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Articles 931 - 960 of 119494
Full-Text Articles in Entire DC Network
Search For Planetary-Mass Ultracompact Binaries Using Data From The First Part Of The Ligo–Virgo–Kagra Fourth Observing Run, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang
Search For Planetary-Mass Ultracompact Binaries Using Data From The First Part Of The Ligo–Virgo–Kagra Fourth Observing Run, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang
Physics & Astronomy Faculty Publications
We present a search for gravitational waves from inspiraling, planetary-mass ultracompact binaries using data from the first part of the fourth observing run of LIGO, Virgo, and KAGRA. Finding no evidence of such systems, we determine the maximum distance reach for such objects and their merger rate densities. Then, we identify classes of primordial black hole mass distributions for which these rate limits can be translated into relevant constraints on the mass distribution of primordial black holes, assuming that they are all composed of dark matter, in the mass range [10−6,10−3]𝑀⊙. Our constraints for the class of primordial black hole …
Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas
Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas
Northeast Journal of Complex Systems (NEJCS)
This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …
Fundamental Solutions To The Fractional Heat Operator, Jacob Flores
Fundamental Solutions To The Fractional Heat Operator, Jacob Flores
Math Theses
In this thesis, we are interested in showing the existence of a fundamental solution to the fractional heat operator. The fractional heat operator is a nonlocal linear operator used to model the time evolution of anomalous diffusion processes whose applicability arises in a wide variety of fields in the physical sciences, engineering, economics, and finance. Fundamental solutions to a partial differential operator are a class of generalized solutions formulated with rich mathematical analysis grounded in classes of well-behaved smooth functions referred to as test functions and their continuous linear functionals referred to as distributions. A primary tool that we use …
Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-46 Site Evaluation Summary Report (Sesr), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Butte Priority Soils Operable Unit Diggings East Final 100% Remedial Design Package Submittal, Josh Bryson
Butte Priority Soils Operable Unit Diggings East Final 100% Remedial Design Package Submittal, Josh Bryson
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2025 Butte Reclamation Evaluation System (Bres) Field Evaluation Summary Report And Technical Recommendations Proposal, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Revised Draft Final Unreclaimed Sites: Ur-07 Site Evaluation Summary Report (Sesr), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-27 Site Evaluation Summary Report (Sesr), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Conditional Approval Letter For The Draft Final 2024 Unreclaimed Sites Sampling: Ur-21 Site Evaluation Summary Report, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Glassy Magnetic Freezing Of Interacting Clusters In Materials Related To The Lk-99 Family, Serafim Teknowijoyo, Domenico Napoletani, Vahan Nikoghosyan, Armen Gulian
Glassy Magnetic Freezing Of Interacting Clusters In Materials Related To The Lk-99 Family, Serafim Teknowijoyo, Domenico Napoletani, Vahan Nikoghosyan, Armen Gulian
Mathematics, Physics, and Computer Science Faculty Articles and Research
We report reproducible magnetization anomalies appearing below room temperature in copper-doped apatite materials belonging to the LK-99 family synthesized via hydrothermal methods. These anomalies are observed consistently across samples prepared under comparable conditions. Although the extracted Mydosh parameter lies within the range often associated with vortex-glass behavior in superconductors, a detailed analysis of DC magnetization, AC susceptibility, field dependence, and magnetic memory effects demonstrates that the observed phenomena are not related to superconductivity. Instead, the data are consistent with glassy magnetic freezing of interacting clusters. Compositional and structural analysis identifies covellite (CuS), one of the constituent phases in these multiphase …
Image Fusion Based On Deep Learning With Different Locations And Sizes Of Objects, Baneen Al-Kalabi, Tawfiq Al-Assadi
Image Fusion Based On Deep Learning With Different Locations And Sizes Of Objects, Baneen Al-Kalabi, Tawfiq Al-Assadi
Journal of Intelligent Informatics, Networking, and Cybersecurity
