Scientific Reports最新文献

Developments in object detection algorithms are critical for urban planning, environmental monitoring, surveillance, and many other applications. The primary objective of the article was to improve detection precision and model efficiency. The paper compared the performance of six different metaheuristic optimization algorithms including Gray Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Remora Optimization Algorithm (ROA), Aquila Optimizer (AO), and Hybrid PSO-GWO (HPSGWO) combined with YOLOv7 and YOLOv8. The study included two distinct remote sensing datasets, RSOD and VHR-10. Many performance measures as precision, recall, and mean average precision (mAP) were used during the training, validation, and testing processes, as well as the fit score. The results show significant improvements in both YOLO variants following optimization using these strategies. The GWO-optimized YOLOv7 with 0.96 mAP 50, and 0.69 mAP 50:95, and the HPSGWO-optimized YOLOv8 with 0.97 mAP 50, and 0.72 mAP 50:95 had the best performance in the RSOD dataset. Similarly, the GWO-optimized versions of YOLOv7 and YOLOv8 had the best performance on the VHR-10 dataset with 0.87 mAP 50, and 0.58 mAP 50:95 for YOLOv7 and with 0.99 mAP 50, and 0.69 mAP 50:95 for YOLOv8, indicating greater performance. The findings supported the usefulness of metaheuristic optimization in increasing the precision and recall rates of YOLO algorithms and demonstrated major significance in improving object recognition tasks in remote sensing imaging, opening up a viable route for applications in a variety of disciplines.

In pediatric liver recipients perioperative factors may affect respiratory and cardiac function, and prolong mechanical ventilation during post-operative period. The use of NAVA can improve the interaction between the patient and the ventilator from both a respiratory and cardiac perspective. The objective of this study is to evaluate the synchronization between the patient and the ventilator, as well as cardiac function, during the application of neurally adjusted ventilatory assist (NAVA) and pressure support ventilation (PSV) in pediatric liver transplant recipients. This is a single-center, prospective, randomized, physiological cross-over controlled trial conducted between 2021 and 2022. Children (1 month-10 years old) who underwent liver transplantation were admitted to the pediatric intensive care unit. Patients were randomised to one of two crossover sequences of ventilation trials of 40 min each (PSV/NAVA/PSV or NAVA/PSV/NAVA). Cardiac function was studied by echocardiogram. Twenty-four patients were enrolled and 21 completed the study. Primary outcomes were variation of asynchrony index (AI) and tricuspid annular plane systolic excursion (TAPSE) during the two ventilation modes. Secondary outcomes were patient-ventilator interaction parameters, gas exchange, left and right ventricular function, and hemodynamic parameters. NAVA compared to PSV: (1) improves patient-ventilator interaction reducing AI (coeff - 6.66 95% CI -11.5 to -1.78, p = 0.008); (2) does not improve TAPSE (coeff 0.62 95% CI -1.49 to 2.74, p < 0.557) No differences in terms of pulmonary gas exchange and hemodynamic parameters were detected. NAVA (when compared to PSV) improves patient-ventilator interaction in terms of asynchronies without affecting cardiac biventricular function.Trial registration: NCT04792788, Registration date: 2021-03-11.

Esketamine (EK) has been widely used in the treatment of depression, but the effects of EK prenatal treatment on embryonic heart development have been rarely reported. This study assesses the effects of varying concentrations of EK on embryonic development and cardiogenesis to determine the teratogenic concentration in the zebrafish model, centering on the interaction between the genes nkx2.5 and gata4 to elucidate the mechanisms underlying cardiac morphogenesis. Zebrafish embryos were classified into six distinct groups and exposed to either a vehicle or EK to ascertain the median lethal concentration (LC₅₀) at 48 and 72 h post-fertilization (hpf) analyzing mortality rate data. Embryonic and cardiac morphologies were assessed utilizing live embryo imaging techniques and stereo microscopy. Nkx2.5 and gata4 were identified via whole-mount in situ hybridization (WISH) and reverse transcription quantitative polymerase chain reaction (RT-qPCR). Exposure to EK leads to significant teratogenic effects on zebrafish embryos, which are both concentration- and time-dependent. The 48 h- and 72 h-LC₅₀ of EK for zebrafish embryos were 1.30 (95% CI 0.92, 1.60) millimolar (mM) and 0.71 (95% CI 0.46, 1.01) mM, respectively. A significant reduction in heart rates and body length were observed and the distance between the sinus venosus and bulbar artery (SV-BA) was found expanded, the pericardial edema area showed significant swelling, and the body axis curvature was more pronounced in the EK exposure groups. Both WISH an RT-qPCR analysis showed nkx2.5 staining intensity and expression significantly decreased, while gata4 assay results were in the opposite direction. Our findings indicate that exposure of zebrafish embryos to EK results in embryonic and cardiac malformations, primarily due to the down-regulation of nkx2.5 and the over-expression of gata4. Equilibrium maintenance and compensatory mechanisms are crucial in spatiotemporal gene regulation.

We introduce efficient tensor network models for sequence processing motivated by correspondence to probabilistic graphical models, interpretability and resource compression. Inductive bias is introduced via network architecture as motivated by correlation and compositional structure in the data. We create expressive networks utilising tensors that are both complex and unitary. As such they may be represented by parameterised quantum circuits and describe physical processes. The relevant inductive biases result in networks with logarithmic treewidth which is paramount for avoiding trainability issues in these spaces. For the same reason, they are also efficiently contractable or 'quantum-inspired'. We demonstrate experimental results for the task of binary classification of bioinformatics and natural language, characterised by long-range correlations and often equipped with syntactic information. This work provides a scalable route for experimentation on the role of tensor structure and syntactic priors in NLP. Since these models map operationally to the qubits of a quantum processor, unbiased sampling equates to taking measurements on the quantum state encoding the learnt probability distribution. We demonstrate implementation on Quantinuum's H2-1 trapped-ion quantum processor, showing the potential of near-term quantum devices.

