Search Results (2,872)

Digital transformation has fundamentally reshaped hospitality distribution ecosystems, altering how hotels connect with customers, manage commercial relationships, and access market demand. While early digitalization narratives anticipated a process of disintermediation, the growing influence of platform-based intermediaries suggests a different trajectory. This study examines how digital transformation has reconfigured hotel distribution ecosystems through a comparative temporal analysis combining reservation-channel data for the 2023 operating period collected from a survey of Madrid hotels, with European benchmark studies spanning 2011–2023. Distribution channels were classified as traditional channels, direct digital channels, and digitally intermediated integrated channels (DIICs) according to their degree of technological integration and intermediary control. The harmonized evidence indicates a decline in the harmonized traditional channel, moderate growth in direct digital channels, and higher DIIC reservation shares across the harmonized benchmark evidence. Early European benchmark studies generally reported DIIC shares of approximately 22–24%, whereas the participating Madrid hotels recorded an average share of 49.3%. Overall, the harmonized evidence is consistent with a long-term shift towards digitally intermediated integrated channels, suggesting that digital transformation has reinforced digital reintermediation rather than effective disintermediation. The study contributes to the literature by providing comparative evidence of long-term changes in hotel distribution structures and by introducing the DIIC framework as an analytical lens for examining digitally mediated intermediation. More broadly, the findings support perspectives that conceptualize tourism digital transformation as a process of platformization and ecosystem reconfiguration rather than simply the adoption of new technologies. Full article

Rapid advances in nanomaterials, wearable biosensors, multimodal acquisition, and artificial intelligence have enabled increasingly integrated health-monitoring systems, yet their progression toward health digital twins remains unclear. We conducted a protocol-driven scoping review of original studies combining nano-enabled multianalyte or multimodal sensing, AI-supported analysis, and health applications. PubMed/MEDLINE, Scopus, Web of Science Core Collection, and IEEE Xplore were searched using a publication cutoff of 10 July 2026; platform execution was completed on 13 July 2026. Two reviewers independently screened 528 unique records and assessed 20 full-text reports. A 79-item charting form was jointly verified for 12 included studies. Nine studies reported reference-method or matrix-relevant analytical validation, nine included human-sample or on-body evidence, and six acquired longitudinal or continuous data. Under the author-proposed, corpus-specific functional classification, six systems were L0, five L1, and one L2; none of the 12 met the L3 or L4 functional criteria. No included study combined dynamic individual-state assimilation with prospective prediction or simulation, and none reported external-site validation or formal predictive uncertainty quantification. Because eligibility required nano-enablement, multiple analytes or channels, AI integration, and selected clinical domains, these findings do not estimate the prevalence or maturity of health digital twins in the wider literature. Progress requires longitudinal multimodal data, validated state updating, external generalization, confidence-aware AI, and prospective evaluation of governed feedback. Full article

Osteoarthritis (OA) is increasingly recognized as a mechanically driven whole-joint disease in which abnormal mechanotransduction initiates a cascade of mitochondrial dysfunction, chronic inflammation, and progressive cartilage degeneration. Among the mechanosensitive molecules identified to date, Piezo1 has emerged as a key mechanosensitive regulator linking pathological mechanical loading to intracellular calcium signaling and downstream cellular responses. Growing evidence indicates that persistent Piezo1 activation promotes mitochondrial calcium overload, excessive reactive oxygen species production, ATP depletion, mitochondrial membrane depolarization, and impaired mitophagy, ultimately amplifying chondrocyte dysfunction and extracellular matrix degradation. In parallel, mitochondrial damage triggers immunometabolic reprogramming through activation of the cGAS–STING pathway and the NLRP3 inflammasome. It also promotes pro-inflammatory cytokines, including interleukin-1β, tumor necrosis factor-α, and interleukin-6. Together, these responses may contribute to a self-perpetuating cycle of inflammation and tissue destruction. This review provides a comprehensive synthesis of recent advances regarding the role of Piezo1 in OA, focusing on the mechanistic links between mechanotransduction, mitochondrial dysfunction, mitophagy, and immunometabolic dysregulation. We further discuss the contribution of mitochondrial quality-control pathways, including PINK1/Parkin-, BNIP3-, and FUNDC1-mediated mitophagy, as well as alterations in mitochondrial dynamics involving DRP1, MFN1, MFN2, and OPA1. Emerging experimental models are discussed as valuable tools for accelerating therapeutic discovery. Finally, we critically evaluate current therapeutic strategies targeting the Piezo1–mitochondria axis, including mechanosensitive channel modulation, mitochondrial protection, mitophagy enhancement, gene therapy, biomaterial-assisted delivery, and nanomedicine. Collectively, current evidence supports the Piezo1–mitochondria–immune axis as an important mechanistic framework contributing to OA pathogenesis and as a potential therapeutic target. Integrating mechanobiology, mitochondrial medicine, and precision-engineered experimental models may facilitate the development of next-generation disease-modifying therapies capable of slowing or preventing osteoarthritis progression. Full article

