Search Results (709)

Visual Question Answering (VQA) in embodied settings draws on computer vision, natural language processing, and robotics. Unlike traditional VQA, Embodied Question Answering (EQA) may require an agent to acquire and retain evidence from a 3D environment before answering a natural language query. This semi-systematic survey reviews a core corpus of 72 papers selected from 210 candidates and supplements it with a separate targeted qualitative update comprising 28 additional records identified through July 2026. We use PMRA (Perception–Memory–Reasoning–Action) as an author-developed analytical framework rather than a new robot-control architecture, together with a three-level taxonomy of task formulations, method architectures, and capability dimensions. An audit of the 20 tabulated datasets, with counts recomputed from the accompanying extraction sheet, finds that five permit or require active exploration and only one requires physical object interaction. We also define four architecture-based stages without using publication year as an assignment rule. The qualitative synthesis identifies examples of explicit memory interfaces and question-conditioned information-acquisition mechanisms, but it does not infer their prevalence, temporal growth, or relative importance from publication frequencies. Finally, we discuss four recurring limitations of foundation-model approaches and nine research directions toward 2030. Full article

This paper establishes new oscillation criteria ensuring that all solutions of a class of third-order nonlinear semi-canonical differential equations with a neutral term exhibit oscillatory behavior. The main objective of this paper is to establish a transformation of the considered semi-canonical equation into an equivalent canonical form without requiring additional restrictive assumptions. By employing this transformation, the equation is reduced to a more tractable form, allowing a clearer analytical treatment. Furthermore, by combining the comparison principle with an integral averaging technique, new sufficient conditions are derived to guarantee the oscillation of the associated canonical equation. These results are then extended to the original semi-canonical framework, thereby ensuring the oscillatory behavior of its solutions. The significance of the proposed approach lies in extending the applicability of known results for canonical equations to a broader class of semi-canonical problems. Finally, several illustrative examples are presented to demonstrate the effectiveness and applicability of the obtained theoretical results. Full article

Background/Objectives: Although artificial intelligence (AI) has the potential to strengthen disease surveillance, predictive analytics, preventive interventions, and population-level decision-making, its successful integration requires health systems to be adequately prepared across technical, workforce, governance, and organizational dimensions. Saudi Arabia’s rapid digital health transformation provides a unique national context for exploring these readiness conditions. This study explored stakeholder perceptions of conditions relevant to health system readiness for integrating AI into public health in Saudi Arabia, including perceived challenges, implementation requirements, and strategic opportunities. Methods: A qualitative descriptive study was conducted using semi-structured interviews with 32 participants, including healthcare professionals, health informatics experts, and policymakers or healthcare planning stakeholders in Saudi Arabia. Participants were purposively selected based on their relevant professional experience. Data were analyzed using Braun and Clarke’s six-phase reflexive thematic analysis. Results: Four major themes were identified: (1) infrastructure readiness, reflecting progress in digital health platforms alongside persistent interoperability and data-integration challenges; (2) workforce capacity, highlighting limited AI literacy and the need for practical, role-specific training; (3) data governance and ethics, emphasizing privacy, accountability, algorithmic bias, and the need for greater regulatory clarity; and (4) perceived strategic opportunities, including preventive care, population health monitoring, disease surveillance, and decision support. The first three themes reflected conditions perceived as relevant to health system readiness, whereas the fourth captured anticipated applications and potential benefits rather than a dimension of current readiness. Overall, participants perceived substantial national strategic commitment and digital health development while identifying important implementation challenges related to interoperability, workforce capability, governance, and regulation. Conclusions: Participants’ accounts suggest that responsible AI integration into public health requires coordinated attention to interoperable infrastructure, workforce competencies, governance mechanisms, regulatory oversight, and human-centered implementation. A phased implementation approach, supported by role-specific AI training and clear governance and regulatory frameworks, may help translate national AI ambitions into safe and effective public health practice. These findings may inform policy development, workforce planning, and implementation strategies for responsible AI integration in Saudi Arabia and other regions whose health systems are undergoing rapid digital transformation. Full article

