Search Results (6,132)

Small modular reactors (SMRs) offer firm low-carbon heat and power, and data centers concentrate large, continuous electrical and cooling loads. Transparent tools for screening their thermal integration are scarce. To the authors’ knowledge, this paper develops the first steady-state thermodynamic framework that couples SMR steam extraction, solar thermal input, and recovered data-center liquid-cooling heat through a single mixing-tank thermal bus serving both an absorption chiller and an organic Rankine cycle (ORC). The framework’s novelty is in its focus on the structural level rather than the component level. Two consistency requirements are built into its equations. First, the data-center control volume closes exactly, so that recovered heat reduces the residual cooling demand and heat removal equals IT dissipation. Second, delivered cooling is credited identically in every configuration compared, so that apparent gains cannot arise from asymmetric accounting. The framework identifies the governing mechanism of the architecture: a small 120 °C extraction stream (1.01% of core thermal power at the activation bound) unlocks the larger 70 °C recovered stream, which cannot drive the chiller alone. At the margin-constrained design point (2.93% extraction), direct liquid recovery removes 20.9 MW_th, absorption cooling serves the remaining 16.2 MW_th, and net electricity is 5.8 MW_e above the all-electric reference. An itemized estimate places the integration-specific parasitic loads at 0.6–1.5 MW_e (central value 1.0 MW_e), which reduces the increment over the liquid-cooled non-integrated reference from $+0.5$ MW_e (gross) to approximately $-0.5$ MW_e (net). A 20,000-sample Monte Carlo analysis across seven uncertain parameters shows the net-of-parasitics gain over the all-electric reference is positive with 92% probability (median $+4.1$ MW_e), while the increment over the non-integrated reference is positive with only 29% probability. A compact exergy inventory attributes 7.1 MW of destruction to the recovery train (process heat exchanger 2.0, mixing 1.2, ORC 2.0, chiller 2.0). The architecture’s robust value therefore lies in thermally driven cooling and the productive use of recovered heat, not in net energy. The framework is a screening tool rather than a validated plant model; a companion study populates it with published plant, climate, and equipment data. Full article

Gas escape relative to magma ascent is a primary control on degassing, yet its governing parameters are difficult to compare across eruptions and planetary environments. This study develops a reduced-order dimensionless framework for diagnosing local gas–melt separation in connected, pre-fragmentation magma. The formulation combines phase mass conservation, porous gas transport, bubble-matrix permeability, independently constrained connected pathways, and inertial resistance. The resulting regime map separates the competition between magma advection and matrix gas segregation from changes caused by sealing, crystallization, fractures, and tuffisite pathways. It shows that crystallization has no unique effect. Matrix obstruction reduces gas escape, whereas brittle pathway formation can enhance it. Global sensitivity analysis indicates that ascent rate and bubble number density account for 98.4% of the variance in the matrix-controlled transport competition over the investigated ranges. When connected permeability is independently specified over the same logarithmic range as ascent rate, both contribute equally to the calculated variance. A literature-constrained calculation for the climactic Chaitén eruption places the bubble-matrix endmember in the advection-dominated regime without adjusting permeability to reproduce the observed outcome. Atmospheric scaling indicates strong near-surface suppression of bubble expansion on Venus, but its magnitude remains highly sensitive to the assumed mechanical overpressure scale. The framework provides a physically testable basis for comparing local degassing states without imposing an arbitrary eruption classifier. It does not predict eruption onset or fragmentation. These require time-dependent dynamics, mechanical failure criteria, and independent validation data. Full article

Understanding the habitat use by mountain ungulates is essential for conservation planning in mountainous ecosystems. However, it becomes important to know the habitat use pattern for endemic species living in rugged and remote terrain. In this study we examined the habitat-use patterns of endemic Himalayan Tahr (Hemitragus jemlahicus), a mountain ungulate in Govind Pashu Vihar (GPV) landscape of western Himalayan region. We surveyed the study area during pre-monsoon season from April 2025 to June 2025. The study area was divided into equal sized 43 grids of 2.5 × 2.5 km each. Data was collected through direct observations and indirect sign surveys, and analyzed using a single-species, single-season occupancy modelling framework. Occupancy (ψ) and detection probability (p) were modelled using nine site-level covariates (topographic, anthropogenic, and environmental) and two sampling-level covariates. As grid size approximated the species’ home range, occupancy (ψ) is interpreted here as an index of site use. The estimated site use (ψ) of Himalayan Tahr was 0.62 (SE ± 0.08), while detection probability (p) was 0.48 (SE ± 0.06). Site use increased with elevation, terrain ruggedness, and north-facing slopes, and was high in alpine grassland, sub-alpine scrubland, and sub-alpine forest, but declined in temperate and dense forest and in areas with intensive livestock grazing. In contrast, detection probability declined with increasing precipitation and was slightly lower under cooler conditions during the survey period. These results suggest that terrain-based security and forage availability, moderated by livestock presence are key correlates of habitat use by Himalayan Tahr. This study represents the first occupancy-based assessment of Himalayan Tahr habitat use in GPV, and the finding will provide critical baseline data to support future management strategies within ecologically sensitive alpine ecosystems. Full article

