Search Results (10,362)

High-precision time and frequency references are essential for satellite navigation, deep-space exploration, and space science missions. To address the large size, high power consumption, and limited integration of conventional Passive Hydrogen Maser (PHM) servo electronics based on discrete analog chains, this paper proposes a miniaturized digital servo architecture for PHMs based on software-defined radio (SDR) and a field-programmable gate array (FPGA). The AD9364 is used as an integrated RF front end for microwave interrogation signal generation, receiver down-conversion, and analog-to-digital conversion (ADC), while digital demodulation, discriminator construction, and closed-loop control are implemented in the FPGA. A dual-frequency interrogation and time-division multiplexing scheme is introduced to separate the atomic and cavity responses, and an oversampling-based processing method combining outlier rejection and averaging decimation is adopted to improve the observation accuracy and noise immunity of weak error signals. Experimental results demonstrate stable closed-loop locking of the atomic transition spectrum, achieving a frequency stability of 1.46 × 10⁻¹² at 1 s, while significantly improving the compactness and integration level of the servo electronics. Full article

Globally, the transport sector accounts for almost a quarter of CO₂ emissions from fuel combustion and generates large amounts of pollutants, placing significant pressure on the environment and human health. By 2050, the European Green Deal requires a 90% reduction in transport-related emissions, making sustainability necessary across all modes of transport. Based on the relevant literature, this study examines the role and potential of railways in decarbonising the EU transport sector. Railway is highly efficient, consuming just 1.9% of transport sector energy while handling 16.9% of freight and 5.1% of passenger transport in the EU, yet is responsible for only 0.4% of total emissions. According to studies, greenhouse gas emissions can be reduced by improving energy efficiency, using low-carbon or renewable energy, and expanding train electrification. The greatest potential for decarbonisation lies in a modal shift to rail. However, this requires significant infrastructure investment: raising line speeds to at least 160 km/h, expanding networks, building terminals, digitalisation, and alignment with TEN-T standards. Although the EU supports the modal shift with funding programmes, the transition is not progressing as expected—the share of road freight transport increased from 74% in 2013 to 78% in 2023. Stronger investment is needed in Member States’ national policies for the development and modernisation of railways. The authors developed a Path Evaluation Matrix (PEM), a quantitative decision framework integrating the fields of energy, transport, politics, and economics. The PEM results indicate that BEMU (battery electric multiple units) is optimal for 68% of secondary lines in south-eastern Europe. Full article

Generative artificial intelligence in higher education is typically framed as either a student productivity tool or an institutional disruption. This agenda-setting essay advances a third position: mobile generative AI functions as relational infrastructure—a persistent communicative presence that mediates identity, meaning-making, and belonging during institutional transition. Focusing on international graduate student onboarding, we abductively “think through” two complementary theoretical lenses. Constitutive Artificial Intelligence Identity Theory (CAIIT) conceptualizes AI as a co-constitutive participant in identity formation through recursive communicative feedback loops. Language Convergence/Meaning Divergence (LC/MD) theory explains how shared institutional language masks interpretive gaps across intercultural and bureaucratic contexts. Reading narrative vignettes through these frameworks, we argue that generative AI is neither simple curricular tool nor personal aid, but both relational and organizational infrastructure, redistributing translational, emotional, and interpretive labor in higher education. We outline four design principles for AI-integrated onboarding: distinguish communicative scaffolding from cognitive replacement; design systems that assume meaning divergence; center equity in AI-mediated transitions; and anticipate ethical risk. Reframing AI as relational infrastructure shifts AI-in-education research toward relational accountability and institutional care. Full article

