Volume 12 | Issue 3 |

 Abstract

Abstract: Cancer is characterized by uncontrolled cell growth and acquisition of metastatic properties. Some common forms include breast cancer, lung cancer, prostate cancer, colorectal cancer, and leukemia. Despite significant advances in research and treatment modalities, cancer remains a significant public health challenge, with millions of new cases diagnosed each year. For effective cancer therapy, it is necessary to improve and develop novel strategies for effective delivery of chemotherapeutics to cancer cells. Conventional chemotherapeutic agents accumulate both in normal and tumor cells due to non-specificity. The ultimate goal of cancer therapy is to reduce systemic toxicity and improve the quality of life. The landscape of cancer treatment has improved significantly over the past four decades. Novel treatment with ONCOS-102, developed by Targovax, is a genetically modified adenovirus designed to selectively infect cancer cells in lungs and stimulate anti-tumor immune responses has been developed in recent years. New approaches, such as Photodynamic therapy(PDT) is a minimally invasive treatment that utilizes a photosensitizing agent, light, and oxygen to selectively destroy oral cancer cells. One photosensitizer that has shown promise in oral cancer treatment is 5-aminolevulinic acid of oral cancer. Immune checkpoint inhibitors, such as anti-PD-1 or anti-PD-L1 antibodies, block this interaction, thereby reactivating T cell-mediated anti-tumor immune responses in Breast cancer. With the development of molecular biology and genomics, targeted therapy research has achieved a breakthrough development, including anti-angiogenesis, immune checkpoint inhibitors, and other treatments that are efficient for treatment of cervical cancer. a novel approach to the development of AR antagonists is to target the amino-terminus domain of the AR. The small molecule AR antagonist EPI-001 inhibits protein-protein interactions necessary for AR transcriptional activity. A promising novel approach for treating gastric cancer involves targeting the human epidermal growth factor receptor 2 (HER2), which is overexpressed in approximately 20% of gastric cancers.

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 Keywords

- Photodynamic therapy, programmed death-ligand 1, human epidermal growth factor receptor 2, Androgen Receptor Signaling Pathway

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In recent years studies on drug utilization (DU) have become a potential tool to be used in the evaluation of health systems. Studies on the process of DU focus on factors related to prescribing, dispensing, administering and taking of medication and its associated events. DU data is available from databases - computerized or otherwise. From these databases different types of information, qualitative or quantitative or referring to a particular population are available. Patient files and computer registries are widely used as instruments for collecting information on DU. Prospective, Concurrent or Retrospective Drug utilization evaluation (DUE) may be used depending upon the timing of data collection. Importance of DUE in Pharmacoepidemiology (PE) have been increasing due to their close association to other areas like - public health, Pharmacovigilance (Pv), Pharmacoeconomics and pharmacogenetics. This review article highlights various aspects, scope, types and future perspectives of DUE.

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 Keywords

Drug utilization (DU), Pharmacoepidemiology (PE), Pharmacoeconomics, Data collection, Drug utilization evaluation (DUE) cycle.

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Leukemia, a widespread and life-threatening cancer that affects people of all ages, is a global health problem. This disorder predominantly affects White Blood Cells (WBCs), altering bone marrow and blood and causing immature lymphocyte proliferation. The accurate and prompt identification of leukemia is critical for successful treatment and increased survival rates. Currently, the diagnosis is based on manual examination of blood samples from microscopic pictures, a slow, time-consuming technique with inadequate accuracy. Furthermore, the visual resemblance between leukemic and normal cells under a microscope adds to the detection problem. Recent years have witnessed the emergence of Convolutional Neural Network (CNN)-based deep learning algorithms, setting new benchmarks in image classification. However, chances to improve their efficacy, learning processes, and overall performance remain, notably in the field of leukemia diagnosis. In this detailed analysis, we dig into several methodologies previously used in the field of blood cancer detection. In addition, we highlight the field by displaying benchmark datasets often used in leukemia detection studies. We want to clarify the intricacies and complexity within this domain through comparative study, thereby driving advancement in leukemia diagnosis and treatment.

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 Keywords

Leukemia Cancer, Deep Learning, Machine Learning, Convolutional Neural Network, Microscopic images.

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The judicial landscape in India is undergoing a significant transformation with regards to the protection and enforcement of the rights of victims. This article delves into the intricate judicial pursuit aimed at safeguarding the rights of victims within the Indian legal framework. Through an analysis of landmark cases, legislative developments, and judicial pronouncements, this study offers insights into the evolving nature of victim rights protection. Key areas of focus include access to justice, compensation, rehabilitation, and participation in legal proceedings. The article highlights the challenges faced by victims in navigating the legal system and the efforts made by the judiciary to address these challenges. Moreover, it explores the role of judicial activism and public interest litigation in advancing the cause of victim rights. By examining the principles of restorative justice and victim-centric approaches, this article underscores the need for a holistic and rights-based approach towards victim protection. Ultimately, it contributes to the ongoing discourse on enhancing the efficacy of legal mechanisms in promoting the rights and dignity of victims in India's evolving socio-legal landscape.

