Search Results (4,918)

The influence of station-to-station line orientation on sea current speed observations using Coastal Acoustic Tomography (CAT) was quantitatively investigated. For this purpose, we conducted CAT experiments at five stations in Yeosu Bay, South Korea. Through these experiments, the sea current speeds were estimated along a total of six tomographic observation lines with different orientations, and the results were compared with current speeds measured simultaneously by an Acoustic Doppler Current Profiler (ADCP). The comparison showed that the concordance between tomography-estimated sea current speed and ADCP-measured sea current speed tended to decrease as the acute angle between the predominant tidal current direction in Yeosu Bay and a tomographic observation line increased. This tendency is interpreted as arising because the smaller the difference between the two one-way travel times obtained during tomographic observations, the greater the effect of the travel time measurement error whose magnitude is relatively direction-independent. This interpretation was supported by a simple numerical simulation. Furthermore, quantitative analysis of these simulation results indicated that a smaller acute angle between the predominant sea current direction in the survey area and a tomographic observation line enhances the robustness of sea current speed estimation against travel time measurement errors. The results show that the station-to-station line in CAT should be arranged considering the predominant sea current direction in the survey area, which can provide an important guideline for selecting station locations. Full article

Precipitation modeling is vital for water resource management in basins with limited gauged data. In this study, the 5 km Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product was downscaled to 1 km at the annual and mean monthly scales for the Catamayo–Chira catchment, a key water source for Ecuador and Peru. Single-variable and multivariable machine learning (ML) methods were applied to data from 10 gauged stations from 2001 to 2023. Predictors included longitude (Long), latitude (Lat), altitude, Normalized Difference Vegetation Index, and Land Surface Temperature. Performance metrics were utilized to assess the methods. The results demonstrated a notable improvement after downscaling compared to the original CHIRPS estimates. The most effective single-variable methods were simple linear regression (LR) for Long and Lat, and non-linear ML methods such as support vector machine with linear kernel (SVM-lin) and with radial basis function kernel (SVM-rbf), and artificial neural networks (ANN), employing all predictors. Surprisingly, single-variable linear methods yield better results than multivariable non-linear ones. These models provided acceptable fits to annual and mean monthly observations, and their performance tended to be better during the drier months. Downscaled annual precipitation distributions successfully captured differences between “El Niño” and non-“El Niño” years. The current study could be replicated in basins with limited gauging data, thereby enhancing water resource management. Full article

Carbon fluxes from the atmosphere to the ocean and from the ocean surface to the deep ocean are a key pathway in the long-term sequestration of anthropogenic CO₂. Particulate Organic Carbon (POC), which comprises living plankton, detritus and other microscopic organisms, is a very dynamic carbon pool in surface waters, so an ability to assess POC reliably from satellites and autonomous profilers is fundamental to the quantification of the reservoirs and fluxes of carbon within the ocean, and to assess their response to climate change. In situ records from sample filtration during dedicated hydrographic surveys are limited both in terms of spatial coverage and time, so reliable algorithms are required that make use of readily available autonomously collected data that provide much better spatial and temporal coverage. In this paper, algorithms that use ocean colour data from satellites to estimate POC are re-assessed, and then the satellite-derived products are compared with near-surface in situ observations from biogeochemical (BGC) Argo profilers. The satellites and in situ BGC-Argo records match each other to within 30%, but a regional bias persists that may be related to the BGC-Argo fluorometers overestimating the chlorophyll concentration in the Southern Ocean. A simple coarse-resolution regional correction to the observed chlorophyll-a concentration and backscatter coefficient, plus the removal of clear outliers, improves the agreement to approximately 15%. The association of POC with the surface chlorophyll value is so strong that an algorithm based on chlorophyll-a alone provides an almost equally good estimate of POC compared with more complex algorithms that incorporate additional bio-optical variables such as the backscattering coefficient. Full article

