Simultaneous removal of nitrogen, phosphorus, and organic matter from oligotrophic water in a system containing biochar and construction waste iron: Performances and biotic community analysis.

The issue of combined pollution in oligotrophic water has garnered increasing attention in recent years. To enhance the pollutant removal efficiency in oligotrophic water, the system containing Zoogloea sp. FY6 was constructed using polyester fiber wrapped sugarcane biochar and construction waste iron (PWSI), and the denitrification test of simulated water and actual oligotrophic water was carried out for 35 days. The experimental findings from the systems indicated that the removal efficiencies of nitrate (NO3--N), total nitrogen (TN), chemical oxygen demand (COD), and total phosphorus (TP) in simulated water were 88.61%, 85.23%, 94.28%, and 98.90%, respectively. The removal efficiencies of actual oligotrophic water were 83.06%, 81.39%, 81.66%, and 97.82%, respectively. Furthermore, the high-throughput sequencing data demonstrated that strain FY6 was successfully loaded onto the biological carrier. According to functional gene predictions derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the introduction of PWSI enhanced intracellular iron cycling and nitrogen metabolism.

Stochastic Schrödinger Equation Approach to Real-Time Dynamics of Anderson-Holstein Impurities: An Open Quantum System Perspective.

We develop a stochastic Schrödinger equation (SSE) framework to simulate the real-time dynamics of Anderson-Holstein (AH) impurities coupled to a continuous Fermionic bath. The bath degrees of freedom are incorporated through fluctuating terms determined by exact system-bath correlations, which is derived in an ab initio manner. We show that such an SSE treatment provides a middle ground between numerically expansive microscopic simulations and macroscopic master equations. Computationally, the SSE model enables efficient numerical methods for propagating stochastic trajectories. We demonstrate that this approach not only naturally provides microscopically detailed information unavailable from reduced models but also captures effects beyond master equations, thus serving as a promising tool to study open quantum dynamics emerging in physics and chemistry.

Simultaneous removal of phosphorus, zinc, and lead from oligotrophic ecosystem by iron-driven denitrification: Performance and mechanisms.

Based on the current situation of complex pollution caused in surface water by oligotrophic condition and heavy metal release from river and lake bottom sediments. This study aimed to achieve the simultaneous removal of nitrate, phosphorus, Zn2+ and Pb2+ through microbial approach. At nitrate concentration of 4.82 mg L-1, carbon to nitrogen ratio of 1.5, pH of 6.0, and Fe2+ concentration of 5.0 mg L-1, the nitrate removal efficiency of Zoogloea sp. FY-6 reached 95.17%. The addition of pollutants under these conditions resulted in 88.76% removal of total phosphorus at 18 h, and 85.46 and 78.59% removal of Zn2+ and Pb2+ respectively, and there was competition for adsorption between Zn2+ and Pb2+. Extracellular polymers and fluorescence excitation-emission substrates confirmed that Fe2+ reduced heavy metal toxicity through promoting bacterial production of secretions and promotes denitrification as a carbon source. Meanwhile, contaminant removal curves and Fourier transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy demonstrated the synchronous removal of Zn2+ and Pb2+ mainly through biological action and the formation of nanoscale iron oxides. Biological-iron precipitation also provided adsorption sites for phosphorus. This research provides the theoretical foundation for applying microorganisms to restore oligotrophic source water (rivers and lakes) containing complex pollutants.

In-situ modified biosynthetic crystals with lanthanum for fluoride removal based on microbially induced calcium precipitation: Characterization, kinetics, and mechanism.

In this research, in-situ modified biosynthetic crystals with lanthanum (BC-La) were synthesized based on anaerobic microbially induced calcium precipitation (MICP) and investigated its capacity for groundwater defluoridation under various operational conditions. The kinetic and thermodynamic models were simulated to explore the effect of the material on the removal of fluoride ion (F-) under various parameters (pH, initial concentration of F-, and temperature). BC-La had the maximum F- adsorption capacity of 10.92 mg g-1 and 96.66% removal efficiency. The pseudo-second-order kinetic model and Langmuir isotherm model were the best kinetic and isotherm models for F- removal from BC-La, which indicated that F- were mainly spontaneously removed through chemisorption and adsorption processes. The specific surface area was 54.26 m2 g-1 and the average pore size was 9.0670 nm. BC-La mainly contained LaCO3OH, LaPO4, CaCO3, Ca5 (PO4)3OH, and F- was mainly removed through ion exchange with the material surface. Moreover, OH-, PO43-, and CO32- significantly influenced the F- removal. This work suggested a novel method for in-situ modification of anaerobic biosynthetic crystals, which improved the defluoridation effect of traditional biosynthetic crystals, increased the stability of the BC-La and allowed to remove F- from groundwater consistently.

Copper Iodide Cluster Incorporated Luminescent Organic-Inorganic Hybrid Coating Exhibiting Both Corrosion Protection and Antibacterial Properties.

