86,664 research outputs found
Endovascular treatment of two concomitant causes of pulsatile tinnitus: sigmoid sinus stenosis and ipsilateral jugular bulb diverticulum. Case report and literature review
No full textSpatiotemporal characterization of brain infarction by sequential multimodal MR imaging following transient focal ischemia in a Rat model of intra-arterial middle cerebral artery occlusion
No full textObjectives To assess spatiotemporal brain infarction evolu- tion by sequential multimodal magnetic resonance (MR) im- aging in an endovascular model of acute stroke in rats. Materials and methods A microwire was selectively placed in the middle cerebral artery (MCA) in 16 consecutives rats dur- ing 90 minutes occlusion. Longitudinal 7-T MR imaging, in- cluding angiography, diffusion, and perfusion was performed during ischemia, immediately after reperfusion, 3 h and 24 h after subsequent reperfusion.
Results MCA occlusion was complete in 75 % and partial in 18.7 %. Hypoperfusion (mean ± SD) was observed in all ani- mals during ischemia (-59 ± 18 % of contralateral hemisphere, area 31±5 mm2). Infarction volume (mean±SD) was 90 ± 64 mm3 during ischemia and 57 ± 67 mm3 at 24 h. Brain infarction was fronto-parietal cortical in five animals (31 %), striatal in four animals (25 %), and cortico-striatal in seven animals (44 %) at 24 h. All rats survived at 24 h.
Conclusion This model is suitable to neuroprotection studies because of possible acute and close characterization of spatio- temporal evolution of brain infarction by MR imaging
techniques, and evidence of ischemic penumbra, the target of neuroprotection agents. However, optimization of the brain infarct reproducibility needs further technical and neurointerventional tools improvements.
Key points
• Nitinol microwire is MRI compatible allowing spatiotempo-
ral characterization of brain infarction in rats.
• Microwire selective placement in middle cerebral artery al-
lows complete artery occlusion in 75 %.
• A diffusion/perfusion mismatch during arterial occlusion is
observed in 77 % of rats
Temporary solitaire stent-assisted coiling: a technique for the treatment of acutely ruptured wide-neck intracranial aneurysms
No full textIn Reply to Antiplatelet Therapy Prior to Temporary Stent-Assisted Coiling
No full textWe would like to thank Drs Almekhlafi and Goyal for their comments concerning our article, “Temporary Solitaire Stent-Assisted Coiling: A Technique for the Treatment of Acutely Ruptured Wide-Neck Intracranial Aneurysms.”
Almekhlafi et al noticed that we performed the procedures without preadministering antiplatelet therapy, and they would like to caution against the wide adoption of this technique with- out pretreatment with antiplatelet agents. They reported the en- dovascular treatment of 10 aneurysms (6 unruptured and 4 ruptured) in 8 patients by using temporary stent-assisted coiling. One of their patients with an unruptured aneurysm was not pretreated with dual antiplatelet therapy and presented with a procedural in-stent thrombosis with no clinical sequelae.
An antiplatelet regimen is usually administered before stent placement in selective cases. However, in our article, we reported our experience in a different situation (acutely ruptured aneurysms). In this setting, to the best of our knowledge, it seems clear that adverse events happen more commonly and clinical out- comes are likely to be worse than those achieved without stent assistance; thus, we did not use antiplatelet therapy in our series. Recently, Bechan et al. compared the rate of stent-placement complications in acutely ruptured versus unruptured aneurysms, and they have shown that the morbidity and mortality increased. Application of dual antiplatelet therapy in stent-assisted coiling of acutely ruptured aneurysms is associated with an increased risk of hemorrhagic complications following shunt placement,5 especially in middle cerebral artery and anterior communicating artery aneurysms.6 In our series, 4 of the 8 patients underwent emergent shunt placement and no hemorrhagic complication was noted.
