Caribbean Journal of Sciences and Technology 2024-03-20T16:47:52+00:00 M/s. ChemBio International Open Journal Systems <p style="text-align: justify;"><em>Caribbean Journal of Science and Technology (CJST)</em> is a half yearly (from 2022), international, open access, peer-reviewed Journal and committed to publish multidisciplinary subjects related to biological, chemical, pharmaceutical, and all technological sciences. Further, CJST preferably encourages articles with novelty. CJST publishes manuscripts of the type Full-length research articles, Review articles, Mini-reviews, Short communications, Case Studies, Perspectives and Letters to the Editor.</p> Solvent-free Synthesis of Fused Pyrimidone Derivatives from Baylis-Hillman Acetates 2024-01-07T05:40:45+00:00 Srihari Ch Siva Rama Krishna Reddy V Santha Kumari Merugu Valli Purnima B Siddique Akber Ansari Ravi Varala Hari Babu Bollikolla <p>By using the Baylis-Hillman acetates as the starting materials, an improved eco-friendly process for the synthesis of fused pyrimidone derivatives has been established. These reactions provide considerable yields (67-78%) of fused pyrimidone derivatives and are easily carried out under mild, solvent-free conditions.</p> 2023-12-31T00:00:00+00:00 Copyright (c) 2023 Caribbean Journal of Sciences and Technology An investigation on the effects of nanoplastic particles on Chlorella vulgaris enzymes and its function on removal of nitrate and phosphate 2024-01-01T06:10:47+00:00 Parichehr Hanachi Maryamsadat Shahidi Mehdi Khoshnamvand Masoomeh Shafiei Hamieh Goshtasbi <p>Plastic waste at sea has been a primary environmental concern for years. The degradation of plastics into small pieces leads to the formation of nanoplastics (NPs) (less than 100 nm) that can enter the environment. Polystyrene is one of the most common plastics, a product of the polymerization of styrene monomers. In this study, the toxic effects of amino polystyrene (PS-NH<sub>2</sub>) NPs with sizes 90 (PS-NH<sub>2</sub>-90), 200 (PS-NH<sub>2</sub>-200), and 300 (PS-NH<sub>2</sub>-300) nm with four different concentrations after 72 hours on viability, activity of enzymes such as superoxide dismutase (SOD), catalase (CAT), glutathione S-Transferase (GST) and reduced glutathione (GSH), carbonyl protein and sulfhydryl protein and antioxidant activity assay by DPPH reagent on the <em>Chlorella vulgaris</em> were investigated. In all enzymatic assays, except the glutathione (GSH) and sulfhydryl protein, the size of 90 nm showed lowest value. Intriguingly, flow cytometry assessment showed a substantial reduction in the viability at PS-NH<sub>2</sub>-90 treated samples for 72 h which means that as the size of the nanoplastic decreases, its toxicity will increase. The toxicity effect of 90 nm NPs with a concentration of 200 mg/L on the microalgae <em>C. vulgaris</em> (with a concentration of 25000 Cells/mL) with the aim of bioremediation of nitrate (with a concentration of 50 mg/L) and phosphate (with a concentration of 6 mg/L) were investigated. According to the obtained results, NPs with a concentration of 200 mg/L with a size of 90 nm have the highest toxicity on the nitrate and phosphate bioremediation by the <em>C vulgaris</em> with a concentration of 25000 Cells/mL.</p> 2023-12-31T00:00:00+00:00 Copyright (c) 2023 Caribbean Journal of Sciences and Technology Enhancing Administrative Efficiency with HIT in Federal Healthcare 2024-01-26T11:22:24+00:00 Sripriya Bayyapu <p>The federal healthcare system in the United States serves millions of Americans, and ensuring the highest quality of care is paramount. Health information technology (HIT) presents a powerful tool to achieve this goal. This paper explores the potential of HIT in improving quality across various aspects of federal healthcare, including clinical care, patient engagement, population health, and administrative efficiency. It examines specific functionalities such as electronic health records (EHRs), telehealth, clinical decision support systems (CDSS), and data analytics. Challenges and barriers hindering optimal HIT utilization are discussed, along with solutions and best practices for successful implementation. By leveraging HIT effectively, the federal healthcare system can enhance quality, optimize resource allocation, and empower patients in their own health journey.</p> <p>This research concludes that by embracing HIT advancements, investing in infrastructure, and training, and prioritizing data-driven initiatives, the federal healthcare system can embark on a transformative journey towards enhanced quality, improved access.</p> 2023-12-31T00:00:00+00:00 Copyright (c) 2024 Caribbean Journal of Sciences and Technology Sulfated tin oxide (STO)-Catalyzed Efficient Synthesis of β-Enaminoesters 2024-03-17T16:25:41+00:00 Srihari Chennuboyina Ramya Krishna Pallapati Pallapati Vijaya Saradhi Ch ravi varala Hari Babu Bollikolla <p>Sulfated tin oxide (STO) is characterized as an effective catalytic system for the synthesis of β-enaminoesters from β-ketoesters. This method has a number of benefits, including shorter reaction times, use of inexpensive and readily available catalyst, compatible reaction conditions, and high product yields.</p> 2023-12-31T00:00:00+00:00 Copyright (c) 2024 Caribbean Journal of Sciences and Technology Speech Emotion Recognition for Autism Spectrum Disorder 2024-03-20T16:47:52+00:00 Sailaja Maddela <p>Our project demonstrates how an emotion can be inferred from the audio file in which the speaker has spoken. The primary goal of this project development is to assist children with Autism Spectrum Disorder (ASD) who cannot identify emotion from speech and may benefit from this project's ability to do o. We are concentrating mostly on this model's fundamental problem of high variance (Overfitting), which may be caused by the lack of audio recordings utilized to train the model. Ryerson's Audio-Visual Database of Emotional Speech and Song (RAVDESS) and the Toronto Emotional Speech Set (TESS) dataset were excellent training datasets for this model to overcome the overfitting issue. Noise removal will be performed as part of the pre-processing step using Python algorithms. Mel-frequency Cepstrum Coefficient (MFCC) simulates the audio features mechanism. Numerous applications support human-computer interactions, but in this case, we're introducing deep learning neural networks (CNN) and Multilayer Perceptron (MLP) to recognize and categorize the precise output. Our final model will classify 8 different emotions (anger, calm, disgust, fearful, happy, neutral, sad, and surprised) with better accuracy.</p> 2023-12-31T00:00:00+00:00 Copyright (c) 2024 Caribbean Journal of Sciences and Technology