Search Results (2,007,438)

Sustainable urban development is increasingly shaped by the joint evolution of social development, ecological conditions, and technological capacity. Understanding how these dimensions are associated with green economic efficiency (GEE) is therefore important for advancing urban green transition. This study examines GEE from a social–ecological–technological (S–E–T) systems perspective and incorporates spatial dependence into the empirical framework. Using panel data for 281 prefecture-level cities in China from 2011 to 2022, this study measures GEE with a Super-SBM model, characterizes its spatiotemporal evolution, and estimates a two-way fixed-effects spatial Durbin model to distinguish local and cross-city associations. The results show that: (1) urban GEE improved overall, while maintaining a clear southeast-high and northwest-low spatial gradient; (2) regional disparities widened over time, and efficiency transitions exhibited strong path dependence and spatial neighborhood effects; (3) the spatial Durbin model is preferred over the SAR and SEM alternatives, indicating that both local conditions and geographically connected cities should be considered; (4) green patenting shows the most stable positive association with GEE, both locally and across connected cities; and (5) population density and ecological conditions display differentiated local and cross-city associations. These findings show that combining the S–E–T framework with spatial panel analysis provides a systematic approach for understanding urban GEE and offers evidence for coordinated green development policies across connected cities. Full article

Arbuscular mycorrhizal (AM) fungi are often considered host generalists. Although the host-mediated assembly of AM fungal communities is well documented, its functional significance remains poorly understood, particularly in organic and low-input agroecosystems, where crop–weed interactions may influence the soil AM fungal reservoir. We investigated plant and AM fungal functional traits, mycorrhizal dependency (MD), and root AM communities in three legume crops and five weed species grown in pots with the same indigenous AM fungal inoculum. AM fungal communities were characterized using SSU rRNA gene clone libraries, sequencing, and terminal restriction fragment length polymorphism (T-RFLP) analysis. Of 825 examined clones, 792 were assigned to AM fungi, representing 23 RFLP types. Plant species significantly affected the plant traits, root colonization, spore density, extraradical mycelium density, and MD. PERMANOVA revealed that plant species explained 97.3% of the variation in the AM fungal community structure, although this result should be interpreted cautiously because within-species dispersion may have contributed to the explained variance. RELATE analysis showed a significant association between the AM fungal community structure and plant–AM fungal functional traits. The specific root length, shoot and root N concentrations, AM fungal colonization, and spore abundance best explained community patterns. Legume crops supported greater AM fungal development and positive growth responses, whereas several weeds hosted diverse AM communities without showing biomass benefits. These findings highlight that weed management could indirectly influence AM fungal persistence through host-mediated community assembly, although field validation is required. Full article

With the rapid development of recycling and secondary utilization of end-of-life battery materials, it is crucial to clarify the impact of full-lifecycle degradation on the thermal safety limits of lithium-ion batteries. This study focuses on a 16 Ah NCM613|graphite pouch battery. First, it analyzes the evolution of capacity decay, thickness expansion, and internal resistance during cycling at room temperature (25 °C) and high temperature (45 °C). Furthermore, an adiabatic accelerated calorimeter (ARC) is employed to investigate the influence of different states of health (SOH) levels (95% and 85%) on the battery’s thermal runaway characteristics. The findings indicate that, macroscopically, batteries in all states follow similar voltage–temperature failure pathways, with mass loss rates confined to a narrow range of approximately 16%, emphasizing the low catastrophic potential of mid-nickel chemistry. However, the microscopic kinetic mechanisms exhibit significant anisotropy: although thickness and internal resistance display no apparent abrupt increase during the late stage of room temperature aging, the capacity exhibits a highly nonlinear plunge behavior. The severe internal lithium plating side reaction triggered by this phenomenon causes the self-heating onset temperature to drop rapidly from 130.0 °C in the fresh state to 79.7 °C. Concurrently, the activation energy of the exothermic side reaction, fitted using a simplified Arrhenius equation, exhibits a non-monotonic variation with aging progress. In the early stages of aging at 95% SOH, due to high temperatures promoting more significant growth of the interfacial film or moderate film formation at room temperature enhancing interfacial thermal stability, the activation energies for both aged batteries increase, and the energy barrier at high temperatures is slightly higher than at room temperature; however, during the deep aging stage at 85% SOH, due to the degradation of active material components and the emergence of lithium plating characteristics, the energy barrier significantly decreases, with high-temperature-aged batteries exhibiting a greater reduction, highlighting the cumulative negative impact of prolonged high-temperature exposure on thermal safety. The research provides a core scientific basis for establishing a battery safety early warning and dynamic health management system covering the entire lifecycle. Full article

