Search Results (221)

This exploratory proof-of-concept study investigated the simultaneous deployment of autonomous, persona-driven Artificial Intelligence (AI) agents across multiple social media platforms using the ElizaOS framework. We developed three platform-specific agents with seven-layer character architectures and deployed them on Twitter/X, Discord, and Telegram for 18 days. The system processed 5389 interactions while gathering feedback from 28 volunteer participants. Addressing three research questions, we found that: (1) automation effectiveness was platform-dependent, with direct support platforms (Telegram, Discord) rated more useful than broadcast-oriented Twitter/X; (2) character design impact depended primarily on platform-persona alignment rather than architectural sophistication; and (3) technical performance showed platform-specific patterns, with median storage times ranging from 9.0 milliseconds (Twitter/X) to 61.5 milliseconds (Telegram) and high variability across all platforms. A notable finding was what we term the “Discord Paradox”—high quality ratings (4.05/5) but lowest preference (8.7%), suggesting platform familiarity and accessibility influence adoption more than agent quality. While the deployment demonstrated technical feasibility and revealed distinct user dynamics across platforms, the findings indicate that platform-specific optimization may be more effective than universal approaches. This exploratory study advances understanding of multi-platform agent deployment for marketing automation, identifying behavioral patterns and platform-specific dynamics that offer testable hypotheses for future systematic research. Full article

Within the ongoing scientific and disciplinary debate on the interplay between climate change and land-use governance, this paper highlights the critical role of urban planning and design in shaping environmental regeneration strategies for coastal urban areas vulnerable to flooding phenomena. These flood events—driven by the combined effects of sea-level rise (SLR) and riverine flood—represent one of the key challenges facing the “global risk society” given their increasing impact on urban areas and the tangible economic, social, and environmental damages they produce. In this context, this paper presents selected outcomes from the findings of the research project “Climate-proof planning and regeneration strategies for adaptation to sea-level rise. Experimentation and innovation in local urban planning in at-risk areas of the Lazio region”, conducted at Sapienza University of Rome. The project focuses on research and experimental planning in coastal areas of Lazio identified as being at risk of SLR-related flooding by 2100. It aims to define theoretical–methodological and operational references for urban regeneration with an ecosystemic approach within the framework of so-called climate-proof planning. This study examines three macro-areas, further subdivided into seven distinct sites, categorized by their prevailing urban functions. For each site, following a preliminary assessment of flood-prone zones, tailored design actions are proposed. These actions are framed within three overarching of urban resilience strategies, developed in previous research by the authors: “defence”, “adaptation”, and “relocation”. Full article

Objectives: To develop a proof-of-concept machine learning (ML) neural network model to predict post-operative visual outcomes in children with congenital cataracts undergoing intraocular lens (IOL) implantation, thereby guiding the optimal timing for IOL insertion. Determining the ideal timing and predicting outcomes for IOL implantation in children remains clinically complex due to variability in eye development and measurement accuracy. Methods: Retrospective analysis using a publicly available dataset from 110 children diagnosed with congenital cataracts, who underwent IOL implantation at the Eye and ENT Hospital of Fudan University. A neural network model with a hidden layer of 10 nodes was developed in MATLAB 2024a using the scaled conjugate gradient algorithm. Input variables included demographic and clinical features; the target was achieving visual acuity greater than 20/40. Performance metrics were evaluated using cross-entropy loss, sensitivity, specificity, and accuracy. Results: Training completed after 14 epochs with the test set reaching the highest performance metrics: 88.2% accuracy, 88.9% sensitivity, and 87.5% specificity. ROC curve analysis showed AUC values of 0.942 (training), 0.920 (validation), 0.885 (test), and 0.917 (overall). Conclusions: The neural network effectively predicted post-operative visual outcomes, offering potential clinical utility in guiding IOL implantation decisions. Despite limitations in dataset diversity, this study lays the foundation for future development of personalized strategies in pediatric cataract care. Full article

