Membrane Separation of Chiral Pharmaceutical Products

Ph.DDOCTOR OF PHILOSOPH

Construction of stable Ta3N5/g-C3N4 metal/non-metal nitride hybrids with enhanced visible-light photocatalysis

In this paper, a novel Ta3N5/g-C3N4 metal/non-metal nitride hybrid was successfully synthesized by a facile impregnation method. The photocatalytic activity of Ta3N5/g-C3N4 hybrid nitrides was evaluated by the degradation of organic dye rhodamine B (RhB) under visible light irradiation, and the result indicated that all Ta3N5/g-C3N4 samples exhibited distinctly enhanced photocatalytic activities for the degradation of RhB than pure g-C3N4. The optimal Ta3N5/g-C3N4 composite sample, with Ta3N5 mass ratio of 2%, demonstrated the highest photocatalytic activity, and its degradation rate constant was 2.71 times as high as that of pure g-C3N4. The enhanced photocatalytic activity of this Ta3N5/g-C3N4 metal/metal-free nitride was predominantly attributed to the synergistic effect which increased visible-light absorption and facilitated the efficient separation of photoinduced electrons and holes. The Ta3N5/g-C3N4 hybrid nitride exhibited excellent photostability and reusability. The possible mechanism for improved photocatalytic performance was proposed. Overall, this work may provide a facile way to synthesize the highly efficient metal/metal-free hybrid nitride photocatalysts with promising applications in environmental purification and energy conversion

ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models

Data-to-text generation is challenging due to the great variety of the input data in terms of domains (e.g., finance vs sports) or schemata (e.g., diverse predicates). Recent end-to-end neural methods thus require substantial training examples to learn to disambiguate and describe the data. Yet, real-world data-to-text problems often suffer from various data-scarce issues: one may have access to only a handful of or no training examples, and/or have to rely on examples in a different domain or schema. To fill this gap, we propose Any-Shot Data-to-Text (ASDOT), a new approach flexibly applicable to diverse settings by making efficient use of any given (or no) examples. ASDOT consists of two steps, data disambiguation and sentence fusion, both of which are amenable to be solved with off-the-shelf pretrained language models (LMs) with optional finetuning. In the data disambiguation stage, we employ the prompted GPT-3 model to understand possibly ambiguous triples from the input data and convert each into a short sentence with reduced ambiguity. The sentence fusion stage then uses an LM like T5 to fuse all the resulting sentences into a coherent paragraph as the final description. We evaluate extensively on various datasets in different scenarios, including the zero-/few-/full-shot settings, and generalization to unseen predicates and out-of-domain data. Experimental results show that ASDOT consistently achieves significant improvement over baselines, e.g., a 30.81 BLEU gain on the DART dataset under the zero-shot setting.Comment: Findings of EMNLP 202

Improved belief propagation decoding algorithm based on decoupling representation of Pauli operators for quantum LDPC codes

We propose a new method called decoupling representation to represent Pauli operators as vectors over GF(2), based on which we propose partially decoupled belief propagation and fully decoupled belief propagation decoding algorithm for quantum low density parity-check codes. Under the assumption that there is no measurement error, compared with traditional belief propagation algorithm in symplectic representation over GF(2), within the same number of iterations, the decoding accuracy of partially decoupled belief propagation and fully decoupled belief propagation algorithm is significantly improved in pure Y noise channel and depolarizing noise channel, which supports that decoding algorithms of quantum error correcting codes might have better performance in decoupling representation than in symplectic representation. The impressive performance of fully decoupled belief propagation algorithm might promote the realization of quantum error correcting codes in engineering

Preparation and Characterization of Chitosan/Cu(II) Affinity Membrane for Urea Adsorption

ABSTRACT: We used silica particles as a porogen to prepare macroporous chitosan membranes and subsequently prepared macroporous chitosan/Cu(II) affinity membranes for urea adsorption. The morphology, porosity, Cu(II) adsorption capacity, and swelling ratio of the macroporous membrane were measured. SEM photographs show the pores in the membrane dispersed uniformly, a feature that didn't change much after the adsorption of Cu(II). The porosity of the membrane had a maximum value when the silica/chitosan ratio was about 12. The Cu(II) adsorption capacity in the membrane leveled off when the initial concentration of CuSO 4 solution exceeded 5 ϫ 10 Ϫ2 mol/L. The macroporous chitosan/Cu(II) affinity membrane was successfully used for urea adsorption. The maximum urea adsorption capacity was 78.8 mg/g membrane, which indicates that the membrane has a great potential for hemodialysis for urea removal

Exact controllability of multiplex networks

Date of Acceptance: 11/09/2014Peer reviewedPublisher PD

Comprehensive eco-environmental effects of the shelter-forest ecological engineering along the Tarim Desert Highway

In this work, we report a comprehensive study about the eco-environmental effects of the shelter forest along the Tarim Desert Highway, including the effects on aeolian environment, soil, micro-climate, biodiversity, and groundwater. The results show that: (1) The movement of windblown sand near the ground surface was affected by the shelter forest. The wind speed and sediment transport rate in the shelter forest decreased by 64%-80% and 87.45%-99.02%, respectively. In addition, there were also significant changes in the sand flux structure, the sand grain size, and the deflation and deposition on the ground surface. (2) Compared to the natural mobile sand, the soil bulk density in the forest area decreased while the total salt content, the total porosity, and the water content increased. In addition, the soil fertility was significantly improved in the forest area, and showed the "first rapid, then slow" variation pattern. (3) The shelter forest showed positive effects on the micro-climate. Within the 6 m height above the ground, the air temperature in the shelter forest at different heights was lower than that in the mobile sand, while the air humidity was higher, while, the soil temperature was also lower in the shelter forest than mobile sand. (4) The number of soil microbial species increased significantly with the improvement of habitat in the shelterbelt. However, the population of different species was not distributed evenly across the surveyed area. (5) Currently, no significant effects of groundwater-pumping and forest-irrigation water have been found on the groundwater level and its salinity. The variation amplitude of both groundwater level and salinity was at the level of centimeters and 1g/L, respectively. No obvious variation trend has been observed

Beta-glucan alters gut microbiota and plasma metabolites in pre-weaning dairy calves

The present study aims to evaluate the alterations in gut microbiome and plasma metabolites of dairy calves with β-glucan (BG) supplementation. Fourteen healthy newborn dairy calves with similar body weight were randomly divided into control (n = 7) and BG (n = 7) groups. All the calves were fed on the basal diet, while calves in the BG group were supplemented with oat BG on d 8 for 14 days. Serum markers, fecal microbiome, and plasma metabolites at d 21 were analyzed. The calves were weaned on d 60 and weighed. The mean weaning weight of the BG group was 4.29 kg heavier than that of the control group. Compared with the control group, the levels of serum globulin, albumin, and superoxide dismutase were increased in the BG group. Oat BG intake increased the gut microbiota richness and decreased the Firmicutes-to-Bacteroidetes ratio. Changes in serum markers were found to be correlated with the plasma metabolites, including sphingosine, trehalose, and 3-methoxy-4-hydroxyphenylglycol sulfate, and gut microbiota such as Ruminococcaceae_NK4A214, Alistipes, and Bacteroides. Overall, these results suggest that the BG promotes growth and health of pre-weaning dairy calves by affecting the interaction between the host and gut microbiota