Gender, globalization and beyond in Karen Tei Yamashita's Tropic of Orange and Jhumpa Lahiri's The Interpreter of Maladies

Ce mémoire explore deux concepts majeurs : la mondialisation et la diaspora et leur impact sur la représentation des femmes dans la série de nouvelles The Interpreter of Maladies de Jhumpa Lahiri et dans le roman Tropic of Orange de Karen Tei Yamashita. Dans le premier chapitre, en s’appuyant sur la théorie de Vijay Mishra, Literature of the Indian Diaspora: Theorizing the Diasporic Imaginary, ce mémoire examinera l’état diasporique de Mrs. Sen à travers la notion de « deuil impossible ». Mrs. Sen sera juxtaposée à deux autres personnages féminins dans le but de démontrer que la mobilité et le passage des frontières n’affectent pas toutes les femmes de la même façon, surtout lorsqu’elles viennent de classes et de milieux sociaux différents. De plus, la condition de Mrs. Sen sera également comparée à celle de son mari pour soutenir que l’impact de l’immigration est plus bénéfique à lui qu’à elle. Ce mémoire repense donc certaines des raisons qui poussent les gens à migrer à travers le monde, ainsi qu’aux impacts de cette migration sur les individus, en particulier les femmes dont le déplacement limite souvent la mobilité, la liberté et l’indépendance. Dans le second chapitre, la théorie de Chandra Talpade Mohanty, Feminism without Borders, sera utilisée pour souligner les différences entre la femme occidentale et la femme dite du tiers monde. En outre, l’essai de Mohanty Under Western Eyes’ Revisited, qui condamne les effets néfastes du capitalisme et de la mondialisation pour promouvoir un projet social basé sur la solidarité, sera utilisé pour étudier la description d’Emi et de Rafaela, deux personnages centraux du roman de Yamashita, et ce, dans le contexte de la mondialisation et de ses opérations déviantes. C’est en tenant compte des modes opérationnels criminels et criminisalisant du capitalisme que la mondialisation sera analysée, et ce, à travers la complicité et la résistance des personnages féminins de Yamashita face au capitalisme global.This thesis explores two major concepts: globalization and diaspora and their impact on the literary representation of women in Jhumpa Lahiri’s collection of short stories The Interpreter of Maladies and Karen Tei Yamashita’s novel Tropic of Orange. In the first chapter, using Vijay Mishra’s theory on the Literature of the Indian Diaspora: Theorizing the Diasporic Imaginary, the thesis examines the diasporic state of Mrs. Sen through Mishra’s notion of “impossible mourning”. I juxtapose Mrs. Sen’s character to two other female characters to argue that mobility and crossing borders do not affect all women equally, especially if they come from different social class and caste backgrounds. In addition, I compare Mrs. Sen’s diasporic condition to her husband’s to contend that the impact of immigration is more beneficial to him than her. This thesis, hence, rethinks some of the reasons why people migrate across the world and its various impacts on individuals, especially women whose displacement often curtails rather than expands their mobility, freedom and independence. In the second chapter, therefore, I use Chandra Talpade Mohanty’s Feminism without Borders to highlight the difference between Western women and so-called Third World women. Furthermore, using Mohanty’s essay “‘Under Western Eyes’ Revisited,” which condemns the detrimental effects of capitalism and globalization and promotes an anti-capitalist and anti-global project based on solidarity, I study the characterization of Emi and Rafaela, two central characters of Yamashita’s novel, within the context of globalization and its deviant operations. Referring to the criminal and criminalizing operative modes of global capitalism, including organ and sex trafficking, deviant globalization is a critical concept in this thesis through which I read Yamashita’s novel and its female characters’ complicity with and resistance to global capitalism

Développement d'une régie de culture du safran (Crocus sativus) adaptée aux conditions climatiques québécoises

