Search Results (1,274)

Background: Diabetic foot ulcers (DFUs) and lower extremity amputations are major contributors to morbidity and mortality in individuals with diabetes. Among patients undergoing active cancer treatment, the risks are compounded by immunosuppression, peripheral neuropathy, and vascular complications. Even minor foot infections or wounds in these patients can necessitate the suspension of cancer therapy, with potentially lifethreatening consequences. This study evaluated the impaqt of integrating symptom-focused patient education with coordinated podiatric care to reduce DFUs and amputations in this highrisk population with concurrent cancer and diabetes. Methods: A five-year retrospective review was conducted at a National Cancer Institute (NCl)designated comprehensive cancer center as part of the Novel Limb Preservation Initiative. The cohort included patients with Type II diabetes undergoing treatment for prostate, breast, colorectal, lymphoma, leukemia, thyroid, or lung cancers. Patients were assigned targeted educational modules based on self-reported diabetic foot symptoms. Podiatric care was individualized according to each patient's signs and symptoms, including routine diabetic foot examinations and close, timely monitoring when indicated. Results: The intervention yielded a DFU incidence of 2. 8% and an amputation rate of 0. 43%, both lower than national benchmarks. Enhanced patient engagement through diabetic foot symptom-focused education and earlier detection of foot complications-including diabetic foot ssues that may appear minor to laypersons-contributed to these improved outcomes. Conclusion: Integrating diabetic foot symptom-focused education with proactive podiatric monitoring significantly reduced DFUs and amputations in this high-risk population. This model, developed under the Novel Limb Preservation Initiative, offers a scalable strategy for broader implementation, particularly in high-risk communities, including Hispanic, African American, low socioeconomic, and rural populations across the United States. Full article

Background/Objectives: Culturally responsive care requires both intercultural communication competence (ICC) and empathy; however, these constructs are often examined separately in nursing research. This study aimed to (i) describe nurses’ ICC and empathy levels, (ii) test the association between ICC and empathy, and (iii) examine group differences by selected demographic and professional variables. Methods: A quantitative, cross-sectional correlational design was conducted with 300 nurses recruited from state and private hospitals. ICC was measured using the Arasaratnam Intercultural Communication Competence Scale (cognitive, affective, and total), and empathy was assessed using the 18-item Jefferson Scale of Empathy (compassionate care, perspective taking, standing in the patient’s shoes, and total). Data were analyzed with descriptive statistics, Pearson correlations, independent-samples t-tests, and one-way ANOVAs with Scheffé post hoc tests (α = 0.05). Results: Both ICC and empathy were above the scale midpoint. Cognitive ICC (M = 4.71, SD = 1.42) exceeded affective ICC (M = 4.35, SD = 1.34), and total empathy was high (M = 4.50, SD = 0.90), with compassionate care as the highest subscale (M = 4.60, SD = 1.10). ICC total was moderately correlated with total empathy (r = 0.607, p < 0.05); affective ICC correlated with compassionate care (r = 0.455) and perspective taking (r = 0.493). Male nurses reported higher ICC than female nurses (p < 0.05), while empathy did not differ by gender. Younger nurses (20–29) scored higher in ICC and empathy than older groups, and nurses with ≥28 years of experience also showed elevated levels. Nurses who willingly chose nursing had higher ICC and empathy across dimensions (all p < 0.001). Hospital type showed minimal differences except for “standing in the patient’s shoes” (private > state, p = 0.04). Conclusions: ICC and empathy were generally high and interrelated among nurses, with meaningful variation across workforce characteristics. Training should emphasize experiential and reflective approaches to strengthen affective ICC and perspective taking, while organizational strategies should foster intrinsic motivation and support professional development across career stages. Full article

Global aging is accelerating, with the proportion of the population aged 60 and above projected to reach 22% by 2050. In cold-region communities, the visual landscape environment is closely associated with the health of older adults, particularly showing associations with blood pressure (BP) and emotion states. However, associations between these factors across different landscape spaces and potential gender differences remain underexplored. This study utilized eye-tracking experiments to collect visual attention data from older adults in three types of cold-region community spaces: inter-building spaces, walkways and squares. The ground, buildings, trees, lawn, and the sky were identified as the primary Areas of Interest (AOIs). The Profile of Mood States (POMS) scale was used to assess emotion during walking experiments, revealing suggestive gender–environment interaction characteristics. Systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) were measured, and a Mann–Whitney U test indicated that DBP in community squares exhibited significant environmental dependency (U = 114.5, p = 0.004, r = 0.44). Hierarchical Linear Models (HLMs) revealed that, after controlling for individual differences, the number of fixation points on ground was independently associated (i.e., independent of measured individual characteristics) with elevated SBP ($\gamma =0.31, p=0.011$), while fixation on trees was associated with reduced SBP ($\gamma =-0.24, p=0.018$). Furthermore, gender moderation effects were observed: the association between ground fixation and SBP was stronger in females ($\gamma =0.18, p=0.022$), whereas the association between sports facilities and DBP was stronger in males ($\gamma =0.29, p=0.009$). Based on these findings, evidence-based design strategies are proposed, including the optimization of ground safety, gender-differentiated planting configurations, and targeted layouts for sports facilities. These results provide empirical support for age-friendly community design in cold regions. Full article

