Search Results (10,975)

Stainless-steel is extensively utilized in the key structural components of the main equipment in the nuclear island of pressurized water reactor nuclear power plants. The operational experience of nuclear power plants demonstrates that stress corrosion is one of the significant factors influencing the long-term safe operation of stainless steel in the high-temperature water of pressurized water reactor nuclear power plants. This study is based on the stress corrosion crack growth rate data of 316SS and 304SS stainless steel in the simulated primary water environment of pressurized water reactor nuclear power plants. Data mining and modeling were conducted using multiple machine learning algorithms, including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and Gaussian Process Regression (GPR), and the Sharpley Additive explanation (SHAP) method was employed to analyze the interpretability of the model. The results indicate that the stress corrosion crack growth rate prediction model based on XGBoost outperforms other models in all assessment indicators. Compared with empirical equations, XGBoost exhibits high flexibility and excellent data-driven learning capabilities. In the test set, 90% of the prediction errors are within the range of experimental values, with the maximum error multiple being 2.5, which significantly improves the prediction accuracy. Moreover, the distribution of SHAP values is consistent with the theoretical study of the stress corrosion behavior of stainless-steel, effectively reflecting the impact of cold working, temperature, and stress intensity factor on the stress corrosion crack growth rate, thereby proving the reliability of the model’s prediction results. The achievements of this study hold significant reference value and application prospects for the prediction of the stress corrosion behavior of stainless-steel in a high-temperature and high-pressure water environment of pressurized water reactor nuclear power plants. Full article

Background/Objectives: Pneumothorax can be a major complication of neonatal lung diseases. We aim to delineate trends and describe the main outcomes related to pneumothorax in very preterm infants (VPI). Methods: Preterm infants < 32 weeks of gestation admitted in two-level III neonatal intensive care units (1995–2019) were included. Risk factors and outcomes were assessed by logistic regression and adjusted for gestational age (GA). Results: In total, 4271 VPI with a mean GA of 28.7 ± 2.3 weeks were evaluated. Pneumothorax was diagnosed in 174 patients (4.1%, 95% Confidence Interval (CI) 3.5–4.7) with its incidence inversely proportional to GA: 9.9% in 23–25 w and 2.1% in 30–31 w (p < 0.001), but stable over the years 1995–1999 (5.2%) and 2015–2019 (4.2%) (p = 0.309). Patients with pneumothorax exhibited higher rates of severe intraventricular hemorrhage (IVH) (Odds Ratio (OR) = 2.0 (95%CI 1.3–3.1), p = 0.003), bronchopulmonary dysplasia (OR = 2.7 (95%CI 1.7–4.4), p < 0.001), and death (OR = 8.5 (95%CI 6.2–11.6), p < 0.001). Independent risk factors for pneumothorax were GA, prolonged premature rupture of membranes, and intubation in the delivery room. The composite outcome of death or severe IVH was higher in patients with pneumothorax with an adjusted OR = 6.7 (95%CI 4.7–9.6), p < 0.001. Although VPI mortality has significantly decreased over the years (20.3% 1995–1999 and 11.7% 2015–2019, p < 0.001), we found no significant difference in pneumothorax-related deaths. Conclusion: Pneumothorax remains a serious threat to VPI, leading to a higher incidence of morbidity, and mortality attributable to this complication has not decreased. Preventive strategies and early recognition are essential for improving disability-free survival in VPI. Full article

