Search Results (32,855)

The increasing use of AI systems for face, object, action, scene, and emotion recognition raises significant privacy risks, particularly when processing Personally Identifiable Information (PII). Current privacy-preserving methods lack adaptability to users’ preferences and contextual requirements, and obfuscate user faces uniformly. This research proposes a user-centric, context-aware, and ontology-driven privacy protection framework that dynamically adjusts privacy decisions based on user-defined preferences, entity sensitivity, and contextual information. The framework integrates state-of-the-art recognition models for recognising faces, objects, scenes, actions, and emotions in real time on data acquired from vision sensors (e.g., cameras). Privacy decisions are directed by a contextual ontology based in Contextual Integrity theory, which classifies entities into private, semi-private, or public categories. Adaptive privacy levels are enforced through obfuscation techniques and a multi-level privacy model that supports user-defined red lines (e.g., “always hide logos”). The framework also proposes a Re-Identifiability Index (RII) using soft biometric features such as gait, hairstyle, clothing, skin tone, age, and gender, to mitigate identity leakage and to support fallback protection when face recognition fails. The experimental evaluation relied on sensor-captured datasets, which replicate real-world image sensors such as surveillance cameras. User studies confirmed that the framework was effective, with over 85.2% of participants rating the obfuscation operations as highly effective, and the other 14.8% stating that obfuscation was adequately effective. Amongst these, 71.4% considered the balance between privacy protection and usability very satisfactory and 28% found it satisfactory. GPU acceleration was deployed to enable real-time performance of these models by reducing frame processing time from 1200 ms (CPU) to 198 ms. This ontology-driven framework employs user-defined red lines, contextual reasoning, and dual metrics (RII/IVI) to dynamically balance privacy protection with scene intelligibility. Unlike current anonymisation methods, the framework provides a real-time, user-centric, and GDPR-compliant method that operationalises privacy-by-design while preserving scene intelligibility. These features make the framework appropriate to a variety of real-world applications including healthcare, surveillance, and social media. Full article

Terminal forensics in large mobile networks is a vital activity for identifying compromised devices and analyzing malicious actions. In contrast, the study described here begins with the domain of terminal forensics as the primary focus, rather than the threat itself. This paper proposes a new multi-criteria decision-making (MCDM) model that integrates complex picture fuzzy sets (CPFS) with the combinative distance-based assessment (CODAS), referred to throughout as complex picture fuzzy CODAS (CPF-CODAS). The aim is to assist in forensic analysis for detecting mobile botnet command and control (C&C) systems. The CPF-CODAS model accounts for the uncertainty, hesitation, and complex numerical values involved in expert decision-making, using degrees of membership as positive, neutral, and negative values. An illustrative forensic case study is constructed where three mobile devices are evaluated by three cybersecurity professionals based on six key parameters related to botnet activity. The results demonstrate that the model can effectively distinguish suspicious devices and support the use of the CPF-CODAS approach in terminal forensics of mobile networks. The robustness, symmetry, and advantages of this model over existing MCDM methods are confirmed through sensitivity and comparison analyses. In conclusion, this paper introduces a novel probabilistic decision-support tool that digital forensic specialists can incorporate into their workflow to proactively identify and prevent actions of mobile botnet C&C servers. Full article

Evaluating regional water resource carrying capacity (WRCC) helps alleviate regional water supply–demand conflicts. This study constructed a 17-indicator system for evaluating WRCC in Major Grain-Producing Areas (MGPAs) based on the “production–living–ecology” functional perspective. It employed a combined Entropy Weight–Root Mean Square Deviation–CRITIC weighting approach with a BP neural network model to conduct a comprehensive assessment of WRCC across 13 MGPAs from 2004 to 2023. The results demonstrated the following: (1) Both MGPAs and the national level exhibit a “ecology dominance–living secondary–production weakness” pattern in functional weighting. (2) WRCC in MGPAs is characterized by agricultural production dominance, basic domestic needs as the core, and localized ecological protection as the focus—significantly differing from the national pattern of industrial-driven, economically interconnected, and trans-regional ecological concerns. (3) Spatiotemporally, WRCC levels across the 13 provinces have consistently increased, with a spatial distribution characterized by “higher in the north, lower in the south.” These findings reveal that water resource management in MGPAs requires strategies distinct from national approaches, emphasizing agricultural water conservation and efficiency alongside localized ecological protection. This provides precise policy tools and scientific decision support for implementing water-based production quotas and coordinating food security with water resource security in these regions. Full article

