Search Results (504)

This study aims to examine the impact of compressor station availability on the techno-economic aspects of natural gas pipeline transportation, using the proposed Trans-Saharan Gas Pipeline (TSGP) project as a case study. A scenario-based technical and economic analysis was conducted to highlight the economic sensitivities of the systems to availability. The economic assessment of the project was performed using a discounted cash flow method, considering lifecycle costs. The techno-economic model was developed using MATLAB R2020b, accounting for variations in ambient temperatures at the compressor station under different flow conditions. Findings indicate an 8.41% increase in project lifecycle cost in one scenario compared to the baseline, assuming a 15% discount rate. However, the baseline case with a 100% compressor station availability assumption appears unrealistic, as shown by its lifecycle cost and net present value estimates. This is because constant operating conditions throughout the project lifecycle are impossible. Additionally, when station availability increases by 7.87% and the cost of standby units rises by 10.24%, avoided income loss due to station unavailability increases by 14.06%. This reveals a trade-off between the extra capital expenditure on standby units and the savings from avoiding income loss. Furthermore, the impact of 2% and 4% escalation rates of fuel and maintenance costs on lifecycle costs results in a rise of 2.70% and 6.15%, respectively, in one scenario compared to the 0% escalation rate. The results demonstrate the significant influence of compressor station availability analysis on pipeline projects, particularly in reducing engine downtime costs and enhancing project revenue. Therefore, the methods presented here help in understanding the importance of compressor station availability in pipeline techno-economics, leading to more effective resource and financial management. Full article

The fatty acid (FA) profile of beef is a key indicator of nutritional quality. This study assessed the ability of Near Infrared Spectroscopy (NIRS) to predict the FA profile in beef samples from southern Chile. A total of 81 FAs were analyzed, and 38% of the calibration models achieved RPD ≥ 2.5 (Ratio of Performance to Deviation). Strong predictive performance was observed for major FAs, particularly SFA and MUFA, with R²p > 0.90 (Coefficient of Determination) for palmitic (16:0). Although PUFA and some CLA isomers showed lower predictive accuracy—likely due to low concentrations and spectral overlap—minor FA such as 9c,11t-18:2 (CLA, rumenic acid) was accurately predicted. External validation confirmed that 77% of FAs showed no significant differences from gas chromatography, highlighting the robustness of NIRS for most compounds analyzed here. NIRS effectively captured FAs related to grass-based diets, such as trans-vaccenic acid and specific CLA isomers. NIRS works as a practical, rapid, and non-destructive tool for FA profiling, with potential uses in nutritional labeling and quality control; however, its application depends on the prior development of robust calibration models, which must be tailored to the specific matrix and analytical objectives. Full article

Objectives: The primary objective was to investigate and compare the effects of three paired-pulse repetitive trans-spinal magnetic stimulation (PP-rTSMS) protocols on balance control and corticospinal network function. Methods: PP-rTSMS (800 pulses, frequency 100 Hz, intensity 70% of the resting motor threshold) was applied over the eighth thoracic vertebra (Th8) in twenty-seven young healthy individuals. Each proband received three verum sessions (using a verum coil with handle oriented (i) cranially, (ii) caudally, and (iii) laterally) and (iv) one sham session (using a sham coil) in a randomised order. Balance ability (Y Balance Test) and corticospinal network functions (motor evoked potentials (MEPs), cortical silent periods (SCPs)) were tested immediately (i) prior to and (ii) after each interventional session. Results: Each verum session induced a significant improvement in balance ability (cranially (F_1,26 = 8.009; p = 0.009; η² = 0.236), caudally (F_1,26 = 4.846; p = 0.037; η² = 0.157), and laterally (F_1,26 = 23,804; p ≤ 0.001; η² = 0.478) oriented grip) as compared to the sham session. In addition, the laterally oriented coil grip was associated with significantly greater balance benefits than both the cranial (F_1,26 = 10.173; p = 0.004; η² = 0.281) and caudal (F_1,26 = 14.058; p ≤ 0.001; η² = 0.351) grip orientations. No significant intervention-induced effects were detected on corticospinal network functions. Conclusions: Our data show that PP-rTSMS effectively supports balance control and that coil orientation significantly influences these effects. Further studies should test variations of this promising approach on healthy and disabled cohorts. Full article

