查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting originating from Shanghai,People's R epublic of China,by NewsRx correspondents,research stated,"Deformable liquid crystal polymers (LCPs) driven by more than one external stimulus have received extensive attention in fields ranging from multifunctional soft robots to bionic actuators. Combining responsive liquid crystal with nonmesogenic responsive gro ups within polymer offers a versatile way to obtain multiresponsive LCPs." Our news editors obtained a quote from the research from Fudan University,"Howe ver,the incorporation of nonmesogenic responsive groups causes interruption in the assembly of mesogens and brings a challenge to the alignment of LCPs. Herein ,a new method is put forward to facilitate uniform mesogen alignment by exertin g water vapor in the film preparation process. Using this method,vapor-assisted alignment,the homeotropic alignment of azobenzene mesogens is achieved in a co polymer containing nonmesogenic poly(ethylene glycol) (PEG). The obtained copoly mer films present photodeformation brought by azobenzene isomerization and humid ity-responsive deformation resulting from the asymmetric swelling of film surfac es. The dual-responsive smart ‘blinds' and bionic flower actuators are fabricate d to demonstrate the integration of the two different stimuli."
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 Machine Learning. According to news reporting originating from Gdansk,Poland,b y NewsRx correspondents,research stated,"This article introduces an innovative method for achieving low-cost and reliable multiobjective optimization (MOO) of microwave passive circuits. The technique capitalizes on the attributes of surr ogate models,specifically artificial neural networks (ANNs),and multiresolutio n electromagnetic (EM) analysis." Financial support for this research came from Icelandic Center for Research (RAN NIS). Our news editors obtained a quote from the research from the Gdansk University o f Technology,"We integrate the search process into a machine learning (ML) fram ework,where each iteration produces multiple infill points selected from the pr esent representation of the Pareto set. This collection is formed by optimizing the ANN metamodel by means of a multiobjective evolutionary algorithm (MOEA). Th e procedure concludes upon convergence,defined as a significant similarity betw een the sets of nondominated solutions acquired through consecutive iterations. Performing the majority of iterations at the low-fidelity EM simulation level en ables additional computational savings. Our methodology has been showcased using two microstrip circuits."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Artificial Intelligence is the su bject of a report. According to news reporting originating from Bari,Italy,by NewsRx correspondents,research stated,"Steatotic liver disease is the most fre quent chronic liver disease worldwide. Ultrasonography (US) is commonly employed for the assessment and diagnosis." Our news editors obtained a quote from the research from the University of Bari Aldo Moro,"Few information is available on the possible use of artificial intel ligence (AI) to ameliorate the diagnostic accuracy of ultrasonography. An AI-bas ed algorithm was developed using a dataset of US images. We prospectively enroll ed 134 patients for algorithm validation. Patients underwent abdominal US and Pr oton Density Fat Fraction MRI scans (MRI-PDFF),assumed as reference technique. The hepatorenal index was manually calculated (HRIM) by 4 operators. An automati c hepatorenal index (HRIA) was obtained by the algorithm. The accuracy of HRIA t o discriminate steatosis grades was evaluated by ROC analysis using MRI-PDFF cut -offs. Overweight was 40 % of subjects (BMI 26.4 kg/cm). The media n HRIA was 1.11 (IQR 0.32) and the average of 4 manually calculated HRIM was 1.0 8 (IQR 0.26),with a 15 % inter-operator variability. Both HRIA (R = 0.79,P<0.0001) and HRIM (R = 0.69,P<0.0001) significantly correlated with liver fat percentage (MRI-PDFF). Accordin g to MRI-PDFF,32 % of enrolled subjects had steatosis. Discrimina tion capacity by AUC between patient with steatosis and patient without steatosi s was better for HRIA than HRIM (AUC: 0.87 vs. 0.82,respectively). ROC analysis showed an AUC = 0.98 for HRIA with 1.64 cut-off in distinguishing between mild and moderate/severe groups. The use of AI improves accuracy and speed of ultraso nography in the diagnosis of liver steatosis."
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 or iginating in Milan,Italy,by NewsRx journalists,research stated,"The introduc tion of artificial intelligence (AI) represents an actual revolution in the radi ological field,including bone lesion imaging. Bone lesions are often detected b oth in healthy and oncological patients and the differential diagnosis can be ch allenging but decisive,because it affects the diagnostic and therapeutic proces s,especially in case of metastases." The news reporters obtained a quote from the research from Universita degli Stud i di Milano,"Several studies have already demonstrated how the integration of A I-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection,increasing the diagnostic accuracy and reducing the overd iagnosis and the number of unnecessary deeper investigations. In addition,radio mics and radiogenomics approaches could go beyond the qualitative features,visi ble to the human eyes,extrapolating cancer genomic and behavior information fro m imaging,in order to plan a targeted and personalized treatment."
