查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Fresh data on artificial intelligence are presented in a new report. According to newsreporting originating from Zhej iang University by NewsRx correspondents, research stated, "Ultrasoundtechnolog y has been recognized as the mainstream approach for the identification of gas-l iquid two-phaseflow patterns, which holds great value in engineering domain."Funders for this research include National Natural Science Foundation of China.Our news journalists obtained a quote from the research from Zhejiang University : "However, commercialrigid probes are bulky, limiting their adaptability to cu rved surfaces. Here, we propose a strategyfor autonomous identification of flow patterns based on flexible ultrasound array and machine learning.The array fea tures high-performance 1-3 piezoelectric composite material, stretchable serpent ine wires,soft Eco-flex layers and a polydimethylsiloxane (PDMS) adhesive layer . The resulting ultrasound arrayexhibits excellent electromechanical characteri stics and offers a large stretchability for an intimate interfacialcontact to c urved surface without the need of ultrasound coupling agents. We demonstrated th atthe flexible ultrasound array combined with machine learning can accurately i dentify gas-liquid two-phaseflow patterns, in a circular pipeline."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on Artificial Intelligenc e is the subject of a report. According to newsreporting from Beijing, People's Republic of China, by NewsRx journalists, research stated, "Shorteningthe acqu isition time of brain three-dimensional T2 fluid-attenuated inversion recovery ( 3D T2 FLAIR) byusing acceleration techniques has the potential to reduce motion artifacts in images and facilitate clinicalapplication. This study aimed to as sess the image quality of brain 3D T2 FLAIR accelerated by artificialintelligen ce-assisted compressed sensing (ACS) in comparison to 3D T2 FLAIR accelerated by parallelimaging (PI)."The news correspondents obtained a quote from the research from Capital Medical University, "In thisprospective cohort study, 102 consecutive participants, inc luding both healthy individuals and those withsuspected brain diseases, were re cruited and underwent both ACS- and PI-3D T2 FLAIR scans with a3.0-Tesla magnet ic resonance imaging system from February 2023 to October 2023 in Beijing Tiantan Hospital, Capital Medical University. Quantitative assessment involved white m atter (WM) and graymatter (GM) signal-to-noise ratio (SNR) and contrast-to-nois e ratio (CNR), whole-image sharpness, andtumor volume. Qualitative assessment i ncluded the scoring of overall image quality, GM-WM bordersharpness, and diagno stic confidence in lesion detection. ACS-3D T2 FLAIR exhibited a shorter acquisition time compared to PI-3D T2 FLAIR (105 320 seconds). ACS-3D T2 FLAIR, compare d to PI-3DT2 FLAIR, demonstrated a significantly higher mean SNR (25.922±6.811 22.544±5.853; P<0.001), SNR(18.324±7.137 17.102±6.659; P=0 .049), CNR (4.613±1.547 4.160±1.552; P<0.001), and sharpnes s(0.413±0.049 0.396±0.034; P<0.001), while no significant differences were found for the overall imagequality ratings (P=0.063) or GM-WM border sharpness ratings (P=0.125). A good agreement on tumorvolume was achieve d between ACS-3D T2 FLAIR and PI-3D T2 FLAIR images (intraclass correlationcoef ficient =0.999; 0.998-1.000; P<0.001). Images acquired with ACS demonstrated nearly equivalentdiagnostic confidence to those obtained with PI (P >0.05)."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Investigators publish new report on Di agnostics and Screening - Biomarkers. Accordingto news originating from Wuhan, People's Republic of China, by NewsRx correspondents, research stated,"Chronic kidney disease (CKD) is an increasingly prevalent medical condition associated w ith high mortalityand cardiovascular complications. The intricate interplay bet ween kidney dysfunction and subsequentmetabolic disturbances may provide insigh ts into the underlying mechanisms driving CKD onset andprogression."Financial supporters for this research include National Key R&D Pro gram of China, Key Researchand Development Project of Hubei Province, Interdisc iplinary Innovative Talents Foundation from RenminHos-pital of Wuhan University , Key Laboratory of Hubei Province.