Significance and Key Challenges in Conducting Stress Testing for Islamic Commercial Banks

With the current cross-border growth in Islamic finance, Islamic commercial banks (ICBs) are looking forward to being perceived as an industry in the process of becoming mature. This would require the establishment of some basic infrastructure, including sophisticated risk management tools that enhance the soundness and resilience of the ICBS. This paper focuses on the latter that is the role and significance of stress testing as a risk management tool. The stress testing has become part of the regulatory and supervisory authorities within the financial stability analysis. The global financial crisis (2008) has placed the spotlight squarely on stress tests. Though, ICBs operate within the similar financial environment, and their balance sheet composition, however, calls for different treatment in stress testing. Apart from the specificities of ICBs, there are key issues and challenges that should be given due considerations in developing an appropriate stress testing regime. This paper explores key specificities and challenges. The paper argues that in the beginning, conducting the stress testing may not appear a simple task for the ICBs. However, a proper consideration to the challenges identified in the paper would certainly tend to improve the overall effectiveness and credibility of the stress testing programmes

Unraveling Single-Cell Heterogeneity Through Graph Neural Networks and Multiplexed Imaging

Cells are the basic building blocks of life, and understanding how they transition from one state to another is a fundamental question in cell biology. Advances in single-cell genomics have enabled the analysis of molecular dynamics in these transitions and motivated the development of computational models to uncover the source of cellular heterogeneity. However, many existing approaches fall short of gleaning information revealed by single-cell variability, instead of clustering data for tasks such as differential gene expression. In this dissertation, the author presents two major contributions. The first contribution is Cellograph, a deep learning framework that uses graph neural networks (GNNs) to derive a single-cell metric of how cells are impacted by a given perturbation. The framework learns a latent space that arranges cells according to transcriptomic similarity and similarity in how they respond to perturbations. This approach can facilitate downstream analyses such as clustering and data visualization, and provide a powerful framework for studying the effects of perturbations under complex treatment regimes. Cellograph is demonstrated on publicly available datasets for cancer drug therapy, stem cell reprogramming, and organoid differentiation. The second contribution is a novel application for studying the cell cycle in human embryonic stem cells (hESCs) by means of iterative indirect immunofluorescence imaging (4i). This method measures a panel of cell cycle, pluripotency, and germ layer proteins at single-cell resolution in hESCs undergoing differentiation to each of the three major germ layers. The findings identify germ layer-specific cell cycle dynamics during differentiation and reveal how proliferation and arrest programs are remodeled as they undergo differentiation, providing a framework to study the role of the cell cycle in stem cell differentiation. Altogether, this work presents a detailed investigation into the mechanisms of single-cell heterogeneity through graph neural networks and multiplexed imaging, providing valuable insights into how cells transition from one state to another and potential applications for treating disease and unraveling the basic science of how cells make decisions.Doctor of Philosoph

Separate Submission of Standard Lymphadenectomy in 6 Packets Versus En Bloc Lymphadenectomy in Bladder Cancer

Introduction:Our aim was to evaluate detection of nodal metastasis during radical cystectomy with standard pelvic lymph node dissection versus en bloc lymphadenectomy for the treatment of bladder cancer. Materials And Methods: Hospital records of a total of 77 Patients with radical cystectomy and either standard pelvic lymph node dissection or en bloc lymphadenectomy were reviewed. Nodal dissection specimens during standard lymphadenectomy were sent for pathology examination in 6 separate containers marked as external iliac, internal iliac, and obturator groups from both sides. En bloc dissection specimens were sent in 2 containers marked as the right and the left pelvic nodes. Clinical and pathological findings of these two groups were compared in terms of the number of dissected lymph nodes, number of nodes with metastasis, lymph node density, and clinical outcomes. Results: There were 34 Patients with standard lymph node dissection and 43 with en bloc lymphadenectomy (anterior pelvic exenteration). Age, sex, duration of the disease, number of transurethral resections prior to cystectomy, pathological grade at cystectomy, and stage of the primary tumor were comparable in the two groups of Patients. The median numbers of nodes removed per Patient were 15.5 (range, 4 to 48) and 7.0 (range, 1 to 24) in those with standard and en bloc lymphadenectomy, respectively (P \u3c .001). Nodal involvement was detected in 10 (29.4%) and 9 (20.9%) Patients, respectively (P = .43). Conclusions: Although nodal involvement was not significantly different between the two groups, standard lymphadenectomy submitted in 6 different containers significantly improved the nodal yield over en bloc resection. Obturator nodes were the most commonly involved nodes in our study

