Thin-film nanocomposite membranes for efficient removal of emerging pharmaceutical organic contaminants from water.

Membranes are receiving significant attention to remove emerging organic micropollutants (OMPs) from wastewater and natural water sources. Herein, we report the facile preparation of a novel thin-film nanocomposite (TFN) membrane with high permeability and efficient removal of OMPs. ZnO nanoparticles were first synthesized using the co-precipitation method and functionalized with N1-(3-Trimethoxysilylpropyl)diethylenetriamine to make the surface rich with amine groups and then synthesized nanomaterials were covalently cross-linked into the active layer during the interfacial polymerization (IP) process. The performance of the membranes containing the cross-linked ZnO was significantly better than the non-cross-linked ZnO NPs containing membranes. Adding multiple hydrophilic groups and entities on the surface significantly decreased the contact angle (from ∼60° to 20°). SEM images confirmed the uniform presence and homogeneous distribution of the functionalized NPs throughout the entire membrane surface. Zeta potential measurements showed the modified membranes have a lower negative charge than the pristine membranes. Filtration studies revealed a significant increase in permeability ascribed to the creation of nanochannels in the membrane's active layer. The modified membranes outperformed commercial NF membranes in removing four common OMPs with rejection efficiencies of ∼30%, 64%, 60%, and 70% for Sulfamethoxazole, Amitriptyline, Omeprazole, and Loperamide HCl, respectively. The higher removal efficiency was attributed to the weakened hydrophobic interactions due to the presence of hydrophilic moieties and a stronger size exclusion effect. Moreover, the modified membranes showed high resistance to bacterial adhesion in static conditions.

Evaluating dye recovery and reusability potential from dyebath effluent using forward osmosis membranes for minimum liquid discharge.

This study focuses on the evaluation of dye recovery and reuse potential from denim and polyester effluents using forward osmosis (FO). A cationic surfactant, tetraethylammonium bromide (TEAB), was used as the draw solution (DS). After optimizing the DS and feed solution (FS) concentrations and temperatures in batch experiments, a DS concentration of 0.75 M was selected at a 60 °C temperature for the semi-continuous mode. It generated a high flux of 18 L/m2/h and a low reverse solute flux (RSF) of 0.4 g/m2/h with 100% dye rejection. Dye reconcentration of 82-98% was achieved in the dyebath effluents. The unique property of surfactants to combine hundreds of monomers into micelle resulted in negligible RSF. Reversible fouling was observed on the membrane active layer, and NaOH and citric acid cleaning achieved about 95% of flux recovery. The functional groups on the membrane's active layer remained undisturbed due to foulant interactions showing its chemical stability against reactive dyes. Recovered dye characterization using 1D proton nuclear magnetic resonance (1HNMR) analysis depicted a 100% structural resemblance to the original dye. Hence, it can be reused for dyeing the next batch. Diluted TEAB solution can be used as fabric detergent and softener within the same textile industry in the finishing process. A minimum liquid and persistent pollutant (dyes) discharge is achieved by adopting the methodology proposed in this work with a strong potential of translating it to an industrial scale.

Recovering and reuse of textile dyes from dyebath effluent using surfactant driven forward osmosis to achieve zero hazardous chemical discharge.

This experimental study explores the feasibility of the reuse of dyes recovered from denim and polyester dyebath effluents using forward osmosis (FO) system to achieve zero hazardous material discharge. In batch experiments, the sodium dodecyl sulfate (SDS) at 0.5 M concentration generated an average flux of 3.5 L/m2/h (LMH) and reverse salt flux (RSF) of only 0.012 g/m2/h (GMH), while maintaining 100% dye rejection. This flux stability comes from the property of surfactants to form micelles and exert a stable osmotic pressure (π) above their critical micelle concentration (CMC). The low RSF is due to the greater micelle size. A colored fouling layer was formed on the membrane active layer (AL), which was easily removed using sodium hydroxide (NaOH) and citric acid. According to Fourier transform infrared spectra and atomic forces microscopy images of the AL, the interaction between foulants and membrane active groups did not significantly affect the physiochemical properties of the membrane. In the semi-continuous experiment, a very stable average flux of 7.3 LMH and RSF of 0.03 GMH was obtained using 0.75 M SDS as draw solution. The stacked 1D proton nuclear magnetic resonance analysis (1HNMR) spectra of both original and recovered disperse dyes showed 100% similarity, which validates the concept that the recovered dyes maintained their integrity during reconcentration and can be reused in the next batch dyeing process. Importantly, the diluted SDS concentration can be directly reused within the same textile industry in scouring and finishing processes. The processes of dye recovery and reuse developed in this study do not produce any waste or hazardous by-products and are suitable for scale-up and onsite industrial applications.

