Volume 13 | Issue 5 |

 Abstract

Abstract: Guppies exhibit breeding behaviour throughout the entire year, with the exception of the winter months, specifically December and January, while demonstrating a peak breeding period in July. The duration of the gestation period varied between 25 and 35 days, It was observed that the caudal region emerges first during the process of parturition. The quantity of fry produced per brood varied between 12 and 60. Newly hatched fries were documented as exhibiting either a transparent or dark pigmentation, characterized by an elongated morphology with developed jaws at the oral region, and demonstrated full capabilities for locomotion, ingestion, and evasion of threats. The guppy exhibited rapid growth, achieving sexual maturity within a period of 8 to 10 weeks and reaching its maximum size within 6 months.(PETERS, 1859) The experimental investigations were undertaken in the Curzon Hall precinct of the Dhaka University campus. A total of 40 specimens of fish were procured from the Kataban fish market as well as various drainage systems within the Curzon Hall vicinity and subsequently transferred to designated rearing aquaria. (PETERS, 1859) Males were readily identifiable due to the presence of a modified anal fin that manifests as a gonopodium, whereas females exhibited a less vibrant body coloration accompanied by a distended abdomen. Each aquarium was designed to contain a volume of 8-10 liters of water. Manual water changes were performed bi-daily in theafternoon, specifically when the therml conditions of the aquatic environment within the aquaarium approximated that of the municipal tap water. The guppy species demonstrates a preference for hard water and is capable of tolerating salinity levels of up to one ppt. Consequently, a half tablespoon (8g) of salt was systematically dissolved in 20 liters of water during each water change. The broods were provided with a diet consisting of bloodworms, belonging to the genus Chironomus along with larvae of mosquitoes, and commercially available pellet feed, administered bi-daily in the mornings and afternoons. The diameter of the eggs was meticulously measured to estimate fecundity. Twelve ripe females of Poecilia reticulata were randomly selected, and fecundity was assessed by enumerating the ova and the various stages of embryonic development through dissection of the abdominal region of the pregnant female specimens. The ontogenetic phase of the embryos present in the pregnant females was examined through dissection of the abdomen of the gravid females.

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Keyword: Guppy fish, Aquarium maintning, fry feeding, Aquarium maintain

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This paper demonstrates a speech recognition system for isolated spoken digits (0-9) based on Hidden Markov Models (HMMs), demonstrating an end-to-end pipeline covering feature extraction, training, and testing. Raw speech signals are analyzed to obtain cepstral coefficients, which are subsequently vector quantized to generate observation sequences. Each digit is represented by an individual HMM trained with the Forward-Backward algorithm, Viterbi decoding, and iterative Baum-Welch re-estimation. In testing, the system predicts unseen speech samples by calculating the likelihood of observation sequences with respect to trained models and predicting the digit of highest likelihood. With high accuracy, the system shows the efficiency of statistical modeling in speech recognition and its promise for real-world use.

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Speech Recognition, Machine Learning, Hidden Markov Models, Feature Extraction, Viterbi Algorithm, Baum-Welch Algorithm

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For patient safety, timely medicine ingestion and drug authenticity are essential, especially in areas where fake medications are common. In order to automate medicine verification and reminder scheduling, this study introduces a clever, AI-driven medication management system that combines computer vision and optical character recognition (OCR). The method makes use of EasyOCR for text recognition and the YOLOv5 object detection model for precise medication name extraction from packaging. Using official documents from the Central Drugs Standard Control Organization (CDSCO), the retrieved medicinal data is validated through the Gemini API and cross-referenced with a validated pharmaceutical dataset. The system retrieves pertinent drug information, such as uses, adverse effects, and safety warnings, after authentication. Users can set up medicine notifications with timing, frequency, and food-intake preferences using a configurable reminder module. To guarantee adherence, prompt reminders are given by email or SMS. Additionally, the system integrates real-time geolocation services using the Google Maps API, enabling users to locate nearby pharmacies for quick and safe access to verified medications. By lowering the possibility of consuming fake medications and increasing medication compliance with clever reminders, this method improves patient safety.

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Drug Authentication, Optical Character Recognition (OCR), YOLOv5, Healthcare Automation, Medicine Reminder System, CDSCO Verification.