This study establishes quantitative relationships between neighborhood layouts, as evaluated by key neighborhood morphological parameters and pedestrian wind environments across China’s five major climate zones. We analyzed 3204 residential neighborhoods using satellite imaging and simulated 281 scenarios by CFD simulations, identifying six typical neighborhood layouts and quantifying their performance in terms of climate specific wind comfort criteria. This work takes an approach that takes into account mechanical wind effects and region-specific criteria for evaluating pedestrian-level wind environment performance, going beyond previous studies that utilize universal evaluation standards. The most influential parameter is building enclosure ratio with sensitivity indices of 0.844 for winter wind proofing. Closed perimeter layout confers 15–20% better winter wind proofing in cold climates and semi-open design enhances summer ventilation by 12–18% in hot climates according to our cross-climate analysis. Quantitative optimization adopting regression technique (R² = 0.727–0.810) points to an optimal enclosure ratio of 0.25–0.28 or 0.52–0.61 with aspect ratio of 1.75–2.75. The results can provide evidence-based design guidelines for high-rise residential neighborhood planning and pedestrian wind environment, aiming to improve urban livability and support climate adaptation strategies across a broad range of climate zones. Full article

Background/Objectives: Clozapine remains the gold standard for treatment-resistant schizophrenia. However, its narrow therapeutic window and risk of severe side effects require close monitoring of both clozapine and its primary metabolite, norclozapine. Existing therapeutic drug monitoring (TDM) methods are limited by delays, high costs, and operational complexity. This study introduces three rapid point-of-care (POC) assays utilizing a miniature mass spectrometer (Mini-MS) to quantify clozapine and norclozapine in plasma, whole blood, and dried blood spots (DBSs), facilitating applications across diverse clinical settings. Methods: The analytical performance of the assay was evaluated for sensitivity, specificity, reproducibility, and correlation with reference methods. Clinical samples from two hospitals were analysed and validated against conventional liquid chromatography tandem mass spectrometry (LC-MS/MS) reference standards at New South Wales Health Pathology (NSWHP) and Tsinghua University laboratories. Results: The Mini-MS assay accurately quantified both analytes within therapeutic ranges across all matrices. Inter-assay coefficients of variation ranged from 7.9 to 14.1% for clozapine and from 1.6 to 14.6% for norclozapine. Accuracy fell between 85 and 117% in plasma and blood extracts. Strong linearity was demonstrated (R² = 0.98–0.99) over the concentration range of 10–1000 ng/mL. Results from the Mini-MS analysis showed excellent correlations with LC-MS/MS results (r = 0.998). Conclusions: In this proof-of-concept study, the Mini-MS-based POC assays enable rapid, reliable quantification of clozapine and norclozapine, with performance comparable to conventional laboratory methods. This platform supports real-time TDM, facilitating timely dose adjustments, adherence monitoring, and ultimately improving patient outcomes. Full article

This article presents a compact tip-tilting platform designed for hardware-in-the-loop emulation of spacecraft relative dynamics and a physical setup for testing tethered systems. The architecture consists of a granite slab supported by a universal joint and two linear actuators to control its orientation. This configuration allows a Floating Spacecraft Simulator to move on the surface in a quasi-frictionless environment under the effect of gravitational acceleration. The architecture includes a dedicated setup to emulate tethered satellite dynamics, providing continuous feedback on the tension along the tether through a mono-axial load cell. By adopting the Buckingham “$\pi$” theorem, the dynamic similarity is introduced for the ground-based experiment to reproduce the orbital dynamics. Proof-of-concept results demonstrate the testbed’s capability to accurately reproduce the Hill–Clohessy–Wiltshire equations. Moreover, the results of the deployed tethered system dynamics are presented. This paper also details the system architecture of the testbed and the methodologies employed during the experimental campaign. Full article