Multi-focus image fusion combines partially focused images into a single all-in-focus composite. Existing object-based methods assume precise spatial and scale alignment across source images, an assumption that frequently fails in Misaligned Multi-Focus Dataset scenarios due to camera displacement and focal length variation. This paper proposes a novel training-free, object-aware fusion framework to address this limitation through a five-stage pipeline: YOLOv8x detection, SAM2-L segmentation, LoFTR correspondence matching, a novel Scale-Aware Area Resize Algorithm, and GLCM-guided MSB/LSB bit-level fusion. The framework was evaluated on the EDMF benchmark (20 image pairs, synthetically modified to simulate Misaligned Multi-Focus Dataset shifts) and a Misaligned Multi-Focus …
Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim
Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim
Journal of Intelligent Informatics, Networking, and Cybersecurity
From transform-domain decorrelation and adaptive entropy coding, we propose a method for efficient lossless compression of medical images in this work. We implement the Integer Discrete Wavelet Transform (IDWT) to decompose the input image into four subbands of LL, LH, HL, HH, encompassing approximation and directional detail elements, in the initial implementation. It also removes spatial redundancy in image information and decomposes image information into a less correlated and more sparsely distributed set of coefficients. To decrease redundancy further, it proposes a subband-dependent differencing scheme, which decorrelates neighbouring wavelet coefficients with directional prediction. So horizontal differencing is done on LH, …
A Blockchain-Integrated Federated Learning Model And Autoencoder-Based Feature Reduction For Improving Iot Intrusion Detection, Tahseen A. Wotaifi
A Blockchain-Integrated Federated Learning Model And Autoencoder-Based Feature Reduction For Improving Iot Intrusion Detection, Tahseen A. Wotaifi
Journal of Intelligent Informatics, Networking, and Cybersecurity
The rapid growth of Internet of Things (IoT) environments has brought forth a wealth of security challenges in detecting network intrusions in diverse and resource-restricted systems. Privacy, scalability, and single point of failure issues plague traditional centralized intrusion detection solutions. To address these challenges, the study proposes a secure and adaptive intrusion detection model using Federated Learning (FL) and Blockchain, augmented with autoencoder-based feature reduction. The ToN-IoT dataset is pre-processed, and then an unsupervised autoencoder is used to build informative low-dimensional feature representations. The processed data is deployed to various clients to mimic a real federated situation. Every client will …
A Dual- Task Hierarchical Graph Attention Network For Protein-Protein Interaction Sites Prediction, Oras A. Hussein, Eman S. Al-Shamery
A Dual- Task Hierarchical Graph Attention Network For Protein-Protein Interaction Sites Prediction, Oras A. Hussein, Eman S. Al-Shamery
Journal of Intelligent Informatics, Networking, and Cybersecurity
In computational structural biology, it is still very hard to accurately find protein-protein interaction (PPI) sites and estimate how strong the interaction would be. In this research, we provide an innovative two-stage deep learning framework that combines residue-level graph representation learning with protein-level regression to achieve a thorough modeling of protein interactions. Protein structures first encoded as residue graphs, with nodes that stand for amino acids and edges that show how close they are to each other in space. To find binding residues, a deep residual Graph Attention Network v2 (GATv2) uses multi-head attention, residual connections, and Jumping Knowledge aggregation …
A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution - Part B: Professional Development Framework And Institutional Implementation, Alessandro M. Selvitella, Jeffrey R. Anderson
A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution - Part B: Professional Development Framework And Institutional Implementation, Alessandro M. Selvitella, Jeffrey R. Anderson
CODEE Journal
This paper presents the professional-development and institutional-implementation component of a three-paper program on introducing data-driven dynamical systems into undergraduate ordinary differential equations instruction at a primarily undergraduate institution. The companion paper \cite{SelvitellaAnderson2026} develops the mathematical and computational content, including regression, regularization, Dynamic Mode Decomposition, Sparse Identification of Nonlinear Dynamics, and a Van der Pol oscillator activity. The present paper asks a complementary implementation question: what departmental structures, graduate teaching assistant roles, professional-development activities, and course-support pathways are needed for such materials to become teachable within local undergraduate settings?
