Search results for: Mukesh R. Goswami

Authors: Shubham Kumar, Chaitanya Goswami, Sudipto Sarkar

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Pseudoplastic (n < 1, n being the power index) fluid flow can be found in food, pharmaceutical and process industries and has very complex flow nature. To our knowledge, inadequate research work has been done in this kind of flow even at very low Reynolds numbers. Here, in the present computation, we have considered unsteady laminar flow over a square cylinder in pseudoplastic flow environment. For Newtonian fluid flow, this laminar vortex shedding range lies between Re = 47-180. In this problem, we consider Re = 100 (Re = U∞ a/ ν, U∞ is the free stream velocity of the flow, a is the side of the cylinder and ν is the kinematic viscosity of the fluid). The pseudoplastic fluid range has been chosen from close to the Newtonian fluid (n = 0.8) to very high pseudoplasticity (n = 0.1). The flow domain is constituted using Gambit 2.2.30 and this software is also used to generate mesh and to impose the boundary conditions. For all places, the domain size is considered as 36a × 16a with 280 ×192 grid point in the streamwise and flow normal directions respectively. The domain and the grid points are selected after a thorough grid independent study at n = 1.0. Fine and equal grid spacing is used close to the square cylinder to capture the upper and lower shear layers shed from the cylinder. Away from the cylinder the grid is unequal in size and stretched out in all direction. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition du/dy = 0, v = 0) at upper and lower domain boundary conditions are used for this simulation. Wall boundary (u = v = 0) is considered on the square cylinder surface. Fully conservative 2-D unsteady Navier-Stokes equations are discretized and then solved by Ansys Fluent 14.5 to understand the flow nature. SIMPLE algorithm written in finite volume method is selected for this purpose which is the default solver in scripted in Fluent. The result obtained for Newtonian fluid flow agrees well with previous work supporting Fluent’s usefulness in academic research. A minute analysis of instantaneous and time averaged flow field is obtained both for Newtonian and pseudoplastic fluid flow. It has been observed that drag coefficient increases continuously with the reduced value of n. Also, the vortex shedding phenomenon changes at n = 0.4 due to flow instability. These are some of the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: Ansys Fluent, CFD, periodic vortex shedding, pseudoplastic fluid flow

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Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

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Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

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Authors: Prince Vivek, Vijay K. Bharti, Manishi Mukesh, Ankita Sharma, Om Prakash Chaurasia, Bhuvnesh Kumar

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High performance of endurance in equid requires adaptive changes involving physio-biochemical, and molecular responses in an attempt to regain homeostasis. We hypothesized that the identification of the suitable reference genes might be considered for assessing of endurance related traits in pony at high altitude and may ensure for individuals struggling to potent endurance trait in ponies at high altitude. A total of 12 mares of ponies, Zanskar breed, were divided into three groups, group-A (without load), group-B, (60 Kg) and group-C (80 Kg) on backpack loads were subjected to a load carry protocol, on a steep climb of 4 km uphill, and of gravel, uneven rocky surface track at an altitude of 3292 m to 3500 m (endpoint). Blood was collected before and immediately after the load carry on sodium heparin anticoagulant, and the peripheral blood mononuclear cell was separated for total RNA isolation and thereafter cDNA synthesis. Real time-PCR reactions were carried out to evaluate the mRNAs expression profile of a panel of putative internal control genes (ICGs), related to different functional classes, namely glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β₂ microglobulin (β₂M), β-actin (ACTB), ribosomal protein 18 (RS18), hypoxanthine-guanine phosophoribosyltransferase (HPRT), ubiquitin B (UBB), ribosomal protein L32 (RPL32), transferrin receptor protein (TFRC), succinate dehydrogenase complex subunit A (SDHA) for normalizing the real-time quantitative polymerase chain reaction (qPCR) data of native pony’s. Three different algorithms, geNorm, NormFinder, and BestKeeper software, were used to evaluate the stability of reference genes. The result showed that GAPDH was best stable gene and stability value for the best combination of two genes was observed TFRC and β₂M. In conclusion, the geometric mean of GAPDH, TFRC and β₂M might be used for accurate normalization of transcriptional data for assessing endurance related traits in Zanskar ponies during load carrying.