Early and accurate detection of lemon disease is necessary for effective citrus crop management. Traditional approaches often lack refined diagnosis, necessitating more powerful solutions. The article introduces adaptive PSO-LemonNetX, a novel framework integrating a novel deep learning model, adaptive Particle Swarm Optimization (PSO)-based feature selection, and explainable AI (XAI) using LIME. The approach improves the accuracy of classification while also enhancing the explainability of the model. Our end-to-end model obtained 97.01% testing and 98.55% validation accuracy. Performance was enhanced further with adaptive PSO and conventional classifiers—100% validation accuracy using Naive Bayes and 98.8% testing accuracy using Naive Bayes and an SVM. The suggested PSO-based feature selection performed better than ReliefF, Kruskal–Wallis, and Chi-squared approaches. Due to its lightweight design and good performance, this approach can be adapted for edge devices in IoT-enabled smart farms, contributing to sustainable and automated disease detection systems. These results show the potential of integrating deep learning, PSO, grid search, and XAI into smart agriculture workflows for enhancing agricultural disease detection and decision-making. Full article

Background/Objectives: Aortic stenosis (AS) leads to progressive left ventricular (LV) pressure overload, adverse myocardial remodeling, and eventual functional decline. While traditional parameters such as left ventricular ejection fraction (LVEF) may remain preserved until advanced stages, they are insufficiently sensitive to early dysfunction. Global longitudinal strain (GLS) offers improved detection but remains load-dependent. In contrast, non-invasive myocardial work (MW)—derived from pressure-strain loops—offers a more load-independent assessment of myocardial function. This systematic review and meta-analysis aimed to evaluate the effects of transcatheter aortic valve implantation (TAVI) on MW indices in patients with severe AS. Methods: We performed a systematic review and meta-analysis of studies reporting non-invasive myocardial work parameters before and after TAVI (PROSPERO ID: CRD420250517138). Databases were searched through 31 March 2025. Pooled mean differences in global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) were calculated using random-effects models. Sensitivity analyses and meta-regression were conducted to explore heterogeneity and the influence of baseline characteristics. Results: Eleven studies encompassing 1493 patients were included. TAVI was associated with a significant reduction in GWI (−236.67 mmHg% [95% CI: −373.82 to −99.52]; I² = 97.0%; p = 0.002) and GCW (−243.71 mmHg% [95% CI: −407.38 to −80.03]; I² = 97.4%; p = 0.006). No significant changes were observed in GWW or GWE. Meta-regression showed age and baseline LVEF significantly influenced GWE changes, but not other parameters. Conclusions: TAVI leads to a significant reduction in GWI and GCW, reflecting decreased myocardial workload and afterload relief. These findings support the utility of MW indices as valuable tools for assessing myocardial adaptation post-TAVI and potentially guiding clinical decision-making. Full article

