Search Results (4,977)

Due to the strong electronegativity of oxygen ions, the valence band maximum (VBM) that is derived from the O 2p orbital leads to strong localization, as well as further heavy hole mass and low hole mobility, which makes it extremely difficult to obtain high-conductivity p-type transparent conductive materials. Herein, we propose the strategy of multiple anions through the introduction of weaker electronegative nitrogen, in consideration of the delocalization on VBM, as well as the stability of octahedral anion cages. As such, first-principles calculations in the framework of density functional theory (DFT) are used for this work. Crystal structure prediction software USPEX (version 2023.0) was adopted to investigate the N-O appropriate ratio in CaTiO_3−xN_x (0 ≤ x ≤ 1) to balance the high transmission of light and highly favorable dispersion at the VBM. Furthermore, the p-type TCO performance of CaTiO_3-xN_x was evaluated based on the hole effective mass, hole mobility, and conductivity. The effectiveness of modulating p-type TCO through N-O multiple anions was also evaluated through defect formation energy and ionization energy. Ultimately, the construction of a CaTiO_3-xN_x/Si heterojunction and band alignment were considered for practical application. This approach attempts to boost the diversity of p-type perovskite-based TCOs and opens a new perspective for engineering and innovative material design for sustainable TCOs demand. Full article

Urban morphology plays a decisive role in regulating microclimate and outdoor thermal comfort in arid cities, where extreme heat and intense solar radiation amplify thermal stress. This study examines the influence of four contrasting urban fabrics in Béchar (Algerian Sahara): the vernacular Ksar, the regular-grid colonial fabric, a modern large-scale residential estate, and low-density detached housing, on local microclimatic conditions. An integrated methodological framework is adopted, combining qualitative morphological analysis, quantitative indicators including density, porosity, height-to-width ratio, and sky view factor, in situ microclimatic measurements, and high-resolution ENVI-met simulations performed for the hottest summer day. Results show that compact urban forms, characterized by low sky view factor values, markedly reduce radiative exposure and improve thermal performance. The vernacular Ksar, exhibiting the lowest SVF, records the lowest mean radiant temperature (approximately 45 °C) and the most favorable average comfort conditions (PMV = 3.77; UTCI = 38.37 °C), representing a reduction of about 3 °C, while its high-thermal-inertia earthen materials ensure effective nocturnal thermal recovery (PMV ≈ 1.06; UTCI = 27.8 °C at 06:00). In contrast, more open modern fabrics, including the colonial grid, large-scale estates, and low-density housing, experience higher thermal stress, reflecting vulnerability to solar exposure and limited thermal inertia. Validation against field measurements confirms model reliability. These findings highlight the continued relevance of vernacular bioclimatic principles for sustainable urban design in arid climates. Full article

Background: Pin tract infections (PTIs) are a frequent complication of external fixation, yet pediatric trauma-specific data—particularly for open long bone fractures—remain limited and heterogeneous. This study evaluated the frequency, severity, timing, management, and outcomes of PTIs in children and adolescents treated with external fixation for open long bone fractures. Methods: This retrospective single-center study included patients younger than 18 years with open long bone fractures treated with external fixation between 2002 and 2023. PTIs were graded using the Checketts–Otterburn classification (grades I–VI). Management included antibiotic regimen and surgical interventions. Outcome was reported by time to bony consolidation. Results: In 40 patients, 16 patients exhibited PTIs (mild: eight; moderate: five; severe: three. A higher grade of Gustilo–Anderson (p = 0.47) and evident macroscopic contamination (p = 0.73) did not appear to influence the occurrence of PTIs by similar duration of initial antibiotic regimen (p = 0.3). The median time to PTI onset was 49 days (IQR 22–80), with the majority occurring after completion of initial systemic antibiotic therapy. The management of PTIs was predominantly conservative: all eight mild cases resolved with intensified local pin tract care, while all eight moderate and severe cases were treated with systemic antibiotics and five required pin exchange or premature fixator removal. Overall bony consolidation was achieved in all patients, and reoperations were related to trauma severity rather than PTIs except in one patient. No cases of osteomyelitis were observed. Conclusion: Pin tract infections are frequently identified in pediatric open long bone fractures treated with external fixation. Using strict diagnostic criteria, any documented inflammatory change or local secretion at the pin–skin interface is considered indicative of PTI. However, the majority of these infections were classified as superficial and manageable with conservative measures, and all affected fractures healed radiologically. Full article