Arctic sea ice is a critical indicator of global climate dynamics, directly influencing maritime navigation, polar biodiversity, and offshore engineering safety. The precise mapping of diverse ice types, such as frazil ice, slush, melt ponds, and open water, is essential for environmental monitoring; however, it remains a formidable challenge in satellite remote sensing. These difficulties arise from low-contrast imagery, overlapping spectral signatures, and the subtle textural nuances characteristic of polar regions. Traditional entropy-based thresholding techniques often falter when segmenting these complex scenes, as they typically rely on Gaussian distribution assumptions that do not align with the stochastic nature of Arctic data. To address these limitations, this paper presents a novel unsupervised segmentation framework based on symmetric cross-entropy (SCE). Unlike standard directional measures, SCE provides a more robust objective function for multi-level thresholding by simultaneously maximizing intra-class cohesion and minimizing inter-class ambiguity. The proposed method uses an optimized search strategy to identify intensity levels that best delineate complex Arctic features. We conducted an extensive entropy-based comparative study that benchmarked SCE against 25 state-of-the-art entropy measures, including Shannon, Kapur, Rényi, Tsallis, and Masi entropies. Our experimental results demonstrate that the SCE method: (i) achieves superior accuracy by consistently outperforming established models in segmentation precision and boundary definition; (ii) provides visual clarity by producing segments with significantly reduced noise, making them ideal for identifying small-scale melt ponds and slush zones; and (iii) demonstrates computational robustness by providing stable threshold values even in datasets with non-Gaussian class distributions and poor illumination. Ultimately, these improvements deliver high-quality ice feature data that enhance risk assessment, operational planning, and predictive modeling. This research marks a major step forward in Arctic sea studies and introduces a valuable new tool for wider image processing and computer vision communities. Full article

Granary systems formed a core institutional foundation of state governance, famine relief, and social stabilization in premodern China. Using the complete corpus of the Twenty-Six Dynastic Histories, this study employs digital humanities methods—including text preprocessing, word-frequency analysis, collocation analysis, time-series comparison, and geographic co-occurrence analysis—to examine the long-term evolution and institutional structure of three major granary types: ever-normal granaries (ChangpingCang), charitable granaries (Yicang), and community granaries (Shecang). The results reveal significant temporal and spatial variation closely associated with dynastic stability, fiscal capacity, and disaster conditions. Ever-normal granaries evolved from early formation in the Western Han to institutional consolidation in the Tang, peak expansion in the Song, and functional diversification thereafter, operating as a centralized mechanism integrating price regulation, fiscal management, and famine relief. Charitable and community granaries, by contrast, display increasingly differentiated roles, reflecting a shift toward localized and socially embedded relief in later periods. Spatial analysis further demonstrates a hierarchical deployment pattern centered on political and agrarian cores and extended through transport corridors and frontier zones. Overall, the study highlights a multilayered relief system combining state authority and social participation, offering a data-driven reinterpretation of Chinese charity and governance. Full article

Currently, the B-cell response patterns induced by viral antigens in avian disease models and their detailed immunological characteristics still require comprehensive elucidation at the single-cell level. In this study, we employed single-cell sequencing (scRNA-seq) and B cell library technology to conduct an in-depth analysis of B cells in the spleens of mice with inactivated duck hepatitis A virus type 1 (DHAV-1) as model antigen. This study aimed to investigate the immunological characteristics of the virus antigen in the mouse model and characteristics of B-Cell Receptors. The results showed that the DHAV-1 group had distinct changes in splenic B cell subset counts, proportions, and intercellular communication. Additionally, an increased trend in communication strength between Gm26917+B and Gm11837+B cells was observed, with enriched expression of C-X-C motif chemokine ligand (CXCL) and lymphotoxin (LT) detected in the DHAV-1 group. Furthermore, the DHAV-1 group exhibited a prominent combination of the IGHV1 family and IGHV3-1/IGHJ3 in the heavy (H) chain variable region. Compared with the CK group (negative control group), the amino acid sequence length and diversity of the CDR3 region in the DHAV-1 group exhibited a decreasing trend. In summary, our findings characterize the immunological features of splenic B cells in mice after immunization with inactivated DHAV-1, and provide a preliminary characterization of DHAV-1-induced B cell transcriptional states and BCR repertoire features, generating testable hypotheses for subsequent mechanistic investigations of B cell-mediated immune responses to viral antigens. Full article