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on Artificial Intelligenc e is the subject of a report. According to newsreporting from London, United Ki ngdom, by NewsRx journalists, research stated, "From fake social mediaaccounts and generative artificial intelligence chatbots to trading algorithms and self-d riving vehicles,robots, bots and algorithms are proliferating and permeating ou r communication channels, social interactions,economic transactions and transpo rtation arteries. Networks of multiple interdependent andinteracting humans and intelligent machines constitute complex social systems for which the collectiveoutcomes cannot be deduced from either human or machine behaviour alone."The news correspondents obtained a quote from the research from the London Schoo l of Economicsand Political Science, "Under this paradigm, we review recent res earch and identify general dynamicsand patterns in situations of competition, c oordination, cooperation, contagion and collective decisionmaking,with context -rich examples from high-frequency trading markets, a social media platform, an opencollaboration community and a discussion forum. To ensure more robust and r esilient human-machinecommunities, we require a new sociology of humans and mac hines."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Fresh data on artificial intelligence are presented in a new report. According to newsoriginating from Beijing, Peopl e's Republic of China, by NewsRx editors, the research stated, "With thedevelop ment of society, spatial artificial intelligence (spatial AI) research is gradua lly able to play a greaterrole."Our news editors obtained a quote from the research from Peking University: "How ever, spatial AI hasproblems such as data alignment, poor interpretability, and cross domain learning. Therefore, this paperproposes an innovative GeoSOT-3D g rid modeling framework for spatial AI research, which enhancesthe application c apabilities of spatial AI. Grid modeling will be able to run through the upstrea m anddownstream of spatial AI research, providing encoding calculations and spa tial neighborhood embeddingmatrices for spatial data. This paper also uses task examples to demonstrate how to effectively organizeand index spatial data usin g GeoSOT-3D grids and conduct spatial AI research."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news reporting from Sichuan, People's Republic of China, by New sRx journalists, research stated, "Goal Navigation(ObjectNav) is the task that a n agent need navigate to an instance of a specific category in an unseen environ ment through visual observations within limited time steps. This work plays a si gnificant role in enhancing the efficiency of locating specific items in indoor spaces and assisting individuals in completing various tasks, as well asprovidi ng support for people with disabilities."Funders for this research include National Natural Science Foundation of China ( NSFC), China PostdoctoralScience Foundation, Natural Science Foundation of Sich uan Province, Central Universities BasicResearch Operating Costs Project.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on Machine Learning is th e subject of a report. According to newsreporting from Bavaria, Germany, by New sRx journalists, research stated, "Molecular analytics increasinglyutilize mach ine learning (ML) for predictive modeling based on data acquired through molecul ar profilingtechnologies. However, developing robust models that accurately cap ture physiological phenotypes ischallenged by the dynamics inherent to biologic al systems, variability stemming from analytical procedures,and the resource-in tensive nature of obtaining sufficiently representative datasets."Funders for this research include LMU Munich, Helmholtz Zentrum Munchen.The news correspondents obtained a quote from the research from Ludwig-Maximilia ns-UniversitatMunchen, "Here, we propose and evaluate a new method: Contextual Out-of-Distribution Integration(CODI). Based on experimental observations, CODI generates synthetic data that integrate unrepresentedsources of variation enco untered in real-world applications into a given molecular fingerprint dataset. B yaugmenting a dataset with out-of-distribution variance, CODI enables an ML mod el to better generalizeto samples beyond the seed training data, reducing the n eed for extensive experimental data collection.Using three independent longitud inal clinical studies and a case-control study, we demonstrate CODI'sapplicatio n to several classification tasks involving vibrational spectroscopy of human bl ood. We showcaseour approach's ability to enable personalized fingerprinting fo r multiyear longitudinal molecular monitoringand enhance the robustness of trai ned ML models for improved disease detection."