A photoluminescent organic-inorganic hybrid coating is synthesized by the incorporation of an emissive Cu4I4 core into a cross-linked coating network through Cu-P coordination bonds. The hybrid coating not only emits strong yellow emission under UV-light irradiation but also exhibits corrosion protection of the metallic surface. Moreover, bactericidal properties are studied that were first reported for Cu4I4-based hybrid light-emitting materials.

Performance of hydrogel immobilized bioreactors combined with different iron ore wastes for denitrification and removal of copper and lead: Optimization and possible mechanism.

Reasonable and efficient removal of mixed pollutants (nitrate and heavy metals) in industrial wastewater under heavy metal pollution has attracted more attention in recent years. The target strain Aquabacterium sp. XL4 was immobilized with different iron ore wastes (IOW) using polyvinyl alcohol (PVA) to construct four immobilized bioreactors. The results showed that when the ratio of C/N was 1.5 and the hydraulic retention time (HRT) was 8.0h, the denitrification performance of the bioreactor was the best, and the maximum denitrification efficiency of the bioreactor with sponge iron (SI) as the iron source was 97.19% (2.42mg L-1 h-1). Furthermore, by adjusting the concentration of Cu2+ and Pb2+, the stress behavior of the bioreactor to heavy metals under the influence of each IOW was investigated. The bioreactor has stronger tolerance and removal efficiency to Pb2+ and Cu2+ in the presence of pellets ore (PO) and refined iron ore (RO), respectively. Moreover, the high-throughput data showed that Aquabacterium accounted for a high proportion in the immobilized bioreactor, and the prediction of functional genes based on the KEGG database showed that the addition of IOW was closely related to the acceleration of nitrate transformation and the inflow and outflow of iron in cells.

New Strategy for Optimizing the Properties of Copper Halide Organic-Inorganic Hybrid Lighting-emitting Materials.

Copper(I) halide organic-inorganic hybrid luminescent materials have many advantages, such as diverse structure, facile synthesis, high luminescent efficiency, tunable optical performance, etc., and show a broad application prospect in energy-saving lighting, display and other fields. However, compared with commercial rare-earth-metal-based phosphors, the reported hybrids generally suffer from poor stability and low luminescent efficiency, which are the bottleneck problem of their practical application. With the aim of developing high-performance organic-inorganic hybrid luminescent materials, a new synthesis strategy has been reported. This strategy can systematically design and synthesis copper(I) halide ionic hybrid structures by combining the covalent bonding and ionic bonding between inorganic and organic components into one structure, and use their synergistic effect to optimizing their properties. This design method is expected to develop high-performance organic-inorganic hybrid luminescent materials, promote the in-depth understanding of this field, and provide new ideas for the optimization of other types of hybrid materials.

Coordinated Anionic Inorganic Module-An Efficient Approach Towards Highly Efficient Blue-Emitting Copper Halide Ionic Hybrid Structures.

Copper halide based organic-inorganic hybrid semiconductors exhibit great potential as light-emitting materials with excellent structural variety and optical tunability. Among them, copper halide hybrid molecular compounds with discrete inorganic modules are particularly interesting due to their high quantum efficiency. However, synthesizing highly efficient blue-emitting molecular clusters remains challenging. Here, we report a novel and facile strategy for the design and synthesis of highly luminescent copper halide hybrid structures by fabricating coordinated anionic inorganic modules in these ionic species. By using this approach, a family of strongly blue-emitting copper halide hybrid ionic structures has been prepared with high internal quantum yields up to 98 %. Strong luminescence from the combination of ionic and covalent bonds in these compounds make them ideal candidates as alternative, rare-earth-element free light-emitting materials for possible use in optoelectronic devices.

Efficient sampling of thermal averages of interacting quantum particle systems with random batches.

An efficient sampling method, the pmmLang + RBM, is proposed to compute the quantum thermal average in the interacting quantum particle system. Benefiting from the random batch method (RBM), the pmmLang + RBM has the potential to reduce the complexity due to interaction forces per time step from O(NP2) to O(NP), where N is the number of beads and P is the number of particles. Although the RBM introduces a random perturbation of the interaction forces at each time step, the long time effects of the random perturbations along the sampling process only result in a small bias in the empirical measure of the pmmLang + RBM from the target distribution, which also implies a small error in the thermal average calculation. We numerically study the convergence of the pmmLang + RBM and quantitatively investigate the dependence of the error in computing the thermal average on the parameters such as batch size, time step, and so on. We also propose an extension of the pmmLang + RBM, which is based on the splitting Monte Carlo method and is applicable when the interacting potential contains a singular part.

Dimeric Cycloparaphenylenes with a Rigid Aromatic Linker.