Background: Nonfatal strangulation (NFS) is one of the most lethal forms of intimate partner violence (IPV) that is associated with increased risk of future homicide, yet it frequently goes unrecognized within healthcare settings. Black women experience disproportionately high rates of IPV while simultaneously facing structural barriers to healthcare access. Little research has examined how Black women survivors experience strangulation and navigate decisions about seeking care following NFS and other potentially lethal forms of IPV. Methods: This secondary qualitative analysis draws on interview data from 28 Black women survivors of IPV who participated in a larger community-engaged mixed-methods study conducted during the COVID-19 pandemic in an Upper Midwestern state. Of these, 17 (60.7%) both reported experiencing strangulation on the parent-study survey and described experiences consistent with nonfatal strangulation during their qualitative interviews and comprised the analytic sample for the present analysis. Guided by Black Feminist Thought, semi-structured interviews examined survivors’ experiences with violence, safety, help-seeking, and interactions with healthcare and social service systems. Data were analyzed using thematic analysis following Schensul and Schensul. Results: Three interconnected themes were identified. First, survivors described racism and anticipated discrimination as significant barriers to seeking healthcare following strangulation. Second, shame, stigma, and fear of judgment contributed to self-silencing and avoidance of formal services. Third, survivors described strangulation as a terrifying and potentially lethal form of violence occurring within broader histories of polyvictimization and cumulative trauma. Despite experiencing serious symptoms, many participants avoided healthcare because they feared retaliation from abusive partners, anticipated dismissive treatment, or believed healthcare systems would be unable to protect them. Together, these experiences illustrate how structural racism, institutional mistrust, and gendered violence intersect to shape healthcare decision-making. Conclusions: Findings suggest that barriers to care following strangulation extend beyond individual help-seeking behaviors and are deeply rooted in structural inequities. Improving outcomes for Black women survivors requires enhanced provider training on strangulation assessment, trauma- and violence-informed approaches, culturally responsive care, and healthcare system reforms that address racism, mistrust, and survivor safety. These findings have important implications for reducing disparities in IPV-related health outcomes and improving responses to high-lethality violence. Full article

Engineering curricula offer students few structured opportunities to practice reasoning about problems whose social, political, and economic dimensions are as consequential as their technical ones. This paper reports an exploratory qualitative study of an undergraduate engineering elective in which students investigate a wicked problem of their choice using multiple systems mapping tools, with an explicit emphasis on problem exploration over solution convergence. Drawing on semi-structured post-course interviews with 13 purposively sampled students across three cohorts, including a case-based transfer task set in an unfamiliar sociotechnical context, we examine what capacities students describe developing and how specific mapping tools mediate their reasoning. Interviews were analysed through a combined deductive–inductive coding approach organized by the STOP (Systems Thinking for Opportunity) framework, an analytic scaffold that links Richmond’s systems thinking competencies, the KEEN entrepreneurial mindset dimensions, and Ardichvili et al.’s opportunity identification model. Students described a shift from solution-first thinking toward systemic inquiry, characterized mapping tools as scaffolds that externalized assumptions and structured prior knowledge, and displayed reasoning patterns consistent with adaptive transfer in the case task. These capacities did not develop uniformly: students’ accounts foregrounded structural and causal reasoning far more than reasoning about system behaviour over time, opportunity identification rarely progressed into formal opportunity development, and students were candid about where individual tools constrained their analyses. We therefore interpret systems mapping pedagogy as an amplifier of opportunity-relevant cognition rather than a direct producer of entrepreneurial outcomes. Reflecting the purposive, high-performing sample and the interview-based design, findings are offered as exploratory and bounded to this course context. The study contributes a transparent, tool-level account of how mapping practice mediates sociotechnical reasoning, a case-based transfer task with explicit criteria as a model for assessing sociotechnical learning, and design guidance for educators seeking to build sociotechnical capacity in engineering curricula. Full article

Rapid and accurate quantification of residual guar gum in bauxite slurry flocculation is a critical bottleneck for closed-loop control of flocculant dosage. In this study, we systematically compared the anti-interference performance of the two UV-Vis spectrophotometer approaches, the single-wavelength absorbance method (A₂₆₃) and the peak-trough difference method (ΔA), in complex slurry matrices. Our results revealed that the two methods respond differently to pH and salt concentration variations, leading to the proposal of a dual-mode synergistic detection strategy. The A₂₆₃ method provides quantification under the specific conditions tested within the ranges of pH 3.0–8.0 and CaCl₂ concentration below 4.5 mmol/L. Beyond these boundaries, deviations from the Beer-Lambert law occurred, attributable to conformational transitions or salting-out aggregation of the polymer chains. In contrast, the ΔA method partially mitigated background drift through differential calculation and exhibited a more stable signal trend than A₂₆₃ across the tested ranges (pH 2.0–11.0, CaCl₂ 0–18 mmol/L), suggesting its potential utility as a semi-quantitative indicator in challenging matrices. However, its quantitative precision was constrained by small absolute signal values and systematic dependence on pH and salt conditions. Based on these findings, we propose a synergistic strategy-preferring the A₂₆₃ method under routine conditions while recommending the ΔA method for high-salinity or wide-pH scenarios- and accordingly define the preliminary applicability boundaries based on signal response observations at a single concentration. Flocculation–sedimentation tests confirmed that the method successfully determined the optimum dosage (5.0 g/kg dry slurry), at which the residual concentration in the supernatant correlated negatively with the sedimentation rate (R² > 0.95). The supernatant matrix after sedimentation (pH ≈ 7.1, low ionic strength) fell exactly within the safe window. This work provides a methodological reference for spectrophotometric quantification of trace organics in turbid, saline, and pH-variable slurry systems, and lays an analytical foundation for intelligent dosage control in bauxite slurry dewatering. Full article

