Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Manag...Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Management System (NLIMS) for Kenya partnered with the Dedan Kimathi University of Technology on a project to develop a pilot LIMS for Nyeri County. A pilot Land Administration System (LAS) has been developed in this work and utilizes an Africanized Land Administration Domain Model (A-LADM) fitted to the Kenyan context. Various processes involved in land administration that required to be automated were identified. Informed by the numbers of applications made for the change of User service, it was picked as the first workflow to be automated. The key outputs of this work were the A-LADM and pilot LAS. The pilot solution uses a webcentric solution, with the data stored and managed centrally from a PostGIS database backend, using the Python Django framework to implement the server side and client side frontend. This solution demonstrates the importance of automating processes and supporting standards based software development. Stakeholder participation is key when implementing systems and 2 workshops are held to capture requirements and validate the developed solution.展开更多
Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workf...Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workflows,machine learning(ML)tech-niques,and robotic experiments have elevated sci-entific research to unprecedented levels.We have explored the iterative theoretical-experimental par-adigm,leveraged by robotic artificial intelligence(AI)chemists to bridge the gap between high-volume theoretical data and high-dimensional exper-imental data in this review.By combining automated high-throughput computations,ML models,and ro-botic large-scale experiments,this novel protocol aimed to accelerate data-driven chemistry innova-tion and materials discovery.Successful applications achieved by this paradigm include nanomaterials,high-entropy alloy catalysts,optical thin films,and oxygen evolution reaction(OER)catalysts from Martian meteorites.We have highlighted the potential for this paradigmatic evolution to redefine research methodologies and promote the next generation of precise and intelligent chemistry innovation.展开更多
文摘Kenya has amassed a wealth of paper based land information records collected over the duration of more than a century. The National Land Commission (NLC) having the mandate to develop a National Land Information Management System (NLIMS) for Kenya partnered with the Dedan Kimathi University of Technology on a project to develop a pilot LIMS for Nyeri County. A pilot Land Administration System (LAS) has been developed in this work and utilizes an Africanized Land Administration Domain Model (A-LADM) fitted to the Kenyan context. Various processes involved in land administration that required to be automated were identified. Informed by the numbers of applications made for the change of User service, it was picked as the first workflow to be automated. The key outputs of this work were the A-LADM and pilot LAS. The pilot solution uses a webcentric solution, with the data stored and managed centrally from a PostGIS database backend, using the Python Django framework to implement the server side and client side frontend. This solution demonstrates the importance of automating processes and supporting standards based software development. Stakeholder participation is key when implementing systems and 2 workshops are held to capture requirements and validate the developed solution.
基金the Innovation Program for Quantum Science and Technology,Chinese Academy of Sciences(CASgrant no.2021ZD0303303)+3 种基金the CAS Project for Young Scientists in Basic Research(grant no.YSBR-005)the National Natural Science Foundation of China(NSFCgrant nos.22025304 and 22033007)K.C.Wong Education Foundation,China(grant no.GJTD-2020-15).
文摘Chemistry and material innovation is undergoing a transformative shift with the integration of advanced computational and experimental technologies over the past few decades.More recently,the advent of automated workflows,machine learning(ML)tech-niques,and robotic experiments have elevated sci-entific research to unprecedented levels.We have explored the iterative theoretical-experimental par-adigm,leveraged by robotic artificial intelligence(AI)chemists to bridge the gap between high-volume theoretical data and high-dimensional exper-imental data in this review.By combining automated high-throughput computations,ML models,and ro-botic large-scale experiments,this novel protocol aimed to accelerate data-driven chemistry innova-tion and materials discovery.Successful applications achieved by this paradigm include nanomaterials,high-entropy alloy catalysts,optical thin films,and oxygen evolution reaction(OER)catalysts from Martian meteorites.We have highlighted the potential for this paradigmatic evolution to redefine research methodologies and promote the next generation of precise and intelligent chemistry innovation.
