Search Results (29,103)

During offshore oilfield development, traditional injection–production processes commonly suffer from delayed regulation, low operational efficiency, and heavy reliance on manual intervention. Achieving real-time diagnosis of injection–production anomalies and dynamic optimization under complex geological conditions and harsh marine environments represents a core scientific challenge. This study presents the development and field deployment of an intelligent cable-controlled injection–production integrated management system. The work is positioned as an application- and system-oriented study, focusing on addressing practical challenges in offshore oilfield operations through the integration of established machine learning techniques into a cohesive operational platform. The system employs a cloud-native microservice architecture and integrates nine functional modules, enabling closed-loop management from data acquisition to intelligent decision making. Key methodological contributions include: (1) a weighted ensemble model combining Random Forest and SVM for blockage diagnosis, balancing global feature learning with boundary sample discrimination to achieve 92% diagnostic accuracy; (2) a Bayesian fusion framework that integrates static geological priors with dynamic sensitivity analysis for probabilistic quantification of injector–producer connectivity, achieving 85% identification accuracy with rigorous uncertainty propagation; and (3) a three-stage human–machine collaborative mechanism that substantially reduces anomaly response latency while ensuring field safety. Field application in Bohai oilfields demonstrates that the system shortens the injection–production response cycle by approximately 42%, reduces anomaly response time from over 72 h to less than 2 h (a 97% reduction), decreases water consumption per ton of oil by 27.6%, and increases injection–production uptime by 11.3 percentage points. This study provides an interpretable, extensible, and closed-loop technical solution for intelligent offshore oilfield development, with future directions including digital twin predictive simulation and reinforcement learning for real-time optimization. Full article

Scene text detection aims to accurately localize text instances in images captured under complex environments. Its performance depends heavily on precise text boundary delineation and reliable semantic discrimination from cluttered backgrounds. However, existing methods still struggle in such complex scenes. Repeated downsampling gradually biases features toward low-frequency components, thereby weakening edge details and local structures that are critical to text morphology. Additionally, semantic information and local details are often modeled independently. This lack of coordination makes high-frequency responses vulnerable to background noise. To address these issues, we propose HFI-Former, a Transformer-based model designed for high-frequency enhancement and feature interaction. The framework consists of multi-scale feature extraction, frequency-enhanced representation, semantic-guided feature interaction, and deformable Transformer encoding. Frequency-domain enhancement is introduced to preserve high-frequency structural features degraded by repeated downsampling. Semantic-aware feature interaction further injects global context to regulate multi-scale feature fusion. Experiments on CTW1500, Total-Text and ICDAR1500 demonstrate competitive boundary localization accuracy and strong overall detection performance in complex scenes. Full article

Machine learning methods have gained significant attention in forecasting waterflooding performance in recent years, but their accuracy often remains insufficient for practical field applications. This study proposes a hybrid framework that integrates a linear dynamical system (LDS) with a neural network (NN). The framework improves oil-rate prediction by decomposing the injection–production relationship into linear and nonlinear components. Specifically, the aggregate injection rate is approximately linearly related to total liquid production, which is effectively captured by the LDS model, based on reservoir material balance principles. In contrast, the oil fraction of the produced liquid, defined as the ratio of oil rate to liquid rate, is bounded between 0 and 1 and typically decreases over time. This nonlinear trend is accurately modeled using a neural network (NN). The parameters of the LDS–NN framework are learned from historical injection and production data via a supervised training process. Furthermore, key hyperparameters within the model can be adjusted to optimize the performance for different reservoir characteristics. The proposed hybrid method is evaluated using both simulated reservoir cases and real field data, and compared against the performance of LDS-only and NN-only models. The results demonstrate that the LDS–NN framework consistently provides more accurate oil-rate predictions than either standalone LDS or NN approaches, across both synthetic and real-world waterflooding scenarios. Full article

