Search Results (1,669)

Recent lattice studies have revealed that the color flux tube between static quark–anti-quark pairs exhibits an excess entanglement entropy (flux-tube entanglement entropy, FTE²) that scales linearly with the quark separation L. In this paper, we demonstrate sim-ilar behavior in a string-net model based on SU(2)_k fusion categories, where the nontriv-ial object j = 1/2 (analogous to color charge) cannot exist in isolation due to the fusion rules, naturally exhibiting “confinement”. We compute the entanglement entropy of the flux tube connecting two j = 1/2 objects using the microcanonical (equal-weight) pre-scription S(R) = ln(dim(Hom(R))) and find an entropy density σ_k = ln d_1/2 = ln(2cos\({\frac{\pi}{k+2}}\)). For 𝑘 = 3, the category reduces to the Fibonacci case, yielding an entropy density σ₃ = ln φ ≈ 0.4812 (φ is the golden ratio), which is qualitatively comparable in magnitude to the scale inferred from lattice studies and the entropy surface mechanism. Under a thermalization assumption for the fusion-channel degrees of freedom, minimiz-ing the free energy F = (𝒥 \({-}\) Tσ_k)L yields a confinement–deconfinement transition at (T_c = 𝒥/σ_k), which is first-order-like (tension sign reversal) rather than a continuous crit-ical transition. The parameter k offers a tunable knob, making the SU(2)_k family a com-putable laboratory for entropic confinement. The predicted entropy-density jump can be directly tested in quantum simulator platforms (e.g., Rydberg arrays or superconducting circuits) that realize Fibonacci anyonic models. Full article

Background: Glioblastoma (GBM) is a primary malignant tumor of the central nervous system and has a high lethal rate despite therapeutic advances. Although immunotherapies have achieved great success in solid tumors, the highly immunosuppressive tumor microenvironment and the blood–brain barrier (BBB) obstruction hinder the development of immunotherapies for GBM. In this study, we innovatively developed a nanohydrogel composite vaccine (nanoCOM-GEL) for GBM immunotherapy via intranasal immunization. Methods: The nanoCOM-GEL used GelMA as the hydrogel matrix and was co-formulated with antigenic peptides, the BBB-penetrating peptide (peptide 22), as well as immune cell stimulants and chemokines. The efficiency of this vaccine in bypassing the BBB and its capacity to induce anti-GBM immune responses were evaluated in vitro and in vivo. Results: The nanoCOM-GEL vaccine demonstrated superior BBB-bypassing and BBTB-penetrating capabilities, potent immunostimulatory activity, and effective GBM-targeting efficacy, as validated in both cellular and animal models. In an orthotopic GBM mouse model (n = 8 per group), intranasal immunization with nanoCOM-GEL significantly extended median survival from 21 days (control group) to more than 60 days (nanoCOM-GEL group), representing a 2.8-fold increase (p < 0.001). The vaccine markedly inhibited tumor growth, as evidenced by an 82.5% reduction in tumor tissue at day 21 compared to controls (p < 0.01). Mechanistically, nanoCOM-GEL increased intratumoral CD8⁺ T cell infiltration by 9.5-fold and upregulated DCs by 6.4-fold, while simultaneously reducing intratumoral M2-type tumor-associated macrophages by 79.3% (p < 0.001), effectively reshaping the immunosuppressive tumor microenvironment. Conclusions: This innovative nanoCOM-GEL vaccine achieved potent anti-GBM therapeutic efficacy and provided a promising strategy for effective GBM immunotherapies. Full article

Environmental variables and eyrie site characteristics may influence reproductive output, yet their associations with Barbary falcon (Falco peregrinus pelegrinoides) productivity remain poorly understood in the Arabian Peninsula. We quantified fledgling production at 59 monitored eyries in northwestern and southwestern Saudi Arabia during the 2026 breeding season. Poisson generalized linear models evaluated February–May climatic conditions, pair type, eyrie cliff–wind alignment (CosDiff), and elevation and eyrie height where available. Monthly analyses for February–April and COM–Poisson sensitivity models assessed temporal consistency and robustness to departures from Poisson equidispersion. Mean productivity was 1.97 fledglings per eyrie (SD = 1.25; range = 0–4). In the best ranked additive model, a one standard deviation increase in seasonal mean wind speed (0.678 m s⁻¹) was associated with 19.5% lower expected productivity (IRR = 0.805, 95% CI = 0.660–0.982, p = 0.032), and more direct eyrie cliff alignment with incoming prevailing wind was associated with 18.7% lower expected productivity (IRR = 0.813, 95% CI = 0.677–0.976, p = 0.026). Monthly wind estimates were comparable across February–April. These findings may inform preliminary release site evaluation, but multi-year studies with cliff-scale measurements are needed to determine whether these associations persist across breeding seasons. Full article