Objectives: In this research study, we introduce a novel approach to develop an innovative nanocarrier system comprising gold nanoparticles (GNPs) loaded with doxorubicin (D) in combination with natural molecules, such as trans-resveratrol (R), piperine (P), and icariin (Ic), against human cervical cancer. The final objective is to improve the anticancer efficacy of doxorubicin on HeLa and CaSki cell lines. Methods: Resveratrol was also used for the synthesis of GNP_R1 nanoparticles. Multi-functional GNPs loaded with D, R, P, and Ic (e.g., GNP_R1@D/R/P/Ic) were successfully prepared and fully characterized by SPR, TEM, HR-TEM, XRD, AFM, DLS, and zeta potential. They were investigated for in vitro stability in various biological media. The cytotoxicity activity was tested on HeLa and CaSki cell lines, using the MTT assay, for their applications as anticancer agents. Results: Our results demonstrate that the novel multi-functional GNPs (such as GNP_R1@D/R and GNP_R1@D/R/P/Ic) can effectively target the cervical cancer cells, improving the bioavailability of therapeutic agents and enhancing their cytotoxicity against cervical cancer cells. In vitro assessments demonstrated that the multi-functional GNPs exhibited improved stability and potential anticancer efficacy on human cervical cancer cells. Conclusions: The described strategy connects the benefits of biomolecules with functional nanoparticles toward the development of various GNP_R1@D/R/P/Ic nanocarriers for their applications as anticancer agents against human cervical cancer. This study provides compelling evidence that the innovative nanoparticles can enhance the therapeutic efficacy of doxorubicin against cervical cancer and offer a more advantageous alternative compared to doxorubicin monotherapy. Full article

Small reservoirs have important functions, such as water resource guarantee, flood control and drought resistance, biological habitat and maintaining regional economic development. In order to better clarify the impact of agricultural activities on the nutritional status of water bodies in small reservoirs, zooplankton were quantitatively collected from four small reservoirs in the Jiuxianshan agricultural area of Qufu, Shandong Province, in March and October 2023, respectively. The physical and chemical parameters in sampling points were determined simultaneously. Meanwhile, water samples were collected for nutrient salt analysis, and the eutrophication of water bodies in four reservoirs was evaluated using the comprehensive nutrient status index method. The research found that the species richness of zooplankton after farming (100 species) was significantly higher than that before farming (81 species) (p < 0.05). On the contrary, the dominant species of zooplankton after farming (7 species) were significantly fewer than those before farming (11 species). The estimation results of the standing stock of zooplankton indicated that the abundance and biomass of zooplankton after farming (92.72 ind./L, 0.13 mg/L) were significantly higher than those before farming (32.51 ind./L, 0.40 mg/L) (p < 0.05). Community similarity analysis based on zooplankton abundance (ANOSIM) indicated that there were significant differences in zooplankton communities before and after farming (R = 0.329, p = 0.001). The results of multi-dimensional non-metric sorting (NMDS) showed that the communities of zooplankton could be clearly divided into two: pre-farming communities and after farming communities. The Monte Carlo test results are as follows (p < 0.05). Transparency (Trans), pH, permanganate index (COD_Mn), electrical conductivity (Cond) and chlorophyll a (Chl-a) had significant effects on the community structure of zooplankton before farming. Total nitrogen (TN), total phosphorus (TP) and electrical conductivity (Cond) had significant effects on the community structure of zooplankton after farming. The co-linearity network analysis based on zooplankton abundance showed that the zooplankton community before farming was more stable than that after farming. The water evaluation results based on the comprehensive nutritional status index method indicated that the water conditions of the reservoirs before farming were mostly in a mild eutrophic state, while the water conditions of the reservoirs after farming were all in a moderate eutrophic state. The results show that the nutritional status of small reservoirs in agricultural areas is significantly affected by agricultural activities. The zooplankton communities in small reservoirs underwent significant changes driven by alterations in the reservoir water environment and nutritional status. Based on the main results of this study, we suggested that the use of fertilizers and pesticides should be appropriately reduced in future agricultural activities. In order to better protect the water quality and aquatic ecology of the water reservoirs in the agricultural area. Full article