Available sight distance (ASD) on motorways represents the unobstructed line of sight from the driver’s perspective to an obstacle on the carriageway, which must equal or exceed the required stopping sight distance (SSD). This study evaluates ASD across both two-dimensional (2D) and three-dimensional (3D) motorway alignments, encompassing right- and left-hand horizontal curves combined with different vertical alignments, as well as roadside and median barriers. 2D analyses were performed on predefined theoretical profiles, while 3D ASD evaluations were conducted on real-world models of existing motorway sections in Croatia. These sections were selected based on their diverse horizontal and vertical geometric alignments, design eras, traffic characteristics, and historical crash data regarding collisions with obstacles. The findings reveal that safety barrier placement on motorways can severely constrain sightlines, demonstrating that even radii exceeding the regulatory minimums are insufficient to guarantee necessary SSD requirements. Visibility restrictions from safety barriers are especially pronounced along barrier-restricted horizontal curves, primarily on right-hand curves and occasionally on left-hand curves, depending on the radius. In certain real-world sections, cut slopes also restrict the required visibility. Current Croatian guidelines rely on 2D analysis, which fails to account for safety barriers obstructing visibility. This research emphasises the critical necessity of conducting continuous 3D sight visibility simulations during initial design phases, while recommending further research that could be implemented to update regulatory frameworks regarding parameters for ASD analysis. Full article

This study proposes a new method for the topological synthesis of principal component projections and hydrogeochemical stoichiometric equality lines on self-organizing map (SOM) component planes to assess groundwater chemistry forming factors and quality in the Pleistocene unconfined aquifer of the Southern Bug and Sinyukha interfluve area, Ukraine. The hydrogeochemical characteristics clustered by the SOM were further examined using the graphical cross-validation method. The groundwater dataset used in the analysis consisted of 10 parameters (i.e., pH, total dissolved solids, $\mathrm{C}{\mathrm{a}}^{2+}$, $\mathrm{M}{\mathrm{g}}^{2+}$, $\mathrm{N}{\mathrm{a}}^{+}$, ${\mathrm{K}}^{+}$, $\mathrm{H}\mathrm{C}{\mathrm{O}}_3^{-}$, $\mathrm{C}{\mathrm{l}}^{-}$, $\mathrm{S}{\mathrm{O}}_4^{2-}$, and $\mathrm{N}{\mathrm{O}}_3^{-}$) from 91 samples collected during the dry season. Subsequently, for SOM construction, we utilized six log-ratio relationships of milliequivalent ion concentrations. Based on the results, the hydrogeochemical groundwater data were classified into three clusters, which revealed three water types and processes controlling their chemistry: salinity driven by sulfate inputs (Cluster 1), highly salinity driven by nitrate-chloride and sulfate pollution (Cluster 2), and relatively fresh water governed by natural carbonate dissolution and silicate weathering (Cluster 3). The salinity types were identifiable in the northern part of the study area, characterized as the primary zone of initial intense pollution. High salinity types were identified in the eastern and southeastern parts of the territory (with delayed water exchange), whereas relatively fresh types were identified in the central part (with active water exchange) as well as in the western and southwestern parts. Modeling confirmed that extensive sulfate, nitrate, and chloride contamination led to anthropogenic degradation of the aquifer system. Full article

