Investigation of zinc-containing peptide deformylase from Leptospira interrogans by X-ray absorption near-edge spectroscopy

Peptide deformylase (PDF, EC 3.5.1.27) is essential for the normal growth of eubacterium but not for mammalians. Recently, PDF has been studied as a target for new antibiotics. Its activity is strongly dependent on the bound metal ion. The crystallographic studies did not show any significant structural difference upon various bound metal ions. In this paper, X-ray absorption spectroscopy was employed to determine the local structure around the zinc ion of PDF from Leptospira interrogans in dry powder. XANES (X-ray absorption near-edge structure) calculations were performed and the local geometry of the active center was reconstructed successfully. By comparing with the crystal structure of an enzyme-product complex, the results from calculations show that a water molecule has moved towards the zinc ion and lies in the distance range to coordinate with the zinc ion weakly

Progress in Antarctic marine geophysical research by the Chinese Polar Program

Marine geophysical survey by the Chinese National Antarctic Research Expedition (CHINARE) began with the first science expedition in 1984/1985, although only four cruises were performed in the vicinity of the Antarctic Peninsula between then and 1991/1992. After a 20 year hiatus, Antarctic marine geophysical research was relaunched by the Chinese Polar Environmental Comprehensive Investigation and Assessment Programs (known simply as the Chinese Polar Program) in 2011/2012. Integrated geophysical surveys have been carried out annually since, in Prydz Bay and the Ross Sea. During the last 5 years, we have acquired about 5500 km of bathymetric, gravimetric, and magnetic lines; more than 1800 km of seismic reflection lines; and data from several heat flow and Ocean Bottom Seismometer (OBS) stations. This work has deepened understandings of geophysical features and their implications for geological tectonics and glacial history in Antarctica and its surrounding seas. Compiled Antarctic Bouguer and Airy isostatic gravity anomalies show different features of tectonics between the East Antarctic stability and West Antarctic activity. Calculated magnetic anomalies, heat flow anomalies and lithospheric anisotropy offshore of Prydz Bay may imply high heat capacity of mantle shielded by the continental shelf lithosphere, but high heat dissipation of mantle due to the Cretaceous breakup of Gondwana along the continent and ocean transition (COT), where large sediment ridges would be brought about by the Oligocene ice sheet retreat and would enlarge free-air gravity anomalies. In the western Ross Sea, CHINARE seismic profiles indicate northern termination of the Terror Rift and deposition time of the grounding zone wedge in the northern JOIDES Basin

A Hybrid Model for Water Quality Prediction Based on an Artificial Neural Network, Wavelet Transform, and Long Short-Term Memory

Clean water is an indispensable essential resource on which humans and other living beings depend. Therefore, the establishment of a water quality prediction model to predict future water quality conditions has a significant social and economic value. In this study, a model based on an artificial neural network (ANN), discrete wavelet transform (DWT), and long short-term memory (LSTM) was constructed to predict the water quality of the Jinjiang River. Firstly, a multi-layer perceptron neural network was used to process the missing values based on the time series in the water quality dataset used in this research. Secondly, the Daubechies 5 (Db5) wavelet was used to divide the water quality data into low-frequency signals and high-frequency signals. Then, the signals were used as the input of LSTM, and LSTM was used for training, testing, and prediction. Finally, the prediction results were compared with the nonlinear auto regression (NAR) neural network model, the ANN-LSTM model, the ARIMA model, multi-layer perceptron neural networks, the LSTM model, and the CNN-LSTM model. The outcome indicated that the ANN-WT-LSTM model proposed in this study performed better than previous models in many evaluation indices. Therefore, the research methods of this study can provide technical support and practical reference for water quality monitoring and the management of the Jinjiang River and other basins

Risk analysis and assessment of water resource carrying capacity based on weighted gray model with improved entropy weighting method in the central plains region of China

