查看更多>>摘要：Current study results on robotics have been published. According to news reporting originating from the Council of Scientific and Industrial Research (CSIR) by NewsRx correspondents, research stated, “Spatial awareness is an important competence for a mobile robotic system.” Our news editors obtained a quote from the research from Council of Scientific and Industrial Research (CSIR): “A robot needs to localise and perform context interpretation to provide any meaningful service. With the deep learning tools and readily available sensors, visual place recognition is a first step towards identifying the environment to bring a robot closer to spatial awareness. In this paper, we implement place recognition on a mobile robot considering a deep learning approach. For simple place classification, where the task involves classifying images into a limited number of categories, all three architectures; VGG16, Inception-v3 and ResNet50, perform well.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Recently, artificial intelligence generated content (AIGC) has been receiving increased attention and is growing exponentially. AIGC is generated based on the intentional information extracted from human-provided instructions by generative artificial intelligence (AI) models.” Our news journalists obtained a quote from the research from Fudan University, “AIGC quickly and automatically generates large amounts of high-quality content. Currently, there is a shortage of medical resources and complex medical procedures in medicine. Due to its characteristics, AIGC can help alleviate these problems. As a result, the application of AIGC in medicine has gained increased attention in recent years. Therefore, this paper provides a comprehensive review on the recent state of studies involving AIGC in medicine. First, we present an overview of AIGC. Furthermore, based on recent studies, the application of AIGC in medicine is reviewed from two aspects: medical image processing and medical text generation. The basic generative AI models, tasks, target organs, datasets and contribution of studies are considered and summarized. Finally, we also discuss the limitations and challenges faced by AIGC and propose possible solutions with relevant studies.”
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, “The process of senescence impairs the function of cells and can ultimately be a key factor in the development of disease. With an aging population, senescence-related diseases are increasing in prevalence.” Our news journalists obtained a quote from the research from the University College London (UCL) Institute of Ophthalmology, “Therefore, understanding the mechanisms of cellular senescence within the central nervous system (CNS), including the retina, may yield new therapeutic pathways to slow or even prevent the development of neuro- and retinal degenerative diseases. One method of probing the changing functions of senescent retinal cells is to observe retinal microglial cells. Their morphological structure may change in response to their surrounding cellular environment. In this chapter, we show how microglial cells in the retina, which are implicated in aging and diseases of the CNS, can be identified, quantified, and classified into five distinct morphotypes using image processing and supervised machine learning algorithms. The process involves dissecting, staining, and mounting mouse retinas, before image capture via fluorescence microscopy. The resulting images can then be classified by morphotype using a support vector machine (SVM) we have recently described showing high accuracy. This SVM model uses shape metrics found to correspond with qualitative descriptions of the shape of each morphotype taken from existing literature. We encourage more objective and widespread use of methods of quantification such as this.”
查看更多>>摘要：New research on Diseases and Conditions - Eagle Syndrome is the subject of a report. According to news originating from Ferrara, Italy, by NewsRx correspondents, research stated, “The aim of the study is to conduct a systematic review of the existing literature on styloidectomy performed through transoral robotic surgery (TORS) in Eagle syndrome (ES). Two independent reviewers (RC and AC) conducted a systematic review of PubMed and Embase databases, seeking articles on TORS performed for ES treatment.” Our news journalists obtained a quote from the research from the University Hospital of Ferrara, “The search was conducted in July 2023. The review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review included a total of 17 adult patients, comprising 12 females and 5 males, with an average age of 52.2 years, all diagnosed with ES. For each patient, we assessed the overall length of the styloid process, the affected side, total intervention duration, hospitalization duration, pre and postoperative Visual Analogue Scale (VAS) scores, and the presence of minor and major complications. We identified 4 articles describing 17 instances of TORS as a surgical treatment for ES in the literature, totaling 18 styloidectomies. The mean age of the patients was 52.2 years, with 12 females and 5 males. The average operation time, inclusive of the docking phase, was 68.8 minutes. Sixteen patients (94.1% of the total) experienced complete symptom disappearance or near-complete resolution after surgery.”
查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, “Machine learning (ML)- based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models is scarce. We aimed to review health-care professional (HCP) and patient perceptions of ML risk prediction models in published literature, to inform future risk prediction model development.” Our news journalists obtained a quote from the research from University College London (UCL), “Following database and citation searches, we identified 41 articles suitable for inclusion. Article quality varied with qualitative studies performing strongest. Overall, perceptions of ML risk prediction models were positive. HCPs and patients considered that models have the potential to add benefit in the health-care setting. However, reservations remain; for example, concerns regarding data quality for model development and fears of unintended consequences following ML model use. We identified that public views regarding these models might be more negative than HCPs and that concerns (eg, extra demands on workload) were not always borne out in practice. Conclusions are tempered by the low number of patient and public studies, the absence of participant ethnic diversity, and variation in article quality.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating in Helsinki, Finland, by NewsRx journalists, research stated, “Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper, we apply a recently introduced manifold visualisation method, slisemap, on datasets from physics and chemistry. slisemap combines manifold visualisation with explainable artificial intelligence.” Financial supporters for this research include Research Council of Finland, Research Council of Finland, Research Council of Finland, Helsinki University Library, Research Council of Finland, Finnish Computing Competence Infrastructure, Doctoral Programme of University of Helsinki.
