Abstract: We study finite orbit-sum termination for the two-sided exponential iteration generated by \( f(x)=2^x-1 \) and its inverse on the unit interval. For \( w\in(0,1] \), put \( u_k(w)=f^k(w) \) for \( k\in\mathbb Z \). A binary digit sequence \( a=(a_k)_{k\in\mathbb Z} \) with $a_0=1$ is normalized by \( \sum_{k\in\mathbb Z}a_k u_k(w)=1. \) Thus the expansion scale is generated by the point being expanded, rather than by an external base or partition, and finite termination is governed by finite orbit-sum equations. We prove existence and uniqueness of normalization roots for admissible digit sequences, construct the associated greedy code, and characterize finite termination by finite orbit-sum hitting equations compatible with the greedy order. The finite terminal set is countable and has Lebesgue measure zero. On the arithmetic side, the first positive and first negative boundary roots are transcendental, and the first positive second-order boundary root is irrational. Assuming Schanuel's conjecture, we exclude all non-trivial rational finite terminal points and prove transcendence for all purely positive finite roots, for all two-term boundary roots paired by the mirror identity, and for all roots with one first negative layer and arbitrary finite positive support.

Abstract: This paper presents the Micro Video Guidance Sensor (UVGS-2), an advanced evolution of the Smartphone Video Guidance Sensor (SVGS), a vision-based 6-DOF pose estimation system for proximity operations in spacecraft, UAVs, and mobile robot platforms. The system is based on the photogrammetric estimation of a beacon’s relative position and attitude in a camera coordinate system, by processing images of illuminated 4-points in the beacon with known non-coplanar geometry. Estimation of the beacon’s 6-DOF position and attitude (XYZ, RPY) in a coordinate system attached to the camera is achieved with higher accuracy compared to standard localization methods based on mapping or inertial navigation. Image acquisition, feature extraction, and state estimation are executed using hardware resources (camera and CPU) of the host robot, resulting in a low-mass, low-power, computationally efficient sensing architecture suitable for embedded and resource-constrained systems. As case study, SVGS and UVGS-2 have been deployed as real-time guidance, navigation, and motion control sensor through integration with NASA’s Astrobee free-flying robot aboard the International Space Station (ISS), supporting autonomous proximity operations and formation flight. Sensor fusion based on the use of existing localization pipelines improves robustness against line-of-sight interruptions and illumination disturbances, and improves accuracy compared to the native Astrobee localization system (AstroLoc). Other case studies have demonstrated high-precision positioning performance in autonomous UAV landing experiments, with reliable target tracking over extended ranges and low angular estimation error, outperforming existing infrared-based landing approaches.

Abstract: Endophytic fungi are microorganisms that reside asymptomatically within healthy plant tissues and establish complex symbiotic relationships with their host plants. In recent years, these microorganisms have gained increasing attention due to their remarkable ability to produce diverse secondary metabolites with significant biological and pharmacological activities. Numerous studies have demonstrated that endophytic fungi isolated from medicinal plants can synthesize bioactive compounds exhibiting antioxidant, antimicrobial, antiviral, anti-inflammatory, antidiabetic, and anticancer properties. Interestingly, some endophytes are capable of producing metabolites structurally similar or identical to those found in their host plants, including taxol, camptothecin, and various phenolic compounds. Compared with conventional plant extraction, endophytic fungi offer several advantages such as rapid growth, sustainable production, reduced environmental impact, and the potential for large-scale fermentation. These characteristics make endophytes promising alternative sources of natural products for pharmaceutical, cosmetic, agricultural, and industrial applications. This review summarizes the biological characteristics of endophytic fungi, methods for isolation and identification, and the major classes of bioactive compounds derived from fungal endophytes, with emphasis on their pharmacological significance and future biotechnological potential.