While Artificial Intelligence (AI) has transformed materials discovery, the primary bottleneck to technological impact remains the transition from lab-scale synthesis to robust, industrial-scale manufacturing. Most promising materials perish in this depth, which is referred as the “valley of death”. The current review consolidates and critically evaluates the emerging ecosystem of AI-driven strategies and frameworks designed specifically to bridge this “lab-to-fab” gap. The review shifts our attention from property prediction to the engineering-driven problems of manufacturability. Furthermore, the review discusses the main obstacles to scaling the production of materials, such as reproducibility, process optimization in the context of uncertainty, and techno-economic viability, as well as the AI approaches being developed to overcome them. This includes Natural Language Processing (NLP) for method extraction, graph neural networks for reaction modeling, reinforcement learning for process control, Bayesian optimization for definition of process windows, and integrated AI–Techno-Economic Analysis (TEA) frameworks. Equally importantly, the review examines the principal failure modes that constrain practical deployment, including out-of-distribution generalization, incomplete and non-transferable literature-derived data, simulator-to-plant mismatch, uncertainty miscalibration, and the continued need for expert oversight. The article concludes with a forward-looking roadmap for the future of AI in chemical and materials engineering. The proposed conclusion is defined by a paradigm shift from simply finding new materials to creating viable, economical, and scalable pathways to produce them, thereby enabling a new era of synthesis-aware materials innovation. Full article

Environmental footprint assessment is increasingly used to characterize the secondary impacts of contaminated site remediation. However, many established green and sustainable remediation tools rely on U.S.-based emission inventories and background data, raising questions about how their estimates change when applied under other regional conditions. This study proposes a three-way evaluation framework that examines Sitewise™ and SEFA outputs alongside a Sitewise-informed China-localized recalculation using domestic emission factors. The framework was applied to an excavation-and-transport brownfield remediation project in northern China using five indicators: greenhouse gas emissions (GHG), energy use, NO_x, SO_x, and particulate matter. In this case, Sitewise™ and SEFA produced numerically similar GHG estimates and moderately different energy estimates, with pairwise differences of 7% and 27%, respectively. Under the assumptions of this case, their GHG estimates were 26% and 20% lower, respectively, than the localized recalculation. A screening counterfactual using a common U.S. reference grid factor indicated that grid factor substitution accounted for 19.2% of the Sitewise-to-localized numerical difference and 24.5% of the SEFA-to-localized numerical difference. Air pollutant results showed stronger pathway dependence: NO_x estimates differed by up to approximately eightfold, and the localized result fell between the two tool estimates under the stated assumptions. Within the tested epistemic ranges, the localized GHG result remained above both fixed tool outputs, the NO_x result remained between them, and the SO_x result remained below both in every draw; the baseline PM relationship was retained in 92.7% of draws, while localized energy equaled the Sitewise™ result by construction. Across the native tool runs and a transparent localized transport linkage screen, a 25% reduction in haul distance was associated with a 12.5–22% reduction in total GHG estimates. The comparison harmonized the remediation program and comparison unit, but not the complete background life cycle boundary; the results therefore represent defined-boundary pathway estimates rather than fully boundary-harmonized LCA results. Because the localized pathway retains the Sitewise-derived fuel–energy balance and activity category shares, it is interpreted as a case-specific factor localization recalculation rather than an independently documented project inventory or external comparison standard. The observed directional differences characterize the present case and tested assumptions and do not support a general judgment about the relative performance of the tools. The framework may be adaptable to other jurisdictions, but its transferability should be evaluated using additional sites, remediation technologies, and independently documented activity inventories. Full article

Nighttime light (NTL) data is widely used to monitor urban development, economic activity and population distribution, supporting socio-economic analysis and sustainable development planning. SDGSAT-1 NTL data, with its multiple bands and high resolution, has become an important source for studying human activity patterns. However, directly summing radiance values on geographic grids assumes equal contributions from all grid cells, regardless of the differences in the ground area represented by each cell. As a result, regional nighttime light totals may be systematically distorted, particularly in cross-latitude analyses where pixel areas differ substantially. To address this aggregation issue, this study proposes a physically explicit area-weighting framework that converts SDGSAT-1 radiance to radiant flux by incorporating the actual surface area represented by each grid cell. The framework is validated using 25 cities spanning different latitudes and development levels in the Northern Hemisphere. Results show that the radiant flux model, which captures total emitted power, demonstrates improved performance over radiance-based aggregation (a density-based measure) in population estimation (R² = 0.85 vs. 0.82). By shifting from light intensity to integrated total energy, this approach improves cross-latitude comparability and enhances the methodological robustness of NTL-based analyses. Full article

