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As mobile internet and Internet of Things technologies rapidly advance, the amount of spatio-temporal big data have surged, and efficient and secure management solutions are urgently needed. Although cloud storage provides convenience, it also brings significant data security challenges. Blockchain technology is an ideal choice for processing large-scale spatio-temporal big data due to its unique security features, but its storage scalability is limited because the data need to be replicated throughout the network. To solve this problem, a common approach is to combine blockchain with off-chain storage to form a hybrid storage blockchain. However, these solutions cannot guarantee the authenticity, integrity, and consistency of on-chain and off-chain data storage, and preprocessing is required in the setup phase to generate public parameters proportional to the data length, which increases the computational burden and reduces transmission efficiency. Therefore, this paper proposes a collaborative storage mechanism for spatio-temporal big data based on incremental aggregation sub-vector commitments, which uses vector commitment binding technology to ensure the secure storage of on-chain and off-chain data. By generating public parameters of fixed length, the computational complexity is reduced and the communication efficiency is improved while improving the security of the system. In addition, we design an aggregation proof protocol that integrates aggregation algorithms and smart contracts to improve the efficiency of data query and verification and ensure the consistency and integrity of spatio-temporal big data storage. Finally, simulation experiments verify the correctness and security of the proposed protocol, providing a solid foundation for the blockchain-based spatio-temporal big data storage system. [ABSTRACT FROM AUTHOR]

Simple Summary: The red imported fire ant, Solenopsis invicta Buren, is a highly invasive species. Some native ants may show aggression towards S. invicta and thus suppress S. invicta invasion. However, only a few such native ants have been identified, and the available data are largely limited to their behaviors. Here, we not only observed the aggression levels between native ants and S. invicta, but also investigated their abundance in various habitats, the seasonal dynamics of their abundance, and their spatial distribution in habitats with S. invicta. Two ant species, Monomorium chinense and Nylanderia bourbonica, were demonstrated to show aggression towards S. invicta and could kill a large proportion of S. invicta. However, another ant, Iridomyrmex anceps, did not show aggression. M. chinense and N. bourbonica are more abundant in green belts (e.g., lawns) and grasslands relative to woodland and farmland. Their abundance is quite low in the early months of the year but increases in later parts of the season. M. chinense and N. bourbonica are restricted to marginal habitats, but after control of S. invicta, they can rebound rapidly within a few weeks. M. chinense and N. bourbonica have the potential to suppress S. invicta invasion in some habitats. Native ants have long been considered for their potential to suppress the red imported fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae), a highly invasive and destructive species. However, the knowledge in this field is limited to behavioral observations of a few related native ants. In this study, by setting up a series of ant combinations of three native ants, i.e., Monomorium chinense Santschi, the robust crazy ant Nylanderia bourbonica Forel, and Iridomyrmex anceps Roger, with S. invicta, we observed the aggression levels and mortality rates. Using baited vials, we also investigated the abundance of native ants in four types of habitats in Eastern China that are preferred by S. invicta (woodland, green belts on roadsides, grassland, and farmland), as well as their seasonal abundance when co-existing with S. invicta and their spatial distribution before and after control of S. invicta. We found that M. chinense and N. bourbonica show a degree of aggression towards S. invicta and can kill substantial proportions of S. invicta under laboratory conditions, but I. anceps does not. Both M. chinense and N. bourbonica can occur in each type of habitat investigated and are more abundant in green belts (particularly lawns with turf) and grasslands relative to other habitats. In grasslands with S. invicta, M. chinense maintained a low density before early July; however, its abundance increased thereafter and reached a peak in September. N. bourbonica also had a low density early in the season and increased steadily from April. Its abundance began to decrease substantially from November. In grasslands invaded by S. invicta, both M. chinense and N. bourbonica were restricted to sites close to the margins before S. invicta was controlled; however, they spread to a larger range within a few weeks after control of S. invicta. In conclusion, M. chinense and N. bourbonica have the potential to suppress S. invicta invasion in habitats that are abundant with these two native ants. [ABSTRACT FROM AUTHOR]

The prediction of vessel trajectories plays a crucial role in ensuring maritime safety and reducing maritime accidents. Substantial progress has been made in trajectory prediction tasks by adopting sequence modeling methods, containing recurrent neural networks (RNNs) and sequence-to-sequence networks (Seq2Seq). However, (1) most of these studies focus on the application of trajectory information, such as the longitude, latitude, course, and speed, while neglecting the impact of differing vessel features and behavioral preferences on the trajectories. (2) Challenges remain in acquiring these features and preferences, as well as enabling the model to sensibly integrate and efficiently express them. To address the issue, we introduce a novel deep framework VEPO-S2S, consisting of a Multi-level Vessel Trajectory Representation Module (Multi-Rep) and a Feature Fusion and Decoding Module (FFDM). Apart from the trajectory information, we first defined the Multi-level Vessel Characteristics in Multi-Rep, encompassing Shallow-level Attributes (vessel length, width, draft, etc.) and Deep-level Features (Sailing Location Preference, Voyage Time Preference, etc.). Subsequently, Multi-Rep was designed to obtain trajectory information and Multi-level Vessel Characteristics, applying distinct encoders for encoding. Next, the FFDM selected and integrated the above features from Multi-Rep for prediction by employing both a priori and a posteriori mechanisms, a Feature Fusion Component, and an enhanced decoder. This allows the model to efficiently leverage them and enhance overall performance. Finally, we conducted comparative experiments with several baseline models. The experimental results demonstrate that VEPO-S2S is both quantitatively and qualitatively superior to the models. [ABSTRACT FROM AUTHOR]

