Search Results (142)

Most research studies have investigated the impact of pet ownership on the mental and physical well-being of elderly populations, supporting the beneficial effect that pets have on their owners. However, few researchers focused on the well-being of both owner and pet. The present study aimed to explore the well-being of pets owned by elderly individuals using an owner assessment tool and the relationship between elderly characteristics and the pet’s health-related quality of life based on the owner’s assessment of their pet’s well-being. Sixty elderly pet owners who made regular visits to veterinary clinics were selected to complete an electronic questionnaire about their pet’s health-related quality of life. The results identified a high agreement percentage on positive indicators related to the pet’s well-being such as “My pet wants to play and My pet responds to my presence” in the happiness domain, “My pet has more good days than bad days” in mental status, “My pet moves normally” in physical status and “My pet keeps him/herself clean” in hygiene which also resulted in a positive relationship with elderly age. Marital status influenced their responses to “My pet responds to my presence and My pet is as active as he/she has been”. The results also support the use of the applied questionnaire to help identify variables that contribute to a pet’s health-related quality of life. The correlation matrix revealed statistically significant positive associations (p < 0.001) among positively phrased items across all domains, as well as among negatively phrased items. These consistent alignments between direct and between reversed items suggest directional coherence and help mitigate potential response bias. Furthermore, the replication of these patterns across multiple domains reinforces the interpretation that the instrument captures a unified construct of pet well-being, In conclusion, based on subjective evaluation of pet-owner relationships, the ownership of pets by elderly individuals could be mutually beneficial to both elderly owners and their pets. Full article

This study investigates the dynamic relationship between bearing gearbox condition indicators (BGCIs) and the lubrication oil temperature within the framework of health and usage monitoring system (HUMS) applications. Using the dynamic autoregressive distributed lag (DARDL) simulation model, we quantified both the short- and long-term responses of condition indicators to shocks in oil temperature, offering a robust framework for a counterfactual analysis. To complement the time-domain perspective, we applied a wavelet coherence analysis (WCA) to explore time–frequency co-movements and phase relationships between the condition indicators under varying operational regimes. The DARDL results revealed that the ball energy, cage energy, and inner and outer race indicators significantly increased in response to the oil temperature in the long run. The WCA results further confirmed the positive association between oil temperature and the condition indicators under examination, aligning with the DARDL estimations. The DARDL model revealed that the ball energy and the inner race energy have statistically significant long-term effects on the oil temperature, with p-values < 0.01. The adjusted R² of 0.785 and the root mean square error (MSE) of 0.008 confirm the model’s robustness. The wavelet coherence analysis showed strong time–frequency correlations, especially in the 8–16 scale range, while the frequency-domain causality (FDC) tests confirmed a bidirectional influence between the oil temperature and several condition indicators. The FDC analysis showed that the oil temperature significantly affected the BGCIs, with evidence of feedback effects, suggesting a mutual dependency. These findings contribute to the advancement of predictive maintenance frameworks in HUMSs by providing practical insights for enhancing system reliability and optimizing maintenance schedules. The integration of dynamic econometric approaches demonstrates a robust methodology for monitoring critical mechanical components and encourages further research in broader aerospace and industrial contexts. Full article

Analyzing and measuring the similarity between two signals is a common task in many vibration-based structural health monitoring applications. Coherence between input and response signals serves as a convenient indicator of damage, based on the premise that nonlinearity due to damage in a linear system manifests as a loss of coherence in specific frequency bands. Because input excitations in civil structures are difficult to measure, damage indicators based on the coherence between two response signals have been developed. These indicators have shown promise in detecting nonlinear behavior in structures that were initially linear. This paper proposes a new damage indicator based on Mutual Information, a nonlinear extension of the squared correlation coefficient, to quantify the similarity between two signals without making assumptions about the nature of their interactions or the underlying dynamics of the system. Mutual Information is distinguished from other nonlinear similarity metrics due to its ability to capture all types of nonlinear dependencies, its high computational efficiency, and its invariance to invertible transformations, such as scaling. The proposed approach is demonstrated using a standard dataset containing experimental data from a three-story aluminum frame structure under 17 different damage states. The results show that the proposed metric can detect deviations from the baseline state due to changes in mass, stiffness, or newly induced nonlinear behavior, suggesting its potential for monitoring changes in the structural system. Full article