Whether and how Agricultural Socialized Services (ASS) are associated with grain-growing smallholders’ general self-reported subjective well-being (SWB) remains unclear. Using 894 survey records collected in Sichuan Province, China, from 21 to 31 August 2023, we estimate ordered probit and instrumental variable two-stage least-squares models. ASS Adoption Breadth is positively associated with SWB. One additional service category is associated with a 2.73-percentage point increase in the probability of reporting the highest SWB category. The IV estimate remains positive and statistically significant (0.077, p < 0.05), conditional on the maintained instrument assumptions. ASS Adoption Breadth is also positively associated with Relative Income Comparison, Log Hired Labor Expenditure, and Plant-protection Drone Adoption. These measured behavioral indicators provide evidence consistent with the hypothesized channels of Perceived Relative Economic Gain, Market-based Labor Substitution, and technology-enabled reduction in direct occupational exposure. They do not directly measure physical workload, pesticide exposure, or health outcomes. The findings inform policies that expand smallholders’ access to agricultural services, but the mechanism interpretations remain provisional. Full article

Financial regulatory penalties are a critical tool for curbing bank violations and play an important role in safeguarding the banking system against systemic risk. This study examines the effects of regulatory penalties imposed by the People’s Bank of China (PBOC) and the National Financial Regulatory Administration (NFRA) on bank systemic risk. We construct a unique dataset of 10,462 penalty decisions manually collected from 2014 to 2023, and employ a two-way fixed effects model to identify the impact of regulatory penalties. The results show that financial regulatory penalties exert a significant mitigating effect on bank systemic risk. This effect operates through two primary channels: first, by reducing the idiosyncratic risk of individual banks; and second, by weakening the intensity of risk transmission across institutions. The risk-controlling effect is further amplified under higher regulatory pressure and stronger creditor oversight. Heterogeneity analysis reveals that the penalty effect varies by penalty type, bank level, and regulatory authority, and is more pronounced for monetary fines, penalties imposed on provincial and municipal branches, and enforcement actions conducted by the NFRA. Notably, when banking institutions and the broader banking system are already in an extreme risk state, financial regulatory penalties may cease to serve as an effective tool for containing systemic risk and preserving financial stability. Our findings suggest that strengthening the enforcement and coordination of macroprudential and microprudential supervision, along with reinforcing market discipline, can enhance the effectiveness of financial penalties in safeguarding financial stability. Full article

To investigate the feasibility of reconstructing electrocardiogram (ECG) waveforms from non-contact millimeter-wave radar measurements, a radar-based ECG reconstruction method using a CNN-BiLSTM network is presented. A synchronous acquisition platform integrating a millimeter-wave radar and a BIOPAC physiological signal acquisition system was established to collect chest-wall vibration signals and reference ECG signals. A multi-channel cross-correlation-based channel selection and temporal alignment procedure was employed to construct paired radar–ECG samples. The radar chest-wall vibration signals were filtered using an 8–30 Hz band-pass filter and then fed into the CNN-BiLSTM model, while a joint time–frequency loss function was introduced to constrain ECG reconstruction. On the self-built vital sign dataset, the reconstructed ECG achieved a correlation coefficient of 0.5631 with the reference ECG, while the mean absolute errors of heart rate and R–R interval were 1.00 BPM and 10.02 ms, respectively. These results suggest that the reconstructed signals preserve basic heartbeat timing and overall rhythm-related information, although the waveform-level agreement varies among samples and does not yet demonstrate consistent recovery of fine-grained ECG morphology. Evaluation on a public dataset further showed condition-dependent reconstruction performance under Resting, Apnea, and Valsalva conditions. Published MultiRes-LinkNet values were included only as contextual numerical references because the baseline was not reimplemented within the same experimental pipeline. Overall, the results provide preliminary evidence for the feasibility of contactless ECG reconstruction from millimeter-wave radar signals and suggest its potential value for radar-based vital sign monitoring. Full article