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Fresh data on Robotics - Robotics and Automation are presented in a new report.According to news reporting from Chang sha, People's Republic of China, by NewsRx journalists, researchstated, "Safe c oordination of fixed-wing UAVs in unstructured environments poses challenges due to theintricate coupling of UAV cooperation, obstacle avoidance, and motion co nstraints. One task is timecriticalcoordination, which means that all UAVs can safely reach their destinations simultaneously."Financial support for this research came from National Natural Science Foundatio n of China (NSFC).The news correspondents obtained a quote from the research from the National Uni versity of DefenseTechnology, "Existing methods, which rely on a spatio-tempora l decoupling framework and design thecoordination law at the control layer, oft en compromise maneuverability and safety in coordination scenarios.To address t he challenges, we propose a planner-based framework that enables fixed-wing UAVs tonavigate in unknown, unstructured environments with time-critical coordinati on. This framework, which isproposed with theoretical analysis, coordinates the UAVs at the planning layer rather than the control layer.Moreover, a different ial-flatness-based trajectory planning method is presented within this framework ,after which a two-step method is designed to undermine the problem of local mi nima."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on Machine Learning is th e subject of a report. According to newsreporting out of Beijing, People's Repu blic of China, by NewsRx editors, research stated, "The immunesystem undergoes progressive functional remodeling from neonatal stages to old age. Therefore, un derstandinghow aging shapes immune cell function is vital for precise treatment of patients at different lifestages."Our news journalists obtained a quote from the research from the Academy of Math ematics andSystems Science, "Here, we constructed the first transcriptomic atla s of immune cells encompassing humanlifespan, ranging from newborns to supercen tenarians, and comprehensively examined gene expressionsignatures involving cel l signaling, metabolism, differentiation, and functions in all cell types to inv estigateimmune aging changes. By comparing immune cell composition among differ ent age groups, HLA highlyexpressing NK cells and CD83 positive B cells were id entified with high percentages exclusively in theteenager (Tg) group, whereas u nknown_T cells were exclusively enriched in the supercentenarian (S c)group. Notably, we found that the biological age (BA) of pediatric COVID-19 p atients with multisysteminflammatory syndrome accelerated aging according to th eir chronological age (CA). Besides, we provedthat inflammatory shift- myeloid abundance and signature correlate with the progression of complications inKawas aki disease (KD). The shift- myeloid signature was also found to be associated w ith KD treatmentresistance, and effective therapies improve treatment outcomes by reducing this signaling. Finally, basedon those age-related immune cell comp ositions, we developed a novel BA prediction model PHARE, which can apply to both scRNA-seq and bulk RNA-seq data. Using thismodel, w e found patients with coronary artery disease (CAD) also exhibit accelerated agi ng compared tohealthy individuals."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Investigators discuss new findings in Robotics - Robotics and Automation. Accordingto news originating from Xi'an, Pe ople's Republic of China, by NewsRx correspondents, research stated,"Achieving fully autonomous driving in urban traffic scenarios is a significant challenge t hat necessitatesbalancing safety, efficiency, and compliance with traffic regul ations. In this letter, we introduce a novelCurriculum Residual Hierarchical Re inforcement Learning (CR-HRL) framework."Financial supporters for this research include National Key R&D Pro gram of China, National NaturalScience Foundation of China (NSFC).Our news journalists obtained a quote from the research from Xi'an Jiaotong Univ ersity, "It integrates arule-based planning model as a guiding mechanism, while a deep reinforcement learning algorithm generatessupplementary residual strate gies. This combination enables the RL agent to perform safe and efficientoverta king in complex traffic scenarios. Furthermore, we implement a detailed three-st age curriculumlearning strategy that enhances the training process. By progress ively increasing task complexity, thecurriculum strategy effectively guides the exploration of autonomous vehicles and improves the reusabilityof sub-strategi es. The effectiveness of the CR-HRL framework is confirmed through ablation expe riments.Comparative experiments further highlight the superior efficiency and d ecision-making capabilities of ourframework over traditional rule-based and RL baseline methods."
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