This study examines the social burden and systemic infrastructure vulnerabilities associated with fatal road traffic incidents in Medellín, Colombia, over the period 2008–2025. Using official records from the Secretaría de Movilidad de Medellín, the analysis quantifies impact through Years of Potential Life Lost (YPLL) and high-resolution spatiotemporal clustering, moving beyond simple fatality counts or economic valuation alone. Phase I applies an age-group proportional allocation method to estimate YPLL for 2762 fatal road traffic incidents, while Phase II employs a spatiotemporal geostatistical framework (ICCE-T) to detect statistically significant concentration clusters. Results indicate that these incidents generated 100,851 years of potential life lost, with individuals aged 15–35 accounting for 64.7% of total YPLL, and the 20–25 age group alone contributing 21.5% of the overall burden. Spatial analysis reveals persistent clustering along key urban corridors, particularly in Comuna 10 (La Candelaria), identifying recurrent nodes of elevated systemic vulnerability. By integrating epidemiological measurement with spatiotemporal analysis, the study provides a decision-oriented analytical framework to support resilient, evidence-based urban mobility interventions and guide strategic public investment under the Safe System approach. Full article

Estimating grades in small-volume, high-grade volcanogenic massive sulfide (VMS) deposits can be difficult due to sharp changes in mineralization and limited data coverage around high-grade zones. This study compares ensemble machine learning models with interpolation and geostatistical methods to compare gold estimation and grade-tonnage results. Random Forest and Gradient Boosting were trained using drillhole composites and evaluated against Inverse Distance Weighting (IDW), Simple Kriging (SK), and Ordinary Kriging (OK). The trained models were applied across the block model to generate continuous grade predictions and support grade-tonnage calculations at multiple cutoff grades. The ensemble models showed lower RMSE and higher R² values and captured grade patterns more efficiently than traditional methods. Grade-tonnage comparison indicated that IDW generated the highest contained gold equivalent at low cutoff grades, while OK and Gradient Boosting produced more consistent and geologically reasonable estimates. Overall, the results show that machine learning methods can complement traditional estimation techniques when combined with geological domain control and appropriate model tuning. Full article

4D millimeter-wave radar provides a promising solution for robust perception in adverse weather. Existing detectors still struggle with sparse and noisy point clouds, and maintaining real-time inference while achieving competitive accuracy remains challenging. We propose SGE-Flow, a streamlined PointPillars-based 4D radar 3D detector that embeds lightweight spatiotemporal geometric enhancements into the voxelization front-end. Velocity Displacement Compensation (VDC) leverages compensated radial velocity to align accumulated points in physical space and improve geometric consistency. Distribution-Aware Density (DAD) enables fast density feature extraction by estimating per-pillar density from simple statistical moments, which also restores vertical distribution cues lost during pillarization. To compensate for the absence of tangential velocity measurements, a Transformer-based Inter-frame Flow (IFF) module infers latent motion from frame-to-frame pillar occupancy changes. Evaluations on the View-of-Delft (VoD) dataset show that SGE-Flow achieves 53.23% 3D mean Average Precision (mAP) while running at 72 frames per second (FPS) on an NVIDIA RTX 3090. The proposed modules are plug-and-play and can also improve strong baselines such as MAFF-Net. Full article

Although higher technical efficiency is theoretically expected to enhance farm sustainability, empirical evidence in livestock systems remains ambiguous. This study investigates the interplay between technical efficiency and sustainability using data from 72 farms in Tokat, Türkiye, selected via stratified random sampling. Technical efficiency was calculated using Data Envelopment Analysis (DEA), while a multidimensional Sustainability Index was constructed using the analytic hierarchy process (AHP) for weighting dimensions. Determinants of inefficiency were estimated using a Tobit model. Results revealed an average technical efficiency of 0.717 and a Composite Sustainability Index of 0.41, classifying the sector as “moderate” but fragile. Crucially, the Kruskal–Wallis test showed no statistically significant difference in sustainability scores across efficiency groups (p > 0.05). This finding confirms a “structural disconnect,” demonstrating that high technical efficiency does not guarantee sustainability because of systemic bottlenecks such as dysfunctional organizations and infrastructure deficits. Furthermore, Tobit results showed that non-farm income and internet access were positively associated with technical efficiency, whereas indebtedness was negatively associated. Consequently, achieving lasting sustainability requires a shift from simple productivity support to structural modernization policies, including the integration of sustainability-oriented criteria such as institutional strengthening, environmental management, and financial capacity into existing support schemes. Full article

