Search

In this paper, the deformation behavior of UNS S32750 (S32750) duplex stainless steel during low cycle fatigue was studied by controlling the number of cycles. The microstructure of the specimens under different cycles was characterized by optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD), and transmission electron microscope (TEM). The microhardness of the two phases was measured by a digital microhardness instrument. The results showed that the microhardness of ferrite increases significantly after the first 4000 cycles, while the austenite shows a higher strain hardening rate after fatigue fracture, and the microhardness of ferrite and austenite increases by 23 HV and 87 HV, respectively. The two-phase kernel average misorientation (KAM) diagram showed that the continuous accumulation of plastic deformation easily leads to the initiation of cracks inside the austenite and at the phase boundaries. The evolution of dislocation morphology in the two phases was obviously different. With the increase in cycle number, the dislocation in ferrite gradually transforms from dislocation bundles and a dislocation array to a sub-grain structure, while the dislocation in austenite gradually develops from dipole array to an ordered Taylor lattice network structure. [ABSTRACT FROM AUTHOR]

The high mobility of unmanned aerial vehicles (UAVs) enables them to improve system throughput by establishing line-of-sight (LoS) links. Nevertheless, in urban environments, these LoS links can be disrupted by complex urban structures, leading to potential interference issues. Reconfigurable intelligent surfaces (RIS) provide an innovative approach to enhance communication performance by intelligently reflecting incident signals. Recent studies suggest that utilizing multi-antenna transmission can increase system efficiency, while single-antenna transmission may be more prone to interference. To address these challenges, this article introduces a RIS-assisted multiple-input single-output (MISO) UAV communication system. Our objective is to optimize the minimum user rate, thereby guaranteeing equitable communication for all users. Nevertheless, the non-convexity inherent in this optimization problem complicates the pursuit of a direct solution. Hence, we decompose the problem into four subproblems: user scheduling optimization, RIS phase-shift optimization, UAV trajectory optimization, and UAV transmit beamforming optimization. To obtain suboptimal solutions, we have developed an alternating iterative optimization algorithm for addressing the four subproblems. Numerical results demonstrate that our algorithm effectively boosts the minimum user rate of the entire system. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) and zinc (Zn) in seawater enter the human body through the food chain. Combined toxicity tests indicated that high concentrations of Cd(II) and low concentrations of Zn(II) had a synergistic effect on humans. Thus, there is an urgent need to prepare a sensor for rapid and simultaneous detection of Cd(II) and Zn(II) in seawater. Herein, a reduced graphene oxide/carboxylated multi-walled carbon nanotube (rGO/MWCNT-COOH)-modified glassy carbon electrode was prepared in the experiments using the dropping method. The synthesis of various materials achieved the purpose of expanding the surface area, and scanning electron microscopy was used to observe the structure of the composite membrane. Moreover, the large number of functional groups on the surface of the composite membrane can also increase the adsorption of ions. For the determination of trace cadmium (II) and zinc (II) in seawater, the method used was differential pulse voltammetry (DPV). The results show that the peak current, which was obtained in the range of 5–400 μg/L for Cd(II) and Zn(II), has a linear relationship with concentration, corresponding to the detection limits of 0.8 μg/L for Cd(II) and 0.98 μg/L for Zn(II). The modified electrode was used to determine the Cd(II) and Zn(II) content in the coastal seawater of the Maowei Sea, and the recovery rate was between 95.8 and 98.2% for Cd(II) and 96.7~99.4% for Zn(II), which provided a novel approach of detection to define trace Cd(II) and Zn(II) in seawater. [ABSTRACT FROM AUTHOR]

Hg(II), as an extremely hazardous heavy metal contaminant in the environment, poses a significant potential hazard to human health and ecosystems. A GR-MWCNTs-COOH/CeO2/Nafion composite film-modified glassy carbon electrode was prepared using the drop-casting method in this study. The GR-MWCNTs-COOH/CeO2/Nafion/GCE was electrochemically investigated through cyclic voltammetry (CV) and differential pulse stripping voltammetry (DPSV). Additionally, the surface morphologies of the composite film were evaluated using scanning electron microscopy (SEM). The conditions, such as buffer solution, pH, deposition potential, deposition time, modified film thickness, and Nafion content, were optimized. Under optimal experimental conditions, a good linear relationship between the peak current response of Hg(II) and its concentration in the range of 5–100 μg·L−1 was observed, with a detection limit of 0.389 μg·L−1. When it was used to detect Hg(II) in offshore seawater, the recovery rate ranged from 94.72% to 103.8%, with RSDs ≤ 5.79%. [ABSTRACT FROM AUTHOR]

