Insights into the roles of recently developed coagulants as pretreatment to remove effluent organic matter for membrane fouling mitigation

© 2018 Elsevier B.V. Membrane fouling by dissolved organic matter (EfOM) in secondary treated effluent is a problematic and inevitable issue during wastewater reclamation using low pressure membrane filtration. This study evaluates the performance of coagulation/flocculation (C/F) using two recently developed coagulants (namely TiCl4 and ZrCl4) in comparison to conventional alum (i.e. Al2(SO4)3) as pretreatment to remove EfOM for subsequent ultrafiltration (UF) membrane fouling mitigation. At the optimal dosage, TiCl4-based C/F pretreatment showed the greatest performance in membrane fouling mitigation, followed by ZrCl4 and then alum. The underlying mechanisms were well explained by classical fouling models and the extended Derjaguin-Landau-Verwey-Overbeek (xDLVO) theory, highlighting a dominant role of standard blocking in the fouling potential of the C/F treated EfOM. The interfacial free energy of cohesion and adhesion showed that C/F pretreatment using TiCl4 and ZrCl4 as coagulant can lower the binding affinity between EfOM molecules and between EfOM molecules and membrane surface, ultimately reduce membrane fouling. The results of size exclusion chromatography (SEC) and fluorescence excitation emission matrix- parallel factor analysis (EEM-PARAFAC) also supported the classical fouling mechanisms, providing additional insights into the potential roles of chemical interactions in the preferential removal of certain organic substances by C/F pretreatment and the chemical composition of subsequent membrane foulants. Protein-like components were highly associated with reversible fouling after the C/F, while the reversibility of humic-like substances was enhanced upon C/F pretreatment. After C/F pretreatment, small sized EfOM molecules became the dominant fraction responsible for UF membrane fouling

Reiterating Visibility: Canadian Librarians’ Experiences of Racial Microaggressions via Findings from a Minority Librarians Network Redux Survey

Based on the data from the Visible Minority Librarians of Canada 2021 Redux Survey, this study examines experiences of racial microaggressions among visible minority librarians in Canada. This research fills the gap in the library and information science (LIS) literature regarding racial microaggressions in librarianship in the Canadian context. Of the 148 respondents, 69% (n=102) experienced at least one stated racial microaggression. The result of a Kruskal-Wallis H test revealed a significant association between years of experience as a librarian and a librarian’s overall experiences with microaggressions. A post hoc test based on Bonferroni correction was run, which indicated that librarians with less than five years of work experience encountered microaggressions less frequently compared to those with 11–15 years of experience. For the ten stated types of racial microaggressions, the most frequently reported type was “I was told that people of all racial groups face the same barriers in employment or promotion,” and the least frequently reported type was “A colleague claimed that he/she felt threatened because of my race.” Fisher\u27s exact tests were further performed to examine how the respondents differed in their experiences of each microaggression. The test results revealed that the librarians with different personal attributes (ethnicity, disability status, gender identity, language used) and employment attributes (librarian experience, management position, library type) had significantly different encounters with eight forms of microaggression. Professional library associations and libraries must strengthen education about racial microaggressions and offer support to visible minority librarians when they are confronted with microaggressive behaviours

Changes in the Library Landscape Regarding Visible Minority Librarians in Canada

As a follow-up to the first 2013 survey, the Visible Minority Librarians of Canada (ViMLoC) network conducted its second comprehensive survey in 2021. The 2021 survey gathered detailed information about the demography, education, and employment of visible minority librarians (VMLs) working in Canadian institutions. 162 VMLs responded to the 2021 survey, 35% up from the 2013 survey. Changes occurred in ethnic identity, generation, where VMLs earned a Master of Library and Information Science (MLIS) or equivalent degree, library type, geographic location, and job responsibilities. The 2021 survey also explored other aspects of the VMLs not covered in the 2013 survey, such as librarian experience, salary, management positions, and mentorship experience. The research findings will help us better understand the current library landscape and help professional associations and library administrators to develop initiatives to support VMLs

Up-regulation of brain-derived neurotrophic factor in primary afferent pathway regulates colon-to-bladder cross-sensitization in rat

Background In humans, inflammation of either the urinary bladder or the distal colon often results in sensory cross-sensitization between these organs. Limited information is known about the mechanisms underlying this clinical syndrome. Studies with animal models have demonstrated that activation of primary afferent pathways may have a role in mediating viscero-visceral cross-organ sensitization. Methods Colonic inflammation was induced by a single dose of tri-nitrobenzene sulfonic acid (TNBS) instilled intracolonically. The histology of the colon and the urinary bladder was examined by hematoxylin and eosin (H&E) stain. The protein expression of transient receptor potential (TRP) ion channel of the vanilloid type 1 (TRPV1) and brain-derived neurotrophic factor (BDNF) were examined by immunohistochemistry and/or western blot. The inter-micturition intervals and the quantity of urine voided were obtained from analysis of cystometrograms. Results At 3 days post TNBS treatment, the protein level of TRPV1 was increased by 2-fold (p \u3c 0.05) in the inflamed distal colon when examined with western blot. TRPV1 was mainly expressed in the axonal terminals in submucosal area of the distal colon, and was co-localized with the neural marker PGP9.5. In sensory neurons in the dorsal root ganglia (DRG), BDNF expression was augmented by colonic inflammation examined in the L1 DRG, and was expressed in TRPV1 positive neurons. The elevated level of BDNF in L1 DRG by colonic inflammation was blunted by prolonged pre-treatment of the animals with the neurotoxin resiniferatoxin (RTX). Colonic inflammation did not alter either the morphology of the urinary bladder or the expression level of TRPV1 in this viscus. However, colonic inflammation decreased the inter-micturition intervals and decreased the quantities of urine voided. The increased bladder activity by colonic inflammation was attenuated by prolonged intraluminal treatment with RTX or treatment with intrathecal BDNF neutralizing antibody. Conclusion Acute colonic inflammation increases bladder activity without affecting bladder morphology. Primary afferent-mediated BDNF up-regulation in the sensory neurons regulates, at least in part, the bladder activity during colonic inflammation

