Volume 13 | Issue 8 |

 Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by significant heterogeneity in behavioral and neurological patterns, making accurate diagnosis and personalized intervention challenging. Traditional diagnostic approaches primarily focus on binary classification, which is insufficient for severity-aware treatment planning. This paper presents an end-toend deep learning–based framework for ASD detection, severity stratification, and personalized intervention recommendation. The proposed methodology integrates supervised Deep Neural Network (DNN) classification with unsupervised K-Means clustering applied to latent feature representations to identify intra-class ASD subgroups. Following classification, only ASD-positive samples are clustered to discover severity- and behavior-based subgroups corresponding to mild, moderate, and severe ASD profiles. These subgroups are subsequently mapped to personalized intervention strategies using AR/VRbased therapeutic content. The proposed framework enables accurate ASD detection, captures hidden heterogeneity, and supports precision-driven intervention planning. Experimental evaluation demonstrates that clustering on deep latent features provides meaningful stratification beyond binary diagnosis, establishing a robust foundation for adaptive and intelligent ASD support systems.

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 Keywords

Autism Spectrum Disorder, Deep Neural Network, K-Means Clustering, Severity Stratification, Latent Feature Learning, Personalized Intervention, AR/VR Therapy

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Medicinal plants have been used to improve human health with little side effects. Iris ensata Thunb. Irsa (Iridaceae) East Asian native is important in Unani medicine with multiple therapeutic activities. Considered a deobstruent (Mufatteh e Sudad), expectorant (Mukhrij e Balgham), phlegm expelling agent (Mushil e Balgham) and antiseptic (D?fi' e Ta'affun), it is extremely popular when it comes to treating respiratory and inflammatory diseases. Unani formulations contain the rhizomes of Irsa to relieve nasal congestion, rhinitis, sore throat, respiratory discomfort, and ulcerative lesions. Phytochemical research has identified several active compounds, such as isoflavones, tannins, triterpenoids, phenolic acids, and essential oils, which have proven pharmacological properties: anti inflammatory, antimicrobial, hepatoprotective, bronchodilatory, and antiallergic. These results confirm synergy between the Unani traditional applications and the emerging scientific evidence. However, the existing evidence is still insufficient because there are several clinical trials and no standardized formulation yet. This review addresses the botanical characteristics, traditional applications, chemical profile, and pharmacological potential of Irsa and its applicability in ancient and modern environments. Despite the encouraging research findings about the potential therapeutic potential, it is important that its safety, effectiveness, and mechanism of action are validated through rigorous pharmacological tests and clinical trials. A combination of Unani wisdom and scientific validation may open the door to evidence based herbal medicine prepared using Iris ensata.

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 Keywords

Irsa, Iris ensata thunb., medicinal plants, phytochemicals, Unani medicine.

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Ionospheric TEC, LSTM, GNSS, Solar Cycle 25, Geomagnetic Index, Kp, Space Weather, Time Series Forecasting.

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The aim of this review is to expose the therapeutic and potential of ethnopharmocological drug, Ipomoea carnea Jacq. and to ellustrate the therapeutic utility of I. carnea Jacq from different literature sources. Phytomedicines are progressively being established in modern therapeutic science. The shrub I. carnea has been used traditionally for thousands of years. However, there are many scientific studies on this medicinal plant which reveals the presence of many phytocompounds (alkaloid, flavonoid, tannin and saponin) in this plant. In this review, we have summarized the biochemical efficiency of phytocompounds of I. carnea. Anti-bacterial, anti-fungal, anti-oxidant, anti-cancer, anti-convulsant, immunomodulatory, anti-diabetic, hepatoprotective, anti-inflammatory, anxiolytic, sedative and wound healing activities are shows by different phtyoextracts of plant and their different parts. However, some toxic effects have been also reported. Some of the major phytocompounds associated with the bioactivity of I. carnea have been reported. This review article might be valuable for phytotherapy researchers, as I. carnea can be a good source for drug development for pharmaceuticals and ayurvedic practitioners.

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Phytocompounds ,therapeutic ,flavonoids , hepatoprotective

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 Abstract

This project presents an IoT-based Smart Bus System with RFID and GSM technology, designed to improve public transportation convenience, safety, and automation. The main controller, an ESP32, manages an RFID ticketing system where passengers swipe their RFID cards to open the bus door, enabled by a servo motor (SM90). After boarding, passengers select their destination using a set of four switches, triggering the system to calculate the fare and send it, along with the GPS coordinates of both start and destination points, directly to the passenger's mobile phone via GSM.The system also includes a Blynk application interface, allowing drivers to control the bus remotely and adjust fare settings based on each stop. A limit switch acts as an accident detection sensor, and in the event of an accident, the system sends an emergency SMS with the bus's GPS location to the relevant authorities. Additionally, an LCD displays real-time data, actions, and fare updates, ensuring transparent communication between the driver and passengers. This integrated approach enhances the efficiency, safety, and user experience of public bus transit systems by combining IoT-based automation and real-time data communication.

