers. Furthermore, no calcification was observed in the dilated aorta. The mRNA expression levels of inflammatory factors were at least two-fold higher in group 1 than in group 4, indicating significant inflammatory response in the progression of AAA information. In conclusion, periarterial application of 15% HCl is a convenient and reliable model to create an abdominal aortic aneurysm in rats, and the potential development mechanism may be related to the proinflammatory effects of HCl.

Block Attention and Switchable Normalization Based Deep Learning Framework for Segmentation of Retinal Vessels

The presence of high blood sugar levels damages blood vessels and causes an eye condition called diabetic retinopathy. The ophthalmologist can detect this disease by looking at the variations in retinal blood vasculature. Manual segmentation of vessels requires highly skilled specialists, and not possible for many patients to be done quickly in their daily routine. For these reasons, it is of great importance to isolate retinal vessels precisely, quickly, and accurately. The difficulty distinguishing the retinal vessels from the background, and the small number of samples in the databases make this segmentation problem difficult. In this study, we propose a novel network called Block Feature Map Distorted Switchable Normalization U-net with Global Context Informative Convolutional Block Attention Module (BFMD SN U-net with GCI- CBAM). We improve the traditional Fully Convolutional Segmentation Networks in multiple aspects with the proposed model; The model converges in earlier epochs, adapts more flexibly to different data, is more robust against overfitting, and gets better feature refinement at different dilation rates to cope with different sizes of retinal vessels. We evaluate the proposed network on two reference retinal datasets, DRIVE and CHASE DB1, and achieve state-of-the-art performances with 97.00 % accuracy and 98.71 % AUC in DRIVE and 97.62 % accuracy and 99.11 % AUC on CHASE DB1 databases. Additionally, the convergence step of the model is reduced and it has fewer parameters than the baseline U-net. In summary, the proposed model surpasses the U-net-based approaches used for retinal vessel separation in the literature.

Long-term clinical and functional results of magnetic sphincter augmentation.

Magnetic sphincter augmentation (MSA) was introduced in 2007 as an alternative surgical procedure for patients with gastroesophageal reflux disease (GERD). The majority of data since MSA's introduction has focused on short and intermediate-term results, demonstrating safety and high efficacy in terms of reflux symptom control, freedom from proton pump inhibitor use and normalization of distal esophageal acid exposure. However, GERD is a chronic condition that demands a long-term solution. Limited available data from studies reporting outcomes at 5years or later following MSA demonstrate that the promising short- and mid-term efficacy and safety profile of MSA remains relatively constant in the long term. Compared with Nissen fundoplication, MSA has a much lower rate of gas-bloat and inability to belch at a short-term follow-up, a difference that persists in the long-term. The most common complaint after MSA at a short-term follow-up is dysphagia. However, limited data suggest dysphagia rates largely decrease by 5years. Dysphagia is the most common indication for dilation and device removal in both early- and long-term studies. However, the overall rates of dilation and removal are similar in short- and long-term reports, suggesting the majority of these procedures are performed in the short-term period after device implantation. The indications and standard practices of MSA have evolved over time. Long-term outcome data currently available are all from patient cohorts who were selected for MSA under early restricted indications and outdated regimens. Therefore, further long-term studies are needed to corroborate the preliminary, yet encouraging long-term results.

Cervical dilatation rate following augmentation of dysfunctional labour with oxytocin alone versus oxytocin and drotaverine among term nulliparas in the Rivers State University Teaching Hospital, Port Harcourt, Nigeria

Cervical dilatation rate following augmentation of dysfunctional labour with oxytocin alone versus oxytocin and drotaverine among term nulliparas in the Rivers State University Teaching Hospital, Port Harcourt, Nigeria

Cervical dilatation rate following augmentation of dysfunctional labour with oxytocin alone versus oxytocin and drotaverine among term nulliparas in the Rivers State University Teaching Hospital, Port Harcourt, Nigeria