The chemical profile and migration behavior of volatile and semi-volatile compounds from silicone molds intended for use in air fryers were investigated. The study combined migration tests using 10% ethanol, 3% acetic acid, and simulant E (Tenax^®) with direct headspace (HS) analysis of the molds by gas chromatography–mass spectrometry (GC-MS). HS analysis and migration tests with aqueous simulants were performed over three heating cycles to simulate repeated use. A non-targeted analytical approach was applied, followed by selective quantification based on toxicological criteria and the relevance of the compounds to the material. A total of 128 substances were identified, including siloxanes and non-intentionally added substances (NIASs). Siloxanes were detected in both simulant E and 10% ethanol. Most NIASs were found at levels below the limit of quantification or within regulatory limits, except for dibutyl phthalate, which exceeded its specific migration limit (0.3 mg kg⁻¹). Furthermore, the sum of migrated cyclic siloxanes in simulant E surpassed the generic specific migration limit (60 mg kg⁻¹) established in Spanish Royal Decree 847/2011, while the release of volatile organic compounds exceeded the recommended value of 0.5%. The results revealed a complex chemical profile characterized by diverse NIASs and elevated migration of cyclic siloxanes in simulant E. Full article

Matrix differential equations with time delay are crucial to the modeling of complex multivariate systems. However, the existing semi-analytic Laplace residual power series method (LRPSM) literature mainly focuses on scalar or no-delay problems, and lacks rigorous theoretical guarantees for matrix-valued time delay systems. This study systematically generalizes LRPSM to the linear time-delay matrix differential equation $X^{\prime }\left(t\right)=AX\left(t\right)+BX(t-\tau )+F\left(t\right)$, where $X\left(t\right)\in {\mathbb{R}}^{n\times n}$, A and B are constant matrices, $\tau >0$ is a constant delay, and the forcing term $F\left(t\right)$ and the history function $\mathrm{\Phi }\left(t\right)$ are analytic. The method of steps is employed to construct the solution piecewise: on each local interval, the solution is expanded asymptotically in the Laplace domain, and the coefficients are determined recursively via the Laplace residual function. We establish local error bounds on the initial interval and derive a global error propagation bound across successive delay interfaces using a variation-of-constants framework. Numerical experiments, including non-diagonal matrices, non-zero history functions, and multi-interval tests, illustrate the effectiveness of the approach. The proposed method reduces exactly to the standard LRPSM for scalar cases, demonstrating its validity as a natural and rigorous generalization of the existing semi-analytical framework. Full article

The reliable long-term prediction of photovoltaic (PV) system performance is essential for optimizing operation, maintenance, and energy management in smart cities. Digital Twin (DT) technology has emerged as a promising approach for real-time monitoring and predictive analytics by continuously integrating physical system measurements with virtual models. However, many existing DT-based studies rely on limited validation periods, lack comprehensive uncertainty quantification, and provide insufficient comparisons with conventional forecasting approaches. To address these limitations, this study proposes a data-driven Digital Twin framework for daily photovoltaic energy production prediction for three silicon photovoltaic technologies (amorphous silicon, polycrystalline silicon, and monocrystalline silicon) operating under semi-arid climatic conditions in Morocco. The framework integrates data quality assessment and statistical production trend analysis based on linear regression, bootstrap confidence intervals, the Mann–Kendall trend test, and Sen’s slope estimator. In addition, the proposed DT model was benchmarked against persistence, linear regression, Random Forest, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) models using a chronological training, validation, and independent testing framework. Model performance was evaluated over an independent test period of 602 consecutive days, representing approximately 1.65 years of continuous operation and more than one complete annual cycle. The proposed Digital Twin improved upon the standalone LightGBM model, achieving an RMSE of 1.3047 kWh/day, an MAE of 0.9255 kWh/day, a MAPE of 14.62%, and an R² of 0.7015, compared with an RMSE of 1.3349 kWh/day, an MAE of 0.9637 kWh/day, and an R² of 0.6875 for LightGBM. Over the 11-year monitoring period, the estimated long-term production trend rates were −0.566% yr⁻¹ for a-Si, −0.335% yr⁻¹ for pc-Si, and −0.260% yr⁻¹ for mc-Si. Bootstrap analysis yielded median long-term production trend rates of −0.573, −0.326, and −0.251% yr⁻¹, respectively, while Mann–Kendall tests indicated no statistically significant monotonic production trend for any technology (p = 0.1611, 0.2758, and 0.3502, respectively). The extended independent testing period, combined with statistical production trend analysis and comparative machine-learning evaluation, demonstrates the applicability of the proposed Digital Twin framework for photovoltaic performance monitoring and adaptive prediction under semi-arid climatic conditions. Full article