Adsorption of Chromium (VI) from Wastewater by Anion Exchange Resin

Strong anion exchange resin (Spectra/Gel IE 1x8) has been investigated as adsorbent for the efficient removal of Cr(VI) ions from synthetic wastewater solutions. Batch experiments were conducted with initial Cr(VI) ions concentration ranging from 25-300 mg/L. Different parameters influencing Cr(VI) adsorption process such as; solution pH, Cr(VI) and adsorbent concentration and contact time were investigated. Results obtained revealed that Cr(VI) was successfully retained by the resin. Equilibrium was established within 30 minutes for initial Cr(VI) concentration up to100 mg/L. The equilibrium data for adsorption of Cr(VI) was fitted with both Langmuir and Freundlich isotherms, however, Langmuir isotherm model was found to be more suitable for the Cr(VI) adsorption and maximum adsorption capacity of the Cr(VI) was found to be 173.8 mg/g. The adsorption process followed second order kinetics. The resin was regenerated by using 4M NaOH as an eluent and retained Cr(VI) adsorption efficiency higher than 83% after three regeneration cycles

Effect Of Bio-Based Lubricant Towards Emissions And Engine Breakdown Due To Spark Plug Fouling In A Two-Stroke Engine

Two-stroke also known as two-cycle gasoline engine is a spark ignition engine. Its uniqueness to the four-stroke engine is that this engine does not require lubricant sump, which makes construction lightweight and simple. Its lubricant is mixed with gasoline and burnt together during combustion. There are reports which stated that higher spark plug fouling is due to carbon deposition on the spark plug electrodes on a two-stroke engine when compared to the four-stroke. While many factors could have affected this situation, however, in this paper, the effect of mineral and bio-based lubricants towards carbon deposition and emissions are studied and reported. Idle, half and full throttle operation modes had been conducted on a two-stroke, 43 cubic centimeter engine. To keep combustion temperature below self-cleaning temperature on all three modes of operation, a zero-load test was utilized. This situation accelerates the deposition process as low temperature causes incomplete combustion. This could lead to the accumulation of char, unburned fuel, as well as condensed water and acids as the byproducts blanket the spark plug electrodes and the exhaust system. Five samples had been prepared with a commercially available mineral lubricant (T0) as reference. Trimethylolpropane Trioleate, TMPTO derived from plant origin was used as the bio-based candidate. It was then mixed with T0 which created another four lubricant samples namely T10, T15, T20 and T50 with 10%, 15%, 20% and 50% TMPTO accordingly. Results show that mineral lubricant T0 delivers the lowest hydrocarbon HC, carbon monoxide CO and smoke opacity during idle and half throttle operations. However, it exhibits a greasy deposit on the spark plug circumference and dry carbon deposits on its insulator tip. T0 also emits a liquid residue at the exhaust manifold. T10 and T50 show a wet deposit blanketing both electrodes. Severe deposition was recorded by T50 that caused the engine to fail half way with its emissions had the worst recording. T15 and T20 exhibit only dry carbon deposition on the spark plug circumference. However, T20 has outperformed T15 in terms of emissions with lower CO and CO2 emissions during idling and half-throttling. With better emissions than T15 and better carbon deposition than mineral (T0), T20 could be proposed to be used as a commercial two-stroke lubricant

Tribological improvement using ionic liquids as additives in synthetic and bio-based lubricants for steel-steel contacts

This study investigates the performance of three ionic liquids (ILs), trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate, trihexyl(tetradecyl)phosphonium decanoate, and 1-butyl-3-methylimidazolium tetrafluoroborate, as lubricant additives in synthetic oil polyalphaolefin (PAO8) and bio-based oil trimethylolpropane trioleate (TMPTO). The ILs were added at 0.5, 1.0, and 1.5 wt% concentrations and evaluated in terms of their miscibility with base oils as well as friction- and wear-reducing abilities. Four-ball and high-frequency reciprocating rig (HFRR) tribotesters were employed to evaluate the tribological performance under a boundary lubrication regime. Worn steel surfaces were characterized using optical microscopy, profilometry, scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) analysis. The results suggested that the addition of trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate and trihexyl(tetradecyl)phosphonium decanoate improved the tribological performance of both PAO8 and TMPTO at an optimum concentration of 1 wt%. They showed good friction reduction, lower overall surface wear, and improved surface finishing. 1-Butyl-3-methylimidazolium tetrafluoroborate managed to improve the tribological performance of both base oils only at 0.5 wt%. A further increase in 1-butyl-3-methylimidazolium tetrafluoroborate concentration caused detrimental effects on the steel surface due to the formation of halogenic compounds

