Search Results (1,957)

Soil salinization in oasis areas of arid regions is recognized as a dynamic and multifaceted environmental threat influenced by both natural processes and human activities. In this study, 13 spatiotemporal predictors derived from field surveys and remote sensing are utilized to construct a spatial probabilistic model of salinization. A Bayesian Belief Network is integrated with spline interpolation in ArcGIS to map the likelihood of salinization, while Partial Least Squares Structural Equation Modeling (PLS-SEM) is applied to analyze the interactions among multiple drivers. The test results of this model indicate that its average sensitivity exceeds 80%, confirming its robustness. Salinization risk is categorized into degradation (35–79% probability), stability (0–58%), and improvement (0–48%) classes. Notably, 58.27% of the 1836.28 km² Keriya Oasis is found to have a 50–79% chance of degradation, whereas only 1.41% (25.91 km²) exceeds a 50% probability of remaining stable, and improvement probabilities are never observed to surpass 50%. Slope gradient and soil organic matter are identified by PLS-SEM as the strongest positive drivers of degradation, while higher population density and coarser soil textures are found to counteract this process. Spatially explicit probability maps are generated to provide critical spatiotemporal insights for sustainable oasis management, revealing the complex controls and limited recovery potential of soil salinization. Full article

In the past three decades, localized research has highlighted shifts in rainfall patterns and temperature trends in central Ethiopia, a region vital for agriculture and economic activities and heavily dependent on climate conditions to sustain livelihoods and ensure food security. However, comprehensive analyses of long-term climate data remain limited for this area. Understanding local climate trends is essential for enhancing agricultural resilience in the study area, a region heavily dependent on rainfall for crop production. This study analyzes historical rainfall and temperature patterns over the past 30 years and projects future climate conditions using downscaled CMIP6 models under SSP4.5 and SSP8.5 scenarios. Results indicate spatial variability in rainfall trends, with certain areas showing increasing rainfall while others experience declines. Temperature has shown a consistent upward trend across all seasons, with more pronounced warming during the short rainy season (Belg). Climate projections suggest continued warming and moderate increases in annual rainfall, particularly under SSP8.5 by the end of the 21st century. It is concluded that both temperature and rainfall are projected to increase in magnitude by 2080, with higher Sen’s slope values compared to earlier periods, indicating a continued upward trend. These findings highlight potential breaks in agricultural calendars, such as shifts in rainfall onset and cessation, shortened or extended growing seasons, and increased risk of temperature-induced stress. This study highlights the need for localized adaptation strategies to safeguard agriculture production and enhance resilience in the face of future climate variability. Full article

In the final phases of casing production, shale gas horizontal wells with a downward slope frequently find it difficult to sustain self-flow production. The ideal tubing insertion depth for self-flow production in gas wells has not been thoroughly studied, even though the timely adoption of tubing production can successfully prolong the self-flow production period. Using a fully dynamic multiphase flow simulation program, the ideal tubing depth for gas well self-flow production was ascertained. A wellbore structural model was built using a particular well as an example. By altering the tubing depth, the formation pressure limit values necessary to sustain gas well self-flow production at various tubing depths were simulated. The appropriate tubing depth for gas well self-flow production was examined, along with the well’s cumulative gas output at various tubing depths. Using the example as a case study, it was discovered that the critical formation pressure for gas well self-flowing production dropped to 7.8 MPa when the tubing was lowered to 2600 m. This effectively increased cumulative production by 56.19 × 10⁶ m³ and extended the self-flow production time by roughly 135 days. The study’s findings offer strong evidence in favor of maximizing shale gas wells’ self-flow production performance in later phases of production. Full article