Background/Objectives: The diagnosis of Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacterial (NTM) infections is accomplished by three main diagnostics methods: smear microscopy, culture, and molecular testing. Diagnostic algorithms used by laboratories can significantly impact clinical and infection control management. Current Canadian Tuberculosis Standards recommend the use of nucleic acid amplification testing (NAAT) for smear-positive patients and smear-negative patients upon request. An alternative algorithm is to utilize NAAT in the Panel approach on all samples, pulmonary and extrapulmonary, to potentially reduce time to diagnosis and treatment. This alternative approach was implemented in November 2019 at the Newfoundland and Labrador Public Health and Microbiology Laboratory (NL PHML) using a laboratory-developed multiplex real-time PCR (LDT m-qPCR) assay targeting Mycobacterium spp. (Myco spp.) and MTBC, performed in parallel with smear and culture. Methods: To investigate the impact of this alternate testing approach, we conducted an observational retrospective analysis of laboratory diagnostic and treatment data, recognizing that temporal changes in epidemiology, clinical practice, and laboratory workflow may also have influenced outcomes. To complete this, study data from three years before and four years after implementation were gathered. Results: The sensitivity/specificity of the smear, m-LDT qPCR-MTBC, m-LDT qPCR-Myco spp., and culture assays in this study were 18.1%/100%, 96.7%/99.8%, 47.6%/99.0%, and 96.8%/100%, respectively. The gold standard utilized for these calculations was clinical diagnosis for active MTBC disease and culture for NTM infections, recognizing that the use of clinical diagnosis may introduce subjectivity. The Panel approach reduced the time to diagnosis of tuberculosis MTBC by 29 days (p < 0.0001) for NL PHML, and when modelled for a laboratory with rapid culture identification, diagnosis was reduced by 14 days (p = 0.003). Among non-empirically treated tuberculosis patients, the time to treatment was decreased by 25.5 days (p < 0.001). For NTM infections, rapid diagnostics only affected one patient’s treatment. This finding agrees with clinical management guidelines, which do not routinely utilize rapid diagnostics for the diagnosis of disease or treatment decisions. The cost implications of additional NAAT testing were calculated to be an increase of CAD 23.62 per sample. Conclusions: Our findings support the adoption of a molecular assay for MTBC as an initial diagnostic tool to decrease time to diagnosis and time to treatment, depending on local epidemiology and irrespective of smear status. Utilizing a molecular assay for genus level identification of NTM had minimal impact on clinical management suggesting its limited diagnostic utility in a broad population setting. Full article

Although liquefied natural gas (LNG) is already widely used as a marine fuel, its use on large cruise ships is a relatively new development. By the end of 2024, twenty-four LNG-fuelled cruise ships were in operation, each carrying several thousand passengers and making frequent port calls. These operational characteristics increase the potential risks compared to conventional cargo ships and require a rigorous safety assessment. In this study, the safety of LNG-fuelled cruise ships is assessed using the Formal Safety Assessment (FSA) framework prescribed by the International Maritime Organization (IMO). The assessment includes a hazard identification (HAZID), a risk analysis, an evaluation of risk control options, a cost–benefit analysis and recommendations for decision-making. Given the limited operational data on LNG-fuelled cruise ships, event trees are developed on the basis of LNG tanker incidents, adjusted to reflect passenger-related risks and cruise-specific operating conditions. A statistical overview of marine casualties involving cruise ships and LNG carriers of more than 20,000 GT over the last 35 years provides a further basis for the analysis. To ensure compliance, the study also analyses class requirements and regulatory frameworks, including risk assessments for ship design, bunker operations and emergency preparedness. These assessments, which are carried out at component, ship and process level, remain essential for safety validation and regulatory approval. The results provide a comprehensive framework for assessing LNG safety in the cruise sector by combining existing safety data, regulatory standards and probabilistic risk modelling. Recent work also confirms that event tree modelling identifies critical accident escalation pathways, particularly in scenarios involving passenger evacuation and port operations, which are under-researched in current practice. The results contribute to the wider debate on alternative fuels and support evidence-based decision-making by ship operators, regulators and industry stakeholders. Full article

