Search Results (16,003)

Background and Objectives: Ventilator-associated pneumonia (VAP) poses a significant threat to the clinical outcomes and hospital stays of mechanically ventilated patients, particularly those recovering from cardiac arrest. Given the already elevated mortality rates in cardiac arrest cases, the addition of VAP further diminishes the chances of survival. Consequently, a paramount focus on VAP prevention becomes imperative. This review endeavors to comprehensively delve into the nuances of VAP, specifically in patients requiring mechanical ventilation in post-cardiac arrest care. The overarching objectives encompass (I) exploring the etiology, risk factors, and pathophysiology of VAP, (II) delving into available diagnostic modalities, and (III) providing insights into the management options and recent treatment guidelines. Methods: A literature search was conducted using PubMed, MEDLINE, and Google Scholar databases for articles about VAP and Cardiac arrest. We used the MeSH terms “VAP”, “Cardiac arrest”, “postcardiac arrest syndrome”, and “postcardiac arrest syndrome”. The clinical presentation, diagnostic, and management strategies of VAP were summarized, and all authors reviewed the selection and decided which studies to include. Key Content and Findings: The incidence and mortality rates of VAP exhibit significant variability, yet a recurring pattern emerges, marked by prolonged hospitalization and exacerbated clinical outcomes. This pattern is attributed to the elevated incidence of drug-resistant infections and the delayed initiation of antimicrobial treatment. This review focuses on VAP, aiming to offer valuable insights into the efficient identification and management of this fatal complication in post-cardiac arrest patients. Conclusion: The prognosis for survival after cardiac arrest is already challenging, and the outlook becomes even more daunting when complicated by VAP. The timely diagnosis of VAP and initiation of antibiotics pose considerable challenges, primarily due to the invasive nature of obtaining high-quality samples and the time required for speciation and identification of antimicrobial sensitivity. The controversy surrounding prophylactic antibiotics persists, but promising new strategies have been proposed; however, they are still awaiting well-designed clinical trials. Full article

Bauhinia s.s. belongs to the Cercidoideae subfamily, located at the base of the Leguminosae family. It displays a variety of growth habits and morphologies, and is widely utilized as both ornamental and medicinal plants globally. The objective of this research is to uncover chloroplast genomes of species from Eastern Asia and Southern Africa, thereby advancing our understanding of the diversity within this genus. This study sequenced Bauhinia purpurea, Bauhinia brachycarpa var. microphylla, Bauhinia variegata var. candida, Bauhinia galpinii, and Bauhinia monandra using the Illumina platform and conducted the construction of phylogenetic trees as well as the estimation of divergence times. Compared to Asian species, the IR regions of African species underwent a contraction of approximately 100–400 bp. The phylogenetic analysis indicated that Asian and African species clustered into two distinct clades, with high support. The divergence of Bauhinia s.s. species occurred in the late Paleocene, and the rps18 and cemA genes were under positive selection. Six hypervariable regions were screened for evolutionary studies and the super-barcode data were used for species delimitation. The results revealed certain differences between African and Asian species in their chloroplast genomes of Bauhinia species. Full article

Background/Objectives: The correlation of handgrip strength (HGS) and morphological characteristics with Big Five personality traits is well documented. However, it is unclear whether these relationships also exist in highly trained and specialized populations, such as tactical athletes, and whether there are specific differences compared to the general population. This study aimed to explore the interplay of handgrip neuromuscular, morphological, and psychological characteristics in tactical athletes and the general population of both genders. Methods: The research was conducted on a sample of 205 participants. A standardized method, procedure, and equipment (Sports Medical solutions) were used to measure the isometric neuromuscular characteristics of the handgrip. Basic morphological characteristics of body height, body mass, and body mass index were measured with a portable stadiometer and the InBody 720 device. Psychological characteristics were assessed with the Mental Toughness Index and Dark Triad Dirty Dozen questionnaires. Results: Numerous significant correlations were obtained, as well as differences between tactical athletes and the general population of both genders. The most prominent correlations were between the excitation index with Psychopathy and the Dark Triad (ρ = −0.41, −0.39) in female tactical athletes, as well as Neuroticism with body height, maximal force, and the maximum rate of force development in the male general population (ρ = 0.49, 0.43, 0.41). The obtained results also revealed gender and occupational specific patterns of researched relationships. Conclusions: Although the results of this study indicated the possibility of the existence of correlations between handgrip neuromuscular, morphological, and psychological characteristics in tactical athletes of both genders, nevertheless, at the moment, there is not enough solid evidence for that. That is why new research is needed. An analysis of muscle contractile and time parameters as neuromuscular indicators in the HGS task proved to be a possible promising method, which brought numerous new insights about the researched relationships. For practical application in the field, we propose including Mental Toughness and the Dark Triad traits in the selection process for future police officers and national security personnel based on the obtained results. Full article

