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526 results on '"Deva, A."'

3. Design, FEM analysis and development of switched reluctance motor electric drive for TRI-wheeler E-vehicle application

Author

Anand, M., Jebarani Evangeline, S., Deva Priya, W., and Chitra Selvi, S.

Abstract

Electric vehicles have seen substantial growth in recent years in the emerging economies of the world. The current market scenario of E-vehicles is dominated by PMSM or BLDC motors due to their higher torque-to-power density, and efficiency with added performance metrics of the motor. However, the higher capital cost of permanent magnets makes the motor designers to consider an alternative to magnetic motors, the so-called Switched Reluctance Motors (SRM). With proper FEM analysis and controller design, if SRMs can able to achieve the performance metrics of a PMSM/BLDC, it will be a breakthrough in the automotive sector with affordable prices. Based on the aforementioned facts, this research work focuses on SRM as a viable alternative to the existing PMSM/BLDC motor. The work concentrates on the design and development of an 8/6 SRM for a Tri-wheeler E-vehicle application. The designed motor is fabricated, tested and controlled by WAVECT, an FPGA-based real-time digital controller which is used to control the commutation of the 8/6 SRM. The yielded response satisfactorily proves that the designed 8/6 SRM can be effectively used for the Tri-wheeler E-vehicle application, thereby paving the way for sustainable energy conservation in the automotive sector.

Published
2024
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4. Enhanced multivariate singular spectrum analysis‐based network traffic forecasting for real time industrial IoT applications

Author

Isravel, Deva Priya, Silas, Salaja, Kathrine, Jaspher, Rajsingh, Elijah Blessing, and J, Andrew

Abstract

Industrial IoT (IIoT) applications are widely used in multiple use cases to automate the industrial environment. Industry 4.0 presents challenges in numerous areas, including heterogeneous data, efficient data sensing and collection, real‐time data processing, and higher request arrival rates, due to the massive amount of industrial data. Building a time‐sensitive network that supports the voluminous and dynamic IoT traffic from heterogeneous applications is complex. Therefore, the authors provide insights into the challenges of industrial networks and propose a strategy for enhanced traffic management. An efficient multivariate forecasting model that adapts the Multivariate Singular Spectrum Analysis is employed for an SDN‐based IIoT network. The proposed method considers multiple traffic flow parameters, such as packet sent and received, flow bytes sent and received, source rate, round trip time, jitter, packet arrival rate and flow duration to predict future flows. The experimental results show that the proposed method can effectively predict by contemplating every possible variation in the observed samples and predict average load, delay, inter‐packet arrival rate and source sending rate with improved accuracy. The forecast results shows reduced error estimation when compared with existing methods with Mean Absolute Percentage Error of 1.64%, Mean Squared Error of 11.99, Root Mean Squared Error of 3.46 and Mean Absolute Error of 2.63. The authors focus on enhancing traffic forecasting to support SDN based Industrial IoT (IIoT) applications. Therefore, a novel multivariate forecasting model that adapts the Multivariate Singular Spectrum Analysis to predict and manage real‐time traffic efficiently. The proposed method was evaluated on the IIoT dataset and found to exhibit better performance for multi‐step ahead forecasts with irregular traffic patterns.

Published
2024
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5. The association between VSX1 exon3 gene variants and keratoconus in Malaysian patients

Author

Deva, Jenny, Ngeow, Yun, and Zin, Thaw

Subjects
Genetic variation -- Research, Keratoconus -- Genetic aspects -- Risk factors -- Development and progression, Health
Abstract

Byline: Jenny. Deva, Yun. Ngeow, Thaw. Zin Purpose: This case-control study aims to examine possible associations of VSX1 exon3 gene variants with the development of keratoconus (KC) in Malaysian patients. [...]

Published
2023

6. Finalists for the Nebula Awards Are Announced

Author

Kuang, R.F., Griffith, Nicola, Muir, Tamsyn, Nayler, Ray, Bradford, K. Tempest, Fagan, Deva, MacGregor, Maya, and Reese, Jenn

Subjects
Nebula Awards
Abstract

The Science Fiction and Fantasy Writers Association revealed the shortlists for its Nebula Awards, given annually to outstanding works of fiction in the genres. R.F. Kuang was named a finalist [...]

