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In this work, crystallization experiments were conducted in three different sizes of crystallizers (5 and 100 ml, and 1 L) to study the influence of temperature on the crystallization of lysozyme. Lysozyme solutions with concentrations of 40 and 30 g L−1 and 10% (w/w) NaCl were used. The temperature was reduced from 20 to 0 °C with various cooling rate and stirring speed. The data indicated that crystallization with cooling but without agitation or with agitation but without cooling led to low yield and inconstancy between batches, whereas that with combined cooling and agitation resulted in tetragonal crystals with high yields. Parameters, including crystallization onset, crystal morphology, crystal size distribution, concentration, supersaturation, and yield were examined by in situ and ex situ observations. The observations within small cooling rate range of 0.030–0.111 °C min−1 indicated that minor changes in cooling rate could cause significant differences in these parameters. The comparison with thermostatic experiment showed that cooling could cause the crystal sizes to be widely dispersed. While high cooling rate lead shorter crystallization onset time and higher supersaturation, thereby result in larger crystal size, higher tendency of aggregation and wider crystal size distribution, low cooling rate can pose a great challenge to the temperature control in scale-up crystallization. The work also demonstrated that the crystallization conditions obtained from 5- to 100-ml crystallizers, from which well-defined crystals with high yields were obtained, could successfully be reproduced in 1-L crystallizer.

Background and aim Balance deficits are common after total knee arthroplasty (TKA); however the responsiveness of commonly used balance measurement tools has not been well defined. The objective of this prospective study was to compare the internal and external responsiveness of four measurement tools in assessing recovery of balance function following TKA. Methods A total of 134 individuals with TKA (95 women; age: 66.3 ± 6.6 years) completed the Balance Evaluation Systems Test (BESTest), Mini-BESTest, Brief-BESTest, and Berg Balance Scale (BBS) at 2, 4, 8, 12, and 24 weeks post-TKA. The Functional Gait Assessment (FGA) served as the anchor measure, and was also measured across these time points. Internal responsiveness was indicated by the standardized response mean (SRM), while external responsiveness was reflected by the degree of association of the changes of balance scores with those of FGA. Results The SRM ranged from 0.60–1.14 for the BESTest, 0.40–0.94 for the Mini-BESTest, 0.27–0.91 for the Brief-BESTest, and 0.19–0.70 for the BBS, over time. The change in BESTest and Mini-BESTest scores predicted the change in the FGA scores across all time periods, except for the Mini-BESTest between weeks 12–24, accounting for 13–27%, and 12–24% of the variance, respectively. The Brief-BESTest scores only predicted FGA scores between the weeks 2–4 ( R 2 = 20%). The changes in BBS scores were not associated with the FGA. Conclusion The BESTest is the most responsive in measuring recovery of balance among individuals with TKA. The Mini-BESTest is a reasonable option during time constraints.

In agent-based simulation, emergent equilibrium describes the macroscopic steady states of agents' interactions. While the state of individual agents might be changing, the collective behavior pattern remains the same in macroscopic equilibrium states. Traditionally, these emergent equilibriums are calculated using Monte Carlo methods. However, these methods require thousands of repeated simulation runs, which are extremely time-consuming. In this paper, we propose a novel three-layer framework to efficiently compute emergent equilibriums. The framework consists of a macro-level pseudo-arclength equilibrium solver (PAES), a micro-level simulator (MLS) and a macro-micro bridge (MMB). It can adaptively explore parameter space and recursively compute equilibrium states using the predictor-corrector scheme. We apply the framework to the popular opinion dynamics and labour market models. The experimental results show that our framework outperformed Monte Carlo experiments in terms of computation efficiency while maintaining the accuracy.