Analysis of Ketamine, a Rave Drug in Pakistan, using Gas Chromatography Coupled with Mass Spectrometer and Flame Ionization Detector: A Case Study

Ketamine is an arylcycloalkylamine, classified as cyclidine and chemically related to phencyclidine (PCP). Ketamine can be identified using modified Scott’s Test and Alkaline Gold Bromide test. This case study involved the analysis of a Ketamine sample. The sample was analyzed qualitatively by chemical spot tests, FT-IR and GC-MS without derivatization. Furthermore, a developed and validated method was used for the quantitative analysis of Ketamine using Gas Chromatography with a Flame Ionization Detector (FID). The certified reference standard of Ketamine in the range of 10- 100μg/mL was used for developing linear correlation with regression coefficient (R2 = 0.9997) for the method. The method produced percentage of sample as 90.27%. The above mentioned techniques and methods provide comparable qualitative and quantitative analytical results helping law enforcement agencies and the forensic community in screening and quantification of ketamine using GCMS coupled with FID

Corrosion behavior of copper, aluminium, and stainless steel 316L in chicken fat oil based biodiesel-diesel blends

This study investigates the corrosion behavior of automotive materials in bio-based fuels. The Response Surface Methodology is employed to evaluate the corrosion rates of materials such as copper, aluminium, and stainless steel when they are exposed to chicken fat-based biodiesel. Copper, aluminium, and stainless steel showed minimum corrosion rate at a blend percentage of 5.86 % when they were immersed for 920 h and maximum corrosion rate at blend percentage 34.14 % when these were immersed for 920 h. Meanwhile, the maximum corrosion rate was observed at a blend percentage of 34.14 % corresponding to the same immersion period. Optimum values indicated by RSM for copper and aluminium were noted at a blend percentage of 10 % and an immersion period of 720 h. Similarly, for stainless steel 316 l, these were 10.91 % and 754.44 h, respectively. Additionally, trials using the B100 for 920 h were conducted on copper, aluminium, and stainless steel 316 l, and the results showed considerably higher corrosion rates than those previously found. The surface morphology of the materials was investigated by X-ray Diffraction and Scanning Electron Microscopy, and it was revealed that copper was the most corrosive material in chicken fat oil-based biodiesel followed by aluminium and stainless steel 316 l

Developing an online predictor to predict product sulfur concentration for HDS unit

Hydrodesulfurization (HDS) is an important process in refining industries. Advanced control system (e.g. model predictive controller) requires on-line measurement of the product sulfur at the reactor outlet. However, most HDS processes do not have a sulfur analyzer at the reactor outlet. In order to predict product sulfur concentration usually a data based sulfur predictor is developed. Performance of data based predictor is usually poor since some of the input parameters (e.g. feed sulfur concentration) are unknown. The objective of this thesis is to overcome these limitations of data based predictors and develop an online product sulfur predictor for HDS unit. In this thesis, a hybrid model is proposed, developed and validated (using industrial data), which could predict product sulfur concentration for online HDS system. The proposed hybrid structure is a combination of a reaction kinetics based HDS reactor model and an empirical model based on support vector regression (SVR). The mechanistic model runs in off-line mode to estimate the feed sulfur concentration while the data based model uses the estimated feed sulfur concentration and other process variables to predict the product sulfur concentration. The predicted sulfur concentration can be compared with the lab measurements or sulfur analyzer located further downstream of the process at the tankage. In case there is a large discrepancy, the predictor goes to a calibration mode and uses the mechanistic model to re-estimate the feed sulfur concentration. The detailed logic for the online prediction is also developed. Finally a Matlab based Graphical User Interface (GUI) has been developed for the hybrid sulfur predictor for easy implementation to any HDS process

Synthesis, Conformation and Antiproliferative Activity of Isothiazoloisoxazole 1,1-dioxides

Sixteen new isothiazoloisoxazole 1,1-dioxides, one new isothiazolotriazole and one new isothiazolopyrazole have been synthesised by using 1,3-dipolar cycloadditions to isothiazole 1,1-dioxides. One sub-set of these isothiazoloisoxazoles showed low μM activity against a human breast carcinoma cell line, whilst a second sub-set plus the isothiazolotriazole demonstrated an interesting restricted rotation of sterically hindered bridgehead substituents. A thiazete 1,1-dioxide produced from one of the isothiazole 1,1-dioxides underwent conversion into an unknown 1,2,3-oxathiazolin-2-oxide upon treatment with Lewis acids, but was inert towards 1,3-dipoles and cyclopropenones. Six supporting crystal structures are included