Background: This case–control study evaluated the concentrations of zinc (Zn), iron (Fe), and copper (Cu) in the aqueous humor (AH) of patients with primary glaucoma, and their relationships with clinical factors. Methods: This study enrolled 100 patients with primary glaucoma and categorized them into subtypes: acute angle-closure crisis (AACC), primary angle-closure glaucoma (PACG), and primary open-angle glaucoma (POAG). A total of 67 patients with senile cataract were enrolled as controls. Their AH samples and clinical information were obtained. Results: In primary glaucoma, Zn, Fe, and Cu concentrations increased, especially in AACC group; Zn, Fe, and Cu were positively correlated mutually; and decreased Zn/Fe and increased Fe/Cu were observed. The number of quadrants with closed anterior chamber angle on gonioscopy was positively associated with Fe and Cu levels in AACC and with Zn and Cu levels in PACG. In POAG, we found negative associations between Zn and the number of quadrants with retinal nerve fiber layer thinning on optical coherence tomography, Fe and age, and Cu and the cup-to-disc ratio. Trace metals showed high efficiency in discriminating primary glaucoma from controls. Conclusions: Zn, Fe, and Cu concentrations in patients with primary glaucoma increased and were associated with clinical factors, acting as potential biomarkers. Full article

Effective monitoring and evaluation (M&E) are essential for ensuring that Maritime Spatial Planning (MSP) contributes to the sustainable development of the blue economy while maintaining alignment with institutional frameworks. The study presented in this paper develops a stakeholder-driven M&E framework for sustainable MSP, emphasizing a participatory methodology to enhance the relevance and applicability of performance assessment. Using a structured mutual learning approach, the research engaged stakeholders in two iterative rounds: the first identified key strategic objectives for a sustainable blue economy through dialogue and a complementary questionnaire survey, while the second refined these into corresponding specific objectives. This process was applied in the context of a case study in Greece, where MSP implementation is shaped by national and EU regulatory frameworks and the socio-economic dynamics of the coastal and maritime sectors. The case study provided a practical testing ground for the proposed methodology, involving stakeholders from government, industry, and civil society to ensure a comprehensive perspective. The insights gained informed the design of a key performance indicator (KPI) framework, integrating qualitative and quantitative metrics tailored to the regional maritime governance landscape. These metrics were selected based on the SMARTIE (Specific, Measurable, Achievable, Relevant, Time-Bound, Inclusive, Equitable) criteria and were clearly aligned with the established objectives. The frequency of measurements, appropriate data collection methods, and indicative data sources were also defined to provide a complete KPIs framework. This stakeholder-driven methodology strengthens the adaptive capacity of MSP by ensuring continuous assessment and revision aligned with sustainability objectives and facilitating ex ante, intermediate, and ex post evaluations. The proposed framework is scalable and transferable, offering a systematic approach to improving policy coherence and decision-making across different geographic, administrative, and sectoral contexts, enabling sustainable governance and maritime governance. Full article