Water quality information of Beijiang River, a tributary of Pearl River in Guangdong, China, was analyzed to provide an overview of the hydrochemical functioning of a major agricultural/rural area and an industrial/urban area. Eighteen water quality parameters were surveyed at 13 sites from 2005 to 2006 on a monthly basis. A bivariate correlation analysis was carried out to evaluate the regional correlations of the water quality parameters, while the principal component analysis (PCA) technique was used to extract the most influential variables for regional variations of river water quality. Six principal components were extracted in PCA which explained more than 78% and 84% of the total variance for agricultural/rural and industrial/urban areas, respectively. Physicochemical factor, organic pollution, sewage pollution, geogenic factor, agricultural nonpoint source pollution, and accumulated pesticide usage were identified as potential pollution sources for agricultural/rural area, whereas industrial wastewaters pollution, mineral pollution, geogenic factor, urban sewage pollution, chemical industrial pollution, and water traffic pollution were the latent pollution sources for industrial/urban area. A multivariate linear regression of absolute principal component scores (MLR-APCS) technique was used to estimate contributions of all identified pollution sources to each water quality parameter. High coefficients of determination of the regression equations suggested that the MLR-APCS model was applicable for estimation of sources of most water quality parameters in the Beijiang River Basin.

In this paper, we further develop the molecular fractionation with conjugate caps (MFCC) scheme for quantum mechanical computation of DNA-ligand interaction energy. We study three oligonuclear acid interaction systems: dinucleotide dCG/water, trinucleotide dCGT/water, and a Watson-Crick paired DNA segment, dCGT/dGCA. Using the basic MFCC approach, the nucleotide chains are cut at each phosphate group and a pair of conjugate caps (concaps) are inserted. Five cap molecules have been tested among which the dimethyl phosphate anion is proposed to be the standard concap for application. For each system, one-dimensional interaction potential curves are computed using the MFCC method and the calculated interaction energies are found to be in excellent agreement with corresponding results obtained from the full system ab initio calculations. The current study extends the application of the MFCC method to ab initio calculations for DNA- or RNA-ligand interaction energies.

An integrated process was specifically developed for the decentralized supply of drinking water from micro-polluted surface water in the rural areas of China. The treatment process combined ozonation with ceramic ultra-filtration (UF), coagulation for pre-treatment and granular activated carbon filtration. A flat-sheet ceramic membrane was used with a cut-off of 60 nm and the measurement of 254 mm (length) × 240 mm (width) × 6 mm (thickness). Ozonation and ceramic UF was set up whthin one reactor. The experimental results showed that the removal efficiencies of the dissolved organic carbon (DOC) and the formation potential of trihalomethanes (THMs), haloacetic acids (HAAs) and ammonia were 80%, 76%, 70% and 90%, respectively; that the turbidity of the product water was below 0.2 NTU and the particle count number (particles larger than 2 μm) was less than 50 counts per mL. The result also showed that all the pathogenic microorganisms were retained by the ceramic and that UF. Ozonation played a critical role in the control of membrane fouling and the removal of contaminants. Exactly, the membrane fouling can be controlled in situ with 3 mg L(-1) ozone at the permeate flux of 80 L m(-2) h(-1), yet the required dosage of ozone was dependent on the quality of the raw water. Therefore, this study is able to provide a highly compacted system for decentralized supply of high-quality drinking water in terms of both chemical and microbiological safety for the rural areas in China.

Aminoglycosides, traditional RNA binders, were found to be a new class of triple helical nucleic acid-stabilizing ligands. Neomycin, of all the aminoglycosides, has shown the most significant effects in stabilizing DNA, RNA, and hybrid triple helices. When compared with minor groove binders or intercalators, neomycin excels at triple helical stabilization in most cases. Molecular modeling studies suggest that neomycin reaches into the larger Watson-Hoogsteen groove. The charge and shape complementarity are the key factors in neomycin-triplex recognition. By conjugating neomycin with intercalators such as BQQ (a potent triple helix intercalating agent designed by Helene), we have progressed in developing more potent triple helix stabilizing ligands. The design of such dual or even triple recognition ligands opens a new paradigm for recognition of triple helix nucleic acids. The article herein presents studies of neomycin as the first molecule that can selectively stabilize nucleic acid triplex structures. These studies are supported by our recent discovery that neomycin prefers to bind to A-like conformations, of which triple helix structures are known to display some characteristics. These findings will contribute to the development of a new series of triplex-specific ligands, and may contribute to either antisense or antigene therapies.