Airborne soiling measurements of entire solar fields with Qfly

Concentrating Solar Power (CSP) plants are often being built in regions with high dust loads such as the Middle East and North Africa. Current soiling measurement methods in solar fields are labor and cost intensive and they only cover small measurement spots. Even a high number of manual measurements can only cover a minimal portion of the total solar field mirror surface. Airborne measurement solutions such as QFly have been developed in recent years to measure the geometry and tracking accuracy of the large CSP mirror areas. Soiling on solar mirrors is qualitatively visible in raw QFly measurement images. In this study we present a method to automatically derive the mirror cleanliness from aerial images taken with QFly. We present scattering investigations that correct for the directional particle scattering, illumination and camera viewing angles. A promising correlation was found between the thus corrected camera RGB signals and reference reflectance measurements that shows an RMSD of 3% for the investigated dust

T-TraCS – An automated method to measure soiling losses at parabolic trough receiver tubes

Soiling of the envelope tubes of parabolic trough collectors can significantly reduce their transmittance and hence the overall collector efficiency. There are only a few methods to quantify soiling losses at absorber tubes of parabolic trough collectors. The existing methods are either laboratory based and cannot be applied automatically or they are personnel intense because they can only be used manually inside of operational solar fields. In this work we present a novel device called T-TraCS capable of automatically measuring the transmission of a sample glass during outdoor exposure with the current solar spectrum and imitating the movement of operational parabolic trough collectors. It can be used in resource assessment campaigns in order to better estimate future soiling losses at the tube level or it can be set up inside a solar field in order to measure the tube soiling losses in real time for CSP plant operation. Scattering simulations are presented that correct the measurement raw values of the T-TraCS and a spectrophotometer for their differences to the optics of a receiver tube. The validation with these final measurements shows good agreement with the reference spectrophotometer with a R2 of 0.996. The T-TraCS is therefore capable of automatically determining the soiling induced transmission losses with high accuracy

Hedrocele Associated With Full-Thickness Rectal Prolapse

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Gastric Band Migration Causing Jejunal Obstruction: a Life-Threatening Complication

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Giant Meckel’s Diverticulum

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Totally Robotic Reversal of Omega-Loop Gastric Bypass to Normal Anatomy

International audienceGastric bypass procedures can potentially lead to middle and long-term complications (Podnos et al. Arch Surg 138(9):957-61, 2003). For several years, Roux-en-Y gastric bypass reversal procedures performed by laparotomy or laparoscopic way have been described in literature (Moon et al. Surg Obes Relat Dis 11(4):821-6, 2015). Major complications are anastomotic ulcers, anastomotic complications or functional disorder such as dumping syndrome, hypocalcemia, severe hypoglycemia, and malnutrition (Moon et al. Surg Obes Relat Dis 11(4):821-6, 2015; Campos et al. Surg Obes Relat Dis 10(1):36-43, 2014). One-anastomosis gastric bypass (OAGB) also called omega-loop gastric bypass (OLGB) or mini-gastric bypass (MGB) is a technique that has demonstrated similar results to traditional Roux-en-Y procedures in terms of weight loss and postoperative quality of life (Lee et al. Ann Surg 242(1):20-8, 2005). However, in a recent description of 1000 patients, the percentage of malnutrition was 0.2 % (two patients) with an indication to revert omega-loop gastric bypass back into normal anatomy (Chevallier et al. Obes Surg 25(6):951-8, 2015), but technical details have not been exposed yet. The first robotic gastric bypass was published by Horgan and Vanuno in 2001 (Horgan and Vanuno J Laparoendosc Adv Surg Tech A 11(6):415-9, 2001). The present work describes for the first time a robotic procedure to reverse OLGB into normal anatomy.METHODS:We present the video report of a 69-year-old woman suffering of severe malnutrition (weight of 42 kg, body mass index of 15.8 kg/m(2), albumin 21 g/l) who had undergone laparoscopic omega-loop gastric bypass 2 years ago (initial weight of 104 kg and initial body mass index of 39.6 kg/m(2)). She was referred to our Bariatric Surgery Unit, and after a period of parenteral nutrition support to improve nutritional status (albumin 32 g/l), we decided in a multidisciplinary staff to perform a reversal omega-loop gastric bypass back into normal anatomy using the DaVinci Si™ system by Intuitive Surgical Inc ®, Sunnyvale, CA.RESULTS:In this high definition video, we present step-by-step robotic reversal of the omega-loop gastric bypass. The procedure began with a careful adhesiolysis of the left lobe of the liver, small gastric pouch, and omega-loop. Then, the gastro-jejunostomy was transected with a 45-mm Endo GIA endocutter with purple staples. The key-point was the creation of a gastro-gastric anastomosis between the small gastric pouch and the excluded stomach. Omega-loop jejunum was resected and the anastomosis was performed in order to avoid intestinal stenosis. The operative time was 232 min. Postoperative course was uneventful and the patient was discharged in postoperative day 8. One month after the procedure, she has gained 10 kg (albumin 34 g/l) and stabilized her nutritional status without further nutritional support.CONCLUSIONS:This is the first case described in the literature of a reversal omega-loop gastric bypass into normal anatomy and the first description of the use of a robotic approach. This intervention is challenging, but a feasible procedure. This technology may increase the number of surgeons who are able to provide the benefits of minimal invasive surgery to their patients without the increased risks of complications associated with initial learning curves. The three-dimensional robotic vision, a stable camera, and the multiples degrees of freedom of the robotic instruments are the features that seem to provide greater surgical precision for these complex laparoscopic operations

Totally Robotic Combined Roux-en-Y Gastric Bypass and Hiatal Hernia Repair with Biological Mesh: Technical Points

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Explaining a model predicting quality of surgical practice: a first presentation to and review by clinical experts

International audiencePurpose: Surgical Data Science (SDS) is an emerging research domain offering data-driven answers to challenges encountered by clinicians during training and practice. We previously developed a framework to assess quality of practice based on two aspects: exposure of the surgical scene (ESS) and the surgeon’s profile of practice (SPP). Here, we wished to investigate the clinical relevance of the parameters learned by this model by (1) interpreting these parameters and identifying associated representative video samples and (2) presenting this information to surgeons in the form of a video-enhanced questionnaire. To our knowledge, this is the first approach in the field of SDS for laparoscopy linking the choices made by a machine learning model predicting surgical quality to clinical expertise.Method: Spatial features and quality of practice scores extracted from labeled and segmented frames in 30 laparoscopic videos were used to predict the ESS and the SPP. The relationships between the inputs and outputs of the model were then analyzed and translated into meaningful sentences (statements, e.g., “To optimize the ESS, it is very important to correctly handle the spleen”). Representative video clips illustrating these statements were semi-automatically identified. Eleven statements and video clips were used in a survey presented to six experienced digestive surgeons to gather their opinions on the algorithmic analyses.Results: All but one of the surgeons agreed with the proposed questionnaire overall. On average, surgeons agreed with 7/11 statements.Conclusion: This proof-of-concept study provides preliminary validation of our model which has a high potential for use to analyze and understand surgical practices