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Tip-enhanced Raman spectroscopy reveals the structural rearrangements of tau protein aggregates at the growth phase

NANOSCALE 2024年第10期16卷 5294-5301页

作者： Sofinska, Kamila Seweryn, Sara Skirlinska-Nosek, Katarzyna Barbasz, Jakub Lipiec, Ewelina [a]Jagiellonian University Faculty of Physics Astronomy and Applied Computer Science M. Smoluchowski Institute of Physics Łojasiewicza 11 30-348 Krakow Poland [b]Jagiellonian University Doctoral School of Exact and Natural Sciences Krakow Poland [c]Jerzy Haber Institute of Catalysis and Surface Chemistry Polish Academy of Sciences Niezapominajek 8 30-239 Krakow Poland

Tau protein aggregates inside neurons in the course of Alzheimer's disease (AD). Because of the enormous number of people suffering from AD, this disease has become one of the world's major health and social problems. The presence of tau lesions clearly correlates with cognitive impairments in AD patients, thus, tau is the target of potential treatments for AD, next to amyloid-beta. The exact mechanism of tau aggregation has not been understood in detail so far;especially little is known about the structural rearrangements of tau aggregates at the growth phase. The research into tau conformation at each step of the aggregation pathway will contribute to the design of effective therapeutic approaches. To follow the secondary structure of individual tau aggregates at the growth phase, we applied tip-enhanced Raman spectroscopy (TERS). The nanospectroscopic approach enabled us to follow the structure of individual aggregates occurring in the subsequent phases of tau aggregation. We applied multivariate data analysis to extract the spectral differences for tau aggregates at different aggregation phases. Moreover, atomic force microscopy (AFM) allowed the tracking of the morphological alterations for species occurring with the progression of tau aggregation. Tip-enhanced Raman spectroscopy (TERS) enabled the structural differences between tau protein aggregates to be revealed, specifically tau protofibrils and young fibrils at the level of individual aggregates.

关键词： Aggregates

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Wigner molecules in phosphorene quantum dots

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Physical Review B 2022年第20期106卷 205304-205304页

作者： Tanmay Thakur Bartłomiej Szafran AGH University of Science and Technology Faculty of Physics and Applied Computer Science al. Mickiewicza 30 30-059 Kraków Poland

We study Wigner crystallization of electron systems in phosphorene quantum dots with the confinement of an electrostatic origin with both circular and elongated geometry. The large effective masses in phosphorene promote the separation of the electron charges already for quantum dots of relatively small size. The anisotropy of the effective mass allows for the formation of Wigner molecules in the laboratory frame with a confined charge density that has lower symmetry than the confinement potential. We find that in circular quantum dots separate single-electron islands are formed for two and four confined electrons but not for three trapped carriers. The spectral signatures of the Wigner crystallization to be resolved by transport spectroscopy are discussed. Systems with Wigner molecule states are characterized by a nearly degenerate ground state at B=0 and are easily spin-polarized by the external magnetic field. In electron systems for which the single-electron islands are not formed, a more even distribution of excited states at B=0 is observed, and the confined system undergoes ground-state symmetry transitions at magnetic fields of the order of 1 T. The system of five electrons in a circular quantum dot is indicated as a special case with two charge configurations that appear in the ground state as the magnetic field is changed: one with the single electron islands formed in the laboratory frame and the other where only the pair-correlation function in the inner coordinates of the system has a molecular form as for three electrons. The formation of Wigner molecules of quasi-1D form is easier for the orientation of elongated quantum dots along the zigzag direction with heavier electron mass. The smaller electron effective mass along the armchair direction allows for freezing out the transverse degree of freedom in the electron motion. Calculations are performed with a version of the configuration interaction approach that uses a single-electron basis that is preo

关键词： Coulomb blockade Localization 1-dimensional systems Quantum dots Wigner crystal Exact diagonalization Transport techniques Variational wave functional methods

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Entanglement Detection with Trace Polynomials

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Physical Review Letters 2024年第7期132卷 070202-070202页

作者： Albert Rico Felix Huber Faculty of Physics Astronomy and Applied Computer Science Institute of Theoretical Physics Jagiellonian University 30-348 Kraków Poland

We provide a systematic method for nonlinear entanglement detection based on trace polynomial inequalities. In particular, this allows us to employ multipartite witnesses for the detection of bipartite states, and vice versa. We identify pairs of entangled states and witnesses for which linear detection fails, but for which nonlinear detection succeeds. With the trace polynomial formulation a great variety of witnesses arise from immanant inequalities, which can be implemented in the laboratory through the randomized measurements toolbox.