Workaholism and perfectionism have increasingly been identified as significant obstacles to effective lifelong learning and skills development, ultimately undermining long-term career adaptability and organizational resilience. This study explores the predictive role of perfectionism and professional workaholism, with a particular focus on their implications for continuous education and occupational sustainability—defined as employees’ ability to remain adaptable and resilient over time. Using a cross-sectional quantitative design, data were collected from 105 participants (54 IT professionals and 51 nurses) who completed standardized measures of perfectionism and workaholism and reported their cognitive–emotional readiness for further training. Four regression models were employed to assess the impact of the three perfectionism dimensions and profession on overall workaholism and its subcomponents (excessive work, compulsive work, supplementary work). Socially prescribed perfectionism emerged as a strong predictor, accounting for over one-third of the variance in workaholism (β = 0.37; R²_adj = 0.368; p < 0.001), while self-oriented perfectionism significantly predicted excessive work (β = 0.25; p = 0.015). Professional domain had no significant effect, indicating the trans-professional nature of these psychological barriers. Additionally, workaholism was associated with reduced cognitive–emotional availability for ongoing training, highlighting its detrimental effects on lifelong learning. Limitations include the cross-sectional design and reliance on convenience sampling. From a practical perspective, the findings support interventions targeting maladaptive perfectionism, aiming to enhance engagement in continuous professional education and foster sustainable work environments, in line with the United Nations Sustainable Development Goals (SDG 4 and SDG 8). Full article

This study investigates the dynamic response mechanisms of discharge capacity in the Han River Estuary to hydrological process changes at the Yangtze–Han River confluence. By constructing a one-dimensional hydrodynamic model for the 265 km Xinglong–Hankou reach, we quantitatively decouple the synergistic effects of riverbed scouring (mean annual incision rate: 0.12 m) and Three Gorges Dam (TGD) operation through four orthogonal scenarios. Key findings reveal: (1) Riverbed incision dominates discharge variation (annual mean contribution >84%), enhancing flood conveyance efficiency with a peak flow increase of 21.3 m³/s during July–September; (2) TGD regulation exhibits spatiotemporal intermittency, contributing 25–36% during impoundment periods (September–October) by reducing Yangtze backwater effects; (3) Nonlinear interactions between drivers reconfigure flow paths—antagonism occurs at low confluence ratios (R < 0.15, e.g., Cd increases to 45 under TGD but decreases to 8 under incision), while synergy at high ratios (R > 0.25) reduces Hanchuan Station flow by 13.84 m³/s; (4) The 180–265 km confluence-proximal zone is identified as a sensitive area, where coupled drivers amplify water surface gradients to −1.41 × 10⁻³ m/km (2.3× upstream) and velocity increments to 0.0027 m/s. The proposed “Natural/Anthropogenic Dual-Stressor Framework” elucidates estuary discharge mechanisms under intensive human interference, providing critical insights for flood control and trans-basin water resource management in tide-free estuaries globally. Full article

Any failure in frontonasal development can lead to malformations at the middle facial region, such as frontonasal dysplasia, midfacial clefts, and hyper/hypotelorism. Various environmental factors influence morphogenesis through epigenetic regulations, including the action of noncoding microRNAs (miRNAs). However, it remains unclear how miRNAs are involved in the frontonasal development. In our analysis of publicly available miRNA-seq and RNA-seq datasets, we found that miR-28a-5p, miR-302a-3p, miR-302b-3p, and miR-302d-3p were differentially expressed in the frontonasal process during embryonic days 10.5 to 13.5 (E10.5–E13.5) in mice. Overexpression of these miRNAs led to a suppression of cell proliferation in cultured mouse embryonic frontonasal mesenchymal (MEFM) cells as well as in O9-1 cells, a cranial neural crest cell line. Through advanced bioinformatic analyses and miRNA-gene regulation assays, we identified that miR-28a-5p regulated a total of 25 genes, miR-302a-3p regulated 23 genes, miR-302b-3p regulated 22 genes, and miR-302d-3p regulated 20 genes. Notably, the expression of miR-302a/b/d-3p—unlike miR-28a-5p—was significantly upregulated by excessive exposure to all-trans retinoic acid (atRA) that induces craniofacial malformations. Inhibition of these miRNAs restored the reduced cell proliferation caused by atRA by normalizing the expression of target genes associated with frontonasal anomalies. Therefore, our findings suggest that miR-302a/b/d-3p plays a crucial role in the development of frontonasal malformations. Full article

