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    Research on Robotics Described by Researchers at Instituto de Ciencias del Mar ( New Technologies for Monitoring and Upscaling Marine Ecosystem Restoration in De ep-Sea Environments)

    94-94页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ro botics. According to news originating from Barcelona, Spain, by NewsRx correspon dents, research stated, “The United Nations (UN)’s call for a decade of ‘ecosyst em restoration’ was prompted by the need to address the extensive impact of anth ropogenic activities on natural ecosystems.” The news reporters obtained a quote from the research from Instituto de Ciencias del Mar: “Marine ecosystem restoration is increasingly necessary due to increas ing habitat degredation in deep waters (> 200 m depth). A t these depths, which are far beyond those accessible by divers, only establishe d and emerging robotic platforms such as remotely operated vehicles (ROVs), auto nomous underwater vehicles (AUVs), landers, and crawlers can operate through man ipulators and multiparametric sensor arrays (e.g., optoacoustic imaging, omics, and environmental probes). The use of advanced technologies for deep-sea ecosyst em restoration can provide: high-resolution three-dimensional (3D) imaging and a coustic mapping of substrates and key taxa, physical manipulation of substrates and key taxa, real-time supervision of remote operations and long-term ecologica l monitoring, and the potential to work autonomously. Here, we describe how robo tic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across larg e spatial scales.”
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    New Findings on Robotics Described by Investigators at Harbin Institute of Techn ology (Optimal Measurement Poses Using Lssa for Robot Kinematics-flexibility Cal ibration)

    95-95页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Robotics have been publi shed. According to news originating from Heilongjiang, People’s Republic of Chin a, by NewsRx correspondents, research stated, “The absolute positioning of robot s is a primary factor limiting their applications. In order to enhance the effic iency and precision of robot calibration, this study introduces a method that ut ilizes the Levy flight and Sparrow Search Algorithm (LSSA) to optimize the measu rement pose of the robot, reducing the number of measurement poses and improving calibration accuracy.” Financial support for this research came from National Key Research and Developm ent Program of China.
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    Beijing Normal University Reports Findings in Machine Learning (Differentiating Microplastics from Natural Particles in Aqueous Suspensions Using Flow Cytometry with Machine Learning)

    96-96页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Beijing, People’s Republ ic of China, by NewsRx journalists, research stated, “Microplastics (MPs) in nat ural waters are heterogeneously mixed with other natural particles including alg al cells and suspended sediments. An easy-to-use and rapid method for directly m easuring and distinguishing MPs from other naturally present colloids in the env ironment would expedite analytical workflows.” The news correspondents obtained a quote from the research from Beijing Normal U niversity, “Here, we established a database of MP scattering and fluorescence pr operties, either alone or in mixtures with natural particles, by stain-free flow cytometry. The resulting high-dimensional data were analyzed using machine lear ning approaches, either unsupervised (e.g., viSNE) or supervised (e.g., random f orest algorithms). We assessed our approach in identifying and quantifying model MPs of diverse sizes, morphologies, and polymer compositions in various suspens ions including phototrophic microorganisms, suspended biofilms, mineral particle s, and sediment. We could precisely quantify MPs in microbial phototrophs and na tural sediments with high organic carbon by both machine learning models (identi fication accuracies over 93 %), although it was not possible to dist inguish between different MP sizes or polymer compositions. By testing the resul ting method in environmental samples through spiking MPs into freshwater samples , we further highlight the applicability of the method to be used as a rapid scr eening tool for MPs.”
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    University of Evry Researcher Highlights Recent Research in Androids (Design and Validation of New Methodology for Hydraulic Passage Integration in Carbon Compo site Mechanisms)

