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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]

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]

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]

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]

This study aims to establish precise quality indicators for evaluating and enhancing ultrasound performance, employing a methodology based on a comprehensive review of the literature, expert insights, and practical application experiences. We conducted a thorough review of both the domestic and international literature on ultrasound quality control to identify potential indicators. A dedicated team was formed to oversee the complete indicator development process. Utilizing a three-round modified Delphi method, we sought expert opinions through personalized email correspondence. Subsequently, data from diverse hospital indicators were collected to validate and assess feasibility. A novel set of seven indicators was compiled initially, followed by the convening of a 36-member nationally representative expert panel. After three rounds of meticulous revisions, consensus was reached on 13 indicators across three domains. These finalized indicators underwent application in various hospital settings, demonstrating their initial validity and feasibility. The development of thirteen ultrasound quality indicators represents a significant milestone in evaluating ultrasound performance. These indicators empower hospitals to monitor changes in quality effectively, fostering efficient quality management practices. [ABSTRACT FROM AUTHOR]

Xylo-oligosaccharides (XOS) enriched with high fractions of X2-X3 are regarded as an effective prebiotic for regulating the intestinal microflora. In this study, the original XOS solution was obtained from bamboo shoots through hydrothermal pretreatment under optimized conditions. Subsequently, enzymatic hydrolysis with endo-xylanase was performed on the original XOS solution to enhance the abundance of the X2-X3 fractions. The results demonstrated that hydrothermal pretreatment yielded 21.24% of XOS in the hydrolysate solution, and subsequent enzymatic hydrolysis significantly increased the proportion of the X2-X3 fractions from 38.87% to 68.21%. Moreover, the XOS solutions with higher amounts of X2-X3 fractions exhibited superior performance in promoting the growth of probiotics such as Bifidobacterium adolescentis and Lactobacillus acidophilus in vitro, leading to increased production of short-chain fatty acids. In the in vivo colitis mouse model, XOS solutions with higher contents of X2-X3 fractions demonstrated enhanced efficacy against intestinal inflammation. Compared with the colitis mice (model group), the XOS solution with higher X2-X3 fractions (S1 group) could significantly increase the number of Streptomyces in the intestinal microflora, while the original XOS solution (S2 group) could significantly increase the number of Bacteroides in the intestinal microflora of colitis mice. In addition, the abundances of Alcaligenes and Pasteurella in the intestinal microflora of the S1 and S2 groups were much lower than in the model group. This effect was attributed to the ability of these XOS solutions to enhance species diversity, reversing the imbalance and disorder within the intestinal microflora. Overall, this work highlights the outstanding potential of XOS enriched with high contents of X2-X3 fractions as a regulator of the intestinal microbiota and as an anti-colitis agent. [ABSTRACT FROM AUTHOR]

Phenanthrene (PHE), as a structurally simple, tricyclic, polycyclic aromatic hydrocarbon (PAHs), is widely present in marine environments and organisms, with serious ecological and health impacts. It is crucial to study fast and simple high-sensitivity detection methods for phenanthrene in seawater for the environment and the human body. In this paper, a immunosensor was prepared by using a multi-wall carbon nanotube (MWCNTs)-chitosan oligosaccharide (COS) nanocomposite membrane loaded with phenanthrene antibody. The principle was based on the antibody–antigen reaction in the immune reaction, using the strong electron transfer ability of multi-walled carbon nanotubes, coupled with chitosan oligosaccharides with an excellent film formation and biocompatibility, to amplify the detection signal. The content of the phenanthrene in seawater was studied via differential pulse voltammetry (DPV) using a potassium ferricyanide system as a redox probe. The antibody concentration, pH value, and probe concentration were optimized. Under the optimal experimental conditions, the response peak current of the phenanthrene was inversely proportional to the concentration of phenanthrene, in the range from 0.5 ng·mL−1 to 80 ng·mL−1, and the detection limit was 0.30 ng·mL−1. The immune sensor was successfully applied to the detection of phenanthrene in marine water, with a recovery rate of 96.1~101.5%, and provided a stable, sensitive, and accurate method for the real-time monitoring of marine environments. [ABSTRACT FROM AUTHOR]