Antibiotic resistance in Gram-negative bacteria remains one of the most pressing challenges to global public health. Blocking the transportation of lipopolysaccharides (LPS), a crucial component of the outer membrane of Gram-negative bacteria, is considered a promising strategy for drug discovery. In the transportation process of LPS, two components of the LPS transport (Lpt) complex, LptA and LptC, are responsible for shuttling LPS across the periplasm to the outer membrane, highlighting their potential as targets for antibacterial drug development. In the current study, a protein–protein interaction (PPI) model of LptA and LptC was constructed, and a molecular screening strategy was employed to search a protein–protein interaction compound library. The screening results indicated that compound 18593 exhibits favorable binding free energy with LptA and LptC. In comparison with the molecular dynamics (MD) simulations on currently known inhibitors, compound 18593 shows more stable target binding ability at the same level. The current study suggests that compound 18593 may exhibit an inhibitory effect on the LPS transport process, making it a promising hit compound for further research. [ABSTRACT FROM AUTHOR]

Diabetes management requires constant monitoring and individualized adjustments. This study proposes a novel approach that leverages digital twins and personal health knowledge graphs (PHKGs) to revolutionize diabetes care. Our key contribution lies in developing a real-time, patient-centric digital twin framework built on PHKGs. This framework integrates data from diverse sources, adhering to HL7 standards and enabling seamless information access and exchange while ensuring high levels of accuracy in data representation and health insights. PHKGs offer a flexible and efficient format that supports various applications. As new knowledge about the patient becomes available, the PHKG can be easily extended to incorporate it, enhancing the precision and accuracy of the care provided. This dynamic approach fosters continuous improvement and facilitates the development of new applications. As a proof of concept, we have demonstrated the versatility of our digital twins by applying it to different use cases in diabetes management. These include predicting glucose levels, optimizing insulin dosage, providing personalized lifestyle recommendations, and visualizing health data. By enabling real-time, patient-specific care, this research paves the way for more precise and personalized healthcare interventions, potentially improving long-term diabetes management outcomes. [ABSTRACT FROM AUTHOR]

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n = 83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n = 123 subjects). Set1, the data set from Scanner1, was reconstructed with standard clinical parameters (5 min; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-min). Set2, data from Scanner2 representing out-of-domain clinical scans, used standard iterative reconstruction (5 min; OSEM). A deep neural network was trained with each dataset: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50% and 75%) of Set1 for training. Scanner1, list-mode 2-min reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1 = 0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1 = 0.755; p-value = 0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1 = 0.478) to 100% training data (F1 = 0.713; p < 0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability. [ABSTRACT FROM AUTHOR]

ADAR (Adenosine Deaminases Acting on RNA) proteins are a group of enzymes that play a vital role in RNA editing by converting adenosine to inosine in RNAs. This process is a frequent post-transcriptional event observed in metazoan transcripts. Recent studies indicate widespread dysregulation of ADAR-mediated RNA editing across many immune-related diseases, such as human cancer. We comprehensively review ADARs' function as pattern recognizers and their capability to contribute to mediating immune-related pathways. We also highlight the potential role of site-specific RNA editing in maintaining homeostasis and its relationship to various diseases, such as human cancers. More importantly, we summarize the latest cutting-edge computational approaches and data resources for predicting and analyzing RNA editing sites. Lastly, we cover the recent advancement in site-directed ADAR editing tool development. This review presents an up-to-date overview of ADAR-mediated RNA editing, how site-specific RNA editing could potentially impact disease pathology, and how they could be harnessed for therapeutic applications. [ABSTRACT FROM AUTHOR]

The accurate detection of collapsed buildings is of great significance for post-disaster rescue and reconstruction. High-resolution optical images are important data sources for identifying collapsed buildings, and the identification accuracy mainly depends on the features extracted from the images. However, existing research lacks a comprehensive screening and general evaluation of the ability of remote sensing features to detect collapsed buildings, and there is still a considerable gap in the operational process of rapid identification of collapsed buildings in remote sensing. Based on 2630 pairs of building samples distributed in 6 regions worldwide, this study evaluated the ability of 25 remote sensing features (including spectral and spatial features) to detect collapsed buildings and select the most capable ones. Then, we test the application effect of selected features in identifying collapsed buildings on large-scale remote sensing images. Based on the two experiments above, an operational process for rapid identification of collapsed buildings was suggested. The result shows that Homogeneity, Energy, Local Entropy, Local Standard Deviation, and Gradient can effectively and stably distinguish collapsed buildings from non-collapsed buildings (Jeffries-Matusita distances are greater than 1.59 and Transformed Divergences are greater than 1.60) and have high recognition accuracy for collapsed buildings on large-scale remote sensing images (F1-scores are 0.71–0.94). In addition, Contrast, Local Coefficient of Variation, Edge Density, and Global Entropy can also distinguish collapsed buildings from non-collapsed buildings at a normal level (Jeffries-Matusita distances are 1.14–1.28, and Transformed Divergences are 1.24–1.48), while Gradient Orientation Entropy, Fractal Dimension, Local Binary Patterns, Edge, Local Mean, Correlation, Gradient Orientation Standard Deviation, Global Coefficient of Variation, Gabor feature, Local Moran'I, and six spectral features have relatively weak abilities (Jeffries-Matusita distances are less than 0.73, and Transformed Divergences are less than 1.07). The selected remote sensing features can support rapid identification of potential collapsed building areas from post-disaster remote sensing images. [ABSTRACT FROM AUTHOR]