During the CO₂ fracturing of unconventional oil and gas resources, the structural and operational parameters significantly influence the fracturing effectiveness. To quantitatively reveal the influence mechanisms of key parameters on the CO₂ jet flow field through perforations, this study employed computational fluid dynamics (CFD) via Ansys Fluent to simulate and compare the effects of the nozzle contraction angle, injection rate, confining pressure, and fluid temperature. The results indicate that the contraction angles and injection rates have a more significant influence on the jet temperature, pressure, and velocity than the confining pressures and fluid temperatures. As the contraction angle increases, the average velocity of the jet core region increases by 5.0% (with the most significant growth at 35°), and the length of the potential core increases correspondingly. The flow through the perforations is characterized by an instantaneous drop of 2.5 °C in temperature and 2.7 MPa in pressure, then transitions to a regime of temperature recovery and dynamical pressure decay along the fracture. Increasing the fracturing displacement raises the maximum jet velocity to 104.7 m/s (an average increase of 15.5%), extends the potential core length, and amplifies the temperature and pressure drops across the perforation from 1.1 °C and 1.2 MPa to 4.2 °C and 4.8 MPa, respectively. Conversely, higher confining pressure reduces the average jet velocity by 4.3%, shortens the potential core, and diminishes the perforation temperature and pressure drops from 5 °C and 3 MPa to 2 °C and 2.5 MPa. In contrast, elevating the fluid temperature increases the jet velocity by an average of 6.3% but exerts minimal influence on the potential core length; the temperature drop at the perforation remains at approximately 2 °C, while the pressure drop rises from 2.2 MPa to 2.9 MPa. Collectively, both the confining pressure and fluid temperature significantly affect the density and velocity characteristics of the jet. An increase in confining pressure enhances the density of the CO₂ jet fluid, which may potentially improve the fracturing impact in actual engineering applications. Quantitatively, the influence of each parameter on the temperature, pressure, and velocity of the CO₂ jet is ranked from the most significant to the least as follows: nozzle contraction angle > fracturing injection displacement > formation confining pressure > fluid temperature. The findings of this research have direct implications for practical application, informing the optimization of the fracturing design to achieve greater efficiency and lower risk in CO₂ fracturing operations. Full article

Lactococcosis caused by Lactococcus garvieae is an emerging threat to warmwater aquaculture, yet evidence integrating field outbreaks with robust molecular confirmation and controlled virulence testing remains limited for Thailand’s cage-cultured tilapia. From May to October 2025, acute mortality events were investigated in cage-cultured Nile tilapia (Oreochromis niloticus) in a reservoir in Ubon Ratchathani Province, Thailand. Suspected outbreaks were defined by abrupt daily mortality exceeding 5% accompanied by septicemia-like clinical signs. Water quality during sampling covered the following ranges: temperature 28.6–31.9 °C, pH 6.5–7.0, salinity 0.02–0.03 ppt, electrical conductivity 0.036–0.046 mS/cm, TDS 22.20–26.50 mg/L, total alkalinity 17.0–34.0 mg/L as CaCO₃, total hardness 12.0–60.0 mg/L as CaCO₃, dissolved oxygen 6.5–7.0 mg/L, and NH₃ were below the limit of detection. Full-length 16S rRNA tissue profiling revealed strong tissue partitioning: blood microbiomes were consistently dominated by Lactococcus and L. garvieae at the species level, whereas gills showed higher richness and mixed communities with multiple opportunistic taxa. Culture isolation was more reliable from blood than gills, yielding 16 Gram-positive, catalase-negative isolates (AAHM-LG2501–AAHM-LG2516) that clustered within the L. garvieae clade in near full-length 16S rRNA phylogenetic analysis and were separated from closely related Lactococcus lineages. A representative blood isolate (AAHM-LG2501) showed dose-dependent virulence in controlled challenges, with an LD₅₀ of ~1.05 × 10⁵ CFU/fish by intraperitoneal injection and an LC₅₀ of ~1.20 × 10⁶ CFU/mL by immersion. Histopathology supported systemic dissemination, with injection producing more consistent multi-organ lesions than immersion, particularly in head kidney, liver, and spleen, while gills exhibited route-associated epithelial and vascular alterations. Together, these findings confirm L. garvieae as a major etiological agent of septicemic outbreaks in cage-cultured tilapia in Thailand and support a practical surveillance framework prioritizing blood sampling, molecular confirmation, and risk-based monitoring to guide biosecurity and vaccine-oriented prevention. Full article

Background: In Parkinson’s disease (PD), changes in the brain begin before clinical symptoms. We have previously shown that VGF precursor levels were reduced in a presymptomatic PD animal model. Objectives: In the present study, we investigated whether two VGF precursor-derived products, namely NAPP-129 protein and TLQP-62 peptide, also exhibit alterations using the same PD animal model. Methods: Specifically, rats were unilaterally injected in the substantia nigra with a viral vector overexpressing green fluorescent protein (N = 12) or α-synuclein (N = 13), the latter resulting in mild dopaminergic alterations without overt motor deficits. Results: NAPP-129 and TLQP-62 were investigated in the substantia nigra, striatum, and plasma by Western blotting or immunoassays using specific antibodies against NAPP and TLQP sequences, alongside other NERP-1- and AQEE-related products. Plasma samples of a Huntington’s disease mouse model were also analyzed. We found reductions in NAPP-129 and TLQP-62 levels in the substantia nigra along with a decrease in NAPP- and TLQP-like plasma immunoreactivity in α-synuclein-overexpressed rats, while the striatum was not affected. NERP-1- and AQEE-related products were not altered. No changes were found in the Huntington’s disease model. Conclusions: These findings indicate that NAPP-129 and TLQP-62 may enhance the sensitivity and specificity of biomarker-based strategies for PD. Full article

