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Robotics & Machine Learning Daily News

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    New Machine Learning Research from Shandong University of Science and Technology Outlined [Distribution of Suitable Habitats for Soft Corals (Alcyonacea) Based on Machine Learning]

    56-56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 artific ial intelligence. According to news originating from Qingdao, People's Republic of China, by NewsRx editors, the research stated, "The soft coral order Alcyonac ea is a common coral found in the deep sea and plays a crucial role in the deep- sea ecosystem." Funders for this research include National Natural Science Foundation of China; Mnr Key Laboratory of Eco-environmental Science And Technology, China; Shandong Provincial Natural Science Foundation; Key Research And Development Program of S handong Province; 801 Institute of Hydrogeology And Engineering Geology; Shandon g Institute of Chinese Engineering S&T Strategy For Development. Our news correspondents obtained a quote from the research from Shandong Univers ity of Science and Technology: "This study aims to predict the distribution of A lcyonacea in the western Pacific Ocean using four machine learning-based species distribution models. The performance of these models is also evaluated. The res ults indicate a high consistency among the prediction results of the different m odels. The soft coral order is primarily distributed in the Thousand Islands Bas in, Japan Trench, and Thousand Islands Trench. Water depth and silicate content are identified as important environmental factors influencing the distribution o f Alcyonacea. The RF, Maxent, and XGBoost models demonstrate high accuracies, wi th the RF model exhibiting the highest prediction accuracy."
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    Research from University of Western Ontario in Robotics Provides New Insights (R eal-Time Point Recognition for Seedlings Using Kernel Density Estimators and Pyr amid Histogram of Oriented Gradients)

    57-58页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on robotics are disc ussed in a new report. According to news reporting from London, Canada, by NewsR x journalists, research stated, "This paper introduces a new real-time method ba sed on a combination of kernel density estimators and pyramid histogram of orien ted gradients for identifying a point of interest along the stem of seedlings su itable for stem-stake coupling, also known as the ‘clipping point'." The news correspondents obtained a quote from the research from University of We stern Ontario: "The recognition of a clipping point is a required step for autom ating the stem-stake coupling task, also known as the clipping task, using the r obotic system under development. At present, the completion of this task depends on the expertise of skilled individuals that perform manual clipping. The robot ic stemstake coupling system is designed to emulate human perception (in vision and cognition) for identifying the clipping points and to replicate human motor skills (in dexterity of manipulation) for attaching the clip to the stem at the identified clipping point. The system is expected to clip various types of vege tables, namely peppers, tomatoes, and cucumbers. Our proposed methodology will s erve as a framework for automatic analysis and the understanding of the images o f seedlings for identifying a suitable clipping point."
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    New Robotics Findings Reported from Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV) (Leader-follower Formation Contro l Based On Non-inertial Frames for Non-holonomic Mobile Robots)

    58-59页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Robotics. According to news reporting from Mexico City, Mexico, by NewsRx journa lists, research stated, "A chain formation strategy based on mobile frames for a set of n differential drive mobile robots is presented. Considering two consecu tive robots in the formation, robots Ri and Ri+1." Funders for this research include Conahcyt, Conahcyt. The news correspondents obtained a quote from the research from the Center for R esearch and Advanced Studies of the National Polytechnic Institute (CINVESTAV), "It is intended that robot Ri+1 follows the delayed trajectory, tau units of tim e, of the leader robot Ri. In this way, the follower robot Ri+1 becomes the lead er robot for robot Ri+ 2 in the formation and so on. With this formation policy, the trailing distance between two consecutive robots varies accordingly to the velocity of the Ri leader robot. Mobile frames are located on the body of the ve hicles, in such a way that the position of robot Ri is determined with respect t o the frame located on Ri+1 robot. The strategy relies on the fact that the gene ral leader robot R1 describes any trajectory generated by bounded linear v1(t) a nd angular omega 1(t) velocities. For the remaining vehicles in the string, the strategy considers a desired trajectory for the follower robot Ri+1 obtained by an estimation of the delayed trajectory of the leader robot Ri. This desired est imated trajectory is obtained under the knowledge of the actual and past input v elocities of the Ri robot. To formally prove the convergence of the formation st rategy, the equations describing the time variation of the relative posture betw een any pair of consecutive vehicles in the formation are obtained, and a feedba ck law based on local measurements is proposed to get the convergence of robot R i+1 to the delayed trajectory, tau units of time, of the trajectory previously d escribed by robot Ri. Lyapunov techniques are considered for this fact."
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    Chongqing University Reports Findings in Machine Learning (Exploring novel lead scaffolds for SGLT2 inhibitors: Insights from machine learning and molecular dyn amics simulations)