Background/Objectives: DPP4 is an enzyme with multiple natural substrates and probable involvement in various mechanisms. It constitutes a drug target for the treatment of diabetes II, although, also related to other disorders. While a number of drugs with competitive inhibitory action and covalent binding capacity are available, undesired side effects exist partly attributed to drug kinetics, and research for finding novel, potent, and safer compounds continues. Despite the research, a low number of uncompetitive and non-competitive inhibitors, which could be of worth for pharmaceutical and mechanism studies, was mentioned. Methods: In the present study sixteen 3-(benzo[d]thiazol-2-yl)-2-aryl thiazolidin-4-ones were selected for evaluation, based on structural characteristics and docking analysis and were tested in vitro for DPP4 inhibitory action using H-Gly-Pro-amidomethyl coumarin substrate. Their mode of inhibition was also in vitro explored. Results: Twelve compounds exhibited IC₅₀ values at the nM range with the best showing IC₅₀ = 12 ± 0.5 nM, better than sitagliptin. Most compounds exhibited a competitive mode of inhibition. Inhibition modes of uncompetitive, non-competitive, and mixed type were also identified. Docking analysis was in accordance with the in vitro results, with a linear correlation of logIC₅₀ with a Probability of Binding Factor(PF) derived using docking analysis to a specific target box and to the whole enzyme. According to the docking results, two probable sites of binding for uncompetitive inhibitors were highlighted in the wider area of the active site and in the propeller loop. Conclusions: Potent inhibitors with IC₅₀ at the nM range and competitive, non-competitive, uncompetitive, and mixed modes of action, one better than sitagliptin, were found. Docking analysis was used to estimate probable sites and ways of binding. However, crystallographic or NMR studies are needed to elucidate the exact way of binding especially for uncompetitive and non-competitive inhibitors. Full article

Background and Objectives: The Index of Response to Stimulation (IRES) is a new index that we introduce in this study to grade the effectiveness of vagus nerve stimulation in the treatment of drug-resistant epilepsy. We assessed 76 patients at 6, 12, and 18 months after VNS evaluating improvement with the IRES in four key dimensions: seizure duration decrease, seizure intensity decrease, improvement in quality of life, and seizure frequency decrease. This scale goes from 0, meaning no improvement, to 8, meaning maximal improvement, making the scale a really good measure of clinical utility. Materials and Methods: This retrospective study followed 76 patients aged 20–65, assessing changes in their IRES scores after VNS therapy using the ASPIRE SR 106 device. Therapy settings were adjusted biweekly to optimize efficacy and patient tolerance. Results: There were improvements in the control of the seizures, measured in terms of increased IRES scores. Improvements were associated with quality-of-life enhancements for the patient and a lesser frequency and intensity of the seizures, testifying further to the predictive ability of the IRES toward successful outcomes. This fact reveals that epilepsy treatment must be individual, according to the profile of the patient. Conclusions: The study confirms the IRES to be a valid tool for the assessment of the impact of VNS on drug-resistant epilepsy and promotes it as an integral part of the evaluation of the patient for personalized therapy. The findings encourage the use of IRES among the elements that support patient selection and insist on its role in the advancement of precision medicine and optimization of treatment. Full article