Le safran est un crocus d'automne qui produit une épice de grande valeur. Plusieurs safranières ont été implantées au cours des dernières années au Québec. Cependant, le type de sol et les conditions climatiques diffèrent passablement par rapport aux pays d'où origine la culture, ce qui nous a mené à tester plusieurs aspects susceptibles d'influencer le rendement en safran, notamment la profondeur et la période de plantation ainsi que l'application d'une combinaison de fertilisants, champignons mycorhiziens et biostimulants à la plantation. Puisque la température influence fortement la floraison chez le safran, un suivi en continu des températures du sol a été effectué durant toute l'année, et un suivi hebdomadaire de l'initiation florale de mai à août. L'émergence des feuilles et des fleurs est retardée et diminue avec la profondeur de plantation. Une plantation à 10 ou 15 cm semble préférable, mais stimule la production de cormes trop petits pour fleurir. La meilleure période de plantation est de la fin juillet jusqu'à la troisième semaine d'août. La fertilisation a accéléré l'émergence des feuilles à l'automne, et a augmenté le nombre de cormes produits ainsi que leur teneur en nutriments. L'ajout de spores de champignons mycorhiziens ainsi que de biostimulants n'a eu aucun effet sur la floraison ou le rendement en safran. Tout traitement confondu, la production de fleurs n'a été bonne qu'une seule année sur les trois années de l'étude. Il semble que le sol ne soit pas assez chaud en juillet lors de l'induction florale. De plus, dans le secteur à l'étude, les températures diminuent trop rapidement à l'automne ce qui retarde la floraison et réduit les rendements. Il est proposé de cultiver le safran dans des secteurs plus méridionaux et de recourir à des techniques visant à réchauffer le sol afin d'augmenter les rendements en safran au Québec.Saffron is an autumn crocus that produces a highly valuable spice. Several saffron farms have been established over recent years in the province of Quebec. However, the edaphic and climatic conditions differ considerably compared to the countries of origin of the crop, which led us to test several aspects that could influence the saffron yield, including planting depth and planting period as well as the application of a combination of fertilizers, mycorrhizal fungi and biostimulants at planting. Since temperature strongly influences saffron flowering, continuous monitoring of soil temperatures was carried out throughout the year, along with a weekly monitoring of flower initiation from May to August. Both leaf and flower emergence were delayed, and final emergence reduced as planting depth increased. Planting at 10 or 15 cm seems preferable but stimulates the production of corms too small to flower. The best planting period is from the end of July until the third week of August. Fertilization hastened leaf emergence in the autumn and improved corm production and their nutrient content. The addition of mycorrhizal fungal spores as well as biostimulants had no effect on flowering or saffron yield. All treatments combined; flower production was good in only one of the three study years. It seems that the soil does not warm enough in July during flower induction. Moreover, in the study area, temperatures drop too rapidly during autumn, which delays flowering and reduces yields. It is proposed to cultivate saffron in more southern areas and to use techniques aimed at soil warming in order to increase saffron yields in Quebec

Implantation d'un modèle de cinétique chimique dans un code d'éléments finis

Modélisation cinétique -- Théorie de la cinétique chimique -- Modèle de réaction -- Écriture en fraction massique -- Modification des taux de réactions -- Les Codes de résolutions -- Équations d'écoulement -- Équations moyennes de conservation -- Les modèles de turbulence -- Équations de bilan -- Conditions aux frontières -- Écriture moyenne des termes sources -- Approches de la combustion turbulente -- Méthodes numériques -- Discrétisation des équations -- Discrétisation du domaine -- Discrétisation dans la zone de la paroi -- Algorithme de calcul -- Résum é des étapes de résolution -- Résultats numériques -- Écoulement dans un canal -- Écoulement dans un canal avec une expansion soudaine -- Écoulement dans deux jets coaxiaux confinés

Utilizing Steel Slag in the Removal of Suspended Solids from Dewatered Construction Water

Construction dewatering is an operation used to remove shallow groundwater that infiltrates construction sites. After recovering this water from the construction sites, the water is either discharged to the sea, injected in deep groundwater aquifers, or treated and reused in some other applications. However, municipal and industrial application of this water is unfeasible due to its poor quality. Thus, in this study, dewatered construction water is being treated utilizing waste steel slag in order to improve the quality of the water. The pH of the dewatered construction water used for this study was 7.59 and the average diameter of steel slag used was 425 nm. For coagulation, the impact of the mass of steel slag and the contact time on the quality of dewatered construction water were studied. By using 5gm/L of steel slag, more than 85% of the total suspended solids and turbidity were removed within 30 minutes.The authors would like to thank Qatar University for the financial support. In addition, the authors would like to thank Qatar Steel for the supply of the steel slag sample

Fouling mitigation strategies for different foulants in membrane distillation

Providing clean water to a rapidly growing population is an issue that is currently getting lots of attention to offer a sustainable solution for water scarcity. Membrane distillation (MD) is one of the latest technologies that provides great potential in water treatment. Even though there is a tremendous amount of research done during the past two decades on membrane distillation, the long-term use of this process is still restricted by membrane fouling. Membrane Fouling can be defined as the accumulation of various materials in the pores or surface of the membrane that affect permeate's quantity and quality. This review highlights the recent observations on various foulants in MD process. Moreover, different fouling mechanisms of inorganic fouling, organic fouling, biological fouling, and colloidal fouling were investigated for better understanding and prevention of membrane fouling. In order to achieve a sustainable MD process, various techniques to mitigate fouling were discussed comprehensively including pre-treatment processes and cleaning methods. The benefits and disadvantages of these approaches have been investigated and reviewed in order to provide an overall understanding of fouling minimization in membrane distillation process. Fouling mitigation strategies have been suggested for different foulants in membrane distillation