Weigh-in-motion (WIM) systems are essential for efficient transportation and monitoring parameters such as vehicle number, speed, and weight to ensure regulatory compliance and enhance road safety. Recently, WIM measurements using the Glass Fiber Reinforced Polymer Fiber Bragg Grating (GFRP-FBG) sensors have shown robustness and effectiveness. However, the accuracy of weight evaluation using the WIM systems based on GFRP-FBG sensors can be significantly influenced by the vehicle-wandering effect, which introduces uncertainties in wheel position determination and weight calculations. This paper assessed the impact of vehicle wandering on the accuracy of a WIM measurement system based on GFRP-FBG sensors by utilizing a new hybrid sensor-camera system that integrates roadside cameras and in-pavement GFRP-FBG sensors. The detailed methodology and framework of the developed hybrid system are introduced, followed by field testing on Highway I-94 in the United States. The field testing results indicate that by using the hybrid system, the wheel load detection accuracy of the WIM system based on GFRP-FBG sensors can be controlled to be a Type I or Type III WIM according to the ASTM 1318E-09 standard, with an average accuracy ranging from 87.83% to 94.65%. At the same time, when the wander distance is less than or equal to 9 cm, the developed WIM system proves to be very cost-effective as it only comprises two GFRP-FBG sensors, one temperature FBG sensor, and one camera. These findings indicate the practical potential to enhance the accuracy of WIM systems based on GFRP-FBG sensors designed for highways for low-coast, reliable, and accurate measurements by addressing vehicle wandering effects. [ABSTRACT FROM AUTHOR]

A high-speed permanent magnet motor is the core driving component of a centrifugal air compressor. The power of the centrifugal air compressor is output by the motor. Its safety and reliability are embodied in the stability of the rotor structure, which greatly affects the stability and working efficiency of the centrifugal air compressor. Much research has focused on the material strength, structural characteristics, and fit clearance of a high-speed rotor, whereas few research articles have focused on the influence of interference fit of high-speed and ultra-high-speed permanent magnet motors, and there is also little research on the thermal failure caused by temperature in high-speed motors. In this paper, the influence of the interference fit and temperature of the high-speed permanent magnet motor is studied. Using finite element analysis conducted by Ansys to obtain simulation data, the influencing factors of the strength of the interference are analyzed comprehensively in the centrifugal compressor rotor system. The interference value and rotational speed range are determined via numerical calculation. Under the condition of minimum interference, when the calculated speed reaches 137,628.82 rpm, the structure of the rotor is loose and fails, which is a mechanical failure caused by the relative sliding of the magnet and the sheath. The calculated speed value differs from the simulation result by about 1.2%. The simulation results show that the maximum stress of the structure can be reduced from 1186.1 MPa to 308.42 MPa by adding chamfer to the end covers in interference fit structure. The effects of interference value, rotational speed, temperature, and sheath thickness on the structure are also analyzed. From the perspective of temperature on structural reliability, the failure temperature of the structure decreases when the interference value increases. The lowest failure temperature is 182.3 °C when the interference value is 70 μm. After that, the interference value increases and the failure temperature increases. The reason for this is the interaction between radial stress and contact stress. These results are caused by the interaction between interference fit and temperature, which should be paid attention to when the structure of a high-speed permanent magnet motor is designed. [ABSTRACT FROM AUTHOR]

The impedance change in an induction coil surrounding a metal tube adapter is investigated using the truncated region eigenfunction expansion (TREE) method. The conventional TREE method is inapplicable to this problem as a consequence of the numerical overflow of the eigenfunctions of the air–metal multi-subdomain regions. The difficulty is surmounted by a normalization procedure for the numerical eigenfunctions obtained from the 1D finite element method (FEM). An efficient algorithm is devised by the Clenshaw–Curtis quadrature rule for integrals involving the numerical eigenfunctions. The numerical results of the TREE and FEM simulation coincide very well in all cases, and the efficiency of the proposed method is also confirmed. [ABSTRACT FROM AUTHOR]

This study aimed to explore the pharmacokinetics (PK) and safety of oral (PO) and intravenous (IV) lefamulin in healthy Chinese subjects and to evaluate the efficacy of the intravenous administration regimen using pharmacokinetic/pharmacodynamic (PK/PD) analysis. This study was a randomized, open-label, single- and multiple-dose, intravenous and oral administration study. PK parameters were calculated, and the probability of target attainment (PTA) and the cumulative fraction of response (CFR) after IV administration of lefamulin 150 mg 1 h q12 h were analyzed with Monte Carlo simulations. Lefamulin exhibited extensive distribution. The mean steady-state AUC0–24 h of 150 mg lefamulin IV and 600 mg lefamulin PO were 10.03 and 13.96 μg·h/mL, respectively. For Streptococcus pneumoniae and Staphylococcus aureus, based on the free-drug AUC over MIC ratio (fAUC/MIC) target of 1-log10 cfu reduction, the PK/PD breakpoints were 0.25 and 0.125 mg/L, respectively. The CFR was over 90% for both types of strains with 95% protein binding rate, suggesting that the regimen was microbiologically effective. Lefamulin was safe and well-tolerated. The PK of lefamulin in healthy Chinese subjects were consistent with that in foreign countries. Lefamulin demonstrated the microbiological effectiveness against Streptococcus pneumoniae and Staphylococcus aureus. [ABSTRACT FROM AUTHOR]