Background/Objectives: The present study evaluates predictive implications of the pretherapeutic Fibrinogen–Albumin-Ratio Index (FARI) in high-grade serous ovarian cancer (HGSOC) patients undergoing primary cytoreductive surgery. Methods: This retrospective study included 161 patients with HGSOC International Federation of Gynecology and Obstetrics (FIGO) stage ≥ IIb, who underwent primary cytoreductive surgery followed by platinum-based chemotherapy. Associations between the FARI and complete tumor resection status were described by receiver operating characteristics, and binary logistic regression models were fitted. Results: Higher preoperative FARI values correlated with higher ascites volumes (r = 0.371, p < 0.001), and higher CA125 levels (r = 0.271, p = 0.001). A high FARI cut at its median (≥11.06) was associated with lower rates of complete tumor resection (OR 3.13, 95% CI [1.63–6.05], p = 0.001), and retrained its predictive value in a multivariable model independent of ascites volumes, CA125 levels, FIGO stage, and Charlson Comorbidity Index (CCI). Conclusions: The FARI appears to act as a surrogate for higher intra-abdominal tumor load. After clinical validation, FARI could serve as a readily available serologic biomarker to complement preoperative patient assessment, helping to identify patients who are likely to achieve complete tumor resection during primary cytoreductive surgery. Full article

Introduction: While tubal occlusion is a prevalent cause of infertility, accounting for 11–35% of infertility cases among women, there remains a limited understanding of the factors influencing clinical pregnancy following in vitro fertilization (IVF). Methods: In our retrospective, cross-sectional cohort study conducted at a single tertiary center, medical records of women aged 19 to 43 years were analyzed. Logistic regression models were employed to identify the prognostic factors associated with clinical pregnancy after IVF in patients with tubal factor infertility, excluding cases with hydrosalpinx. Results: Data from 219 women diagnosed with tubal occlusion were compared to 1140 cases with non-tubal indication, covering a total of 1359 IVF cycles. A lower maternal age (adjusted odds ratio [AOR]: 0.89, p = 0.001) and a higher embryo quality (AOR: 1.26, p = 0.01) emerged as important factors in clinical pregnancy in the tubal infertility group. Moreover, a lower maternal (AOR:0.91, p < 0.01) and paternal age (p = 0.001), and favorable semen quality (AOR: 1.32, p = 0.03) were critical determinants in the non-tubal infertility group. BMI was generally higher in tubal infertility patients (p = 0.01). Furthermore, FSH level (AOR: 0.93, p = 0.004), AMH level (p < 0.04), number of embryos transferred (AOR: 2.04, p < 0.001), and embryo quality (AOR: 1.26, p < 0.001) came into prominence only in the non-tubal infertility group. The clinical pregnancy rate (34.2%) of women with tubal occlusion did not differ significantly from those in other forms of infertility undergoing IVF (35.4%). Conclusions: Although tubal infertility is typically anticipated to yield the highest clinical pregnancy rates following IVF, it is crucial to acknowledge that both maternal and paternal characteristics can also significantly impact the outcomes. Full article

Objective: A late mid-trimester fetal organ scan (lMTS) is recommended between 18 and 22 weeks of pregnancy. Evidence has been accumulating on the effectiveness of first-trimester anatomy scans. Early mid-trimester fetal scans (eMTSs; 14–17 weeks) may have the advantage of visualization of most organs, hence allowing earlier genetic assessment and decision making. Our aim is to examine the effectiveness of eMTSs in identifying fetal anomalies compared to lMTSs. Methods: A retrospective study was conducted based on data from the multidisciplinary prenatal diagnosis clinic in a tertiary center. During the study period (2011–2021), an out-of-pocket eMTS in a community setting was offered routinely to the general population. Women who had previously undergone an eMTS and were later assessed due to a fetal anomaly in our clinic were included in the study. The cohort was divided into two groups according to whether the anomaly had been detected during the eMTS. We then compared the groups for factors that may be associated with anomaly detection in eMTSs. We used t-tests and chi-square tests, for quantitative and qualitative variables, respectively, to determine variables related to eMTS anomaly detection, and logistic regression for multivariate analysis. Results: Of 1525 women assessed in our multidisciplinary clinic, 340 were included in the study. The anomaly detection rate of the eMTS compared to the lMTS was 59.1% The eMTS detection rates for specific organ systems were as follows: skeletal, 57%; cardiac, 52%; congenital anomalies of the kidneys and urinary tract (CAKUT), 44%; central nervous system, 32.4%; chest, 33%; and abdominal, 28%. In multivariate analysis, abnormal first-trimester screening (aOR 3.2; 95%CI 1.26–8.08) and multiple anomalies (aOR 1.86; 95%CI 1.02–3.37) were found to be associated with eMTS anomaly detection. Conclusions: The eMTS detection rate was nearly 60% and was most accurate in detecting skeletal, cardiac, and CAKUT anomalies. Since the eMTS was community-based, this rate likely reflects a “real-world” scenario. Our findings support consideration of performing an eMTS or first-trimester scan routinely for earlier diagnosis and decision making, as an adjunctive to lMTSs. Future studies will examine the cost-effectiveness of early scans. Full article

