Synergistic effect of dual phase cocatalysts: MoC-Mo2C quantum dots anchored on g-C3N4 for high-stability photocatalytic hydrogen evolution.

The extensive examination of hexagonal molybdenum carbide (ß-Mo2C) as a non-noble cocatalyst in the realm of photocatalytic H2 evolution is predominantly motivated by its exceptional capacity to adsorb H+ ions akin to Pt and its advantageous conductivity characteristics. However, the H2 evolution rate of photocatalysts modified with ß-Mo2C is limited as a result of their comparatively low ability to release H through desorption. Therefore, a facile method was employed to synthesize carbon intercalated dual phase molybdenum carbide (MC@C) quantum dots (ca. 3.13 nm) containing both α-MoC and ß-Mo2C decorated on g-C3N4 (gCN). The synthesis process involved a simple and efficient combination of sonication-assisted self-assembly and calcination techniques. 3-MC@C/gCN exhibited the highest efficiency in generating H2, with a rate of 4078 µmol g-1h-1 under 4 h simulated sunlight irradiation, which is 13 times higher than pristine gCN. Furthermore, from the cycle test, 3-MC@C/gCN showcased exceptional photochemical stability of 65 h, as it maintained a H2 evolution rate of 40 mmol g-1h-1. The heightened level of activity observed in the 3-MC@C/gCN system can be ascribed to the synergistic effects of MoC-Mo2C that arise due to the existence of a carbon layer. The presence of a carbon layer enhanced the transmission of photoinduced electrons, while the MoC-Mo2C@C composite served as active sites, thereby facilitating the H2 production reaction of gCN. The present study introduces a potentially paradigm-shifting concept pertaining to the exploration of novel Mo-based cocatalysts with the aim of augmenting the efficacy of photocatalytic H2 production.

Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd Counting.

Multidomain crowd counting aims to learn a general model for multiple diverse datasets. However, deep networks prefer modeling distributions of the dominant domains instead of all domains, which is known as domain bias. In this study, we propose a simple-yet-effective modulating domain-specific knowledge network (MDKNet) to handle the domain bias issue in multidomain crowd counting. MDKNet is achieved by employing the idea of "modulating", enabling deep network balancing and modeling different distributions of diverse datasets with little bias. Specifically, we propose an instance-specific batch normalization (IsBN) module, which serves as a base modulator to refine the information flow to be adaptive to domain distributions. To precisely modulating the domain-specific information, the domain-guided virtual classifier (DVC) is then introduced to learn a domain-separable latent space. This space is employed as an input guidance for the IsBN modulator, such that the mixture distributions of multiple datasets can be well treated. Extensive experiments performed on popular benchmarks, including Shanghai-tech A/B, QNRF, and NWPU validate the superiority of MDKNet in tackling multidomain crowd counting and the effectiveness for multidomain learning. Code is available at https://github.com/csguomy/MDKNet.

Evaluating AI rib fracture detections using follow-up CT scans.

PURPOSE: This study compares the results of Artificial Intelligence (AI) diagnosis of rib fractures using initial CT and follow-up CT as the final diagnostic criteria, and studies AI-assisted diagnosis in improving the detection rate of rib fractures. METHODS: A retrospective study was conducted on 113 patients who underwent initial and follow-up CT scans due to trauma. The initial and follow-up CT were used as diagnostic criteria, respectively. All images were transmitted to the AI software (V2.1.0, Huiying Medical Technology Co., Beijing, China) for rib fracture detection. The radiologist group (Group 1), AI group (Group 2), and Radiologist with AI group (Group 3) reviewed CT images at an interval of one month, recorded and compared the differences in the sensitivity and specificity for diagnosing rib fractures. RESULTS: 589 and 712 rib fractures were diagnosed by the initial and follow-up CT, respectively. The initial CT diagnosis failed to detect 127 rib fractures, resulting in a missed rate of 17.84%. In addition, four normal ribs were mistakenly identified as being fractured. The follow-up CT was regarded as the diagnostic standard for rib fractures. The sensitivity and specificity were 82.16% and 99.80% for Group 1, 79.35% and 84.90% for Group 2, and 91.57% and 99.70% for Group 3. The sensitivity of Group 3 was higher than that of Group 1 and Group 2 (p < 0.05). The specificity was lower for Group 2 compared with Group 1 and Group 3 (p < 0.05). CONCLUSION: AI-assisted diagnosis improved the detection rate of rib fractures, the follow-up CT should be used for the diagnosis standard of rib fractures, and AI misdiagnoses can be greatly reduced when a radiologist reviews the diagnosis.