Keywords: endurance exercise, ubiquitin B (UBB), β₂ microglobulin (β₂M), high altitude, Zanskar ponies, reference gene

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Authors: Mukesh K. Dwivedi, Rajeshwar N. Srivastava, Amit K. Bhagat, Saloni Raj

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Introduction: Management of Pressure Ulcer (PU) is an ongoing clinical challenge particularly in traumatic paraplegia patients in developing countries where socio economic conditions often dictate treatment modalities. When negative pressure wound therapy (NPWT) was introduced, there were a series of devices (V.A.C., KCI, San Antonio, TX) manufactured. These devices for NPWT are costly and hard to afford by patients in developing countries like India. Considering this limitation, this study was planned to design an RCT to compare NPWT by an indigenized locally constructed NPD and conventional gauze dressing for the treatment of PU. Material and Methods: This RCT (CTRI/2014/09/0050) was conducted in the Department of Orthopaedic Surgery at King George’s Medical University (KGMU), India. Thirty-four (34) subjects of traumatic paraplegia having PU of stage 3 or 4, were enrolled and randomized in two treatment groups (NPWT Group & Conventional dressing group). The outcome measures of this study were surface area and depth of PU, exudates, microorganisms and matrix metalloproteinase-8 (MMP-8) during 0 to 9 weeks follow-ups. Levels of MMP-8 were analyzed in the tissues of PU at week 0, 3, 6 and week 9 by Enzyme Linked Immuno Sorbent Assay (ELISA). Results: Significantly reduced length of PU in NPWT group was observed at week 6 (p=0.04) which further reduced at week 9 (p=0.001) as compared to conventionally treated group. Similarly significant reduction of width and depth of PU was observed in NPWT at week 9 (p<0.05). The exudate became significantly (p=0.001) lower in NPWT group as compared with conventionally treated group from 6th to 9th week. Clearance and conversion of slough into red granulation tissue was significantly higher in NPWT group (p=0.001). At week 9, the wound culture was negative in all the subjects of NPWT group, while it was positive in 10 (41⋅6%) subjects of conventional group. Significantly lower level of MMP-8 was observed in subjects of NPWT group at week 6 (0.006**), and continually more reduction was observed at week 9 (<0.0001**) as compared to the conventional group. Conclusion: NPWT by locally constructed NPD is better wound care procedure for management of PU. Our device gave similar results as commercially available devices. Reduction of level of MMP-8 and increased rate of healing was achieved by negative pressure wound therapy (NPWT) as compared to conventional dressing.

Keywords: NPWT, NPD, MMP8, ELISA

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Authors: Vimal Kumar Dewangan, T. S. Sampath Kumar, Mukesh Doble, Viju Daniel Varghese

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The apatite-based, i.e., calcium-deficient hydroxyapatite (CDHAp) bone cement is well-known potential bone graft/substitute in orthopaedics due to its similar chemical composition with natural bone minerals. Therefore, an easy approach was attempted to fabricate the apatite-based (CDHAp) bone cement with improved injectability, bioresorbability, and macroporosity. In this study, the desired bone cement was developed by mixing the solid phase (consisting of wet chemically synthesized nanocrystalline hydroxyapatite and commercially available (synthetic) tricalcium phosphate) and the liquid phase (consisting of cement binding accelerator with few biopolymers in a dilute acidic solution) along with a liquid porogen as polysorbate or a solid porogen as mannitol (for comparison) in an optimized liquid-to-powder ratio. The fabricated cement sets within clinically preferred setting time (≤20 minutes) are better injectable (>70%) and also stable at ~7.3-7.4 (physiological pH). The CDHAp phased bone cement was resulted by immersing the fabricated after-set cement in phosphate buffer solution and other similar artificial body fluids and incubated at physiological conditions for seven days, confirmed through the X-ray diffraction and Fourier transform-infrared spectroscopy analyses. The so-formed synthetic apatite-based bone cement holds the acceptable compressive strength (within the range of trabecular bone) with average interconnected pores size falls in a macropores range (~50-200μm) inside the cement, verified by scanning electron microscopy (SEM), mercury intrusion porosimetry and micro-CT analysis techniques. Also, it is biodegradable (degrades ~19-22% within 10-12 weeks) when incubated in artificial body fluids under physiological conditions. The biocompatibility study of the bone cement, when incubated with MG63 cells, shows a significant increase in the cell viability after 3rd day of incubation compared with the control, and the cells were well-attached and spread completely on the surface of the bone cement, confirmed through SEM and fluorescence microscopy analyses. With this all, we can conclude that the developed synthetic macroporous apatite-based bone cement may have the potential to become promising material used as a trabecular bone substitute.