Culvert construction at stream crossing sites can lead to zones of high-velocity water flow which can disrupt the dispersal and connectivity of species of greatest conservation need (SGCN) in Texas. To help inform effective culvert design, the swimming performance of the following seven fish species has been measured, the first three of which are SGCN themselves, and the last four serve as hosts for glochidia of SGCN mussels (mussel genera indicated in parentheses): Colorado Roundnose Minnow, Texas Shiner, Headwater Catfish, Largemouth Bass (host for Lampsilis spp.), Green Sunfish (host for Lampsilis spp.), Channel Catfish (host for Cyclonaias spp.) and Blacktail Shiner (host for Fusconaia spp.). The primary objective was to measure the critical swimming speeds (U_crit) under a range of relevant temperatures (15, 22.5, and 30 °C) to be used in site-specific calculations of culvert water velocities (Vf). A secondary objective was to collect additional physiological endpoints of relevance to overall swimming performance, including maximum burst swimming speed (U_max), metabolic rate measurements (i.e., standard (SMR), maximum (MMR) and aerobic scope (AS)) and calculations of cost of transport (COT) and optimal swimming speed (U_opt). As expected, U_crit tended to increase with increasing temperature for several species with metabolic rate measurements following congruent trends, whereas U_max exhibited thermal independence for all species. Full article

Quantum key distribution (QKD) employs quantum states to generate shared cryptographic keys. An attacker interacting with the modeled non-orthogonal quantum signals can affect the monitored statistics, and hence they can be detected under the specified protocol assumptions, but this trait does not inherently authenticate the classical channel, and it does not prevent implementation side channels. In this work, we introduce ModPhase-8 (QUEST), a proposed QKD modulation and adaptive-receiver architecture evaluated through analytical modeling and simulation. Instead of using only a few quantum signal types, our system uses eight carefully designed signal variations created by adjusting the phase between two very short light pulses. The eight phase states are organized into four phase bases, each containing two antipodal states that encode one binary raw-key value. The enlarged signal set diversifies the physical representation of the key bit and changes the state-discrimination problem faced by an eavesdropper, but it does not increase the raw-key payload beyond one bit per successfully sifted signal. On the receiving side, the system adaptively switches between two measurement techniques based on the prevailing channel conditions. This adaptive detection mechanism enhances reliability and helps maintain low error rates even when the communication channel is affected by noise. We provide an analytical security assessment under the stated collective-attack, source, channel, receiver, and trusted-device assumptions, supplemented by attack-specific analyses of intercept–resend, beam-splitting, source-side multi-photon leakage, and selected implementation-related vulnerabilities. Simulation studies were conducted to examine the physical-layer and post-processing behavior of the proposed protocol under explicitly stated channel, receiver, detector, and finite-sample values. Under the adopted simulation model, ModPhase-8 maintains low error rates in the low- and moderate-noise operating regimes and exhibits favorable receiver-level robustness across the investigated channel conditions. The reported rate values are model-based performance estimates rather than rigorously certified secret-key lower bounds. In particular, Qiskit simulation does not establish a composable security proof or an optimal bound on Eve’s information for the exact eight-state time-bin ensemble. A protocol-specific numerical security analysis incorporating the homodyne–heterodyne measurement operators, post-selection, reconciliation efficiency, finite-size effects, and Eve’s Holevo information remains necessary before definitive rate comparisons can be made. ModPhase-8 should therefore be interpreted as a practically motivated receiver and modulation framework whose security-rate performance remains subject to further protocol-specific analysis. Full article

