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Tryptanthrin is a natural alkaloidal compound having basic indoloquinazoline moiety. It is obtained from various natural plant sources as well as different cell cultures including ...yeast etc. Trptanthrin is considered as biogenetic precursor for phaitanthrin A–C, pyrroloindoloquinazoline, (±)-cruciferane. Different synthetic approaches for the synthesis of tryptanthrin have been very well reported. It has broad spectrum of biological activities including anticancer activity, anti-inflammatory, antiprotozoal, antiallergic, antioxidant, and antimicrobial. In this review, our focus will be, on the various approaches for the synthesis of tryptanthrins and its derivatives along with the biological activities.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK, ZRSKP
Dihydropyrimidines are the most important heterocyclic ring systems which play an important role in the synthesis of DNA and RNA. Synthetically they were synthesized using Multi-component reactions ...like Biginelli reaction and Hantzschdihydropyridine. In the past decades, such Biginelli type dihydropyrimidones have received a considerable amount of attention due to the interesting pharmacological properties associated with this heterocyclic scaffold. In this review, we highlight recent developments in this area, with a focus on the DHPMs, recently developed as anti-inflammatory, anti-HIV, anti-tubercular, antifungal anticancer, antibacterial, antifilarial, antihyperglycemic, antihypertensive, analgesic, anti-convulsant, antioxidant, anti-TRPA1, anti-SARS, and anti-cancer activity and α1a binding affinity.
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•This review is focused on synthetic prospective of dihydropyrimidinones.•This review is also focused on medicinal prospective of dihydropyrimidinones.•It includes structure-activity relationship study of different activities.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK, ZRSKP
The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the ...coronavirus-19 disease and the on-demand necessity to perform surgery during space missions. Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing. Among all 3D printing techniques, fused deposition modelling (FDM) is a low-cost and more rapid printing technique. This article proposes the fabrication of surgical instruments, namely, forceps and hemostat using the fused deposition modeling (FDM) process. Excellent mechanical properties are the only indicator to judge the quality of the functional parts. The mechanical properties of FDM-processed parts depend on various process parameters. These parameters are layer height, infill pattern, top/bottom pattern, number of top/bottom layers, infill density, flow, number of shells, printing temperature, build plate temperature, printing speed, and fan speed. Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid (PLA) parts printed by FDM. The experiments have performed through Taguchi's L
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orthogonal array (OA). Variance analysis (ANOVA) ascertains the significance of the process parameters and their percent contributions to the evaluation indexes. Finally, as a multi-objective optimization technique, grey relational analysis (GRA) obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties. Scanning electron microscopy (SEM) examines the types of defects and strong bonding between rasters. The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength (42.6 MPa) and modulus of elasticity (3274 MPa).
Objectives The aim of this study was to examine the effect of continuous positive airway pressure (CPAP) therapy on atrial fibrillation (AF) recurrence in patients with obstructive sleep apnea (OSA) ...undergoing pulmonary vein isolation (PVI). Background OSA is a predictor of AF recurrence following PVI. However, the impact of CPAP therapy on PVI outcome in patients with OSA is poorly known. Methods Among 426 patients who underwent PVI between 2007 and 2010, 62 patients had a polysomnography-confirmed diagnosis of OSA. While 32 patients were “CPAP users” the remaining 30 patients were “CPAP nonusers.” The recurrence of any atrial tachyarrhythmia, use of antiarrhythmic drugs, and need for repeat ablations were compared between the groups during a follow-up period of 12 months. Additionally, the outcome of patients with OSA was compared to a group of patients from the same PVI cohort without OSA. Results CPAP therapy resulted in higher AF-free survival rate (71.9% vs. 36.7%; p = 0.01) and AF-free survival off antiarrhythmic drugs or repeat ablation following PVI (65.6% vs. 33.3%; p = 0.02). AF recurrence rate of CPAP-treated patients was similar to a group of patients without OSA (HR: 0.7, p = 0.46). AF recurrence following PVI in CPAP nonuser patients was significantly higher (HR: 2.4, p < 0.02) and similar to that of OSA patients managed medically without ablation (HR: 2.1, p = 0.68). Conclusions CPAP is an important therapy in OSA patients undergoing PVI that improves arrhythmia free survival. PVI offers limited value to OSA patients not treated with CPAP.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
The work reported in present study deals with the development of a novel stochastic model and estimation of parameters to assess reliability characteristics for a turbogenerator unit of thermal power ...plant under classical and Bayesian frameworks. Turbogenerator unit consists of five components namely turbine lubrication, turbine governing, generator oil system, generator gas system and generator excitation system. The concepts of cold standby redundancy and Weibull distributed random variables are used in development of stochastic model. The shape parameter for all the random variables is same while scale parameter is different. Regenerative point technique and semi-Markov approach are used for evaluation of reliability characteristics. Sufficient repair facility always remains available in plant as well as repair done by the repairman is considered perfect. As the life testing experiments are time consuming, so to highlight the importance of proposed model Monte Carlo simulation study is carried out. A comparative analysis is done between true, classical and Bayesian results of MTSF, availability and profit function.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•A four-dimensional non-autonomous NPZT (nutrient-phytoplankton-zooplankton-environmental toxins) model with group defence is presented.•The change in population densities with respect to some ...important parameters is explained, and this change also leads to occurrence of Hopf-bifurcation in autonomous model.•We establish the existence and global stability of the periodic solution for the non- autonomous model analytically.•Both autonomous and non-autonomous models show different kinds of multistability.•Non-autonomous model also shows the chaotic nature due to seasonality of parameters.
