Search Results (13)

The alpine valley agricultural region is the most intensively human-impacted ecosystem type on the Qinghai–Tibet Plateau, and its ecosystem respiration (RE) plays an important role in regional carbon cycling and climate change responses. However, it remains unclear whether systematic differences exist in the spatiotemporal patterns of RE and its environmental controls across high-altitude agricultural watersheds. Using multi-source remote sensing and reanalysis data from 2000 to 2024, this study focuses on two representative valley agricultural basins on the Qinghai–Tibet Plateau—the Huangshui River Basin (HSH) and the Yijianglianghe River (YJLH). A dual-model framework combining a Random Forest model and a Lloyd–Taylor mechanistic model was developed to examine the spatiotemporal dynamics, driving mechanisms, and temperature sensitivity of RE. The results show that RE increased in both basins over the study period, while their dominant controlling mechanisms differed markedly. Gross primary productivity (GPP) was the most important driver in both basins (23.6% in HSH and 24.5% in YJLH). However, temperature and precipitation contributed more in YJLH (14.5% vs. 9.4%), suggesting that RE in the higher-altitude basin is more strongly constrained by hydrothermal conditions under colder and harsher climates. Spatially, high RE values in the HSH were mainly concentrated in mid- and low-elevation valley farmlands, whereas the YJLH exhibited a clear decrease in RE with increasing elevation, indicating a stronger topographic control. Both basins showed significant spatial clustering of RE (Moran’s I ≈ 0.93), with stronger spatial aggregation in the HSH. Temperature sensitivity (Q₁₀) generally increased with elevation, and the YJLH exhibited markedly higher Q₁₀ values in high-altitude regions, indicating stronger temperature responsiveness under extreme cold conditions. Empirical Q₁₀ values were consistently higher than theoretical estimates, implying that ecosystem respiration is not only directly driven by temperature, but may also be amplified indirectly through enhanced vegetation productivity and increased substrate availability. Overall, this study reveals a clear divergence in RE control mechanisms across valley agricultural systems on the Qinghai–Tibet Plateau: productivity-driven regulation dominates in low-elevation regions, whereas hydrothermal constraints become increasingly important in high-altitude environments, leading to a transition from “productivity control” to “hydrothermal constraint control.” This shift highlights the nonlinear response of alpine agroecosystems to elevation gradients and climate change, providing mechanistic evidence for understanding carbon cycling in high-altitude anthropogenic ecosystems. Full article

The transformation of trade structures represents a core dimension of economic integration in Central and Eastern Europe, particularly following EU accession and deeper participation in global value chains. Romania and Poland, despite similar institutional frameworks, have exhibited distinct trade trajectories in terms of specialisation patterns, intra–industry trade intensity and external balance. Understanding these differences is essential for assessing the quality of integration, competitiveness and structural upgrading in emerging European economies. Existing empirical studies often focus on single indicators or shorter time horizons, leaving room for a comprehensive, long–run comparative assessment based on multiple trade dimensions. The purpose of this article is to compare the evolution of trade specialisation, intra–industry trade and trade balance in Romania and Poland over the period 2002–2024. The study aims to identify similarities and divergences in their trade structures and to evaluate whether trade expansion has been accompanied by qualitative improvements and external rebalancing. By adopting a comparative perspective, the article seeks to contribute to the literature on trade integration and structural transformation in Central and Eastern Europe. The analysis is based on annual sectoral data on imports and exports for Romania and Poland covering the period 2002–2024. Three complementary indicators are employed: a symmetric Balassa–type revealed comparative advantage index (RSCA), the Grubel–Lloyd intra–industry trade index, and an export–import coverage ratio used as a proxy for sectoral trade balance. Descriptive analysis is complemented by linear trend estimation and structural break tests in order to capture long–run dynamics and identify major shifts associated with EU accession and post–crisis adjustments. The results show that while both countries experienced substantial trade expansion, Poland achieved a significantly stronger qualitative outcome, characterised by higher intra–industry trade intensity and convergence towards aggregate trade balance by 2024. Romania, although recording improvements in trade composition, maintained a persistent trade deficit. The article adds value by providing a long–run, indicator–based comparative framework that integrates specialisation, intra–industry trade and external balance into a single empirical analysis. Full article

In this paper, we explore using the Harrow–Hassidim–Lloyd (HHL) algorithm to address scientific and engineering problems through quantum computing, utilizing the NWQSim simulation package on a high-performance computing platform. Focusing on domains such as power-grid management and climate projection, we demonstrate the correlations of the accuracy of quantum phase estimation, along with various properties of coefficient matrices, on the final solution and quantum resource cost in iterative and non-iterative numerical methods such as the Newton–Raphson method and finite difference method, as well as their impacts on quantum error correction costs using the Microsoft Azure Quantum resource estimator. We summarize the exponential resource cost from quantum phase estimation before and after quantum error correction and illustrate a potential way to reduce the demands on physical qubits. This work lays down a preliminary step for future investigations, urging a closer examination of quantum algorithms’ scalability and efficiency in domain applications. Full article