Reversing HIV-1 latency promotes the killing of infected cells and is essential for cure strategies. However, current latency-reversing agents (LRAs) are not entirely effective and safe in activating latent viruses in patients. In this study, we investigated whether Scopoletin (6-Methoxy-7-hydroxycoumarin), an important coumarin phytoalexin found in plants with multiple pharmacological activities, can reactivate HIV-1 latency and elucidated its underlying mechanism. Using the Jurkat T cell model of HIV-1 latency, we found that Scopoletin can reactivate latent HIV-1 replication with a similar potency to Prostratin and did so in a dose- and time-dependent manner. Moreover, we provide evidence indicating that Scopoletin-induced HIV-1 reactivation involves the nuclear factor kappa B (NF-κB) signaling pathway. Importantly, Scopoletin did not have a stimulatory effect on T lymphocyte receptors or HIV-1 receptors. In conclusion, our study suggests that Scopoletin has the potential to reactivate latent HIV-1 without causing global T-cell activation, making it a promising treatment option for anti-HIV-1 latency strategies. [ABSTRACT FROM AUTHOR]

The classification of drilling conditions is a crucial task in the drilling process, playing a vital role in improving drilling efficiency and reducing costs. In this study, we propose an improved stacking ensemble learning algorithm with the objective of enhancing the performance of drilling conditions classification. Additionally, this algorithm aims to have a positive impact on automated drilling time estimation and the continuous improvement of efficiency. In our experimental setup, we employed various base learners, such as random forests, support vector machine, and the K-nearest neighbors algorithm, as initial models for the task of drilling conditions classification. To improve the model's expressive power and feature relevance specifically for this task, we enhanced the meta-model component of the stacking algorithm by incorporating feature engineering techniques. The experimental results show that the improved ensemble learning algorithm achieves an accuracy and recall rate of 97% and 98%, respectively. Through continuous improvement in drilling operations, the average sliding time is reduced by 21.1%, and the average Rate of Penetration (ROP) is increased by 15.65%. This research holds significant importance for engineering practice in the drilling industry, providing robust support for optimizing and enhancing the drilling process. [ABSTRACT FROM AUTHOR]

Crude oil resource scheduling is one of the critical issues upstream in the crude oil industry chain. It aims to reduce transportation and inventory costs and avoid alerts of inventory limit violations by formulating reasonable crude oil transportation and inventory strategies. Two main difficulties coexist in this problem: the large problem scale and uncertain supply and demand. Traditional operations research (OR) methods, which rely on forecasting supply and demand, face significant challenges when applied to the complicated and uncertain short-term operational process of the crude oil supply chain. To address these challenges, this paper presents a novel hierarchical optimization framework and proposes a well-designed hierarchical reinforcement learning (HRL) algorithm. Specifically, reinforcement learning (RL), as an upper-level agent, is used to select the operational operators combined by various sub-goals and solving orders, while the lower-level agent finds a viable solution and provides penalty feedback to the upper-level agent based on the chosen operator. Additionally, we deploy a simulator based on real-world data and execute comprehensive experiments. Regarding the alert number, maximum alert penalty, and overall transportation cost, our HRL method outperforms existing OR and two RL algorithms in the majority of time steps. [ABSTRACT FROM AUTHOR]

Chimeric antigen receptor (CAR)-T cells, a therapeutic agent for solid tumors, are not completely effective due to a lack of infiltration of T cells into the tumor site and immunity caused by Programmed Death Receptor 1(PD1). Here, an epidermal growth factor receptor (EGFR) CAR-T cell was engineered to express the chemokine receptor CCR6 and secrete PD1 blocking Single-chain antibody fragment (scFv) E27 to enhance their anti-tumor effects. The findings showed that CCR6 enhanced the migration of EGFR CAR-E27-CCR6 T cells in vitro by the Transwell migration assay. When incubated with tumor cells, EGFR CAR-E27-CCR6 T cells specifically exerted potent cytotoxicity and produced high levels of pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α), interleukin-2 (IL-2), and interferon-γ (IFN-γ). A non-small cell lung carcinoma (NSCLC) cell line-derived xenograft model was constructed by implanting modified A549 cell lines into immunodeficient NOD.PrkdcscidIl2rgem1/Smoc (NSG) mice. In comparison with traditional EGFR CAR-T cells, live imaging indicated that EGFR CAR-E27-CCR6 T cells displayed superior anti-tumor function. In addition, the histopathological examination of mouse organs showed no obvious organic damage. Our findings confirmed that PD1 blocking and CCR6 can enhance the anti-tumor function of EGFR CAR-T cells in an NSCLC xenograft model, providing an effective treatment strategy to improve the efficacy of CAR-T in NSCLC. [ABSTRACT FROM AUTHOR]

