The study aims to suggest sampling structures to avoid sacrificial pseudoreplication in the evaluation of Leadership in Energy and Environmental Design (LEED)-certified projects. The sampling includes two structures that exclude sacrificial pseudorep...
Increasing attention is being paid on leaf area index (LAI) retrieval in mountainous areas. Mountainous areas present extreme topographic variability, and are characterized by more spatial heterogeneity and inaccessibility compared with flat terrain....
Rainfall–triggered clustered landslides pose severe risks to communities and infrastructure in mountainous regions. High–precision susceptibility assessment is essential for early warning and hazard mitigation. The traditional buffering m...
Due to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis. Data-driven machine learning methods can evaluate flood...
The recognition of fine-grained objects is crucial for future remote sensing applications, but this task is faced with the few-shot problem due to limited labeled data. In addition, the existing few-shot learning methods do not consider the unique ch...
Pasture nutritive value is economically important in south-eastern Australian dairy production systems, yet measurement of nutritive characteristics in pasture cultivar evaluation trials is not routinely undertaken, primarily due to cost. An approach...
Although DNA barcoding has become a useful tool for species identification and biodiversity surveys in plant sciences, there remains little consensus concerning appropriate sampling strategies and the treatment of indels. To address these two issues,...
Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUCss,...
Remote sensing (RS)-derived vegetation indices (VIs) with medium and high spatial resolution have emerged as a promising dataset for fine-scale ecosystem modeling and agricultural monitoring at local or global scales. Before they can be used as relia...
The high spectral resolution of hyperspectral images (HSIs) provides rich information but causes data redundancy, which imposes a computational burden on practical applications. Band selection methods can select a subset of HSI without changing the m...
The uncoordinated charging behaviors of electric vehicles (EVs) challenge the stable operation of the grid, e.g., increasing the peak-to-valley ratio of the grid and diminishing power supply reliability. A Monte Carlo sampling method is employed to d...
In addressing the optimal motion planning issue for multi-arm rock drilling robots, this paper introduces a high-precision motion planning method based on Multi-Strategy Sampling RRT* (MSS-RRT*). A dual Jacobi iterative inverse solution method, coupl...
The dynamics of chemical components in sediment porewater are crucial for marine ecological research, resource assessment, and environmental monitoring. A scientific sampling strategy is key to obtaining high-quality porewater. This study aims to exp...
Background: Asparaginase (ASPase) plays an important role in the therapy of acute lymphoblastic leukemia (ALL). Serum ASPase activity (SAA) can be modified and even abolished by host immune responses; therefore, current treatment guidelines recommend...
This study explores two modeling issues that may cause uncertainty in landslide susceptibility assessments when different sampling strategies are employed. The first issue is that extracted attributes within a landslide inventory polygon can vary if...
Accurate analysis of pesticide residue in real samples is essential for food safety and environmental protection. However, a traditional electrochemical sensor based on single-signal output is easily affected by background noise, environmental condit...
By using 14 SSR primer pairs, we here analyzed and compared the amplification results of 534 DNA samples from six red sugar beet germplasm resources under three treatments. These data were used to explore the sampling strategy for the aforementioned...
Designing a sampling strategy for soil property mapping from remote sensing imagery entails making decisions about sampling pattern and number of samples. A consistent number of ancillary data strongly related to the target variable allows applying a...
In combination with Bayesian estimates based on a population pharmacokinetic model, limited sampling strategies (LSS) may reduce the number of samples required for individual pharmacokinetic parameter estimations. Such strategies reduce the burden wh...
This study presents and evaluates three sampling strategies to characterize electricity demand in regions of Colombia with limited metering infrastructure. These areas lack Advanced Metering Infrastructure (AMI), relying instead on traditional monthl...
This paper focuses on large-scale landslide susceptibility modelling in NW Croatia. The objective of this research was to provide new insight into stable and unstable area sampling strategies on a representative inventory of small and shallow landsli...
Environmental DNA (eDNA) metabarcoding has become a powerful, non-invasive method for detecting aquatic organisms. However, optimal sampling strategies for benthic taxa in lentic ecosystems remain unclear. This study evaluated the effectiveness of eD...
Currently, the export regime of a catchment is often characterized by the relationship between compound concentration and discharge in the catchment outlet or, more specifically, by the regression slope in log-concentrations versus log-discharge plot...
Traditional maritime target element resolution, relying on manual experience and uniform sampling, lacks accuracy and efficiency in non-uniform sampling, missing data, and noisy scenarios. While large language models (LLMs) offer a solution, their ge...
In occupational settings where exposure to organic dust occurs (e.g., intensive animal production, waste management, farming and many others) workers can also be exposed to mycotoxins. However, recognizing exposure to mycotoxins in workplace environm...
We investigate the profitability of systematic sector rotation strategies in the Canadian equity market using TSX 60 constituents (2000–2025). Testing 72 distinct strategies across three theoretical frameworks—momentum, mean-reversion, an...