Confusion-Based Metric Learning for Regularizing Zero-Shot Image Retrieval and Clustering.

Deep metric learning turns to be attractive in zero-shot image retrieval and clustering (ZSRC) task in which a good embedding/metric is requested such that the unseen classes can be distinguished well. Most existing works deem this "good" embedding just to be the discriminative one and race to devise the powerful metric objectives or the hard-sample mining strategies for learning discriminative deep metrics. However, in this article, we first emphasize that the generalization ability is also a core ingredient of this "good" metric and it largely affects the metric performance in zero-shot settings as a matter of fact. Then, we propose the confusion-based metric learning (CML) framework to explicitly optimize a robust metric. It is mainly achieved by introducing two interesting regularization terms, i.e., the energy confusion (EC) and diversity confusion (DC) terms. These terms daringly break away from the traditional deep metric learning idea of designing discriminative objectives and instead seek to "confuse" the learned model. These two confusion terms focus on local and global feature distribution confusions, respectively. We train these confusion terms together with the conventional deep metric objective in an adversarial manner. Although it seems weird to "confuse" the model learning, we show that our CML indeed serves as an efficient regularization framework for deep metric learning and it is applicable to various conventional metric methods. This article empirically and experimentally demonstrates the importance of learning an embedding/metric with good generalization, achieving the state-of-the-art performances on the popular CUB, CARS, Stanford Online Products, and In-Shop datasets for ZSRC tasks.

Artificial Intelligence in Coronary CT Angiography: Current Status and Future Prospects.

Coronary heart disease (CHD) is the leading cause of mortality in the world. Early detection and treatment of CHD are crucial. Currently, coronary CT angiography (CCTA) has been the prior choice for CHD screening and diagnosis, but it cannot meet the clinical needs in terms of examination quality, the accuracy of reporting, and the accuracy of prognosis analysis. In recent years, artificial intelligence (AI) has developed rapidly in the field of medicine; it played a key role in auxiliary diagnosis, disease mechanism analysis, and prognosis assessment, including a series of studies related to CHD. In this article, the application and research status of AI in CCTA were summarized and the prospects of this field were also described.

Classification of Microcalcification Clusters Using Bilateral Features Based on Graph Convolutional Network.

Breast cancer is one of the diseases with the highest incidence and mortality among women in the world, which has posed a serious threat to women's health. The appearance of clustered calcifications is one of the important signs of breast cancer, and thus how to classify clustered calcifications comes to be a key breakthrough in controlling breast cancer. In this study, the discriminant model based on image convolution is used to learn the image features related to the classification of clustered microcalcifications, and the graph convolutional network (GCN) based on topological graph is used to learn the spatial distribution characteristics of clustered microcalcifications. These two models are fused to obtain a complementary model of image information and spatial information. The results show that the performance of the fusion model proposed in this paper is obviously superior to that of the two classification models in the classification of clustered microcalcification.

Enhancing electronic metal support interaction (EMSI) over Pt/TiO2 for efficient catalytic wet air oxidation of phenol in wastewater.