Estuarine and river-influenced coastal ecosystems are recognized as important sinks and channels for transfer of heavy metals into the marine environment. Continuous intake of metal pollutants could create chronic exposure situations, perhaps leading to molecular and cellular damage to resident biota, even if environmental concentrations are within regulatory limits. Thus, the incorporation of molecular and genotoxicity biomarkers into environmental monitoring programs has received growing interest, as changes in gene expression are among the earliest detectable responses to pollutant stress and may precede genotoxic effects, including DNA damage, at higher or prolonged levels of contaminant exposure. The present study aimed to determine the levels of heavy metals in the coastal zone where the Deliçay River flows into the Gulf of Iskenderun in the extreme northeastern Mediterranean Sea, Türkiye, and to investigate the genotoxic effects in the euryhaline ray-finned fish golden grey mullet (Chelon auratus). In this study, seasonal water samples (n = 3 per site per season) and C. auratus specimens (n = 10 per site per season; total n = 80) were collected from a reference site and the Deliçay estuary. Water samples were analyzed for metals (cadmium (Cd), chromium (Cr), iron (Fe), lead (Pb), and zinc (Zn)) and fish samples were analyzed with the micronucleus (MN) test for determining nuclear abnormalities and the comet test for DNA damage levels. The concentrations of Fe, Zn, and Pb in seawater exceeded the Criterion Continuous Concentration (CCC) thresholds during the summer and autumn seasons, as well as in terms of annual mean values, indicating a potential chronic ecological risk to marine organisms. From the results of the micronucleus test performed in the present study, the highest MN frequencies (10.16 ± 0.15%) and other erythrocytic nuclear anomalies [kidney-shaped (10.36 ± 0.32%), binucleated (14.20 ± 0.10%), notched (14.63 ± 0.20%), lobed (15.43 ± 0.11%), and budded (15.33 ± 0.15%)] were found along the studied coastal zone in summer season. Results of the comet test, supporting the micronucleus test results, showed the highest percentages of DNA damage determined in all seasons in the gill and liver tissues of fish sampled in the studied coastal zone. This study is the first to evaluate the effects of heavy metal-induced genotoxic stress on ecological integrity in this coastal zone using a biomarker-based approach, and the results underscore the need for comprehensive environmental monitoring and pollution reduction strategies to protect ecosystem health. Full article

Large yellow croaker (Larimichthys crocea) is an economically important marine fish, yet rapid and non-destructive discrimination between sea-caught and farmed collection-source groups remains challenging. This study developed a fish-level analytical workflow integrating YOLO11n-seg instance segmentation with visible–near-infrared hyperspectral imaging to extract relative reflectance ratios from six anatomical regions. The analytical cohort comprised 258 unique fish, including 171 sea-caught and 87 farmed individuals. Source categories were assigned according to the original capture or cage-culture collection channels. Fish identity was used as the grouping unit in five-fold internal cross-validation, and classification performance was evaluated based on out-of-fold fish-level predictions. Logistic-regression models achieved AUC values ranging from 0.985 to 1.000 across the six individual anatomical regions. The combined six-region model achieved an accuracy of 0.996 (95% CI, 0.988–1.000) and an AUC of 1.000 (95% CI, 1.000–1.000) within the present cohort. For anatomical-region segmentation, the 20-image validation set contained 140 annotated instances. Bounding-box precision, recall, mAP@0.5, and mAP@0.5–0.95 were 0.976, 0.983, 0.981, and 0.700, respectively, while the corresponding mask metrics were 0.969, 0.976, 0.972, and 0.669. These results indicate that region-specific hyperspectral information can support highly accurate internal discrimination between the two collection-source groups and provide an interpretable basis for characterizing source-associated spectral differences. However, the source labels were not independently verified, potentially influential covariates were incompletely recorded, and no independent external cohort was available. Therefore, the present findings should be interpreted as internally validated collection-source discrimination rather than verified provenance authentication or evidence of external generalizability. Full article