Modern distributed computing systems and applications with strict privacy requirements demand robust data confidentiality. A primary challenge involves enabling parties to exchange data or perform joint computations. These interactions must avoid revealing private information about the data. Protocols with the obliviousness property, known as oblivious protocols, address this issue. They ensure that no party learns more than necessary. This survey analyzes the security and performance of post-quantum oblivious protocols, with a focus on oblivious transfer and oblivious pseudorandom functions. The evaluation assesses resilience against malicious adversaries in the Universal Composability framework. Efficiency is quantified through communication and computational overhead. It identifies optimal scenarios for these protocols. This paper also surveys related primitives, such as oblivious signatures and data structures, along with their applications. Key findings highlight the inherent trade-offs between computational cost and communication complexity in post-quantum oblivious constructions. Open challenges and future research directions are outlined. Emphasis is placed on quantum-resistant designs and formal security proofs in stronger adversarial models. Full article

In a world of rapidly globalizing food markets, biodiversity, authenticity, and the safety of food products have become a universal concern. DNA barcoding is a widely used molecular-based method that can identify biological material and is used for the traceability of both raw materials and ingredients in processed food. In the present study, contacted within the framework of the BioValue Horizon Project, which promotes the role of agrobiodiversity in sustainable food systems, DNA barcoding using the ITS and rbcL markers was employed as a proof-of-concept approach to reveal the biodiversity and authenticity of ten commercial plant-based products. Following successful DNA amplification and sequencing using six products as a proof-of-concept, a diverse range of plant genera and species were identified, verifying biodiversity. A strong correlation between ITS and rbcL-based markers was demonstrated, supporting their combined use for reliable species-level biodiversity assessment. Finally, heat map analysis of label contents and sequencing-based genera identification confirmed high concordance between label claims and sequencing results in most cases, though undeclared species and absent labeled taxa were also detected, highlighting potential mislabeling or cross-contamination. Full article

Traceable ring signatures (TRSs) allow a signer to create a signature that maintains anonymity while enabling traceability if needed. It merges the characteristics of traditional ring signatures with the ability to trace signers, making it ideal for applications that demand both confidentiality and accountability. In a TRS scheme, a ring of potential signers generates a signature on a message without disclosing the actual signer’s identity. However, the identity can be traced if the signer uses the same tag for multiple signatures. This paper introduces a novel formal construction of TRS under universally composable (UC) security. We integrate verifiable random functions (VRFs) and zero-knowledge proofs for membership, employing Pedersen commitments. Our signature schemes maintain a logarithmic size while preserving the UC security guarantees. Additionally, we explore the potential to extend the property of one-time anonymity in TRS to K-time anonymity. Full article

Introduction: Oral squamous cell carcinoma (OSCC) is one of the most common tumours worldwide. This study investigated the suitability of visible and near-infrared hyperspectral imaging compared to visual assessment and conventional digital image analysis for quantifying immunohistochemical staining on the example of Dickkopf-3 (DKK-3) in OSCC. Materials and methods: A retrospective analysis of TMAs containing DKK-3 stained OSCC of 50 patients was retrieved from the archives at the Institute of Pathology, Medical University of Innsbruck. TMAs were first evaluated visually, followed by digital image analysis using QuPath (version 0.3.2, open-source software). For hyperspectral imaging, six exemplary cases were selected (three cases with strong expression and three cases with weak expression) and evaluated. The collected hyperspectral images were visualised using TIVITA (Tissue Imaging System). The resulting true-colour images and the classified HSI images were then assessed using the QuPath software. The Allred score and the H-score were used for all analyses. Results: 97 tissue cores were used for visual and digital image analysis. No significant difference was found between the evaluations of visual and digital image analysis using the H-score (pWilcoxon = 0.278), and both H-scores correlated significantly with each other (p^Spearman < 0.001). Similar results were also found using the Allred score. The kappa value was 0.67, which represents a “substantial” correlation. Finally, the H-scores and Allred scores were compared for visual, digital, and HSI imaging. No significant differences were found between the three groups concerning the H-score (pWilcoxon > 0.1). Using Cohen’s Kappa, a “fair” to “moderate” correlation was observed between the three evaluations. Conclusion: Visible and near-infrared hyperspectral imaging (VIS-NIR-HSI) is a promising complementary tool for digital pathology workflows. This proof-of-concept study suggests that HSI offers the potential for more objective quantification of DKK-3 expression in oropharyngeal squamous cell carcinoma, particularly in cases with weak staining. However, given the small sample size and exploratory design, the findings should be regarded as hypothesis-generating. Future studies with larger, clinically annotated cohorts and standardised workflows are needed before any consideration of routine clinical application. Full article

