Search Results (145)

Escherichia coli displays strong adaptability for growth and reproduction at low temperatures, with ribosome biogenesis being a critical process for its growth in cold environments. The cold-shock proteins (CSPs) encompass a protein family that can assist bacterial growth at low temperatures by acting as molecular chaperones. In this study, we investigated whether CSP CspA, CspE, and CspI affect ribosomal RNA (rRNA) transcription. Deletion of the single genes encoding these proteins had only a very marginal effect on cellular growth at low temperatures, and rRNA synthesis was hardly affected. Double and triple deletion of the genes encoding these proteins resulted in a much stronger phenotype providing evidence that CspA, CspE, and CspI play an essential role in maintaining 16S rRNA synthesis and enabling optimal cellular growth at low temperatures. These findings suggest the existence of efficient backup mechanisms able to compensate for the absence of a single CSP. Full article

Deep coalbed methane development faces technical challenges, such as high in situ stress and low permeability. The dynamic evolution of fractures after hydraulic fracturing and the flowback mechanism are crucial for optimizing productivity. This paper focuses on the inversion of post-fracturing fracture volume parameters and dynamic analysis of the flowback in deep coalbed methane wells, with 89 vertical wells in the eastern margin of the Ordos Basin as the research objects, conducting systematic studies. Firstly, through the analysis of the double-logarithmic curve of normalized pressure and material balance time, the quantitative inversion of the volume of propped fractures and unpropped secondary fractures was realized. Using Pearson correlation coefficients to screen characteristic parameters, four machine learning models (Ridge Regression, Decision Tree, Random Forest, and AdaBoost) were constructed for fracture volume inversion prediction. The results show that the Random Forest model performed the best, with a test set R² of 0.86 and good generalization performance, so it was selected as the final prediction model. With the help of the SHAP model to analyze the influence of each characteristic parameter, it was found that the total fluid volume into the well, proppant intensity, minimum horizontal in situ stress, and elastic modulus were the main driving factors, all of which had threshold effects and exerted non-linear influences on fracture volume. The interaction of multiple parameters was explored by the Partial Dependence Plot (PDP) method, revealing the synergistic mechanism of geological and engineering parameters. For example, a high elastic modulus can enhance the promoting effect of fluid volume into the well and proppant intensity. There is a critical threshold of 2600 m³ in the interaction between the total fluid volume into the well and the minimum horizontal in situ stress. These findings provide a theoretical basis and technical support for optimizing fracturing operation parameters and efficient development of deep coalbed methane. Full article

The Variscan and Mesozoic basement are covered by Neogene and Quaternary sediments belonging to the Guadalquivir foreland Basin (southern Spain). This study explores the subsurface of the northern margin of its westernmost sector using the HVSR method, recording seismic noise at 334 stations between the mouths of the Guadiana and the Guadalquivir rivers, near Doñana National Park. Fundamental frequency and basement measurements enabled the estimation of an empirical formula for basement depth: h = 80.16·f₀^−1.48. Five distinct HVSR responses were obtained: (a) low-frequency peaks, indicating deep substratum; (b) high-frequency peaks, shallow bedrock; (c) broad peaks, potential critical zones (3D-2D effects, suggesting faults); (d) double peaks (marshlands); and (e) no peaks, near-outcropping bedrock. The soil fundamental frequencies range from 0.23 to 18 Hz, with bedrock depth ranges from 1 to 5 m in the northwest to over 600 m in the southeast. Borehole data correlate strongly with HVSR-derived results, with typical discrepancies of only a few tens of meters, likely due to the presence of non-geological basement acting as a mechanical basement. Although the possibility of ancient fluvial terraces of the Guadalquivir River contributing to abrupt slope changes is considered, H/V spectra with broad peaks suggest tectonic origins. This study presents the first regional three-dimensional model of the basin basement over an area exceeding 2300 km², revealing a horst-and-graben system formed by foreland deformation linked to the westward advance of the Rif-Betic orogenic front. Full article