Clostridium ljungdahlii is a representative autotrophic acetogen capable of producing multiple chemicals from one-carbon gases (CO2/CO). The metabolic and regulatory networks of this carbon-fixing bacterium are interesting, but still remain minimally explored. Here, based on bioinformatics analysis followed by functional screening, we identified a RpiR family transcription factor (TF) that can regulate the autotrophic growth and carbon fixation of C. ljungdahlii. After deletion of the corresponding gene, the resulting mutant strain exhibited significantly impaired growth in gas fermentation, thus reducing the production of acetic acid and ethanol. In contrast, the overexpression of this TF gene could promote cell growth, indicating a positive regulatory effect of this TF in C. ljungdahlii. Thus, we named the TF as GssR (growth and solvent synthesis regulator). Through the following comparative transcriptomic analysis and biochemical verification, we discovered three important genes (encoding pyruvate carboxylase, carbon hunger protein CstA, and a BlaI family transcription factor) that were directly regulated by GssR. Furthermore, an upstream regulator, BirA, that could directly bind to gssR was found; thus, these two regulators may form a cascade regulation and jointly affect the physiology and metabolism of C. ljungdahlii. These findings substantively expand our understanding on the metabolic regulation of carbon fixation in gas-fermenting Clostridium species. [ABSTRACT FROM AUTHOR]

Rice husks are a feedstock of biogenic silica because of their high silica content. After silica extraction, a solid residue comprising mostly carbohydrates is present. Solid residue valorization is important for closed-loop systems using rice husk and has minimal negative environmental impacts. In this study, we used solid rice husk that was generated by silica extractionto anaerobic digestion for producing biomethane. The rice husk residue was characterized in terms of total solids, volatile solids, pH, composition, and particle size. Changing the characteristics increased biogas production by 2.48-fold compared to that of raw rice husk. The residue produced 166.4 mL-biogas g−1 vs. and 100.4 mL CH 4 g−1 VS, much more than previously reported. Microbial community analysis, which was conducted to investigate the biological reasons for increased biogas and methane, found increased Bacteroidetes levels in the rice husk samples. Among archaeal communities, Bathyarchaeota was more abundant in all rice husk samples than in the inoculum. The rice husk residue contained more operational taxonomic units than other samples. These changes in the microbial community significantly influenced the anaerobic digestion of the rice husk residue and improved methane production. Our findings provide a basis for the cleaner utilization of rice husk residue to produce renewable energy. [ABSTRACT FROM AUTHOR]

C-Mos, a proto-oncogene, regulates oocyte maturation by activating the classical MAPK pathway in cells. To examine the function of C-Mos in Hyriopsis cumingii, C-Mos was identified in this study. The full-length cDNA of C-Mos was 2213 bp, including 144 bp in the 5′ UTR, 923 bp in 3′ the UTR, and 1146 bp in the open reading frame (ORF) region. During early gonad development, the expression of C-Mos from 4 to 6 months of age in H. cumingii was significantly higher than that in other months, with the highest expression in 6-month-old H. cumingii, suggesting that C-Mos may be involved in early gonadal development in H. cumingii. Clear hybridization signals were found by in situ hybridization in the oocytes, oocyte nucleus and oogonium, and a small number of hybridization signals were found in the follicular wall of the male gonads. In addition, the C-Mos RNA interference (RNAi) assay results showed that the knockdown of C-Mos caused a down-regulation of ERK and P90rsk. In summary, these results indicate that C-Mos has a crucial part to play in gonadal development in H. cumingii. [ABSTRACT FROM AUTHOR]