Abstract: To address the issues of large temperature fluctuations, poor spatial perception, and low control robustness in traditional residential air conditioners, this paper proposes an adaptive temperature control algorithm based on millimeter-wave radar and a Light Gradient Boosting Machine (LGBM). Given that the bed is the primary obstacle and heat source in a bedroom, we develop a bed localization method using point cloud clustering. This method accurately identifies the bed position through time - window filtering, outlier removal, and density clustering. An LGBM weak teacher model, trained on massive cloud data, takes the bed position, indoor temperature, and compressor parameters as inputs to optimize air direction and fan speed, thereby effectively suppressing steady-state fluctuations in the return air temperature. Experiments on 719 real - world devices demonstrate that the bed positioning accuracy reaches 83.6% under an error tolerance of 0.5 m, the average absolute temperature fluctuation is reduced to 0.21◦C, and the control accuracy of the air guide mechanism exceeds 0.98. The proposed method requires no hardware modification, offers strong generalizability and low deployment cost, significantly improves temperature stability and thermal comfort in bedroom environments, and provides a feasible technical solution for intelligent residential air conditioning control.

Abstract: Large language model (LLM) agents are increasingly expected to solve long-horizon tasks through repeated interaction with external environments, tools, users, and other agents. In this setting, agent skills have emerged as a central mechanism for transforming fragmented experience into reusable procedural knowledge. Unlike raw memory which preserves past traces, or abstract rules which often lack executable detail, skills compress recurring patterns of successful behavior into operational artifacts that can guide future action. However, existing studies on agent skills remain scattered across diverse areas, making it difficult to form a unified understanding of what skills are, how they are represented, and how they should be governed. To bridge this gap, this paper presents a comprehensive survey of agent skills. We propose a six-layer taxonomy covering ontology, representation and packaging, lifecycle, runtime integration, governance, and applications. We first define agent skills as reusable procedural abstractions that connect memory, human expertise, and execution. We then review major skill representations, including natural-language guidance, executable code snippets, decision graphs, filesystem-based packages, and structured skill records. Next, we analyze the skill lifecycle, from acquisition, storage, retrieval, usage, and maintenance to selective internalization into model behavior. We further examine how skills integrate with terminal interfaces, tool interfaces, multi-agent systems, and agent harnesses. In addition, we discuss the emerging skill ecosystem, its security and governance risks, and mechanisms for trusted deployment. Finally, we survey applications in robotics, games, web agents, GUI/mobile/OS agents, and software engineering, and identify open challenges in evaluation, robustness, standardization, safety, and infrastructure. Related resources, as well as the latest developments in this field, are accessible on https://github.com/DataArcTech/Awesome-Agent-Skill-Papers.

Abstract: Background/Objectives: This study evaluates the adaptation of a novel filling material (Odne®Fill, Switzerland) to the walls of the shaped root canal using micro-computed tomography. Methods: Fourteen extracted human molars (6 maxillary and 8 mandibular), comprising a total of 32 root canals, were included. After canal preparation, all canals were filled with Odne®Fill according to the manufacturer’s instructions. Periapical radiographs and micro-computed tomography were used to assess the extent of canal wall coverage by the filling material. Surface coverage was quantified by image segmentation and statistically analyzed. Results: The percentage of canal wall coverage ranged from 93.31% to 99.98%. The mean coverage rate was 97.63% (SD 1.70%) and the median was 98.23%, indicating a high degree of adaptation of the filling material to the ex vivo prepared canal walls. Conclusions: Under the conditions of this ex vivo study Odne®Fill demonstrated high canal wall adaptation values. These findings should be interpreted with caution and further com-parative and long-term studies are required before clinical relevance can be established.

Abstract: This article advances a systematic theological diagnosis of the contemporary crisis in Christian thought, contending that dominant modes of theologizing have become epistemically, politically, and spiritually toxic. Beginning with a critical analysis of the habitus of theologization, it demonstrates how inherited theological dispositions reproduce and normalize forms of violence embedded within colonial, cisheteropatriarchal, and necropolitical regimes. The study then interrogates the proliferation of theological narratives of terror and the corrosive effects of decent, docile, and obedient theologies that legitimize exclusion, dehumanization, and imperial projects—most starkly exemplified in the deployment of theological discourses to rationalize the ongoing genocide in Palestine and the systematic marginalization of queer/cuir/maricas, trans, and gender-nonconforming bodies. Against this backdrop, the article proposes two liberative antidotes. The first is Palestinian Liberation Theologies (PLT), which reclaim theological imagination through situated resistance, political commitment, and forms of spiritual endurance. The second emerges from Latin American Liberation Theology (LLT), as reconfigured through queer/cuir/marica dissident experiences, whose embodied, indecent, and decolonial imaginaries disrupt regimes of theological purity and open pathways for insurgent, life-affirming practices. Taken together, these antitoxic interventions articulate a decolonial and emancipatory horizon for theology—one grounded in relationality, insurgent imagination, and activist commitment. In this sense, theological detoxification is not merely a critical task but an indispensable condition for envisioning alternative worlds amid ongoing civilizational collapse.

