Search Results (43)

Understanding the interplay between lightning activity and hydrometeor distribution is crucial for advancing knowledge of thunderstorm electrification processes. Using three-dimensional lightning mapping and dual-polarization radar observations, this study investigates the spatiotemporal correlations between low-frequency (LF) lightning sources and hydrometeors during a severe thunderstorm on 11 June 2014, in North Carolina, USA. The results reveal that lightning sources are predominantly observed above 6 km (near the −10 °C isotherm) and stabilize into a dual-peak vertical distribution as the storm progresses into its mature stage, with peaks located at 6–7 km (−10 °C to −15 °C) and 10–11 km (approximately −40 °C). Low-density graupel (LDG) and aggregates (AGs) dominate at lightning locations. Stronger updrafts lead to higher proportions of LDG and high-density graupel (HDG), and lower proportions of AG. LDG exhibits the strongest positive correlation with LF lightning sources, with a peak correlation coefficient of 0.65 at 9 km. During the vigorous development stage, HDG and hail (Ha) also show positive correlations with LF lightning sources, with peak correlation coefficients of 0.52 at 7 km and 0.42 at 8 km, respectively. As the storm reaches its mature phase, the correlation between LDG and lightning sources also displays a dual-peak vertical distribution, with peaks at 7–8 km and 13–14 km. Both the peak correlation coefficient and its corresponding height increase with the strengthening of updrafts, underscoring the critical role of updrafts in microphysical characteristics and driving electrification processes. Full article

Background/Objectives: Delayed gastric emptying (DGE) is a well-known complication of laparoscopic pylorus-preserving gastrectomy (LPPG). Patients who underwent LPPG in the KLASS-04 trial, which was a multicenter prospective randomized control trial comparing LPPG and laparoscopic distal gastrectomy (LDG), showed an unneglectable incidence of long-term DGE compared to patients who underwent LDG. This study aimed to identify the multifactorial risk factors associated with DGE and to analyze the quality of life (QoL) of patients with DGE following LPPG. Methods: DGE was defined as “nearly normal diet residue” at least once in the endoscopic follow-up at 1, 2, and 3 years after the surgery. Clinicopathological features, surgical outcomes, and QoL were compared between the DGE and non-DGE groups. Results: DGE was observed in 21/124 patients (16.3%) who underwent LPPG. Patients without previous abdominal surgery had a higher incidence of DGE in the univariate (32% vs. 4.8%, p = 0.011) and logistic regression analyses (odds ratio: 0.106, 95% confidence interval: 0.014–0.824, p = 0.032). Patients with DGE reported more symptoms of nausea and vomiting (p = 0.004), constipation (p = 0.04), and a dry mouth (p = 0.005). Conclusions: Despite the strict protocol used to avoid well-known risk factors for DGE, such as damage to the hepatic branch of the vagus nerve, infrapyloric artery and vein, and short antral cuff, the LPPG group of the KLASS-04 trial exhibited a considerable incidence of DGE. No clinicopathological or surgical factors, other than the absence of a previous surgical history, were identified as multifactorial risk factors for DGE. However, DGE had a negative impact on the QoL of patients. Full article

As the development of offshore wind energy transforms from coastal to deep-sea regions, designing a cost effective mooring system while ensuring the safety of floating offshore wind turbine (FOWT) remains a critical challenge, especially considering extreme wave environments. This study employs a model coupling computational fluid dynamics (CFD) and finite element method (FEM) to investigate the responses of a parked FOWT platform with its mooring system under rogue wave conditions. Specifically, the mooring dynamics are solved using a local discontinuous Galerkin (LDG) method, which is believed to provide high accuracy. Firstly, rogue wave generation and the coupled CFD-FEM are validated through comparisons with existing experimental and numerical data. Secondly, FOWT platform motions and mooring tensions caused by a rogue wave are obtained through simulations, which are compared with the ones caused by a similar peak-clipped rogue wave. Lastly, analysis of four different mooring design schemes is conducted to evaluate their performance on reducing the mooring tensions. The results indicate that the rogue wave leads to significantly enlarged FOWT platform motions and mooring tensions, while doubling the number of mooring lines with specific line angles provides the most balanced performance considering cost-effectiveness and structural safety under identical rogue wave conditions. Full article

