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Articles 151 - 180 of 293382
Full-Text Articles in Entire DC Network
Mgrre_Thinsections_Mgrre_11_18, Mgrre
Mgrre_Thinsections_Mgrre_11_17, Mgrre
Mgrre_Thinsections_Mgrre_11_16, Mgrre
Peakon Solutions And Analytical Properties For The Camassa–Holm-Type Equations With Quadratic Nonlinearities, Yonghong Chen, Zhijun Qiao, Mingxuan Zhu
Peakon Solutions And Analytical Properties For The Camassa–Holm-Type Equations With Quadratic Nonlinearities, Yonghong Chen, Zhijun Qiao, Mingxuan Zhu
School of Mathematical & Statistical Sciences Faculty Publications
In this paper, we derive the multi-peakon dynamical system of a class of Camassa-Holm-type equations with quadratic nonlinearities. We also consider the analytical properties for the Cauchy problem. Firstly, we establish local well-posedness of solutions in Besov spaces and then provide the blow-up criteria. Subsequently, we impose appropriate sufficient conditions on the initial data to guarantee that the corresponding solution either exists globally or blows up in a finite time. Finally, we prove the ill-posedness in the Besov space B2,∞3/2 by utilizing the non-traveling wave solutions.
Mgrre_Thinsections_Mgrre_11_15, Mgrre
Mgrre_Thinsections_Mgrre_11_14, Mgrre
Mgrre_Thinsections_Mgrre_11_13, Mgrre
Mgrre_Thinsections_Mgrre_11_12, Mgrre
Mgrre_Thinsections_Mgrre_11_11, Mgrre
Mgrre_Thinsections_Mgrre_11_10, Mgrre
Mgrre_Thinsections_Mgrre_11_9, Mgrre
Mgrre_Thinsections_Mgrre_11_8, Mgrre
Mgrre_Thinsections_Mgrre_11_7, Mgrre
Mgrre_Thinsections_Mgrre_11_6, Mgrre
Mgrre_Thinsections_Mgrre_11_5, Mgrre
Mgrre_Thinsections_Mgrre_11_4, Mgrre
Mgrre_Thinsections_Mgrre_11_3, Mgrre
A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima
A Review Of Gallium And Germanium Recovery From Industrial Solid Residues, Ernest V. Oteng, Marthias Silwamba, Lana Alagha, Alex Luyima
Mining Engineering Faculty Research & Creative Works
The global demand for critical elements such as gallium (Ga) and germanium (Ge), and the shift toward circular mining has accelerated the development of new extraction and recovery processing these metals from industrial solid residues. This transition is driven by a substantial surge in demand for advanced technologies and the depletion of primary ore. Consequently, industrial solid residues, particularly zinc processing residues, smelter slags, flue dusts, and coal fly ash, are emerging as viable alternative sources. These residues incorporate Ga and Ge through isomorphic substitution in phases such as ferrites, silicates, and glassy aluminosilicates, and are enriched by industrial processes, …
Mgrre_Thinsections_Mgrre_11_2, Mgrre
Tiny Large Language Models For Iot Networks: Potentials And Challenges, Muhammed Golec, Suhib Bani Melhem, Yaser Khamayseh, Abdulmalik Alwarafy, Naofal Al-Dhahir
Tiny Large Language Models For Iot Networks: Potentials And Challenges, Muhammed Golec, Suhib Bani Melhem, Yaser Khamayseh, Abdulmalik Alwarafy, Naofal Al-Dhahir
All Works
Large Language Models (LLM), which have gained great momentum in recent years, have revolutionized the field of Artificial Intelligence (AI); while their applicability for hardware-constrained Internet of Things (IoT) environments has begun to be questioned. This has led to the emergence of compact architecture and resource-efficient Tiny LLM models. This survey paper systematically examines Tiny LLMs for IoT networks and classifies existing approaches in five basic dimensions: model architectures, optimization strategies, transfer learning methods, deployment paradigms, and explainability-security integration. By applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, 139 related studies published between 2020 and 2025 …
Defense-To-Attack: Bypassing Weak Defenses Enables Stronger Jailbreaks In Vision-Language Models, Yunhan Zhao, Xiang Zheng, Yige Li, Xingjun Ma
Defense-To-Attack: Bypassing Weak Defenses Enables Stronger Jailbreaks In Vision-Language Models, Yunhan Zhao, Xiang Zheng, Yige Li, Xingjun Ma
Research Collection School Of Computing and Information Systems
Despite their superb capabilities, Vision-Language Models (VLMs) have been shown to be vulnerable to jailbreak attacks. While recent jailbreaks have achieved notable progress, their effectiveness and efficiency can still be improved. In this work, we reveal an interesting phenomenon: incorporating weak defense cues into the attack pipeline can significantly enhance both the effectiveness and efficiency of jailbreaks on VLMs. Building on this insight, we propose Defense2Attack, a novel jailbreak method that bypasses the safety guardrails of VLMs by leveraging defensive patterns to guide jailbreak prompt construction. Specifically, Defense2Attack consists of three key components: (1) a visual optimizer that embeds universal …
Analyzing Developer Discussions On Eu And Us Privacy Legislation Compliance In Github Repositories, Georgia M. Kapitsaki, Maria Papoutsoglou, Christoph Treude, Ioanna Theophilou