Abstract: Background: Early childhood caries remains a major public health burden in Thailand, particularly among preschool children, despite the implementation of national oral health policies. With the decentralization of child development centers (CDCs) to local adminis-trative organizations (LAOs), understanding system-level determinants of oral health ser-vice effectiveness has become critical. This study aimed to identify key determinants in-fluencing the effectiveness of oral health care systems for preschool children within CDCs in northeastern Thailand. Methods: A cross-sectional analytical study was conducted among 270 stakeholders across urban, peri-urban, and rural CDCs in Ubon Ratchathani Province. Participants were selected using multi-stage random sampling. Data were col-lected between November 2023 and January 2024 using a structured questionnaire with established content validity (IOC > 0.50) and reliability (Cronbach’s alpha = 0.71–0.77). Variables were organized within an Input–Process–Output (IPO) framework. Descriptive statistics, Pearson’s correlation, and multiple linear regression analyses were performed to identify significant predictors of system effectiveness. Results: The oral health care system demonstrated strong performance in preventive service delivery, including universal oral health examinations and fluoride varnish application (100%), and high personnel readi-ness (99.63%). However, critical gaps were identified in monitoring and evaluation sys-tems (8.15%), budget adequacy (60.37%), and continuity of treatment follow-up (48.89%). The prevalence of dental caries among preschool children was 57.83%. Multiple regression analysis revealed that service delivery processes (β = 0.458, p < 0.001) and home visits by public health and dental personnel (β = 0.303, p = 0.008) were significant determinants of system effectiveness, jointly explaining 11.1% of the variance (R² = 0.111). Conclusions: The effectiveness of preschool oral health care systems in decentralized settings is driven pri-marily by the quality of service delivery processes and the integration of proactive commu-nity outreach through home visits. Strengthening monitoring and evaluation mechanisms, ensuring sustainable financing, and enhancing continuity of care between CDCs and households are essential for improving oral health outcomes. These findings provide ac-tionable evidence for policymakers and local health administrators seeking to optimize oral health systems under decentralized governance structures.

Abstract: Disputes over change orders on construction projects often arise due to varying interpretations and priorities of the key stakeholders, namely the owners, designer and contractor. This problem is particularly evident in the flourishing construction sector of the Kingdom of Saudi Arabia due to the delay of large-scale projects. A significant reason for these delays is huge claims on changes orders and traditional means of resolution such as litigation and arbitration are not able to yield timely resolutions. These challenges highlight the need to better manage and assess the impacts of change in a more proactive manner. This research proposes the BIM-based framework which offers the solution to the above-mentioned challenges through the creation of the Integrated Virtual Environment. The setup involves linking Revit for 3D modelling with Navisworks for coordination and visualization, and Primavera for scheduling and cost control into a seamless network. This link allows project information to be displayed in an orderly manner. Furthermore, any changes in design will be connected to the effect on time and cost. In this virtual environment, the framework aims to capture and visualize the effects of change orders in terms of schedule delays and cost overruns. This approach helps the stakeholders to trace how the changes are spreading in different dimensions of the project providing a clearer and common understanding of what changes those will bring. Having more light helps with better conversations, helps with discussions at the start, and helps avoid claims. The overall findings suggest that the combined use of BIM and project management tools may create a consistent virtual platform for the analysis of change orders and their impacts on time and cost. Through a real case study, the framework is developed and validated to showcase its practical capability of aiding decision-making, reducing disputes, and improving overall project performance. The effective management of change is vital in minimizing delays and facilitating better project delivery, especially in the fast-growing construction industry of Saudi Arabia.