Published
2023

15. Study on Influence of Core Structure on Catalytic Converter Performance Using CFD

Author

Muthukumaran, V., Balaji, Selvaraj, Senthilkumar, K.M., Navaneethan, M., and Mano, D. Deva Jebas

Abstract

In recent years, as the automotive industry is growing, one of the major hope for future vehicles is to meet emissions regulations. Automobiles pollute the air, and clean-air laws have made Catalytic Converters a legal requirement because they convert harmful pollutants from an engine's exhaust into cleaner emissions. The device works with the principle of a catalyst, something that causes or speeds up a chemical reaction without itself being changed. But the presence of a catalytic converter increases the exhaust back pressure which has an indirect effect on the engine efficiency ie engine efficiency decreases, thus increasing fuel consumption. The performance of a catalytic converter is substantially affected by the flow distribution inside the substrate, a uniform flow distribution can increase its efficiency, lower the pressure drop and optimize engine performance. The flow distribution in a catalytic converter assembly 15 is governed by the geometry configurations of the inlet and outlet cone section, the substrate, and exhaust gas compositions, and therefore a better design of the catalytic converter is very important. This Project deals with the fundamental understanding and study of complex processes taking place involving fluid flow, pressure, and velocity profiles in the catalytic converter using ANSYS WORKBENCH 2022 R1. The main objective of our analysis is to determine the most effective and optimum design of a Catalytic Converter

Published
2024
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19. Effect of Addition of Rare Earth Element Cerium on the Microstructure and Mechanical Properties of Microalloyed Peritectic Grade Steel

Author

Kumar, Vikash, Deva, Anjana, and Chattopadhyay, Kausik

Abstract

Non-metallic inclusions in steel negatively affect operational processes and mechanical properties based on their morphology, size, physical state and distribution. Inclusion modification is especially important when sulphur levels are high because the sulphides that form can affect the operational process more significantly than the unmodified inclusions themselves. This research is an attempt to examine the impact of cerium addition on tensile and impact toughness properties, grain size, inclusion composition, morphology and fracture surface of microalloyed peritectic grade steel. The impact toughness at − 40 °C significantly increased by 139 and 164% and yield strength improved from 431 to 495 and 483 MPa with the addition of 0.015 and 0.045 wt% cerium, respectively. The improvement in mechanical properties has been attributed to the combined effect of altering the shape and composition of inclusions, refinement in grain size and uniform dispersion of inclusion in matrix.

Published
2024
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20. Multi-Objective Optimization of Turning for Nickel-Based Alloys Using Taguchi-GRA and TOPSIS Approaches

Author

Mastan Rao, P., Deva Raj, Ch., Dhoria, Sneha H., Vijaya, M., and Chowdary, J. Ranga Raya

Abstract

One of the significant challenges faced by industries today is obtaining the best process parameters while meeting the needs of both producers and users. It is necessary to introduce and use optimization strategies to accomplish this aim and satisfy these demands. This paper examines the exploit of Taguchi grey relational analysis (GRA) to optimize the turning process parameters of a nickel-based alloy, considering surface roughness (SR), tool wear rate (TW), and material removal rate (MRR). The approach combines L9 experiments with grey relational analysis, incorporating control parameters such as speed (A) at 300 rpm, 400 rpm, and 500 rpm; feed rate (B) at 0.05 mm/rev, 0.10 mm/rev, and 0.15 mm/rev; and cutting depth (C) at 0.1 mm, 0.3 mm, and 0.5 mm. The optimal parameter values obtained were A= 300 rpm, B= 0.15 mm/rev, and C= 0.5 mm, resulting in the best production outcomes: SR = 1.56 µm, TW = 0.0178 mm, and MRR = 2.14884 cm3/min. To compare the results, technique TOPSIS, a Multiple Attribute Decision Making technique, was also employed. The optimal parameter values derived from TOPSIS were A= 500 rpm, B= 0.15 mm/rev, and C= 0.5 mm, leading to ideal output parameters: SR = 1.774 µm, TW = 0.0191 mm, and MRR = 3.85226 cm3/min. The comparative study demonstrates the efficiency of the Taguchi GRA approach in optimizing turning process parameters for nickel-based alloys. Using this approach, we accomplished significant decreases in surface roughness (SR), tool wear rate (TW), and material removal rate (MRR) by 12.6%, 6.81%, and 44.21%, respectively.

Published
2024
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22. Exploring the antifungal potential of essential oils against grey mould on tomatoes

Author

Ramachandra, Sudharshan Keralapura, Nath, Hiranya Kr Deva, Kalita, Hia, Kaushik, Snata, and Narayanappa, Nagesh