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Victim rights, judicial pursuit, India, access to justice, compensation, rehabilitation, legal proceedings.

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In this paper, we propose the use of CycleGAN for custom outfit generation. CycleGAN is a type of Generative Adversarial Network (GAN) that can learn to map images from one domain to another domain without requiring paired training data. Our goal is to generate new, realistic images of clothing items based on existing images from a different source domain. We propose a novel approach that combines CycleGAN with a fine-tuning step using a small set of paired data. Our approach is able to generate custom outfits that are both realistic and visually appealing, with high-quality details and textures. We evaluate our approach using a clothing dataset and demonstrate that it outperforms other state-of-the-art methods in terms of image quality and visual similarity.

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CycleGAN, GAN.

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The depression is a medical condition and it is among the major mental diseases that affects numerous people worldwide. For this work, the Distress Analysis Interview Corpus-Wizard of Oz interviews (DAJC-WOZ) dataset will be utilized which contains 189 sessions in zip file format and responses from 59 depressed and BO non-depressed patients[1]. This dataset has video, audio and text clips so individual preprocessing techniques are utilized which is given as a source for depression detection level. The inputs are in the form of video, audio and text, so individual preprocessing methods for feature extraction are used with separate techniques. Then, the extracted features from separate techniques are concatenated and given as input for the classification of depression level. The Long-Short Term Memory (LSTM) can be utilized in this research for classifying the depression levels

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 Abstract

vikashshil desho k liye aarthik prgati me buniyadi dhache ke mhatva ka adhyayan

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vikashshil desho k liye aarthik prgati me buniyadi dhache ke mhatva ka adhyayan

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Wheat crop classification and prediction are important tasks for the optimization of crop yield and resource utilization. In this study, we propose an Artificial Neural Network (ANN) model integrated with Genetic Algorithm (GA) to predict and classify the wheat crop images of different ages. The dataset of 19,300 images was used, and the model was trained and tested using various performance evaluation metrics. The results show that the proposed ANN+GA model achieved the highest accuracy of 99.29% during the training phase and 98.65% during the testing phase. The model was also compared with other state-of-the-art machine learning models, and the proposed model was found to be superior in terms of accuracy, specificity, sensitivity, precision, and F-measure. The graph of training and testing accurateness and loss values in contradiction of individual epoch demonstrating the speediness of model convergence. Our proposed model is feasible and robust, giving better classification and crop forecast outcomes for numerous wheat crop age groups with least resource necessities. These findings could be useful for farmers and agricultural researchers in improving crop yield and resource management.

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Genetic algorithm, Artificial Neural Network, prediction, crop yield

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 Abstract

Competency helps to perform your work/job effectively. Competency is human quality, like- collaborative skills, knowledge and skills. An effective digital pedagogy thus starts not with a static list of tools, but with fundamental learning goals and strategies, to which appropriate technology is added to strengthen student outcomes and objectives. Technological awareness expresses the knowledge, experience, comfort and skills needed to use basic technology. In the 21st century, it is essential for teachers because today's word is changing rapidly and the education sector is experiencing these changes, especially in media. The overarching purpose of this research was to find out to what is the competency of teacher to use the technology in teaching. A representative sample of 90 higher secondary school teachers (50 in the city and 40 in the village side) was taken, and Teacher's Techno- Pedagogical Competence Scale developed by S. Rajshekhar and K. Sathiyaraj, was used to collect data. The scale consists 40 items divided into four category- I. Technology in preparation for teaching, II. Technology in providing motivation, III. Technology in presentation, IV. Technology in evaluation. After collecting or analyzing the data, the researcher found that there is no significant difference between Techno - Pedagogical Competency of higher secondary school teachers based on gender (male and female) and region (urban and rural).

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 Keywords

Technology, Digital Pedagogy, Technology and Pedagogy

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The importance of road transport is huge as it plays a vital role in connecting people. According to data released by the Pune City Traffic Police, nearly 293 Punekars lost their lives in road accidents in the city in 2022. An analysis conducted by the Pune Traffic Branch has revealed that of the 87 fatal two wheeler deaths in accidents on Pune roads in 2020. The timely emergency pre-hospital care and subsequent transportation of accident victims to the health facility may help reduce the accident and injury outcomes. This project focuses on detecting ongoing accidents to activate emergency services promptly. The system is equipped with sensors which are capable of detecting sudden impacts or collisions, signifying the occurrence of an accident. Key feature of the project include the seamless operation of the embedded system, allowing it to function without interfering with the bike's normal operations. In brief, the project holds the potential to save lives and improve emergency management for motorcycle accidents, providing a vital contribution to road safety without going into accident prediction.

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 Keywords

SOS, Emergency services, Sensors, Accident detection

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