Background: To investigate the epidemiological characteristics and resistance changes of carbapenem-resistant organisms (CROs) under the COVID-19 outbreak to provide evidence for precise prevention and control measures against hospital-acquired infections during the pandemic. Methods: The distribution characteristics of CROs (i.e., carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii) were analyzed by collecting the results of the antibiotic susceptibility tests of diagnostic isolates from all patients. Using interrupted time series analysis, we applied Poisson and linear segmented regression models to evaluate the effects of COVID-19 on the numbers and drug resistance of CROs. We also conducted a stratified analysis using the Cochran–Mantel–Haenszel test. Results: The resistance rate of carbapenem-resistant Acinetobacter baumannii (CRAB) was 38.73% higher after the COVID-19 outbreak compared with before (p < 0.05). In addition, the long-term effect indicated that the prevalence of CRAB had a decreasing trend (p < 0.05). However, the overall resistance rate of Klebsiella pneumoniae did not significantly change after the COVID-19 outbreak. Stratified analysis revealed that the carbapenem-resistant Klebsiella pneumoniae (CRKP) rate increased in females (OR = 1.98, p < 0.05), those over 65 years old (OR = 1.49, p < 0.05), those with sputum samples (OR = 1.40, p < 0.05), and those in the neurology group (OR = 2.14, p < 0.05). Conclusion: The COVID-19 pandemic has affected the change in nosocomial infections and resistance rates in CROs, highlighting the need for hospitals to closely monitor CROs, especially in high-risk populations and clinical departments. It is possible that lower adherence to infection control in crowded wards and staffing shortages may have contributed to this trend during the COVID-19 pandemic, which warrants further research. [ABSTRACT FROM AUTHOR]

Dielectric barrier discharge (DBD) plasma in advanced oxidation technology can degrade organic pollutants in water under mild conditions. It has the advantages of universality, simple reaction conditions, and no secondary pollution. However, the light, electrons, and low-reactive substances generated during the discharge process cannot be fully utilized, which limits the further application of DBD plasma. Therefore, the DBD system coupled with catalysis can not only solve the above problem, but also transforms the low-active substances into high-active substances and improves the degradation rate of organic pollutants. Based on this fact, this review focuses on the characteristics and principles of DBD plasma coupled with photocatalysis, adsorption, Fenton oxidation, persulfate oxidation and composite technology to treat organic wastewater. This review puts forward some problems of DBD synergetic catalysis technology, and looks forward to the future development direction of this technology to treat organic pollutants in water. [ABSTRACT FROM AUTHOR]

As a major public health problem, the prevalence of Acinetobacter baumannii (A. baumannii) infections in hospitals due to the pathogen's multiple-antibiotic resistance has attracted extensive attention. We previously reported a series of 1,3-diamino-7H-pyrrolo[3,2-f]quinazoline (PQZ) compounds, which were designed by targeting Escherichia coli dihydrofolate reductase (ecDHFR), and exhibited potent antibacterial activities. In the current study, based on our molecular-modeling study, it was proposed that PQZ compounds may function as potent A. baumannii DHFR (abDHFR)-inhibitors as well, which inspired us to consider their anti-A. baumannii abilities. We further found that three PQZ compounds, OYYF-171, -172, and -175, showed significant antibacterial activities against A. baumannii, including multidrug-resistant (MDR) strains, which are significantly stronger than the typical DHFR-inhibitor, trimethoprim (TMP), and superior to, or comparable to, the other tested antibacterial agents belonging to β-lactam, aminoglycoside, and quinolone. The significant synergistic effect between the representative compound OYYF-171 and the dihydropteroate synthase (DHPS)-inhibitor sulfamethoxazole (SMZ) was observed in both the microdilution-checkerboard assay and time-killing assay, which indicated that using SMZ in combination with PQZ compounds could help to reduce the required dosage and forestall resistance. Our study shows that PQZ is a promising scaffold for the further development of folate-metabolism inhibitors against MDR A. baumannii. [ABSTRACT FROM AUTHOR]

Pollen allergies have a serious impact on people's physical and mental health. Accurate and efficient prediction of the outbreak date of pollen allergies plays an important role in the conservation of people sensitive to allergenic pollen. It is a frontier research to combine new social media data and satellite data to develop a model to forecast the outbreak date of pollen allergies. This study extracted the real outbreak dates of spring pollen allergies from Sina Weibo records from 2011 to 2021 in Beijing and calculated five vegetation indices of three vegetation types as phenological characteristics within the 30 days before the average outbreak date. The sensitivity coefficients and correlation coefficients were used to screen the phenological characteristics that best reflected the outbreak date of spring pollen allergy. Based on the best characteristic, two kinds of prediction models for the outbreak date of spring pollen allergy in Beijing were established (the linear fit prediction model and the cumulative linear fit prediction model), and the root mean square error (RMSE) was calculated as the prediction accuracy. The results showed that (1) the date of EVI2 (2-band enhanced vegetation index) in evergreen forest first reaching 0.138 can best reflect the outbreak date of pollen allergies in spring, and (2) the cumulative linear fit prediction model based on EVI2 in evergreen forests can obtain a high accuracy with an average RMSE of 3.6 days, which can predict the outbreak date of spring pollen allergies 30 days in advance. Compared with the existing indirect prediction models (which predict pollen concentrations rather than pollen allergies), this model provides a new direct way to predict pollen allergy outbreaks by using only remote sensing time-series data before pollen allergy outbreaks. The new prediction model also has better representativeness and operability and is capable of assisting public health management. [ABSTRACT FROM AUTHOR]

