Novel Ceramics and Metal-Ceramic Composites via Fused Deposition Process

Indirect fused·· deposition process is utilized.·.. to ·fabricate controlled porosity ceramic structures using alumina, mullite, zirconia, LSCF-perovskite, tricalcium phosphate and hydroxyapatite, where pore size, pore shape and pore connectivity are varied from one end to the other end of the parts. Some of these porous ceramics are then infiltrated with metals via pressureless reactive metal infiltration to form novel metal-ceramic composites. Thispaper will describe processing, structures of various porous and metal-infiltrated composites and their physical and mechanical properties.Mechanical Engineerin

Deep Forward and Inverse Perceptual Models for Tracking and Prediction

We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically, we present a perceptual model for generating video frames from state with deep networks, and provide a framework for its use in tracking and prediction tasks. We show that our proposed model greatly outperforms standard deconvolutional methods and GANs for image generation, producing clear, photo-realistic images. We also develop a convolutional neural network model for state estimation and compare the result to an Extended Kalman Filter to estimate robot trajectories. We validate all models on a real robotic system.Comment: 8 pages, International Conference on Robotics and Automation (ICRA) 201

A Bi-Directional GRU Architecture for the Self-Attention Mechanism: An Adaptable, Multi-Layered Approach with Blend of Word Embedding

Sentiment analysis (SA) has become an essential component of natural language processing (NLP) with numerous practical applications to understanding “what other people think”. Various techniques have been developed to tackle SA using deep learning (DL); however, current research lacks comprehensive strategies incorporating multiple-word embeddings. This study proposes a self-attention mechanism that leverages DL and involves the contextual integration of word embedding with a time-dispersed bidirectional gated recurrent unit (Bi-GRU). This work employs word embedding approaches GloVe, word2vec, and fastText to achieve better predictive capabilities. By integrating these techniques, the study aims to improve the classifier’s capability to precisely analyze and categorize sentiments in textual data from the domain of movies. The investigation seeks to enhance the classifier’s performance in NLP tasks by addressing the challenges of underfitting and overfitting in DL. To evaluate the model’s effectiveness, an openly available IMDb dataset was utilized, achieving a remarkable testing accuracy of 99.70%

A Novel Paradigm for Sentiment Analysis on COVID-19 Tweets with Transfer Learning Based Fine-Tuned BERT

The rapid escalation in global COVID-19 cases has engendered profound emotions of fear, agitation, and despondency within society. It is evident from COVID-19-related tweets that spark panic and elevate stress among individuals. Analyzing the sentiment expressed in online comments aids various stakeholders in monitoring the situation. This research aims to improve the performance of pre-trained bidirectional encoder representations from transformers (BERT) by employing transfer learning (TL) and fine hyper-parameter tuning (FT). The model is applied to three distinct COVID-19-related datasets, and each of the datasets belongs to a different class. The evaluation of the model’s performance involves six different machine learning (ML) classification models. This model is trained and evaluated using metrics such as accuracy, precision, recall, and F1-score. Heat maps are generated for each model to visualize the results. The performance of the model demonstrates accuracies of 83%, 97%, and 98% for Class-5, Class-3, and binary classifications, respectively

IN VITRO BIOLOGICAL STUDY OF SEVEN NEPALESE MEDICINAL PLANTS AND ISOLATION OF CHEMICAL CONSTITUENTS FROM CISSAMPELOS PAREIRA

Objective: This study aimed to investigate the phytochemical analysis and biological activities of methanol extracts of seven medicinal plants such as Anisomeles indica, Achyranthes bidentata, Sphenomeris chinensis, Cleistocalyx operculatus, Malvaviscus arboreus, Cissampelos pareira, and Tectaria coadunate collected from Tanahun district of Nepal. Methods: Phytochemical analysis was performed by color differentiation methods adopting the standard protocol. Antioxidant activity of plant extracts was evaluated by 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay. Flavonoid content was estimated by aluminum chloride colorimetric method. Antidiabetic activity was evaluated by α-amylase inhibition assay where acarbose was used as standard. Toxic effect was studied by brine shrimp bioassay. Results: Phytochemical analysis showed the presence of alkaloids, polyphenols, flavonoids glycoside, and terpenoid in most of the extracts. T. coadunate and C. pareira exhibited high antioxidant activity with IC50 41.84 and 52.03 μg/ml, respectively. Whereas, the plant extracts of Malvaviscus arboretum, S. chinensis, and A. bidentata exhibited moderate antioxidant activity with IC50 76.07, 81.05, and 89.93 µg/ml, respectively. The result of flavonoid content showed the values ranged A. indica (1.84 mg quercetin equivalent per gram [mg QE/g]) to A. bidentata (5.93 mg QE/g). C. pareira and S. chinensis exhibited the highest α amylase inhibition activity with IC50 471.68 and 517.59 µg/ml, respectively. Whereas, A. indica and M. arboreus showed moderate activity with IC50 626.12 and 952.39 μg/ml, respectively. C. pareira exhibited against Staphylococcus aureus (ATCC 25923) with a zone of inhibition 12 mm/well, and Escherichia coli (ATCC 25922) 9 mm/well but, T. coadunate showed 14 mm/well against S. aureus. The plant extracts of A. bidentata and C. operculatus showed toxic effect against newly hatched brine shrimp larvae. The chemical compounds isolated from C. pareira indicated by gas chromatography-mass spectrometry analysis were 3-isopropoxy-1,1,1,7,7,7-hexamethyl-3,5,5-tris(trimethylsiloxy) tetrasiloxane, alpha-tocopherol, pentadecanoic acid, and 4,22-stigmastadiene-3-one. The major compound was indicated by percent peak area and base m/z value as alpha-tocopherol. Conclusion: Present study revealed that plant extracts are the potential source of antioxidant, antidiabetic, and antibacterial agents showing different biological activities. The results of this study provide partial scientific support for the traditional application of medicinal plants to cure diabetes and infectious diseases, although further studies are needed to assess the mechanism of action

ACUTE HYDROCEPHALUS SECONDARY TO INTRAVENTRICULAR NEUROCYSTICERCOSIS CAUSING SUDDEN DEATH.

Neucysticercosis (NCC) is the most common Helminthic infection of the central nervous system and its epidemiology is changing due to increasing travel and migration. Evidence to guide management of the intraventricular form is limited. The intraventricularvariant of NCC is less common than parenchymal disease and usually presents with acutely raised intracranial pressure and untreated it progresses rapidly with high mortality. It is considered as a potentially life threatening emergency. We report an acute case of 30 year old female who suffered from cephalalgia which rapidly worsened and ended in her sudden and unexpected death. Magnetic resonance imaging (MRI) of the brain was obtained. Features demonstrated on MRI scan were consistent with a diagnosis of intraventricular NCC