Women play a key role in Greek olive cultivation, a sector at the heart of local economies currently facing increasing pressures from climate change. This study explores gender roles, responsibilities, and access to resources shaping the adoption of sustainable agriculture practices. Through in-depth interviews with female farmers on the island of Crete, the results show that women face limited access to training and financial services as well as gender-based discrimination and the hidden caregiving and house working tasks. However, they manifest a strong openness towards sustainable practices, driven by environmental values, even among those lacking decision-making authority. Despite these challenges, women show a positive attitude toward learning and innovation, calling for more institutional support and training opportunities. This study sheds light on the need for recognition of women’s roles in agriculture, particularly in the context of climate adaptation, and offers practical recommendations to improve gender roles within the olive sector. Full article

Federated learning effectively addresses the issues of data privacy and communication overhead in traditional deep learning through distributed local training. However, its open architecture is seriously threatened by backdoor attacks, where malicious clients can implant triggers to control the global model. To address these issues, this paper proposes a novel three-stage defense mechanism based on local clients. First, through text readability analysis, each client’s local data is independently evaluated to construct a global scoring distribution model, and a dynamic threshold is used to precisely locate and remove suspicious samples with low readability. Second, frequency analysis and perturbation are performed on the remaining data to identify and disrupt triggers based on specific words while preserving the basic semantics of the text. Third, n-gram distribution analysis is employed to detect and remove samples containing abnormally high-frequency word sequences, which may correspond to complex backdoor attack patterns. Experimental results show that this method can effectively defend against various backdoor attacks with minimal impact on model accuracy, providing a new solution for the security of federated learning. Full article

Patients with traumatic brain injury (TBI) have an elevated risk of developing chronic psychiatric and behavioral disorders, including impairments in motor function, memory deficits, anxiety, and depression. Although a substantial body of work has addressed the treatment and rehabilitation of sensory, motor, and cognitive symptoms after TBI, there is a relative scarcity of comprehensive behavioral assessments targeting neuropsychiatric manifestations in preclinical models. This study aims to investigate the connections between emotional sequelae after TBI and modifications in local field potentials (LFPs). Following cryogenic lesion-induced TBI, animals exhibited anxiety-like behaviors as assessed by the open field test (p < 0.001), light/dark box test (p < 0.001), and elevated plus maze test (p < 0.01). Depression-like behavior was observed using the forced swim test (p < 0.001). LFP analysis demonstrated a marked elevation in neural oscillatory activity associated with anxiety and depression in the contralateral hemisphere relative to the ipsilateral side (p < 0.001). These results indicate that the emotional consequences triggered by TBI may be linked to dysregulated synchronous neural activity between the ipsilateral and contralateral hemispheres. Full article

Quantum anomalies are traditionally understood as classical symmetries that fail to survive quantization, while experimental “anomalies” denote deviations between theoretical predictions and measured values. In this work, we develop a unified framework in which both phenomena can be interpreted through the lens of algebraic quantum field theory (AQFT). Building on the renormalization group viewed as an extension problem, we show that renormalization ambiguities correspond to nontrivial elements of Hochschild cohomology, giving rise to a deformation of the observable algebra $A*B=AB+\epsilon \omega (A,B)$, where $\omega$ is a Hochschild 2-cocycle. We interpret $\omega$ as an intrinsic algebraic curvature of the net of local algebras, namely the (local) Hochschild class that measures the obstruction to trivializing infinitesimal scheme changes by inner redefinitions under locality and covariance constraints. The transported product is associative; its first-order expansion is associative up to $\mathcal{O}\left({\epsilon }^2\right)$ while preserving the *-structure and Ward identities to the first order. We prove the existence of nontrivial cocycles in the perturbative AQFT setting, derive the conditions under which the deformed product respects positivity and locality, and establish the compatibility with current conservation. The construction provides a direct algebraic bridge to standard cohomological anomalies (chiral, trace, and gravitational) and yields correlated deformations of physical amplitudes. Fixing the small deformation parameter $\epsilon$ from the muon $(g-2)$ discrepancy, we propagate the framework to predictions for the electron $(g-2)$, charged lepton EDMs, and other low-energy observables. This approach reduces reliance on ad hoc form-factor parametrizations by organizing first-order scheme-induced deformations into correlation laws among low-energy observables. We argue that interpreting quantum anomalies as manifestations of algebraic curvature opens a pathway to a unified, testable account of renormalization ambiguities and their phenomenological consequences. We emphasize that the framework does not eliminate renormalization or quantum anomalies; rather, it repackages the finite renormalization freedom of pAQFT into cohomological data and relates it functorially to standard anomaly classes. Full article