The control chart is a fundamental tool in statistical process control (SPC), widely employed in manufacturing and construction industries for process monitoring with the primary objective of maintaining quality standards and improving operational efficiency. Control charts play a crucial role in identifying special cause variations and guiding the process back to statistical control. While Shewhart control charts excel at detecting significant shifts, EWMA and CUSUM charts are better suited for detecting smaller to moderate shifts. However, the effectiveness of all these control charts is compromised when the underlying distribution deviates from normality. In response to this challenge, this study introduces a robust mixed EWMA-CUSUM control chart tailored for monitoring processes characterized via symmetric but non-normal distributions. The key innovation of the proposed approach lies in the integration of a robust estimator, based on order statistics, that leverages the generalized least square (GLS) technique developed by Lloyd. This integration enhances the chart’s robustness and minimizes estimator variance, even in the presence of non-normality. To demonstrate the effectiveness of the proposed control chart, a comprehensive comparison is conducted with several well-known control charts. Results of the study clearly show that the proposed chart exhibits superior sensitivity to small and moderate shifts in process parameters when compared to its predecessors. Through a compelling illustrative example, a real-life application of the enhanced performance of the proposed control chart is provided in comparison to existing alternatives. Full article

Shipping, as an important part of the global supply chain, has always been quite sensitive to maritime accidents. Fatality and injury are important metrics indicating an accident’s severity. Understanding the driving factors of fatality and injury outcomes of maritime accidents can help to improve supply chain security. Based on maritime accident data obtained from the Lloyd’s List Intelligence, this paper identifies accident-prone sea areas through kernel density estimation (KDE) and selects two of the areas to conduct a comparative study on factors contributing to fatality and injury outcomes of maritime accidents through zero-inflated negative binomial (ZINB) and elastic analysis. The results show that collision and ship age significantly impact the number of fatalities and injuries. Specifically, collision and ship age have greater impacts on fatality and injury outcomes of accidents that occurred in the English Channel and North Sea. Whether the accident occurs in ports and whether the accident causes a total loss have more significant impacts on the fatality and injury outcomes of accidents in the Black Sea and the eastern Mediterranean Sea. The research results can potentially support the reduction of fatalities and injuries in maritime accident and help to manage maritime risk. Full article

In this research, a new application using broadband ship noise as a source-of-opportunity to estimate the scattering field from the underwater targets is reported. For this purpose, a field trial was conducted in collaboration with JASCO Applied Sciences at Duncan’s Cove, Canada in September 2020. A hydrophone array was deployed in the outbound shipping lane at a depth of approximately 71 m to collect broadband noise data from different ship types and effectively localize the underwater targets. In this experiment, a target was installed at a distance (93 m) from the hydrophone array at a depth of 25 m. In this study, a matched field processing (MFP) algorithm is utilized for localization. Different propagation models are presented using Green’s function to generate the replica signal; this includes normal modes in a shallow water waveguide, the Lloyd-mirror pattern for deep water, as well as the image model. We use the MFP algorithm with different types of underwater environment models and a proposed estimator to find the best match between the received signal and the replica signal. Finally, by applying the scatter function on the proposed multi-channel cross correlation coefficient time-frequency localization algorithm, the location of target is detected. Full article

Scirtothrips dorsalis Hood is an invasive and foliar pest of Florida blueberry that reduces plant growth by feeding on new leaf growth. A sampling plan is needed to make informed control decisions for S. dorsalis in blueberry. Fourteen blueberry fields in central Florida were surveyed in 2017 and 2018 after summer pruning to determine the spatial and temporal distribution of S. dorsalis and to develop a fixed-precision sampling plan. A sampling unit of ten blueberry shoots (with four to five leaves each) was collected from one blueberry bush at each point along a 40 × 40 m grid. Field counts of S. dorsalis varied largely ranging from zero to 1122 adults and larvae per sampling unit. Scirtothrips dorsalis had aggregated distribution that was consistent within fields and temporally stable between summers, according to Taylor’s power law (TPL) (aggregation parameter, b = 1.57), probability distributions (56 out of 70 sampling occasions fit the negative binomial distribution), Lloyd’s index (b > 1 in 94% occasions), and Spatial Analysis by Distance IndicEs (31% had significant clusters). The newly developed fixed-precision sampling plan required 167, 42, seven, or three sampling units to estimate a nominal mean density of 20 S. dorsalis per sampling unit with a precision of 5%, 10%, 25%, or 40%, respectively. New knowledge on S. dorsalis distribution will aid in evaluating the timing and effectiveness of control measures. Full article

