Search Results (69,633)

This study addresses the potential of machine learning (ML) algorithms in geophysical and geodetic research, particularly for enhancing GNSS time series analysis. We employed XGBoost and Long Short-Term Memory (LSTM) networks to analyze GNSS time series data from the tectonically active Anatolian region. The primary objective was to detect discontinuities associated with seismic events. Using over 13 years of daily data from 15 GNSS stations, our analysis was conducted in two main steps. First, we characterized the signals by identifying linear trends and seasonal variations, achieving $R^2$ values of 0.84 for the XGBoost v.2.1.0 model and 0.81 for the LSTM model. Next, we focused on the residual signals, which are primarily related to tectonic movements. We applied various threshold values and tested different hyperparameters to identify the best-fitting models. We designed a confusion matrix to evaluate and classify the performance of our models. Both XGBoost and LSTM demonstrated robust performance, with XGBoost showing higher true positive rates, indicating its superior ability to detect precise discontinuities. Conversely, LSTM exhibited a lower false positive rate, highlighting its precision in minimizing false alarms. Our findings indicate that the best fitting models for both methods are capable of detecting seismic events (Mw ≥ 4.0) with approximately 85% precision. Full article

Rayleigh lidar equipped on airborne floating platforms has received increasing attention in recent years due to the demand for exploring the middle atmosphere. However, the inevitable attitude fluctuation of the platform affects the measurement accuracy of the photon profile, which greatly affects temperature retrieval. Here, an extensive theoretical analysis model of geometrical transformations between the actual altitude and detection distance under attitude fluctuations was constructed by taking pitch, roll, and observation angles into consideration. Based on this model and measured attitude angles, the influence of platform fluctuation on lidar measurement was analyzed by calculating the deviations between temperature retrieval results and the NRLMSISE-00 model at different observation angles, which demonstrated that the altitude displacement from the variation of pitch angle is a crucial factor in causing temperature retrieval error, especially at large observation angles. Then, an attitude compensation method was designed to eliminate the impact of fluctuations, incorporating the merits of good robustness. Under the observation angle of 45° and average pitch angle of around 4°, the maximum temperature deviation after attitude compensation was reduced from 21.29 K to 0.366 K, a reduction of around two orders of magnitude, indicating that the method can significantly improve the measurement accuracy of Rayleigh lidar. Full article

Thorium is a radionuclide used in various environmental studies such as dating, sediment movement, soil–plant transfer studies, and contamination of waste from the natural fuel cycle. The liquid–liquid extraction method using tri-n-butyl phosphate (TBP) allows for the separation of Th from the accompanying actinides. However, the separation of Th and U present in the same sample is not trivial. This separation is influenced by the starting acid (HCl or HNO₃), the concentration of TBP in an organic solvent, and the concentration of the acid used for re-extracting Th, which is typically HCl. Therefore, it is necessary to study these factors to ensure that the method has sufficient chemical yield and selectivity in complex matrices. This study presents a systematic investigation of the aforementioned parameters, making the necessary variations to select an optimal method for the radiochemical separation of Th. The ideal conditions were obtained using 4 M HCl as the acid prior to extraction, a 1:4 solution of TBP in xylene, and 4 M HCl as the re-extracting agent. The accuracy and precision were studied in four intercomparison exercises conducted in quadruplicate, using the parameters E_numbers, RB(%), and RSD(%) for ²³²Th and ²³⁰Th. The sensitivity of the method was experimentally studied and the limit of detection (LoD) was determined according to ISO 11929:2005. Additionally, the linearity of the method showed that the experimental and theoretical activity concentrations of ²³²Th and ²³⁰Th had slopes of 1 with an intercept close to 0. Full article

