Long period start-up is one of the main restraining factors of the single-stage completely autotrophic nitrogen removal over nitrite (CANON) process.This study investigated the fast start-up of the CANON process initiated by a submerged biological aerated filter (SBAF) method.With conventional activated sludge from the secondary sedimentation tank of municipal waste water treatment plants as the seed sludge,the CANON process was successfully started up after the acclimation of sludge microorganisms for 48 days under the experimental conditions of (30±2)℃,organic carbon free and controlled dissolved oxygen (stage Ⅰ:0.3-0.5mg·L;stage Ⅱ-Ⅳ:0.1-0.2mg·L),with the maximum removal rates of ammonia nitrogen and total nitrogen achieved at 99.9% and 86.5%,respectively.The population structure characteristics of microorganisms in the system were studied using high-throughput sequencing of 16S rDNA amplicon.The results demonstrated that the two dominant microbial strains in the system were Proteobacteria and Planctomycetes,accounting for 26.6% and 17.8%,respectively.The major contributors of nitrogen removal were in -Proteobacteria and in Brocadiae.Through the above experiments,it was revealed that the investigated SBAF based CANON possesses had the advantages of fast start-up,efficient biological nitrogen removal and stable operation process.
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http://dx.doi.org/10.13227/j.hjkx.201607085 | DOI Listing |
Neuroradiol J
January 2025
Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA.
This study evaluates the efficacy of deep learning models in identifying infarct tissue on computed tomography perfusion (CTP) scans from patients with acute ischemic stroke due to large vessel occlusion, specifically addressing the potential influence of varying noise reduction techniques implemented by different vendors. We analyzed CTP scans from 60 patients who underwent mechanical thrombectomy achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2c or 3, ensuring minimal changes in the infarct core between the initial CTP and follow-up MR imaging. Noise reduction techniques, including principal component analysis (PCA), wavelet, non-local means (NLM), and a no denoising approach, were employed to create hemodynamic parameter maps.
View Article and Find Full Text PDFMed Image Anal
January 2025
School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China; Shanghai Artificial Intelligence Laboratory, Shanghai, China. Electronic address:
Radiation therapy is a primary and effective treatment strategy for NasoPharyngeal Carcinoma (NPC). The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis. Despite that deep learning has achieved remarkable performance on various medical image segmentation tasks, its performance on OARs and GTVs of NPC is still limited, and high-quality benchmark datasets on this task are highly desirable for model development and evaluation.
View Article and Find Full Text PDFSci Rep
January 2025
Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192, Japan.
Front Radiol
December 2024
Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Brain Lang
January 2025
Dept. of Speech-Language Pathology, SUNY Buffalo State, Buffalo, NY, USA.
This study presents an examination of the neural connectivity associated with processing speech in noisy environments, an ability that declines with age. We correlated subjects' speech-in-noise (SIN) ability with resting-state MRI scans and Fractional Anisotropy (FA) values from the auditory section of the corpus callosum, both with and without correcting for age. The results revealed that subjects who performed poorly on the right ear SIN test (QuickSIN, MedRx) had higher correlations between the primary auditory cortex and regions of the brain that process language.
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