A practical approach to synthesize polyamide thin film nanocomposite (TFN) membranes with improved separation properties for water/wastewater treatment

TFN membranes containing 0.05 or 0.10 w/v% surface-functionalized TNTs in a PA selective layer were synthesized for better performances in water/wastewater treatment.</p

Improving ‘lipid productivity’ in microalgae by bilateral enhancement of biomass and lipid contents: A review

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Microalgae have received widespread interest owing to their potential in biofuel production. However, economical microalgal biomass production is conditioned by enhancing the lipid accumulation without decreasing growth rate or by increasing both simultaneously. While extensive investigation has been performed on promoting the economic feasibility of microalgal-based biofuel production that aims to increase the productivity of microalgae species, only a handful of them deal with increasing lipid productivity (based on lipid contents and growth rate) in the feedstock production process. The purpose of this review is to provide an overview of the recent advances and novel approaches in promoting lipid productivity (depends on biomass and lipid contents) in feedstock production from strain selection to after-harvesting stages. The current study comprises two parts. In the first part, bilateral improving biomass/lipid production will be investigated in upstream measures, including strain selection, genetic engineering, and cultivation stages. In the second part, the enhancement of lipid productivity will be discussed in the downstream measure included in the harvesting and after-harvesting stages. An integrated approach involving the strategies for increasing lipid productivity in up-and down-stream measures can be a breakthrough approach that would promote the commercialization of market-driven microalgae-derived biofuel production

Leptospirosis in American Samoa – Estimating and Mapping Risk Using Environmental Data

Leptospirosis is the most common bacterial infection transmitted from animals to humans. Infected animals excrete the bacteria in their urine, and humans can become infected through contact with animals or a contaminated environment such as water and soil. Environmental factors are important in determining the risk of human infection, and differ between ecological settings. The wide range of risk factors include high rainfall and flooding; poor sanitation and hygiene; urbanisation and overcrowding; contact with animals (including rodents, livestock, pets, and wildlife); outdoor recreation and ecotourism; and environmental degradation. Predictive risk maps have been produced for many infectious diseases to identify high-risk areas for transmission and guide allocation of public health resources. Maps are particularly useful where disease surveillance and epidemiological data are poor. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk. This study demonstrated the value of geographic information systems and disease mapping for identifying environmental risk factors for leptospirosis, and enhancing our understanding of disease transmission. Similar principles could be used to investigate the epidemiology of leptospirosis in other areas

A novel malaria vaccine candidate antigen expressed in Tetrahymena thermophila

Development of effective malaria vaccines is hampered by the problem of producing correctly folded Plasmodium proteins for use as vaccine components. We have investigated the use of a novel ciliate expression system, Tetrahymena thermophila, as a P. falciparum vaccine antigen platform. A synthetic vaccine antigen composed of N-terminal and C-terminal regions of merozoite surface protein-1 (MSP-1) was expressed in Tetrahymena thermophila. The recombinant antigen was secreted into the culture medium and purified by monoclonal antibody (mAb) affinity chromatography. The vaccine was immunogenic in MF1 mice, eliciting high antibody titers against both N- and C-terminal components. Sera from immunized animals reacted strongly with P. falciparum parasites from three antigenically different strains by immunofluorescence assays, confirming that the antibodies produced are able to recognize parasite antigens in their native form. Epitope mapping of serum reactivity with a peptide library derived from all three MSP-1 Block 2 serotypes confirmed that the MSP-1 Block 2 hybrid component of the vaccine had effectively targeted all three serotypes of this polymorphic region of MSP-1. This study has successfully demonstrated the use of Tetrahymena thermophila as a recombinant protein expression platform for the production of malaria vaccine antigens