Background: Multisegmental lumbar degenerative disease (ms-LDD) is a common condition in older adults, often requiring surgical intervention. While rigid stabilization remains the gold standard, it is associated with complications such as adjacent segment disease (ASD), higher blood loss, and longer recovery times. The Dynesys dynamic stabilization system offers an alternative by preserving motion while stabilizing the spine. However, data comparing Dynesys with fusion in multisegmental cases are limited. Objective: This study evaluates the clinical and radiographic outcomes of Dynesys dynamic stabilization versus rigid stabilization in the treatment of ms-LDD. Methods: A retrospective analysis was conducted on 53 patients (mean age: 62.25 ± 15.37 years) who underwent either Dynesys dynamic stabilization (n = 27) or PLIF (n = 26) for ms-LDD involving at least seven motion segments. Clinical outcomes were assessed using the Visual Analog Scale (VAS) and Oswestry Disability Index (ODI), while radiological parameters such as lumbar lordosis (LL), sagittal vertical axis (SVA), and spinopelvic parameters (pelvic incidence, pelvic tilt and, sacral slope) were analyzed. A two-stage surgical approach was employed in the Dynesys group to enhance osseointegration, particularly in elderly osteoporotic patients. Results: Both groups showed significant improvements in VAS and ODI scores postoperatively (p < 0.001), with no significant differences between them. However, the Dynesys group demonstrated superior sagittal alignment correction, with a significant increase in LL (p < 0.002) and a significant decrease in SVA (p < 0.0015), whereas changes in the rigid stabilization group were not statistically significant. Additionally, the Dynesys group had fewer complications, including a lower incidence of ASD (0 vs. 6 cases). The two-stage technique facilitated improved screw osseointegration and reduced surgical risks in osteoporotic patients. Conclusions: Dynesys dynamic stabilization is an effective alternative to rigid stabilization in ms-LDD, offering comparable pain relief and functional improvement while preserving motion and reducing ASD risk. The two-stage approach enhances long-term stability, making it particularly suitable for elderly or osteoporotic patients. Further long-term studies are needed to confirm these findings. Full article

Preventing progressive collapse induced by accidental events poses a critical challenge in the design and construction of resilient structures. While substantial progress has been made in planar structures, the progressive collapse mechanisms of precast concrete spatial structures—particularly regarding the effects of precast slabs—remain inadequately explored. This study develops a refined finite element modeling approach to investigate progressive collapse mechanisms in fully bonded prestressed precast concrete (FB-PPC) spatial frames, both with and without precast slabs. The modeling approach was validated against available test data from related sub-assemblies, and applied to assess the collapse performance. A series of pushdown analyses were conducted on the spatial frames under various column removal scenarios. The load–displacement curves, slab contribution, and failure modes under different conditions were compared and analyzed. A simplified energy-based dynamic assessment was additionally employed to offer a rapid estimation of the dynamic collapse capacity. The results show that when interior or side columns fail, the progressive collapse process can be divided into the beam action stage and the catenary action (CA) stage. During the beam action stage, the compressive membrane action (CMA) of the slabs and the compressive arch action (CAA) of the beams work in coordination. Additionally, the tensile membrane action (TMA) of the slabs strengthens the CA in the beams. When the corner columns fail, the collapse stages comprise the beam action stage followed by the collapse stage. Due to insufficient lateral restraints around the failed column, the development of CA is limited. The membrane action of the slabs cannot be fully mobilized. The contribution of the slabs is significant, as it can substantially enhance the vertical resistance and restrain the lateral displacement of the columns. The energy-based dynamic assessment further reveals that FB-PPC spatial frames exhibit high ductility and residual strength following sudden column removal, with dynamic load–displacement curves showing sustained plateaus or gentle slopes across all scenarios. The inclusion of precast slabs consistently enhances both the peak load capacity and the residual resistance in dynamic collapse curves. Full article

The high cost of hydrogen production is the primary factor limiting the development of the hydrogen energy industry chain. Additionally, due to the inefficiency of hydrogen production by water electrolysis technology, the development of high-performance catalysts is an effective means of producing low-cost hydrogen. In water electrolysis technology, the electrocatalytic activity of the electrode affects the kinetics of the oxygen evolution reaction (OER) and the hydrogen evolution rate. This study utilizes the liquid phase co-precipitation method to synthesize three types of Prussian blue analog (PBA) electrocatalytic materials: Fe/PBA(Fe₄[Fe(CN)₆]₃), Fe-Mn/PBA((Fe, Mn)₃[Fe(CN)₆]₂·nH₂O), and Fe-Mn-Co/PBA((Mn, Co, Fe)₃^II[Fe^III(CN)₆]₂·nH₂O). X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses show that Fe-Mn-Co/PBA has a smaller particle size and higher crystallinity, and its grain boundary defects provide more active sites for electrochemical reactions. The electrochemical test shows that Fe-Mn-Co/PBA exhibits the best electrochemical performance. The overpotential of the oxygen evolution reaction (OER) under 1 M alkaline electrolyte at 10/50 mA·cm⁻² is 270/350 mV, with a Tafel slope of 48 mV·dec⁻¹, and stable electrocatalytic activity is maintained at 5 mA·cm⁻². All of these are attributed to the synergistic effect of Fe, Mn, and Co metal ions, grain refinement, and the generation of grain boundary defects and internal stresses. Full article