Abstract

Grey mould, caused by the devastating pathogen Botrytis cinerea, poses a significant threat to tomato plants in both field and greenhouse conditions and causes significant pre and postharvest losses worldwide. Our study aimed to explore the antifungal potential of essential oils against the Botrytis cinereaof tomatoes. The putative pathogen was isolated, purified and characterized by cultural, morphological and molecular studies and the association was confirmed by a pathogenicity test. Essential oils were extracted from Garlic cloves, Artemisia leaves, and Jatropha seeds using the Soxhlet apparatus, and their compositions were analyzed using gas chromatography-mass spectrometry. In vitro, tests evaluated the efficacy of these oils at different concentrations (25, 50, 75, 100, 250, 500 and 1000 ppm) against B. cinerea. Garlic oil showed remarkable antifungal properties, inhibiting mycelial growth by 100% at concentrations of 75 ppm and above, Artemisia oil exhibited a significant inhibitory effect of 62.65% at 1000 ppm. Jatropha oil was the least effective, with an inhibition effect of only 8.66% at the highest concentration (1000 ppm) after 120 h. Based on the in vitro test, garlic essential oil was further tested in the pot at 75, 100 and 250 ppm. The essential oil was sprayed both protective and curative. Garlic oil at a concentration of 250 ppm effectively reduced disease incidence and index and increased tomato yield. However, the curative spray showed better control than the protective spray. This study highlights the potential of essential oils, particularly garlic oil, as a natural alternative for managing grey mould in tomatoes, paving the way for resilient and sustainable approaches to protect tomato crops from devastating fungal disease.

Published
2024
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24. MicroRNA Expression Profile in Early-Stage Breast Cancers

Author

Patel, Krishna, Rao, Deva Magendhra, Sundersingh, Shirley, Velusami, Sridevi, Rajkumar, Thangarajan, Nair, Bipin, Pandey, Akhilesh, Chatterjee, Aditi, Mani, Samson, and Gowda, Harsha

Abstract

Background: Breast cancer is one of the leading causes of cancer deaths in women. Early diagnosis offers the best hope for a cure. Ductal carcinoma in situ is considered a precursor of invasive ductal carcinoma of the breast. In this study, we carried out microRNA sequencing from 7 ductal carcinoma in situ (DCIS), 6 infiltrating ductal carcinomas (IDC Stage IIA) with paired normal, and 5 unpaired normal breast tissue samples.Methods: We have deployed miRge for microRNA analysis, DESeq for differential expression analysis, and Cytoscape for competing endogenous RNA network investigation.Results: Here, we identified 76 miRNAs that were differentially expressed in DCIS and IDC. Additionally, we provide preliminary evidence of miR-365b-3p and miR-7-1-3p being overexpressed, and miR-6507-5p, miR-487b-3p, and miR-654-3p being downregulated in DCIS relative to normal breast tissue. We also identified a miRNA miR-766-3p that was overexpressed in earlystage IDCs. The overexpression of miR-301a-3p in DCIS and IDC was confirmed in 32 independent breast cancer tissue samples.Conclusion: Higher expression of miR-301a-3p is associated with poor overall survival in The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset, indicating that it may be associated with DCIS at high risk of progressing to IDC and warrants deeper investigation.

Published
2024
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25. Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India

Author

Aneesha Satya, B., Shashi, M, and Deva, Pratap

Abstract

Geographical Information System (GIS) and remote sensing have become necessary tools in finding out land use land cover (LULC) change integrated with their associated driving factors. The utilization of satellite imagery made it easy to interpret the highly urbanized Warangal City that has experienced a lot of change in LULC during the last few decades. This paper discusses the ability of the integration of cellular automata (CA) and Markov chain–based 2D land use simulation module conjunction with GIS techniques. Markov chain algorithm is used for calibration and optimization by considering LULC of appropriate set of images for the years 2004, 2006, and 2018. Transitional change in LULC from one class to another is simulated using an artificial neural network (ANN) while cellular automata simulation is carried out to predict the plausible future LULC for the year 2052 after validating the model using the LULC of the year 2018. Analysis of the multi-temporal LULC maps indicated that the biophysical and socio-economic factors have greatly influenced the rise in built up while a decrease in agriculture in the year 2052. In conclusion, this technique is a powerful tool for monitoring and modeling change in land cover. Further suggestions for government officials are provided for an effective policymaking and to protect the land resource.

Published
2024
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26. Cascaded Sapphire Fiber Bragg Gratings Inscribed by Femtosecond Laser for Molten Steel Studies

Author

Alla, Dinesh Reddy, Neelakandan, Deva Prasad, Mumtaz, Farhan, Gerald, Rex E., Bartlett, Laura, O'Malley, Ronald J., Smith, Jeffrey D., and Huang, Jie

Abstract

This research reports a distributed fiber optic high-temperature sensing system tailored for applications in the steel industry and various other sectors. Recent advancements in optical sensor technology have led to the exploration of sapphire crystal fibers as a solution for sensing in harsh environments. Utilizing a femtosecond (fs) laser, cascaded fiber Bragg gratings (FBGs) were meticulously fabricated within a multimode sapphire optical fiber. These FBGs endowed the system with distributed sensing capabilities and underwent rigorous testing under extreme temperatures, reaching up to 1800 °C. The study delves into the investigation of the FBG reflection spectrum, facilitated by the development of a sophisticated multimode demodulation system, which contributed to the attainment of precise temperature measurements with a performance accuracy of 99.9%. Demonstrating exceptional thermal stability, the sapphire FBGs endured temperatures of 1600 °C for a sustained duration of 22 h. Furthermore, this article explores the application of distributed temperature sensing employing multiple sapphire FBGs, showcasing their utility in temperature measurements related to molten steel studies.