Continuous and robust trajectory tracking of unmanned aerial vehicles (UAVs) plays a crucial role in urban air transportation systems. Accordingly, this article presents an end-to-end spatiotemporal correlation integration (ESCI)-based UAV tracking framework by leveraging a high-resolution cascade multiple input multiple output (MIMO) radar. On this account, a novel joint anti-interference detection and tracking system for weak extended targets is presented in this paper; the proposed method handles them jointly by integrating a continuous detection process into tracking. It not only eliminates the threshold decision-making process to avoid the loss of weak target information, but also significantly reduces the interference from other co-channel radars and strong clutters by exploring the spatiotemporal correlations within a sequence of radar frames, thereby improving the detectability of weak targets. In addition, to accommodate the time-varying number and extended size of radar reflections, with the ellipse spatial probability distribution model, the extended UAV with multiple scattering sources can be treated as an entity to track, and the complex measurement-to-object association procedure can be avoided. Finally, with Texas Instruments AWR2243 (TI AWR2243) we can utilize a cascade frequency-modulated continuous wave–multiple input multiple output (FMCW-MIMO) radar platform. The results show that the proposed method can obtain outstanding anti-interference performance for extended UAV tracking compared with state-of-the-art methods. Full article

The mining of relevant association rules from transactional databases is a fundamental process in data mining. Traditional algorithms, however, will typically be based on fixed thresholds and general rule generation, with the result being large and redundant outcomes. This paper presents DERAR (Dynamic Extracting of Relevant Association Rules), a dynamic approach integrating structure pattern mining and dynamic multi-criteria filtering. The process begins with the generation of frequent meta-patterns. Each entity is given a stability score for its consistency across various data projections, then sorted by mutual information in order to preserve the most informative dimensions. The resulting association rules from these models are filtered through a dynamic confidence threshold that is adjusted according to the statistical distribution of the dataset. A final semantic filtering phase identifies rules with high coherence between antecedent and consequent. Experimental results show that DERAR reduces rules by up to 85%, improving interpretability and coherence. It outperforms Apriori, FP-Growth, and H-Apriori in rule quality and computational efficiency. DERAR consistently achieves lower execution times and memory use, especially on large or sparse datasets. These results confirm the benefits of adaptive, semantically guided rule mining for generating concise, high-quality, and actionable knowledge. Full article

Dynamic criticality—the balance between order and chaos—is fundamental to genome regulation and cellular transitions. In this study, we investigate the distinct behaviors of gene expression dynamics in MCF-7 breast cancer cells under two stimuli: heregulin (HRG), which promotes cell fate transitions, and epidermal growth factor (EGF), which binds to the same receptor but fails to induce cell-fate changes. We model the system as an open, nonequilibrium thermodynamic system and introduce a convergence-based approach for the robust estimation of information-thermodynamic metrics. Our analysis reveals that the Shannon entropy of the critical point (CP) dynamically synchronizes with the entropy of the rest of the whole expression system (WES), reflecting coordinated transitions between ordered and disordered phases. This phase synchronization is driven by net mutual information scaling with CP entropy dynamics, demonstrating how the CP governs genome-wide coherence. Furthermore, higher-order mutual information emerges as a defining feature of the nonlinear gene expression network, capturing collective effects beyond simple pairwise interactions. By achieving thermodynamic phase synchronization, the CP orchestrates the entire expression system. Under HRG stimulation, the CP becomes active, functioning as a Maxwell’s demon with dynamic, rewritable chromatin memory to guide a critical transition in cell fate. In contrast, under EGF stimulation, the CP remains inactive in this strategic role, passively facilitating a non-critical transition. These findings establish a biophysical framework for cell fate determination, paving the way for innovative approaches in cancer research and stem cell therapy. Full article