Abstract: This study examines the phenomenon of pseudoconfident knowledge in the context of the everyday use of generative artificial intelligence. By pseudoconfident knowledge, we mean a response that is substantively plausible, rhetorically coherent, and outwardly persuasive but is treated and understood as knowledge before its actual reliability has been established. Of course, we do not use the term “pseudoconfident knowledge” to denote knowledge in the strict epistemological sense. Rather, it denotes a special form of AI-generated content that acquires the status of knowledge in the user’s perception before its reliability, source-based justification, or factual correctness have been established. The problem here is not that such an answer is already knowledge but that it is prematurely accepted as knowledge because of its coherence, completeness, and rhetorical confidence. The aim of the study is to identify the epistemic gap between the everyday operational integration of artificial intelligence and the user’s critical ability to distinguish between persuasiveness and justification. The theoretical framework combines approaches to AI literacy, epistemic vigilance, and contemporary forms of digital mediation in the circulation of knowledge. The empirical basis of the study is an online survey of AI users. The analysis was conducted using descriptive statistics, contingency tables, and methods for testing associations between categorical variables. The results show that the key differentiating factor is not the frequency of AI use but the strategy used in handling its responses. More epistemically robust positions are associated with practices of comparison, editing, and verification, whereas uncritical acceptance of the answer is associated with greater vulnerability to pseudoconfident knowledge. We conclude that the spread of generative artificial intelligence is producing a new socioepistemic problem that calls for a shift in emphasis from simple instrumental literacy toward a culture of verification, doubt, and epistemic responsibility.

Abstract: Glass-ceramic foams (BVZ: bottle glass waste–zirconia residue–bentonite) were produced using the polymeric replica method from low-cost raw materials, comprising approximately 85 wt% bottle glass waste and zirconia residue, and 15 wt% regional bentonite. To evaluate the effect of zirconia residue on the microstructure and physicochemical properties of the BVZ foams, aqueous precursor suspensions were prepared with varying proportions of bottle glass waste (59.7–69.7 wt%) and zirconia residue (14.9–19.9 wt%), and sintered at 750 °C, 800 °C, and 850 °C. X-ray diffraction (XRD) analysis revealed a reduction of the amorphous halo (15–35° 2θ) and an increase in crystallinity with increasing temperature, indicating devitrification of the glassy matrix. The main crystalline phases identified were zircon (ZrSiO₄), nepheline (NaAlSiO₄), AlPO₄, and zirconia (ZrO₂), with evidence of minor domains structurally compatible with NASICON-type phases (NaZr₂(PO₄)₃). In general, glass-ceramic foams produced with high waste content showed greater densification and reduced porosity at 850 °C. The mechanical strength was sufficient for handling and assembly in electrochemical cell components, while the reduced brittleness supports safe processing and indicates potential for scalable manufacturing.

Abstract: The mathematization of science is undergoing a structural transformation driven by the rise of computation and data-intensive methods. While classical mathematization relied on explicitly defined laws and formal structures, contemporary scientific practice increasingly encounters mathematical objects that arise as outcomes of dynamical and algorithmic processes. This paper introduces the notion of {\emph computationally emergent structures} to describe entities generated and stabilized through the interaction of parameterized models, optimization dynamics, and data. We develop a minimal formal framework in which such structures are characterized as asymptotic outcomes of learning dynamics and show that, in over parameterized regimes, they are selected by implicit variational principles not specified a priori. This framework provides a unified account of implicit regularization, kernel regimes, and stability phenomena in modern learning systems. These results show that contemporary learning systems operate according to implicit variational principles in which geometry, dynamics, and data jointly determine effective mathematical structure. They thereby identify a shift from representation to dynamical emergence, extending the scope of mathematization toward a theory of structure formation grounded in computation.

Abstract: Climate change is placing global agriculture under growing pressure, as plants must withstand extreme environmental conditions such as drought and high salinity, both inducing osmotic and oxidative stress. As part of their survival strategies, plants accumulate protective molecules (osmolytes), including the amino acid proline. For decades, plant biology has largely assumed that high proline accumulation under stress signals strong stress tolerance. However, this review challenges that “proline-centric” perspective. Analyses across a wide range of plant species reveal a more complex picture. Stress-induced proline accumulation is not universal: in some species, proline levels remain relatively unchanged, with other metabolites acting as functional osmolytes, or increase only in response to artificially applied severe stress conditions. Even when proline increases, its absolute concentrations may be too low to contribute significantly to osmotic adjustment. Nevertheless, proline may still be involved in stress tolerance mechanisms through its additional roles, detoxifying reactive oxygen species (ROS), directly stabilising proteins or acting as a stress signalling molecule. Comparative analyses of genetically related taxa with varying degrees of stress tolerance sometimes show negative correlations between proline accumulation and tolerance, with higher proline concentrations measured in the most sensitive genotypes. Overall, the evidence indicates that proline’s role in plant survival is highly context-dependent and strongly influenced by genetic background and must therefore be evaluated on a case-by-case basis. Distinguishing whether proline acts as an adaptive defence or merely as a biochemical marker of physiological strain is essential for accurately assessing plant stress tolerance.