Structural failures in the barge midship sections can cause operational delay, sinking, cargo loss and environmental damage. These failures can be generated by the barge and cargo weights, and wave load effects on the midships sections. These load types must be considered in the design of the barge midship sections. Here, we present the structural analysis of a barge midship section that has decreased up to 36.4% of its deck thickness caused by corrosion. This analysis is developed using finite element method (FEM) models that include the barge and cargo weights, and wave load effects. The FEM models regarded three cargo tanks in the midship section, containing the main longitudinal and transverse structural elements. In addition, the hull girder section modulus and the required deck thickness of the barge were calculated using Lloyd’s Register rules. These rules were applied to estimate the permissible bending stresses at deck and bottom plates under sagging and hogging conditions, which agreed well with those of the FEM models. Based on FEM models, the maximum compressive normal stress and von Mises stress of the hull girder structure were 175.54 MPa and 215.53 MPa, respectively. These stress values do not overcome the yield strength (250 MPa) of the barge material, allowing a safe structural behavior of the barge. The structural modeling of the barge midship section can predict its structural behavior under different sagging and hogging conditions, considering the cargo, weight and wave loads. Full article

South Korea has learned a valuable lesson from the Middle East respiratory syndrome (MERS) coronavirus outbreak in 2015. The 2015 MERS-CoV outbreak in Korea was the largest outbreak outside the Middle Eastern countries and was characterized as a nosocomial infection and a superspreading event. To assess the characteristics of a super spreading event, we specifically analyze the behaviors and epidemiological features of superspreaders. Furthermore, we employ a branching process model to understand a significantly high level of heterogeneity in generating secondary cases. The existing model of the branching process (Lloyd-Smith model) is used to incorporate individual heterogeneity into the model, and the key epidemiological components (the reproduction number and the dispersive parameter) are estimated through the empirical transmission tree of the MERS-CoV data. We also investigate the impact of control intervention strategies on the MERS-CoV dynamics of the Lloyd-Smith model. Our results highlight the roles of superspreaders in a high level of heterogeneity. This indicates that the conditions within hospitals as well as multiple hospital visits were the crucial factors for superspreading events of the 2015 MERS-CoV outbreak. Full article

The coke combustion rate in an iron ore sintering process is one of the most important determining factors of quality and productivity. Biomass carbon material is considered to be a coke substitute with a lower CO₂ emission in the sintering process. The purpose of this study was to investigate the combustion rate of a biomass carbon material and to use a sintering simulation model to calculate its temperature profile. The samples were prepared using alumina powder and woody biomass powder. To simplify the experimental conditions, alumina powder, which cannot be reduced, was prepared as a substitute of iron ore. Combustion experiments were carried out in the open at 1073 K~1523 K. The results show that the combustion rates of the biomass carbon material were higher than that of coke. The results were analyzed using an unreacted core model with one reaction interface. The kinetic analysis found that the k_c of charcoal was higher than that of coke. It is believed that the larger surface area of charcoal may affect its combustion rate. The analysis of the sintering simulation results shows that the high temperature range of charcoal was smaller than that of coke because of charcoal’s low fixed carbon content and density. Full article

Convolutional neural networks (CNN) have achieved excellent results in the field of image recognition that classifies objects in images. A typical CNN consists of a deep architecture that uses a large number of weights and layers to achieve high performance. CNN requires relatively large memory space and computational costs, which not only increase the time to train the model but also limit the real-time application of the trained model. For this reason, various neural network compression methodologies have been studied to efficiently use CNN in small embedded hardware such as mobile and edge devices. In this paper, we propose a kernel density estimation based non-uniform quantization methodology that can perform compression efficiently. The proposed method performs efficient weights quantization using a significantly smaller number of sampled weights than the number of original weights. Four-bit quantization experiments on the classification of the ImageNet dataset with various CNN architectures show that the proposed methodology can perform weights quantization efficiently in terms of computational costs without significant reduction in model performance. Full article

A columnar joint network is a natural fracture pattern with high symmetry, which leads to the anisotropy mechanical property of columnar basalt. For a better understanding the mechanical behavior, a novel modeling method for columnar jointed rock mass through field investigation is proposed in this paper. Natural columnar jointed networks lies between random and centroidal Voronoi tessellations. This heterogeneity of columnar cells in shape and area can be represented using the coefficient of variation, which can be easily estimated. Using the bisection method, a modified Lloyd’s algorithm is proposed to generate a Voronoi diagram with a specified coefficient of variation. Modelling of the columnar jointed rock mass using six parameters is then presented. A case study of columnar basalt at Baihetan Dam is performed to demonstrate the feasibility of this method. The results show that this method is applicable in the modeling of columnar jointed rock mass as well as similar polycrystalline materials. Full article

This paper presents a joint estimation method of source range and depth using a bottom-deployed vertical line array (VLA). The method utilizes the information on the arrival angle of direct (D) path in space domain and the interference characteristic of D and surface-reflected (SR) paths in frequency domain. The former is related to a ray tracing technique to backpropagate the rays and produces an ambiguity surface of source range. The latter utilizes Lloyd’s mirror principle to obtain an ambiguity surface of source depth. The acoustic transmission duct is the well-known reliable acoustic path (RAP). The ambiguity surface of the combined estimation is a dimensionless ad hoc function. Numerical efficiency and experimental verification show that the proposed method is a good candidate for initial coarse estimation of source position. Full article