Locating community facilities is a long-term, daunting task for governments, requiring ongoing budget or policy updates for gradual improvement. This study proposes a bi-objective multi-scenario dynamic model (BOMSDM) for community-facility siting, which aims to maximize service efficiency and social equity while considering variable facility numbers and inter-community competition. This study also provides a framework to demonstrate how the newly proposed model operates. This framework includes the BOMSDM itself, the data collection and processing method, and the constrained NSGA-II as the computational algorithm. Under this framework, the BOMSDM, along with three comparative frameworks derived from traditional models—including a random allocation non-incremental model, a random allocation incremental model, and an average allocation non-incremental model—was applied to a real-world scenario in Shaoxing. The results demonstrate the effectiveness and superiority of BOMSDM: it significantly outperforms the realistic solution in terms of service efficiency, fairness, and community allocation rate. Compared to alternative frameworks, BOMSDM sacrifices some objective values in scenarios without facility redundancy to ensure higher community coverage while exhibiting rapid improvement in objective values when redundancy is present, highlighting the framework’s flexibility. This framework provides government decision-makers with an effective tool for community-facility site selection. Full article

Many real-world expensive industrial and engineering multi-objective optimization problems (MOPs) are driven by historical, experimental, or simulation data. In such scenarios, due to the expensive cost and time required, we are only left with a small amount of labeled data to perform the optimization. These offline data-driven MOPs are usually solved by multi-objective evolutionary algorithms (MOEAs) with the help of surrogate models constructed from offline historical data. The key challenge in developing these data-driven MOEAs is that they have to replace multiple conflicting fitness functions by approximating these objective functions, which may produce cumulative approximation errors and misguide the search. In order to build a reliable surrogate model from a small amount of multi-output offline data and solve the DDMOPs, we have proposed an adaptive model selection method with a reliable individual-based model management-driven MOEA. The proposed algorithm dynamically selects between DNN and XGBoost by comparing their k-fold cross-validation MAE error, which can capture the true generalization ability of the surrogates on unseen data. Then, the selected surrogate is updated with a reliable individual selection strategy, where the individual who is closest, both in the decision and objective space, to the most preferred solution among labeled offline data is chosen. As a result, these two strategies guide the underlying MOEA to the Pareto optimal solutions. The empirical results of the ZDT and DTLZ benchmark test suite validate the use of the three state-of-the-art offline DDMOEAs, showing that our algorithm is able to achieve highly competitive results in terms of convergence and diversity for 2–3 objectives. Finally, our algorithm is applied to an offline data-driven multi-objective problem—transonic airfoil (RAE 2822) shape optimization— to validate its efficiency on real-world DDMOPs. Full article

Background/Objectives: The p48 MW HPC is a novel low-profile flow diverter covered by a hydrophilic polymer coating with antithrombogenic properties, which may reduce ischemic complications and enable a single antiplatelet therapy after insertion of the stent. In this single-center experience, we describe the efficacy of this device, focusing on the illustration of different therapeutic indications and the outcome in various clinical settings with regard to vessel anatomy, bleeding state, and aneurysm configuration. Methods: We retrospectively reviewed our database for all patients being treated with a p48 MW HPC flow diverter between February 2019 and July 2021. The efficacy of the treatment was evaluated according to the O’Kelly–Marotta (OKM) scale in the last digital subtraction angiography (DSA) follow-up. Information on complications and medications were collected from our medical records. In addition, to illustrate different indications and clinical settings, we present six of these cases in closer detail. Results: 18 aneurysms in 14 patients were treated with the p48 MW HPC flow diverter and in one case with an additional Derivo device. Periprocedural events occurred in 28.6% of the treated patients, which were all successfully resolved within the same session. Follow-up examination information was available for 67% of patients, of which 75% showed complete occlusion of the aneurysm and 83.3% showed a favorable occlusion result (OKM C-D). Two patients with ruptured aneurysms received a single antiplatelet therapy with ASA without thrombotic complications, at least in the short term. New braid deformation patterns were observed in 16.6% at the follow-up examination, but none with subsequent clinical significance. Conclusions: The p48 MW HPC is safe and effective in the treatment of a wide spectrum of differently configurated, ruptured, and unruptured aneurysms. Single antiplatelet therapy might be an option in selected cases. Full article