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 Artificial Intelligence. According to news reporting originating in St. Petersbu rg,Florida,by NewsRx journalists,research stated,"Harmful algal blooms (HABs ) of the toxic dinoflagellate Karenia brevis (K. brevis) occur annually on the W est Florida Shelf (WFS). Detection of these blooms using satellite observations often suffers from two problems: lack of accurate algorithms to identify phytopl ankton blooms in optically complex waters and patchiness (i.e.,heterogeneity) o f K. brevis during blooms." The news reporters obtained a quote from the research from the University of Sou thern Florida,"Here,using data collected by the Visible Infrared Imaging Radio meter Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) betw een 2017 and 2019,we develop a practical approach to overcome these difficultie s despite the lack of a chlorophyll-a fluorescence band on VIIRS. The approach i s based on artificial intelligence (specifically,a deep-learning (DL) convoluti onal neural network model),which uses spatial coherence of bloom patches to acc ount for the patchiness of K. brevis concentrations. After proper training,the overall performance (i.e.,F1 score) of the deep learning model is 89% . Extracted K. brevis patches were consistent with those derived from the Modera te Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite,which has a fluorescence band. Furthermore,the wider swath of VIIRS over MODIS (3040-km versus 2330-km) led to more valid observations of bloom extent,enabling improve d near-realtime applications."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Oncology - Endometrial Cancer is the subject of a report. According to news reporting from Beijing,People's Repu blic of China,by NewsRx journalists,research stated,"Endometrial cancer (EC),the second most common malignancy in the female reproductive system,has garner ed increasing attention for its genomic heterogeneity,but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in E C through a comprehensive multi-omics analysis (RNAseq datasets from The Cancer Genome Atlas [TCGA],Cancer Cell Line Enc yclopedia [CCLE],and GEO datasets; the Cl inical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy." The news correspondents obtained a quote from the research from China-Japan Frie ndship Hospital,"Unsupervised consensus clustering was performed to categorize EC patients into three metabolismpathway- based subgroups (MPSs). These MPS subg roups had distinct clinical prognoses,transcriptomic and genomic alterations,i mmune microenvironment landscape,and unique patterns of chemotherapy sensitivit y. Moreover,the MPS2 subgroup had a better response to immunotherapy. Finally,three machine learning algorithms (LASSO,random forest,and stepwise multivaria te Cox regression) were used for developing a prognostic metagene signature base d on metabolic molecules. Thus,a 13-hub gene-based classifier was constructed t o predict patients' MPS subtypes,offering a more accessible and practical appro ach."
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 Machine Learning. According to news reporting originating from Perugia,Italy,by NewsR x correspondents,research stated,"In this study we define a comprehensive meth od for analyzing electrochemical impedance spectra of lithium batteries using eq uivalent circuit models,and for information extraction on state -of -charge and state -of -health from impedance data by means of machine learning methods. Est imation of circuit parameters typically implies a non -linear optimization probl em." Financial supporters for this research include European Union-Next Generation EU ,Mission Innovation program of Ministry of Environment and Energy Security (MAS E,ex-MITE) via the IEMAP project. Our news editors obtained a quote from the research from the University of Perug ia,"A detailed method for estimating initial values of the optimization algorit hm is described,emphasizing short computation times and efficient convergence t o global minimum. Parameters identifiability is investigated through an analysis of the injectivity of the model,Cramer-Rao lower bound,profile likelihood,an d sensitivity analysis. An exploratory data analysis is presented to estimate th e degree of correlation between impedance spectra (or circuit parameters) and ba ttery state -of -charge or state -of -health,prior to the implementation of any machine learning algorithm. A publicly available dataset of impedance spectra o f five lithium-polymer batteries is used to test the whole procedure."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting out of Harbin,People's Republic of China,by NewsRx editors,research stated,"The visual perception of landscape spaces between residences in cold regions is important for public hea lth." Financial supporters for this research include National Natural Science Foundati on of China. Our news correspondents obtained a quote from the research from Harbin Institute of Technology: "To compensate for the existing research ignoring the cold snow season's influence,this study selected two types of outdoor landscape space env ironments in non-snow and snow seasons as research objects. An eye tracker combi ned with a semantic differential (SD) questionnaire was used to verify the feasi bility of the application of virtual reality technology,screen out the gaze cha racteristics in the landscape space,and reveal the design factors related to la ndscape visual perception. In the snow season,the spatial aspect ratio (SAR),b uilding elevation saturation (BS),and grass proportion in the field of view (GP ) showed strong correlations with the landscape visual perception scores (W). In the non-snow season,in addition to the above three factors,the roof height di fference (RHD),tall-tree height (TTH),and hue contrast (HC) also markedly infl uenced W. The effects of factors on W were revealed in immersive virtual environ ment (IVE) orthogonal experiments,and the genetic algorithm (GA) and k-nearest neighbor algorithm (KNN) were combined to optimize the environmental factors."
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 Evolvable Hardware. According to news reporting out of Manipal,India,by NewsRx editors,research stated,"Trading off performance metrics in control design fo r position tracking is unavoidable. This has severe consequences in mission-crit ical systems such as quadcopter applications." Our news journalists obtained a quote from the research from the Manipal Academy of Higher Education,"The controller area and propulsion energy are conflicting design parameters,whereas the reliability and tracking speed are related metri cs to be optimized. In this research,a switching-based position controller was co-simulated with the quadcopter model. Performance analysis of the Field Progra mmable Gate Array (FPGA)-based controller validates a better scheme for tracking speed,propulsion energy,and reliability optimization under similar error perf ormance. To improve the computation power and controller area,the dynamic parti al reconfiguration(DPR) approach has been adapted and implemented on FPGA using the Vivado Integrated Development Environment (IDE),where a ranking-based appro ach brings into action either proportional derivative,sliding mode,or model pr edictive controllers for each dimension of position tracking. It is verified by analyzing the cumulative tracking speed,reliability,controller area,and propu lsion energy metrics that the proposed controller can optimize all these metrics within three successive iterations of tracking either in the same direction or in any combination of directions."
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 originating in Pittsburgh,Pe nnsylvania,by NewsRx journalists,research stated,"This work proposes an auton omous multi-robot exploration pipeline that coordinates the behaviors of robots in an indoor environment composed of multiple rooms. Contrary to simple frontier -based exploration approaches,we aim to enable robots to methodically explore a nd observe an unknown set of rooms in a structured building,keeping track of wh ich rooms are already explored and sharing this information among robots to coor dinate their behaviors in a distributed manner." Financial support for this research came from Defence Science and Technology Age ncy.
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