Phenol is one of the major hazardous organic compounds in industrial wastewater. In this work, a highly active Pt/TiO2 catalyst for catalytic wet air oxidation (CWAO) of phenol was obtained by supporting pre-synthesized Pt on TiO2. During the followed hydrogen reduction, strong hydrogen spillover occurred without the migration of TiO2 onto Pt. The reduced support then enhanced the electron transfer from TiO2 to Pt, increasing the percentage of partially negative Pt (Ptδ-), which has been confirmed by XPS. The strong EMSI made the obtained catalyst far more active than Pt/TiO2 prepared by impregnation method. The electron-enriched Pt/TiO2 achieved total organic carbon (TOC) conversion of 88.8% and TOF 149 h-1 at 100 °C and 2 MPa O2, while conventional Pt/TiO2 gave TOC conversion of 39.5% and TOF 41 h-1 for CWAO of phenol. Our work indicates that the enhancement of EMSI between metal and support can be an effective approach to develop highly active catalysts for phenol treatment.

Survival Outcomes of Lobectomy Versus Segmentectomy in Clinical Stage I Non-Small Cell Lung Cancer: A Meta-Analysis.

INTRODUCTION: The gold standard surgical therapy for patients with clinical stage I non-small cell lung cancer (NSCLC) is lobectomy with mediastinal lymph node dissection. Meanwhile, segmentectomy has emerged as an alternative choice with the advantage of fewer postoperative complications. The acceptance of this procedure remains controversial, and conflicting results exist in the retrospective trials. OBJECTIVES: The aim of this meta-analysis was to analyze the survival outcomes of lobectomy versus segmentectomy in clinical stage I NSCLC. METHODS: A computerized literature search was done on published trials in PubMed, Embase, and the Cochrane Library to June 2019 to identify clinical trials. Lung cancer-specific survival (LCSS) and overall survival (OS) were measured as outcomes. Statistical analysis was performed in the Meta-analysis Revman 5.3 software. RESULTS: A systematic literature search was conducted including seven studies. In this meta-analysis, the LCSS and OS in the lobectomy group were linked to a markedly lower trend in comparison to the segmentectomy group without significant statistical difference (P > 0.05), indicating that lobectomy confers an equivalent survival outcome compared with segmentectomy. CONCLUSION: No significant differences were found in survival outcomes between lobectomy and segmentectomy. Further large-scale, prospective, randomized trials are needed to explore reasonable surgical treatments for early-stage lung cancer.

A Clinical Study of Noninvasive Assessment of Lung Lesions in Patients with Coronavirus Disease-19 (COVID-19) by Bedside Ultrasound.

PURPOSE: This study was conducted to explore the clinical value of noninvasive assessment of bedside ultrasound in the diagnosis of lung lesions of Coronavirus Disease-19. METHODS: In this retrospective study, 30 patients with Coronavirus Disease-19 admitted to our hospital from January 18 to February 5, 2020, were selected as the research subjects. All cases were examined by lung ultrasound and CT. Lung lesions were reviewed by blinded observers, with imaging scores being used to analyze the ultrasound findings of lung lesions in patients with Coronavirus Disease-19 and with chest CT being used as the reference standard. The clinical value of ultrasound in the noninvasive assessment of lung lesions was evaluated. RESULTS: Lung ultrasound signs in patients with Coronavirus Disease-19 were mainly manifested as interstitial pulmonary edema (90.0 %, 27/30) and pulmonary consolidations (20.0 %, 6/30). The lung lesions were mainly distributed in the subpleural and peripheral pulmonary zones. The lower lobe and the dorsal region had a greater tendency to be involved. There was moderate agreement (Kappa = 0.529) between the noninvasive assessment of bedside ultrasound for lung lesions in patients with Coronavirus Disease-19 and CT. The ultrasound scores to evaluate mild, moderate and severe lung lesions exhibited sensitivity of 68.8 % (11/16), 77.8 % (7/9), 100.0 % (2/2), specificity of 85.7 % (12/14), 76.2 % (16/21), 92.9 % (26/28), and diagnostic accuracy of 76.7 % (23/30), 76.7 % (23/30), 93.3 % (28/30), respectively. The follow-up dynamic ultrasound examination showed that the condition of all patients worsened gradually, with the ultrasound scores of lung lesions increasing to varying degrees. CONCLUSION: Though the diagnostic efficacy of bedside ultrasound is relatively low for mild to moderate patients, it is high for severe patients. Bedside ultrasound has important clinical significance for noninvasive assessment and dynamic observation of lung lesions in patients with Coronavirus Disease-19, which is worth further consideration.