Rapid population growth is intensifying global energy demand and waste generation. Slaughterhouse waste is creating important environmental problems. Transforming this into renewable energy through technologies like anaerobic digestion offers a sustainable pathway to reduce environmental impacts and support the energy transition. The main objective of this study was to examine the biodegradability of the slaughterhouse semi-liquid fraction (S), slaughterhouse liquid fractions (L), and their mixtures (25%, 50%, and 75%) through a two-phase anaerobic co-digestion (TPAcD) process. Batch reactors were operated in two separate microbiological and thermal phases. In the first, a thermophilic 55 °C–acidogenic stage, biochemical hydrogen potential (BHP) assays were conducted to evaluate green hydrogen production, while in the second, a mesophilic 35 °C–methanogenic stage, biochemical methane potential (BMP) assays were carried out to assess biomethane generation. The most relevant findings revealed that while liquid fractions maximized hydrogen recovery, overall yields remained limited due to competitive metabolic pathways. Notably, the 25L:75S configuration optimized hydrolysis, with a 1280% increase in soluble COD, establishing the semi-liquid fraction as a critical organic reservoir for thermophilic–acidogenic activity. In the subsequent stage, the acidogenic pre-treatment significantly enhanced methanogenesis, where the same 25L:75S mixture exhibited a synergistic methane yield of 495.46 mL CH₄/g VS. This 13.8% improvement over the theoretical additive potential confirms that strategic substrate balancing overcomes individual feedstock limitations, maximizing energy recovery in sequential anaerobic digestion. These results highlight the potential of phase-separated anaerobic co-digestion as a strategy to improve the valorization of slaughterhouse wastes. Full article

The decarbonization of the residential sector is a critical component of the European Green Deal, particularly in transition economies like Poland. This study proposes a comprehensive techno-economic optimization of a deeply retrofitted single-family house aiming for net-zero energy building (NZEB) status. The research specifically focuses on the Polish coastal climate zone, characterized by distinct humidity, wind, and temperature profiles compared to inland regions, which significantly influence the efficiency of air-to-water heat pumps (ASHP). Based on a real-world energy audit, the study simulates the synergy between a deep thermal envelope upgrade and a hybrid system comprising an ASHP, photovoltaics (PV), and battery energy storage (BES). This paper presents a detailed economic analysis of such hybrid systems under the new Polish ‘net-billing’ prosumer mechanism. The study evaluates the impact of electricity tariff structures (flat-rate G11 vs. time-of-use G12w) on the investment’s profitability. By calculating key performance indicators—including the levelized cost of energy (LCOE), net present value (NPV), and self-sufficiency ratio (SSR)—the research assesses various system configurations. The initial evaluation indicates that while deep retrofitting significantly reduces heating demand, integrating battery storage plays a critical role in enhancing economic returns under the net-billing framework. The analysis demonstrates that the optimized hybrid system (9.0 kWp PV + 10 kWh BESS) achieves an average annual self-sufficiency ratio (SSR) of 49.8% and reduces the non-renewable primary energy (EP) indicator to 0.0 kWh/(m²·year). Economically, the investment yields a positive NPV of €3194, an IRR of 5.25%, and a LCOE of €0.184/kWh, which is 34% lower than projected grid prices. Furthermore, switching to a time-of-use tariff (G12w) generates an additional 11% (€139) in annual savings. These quantitative findings provide actionable guidelines for policymakers and investors, confirming the financial viability and environmental benefit (annual reduction of 6.12 MgCO₂) of NZEB standards in coastal areas. Full article

The geomorphological characterization of coastal–marine environments is essential for environmental management and biodiversity conservation. The objective of this study was to model the geomorphological diversity of the Punta de Coles National Reserve, located in Puerto de Ilo, Moquegua, Peru, using GNSS geodetic receivers, integrating topographic and bathymetric data to continuously represent both the emerged and submerged relief. The methodology involved establishing two “C”-order geodetic control points, implementing a closed polygon with 13 vertices, conducting a topographic survey, and recording bathymetric data along coastal transects extending 1 km offshore using an echo sounder and GNSS positioning. The data were processed in a GIS environment to generate a Coastal–Marine Digital Terrain Model (CM-DTM) with metric resolution. The results showed a total area of 171.451 ha, with elevation variations ranging from sea level to 71.617 m above sea level. Distinct geomorphological units were identified, such as coastal plains (0–5% slope), hills (15–35%), and cliffs (>45%), in addition to 16 rocky islets covering 1.537 ha. In the underwater environment, the model made it possible to identify submerged terraces, slopes, and local depressions down to a depth of −115 m, revealing a continuous transition between the land and sea topography; additionally, areas with a higher susceptibility to erosion and areas of high ecological importance were identified. This study’s contribution lies in the integration of GNSS geodetic data with topobathymetric surveys, which enabled the generation of a high-precision continuous model in an area with limited prior information, establishing a scientific baseline for coastal and marine management and conservation. Full article