Intelligent breast cancer diagnostic system empowered by deep extreme gradient descent optimization.

Cancer is a manifestation of disorders caused by the changes in the body's cells that go far beyond healthy development as well as stabilization. Breast cancer is a common disease. According to the stats given by the World Health Organization (WHO), 7.8 million women are diagnosed with breast cancer. Breast cancer is the name of the malignant tumor which is normally developed by the cells in the breast. Machine learning (ML) approaches, on the other hand, provide a variety of probabilistic and statistical ways for intelligent systems to learn from prior experiences to recognize patterns in a dataset that can be used, in the future, for decision making. This endeavor aims to build a deep learning-based model for the prediction of breast cancer with a better accuracy. A novel deep extreme gradient descent optimization (DEGDO) has been developed for the breast cancer detection. The proposed model consists of two stages of training and validation. The training phase, in turn, consists of three major layers data acquisition layer, preprocessing layer, and application layer. The data acquisition layer takes the data and passes it to preprocessing layer. In the preprocessing layer, noise and missing values are converted to the normalized which is then fed to the application layer. In application layer, the model is trained with a deep extreme gradient descent optimization technique. The trained model is stored on the server. In the validation phase, it is imported to process the actual data to diagnose. This study has used Wisconsin Breast Cancer Diagnostic dataset to train and test the model. The results obtained by the proposed model outperform many other approaches by attaining 98.73 % accuracy, 99.60% specificity, 99.43% sensitivity, and 99.48% precision.

Intelligent Cardiovascular Disease Prediction Empowered with Gradient Descent Optimization.

Disorders of the heart and blood vessels are named cardiovascular disease. 'The heart's proper functionality is of an utmost necessity for the survival of life. The death rate due to heart disease, has been increased rapidly. Cardiovascular illness is believed the deadliest cause of death across the globe. From the facts and figures shared by the WHO (World Health Organization) 17.9 Million human lost their lives due to cardiovascular diseases. This research is carried out for the effective diagnosis of heart disease using the heart disease dataset available on the UCI Machine Repository. Heart disease diagnosis with an optimization algorithm can be fruitful in terms of higher accuracy and sensitivity. Finding an acceptable optimal solution among multiple solutions for a specific problem is known as optimization. Different machine learning algorithms have been applied as Support Machine Vector (SVM), K-Nearest Neighbor (KNN), Naïve Bayes (NB), Artificial Neural Network (ANN), Random Forest (RF), and Gradient Descent Optimization (GDO). Intelligent Cardiovascular Disease Prediction Empowered with Gradient Descent Optimization model produces the optimal results among under consideration classification algorithms. 98.54 % accuracy has been achieved by the GDO based model while performance evaluation it. 99.43% sensitivity (recall) and 97.76% precision have also been recorded. From the prediction results of the system, it's satisfactory to utilize it for cardiovascular disease diagnosis. The proposed system will be helpful for the analysis of cardiovascular disease.

Investigation of flux stability and fouling mechanism during simultaneous treatment of different produced water streams using forward osmosis and membrane distillation.

Forward osmosis-membrane distillation (FO-MD) hybrids were recently found suitable for produced water treatment. Exclusion of synthetic chemical draw solutions, typically used for FO, can reduce FO-MD operational costs and ease its onsite application. This study experimentally validates a novel concept for the simultaneous treatment of different produced water streams available at the same industrial site using an FO-MD hybrid system. The water oil separator outlet (WO) stream was selected as FO draw solution and it generated average fluxes ranging between 8.30 LMH and 26.78 LMH with four different feed streams. FO fluxes were found to be governed by the complex composition of the feed streams. On the other hand, with WO stream as MD feed, an average flux of 14.41 LMH was achieved. Calcium ions were found as a main reason for MD flux decline in the form of CaSO4 scaling and stimulating the interaction between the membrane and humic acid molecules to form scale layer causing reduction in heat transfer and decline in MD flux (6%). Emulsified oil solution was responsible for partial pore clogging resulting in further 2% flux decline. Ethylenediaminetetraaceticacid (EDTA) was able to mask a portion of calcium ions and resulted in a complete recovery of the original MD flux. Under hybrid FO-MD experiments MD fluxes between 5.62 LMH and 11.12 LMH were achieved. Therefore, the novel concept is validated to produce fairly stable FO and MD fluxes, with few streams, without severe fouling and producing excellent product water quality.