The interaction between phytoplankton and zooplankton has a significant impact on the marine ecology. The interplay between these two species is the building blocks for most of the food webs operating in an aquatic ecosphere. The environmental toxins released by different external sources also affect the phytoplankton-zooplankton dynamics. In the present study, we propose a model to explore the kinetics of a nutrient-phytoplankton-zooplankton-environmental toxins (NPZT) system. The defence mechanism of phytoplankton against zooplankton is reflected through modified Holling type IV response, whereas the consumption of nutrients by phytoplankton is outlined by Holling type II response. The external toxins are assumed to have the capability of reducing the birth rate of phytoplankton species after coming into contact with their cells. To make our model more pragmatic, seasonal variation in the parameters is also taken into account. Firstly, we do the analysis related to the autonomous model (non-seasonal) like; its boundedness, existence of equilibrium points, their stability analysis, and occurrence of Hopf-bifurcation. Further, for the non-autonomous model (seasonal), we analyze the existence of positive periodic solution and its global stability. Through numerical simulations, we observe that for the non-seasonal model, increasing the rate of suppressing phytoplankton’s growth by environmental toxin, and rate at which environmental toxin is added to system make it unstable through Hopf-bifurcation. These oscillations can be removed by raising phytoplankton’s inhibitory effect against zooplankton, and this increment also leads to the extinction of the zooplankton population, making zooplankton free equilibrium a stable one. Both models, non-seasonal as well as seasonal manifest different types of multistability, and this is an exciting character associated with non-linear models. We also note that the inclusion of seasonality in our system promotes the coexistence of all populations. Further, through numerical simulations, we show that making some of the parameters seasonal can cause the emergence of chaos in the system. To verify chaos, we sketch the Poincaré map and evaluate the maximum Lyapunov exponent. The seasonal model also shows the switching of stability through different periodic and chaotic windows on varying the maximum intrinsic growth rate for phytoplankton, and contact rate between environmental toxin and phytoplankton. To substantiate our results, we picture several time-series graphs, basins of attraction, one and two-parametric bifurcation diagrams. Thus we expect that the present work can assist biologists and mathematicians in studying nutrient-plankton systems in a more detailed and realistic manner. This study can also help researchers in the estimation of non-seasonal as well as seasonal parameters while studying these types of complex non-linear models. Therefore, the present work seems to be enriched from a mathematical and biological point of view.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
COVID-19 has emerged as the most alarming infection of the present time instigated by the virus SARS-CoV-2. In spite of advanced research technologies, the exact pathophysiology and treatment of the ...condition still need to be explored. However, SARS-CoV-2 has several structural and functional similarities that resemble SARS-CoV and MERS-CoV which may be beneficial in exploring the possible treatment and diagnostic strategies for SARS-CoV-2. This review discusses the pathogen phenotype, genotype, replication, pathophysiology, elicited immune response and emerging variants of SARS-CoV-2 and their similarities with other similar viruses. SARS-CoV-2 infection is detected by a number of diagnostics techniques, their advantages and limitations are also discussed in detail. The review also focuses on nanotechnology-based easy and fast detection of SARS-CoV-2 infection. Various pathways which might play a vital role during SARS-CoV-2 infection have been elaborately discussed since immune response plays a major role during viral infections.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate due to risks of breast cancer. Early detection ...of cancer boosts increasing the survival chance up to 8%. Primarily, breast images emanating from mammograms, X-Rays or MRI are analyzed by radiologists to detect abnormalities. However, even experienced radiologists face problems in identifying features like micro-calcifications, lumps and masses, leading to high false positive and high false negative. Recent advancement in image processing and deep learning create some hopes in devising more enhanced applications that can be used for the early detection of breast cancer. In this work, we have developed a Deep Convolutional Neural Network (CNN) to segment and classify the various types of breast abnormalities, such as calcifications, masses, asymmetry and carcinomas, unlike existing research work, which mainly classified the cancer into benign and malignant, leading to improved disease management. Firstly, a transfer learning was carried out on our dataset using the pre-trained model ResNet50. Along similar lines, we have developed an enhanced deep learning model, in which learning rate is considered as one of the most important attributes while training the neural network. The learning rate is set adaptively in our proposed model based on changes in error curves during the learning process involved. The proposed deep learning model has achieved a performance of 88% in the classification of these four types of breast cancer abnormalities such as, masses, calcifications, carcinomas and asymmetry mammograms.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Reconfigurable Manufacturing Systems provide the functionality and capacity needed, when needed. The Reconfigurable Machine Tool (RMT) plays a pivotal role in the fulfilment of this objective through ...their modular structure consisting of basic and auxiliary modules along with the open architecture software. In the present work, a novel approach based on the module interactions and machine capability is proposed to measure the machine reconfigurability and operational capability of an RMT. The developed performance measures along with cost are considered as the multiple objectives for the optimal machine assignment for a single part flow line allowing paralleling of similar machines. The multi-objective optimisation problem in hand is targeted in two phases. In the first phase, non-dominated sorting genetic algorithm II is applied to obtain the non-dominated solutions. In the subsequent stage, a multiple attribute decision-making approach is employed to rank the pareto frontiers. The proposed solutions are ranked based on Shannon entropy weight and Technique for Order Preference by Similarity to Ideal Solution method. The study reveals that the developed performance measures along with the hybrid approach have a great potential in handling the RMS optimisation and cost-benefit issues.
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BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in ON ...time, whereas quantum algorithm design is based on Grover's method, which completes the search in ON time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum‐based combined exact (QBCE) algorithm for the pattern‐matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing‐based exact (QPBE) pattern‐matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are OtandON, and the exceptional worst case is bounded by OtandON. Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern‐matching methods.
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