Exploring potential machine learning application based on big data for prediction of wastewater quality from different full-scale wastewater treatment plants.

Water pollution generated from intensive anthropogenic activities has emerged as a critical issue concerning ecosystem balance and livelihoods worldwide. Although optimizing wastewater treatment efficiency is widely regarded as the foremost step to minimize pollutants released into the environment, this widespread application has encountered two major problems: firstly, the significant variation of influent wastewater constituents; secondly, complex treatment processes within wastewater treatment plants (WWTPs). Based on the data collected hourly using real-time sensors in three different full-scale WWTPs (24 h × 365 days × 3 WWTPs × 10 wastewater parameters), this work introduced the potential application of Machine Learning (ML) to predict wastewater quality. In this work, six different ML algorithms were examined and compared, varying from shallow to deep learning architectures including Seasonal Autoregressive Integrated Moving Average (SARIMAX), Random Forest (RF), Support Vector Machine (SVM), Gradient Tree Boosting (GTB), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Long Short-Term Memory (LSTM). These models were developed to detect total phosphorus in the outlet (Outlet-TP), which served as an output variable due to the rising concerns about the eutrophication problem. Irrespective of WWTPs, SARIMAX consistently demonstrated the best performance for regression estimation as evidenced by the lowest values of Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the highest coefficient of determination (R2). In terms of computation efficiency, SARIMAX exhibited acceptable time computation, acknowledging the successful application of this algorithm for Outlet-TP modeling. In contrast, the complex structure of LSTM made it time-consuming and unstable coupled with noise, while other shallower architectures, i.e., RF, SVM, GTB, and ANFIS were unable to address large datasets with nonlinear and nonstationary behavior. Consequently, this study provides a reliable and accurate approach to forecast wastewater effluent quality, which is pivotal in terms of the socio-economic aspects of wastewater management

Nature's lessons in design: nanomachines to scaffold, remodel and shape membrane compartments.

Compartmentalisation of cellular processes is fundamental to regulation of metabolism in Eukaryotic organisms and is primarily provided by membrane-bound organelles. These organelles are dynamic structures whose membrane barriers are continually shaped, remodelled and scaffolded by a rich variety of highly sophisticated protein complexes. Towards the goal of bottom-up assembly of compartmentalised protocells in synthetic biology, we believe it will be important to harness and reconstitute the membrane shaping and sculpting characteristics of natural cells. We review different in vitro membrane models and how biophysical investigations of minimal systems combined with appropriate theoretical modelling have been used to gain new insights into the intricate mechanisms of these membrane nanomachines, paying particular attention to proteins involved in membrane fusion, fission and cytoskeletal scaffolding processes. We argue that minimal machineries need to be developed and optimised for employment in artificial protocell systems rather than the complex environs of a living organism. Thus, well-characterised minimal components might be predictably combined into functional, compartmentalised protocellular materials that can be engineered for wide-ranging applications

Milk oligosaccharides: a review

Milk oligosaccharides (OSs) confer unique health benefits to the neonate. Although human digestive enzymes cannot degrade these sugars, they support specific commensal microbes and act as decoys to prevent the adhesion of pathogenic micro-organisms to gastrointestinal cells. The limited availability of human milk oligosaccharides (HMOs) impedes research into these molecules and their potential applications in functional food formulations. Recent studies show that complex OSs with fucose and N-acetyl neuraminic acid (key structural elements of HMO bioactivity) also exist in caprine milk, suggesting a potential source of bioactive milk OSs suitable as a functional food ingredient

Total synthesis of Escherichia coli with a recoded genome

Nature uses 64 codons to encode the synthesis of proteins from the genome, and chooses 1 sense codon—out of up to 6 synonyms—to encode each amino acid. Synonymous codon choice has diverse and important roles, and many synonymous substitutions are detrimental. Here we demonstrate that the number of codons used to encode the canonical amino acids can be reduced, through the genome-wide substitution of target codons by defined synonyms. We create a variant of Escherichia coli with a four-megabase synthetic genome through a high-fidelity convergent total synthesis. Our synthetic genome implements a defined recoding and refactoring scheme—with simple corrections at just seven positions—to replace every known occurrence of two sense codons and a stop codon in the genome. Thus, we recode 18,214 codons to create an organism with a 61-codon genome; this organism uses 59 codons to encode the 20 amino acids, and enables the deletion of a previously essential transfer RNA

A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands

10.1371/journal.pone.0039076PLoS ONE76

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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