This paper investigates the structural properties of solutions of vector equilibrium systems and mixed variational inequalities in topological vector spaces. Based on Himmelberg-type fixed point theorem, combined with the analysis of set-valued mapping and quasi-monotone conditions, the existence criteria of solutions for two classes of generalized equilibrium problems with weak compactness constraints are constructed. This work introduces an innovative application of the measurable selection theorem of semi-continuous function space to eliminate the traditional compactness constraints, and provides a more universal theoretical framework for game theory and the economic equilibrium model. In the analysis of mixed variational problems, the topological stability of the solution set under the action of generalized monotone mappings is revealed by constructing a new KKM class of mappings and introducing the theory of pseudomonotone operators. In particular, by replacing the classical compactness assumption with pseudo-compactness, this study successfully extends the research boundary of scholars on variational inequalities, and its innovations are mainly reflected in the following aspects: (1) constructing a weak convergence analysis framework applicable to locally convex topological vector spaces, (2) optimizing the monotonicity constraint of mappings by introducing a semi-continuous asymmetric condition, and (3) in the proof of the nonemptiness of the solution set, the approximation technique based on the family of relatively nearest neighbor fields is developed. The results not only improve the theoretical system of variational analysis, but also provide a new mathematical tool for the non-compact parameter space analysis of economic equilibrium models and engineering optimization problems. This work presents a novel combination of measurable selection theory and pseudomonotone operator theory to handle non-compact constraints, advancing the theoretical framework for economic equilibrium analysis. Full article

The aim of this work was to construct explicit expressions for the summation of Dirichlet Beta functions with odd arguments and Zeta functions with even arguments. In the established literature, this is typically done using Fourier series expansions or Bernoulli numbers and polynomials. Here, instead, we achieve our goal by employing tools from probability: specifically, we introduce a generalisation of a technique based on multiple integrals and the algebra of random variables. This also allows us to increase the number of nested integrals and Cauchy random variables involved. Another key contribution is that, by generalising the exponent of Cauchy random variables, we obtain an original proof of the reflection formulae for the Digamma and Trigamma functions. These probabilistic proofs crucially utilise the Mellin transform to compute the integrals needed to determine probability density functions. It is noteworthy that, while understanding the presented topic requires knowledge of the rules for calculating multiple integrals (Fubini’s Theorem) and the algebra of continuous random variables, these are concepts commonly acquired by second-year university students in STEM disciplines. Our study thus offers new perspectives on how the mathematical functions considered relate and shows the significant role of probabilistic methods in promoting comprehension of this research area, in a way accessible to a broad and non-specialist audience. Full article