The orthogonal triangular factorization (QRF) method is a widespread tool to calculate eigenvalues and has been used for many practical applications. However, as an emerging topic, only a few works have been devoted to handling dynamic QR factorization (DQRF). Moreover, the traditional methods for dynamic problems suffer from lagging errors and are susceptible to noise, thereby being unable to satisfy the requirements of the real-time solution. In this paper, a bounded adaptive function activated recurrent neural network (BAFARNN) is proposed to solve the DQRF with a faster convergence speed and enhance existing solution methods' robustness. Theoretical analysis shows that the model can achieve global convergence in different environments. The results of the systematic experiment show that the BAFARNN model outperforms both the original ZNN (OZNN) model and the noise-tolerant zeroing neural network (NTZNN) model in terms of accuracy and convergence speed. This is true for both single constants and time-varying noise disturbances. [ABSTRACT FROM AUTHOR]

The occurrence, multi-index assessment, and sources of heavy metals in surface sediments of Zhelin Bay were investigated. Average heavy metal concentrations (mg/kg) were 81.89 (Cr), 770.76 (Mn), 16.81 (Co), 62.25 (Ni), 96.30 (Cu), 162.04 (Zn), and 73.40 (Pb), with the concentrations of studied seven heavy metals being significantly higher than their corresponding background values. Geo-accumulation index (Igeo) and pollution load index (PLI) were implemented to assess degree of heavy metal contamination. The Igeo and PLI indicated that Cr, Mn, Co, Zn, and Pb were slightly polluted, and Cu and Ni were moderately polluted in the region. Potential ecological risk index (RI) and mean possible effect level (PEL) quotient were conducted to assess ecological risk. The RI and mean PEL quotient demonstrated that surface sediments of Zhelin Bay were slight ecological risks and exhibited a 21% probability of toxicity. Principal component analysis (PCA) combined with the correlation analysis (CA) and hierarchical cluster analysis (HAC) revealed that the heavy metal contamination in Zhelin Bay might originate from three type sources. [ABSTRACT FROM AUTHOR]

Double-lumen endobronchial tube (DLT) intubation is more challenging than single-lumen tube intubation is, and the rigid video stylet (RVS) is one of the tools that has emerged to deal with this demanding intubation procedure. We evaluated whether the UE® RVS can shorten the DLT intubation time and improve the first-attempt intubation success rate compared with that of Macintosh laryngoscope (ML). A total of 130 participants scheduled to undergo thoracoscopic pulmonary surgeries were enrolled. They were randomized to receive either ML- or RVS-assisted DLT intubation. The primary outcomes were the intubation time and first-attempt intubation success rate. The secondary outcomes were the overall intubation success rate, mean arterial pressure, postoperative sore throat (POST), and postoperative hoarseness at 1 h and 24 h. Compared with the ML group, the intubation time was significantly shorter in the RVS group (p < 0.001; 30.82 ± 10.61 vs. 39.62 ± 6.54 s), however, the first-attempt success rate was significantly lower (p = 0.048; 83.08% vs. 95.16%). The POST at 1 h was less severe in the RVS group (p = 0.021). No significant differences were found for the other indicators. Among the patients with normal airways, the UE® RVS can achieve faster DLT intubation and decrease the severity of a POST at 1 h, although it was associated with a lower first-attempt intubation success rate. [ABSTRACT FROM AUTHOR]

