Search Results (4,798)

Quantum computing exploits the principles of quantum mechanics to perform computation. Information is stored in qubits and processed with a sequence of quantum gates arranged as circuits. Verifying the correctness of quantum circuits is becoming essential as hardware scales in qubit count and architectural complexity. Traditional testing and naive simulation do not scale and quickly become computationally infeasible because the state space grows exponentially. This creates a strong need for more powerful and scalable verification techniques. Formal methods offer a viable solution by providing mathematically rigorous and scalable verification techniques that address these scalability challenges through abstraction, symbolic reasoning, and probabilistic guarantees. This study examines how formal methods are applied to quantum-circuit verification. Specifically, four families of formal techniques: barrier certificates, abstract interpretation, model checking, and theorem proving are examined, along with the theoretical foundations and practical applications of these techniques. Finally, the study highlights open challenges and identifies promising directions for future research. An extensive set of references is included to support further study and exploration. Full article

Data in multi-tenant cloud environments is increasingly shared across organizations, making strong in-memory isolation a critical requirement. Existing confidential computing mechanisms such as AMD SEV provide hardware-enforced protection, but they require specialized processors and incur non-trivial performance overhead, which limits their deployment in heterogeneous clouds. This paper presents DASPRI, a software-based approach that constructs an isolated execution environment for trusted virtual machines by combining dual address spaces with privilege restriction. DASPRI partitions physical memory into a normal region and an isolated region on NUMA systems, and steers all memory allocations of trusted VMs into the isolated region by monitoring page faults and kernel allocation paths. It further hardens the isolated region by mediating direct and dynamic kernel mappings and by maintaining separate page caches for trusted and normal VMs. Remote attestation is integrated to protect the integrity of metadata used to identify trusted VMs. We implement DASPRI on a HUAWEI Kunpeng AArch64 server running OpenEuler and evaluate it using microbenchmarks and UnixBench. Experimental results show that DASPRI enforces strong memory isolation with less than 5% overhead on basic system operations and only 1.3% degradation in overall host performance. Full article

University campus green spaces function as critical microcosms of urban building environments, directly advancing Sustainable Development Goals 3 (Good Health and Well-being) and 11 (Sustainable Cities and Communities) through evidence-based landscape design. Taking a large university in China as the research object, this study integrates virtual reality (VR) simulations with synchronized psychophysiological measurements and perceptual scales to quantify how three planting modes—clustered, scattered, and regular—influence restorative experiences across teaching, living, and administrative areas. Rigorous data processing ensured robustness. The results revealed functional-area-specific restoration pathways: clustered planting enhanced relaxation in living zones, scattered planting elevated vitality in teaching areas, and regular planting reinforced security perception in administrative spaces. A path model was used to elucidate how four-dimensional (4D) landscape indicators (openness, pleasantness, diversity, focus) mediate psychological and physiological responses. Theoretically, this 4D framework translates abstract restorative experiences into operable design dimensions; methodologically, VR-based multi-source measurement offers a replicable technical pathway for scheme verification; practically, it serves as a quantitative tool for planting optimization. Critically, these campus-derived insights offer transferable design principles for enhancing well-being across urban building environments, delivering a replicable VR-assisted framework that directly contributes to sustainable cities through human-centered, evidence-based landscape solutions. Full article

