Durable superhydrophobic polyvinylidene fluoride membranes via facile spray-coating for effective membrane distillation

Membrane wetting and fouling substantially limits application and deployment of membrane distillation process. Designing high-performance superhydrophobic membranes offers an effective solution to solve the challenge. In this work, a highly durable superhydrophobic surface (water contact angle of 170.8 ± 1.3°) was constructed via a facile and rapid spray-coating of extremely hydrophobic SiO2 nanoparticles onto a porous polyvinylidene fluoride (PVDF) substrate for membrane distillation. The superhydrophobic membrane coated by fluorinated SiO2 nanoparticles exhibited a superior physicochemical stability in a wide range of extreme environments (i.e., NaOH, HCl, hot water, rust water, humic acid solution, ultrasonication, and high-speed water scouring). During 8-h continuous membrane distillation desalination experiment, the coated superhydrophobic membrane experienced a consistently stable water vapor flux (ca. 19.1 kg·m−2·h−1) and desalination efficiency (99.99 %). Additionally, such a stable superhydrophobicity endowed the spray-coated PVDF membrane to overcome membrane wetting and fouling during membrane distillation of highly saline solutions containing foulants (i.e., humic acid and rust). Results reported in this study provides a useful concept and strategy in facile construction of robust superhydrophobic membranes via spray-coating for effective membrane distillation.</p

Detection of Candida DNA in peritoneal fluids by PCR assay optimizing the diagnosis and treatment for intra-abdominal candidiasis in high-risk ICU patients: A prospective cohort study

BackgroundIntra-abdominal candidiasis (IAC) is the predominant type of invasive candidiasis with high mortality in critically ill patients. This study aimed to investigate whether the polymerase chain reaction (PCR) assay for detecting Candida DNA in peritoneal fluids (PF) is useful in diagnosing and management of IAC in high-risk patients in intensive care unit (ICU).MethodsA prospective single-center cohort study of surgical patients at high risk for IAC was conducted in the ICU. PF was collected from the abdominal drainage tubes (within 24 h) or by percutaneous puncture. Direct PF smear microscopy, PF culture, blood culture, and serum (1–3)-β-D-glucan were performed in all patients. For Candida PCR assay, the ITS1/ITS4 primers that targeted the ITS1-5.8 s-ITS2 regions were used for PCR, and sequencing analysis was used to identify the pathogen at the species level. IAC was defined according to the 2013 European consensus criteria.ResultsAmong 83 patients at high risk for IAC, the IAC criteria were present in 17 (20.5%). The sensitivity and specificity of the Candida PCR assay were 64.7 and 89.4%, respectively, and the area under the receiver operating characteristic curve was 0.77 (95% CI: 0.63–0.91). In this cohort, the positive predictive value and negative predictive value were 90.8% (95% CI: 80.3–96.2%) and 61.1% (95% CI: 36.1–81.7%), respectively. Diagnostic consistency was moderate (kappa 0.529, p &lt; 0.001) according to the 2013 European consensus criteria.ConclusionDetection of Candida DNA in PF using PCR can be considered an adjunct to existing routine diagnostic tools which may optimize the diagnosis and antifungal treatment of IAC in high-risk patients in the ICU

Improving Ocean Color Data Coverage through Machine Learning

Oceanic chlorophyll-a concentration (Chl, mg m−3) maps derived from satellite ocean color measurements are the only data source which provides synoptic information of phytoplankton abundance on global scale. However, after excluding data collected under non-optimal observing conditions such as strong sun glint, clouds, thick aerosols, straylight, and large viewing angles, only ~5% of MODIS ocean measurements lead to valid Chl retrievals, regardless of the fact that about 25–30% of the global ocean is cloud free. A recently developed ocean color index (CI) is effective in deriving relative ocean color patterns under most non-optimal observing conditions to improve coverage, but these patterns cannot be interpreted as Chl. In this study, we combine the advantage of the high-quality, low-coverage Chl and lower-quality, higher-coverage CI to improve spatial and temporal coverage of Chl through machine learning, specifically via a random forest based regression ensemble (RFRE) approach. For every MODIS scene, the machine learning requires CI, Rayleigh-corrected reflectance (Rrc (λ = 469, 555, 645 nm), dimensionless), and high-quality low-coverage Chl from the common pixels where they all have valid data to develop an RFRE-based model to convert CI and Rrc (λ) to Chl. The model is then applied to all valid CI pixels of the same scene to derive Chl. This process is repeated for each scene, and the model parameterization is optimized for each scene independently. The approach has been tested for the Yellow Sea and East China Sea (YSECS) where non-optimal observing conditions frequently occur. Validations using extensive field measurements and image-based statistics for 2017 show very promising results, where coverage in the new Chl maps is increased by ~3.5 times without noticeable degradation in quality as compared with the original Chl data products. The improvement in Chl coverage without compromising data quality is not only critical in revealing otherwise unknown bloom patterns, but also important in reducing uncertainties in time-series analysis. Tests of the RFRE approach for several other regions such as the East Caribbean, Arabian Sea, and Gulf of Mexico suggest its general applicability in improving Chl coverage of other regions

Foliar Fertilizer Application Alters the Effect of Girdling on the Nutrient Contents and Yield of <i>Camellia oleifera</i>

Improving the economic benefits of Camellia oleifera is a major problem for C. oleifera growers, and girdling and foliar fertilizer have significant effects on improving the economic benefits of plants. This study explains the effects of girdling, girdling + foliar fertilizer on nutrient distribution, and the economic benefits of C. oleifera at different times. It also explains the N, P, and K contents of roots, leaves, fruits, and flower buds (sampled in March, May, August, and October 2021) and their economic benefits. The results showed girdling promoted the accumulation of N and K in leaves in March 2021 (before spring shoot emergence) but inhibited the accumulation of P, which led to the accumulation of P in roots and that of N in fruits in August 2021 (fruit expansion period). Foliar fertilizer application after girdling replenished the P content of leaves in March 2021, and P continued to accumulate in large quantities at the subsequent sampling time points. The N and P contents of the root system decreased in March. In October (fruit ripening stage), girdled shrubs showed higher contents of N and K in fruits and flower buds, and consequently lower relative contents of N and K in roots and leaves but higher content of P in leaves. Foliar fertilizer application slowed down the effects of girdling on nutrient accumulation in fruits and flower buds. Spraying foliar fertilizer decreased the N:P ratio in the flower buds and fruits of girdled plants. Thus, foliar fertilizer spray weakened the effects of girdling on the nutrient content and economic benefits of C. oleifera. In conclusion, girdling changed the nutrient accumulation pattern in various organs of C. oleifera at different stages, increased leaf N:K ratio before shoot emergence, reduced root K content at the fruit expansion stage and the N:K ratio of mature fruit, and promoted economic benefits