    97-97页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New study results on androids have been published . According to news reporting from Evry, France, by NewsRx journalists, research stated, “Humanoid robots have rapidly become the focus of research in recent ye ars, with the most impressive humanoids being hydraulically actuated. This is du e to the capacity of hydraulic actuation to provide simultaneous high forces wit h dynamic motion.” Our news reporters obtained a quote from the research from University of Evry: “ The scarcity of hydraulic robots is mainly due to the difficulty in managing hyd raulic pipes. These decrease the robot’s social acceptance and safety and are th e main source of leaks. Recently, there has been a new trend in hydraulically ac tuated robots that involves creating internal oil passages within the robotic pa rts to eliminate the need for external flexible tubes. Developing these parts us ing carbon composite materials provides an additional advantage of ensuring ligh tweight yet robust robotic parts. However, assembling hydraulically integrated p arts is challenging due to the leakproof requirement and the high pressures invo lved. This article proposes a new, reliable, and effective method that ensures a strong, leakproof assembly. A mathematical model with 11 parameters describing the assembly zone and accounting for geometric parameters, material characterist ic parameters, and porosity has been developed.”
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    Researcher at Sichuan University Targets Machine Learning (State of Health Estim ation for Lithium-Ion Batteries with Deep Learning Approach and Direct Current I nternal Resistance)

    98-98页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Chengdu, Peopl e’s Republic of China, by NewsRx editors, research stated, “Battery state of hea lth (SOH), which is a crucial parameter of the battery management system, reflec ts the rate of performance degradation and the aging level of lithium-ion batter ies (LIBs) during operation.” Our news reporters obtained a quote from the research from Sichuan University: “ However, traditional machine learning models face challenges in accurately diagn osing battery SOH in complex application scenarios. Hence, we developed a deep l earning framework for battery SOH estimation without prior knowledge of the degr adation in battery capacity. Our framework incorporates a series of deep neural networks (DNNs) that utilize the direct current internal resistance (DCIR) featu re to estimate the SOH. The correlation of the DCIR feature with the fade in cap acity is quantified as strong under various conditions using Pearson correlation coefficients. We utilize the K-fold cross-validation method to select the hyper parameters in the DNN models and the optimal hyperparameter conditions compared with machine learning models with significant advantages and reliable prediction accuracies.”
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    University of Pisa Reports Findings in Hernias (Internal hernia through the Trei tz fossa after robotic pancreatoduodenectomy: pathogenesis and preventive measur es)

    98-99页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Gastroenterology - Her nias is the subject of a report. According to news reporting originating in Pisa , Italy, by NewsRx journalists, research stated, “Internal hernia through the Tr eitz fossa following robotic pancreatoduodenectomy is a rare but potentially ser ious complication.In our review of 328 cases of robotic pancreatoduodenectomies , two patients (0.6%) required repeat surgery due to internal herni ation of the entire small bowel through the Treitz fossa.” The news reporters obtained a quote from the research from the University of Pis a, “This complication can present as afferent loop syndrome, with symptoms inclu ding nausea, vomiting, and abdominal distension, possibly leading to cholangitis and pancreatitis. Timely diagnosis and intervention are paramount, as conservat ive management often fails. Preventive measures involve closing the peritoneal d efect in the Treitz fossa at the end of robotic pancreatoduodenectomy, particula rly in lean patients with thin mesentery who are at increased risk of internal h ernia due to increased mobility of the small bowel.”
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    Reports on Machine Learning Findings from University of Toronto Provide New Insi ghts (Machine Learning Assisted Design of Bcc High Entropy Alloys for Room Tempe rature Hydrogen Storage)

    99-100页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on Machine Learning is now available. According to news originating from Toronto, Canada, by NewsRx correspondents, r esearch stated, “Body-centered cubic (BCC) alloy systems can theoretically store double amounts of hydrogen compared with commercial metal hydrides at room temp erature, and BCC high entropy alloys (HEAs) have shown the potential to reach th is theoretic limit.” Financial support for this research came from University of Toronto. Our news journalists obtained a quote from the research from the University of T oronto, “However, the high thermodynamic stability of the dihydrides formed duri ng hydrogen storage results in high operating temperatures. Here, by employing m ulti-objective Bayesian optimization-aided density functional theory calculation s, we discovered 8 new HEA candidates for hydrogen storage, including the VNbCrM oMn HEA that can store 2.83 wt% hydrogen at room temperature and a tmospheric pressure, vastly exceeding the hydrogen capacities of 1.38 wt% and 1.91 wt% for commercial LaNi5H6 and TiFeH2.”
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    New Findings on Machine Learning from Imperial College London Summarized (Ensemb le Kalman Filter for Gan-convlstm Based Long Lead-time Forecasting)