MAPKAPK2 (MK2) is an important regulator of the p38 mitogen-activated protein kinase (p38 MAPK) pathway, which is involved in a plethora of cellular processes concluding the development of gamete cells in meiosis and resisting pathogenic bacterial infestation. Hyriopsis cumingii is a significant mussel resource in China and a good material for pearl breeding. To explore the role of MK2 in H. cumingii, MK2 was identified and cloned, whose full-length cDNA was 1568 bp, including 87 bp in 5′ UTR, 398 bp in 3′ UTR, and 1083 bp in the open reading frame (ORF) region, encoding 360 amino acids. The expression of MK2 was the highest in the gills. Meanwhile, there was a significant difference in the gonads. After Aeromonas hydrophila and Lipopolysaccharide (LPS) infestation, the transcript level of the MK2 was upregulated in the gills. It indicated that MK2 might be involved in the innate immune response of H. cumingii after a pathogenic attack. After quantifying H. cumingii of different ages, it was found that the expression of MK2 was highest at 1 year old. In situ hybridization (ISH) results showed that the blue-purple hybridization signal was very significant in the oocytes and egg membranes of the female gonads of H. cumingii. The expression of MK2 increased gradually at the age of 1 to 5 months and showed a downward trend at the age of 5 to 8 months. It was suggested that MK2 might play an important role in the formation of primitive germ cells in H. cumingii. To sum up, MK2 might not only be involved in the immune response against pathogenic bacterial infection but also might play an important role in the development of the gonads in H. cumingii. [ABSTRACT FROM AUTHOR]

Background: Sepsis commonly causes acute respiratory distress syndrome (ARDS), and ARDS contributes to poor prognosis in sepsis patients. Early prediction of ARDS for sepsis patients remains a clinical challenge. This study aims to develop and validate chest computed tomography (CT) radiomic-based signatures for early prediction of ARDS and assessment of individual severity in sepsis patients. Methods: In this ambispective observational cohort study, a deep learning model, a sepsis-induced acute respiratory distress syndrome (SI-ARDS) prediction neural network, will be developed to extract radiomics features of chest CT from sepsis patients. The datasets will be collected from these retrospective and prospective cohorts, including 400 patients diagnosed with sepsis-3 definition during a period from 1 May 2015 to 30 May 2022. 160 patients of the retrospective cohort will be selected as a discovering group to reconstruct the model and 40 patients of the retrospective cohort will be selected as a testing group for internal validation. Additionally, 200 patients of the prospective cohort from two hospitals will be selected as a validating group for external validation. Data pertaining to chest CT, clinical information, immune-associated inflammatory indicators and follow-up will be collected. The primary outcome is to develop and validate the model, predicting in-hospital incidence of SI-ARDS. Finally, model performance will be evaluated using the area under the curve (AUC) of receiver operating characteristic (ROC), sensitivity and specificity, using internal and external validations. Discussion: Present studies reveal that early identification and classification of the SI-ARDS is essential to improve prognosis and disease management. Chest CT has been sought as a useful diagnostic tool to identify ARDS. However, when characteristic imaging findings were clearly presented, delays in diagnosis and treatment were impossible to avoid. In this ambispective cohort study, we hope to develop a novel model incorporating radiomic signatures and clinical signatures to provide an easy-to-use and individualized prediction of SI-ARDS occurrence and severe degree in patients at early stage. [ABSTRACT FROM AUTHOR]

Recently, the application of memristors to improve chaos complexity in discrete chaotic systems has been paid more and more attention to. To enrich the application examples of discrete memristor-based chaotic systems, this article proposes a new three-dimensional (3-D) memristor-based Lozi map by introducing a discrete memristor into the original two-dimensional (2-D) Lozi map. The proposed map has no fixed points but can generate hidden hyperchaos, so it is a hidden hyperchaotic map. The dynamical effects of the discrete memristor on the memristor-based Lozi map and two types of coexisting hidden attractors boosted by the initial conditions are demonstrated using some numerical methods. The numerical results clearly show that the introduced discrete memristor allows the proposed map to have complicated hidden dynamics evolutions and also exhibit heterogeneous and homogeneous hidden multistability. Finally, a digital platform is used to realize the memristor-based Lozi map, and its experimental phase portraits are obtained to confirm the numerical ones. [ABSTRACT FROM AUTHOR]