In the context of global energy transition and climate change, exogenous energy shocks (such as energy price volatility, renewable energy uncertainty, and increasing power demand) pose growing challenges to power system carbon neutrality. However, existing studies mainly focus on optimizing emission-reduction pathways while neglecting system resilience under energy shocks. This study applies a coupled LEAP-NEMO model for Guangdong Province, integrating demand growth, generation evolution, dispatch optimization, system costs, and carbon constraints. Five scenarios (BAS, COM, COM_ES1, COM_ES2, and COM_ES3) are established to assess the impacts of exogenous energy shocks on carbon-neutral transition pathways. The results show that under COM scenario, Guangdong’s power system’s carbon emissions will peak by 2030 and reach net-zero by 2055. Different energy shocks produce substantially different effects on the carbon-neutral transition. Fossil fuel price shocks (COM_ES1) have limited impacts, with cumulative emissions changing by only 2.1% relative to COM. Renewable energy volatility (COM_ES2) reduces wind and solar generation and raises cumulative emissions by 73.7%, preventing carbon neutrality by 2060. Demand growth (COM_ES3) poses the most severe challenge, with cumulative emissions reaching 2.04 times those of the COM scenario. Resilience analysis further shows that renewable energy volatility causes the largest deterioration in reserve margin performance, while demand growth has the strongest effects on emissions and cost performance. These results identify renewable generation uncertainty and electricity demand growth as the key risks to a smooth carbon-neutral transition, highlighting the need for coordinated deployment of energy storage, nuclear power, flexible resources, and demand-side management. Full article

Consumers face increasing pressure to choose more environmentally sustainable foods and evidence-based behavioural interventions can support consumers in this task. This study seeks to provide insight into intervention design in the Australian context using two behavioural frameworks: the Capability, Opportunity, and Motivation Model of Behaviour Change (COM-B) and the Transtheoretical Model of Behaviour Change (TTM). Consumer data were collected through an online survey conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) from November 2021 to February 2022 (n = 1307). Behavioural barriers affecting environmentally sustainable food choice (based on COM-B) were assessed, and chi-square tests of independence were used to identify barriers and other participant variables associated with different ‘stages of change’ (based on TTM). The top three barriers reported were: “know how to identify these food products” (n = 837, 64%); “have more information about these food products” (n = 640, 49%); and “have more access to these food products” (n = 614, 47%). Regarding intent to make environmentally sustainable food choices, the most common ‘stages of change’ were ‘Action’ (n = 573), ‘Maintenance’ (n = 411), and ‘Pre-Action’ (n = 266). These groups were found to be significantly associated with participant characteristics, including age, diet quality, and climate concern, as well as specific COM-B barriers. For example, Action-stage individuals were found to have a statistically significant and strong association with statements relating to product identification (χ2(2) = 43.54, p = 0.017, V = 0.19) and requiring more triggers to prompt action (χ2(2) = 28.67, p = 0.017, V = 0.15). Based on the presented findings, which were collected using a dual COM-B and TTM framework, a range of behaviour-stage tailored behavioural intervention approaches are discussed that may ease the consumer transition to more consistent environmentally sustainable food choices. Full article

Commodity futures markets exhibit pronounced non-stationarity, nonlinearity, and multifractal characteristics that challenge traditional linear models. We employ a multiscale framework integrating four methodologies—MF-DCCA, PG irreversibility index, MSWPE, and JS-divergence segmentation—to analyze these features using daily closing prices for WTI crude oil, agricultural commodities (US soybeans, meal, oil, and wheat), the US dollar index, and Chinese No. 2 soybeans, spanning from 2 January 2018 to 1 October 2025, sourced from Investing.com and Matteo Iacoviello’s GPR database. The analysis yields three key results. First, scale dependence varies across commodities and is shaped by supply adjustment elasticity: energy markets show scale-dependent amplification and directional sign reversals, while agricultural markets maintain near-monofractal structures. Second, multiple methods converge on a characteristic time scale of approximately 20 days, linking physical logistics rhythms with financial pricing. Third, the persistence of structural reconstruction after shocks depends on systemic penetration depth, with exogenous macroeconomic uncertainty exerting stronger and more lasting effects than market-internal events. Together, supply elasticity, physical logistics rhythms, and systemic penetration depth constitute the three fundamental determinants of nonlinear commodity futures dynamics, with implications for cross-commodity allocation, multi-horizon risk management, and geopolitical scenario analysis. Full article

