Search Results (154)

Gridded precipitation datasets (GPDs) have complemented gauge-based measurements in global hydrology by providing spatiotemporally continuous rainfall estimates for streamflow prediction. However, these datasets suffer from uncertainties in space and time, particularly in complex terrains like the Himalayas. Merging multi-GPDs offers a potential solution to reduce such uncertainties, but the actual contribution of the merged product to hydrological modeling remains underexplored in data-scarce and topographically complex regions. Here, we applied a gauge-independent merging technique called Signal-to-Noise Ratio optimization (SNR-opt) to merge three precipitation products: ERA5, SM2RAIN, and IMERG-late. The resulting Merged Gridded Precipitation Dataset (MGPD) was evaluated using the hydrological model (HYMOD) across three major river basins in the Central Himalayas (Koshi, Narayani, and Karnali). The results show that MGPD significantly outperforms the individual GPDs in streamflow simulation. This is evidenced by higher Nash–Sutcliffe Efficiency (NSE) values, 0.87 (Narayani) and 0.86 (Karnali), compared to ERA5 (0.83, 0.82), SM2RAIN (0.83, 0.85), and IMERG-Late (0.82, 0.78). In Koshi, the merged product (NSE = 0.80) showed slightly lower performance than SM2RAIN (NSE = 0.82) and ERA5 (NSE = 0.81), likely due to the poor performance of IMERG-Late (NSE = 0.69) in this basin. These findings underscore the value of merging precipitation datasets to enhance the accuracy and reliability of hydrological modeling, especially in ungauged or data-scarce mountainous regions, offering important implications for water resource management and forecasting. Full article

A semi-parametric mixture model, combining kernel density estimation (KDE) and the generalized Pareto distribution (GPD), is applied to analyze the statistical characteristics of earthquake magnitudes. Data below a threshold are fitted using KDE, while data above the threshold are modeled using the GPD. Both the kernel bandwidth and the threshold are directly estimable as parameters. An estimation method based on the empirical distribution function (EDF) and maximum likelihood estimation (MLE) is used to estimate the parameters of the mixture model. The application of this model to earthquake magnitude analysis offers insights for seismic hazard assessment. Full article

Zhejiang Province in China is one of the most typhoon-prone regions globally, making typhoon and storm surge hazard analysis critically important for disaster mitigation. This study integrates the Tropical Cyclone Risk Model (TCRM) with a machine learning-based storm surge forecasting model to analyze typhoon hazards and storm surge risks at four representative coastal sites in Zhejiang Province: Haimen, Ruian, Wenzhou, and Zhapu. Firstly, the input database of the TCRM has been updated and subsequently used to generate a 1000-year synthetic typhoon event catalog for the Northwest Pacific region. Secondly, four machine learning models—Long Short-Term Memory (LSTM), Back Propagation (BP), Support Vector Regression (SVR), and Random Forest (RF)—were developed to forecast storm surge component at the four sites, with sensitivity analysis conducted on the input parameters. Among the four models, RF consistently outperformed the others across all four sites. Thirdly, by integrating the storm surge forecasting model with the Yan Meng (YM) typhoon wind field model, extreme wind speed sequences and extreme surge component sequences were derived for the four coastal sites. Finally, four extreme value distribution models—empirical distribution, Weibull, Gumbel, and Generalized Pareto Distribution (GPD)—were applied to fit the extreme wind and surge sequences. Goodness-of-fit tests indicated that the GPD best captured extreme wind speeds at all four sites and extreme surge levels at Haimen, Ruian, and Wenzhou. Using the optimal distributions, return periods (10-, 50-, 100-, and 200-year) for extreme wind speeds and surge components were calculated, providing actionable references for disaster risk management authorities. Full article

Guanidinoacetic acid (GAA) has been used in ruminant feeding, but it is still unclear whether the exogenous addition of methyl donors, such as methionine (Met), can enhance the effects of GAA. This study investigated the effects of dietary GAA alone or combined with Met on beef cattle growth performance and explored the underlying mechanisms via blood analysis, liver metabolomics, and transcriptomics. Forty-five Simmental bulls (453.43 ± 29.05 kg) were assigned to three groups for 140 days: CON (control), GAA (0.1% GAA), and GAM (0.1% GAA + 0.1% Met), where each group consisted of 15 bulls. Compared with the CON group, the average daily gain (ADG) and feed conversion efficiency (FCE) of the two feed additive groups were significantly increased, and the digestibility of neutral detergent fiber (NDF) was improved (p < 0.05). Among the three treatment groups, the GAM group showed a higher rumen total volatile fatty acids (TVFAs) content and digestibility of dry matter (DM) and crude protein (CP) in the beef cattle. The serum indices showed that the contents of indicators related to protein metabolism, lipid metabolism, and creatine metabolism showed different increases in the additive groups (p < 0.05). It is worth noting that the antioxidant indexes in the serum and liver tissues of beef cattle in the two additive groups were significantly improved (p < 0.05). The liver metabolites related to protein metabolism (e.g., L-asparagine, L-glutamic acid) and lipid metabolism (e.g., PC (17:0/0:0)) were elevated in two additive groups, where Met further enhanced the amino acid metabolism in GAM. In the two additive groups, transcriptomic profiling identified significant changes in the expression of genes associated with protein metabolism (including PIK3CD, AKT3, EIF4E, HDC, and SDS) and lipid metabolism (such as CD36, SCD5, ABCA1, APOC2, GPD2, and LPCAT2) in the hepatic tissues of cattle (p < 0.05). Overall, the GAA and Met supplementation enhanced the growth performance by improving the nutrient digestibility, serum protein and creatine metabolisms, antioxidant capacity, and hepatic energy and protein and lipid metabolisms. The inclusion of Met in the diet was shown to enhance the nutrient digestibility and promote more efficient amino acid metabolism within the liver of the beef cattle. Full article