Molecular evolutionary and structural analysis of human UCHL1 gene demonstrates the relevant role of intragenic epistasis in Parkinson's disease and other neurological disorders.

BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disorder. PD associated human UCHL1 (Ubiquitin C-terminal hydrolase L1) gene belongs to the family of deubiquitinases and is known to be highly expressed in neurons (1-2% in soluble form). Several functions of UCHL1 have been proposed including ubiquitin hydrolyze activity, ubiquitin ligase activity and stabilization of the mono-ubiquitin. Mutations in human UCHL1 gene have been associated with PD and other neurodegenerative disorders. The present study aims to decipher the sequence evolutionary pattern and structural dynamics of UCHL1. Furthermore, structural and interactional analysis of UCHL1 was performed to help elucidate the pathogenesis of PD. RESULTS: The phylogenetic tree topology suggests that the UCHL1 gene had originated in early gnathostome evolutionary history. Evolutionary rate analysis of orthologous sequences reveals strong purifying selection on UCHL1. Comparative structural analysis of UCHL1 pinpoints an important protein segment spanning amino acid residues 32 to 39 within secretion site with crucial implications in evolution and PD pathogenesis through a well known phenomenon called intragenic epistasis. Identified critical protein segment appears to play an indispensable role in protein stability, proper protein conformation as well as harboring critical interaction sites. CONCLUSIONS: Conclusively, the critical protein segment of UCHL1 identified in the present study not only demonstrates the relevant role of intraprotein conformational epistasis in the pathophysiology of PD but also offers a novel therapeutic target for the disease.

Insight into the effect of organic and inorganic draw solutes on the flux stability and sludge characteristics in the osmotic membrane bioreactor.

In this study, chloride based (CaCl2 and MgCl2) and acetate based (NaOAc and MgOAc) salts in comparison with NaCl were investigated as draw solutions (DS) to evaluate their viability in the osmotic membrane bioreactor (OMBR). Membrane distillation was coupled with an OMBR setup to develop a hybrid OMBR-MD system, for the production of clean water and DS recovery. Results demonstrate that organic DS were able to mitigate the salinity buildup in the bioreactor as compared to inorganic salts. Prolonged filtration runs were observed with MgCl2 and MgOAc in contrast with other draw solutes at the same molar concentration. Significant membrane fouling was observed with NaOAc while rapid flux decline due to increased salinity build-up was witnessed with NaCl and CaCl2. Improved characteristics of mixed liquor in terms of sludge filterability, particle size, and biomass growth along with the degradation of soluble microbial products (SMP) were found with organic DS.

Membrane fouling and performance evaluation of conventional membrane bioreactor (MBR), moving biofilm MBR and oxic/anoxic MBR.

In this study, three laboratory scale submerged membrane bioreactors (MBRs) comprising a conventional MBR (C-MBR), moving bed MBR (MB-MBR) and anoxic-oxic MBR (A/O-MBR) were continuously operated with synthesized domestic wastewater (chemical oxygen demand, COD = 500 mg/L) for 150 days under similar operational and environmental conditions. Kaldnes(®) plastic media with 20% dry volume was used as a biofilm carrier in the MB-MBR and A/O-MBR. The treatment performance and fouling propensity of the MBRs were evaluated. The effect of cake layer formation in all three MBRs was almost the same. However, pore blocking caused a major difference in the resultant water flux. The A/O-MBR showed the highest total nitrogen and phosphorus (PO4-P) removal efficiencies of 83.2 and 69.7%, respectively. Due to the high removal of nitrogen, fewer protein contents were found in the soluble and bound extracellular polymeric substances (EPS) of the A/O-MBR. Fouling trends of the MBRs showed 12, 14 and 20 days filtration cycles for C-MBR, MB-MBR and A/O-MBR, respectively. A 25% reduction of the soluble EPS and a 37% reduction of the bound EPS concentrations in A/O-MBR compared with C-MBR was a major contributing factor for fouling retardation and the enhanced filtration capacity of the A/O-MBR.