Considering that heavy-metal contamination of seawater is getting worse, building a quick, accurate and portable device for detecting trace zinc in seawater in real time would be very beneficial. In this work, a microfluidic system was developed that includes a planar disc electrode, a micro-cavity for detection, an electrochemical workstation, a computer, a container for waste liquid reprocessing, an external pipeline and other components as well as a graphene/cerium oxide/nano-cerium oxide/Nafion composite membrane was used to modify the planar disc electrode (GR/CeO2/Nafion/Au) to investigate the electrochemical behaviour of Zn(II) using cyclic voltammetry, square-wave voltammetry and orthogonal test methods. Under optimal experimental conditions, the peak reaction current of Zn(II) showed a good linear relationship with the concentration of Zn(II) in the range of 1–900 μg/L with a correlation coefficient of 0.998, and the detection limit of the method was 0.87 μg/L. In addition, the microfluidic system had good stability, reproducibility and anti-interference. The system was used for determining zinc ions in real seawater samples, and the results were very similar to those of inductively coupled plasma–emission spectrometry, demonstrating the practicality of the system for the detection of trace zinc. [ABSTRACT FROM AUTHOR]

Introduction: Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer. The presence of lymph node metastasis plays a crucial role in determining the overall treatment approach and long‐term prognosis for early LUAD, therefore accurate prediction of lymph node metastasis is essential to guide treatment decisions and ultimately improve patient outcomes. Methods: We performed transcriptome sequencing on T1 LUAD patients with positive or negative lymph node metastases and combined this data with The Cancer Genome Atlas Program cohort to identify potential risk molecules at the tissue level. Subsequently, by detecting the expression of these risk molecules by real‐time quantitative PCR in serum samples, we developed a model to predict the risk of lymph node metastasis from a training cohort of 96 patients and a validation cohort of 158 patients. Results: Through transcriptome sequencing analysis of tissue samples, we identified 11 RNA (miR‐412, miR‐219, miR‐371, FOXC1, ID1, MMP13, COL11A1, PODXL2, CXCL13, SPOCK1 and MECOM) associated with positive lymph node metastases in T1 LUAD. As the expression of FOXC1 and COL11A1 was not detected in serum, we constructed a predictive model that accurately identifies patients with positive lymph node metastases using the remaining nine RNA molecules in the serum of T1 LUAD patients. In the training set, the model achieved an area under the curve (AUC) of 0.89, and in the validation set, the AUC was 0.91. Conclusions: We have established a new risk prediction model using serum samples from T1 LUAD patients, enabling noninvasive identification of those with positive lymph node metastases. [ABSTRACT FROM AUTHOR]

Duplex stainless steels are widely used in many fields due to their excellent corrosion resistance and mechanical properties. However, it is a challenge to achieve duplex microstructure and excellent properties through additive manufacturing. In this work, a 0.09% N 25Cr-type duplex stainless steel was prepared by additive manufacturing (AM) and heat treatment, and its corrosion resistance was investigated. The results show that, compared with S32750 duplex stainless steel prepared by a conventional process, the combination value of film resistance and charge transfer resistance of AM duplex stainless steel was increased by 3.2–5.5 times and the pitting potential was increased by more than 100 mV. The disappearance of residual thermal stress and the reasonable distribution of Cr and N elements in the two phases are the reasons for the improvement of the corrosion resistance of AM duplex stainless steel after heat treatment. In addition, the extremely high purity of AM duplex stainless steel with no visible inclusions resulted in a higher corrosion resistance exhibited at lower pitting-resistance-equivalent number values. [ABSTRACT FROM AUTHOR]

Summary: Finding similar scientific workflow modules that can substitute essential components of the privacy workflows from public repositories to create a personalized workflow is growing in popularity. This is a cost‐effective and error‐free strategy for the scientific community. Currently, module alignment approaches heavily depend on syntactic information such as modules' names and types. However, the contextual semantic information of modules, which encompasses inputs, outputs, and datalinks connecting modules, can also convey their functions. Unfortunately, this information is scarcely utilized during the module alignment process. In this work, we propose a module alignment method based on neighbor information for scientific workflow (MANSOR). Specifically, we present a rule‐based attribute similarity computation approach for calculating initial module‐pair similarity in two workflows. The relation similarity is then employed to iteratively fine‐tune the matching degree with uncertainty of module pairs by considering the contextual semantics until reaching a steady state. After pairwise comparison of workflows, the module alignment results are determined based on their module‐pair similarity. Experimental results on the human‐curated corpus of ratings indicate that MANSOR outperforms the existing state‐of‐the‐art approaches with statistical significance. [ABSTRACT FROM AUTHOR]