Advances in geroscience suggest that aging is modulated by molecular pathways that are amenable to dietary and pharmacological intervention. We conducted an integrative critical review of caloric restriction (CR), intermittent fasting (IF), and caloric restriction mimetics (CR-mimetics) to compare shared mechanisms, clinical evidence, limitations, and translational potential. Across modalities, CR and IF consistently activate AMP-activated protein kinase and sirtuins, inhibit mTOR (mechanistic target of rapamycin) signaling, and enhance autophagy, aligning with improvements in insulin sensitivity, lipid profile, low-grade inflammation, and selected epigenetic aging measures in humans. CR-mimetics, such as metformin, resveratrol, rapamycin, and spermidine, partially reproduce these effects; however, long-term safety and efficacy in healthy populations remain incompletely defined. Methodological constraints—short trial duration, selective samples, intermediate (nonclinical) endpoints, and limited adherence monitoring—impede definitive conclusions on hard outcomes (frailty, disability, hospitalization, mortality). We propose the Active Management of Aging and Longevity (AMAL) model, a three-level biomarker-guided framework that integrates personalized diet, chrono-nutrition, exercise, and the selective use of CR-mimetics, along with digital monitoring and decision support. AMAL emphasizes epigenetic clocks, multi-omics profiling, inflammatory and microbiome metrics, and adaptive protocols to enhance adherence and clinical relevance. Overall, CR, IF, and CR mimetics constitute promising, complementary strategies to modulate biological aging; rigorous long-term trials with standardized biomarkers and clinically meaningful endpoints are needed to enable their scalable implementation. Full article

Background/Objectives: The attainment of a stone-free (SF) condition is a fundamental indicator of successful outcomes after flexible ureteroscopy (fURS) for urinary stone disease. External confirmations of preoperative scores remain limited. We externally validated the T.O.HO. and S.T.O.N.E. scores in an independent Japanese cohort and examined calibration, decision curve utility, and threshold-guided use to support personalized planning. Methods: We retrospectively analyzed 361 consecutive patients treated with fURS from March 2018 to August 2023. Postoperative SF status was defined as the absence of residual calculi greater than 2 mm on non-contrast computed tomography performed within three months of surgery. Independent determinants of SF were identified using multivariable logistic regression, predictive performance was quantified by receiver operating characteristic analyses with DeLong’s test, and model calibration and decision curve analysis were additionally assessed. Results: Among the 361 patients, 255 (70.6%) achieved an SF state. A larger stone diameter, the presence of lower-pole calculi, and preoperative pyuria (positive urine WBC) were significant independent predictors of residual fragments. T.O.HO. demonstrated superior discrimination (AUC 0.86) compared with S.T.O.N.E. (AUC 0.77; p < 0.01) and surpassed individual predictors. Both scores showed acceptable calibration. Decision curve analysis demonstrated higher net benefit for T.O.HO. across clinically relevant thresholds. We provide clinically useful cut-offs (e.g., T.O.HO. ≤5: high SF probability; 6: trade-off discussion; ≥7: higher residual risk) to align actions with patient priorities. Conclusions: Beyond discrimination, a calibrated, threshold-aware use of T.O.HO. enables personalized preoperative counseling and shared decision-making, potentially reducing unnecessary staging and enhancing routine fURS planning. Full article