We describe a three-phase professional-development model for graduate teaching assistants in the …
Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation, Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini De Andrade, Joshua B. Fisher, Justin L. Huntington, Christopher Pearson, R. Iestyn Woolway, Roseilson Vale, Júlio Tota, Gabriel B. Senay, Huilin Gao, Anderson Ruhoff
Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation, Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini De Andrade, Joshua B. Fisher, Justin L. Huntington, Christopher Pearson, R. Iestyn Woolway, Roseilson Vale, Júlio Tota, Gabriel B. Senay, Huilin Gao, Anderson Ruhoff
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing‐based …
Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano
Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano
Publications
The inner surface pressure of an axisymmetric inlet/isolator model was measured using anodized-aluminum pressure-sensitive paint (PSP) viewing through cast acrylic. Temperaturesensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at 𝑹𝒆 = 7.1 ×106 /m under conventional noise conditions. Transverse jet injection with jet-to-inlet mass-flow ratios up to 0.8 was used to induce unstart in the inlet/isolator. Background-oriented schlieren visualization of the inlet shocks was collected simultaneously with the PSP to determine when the inlet unstarted. Computational fluid dynamics results were used to determine off-wall flow structures and quantify approach …
Exogenous Ribosome Incorporation Induces Lineage Transdifferentiation In Intestinal And Liver Cancer Cells, Haoxuan Gu, Nadia Wahyuningsih, Keisuke Yamashita, Shota Inoue, Fuchao Tan, Mani Sharaki, Muhaimin Rifa’I, Kunimasa Ohta
Exogenous Ribosome Incorporation Induces Lineage Transdifferentiation In Intestinal And Liver Cancer Cells, Haoxuan Gu, Nadia Wahyuningsih, Keisuke Yamashita, Shota Inoue, Fuchao Tan, Mani Sharaki, Muhaimin Rifa’I, Kunimasa Ohta
Karbala International Journal of Modern Science
It has previously been shown that exogenous bacterial ribosomes added to somatic cells and various cancer cell lines generate ribosome-induced cell clusters (RICs) capable of transdifferentiating into multiple cellular lineages. However, the scope of ribosome-induced transdifferentiation in cancer cells remains poorly understood. This study aimed to analyze the effects of exogenous ribosome incorporation on human cancer cell lines, specifically the intestinal epithelial cell line Caco-2 and the hepatocellular carcinoma cell line HepG2. Caco-2 and HepG2 cells were cultured with purified bacterial ribosomes in human ES/iPS cell medium after trypsinization, resulting in the formation of ribosome-induced Caco-2 (RICs-Ca) and HepG2 (RICs-He) …
Mathematically Driven Enhancement In Information Security, Suhaib Badran, Asmaa Alqassab
Mathematically Driven Enhancement In Information Security, Suhaib Badran, Asmaa Alqassab
Karbala International Journal of Modern Science
A new mathematically based cryptographic method has been proposed to improve information security; it involves transforming data into a matrix and performing bit-level operations. This decryption then follows the basic mechanism of a deterministic, fully invertible algorithm, with this invertible algorithm having the same principle as the existing ones: the process of decryption is symmetrical, where the process is reversed based on the input of the ciphertext. The plaintext is transformed into a square matrix, which includes matrix rotation, permutation of rows, circular bit shifting, and finally an affine linear transformation followed by an additional Base62-like encoding layer to further …
Tapping Into The Ocean’S Hidden Energy: Feasibility Of A 5 Mw Otec Installation In North Bali, Widodo Setiyo Pranowo, Yani Permanawati, Gisela Malya Asoka Anindita, Agung Kurniawan, Albertus Sulaiman, Johar Setiyadi, Safri Burhanuddin, Ivonne Milichristi Radjawane, Hansan Park, Endro Sigit Kurniawan
Tapping Into The Ocean’S Hidden Energy: Feasibility Of A 5 Mw Otec Installation In North Bali, Widodo Setiyo Pranowo, Yani Permanawati, Gisela Malya Asoka Anindita, Agung Kurniawan, Albertus Sulaiman, Johar Setiyadi, Safri Burhanuddin, Ivonne Milichristi Radjawane, Hansan Park, Endro Sigit Kurniawan
Karbala International Journal of Modern Science
Indonesia is an archipelagic country surrounded by water and faces energy challenges due to the low use of renewable energy. Among the potential renewable options, marine energy is a particularly suitable resource given the country’s geographical nature. Based on this discussion, seawater temperature can be used as an alternative ocean thermal en-ergy known as ocean thermal energy conversion (OTEC) by using the difference in sea surface and deep-sea water temperatures. Therefore, this study aimed to examine OTEC installations in North Bali waters using closed-cycle OTEC calculations for a 5 MW system. Following this objective, we examined the water conditions by …