Introduction: Bivalirudin is recommended as an alternative to heparin in cardiac surgery with cardiopulmonary bypass. Although it has been used in infants and children for this indication, there is a paucity of data on the pharmacologic effects of bivalirudin in neonates. Given the immaturity of the hemostatic system in neonates, we hypothesized that coagulation responses to bivalirudin in this population would be different than in adults. Methods: Blood samples were drawn from placenta‐cord units and from healthy adult donors. The study was carried out in two steps. First, bivalirudin was added to cord and adult blood samples at concentrations of 0, 5, 10, 15, and 20 μg/mL. Activated clotting time and thromboelastographic variables were recorded. Next, we used a Chandler loop system to assess the efficacy of bivalirudin in a simple model of cardiopulmonary bypass. The loops were primed with cord or adult blood and were run until thrombus was detected. Plasma bivalirudin concentrations were measured at 1, 15, 30, 45, 60, and 75 min after initiating rotation of the loops using liquid chromatography/mass spectrometry. Results: Bivalirudin elicited a dose‐dependent prolongation inhibition of coagulation in both cord and adult blood samples with greater potency in cord blood in comparison to adult blood (activated clotting time: 627 ± 50 vs. 452 ± 22 s at 15 μg/mL bivalirudin, p <.0001). This relative potency was also demonstrated in the Chandler loop system, but interestingly, cord blood appeared to inactivate bivalirudin more rapidly than adult blood with earlier clotting in loops containing cord blood. Conclusions: This study demonstrates that bivalirudin has greater potency in cord blood in vitro than in adult blood. Plasma degradation appears to proceed more rapidly in cord blood than in adults. Both of these findings should be considered when planning dosing regimens in neonatal patients. [ABSTRACT FROM AUTHOR]

Chinese classical gardens are a significant cultural heritage in the history of world gardening, with their central architectural principle of "scenes changing as steps move" (步移景异) embodying traditional Chinese aesthetic ideals. This study employed the variation of visual complexity during a tour as a representation of this principle, using Jingxinzhai (静心斋) Garden as a case study. The visual environmental characteristics were quantified using the Fraclab box-counting, Canny edge detection, and DeepLab V3 + model, and the spatial distribution of fractal dimension and visual index of landscape elements were analyzed. Through partial correlation analysis, hierarchical regression analysis, and one-way ANOVA, the relevant factors (BVI, RVI, GVI, WVI) and influencing factors (BVI, RVI, GVI) and the differences among landscape element combinations of visual complexity were identified. Furthermore, the distribution patterns and causes of visual complexity in Chinese classical gardens were then discussed. This study proposes an effective method for quantifying the visual environmental characteristics of Chinese classical gardens and provides an explanation of the concept of "scenes changing as steps move" from the perspective of visual environment. It offers important references for a deeper understanding of Chinese classical garden design and planning. [ABSTRACT FROM AUTHOR]

With the evolution of fifth-generation (5G) to sixth-generation (6G) communication systems, the utilization of spectrum resources faces incremental challenges. Integrated sensing and communication (ISAC) technology, as a crucial element in 6G technology, is expected to enhance energy efficiency and spectrum utilization efficiency by integrating radar and communication signals, achieving environmental awareness, and enabling scene interconnection. Simultaneously, to realize the vision of seamless coverage in 6G, research on integrated satellite-terrestrial communication has been prioritized. To integrate the advantages, ISAC for integrated satellite–terrestrial networks (ISTNs) in 6G has emerged as a potential research direction. This paper offers an extensive overview of the present state of key technologies for ISAC and the development of ISTNs. Meanwhile, with a focus on the ISTN-oriented 6G ISAC system, several hotspot topics, including future application scenarios and key technological developments, are outlined and demonstrated. [ABSTRACT FROM AUTHOR]