AI is currently shaping how people are being entrepreneurial by allowing the establishment of AI-native ventures. The creation of these new types of businesses builds off an infrastructure of data, computing power, and research that typically accompany advanced economies. In contrast, most developing economies are still experiencing institutional and structural barriers that inhibit the formation of new ventures and their subsequent growth. Despite the existence of research that explores some of the ways in which successful ecosystems from developed economies could be applied to developing ecosystems, there is little guidance on how to systematically adapt these successful practices in resource-constrained environments. This research uses a comparative, document-based study design to assess how to benchmark and configure AI-native entrepreneurship ecosystems across heterogeneous institutional environments. Using Switzerland and Jordan as two contrasting analytical cases, we define twelve dimensions of an ecosystem and then create comparative ecosystem profiles using a standardized coding and scoring framework. We combine dimension-level data on talent development, applied research, infrastructure, financing, governance and market access with baseline socio-economic indicators. Our results demonstrate a high level of structural asymmetry between the two ecosystems. Switzerland has a balanced and highly coordinated configuration, whereas there is a strong university anchor and demand for talent in Jordan, but there are also significant weaknesses in terms of infrastructure, financing, and industry linkages. Building from these results, we present the parameter re-weighting and the context-sensitive design model to encourage the emergence of AI-native entrepreneurship in Jordan through coordinated architecture, collaborative experimentation resources and internationalization at an early stage. This article advances both the fields of entrepreneurial ecosystems and digital entrepreneurship by framing AI-native entrepreneurship as a new form of knowledge-intensive venture creation and providing a context-sensitive approach for adapting entrepreneurial ecosystems. The results provide a document-informed basis for policymakers, academic institutions and other ecosystem actors seeking to develop AI-based innovation in resource-constrained economies. Full article

Aiming at the challenges of potato storage scenarios, severe target stacking and occlusion, and large variations in defect characteristics in potato storage environments, a potato defect detection method named MDS-DETR was proposed, and its deployment on a robotic sorting platform was validated. First, potato images under different illumination conditions and stacking states were collected in potato storage warehouses to construct a potato defect dataset containing defects such as black spot, sprouting, dry rot, decay, green skin, and cracking. Subsequently, according to the characteristics of object detection tasks in storage scenarios, an MCF module was designed to strengthen the extraction and integration of contextual features across different spatial scales. An AIFI-DyMona structure, namely Anchor-free Instance Feature Interaction with Dynamic Mona, was constructed to improve the stability of feature representation under different illumination conditions. In addition, the Shape-IoU regression strategy was incorporated to improve the network sensitivity to irregular defect contours and geometric characteristics. Validation experiments demonstrated that the proposed MDS-DETR framework achieved 96.3% mAP@0.5, with only 14.2 M parameters and 42.9 G FLOPs. Compared with several representative object detection algorithms, the proposed method exhibited superior recognition capability and stronger robustness under complicated storage conditions, while also showing better suppression of missed and incorrect detections. To further evaluate its practical applicability, the trained network was integrated into an intelligent potato sorting robot and tested in real warehouse scenarios. Experimental observations indicated that the robotic system consistently maintained a sorting accuracy exceeding 95%, demonstrating the effectiveness and practical deployment potential of the proposed approach for potato storage applications. This study can provide a reference for intelligent detection and automated sorting in potato storage processes. Full article

This study investigates the collaborative green vehicle routing problem with time-dependent travel speeds (CGVRP-TD), which integrates horizontal collaboration among multiple depots with time-dependent traffic conditions. The problem jointly optimizes customer allocation, vehicle routing, and departure-time decisions to minimize transportation-related carbon emissions subject to vehicle capacity and customer time-window constraints. We formulate the CGVRP-TD as a mixed-integer programming model and develop a two-phase adaptive large neighborhood search algorithm with embedded departure-time optimization. The first phase explores routing and customer-assignment decisions using problem-specific operators, including two speed-related removal operators, while the second phase applies exact departure-time optimization to fixed routes. Computational experiments show that the proposed algorithm obtains high-quality solutions efficiently and that both departure-time optimization and speed-related operators contribute to emission reduction. The results further demonstrate that combining horizontal collaboration with time-dependent travel-speed information can substantially reduce transportation emissions while preserving on-time service. We also discuss emission-savings allocation mechanisms for sustaining collaboration among participating depots. Full article