Published
2024
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27. Synthesis of mesoporous structured ZnMn2O4nanoparticles as electrode for supercapacitor application

Author

Deva, P., Ravi, S., and Manoharan, C.

Abstract

Spinel ZnMn2O4has been gaining more attention in the realm of supercapacitor applications due to its accessibility, affordability, sustainability, high specific capacitance, and excellent rate capability. In this study, spinel ZnMn2O4was synthesized using a rapid, eco-friendly citric acid-mediated sol–gel auto-combustion approach. A thorough study was conducted to correlate the phase structure, surface morphology, functional groups, oxidation states, specific surface area, and redox reaction of the electroactive species with their potential impact on the electrochemical behaviour of electrode material. The prepared spinel ZnMn2O4electrode material showed an impressive specific capacitance value of 417.5 F g−1under low electrolyte concentrations and a current density of 1 A g−1. In an aqueous electrolyte, the reaction kinetics of the supercapacitor become very fast and this is responsible for its high capacitance. An excellent coulombic efficiency of 87% was obtained for this electrode material even after 5000 cycles. The exceptional electrochemical performance is mainly attributed to the nanoparticles, which have a large reaction surface area, fast transfer of ions and electrons, high ionic conductivity, and excellent structural durability. These significant results emphasize the ZnMn2O4, potential as a supercapacitor material.

Published
2024
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28. Eco-friendly bioremediation of petroleum-based inks from printing machine waste implementing native strain Pseudomonas aeruginosaMDP14

Author

Prasanna, Maria Albert Mary Deva, Siddharthan, Nagarajan, Raguvaran, Krishnan, Ayyasamy, Pudukadu Munusamy, Hemalatha, Natarajan, and Ragavendran, Chinnasamy

Abstract

The printing inks are a kind of petrochemical pollutants released from print machines of print industries. As the printer rollers are subjected to kerosene wash, the discharge waste contains kerosene in addition to inks. Environmental pollution with petroleum and petrochemical products are being recognized the most serious global problem. These petroleum-based waste discharges are very toxic to environment. Therefore, in this study, it is aimed to apply bioremediation strategies to reduce petrochemical pollution. The petrochemical and printing ink degrading bacteria are isolated from soil polluted by printing machine waste discharge. The potential bacterial isolate was identified by morphological, biochemical, and molecular characterization as Pseudomonas aeruginosaMDP14. Bioremediation study was carried out using a column technique. The microbial-treated and untreated samples of printing machine roller waste water were analyzed for physicochemical parameters, gas chromatography–mass spectrometry, and subjected to toxicity assessments. Ink bioremediation study results confirmed that potential microbe augmentation combined with endogenous microbes of unsterile effluent supported maximum 80% of different ink substrate degradation. It was also noted that untreated effluent sample was highly toxic when compared with treated effluent samples. Based on GC–MS results, sulfurous acid, oxalic acid, fumaric acid, and cis-vaccenic acid component peaks were found reduced in bioremediated sterile effluent sample. It can be concluded that the washed waste of rollers in printing machine could be bioremediated to reduce its biological toxicity before letting it into the surrounding environment. The GC result gives the future scope to extend the research to study the type and nature of breakdown products of print ink bioremediation.

Published
2024
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29. Novel optimised deep learning approach for an efficient traffic state prediction based on CAE-ICCDCS-GRU model

Author

Hema, D. Deva and Kumar, K. Ashok

Abstract

Deep neural networks (DNNs) have recently been proven capable of forecasting traffic flow from large datasets. While existing DNN models can outperform shallow models, it is still a work in progress to adjust the hyperparameters of DNN models using an effective optimisation approach. Therefore, an improved crossover-chaos-based dynamic cuckoo search (ICCDCS) algorithm has been developed to improve the traffic state prediction efficiency. In the proposed traffic state prediction model, convolutional auto-encoder (CAE) is employed to achieve efficient noise filtering with feature extraction, and the gated recurrent unit model (GRU) uses ICCDCS to optimise its hyperparameters for forecasting traffic status in the most efficient way possible. To increase the effectiveness of the cuckoo search, ICCDCS combines the Circle map for chaos, crossover operation, and boundary management method. These combined features make it possible to select a better GRU hyperparameter, improving the accuracy of traffic state forecasting. Faster searches and better information interchange are ICCDCS benefits. The efficiency of ICCDCS algorithm has been tested with test functions. Other optimisation techniques are less accurate than ICCDCS. The result of CAE-ICCDCS-GRU reveals drastic improvement in the performance, apparently in terms of minimised error due to its optimised parameters of GRU.

