State transition dynamics of reputation considering third-order information and multiple reputation values: by Hitoshi Yamamoto (738861)

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Correlation analysis of three samples. by Xiujuan Jiang (1884682)

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Number of birth rate regions in three categories (2006–2023). by Xiujuan Jiang (1884682)

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Intraoperative facial and intraoral photographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Spatial and temporal distribution of the three types of birth rate areas in the Yangtze River Basin. by Xiujuan Jiang (1884682)

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Third. by Cuicui Liu (1496260)

Comparison of 1^st, 2^nd, and 3^rd antibiotic prescription. by Thomas Hanslmeier (19949694)

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Posttreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Pretreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

These subfigures show a visualization of the context embeddings for the DSVAE model with LS=2=4,CS=2. The first subfigure from the left shows three patient clusters, the second sub... by Eloy Geenjaar (21533195)

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Validation of child labor measures using third-party data, households with all children in school. by Guilherme Lichand (11410286)

Evaluation rule considering third-order information and multiple reputation values: By cluster analysis and best-fitting distribution for each distribution done on basis of BIC, re... by Hitoshi Yamamoto (738861)

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Superimposition of the cephalometric tracings obtained before and after treatment of case with mandibular third molar extraction. by Lijuan Liu (136685)

Comparison of pretreatment cephalometric variables between premolar extraction and mandibular third molar extraction groups. by Lijuan Liu (136685)

Shares of specialist groups prescribing 1^st, 2^nd, and 3^rd antibiotic prescriptions in UTI treatment of females (N39.0, N30.0) in 2018 and 2019. by Thomas Hanslmeier (19949694)

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Shares of antibiotic substances on total prescription in UTI treatment (N39.0, N30.0) by sex and age group in 2019 (female: n = 238.670 prescriptions; male: n = 40.641 prescription... by Thomas Hanslmeier (19949694)

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Shares of antibiotic substances on total prescription by quarter from 2013 to 2019 for female and male patients with UTI (N39.0, N30.0)(female: n = 1.681.255 prescriptions; male: n... by Thomas Hanslmeier (19949694)

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Number of antibiotic prescriptions in female and male patients with UTI (N30.0 and/or N39.0). by Thomas Hanslmeier (19949694)

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Shares of antibiotic substances on total prescription in female patients with UTI (N39.0, N30.0) by physician specialties (GPs: n = 1.299.641 prescriptions; gynecologists n = 141.8... by Thomas Hanslmeier (19949694)

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UTI diagnoses by sex and physician specialty (2013–2019). by Thomas Hanslmeier (19949694)

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