Membrane processes for water and wastewater treatment (study and modeling of interactions between membrane and organic matter)

L objectif de cette thèse est de mettre en évidence le comportement à l échelle microscopique des composés organiques au cours des procédés de traitement de mélanges complexes, en particulier les procédés membranaires. Pour cela des outils expérimentaux et de modélisation ont été mis au point. Les méthodes de caractérisation expérimentale des mélanges complexes et de l état de surface des solides utilisés sont entre autres la construction d isothermes d adsorption et la mesure des tensions interfaciales par la méthode de la goutte posée. Le cas étudié ici est celui de la filtration de solutions modèles de tensioactifs par osmose inverse. Nous avons montré que le comportement des composés organiques (tensioactifs) influence la performance du procédé membranaire et les propriétés de membranes. L outil de simulation du comportement des composés en phase liquide et à l interface liquide-solide permettant une description à une échelle plus fine que celle atteignable expérimentalement est la DPD (Dissipative Particle Dynamics). Une première étape a permis de simuler l agrégation des tensioactifs en solution et de retrouver les valeurs expérimentales des concentrations micellaires critiques et nombres d agrégation de tensioactifs anioniques. L étude de l adsorption des tensioactifs sur une membrane d osmose inverse a été initiée, avec pour objectif de mettre en évidence l organisation des composés à l échelle locale. L apport des outils développés a été démontré et leur utilisation pourra être approfondie dans des travaux ultérieurs.The aim of this work is a better understanding of the microscopic behavior of organic matters during the wastewater treatment of complex mixtures, especially during the membrane processes. Both experimental and simulation methods were developed in this work. Experimentally, adsorption isotherms were built to study the adsorption of organic matters on the membrane surface during the filtration. The sessile drop measurement allowed investigating the surface properties (interfacial tensions) of the membrane. After the filtration of surfactants by reverse osmosis (RO), we found that the surfactants played an important role in the performance and the surface properties of the RO membrane. The DPD (Dissipative Particle Dynamics) simulation method was used to model the behavior of anionic surfactants in solution and at the solid/liquid interface from a more detailed aspect than experiments. Firstly, the micellization of three anionic surfactants in aqueous solution was simulated and the model was validated by comparing the equilibrium properties (the critical micelle concentration and aggregation number) of micelle solutions obtained from simulation to the experimental values in literature. Then the model was extended to simulate the adsorption of surfactants on the RO membrane. The construction of a system with a membrane was initiated, and the study on the organizations of surfactants at the membrane surface opens a door to further active research.CHATENAY MALABRY-Ecole centrale (920192301) / SudocSudocFranceF

COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks

Pruning refers to the elimination of trivial weights from neural networks. The sub-networks within an overparameterized model produced after pruning are often called Lottery tickets. This research aims to generate winning lottery tickets from a set of lottery tickets that can achieve similar accuracy to the original unpruned network. We introduce a novel winning ticket called Cyclic Overlapping Lottery Ticket (COLT) by data splitting and cyclic retraining of the pruned network from scratch. We apply a cyclic pruning algorithm that keeps only the overlapping weights of different pruned models trained on different data segments. Our results demonstrate that COLT can achieve similar accuracies (obtained by the unpruned model) while maintaining high sparsities. We show that the accuracy of COLT is on par with the winning tickets of Lottery Ticket Hypothesis (LTH) and, at times, is better. Moreover, COLTs can be generated using fewer iterations than tickets generated by the popular Iterative Magnitude Pruning (IMP) method. In addition, we also notice COLTs generated on large datasets can be transferred to small ones without compromising performance, demonstrating its generalizing capability. We conduct all our experiments on Cifar-10, Cifar-100 & TinyImageNet datasets and report superior performance than the state-of-the-art methods

Reserve Allocation in Active Distribution Systems for Tertiary Frequency Regulation: A Coalitional Game Theory-based Approach

This paper proposes a coalitional game theory-based approach for reserve optimization to enable DERs participate in tertiary frequency regulation. A two-stage approach is proposed to effectively and precisely allocate spinning reserve requirements from each DER in distribution systems. In the first stage, two types of characteristic functions: worthiness index (WI) and power loss reduction (PLR) of each coalition are computed. In the second stage, the equivalent Shapley values are computed based on the characteristic functions, which are used to determine distribution factors for reserve allocation among DERs

Investigation of Biochemical Alterations in Ischemic Stroke Using Fourier Transform Infrared Imaging Spectroscopy-A Preliminary Study.