查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting out of Aachen, Germany, by NewsRx editors, research stated, “Animals have evolved mechanisms to travel safely and efficiently within different habitats. On a journey in dense terrains animals avoid collisions and cross narrow passages while controlling an overall course.” Our news journalists obtained a quote from the research from Peter Grunberg Institut, “Multiple hypotheses target how animals solve challenges faced during such travel. Here we show that a single mechanism enables safe and efficient travel. We developed a robot inspired by insects. It has remarkable capabilities to travel in dense terrain, avoiding collisions, crossing gaps and selecting safe passages. These capabilities are accomplished by a neuromorphic network steering the robot toward regions of low apparent motion. Our system leverages knowledge about vision processing and obstacle avoidance in insects. Our results demonstrate how insects might safely travel through diverse habitats. We anticipate our system to be a working hypothesis to study insects’ travels in dense terrains.”
查看更多>>摘要：Researchers detail new data in Artificial Intelligence. According to news reporting originating in Dalian, People’s Republic of China, by NewsRx journalists, research stated, “With the continuous improvement and development of the metauniverse concept, numerous new technologies have emerged to address the new demands, including big data technology, artificial intelligence technology, immersive interaction technology, and decentralized network ecological technology. However, the large-scale deployment and usage of these technologies have raised concerns about energy consumption and sustainability.” Funders for this research include National Key R\&D Program of China, Guangdong Province Basic and Applied Basic Research Foundation. The news reporters obtained a quote from the research from Dalian Maritime University, “This article proposes a green distributed network architecture that combines edge intelligence and the metauniverse. We utilize artificial intelligence to guide edge nodes, improving data processing and transmission efficiency, thereby optimizing energy utilization for Al tasks within the network. Our proposed architecture primarily adopts a model splitting and distributed routing decision framework to achieve this objective. By adopting this architecture, we can effectively meet the developmental requirements of the metauniverse while promoting sustainability through efficient energy utilization.”
查看更多>>摘要：Fresh data on robotics are presented in a new report. According to news reporting from Jeddah, Saudi Arabia, by NewsRx journalists, research stated, “This paper presents an advanced control strategy based on Fractional-Order Sliding Mode Control (FO-SMC), which introduces a robust solution to significantly improve the reliability of robotic manipulator systems and increase its control performance.” Funders for this research include King Abdulaziz University. Our news reporters obtained a quote from the research from Department of Electrical and Computer Engineering: “The proposed FO-SMC strategy includes a two-key term-based Fractional Sliding Function (FSF) that presents the main contribution of this work. Additionally, a fractional-order-based Lyapunov stability analysis is developed for a class of nonlinear systems to guarantee the asymptotic stability of the closed loop system.” According to the news editors, the research concluded: “Four FSF-based versions of the designed FO-SMC are studied and discussed. Various scenarios of the proposed control strategy are tested on a 3-degree-of-freedom SCARA robotic arm and compared to recent FO-SMC works, demonstrating the effectiveness of the new proposed control strategy to (i) ensure the asymptotic stability, (ⅱ) achieve a smooth start-up, (ⅲ) cancel the static error, giving a good tracking trajectory, and (ⅳ) reduce the control torques, yielding a consumed energy minimization.”
查看更多>>摘要：Researchers detail new data in Robotics. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “The efficiency of a robotic system is primarily determined by its ability to navigate complex and interactive environments. In real-world scenarios, cluttered surroundings are common, requiring a robot to navigate diverse spaces and displace objects to pave a path towards its objective.” Financial support for this research came from Science & Technology Commission of Shanghai Municipality (STCSM). Our news editors obtained a quote from the research from East China Normal University, “Consequently, ‘Visual Interactive Navigation’ presents several challenges, including how to retain historical exploration information from partially observable visual signals, and how to utilize sparse rewards in reinforcement learning to simultaneously learn a latent representation and a control policy. Addressing these challenges, we introduce a Transformer-based Visual Memory Encoder (VME-Transformer), capable of embedding both recent and long-term exploration information into memory. Additionally, we explicitly estimate the robot’s next pose, conditioned on the impending action, to bootstrap the learning process of the high-capacity VME-Transformer. We further regularize the value function by introducing input perturbations, thereby enhancing its generalization capabilities in previously unseen environments.”
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