查看更多>>摘要：Fresh data on artificial intelligence are presented in a new report. According to news originating from College Station, Texas, by NewsRx editors, the research stated, “Automated fault detection and diagnostics analysis in commercial building systems using machine learning (ML) can improve the building’s efficiency and conserve energy costs from inefficient equipment operation.” Financial supporters for this research include Texas A&M University’s Tees Energy Systems Lab. Our news editors obtained a quote from the research from Energy Systems Laboratory: “However, ML can be challenging to implement in existing systems due to a lack of common data standards and because of a lack of building operators trained in ML techniques. Additionally, results from ML procedures can be complicated for untrained users to interpret. Boolean rule-based analysis is standard in current automated fault detection and diagnostics (AFDD) solutions but limits analysis to the rules defined and calibrated by energy engineers. Boolean rule-based analysis and ML can be combined to create an effective fault detection and diagnostics (FDD) tool. Three examples of ML’s advantages over rule-based analysis are explored by analyzing functional building equipment. ML can detect long-term faults in the system caused by a lack of system maintenance.”
查看更多>>摘要：Current study results on Rare Diseases and Conditions have been published. According to news reporting originating from Portland, Oregon, by NewsRx correspondents, research stated, “Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa decarboxylase gene. Deficiency of the AADC enzyme results in combined severe reductions in monoamine neurotransmitters: dopamine, serotonin, epinephrine, and norepinephrine.” Financial support for this research came from PTC Therapeutics, South Plain-field, New Jersey, USA. Our news editors obtained a quote from the research from Oregon Health & Science University (OHSU), “This leads to widespread neurological complications affecting motor, behavioral, and autonomic function. The goal of this study was to use EHR data to identify previously undiagnosed patients who may have AADCd without available training cases for the disease. A multiple symptom and related disease annotated dataset was created and used to train individual concept classifiers on annotated sentence data. A multistep algorithm was then used to combine concept predictions into a single patient rank value. Using an 8000- patient dataset that the algorithms had not seen before ranking, the top and bottom 200 ranked patients were manually reviewed for clinical indications of performing an AADCd diagnostic screening test. The top-ranked patients were 22.5% positively assessed for diagnostic screening, with 0% for the bottom-ranked patients. This result is statistically significant at P＜.0001.”
查看更多>>摘要：Researchers detail new data in Machine Learning. According to news reporting from Wuhan, People’s Republic of China, by NewsRx journalists, research stated, “The determination of fundamental rock mechanical properties, uniaxial compression strength (UCS) and elastic modulus (E), constitutes a pivotal facet of rock engineering design. However, deriving these properties directly from standard laboratory tests on rock core samples can be challenging, especially when dealing with deep highstress rock formations and weak fractured strata.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Innovation Group Project of Hubei Provincial Natural Science Foundation, Fundamental Research Funds for the Central Universities.
查看更多>>摘要：Data detailed on pattern recognition and artificial intelligence have been presented. According to news originating from Zhenjiang, People’s Republic of China, by NewsRx editors, the research stated, “Aimed at the problems of complex industrial site environment, difficult identification of assembly features and low positioning accuracy, a new visual identification and positioning method is proposed, which can well identify and locate parts and products with different characteristics.” Funders for this research include The Jiangsu Province Key Laboratory of Advanced Manufacturing And Process of Marine Machinery Development.