The issue of global water shortage is a serious concern. The scientific evaluation of water resource carrying capacity (WRCC) serves as the foundation for implementing measures to protect water resources. In addition, most of the studies are based on the analysis and research of regional WRCC from the aspects of water quantity and water quality. There are few studies on the four aspects of water resources endowment conditions, society, economy and ecological environment, which is difficult to scientifically and accurately reflect the analysis and evaluation of regional WRCC by the four systems. Therefore, it is necessary to conduct a deeper discussion and Analysis on this topic. This study presents a WRCC index system and corresponding ranking criteria based on 20 influencing factors from four aspects: water resources endowment (WRE), economy, society, and ecological environment. In addition, by combining the improved entropy weighting method (EWM) with gray correlation analysis, the weighted gray technique for order preference by similarity to an ideal solution (TOPSIS) model is proposed for analyzing and assessing WRCC risk. Finally, the WRCC of the study area from 2012 to 2021 is comprehensively evaluated in the central plains region of China (CPROC) as an example. The results show that the comprehensive evaluation obtained a multi-year average value of 0.2935, and the water resources shortage in the CPROC is generally in grade III status. The comprehensive average value of Beijing is 0.345, and the comprehensive average value of Henan is 0.397. The overall degree of water resources shortage is in the state of grade V shortage, Shaanxi is in the state of grade IV shortage, and the degree of water resources in Tianjin and Shanxi is relatively good. This study provides corresponding scientific basis and methodological guidance for the sustainable utilization of water resources and healthy socio-economic performance in the CPROC

A data-driven model for water quality prediction in Tai Lake, China, using secondary modal decomposition with multidimensional external features

Study region: Tai Lake, the third largest freshwater lake in China, with a history of serious ecological pollution incidents. Study focus: Lake water quality prediction techniques are essential to ensure an early emergency response capability for sustainable water management. Herein, an effective data-driven ensemble model was developed for predicting lake dissolved oxygen (DO) based on meteorological factors, water quality indicators and spatial information. First, variation mode decomposition (VMD) was used to decompose data into multiple modal components and classify them into feature terms and self terms. The feature terms were combined with relevant external features for multivariate prediction by convolutional neural network (CNN) and a bi-directional long and short-term memory (BiLSTM) with attention mechanism (AT), as well as using the whale optimization algorithm (WOA) to optimize the model hyperparameters. The self terms form a secondary modal decomposition model. Finally, the groupings were linearly summed to obtain outcome. New hydrological insights for the region:: The proposed model has the highest prediction accuracy in Tai Lake as well as the best prediction effect using 0.5 days as the period. This research also establishes a stepwise water temperature regulation mechanism, where the output of the target DO content value is achieved by changing the magnitude of water temperature and combining it with this prediction model, thereby strengthening the protection of water resources and the management of fishery production

A Parallel Bioinspired Algorithm for Chinese Postman Problem Based on Molecular Computing

The Chinese postman problem is a classic resource allocation and scheduling problem, which has been widely used in practice. As a classical nondeterministic polynomial problem, finding its efficient algorithm has always been the research direction of scholars. In this paper, a new bioinspired algorithm is proposed to solve the Chinese postman problem based on molecular computation, which has the advantages of high computational efficiency, large storage capacity, and strong parallel computing ability. In the calculation, DNA chain is used to properly represent the vertex, edge, and corresponding weight, and then all possible path combinations are effectively generated through biochemical reactions. The feasible solution space is obtained by deleting the nonfeasible solution chains, and the optimal solution is solved by algorithm. Then the computational complexity and feasibility of the DNA algorithm are proved. By comparison, it is found that the computational complexity of the DNA algorithm is significantly better than that of previous algorithms. The correctness of the algorithm is verified by simulation experiments. With the maturity of biological operation technology, this algorithm has a broad application space in solving large-scale combinatorial optimization problems

A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction

With the accelerated industrialization and urbanization process, water pollution in rivers is being increasingly worsened, and has caused a series of ecological and environmental issues. The prediction of river water quality index (WQI) is a prerequisite for river pollution prevention and management. However, the water quality data series is non-smooth and non-linear, and a strong coupling relationship between different water quality parameters that influence each other is observed, making it an inevitable problem to accurately predict water quality parameters. To this end, a combination of machine learning and intelligent optimization algorithms was hereby used to break this dilemma. Specifically, a Back Propagation Neural Network (BPNN) model was established using the Artificial Bee Colony (ABC) algorithm, with the three adaptive evolutionary strategies, i.e., dynamic adaptive factors, probability selection and gradient initialization combined to form the Adaptive Evolutionary Artificial Bee Colony (AEABC) algorithm. The experimental results of this algorithm demonstrate that the AEABC-BPNN model only requires 14 iterations to converge in this case. The predictions of WQI can reduce the error evaluation indicators of mean square error (MSE) to 0.2745, which is at least 25.2% lower than those of the rest algorithms compared, and the mean absolute percentage error (MAPE) is lower than 7.58%. In four WQIs, the prediction interval coverage percentage (PICP) reaches 100%. Besides, robustness testing experiments were also designed to verify that the AEABC-BPNN model still outperforms the rest of the algorithms in terms of prediction accuracy when guided by historical error data. The proposed model plays a pivotal role in water pollution management in rivers and lakes, and has scientific significance for future water environmental protection

