Non-singlet Baryons in Less Supersymmetric Backgrounds

We analyze the holographic description of non-singlet baryons in various backgrounds with reduced supersymmetries and/or confinement. We show that they exist in all AdS_5xY_5 backgrounds with Y_5 an Einstein manifold bearing five form flux, for a number of quarks 5N/8< k< N, independently on the supersymmetries preserved. This result still holds for gamma_i deformations. In the confining Maldacena-Nunez background non-singlet baryons also exist, although in this case the interval for the number of quarks is reduced as compared to the conformal case. We generalize these configurations to include a non-vanishing magnetic flux such that a complementary microscopical description can be given in terms of lower dimensional branes expanding into fuzzy baryons. This description is a first step towards exploring the finite 't Hooft coupling region.Comment: 36 Pages, 1 figure, Latex, v2: few minor changes, JHEP versio

Surreal: Enhancing Surgical simulation Realism using style transfer

Surgical simulation is an increasingly important element of surgical education. Using simulation can be a means to address some of the significant challenges in developing surgical skills with limited time and resources. The photo-realistic fidelity of simulations is a key feature that can improve the experience and transfer ratio of trainees. In this paper, we demonstrate how we can enhance the visual fidelity of existing surgical simulation by performing style transfer of multi-class labels from real surgical video onto synthetic content. We demonstrate our approach on simulations of cataract surgery using real data labels from an existing public dataset. Our results highlight the feasibility of the approach and also the powerful possibility to extend this technique to incorporate additional temporal constraints and to different applications

Semiclassical strings in marginally deformed toric AdS/CFT

We study string solutions in the beta-deformed Sasaki-Einstein gauge/gravity dualities. We find that the BPS point-like strings move in the submanifolds where the two U(1) circles shrink to zero size. In the corresponding T^3 fibration description, the strings live on the edges of the polyhedron, where the T^3 fibration degenerates to T^1. Moreover, we find that for each deformed Sasaki-Einstein manifold the BPS string solutions exist only for particular values of the deformation parameter. Our results imply that in the dual field theory the corresponding BPS operators exist only for these particular values of the deformation parameter we find. We also examine the non-BPS strings, derive their dispersion relations and compare them with the undeformed ones. Finally, we comment on the range of the validity of our solutions and their dependence on the deformation parameter.Comment: 29 pages, 9 figure

A spherical joint robotic end-effector for the Expanded Endoscopic Endonasal Approach

The endonasal transsphenoidal approach allows surgeons to access the pituitary gland through the natural orifice of the nose. Recently, surgeons have also described an Expanded Endoscopic Endonasal Approach (EEEA) for the treatment of other tumours around the base of the brain. However, operating in this way with nonarticulated tools is technically very difficult and not widely adopted. The goal of this study is to develop an articulated end-effector for a novel handheld robotic tool for the EEEA. We present a design and implementation of a 3.6mm diameter, three degrees-of-freedom, tendon-driven robotic end-effector that, contrary to rigid instruments which operate under fulcrum, will give the surgeon the ability to reach areas on the surface of the brain that were previously inaccessible. We model the end-effector kinematics in simulation to study the theoretical workspace it can achieve prior to implementing a test-bench device to validate the efficacy of the end-effector. We find promising repeatability of the proposed robotic end-effector of 0.42mm with an effective workspace with limits of ±30∘, which is greater than conventional neurosurgical tools. Additionally, although the tool’s end-effector has a small enough diameter to operate through the narrow nasal access path and the constrained workspace of EEEA, it showcased promising structural integrity and was able to support approximately a 6N load, despite a large deflection angle the limiting of which is scope of future work. These preliminary results indicate the end-effector is a promising first step towards developing appropriate handheld robotic instrumentation to drive EEEA adoption

Can surgical simulation be used to train detection and classification of neural networks?

Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems

Towards video-based surgical workflow understanding in open orthopaedic surgery

Safe and efficient surgical training and workflow management play a critical role in clinical competency and ultimately, patient outcomes. Video data in minimally invasive surgery (MIS) have enabled opportunities for vision-based artificial intelligence (AI) systems to improve surgical skills training and assurance through post-operative video analysis and development of real-time computer-assisted interventions (CAI). Despite the availability of mounted cameras for the operating room (OR), similar capabilities are much more complex to develop for recording open surgery procedures, which has resulted in a shortage of exemplar video-based training materials. In this paper, we present a potential solution to record open surgical procedures using head-mounted cameras. Recorded videos were anonymised to remove patient and staff identifiable information using a machine learning algorithm that achieves state-of-the-art results on the OR Face dataset. We then propose a CNN-LSTM-based model to automatically segment videos into different surgical phases, which has never been previously demonstrated in open procedures. The redacted videos, along with the automatically predicted phases, are then available for surgeons and their teams for post-operative review and analysis. To our knowledge, this is the first demonstration of the feasibility of deploying camera recording systems and developing machine learning-based workflow analysis solutions for open surgery, particularly in orthopaedics

On the pulsating strings in AdS_5 x T^{1,1}

We study the class of pulsating strings in AdS_5 x T^{1,1}. Using a generalized ansatz for pulsating string configurations we find new solutions of this class. Further we semiclassically quantize the theory and obtain the first correction to the energy. The latter, due to AdS/CFT correspondence, is supposed to give the anomalous dimensions of operators in the dual N=1 superconformal gauge field theory.Comment: 12 pages, improvements made, references adde