关键词： Quantum correlations, foundations & formalism

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Machine Learning Approaches in Cybersecurity to Enhance Security in Future Network Technologies

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SN computer science 2025年第4期6卷 1-18页

作者： Ahmad, Sultan Haque, Md. Alimul Abdeljaber, Hikmat A. M. Eljialy, A.E.M. Nazeer, Jabeen Mishra, B.K. Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj 11942 Saudi Arabia University Center for Research and Development (UCRD) Department of Computer Science and Engineering Chandigarh University Mohali Punjab Gharuan 140413 India Department of Computer Science Veer Kunwar Singh University Bihar Ara India Department of Computer Science Faculty of Information Technology Applied Science Private University Amman Jordan MEU Research Unit Middle East University Amman 11831 Jordan Department of Information Systems College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj 11942 Saudi Arabia Department of Physics Veer Kunwar Singh University Ara 802301 India

As technology continues to evolve rapidly, cybersecurity has become a critical global concern. The increasing sophistication of cyber threats poses significant risks to individuals, businesses, and governments. To combat these threats, cybersecurity tools play a crucial role in monitoring, detecting, and mitigating security risks in digital environments. These tools ensure data protection, prevent unauthorized access, and safeguard sensitive information. However, traditional cybersecurity approaches are struggling to keep pace with emerging cyber-attacks. In response, machine learning (ML) has emerged as a powerful solution for enhancing cybersecurity strategies. ML algorithms enable organizations to analyze large datasets, identify anomalies, and predict potential threats with greater accuracy. Cybersecurity tools, integrated with ML, act as the final line of defense against attacks such as data breaches, identity theft, and system intrusions. This research explores the application of ML in selecting and optimizing cybersecurity models for enterprise ICT systems. It also emphasizes the growing demand for skilled professionals who can develop and implement ML-based security solutions. By examining current trends and future possibilities, this study provides valuable insights into the role of ML in strengthening cybersecurity measures and enhancing overall digital protection for organizations worldwide. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cyber security Cybercrime Data analysis ML algorithms Network security Threats

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Interpretable Multi-task Learning with Shared Variable Embeddings

arXiv

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arXiv 2024年

作者： Zelaszczyk, Maciej Mańdziuk, Jacek Faculty of Mathematics and Information Science Warsaw University of Technology Poland Faculty of Computer Science AGH University of Krakow Poland

This paper proposes a general interpretable predictive system with shared information. The system is able to perform predictions in a multi-task setting where distinct tasks are not bound to have the same input/output structure. Embeddings of input and output variables in a common space are obtained, where the input embeddings are produced through attending to a set of shared embeddings, reused across tasks. All the embeddings are treated as model parameters and learned. The approach is distinct from existing vector quantization methods. Specific restrictions on the space of shared embedings and the sparsity of the attention mechanism are considered. Experiments show that the introduction of shared embeddings does not deteriorate the results obtained from a vanilla variable embeddings method. We run a number of further ablations. Inducing sparsity in the attention mechanism leads to both an increase in accuracy and a significant decrease in the number of training steps required. Shared embeddings provide a measure of interpretability in terms of both a qualitative assessment and the ability to map specific shared embeddings to pre-defined concepts that are not tailored to the considered model. There seems to be a trade-off between accuracy and interpretability. The basic shared embeddings method favors interpretability, whereas the sparse attention method promotes accuracy. The results lead to the conclusion that variable embedding methods may be extended with shared information to provide increased interpretability and accuracy. © 2024, CC BY.

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Thermalization at the femtoscale seen in high-energy Pb+Pb collisions

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Physical Review C 2024年第5期109卷 L051902-L051902页

作者： Rupam Samanta Somadutta Bhatta Jiangyong Jia Matthew Luzum Jean-Yves Ollitrault AGH University of Science and Technology Faculty of Physics and Applied Computer Science Aleja Mickiewicza 30 30-059 Cracow Poland Université Paris Saclay CNRS CEA Institut de Physique Théorique 91191 Gif-sur-Yvette France Department of Chemistry Stony Brook University Stony Brook New York 11794 USA Physics Department Brookhaven National Laboratory Upton New York 11976 USA Instituto de Física Universidade de São Paulo Rua do Matão 1371 Butantã 05508-090 São Paulo Brazil

A collision between two atomic nuclei accelerated at a speed close to that of light creates a dense system of quarks and gluons. Interactions among them are so strong that they behave collectively like a droplet of fluid of ten-femtometer size, which expands into the vacuum and eventually fragments into thousands of particles. We report a new manifestation of thermalization in recent data from the Large Hadron Collider. Our analysis is based on results from the ATLAS Collaboration, which has measured the variance of the momentum per particle across Pb+Pb collision events with the same particle multiplicity. This variance decreases steeply over a narrow multiplicity range corresponding to central collisions. We provide a simple explanation of this newly observed phenomenon: For a given multiplicity, the momentum per particle increases with increasing impact parameter. Since a larger impact parameter goes along with a smaller collision volume, this in turn implies that the momentum per particle increases as a function of density, which is a generic consequence of thermalization. Our analysis provides the first direct evidence of this phenomenon at the femtoscale.

关键词： Charged-particle multiplicity Collective flow Particle correlations & fluctuations Quark-gluon plasma

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7th International Conference of computer and Informatics Engineering, IC2IE 2024

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798331505530

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. technology also plays an essential role in supporting runners and running races. technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential. © 2024 IEEE.

