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 trans lation have been published. According to news reporting from Shenyang, People's Republic of China, by NewsRx journalists, research stated, "Unlike general trans lation, constrained translation necessitates the proper use of predefined restri ctions, such as specific terminologies and entities, during the translation proc ess." Our news journalists obtained a quote from the research from Northeastern Univer sity: "However, current neural machine translation (NMT) models exhibit proficie nt performance solely in the domains of general translation or constrained trans lation. In this work, the author introduces the zero-shot unified constrained tr anslation training framework, which adopts a novel approach of transforming cons traints into textual explanations, thereby harmonizing the tasks of constrained translation with general translation. Furthermore, the author discovers the pivo tal role of constructing synthetic data for domain-specific constrained translat ion in enhancing the model's performance on constrained translation tasks. To th is end, the author utilizes large language models (LLMs) to generate domain-spec ific synthetic data for constrained translation. Experiments across four dataset s and four translation directions, incorporating both general and constrained tr anslations, demonstrate that models trained with the proposed framework and synt hetic data achieve superior translation quality and constraint satisfaction rate s, surpassing several baseline models in both general and contrained translation ."
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 out of Louvain la Neuve, Belg ium, by NewsRx editors, research stated, "Combinatorial and guided screening of materials space with density-functional theory and related approaches has provid ed a wealth of hypothetical inorganic materials, which are increasingly tabulate d in open databases. The OPTIMADE API is a standardised format for representing crystal structures, their measured and computed properties, and the methods for querying and filtering them from remote resources." Financial supporters for this research include Fonds De La Recherche Scientifiqu e - FNRS, Federation WAllonie-Bruxelles.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting out of Florianopolis, Brazil, by NewsRx editors, research stated, "Knowledge about Machine Learning is becoming e ssential, yet it remains a restricted privilege that may not be available to stu dents from a low socio-economic status background." The news editors obtained a quote from the research from Federal University of S anta Catarina: "Thus, in order to provide equal opportunities, we taught ML conc epts and applications to 158 middle and high school students from a low socio-ec onomic background in Brazil. Results show that these students can understand how ML works and execute the main steps of a human-centered process for developing an image classification model. No substantial differences regarding class period s, educational stage, and sex assigned at birth were observed. The course was pe rceived as fun and motivating, especiAlly to girls. Despite the limitations in t his context, the results show that they can be overcome. Mitigating solutions in volve partnerships between social institutions and university, an adapted pedago gical approach as well as increased on-by-one assistance."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting out of Zhenjiang, Peo ple's Republic of China, by NewsRx editors, research stated, "With the escalatin g severity of global climate change, the significance of carbon capture technolo gy has become increasingly evident with respect to the aim of reaching carbon pe ak and carbon neutrality. Due to the exceptional selectivity, high adsorption ca pacity, and long-term stability, solid sorbents are regarded as crucial material s for effective CO2 capture." Financial support for this research came from Senior Talent Foundation of Jiangs u University. Our news journalists obtained a quote from the research from Jiangsu University, "Machine learning, as an emerging and crucial tool in artificial intelligence, has been adopted for the high-efficient screen of catalysts and sorbents in rece nt years. By analyzing available data on material properties, machine learning c an greatly enhance the effectiveness and precision in identifying high-efficienc y CO2 sorbents. This work provides an overview of the latest advancements in the application of machine learning technology in CO2 capture, which specificAlly f ocuses on CO2 capture by sorbents. Several machine learning techniques and their applications in different types of CO2 sorbents are fully summarized with conci se comments, followed with conclusion and some chAllenges and perspectives."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news originating from Maynoot h University by NewsRx editors, the research stated, "Body balancing is a comple x task that includes the coordination of muscles, tendons, bones, ears, eyes, and the brain. Imbalance or disequilibrium is the inability to maintain the center of gravity." Funders for this research include Regional Innovation Strategy; National Researc h Foundation of Korea (Nrf)-korea Government. The news journalists obtained a quote from the research from Maynooth University : "Perpetuating body balance plays an important role in preventing us from fAlli ng or swaying. Biomechanical tests and video analysis can be performed to analyz e body imbalance. The musculoskeletal system is one of the fundamental systems b y which our balance or equilibrium is sustained and our upright posture is maint ained. Electromyogram (EMG) and ground reaction force (GRF) monitoring can be ut ilized in cases where a rapid response to body imbalance is a necessity. Body ba lance also depends on visual stimuli that can be either real or virtual. Researc hers have used virtual reality (VR) to predict motion sickness and analyze heart rate variability, as well as in rehabilitation. VR can also be used to induce b ody imbalance in a controlled way. In this research, body imbalance was induced in a controlled way by playing an Oculus game and, simultaneously, EMG and GRF w ere recorded."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Prostate Ca ncer is the subject of a report. According to news reporting from Shandong, Peop le's Republic of China, by NewsRx journalists, research stated, "This research s eeks to formulate a prognostic model for forecasting prostate cancer recurrence by examining the interaction between mitochondrial function and programmed cell death (PCD). The research involved analyzing four gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) using univariat e Cox regression." The news correspondents obtained a quote from the research from the Fourth Peopl e's Hospital of Jinan, "These analyses identified genes linked with mitochondria l function and PCD that correlate with recurrence prognosis. Various machine lea rning algorithms were then employed to construct an optimal predictive model. A key outcome was the creation of a mitochondrial-related programmed cell death in dex (mtPCDI), which effectively predicts the prognosis of prostate cancer patien ts. It was observed that individuals with lower mtPCDI exhibited higher immune a ctivity, correlating with better recurrence outcomes."