Navigation safety is one of the primary operational requirements for unmanned surface vehicles (USVs) in a complex marine environment, mainly guaranteed by a reliable path planning system for collision avoidance. This work proposes a novel weighted sum multi-objective optimisation strategy for USV collision avoidance path planning in restricted waters. In particular, the coefficients of different objectives could be tuned to emphasise the most critical design consideration under varying navigation scenarios. Moreover, in addition to the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), the terrain and weather constraints were also considered in the path planning system. The proposed USV collision avoidance path planning framework's effectiveness was demonstrated through numerical simulations and hardware-in-the-loop (HIL) tests. The numerical simulation results indicate that the proposed method could avoid collision with dynamic and static obstacles, and it is also adaptive to different navigation restrictions and preferences. Moreover, a USV navigation platform was established by incorporating true Automatic Identification System (AIS) signals, and HIL tests were performed with real-time AIS data in a water channel in the Zhoushan archipelago. The results demonstrate that the proposed USV path planning strategy is applicable in restricted waters with complex terrains and weather constraints. [ABSTRACT FROM AUTHOR]

Loaders are widely used in the construction of earthworks for construction projects. Due to the large volume and mass of these machines, they have shortcomings such as low driving efficiency and high energy consumption. To address these shortcomings, this work applied eclectic drive technology to a loader's traction system. A wheel electric drive system with a switched reluctance driver (SRD) was developed. The operating principle and basic structure of the SRD system were analyzed. A new voltage PWM-controlled strategy with dynamic adjustable turn-on and turn-off angles and a single conducting phase in a fixed period was developed. Then, an SRD simulation model was established in MATLAB/Simulink. A simulation of the working condition for the loader was performed. A test bench for the SRD was built and accordingly the transportation and operation conditions were tested. The corresponding speed–time curve of transportation and operation was obtained. Simulation and experiment results showed that the electric drive system with SRD had excellent responses to changes in torque and speed and adapted well to the various working conditions of the loader. The system could effectively traction the loader and verified the feasibility and applicability of the wheel electric drive system. [ABSTRACT FROM AUTHOR]

As a popular research direction in the field of intelligent transportation, various scholars have widely concerned themselves with traffic sign detection However, there are still some key issues that need to be further solved in order to thoroughly apply related technologies to real scenarios, such as the feature extraction scheme of traffic sign images, the optimal selection of detection methods, and the objective limitations of detection tasks. For the purpose of overcoming these difficulties, this paper proposes a lightweight real-time traffic sign detection integration framework based on YOLO by combining deep learning methods. The framework optimizes the latency concern by reducing the computational overhead of the network, and facilitates information transfer and sharing at diverse levels. While improving the detection efficiency, it ensures a certain degree of generalization and robustness, and enhances the detection performance of traffic signs in objective environments, such as scale and illumination changes. The proposed model is tested and evaluated on real road scene datasets and compared with the current mainstream advanced detection models to verify its effectiveness. In addition, this paper successfully finds a reasonable balance between detection performance and deployment difficulty by effectively reducing the computational cost, which provides a possibility for realistic deployment on edge devices with limited hardware conditions, such as mobile devices and embedded devices. More importantly, the related theories have certain application potential in technology industries such as artificial intelligence or autonomous driving. [ABSTRACT FROM AUTHOR]

Excessive fat accumulation can lead to obesity, diabetes, hyperlipidemia, atherosclerosis, and other diseases. MicroRNAs are a class of microRNAs that regulate gene expression and are highly conserved in function among species. microRNAs have been shown to act as regulatory factors to inhibit fat accumulation in the body. We found that miR-370-3p was expressed at lower levels in the fat mass of mice on a high-fat diet than in mice on a normal control diet. Furthermore, our data showed that the overexpression of miR-370-3p significantly suppressed the mRNA expression levels of adipogenic markers. Thus, miR-370-3p overexpression reduced lipid accumulation. Conversely, the inhibition of miR-370-3p suppressed 3T3-L1 preadipocyte proliferation and promoted preadipocyte differentiation. In addition, Mknk1, a target gene of miR-370-3p, plays an opposing role in preadipocyte proliferation and differentiation. Moreover, consistent results from in vitro as well as in vivo experiments suggest that the inhibition of fat accumulation by miR-370-3p may result from the inhibition of saturated fatty acids that promote the accumulation of polyunsaturated fatty acids. In conclusion, these results suggest that miR-370-3p plays an important role in adipogenesis and fatty acid metabolism through the regulation of Mknk1. [ABSTRACT FROM AUTHOR]