In Italy, the debate on migrants often focuses on issues such as social integration, economic conditions, and access to services. However, a little-investigated aspect concerns the double stigmatization of LGBTQ+ migrants, a reality made invisible by both the lack of research and the strict anti-LGBTQ+ laws present in many countries of origin. This study aimed to compare homonegativity levels between first- and second-generation migrants. A quantitative approach was used, with 127 participants (age 18–55, M = 30.63, SD = 11.58) completing an anonymous online questionnaire in three different languages. The instrument included a sociodemographic form and the Italian Scale for Measuring Homonegativity. A multivariate General Linear Model (GLM) analysis revealed significant effects of generation (p < 0.001, η² = 0.688) and gender (p < 0.01, η² = 0.144), with second-generation youth and women reporting lower levels of homonegativity. Religious affiliation had a minimal impact, influencing only the perception of deviance towards gay men (p < 0.05). Interactions between factors were generally non-significant, except for gender and religion. These findings underline the importance of generational and gender differences in the formation of homonegativity and highlight the need for further research to explore the cultural and social dynamics influencing these attitudes. In addition, there is a need to further explore how experiences of discrimination influence the well-being of LGBTQ+ migrants and what resilience strategies are adopted to address the challenges of homonegativity and marginalization. Full article

With the progress of green transformation, government subsidies have become an important incentive for enterprises to invest in green technologies. However, their effectiveness differs markedly under alternative decision-making structures. This study develops a two-tier green supply chain game model comprising manufacturers and e-commerce platform self-operators. Six game structures are examined, covering both scenarios without subsidies and those in which manufacturers receive subsidies. The analysis focuses on product greenness, service levels, retail prices, and the profits of supply chain members. The results show that government subsidies substantially enhance manufacturers’ green investments and motivate platform self-operators to provide higher levels of green services, thereby improving market performance and overall supply chain profitability. Among the different structures, centralized decision-making demonstrates the strongest coordination effect and maximizes the subsidy impact. In contrast, within decentralized structures, subsidies help alleviate double marginalization, but their effectiveness is constrained by the distribution of power. These findings highlight the heterogeneous impacts of subsidies on green supply chain performance, offering theoretical support for targeted government policy design and practical guidance for enterprises to optimize green collaborative strategies. Full article

Objectives: This randomized, double-blind, active-controlled non-inferiority phase 4 clinical trial was conducted to evaluate the immunogenicity and safety of a 23-valent pneumococcal polysaccharide vaccine (PPSV23) compared to an active comparator vaccine. Methods: Pneumococcal vaccine-naïve participants aged ≥2 years were randomly assigned in a 2:1 ratio to receive a single dose of either the investigational vaccine (n = 1199) or the comparator vaccine (n = 600). Immunogenicity was evaluated at baseline and 30 days post-vaccination by measuring serotype-specific IgG antibodies against all 23 pneumococcal serotypes using enzyme-linked immunosorbent assay. The primary outcome was seroconversion, defined as a ≥two-fold increase in serotype-specific IgG antibody titers at day 30 compared to baseline. Results: At one month post-vaccination, seroconversion rates for each of the 23 serotypes ranged from 59.22% to 95.67% in the treatment group, compared to 59.66% to 94.07% in the control group. Non-inferiority was demonstrated for all serotypes, with the lower bounds of the 95% confidence intervals (95%CI) for rate differences exceeding the predefined −10% margin. Moreover, superiority was observed for 12 serotypes (6B, 23F, 1, 2, 4, 8, 9N, 9V, 11A, 15B, 17F and 18C), as the lower bounds of their 95%CI for rate differences were above 0. Adverse reactions were reported in 236 (19.68%) participants of the investigational group and 118 (19.67%) of the control group within 30 days post-vaccination, with no significant differences between groups. Conclusions: The PPSV23 vaccine administered among individual aged ≥2 years was safe, well tolerated and immunogenic, eliciting an immune response either comparable to or higher than control vaccine. These findings support its use as a safe and effective option for pneumococcal immunization. Full article