Preliminary evidence from a multicenter prospective observational study of the safety and efficacy of chloroquine for the treatment of COVID-19.

Effective therapies are urgently needed for the SARS-CoV-2 pandemic. Chloroquine has been proved to have antiviral effect against coronavirus in vitro. In this study, we aimed to assess the efficacy and safety of chloroquine with different doses in COVID-19. In this multicenter prospective observational study, we enrolled patients older than 18 years old with confirmed SARS-CoV-2 infection excluding critical cases from 12 hospitals in Guangdong and Hubei Provinces. Eligible patients received chloroquine phosphate 500 mg, orally, once (half dose) or twice (full dose) daily. Patients treated with non-chloroquine therapy were included as historical controls. The primary endpoint is the time to undetectable viral RNA. Secondary outcomes include the proportion of patients with undetectable viral RNA by day 10 and 14, hospitalization time, duration of fever, and adverse events. A total of 197 patients completed chloroquine treatment, and 176 patients were included as historical controls. The median time to achieve an undetectable viral RNA was shorter in chloroquine than in non-chloroquine (absolute difference in medians -6.0 days; 95% CI -6.0 to -4.0). The duration of fever is shorter in chloroquine (geometric mean ratio 0.6; 95% CI 0.5 to 0.8). No serious adverse events were observed in the chloroquine group. Patients treated with half dose experienced lower rate of adverse events than with full dose. Although randomized trials are needed for further evaluation, this study provides evidence for safety and efficacy of chloroquine in COVID-19 and suggests that chloroquine can be a cost-effective therapy for combating the COVID-19 pandemic.

Effect of Metal Precursors on the Performance of Pt/SAPO-11 Catalysts for n-Dodecane Hydroisomerization.

Pt(NH3)4(NO3)2, Pt(NH3)4(Ac)2, (NH4)2PtCl4, and H2PtCl6 were used to prepare Pt/SAPO-11 catalysts to investigate the effect of Pt precursors on the hydroisomerization of n-dodecane. The catalyst derived from Pt(NH3)4(NO3)2 displays the best hydroisomerization activity and selectivity among these precursors. The hydroisomerization conversion of n-dodecane is affected by the platinum particle size, platinum dispersion, the location of platinum, and the valence state of platinum. The selectivity of n-dodecane is determined by the number of Brønsted acid sites and Pt crystal planes. These conclusions are verified by combining transmission electron microscopy, high-resolution transmission electron microscopy, hydrogen temperature programmed reduction, NH3-temperature programmed desorption, and Py-IR studies. The catalyst prepared with Pt(NH3)4(NO3)2 as the precursor exhibits the smallest platinum particle size and the highest platinum dispersion. Most of the platinum particles are supported on the external surface of SAPO-11 with the Pt(111) crystal face. Such a catalyst also possesses a suitable number of Brønsted acid sites and then displays the best catalytic performance. Obviously, the use of various precursors for the Pt-based catalyst can significantly affect the performance of Pt/SAPO-11 for the hydroisomerization of n-dodecane.

Quantitative study of liver hemodynamic changes in rats with small-for-size syndrome by the 4D-CT perfusion technique.