As an efficient clean energy technology, water electrolysis for hydrogen production has its efficiency limited by the sluggish oxygen evolution reaction (OER) kinetics, which drives the demand for the development of high-performance anode OER catalysts. This work constructs bimetallic (Al, Mn) co-doped nanoporous spinel CoFe₂O₄ (np-CFO) with a tunable structure and composition as an OER catalyst through a simple two-step dealloying strategy. The as-formed np-CFO (Al and Mn) features a hierarchical flaky configuration; that is, there are a large number of fine nanosheets attached to the surface of a regular micron-sized flake, which not only increases the number of active sites but also enhances mass transport efficiency. Consequently, the optimized catalyst exhibits a low OER overpotential of only 320 mV at a current density of 10 mA cm⁻², a minimal Tafel slope of 45.09 mV dec⁻¹, and exceptional durability. Even under industrial conditions (6 M KOH, 60 °C), it only needs 1.83 V to achieve a current density of 500 mA cm⁻² and can maintain good stability for approximately 100 h at this high current density. Theoretical simulations indicate that Al and Mn co-doping could indeed optimize the electronic structure of CFO and thus decrease the energy barrier of OER to 1.35 eV. This work offers a practical approach towards synthesizing efficient and stable OER catalysts. Full article

Background/Objectives: Although numerous prognostic biomarkers have been proposed for colorectal cancer (CRC), their longitudinal evaluation remains limited. The aim of this study was to investigate longitudinal changes in biomarkers calculated from routinely used laboratory markers and their relationships to common chronic diseases (comorbidities). Methods: A retrospective longitudinal observational study was completed with the inclusion of 817 CRC patients and a total of 4542 measurement points. Pan-immune inflammation value (PIV), prognostic nutritional index (PNI), and systemic immune-inflammation index (SII) were calculated based on complete blood count and albumin measurement data. Results: Longitudinal data analyses confirmed the different values and slopes of the parameters tested at the different endpoints. Survivors had the lowest and most constant PIVs and SII values, and the highest and most slowly decreasing PNI values. Those patients with non-cancerous death had similar values to the previous cohort, but an increase/decrease occurred towards the death event. Patients with CRC-related death had significantly higher PIVs and SII values and significantly lower PNI values (p < 0.0001), and a significant increase/decrease was observed at the early observational periods. The presence of lymph node and/or distant metastases, adjuvant chemotherapy, and hypertension significantly affected PIVs and SII and/or PNI values. The changes in PIVs and SII and PNI values toward pathological values are poor prognostic signs (p < 0.0001). Conclusions: Each of the three calculated markers demonstrates suitability for longitudinal patient follow-up, and their pathological alterations over time serve as valuable prognostic indicators. They may also be useful to detect certain clinicopathological parameters early. Full article

Xi’an, China, has a complex geological environment, with geological hazards seriously hindering urban development and safety. This study analyzed the conditions leading to disaster formation and screened 12 evaluation factors (e.g., slope and slope direction) using Spearman’s correlation. Furthermore, it also introduced an innovative combined weighting method, integrating subjective weights from the hierarchical analysis method and objective weights from the entropy method, as well as an information value model for susceptibility assessment. The main results are as follows: (1) There are 787 hazard points—landslides/collapses are concentrated in loess areas and Qinling foothills, while subsidence/fissures are concentrated in plains. (2) The combined weighting method effectively overcame the limitations of single methods. (3) Validation using hazard density and ROC curves showed that the combined weighting information value model achieved the highest accuracy (AUC = 0.872). (4) The model was applied to classify the disaster susceptibility of Xi’an into high (12.31%), medium (18.68%), low (7.88%), and non-susceptible (61.14%) zones. The results are consistent with the actual distribution of disasters, thus providing a scientific basis for disaster prevention. Full article