Background: Gingival recession is a common condition involving apical displacement of the gingival margin, leading to root surface exposure and associated complications such as dentin hypersensitivity and root caries. Among the most effective treatment options are the tunneling technique (TUN) and the coronally advanced flap (CAF), both combined with connective tissue grafts (CTGs). This study aimed to evaluate and compare the clinical outcomes of TUN + CTG and CAF + CTG in terms of root coverage and keratinized tissue width (KTW) over a 6–12-month follow-up. Methods: A randomized, double-blind clinical trial was conducted following CONSORT guidelines (ClinicalTrials.gov ID: NCT06228534). Participants were randomly assigned to receive either TUN + CTG or CAF + CTG. Clinical parameters, including gingival recession depth (REC) and KTW, were assessed at baseline as well as 6 months and 12 months postoperatively using a calibrated periodontal probe. Statistical analysis was performed using descriptive statistics and linear mixed models to compare outcomes over time, with a significance level set at 5%. Results: Both techniques demonstrated significant clinical improvements. At 6 months, mean root coverage was 100% in CAF + CTG cases and 97% in TUN + CTG cases, while complete root coverage (REC = 0) was observed in 100% and 89% of cases, respectively. At 12 months, root coverage remained stable, at 99% in the CAF + CTG group and 97% in the TUN + CTG group. KTW increased in both groups, with higher values observed in the CAF + CTG group (3.53 mm vs. 3.11 mm in TUN + CTG at 12 months). No significant postoperative complications were reported. Conclusions: Both TUN + CTG and CAF + CTG are safe and effective techniques for treating RT1 and RT2 gingival recession, offering high percentages of root coverage and increased KTW. While CAF + CTG achieved slightly superior coverage and tissue gain, the TUN was associated with better aesthetic outcomes and faster recovery, making it a valuable alternative in clinical practice. Full article

Lithological identification of outcrops in complex geological settings plays a crucial role in hydrocarbon exploration and geological modeling. To address the limitations of traditional field surveys, such as low efficiency and high risk, we proposed an intelligent lithology recognition method, SG-RFGeo, for terrestrial laser scanning (TLS) outcrop point clouds, which integrates spectral and geometric features. The workflow involves several key steps. First, lithological recognition units are created through regular grid segmentation. From these units, spectral reflectance statistics (e.g., mean, standard deviation, kurtosis, and other related metrics), and geometric morphological features (e.g., surface variation rate, curvature, planarity, among others) are extracted. Next, a double-layer random forest model is employed for lithology identification. In the shallow layer, the Gini index is used to select relevant features for a coarse classification of vegetation, conglomerate, and mud–sandstone. The deep-layer module applies an optimized feature set to further classify thinly interbedded sandstone and mudstone. Geological prior knowledge, such as stratigraphic attitudes, is incorporated to spatially constrain and post-process the classification results, enhancing their geological plausibility. The method was tested on a TLS dataset from the Yueyawan outcrop of the Qingshuihe Formation, located on the southern margin of the Junggar Basin in China. Results demonstrate that the integration of spectral and geometric features significantly improves classification performance, with the Macro F1-score increasing from 0.65 (with single-feature input) to 0.82. Further, post-processing with stratigraphic constraints boosts the overall classification accuracy to 93%, outperforming SVM (59.2%), XGBoost (67.8%), and PointNet (75.3%). These findings demonstrate that integrating multi-source features and geological prior constraints effectively addresses the challenges of lithological identification in complex outcrops, providing a novel approach for high-precision geological modeling and exploration. Full article

As environmental issues become increasingly prominent, the sustainable practices of enterprises, especially measures at the product level, have garnered widespread attention from scholars. Although numerous studies have explored suppliers’ sales strategies for green products, they often overlook the scenario where suppliers simultaneously sell both green and non-green products.This study focuses on the sales mode selection strategies of suppliers when providing green and non-green products through e-commerce platforms. Utilizing a game model, we analyze the equilibrium strategies between suppliers and e-commerce platforms, and conduct sensitivity analyses to evaluate the impact of key parameters on decision-making. The results reveal that there are significant differences in the strategic preferences of suppliers and e-commerce platforms. However, when commission rates are moderate and green products incur high production costs, these preferences tend to align, leading to Pareto optimal outcomes. Additionally, our findings demonstrate that adopting differentiated sales modes for the two product types can effectively mitigate the problem of double marginalization, thereby enhancing the efficiencyof supply chains. These insights provide valuable guidance for e-commerce platform managers and suppliers in making decisions on sales models for managing multiple types of products. Full article