The study introduces a new method for predicting software defects based on Residual/Shuffle (RS) Networks and an enhanced version of Fish Migration Optimization (UFMO). The overall contribution is to improve the accuracy, and reduce the manual effort needed. The originality of this work rests in the synergic use of deep learning and metaheuristics to train the software code for extraction of semantic and structural properties. The model is tested on a variety of open-source projects, yielding an average accuracy of 93% and surpassing the performance of the state-of-the-art models. The results indicate an overall increase in the precision (78-98%), recall (71-98%), F-measure (72-96%), and Area Under the Curve (AUC) (78-99%). The proposed model is simple and efficient and proves to be effective in identifying potential defects, consequently decreasing the chance of missing these defects and improving the overall quality of the software as opposed to existing approaches. However, the analysis is limited to open-source projects and warrants further evaluation on proprietary software. The study enables a robust and efficient tool for developers. This approach can revolutionize software development practices in order to use artificial intelligence to solve difficult issues presented in software. The model offers high accuracy to reduce the software development cost, which can improve user satisfaction, and enhance the overall quality of software being developed.

This study aims to experimentally demonstrate a liquid desiccant systems effectiveness by using thermo-chemical fluid, such as aqueous solution of calcium chloride. This study evaluated the effect of operating temperatures on air properties (temperature, relative humidity, and moisture content) and system effectiveness by varying air flow rates. The system's functionality was influenced by the operational temperature and air flow rate, and the dehumidification effectiveness was higher at low operating temperatures and low airflow rates. An ANN metamodel-based control strategy is also proposed for implementation in hybrid thermo-chemical networks with the help of system performance data and real-time data. The suggested ANN model's results were validated using a variety of measuring techniques, including the RMSE, MAPE, correlation (R), and coefficient of determination (R²). The proposed ANN analysis achieved an excellent correlation between predicted and experimentally measured data.

The interaction between crossflow and liquid jets is common in engineering applications, such as in gas-steam catapult power systems and supersonic ramjets. Studying the atomization process of liquid jets in crossflow has significant engineering value. In this work, high-speed photography was used. The experimental results indicate that factors such as airflow velocity, temperature, jet velocity, temperature, and nozzle diameter can affect the depth of jet penetration. Considering the influence of various factors, an empirical formula for calculating jet penetration is obtained. The results can support the design of gas-steam catapult propulsion systems and be extended to other applications, such as supersonic ramjets.

Candidiasis poses a significant threat to human health, especially in immunocompromised patients. However, there is a paucity of epidemiological data concerning the prevalence of candidiasis in developing regions of China. We conducted a retrospective study on patients positive for Candida infections in a tertiary care hospital in Shantou, China, to identify the clinical characteristics and risk factors for candidiasis. Of 5,095 cases of candidiasis, 489 (9.59%) were candidemia infections. Candida albicans (n = 230, 47.0%) was the predominant species identified among all patients. Non-albicans Candida (NAC) was more prevalent in adult patients, while Candida glabrata was slightly more frequent in pediatric patients (n = 10, 14.7%). Pulmonary diseases (n = 200, 47.8%) were the most common underlying comorbidities in adult patients (n = 25, 35.2%). Thrombocytopenia was the only laboratory finding higher in adult patients than in pediatric patients. Respiratory dysfunction, the presence of a central venous catheter, septic shock, and thrombocytopenia were independent risk factors for candidemia-related 30-day mortality. Amphotericin B exhibited high efficacy (100%), and itraconazole exhibited the lowest efficacy against all tested Candida isolates. C. glabrata had a lower susceptibility to azole, although this was not statistically significant. The epidemiological data on candidiasis, specifically candidemia in pediatric and adult patients, varied regarding the prevalence of Candida species and associated risk factors. This study provides guidance for prescribing the appropriate therapy and yields insights into the susceptibility patterns of different Candida isolates to antifungal drugs.

The proteomic profile of the human cardiac conduction system: the sinoatrial node (SAN) and atrioventricular node (AVN), remains poorly understood. The aim of the current study is to identify proteomic characteristic of the human SAN and AVN in the comparison to working myocardium of the right atrium (RAM) and right ventricle (RVM). The proteomic analysis was performed on 10 autopsied human heart specimens collected from healthy adults. During the data-independent acquisition proteomics analysis 2752 different proteins were identified in all sample sets. In both nodal tissues (compared to working myocardium), the following pathways were upregulated: regulation of Insulin-like Growth Factor transport and uptake by Insulin-like Growth Factor Binding Proteins, post-translational protein phosphorylation, glutathione metabolism, metabolism of carbohydrates, glycolysis and gluconeogenesis. Other common for nodal tissue pathways were these related to immune system and related to extracellular matrix. The pathways related to cardiac muscle contraction were more abundant in RAM and RVM samples. The current study presents extensive comparative analysis of protein abundance in the human SAN and AVN. Few key differences may be found in the nodal proteome in comparison to working cardiomyocytes, including involvement of immune system and upregulated pathways related to extracellular matrix. The SAN exhibits enrichment in the PPAR signaling and pentose phosphate pathways, as well as prostaglandin synthesis and regulatory proteins, compared to the AVN.