Film-based cellulose nitrate negatives are a unique class of objects that contain important information about life, historical buildings, and the natural landscapes of past years. Increased sensitivity to storage conditions makes these objects highly flammable and can lead to irretrievable loss. In this regard, timely identification of the degradation process is a necessary step towards further conservation and restoration. This work studies the possibility of detecting the degradation process based on cellulose nitrate artifact yellowing. A total of 20 normal and 20 yellowed negatives from the collection of Karl Kosse (The State Museum and Exhibition Center ROSPHOTO) were selected as objects for statistical study. The novelty of this work is in its demonstration of the possibility to divide negatives into normal and yellowed areas with different shades based on different B/R and B/G ratios of both light and dark negatives, i.e., regardless of the distribution of RGB component values for the obtained digital photo from the negative. Moreover, the obtained differentiation result was demonstrated for individual image pixels, without the need for averaging over a certain area. Full article

Background/Objectives: Early and accurate diagnosis of skin cancer improves survival rates; however, dermatologists often struggle with lesion detection due to similar pigmentation. Deep learning and transfer learning models have shown promise in diagnosing skin cancers through image processing. Integrating attention mechanisms (AMs) with deep learning has further enhanced the accuracy of medical image classification. While significant progress has been made, further research is needed to improve the detection accuracy. Previous studies have not explored the integration of attention mechanisms with the pre-trained Xception transfer learning model for binary classification of skin cancer. This study aims to investigate the impact of various attention mechanisms on the Xception model’s performance in detecting benign and malignant skin lesions. Methods: We conducted four experiments on the HAM10000 dataset. Three models integrated self-attention (SL), hard attention (HD), and soft attention (SF) mechanisms, while the fourth model used the standard Xception without attention mechanisms. Each mechanism analyzed features from the Xception model uniquely: self-attention examined the input relationships, hard-attention selected elements sparsely, and soft-attention distributed the focus probabilistically. Results: Integrating AMs into the Xception architecture effectively enhanced its performance. The accuracy of the Xception alone was 91.05%. With AMs, the accuracy increased to 94.11% using self-attention, 93.29% with soft attention, and 92.97% with hard attention. Moreover, the proposed models outperformed previous studies in terms of the recall metrics, which are crucial for medical investigations. Conclusions: These findings suggest that AMs can enhance performance in relation to complex medical imaging tasks, potentially supporting earlier diagnosis and improving treatment outcomes. Full article

In this study, we successfully captured and compared the gas−particle flow field in a real-sized industrial-scale micron air classifier and in a prototype. All simulation calculations were performed using high-performance computing (HPC) systems and 3D transient simulations with the TWC-RSM–DPM (Two-Way Coupling–Reynolds Stress Model–Discrete Phase Model) in ANSYS Fluent (version 2022 R2). The following objectives were achieved: (i) a comparison of the simulation results was made between a real-size industrial-scale micron air classifier and a prototype model (scaled-down model) to show the differences between them and highlight the necessity of a simulation study on a real-size industrial-scale model for optimization purposes; (ii) a detailed analysis of the effects of the multiple vortices inside both the main and secondary classification zones provided a deeper understanding of the classification mechanism of the real-sized industrial-scale micron air classifier; and (iii) on the basis of the classifier’s key performance indicators (KPIs: d₅₀, K, η) and the constrained condition (i.e., the know-how particle size distribution curve (KHC) of quartz fine powder material of 0–45 µm) applied in manufacturing engineering stone, the relationship between the operating parameters and classification performance was addressed, and the optimal set of operating parameters for the production of quartz fine powder material (0–45 µm) was selected. The simulation results will be validated using experimental results at the Vicostone Plant, Phenikaa Group. Full article

Object detection in underwater environments presents significant challenges due to the inherent limitations of sonar imaging, such as noise, low resolution, lack of texture, and color information. This paper introduces AquaYOLO, an enhanced YOLOv8 version specifically designed to improve object detection accuracy in underwater sonar images. AquaYOLO replaces traditional convolutional layers with a residual block in the backbone network to enhance feature extraction. In addition, we introduce Dynamic Selection Aggregation Module (DSAM) and Context-Aware Feature Selection (CAFS) in the neck network. These modifications allow AquaYOLO to capture intricate details better and reduce feature redundancy, leading to improved performance in underwater object detection tasks. The model is evaluated on two standard underwater sonar datasets, UATD and Marine Debris, demonstrating superior accuracy and robustness compared to baseline models. Full article

