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Policy document mention is considered to indicate the significance and societal impact of scientific product. However, the accuracy of policy document altmetrics data needs to be evaluated to fully understand its strength and limitation. An in-depth coding analysis was conducted on sample policy documents records of Altmetric.com database. The sample consists of 2079 records from all 79 distinct policy document source platforms tracked by the database. Errors about mentioned publications in the policy documents (type A error) are found in 8% of the records, while errors about either the recorded policy documents or the mentioned publications in the altmetrics database (type B error) are found in 70% of the records. In type B error, policy document link error (5% of the records) could be attributable to the policy document website, transcription error (52% of the records) could be attributable to the third-party bibliographic data provider. These two categories of error are relatively minor and may have limited influence on altmetrics research and practices. False positive policy document mention (13% of the records), however, could be attributable to the Altmetric database and may diminish the validity of research based on the policy document altmetrics data. The underlying reasons remain to be further investigated. Considering the high complexity of extracting mentions of publications from various sources and formats of policy documents as well as its short history, Altmetric database has achieved excellent performance.

Underwater images suffer from low visibility and contrast caused by absorption and scattering, which leads to haze and some further limitations. The existing underwater single image dehazing methods cannot achieve a balance between the performance and computational complexity, and are difficult to produce satisfactory results in the regions with large distance. To overcome these problems, we propose a new underwater single image dehazing method, which includes an improved background light estimation based on the quad-tree subdivision iteration algorithm, and a novel transmission estimation method. For the background light estimation, we introduce a robust score for each region of the image, which can evaluate the region from both smoothness and color. For the transmission estimation, we propose the color space dimensionality reduction prior (CSDRP), which allows conversing an image from the three-dimensional RGB color space to a 2D color space, namely the UV color space. In the UV color space, by clustering the pixels into mounts of haze-lines and carefully setting the haze-free boundary, the transmission map can be figured out and used to produce an excellent dehazed image. Experimental results show that our method has competitive effects compared with mainstream underwater single image dehazing methods.

3, 5, 6-trichloro-2-pyridinol (TCP) is a widespread organic pollutant with persistent, mobile and high antimicrobial effects. Here, nanoFe3O4 was firstly introduced into the anoxic biodegradation of TCP. It was found that nanoFe3O4 significantly accelerated TCP biodegradation. The removal rate of TCP (100 mg L−1) increased from 83.03% to 98.74% within 12 h in the presence of nanoFe3O4, and the addition of nanoFe3O4 also promoted the accumulation of CO2. Reductive dechlorination mechanism was involved in anoxic biodegradation of TCP. Molecular approaches further revealed that nanoFe3O4 distinctly induced the shifts of bacterial community. The dominant genus Ochrobactrum was converted to genus Delftia in nanoFe3O4 treatment, and the relative abundance of Delftia increased from 10.26% to 44.62%. Meanwhile, the total relative abundance of bacteria related to TCP dechlorination and degradation significantly increased in the presence of nanoFe3O4. These results indicated that nanoFe3O4 induced the enrichment of TCP-degrading bacteria to promote the anoxic biodegradation of TCP.

As a natural sweetening and solubilizing agent, rubusoside has great potential in the application of healthy beverages and pharmaceuticals. However, the direct extraction and purification of rubusoside from raw materials is inefficient. In this work, a novel β-glucosidase (CsBGL) was obtained from Chryseobacterium scophthalmum 1433 through screening of the environmental microorganisms. CsBGL markedly hydrolyzed sophorese (Glcβ1-2Glc) and laminaribiose (Glcβ1-3Glc), but for steviol glycosides, it only hydrolyzed the C-13/C-19-linked sophorese, instead of the C-13/C-19-linked Glcβ1-2[Glcβ1-3]Glc trisaccharide and Glcβ1-monosaccharide. It efficiently hydrolyzed stevioside (240 g/L) to produce rubusoside (99% yield) at 47.5°C for 70 min. Even when using a crude steviol glycosides extract (500 g/L) containing ∼226 g/L stevioside as the substrate, CsBGL could also convert stevioside to rubusoside (99% yield) at 47.5°C for 2 h, in which the rubusoside concentration increased from the initial 42 g/L to the final 222 g/L. These results reveal that CsBGL would be a promising biocatalyst for the industry-scale production of rubusoside from stevioside or/and the crude steviol glycosides extract., Graphical Abstract As a natural sweetening and solubilizing agent, rubusoside has great potential in the application of healthy beverages and pharmaceuticals. A novel β-glucosidase CsBGL obtained here from Chryseobacterium scophthalmum 1433 through screening of the environmental microorganisms could specifically hydrolyze the C-13- or/and C-19-linked sophorese of steviol glycosides, but not the C-13- or/and C-19-linked Glcβ1-2[Glcβ1-3]Glc trisaccharide and Glcβ1-monosaccharide of steviol glycosides, and thus could be a promising biocatalyst for efficient rubusoside production from stevioside.