The increasing cost of energy and the need for low-carbon solutions have strengthened interest in wastewater as a stable and underutilized source of recoverable heat. This study assesses the technical feasibility, economic viability, and environmental benefits of a wastewater heat recovery system based on a case study of the Gorzyce municipal wastewater treatment plant in Poland. Water-to-water heat pump configurations and application scenarios are analyzed together with data-driven forecasting of wastewater outflow using artificial neural networks (MLP and RBF). Operational data from 2025 were used to estimate thermal potential and support system sizing. RBF networks provided more accurate flow forecasts than MLP models, improving reliability of energy recovery planning. Results show that even with a 1 K cooling depth, the annual heat recovery potential reaches about 1.16 GWh. The proposed heat pump system achieved the COP values of 3.0–3.4 and seasonal COP around 3.2, confirming high technical performance supported by stable wastewater temperatures. The recovered heat can fully cover the facility’s heating demand, demonstrating clear technical feasibility. The economic analysis indicates annual savings of about EUR 2310 compared to gas heating, with a simple payback period of roughly 13 years, reduced to 7–8 years when combined with on-site photovoltaics. Environmental benefits include CO₂ emission reductions of about 5.5 tones per year. Overall, wastewater heat recovery supported by predictive modeling and renewable electricity is a practical, cost-effective, and environmentally friendly solution for municipal infrastructure. Full article

Vapour-compression refrigeration and cooling systems represent a significant share of global electricity consumption, being estimated to account for approximately 10% to 20% of the worldwide electricity demand, which highlights their critical impact on energy efficiency and sustainability. In this context, improving the thermodynamic and exergoeconomic performance of refrigeration cycles, as well as the appropriate selection of the refrigerant, has become a key research priority. Therefore, this work aims to comparatively evaluate the energy, exergy, exergy cost, and exergoeconomic performance of three vapour-compression refrigeration cycle configurations: a simple cycle, a two-stage cycle with a flash tank, and a two-stage cycle with a flash tank and a mixing chamber. Six refrigerants (R134a, R600a, R290, R1234yf, R1234ze (E), and R717) were analysed under evaporation temperatures of 228–238 K and condensation temperatures of 298–308 K. The performance evaluation was carried out using the Fuel–Product–Residue (FPR) methodology, considering the coefficient of performance (COP), exergy efficiency, system irreversibilities, and exergy and exergoeconomic costs. The results indicate that the incorporation of the mixing chamber increases the COP by up to 7% and the exergy efficiency by up to 6% compared to the simple cycle, while reducing exergoeconomic costs by up to 10% for the most favourable refrigerants. Among the working fluids analysed, R600a exhibits the best overall performance (COP up to 4.3 and an exergy efficiency of 33%), followed by R290 and R717, whereas R1234yf shows the lowest efficiencies (COP ≈ 3.7 and exergy efficiency ≈ 28%) and the highest exergoeconomic costs. These findings demonstrate that the design of vapour-compression refrigeration systems should involve the joint selection of the cycle configuration and the refrigerant based on integrated energy, exergy, and exergoeconomic criteria. Overall, the results highlight that both the refrigerant and the cycle configuration must be selected simultaneously, considering energy, exergy, and exergoeconomic criteria, to achieve more efficient and sustainable industrial applications. Full article