Background: Wearable sensors have gained increasing popularity as an objective method for remotely monitoring infant movement in naturalistic settings. Over the first year of life, infants generate a wide range of motions, from goal-directed to spontaneous movement. These include linear movements, such as kicks, and orientation changes, such as postural transitions. Many sensor processing pipelines emphasize capturing linear movements through movement-generated acceleration while focusing less on information about orientation embedded in the gravitational part of the data. Here, we introduce a complementary gravity-referenced approach that extracts the gravitational component of accelerometer signals to estimate limb orientation, extending the reliable quantification of rich and detailed aspects of infant movement. Infant orientation has demonstrated clinical relevance, including associations with later neuromotor outcomes, and it can be used to chart infant motor development, motivating the development of objective methods to quantify orientation from sensor data. Methods: Wearable sensors (Opal APDM) were used to longitudinally evaluate infant motor activity recorded in sessions conducted at 3, 6, 9, and 12 months of age. We extracted data from a 5 min segment that has simultaneous video recordings. From these datasets, applying the gravity-referenced method, we computed pitch, roll, and yaw, angles that collectively describe limb orientation. We then quantified orientation variability using axis-specific circular standard deviations (SDs) for pitch, roll, and yaw and a multi-axis composite measure based on generalized variance. Results: Axis-specific circular SDs for pitch, roll, and yaw, as well as the composite generalized variance, increased significantly from 3 to 12 months (p ≤ 0.01 for each metric). Composite variability was strongly associated with Mullen gross motor outcomes at 9 and 12 months of age (r = 0.55, p < 0.001). Conclusions: Overall, gravity-referenced pitch, roll, and yaw provide rich orientation features that increased as infants develop more postural transitions. Furthermore, the orientation features correlated with standardized measures of infant motor function. These orientation metrics can complement traditional linear kinematic measures and improve our ability to granularly track infant motor development in the first year of life. Full article

This study analyzes the long-run relationships between digitalization, investment, innovation, and economic growth in connection with the energy transition in the SPRING-F group (Spain, Poland, Romania, Italy, the Netherlands, Germany, and France) using annual data for the period of 2000–2024. The analysis starts from the premise that digitalization affects economic performance not only directly, but also through structural transmission mechanisms linked to investment and the energy transition. To capture these dynamics, this study employs three complementary panel ARDL models. The first model explains economic growth (GDP per capita) as a function of digitalization, capital accumulation, R&D expenditure, renewable energy consumption, trade openness, and foreign direct investment. The second model estimates gross capital formation (GCF) in order to assess the investment transmission channel. The third model explains renewable energy consumption (RNEC) in order to capture the sustainability dimension. The results show that trade openness and capital accumulation are the strongest long-run drivers of economic growth in the SPRING-F group. Internet use, R&D expenditure, and FDI also display positive long-run associations with GDP per capita, whereas fixed broadband subscriptions and renewable energy consumption enter the growth equation with negative coefficients, suggesting that digital infrastructure and the green transition do not automatically generate immediate growth gains. The GCF model confirms that investment acts as an important transmission mechanism, especially through the robust GDP–GCF linkage. The RNEC model indicates that the energy transition is positively associated with investment, innovation, and trade openness, while GDP and digital infrastructure remain negatively associated with the renewable energy share. Overall, the findings point to a conditional and nonlinear relationship between growth, digitalization, investment, and sustainability, with the sustainability channel remaining more specification-sensitive than the growth and investment equations. The long-run results for the GDP equation should also be interpreted with additional caution, given the comparatively weaker cointegration evidence for Model 1. Full article