Zero-shot generalization to out-of-distribution (OOD) teammates and opponents in multi-agent systems (MASs) remains a fundamental challenge for general-purpose AI, especially in open-ended interaction scenarios. Existing multi-agent reinforcement learning (MARL) paradigms, such as self-play and population-based training, often collapse to a limited subset of Nash equilibria, leaving agents brittle when faced with semantically diverse, unseen behaviors. Recent approaches that invoke Large Language Models (LLMs) at run time can improve adaptability but introduce substantial latency and can become less reliable as task horizons grow; in contrast, LLM-assisted reward-shaping methods remain constrained by the inefficiency of the inner reinforcement-learning loop. To address these limitations, we propose LLM-TOC (LLM-Driven Theory-of-Mind Adversarial Curriculum), which casts generalization as a bi-level Stackelberg game: in the inner loop, a MARL agent (the follower) minimizes regret against a fixed population, while in the outer loop, an LLM serves as a semantic oracle that generates executable adversarial or cooperative strategies in a Turing-complete code space to maximize the agent’s regret. To cope with the absence of gradients in discrete code generation, we introduce Gradient Saliency Feedback, which transforms pixel-level value fluctuations into semantically meaningful causal cues to steer the LLM toward targeted strategy synthesis. We further provide motivating theoretical analysis via the PAC-Bayes framework, showing that LLM-TOC converges at rate $O(1/\sqrt{K})$ and yields a tighter generalization error bound than parameter-space exploration under reasonable preconditions. Experiments on the Melting Pot benchmark demonstrate that, with expected cumulative collective return as the core zero-shot generalization metric, LLM-TOC consistently outperforms self-play baselines (IPPO and MAPPO) and the LLM-inference method Hypothetical Minds across all held-out test scenarios, reaching 75% to 85% of the upper-bound performance of Oracle PPO. Meanwhile, with the number of RL environment interaction steps to reach the target relative performance as the core efficiency metric, our framework reduces the total training computational cost by more than 60% compared with mainstream baselines. Full article

Enclosed learning spaces, e.g., classrooms, are used in most schools. Open learning spaces, which enable teaching more than one group of students at a time, have become increasingly popular. A recent survey showed that acoustic satisfaction was lower among teachers working in open learning spaces. Our purpose was to compare the acoustic conditions of these learning space types. We investigated the room acoustic quality of 73 learning spaces in 20 schools. Ten schools involved only enclosed and ten both open and enclosed learning spaces. Measurements concerned speech transmission index, STI, background noise level, L_Aeq, and reverberation time, T. Variation in results in both learning space types was rather large. In enclosed learning spaces, STI varied within 0.64–0.83, L_Aeq within 25–47 dB, and T within 0.34–0.82 s. The corresponding variations in open learning spaces were 0.47–0.91, 29–44 dB, and 0.44–0.72 s. The differences between enclosed and open learning spaces were surprisingly small. Due to the different intended uses of these space types, Finnish target values are tighter for open than for enclosed learning spaces. These target values were fulfilled in 56% of enclosed and 9% of open learning spaces. The more frequent violation of target values in open learning spaces was due to the STI being too large at longer distances. Our study provides suggestive evidence that the room acoustic conditions are worse in open than enclosed learning spaces. Further research is needed to prove whether room acoustic conditions could explain worse acoustic satisfaction in teachers. Full article

Urban flood frequency analysis faces unique challenges as land development alters watershed hydrology, producing nonstationary flood records. This study demonstrates nonstationary flood frequency analysis (NSFFA) using RMC-BestFit, an open-source Bayesian software, through two Texas case studies. Brays Bayou at Houston (96 years of record) exemplifies an urbanized watershed with increasing flood trends; a step-logistic model captures both the abrupt increase in mean flood magnitude around 1968 and the progressive decrease in log-space variance as urbanization homogenized runoff response. O.C. Fisher Reservoir (169 years of record) exhibits decreasing trends attributed to brush encroachment and groundwater extraction; despite a sinusoidal model achieving best information criteria, a step function was selected based on physical reasoning, demonstrating that statistical fit alone should not dictate model selection. Results reveal contrasting frequency curve patterns: at O.C. Fisher, stationary and nonstationary curves differ uniformly (53% reduction in 100-year flood), while at Brays Bayou, curves differ substantially for frequent events (48% increase in 2-year flood) but converge in the extreme tail due to opposing trends in location and scale parameters. These findings underscore that NSFFA relevance depends on decision context. Bayesian methods offer key advantages including flexible integration of diverse data sources, comprehensive uncertainty quantification, and principled model comparison. Open-source software democratizes access to these methods, promoting transparency and reproducibility. Full article