Background/Objectives: An increasing number of apparently healthy individuals are adhering to a gluten-free lifestyle without any underlying medical indications, although the evidence for the health benefits in these individuals remains unclear. Although it has already been shown that a low- or gluten-free diet alters the gut microbiota, few studies have examined the effects of this diet on healthy subjects. Therefore, our aim was to evaluate whether and how a prolonged low-gluten diet impacts gut microbiota composition and function in healthy adults, bearing in mind its intimate link to the host’s health. Methods: Forty healthy volunteers habitually consuming a gluten-containing diet (HGD, high-gluten diet) were included in a randomised control trial consisting of two successive 8-week dietary intervention periods on a low-gluten diet (LGD). After each 8-week period, gut microbiota composition was assessed by 16S rRNA gene sequencing, molecular quantification by qPCR, and a cultural approach, while its metabolic capacity was evaluated through measuring faecal fermentative metabolites by ¹H NMR. Results: A prolonged period of LGD for 16 weeks reduced gut microbiota richness and decreased the relative abundance of bacterial species with previously reported potential health benefits such as Akkermansia muciniphila and Bifidobacterium sp. A decrease in certain plant cell wall polysaccharide-degrading species was also observed. While there was no major modification affecting the main short-chain fatty acid profiles, the concentration of the intermediate metabolite, ethanol, was increased in faecal samples. Conclusions: A 16-week LGD significantly altered both composition and metabolic production of the gut microbiota in healthy individuals, towards a more dysbiotic profile previously linked to adverse effects on the host’s health. Therefore, the evaluation of longer-term LDG would consolidate these results and enable a more in-depth examination of its impact on the host’s physiology, immunity, and metabolism. Full article

Incorporating specific nutritional supplements into animal diets can significantly enhance the quality and various characteristics of animal meat. This study investigated the effects of fermented Zanthoxylum schinifolium leaves (ZSLs) on growth performance, meat quality, and sensory attributes in Sanhuang chickens. Three hundred one-day-old Sanhuang chickens were randomly divided into five groups and reared for 70 days: NC (control, basal diet), NF (6% unfermented ZSLs), LDG (3% fermented ZSLs), MDG (6% fermented ZSLs), and HDG (9% fermented ZSLs). Supplementation with 6% fermented ZSLs significantly increased the leg muscle percentage by 7.4% and decreased the abdominal fat percentage by 22.6%. Meat quality improved notably in MDG, with higher levels of polyunsaturated fatty acids, particularly n-3 polyunsaturated fatty acids. Increasing the proportion of fermented ZSLs enhanced the levels of umami amino acids and sweet amino acids by 36.5% and 11.6%, respectively. Additionally, the enhancement of aroma and flavor of chicken may be correlated with supplementation of fermented ZSLs. These results establish fermented ZSLs as a valuable feed additive for improving production efficiency and meat quality in Sanhuang chickens. Full article

In this paper, a structure-preserving local discontinuous Galerkin (LDG) method is proposed for parabolic stochastic partial differential equations with periodic boundary conditions and multiplicative noise. It is proven that under certain conditions, this numerical method is stable in the $L^2$ sense and can preserve energy conservation. The optimal spatial error estimate in the mean square sense can reach $n+1$ if the degree of the polynomial is n. The correctness of the theoretical results is verified through numerical examples. Full article

Background/Objectives: During laparoscopic pylorus-preserving gastrectomy (LPPG), the preservation of the infra-pyloric artery (IPA) and dissection of the infra-pyloric lymph node (LN) station 6 are essential, underscoring the importance of understanding the anatomical structure of the IPA. This study aimed to investigate anatomical variations in the IPA and surgical outcomes based on data from a multicenter prospective trial. Methods: A post hoc analysis was conducted based on the Korean Laparoendoscopic Gastrointestinal Surgery Study (KLASS)-04 trial, in which patients randomly underwent LPPG or laparoscopic distal gastrectomy (LDG). The IPA variations were categorized into three groups: distal, caudal, and proximal. Clinicopathological characteristics and surgical outcomes were analyzed according to the IPA type. Results: Among the 192 patients, the distribution of IPA types was as follows: 45 (23.44%) distal, 74 (38.54%) caudal, and 73 (38.02%) proximal. There were no significant differences in the clinicopathological characteristics between the IPA types. Of the 119 patients who underwent LPPG, a significant difference in operative time was observed based on the IPA type, with a longer duration observed with the distal type compared to that of the proximal type (distal type vs. proximal type: 202.5 (150–275) vs. 170 (105–265) min, p = 0.0300). No significant differences were observed in other surgical outcomes. Conclusions: The distribution of IPA types was more diverse than that reported in previous studies. There was a statistically significant difference in the operating time based on the IPA type. Identifying IPA variations during LPPG may be beneficial for gastric cancer surgeons. Full article

The current research study presents a comprehensive analysis of the local discontinuous Galerkin (LDG) method for solving multi-order fractional differential equations (FDEs), with an emphasis on circuit modeling applications. We investigated the existence, uniqueness, and numerical stability of LDG-based discretized formulation, leveraging the Liouville–Caputo fractional derivative and upwind numerical fluxes to discretize governing equations while preserving stability. The method was validated through benchmark test cases, including comparisons with analytical solutions and established numerical techniques (e.g., Gegenbauer wavelets and Dickson collocation). The results demonstrate that the LDG method achieves high-accuracy solutions (e.g., with a relatively large time step size) and reduced computational costs, which are attributed to its element-wise formulation. These findings position LDG as a promising tool for complex scientific and engineering applications, particularly in modeling fractional-order systems such as RL, RLC circuits, and other electrical circuit equations. Full article