The maintenance of gas turbines relies a lot on gas path diagnostics (GPD), which includes two approaches. The first approach employs a physics-based model (thermodynamic model) to convert measurement shifts (deviations) induced by deterioration into fault parameters, which drastically simplify diagnostics. The second approach relies on data-driven models, makes diagnosis in the space of measurement deviations, and involves pattern recognition techniques. Although a thermodynamic model is an essential element of GPD, it has limitations. This model is a complex software critical to computer resources, and the computation sometimes does not converge. Therefore, it is difficult to use the model in online applications. Since the 1990s, we have developed many thermodynamic models for different engines. Since the 2000s, simplified data-driven models were investigated. This paper proposes to substitute a thermodynamic model for novel simplified data-driven models that have the same functionality, i.e., take into consideration the influence of both operating conditions and engine faults. The proposed models are formed and compared with the underlying thermodynamic model. To obtain a solid conclusion about these models, they are verified in twelve test cases formed by three test-case engines, two model types, and two approximation functions. Although the accuracy of the simplified models varies from 1.15% to 0.0082%, it was found acceptable even for the worst case. Thus, these simple-but-accurate models with the functionality of a physics-based model represent a good replacement for the latter. It is expected that the models will stimulate the further development of advanced diagnostic systems. Full article

The GPD1L gene encodes a small cytoplasmic protein that is involved in the regulation of sodium currents. Alterations in this gene have been associated with Brugada syndrome. This rare arrhythmogenic syndrome is characterized by a typical electrocardiographic pattern, incomplete penetrance, variable expressivity, and risk of sudden cardiac death. To date, few families with a clinical diagnosis of Brugada syndrome caused by a rare alteration in the GPD1L gene have been reported worldwide. The increase in data focused on genetic variants allows us to improve the interpretation of their role in Brugada syndrome. In our study, we have compiled the GPD1L variants reported so far in patients with a definitive clinical diagnosis or suspected Brugada syndrome. We performed an exhaustive update and interpretation of each variant following the guidelines of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Our results showed that none of the variants described to date can be classified as truly harmful in Brugada syndrome. Despite this fact, more clinical and genetic data are needed to definitively rule out the GPD1L gene as a cause of Brugada syndrome. In summary, to date, there is insufficient evidence to conclude a definitive association between GPD1L and Brugada syndrome. Full article

Hypoxic stress causes cell damage and serious diseases in organisms, especially in aquatic animals. It is important to elucidate the changes in metabolic function caused by hypoxia and the mechanisms underlying these changes. This study focuses on the low oxygen tolerance feature of a new blunt snout bream strain (GBSBF1). Our data show that GBSBF1 has a different lipid and carbohydrate metabolism pattern than wild-type bream, with altering glycolysis and lipid synthesis. In GBSBF1, the expression levels of phd2 and vhl genes are significantly decreased, while the activation of HIF-3α protein is observed to have risen significantly. The results indicate that enhanced HIF-3α can positively regulate gpd1ab and gpam through PPAR-γ, which increases glucose metabolism and reduces lipolysis of GBSBF1. This research is beneficial for creating new aquaculture strains with low oxygen tolerance traits. Full article