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Background: Adhatoda vasica Nees also known as "Justicia Adhatoda L., vasaka, adosa, Malabar nut tree" belongs to the family of Acanthaceae is considered the most significant plant in the world. This plant has been used in the indigenous medicinal system of India for more than 2000 years. Vasicine is the main chemical constituent present in this plant which possess various medicinal properties like antispasmodic, sedative, expectorant, antitussive, anti-bacterial, anti-microbial, anti-diabetic, antiasthma, wound healing, abortifacient and anti-pyorrhea. Objective: The main objective of the study was to formulate and evaluate the antimicrobial properties herbal ointment from the local medicinal plants. Methods: The extract was obtained by the decoction method. Simple ointment IP was use as ointment base for the dispersion of the plant extract. The ointment was formulated and evaluated using standard parameters. The antimicrobial activity of the extract in different concentration were investigated by using one gram-positive bacteria (Staphylococcus aureus) and one gram-negative bacteria (Escherichia coli) through disc-diffusion method. Results: The antimicrobial potential of the formulated ointment was studied. The ointment also showed significant antimicrobial activity against all the tested organism. This activity was maintained when the extract was incorporated into the ointment base. Conclusion: In future, the extract can be used for the commercial production of Adhatoda vasica ointment. Similarly, this ointment can be tested for skin related bacterial infection.

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Adhatoda vasica; decoction; anti-microbial; disc-diffusion method; irritancy; spreadability; stability

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Background: This study aims to investigate the effectiveness of assertiveness training in reducing social anxiety among adolescent girls in selected high schools. The specific objectives are: 1. To determine the prevalence of social anxiety among adolescent girls. 2. To compare pre-test and post-test levels of social anxiety in study and control groups. 3. To assess the effectiveness of assertiveness training in reducing social anxiety among adolescent girls in the study group. Methodology: This study employed a quantitative evaluative approach, utilizing a quasi-experimental research design with a non-equivalent control group pre-test and post-test framework. This design allowed for the assessment of the effectiveness of assertiveness training on social anxiety among adolescent girls. Results: The prevalence of social anxiety among adolescent females within the experimental cohort indicated that 30 (54%) participants exhibited symptoms of social anxiety. In contrast, the control group revealed that 30 (46%) adolescent females also presented with social anxiety. Following the post-assessment, it was determined that within the experimental group, 110 (72.37%) participants reported the absence of social anxiety, 26 (17.1%) exhibited mild social anxiety, 12 (7.9%) experienced moderate social anxiety, and 4 (2.63%) displayed severe social anxiety. Conversely, in the control group, 99 (61.87%) reported mild social anxiety, 39 (24.37%) experienced moderate social anxiety, 17 (10.63%) indicated severe social anxiety, and 5 (3.13%) exhibited very severe social anxiety. With regard to the pre-test and post-test levels of social anxiety among adolescent females, the mean score reflecting the level of social anxiety in the experimental group was recorded at 63.49 during the pre-test and subsequently decreased to 58.11 in the post-test. The calculated paired 't' value was found to be 16.405*, which holds statistical significance at p<0.05. Conclusion: The study concluded that social anxiety is a significant issue among adolescent girls, particularly after the age of 12, with many developing social anxiety during this critical period of adolescence.

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 Keywords

Effectiveness, Assertiveness training, Social anxiety, Adolescent girls, High schools

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Enhancing the Power of Computer Vision through Data Science" offers a comprehensive exploration of how the fusion of these two cutting-edge fields can unlock new dimensions of technological innovation. By synergizing computer vision's ability to interpret visual data with data science's analytical prowess, attendees will leave with a deepened understanding of how to harness the combined power of these disciplines to create smarter, more perceptive, and ethically sound computer vision solutions. The rapid advancements in computer vision technology have transformed the way we interact with and perceive the world around us. From facial recognition systems to autonomous vehicles, computer vision has enabled a wide range of applications that enhance efficiency, safety, and convenience. The integration of data science techniques with computer vision technology has resulted in significant advancements across various domains. This exploration delves into how data science enhances the potential of computer vision, leading to breakthroughs that optimize accuracy, adaptability, and decision-making. Furthermore, the seminar explores the role of big data in revolutionizing computer vision applications. It examines how the abundance of visual data, coupled with data science methodologies, enables the creation of more comprehensive and context-aware vision systems. Attendees will gain an understanding of how data-driven insights can lead to improved decisionmaking in fields like healthcare diagnostics, industrial automation, and urban planning.

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Computer Vision, Deep Learning, Object Detection, Image Classification, Convolutional Neural Networks (CNN)..

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The authors intend to find out the life, livelihood and health security of the Bhumij study population during the Covid-19 Period. The findings of the study show that the Bhumij, a tribe in Odisha is a marginalized group but somehow built resilience to make improvements over the vulnerable life conditions and became successful in their trial. The timely intervention made by the PRI members, AWW, and ASHA about the out break of the contagious disease made them alert. They kept on continuing fishing and crab catching as it is their principal source of livelihood though there were hinderances in selling the fish due to police patrolling and irregularity of the daily market. They satisfactorily managed their household expenses with scarce resources. Simultaneously they acknowledge the healthy natural environment and the naturally built strong immune system which protected them to be infected from the contagious Corona virus. Moreover, the on time information and preventive measures of hand washing and social distancing saved them from the Corona pandemic. The social security system by the Government though was minimum but that made them happy. The migrant workers of the community reached home well in advance before the out break of Corona however, two migrant young men made more expenses to buy air tickets as to reach home. They not only overcame the pandemic but also built resilience so that the experiences can help them in the future course of any vulnerable situation in life.

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Bhumij Livelihood, Corona Pandemic, Lockdown Period, Social Distancing, Resilience and Revival,

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Cloud computing has revolutionized the way organizations manage and deploy IT resources, offering benefits like scalability, cost-efficiency, and accessibility. However, with these advantages come significant risks related to data security, privacy, compliance, and service reliability. This journal introduces a comprehensive Cloud Computing Risk Assessment Framework designed to evaluate and mitigate risks associated with the adoption and operation of cloud services. The framework is built around a multi-layered approach that includes risk identification, risk analysis, risk evaluation, and risk mitigation strategies. It addresses key concerns such as data integrity, multi-tenancy, access control, vendor lock-in, and service-level agreements (SLAs). Case studies and practical applications of the framework are discussed, illustrating its effectiveness in assessing risks across different deployment models (public, private, and hybrid clouds). This framework aims to guide organizations in making informed decisions about cloud adoption, ensuring secure and compliant cloud operations while minimizing potential vulnerabilities.

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- CC - Cloud Computing, RA - Risk Assessment, RM - Risk Management, SP - Service Provisioning, IaaS - Infrastructure as a Service, PaaS - Platform as a Service, SaaS - Software as a Service, OPTIMIS - Optimized Infrastructure Services, QUIRC - Quantitative Impact and Risk Assessment for Cloud Security, IT - Information Technology, SLAs - Service Level Agreements, VM - Virtual Machine, CSP - Cloud Service Provider, ISO - International Organization for Standardization, NIST - National Institute of

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A network architecture known as software-defined networking (SDN) moves the control panel to an application known as Controller, separating it from the data panel. The newest method for configuring, managing, and running networks is called software defined networking, or SDN. The network or application infrastructure's centralized store of policy and control instructions is called an SDN controller. Data across the network is vulnerable to assaults if it is not properly secured. We can set up SDN controllers to identify assaults like denial-of-service (DDOS) that can cause network congestion by using SDN policies. When the attack is identified, we can use the policies to determine whether to forward or drop the packet.

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SDN, DDOS, Network Architecture, Network Attack, IDS.

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Retailing ethics is critical in shaping consumer trust and loyalty, especially in online commerce, where ethical concerns such as Privacy, Security, and deceptive practices impact consumer behavior. The objective of this study was to assess the retailing ethics of selected online stores in Doha, State of Qatar, as perceived by consumers based on the six ethical dimensions: Privacy, Security, Reliability, Non-deception, Service Recovery, and Shared Value.

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Consumer Perception; E-commerce; Online Retailing Ethics; Consumer Trust; Consumer Loyalty; Ethical Dimensions; Consumer Perception; Online Retailers; Ethical Practices; Transparency; Deceptive Marketing; Service Quality; Qatar; Doha; Demographic Differences; Trust Factors; Ethics

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