Background: Women with endometriosis frequently experience mobility limitations that affect daily functioning. A specific tool to assess these restrictions would help clinicians to better understand patients’ functional challenges, facilitating more effective communication and shared decision making. Addressing this gap is essential for strengthening patient–professional dialogue and improving individualized care. Objective: To develop the new instrument MobEndo and to perform initial psychometric testing of the tool. Methods: The initial domains and items were generated through semi-structured interviews with patients and based on experts’ advice. Guided by the International Classification of Functioning, Disability, and Health (ICF) framework, exploratory factor analysis was conducted on data from patients diagnosed with endometriosis. Internal consistency was assessed using Cronbach’s alpha, considering values ≥ 0.70 as acceptable. Test–retest reliability was examined using intraclass correlation coefficients (ICCs), and ICC values were judged as excellent if >0.75. Construct validity was evaluated through concurrent, discriminant, and known-groups validity. For the known-groups validity hypothesis, participants were categorized by baseline pain levels. Results: The final questionnaire included 18 items, developed from responses from 301 women (mean age 38.96 ± 6.85). Factor analysis revealed two components—transitioning between body positions and performing movements requiring stabilization and executing load-bearing tasks involving the upper limbs—with the model explaining 71.78% of the total variance. Reliability was excellent, with a Cronbach’s alpha of 0.977. The ICC for the total score was 0.976 (95% CI 0.949–0.988), with similarly high values for each component. Concurrent validity correlations were significant, while discriminant validity showed no relevant associations. Known-groups analyses showed clear differences across pain-level groups. Conclusions: The questionnaire is a valid and reliable tool for capturing women’s perceived mobility limitations in endometriosis. Full article

Background/Objectives: Cervical cancer is widely recognized as a preventable disease; however, participation in screening programs remains insufficient in many transitional health systems. In the Georgia, organized screening services are available, yet utilisation remains low, indicating barriers to screening extend beyond access alone. This study, therefore, examined physician-level factors influencing the promotion of cervical cancer screening in the Adjara region of Georgia, with focus on routine clinical practice and organizational conditions. Methods: A cross-sectional survey was carried out among physicians providing outpatient and preventive services in six municipalities of the Adjara region. The analysis was guided by a socio-ecological framework and examined individual, inter-personal, and organizational factors in relation to physicians’ recent cervical cancer screening recommendation practices. Multivariable logistic and ordinal regression analyses were used to identify factors associated with screening promotion. Results: Despite a generally high level of support for cervical cancer screening among physicians, regular screening recommendations were not consistently reported. Limited consultation time, uncertainty regarding screening-related harms, and rural practice settings were independently associated with a lower probability of having recently recommended screening. In contrast, favourable attitudes toward screening on their own were not sufficient to translate into routine preventive practice. Conclusions: These findings indicate that gaps between physician attitudes and screening promotion are largely driven by structural and organizational factors rather than a lack of professional support. Efforts to reduce workflow constraints, improve clarity around screening guidance, and integrate preventive counselling into routine clinical practice may be essential for improving screening uptake in similar healthcare system contexts. Full article

The development of high-performance Fortran code for large-scale scientific simulations is inherently challenging: direct Fortran implementation demands substantial expertise in numerical methods, optimization and system architecture. Manual derivation of numerical schemes is error-prone and time-consuming. This paper advocates a four-stage development methodology involving Python prototyping and symbolic derivation. Systematic validation at each step of incremental transition from symbolic specification to Fortran code produces numerically correct maintainable code faster than by direct manual implementation without sacrificing the resultant performance or code quality. Large Language Models effectively accelerate Python prototyping and boilerplate generation but require rigorous verification of the generated Fortran code. We suggest practical implementation guidelines including validation strategies. Python prototyping and symbolic code generation provide effective instruments for developing efficient production-ready Fortran implementations. Full article

Deep learning systems deployed in regulated settings require explanations that are accurate and stable under nuisance transformations, yet classical post hoc transition matrices rely on fidelity-only fitting that fails to guarantee consistent explanations under spatial rotations or other group actions. In this work, we propose Equivariant Transition Matrices, a post hoc approach that augments transition matrices with Lie-group-aware structural constraints to bridge this research gap. Our method estimates infinitesimal generators in the formal and mental feature spaces, enforces an approximate intertwining relation at the Lie algebra level, and solves the resulting convex Least-Squares problem via singular value decomposition for small networks or implicit operators for large systems. We introduce diagnostics for symmetry validation and an unsupervised strategy for regularization weight selection. On a controlled synthetic benchmark, our approach reduces the symmetry defect from 13,100 to 0.0425 while increasing the mean squared error marginally from 0.00367 to 0.00524. On the MNIST dataset, the symmetry defect decreases by 72.6 percent (141.19 to 38.65) with changes in structural similarity and peak signal-to-noise ratio below 0.03 percent and 0.06 percent, respectively. These results demonstrate that explanation-level equivariance can be reliably imposed post-training, providing geometrically consistent interpretations for fixed deep models. Full article