Additive Manufacturing (AM) is a pivotal technology for transforming complex geometries with minimal tooling requirements. Among the several AM techniques, Wire Arc Additive Manufacturing (WAAM) is notable for its ability to produce large metal components, which makes it particularly appealing in the aerospace sector. However, precise control of the bead geometry, specifically bead width and height, is essential for maintaining the structural integrity of WAAM-manufactured parts. This paper introduces a methodology using a Deep Neural Network (DNN) model for forecasting the bead geometry in the WAAM process, focusing on gas metal arc welding cold metal transfer (GMAW-CMT) WAAM. This study addresses the challenges of bead geometry prediction by developing a robust predictive framework. Key process parameters, such as the wire travel speed, wire feed rate, and bead dimensions of the previous layer, were monitored using a Coordinate Measuring Machine (CMM) to ensure precision. The collected data were used to train and validate various regression models, including linear regression, ridge regression, regression, polynomial regression (Quadratic and Cubic), Random Forest, and a custom-designed DNN. Among these, the Random Forest and DNN models were particularly effective, with the DNN showing significant accuracy owing to its ability to learn complex nonlinear relationships inherent in the WAAM process. The DNN model architecture consists of multiple hidden layers with varying neuron counts, trained using backpropagation, and optimized using the Adam optimizer. The model achieved mean absolute percentage error (MAPE) values of 0.014% for the width and 0.012% for the height, and root mean squared error (RMSE) values of 0.122 for the width and 0.153 for the height. These results highlight the superior capability of the DNN model in predicting bead geometry compared to other regression models, including the Random Forest and traditional regression techniques. These findings emphasize the potential of deep learning techniques to enhance the accuracy and efficiency of WAAM processes. Full article

The purpose of this study was to identify the correlates of depressive symptoms and the prevalence of depression, distress, and demoralization among patients with cancer in Taiwan in relation to their sociodemographics. A cross-sectional study design with convenience sampling was used to recruit 191 consecutive patients with cancer from the Cancer Center of a teaching hospital in northern Taiwan. Multiple linear regression was applied to analyze the determinants of depressive symptoms. The prevalence rates of depression (including suspected cases), distress, and demoralization were 17.8%, 36.1%, and 32.5%, respectively. The regression model explained 42.2% of the total variance, with significant predictors including marital status, life dependence, comorbidity, demoralization, and distress. The results demonstrated that higher levels of distress and demoralization were associated with more depressive symptoms. Demoralization and distress played vital roles in moderating depressive symptoms among patients with cancer. Nursing interventions should integrate appropriate mental health services, such as alleviating distress and demoralization, to prevent the occurrence of depression in patients with cancer. Full article

Hurricane incidents have become increasingly frequent along the coastal United States and have had a negative impact on the mangrove forests and their ecosystem services across the southeastern region. Mangroves play a key role in providing coastal protection during hurricanes by attenuating storm surges and reducing erosion. However, their resilience is being increasingly compromised due to climate change through sea level rises and the greater intensity of storms. This article examines the role of remote sensing tools in studying the impacts of hurricanes on mangrove forests in the coastal United States. Our results show that various remote sensing tools including satellite imagery, Light detection and ranging (LiDAR) and unmanned aerial vehicles (UAVs) have been used to detect mangrove damage, monitor their recovery and analyze their 3D structural changes. Landsat 8 OLI (14%) has been particularly useful in long-term assessments, followed by Landsat 5 TM (9%) and NASA G-LiHT LiDAR (8%). Random forest (24%) and linear regression (24%) models were the most common modeling techniques, with the former being the most frequently used method for classifying satellite images. Some studies have shown significant mangrove canopy loss after major hurricanes, and damage was seen to vary spatially based on factors such as proximity to oceans, elevation and canopy structure, with taller mangroves typically experiencing greater damage. Recovery rates after hurricane-induced damage also vary, as some areas were seen to show rapid regrowth within months while others remained impacted after many years. The current challenges include capturing fine-scale changes owing to the dearth of remote sensing data with high temporal and spatial resolution. This review provides insights into the current remote sensing applications used in hurricane-prone mangrove habitats and is intended to guide future research directions, inform coastal management strategies and support conservation efforts. Full article

