Many genus-level changes to the classification of Trochilini were enacted in Stiles et al. (2017b). We have since found that two further genera therein emended each require replacement names. The first of these requiring a replacement name is Uranomitra Reichenbach, 1854 [March], which is herewith interpreted as an additional synonym of Saucerottia Bonaparte, 1850, along with its junior synonym Cyanomyia Bonaparte, 1854a [May]. We show that both must have the same type species, as originally designated, Trochilus quadricolor Vieillot, 1822 = Ornismya cyanocephala Lesson, 1829. The second case in which a replacement name is required is Leucolia Mulsant E. Verreaux, 1866, herewith interpreted as an additional synonym of Leucippus Bonaparte, 1850, with the same type species, Trochilus fallax Bourcier, 1843. We herein propose replacement names for both Uranomitra and Leucolia.
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http://dx.doi.org/10.11646/zootaxa.4950.2.8 | DOI Listing |
J Mater Chem B
January 2025
National Engineering Research Center for Biomaterials, College of Biomedical Engineering, Sichuan University, Chengdu, 610065, P. R. China.
Wound healing is a complex and dynamic biological process that requires meticulous management to ensure optimal outcomes. Traditional wound dressings, such as gauze and bandages, although commonly used, often fall short in their frequent need for replacement, lack of real-time monitoring and absence of anti-inflammatory and antibacterial properties, which can lead to increased risk of infection and delayed healing. Here, we address these limitations by introducing an innovative hydrogel dressing, named PHDNN6, to combine wireless Bluetooth temperature monitoring and light-triggered nitric oxide (NO) release to enhance wound healing and management.
View Article and Find Full Text PDFCochrane Database Syst Rev
January 2025
Department of Health Promotion and Policy, University of Massachusetts, Amherst, MA, USA.
Background: Electronic cigarettes (ECs) are handheld electronic vaping devices that produce an aerosol by heating an e-liquid. People who smoke, healthcare providers, and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review.
View Article and Find Full Text PDFSci Rep
January 2025
College of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, 524088, China.
To address the problems of complex cloud features in satellite cloud maps, inaccurate typhoon localization, and poor target detection accuracy, this paper proposes a new typhoon localization algorithm, named TGE-YOLO. It is based on the YOLOv8n model with excellent high-low feature fusion capability and innovatively achieves the organic combination of feature fusion, computational efficiency, and localization accuracy. Firstly, the TFAM_Concat module is creatively designed in the neck network, which comprehensively utilizes the detailed information of shallow features and the semantic information of deeper features, enhancing the fusion ability of features at each layer.
View Article and Find Full Text PDFMedicina (Kaunas)
January 2025
Department of Anesthesiology and Intensive Care, Astana Medical University, Astana 010000, Kazakhstan.
This case report highlights the use of continuous infusion of meropenem in a 42-year-old septic female patient with periprosthetic infection and end-stage renal disease receiving prolonged intermittent renal replacement therapy (PIRRT). Antibiotic infusion in patients receiving renal replacement therapy has its own peculiarities. There are many studies on the optimal dosing regimen for meropenem in renal dysfunction, but studies on the optimal infusion duration in these patients are limited.
View Article and Find Full Text PDFSci Rep
January 2025
Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, 100192, China.
Object detection is crucial for remote sensing image processing, yet the detection of small objects remains highly challenging due to factors such as image noise and cluttered backgrounds. In response to this challenge, this paper proposes an improved network, named SED-YOLO, based on YOLOv5s. Firstly, we leverage Switchable Atrous Convolution (SAC) to replace the standard convolutions in the original C3 modules of the backbone network, thereby enhancing feature extraction capabilities and adaptability.
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