International Young Scientist Awards

1. Introduction to NFV and the Role of AI. Network Function Virtualization (NFV) revolutionizes traditional networking by replacing dedicated hardware appliances with software-based network functions running on standard servers. This shift offers greater flexibility, scalability, and cost-efficiency. However, managing virtualized network functions (VNFs) in dynamic and large-scale environments brings complexity in orchestration, resource allocation, and performance optimization. Here, Artificial Intelligence (AI) plays a transformative role. By leveraging AI's capabilities in pattern recognition, decision-making, and automation, NFV environments can become more adaptive, self-healing, and predictive. AI facilitates real-time network monitoring and intelligent automation, enabling networks to respond to fluctuations in traffic and demand. As NFV gains momentum across telecom and enterprise sectors, AI emerges as a critical enabler that not only simplifies operations but also enhan...

In a surprising twist, scientists have observed that Earth is spinning slightly faster this summer, with July 22 expected to be one of the shortest days ever recorded. This acceleration in Earth's rotation could lead to significant implications for timekeeping systems, digital communications, and GPS technology that depend on ultra-precise timing. Typically, a day on Earth lasts exactly 86,400 seconds (24 hours), but Earth's rotation is not perfectly consistent. Various factors, such as seismic activity, melting glaciers, and mass redistribution due to climate change, can subtly influence the planet's spin. According to recent astronomical calculations and atomic clock data, Earth has been rotating faster than usual, trimming off up to 1.3 milliseconds on certain days. Scientists speculate that one contributing factor could be the ongoing redistribution of water masses, especially from melting polar ice caps. This movement slightly alters Earth's moment of inertia, ...

Machine learning (ML) is revolutionizing the field of robotics by equipping machines with the ability to learn from experience, adapt to dynamic environments, and make intelligent decisions without explicit programming. Traditional robotic systems rely heavily on predefined rules and static programming, which limit their adaptability and intelligence. In contrast, machine learning techniques allow robots to evolve beyond rigid instructions and operate autonomously in complex, unstructured environments.   One of the key advantages of incorporating machine learning into robotics is enhanced autonomy. Robots embedded with ML algorithms can perceive their surroundings through sensors and cameras, process this data in real time, and make decisions based on past experiences. For example, in autonomous navigation, reinforcement learning enables robots to explore unknown terrains, avoid obstacles, and optimize paths by learning from trial and error. This adaptability is crucial for applica...

 As climate change accelerates and urbanization surges, nations around the world are increasingly recognizing the urgency of sustainable construction. In response, a growing number of countries are adopting and upgrading green building codes to minimize environmental impact, improve energy efficiency, and ensure healthier living spaces. These codes set standards for energy use, water conservation, indoor air quality, building materials, waste reduction, and overall environmental performance. Green building codes are no longer optional or limited to a few progressive cities—they are becoming mainstream policy in both developed and developing nations. Countries such as the United States, Germany, Singapore, India, and the United Arab Emirates have introduced comprehensive frameworks that require new construction and major renovations to meet eco-friendly benchmarks. In the European Union, the Energy Performance of Buildings Directive mandates that all new buildings must be nearly ze...

Smart nanomaterials have emerged as transformative tools in the fields of biosensing and diagnostics, offering unprecedented sensitivity, selectivity, and real-time analysis capabilities. These materials, which include nanoparticles, nanowires, quantum dots, carbon-based nanostructures (like graphene and carbon nanotubes), and stimuli-responsive polymers, are designed to respond dynamically to biological or chemical stimuli, enabling precise detection of target analytes at ultra-low concentrations.   In biosensing applications, smart nanomaterials act as critical components that improve the transduction mechanism—converting biological interactions into measurable signals. Their large surface-to-volume ratio allows enhanced interaction with biomolecules such as DNA, proteins, and enzymes, facilitating faster and more accurate detection. Gold nanoparticles and magnetic nanoparticles, for example, are commonly functionalized with antibodies or aptamers to create highly specific bios...

Chemically-Induced Dynamic Nuclear Polarization (CIDNP) is a sophisticated magnetic resonance technique that enhances nuclear spin polarization, leading to significantly improved nuclear magnetic resonance (NMR) signal sensitivity. This effect originates from the spin dynamics of radical pairs generated during chemical reactions. When applied to the field of artificial photosynthesis, CIDNP offers a powerful window into understanding the fundamental processes that govern light-driven energy conversion and electron transfer mechanisms.   Artificial photosynthesis seeks to emulate natural photosynthetic systems by capturing solar energy and converting it into chemical fuels, such as hydrogen or hydrocarbons, using water and carbon dioxide as feedstocks. A major challenge in this field lies in deciphering the short-lived radical intermediates and transient electron transfer events that dictate the overall efficiency of photochemical reactions. CIDNP addresses this challenge by selec...