The beginning of the COVID-19 pandemic was marked by a sharp decline in syphilis infections in many countries worldwide, including Greece. However, a resurgence of positive cases started to appear in the second half of 2020. The aim of this study was to explore the impact of the pandemic on the incidence of new syphilis infections and reinfections and analyze the sociodemographic characteristics associated with recurrent episodes. We analyzed medical records from a 14-month period after the beginning of the pandemic and compared them with the respective period before the start of the pandemic. Our participants consisted mainly of men, with a median age of 43 years, homosexual orientation, and higher education. During COVID-19, more HIV patients presented for syphilis testing (38.0% vs. 34.6%, p = 0.025). Overall, we observed almost a two-fold increase in positive syphilis cases during COVID-19 (21.1% vs. 12.4%, p < 0.001), with new infections rising from 8.4% to 13.2% and reinfections from 4.0% to 7.9%. Multivariable logistic regression analysis revealed that the COVID-19 pandemic, among different parameters (such as age, gender, sexual orientation, HIV status, and educational level), was the only factor associated with higher positive syphilis rates (OR 1.47, 95% CI: 1.07–2.01, p = 0.003). Our results highlight the need to ensure enhanced prevention and undisrupted healthcare services, with a focus on future pandemics. Full article

Background/Objectives: Patients with Non-Alcoholic Fatty Liver Disease (NAFLD) are reported to have an increased risk of developing severe infections, leading to hospitalizations with sepsis. However, data regarding the impact of comorbid NAFLD on in-hospital outcomes of patients with sepsis is scarce. Methods: This nationwide retrospective observational study using discharge data from the National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), and Agency for Healthcare Research and Quality included 21,057,911 adult patients who were admitted to hospitals in the United States between 2000 and 2019 with a primary discharge diagnosis of sepsis. These patients were categorized according to the presence or absence of comorbid NAFLD. The twenty-year trend of nationwide NAFLD prevalence among sepsis inpatients was elucidated. Multivariable logistic regression analysis was used to analyze NAFLD’s impact on sepsis outcomes. Results: In the twenty-year study period, the prevalence of NALFD among sepsis inpatients trended up from 1.2% in 2000 to 4.2% in 2019. Similar trends were observed in regional analysis. While overall sepsis mortality decreased, comorbid NAFLD in sepsis patients was consistently associated with a higher adjusted in-hospital all-cause mortality rate (adjusted odds ratio (OR), 1.19; 95% confidence interval (CI), 1.07–1.32), higher odds of developing septic shock, and higher likelihood of development of multi–organ dysfunction. Conclusions: Comorbid NAFLD in the stage of NASH or cirrhosis is associated with higher in-hospital all-cause mortality and worse clinical outcomes in sepsis inpatients. Addressing this rising epidemic will be of paramount importance to improve sepsis in-hospital outcomes. Full article