There is little question that the distribution and numbers of large mammals have been altered by human activities. In North America, native ungulates have declined substantially since the mid-1800s. There is no baseline, however, against which to measure the magnitude of changes aside from anecdotal accounts or published information derived from a single location at a single point in time and extrapolated to derive a continent-wide population estimate. One example is bighorn sheep (Ovis canadensis), which were estimated to number from 1.5 to 2.0 million individuals in 1850. The literature is replete with references to those numbers, yet the derivation of that ‘estimate’ has not been formally questioned; bighorn sheep, which are endemic to North America, currently number approximately 85,000 individuals. We combined basic math and logic to develop a simple model of population density at differing scales and examined results reductio ad absurdum to question the estimate of 1.5 million bighorn sheep and the magnitude of the hypothesized decline that followed. We evaluated the plausibility of bighorn sheep population densities that must have existed at four spatial scales if there were ≥1.5 million individuals and argue that such numbers likely never existed. Continued use of 1.5 million bighorn sheep as a baseline against which to assess the magnitude of anthropogenic impacts is unwise, inappropriate, and apt to become problematic in the context of the conservation of habitat, populations, or restoration to historical ranges. Credibility matters in science, management, and conservation. Full article

Background/Objectives: Pediatric shock is a final common pathway of cardiovascular failure across diverse emergencies, yet data from mixed emergency cohorts outside intensive care units remain limited. This study aimed to describe the distribution, etiologic subtypes, and clinical correlates of shock in children presenting within a diagnosis-based emergency cohort. Methods: A retrospective single-centre study was conducted in children aged 0–16 years presenting with selected acute pediatric emergencies, among whom cases with and without shock were compared. Shock was defined using documented diagnoses and compatible hemodynamic features, and multiple etiologic types of shock were analyzed, including hypovolemic, septic, cardiogenic, and anaphylactic shock. Demographic and diagnostic variables—age, length of stay, organ support, age strata, and selected comorbidities—and baseline clinical features were compared between children with and without shock using non-parametric and χ²/Fisher’s exact tests. Results: Within the prespecified diagnosis-based analytic cohort, 36/128 children (28.1%) met the study criteria for shock and occurred across all prespecified acute pediatric emergency groups, with the highest proportional burden in heart failure and meningitis; this proportion should not be interpreted as an emergency-department prevalence estimate. Children with shock were younger, with clustering in infants < 1 year and those aged 5–9 years, and tended to stay longer in hospital. Pre-existing cardiac disease, severe dehydration, and altered mental status/coma were more frequent among children with shock. Septic and cardiogenic shock required the most intensive organ support. Conclusions: In this pediatric emergency cohort, shock emerged as a clinically relevant and etiologically heterogeneous complication across diverse acute presentations, with a distinct age-related vulnerability pattern and consistent associations with readily identifiable bedside clinical features. Simple bedside information—particularly cardiac comorbidity, dehydration, and altered consciousness—may assist the early recognition of children with evolving circulatory failure and support closer monitoring and timely escalation of care. By focusing on a mixed emergency population outside the intensive care unit, this study provides a real-world clinical perspective that may help refine early bedside assessment and improve vigilance for shock in pediatric emergency departments. Full article

Capillary refill time (CRT) is widely used in pediatric and emergency medicine as an indicator of peripheral circulation. CRT is defined as the time required for the skin to return to its original color after external compression is applied and then released. In current clinical practice, however, CRT assessment remains qualitative and relies heavily on the magnitude and consistency of compression applied by the measurer, as well as on subjective visual color perception, which together result in limited measurement reliability. To improve measurement reliability, several quantitative CRT measurement devices have been developed. Nevertheless, these devices are dedicated specifically to CRT measurement, which limits their versatility and complicates clinical implementation. In this study, we developed a simple and quantitative CRT measurement method using a smartphone. Based on skin color changes captured by the rear camera, we proposed a method to assess the adequacy of the applied compression force and implemented an application to calculate CRT. In addition, we investigated an algorithm to reduce the influence of pulse waves observed in the post-release waveform, enabling more stable CRT estimation. Furthermore, a dedicated smartphone case was designed to immobilize the finger during measurement, thereby improving measurement reliability. The feasibility of the proposed method was evaluated by examining agreement with a previously developed CRT measurement device and by assessing intraexaminer reliability, confirming its effectiveness. Full article