We review a theoretical and experimental programme with the aim of understanding two intimately related fundamental phenomena in biophysics: (i) the classical analogue of Fröhlich phonon condensation in macromolecules driven out of thermal equilibrium and (ii) the consequent activation of long-range resonant electrodynamic intermolecular forces. Both phenomena are underpinned by explicit Hamiltonian models. The first is derived by applying the time-dependent variational principle (TDVP) to the quantum Wu–Austin model, producing a fully classical Hamiltonian in action-angle variables whose nonlinear rate equations exhibit a nonequilibrium phase transition: the channelling of supplied energy into the lowest-frequency collective mode. The second is grounded in a classical electrodynamic Hamiltonian for two coupled oscillating dipoles whose normal-mode structure predicts long-range (∼$1/r^3$) resonant interactions, absent at thermal equilibrium but activated by out-of-equilibrium collective oscillations. We also discuss a complementary Hamiltonian approach that connects Fröhlich’s rate equations directly to Hamilton’s equations of motion, clarifying the role of bath-mediated nonlinear coupling and the conditions for strong condensation at room temperature. In addition, the TDVP is applied to a Davydov–Holstein–Fröhlich Hamiltonian describing electron–phonon motion along the backbone of a specific DNA sequence and its cognate restriction enzyme, EcoRI: the time-domain Fourier cross-spectrum of the resulting electron currents exhibits a sharp co-resonance peak for the canonical recognition sequence that disappears upon randomisation, providing a sequence-specific electrodynamic signature of DNA–protein recognition. Experimental evidence from THz near-field spectroscopy, fluorescence correlation spectroscopy, and direct observation of protein clustering is reviewed in relation to these theoretical predictions. The results establish a coherent physical picture suggesting that metabolic energy supply can play a role in driving macromolecules into coherently oscillating states that activate selective, distance-reaching electrodynamic forces capable of contributing to the organisation of biochemical reactions in living matter. Full article

Although natural resources and geographical factors limit herders’ employment options, the development of digital rural helps herding households compete on an equal footing by expanding employment opportunities. Using survey data collected from 2790 herder households in 26 counties across Gansu, Qinghai, Sichuan and Tibet from 2023 to 2025, this study examines the relationship between county-level digital rural development and non-farm employment. We find that digital rural development is positively associated with the likelihood that household heads engage primarily in non-farm employment. This finding remains stable across a series of robustness and endogeneity checks. Moreover, the positive association is weaker in areas with a larger primary-industry base and among households engaged in forage cultivation, suggesting that local production structures and household labor commitments constrain the conversion of digital opportunities into employment diversification. Further analysis indicates that digital finance and digital consumption are two potential channels through which digital rural development supports non-farm employment. These findings highlight that the employment benefits of digital development depend not only on digital access but also on the flexibility of household labor allocation and the availability of non-farm opportunities in pastoral areas. Full article

This study aimed to investigate the regulatory effects of dietary dandelion supplementation on the ruminal physiological status of lambs fed a high-concentrate diet. Twenty-two 6-month-old female crossbred lambs with an initial body weight of 32.05 ± 0.43 kg were randomly assigned to two groups (n = 11 per group): the HC group (fed a high-concentrate basal diet) and the DD group (basal diet supplemented with 2 g/kg dandelion powder), with a 14-day adaptation and 60-day experimental period. The results showed that compared with the HC group, dandelion supplementation significantly improved lamb growth performance and modulated ruminal fermentation parameters and tissue morphology. For inflammatory indices, the concentration of interleukin-10 (IL-10) was significantly increased, while the concentrations of interleukin-1β (IL-1β), lipopolysaccharide (LPS) and histamine (HIS) were significantly decreased (p < 0.05). Meanwhile, dandelion supplementation upregulated the mRNA expression of ruminal epithelial tight junction proteins and hexokinase II (HK-II), while downregulating the mRNA expression of myeloid differentiation factor 88 (MyD88), voltage-dependent anion channel 1 (VDAC1), inositol 1,4,5-trisphosphate receptor (IP3R), NLR family pyrin domain containing 3 (NLRP3), and caspase-1. Metagenomic analysis revealed that dandelion supplementation did not alter ruminal microbial α-diversity, but slightly modulated community composition and functional profiles. The abundances of dominant phyla Bacteroidota and Bacillota showed only slight fluctuations, while fiber-degrading genera (Xylanibacter, Quinella, Selenomonas) showed a trend toward enrichment, and proteolytic taxa were decreased. CAZyme analysis revealed an upward trend in families CE4, CE8, GH32, and GH13_46 (pectin/starch degradation) and a downward trend in GH73, GH27, and GT14 (oligosaccharide/peptidoglycan/polysaccharide metabolism) in the DD group. KEGG orthology annotation suggested that nominal KO differences were mainly associated with carbohydrate metabolism pathways, including starch and sucrose metabolism and peptidoglycan biosynthesis. None of these features, however, remained significant after FDR correction (raw p < 0.05; all q > 0.05). Collectively, dietary dandelion supplementation was associated with alterations in ruminal physiological status and microbial community in lambs fed a high-concentrate diet, providing foundational data for dandelion application in lamb diets under short-term feeding conditions. Full article