Graphite, a critical material for furnace walls, is pivotal to the reliability of the carbon-free hydrogen production industry through methane pyrolysis catalyzed by molten metals. This study systematically investigates the corrosion behavior of molten CuSn alloy on three typical commercial graphite materials—low-density graphite (LDG), high-density graphite (HDG), and pyrolytic graphite (PyG)—with a focus on their corrosion resistance and the underlying mechanisms responsible for graphite corrosion over a period of up to 1000 h at 1100 °C. The experimental results show that LDG suffered the most severe corrosion, with a mass loss of up to 60.09% and a hardness decrease from 0.73 GPa to 0.17 GPa, whereas PyG demonstrated the best corrosion resistance, with only a 5.64% mass loss and a hardness drop from 0.52 GPa to 0.35 GPa. SEM and XRD analyses revealed that the porous structures of LDG and HDG suffered significant macroscopic corrosion, caused by the stress from molten metal infiltration and aggregation in the pores, leading to structural collapse. Interestingly, all three types of graphite, including the non-porous PyG, exhibited disordered microstructural degradation as detected by Raman spectroscopy. Molecular dynamics (MD) simulations confirmed that the thermal motion of Cu and Sn atoms primarily drives the microstructural corrosion of graphite, suggesting that the corrosion process involves both micro- and macro-level damage. These findings provide crucial insight into the compatibility of different graphite materials with molten CuSn alloy and valuable guidance for material selection in methane pyrolysis devices. Full article

Geospatial knowledge graphs provide critical technology for integrating geographic information and semantic knowledge, which are very useful for geographic data analysis. As the scale of geospatial knowledge graphs continues to grow, the distributed management of geospatial knowledge graphs is becoming an inevitable requirement. Geospatial knowledge graph partitioning is the core technology for the distributed management of geospatial knowledge graphs. To support geographic data analysis, spatial relationships between entities should be considered in the application of geospatial knowledge graphs. However, existing knowledge graph partitioning methods overlook the spatial relationships between entities, resulting in the low efficiency of spatial queries. To address this issue, this study proposes a geospatial knowledge graph partitioning method based on dual clustering which performs two different clustering methods step by step. First, the density peak clustering method (DPC) is used to cluster geographic nodes. The nodes within each cluster are merged into a super-node. Then, we use an efficient graph clustering method (i.e., Leiden) to identify the community structure of the graph. Nodes belonging to the same community are further merged to reduce the size of the graph. Finally, partitioning operations are performed on the compressed graph based on the idea of the Linear-Weighted Deterministic Greedy Policy (LDG). We construct a geospatial knowledge graph based on YAGO3 to evaluate the performance of the proposed graph partitioning method. The experimental results show that the proposed method outperforms ten comparison methods in terms of graph partitioning quality and spatial query efficiency. Full article

The coronavirus disease 2019 (COVID-19) survivors are frequently observed to present persistent symptoms constituting what has been called “post-acute COVID-19 syndrome” (PACS) or “long COVID-19”. Some clinical risk factors have been identified to be associated with PACS development; however, specific mechanisms responsible for PACS pathology remain unknown. This study investigates clinical, immunological, and metabolomic risk factors associated with post-acute COVID-19 syndrome (PACS) in 51 patients, assessed 7–19 months after acute infection. Among the participants, 62.7% were male and 37.2% were female, with an average age of 47.8 years. At the follow-up, 37.2% met the criteria for PACS, revealing significant differences in immunological and metabolomic profiles at the time of acute infection. Patients with PACS were characterized by elevated levels of mature low-density granulocytes (LDGs), interleukin-8 (IL-8), pyruvate, pseudouridine, and cystine. Baseline multivariate analysis showed increased pyruvate and decreased alpha tocopherol levels. At follow-up, there was a decrease in absolute B lymphocytes and an increase in non-classical monocytes and 3-hydroxyisovaleric acid levels. These findings suggest that specific immunological and metabolomic markers during acute infection can help identify patients at higher risk of developing persistent PACS. Full article