With the advancement of digital technology and Industry 4.0, artificial intelligence (AI) is gradually embedded in human resource management and has become an important digital foundation to support the sustainable transformation of enterprises. However, the research in the manufacturing context, particularly through the challenge perspective at different levels, remains fragmented. This work represents a systematic review of 347 articles from Scopus and Web of Science from 2000 to 2025 and employs a dual-method analysis strategy embracing metrics and in-depth coding on 100 core publications. Excel, Bibliometrix, CiteSpace, Latent Dirichlet Allocation (LDA), and VOSviewer were utilized for quantitative analysis, while open–axial–selective coding of the Grounded theory approach was applied to generate qualitative results. The findings revealed six key challenges in integrating AI-HRM within manufacturing and six approaches to solve the identified issues. The Challenge–Approach Matching Matrix was constructed, illustrating the suitability of different pathways for addressing specific challenges. Analysis of thematic evolution in AI-HRM research resulted in the identification of three distinctive phases and demonstrated a consistent shift from technology-centric approaches towards human–machine collaboration. The primary contribution of this research lies in proposing a Multi-Level Embedded Framework providing a complex view of AI-HRM in a manufacturing sector at micro, meso, and macro levels. The absence of sustainable HR transformation through AI integration was identified as the critical challenge at the macro level. This research provides theoretical and practical implications for designing the sustainable HRM system based on ESG principles and favors the United Nations Sustainable Development Goals 9 and 12. Full article

This paper introduces and investigates a new class of generalized open sets, called fuzzy $h_{\mathcal{I}}$-open sets, in fuzzy ideal topological spaces $(X,\tilde{\tau },\tilde{\mathcal{I}})$. We prove that the collection of all fuzzy $h_{\mathcal{I}}$-open sets forms a fuzzy topology ${\tilde{\tau }}^{h_{\mathcal{I}}}$ satisfying $\tilde{\tau }\subseteq {\tilde{\tau }}^{h_{\mathcal{I}}}$ and show that ${\tilde{\tau }}^{\ast }$ and ${\tilde{\tau }}^{h_{\mathcal{I}}}$ are in general incomparable, demonstrating that the $h_{\mathcal{I}}$-construction captures fundamentally different information from the ∗-topology. We establish precise conditions under which these topologies coincide and introduce a fuzzy $h_{\mathcal{I}}$-$T_1$ separation axiom. Furthermore, we develop a comprehensive hierarchy of generalizations—fuzzy $h{\alpha }_{\mathcal{I}}$-open, fuzzy $h{p}_{\mathcal{I}}$-open, fuzzy $h{s}_{\mathcal{I}}$-open, and fuzzy $h{\beta }_{\mathcal{I}}$-open sets—and prove that these classes are pairwise distinct through genuinely fuzzy (non-characteristic) examples. We introduce fuzzy $h_{\mathcal{I}}$-continuous and fuzzy $h_{\mathcal{I}}$-irresolute functions, providing six equivalent characterizations and a closed-set criterion via the ∗-interior operator. The framework is applied to a concrete multi-criteria decision-making problem, where the ideal filters negligible criteria and the $h_{\mathcal{I}}$-interior provides a refined ranking that demonstrably outperforms the original fuzzy topology. Full article