Land-based hyperspectral imaging provides high spatial and spectral resolution for detecting camouflaged targets, but practical deployment remains limited by strong target background spectral similarity, scarce annotated hyperspectral samples, and the computational cost of full-band processing. To address these issues, this paper proposes HCTDNet (Hyperspectral Camouflaged Target Detection Network), a land-based hyperspectral image analysis framework. The method first employs band extraction for data dimensionality reduction, compressing multi-channel hyperspectral images into 3-channel virtual RGB representations, which reduces spectral redundancy while preliminarily enhancing camouflaged target saliency. A pre-trained RGB camouflaged target detector is then adopted as the backbone model, with its parameters frozen to maintain stability, while trainable modality-specific prompts are learned to improve training efficiency. Finally, model fine-tuning is performed using a self-constructed camouflaged target dataset to enhance robustness in detecting camouflaged targets within virtual RGB images. During inference, preprocessed hyperspectral images are fed into the model to generate detection results for camouflaged target regions. The experiments performed on our self-collected land-based hyperspectral dataset with camouflaged targets reveal that HCTDNet achieves superior detection performance compared with seven classical hyperspectral target detection methods while maintaining an average inference speed of approximately 16 FPS. The proposed framework provides an efficient and near-real-time applicable solution for land-based hyperspectral camouflaged target detection, showing significant practical potential. Full article

Calligonum polygonoides is a rare desert shrub that is of high ecological importance in Egypt, yet its habitat requirements and physiological responses to environmental variability remain poorly understood, particularly under increasing climatic and anthropogenic pressures. To address this knowledge gap, this study integrates GIS-based habitat suitability modeling with hyperspectral leaf spectroscopy to evaluate the environmental factors associated with species distribution and leaf optical responses across two ecologically contrasting wadis (Wadi El-Galala and Wadi El-Assiuty). Environmental layers (DEM, EC, TSS, pH, temperature, rainfall, humidity, evaporation) were integrated using a multi-criteria evaluation framework, while plant cover, density, and spectral measurements were collected from 14 field plots. The results show that C. polygonoides favors moderately elevated zones characterized by low salinity, slightly alkaline soils, and intermediate climatic conditions. Approximately 24.3% of the landscape was classified as highly suitable, primarily along channel belts and alluvial fans with improved drainage and reduced salt accumulation. Spectral signatures showed descriptive differences between the two wadis. Plants from Wadi El-Galala showed relatively higher NIR reflectance and more pronounced SWIR water-absorption features compared with Wadi El-Assiuty, which may reflect differences in leaf structure and water status under contrasting habitat conditions. These spectral patterns were broadly consistent with the spatial suitability outputs and provide complementary descriptive information on leaf optical properties. Habitat suitability modeling showed that 91.7% of the recorded field occurrence points (33 out of 36 shrubs) were located within high-suitability zones, while no occurrences were recorded in low-suitability areas. This pattern indicates spatial agreement between observed occurrences and predicted suitability classes, but it should not be interpreted as formal model validation because absence data and independent validation records were not available. Overall, the findings provide preliminary spatial and spectral information that may support future field verification and site-specific conservation planning for C. polygonoides in the investigated wadis. Full article