Fully actuated multirotor UAVs (FA-mUAVs) have attracted attention for aerial physical interaction because they generate translational forces without tilting the vehicle, thereby supporting interaction precision and payload-transportation stability. However, this capability relies on an accurate center-of-mass (CoM)-dependent thrust-to-wrench allocation geometry. When the CoM shifts due to payload variation or physical interaction, the nominal allocation geometry produces incorrect moment arms and recurrent unintended torques. Existing robust and robust-adaptive approaches compensate for these effects through the input channel while leaving the allocation geometry unchanged. Conversely, allocation-level CoM correction addresses the geometric source of the mismatch but does not by itself provide transient robustness during estimator convergence or against non-CoM disturbances. This paper proposes a transient-buffered allocation-geometry adaptation framework that addresses these two limitations within a single architecture. The framework combines an input-channel robust layer with allocation-level CoM adaptation: the robust layer buffers instantaneous mismatch and residual disturbances, while the adaptation layer processes the filtered compensation signal generated by the robust layer through the CoM-dependent regression to estimate the CoM and update the allocator, without assuming a unique separation of CoM-induced and non-CoM components. Stability analysis establishes boundedness and phase-dependent convergence of the CoM-estimation error. Real-flight experiments show that adding the CoM-estimation/allocation-update path to a retained disturbance-observer (DOB) robust baseline improves attitude regulation and reduces rotational compensation demand. Full article

Background/Objectives: People Living with HIV (PLWH) often have comorbidities require polypharmacy, increasing the risk of adverse events (AEs) associated with drug–drug/drug–supplement interactions (DDIs/DSIs). However, DDIs and DSIs, including those involving antiretrovirals (ARVs), and their related effects have not been exhaustively assessed. This study aimed to determine, in HIV patients on HAART who are taking multiple medications, the prevalence of DDIs and DSIs involving both ARVs and non-ARV co-medications, and their clinical relevance and consequences. Methods: In this longitudinal observational study, PLWH receiving HAART were consecutively enrolled at the University Hospital of Salerno and followed up during scheduled visits. Demographic, clinical, and pharmacological data were collected. DDIs/DSIs were identified using Drugs.com, Lexicomp, and the Liverpool HIV Interaction Checker. Interactions classified as major (Drugs.com), consider therapy modification or avoid combination (Lexicomp), and do not coadminister (Liverpool) were deemed highly clinically relevant. This assessment was supplemented with review of SmPCs and the available literature. Results: Among 84 PLWH, 229 interactions were identified, and 37/229 (16.2%) were highly clinically relevant. Eight patients (9.5%) experienced AEs predicted by the tools. Four were DDIs: cobicistat/alprazolam associated with sedation and dyspnoea, rilpivirine/hydroxychloroquine with QT prolongation, bictegravir/ursodeoxycholic acid with rising viremia, and atorvastatin/fenofibrate with myalgia. Four DSIs between bictegravir and supplements containing divalent ions have been associated with increasing viremia. After medication review, alprazolam was replaced with zolpidem, rilpivirine-based HAART with bictegravir/emtricitabine/tenofovir alafenamide, and atorvastatin/fenofibrate with simvastatin/ezetimibe, and ursodeoxycholic acid and supplements were discontinued. These interventions were temporally associated with clinical improvement of interaction-related AEs and good virological control. Conclusions: This study highlights the importance of predicting DDIs/DSIs in PLWH undergoing polypharmacy. Medication review supports clinical decision-making, preventing avoidable adverse outcomes. Full article