The research for crop improvement is a continuous process that enhances plant quality, yield, and ameliorates their adaptability to changing climatic conditions. Chilli is cultivated worldwide as a vegetable, spice, or natural colour additive and is an economically and medicinally important crop. A basic requirement for crop improvement in breeding programmes is the presence of genetic diversity within the crop. Smallholder farmers of chilli usually face challenges in acquiring commercial hybrid seeds because of their high cost and the need for annual purchases. Open-pollinated varieties (OPVs) can serve as a sustainable alternative that provides broader genetic variability, allowing adaptation to local growing conditions, and enabling farmers to save seeds for successive planting season. These characteristics make OPVs economically viable and valuable genetic resources for future chilli cultivation and breeding programmes. This review highlights the potential of OPVs in promoting sustainable chilli cultivation, enhancing genetic diversity, and supporting breeding to develop resilient and economically viable cultivars. Full article

The development of sustainable smart cities is closely linked to the implementation of artificial intelligence in urban services, which opens up new possibilities for efficient resource management, improving the quality of life and strengthening the participation of citizens. At the same time, the question arises as to how legal and strategic frameworks can support the use of artificial intelligence in a way that contributes to environmental, social and economic sustainability in line with the objectives of the European Union. The aim of this scientific study is to examine the interdisciplinary use of artificial intelligence, data management and sustainability at the European Union level, including support instruments such as regulatory initiatives and funding programs, and to assess their implementation in relation to smart cities. Methodologically, the research is based on a legal analysis of key European and national documents, supplemented by descriptive statistics and visualizations of indicators of digitalization and urban sustainability. In the scientific study, we use the methods of synthesis, comparison and abstraction. The results suggest that the legislative and support framework of the European Union can be a significant impetus for the transformation of individual smart cities, but requires effective coordination and strategic management at the level of local governments. The research highlights the need for an integrated legal-managerial approach that will enable the full use of the potential of artificial intelligence in supporting sustainable urban development of cities. Full article

The environmental impacts of road transport, in particular air pollution and noise, are receiving increasing attention in urban and regional planning, as they can not only predict vehicle movements but also provide detailed information on traffic volumes and speed distributions, which are indispensable for effective regulation, targeted interventions and health-conscious urban planning. This study presents an emission calculation module that can be integrated into traffic models and provides detailed estimates of pollutants emitted by road vehicles. The developed module builds on the COPERT methodology, which accounts not only for exhaust emissions such as ${\mathrm{CO}}_2$, ${\mathrm{NO}}_x$ and PM, but also for non-exhaust emissions from brake wear, tyre wear, road abrasion and evaporation. The presented system has an open architecture, enabling further customisation, particularly when local measured data are available. This contributes to building a stronger, data-driven link between transport planning and environmental protection. Full article

With the rapid advancement of integrated thermal management systems (ITMS) for new energy vehicles (NEVs), flow losses and hydrodynamic characteristics within multi-way valves have become critical determinants of system performance. In this study, a three-dimensional computational fluid dynamics model is established for a multi-way valve used in a representative NEV ITMS, where PAG46 coolant is employed as the working fluid. The steady-state pressure-loss characteristics under three typical operating modes—cooling, heating, and waste heat recovery—are investigated, together with the transient hydrodynamic response during mode switching. The steady-state results indicate that pressure losses are primarily concentrated in regions with abrupt changes in flow direction and sudden variations in cross-sectional area, and that the cooling mode generally exhibits the highest overall pressure loss due to the involvement of all flow channels and stronger flow curvature. Furthermore, a parametric analysis of the valve body corner chamfers and valve spool fillets reveals a non-monotonic dependence of pressure drop on chamfer radius, highlighting a trade-off between streamline smoothness and the effective flow cross-sectional area. Transient analysis, exemplified by the transition from heating to waste heat recovery mode, demonstrates that dynamic changes in channel opening induce a significant reconstruction of the internal velocity and pressure fields. Local high-velocity zones, transient pressure peaks, and pronounced fluctuations of hydraulic torque on the valve spool emerge during the switching process, imposing higher requirements on the torque output and motion stability of the actuator mechanism. Consequently, this study provides a theoretical basis and engineering guidance for the structural optimization and actuator matching of multi-way valves in NEV thermal management systems. Full article

