Physical Sciences and Engineering

Weather Forecasting or Predictions plays an important role in human life as it impacts agriculture, transportation and natural disasters. Therefore, the development of new techniques in machine learning is continuing to enable better and accurate predictions of weather using historical data such as temperature, dew point temperature, relative humidity, visibility, pressure, and wind speed over the years. The primary goal of my system is to develop a model that will be precise and accurate for short-term predictions.

In this paper, synthesis and photoluminescence (PL) properties of rare earth Tb3+dopedSr2P2O7 Phosphors were prepared by conventional solid state reaction method and photoluminescence (PL) properties of samples were examined for proper excitation. All the samples were synthesized by high-temperature SSR- method. The X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy characterization confirms the formation of pure α-phase with crystallized in orthorhombic structure of samples.

This research investigates the integration of AI-powered UI adaptation and data automation into secure front-end systems focusing on improving the user experience and scalability, real-time accessibility, and ethics. The quantitative research design targeted users, developers, and designers who are typically involved in AI-driven front-end systems across various industries. Data was collected through an online questionnaire developed by the researchers themselves and analyzed using descriptive and inferential statistics that included independent t-test, ANOVA, and Pearson correlation.

Lactic acid is a commodity product with wide industrial application, which can be generated from different raw materials, making it a target of interest for large companies. On the other hand, most organic acids on the market produced via chemical synthesis generates high levels of pollution. That way, the second-generation organic acids is part of this context, moving towards emerging and future-oriented technologies.

In vertebrates like fish, mesencephalon or mid brain consists of two regions optic tectum (OT), that act as centre for processing visual impulses and generating motor response and tegmentum containing nerve tracts. Both structural and physiological properties of OT helps to know the mechanism of organizing behaviour. Present paper analyses the midbrain (mesencephalon) of two different fishes, Carassius auratus and Botia striata with respect to its feeding behaviour. Both these aquarium fishes belongs to cypriniformes order, but exhibit different feeding behaviours.

Groper’s space maintainer is a fixed, functional space maintainer used in pediatric dentistry to preservearch length following prematureloss of primary anteriorteeth. Designed specifically for the esthetic and functional needs of young children, it consists of a band or crown on a posterior tooth connected to a wire framework that supports artificial anterior teeth. Unlike traditional space maintainers, Groper’s appliance restores not only the space but also provides esthetic replacement of missing incisors, improving speech, mastication, and self-esteem.

Background: The integration of Artificial Intelligence (AI) in endodontics has gained substantial attention in recent years, offering innovative solutions for diagnosis, treatment planning, and clinical decision-making. Given the increasing complexity of endodontic procedures and the limitations of human analysis in imaging, AI systems present a promising alternative to support dental professionals.

This scientific article aims to present the process of urban evolution of Teresina - Piauí, Brazil from 1800 to 1950 and discuss the influences of 18th century Portuguese urban planning on the city's urban design. The study showed how the creation of new cities during the colonial period in Brazil influenced urban planning in Teresina, the first planned capital of the imperial period. Although influenced by Portuguese norms, urban planning in colonial Brazil was adapted to local conditions and city formation needs.

Data stream mining in non-stationary environments presents the twin challenges of automated model selection and concept drift adaptation. This paper proposes a framework for Adaptive AutoML Pipelines capable of continuous learning from large-scale streaming data under evolving distributions. We integrate Automated Machine Learning (AutoML) with online learning to dynamically optimize full model pipelines – including preprocessing, feature selection, and classification – as new data arrive and concepts change.

The integration of Artificial Intelligence (AI) into supply chain management has revolutionized business operations, offering enhanced efficiency, accuracy, and adaptability. This research paper provides a comprehensive analysis of the impact of AI on supply chains, exploring both the opportunities and challenges it presents.