Simple Summary: Chicken face detection is a fundamental task for accurate poultry management. Achieving satisfactory chicken face detection is necessary to implement downstream tasks, such as day-age detection, behavior recognition, and health monitoring. Nonetheless, the image dataset of the chicken face is small-scale, and there are few related studies. Moreover, chicken heads and features are smaller than other livestock, making recognition tricky. Inspired by these significances and obstacles, this paper proposes a chicken face detection network with an augmentation module. Based on the YOLOv4 backbone, our model achieved 0.91 F1, 0.84 mAP, and 37 FPS, far surpassing the two-stage RCNN and EfficientDet baselines. This model can be applied to an actual chicken coop, and its performance is adequate to conduct downstream tasks. Achieving high-accuracy chicken face detection is a significant breakthrough for smart poultry agriculture in large-scale farming and precision management. However, the current dataset of chicken faces based on accurate data is scarce, detection models possess low accuracy and slow speed, and the related detection algorithm is ineffective for small object detection. To tackle these problems, an object detection network based on GAN-MAE (generative adversarial network-masked autoencoders) data augmentation is proposed in this paper for detecting chickens of different ages. First, the images were generated using GAN and MAE to augment the dataset. Afterward, CSPDarknet53 was used as the backbone network to enhance the receptive field in the object detection network to detect different sizes of objects in the same image. The 128 × 128 feature map output was added to three feature map outputs of this paper, thus changing the feature map output of eightfold downsampling to fourfold downsampling, which provided smaller object features for subsequent feature fusion. Secondly, the feature fusion module was improved based on the idea of dense connection. Then the module achieved feature reuse so that the YOLO head classifier could combine features from different levels of feature layers to capture greater classification and detection results. Ultimately, the comparison experiments' outcomes showed that the mAP (mean average Precision) of the suggested method was up to 0.84, which was 29.2% higher than other networks', and the detection speed was the same, up to 37 frames per second. Better detection accuracy can be obtained while meeting the actual scenario detection requirements. Additionally, an end-to-end web system was designed to apply the algorithm to practical applications. [ABSTRACT FROM AUTHOR]

In the context of the global pandemic of COVID-19, the use and disposal of medical masks have created a series of ethical and environmental issues. The purpose of this paper is to study and evaluate the high temperature properties and thermal storage stability of discarded-mask (DM)-modified asphalt from a multi-scale perspective using molecular dynamics (MD) simulation and experimental methods. A series of tests was conducted to evaluate the physical, rheological, thermal storage stability and microscopic properties of the samples. These tests include softening point, rotational viscosity, dynamic shear rheology (DSR), Fourier transform infrared (FT-IR) spectroscopy and molecular dynamics simulation. The results showed that the DM modifier could improve the softening point, rotational viscosity and rutting factor of the asphalt. After thermal storage, the DM-modified asphalt produced segregation. The difference in the softening point between the top and bottom of the sample increased from 2.2 °C to 17.1 °C when the DM modifier admixture was increased from 1% to 4%. FT-IR test results showed that the main component of the DM modifier was polypropylene, and the DM-modified asphalt was mainly a physical co-blending process. MD simulation results show that the DM modifier can increase the cohesive energy density (CED) and reduce the fractional free volume (FFV) of asphalt and reduce the binding energy between base asphalt and DM modifier. Multi-scale characterization reveals that DM modifiers can improve the high temperature performance and reduce the thermal storage stability of asphalt. It is noteworthy that both macroscopic tests and microscopic simulations show that 1% is an acceptable dosage level. [ABSTRACT FROM AUTHOR]

An accurate and reliable susceptibility testing method for polymyxins is urgently needed not only for the clinical laboratory but also for new polymyxin-like lipopeptide development. Reference broth microdilution (rBMD), which was the recommended method by CLSI-EUCAST in clinics, has been proven not to be ideal, while the agar dilution (AD) method that was widely used in new antibiotics discovery has been neglected. In the present study, the AD method was compared with rBMD and broth macrodilution (BMAD) in susceptibility testing of polymyxin B and colistin against >200 Gram-negative isolates. AD showed strong agreement with BMAD for colistin (except for Klebsiella aerogenes and Pseudomonas aeruginosa); however, its performance was poor for polymyxin B or compared to rBMD. MICs of AD method were not affected when different types of Petri dishes were used, while glass-bottom microtiter plates could lower the MIC of polymyxins 2–8 times compared to tissue-culture-treated polystyrene plates when using rBMD, which demonstrated that tissue-culture-treated plates were not suitable. It was then validated with non-tissue-culture-treated plates. The culture volume was another influencing factor of accuracy for rBMD, and 200 μL seemed to be the most suitable volume for MIC detection of polymyxins. Additionally, no lack of growth phenomenon (skipped well) was observed for AD when it frequently occurred for both BMAD and rBMD. As for strains carrying mcr-1 gene, 100% of AD results were in essential agreement (EA) and categorical agreement (CA) with both rBMD and BMAD. Overall, rBMD is convenient and widely accepted for susceptibility testing of polymyxins. Although it may be too early to say that AD is superior compared to rBMD and BMAD, it did show some advantages in repeatability and anti-interference ability. [ABSTRACT FROM AUTHOR]

Residual sediment transport, which is influenced by many factors including tide, wind, and waves, controls coastal morphological changes on different time scales. For fine-grained coasts where the wave effects are limited, it is still unclear to what extent the wind-driven current can impact the residual sediment transport. Taking the fine-grained Jiangsu Coast as an example, this study aimed to identify the contribution of wind on residual sediment transport over different time scales using a newly developed model. On a seasonal scale, wind-induced sediment transport shows strong seasonal characteristics, where the residual transport is more significant in the winter and summer. Nevertheless, the tide plays a dominant role in both residual current and sediment transport and the annual sediment budget over the coast. On the scale of tidal cycles, the extreme winds overwhelm the tides, controlling the residual sediment transport. However, the net sediment transport caused by the northerly winds (representing cold waves) is comparable to that of the southerly winds (representing typhoons). Therefore, although extreme winds can drive massive sediment transport in a short period, their contribution to annual sediment transport is limited. [ABSTRACT FROM AUTHOR]