OBJECTIVE: The microcirculatory hemodynamic changes of small-for-size syndrome (SFSS) are still unclear. In this study, they were investigated by four-dimensional CT perfusion (4D-CTP) technique. METHODS: The sham group, 50, 60, 70 and 80 % partial hepatectomy (PH) rat groups were established. At 1 hour (1 h), 1 day (1 d), 3 days (3 d) and 7 days (7 d) post-operation, serological examination, 4D-CTP scan and histopathological examination were performed. One-way analysis of variance and the Kruskal-Wallis test were used for the comparison. RESULTS: Based on the diagnostic criteria of SFSS, the 80 % group was considered to be a successful model. In all the PH groups, portal vein perfusion and total liver perfusion peaked at 1 h and declined at 1d and 3d. Both portal vein perfusion and total liver perfusion were significantly higher in the 80 % group than the sham group, 50 and 60% groups at 1 h (p < 0.05), and 80 % group at 3d and 7d (p < 0.05). In the 50 and 60 % groups, hepatic artery perfusion decreased at 1 h and maintained at a lower level until at 7 d; whereas, in the 70 and 80% groups, it increased at 1 h, then decreased and reached the lowest level at 7 d. No significant difference appeared in hepatic artery perfusion between any two groups at any time points. At all time points, hepatic perfusion index was lower in all the PH groups than the sham group. Significant differences in hepatic perfusion index appeared between the 80% group and the sham group at 1 h and 1 d (p < 0.05). CONCLUSIONS: The CTP parameters quantitatively revealed the microcirculatory hemodynamic changes in SFSS, which were further confirmed to be associated with histopathological injury. It is suggested that the hemodynamic changes in SFSS remnant liver can provide useful information for further revealing the mechanism of SFSS and may help for guiding the treatments. ADVANCES IN KNOWLEDGE: By using the 4D-CTP technique, the hepatic microcirculatory hemodynamic changes could be quantitatively measured in vivo for small animal research.

Characteristics and environmental response of secondary minerals in AMD from Dabaoshan Mine, South China.

This article documents the new precipitates formed related to acid mine drainage (AMD) at Dabaoshan mine (South China). X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope & Energy Spectrometer (SEM-EDS) have been used to detect minerals in AMD impoundment and downstream creeks. The occurrences, the mineralogical species and the micro-morphological characteristics of secondary minerals from different pH conditions has been carried out. Iron- hydroxysulfates and iron-oxyhydroxides are the main secondary minerals, and they occurred as both poorly and well-crystalline minerals. Jarosite nearly predominate as pseudocubic crystals at pH 2.5-4.0. Schwertmannite-rich sediments occurred at pH 3.82-4.5 as urchin-like, pin-cushion and as well as globular-like aggregates and show high concentrations of Mn, Cu, Pb and As due to adsorption and co-precipitation. Goethite formed mainly as botryoidal and flaky assemblages. Paragenesis of different types of schwertmannite indicate that pH condition is not the dominant factor controlling morphology but the main parameter for the variation of minerals species. Statistical analysis reveal obvious changing tendency in Zn, Cd and SO4 within pH. FTIR analysis show adsorption of Cu, Pb, Zn and As on secondary iron minerals. Water elements with high concentrations in the impoundment and the obvious decrease in downstream creak reflected an accumulation and evaporation in AMD impoundment and a dilution in downstream area respectively. These results indicate that secondary minerals associated with AMD can play an important role in attenuating toxic elements.

Early prediction of survival in hepatocellular carcinoma patients treated with transarterial chemoembolization plus sorafenib.