Mineralogy and trace element geochemistry of sulfide minerals from the Wocan Hydrothermal Field on the slow-spreading Carlsberg Ridge, Indian Ocean

Highlights • First present seafloor hydrothermal mineralization processes at both Wocan-1 and Wocan-2 on the slow-spreading Carlsberg Ridge. • The Cu-rich chimneys were formed at slightly lower temperatures than Cu-rich and Fe-rich massive sulfides. • The main Ag-carriers were both late-stage Cu sulfides and Fe sulfides, which deposited under low temperatures and oxidized conditions. • Fluid mixing of hydrothermal fluids with seawater might result in significant redistributions of trace metal elements in sulfides. Abstract The basalt-hosted Wocan hydrothermal field (WHF), located on the NW slope of an axial volcanic ridge in a depth of ∼3000 m at 6°22′N on the slow-spreading Carlsberg Ridge, northwest Indian Ocean, was discovered in 2013 during Chinese DY28th cruise. Preliminary investigations show that the field consists of two hydrothermal sites: Wocan-1, which shows indications for recent high-temperature hydrothermal activity, is located near the peak of the axial volcanic ridge in a water depth of 2970-2990 m, and the inactive Wocan-2 site, located at a water depth of 3100 m, ∼1.7 km to the northwest of Wocan-1. The recovered hydrothermal precipitates can be classified into four groups: (i) Cu-rich chimneys; (ii) Cu-rich massive sulfides; (iii) Fe-rich massive sulfides; and (iv) silicified massive sulfides. We conducted mineral texture and assemblage observation and Laser-ablation ICP-MS analyses of the hydrothermal precipitates to study the mineralization processes. Our results show that there are distinct systematic trace element distributions throughout the different minerals in the four sample groups. In general, chalcopyrite from the group (i) is enriched in Pb, As, Mo, Ga, Ge, V, and Sb, metals that are commonly referred to as medium- to low-temperature elements. In contrast these elements are present in low contents in the chalcopyrite grains from other sample groups. Selenium, a typical high-temperature metal, is enriched in chalcopyrite from groups (ii) and (iv), whereas Ag and Sn are enriched only in some silicified massive sulfides. As with chalcopyrite, pyrite also shows distinct trace element associations in grains with different habitus. The low-temperature association of elements (Pb, Mo, Mn, U, Mg, Ag, and Tl) is typically present in colloform/framboidal pyrite, whereas the high-temperature association (Se, Co, and Bi) is enriched in euhedral pyrite. Sphalerite in the groups (i) and (iii) at Wocan-1 is characterized by high concentrations of Ga, Ge, Pb, Cd, As, and Sb, indicating that sphalerite in these sample groups likely precipitated at intermediate temperatures. Early bornite, which mainly occurs in the central part of the Cu-rich chimney, is typically enriched in Sn and In compared to the other minerals. In contrast, late bornite that likely formed during increasing interaction of hydrothermal fluids with cold, oxygenated seawater has low Sn and In, but significantly higher concentrations of Ag, Au, Mo and U. Digenite, also forming in the exterior parts of the samples during the late stages of hydrothermal fluid venting, is poor in most trace elements, except Ag and U. The notable Ag enrichment in the late-stage mineral assemblages at both Wocan-1 and Wocan-2 may therefore be related to lower temperatures and elevated pH. Our results indicate that Wocan-1 has experienced a cycle of heating with Cu-rich chimney growth and subsequent cooling, followed by late seafloor weathering, while Wocan-2 has seen intermediate- to high-temperature mineralization followed by intense silicification of sulfides. Seafloor weathering processes or mixing of hydrothermal fluids with seawater during the waning stages of hydrothermal fluid flow result in significant redistributions of trace elements in sulfide minerals