Background: Dysfunctional labour is the commonest abnormality of the first stage of labour. It complicates 50% of nulliparous deliveries and is associated with increased perinatal morbidity and mortality. Dysfunctional labour occurs when the progress in the active phase of labour is abnormally slow (&lt;1 cm/hr). It is largely due to ineffective uterine contractions or slow cervical dilatation. Augmentation of labour with oxytocin is the standard management of dysfunctional labour as it enhances uterine contractions. In many cases, despite good uterine contractions slow progress persists due to cervical smooth muscle spasms. Drotaverine a smooth muscle relaxant can be used to relieve cervical smooth muscle spasms. Aim/objective: This study compared the cervical dilatation rate in term nulliparas following augmentation of dysfunctional labour with oxytocin versus oxytocin and drotaverine. Methods: The study was a single-blinded randomized clinical trial involving 156 term nulliparous women with dysfunctional labour, who were randomized into two groups. Each group had 78 participants and received either oxytocin with a placebo or oxytocin with drotaverine. They were monitored until delivery and the cervical dilatation rates in both groups were compared. Data obtained were analysed using SPSS version 23 software. The level of significance was set at 0.05. Results: The two groups were similar in their baseline characteristics, the mean pre-intervention cervical dilatation rate were also similar (0.53 cm/hr vs. 0.52 cm/hr, p = 0.85). Following augmentation, the cervical dilatation rate in the oxytocin-drotaverine group was significantly faster than in the oxytocin-placebo group (1.60 cm/hr vs. 1.20 cm/hr, p &lt; 0.01). Conclusion: The use of drotaverine with oxytocin in managing dysfunctional labour in term nulliparous women leads to a faster cervical dilatation rate.

Analysis of the efficacy and risk factors of surgical treatment of recurrent UPJO in adults

BackgroundTo compare the efficacy of secondary pyeloplasty and balloon dilation and to analyze the risk factors for secondary surgical failure in patients with recurrent uretero-pelvic junction obstruction (UPJO).MethodsWe retrospectively analyzed 65 patients with recurrent UPJO who underwent secondary surgery between September 2011 and March 2019, of whom 33 had complete baseline data and follow-up data. General clinical information, perioperative data, and follow-up results were collected from patients. Risk factors for surgical failure in patients with recurrent UPJO were analyzed using logistic regression.ResultsThe failure rates of secondary pyeloplasty and balloon dilation in secondary surgery were 16.7% and 33.3%, respectively. Univariate analysis showed that ureteral stenosis length and operative time were associated with secondary pyeloplasty and balloon dilatation failure (p < 0.05), and ureteral stenosis length was an independent risk factor for secondary pyeloplasty failure (OR = 0.074, 95% CI: 0.006–0.864, p = 0.038). In the balloon dilation group, treatment failure rates were significantly lower in patients with stenotic segment lengths less than 1 ± 0.32 cm than in patients with stenotic segment lengths greater than 1 ± 0.32 cm (p = 0.019).ConclusionsThe secondary pyeloplasty may provide better benefit. Ureteral stricture length is an independent risk factor for failure of secondary pyeloplasty and a potential risk factor for balloon dilatation. Operation time is a potential risk factor for pyeloplasty and balloon dilatation.

Persistent Sciatic Artery: A Cadaveric Case Study

Objective The persistent sciatic artery associated with birth is a rare anomaly with a high rate of abnormal dilatation, blockage and stenosis prompting in extreme thrombosis, caudal embolisation, or aneurysm rupture. This is a case report on cadaveric specimen (50-year-old) African female cadaver in the Human Anatomy Laboratory, Department of Human Anatomy, Uzima University. Methods: During routine cadaveric dissections by first year medical students a peculiar structure was noted behind the right thigh after exposure of gluteal muscles. Results: The structure, identified as persistent sciatic artery, entered the gluteal region through the greater sciatic foramen and lied superficial to the sciatic nerve. The vessel was large and it passed out of the pelvis through the greater sciatic foramen below the pirifomis and descended posterior to the sciatic nerve. Muscular and articular branches branched off from artery through its course. The artery descended behind the thigh and was traversed obliquely by the long head of the biceps femoris muscle posteriorly. The sciatic artery continued as the popliteal artery that lied alongside popliteal vein, which was retraced back from the infrapiriform fossa. The femoral arteries were hypoplastic and had no obvious connections with the sciatic artery. Conclusion: It is a vital practice to recognize the position and tendency of sciatic artery to develop aneurysms and subsequent deep vein thrombosis that may be life threatening. Furthermore, understanding of this principle changes the approach to surgical interventions that are required during the process of bypass grafting.