Few therapeutic options are available to treat COVID-19. The KEAP1/NRF2 pathway, the major redox-responsive pathway, has emerged as a potential therapeutic target for COVID-19 as it regulates redox homeostasis and inflammation that are altered during SARS-CoV-2 infection. Here, we characterized the effects of NRF2-agonist Sulfodyne^®, a stabilized natural Sulforaphane, in cellular and animal models of SARS-CoV-2 infection. In pulmonary or colonic epithelial cell lines, Sulfodyne^® elicited a more efficient inhibition of SARS-CoV-2 replication than NRF2-agonists DMF and CDDO. This antiviral activity was not dependent on NRF2 but was associated with the regulation of several metabolic pathways, including the inhibition of ER stress and mTOR signaling, which are activated during SARS-CoV-2 infection. Sulfodyne^® also decreased SARS-CoV-2 mediated inflammatory responses by inhibiting the delayed induction of IFNB1 and type I IFN-stimulated genes in infected epithelial cell lines and by reducing the activation of human by-stander monocytes recruited after SARS-CoV-2 infection. In K18-hACE2 mice infected with SARS-CoV-2, Sulfodyne^® treatment reduced both early lung viral load and disease severity by fine-tuning IFN-beta levels. Altogether, these results provide evidence for multiple mechanisms that underlie the antiviral and anti-inflammatory activities of Sulfodyne^® and pinpoint Sulfodyne^® as a potent therapeutic agent against pathogenic effects of SARS-CoV-2 infection. Full article

Noise removal is a critical stage in the preprocessing of point clouds, exerting a significant impact on subsequent processes such as point cloud classification, segmentation, feature extraction, and 3D reconstruction. The exploration of methods capable of adapting to and effectively handling the noise in point clouds from real-world outdoor scenes remains an open and practically significant issue. Addressing this issue, this study proposes an adaptive kernel approach based on local density and global statistics (AKA-LDGS). This method constructs the overall framework for point cloud denoising using Bayesian estimation theory. It dynamically sets the prior probabilities of real and noise points according to the spatial function relationship, which varies with the distance from the points to the center of the LiDAR. The probability density function (PDF) for real points is constructed using a multivariate Gaussian distribution, while the PDF for noise points is established using a data-driven, non-parametric adaptive kernel density estimation (KDE) approach. Experimental results demonstrate that this method can effectively remove noise from point clouds in real-world outdoor scenes while maintaining the overall structural features of the point cloud. Full article

Organizations like the Clinical and Laboratory Standards Institute (CLSI) or the European Committee of Antimicrobial Susceptibility Testing (EUCAST) provide standardized methodologies for antimicrobial susceptibility testing of a wide range of nonfastidious and fastidious bacteria, but so far not for Mycoplasma spp. of animal origin. Recently, a proposed method for the standardized broth microdilution testing of Mycoplasma hyorhinis using commercial Sensititre microtiter plates was presented. In this study, we evaluated this broth microdilution method with 37 field isolates and tested their susceptibility toward the following antimicrobial agents: doxycycline, enrofloxacin, erythromycin, florfenicol, gentamicin, marbofloxacin, tetracycline, tiamulin, tilmicosin, tulathromycin, and tylosin. The isolates originated from different countries, isolation sites, and years. The broth microdilution method was carried out using a modified Friis broth as the culture and test medium. For macrolides and lincosamides, a bimodal distribution with elevated MIC values could be observed for almost half of the tested field isolates, deducing reduced susceptibility toward these substances. With a recently published protocol, we were able to test a variety of field isolates, and consistent data could be obtained. Using this method, monitoring studies of Mycoplasma hyorhinis isolates can be carried out in a comparable manner, and the observed susceptibility profiles can be screened for possible changes in MIC values in the future. Full article

An infectious disease called tuberculosis (TB) exhibits pneumonia-like symptoms and traits. One of the most important methods for identifying and diagnosing pneumonia and tuberculosis is X-ray imaging. However, early discrimination is difficult for radiologists and doctors because of the similarities between pneumonia and tuberculosis. As a result, patients do not receive the proper care, which in turn does not prevent the disease from spreading. The goal of this study is to extract hybrid features using a variety of techniques in order to achieve promising results in differentiating between pneumonia and tuberculosis. In this study, several approaches for early identification and distinguishing tuberculosis from pneumonia were suggested. The first proposed system for differentiating between pneumonia and tuberculosis uses hybrid techniques, VGG16 + support vector machine (SVM) and ResNet18 + SVM. The second proposed system for distinguishing between pneumonia and tuberculosis uses an artificial neural network (ANN) based on integrating features of VGG16 and ResNet18, before and after reducing the high dimensions using the principal component analysis (PCA) method. The third proposed system for distinguishing between pneumonia and tuberculosis uses ANN based on integrating features of VGG16 and ResNet18 separately with handcrafted features extracted by local binary pattern (LBP), discrete wavelet transform (DWT) and gray level co-occurrence matrix (GLCM) algorithms. All the proposed systems have achieved superior results in the early differentiation between pneumonia and tuberculosis. An ANN based on the features of VGG16 with LBP, DWT and GLCM (LDG) reached an accuracy of 99.6%, sensitivity of 99.17%, specificity of 99.42%, precision of 99.63%, and an AUC of 99.58%. Full article