Pulmonary fibrosis (PF) is a progressive and fatal lung disease characterized by irreversible alveolar destruction and pathological extracellular matrix (ECM) deposition. Currently approved agents (pirfenidone and nintedanib) slow functional decline but do not reverse established fibrosis or restore functional alveoli. Multifunctional bioscaffolds present a promising therapeutic strategy through targeted modulation of critical cellular processes, including proliferation, migration, and differentiation. This review synthesizes recent advances in scaffold-based interventions for PF, with a focus on their dual mechano-epigenetic regulatory functions. We delineate how scaffold properties (elastic modulus, stiffness gradients, dynamic mechanical cues) direct cell fate decisions via mechanotransduction pathways, exemplified by focal adhesion–cytoskeleton coupling. Critically, we highlight how pathological mechanical inputs establish and perpetuate self-reinforcing epigenetic barriers to regeneration through aberrant chromatin states. Furthermore, we examine scaffolds as platforms for precision epigenetic drug delivery, particularly controlled release of inhibitors targeting DNA methyltransferases (DNMTi) and histone deacetylases (HDACi) to disrupt this mechano-reinforced barrier. Evidence from PF murine models and ex vivo lung slice cultures demonstrate scaffold-mediated remodeling of the fibrotic niche, with key studies reporting substantial reductions in collagen deposition and significant increases in alveolar epithelial cell markers following intervention. These quantitative outcomes highlight enhanced alveolar epithelial plasticity and upregulating antifibrotic gene networks. Emerging integration of stimuli-responsive biomaterials, CRISPR/dCas9-based epigenetic editors, and AI-driven design to enhance scaffold functionality is discussed. Collectively, multifunctional bioscaffolds hold significant potential for clinical translation by uniquely co-targeting mechanotransduction and epigenetic reprogramming. Future work will need to resolve persistent challenges, including the erasure of pathological mechanical memory and precise spatiotemporal control of epigenetic modifiers in vivo, to unlock their full therapeutic potential. Full article

The Attribute-Based Access Control (ABAC) model provides access control decisions based on subject, object (resource), and contextual attributes. However, the use of sensitive attributes in access control decisions poses many security and privacy challenges, particularly in cloud environment where third parties are involved. To address this shortcoming, we present a novel privacy-preserving Dummy-ABAC model that obfuscates real attributes with dummy attributes before transmission to the cloud server. In the proposed model, only dummy attributes are stored in the cloud database, whereas real attributes and mapping tokens are stored in a local machine database. Only dummy attributes are used for the access request evaluation in the cloud, and real data are retrieved in the post-decision mechanism using secure tokens. The security of the proposed model was assessed using a simulated threat scenario, including attribute inference, policy injection, and reverse mapping attacks. Experimental evaluation using machine learning classifiers (“DecisionTree” DT, “RandomForest” RF), demonstrated that inference accuracy dropped from ~0.65 on real attributes to ~0.25 on dummy attributes confirming improved resistance to inference attacks. Furthermore, the model rejects malformed and unauthorized policies. Performance analysis of dummy generation, token generation, encoding, and nearest-neighbor search, demonstrated minimal latency in both local and cloud environments. Overall, the proposed model ensures an efficient, secure, and privacy-preserving access control in cloud environments. Full article

High-rise building facades offer an alternative site for installing photovoltaic panels, which are traditionally placed on rooftops. The unique spatial configuration of high-rise buildings, characterized by a small footprint area relative to their height, supports the application of vertical facades for this purpose. Photovoltaic panels installed in these areas not only generate electricity but also enhance the aesthetic dimension of the urban landscape. The proposed methodology uses the EnergyPlus software to simulate the electricity generation of photovoltaic panels mounted on the walls of high-rise buildings in the city of Kragujevac, Serbia. A technical, economic, and environmental analysis was conducted for two scenarios: (1) photovoltaic panels installed on two facade areas with the highest solar potential, and (2) photovoltaic panels installed on all four available facade areas. In Scenario 1, the annual reduction in electricity consumption, annual cost savings in electricity consumption, and investment payback period range from 13 to 38%, 11 to 31%, and 8.4 to 10.6 years, respectively. In Scenario 2, these values range from 23 to 58%, 18 to 47%, and 10.9 to 12.9 years, respectively. The results indicate that southeast and southwest facades consistently achieve higher levels of electricity generation, underscoring the importance of prioritizing high-performing orientations rather than maximizing overall surface coverage. The methodology is particularly efficient for analyzing the solar potential of numerous buildings with comparable shapes, which is a characteristic commonly found in Eastern European architecture from the late 20th century. The study demonstrates the applicability of the proposed methodology as a practical and adaptable tool for assessing early-stage solar potential and providing decision support in urban energy planning. The approach addresses the identified methodological gap by offering a low-cost, flexible framework for assessing solar potential across diverse urban contexts and building typologies, while significantly simplifying the modeling process. Full article

