41 research outputs found

    Syntheses of indoles and natural indole alkaloids from 2-nitrostyrene derivatives

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    A short and flexible synthesis of 2,3-disubstituted indoles employing a Barluenga-type palladium-catalyzed cross-coupling of p-tosylhydrazones with 2-nitroarylhalides followed by a palladium-catalyzed, carbon monoxide-mediated reductive cyclization was developed. Significantly better overall yields were obtained performing the two-step reaction sequence in a one-pot reaction. Secondly, in order to facilitate biological studies of ergotryptamine, a recently isolated ergot alkaloid, it was selected as a target for synthesis. In an attempt to synthesize ergotryptamine, a palladium catalyzed Kosugi-Migita-Stille cross coupling, a Mizoroki-Heck reaction, and a carbon monoxide-mediated palladium-catalyzed reductive cyclization were utilized as the key steps. Using a similar synthetic approach, synthesis of another indole norpsilocin, a component of magic mushroom, was accomplished in two additional steps. Additionally, a selection of β-acyl-β-alkyl substituted 2-nitrostyrenes were subjected to a palladium-catalyzed, carbon monoxide-mediated reductive cyclization. 2-Substituted 3-acylindoles with rearranged carbon skeleton were observed in all cases. In addition to indoles, small amounts of the corresponding quinolone-N-oxide and/or quinoline were isolated as side products in a number of cases. The cyclization precursors, β-acyl-β-alkyl substituted 2-nitrostyrenes, were synthesized via either a Wittig reaction or an aldol condensation. Finally, a short synthetic sequence leading to two marine diastereomeric azepino indole alkaloids hyrtioreticulins C and D was completed. A reductive amination via a trans-imination, a regioselective intramolecular Mizoroki-Heck reaction, and a palladium-catalyzed reductive cyclization were the major steps in the synthetic sequence

    Fully Fuzzy Linear System in Circuit Analysis with the Study of Weak Solution

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    In this paper, a simpler method to solve a fully fuzzy linear system (FFLS) with unrestricted coefficient matrix is discussed. FFLS is applied in circuit analysis instead of crisp linear system to reflect the real life situation much better. Arithmetic operations of triangular fuzzy number (TFN) are justified by forming FFLS in an electrical circuit with fuzzy sources and fuzzy resistors and then the system was solved by the simpler method. Finally, the case of weak solution is overcome by proposing a new definition of TFN. Keywords: Fuzzy number, Triangular fuzzy number, Fully fuzzy linear system, Circuit analysis, Weak solutio

    Monoclonal antibody: a cell specific immunotherapy to treat cancer

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    Fundamentally, the therapy technique which is utilized in malignancy immunotherapy, monoclonal antibodies (mAb), is one of them, and it is used extensively as a treatment for the disease. To achieve more successful treatment, novel combination treatments and treatment procedures must be created. The purpose of this study is the improvement of mAb treatment and detail late advance and new limits, particularly in cancer therapy. With various keywords, we searched Google Scholar, PubMed, and Scopus for monoclonal antibody therapy as an alternate form of chemotherapy. The number of patients who received each therapy regimen, and the recovery rate are all displayed in this study, also a comparative study between monotherapy and chemotherapy. The result showed that rituximab had a greater overall response rate than other drugs, at 68%. In the combination treatment group (monotherapy+chemotherapy), 100% of patients had adverse events, compared to 84.2 percent in the monotherapy group. The pharmaceutical industry's fastest-growing medications, monoclonal antibodies are increasingly being examined in Clinical trials as stand-alone treatments or in conjunction with other therapies. It has a promising future since it will provide better tailored therapy and combination therapy for the treatment of cancer

    Hand Gesture Recognition Using a Radar Echo I–Q Plot and a Convolutional Neural Network

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    We propose a hand gesture recognition technique using a convolutional neural network applied to radar echo inphase/quadrature (I/Q) plot trajectories. The proposed technique is demonstrated to accurately recognize six types of hand gestures for ten participants. The system consists of a low-cost 2.4-GHz continuous-wave monostatic radar with a single antenna. The radar echo trajectories are converted to low-resolution images and are used for the training and evaluation of the proposed technique. Results indicate that the proposed technique can recognize hand gestures with average accuracy exceeding 90%