This study examines the emotional, communicative, and relational work through which employees and managers sustain service in multicultural restaurant settings. It uses intercultural service labour as an integrative analytical lens to explain how service actors manage different expectations regarding language, hierarchy, tone, face, food knowledge, and appropriate interaction. The study adopted a qualitative multi-site design based on 27 semi-structured interviews with owners and managers, employees, and customers in Indian restaurants in Bangkok, Pattaya, and Si Racha, Thailand. Data were analysed using a hybrid deductive–inductive thematic approach. Five interconnected dimensions emerged: reading tone, silence, and face; mediating at service boundaries; making unfamiliar cuisine serviceable; learning through mistakes and adjustment; and calibrating service to different expectations. Participants’ accounts showed that sustaining service involved not only technical competence but also the capacity to interpret ambiguous cues, protect face, clarify incomplete understanding, reduce customer uncertainty, and adjust communication through experience. This labour was distributed across restaurant roles and often remained informal and weakly recognised. The study connects emotional labour, intercultural competence, and brokerage within a work-process perspective. It reframes intercultural competence as a situated accomplishment and shows how smooth multicultural service depends on informal coordination that organisations frequently rely on but rarely recognise. Full article

Accurate AFM nanoindentation analysis requires models that account for the rounded apex of real pyramidal indenters. Although exact force-indentation equations for n-sided blunt pyramids exist, their numerical complexity limits routine use. In this work, a simple closed-form analytical approximation is developed that directly relates force to indentation depth for blunt pyramidal indenters. The method employs first-order Maclaurin series expansions of the geometric terms and the generic indentation differential equation, yielding a closed-form second-degree polynomial expression that is readily implemented in AFM data analysis. Comparison with the exact solutions showed that the approximation error decreases with indentation depth and is governed by the pyramid geometry rather than the tip radius. Simulated and experimental AFM data confirmed accurate Young’s modulus estimation above a geometry-dependent validity threshold. For a four-sided blunt pyramidal indenter, the proposed criterion predicts minimum indentation depths ranging from approximately $10.4 R_c$ for θ = 15° to 2.4 $R_c$ for θ = 45° where $R_c$ is the tip radius and θ is the pyramid’s semi-included angle. Application of the model to simulated AFM datasets yielded Young’s modulus values between 18.5 and 19.8 kPa for a true modulus of 20 kPa, corresponding to errors below 8% in all examined cases. Furthermore, the closed-form equation provided very good agreement with AFM nanoindentation data obtained from human prostate cancer cells. It is also shown that the generic derived equation includes the case of a spheroconical indenter as a limiting case. Young’s modulus is obtained directly from the quadratic coefficient, eliminating the need for tip-radius calibration. In addition, the formulation is applicable to heterogeneous materials, providing an effective local modulus through the weighted mean value theorem for integrals. The approach offers a practical and computationally efficient alternative for AFM data processing, improving the robustness of modulus estimation for soft biological materials. Full article

This article examines the cartographic design of nano-scale productive systems led by women nano-entrepreneurs, understood as family-based productive arrangements embedded in everyday domestic spaces. In rural contexts, many women-led ventures operate at a nano-scale and are organized around household dynamics, where entrepreneurial leadership, family labor, and productive activities intersect. Drawing on a qualitative territorial research approach, the study combines semi-structured interviews, fieldwork, and cartographic design to identify productive actions and the spaces in which they take place. The findings show that these nano-scale productive systems function through the articulation of multiple actions rather than formal organizational structures, and that women exercise entrepreneurial leadership by coordinating family-based activities within and beyond the home. As a result, everyday spaces, particularly the household, are resignified as workshops, points of sale, and centers of management, giving rise to locally embedded family-based enterprises in emerging rural economies. Using cartographic design as an analytical tool, the article contributes to research on family entrepreneurship and leadership by highlighting how women-led nanoenterprises reshape spatial organization, and productive practices within emerging family firms. Full article