    59-60页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting out of Chongqing, People's Republic of C hina, by NewsRx editors, research stated, "Sodium-glucose cotransporter 2 (SGLT2 ) plays a pivotal role in mediating glucose reabsorption within the renal filtra te, representing a well-known target in type 2 diabetes and heart failure. Recen t emphasis has been directed toward designing SGLT2 inhibitors, with C-glycoside inhibitors emerging as front-runners." Our news journalists obtained a quote from the research from Chongqing Universit y, "The architecture of SGLT2 has been successfully resolved using cryo-electron microscopy. However, comprehension of the pharmacophores within the binding sit e of SGLT2 remains unclear. Here, we use machine learning and molecular dynamics simulations on SGLT2 bound with its inhibitors in preclinical or clinical devel opment to shed light on this issue. Our dataset comprises 1240 SGLT2 inhibitors amalgamated from diverse sources, forming the basis for constructing machine lea rning models. SHapley Additive exPlanation (SHAP) elucidates the crucial fragmen ts that contribute to inhibitor activity, specifically Morgan_3, 16 2, 310, 325, 366, 470, 597, 714, 926, and 975. Furthermore, the computed binding free energies and per- residue contributions for SGLT2-inhibitor complexes unvei l crucial fragments of inhibitors that interact with residues Asn-75, His-80, Va l-95, Phe-98, Val-157, Leu-274, and Phe-453 in the binding site of SGLT2."
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    Recent Findings in Robotics Described by Researchers from Hefei University of Te chnology (Climbing Robot Based On Triangle Wheels Obstacle Crossing Design: Mode ling Simulation and Motion Analysis)

    60-61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 Robotics have been published. According to news originating from Hefei, People's Republic of China, by NewsRx correspondents, research stated, "Intelligent overhead distribu tion line work must be realized to solve the problem of line operation and maint enance. Routine manual detection has serious hidden safety issues in the distrib ution network of overhead transmission line maintenance and maintenance work." Financial support for this research came from This work is supported by the Scie nce and Technology Project of Anhui Electric Research Institute of State Grid Co rporation of China (Grant No. 52120520005B) and the National Natural Science Fou ndation of China (Grant No. 51975174 and No. 51975005)..
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    Reports from Anhui Agricultural University Describe Recent Advances in Robotics (Path Planning and Motion Control Method for Sick and Dead Animal Transport Robo ts Integrating Improved A * Algorithm and Fuzzy PID)

    61-63页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in robotics. A ccording to news reporting from Hefei, People's Republic of China, by NewsRx jou rnalists, research stated, "[Objective]A k ey challenge for the harmless treatment center of sick and dead animal is to pre vent secondary environmental pollution, especially during the process of transpo rting the animals from cold storage to intelligent treatment facilities. In orde r to solve this problem and achieve the intelligent equipment process of transpo rting sick and dead animal from storage cold storage to harmless treatment equip ment in the harmless treatment center, it is necessary to conduct in-depth resea rch on the key technical problems of path planning and autonomous walking of tra nsport robots.[Methods]A * algorithm is ma inly adopted for the robot path planning algorithm for indoor environments, but traditional A * algorithms have some problems, such as having many inflection po ints, poor smoothness, long calculation time, and many traversal nodes. In order to solve these problems, a path planning method for the harmless treatment of d iseased and dead animal using transport robots based on the improved A algorithm was constructed, as well as a motion control method based on fuzzy proportional integral differential (PID)."
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    Fudan University Reports Findings in Heart Disease (Comparison of machine learni ng-based CT fractional flow reserve with cardiac MR perfusion mapping for ischem ia diagnosis in stable coronary artery disease)