Adding occupants to an enclosed space often leads to perceptible changes in the sound field and, therefore, speech intelligibility; however, this issue has not yet been examined in automotive cabins. This study investigated the effect of occupants in an automotive cabin on SI. Binaural room impulse responses (BRIRs) were measured in an automotive cabin with an artificial mouth and dummy head under different speaker–listener position configurations and occupancy modes. Based on the measured BRIRs, the speech transmission index (STI) was determined, and subjective speech–reception thresholds (SRTs) in Mandarin Chinese were assessed. The results indicate that speech intelligibility mostly decreased slightly after adding additional occupants. In most cases, the occupants did not significantly affect speech intelligibility, with STI variations of no more than the just-noticeable difference and SRT variation within 1 dB. When the listener was in the back-right seat, the effect of the occupants on speech intelligibility could not be ignored, with STI variations of up to 0.07 and an SRT variation of 2 dB under different occupancy modes. In addition, the influence of front-row passengers on the speech intelligibility of rear-row listeners was extremely small, and vice versa. Furthermore, altering the distribution of occupants had an effect comparable to changing the number of occupants. Full article

Root system architecture is pivotal for the acquisition of water and nutrients in maize, serving as an essential foundation for achieving high and stable yields. Identification of the genetic components and natural variations determining root traits may facilitate molecular breeding of maize varieties with better root traits. Melatonin plays an important role in plant physiology and development. In this study, nine melatonin biosynthesis genes were re-sequenced in 348 inbred lines, 68 landraces, and 32 teosintes to investigate variations related to maize root traits. The analysis of nucleotide diversity suggested that these genes may have undergone selection, particularly within their promoter regions. Marker–trait association analysis identified 26 variants significantly associated with six root traits. Five variations within the ZmTDC4 promoter were significantly correlated with both total root length (TRL) and lateral root length (LRL). Among these, SNP-1784 explained the most phenotypic variation of root traits, including TRL and LRL, that has undergone selection throughout maize domestication and improvement. Furthermore, knockout of ZmTDC4 in maize resulted in a pronounced reduction in root length, underscoring its critical role in root development. Collectively, these findings elucidate the role of melatonin synthesis genes in root development and identified favorable alleles, thus providing key loci for breeding maize varieties with superior root systems. Full article

Litter is a pervasive social and environmental issue that continues to evade effective and sustainable mitigation strategies. As the nature of waste items can influence methods and rates of littering, an understanding of litter typologies associated with specific sites has the potential to inform targeted anti-littering efforts. In this study, data analysis methods from ecology were applied to litter surveys to evaluate patterns among urban litter items found in two types of streets in England (High Streets and Central Business Districts). The results indicate that sites characterised as a High Street (predominantly leisure activities such as shopping and dining) contained lower densities and less variety yet featured litter items with a higher potential for environmental contamination than sites categorised as Central Business Districts (identified by high numbers of professional workers and transport links). Although litter was significantly different between sites, the litter community structure was not. Our results suggest that litter typologies and associated activities can lead to specific knowledge of key influential items in a site and inform future evidence-based and sustainable mitigation systems. Full article

Synthetic aperture radar (SAR) inter-pulse parameter agility technology involves dynamically adjusting parameters such as the pulse width, chirp rate, carrier frequency, and pulse repetition interval within a certain range; this effectively increases the complexity and uncertainty of radar waveforms, thereby countering active deceptive interference signals from multiple dimensions. With the development of active deceptive interference technology, single-parameter agility can no longer meet the requirements, making multi-parameter joint agility one of the main research directions. However, inter-pulse carrier frequency agility can cause azimuth Doppler chirp rate variation, making azimuth compression difficult and compensation computationally intensive, thus hindering imaging. Additionally, pulse repetition interval (PRI) agility leads to non-uniform azimuth sampling, severely deteriorating image quality. To address these issues, this paper proposes a multi-parameter agile SAR imaging scheme based on traditional frequency domain imaging algorithms. This scheme can handle joint agility of pulse width, chirp rate polarity, carrier frequency, and PRI, with relatively low computational complexity, making it feasible for engineering implementation. By inverting SAR images, the echoes with multi-parameter joint agility are obtained, and active deceptive interference signals are added for processing. The interference-suppressed imaging results verify the effectiveness of the proposed method. Furthermore, simulation results of point targets with multiple parameters under the proposed processing algorithm show that the peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) are improved by 12 dB and 10 dB, respectively, compared to the traditional fixed waveform scheme. Full article