Background/Objectives: Dried blood spot (DBS) sampling, a technique for collecting capillary blood samples, is widely used in therapeutic drug monitoring, pharmacokinetic and toxicology research, newborn screening, and population health because it enables simple, non-invasive sampling across large cohorts. However, it presents several challenges, mainly due to the effect of hematocrit (HCT), which can influence the quantification of analytes. Methods: A combination of methods was developed to estimate the HCT and blood volume in DBS samples. Image analysis and hemoglobin (Hb) quantification using UV-VIS spectrometry were used for HCT estimation, and conductivity was used to determine blood volume. DBS samples from five donors were prepared with HCT between 0.2 and 0.6 and were used to prepare calibrators and quality control samples. The developed methods were applied to 23 samples obtained from ten adult patients with inflammatory bowel disease. Results: The methods for HCT determination using image analysis or Hb measurements were linear (r² > 0.994), with acceptable accuracy (90.3–102.2%) and precision (<7.4%). Moreover, the conductivity method was linear (r² = 0.999) and enabled accurate (96.8–100%) and precise (<5.65%) determination of blood volume in DBS samples. All three methods were in good agreement with the reference values in patient samples. Finally, strategies to correct HCT- and volume-related bias in DBS samples were proposed for analytes with different blood cell-to-plasma partition coefficients. Conclusions: We accurately and precisely estimated HCT in DBS samples using image analysis and Hb determination, and the volume of blood in DBS using conductivity measurement. We evaluated different approaches and derived an optimal procedure for HCT-bias correction. Full article

Nowadays, there is a global trend of consuming lower-alcohol beverages, while there is a market trend for consuming ready-to-drink products. The present study describes the development of new alcoholic beverages by the simple addition of rose water to the traditional marc spirit tsipouro. New beverages have lower alcohol content (30% v/v) than the mother tsipouro (40% v/v), exhibiting noteworthy antioxidant activity. Tsipouro–rose water beverages exhibited several aroma volatiles which originated from rose water, as determined by SPME GC-MS. Among them were the phenylethyl alcohol, eucalyptol, linalool, citronellol, geraniol, alpha-terpineol, which are known as rose water aroma compounds. The antioxidant activity of tsipouro–rose water beverages as estimated by the Folin, FRAP and DPPH assays appeared to be higher than the diluted tsipouro of the same alcohol content in a dose-dependent manner after mixing and after storage for 30 and 60 days. Preliminary organoleptic evaluation indicated that tsipouro–rose water products exhibit a rose-like aroma and were of acceptable organoleptic quality, especially that with a lower concentration of rose water. Full article

Biological wastewater treatment relies primarily on activated sludge and anaerobic digestion for the removal of organic matter. In urban wastewater treatment plants discharging into eutrophication-sensitive environments, the simultaneous removal of carbon, nitrogen, and phosphorus is required to meet increasingly stringent discharge limits. Under these conditions, the transformation of complex organic matter into volatile fatty acids (VFAs) represents a more efficient strategy than complete mineralization, as biodegradable carbon is essential to sustain biological nitrogen and phosphorus removal processes. In this study, an anaerobic sequencing batch reactor was operated under acidogenic conditions to promote the conversion of organic matter into VFAs. For the first time, this study demonstrates how temperature-controlled acidogenic pretreatment can reliably supply biodegradable carbon to support efficient downstream nitrogen and phosphorus removal in municipal wastewater treatment. A kinetic model was developed to describe the temporal evolution of the different carbon fractions involved in anaerobic digestion, including biodegradable and non-biodegradable organic matter, intermediate compounds, short-chain volatile fatty acids, and biogas. The model assumes first-order kinetics and constant biomass concentration and was successfully validated against experimental data, with deviations below 10%. Estimated kinetic constants exhibited a strong temperature dependence, particularly for hydrolysis and acidogenic pathways, whereas methanogenic steps showed lower sensitivity. Overall, the results demonstrate that temperature is a key operational parameter governing acidogenic performance and carbon transformation pathway. The simple and novel proposed kinetic model provides a useful tool for predicting VFA production and optimizing anaerobic pretreatment strategies aimed at enhancing downstream nutrient removal processes. Optimizing SBR operation for nutrient removal also offers sustainability benefits by improving resource efficiency and reducing energy and chemical inputs. Full article