Antheraea pernyi larvae growing in the wild suffer damage from the drift diffusion of insecticides used in surrounding farmland. In this study, we assessed the toxicity of beta-cypermethrin, chlorantraniliprole, imidacloprid, and thiamethoxam to different A. pernyi strains. It was found that the lowest LC₅₀ value of the Liaocanda9 strain against beta-cypermethrin (0.008 mg/L) was significantly higher than that of the Kangda strain (0.0047 mg/L). Additionally, beta-cypermethrin exposure was associated with significant increases in detoxification and antioxidant enzyme activities in both strains. Transcriptomic analysis showed that differentially expressed genes (DEGs) were significantly enriched in pathways related to oxidoreductase activity and transmembrane transporter activity terms. Furthermore, these genes were differentially expressed following the beta-cypermethrin exposure. The dsRNA injection treatment effectively inhibited the expression of P450 genes, thereby reducing the tolerance of A. pernyi against beta-cypermethrin by 25.93–55.56%. Molecular docking predicted that beta-cypermethrin bound to ABCG1, ABCG5, and CYP9A22 with hydrogen bonds. These results indicate that ABC transporters and P450s contribute to the tolerance of A. pernyi against beta-cypermethrin. Full article

Background: Exosomes (Exos) derived from immune cells are emerging as potent drug delivery vectors. However, their biodistribution in clinically relevant lung cancer models remains underexplored. This study aimed to evaluate the lung-homing ability of NK cell Exos (NK-Exos) compared to mesenchymal stem cell Exos (MSC-Exos) in an orthotopic lung cancer model. Methods: Male SCID mice were orthotopically injected with luciferase-tagged A549 cells into the left lung to establish the tumor model. Mice were randomized into four groups: G1 (Healthy Control), G2 (Tumor Control + PBS), G3 (Tumor + DiR-labeled NK-Exos; 5 µM DiR + 5–7 × 10⁹ Exo particles/100 μL/mouse), and G4 (Tumor + DiR-labeled MSC-Exos; 5 µM DiR + 5–7 × 10⁹ Exo particles/100 μL/mouse). Six hours (15 min, 1 h, 2 h, 4 h, 6 h) post-intravenous injection, ex vivo biodistribution was assessed using the MILabs Spectrum imaging system. Results: Umbilical cord blood-NK-Exos (UCB-NK-Exos; G3) exhibited superior accumulation in lung tissues compared to UCB-MSC-Exos (G4), suggesting enhanced pulmonary retention. Intra-pulmonary analysis revealed an asymmetric distribution, with significantly higher radiant efficiency in the right lung (non-tumor bearing) compared to the left lung (tumor injection site) across Exo-treated groups. Conclusions: UCB-NK-Exos demonstrate distinct lung-targeting properties superior to MSC-Exos, supporting their potential as therapeutic carriers. Full article

The lithology of multilayer superposed coal-measure reservoirs is highly interbedded, and the mechanical contrast between adjacent layers is significant, resulting in strong uncertainty in the initiation and propagation behavior of hydraulic fractures. To address the problem that the fracture-propagation mechanism under multi-lithology assemblages remains insufficiently understood, typical layered composite specimens were constructed, and large-scale true triaxial hydraulic fracturing physical simulation tests were performed to systematically investigate the effects of coal seam thickness, interlayer thickness, injection rate, and fracturing-fluid viscosity on fracturing pressure, fracture propagation path, and propagation capacity. The results show that when the coal seam thickness does not exceed 90 mm, cross-layer connectivity at the fracture breakthrough interface is more likely to occur. Interlayer thickness directly controls fracture-height growth. When the mudstone interlayer thickness is 40 mm, the fracture still retains the ability to propagate across layers, whereas this ability decreases significantly as the interlayer becomes thicker. When the injection rate is increased from 20 mL min⁻¹ to 30 mL min⁻¹, the overall pump-pressure platform rises, accompanied by a simultaneous increase in fracture extension scale and connectivity. As the fracturing-fluid viscosity increases from 3 mPa·s to 24 mPa·s, both the fracturing pressure and platform pressure increase significantly, and the fracture morphology gradually changes from dispersed propagation to more concentrated extension. The results further indicate that structural constraint factors (coal seam thickness and interlayer thickness) and dynamic driving factors (injection rate and fracturing-fluid viscosity) jointly control the spatial structure and pressure-response characteristics of fractures. Among these factors, interlayer thickness determines the conditions for cross-layer fracture propagation, injection rate and fluid viscosity control the ability to maintain net pressure within the fracture, and coal seam thickness constitutes an important geometric constraint. These findings provide an experimental basis for fracturing-parameter optimization and cross-layer stimulation design in multilayer superposed reservoirs. Full article