Accurate and computationally efficient prediction of radioactive plume dispersion is essential for rapid risk assessment and emergency response in the event of accidental atmospheric releases. This study presents a three-dimensional, mass-conservative numerical framework for simulating mesoscale transport and transformation of radionuclides under varying meteorological conditions. The proposed model is based on the advection–diffusion equation and incorporates key physical processes, including turbulent diffusion, gravitational settling, precipitation washout, radioactive decay, surface absorption, and re-emission. A hybrid numerical scheme is developed that combines a semi-implicit Crank–Nicolson discretization for diffusion terms with a second-order Total Variation Diminishing (TVD) scheme employing a Van Leer limiter for advection. The framework is intended as a computationally tractable engineering model; operational applicability requires further assessment using measured runtime performance and independent physical validation. In addition, a modified parameterization of turbulent-diffusion coefficients is introduced, extending classical Pasquill–Gifford formulations to better represent mesoscale atmospheric behavior with bounded dispersion characteristics. The numerical implementation is verified against an analytical constant-coefficient advection–diffusion solution using concentration-error norms, plume-moment errors, mass-balance analysis, and grid-refinement tests. Additional idealized iodine-131 simulations illustrate the behavior of the framework under moderate-wind and stable atmospheric conditions. The results highlight the dominant role of advective transport and precipitation scavenging under moderate wind conditions, as well as strong localization effects under stable atmospheric stratification. The proposed model provides a practical compromise between the simplicity of Gaussian plume approaches and the high computational cost of full-physics atmospheric models, indicating its potential for rapid engineering calculations, subject to further validation against atmospheric observations and established operational dispersion models. Full article

This study investigates the vibro-acoustic behavior of a thin square aluminum plate with a central clamped hole, inspired by splash cymbal configurations. The structural dynamics are analyzed using finite element method (FEM) modal and frequency response function (FRF) simulations, while experimental measurements validate the modal characteristics. A semi-analytical Rayleigh–Ritz model is also employed to estimate the natural frequencies and provide an additional reference for comparison. Excellent agreement is observed between the predicted and measured resonance frequencies and overall dynamic response. Acoustic radiation is evaluated through coupled structural–acoustic analyses using a Rayleigh integral formulation and an indirect variational boundary element method (BEM). The sound pressure radiated to a field point above the plate is compared with the FEM-derived FRF results. The results demonstrate a correlation between structural vibration and acoustic response, with variations in radiation efficiency influenced by the central clamp and higher-frequency modal behavior. The Rayleigh approach shows good agreement but exhibits numerical noise and overprediction of modal contributions. In contrast, the BEM provides smoother responses and more physically consistent results. These findings are relevant for noise control, vibration reduction, and sound synthesis applications in mechanical systems. Full article

Autonomous robotic systems operating in residential environments must maintain safe, reliable, and adaptive performance under heterogeneous conditions characterized by environmental uncertainty. Achieving this performance is difficult because such systems must simultaneously cope with variable contact states and complex subsystem interactions. Conventional component-oriented engineering approaches often fail to capture how internal faults, external disturbances, and architectural decisions interact to generate system-level instabilities and hazards. This paper proposes a Systems Thinking-based Safety-by-Design framework to support the sustainable early-stage design of autonomous residential robotic systems. The methodology formalizes the relationships among internal faults (F), environmental variability (E), system behaviour (S), architecture (A), instabilities (I), hazards (H), and safety barriers (B) through the dependencies S = f(F,E), I = g(S,A), and H = h(I,B). Environmental variability is treated as an active design driver influencing system behaviour, architectural decisions, and safety requirements. The framework is evaluated as a proof-of-concept, semi-quantitative analytical demonstration, rather than an experimentally validated result, using an autonomous window-cleaning robot: its functional subsystems are mapped to the conceptual model and fault-dominated, environment-dominated, and coupled degradation scenarios are assessed through a semi-quantitative index. The results show that risk emerges from subsystem interactions rather than isolated component failures and that adaptive architectures reduce instability propagation under uncertain operating conditions. The proposed framework supports early engineering decisions that improve robustness, resilience, safety, maintainability, and sustainability. Full article