The extraction of the Generalized Parton Distributions of the nucleons from phenomenological analyses of experimental data presents a challenging problem which is being actively studied in the literature. Due to theoretical limitations of some of the well-known channels, currently many new processes are being analyzed in the literature as potential novel probes. In this proceeding we propose to use the exclusive photoproduction of ${\eta }_c\gamma$ pairs as a new channel for study of the GPDs. Our analysis shows that this process is primarily sensitive to the unpolarized gluon GPDs $H_g$ in the Efremov-Radyushkin-Brodsky-Lepage (ERBL) kinematics. The numerical estimates of the cross-section and the expected counting rates for middle-energy photoproduction experiments show that expected counting rates are sufficiently large for a dedicated experimental study at the future Electron-Ion Collider (EIC) or in ultraperipheral collisions at the LHC. The total (integrated) photoproduction cross-section ${\sigma }_{\mathrm{tot}}^{\gamma p\to \gamma {\eta }_{c}p}$ in this kinematics scales with energy W as ${\sigma }_{\mathrm{tot}}^{\gamma p\to \gamma {\eta }_{c}p}\left(W,M_{\gamma {\eta }_c}\ge 3.5\mathrm{GeV}\right)\approx 0.48\mathrm{pb}{\left({\displaystyle \frac{W}{100\mathrm{GeV}}}\right)}^{0.75},$ and yields a few thousands of events per $100{\mathrm{fb}}^{-1}$ of the integrated luminosity. Full article

This paper presents an efficient grasp pose estimation algorithm for robotic arm systems with a two-finger parallel gripper and a consumer-grade depth camera. Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. Initial estimation fits an ellipsoid to determine principal axes, followed by nonlinear optimization for a six-degree-of-freedom grasp pose. Validation through simulations and experiments showed a target grasp success rate (TGSR) of over 83% under low noise, with only a 4.9% drop under high noise—representing a 68.0% and a 42.4% improvement over GPD and PointNetGPD, respectively. In real-world tests, success rates ranged from 95 to 100%, and the computational efficiency was improved by 56.3% compared to deep learning methods, proving its practicality for real-time applications. These results demonstrate stable and reliable grasping performance, even in noisy environments and with low-cost sensors. Full article

Understanding the genetic characteristics of indigenous goat breeds is vital for their conservation and breeding. Haimen goats, native to China’s Yangtze River Delta, possess distinctive traits such as white hair, moderate growth rate, high-quality meat, and small body size. However, knowledge regarding the genetic structure and germplasm characteristics of Haimen goats remains limited. In this study, we performed 20× whole-genome resequencing of 90 goats (60 Haimen goats and 30 Boer goats) to identify single-nucleotide polymorphisms (SNPs) and insertions/deletions (Indels) associated with growth traits. Here, we analyzed population genetic structure and genome-wide selection signatures between the Haimen and Boer goats based on whole-genome resequencing data. The principal component analysis (PCA) and neighbor-joining (N-J) tree results demonstrated significant genetic differentiation between the Haimen and Boer goats. The nucleotide diversity (Pi) and linkage disequilibrium (LD) decay results indicated higher genomic diversity in the Haimen goat population. Furthermore, selective sweep analysis identified candidate genes associated with growth traits. These genes exhibited strong selection signatures and were related to body size (DONSON, BMPR1B, and EPHA5), muscle development (GART, VGLL3, MYH15), and fat metabolism (ADAMTS5, LRP6, XDH, CPT1A, and GPD1). We also identified growth-related candidate genes (NCOR1, DPP6, NOTCH2, and FGGY) specific to Haimen goats. Among these genes, pancreatic lipase-related protein 1 (PNLIPRP1) emerged as the primary candidate gene influencing growth phenotypes. Further analysis revealed that a 26 bp Indel in PNLIPRP1 increased its gene expression, suggesting that this Indel could serve as a molecular marker for early marker-assisted selection, potentially enhancing early growth in goats. These findings provide valuable molecular markers and candidate genes for improving growth traits in Haimen goat breeding. Full article

Melanoma is among the most abundant malignancies in the US and worldwide. Ligstroside aglycone (LA) is a rare extra-virgin olive oil-derived monophenolic secoiridoid with diverse bioactivities. LA dose–response screening at the NCI 60 cancer cells panel identified the high sensitivity of the Malme-3M cell line, which harbors a BRAF V600E mutation. Daily oral 10 mg/kg LA exhibited potent in vivo antitumor effects against Malme-3M cells xenograft in a nude mouse model by targeting the BRAF signaling pathway. A human Clariom S microarray analysis of the collected Malme- 3M tumors identified 571 dysregulated genes, with the downregulation of pathways critical for melanoma cells growth and survival. A Western blot analysis of the collected animal tumors further validated the downregulation of the mutated BRAF–MAPK axis, as well as the GPD1 and ELOVL6 expression levels. A histopathological analysis of Malme-3M tumor sections showed extensive focal tumor necrosis in treated mice. An immunofluorescence study of tumor sections showed notable reductions in proliferation marker ki67 and the vasculogenesis marker CD31 in treated tumors. These findings promote LA as a potential nutraceutical lead for the control of the BRAF V600E mutant melanoma. Full article

