Abstract

This study focuses on parameter optimization and detection signal comparison of planar coil
particle detection sensors, and conducts in-depth analysis of different core materials. Through finite
element simulation analysis and experimental verification, the influence of coil turns, diameter,
thickness and other parameters on magnetic field distribution and particle detection signals was
systematically explored, and the sensor chip structure design was optimized. The study found that a
planar coil with 60 turns and an inner diameter of 1.2 mm performed best. At the same time, the
enhancement effect of different magnetic core materials (including iron core, silicon steel sheet and
permalloy) on the magnetic field and detection signal was investigated. It was found that the
permalloy magnetic core can significantly improve the sensor performance. Copper particles have
effective detection capabilities. This research provides theoretical and experimental basis for
optimizing the detection sensor of metal particle contaminants in oil, and has important academic
value and application prospects.

Abstract

Improving energy management is essential for sustainability since building energy use is rising.
This study is a trailblazer in using multi-criteria decision-making (MCDM) methodologies for the
real-time operational optimization of building energy systems. Data collection and pre-processing,
feature extraction, feature selection, classification, trust authentication, encryption, and decryption
are among the techniques used in this approach. Pre-processing procedures for the raw data include
feature encoding, dimension reduction, and normalization approaches. The Hybrid Grey Level Cooccurrence Matrix Fast Fourier Transform (HGLCM-FFT) method is used for feature extraction.
Filter-based methods are used for feature selection, including IG, CS, symmetric uncertainty, and
gain ratio. The Hierarchical Gradient Boosted Isolation Forest (HGB-IF) technique is used for the
classification. Distributed Adaptive Trust-Based Authentication (DAT-BA), a security architecture
in distributed cloud environments, uses trust authentication. The Particle Swarm Optimized
Symmetrical Blowfish (PSOSB) method is used for encryption and decryption. The suggested work
is implemented using OS Python – 3.9.6; the performance of the proposed model is Attack
Detection Rate, False alarm rate, True positive rate, Network usage, CPU usage, Encryption time,
encryption time and Throughput.

Abstract

Life expectancy has increased significantly due to declining mortality rates, especially a mong adults and older individuals. However, this rapid aging of the population has also led to a rise in age-related diseases, putting more people at risk of chronic illness and disability. Maintaining health, resilience, and independence throughout life has thus become a key research priority, vital both for individual well-being and the sustainability of healthcare systems. Studies on longevity populations provide insights into factors that may beneficially alter the epigenome over a lifetime, promoting health and longevity. Longevity is seen as a major achievement of modern society, reflecting not only an extended lifespan but also a prolonged period of health. Certain regions, known as Longevity Blue Zones (LBZs)—such as Okinawa (Japan), the Nicoya Peninsula (Costa Rica), Loma Linda (California), Ikaria (Greece), and Ogliastra (Sardinia)—are celebrated for their high percentage of long-lived residents who often avoid age-related disabilities. Longevity is not universally distributed, so identifying LBZ-like areas worldwide is crucial to understanding additional factors that may contribute to a long, healthy life. This narrative review aims to explore the commonalities between the Cilento region in Italy and recognized LBZs, examining environmental, dietary, and lifestyle factors.We conducted a search for articles published from 2004 to the present, limited to English, German, and Italian studies in PubMed/Medline, Scopus, and Google Scholar. Through collaborative consensus, 18 final references were selected. A descriptive comparative approach was used to evaluate the similarities between Cilento and LBZs.Cilento and LBZs share several characteristics, including hilly terrain, moderate altitudes (between 355 and 600 meters), and mild climates (average temperatures of 17.4 to 23.5°C). Both regions exhibit traditional professions such as farming and animal husbandry, a largely Mediterranean or plant-based diet rich in legumes, vegetables, and olive oil, and strong social cohesion with deep family, religious, and community ties. These traits promote resilience, optimism, and mental well-being, which are essential for healthy aging.Given its similarities, Cilento may represent an as-yet-unrecognized LBZ. Insights from this region could be applied more broadly to help prevent chronic diseases and slow aging. Studying Cilento’s centenarians may also offer new parameters for understanding why certain regions enjoy extended life expectancy.

Abstract

Altered states of consciousness (ASC) encompass phenomena such as near-death experiences (NDEs). Numerous individuals who have undergone near-death experiences have recounted experiencing intense mental lucidity, extraordinary sensory images, and a distinct recollection of the event that surpasses the realism of their ordinary existence. The Quantum Hologram Theory of Physics and Consciousness (QHTC) elucidates the fundamental characteristics of the quantum properties of the human mind including the non-local principle that suggests that the mind transcends the boundaries of space and time. The QHTC proposes that during an ASC, the cognitive process of the human accelerates due to its non-locality property. Natural language processing (NLP) is an artificial intelligence technique that refers to a collection of computer methods used to analyze and represent texts that occur naturally. Ontology is a firmly established theoretical field in the philosophy of language that focuses on conceptual frameworks for understanding reality. This study employs NLP to extract linguistic sequences from NDEs narratives stored in a database including 4267 records. It then utilizes ontology research approaches to establish a mapping between the QHTC ontology and human language. The research aims to verify some ontological components of the QHTC, including the non-locality principle of the quantum model of the mind that explains that during ASC, cognitive processes accelerate and there is an enhanced level of perceptual lucidity. The research has the objective to understand the quantum nature of the mind that can help researchers to develop quantum artificial intelligence models that can profit from the quantum non-locality of the mind that would improve tremendously the power of artificial intelligence.