In 2071, the Hydraulic community will commemorate the second centenary of the Baré de Saint-Venant equations, also known as the Shallow Water Equations (SWE). These equations are fundamental to the study of open-channel flow. As non-linear partial differential equations, their solutions were largely unattainable until the development of computers and numerical methods. Following 1960, various numerical schemes emerged, with Preissmann’s scheme becoming the most widely employed in many software applications. In the 1990s, some researchers identified a significant limitation in existing software and codes: the inability to simulate transcritical flow. At that time, Preissmann’s scheme was the dominant method employed in hydraulics tools, leading the research community to conclude that this scheme could not handle transcritical flow due to suspected instability. In response to this concern, several researchers suggested modifications to Preissmann’s scheme to enable the simulation of transcritical flow. This paper will demonstrate that these accusations against the Preissmann scheme are unfounded and that the proposed improvements are unnecessary. The observed instability is not due to the numerical method itself, but rather a mathematical instability inherent to the SWE, which can lead to ill-posed conditions if a specific derived condition is not met. In the context of a friction slope formula based on Manning or Chézy types, the condition for ill-posedness of the 1D shallow water equations simplifies to the Vedernikov number condition, which is necessary for roll waves to develop in uniform flow. This derived condition is also relevant for the formation of roll waves in unsteady flow when the 1D shallow water equations become ill-posed. Full article

Habitat fragmentation restricts the movement of large mammals across broad landscapes, leading to isolation of individuals or groups, reduced interaction with other species, and limited access to vital resources in surrounding habitats. In this study, we aimed to determine the wildlife ecological corridors for five large mammals (Ursus arctos, Cervus elaphus, Capreolus capreolus, Sus scrofa, and Canis lupus) between Kastamonu Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. In the field studies, we used the transect, indirect observation, and camera-trap methods to collect presence data. Maximum Entropy (MaxEnt) (v. 3.4.1) software was used to create habitat suitability models of the target species, which are based on the presence-only data approach. The results indicated that AUC values varied between 0.808 and 0.835, with water sources, stand type, and slope contributing most significantly to model performance. In order to determine wildlife ecological corridors, resistance surface maps were created using the species distribution models (SDMs), and bottleneck areas were determined. The Circuit Theory approach was used to model the connections between ecological corridors. As a result of this study, we developed connectivity models for five large mammals based on Circuit Theory, identified priority wildlife ecological corridors, and evaluated critical connection points between two protected areas, Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. These findings highlight the essential role of ecological corridors in sustaining landscape-level connectivity and supporting the long-term conservation of wide-ranging species. Full article

Prostate cancer (PCa) is the second leading cause of cancer-related death among men in most Western countries. Current therapies for PCa are limited, often ineffective, and associated with significant side effects. As a result, there is a growing interest in exploring new therapeutic agents, particularly from the polyphyletic group of algae, which offers a promising source of compounds with anticancer properties. Our research group has focused on investigating the effects of a novel oleoresin from Gracilaria chilensis, known as Gracilex^®, as a potential therapeutic agent against PCa using both in vitro and in vivo models. Our findings indicate that Gracilex^® exhibits a time- and dose-dependent inhibitory effect on cell survival in LNCaP and PC-3 PCa, reducing viability by over 50% and inducing apoptosis, as evidenced by a significant increase in activated caspase-3 expression in both cell lines. Moreover, Gracilex^® significantly reduces the proliferation rate of both LNCaP and PC-3 prostate cancer cell lines, as evidenced by a marked decrease in the growth curve slope (p = 0.0034 for LNCaP; p < 0.0001 for PC-3) and a 40–50% reduction in the proportion of Ki-67-positive PCa cells. In addition, Gracilex^® significantly reduces in vitro cell migration and invasion in LNCaP and PC-3 cell lines. Lastly, Gracilex^® inhibits tumor growth in an in vivo xenograft model, an effect that correlates with the reduced PCa cell proliferation observed in tumor tissue sections. Collectively, our data strongly support the broad antitumoral effects of Gracilex^® on PCa cells in vitro and in vivo. These findings advance our understanding of its potential therapeutic role in PCa and highlight the relevance of further investigating algae-derived compounds for cancer treatment. Full article