Simple Summary: In brief, the mitochondrial genome of L. ikeae has a total length of 16,498 bp and encodes 13 PCGs, 22 transfer RNA genes, two ribosomal RNA genes, and a D-loop (control) region. Gene rearrangement is not observed. The mitochondrial genome of L. ikeae exhibits an AT preference, with AT skew > 0 and GC skew < 0 across the entire genome. The phylogenetic relationships of Sicydiinae based on 13 mitochondrial PCG sequences are Sicydium + (Stiphodon + (Sicyopus + Lentipes)) + Sicyopterus, indicating that Sicydium, Sicyopterus, Lentipes, and Stiphodon are all monophyletic groups. We sequenced and analyzed the complete mitochondrial genome of Lentipes ikeae and explored the phylogenetic relationships among Sicydiinae based on mitochondrial genome sequences. The complete mitochondrial genome sequence of L. ikeae was determined using the Illumina HiSeq X Ten sequencing platform, and the gene structural characteristics and base composition were analyzed. Based on the mitochondrial genome sequences of 28 Sicydiinae species published in GenBank and mitochondrial protein-coding genes (PCGs), Acanthogobius flavimanus (Gobionellinae) was selected as an outgroup to construct phylogenetic trees of Sicydiinae using the maximum likelihood and Bayesian inference methods. The mitochondrial genome of L. ikeae (GenBank number: OP764680) has a total length of 16,498 bp and encodes 13 PCGs, 22 transfer RNA genes, two ribosomal RNA genes, and a D-loop (control) region. Gene rearrangement is not observed. The mitochondrial genome of L. ikeae exhibits an AT preference, with AT skew > 0 and GC skew < 0 across the entire genome. The phylogenetic relationships of Sicydiinae based on 13 mitochondrial PCG sequences are Sicydium + (Stiphodon + (Sicyopus + Lentipes)) + Sicyopterus, indicating that Sicydium, Sicyopterus, Lentipes, and Stiphodon are all monophyletic groups. [ABSTRACT FROM AUTHOR]

With the increasing complexity of patrol tasks, the use of deep reinforcement learning for collaborative coverage path planning (CPP) of multi-mobile robots has become a new hotspot. Taking into account the complexity of environmental factors and operational limitations, such as terrain obstacles and the scope of the task area, in order to complete the CPP task better, this paper proposes an improved K-Means clustering algorithm to divide the multi-robot task area. The improved K-Means clustering algorithm improves the selection of the first initial clustering point, which makes the clustering process more reasonable and helps to distribute tasks more evenly. Simultaneously, it introduces deep reinforcement learning with a dueling network structure to better deal with terrain obstacles and improves the reward function to guide the coverage process. The simulation experiments have confirmed the advantages of this method in terms of balanced task assignment, improvement in strategy quality, and enhancement of coverage efficiency. It can reduce path duplication and omission while ensuring coverage quality. [ABSTRACT FROM AUTHOR]

Objective: Postradiation nasopharyngeal necrosis (PRNN) frequently develops after second‐course radiotherapy for nasopharyngeal carcinoma (NPC). PRNN can lead to internal carotid artery (ICA) massive hemorrhage due to ICA rupture, resulting in sudden death. This study aims to explore the pretreatment of the ICA to prevent fatal massive hemorrhage in PRNN patients. Study Design: Retrospective cohort study. Setting: Sun Yat‐sen University Cancer Center. Methods: Patients diagnosed with NPC and PRNN from January 2010 to September 2022 were included. The Cox proportional hazards regression analysis was performed to analyze risk factors for massive hemorrhage and survival. A nomogram was developed to integrate prognostic models and perform parameter calibration. Results: Two hundred and fifty‐four PRNN patients were included in this study. Prophylactic ICA occlusion significantly reduced the risk of ICA hemorrhage compared to no prophylactic ICA occlusion (3.6% vs 40.6%, P <.001). Surgical repair on necrosis significantly prevented hemorrhage and improved survival. The nomogram, incorporating the above 2 factors and the nearest distance from necrosis to ICA ≤ 3 mm, exhibited excellent discriminative ability for hemorrhage. We identified 3 high‐risk factors that indicate the need for prophylactic ICA management in PRNN patients: (1) exposure of ICA by rhinoscopy; (2) signs of ICA erosion on MRA scanning; (3) the depth of soft tissue coverage surrounding the ICA wall within the necrotic cavity is less than 3 mm on magnetic resonance imaging. Conclusion: We have identified 3 high‐risk factors for PRNN patients that necessitate prophylactic ICA management. These findings are expected to contribute to improving the quality of life and overall survival of PRNN patients. [ABSTRACT FROM AUTHOR]

With the rapid development of object detection technology for unmanned aerial vehicles (UAVs), it is convenient to collect data from UAV aerial photographs. They have a wide range of applications in several fields, such as monitoring, geological exploration, precision agriculture, and disaster early warning. In recent years, many methods based on artificial intelligence have been proposed for UAV object detection, and deep learning is a key area in this field. Significant progress has been achieved in the area of deep-learning-based UAV object detection. Thus, this paper presents a review of recent research on deep-learning-based UAV object detection. This survey provides an overview of the development of UAVs and summarizes the deep-learning-based methods in object detection for UAVs. In addition, the key issues in UAV object detection are analyzed, such as small object detection, object detection under complex backgrounds, object rotation, scale change, and category imbalance problems. Then, some representative solutions based on deep learning for these issues are summarized. Finally, future research directions in the field of UAV object detection are discussed. [ABSTRACT FROM AUTHOR]