关键词： artificial intelligence aspects marathon performance

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Heider balance on Archimedean lattices and cliques

arXiv

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arXiv 2024年

作者： Malarz, Krzysztof Woloszyn, Maciej Kulakowski, Krzysztof AGH University Faculty of Physics and Applied Computer Science al. Mickiewicza 30 Kraków30-059 Poland

We investigate the work function U(T) for the Heider balance, driven by a thermal noise T, on several planar networks that contain separated triangles, pairs of triangles, chains of triangles and complex structures of triangles. In simulations, the heat-bath algorithm is applied. Two schemes of link values updating are considered: synchronous and asynchronous (sequential). The latter results are compared with analytical calculations for small cliques. We argue that the actual shape of U(T) is a consequence of a local topology rather than of a macroscopic ordering. Finally, we present the mathematical proof that for any planar lattice, perfect structural (Heider) balance is unreachable at T > 0. © 2024, CC BY.

关键词： Crystal lattices

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Anisotropic, multiband, and strong-coupling superconductivity of the Pb0.64Bi0.36 alloy

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Physical Review B 2024年第21期110卷 214510-214510页

作者： Sylwia Gutowska Karolina Górnicka Paweł Wójcik Tomasz Klimczuk Bartlomiej Wiendlocha University of Vienna Faculty of Physics and Center for Computational Materials Science Kolingasse 14-16 A-1090 Vienna Austria AGH University of Krakow Faculty of Physics and Applied Computer Science Aleja Mickiewicza 30 30-059 Krakow Poland Materials Science and Technology Division Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Faculty of Applied Physics and Mathematics and Advanced Materials Centre Gdansk University of Technology ul. Narutowicza 11/12 80-233 Gdańsk Poland

This paper presents theoretical and experimental studies on the superconductivity of Pb0.64Bi0.36 alloy, which is a prototype of strongly coupled superconductors and exhibits one of the strongest coupling under ambient pressure among the materials studied so far. The critical temperature, the specific heat in the superconducting state, and the magnetic critical fields are experimentally determined. Deviations from the single-gap s-wave BCS-like behavior are observed. The electronic structure, phonons, and electron-phonon interactions are analyzed in relation to the metallic Pb, explaining why the Pb-Bi alloy exhibits such a large value of the electron-phonon coupling parameter λ≃2. Superconductivity is studied using the isotropic Eliashberg formalism as well as the anisotropic density functional theory for superconductors. We find that while Pb is a two-gap superconductor with well-defined separate superconducting gaps, in the Pb-Bi alloy an overlapped three-gap-like structure is formed with a strong anisotropy. Furthermore, the chemical disorder, inherent to this alloy, leads to strong electron scattering, which is found to reduce the critical temperature.

关键词： Anisotropy

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AI-Infused Predictive Digital Twin Systems for Resilient IoT Software Architectures 4

AI-Infused Predictive Digital Twin Systems for Resilient IoT...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Gupta, Raj Kumar Dhasmana, Gulshan Benvin, Shalet Bhargav, H.K. Jadhav, Girish Rao, Tarini Department of Physics Bhabua India Graphic Era Deemed to be University Department of Computer Science & Engineering Dehradun India Bgs Institute of Technology Adichunchanagiri University Department of Computer Science and Engineering Mandya India Shridevi Institute of Engineering and Technology Department of Computer Science and Engineering Tumakuru India Parul institute of Engineering and Technology Parul University Faculty of Engineering and Technology Department of Electrical Engineering Post Limda India Faculty of Law Pune India

ISBN: (纸本)9798350352931

The proliferation of Internet of Things (IoT) networks has significantly increased the complexity of software architectures, leading to heightened vulnerabilities and system inefficiencies. AI-infused Predictive Digital Twin Systems provide a promising approach by integrating real-time data analytics with predictive AI models to monitor, forecast, and enhance the health and security of IoT software architectures. This paper introduces an AI-Infused Predictive Digital Twin System designed to create resilient IoT software architectures. Experimental validation was conducted using a large-scale IoT network with 1,000 interconnected devices. The AI-Infused Predictive Digital Twin System achieved a 97.8% accuracy in anomaly detection, with a 28% reduction in system disruptions compared to conventional monitoring solutions. The RL-based optimization module resulted in a 20% improvement in resource utilization efficiency and a 30% increase in overall system resilience under varying load conditions. The integration of the blockchain audit layer significantly improved traceability and reduced security breach recovery time by 40%. The AI-Infused Predictive Digital Twin System provides an innovative solution for developing resilient IoT software architectures. By integrating predictive AI models and real-time digital twin technology, the framework enables continuous monitoring, proactive anomaly detection, and dynamic optimization. The experimental results demonstrate the system's capability to enhance resilience, efficiency, and security in complex IoT environments, making it a valuable tool for managing and securing next-generation IoT architectures. Future work will explore expanding the system's capabilities to support multi-cloud IoT networks and developing more sophisticated AI models for enhanced predictive accuracy and operational efficiency. © 2024 IEEE.

关键词： Blockchain

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