Combinatorial optimization problems (COPs) are a class of NP-hard problems with great practical significance. Traditional approaches for COPs suffer from high computational time and reliance on expert knowledge, and machine learning (ML) methods, as powerful tools have been used to overcome these problems. In this review, the COPs in energy areas with a series of modern ML approaches, i.e., the interdisciplinary areas of COPs, ML and energy areas, are mainly investigated. Recent works on solving COPs using ML are sorted out firstly by methods which include supervised learning (SL), deep learning (DL), reinforcement learning (RL) and recently proposed game theoretic methods, and then problems where the timeline of the improvements for some fundamental COPs is the layout. Practical applications of ML methods in the energy areas, including the petroleum supply chain, steel-making, electric power system and wind power, are summarized for the first time, and challenges in this field are analyzed. [ABSTRACT FROM AUTHOR]

With the development of power systems, the power flow problem of transmission line is becoming more and more prominent. This paper presents a power flow regulation method based on phase shifting transformer (PST). Firstly, the working principle and performance of PST are analyzed. Then, the simulation model of BPA multi node system is established. PST access reduces the line imbalance to less than 8%. On this basis, considering the influence of saturation effect and leakage reactance, a PST suitable for 220 kV power grid is designed. Three different working conditions are simulated by PSCAD software. Under normal working conditions and N-1 conditions, PST can increase the transmission limit of the ring network section by more than 20%. When a short-circuit fault occurs, PST can also suppress the fault current. For 220 kV practical projects, unified power flow controller (UPFC) has faster response speed and stronger performance, but PST is more economical and reliable, and the equipment cost is 49.86% lower than that of UPFC. The power flow regulation method based on PST has good steady-state effect. It can improve the utilization efficiency of power grid assets and optimize the power flow distribution in a short time and at low cost. [ABSTRACT FROM AUTHOR]

Background: Liver fibrosis, as a common and refractory disease, is challenging to treat due to the lack of effective agents worldwide. Recently, we have developed a novel compound, N-(3,4,5-trichlorophenyl)-2(3-nitrobenzenesulfonamide) benzamide (IMB16-4), which is expected to have good potential effects against liver fibrosis. However, IMB16-4 is water-insoluble and has very low bioavailability. Methods: Mesoporous silica nanoparticles (MSNs) were selected as drug carriers for the purpose of increasing the dissolution of IMB16-4, as well as improving its oral bioavailability and inhibiting liver fibrosis. The physical states of IMB16-4 and IMB16-4-MSNs were investigated using nitrogen adsorption, thermogravimetric analysis (TGA), HPLC, UV-Vis, X-ray diffraction (XRD) and differential scanning calorimetry (DSC). Results: The results show that MSNs enhanced the dissolution rate of IMB16-4 significantly. IMB16-4-MSNs reduced cytotoxicity at high concentrations of IMB16-4 on human hepatic stellate cells LX-2 cells and improved oral bioavailability up to 530% compared with raw IMB16-4 on Sprague–Dawley (SD) rats. In addition, IMB16-4-MSNs repressed hepatic fibrogenesis by decreasing the expression of hepatic fibrogenic markers, including α-smooth muscle actin (α-SMA), transforming growth factor-beta (TGF-β1) and matrix metalloproteinase-2 (MMP2) in LX-2 cells. Conclusions: These results provided powerful information on the use of IMB16-4-MSNs for the treatment of liver fibrosis in the future. [ABSTRACT FROM AUTHOR]

Quick and effective detection of biothiols in biological fluids has gained increasing attention due to its vital biological functions. In this paper, a novel reversible fluorescence chemosensor (L-Cu2+) based on a benzocoumarin-Cu2+ ensemble has been developed for the detection of biothiols (Cys, Hcy and GSH) in human urine. The chemosensing ensemble (L-Cu2+) contains a 2:1 stoichiometry structure between fluorescent ligand L and paramagnetic Cu2+. L was found to exclusively bond with Cu2+ ions accompanied with a dramatic fluorescence quenching maximum at 443 nm and an increase of an absorbance band centered at 378 nm. Then, the in situ generated fluorescence sluggish ensemble, L-Cu2+, was successfully used as a chemosensor for the detection of biothiols with a fluorescence "OFF-ON" response modality. Upon the addition of biothiols, the decomplexation of L-Cu2+ led to the liberation of the fluorescent ligand, L, resulting in the recovery of fluorescence and absorbance spectra. Studies revealed that L-Cu2+ possesses simple synthesis, excellent stability, high sensitivity, reliability at a broad pH range and desired renewability (at least 5 times). The practical application of L-Cu2+ was then demonstrated by the detection of biothiols in human urine sample. [ABSTRACT FROM AUTHOR]