This work demonstrates a three-step method for the synthesis and production of submicron spherical gold particles using laser ablation in liquid (LAL), laser-induced fragmentation in liquid (LFL), laser-induced nanochain formation, and laser melting in liquid (LML). The nanoparticles were characterized using transmission electron microscopy (TEM), dynamic light scattering (DLS), and UV–visible spectroscopy. In the first stage, spherical gold nanoparticles with a size of 20 nm were obtained using LAL and LFL. Subsequent irradiation of gold nanoparticle colloids with radiation at a wavelength of 532 nm leads to the formation of gold nanochains. Irradiation of nanochain colloids with radiation at a wavelength of 1064 nm leads to the formation of large spherical gold particles with a size of 50 to 200 nm. The formation of submicron gold particles upon irradiation of 2 mL of colloid occurs within the first minutes of irradiation and is complete after 480,000 laser pulses. Increasing the laser pulse energy leads to the formation of larger particles; after exceeding the threshold energy (321 mJ/cm²), fragmentation is observed. Increasing the concentration of nanoparticles in the initial colloid up to 150 μg/mL leads to a linear increase in the size of submicron nanoparticles. The use of picosecond pulses for irradiating nanochains demonstrates the formation of the largest particles (200 nm) compared to nanosecond pulses, which may be due to the effect of local surface melting. The described technique opens the possibility of synthesizing stable gold nanoparticles over a wide range of sizes, from a few to hundreds of nanometers, without the use of chemical reagents. Full article

Knowledge graphs (KGs) offer a structured and collaborative approach to integrating diverse knowledge from various domains. However, constructing knowledge graphs typically requires significant manual effort and heavily relies on pretrained models, limiting their adaptability to specific sub-domains. This paper proposes an innovative, efficient, and locally deployable knowledge graph construction framework that leverages low-rank adaptation (LoRA) to fine-tune large language models (LLMs) in order to reduce noise. By integrating iterative optimization, consistency-guided filtering, and prompt-based extraction, the proposed method achieves a balance between precision and coverage, enabling the robust extraction of standardized subject–predicate–object triples from raw long texts. This makes it highly effective for knowledge graph construction and downstream reasoning tasks. We applied the parameter-efficient open-source model Qwen3-14B, and experimental results on the SciERC dataset show that, under strict matching (i.e., ensuring the exact matching of all components), our method achieved an F1 score of 0.358, outperforming the baseline model’s F1 score of 0.349. Under fuzzy matching (allowing some parts of the triples to be unmatched), the F1 score reached 0.447, outperforming the baseline model’s F1 score of 0.392, demonstrating the effectiveness of our approach. Ablation studies validate the robustness and generalization potential of our method, highlighting the contribution of each component to the overall performance. Full article

Our work develops the structural mathematical framework of the REGENerative Agriculture (REGENA) Production Function, contributing to the limited global literature of regenerative farming production functions with consistency to the 2nd Law of Thermodynamics and the underlying biophysical processes for ecosystem services’ generation. The accurate structural economic modeling of regenerative farming practices comprises a first vital step for the shift of global agriculture from conventional farming—utilizing petrochemical fertilizers, pesticides and intensive tillage—to regenerative farming—utilizing local agro-ecological capital forms, such as micro-organisms, organic biomasses, no-tillage and resistant varieties. In this context, we empirically test the REGENA structural change patterns with data from eight experimental plots in six Mediterranean countries in Southern Europe and Northern Africa for three crop compositions: (a) with exclusively conventional practices, (b) with exclusively regenerative practices and (c) with mixed conventional and regenerative practices. Finally, we discuss in detail the scientific, institutional, economic and financial engineering challenges for the market uptake of regenerative farming and the contribution of REGENA for the achievement of this goal. In addition, as regenerative farming is knowledge-intensive, we review the vital aspect of Open Innovation (OI) and protected Intellectual Property (IP) business models as essential parts of regenerative farming knowledge-sharing clusters and trading alliances. Full article

Various TinyML models face a constantly challenging environment when running on emerging sixth-generation (6G) edge networks, with volatile wireless environments, limited computing power, and highly constrained energy use. This paper introduces DRL-TinyEdge, a latency- and energy-sensitive deep reinforcement learning (DRL) platform optimised for the 6G edge of adaptive TinyML. The suggested on-device DRL controller autonomously decides on the execution venue (local, partial, or cloud) and model configuration (depth, quantization, and frequency) in real time to trade off accuracy, latency, and power savings. To assure safety during adaptation to changing conditions, the multi-objective reward will be a combination of p95 latency, per-inference energy, preservation of accuracy and policy stability. The system is tested under two workloads representative of classical applications, including image classification (CIFAR-10) and sensor analytics in an industrial IoT system, on a low-power platform (ESP32, Jetson Nano) connected to a simulated 6G mmWave testbed. Findings indicate uniform improvements, with up to a 28 per cent decrease in p95 latency and a 43 per cent decrease in energy per inference, and with accuracy differences of less than 1 per cent compared to baseline models. DRL-TinyEdge offers better adaptability, stability, and scalability when using a CPU < 5 and a decision latency < 10 ms, compared to Static-Offload, Heuristic-QoS, or TinyNAS/QAT. Code, hyperparameter settings, and measurement programmes will also be published at the time of acceptance to enable reproducibility and open benchmarking. Full article