Published
2024
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30. Automatic Detection of Covid-19 based on Xception Network with Optimized CNN

Author

Deva Priya, V. Helen and Juliet, A. Vimala

Abstract

An exact and quick finding of Covid-19 patients plays a major part in the initial period of medicinal treatment and prevention. Automatic recognition of COVID-19 cases utilizing lung X-ray images may help lessen the effect of this infection on human civilization. In recent years, computer vision is the major solution for diagnosing the covid-19 disease by utilizing X-ray images. Besides, many researchers had presented efficient Artificial Intelligence (AI)methods for identifying Covid-19 disease. Nevertheless, the accuracy and time consumption of the model is further to be improved. Thus, in this work, we proposed a novel Xception network with an optimized convolution neural network (OCNN). The CNN architecture is enhanced by using the adaptive seagull optimization (ASO) algorithm. There are three stages of the approach: pre-processing, feature extraction, and classification. At first, a median filter is applied to each image to reduce the noise present in the input image. Then, the noise-free images are fed to the Xception network to extract the features of the images. A convolution network is used to classify an image as positive or negative after feature extraction. The performance of the proposed approach is analyzed based on various metrics and performance compared with other techniques.

Published
2024
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31. Pneumatic Non-Equibiaxial Cell Stretching Device With Live-Cell Imaging

Author

Wang, Jue, Chatterjee, Aritra, Zigan, Clarisse, Alborn, Maya, Chan, Deva D., and Chortos, Alex

Abstract

Objective: Adherent cell behavior is influenced by a complex interplay of factors, including chemical and mechanical signals. In vitro experiments that mimic the mechanical environment experienced by cells in vivo are crucial for understanding cellular behavior and the progression of disease. In this study, we developed and validated a low-cost pneumatically-controlled cell stretcher with independent control of strain in two directions of a membrane, enabling unequal biaxial stretching and real-time microscopy during actuation. Methods: The stretching was achieved by two independent pneumatic channels controlled by electrical signals. We used finite element simulations to compute the membrane's strain field and particle tracking algorithms based on image processing techniques to validate the strain fields and measure the cell orientation and morphology. Results: The device can supply uniaxial, equibiaxial, and unequal biaxial stretching up to $\text{15} \%$ strain in each direction at a frequency of $\text{1}\,{\rm Hz}$, with a strain measurement error of less than 1%. Through live cell imaging, we determined that distinct stretching patterns elicited differing responses and alterations in cell orientation and morphology, particularly in terms of cell length and area. Conclusion: The device successfully provides a large, uniform, and variable strain field for cell experiments, while also enabling real-time, live cell imaging. Significance: This scalable, low-cost platform provides mechanical stimulation to cell cultures by independently controlling strains in two directions. This could contribute to a deeper understanding of cellular response to bio-realistic strains and could be useful for future in vitro drug testing platforms.

Published
2024
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34. Morphometry and Life-Stage Wise Length–Weight Relationships of, Labeo gonius(Hamilton–Buchanan, 1822), Under Captive Condition

Author

Ahirwal, Surendra Kumar, Sarma, Kamal, Das, Sanjay Kumar, Kumar, Tarkeshwar, Singh, Jaspreet, Bharti, Vivekananda, and Narayan, Deva

Abstract

Labeo goniusis a commercially important and potential candidate species for aquaculture systems. Our study aims to determine its morphometric characters, meristic counts, and life-stage wise length–weight relationships under captive condition. All morphometric characters are significantly correlated with total length and head length. The total length has the maximum degree of correlation with standard length (r= 0.991), whereas head length has with inter-orbital length (r= 0.902). Meristic counts indicated that the maximum coefficients of variation were for the gill rakers (8.51%), while lowest for ventral fin rays (1.10%). Gill rakers are more numerous in the species which varied from the 41 to 71. The length–weight relationship was established as W = 0.0015*L1.2836(r2= 0.696) for fry, W = 0.000036*L2.8271(r2= 0.7163) for fingerlings, W = 0.000008*L3.0924(r2= 0.9358) for juveniles, and W = 0.00006*L3.1726(r2= 0.9453) for adults. Negative allometric growth patterns were observed for fry and fingerlings (b< 3), whereas positive for juveniles and adults (b> 3). All the estimated physiochemical water quality parameters are within the permissible limit.