As health services shift to digital delivery, older adults face practical online risks, including operational errors, difficulty interpreting clinical information, unclear privacy consent procedures, and telecommunications fraud. Existing empirical work mostly adopts questionnaire and interview designs to document older adults’ real-world digital usage, yet few studies systematically analyze policy documents as an external intervention system and assess how they address four core usage barriers: limited digital proficiency, constrained service access, weak sustained participation, and individualized online safety threats. This paper analyzes 1008 policy records extracted from the Peking University Legal Database covering 2007–2025, and develops a four-dimensional analytical framework split into B1 (Digital Capacity and Age-Friendly Support), B2 (Digital Health Management Support), B3 (Home- and Community-Based Care Support), and B4 (Institutional Care and Risk Governance). The analytical toolkit combines a Capability–Opportunity–Motivation–Behavior (COM-B) diagnostic model, an M1–M4 intervention-mechanism coding protocol, Latent Dirichlet Allocation (LDA) topic modeling, and two indices: the Digital Adaptation Policy Orientation Index (DAPOI) and the Behavioral Intervention Diversity Index (BIDI). Coding outputs reveal a pronounced structural imbalance in policy allocation for older adults’ digital health in China: community and institutional governance clauses (B3, B4) dominate the corpus, while person-centred support including one-on-one operational coaching, clinical data interpretation guidance and offline manual backup channels accounts for a marginal share of all coded entries (B1, B2). Age-friendly digital policies issued circa 2020 serve primarily short-term emergency adjustments instead of permanent institutional arrangements. Built on full-text policy coding outputs, this work defines policy-supported digital resilience as a holistic protective system formed by coordinated institutional clauses. Every result reported is sourced exclusively from supply-side policy records, which provides policy-level evidence for subsequent behavioral research on older adults’ digital risk management and digital welfare construction. Full article

Acidic soils are widespread in global agroforestry systems and severely constrain crop production through proton stress, aluminum/manganese phytotoxicity, phosphorus fixation, and rhizosphere microbiome reassembly. Rhizosphere diazotrophs can theoretically contribute to plant nitrogen (N) nutrition and stress adaptation. However, their N-fixation efficiency and growth-promoting effects in acidic soils are often highly unstable, limiting the predictability of field applications. This narrative mechanistic review synthesizes and critically interprets evidence on the physicochemical filters governing diazotroph survival in acidic soils, nitrogenase regulation, root-exudate-mediated recruitment, multi-guild microbial interactions, and the conditional design of synthetic microbial communities (SynComs) and inoculant formulations. We further discuss the potential complementary roles of phosphate-solubilizing bacteria (PSB) and arbuscular mycorrhizal fungi (AMF) and propose minimum reporting standards to improve field translatability. The synthesis indicates that effective diazotroph-mediated crop promotion depends on pH buffering, metal detoxification, carbon supply, phosphorus availability, host compatibility, and native microbiome receptivity. The proposed evidence-chain and microbiome-compatibility framework is a conceptual guide for evaluating these linked conditions rather than an empirically validated predictive model. Full article

Face detection serves as the prerequisite and foundation for individual sheep and goat identification. Considering the practical detection process, the facial region of sheep and goats shares similarities with the torso texture features, which could be easily interfered with by the background and other factors, along with the presence of varying face scales. RetinaFace was selected as the framework, with GhostNet used as the backbone for feature extraction, thereby significantly reducing model complexity and computational load. A new feature extraction unit—SRM module—was designed through the integration of the Multi-Source Domain Adaptation (MSDA) attention mechanism and Reparameterized Non-local Cross-scale Feature Exchange Layer 4 (RepNCSPELAN4) to mitigate the impact of environmental factors and enhance the fine-grained feature extraction of the sheep and goat’s face. A new feature fusion network—A_EFPN—was designed through the com-bination of Efficient Reparameterized Generalized-FPN (RepGFPN) and Alterable Kernel Convolution (AKConv), thereby enhancing feature interaction and improving the model’s multi-scale detection ability. An optimized multi-task joint loss function was employed to retain three facial key points: the left eye, right eye, and nose, thereby reducing the number of model regression parameters. Experimental results demonstrate that the proposed method achieved 96.15% Precision, 97.06% Recall, 96.60% F1 Score, 98.31% AP, 2.40% NME, 2.36 G FLOPs, 3.63 M Params, and a weight of 14.75 MB. It was demonstrated to be applicable to the rapid and accurate detection of sheep and goat faces in the actual breeding environment, providing the foundation for subsequent sheep and goat face recognition. Full article

As consumption becomes increasingly mediated by digital platforms, green nudging has emerged as an important tool for promoting sustainable consumption. Platform green nudging is characterised by datafication, interface design, algorithmisation, and commercial embedding. These features reshape the choice architecture of sustainable consumption and may reduce the cognitive and behavioural costs associated with green choices. Yet they may also compress complex environmental practices into simple symbols, producing a green interface impression that exceeds what the available environmental evidence can support. This paper combines normative ethical analysis with an illustrative case analysis to examine the ethical boundaries of platform green nudging and to develop corresponding governance requirements. It argues that its ethical legitimacy should be assessed against welfare, transparency, and autonomy. Its goals should serve the environmental public good and consumers’ genuine interests; green information should be clear and substantiated; and consumers should retain room to understand, compare, reflect on, and refuse platform suggestions. Using Booking.com’s “Travel Sustainable” programme, the paper identifies transparency as the most clearly supported ethical risk, while welfare and autonomy concerns are treated primarily as structural risks requiring further empirical examination. It proposes evidentiary grounding, interface calibration, choice safeguards, and platform accountability to support credible green information, autonomous judgment, and long-term sustainable consumption. Full article