This paper investigates the strategic interaction between an online retailer (e.g., Amazon) and a third-party retailer (3PR) under sequential and simultaneous quantity competition models. The platform and 3PR simultaneously compete and cooperate with each other. By game-theoretic analysis, we confirm that the degree of competition between the online retailer and the 3PR in the sequential quantity game is lower than that in the simultaneous quantity game. More importantly, when the two retailers’ products are sold on the platform, their profits are both much higher in the sequential quantity game than in the simultaneous quantity game, leading to a win–win situation. Meanwhile, the coexistence of the two retailers’ products on the platform is able to mitigate the double marginal effect between the online retailer and the 3PR and to increase consumer surplus and social welfare. Our results provide operational insights for platform governance and 3PR participation strategies. Full article

Background: The prevalence of diabetes increases with age, and food bioactive compounds have shown potential in mitigating its development. This study aimed to evaluate the efficacy of curcumin in preventing type 2 diabetes mellitus (T2DM) in older adults with prediabetes. We hypothesized that curcumin, due to its insulin-sensitizing effects, would help maintain glucose homeostasis, metabolic health, and gut health. Methods: This randomized, double-blind, placebo-controlled trial included 28 older adults (aged 60 years or older) with prediabetes or overweight/obesity. Participants were randomly assigned to receive either curcumin (80 mg) or placebo capsules for 12 weeks. The primary outcome measures were glucose homeostasis markers, including hemoglobin A1c (HbA1c), blood glucose, and insulin levels. Secondary outcomes included body composition, body mass index (BMI), body weight, lipid profiles, and gut microbiome composition. Data normality was assessed using the Shapiro–Wilk test, and two-way repeated-measures ANOVA with multiple comparisons was used to find differences between groups and over time. Results: A total of 23 participants (age = 66.52 ± 5.76 years; 14 in the curcumin group and 9 in the placebo group) completed the 12-week intervention. HbA1c levels significantly decreased in the curcumin group, whereas levels remained stable in the placebo group. While the curcumin group observed an increase in AST levels, the ALT level was reduced in the placebo group. Both the curcumin and placebo groups showed a reduced ALT/AST ratio by the end of the intervention. Body mass index, lipid profiles, and body composition showed no significant changes over the study period. Gut microbiome analysis revealed no significant changes in alpha diversity or beta diversity of microbiome; however, there was marginal enrichment of beneficial bacteria such as Bacteroidota (phylum), Bacteroidaceae (family), Agathobacter, Bacteroides, and Roseburia (genera) in the curcumin-supplemented group over time. Conclusions: Curcumin supplementation improved or favorably maintained glucose homeostasis and showed modest improvements in beneficial gut microbiota in older adults with prediabetes, potentially reducing the risk of developing diabetes. Long-term studies with larger sample sizes are needed to confirm these findings and determine the clinical relevance of curcumin supplementation for prediabetes prevention. Full article

Traditional price prediction of construction material concrete often adopts macroeconomic indicators as independent variables. However, since there is often a closer relationship between the raw materials of construction concrete and the production of construction materials, the price prediction of construction concrete based on raw material prices can more directly ensure the prediction accuracy. Therefore, this study proposes a Double-Branch Physics-Informed Neural Network (DB-PINN) model based on both macroeconomic indicators and raw material price factors for the construction concrete price prediction. In particular, this model utilizes an Artificial Neural Network (ANN) as the baseline algorithm and incorporates physical constraints, such as a Multiple Linear Regression (MLR) model and a Vector Error Correction Model (VECM) to modify the loss function. To improve the prediction accuracy of the DB-PINN model, a feature analysis of the effect of the raw material price factors on the construction concrete price is conducted. Results showed that the proposed DB-PINN model has high accuracy in concrete price prediction. Further, to explore the specific ways in which macroeconomic indicators affect the concrete price prediction, a Marginal Effect Analysis (MEA) is conducted. Moreover, a comparative analysis using a traditional ANN model is conducted to verify the efficiency of the DB-PINN model, and a parameter sensitivity analysis is performed to reveal the impact of each raw material price factor and macroeconomic indicator on the construction concrete price. This study incorporates the introduction of raw material prices as input parameters for construction concrete price prediction, which facilitates the development of urban construction concrete price management in the pre-project phase. Full article