AIM: To identify clinical biomarkers that could early predict improved survival in patients with advanced-stage hepatocellular carcinoma (HCC) treated with transarterial chemoembolization combined with sorafenib (TACE-S). METHODS: We retrospectively evaluated the medical records of consecutive patients with advanced-stage HCC who underwent TACE-S from January 2012 to December 2015. At the first follow-up 4-6 wk after TACE-S (median, 38 d; range, 33-45 d), patients exhibiting the modified Response Evaluation Criteria in Solid Tumors (mRECIST)-evaluated complete response, partial response, and stable disease were categorized as early disease control. At this time point, multiple variables were analyzed to identify the related factors affecting survival. RESULTS: Ninety-five patients were included in this study, and 60 of these patients achieved early disease control, with an overall disease control rate (DCR) of 63.2%. Patients who got sorafenib at the first TACE (no previous TACE) and patients without portal vein tumor thrombus (PVTT) had a higher DCR than those who underwent previous TACE before TACE-S (72.4% vs 48.6%, P = 0.019) and those with PVTT (75.5% vs 50.0%, P = 0.010). Early disease control after TACE-S, no previous TACE, and no PVTT were the independent prognostic factors for survival in the uni- and multivariate analyses. CONCLUSION: The first follow-up 4-6 wk after TACE-S can be used as the earliest time point to assess the response to TACE-S, and patients with mRECIST-evaluated early disease control, no previous TACE, and no PVTT had better survival.

Highly Dispersed Metal Carbide on ZIF-Derived Pyridinic-N-Doped Carbon for CO2 Enrichment and Selective Hydrogenation.

Catalytic conversion of CO2 into chemicals is a critical issue for energy and environmental research. Among such reactions, converting CO2 into CO has been regarded as a significant foundation to generate a liquid fuels and chemicals on a large scale. In this work, zeolitic imidazolate framework-derived N-doped carbon-supported metal carbide catalysts (M/ZIF-8-C; M=Ni, Fe, Co and Cu) with highly dispersed metal carbide were prepared for selective CO2 hydrogenation. Under the same metal loadings, catalytic activity for CO2 hydrogenation to CO follows the order: Ni/ZIF-8-C≈Fe/ZIF-8-C>Co/ZIF-8-C>Cu/ZIF-8-C. These catalysts are composed of carbide or metal supported on pyridinic N sites within the N-doped carbon structure. ZIF-8-derived pyridinic nitrogen and carbide effect CO2 adsorption, whereas dispersed Ni or Fe carbide and metal species serve as an active site for CO2 hydrogenation. The supported Ni catalyst exhibits extraordinary catalytic performance, which results from high dispersion of the metal and exposure of the carbide. Based on high-sensitivity low-energy ion scattering (HS-LEIS) and line scan results, density functional theory (DFT) was used to understand reaction mechanism of selective CO2 hydrogenation over Ni/ZIF-8-C. The product CO is derived mainly from the direct cleavage of C-O bonds in CO2 * rather than decomposition of COOH*. The CO* desorption energy on Ni/ZIF-8-C is lower than that for further hydrogenation and dissociation. Comparison of Ni/ZIF-8-C with ZIF-8-C indicates that the combined effects of the highly dispersed metal or carbide and weak CO adsorption result in high CO selectivity for CO2 hydrogenation.

Revealing the Role of Interfacial Properties on Catalytic Behaviors by in Situ Surface-Enhanced Raman Spectroscopy.

Insightful understanding of how interfacial structures and properties affect catalytic processes is one of the most challenging issues in heterogeneous catalysis. Here, the essential roles of Pt-Au and Pt-oxide-Au interfaces on the activation of H2 and the hydrogenation of para-nitrothiophenol (pNTP) were studied at molecular level by in situ surface-enhanced Raman spectroscopy (SERS) and shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS). Pt-Au and Pt-oxide-Au interfaces were fabricated through the synthesis of Pt-on-Au and Pt-on-SHINs nanocomposites. Direct spectroscopic evidence demonstrates that the atomic hydrogen species generated on the Pt nanocatalysts can spill over from Pt to Au via the Pt-Au and Pt-TiO2-Au interfaces, but would be blocked at the Pt-SiO2-Au interfaces, leading to the different reaction pathways and product selectivity on Pt-on-Au and Pt-on-SHINs nanocomposites. Such findings have also been verified by the density functional theory calculation. In addition, it is found that nanocatalysts assembled on pinhole-free shell-isolated nanoparticles (Pt-on-pinhole-free-SHINs) can override the influence of the Au core on the reaction and can be applied as promising platforms for the in situ study of heterogeneous catalysis. This work offers a concrete example of how SERS/SHINERS elucidate details about in situ reaction and helps to dig out the fundamental role of interfaces in catalysis.