Keywords: calcium deficient hydroxyapatite, synthetic apatite-based bone cement, injectability, macroporosity, trabecular bone substitute

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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Authors: Indu Gaur, Neha Bhadauria, Shilpi Shilpi, Susmita Goswami, Prem D. Sharma, Prabir K. Paul

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The concept of organic agriculture has been accepted as novelty in Indian society, but there is no data available on the human pathogens colonizing plant parts due to such practices. Also, the pattern and mechanism of their colonization need to be understood in order to devise possible strategies for their prevention. In the present study, human pathogenic bacteria were isolated from organically grown tomato plants and five of them were identified as Klebsiella pneumoniae, Enterobacter ludwigii, Serratia fonticola, Stenotrophomonas maltophilia and Chryseobacterium jejuense. Tomato plants were grown in controlled aseptic conditions with 25±1˚C, 70% humidity and 12 hour L/D photoperiod. Six weeks old plants were divided into 6 groups of 25 plants each and treated as follows: Group 1: K. pneumonia, Group 2: E. ludwigii, Group 3: S. fonticola, Group 4: S. maltophilia, Group 5: C. jejuense, Group 6: Sterile distilled water (control). The inoculums for all treatments were prepared by overnight growth with uniform concentration of 108 cells/ml. Leaf samples from above groups were collected at 0.5, 2, 4, 6 and 24 hours post inoculation for the colony forming unit counts (CFU/cm2 of leaf area) of individual pathogens using leaf impression method. These CFU counts were used for the in vivo colonization assay and adherence assay of individual pathogens. Also, resistance of these pathogens to at least 12 antibiotics was studied. Based on these findings S. fonticola was found to be most prominently colonizing the phylloplane of tomato and was further studied. Tomato plants grown in controlled aseptic conditions same as mentioned above were divided into 2 groups of 25 plants each and treated as follows: Group 1: S. fonticola, Group 2: Sterile distilled water (control). Leaf samples from above groups were collected at 0, 24, 48, 72 and 96 hours post inoculation and homogenized in suitable buffers for surface and cell wall protein isolation. Protein samples thus obtained were subjected to isocratic SDS-gel electrophoresis and analyzed. It was observed that presence of S. fonticola could induce the expression of at least 3 additional cell wall proteins at different time intervals. Surface proteins also showed variation in the expression pattern at different sampling intervals. Further identification of these proteins by MALDI-MS and bioinformatics tools revealed the gene(s) involved in the interaction of S. fonticola with tomato phylloplane.

Keywords: cell wall proteins, human pathogenic bacteria, phylloplane, solanum lycopersicum

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Authors: Deepak Kumar, Ravi Rajwanshi, Mohd. Aslam Yusuf, Nisha Kant Pandey, Preeti Singh, Mukesh Saxena, Neera Bhalla Sarin