In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a "local climate" and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to study the correlation between haze weather and local climate. First, we select Beijing, China and its surrounding areas (East longitude 115°20′11″–117°40′35″, North latitude 39°21′11″–41°7′51″) as the study area. We collected data from meteorological stations in Beijing and Xianghe from March 2014 to February 2015, and analyzed the meteorological parameters through correlation analysis and a grey correlation model. We study the correlation between the six influencing factors of temperature, dew point, humidity, wind speed, air pressure and visibility and PM2.5, so as to analyze the correlation between haze weather and local climate more comprehensively. The results show that the influence of each index on PM2.5 in descending order is air pressure, wind speed, humidity, dew point, temperature and visibility. The qualitative analysis results confirm each other. Among them, air pressure (correlation 0.771) has the greatest impact on haze weather, and visibility (correlation 0.511) is the weakest. [ABSTRACT FROM AUTHOR]

In deserts, pond cladocerans suffer harsh conditions like low and erratic rainfall, high evaporation, and highly variable salinity, and they have limited species richness. The limited species can take advantage of ephippia or resting eggs for being dispersed with winds in such habitats. Thus, environmental selection is assumed to play a major role in community assembly, especially at a fine spatial scale. Located in Inner Mongolia, the Ulan Buh desert has plenty of temporary water bodies and a few permanent lakes filled by groundwater. To determine species diversity and the role of environmental selection in community assembly in such a harsh environment, we sampled 37 sand ponds in June 2012. Fourteen species of Cladocera were found in total, including six pelagic species, eight littoral species, and two benthic species. These cladocerans were mainly temperate and cosmopolitan fauna. Our classification and regression tree model showed that conductivity, dissolved oxygen, and pH were the main factors correlated with species richness in the sand ponds. Spatial analysis using a PCNM model demonstrated a broad-scale spatial structure in the cladoceran communities. Conductivity was the most significant environmental variable explaining cladoceran community variation. Two species, Moina cf. brachiata and Ceriodaphnia reticulata occurred commonly, with an overlap at intermediate conductivity. Our results, therefore, support that environmental selection plays a major role in structuring cladoceran communities in deserts. [ABSTRACT FROM AUTHOR]

Providing high-quality medical services is of great importance in the imaging department, as there is a growing focus on personal health, and high-quality services can lead to improved patient outcomes. Many quality improvement (QI) programs with good guidance and fine measurement for improvement have been reported to be effective. In order to improve the quality of ultrasound departments in China, we conducted this study of a national quality improvement program. A total of 1297 public hospitals were included in this QI program on ultrasound departments in China from 2017 to 2019. The effect of this QI program was investigated, and potential factors, including hospital level and local economic development, were considered. The outcome indicators, the positive rate and diagnostic accuracy, were improved significantly between the two phases (positive rate, 2017 vs. 2019: 66.21% vs. 73.91%, p < 0.001; diagnostic accuracy, 2017 vs. 2019: 85.37% vs. 89.74%; p < 0.001). Additionally, they were improved in secondary and tertiary hospitals, with the improvement in secondary hospitals being greater. Notably, the enhancement of diagnostic accuracy in low-GDP provinces was almost 20%, which was more significant than the enhancement in high-GDP provinces. However, the important structural indicator, the doctor-to-patient ratio, decreased from 1.05:10,000 to 0.96:10,000 (p = 0.026). This study suggests that the national ultrasound QI program improved the outcome indicators, with secondary-level hospitals improving more than tertiary hospitals and low-GDP provinces improving more than high-GDP regions. Additionally, as there is a growing need for ultrasound examinations, more ultrasound doctors are needed in China.