    100-101页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from London, Un ited Kingdom, by NewsRx correspondents, research stated, “Datadriven machine le arning techniques have been increasingly utilized for accelerating nonlinear dyn amic system prediction. However, machine learning-based models for long lead-tim e forecasts remain a significant challenge due to the accumulation of uncertaint y along the time dimension in online deployment.” Financial supporters for this research include China Scholarship Council, Engine ering & Physical Sciences Research Council (EPSRC), Imperial Colle ge ICT service.
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    Guangxi University of Science and Technology Reports Findings in Disease-Free Su rvival (Efficacy and safety of robotic radical hysterectomy in cervical cancer c ompared with laparoscopic radical hysterectomy: a meta-analysis)

    101-102页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Epidemiology - Disease -Free Survival is the subject of a report. According to news reporting out of Gu angxi, People’s Republic of China, by NewsRx editors, research stated, “Robotic radical hysterectomy (RRH) is a newly developed minimally invasive surgery that has been suggested as a substitute for laparoscopic radical hysterectomy (LRH). This meta-analysis aims to assess the clinical efficacy and safety of robot-assi sted radical hysterectomy (RRH) for cervical cancer.” Our news journalists obtained a quote from the research from the Guangxi Univers ity of Science and Technology, “A systematic search was conducted in four databa ses (Medline, Embase, Web of Science, and CENTRAL) for studies comparing the uti lization of RRH and LRH in the treatment of cervical cancer. The search included articles published from the inception of the databases up until July 18, 2023. Meta-analyses were conducted to assess several surgical outcomes, including oper ation time, estimated blood loss, length of hospital stay, pelvic lymph nodes, p ositive surgical margin, total complications, one-year recurrence rate, one-year mortality, and one-year disease-free survival rate. Six studies were included f or meta-analysis. In total, 234 patients were in the RRH group and 174 patients were in the LRH group. RRH had significantly longer operative time (MD=14.23,95% CI:5.27 23.20, P=0.002),shorter hospital stay (MD= -1.10,95% CI:-1 .43 0.76, P<0.00001),more dissected pelvic lymph nodes(MD=0 .89,95%CI:0.18 1.60, P =0.01) and less blood loss(WMD = -27.78,95% CI:-58.69 -3.14, P=0.08, I 80%) compared with LRH. No significant difference was observed between two groups regarding positive surgical margin ( OR = 0.59, 95% CI 0.18 2.76, P=0.61), over complications (OR = 0.7 7, 95% CI, 0.46-1.28, P=0.31), one-year recurrence rate (OR = 0.19 , 95% CI 0.03-1.15, P=0.13), one-year mortality rate (OR = 0.19, 9 5% CI 0.03-1.15, P=0.07) and disease-free survival at one year (OR = 1.92, 95% CI 0.32-11.50, P=0.48). RRH is an increasingly popula r surgical method known for its high level of security and efficiency. It has ma ny benefits in comparison to LRH, such as decreased blood loss, a higher quantit y of dissected pelvic lymph nodes, and a shorter duration of hospitalization.”
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    Studies in the Area of Robotics Reported from Guangdong University of Technology (Bicr-slam: a Multi-source Fusion Slam System for Biped Climbing Robots In Trus s Environments)

    102-103页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Robotic s. According to news reporting originating in Guangzhou, People’s Republic of Ch ina, by NewsRx journalists, research stated, “The low -texture, shape -similar, interconnected and mutual -occlusion nature of truss members poses challenges fo r simultaneous localization and mapping of biped climbing robots in truss enviro nments. In this paper, we propose BiCRSLAM, a multi -source fusion SLAM system, to estimate both the distinctive state of the robot and a parametric representa tion of the truss, going beyond traditional point cloud mapping.” Financial supporters for this research include Guangdong Basic and Applied Basic Research Fund, China, Research and Development Programs in Key Areas of Guangdo ng Province, China, Foshan Science and Technology Innovation Team Project, China .
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