The two-dimensional (2D) hydrogen atom is a fundamental atomic model that is important for various technologies based on 2D materials. Here, the atomic model is revisited to enhance understanding of the hydrogen wavefunctions. Unlike in previous studies, we propose an alternative expression of azimuthal wavefunctions, which are the eigenstates of the square of angular momentum and exhibit rotational symmetry. Remarkably, our expression leads to the rotation and oscillation along the azimuthal direction of the probability densities, which do not appear in the conventional wavefunctions. These behaviors are validated by the numerical results obtained through the 2D finite difference approach. Variation in oscillator strengths due to the rotation of wavefunctions is observed in our proposed 2D hydrogen wavefunctions, whereas those due to the conventional wavefunctions remain constant. More importantly, the proposed wavefunctions’ advantage is illustrating the orbital shapes of the planar hydrogen states, whose orientation is labeled here using Cartesian representation for the first time. This study can be applied to visualize the orbital characteristics of the states in quantum confinement with a radial potential. Full article

Background: The aim of this research is to achieve the early detection of facial characteristics in patients diagnosed with neurodevelopmental deficits and obstructive sleep apnoea–hypopnea syndrome (OSAHS) through the analysis of the VERT index and Ricketts’ cephalometry to minimise the neurocognitive morbidity associated with these disorders. Methods: This clinical study was conducted on 44 patients aged 4 to 15 years. Participants completed an initial questionnaire about sleep disturbances, followed by a polysomnography, a radiographic study, and an oral examination. Results: The maximum variability in the data was obtained in the mandibular plane angle, where we observed that the measurement was higher in patients diagnosed with OSAHS. The relative and normalised indices of facial depth and the mandibular plane showed variations between patients with a clinical picture compatible with OSAHS and the control group without pathology. Conclusions: Our findings indicate that Ricketts’ VERT index by itself is unable to provide evidence of a diagnosis compatible with OSAHS in patients with early neurodevelopmental deficits, but, after analysing the results obtained, we observed that for the cephalometric measurements of the mandibular plane angle and facial depth relative to the patient’s age, there are sufficiently strong variations for creating a solid method of differential diagnosis, thus preventing complications at the neurocognitive level. Full article

Anoikis is a distinct type of programmed cell death and a unique mechanism for tumor progress. However, its exact function in gastric cancer (GC) remains unknown. This study aims to investigate the function of anoikis-related lncRNA (ar-lncRNA) in the prognosis of GC and its immunological infiltration. The ar-lncRNAs were derived from RNA sequencing data and associated clinical information obtained from The Cancer Genome Atlas. Pearson correlation analysis, differential screening, LASSO and Cox regression were utilized to identify the typical ar-lncRNAs with prognostic significance, and the corresponding risk model was constructed, respectively. Comprehensive methods were employed to assess the clinical characteristics of the prediction model, ensuring the accuracy of the prediction results. Further analysis was conducted on the relationship between immune microenvironment and risk features, and sensitivity predictions were made about anticancer medicines. A risk model was built according to seven selected ar-lncRNAs. The model was validated and the calibration plots were highly consistent in validating nomogram predictions. Further analyses revealed the great accuracy of the model and its ability to serve as a stand-alone GC prognostic factor. We subsequently disclosed that high-risk groups display significant enrichment in pathways related to tumors and the immune system. Additionally, in tumor immunoassays, notable variations in immune infiltrates and checkpoints were noted between different risk groups. This study proposes, for the first time, that prognostic signatures of ar-lncRNA can be established in GC. These signatures accurately predict the prognosis of GC and offer potential biomarkers, suggesting new avenues for basic research, prognosis prediction and personalized diagnosis and treatment of GC. Full article