Analyzing Developer Discussions On Eu And Us Privacy Legislation Compliance In Github Repositories, Georgia M. Kapitsaki, Maria Papoutsoglou, Christoph Treude, Ioanna Theophilou
Research Collection School Of Computing and Information Systems
Context: Privacy legislation has impacted the way software systems are developed, prompting practitioners to update their implementations. Specifically, the EU General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have forced the community to focus on users’ data privacy. Objectives: Relying on the vast amount of data on developer issues available in GitHub repositories, our aim is to gather empirical evidence on the issues developers of Open Source Software discuss to comply with privacy legislation. Method: We examined such discussions by mining and analyzing 32,820 issues from GitHub repositories. We partially analyzed the dataset automatically to identify …
Effects Of Demineralization Protocols On Hydrogen And Oxygen Isotope Ratios In Fossil Bone Collagen, Linda M. Reynard
Effects Of Demineralization Protocols On Hydrogen And Oxygen Isotope Ratios In Fossil Bone Collagen, Linda M. Reynard
Boise State University Publications and Presentations
The effect of three commonly used preparation protocols on bone collagen δ2H and δ18O values was investigated, using six generally well-preserved faunal bones (cattle, bison, horse) ranging in age from the Holocene to Late Pleistocene. The treatments tested were ethylene diamine tetraacetic acid demineralization without gelatinization and hydrochloric acid demineralization with and without gelatinization. There are significant shifts in δ18O values among preparation methods. No systematic shifts in bone collagen δ2H values were noted among the three treatments, and most offsets were low (< 2–3 ‰) and smaller than typical measurement uncertainties. A few sample/treatment combinations yielded slightly higher inter-treatment δ2H differences (∼ 5–7 ‰). Lower mass fraction of hydrogen in …
Glomalin-Related Soil Protein In Colluvial Soils As A Proxy For Reconstructing Millenary Changes In Landscape And Soil Health, Axel Werner, Lourdes López-Merino, Joeri Kaal, Cruz Ferro-Vázquez, Oscar Serrano
Glomalin-Related Soil Protein In Colluvial Soils As A Proxy For Reconstructing Millenary Changes In Landscape And Soil Health, Axel Werner, Lourdes López-Merino, Joeri Kaal, Cruz Ferro-Vázquez, Oscar Serrano
Research outputs 2022 to 2026
Glomalin-related soil protein (GRSP) is an operationally defined soil organic matter pool that includes a heat shock protein linked to arbuscular mycorrhizal fungi (AMF) living in symbiosis with most vascular plants and plays a key role in soil health. However, the potential of GRSP as a palaeoecological proxy remains unexplored. We analysed the GRSP content in a North-western Iberian colluvial soil profile encompassing the last 14,000 years. We aimed to 1) identify whether GRSP is preserved, and 2) investigate whether GRSP could be used as a palaeoecological proxy after comparing its record with palynological and pedoanthracological records that account for …
Managing Collaboration Under Conservation Crisis: Trust, Risk, And Control In The Gulf Of Maine Fishery Management Network, Evelyn Roozee, Owen Temby, Dongkyu Kim, Antonia Sohns, Anthony Rocha Lima, Jasper R. De Vries, Gordon M. Hickey
Managing Collaboration Under Conservation Crisis: Trust, Risk, And Control In The Gulf Of Maine Fishery Management Network, Evelyn Roozee, Owen Temby, Dongkyu Kim, Antonia Sohns, Anthony Rocha Lima, Jasper R. De Vries, Gordon M. Hickey
School of Earth, Environmental, & Marine Sciences Faculty Publications
Transboundary fishery management and the intertwined conservation of critically endangered species represent significant governance challenges that require ongoing inter-organizational communication, collaboration, and collective action to achieve shared objectives. Previous research suggests that inter-organizational collaborative performance depends heavily on different dimensions of trust and complementary control mechanisms to mitigate the perceived risks of collaborating and enable the reciprocal sharing of resources and the coordination of activities. However, it is unclear how proposed relationships between trust, risk, and control are shaped by disruptions to established transboundary management networks. This study presents the results of survey research conducted in the Gulf of Maine …
Keyframe Selection From Motion Capture Data With Dual-Agent Reinforcement Learning, Kun Hu, Wang, Clinton Mo, Mingyang Ma, Shaohui Mei, Zebin Chen, Zhiyong Wang
Keyframe Selection From Motion Capture Data With Dual-Agent Reinforcement Learning, Kun Hu, Wang, Clinton Mo, Mingyang Ma, Shaohui Mei, Zebin Chen, Zhiyong Wang
Research outputs 2022 to 2026