Background/Objectives: This Phase 3, randomised, double-blind, multicentre trial evaluated the efficacy and safety of a novel hyaluronic acid hydrogel cross-linked with hexamethylenediamine (HMDA-HA) compared to a conventional 1,4-butanediol diglycidyl ether cross-linked HA (BDDE-HA) in patients with mild-to-moderate knee osteoarthritis (OA). Methods: A total of 223 adults (mean age 63.5 years; 167 women) with Kellgren–Lawrence (KL) grade I–III knee OA were randomised 1:1 to receive two intra-articular injections of HMDA-HA or BDDE-HA at baseline and at 24 weeks. The primary endpoint was changes from baseline in weight-bearing pain (WBP) on a 100 mm visual analogue scale (VAS) at Week 12, assessed in the per-protocol population. A non-inferiority margin of 10 mm was predefined. Secondary outcomes included global assessments, Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index scores, responder rates, and rescue medication use [ClinicalTrials.gov: NCT06307847]. Results: At Week 12, least squares mean change (standard error [SE]) in WBP was −23.72 (1.88) mm in the HMDA-HA group (n = 83) and −25.99 (1.76) mm in the BDDE-HA group (n = 95), yielding a difference of 2.26 mm (95% confidence interval [CI]: −2.83 to 7.34; p = 0.3825), thus demonstrating the non-inferiority of HMDA-HA to BDDE-HA. Secondary outcomes were comparable between groups. A total of 136 adverse events were reported: 44 (41.1%) in the HMDA-HA group and 32 (28.1%) in the BDDE-HA group, with no treatment-related adverse drug reactions. Conclusions: A single-injection intra-articular regimen of HMDA-HA was effective and safe for the treatment of adult patients with mild-to-moderate knee OA. Full article

Accurately estimating a sequence of latent variables in state observation models remains a challenging problem, particularly when maintaining coherence among consecutive estimates. While forward filtering and smoothing methods provide coherent marginal distributions, they often fail to maintain coherence in marginal MAP estimates. Existing methods efficiently handle discrete-state or Gaussian models. However, general models remain challenging. Recently, a recursive Bayesian decoder has been discussed, which effectively infers coherent state estimates in a wide range of models, including Gaussian and Gaussian mixture models. In this work, we analyze the theoretical properties and implications of this method, drawing connections to classical inference frameworks. The versatile applicability of mixture models and the prevailing advantage of the recursive Bayesian decoding method are demonstrated using the double-slit experiment. Rather than inferring the state of a quantum particle itself, we utilize interference patterns from the slit experiments to decode the movement of a non-stationary particle detector. Our findings indicate that, by appropriate modeling and inference, the fundamental uncertainty associated with quantum objects can be leveraged to decrease the induced uncertainty of states associated with classical objects. We thoroughly discuss the interpretability of the simulation results from multiple perspectives. Full article

Background/Objectives: Anxiety and stress are interrelated and connected to reduced health-related quality of life. Botanicals such as Apocynum venetum L. (A. venetum) have been shown to improve health outcomes. No human studies have been conducted in a diverse large group of healthy adults in the US. The purpose of this randomized, double-blind, placebo-controlled study was to evaluate the effects of Venetron^® Rafuma (A. venetum leaf extract) on self-reported anxiety levels and overall health outcomes compared to placebo. Methods: Healthy adults (N = 476) seeking improvement in self-reported anxiety and stress were randomly assigned to receive 50 mg of A. venetum (n = 234) or placebo (n = 242) for 6 weeks. Feelings of anxiety were assessed at baseline and weekly using Patient-Reported Outcomes Measurement Information System (PROMIS™) Anxiety 8A. Perceived stress, sleep quality, and cognitive function were evaluated at baseline and weekly using validated assessments. A linear mixed-effects regression model was used to compare the change in health outcome scores between active and placebo groups. Results: A total of 370 participants completed at least one additional assessment and were included in the analysis: 179 in the active arm and 191 in the placebo arm. There was a significant difference between the groups in the rate of improvement in perceived stress and sleep disturbance. The active group was significantly more likely to experience a Minimal Clinically Important Difference (MCID) in their perceived stress and marginally significantly more likely to experience an MCID in their feelings of anxiety. Participants who reported experiencing side effects did not significantly differ between arms. Conclusions: Venetron^® may be safe and effective therapy for stress and sleep disturbance among those suffering from feelings of anxiety. Full article