Brain damage, long-term disability and death are the dreadful consequences of ischemic stroke. It causes imbalance in the biochemical constituents that distorts the brain dynamics. Understanding the sub-cellular alterations associated with the stroke will contribute to deeper molecular understanding of brain plasticity and recovery. Current routine approaches examining lipid and protein biochemical changes post stoke can be difficult. Fourier Transform Infrared (FTIR) imaging spectroscopy can play a vital role in detecting these molecular alterations on a sub-cellular level due to its high spatial resolution, accuracy and sensitivity. This study investigates the biochemical and molecular changes in peri-infract zone (PIZ) (contiguous area not completely damaged by stroke) and ipsi-lesional white matter (WM) (right below the stroke and PIZ regions) nine weeks post photothrombotic ischemic stroke in rats. FTIR imaging spectroscopy and transmission electron microscopy (TEM) techniques were applied to investigate brain tissue samples while hematoxylin and eosin (H&E) stained images of adjacent sections were prepared for comparison and examination the morphological changes post stroke. TEM results revealed shearing of myelin sheaths and loss of cell membrane, structure and integrity after ischemic stroke. FTIR results showed that ipsi-lesional PIZ and WM experienced reduction in total protein and total lipid content compared to contra-lesional hemisphere. The lipid/protein ratio reduced in PIZ and adjacent WM indicated lipid peroxidation, which results in lipid chain fragmentation and an increase in olefinic content. Protein structural change is observed in PIZ due to the shift from random coli and α-helical structures to β-sheet conformation. FTIR imaging bio-spectroscopy provide novel biochemical information at sub-cellular levels that be difficult to be obtained by routine approaches. The results suggest that successful therapeutic strategy that is based on administration of anti-oxidant therapy, which could reduce and prevent neurotoxicity by scavenging the lipid peroxidation products. This approach will mitigate tissue damage in chronic ischemic period. FTIR imaging bio-spectroscopy can be used as a powerful tool and offer new approach in stroke and neurodegenerative diseases research

Water level forecasting using spatiotemporal attention-based long short-term memory network

Bangladesh is in the floodplains of the Ganges, Brahmaputra, and Meghna River delta, crisscrossed by an intricate web of rivers. Although the country is highly prone to flooding, the use of state-of-the-art deep learning models in predicting river water levels to aid flood forecasting is underexplored. Deep learning and attention-based models have shown high potential for accurately forecasting floods over space and time. The present study aims to develop a long short-term memory (LSTM) network and its attention-based architectures to predict flood water levels in the rivers of Bangladesh. The models developed in this study incorporated gauge-based water level data over 7 days for flood prediction at Dhaka and Sylhet stations. This study developed five models: artificial neural network (ANN), LSTM, spatial attention LSTM (SALSTM), temporal attention LSTM (TALSTM), and spatiotemporal attention LSTM (STALSTM). The multiple imputation by chained equations (MICE) method was applied to address missing data in the time series analysis. The results showed that the use of both spatial and temporal attention together increases the predictive performance of the LSTM model, which outperforms other attention-based LSTM models. The STALSTM-based flood forecasting system, developed in this study, could inform flood management plans to accurately predict floods in Bangladesh and elsewhere

Observed variability in physical and biogeochemical parameters in the central Arabian Gulf

In situ measurements of physical and biogeochemical variables were conducted along a transect in the Exclusive Economic Zone (EEZ) of Qatar during late summer (September 2014) and winter (January 2015) to investigate their vertical, spatial and temporal variability. The study reveals that the water column is characterized by strong stratification during late summer in the deepest station, where the water depth is around 65 m and the surface to bottom temperature variation is around 9.1°C. The water column is vertically homogeneous during winter due to surface cooling and wind mixing. The surface to 23 m water column is characterized by ample dissolved oxygen (DO) during late summer and winter in the offshore regions, however, relatively low DO is found during late summer due to weak mixing and advection under weak winds and currents. Dissolved oxygen drops to hypoxic levels below the summer thermocline, and the winter high DO layer extends up to the bottom. Chlorophyll-a (Chl-a) is relatively high during late summer in the offshore region, while that in the nearshore regions is very low, which is linked to the anthropogenic stresses from the central east coast of Qatar. The results identified in this study fill an essential gap in the knowledge of regional primary production dynamics.Environmental Science Center (ESC) & Department of Biological and Environmental Sciences (DBES), Qatar University (QU