Background: Despite the growing demand for amyloid PET quantification, practical challenges remain. As automated software platforms are increasingly adopted to address these limitations, we evaluated the reliability of commercial tools for Centiloid quantification against the original Centiloid Project method. Methods: This retrospective study included 332 amyloid PET scans (165 [¹⁸F]Florbetaben; 167 [¹⁸F]Flutemetamol) performed for suspected mild cognitive impairments or dementia, paired with T1-weighted MRI within one year. Centiloid values were calculated using three automated software platforms, BTXBrain, MIMneuro, and SCALE PET, and compared with the original Centiloid method. The agreement was assessed using Pearson’s correlation coefficient, the intraclass correlation coefficient (ICC), a Passing–Bablok regression, and Bland–Altman plots. The concordance with the visual interpretation was evaluated using receiver operating characteristic (ROC) curves. Results: BTXBrain (R = 0.993; ICC = 0.986) and SCALE PET (R = 0.992; ICC = 0.991) demonstrated an excellent correlation with the reference, while MIMneuro showed a slightly lower agreement (R = 0.974; ICC = 0.966). BTXBrain exhibited a proportional underestimation (slope = 0.872 [0.860–0.885]), MIMneuro showed a significant overestimation (slope = 1.053 [1.026–1.081]), and SCALE PET demonstrated a minimal bias (slope = 1.014 [0.999–1.029]). The bias pattern was particularly noted for FMM. All platforms maintained their trends for correlations and biases when focusing on subthreshold-to-low-positive ranges (0–50 Centiloid units). However, all platforms showed an excellent agreement with the visual interpretation (areas under ROC curves > 0.996 for all). Conclusions: Three automated platforms demonstrated an acceptable reliability for Centiloid quantification, although software-specific biases were observed. These differences did not impair their feasibility in aiding the image interpretation, as supported by the concordance with visual readings. Nevertheless, users should recognize the platform-specific characteristics when applying diagnostic thresholds or interpreting longitudinal changes. Full article

Accurate prediction of landslide-induced displacement is essential for the structural integrity and operational safety of buildings and infrastructure situated in geologically unstable regions. This study introduces a novel hybrid predictive framework that synergistically integrates Gaussian Process Regression (GPR) with Temporal Convolutional Neural Networks (TCNs), herein referred to as the GTCN model, to forecast displacement at building monitoring points subject to landslide activity. The proposed methodology is validated using time-series monitoring data collected from the slope adjacent to the Zhongliang Reservoir in Wuxi County, Chongqing, an area where slope instability poses a significant threat to nearby structural assets. Experimental results demonstrate the GTCN model’s superior predictive performance, particularly under challenging conditions of incomplete or sparsely sampled data. The model proves highly effective in accurately characterizing both abrupt fluctuations within the displacement time series and capturing long-term deformation trends. Furthermore, the GTCN framework outperforms comparative hybrid models based on Gated Recurrent Units (GRUs) and GPR, with its advantage being especially pronounced in data-limited scenarios. It also exhibits enhanced capability for temporal feature extraction relative to conventional imputation-based forecasting strategies like forward-filling. By effectively modeling both nonlinear trends and uncertainty within displacement sequences, the GTCN framework offers a robust and scalable solution for landslide-related risk assessment and early warning applications. Its applicability to building safety monitoring underscores its potential contribution to geotechnical hazard mitigation and resilient infrastructure management. Full article

Background and Objectives: Surgical site infections (SSIs) are a frequent complication after lower extremity fracture surgery, yet tools for individualized risk prediction remain limited. This study aimed to develop and internally validate a nomogram for individualized SSI risk prediction based on perioperative clinical parameters. Materials and Methods: This retrospective cohort study included adults who underwent lower extremity fracture surgery between 2022 and 2025 at a tertiary care center. Thirty candidate predictors were evaluated. Feature selection was performed using six strategies, and the final model was developed with logistic regression based on bootstrap inclusion frequency. Model performance was assessed by area under the curve, calibration slope, Brier score, sensitivity, and specificity. Results: Among 638 patients undergoing lower extremity fracture surgery, 76 (11.9%) developed SSIs. Of six feature selection strategies compared, bootstrap inclusion frequency identified seven predictors: red blood cell count, preoperative C-reactive protein, chronic kidney disease, operative time, chronic obstructive pulmonary disease, body mass index, and blood transfusion. The final model demonstrated an AUROC of 0.924 (95% CI, 0.876–0.973), a calibration slope of 1.03, and a Brier score of 0.0602. Sensitivity was 86.2% (95% CI, 69.4–94.5) and specificity was 89.5% (95% CI, 83.8–93.3). Chronic kidney disease (OR, 88.75; 95% CI, 5.51–1428.80) and blood transfusion (OR, 85.07; 95% CI, 11.69–619.09) were the strongest predictors of infection. Conclusions: The developed nomogram demonstrates strong predictive performance and may support personalized SSI risk assessment in patients undergoing lower extremity fracture surgery. Full article