Published
2023
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39. Impact of the Preprocessing Steps in Deep Learning-Based Image Classifications

Author

Koresh, H. James Deva

Abstract

Deep learning softwares are designed using artificial neural networks for various applications by training and testing them with an appropriate dataset. The raw image samples available in the dataset may contain noisy and unclear information due to radiation, heat and poor lighting conditions. Therefore, the researchers are trying to filter and enhance such noisy images through preprocessing steps for providing a valid feature information to the neural network layers included in the deep learning software. However, there are certain claims that roam around the researchers such as an image may lose some useful information when it is not preprocessed with an appropriate filter or enhancement technique. Hence, the work reviews the efficacy of the methodologies that are designed with and without a preprocessing step. Also, the work summarizes the common reasons and statements highlighted by the researchers for using and avoiding the preprocessing steps on designing a deep learning approach. The study is conducted to provide a clarity toward the requirement and non-requirement of preprocessing step in a deep learning software.

Published
2024
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40. Association of Different Prescribing Patterns for Oral Corticosteroids With Fracture Preventive Care Among Older Adults in the UK and Ontario

Author

Matthewman, Julian, Tadrous, Mina, Mansfield, Kathryn E., Thiruchelvam, Deva, Redelmeier, Donald A., Cheung, Angela M., Lega, Iliana C., Prieto-Alhambra, Daniel, Cunliffe, Lawrence A., Mulick, Amy, Henderson, Alasdair, Langan, Sinéad M., and Drucker, Aaron M.

Abstract

IMPORTANCE: Identifying and mitigating modifiable gaps in fracture preventive care for people with relapsing-remitting conditions such as eczema, asthma, and chronic obstructive pulmonary disease who are prescribed high cumulative oral corticosteroid doses may decrease fracture-associated morbidity and mortality. OBJECTIVE: To estimate the association between different oral corticosteroid prescribing patterns and appropriate fracture preventive care, including treatment with fracture preventive care medications, among older adults with high cumulative oral corticosteroid exposure. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included 65 195 participants with UK electronic medical record data from the Clinical Practice Research Datalink (January 2, 1998, to January 31, 2020) and 28 674 participants with Ontario, Canada, health administrative data from ICES (April 1, 2002, to September 30, 2020). Participants were adults 66 years or older with eczema, asthma, or chronic obstructive pulmonary disease receiving prescriptions for oral corticosteroids with cumulative prednisolone equivalent doses of 450 mg or higher within 6 months. Data were analyzed October 22, 2020, to September 6, 2022. EXPOSURES: Participants with prescriptions crossing the 450-mg cumulative oral corticosteroid threshold in less than 90 days were classified as having high-intensity prescriptions, and participants crossing the threshold in 90 days or more as having low-intensity prescriptions. Multiple alternative exposure definitions were used in sensitivity analyses. MAIN OUTCOMES AND MEASURES: The primary outcome was prescribed fracture preventive care. A secondary outcome was major osteoporotic fracture. Individuals were followed up from the date they crossed the cumulative oral corticosteroid threshold until their outcome or the end of follow-up (up to 1 year after index date). Rates were calculated for fracture preventive care and fractures, and hazard ratios (HRs) were estimated from Cox proportional hazards regression models comparing high- vs low-intensity oral corticosteroid prescriptions. RESULTS: In both the UK cohort of 65 195 participants (mean [IQR] age, 75 [71-81] years; 32 981 [50.6%] male) and the Ontario cohort of 28 674 participants (mean [IQR] age, 73 [69-79] years; 17 071 [59.5%] male), individuals with high-intensity oral corticosteroid prescriptions had substantially higher rates of fracture preventive care than individuals with low-intensity prescriptions (UK: 134 vs 57 per 1000 person-years; crude HR, 2.34; 95% CI, 2.19-2.51, and Ontario: 73 vs 48 per 1000 person-years; crude HR, 1.49; 95% CI, 1.29-1.72). People with high- and low-intensity oral corticosteroid prescriptions had similar rates of major osteoporotic fractures (UK: crude rates, 14 vs 13 per 1000 person-years; crude HR, 1.07; 95% CI, 0.98-1.15 and Ontario: crude rates, 20 vs 23 per 1000 person-years; crude HR, 0.87; 95% CI, 0.79-0.96). Results from sensitivity analyses suggested that reaching a high cumulative oral corticosteroid dose within a shorter time, with fewer prescriptions, or with fewer or shorter gaps between prescriptions, increased fracture preventive care prescribing. CONCLUSIONS: The results of this cohort study suggest that older adults prescribed high cumulative oral corticosteroids across multiple prescriptions, or with many or long gaps between prescriptions, may be missing opportunities for fracture preventive care.

