Multi-omics analysis reveals the collaboration and metabolisms of the anammox consortia driven by soluble/non-soluble Fe(III) as the sole iron element.

Iron is recognized as a physiological requirement for anammox bacteria (AnAOB), with Fe(II) considered to be the most effective form. However, Fe(III), instead of Fe(II) is the common iron form in natural and artificial ecosystems. In this study, the nitrogen removal performance and metabolic mechanisms in anammox consortia with soluble and non-soluble Fe(III) as the sole iron element were investigated. After the 150-day operation, the soluble (FeCl3) and insoluble (Fe2O3) Fe(III)-fed anammox systems reached nitrogen removal rates of 71.84 ± 0.80% and 50.20 ± 0.98%, respectively. AnAOB could survive with soluble (FeCl3) or insoluble (Fe2O3) Fe(III) as the sole iron element, reaching relative abundances of 18.49% and 13.16%, respectively. The results show that the formation of anammox core consortia can enable AnAOB's survival to adverse external conditions of Fe(II) deficiency. Metagenomic and metatranscriptomic analysis reveal that Ca. Kuenenia can only uptake Fe(II) into the cell for metabolisms either independently through the extracellular electron transfer or with the cross-feeding of symbiotic microbes. This study provides insight into the utilization and metabolic mechanisms of Fe(III) in Ca. Kuenenia-dominated consortia, and deepens the understanding of anammox core consortia in the nitrogen, carbon, and iron cycling, further promoting the practical applications of anammox processes.

Parental homework involvement and students' mathematics achievement: a meta-analysis.

Introduction: Given the importance of parent involvement to students' academic achievement, researchers have used a variety of methods to investigate the relationship between the two, but few focus on the relationship between parental homework involvement and students' achievement in a specific subject by using meta-analysis. This meta-analysis investigated the relationship between parent homework involvement and students' mathematics achievement from two dimensions: supportive (SPI) and intrusive parent homework involvement (IPI), along with their moderators. Methods: Accessed through Web of Science, Taylor and Francis Online, EBSCO, Springer Link, Elsevier, and ProQuest databases, a total of 20 empirical studies between 2005 to 2022, 41 independent effect sizes were included (N = 16,338). Effect size estimations were obtained by transforming Fisher's correlation coefficient. This study has conducted the heterogeneity tests of the magnitudes grouped according to different moderators, and investigated the publication bias that affects meta-analysis studies. Results and discussion: The results showed an overall positive link between SPI and students' mathematics achievement (r = 0.076, 95% CI = [0.037, 0.114]) and a negative link between IPI and students' mathematics achievement (r = -0.153, 95% CI = [-0.226, -0.079]). For the link of SPI and students' mathematics achievement, the effect sizes were (a) strongest when SPI was measured by autonomy support, followed by content support and provision of structure respectively; (b) stronger when students' mathematics achievement indicated by non-standardized measurement than standardized measurement. For the link of IPI and students' mathematics achievement, the effect sizes varied across grade level, strongest in high school, followed by middle school and lowest in primary school. These findings provide important implications for how to improve parental homework involvement practice to increase students' mathematics achievement.

Co/N co-doped porous carbon as a catalyst for the degradation of RhB by efficient activation of peroxymonosulfate.

We report on the preparation of Co/N-NPCx/y with porous structure and excellent activation properties. The synthesis involves the preparation of Zn/Co-ZIFx and the carbonization of Zn/Co-ZIFx at a high temperature in an inert atmosphere. The volatilization of zinc during carbonization results in a porous structure, which is beneficial to the migration of pollutants. The sizes, specific surface areas, and pore size distribution of Co/N-NPCx/y can be achieved by tuning Zn/Co ratio. The calcination temperatures mainly affect the crystalline phase, crystallinity, and magnetic properties of the as-prepared materials. The effects of the as-prepared materials properties and activation conditions on the Rhodamine B (RhB) degradation by PMS activation were investigated. Overall, it exhibited superior catalytic activity in PMS activation, as evidenced by almost complete removal of RhB (0.020 mM, 100 mL) by using 5 mg/L Co/N-NPC0.5/900 and 1.250 mM PMS within 30 min. Furthermore, it confirmed the participation of SO4•-, •OH, and 1O2 in the catalytic reaction, and both SO4•- and 1O2 were the main reactive oxygen species that play a major role.

Automated rock mass condition assessment during TBM tunnel excavation using deep learning.

Rock mass condition assessment during tunnel excavation is a critical step for the intelligent control of tunnel boring machine (TBM). To address this and achieve automatic detection, a visual assessment system is installed to the TBM and a lager in-situ rock mass image dataset is collected from the water conveyance channel project. The rock mass condition assessment task is transformed into a fine-grain classification task. To fulfill the task, a self-convolution based attention fusion network (SAFN) is designed in this paper. The core of our method is the discovery and fusion of the object attention map within a deep neural network. The network consists of two novel modules, the self-convolution based attention extractor (SAE) module and the self-convolution based attention pooling algorithm (SAP) module. The former is designed to detect the intact rock regions generating the attention map, and the latter is designed to improve the performance of classifier by fusing the attention map that focuses on the intact rock regions. The results of SAFN are evaluated from aspects of interpretability, ablation, accuracy and cross-validation, and it outperforms state-of-the-art models in the rock mass assessment dataset. Furthermore, the dynamic filed test show that our assessment system based on the SAFN model is accurate and efficient for automated classification of rock mass.

Sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage.

The problem of sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage is investigated in this paper. The objective of designing controllers is to guarantee the stability and anti-disturbance performance of the closed-loop systems while some sensor outages happen. Firstly, based on matrix transformation, the state-space model of structural systems with sensor outages and uncertainties appearing in the mass, damping and stiffness matrices is established. Secondly, by considering most of those earthquakes or strong winds happen in a very short time, and it is often the peak values make the structures damaged, the finite-time stability analysis method is introduced to constrain the state responses in a given time interval, and the H-infinity stability is adopted in the controller design to make sure that the closed-loop system has a prescribed level of disturbance attenuation performance during the whole control process. Furthermore, all stabilization conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using the LMI Toolbox. Finally, numerical examples are given to demonstrate the effectiveness of the proposed theorems.

Changes in the myosin secondary structure and shrimp surimi gel strength induced by dense phase carbon dioxide.

Dense phase carbon dioxide (DPCD) could induce protein conformation changes. Myosin and shrimp surimi from Litopenaeus vannamei were treated with DPCD at 5-25MPa and 40-60°C for 20min. Myosin secondary structure was investigated by circular dichroism and shrimp surimi gel strength was determined using textural analysis to develop correlations between them. DPCD had a greater effect on secondary structure and gel strength than heating. With increasing pressure and temperature, the α-helix content of DPCD-treated myosin decreased, while the ß-sheet, ß-turn and random coil contents increased, and the shrimp surimi gel strength increased. The α-helix content was negatively correlated with gel strength, while the ß-sheet, ß-turn and random coil contents were positively correlated with gel strength. Therefore, when DPCD induced myosin to form a gel, the α-helix of myosin was unfolded and gradually converted to a ß-sheet. Such transformations led to protein-protein interactions and cross-linking, which formed a three-dimensional network to enhance the gel strength.