Background/Objectives: Cardiovasc{Citation}ular disease accounts for 50% of chronic kidney disease (CKD) mortality, yet fewer than 40% of patients achieve guideline LDL-cholesterol (LDL-C) targets on statins. Injectable lipid-lowering therapies (ILLTs)—PCSK9 inhibitors and inclisiran—offer 50–70% LDL-C reductions but lack comprehensive CKD-specific evidence synthesis. This systematic review evaluated ILLT efficacy, safety, and implementation across kidney function stages including dialysis. Methods: Following PROSPERO registration (CRD42024612594), we searched MEDLINE, Embase, Cochrane Library, CINAHL, and Google Scholar (1995–August 2025). Two reviewers independently screened studies using PICOS criteria: adults with CKD stages G3-G5, dialysis, or transplant recipients receiving injectable lipid therapies. Primary outcomes were LDL-C percentage change and major adverse cardiovascular events. Quality was assessed using NIH tools. Given heterogeneity, we performed narrative synthesis following SWiM guidance. Results: Eight studies (n = 28,013) met the criteria. The FOURIER trial demonstrated that evolocumab achieved 58–59% LDL-C reductions across kidney function strata (interaction p = 0.77) with preserved cardiovascular benefit (HR 0.82–0.89). Absolute risk reduction was greater in advanced CKD (2.5% vs. 1.7%), reflecting higher baseline rates. Pharmacokinetic studies showed no eGFR-exposure correlation requiring dose adjustment; evolocumab was not removed by haemodialysis. Inclisiran achieved a 67–80% PCSK9 reduction and a 35–58% LDL-C reduction across renal groups, with twice-yearly maintenance dosing. Both classes reduced non-HDL-C (45–50%), apoB (40–45%), and lipoprotein(a) (20–25%). Safety was favourable, with mild injection-site reactions (< 5%); no renal decline signals emerged. Conclusions: Evidence for injectable lipid-lowering therapies in CKD are driven largely by a single large post hoc subgroup analysis (FOURIER) and small phase 1–2 PK/PD studies, with minimal dialysis representation and no transplant data. These agents appear to provide substantial LDL-C reductions across CKD stages G3–G5 without dose adjustment, but cardiovascular and renal outcome data in advanced CKD and dialysis remain limited and should be interpreted cautiously. Full article

The hydrojet-shield machine, a rapidly advancing shield machine type, uses slurry for excavation and muck removal via a pipeline system. The pipeline includes a flushed feeding system that injects slurry into areas at risk of obstruction. This study provides a computational fluid dynamics (CFD) analysis of the flow characteristics of a large hydraulic shield machine, proposing the Particle Lifting Coefficient (L) and Regional Improvement Ratio (I) as innovative criteria to evaluate the effects of flow rate distribution and cutting wheel rotational velocity. By adjusting the proportion of scouring flow in the lower part of the chambers to 30%, 50%, and 100%, three flow distribution strategies, labeled as FC1, FC2, and FC3, were obtained to suit normal slurry transport conditions, address cutterhead mud accumulation, and deal with the deposition of rock and soil particles at the bottom of the chamber, respectively. The FC3 strategy amplifies the flow of symmetric jets in the lower scouring region, strengthening the upward flow that entrains surrounding fluid, thereby significantly increasing the L and I values in the targeted area and showing great potential for inhibiting the settlement and deposition of rock and soil debris. This study also emphasizes the need to integrate slurry jet distribution strategies with real-time monitoring of cutterhead mud accumulation and chamber deposition, while adjusting cutterhead rotation speed based on geological conditions. Full article