Deep learning models, particularly transformer architectures, have revolutionized various computer vision tasks, including image classification. However, their performance under different types and levels of noise remains a crucial area of investigation. In this study, we explore the noise sensitivity of prominent transformer models trained on the ImageNet dataset. We systematically evaluate 22 transformer variants, ranging from state-of-the-art large-scale models to compact versions tailored for mobile applications, under five common types of image distortions. Our findings reveal diverse sensitivities across different transformer architectures, with notable variations in performance observed under additive Gaussian noise, multiplicative Gaussian noise, Gaussian blur, salt-and-pepper noise, and JPEG compression. Interestingly, we observe a consistent robustness of transformer models to JPEG compression, with top-5 accuracies exhibiting higher resilience to noise compared to top-1 accuracies. Furthermore, our analysis highlights the vulnerability of mobile-oriented transformer variants to various noise types, underscoring the importance of noise robustness considerations in model design and deployment for real-world applications. These insights contribute to a deeper understanding of transformer model behavior under noisy conditions and have implications for improving the robustness and reliability of deep learning systems in practical scenarios. Full article

Rainfall variability and its underlying physical mechanisms are crucial for improving the predictive accuracy of July rainfall patterns in the Sichuan-Shaanxi (SS) region of Southwestern China. This study utilized observational 24 h accumulated rainfall data from China in conjunction with reanalysis products sourced from the European Centre for Medium-Range Weather Forecasts (ECMWF). The purpose of this study was to elucidate the relationship between daily variations in the daily Asian-Pacific Oscillation (APO), atmospheric circulation, and daily rainfall patterns in the SS region, and to evaluate the impact of atmospheric circulation anomalies on these relationships. The results reveal a discernible intensification in the sea–land thermal contrast associated with atmospheric circulation anomalies transitioning from the daily extremely low APO (ELA) to the extremely high APO (EHA) days. These conditions lead to an increased presence of water vapor and widespread anomalies in rainfall that exceed normal levels in the SS region. Concurrently, the increase in stations experiencing extreme rainfall events (EREs) accounts for 21.3% of the overall increase in stations experiencing rainfall. The increase in rainfall amount contributed by EREs (RA-EREs) accounts for 73.5% of the overall increase in the total rainfall amount (TRA) across the SS region. Specifically, heavy rainfall (HR) and downpour rainfall (DR) during EREs accounted for 65.7% (HR) and 95.3% (DR) of the overall increase in the TRA, respectively. Relative to the ELA days, there was a substantial 122.6% increase in the occurrence frequency of EREs and a 23.3% increase in their intensity. The study suggests that the daily APO index emerges as a better indicator of July rainfall events in the SS region, with EREs significantly contributing to the overall increase in rainfall in this region. These findings indicate the importance of improving predictive capabilities for daily variability in the APO index and their correlation with rainfall events in the SS region. The results may inform the development of effective adaptation and mitigation strategies to manage the potential impacts of EREs on agriculture, water resources, sustainable development, and infrastructure in the region. Full article