New nitroindazole-porphyrin conjugates: synthesis, characterization and antibacterial properties

The synthesis of new porphyrin-indazole hybrids by a Knoevenagel condensation of 2-formyl-5,10,15,20-tetraphenylporphyrin and N-methyl-nitroindazolylacetonitrile derivatives is reported. The target compounds were isolated in moderate to good yields (32-57%) and some of the isolated porphyrin-indazole conjugates showed good performance in the generation of singlet oxygen when irradiated with visible light. Their efficiency as photosensitizers in the photoinactivation of methicillin resistant Staphylococcus aureus-MRSA was evaluated. All derivatives showed to be able to photoinactivate the MRSA bacteria. Compound 3a appears to be the most promising photosensitiser (PS) in the photoinactivation of these bacteria, despite being the least efficient in singlet oxygen generation. The addition of potassium iodide (KI) significantly potentiated the antimicrobial Photodynamic Therapy (aPDT) process mediated by all the analysed porphyrin-indazole conjugates. The combined action of nitroindazole-porphyrins with potassium iodide (KI) action appears to be promising in the photoinactivation of MRSA.publishe

Biosynthesis of silver nanoparticles from Cymbopogon citratus leaf extract and evaluation of their antimicrobial properties

Background: Silver nanoparticles (AgNPs) are toxic to microorganisms and can potentially kill multidrug-resistant bacteria. Nanoparticles can be synthesized in many ways, such as physical or chemical methods. Recently, it has been found that plant molecules can perform the same reduction reactions necessary for the production of nanoparticles but in a much more efficient way. Results: Here, green chemistry was employed to synthesize AgNPs using leaf extracts of Cymbopogon citratus. The effects of different parameters such as temperature, pH, and the volume of plant extract were also tested using their absorbance pattern at different wavelengths. The Surface Plasmon Resonance (SPR) changed with the changes in parameters. Changes in temperature from 20 °C to 60 °C have changed the highest absorbance from 0.972 to 3.893 with an SPR of 470 nm. At higher pH (11.1), the particles become highly unstable and have irregular shapes and sizes. The peak shifts to the right at a lower pH level (3.97), indicating a smaller but unstable compound. We have also investigated the effect of the volume of plant extracts on the reaction time. The sample with the highest amount of plant extract showed the most absorbance with a value of 0.963 at λmax, calculated to be 470 nm. The total formation of the AgNPs was observed visually with a color change from yellow to brownish-black. UV-visible spectroscopy was used to monitor the quantitative formation of AgNPs, showing a signature peak in absorbance between 400 and 500 nm. We have estimated the size of the nanoparticles as 47 nm by comparing the experimental data with the theoretical value using Mieplot. The biosynthesized AgNPs showed enhanced antibacterial activity against several multidrug-resistant bacteria, determined based on the minimal inhibitory concentration and zone of inhibition. Conclusion: The findings of this study indicate that an aqueous extract of C. citratus can synthesize AgNPs when silver nitrate is used as a precursor, and AgNPs act as antimicrobial property enhancers, which can be used to treat antibiotic-resistant bacteria. Hence, mass production and green synthesis of AgNPs from C. citratus will be able to increase the overall health of the general population. Moreover, it will enormously reduce the costs for drug development and provide employment options in the remotely located source areas. Finally, our findings will influence further studies in this field to better understand the properties and applications of AgNPs and ultimately contribute to improving planetary health by increasing immunity with high biocompatibility and less drug toxicity

A multi-targeted approach to suppress tumor-promoting inflammation

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-κB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes

Decisionmakers' Allocation of Physical Therapy and Occupational Therapy Services in Ontario Homecare

Hospital stays have grown increasingly shorter with a corresponding increase in the use of homecare services. However, we have a limited understanding of how homecare services are allocated in Ontario, particularly homecare rehabilitation services. The primary objective of this research is to explore the current decision-making processes for the allocation of occupational and physical therapy services in homecare for the long stay clients. To address this objective a exploratory study using key informant interviews was conducted. The results indicate that the process of decision making for the allocation of therapy services is comprised of a series of stages called intake, assessment, referral to service provider and reassessment. Amongst these the process of determining the volume of therapy services varies widely across different region. These variations are primarily due to the regional contextual (e.g. financial constraints) factors of the individual CCACs.MAS