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Bruderholz, Swi tzerland, by NewsRx correspondents, research stated, "The implementation of arti ficial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms." Financial support for this research came from University of Basel. Our news journalists obtained a quote from the research from the Department of O rthopaedic Surgery and Traumatology, "Yet there's only scarce evidence for measu rable value in terms of patient outcomes, clinical decision-making or socio-econ omic impact. Our aim was to investigate the significance of AI in the emergency treatment of wrist trauma patients. Two groups of physicians were confronted wit h twenty realistic cases of wrist trauma patients and had to find the correct di agnosis and provide a treatment recommendation. One group was assisted by an AI- enabled application which detects and localizes distal radius fractures (DRF) wi th near-to-perfect precision while the other group had no help. Primary outcome measurement was diagnostic accuracy. Secondary outcome measurements were require d time, number of added CT scans and senior consultations, correctness of the tr eatment, subjective and objective stress levels. The AI-supported group was able to make a diagnosis without support (no additional CT, no senior consultation) in significantly more of the cases than the control group (75% vs. 52%, p = 0.003). The AI-enhanced group detected DRF with superior sensitivity (1.00 vs. 0.96, p = 0.06) and specificity (0.99 vs. 0.93, p = 0.17), used significantly less additional CT scans to reach the correct diagnosis (14% vs. 28%, p = 0.02) and was subjectively significantly less stressed (p = 0.05). The results indicate that physicians can diagnose wrist trauma more accurately and faster when aided by an AI-tool that lessens the need for extra diagnostic procedures. The AI-tool also seems to lower physicians' stress levels while examining cases."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in West Bengal, India, by NewsRx journalists, research stated, "Skewness and kurtosis were analy sed using mean data from the F2 to F5 generations of three interspecific tomato hybrids, incorporating two feral species: Solanum pimpinellifolium (Currant Toma to) and Solanum lycopersicum var. cerasiformae (Cherry Tomato). The study canter ed on three crucial traits impacting fruit yield, with predictions generated thr ough artificial neural networks and multiple linear regression." Financial support for this research came from National Bureau of Plant Genetic R esources, New Delhi, India. The news reporters obtained a quote from the research from the Department of Agr iculture, "Plant height (PH), fruit weight (FW) and test weight of seeds (TSW) w ere identified as the most sensitive traits influencing fruit yield/plant in the Alisa Craig Aft x Solanum pimpinellifolium (Cross 1) and the Berika x Solanum l ycopersicum var. cerasiformae (Cross 2). In contrast, fruits per plant (FPP), FW and TSW emerged as the key contributors to fruit yield in the BCT 115 dg x Sola num lycopersicum var. cerasiformae (Cross 3). Skewness and kurtosis distribution suggested complementary gene action with fewer number of segregating genes for PH in Cross 1, FW across All three cross combinations, TSW in Cross 1, and FPP i n Cross 3. Duplicate gene action with fewer genes could be predicted for TSW in Cross 2 and Cross 3 while complementary gene action and a greater number of segr egating genes were suggested for PH in Cross 2. Moderate-to-high narrow sense he ritability was determined for All the characters suggesting phenotypic selection to be rewarding. Isolation of seven promising segregates based on the important yield attributers from three inter-specific hybrids in F5 generation establishe d the worth of advancing interspecific hybrids."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Gliomas is the subject of a report. According to news reporting out of Weifang, People's Re public of China, by NewsRx editors, research stated, "To investigate the applica tion value of support vector machine (SVM) model based on diffusion-weighted ima ging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1(IDH-1) mutation and Ki-6 7 expression in glioma. The DWI, DCE and APTW images of 309 patients with glioma confirmed by pathology were retrospectively analyzed and divided into the IDH-1 group (IDH-1(+) group and IDH-1(-) group) and Ki-67 group (low expression group (Ki-67 10 %) and high expression group (Ki-67 > 10%))." Our news journalists obtained a quote from the research from Weifang People's Ho spital, "All cases were divided into the training set, and validation set accord ing to the ratio of 7:3. The training set was used to select features and establ ish machine learning models. The SVM model was established with the data after f eature selection. Four single sequence models and one combined model were establ ished in IDH-1 group and Ki-67 group. The receiver operator characteristic (ROC) curve was used to evaluate the diagnostic performance of the model. Validation set data was used for further validation. Both in the IDH-1 group and Ki-67 grou p, the combined model had better predictive efficiency than single sequence mode l, although the single sequence model had a better predictive efficiency. In the Ki-67 group, the combined model was built from six selected radiomics features, and the AUC were 0.965 and 0.931 in the training and validation sets, respectiv ely. In the IDH-1 group, the combined model was built from four selected radiomi cs features, and the AUC were 0.997 and 0.967 in the training and validation set s, respectively. The radiomics model established by DWI, DCE and APTW images cou ld be used to detect IDH-1 mutation and Ki-67 expression in glioma patients befo re surgery."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Brain-Based Devices is the subject of a report. According to news reporting originating in Lowell, Mas sachusetts, by NewsRx journalists, research stated, "Invasive Microelectrode Arr ays (MEAs) have been a significant and useful tool for us to gain a fundamental understanding of how the brain works through high spatiotemporal resolution neur on-level recordings and/or stimulations. Through decades of research, various ty pes of microwire, silicon, and flexible substrate-based MEAs have been developed using the evolving new materials, novel design concepts, and cutting-edge advan ced manufacturing capabilities." Financial support for this research came from National Institutes of Health (NIH ) - USA.
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