Cold-climate dwellings can face coincident electricity and domestic hot-water shortfalls in winter, when solar availability is at its lowest. This study evaluates an integrated residential system for Aomori, Japan, combining photovoltaics, evacuated-tube solar water heating, and battery storage with electrolysis, compressed-hydrogen storage, and a PEM fuel cell operated in combined-heat-and-power mode. Building on a screening-level annual-balance analysis, a coupled annual TRNSYS simulation with a 0.125 h time step resolved battery dispatch, electrolyzer part-load operation, hydrogen compression and finite storage, seasonal fuel-cell operation, and heat recovery. The results show that the principal value of seasonal hydrogen lies in improving winter supply adequacy, dispatchability, and heat recovery rather than annual conversion efficiency. Fuel-cell heat recovery increased the number of days satisfying the hot-water screening indicator—a daily mean tank temperature of at least 43 °C—from 221 to 332. A reserve-aware criterion identified a 225 W electrolyzer operating-power cap as the positive-reserve case; 205 W was near-cyclic with a negligible margin, whereas the original 475 W cap was substantially oversized. The hydrogen pathway remained markedly less efficient than direct photovoltaic and solar-thermal use, and the estimated storage hardware’s lower bound substantially exceeded the break-even capital ceiling supported by the annual operating value. Seasonal hydrogen can therefore strengthen winter energy adequacy and heat recovery but is not yet cost-effective at the single-dwelling scale under the investigated conditions. Full article

The performance of low-temperature detectors utilizing thermal effects is determined by their energy relaxation properties. Usually, heat transport experiments in mesoscopic structures are carried out in the steady state, where temperature gradients do not change in time. Here, we present an experimental study of dynamic thermal relaxation in a mesoscopic system—thin metallic film. We find that thermal relaxation of hot electrons in copper and silver films is characterized by several time constants, and that the annealing of the films changes them. In most cases, two time constants are observed, and we can model the system by introducing an additional thermal reservoir coupled to the film electrons. We determine the specific heat of this reservoir and its coupling to the electrons. We suspect that multiscale thermal relaxation arises from the complicated morphology of the films, in which the electron–phonon coupling strength in grains with different orientations varies. Full article

To addressthe challenge of attitude control in quad-ducted fan unmanned aerial vehicles (UAVs) under coupled disturbances comprising thrust lag, ground effect and a composite wind field during near-ground flight and to mitigate the inherent trade-off between disturbance rejection and noise suppression in fixed-bandwidth extended state observers (ESOs), this paper proposes a robust attitude control method based on a Sigmoid law adaptive-bandwidth extended state observer (AB-ESO). An attitude dynamic model covering the above multi-source disturbances is established, with all uncertainties uniformly treated as lumped disturbances. An adaptive-bandwidth mechanism with filtering and rate-limiting modules is designed for smooth continuous bandwidth tuning. A composite control framework integrating disturbance feedforward, lag compensation and attitude feedback is constructed, and the uniform ultimate boundedness of the closed-loop system is proved. Comparative simulations are conducted against six baseline controllers, including a cascade proportional–integral–derivative (PID) controller, fixed-bandwidth ESOs, incremental nonlinear dynamic inversion (INDI), fast terminal sliding mode control (FTSMC) and a time-varying bandwidth ESO, in a near-ground composite wind scenario. Results show that the proposed method achieves improved comprehensive performance: the three-axis average tracking root mean square error (RMSE) is approximately 72% lower than of the PID controller and 15.8% lower than that of the high-bandwidth ESO, and the control output total variation is reduced by about 27.8%. Monte Carlo verification with 100 random turbulence groups further validates the strong statistical robustness of the proposed method. All validations in this work are based on numerical simulations. This study provides a technical reference for high-precision control of ducted fan UAVs in near-ground environments. Full article

