Active contour configuration model for estimating the posterior ablative margin in image fusion of real-time ultrasound and 3D ultrasound or magnetic resonance images for radiofrequency ablation: an experimental study

Purpose The purpose of this study was to evaluate the accuracy of an active contour model for estimating the posterior ablative margin in images obtained by the fusion of real-time ultrasonography (US) and 3-dimensional (3D) US or magnetic resonance (MR) images of an experimental tumor model for radiofrequency ablation. Methods Chickpeas (n=12) and bovine rump meat (n=12) were used as an experimental tumor model. Grayscale 3D US and T1-weighted MR images were pre-acquired for use as reference datasets. US and MR/3D US fusion was performed for one group (n=4), and US and 3D US fusion only (n=8) was performed for the other group. Half of the models in each group were completely ablated, while the other half were incompletely ablated. Hyperechoic ablation areas were extracted using an active contour model from real-time US images, and the posterior margin of the ablation zone was estimated from the anterior margin. After the experiments, the ablated pieces of bovine rump meat were cut along the electrode path and the cut planes were photographed. The US images with the estimated posterior margin were compared with the photographs and post-ablation MR images. The extracted contours of the ablation zones from 12 US fusion videos and post-ablation MR images were also matched. Results In the four models fused under real-time US with MR/3D US, compression from the transducer and the insertion of an electrode resulted in misregistration between the real-time US and MR images, making the estimation of the ablation zones less accurate than was achieved through fusion between real-time US and 3D US. Eight of the 12 post-ablation 3D US images were graded as good when compared with the sectioned specimens, and 10 of the 12 were graded as good in a comparison with nicotinamide adenine dinucleotide staining and histopathologic results. Conclusion Estimating the posterior ablative margin using an active contour model is a feasible way of predicting the ablation area, and US/3D US fusion was more accurate than US/MR fusion

Clinical Practice Guideline for Accurate Diagnosis and Effective Treatment of Gastrointestinal Stromal Tumor in Korea

Despite the rarity in incidence and prevalence, gastrointestinal stromal tumor (GIST) has emerged as a distinct pathogenetic entity. And the clinical management of GIST has been evolving very rapidly due to the recent recognition of its oncogenic signal transduction pathway and the introduction of new molecular-targeted therapy. Successful management of GIST requires a multidisciplinary approach firmly based on accurate histopathologic diagnosis. However, there was no standardized guideline for the management of Korean GIST patients. In 2007, the Korean GIST study group (KGSG) published the first guideline for optimal diagnosis and treatment of GIST in Korea. As the second version of the guideline, we herein have updated recent clinical recommendations and reflected changes in diagnosis, surgical and medical treatments for more optimal clinical practice for GIST in Korea. We hope the guideline can be of help in enhancing the quality of diagnosis by members of the Korean associate of physicians involving in GIST patients's care and subsequently in achieving optimal efficacy of treatment

Nitro group reduction and Suzuki reaction catalysed by palladium supported on magnetic nanoparticles modified with carbon quantum dots generated from glycerol and urea