    Antibiotic resistance situation in Dhaka, Bangladesh: a review

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    Antibiotic resistance is global trouble and in the megacities, it is causing more rapidly due to the misuse and overuse of antibiotics. This systematic evaluation used to be carried out to summarize the contemporary day kingdom of affairs of antibiotic resistance in Dhaka, to emerge as aware of gaps in close observation, and to prink tips primarily based on honesty and surely on the findings. Google scholar, PubMed, and Bangladeshi journals online have been searched for the use of applicable key phrases to select articles connected to antibiotic resistance in Dhaka, Bangladesh published between 2004 to 2020. The resistance of a bacterium to a given drug was once added as the median resistance and interquartile fluctuate. Forty-one articles have been blanketed in this systematic review. Antimicrobial susceptibility trying out used to be once as quickly as carried out via disk diffusion approach in 97.56% of studies, at the equal time as the clinical and laboratory standards institute suggestions had been accompanied in 92.68%. Data concerning the susceptibility attempting out method and furnish of sickness (hospital/community) had been absent in 12.19%, 10.52%, and 90.24% of the research, respectively. An excessive prevalence of resistance used to be detected in most examined pathogens, and many of the normal first-line pills have been the most importantly ineffective. Resistance to carbapenems was once low in most cases. An excessive incidence of resistance to most antibiotics used to be detected, alongside necessary gaps in surveillance and facts gaps in the methodological data of the show up to be up

    A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization

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    Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO\u27s exploration phase is enhanced, and the SHO\u27s hunting mechanisms are modified with PSO\u27s velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization

    Fruit Quality Assessment with Densely Connected Convolutional Neural Network

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    Accurate recognition of food items along with quality assessment is of paramount importance in the agricultural industry. Such automated systems can speed up the wheel of the food processing sector and save tons of manual labor. In this connection, the recent advancement of Deep learning-based architectures has introduced a wide variety of solutions offering remarkable performance in several classification tasks. In this work, we have exploited the concept of Densely Connected Convolutional Neural Networks (DenseNets) for fruit quality assessment. The feature propagation towards the deeper layers has enabled the network to tackle the vanishing gradient problems and ensured the reuse of features to learn meaningful insights. Evaluating on a dataset of 19,526 images containing six fruits having three quality grades for each, the proposed pipeline achieved a remarkable accuracy of 99.67%. The robustness of the model was further tested for fruit classification and quality assessment tasks where the model produced a similar performance, which makes it suitable for real-life applications.Comment: Accepted in 12th ICECE (4 pages, 3 Figures, 3 Tables

    An Efficient Transfer Learning-based Approach for Apple Leaf Disease Classification

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    Correct identification and categorization of plant diseases are crucial for ensuring the safety of the global food supply and the overall financial success of stakeholders. In this regard, a wide range of solutions has been made available by introducing deep learning-based classification systems for different staple crops. Despite being one of the most important commercial crops in many parts of the globe, research proposing a smart solution for automatically classifying apple leaf diseases remains relatively unexplored. This study presents a technique for identifying apple leaf diseases based on transfer learning. The system extracts features using a pretrained EfficientNetV2S architecture and passes to a classifier block for effective prediction. The class imbalance issues are tackled by utilizing runtime data augmentation. The effect of various hyperparameters, such as input resolution, learning rate, number of epochs, etc., has been investigated carefully. The competence of the proposed pipeline has been evaluated on the apple leaf disease subset from the publicly available `PlantVillage' dataset, where it achieved an accuracy of 99.21%, outperforming the existing works.Comment: Accepted in ECCE 2023, 6 pages, 6 figures, 4 table

    Surface Characteristics of Ti-5Al-2.5Sn in Electrical Discharge Machining Using Negative Polarity of Electrode

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    A large number of parameters significantly affect the performance of electrical discharge machining (EDM) which is a non-conventional technique. The choice of the EDM parameters depends on workpieceelectrode material combination. So, the selection of parameters becomes intricate. This manuscript presents the surface characteristics of the machined surface in EDM on Ti-5Al-2.5Sn titanium alloy. The surface roughness and the microstructure of the machined surface are explored for different EDM parameters and electrode materials. Experimentation was accomplished using negative polarity of copper, copper-tungsten and graphite electrode. In this study, peak current, pulse-on time, pulse-off time and servo-voltage are taken into consideration as process variables. The surface roughness is greatly influenced by peak current and pulse-on time among the selected electrical parameters. Among the three electrodes, the copper electrode produces the lowest surface roughness whilst graphite electrode gives the highest surface roughness. The surface characteristics (crater, crack and globule) are distorted on account of discharge energy. In context of fine surface characteristics, the copper can become as first choice electrode materials
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