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Global issues are leading to concerns over food security. These include climate change, urbanization, increase in population subsequently leading to greater energy and water demand. Futuristic approach for crop improvement involves gene pyramiding for agronomic traits that empower the plants to withstand multiple stresses. In an earlier study from the laboratory, the efficacy of overexpressing γ-tocopherol methyl transferase (γ-TMT) gene from the vitamin E biosynthetic pathway has been shown to result in six-fold increase of the most biologically active form, the α-tocopherol in Brassica juncea which resulted in alleviation of salt, heavy metal and osmoticum induced stress by the transgenic plants. The glyoxalase I (gly I) gene from the glyoxalase pathway has also been earlier shown by us to impart tolerance against multiple abioitc stresses by detoxification of the cytotoxic compound methylglyoxal in Brassica juncea. Recently, both the transgenes were pyramided in Brassica juncea lines through sexual crosses involving two stable Brassica juncea lines overexpressing γ-TMT and gly I genes respectively. The transgene integration was confirmed by PCR analysis and their mRNA expression was evident by RT-PCR analysis. Preliminary physiological investigations showed ~55% increased seed germination under 200 mM NaCl stress in the pyramided line and 81% higher seed germination under 200 mM mannitol stress as compared to the WT control plants. The pyramided lines also retained more chlorophyll content when the leaf discs were floated on NaCl (200, 400 and 600 mM) or mannitol (200, 400 and 600 mM) compared to the WT control plants. These plants had higher Relative Water Content and greater solute accumulation under stress compared to the parental plants having γ-TMT or the glyI gene respectively. The studies revealed the synergy of two components from different metabolic pathways in enhancing stress hardiness of the transgenic B. juncea plants. It was concluded that pyramiding of genes (γ-TMT and glyI) from diverse pathways can lead to enhanced tolerance to salt and mannitol stress (simulating drought conditions). This strategy can prove useful in enhancing the crop yields under various abiotic stresses.

Keywords: abiotic stress, brassica juncea, glyoxalase I, α-tocopherol

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Authors: Mohit Kumar, Beklashwar Salona, Shiv Murti, Mukesh Singh

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We report here a case of five-months old male baby, born as second child of non-consanguineous parents with no considerable history of genetic abnormality which was referred to our cytogenetic laboratory for chromosomal analysis. Physical dysmorphic facial features including mongoloid face, cleft palate, simian crease, and developmental delay were observed. We present this case with unique balanced autosomal translocation of t(3;10)(p21;p13). The risk of phenotypic abnormalities based on de novo balanced translocation was estimated to be 7%. The association of balanced chromosomal rearrangement with Down syndrome features such as multiple congenital anomalies, facial dysmorphism and congenital heart anomalies are very rare in a 5-months old male child. Trisomy-21 is not uncommon in chromosomal abnormality with the birth defect and balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion (RSA). Two ml heparinized peripheral blood cells cultured in RPMI-1640 for 72 hours supplemented with 20% fetal bovine serum, phytohemagglutinin (PHA), and antibiotics were used for chromosomal analysis. A total 30 metaphases images were captured using Olympus-BX51 microscope and analyzed using Bio-view karyotyping software through GTG-banding (G bands by trypsin and Giemsa) according to International System for Human Cytogenetic Nomenclature 2016. The results showed balanced translocation between short arm of chromosome # 3 and short arm of chromosome # 10. The karyotype of the child was found to be 46,XY,t(3;10)(p21; p13). Chromosomal abnormalities are one of the major causes of birth defect in new born babies. Also, balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion. The index case presented with dysmorphic facial features and had a balanced translocation 46,XY,t(3;10)(p21;p13). This translocation with break points at (p21; p13) has not been reported in the literature in a child with facial dysmorphism. To the best of our knowledge, this is the first report of novel balanced translocation t(3;10) with break points in a child with dysmorphic features. We found balanced chromosomal translocation instead of any trisomy or unbalanced aberrations along with some phenotypic abnormalities. Therefore, we suggest that such novel balanced translocation with abnormal phenotype should be reported in order to enable the pathologist, pediatrician, and gynecologist to have a better insight into the intricacies of chromosomal abnormalities and their associated phenotypic features. We hypothesized that dysmorphic features as seen in this case may be the result of change in the pattern of genes located at the breakpoint area in balanced translocations or may be due to deletion or mutation of genes located on the p-arm of chromosome # 3 and p-arm of chromosome # 10.

Keywords: balanced translocation, karyotyping, phenotypic abnormalities, facial dimorphisms

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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