Plants have coevolved with microbes for nearly 500 million years; however, their interrelationship is not well understood. Plant roots have an intricate relationship with soil microbes. Such relationships mold the growth, development, immunity and physiology of plants and thus are of immense interest to agriculture and the environment. Technological advancements in sequencing, imaging, omics, synthetic biology and artificial intelligence have allowed scientists to dissect such relationships to a higher resolution. Thus, these advances have facilitated a deeper understanding of plant–microbe interactions and their role in the life cycle of plants and the environment. However, factors such as microbial diversity, microbial abundance, heterogeneity of soil and plasticity of the environment have precluded a clear in situ understanding of microbial community structure. Thus, constructing synthetic microbial communities or SynComs and investigating their effect on plants in a controlled environment offers a reductionist and manageable approach to understand plant–microbe relationships. This approach reduces the confounding variables present in the natural environment and facilitates the understanding of such complex interactions. Members of such communities are identified using 16S rRNA sequencing and are constructed using few microorganisms; often fungal strains are added for cross-kingdom SynComs. Metabolic modeling, metabolic cross-feeding along with ecological and evolutionary principles, can be used while choosing candidates for SynComs. Scalability, transferability, reproducibility, predictability and stability are the major bottlenecks in SynCom research. This emerging area of science may have transformative impact in agriculture, environment and space colonization. In this article, we present our perspective on the latest advancements, challenges and future potential of this technology. Full article

Industrial heritage tourism depends on more than the preservation of visible structures; it also requires visitors to perceive historical and cultural meaning. This study examines public perceptions of eight representative industrial heritage tourism sites in Wuhan. Drawing on Scene Theory, we developed a three-dimensional framework encompassing physical, social, and cultural scenes. We collected user-generated content (UGC) from Dianping.com and evaluated 12 perception elements using semantic network analysis and a modified Importance–Performance Analysis based on topic salience and satisfaction. Public perceptions were dominated by visual aesthetics and social-media engagement. Ecological atmosphere received favourable evaluations despite its lower salience, whereas homogeneous commercial offerings weakened the visitor experience. Era memory and industrial heritage combined relatively high salience with low satisfaction, revealing a gap between visible physical remains and the communication of industrial history and collective memory. A hierarchical analysis further showed that only 8.40% of culture-related reviews contained deep industrial narratives. We therefore propose strategies that improve spatial interpretation, embed site-specific industrial identity in commercial and social experiences, and connect heritage objects with historical processes and workers’ memories. These findings provide an evidence-based framework for strengthening cultural interpretation in the revitalization of Wuhan’s industrial heritage. Full article

The rapid development of large model-driven agent applications, such as digital assistants and robots, requires 6G radio access networks (RAN) to deliver enhanced flexibility, adaptability, and low-latency capabilities. However, the existing RAN user plane (UP) architecture suffers from coarse decoupling granularity and significant cross-layer functional redundancy. These limitations severely hinder the on-demand orchestration and dynamic reconfiguration required by heterogeneous agent services. To address these challenges, this paper proposes a ComBERT-driven service-based RAN UP decoupling method, specifically targeting the functional coupling and redundancy between the PDCP and RLC sublayers. First, we develop a domain-specific language model, ComBERT, by pre-training a BERT model on a 3GPP protocol corpus and fine-tuning it on text-matching tasks to deeply comprehend protocol semantics. Subsequently, ComBERT is utilized to extract semantic features from UP functional components, employing a sliding window mechanism to overcome truncation in lengthy protocol texts and using cosine similarity to measure functional relevance. Finally, a threshold-based fusion algorithm is designed to identify and merge cross-layer redundant functions, thereby forming independent service units with distinct responsibilities. These fused units serve as the basic building blocks for scenario-specific orchestration. Simulation results demonstrate that the proposed method reduces the number of UP components by 12.5%, 18.7%, and 18.2% in eMBB, URLLC, and mMTC scenarios, respectively. Simultaneously, it decreases average processing delays by 7.9%, 10.2%, and 11.0% across these respective scenarios. Ultimately, this approach effectively improves the lightweight deployment, processing efficiency, and reconfiguration capabilities of the service-based UP, providing a crucial foundation for on-demand service orchestration in 6G networks tailored to agent services. Full article