In situ dynamic tracking of heterogeneous nanocatalytic processes by shell-isolated nanoparticle-enhanced Raman spectroscopy.

Surface molecular information acquired in situ from a catalytic process can greatly promote the rational design of highly efficient catalysts by revealing structure-activity relationships and reaction mechanisms. Raman spectroscopy can provide this rich structural information, but normal Raman is not sensitive enough to detect trace active species adsorbed on the surface of catalysts. Here we develop a general method for in situ monitoring of heterogeneous catalytic processes through shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) satellite nanocomposites (Au-core silica-shell nanocatalyst-satellite structures), which are stable and have extremely high surface Raman sensitivity. By combining operando SHINERS with density functional theory calculations, we identify the working mechanisms for CO oxidation over PtFe and Pd nanocatalysts, which are typical low- and high-temperature catalysts, respectively. Active species, such as surface oxides, superoxide/peroxide species and Pd-C/Pt-C bonds are directly observed during the reactions. We demonstrate that in situ SHINERS can provide a deep understanding of the fundamental concepts of catalysis.

Enhancing enzyme stability and metabolic functional ability of ß-galactosidase through functionalized polymer nanofiber immobilization.

A functionalized polystyrene nanofiber (PSNF) immobilized ß-galactosidase assembly (PSNF-Gal) was synthesized as a nanobiocatalyst aiming to enhance the biocatalyst stability and functional ability. The PSNF fabricated by electrospinning was functionalized through a chemical oxidation method for enzyme binding. The bioengineering performance of the enzyme carriers was further evaluated for bioconversion of lactose to galacto-oligosaccharides (GOS). The modified PSNF-Gal demonstrated distinguished performances to preserve the same activity as the free ß-galactosidase at the optimum pH of 7.0, and to enhance the enzyme stability of PSNF-Gal in an alkaline condition up to pH 10. The PSNF assembly demonstrated improved thermal stability from 37 to 60 °C. The nanobiocatalyst was able to retain 30 % of its initial activity after ninth operation cycles comparing to four cycles with the unmodified counterpart. In contrast with free ß-galactosidase, the modified PSNF-Gal enhanced the GOS yield from 14 to 28 %. These findings show the chemically modified PSNF-based nanobiocatalyst may be pertinent for various enzyme-catalysed bioprocessing applications.

[Micro-FTIR mapping tracer for the heterogeneity growth of nitrogen impurities in natural diamond from three localities in China].

The geographic locality determination of diamonds is of great significance in understanding the mantle evolution, restricting the illegal trade of conflict diamonds, etc. In the present article, the in-situ analysis of micro-FTIR surface scan technique was first applied to analyze 14 IaAB natural diamond specimens from China's three commercial localities. According to the FTIR spectra of diamonds, the nitrogen contents were calculated (1616 data points of FTIR) and used for mapping tracer. Th results showed that the nitrogen contents and its aggregation often varied in the process of diamond growth, and the nitrogen contents in initial nucleation stage could be higher or lower than in other stages. It is not an unidirectional variation for nitroge contents in different growth stages, indicating that the carbon and nitrogen had a complex exchange with mantle fluid during the diamond's crystallization course. It was regionally different between the diamonds from the three localities in the frequency distribution of nitrogen contents and NB%/N(T). Micro-FTIR mapping is more intuitive than the method of selecting discontinuous points, and it can trace the heterogeneous growth of nitrogen impurities in natural diamonds consecutively.