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Objectives: In advanced stages of osteoradionecrosis, medication-related osteonecrosis of the jaw, and osteomyelitis, a resection of sections of the mandible may be unavoidable. The determination of adequate bony resection margins is a fundamental problem because bony resection margins cannot be secured intraoperatively. Single-photon emission computed tomography (SPECT-CT) is more accurate than conventional imaging techniques in detecting inflammatory jaw pathologies.

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Aspect category sentiment analysis based on pre-trained BiLSTM and syntax-aware graph attention network.

Sci Rep

January 2025

Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, 100081, China.

Aspect Category Sentiment Analysis (ACSA) is a fine-grained sentiment analysis task aimed at predicting the sentiment polarity associated with aspect categories within a sentence.Most existing ACSA methods are based on a given aspect category to locate sentiment words related to it. When irrelevant sentiment words have semantic meaning for the given aspect category, it may cause the problem that sentiment words cannot be matched with aspect categories.

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The problem of ground-level ozone (O) pollution has become a global environmental challenge with far-reaching impacts on public health and ecosystems. Effective control of ozone pollution still faces complex challenges from factors such as complex precursor interactions, variable meteorological conditions and atmospheric chemical processes. To address this problem, a convolutional neural network (CNN) model combining the improved particle swarm optimization (IPSO) algorithm and SHAP analysis, called SHAP-IPSO-CNN, is developed in this study, aiming to reveal the key factors affecting ground-level ozone pollution and their interaction mechanisms.

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Multiclass imbalance is a challenging problem in real-world datasets, where certain classes may have a low number of samples because they correspond to rare occurrences. To address the challenge of multiclass imbalance, this paper introduces a novel hybrid cluster-based oversampling and undersampling (HCBOU) technique. By clustering and separating classes into majority and minority categories, this algorithm retains the most information during undersampling while generating efficient data in the minority class.

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The increasing level of cadmium (Cd) contamination in soil due to anthropogenic actions is a significant problem. This problem not only harms the natural environment, but it also causes major harm to human health via the food chain. The use of chelating agent is a useful strategy to avoid heavy metal uptake and accumulation in plants.

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