Today, as planners and urban designers increasingly rely on computational modeling to study complex urban systems, a methodological shift toward virtual experimentation is discernible because the real-world factors are difficult to control. This paper investigates the effect of the realism of computer simulations on distance perception in urban squares and streets. This study used Autodesk 3ds Max^® for modeling and V-Ray for rendering to create systematic variations in distances, with 172 participants providing distance estimates for 216 images. Results indicated that realism had a significant effect on distance perception, increasing estimation accuracy from r = 0.8 to r = 0.94. Lower realism was always associated with an underestimation of the distance, whereas higher realism manifested both overestimation and underestimation. Underestimation is dominant at long distances (>20 m), attributable to a lack of cues, common in low realism; overestimation happens only for short distances (≤20 m) due to high realism. These findings underscore the importance of simulation fidelity for urban designers and planners, enhancing the validity of virtual tools in design, research, and decision-making. Full article

Colorectal liver metastases (CRLM) management remains a complex conundrum in the context of potential curable disease. The combination of systemic therapy and surgery, with overall survival outcomes up to 58% at five years, has become the gold standard. Locoregional therapies have gained evidence in complementing surgery or even substituting it in selected cases. Adequate patient selection is paramount, but prognostic models have certain limitations that prevent their full implementation in clinical practice. A plethora of prognostic factors exists, with variable evidence supporting their definitive role. Thus, CRLM management decisions frequently vary depending on multidisciplinary team experience and hospital access to systemic and locoregional treatments. Definition of resectability has evolved in recent years due to technical developments in surgical and non-surgical approaches. Complexity is added when trying to fully understand the integration between local and systemic treatment. Whereas evidence in the context of resectable disease has been attempted in several phase III trials, definitive conclusions regarding the best approach to potentially resectable disease cannot be drawn. In addition, liver transplantation has gained evidence and is proposed in selected patients, raising a challenge regarding its integration and wider implementation. In this review, current standards in the management of CRLM regarding patient selection, resectability, surgical and non-surgical locoregional strategies, as well as the best systemic approach are covered. Full article

Background/Objectives: Decision-making under socially evaluative stress engages a dynamic interplay between cognitive control, emotional appraisal, and motivational systems. Contemporary models of multi-level co-regulation posit that these systems operate in reciprocal modulation, redistributing processing resources to prioritise either rapid socio-emotional alignment or deliberate evaluation depending on situational demands. Methods: Adopting a neurofunctional approach, a novel dual-task protocol combining the MetaCognition–Stress Convergence Paradigm (MSCP) and the Social Stress Test Neuro-Evaluation (SST-NeuroEval), a simulated social–evaluative speech task calibrated across progressive emotional intensities, was implemented. Twenty professionals from an HR consultancy firm participated in the study, with concurrent recording of frontal-temporoparietal electroencephalography (EEG) and bespoke psychometric indices: the MetaStress-Insight Index and the TimeSense Scale. Results: Findings revealed that decision contexts with higher socio-emotional salience elicited faster, emotionally guided choices (mean RT difference emotional vs. cognitive: −220 ms, p = 0.026), accompanied by oscillatory signatures (frontal delta: F(1,19) = 13.30, p = 0.002; gamma: F(3,57) = 14.93, p ≤ 0.001) consistent with intensified socio-emotional integration and contextual reconstruction. Under evaluative stress, oscillatory activity shifted across phases, reflecting the transition from anticipatory regulation to reactive engagement, in line with models of phase-dependent stress adaptation. Across paradigms, convergences emerged between decision orientation, subjective stress, and oscillatory patterns, supporting the view that cognitive–emotional regulation operates as a coordinated, multi-level system. Conclusions: These results underscore the importance of integrating behavioural, experiential, and neural indices to characterise how individuals adaptively regulate decision-making under socially evaluative stress and highlight the potential of dual-paradigm designs for advancing theory and application in cognitive–affective neuroscience. Full article