Current industrial robotic manipulators have made their lack of flexibility evident. The systems must know beforehand the piece and its position. To address this issue, contemporary approaches typically employ learning-based techniques, which rely on extensive amounts of data. To obtain vast data, an often sought tool is an extensive grasp dataset. This work introduces our Physics-Based Self-Supervised Grasp Pose Detection (PBSS-GPD) pipeline for model-based grasping point detection, which is useful for generating grasp pose datasets. Given a gripper-object pair, it samples grasping pose candidates using a modified version of GPD (implementing inner-grasps, CAD support…) and quantifies their quality using the MuJoCo physics engine and a grasp quality metric that takes into account the pose of the object over time. The system is optimized to run on CPU in headless-parallelized mode, with the option of running in a graphical interface or headless and storing videos of the process. The system has been validated obtaining grasping poses for a subset of Egad! objects using the Franka Panda two-finger gripper, compared with state-of-the-art grasp generation pipelines and tested in a real scenario. While our system achieves similar accuracy compared to a contemporary approach, 84% on the real-world validation, it has proven to be effective at generating grasps with good centering 18 times faster than the compared system. Full article

Water management has evolved significantly, but sustainability remains a critical challenge. Ancient Roman aqueducts, despite their engineering marvel, operated with constant flow, leading to substantial water waste. Later, rooftop reservoir systems continued this inefficiency, as excess water would overflow. Only recently have demand-driven networks shown potential for reducing waste, though substantial water leaks continue to undermine these efforts. Achieving true sustainability in water distribution requires minimizing leaks through the use of models that adopt accurate water demand scenarios and identifying an optimal peak factor (PF). In fact, water distribution networks (WDNs) are commonly designed, analyzed, and calibrated using deterministic demand scenarios based on average annual consumption and scaled by a chosen PF. However, for efficient design and management, it is essential to associate a probabilistic value with the consumption data used in the analyses. This study introduces a novel methodology for estimating PFs with a specific return period at the District Meter Area (DMA) scale, utilizing extreme value statistical analysis. The generalized Pareto distribution (GPD) models were applied to provide more reliable PF estimates. The proposed methodology was validated using hourly residential consumption data from a DMA located in Southern Italy, demonstrating its effectiveness in improving the accuracy of WDN design. Full article

There is compelling evidence that the absorption of low-energy UV radiation directly by DNA in solution generates guanine radicals with quantum yields that are strongly dependent on the secondary structure. Key players in this unexpected phenomenon are the photo-induced charge transfer (CT) states, in which an electric charge has been transferred from one nucleobase to another. The present work examines the factors affecting the population of these states during electronic relaxation. It focuses on two dinucleotides with opposite orientation: 5′-dApdG-3′ (AG) and 5′-dGpdA-3′ (GA). Quantum chemistry calculations determine their ground state geometry and the associated Franck–Condon states, map their relaxation pathways leading to excited state minima, and compute their absorption spectra. It has been shown that the most stable conformer is anti-syn for AG and anti-anti for GA. The ground state geometry governs both the excited states populated upon UV photon absorption and the type of excited state minima reached during their relaxation. Their fingerprints are detected in the transient absorption spectra recorded with excitation at 266 nm and a time resolution of 30 fs. Our measurements reveal that in the large majority of dinucleotides, chromophore coupling is already operative in the ground state and that the charge transfer process occurs within ~120 fs. The competition among various relaxation pathways affects the quantum yields of the CT state formation in each dinucleotide, which are estimated to be 0.18 and 0.32 for AG and GA, respectively. Full article

Energy metabolism is a fundamental aspect of the aggressiveness and invasiveness of breast cancer (BC), the neoplasm that most affects women worldwide. Nonetheless, the impact of genetic somatic mutations on glycolysis and oxidative phosphorylation (OXPHOS) genes in BC remains unclear. To fill these gaps, the mutational profiles of 205 screened genes related to glycolysis and OXPHOS in 968 individuals with BC from The Cancer Genome Atlas (TCGA) project were performed. We carried out analyses to characterize the mutational profile of BC, assess the clonality of tumors, identify somatic mutation co-occurrence, and predict the pathogenicity of these alterations. In total, 408 mutations in 132 genes related to the glycolysis and OXPHOS pathways were detected. The PGK1, PC, PCK1, HK1, DONSON, GPD1, NDUFS1, and FOXRED1 genes are also associated with the tumorigenesis process in other types of cancer, as are the genes BRCA1, BRCA2, and HMCN1, which had been previously described as oncogenes in BC, with whom the target genes of this work were associated. Seven mutations were identified and highlighted due to the high pathogenicity, which are present in more than one of our results and are documented in the literature as being correlated with other diseases. These mutations are rs267606829 (FOXRED1), COSV53860306 (HK1), rs201634181 (NDUFS1), rs774052186 (DONSON), rs119103242 (PC), rs1436643226 (PC), and rs104894677 (ETFB). They could be further investigated as potential biomarkers for diagnosis, prognosis, and treatment of BC patients. Full article