Assessment And Evidence Practices In Cybersecurity Education: A Systematic Review (2015–2025), James K. Mayberry
Assessment And Evidence Practices In Cybersecurity Education: A Systematic Review (2015–2025), James K. Mayberry
Journal of Cybersecurity Education, Research and Practice
This study presents a PRISMA-based systematic review of 412 cybersecurity education intervention studies, coding assessment methods, evidence types, claimed outcomes, use of established assessment instruments, and artifact availability. Despite frequent claims of skill development and workforce preparation, 45.4% of studies reported no identifiable assessment. Knowledge tests appeared in 11.4% of studies, while performance assessments appeared in 10.2%. From 2015 to 2025, assessment practices remained dominated by post-only designs or no assessment, with no statistically detectable increase in pre/post-capable designs. Use of established assessment instruments was rare, with 94.2% of assessed studies using ad hoc measures or not identifying an established …
Surveying First-Year Stem Students’ Self-Reported Knowledge, Skills, And Attitudes Towards Teamwork, Gregory R. Goldsmith, Camilla Acosta
Surveying First-Year Stem Students’ Self-Reported Knowledge, Skills, And Attitudes Towards Teamwork, Gregory R. Goldsmith, Camilla Acosta
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The ability to work in a team is cited as a key outcome for many undergraduate Science, Technology, Engineering, and Mathematics (STEM) programs, both as a method for improving learning and as a highly desired trait for employers. Despite a growing focus on teamwork, our ability to design appropriate teamwork curriculum is limited by our poor understanding of what students arriving at university know about teamwork, what teamwork skills they consider themselves to possess, and their attitudes towards teamwork. We delivered a mixed-methods survey to first-year STEM undergraduate students (n = 205) to benchmark knowledge, skills and attitudes towards …
Enhancing Ecological Resilience: Evaluating Peanut Island's Breakwater Impacts On Coral Reef And Shoreline Dynamics, Dayana Castillo
Enhancing Ecological Resilience: Evaluating Peanut Island's Breakwater Impacts On Coral Reef And Shoreline Dynamics, Dayana Castillo
Electronic Theses and Dissertations 2020 - Present
Anthropogenic shoreline modification and inlet-driven hydrodynamic processes can alter sediment transport pathways and sediment deposition in adjacent coral reef environments. This study evaluated how coastal engineering structures, sediment transport dynamics, and localized hydrodynamic processes influence sediment distribution and coral-associated habitats at Peanut Island, Florida. Beach profile surveys, shoreline mapping, sediment grain size analyses, coral monitoring, and historical aerial imagery were used to assess shoreline variability, sediment characteristics, and long-term shoreline evolution between October 2024 and July 2025. Results indicated that much of the eastern shoreline remained relatively stable, while greater variability was observed along the southern shoreline adjacent to the …
Ecological Gdp Of “Lucid Waters And Lush Mountains Are Invaluable Assets”, Wang Guangqian, Deyu Zhong
Ecological Gdp Of “Lucid Waters And Lush Mountains Are Invaluable Assets”, Wang Guangqian, Deyu Zhong
Bulletin of Chinese Academy of Sciences (Chinese Version)
Based on the concept of “lucid waters and lush mountains are invaluable assets”, this study investigates the theoretical connotation and accounting pathways of ecological GDP. (1) The core connotation of ecological value is elucidated from three dimensions—time, space, and civilization—and an economic quantification framework of principal–interest–interest rate is constructed. With four categories of ecological products as the foundation, the Green Certificate as the entitlement instrument, and a 5% annual simple interest rate as the accounting benchmark, ecological value is transformed from qualitative description to quantitative accounting. (2) The concept of ecological new quality productive forces is proposed, revealing its four-dimensional …
Building Ai-Native Innovation System To Drive Transformation And Innovation In Research Organization And Management Models, Hong Xuehai
Bulletin of Chinese Academy of Sciences (Chinese Version)