Soliton molecules offer practical advantages in high-speed optical communication, precision spectroscopy, and micromachining. In all-normal dispersion fiber lasers, group velocity dispersion broadens the pulse duration, hindering the attainment of the nonlinearity dispersion balance essential for soliton molecule formation. Consequently, the generation of soliton molecules in such lasers is a technically demanding task. Here, we report an all-normal dispersion fiber laser, mode-locked via nonlinear polarization evolution (NPE) and Lyot filtering. By adjusting the intracavity polarization, this setup allows direct control over pulse interactions, enabling the generation of stable soliton molecules, soliton bound states, and multipulse states. A spectral modulation period of up to 0.95 nm is achieved. In addition, different types of solitons, such as soliton singlets and soliton molecules in tightly and loosely bound states, are observed. Full article

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Full article

Poetry, the bearer of collective memory in the Turkish state tradition, has been used as an art and administrative tool for generations in the Ottoman dynasty. The fact that 27 of the 36 Ottoman sultans wrote poetry and 10 sultans owned a “divan” (poetry book) suggests that this art served a political function for the dynasty. This study aims to investigate whether the sultan poets used poetry as a religiously based political propaganda tool to appear pious and artistic and to reinforce the legitimacy of their reign. Because the poems in these works are noteworthy as texts that promote the image of the sultan as a just, pious, and powerful ruler, legitimise Islamic expansionist policy (jihad), and aim to perpetuate cultural superiority. The study includes an analysis of relevant examples selected from the poems of ten Ottoman sultans (Mehmed II, Bayezid II, Selim I, Suleyman I, Selim II, Murad III, Ahmed I, Osman II, Ahmed III, Selim III). It is argued that these types of poems by Ottoman sultans, besides being the result of a simple literary pursuit; they served as a means of communication that reinforced the religious and political legitimacy of the sultans. Full article

(Li_0.4Co_0.2Ni_0.2Cu_0.2Zn_0.2)WO₄ high-entropy ceramics were prepared by a conventional solid-state reaction route. This study thoroughly explores the interrelationships between their crystal structure, bond properties, and microwave dielectric characteristics. X-ray diffraction analysis verified that all specimens crystallized in a single-phase ZnWO₄-type structure. According to Rietveld refinement of the XRD data, the lattice parameters are affected by the ionic radii of the constituent elements, confirming their dissolution and random distribution at Zn sites. Relative density exhibited a strong dependence on sintering temperature. Bonding analysis highlights the crucial role of the W–O bond in governing the dielectric response of the (Li_0.4Co_0.2Ni_0.2Cu_0.2Zn_0.2)WO₄ (LCNCZW) ceramics. Moreover, sinterability can be improved through optimizing the sintering process. Notably, samples sintered at 850 °C attained suitable dielectric performance, characterized by εᵣ = 11.697 ± 0.204, Q × f = 23,851 ± 0.126 GHz, and τ_f = 21.335 ± 0.232 ppm/°C. These results demonstrate that high-entropy design can effectively improve the sinterability and microwave dielectric performance of wolframite-type ceramics, offering a promising strategy for the development of microwave dielectric ceramics for communication devices. Full article

In cooperative multi-agent reinforcement learning (MARL), communication can address the challenges of partial observability and environmental non-stationarity by conveying environmental features and decision intents, respectively. However, existing methods either focus on only one type of information—failing to tackle both challenges simultaneously—or conflate these signals, causing agents to confuse environmental context with decision intents. This paper introduces Disentangling Environment and Decision messages for Multi-Agent Communication (DEDMAC), a framework that explicitly separates these two information types into two distinct message streams and processes them independently. Specifically, environment messages are integrated into long-term memory to resolve partial observability, while decision messages provide instantaneous intent signals to mitigate non-stationarity and facilitate coordination. To prevent semantic confusion between the two message streams, we employ mutual information constraints to ensure semantic disentanglement. Furthermore, we design a mechanism that leverages global information to correct intent biases in decision messages resulting from limited local perspectives during generation. Evaluations across complex multi-agent benchmarks demonstrate that DEDMAC significantly outperforms state-of-the-art communication-based methods. These findings indicate that the explicit separation and specialized processing of environment and decision semantics are critical for achieving optimal performance in dynamic, collaborative multi-agent systems. Full article