Landscape, as an important component of environmental quality, is increasingly valued by scholars for its visual dimension. Unlike evaluating landscape visual quality through on-site observation or using digital photos, the landscape visualization modeling method supported by unmanned aerial vehicle (UAV) aerial photography, geographic information System (GIS), and PixScape has the advantage of systematically scanning landscape geographic space. The data acquisition is convenient and fast, and the resolution is high, providing a new attempt for landscape visualization analysis. In order to explore the application of visibility modeling based on high-resolution UAV remote sensing images in landscape visual evaluation, this study takes campus landscape as an example and uses high-resolution campus UAV remote sensing images as the basic data source to analyze the differences between the planar method and tangent method provided by PixScape 1.2 software in visual modeling. Six evaluation factors, including Naturalness (N), Normalized Shannon Diversity Index (S), Contagion (CONTAG), Shannon depth (SD), Depth Line (DL), and Skyline (SL), are selected to evaluate the landscape vision of four viewpoints in the campus based on analytic hierarchy process (AHP) method. The results indicate that the tangent method considers the visual impact of the vertical amplitude and the distance between landscape and viewpoints, which is more in line with the real visual perception of the human eyes. In addition, objective quantitative evaluation metrics based on visibility modeling can reflect the visual differences of landscapes from different viewpoints and have good applicability in campus landscape visual evaluation. It is expected that this research can enrich the method system of landscape visual evaluation and provide technical references for it. Full article

To effectively and objectively evaluate the spatial efficiency of rail transit station areas, seventeen typical rail station areas in Xi’an were selected as the research object. An evaluation system for spatial efficiency was constructed based on data from field research, satellite images, Baidu heat maps, and station passenger flow statistics. Key factors such as land use, transportation systems, social aspects, and spatial efficiency are considered in the framework. A data envelopment analysis (DEA) method was used to evaluate the spatial efficiency of these sample station areas. The results are as follows. ① An incomplete symmetric relationship exists between the Constant Returns to Scale Technical Efficiency (Crste) and the Variable Returns to Scale Technical Efficiency (Vrste) of station area spatial efficiency. The keys to improving station area spatial efficiency include reducing redundant resource investments and establishing a rational resource allocation structure. ② For high-efficiency station areas, the Crste and Vrste are relatively high, with an overall increasing return to scale efficiency (Scale). In medium-efficiency station areas, the Crste is relatively high, but either Vrste or Scale is low. In low-efficiency station areas, the Crste is moderate, and both Vrste and Scale are low. The findings provide a reference for the intensive use of land around Xi’an rail stations, as well as support for the sustainable operation of rail transit. Full article

Objectives: This study aimed to investigate the relationship between the sarcopenia index (SI), which is derived from serum creatinine and cystatin C levels, and osteoporosis in chronic kidney disease (CKD). Methods: This study initially included patients who underwent dual-energy X-ray absorptiometry (DXA) and serum creatinine and cystatin C testing between 2005 and 2022. Subsequently, patients diagnosed with CKD were selected for the final analysis, totaling 102 patients. Both traditional and new SI were calculated, with each participant categorized into one of two groups (non-osteoporosis and osteoporosis) according to bone mineral density. To enhance statistical validity, the patients were further divided into low- and high-index groups based on the median value of both indices for comparative analysis. The association between SI and the risk of osteoporosis was estimated using multivariable logistic regression analysis. Results: Participants with lower SI values had lower bone mineral density and a higher diabetes mellitus prevalence. The non-osteoporotic group exhibited significantly higher mean values for both traditional and new SI. Multivariable logistic regression analysis identified three statistically significant variables: both indices, sex, and diabetes mellitus. Both traditional and new SI yielded individual odds ratios of 0.906 with estimated areas under the curve of 0.847 for traditional SI and 0.833 for new SI. Conclusions: This study confirmed that both traditional and new SI are associated with osteoporosis in patients with CKD. Therefore, clinicians can raise the suspicion of osteoporosis based on traditional and new SI in patients with CKD, even when DXA results are unavailable. Full article