Application of Green Polymeric Nanocomposites for Enhanced Oil Recovery by Spontaneous Imbibition from Carbonate Reservoirs

This study experimentally investigates the effect of green polymeric nanoparticles on the interfacial tension (IFT) and wettability of carbonate reservoirs to effectively change the enhanced oil recovery (EOR) parameters. This experimental study compares the performance of xanthan/magnetite/SiO2 nanocomposites (NC) and several green materials, i.e., eucalyptus plant nanocomposites (ENC) and walnut shell ones (WNC) on the oil recovery with performing series of spontaneous imbibition tests. Scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDAX), and BET (Brunauer, Emmett, and Teller) surface analysis tests are also applied to monitor the morphology and crystalline structure of NC, ENC, and WNC. Then, the IFT and contact angle (CA) were measured in the presence of these materials under various reservoir conditions and solvent salinities. It was found that both ENC and WNC nanocomposites decreased CA and IFT, but ENC performed better than WNC under different salinities, namely, seawater (SW), double diluted salted (2 SW), ten times diluted seawater (10 SW), formation water (FW), and distilled water (DIW), which were applied at 70 °C, 2000 psi, and 0.05 wt.% nanocomposites concentration. Based on better results, ENC nanofluid at salinity concentrations of 10 SW and 2 SW ENC were selected for the EOR of carbonate rocks under reservoir conditions. The contact angles of ENC nanocomposites at the salinities of 2 SW and 10 SW were 49 and 43.4°, respectively. Zeta potential values were −44.39 and −46.58 for 2 SW and 10 SW ENC nanofluids, which is evidence of the high stability of ENC nanocomposites. The imbibition results at 70 °C and 2000 psi with 0.05 wt.% ENC at 10 SW and 2 SW led to incremental oil recoveries of 64.13% and 60.12%, respectively, compared to NC, which was 46.16%.The publication of this article was funded by the Qatar National Library

High flow nasal cannula therapy versus continuous positive airway pressure and nasal positive pressure ventilation in infants with severe bronchiolitis: a randomized controlled trial

Introduction: non-invasive ventilation is widely used in the respiratory management of severe bronchiolitis. Methods: a randomized controlled trial was carried out in a tertiary pediatric university hospital´s PICU over 3 years to compare between continuous positive airway pressure/nasal positive pressure ventilation (CPAP/NPPV) and high flow nasal cannula (HFNC) devices for severe bronchiolitis. The trial was recorded in the national library of medicine registry (NCT04650230). Patients aged from 7 days to 6 months, admitted for severe bronchiolitis were enrolled. Eligible patients were randomly chosen to receive either HFNC or CPAP/NPPV. If HFNC failed, the switch to CPAP/NPPV was allowed. Mechanical ventilation was the last resort in case of CPAP/NPPV device failure. The primary outcome was the success of the treatment defined by no need of care escalation. The secondary outcomes were failure predictors, intubation rate, stay length, serious adverse events, and mortality. Results: a total of 268 patients were enrolled. The data of 255 participants were analyzed. The mean age was 51.13 ± 34.43 days. Participants were randomized into two groups; HFNC group (n=130) and CPAP/NPPV group (n=125). The success of the treatment was significantly higher in the CPAP/NPPV group (70.4% [61.6%- 78.2%) comparing to HFNC group (50.7% [41.9%- 59.6%])- (p=0.001). For secondary outcomes, lower baseline pH was the only significant failure predictor in the CPAP/NPPV group (p=0.035). There were no differences in intubation rate or serious adverse events between the groups. Conclusion: high flow nasal cannula was safe and efficient, but CPAP/ NPPV was better in preventing treatment failure. The switch to CPAP/NPPV if HFNC failed, avoided intubation in 54% of the cases