Published
2023
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42. Affinity variation in the interactions of tryptophan- β-cyclodextrin-platinum complex with G-quadruplex and duplex DNAs

Author

Muruganantham, Aishwarya, Deva Sahayam, Arokya Nithya, Suganthi, Soundarapandian, Alexander, Aleyamma, Sumohan Pillai, Archana, and Enoch, Israel V. M. V.

Abstract

AbstractDNA forms non-canonical Guanine-rich-quadruplex structures that play crucial roles such as maintenance of the telomere, transcription, and replication. Selective binding of small molecular ligands to G-quadruplexes and stabilization of them gain importance in the control of cell proliferation and development of therapeutics. In this paper, we report the synthesis of a tryptophan-β-cyclodextrin complex and its platinum complex. The binding interaction of the synthesized Trp-β-CD-Pt compound with various DNAs, including a duplex DNA and three quadruplexes, are investigated. The binding of the compound to quadruplexes shows a general increase in the binding strength compared to the strength of binding with the duplex, CT-DNA. The compound reveals the strongest binding with kit22. An enhancement of fluorescence is generally observed when the ligand binds to all the DNAs, except myc22. The structure of the host: guest complex with Berberine, a model G-quadruplex binding ligand, is investigated using 2 D ROESY spectroscopy. The host: guest binding is strong and the DNA interaction does not extract much of the Berberine molecule from the complex. The differential bindings of the ligand in free- and Berberine-loaded forms with different G-quadruplexes are discussed in detail based on binding strengths and the modulation of fluorescence.Communicated by Ramaswamy H. Sarma

Published
2023
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43. Burnout in US hematologists and oncologists: impact of compensation models and advanced practice provider support

Author

Lee, Alfred Ian, Masselink, Leah E., De Castro, Laura M., Marshall, Ariela L., Connell, Nathan T., Dent, Georgette A., Fritz, Josel, Homer, Morgan, Lucas, Tiffany L., Naik, Rakhi P., Nelson, Marquita, O’Connell, Casey L., Rajasekhar, Anita, Reynolds, Robby J., Sharma, Deva, Smith, Melody, Weeks, Lachelle D., and Erikson, Clese E.

Abstract

•Compensation plans based solely on clinical productivity are associated with high burnout among hematologists and oncologists.•Increased utilization of advanced practice providers is inversely associated with high burnout among community hematologists and oncologists.

Published
2023
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44. Effectiveness and safety of optical coherence tomography-guided PCI in Indian patients with complex lesions: A multicenter, prospective registry

Author

Chandra, Praveen, Sethuraman, Selvamani, Roy, Sanjeeb, Mohanty, Arun, Parikh, Keyur, Charantharalyil Gopalan, Bahuleyan, Sahoo, Prasant Kumar, Kasturi, Sridhar, Shah, Vijay Trambaklal, Kumar, Viveka, Pinto, Brian, Rath, Pratap Chandra, Yerramareddy, Vijayachandra Reddy, Davidson, Deepak, Navasundi, Girish B., Subban, Vijayakumar, Livingston, Nandhini, Rajaraman, Deva Preethi, Narang, Manish, West, Nick E.J., and Mullasari, Ajit

Abstract

Optical coherence tomography (OCT) is reported to be a feasible and safe imaging modality for the guidance of percutaneous coronary intervention (PCI) of complex lesions.

Published
2023
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45. Mandatory human rights due diligence laws in Europe: A mirage for rightsholders?

Author

Deva, Surya

Abstract

AbstractMandatory human rights due diligence (HRDD) laws in the European Union (EU) – both enacted and in the making – seem to be a promising tool to harden soft international standards in the business and human rights (BHR) field, the most prominent of these being the UN Guiding Principles on Business and Human Rights (UNGPs). This article develops a two-layered critique of mandatory HRDD laws. It problematizes the very concept of HRDD as articulated by the UNGPs. I will argue that due to various conceptual, operational and structural limitations, HRDD alone will not bring the desired changes for rightsholders, because this process does not address various asymmetries of power between corporations and affected communities. The second layer of critique concerns the content of mandatory HRDD laws enacted in France, the Netherlands, Switzerland, Norway and Germany. Assessing these laws vis-à-vis six preconditions required to protect effectively people and the planet from business-related harms, it is clear that these mandatory HRDD laws are half-hearted attempts to tame business-related human rights abuses and hold the relevant corporate actors accountable. In addition to developing more ambitious mandatory HRDD laws in future, states should employ a range of additional regulatory tools that pay greater attention to achieving outcomes, drawing red lines in certain situations, and promoting access to remedy and corporate accountability.