To address the challenge of low detection accuracy and slow detection speed in unmanned aerial vehicle (UAV) aerial images target detection tasks, caused by factors such as complex ground environments, varying UAV flight altitudes and angles, and changes in lighting conditions, this study proposes an end-to-end adaptive multi-scale feature extraction and fusion detection network, named AMFEF-DETR. Specifically, to extract target features from complex backgrounds more accurately, we propose an adaptive backbone network, FADC-ResNet, which dynamically adjusts dilation rates and performs adaptive frequency awareness. This enables the convolutional kernels to effectively adapt to varying scales of ground targets, capturing more details while expanding the receptive field. We also propose a HiLo attention-based intra-scale feature interaction (HLIFI) module to handle high-level features from the backbone. This module uses dual-pathway encoding of high and low frequencies to enhance the focus on the details of dense small targets while reducing noise interference. Additionally, the bidirectional adaptive feature pyramid network (BAFPN) is proposed for cross-scale feature fusion, integrating semantic information and enhancing adaptability. The Inner-Shape-IoU loss function, designed to focus on bounding box shapes and incorporate auxiliary boxes, is introduced to accelerate convergence and improve regression accuracy. When evaluated on the VisDrone dataset, the AMFEF-DETR demonstrated improvements of 4.02% and 16.71% in mAP50 and FPS, respectively, compared to the RT-DETR. Additionally, the AMFEF-DETR model exhibited strong robustness, achieving mAP50 values 2.68% and 3.75% higher than the RT-DETR and YOLOv10, respectively, on the HIT-UAV dataset. Full article

Background/Objectives: Acute exacerbation (AE) of interstitial lung disease (ILD) is a major challenge. This study aimed to retrospectively investigate occurrences of AEs in patients with ILDs, including idiopathic pulmonary fibrosis (IPF), non-IPF (iNSIP: idiopathic nonspecific interstitial pneumonia), and connective tissue disease (CTD)-associated ILDs (CTD-ILDs), at a single tertiary center before and after the coronavirus disease 2019 (COVID-19) pandemic. The study aimed to clarify the seasonal and regional trends of AEs of ILDs, assess the roles of viral and bacterial infections, and identify key prognostic factors for patient outcomes. Methods: We conducted a retrospective review of hospitalized adult patients with AEs of ILDs from January 2019 to February 2024. Results: A total of 93 patients were enrolled: IPF (n = 42), iNSIP (n = 37), and CTD-ILDs (n = 14). The median age was 80 years (interquartile range: 74.0–86.0 years), with males comprising 64.5% (n = 60). AEs of ILDs predominantly occurred in winter and were particularly notable after summer 2023, coinciding with the lifting of COVID-19-related travel restrictions in Japan. Patient referrals from different areas (Northern Tama, East and/or Southern Tama, and other Tokyo metropolitan areas) were evenly distributed throughout the study period. Viral infections were detected in only two patients (SARS-CoV-2), and bacterial infections included methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa. The Cox regression analysis identified serum lactate dehydrogenase levels ≥350 IU/L and tachypnea (respiratory rate ≥ 30 breaths per min) on admission as prognostic factors for mortality, with a hazard ratio [HR] of 2.783 (95% confidence interval [CI]: 1.480–5.235, p = 0.001) and an HR of 3.332 (95% CI: 1.710–6.492, p < 0.001), respectively. Conclusions: AEs of ILDs predominantly occur in winter, and viral and bacterial infections are infrequently detected. Elevated serum LDH levels and tachypnea are crucial prognostic markers for mortality. This study highlights the seasonal trend in the AE of ILD and emphasizes the importance of specific prognostic indicators in clinical practice. Full article

Objectives: To evaluate the safety and efficacy of catheter-directed thrombolysis (CDT) with the recombinant tissue plasminogen activator (rt-PA) in all patients with symptomatic peripheral artery disease in real world practice. Methods: Consecutive patients treated with CDT between January 2013 and December 2020 were included in this retrospective analysis. The primary endpoint was the rate of serious adverse events (SAEs) until discharge. Secondary endpoints included interventional success, predictors for SAEs, bleeding and reperfusion edema/compartment syndrome, limb salvage, and clinical outcomes including target lesion revascularization rate (TLR). Results: Overall, 1238 patients were treated with CDT. SAEs occurred in 511 (41.3%) of the patients, 314 (25.4%) being bleeding complications. There were 95 cases of reperfusion edema/compartment syndrome. Forty-two patients underwent amputation and 33 patients (2.7%) died. CDT was successful in 1177 cases (95.1%). Multivariate logistic regression analysis identified age, abciximab and alprostadil usage, and lysis duration as predictors for SAEs and the use of abciximab as a predictor of reperfusion edema/compartment syndrome. Predictors for bleeding were age, alprostadil usage, and lysis duration. At 12 and 24 months, the limb salvage rate was 91.6% and 88.8%, and TLR rate was 46% and 57.2%, respectively. Conclusions: CDT is an effective endovascular method for the treatment of thrombotic peripheral artery occlusions but is associated with a high complication rate. For SAEs in general and bleeding specifically, increasing age, alprostadil use, and lysis duration were independent risk factors. Full article