Drawing on ERA5 reanalysis data for 2005–2025, this study examines long-term environmental change across China’s eight major deserts and on this basis develops a data-informed framework for integrating geoscientific evidence into geographical fieldwork education. Temperature change, surface radiation and vertical soil moisture profiles are used to construct inquiry tasks on regional warming, land–atmosphere interactions and dryland hydrology. A four-dimensional resource assessment integrating solar resource abundance, thermal stability, soil moisture support and wind exposure stability is then applied using multi-criteria decision analysis (MCDA) to compare relative resource characteristics and ecological constraints across desert regions. The contrasting resource profiles of the Taklimakan, Tengger, and Kubuqi Deserts provide the basis for a scenario-based decision-making activity incorporating equal-weight, energy-priority, and ecology-priority perspectives on renewable energy development and ecological protection. Rather than treating deserts as static landscapes, the proposed framework positions them as dynamic coupled human–environment systems and is designed to engage students in interpreting long-term datasets, comparing regional processes and evaluating sustainability trade-offs. The study illustrates how environmental datasets can be organised into fieldwork questions, analytical tasks and decision scenarios, offering an adaptable framework in which quantitative reasoning, systems thinking and evidence-based sustainability learning are specified as intended educational outcomes in higher geographical education. Full article

Measurements are presented from a purpose-built outdoor test facility for the assurance of situational awareness sensors for Autonomous Vehicles (AVs). The testbed included meteorological instrumentation for an accurate high-resolution picture of weather traversing the site. Static targets at ranges up to 250 m were observed simultaneously with multiple radar, LiDAR and camera systems exposed to the natural weather events over a two-year period. The aim of the testbed was to collect data over a prolonged period of time (2 years) to ensure the maximum amount of variation in weather was encountered. Uniquely, the testbed treats the measurement of weather as an equal metrology challenge to that of measuring the CAV sensor response with the aim of understanding the extent to which it is possible to quantitatively correlate sensor performance degradation with weather parameters. In this paper case study examples of the testbed data for rainfall, fog and ‘ideal’ neutral conditions have been analysed. Correlations between sensor performance degradation and weather parameters were observed in several cases, including comparisons with rain rate and MOR (visibility). However, large uncertainties and complex interactions between weather-related performance reduction and secondary weather effects, like sensor window and target surface wetting, make an explicit determination of the severity at which a weather condition causes a sensor to become untrustworthy, problematic. Full article

This study assesses roadside grass biomass harvesting and allocation to collection centers using spatially explicit methods for preliminary district-heating supply-chain planning. Road-network data combined with mowing data for county roads were used to estimate theoretical, technically recoverable, and annual energy potentials in Kołobrzeg County, Poland, while high-resolution aerial imagery was used to identify roadside sections where biomass cannot be harvested, such as bridges, paved shoulders, gravel surfaces, and bicycle paths. Dijkstra’s algorithm calculated shortest network distances, after which a custom assignment procedure allocated road nodes and associated biomass to collection centers using either the baseline distance-based rule or its capacity-constrained extension. The estimated annual energy potential ranged from 14.9 to 38.1 TJ/a among the analyzed municipalities. In the two-center scenarios, the number of nodes assigned to the southern center increased from 25 under its $3000\mathrm{t}$ limit to 41 under equal $5875\mathrm{t}$ limits at both centers. The results show that combining aerial-image interpretation, biomass-to-energy estimation, and network-based allocation provides a transparent framework for identifying priority collection areas and organizing roadside biomass transport. The proposed workflow can support local authorities in preliminary biomass supply-chain planning and can be adapted to other regions with suitable spatial data. Full article

Background/Objectives: Schools constitute the principal setting for the identification of children’s psychosocial risk and the delivery of preventive support, and school-health surveillance therefore depends on informant reports. Selection of the reporting informant is constrained by feasibility, cost, and questionnaire length, which frequently preclude multi-informant assessments, and the question of whether adult and child reports index a common property has predominantly been examined in single-country designs. The present study estimated the criterion-related validity of child, teacher, and principal reports of school safety across multiple education systems, against outcomes spanning children’s experience, institutional functioning, and externally assessed achievements; the estimand was thus informant-specific validity rather than cross-informant agreement. Methods: TIMSS 2023 Grade 4 data from 12,955 schools in 63 education systems (395,961 children, 27,100 teacher records) were analyzed, with child, teacher, and principal reports modeled as separate informants. Students were randomly split within schools so that no student contributed both a predictor and an outcome; the split was replicated 50 times and averaged. Convergence was evaluated with a multitrait–multi-informant model, with ceiling effects and differential unreliability specified as rival explanations; informant contributions were estimated by an exact relative-importance (LMG) variance decomposition, with response surface analysis reported as a secondary characterization of directional discrepancy. Results: Median school-level cross-informant correlations were below 0.10 and were not attributable to ceiling effects or to unreliability. With all three informants retained, the child report accounted for 95% (95% CI 92–97) of the informant-explained variance in school belonging and 75% (65–82) in peer victimization, but 44% (28–59) in mathematics, where the three contributions were approximately equal. These proportions were computed on a modest total: the three informant scores jointly explained between 1% and 13% of between-school variance. The pattern was robust to informant, item, covariate, and weighting specifications, and to correction for differential predictor unreliability. Conclusions: Criterion-related informant validity in school safety measurement was domain-specific. For outcomes describing children’s experience, adult reports contributed substantially lesser than child reports and cannot be regarded as interchangeable substitutes for children’s reports of experienced safety. Because school-health surveillance, risk identification, preventive targeting, and resource allocation depend on these inputs, valid monitoring requires student self-reports rather than adult proxy reports alone. Full article