Abstract: Background: Seasonal influenza prevention in young adults is influenced by access, trust, and vaccine information exposure, but local evidence linking vaccination uptake with illness and economic burden is limited. Methods: We conducted a cross-sectional electronic survey of adults aged 18-49 years who lived, worked, or studied in the San Francisco Bay Area during the 2025 to 2026 influenza season. Measures included vaccination uptake, influenza-like illness, recovery, functional and economic burden, vaccination sites, and vaccine information exposure. Multivariable logistic regression examined factors associated with vaccination uptake; Kaplan-Meier and Cox models examined time to recovery. Results: Of 554 responses, 463 were included. Vaccination uptake was 86.2% (n=399; 95% confidence interval [CI], 82.7%-89.2%), and 38.4% reported influenza-like illness. Among those with illness, median recovery time was 5 days, median missed work or school was 2 days, and median direct out-of-pocket cost was US$20. Prior season vaccination (adjusted odds ratio [aOR], 2.24; 95% CI, 1.15-4.34) and greater trust in Centers for Disease Control and Prevention or public health agencies (aOR, 1.46; 95% CI, 1.05-2.02) were associated with vaccination. Pharmacies were the second most common vaccination site and preferred future site. Conclusion: Influenza prevention for young adults may benefit from pharmacy-inclusive, multichannel access paired with trusted communication.

Abstract: In resource-constrained settings, structural and material inequalities shape children’s developmental opportunities, yet developmental pathways remain diverse even within shared hardship. This study examined developmental continuity and variation in cognitive trajectories among children born in adversity and assessed whether maternal structural positioning and household material conditions were associated with developmental progression. Data were drawn from 742 children born to adolescent mothers in the large longitudinal cohort in the Eastern Cape, South Africa. Cognitive functioning was assessed using the Mullen Scales of Early Learning (MSEL) at baseline and the Kaufman Assessment Battery for Children (KABC-II) at follow-up. Baseline functioning predicted later cognitive placement, indicating developmental continuity (B = 0.074, SE = 0.030, p = .015). Lower maternal educational attainment was associated with more constrained developmental progression (B = −0.097, SE = 0.023, p < .001), and maternal not in education, employment, or training (NEET) status also predicted constrained trajectories (B = −0.200, SE = 0.049, p < .001). In contrast, consistent access to basic household necessities was associated with more favourable developmental trajectories (B = 0.024, SE = 0.009, p = .012). These findings indicate that variation in children’s developmental trajectories reflects differences in structural positioning and household material conditions. Supporting adolescent mothers’ engagement in education and access to stable resources may represent an important pathway for improving child developmental outcomes.

Abstract: Neuroinflammation, driven by microglial activation and oxidative stress, is a key pathological feature of various neurodegenerative diseases. Dendropanax morbifera Léveille (DM) is a medicinal plant known for its diverse pharmacological activities; how-ever, the influence of leaf developmental stage on its neuroprotective potential remains poorly understood. In this study, we compared the phytochemical profiles of young DM (YDM) and mature DM leaves and evaluated their effects on neuronal metabolism and microglia-mediated neuroinflammation. HPLC analysis revealed that YDM contained approximately 2.4-fold higher levels of chlorogenic acid than DM, while DM exhibited higher quercetin content. In differentiated N2A neuronal cells, YDM treatment significantly upregulated the expression of key metabolic and mitochondrial regulators, including PGC-1α, PPARγ, and CPT2, suggesting an enhanced capacity for mitochondrial biogenesis and fatty acid β-oxidation. Under inflammatory conditions, YDM more potently suppressed the secretion of pro-inflammatory cytokines (IL-6 and TNF-α) in LPS-stimulated BV2 microglia compared to DM. Further-more, in N2A cells treated with a BV2–conditioned medium, both extracts effectively mitigated reactive oxygen species production and restored brain-derived neurotrophic factor expression. These findings demonstrate that leaf age is a critical determinant of the phytochemical composition and biological activity of DM. Our results suggest that chlorogenic acid-rich YDM preparations may offer superior therapeutic advantages in targeting neuroinflammatory and metabolic dysregulation in the central nervous system.