A CFD-based constrained three-component aerodynamic-trim procedure is implemented to investigate the load balance and coupled flowfield response of a simplified shipborne helicopter hovering over a flight deck. During the unsteady CFD calculation, the collective and cyclic pitch controls are updated according to the period-averaged vertical force and the rolling and pitching moments of the helicopter center of gravity. A pre-trim initialization is introduced before the formal-trim process to avoid large pitch corrections from the initial fixed-pitch state. Under a 20 m/s headwind, the initial fixed-pitch case shows a vertical-force deficit and extra rolling and pitching moments. After dynamic trim, the pitch controls converge to ${\theta }_0=8.46°$, $A_1=-2.48°$, and $B_1=1.20°$. Over the final one-revolution interval of approximately t = 31.74–32.00 s, the period-averaged loads are $F_z=112.82 \mathrm{k}\mathrm{N}$, $M_x=-0.06 \mathrm{k}\mathrm{N}·\mathrm{m}$, and $M_y=-0.07 \mathrm{k}\mathrm{N}·\mathrm{m}$. Additional +30° and −30° oblique-wind calculations confirm convergence toward the prescribed three-component load targets under asymmetric inflow conditions. The instantaneous flowfield comparisons suggest local responses in the rotor-inflow and fuselage-pressure regions after trim. Frequency-domain analysis identifies a dominant blade-passing-frequency component together with additional low-frequency content characteristic of the coupled rotor–ship aerodynamic response. Full article

RNA aptamers are often used as ligand-recognition modules in engineered RNA systems, but integration into larger RNA constructs can influence stability and ligand binding. As a result, aptamer sequences may need to be adapted to new environments while preserving essential properties. Here, we examine this sequence editability problem for the theophylline RNA aptamer. Starting from the experimentally determined structure, we introduced targeted mutations in peripheral structural elements while leaving the recognition site unchanged. The native aptamer, mutated variants, a Mg²⁺-depleted system, and a caffeine-bound control were analyzed using three independent 1 $\mathsf{\mu }$s molecular dynamics simulations. Binding energetics were estimated with multiple end-point as well as alchemical free energy approaches. Results were interpreted together with base pair stability, the conformational landscape of the binding pocket, and per-nucleotide energy contributions. This allows us to predict whether an edit is tolerated or disruptive. Some mutations retained structural and energetic profiles comparable to the native aptamer, whereas others reduced ligand affinity by propagating structural distortions into the binding pocket. These results show that sequence changes outside the binding site can modulate ligand binding indirectly, and that the ligand interaction network is useful for evaluating edited aptamers. The introduced workflow provides a novel combination of established computational strategies for efficient in silico screening of aptamer variants before experimental testing and can be integrated into the design of larger RNA structures. This works particularly well when an experimental structure is available and the tested mutations are small enough not to disrupt the folding pathway. Full article

Background and Objectives: Body mass index (BMI) has a complex relationship with skeletal health. Higher BMI is often associated with higher bone mineral density (BMD), but this apparent densitometric advantage may not fully reflect bone microarchitecture. Trabecular bone score (TBS) may provide complementary information in overweight and obese postmenopausal women. This study evaluated the associations between BMI, BMD, and TBS in postmenopausal women and assessed whether increased BMI is associated with discordant skeletal phenotypes characterized by non-osteoporotic densitometric status but impaired trabecular microarchitecture. Materials and Methods: This retrospective observational study screened 110 DXA/TBS reports from patients evaluated in a tertiary DXA center. Inclusion criteria were female sex, postmenopausal status, available BMI or sufficient anthropometric data for BMI calculation, valid lumbar spine DXA, at least one valid hip DXA assessment, and valid lumbar TBS assessment. Four cases were excluded: two male patients and two non-menopausal female patients. The final analytical cohort included 106 postmenopausal women. Lumbar spine and hip BMD, T-scores, TBS, Bone Resilience Index, anthropometric variables, and menopausal variables were extracted from DXA/TBS reports. BMI was analyzed both continuously and by category: under/normal-weight, overweight, and obesity. Correlation analyses, group comparisons, and linear regression models were used to evaluate the relationship between BMI and skeletal parameters. Discordant skeletal phenotypes were defined descriptively as non-osteoporotic DXA findings combined with degraded TBS. Results: The final cohort had a mean age of 65.2 ± 7.6 years and a mean BMI of 27.3 ± 4.5 kg/m². BMI was positively associated with lumbar spine BMD (r = 0.392, p < 0.001), minimum femoral neck BMD (r = 0.382, p < 0.001), and minimum total hip BMD (r = 0.508, p < 0.001), but negatively associated with TBS (r = −0.307, p = 0.001). Mean TBS decreased across BMI categories, from 1.283 ± 0.084 in the under/normal-weight group to 1.255 ± 0.088 in the overweight group and 1.199 ± 0.109 in the obesity group. In the fully adjusted regression model including BMI, age, years since menopause, lumbar spine BMD, and lowest hip T-score, BMI remained an independent negative predictor of TBS (β = −0.0126, p < 0.001). Discordant skeletal phenotypes combining non-osteoporotic DXA status with degraded TBS were more frequent in patients with obesity. Conclusions: In postmenopausal women, higher BMI was associated with higher BMD but lower TBS, supporting a divergent relationship between densitometric findings and DXA-derived trabecular texture parameters. These findings suggest that TBS may complement BMD in describing skeletal imaging status in overweight and obese women. Because fracture outcomes and complete clinical risk data were not available, the present results should be interpreted as evidence of imaging discordance rather than direct evidence of clinical underdiagnosis or misclassification. Full article