Long-term degradation of vanadium redox flow batteries (VRFBs) is strongly coupled with the evolution of discharge direct current internal resistance (DCIR). This work employs 213 constant-current cycles on a 4 cm² single cell to examine the associations between discharge DCIR and capacity, discharge voltage and efficiencies. The average values of the initial 10 cycles were used as the baseline. Multiple statistical approaches, including detrending, differencing, moving-block bootstrap, and internal chronological holdout evaluation were used to assess the influence of shared temporal trends and serial dependence. Self-calculated DCIR matches test records closely with merely 1.03% average relative error. After trend correction, normalized DCIR maintains a strong negative correlation with normalized capacity. The established free-intercept quadratic model achieved the best full-data fitting performance, with an R² of 0.99593 and a root mean square error (RMSE) of 0.00524. The fitted empirical relationship indicates that equal increments in normalized DCIR are associated with larger concurrent capacity-state reductions in the higher-resistance region. During the internal chronological holdout evaluation, the DCIR-based model yielded an RMSE of 0.00854. These results establish a statistically robust DCIR–capacity relationship over long-term cycling and demonstrate the potential of routinely recorded discharge DCIR as a low-cost concurrent capacity-state indicator, providing a quantitative foundation for its future extension to broader VRFB operating scenarios. Full article

This paper investigates the cross-sectional reliability and persistence of commonly used portfolio performance indicators when employed as portfolio selection metrics over a broad multi-asset investment universe. Using 14 years of daily data (2012–2025) spanning a diverse multi-asset universe, we construct the full cross-section of feasible equally weighted portfolios and assess how consistently different selection metrics identify top-performing portfolios out of sample. At each decision date, portfolios are selected by maximizing an in-sample decision criterion, after which the same criterion is re-evaluated out of sample across the entire portfolio universe and the selected portfolio is ranked based on its out-of-sample metric value. This cross-sectional, rank-based framework is designed to mitigate spurious predictability driven by correlation, overfitting, and look-ahead bias by evaluating each selected portfolio relative to the full cross-sectional opportunity set using strictly out-of-sample rankings. Across multiple time scales, we document a robust separation between decision accuracy and decision stability. While the Omega ratio maximizes short- and medium-horizon selection accuracy, the Calmar ratio exhibits superior tail robustness and substantially higher decision persistence. At longer horizons, average selection accuracy converges across the metrics, while Calmar retains a substantial stability advantage. The main contribution of this study is the introduction of a cross-sectional decision-based evaluation framework that assesses performance measures according to the persistence of their portfolio selection decisions rather than solely their realized return characteristics. The results indicate that different selection metrics emphasize distinct dimensions of decision quality, including tail dominance, stability, and persistence, rather than converging to a single notion of optimality. Our findings are further supported by robustness checks based on alternative portfolio sizes and bootstrap-based statistical validation. Full article

This study asks whether chief executive compensation at private nonprofit four-year institutions reflects financial performance or financial scale. The sample is 569 institutions in the 1000 to 4999 enrollment band, matched to IPEDS finance data for 2018–19 through 2023–24 and IRS Form 990 compensation data. Financial scale dominates: when entered jointly, the revenue coefficient is 0.295, enrollment is insignificant, and a Wald test rejects the equality of coefficients, although compensation remains positively associated with performance (0.088, p = 0.001). As a test of agency theory, institutions whose revenue and net tuition both declined are compensated about 14 percent below prediction; in an exploratory severity analysis, the discount reaches about 16 percent when each fell more than 20 percent in constant dollars. These are cross-sectional associations, not causal effects of board policy. Panel estimates are consistent with the discount developing over the window (the growth differential is significant at the 10 percent level). Adjustment is incomplete: about half of institutions in real decline are paid above prediction; the breakaway core label for this group is descriptive, not a finding of excess, and its larger enrollment is not distinguishable from the sector-wide pattern. Because the sector’s recovery is nominal rather than real, above-benchmark compensation occurs amid real contraction. Full article