Artificial neural network and neuron models have made significant contributions to the area of neurodynamics. Investigating the dynamics of artificial neurons and neural networks is vital in developing brain-like systems and understanding how the brain functions. Neural network models and memristive neurons are currently demonstrating a lot of promise in the study of neurodynamics. In order to model the dynamics of biological synapses, this study explores the complex dynamical behavior of a discrete fractional Hopfield-type neural network using a flux-controlled memristive element with periodic memductance. Hyperbolic tangent and sine are the heterogeneous activation functions that are implemented in the proposed system to improve nonlinearity and replicate various forms of brain activity. Stability and bifurcation analyses are used to illustrate the nonlinear dynamical nature of the constructed network model. We examine how the fractional order $\left(\nu \right)$ and periodical memductance aspects influence the dynamics of the system to emphasize the emerging complex phenomena like multi-layered dynamics and the presence of several distinct dynamical states throughout the system variables. Randomness and complexity of the time series data for the proposed system are illustrated with the help of approximate entropy analysis. These findings could help researchers better understand brain-like memory networks, neuromorphic computers, and the theoretical study of neurological and mental abilities. The study of multi-layer attractors can be useful in advanced sensory devices, neuromorphic devices, and secure communication. Full article

Context-aware mobile applications operating in environments with intermittent or unreliable connectivity must support offline-first behavior while preserving consistent decision-making and timely synchronization. Traditional cloud-centric architectures often fail to provide adequate availability, responsiveness, and reliable context reasoning under such conditions. This paper presents CAMS-F Edge DTN, an edge-centric runtime designed to support offline-first context-aware applications operating under intermittent connectivity. The proposed approach extends the CAMS domain-specific language (DSL) with declarative policies for semantic reconciliation, opportunistic synchronization, and context-aware conflict resolution. The runtime integrates Conflict-Free Replicated Data Types (CRDTs), opportunistic communication channels such as Bluetooth and Wi-Fi Direct, and MQTT-SN messaging to enable robust data exchange across mobile, vehicular, and edge nodes. CAMS F-Edge DTN supports offline-first execution by allowing applications to evaluate contextual rules locally and reconcile distributed state asynchronously when connectivity becomes available. The approach is evaluated through controlled experiments and case studies in rural logistics and healthcare distribution scenarios. The experimental results show that the proposed architecture maintains 96–99% operational availability under intermittent connectivity and up to 100% availability during fully offline operation, while achieving low-latency local reasoning (<10 ms median latency) and deterministic state convergence through CRDT-based synchronization mechanisms. Full article

The cervicovaginal microbiome (CVMB) is pivotal in maintaining the homeostasis of the lower female genital tract and has emerged as a significant modulator of cervical carcinogenesis. Although persistent infection with high-risk human papillomavirus (HR-HPV) is a prerequisite for the development of cervical intraepithelial neoplasia (CIN) and subsequent cervical carcinoma, it remains insufficient alone to drive oncogenesis. Accumulating evidence suggests that alterations in the CVMB composition profoundly impact HPV persistence, local immune responses, and disease progression. A vaginal microbiota dominated by Lactobacillus species, most notably Lactobacillus crispatus, correlates with low microbial diversity, robust immune regulation, and facilitated HPV clearance. Conversely, microbial dysbiosis—characterized by Lactobacillus depletion and a concomitant proliferation of anaerobic taxa, typical of Community State Type (CST) IV and Lactobacillus iners-dominated profiles—is strongly associated with chronic inflammation, oxidative stress, epithelial barrier compromise, and an elevated risk of CIN progression. This review synthesizes current evidence regarding the multifaceted interactions among the cervicovaginal microbiome, HPV pathogenesis, immune dysregulation, and oxidative stress in the etiology of CIN. Elucidating these intricate host–microbiome dynamics may precipitate the discovery of novel microbiome-derived biomarkers, ultimately informing innovative prophylactic and therapeutic interventions for cervical cancer. Full article

With the increasing importance of securing quantum communication networks, practical and robust entity authentication is a critical requirement. Accordingly, we propose and experimentally validate a quantum entity authentication (QEA) protocol specifically designed for integration with BB84-type quantum key distribution (QKD) workflows and existing terminal architectures. We analyze the protocol’s security against intercept–resend man-in-the-middle (MitM) impersonation, showing that an unauthenticated adversary induces a characteristic 25% correlation error and that the rejection probability approaches unity as the number of detected authentication events increases. For practical realization, the protocol is deployed using weak coherent pulses (WCPs) with decoy-state estimation to bound single-photon contributions and mitigate photon-number-splitting (PNS)-enabled leakage. The system is demonstrated over a field-deployed fiber link of approximately 20 km with ~8 dB optical loss using signal/decoy intensities of ~0.5/~0.15 and sending probabilities 0.88/0.10/0.02 (signal/decoy/vacuum). Across both verification directions, stable operation is observed with quantum bit error rate (QBER) typically fluctuating between 1% and 4% while the sifted key rate remains constant over time. These results provide an experimental basis for integrating physical-layer entity authentication into deployed quantum communication networks. Full article