Published
2023
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46. Use of Telemedicine for Postdischarge Assessment of the Surgical Wound

Author

Glasbey, James, Trout, Issi, Adeyeye, Victoria, Ademuyiwa, Adesoji, Adisa, Adewale, Bhatt, Alisha, Biccard, Bruce, Brocklehurst, Peter, Chakrabortee, Sohini, Allen Ingabire, Jean De La Croix, Dossou, Francis Moïse, Durán, Irani, Dutta, Rohini, Ghosh, Dhruva, Gyamfi, Frank, Hardy, Pollyanna, Hyman, Gabriella, Jain, Ritu, Kadir, Bryar, Knight, Stephen, Ladipo-Ajayi, Oluwaseun, Lawani, Ismail, Lawani, Souliath, Lillywhite, Rachel, Macefield, Rhiannon, Magill, Laura, Martin, Janet, Mathers, Jonathan, McLean, Kenneth, Mistry, Unam, Mittal, Rohin, Moore, Rachel, Morton, Dion, Ntirenganya, Faustin, Ofori, Emmanuel, Pearse, Rupert, Peón, Alberto, Pinkney, Thomas, Medina, Antonio Ramos de la, Ronald, Tubasiime, Roman, David, Simoes, Joana, Slade, Anita, Tabiri, Stephen, Smith, Donna, Harrison, Ewen, Bhangu, Aneel, Glasbey, James, Trout, Issi, Bhangu, Aneel, Runigamugabo, Azmina Verjee Emmy, Ademuyiwa, Adesoji O, Adisa, Adewale O, Aguilera, Maria Lorena, Altamini, Afnan, Alexander, Philip, Al-Saqqa, Sara W, Borda-Luque, Giuliano, Cornick, Jen, Costas-Chavarri, Ainhoa, Drake, Thomas M, Fergusson, Stuart J, Fitzgerald, J Edward, Glasbey, James, Ingabire, J.C Allen, Ismaïl, Lawani, Jaffry, Zahra, Salem, Hosni Khairy, Khatri, Chetan, Kirby, Andrew, Kojo, Anyomih Theophilus Teddy, Lapitan, Marie Carmela, Lilford, Richard, Mihaljevic, Andre L, Mohan, Midhun, Morton, Dion, Mutabazi, Alphonse Zeta, Nepogodiev, Dmitri, Ntirenganya, Faustin, Ots, Riinu, Pata, Francesco, Pinkney, Thomas, Poškus, Tomas, Qureshi, Ahmad Uzair, la Medina, Antonio Ramos-De, Rayne, Sarah, Recinos, Gustavo, Søreide, Kjetil, Shaw, Catherine A, Shu, Sebastian, Spence, Richard, Smart, Neil, Tabiri, Stephen, Lilford, Richard, Morton, Dion, Harrison, Ewen M, Bhangu, Aneel, Modolo, Maria Marta, Iyer, Dushyant, King, Sebastian, Arthur, Tom, Nahar, Sayeda Nazmum, Waterman, Ade, Ismaïl, Lawani, Walsh, Michael, Agarwal, Arnav, Zani, Augusto, Firdouse, Mohammed, Rouse, Tyler, Liu, Qinyang, Correa, Juan Camilo, 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Hassanein Ahmed, Rekhis, Syrine, Rommaneh, Muna, Halhouli, Oday, Sam, Zi Hao, Chen, Jacky Hong Chieh, Ismaïl, Lawani, Pata, Francesco, Nita, Gabriela Elisa, Coccolini, Federico, Ansaloni, Luca, Pugliesi, Thays Brunelli, Pardo, Gabriel, Blanco, Ruth, and Escobar, Eugenio Grasset

Published
2023
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47. Boron Containing Low Carbon Deep Drawing Continuous Annealed Steel Sheet with Improved Plastic Anisotropy

Author

Deva, Anjana, Sahoo, Biraj Kumar, and Chowdhury, Sandip Ghosh

Abstract

In current market scenario, cold-rolled steel sheets need high quality requirements to suit the continuous automated forming process for manufacturing components of diverse end applications. Deep drawability, which is one of the crucial property of steel for forming application, is influenced by factors like alloy chemistry, microstructure, texture evolution and precipitation characteristics. All these microstructural factors are in turn affected directly by the annealing process employed. In the present study, specially designed continuous annealing process has been employed to assess the influence of boron to nitrogen (B/N) ratio (0–0.87)on mechanical and drawing properties of low carbon (0.03–0.035 wt %), low manganese (0.15–0.18 wt%) and low sulphur (0.005–0.008 wt%) steel. Steel with B/N ratio of 0.185resulted into best combination of properties in terms of lowest YS/UTS ratio (0.81),high plastic anisotropy (rm:1.545) along with 310 MPa yield strength, 380 MPa ultimate tensile strength, 20% uniform elongation and 32% total elongation. It has been found that the B/N ratio, rather than the absolute boron, influences the precipitation characteristics of carbides and favorable texture development during continuous annealing process.

Published
2023
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