Systematic sampling design is an ordered observation scheme that is popular in data collection because it has the property of uniform coverage and is operationally simple. This scheme is, however, susceptible to extreme observations, which may severe...
We evaluated mycophenolic acid (MPA) limited sampling strategies (LSSs) established using multiple linear regression (MLR) in children with nephrotic syndrome treated with mycophenolate mofetil (MMF). MLR-LSS is an easy-to-determine approach of thera...
A heavy workload is required for sample collection for urban land use classification, and researchers are in urgent need of sampling strategies as a guide to achieve more effective work. In this paper, we make use of an urban land use survey to obtai...
For satellite electronic components characterized by high reliability and long lifespan, achieving improved efficiency in reliability prediction is essential when only a limited amount of data is available. Many studies have collected degradation dat...
Parkinson’s disease (PD) is a neurological disorder that severely affects motor function, especially gait, requiring accurate diagnosis and assessment instruments. This study presents Dense Multiscale Sample Entropy (DM-SamEn) as an innovative...
Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and co...
13 January 2025
Retailers of digital goods such as e-books, online newspapers, and mobile applications often use strategies in multiple aspects. Meanwhile, they need to consider the interrelation between their strategies. Nevertheless, little rigorous research has b...
Core collections can act as a genetic germplasm resource for biologists and breeders. Thirty-seven phenotypic traits from 471 Miscanthus accessions in China were used to design 203 sampling schemes to screen the genetic variations in different sampli...
Therapeutic drug monitoring of ibrutinib is based on the area under the curve of concentration vs. time (AUCIBRU) instead of trough concentration (Cmin,ss) because of a limited accumulation in plasma. Our objective was to identify a limited sampling...
Acceptance sampling plans are divided into attributes and variables, which are used to evaluate the mechanism for determining lot quality. Traditional attribute sampling plans usually choose the Acceptable Quality Level (AQL) for each stage based on...
The accuracy of data-driven landslide susceptibility prediction depends heavily on the quality of non-landslide samples and the selection of machine-learning algorithms. Current methods rely on artificial prior knowledge to obtain negative samples fr...
Microorganisms are diverse and play key roles in lake ecosystems, therefore, a robust estimation of their biodiversity and community structure is crucial for determining their ecological roles in lakes. Conventionally, molecular surveys of microorgan...
Moisture content is the most relevant quality parameter for wood fuels. Effective and fast determination of moisture of incoming feedstock is essential in the management of bioenergy facilities. The availability of fast and reliable moisture meters b...
Landslides are among the most destructive geological hazards, necessitating precise landslide susceptibility mapping (LSM) for effective risk management. This study focuses on the northeastern region of Leshan City and investigates the influence of v...
The accuracy of online parameter identification for permanent magnet synchronous motors (PMSMs) is constrained by discrete model errors, rank deficiency in the steady-state identification matrix, and voltage deviations resulting from inverter nonline...
Accurate and real-time quality prediction to realize the optimal process control at a competitive price is an important issue in Industrial 4.0. This paper shows a successful engineering application of how smart soft sensors can be combined with mach...
While mycotoxins are generally regarded as food contamination issues, there is growing interest in mycotoxins as environmental pollutants. The main sources of trichothecene and zearalenone mycotoxins in the environment are mainly attributed to Fusari...
Hydraulic tomography (HT) based on the successive linear estimator (SLE) offers the high-resolution characterization of aquifer heterogeneity but conventionally requires prolonged pumping to achieve steady-state conditions, limiting its applicability...
In recent years, the rapid development of artificial intelligence has promoted the widespread application of convolutional neural networks (CNNs) in neuroimaging analysis. Although three-dimensional (3D) CNNs can utilize the spatial information in 3D...
In landslide susceptibility modeling, research has predominantly focused on predicting landslides by identifying predisposing factors, often using inventories primarily based on the highest points of landslide crowns. However, a significant challenge...
Contrastive learning techniques make it possible to pretrain a general model in a self-supervised paradigm using a large number of unlabeled remote sensing images. The core idea is to pull positive samples defined by data augmentation techniques clos...
Background: Meltdose tacrolimus (Envarsus®) has been marketed as a formulation achieving a more consistent tacrolimus exposure. Due to the narrow therapeutic window of tacrolimus, dose individualization is essential. Relaxation of the upper age l...
This paper proposes an improved RRT*-Connect algorithm (IRRT*-Connect) for robotic arm path planning in narrow environments with multiple obstacles. A heuristic sampling strategy is adopted with the integration of the ellipsoidal subset sampling and...
A new non-uniform photonic sampling (NPS) strategy and its special signal reconstruction algorithm are proposed to achieve digital acquisition of broadband periodic signals at a low sampling rate. Compared with the existing schemes, the NPS strategy...
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