As Drs Almekhlafi and Goyal noted, temporary stent-assisted coiling could be a helpful technique; however, it should be considered only when other endovascular techniques are not feasible, especially in the setting of acute ruptured aneurysms. The current literature does not support using antiplatelet therapy in this set- ting because it associated with worse prognosis
AI-Powered Drone to Address Smart City Security Issues
No full textThe idea of a dazzling metropolis has drawn interest from all across the world. New innovations like blockchain, IoT, artificial intelligence, robots, and many other things were added to it. Security is one of the top issues for people living in big cities, and everyone wants to feel completely secure when traveling around every single day. In this research, we will look into how CEOs in affluent cities use and value robots, especially in terms of security. To understand the robot security the board stream, some approaches and intricacies are used. Following that is a discussion of issues with urban security and the application of artificial intelligence to drones as a management tool. The use of cutting-edge technology, such as blockchain, to support smart urban community management is covered in the last part. The smart city idea and all of its benefits for local inspection are supported by robotic use. The idea of thriving urban areas is spreading around the world and is crucial in the context of developing economies. We examined how to leverage cutting-edge technologies in this project to make it feasible. Artificial intelligence, robotics breakthroughs, and blockchain technologies all have significant effects. This research highlights their significance to analysts and how they consider them when assessing prospects. This project will be very beneficial for analysts and experts in a relevant subject
Quantifying uncertainty in internet of medical things and big-data services using intelligence and deep learning
No full textIn the cloud-based Internet of Things (IoT) environments, quantifying uncertainty is an important element input to keep the acceptable level of reliability in various configurations. In this paper, we aim to address the pricing model of delivering data over the cloud while taking into consideration the dynamic uncertainty factors such as network topology, transmission/reception energy, nodal charge and power, and computation capacity. These uncertainty factors are mapped to different nodes with varying capabilities to be processed using Artificial Intelligence (AI)-based algorithms. Accordingly, we aim to find a way to calculate and predict the price per big data service over the cloud using AI and deep learning. Therefore, in this paper, we propose a framework to address big data delivery issues in cloud-based IoT environments by considering uncertainty factors. We compare the performance of the framework using two AI-based techniques called Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA) in both centralized and distributed versions. The use of AI techniques can be applied in multilevel to provide a kind of deep learning to further improve the performance of the system under study. The results reveal that the distributed algorithm outperforms the centralized one. In addition, the results show that the GA has lower running time compared to the SAA in all the test cases such as 68% of improvement in the centralized version, and 66% of improvement in the distributed version in case when the size of uncertainty array is 256. Moreover, when the size of uncertainty array increases, the results show 60% speed up in the distributed GA compared to its centralized version. The improvements achieved would help the service providers to actually improve their profit using the proposed framework
Guest Editorial: Smart Measurement in Machine Vision for Challenging Applications
No full textSmart measurements are widely deployed in many applications due to the technology advancement. For various industrial applications, automated inspection and analysis based on the image is provided by machine vision. For the measurements in these applications, sensors must be connected. Machine vision tries to creatively combine already existing technology and use them to address current issues. The term "measurement" is frequently used to refer to many tasks and is the cornerstone of industrial automation and security deployment. This Special Issue of Instrumentation & Measurement Magazine addresses some novel achievements in the measurement and instrumentation science and technology fields. It advances machine vision concerning production, application of smart materials, measurement and estimation techniques, etc. The variety of selected papers reflects the efforts made by the authors to focus either on methodological aspects or technical issues. In particular, three papers have been accepted for publication, reflecting several aspects of the abovementioned fields by covering machine vision and image processing technology
Applications of Artificial Intelligence and Machine learning in smart cities
No full textSmart cities are aimed to efficiently manage growing urbanization, energy consumption, maintain a green environment, improve the economic and living standards of their citizens, and raise the people's capabilities to efficiently use and adopt the modern information and communication technology (ICT). In the smart cities concept, ICT is playing a vital role in policy design, decision, implementation, and ultimate productive services. The primary objective of this review is to explore the role of artificial intelligence (AI), machine learning (ML), and deep reinforcement learning (DRL) in the evolution of smart cities. The preceding techniques are efficiently used to design optimal policy regarding various smart city-oriented complex problems. In this survey, we present in-depth details of the applications of the prior techniques in intelligent transportation systems (ITSs), cyber-security, energy-efficient utilization of smart grids (SGs), effective use of unmanned aerial vehicles (UAVs) to assure the best services of 5G and beyond 5G (B5G) communications, and smart health care system in a smart city. Finally, we present various research challenges and future research directions where the aforementioned techniques can play an outstanding role to realize the concept of a smart city
Share: A Design Pattern for Dynamic Composition of IoT Services
No full textThe Internet-of-Things (IoT) is one of the modern technological revolutions that enables communication amongst a plethora of different devices. To date 30 billion devices are connected to the internet more than 75 billion devices are foreseen to be connected worldwide by 2025, a five fold increase in ten years. Devices can have different brands and developers and can be designed to function on a proprietary ecosystem, with separate applications, gateways and tools to support them. This fragmentation can be disastrous in certain industries, such as the medical ones, and limit integration between different systems. In this paper, we envision a solution to overcome this interaction problems. We propose Share a novel programming standard through a design pattern. This allows on the fly service composition of resource constrained IoT devices. To this ending, IoT devices exchange integration codes which specify the data format and the interaction protocol. The design by contract scheme (DCS) is used to make sure that the matching services verify the constraints dictated by the composition. Unlike other on the fly approaches, Share can run on very small and resource constrained devices. Share has been implemented by using LUA programming language and has been validated on the ESP30 embedded device
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