Dimeric cycloparaphenylene (CPP) architectures with well-defined flipping motion are constructed taking advantage of an efficient cyclocondensation reaction. Variable-temperature nuclear magnetic resonance (VT-NMR) analyses and theoretical calculations indicate rapid interconversion of cis and trans conformers at room temperature, while energetically favorable trans conformer exists at low temperature with the metastable cis conformer hidden. The trihexylsilylethynyl-substituted dimer exhibits bright emission in solution at 616 nm with quantum yield up to 80 %, representing the brightest CPP-based emitter beyond 600 nm. A 1:2 host-guest complex of the dimer and C60 is established with negative cooperativity, demonstrating the first example of 1:2 complex from CPP derivatives.

An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images.

Contemporary medical imaging is becoming increasingly more quantitative. The emerging field of radiomics is a leading example. By translating unstructured data (i.e., images) into structured data (i.e., imaging features), radiomics can potentially characterize clinically useful imaging phenotypes. In this paper, an exploratory radiomics approach is used to investigate the potential association between quantitative imaging features and pulmonary function in CT images. Thirty-nine radiomic features were extracted from the lungs of 64 patients as potential imaging biomarkers for pulmonary function. Collectively, these features capture the morphology of the lungs, as well as intensity variations, fine-texture, and coarse-texture of the pulmonary tissue. The extracted lung radiomics data was compared to conventional pulmonary function tests. In general, patients with larger lungs of homogeneous, low attenuating pulmonary tissue (as measured via radiomics) were found to be associated with poor spirometry performance and a lower diffusing capacity for carbon monoxide. Unsupervised dynamic data clustering revealed subsets of patients with similar lung radiomic patterns that were found to be associated with similar forced expiratory volume in one second (FEV1) measurements. This implies that patients with similar radiomic feature vectors also presented with comparable spirometry performance, and were separable by varying degrees of pulmonary function as measured by imaging.

Association of pre-treatment radiomic features with lung cancer recurrence following stereotactic body radiation therapy.

The purpose of this work was to investigate the potential relationship between radiomic features extracted from pre-treatment x-ray CT images and clinical outcomes following stereotactic body radiation therapy (SBRT) for non-small-cell lung cancer (NSCLC). Seventy patients who received SBRT for stage-1 NSCLC were retrospectively identified. The tumor was contoured on pre-treatment free-breathing CT images, from which 43 quantitative radiomic features were extracted to collectively capture tumor morphology, intensity, fine-texture, and coarse-texture. Treatment failure was defined based on cancer recurrence, local cancer recurrence, and non-local cancer recurrence following SBRT. The univariate association between each radiomic feature and each clinical endpoint was analyzed using Welch's t-test, and p-values were corrected for multiple hypothesis testing. Multivariate associations were based on regularized logistic regression with a singular value decomposition to reduce the dimensionality of the radiomics data. Two features demonstrated a statistically significant association with local failure: Homogeneity2 (p = 0.022) and Long-Run-High-Gray-Level-Emphasis (p = 0.048). These results indicate that relatively dense tumors with a homogenous coarse texture might be linked to higher rates of local recurrence. Multivariable logistic regression models produced maximum [Formula: see text] values of [Formula: see text], and [Formula: see text], for the recurrence, local recurrence, and non-local recurrence endpoints, respectively. The CT-based radiomic features used in this study may be more associated with local failure than non-local failure following SBRT for stage I NSCLC. This finding is supported by both univariate and multivariate analyses.

Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping.

To accelerate the thermal equilibrium sampling of multi-level quantum systems, the infinite swapping limit of a recently proposed multi-level ring polymer representation is investigated. In the infinite swapping limit, the ring polymer evolves according to an averaged Hamiltonian with respect to all possible surface index configurations of the ring polymer and thus connects the surface hopping approach to the mean-field path-integral molecular dynamics. A multiscale integrator for the infinite swapping limit is also proposed to enable efficient sampling based on the limiting dynamics. Numerical results demonstrate the huge improvement of sampling efficiency of the infinite swapping compared with the direct simulation of path-integral molecular dynamics with surface hopping.

Path integral molecular dynamics with surface hopping for thermal equilibrium sampling of nonadiabatic systems.

In this work, a novel ring polymer representation for a multi-level quantum system is proposed for thermal average calculations. The proposed representation keeps the discreteness of the electronic states: besides position and momentum, each bead in the ring polymer is also characterized by a surface index indicating the electronic energy surface. A path integral molecular dynamics with surface hopping (PIMD-SH) dynamics is also developed to sample the equilibrium distribution of the ring polymer configurational space. The PIMD-SH sampling method is validated theoretically and by numerical examples.

Improved sampling and validation of frozen Gaussian approximation with surface hopping algorithm for nonadiabatic dynamics.

In the spirit of the fewest switches surface hopping, the frozen Gaussian approximation with surface hopping (FGA-SH) method samples a path integral representation of the non-adiabatic dynamics in the semiclassical regime. An improved sampling scheme is developed in this work for FGA-SH based on birth and death branching processes. The algorithm is validated for the standard test examples of non-adiabatic dynamics.