In a groundbreaking development, scientists have invented a shape-shifting "electronic ink" that could revolutionize the future of flexible gadgets and wearable technology. This novel material, developed by researchers at the Chinese Academy of Sciences, is composed of liquid metal gallium and magnetic particles, allowing it to dynamically switch between soft and rigid states depending on temperature.   The ink remains soft and stretchable at room temperature , but when exposed to heat—particularly above 70°C—it becomes over 1,400 times softer, enabling it to flow like a fluid. Once the temperature drops, the ink returns to a rigid form, retaining its printed shape and electrical functionality. This reversible transition is made possible through the incorporation of gallium oxide, which reacts to temperature fluctuations without affecting the conductive properties of the ink. Such a material opens new avenues for next-generation flexible electronics, including foldable dis...

The dream of colonizing Mars has captivated scientists, engineers, and visionaries for decades. With advancements in space technology and renewed interest from both governmental agencies like NASA and private companies such as SpaceX, the prospect of human habitation on the Red Planet is becoming increasingly plausible. However, turning this dream into reality involves addressing a complex array of challenges while also harnessing exciting opportunities. One of the foremost challenges is the harsh Martian environment . With an average temperature of -63°C, a thin carbon dioxide-rich atmosphere, and intense radiation from the sun due to the lack of a protective magnetic field, Mars is far from hospitable. Establishing sustainable habitats will require advanced technologies in life support systems, radiation shielding, and thermal regulation. Additionally, transportation to and from Mars is expensive and time-consuming, demanding innovations in propulsion systems and fuel efficiency. ...

In a groundbreaking advancement at the intersection of quantum computing and artificial intelligence , researchers have introduced a novel hybrid quantum deep learning model—BLS-QLSTM (Broad Learning System–Quantum Long Short-Term Memory)—designed to forecast stock market indices with high precision. This hybrid model harnesses the pattern recognition strength of deep learning and the superior computational parallelism of quantum algorithms to analyze complex, non-linear financial time series data.   Traditional machine learning models often struggle with market volatility, high-dimensional data, and chaotic fluctuations. However, BLS-QLSTM integrates quantum-inspired gates into the LSTM architecture to capture long-term dependencies while reducing computational overhead. The inclusion of Broad Learning allows for fast feature mapping and layered adaptability, making the model both efficient and robust against overfitting. Empirical evaluations using real-world stock datasets—su...

In 2025, blockchain technology has firmly stepped beyond its cryptocurrency roots to revolutionize real-world industries across the globe. While Bitcoin and Ethereum introduced blockchain to the masses, today’s applications span sectors such as healthcare, supply chain, finance, real estate, and public administration—delivering enhanced transparency, security, and decentralization.   One of the most significant shifts has been in supply chain management . Enterprises now use blockchain to track goods from origin to delivery, ensuring authenticity and reducing fraud. Brands across agriculture, pharmaceuticals, and luxury goods leverage blockchain to offer tamper-proof records and improve consumer trust. In healthcare , blockchain secures patient records, enabling seamless sharing across hospitals while maintaining privacy. This not only reduces data breaches but also improves diagnostics and patient outcomes. During pandemics or large-scale public health efforts, blockchain aids in...

After completing essential maintenance and logistics tasks, astronauts aboard the International Space Station (ISS) have resumed their scientific research activities, marking a crucial phase in the advancement of space science and technology. The return to research underscores the ISS's vital role as a microgravity laboratory where a wide range of experiments are conducted—many of which cannot be performed on Earth. This transition allows crew members to focus on experiments in fields such as biotechnology , materials science, Earth observation, and human physiology. The microgravity environment provides a unique platform for investigating biological systems and physical processes, paving the way for innovations in medical research, pharmaceutical development, and sustainable technologies. Among the prominent experiments resumed are those related to plant growth in space, which are key to future long-duration space missions and deep space exploration. These studies help scientists...

Urban Heat Islands (UHIs)—urban areas that experience significantly higher temperatures than their rural surroundings—pose a serious environmental and public health challenge, especially in the context of global climate change. In response, cities across the world are increasingly turning to spatial data analysis to understand and mitigate the UHI effect more effectively.     Spatial data analysis uses geospatial technologies such as GIS (Geographic Information Systems), remote sensing, and satellite imagery to analyze the spatial distribution of heat intensity, land use patterns, vegetation cover, and population density. This data-driven approach enables researchers, urban planners, and policymakers to make informed decisions and design targeted interventions that reduce surface and ambient temperatures in heat-vulnerable areas. Recent studies have demonstrated that spatial analysis can accurately identify UHI hotspots at the neighborhood level. For instance, thermal satell...