We report a coherent tri-frequency microwave signal generation approach using an optoelectronic oscillator (OEO). In the previous literature, the OEO-based schemes can only generate coherent microwave signals with dual frequencies. In this work, we demonstrate that the generation of coherent tri-frequency microwave signals is also possible using an OEO loop. The key component in our scheme is a tri-passband electrical filter, which has a narrow passband in the middle and two wide passbands on both sides. The OEO loop initially oscillates at the central frequency of the narrow passband with a single-tone f₁. By injecting a microwave signal, f_inj, into the OEO loop, down- and up-converted microwave signals at frequencies of f₂ = f₁ − f_inj and f₃ = f₁ + f_inj, respectively, are generated by frequency mixing in a microwave mixer. The two wide passbands of the electrical filter allow the oscillation of the converted signals at a wide frequency bandwidth by simply tuning the frequency of the injected signal. Moreover, the tri-frequency microwave signals are phase-locked through frequency mixing and mutual injection locking. The proposed scheme is theoretically analyzed and experimentally validated. In the experiments, coherent tri-frequency microwave signals with low phase noise are successfully generated at a fixed frequency of 14 GHz and two tunable frequency ranges from 9 to 12 GHz and from 16 to 19 GHz, respectively. Full article

The choice of constellations largely affects the performance of both wireless and optical communications. To address increasing capacity requirements, constellation shaping, especially for high-order modulations, is imperative in high-speed coherent communication systems. This paper, thus, proposes novel mutual information neural estimation (MINE)-based geometric, probabilistic, and joint constellation shaping schemes, i.e., the MINE-GCS, MINE-PCS, and MINE-JCS, to maximize mutual information (MI) via emerging deep learning (DL) techniques. Innovatively, we first introduce the MINE module to effectively estimate and maximize MI through backpropagation, without clear knowledge of the channel state information. Then, we train encoder and probability generator networks with different signal-to-noise ratios to optimize the distribution locations and probabilities of the points, respectively. Note that MINE transforms the precise MI calculation problem into a parameter optimization problem. Our MINE-based schemes only optimize the transmitter end, and avoid the computational and structural complexity in traditional shaping. All the designs were verified through simulations as having superior performance for MI, among which the MINE-JCS undoubtedly performed the best for additive white Gaussian noise, compared to the unshaped QAMs and even the end-to-end training and other DL-based joint shaping schemes. For example, the low-order 8-ary MINE-GCS could achieve an MI gain of about 0.1 bits/symbol compared to the unshaped Star-8QAM. It is worth emphasizing that our proposed schemes achieve a balance between implementation complexity and MI performance, and they are expected to be applied in various practical scenarios with different noise and fading levels in the future. Full article

Applying the acoustic orbital angular momentum (AOAM) wave for underwater imaging can yield richer differential target echo information, a consequence of its spiral wavefront phase and multiple mutually orthogonal modes. In broadband AOAM wave imaging, the resolution of conventional beamforming is very low. Although sub-band processing can improve resolution, it cannot handle coherent signal sources. To further enhance the resolution of broadband AOAM wave underwater imaging and address the imaging issue of coherent signals in practice, this paper proposed a modal-domain focusing beamforming method. This paper initially established the echo signal model of broadband AOAM waves based on a uniform circular array. This was followed by the derivation of the beam output signal model. Finally, a new modal-domain focusing transformation matrix was constructed. Numerical results show that the proposed method reduces the background level of the beam pattern to −86dB in simple coherent target source imaging, compared with −40dB for sub-band methods and −70dB for plane wave focusing processing. Furthermore, under different noise conditions, the proposed method achieves high-resolution imaging of complex structures and good imaging of details. Full article

This paper examines the intellectual crises of (post-)modern philosophy, proposing a cosmopolitan philosophy as a remedy for the philosophical fragmentation that has contributed to global intellectual and cultural disintegration. Drawing on the ontological framework of Semyon Frank and enriched by Henry Corbin’s comparative philosophy and phenomenological hermeneutics, the paper establishes a new foundation for constructing a cosmopolitan philosophy within a post-foundationalist framework. Frank’s concept of “All-Unity” offers a metaphysical basis that reconciles the universal with the particular, resolving the antinomies of universality versus singularity and historicity versus non-historicity as foundational conditions of the possibility for this philosophy. Corbin’s focus on intuition and the imaginal realm further deepens this approach, enabling the integration of diverse intellectual traditions while honoring their unique and particular contributions. This paper argues that cosmopolitan philosophy can provide a coherent framework for engaging with the complexities of global thought and diverse intellectual traditions, offering a foundation for mutual understanding and addressing the existential crises of contemporary life. Full article