Poisoning and shilling attacks remain a serious threat to recommender systems, especially as attackers increasingly mimic plausible profile statistics. This paper proposes an architecture-independent behavioral detection layer that models user interactions as short-window phase-dynamic trajectories rather than static aggregates. Interaction logs are transformed into temporal signals, reconstructed in phase space by delay embedding, and summarized by a compact 15-dimensional portrait combining recurrence-based, entropy-based, spectral, and stabilizing statistical descriptors. In a controlled targeted injection protocol evaluated over 10 independent runs, the statistical baseline achieved PR-AUC = 0.723 ± 0.037 and TPR@1%FPR = 0.029 ± 0.006, the dynamic block achieved PR-AUC = 0.831 ± 0.011 and TPR@1%FPR = 0.220 ± 0.050, and the full portrait achieved PR-AUC = 0.872 ± 0.017 and TPR@1%FPR = 0.291 ± 0.043. Sensitivity analysis showed that recurrence-only descriptors were parameter-sensitive, whereas the extended dynamic block formed a stable high-performance region across a broad range of embedding settings. An IQR-normalized aggregated risk score further demonstrated clear post-window regime separation during injection periods. The results indicate that poisoning attacks primarily deform the temporal organization of behavior rather than only first-order statistics. The proposed phase-dynamic portrait is therefore best interpreted as a complementary behavioral risk-scoring layer for auditing, filtering, and monitoring rather than as a standalone defense. Full article

Background/Objectives: To evaluate the influence of different DIXON contrasts on the quality of subtraction images in dynamic breast MRI using maximum intensity projections (MIPs). Methods: This retrospective study included n = 40 women (median age: 53.5 years, range 23–83) undergoing clinically indicated breast MRI (3T). For each MRI examination, two independent readers individually evaluated GBCA-enhanced subtraction MIPS for different timepoints (n = 5) and DIXON contrasts (n = 4) per breast, resulting in a total of 800 individual evaluations. Evaluations comprised (a) qualitative measures, using Likert-scores for artefact strength, breast parenchyma visibility, lesion visibility and reading confidence; and (b) signal intensity, measured in three regions of interest with the apparent signal-to-noise ratio (aSNR) and apparent contrast-to-noise ratio (aCNR) calculated. The evaluation results were analysed to identify differences between DIXON contrasts. Results: The “only water” DIXON contrast at ~120s after GBCA injection achieved the highest lesion conspicuity and reading confidence scores and lowest artefact scores; however, its performance was not statistically significant (p > 0.05) compared to the “in-phase” and “opposed-phase” subtractions. The aCNR at the second timepoint was slightly, but not significantly (p > 0.05), lower than the first timepoint, whilst aSNR increased significantly from the first to second timepoint in all contrasts. Conclusions: Subtraction MIPs derived from the “only water” DIXON contrast achieved the highest qualitative scoring for lesion conspicuity and confidence, with the aSNR increasing and aCNR decreasing between the first and second timepoints. Full article

Background/Objectives: Medication errors remain a patient safety concern in neonatal intensive care units (NICU), mainly due to multiple dilution steps, a lack of standardized preparation instructions, and the frequent use of high-alert medications. While standard concentrations (SCs) for intravenous (iv) medication are recommended internationally, a national standard is missing for NICUs in Germany. The aim of this study was to evaluate a proposal for a national list of standardized iv medication concentrations to be used in German NICUs. Methods: In collaboration with the German Society for Neonatology and Pediatric Intensive Care (GNPI) and the Federal Association of German Hospital Pharmacists (ADKA), a multiprofessional expert team, including experts from the medication safety initiatives TELE-KASPER and Kinderformularium.DE and affiliated with seven German university hospitals, evaluated SCs for infusion medication administered to infants weighing 500 g to 5 kg. The evaluation process was based on international SCs lists, clinical practice, stability data, and handling aspects. Medication used in at least four of the seven hospitals was shortlisted. In the first round of the consensus process, an online survey submitted to the German Level-1 NICUs (n = 165) and their affiliated hospital pharmacies identified preferred SCs. In the second round of the consensus process, the expert team further evaluated the results of the survey. Results: The survey response rate was 52%. The consensus process resulted in a list encompassing 50 iv medications and 80 appropriate SCs. Ancillary information on preparation, stability, osmolarity, pH, and practical administration was added. Conclusions: The proposed SCs for infusion medication used in NICUs have the potential to reduce medication errors, simplify electronic prescribing, and improve workflow efficiency. Implementation aligns with international patient safety initiatives to improve medication safety in pediatric patients. Full article