Mycelium-based composites (MBCs) exhibit varied properties as alternative biodegradable materials that can be used in various industries such as construction, furniture, household goods, and packaging. However, these properties are primarily influenced by the type of substrate used. This study aims to investigate the properties of MBCs produced from Lentinus sajor-caju strain CMU-NK0427 using different ratios of sawdust to corn husk in the development of mycelium composite boards (MCBs) with thicknesses of 8, 16, and 24 mm. The results indicate that variations in the ratios of corn husk to sawdust and thickness affected the mechanical and physical properties of the obtained MCBs. Reducing the corn husk content in the substrate increased the modulus of elasticity, density, and thermal conductivity, while increasing the corn husk content increased the bending strength, shrinkage, water absorption, and volumetric swelling. Additionally, an increase in thickness with the same substrate ratio only indicated an increase in density and shrinkage. MCBs have sound absorption properties ranging from 61 to 94% at a frequency of 1000 Hz. According to the correlation results, a reduction in corn husk content in the substrate has a significant positive effect on the reduction in bending strength, shrinkage, and water absorption in MCBs. However, a decrease in corn husk content shows a strong negative correlation with the increase in the modulus of elasticity, density, and thermal conductivity. The thickness of MCBs with the same substrate ratio only shows a significant negative correlation with the modulus of elasticity and bending strength. Compared to commercial boards, the mechanical (bending strength) and physical (density, thermal conductivity, and sound absorption) properties of MCBs made from a 100% corn husk ratio are most similar to those of softboards and acoustic boards. The results of this study can provide valuable information for the production of MCBs and will serve as a guide to enhance strategies for further improving their properties for commercial manufacturing, as well as fulfilling the long-term goal of eco-friendly recycling of lignocellulosic substrates. Full article

This study delves deeper into the impact of environmental temperature variations on the nervous system in teleost fish. Previous research has demonstrated that exposing adult zebrafish (Danio rerio) to 18 °C and 34 °C for 4 or 21 days induces behavioural changes compared to fish kept at a control temperature of 26 °C, suggesting alterations in the nervous system. Subsequent studies revealed that these temperature conditions also modify brain protein expression, indicating potential neurotoxic effects. The primary aim of this work was to investigate the effects of prolonged exposure (21 days) to 18 °C or 34 °C on the brain lipidomes of adult zebrafish compared to a control temperature. Analysis of the brain lipidome highlighted significant alteration in the relative abundances of specific lipid molecules at 18 °C and 34 °C, confirming distinct effects induced by both tested temperatures. Exposure to 18 °C resulted in an increase in levels of phospholipids, such as phosphatidylethanolamine, alongside a general reduction in levels of sphingolipids, including sphingomyelin. Conversely, exposure to 34 °C produced more pronounced effects, with increases in levels of phosphatidylethanolamine and those of various sphingolipids such as ceramide, gangliosides, and sphingomyelin, alongside a reduction in levels of ether phospholipids, including lysophosphatidylethanolamine ether, phosphatidylethanolamine ether, and phosphatidylglycerol ether, as well as levels of glycolipids like monogalactosyldiacylglycerol. These results, when integrated with existing proteomic and behavioural data, offer new insights into the effects of thermal variations on the nervous system in teleost fish. Specifically, our proteomic and lipidomic findings suggest that elevated temperatures may disrupt mitochondrial function, increase neuronal susceptibility to oxidative stress and cytotoxicity, alter axonal myelination, impair nerve impulse transmission, hinder synapse function and neurotransmitter release, and potentially lead to increased neuronal death. These findings are particularly relevant in the fields of cell biology, neurobiology, and ecotoxicology, especially in the context of global warming. Full article

Rice is a staple crop in sub-Saharan Africa, and it is mostly produced by Asian cultivars of Oryza sativa that were introduced to the continent around the fifteenth or sixteenth century. O. glaberrima, the native African rice, has also been planted due to its valuable traits of insect and drought tolerance. Due to competition and resistance evolution, weedy rice has evolved from O. sativa and O. glaberrima, posing an increasing threat to rice production. This paper provides an overview of current knowledge on the introduction and domestication history of cultivated rice in Africa, as well as the genetic properties of African weedy rice that invades paddy fields. Recent developments in genome sequencing have made it possible to uncover findings about O. glaberrima’s population structure, stress resilience genes, and domestication bottleneck. Future rice genomic research in Africa should prioritize producing more high-quality reference genomes, quantifying the impact of crop–wild hybridization, elucidating weed adaptation mechanisms through resequencing, and establishing a connection between genomic variation and stress tolerance phenotypes to accelerate breeding efforts. Full article