Biodegradation of 3,5,6-trichloro-2-pyridinol (TCP) in drylands is an important biological process of detoxification. Flooding in drylands can result in the formation of anaerobic habitats. However, little is known about the microbial metabolism of TCP in dryland soil under anaerobic conditions. Here, chlorpyrifos-contaminated dryland soil was incubated to enrich the TCP-degrading microbial consortium under anaerobic conditions. Chloridion and CO2 were released with TCP degradation, and the enrichment cultures of dryland soil could metabolize 97% of TCP (100 mg/L) within 20 h. Both reductive and hydrolysis dechlorination mechanisms were involved in TCP biodegradation under anaerobic conditions. Bacterial taxonomic analysis revealed that the aerobic TCP-degrading bacteria Ochrobactrum and dechlorination bacteria Delftia were the dominant genera. Anaerobic and facultative bacteria; i.e., Bacteroides, Bacillus, and Cupriavidus had lower relative abundances, but they were significantly enriched following treatment with TCP. These results indicate that the enrichment cultures of dryland soil dominated by aerobic bacteria could dechlorinate and degrade TCP under anaerobic conditions.

The effect of particle size on the transformation kinetics of flue gas desulfurization (FGD) gypsum to α-calcium sulfate hemihydrate (α-HH) in calcium chloride (CaCl2) solutions was investigated to better guide value-added FGD gypsum use. Gypsum samples from different sources were sieved into several size groups, and their transformation rates were compared. The results showed that using FGD gypsum with a smaller particle size accelerated the transformation to α-HH. The size effect accelerated nucleation kinetics of α-HH rather than its crystal growth rate (that is, the thermodynamic driving force for the transformation changed little with particle size variation). Analysis using a kinetics model revealed that a smaller gypsum particle size lowered the overall activation energy barrier for the transformation. This is because the smaller gypsum particles had a larger relative specific surface area and thus provided more nucleation sites and crystalline defects to promote α-HH nucleation. A smaller particle size of FGD gypsum also gave a higher yield of fine α-HH particles because of the increased incidence of primary and secondary nucleation coupled with attrition. This paper indicates the transformation of FGD gypsum into α-HH could be effectively promoted by regulating FGD gypsum particle size.

Underwater images suffer from low visibility caused by absorption and scattering, which leads to haze and some further limitations. To overcome these issues, we propose a novel dehaze method based on a universal observation that all pixels of most underwater images tend to distribute nearby a specific plane in RGB space. This observation is named the color space dimensionality reduction prior. By projecting all pixels to this plane, namely the UV color space, the color distribution of these pixels can be reduced from the three-dimensional space (RGB space) to a new two-dimensional space (UV space) without causing any excessive color shift. By carefully setting the haze-free boundary in UV space, we can obtain the image transmission and finally produce an excellent dehazed image. Experimental results show that our method has competitive results compared with mainstream underwater single image dehazing methods.

Underwater imaging has been increasingly employed in vision-based marine research. However, the inappropriate installation of a light source and the complex underwater environment will result in the uneven illumination and overexposure on the captured images. To address these issues, an underwater image enhancement framework for autonomous underwater vehicles platform is proposed, which consists of underwater light source optimization and illumination nonuniformity correction. The light source optimization method improves the imaging quality by computing an appropriate angle of the light casting. In this way, the center of the field of view is always well lit. In addition, an adaptive filter-based illumination correction algorithm is proposed to solve the uneven illumination caused by the artificial light source. During this process, image block segmentation and the measure of image enhancement index are applied to improve the adaptability and reduce the calculation errors of the filter parameters. A dataset with real underwater images collected under different natural conditions has been built and tested. The experimental results indicate that the proposed method is more adaptive and effective than the typical methods.

3, 5, 6-trichloro-2-pyridinol (TCP) is a widespread organic pollutant with persistent, mobile and high antimicrobial effects. Here, nanoFe

General and abdominal obesity are the major subtypes of obesity. Compared with general obesity, abdominal obesity was considered to be more closely associated with chronic diabetes complications, such as cardiovascular diseases and diabetic retinopathy (1,2). Although the association between abdominal obesity and urinary albumin was reported in previous studies (3–5), whether abdominal obesity is more closely associated with diabetic kidney disease (DKD) than general obesity has not been reported yet. Two studies were carried out to investigate the association of general and abdominal obesity with DKD. Study A was a cross-sectional study. Body composition was assessed using DXA among 1,016 patients with type 2 diabetes (T2D). General obesity parameters, including BMI, total body fat percentage (TBF), and fat mass index (FMI), and abdominal obesity parameters, including waist circumference (WC), waist-to-height ratio (WHtR), and visceral adipose tissue (VAT), were measured. DKD is defined as chronic kidney disease (CKD) stage 3–5 (estimated glomerular filtration rate [eGFR]