Digital diversification increasingly occurs not through acquisition or formal alliance but through staged, option-like commitments between large technology firms and frontier artificial intelligence (AI) developers. This paper uses the Amazon–OpenAI partnership (November 2025–March 2026) as an illustrative case to examine how such staged commitments can be understood through a real-options lens. The paper organizes the case around five synergy categories adapted from the M&A and ecosystem literature—market power, relational, network, non-market, and ecosystem synergies—and shows that Amazon’s two-tranche investment structure ($15 billion committed, with a further $35 billion conditional on technological and commercial milestones) resembles a compound sequential call option. The paper illustrates this logic with a compound option and binomial lattice valuation, using publicly disclosed deal terms and volatility proxies from comparable AI firms. The paper emphasizes that this valuation is indicative rather than precise: it depends on assumptions about OpenAI’s eventual IPO valuation, the durability of Amazon’s ownership share, and the appropriateness of peer-firm volatility as a proxy, all of which are uncertain at the time of writing. The paper’s contribution is conceptual: it introduces ‘staged ecosystem optionality’ as a mechanism of digital diversification and offers a road map for future research. Full article

More than 70% of non-obstructive azoospermia (NOA) cases remain idiopathic, and the underlying genetic causes need to be investigated. In this study, we aimed to identify genes and variants associated with the etiology of NOA. Two NOA patients from consanguineous families, with normal karyotypes and no Y-chromosome microdeletions, were selected for whole-genome sequencing (WGS). Candidate variants were validated by Sanger sequencing. Structural protein modeling and assessment of mutation-induced changes in molecular interactions were performed using SWISS-MODEL and AlphaFold. We identified a candidate homozygous missense variant (c.899C>T, p.(Ser300Phe); rs375931805) in SOX30 in one patient; this transcription factor is highly expressed in the testis. In the second patient, a homozygous missense variant (c.1472C>T, p.(Thr491Met); rs746902232) in RNF220 and a hemizygous missense variant (c.2354A>G, p.(Gln785Arg) in the X-linked AKAP4 gene were simultaneously detected. Previous studies have shown that SOX30 knockout in mice leads to meiosis I arrest and impaired spermiogenesis. AKAP4 is exclusively expressed in the testis, and missense variants have been reported in different forms of male infertility. The co-occurrence of variants in AKAP4 and RNF220 may suggest an oligogenic etiology of NOA and contribute to the phenotypic variability associated with AKAP4 variants. Full article

Large-scale dairy farms with anaerobic digestion (AD) are expanding rapidly in China, yet high-resolution assessments of N flows, N use efficiency (NUE), and N footprint remain limited. This study conducted a process-based N accounting and N footprint assessment for a large-scale commercial dairy farm with AD in China using farm-specific data on herd structure, feed intake, milk production, manure management, feed production, transportation, and on-farm energy use. Whole-farm N flows were traced from feed inputs to animal products, manure excretion, manure treatment, field application, soil deposition, and environmental losses. Total herd N intake was 3.12 × 10⁶ kg N yr⁻¹, of which 5.83 × 10⁵ kg N was exported in milk, and 2.45 × 10⁶ kg N was excreted. Lactating cow milk NUE was 28.11%, while whole-herd milk-only and product NUE were 18.70% and 19.90%, respectively. The milk-allocated N footprint was 7.21 g N kg⁻¹ fat- and protein-corrected milk (FPCM) under the cradle-to-farm-gate boundary and increased to 13.56 g N kg⁻¹ FPCM when manure land application was included. Feed production was the largest contributor under the cradle-to-farm-gate boundary, whereas manure management dominated under the expanded boundary. Scenario analysis showed that the largest simulated reductions were 30.52% for dietary mitigation under the cradle-to-farm-gate boundary and 18.77% for combined manure-management mitigation under the expanded boundary. These results highlight the need for coordinated improvements in feeding, herd management, and manure management. Full article