Background: This study investigates patients’ use of eHealth services, their awareness of the availability of these services, and their intention to use them in primary care. It also examines patient characteristics and factors that influence the use of these services. Methods: A cross-sectional design using questionnaires was conducted. Based on the unified theory of acceptance and use of technology (UTAUT), the participants rated the two most common services. Descriptive analyses and linear correlation analyses were performed. A simple linear regression was conducted to identify factors influencing the participants’ intention to use eHealth services. Results: In total, 1203 participants with an average age of 43.7 years were surveyed. The participants’ usage rates varied, with the lowest at 2.4%, for measuring vital signs, and the highest at 47.4%, for booking appointments. The intentions to use the services ranged from 22.5%, for video consultations, to 46.6%, for prescription refill requests. Approximately 20% of the respondents were unaware of each service’s availability. Positive associations were found between all the constructs and the intention to use online services, with a younger age being the most significant factor. Conclusions: The use of and intention to use eHealth services varied greatly. The participants were often unaware of the availability of these services. Promoting the availability and benefits of eHealth services could enhance patient engagement in primary care settings. Full article

Background: The survival benefit of surgical revascularization in multivessel coronary artery disease is well understood, though it can be modified by left ventricular dysfunction. Chronic exposure to air pollutants has gained more attention recently as a possible non-traditional morbidity and mortality cardiovascular risk factor. This study identified possible 5-year mortality risk factors related to postoperative left ventricular performance, including air pollutants. Patients: There were 283 patients (244 (86%) males) with a median age of 65 (60–70) years enrolled in the retrospective analysis. All patients were referred for off-pump coronary artery revascularization due to chronic coronary syndrome that presented as a multivessel coronary artery disease. They were divided into three groups depending on the postoperative course of left ventricular fraction (LVEF 50% or more (169 patients), LVEF between 41 and 49% (61 patients), and LVEF 40% or less (53 patients)). Results: The overall survival rate was 84% (237 patients) in a median follow-up time of 5.3 (4.8–6.1) years. The median (Q1–Q3) chronic air pollution exposures for the analyzed group were 19.3 (16.9–22.4) μg/m³ for fine particles such as PM_2.5, 25.8 (22.5–29.4) μg/m³ for coarse particles such as PM₁₀, and 12.2 (9.7–14.9) μg/m³ for nitric dioxide (NO₂). The mortality in the first group (LVEF at least 50%) was 23 (13.6%), in the second group (LVEF 41–49%) was 9 (15%), and in the third group (LVEF 40% or less) was 14 (26%). The multivariable regression analysis for the five-year mortality risk in the first group revealed the predictive value of dyslipidemia (HR: 3.254, 95% CI: 1.008–10.511, p = 0.049). The multivariable regression analysis for five-year mortality risk in the second group revealed the predictive value of dyslipidemia (HR: 3.391, 95% CI: 1.001–11.874, p = 0.050) and PM_2.5 (HR: 1.327, 95% CI: 1.085–1.625, p = 0.006). In the third group (severely decreased LVEF), chronic PM_2.5 exposure was found to be significant (HR: 1.518, 95% CI: 1.50–2.195, p = 0.026) for 5-year mortality prediction. Conclusions: Traditional risk factors, such as dyslipidemia, are pivotal in the 5-year mortality risk following surgical revascularization. Chronic exposure to ambient air pollutants such as PM_2.5 may be an additional risk factor in patients with left ventricular dysfunction. Full article