Photoacoustic computed tomography (PACT) has been widely explored for non-ionizing functional and molecular imaging of humans and small animals. In order for light to penetrate deep inside tissue, a bulky and high-cost tunable laser is typically used. Light-emitting diodes (LEDs) have recently emerged as cost-effective and portable alternative illumination sources for photoacoustic imaging. In this study, we have developed a portable, low-cost, five-dimensional (x, y, z, t, λ) PACT system using multi-wavelength LED excitation to enable similar functional and molecular imaging capabilities as standard tunable lasers. Four LED arrays and a linear ultrasound transducer detector array are housed in a hollow cylindrical geometry that rotates 360 degrees to allow multiple projections through the subject of interest placed inside the cylinder. The structural, functional, and molecular imaging capabilities of the LED–PACT system are validated using various tissue-mimicking phantom studies. The axial, lateral, and elevational resolutions of the system at 2.3 cm depth are estimated as 0.12 mm, 0.3 mm, and 2.1 mm, respectively. Spectrally unmixed photoacoustic contrasts from tubes filled with oxy- and deoxy-hemoglobin, indocyanine green, methylene blue, and melanin molecules demonstrate the multispectral molecular imaging capabilities of the system. Human-finger-mimicking phantoms made of a bone and blood tubes show structural and functional oxygen saturation imaging capabilities. Together, these results demonstrate the potential of the proposed LED-based, low-cost, portable PACT system for pre-clinical and clinical applications. [ABSTRACT FROM AUTHOR]

Background: Antibiotic-resistant H. pylori was increasingly found in infected individuals, which resulted in treatment failure and required alternative therapeutic strategies. Daphnetin, a coumarin-derivative compound, has multiple pharmacological activities. Methods: The mechanism of daphnetin on H. pylori was investigated focusing on its effect on cell morphologies, transcription of genes related to virulence, adhesion, and cytotoxicity to human gastric epithelial (GES-1) cell line. Results: Daphnetin showed good activities against multidrug resistant (MDR) H. pylori clinical isolates, with minimal inhibitory concentration (MIC) values ranging from 25 to 100 μg/mL. In addition, daphnetin exposure resulted in H. pylori morphological changes. Moreover, daphnetin caused increased translocation of phosphatidylserine (PS), DNA damage, and recA expression, and RecA protein production vs. control group. Of great importance, daphnetin significantly decreased H. pylori adhesion to GES-1 cell line vs. control group, which may be related to the reduced expression of colonization related genes (e.g., babA and ureI). Conclusions: These results suggested that daphnetin has good activity against MDR H. pylori. The mechanism(s) of daphnetin against H. pylori were related to change of membrane structure, increase of DNA damage and PS translocation, and decrease of H. pylori attachment to GES-1 cells. [ABSTRACT FROM AUTHOR]

Regional transportation development (RTD) is an important stressor of urban agglomeration ecosystems. Groundwater recharge potential may be adversely affected when natural soil is replaced by impervious materials. To systematically identify the urban agglomeration ecological risk (UAER) of RTD in the southern Fujian Golden Triangle, water regulation was used as an assessment endpoint, and RTD was considered the stressor. We used the Soil Conservation Service Curve Number method (SCS-CN) to analyze the internal relationship between the assessment endpoint and the stressor factors. Then, a multi-level risk characterization method was used to show the evolutionary process of risk, and to provide a scientific basis for the management of UAER. Based on the current RTD plan, the UAER assessment shows that there is a 0.90 probability of that the risk distribution results will occur by 2030. The intensity of stress from arterial roads on the urban agglomeration ecosystem is greater than that of the railway system. By considering the development of the railway system as a factor in the stress of RTD, this study of UAER assessment differs from past studies of urban ecological risk assessment, since the latter considers only highways. We also propose a systematic method of risk assessment simulation-prediction. [ABSTRACT FROM AUTHOR]

ADAR (Adenosine Deaminases Acting on RNA) proteins are a group of enzymes that play a vital role in RNA editing by converting adenosine to inosine in RNAs. This process is a frequent post-transcriptional event observed in metazoan transcripts. Recent studies indicate widespread dysregulation of ADAR-mediated RNA editing across many immune-related diseases, such as human cancer. We comprehensively review ADARs' function as pattern recognizers and their capability to contribute to mediating immune-related pathways. We also highlight the potential role of site-specific RNA editing in maintaining homeostasis and its relationship to various diseases, such as human cancers. More importantly, we summarize the latest cutting-edge computational approaches and data resources for predicting and analyzing RNA editing sites. Lastly, we cover the recent advancement in site-directed ADAR editing tool development. This review presents an up-to-date overview of ADAR-mediated RNA editing, how site-specific RNA editing could potentially impact disease pathology, and how they could be harnessed for therapeutic applications.

Emotion recognition based on physiological signals has been a hot topic and applied in many areas such as safe driving, health care and social security. In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods, the published emotional physiological datasets, features, classifiers, and the whole framework for emotion recognition based on the physiological signals. A summary and comparation among the recent studies has been conducted, which reveals the current existing problems and the future work has been discussed.

Marine natural products and their synthetic derivatives represent a major source of novel candidate anti-cancer compounds. We have recently tested the anti-cancer activity of more than forty novel compounds based on an iminoquinone makaluvamine scaffold, and have found that many of the compounds exert potent cytotoxic activity against human cancer cell lines. One of the most potent compounds, BA-TPQ [(11,12),7-(benzylamino)-1,3,4,8-tetrahydropyrrolo[4,3,2-de]quinolin-8(1H)-one], was active against a variety of human cancer cell lines, and inhibited the growth of breast and prostate xenograft tumors in mice. However, there was some toxicity noted in the mice following administration of the compound. In order to further the development of BA-TPQ, and in a search for potential sites of accumulation that might underlie the observed toxicity of the compound, we accomplished preclinical pharmacological studies of the compound. We herein report the in vitro and in vivo pharmacological properties of BA-TPQ, including its stability in plasma, plasma protein binding, metabolism by S9 enzymes, and plasma and tissue distribution. We believe these studies will be useful for further investigations, and may be useful for other investigators examining the use of similar compounds for cancer therapy.