In an air-conditioned multinational graduate students’ office in Japan during the winter season, we examined indoor environmental conditions, occupants’ perceptions, and their acceptance levels over five consecutive days. Indoor air quality (IAQ) acceptance peaked on the third day, coinciding with the most favourable thermal sensation vote, which was “neutral” at a geometric mean indoor temperature of 25.1 °C. Aural comfort received the lowest acceptance due to ongoing construction work, but did not significantly impact overall IEQ acceptance, thus suggesting that unacceptable aspects of indoor environmental quality (IEQ) can be offset by acceptable aspects. IAQ and thermal comfort compensated for its effects, offering insights into occupants’ environmental tolerance. IAQ sensation votes and visual comfort votes exhibit a strong relationship with overall comfort, as indicated by their respective R² values. However, variations in overall comfort are primarily explained by IAQ, which has the highest R² value of 0.50, suggesting that IAQ accounts for 50% of the changes in overall occupant comfort. Non-Japanese participants had lower IEQ acceptance and a significantly higher number of complaints than Japanese participants more so in visual comfort where acceptable luminance levels were higher in Japan than other participants’ countries of origin. Thermal comfort was mutually highly accepted by both groups. Nose and eye irritation were significantly experienced by the international participants due to low RH levels but experiencing loss of concentration and lethargy was comparable in both groups (p > 0.05, t-test). We recommend global coherence in indoor environmental quality standards as is the case with drinking water standards for public health protection and seamless transitions in new indoor environments. Full article

The Mutual Optical Intensity (MOI) model is further developed to simulate the propagation of partially coherent X-ray vortex beams through free space. The intensity, phase, and amplitude distributions of the degree of coherence in the far field zone are numerically calculated using the MOI model. The effects of the coherence property and topological charge on the vortex beam are analyzed. For Gaussian Schell-model vortex beams, a vortex structure appears around the coherence singularity at the amplitude distribution of the degree of coherence relative to the central point. The number and rotation direction of the vortex structure are consistent with the magnitude and sign of the topological charge of the partially coherent vortex beam. As the spatial coherence decreases, the size of the vortex structure for the phase and amplitude distributions of the degree of coherence gradually increase until they disappear. The intensity of the dark hollow region increases with increasing topological charge. In addition, for the Laguerre–Gaussian Schell-model vortex beam, there is no singularity or vortex structure at the amplitude distribution of the degree of coherence relative to the central point. Therefore, the vortex structure around the coherence singularity at the amplitude distributions of the degree of coherence relative to the central point can be used to measure the vortex beam types and topological charge. Full article

Hypergraph analysis extends traditional graph theory by enabling the study of complex, many-to-many relationships in networks, offering powerful tools for understanding brain connectivity. This case study introduces a novel methodology for constructing both graphs and hypergraphs of functional brain connectivity during figurative attention tasks, where subjects interpret the ambiguous Necker cube illusion. Using a frequency-tagging approach, we simultaneously modulated two cube faces at distinct frequencies while recording electroencephalography (EEG) responses. Brain connectivity networks were constructed using multiple measures—coherence, cross-correlation, and mutual information—providing complementary insights into functional relationships between regions. Our hypergraph analysis revealed distinct connectivity patterns associated with attending to different cube orientations, including previously unobserved higher-order relationships between brain regions. The results demonstrate bilateral cortico–cortical interactions and suggest integrated processing hubs that may coordinate visual attention networks. This methodological framework not only advances our understanding of the neural basis of visual attention but also offers potential applications in attention monitoring and clinical assessment of attention disorders. While based on a single subject, this proof-of-concept study establishes a foundation for larger-scale investigations of brain network dynamics during ambiguous visual processing. Full article