A comprehensive understanding of microbial assembly is essential for achieving stable performance in biological wastewater treatment. Nevertheless, few studies have quantified these phenomena in detail, particularly in anammox-based processes. This study integrated mathematical and microbial approaches to analyze a 330-day anammox reactor with stable nitrogen removal efficiency (97 - 99%) despite changes in the high nitrogen loading rate, nitrogen concentration, and hydraulic retention time. A high value of functional redundancy (0.82) was obtained, with 84.6% of the microbial species following the neutral community model in stochastic processes, thus maintaining the stability of the dominant species and function in the microbial community. This study represents an initial attempt to quantify and evaluate the importance of functional redundancy in an anammox reactor. Based on these findings, engineering strategies have also been proposed to preserve high functional redundancy in stabilizing system performance under varying operating conditions.
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http://dx.doi.org/10.1016/j.biortech.2024.132029 | DOI Listing |
Sci Rep
January 2025
Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Humans exploit motor synergies for motor control; however, how they emerge during motor learning is not clearly understood. Few studies have dealt with the computational mechanism for generating synergies. Previously, optimal control generated synergistic motion for the upper limb; however, it has not yet been applied to the high-dimensional whole-body system.
View Article and Find Full Text PDFMol Genet Genomics
January 2025
Department of Botany, Biology Institute, UnB, Brasília, DF, 70910-900, Brazil.
Precursors of microRNAs (pre-miRNAs) are less used in silico to mine miRNAs. This study developed PmiR-Select based on covariance models (CMs) to identify new pre-miRNAs, detecting conserved secondary structural features across RNA sequences and eliminating the redundancy. The pipeline preceded PmiR-Select filtered 20% plant pre-miRNAs (from 38589 to 8677) from miRBase.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Washington, Seattle, WA, USA.
Background: Protein homeostasis (proteostasis) mechanisms fail with aging and disease, promoting toxic protein accumulation. Neurons are particularly vulnerable to proteostatic disruption leading to aging related neurodegeneration. Abnormal activation of the endoplasmic reticulum unfolded protein response (UPR) is implicated in tauopathies, a group of neurodegenerative diseases characterized by pathological accumulation of the microtubule-associated protein tau.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, UNSW Sydney, NSW, Australia.
Background: Language and cultural factors are known to influence cognitive performance on neuropsychological measures used to assess cognitive impairment and dementia. A new measure, the Characterising Language Experience and Acculturation Questionnaire (CLEAr-Q) was developed to address the gap in access to a brief measure of these factors in the Australian context. The aim is to validate and further develop the CLEAr-Q as a tool to capture linguistic and acculturation variables to improve measurement of cognition in older adults from Culturally and Linguistically Diverse (CALD) backgrounds.
View Article and Find Full Text PDFFront Plant Sci
December 2024
School of Software, Henan Institute of Science and Technology, Xinxiang, Henan, China.
Introduction: Pests are important factors affecting the growth of cotton, and it is a challenge to accurately detect cotton pests under complex natural conditions, such as low-light environments. This paper proposes a low-light environments cotton pest detection method, DCP-YOLOv7x, based on YOLOv7x, to address the issues of degraded image quality, difficult feature extraction, and low detection precision of cotton pests in low-light environments.
Methods: The DCP-YOLOv7x method first enhances low-quality cotton pest images using FFDNet (Fast and Flexible Denoising Convolutional Neural Network) and the EnlightenGAN low-light image enhancement network.
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