Recent advances in hyperspectral image (HSI) classification have demonstrated the effectiveness of hybrid architectures that integrate convolutional neural networks (CNNs) and Transformers, leveraging CNNs for local feature extraction and Transformers for global dependency modeling. However, existing fusion approaches face three critical challenges: (1) insufficient synergy between spectral and spatial feature learning due to rigid coupling mechanisms; (2) high computational complexity resulting from redundant attention calculations; and (3) limited adaptability to spectral redundancy and noise in small-sample scenarios. To address these limitations, we propose HyperTransXNet, a novel CNN-Transformer hybrid architecture that incorporates adaptive spectral-spatial fusion. Specifically, the proposed HyperTransXNet comprises three key modules: (1) a Hybrid Spatial-Spectral Module (HSSM) that captures the refined local spectral-spatial features and models global spectral correlations by combining depth-wise dynamic convolution with frequency-domain attention; (2) a Mixture-of-Experts Routing (MoE-R) module that adaptively fuses multi-scale features by dynamically selecting optimal experts via Top-K sparse weights; and (3) a Spatial-Spectral Tokens Enhancer (SSTE) module that ensures causality-preserving interactions between spectral bands and spatial contexts. Extensive experiments on the Indian Pines, Houston 2013, and WHU-Hi-LongKou datasets demonstrate the superiority of HyperTransXNet. Full article

In this paper, we propose TransConvNet, a hybrid model combining Convolutional Neural Networks (CNNs), self-attention mechanisms, and transfer learning for wireless signal recognition under challenging conditions. The model effectively addresses challenges such as low signal-to-noise ratio (SNR), low sampling rates, and limited labeled data. The CNN module extracts local features and suppresses noise, while the self-attention mechanism within the Transformer encoder captures long-range dependencies in the signal. To enhance performance with limited data, we incorporate transfer learning by leveraging pre-trained models, ensuring faster convergence and improved generalization. Extensive experiments were conducted on a six-class wireless signal dataset, downsampled to 1 MSPS to simulate real-world constraints. The proposed TransConvNet achieved 92.1% accuracy, outperforming baseline models such as LSTM, CNN, and RNN across multiple evaluation metrics, including RMSE and $R^2$. The model demonstrated strong robustness under varying SNR conditions and exhibited superior discriminative ability, as confirmed by Precision–Recall and ROC curves. These results validate the effectiveness and robustness of the TransConvNet model for wireless signal recognition, particularly in resource-constrained and noisy environments. Full article

The incidence of fatal anaphylaxis is increasing, but there is still no recognized “golden standard” for forensic diagnosis. Due to its non-specific symptoms, especially cardiovascular symptoms without cutaneous changes, it can easily be misdiagnosed as acute myocardial infarction. Here, we established rat models (n = 12) of fatal anaphylaxis (FA), acute myocardial infarction (AMI), and coronary atherosclerosis with anaphylaxis (CAA). The untargeted metabolomics of plasma and 16S rRNA sequencing of fecal matter was performed, and a random forest was used to identify potential biomarkers. Three metabolites (tryptophan, trans-3-indole acrylic acid, and imidazole acetic acid) and three microbial genera (g_Prevotellaceae_Ga6A1_group, g_UCG_008, and g_Eubacterium_hallii_group) were identified as potential biomarkers for distinguishing anaphylaxis and non-anaphylaxis. The classification model of plasma metabolites showed a much better discriminatory performance than that of microbial genus, serum IgE, and tryptase. The performance of the microbial genera was superior to the serum IgE but inferior to the serum tryptase. Forensic samples of fatal anaphylaxis and non-anaphylaxis deaths (n = 12) were collected for untargeted metabolomics detection. The results showed that among the three identified metabolic biomarkers, tryptophan has better stability in cadaveric blood samples. Its diagnostic performance (AUC = 87.1528) was superior to serum IgE and tryptase, making it more suitable as a postmortem biomarker of fatal anaphylaxis. Full article