The expansion and ongoing refinement of control solutions for three-phase microgrids are key enablers in the transition from conventional distribution networks to smart microgrids. By integrating distributed generation, a microgrid can operate in either grid-connected or island mode. One of the major technical challenges in microgrid operation is mitigating or eliminating phase power unbalances. Unbalanced single-phase loads, combined with unbalanced and intermittent single-phase generation, can produce adverse effects on both energy efficiency and power quality. Unlike conventional distribution networks, microgrids may exhibit bidirectional power flows, which can occur simultaneously on all phases or differ from phase to phase. This paper introduces new analytical expressions for sizing a balancing capacitive compensator (BCC) for three-phase four-wire systems and derives a simplified sizing algorithm. The approach is validated through a numerical study using a Matlab/Simulink model of a low-voltage three-phase microgrid with high penetration of single-phase loads and single-phase distributed sources. The BCC is installed at the point of common coupling (PCC) between the microgrid and the main grid. Three operating regimes (cases) of the microgrid were analyzed, considering three compensation scenarios (sub-cases) for each: 1—without compensation, 2—with balanced capacitive compensation (classical), and 3—with unbalanced capacitive compensation (with BCC). For each of the three regimes (cases), the use of the BCC determines, at the PCC, in addition to the cancellation of the reactive component of the positive sequence current, the cancellation of the negative- and zero-sequence currents. In other words, the BCC–microgrid assembly is seen from the main grid either as a perfectly balanced active power load or as a perfectly balanced active power source. Thus, the BCC prevents the propagation of the unbalance disturbance in the main grid; in the considered case study, this also results from the cancellation of the negative- and zero-sequence components of the phase voltages measured at the PCC. The results show that the load-balancing capability of the BCC can be extended to power-flow balancing in any network section, including cases where the phase power directions differ. Implemented as a BCC-type SVC or as an automatically adjustable variant (ABCC), the proposed unbalanced shunt capacitive compensation method is effective for mitigating or eliminating bidirectional phase power-flow unbalances. Full article

In the context of global efforts to achieve carbon neutrality, understanding how digital–intelligent integration influences carbon emissions is crucial for advancing the ecological transition. Using panel data from 30 provincial-level regions in China (2014–2023), a digital–intelligent integration index was constructed via entropy weighting and a coupling coordination model. Employing fixed-effects, mediation, and spatial Durbin models, the analysis shows that digital–intelligent integration is significantly associated with lower carbon intensity, a result that is robust to endogeneity concerns and alternative specifications. Industrial structure upgrading and green technology innovation were identified as mediating pathways. Furthermore, digital–intelligent integration generates positive spatial spillovers, reducing carbon intensity in neighboring provinces. Notably, these spillovers are geographically constrained and vary significantly across the regions. These findings indicate the need to formulate regionally differentiated strategies to harness the specific mechanisms through which digital–intelligent integration operates in different contexts. Full article

Latin America faces growing challenges in the management of municipal solid waste (MSW). This is particularly evident in medium-sized and metropolitan cities where rapid urbanization, limited infrastructure, and high proportions of organic waste (40–70%) converge. This review synthesizes the most recent advances in organic waste management, valorization strategies, environmental performance, and policy frameworks in Mexico and Latin America. To provide a comprehensive overview, evidence from studies on informal recycling systems, route optimization, sustainable landfill siting, food waste valorization, life cycle assessments (LCAs), and biogas production is integrated. Techno-economic analyses of energy recovery from organic fractions are specifically reviewed. This review highlights that valorization of organic waste through composting, anaerobic digestion, food supplementation, and bioproduct generation can reduce greenhouse gas emissions by 40–70% compared to landfilling, with AD–composting hybrids achieving the highest reductions of 60–70%. Community composting achieved moderate reductions, 30–50%, but at significantly lower cost and with greater social co-benefits. These alternatives for valorizing the organic fraction extend the lifespan of both confined and open landfills. It also contributes to mitigating the public health impacts related to open dumping, disease vectors, and contaminated leachate. In short, this review also highlights shortcomings in policy coherence, financial mechanisms, source separation, and technology adoption. A strategic framework is proposed that prioritizes decentralized treatment systems, the integration of informal recyclers, tax incentives, community-based waste separation, and planning based on Life Cycle Assessment (LCA). The findings point to a viable strategy for transitioning from landfill dependency to circular waste management systems that improve the quality of life for the population of Latin America and the Caribbean. Full article