    63-64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 Heart Disorders and Di seases-Heart Disease is the subject of a report. According to news reporting f rom Shanghai, People's Republic of China, by NewsRx journalists, research stated, "To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resona nce (MR) perfusion mapping for functional assessment of coronary stenosis. Betwe en October 2020 and March 2022, consecutive participants with stable coronary ar tery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardi ac MR, and invasive fractional flow reserve (FFR) within 2 weeks." The news correspondents obtained a quote from the research from Fudan University, "Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenos is was defined as FFR 0.8 or > 90% stenosi s on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodyn amically significant stenosis was detected in 36 (33%). Among the q uantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant s tenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0. 89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperf ormed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with im proved specificity (95% vs 82%, p = 0.01) and accurac y (95% vs 81%, p<0.01). ML-base d CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantit ative perfusion mapping had a favorable performance in per-patient analysis."
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    Centre for Data Science Reports Findings in Atrial Fibrillation (Optimizing warf arin dosing for patients with atrial fibrillation using machine learning)

    64-65页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Heart Disorders and Diseases-At rial Fibrillation is the subject of a report. According to news reporting origin ating from Hamilton, Canada, by NewsRx correspondents, research stated, "While n ovel oral anticoagulants are increasingly used to reduce risk of stroke in patie nts with atrial fibrillation, vitamin K antagonists such as warfarin continue to be used extensively for stroke prevention across the world. While effective in reducing the risk of strokes, the complex pharmacodynamics of warfarin make it d ifficult to use clinically, with many patients experiencing under- and/or over- anticoagulation." Financial support for this research came from Core operating budget of the Cente r for Data Science and Digital Health at Hamilton Health Sciences.
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    Second Affiliated Hospital Reports Findings in Personalized Medicine (Machine le arning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy)

    65-66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 Drugs and Therapies-Personalized Medicine is the subject of a report. According to news reporting ou t of Shanghai, People's Republic of China, by NewsRx editors, research stated, " Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments." Our news journalists obtained a quote from the research from Second Affiliated H ospital, "Programmed cell death (PCD) pathways play a pivotal role in the develo pment and progression of various cancers, offering potential as prognostic indic ators and drug sensitivity markers for LUAD patients. The development and valida tion of predictive models were conducted by integrating 13 PCD patterns with com prehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizi ng the machine learning algorithms, we identified ten critical differentially ex pressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP 1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a progra mmed cell death index (PCDI) based on these genes across the aforementioned coho rts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation betwee n the PCDI and immune features in LUAD, including immune cell infiltration and t he expression of immune checkpoint molecules. Additionally, we found that patien ts with a high PCDI score may exhibit resistance to immunotherapy and standard a djuvant chemotherapy regimens; however, they may benefit from other FDA-supporte d drugs such as docetaxel and dasatinib."
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    Study Findings from Lulea University of Technology Provide New Insights into Rob otics (A Comparative Field Study of Global Pose Estimation Algorithms In Subterr anean Environments)

    66-67页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on Robotics is now available. Accordi ng to news reporting originating in Lulea, Sweden, by NewsRx journalists, resear ch stated, "In this article, we perform a novel and extended field evaluation of the state-of-the-art algorithmic frameworks' performance on global pose estimat ion. More specifically, we focus on relocalizing a mobile robot in a pre-built 3 D point cloud map of a large subterranean environment." Financial support for this research came from European Union (EU). The news reporters obtained a quote from the research from the Lulea University of Technology, "The evaluation is divided into two parts. The first part consist s of multiple simulations performed in two different Gazebo SubT worlds, where o ne is flat with various types of features, while another has uneven structure an d is more textured. The second part is an experimental evaluation and takes plac e in a real-world underground tunnel. In all evaluation tests, the robot's pose is selected in such a way that we can test the robustness, as well as the featur e extraction capability, of each algorithm. The evaluation is carried out using three ROS packages: a) hdl_global_localization using b oth BBS and FPFH+RANSAC, b) LIO-SAM_based_relocalizati on, and c) Fast-LIO-Localization."
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