Artificial intelligence (AI) is profoundly reshaping research paradigms. This study aims to analyze the intrinsic mechanisms through which AI empowers scientific research and its impact on the organizational management models of research. By summarizing what AI can and cannot do in empowering research, it reveals the current effectiveness and capability boundaries of AI in this domain. Based on the extraction of common core conditions for AI-empowered research and the deconstruction of typical cases of AI-enabled research organizational models, this study analyzes the differences between the organizational management model of AI-empowered research and traditional research organizational models. Furthermore, it proposes three …
Policy Reflections On Promoting Strategic Oriented Basic Research In China: Insights From The U. S. Department Of Energy’S Basic Research Funding System, You Yu, Yun Liu, Wenneng Zhou
Policy Reflections On Promoting Strategic Oriented Basic Research In China: Insights From The U. S. Department Of Energy’S Basic Research Funding System, You Yu, Yun Liu, Wenneng Zhou
Bulletin of Chinese Academy of Sciences (Chinese Version)
Strategy-oriented basic research is a key pathway to driving major original breakthroughs at the frontiers of science, serving national strategic needs, and securing a leading position in global science and technology. It is also a vital pillar for achieving high-level self-reliance and self-strengthening in science and technology and enhancing the capacity for original innovation. Faced with the urgent need to build a science and technology powerhouse and achieve breakthroughs in key core technologies, China has gradually improved its organizational framework for advancing strategy-oriented basic research and has established a solid foundation for policy support and resource allocation. Nevertheless, when measured …
Ai-Powered Knowledge Engines As Research Infrastructure For Systematic Knowledge Discovery, Gary Welz
Ai-Powered Knowledge Engines As Research Infrastructure For Systematic Knowledge Discovery, Gary Welz
Publications and Research
This paper proposes knowledge engines as a framework for understanding how intelligent systems — both human and artificial — systematically discover, integrate, and generate knowledge. We argue that history’s greatest scientific minds functioned as knowledge engines, processing information through iterative cycles of ingestion, analysis, synthesis, and communication, guided by curiosity and willingness to challenge established beliefs.
We propose a taxonomy of nine integrated capabilities — ingestion, digestion, analysis, calculation, comparison, connection, association, analogy, and multimodal communication — that any serious knowledge engine must combine systematically. The argument is deliberately integrative: achieving ambitious research goals requires orchestrating all nine capabilities within …
Can An Ai System Be Creative? A Critical Perspective From Art And Engineering, Ivan Magrin-Chagnolleau
Can An Ai System Be Creative? A Critical Perspective From Art And Engineering, Ivan Magrin-Chagnolleau
Presidential Fellows Articles and Research
This paper examines the question of whether artificial intelligence (AI) systems can be creative, approached from the dual perspective of a researcher trained in electrical engineering, pattern recognition, machine learning, and neural networks, who has also spent most of his life engaged in the arts as actor, stage and film director, writer, composer, and visual artist, and in philosophy. Drawing on Margaret Boden’s foundational framework — both her three properties of creativity (novelty, surprise, and value) and her three types of creative processes (combinatorial, exploratory, and transformational) — the paper argues that AI systems are structurally incapable of creativity in …
One-For-All Community Search On Unseen Graphs, Mo Li, Zhaosong Zhao, Linlin Ding, Renata Borovica-Gajic, Zhongming Yao, Jianxin Li
One-For-All Community Search On Unseen Graphs, Mo Li, Zhaosong Zhao, Linlin Ding, Renata Borovica-Gajic, Zhongming Yao, Jianxin Li
Research outputs 2022 to 2026
Community search is a fundamental graph-based retrieval problem that aims to identify a query-dependent subgraph whose nodes exhibit strong internal connectivity. While recent learning-based methods improve retrieval effectiveness via graph representation learning, they follow a ''one-use-one-train'' paradigm that requires retraining or fine-tuning for each target graph, leading to high data dependency, high training costs, and limited generalization. To handle this, we propose OFA-CS, a ''one-for-all'' community search framework trained once on source datasets and directly deployed to arbitrary unseen graphs without retraining or fine-tuning, while preserving strong performance. Specifically, we introduce a Spectral-Aware Feature Alignment module to unify feature dimensionality …