Glycerol and urea were used as green and cheap sources of carbon quantum dots (CQD) for modifying Fe3O4 nanoparticles (NPs). The obtained CQD@Fe3O4 NPs were used for the stabilization of palladium species and the prepared catalyst, Pd@CQD@Fe3O4, was characterized using various techniques. This magnetic supported palladium was applied as an efficient catalyst for the reduction of aromatic nitro compounds to primary amines at room temperature using very low palladium loading (0.008 mol%) and also for the Suzuki–Miyaura cross-coupling reaction of aryl halides as well as challenging heteroaryl bromides and aryl diazonium salts with arylboronic acids and with potassium phenyltrifluoroborate. This magnetically recyclable catalyst was recovered and reused for seven consecutive runs in the reduction of 4-nitrotoluene to p-toluidine and for ten consecutive runs in the reaction of 4-iodoanisole with phenylboronic acid with small decrease of activity. The catalyst reused in the Suzuki reaction was characterized using transmission electron microscopy, vibrating sample magnetometry and X-ray photoelectron spectroscopy. Using experiments such as hot filtration and poisoning tests, it has been shown that the true catalyst works under homogeneous conditions according to the release–return pathway of active palladium species.Iran National Science Foundation, Grant/Award Number: 95844587; the Generalitat Valenciana, Grant/Award Number: PROMETEOII/2014/017; the Spanish Ministerio de Economía, Industria y Competitividad, Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER, EU), Grant/Award Number: CTQ2016‐81797‐REDC and CTQ2016‐76782‐P; the Spanish Ministerio de Economía y Competitividad (MINECO), Grant/Award Number: CTQ2014‐51912‐REDC and CTQ2013‐43446‐P

Catalytic Upgrading of Biomass Model Compounds: Novel Approaches and Lessons Learnt from Traditional Hydrodeoxygenation – a Review

Catalytic hydrodeoxygenation (HDO) is a fundamental process for bio‐resources upgrading to produce transportation fuels or added value chemicals. The bottleneck of this technology to be implemented at commercial scale is its dependence on high pressure hydrogen, an expensive resource which utilization also poses safety concerns. In this scenario, the development of hydrogen‐free alternatives to facilitate oxygen removal in biomass derived compounds is a major challenge for catalysis science but at the same time it could revolutionize biomass processing technologies. In this review we have analysed several novel approaches, including catalytic transfer hydrogenation (CTH), combined reforming and hydrodeoxygenation, metal hydrolysis and subsequent hydrodeoxygenation along with non‐thermal plasma (NTP) to avoid the supply of external H2. The knowledge accumulated from traditional HDO sets the grounds for catalysts and processes development among the hydrogen alternatives. In this sense, mechanistic aspects for HDO and the proposed alternatives are carefully analysed in this work. Biomass model compounds are selected aiming to provide an in‐depth description of the different processes and stablish solid correlations catalysts composition‐catalytic performance which can be further extrapolated to more complex biomass feedstocks. Moreover, the current challenges and research trends of novel hydrodeoxygenation strategies are also presented aiming to spark inspiration among the broad community of scientists working towards a low carbon society where bio‐resources will play a major role.Financial support for this work was provided by the Department of Chemical and Process Engineering of the University of Surrey and the EPSRC grants EP/J020184/2 and EP/R512904/1 as well as the Royal Society Research Grant RSGR1180353. Authors would also like to acknowledge the Ministerio de Economía, Industriay Competitividad of Spain (Project MAT2013‐45008‐P) and the Chinese Scholarship Council (CSC). LPP also thanks Comunitat Valenciana for her postdoctoral fellow (APOSTD2017)

An Antenna Proximity Sensor for Mobile Terminals Using Reflection Coefficient

This paper presents a new antenna proximity sensor for mobile terminals based on the measured reflection coefficient using a bidirectional coupler which is positioned between the main antenna and the front-end module. Using the coupled forward and reverse long-term evolution signals by the bidirectional coupler, the reflection coefficient looking into the antenna was calculated in the base-band processor. The measured reflection coefficients showed clear differences for both the types of objects, and the distances between the terminal and the objects. The proposed antenna proximity sensor showed a recognition distance that was approximately 5 mm longer than that of a conventional capacitive proximity sensor

Cognitive Motivations of Free Riding and Cooperation and Impaired Strategic Decision Making in Schizophrenia During a Public Goods Game