查看更多>>摘要：New research on Oncology - Pancreatic Cancer is the subject of a report. According to news reporting from Tianjin, People’s Republic of China, by NewsRx journalists, research stated, “Pancreatic cancer (PC) has the poorest prognosis compared to other common cancers because of its aggressive nature, late detection, and resistance to systemic treatment. In this study, we aimed to identify novel biomarkers for PC patients and further explored their function in PC progression.” The news correspondents obtained a quote from the research from Tianjin Fourth Central Hospital, “We analyzed GSE62452 and GSE28735 datasets, identifying 35 differentially expressed genes (DEGs) between PC specimens and non-tumors. Based on 35 DEGs, we performed machine learning and identified eight diagnostic genes involved in PC progression. Then, we further screened three critical genes (CTSE, LAMC2 and SLC6A14) using three GEO datasets. A new diagnostic model was developed based on them and showed a strong predictive ability in screen PC specimens from non-tumor specimens in GEO, TCGA datasets and our cohorts. Then, clinical assays based on TCGA datasets indicated that the expression of LAMC2 and SLC6A14 was associated with advanced clinical stage and poor prognosis. The expressions of LAMC2 and SLC6A14, as well as the abundances of a variety of immune cells, exhibited a significant positive association with one another. Functionally, we confirmed that SLC6A14 was highly expressed in PC and its knockdown suppressed the proliferation, migration, invasion and EMT signal via regulating Wnt/b-catenin signaling pathway. Overall, our findings developed a novel diagnostic model for PC patients. SLC6A14 may promote PC progression via modulating Wnt/b-catenin signaling.”
查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from Madison, Wisconsin, by NewsRx correspondents, research stated, “In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality.” Funders for this research include National Science Foundation; U.S. National Science Foundation Training-based Workforce Development. Our news correspondents obtained a quote from the research from University of Wisconsin Madison: “The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images.”
查看更多>>摘要：Investigators publish new report on computational intelligence. According to news originating from Tokyo, Japan, by NewsRx correspondents, research stated, “This paper proposes a method to generate a synthetic rating matrix based on user’s rational behavior, with the aim of generating a largescale rating matrix at low cost. Collaborative filtering is one of the major techniques for recommender systems, which is widely used because it can recommend items using only a history of ratings given to the items by users.” Financial supporters for this research include Japan Society For The Promotion of Science.
查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting from Singapore, Singapore, by NewsRx journalists, research stated, “For the existing adaptive constrained robotic control algorithms, the demanding “feasibility conditions” on virtual controller is normally inevitable and the extra limits on constraining functions have to be imposed, making the corresponding approaches more demanding and less user friendly in control development. Here, we develop a new neuroadaptive constrained control strategy for uncertain robotic manipulators in the presence of position and velocity constraints.” Financial support for this research came from National University of Singapore. The news correspondents obtained a quote from the research from the National University of Singapore, “First, a novel unified mapping function (UMF) is constructed so that the restriction on constraining boundaries is removed and more kinds of constraining forms can be handled. Second, by integrating the UMF-based coordinate transformation with the “universal” approximation characteristic of neural networks over some compact set, the developed neuroadaptive control completely obviates the complicated yet undesired “feasibility conditions.” Furthermore, it is proven that all closed-loop signals are semiglobally bounded and the constraints are not violated.”
查看更多>>摘要：A new study on robotics is now available. According to news reporting originating from Braunschweig, Germany, by NewsRx correspondents, research stated, “This study explores the potential use of new connections to shape precast building geometries, focusing on connection performance, robotic fabrication, and foldable structural elements.” The news reporters obtained a quote from the research from Technical University Braunschweig (TU Braunschweig): “Three connection types, including coupled-bolts, hinges, and steel tubes, were initially proposed and assessed in beam and portal frame geometries. In contrast, the study introduces conceptual ideas; initial experimental and numerical studies were conducted to estimate connection capacities. Robotic fabrication for connecting elements to reused concrete and converting floor elements into beams was detailed, showcasing robotic technology’s performance and potential. These connections were employed in designing new precast element geometries, ranging from simple beams to multi-story buildings. Geometric properties and volume quantities of folded and opened geometries were studied using 37 CAD models. To properly discuss the joint performance reference, monolithic elements with exact dimensions were created for comparison.”
查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting from Boston, Massachusetts, by NewsRx journalists, research stated, “Artificial intelligence (AI)- based technologies embody countless solutions in radiation oncology, yet translation of AI-assisted software tools to actual clinical environments remains unrealized. We present the Deep Learning On-Demand Assistant (DL-ODA), a fully automated, end-to-end clinical platform that enables AI interventions for any disease site featuring an automated model-training pipeline, auto-segmentations, and QA reporting.”
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