Bioactive extracts from living plants (LR) and beach deposits (NR) of the submerged brackish water angiosperm Ruppia maritima were examined for their antioxidant activity and anticancer potential. LR extract scavenged effectively free radicals with IC₅₀ values of 38.00 μg/mL (DPPH^•), 12.00 μg/mL (ABTS^•+), 281.00 μg/mL (OH^•), and 53.00 μg/mL (O₂^•), and exhibited reducing activity with an RP_0.5AU value of 37.00 μg/mL. NR extract retained a significant part of LR extract’s antioxidant activity by scavenging free radicals with IC₅₀ values of 180.00 μg/mL (DPPH^•), 60.00 μg/mL (ABTS^•+), and 164.00 μg/mL (O₂^•), and exhibited reducing activity with an RP_0.5AU value of 107.00 μg/mL. Importantly, NR extract (IC₅₀ value: 60.00 μg/mL) exhibited much higher inhibitory activity than LR extract (IC₅₀ value: 1100.00 μg/mL) in XTT assay. HPLC analysis revealed that both R. maritima extracts contained phenolics, such as chicoric acid, quercetin-3-O-glucopyranoside, p-coumaric acid, 3,5-dimethoxy-4-hydroxicinnanic acid, trans-ferulic acid, and rutin hydrate, possessing antioxidant and/or anticancer activity. Thus, the present study showed for the first time that R. maritima extracts from either LR or NR are a promising source of bioactive compounds having beneficial properties for human health. Full article

Background/Objectives: High-fat-diet (HFD) consumption drives chronic liver injury via gut dysbiosis and metabolic disturban. Apple cider vinegar, rich in polyphenols and organic acids, shows potential in metabolic regulation. This study aimed to investigate whether apple cider vinegar powder (ACVP) alleviates HFD-induced liver injury by modulating the gut–liver axis. Methods: For 12 weeks, C57BL/6 J mice received daily ACVP gavage while being fed a HFD. A series of biological assessments were conducted, including systemic metabolic evaluations (body weight, serum alanine aminotransferase (ALT)/aspartate aminotransferase (AST), and lipid/glucose levels), hepatic steatosis (hematoxylin and eosin (H&E) staining), intestinal microbiome characterization (16S rRNA gene genomic analysis), and comprehensive metabolite profiling of cecal contents (non-targeted metabolomics). Pearson correlation networks integrated multi-omics data. Results: ACVP attenuated HFD-induced weight gain by 26.3%, hepatomegaly and dyslipidemia, as well as reduced hepatic lipid vacuoles and serum ALT (48%)/AST (21.5%). ACVP restored gut microbiota diversity, enriching Muribaculaceae. Cecal metabolomics identified 38 HFD-perturbed metabolites reversed by ACVP, including indolelactate, hyocholate, and taurocholic acid. the Kyoto encyclopedia of genes and genomes (KEGG) analysis revealed ACVP-mediated recovery of linoleic acid metabolism. Correlation networks linked Akkermansia to anti-inflammatory metabolites (e.g., trans-ferulic), while Desulfobacterota correlated with pro-inflammatory oxylipins (e.g., 12,13-dihydroxy-9Z-octadecenoic acid (DHOME)). Conclusions: ACVP mitigates HFD-induced liver injury by remodeling gut microbiota, restoring microbial metabolites, and enhancing gut–liver crosstalk. Full article

Single-cell RNA sequencing (scRNA-seq) enables expression quantitative trait locus (eQTL) analysis at cellular resolution, offering new opportunities to uncover regulatory variants with cell-type-specific effects. However, existing tools are often limited in functionality, input compatibility, or scalability for sparse single-cell data. To address these challenges, we developed scQTLtools, a comprehensive R/Bioconductor package that facilitates end-to-end single-cell eQTL analysis, from preprocessing to visualization. The toolkit supports flexible input formats, including Seurat and SingleCellExperiment objects, handles both binary and three-class genotype encodings, and provides dedicated functions for gene expression normalization, SNP and gene filtering, eQTL mapping, and versatile result visualization. To accommodate diverse data characteristics, scQTLtools implements three statistical models—linear regression, Poisson regression, and zero-inflated negative binomial regression. We applied scQTLtools to scRNA-seq data from human acute myeloid leukemia and identified eQTLs with regulatory effects that varied across cell types. Visualization of SNP–gene pairs revealed both positive and negative associations between genotype and gene expression. These results demonstrate the ability of scQTLtools to uncover cell-type-specific regulatory variation that is often missed by bulk eQTL analyses. Currently, scQTLtools supports cis-eQTL mapping; future development will extend to include trans-eQTL detection. Overall, scQTLtools offers a robust, flexible, and user-friendly framework for dissecting genotype–expression relationships in heterogeneous cellular populations. Full article