Abstract: Entanglement swapping can connect segmented quantum channels to form long-distance quantum channels, which is a key mechanism for realizing large-scale quantum networks and remote quantum communication. In this paper, we show the basic principles of entanglement swapping and propose a new calculation method to derive entanglement swapping results, which is demonstrated through the entanglement swapping between two bipartite entangled states. In addition, we propose an infinitely scalable star-shaped quantum network, which is composed of quantum computers connected through quantum channels. These computers interact with an observable universe: obtaining observational information from it and automatically providing feedback after processing the information.

Abstract: Dirty paper coding (DPC) is applied to linear multi-input multi-output (MIMO) broadcast channels with additive white Gaussian noise and one message per receiver. The method decomposes each receiver channel into parallel scalar channels with known interference, then applies modulo operators, amplitude-shift keying (ASK), and probabilistic shaping. The achievable rate tuples include all points inside the capacity region by choosing truncated Gaussian shaping, large ASK alphabets, and large modulo intervals. Simulations with short polar codes show significant rate gains from DPC compared to conventional linear precoding, while maintaining similar encoder and decoder complexities.

Abstract: Generative artificial intelligence is increasingly embedded in recursive informational ecosystems in which outputs are produced, published, retrieved, summarized, copied and pasted into new human or machine production. This paper proposes a preliminary predictive framework for Dissipative Semantic Homogenization (DSH), a possible re-gime in which recursive generative AI ecosystems dissipate physical energy while corpus-level semantic diversity contracts and saturates. The framework does not iden-tify thermodynamic entropy with semantic entropy. Instead, it treats them as opera-tionally coupled variables: semantic distributions are transformed by physically im-plemented computation, while energy dissipation provides a macroscopic cost proxy. We model semantic diversity as Shannon entropy over a corpus-level partition of se-mantic states and introduce modal amplification, independent novelty injection, and AI assimilation of nominally human production as control variables. The model yields empirically testable implications: semantic contraction should occur only when effec-tive independent novelty falls below a stability threshold; contraction should be scale-dependent; and cumulative semantic loss should saturate even while physical entropy production continues. The framework is not presented as an empirical law, but as a testable theoretical model for future longitudinal and controlled studies.

Abstract: Flash drought, as a rapidly developing form of drought, has become an increasing threat to agricultural production, ecosystem stability, and regional carbon cycling, par-ticularly in croplands within monsoon regions. Existing studies have mainly focused on point-scale identification or conventional vegetation indices, while a systematic understanding of the regional spatiotemporal evolution of flash droughts and crop-specific differences in photosynthetic recovery remains limited. Using mul-ti-source remote sensing data from the North China Plain and the Middle-Lower Yangtze Plain during 2001–2024, this study integrated triple collocation error assess-ment, root-zone soil moisture percentile-based identification, connected component tracking, and Random Forest–SHAP analysis to characterize flash drought trajectories and their impacts on vegetation. The results showed that the southern Middle-Lower Yangtze Plain exhibited a high-frequency but low-intensity pattern, whereas the cen-tral North China Plain was characterized by relatively low frequency but higher inten-sity and longer duration. Rice-based systems were more vulnerable to frequent flash drought shocks, while rainfed and rotation systems faced stronger cumulative risks. Solar-induced chlorophyll fluorescence (SIF) responded to flash droughts 6–9 days ear-lier than gross primary productivity (GPP), and all cropping systems exhibited a “rapid physiological response–lagged carbon assimilation recovery” pattern. The month of occurrence, drought duration, and decline rate were identified as the dominant factors controlling photosynthetic recovery. These findings extend the flash drought monitor-ing framework from the perspectives of regional connectivity and crop recovery mechanisms, and provide a remote sensing-based scientific basis for agricultural early warning, drought mitigation, and food security management.