Background Compared with general obesity, abdominal obesity has been shown to be more closely correlated to chronic diabetic complications such as cardiovascular disease and diabetic retinopathy. The association between obesity and diabetic kidney disease is unclear. We did two independent studies, one cross-sectional study and one 5 year prospective study, to investigate the association of general and abdominal obesity with diabetic kidney disease. Methods In the cross-sectional study in a hospital in Chongqing, China, body composition was assessed with dual-energy X-ray absorptiometry in 1016 patients with type 2 diabetes. Variables measured to define general obesity were BMI, total body fat percentage, and fat-mass index (ratio of fat mass to height squared). Abdominal obesity variables were waist circumference, waist-to-height ratio, and visceral adipose tissue. Diabetic kidney disease was defined as chronic kidney disease stage 3–5 (estimated glomerular filtration rate [eGFR] 2 ). In the prospective study, 279 patients with type 2 diabetes without diabetic kidney disease at baseline were followed up for 5 years after initial assessment in a community centre. BMI, waist circumference, waist-to-height ratio, and waist-to-hip ratio were used as indicators of obesity type in the prospective study. Obesity-related variables were split into low, median, and high tertiles and patients were stratified by values accordingly for both studies. Ethical approval was granted by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University. Informed consent was provided by all participants. Multivariate logistic analysis was done to determine whether parameters of obesity could be risk factors for diabetic kidney disease and adjustments made for confounding factors. The odds ratios (ORs) of general obesity parameters and abdominal obesity parameters were calculated, with reference to the lowest tertile of those parameters; OR was 1. Findings In the cross-sectional study, 470 patients had stage 1 chronic kidney disease, 374 patients had stage 2 disease, and 172 patients had stages 3–5 disease. Participants with higher BMI (24·67 kg/m 2 [SD 3·33] in those with stage 1 chronic kidney disease vs 24·78 kg/m 2 [3·14] in those with stage 2 chronic kidney disease vs 25·40 kg/m 2 [3·18] in those with stages 3–5 chronic kidney disease; p=0·040), total body fat percentage (29·21% [6·17] vs 29·57% [6·16] vs 30·74% [6·18]; p=0·024), fat-mass index (7·31 kg/m 2 [2·21] vs 7·43 kg/m 2 [2·21] vs 7·89 kg/m 2 [2·14]; p=0·014), waist circumference (92·71 cm [9·31] vs 93·98 cm [9·08] vs 95·52 cm [8·88]; p=0·047), waist-to-height ratio (0·57 [IQR 0·54–0·61] vs 0·58 [0·55–0·62] vs 0·61 [0·56–0·65]; p 2 [43·34] vs 121·67 cm 2 [43·10] vs 133·31 cm 2 [45·01]; p=0·0022) were more likely to have a lower eGFR, compared with those with lower values. Logistic regression analyses showed that variables of general obesity were associated with a risk of diabetic kidney disease (in the median vs high tertiles, for BMI p trend =0·0371; for total body fat percentage p trend =0·044; for fat-mass index p trend =0·0053). However, there was no correlation when visceral adipose tissue was adjusted (in the median vs high tertiles, for BMI p trend =0·18; for total body fat percentage p trend =0·66; for fat-mass index p trend =0·26). In the prospective study, 41 patients developed diabetic kidney disease after 6 years follow-up. No association was noted between BMI and risk of diabetic kidney disease or in the crude or adjusted models (in the crude model 1·11 [0·49–2·50] in the median tertile vs 1·10 [0·48–2·47] in the high tertile, p=0·81; in the waist-to-height ratio-adjusted model 0·43 [0·26–1·18] vs 0·76 [0·32–1·80], p=0·24; in the multivariable model 0·44 [0·13–5·54] vs 1·33 [0·25–6·97], p=0·40). Abdominal obesity variables were associated with risk of diabetic kidney disease after adjustment for BMI (for waist circumference 1·39 [1·10–8·03] in the median tertile vs 2·59 [1·45–9·31] in the high tertile, p=0·022; for waist-to-hip ratio 2·63 [0·71–5·79] vs 5·16 [1·38–9·31], p=0·015; for waist-to-height ratio 3·35 [0·86–7·08] vs 5·96 [1·51–13·06], p=0·03). The associations between the risk of diabetic kidney disease and waist circumference, waist-to-hip ratio, waist-to-height ratio were the same after adjustment for other confounders. Interpretation Abdominal obesity is more closely associated with the risk of diabetic kidney disease than general obesity in China. Funding National Key Clinical Specialties Construction Program of China, the National Natural Science Foundation of China and The Fundamental Science and Advanced Technology Research of Chongqing.

This paper presents the factor clustering analysis for violent crimes. The efficiency of Rough-fuzzy C-means algorithm is affected by the numbers of clusters, and not all centroids are beneficial. The analyzing of violent crime data does not need human intervention for impartiality. The information entropy is a helpful tool for resolving those issues. In this paper, a novel discrete Rough-fuzzy C-means based on information entropy algorithm (DRFCMI) is proposed, which can obtain typical conclusions objectively. Experimental results illustrate that our proposed method is efficient.