Climate change has intensified the need for adaptation in urban environments, yet its integration into historic urban squares, where recreational activities were heavily concentrated, has remained underexplored. In this context, the study examined the square located between Hagia Sophia and the Blue Mosque, which is also defined as an urban recreation area and a focal point of culture-based tourism, during periods of extreme weather conditions and high flows of both local (n = 152), and international tourists (n = 236), evaluating it through different spatial activity typologies. A total of 388 participants were surveyed at 25 survey points within the square, while meteorological parameters were obtained from meteorological stations. The findings showed that the lowest level of heat stress across all typologies corresponded to “slight heat stress,” while user responses varied according to spatial characteristics. In movement spaces, the absence of shading elements increased both heat stress and shade demand, whereas in stationary spaces, the presence of trees reduced heat stress but preferences for lower air humidity persisted even under shaded conditions. Sky openness was not identified as a direct determinant of thermal sensation, with meteorological and perceptual factors proving more influential. PET explained approximately 65% of the variation in MTSV among tourists, compared to 55% among local residents. Across typologies, only increases in air temperature negatively affected thermal satisfaction. Moreover, tourists perceived the square more holistically and reported higher satisfaction compared to locals, whose environmental demands were distinct. These results highlighted the importance of spatial activity typologies in shaping thermal experience and underlined the necessity of design strategies that extended beyond heat-mitigation measures. Holistic and flexible approaches that accounted for user profiles, activity types, and intensity of use were found to be essential for improving thermal comfort in historic urban squares with diverse spatial configurations. Full article

Public buildings and open spaces form key elements in an exchange system of both tangible resources (energy, water, physical spaces) and intangible assets (services, skills, time). This study presents an innovative protocol (AGAPE—Automatic GIS Assessment Protocol for Energy and environment) to regenerate metropolitan suburbs by managing common resources and support sustainable communities. It tackles energy poverty by integrating urban planning, environmental design, and economics into geographic information science. This expedites public well-being by redesigning public facilities to enhance community connections and improve bioclimatic resilience. The model test site is a peripheral suburban area, Melito di Napoli, within the Metropolitan City of Naples (Italy), characterized by high population density and ongoing suburban expansion. The protocol evaluates temporal scenarios for implementing multi-purpose solutions, supporting public agencies in strategic intervention assessments, optimizing funding allocation and community benefits. The modeling of redesigned community assets reveal key outcomes: renewed land-use opportunities, reduced spatial inequities, and increased climate change resilience. The transformation of public buildings and facilities into multi-benefit community cores catalyzes virtuous urban regeneration processes. The model AGAPE provides a replicable decision framework to transform existing settlements and to drive the transition towards more sustainable, equitable urban communities. Full article

Affiliated Open Spaces (AOS) constitute vital public assets within high-density vertical cities. However, prevailing scholarship remains largely confined to two-dimensional horizontal perspectives, overlooking the quantitative impact of vertical built environment characteristics on spatial distribution and human behavior. Focusing on four high-density districts in Guangzhou typified by distinct three-dimensional morphologies, this study integrates field surveys, 3D geospatial data acquisition, and 621 valid questionnaires to empirically analyze the impact of 3D spatial features on user behavior and the mediating role of accessibility. Utilizing the ArcGIS 3D Analyst for vertical accessibility measurement and Partial Least Squares Structural Equation Modeling (PLS-SEM) for path analysis, the study tests the hypothesized relationships using multi-source data. The results indicate that (1) a user’s vertical location exerts a significant negative impact on both accessibility and human behavior; (2) building density and building functional diversity indirectly promote user engagement primarily by significantly enhancing accessibility, thereby confirming accessibility as a critical mediator; and (3) significant spatial heterogeneity exists, revealing distinct correlation patterns across varying built environments. This research elucidates the pivotal constraint of “vertical location” and validates the mediating efficacy of accessibility, offering empirical insights for human-centric vertical urban planning. Full article

In clinical practice, the coexistence of Superior Mesenteric Artery (SMA) syndrome (also known as Wilkie’s syndrome) and Celiac Artery Compression Syndrome (also referred to as Dunbar’s syndrome) is extremely rare. This combined pathology is characterized by simultaneous impairment of blood flow in the celiac trunk and compression of the duodenum, which complicates both diagnosis and treatment strategy selection. Traditional open surgical correction is associated with significant invasiveness due to the complexity of the anatomical relationships involved. Minimally invasive approaches, including robot-assisted surgery, allow precise dissection within confined anatomical spaces. This article presents a clinical case of simultaneous robot-assisted decompression of the celiac trunk and duodenum using the da Vinci Xi system. The case demonstrates the technical feasibility of a combined minimally invasive approach for the management of concurrent vascular and duodenal compression. Full article