Background/Objectives: Nerve injuries cause functional loss and psychosocial issues due to prolonged rehabilitation. Recently, 3D-modeled nerve conduits have been used to aid in surgical planning. This study investigated the impact of 3D-bioprinted PLA, chitosan, alginate, and collagen conduits on nerve regeneration in a rat sciatic nerve crush injury model. Methods: This study, conducted at Kütahya University of Health Sciences, involves 50 rats were divided into four groups: (1) sham-operated controls, (2) sciatic nerve injury without treatment, (3) injury treated with a PLA conduit, and (4) injury treated with 3D-printed tubes composed of chitosan and alginate. The procedures were performed, blood was collected, and the rats were sacrificed after two months. Weekly checks for infection, scar healing, and motor responses were performed. Results: Rats with nerve conduits showed less macroscopic scarring. Weekly assessments of motor nerve recovery showed no movement restrictions in limbs treated with PLA conduits, graft conduits, or conduits bridging retracted nerve stumps, based on responses to stimulus checks. An infection developed in the sciatic nerve and surrounding muscle tissue of one rat with a bio-graft conduit, prompting histopathological examination to investigate its cause. Conclusions: This proof-of-principle study demonstrates the feasibility of using 3D-printed biocompatible nerve conduits for peripheral nerve repair, providing a basis for future, more comprehensive investigations. Full article

This paper proposes a technological framework designed to mitigate the inherent risks associated with the deployment of artificial intelligence (AI) in decision-making and task execution within the management processes. The Agreement Validation Interface (AVI) functions as a modular Application Programming Interface (API) Gateway positioned between user applications and LLMs. This gateway architecture is designed to be LLM-agnostic, meaning it can operate with various underlying LLMs without requiring specific modifications for each model. This universality is achieved by standardizing the interface for requests and responses and applying a consistent set of validation and enhancement processes irrespective of the chosen LLM provider, thus offering a consistent governance layer across a diverse LLM ecosystem. AVI facilitates the orchestration of multiple AI subcomponents for input–output validation, response evaluation, and contextual reasoning, thereby enabling real-time, bidirectional filtering of user interactions. A proof-of-concept (PoC) implementation of AVI was developed and rigorously evaluated using industry-standard benchmarks. The system was tested for its effectiveness in mitigating adversarial prompts, reducing toxic outputs, detecting personally identifiable information (PII), and enhancing factual consistency. The results demonstrated that AVI reduced successful fast injection attacks by 82%, decreased toxic content generation by 75%, and achieved high PII detection performance (F1-score ≈ 0.95). Furthermore, the contextual reasoning module significantly improved the neutrality and factual validity of model outputs. Although the integration of AVI introduced a moderate increase in latency, the overall framework effectively enhanced the reliability, safety, and interpretability of LLM-driven applications. AVI provides a scalable and adaptable architectural template for the responsible deployment of generative AI in high-stakes domains such as finance, healthcare, and education, promoting safer and more ethical use of AI technologies. Full article

Background/Objectives: Intermittent pneumatic impulse compression (IIC) is a well-established drainage treatment that reduces edema and enhances arterial blood flow. While widely utilized in various medical fields, its efficacy in dermatology, particularly for stasis dermatitis, remains underexplored. This study evaluates the effectiveness of IIC in inpatients with bilateral stasis dermatitis by comparing standard therapy alone versus standard therapy with additional IIC on one leg over five days. Methods: Seventeen patients from the Dermatology Department at University Hospital Duesseldorf were enrolled. Both legs received standard therapy, while one randomized leg received additional IIC for four hours daily. Measurements, including transcutaneous oxygen pressure (tcpO₂), leg circumference, and pain sensation, were taken at baseline, the first day post-IIC, and after five days. Statistical analysis included paired t-tests, with significance set at p < 0.05. Results: The IIC-treated legs exhibited significant improvements in tissue oxygen saturation (MD = 19.87 mmHg, SD = 27.82, p = 0.012) and reduced ankle circumference (MD = −2.125 cm, SD = 1.593, p < 0.0001). No significant changes were observed in tcpO₂ or circumference in the non-IIC-treated legs. Other leg circumference measurements (calf, above the knee) did not demonstrate significant improvements in either group. Pain levels remained stable under IIC therapy. Conclusions: This proof-of-concept study provides evidence supporting IIC as a beneficial adjunct therapy for stasis dermatitis, demonstrating significant edema reduction and enhanced oxygenation. Further investigations are warranted to confirm these findings and expand clinical applicability. Full article