Animation production workflows centered around motion capture techniques require animators to edit motions based on a set of keyframes. However, most existing keyframe selection methods are optimization-based, which suffer from the issues of flexibility and efficiency. In this paper, a novel deep reinforcement learning method with dual agents are proposed for unsupervised keyframe selection. First, an S-Agent and an R-Agent evaluate the actions of selection and refinement, respectively. A deep spatio-temporal network, namely graph keyframe evaluation network (GKEN), is proposed for the agents. Then, an animation specified reward is devised based on reconstruction, which fulfills three important properties of the …
Optimizing Multi-Layer/Multi-Physics Passive Adaptive Thermal Enclosures For Climate-Responsive Energy Regulation: A Numerical Study, Rajae Bousselham, Mingjiang Tao, Sergio Granados-Focil, Adriana Hera, Steven Van Dessel
Optimizing Multi-Layer/Multi-Physics Passive Adaptive Thermal Enclosures For Climate-Responsive Energy Regulation: A Numerical Study, Rajae Bousselham, Mingjiang Tao, Sergio Granados-Focil, Adriana Hera, Steven Van Dessel
Chemistry
Adaptive facades regulate heat transfer by adjusting their thermal behavior in response to environmental conditions. Passive adaptive systems, including stimuli-responsive thermal storage materials, tunable radiative coatings, and variable-conductivity layers, offer significant potential for material-based thermal regulation. However, their combined potential remains unexplored, as most studies examine individual mechanisms in isolation. As a result, trade-offs among energy savings, material usage, design complexity, and climate responsiveness are often underrepresented, overlooking coupled interactions in multilayer assemblies limiting their effectiveness. This study develops a transient three-dimensional numerical framework coupling heat transfer with multi-objective optimization to evaluate trade-offs between minimizing annual energy consumption and enclosure …
Semantic-Structural Decoupling: Disentangling Semantic Attention From Structural Bias In The Attention Manifold, Pengkun Jiao, Bin Zhu, Jingjing Chen, Yu-Gang Jiang
Semantic-Structural Decoupling: Disentangling Semantic Attention From Structural Bias In The Attention Manifold, Pengkun Jiao, Bin Zhu, Jingjing Chen, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
The empirical success of attention mechanism in Multimodal Large Language Models (MLLMs) often obscures its inherent, subtle flaws. Specifically, MLLMs consistently exhibit disproportionate attention toward certain semantically uninformative visual tokens, a phenomenon termed "register" or "Visual Attention Sinks." While existing inference intervention methods attempt to identify these sink tokens and redistribute their attention weights, such approaches typically treat these tokens in isolation and suffer from computational inefficiency. Instead, we reframe this phenomenon as a generalized textual bias exerted over visual features that extends beyond isolated sink tokens. From this perspective, a pervasive structural bias leads to the dilution of the …
A Finite Element Model For Thermomechanical Stress-Strain Fields In Transversely Isotropic Strain-Limiting Materials, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah
A Finite Element Model For Thermomechanical Stress-Strain Fields In Transversely Isotropic Strain-Limiting Materials, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah
School of Mathematical & Statistical Sciences Faculty Publications
This paper presents a comprehensive computational framework for investigating thermo-elastic fracture in transversely isotropic materials, where classical linear elasticity fails to predict physically realistic behavior near stress concentrations. We address the challenge of unphysical strain singularities at crack tips by employing a strain-limiting theory of elasticity. This theory is characterized by an algebraically nonlinear constitutive relationship between stress and strain, which intrinsically enforces a limit on the norm of the strain tensor. This approach allows the development of very large stresses, as expected near a crack tip, while ensuring that the corresponding strains remain physically bounded. A loosely coupled system …
Pattern Formation In Quantum Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung
Pattern Formation In Quantum Hierarchical Cellular Neural Networks, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Chayapuntika Indoung
School of Mathematical & Statistical Sciences Faculty Publications
We present a new class of quantum neural networks (QNNs) whose states are solutions of p -adic Schrödinger equations with a non-local potential that controls the interaction between the neurons. These equations are obtained as Wick rotations of the state equations of p -adic cellular neural networks (CNNs). The p -adic CNNs arise as continuous limits of large discrete hierarchical neural networks (NNs). The CNNs are bio-inspired by the Wilson–Cowan model, which describes the macroscopic dynamics of large populations of neurons. We provide a detailed study of the discretization of the new p -adic Schrödinger equations, which allows the construction …