Predictive factors of morbidity after surgical treatment of hepatic hydatid cyst

Introduction Surgery remains the basic treatment of hepatic hydatid cyst (HHC). However, it is associated with significant morbidity. The aim of our study was to evaluate mortality and morbidity of surgery of the HHC and to highlight the risk factors. Methods A retrospective study was conducted from January 1, 1996 to December 31, 2006. 391 patients hospitalized for HHC and operated in the Department of General Surgery “A” of the Rabta Hospital in Tunis, Tunisia. Results The overall mortality rate was 0.7% while the overall morbidity rate was 20.4%. About 16.6% suffered from specific complications, while 3.8% suffered from non-specific complications. Predictors of morbidity in a univariate analysis included cysts larger than 9 cm, dome cysts, cysts with bilious contents, type II, III, IV or V on ultrasound classification, fissured cysts and intrabiliary rupture of hepatic hydatid cyst. The multivariate study consisted of independent predictors of disease at the site of the liver dome, the cysto-biliary fistula and intrabiliary rupture of hepatic hydatid cyst Conclusion The hepatic hydatid cyst of the dome and the existence of preoperative complications in particular intrabiliary rupture of hepatic hydatid cyst are the main factors of morbidity. A better understanding of these factors allows the surgeon to choose the appropiate surgical technique that is associated with less morbidity.Pan African Medical Journal 2012; 13:2

Constructing an Intelligent Model Based on Support Vector Regression to Simulate the Solubility of Drugs in Polymeric Media

This study constructs a machine learning method to simultaneously analyze the thermodynamic behavior of many polymer–drug systems. The solubility temperature of Acetaminophen, Celecoxib, Chloramphenicol, D-Mannitol, Felodipine, Ibuprofen, Ibuprofen Sodium, Indomethacin, Itraconazole, Naproxen, Nifedipine, Paracetamol, Sulfadiazine, Sulfadimidine, Sulfamerazine, and Sulfathiazole in 1,3-bis[2-pyrrolidone-1-yl] butane, Polyvinyl Acetate, Polyvinylpyrrolidone (PVP), PVP K12, PVP K15, PVP K17, PVP K25, PVP/VA, PVP/VA 335, PVP/VA 535, PVP/VA 635, PVP/VA 735, Soluplus analyzes from a modeling perspective. The least-squares support vector regression (LS-SVR) designs to approximate the solubility temperature of drugs in polymers from polymer and drug types and drug loading in polymers. The structure of this machine learning model is well-tuned by conducting trial and error on the kernel type (i.e., Gaussian, polynomial, and linear) and methods used for adjusting the LS-SVR coefficients (i.e., leave-one-out and 10-fold cross-validation scenarios). Results of the sensitivity analysis showed that the Gaussian kernel and 10-fold cross-validation is the best candidate for developing an LS-SVR for the given task. The built model yielded results consistent with 278 experimental samples reported in the literature. Indeed, the mean absolute relative deviation percent of 8.35 and 7.25 is achieved in the training and testing stages, respectively. The performance on the largest available dataset confirms its applicability. Such a reliable tool is essential for monitoring polymer–drug systems’ stability and deliverability, especially for poorly soluble drugs in polymers, which can be further validated by adopting it to an actual implementation in the future

Explainable deep learning model for automatic mulberry leaf disease classification

Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the world’s raw silk. Manual leaf disease identification is tedious and error-prone. Computer vision can categorize leaf diseases early and overcome the challenges of manual identification. No mulberry leaf deep learning (DL) models have been reported. Therefore, in this study, two types of leaf diseases: leaf rust and leaf spot, with disease-free leaves, were collected from two regions of Bangladesh. Sericulture experts annotated the leaf images. The images were pre-processed, and 6,000 synthetic images were generated using typical image augmentation methods from the original 764 training images. Additional 218 and 109 images were employed for testing and validation respectively. In addition, a unique lightweight parallel depth-wise separable CNN model, PDS-CNN was developed by applying depth-wise separable convolutional layers to reduce parameters, layers, and size while boosting classification performance. Finally, the explainable capability of PDS-CNN is obtained through the use of SHapley Additive exPlanations (SHAP) evaluated by a sericulture specialist. The proposed PDS-CNN outperforms well-known deep transfer learning models, achieving an optimistic accuracy of 95.05 ± 2.86% for three-class classifications and 96.06 ± 3.01% for binary classifications with only 0.53 million parameters, 8 layers, and a size of 6.3 megabytes. Furthermore, when compared with other well-known transfer models, the proposed model identified mulberry leaf diseases with higher accuracy, fewer factors, fewer layers, and lower overall size. The visually expressive SHAP explanation images validate the models’ findings aligning with the predictions made the sericulture specialist. Based on these findings, it is possible to conclude that the explainable AI (XAI)-based PDS-CNN can provide sericulture specialists with an effective tool for accurately categorizing mulberry leaves