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 Keywords

IoT-based transportation, Smart bus system, RFID ticketing, GSM communication, GPS tracking, ESP32 microcontroller, Blynk IoT platform, Automated fare calculation, Passenger safety system, Accident detection, Servo motor door control, Real-time monitoring, Public transportation automation, Emergency alert system, LCD display interface

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Social Media Marketing: An Emerging Tool for Business Growth Abstract Social media marketing has become one of the most powerful tools for businesses to engage with customers, build brand awareness, and drive sales. With the rapid growth of digital platforms such as Facebook, Instagram, LinkedIn, Twitter (X), and YouTube, organizations are increasingly shifting their focus toward online strategies. This paper analyses the importance, scope, and effectiveness of social media marketing, highlighting its role in shaping consumer behaviour and business performance. The findings indicate that social media not only enhances customer engagement but also provides measurable results, making it an essential element of modern marketing strategies.

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Social media platforms, Digital Marketing, Conent strategy,

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Abstract The Pur??as, often regarded as religious and mythological texts, also serve as vital sources for reconstructing the history and culture of ancient India. While primarily intended to convey religious teachings, cosmological ideas, and ethical principles, they preserve accounts of dynasties, rulers, and political traditions that illuminate the evolution of early state systems and collective memory. Genealogical lists and descriptions of succession, particularly in the Vi??u, Matsya, Bh?gavata, and V?yu Pur??as, provide historical insights despite inconsistencies and legendary embellishments. Beyond politics, these texts reveal the socio-cultural life of early India. They describe rituals, festivals, var?a and ??rama frameworks, and customary practices that governed society. Environmental attitudes appear in myths about rivers, mountains, and forests, reflecting deep links between nature and human life. Economic references--agriculture, irrigation, trade, and resource use--highlight the material basis of society. Methodological challenges remain, as myth and history often intertwine, and later interpolations complicate chronology. Yet, when critically examined alongside archaeology, epigraphy, and other traditions such as the R?m?ya?a, Mah?bh?rata, Buddhist J?takas, and Jain texts, the Pur??as emerge as hybrid records--part myth, part history. They function as cultural archives, preserving political memory, ethical ideals, and everyday realities, thereby enriching early Indian historiography.

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 Keywords

Pur??as, Ancient India, Historical Sources, Society, Culture, Historiography

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Bone fracture and bone tumor diagnosis are among the most important issues in orthopedic and oncological practice, especially in areas with low expertise in radiological diagnosis. This paper presents a deep learning based framework for the automated detection of fractures and tumors in radiographic and MRI images using the YOLOv11n object detection model. The system was trained on a combination of two curated sets of 1,500 tumor specimens including osteosarcoma and benign lesions and 3,000 fracture samples including transverse fractures, oblique fractures, and comminuted fractures. Grazing conversion, normalising, and worsening strategies were applied to improve dataset variety and robohardness. The model showed good performance with an accuracy of 92.8%, precision of 92.4%, recall of 90.1%, and mean average precision (mAP) at detection threshold of 0.5 for tumor detection (90.8% mAP), and 94.3% accuracy, 93.2% precision and 94.9% recall for fracture detection. To enable real-world applicability, the framework was deployed through a Streamlit-based web application offering role-specific access for patients and doctors, real-time image uploads, annotated visualizations, heatmap-based interpretability, and multi-format report exports (CSV, PDF, JSON). By offering strong detection accuracy while keeping the interface approach easy to use, the proposed system offers reliable assistance to minimize delay in diagnosis, error rates and enhance patient outcome in both orthopaedic and oncological treatment.

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 Keywords

Tumor Detection, Fracture Detection, YOLOv11n, Deep Learning, Medical Imaging, X-ray, MRI, Streamlit, PyTorch, Computer Vision, Object Detection, Healthcare AI, SQLite, Diagnostic Reports.

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Creative Commons Attribution 4.0 and The Open Definition

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Metal oxide nanoparticles (MONPs) are a class of nanomaterials known for their unique physical, chemical, and biological properties. Due to their high surface-to-volume ratio, stability, and functional versatility, MONPs have found wide spread applications in medicines, environmental remediation, food packaging, cosmetics, and catalysis. Commonly studied metal oxide include zinc oxide (ZnO), titanium dioxide (TiO2), iron oxide (Fe3O4), and copper oxide (CuO), each offering distinct functionalities. These nanoparticles can be synthesized through various methods such as sol-gel, co-precipitation, hydrothermal, and green synthesis, which influence their size, morphology, and reactivity. Characterization techniques like XRD, SEM, TEM, and FTIR are essential to understand their structural and functional properties. The promising biomedical and industrial applications of MONPs are balanced with ongoing research into their toxicity, environmental impact, and safe use. This review aims to provide an overview of the synthesis, characterization, and emerging applications of metal oxide nanoparticles, highlighting their role in advancing nanotechnology-based solutions.

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 Keywords

Metal oxide nanoparticles, Metal oxide synthesis, Characterization, Inorganic nanoparticle, Biomedical applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Soil is a critical factor for a successful agriculture. The Growth of Crops is affected by the chemical features of soil. Choosing the right type of crops for that particular type of soil is also important. Machine Learning techniques can be used to classify the soil series data. The results of such classification can further be combined with crop dataset to predict the crops that are suitable for the soil series of a particular region and its climatic conditions. Predicting a crop well in advance requires a systematic study of huge data coming from various variables like soil quality pH, N, P, K etc. As Prediction of crop deals with large set of database thus making this prediction system a perfect candidate for application of data science. The success of any crop prediction system heavily relies on how accurately the features have been extracted and how appropriately classifiers have been employed.

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Index Terms - Soil classification, Crop prediction, Machine learning, Data science, Soil quality analysis, Feature extraction, Soil-crop suitability, Precision agriculture, Crop recommendation system

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