Schizophrenia is generally characterized by various positive and negative symptoms that are accompanied by significant social dysfunction. Various researchers investigated the functional impairments in schizophrenia including impaired theory of mind (TOM), poor integration of affective and cognitive information, and malfunctioning of adaptive and strategic learning process. However, most of the studies were limited to simplified cognitive tests or computerized choice games that exclude real social interaction. The aim of the current study was to investigate human strategies based on the incentives and particularly the cognitive and emotional motivations of free riding. We examined the decision patterns of 41 healthy subjects (HSs) and 37 schizophrenia patients (SZ) during the public goods game (PGG), one of the games simulating human cooperation and free riding in group interactions. Strategic decision processes during the iterative binary PGG were assessed in terms of cognitive understanding, loss sensitivity, and TOM. We found that greed and loss sensitivity both motivated free-riding behavior in the HS, but that they were more vulnerable to greedy incentives than to possible loss. More significantly, the SZ clearly displayed a lower prevalence of free riding and distinct decision patterns from HS. Nonstrategic and unexpectedly low free ridings in the SZ likely arise from poor integration of cognitive and affective information. We suggest that loss sensitivity and TOM as well as cognitive understanding are involved in regulation of the free riding and cooperative behavior

Indoor Air Quality Analysis Using Deep Learning with Sensor Data

Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the measurements and predict the air quality of near future. We designed a microchip made out of sensors that is capable of periodically recording measurements, and proposed a model that estimates atmospheric changes using deep learning. In addition, we developed an efficient algorithm to determine the optimal observation period for accurate air quality prediction. Experimental results with real-world data demonstrate the feasibility of our approach

Economic dispatch constrained by central multi-period security for Global Energy Interconnection and its application in the Northeast Asia

AbstractIn recent years, the global energy interconnection (GEI) has more and more profound influence around the world, which is a highly practical way for humans to handle the energy crisis. In the studies of GEI, the economic dispatch (ED) is a basic and important content. In this paper, a model of dynamic economic dispatch (DED) of GEI is presented, which include the renewable energy generation. The objective function of this model is composed of the operating costs and the renewable energy curtailment. A series of case studies for the transnational energy interconnection in Northeast Asia are given to verify the superiority of GEI and for further analysis. Keywords: Global energy interconnection, Dynamic economic dispatch, Renewable energy resource

Effect of DA-9701 on Gastric Motor Function Assessed by Magnetic Resonance Imaging in Healthy Volunteers: A Randomized, Double-Blind, Placebo-Controlled Trial.

Improving gastric accommodation and gastric emptying is an attractive physiological treatment target in patients with functional dyspepsia (FD). We evaluated the effect of DA-9701, a new drug for FD, on gastric motor function after a meal in healthy volunteers using magnetic resonance imaging (MRI).Forty healthy volunteers were randomly allocated to receive either DA-9701 or placebo. After 5 days of treatment, subjects underwent gastric MRI (60 min before and 15, 30, 45, 60, 90, and 120 min after a liquid test meal). Gastric volume was measured through 3-dimensional reconstruction from MRI data. We analyzed 4 outcome variables including changes in total gastric volume (TGV), proximal TGV, and proximal to distal TGV ratio after a meal and gastric emptying rates after adjusting values at the pre-test meal.Changes in TGV and proximal TGV after a meal did not differ between the DA-9701 and placebo groups (difference between groups -25.9 mL, 95% confidence interval [CI] -54.0 to 2.3 mL, P = 0.070 and -2.9 mL, 95% CI -30.3 to 24.5 mL, P = 0.832, respectively). However, pre-treatment with DA-9701 increased postprandial proximal to distal TGV ratio more than placebo (difference between groups 0.93, 95% CI 0.08 to 1.79, P = 0.034). In addition, pre-treatment with DA-9701 significantly increased gastric emptying as compared with placebo (mean difference between groups 3.41%, 95% CI 0.54% to 6.29%, P = 0.021, by mixed model for repeated measures).Our results suggested that DA-9701 enhances gastric emptying and does not significantly affect gastric accommodation in healthy volunteers. Further studies to confirm whether DA-9701 enhances these gastric motor functions in patients with FD are warranted.ClinicalTrials.gov NCT02091635