For the first time, the ternary Zintl phases RbCaBi and CsCaBi have been synthesized and structurally characterized via single-crystal X-ray diffraction methods. These two compounds, alongside KCaBi, are confirmed to crystallize in a tetragonal crystal system with the space group P4/nmm (no. 129) with two formula units per cell. The lattice constants increase monotonically from a = 5.3812(10) Å and c = 8.410(3) Å for KCaBi, to a = 5.4139(7) Å and c = 8.6180(17) Å for RbCaBi, and to a = 5.4709(11) Å and c = 8.914(3) Å for CsCaBi. The crystal structure can be visualized as an array of square prisms formed of Bi atoms, which are centered by alkali metal atoms, while the Ca atoms fill tetrahedra formed of Bi atoms. There are no direct Bi–Bi interactions in the crystal structure; therefore, with full cation ordering present, the chemical bonding in the ACaBi compounds can be rationalized within the fully ionic approximation as A⁺Ca²⁺Bi³⁻ (A = K, Rb, Cs). This suggests the opening of an (narrow) energy gap between the valence and conduction bands, i.e., semiconducting behavior. Full article

Professors, students, and researchers from universities around the world use software distributed under licenses for numerical simulation purposes, which requires a computer with considerable hardware capabilities. This implies a high cost of simulations in engineering applications that require dynamic modeling using numerical methods, particularly in robotics and nonlinear control. This article compares and analyzes the performance of a frugal simulation scheme based on the use of low-cost, free, and open-source technology, specifically a low-power, single-board minicomputer (Raspberry Pi) in conjunction with GNU-Octave software. The benchmark is a numerical simulation of trajectory tracking control in the joint space of a Selective Conformal Assembly Robot Arm (SCARA). To perform this task, a system of coupled nonlinear differential equations is solved in matrix form using a numerical method known as an ODE solver. This solution includes the control law and the dynamic system model derived from Euler–Lagrange formalism. The time complexity and accuracy are analyzed to compare the performance of the frugal simulation tool with that of a conventional simulation setup consisting of a personal computer and MATLAB^TM running the same simulation code. The analysis shows minimal deviations in the numerical solutions and reasonable time complexity. Moreover, the frugality score of this approach and the low acquisition cost of the simulation tool enable the creation of simulation laboratories at universities with limited budgets for education and research. Full article

Systematic, spatially explicit tree inventories are increasingly implemented in cities worldwide, as they are crucial for evidence-based green infrastructure planning. Currently, different approaches are adopted, which differ in methodological framework and parameter standardization, limiting comparative assessments and coordinated monitoring. This study presents a replicable protocol for a field-based digital street tree census, applied in a densely built central area and in a low-density suburban area of Rome. Field surveys documented a set of 15 parameters, including species identity, dendrometric and tree pit parameters, acquired using open-source QGIS/QField tools. Subsequent analysis evaluated floristic diversity, population structure, and climate suitability at the neighborhood scale, enabling the identification of context-specific vulnerabilities. The testing of the methodology shown in this work involved 13,017 georeferenced tree pits, pointing out substantial pit restoration needs and insufficient soil conditions in the most densely urbanized area, whereas the suburban area shows optimal conditions with extensive road verge green spaces. Joint interpretation of the considered parameters reveals that high floristic diversity alone does not guarantee climate resilience: high-diversity neighborhoods can exhibit substantial non-climate-resilient species and limited alignment with local species recommendations, demonstrating that comprehensive evaluation of street tree populations requires integrated analysis. The operationalized protocol establishes a replicable, municipally scalable methodological framework, providing policymakers with fine-scale, actionable insights enabling differentiated urban forestry strategies addressing both infrastructure deficits and long-term species climate suitability. Full article