Operative technique in robotic pancreaticoduodenectomy (RPD) at University of Illinois at Chicago (IC): U17 steps standardized technique

Background: Minimally invasive pancreaticoduodenectomy (MIPD) was introduced in the attempt to improve the outcomes of the open approach. Laparoscopic pancreaticoduodenectomy (LPD) was first reported by Gagner and Pomp (Surg Endosc 8:408–410, 1994). Unfortunately, due to its complexity and technical demand, LPD never reached widespread popularity. Since it was first performed by P. C. Giulianotti in 2001, Robotic PD (RPD) has been gaining ground among surgeons. MIPD is included as a surgical option in the latest NCCN Guidelines. However, lack of surgical standardization, however, has limited the reproducibility of MIPD and made the acquisition of the technique by other surgeons difficult. We provide an accurate description of our standardized step-by-step RDP technique. Methods: We took advantage of our 15-year long experience and > 150 cases performed to provide a step-by-step guidance of our RPD standardized technique. The description includes practical “tips and tricks” to facilitate the learning curve and assist with the teaching/evaluation process. Results: 17 surgical steps were identified as key components of the RPD procedure. The steps reflect the subdivision of the RPD into several parts which help to understand a strategy that takes into accounts specific anatomical landmarks and the demands of the robotic platform. Conclusions: Standardization is a key element of the learning curve of RPD. It can potentially provide consistent, reproducible results that can be more easily evaluated. Despite promising results, full acceptance of RPD as the ‘gold standard’ is still work in progress. Randomized-controlled trials with the application of a standardized technique are necessary to better define the role of RP

Educational step-by-step surgical video about operative technique in robotic pancreaticoduodenectomy (RPD) at University of Illinois at Chicago (UIC): 17 steps standardized technique-Lessons learned since the first worldwide RPD performed in the year 2001

Background: RPD (Robotic pancreatoduodenectomy) was first performed by P. C. Giulianotti in 2001 (Arch Surg 138(7):777-784, 2003). Since then, the complexity and lack of technique standardization has slowed down its widespread utilization. RPD has been increasingly adopted worldwide and in few centres is the preferred apporached approach by certain surgeons. Some large retrospective series are available and data seem to indicate that RPD is safe/feasible, and a valid alternative to the classic open Whipple. Our group has recently described a standardized 17 steps approach to RPD (Giulianotti et al. Surg Endosc 32(10): 4329-4336, 2018). Herin, we present an educational step-by-step surgical video with short technical/operative description to visually exemplify the RPD 17 steps technique. Methods: The current project has been approved by our local Institutional Review Board (IRB). We edited a step-by-step video guidance of our RPD standardized technique. The data/video images were collected from a retrospective analysis of a prospectively collected database (IRB approved). The narration and the images describe hands-on operative "tips and tricks" to facilitate the learning/teaching/evaluation process. Results: Each of the 17 surgical steps is visually represented and explained to help the in-depth understanding of the relevant surgical anatomy and the specific operative technique. Conclusions: Educational videos descriptions like the one herein presented are a valid learning/teaching tool to implement standardized surgical approaches. Standardization is a crucial component of the learning curve. This approach can create more objective and reproducible data which might be more reliably assessed/compared across institutions and by different surgeons. Promising results are arising from several centers about RPD. However, RPD as gold standard-approach is still a matter of debate. Randomized-controlled studies (RCT) are required to better validate the precise role of RPD

The role of off-board EV battery chargers in smart homes and smart grids: operation with renewables and energy storage systems

Concerns about climate changes and environmental air pollution are leading to the adoption of new technologies for transportation, mainly based on vehicle electrification and the interaction with smart grids, and also with the introduction of renewable energy sources (RES) accompanied by energy storage systems (ESS). For these three fundamental pillars, new power electronics technologies are emerging to transform the electrical power grid, targeting a flexible and collaborative operation. As a distinctive factor, the vehicle electrification has stimulated the presence of new technologies in terms of power management, both for smart homes and smart grids. As the title indicates, this book chapter focuses on the role of off-board EV battery chargers in terms of operation modes and contextualization for smart homes and smart grids in terms of opportunities. Based on a review of on-board and off-board EV battery charging systems (EV-BCS), this chapter focus on the off-board EV-BCS framed with RES and ESS as a dominant system in future smart homes. Contextualizing these aspects, three distinct cases are considered: (1) An ac smart home using separate power converters, according to the considered technologies; (2) A hybrid ac and dc smart home with an off-board EV-BCS interfacing RES and ESS, and with the electrical appliances plugged-in to the ac power grid; (3) A dc smart home using a unified 2 off-board EV-BCS with a single interface for the electrical power grid, and with multiple dc interfaces (RES, ESS, and electrical appliances). The results for each case are obtained in terms of efficiency and power quality, demonstrating that the off-board EV-BCS, as a unified structure for smart homes, presents better results. Besides, the off-board EV-BCS can also be used as an important asset for the smart grid, even when the EV is not plugged-in at the smart home.(undefined

Relationship between circum-Arctic atmospheric wave patterns and large-scale wildfires in boreal summer

Long-term assessment of severe wildfires and associated air pollution and related climate patterns in and around the Arctic is essential for assessing healthy human life status. To examine the relationships, we analyzed the National Aeronautics and Space Administration (NASA) modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Our investigation based on this state-of-the-art atmospheric reanalysis data reveals that 13 out of the 20 months with the highest PM2.5 (corresponding to the highly elevated organic carbon in the particulate organic matter [POM] form) monthly mean mass concentration over the Arctic for 2003-2017 were all in summer (July and August), during which POM of >= 0.5 mu g m(-3) and PM2.5 were positively correlated. This correlation suggests that high PM2.5 in the Arctic is linked to large wildfire contributions and characterized by significant anticyclonic anomalies (i.e. clockwise atmospheric circulation) with anomalous surface warmth and drier conditions over Siberia and subpolar North America, in addition to Europe. A similar climate pattern was also identified through an independent regression analysis for the July and August mean data between the same atmospheric variables and the sign-reversed Scandinavian pattern index. We named this pattern of recent atmospheric circulation anomalies the circum-Arctic wave (CAW) pattern as a manifestation of eastward group-velocity propagation of stationary Rossby waves (i.e. large-scale atmospheric waves). The CAW induces concomitant development of warm anticyclonic anomalies over Europe, Siberia, Alaska, and Canada, as observed in late June 2019. Surprisingly, the extended regression analysis of the 1980-2017 period revealed that the CAW pattern was not prominent before 2003. Understanding the CAW pattern under future climate change and global warming would lead to better prediction of co-occurrences of European heatwaves and large-scale wildfires with air pollution over Siberia, Alaska, and Canada in and around the Arctic in summer

Spatio-temporal patterns of land use/land cover change in the heterogeneous coastal Region of Bangladesh between 1990 and 2017

Although a detailed analysis of land use and land cover (LULC) change is essential in providing a greater understanding of increased human-environment interactions across the coastal region of Bangladesh, substantial challenges still exist for accurately classifying coastal LULC. This is due to the existence of high-level landscape heterogeneity and unavailability of good quality remotely sensed data. This study, the first of a kind, implemented a unique methodological approach to this challenge. Using freely available Landsat imagery, eXtreme Gradient Boosting (XGBoost)-based informative feature selection and Random Forest classification is used to elucidate spatio-temporal patterns of LULC across coastal areas over a 28-year period (1990–2017). We show that the XGBoost feature selection approach effectively addresses the issue of high landscape heterogeneity and spectral complexities in the image data, successfully augmenting the RF model performance (providing a mean user’s accuracy > 0.82). Multi-temporal LULC maps reveal that Bangladesh’s coastal areas experienced a net increase in agricultural land (5.44%), built-up (4.91%) and river (4.52%) areas over the past 28 years. While vegetation cover experienced a net decrease (8.26%), an increasing vegetation trend was observed in the years since 2000, primarily due to the Bangladesh government’s afforestation initiatives across the southern coastal belts. These findings provide a comprehensive picture of coastal LULC patterns, which will be useful for policy makers and resource managers to incorporate into coastal land use and environmental management practices. This work also provides useful methodological insights for future research to effectively address the spatial and spectral complexities of remotely sensed data used in classifying the LULC of a heterogeneous landscape

A Fast Classification Method of Faults in Power Electronic Circuits Based on Support Vector Machines

Fault detection and location are important and front-end tasks in assuring the reliability of power electronic circuits. In essence, both tasks can be considered as the classification problem. This paper presents a fast fault classification method for power electronic circuits by using the support vector machine (SVM) as a classifier and the wavelet transform as a feature extraction technique. Using one-against-rest SVM and one-against-one SVM are two general approaches to fault classification in power electronic circuits. However, these methods have a high computational complexity, therefore in this design we employ a directed acyclic graph (DAG) SVM to implement the fault classification. The DAG SVM is close to the one-against-one SVM regarding its classification performance, but it is much faster. Moreover, in the presented approach, the DAG SVM is improved by introducing the method of Knearest neighbours to reduce some computations, so that the classification time can be further reduced. A rectifier and an inverter are demonstrated to prove effectiveness of the presented design