Review: Identification of roadmap of fourth construction industrial revolution

Industrial revolution is a series of events driven by the growth of technological innovations, and so far, the world had witnessed the first three industrial revolutions. Today, a new revolution referred to as the fourth industrial revolution is entering even though it is still in its early stages of development. Many developed countries had established their own roadmap or strategic plan as a first step. However, only a few of them touched the construction sector even though the construction industry provides a significant contribution to the country’s GDP. Based on this understanding, there is a fundamental need to give a clear view of Industry 3.0 to Industry 4.0 from the construction industry’s perspective, since most users are still finding their way in this transition. An extensive literature review is used to define the scope and terms of the field of construction in the industrial revolution. Towards this goal, a clear definition and concept of each revolution, key technologies related to construction and challenges faced by the industry will be explored. Simultaneously, this review paper also benchmarked a few documents as a simple guide in the transition process to the fourth industrial revolution to avoid a lag in a world where changes are swift and sudden. Therefore, this review paper contributes by providing a better understanding of the challenges and trends in Construction 4.0 to academics and practitioners. Moreover, it will spark new ideas on the policy or strategic roadmap development in the future

A novel chemiluminescence assay of organophosphorous pesticide quinalphos residue in vegetable with luminol detection

<p>Abstract</p> <p>Background</p> <p>Organophosphorous pesticides are the most popular pesticides used in agriculture. As acetylcholinesterase inhibitors, organophosphorous pesticides are toxic organic chemicals. The control and detection of organophosphorous pesticide residue in food, water, and environment therefore plays a very important role in maintaining physical health. A sensitive, rapid, simple chemiluminescence(CL) method has been developed for the determination of quinalphos based on the reaction of quinalphos with luminol-H₂O₂in an alkaline medium. The method has been applied to detection of quinalphos in vegetable samples with satisfactory results.</p> <p>Results</p> <p>The CL method for the determination of organophosphorous pesticide quinalphos is based on the phenomenon that quinalphos can apparently enhance the CL intensity of the luminol-H₂O₂system. The optimal conditions were: luminol concentration 5.0 × 10^-4mol/L, H₂O₂concentration 0.05 mol/L.pH value 13. In order to restrain the interference from metal ions, 1.0 × 10^-3mol/L of EDTA was added to the luminol solution. The possible mechanism was proposed.</p> <p>Conclusion</p> <p>Under the optimum reaction conditions, CL was linear with the concentration of quinalphos in the range of 0.02 μg/mL -1.0 μg/mL and the detection limit was 0.0055 μg/mL (3σ). This method has been successfully applied to the detection of quinalphos in vegetable samples. According to the experimental data, the average recoveries for quinalphos in cherry tomato and green pepper 97.20% and 90.13%. Meanwhile, the possible mechanism was proposed.</p

Efficient control of atmospheric sulfate production based on three formation regimes

The formation of sulfate (SO₄²⁻) in the atmosphere is linked chemically to its direct precursor, sulfur dioxide (SO₂), through several key oxidation paths for which nitrogen oxides or NO_x (NO and NO₂) play essential roles. Here we present a coherent description of the dependence of SO₄²⁻ formation on SO₂ and NO_x under haze-fog conditions, in which fog events are accompanied by high aerosol loadings and fog-water pH in the range of 4.7–6.9. Three SO₄²⁻ formation regimes emerge as defined by the role played by NO_x. In the low-NO_x regime, NO_x act as catalyst for HO_x, which is a major oxidant for SO₂, whereas in the high-NO_x regime, NO₂ is a sink for HO_x. Moreover, at highly elevated NO_x levels, a so-called NO₂-oxidant regime exists in which aqueous NO₂ serves as the dominant oxidant of SO₂. This regime also exists under clean fog conditions but is less prominent. Sensitivity calculations using an emission-driven box model show that the reduction of SO₄²⁻ is comparably sensitive to the reduction of SO₂ and NO_x emissions in the NO₂-oxidant regime, suggesting a co-reduction strategy. Formation of SO₄²⁻ is relatively insensitive to NO_x reduction in the low-NO_x regime, whereas reduction of NO_x actually leads to increased SO₄²⁻ production in the intermediate high-NO_x regime

NMR metabolomic modeling of age and lifespan: A multicohort analysis.

Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age-related disease. Ninety-eight metabolic variables were measured in blood from nine UK and Finnish cohort studies (N ≈31,000 individuals, age range 24-86 years). We used nonlinear and penalized regression to model CA and time to all-cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank (N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type-2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all-cause mortality. Seven-fold cross-validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8-9 years). Metabolomic age models, adjusted for CA, were associated with C-reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest (r = 0.29-0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability