Volume 13 | Issue 12 |

 Abstract

Cerebral palsy (CP) is a disorder characterized by abnormal tone, posture and movement and clinically classified based on the predominant motor syndrome--spastic hemiplegia, spastic diplegia, spastic quadriplegia, and extrapyramidal or dyskinetic. The incidence of CP is 2-3 per 1,000 live births. Prematurity and low birthweight are important risk factors for CP; however, multiple other factors have been associated with an increased risk for CP, including maternal infections, and multiple gestation. In most cases of CP the initial injury to the brain occurs during early fetal brain development; intracerebral hemorrhage and periventricular leukomalacia are the main pathologic findings found in preterm infants who develop CP. The diagnosis of CP is primarily based on clinical findings. Early diagnosis is possible based on a combination of clinical history, use of standardized neuromotor assessment and findings on magnetic resonance imaging (MRI); however, in most clinical settings CP is more reliably recognized by 2 years of age. Because CP is associated with multiple associated and secondary medical conditions, its management requires a multidisciplinary team approach. Most children with CP grow up to be productive adults. Sahaja (Hereditary) Garbhaja (Congenital) and Jataja (Psychosomatic) types of diseases. Aim & Objectives: The aim of this study was to assess the efficacy of Ayurvedic interventions, including oral medications and Panchakarma procedures, in improving the condition of patient with spastic cerebral palsy who had previously shown no improvement with conventional treatments. Materials and methods: This case study Age of the patient - Sex of patient male Age of patient 3 y 6m,In Developmental history,No neck holding. Neonatal history: Term baby Meconium aspiration Weak cry HIE, Fever with convulsions after a week of discharge Treatment at various higher centres Complaints :Unable to stand on its own Drowlling Unable to chew food. Patient was advised admission for 7 days and was treated with internal medications, During the treatment all the signs and symptoms of cerebral palsy reduced to a very high extend.

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Shalipinda Sweda, Abhyanga, Shamanoushadi, Swarnaprashana.

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 Abstract

Jhaarakhand Rajay Mein Vidhaan Sabha Chunaav (2024) Mein Jhaamumo Ke Jeet Aur Bhajapa Ke Parajay Ke Pramukh Karak - Ek Sameeksha

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Jhaarakhand Rajay Mein Vidhaan Sabha Chunaav (2024) Mein Jhaamumo Ke Jeet Aur Bhajapa Ke Parajay Ke Pramukh Karak - Ek Sameeksha

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Road traffic accidents remain a major global safety challenge, with driver fatigue and alcohol consumption identified as leading causes. This project proposes the development of a smart, real-time embedded safety system designed to continuously assess driver alertness and detect alcohol impairment. Driver drowsiness is identified using computer vision-based facial analysis, where facial landmarks are tracked to compute the Eye Aspect Ratio (EAR). Alcohol presence is detected through breath analysis using an MQ3 alcohol sensor. When hazardous conditions are identified, the system immediately issues preventive alerts via a buzzer and an OLED display, enabling timely corrective action. The solution is implemented on an ESP32 platform and utilizes Python with OpenCV for real-time image processing. This cost effective and non-intrusive system bridges the gap between expensive commercial driver monitoring solutions and conventional reactive safety mechanisms. Experimental results indicate reliable real-time performance with high detection accuracy and reduced false alarms, making the system a practical and proactive approach to improving road safety.

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Driver Drowsiness Detection, Alcohol Detection, Eye Aspect Ratio, Machine Vision, MQ3 Sensor, ESP-32 , Real- Time Monitoring

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The present research attempts to develop a first order (D1) UV-spectrophotometric method that is convenient to use, robust, cost-effective, quick, and precise for the simultaneous measurement of Dapagliflozin propanediol monohydrate and Eplerenone in their synthetic mixture. The method was validated as per ICHQ2(R2) guidelines. Methanol was utilized as solvent for preparation of sample solution and the detection wavelength to determine DAPA and EPLE in developed fist order UV spectrophotometric method was 240.41 nm and 254 nm respectively. The linearity range for DAPA is 4-12 ?g/ml and EPLE is 10-30 ?g/ml in methanol. The regression coefficient was found to be 0.9988 and 0.9969 for DAPA and EPLE respectively. The LOD and LOQ for DAPA was identified to be 0.4693 and 1.4222 and that for EPLE was 1.314 and 3.983 respectively. Thus, this method provides suitable advantages like improved resolution of overlapping peaks, better selectivity, minimizes background interference. The developed method was successfully applied for the quantification of DAPA and EPLE from their synthetic mixture.

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Dapagliflozin Propanediol Monohydrate (DAPA), Eplerenone (EPLE), First order derivative (D1) UV-Spectrophotometric method, ICH Q2(R2) Guideline

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The report presents a fast and adaptable ship routing algorithm leveraging machine learning techniques to optimize maritime navigation, considering real-time environmental factors. It addresses limitations of traditional rigid routing methods by incorporating dynamic data such as weather, sea currents, and vessel load to improve fuel efficiency, safety, and operational costs. The developed system demonstrates enhanced route planning performance, contributing towards sustainable and intelligent maritime transportation.

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Ship Routing Optimization, Machine Learning, Maritime Navigation, Adaptive Routing Algorithm.

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Pharmacovigilance (PV) is a crucial scientific discipline that focuses on the detection, assessment, understanding, and prevention of adverse effects or any drug- related problems. As the global pharmaceutical industry continues to expand and innovate, ensuring drug safety has become more important than ever.

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Pharmacovigilance, global drug safety, Uppsala Monitoring Centre

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Food and catering services play a vital role in meeting the dietary and event needs of customers in urban areas. Customer satisfaction in this sector depends on multiple factors such as service quality, food quality, staff behavior, timeliness, and overall service experience. This study aims to assess the level of user satisfaction in food and catering management services in Tirupur and to identify the factors that most influence customer preferences. A structured questionnaire was administered to 100 customers, collecting information on demographic profiles, usage patterns, and satisfaction levels. Data were analyzed using descriptive statistics, ranking analysis and chi-square tests to examine relationships between variables. The results indicate that timely service, staff behavior, and food quality are the most critical factors affecting customer satisfaction, while other factors such as hygiene, pricing, and ambience also contribute moderately. The findings provide useful insights for catering service providers to enhance service quality and meet customer expectations effectively.

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Customer satisfaction, food quality, service quality, catering management, event management, services, etc.,

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Amish Tripathi's Shiva Trilogy has emerged as a significant contribution to contemporary Indian fiction, reimagining mythological narratives through the lens of humanism and ethical leadership. This paper examines how the trilogy systematically privileges human agency, ethical reasoning, and moral autonomy over traditional constructs of divinity, fate, and predestination. Through close reading and engagement with leadership theory, this research explores how Tripathi crafts Shiva not as a predestined god but as a leader shaped by empathy, reason, and ethical deliberation. The analysis highlights the trilogy's challenge to divine right and explores its implications for ethical leadership in both literary and real-world contexts. The findings suggest that Tripathi's humanistic reinterpretation of myth offers valuable insights for leadership studies and the evolution of Indian literary traditions.

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Amish Tripathi, Shiva Trilogy, humanism, ethical leadership, Indian mythology, divinity, leadership theory, contemporary fiction

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According to studies of international monetary data, the sum of money lost due to fraud in all transactions around the world keeps rising. In particular, the adoption of the Bank-as-a-Service model by financial institutions will place additional strain on payment processing infrastructure and exacerbate the already serious problem of payment fraud. Using automated machine training and Big Data analysis methods, this research aims to synthesis viable solutions for detection of fraud in electronic payment systems. Online Payment fraud has been given a lot of attention since it can result in significant economic losses and negative consequences for account holders. In order to construct a reliable model for identifying fraud, it is essential to employ efficient feature engineering. It is discovered, however, that the present feature engineering that relies on transaction frequency has flaws. Convenient as they may be, fraudsters are drawn to modern money transfer services to conduct scams in which unsuspecting victims are tricked into sending money to fake accounts. As a result of the limitations of conventional rule-based methods for detecting fraud, machine learning models have found widespread application. Most studies build features by extracting patterns using raw transaction records because learning directly from transaction data is challenging owing to its enormous dimensionality. Recency, frequency, financial, and anomaly detection are some of the common labels used to classify these characteristics in the existing research. Using real-world transaction data, features can be extracted and most relevant features can be selected to train the machine learning model for accurate fraud detection. The temporal properties of user transactions are shown using frequency-based feature engineering, however the characteristics of fraud and the differentiation of transaction behaviors are not taken into sufficient account. In this research a Multi Level Associated Weighted Feature Vector (ML-AWFV) Model using machine learning is proposed for accurate feature extraction and selection for further processing of online payment fraud detection. The proposed model when contrasted with the existing

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Keywords: Online Payment Fraud, Transactions, Feature Extraction, Feature Selection, Machine Learning, Financial Loss.

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This research examines how architecture students perceive and decode facade geometry at multiple scales. The exercise revealed how shifts in scale, fragmentation, and viewing distance generate diverse readings of the same elevation. By comparing these interpretations with the student's subsequent institutional facade designs, the study demonstrates how plural perceptions influence design thinking. The activity helps students understand complex elevations by making them see more clearly, recognize patterns, and find meaning in what they observe. This shows that studying a facade at different scales helps students understand it better. This method supports students in recognizing finer details, improving clarity in observation, and forming more meaningful interpretations of the architectural facade for their campus design

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Facade perception, scalar analysis, fractal geometry, architectural interpretation, design thinking, pattern recognition, architectural education.

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